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Vitamin D debates

Larry H. Bernstein, MD, FCAP, Curator

LPBI

Article ID #196: Vitamin D debates. Published on 11/7/2015

WordCloud Image Produced by Adam Tubman

 

Vitamin D: Time for Rational Decision-Making

JoAnn E. Manson, MD, DrPH

Hello. This is Dr JoAnn Manson, professor of medicine at Harvard Medical School and Brigham and Women’s Hospital. I would like to talk with you about the vitamin D dilemma. The question of whether to screen routinely for vitamin D deficiency or to recommend high-dose vitamin D supplementation for our patients continues to be one of the most perplexing and vexing issues in clinical practice, and many clinicians are seeking guidance on these issues.

There appears to be a growing disconnect between the observational studies and the randomized clinical trials of vitamin D. For example, the observational studies are showing a fairly consistent relationship between low blood levels of vitamin D and an increased risk for heart disease, cancer, diabetes, and many other chronic diseases. Yet, the randomized clinical trials of vitamin D supplementation to date have been generally disappointing. This includes several randomized trials published over the past few months, including a meta-analysis[1] of randomized trials of vitamin D supplementation showing minimal, if any, benefit in terms of lowering blood pressure; a trial[2] of high-dose vitamin D supplementation showing no clear benefit for muscle strength, bone mineral density, or even the risk for falls; and, most recently, a randomized trial[3] of vitamin D supplementation with and without calcium showing no clear benefit in reducing the risk for colorectal adenomas. The latter trial was very recently published in the New England Journal of Medicine.

The Institute of Medicine (IOM)[4] and the US Preventive Services Task Force[5] do not endorse routine universal screening for vitamin D deficiency. They also recommend more moderate intakes [of vitamin D]. For example, the IOM recommends 600-800 IU a day for adults and also recommends avoiding daily intakes above 4000 IU, which has been set as the tolerable upper intake level.

However, it is important to keep in mind that these are public health population guidelines for a generally healthy population, and they by no means preclude individual decision-making by the clinician in the context of a patient who may have health conditions or risk factors that would indicate a benefit from targeted screening for vitamin D deficiency or higher-dose supplementation. For example, some patients may have higher vitamin D requirements. This may include patients with bone health problems (osteoporosis, osteomalacia) or poor diets, those who spend minimal time outdoors, those with malabsorption syndromes, or those who take medications that may interfere with vitamin D metabolism (glucocorticoids, anticonvulsant medications, and antituberculosis drugs). Therefore, overall, there is a role for individualized decision-making, in terms of screening for vitamin D deficiency in patients who have bone health problems or special risk factors, and even treating with higher doses of vitamin D, which may go above 4000 IU a day in patients who have higher requirements.

In the next several years, large-scale, randomized trials of vitamin D supplementation, including high-dose vitamin D supplementation, will be completed—and these results will be published. They will help to inform clinical decision-making, so stay tuned for those results.

Thank you so much for your attention. This is JoAnn Manson.

References

  1. Beveridge LA, Struthers AD, Khan F, et al. D-PRESSURE Collaboration. Effect of vitamin D supplementation on blood pressure: a systematic review and meta-analysis incorporating individual patient data. JAMA Intern Med. 2015;175:745-754. Abstract
  2. Hansen KE, Johnson RE, Chambers KR, et al. Treatment of vitamin D insufficiency in postmenopausal women: a randomized clinical trial. JAMA Intern Med. 2015;175:1612-1621. Abstract
  3. Baron JA, Barry EL, Mott LA, et al. A trial of calcium and vitamin D for the prevention of colorectal adenomas. N Engl J Med. 2015;373:1519-1530. Abstract
  4. Institute of Medicine. Dietary Reference Intakes for Calcium and Vitamin D. Washington, DC: National Academies Press; 2011. http://iom.nationalacademies.org/Reports/2010/Dietary-Reference-Intakes-for-Calcium-and-Vitamin-D.aspx Accessed October 28, 2015.
  5. US Preventive Services Task Force. Final Recommendation Statement: Vitamin D Deficiency: Screening, 2014.http://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/vitamin-d-deficiency-screening Accessed October 28, 2015.

 

Isn’t there much more to this than the debates entail?

The vitamin D hormone and its nuclear receptor: molecular actions and disease states.
 J Endocrinol. 1997 Sep;154 Suppl:S57-73.      http://dx.doi.org:/10.1677/joe.0.154S057

Vitamin D plays a major role in bone mineral homeostasis by promoting the transport of calcium and phosphate to ensure that the blood levels of these ions are sufficient for the normal mineralization of type I collagen matrix in the skeleton. In contrast to classic vitamin D-deficiency rickets, a number of vitamin D-resistant rachitic syndromes are caused by acquired and hereditary defects in the metabolic activation of the vitamin to its hormonal form, 1,25-dihydroxyvitamin D3 (1,25(OH)2D3), or in the subsequent functions of the hormone in target cells. The actions of 1,25(OH)2D3 are mediated by the nuclear vitamin D receptor (VDR), a phosphoprotein which binds the hormone with-high affinity and regulates the expression of genes via zinc finger-mediated DNA binding and protein-protein interactions. In hereditary hypocalcemic vitamin D-resistant rickets (HVDRR), natural mutations in human VDR that confer patients with tissue insensitivity to 1,25(OH)2D3 are particularly instructive in revealing VDR structure function relationships. These mutations fall into three categories: (i) DNA binding/nuclear localization, (ii) hormone binding and (iii) heterodimerization with retinoid X receptors (RXRs). That all three classes of VDR mutations generate the HVDRR phenotype is consistent with a basic model of the active receptor as a DNA-bound, 1,25(OH)2D3-liganded heterodimer of VDR and RXR. Vitamin D responsive elements (VDREs) consisting of direct hexanucleotide repeats with a spacer of three nucleotides have been identified in the promoter regions of positively controlled genes expressed in bone, such as osteocalcin, osteopontin, beta 3-integrin and vitamin D 24-OHase. The 1,25(OH)2D3 ligand promotes VDR-RXR heterodimerization and specific, high affinity VDRE binding, whereas the ligand for RXR, 9-cis retinoic acid (9-cis RA), is capable of suppressing 1,25(OH)2D3-stimulated transcription by diverting RXR to form homodimers. However, initial 1,25(OH)2D3 liganding of a VDR monomer renders it competent not only to recruit RXR into a heterodimer but also to conformationally silence the ability of its RXR partner to bind 9-cis RA and dissociate the heterodimer. Additional probing of protein-protein interactions has revealed that VDR also binds to basal transcription factor IIB (TFIIB) and, in the presence of 1,25(OH)2D3, an RXR-VDR-TFIIB ternary complex can be created in solution. Moreover, for transcriptional activation by 1,25(OH)2D3, both VDR and RXR require an intact short amphipathic alpha-helix, known as AF-2, positioned at their extreme C-termini. Because the AF-2 domains participate neither in VDR-RXR heterodimerization nor in TFIIB association, it is hypothesized that they contact, in a ligand-dependent fashion, transcriptional coactivators such as those of the steroid receptor coactivator family, constituting yet a third protein-protein interaction for VDR. Therefore, in VDR-mediated transcriptional activation, 1,25(OH)2D3 binding to VDR alters the conformation of the ligand binding domain such that it: (i) engages in strong heterodimerization with RXR to facilitate VDRE binding, (ii) influences the RXR ligand binding domain such that it is resistant to the binding of 9-cis RA but active in recruiting coactivator to its AF-2 and (iii) presents the AF-2 region in VDR for coactivator association. The above events, including bridging by coactivators to the TATA binding protein and associated factors, may position VDR such that it is able to attract TFIIB and the balance of the RNA polymerase II transcription machinery, culminating in repeated transcriptional initiation of VDRE-containing, vitamin D target genes. Such a model would explain the action of 1,25(OH)2D3 to elicit bone remodeling by stimulating osteoblast and osteoclast precursor gene expression, while concomitantly triggering the termination of its hormonal signal by inducing the 24-OHase catabolizing enzyme.

 

Classic nutritional rickets is caused by the simultaneous deprivation of sunlight exposure and dietary vitamin D. As depicted in Fig. 1, the pathways comprising the metabolic activation of the vitamin to its hormonal form and subsequent functions in target tissues present a number of additional steps where defects elicit vitamin D-resistant rachitic syndromes. Two of these disorders involve the inadequate bioactivation of 25-hydroxy¬ vitamin D3 (25(OH)D3) to 1,25-dihydroxyvitamin D3 (l,25(OH)2D3) by the kidney as catalyzed by the 1-OHase enzyme (Fig. 1).

Figure 1 Bioactivation of vitamin D3 and actions of the 1,25(OH)2D3 hormonal metabolite on intestine, bone and kidney, along with related rachitic syndromes. The production of 1,25(OH)2D3 is depicted in the lowet portion and its functions on mineral ttansport in target cells ate pictured in the upper portion. Defects eliciting rachitic syndromes ate boxed, with the televant mutated gene and chromosomal location denoted where appropriate

Acquired chronic renal failure results in renal rickets and secondary hyperparathyroidism (renal osteodystrophy) when the compromising of renal mass reduces 1-OHase activity (Haussier oc McCain 1977). The etiology of pseudo-vitamin D-deficiency rickets (PDDR) apparently involves a hereditary defect in the gene coding for the 1-OHase enzyme (Labuda et al. 1992). Interestingly, the PDDR locus is resolvable from that of the vitamin D receptor (VDR) but maps very close to it on chromosome 12 in the 12ql3—14 region (Labuda et al. 1992). Recently, a cDNA was cloned for the rat 1-OHase (St-Arnaud et al. 1996) and it is expected that the human renal 1-OHase gene will soon be cloned and its chromosomal location determined. The likelihood that both the gene encoding the enzyme that generates the l,25(OH)2D3 hormone and the cognate hormone receptor gene lie in close proximity on chromosome 12 invites speculation about the evolution of the vitamin D ligand receptor system. The traditional actions of vitamin D, via its l,25(OH)2D3 hormonal metabolite, are to effect calcium and phosphate homeostasis to ensure the deposition of bone mineral on type I collagen matrix (summarized in Fig. 1).

Figure 1 Bioactivation of vitamin D3 and actions of the 1,25(OH)2D3 hormonal metabolite on intestine, bone and kidney, along with related rachitic syndromes. The production of 1,25(OH)2D3 is depicted in the lowet portion and its functions on mineral ttansport in target cells ate pictured in the upper portion. Defects eliciting rachitic syndromes ate boxed, with the televant mutated gene and chromosomal location denoted where appropriate

 

l,25(OH)2D3 stimulates intestinal calcium and phosphate absorption, bone calcium and phosphate résorption, and renal calcium and phosphate reabsorption, all resulting in a sufficient CaP04 ion product to precipitate hydroxyapatite. Failure to achieve normal bone mineral accretion by these mechanisms leads to rachitic syndromes. Recently, a breakthrough has occurred in our understand¬ ing of what was originally known as hypophosphatemic vitamin D-resistant rickets, a familial disorder of renal phosphate wasting more appropriately referred to as dominant X-linked hypophosphatemic (HYP) rickets (Fig. 1). The gene defect responsible for HYP rickets has been fine mapped in the Xp22T region, harboring a gene identified as PEX, or phosphate regulating gene with homologies to endopeptidases located on the X-chromosome (Francis et al. 1995). One hypothesis is that PEX codes for an endopeptidase that apparently correctly processes a peptide precursor to yield a novel, as yet unidentified, phosphate retaining hormone. The normal function of this hormone may be to oppose the action of parathyroid hormone (PTH) and stimulate phosphate reabsorption by the renal tubule by inducing the Na -phosphate cotransporter. However, the existence of tumor-induced osteomalacia, an acquired disorder that closely resembles the phosphate wasting of HYP rickets and is characterized by low circulating l,25(OH)2D3 (Parker et al. 1981), combined with renal cross-transplantation (Nesbitt et al. 1992) and parabiosis (Meyer et al. 1989) studies in normal and hyp mice, indicates strongly that the HYP phenotype is caused by excessive amounts of a phosphaturic hormone in the circulation. This humoral peptide is distinct from PTH and has been named phosphatonin (Cai et al. 199A, Econs & Drezner 1994). Thus, instead of PEX mutations result¬ ing in insufficient generation of a novel phosphate retaining peptide, they may instead elicit the appearance of abnormally high circulating levels of phosphatonin, with the normal role of the PEX gene product postulated to be the proteolytic inactivation of this phosphaturic principle. Most germane to the vitamin D endocrine system is the fact that serum l,25(OH)2D3 levels are inappropriately low for the prevailing phosphate concentrations in HYP rickets and patients can be cured with a therapeutic combination of phosphate and l,25(OH)2D3 (Harrel et al. 1985). Because it is well known that hypophosphatemia stimulates l,25(OH)2D3 production (Hughes et al. 1975), the PEX/phosphatonin system might constitute yet another regulatory loop in maintaining normal phosphate homeostasis. One could hypothesize that under hypo- phosphatemic conditions, when l,25(OH)2D3 levels are elevated, the sterol hormone not only increases intestinal phosphate absorption (Fig. 1) and suppresses PTH synthesis (DeMay et al. 1992) to conserve phosphate, but also induces the PEX gene product (Rowe et al. 1996) to cleave phosphatonin and further promote renal phosphate reclamation. l,25(OH)2D3 is primarily recognized as a calcémic hormone, perhaps due to the abundance of dietary phosphate, or because calcium homeostasis is more vitamin D-dependent than the regulation of extracellular phos¬ phate. Regardless of the mechanism, traditional vitamin D-deficiency and clinically significant defects in the vitamin D receptor lead invariably to hypocalcemia and secondary hyperparathyroidism, with phosphate being somewhat less affected. As illustrated in Fig. 1, target tissue insensitivity to l,25(OH)2D3 is known as hereditary hypocalcémie vitamin D-resistant rickets (HVDRR) and is caused by defects in the gene on chromosome 12 coding for the VDR. A review of the etiology of HVDRR and the natural mutations in the VDR that confer tissue insensitivity and clinical resistance to l,25(OH)2D3 is particularly instructive in illuminating the physiologic relevance of the l,25(OH)-,D3-VDR hormone-receptor complex as well as structure/function relationships in the receptor itself.

Natural mutations in the nuclear vitamin D receptor Clinically significant hereditary hypocalcémie vitamin D-resistant rickets is an autosomal recessive disorder resulting in a phenotype characterized by severe bowing of the lower extremities, short stature and, often, alopecia (Rut et al. 199A). The serum chemistry in HVDRR includes frank hypocalcemia, secondary hyperpara¬ thyroidism, elevated alkaline phosphatase, variable hypophosphatemia and markedly increased l,25(OH)2D3. The symptoms of HVDRR, with the exception of alopecia, mimic classic vitamin D-deficiency rickets, suggesting that VDR not only mediates the bone mineral homeostatic actions of vitamin D but may also participate in the differentiation of hair follicles in utero. Recently, VDR knockout mice have been created (Yoshizawa et al. 1996), revealing apparently normal hétérozygotes but severely affected homozygotes (VDR-/-), 90% ofwhich die within 8—10 weeks. Surviving mice lose their hair and possess low bone mass, hypocalcemia, hypophosphatemia and 10-fold elevated l,25(OH)2D3 coincident with extremely low 24,25(OH)2D3. All of these parameters in the VDR knockout mouse mimic the phenotype of patients with HVDRR, confirming that VDR normally mediates all of the bone mineral regulating functions of vitamin D. Interestingly, although natural point mutations in other receptors related to VDR, such as thyroid hormone receptor ß (TRß) (Collingwood et al. 1994), are charac¬ terized by dominant negative receptors that generate the thyroid hormone resistant phenotype in the heterozygotic context, no natural, dominant negative mutations have yet been identified in HVDRR patients (Whitfield et al. 1996). Thus, all HVDRR cases studied to date are homozygous for the particular VDR mutation.

Figure 2 Natural mutations in the human vitamin D receptor leading to 1,25(OH)2D¡ hormone resistance. See text for details and citations. N37, K91 and E92 are not sites of VDR natural mutations, but are so designated because they ate heterodimerization contacts that lie within the DNA binding domain (Hsieh et al. 1995, Rastinejad et al. 1995). The eight cysteine residues (C) that tetrahedrally coordinate two zinc atoms in the finger sttucture are also denoted.

Figure 2 illustrates a number of point mutations in VDR that have been detected in HVDRR patients (reviewed in Rut et al. 199A, Haussler et al. 1995). Three of these genetic alterations result in nonsense mutations that introduce stop codons in VDR (K73stop, Q152sfo|> and Y295stop), creating truncated VDRs that lack both hormone- and DNA-binding (heterodimerization) capacities and are associated with unstable mRNAs. More revealing are the series of missense mutations (Fig. 2) that can be classified according to three of the basic molecular functions of VDR: (i) DNA binding/nuclear localization by the N-terminal zinc finger region, (ii) l,25(OH)2D3 hormone binding by the C-terminal domain and (iii) heterodimerization with retinoid X receptors (RXRs) through subregions of the C-terminal domain. As depicted schematically in Fig. 2 and discussed in detail later, VDR is a ligand-dependent transcription factor that controls gene expression by heterodimerizing with RXR and associating specifically with vitamin D responsive elements (VDREs) in target genes. Since VDR is a member of the steroid, retinoid, thyroid hormone receptor superfamily, and belongs to the VDR/retinoic acid receptor (RAR)/TR subfamily of RXR heterodimerizing species (Haussler et al. 1991), it is reasonable to draw from data on RAR and TR for comparison with VDR.

The greatest number of VDR natural mutations char¬ acterized to date are localized to the DNA binding, zinc finger region (Fig. 2). The first two discovered, G33D and R73Q (Hughes et al. 1988), reside at the ‘tips’ of the fingers and affect charge—charge interactions between VDR and the phosphate backbone of DNA. When viewed in toto, the zinc finger region mutations in HVDRR (Fig. 2) have the following two general prop¬ erties: (i) they occur in residues conserved across the entire nuclear receptor superfamily and (ii) most lie within -helices on the C-terminal side of the first and second fingers which are intimately involved in DNA base recognition and phosphate backbone contacts respectively (Rastinejad et al. 1995). These observations suggest that many of the clinically significant mutations in VDR which are still compatible with life may not greatly perturb the fundamental structure of the DNA binding domain of the receptor, but instead compromise its ability to recog¬ nize DNA with specificity and high affinity. Whether HVDRR cases with mutations in zinc finger region residues unique to VDR will be uncovered depends upon the properties of such alterations, which could range from innocuous to lethal.

Mutations located within the hormone binding domain of VDR also elicit the HVDRR phenotype (Fig. 2), including R274L (Kristjansson et al. 1993) and H305Q (Malloy et al 1995). Transcriptional activation by R274L and H305G VDR is attenuated as a result of inefficient l,25(OH)2D3 binding, ranging from severe in the case of R274L to a modest increase in Kd for H305Q. In both instances, transcriptional activation is restored when the dose of l,25(OH)2D3 is raised to pharmacologie levels (10 m) in transfection experiments (Kristjansson et al. 1993, Malloy et al. 1995). Our laboratory has recently characterized two novel VDR hormone binding domain mutations in HVDRR patients, I314S and R391C, that significantly affect the heterodimerization of VDR with RXR (Whitfield et al. 1996). Both of these C-terminal replacements (Fig. 2), however, do display some degree of what may be a hormone binding deficit, a phenomenon not observable in typical in vitro ligand binding kinetic assays at 4 °C. Thus, only at 37 °C in intact cells do R391C and I314S exhibit apparent slight and significant impairment of l,25(OH)2D3 high affinity retention respectively (Whitfield et al. 1996). Further, the two mutations in question are situated in or adjacent to heptad repeats (Fig. 2), hypothetical coiled-coil-like structures that were originally proposed to participate in the heterodimerization of VDR, RAR, and TR with RXR (Forman & Samuels 1990, Nakajima et al. 1994). Consist¬ ent with this concept, both R391C and I314S VDRs do not bind RXR with normal affinity when assayed in vitro, with the greatest impairment of heterodimerization occur¬ ring with R391C (affinity reduced by one order of magnitude) (Whitfield et al. 1996). Additional evidence supporting blunted RXR heterodimerization by these two mutant VDRs is provided by transfection experiments in restored to that of normal fibroblasts when fibroblasts from patients harboring either the R391C or the I314S mutation are cotransfected with exogenous RXR. Yet this apparent RXR rescue of the mutated VDRs requires approximately 10-fold elevated l,25(OH)2D3 doses com¬ pared with the response to hormone in normal fibroblasts (Whitfield et al. 1996). This latter observation reveals that the hormone binding and heterodimerization functions of VDR are not entirely separable, an aspect which is also apparent from fundamental biochemical analysis of the hormone dependency of VDR-RXR heterodimer binding to VDREs as discussed in detail below.

Understanding the molecular properties of natural VDR mutations in HVDRR allows us to comprehend why the patients respond differentially to therapy with massive doses of l,25(OH)2D3, or suitable analogs. For example, cases with zinc finger region aberrations are unresponsive to the hormone because DNA binding is precluded by the absence of structural complemen¬ tarity between VDR and the VDRE, regardless of the l,25(OH)2D3 liganding or heterodimerization of the receptor in solution. Conversely, patients harboring mutations in the hormone binding/heterodimerization domain can be responsive to pharmacologie doses of l,25(OH)2D3 or analogs, even though the hormone already is increased in the circulation because of the hypocalcemia caused by tissue insensitivity. For example, patient I314S was essentially cured by excess vitamin D metabolite, indicating that compensating for the hormone binding deficit was able to override the milder heterodimerization defect and allow sufficient VDRE binding by the VDR-RXR heterodimer. Conversely, patient R391C responded only modestly to treatment with excess l,25(OH)2D3 analog, presumably because the fundamental heterodimerization defect could not be overcome and therefore normal VDRE binding could not be achieved (Whitfield et al. 1996).

The final insights gained from the natural VDR mutations summarized in Fig. 2 are structural in nature. We have discussed previously that the zinc finger mutations are confined to absolutely conserved residues. In the crystal structure of the DNA binding domain heterodimers of RXRa and TRß (Rastinejad et al. 1995), the lysine and arginine residues corresponding to K45 and R50 in human VDR (hVDR) make direct base contacts with DNA, while the arginines corresponding to R73 and R80 in hVDR make direct DNA phosphate backbone contacts. That mutations in these four residues are clinically important in the etiology of HVDRR argues for structural congruity between the VDR finger region and that of TR. Rastinejad et al. (1995) have extended this assumption to include a modeling of RXR-TR vs RXRVDR bound to DNA which accommodates the fact that TR binds as a heterodimer to a direct hexanucleotide repeat spaced by four nucleotides (DR+4), while VDR binds as a heterodimer to a similar set of half elements spaced by three nucleotides (DR+3). In addition to verifying the common protein-DNA interfaces, their modeling predicts that hVDR residues N37 in the first finger and K91/E92 C-terminal of the second finger (see Fig. 2) engage in heterodimeric contacts with residues in the second zinc finger ofRXR to form effectively a stable, DNA-supported heterodimer. Indeed, recent site-directed mutational studies (Hsieh et al. 1995) indicate that the alteration ofK91 and E92 in hVDR in fact grossly reduces transactivation while moderately attenuating hetero¬ dimerization and DNA binding, thus confirming the importance of K91 and E92. An additional surprising finding was that the K91/E92 double mutant manifested dominant negative characteristics (Hsieh et al. 1995), distinguishing it from the natural HVDRR replacements discussed above. Apparently, the K91/E92 mutant VDR is able to bind DNA sufficiently through its native zinc finger and strong heterodimerization function in the ligand binding domain such that it can block binding by wild type receptor, but is rendered inactive in stimulating transcription because of a presumed conformational per¬ turbation initiated by unstable or improper alignment of the heterodimer on the VDRE.

Based upon recently reported X-ray crystal structures of the ligand binding domains of ligand-occupied hRARy (Renaud et al. 1995), agonist-occupied rat TRa, (Wagner et al. 1995) and unoccupied, but dimeric hRXRa (Bourguet et al. 1995), it is also possible to incorporate the HVDRR mutations in the hormone binding domain (Fig. 2) into a hypothetical structural context. Figure 3 constitutes a schematic compilation of the existing crystallographic data and compares them with natural and artificially generated mutations in hVDR. At the top of Fig. 3, the residue numbers for VDR in the ligand binding domain appear in relation to the older heptad repeat nomenclature (heptads 1—9, dotted boxes). At least some of these heptads, particularly heptads 4 and 9, are thought to facilitate heterodimerization (Nakajima et al. 1994). The El region is a highly conserved area that supports heterodimerization (Whitfield et al. 1995è). The helices depicted schematically in Fig. 3 (open boxes) are those determined for hRARy; this general pattern of -helices and ß-strands (solid boxes) appears to be well conserved across the TR, RAR and RXR members of the subfamily crystallized thus far (Bourguet et al. 1995, Renaud et al. 1995, Wagner et al. 1995). Although the heterodimerization domains have yet to be elucidated by structural analysis, the homodimerization domain of RXR is comprised of helices 7, 9 and 10 (Fig. 3 and Bourguet et al. 1995). Flanking the dimerization region are clusters of ligand binding contacts, shown for RAR and TR in Fig. 3, which paint a picture of hormone binding involving helices 3, 5, 11 and 12 plus portions of helices 6 and 7 along with their intervening loop, as well as the loop between ß-strands 1 and 2.

Figure 3 Hormone binding (R274L and H305Q) and heterodimerization (I314S and R391C) natural mutations in VDR that confer the HVDRR phenotype are positioned in the context of retinoid and thyroid hormone receptor subfamily ligand binding domain structures. See text for details and citations.

As summarized in Fig. 3 and discussed by Whitfield et al. (1995a, 1996), a number of artificially generated mutants in hVDR support the con¬ cept that the dimerization and honnone binding regions in VDR are well aligned with those in RXR, RAR and TR. Of even greater interest and relevance to the present monograph, the four clinically important hVDR mutants under consideration correspond to pertinent locations in the known structures of the retinoid and thyroid hormone receptor ligand binding domains. We postulate that this general structural organization represents that of the VDR ligand binding domain. As shown in Fig. 3, the pure hormone binding mutant hVDRs, namely R274L and H305Q, are located precisely within ligand clusters in helix 5 and in the loop between helix 6 and 7 respectively. I314S, which endows hVDR with combined defects in hormone retention and heterodimerization, lies within helix 7 at a presumed interface of ligand binding and dimerization activities of the receptor (Fig. 3). Finally, R391C is positioned well within the helix 10 dimerization surface, but not far removed from C-terminal ligand binding contacts that are likely influenced by replacement of this amino acid in hVDR. Thus, at least within the context of the assumed structural organization of VDR derived from that of other subfamily members, the I314S and R391C mutations are situated precisely where they would be predicted to lie, given the biological properties of the mutant receptors and the phenotype of the patients. These results not only have profound implications con¬ cerning the putative structure of VDR in relation to its closest relatives, but prove unequivocally that the calcémic actions of l,25(OH)2D3 are mediated by the vitamin D receptor, existing as a l,25(OH)2D3-liganded heterodimer with RXR that is bound to DNA.

Physiology and cellular actions of l,25(OH)2D3

In order to delineate the physiologic roles for the vitamin D hormone, it is appropriate first to place the VDR mediator into the context of vitamin D metabolism and cellular actions. Figure 4 summarizes the integration of vitamin D metabolism and cellular actions introduced in Fig. 1, with physiologic regulatory events now super¬ imposed on the metabolic pathway and the inclusion of an expanded list of physiologic actions for the 1,25( )2 4 hormone. The conversion of vitamin D3 to 25(OH)D3 by the liver is a constitutive metabolic step, followed by the 1-hydroxylation of25(OH)D3 to l,25(OH)2D3, a reaction under exquisite control (Haussler & McCain 1977). When blood calcium is low, activation of this latter step occurs, either as a result of the hypocalcémie state per se, or in response to elevated PTH, each of which serves indepen¬ dently to enhance renal 1-OHase activity. Low phosphate is also capable of separately upregulating the 1-OHase enzyme. To limit activation, the hormonal product, l,25(OH)2D3, effects an ultra-short feedback loop to suppress its own biosynthesis in the kidney and also represses PTH synthesis to remove the peptide hormone stimulus of the 1-OHase via a longer feedback loop (Fig. 4). However, the dominant negative feedback controls of 1-OHase activity appear to result from the concerted actions of l,25(OH)2D3 to stimulate bone mineral résorption and to promote intestinal calcium and phosphate absorption, which together elicit an increase in blood calcium and phosphate levels, each of which down-regulates the 1-OHase.

Figure 4 Vitamin D metabolism and cellulat actions, mediated by the VDR-RXR heterodimer binding to a VDRE

The process by which l,25(OH)2D3 causes bone remodeling is complex, involving stimulation of osteoclast differentiation and osteoblastic production of osteopontin, both of which activate résorption in part through the recognition of bone matrix osteopontin by osteoclast surface avß3-integrin. The résorption effect is supported by l,25(OH)2D3-elicited suppression of bone formation via the induction of osteocalcin and the repression of type I collagen. This latter insight that the normal function of osteocalcin is to curtail bone matrix formation arises from the creation of osteocalcin knockout mice (Ducy et al. 1996). In addition to stimulating the transcription of bone-related genes such as osteopontin and osteocalcin, the l,25(OH)2D3 hormone also induces its own eatab¬ olism in kidney as well as other target tissues like bone by enhancing the expression of the vitamin D-24-OHase enzyme. 24-Hydroxylation of l,25(OH)2D3 is the first step in deactivating the hormone, which is eventually metabolized by side chain cleavage to calcitróle acid (Haussler 1986). Thus, the synthesis of l,25(OH),D3 is not only governed by feedback mechanisms that sense l,25(OH)2D3, calcium, PTH and phosphate concentrations, but the hormone induces the termination of its own signal in target tissues, qualifying l,25(OH)2D3 as a bonafide hormone by any definition.

Figure 4 Vitamin D metabolism and cellulat actions, mediated by the VDR-RXR heterodimer binding to a VDRE

As introduced in the section on HVDRR, mediation of the cellular functions of l,25(OH)2D3 requires that VDR bind the hormonal ligand specifically and with high affinity (Fig. 4). Upon such binding, VDR becomes hyperphosphorylated (Jurutka et al. 1993, Haussler et al. 1994) and recruits RXR into a hetero¬ dimeric complex that binds strongly to DNA (Fig. 4). The l,25(OH)2D3-hganded RXR-VDR heterocomplex selectively recognizes VDREs in the promoter regions of positively controlled genes such as osteocalcin (MacDonald et al. 1991), osteopontin (Noda et al. 1990), vitamin D-24-OHase (Ohyama et al. 199A) and ß3-integrin (Cao et al. 1993). Negative VDREs (Haussler et al. 1995) exist in the 5′-regions of the genes for type I collagen (Pavlin et al. 199A), bone sialoprotein (Li & Sodek 1993), PTH (DeMay et al. 1992) and PTH-related peptide (Falzon 1996, Kremer et al. 1996). The mechanisms whereby VDR accomplishes positive and negative control of DNA transcription after VDRE association are not well under¬ stood, although substantial progress has been made in comprehending the stimulation of transcription as detailed in later sections of this article. Moreover, as summarized in Fig. 5, a number of VDREs have been definitively characterized. The prototypical VDBJS is found in the osteocalcin gene, consisting of an imperfect direct repeat of hexanucleotide estrogen responsive element (ERE)-like, half-sites with a spacer of three nucleotides (DR+3). Classic EREs possess a central GT core at positions 3 and 4 of the hexanucleotide, but this feature is only partially conserved in the six natural positive VDREs listed in Fig. 5. There is, however, absolute conservation of the A in position 6 of the 5′ half-element and of the G at position 2 of the 3′ half-element. A preliminary working consensus for the positive VDRE can be derived from these natural VDREs (see boxed sequence in Fig. 5). This generaliz¬ ation is supported, in part, by PCR experiments that were designed to select, from random oligonucleotides, the highest affinity DNA ligand for the RXR-VDR heterodimer (Nishikawa et al. 1994, Colnot et al. 1995).

Figure 5 Natural vitamin D responsive elements (DR+3s) in genes positively tegulated by l,25(OH)2D3. The consensus VDREs are based on either sequence comparisons (boxed) or a selection of random sequences (at bottom).

The random selection process yields an identical VDRE 5′ half-element of GGGTCA (Fig. 5, bottom), which is also a preferred RXR target when RXR homodimers bind to DNA (Yang et al. 1995). This observation is in concert with the conclusion (Jin & Pike 1996) that, with respect to association ofRXR-VDR with VDREs, RXR lies on the 5′ half-element whereas VDR is situated on the 3′ half-element. Examination of both consensus sequences suggests that the G at position 3 of the spacer is important in VDR binding, a deduction consistent with the finding (MacDonald et al. 1991) that this base is partially protected by RXR-VDR in methylation interference assays. How¬ ever, interesting differences arise when one compares the most frequently encountered 3′ half-element bases in natural VDREs, namely the GGGGCA composite which actually occurs in human osteocalcin, with the GGTTCA random consensus selection for the 3′ half-element (Fig. 5). Clearly, GGTTCA represents a potent VDR binding site, a supposition that is bolstered by the fact that osteopontin, which possesses a perfect DR+3 of GGTTCA, is the highest affinity VDRE we have tested (data not shown). Intriguingly, Ts at positions 3 and 4 in the 3′ VDR half-site occur infrequently in the balance of natural VDREs (Fig. 5). The paucity of Ts in the 3′ half-element could be related to a need for varying potency of VDREs in regulated genes, or may even provide for a repertoire of different VDR conformations that could be induced by contact with distinct 3′ half-site core sequences. This postulated range of VDR conforma¬ tions might endow the receptor with the ability to recruit a variety of different coactivators and corepressors, or even to favor the binding of one vitamin D metabolite ligand over another. Irrespective of the above considerations, it is evident that the primary VDRE is a DR+3 recognition site in DNA that directs the VDR to the promoter region of l,25(OH)2D3 regulated genes, ultimately altering the functions of target cells as a result of transcriptional control of gene expression.

Significance of lipophilic ligands in the association of RXR-VDR with DNA

Dimeric complexes are a feature commonly employed in the regulation of eukaryotic transcriptional systems. This process of protein dimerization often will generate novel heterodimeric complexes which display highly cooperative binding to DNA as well as an altered target sequence specificity (Glass 1994). Among the classical steroid hormone receptors, dimerization results in the formation of symmetrical homodimeric protein complexes on palindromic DNA half sites. Dimerization has been shown to be mediated in part by residues within the DNA binding domain of the receptor (Luisi et al. 1991) and is enhanced by residues within the ligand binding domain (Falwell et al. 1990). The other subfamily of nuclear hormone receptors, including VDR, TR and RAR, apparently binds with highest affinity to direct repeat elements either as homodimers or, more commonly, as heterodimers with RXR (Kliewer et al. 1992). In both subgroups of nuclear receptors, protein-protein interactions serve to align the DNA binding domains so that they are optimally positioned to bind to their specific DNA target sequences (Kurokawa et al. 1993, Perlmann et al. 1993, Rastinejad et al. 1995). The ligand binding region of these receptors is multifunctional, in that this domain not only binds the cognate ligand, but also it possesses a dimerization surface as well as the ligand-dependent transactivation function, AF-2 (Gronemeyer 1991, Chambón 1994). The dimerization surface consists of packed helices which are stabilized by hydrophobic heptad repeats interspersed throughout the structure. Ligand apparently can influence different functional components, including the dimerization interface, and the activating AF-2 domain (Renaud et al. 1995, Wagner et al. 1995). Therefore, a likely role for ligand is to regulate the association and dissociation of dimeric protein complexes and hence regulate specific binding to DNA target sequences.

In this regard the following three questions remain regarding l,25(OH)2D3-mediated control of positively regulated genes: (i) does VDR bind as a homodimer (Freedman et al. 1994, Nishikawa et al. 1994) as well as a heterodimer to DR+3 VDREs? (ii) What is the effect of the l,25(OH)2D3 ligand on VDR or VDR-RXR binding to VDREs? (iii) What role does 9-cis retinoic acid, the RXR ligand, play m RXR-VDR binding to VDREs and enhanced transcription of l,25(OH)2D3-responsive genes? It is generally accepted that TR forms homodimers as well as heterodimers with RXR on thyroid hormone responsive elements (TREs), although recent data suggest that the TR homodimer, when unoccupied by thyroid hormone, operates as a repressor of transcription (Chin & Yen 1996, Schulman et al. 1996). Thyroid hormone is proposed to dissociate TR homodimers to facilitate TRRXR heterodimerization on the TRE and stimulate transcription. In contrast, RAR does not appear to be capable of forming homodimers on DR+5 retinoic acid responsive elements (RAREs) (Perlmann et al. 1996), instead cooperating exclusively with RXR in RARE association and vitamin A metabolite-responsive transcrip¬ tion. When present in excess in gel mobility shift DNA binding assays in vitro, both TR and RAR display RXR heterodimeric association with their respective hormone responsive elements (HREs) in the absence of added lipophilic ligand. These in vitro studies are consistent with immunocytochemical data indicating that, unlike classic steroid honnone receptors that reside in the cytoplasm complexed with Hsp-90 and other proteins in their unoccupied state, unliganded TR, RAR and VDR (Clemens et al. 1988) exist in the nucleus in general association with DNA. These findings have led to the dogma that ligand is not required for TR, RAR and VDR to associate with target HREs. Indeed, we have observed that addition of 260 ng baculovirus-expressed hVDR to a gel shift reaction generates weak homodimeric VDR as well as strong VDR-RXR-heterodimeric binding to a rat osteocalcin VDRE probe, both of which are independent of the presence of l,25(OH)2D3 (Nakajima et al. 1994). However, in vivo footprinting experiments (Blanco et al. 1996, Chen et al. 1996) have led to the conclusion that, at least in the case of RAR-RXR heterodimers, RAR ligands are required for RARE binding. We, therefore, sought to devise an in vitro gel shift assay that would more accurately reflect the in vivo situation, primarily consisting of the use of physiologic salt (0-15 m KCl) concentrations and limited amounts of partially purified, baculovirusexpressed VDR and RXRs (Thompson et al. 1997). Utilizing this assay, we have addressed the three questions regarding VDR/RXR listed above, namely heterodimer versus homodimer, the potential role of l,25(OH)2D3 and the effect of 9-cis retinoic acid (9-cis RA).

When 20 ng VDR (~ 10 nM) or 20 ng VDR plus 20 ng RXR are incubated with either the rat osteocalcin or mouse osteopontin VDREs (see Fig. 5), no DNA-bound homodimeric VDR species is apparent, but a VDRE complexed VDR-RXR heterodimer occurs that is strik¬ ingly dependent upon the presence of the l,25(OH)2D3 ligand (Thompson et al. 1997). Thus, at receptor levels approaching that in a typical target cell, a VDR liganddependent heterodimer with RXR is the preferred VDRE binding species. Only when VDR or VDR plus RXR levels are raised to 100 ng of each receptor with the mouse osteopontin VDRE (Thompson et al. 1997), or 260 ng with the weaker rat osteocalcin VDRE (Nakajima et al. 1994), can faint homodimers of VDR bound to the probe be visualized. In addition, at these greater amounts ofreceptors, neither the VDR homodimer nor the VDRRXR heterocomplexes are modulated significantly by inclusion of l,25(OH)2D3 in the incubation (Thompson et al. 1997). We, therefore, conclude that higher receptor levels in vitro generate artifactual VDR homodimers as well as attenuate the normal physiological ligand dependence of VDR-RXR binding to the VDRE. To explain seemingly ligand-independent VDR-RXR association with the VDRE, we postulate the existence of a subpopulation of VDR that is unstably activated in the absence of l,25(OH)2D3 (Schulman et al. 1996) and therefore capable of heterodimerization to generate a positive gel mobility shift under conditions of vast receptor excess. In contrast, our physiologically relevant gel shift assay at <10nM receptor levels and 0-15 m KCl reflects the presumed in vivo events of ligand triggered heterodimerization (Blanco et al. 1996, Chen et al. 1996), and extends earlier in vitro data showing that l,25(OH)2D3 enhances VDRRXR complex formation (Sone et al. 1991, MacDonald et al. 1993, Ohyama et al. 1994).

Next, we tested the effect of 9-cis RA in this gel shift assay. A spectrum of data exists on the role of 9-cis RA in l,25(OH)2D3-stimulated transcription, including demon¬ stration of synergistic action with l,25(OH)2D3 (Carlberg et al. 1993, Schrader et al. 1994, Kato et al. 1995, Sasaki et al. 1995), negligible action (Ferrara et al. 1994), or an inhibitory effect (MacDonald et al. 1993, Jin & Pike 1994, Lemon & Freedman 1996). These marked differences likely result from varying transfection and ligand addition protocols, as well as cell and species specificity. Employing the physiological gel shift procedure with biochemically defined components, we obtained clear evidence that 9-cis RA is a potent inhibitor of l,25(OH)2D3-enhanced, VDR-RXR binding to VDREs such as osteocalcin, with dramatic attenuation by the retinoid occurring at concentrations as low as 10 m (Thompson et al. 1997). Previous gel shift data had also hinted at 9-cis RA inhibition (MacDonald et al. 1993, Cheskis & Freedman 1994), even though higher concentrations of 9-cis RA were utilized in these earlier studies. One somewhat puzzling finding, however, was that the suppressive effect of 9-cis RA seemed more pronounced in vitro than in transfected cells, where retinoid inhibition of l,25(OH)2D3-stimulated transcription is significant, but 50% or less in magnitude (MacDonald et al. 1993). This suggested that multiple pathways may exist for the assembly of the RXR-VDR heterocomplex in vivo. To probe for distinct routes of assembly, we varied the order of addition ofVDR, RXR, l,25(OH)2D3 and 9-cis RA in the gel shift assay for VDRE binding (Thompson et al. 1997). The results showed that 9-cis RA is a potent inhibitor of VDR-RXR heterodimerization on the VDRE in all situations except when VDR alone is preincubated with l,25(OH)2D3 followed by addition of RXR (Thompson et al. 1997). To explain these data, we have developed the model depicted in Fig. 6, which hypothesizes two alternative allosteric pathways for the interaction ofVDR-RXR with the VDRE.

Figure 6 Model of two different allosteric pathways for VDR-RXR-1,25(OH)2D3 binding to DNA.

In pathway A (Fig. 6), l,25(OH)2D3 occupies monomeric VDR, altering the conformation of the ligand binding domain such that it recruits RXR for heterodimeric binding to DNA and subsequent VDRE recognition. Importantly, we pos¬ tulate that previously occupied VDR conformationally influences RXR in the resulting heterodimer such that it is incapable of being liganded by 9-cis RA (pathway A, Fig. 6). This action to abolish RXR ligand responsiveness both silences the ability of 9-cis RA spuriously to trigger vitamin D hormone signal transduction, and prevents 9-cis RA from dissociating the RXR-VDR complex in order to divert RXR for retinoid signal transduction. On the other hand, as illustrated in pathway (Fig. 6), we propose that RXR exists in a different, 9-cis RA-receptive, allosteric state in most other circumstances, such as when present as a monomer, in an apoheterodimer with VDR, or even when the apoheterodimer of RXR and VDR is subsequently liganded with l,25(OH)2D3. This latter species of RXR-VDR-l,25(OH)2D3 (pathway B) is hypothesized to be fully competent in VDRE recognition, but the 9-cis RA binding function of the RXR partner has not been conformationally repressed, rendering this form sensitive to dissociation by 9-cis RA, which would then favor the formation of retinoid-occupied RXR homo¬ dimers. Therefore, unless VDR monomers are first occu¬ pied by l,25(OH)2D3 (pathway A), 9-cis RA can operate to divert or dissociate RXR and direct it to form RXR homodimers (pathway B). It is tempting to speculate that the l,25(OH),D3-liganded heterodimer in pathway A is more potent in transcriptional stimulation than the analogous species in pathway B, perhaps because the AF-2 function of the RXR partner is allosterically activated only in the former instance. The l,25(OH)2D3-occupied VDR-RXR in pathway has the advantage of flexible regulation because it is effectively a two-ligand switch. It likely occurs in vivo because, as stated above, the fact that 9-cis RA blunting significant but incomplete suggests that at least two populations of RXR-VDR heterodimers exist. Finally, when our model (Fig. 6) is compared with those for RXR-RAR and RXR-TR (Forman et al. 1995), it is evident that VDR is closer in mechanism of action to the TR, where 9-cis RA inhibits TR signal transduction by diversion of BJÍR (Lehmann et al. 1993). Also analogous is the fact that thyroid hormone occupation of the TR partner abolishes 9-cis RA binding to the RXR counter¬ part (Forman et al. 1995). Finally, the action of RXRPJ\R heterodimers seems to be fundamentally different from that of RXR-VDR in that RAR liganding by a retinoid facilitates RXR occupation by its retinoid ligand, resulting in cooperative stimulation of gene transcription by the repertoire of vitamin A metabolites.

VDR protein-protein interactions that effect gene transcription

Although we now have at least a rudimentary understand¬ ing of ligand-induced VDR binding to a VDRE, the next logical question is how does VDR regulate the machinery for gene transcription? In the basal state ofDNA transcrip¬ tion, the TATA-box binding protein (TBP) and its associated factors (TAFs) are bound to the TATA box at approximately position — 20 in the 5′ region of controlled genes, but the frequency of transcriptional initiations is very low because the RNA polymerase II-basal transcription factor IIB (TFIIB) enzyme complex is not stably associated with TBP-TAFs. The recruitment of the TFIIB-RNA polymerase II complex appears to be the rate limiting step in preinitiation complex formation, and is stimulated dramatically when a transacting factor or factors bind to upstream enhancers. In a process involving DNA looping, transactivators are thought to attract TFIIB and also interact with TAFs, forming a stable preinitiation complex that executes repeated rounds of productive transcription. Recent data indicate that the activation function in the hormone binding domain of the estrogen receptor, AF-2, associates specifically with a TAF known as TAFn30 (Jacq et al. 1994) and that the estrogen receptor (ER) binds to TFIIB in vitro (lng et al. 1992). In collaboration with Ozato and associates and Tsai and O’Malley, we have observed that hVDR also specifically associates with hTFIIB (Blanco et al. 1995). In this work, Blanco et al. (1995) showed that VDR binds to a TFIIB-glutathione S transferase fusion protein linked to glutathione-laden beads. Additionally, it was observed that both TRa and RARa interact with hTFIIB (Blanco et al. 1995), but that RXR does so only very weakly (P W Jurutka, L S Remus and M R Haussler, unpublished results). This last result suggests that, while the ligand binding partners in the VDR/TR/RAR subfamily provide a hard-wired connection to the assembly and en¬ hancement of the transcription machinery, the RXR partner is not primarily engaged in TFIIB contact.

Independent data obtained by MacDonald et al. (1995) using the powerful yeast two-hybrid system to detect protein-protein interactions also revealed that hVDR binds efficiently to TFIIB. Moreover, MacDonald et al. (1995) further exploited the yeast two-hybrid system to prove that, while hVDR and RXR interact, no homodimeric association occurs for hVDR alone, providing further evidence against the existence of physiologically significant VDR homodimers. Utilizing fusion protein technology, they also showed that VDR interacts directly with RXR to form a heterodimer in solution in the absence of DNA and, further, that this process was enhanced 8-fold by the presence of l,25(OH)2D3 hor¬ mone (MacDonald et al. 1995). Because hVDR-TFIIB association is not dependent upon the l,25(OH)2D, ligand (Blanco et al. 1995, MacDonald et al. 1995), the role of l,25(OH)2D3 can now be further resolved to an early participation in conforming VDR such that it attracts RXR followed by the targeting of the resulting RXR-VDR heterodimer to VDREs (see Fig. 6).

Figure 6 Model of two different allosteric pathways for VDR-RXR-1,25(OH)2D3 binding to DNA.

Interestingly, the presence of BJCR further facilitates VDR-TFIIB association, especially in the presence of l,25(OH)2D3 (PW Jurutka, LS Remus and MR Haussler, unpublished results). In fact, because of its capacity to enhance VDR-RXR heterodimerization, the l,25(OH)2D3 ligand is capable ofgenerating high levels of an RXR-VDR-TFIIB ternary complex in solution, sig¬ nificantly in excess ofthat occurring with either RXR and TFIIB or even with VDR and TFIIB (P W Jurutka, L S Remus and M R Haussler, unpublished results). These data not only reaffirm the interaction ofVDR with TFIIB, but also they imply that the l,25(OH)2D3-liganded VDR-RXR complex is the most efficient binder of TFIIB. This latter effect may be the result of positive conformational influences of RXR on liganded VDR, since VDR is the primary attachment moiety for TFIIB.

Because VDR-TFIIB interactions have been detected either in vitro or in the yeast system where certain mammalian cell restrictions may be relaxed, it was import¬ ant to confirm the relevance ofVDR-TFIIB association in mammalian cells. Blanco et al. (1995) have reported functional studies which, for the first time, show the interaction ofTFIIB with a member ofthe steroid receptor superfamily in ligand-dependent activation oftranscription in intact cells. In pluripotent PI9 mouse embryonal carcinoma cells, transfection of hVDR or hTFIIB alone produced no better than a 2-fold induction of VDREluciferase reporter expression by l,25(OH)2D3. However, when transfected together, hVDR and hTFIIB mediated a synergistic transcriptional response of approximately 30-fold when l,25(OH)2D3 was added, an effect which was absolutely dependent on the presence of the VDRE in the luciferase construct. It should be noted that the VDR-TFIIB positive cooperation appears to be cellspecific because similar experiments in contact-inhibited NIH/3T3 Swiss mouse embryo cells resulted in squelching of transcription by TFIIB. Therefore, in more differentiated cells, perhaps including osteoblasts or fibro¬ blasts, accessory coactivators may be present to modulate TFIIB or bridge between VDR and TFIIB.

In summary, VDR and TFIIB are hypothesized to exist in a multi-subunit transcription complex which also con¬ tains TAFs and/or coactivators that may be promoter- or tissue-specific. Further characterization of this complex will require the discovery of cell type and promoterspecific components via transfection and biochemical interaction studies. Ultimately, an in vitro transcription system must be devised which utilizes defined components to replicate faithfully l,25(OH)2D3-stimulated gene expression.

One subdomain of VDR that likely interacts with coactivators and/or basal transcription factors is the extreme C-terminus. We have previously shown that 403 hVDR, a truncated receptor that lacks the C-terminal 25 amino acids, binds l,25(OH),D3 ligand with reasonable affinity and heterodimerizes normally with RXR, but is devoid of transcriptional activity (Nakajima et al. 1994). These data suggest that VDR contains a transcriptional activation domain near its C-terminus.

Figure 7 The extreme C-terminal amino acid sequence compared across the nuclear receptor superfamily: VDR appears to share the ligand-dependent transcription activation function (AF-2). AR, androgen receptor; CR, glucocorticoid receptor; PR, progesterone receptor.

Indeed, as illustrated in Fig. 7, the region of VDR from residues 416 to 422 possesses a high degree of similarity to the analogous sequences in the entire nuclear receptor superfamily. One hallmark of this conserved sequence is the glutamic acid residue at position 420 of hVDR (Fig. 7) included in a consensus of (where cp=a hydrophobic amino acid) for this domain (Renaud et al. 1995, Wagner et al. 1995). Allowing for conservative replace¬ ments, it seems virtually certain that hVDR forms an amphipathic helix (corresponding to helix 12 in the other receptors) surrounding glutamic acid-420 that is analogous to the ligand-dependent activation function (AF-2) char¬ acterized for TR (Barettino et al. 199A), RAR (Renaud et al. 1995), RXR (Leng et al. 1995) and ER (Danielian et al. 1992). Although this AF-2 domain is capable of autonomously activating transcription (Leng et al. 1995), that such activity is modest may be because of the fact that the AF-2 region is proposed to operate in a liganddependent fashion, involving a structural rearrangement to reposition the AF-2 for both intramolecular and intermolecular protein—protein interactions. Specifically, based upon the crystal structure of unoccupied RXR (Bourguet et al. 1995) and liganded RAR (Renaud et al. 1995) and TR (Wagner et al. 1995), helix 12/AF-2 appears to protrude outward from the more globular ensemble of helices 1—11 in the absence ofligand, such that it is unable to interact efficiently with coactivator/transcription factor. Upon liganding, a conformational signal is then transmit¬ ted to helix 12 that causes it to fold back on helix 11 and attach to the face of the globular ligand binding domain. The pivoting of helix 12 seemingly accomplishes two feats that mediate ligand-activated transcription by the receptor: (i) closing of a ‘door’ on the channel through which the lipophilic ligand enters the internal binding pocket of the receptor, and (ii) locking helix 12 into a stable confor¬ mation that facilitates its interaction with coactivator/ transcription factor. Ligand binding contacts on or near helix 12 (see Fig. 3) probably are significant in maintaining this active positioning of helix 12, essentially trapping ligand in the binding pocket to effect more sustained transactivation events.

Figure 7 The extreme C-terminal amino acid sequence compared across the nuclear receptor superfamily: VDR appears to share the ligand-dependent transcription activation function (AF-2). AR, androgen receptor; CR, glucocorticoid receptor; PR, progesterone receptor.

In order to evaluate the relevance of the above proposed mechanism for VDR action, we (Jurutka et al. 1997) have altered E-420 and L-417 (see Fig. 7) individually to alanine residues, which preserves the putative -helical character of this region. The altered VDRs bind ligand near-normally, with only a mild increase (about 3-fold) in the Kd for the E420A receptor. Both E420A and L417A hVDRs also heterodimerize efficiently with RXR and associate with VDREs similarly to wild-type hVDR, yet their capacity for l,25(OH)2D3-stimulated transcription is abolished, even at high doses ofligand (Jurutka et al. 1997). These point mutations, therefore, identify a C-terminal AF-2 in VDR which corresponds to similar activation domains in other nuclear receptor superfamily members. Because VDR interacts with TFIIB, one of the first questions we asked was whether the VDR AF-2 consti¬ tutes a contact site for this basal transcription factor. Although some very preliminary evidence existed for an association between TFIIB and the C-terminus of hVDR (MacDonald et al. 1995), we observed that neither the E420A nor the L417A mutant VDRs are impaired in their interaction with TFIIB as probed with glutathione-S transferase—TFIIB fusion protein binding technology (Jurutka et al. 1997). Thus, the domain(s) of VDR that interfaces with TFIIB apparently lies elsewhere in the receptor, possibly in the N-terminal portion of the ligand-binding region (Blanco et al. 1995), in the hinge (MacDonald et al. 1995), or in the vicinity of the DNA-binding zinc fingers.

The present experiments with VDR are in concert with recent insight into the function of AF-2 in other nuclear receptors, which is to recruit coactivators of the type of steroid receptor coactivator-1 (SRC-1) (Oñate et al. 1995). A number of candidate coactivators have been isolated in addition to SRC-1 (Halachmi et al. 199A, Baniahmad et al. 1995, CavaiUes et at. 1995, Lee et al. 1995, Hong et al. 1996) and, in several cases, interaction with nuclear receptors requires intact AF-2 core regions (Baniahmad et al. 1995, CavaiUes et al. 1995). Moreover, AF-2 mutations act as dominant negative receptors, for example in the case of hRARy (Renaud et al. 1995). Indeed, we have observed that VDR AF-2 mutants E420A and L417A exhibit dominant negative properties with respect to transcriptional activation (Jurutka et al. 1997). Such AF-2 altered receptors are inactive transcriptionally, but can bind l,25(OH)2D3 ligand and heterodimerize normally on VDREs, the consequence being competition with wild-type VDR-RXR heterodimers for VDRE binding. These data argue that the AF-2 of the primary VDR partner in an RXR-VDR heterodimer is absolutely required for the mediation of l,25(OH)2D3-activated transcription, not only for its intrinsic activation potential, but also because of its presumed role in stabilizing the retention of l,25(OH)2D3 ligand in the VDR binding pocket.

Figure 6 Model of two different allosteric pathways for VDR-RXR-1,25(OH)2D3 binding to DNA.

What part, if any, is played by the AF-2 domain (Fig. 7) of the RXR ‘silent’ partner in the RXR-VDRl,25(OH)2D3 signal transduction pathway? To investigate this phenomenon, AF-2 truncated mutants of RXRa or RXRß were created and tested for their ability to function as dominant negative modulators of l,25(OH)2D3- stimulated transcription (Blanco et al. 1996). Because previous data with RXR-RAR control of gene expression seemed to indicate that the RXR AF-2 was dispensable (Durand et al. 1994), we were surprised to find that AF-2 truncated RXRs were potent dominant negative effectors of l,25(OH)2D3 action in transfected cells (Blanco et al. 1996). We, therefore, conclude that although the RXR ‘silent’ partner in VDR signaling apparently is not occupied by retinoid ligand (see Fig. 6), its AF-2 does play an active role in transcriptional stimulation. A similar conclusion has also been reached recently by two other groups studying RXR-RAR action (Chen et al. 1996, Schulman et al. 1996), with the use of RAR-specific ligands precluding ligand binding by the RXR partner. However, Schulman et al. (1996) have introduced a caveat to the above theory as they point out that AF-2-truncated RXRs in heterodimers become strong, constitutive binders of corepressors like the silencing mediators of retinoid and thyroid hormone receptors (SMRTs). Thus, an alternative explanation to an active coactivator-binding role for RXR AF-2 in heterodimers is that it plays a more passive role in excluding corepressors. In this latter scenario, truncation or point mutation (Schulman et al. 1996) of RXR AF-2 generates spurious corepressor binding rather than compromising coactivator contact. Only additional research into coactivator and corepressor associations of VDR-RXR heterodimers will resolve this issue.

General mechanism for vitamin D hormone action on transcription

In order to provide a working hypothesis for l,25(OH)2D3 action at the molecular level, we have developed the model illustrated in Fig. 8. It is based primarily on data from our laboratory and others studying 1,25(OH)2D3 and VDR, and it relies on the assumed similarities between VDR action and that of TR and RAR. VDR is proposed to exist in target cell nuclei, perhaps very weakly associ¬ ated with DNA, in a monomeric, inactive conformation with the C-terminal AF-2 domain extended away from the hormone binding cavity. Upon liganding with l,25(OH)2D3, VDR assumes an active conformation, with the AF-2 pivoted into correct position for both ligand retention and coactivator contact. In addition, the hormone facilitates interaction of VDR and RXR through a stabilized heterodimerization interface. In turn, 1,25(OH)2D3-occupied VDR may itselffunction as a kind of allosteric regulator of RXR, perhaps by conveying a confonnational signal through the juxtapositioned dimer¬ ization domains to induce the AF-2 ofRXR into an active conformation for coactivator binding. As discussed above (see Fig. 6), the joining of preliganded VDR and unliganded RXR apparently renders the RXR partner unresponsive to binding and either activation or dissocia¬ tion by 9-cis RA. Alternatively, if 9-cis RA encounters RXR monomer first (Fig. 8), or binds to RXR that is complexed with VDR in an apoheterodimer (Fig. 6), the retinoid is able to divert the RXR to generate homo¬ dimers and effectively blunt l,25(OH)2D3-driven transcription In the primary activation pathway pictured in Fig. 8, the RXR-VDR-l,25(OH)2D3 complex recognizes and targets the genes to be controlled through high affinity association with the VDRE in a gene promoter region. Coactivators that are presumed to bind to VDR and RXR AF-2 s are then postulated to link with TAFs/TBP, thereby looping out DNA 5′ of the TATA box. This series of events positions VDR such that it can independently recruit TFIIB to the promoter complex, a process that initiates the assembly of the RNA polymerase II holoenzyme into the preinitiation complex. Precedents exist for transcription factors independently attracting TFIIB, such as hepatocyte nuclear factor-4 (Malik & Karathanasis 1996), as well as for a sequential, two-step pathway for activator-stimulated transcriptional initiation (Struhl 1996, Stargell & Struhl 1996). Using the latter model as an analogy, the VDR activator would contact both TBP/ TAFs (via – coactivator bridges) and TFIIB in order to initiate RNA polymerase II holoenzyme assembly. The order of attachment of these two ‘arms’ of activation has not been determined but, at least, in the case of acidic activators, recruitment to the TATA element precedes interaction with components of the initiation complex (Stargell & Struhl 1996). It is of interest that the mechan¬ ism of l,25(OH)2D3 action depicted in Fig. 8 is not only essential for induction of bone remodeling and other vitamin D functions, but is also self-limiting via 24-OHase induction. In addition, these actions of l,25(OH),D, would be blunted under conditions within a cell where 9-cis RA concentrations dominate over those of l,25(OH)2D3.

Figure 8 Model for transcriptional activation by 1,25(OH)2D3 on the promoter of a target gene

The above described molecular mechanism whereby the vitamin D hormone controls gene expression requires further experimental evaluation. To advance our under¬ standing of the structure/function relationships in VDR, a physical characterization of the structure of VDR via X-ray crystallography will be required. Furthermore, in order to comprehend the genomic action of vitamin D in calcium homeostatic and other target cells, it will be necessary to elucidate the detailed involvement of various RXR isoforms, specific TAFs and novel coactivators/ corepressors that might influence the regulation of differ¬ ent vitamin D-controlled promoters. This information in its entirety should assist in determining the potential role for VDR and l,25(OH)2D3 in the pathophysiology of osteoporosis and other endocrine-related bone diseases.

References

Baniahmad C, Nawaz Z, Baniahmad A, Gleeson MAG, Tsai M-J & O’Malley BW 1995 Enhancement of human estrogen receptor activity by SPT6: a potential coactivator. Molecular Endocrinology 9 34-43.

Barettino D, Ruiz MdMV & Stunnenberg HG 1994 Characterization of the ligand-dependent transactivation domain of thyroid hormone receptor. EMBOJournal 13 3039-3049.

Blanco JCG, Wang I-M, Tsai SY, Tsai MJ, O’Malley BW, Jurutka PW, Haussler MR & Ozato 1995 Transcription factor TFIIB and the vitamin D receptor cooperatively activate ligand-dependent transcription. Proceedings of the National Academy of Sciences of the USA 92 1535-1539.

Blanco JCG, Dey A, Leid M, Minucci S, Park B-K, Jurutka PW, Haussler MR & Ozato 1996 Inhibition of ligand induced promoter occupancy in vivo by a dominant negative RXR. Genes to Cells 1 209-221.

Bourguet W, Ruff M, Chambón , Gronemeyer & Moras D 1995 Crystal structure of the ligand-binding domain of the human nuclear receptor RXR-a. Nature 375 377-382.

Cai Q, Hodgson SF, Kao PC, Lennon VA, Klee GG, Zinmeister AR & Kumar R 1994 Inhibition of renal phosphate transport by a tumor product in a patient with oncogeneic osteomalacia. New England Journal of Medicine 330 1645-1649.

Cao X, Ross FP, Zhang L, MacDonald PN, Chappel J & Teitelbaum SL 1993 Cloning of the promoter for the avian integrin ß3 subunit gene and its regulation by 1,25-dihydroxyvitamin D3. Journal of Biological Chemistry 268 27371-27380.

Carlberg C, Bendik I, Wyss A, Meier E, Sturzenbecker LJ, Grippo JF & Hunziker W 1993 Two nuclear signalling pathways for vitamin D. Nature 361 657-660.

more…

 

The structure of the nuclear hormone receptors.
  • 1Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch at Galveston, 77555-0645, USA.

Steroids. 1999 May;64(5):310-9.   http://www.ncbi.nlm.nih.gov/pubmed/10406480

The functions of the group of proteins known as nuclear receptors will be understood fully only when their working three-dimensional structures are known. These ligand-activated transcription factors belong to the steroid-thyroid-retinoid receptor superfamily, which include the receptors for steroids, thyroid hormone, vitamins A- and D-derived hormones, and certain fatty acids. The majority of family members are homologous proteins for which no ligand has been identified (the orphan receptors). Molecular cloning and structure/function analyses have revealed that the members of the superfamily have a common functional domain structure. This includes a variable N-terminal domain, often important for transactivation of transcription; a well conserved DNA-binding domain, crucial for recognition of specific DNA sequences and protein:protein interactions; and at the C-terminal end, a ligand-binding domain, important for hormone binding, protein: protein interactions, and additional transactivation activity. Although the structure of some independently expressed single domains of a few of these receptors have been solved, no holoreceptor structure or structure of any two domains together is yet available. Thus, the three-dimensional structure of the DNA-binding domains of the glucocorticoid, estrogen, retinoic acid-beta, and retinoid X receptors, and of the ligand-binding domains of the thyroid, retinoic acid-gamma, retinoid X, estrogen, progesterone, and peroxisome proliferator activated-gamma receptors have been solved. The secondary structure of the glucocorticoid receptor N-terminal domain, in particular the taul transcription activation region, has also been studied. The structural studies available not only provide a beginning stereochemical knowledge of these receptors, but also a basis for understanding some of the topological details of the interaction of the receptor complexes with coactivators, corepressors, and other components of the transcriptional machinery. In this review, we summarize and discuss the current information on structures of the steroid-thyroid-retinoid receptors.

 

 Cellular retinoid-binding proteins.
Ong DE1.  Author information
Arch Dermatol. 1987 Dec;123(12):1693-1695a.

A number of specific carrier proteins for members of the vitamin A family have been discovered. Two of these proteins bind all-trans-retinol and are found within cells important in vitamin A metabolism or function. These two proteins have considerable sequence homology and have been named cellular retinol-binding protein (CRBP) and cellular retinol-binding protein, type II (CRBP [II]). A third intracellular protein, cellular retinoic acid-binding protein (CRABP) also is structurally similar but binds only retinoic acid. Although retinol appears to be bound quite similarly by the two retinol-binding proteins, subtle differences are apparent that appear to be related to the different functions of the two proteins. That, coupled with the specific cellular locations of the two proteins, suggests their roles. Cellular retinol-binding protein appears to have several roles, including (1) delivering retinol to specific binding sites within the nucleus and (2) participating in the transepithelial movement of retinol across certain blood-organ barriers. In contrast, CRBP (II) appears to be involved in the intestinal absorption of vitamin A and, in particular, may direct retinol to a specific esterifying enzyme, resulting in the production of fatty acyl esters of retinol that are incorporated into chylomicrons for release to the lymph. Like CRBP, CRABP can deliver its ligand retinoic acid to specific binding sites within the nucleus, sites different from those for retinol. The nuclear binding of retinol and retinoic acid may be part of the mechanism by which vitamin A directs the state of differentiation of epithelial tissue.

 

Interaction of the Retinol/Cellular Retinol-binding Protein Complex with Isolated Nuclei and Nuclear Components
GENE LIAU, DAVID E. ONG, and FRANK CHYTIL
Department of Biochemistry, Vanderbilt University School of Medicine, Nashville, Tennessee 37232
http://jcb.rupress.org/content/91/1/63.full.pdf

Retinol (vitamin A alcohol) is involved in the proper differentiation of epithelia. The mechanism of this involvement is unknown. We have previously reported that purified cellular retinol-binding protein (CRBP) will mediate specific binding of retinol to nuclei isolated from rat liver. We now report that pure CRBP delivers retinol to the specific nuclear binding sites without itself remaining bound. Triton X-100-treated nuclei retain the majority of these binding sites. CRBP is also capable of delivering retinol specifically to isolated chromatin with no apparent loss of binding sites, as compared to whole nuclei . CRBP again does not remain bound after transferring retinol to the chromatin binding sites. When isolated nuclei are incubated with [ 3H]retinol-CRBP, sectioned, and autoradiographed, specifically bound retinol is found distributed throughout the nuclei . Thus, CRBP delivers retinol to the interior of the nucleus, to specific binding sites which are primarily, if not solely, on the chromatin . The binding of retinol to these sites may affect gene expression.

Early histological studies have clearly shown that when animals become vitamin A deficient various epithelial tissues of these animals lose the ability to maintain proper differentiation (1) . However, providing retinol (vitamin A alcohol) to the animal permits tissue repair, with improperly differentiated cells rapidly replaced by normal cells (2) . This indicates that vitamin A has an essential role in cellular differentiation . The action of retinol appears to be mediated by a specific intracellular protein called cellular retinol-binding protein (CRBP). CRBP binds retinol with great avidity and specificity and has been detected in a number oftissues (3, 4) . Recently, CRBP was purified and partially characterized (5, 6) . It is distinct from the well-known serum retinol transport protein called retinol-binding protein (5, 7) . That CRBP plays an important role in the action of vitamin A is suggested by the following observations: It is found complexed with retinol in vivo (4, 8). It binds cis-isomers of retinol with a specificity that parallels the in vivo activity of these isomers (9), Finally, if retinol is first complexed with CRBP, the retinol can bind to the nucleus in a specific and saturable manner (10) . In this study we compare the interaction of the CRBP-retinol complex with isolated nuclei to its interaction with isolated chromatin and follow the fate of both the protein and the ligand . The nuclear binding sites for retinol were localized using autoradiography .

……

The experiments described here were designed to gain insight concerning the still unknown molecular mechanisms by which retinol exerts its effects on the differentiation of epithelia. Alterations in genomic expression appear to be induced in animals fed a retinol-deficient diet, as shown by changes in nuclear RNA synthesis observed in vivo (27-30) as well as in vitro (13) . A working hypothesis has been used that retinol, being a small molecule, might exert its action in a way similar to the accepted model for the mode of action of steroid hormones in differentiation . This model involves binding of the steroid hormone inside the target cell to a specific binding protein called a receptor . The resulting cytoplasmic ligand receptor complex, after undergoing a not fully understood conformational change, translocates to the nucleus . The receptor protein can then be detected in nuclear extracts by its ability to bind specifically the steroid hormone. The receptor steroid complex has been shown to interact with chromatin. Such interaction is believed to lead to an altered expression of the genome, which is the basis for the steroid hormone-induced differentiation (31) .

The steroid hormone model has been used profitably to investigate the mode of retinol action . Indeed, a specific binding protein for retinol, CRBP, was discovered to be present in many tissues (3) . Moreover, after purifying this protein to homogeneity, it was demonstrated that CRBP is able to deliver retinol to the nucleus in a specific manner (10) .

However, we report here a unique feature which appears to be distinct from the steroid hormone model. Using retinol CRBP complex in which the radioactive label is on the protein, we find that CRBP delivers retinol in a specific manner to the nucleus; the retinol associates with chromatin, but the protein itself does not remain bound. This conclusion is based on the observation that the radioactively-labeled protein is still able to deliver retinol inside the nucleus, but it cannot be recovered with the nucleus, in contrast to steroid hormone receptors.

The interaction of the specifically delivered retinol appears to be primarily with chromatin. The outer nuclear envelope is apparently not significantly involved in the interaction as Triton X-100-treated nuclei retain 70% of the retinol binding sites found in intact nuclei. It is still possible that the isolated chromatin and the Triton-treated nuclei contain some of the nuclear matrix and that it is actually the matrix which contains the specific binding sites for retinol. However, preliminary evidence indicates that the specific binding sites remain with a soluble chromatin preparation prepared by mild nuclease digest of nuclei rather than with the nuclear matrix. That the CRBP is necessary for delivering retinol to the nucleus is clearly documented by autoradiography. Free retinol, not bound to CRBP, binds nonspecifically to the nuclei, and to chromatin, and autoradiography shows indiscriminate localization of retinol in the lipid-rich nuclear membrane areas.

The data presented here invite the proposal that the retinolCRBP complex enters the nucleus in some manner which is apparently not dependent on the nuclear membrane. The complex then recognizes a limited number (generally an order of magnitude greater than for steroid hormones) of specific sites on the chromatin where the transfer of retinol from CRBP to these sites takes place. The sites were not detectable and may not be accessible if the retinol is free from CRBP. After the transfer CRBP does not remain associated with the specific sites . The functional significance of the specific interaction between retinol and chromatin remains to be demonstrated .

 

Inhibition of vitamin D receptor-retinoid X receptor-vitamin D response element complex formation by nuclear extracts of vitamin D-resistant New World primate cells.
Most New World primate (NWP) genera evolved to require high circulating levels of steroid hormones and vitamin D. We hypothesized that an intracellular vitamin D binding protein (IDBP), present in both nuclear and cytoplasmic fractions of NWP cells, or another protein(s) may cause or contribute to the steroid hormone-resistant state in NWP by disruption of the receptor dimerization process and/or by interference of receptor complex binding to the consensus response elements present in the enhancer regions of steroid-responsive genes. We employed electromobility shift assay (EMSA) to screen for the presence of proteins capable of binding to the vitamin D response element (VDRE). Nuclear and post-nuclear extracts were prepared from two B-lymphoblastoid cell lines known to be representative of the vitamin D-resistant and wild type phenotypes, respectively. The extracts were compared for their ability to retard the migration of radiolabeled double stranded oligomers representative of the VDREs of the human osteocalcin and the mouse osteopontin gene promoters. A specific, retarded band containing VDR-RXR was identified when wild type cell but not when vitamin D-resistant cell nuclear extract was used in the binding reaction with either probe. In addition, vitamin D-resistant cell nuclear extract contained a protein(s) which was bound specifically to the VDRE and was capable of completely inhibiting VDR-RXR-VDRE complex formation; these effects were not demonstrated with nuclear extract from the wild type cell line or with the post-nuclear extract of the vitamin D-resistant cell line. We conclude that a VDRE-binding protein(s), distinct from IDBP and present in nuclear extract of cells from a prototypical vitamin D-resistant NWP, is capable of inhibiting normal VDR-RXR heterodimer binding to the VDRE.
Reversing Bacteria-Induced Vitamin D Receptor Dysfunction to Treat Chronic Disease: Why Vitamin D Supplementation Can Be Immunosuppressive, Potentially Leading to Pathogen Increase
by J.C. Waterhouse, PhD
Recent attempts to increase vitamin D supplementation to prevent and treat chronic disease have arisen primarily out of observations of low vitamin D levels (25-D) being associated with a variety of diseases. However, new research indicates that these low vitamin D levels are often the result rather than the cause of the disease process, just as in the autoimmune disease, sarcoidosis. Trevor Marshall, PhD, recently summarized this alternative perspective on vitamin D, in a session he co-chaired at the 6th International Congress on Autoimmunity. He and his colleagues presented in silico* and clinical data from the last eight years, indicating that intraphagocytic bacteria are able to block the vitamin D receptor (VDR), and this leads to abnormally low measured vitamin D levels. A second consequence of the bacteria-induced VDR blockage is inhibition of innate immunity. By blocking the VDR, bacteria are able to cause persistent infection and inflammation and thus cause many chronic diseases. Short-term symptom reduction observed from vitamin D supplementation appears to be due to immune suppression by precursor forms of vitamin D that add to the bacterial blockage of the VDR. In silico data also indicates that high levels of vitamin D metabolites suppress antimicrobial peptide production by binding to other nuclear receptors (e.g., thyroid-alpha-1, glucocorticoid). Increasingly, epidemiological, geographical and clinical data are lending support to this model of disease. Studies using more advanced cell culture and molecular techniques are confirming the presence of previously undetected bacteria, including biofilm and cell wall deficient bacteria, as well as “persisters.” A greater understanding of how bacteria resist standard antibiotic approaches is also being gained. A protocol has been developed that is successfully restoring VDR and innate immune function with a VDR agonist and eliminating pathogens with low-dose, pulsed combinations of antibiotics. Immunopathological reactions (a.k.a., Jarisch-Herxheimer reactions) occur due to increased pro-inflammatory cytokines resulting from bacterial killing. The result is an exacerbation of symptoms with each dose of antibiotic, but improvement occurs over the long-term. Remission is being achieved in numerous chronic conditions, including many autoimmune diseases and fibromyalgia, as well as many diseases of aging. Although vitamin D ingestion is avoided as part of this protocol, the evidence indicates that the net result of the protocol is improved vitamin D receptor activation.

Introduction
Vitamin D is a topic of increasing interest and has been implicated in many physiological processes beyond its initially recognized role in calcium absorption and metabolism.1 Vitamin D is found in supplements and a few foods (e.g., fish, liver, egg yolk, fortified products). The majority of vitamin D is produced in the skin when exposed to UV radiation from sunlight. But some have begun advocating consumption of levels of vitamin D above the RDA, and some advocate very high levels, ranging from 1,000 to 5,000 IU or more daily.2 Vitamin D is a secosteroid, with a close resemblance in structure to immunosuppressive steroids. Levels of the various vitamin D metabolites are the result of complex feedback mechanisms involving multiple enzymes and receptors, indicating that it is regulated more like a steroid than a nutrient.1

Short-term symptom reduction has sometimes been observed through increases in sun exposure 3,4 or vitamin D supplementation.5 However, this appears to be due to the anti-inflammatory effect arising from immune suppression, analogous to the effect of a steroid, such as prednisone. If one were to assume that the inflammation is purely pathological, this might be considered beneficial, but evidence that has been accumulating over many decades indicates that inflammation in most chronic diseases is occurring in response to undetected chronic bacterial infection (see below). Since immune suppression can promote the increase of pathogens, the effect of vitamin D supplementation is not likely to be harmless in this situation, but appears to have long-term effects associated with increased levels of bacterial pathogens. The role of this microbiota in producing the inflammation and oxidative stress observed in so many diseases will be discussed near the end of this article.6-8

Vitamin D from food or sun is first converted to 25-D (25-hydroxyvitamin-D) and then converted in a second step to the active 1,25D form (1,25-dihydroxyvitamin-D) that is able to activate the vitamin D receptor (VDR). The type of vitamin D usually measured in the blood is the precursor form, 25-D, rather than 1,25-D, the form that activates the receptor. Activation of the vitamin D receptor is extremely important, as it has numerous effects, including effects on the immune system1 and cancer.9,10 However, recent research indicates that increasing vitamin D via supplementation or sun exposure is not the way to achieve more VDR activation in chronic disease, due to blockage of the VDR by bacterial products.6 This insight has been put to use in a new model of chronic disease and a new protocol.6,8,11-14

A New Perspective on Vitamin D and a New Treatment Approach

Trevor Marshall, PhD, (Murdoch University, Australia) has developed a model of chronic autoimmune and inflammatory diseases in which intraphagocytic bacteria cause disease by producing a substance that binds to and blocks the VDR.1 One such substance has been already identified providing proof of principle.1

  • The VDR is important for adequate innate immune function, including the production of numerous antimicrobial peptides.15

These include

  1. cathelicidin and
  2. beta-defensin,

two of the body’s own arsenal of internally produced antibiotics.

Thus, VDR blockage would seem to be an excellent bacterial strategy, as it would lead to poor innate immune system function and further growth of bacteria and other pathogens. A functioning VDR also appears to be important in controlling cell growth and metastasis, so as to help prevent and control cancerous growths.9,10

A protocol based on this model of disease has been achieving a high rate of improvement/remissions in a wide array of conditions.6,11-14,16-18 It involves the use of

  • a VDR agonist, olmesartan, which is able to activate the VDR effectively and safely.

In addition, low dosages of combinations of select pulsed antibiotics are used to eliminate the bacteria, which also helps restore VDR functioning. The protocol also involves avoidance of vitamin D supplementation. When faced with VDR dysfunction, the evidence indicates that

  • attempting to increase 25-D only adds to the dysregulation of the vitamin D metabolites without being able to adequately overcome the bacteria-induced VDR blockage.6,8

Too much vitamin D can be harmful in two ways, according to Marshall’s work.1,6

  1. In silico data from highly sophisticated molecular modeling shows that high vitamin D levels can block the VDR and thus block innate immune function.18 In addition,
  2. high levels of various vitamin D metabolites can affect thyroid-alpha-1, glucorticoid, and androgen receptors and disrupt hormonal control and further affect innate immune function.1

Thus, any short-term symptom reduction from high levels of vitamin D that may occur is probably occurring at the cost of long-term pathogen increase. This has been supported by observations of patient’s responses over time. In the short-term, even for ten years or more in some cases, the person may feel better with high vitamin D intake. But in the long-term, the chronic infection progresses, because the high 25-D is only adding to the bacterial blockage of the VDR and the suppression of bacterial killing.18

Symptoms increase when the immune system is better able to kill the pathogens, due to the high levels of inflammatory cytokine levels that occur. This is called the immunopathological reaction or Jarisch-Herxheimer reaction.6,11 The symptoms range from pain and fatigue to cognitive impairment and depression, but include numerous other symptoms characteristic of the underlying inflammatory condition.6,11 By suppressing the immune response, vitamin D supplementation may suppress these symptoms in the short-term and may even result in a sort of dependence on vitamin D supplementation or sun exposure to keep the symptoms at bay.

The long-term efficacy of the protocol (sometimes called the Marshall Protocol or MP) in activating the VDR is also supported by improved or stabilized bone density, which is typical in patients on the protocol, if the RDA of calcium is consumed. The protocol replaces vitamin D supplementation with use of the VDR agonist olmesartan (120 to 160 mg in divided doses) and reduces the level of bacteria blocking the VDR with antibiotics and, in this way, is apparently effective in activating the VDR.6,12

Marshall proposes that vitamin D receptor blockage results in the low levels of 25-D that have been observed in numerous diseases. The precursor, 25-D form is the form that is most frequently measured. The VDR blockage typically leads to dysregulation of metabolite levels, and one effect is down-regulation of the conversion of vitamin D to 25-D.1 Thus, according to this perspective, low 25-D levels are the result, not a cause, of the disease process. It follows that a low serum 25-D is not indicative of a true vitamin D deficiency in this situation. Both laboratory19 and clinical findings20 have supported the existence of an apparently similar type of down-regulation of conversion to 25-D.

At the same time that low 25-D is observed, high 1,25-D levels are also usually observed. In fact, elevated 1,25-D has been shown to be a good indicator of inflammatory and autoimmune disease.13,16 When interpreting the results, however, it should be remembered that samples must be frozen until analyzed for accurate 1,25-D results. And occasionally, in cases of quite advanced disease or elderly patients, 1,25-D will be low as well, yet still be consistent with VDR blockage and inflammatory disease.21

Marshall’s protocol was first used to treat sarcoidosis. It is well established that a dysregulation of vitamin D levels, often with very high 1,25-D and low 25-D, occurs in this condition.22 Marshall’s and other’s work has confirmed that this dysregulation also occurs in a wide range of other diseases.12,13,23,24 This pattern of high 1,25-D and low 25-D also exists in VDR knockout mice.25 These mice are genetically engineered to lack a VDR, a situation analogous to a bacteria-blocked VDR.

The very complex relationships among genes, metabolites, enzymes, and receptors that Marshall recently summarized1,6 show that vitamin D is not a mere nutrient. In fact, the active form is a secosteroid transcriptional factor. It is part of a highly regulated and complex system influencing many aspects of metabolism and immune function. There are several feedback and feedforward pathways that influence the levels of various vitamin D forms that Marshall reviewed in depth.1

Marshall was recently invited to co-chair a session on vitamin D at the 6th Annual International Autoimmunity Conference, and he gave one of the keynote presentations of the session.6 Several other presentations were given that support the protocol and model. For example, Perez presented data on treatment response in 20 autoimmune conditions that support Marshall’s model.11 The autoimmune diseases successfully treated in this open-label trial include rheumatoid arthritis, systemic lupus erythematosis, diabetes type 1 and 2, psoriasis, Hashimoto’s thyroiditis, Sjogren’s syndrome, scleroderma, uveitis, myasthenia gravis, and ankylosing spondylitis. Chronic fatigue syndrome and fibromyalgia were shown to respond to the protocol in another presentation.17 And another study indicated that dysregulation of nuclear receptors in the endometrium by vitamin D, along with chronic bacterial infection, can help explain the higher prevalence of some autoimmune diseases in women.26

Epidemiological and Short-Term Clinical and Experimental Data
The in silico and clinical data discussed above provide strong evidence for Marshall’s model, and some might argue it is more reliable than epidemiological and short-term evidence. It is widely recognized that there are many limitations inherent in epidemiological and short-term experimental data due to difficulties in obtaining relevant and accurate results. Confounding factors and the inability to assess the effects of long-term immune suppression from high levels of vitamin D make the results less reliable.13,21 Experiments using animal models have the problem of genetic differences and different disease causation methods.1,13Studies of supplementation are often not randomized and thus are subject to unknown confounding factors that may affect the choice to take vitamin D supplements.13 Furthermore, sun exposure is hard to quantify and is often left out of the analyses. Any of the above can lead to invalid conclusions.

Despite this, a number of recent studies that may be relevant will be discussed here to show that there is much independent support for Marshall’s model among these types of studies. In addition, some lesser-known aspects of some of the studies used to support a high vitamin D intake will be reviewed, which cast doubt on some of their conclusions.

Cancer and All-Cause Mortality
In the case of cancer prevention, a recent randomized controlled trial of calcium and vitamin D by Lappe et al.27 is used to support vitamin D supplementation. However, it has a number of serious limitations. One problem is the assumption that removing the data from the first year is justified. If one looks at Figure 1, in the article by Lappe et al,27 in which the data from the first year was included, there is very little difference between calcium and vitamin D vs. calcium alone throughout the study period. No group of patients was given vitamin D alone. Also, there is not yet long-term data on incidence, since the study lasted only four years. Any reduced incidence may reflect delay in diagnosis. In addition, long-term survival may not ultimately improve. In fact, patients taking vitamin D might even die sooner (see below). In addition to the above critique, a number of published comments have also taken issue with this trial, pointing to other problems and limitations.9,28

Another recent study29 reported finding barely significant lower cancer rates in premenopausal women (95% confidence interval, 0.42-1.0) who consumed more vitamin D. However, they found a marginally significant higher rate of moderately differentiated tumors in postmenopausal women who had higher vitamin D intake. And since postmenopausal women make up a much higher proportion of breast cancer cases, this is particularly concerning. This is just one example of the rather inconclusive, mixed data on vitamin D supplementation that becomes apparent when the vitamin D studies are looked at as a whole (see Discussion section in ref. 29). Even the benefit for premenopausal women is questionable. Bertone-Johnson et al.30 pointed out a quite plausible rationale for the existence of a bias toward low estrogen in those who choose to take vitamin D supplements.

A number of limitations found in the other studies are used as a basis for supporting vitamin D supplementation. For instance, the data is rarely long-term enough and rarely covers all the effects possible. Although there may be an appearance of benefit in the short-term or for subsets of the populations studied, a large, long-term prospective study showed no effect of 25-D on the overall cancer mortality rate in the long-term.31 Freedman et al.31 even showed a suggestion of a negative effect of higher vitamin D levels. There was a non-significant increase in overall mortality in the two groups with 25-D at higher levels (80 to <100 nmol/L: Risk Ratio = 1.21, 95% CI =0.83 to 1.78; =100 nmol/L: Risk Ratio = 1.35; 95% CI = 0.78 to 2.31, where 100 nmol/L corresponds to about 40 ng/ml).

This is in accord with a study in prostate cancer32 (also see discussion in ref. 21) and one in pancreatic cancer33 that found higher cancer rates when 25-D was high. Cancer rates increased among patients with a 25-D level above approximately 32 ng/ml. Evidence regarding solar radiation and geographical/latitudinal analyses are also used as evidence, yet solar radiation has many other effects besides raising 25-D.34,35 Many other relevant factors, such as pathogen distributions, climate effects on pathogen spread36,37 and host susceptibility,38 diet, and pollution levels also vary with geographical location.

It was recently pointed out in the Bulletin of the World Health Organization that high 25-D has been found to be associated with greater cancer risk in some studies.39 Studies mentioned, included one that found that there was a higher rate of many internal cancers in patients who have a type of skin cancer that is considered to be the best indicator of long-term sun exposure.40 Another study discussed failed to find a geographical pattern that would support a protective effect of increased 25-D.41 On the whole, in these epidemiological studies, the data is mixed and inconsistent, which is to be expected when there are so many unknown confounding factors affecting 25-D levels and disease incidence that may bias the results.13 In addition, a recent large prospective study presented evidence suggesting that circulating 25-D concentrations may be associated with increased risk of aggressive prostate cancer.42 For all types of prostate cancer, the data failed to support the hypothesis that higher vitamin D decreases prostate cancer risk.42

Studies looking at overall mortality benefits of vitamin D are sometimes misleading at first glance. In the large meta-analysis done recently on the effect of vitamin D and calcium on mortality rates,43 the abstract attributes reduced mortality to vitamin D, yet the only statistically significant results were for calcium together with vitamin D. Another serious problem is that most of the studies analyzed in the meta-analysis were only a few years in duration, so long-term effects on mortality and morbidity could not be accurately assessed.

Bone Density, Parathyroid Hormone
Another area that should be re-evaluated is the negative association between parathyroid hormone and 25-D levels. This association is often used to assert that high levels of 25-D (e.g., 40 –50 ng/ml or more) are optimal. Aloia et al.44 has pointed out that the studies that conclude these high levels of vitamin D are needed fail to require adequate calcium intake, and that is why such high levels are suggested. It should also be considered whether both low 25-D and high PTH are due to the disease process rather than the low 25-D causing the elevated PTH. In addition, only a small percentage of patients with low 25-D have elevated PTH. The low 25-D may be indicating a systemic chronic bacterial infection, and the abnormally high PTH levels in a small percentage of patients may merely be pointing to those cases in which bacteria have infected the parathyroid gland to a greater degree.

In a study comparing vitamin D supplementation with calcium supplementation,45“the effect of calcium on bone loss was blunted in subjects with the highest levels of serum 25OH vitamin D [25-D].” This last finding is supportive of Marshall’s in silico work indicating that high 25-D actually blocks the VDR.6,18 The largest meta-analysis so far clearly showed benefit from calcium supplementation; however, benefit for vitamin D was much less clear.46 No significant benefit for fracture risk was found when comparing vitamin D and calcium to calcium alone, though some differences were found between vitamin D levels.

Another factor that needs to be considered is whether immune suppression is the cause of bone density improvement when high vitamin D levels are used. Immunosuppressive drugs that lower TNF-alpha using antibodies can improve bone density by reducing inflammation.47 High levels of vitamin D supplementation can also lower TNF-alpha48 and suppress the immune response. Thus, it is possible that an increase in bone density from vitamin D supplementation could be the result of immune suppression via TNF reduction, rather than correction of a vitamin D deficiency. TNF-lowering drugs such as infliximab (Remicade) increase risk of cancer and tuberculosis. Thus, the desirability of improving bone density through immune suppression is questionable. This immunosuppressive effect of vitamin D may even explain what seems to be a beneficial effect on falls and muscle strength of elevating vitamin D through supplementation.21 This may be only a symptom reduction in the short-term and may be harmful in the long-term due to the immune suppression.

Autoimmune Disease
In the area of autoimmune disease, the data is equally mixed, and sometimes the larger, more recent studies fail to show any effect of vitamin D levels. For example, a recent large study failed to find an association between serum 25-D levels and the incidence of systemic lupus erythematosis and rheumatoid arthritis.49 Research has found that the average age at which patients acquired rheumatoid arthritis is 12 years earlier in Mexico than in Canada and pointed to the possible role of infectious agents in causing the disease.50 And clearly this study does not support the idea that sun exposure is beneficial for rheumatoid arthritis, since Mexico gets far more sun than Canada.

Although some studies in type 2 diabetes have indicated vitamin D supplementation may be preventive,51 these studies were not randomized and thus are subject to many known and unknown confounding factors affecting a parent’s decision to give a child supplemental vitamin D.13 And even if it were clearly established that vitamin D supplementation reduced the incidence of diabetes in infants and small children, that would not mean that it would help in established disease or older patients, nor would it necessarily mean it is the optimal way to achieve diabetes prevention and long-term health. The positive response of both type 1 and type 2 diabetes patients to the Marshall Protocol11 indicates research on the role of bacteria in diabetes should be a priority.

Influenza and Colds
It has been proposed that vitamin D levels’ decline in winter best accounts for the seasonality of colds and influenza52 and that this potentially supports the need for increased supplementation.52,53 However, new evidence indicates that changes in the viral coat properties can account for the seasonal outbreaks at higher latitudes.36,37 Effects on the airways in dry, cold climates also appear to increase susceptibility to viral and bacterial infections in winter and could contribute to higher winter prevalence of respiratory infections in cold climates.38

Another important point is that the patients being followed on the Marshall Protocol include a number of individuals who report that during the worst period of their chronic illness, they had few or no colds or flu-like illnesses, sometimes for many years at a time. And sometimes this low rate of colds was apparent even years before their illness. This has also been reported in Parkinson’s disease, with the decrease in viral respiratory infections also occurring several years before the disease was diagnosed.54 Thus, even if future research were to establish that vitamin D supplementation reduced colds and influenza, this is by no means an adequate argument for its use. The above observations in chronically ill patients indicate that observing a reduction in respiratory viral infections is not always a sign of good overall health.

Indications of Long-Term Negative Effects of Vitamin D Supplementation
Brannon et al.55 pointed out in a recent report from a roundtable discussion of vitamin D data needs that many studies so far have not yet adequately investigated potential negative consequences such as soft tissue calcification. Vitamin D has been implicated in arterial calcification in the past56 as well as other negative effects.13 The report by the roundtable of vitamin D experts expressed concern that many studies may be shortsighted with regard to adverse outcomes.55

A disturbing new study showed a highly significant correlation (p=0.007) between increased vitamin D intake from food and supplements and the volume of brain lesions shown by MRI in elderly adults.57 In the multivariable regression model, vitamin D intake retained its significant correlation with brain lesion volume even after the effects of calcium were statistically removed. However, calcium did not retain a significant independent correlation with the lesions when the study controlled for vitamin D. Thus, the analysis points to vitamin D supplementation as the key factor in higher lesion volume in this study. These types of brain lesions have been linked to adverse effects in many studies, e.g., stroke,58 psychiatric disorders,59,60 brain atrophy,61 and earlier death.62 Interestingly, the levels of vitamin D intake were not particularly high by some standards, with the highest intake estimated at 1015 mg daily (mean of 341 mg), about half coming from supplements and the rest from food.

The correlation between vitamin D intake and brain lesions seems to lend further support to Marshall’s work. In another study, the finding that over a three-year period, a small percentage of patients were found to have a slight regression of their brain lesions,63 leaves room for hope that the lesions are potentially reversible. Reversibility would be in accord with the improvement of depression and cognitive deficits and other neurological symptoms reported in patients on the Marshall Protocol.6,64

Elusive Bacterial Pathogens Are Detected with Improved Methods
Over many decades, researchers have reported evidence that hard-to-detect bacterial infections are the cause of many diseases,65,66 including autoimmune disease,65-68 cardiovascular disease,69-71 and even cancer.72-77 Some have noted the recent trend toward finding more infectious causes of disease and suggested this is likely to increase in the coming years.6,71,77-80

Recently, Barry Marshall received the Nobel Prize for discovering that the bacteria Helicobacter pylori causes ulcers. And it is now known that H. pylori is a causal factor in stomach cancer.77

New techniques using 16s ribosomal RNA shotgun sequencing,81,82 as well as more advanced culturing and observational techniques65,66,80,83-85 are suggesting that, up until now, most microbiologists have failed to detect a large percentage of potential disease-causing agents. “Persister” cells have been identified that escape antibiotic treatment.86 Cell wall deficient organisms have long been studied,65-66and just recently, advances have been made in understanding their structure and in culturing techniques.80 Research is also indicating that a bacterial biofilm-like microbiota of multiple species even exists within human cells.6,8

Bacteria that grow on a surface in a multi-species community, protected by both a biofilm and the combined effect of their individual resistance strategies, have been a growing area of research.79 Bacterial biofilms have been found to cause the non-healing ulcers in diabetics and may be successfully treated using novel approaches, thus reducing the need for limb amputation.88

Other examples of studies detecting unexpected bacterial pathogens include work linking pathogens in amniotic fluid to pre-term birth89 and research showing numerous previously undetected species in the biofilms that coat prosthetic hip joints.82 Many species of bacteria have been in wounds that were previously undetected using older techniques.81 Macfarlane et al.90 used a combination of more advanced techniques to study bacteria in biofilm communities in patients with Barrett’s esophagus, a pre-cancerous condition. Their methods revealed significant differences between patients and controls in the types and numbers of bacterial species, differences that were previously undetected using older techniques.

Increasingly, inflammation is observed in chronic diseases ranging from depression to cardiovascular disease and cancer.87 The above trends, when combined with observations of bacteria in numerous diseases6,13,65,66,71,91 and the success of the anti-bacterial protocol developed by Marshall6,8,11,13 suggest an extensive role for previously unidentified chronic bacterial infections.

Research is also supporting the ineffectiveness of most standard antibiotic protocols against these bacteria70 and suggesting why other approaches may work better. For instance, some antibiotics target cell walls, and this actually promotes the production of cell wall deficient forms of bacteria that resist many antibiotics.80 Furthermore, many antibiotics are known to inhibit phagocytosis and other aspects of the immune response when taken at high, constant dosages.92

The ability of bacteriostatic antibiotics such as clindamycin to be effective at low doses has been documented.93,94 The survival of “persister” cells mean that pulsed antibiotics are likely to be more effective.86 And fascinating investigations of biofilm communities have revealed many ways in which bacteria can resist antibiotics when used in traditional ways.95 The existence of communities of many bacterial species means that combinations of antibiotics are probably needed to be effective against all the species present. Thus, there is increasing support for the use of pulsed, low dosages of combinations of bacteriostatic antibiotics as used in the anti-bacterial protocol discussed here.

What is particularly encouraging is that the effectiveness of Marshall’s protocol in many systemic chronic disease indicates that these elusive pathogens do respond to select currently available bacteriostatic antibiotics when innate immune function is restored through restoring vitamin D receptor function.6,11 Not only do the bacterial infections appear to resolve, the evidence so far suggests that the improved immune response leads to reduced viral, fungal, and protozoal infections as well.

Conclusions
In silico and clinical data indicate that it is likely that associations between low vitamin D levels and chronic diseases are not evidence of deficiency, but result from a bacteria-induced blockage of the vitamin D receptor, leading to down-regulation of 25-D levels.1,6 According to this model of chronic disease, the short-term benefits sometimes perceived with high vitamin D levels are not due to correction of a vitamin D deficiency but due to suppression of bacterial killing and the immunopathological reaction that accompanies it. Data on reversal of a range of inflammatory and autoimmune diseases through an anti-bacterial protocol that includes vitamin D avoidance and a VDR agonist support this view.6,11

As discussed in detail above, it appears that increasing vitamin D supplementation is not the answer to these chronic diseases and is likely to be counter-productive. Other researchers have also raised concerns regarding vitamin D supplementation’s potential adverse effects. Potential dangers include increased aortic calcification55,56 and brain lesions shown by MRI57 (also see above). In addition, some studies have even found evidence of increased danger from cancer in association with higher levels of vitamin D.32,33,39,40,42

Many have been attracted to the area of vitamin D research, recognizing interesting patterns and responses to supplementation that at first seemed to indicate widespread deficiency and, at the very least, indicate that vitamin D plays a powerful role in physiological processes. Great strides have been made in the last 30 years by scientists with a range of perspectives, and this has led to great excitement and a laudable commitment to use that knowledge to help patients.

However, new genomic and molecular research and the positive response to a new anti-bacterial protocol that involves the avoidance of vitamin D indicate the need for a reappraisal of the data gathered so far. It appears that attempting to raise 25-D through vitamin D supplementation or sun exposure is not the right approach to many, if not most, common chronic diseases. Instead, as discussed above, the evidence supports the effectiveness of a new protocol in restoring vitamin D receptor function, which appears to be a crucial factor in recovery.

One of the most commendable attributes of a truly objective scientist is the willingness to be open to changing long-held positions in the light of new evidence. It will be interesting to see how many have this all-too-rare quality, as research and discussion of vitamin D and the VDR continues. It is to be hoped that the tremendous healing potential likely to be available from eliminating the pathogens that cause chronic disease will inspire an especially high level of open-minded discussion and cooperation.

Caution: The immunopathological reactions from killing the high levels of bacteria that have accumulated in chronically ill patients can be severe and even life-threatening, and thus the Marshall Protocol must be done very carefully and slowly, according to the guidelines.7,96 For the sake of safety, antibiotics must be started at quite low dosages, starting with only one antibiotic. Health care providers are responsible for the use of this information. Neither Autoimmunity Research, Inc., nor the author assume responsibility for the use or misuse of this protocol.

Note: Neither the author, Prof. Marshall, nor the non-profit Autoimmunity Research, Inc. have any financial connection with any product or lab mentioned with regard to the Marshall Protocol. The information needed to implement the Marshall Protocol is available free of charge fromwww.AutoimmunityResearch.org.

Vitamin D3 and Its Nuclear Receptor Increase the Expression and Activity of the Human Proton-Coupled Folate Transporter

Folates are essential for nucleic acid synthesis and are particularly required in rapidly proliferating tissues, such as intestinal epithelium and hemopoietic cells. Availability of dietary folates is determined by their absorption across the intestinal epithelium, mediated by the proton-coupled folate transporter (PCFT) at the apical enterocyte membranes. Whereas transport properties of PCFT are well characterized, regulation of PCFT gene expression remains less elucidated. We have studied the mechanisms that regulate PCFT promoter activity and expression in intestine-derived cells. PCFT mRNA levels are increased in Caco-2 cells treated with 1,25-dihydroxyvitamin D3 (vitamin D3) in a dose-dependent fashion, and the duodenal rat Pcft mRNA expression is induced by vitamin D3 ex vivo. The PCFTpromoter region is transactivated by the vitamin D receptor (VDR) and its heterodimeric partner retinoid X receptor-α (RXRα) in the presence of vitamin D3. In silico analyses predicted a VDR response element (VDRE) in the PCFT promoter region −1694/−1680. DNA binding assays showed direct and specific binding of the VDR:RXRα heterodimer to the PCFT(−1694/−1680), and chromatin immunoprecipitations verified that this interaction occurs within living cells. Mutational promoter analyses confirmed that the PCFT(−1694/−1680) motif mediates a transcriptional response to vitamin D3. In functional support of this regulatory mechanism, treatment with vitamin D3 significantly increased the uptake of [3H]folic acid into Caco-2 cells at pH 5.5. In conclusion, vitamin D3 and VDR increase intestinal PCFT expression, resulting in enhanced cellular folate uptake. Pharmacological treatment of patients with vitamin D3 may have the added therapeutic benefit of enhancing the intestinal absorption of folates.

Folates are water-soluble B vitamins that act as one-carbon donors required for purine biosynthesis and for cellular methylation reactions. They are essential for de novo synthesis of nucleic acids, and thus for production and maintenance of new cells, particularly in rapidly dividing tissues such as bone marrow and intestinal epithelium (Kamen, 1997). Adequate dietary folate availability is especially important during periods of rapid cell division, such as during pregnancy and infancy. Folate deficiency has been associated with reduced erythropoiesis, which can lead to megaloblastic anemia in both children and adults (Ifergan and Assaraf, 2008). Deficiency of folate availability in pregnant women has been linked to neural tube defects, such as spina bifida, in children (Pitkin, 2007). This has prompted the application of folate supplementation schemes either as pills or via fortification of grain products with folates (Eichholzer et al., 2006). Folates have also been proposed to act as protective agents against colorectal neoplasia, although contradictory results have also been reported (Sanderson et al., 2007).

The availability of diet-derived folates is primarily determined by the rate of their uptake into the epithelial cells of the intestine, mediated by the proton-coupled folate transporter (PCFT, gene symbol SLC46A1), localized at the apical brush-border membranes of enterocytes (Subramanian et al., 2008a). PCFT is an electrogenic transporter that functions optimally at a low pH (Qiu et al., 2006;Umapathy et al., 2007). Despite being abundantly expressed in enterocytes, the second folate transporter, termed reduced folate carrier (RFC, gene symbolSLC19A1), has recently been shown not to play an important role in intestinal folate absorption (Zhao et al., 2004; Wang et al., 2005).

The human PCFT gene resides on chromosome 17, contains 5 exons, and is expressed as two prominent mRNA isoforms of 2.1 and 2.7 kilobase pairs (Qiu et al., 2006). Mutations in the PCFT gene have been associated with hereditary folate malabsorption, a rare autosomal recessive disorder (Qiu et al., 2006; Zhao et al., 2007). The PCFT protein is predicted to have a structure harboring 12 transmembrane domains (Qiu et al., 2007; Subramanian et al., 2008a). Although the transport function of PCFT has been studied extensively, relatively little is known about the regulation of PCFT gene expression. PCFT promoter activity has been shown possibly to be epigenetically regulated by its methylation status in human tumor cell lines (Gonen et al., 2008). Furthermore, both the PCFT mRNA expression levels and PCFT promoter activity positively correlate with the level of differentiation of colon-derived Caco-2 cells (Subramanian et al., 2008b).

In addition to its well known roles in regulating calcium homeostasis and bone mineralization, 1,25-dihydroxyvitamin D3 (vitamin D3), the biologically active metabolite of vitamin D, executes many other important functions, particularly in the intestine. For example, vitamin D3 promotes the integrity of mucosal tight junctions (Kong et al., 2008). Many effects of vitamin D3 are mediated via its action as a ligand for the vitamin D receptor (VDR; gene symbol NR1I1), a member of the nuclear receptor family of transcription factors (Dusso et al., 2005). VDR typically regulates gene expression by directly interacting with so-called direct repeat-3 (DR-3; a direct repeat of AGGTCA-like hexamers separated by three nucleotides) motifs within the target promoters, as a heterodimer with another nuclear receptor, retinoid X receptor-α (RXRα; gene symbol NR2B1) (Haussler et al., 1997). Genetic variants of VDR have been associated with inflammatory bowel disease (Simmons et al., 2000; Naderi et al., 2008). Similarly to folates, both VDR and its ligand vitamin D3 have been proposed to be protective against intestinal neoplasia (Ali and Vaidya, 2007). Dietary folate intake has been suggested to regulate gene expression of the components of the vitamin D system, possibly via epigenetic control through the function of folates as methyl donors (Cross et al., 2006). Several intestinally expressed transporter genes, such as those encoding the multidrug resistance protein 1 and multidrug resistance-associated protein 2, have recently been shown to be induced by vitamin D3 (Fan et al., 2009). We investigated whether vitamin D3 regulates the expression of the PCFT gene, encoding a transporter crucial for intestinal folate absorption. The human well polarized enterocyte-derived Caco-2 cells exhibit many of the characteristics associated with mature enterocytes and were used here to investigate the effects of vitamin D3 on PCFT gene expression and folate transport activity.

……..

Vitamin D3 regulates the expression of its target genes primarily by acting as an agonistic ligand for its DNA-binding nuclear receptor VDR, although nongenomic actions by vitamin D3 have also been described previously (Christakos et al., 2003;Dusso et al., 2005). VDR, an important regulator of differentiation and proliferation of enterocytes, typically activates gene expression by heterodimerizing with its nuclear receptor partner RXRα. VDR:RXRα heterodimers then directly bind to DR-3-like elements on the target genes. It should be noted that other modes of VDR-mediated regulation, either via direct interaction with other DNA-binding factors or through nongenomic actions, have also been reported (Dusso et al., 2005).

Here we demonstrate that VDR is a ligand-dependent transactivator of the humanPCFT gene, coding for a vital transporter for intestinal absorption of dietary folates. PCFT mRNA is also abundantly expressed in the liver (Qiu et al., 2006). However, VDR is expressed at very low levels in primary human hepatocytes or hepatocyte-derived cell lines (Gascon-Barre et al., 2003; data not shown), suggesting that VDR-mediated regulation of the PCFT gene may not occur in hepatocytes.

Endogenous PCFT mRNA levels were induced by vitamin D3 in a dose-dependent manner in Caco-2 cells (Fig. 1A). This increase was not further enhanced by cotreatment of cells with the RXRα ligand 9-cis retinoic acid (data not shown), consistent with a previous report that VDR:RXRα heterodimers, at least in some promoter contexts, may not respond to RXRα ligands (Forman et al., 1995). Alternatively, saturating levels of RXRα ligands may already be endogenously present in cells in these experimental conditions. In transient transfection assays, the PCFT promoter fragment −2231/+96 exhibited significant response to exogenous expression of VDR alone in the presence of its ligand (Fig. 2), most probably supported by endogenously expressed RXRα in Caco-2 cells.

Supporting the importance of the VDR:RXRα heterodimer formation for PCFTpromoter regulation, the luciferase values were further significantly elevated upon exogenous expression of RXRα. Exogenous expression of VDR in the absence of vitamin D3 did not notably influence the activity of the PCFT(−2231/+96) promoter, indicating ligand-dependence of VDR action. In deletional transfection analysis, the strongest induction in response to VDR and RXRα in the presence of their ligands was achieved with the PCFT(−2231/+96) promoter fragment (Fig. 3A). Induction of the shortest deletion variant tested [PCFT(−843/+96)luc] was approximately 50% of that achieved for the PCFT(−2231/+96), indicating that this more proximal region is likely to contain further DNA elements mediating a response to vitamin D3. However, in our current study, we focused on the distal region between the nucleotides −2231 and −1674 upstream of the transcriptional start site of the human PCFT gene, which confers maximal response to vitamin D3. In our computational analysis, we identified a putative VDRE within the PCFTpromoter region between nucleotides −1694 and −1680. We have not so far been successful in identifying further binding sites for the VDR:RXRα heterodimer in the more proximal region of the PCFT promoter. It may be that, in addition to direct DNA-binding to the PCFT(−1694/−1680) element identified here, VDR may also affect PCFT promoter activity indirectly, via interactions with other DNA-binding factors. For example, it has been proposed that the p27Kip1 gene is regulated by VDR via response elements for unrelated DNA-binding transcription factors Sp1 and NF-Y (Huang et al., 2004).

Both endogenously expressed and recombinant VDR and RXRα bound to thePCFT(−1694/−1680) element specifically and as obligate heterodimers (Fig. 4). The interaction between VDR and this region of the PCFT promoter within living cells treated with VDR and RXRα ligands was confirmed by chromatin immunoprecipitation tests (Fig. 5). Heterologous promoter assays proved that thePCFT(−1694/−1680) element can function as an independent VDR response element. The significant decrease in VDR:RXRα-mediated induction upon mutagenesis of the PCFT(−1694/−1680) element confirmed that it is an important functional mediator of the effect (Fig. 6, A and B).

Although we observed vitamin D3-mediated increase of rat Pcft mRNA expression ex vivo (Fig. 1C), the rat Pcft promoter (chromosome 10; GenBank accession number NW_047336) exhibits no significant overall homology with the humanPCFT promoter over the proximal 3000-bp regions. This suggests that despite the divergence of the promoter sequences between human and rodent PCFT/Pcftgenes, the functional response to vitamin D3 is conserved.

The activation of PCFT gene transcription by VDR also translates into an increase in PCFT protein function. Vitamin D3 treatment of Caco-2 cells led to significantly increased uptake of folate across the apical membrane, in a dose-dependent manner (Fig. 7). In keeping with the fact that PCFT strongly prefers an acidic milieu for its transport function (Qiu et al., 2006; Nakai et al., 2007; Unal et al., 2009), we only observed vitamin D3-stimulated transport activity at pH5.5, but not at neutral pH. These data strongly suggest that vitamin D3-mediated transcriptional activation of PCFT gene expression leads to an increase of PCFT transport function. Consistent with our model, mRNA expression of the other known folate carrier expressed in Caco-2 cells, RFC, which functions efficiently at neutral pH (Ganapathy et al., 2004; Wang et al., 2004), was not affected by vitamin D3treatment (Fig. 1B). It has been reported that vitamin D3-induced gene expression increases as Caco-2 cells differentiate (Cui et al., 2009). Thus, our current findings on VDR-mediated regulation of PCFT expression provide a possible molecular mechanism for a prior observation that folate uptake into Caco-2 cells is enhanced upon confluence-associated differentiation (Subramanian et al., 2008b).

Our results suggest that intestinal folate absorption may be enhanced by an increase in dietary vitamin D3 intake. Food products are often supplemented with folates, because of their proposed beneficial health effects. Based on our current study, supplementation of vitamin D3 may enhance the intestinal absorption of folates. PCFT also transports the antifolate drug methotrexate (MTX) (Inoue et al., 2008; Yuasa et al., 2009) widely used in the treatment of autoimmune diseases and cancer. MTX interferes with folate metabolism by competitively inhibiting the enzyme dihydrofolate reductase. Our results may further suggest a potential mechanism to increase intestinal absorption of MTX via simultaneous treatment with vitamin D3, thereby affecting the bioavailability of MTX. Patients suffering from inflammatory bowel disease are frequently on long-term treatment with calcium and vitamin D3 as a prophylaxis against osteopenia and osteoporosis (Lichtenstein et al., 2006). This patient group is frequently treated with folates (in the case of folate deficiency) or MTX (as a second-line immunosuppressant) (Rizzello et al., 2002). MTX therapy per se requires prophylactic administration of folates, and these patients often receive additional calcium/vitamin D3. Our current results may warrant a closer investigation into potential drug-drug interactions between pharmacologically administered vitamin D3, MTX, and folates. Taking into account the previous report that folates regulate the expression of genes involved in vitamin D3 metabolism, it may be that folate and vitamin D3 homeostasis are closely interlinked through such mutual regulatory interactions.

 

Innate immune response and Th1 inflammation
http://mpkb.org/home/pathogenesis/innate_immunity

The innate immune response is the body’s first line of defense against and non-specific way for responding to bacterial pathogens.1 Located in the nucleus of a variety of cells, the Vitamin D nuclear receptor (VDR) plays a crucial, often under-appreciated, role in the innate immune response.

When functioning properly, the VDR transcribes between hundreds2 and thousands of genes3including those for the proteins known as the antimicrobial peptides. Antimicrobial peptides are “the body’s natural antibiotics,” crucial for both prevention and clearance of infection.4The VDR also expresses the TLR2 receptor, which is expressed on the surface of certain cells and recognizes foreign substances.

The body controls activity of the VDR through regulation of the vitamin D metabolites. 25-hydroxyvitamin D (25-D) antagonizes or inactivates the Receptor while 1,25-dihydroxyvitamin D (1,25-D) agonizes or activates the Receptor.

Greater than 36 types of tissue have been identified as having a Vitamin D Receptor.5

Another component of the innate immune response is the release of inflammatory cytokines. The result is what medicine calls inflammation, which generally leads to an increase in symptoms.

Before the Human Microbiome Project, scientists couldn’t link bacteria to inflammatory diseases. But with the advent of DNA sequencing technology, scientists have detected many of the bacteria capable of generating an inflammatory response. All diseases of unknown etiology are inflammatory diseases.

Nuclear receptors and ligands

Nuclear receptors are a class of proteins found within the interior of cells that are responsible for sensing the presence of hormones and certain other molecules. A unique property of nuclear receptors which differentiate them from other classes of receptors is their ability to directly interact with and control the expression of genomic DNA. Some of the molecules (or ligands) which bind the nuclear receptor activate (agonize) it and some inactivate (antagonize) it.

It is commonly accepted that most ligands, approximately 95% to 98%, inactivate the nuclear receptors. Since the nuclear receptors play a significant role in the immune response, this factor alone may explain why so many drugs and substances found in food and drink are immunosuppressive.

Because the expression of a large number of genes is regulated by nuclear receptors, ligands that activate these receptors can have profound effects on the organism. Many of these regulated genes are associated with various diseases which explains why the molecular targets of approximately 13% of FDA approved drugs are nuclear receptors.6

Different cell types have different nuclear receptors. One of the nuclear receptors seen in immune cells is the Vitamin D Receptor (VDR). The VDR has two endogenous or “native” ligands, which are also the two main forms of vitamin D in the human body: 25-hydroxyvitamin D (25-D) and 1,25-dihydroxyvitamin D (1,25-D). Non-native or exogenous ligands can also inactivate or activate a nuclear receptor, depending on its molecular structure.

Ligands compete to dock at nuclear receptors. When is a given kind of ligand such as 25-D as opposed to 1,25-D more likely to bind to the VDR? It depends. 1,25-D tends to be much less common than 25-D – by a factor of 1,000 or more – so it binds to the receptor much more infrequently. A greater concentration of a given molecule can displace competing molecules off the nuclear receptor. Affinity occurs in logarithmic fashion, which is to say that it operates on the basis of a sliding scale. In short, an increase in 1,25-D and a decrease in 25-D can tilt the odds in favor of 1,25-D, and vise versa.

Affinity as well as the question of whether a ligand inactivates or activates a nuclear receptor can all be validated using in silicomodeling. Although less precise, it is also possible to measure these properties in vitro.

Activated by 1,25-D and inactivated by 25-D, the Vitamin D nuclear receptor (VDR) transcribes a number of genes crucial to the function of the innate immune response.

Role of Vitamin D Receptor in innate immunity

Vitamin D/VDR have multiple critical functions in regulating the response to intestinal homeostasis, tight junctions, pathogen invasion, commensal bacterial colonization, antimicrobe peptide secretion, and mucosal defense…. The involvement of Vitamin D/VDR in anti-inflammation and anti-infection represents a newly identified and highly significant activity for VDR.

Jun Sun 7

When activated by 1,25-D, the Vitamin D Receptor (also called the calcitriol receptor) transcribes thousands of genes.8 It is commonly known that the VDR functions in regulating calcium metabolism.9 It is becoming increasingly clear, however, that the clinically accepted role of the Vitamin D metabolites, that of regulating calcium homeostasis, is just a small subset of the functions actually performed by these hormones. 

Transcription of antimicrobial peptides

One of the VDR’s key functions is the transcription of antimicrobial peptides.10 11 See below.  

Other antimicrobial activity of the VDR

Additionally, when the VDR is activated, TLR2 is expressed.12 TLR2 is a receptor, which is expressed on the surface of certain cells and recognizes native or foreign substances, and passes on appropriate signals to the cell and/or the nervous system.

When activated TLR2 allows the immune system to recognize gram-positive bacteria, including Staphylococcus aureus13 14Chlamydia pneumoniae15 and Mycoplasma pneumoniae.16 TLR2 also protects from intracellular infections such as Mycobacteria tuberculosis.17  

Antimicrobial peptides

The antimicrobial peptides (AMPs), of which there are hundreds, are families of proteins, which have been called “the body’s natural antibiotics,” crucial for both prevention and clearance of infection. AMPs are broad-spectrum, responding to pathogens in a non-specific manner.18

For example, consider cathelicidin, a protein transcribed the VDR, which not unlike a Swiss Army knife, has many different functions. Because it can be differentially spliced, the cathelicidin protein itself can respond to a range of very different microbial challenges. In humans, the cathelicidin antimicrobial peptide gene encodes an inactive precursor protein (hCAP18) that is processed to release a 37amino-acid peptide (LL-37) from the C-terminus. LL-37 is susceptible to proteolitic processing by a variety of enzymes, generating many different cathelicidin-derived peptides, each of which has specific targets. For example, LL-37 is generated in response toStaphylococcus aureus, yet LL-37 represents 20% of the cathelicidin-derived peptides, with the smaller peptides being much more abundant and able to target even more diverse microbial forms.19

AMPs have been documented to kill bacteria and disrupt their function through the following modes of action:

  • interfering with metabolism
  • targeting cytoplasmic components
  • disrupting membranes
  • act as chemokines and/or induce chemokine production, which directs traffic of bacteria

Also, AMPs aid in recovery from infection by:

  • promoting wound healing
  • inhibiting inflammation

In many cases, the exact mechanism by which antimicrobial peptides kill bacteria is unknown. In contrast to many conventional antibiotics including those used by the Marshall Protocol, AMPs appear to be bacteriocidal (a killer of bacteria) instead of bacteriostatic (an inhibitor of bacterial growth).

Two of the more significant families of AMPs are cathelicidin and the beta-defensins. Of these two families, cathelicidin is the most common.

The full extent by which microbes interfere with AMP expression is the subject of a rapidly growing body of research.20 21 22

Antimicrobial peptides target fungi and viruses

The antimicrobial peptides play a role in mitigating the virulence of the virome and other non-bacterial infectious agents. In addition to its antibacterial activity, alpha-defensin human neutrophil peptide-1 inhibits HIV and influenza virus entry into target cells.23 It diminishes HIV replication and can inactivate cytomegalovirus, herpes simplex virus, vesicular stomatitis virus and adenovirus.24 In addition to killing both gram positive and gram-negative bacteria, human beta-defensins HBD-1, HDB-2, and HBD-3 have also been shown to kill the opportunistic yeast species Candida albicans.25 Cathelicidin also possesses antiviral and antifungal activity.26 27

In other words, there is a reason why this group of proteins are named antimicrobial peptides rather than antibacterial peptides.

Unexpected antimicrobial peptides

There are now several examples of substances believed to cause disease, which have since been proven to be part of host defense.

  • amyloid beta (amyloid-β) – In a seminal 2010 study, a team of Harvard researchers showed that amyloid beta – the hallmark of Alzheimer’s disease – can act as an antimicrobial peptide, having antimicrobial activity against eight common microorganisms, including Streptococcus, Staphylococcus aureus, and Listeria.28 This led study author Rudolph E. Tanzi, PhD to conclude that amyloid beta is “the brain’s protector.” However, a 2010 study suggests that toxic levels of amyloid beta “dramatically suppresses VDR expression.” This suggests that overexpression of amyloid beta serves the interests of at least some microbes.29Read more.
  • certain human prion proteins   

Evolutionarily conserved

The TLR2/1 and cathelicidin-vitamin D pathway has long played a “powerful force” in protecting the body against infection. This is evidenced by the fact that the Alu short interspersed element (SINE), which transcribes the vitamin D receptor binding element (VDRE), has been evolutionarily conserved for 55-60 million years, but not prior.30 The differences in this pathway between humans/primates and other mammals call into question animal models that try to emulate the vitamin D system and indeed the immune system.

Inflammation

Another component of the innate immune response is inflammation, the universal initial response of the organism to any injurious agent.31 Inflammation is a systemic physiological process fundamental for survival.32 The identification of bacteria and other pathogens triggers the release of inflammatory cytokines. These cytokines include interferon-gamma, tumor necrosis factor-alpha (TNF-alpha), and Nuclear Factor-kappa B (NF-kappaB). Cytokines are regulatory proteins, such as the interleukins and lymphokines, that are released by cells of the immune system and act as intercellular mediators in the generation of an immune response. The result is what medicine calls inflammation, which generally leads to an increase in symptoms.

Th1/Th17 inflammation

One key type of inflammation is the Th1/Th17 (T-helper) inflammatory response. In the interests of concision, the Th1/Th17, on this site and others, the Th1/Th17 response is referred to as the Th1 response. This reaction occurs in response to intracellular pathogens, which according to the Marshall Pathogenesis, play a driving force in chronic disease.

All Th1 diseases are marked by an inflammatory response

Before the Human Microbiome Project, scientists couldn’t consistently link bacteria to inflammatory diseases. But with the advent of DNA sequencing technology, scientists have detected many of the bacteria capable of generating an inflammatory response. All diseases of unknown etiology are inflammatory diseases.

An inflammatory immune response—one of the body’s primary means to protect against infection—defines multiple established infectious causes of chronic diseases, including some cancers. Inflammation also drives many chronic conditions that are still classified as (noninfectious) autoimmune or immune-mediated (e.g., systemic lupus erythematosus, rheumatoid arthritis, Crohn’s disease). Both [the innate and adaptive immune systems] play critical roles in the pathogenesis of these inflammatory syndromes. Therefore, inflammation is a clear potential link between infectious agents and chronic diseases.

Siobhán M. O’Connor et al. 33

Th2 inflammation

According to the Marshall Pathogenesis, generally speaking, any activity of the Th2 cytokines in chronic disease is a result of the primary Th1-inducing pathogens.

Many palliative therapies interfere with inflammation

While inflammation is associated with disease, inflammation often serves an invaluable role as the immune system fights off chronic pathogens. Numerous medications artificially suppress inflammation including anti-TNF drugs, interferon, corticosteroids, antifungals, and anti-pyreutics. While interfering with the inflammatory response typically reduces immunopathology and makes a patient feel less symptomatic in the near term, doing so allows the bacteria which cause chronic disease to proliferate.

The release of cytokines appears to be essential for recovery after an infection. One study found that the cytokine TNF-alpha – which is blocked by anti-TNF drugs – is necessary for the proper expression of acquired specific resistance following infection withMycobacterium tuberculosis.34 35 36 Another effect of the use of TNF blockers is to break or reduce the formation of granuloma, one of the body’s mechanisms to control bacterial pathogens.37

Commensal microbes

The host innate immune defense system is highly active in healthy tissue.38 Commensal bacteria can activate innate immune responses.39 40

Keywords:
References
2 Ramagopalan SV, Heger A, Berlanga AJ, Maugeri NJ, Lincoln MR, Burrell A, Handunnetthi L, Handel AE, Disanto G, Orton SM, Watson CT, Morahan JM, Giovannoni G, Ponting CP, Ebers GC, Knight JC A ChIP-seq defined genome-wide map of vitamin D receptor binding: associations with disease and evolution. Genome Res. 2010;20:1352-60.
3 , 8 Wang TT, Tavera-Mendoza LE, Laperriere D, Libby E, MacLeod NB, Nagai Y, Bourdeau V, Konstorum A, Lallemant B, Zhang R, Mader S, White JH Large-scale in silico and microarray-based identification of direct 1,25-dihydroxyvitamin D3 target genes. Mol Endocrinol. 2005;19:2685-95.
4 , 18 Zasloff M Antimicrobial peptides of multicellular organisms. Nature. 2002;415:389-95.
6 Overington JP, Al-Lazikani B, Hopkins AL How many drug targets are there? Nat Rev Drug Discov. 2006;5:993-6.
7 Sun J Vitamin D and mucosal immune function. Curr Opin Gastroenterol. 2010;:.
9 Li YC, Bolt MJ, Cao LP, Sitrin MD Effects of vitamin D receptor inactivation on the expression of calbindins and calcium metabolism. Am J Physiol Endocrinol Metab. 2001;281:E558-64.
10 Wang TT, Nestel FP, Bourdeau V, Nagai Y, Wang Q, Liao J, Tavera-Mendoza L, Lin R, Hanrahan JW, Mader S, White JH Cutting edge: 1,25-dihydroxyvitamin D3 is a direct inducer of antimicrobial peptide gene expression. J Immunol. 2004;173:2909-12.
12 Schauber J, Dorschner RA, Coda AB, Büchau AS, Liu PT, Kiken D, Helfrich YR, Kang S, Elalieh HZ, Steinmeyer A, Zügel U, Bikle DD, Modlin RL, Gallo RL Injury enhances TLR2 function and antimicrobial peptide expression through a vitamin D-dependent mechanism. J Clin Invest. 2007;117:803-11.
14 González-Zorn B, Senna JP, Fiette L, Shorte S, Testard A, Chignard M, Courvalin P, Grillot-Courvalin C Bacterial and host factors implicated in nasal carriage of methicillin-resistant Staphylococcus aureus in mice. Infect Immun. 2005;73:1847-51.
15 Cao F, Castrillo A, Tontonoz P, Re F, Byrne GI Chlamydia pneumoniae–induced macrophage foam cell formation is mediated by Toll-like receptor 2. Infect Immun. 2007;75:753-9.
16 Chu HW, Jeyaseelan S, Rino JG, Voelker DR, Wexler RB, Campbell K, Harbeck RJ, Martin RJ TLR2 signaling is critical for Mycoplasma pneumoniae-induced airway mucin expression. J Immunol. 2005;174:5713-9.
17 Carlos D, Frantz FG, Souza-Júnior DA, Jamur MC, Oliver C, Ramos SG, Quesniaux VF, Ryffel B, Silva CL, Bozza MT, Faccioli LHTLR2-dependent mast cell activation contributes to the control of Mycobacterium tuberculosis infection. Microbes Infect.2009;11:770-8.
20 Chakraborty K, Ghosh S, Koley H, Mukhopadhyay AK, Ramamurthy T, Saha DR, Mukhopadhyay D, Roychowdhury S, Hamabata T, Takeda Y, Das S Bacterial exotoxins downregulate cathelicidin (hCAP-18/LL-37) and human beta-defensin 1 (HBD-1) expression in the intestinal epithelial cells. Cell Microbiol. 2008;10:2520-37.

 

Role of Dihydroxyvitamin D3 and Its Nuclear Receptor in Novel Directed Therapies for Cancer

S. Ondková, D. Macejová and J. Brtko
Gen. Physiol. Biophys. (2006), 25, 339—353   http://www.gpb.sav.sk/2006_04_339.pdf

Dihydroxyvitamin D3 is known to affect broad spectrum of various biochemical and molecular biological reactions in organisms. Research on the role and function of nuclear vitamin D receptors (VDR) playing a role as dihydroxyvitamin D3 inducible transcription factor belongs to dynamically developing branches of molecular endocrinology. In higher organisms, full functionality of VDR in the form of heterodimer with nuclear 9-cis retinoic acid receptor is essential for biological effects of dihydroxyvitamin D3. This article summarizes selected effects of biologically active vitamin D3 acting through their cognate nuclear receptors, and also its potential use in therapy and prevention of various types of cancer.

……

Vitamin D family consists of 9,10-secosteroids which differ in their side-chain structures. They are classified into five forms: D2, ergocalciferol; D3, cholecalciferol; D4, 22,23-dihydroergocalciferol; D5, sitosterol (24-ethylcholecalciferol) and D6, stigmasterol (Napoli et al. 1979). The main forms are vitamin D2 (ergocalciferol: plant origin) and vitamin D3 (cholecalciferol: animal origin). Both 25-hydroxyvitamin D2 and 1α,25-dihydroxyvitamin D2 have been evaluated for their biological functions. Vitamin D itself is a prohormone that is metabolically converted to the biologically active metabolite, 1,25-dihydroxyvitamin D3 in kidney. This vitamin D3, currently considered a steroid hormone, activates its cognate nuclear receptor (vitamin D receptor or VDR) which alter transcription rates of the target genes responsible for its biological responses. In general, vitamin D is essential for mineral homeostasis, for absorption and utilization of both calcium and phosphate and it aids in the mobilization of bone calcium and maintenance of serum calcium concentrations. Through these function, it plays an important role in ensuring proper functioning of muscles, nerves, blood clotting, cell growth and energy utilization. It has been proposed that vitamin D is also important for insulin and prolactin secretion, immune and stress responses, melanin synthesis and for differentiation of skin and blood cells (Lips 2006). Vitamin D metabolites also play a role in the prevention of auto-immune diseases and cancer (Pinette et al. 2003; Dusso et al. 2005). The steroid hormone 1α,25-dihydroxyvitamin D3 (calcitriol) exerts biological responses by interaction with both the well-characterized nuclear receptor (VDRnuc) responsible for activation gene transcription and not fully characterized membrane-associated protein/receptor (VDRmem) involved in generating a variety of rapid, non-genotropic responses (Evans 1988; Norman et al. 2002).

Vitamin D metabolism

Vitamin D, the “sunshine” vitamin, is synthesized under the influence of ultraviolet light in the skin. Many mammals have provitamin D (7-dehydrocholesterol) which is converted to provitamin D3 in their skin. When human skin is exposed to sunlight, the UV-B photons (wavelengths 290–315 nm) interact with 7-dehydrocholesterol causing photolysis and cleavage of the B-ring of the steroid structure, which upon thermoisomerization yields a secosteroid. Thus, provitamin D3 which is inherently unstable rapidly converts by a temperature-dependent process to vitamin D3 (MacLaughlin et al. 1982; Holick 1994). Vitamin D3 enters the blood circulation and binds to vitamin D binding protein (DBP) (Haddad et al. 1993) which carries vitamin D3 to liver and kidney for bioactivation (Wikvall 2001). In the first activation step, vitamin D3 is hydroxylated by the enzyme 25-hydroxylase to 25- hydroxyvitamin D3 mainly in the liver. This metabolite is present in the circulation at the concentration of more than 0.05 µmol/l (20 ng/ml). In the second step, the biologically active hormone 1α,25-dihydroxyvitamin D3 is generated by hydroxylation of 25-hydroxyvitamin D3 at 1α-position in kidney. The enzyme 1α-hydroxylase has been shown to be also present in keratinocytes and prostate epithelial cells, suggesting that those organs may also be able to generate 1α,25-dihydroxyvitamin D3 from 25-dihydroxyvitamin D3 (Schwartz et al. 1998). The activity of 1α-hydroxylase in the kidney serves as the major control point in production of the active hormone. The active metabolite 1α,25-dihydroxyvitamin D3 is present in human plasma at the concentration ranging from 0.05 to 0.15 nmol/l (20–60 pg/ml) (Hartwell et al. 1987; Gross et al. 1996). In general, 90 to 100% of the most human being vitamin D requirement comes from exposure to sunlight (Holick 2003) and the rest of the vitamin D3 content is obtained from diet (Malloy and Feldman 1999). The catabolism of vitamin D occurs by further hydroxylation of 25-dihydroxyvitamin D3 by 24-hydroxylase to yield 24,25-dihydroxyvitamin D3. The 24-hydroxylase is ubiquitous enzyme and is expressed in all the cells expressing VDR. This enzyme is regulated by parathyroid hormone and 1α,25-dihydroxyvitamin D3. The major significance of 24-hydroxylation is inactivation of vitamin D (Nishimura et al. 1994; Brenza and DeLuca 2000). The combinations of 1,25-dihydroxyvitamin D3 with inhibitors of 24-hydroxylase such as ketoconazole or liarozole may enhance its antitumour effects in prostate cancer therapy.

Vitamin D3 receptor

More than 2000 synthetic analogues of the biological active form of vitamin D, 1α,25-dihydroxyvitamin D3, are presently known. Basically, all of them interfere with the molecular switch of nuclear 1α,25-dihydroxyvitamin D3 signalling, which is the complex of the VDR, the retinoid X receptor (RXR), and a 1α,25-dihydroxyvitamin D3 response element (VDRE) (Carlberg 2003).

VDR is the only nuclear protein that binds the biologically most active vitamin D metabolite, 1α,25-dihydroxyvitamin D3, with high affinity (Kd = 0.1 nmol/l). This classifies the VDR into the classical endocrine receptor subgroup of the nuclear receptor superfamily, which also contains the nuclear receptors for hormones as retinoic acid, thyroid hormone, estradiol, progesterone, testosterone, cortisol, and aldosterol (Carlberg 1995). Similarly, like other biologically active ligand for nuclear hormone receptors, 1,25-dihydroxyvitamin D3 can modulate expression of selected ion transport protein genes (Van Baal et al. 1996; Hudecova et al. 2004).

The VDR was first isolated after trancfection of COS-1 cells with cloned sequences of complementary DNA that was isolated from human intestine (Baker et al. 1988). VDR has been found in more than 30 tissues including intestine, colon, breast, lung, ovary, bone, kidney, parathyroid gland, pancreatic β-cells, monocytes, keratinocytes, and many cancer cells, suggesting that the vitamin D endocrine system may also be involved in regulating the immune systems, cellular growth, differentiation and apoptosis (Jones et al. 1998). The active form of vitamin D binds to intracellular receptors that then function as transcription factors to modulate gene expression. Like the receptors for other steroid hormones and thyroid hormones, the VDR has specific hormone-binding and DNA-binding domains. It contains two zinc finger structures forming a characteristic DNA-binding domain (DBD) of 66 amino acids and a carboxy-terminal ligand-binding domain (LBD) of approximately 300 amino acids, which is formed by 12 α-helices. Ligand binding causes a conformational change within the LBD, in which helix 12, the most carboxy-terminal α-helix, closes the ligand-binding pocket via a “mouse-trap like” intramolecular folding (Moras and Gronemeyer 1998). Moreover, the LBD is involved in a variety of interactions with nuclear proteins, such as other nuclear receptors, corepressor and coactivator proteins. These ligand-triggered protein-protein interactions are the central molecular event of nuclear 1α,25-dihydroxyvitamin D3 signalling.

….

Role of vitamin D3 in cancer

Some of biologically active ligands for nuclear receptors exert tumour-suppressive activity, and they have therapeutical exploitation due to their antiproliferative and apoptosis-inducing effects (Brtko and Thalhamer 2003).

…..

During the last decade, evidence for vitamin D3 effects has been accumulating not only for prostate cancer (Feldman et al. 1995; Ma et al. 2004) but also for colon cancer (Cross et al. 1997; Bischof et al. 1998). 1α-hydroxylase was found to be Vitamin D and Cancer Treatment 347 expressed and active in colorectal cancer (Bareis et al. 2001; Cross et al. 2001; Tangpricha et al. 2001; Ogunkolade et al. 2002) and ovarian cancer (Miettinen et al. 2004). In both colon and also lung tumours, CYP24A1 mRNA was significantly up-regulated, while VDR mRNA was generally down-regulated when compared to respective normal tissues. When the level of VDR in 12 malignant colonic tumours was compared with that of adjacent normal tissue, in 9 cases out of 12, expression of VDR in tumours was decreased. However, in that study, the expression of CYP24A1 was not assessed. It has also been shown that, at least in human colon cancer cell lines, the level of VDR correlates with the degree of cell differentiation (Shabahang et al. 1993; Anderson et al. 2006).

Recently, it has been suggested that actually 20–30% of colorectal cancer incidence might be due to insufficient exposure to sunlight. This fact was strengthen by correlation between reduced colorectal cancer incidence and sunlight exposure, low skin pigmentation, nutritional vitamin D intake and high serum levels of 25- hydroxyvitamin D3 (Grant and Garland 2003). In the colon at least, CYP27B1 and VDR expression was described to be actually elevated during early tumour progression and that described dual positivity was found in many, but not all the tumour cells. In human colon tumours, CYP24 mRNA is quite highly expressed and the studies also demonstrated that with the exception of differentiated Caco-2 cells, CYP24 activity is constitutively present or can be induced by 1α,25- dihydroxyvitamin D3. During tumour progression in the colon, not only VDR but CYP27B1 and CYP24 expression were found to be increased in tumour tissues (Bareis et al. 2001; Bises et al. 2004).

Androgens, retinoids, glucocorticoids, estrogens and agonists of peroxisome proliferator-activated receptor directly or indirectly have reasonable impact on vitamin D signalling pathways, and vice versa. It was proposed that sex hormones might reduce colorectal cancer risk (McMichael and Potter 1980). The studies suggested that current and long-term use of estrogens is associated with a substantial decrease in risk of fatal colon cancer. The mechanism, however, by which estrogens could inhibit colonic tumour growth, remains an enigma. There are at least two distinct estrogen receptors in the human body: ERα and ERβ. In the normal human colon, ERβ is widely regarded to be the predominant subtype (CampbellThompson et al. 2001). In a recently terminated pilot study together with Strang Cancer Prevention Centre at Rockefeller University (NY, USA), tissues from postmenopausal women receiving 17β-estradiol for expression of CYP27B1 by real time RT-PCR were examined. CYP27B1 was found to be elevated significantly in all subjects after receiving 17β-estradiol for 4 weeks.

Amplification of chromosomal region 20q12q13 containing the CYP24A1 gene has been reported in ovarian cancer, as well (Tanner et al. 2000). Although inhibition of ovarian cancer cell growth by 1α,25-dihydroxyvitamin D3 has been reported (Saunders et al. 1992, 1995), a clinical trial testing the efficacy of 1α,25- dihydroxyvitamin D3 combined with isotretinoin in treating 22 epithelial ovarian cancer patients for 74 weeks has not produced positive results (Rustin et al. 1996).

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developments in medical spectroscopy

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

Using QCLs for MIR-Based Spectral Imaging — Applications in Tissue Pathology
A quantum cascade laser (QCL) microscope allows for fast data acquisition, real-time chemical imaging and the ability to collect only spectral frequencies of interest. Due to their high-quality, highly tunable illumination characteristics and excellent signal-to-noise performance, QCLs are paving the way for the next generation of mid-infrared (MIR) imaging methodologies.

Using QCLs for MIR-Based Spectral Imaging — Applications in Tissue Pathology

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Efficient Spectroscopic Imaging Demonstrated In Vivo
Although optical spectroscopy is routinely used study molecules in cell samples, it is currently not practical to perform in vivo. Now, a converted Raman spectroscopy system has been used to reveal the chemical composition of living tissues in seconds.

Efficient Spectroscopic Imaging Demonstrated In Vivo

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Broadband Laser Aimed at Cancer Detection
Covering a wide swath of the mid-infrared region, a new laser system offers greater spectral sensitivity.

Broadband Laser Aimed at Cancer Detection

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Using QCLs for MIR-Based Spectral Imaging — Applications in Tissue Pathology

A quantum cascade laser (QCL) microscope allows for fast data acquisition, real-time chemical imaging and the ability to collect only spectral frequencies of interest. Due to their high-quality, highly tunable illumination characteristics and excellent signal-to-noise performance, QCLs are paving the way for the next generation of mid-infrared (MIR) imaging methodologies.

MICHAEL WALSH, UNIVERSITY OF ILLINOIS AT CHICAGO; MATTHEW BARRE & BENJAMIN BIRD, DAYLIGHT SOLUTIONS

H. Sreedhar*1, V. Varma*2, A. Graham3, Z. Richards1, F. Gambacorata4, A. Bhatt1,
P. Nguyen1, K. Meinke1, L. Nonn1, G. Guzman1, E. Fotheringham5, M. Weida5,
D. Arnone5, B. Mohar5, J. Rowlette5
1 Department of Bioengineering, University of Illinois at Chicago
2 Department of Pathology, University of Illinois at Chicago
3 Department of Bioengineering, University of Illinois at Urbana-Champaign
4 Department of Chemical Engineering, University of Illinois at Chicago
5 Daylight Solutions, San Diego
*Contributed Equally

Real-time, MIR chemical imaging microscopes could soon become powerful frontline screening tools for practicing pathologists. The ability to see differences in the biochemical makeup across a tissue sample greatly enhances a practioner’s ability to detect early stages of disease or disease variants. Today, this is accomplished much as it was 100 years ago — through the use of specially formulated stains and dyes in combination with white light microscopy. A new MIR, QCL-based microscope from Daylight Solutions enables real-time, nondestructive biochemical imaging of tissues without the need to perturb the sample with chemical or heat treatments, thus preserving the sample for follow-on fluorescence tagging, histochemical staining or other “omics” testing within the workflow.
MIR chemical imaging is a well-established absorbance spectroscopy technique; it senses the relative amount of light that molecules absorb due to their unique vibrational resonances falling within the MIR portion of the electromagnetic spectrum (i.e., wavelengths from approximately 2 to 15 µm). This absorption can be detected with a variety of MIR detector types and can provide detailed information about the sample’s chemical composition.

The most common instrument for this type of measurement is known as a Fourier transform infrared (FTIR) spectrometer. FTIR systems use a broadband MIR light source, known as a globar, to illuminate a sample; the absorption spectrum is generated by the use of interferometry. Throughout the past decade, FTIR systems have incorporated linear arrays and 2D focal plane arrays (FPAs) in a microscope configuration to enable a technique known as chemical imaging.

With this approach, the illumination beam is expanded across a sample area, and the data produced is transformed into a hyperspectral data cube — a 2D image of the sample with an absorption profile associated with every pixel. This is a very versatile technique that allows the detailed spatial distribution of chemical content to be analyzed across a sample. Recently, this technique has proved to be very useful within the biomedical imaging sector for label-free, biochemical analyses of cells, tissue and biofluids.

While FTIR microscopy now is established as a powerful technique for a wide variety of applications, the instruments used for this methodology are fundamentally limited by the brightness of the globar source. Users looking to maximize the signal-to-noise ratios, and the associated resolutions of the images produced are forced to use synchrotron facilities, which replace the globar light source with a MIR beam generated by a particle accelerator. This approach can yield excellent results but clearly is not practical for benchtop applications; it is particularly unfit for biomedical imaging applications within clinical settings.

The recent advent of QCLs has provided an ideal light source for next-generation MIR microscopy. They are compact, semiconductor-based lasers that produce high-brightness light in the MIR region. The devices can be manufactured in an external cavity configuration to provide broadly tunable output with a narrow spectral bandwidth at each frequency. In this configuration, a QCL can be tuned across the MIR spectrum to sequentially capture an absorption profile for chemical identification.

Daylight Solutions’ IR microscope incorporates a broadly tunable and high-brightness QCL light source (it is an order of magnitude brighter than a synchrotron), a set of high numerical aperture (NA) diffraction-limited objectives, and an uncooled microbolometer FPA into a compact, benchtop instrument, as shown in Figure 1. The instrument provides rapid, high-resolution chemical images across very large fields of view and also provides a real-time chemical imaging mode. By overcoming the physical size, camera cooling and data collection time requirements of FTIR-based instruments, the microscope is positioned to bring MIR microscopy beyond research settings and into clinical use.

Schematic of a quantum cascade laser (QCL) microscope.


Figure 1. Schematic of a quantum cascade laser (QCL) microscope. Courtesy of Daylight Solutions.


Dr. Michael Walsh of the University of Illinois at Chicago (UIC) conducts research within the pathology department’s Spectral Pathology Lab, which has been using the IR microscope for the past several months. Walsh has been focused on developing chemical imaging techniques, with the ultimate goal of improving diagnoses within the field of tissue pathology.

Currently, the state-of-the-art method-ology used for the diagnosis of most solid-organ diseases is to extract a tissue sample via a biopsy. Tissue inherently has very little contrast and needs to be stained with dyes or probes to visualize and identify cell types and tissue structures. The field of pathology is based on examining the stained tissues, typically using white light, to determine if the tissue morphology deviates from a normal pattern. If the tissue looks abnormal, the disease state may be further subclassified by grade or by predicted outcome. However, the field of pathology is limited by the information that can be derived from the stained tissues and the subjective interpretation of the tissue by a highly trained pathologist.

Spero microscope.


Spero microscope. Courtesy of Daylight Solutions.


UIC’s Spectral Pathology Lab is focused on identifying areas in pathology where current techniques fail, or where there is a need for additional diagnostic or prognostic information that can help improve patient care. Potentially, MIR imaging is a very valuable adjunct to the current practice of pathology. Rather than using only stains, MIR imaging can interrogate the entire biochemistry of the tissue and render a diagnosis in an objective fashion. Traditionally, MIR imaging with an FTIR system has been limited by slow data acquisition speeds and the need to collect the entire spectral data cube. QCL imaging with the Spero microscope has the potential to speed up the data acquisition of images obtained from a tissue sample and to collect only the spectral frequencies of interest. The device also provides real-time imaging of samples at 30 fps, which could allow pathologists to very rapidly identify areas of interest on a tissue biopsy in a manner that is similar to their current clinical workflows. Some examples of the comparison of FTIR-derived and QCL-derived images from multiple organ tissues of interest are presented.

H&E-stained image of a mouse brain section on IR reflective slide, with selected regions labeled: hypothalamus, thalamus, and dentate gyrus.
Figure 2.
(a) H&E-stained image of a mouse brain section on IR reflective slide, with selected regions labeled: hypothalamus, thalamus, and dentate gyrus. (b) Transflectance QCL IR image of same region, prior to staining, at 1652 cm−1, in which the thalamus is clearly distinguished from surrounding regions. (c) Same region at 1548 cm−1. (d) Same region at 1500 cm−1. Courtesy of University of Illinois at Chicago (UIC)/Spectral Pathology Lab.


A tissue section from a mouse brain was scanned using the Spero microscope’s high-magnification objective (12.5×; 0.7 NA; 1.4 × 1.4-µm pixels) at various MIR frequencies in transflection mode, as shown in Figure 2. The tissue then was stained using hematoxylin and eosin (H&E), the most common stain in histopathology, and is displayed in Figure 2a. Using the H&E stain, regions were identified in the brain (thalamus, dentate gyrus and hypothalamus) that correlated with structures in the IR image. By illuminating the tissue at various wavelengths, discrete tissue features exhibit contrast due to the difference in absorption, as highlighted in the IR images taken at 1652, 1548 and 1500 cm−1 in Figure 2b-d, respectively. The microscope also makes it possible to visualize tissue at these individual wavelengths in real time. The identification of cell types and their biochemical changes is of particular interest in neuropathology.

Transmission FTIR image of a 4-µm thick section from a human liver tissue microarray on barium fluoride at 1650 cm-1.
Figure 3.
(a) Transmission FTIR image of a 4-µm thick section from a human liver tissue microarray on barium fluoride at 1650 cm-1. The image was taken with 64 coadditions of successive scans. (b) Transmission image from the Spero microscope of the same tissue at 1652 cm-1, both baseline corrected between 1796 cm-1 and 904 cm-1. In both images, the bright white stripe dividing the tissue core roughly in half is a region of fibrosis (red arrow), while the rest of the tissue on either side is composed primarily of hepatocytes (blue arrow). Courtesy of UIC/Spectral Pathology Lab.


A single biopsy core obtained from human liver tissue was scanned in transmission mode on a barium fluoride substrate by an Agilent Cary 600 Series FTIR microscope (Figure 3a). The FTIR image was acquired using a 36× Cassegrain collecting objective and a 15× Cassegrain condenser for a pixel size of 2.2 × 2.2 µm. Figure 3b shows the same liver core acquired using the Spero microscope with the high-magnification collecting objective (12.5×, 0.7 NA) and condenser objective for a pixel size of 1.4 × 1.4 µm. High-definition IR imaging enables clear contrast and identification of the band of fibrosis in the center of the core and the surrounding regions of liver cells, known as hepatocytes, and is indicated within Figure 3a-b. Acquisition of IR imaging data at the diffraction limit enables chemical information to be recorded from tissue structures at the single-cell level, allowing accurate characterization of individual tissue components, different cell types, varied disease states or other aspects of a tissue section.

Averaged spectra for regions of interest corresponding to the hepatocytes and the fibrotic area on the FTIR image in Figure 3a.
Figure 4.
(a) Averaged spectra for regions of interest corresponding to the hepatocytes and the fibrotic area on the FTIR image in Figure 3a. Spectra have been truncated from 1800 to 900 cm-1, normalized to 1650 cm-1, and baseline corrected between 1796 and 904 cm-1. (b) Averaged spectra for regions of interest corresponding to the hepatocytes and the fibrotic area on the Spero microscope image in Figure 3b. Spectra have been normalized to 1652 cm-1 and baseline corrected between 1796 and 904 cm-1.


Figure 4 displays average spectra calculated from homogenous tissue regions that describe hepatocytes and fibrosis within the liver tissue core shown in Figure 3. The spectra acquired from both FTIR and QCL systems are very similar. Walsh is focused on developing spectral classifiers that can aid pathologists in making very difficult diagnoses in the precancerous stages of liver cancer.

H&E-stained section of human colon tissue, and FTIR (with 16 coadditions) and Spero microscope transmission images of a 4-µm thick serial section of the same sample on barium fluoride. FTIR image shown at 1650 cm-1, Spero microscope image shown at 1652 cm-1.
Figure 5.
H&E-stained section of human colon tissue, and FTIR (with 16 coadditions) and Spero microscope transmission images of a 4-µm thick serial section of the same sample on barium fluoride. FTIR image shown at 1650 cm-1, Spero microscope image shown at 1652 cm-1. The red circle indicates mucin, the green circle indicates malignant colon carcinoma epithelium, and the blue circle indicates fibroblastic stroma. The raw spectra (taken from single pixels in approximately the same location for each of the three tissue features) are shown below their respective IR images. The FTIR spectra were truncated to match the Spero microscope’s spectral range of 1800 to 900 cm-1. Courtesy of UIC/Spectral Pathology Lab.


Point spectra from individual pixels were obtained and compared from a human colon sample on barium fluoride scanned in transmission on the same FTIR and QCL systems, which is shown in Figure 5. A serial section was obtained and stained with H&E to identify the different tissue structures. Using the H&E image as a reference, spectra from mucin (red), malignant colon carcinoma epithelium (green) and fibroblastic stroma (blue) were collected from a single pixel at approximately the same location. The unprocessed QCL and FTIR spectra are shown directly beneath their respective images. The FTIR system has an FPA size of 128 × 128 detector elements, while the Spero system has a microbolometer of 480 × 480 detector elements. Therefore, the FTIR image was collected as a mosaic and then stitched together.

FTIR and Spero microscope spectra from a single pixel of mucin, from the tissue shown in Figure 5.
Figure 6.
(a) FTIR and Spero microscope spectra from a single pixel of mucin, from the tissue shown in Figure 5. (b) FTIR and Spero microscope spectra from a single pixel of malignant colon carcinoma epithelium, from the same tissue. (c) FTIR and Spero microscope spectra from a single pixel of fibroblastic stroma. All spectra have been normalized (FTIR to 1650 cm-1, Spero to 1652 cm-1) and baseline corrected between 1796 and 904 cm-1, with the FTIR spectra truncated to match the Spero microscope’s spectral range of 1800 to 900 cm-1. Note that pixels for each tissue feature were located in approximately the same region, and that the two images have different pixel sizes (2.2 × 2.2 µm for FTIR, 1.4 × 1.4 µm for Spero microscope). Courtesy of UIC/Spectral Pathology Lab.


The spectra obtained from the regions of interest depicted in Figure 5 were preprocessed, as shown in Figure 6. The data was peak height normalized to the Amide I band. The FTIR data and QCL data were processed using a simple, two-point linear baseline correction between 1796 and 904 cm−1. Figure 6a-c shows the processed data from single pixels looking at the biochemistry of mucin, malignant colon carcinoma epithelium and fibroblastic stroma, respectively. The spectra from the QCL and FTIR systems are very similar on an individual-pixel level.

Finally, Figure 7 shows the scan of a frozen prostate tissue section captured with the microscope. Once thawed, the system can quickly image these sections at a single frequency of interest. The real-time capabilities of the system combined with the capacity for scanning frozen samples could someday allow for the analysis of samples in a time-critical intraoperative setting.

Transflectance scan of a 5-µm frozen human prostate tissue section on Kevley low-emissivity substrate captured with the Spero microscope.


Figure 7. Transflectance scan of a 5-µm frozen human prostate tissue section on Kevley low-emissivity substrate captured with the Spero microscope. Visualized with a false color map at 1640 cm-1. Data was baseline corrected between 1796 and 904 cm-1. Courtesy of UIC/Spectral Pathology Lab. University of Illinois at Chicago — Spectral Pathology Lab members, from left to right: David Martinez, Francesca Gambacorta, Vishal Varma, Andrew Graham and Michael Walsh. Courtesy of Daylight Solutions.


While there has been significant interest in MIR imaging for pathology applications for a number of years1-5, the technology has lacked the maturity to be ready for clinical implementation due to slow scanning speeds, low spatial resolutions and by a lack of computational power to fully handle large multispectral datasets. The Spero microscope, coupled with modern computing power, overcomes these limitations. The information detailed above demonstrates that the quality of the images and spectra obtained from the instrument are similar to those offered by FTIR imaging methods but with the additional benefits associated with the use of a QCL-based system. Recent advances in large multielement FPAs6-8) and high-resolution imaging approaches9-11 for tissue pathology have made this a much more attractive approach for fast and detailed image acquisition. QCLs represent the next step toward clinical implementation — they have demonstrated fast data acquisition, live-imaging capabilities and the ability to collect only spectral frequencies of diagnostic value.

Meet the authors

Michael Walsh holds a PhD in biological sciences and is an assistant professor at the University of Illinois at Chicago in Chicago; email: walshm@uic.edu. Matthew Barre is the business development manager at Daylight Solutions in San Diego; email: mbarre@daylightsolutions.com. Benjamin Bird is an applications scientist at Daylight Solutions in San Diego; email: bbird@daylightsolutions.com.

References

1. D.C. Fernandez et al. (2005). Infrared spectroscopic imaging for histopathologic recognition. Nat Biotechnol, Vol. 23, Issue 4, pp. 469-474.

2. C. Matthaus et al. (2008). Chapter 10: Infrared and Raman microscopy in cell biology. Methods Cell Biol, Vol. 89, pp. 275-308.

3. C. Kendall et al. (2009). Vibrational spectroscopy: a clinical tool for cancer diagnostics. Analyst, Vol. 134, Issue 6, pp. 1029-1045.

4. C. Krafft et al. (2009). Disease recognition by infrared and Raman spectroscopy. J Biophotonics, Vol. 2, Issue 1-2, pp. 13-28.

5. F.L. Martin et al. (2010). Distinguishing cell types or populations based on the computational analysis of their infrared spectra. Nat Protoc, Vol. 5, Issue 11, pp. 1748-1760.

 

 

Broadband Laser Aimed at Cancer Detection

Covering a wide swath of the mid-infrared, a new system offers greater spectral sensitivity

BY JAMES F. LOWE, WEB MANAGING EDITOR, JAMES.LOWE@PHOTONICS.COM

MUNICH, Sept. 25, 2015 — Mid-infrared (MIR) light is rich with molecular “fingerprint” information that can be used to detect substances from atmospheric pollutants to cancer cells.

While some lasers already operate in this region, enabling a variety of spectroscopy applications, their linewidth is relatively narrow, which limits the types of substances they can detect at any given moment.

Now a team of researchers from Germany and Spain has developed a laser system with phase-coherent emission from 6.8 to 16.4 μm and output power of 0.1 W. That is broad and powerful enough, they said, to detect subtle signs of cancer early in its development.

Molecules absorb portions of the MIR spectrum in ways that are unique to their atomic structures, and their absorption patterns provide a means of identifying the molecules with great specificity, even in low concentrations.

 

Emission spectrum


The emission spectrum of the laser and corresponding molecular fingerprint regions. Courtesy of the Institute of Photonic Sciences (ICFO).


“Cancer causes subtle modification in protein structure and content within a cell,” said professor Dr. Jens Biegert, a group leader at the Institute of Photonic Sciences (ICFO) in Barcelona. “Looking at only a few nanometer range, the probability of detection is extremely low. But comparing many of such intervals, one can have an extremely high confidence level.”

The new laser system generates MIR pulses via difference-frequency generation driven by the nonlinearly compressed pulses of a Kerr-lens mode-locked Yb:YAG thin-disc oscillator. It features a repetition rate of 100 MHz and pulse durations of 66 fs — so short that the electric field oscillates only twice per pulse.

Lab


Staff scientist Dr. Ioachim Pupeza (left) and postdoctoral researcher Oleg Pronin helped develop a laser system that emits ultrashort pulses of mid-infrared light. These pulses can be used to detect trace molecules in gaseous and liquid media. Courtesy of Thorsten Naeser/Ludwig Maximilian University.


“Since we now possess a compact source of high-intensity and coherent infrared light, we have a tool that can serve as an extremely sensitive sensor for the detection of molecules, and is suitable for serial production,” said project leader Dr. Ioachim Pupeza, a staff scientist at Ludwig Maximilian University of Munich (LMU).

The LMU and ICFO researchers aim to use their MIR laser to identify and quantify disease markers in exhaled air. Many diseases, including some types of cancer, are thought to produce specific molecules that end up in the air expelled from the lungs.

“We assume that exhaled breath contains well over 1000 different molecular species,” said Dr. Alexander Apolonskiy, an LMU group leader.

However, the amount of molecular biomarkers present in exhaled breath is extraordinarily low, meaning a diagnostic tool would need to be capable of detecting concentrations of at least one part per billion. The next step will be to couple the new laser system with a novel amplifier that would increase its brightness and boost sensitivity one part per trillion.

Detecting MIR signatures

The laser’s output spans more than one octave. Until now, the researchers said, such broadband emission has only been available from large-scale synchrotron sources.

Other more compact MIR sources, such as quantum cascade lasers (QCLs), have narrower linewidths. Tuning them to different sensing bands is time consuming, and combining multiple QCLs emitting in different parts of the MIR would be cost-prohibitive, Biegert said.

Meanwhile, the laser system’s 100-MHz pulse train is hundreds to thousands of times more powerful than state-of-the-art frequency combs that emit in the same range, the researchers said.

Detecting broadband MIR signals presents its own problems, however. Detectors for this region have poor signal-to-noise ratios unless cooled with liquid nitrogen, the researchers said.

In this case, electro-optical sampling proved to be a better option. Well-established for the terahertz range, the technique is less common in the fingerprint region.

“In the MIR range, there are not many groups who have implemented this already, because you need a broadband, phase-stable MIR pulse and an ultrashort sample pulse at the same time, which is quite challenging,” Pupeza said.

Having solved that problem with their broadband laser, the team now could use electro-optical sampling to extract the data they wanted.

In a nutshell, the process works like this: The electric field of an MIR pulse alters the birefringence of a crystal. This change can be measured by observing how the polarization of slightly shorter near-infrared (NIR) pulse is changed while propagating through the same crystal at the same time. In the end, only the NIR pulse is measured directly.

“Therefore, one big advantage is low-noise detection in the NIR, even though one obtains information on spectral components in the MIR,” said Ioachim Pupeza. “You only need to perform a Fourier transform numerically to get the spectrum of the pulse once you have its electric field.”

http://www.photonics.com/Article.aspx?AID=57757
The research was published in Nature Photonics (doi: 10.1038/nphoton.2015.179).

 

 

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Human Genetics and Childhood Diseases, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Human Genetics and Childhood Diseases

Curator: Larry H. Bernstein, MD, FCAP

 

 

 

Publication Roundup: HGMD

HGMD®, the Human Gene Mutation Database is used by scientists around the world to find information on reported genetic mutations. The papers below use the database to advance our understanding of disease, DNA dynamics, and more.

https://www.qiagenbioinformatics.com/blog/translational/publication-roundup-hgmd

Local DNA dynamics shape mutational patterns of mononucleotide repeats in human genomes
First author: Albino Bacolla

Scientists in the US and UK published results in Nucleic Acids Research of a detailed analysis of single-base substitutions and indels in the human genome. Their findings show that certain base positions are more susceptible to mutagenesis than others. They used HGMD Professional to find mutations in specific genomic regions for analysis; the paper includes charts showing mutation patterns, germline SNPs, and more from HGMD data.

High prevalence of CDH23 mutations in patients with congenital high-frequency sporadic or recessively inherited hearing loss
First author: Kunio Mizutari

This Orphanet Journal of Rare Diseases paper from scientists in Japan sequenced 72 patients with unexplained hearing loss, finding several CDH23 mutations, some of which were novel. Mutations in the gene have been linked to Usher syndrome and other forms of hereditary hearing loss. The scientists used HGMD to find all known CDH23 mutations within nearly 70 coding regions.

Mutation analyses and prenatal diagnosis in families of X-linked severe combined immunodeficiency caused by IL2Rγ gene novel mutation
First author: Q.L. Bai

In Genetics and Molecular Research, scientists report the utility of mutation analysis of the interleukin-2 receptor gamma gene to assess carrier status and perform prenatal diagnosis for X-linked severe combined immunodeficiency. They studied two high-risk families, along with 100 controls, to evaluate the approach. Sequence variation was determined using HGMD Professional and an X-SCID database, and a new mutation was discovered in the project.

Impact of glucocerebrosidase mutations on motor and nonmotor complications in Parkinson’s disease
First author: Tomoko Oeda

Researchers from three hospitals in Japan published this Neurobiology of Aging report that may help stratify Parkinson’s disease patients by prognosis. They sequenced mutations in the GBA gene in 215 patients, finding that those who had mutations associated with Gaucher disease suffered dementia and psychosis much earlier than those who didn’t. The team found previously reported GBA mutations using HGMD Professional.

Comprehensive Genetic Characterization of a Spanish Brugada Syndrome Cohort
First author: Elisabet Selga

In this PLoS One publication, scientists from a number of institutions in Spain examined genetic variation among patients with Brugada syndrome, a rare genetic cardiac arrhythmia. They sequenced 14 genes in 55 patients, identifying 61 variants and finding the subset that appear pathogenic. Variants were filtered against a number of databases, including HGMD.

 

 

Local DNA dynamics shape mutational patterns of mononucleotide repeats in human genomes

Albino Bacolla1Xiao Zhu2Hanning Chen3Katy Howells4David N. Cooper4 and Karen M. Vasquez1

Nucl. Acids Res. (26 May 2015) 43(10): 5065-5080.   http://dx.doi.org:/10.1093/nar/gkv364

Single base substitutions (SBSs) and insertions/deletions are critical for generating population diversity and can lead both to inherited disease and cancer. Whereas on a genome-wide scale SBSs are influenced by cellular factors, on a fine scale SBSs are influenced by the local DNA sequence-context, although the role of flanking sequence is often unclear. Herein, we used bioinformatics, molecular dynamics and hybrid quantum mechanics/molecular mechanics to analyze sequence context-dependent mutagenesis at mononucleotide repeats (A-tracts and G-tracts) in human population variation and in cancer genomes. SBSs and insertions/deletions occur predominantly at the first and last base-pairs of A-tracts, whereas they are concentrated at the second and third base-pairs in G-tracts. These positions correspond to the most flexible sites along A-tracts, and to sites where a ‘hole’, generated by the loss of an electron through oxidation, is most likely to be localized in G-tracts. For A-tracts, most SBSs occur in the direction of the base-pair flanking the tracts. We conclude that intrinsic features of local DNA structure, i.e. base-pair flexibility and charge transfer, render specific nucleotides along mononucleotide runs susceptible to base modification, which then yields mutations. Thus, local DNA dynamics contributes to phenotypic variation and disease in the human population.

INTRODUCTION

Changes in human genomic DNA in the form of base substitutions and insertions/deletions (indels) are essential to ensure population diversity, adaptation to the environment, defense from pathogens and self-recognition; they are also a critical source of human inherited disease and cancer. On a genome-wide scale, base substitutions result from the combined action of several factors, including replication fidelity, lagging versus leading strand DNA synthesis, repair, recombination, replication timing, transcription, nucleosome occupancy, etc., both in the germline and in cancer (14). On a much finer scale [(over a few base pairs (bp)], rates of base substitutions may be strongly influenced by interrelationships between base–protein and base–base interactions. For example, the mutator role of activation-induced deaminase (AID) in B-cells during class-switch recombination and somatic hypermutation (5) targets preferentially cytosines within WRC (W: A|T; R: A|G) sequences (6), whereas apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) overexpression displays a preference for base substitutions at cytosines in TCW contexts (7). Other examples, such as the induction of C→T transitions at CG:CG dinucleotides by cytosine-5-methylation and the role of UV light in promoting base substitutions at pyrimidine dimers have been well documented (reviewed in (4,8)). More recently, complex patterns of base substitution at guanosines in cancer genomes have been found to correlate with changes in guanosine ionization potentials as a result of electronic interactions with flanking bases (9), suggesting a role for electron transfer and oxidation reactions in sequence-dependent mutagenesis. However, despite these advances, the increasing number of sequence-dependent patterns of mutation noted in genome-wide sequencing studies has met with a lack of understanding of most of the underlying mechanisms (10). Thus, a picture is emerging in which mutations are often heavily dependent on sequence-context, but for which our comprehension is limited.

Mononucleotide repeats comprise blocks of identical base pairs (A|T or C|G; hereafter referred to as A-tracts and G-tracts) and display distinct features: they are abundant in vertebrate genomes; mutations within the tracts occur more frequently than the genome-wide average; mutations generally increase with increasing tract length; length instability is a hallmark of mismatch repair-deficiency in cancers; and sequence polymorphism within the general population has been linked to phenotypic diversity (1115). Thus, mononucleotide repeats appear ideal for addressing the question of sequence-dependent mutagenesis since base pairs within the tracts are flanked by identical neighbors. Both historic and recent investigations concur with the conclusion that a major source of mononucleotide repeat polymorphism is the occurrence of slippage (i.e. repeat misalignment) during semiconservative DNA replication, which gives rise to the addition or deletion of repeat units (11,12). An additional and equally important source of mutation has recently been suggested to arise from errors in DNA replication by translesion synthesis DNA polymerases, such as pol η and pol κ (13), also on slipped intermediates, leading to single base substitutions.

A key question that remains unanswered in these studies and which is relevant to the issue of sequence context-dependent mutagenesis is whether all base pairs within mononucleotide repeats display identical susceptibility to single base changes and whether indels (which are consequent to DNA breakage) occur randomly within the tracts.

Herein, we combine bioinformatics analyses on mononucleotide repeat variants from the 1000 Genomes Project and cancer genomes with molecular dynamics simulations and hybrid quantum mechanics/molecular mechanics calculations to address the question of sequence-dependent mutagenesis within these tracts. We show that mutations along both A-tracts and G-tracts are highly non-uniform. Specifically, both base substitutions and indels occur preferentially at the first and last bp of A-tracts, whereas they are concentrated between the second and third G:C base pairs in G-tracts. These positions coincide with the most flexible base pairs for A-tracts and with the preferential localization of a ‘hole’ that results when one electron is lost due to an oxidation reaction anywhere along G-tracts. Thus, despite the uniformity of sequence composition, mutations occur in a sequence-dependent context at homopolymeric runs according to a hierarchy that is imposed by both local DNA structural features and long-range base–base interactions. We also show that the repair processes leading to base substitution must differ between A- and G-tracts, since in the former, but not in the latter, base substitutions occur predominantly in the direction of the base immediately flanking the tracts. Additional sequence-dependent patterns of mutation are likely to arise from studies of more heterogeneous sequence combinations, possibly involving other aspects intrinsic to the structure of DNA.

 

RESULTS

Mononucleotide repeat variation is defined by tract length and flanking base composition

We define mononucleotide repeats in the GRCh37/hg19 (hg19) human genome assembly as uninterrupted runs of A:T and G:C base pairs (hereafter referred to as A-tracts and G-tracts, respectively) from 4 to 13 base pairs in length (Figure 1A). We retrieved a total of 48,767,945 A-tracts and 13,633,781 G-tracts, both of which displayed a biphasic distribution with an inflection point between tract lengths of 8 and 9 (bp) and with the number of runs declining with length more dramatically for G-tracts than for A-tracts (Figure 1B), as noted previously (29). Both the number of short tracts and the extent of decline varied with flanking base composition, TA[n]T runs being two- to three-fold more abundant than CA[n]Cs (Supplementary Figure S1A) and AG[n]As declining the most rapidly (Supplementary Figure S1B). Thus, mononucleotide runs exist as a collection of separate pools of sequences in extant human genomes, each maintained at distinctive rates of sequence stability, as determined by factors such as bp composition (A:T versus G:C), tract length and flanking sequence composition.

Figure 1.

Mononucleotide repeat variation, evolutionary conservation and association with transcription. (A) The search algorithm was designed to retrieve runs of As or Ts (A-tracts) and Gs or Cs (G-tracts) length n (n = 4 to 13), along with their 5′ (n = 0) and 3′ (n = n + 1) nearest neighbors from hg19. Tract bases were numbered 5′ to 3′ with respect to the purine-rich sequence. The panel exemplifies the nomenclature for A- and G-tracts of length 4. (B) Logarithmic plot of the number of A-tracts (closed circles) and G-tracts (open circles) in hg19 as a function of length. (C) Normalized fractions of polymorphic tracts (F SNV) (number of SNVs divided by both hg19 number of tracts and n) from the 1KGP for A-tracts (closed circles) and G-tracts (open circles). (D) Radial plot of SNVs in the 1KGP at the 5′ and 3′ nearest neighbors of A-tracts. Periphery, tract length; horizontal axis, scale for the fraction of SNVs (F SNV). (E) Radial plot of SNVs in the 1KGP at the 5′ and 3′ nearest neighbors of G-tracts. (F) Percent difference in the numbers of A-tracts (closed circles) and G-tracts (open circles) between syntenic regions of hg19 and HN genomes. (G) The exponents of Benjamini-corrected P-values for A-tract-containing genes enriched in transcription-factor binding sites plotted as a function of A-tract length (triangles); each value represents the median of the top 11 USCS_TFBS terms. The percent A-tracts (closed circles) and G-tracts (open circles) intersecting genomic regions pulled-down by chromatin immunoprecipitation using antibodies against transcription factors are plotted as a function of tract length. (H) List of gene enrichment terms with a Benjamini-corrected P-value of <0.05 in common between genes containing A- and G-tracts of lengths 4–13, excluding the UCSC_TFBS terms.

 We examined the extent of sequence variation in the human population by mapping 38,878,546 single nucleotide variants (SNVs) from 1092 haplotype-resolved genomes (the 1000 Genomes Project, 1KGP) (30) to the hg19 A- and G-tracts. The normalized fractions of polymorphic tracts (F SNV) were greater for G-tracts than A-tracts and both displayed Gaussian-type distributions, with maxima of 0.067 for G-tracts of length 8 and 0.017 for A-tracts of length 9 (Figure 1C). CA[n]C and AG[n]A runs displayed the highest F SNV values for A- and G-tracts, respectively (Supplementary Figure S1C and D), with F SNV values for AG[n]As attaining ∼0.10 at length 8. We conclude that flanking base composition influences the rates of SNV within mononucleotide runs and, as a consequence, their representation in the reference human genome.

F SNV values at the flanking 5′ and 3′ bp were similar between A- and G-tracts, except for minor differences for the least represented (i.e. longest) tracts and did not exceed 0.02 (Supplementary Figure S1E). These fractions are expected to be greater than at more distant positions from the tracts, based on previous data (29). SNVs at G-tracts, but not at A-tracts, were more frequent than at flanking base pairs. F SNVs for base pairs flanking short (≤8 bp) tracts were at least twice as high as those flanking long tracts; F SNVs also displayed distinct sequence preference with most (∼0.1) variants occurring at Ts 3′ of G-tracts (Figure 1D and E). In summary, SNVs at mononucleotide runs do not increase monotonically with length but peak at 8–9 bp. This behavior mirrors the genomic distributions, both with respect to the total number of tracts (Figure 1B) and the subsets flanked by specific-sequence combinations (Supplementary Figure S1A–D). Variation at flanking base pairs also displayed a biphasic pattern centered at a length of 8–9 bp, with a greater chance of variation adjacent to G- than A-tracts and with characteristic sequence preferences.

Long tracts are evolutionarily conserved and associated with high transcription

To assess whether more variable monosatellite runs (Figure 1C) might have undergone a greater reduction in number in extant humans relative to extinct hominids, we compared the number of A- and G-tracts between syntenic regions of five individuals comprising hg19 and three Neanderthal (HN) specimens (31). The difference between hg19 and HN was very small (<±2%) for the short tracts, but it displayed more negative values in hg19 with increasing tract length, which reached a maximum of −11.8 and −32.7% for A- and G-tracts, respectively, of length 9. Beyond this threshold, the numbers of tracts converged for A-tracts, whereas they were more abundant in hg19 for G-tracts >11 bp (Figure 1F). In summary, the largest difference in the number of mononucleotide runs between hg19 and HN sequences was centered at 9 bp for both A- and G-tracts, suggesting that the length distributions (Figure 1A and Supplementary Figure S1A and B) reflect distinct rates of evolutionary gains and losses due to differential sequence mutability (Figure 1C) as a function of length and flanking sequence composition (12).

The fact that long (>9 bp) mononucleotide runs display low variability in the human population (Figure 1C) and sequence conservation during evolutionary divergence (Figure 1F) raises the possibility that they might serve functional roles. Through gene enrichment analyses, we found that genes containing A- and G-tracts were enriched for genes associated with the term ‘UCSC_TFBS’, which pertains to transcripts harboring frequent transcription factor binding sites (32,33). For A-tract-containing genes, the median P-values for the top 11 UCSC_TFBS terms decreased from 2.95E-26 for tracts of length 4 to 5.22E-241 for tracts of length 13 (Figure 1G). The percent of A-tracts intersecting genomic fragments amplified from chromatin immunoprecipitation using transcription-factor binding antibodies (32,33) also increased from 8.7 to 9.9 from length 6 to 13, whereas it was constant (mean ± SD, 22.4 ± 1.1) for G-tracts (Figure1G). For gene classes excluding ‘UCSC_TFBS’, a search for categories enriched at P < 0.05 and common to all A- and G-tract-containing genes returned a set of 25 terms, 22 of which were associated with high levels of tissue-specific gene expression (Figure 1H). In summary, these analyses extend prior work (14) supporting a role for mononucleotide tracts in enhancing gene expression, a function that for A-tracts appears to increase with increasing tract length.

Repeat variability is highly skewed

Next we addressed whether bp along A- and G-tracts display equal probability and type of variation. In the 1KGP dataset, the number of SNVs at each position along both A- and G-tracts of length 4 was within a two-fold difference (144,000–240,000); for both types of sequence, transitions (i.e. A→G and G→A) were the predominant (51–78%) type of base substitution (Supplementary Figure S2A and B). However, with increasing length, the number of SNVs decreased up to 30-fold more drastically for G-tracts than for A-tracts, with increasing numbers of transversions (A→T and G→C|T) being predominant. Normalizing the data for the number of tracts genome-wide revealed that the extent of SNV varied by up to 10-fold, depending upon tract length and bp position. Specifically, the highest degree of variation was observed at the first and last A within the A-tracts (i.e. A1 and An), which underwent up to 61% A→T and 43% A→C transversions, respectively, at length 9 (Figure 2A). Likewise, for G-tracts, the most polymorphic sites were G3, followed by G2, for mid-size tracts of 8–10 bp, with 44% G→C transversions at G3 for tracts of length 8 (Figure2B). Thus, the extent of SNV at mononucleotide runs is grossly skewed in human genomes, both along the sequence itself and across tract length, which must account for the bell-shape behavior in F SNV for the tracts as a whole (Figure 1C).

Figure 2.

Population variation spectra. (A) Variation spectra of A-tracts. Percent (number of SNVs at each position divided by the number of tracts in hg19 × 100) of A→T (black), A→C (red) and A→G (green) SNVs in the 1KGP dataset (left). Percent SNVs at A1 as a function of tract length (right). (B) Variation spectra of G-tracts. As in panel A with G→T (black), G→C (red) and G→A (cyan) (left). Percent SNVs at G3 as a function of tract length (right). (C) Percent A→T, A→C and A→G transitions at each position along A-tracts (stars) preceded and followed by a T (TA[n]T, left), C (CA[n]C), center) and G (GA[n]G, right) as a function of tract length. (D) Percent G→T, G→C and G→A transitions at each position along G-tracts (stars) preceded and followed by a T (TG[n]T, left), C (CG[n]C), center) and A (AG[n]A, right) as a function of tract length. (E) Percent transitions at base pairs (stars) preceding or following A-tracts (left) and G-tracts (right) as a function of tract length (n). *, mutated position.

We assessed whether SNV hypervariability was associated with specific combinations of nearest neighbors. For A-tracts flanked 5′ by a T, C or G, the highest percentage of SNVs was observed at A1 when preceded by a T, which reached 7.9% for TA[n] tracts of length 9 (Supplementary Figure S2C). By contrast, for 3′ T, C or G, the greatest effect was elicited by a C, with the highest percentage (7.1%) of SNVs at An for A[n]C tracts of length 9 (Supplementary Figure S2D). Therefore, flanking base pairs play a critical role both in the spectra and frequencies of SNVs at A-tracts. More detailed plots along A-tracts either preceded (Supplementary Figure S2E), followed (Supplementary Figure S2F) or preceded and followed (Figure 2C) by a T, C or G revealed the dramatic and long-range (up to 9–10 bp for the longest tracts, higher than the value of 4 bp predicted by mathematical models of slippage (11)) influence of flanking base pairs on variation spectra, in which up to 95% of the changes were in the direction of the base flanking the tract. Because the number of A-tracts preceded or followed by a specific base varies by up to three-fold (Supplementary Figure S2G), we conclude that for A-tracts, the overall mutation fractions and spectra are the result of at least three variables; length, position along the tract, and base composition of the 5′ and 3′ nearest-neighbors.

For G-tracts flanked 5′ by a T, C or A, high percentages (10–12%) of SNVs were observed at G1 for tracts preceded by a C, an effect that decreased with increasing tract length (Supplementary Figure S3A). This result, together with an exceedingly low number of G→A transitions at G1 for tracts not preceded by a C (Supplementary Figure S3C) relative to all tracts (Supplementary Figure S2B), is consistent with the known high mutability of CG:CG dinucleotides as a result of cytosine-5 methylation (9). The hypermutability at G2 was observed preferentially for tracts preceded by an A, and to a lesser extent T, whereas that at G3 was insensitive to flanking sequence composition. Likewise, G-tracts flanked 3′ by a T, C or A did not display marked sequence-dependent effects (Supplementary Figure S3B). Detailed plots of the SNV spectra along G-tracts either preceded (Supplementary Figure S3D), followed (Supplementary Figure S3E), or preceded and followed (Figure 2D) by a T, C or A revealed a noticeable effect only for 5′ T in association with G→T substitutions at G1for tracts of length ≥8. Thus, despite a consistent over-representation of G-tracts flanked 5′ by a T (Supplementary Figures S3F and S1B), which must account for the high absolute number of SNVs at G1 for TG[n] relative to AG[n] and CG[n] (Supplementary Figure S3G), nearest-neighbor base composition seems to play a lesser role in SNV spectra at G-tracts than at A-tracts.

With respect to SNVs at the flanking 5′ and 3′ nearest positions, no B→A or H→G substitutions (Figure 1A) were found above a length threshold of 9 for A-tracts and 8 for G-tracts (Figure 2E, gray shading) out of 5969 SNVs, implying that tract expansion by recruiting flanking base pairs is disfavored at these lengths. In summary, base substitution along mononucleotide repeats is strongly skewed towards the edges of A-tracts and within the 5′ half of G-tracts, with frequencies that peak at midsize lengths (8–9 bp). For A-tracts ≥7 bp, base substitution occurred almost exclusively in the direction of the flanking nearest-neighbors. Finally, base substitution at flanking bases did not contribute to tract expansion for mononucleotide runs longer than 8–9 bp.

Insertions and deletions display length and positional preference

In addition to SNVs, mononucleotide runs are polymorphic in length as a result of indels. Herein, we consider separately two types of indels: one in which tract length changes by ±1 and flanking bp composition is not altered (slippage); the other comprising all other cases involving the addition or removal of 1–200 bp (indels). Slippage is a widely accepted mutational mechanism (1112,34), whereby DNA replication errors at reiterated DNA motifs cause changes in the number of motifs (most often +/−1). The normalized fractions of slippage in the 1KGP dataset peaked at lengths of 8 bp for A-tracts and 9 bp for G-tracts (Figure 3A), generating bell-shaped curves similar to those observed for SNVs (Figure1C) and with no differences in the highest fraction of ‘slipped’ tracts, which peaked at ∼0.02. By contrast, +1 slippage occurred more frequently than −1 slippage at A-tracts (Figure 3B). These results support recent studies on microsatellite repeats (12) and contrast with previous conclusions that slippage increases monotonically with tract length, and that the extent of slippage differs between A- and G-tracts (35,36).

Figure 3.

Population insertions and deletions. (A) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage in the 1KGP dataset as a function of tract length. Data were obtained by dividing the number of events by both the number of hg19 tracts and tract length (n). (B) Ratio of the number of +1 to −1 slippage for A-tracts (closed circles) and G-tracts (open circles). (C) Indels at A-tracts. For positions along the tracts (‘Tract’), ‘F Indel’ is the ratio between the number of indels and the number of tracts in hg19 multiplied by tract length. For the positions immediately flanking the tracts genomic coordinates (‘Before tract’ and ‘After tract’), ‘F Indel’ is the ratio between the number of indels and the number of tracts in hg19. (D) Indels at G-tracts, calculated as described in panel C. (E) Heatmap representation of insertions along A-tracts. The percent insertions (i.e. the number of insertions at each position divided by the number of tracts in hg19) (y-axis) plotted as a function of location (x-axis) from position 0 (insertion between the bp 5′ to the tract and the first bp of the tract) to position n + 1 (insertion between the bp 3′ to the last bp of the tract and the following bp) (see Figure 1A) and as a function of tract length (z-axis). (F) Heatmap representation of insertions along G-tracts.

With respect to indels, the normalized fractions were low (<1 × 10−3) along short (4–6 bp) A- and G-tracts, but rose to a plateau for longer tracts as reported earlier (11); this plateau was 10-fold higher for G-tracts (∼0.03) than for A-tracts (∼0.003) (Figure 3C and D). Indels also occurred more frequently (up to six-fold for A-tracts of length 11) at nearest-neighboring base pairs (‘Before tract’ and ‘After tract’ in Figure 3C and D) than along the tracts. Thus, contrary to SNVs and slippage, indels increased to a plateau with mononucleotide tract length.

We analyzed in detail the locations of insertions along the tracts and the flanking positions with respect to the 5′ to 3′ orientation of the tracts (Figure 1A). The normalized fractions demonstrated that insertions peaked at the 3′, and to a lesser extent 5′, ends of the longest A-tracts (Figure 3E), but remained low. For G-tracts, insertions occurred most efficiently at two locations (G2–3 and G5) (Figure 3F), they increased with tract length (up to ∼0.04), and attained ∼10-fold higher values than for A-tracts. In conclusion, insertion sites at A- and G-tracts followed the patterns observed for SNVs (Figure 2A and B), suggesting that factors associated with local DNA dynamics sensitize specific bases along the tracts to genetic alteration, inducing both SBS and indels.

Base pair flexibility and charge localization map to sites of sequence changes

To elucidate elements of intrinsic DNA dynamics that may be responsible for the biases in SNV and insertion sites, we performed molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations on model A[6], A[9], G[6] and G[9] duplex DNA fragments. We focused on water bridge coordination (Figure 4A), bp step flexibility, and for the G[6] and G[9], charge localization, as these properties are known to impact the susceptibility of DNA to base damage, repair and mutation. The fractions of one water coordination increased along the A[9] and A[6] structures in a 5′ to 3′ direction, irrespective of flanking sequence composition, in concert with a decrease in minor groove width (Figure 4B and Supplementary Figure S4A) as predicted (37). Vstep, a measure of bp structural fluctuation, displayed a prominent peak of ∼40 Å3deg3 at the 5′-TA-3′ step for both structures (Figure 4C and Supplementary Figure S4B), which together with low water occupancy points to 5′-TA-3′ being a preferred location for base modification and mutation. In the G[9] and G[6] structures water coordination involved mostly two-water bridges due to wide (∼14 Å) minor grooves (Figure 4Dand Supplementary Figure S4C), whereas flexibility was modest (∼20–22 Å3deg3, Figure 4E and Supplementary Figure S4D). Thus, bp dynamics are likely to impact mutations at A-tracts to a greater extent than at G-tracts. Guanine has the lowest ionization potential (IP) of all four bases and IP further decreases at guanine runs, rendering them targets for electron loss, charge localization, oxidation and eventually mutation (4,38). Because after electron loss the ensuing charge (hole) can migrate along the DNA double-helix and relocalize at specific guanines, we addressed whether the preferred sites of mutation along G-tracts, i.e. G2–3 and G5, would also be preferred sites for charge localization. The QM/MM determinations indicated that whereas for the short G[6] fragment the difference in the density-derived atomic partial charges (DDAPC) (i.e. the hole) localized most often (∼50%) to the first position (Figure 4F), for the long G[9] fragment charge localization shifted downstream (mostly to the second, but also to positions 6–7, Figure 4G). Importantly, the charge was found exclusively around the guanine rings (Figure 4H). Thus, the two main sites of sequence change along G-tracts, i.e. G2–3 and G5, coincide with positions where charge localization and hence one-electron oxidation reactions is predicted to occur most frequently. In summary, bp flexibility at A-tracts and charge transfer at G-tracts likely represent intrinsic DNA features underlying the bias in SNV and insertions at mononucleotide runs in human genomes.

Figure 4.

MD and QM/MM simulations. (A) Molecular modeling of one (left) and two (right) minor groove water bridge coordination. (B) Fraction of one-water bridge occupancy (left axis) at A[9] DNA sequences flanked 5′ and 3′ by a T (black circles), C (red circles) or G (green circles). Minor groove widths (right axis), as determined from intrastrand phosphate-to-phosphate distances. (C) Vstep for A[9] DNA sequences, determined as the product of the square root of the eigenvalues (λi) described by the six bp step parameters shift, slide, rise, tilt, roll and twist; i.e. Vstep=6i=1λi−−√. (D) Fraction of one- (black circles) and two-water (red circles) bridge occupancy (left axis) at G[9] DNA sequences. Minor groove widths (right axis), as assessed from intrastrand phosphate-to-phosphate distances. (E) Vstep for G9 DNA sequences. (F) Average charge redistribution (open circles and right axis) for G[6] DNA structures upon vertical ionization, examined by calculating the difference on the density-derived atomic partial charges (DDAPC) for the neutral and negatively charged states. Histogram of the number of instances (left axis) in which the largest charge redistribution occurred at a specific position along the G[6] structures. (G) DDAPC for G[9] DNA structures (open circles and right axis) and histogram of the number of instances (left axis) in which the largest charge redistribution occurred at a specific position. (H) VMD rendering of a G[9] DNA structure displaying hole localization at G2. Capped base pairs were removed for clarity.

Position and orientation along nucleosome core particles modulate sequence variation

DNA wrapped around histones in nucleosomes is subject to local deformation (39), which may impact mutation. Thus, we analyzed the 1KGP SNVs at A- and G-tracts predicted to overlap with well-positioned nucleosome core particles (NCPs) (16). In hg19, the percentage of tracts that overlap with NCPs decreased moderately from ∼90% at length of 4 to 81% and 71% for A- and G-tracts of length 13, respectively (Figure 5A), suggesting that mononucleotide runs are not depleted in NCPs in human genomes as previously proposed (40). A-tracts of lengths 4–8 base pairs displayed distinctive peaks along the NCP surface in phase with the helical repeat of DNA (10.5 bp) and with minor grooves facing toward the inner protein core (lengths 4–5) (16) (Figure 5B and Supplementary Figure S5A). A-tracts of length of 9–13 bp exhibited only half (six) the peaks evident for the shorter tracts. For the G-tracts, only small peaks with no clear minor groove-inward-facing regions were detected (Supplementary Figure S5B).

Figure 5.

Positioning along nucleosome core particles. (A) Percent of A-tract (open circles) and G-tract (closed circles) base pairs in hg19 overlapping with well-positioned NCP genomic coordinates as a function of tract length. (B) Counts of base pairs in hg19 A-tracts of length 5 overlapping with NCPs genomic regions as a function of distance from the histone octamer dyad axis. Minor groove-inward-facing regions (gray) were derived from the X-ray crystal structure of NCP147 (41). (C) Percent SNVs in the 1KGP dataset (left axis) at every bp along A-tracts of length 5 for tracts centered at maxima (black) and minima (gray) along NCPs (Figure 5B). Percent increase (right axis) of SNVs at minima relative to maxima (green). P-values for paired t-tests: 0.013 (*), 0.002 (**) and 4.7 × 10−6 (***). (D) Whisker plots of%SNVs (left axis) at A1 for A-tracts of length 5 centered at maxima and minima (black) along NCPs (Figure 5B). Percent difference (right axis) in the number of A-tracts of length 5 in hg19 preceded by C, T or G (red) between those centered at minima and those centered at maxima (Figure5B). (E) C-containing/G-containing ratios (see text) for G-tracts of length 5 in hg19 as a function of distance from the NCP dyad axis (black) and location of core histones (maroon and green). Peaks correspond to negative iSAT (i.e. tilt parameters multiplied by the corresponding sin θ) values (gray) (39). Ratios of%SNV at G1 (upshifted by 0.5 for clarity) between C-containing (5′-CCCCCG-3′ sequences on the hg19 forward strand) and G-containing (5′-CGGGGG-3′ sequences on the hg19 forward strand) (Figure 1A) CG[5] tracts mapping NCP Chip-seq genomic intervals (red) fitted by a non-parametric local regression (loess; sampling proportion, 0.100; polynomial degree, 3). (F) VMD rendering (top) of TATTT residues 34–38 (yellow) and the complementary AAATA residues 672–753 (pink) from the 1EQZ pdb nucleosomal crystal structure, corresponding to peak area from −40 to −36 in Figure 5E. The switch in G-tract (lengths of 5 and 7) orientation along NCPs (bottom) serves to position the C-containing strand on the outside (yellow) and, correspondingly, the G-containing strand on the inside (pink).

 To assess if tract-positioning along NCPs influences SNVs, we selected A-tracts of lengths 5, 7 and 9 bp and G-tracts of lengths 5 and 7 bp whose central positions coincided with either the maxima or minima (41) (Figure 5B and Supplementary Figure S5A and B) and conducted pair-wiset-tests (330 total) between permutations of ‘categories’, including ‘tracts centered at maxima versus minima’, ‘position along the tracts’, ‘flanking sequence composition’, ‘specific NCP locations’ and ‘tract orientation’. For A-tracts, 79/207 (38%) significant pairs were found, 68 (86%) of which were related to differences between tracts centered at maxima versus minima, with a preponderance (63%) of tests displaying increased %SNVs at minima (Supplementary Figure S5C and E). For example, %SNVs at length 5 bp were greater at minima than at maxima at each position along the A-tracts (Figure 5C). A→C substitutions at A1 were more abundant at maxima than at minima (mean ± SD, 18.7 ± 0.7% at max and 17.6 ± 0.8% at min; P-value 0.001), whereas A→T substitutions at the same position displayed the opposite trend (mean ± SD, 18.4 ± 0.5% at max and 19.8 ± 1.1% at min; P-value 0.0005) (Figure 5D). A-tracts of length 7 also exhibited a similar pattern at A7 (Supplementary Figure S5H). The percentages of CA[5] and A[7]C tracts in hg19 centered at maxima were greater than at minima and the reverse was observed for the TA[5] and A[7T] tracts (Figure 5D and Supplementary Figure S5H). Thus, we conclude that positioning along the NCP surface of both the double-helical grooves and junctions with flanking base pairs influence SNVs along A-tracts. However, this influence is complex and for the most part, difficult to predict.

For G-tracts, most pairwise comparisons (18/34, 53%) indicated SNV variation according to sequence orientation (Supplementary Figure S5F and G). In hg19, the ratio of the numbers of G-tracts of lengths 5 and 7 for which the C-containing strand coincided with the forward sequence (downstream example sequence in Figure 1A) to the numbers of G-tracts for which the G-containing strand coincided with the forward sequence (upstream example sequence in Figure 1A) (C-containing/G-containing ratios) displayed a prominent 10.5-bp oscillation in phase with iSAT (Figure 5E), a measure of ‘inside’ and ‘outside’ bases, according to the bp step tilt parameter (39). Analysis of the helical path of a 146-bp DNA fragment wrapped around histones showed that the oscillation in the C-containing/G-containing ratios corresponds to a preference for guanine bases to face the protein core (Figure 5F). We analyzed the subset of G-tracts preceded by a 5′ C (i.e. CG[5]) to assess whether SNVs at G1, the position known to be mutable due to CpG methylation also oscillated with the C-containing/G-containing ratios. Oscillation in SNV-C-containing/SNV-G-containing values was evident, with peaks aligning to the hg19 troughs (Figure 5E) implying that the cytosines facing the protein surface harbor more variants than those facing away. We conclude that A- and G-tracts display preferential positioning (the former) and orientation (the latter) along NCPs, which in turn modulate the rate of sequence variation.

Mutations associated with human disease

Knowing that the first and last As of long A-tracts and G2–3 in G-tracts are the major sites of SNV in the human population, we addressed whether these features are also discernible in mutated mononucleotide tracts associated with human genetic disease. We collected 9,450,456 unique SBSs (both SBSs and SNVs refer to single base changes) from sequenced cancer genomes and normalized the percent mutations along A- and G-tracts to enable a direct comparison with the 1KGP dataset. For A-tracts (Figure 6A and Supplementary Figure S6A), SBSs displayed the same trend as the 1KGP data (Figure 2A) with respect to the bell-shape increase in mutations at A1 and An and the mutation spectra, although the susceptibility to mutation as a function of tract length attained greater values (6.36% for length 11 in cancer versus 4.15% for length 9 in the 1KGP datasets at A1). The first and last 3 bp also harbored more SBSs than in the 1KGP dataset for tracts >7 bp, a feature that we found to be due exclusively to a large cancer dataset (42) containing high-level microsatellite instability (MSI) samples (Supplementary Figure S6B and C), which are known to result from mismatch-repair deficiency (15). Thus, A-tracts display similar patterns of base substitution between the germline and somatic cancer tissues. For G-tracts, mutation spectra were characterized by G→T transversions at tract lengths >7, particularly at G1, the most frequently mutated position for tracts lengths up to 11 bp (Figure 6B and Supplementary Figure S6D). This trend persisted even when the high rates of methylation-mediated deamination mutations at the CG dinucleotide were removed (Supplementary Figure S6E). Thus, mutation patterns in cancer genomes contrast with those observed in the germline, both with respect to the most mutable position (G1 versus G2–3) and the types of base substitution (G→T in cancer genomes versus G→T and G→C in the germline).

Figure 6.

Mutation patterns in cancer genomes. (A) Mutation spectra for SBSs at A-tracts. Percent values were obtained by dividing the total number of SBSs at each position by the number of tracts in hg19 and then multiplying by 3.2516 to equalize the percentage of A-tracts of length 4 between the cancer genomes and the 1KGP datasets. (B) Mutation spectra for SBSs at G-tracts in cancer genomes. Percent values were obtained as in (A) using a multiplication factor of 3.7419. (C) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage, obtained by dividing the number of events by both the number of tracts in hg19 and tract length. (D) Indels at A-tracts, calculated as described in Figure 3C. (E) Indels at G-tracts, calculated as described in Figure3C. (F) Heatmap representation of insertions along G-tracts, as described in Figure 3E.

 With respect to slippage, the fractions for A-tracts elicited an excess at lengths 9 and 10 bp relative to the 1KGP dataset, which was also due to the MSI-containing dataset. For G-tracts, the fractions peaked at length 8, as for the 1KGP dataset (Figures 3A and 6C), implying that the propensity to undergo slippage is indistinguishable between the germline and soma. Indels were also more abundant at flanking base pairs than along the tracts (Figure 6D and E), particularly for G-tracts of length >7, similar to the 1KGP dataset (Figure 3C and D). Detailed analyses of insertions revealed that both G1 and the preceding position were the most significant sites of mutation (F-values up to 0.08 at G1 for tracts of length 8) (Figure 6F). Thus, the 5′ end of long G-tracts is the most susceptible site for both SBSs and insertions in cancer genomes, in contrast to the germline where these occur within the runs, typically at G2–3.

We also extracted the mutated A- and G-tracts from the Human Gene Mutation Database (HGMD), a collection of >150,000 germline gene mutations associated with human inherited disease. A total of 1519 genes were mutated at A- or G-tracts out of a total of 3972 (38%); 3480 SBSs and 2866 slippage events were noted within these tracts, 85 and 46% of which were predicted to be disease-causing, respectively (Figure 7A and Supplementary Table S1). Ranking genes by the number of literature reports indicated that among the top 10 entries three were associated with cancer (BRCA1, BRCA2 and APC), two with hemophilia (F8 and F9), four with debilitating lesions of the skin (COL71A), muscle (DMD), lung (CFTR) and kidney (PKD1), with one causing hypercholesterolemia (LDLR) (Figure 7B). Thus, mutations within A- and G-tracts carry a high social burden by contributing to some of the most common human pathological conditions.

Figure 7.

Mutation patterns in HGMD and model for sequence context-dependent changes. (A) Number of germline SBSs and slippage events (Slip.) at A- and G-tracts in HGMD. Gene alterations were classified as disease-causing mutation (DM), likely disease-causing mutation (DM?), disease-associated and putatively functional polymorphism (DFP), disease-associated polymorphism with additional supporting functional evidence (DP) and invitro/laboratory orinvivo functional polymorphism (FP). Codon changes (SIFT predictor) were classified as damaging (d), null (n), tolerated (t) and low-confidence prediction (l). (B) The 10 most commonly reported genes in HGMD with mutations at A- and G-tracts. Various mutated tracts were generally reported for the same gene in different reports. (C) Mutation spectra for SBSs at A- (left) and G-tracts (right) in HGMD. Percent values were obtained by dividing the total number of SBSs at each position by the number of tracts in hg19 exons. A|G→T (black), A|G→C (red), A→G (green), G→A (cyan). (D) Normalized fractions of A-tracts (closed circles) and G-tracts (open circles) displaying +/−1 bp slippage, obtained by dividing the total number of events by the number of tracts in hg19 exons and by tract length. (E) Model for sequence context-dependent changes at A-tracts (left) and G-tracts (right). *, site of base modification.

 For both A- and G-tracts, SBSs occurred mostly at tract lengths of 4–7, with patterns more similar to those in the 1KGP than in the cancer datasets, both with respect to the location of the most mutable positions (first and last As and first/second Gs) and the types of base substitution (A→T and G→H) (Figure 7C and Supplementary Figure S6F). Likewise, slippage events peaked at tract lengths of 7–9 as observed in the 1KGP dataset (Figure 7D). In summary, the patterns of both SBSs and slippage in the HGMD dataset followed the trend observed in the 1KGP dataset, suggesting that germline variants at mononucleotide repeats leading to either population variation or human inherited disease may have arisen through similar mechanisms.
DISCUSSION

Why are specific A:T and G:C base pairs within A- and G-tracts more susceptible to sequence changes than their identical neighbors? For A-tracts, bp flexibility may play a role. Chemical damage to DNA, such as by hydroxyl radicals has been shown to be proportional to the geometrical solvent-accessible surface of the atomic groups, which increases with DNA flexibility (43). Along A-tracts flexibility is restricted, but it is high at both the 5′ and 3′ junctions. Thus, the fact that the highest rates of mutation coincide with the highest degree of flexibility at the 5′-TA-3′ bp step is consistent with the view that this position may be susceptible to DNA damage as a result of flexibility. Other sources of DNA dynamics are also likely to be relevant, such as sugar flexibility at the junctions, which increases with tract length (44). Chemical modification at these junctions may then lead to base substitution and indels, the latter as a result of strand breaks.

With respect to SNV mutation spectra, these were found mostly in the direction of flanking base composition above a length of 7–8 bp. We interpret this behavior in terms of DNA slippage along A-tracts when attempts are made during translesion synthesis (TLS) to bypass a damaged site (Figure 7Ei). Two scenarios may be considered to account for A→T transitions at A1. In the first, the last tract-template base would loop out into the polymerase active site permitting base-pairing and strand elongation (Figure 7Eii) using the tract-flanking base as a template (34,4546). In the second (Figure 7Eiii), slippage would occur behind the polymerase, prompting extension past the newly created A*:T mispair generated by primer/template misalignment. Either pathway would yield a common intermediate (Figure 7Eiv) that contains the base complementary to the junction across from the damaged site upon slippage resolution (34). Following DNA synthesis (S) and/or repair (R) (Figure 7Ev and vi), this mispair will generate a base change that is always identical to the tract-flanking base.

For G-tracts, the high rates of G→T transversions at G1 in cancer genomes are also consistent with preferred chemical attack at this site due to high flexibility (Figure 7F top). Direct chemical attack at a guanine is known to result in stable products, such as 8-oxo-G and Fapy-G, both of which are known to yield G→T transversions (4750). Thus, G1 may be the most susceptible site for such reactions for G-tracts of lengths ≥7 (Figure 7Fright), which in cancer genomes would become a mutation hotspot. In the germline, SNVs peaked inside G-tract base pairs, while mutational spectra were insensitive to flanking base composition; these events are inconsistent with a role for template misalignment and slippage as noted for A-tracts. Rather, the correspondence between hotspot mutations at G2–3 and G5 and the QM/MM simulations suggest a role for charge transfer. A large body of work during the past 20 years using computational, theoretical chemistry and biophysical techniques on short oligonucleotides, has shown that guanine is the most easily oxidizable base in DNA and that indeed a guanine radical cation can be generated through long-range hole transfer from an oxidant via one-electron oxidation mechanisms (5155). GGG triplets were found to act as the most effective traps in hole transfer by both experimental and theoretical work (5659), demonstrating that the resulting guanine radical cation (or its neutral deprotonated form) became rather delocalized, but it preferentially centered at the first and second G. These well-established patterns of chemical reactivity are consistent with our experimental observation of high mutation frequencies at G1 for short G-tracts and the results from QM/MM simulations on G6. For longer tracts, the downstream shift in mutation hotspots, i.e., G2–3 and G5, also correlate well with the charge localization predicted from QM/MM simulations, which explicitly included solvent effects and structural fluctuations. Thus, in conjunction with the constrained density functional theory (60), both the neutral and oxidized forms of a guanine nucleobase can be reliably constructed to infer the accurate determination of mutational patterns of mononucleotide repeats in human genomic DNA.

The compact organization of the sperm genome (61), and presumably low levels of oxidative stress in the germline, may enable guanine oxidization through one-electron oxidation reactions rather than by direct chemical attack, thereby favoring the formation of radical cations. A charge injected at G1 by electron loss would then migrate to neighboring guanines and localize at sites of low IP, such as G2 (Figure 7F left). Guanine radical cations are known to readily undergo further chemical modification leading to products such as 8-oxo-G, oxazolone, imidazolone, guanidinohydantoin, and spiroiminodyhydantoin (62) (M in Figure 7F), to yield G→T, G→C and G→A substitutions (4,63). Our model is in line with recent observations in which mutations at guanines within short G-runs (1–4 bp) correlate with sequence-dependent IPs at the target guanine in cancer genomes (9). Interestingly, these correlations were not observed in the germline (9). We interpret these composite observations as follows. The IP values for G-runs have been shown to decrease asymptotically with tract length, although the absolute values vary according to the methods and assumptions used (we obtained a value of 5.43 eV for both G[6] and G[9]) (64,65). We suggest that short G-runs with high IPs undergo one-electron oxidation reactions in the oxidative environment of cancer cells but would be refractory to such a mechanism in the germline (Figure 7Fright yellow and left white sectors). As length increases and IP values fall, G-runs would be attacked directly by oxidants abundant in tumor cells (Figure 7F orange sector), whereas oxidation will be limited to electron loss in the germline environment (Figure 7F left yellow sector).

These models (template misalignment for A-tracts and charge transfer for G-tracts) suggest a more complex scenario for mechanisms underlying mononucleotide repeat polymorphism in the human population than recently proposed (13), in which nucleotide misincorporation by error-prone polymerases is proposed as a primary source of mutations at both A- and G-tracts. As already stated, the directionality of SNVs toward tract-flanking bases in A-tracts and the hotspot mutations at G2–3, supports multiple and distinct mechanisms of base substitution at mononucleotide repeats.

Our analyses highlight additional information, including the lack of mutations in the direction of tract-base composition for base pairs flanking long tracts, the association with gene expression and the preference of guanines for the inner NCP surface, and extend prior observations (12) such as the bell-shape character of base substitution and slippage, whose mechanisms remain to be fully clarified. Finally, we document the contribution of mononucleotide mutagenesis to key aspects of human pathology beyond the well-established MSI instability in cancer (15), including hemophilia and tissue degeneration. Our collective work supports the conclusion that as the human genome undergoes evolutionary diversification and along the way suffers disease-associated mutations, oxidation reactions including charge transfer may play a prominent role.

SUPPLEMENTARY DATA

Supplementary Data are available at NAR Online.

 

 

Mutation analyses and prenatal diagnosis in families of X-linked severe combined immunodeficiency caused by IL2Rγ gene novel mutation

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Genet. Mol. Res. 14 (2): 6164 – 6172   DOI: 10.4238/2015.June.9.2
Severe combined immunodeficiency diseases (SCIDs) are a group of primary immunodeficiency diseases characterized by a severe lack of T cells (or T cell dysfunction) caused by various gene abnormalities and accompanied by B cell dysfunction (WHO, 1992; Buckley et al., 1997). The incidence rates in infants were 1/75,000-1/10,0000 (WHO, 1992), but no morbidity statistics are available in China. The 2 genetic modes of SCID include X-linked recessive and autosomal recessive genetic inheritance. X-linked severe combined immunodeficiency (X-SCID) is the most common form, accounting for 50-60% of SCID cases (Noguchi et al., 1993). Immune system abnormalities in patients with X-SCID include T-B+NK-, in which T cells (CD3+) and natural killer (NK) cells (CD16+/CD56+) are absent or significantly reduced, and the number of B cells (CD19+) is normal or increased, causing reduced immunoglobulin production and class switching disorder (Buckley, 2004; Fischer et al., 2005). The IL- 2Rg gene mutation has been confirmed to be a major cause of X-SCID (Noguchi et al., 1993). In recent years, great progress has been made in understanding the pathogenesis of primary immunodeficiency disease and its application in clinical treatment, particularly regarding the development of critical care medicine and immune reconstruction technology. With timely control of infection and early bone marrow or stem cell transplantation, X-SCID patients can be treated, prolonging survival time. Therefore, early diagnosis of X-SCID is very important for patient treatment. Gene diagnosis has become a better early diagnosis or differential diagnosis method. In addition, familial X-SCID brings a great psychological burden to the relatives of patients. Ordinary chromosome analysis and immunological evaluation cannot be used for female carrier identification and fetal diagnosis, and gene diagnosis is the most effective method of carrier detection and prenatal diagnosis. In this study, we detected mutations in 2 families with X-SCID and identified 2 novel mutations, confirming the X-SCID pedigrees. Prenatal diagnosis was performed for the pregnant fetus in the mother of one of the probands based on gene diagnosis. Female individuals in this family were subjected to carrier detection.
IL2Rg gene mutation test Direct sequencing of 1-8 exons and the flanking region of the IL2Rg gene by PCR in family 1 showed that the 3rd exon of the proband contained the c.361-363delGAG heterozygous deletion mutation, which led to deletion of the 121st amino acid glutamate (p.E121del) in its coding product. There were no sequence variations in other coding regions or in the shear zone. The proband’s mother carried the same heterozygous mutation, while his father did not carry the mutation site (Figure 2a, b, c). This mutation was not observed in any cases of the control group, and this family was identified as an X-SCID family. The c.510-511insGAACT insertion heterozygous mutation was present in the 4th exon of the proband’s mother in family 2. This mutation was a 5-base repeat of GAACT, resulting in a change in amino acid 173 from tryptophan into a stop codon (p.W173X). While there were no sequence variations in other coding regions or in the shear zone, the patient’s father did not carry the mutation (see Figure 2d, e). We did not find this mutation in the healthy control group. We presumed that the 4th exon of the deceased child in family 2 contained the c.510-511insGAACT insertion mutation, leading to X-SCID symptoms, and thus we speculated that this family was an X-SCID pedigree. Prenatal diagnosis We verified the chorionic villus status of the fetus in family 1 using the PowerPlex 16 HS System kit. The results of prenatal diagnosis showed that the fetal tissue contained no maternal contamination and that this fetus was female. The results of prenatal diagnosis showed that there was no c.361-363delGAG (p.E121del) heterozygous mutation in the female fetus of family 1.
Figure 2. Sequencing graph of IL2Rg gene in 2 pedigrees with X-chain severe combined immunodeficiency. a.-c. Family 1. a. Normal control (rectangle indicates 3 edentulous bases of this patient). b. Proband carrying the c.361- 363delGAG (p.E121del) mutation (arrow indicates deletion of fragment connection sites). c. The proband’s mother contained a c.361-363delGAG (p.E121del) heterozygous mutation (arrow). d.-e. Family 2. d. The proband’s mother carried the c.510-511insGAACT (p.W173X) heterozygous mutation (arrow indicates that the reverse sequencing graph was positive). e. Normal control (rectangular box indicates 2 normal copies of GAACT (the mutation fragment was 3 copies). Carrier detection results For the c.361-363delGAG (p.E121del) site, the gene analysis results of the female individual in family 1 showed that I2 (proband’s grandmother) was a heterozygous carrier and that II3 (proband’s aunt) was a non-carrier and had no mutations.
IL-2 can combine with the IL-2 receptor (IL-2R) of the immune cell membrane. IL-2R is composed of 3 subunits, including the IL-2Ra chain (CD25), IL-2Rb chain (CD122), and IL- 2Rg chain (CD132). IL-2Rg functional units in common with IL-4, IL-7, IL-9, IL-15, IL-21, and other cytokine receptors, and these regions are referred to as the total chain (Li et al., 2000). The IL-2Rg chain can maintain the integrity of the IL-2R complex and is required for the internalization of the IL-2/IL-2R complex; it is also the link that contacts the cell membrane surface factor region and downstream cell signal transduction molecules. Therefore, the integrity of the IL-2Rg chain is vital for the immune function of an organism (Malka et al., 2008; Shi et al., 2009).
Mutations in the IL2Rg gene, which encodes IL-2Rg, were identified to be a major cause of X-SCID in 1993 (Noguchi et al., 1993). The IL2Rg gene is located on chromosome X q21.3-22, is 37.5 kb length, and contains 8 exons, which encode 369 IL-2Rg amino acids. The IL2Rg chain exhibits varying structural regions, such as the signal peptide [amino acids (AA) 1-22], extracellular domain (AA 23-262), transmembrane region (AA 263-283), and intracellular region (AA 284-369). The WSXWS motif is located in the extracellular region (AA 237-241), while Box 1 is located in the intracellular region (AA 286-294).
By the end of 2013, the Human Gene Mutation Database contained a total of 200 mutations in the IL2Rg gene (HGMD Professional 2013.4). The most common mutation types in the IL2Rg gene were the missense or nonsense mutations, which result from single base changes. A total of 100 missense or nonsense mutations have been identified, followed by insertion or deletion mutations in a total of 50 species. The 3rd most common type of mutations includes shear mutations in approximately 30 species. Eight exons contained mutations, and mutations in 3rd or 4th exons were the highest, accounting for a total mutation rate of 43% (86/200). According to the X-SCID gene database (IL2RGbase) (http://research.nhgri. nih.gov/scid/), the gene mutations in IL2Rg mainly occurred in the extracellular region of the IL2Rg chain (Fugmann et al., 1998). Zhang et al. (2013) reported that the IL2Rg gene mutations in 10 patients with X-SCID in China were located in the extracellular region. Two mutations reported in our study were also located in the extracellular region. The mutation of IL2Rg gene in family 1 was a codon mutation in the 3rd exon, resulting in a 3-base deletion. The c.361-363delGAG (p.E121del) mutation was located in the extracellular area of the IL- 2Rg subunit, and we inferred that the 121 glutamate deletion caused by the mutation would lead to changes in the structure of the peptide chain, affecting signal transmission and resulting in serious symptoms. The mutation of family 2 was a GAACT repeat of ILR2g gene; this repeat of 5 bases resulted in 173 codon changes from tryptophan into a stop codon. Generation of the peptide chain with the mutation lacked 196 amino acids compared to the normal chain, including the intracellular, transmembrane, and some extracellular regions, directly affecting the structure and function of receptors and causing disease. No studies have been reported regarding these 2 mutations. We combined with the mutation characteristics and clinical manifestations and diagnosed family 1 as X-SCID pedigrees. Although the patient in family 2 was deceased, it can be speculated that the 2 deceased patients in family 2 were X-SCID pedigrees caused by c.510-511insGAACT (W173X).
Prenatal diagnosis can accurately identify fetal situations and be used to avoid birth defects, which can also ease the anxiety of the pregnant mother. Gene diagnosis for pedigrees of patients based on DNA samples has advanced recently, particularly with the application of high-throughput sequencing technology (Alsina et al., 2013). We can now perform gene analysis for varied clinical infectious diseases for differential diagnosis. However, the effectiveness of prenatal diagnosis for pedigrees in which the proband is dead remains unclear. Because the gene mutations in the proband is unknown in these cases, the patient’s situation was only inferred by his mother’s genotypes. However, we considered that for the deceased, if we can define the mother was a pathogenic gene carrier, even if the proband is not X-SCID, the woman also has a risk of having X-SCID children and this pedigree may be X-linked recessive inheritance. Prenatal diagnosis may provide a choice for preventing the birth of patients in these families in the premise of informed consent.
Gene diagnosis of IL2Rg can also be used for carrier detection of suspected females in the family.
In the present study, we performed carrier detection of the patient’s grandmother and aunt in family 1 and determined that the patient’s pathogenic mutations were from his grandmother. His aunt did not inherit the pathogenic gene, and thus she was a non-carrier and her fertility will not be affected. In this study, we used direct sequencing of PCR products and identified IL2Rg gene mutations in 2 pedigrees with X-SCID. We found 2 unreported mutations in the IL2Rg gene, and prenatal diagnosis and carrier detection were conducted in 1 X-SCID family. Because the incidence rate of X-SCID is extremely low, it is difficult to promote the widespread use and application of genetic diagnosis. However, this study may provide some implications for the diagnosis of infants with immunodeficiency, and gene diagnosis techniques such as conventional or high-throughput sequencing should be used as soon as possible during pregnancy, which can be used to guide treatment. This method can also provide reliable prenatal diagnosis and carrier detection service for these families.
MEF2A gene mutations and susceptibility to coronary artery disease in the Chinese population
J. Li1 , H.-X. Chen2 , J.-G. Yang3 , W. Li3 , R. Du3 and L. Tian3       DOI http://dx.doi.org/10.4238/2014.October.20.15
Coronary artery disease (CAD) has high morbidity and mortality rates worldwide. Thus, the pathogenesis of CAD has long been the focus of medical studies. Myocyte enhancer factor 2A (MEF2A) was first discovered as a CAD-related gene by Wang (2005) and Wang et al. (2003, 2005). Three mutation points in exon 7 of MEF2A were subsequently identified by Bhagavatula et al. (2004); however, Altshuler and Hirschhorn (2005) and Weng et al. (2005) predicted that the MEF2A gene lacked mutations. Zhou et al. (2006a,b) analyzed the mutations and polymorphisms in exons 7 and 11 of the MEF2A gene in the Han population in Beijing, and various rare mutations were found in exon 11 rather than in exon 7. The clinical significance of specific 21-bp deletions in MEF2A was also explored, and previous studies have shown mixed results. In this study, polymerase chain reaction-singlestrand conformation polymorphism (PCR-SSCP) and DNA sequencing were used to detect exon 11 of the MEF2A gene in samples collected from 210 CAD patients and 190 healthy controls and to investigate the function of the MEF2A gene in CAD pathogenesis and their correlation.
CAD, a common disease in China, is induced by multiple factors, such as genetics, the environment, and lifestyle. Thus, a multi-faceted approach is necessary in the study of CAD pathogenesis, particularly in molecular biology research, which is important for developing comprehensive treatment of CAD based on gene therapy. The MEF2A gene was first identified as a CAD-related gene through linkage analysis of a large family with CAD (9 of 13 patients developed MI) in 2003.
In this study, we found the following mutations: 1) codon 451G/T (147191) heterozygous or homozygous mutation; 2) loss of 1 (Q), 2 (QQ), 3 (QQP), 6 (425QQQQQQ430), and 7 (424QQQQQQQ430) amino acids (147108-147131); and 3) codon 435G/A (147143) heterozygous mutation. Among these mutations, the synonymous mutation at locus 147191 was confirmed by reference to the National Center for Biotechnology Information (NCBI) database to be a single nucleotide polymorphism, which was also demonstrated in our study by the extensive presence of this polymorphism in healthy controls. However, the heterozygous mutation at locus 147143 was only found in the genomes of CAD patients, and was therefore identified as a mutation.
Given that MEF2A is a CAD-related gene, the results of various studies are controversial among several countries. Weng et al. (2005) screened gene mutations in exon 11 of the MEF2A gene from 300 CAD patients and 1500 healthy controls. They hypothesized that the changes in 5-12 CAG repeats are genetic polymorphisms and that the 21-base deletion in exon 11 of the MEF2A gene did not induce autosomal dominant genetic CAD. Gonzalez et al. (2006) suggested that the CAG repeat polymorphism was independent of MI susceptibility in Spanish patients. Kajimoto et al. (2005) reported that the CAG repeat sequence was not correlated with MI susceptibility in Japanese patients. Horan et al. (2006) also found that the CAG repeat sequence was not associated with the susceptibility to early-onset familial CAD in an Irish population. Hsu et al. (2010) identified no correlation between the CAG repeat sequence and CAD susceptibility in the Taiwanese population. Dai et al. (2010) found that the structural change in exon 11 was not related to CAD in the Chinese Han population. Lieb et al. (2008) and Guella et al. (2009) hypothesized that MEF2A was independent of CAD. However, Yuan et al. (2006) and Han et al. (2007) suggested that the CAG repeat sequence was correlated with CAD because 9 CAG repeats was an independent predictor of CAD. Elhawari et al. (2010) and Maiolino et al. (2011) suggested that MEF2A is a susceptibility gene for CAD. Dai et al. (2013) showed that mutations in exon 12 are associated with the early onset of CAD in the Chinese population. Liu et al. (2012) failed to demonstrate a correlation between the CAG repeat sequence and CAD through case-control analysis, systematic review, and meta-analysis, but found that the 21- base deletion in exon 11 was strongly associated with CAD, and that genetic variations in MEF2A may be a relatively rare, but specific, pathogenic gene for CAD/MI. Kajimoto et al. (2005) reported 4-15 CAG repeats. However, only 4-11 CAG repeats were observed in our study, possibly because of genetic differences in patients in this study. Eleven CAG repeats were observed in most samples from the control group, and the proportion of 10, 9, and 8 repeats exceeded 1%. The heterozygous mutation at 147143, as well as the 4 and 5 CAG repeats, was only observed in CAD patients. Thus, we speculated that the CAG repeat sequence is correlated with CAD susceptibility, and the presence of 4 or 5 repeats may be a risk factor for CAD, which was inconsistent with the results obtained by Han et al. (2007). The inconsistency in these results may be explained by the differences in subjects and sample sizes among studies.
Impact of glucocerebrosidase mutations on motor and nonmotor complications in Parkinson’s disease

Homozygous and compound heterozygous mutations in GBA encoding glucocerebrosidase lead to Gaucher disease (GD). A link between heterozygous GBAmutations and Parkinson’s disease (PD) has been suggested ( Bembi et al., 2003,Goker-Alpan et al., 2004, Halperin et al., 2006, Machaczka et al., 1999, Neudorfer et al., 1996, Tayebi et al., 2001 and Tayebi et al., 2003). In 2009, a 16-center worldwide analysis of GBA revealed that heterozygous GBA mutation carriers have a strong risk of PD ( Sidransky et al., 2009).

In addition, heterozygote GBA mutations not only carry a risk for PD development but also the possibility of some risk burden on the progression of PD clinical course. In cross-sectional analyses of GBA mutations in PD patients, earlier disease onset, increased cognitive impairment, a greater family history of PD, and more frequent pain were reported in patients with mutations, compared with no mutations ( Chahine et al., 2013,Clark et al., 2007, Gan-Or et al., 2008, Kresojevic et al., 2015, Lwin et al., 2004, Malec-Litwinowicz et al., 2014, Mitsui et al., 2009, Neumann et al., 2009, Nichols et al., 2009,Seto-Salvia et al., 2012, Sidransky et al., 2009, Swan and Saunders-Pullman, 2013 and Wang et al., 2012). Recently, a few prospective studies have investigated clinical features of PD with GBA and showed a more rapid progression of motor impairment and cognitive decline in GBA mutation cases than in PD controls ( Beavan et al., 2015, Brockmann et al., 2015 and Winder-Rhodes et al., 2013). However, in terms of motor complications such as wearing-off and dyskinesia, no studies exist in the longitudinal course of PD with GBA mutations.

Here, we conducted a multicenter retrospective cohort analysis, and the data were investigated by survival time analysis to show the impact of GBA mutations on PD clinical course. We also investigated regional cerebral blood flow (rCBF) and cardiac sympathetic nerve degeneration of subjects with GBA mutations, compared with matched PD controls.

3.1. Subjects

Among the 224 eligible PD patients (the subjects were not related to each other), 9 subjects were excluded from the analysis (4 due to multiple system atrophy findings on subsequent brain MRI and 5 because of insufficient clinical information). Therefore, 215 PD patients [female, 52.1%; age, 66.7 ± 10.8 (mean ± standard deviation)] were analyzed. For non-PD healthy controls, 126 patients’ spouses (female, 58.7%; age, 67.3 ± 10.3) without a family history of PD or GD were enrolled.

3.2. GBA mutations and risk ratios for PD

In the PD subjects, we identified 10 nonsynonymous and 2 synonymous GBA variants. Within the nonsynonymous variants, 7 mutations were previously reported in GD [R120W, L444P-A456P-V460 (RecNciI), L444P, D409H, A384D, D380N, and444L(1447-1466 del 20, insTG)] as GD-associated mutations. Three nonsynonymous mutations have never been reported in GD patients [I(-20)V, I489V, and there was one novel mutation (Y11H)].

GD-associated GBA mutations were found in 19 of the 215 (8.8%) PD patients but none in the healthy controls. The risk of PD development relative to these GD-associated mutations was estimated as an OR of 25.1 [95% confidence interval (CI), 1.50–420,p = 0.0001] with 0-cell correction. The nonsynonymous mutations that were not reported in GD patients had no association with PD development (p = 0.506; OR, 1.3; 95% CI, 0.7–2.6) ( Table 1). Four subjects had double mutations. For subsequent analyses, 2 subjects with double mutations of I (-20)V and K466K were adopted to the group of mutations unreported in GD, and 2 subjects with double mutations of R120W and I(-20)V, and of R120W and L336L were adopted to the group of GD-associated mutations.

Table 1.Frequency of glucocerebrosidase gene allele in Parkinson’s disease patients and controls

Allele name PD (n = 215) Controls (n = 126) p Odds ratio (95% CI)
GD-associated mutations
 R120W 7a 0 0.050 9.1 (0.5–160.8)
 RecNciI (L444P-A456P-V460) 4 0
 L444P 4 0
 D409H 1 0
 A384D 1 0
 D380N 1 0
444L(1447-1466 del 20, insTG) 1 0
 Subtotal, n (%) 19 (8.8%) 0 (0%) <0.001 25.1 (1.5–419.8)b
Nonsynonymous mutations not reported in GD
 I(-20)V 27a 13 0.603 1.3 (0.6–2.5)
 I489V 3 0
 Y11Hc 0 1
 Subtotal, n (%) 30 (14.0%) 14 (11.1%) 0.506 1.3 (0.7–2.6)
Synonymous, n
 K466K 2a 1
 L336L 1a 0
Allele names refer to the processed protein (excluding the 39-residue signal peptide).

Key: CI, confidence interval; GD, Gaucher disease; PD, Parkinson’s disease.

a Four subjects had double mutations; 2 of I(-20)V and K466K, 1 of I(-20)V and R120W, and 1 of R120W and L336L.
b Odds ratio was calculated by adding 0.5 to each value.
c Novel mutation.
3.3. Clinical features of PD patients by GBA mutation groups

The clinical features of PD patients with GD-associated mutations, those with mutations unreported in GD, and those without mutations are shown in Table 2. In the GD-associated mutation group, females, those with a family history and those with dementia (DSM IV) were significantly more frequent than those in the no-mutation group (p = 0.047, 0.012, and 0.020, respectively). The age of PD onset was lower in patients with GD-associated mutations (55.2 ± 9.9 years ± standard deviation), compared with those without mutations (59.3 ± 11.5), although the statistical difference was not significant. There were no differences in clinical manifestations between subjects with mutations unreported in GD and those without mutations, except for dopamine agonist dosage (p = 0.026) ( Table 2).

Table 2.Epidemiological and clinical features of PD patients with Gaucher disease–associated GBA mutations, those with mutations previously unreported in GD and those without mutations

Variables Total n = 215 Mutation (-) GD-associated mutations


Mutations unreported in GD


167 19a pb 29c pd
Sex Female, n (%) 83 (49.7) 14 (73.7) 0.047 15 (51.7) ns
Age Mean (SD) 67.0 (10.8) 62.2 (10.7) 0.063e 67.5 (11.2) nsf
Disease duration (y) Mean (SD) 7.7 (5.5) 6.9 (4.6) nsf 7.2 (4.9) nsf
Onset age Mean (SD) 59.3 (11.5) 55.2 (9.9) ns 60.3 (11.8) ns
Family history Yes, n (%) 17 (11.0)g 6 (31.6) 0.012 0 (0.0) ns
Dementia (DSM-IV) Yes, n (%) 29 (17.4) 9 (47.4) 0.020 5 (17.2) ns
MMSE Mean (SD) 25.8 (5.4)h 23.3 (7.7) nsf 27.0 (3.4)i nsf
Onset symptom (tremor vs. others) Tremor, n (%) 78 (46.8) 9 (47.4) ns 15 (51.7) ns
Modified H-Y on (<3 vs. ≥3) ≥3, n (%) 82 (49.1) 14 (73.7) 0.042 16 (55.2) ns
UPDRS part 3 Mean (SD) 23.6 (12.2)j 28.5 (13.8) nsf 21.9 (8.7) nsf
Wearing off Yes, n (%) 70 (41.9) 9 (47.4) ns 13 (44.8) ns
Dyskinesia Yes, n (%) 49 (29.3) 8 (42.1) ns 8 (27.6) ns
Mood disorder Yes, n (%) 43 (25.7) 8 (42.1) ns 7 (24.1) ns
Orthostatic hypotension symptom Yes, n (%) 21 (12.6) 5 (26.3) ns 7 (24.1) ns
Psychosis history Yes, n (%) 59 (35.3) 10 (52.6) ns 7 (24.1) ns
ICD history Yes, n (%) 8 (4.8) 1 (5.3) ns 1 (3.4) ns
Stereotactic brain surgery for PD Yes, n (%) 4 (2.4) 0 (0.0) ns 0 (0.0) ns
Agonist LED mg/d Mean (SD) 92.8 (114.2) 72.1 (137.7) nse 163.7 (155.6) 0.026e
Levodopa LED mg/d Mean (SD) 400.7 (184.2) 456.7 (206.9) nsf 369.2 (230.3) nse
Total LED mg/d Mean (SD) 496.4 (233.7) 537.9 (258.9) nsf 525.7 (287.4) nsf
Categorical data were examined by Fisher’s exact test.

Key: DSM-IV, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition; GBA, glucocerebrosidase gene; GD, Gaucher disease; H-Y, Hoehn and Yahr; ICD, impulse control disorder; LED, levodopa equivalent dose; ns, not significant; MMSE, Mini-Mental State Examination; PD, Parkinson’s disease; SD, standard deviation; UPDRS, Unified Parkinson’s Disease Rating Scale.

a Including a double-mutation subject (with a mutation unreported in GD).
b GD-associated mutations versus mutation (-).
c Two subjects with double mutation, including GD-associated mutations, were assigned to GD-associated mutation group.
d Other mutations versus mutation (-).
e Examined by Student t test after Levene’s test for equality of variances.
f Examined by Mann-Whitney U-test because of non-Gaussian distribution.
g    n = 155 due to 10 missing data.
h    n = 164 due to 3 missing data.
i     n = 28 due to 1 missing datum.
j     n = 165 due to 2 missing data.

3.4. Survival time analyses to develop dementia, psychosis, dyskinesia, and wearing-off

Time to develop clinical outcomes (dementia, psychosis, dyskinesia, and wearing-off) was compared in 19 subjects with GD-associated mutations, 29 with mutations unreported in GD, and 167 without mutation. The median observation time was 6.0 years. The subjects with GD-associated mutations showed a significantly earlier development of dementia and psychosis, compared with subjects without mutation (p < 0.001 and p = 0.017) ( Supplementary Table e-1, Fig. 1A and B). We rereviewed the clinical record of the subject who showed early dementia (defined by DSM IV) ( Fig. 1A) and made sure it did not satisfy the criteria of DLB ( McKeith et al., 2005).

Kaplan–Meier curves of dementia and psychosis in Parkinson's disease (PD) ...

Fig. 1.

Kaplan–Meier curves of dementia and psychosis in Parkinson’s disease (PD) patients with Gaucher disease (GD)-associated glucocerebrosidase gene (GBA) mutations and those without mutations. PD patients with GD-associated GBA mutations and those without GBA mutations were compared to investigate the time taken to develop dementia (A) and psychosis (B). Because of insufficient information in several patients, the numbers in each analysis were different. The patients with and without mutations were 17 and 165 (A), 18 and 165 (B) against a total of 19 and 167. DSM IV, Diagnostic and Statistical Manual of Mental Disorders, revised fourth edition. p-Values were calculated by log-rank tests.

The associations of GBA mutations and these symptoms were estimated as HRs, adjusting for sex and age at PD onset. HRs were 8.3 for dementia (95% CI, 3.3–20.9; p < 0.001) and 3.1 for psychosis (95% CI, 1.5–6.4; p = 0.002). The time until development of wearing-off and dyskinesia complications was not statistically significant, with HRs of 1.5 (95% CI, 0.8–3.1; p = 0.219) and 1.9 (95% CI, 0.9–4.1; p = 0.086) ( Table 3).

Table 3.Hazard ratios of GBA pathogenic mutations for clinical symptoms

Model Clinical feature Hazard ratio 95% CI p
1 Dementia (DSM-IV) 8.3 3.3–20.9 <0.001
2 Psychosis 3.1 1.5–6.4 0.002
3 Wearing-off 1.5 0.8–3.1 0.219
4 Dyskinesia 1.9 0.9–4.1 0.086
Each model was adjusted for sex and age at onset.

Key: CI, confidence interval; DSM-IV; The Diagnostic and Statistical Manual of Mental Disorders part 1IV; GBA, glucocerebrosidase.

Subjects with mutations unreported in GD did not show significant differences in time to develop all 4 outcomes, compared with no mutation subjects. Therefore, subjects with GD-unreported mutations were regarded as subjects without GBA mutations in further analyses.

3.5. rCBF on SPECT in patients with GD-associated GBA mutations

We conducted pixel-by-pixel comparisons of rCBF on SPECT between PD subjects with mutations (cases) and sex-, age-, and disease duration-matched PD subjects without any mutations in GBA (controls). Four controls were adopted for each case (except for a 34-year-old female case who was matched to a control), and in total 12 cases (female 50%, age at SPECT mean ± standard error (SE); 58.9 ± 3.3 years, disease duration at SPECT 7.3 ± 1.5 years) and 45 controls (female 64.4%, age at SPECT mean ± SE; 61.0 ± 1.3 years, disease duration at SPECT 7.1 ± 0.7 years) were analyzed. As a result, a significantly lower rCBF was seen in the cases compared to the controls in the bilateral parietal cortex, including the precuneus ( Fig. 2).

Regional cerebral blood flow in the group with GD-associated mutations compared ...

Fig. 2.

Regional cerebral blood flow in the group with GD-associated mutations compared with the matched Parkinson’s disease group without mutations. Regions with lower regional cerebral blood flow in the group with GD-associated mutations displayed on an anatomic reference map. Abbreviation: GD, Gaucher disease.

3.6. H/M ratios on MIBG scintigraphy in patients with GD-associated GBA mutations

Cardiac MIBG scintigraphy visualizes catecholaminergic terminals in vivo that are reduced as well as brain dopaminergic neurons in PD patients. We also investigated MIBG scintigraphy between 16 cases (female 68.8%, age at examination mean ± SE; 60.2 ± 2.6 years, disease duration at examination 6.2 ± 1.2 years) and sex-, age- and disease duration-matched 61 controls [(63.8 %, age 62.0 ± 1.1 years, disease duration 5.5 ± 0.6 years) (1:4 except for 1 young 34-year-old female case who was matched to a control)]. In the results, both early and late H/M ratios declined in both groups and did not show any significant differences (p = 0.309 and 0.244) ( Supplementary Table e-2).

4. Discussion

4.1. Contributions of GD-associated GBA mutations to the development of PD

In the analysis of 215 PD patients and 126 non-PD controls, we identified 10 nonsynonymous heterozygous GBA mutations, including 1 novel mutation. Among these mutations, 7 were GD-associated, and the patients carrying these mutations represented 8.8% of the PD cohort. No significant association was found between the GD-unreported mutations and PD development, which suggests that only the GD-associated mutations are a genetic risk for PD. According to a worldwide multicenter analysis of 1883 fully sequenced PD patients, 7% of the GD-associated mutations are found in non-Ashkenazi Jewish PD patients ( Sidransky et al., 2009). Although the mutation frequency in the present study was similar to previous results, the OR of GD-associated heterozygous mutations (25.1) was significantly greater than the OR (5.43) of other ethnic cohorts (Sidransky et al., 2009) and was consistent with an OR of 28.0 from a previous Japanese report ( Mitsui et al., 2009). These results, taken together, suggest the possibility thatGBA mutations are at a distinct risk for PD in the Japanese population. However, a larger Japanese cohort study is required to confirm this.

4.2. Cross-sectional clinical figures of PD with GBA mutations

Before the survival time analyses, we investigated clinical features at enrollment between mutation groups. The lower onset age, more frequent family history and dementia, and worse disease severity of PD in patients with GBA mutations, compared with those without mutations, were consistent with previous cross-sectional case-control reports ( Anheim et al., 2012, Brockmann et al., 2011, Chahine et al., 2013, Lesage et al., 2011, Li et al., 2013, Mitsui et al., 2009, Neumann et al., 2009, Seto-Salvia et al., 2012 and Sidransky et al., 2009). In contrast, female-predominance (73.7%, p = 0.047) in patients with mutations observed in the present study is inconsistent ( Neumann et al., 2009 and Seto-Salvia et al., 2012).

4.3. Impact of GBA mutations on the clinical course of PD

To investigate the impact of GBA mutations on the clinical course of PD, a prospective-designed study over a long period is preferred. Although there has been a few longitudinally designed study to date, follow-up clinical data for a median of 6 years of 121 PD cases from a community-based incident cohort was recently reanalyzed; results demonstrate that progression to dementia defined by DSM IV (HR 5.7) and Hoehn and Yahr stage 3 (HR 3.2) are significantly earlier in 4 GBA mutation-carrier patients compared with 117 patients with wild-type GBA ( Winder-Rhodes et al., 2013). A 2-year follow-up clinical report of 28 heterozygous GBA carriers who were recruited from relatives of GD-patients shows slight but significant deterioration of cognition and smelling, compared to healthy controls ( Beavan et al., 2015). Brockmann et al. (2015)assessed motor and nonmotor symptoms including cognitive and mood disturbances for 3 years in 20 PD patients with GBA mutations and showed a more rapid disease progression of motor impairment and cognitive decline in GBA mutation cases comparing to sporadic PD controls. The current long-term retrospective cohort study up to 12 years reinforced these results. It revealed that dementia and psychosis developed significantly earlier in subjects with GD-associated mutations compared with those without mutation, and the HRs of GBA mutations were estimated at 8.3 for dementia and 23.1 for psychosis, with adjustments for sex and PD onset age. In contrast, the results showed no significant difference in developing wearing-off and dyskinesia.

In this study, we also investigated whether GD-unreported mutations affected the clinical course of PD. In both cross-sectional and survival time analyses, the mutations unreported in GD carried no increased burden on clinical symptoms such as dementia, psychosis, wearing-off, and dyskinesia.

4.4. Reduced rCBF in PD with GBA mutations compared with matched PD controls

We found a significantly decreased rCBF, reflecting decreased synaptic activity, in the bilateral parietal cortex including the precuneus, in subjects with GD-associated mutations compared with matched subjects without mutations. The pattern of reduced rCBF was very similar to the pattern of H215O positron-emission tomography that Goker-Alpan et.al. (2012) reported, showing decreased resting rCBF in the lateral parietal association cortex and the precuneus bilaterally in GD subjects with parkinsonism (7 subjects with homozygous or compound heterozygous GBA mutations), compared with 11 PD without GBA mutations. Results suggest that PD with heterozygous GBAmutations and GD patients presenting parkinsonism had a common reduced pattern of rCBF. Interestingly, in their study, rCBF in the precuneus—but not in the lateral parietal cortex—correlated with IQ, suggesting that the involvement of the precuneus is critical for defining GBA-associated patterns.

4.5. Reduced cardiac MIBG H/M ratios as well as matched PD controls

We also showed that cardiac MIBG H/M ratios in subjects with GD-associated mutations were lower than the cutoff point for PD discrimination (Sawada et al., 2009), suggesting that postganglionic sympathetic nerve terminals to the epicardium were denervated, as well as in PD without mutations.

4.6. Mechanisms of impact on PD clinical course by GD-associated GBA mutations

Experimental studies suggesting a bidirectional pathogenic loop between α-synuclein and glucocerebrosidase have been accumulated (Fishbein et al., 2014, Gegg et al., 2012, Mazzulli et al., 2011, Noelker et al., 2015, Schondorf et al., 2014 and Uemura et al., 2015). Loss of glucocerebrosidase function compromises α-synuclein degradation in lysosome, whereas aggregated α-synuclein inhibits normal lysosomal function of glucocerebrosidase. The pathogenic loop may facilitate neurodegeneration in GD-associated PD brain, resulting in early development of dementia or psychosis as shown in the present study. Several recent researches propose the possibility that the similar mechanism as in PD with GBA mutations exists even in idiopathic PD brain ( Alcalay et al., 2015, Chiasserini et al., 2015, Gegg et al., 2012 and Murphy et al., 2014). On the other hand, the impacts of GD-associated GBA mutations for the development of motor complications such as wearing-off and dyskinesia were not statistically significant, suggesting other pathophysiological mechanisms in the striatal circuit brought out after long-term therapy especially by l-dopa.

4.7. Limitations

Our study has several limitations. In the design of the study, we assumed that the sample size was 215 (PD patients) for survival time analyses and investigated 224 PD patients. We assumed that the mutation prevalence would be 9.4%, and in fact, we found 19 patients with mutations (8.5%) of the 224 patients. Based on these figures, we estimated the risk ratios of heterozygous GBA mutations for the risk of PD development and PD clinical symptoms as ORs in the cross-sectional multivariate analyses, although the 95% CIs were broad. More of subject numbers will be needed to determine robust risk ratios.

Comprehensive Genetic Characterization of a Spanish Brugada Syndrome Cohort

PLOS   Published: July 14, 2015   DOI: http://dx.doi.org:/10.1371/journal.pone.0132888

Brugada syndrome (BrS) was identified as a new clinical entity in 1992 [1]. Six years later, the first genetic basis for the disease was identified, with the discovery of genetic variations inSCN5A [2]. Nowadays, more than 300 pathogenic variations in this first gene are known to be associated with BrS [3]. SCN5A encodes for the α subunit of the cardiac voltage-dependent sodium channel (Nav1.5), which is responsible for inward sodium current (INa), and thus plays an essential role in phase 0 of the cardiac action potential (AP). Genetic variations in this gene can explain around 20–25% of BrS cases [3].

Since BrS was classified as a genetic disease, several other genes have been described to confer BrS-susceptibility [47]. Pathogenic variations have been mainly described in: 1) genes encoding proteins that modulate Nav1.5 function, and 2) other calcium and potassium channels and their regulatory subunits. All these proteins participate, either directly or indirectly, in the development of the cardiac AP. Although the incidence of pathogenic variations in these BrS-associated genes is low [6], it is considered that, among all of them, they could provide a genetic diagnosis for up to an extra 5–10% of BrS cases. Hence, altogether, a genetic diagnosis can be achieved approximately in 35% of clinically diagnosed BrS patients.
Other types of genetic abnormalities have been suggested to explain the remaining percentage of undiagnosed patients. Indeed, multiplex ligation-dependent probe amplification (MLPA) has allowed the detection of large-scale gene rearrangements involving one or several exons ofSCN5A in BrS cases. However, the low proportion of BrS patients carrying large genetic imbalances identified to date suggests that this type of rearrangements will provide a genetic diagnosis for a modest percentage of BrS cases [810].
BrS has been associated with an increased risk of sudden cardiac death (SCD), despite the reported variability in disease penetrance and expressivity [11]. The prevalence of BrS is estimated at about 1.34 cases per 100 000 individuals per year, with a higher incidence in Asia than in the United States and Europe [12]. However, the dynamic nature of the typical electrocardiogram (ECG) and the fact that it is often concealed, hinder the diagnosis of BrS. Therefore, an exhaustive genetic testing and subsequent family screening may prove to be crucial in identifying silent carriers. A large percentage of these pathogenic variation carriers are clinically asymptomatic, and may be at risk of SCD, which is, sometimes, the first manifestation of the disease [13].
In the present work, we aimed to determine the spectrum and prevalence of genetic variations in BrS-susceptibility genes in a Spanish cohort diagnosed with BrS, and to identify variation carriers among relatives, which would enable the adoption of preventive measures to avoid SCD in their families.

Results  
Study population 

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Table 1. Demographics of the 55 Spanish BrS patients included in the study.

The table shows the demographic characteristics of all the patients included in the study. Numbers in parentheses represent the relative percentages for each condition. T1 ECG refers to Type 1 BrS diagnostic electrocardiogram (ECG), obtained either spontaneously, or after drug challenge. The information regarding both the electrophysiological studies (EPS) and the treatment was not available for all the patients. Two of the patients that didn’t receive any treatment died, and were not taken into account for the calculations of percentages (+2 dead). ICD, intracardiac cardioverter defibrillator.

http://dx.doi.org:/10.1371/journal.pone.0132888.t001

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Table 2. Characteristics of the Spanish BrS patients carrying rare genetic variations.

The table shows the clinical characteristics of the probands who carried rare genetic variations in SCN5A, SCN2B, or RANGRF. All of them are potentially pathogenic except that found in RANGRF, which is of unknown significance (see discussion). All the potentially pathogenic variations (PPVs) that had been previously reported, except p.P1725L and p.R1898C, had been identified in BrS patients. p.P1725L had been associated with Long QT Syndrome and p.R1898C was found in Exome Variant Server with a MAF of 0.0079%. No rare variations were identified in the control population. Patient’s age is expressed in years. Bold identifies the patients carrying variations that had not been described previously. M, male; F, female; S, syncope; ICD, intracardiac cardioverter defibrillator; UK, unknown; EPS, electrophysiological studies (+, positive response;-, negative response; N/P, not performed). The two patients who carried two PPVs each are identified by a and b, respectively.

http://dx.doi.org:/10.1371/journal.pone.0132888.t002

Sequencing of genes associated with BrS

We performed a genetic screening of 14 genes (SCN5A, CACNA1C, CACNB2, GPD1L,SCN1B, SCN2B, SCN3B, SCN4B, KCNE3, RANGRF, HCN4, KCNJ8, KCND3, and KCNE1L), which allowed the identification of 61 genetic variations in our cohort. Of these, 20 were classified as potentially pathogenic variations (PPVs), one variation of unknown significance, and 40 common or synonymous variants considered benign.

The 20 PPVs were found in 18 of the 55 patients (32.7% of the patients, 83.3% males; Table 2). Sixteen patients (88.9%) carried one PPV, and two patients (11.1%) carried two different PPVs each. Nineteen out of the 20 PPVs identified were localized in SCN5A and one in SCN2B.

The vast majority of the PPVs identified were missense (70%). We also detected 2 nonsense variations (10%), 3 insertions or deletions causing frameshifts (15%), and one splicing variation (5%). The three frameshifts (p.R569Pfs*151, p.E625Rfs*95 and p.R1623Efs*7) were identified in SCN5A. These were not found in any of the databases consulted (see Methods), and were thus considered potentially pathogenic (see below). The other 16 rare variations identified inSCN5A had been previously described, and hence were also considered potentially pathogenic. Fourteen of them had been identified in BrS patients. Of these, 6 had also been identified in individuals diagnosed with other cardiac electric diseases (i.e. Sick Sinus Syndrome, Long QT Syndrome, Sudden Unexplained Nocturnal Death Syndrome or Idiopathic Ventricular Fibrillation [2,15,16,20,21,25]). The other 2, p.P1725L and p.R1898C, had only been associated with Long QT Syndrome or found in Exome Variant Server with a MAF of 0.0079%, respectively. Furthermore, we identified a variation in SCN2B (c.632A>G in exon 4 of the gene, resulting in p.D211G) which was considered pathogenic. This patient was included within our cohort, but the functional characterization of channels expressing SCN2B p.D211G was object of a previous study from our group [7]. We also identified a nonsense variation in RANGRFwhich has been formerly reported as rare genetic variation of unknown significance [29].

Additionally, we screened the relatives of those probands carrying a PPV. We analysed a total of 129 relatives, 69 of which (53.5%) were variation carriers. Genotype-phenotype correlations evidenced that 8 of the families displayed complete penetrance (S3 Table). Additionally, no relatives were available for one of the probands carrying a PPV, thus hampering genotype-phenotype correlation assessment. The other 12 families showed incomplete penetrance.

 

MLPA analysis

The 37 patients with negative results after the genetic screening of the 14 BrS-associated genes underwent MLPA analyses of SCN5A. This technique did not reveal any large exon deletion or duplication in this gene for any of the patients.

 

SCN5A p.R569Pfs*151 (c.1705dupC), a novel PPV

A 41-year-old asymptomatic male presented a type 3 BrS ECG which was suggestive of BrS. Flecainide challenge unmasked a type 1 BrS ECG (Fig 1A, left), which was also spontaneously observed sometimes during medical follow up. Sequencing of SCN5A revealed a duplication of a cytosine at position 1705 (c.1705dupC; Fig 1A, right), which originated a frameshift that lead to a truncated Nav1.5 channel (p.R569Pfs*151). The proband’s sister also carried this duplication, but had never presented signs of arrhythmogenesis. The proband’s twin daughters were also variation carriers, displayed normal ECGs and, to date, are asymptomatic (Fig 1A, middle). Thus, p.R569Pfs*151 represents a novel genetic alteration in the Nav1.5 channel that could potentially lead to BrS, but with incomplete penetrance.

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Fig 1. Characteristics of the probands carrying non-reported potentially pathogenic variations (PPVs) in SCN5A and their families.

Left: Electrocardiograms of the probands: (A) patient carrying the p.R569Pfs*151 variation, showing the ST elevation characteristic of BrS in V1 at the time of the flecainide test; (B) patient carrying the p.E625Rfs*95 variation, showing the spontaneous ST elevation characteristic of BrS in V1 and V2; and (C) patient carrying the p.R1623Efs*7 variation, showing the spontaneous ST elevation characteristic of BrS in V1 and V2. Middle: Family pedigrees. Open symbols designate clinically normal subjects, filled symbols mark clinically affected individuals and question marks identify subjects without an available clinical diagnosis. Plus signs indicate the carriers of the PPVs and minus signs, non-carriers. The crosses mark deceased individuals and arrows identify the proband. Right: Detail of the electropherograms obtained after SCN5Asequence analysis of a control subject (left panels) and of the probands (right panels).

http://dx.doi.org:/10.1371/journal.pone.0132888.g001

SCN5A p.E625Rfs*95 (c.1872dupA), a novel PPV

A 51-year-old asymptomatic male was diagnosed with BrS since he presented a spontaneous ST segment elevation in leads V1 and V2 characteristic of type 1 BrS ECG (Fig 1B, left). The sequencing of SCN5A evidenced an adenine duplication at position 1872 (c.1872dupA, Fig 1B, right). This genetic variation results in a truncated Nav1.5 channel (p.E625Rfs*95). The genetic analysis of the proband’s relatives proved that only her mother carried the variation (Fig 1B, middle). She was asymptomatic, but a BrS ECG was unmasked upon ajmaline challenge. The proband’s sister was found dead in her crib at 6 months of age, which suggests that her death might be compatible with BrS. Therefore, the p.E625Rfs*95 variation in the Nav1.5 channel represents a novel genetic alteration potentially causing BrS.

SCN5A p.R1623Efs*7 (c.4867delC), a novel PPV

The proband, a 31-year-old male, was admitted to hospital after suffering a syncope. His baseline 12-lead ECG showed a ST segment elevation in leads V1 and V2 that strongly suggested BrS type 1 (Fig 1C, left). A deletion of the cytosine at position 4867 (c.4867delC) was observed upon SCN5A sequencing (Fig 1C, right). This base deletion leads to a frameshift that originates a truncated Nav1.5 channel (p.R1623Efs*7). Genetic screening of his parents and sisters evidenced that none of them carried this novel variation (Fig 1C, middle). None of them had presented any signs of arrhythmogenicity, nor had a BrS ECG. Nevertheless, in uterogenetic analysis of one of his daughters proved that she had inherited the variation. She died when she was 1 year of age of non-arrhythmogenic causes. Hence, the p.R1623Efs*7 variation in the Nav1.5 channel is a novel genetic alteration originated de novo in the proband that could potentially lead to BrS.

Synonymous and common genetic variations portrayal

In our cohort, we identified 40 single nucleotide variations which were common genetic variants and/or synonymous variants (S2 Table). Twenty-nine had a minor allele frequency (MAF) over 1%, and were thus considered common genetic variants.

We also identified 11 variants with MAF less than 1%. Of them, 9 were synonymous variants, what made us assume that they were not disease-causing. Four of these synonymous variants were not found in any of the databases consulted, and thus their MAF was considered to be less than 1%. Each of these synonymous variations was identified in 1 patient of the cohort. A similar proportion of individuals carrying these novel variations was detected upon sequencing of 300 healthy Spanish individuals (600 alleles). The remaining 2 variants were missense, and although they had either a MAF of less than 1% or an unknown MAF according to the Exome Variant Server and dbSNP websites, they were common in our cohort (29.2 and 50%, respectively; S2 Table), and a similar MAF was detected in a Spanish cohort of healthy individuals (26.7% and 48.8%, respectively).

Influence of phenotype and age on PPV discovery

To assess if a connection existed between the probands’ phenotype and the PPV detection yield, we classified the patients in our cohort according to their ECG (spontaneous or induced type 1), the presence of BrS cases within their families, and the presence/absence of symptoms. Even though the overall PPV detection yield was 32.7%, it was even higher for symptomatic patients (Fig 2). Indeed, in this group of patients, having a family history of BrS was identified as a factor for increased PPV discovery yield. In the case of absence of BrS in the family, the variation discovery yield was almost double for those patients having a spontaneous type 1 BrS ECG than for patients with drug-induced type 1 ECG (45.5% vs 25%, respectively). In addition, we identified a PPV in 44.4% of the asymptomatic patients who presented family history of BrS and a spontaneous type 1 BrS ECG. When the patient presented drug-induced type 1 ECG or in the absence of family history of BrS, the PPV discovery yield was of around 15%.

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Fig 2. Influence of the phenotype on PPV discovery yield.

Bar graph comparing the PPV detection yield in 8 different clinical categories (stated below the graph). Each bar shows the total number of patients for each clinical category divided in those with a PPV (black) and those without an identified PPV (white). The number of patients (in brackets) and percentages are given. Pos, positive; Neg, negative; Spont, spontaneous type 1 BrS ECG; Drug, drug-induced type 1 BrS ECG; n, number of patients.

http://dx.doi.org/:10.1371/journal.pone.0132888.g002

We also investigated the role of age on the PPV occurrence. No significant age differences were observed between variation carriers and non-carriers (38.6±10.3 and 43.5±14.4, respectively, p = 0.16). However, the PPV discovery yield was higher for patients with ages between 30 and 50 years: out of the total of patients carrying a PPV, 83.3% of the patients were in this age range, while 11.1% were younger and 5.6% were older patients (Fig 3A, upper panel). The PPV discovery yield was significantly higher for symptomatic than for asymptomatic patients (42.3% vs 24.1%, respectively; Fig 3A, lower panels).

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Fig 3. Influence of the age on PPVs discovery yield.

(A) Pie charts showing the distribution of patients in the overall population as well as in the categories of symptomatic and asymptomatic patients regarding PPV discovery. The percentage and the number of patients (in brackets) are given for each group. The small pie charts correspond to the age distribution of patients with an identified PPV. (B) Bar graphs of the PPV detection yields obtained for each of the age groups (< 30 years, 30–50 years and > 50 years). Numbers inside each bar correspond to the number of patients carrying a PPV for each category and the percentages represent the variation detection yield.

http://dx.doi.org:/10.1371/journal.pone.0132888.g003

Noteworthy, in the 30–50 age range, 52.9% (9/17) of the symptomatic patients and 35.3% (6/17) of asymptomatic patients carried one PPV (Fig 3B, middle). Additionally, 40% (2/5) of the symptomatic young patients (< 30 years) were variation carriers, while no PPVs were identified in asymptomatic patients within this age range.

Overall, 55 unrelated Spanish patients clinically diagnosed with BrS were included in our study.Table 1 shows the demographics of this cohort, and Table 2 and S1 Table show the clinical and genetic characteristics of all the patients included in the study. The mean age at clinical diagnosis was of 41.9±13.3 years. Although the majority of patients were males (74.5%), their age at diagnosis was not different than that of females (41.8±12.1 years and 42.3±16.3 years, respectively; p = 0.92). A type 1 BrS ECG was present spontaneously in 37 patients (67.3%), and drug challenge revealed a type 1 BrS ECG for the remaining 18 patients (32.7%). Almost half of the patients had experienced symptoms, including 2 SCD and 4 aborted SCD. Patients who had not previously experienced any signs of arrhythmogenicity despite having a BrS ECG were considered asymptomatic. Comparison of symptomatic vs asymptomatic patients evidenced a similar percentage of males (73.1% and 75.9%, respectively). However, the mean age at diagnosis was different between the two groups of patients (37.7±14.3 and 45.7±11.4, respectively; p<0.05).

Discussion

To the best of our knowledge, this is the first comprehensive genetic evaluation of 14 BrS-susceptibility genes and MLPA of SCN5A in a Spanish cohort. Well delimited BrS cohorts from Japan, China, Greece and even Spain have been genetically studied [24,3032]. Additionally, an international compendium of BrS genetic variations identified in more than 2100 unrelated patients from different countries was published in 2010 [3]. However, all these studies screenedSCN5A exclusively. In 2012, Crotti et al. reported the spectrum and prevalence of genetic variations in 12 BrS-susceptibility genes in a BrS cohort [5]. However, this study included patients of different ethnicity. Here, we report the analysis of 14 genes which has been conducted on a well-defined BrS cohort of the same ethnicity.

Our results confirm that SCN5A is still the most prevalent gene associated with BrS. Indeed,SCN5A-mediated BrS in our cohort (30.9%) is higher than the proportion described in other European reports [3,23], where a potentially causative variation is identified in only 20–25% of BrS patients. The reason for this discrepancy is unclear but could point towards a higher prevalence of SCN5A PPVs in the Spanish population or to selection bias. Additionally, we identified a genetic variation in SCN2B (c.632A>G, which results in p.D211G). We have formerly published the comprehensive electrophysiological characterization of this variation, and showed that indeed this variation could be responsible of the phenotype of the patient, thus linking SCN2B with BrS for the first time [7]. Also, we identified a variation in RANGRF. This variation (c.181G>T leading to p.E61X) had been previously reported in a Danish atrial fibrillation cohort [33]. Surprisingly, the authors reported an incidence of 0.4% for this variation in the healthy Danish population, which brought into question its pathogenicity. Our finding of this variation in an asymptomatic patient displaying a type 2 BrS ECG also points toward considering it as a rare genetic variation with a potential modifier effect on the phenotype but not clearly responsible for the disease [29].

No PPVs were identified in the other genes tested. Certainly, it is well accepted that the contribution of these genes to the disease is minor, and thus should only be considered under special circumstances [13,34]. In addition, recent studies have questioned the causality of variations identified in some of these minority genes [35].

We also used the MLPA technique for the detection of large exon duplications and/or deletions in SCN5A in patients without PPVs, and no large rearrangements were identified. This is in accordance with previous reports, which revealed that such imbalances are uncommon [810].

Kapplinger et al. [3] reported a predominance of PPVs in transmembrane regions of Nav1.5. Indeed, it has been proposed that most rare genetic variations in interdomain linkers may be considered as non-pathogenic [36]. In contrast, PPVs identified in this study are mainly located in extracellular loops and cytosolic linker regions of Nav1.5 (Fig 4). Additionally, 2 of our non-previously reported frameshifts are located in the DI-DII linker. These 2 genetic variations lead to truncated proteins, which would lack around 75% of the protein sequence, and thus are presupposed to be pathogenic.

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Fig 4. Nav1.5 channel scheme showing the relative position of the SCN5A PPVs identified in our cohort.

Open symbols indicate already described variations and closed symbols locate novel variations reported in this study. DI to DIV designate the 4 domains of the protein, and numbers 1–6 identify the different segments within each domain. Crosses mark the voltage sensor.

http://dx.doi.org:/10.1371/journal.pone.0132888.g004

In our cohort, we have identified 40 synonymous or common genetic variations, 4 of which have not been previously reported. These variations are gradually becoming more and more important in the explanation of certain phenotypes of genetic diseases. Only a few common variations identified here are already published as phenotypic modifiers [37,38]. The effect of these and other common variants identified in our cohort on BrS phenotype should be further studied.

Unexpectedly, almost 40% (7/18) of the PPV carriers did not present signs of arrhythmogenicity. We also performed genotype-phenotype correlations of the PPVs identified in the families (S3 Table). These studies uncovered relatives, most of whom were young individuals, who carried a familial variation but had never exhibited any clinical manifestations of the disease. This is in agreement with Crotti et al. and Priori et al. [5,23], who postulated that a positive genetic testing result is not always associated with the presence of symptoms. Indeed, the existence of asymptomatic patients carrying genetic variations described to cause a severe Nav1.5 channel dysfunction has been reported [39]. The identification of silent carriers is of paramount importance since it allows the adoption of preventive measures before any lethal episode takes place. Unknown environmental factors, medication and modifier genes have been suggested to influence and/or predispose to arrhythmogenesis [11]. Hence, this group of patients has to be cautiously followed in order to avoid fatal events.

Our studies on the connection between patients’ phenotype and the PPV detection yield highlighted the presence of symptoms as a factor for an increased variation discovery yield. Within the group of symptomatic individuals, a PPV was identified in a higher proportion of patients displaying a spontaneous type 1 BrS ECG than for patients showing a drug-induced ECG. Likewise, within the asymptomatic patients with family history of BrS, those who presented spontaneous type 1 BrS ECG carried a PPV more often than those with a drug-induced ECG (Fig 2). Referring to age, the vast majority (17/20, 85%) of the PPVs were identified in patients around their fourth decade of age (30–50 years). This is in accordance with the accepted mean age of disease manifestation. Moreover, in this age range, more than 50% of the patients who presented symptoms carried a variation that could be pathogenic (Fig 3). Importantly, 35.3% of asymptomatic patients of around 40 years of age also carried one of such variations. These data highlight the importance of performing a genetic test even in the absence of clinical manifestations of the disease, and particularly when in the 30–50 years range, which is in accordance with consensus recommendations [13,34].

In conclusion, we have analysed for the first time 14 BrS-susceptibility genes and performed MLPA of SCN5A in a Spanish BrS cohort. Our cohort showed male prevalence with a mean age of disease manifestation around 40 years. BrS in this cohort was almost exclusivelySCN5A-mediated. The mean PPV discovery yield in our Spanish BrS patients is higher than that described for other BrS cohorts (32.7% vs 20–25%, respectively), and is even higher for patients in the 30–50 years age range (up to 53% for symptomatic patients). All these evidences support the genetic testing, at least of SCN5A, in all clinically well diagnosed BrS patients.

 

Study Limitations

First of all, drug challenge tests were not performed for all the relatives who were asymptomatic variation carriers. This fact hampered their clinical diagnosis and represents an impediment to definitely assess the link between PPVs and BrS. These patients are nowadays under follow-up.

New PPVs have been identified in our cohort. The clinical information available for the families suggests that these new variations could be pathogenic. Still, in vitro studies of these variations are required in order to evaluate their functional effects and verify their pathogenic role. Additionally, genotyping in an independent cohort would help reduce the likelihood of type I (false positive) error in genetic variant discovery.

We have to acknowledge that the study set is relatively small. Consequently, the classification of patients according to the different clinical categories rendered rather small sub-groups, which may lead to over-interpretation of the results. Future studies will be directed to the genetic screening of additional Spanish BrS patients, which will probably reinforce the significance of the tendencies observed here.

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Elephants and cancer

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

In 1992, I moved to the Washington DC area and attended a conference on new and projected trends in cancer care at the National Institutes of Health.

Researchers in Texas are now reporting that there may be a smarter way to combat cancer-associated KRAS (Kirsten rat sarcoma viral oncogene homolog) mutations and possibly attack specific tumor types in a new targeted manner.

A new study at a single center in Japan found no significant differences in the rate of BRCA mutations between ovarian cancer patients with or without family histories of the mutations and recommends that BRCA1/2 testing be required for all ovarian cancer patients

 

Why Elephants Don’t Get Cancer

Blog | October 30, 2015 | Cancer and Genetics
By Deborah A. Boyle, RN, MSN, AOCNS, FAAN

Image © Marchenko Yevhen/ Shutterstock.com
In 1992, I moved to the Washington DC area and attended a conference on new and projected trends in cancer care at the National Institutes of Health. A pediatric immunologist who treated and studied rare genetically-based childhood illnesses told the audience of oncology nurses that in the future there will be no need for surgery, radiation, or systemic antineoplastic therapies to treat cancer. Rather, genetic molecular engineering will be used to stop and reverse early signs of cancer and counter carcinogenesis even at later stages. I sat in the audience and was awestruck by this forecast. I found it unfathomable that this could ever become a reality.
Fast forward to 2015, over 20 years later, and I read in the science column of the Los Angeles Times the story entitled, “Elephants’ Anti-Cancer Secret” (October 10, 2015, p.B2). Reporting on a study published in a recent issue of JAMA,1, 2 the columnist shares the finding that elephants (and other large mammals) rarely get cancer. Scientists recently revealed the potential reason for such.

African elephants have twenty copies of a gene called TP53, which produces a protein that suppresses tumor growth. Humans on the other hand, have only one copy of this gene. Collaborating with a zookeeper at Utah’s Hogle Zoo in Salt Lake City and the chief veterinarian for Ringling Bros. Barnum and Bailey Circus, the researchers also identified that elephants were able to make copies of TP53 such that they were incorporated into the genome over time. Additionally, when the elephants’ cells were exposed to radiation, cell death occurred at twice the rate of human cells.

In recent years, the advent of targeted therapies and the identification of genes associated with heightened cancer risk have put the spotlight on genetics in the management of cancer.

The implications of this research will undoubtedly help keep the focus on this critical area of cancer research. The scientists involved in this investigation posited that perhaps a drug could be created that mimics the actions of TP53 or that the insertion of TP53 genes into precancerous cells could reverse mutations. Since it took millions of years for the elephants of today to evolve, I guess waiting 20 years for this type of knowledge to come forth isn’t that long to wait.

I’ve become a believer in the profound possibility of genetics in cancer therapy. That physician I heard decades ago was “right on.”

REFERENCES

Abegglen LM, Caulin AF, Chan A, et al. (2015).
Potential Mechanisms for Cancer Resistance in Elephants and Comparative Cellular Response to DNA Damage in Humans.
JAMA, Oct 8:1-11. http://dx.doi.org:/10.1001/jama.2015.13134.
Greaves M, Ermini L. (2015).
Evolutionary Adaptation to Risk of Cancer: Evidence From Cancer Resistance in Elephants.
JAMA, Oct 8:1-3. http://dx.doi.org:/10.1001/jama.2015.13153.
– See more at: http://www.oncotherapynetwork.com/cancer-and-genetics/why-elephants-dont-get-cancer#sthash.5xGzcSFp.dpuf

 

Researchers Develop New Classification Model for Cancer-Associated KRAS Mutations

News | October 28, 2015 | Cancer and Genetics
By John Schieszer
Researchers in Texas are now reporting that there may be a smarter way to combat cancer-associated KRAS (Kirsten rat sarcoma viral oncogene homolog) mutations and possibly attack specific tumor types in a new targeted manner. They are reporting that the use of biochemical profiling and sub classification of KRAS-driven cancers may lead to a more rational selection of therapies targeting specific KRAS isoforms or specific RAS effectors.
KRAS is one of the main members of the RAS family. About one-third of all human cancers, including a high percentage of pancreatic, lung, and colorectal cancers, are driven by mutations in RAS genes, which also make cells resistant to some available cancer therapies, according to the National Cancer Institute.

The UT Southwestern Medical Center researchers have developed a new classification for cancers caused by KRAS. They are investigating a new strategy based on models that the researchers developed to classify cancers caused by KRAS mutations, which cause cells to grow uncontrollably. Although KRAS-driven cancer mutations have long been a focus of cancer research, effective targeted therapies are not available.

“This work further supports the idea that not all oncogenic KRAS mutations function in the same way to cause cancer. The model we developed may help in sub classifying KRAS-mutant cancers so they can be treated more effectively, using therapies that are tailored to each mutation,” said Kenneth Westover, MD, who is an as Assistant Professor of Radiation Oncology and Biochemistry at the University of Texas Southwestern Medical Center, in a news release.1 “Furthermore, this study gives new fundamental understanding to why certain KRAS-mutant cancers, for example those containing the KRAS G13D mutation, behave as they do.”

The researchers, who have published their findings in Molecular Cancer Research, have characterized the most common KRAS mutants biochemically for substrate binding kinetics, intrinsic and GTPase-activating protein (GAP)–stimulated GTPase activities, and interactions with the RAS effector, RAF kinase. They report that KRAS G13D appears to show rapid nucleotide exchange kinetics compared with other mutants analyzed.2

In this study, the researchers evaluated eight of the most common KRAS mutants for key biochemical properties including nucleotide exchange rates, enzymatic activity, and binding activity related to a key signaling protein, RAF kinase. The researchers observed significant differences between the mutants, including about a tenfold increase in the rate of nucleotide exchange for the specific mutant KRAS G13D, highly variable KRAS enzymatic activities, and variability in affinity for RAF. They also determined high-resolution, three-dimensional X-ray crystal structures for several of the most common mutants, which led to a better understanding of some of the biochemical activities observed.

The researchers now plan to test their models in more complex experimental systems, such as genetically engineered cancer cell lines.

REFERENCES

UT Southwestern Medical Center. (2015).
Researchers develop classification model for cancers caused by most frequently mutated cancer gene.
Hunter JC, Manandhar A, Carrasco MA, et al. (2015).

Biochemical and Structural Analysis of Common Cancer-Associated KRAS Mutations.
Molecular Cancer Research, Sep;13(9):1325-35.
– See more at: http://www.oncotherapynetwork.com/cancer-and-genetics/researchers-develop-new-classification-model-cancer-associated-kras-mutations#sthash.kkK8G0Mi.dpuf

 

 

 

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Diagnostic Revelations

Larry H. Bernstein, MD, FCAP, Curator

LPBI

New Liquid Biopsy Test Uses Platelet RNA as Cancer Diagnostic

  • Click Image To Enlarge +
    Using platelet RNA, scientists have been able to detect the presence of cancer and pinpoint its primary location. [Best et al., 2015, Cancer Cell 28, 1–11]

    The age of fast, accurate, and noninvasive cancer screening is rapidly becoming reality. The power of next-generation sequencing has allowed molecular diagnostic techniques to sample small amounts of blood for the genetic hallmarks of tumorigenesis. These liquid biopsy procedures, as they have been dubbed, typically search for circulating tumor DNA (ctDNA) that has made its way into the systemic circulation from tumor cells that have died or enrich for circulating tumor cells (CTCs) that have broken off from the primary cancer site.

    Now, a team of researchers lead by scientists at Massachusetts General Hospital (MGH), have developed a new diagnostic test that analyzes the tumor RNA picked up in circulating platelets. The investigators believe this new method could become even more useful than other molecular technologies for diagnosing cancer since it can also determine the primary location of the tumor and provide insight to potential therapeutic approaches.

    “By combining next-generation-sequencing gene expression profiles of platelet RNA with computational algorithms we developed, we were able to detect the presence of cancer with 96 percent accuracy,” explains co-senior author Bakhos Tannous, Ph.D., associate professor Harvard Medical School and associate neuroscientist at MGH. “Platelet RNA signatures also provide valuable information on the type of tumor present in the body and can guide the selection of the most optimal treatment for individual patients.

    The findings from this study were published recently in Cancer Cell through an article entitled “RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics.”

    In the current study the research team describes finding that the RNA profiles of tumor-educated platelets (TEPs)—those that have taken up molecules shed by tumors—can distinguish among blood samples of healthy individuals and those of patients with six types of cancer, determine the location of the primary tumor, and identify tumors carrying mutations that can guide therapeutic decision-making.

    Over the past several years, the scientific literature has shown that in addition to their role in promoting blood clotting, platelets take up protein and RNA molecules from tumors, possibly playing a role in tumor growth and metastasis. Dr. Tannous and his colleagues set out to determine whether tumor RNA carried in platelets could be used to diagnose and classify common types of cancer.

    The investigators isolated platelets from blood samples taken from 55 healthy donors, 39 individual with early-stage cancer and 189 patients with advanced, metastatic cancer. Among those patients with cancer, they were diagnosed with non-small-cell lung cancer, colorectal cancer, glioblastoma, pancreatic cancer, hepatobiliary cancer, or breast cancer.

    The comparison of RNA profiles from the healthy donors to those of the cancer patients identified increased levels of approximately 1,500 RNA molecules—many involved in cancer-associated processes—and a reduction of almost 800 in samples from cancer patients. Using their novel algorithm, the MGH group was able to examine close to 1,000 RNAs from almost 300 individuals with 96% accuracy for the presence of cancer.

    Additionally, the platelet mRNA profiles were able to identify the particular type of cancer within each patient participant, including distinguishing among three types of gastrointestinal adenocarcinoma: colorectal cancer, pancreatic cancer, and hepatobiliary cancer. Platelets from patients with tumors driven by mutations in KRAS or EGFR proteins—biomarkers that can guide the use of drugs targeting those mutations—proved to have unique RNA profiles as well.

    The researchers were excited by their findings and emphasize the uniqueness of their approach as currently utilized liquid biopsy approaches have been unable to diagnose cancer while simultaneously pinpointing the location of the primary tumor.

    “We observed that the mRNA profiles of tumor-educated platelets have the sensitivity and specificity to detect cancer, even in early, non-metastasized tumors,” noted Dr. Tannous. “We are further assessing the potential of TEP-based screening for therapeutic decision making and also investigating how non-cancerous diseases may further influence the RNA repertoire of TEPs.”

  • RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics

Myron G. Best Nik Sol, Jihane Tannous, Bart A. Westerman, François Rustenburg, Pepijn Schellen, Heleen Verschueren, Edward Post, Jan Koster, Bauke Ylstra, Irsan Kooi, et al.
Highlights

Tumors “educate” platelets (TEPs) by altering the platelet RNA profile

TEPs provide a RNA biosource for pan-cancer, multiclass, and companion diagnostics

TEP-based liquid biopsies may guide clinical diagnostics and therapy selection

A total of 100–500 pg of total platelet RNA is sufficient for TEP-based diagnostics

mRNA Profiles of Tumor-Educated Platelets Are Distinct from Platelets of Healthy Individuals

Summary

Tumor-educated blood platelets (TEPs) are implicated as central players in the systemic and local responses to tumor growth, thereby altering their RNA profile. We determined the diagnostic potential of TEPs by mRNA sequencing of 283 platelet samples. We distinguished 228 patients with localized and metastasized tumors from 55 healthy individuals with 96% accuracy. Across six different tumor types, the location of the primary tumor was correctly identified with 71% accuracy. Also, MET or HER2-positive, and mutant KRAS, EGFR, orPIK3CA tumors were accurately distinguished using surrogate TEP mRNA profiles. Our results indicate that blood platelets provide a valuable platform for pan-cancer, multiclass cancer, and companion diagnostics, possibly enabling clinical advances in blood-based “liquid biopsies”.

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Significance

Blood-based “liquid biopsies” provide a means for minimally invasive molecular diagnostics, overcoming limitations of tissue acquisition. Early detection of cancer, clinical cancer diagnostics, and companion diagnostics are regarded as important applications of liquid biopsies. Here, we report that mRNA profiles of tumor-educated blood platelets (TEPs) enable for pan-cancer, multiclass cancer, and companion diagnostics in both localized and metastasized cancer patients. The ability of TEPs to pinpoint the location of the primary tumor advances the use of liquid biopsies for cancer diagnostics. The results of this proof-of-principle study indicate that blood platelets are a potential all-in-one platform for blood-based cancer diagnostics, using the equivalent of one drop of blood.

Introduction

Cancer is primarily diagnosed by clinical presentation, radiology, biochemical tests, and pathological analysis of tumor tissue, increasingly supported by molecular diagnostic tests. Molecular profiling of tumor tissue samples has emerged as a potential cancer classifying method (Akbani et al., 2014, Golub et al., 1999, Han et al., 2014, Hoadley et al., 2014, Kandoth et al., 2013,Ramaswamy et al., 2001, Su et al., 2001). In order to overcome limitations of tissue acquisition, the use of blood-based liquid biopsies has been suggested (Alix-Panabières et al., 2012, Crowley et al., 2013, Haber and Velculescu, 2014). Several blood-based biosources are currently being evaluated as liquid biopsies, including plasma DNA (Bettegowda et al., 2014, Chan et al., 2013, Diehl et al., 2008, Murtaza et al., 2013, Newman et al., 2014, Thierry et al., 2014) and circulating tumor cells (Bidard et al., 2014, Dawson et al., 2013, Maheswaran et al., 2008, Rack et al., 2014). So far, implementation of liquid biopsies for early detection of cancer has been hampered by non-specificity of these biosources to pinpoint the nature of the primary tumor (Alix-Panabières and Pantel, 2014,Bettegowda et al., 2014).

It has been reported that tumor-educated platelets (TEPs) may enable blood-based cancer diagnostics (Calverley et al., 2010, McAllister and Weinberg, 2014,Nilsson et al., 2011). Blood platelets—the second most-abundant cell type in peripheral blood—are circulating anucleated cell fragments that originate from megakaryocytes in bone marrow and are traditionally known for their role in hemostasis and initiation of wound healing (George, 2000, Leslie, 2010). More recently, platelets have emerged as central players in the systemic and local responses to tumor growth. Confrontation of platelets with tumor cells via transfer of tumor-associated biomolecules (“education”) is an emerging concept and results in the sequestration of such biomolecules (Klement et al., 2009,Kuznetsov et al., 2012, McAllister and Weinberg, 2014, Nilsson et al., 2011,Quail and Joyce, 2013). Moreover, external stimuli, such as activation of platelet surface receptors and lipopolysaccharide-mediated platelet activation (Denis et al., 2005, Rondina et al., 2011), induce specific splicing of pre-mRNAs in circulating platelets (Power et al., 2009, Rowley et al., 2011, Schubert et al., 2014). Platelets may also undergo queue-specific splice events in response to signals released by cancer cells and the tumor microenvironment—such as stromal and immune cells. The combination of specific splice events in response to external signals and the capacity of platelets to directly ingest (spliced) circulating mRNA can provide TEPs with a highly dynamic mRNA repertoire, with potential applicability to cancer diagnostics (Calverley et al., 2010, Nilsson et al., 2011) (Figure 1A). In this study, we characterize the platelet mRNA profiles of various cancer patients and healthy donors and investigate their potential for TEP-based pan-cancer, multiclass cancer, and companion diagnostics.

  
Results

We prospectively collected and isolated blood platelets from healthy donors (n = 55) and both treated and untreated patients with early, localized (n = 39) or advanced, metastatic cancer (n = 189) diagnosed by clinical presentation and pathological analysis of tumor tissue supported by molecular diagnostics tests. The patient cohort included six tumor types, i.e., non-small cell lung carcinoma (NSCLC, n = 60), colorectal cancer (CRC, n = 41), glioblastoma (GBM, n = 39), pancreatic cancer (PAAD, n = 35), hepatobiliary cancer (HBC, n = 14), and breast cancer (BrCa, n = 39) (Figure 1B; Table 1; Table S1). The cohort of healthy donors covered a wide range of ages (21–64 years old, Table 1).

Table 1Summary of Patient Characteristics
PATIENT GROUP TOTAL (N) GENDER M (%)A AGE (SD)B METASTASIS (%) MUTATION PRESENCE (%)
TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION
HD 39 16 21 (54) 6 (38) 41 (13) 38 (16)
GBM 23 16 18 (78) 10 (63) 59 (16) 62 (14) 0 (0) 0 (0)
NSCLC 36 24 14 (39) 14 (58) 60 (11) 59 (12) 33 (92) 23 (96) KRAS 15 (42) 11 (46)
EGFR 14 (39) 7 (29)
MET-overexpression 5 (14) 3 (13)
CRC 25 16 13 (52) 9 (56) 59 (13) 63 (16) 20 (80) 15 (94) KRAS 7 (28) 8 (50)
PAAD 21 14 12 (57) 7 (50) 66 (9) 66 (10) 15 (71) 9 (64) KRAS 13 (62) 9 (64)
BrCa 23 16 0 (0) 0 (0) 59 (11) 59 (11) 16 (70) 9 (56) HER2+ 7 (30) 5 (31)
PIK3CA 6 (26) 2 (13)
triple negative 5 (22) 3 (19)
HBC 8 6 6 (75) 2 (33) 68 (13) 62 (16) 6 (75) 4 (67) KRAS 3 (38) 1 (17)

HD, healthy donors; GBM, glioblastoma; NSCLC, non-small cell lung cancer; CRC, colorectal cancer; PAAD, pancreatic cancer; BrCa, breast cancer; HBC, hepatobiliary cancer. See also Table S1.

aIndicated are number of male individuals.
bIndicated is mean age in years.

Platelet purity was confirmed by morphological analysis of randomly selected and freshly isolated platelet samples (contamination is 1 to 5 nucleated cells per 10 million platelets, see Supplemental Experimental Procedures), and platelet RNA was isolated and evaluated for quality and quantity (Figure S1A). A total of 100–500 pg of platelet total RNA (the equivalent of purified platelets in less than one drop of blood) was used for SMARTer mRNA amplification and sequencing (Ramsköld et al., 2012) (Figures 1C and S1A). Platelet RNA sequencing yielded a mean read count of ∼22 million reads per sample. After selection of intron-spanning (spliced) RNA reads and exclusion of genes with low coverage (seeSupplemental Experimental Procedures), we detected in platelets of healthy donors (n = 55) and localized and metastasized cancer patients (n = 228) 5,003 different protein coding and non-coding RNAs that were used for subsequent analyses. The obtained platelet RNA profiles correlated with previously reported mRNA profiles of platelets (Bray et al., 2013, Kissopoulou et al., 2013, Rowley et al., 2011, Simon et al., 2014) and megakaryocytes (Chen et al., 2014) and not with various non-related blood cell mRNA profiles (Hrdlickova et al., 2014) (Figure S1B). Furthermore, DAVID Gene Ontology (GO) analysis revealed that the detected RNAs are strongly enriched for transcripts associated with blood platelets (false discovery rate [FDR] < 10−126).

Among the 5,003 RNAs, we identified known platelet markers, such as B2M, PPBP, TMSB4X, PF4, and several long non-coding RNAs (e.g., MALAT1). A total of 1,453 out of 5,003 mRNAs were increased and 793 out of 5,003 mRNAs were decreased in TEPs as compared to platelet samples of healthy donors (FDR < 0.001), while presenting a strong correlation between these platelet mRNA profiles (r = 0.90, Pearson correlation) (Figure 1D). Unsupervised hierarchical clustering based on the differentially detected platelet mRNAs distinguished two sample groups with minor overlap (Figure 1E; Table S2). DAVID GO analysis revealed that the increased TEP mRNAs were enriched for biological processes such as vesicle-mediated transport and the cytoskeletal protein binding while decreased mRNAs were strongly involved in RNA processing and splicing (Table S3). A correlative analysis of gene set enrichment (CAGE) GO methodology, in which 3,875 curated gene sets of the GSEA database were correlated to TEP profiles (see Experimental Procedures), demonstrated significant correlation of TEP mRNA profiles with cancer tissue signatures, histone deacetylases regulation, and platelets (Table 2). The levels of 20 non-protein coding RNAs were altered in TEPs as compared to platelets from healthy individuals and these show a tumor type-associated RNA profile (Figure S1C).

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Tumor-Educated Platelet mRNA Profiling for Pan-Cancer Diagnostics

(A) Schematic overview of tumor-educated platelets (TEPs) as biosource for liquid biopsies.

(B) Number of platelet samples of healthy donors and patients with different types of cancer.

(C) TEP mRNA sequencing (mRNA-seq) workflow, as starting from 6 ml EDTA-coated tubes, to platelet isolation, mRNA amplification, and sequencing.

(D) Correlation plot of mRNAs detected in healthy donor (HD) platelets and cancer patients’ TEPs, including highlighted increased (red) and decreased (blue) TEP mRNAs.

(E) Heatmap of unsupervised clustering of platelet mRNA profiles of healthy donors (red) and patients with cancer (gray).

(F) Cross-table of pan-cancer SVM/LOOCV diagnostics of healthy donor subjects and patients with cancer in training cohort (n = 175). Indicated are sample numbers and detection rates in percentages.

(G) Performance of pan-cancer SVM algorithm in validation cohort (n = 108). Indicated are sample numbers and detection rates in percentages.

(H) ROC-curve of SVM diagnostics of training (red), validation (blue) cohort, and random classifiers, indicating the classification accuracies obtained by chance of the training and validation cohort (gray).

(I) Total accuracy ratios of SVM classification in five subgroups, including corresponding predictive strengths. Genes, number of mRNAs included in training of the SVM algorithm.

See also Figure S1 and Tables S1, S2, S3, and S4.

Table 2Pan-Cancer CAGE Gene Ontology
TOP 25 GO CORRELATIONS
# LOWESTA HIGHESTA
DOWN
Translation 10 −0.865 −0.890
Immune, T cell 5 −0.853 −0.883
Cancer-associated 2 −0.875 −0.887
Viral replication 2 −0.875 −0.878
IL-signaling 2 −0.869 −0.874
RNA processing 1 −0.886
Ago2-Dicer-silencing 1 −0.882
Protein metabolism 1 −0.879
Receptor processing 1 −0.869
UP
Cancer-associated 6 −0.783 −0.906
Infection 3 −0.798 −0.853
HDAC 3 −0.795 −0.852
Platelet 3 −0.837 −0.906
Cytoskeleton 2 −0.801 −0.886
Hypoxia 2 −0.763 −0.937
Protease 1 −0.854
Immunodeficiency 1 −0.812
Differentiation 1 −0.810
Immune differentiation 1 −0.801
Methylation 1 −0.778
Metabolism 1 −0.768

Top-ranking correlations of platelet-mRNA profiles with 3,875 Broad Institute curated gene sets. CAGE, Correlative Analysis of Gene Set Enrichment; GO, gene ontology; #, number of hits per annotation; IL, interleukin; HDAC, histone deacetylase.

aIndicated are lowest and highest correlations per annotation.

Next, we determined the diagnostic accuracy of TEP-based pan-cancer classification in the training cohort (n = 175), employing a leave-one-out cross-validation support vector machine algorithm (SVM/LOOCV, see Experimental Procedures; Figures S1D and S1E), previously used to classify primary and metastatic tumor tissues (Ramaswamy et al., 2001, Su et al., 2001, Vapnik, 1998, Yeang et al., 2001). Briefly, the SVM algorithm (blindly) classifies each individual sample as cancer or healthy by comparison to all other samples (175 − 1) and was performed 175 times to classify and cross validate all individuals samples. The algorithms we developed use a limited number of different spliced RNAs for sample classification. To determine the specific input gene lists for the classifying algorithms we performed ANOVA testing for differences (as implemented in the R-package edgeR), yielding classifier-specific gene lists (Table S4). For the specific algorithm of the pan-cancer TEP-based classifier test we selected 1,072 RNAs (Table S4) for the n = 175 training cohort, yielding a sensitivity of 96%, a specificity of 92%, and an accuracy of 95% (Figure 1F). Subsequent validation using a separate validation cohort (n = 108), not involved in input gene list selection and training of the algorithm, yielded a sensitivity of 97%, a specificity of 94%, and an accuracy of 96% (Figure 1G), with an area under the curve (AUC) of 0.986 to detect cancer (Figure 1H) and high predictive strength (Figure 1I). In contrast, random classifiers, as determined by multiple rounds of randomly shuffling class labels (permutation) during the SVM training process (see Experimental Procedures), had no predictive power (mean overall accuracy: 78%, SD ± 0.3%, p < 0.01), thereby showing, albeit an unbalanced representation of both groups in the study cohort, specificity of our procedure. A total of 100 times random class-proportional subsampling of the entire dataset in a training and validation set (ratio 60:40) yielded similar accuracy rates (mean overall accuracy: 96%, SD: ± 2%), confirming reproducible classification accuracy in this dataset. Of note, all 39 patients with localized tumors and 33 of the 39 patients with primary tumors in the CNS were correctly classified as cancer patients (Figure 1I). Visualization of 22 genes previously identified at differential RNA levels in platelets of patients with various non-cancerous diseases (Gnatenko et al., 2010, Healy et al., 2006, Lood et al., 2010,Raghavachari et al., 2007), revealed mixed levels in our TEP dataset (Figure S1F), suggesting that the platelet RNA repertoire in patients with non-cancerous disease is distinct from patients with cancer.

Tumor-Specific Educational Program of Blood Platelets Allows for Multiclass Cancer Diagnostics

In addition to the pan-cancer diagnosis, the TEP mRNA profiles also distinguished healthy donors and patients with specific types of cancer, as demonstrated by the unsupervised hierarchical clustering of differential platelet mRNA levels of healthy donors and all six individual tumor types, i.e., NSCLC, CRC, GBM, PAAD, BrCa, and HBC (Figures 2A, all p < 0.0001, Fisher’s exact test, and S2A; Table S5), and this resulted in tumor-specific gene lists that were used as input for training and validation of the tumor-specific algorithms (Table S4). For the unsupervised clustering of the all-female group of BrCa patients, male healthy donors were excluded to avoid sample bias due to gender-specific platelet mRNA profiles (Figure S2B). SVM-based classification of all individual tumor classes with healthy donors resulted in clear distinction of both groups in both the training and validation cohort, with high sensitivity and specificity, and 38/39 (97%) cancer patients with localized disease were classified correctly (Figures 2B and S2C). CAGE GO analysis showed that biological processes differed between TEPs of individual tumor types, suggestive of tumor-specific “educational” programs (Table S6). We did not detect sufficient differences in mRNA levels to discriminate patients with non-metastasized from patients with metastasized tumors, suggesting that the altered platelet profile is predominantly influenced by the molecular tumor type and, to a lesser extent, by tumor progression and metastases.

 We next determined whether we could discriminate three different types of adenocarcinomas in the gastro-intestinal tract by analysis of the TEP-profiles, i.e., CRC, PAAD, and HBC. We developed a CRC/PAAD/HBC algorithm that correctly classified the mixed TEP samples (n = 90) with an overall accuracy of 76% (mean overall accuracy random classifiers: 42%, SD: ± 5%, p < 0.01,Figure 2C). In order to determine whether the TEP mRNA profiles allowed for multiclass cancer diagnosis across all tumor types and healthy donors, we extended the SVM/LOOCV classification test using a combination of algorithms that classified each individual sample of the training cohort (n = 175) as healthy donor or one of six tumor types (Figures S2D and S2E). The results of the multiclass cancer diagnostics test resulted in an average accuracy of 71% (mean overall accuracy random classifiers: 19%, SD: ± 2%, p < 0.01,Figure 2D), demonstrating significant multiclass cancer discriminative power in the platelet mRNA profiles. The classification capacity of the multiclass SVM-based classifier was confirmed in the validation cohort of 108 samples, with an overall accuracy of 71% (Figure 2E). An overall accuracy of 71% might not be sufficient for introduction into cancer diagnostics. However, of the initially misclassified samples according to the SVM algorithms choice with strongest classification strength the second ranked classification was correct in 60% of the cases. This yields an overall accuracy using the combined first and second ranked classifications of 89%. The low validation score of HBC samples can be attributed to the relative low number of samples and possibly to the heterogenic nature of this group of cancers (hepatocellular cancers and cholangiocarcinomas).
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Tumor-Educated Platelet mRNA Profiles for Multiclass Cancer Diagnostics

(A) Heatmaps of unsupervised clustering of platelet mRNA profiles of healthy donors (HD; n = 55) (red) and patients with non-small cell lung cancer (NSCLC; n = 60), colorectal cancer (CRC; n = 41), glioblastoma (GBM; n = 39), pancreatic cancer (PAAD, n = 35), breast cancer (BrCa; n = 39; female HD; n = 29), and hepatobiliary cancer (HBC; n = 14).

(B) ROC-curve of SVM diagnostics of healthy donors and individual tumor classes in both training (left) and validation (right) cohort. Random classifiers, indicating the classification accuracies obtained by chance, are shown in gray.

(C) Confusion matrix of multiclass SVM/LOOCV diagnostics of patients with CRC, PAAD, and HBC. Indicated are detection rates as compared to the actual classes in percentages.

(D) Confusion matrix of multiclass SVM/LOOCV diagnostics of the training cohort consisting of healthy donors (healthy) and patients with GBM, NSCLC, PAAD, CRC, BrCa, and HBC. Indicated are detection rates as compared to the actual classes in percentages.

(E) Confusion matrix of multiclass SVM algorithm in a validation cohort (n = 108). Indicated are sample numbers and detection rates in percentages. Genes, number of mRNAs included in training of the SVM algorithm.

See also Figure S2 and Tables S4, S5, and S6.

Companion Diagnostics Tumor Tissue Biomarkers Are Reflected by Surrogate TEP mRNA Onco-signatures

Blood provides a promising biosource for the detection of companion diagnostics biomarkers for therapy selection (Bettegowda et al., 2014, Crowley et al., 2013,Papadopoulos et al., 2006). We selected platelet samples of patients with distinct therapy-guiding markers confirmed in matching tumor tissue. Although the platelet mRNA profiles contained undetectable or low levels of these mutant biomarkers, the TEP mRNA profiles did allow to distinguish patients with KRASmutant tumors from KRAS wild-type tumors in PAAD, CRC, NSCLC, and HBC patients, and EGFR mutant tumors in NSCLC patients, using algorithms specifically trained on biomarker-specific input gene lists (all p < 0.01 versus random classifiers, Figures 3A–3E ; Table S4). Even though the number of samples analyzed is relatively low and the risk of algorithm overfitting needs to be taken into account, the TEP profiles distinguished patients with HER2-amplified, PIK3CA mutant or triple-negative BrCa, and NSCLC patients with MET overexpression (all p < 0.01 versus random classifiers, Figures 3F–3I).

 We subsequently compared the diagnostic accuracy of the TEP mRNA classification method with a targeted KRAS (exon 12 and 13) and EGFR (exon 20 and 21) amplicon deep sequencing strategy (∼5,000× coverage) on the Illumina Miseq platform using prospectively collected blood samples of patients with localized or metastasized cancer. This method did allow for the detection of individual mutant KRAS and EGFR sequences in both plasma DNA and platelet RNA (Table S7), indicating sequestration and potential education capacity of mutant, tumor-derived RNA biomarkers in TEPs. Mutant KRAS was detected in 62% and 39%, respectively, of plasma DNA (n = 103, kappa statistics = 0.370, p < 0.05) and platelet RNA (n = 144, kappa statistics = 0.213, p < 0.05) of patients with a KRAS mutation in primary tumor tissue. The sensitivity of the plasma DNA tests was relatively poor as reported by others (Bettegowda et al., 2014, Thierry et al., 2014), which may partly be attributed to the loss of plasma DNA quality due to relatively long blood sample storage (EDTA blood samples were stored up to 48 hr at room temperature before plasma isolation). To discriminate KRAS mutant from wild-type tumors in blood, the TEP mRNA profiles provided superior concordance with tissue molecular status (kappa statistics = 0.795–0.895, p < 0.05) compared to KRAS amplicon sequencing analysis of both plasma DNA and platelet RNA (Table S7). Thus, TEP mRNA profiles can harness potential blood-based surrogate onco-signatures for tumor tissue biomarkers that enable cancer patient stratification and therapy selection.
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Tumor-Educated Platelet mRNA Profiles for Molecular Pathway Diagnostics

Cross tables of SVM/LOOCV diagnostics with the molecular markers KRAS in (A) CRC, (B) PAAD, and (C) NSCLC patients, (D) KRAS in the combined cohort of patients with either CRC, PAAD, NSCLC, or HBC, (E) EGFR and (F) MET in NSCLC patients, (G) PIK3CA mutations, (H) HER2-amplification, and (I) triple negative status in BrCa patients. Genes, number of mRNAs included in training of the SVM algorithm. See alsoTables S4 and S7.

TEP-Profiles Provide an All-in-One Biosource for Blood-Based Liquid Biopsies in Patients with Cancer

Unequivocal discrimination of primary versus metastatic nature of a tumor may be difficult and hamper adequate therapy selection. Since the TEP profiles closely resemble the different tumor types as determined by their organ of origin—regardless of systemic dissemination—this potentially allows for organ-specific cancer diagnostics. Hence we selected all healthy donors and all patients with primary or metastatic tumor burden in the lung (n = 154), brain (n = 114), or liver (n = 127). We performed “organ exams” and instructed the SVM/LOOCV algorithm to determine for lung, brain, and liver the presence or absence of cancer (96%, 91%, and 96% accuracy, respectively), with cancer subclassified as primary or metastatic tumor (84%, 93%, and 90% accuracy, respectively) and in case of metastases to identify the potential organ of origin (64%, 70%, and 64% accuracy, respectively). The platelet mRNA profiles enabled assignment of the cancer to the different organs with high accuracy (Figure 4). In addition, using the same TEP mRNA profiles we were able to again indicate the biomarker status of the tumor tissues (90%, 82%, and 93% accuracy, respectively) (Figure 4).

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Organ-Focused TEP-Based Cancer Diagnostics

SVM/LOOCV diagnostics of healthy donors (n = 55) and patients with primary or metastatic tumor burden in the lung (n = 99; totaling 154 tests), brain (n = 62; totaling 114 tests), or liver (n = 72; totaling 127 tests), to determine the presence or absence of cancer, with cancer subclassified as primary or metastatic tumor, in case of metastases the identified organ of origin, and the correctly identified molecular markers. Of note, at the exam level of mutational subtypes some samples were included in multiple classifiers (i.e., KRAS, EGFR, PIK3CA,HER2-amplification, MET-overexpression, or triple negative status), explaining the higher number in mutational tests than the total number of included samples. TP, true positive; FP, false positive; FN, false negative; TN, true negative. Indicated are sample numbers and detection rates in percentages.

Discussion

The use of blood-based liquid biopsies to detect, diagnose, and monitor cancer may enable earlier diagnosis of cancer, lower costs by tailoring molecular targeted treatments, improve convenience for cancer patients, and ultimately supplements clinical oncological decision-making. Current blood-based biosources under evaluation demonstrate suboptimal sensitivity for cancer diagnostics, in particular in patients with localized disease. So far, none of the current blood-based biosources, including plasma DNA, exosomes, and CTCs, have been employed for multiclass cancer diagnostics (Alix-Panabières and Pantel, 2014, Bettegowda et al., 2014, Skog et al., 2008), hampering its implementation for early cancer detection. Here, we report that molecular interrogation of blood platelet mRNA can offer valuable diagnostics information for all cancer patients analyzed—spanning six different tumor types. Our results suggest that platelets may be employable as an all-in-one biosource to broadly scan for molecular traces of cancer in general and provide a strong indication on tumor type and molecular subclass. This includes patients with localized disease possibly allowing for targeted diagnostic confirmation using routine clinical diagnostics for each particular tumor type.

Since the discovery of circulating tumor material in blood of patients with cancer (Leon et al., 1977) and the recognition of the clinical utility of blood-based liquid biopsies, a wealth of studies has assessed the use of blood for cancer diagnostics, prognostication and treatment monitoring (Alix-Panabières et al., 2012, Bidard et al., 2014, Crowley et al., 2013, Haber and Velculescu, 2014). By development of highly sensitive targeted detection methods, such as targeted deep sequencing (Newman et al., 2014), droplet digital PCR (Bettegowda et al., 2014), and allele-specific PCR (Maheswaran et al., 2008, Thierry et al., 2014), the utility and applicability of liquid biopsies for clinical implementation has accelerated. These advances previously allowed for a pan-cancer comparison of various biosources and revealed that in >75% of cancers, including advanced stage pancreas, colorectal, breast, and ovarian cancer, cell-free DNA is detectable although detection rates are dependent on the grade of the tumor and depth of analysis (Bettegowda et al., 2014). Here, we show that the platelet RNA profiles are affected in nearly all cancer patients, regardless of the type of tumor, although the abundance of tumor-associated RNAs seems variable among cancer patients. In addition, surrogate RNA onco-signatures of tissue biomarkers, also in 88% of localized KRAS mutant cancer patients as measured by the tumor-specific and pan-cancer SVM/LOOCV procedures, are readily available from a minute amount (100–500 pg) of platelet RNA. As whole blood can be stored up to 48 hr on room temperature prior to isolation of the platelet pellet, while maintaining high-quality RNA and the dominant cancer RNA signatures, TEPs can be more readily implemented in daily clinical laboratory practice and could potentially be shipped prior to further blood sample processing.

Blood platelets are widely involved in tumor growth and cancer progression (Gay and Felding-Habermann, 2011). Platelets sequester solubilized tumor-associated proteins (Klement et al., 2009) and spliced and unspliced mRNAs (Calverley et al., 2010, Nilsson et al., 2011), whereas platelets do also directly interact with tumor cells (Labelle et al., 2011), neutrophils (Sreeramkumar et al., 2014), circulating NK-cells (Palumbo et al., 2005, Placke et al., 2012), and circulating tumor cells (Ting et al., 2014, Yu et al., 2013). Interestingly, in vivo experiments have revealed breast cancer-mediated systemic instigation by supplying circulating platelets with pro-inflammatory and pro-angiogenic proteins, supporting outgrowth of dormant metastatic foci (Kuznetsov et al., 2012). Using a gene ontology methodology, CAGE, we correlated TEP-cancer signatures with publicly available curated datasets. Indeed, we identified widespread correlations with cancer tissues, hypoxia, platelet-signatures, and cytoskeleton, possibly reflecting the “alert” and pro-tumorigenic state of TEPs. We observed strong negative correlations with RNAs implicated in RNA translation, T cell immunity, and interleukin-signaling, implying diminished needs of TEPs for RNAs involved in these biological processes or orchestrated translation of these RNAs to proteins (Denis et al., 2005). We observed that the tumor-specific educational programs in TEPs are predominantly influenced by tumor type and, to a lesser extent, by tumor progression and metastases. Although we were not able to measure significant differences between non-metastasized and metastasized tumors, we do not exclude that the use of larger sample sets could allow for the generation of SVM algorithms that do have the power to discriminate between certain stages of cancer, including those with in situ carcinomas and even pre-malignant lesions. In addition, different molecular tumor subtypes (e.g., HER2-amplified versus wild-type BrCa) result in different effects on the platelet profiles, possibly caused by different “educational” stimuli generated by the different molecular tumor subtypes (Koboldt et al., 2012). Altogether, the RNA content of platelets in patients with cancer is dependent on the transcriptional state of the bone-marrow megakaryocyte (Calverley et al., 2010, McAllister and Weinberg, 2014), complemented by sequestration of spliced RNA (Nilsson et al., 2011), release of RNA (Clancy and Freedman, 2014, Kirschbaum et al., 2015, Rak and Guha, 2012, Risitano et al., 2012), and possibly queue-specific pre-mRNA splicing during platelet circulation. Partial or complete normalization of the platelet profiles following successful treatment of the tumor would enable TEP-based disease recurrence monitoring, requiring the analysis of follow-up platelet samples. Future studies will be required to address the tumor-specific “educated” profiles on both an (small non-coding) RNA (Laffont et al., 2013, Landry et al., 2009, Leidinger et al., 2014, Lu et al., 2005) and protein (Burkhart et al., 2014,Geiger et al., 2013, Klement et al., 2009) level and determine the ability of gene ontology, blood-based cancer classification.

In conclusion, we provide robust evidence for the clinical relevance of blood platelets for liquid biopsy-based molecular diagnostics in patients with several types of cancer. Further validation is warranted to determine the potential of surrogate TEP profiles for blood-based companion diagnostics, therapy selection, longitudinal monitoring, and disease recurrence monitoring. In addition, we expect the self-learning algorithms to further improve by including significantly more samples. For this approach, isolation of the platelet fraction from whole blood should be performed within 48 hr after blood withdrawal, the platelet fraction can subsequently be frozen for cancer diagnosis. Also, future studies should address causes and anticipated risks of outlier samples identified in this study, such as healthy donors classified as cancer patients. Systemic factors such as chronic or transient inflammatory diseases, or cardiovascular events and other non-cancerous diseases may also influence the platelet mRNA profile and require evaluation in follow-up studies, possibly also including individuals predisposed for cancer.

References   

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RNAi, CRISPR and Gene Expression

Larry H. Bernstein, MD, FCAP, Curator

LPBI

2.2.16

2.2.16   RNAi, CRISPR and Gene Expression, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

Down and Out with RNAi and CRISPR

Gene-Silencing and Gene-Disabling Techniques Are Moving To the Heart of Drug Discovery

  • Click Image To Enlarge +
    RNA interference (RNAi) silences, or knocks down, the translation of a gene by inducing degradation of a gene target’s transcript. To advance RNAi applications, Thermo Fisher Scientific has developed two types of small RNA molecules: short interfering RNAs and microRNAs. The company also offers products for RNAi analysis in vitro and in vivo, including libraries for high-throughput applications.

    Genes can be knocked down with RNA interference (RNAi) or knocked out with CRISPR-Cas9. RNAi, the screening workhorse, knocks down the translation of genes by inducing rapid degradation of a gene target’s transcript.

    CRISPR-Cas9, the new but already celebrated genome-editing technology, cleaves specific DNA sequences to render genes inoperative. Although mechanistically different, the two techniques complement one another, and when used together facilitate discovery and validation of scientific findings.

    RNAi technologies along with other developments in functional genomics screening were discussed by industry leaders at the recent Discovery on Target conference. The conference, which emphasized the identification and validation of novel drug targets and the exploration of unknown cellular pathways, included a symposium on the development of CRISPR-based therapies.

    RNAi screening can be performed in either pooled or arrayed formats. Pooled screening provides an affordable benchtop option, but requires back-end deconvolution and deep sequencing to identify the shRNA causing the specific phenotype. Targets are much easier to identify using the arrayed format since each shRNA clone is in an individual well.

    “CRISPR complements RNAi screens,” commented Ryan Raver, Ph.D., global product manager of functional genomics at Sigma-Aldrich. “You can do a whole genome screen with either small interfering RNA (siRNA) or small hairpin RNA (shRNA), then validate with individual CRISPRs to ensure it is a true result.”

    A powerful and useful validation method for knockdown or knockout studies is to use lentiviral open reading frames (ORFs) for gene re-expression, for rescue experiments, or to detect whether the wild-type phenotype is restored. However, the ORF randomly integrates into the genome. Also, with this validation technique, gene expression is not acting under the endogenous promoter. Accordingly, physiologically relevant levels of the gene may not be expressed unless controlled for via an inducible system.

    In the future, CRISPR activators may provide more efficient ways to express not only wild-type but also mutant forms of genes under the endogenous promoter.

    Choice of screening technique depends on the researcher and the research question. Whole gene knockout may be necessary to observe a phenotype, while partial knockdown might be required to investigate functions of essential or lethal genes. Use of both techniques is recommended to identify all potential targets.

    For example, recently, a whole genome siRNA screen on a human glioblastoma cell line identified a gene, known as FAT1, as a negative regulator of apoptosis. A CRISPR-mediated knockout of the gene also conferred sensitivity to death receptor–induced apoptosis with an even stronger phenotype, thereby validating FAT1’s new role and link to extrinsic apoptosis, a new model system.

    Dr. Raver indicated that next-generation RNAi libraries that are microRNA-adapted might have a more robust knockdown of gene expression, up to 90–95% in some cases. Ultracomplex shRNA libraries help to minimize both false-negative and false-positive rates by targeting each gene with ~25 independent shRNAs and by including thousands of negative-control shRNAs.

    Recently, a relevant paper emerged from the laboratory of Jonathan Weissman, Ph.D., a professor of cellular and molecular pharmacology at the University of California, San Francisco. The paper described how a new ultracomplex pooled shRNA library was optimized by means of a microRNA-adapted system. This system, which was able to achieve high specificity in the detection of hit genes, produced robust results. In fact, they were comparable to results obtained with a CRISPR pooled screen. Members of the Weissman group systematically optimized the promoter and microRNA contexts for shRNA expression along with a selection of guide strands.

    Using a sublibrary of proteostasis genes (targeting 2,933 genes), the investigators compared CRISPR and RNAi pooled screens. Data showed 48 hits unique to RNAi, 40 unique to CRISPR, and an overlap of 21 hits (with a 5% false discovery rate cut-off). Together, the technologies provided a more complete research story.

    Arrayed CRISPR Screens

  • Click Image To Enlarge +
    Synthetic crRNA:tracrRNA reagents can be used in a similar manner to siRNA reagents for assessment of phenotypes in a cell population. Top row: A reporter cell line stably expressing Cas9 nuclease was transfected with GE Dharmacon’s Edit-R synthetic crRNA:tracrRNA system, which was used to target three positive control genes (PSMD7, PSMD14, and VCP) and a negative control gene (PPIB). Green cells indicate EGFP signaling occuring as a result of proteasome pathway disruption. Bottom row: A siGENOME siRNA pool targeting the same genes was used in the same reporter cell line.

    “RNA screens are well accepted and will continue to be used, but it is important biologically that researchers step away from the RNA mechanism to further study and validate their hits to eliminate potential bias,” explained Louise Baskin, senior product manager, Dharmacon, part of GE Healthcare. “The natural progression is to adopt CRISPR in the later stages.”

    RNAi uses the cell’s endogenous mechanism. All of the components required for gene knockdown are already within the cell, and the delivery of the siRNA starts the process. With the CRISPR gene-editing system, which is derived from a bacterial immune defense system, delivery of both the guide RNA and the Cas9 nuclease, often the rate limiter in terms of knockout efficiency, are required.

    In pooled approaches, the cell has to either drop out or overexpress so that it is sortable, limiting the types of addressable biological questions. A CRISPR-arrayed approach opens up the door for use of other analytical tools, such as high-content imaging, to identify hits of interest.

    To facilitate use of CRISPR, GE recently introduced Dharmacon Edit-R synthetic CRISPR RNA (crRNA) libraries that can be used to carry out high-throughput arrayed analysis of multiple genes. Rather than a vector- or plasmid-based gRNA to guide the targeting of the Cas9 cleavage, a synthetic crRNA and tracrRNA are used. These algorithm-designed crRNA reagents can be delivered into the cells very much like siRNA, opening up the capability to screen multiple target regions for many different genes simultaneously.

    GE showed a very strong overlap between CRISPR and RNAi using this arrayed approach to validate RNAi screen hits with synthetic crRNA. The data concluded that CRISPR can be used for medium- or high-throughput validation of knockdown studies.

    “We will continue to see a lot of cooperation between RNAi and gene editing,” declared Baskin. “Using the CRISPR mechanism to knockin could introduce mutations to help understand gene function at a much deeper level, including a more thorough functional analysis of noncoding genes.

    “These regulatory RNAs often act in the nucleus to control translation and transcription, so to knockdown these genes with RNAi would require export to the cytoplasm. Precision gene editing, which takes place in the nucleus, will help us understand the noncoding transcriptome and dive deeper into how those genes regulate disease progression, cellular development and other aspects of human health and biology.”

    Tool Selection

    Click Image To Enlarge +
    Schematic of a pooled shRNA screening workflow developed by Transomic Technologies. Cells are transduced, and positive or negative selection screens are performed. PCR amplification and sequencing of the shRNA integrated into the target cell genome allows the determination of shRNA representation in the population.

    The functional genomics tool should fit the specific biology; the biology should not be forced to fit the tool. Points to consider include the regulation of expression, the cell line or model system, as well as assay scale and design. For example, there may be a need for regulatable expression. There may be limitations around the cell line or model system. And assay scale and design may include delivery conditions and timing to optimally complete perturbation and reporting.

    “Both RNAi- and CRISPR-based gene modulation strategies have pros and cons that should be considered based on the biology of the genes being studied,” commented Gwen Fewell, Ph.D., chief commercial officer, Transomic Technologies.

    RNAi reagents, which can produce hypomorphic or transient gene-suppression states, are well known for their use in probing drug targets. In addition, these reagents are enriching studies of gene function. CRISPR-Cas9 reagents, which produce clean heterozygous and null mutations, are important for studying tumor suppressors and other genes where complete loss of function is desired.

    Timing to readout the effects of gene perturbation must be considered to ensure that the biological assay is feasible. RNAi gene knockdown effects can be seen in as little as 24–72 hours, and inducible and reversible gene knockdown can be realized. CRISPR-based gene knockout effects may become complete and permanent only after 10 days.

    Both RNAi and CRISPR reagents work well for pooled positive selection screens; however, for negative selection screens, RNAi is the more mature tool. Current versions of CRISPR pooled reagents can produce mixed populations containing a fraction of non-null mutations, which can reduce the overall accuracy of the readout.

    To meet the needs of varied and complex biological questions, Transomic Technologies has developed both RNAi and CRISPR tools with options for optimal expression, selection, and assay scale. For example, the company’s shERWOOD-UltramiR shRNA reagents incorporate advances in design and small RNA processing to produce increased potency and specificity of knockdown, particularly important for pooled screens.

    Sequence-verified pooled shRNA screening libraries provide flexibility in promoter choice, in vitro formats, in vivo formats, and a choice of viral vectors for optimal delivery and expression in biologically relevant cell lines, primary cells or in vivo.

    The company’s line of lentiviral-based CRISPR-Cas9 reagents has variable selectable markers such that guide RNA- and Cas9-expressing vectors, including inducible Cas9, can be co-delivered and selected for in the same cell to increase editing efficiency. Promoter options are available to ensure expression across a range of cell types.

    “Researchers are using RNAi and CRISPR reagents individually and in combination as cross-validation tools, or to engineer CRISPR-based models to perform RNAi-based assays,” informs Dr. Fewell. “Most exciting are parallel CRISPR and RNAi screens that have tremendous potential to uncover novel biology.”

    Converging Technologies

    The convergence of RNAi technology with genome-editing tools, such as CRISPR-Cas9 and transcription activator-like effector nucleases, combined with next-generation sequencing will allow researchers to dissect biological systems in a way not previously possible.

    “From a purely technical standpoint, the challenges for traditional RNAi screens come down to efficient delivery of the RNAi reagents and having those reagents provide significant, consistent, and lasting knockdown of the target mRNAs,” states Ross Whittaker, Ph.D., a product manager for genome editing products at Thermo Fisher Scientific. “We have approached these challenges with a series of reagents and siRNA libraries designed to increase the success of RNAi screens.”

    Thermo Fisher’ provides lipid-transfection RNAiMax reagents, which effectively deliver siRNA. In addition, the company’s Silencer and Silencer Select siRNA libraries provide consistent and significant knockdown of the target mRNAs. These siRNA libraries utilize highly stringent bioinformatic designs that ensure accurate and potent targeting for gene-silencing studies. The Silencer Select technology adds a higher level of efficacy and specificity due to chemical modifications with locked nucleic acid (LNA) chemistry.

    The libraries alleviate concerns for false-positive or false-negative data. The high potency allows less reagent use; thus, more screens or validations can be conducted per library.

    Dr. Whittaker believes that researchers will migrate regularly between RNAi and CRISPR-Cas9 technology in the future. CRISPR-Cas9 will be used to create engineered cell lines not only to validate RNAi hits but also to follow up on the underlying mechanisms. Cell lines engineered with CRISPR-Cas9 will be utilized in RNAi screens. In the long term, CRISPR-Cas9 screening will likely replace RNAi screening in many cases, especially with the introduction of arrayed CRISPR libraries.

    Validating Antibodies with RNAi

    Unreliable antibody specificity is a widespread problem for researchers, but RNAi is assuaging scientists’ concerns as a validation method.

    The procedure introduces short hairpin RNAs (shRNAs) to reduce expression levels of a targeted protein. The associated antibody follows. With its protein knocked down, a truly specific antibody shows dramatically reduced or no signal on a Western blot. Short of knockout animal models, RNAi is arguably the most effective method of validating research antibodies.

    The method is not common among antibody suppliers—time and cost being the chief barriers to its adoption, although some companies are beginning to embrace RNAi validation.

    “In the interest of fostering better science, Proteintech felt it was necessary to implement this practice,” said Jason Li, Ph.D., founder and CEO of Proteintech Group, which made RNAi standard protocol in February 2015. “When researchers can depend on reproducibility, they execute more thorough experiments and advance the treatment of human diseases and conditions.”

Junk DNA Kept in Good Repair by Nuclear Membrane  

Heterochromatin has the dubious distinction of being called the “dark matter” of DNA, and it has even suffered the indignity of being dismissed as “junk DNA.” But it seems to get more respectful treatment inside the nucleus, where it has the benefit of a special repair mechanism. This mechanism, discovered by scientists based at the University of Southern California (USC), transports broken heterochromatin sequences from the hurly-burly of the heterochromatin domain so that they can be repaired in the relative peace and quiet of the nuclear periphery.

This finding suggests that the nuclear membrane is more versatile than is generally appreciated. Yes, it serves as a protective container for nuclear material, and it uses its pores to manage the transport of molecules in and out of the nucleus. But it may also play a special role in maintaining the integrity of heterochromatin, which tends to be overlooked because it consists largely of noncoding DNA, including repetitive stretches of no apparent function.

“Scientists are now starting to pay a lot of attention to this mysterious component of the genome,” said Irene E. Chiolo, Ph.D., an assistant professor at USC. “Heterochromatin is not only essential for chromosome maintenance during cell division; it also poses specific threats to genome stability. Heterochromatin is potentially one of the most powerful driving forces for cancer formation, but it is the ‘dark matter’ of the genome. We are just beginning to unravel how repair works here.”

Dr. Chilo led an effort to understand how heterochromatin stays in good repair, even though it is particularly vulnerable to a kind of repair error called ectopic recombination. This kind of error is apt to occur when flaws in repeated sequences undergo homologous recombination (HR) by means of double-strand break (DSB) repair. Specifically, repeated sequences tend to recombine with each other during DNA repair.

Working with the fruit fly Drosophila melanogaster, Dr. Chilo’s team observed that breaks in heterochromatin are repaired after damaged sequences move away from the rest of the chromosome to the inner wall of the nuclear membrane. There, a trio of proteins mends the break in a safe environment, where it cannot accidentally get tangled up with incorrect chromosomes.

The details appeared October 26 in Nature Cell Biology, in an article entitled, “Heterochromatic breaks move to the nuclear periphery to continue recombinational repair.”

“[Heterochromatic] DSBs move to the nuclear periphery to continue HR repair,” the authors wrote. “Relocalization depends on nuclear pores and inner nuclear membrane proteins (INMPs) that anchor repair sites to the nuclear periphery through the Smc5/6-interacting proteins STUbL/RENi. Both the initial block to HR progression inside the heterochromatin domain, and the targeting of repair sites to the nuclear periphery, rely on SUMO and SUMO E3 ligases.”

“We knew that nuclear membrane dysfunctions are common in cancer cells,” Dr. Chiolo said. “Our studies now suggest how these dysfunctions can affect heterochromatin repair and have a causative role in cancer progression.”

This study may help reveal how and why organisms become more predisposed to cancer as they age—the nuclear membrane progressively deteriorates as an organism ages, removing this bulwark against genome instability.

Next, Dr. Chiolo and her team will explore how the movement of broken sequences is accomplished and regulated, and what happens in cells and organisms when this membrane-based repair mechanism fails. Their ultimate goal is to understand how this mechanism functions in human cells and identify new strategies to prevent their catastrophic failure and cancer formation.

Gene Found that Regulates Stem Cell Number Production

Gene Found that Regulates Stem Cell Number Production

The gene Prkci promotes the generation of differentiated cells (red). However if Prkci activity is reduced or absent, neural stem cells (green) are promoted. [In Kyoung Mah]

A scientific team from the University of Southern California (USC) and the University of California, San Diego have described an important gene that maintains a critical balance between producing too many
and too few stem cells. Called Prkci, the gene influences whether stem cells self-renew to produce more stem cells, or differentiate into more specialized cell types, such as blood or nerves.

When it comes to stem cells, too much of a good thing isn’t necessarily a benefit: producing too many new stem cells may lead to cancer; making too few inhibits the repair and maintenance of the body.

In their experiments, the researchers grew mouse embryonic stem cells, which lacked Prkci, into embryo-like structures in the laboratory. Without Prkci, the stem cells favored self-renewal, generating large numbers of stem cells and, subsequently, an abundance of secondary structures.

Upon closer inspection, the stem cells lacking Prkci had many activated genes typical of stem cells, and some activated genes typical of neural, cardiac, and blood-forming cells. Therefore, the loss of Prkci can also encourage stem cells to differentiate into the progenitor cells that form neurons, heart muscle, and blood.

Prkci achieves these effects by activating or deactivating a well-known group of interacting genes that are part of the Notch signaling pathway. In the absence of Prkci, the Notch pathway produces a protein that signals to stem cells to make more stem cells. In the presence of Prkci, the Notch pathway remains silent, and stem cells differentiate into specific cell types.

These findings have implications for developing patient therapies. Even though Prkci can be active in certain skin cancers, inhibiting it might lead to unintended consequences, such as tumor overgrowth. However, for patients with certain injuries or diseases, it could be therapeutic to use small molecule inhibitors to block the activity of Prkci, thus boosting stem cell production.

“We expect that our findings will be applicable in diverse contexts and make it possible to easily generate stem cells that have typically been difficult to generate,” said Francesca Mariani, Ph.D., principal investigator at the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC.

Their study (“Atypical PKC-iota Controls Stem Cell Expansion via Regulation of the Notch Pathway”) was published in a Stem Cell Reports.

Atypical PKC-iota Controls Stem Cell Expansion via Regulation of the Notch Pathway

In Kyoung Mah,1 Rachel Soloff,2,3 Stephen M. Hedrick,2 and Francesca V. Mariani1, *

Stem Cell Reports (2015),     http://dx.doi.org/10.1016/j.stemcr.2015.09.021

The number of stem/progenitor cells available can profoundly impact tissue homeostasis and the response to injury or disease. Here, we propose that an atypical PKC, Prkci, is a key player in regulating the switch from an expansion to a differentiation/maintenance phase via regulation of Notch, thus linking the polarity pathway with the control of stem cell self-renewal. Prkci is known to influence symmetric cell division in invertebrates; however a definitive role in mammals has not yet emerged. Using a genetic approach, we find that loss of Prkci results in a marked increase in the number of various stem/progenitor cells. The mechanism used likely involves inactivation and symmetric localization of NUMB, leading to the activation of NOTCH1 and its downstream effectors. Inhibition of atypical PKCs may be useful for boosting the production of pluripotent stem cells, multipotent stem cells, or possibly even primordial germ cells by promoting the stem cell/progenitor fate.

The control of asymmetric versus symmetric cell division in stem and progenitor cells balances self-renewal and differentiation to mediate tissue homeostasis and repair and involves key proteins that control cell polarity. In the case of excess symmetric division, too many stem-cell-like daughter cells are generated that can lead to tumor initiation and growth. Conversely, excess asymmetric cell division can severely limit the number of cells available for homeostasis and repair (Go´mez-Lo´pez et al., 2014; Inaba and Yamashita, 2012). The Notch pathway has been implicated in controlling stem cell self-renewal in a number of different contexts (Hori et al., 2013). However, how cell polarity, asymmetric cell division, and the activation of determinants ultimately impinges upon the control of stem cell expansion and maintenance is not fully understood. In this study, we examine the role of an atypical protein kinase C (aPKC), PRKCi, in stem cell self-renewal and, in particular, determine whether PRKCi acts via the Notch pathway. PKCs are serine-threonine kinases that control many basic cellular processes and are typically classified into three subgroups—conventional, novel, and the aPKCs iota and zeta, which, in contrast to the others, are not activated by diacylglyceride or calcium. The aPKC proteins are best known for being central components of an evolutionarily conserved Par3-Par6-aPKC trimeric complex that controls cell polarity in C. elegans, Drosophila, Xenopus, zebrafish, and mammalian cells (Suzuki and Ohno, 2006).

Before Notch influences stem cell self-renewal, the regulation of cell polarity, asymmetric versus symmetric cell division, and the segregation of cell fate determinants such as NUMB may first be required (Knoblich, 2008). For example, mutational analysis in Drosophila has demonstrated that the aPKC-containing trimeric complex is required for maintaining polarity and for mediating asymmetric cell division during neurogenesis via activation and segregation of NUMB (Wirtz-Peitz et al., 2008). NUMB then functions as a cell fate determinant by inhibiting Notch signaling and preventing self-renewal (Wang et al., 2006). In mammals, the PAR3-PAR6-aPKC complex also can bind and phosphorylate NUMB in epithelial cells and can regulate the unequal distribution of Numb during asymmetric cell division (Smith et al., 2007). During mammalian neurogenesis, asymmetric division is also thought to involve the PAR3-PAR6-aPKC complex, NUMB segregation, and NOTCH activation (Bultje et al., 2009).

Mice deficient in Prkcz are grossly normal, with mild defects in secondary lymphoid organs (Leitges et al., 2001). In contrast, deficiency of the Prkci isozyme results in early embryonic lethality at embryonic day (E)9.5 (Seidl et al., 2013; Soloff et al., 2004). A few studies have investigated the conditional inactivation of Prkci; however, no dramatic changes in progenitor generation were detected in hematopoietic stem cells (HSCs) or the brain (Imai et al., 2006; Sengupta et al., 2011), although one study found evidence of a role for Prkci in controlling asymmetric cell division in the skin (Niessen et al., 2013). Analysis may be complicated by functional redundancy between the iota and zeta isoforms and/or because further studies perturbing aPKCs in specific cell lineages and/or at specific developmental stages are needed.

Here, we investigate the requirement of Prkci in mouse cells using an in vitro system that bypasses early embryonic lethality. Embryonic stem (ES) cells are used to make embryoid bodies (EBs) that develop like the early post-implantation embryo in terms of lineage specification and morphology and can also be maintained in culture long enough to observe advanced stages of cellular differentiation (Desbaillets et al., 2000). Using this approach, we provide genetic evidence that inactivation of Prkci signaling leads to enhanced generation of pluripotent cells and some types of multipotent stem cells, including cells with primordial germ cell (PGC) characteristics. In addition, we provide evidence that aPKCs ultimately regulate stem cell fate via the Notch pathway.

Figure 1. Prkci/ EBs Contain Cells with Pluripotency Characteristics (A and A0 ) Day (d) 12 heterozygous EBs have few OCT4/E-CAD+ cells, while null EBs contain many in clusters at the EB periphery. Inset: OCT4 (nucleus)/E-CAD (cytoplasm) double-positive cells. (B and B0 ) Adjacent sections in a null EB show that OCT4+ cells are likely also SSEA1+. (C) Dissociated day-12 Prkci/ EBs contain five to six times more OCT4+ and approximately three times more SSEA1+ cells than heterozygous EBs (three independent experiments). (D and D0 ) After 2 days in ES cell culture, no colonies are visible in null SSEA1 cultures while present in null SSEA1+ cultures (red arrows). (E–E00) SSEA1+ sorted cells can be maintained for many passages, 27+. (E) Prkci+/ sorted cells make colonies with differentiated cells at the outer edges (n = 27/35). (E0 ) Null cells form colonies with distinct edges (n = 39/45). (E00) The percentage of undifferentiated colonies is shown. ***p < 0.001. (F) Sorted null cells express stem cell and differentiation markers at similar levels to normal ES cells (versus heterozygous EBs) (three independent experiments). (G) EBs made from null SSEA1+ sorted cells express germ layer marker genes at the indicated days. Error bars indicate mean ± SEM, three independent experiments. Scale bars, 100 mm in (A, D, and E); 25 mm in (B). See also Figure S1.

RESULTS

Prkci/ Cultures Have More Pluripotent Cells Even under Differentiation Conditions First, we compared Prkci null EB development to that of Prkci/ embryos. Consistent with another null allele (Seidl et al., 2013), both null embryos and EBs fail to properly cavitate (Figures S1A and S1B). The failure to cavitate is unlikely to be due to the inability to form one of the three germ layers, as null EBs express germ-layer-specific genes (Figure S1E). A failure of cavitation could alternatively be caused by an accumulation of pluripotent cells. For example, EBs generated from Timeless knockdown cells do not cavitate and contain large numbers of OCT4-expressing cells (O’Reilly et al., 2011). In addition, EBs generated with Prkcz isoform knockdown cells contain OCT4+ cells under differentiation conditions (Dutta et al., 2011; Rajendran et al., 2013). Thus, we first evaluated ES colony differentiation by alkaline phosphatase (AP) staining. After 4 days without leukemia inhibitory factor (LIF), Prkci/ ES cell colonies retained crisp boundaries and strong AP staining. In contrast, Prkci+/ colonies had uneven colony boundaries with diffuse AP staining (Figures S1F–S1F00). To definitively detect pluripotent cells, day-12 EBs were assayed for OCT4 and E-CADHERIN (E-CAD) protein expression. Prkci+/ EBs had very few OCT4/E-CAD double-positive cells (Figure 1A); however, null EBs contained large clusters of OCT4/E-CAD double-positive cells, concentrated in a peripheral zone (Figure 1A0 ). By examining adjacent sections, we found that OCT4+ cells could also be positive for stage-specific embryonic antigen 1 (SSEA1) (Figures 1B and 1B0 ). Quantification by fluorescence-activated cell sorting (FACS) analysis showed that day-12 Prkci/ EBs had more OCT4+ and SSEA1+ cells than Prkci+/ EBs (Figure 1C). We did not find any difference between heterozygous and wild-type cells with respect to the number of OCT4+ or SSEA1+ cells or in their levels of expression for Oct4, Nanog, and Sox2 (Figures S1I, S1I0 and S1J). However, we did find that Oct4, Nanog, and Sox2 were highly upregulated in OCT4+ null cells (Figure S1G). Thus, together, these data indicate that Prkci/ EBs contain large numbers of pluripotent stem cells, despite being cultured under differentiation conditions.

Functional Pluripotency Tests If primary EBs have a pluripotent population with the capacity to undergo self-renewal, they can easily form secondary EBs (O’Reilly et al., 2011). Using this assay, we found that more secondary EBs could be generated from Prkci/ versus Prkci+/ EBs, especially at days 6, 10, and 16; even when plated at a low density to control for aggregation (Figure S1H). To test whether SSEA1+ cells could maintain pluripotency long term, FACS-sorted Prkci/ SSEA1+ and SSEA1 cells were plated at a low density and maintained under ES cell culture conditions. SSEA1 cells were never able to form identifiable colonies and could not be maintained in culture (Figure 1D). SSEA1+ cells, however, formed many distinct colonies after 2 days of culture, and these cells could be maintained for over 27 passages (Figures 1D0 , 1E0 , and 1E00). Prkci+/ SSEA1+ cells formed colonies that easily differentiated at the outer edge, even in the presence of LIF (Figure 1E). In contrast Prkci/ SSEA1+ cells maintained distinct round colonies (Figure 1E0 ). Next, we determined whether null SSEA1+ cells expressed pluripotency and differentiation markers similarly to normal ES cells. Indeed, we found that Oct4, Nanog, and Sox2 were upregulated in both null SSEA1+ EB cells and heterozygous ES cells. In addition, differentiated markers (Fgf5, T, Wnt3, and Afp) and tissue stem/progenitor cell markers (neural: Nestin, Sox1, and NeuroD; cardiac: Nkx2-5 and Isl1; and hematopoietic: Gata1 and Hba-x) were downregulated in both SSEA1+ cells and heterozygous ES cells (Figure 1F). SSEA1+ cells likely have a wide range of potential, since EBs generated from these cells expressed markers for all three germ layers (Figure 1G).

Figure 2. Prkci and Pluripotency Pathways (A) ERK1/2 phosphorylation (Y202/Y204) is reduced in null ES cells and early day (d)-6 null EBs compared to heterozygous EBs and strongly increased at later stages. The first lane shows ES cells activated (A) by serum treatment 1 day after serum depletion. (B) Quantification of pERK1/2 normalized to non-phosphorylated ERK1/2 (three independent experiments; mean ± SEM; **p < 0.01). (C) pERK1/2 Y202/Y204 is strongly expressed in the columnar epithelium of heterozygous EBs that have just cavitated. Null EBs have lower expression. OCT4 and pERK1/2 expression do not co-localize. Scale bar, 100 mm. (D) pERK1/2Y202/Y204 levels are lower in null SSEA1+ sorted cells than in heterozygous or in null day-12 EBs that have undergone further differentiation. pSTAT3 and STAT levels are unchanged. See also Figure S2.

ERK1/2 Signaling during EB Development Stem cell self-renewal has been shown to require the activation of the JAK/STAT3 and PI3K/AKT pathways and the inhibition of ERK1/2 and GSK3 pathways (Kunath et al., 2007; Niwa et al., 1998; Sato et al., 2004; Watanabe et al., 2006). We found that both STAT3 and phosphorylated STAT3 levels were not grossly altered and that the p-STAT3/STAT3 ratio was similar between heterozygous and null ES cells and EBs (Figures S2A and S2B). In addition we did not see any difference in AKT, pAKT, or b-CATENIN levels when comparing heterozygous to null ES cells or EBs (Figures S2A and S2C). Thus, the effects observed by the loss of Prkci are unlikely to be due to a significant alteration in the JAK/STAT3, PI3K/AKT, or GSK3 pathways.

Next, we investigated ERK1/2 expression and activation. Consistent with other studies showing ERK1/2 activation to be downstream of Prkci in some mammalian cell types (Boeckeler et al., 2010; Litherland et al., 2010), pERK1/2 was markedly inactivated in Prkci null versus heterozygous ES cells. In addition, during differentiation, null EBs displayed strong pERK1/2 inhibition early (until day 6). Later, pERK1/2 was activated strongly, as the EB began differentiating (Figures 2A and 2B). By immunofluorescence, pERK1/2 was strongly enriched in the columnar epithelium of control EBs, while overall levels were much lower in Prkci/ EBs (Figure 2C). In addition, high OCT4 expression correlated with a marked inactivation of pERK1/2 (Figure 2C). Next, we examined Prkci/ SSEA1+ cells by western blot. We found that SSEA1+ cells isolated from day-12 null EBs had pSTAT3 expression levels similar to whole EBs, while pERK1/2 levels were low (Figure 2D). Thus, these experiments indicate that the higher numbers of pluripotent cells in null EBs correlate with a strong inactivation of ERK1/2.

Neural Stem Cell Fate Is Favored in Prkci/ EBs It is well known that ERK/MEK inhibition is not sufficient for pluripotent stem cell maintenance (Ying et al., 2008); thus, other pathways are likely involved. Therefore, we used a TaqMan Mouse Stem Cell Pluripotency Panel (#4385363) on an OpenArray platform to investigate the mechanism of Prkci action. Day 13 and day 20 Prkci/ EBs expressed high levels of pluripotency and stemness markers versus heterozygous EBs, including Oct4, Utf1, Nodal, Xist, Fgf4, Gal, Lefty1, and Lefty2. However, interestingly, EBs also expressed markers for differentiated cell types and tissue stem cells, including Sst, Syp, and Sycp3 (neural-related genes), Isl1 (cardiac progenitor marker), Hba-x, and Cd34 (hematopoietic markers). Based on this first-pass test, we sought to determine whether loss of Prkci might favor the generation of neural, cardiac, and hematopoietic cell types and/or their progenitors.

Figure 3. Neural Stem Cell Populations Are Increased in Null EBs (A–C0 ) Prkci/ EBs (B) have more NESTINpositive cells than Prkci+/ EBs (A). (C and C0 ) MAP2 and TUJ1 are expressed in null EBs, similarly to heterozygous EBs (data not shown). (D) EBs were assessed for PAX6 expression, and the images were used for quantification (Figures S3A and S3B). The pixel count ratio of PAX6+ cells in null EBs (green) is substantially higher than that found in heterozygous EBs (black) (three independent experiments; mean ± SEM; *p < 0.05). (E–F000) Day 4 after RA treatment, Prkci/ EBs have more NESTIN- than TUJ1-positive neurons (E and F). However, null cells can still terminally differentiate into NEUROD-, NEUN-, and MAP2-positive cells (F0 –F000). Scale bars, 25 mm in (A and C) and 50 mm in (E). See also Figure S3. Ste

The Generation of Cardiomyocyte and Erythrocyte Progenitors Is Also Favored Next, we examined ISL1 expression (a cardiac stem cell marker) by immunofluorescence and found that Prkci/ EBs contained larger ISL1 clusters compared with Prkci+/ EBs; this was confirmed using an image quantification assay (Figures 4A, 4A0 , and 4C). Differentiated cardiac cells and ventral spinal neurons can also express ISL1 (Ericson et al., 1992); therefore, we also examined Nkx2-5 expression, a better stem cell marker and regulator of cardiac progenitor determination (Brown et al., 2004), by RT-PCR and immunofluorescence. In null EBs, Nkx2-5 was upregulated (Figure 4D). In addition, in response to RA, which can promote cardiac fates in vitro (Niebruegge et al., 2008), cells expressing NKX2-5 were more prevalent in null versus heterozygous EBs (Figures 4B and 4B0 ).The abundant cardiac progenitors found in null EBs were still capable of undergoing differentiation (Figures 4E–4F0 ).

Figure 4. Cardiomyocyte and Erythrocyte Progenitors Are Increased in Prkci/ EBs (A–F0 ) In (A, A0 , E, and E0 ), Prkci/ EBs cultured without LIF have more ISL1 (cardiac progenitor marker) and a-ACTININ-positive cells compared to heterozygous EBs. (C) At day (d) 9, the pixel count ratio for ISL1 expression indicates that null EBs (green) have larger ISL1 populations than heterozygous EBs (black) (three independent experiments, n = 20 heterozygous EBs, 21 null EBs total; mean ± SEM; *p < 0.05). In (B, B0 , D, F, and F0 ), RA treatment induces more NKX2-5 (both nuclear and cytoplasmic) and a-ACTININ expression in null EBs. Arrows point to fibers in (F0 ). (G) Null EBs (green) generate more beating EBs with RA treatment compared to heterozygous EBs (black) (four independent experiments; mean ± SEM; *p < 0.05, ***p < 0.001). (H) Dissociated null EBs of different stages (green) generate more erythrocytes in a colony-forming assay (CFU-E) (four independent experiments; mean ± SEM; **p < 0.01). (I) Examples of red colonies. (J) Gene expression for primitive HSC markers is upregulated in null EBs (relative to heterozygous EBs) (three independent experiments; mean ± SEM). Scale bars, 50 mm in (A, B, and E); 100 mm in (F), and 25 mm in (I). See also Figure S4. 6

Hba-x expression is restricted to yolk sac blood islands and primitive erythrocyte populations (Lux et al., 2008; Trimborn et al., 1999). Cd34 is also a primitive HSC marker (Sutherland et al., 1992). Next, we determined whether the elevated expression of these markers observed with OpenArray might represent higher numbers of primitive hematopoietic progenitors. Using a colony-forming assay (Baum et al., 1992), we found that red colonies (indicative of erythrocyte differentiation; examples in Figure 4I) were produced significantly earlier and more readily from cells isolated from null versus heterozygous EBs (Figure 4H). By quantitative real-time PCR, upregulation of Hba-x and Cd34 genes confirmed the OpenArray results (Figure 4J). In addition, we found Gata1, an erythropoiesis-specific factor, and Epor, an erythropoietin receptor that mediates erythroid cell proliferation and differentiation (Chiba et al., 1991), to be highly upregulated in null versus heterozygous EBs (Figure 4J). These data suggest that the loss of Prkci promotes the generation of primitive erythroid progenitors that can differentiate into erythrocytes.

To determine whether the aforementioned tissue stem cells identified were represented in the OCT4+ population that we described earlier, we examined the expression of PAX6, ISL1, and OCT4 in adjacent EB sections. We found that cells expressing OCT4 appeared to represent a distinct population from those expressing PAX6 and ISL1 (although some cells were PAX6 and ISL1 double-positive) (Figures S4A–S4C).

Prkci/ Cells Are More Likely to Inherit NUMB/aNOTCH1 Symmetrically The enhanced production of both pluripotent and tissue stem cells suggests that the mechanism underlying the action of Prkci in these different contexts is fundamentally similar. Because the Notch pathway controls stem cell self-renewal in many contexts (Hori et al., 2013), and because previous studies implicated a connection between PRKCi function and the Notch pathway (Bultje et al., 2009; Smith et al., 2007), we examined the localization and activation of a key player in the Notch pathway, NUMB, (Inaba and Yamashita, 2012). Differences in NUMB expression were first evident in whole EBs, where polarized expression was evident in the ectodermal and endodermal epithelia of heterozygous EBs, while Prkci/ EBs exhibited a more even distribution (Figures 5A–5B0 ). To more definitively determine the inheritance of NUMB during cell division, doublets undergoing telophase or cytokinesis were scored for symmetric (evenly distributed in both cells) or asymmetric (unequally distributed) NUMB localization (examples: Figures 5C and 5C0 ).

Because NUMB can be directly phosphorylated by aPKCs (both PRKCi and PRKCz) (Smith et al., 2007; Zhou et al., 2011), loss of Prkci might be expected to lead to decreased NUMB phosphorylation. Three NUMB phosphorylation sites—Ser7, Ser276, and Ser295—could be aPKC mediated (Smith et al., 2007). By immunofluorescence, we found that one of the most well-characterized sites (Ser276), was strongly inactivated in null versus heterozygous EBs, especially in the core (Figures 5F and 5G). Western analysis also confirmed that the levels of pNUMB (Ser276) were decreased in null versus heterozygous EBs (Figure S5F). Thus, genetic inactivation of Prkci leads to a marked decrease in the phosphorylation status of NUMB.

Notch pathway inhibition by NUMB has been observed in flies and mammals (Berdnik et al., 2002; French et al., 2002). Therefore, we investigated whether reduced Numb activity in Prkci/ EBs might lead to enhanced NOTCH1 activity and the upregulation of the downstream transcriptional readouts (Meier-Stiegen et al., 2010). An overall increase in NOTCH1 activation was supported by western blot analysis showing that the level of activated NOTCH1 (aNOTCH1) was strongly increased in day 6 and day 10 null versus heterozygous EBs (Figure S5G). This was supported by immunofluorescence in EBs, where widespread strong expression of aNOTCH1 was seen in most null cells (Figures 5I and 5I0 ), while in heterozygous EBs, this pattern was observed only in the OCT4+ cells (Figures 5H and 5H0 ).

Figure 5. Prkci/ Cells Preferentially Inherit Symmetric Localization of NUMB and aNOTCH1 and Notch Signaling Is Required for Stem Cell Self-Renewal in Null Cells (A–B0 ) In (A and B), day (d)-7 heterozygous EBs have polarized NUMB localization within epithelia and strong expression in the endoderm, while null EBs have a more even distribution. (A0 and B0 ) Enlarged views. (C and C0 ) Asymmetric and symmetric NUMB expression examples. (D) Doublets from day-10 null EBs have more symmetric inheritance when compared to day-10 heterozygous doublets (three independent experiments; mean ± SEM; **p < 0.01). A red line indicates a ratio of 1 (equal percent symmetric and asymmetric). (E) CD24high null doublets exhibited more symmetric NUMB inheritance than CD24high heterozygous doublets (three independent experiments; mean ± SEM; *p < 0.05). A red line indicates where the ratio is 1. (F and G) Decreased pNUMB (Ser276) is evident in the core of null versus heterozygous EBs (n = 10 of each genotype). (H–I0 ) In (H and I), aNOTCH1 is strongly expressed in heterozygous EBs, including both OCT4+ and OCT4 cells, while strong aNOTCH1 expression is predominant in OCT4+ cells of null EBs (n = 10 of each genotype)). (H0 and I0 ) Enlarged views of boxed regions. OCT4+ cells are demarcated with dotted lines. (J and J0 ) OCT4+ cells express HES5 strongly in the nucleus (three independent experiments). (K) Null doublets from dissociated EBs have more symmetric aNOTCH1 inheritance compared to heterozygous doublets (three independent experiments; mean ± SEM; **p < 0.01). A red line indicates where the ratio is 1. (L) CD24high Prkci/ doublets exhibit more symmetric aNOTCH1 than CD24high heterozygous doublets (three independent experiments; mean ± SEM; *p < 0.05). A red line indicates where the ratio is 1. (M and M0 ) Examples of asymmetric and symmetric aNOTCH1 localization. (N and O) Day-3 DMSO-treated null ES colonies show strong AP staining all the way to the colony edge in (N). Treatment with 3 mM DAPT led to more differentiation in (O). (P–R) OCT4 is strongly expressed in day-4 DMSO-treated null ES cultures (P). With DAPT (Q,R), OCT4 expression is decreased. (S) Working model: In daughter cells that undergo differentiation, PRKCi can associate with PAR3 and PAR6. NUMB is recruited and directly phosphorylated. The activation of NUMB then leads to an inhibition in NOTCH1 activation and stimulation of a differentiation/maintenance program. In the absence of Prkci, the PAR3/PAR6 complex cannot assemble (although it may do so minimally with Prkcz). NUMB asymmetric localization and phosphorylation is reduced. Low levels of pNUMB are not sufficient to block NOTCH1 activation, and activated NOTCH1 preserves the stem cell self-renewal program. We suggest that PRKCi functions to drive differentiation by pushing the switch from an expansion phase that is symmetric to a differentiation and/or maintenance phase that is predominantly asymmetric. In situations of low or absent PRKCi, we propose that the expansion phase is prolonged. Scale bars, 50 mm in (A, B, F, G, H, I, J, J0 , P–R); 200 mm in (A0 and B0 ); 25 mm in (C, C0 , M, and M0 ); and 100 mm in (H0 , I0 , N, and O). See also Figure S5.

Figure 6. Additional Inhibition of PRKCz Results in an Even Higher Percentage of OCT4-, SSEA1-, and STELLA-Positive Cells (A and A0 ) After day 4 without LIF, heterozygous ES cells undergo differentiation in the presence of Go¨6983, while null ES cells stay as distinct colonies in (A0 ). (B and B0 ) Go¨6983 stimulates an increase in OCT4+ populations in heterozygous EBs and an even larger OCT4+ population in null EBs in (B0 , insets: green and red channels separately). (C–D0 ) An even higher percentage of cells are OCT4+ (C and C0 ) and SSEA1+ (D and D0 ) with Go¨6983 treatment (day 12, three independent experiments). (E and F) More STELLA+ clusters containing a larger number of cells are present in drugtreated heterozygous EBs. (G and H) Null EBs also have more STELLA+ clusters and cells. Drug-treated null EBs exhibit a dramatic increase in the number of STELLA+ cells. (I–K) Some cells are double positive for STELLA and VASA in drug-treated null EBs (yellow arrows). There are also VASAonly (green arrows) and STELLA-only cells (red arrows) (three independent experiments). (L–P) Treatment with ZIP results in an increase in OCT4+ and STELLA+ cells. ZIP treatment also results in more cells that are VASA+ (three independent experiments); n = 11 for Prkci+/, and n = 13 for Prkci+/ + ZIP; n = 14 for Prkci/, and n = 20 for Prkci/ + ZIP; eight EBs assayed for both STELLA and VASA expression). Scale bars, 100 mm in (A and A0 ); 50 mm in (B and B0 ); and 25 mm in (E, I, and L).

DISCUSSION In this report, we suggest that Prkci controls the balance between stem cell expansion and differentiation/maintenance by regulating the activation of NUMB, NOTCH1, and Hes /Hey downstream effector genes. In the absence of Prkci, the pluripotent cell fate is favored, even without LIF, yet cells still retain a broad capacity to differentiate. In addition, loss of Prkci results in enhanced generation of tissue progenitors such as neural stem cells and cardiomyocyte and erythrocyte progenitors. In contrast to recent findings on Prkcz (Dutta et al., 2011), loss of Prkci does not appear to influence STAT3, AKT, or GSK3 signaling but results in decreased ERK1/2 activation. We hypothesize that, in the absence of Prkci, although ERK1/2 inhibition may be involved, it is the decreased NUMB phosphorylation and increased NOTCH1 activation that promotes stem and progenitor cell fate. Thus, we conclude that PRKCi, a protein known to be required for cell polarity, also plays an essential role in controlling stem cell fate and generation via regulating NOTCH1 activation.

Notch Activation Drives the Decision to Self-Renew versus Differentiate Notch plays an important role in balancing stem cell selfrenewal and differentiation in a variety of stem cell types and may be one of the key downstream effectors of Prkci signaling. Sustained Notch1 activity in embryonic neural progenitors has been shown to maintain their undifferentiated state (Jadhav et al., 2006). Similarly, sustained constitutive activation of NOTCH1 stimulates the proliferation of immature cardiomyocytes in the rat myocardium (Collesi et al., 2008). In HSCs, overexpression of constitutively active NOTCH1 in hematopoietic progenitors and stem cells supports both primitive and definitive HSC selfrenewal (Stier et al., 2002). Together, these studies suggest that activation and/or sustained Notch signaling can lead to an increase in certain tissue stem cell populations. Thus, a working model for how tissue stem cell populations are favored in the absence of Prkci involves a sequence of events that ultimately leads to Notch activation. Recent studies have shown that aPKCs can be found in a complex with NUMB in both Drosophila and mammalian cells (Smith et al., 2007; Zhou et al., 2011); hence, in our working model (Figure 5S), we propose that the localization and phosphorylation of NUMB is highly dependent on the activity of PRKCi. When Prkci is downregulated or absent (as shown here), cell polarity is not promoted, leading to diffuse distribution and decreased phosphorylation of NUMB. Without active NUMB, NOTCH1 activation is enhanced, Hes/Hey genes are upregulated, and stem/progenitor fate generation is favored. To initiate differentiation, polarization could be stochastically determined but could also be dependent on external cues such as the presentation of certain ligands or extracellular matrix (ECM) proteins (Habib et al., 2013). When PRKCi is active and the cell becomes polarized, a trimeric complex is formed with PRKCi, PAR3, and PAR6. Numb is then recruited and phosphorylated, leading to Notch inactivation, the repression of downstream Hes/Hey genes, and differentiation is favored (see Figure 5S). Support for this working model comes from studies in Drosophila showing that the aPKC complex is essential for Numb activation and asymmetric localization (Knoblich, 2008; Smith et al., 2007; Wang et al., 2006). Additional studies on mouse neural progenitors show that regulating Numb localization and Notch activation is critical for maintaining the proper number of stem/progenitor cells in balance with differentiation (Bultje et al., 2009). Thus, an important function for PRKCi may be to regulate the switch between symmetric expansion of stem/progenitor cells to an asymmetric differentiation/maintenance phase. In situations of low or absent PRKCi, we propose that the expansion phase is favored. Thus, temporarily blocking either, or both, of the aPKC isozymes may be a powerful approach for expanding specific stem/progenitor populations for use in basic research or for therapeutic applications.

Although we do not see changes in the activation status of the STAT3, AKT, or GSK3 pathway, loss of Prkci results in an inhibition of ERK1/2 (Figures 2A and 2B). This result is consistent with the findings that ERK1/2 inhibition is both correlated with and directly increases ES cell selfrenewal (Burdon et al., 1999). Modulation of ERK1/2 activity by Prkci has been observed in cancer cells and chondrocytes (Litherland et al., 2010; Murray et al., 2011). Although it is not clear whether a direct interaction exists between Prkci and ERK1/2, Prkcz directly interacts with ERK1/2 in the mouse liver and in hypoxia-exposed cells (Das et al., 2008; Peng et al., 2008). The Prkcz isozyme is still expressed in Prkci null cells but evidently cannot suf- ficiently compensate and activate the pathway normally. Furthermore, knocking down Prkcz function in ES cells does not result in ERK1/2 inhibition, suggesting that this isozyme does not impact ERK1/2 signaling in ES cells (Dutta et al., 2011). Therefore, although PRKCi may interact with ERK1/2 and be directly required for its activation, ERK1/2 inhibition could also be a readout for cells that are more stem-like. Further studies will be needed to address this question.

Utility of Inhibiting aPKC Function Loss of Prkci resulted in EBs that contained slightly more STELLA+ cells than EBs made from +/ cells. Furthermore, inhibition of both aPKC isozymes by treating Prkci null cells with the PKC inhibitor Go¨6983 or the more specific inhibitor, ZIP, strongly promoted the generation of large clusters of STELLA+ and VASA+ cells, suggesting that inhibition of both isozymes is important for PGC progenitor expansion (Figure 6). It is unclear what the mechanism for this might be; however, one possibility is that blocking both aPKCs is necessary to promote NOTCH1 activation in PGCs or in PGC progenitor cells that may ordinarily have strong inhibitions to expansion (Feng et al., 2014). Regardless of mechanism, the ability to generate PGC-like cells in culture is notoriously challenging, and our results provide a method for future studies on PGC specification and differentiation. Expansion of stem/progenitor pools may not be desirable in the context of cancer. Prkci has been characterized as a human oncogene, a useful prognostic cancer marker, and a therapeutic target for cancer treatment. Overexpression of Prkci is found in epithelial cancers (Fields and Regala, 2007), and Prkci inhibitors are being evaluated as candidate cancer therapies (Atwood et al., 2013; Mansfield et al., 2013). However, because our results show that Prkci inhibition leads to enhanced stem cell production in vitro, Prkci inhibitor treatment as a cancer therapy might lead to unintended consequences (tumor overgrowth), depending on the context and treatment regimen. Thus, extending our findings to human stem and cancer stem cells is needed.

In summary, here, we demonstrate that loss of Prkci leads to the generation of abundant pluripotent cells, even under differentiation conditions. In addition, we show that tissue stem cells such as neural stem cells, primitive erythrocytes, and cardiomyocyte progenitors can also be abundantly produced in the absence of Prkci. These increases in stem cell production correlate with decreased NUMB activation and symmetric NUMB localization and require Notch signaling. Further inhibition of Prkcz may have an additive effect and can enhance the production of PGC-like cells. Thus, Prkci (along with Prkcz) may play key roles in stem cell self-renewal and differentiation by regulating the Notch pathway. Furthermore, inhibition of Prkci and or Prkcz activity with specific small-molecule inhibitors might be a powerful method to boost stem cell production in the context of injury or disease.

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MedChemComm articles -3rd Q 2015

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

MedChemComm articles in July, August and September 2015.

MedChemComm medchemcomm-rsc@rsc.org

 

Transition metal diamine complexes with antimicrobial activity against Staphylococcus aureus and methicillin-resistant S. aureus (MRSA)
G. W. Karpin, D. M. Morris, M. T. Ngo, J. S. Merola and J. O. Falkinham III
DOI: 10.1039/C5MD00228A, Concise Article
Multivalent glycoconjugates as vaccines and potential drug candidates
Sumati Bhatia, Mathias Dimde and Rainer Haag
DOI: 10.1039/C4MD00143E, Review Article
Polypharmacology modelling using proteochemometrics (PCM): recent methodological developments, applications to target families, and future prospects
Isidro Cortés-Ciriano, Qurrat Ul Ain, Vigneshwari Subramanian, Eelke B. Lenselink, Oscar Méndez-Lucio, Adriaan P. IJzerman, Gerd Wohlfahrt, Peteris Prusis, Thérèse E. Malliavin, Gerard J. P. van Westen and Andreas Bender
DOI: 10.1039/C4MD00216D, Review Article
Towards understanding cell penetration by stapled peptides
Qian Chu, Raymond E. Moellering, Gerard J. Hilinski, Young-Woo Kim, Tom N. Grossmann, Johannes T.-H. Yeh and Gregory L. Verdine
DOI: 10.1039/C4MD00131A, Concise Article

Rational design of protein–protein interaction inhibitors
Didier Rognan
DOI: 10.1039/C4MD00328D, Review Article

 

Transition metal diamine complexes with antimicrobial activity againstStaphylococcus aureus and methicillin-resistant S. aureus (MRSA)

Med. Chem. Commun., 2015,6, 1471-1478     DOI: http://dx.doi.org:/10.1039/C5MD00228A

 

Multivalent glycoconjugates as vaccines and potential drug candidates

Med. Chem. Commun., 2014,5, 862-878   DOI: http://dx.doi.org:/10.1039/C4MD00143E

Pathogens adhere to the host cells during the first steps of infection through multivalent interactions which involve protein–glycan recognition. Multivalent interactions are also involved at different stages of immune response. Insights into these multivalent interactions generate a way to use suitable carbohydrate ligands that are attached to a basic scaffold consisting of e.g., dendrimer, polymer, nanoparticle, etc., with a suitable linker. Thus a multivalent architecture can be obtained with controllable spatial and topology parameters which can interfere with pathogen adhesion. Multivalent glycoconjugates bearing natural or unnatural carbohydrate antigen epitopes have also been used as carbohydrate based vaccines to stimulate an innate and adaptive immune response. Designing and synthesizing an efficient multivalent architecture with optimal ligand density and a suitable linker is a challenging task. This review presents a concise report on the endeavors to potentially use multi- and polyvalent glycoconjugates as vaccines as well as anti-infectious and anti-inflammatory drug candidates.

 

Graphical abstract: Multivalent glycoconjugates as vaccines and potential drug candidates

 

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Polypharmacology modelling using proteochemometrics (PCM): recent methodological developments, applications to target families, and future prospects

Proteochemometric (PCM) modelling is a computational method to model the bioactivity of multiple ligands against multiple related protein targets simultaneously. Hence it has been found to be particularly useful when exploring the selectivity and promiscuity of ligands on different proteins. In this review, we will firstly provide a brief introduction to the main concepts of PCM for readers new to the field. The next part focuses on recent technical advances, including the application of support vector machines (SVMs) using different kernel functions, random forests, Gaussian processes and collaborative filtering. The subsequent section will then describe some novel practical applications of PCM in the medicinal chemistry field, including studies on GPCRs, kinases, viral proteins (e.g. from HIV) and epigenetic targets such as histone deacetylases. Finally, we will conclude by summarizing novel developments in PCM, which we expect to gain further importance in the future. These developments include adding three-dimensional protein target information, application of PCM to the prediction of binding energies, and application of the concept in the fields of pharmacogenomics and toxicogenomics. This review is an update to a related publication in 2011 and it mainly focuses on developments in the field since then.

 

Graphical abstract: Polypharmacology modelling using proteochemometrics (PCM): recent methodological developments, applications to target families, and future prospects

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Experimental and computational studies of fatty acid distribution networks

 

Kinetics and non-exponential binding of DNA-coated colloids

 

Configuration of nonspherical amphiphilic particles at a fluid–fluid interface

 

 

Towards understanding cell penetration by stapled peptides

Med. Chem. Commun., 2015,6, 111-119   DOI: http://dx.doi.org:/10.1039/C4MD00131A

Hydrocarbon-stapled α-helical peptides are a new class of targeting molecules capable of penetrating cells and engaging intracellular targets formerly considered intractable. This technology has been applied to the development of cell-permeable ligands targeting key intracellular protein–protein interactions. However, the properties governing cell penetration of hydrocarbon-stapled peptides have not yet been rigorously investigated. Herein we report our studies to systematically probe cellular uptake of stapled peptides. We developed a high-throughput epifluorescence microscopy assay to quantitatively measure stapled peptide intracellular accumulation and demonstrated that this assay yielded highly reproducible results. Using this assay, we analyzed more than 200 peptides with various sequences, staple positions and types, and found that cell penetration ability is strongly related to staple type and formal charge, whereas other physicochemical parameters do not appear to have a significant effect. We next investigated the mechanism(s) involved in stapled peptide internalization and have demonstrated that stapled peptides penetrate cells through a clathrin- and caveolin-independent endocytosis pathway that involves, in part, sulfated cell surface proteoglycans, but that also seems to exploit a novel, uncharacterized pathway. Taken together, staple type and charge are the key physical properties in determining the cell penetration ability of stapled peptides, and anionic cell surface proteoglycans might serve as receptors to mediate stapled peptide internalization. These findings improve our understanding of stapled peptides as chemical probes and potential targeted therapeutics, and provide useful guidelines for the design of next-generation stapled peptides with enhanced cell permeability.

Graphical abstract: Towards understanding cell penetration by stapled peptides

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Introduction Hydrocarbon stapled a-helical peptides are an exciting new class of investigational agents capable of targeting and interfering with intracellular protein–protein interactions.1,2 (For reviews on hydrocarbon stapled peptides, see ref. 3 and 4, and for reviews on synthetic a-helix stabilization in general, see ref. 5 and 6.) These peptides contain a synthetic brace, referred to as a staple, introduced across one face of an a-helix (Fig. 1), that in favorable cases can increase a-helical content and protease resistance, enhance target binding affinity, promote cell membrane penetration, and suppress clearance in vivo. 7–10

Fig. 1 All-hydrocarbon stapled peptide technology. (a) Schematic illustration of peptide stapling. Two alpha-methylated, alkenyl-bearing non-natural amino acids are incorporated at two or more positions in the peptide chain and then cross-linked by ruthenium-catalyzed ringclosing olefin metathesis. (b) Different types of alkenyl-containing non-natural amino acids with distinct stereochemistry at the a-carbon and varied lengths of alkenyl side chains. (c) Three types of stapled peptides used in this study with optimized combinations of nonnatural amino acids.

Stapled peptides are synthesized via incorporation of two amethyl, a-alkenyl amino acids at defined positions in a synthetic peptide, followed by ring-closing olefin metathesis to close the helix-spanning hydrocarbon bridge (Fig. 1a).11,12 The two components of the staple, namely the hydrocarbon bridge and terminal methyl groups, are both important to obtain maximal effectiveness of the conformationally constrained peptide products. This technology has been successfully utilized to target several classes of proteins formerly considered intractable, including multi-component transcription factor complexes and protein–protein interactions having extended interfaces, such as the NOTCH transcription factor complex,13 the b-catenin–TCF interaction in the oncogenic Wnt signaling pathway,14 and the epigenetic modulator PRC2 complex.15 Given the difficulties of developing traditional small molecule drugs that can successfully target intracellular protein–protein interactions, hydrocarbon stapling technology is widely considered to represent a promising avenue of research for the development of chemical probes and potential targeted therapeutics.

Multiple types of hydrocarbon staples have been obtained by varying the relative placement of the cross-linking a,a-disubstituted amino acids, as well as the stereochemistry at the acarbon and the lengths of the alkenyl substituents (Fig. 1b).16,17 These staple types were optimized to provide robust a-helical stabilization and confer the potential for in vitro and in vivo activity. As a result of the combinatorial search process used to identify helix-stabilizing hydrocarbon staples, the diversity of the resulting macrocyclic bridges has revealed stapled peptides with different physicochemical properties. Recently, a new hyperstable version of stapled peptide with tandem crosslinks, referred to as a stitched peptide, was generated by introduction of S5 at the i position, B5 at the i + 4 position, and S8 at the i + 11 position (Fig. 1c) (Y.-W. Kim and G. L. Verdine, to be published).

Of the physicochemical properties demonstrated by peptide bearing hydrocarbon staples, the capacity to promote cellular membrane penetration is perhaps the most signicant and yet remains the most poorly understood. Independent of hydrocarbon-stapled peptides, several classes of cell penetrating peptides (CPPs) have been discovered, including naturally occuring transcription factor domains such as pennetratin18 and HIV-Tat19 and synthetic cationic peptides such as polyArginine peptides.20 Notably, despite extensive exploration during the past two decades, the mechanism(s) by which CPPs enter cells remain unclear.21–23 In contrast to CPPs, in which cell penetration appears to be sequence-dependent, numerous cell permeable stapled peptides have been discovered for peptide scaffolds with little sequence homology. These divergent observations regarding cell penetration is proposed to result from several features of stapled peptides that differentiate them from typical CPPs. For example, the introduction of an allhydrocarbon cross-link results in a constrained a-helical conformation, which embeds the hydrophilic amide backbone in the core of the folded structure. Furthermore, the hydrocarbon brace itself introduces a significantly hydrophobic patch to one face of the peptide. The exposure of the hydrophobic moiety as well as the masking of the hydrophilic peptide backbone may facilitate the interaction of stapled peptides with the hydrophobic interior of the cell membrane and thereby enhance the cellular uptake. As cell penetration is a critical property of stapled peptides, we sought to develop quantitative methods to correlate a battery of stapled peptide properties with the capacity for cellular uptake. A direct comparison with several well-known CPPs has revealed that stapled peptides, including some stapled versions of the CPPs, exhibit more robust cell penetration. Lastly, we have demonstrated that stapled peptides penetrate cells through a clathrin- and caveolin-independent endocytosis pathway that involves, in part, sulfated cell surface proteoglycans. These findings significantly expand our current understanding of cell penetration by stapled peptides and provide useful information for the future rational design of cell penetrating stapled peptides with novel applications.

Results and discussion

Development of a high-throughput assay to quantitatively measure cellular uptake of peptides

Understanding the internalization process of cell penetrating peptides (CPPs), especially stapled peptides, has been a subject of great interest. The majority of previous studies have been performed by either using high-resolution microscopy to show the existence of fluorophore-labeled CPPs inside cells, or by quantitatively measuring intracellular fluorescence by flow cytometry.24,25 Although these two methods can provide important information regarding cell penetration, their respective limitations prompted us to adopt an assay that combines high-resolution imaging with reliable quantitation of intracellular accumulation to better analyze and understand the cell penetration of stapled peptides. In recent years, highthroughput cell-based imaging platforms have become increasingly popular to screen for small molecule modulators of various biological processes.26,27 Taking advantage of one of these platforms, high-content epifluorescence microscopy, we developed a high-throughput quantitative assay to measure stapled peptide intracellular access.

Proof-of-principle experiments were performed to determine whether epifluorescence microscopy could be used to quantitatively compare stapled peptide intracellular access. Human U2OS osteosarcoma cells were seeded in black, clear-bottom 384-well plates and then incubated in serum-containing media supplemented with fluorescein-labeled peptides or DMSO vehicle for 12 hours. After the treatment, cells were washed thoroughly with PBS to remove excess peptide, fixed with 4% formaldehyde, and stained with Hoechst dye to visualize nuclei. Once prepared, the plates were imaged and quantified by epi- fluorescence microscopy according to a protocol developed and discussed in detail in Experimental methods. An initial z-scan was performed using the Hoechst channel to locate the cells, and the microscope parameters were subsequently adjusted to optimize the cell size and fluorescence intensity. The parameters from this acquisition were then applied to the FITC channel, and the microscope scanned and recorded images of the FITC-labeled peptides within the z-plane of the cell. This assay was performed in a high-throughput manner, resulting in a panel of Hoechst/FITC images from individual wells (Fig. S1†). The raw image data was then analyzed using MetaXpress® software (Fig. 2a). Cells were identified based on the Hoechst stain of nuclei, with the requirement that they were a contiguous fluorescent region having a specific intensity above local background as well as having a diameter between defined minimum and maximum to be designated as “positive” cells. The cytoplasm of each cell was then identied according to the spatial location of FITC signal in relation to the nuclei as well as empiric parameters (details in Experimental methods). The FITC intensities in the cytoplasm and nuclei were then quantified separately, and the sum of these two values yielded the FITC signal for the whole cell, which can be considered the relative intracellular peptide intensity. In addition, FITC negative cells were identified on the basis of a positive Hoechst stain, which was accompanied by an absence of appreciable signal in the FITC channel.

Fig. 2 Quantitative measurement of cellular peptide intensity. (a) Hoechst channel (left) showing the location and size of nuclei, FITC channel (middle) showing the fluorescence intensity of the same cells. Information about cell size and fluorescence intensity was integrated to identify the FITC positive (green mask) and negative (red mask) cell (right). For positive cells, additional parameters allowed determination of the fluorescence intensity in the nucleus (inner intense green) and the cytoplasm (outer dim green). (b) The background fluorescence the DMSO vehicle was almost identical among different experiments. (c) Four stapled peptides from different batches of synthesis generated similar intracellular fluorescence intensity in different tests. Error bars represent the S.D. of two measurements.

We found that this system generated highly reproducible and reliable results from assay-to-assay and with different stocks of the same stapled peptides. As shown in Fig. 2b, there were negligible fluorescence differences among experiments for cells treated with DMSO vehicle, which could be used as a fluorescence background for all subsequent experiments. In addition, the same stapled peptides from different batches of synthesis and stocks featured almost identical intracellular fluorescence signals in different tests (Fig. 2c), indicating that the assay developed in this study produces repeatable and reliable results that could be directly combined and compared from a large set of experiments. Furthermore, to determine how this assay performs as a screening tool, we have calculated Z0 factor of 0.54 by using the most penetrant A6 peptide as a positive control and DMSO background as negative control, which also indicates a statistically good assay quality.

Analysis of cell penetration by stapled peptides The development of this quantitative high-throughput assay enabled a broad investigation of the physicochemical properties governing the cell uptake of a diverse set of hydrocarbonstapled peptides synthesized in our laboratory. We postulated that any correlation between cellular uptake and physicochemical properties would illuminate characteristics associated with productive cellular uptake and inform the future design of stapled peptides with improved cell penetration.28 To this end, we screened and analyzed more than 200 discrete FITC-labeled peptides belonging to three different classes: wild-type (unmodified), stapled and stitched peptides. All peptides were converted to two-dimensional structures and analyzed for theoretical physicochemical properties with the publicly available Marvin View software package from ChemAxon. Properties including the molecular weight, theoretical pI, calculated 2D polar surface area (PSA), theoretical log P and formal charge at pH 7.5 were calculated for each peptide (Table S1†). In general, the unmodified, stapled and stitched peptide libraries present in this screen had relatively similar physicochemical characteristics (Fig. S2†). The mean molecular weight and calculated PSA values were nearly identical among the three peptide classes. A notable difference was observed among theoretical log P values, which were significantly higher for the stapled and stitched peptides relative to the unmodified peptides, which is not surprising as these modified peptides contain a solvent exposed hydrocarbon crosslink. Additionally, the stapled peptide class had a mean formal charge of approximately zero while the stitched and unmodified peptide classes exhibited a positive mean charge. Overall, the calculated physicochemical properties indicated that the peptide classes were quite similar in terms of their mean properties, which is useful when making comparisons among their cell penetration properties.

We next performed an intracellular access screen by treating U2OS cells with 1 mM of FITC-labeled peptide for 12 hours in duplicate. All assays contained control DMSO wells and positive control peptides, which were compared among assays to ensure plate-to-plate reproducibility (Fig. 2b and c). The primary readout of the screen was mean cellular fluorescence intensity. As the DMSO background was highly consistent between wells and experiments, a mean background value was subtracted from all data. The results of the screen were used to generate plots comparing cell penetration with peptide physicochemical parameters. Interestingly, as a class, stapled and stitched peptides exhibited significantly higher cell penetration compared with wild-type unmodified peptides, which contained several established cell penetrating peptides (CPPs; Fig. 3a). Given that all three peptide classes have similar physicochemical properties in general, the benefit in cell penetration can be largely attributed to the synthetic stabilization of the a-helical peptides with all-hydrocarbon peptide stapling technology. Furthermore, we found that peptide charge near physiologic pH exhibited a strong correlation with intracellular access and could be fitted into a Gaussian distribution with a population centroid at a formal charge of +4 (Fig. 3b). In particular, peptides exhibiting a net negative charge (7 to 1) exhibited little cellular uptake, whereas peptides of approximately neutral charge (1 to +1) displayed moderate cell penetration above background. Interestingly, peptides with a net positive charge (+1 to +7) showed significantly higher cell penetration as a group. Cellular uptake did not appear to increase linearly with charge, as the cell penetration decreases dramatically for the peptides in this study with charge greater than +7. The same trend between formal charge and cellular uptake were observed for individual stapled and stitched peptide classes as well (Fig. S3†). This observation is not consistent with previously reported models that indicate that peptides/mini-proteins with more positive charge have better penetration properties due to tighter electrostatic interactions with the negatively charged phospholipid membrane.29,30 The lower penetration for highly charged peptides in this study could result from any one of many factors including, for example, peptide aggregation in solution, the disruption of peptide packing during internalization or difficulty in dissociation from cell membrane. Additional tests with a larger number of peptides could further our understanding of this phenomenon. In addition, there was no discernible correlation between cell penetration and peptide molecular weight, log P, pI value or PSA (Fig. S4†). Taken together, these data demonstrated that the staple type and peptide charge are key physical properties correlated with peptide cell penetration ability, whereas the other parameters do not appear to be significantly associated.

In order to further investigate the cell penetration properties for stapled peptides and to systematically analyze the similarities and differences in cellular uptake between stapled peptides and other wild-type cell penetrating peptides, we compared cell penetration of several stapled peptides to that of three well known wild-type CPPs: Tat (48–60), penetratin (Antennapedia 43–58) and poly-Arg8 (Table S2†). First, we investigated the cellular uptake at varied peptide concentrations. As shown in Fig. 4a and b, both wild-type CPPs and stapled peptides showed dose-dependent increases in cell penetration. Strong intracellular fluorescence was detected in the low micromolar range, and although the levels of accumulation were different for distinct peptides, stapled peptides featured more robust dosedependent cell penetration at lower concentrations relative to wild-type CPPs, in general. It is also interesting to note that while significant increases in intracellular fluorescence were mostly evident in the 1–10 mM range for stapled peptides, distinct profiles were observed for specific peptides. For example, TNG147 showed little cell penetration at 1 mM but showed a dramatic increase at 5 mM, which might suggest that concentration-dependent peptide packing or a receptor-mediated mechanism may facilitate the cell penetration process, and these processes may be triggered at different concentrations for distinct peptides. Furthermore, it is worth noting that the stapled peptides studied here were more cell permeable than wild-type CPPs at most concentrations tested, exhibiting nearly an order of magnitude higher intracellular fluorescence at the same treatment concentrations.

Fig. 4 Effects of peptide concentration and incubation time on cellular uptake of stapled and wild-type peptides. (a) Wild-type and (b) stapled peptides showed a dose-dependent increase in cell internalization. Cellular uptake for (c) penetratin and (d) SAHM1 peptides over time at concentrations of 5 and 10 mM. (e) A pulse-chase penetration assay for SAHM1 peptide in which fresh medium containing either a new batch of peptide or DMSO vehicle were exchanged at 12 hours after initial treatment. Error bars represent the S.D. of triplicate samples.

We next performed a time-course penetration assay to better understand the kinetics of peptide internalization using a representative CPP and stapled peptide. Penetratin and SAHM1 showed distinct kinetics of uptake and stabilization throughout a 24 hour time course. 5 mM and 10 mM penetratin peptide exhibited similar intracellular cellular fluorescence after 2 hours, which then decreased until approximately 8 hours and finally stabilized at different intracellular levels until 24 hours (Fig. 4c). On the other hand, the stapled peptide SAHM1 showed time- and dose-dependent cellular uptake, which stabilized after approximately 8 hours (Fig. 4d). Compared to the wild-type penetratin, the SAHM1 profile was unique in that dose-dependent accumulation was evident at all time points and no loss of signal was observed. One explanation for the loss of signal observed with penetratin could be attributed to an equilibrium between cell penetration and subsequent intracellular proteolysis followed by export of the fluorophore. The presence of the all-hydrocarbon crosslink in its peptide sequence and lower net charge of SAHM1 relative to penetratin, could contribute to enhanced cellular uptake and reduced intracellular proteolysis, leading to continuous accumulation in cells. To further explore the equilibrium observed for stapled peptides, we performed a pulse-chase experiment using SAHM1. After 12 hours of incubation with SAHM1, cell culture medium was aspirated and the cells were extensively washed with PBS to completely remove excess peptide. Then fresh medium containing either a new batch of 1 mM peptide or DMSO vehicle was added to cells and incubated for the indicated time points (Fig. 4e). As expected, the cellular uptake increased for the first 12 hours incubation. After medium exchange, cells incubated with fresh medium containing DMSO vehicle retained the intracellular fluorescence intensity. Interestingly, the signal for cells treated with a new batch of staple peptide continued to increase up to 24 hours (Fig. 4e). This observation indicates that despite incubation over a time course previously shown to reach equilibrium, the mechanism(s) responsible for cellular uptake are not saturated, as evidenced by further uptake upon replacement with fresh stapled peptide. Taken together, these data indicate that the mechanism(s) underlying cellular uptake by both CPPs and stapled peptides exhibit time- and dose-dependency that is not saturable at early time points or low micromolar doses and, importantly, appears to be more robustly utilized by stapled peptides.15,31

Given that stapled peptides exhibit better cell penetration properties in general than parent unmodified peptides, we wondered whether the peptide stapling strategy could be applied generally to improve cellular uptake of parent unmodified peptides. To test this hypothesis, we designed a panel of stapled peptides based on Tat (48–60), penetratin and poly-Arg8 (Fig. 5a). These stapled peptides and their parent unmodified peptides were incubated in U2OS cells for 12 hours with a concentration range from 10 nM to 20 mM, mirroring the dosedependent uptake studies shown in Fig. 4. As expected, all peptides showed dose-dependent cell penetration (Fig. 5b–d). Interestingly, stapled peptides derived from penetratin and poly-Arg8 showed improved cell permeability at concentrations starting from 1 mM for stapled penetratin and 5 mM for stapled poly-Arg8. It is noteworthy that the staple position also affected the cellular uptake as the two stapled penetratin peptides with different crosslink positions exhibited varied cell penetration, though both were superior to wild-type penetratin. In contrast, reduced cellular uptake was observed for both stapled peptide variants derived from the Tat sequence (Fig. 5b). This could result from several possible effects, including disruption of peptide secondary structure, masking of residues essential for surface recognition or altering peptide packing interactions involved in cell penetration. Further focused study of these variants is warranted to elucidate the source of altered cellular uptake, however these data clearly demonstrate that peptide stapling may be a general method to further improve the cell permeability of CPPs, which could serve as more efficient transduction domains for molecular cargoes. In addition, while increasing the helical content of stabilized peptides has been stated to be a guiding principle in the successful design of biologically active stapled peptides, it has not been shown to be generally correlated with cell penetration. To specifically address whether increasing the helical content of a peptide is correlated with augmented cell penetration, we have measured the relative helicity of hydrocarbon stapled variants of Tat, penetratin and poly-Arg8 (Fig. S5†). Notably, we did not observe a general correlation between increased helical character and cell penetration of these peptides. Peptide stapling increased the helical content of both Tat and poly-Arg8 peptide sequences, which were largely unstructured when unmodified. In contrast, the unmodified penetratin peptide had signicant helical content (>50%), and the hydrocarbon stapled variants of this sequence largely retained their helicity, albeit lower overall helicity. Intriguingly, these species demonstrated the differing effect of hydrocarbon stapling and increased helical content on cell penetration since introduction of the hydrocarbon staple increased the cellular uptake of both penetratin and poly-Arg8 sequences, while it decreased uptake for Tat peptides. Therefore, we cannot conclusively state, a priori, that the incorporation of a hydrocarbon staple or increased a-helicity will lead to more productive cellular penetration, although in general stapling can increase the uptake of specific sequences (Fig. 5) and as a class stapled and stitched peptides are more cell penetrant (Fig. 3a). A more comprehensive follow-up study with CD analyses on a larger peptide library is needed to better address this question.

Fig. 5 Effects of all-hydrocarbon staples on cell penetration by wild-type cell penetrating peptides. (a) List of wild-type cell penetrating peptides and their stapled derivatives investigated in this study. (b–d) Dose-dependent cell penetration assays showed that stapling strategy greatly improves the cellular uptake of penetratin and poly-Arg8 peptides. Experiments were performed in triplicate, and error bars represent S.D. of three measurements.

Mechanistic studies of cell penetration by stapled peptides The aforementioned studies indicate that stapled peptides exhibit better cellular uptake properties than wild-type peptides in general, and that internalization correlated primarily with hydrocarbon staple type and formal peptide charge. However, the mechanism(s) utilized by peptides to translocate across the cell membrane are still unclear. Therefore, we sought to investigate the uptake mechanism(s) for stapled peptides. The uptake mechanism(s) of wild-type CPPs have been extensively studied. Some evidence indicates that they enter cells via energy-dependent endocytosis, which is an active transport process, however data suggesting passive diffusion for CPPs have also been reported; hence, the mechanism(s) of cell uptake by CPPs remains ambiguous.32–34 We first sought to determine whether cell penetration by stapled peptides and wild-type CPPs occurs via ATP-dependent endocytosis.2 Cells were pre-treated with NaN3 and 2-deoxyglucose (2-DG) to reduce cellular ATP levels, and then incubated with FITC-labeled peptides (wildtype and stapled) for 4 hours and compared to normal cells for intracellular fluorescence. Cellular ATP levels were confirmed to be decreased by approximately 90% after NaN3 and 2-DG treatment (Fig. S6†), but Tat and poly-Arg8 exhibited almost identical cellular uptake in ATP-depleted and normal cells, supporting the model that they utilize passive diffusion to translocate across the cell membrane. However, penetratin and all stapled peptides showed 20–50% lower accumulation in ATP-depleted cells, indicating an active trans-membrane process requiring cellular ATP (Fig. 6a). These data indicate that there may be more than one uptake mechanism for CPPs and stapled peptides, but that for the most robust cell penetrating peptides (penetratin and stapled peptides studied here), the internalization mechanism(s) involves ATP-dependent endocytosis.

Fig. 6 Mechanistic study of cell penetration by stapled peptides and wild-type cell penetrating peptides. (a) Cellular uptake in normal and ATP-depleted cells indicated that stapled peptides penetrate cells via an ATP-dependent endocytosis. (b) Impaired uptake was observed in NaClO3 treated cells, which inhibit proteoglycan biosynthesis. (c) Cell penetration of wild-type and stapled peptides in wild-type CHO and proteoglycan-deficient CHO cells. Experiments were performed in triplicate, and error bars represent S.D. of three measurements.*P < 0.05, **P < 0.01, ***P < 0.001.

Next, we sought to identify the specific pathway(s) utilized for cellular uptake, since energy-dependent endocytosis can be accomplished by several different pathways including caveolinand clathrin-mediated endocytosis. We repeated the cell penetration experiments under a variety of conditions that each blocked a different endocytosis pathway (Table S3†).35–37 We found that uptake was partially blocked in cells treated with sodium chlorate (Fig. 6b), which aborts the decoration of cells with sulfated proteoglycans, but was unaffected by inhibitors of other endocytic pathways (Fig. S7†). It thus appears that interaction with sulfated proteoglycans is responsible for some, but not all, endocytic uptake of stapled peptides and wild-type CPPs. It is reasonable to connect this result with the previous discovery that peptide charge is a key factor determining cell penetration. Proteoglycans are negatively charged under physiologic conditions due to the occurrence of sulfate groups, and these might form electrostatic pairs with positively charged peptides to facilitate anchoring on the cell membrane.38–40 To further confirm that sulfated proteoglycans are important to mediate cellular uptake for peptides, we performed a secondary assay using wild-type CHO cells (CHO-K1) and proteoglycan deficient CHO cells (pgsA-745) which harbor a defect in xylosyltransferase, thereby preventing glycosaminoglycan biosynthesis. All peptides showed similar penetration properties in wild-type CHO cells, but uptake was decreased by approximately 50% in proteoglycan-deficient CHO cells, consistent with the experiment using a small molecule inhibitor (Fig. 6c). Taken together, our data suggest that CPPs and stapled peptides penetrate cells through a clathrin- and caveolin-independent endocytosis pathway that is in part mediated by interaction with anionic cell surface proteoglycans. This result is very similar to the previous reports on the mechanism of cellular uptake for supercharged GFP (scGFP), which likewise does not utilize clathrin- or caveolin-mediated endocytosis.41 Notably, scGFP internalization requires actin polymerization, which may not be required for peptide penetration (Fig. S7c†) types, and distinct physicochemical properties. As a result, we found that stapled peptides penetrate cells more efficiently than unmodified peptides, including well-characterized cell penetrating peptides. For the panel of peptides used in this study, only staple type and formal charge were significantly correlated with cell penetration potential, whereas the other physical parameters did not appear to have a signicant effect. We further studied the relationships between cellular uptake and

In conclusion, we sought to investigate the cell penetration properties of stapled peptides, which is one of the most significant yet poorly understood aspects of peptide stapling technology and cellular transduction technologies in general. In order to address this problem, we developed a high-throughput assay to quantitatively measure stapled peptide intracellular accumulation. Using this assay, we analyzed more than 200 discrete peptides with various sequences, staple positions and peptide concentration or incubation time, revealing that stapled peptides accumulate in cells in a dose-dependent fashion and reach steady intracellular levels over a course of a few hours. These studies revealed similar time- and dosedependent behavior for CPPs and stapled peptides, but stapled peptides, including stapled versions of CPPs, were shown to be 10- to 20-fold more penetrant, measured by intracellular fluorescence level at a given dose, than the most potent CPP. We also propose that the specific intracellular accumulation and stabilization kinetics of stapled peptides or unmodified CPPs may be a consequence of equilibria between peptide penetration, cellular proteolysis and/or retrograde transport of the species. Finally, we investigated the mechanism(s) involved in the internalization of stapled peptide and unmodified CPPs and demonstrated that cell penetration occurs through a clathrinand caveolin-independent, energy-dependent endocytosis pathway that utilizes, in part, sulfated cell surface proteoglycans. This dataset provides significant insight into the physicochemical properties correlated with productive cellular penetration as well as a more detailed understanding of the mechanism(s) utilized by stapled peptides to access intracellular compartments, which together should aid in the design of and characterization of novel stapled peptides in the future.

 

Rational design of protein–protein interaction inhibitors

Med. Chem. Commun., 2015,6, 51-60    DOI: http://dx.doi.org:/10.1039/C4MD00328D
Protein–protein interactions are at the heart of most physiopathological processes. As such, they have attracted considerable attention for designing drugs of the future. Although initially considered as high-value but difficult to identify, low molecular weight compounds able to selectively and potently modulate protein–protein interactions have recently reached clinical trials. Along with high-throughput screening of compound libraries, combining structural and computational approaches has boosted this formerly minor area of research into a currently tremendously active field. This review highlights the very recent developments in the rational design of protein–protein interaction inhibitors.
Graphical abstract: Rational design of protein–protein interaction inhibitors

Didier Rognan heads the Laboratory of Structural Chemogenomics at the Faculty of Pharmacy of Strasbourg (France). He studied Pharmacy at the University of Rennes (France) and did a Ph.D. in Medicinal Chemistry in Strasbourg (France) under the supervision of Prof. C.G. Wermuth. Aer a postdoctoral fellowship at the University of Tubingen (Ger- ¨ many), he moved as an Assistant Professor to the Swiss Federal Institute of Technology (ETH) until October 2000. He was then appointed Research Director at the CNRS to build a new group in Strasbourg. He is mainly interested in all aspects (method development and applications) of structurebased drug design, notably on G protein-coupled receptor ligands and protein–protein interaction inhibitors.

Introduction Drug discovery is a long, costly, multi-step endeavour which aims at reducing all possible risks to deliver a novel therapeutic solution to previously unmet clinical needs. To reduce chemical risks, empirical rules are used to filter the chemical space and retain drug-like low molecular weight compounds. Reduction of the biological risk is addressed by considering privileged target families (e.g., G protein-coupled receptors and kinases) whose activation/inhibition by drug-like compounds is likely to correct or reverse pathological states. Until recently, mostly single macromolecules (proteins and nucleic acids) have been considered as potential drug targets. Out of 68 000 proteins currently annotated in UniProt for the human proteome,1 only about 300 targets2 have been addressed by current drugs, and the large majority of single targets is still awaiting first-in class drugs.

Besides single targets, large scale genomics and proteomics3 have identified complex networks of targets and pathways regulating physiopathological processes in a coordinated manner. The current human protein–protein interactome has been estimated between 130 000 (ref. 4) and 650 000 (ref. 5) complexes, out of which only a tiny amount is known, and only a very few6–8 have been the object of a drug discovery initiative. Protein–protein interactions (PPIs) therefore describe a totally new biological space that attracts more and more attention, with 26PPI inhibitors9,10 already under clinical development, notably in the oncology field.11 Despite PPIs may adopt quite different sizes, shapes and electrostatics,12 identifying highaffinity PPI inhibitors is a considerable challenge for many reasons: (i) in contrast to conventional targets, a medicinal chemist cannot start inhibitor design from the structure of endogenous ligands, (i) PPIs often involve flat surfaces delocalized over multiple epitopes, usually lack well-defined buried cavities13 typical of conventional targets, and are significantly larger (ca. 1000–3000 A˚2 ) than enzyme/receptor pockets (300– 1000 A˚2 ), (iii) high-throughput screening of traditional compound libraries often returns no viable hits14 for the main reason that PPI inhibitor chemical space is quite different from that described by traditional drug-like compounds.10 Nonetheless, thanks to bioinformatics and proteomics-guided prioritization of therapeutically relevant protein–protein complexes, more and more PPI inhibitors are currently reported. Several excellent reviews6,7,9,11,15–18 have already been published on experimental methods (high throughput screening, biochemical and cellular assays, and fragment-based approaches) suitable to discover PPI inhibitors. The present report will only cover computer-aided approaches, with a major emphasis on structure-based methods and recent discoveries (2012–2014).

Databases Preliminary access to experimentally validated data is key to launch a drug discovery program on PPI modulators. A multitude of databases storing genomics, proteomics and structural data are currently available to help the medicinal chemist. We will here briefly review these archives, focusing mostly on easily interpretable structural data.

PPI databases Many experimental methods with different throughputs (from low to high) have been developed to characterize binary interactomes in various species, among which the most prominent has been the yeast two-hybrid (Y2H) assays, and mass-spectrometry (MS) coupled with co-immunoprecipitation or coaffinity purification.19 These experimental data are stored in many primary databases (Table 1) that are difficult to mine due to their large heterogeneity. Metadatabases have been derived thereof to facilitate their analysis, among which the most popular are APID and PRIMOS (Table 1). These metadatabases cover a wide range of organisms and notably offer the possibility to mine experimental PPI data according to disease relevance or inter-organism crosstalk, and provide graphic tools to visualize complex networks of interacting proteins and identifying important protein nodes (hubs). It is however very difficult, from this large amount of data, to clearly prioritize PPIs for a drug discovery program. Attempts to classify the PPIs by structural druggability25 (although ligandability26 is probably a better term) are worth mentioning but should be taken with care due to the still insufficient number of existing PPI three-dimensional (3D) structures.

Table 1 Protein–protein interaction databases

Database                 Interactions                         Website                                                             References

BIND                             32 211           http://bond.unleashedinformatics.com                       20

DIP                                 78 191           http://dip.doe-mbi.ucla.edu/dip/Main.cgi                  21

HPRD                           41 327            http://www.hprd.org/                                                           22

IntAct                      448 986             http://www.ebi.ac.uk/intact/                                            17

MIPS                              9 835             http://mips.helmholtz-muenchen.de/proj/ppi/      23

APID                         196 700             http://bioinfow.dep.usal.es/apid/index.htm             24

PRIMOS                  384 127             http://primos.fh-hagenberg.at/                                        19

 

 

Table 2 Database of low molecular-weight PPI inhibitors
Database                 Ligands                             Website                                                                  References

2P2I                                 71                   http://2p2idb.cnrs-mrs.fr/                                                12

iPPI-DB                      1650               http://www.ippidb.cdithem.fr/                                        10

TIMBAL                      6896              http://mordred.bioc.cam.ac.uk/ timbal                        29

Ligand databases Initially limited to a limited subset of inhibitors able to disrupt few PPIs (e.g. p53/MDM2, Bcl-Xl/Bak, and IL-2/IL-2Ra),7,27 the repertoire of PPI inhibitors rises constantly thanks to exciting developments in biophysical fragment screening.15,28 Three publicly available databases storing information on PPIs and their inhibitors (Table 2) may be used to better describe the structural properties of druggable PPIs and the chemical space associated with their disruptors.

The 2P2Idb database12 is a hand-curated repository of protein–protein complexes of known X-ray structures (X-ray diffraction and nuclear magnetic resonance spectroscopy) for which at least one low molecular weight orthosteric inhibitor has been co-crystallized with one of the two protein partners. It currently describes 71 inhibitors for 14 PPIs, clustered in two groups (Fig. 1) with respect to the nature of the interface (protein–peptide and protein–protein). Companion tools (2P2I inspector,30 2P2I score,30 and 2P2I hunter31) are provided to analyse PPIs at a structural level, predict their structural druggability and design PPI focussed libraries, respectively.

Fig. 1 Prototypical examples of class I (left panel) and class II PPIs (right panel), exemplified by the Bcl-Xl/Bak (PDB id 1BXL) and integrase/LEDGF (PDB id 2B4J) complexes, respectively. Class I PPIs involve the interaction of a globular protein with a peptide or a single secondary structure (a-helix and b-strand) of a second protein partner. Class II PPIs are characterized by the interaction of two globular proteins.

The iPPI-DB10 is another manually curated database from world patents and the medicinal chemistry literature, focussing on low molecular weight orthosteric inhibitors, disease-related protein–protein interfaces and a clear biochemical readout (e.g. fluorescence polarisation and enzyme-linked immunosorbent assay). The database archives 1650 PPI inhibitors targeting 13 families of homologous PPI targets mainly involved in cancer, immune disorders and infectious diseases.

Finally, the TIMBAL database29 reports ca. 7000 inhibitors for 50 known PPIs. In contrast to the two other databases, TIMBAL is maintained through a predefined list of PPIs and automated searches in ChEMBL32 and the Protein Data Bank.33 In contrast to the other databases, TIMBAL also registers short peptides with an upper molecular weight limit of 1200 Da. It should be pointed that most of the 15 000 uncurated biological data present in TIMBAL arise from a single target family (integrins) and should be considered with care.

Analysing the content of these databases enables a first comparison of PPI inhibitors versus drugs, as well as PPIs amenable to disruption versus standard heterodimers. PPI surfaces disrupted by inhibitors tend to be smaller, more hydrophobic and accessible than standard heterodimers.12 As a consequence, low molecular weight PPI inhibitors tend to be larger, more hydrophobic and more aromatic-rich than standard drugs. Interestingly, many of them (ca. 60%) still comply with Lipinski’s rule-of-five, 10 revealing some hopes in the developability of such compounds.

However, it should be stated that the set of empirical rules designed to discriminate druggable from non-druggable PPIs, as well as to distinguish PPI inhibitors from conventional druglike compounds still rely on a very limited set of highly homologous data (PPIs, inhibitors), and should therefore be regarded with caution. Increasing coverage of the PPI repertoire by future experimental screens will undoubtedly lead to a better denition of PPI biological and chemical spaces. We therefore expect in the future the above-mentioned rules to be rened and be more descriptive of the true world of PPI inhibitors, notably with respect to rational design of PPI focussed libraries.

 

Rational design of PPI modulators

Sequence-based approaches Whatever the nature of the PPI (type I or type II, see the definition above), PPI interfaces are often characterized by the presence of hotspots,34 in other words anchor residues that contribute the most to the binding free energy of the protein– protein complex. The interaction of a single modified amino acid with a single anchor residue might be sufficient to disrupt a PPI as elegantly demonstrated by Lin et al. in a recent study.35 Capitalizing on the presence of a reactive cysteine (C246) at the interface of the complex between caspase-7 (CASP7) and the Xlinked inhibitor of apoptosis protein (XIAP), they designed the N-iodoacetyl-lysine amino acid derivative 1 (Fig. 2) that covalently traps C246 and further disrupts the XIAP–CASP7 complex, therefore triggering CASP7-dependent apoptosis and killing MCF-7 breast cancer cells (EC50 ¼ 0.64 mM) previously resistant to chemotherapy.

The easiest way to inhibit a PPI is to start with the amino acid sequence of one interacting epitope, notably if the latter is part of regular secondary structures (a-helix, b-strand, and b-turn). For example, a-helical peptides mimicking the sequence of protein transmembrane domains may disrupt PPIs quite efficiently.36,37

Fig. 2 Peptidomimetics as PPI disruptors

 

Due to poor pharmacokinetic profiles, linear peptides are good in vitro tools but usually not efficient clinical candidates. Chemical modifications are required to stabilize their secondary structures in physiological media and prevent early degradation. Among the most exciting developments in this area38,39 is the design of stapled peptides.40,41 Stapled peptides are synthetic analogues of a-helical protein epitopes involved in a PPI, and in which a covalent hydrocarbon linkage connects adjacent turns of the helix. Stapling is known to significantly increase the in vivo half-life of the natural peptide (increasing proteolytic stability), decrease the entropic cost of binding, and even enable cellular uptake.42 Many stapled peptides with potent in vivo activities have already been reported.39 One of these stapled peptides (ATSP-7041, compound 2, Fig. 2) just entered clinical development as a dual nM MDM2/MDMX inhibitor for p53-dependent cancer therapy.43

Heterocyclic scaffolds mimicking secondary structures can also be obtained by solution-phase synthesis to afford peptidomimetic libraries amenable to PPI inhibition. Whitby et al. notably reported the design of 8000 member 4-acetamido-3- alkoxy-benzamide focused library featuring weak p53/MDM2 inhibitors and potent HIV-1/gp41 inhibition (compound 3, Fig. 2).44 When the peptide epitope is not structured, developing macrocyclic analogues is more difficult but still feasible as recently demonstrated by Glas et al.38 who successfully improved 14-3-3 binding of a 11-mer peptide from a bacterial ExoS virulence factor by cross-linking binding amino acids with polymethylene linkers, up to an in vitro 40 nM disruptor of the ExoS/14-3-3 interaction (compound 4, Fig. 2). Interestingly, the cross-linker was not only chosen to rigidify the natural ExoS peptide structure but also to directly provide additional hydrophobic interactions to the 14-3-3 binding site.38 Only in exceptional cases the natural unmodified peptide is directly usable as a PPI inhibitor. One recent example is the 28 amino acid cell-penetrating peptide (p28) from a bacterial azurin redox protein, that binds to the DNA-binding domain of the p53 tumor suppressor and inhibits p53 degradation by interfering with the Cop1-mediated ubiquitination,45 thereby enhancing p53 levels in cancer cells and exhibiting antitumoral efficacy in patients with advanced solid tumors.46

Pharmacophore-based approaches As defined by the IUPAC,47 a pharmacophore is “an ensemble of steric and electronic features that are necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger (or block) its biological response.” Although pharmacophores are mainly used to align and compare ligands sharing the same target,48 the same concept can be easily transferred to PPIs in which one partner is the “receptor” and the second one the “ligand”. Pharmacophore features (hydrophobic, aromatic, H-bond donor and H-bond acceptor, positively and negatively ionisable) can therefore be manually or automatically mapped to atoms of the ligand in direct interactions with the receptor. The resulting pharmacophore can then be used to identify a compound library for hits fulfilling the defined query. Several tools (e.g. LigandScout,49 Discovery Studio,50 and Pocket Query51) can be directly used to map PPI pharmacophores onto protein–protein X-ray structures (Fig. 3).

Fig. 3 Example of a PPI pharmacophore mapped onto interacting atoms of human LEDGF (yellow ribbons) bound to HIV-1 integrase (red ribbons, PDB ID 2B4J). The PPI pharmacophore is composed of 2 Hbond donors (magenta balls), two H-bond acceptors (green balls), one hydrophobic feature (cyan ball) and 6 exclusion volumes (gray balls).

Using a manual PPI pharmacophore defined from the X-ray structure of the Annexin A2/S100A10 complex, a pro-angiogenic complex, Reddy et al.52 derived a simple pharmacophore (2 hydrophobes, 2 H-bond donors, and 2 H-bond acceptors) using the Unity program,53 and screened a library of 700 000 compounds to select 586 hits which were further docked to the Annexin A2 binding site to retain only 190 candidates with both a good docking and pharmacophore fitness score (Table 3). Out of 190 tested compounds, 7 hits blocked the interaction between S100A10 and the Annexin A2 N-terminus in a competitive fluorescent binding assay, with the most potent PPI inhibitor (compound 5, Fig. 4) exhibiting an IC50 of 24 mM.52 Geppert et al.54 reported the rational discovery of a low molecular weight inhibitor of the complex between interferon-a (IFN-a) and its receptor (IFNAR2). Fortunately, the PPI interface was small enough (ca. 800 A˚2 ) to be targeted by a small heterocyclic compound. After identifying major hotspots at the IFN-a surface, a fuzzy receptor-based pharmacophore was determined using the VirtualLigand approach,55 which assigns pharmacophoric features to Gaussian densities. Screening a collection of 556 000 commercially available compounds retained six virtual hits, out of which two were weak IFN-a inhibitors, but one (compound 6, Fig. 4) was confirmed by NMR and surface plasmon resonance (SPR) to bind to IFN-a with a dissociation constant (Kd) of 4 mM and to inhibit IFN-a responses in various cell assays. The novel inhibitor may be useful to reduce IFN-a titers in autoimmune disorders.

 

Table 3 Protein–protein pharmacophore searches to identify PPI inhibitors

Target                                     Library size                          Tested                        Hits                      Ref.

Annexin A2/S100A        10 700 000                              190                               7                          52

INFAR2/IFN-a                       556 000                                   6                               3                          54

p53/MDM2                                  21 287                                  15                               6                          56

Nrf2/Keap1                                   21 199                                  17                                1                          57

PKC3/RACK2                          330 000                                 19                                1                          58

 

Due to the inherent complexity of PPI pharmacophores (many features covering a large surface), combining several pharmacophores into a consensus model may help to retrieve essential features and simplify pharmacophore queries. Xue et al. applied this approach to the identification of p53–MDM2 inhibitors.56 The p53–MDM2 complex has become a prototypical PPI for its biological background (this interaction plays an important role in regulating the transcriptional activity of tumour cells) and many high affinity low molecular-weight inhibitors of this PPI identified by various screening approaches.59 Starting from a set of 15 MDM2-peptide X-ray structures, a common feature structure-based pharmacophore (2 H-bond donors, one H-bond acceptor, 2 aromatic rings, and one hydrophobe) was first identified. In addition, a receptorligand pharmacophore (five hydrophobes, one aromatic, and one H-bond donor) was generated from a separate set of 10 MDM2-non peptide complexes. Merging both pharmacophores and retaining the most common features led to an ensemble pharmacophore definition (two aromatic rings, two hydrophobes, and one H-bond donor) taking into account both peptide and non-peptide binding. This pharmacophore was used to screen a collection of 21 287 commercially available compounds, and led to a hit list of 15 compounds out of which 6 were confirmed as p53–MDM2 inhibitors using an in vitro uorescence polarization assay.56 The most potent inhibitor (compound 7, Fig. 4) is a 180 nM MDM2 inhibitor. Despite a good selectivity in a MTT tumour cell proliferation assay (p53+/+ vs. p53/ cells), compound 7 was a weak inhibitor (IC50 ¼ 85 mM) of tumour cell growth, because of poor pharmacokinetic properties.

Fig. 4 PPI inhibitors identified by pharmacophore-based virtual screening.

Along the same lines, two X-ray structures were used to derive inhibitors of the PPI between Keap1 and Nrf2, a complex involved in the response to oxidative stress.57 The two PPI pharmacophores were merged into a single query consisting of one H-bond donor, two H-bond acceptors and three negative ionisable centers. To afford some fuzziness in the search, up to two features were allowed to be missed by virtual hits. Since the Keap1-binding epitope of Nrf2 is composed of several acidic residues, only compounds bearing a negative charge were searched among a full commercial library of 251 774 compounds. The remaining 21 199 hit list was matched to the pharmacophore, and led after confirmation with docking and MM-PBSA scoring, to a list of 17 potential hits which were tested for Keap1–Nrf2 inhibition using an in vitro fluorescence polarization assay. A single compound (compound 9, Fig. 3) was confirmed in vitro as a moderately potent Keap1–Nrf2 inhibitor with an EC50 of 9.8 mM.57 Interestingly, the inhibitor activated the Nrf2 transcriptional activity .

When both protein partners involved in the PPI have not been co-crystallized, it is still possible to rationally discover PPI inhibitors, starting from the sole X-ray structure of one of the two proteins. This approach was followed by Rechfeld et al. in the discovery of PKC3–RACK2 inhibitors.58 Starting from the Xray structure of the PKC3 octameric epitope binding to RACK2 (a receptor for activated protein kinase C), a simple peptide-based pharmacophore model (3 H-bond donor/acceptor, one hydrophobe) was defined and used to screen a collection of 330 000 compounds. Out of 19 virtual hits, a thienoquinoline was found to disrupt the PPI in vitro and served as a query for a secondary screen for chemically similar analogues, which led to compound 8 (Fig. 4) as a micromolar potent PKC3-RACK2 inhibitor (IC50 ¼ 5.9 mM) which also inhibited PKC3 downstream signalling, HeLa cancer cell migration and invasion.58

Finally, pharmacophore searches may be used to prioritize privileged scaffolds for synthesizing PPI-focused libraries. For example, Fry et al. reported a rational approach to PPI library design targeting a-helical binding epitopes.60 Starting from the known X-ray structure of an a-helical p53 epitope binding to MDM2, a three point pharmacophore, featuring the three important hydrophobic side chains (Phe19, Trp23, and Leu26) of the p53 peptide, was designed and used to find heterocyclic scaffolds among the CSD database61 of small molecule X-ray structures. Several small-sized libraries (ca. 100 members) were synthesized from each hit and tested for general inhibition of PPIs involving an a-helical epitope (e.g. MDM2, BCL2, BCL-XL, and MCL1). Although no potent hit could be discovered, the average hit rate was far superior (4%) to what should be expected from a random screen. Moreover, many starting hits exhibited good ligand efficiencies,60 and are therefore interesting starting points for hit leading optimization.

Despite its apparent simplicity, PPI-based pharmacophore search is a fast, cost-effective and simple in silico approach to discover the very first inhibitors of a particular PPI. Of course, all successful examples mentioned above imply that the PPI is of manageable size and does not involve a too large and complex binding epitope. Beside the existence of a X-ray or NMR structure of the protein–protein (peptide) complex, it is therefore equally important to properly select PPIs amenable to pharmacophore-based searches, notably with respect to the complexity of the query (5–6 features) and its hydrophobic/ hydrophilic balance.

Docking-based approaches At the first sight, protein–ligand docking should be considered as the most intuitive and logical computational tool to predict likely ligands of any target of known 3D structures.62 Unfortunately, severe drawbacks associated with the scoring of protein– ligand interactions render that tool usually suitable for positioning a ligand into a binding site, but rarely to predict binding free energies or to precisely rank ligands by decreasing affinity.63 Moreover, the ability of docking algorithms to anchor ligands to flat PPI surfaces has long remained elusive. In a benchmark study, Kruger ¨ et al. used two popular docking tools (AutoDock and Glide) to reproduce the known X-ray structure of PPI inhibitors to their target.64 Surprisingly, the performance of these standard docking programs with respect to the positioning of the ligand (rmsd to the X-ray structure) was only moderately affected by switching from conventional targets to PPIs. Although PPI inhibitors with more than 10 rotatable bonds were found more difficult to properly dock, a good pose was generated in ca. 54% of the 80 PPI inhibitors considered. Docking to PPIs providing at least one charge residue was favoured over those purely hydrophobic.64 There are therefore no particular reasons to discard docking-based approaches from rational PPI inhibitor discovery scenarios. Many of the following success stories support this assumption.

We will not here review the many recent reports describing docking as a mean to predict the binding mode of a PPI inhibitor discovered by an experimental screening method.59,65–68 The next section will only focus on inhibitors discovered by a docking-based virtual screening campaign (Table 4).

 

Table 4 Protein–protein inhibitors discovered by docking-based screening

Target                   Library size                                     Tested                             Hits                   Ref.

TLR4/MD-           2 50 000                                           14                                      3                      69

uPA–uPAR      5 000 000                                            50                                      3                     70

IL-6/gp130                          9                                                2                                     2                     71

Keap1–Nrf2            153 611                                              65                                     9                     72

CRYAB/VEGF       139 735                                             40                                     4                    73

NRP-1/VEGF-        429 623                                        1317                                   56                   74

PPxY/Nedd4       4 800 000                                          20                                       1                  75

p53/MDM2                  87 430                                        295                                       1                 76

 

Despite an apparent unsuitable large and concave cavity, the MD-2-binding site at the surface of the toll-like receptor 4 (TLR4) was selected for pharmacophore-constrained FlexX77 docking of a library of 49 600 compounds pre-filtered for 3D shape similarity to an existing TLR4 antagonist.69 40 virtual hits were selected for in vitro TLR4 binding and functional antagonism, and 3 of them could be confirmed experimentally. The most potent antagonist (compound 10, Fig. 5) blocked TLR4 in a gene receptor assay with an IC50 of 16.6 mM and inhibited proinflammatory cytokine release (e.g. TNF-a) from human peripheral blood mononuclear cells upon LPS activation. Due to unfavourable aqueous solubility, the compound could not be tested in vivo but represent a good starting hit for developing small molecule TLR4 antagonists for the treatment of neuropathic pain and sepsis.

Fig. 5 PPI inhibitors identified by docking-based virtual screening

To account for the conformational flexibility of proteins, Khanna et al. reported a cascade docking-based virtual screening for discovering inhibitors of the interaction between the urokinase-type plasminogen activator (uPA) and the urokinase receptor (uPAR).70 Two X-ray structures of the uPAR were first used for docking a collection of 5 million commercially available compounds using AutoDock4.78 10 000 top-ranked virtual hits were further docked, still with AutoDock, to 50 molecular dynamics snapshots of the uPAR structure, leading to 500 top-ranked compounds which, in a third step, were docked using a different program (Glide) on the 50 receptor conformers. After clustering the top 250 compounds by chemical similarity, the highest scoring compounds from each of the top 50 clusters were finally selected, purchased and evaluated in vitro in a fluorescence polarization assay. Among the three validated hits, the most potent inhibitor (compound 11, Fig. 5) binds to uPRA with a submicromolar affinity (Kd ¼ 310 nM) and inhibits the uPA–uPAR interaction with an IC50 of 10 mM.70 The hit blocked invasion of breast cancer cells but not their migration or adhesion. A close analogue of compound 11 was recently shown to be efficient in an in vivo breast cancer metastasis assay.79

Docking is not limited to the study of single protein–ligand interactions. In an elegant study, Li et al. reports a computational method enabling the simultaneous docking of multiple fragments to a single binding site, by analogy to experimental fragment screening.71 When applied to the PPI between IL-6 and gp130, simultaneous docking of two fragment pools (6 and 3 fragments, respectively) targeting two different hotspots at the PPI, two theoretical ligands could be reconstructed after tethering the best fragments at each hotspot. Searching for known drugs80 which are chemically similar to the two virtual hits suggested than two estrogen receptor modulators (raloxifene and bazedoxifene) may bind to the gp130/IL-6 PPI. Effective binding of both drugs to gp130 was confirmed experimentally, as well as inhibition of IL-6 induced STAT3 phosphorylation in various cancer cell lines defective in estrogen receptor expression. Bazedoxifene (compound 12, Fig. 5) was the most efficient (IC50 ¼ 25 mM) in inhibiting the ER-independent IL6-induced breast cancer cell proliferation, thereby offering some repositioning potential in the treatment of IL-6/gp130/STAT3 dependent tumours.71

The Nrf2–Keap1 complex, previously investigated using a pharmacophore-based approach (see the previous section), was also used for docking 300 000 commercially available compounds with the program Glide. Among the chemically diverse 65 top-ranking hits, 9 compounds were confirmed to be PPI inhibitors, the most potent disruptor (compound 13, Fig. 5) exhibiting a Kd of 2.9 mM in a fluorescence anisotropy-based assay.

A major hurdle in PPI inhibitor development is the frequently objected high molecular weight and unfavourable pharmacokinetic properties. Chen et al. strikingly contradicted this dogma by reporting a very low molecular weight inhibitor of the aB-crystallin (CRYAB)/VEGF-A interaction.73 CRYAB is a protein overexpressed in triple-negative breast cancer cells that acts as a chaperone to several proteins including the proangiogenic vascular endothelial growth factor (VEGF). Disrupting the interaction between CRYAB and VEGF-A is therefore a potential approach to cancer cell proliferation and invasion. The VEGF-binding site on the surface of the CRYAB X-ray structure was therefore targeted by docking 140 000 compounds from the NCI database using the Dock6.5 program (UCSF). Despite a very modest molecular weight (161.16 Da), one compound (compound 14, Fig. 5) was identified as an in vitro disruptor of the CRYAB/VEGF-A interface with an IC50 of ca. 20 mM. Intraperitoneal injection of compound 14 (200 mg kg1 ) remarkably suppresses tumour growth in vivo in human breast cancer xenograph models. VEGF-A is an important angiogenic factor that interacts with many other partners, notably the family of neuropilin receptors (NRP-1, NRP-2) whose inhibition leads to cancer cell apoptosis. The PPI between the C-terminal end of VEGF-A165 and the tandem b1 and b2 domains of NRP-1 was targeted for docking 430 000 molecules with a consensus docking approach relying on two docking programs (SurflexDock81 and ICM82). A consensus list of 1317 top-scoring compounds was retained for their in vitro anti-proliferative activity and binding to NRP-1 using a chemiluminescent assay.74 56 molecules (hit rate of 4.2%) antagonized the NRP-1/ VEGF-A interaction by at least 30% at the concentration of 10 mM. The best hit (compound 15, Fig. 5) is the first non-peptide NRP-1/VEGF-A antagonist (IC50 ¼ 34 mM) and displays remarkable anti-proliferative effects (IC50 ¼ 0.2 mM) on breast cancer cells. Administered at the dose of 50 mg kg1 in NOG xenographed mice, compound 15 strongly inhibits tumour growth inhibition by inducing cell apoptosis, without any effect on pro-angiogenic kinases.

Although most of the above reported therapeutical indications remain in the oncology field, PPI inhibitors have clear potential in other areas, notably infectious diseases as recently demonstrated by Han et al.75 who reported the structure-based discovery of antiviral compounds inhibiting viral–host interactions. The PPI target is the complex between the conserved Ldomain PPxY sequence of several viral matrix proteins (e.g. Ebola, Marburg, Lassa fever, and VSV) and the ubiquitin ligase Nedd4 protein. Docking ca. 5 million compounds (ZINC database)83 on the Nedd4 X-ray structure with the AutoDock4 program, yielded to the evaluation of 20 compounds, out of which one molecule was confirmed as a true inhibitor of the PPI in a cellular assay. Acquiring close analogs of the initial hit led to two more potent inhibitors (compounds 16 and 17, Fig. 5) as submicromolar inhibitors of the PPxY–Nedd4 interaction in vitro. 75 Both compounds exhibit antibudding activity against Ebola, Lassa fever, Marburg and VSV viruses, thereby decreasing viral titers, without apparent cytotoxicity on HEK293T cells.

Natural compounds are also a major source of potentially interesting PPI inhibitors. By docking a library of commercially available compounds to the p53 binding site, Vogel et al. recently reported lithocholic acid (compound 18, Fig. 5), a secondary bile acid, as a weak binder (Kd of 15 mM) to MDM4 and MDM2 proteins with a slight preference for MDM4.76 The natural compound was further shown to inhibit p53–MDM4 interactions and promote apoptosis in a p53-dependent manner by inducting caspase3/7.

Conclusions

We should acknowledge that peptides usually remain a good starting point to derive PPI inhibitors. Given the increasing number of high resolution X-ray structures of biologically relevant protein–protein complexes, the number of potentially increasing PPIs is likely to significantly rise in the next years. Provided that molecular rules exist to prioritize the most interesting anchoring residues at the interface, continuous protein epitopes can be easily converted into linear peptides for quick experimental validation. Recent progress in peptide stabilisation by chemical stapling next opens an immense eld for deriving either pharmacological tools or drug candidates. Numerous successes in identifying non-peptide PPI inhibitors also exist. The present review has only considered inhibitors mostly discovered by a rational structure-based virtual screening approach. Despite the few cases described herein (15 in total), examples are pretty much indicative of results than can be reasonably achieved. Comparing the properties of PPIs (Fig. 6A and B) and their inhibitors (Fig. 6C) with previously reported larger PPI data,64 some trends could be verified. Considering success as the availability of low micromolar nonpeptide inhibitors, successfully targeted PPIs present a higher proportion of charged residues with respect to conventional targets (sc-PDB data).84 Unsurprisingly, PPI inhibitors bind to smaller cavities (200–350 A˚3 ) than that presented by conventional targets (450–800 A˚3 range). Consequently, PPI inhibitors present a high proportion of aromatic rings, amide moieties and charged groups (Fig. 4 and 5) that hamper their druggability potential, as estimated here by the QED metric85 (Fig. 6C). We notice a significant proportion of negatively charged compounds, suggesting that a strong electrostatic interaction with the target is often mandatory to reach detectable affinity to PPI-participating cavities.

Fig. 6 Properties of PPIs and their inhibitors: (A) cavity properties expressed in percentage according to the cavity detection VolSite program86 (Hydro, hydrophobic; Aro, aromatic; H-bond, H-bond accepting/donating properties; Neg: negatively charged; Pos, positively charged, Du: fully accessible); (B) cavity volumes targeted by PPI inhibitors (this review) and conventional ligands (sc-PDB data84). The box delimits the 25th and 75th percentiles, and the whiskers delimit the 5th and 95th percentiles. The median and mean values are indicated by a horizontal line and an empty square in the box; (C) quantitative estimate of druggability (QED)85 of the inhibitors. QED values for true drug-like compounds should be over 0.5 (red broken line).

However, the current survey also indicates that there is no absolute dogma with respect to PPI inhibitor identification. Very low molecular weight compounds (compounds 1, 6 and 14) have been successfully identified as PPI disruptors.

Beside interfacial inhibitors, there exist promising alternative ways of inhibiting PPIs. For example, PPI stabilizers87,88 (e.g. paclitaxel, rapmycine, and forskolin) bind to rim exposed pockets at or very close to the interface, and also lead to the functional inactivation of the protein–protein complex. Such stabilizers are frequent in the nature, and this area still has not been fully exploited until now. Likewise, the allosteric inhibition of PPIs, at pockets remote from the interface, clearly deserves some consideration. Such pockets have been shown to be frequent at the close vicinity of two protein chains in close interaction,89 and represent, at least for some of them, more ligandable pockets than those presented by PPIs.

Although dominated by a continent of flat and featureless interfaces, the PPI world is also populated by very different islands in terms of shape and electrostatics that should not been discarded. Many factors are likely to increase our knowledge of PPIs and their inhibitors among which: (i) the increasing number of biologically relevant and crystallized protein–protein complexes, (ii) the development of label-free experimental screening techniques, and (iii) the significant contribution of molecular simulations to detect transient interfaces. Medicinal chemistry will be a key factor to transform moderately potent PPI inhibitor hits into clinical candidates with desired pharmacokinetic properties.

References

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?query¼organism% 3A9606+AND+keyword:%22Complete+proteome+[KW- 0181]%22, (accessed 17/07/2014).

2 J. P. Overington, B. Al-Lazikani and A. L. Hopkins, Nat. Rev. Drug Discovery, 2006, 5, 993–996.

3 P. Legrain and J. C. Rain, J. Proteomics, 2014, 107, 93–97.

4 K. Venkatesan, J. F. Rual, A. Vazquez, U. Stelzl, I. Lemmens, T. Hirozane-Kishikawa, T. Hao, M. Zenkner, X. Xin, K. I. Goh, M. A. Yildirim, N. Simonis, K. Heinzmann, ….A. L. Barabasi and M. Vidal, Nat. Methods, 2009, 6, 83–90.

5 M. P. Stumpf, T. Thorne, E. de Silva, R. Stewart, H. J. An, M. Lappe and C. Wiuf, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 6959–6964

 

 

 

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Single Nucleotide Repair and Tunable DNA-directed Assembly of Nanomaterials, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

single nucleotide repair and tunable DNA-directed assembly of nanomaterials

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Expanding DNAzyme functionality through enzyme cascades with applications in single nucleotide repair and tunable DNA-directed assembly of nanomaterials

Yu Xiang,a   Zidong Wang,b   Hang Xinga and   Yi Lu*ab     Show Affiliations
Chem. Sci., 2013, 4, 398-404       DOI:  <a href="http://dx.doi.org:/10.1039/C2SC20763J”>http://dx.doi.org:/10.1039/C2SC20763J

Many biological functions require two or more enzymes working together in cascades. While many examples of protein and RNA enzyme cascades are known, few enzyme cascades containing solely DNAzymes have been reported. Herein we demonstrate the combination of an 8–17 DNAzyme with RNA cleavage activity and an E47 DNAzyme with DNA ligation activity to achieve a new function of single ribonucleotide repair in DNA while maintaining the integrity of the original DNA sequence, which is difficult for a single DNAzyme to achieve. In addition, this method is applied to modify the sequences of DNA strands immobilized on the surface ofnanoparticles to control the DNA-directed assembly selectively and sequentially. Such an approach can be applied to other DNAzymes with different activities to expand the functions of DNAzymes and the scope of their applications.

Graphical abstract: Expanding DNAzyme functionality through enzyme cascades with applications in single nucleotide repair and tunable DNA-directed assembly of nanomaterials
The discovery of deoxyribozymes (DNAzymes) with enzymatic activity in the 1990s1,2 has demonstrated that DNA molecules are not simply inert biopolymers for genetic storage; they can be active catalysts as well.3–8 Since then, many DNAzymes have been obtained with catalytic functions such as cleavage,2,9–13 ligation,14–16 phosphorylation,17 adenylation18 or depurination19 of nucleic acids, as well as other reactions including porphyrin metallation, C–C bond formation, nucleopeptide linkage formation, oxygen transfer and thymine dimer repair.20–26 Because DNAzymes are facile to synthesize and more stable than protein and RNA enzymes, they have been widely used in applications such as nanomaterial assembly,27,28 biosensing,29–31 logical computing,32 nanomachine engineering,33 antiviral or gene therapy,34 and in vitro RNA manipulation.35 Despite these successes, the application of DNAzymes is limited by the narrower range of catalytic functionality compared to protein enzymes. One possible approach to addressing this issue would be to combine enzymes with different reactivities to form a cascade of successive enzymatic reactions, which together create new functionality. Indeed, many such examples exist in biology, since nearly all important biological functions, such as the pathways involved in DNA repair and protein synthesis, require a cascade of multiple protein enzymes to carry out their full function. In contrast, little has been reported about the use of DNAzyme cascades to realize enhanced functionality. Such a strategy could expand the functionality of DNAzymes to a level more on par with protein and RNA enzymes, which should greatly increase the range of possible applications.
One such application is single nucleotide repair, i.e., excision of a misincorporated ribonucleotide in single-stranded DNA and subsequent insertion of the corresponding deoxyribonucleotide at the excision site. The misincorporation of ribonucleotides into DNA strands can occur from exposure to external oxidizing agents or ionizing radiation,36 or spontaneously during DNA replication.37 Misincorporation of ribonucleotide can distort the structure of DNA,38 reduce its stability,39 and interfere with the normal interaction between DNA and DNA polymerases.40 In fact, the overexpression of DNA polymerases that are prone to ribonucleotide misincorporation has been linked to many cancers, including ovarian, prostate, breast and colon cancers.41 In nature, protein enzymes such as RNase H and FEN-1 can efficiently excise misincorporated ribonucleotides in DNA by cleaving the DNA at the ribonucleotide site and then restoring the correct deoxyribonucleotides by DNA polymerases,42,43 which is an example of an enzyme cascade. It would be interesting to nd out if a similar function could be achieved through DNAzyme cascades.
Another potential application is in tuning the properties of DNA-functionalized nanomaterials. For example, DNA-functionalized gold nanoparticles27 have emerged as an attractive platform for biosensing,32,44–50 nanomedicine,45 and as building blocks for controlled nanoassemblies.51–55 Although much research has been focused on the surface modification of gold nanoparticles with DNA for various applications, there are still limited methods to modify the sequences of DNA already immobilized on gold nanoparticles in order to make the properties of the DNA-modified nanomaterials tunable aer fabrication. The use of DNAzymes is a promising approach for DNA modification on nanomaterials56 due to the excellent stability of DNAzymes and their smaller size compared to protein enzymes, thereby minimizing steric effects between the enzyme and the DNA in order to avoid reduction in reaction efficiency. However, it is still very challenging to modify a specific DNA sequence on multiple-DNA-functionalized nanomaterials to tune their functions in a selective and sequential fashion.
Herein, we demonstrate a cascade of two DNAzymes with RNA cleavage and DNA ligation activities, respectively, in order to carry out single nucleotide repair or selective sequence modification of DNA. In a one-pot reaction, a single misincorporated ribonucleotide in a DNA strand was converted to the corresponding deoxyribonucleotide while maintaining sequence integrity. Furthermore, the sequences of DNA strands immobilized on multiple functional nanoparticles were successfully modified in order to control and alter the DNAdirected assembly of nanoparticles in a stepwise and selective fashion.
Results and discussion To demonstrate that single nucleotide repair in DNA can be achieved by the cascade of two DNAzymes, we used a 26-nt DNA strand (O1) containing a misincorporated cytidine (rC) ribonucleotide as an example. The goal was to convert the rC in O1 into a deoxycytidine (C), as seen in O4 (Fig. 1a), while maintaining the integrity of the DNA sequence. The DNAzymes 17Em1 (Fig. 1a, blue) with RNA cleavage activity2,57–59 and E47 (Fig. 1a, red) with DNA ligation activity14,60 were chosen as the cascade pair in this study. The 17Em1 DNAzyme catalyzes the hydrolysis of the 30 phosphodiester linkage of the internal rC in the DNA strand when metal ion cofactors such as Pb2+ and Zn2+ are present (Fig. S1a in ESI†). On the other hand, the E47 DNAzyme can induce the catalytic ligation of the 50 –OH of the DNA substrate with another 30 -phosphorylated DNA strand (activated by imidazole)14 in the presence of Cu2+ or Zn2+ as the metal cofactor (Fig. S1b in ESI†). Therefore, by sequential cleavage and ligation reactions catalyzed by these two DNAzymes on O1 containing rC, O1 could first be cleaved at the 30 phosphodiester of the rC by 17Em1 and then undergo ligation at the cleavage site with another 30 -phosphorylated DNA strand of an identical sequence (except with deoxyribonucleotide C in place of ribonucleotide rC) by E47. The product O4 has a sequence identical to the starting strand O1, with the rC replaced with C.
Fig. 1 (a) Conversion of a single ribonucleotide (rC) in a DNA strand O1 to a deoxyribonucleotide (C) by the cascade of DNAzymes 17Em1 and E47: O1 is cleaved by 17Em1 to afford products of O2 and Oc; O2 is then ligated with O3 (activated by imidazole) to form O4 by E47. (b) Sequence modification of a DNA strand O5 to O4 through a similar protocol by the cascade of DNAzymes 17Em2 and E47.
Initially, 30 -fluorescein-labeled O1 was treated with 17Em1 to form DNA duplex O1-17Em1 via 18 matched base pairs (9 on each binding arm). In the presence of Pb2+, O1 was efficiently cleaved by 17Em1 into fragments O2 and Oc, resulting in the dehybridization of the duplex because the melting temperature of the duplex between 17Em1 and O2 or between 17Em1 and Oc is below room temperature (Fig. 1a). The fluorescence image after polyacrylamide gel electrophoresis (PAGE) suggested the complete cleavage of O1 and formation of O2 (Fig. 2a, lane 1 and 2 for O1 and O2, respectively), while Oc was not visible on the gel due to the lack of a fluorescein label. The cleavage reaction product O2 was also confirmed by the result from matrixassisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrum (Table 1 and Fig. S2 in ESI†). Control experiments using a DNAzyme of a different sequence (17Em2) or without Pb2+ showed negligible cleavage of the substrate O1 (Fig. S3 in ESI†) due to the specificity of the DNAzyme and the essential role of the metal ion cofactor.2,57–59 Subsequently, without any purification of O2 from the mixture solution after the previous cleavage step, E47 and 30 -phosphorylated O3 (imidazole-activated) were added into the solution to generate another DNA complex O2–O3-E47, which gave O4 as the product after the E47-catalyzed ligation reaction in the presence of Cu2+ (Fig. 1a).14,60 The formation of O4 was confirmed by both fluorescent PAGE (Fig. 2a, the upper band of lane 3) and MALDITOF MS (Table 1 and Fig. S2 in ESI†), while some unreacted O2 was also observed on the gel (Fig. 2a, the lower band of lane 3). Here, O3 was invisible due to the lack of a fluorescein label. Considerably lower levels of ligation between O2 and O3 were observed if either E47 or Cu2+ was absent (Fig. S3 in ESI†). Together these results indicate that the reactions catalyzed by the DNAzyme cascade were achieved through a one-pot reaction without isolation and purification of the intermediate O2.
Fig. 2 (a) Fluorescent PAGE (20% denaturing gel) images of the transformation from O1 to O4 by DNAzymes 17Em1 and E47. Lanes in (a): 1, O1; 2, 1 after cleavage by 17Em1 to yield O2 and Oc in the presence of Pb2+; 3, 2 after ligation to yield O4 by E47 in the presence of O3 and Cu2+; 4, 2 after ligation to yield O4 + 8A by E47 in the presence of O3 + 8A and Cu2+; 5, O4 in the presence of Pb2+ and 17Em1. (b) Fluorescent PAGE images of the transformation from O5 to O4 by 17Em2 and E47: Lanes in (b): 1, O5; 2, 1 after cleavage by 17Em2 to yield O2 in the presence of Pb2+; 3, 2 after ligation to yield O4 by E47 in the presence of O3 and Cu2+; 4, 2 after ligation to yield O4 + 8A by E47 in the presence of O3 + 8A and Cu2+; 5, O4 in the presence of Pb2+ and 17Em2
To provide further confirmation of the above successful conversion of rC in O1 to C in O4, while keeping other sequences identical, a longer O3 + 8A (O3 extended by A8 at 50 ) was used in place of O3 (Fig. 1a). Under the same conditions, a longer product O4 + 8A was obtained (Fig. 2a, the upper band of lane 4) with slower gel migration compared to O4 (Fig. 2a, the upper band of lane 3), suggesting that the ligation reaction occurred mostly between O2 and imidazole-activated O3, and not between O2 and un-activated Oc (Oc is the product from the previous cleavage reaction of O1 and 17Em1), in which case a band with the same migration as O4 would have been observed. The presence of C rather than rC in the product O4 was supported by the lower molecular weight of O4 in the MALDI-TOF mass spectrum as compared to that of O1 (Table 1), as well as the increased resistance to hydrolysis of O4 even in the presence of Pb2+ and 17Em1 (Fig. 2a, lane 5), which can catalyze the cleavage of a substrate containing an internal ribonucleotide linkage (O1),2,57 but not a substrate containing entirely deoxyribonucleotides (O4).
Table 1 Measured and calculated molecular weight (m/z) in MALDI-TOF mass spectra of 30 -fluorescein-labeled DNAs (O1, O2, O4 and O5). For full spectra, see Fig. S2 in ESI.†
DNA O1 O2 O4 O5 Measured 8831.6 4824.1 8812.3 8819.1 Calculated 8831.9 4826.3 8815.9 8821.9duct O4 + 8A was obtained (Fig. 2a, the upper band of lane 4) with slower gel migration compared to O4 (Fig. 2a, the upper band of lane 3), suggesting that the ligation reaction occurred mostly between O2 and imidazole-activated O3, and not between O2 and un-activated Oc (Oc is the product from the previous cleavage reaction of O1 and 17Em1), in which case a band with the same migration as O4 would have been observed. The presence of C rather than rC in the product O4 was supported by the lower molecular weight of O4 in the MALDI-TOF mass spectrum as compared to that of O1 (Table 1), as well as the increased resistance to hydrolysis of O4 even in the presence of Pb2+ and 17Em1 (Fig. 2a, lane 5), which can catalyze the cleavage of a substrate containing an internal ribonucleotide linkage (O1),2,57 but not a substrate containing entirely deoxyribonucleotides (O4).
In addition to the single nucleotide repair functionality, it is also possible to use this methodology to edit the sequence of a DNA strand, which was used to convert the DNA strand O5 into O4 using the same cascade and conditions as before (Fig. 1b and S4 in ESI†). The product O4 was confirmed by PAGE (Fig. 2b) and MALDI-TOF MS (Table 1 and Fig. S2 in ESI†) and found to be identical to that obtained from the method in Fig. 1a.
Encouraged by the above results, we applied this method to modify the sequence of DNA immobilized on gold nanoparticles27 (AuNPs) to control the DNA-directed assembly of the AuNPs in a selective manner. DNA-functionalized gold AuNPs have been used in a variety of applications due to both their unique properties and the sequence-dependent hybridization of ssDNA immobilized on the AuNPs for controlled assembly.51–55 As shown in Fig. 3, when AuNPs are functionalized by complementary DNAs, the AuNPs can assemble into an “aggregated” state via DNA hybridization, which shows red-shifted and broadened absorption spectra compared to AuNPs functionalized by non-complementary DNAs.
Fig. 3 Assembly of two types of DNA-functionalized gold nanoparticles. If the sequences of the two DNAs are not complementary, the gold nanoparticles are in a “dispersed” state and exhibit a red color with a sharp absorption band peaked around 532 nm (left). In contrast, the assembly of the gold nanoparticles with complementary DNAs causes the formation of an “aggregated” state with a broad absorption band around 600 nm (right).
By modifying the sequences of DNA on the AuNPs, the assembly of the particles can be effectively controlled. Although methods for fabrication of DNAfunctionalized AuNPs have been developed,27 there are still limited methods to modify the DNA sequences already immobilized on AuNPs in order to tune their functions. It is even more challenging to modify a specific DNA sequence on multiply-functionalized AuNPs with different DNA sequences on each nanoparticle. Selective modification can allow each different function of the AuNP to be controlled in a selective fashion for potential applications.
AuNPs of 13 nm diameter were functionalized with DNA molecules via 30 -end thiols and used for this study. The formation of the AuNP assembly was confirmed by TEM images (Fig. S5 in ESI†) and characterized by large changes in absorption spectra27 (A700/A532 changed from <0.15 to >0.50 as illustrated in Fig. 5 and Table S1 in ESI†). As shown in Fig. 4, O6- functionalized AuNPs (red) were found to be able to form aggregates with O9-functionalized AuNPs (blue) via DNAdirected assembly through 12 complementary base pairs (Fig. 5 and S5 and Table S1†), but not with O10-functionalized AuNPs (purple), because of the 4 mismatched base pairs in the middle of the binding arm (Fig. 5 and S5 and Table S1†). After being treated with 17Em2 and Pb2+, the O6 on the surface of AuNPs was cleaved and converted to O8, which could not hybridize with either O9 or O10 efficiently. Thus no DNA-directed assembly was observed between the resulting O8-functionalized AuNPs and either O9- or O10-functionalized AuNPs (Fig. 5 and S5 and Table S1†). However, after a subsequent ligation reaction catalyzed by E47 in the presence of imidazole-activated O3 and Cu2+, O8 on the surface of AuNPs could be extended to O7, making the AuNPs capable of assembling with O10-, but not O9- functionalized AuNPs (Fig. 5 and S5 and Table S1†).
 Fig. 4 Controlling the assembly of DNA-functionalized gold nanoparticles via cascade-mediated modification of the DNA sequences. The solid and dashed lines indicate the successful and unsuccessful formation of aggregates, respectively. The inset shows the assembly of AuNPs modified with the complementary strands O6 and O9 (top) and the lack of assembly between AuNPs modified with noncomplementary strands O9 and O7 (obtained by treating O6-functionalized AuNPs with 17Em2 and E47) (bottom)
Fig. 5 Absorption spectra of O6-, O7- or O8-functionalized AuNPs in the presence of O9- and O10-functionalized AuNPs, respectively. The red-shift of the peak indicates the formation of AuNP aggregations due to the hybridization of complementary DNAs on the AuNPs.27 For the ratios of absorbance (A700/A532), see Table S1 in ESI.†
 Interestingly, the product, O7-functionalized AuNPs, showed inverse characteristics in the formation of DNA-directed assembly with O10- and O9-functionalized AuNPs, compared to the original O6-functionalized AuNPs. TEM images of O6- functionalized AuNPs, either with or without treatment with 17Em2/E47, mixed with O10-functionalized AuNPs, are displayed in the inset of Fig. 4. These results clearly demonstrate that the ability to edit and replace DNA on AuNPs allows for exquisite programmable control over the assembly of nanoparticles.
Taking advantage of the specificity of DNAzyme to its nucleic acid substrates by complementary base pairing in the binding arms, selective modification of DNA sequences on surface of multiple functional AuNPs was also achieved in this work. As depicted in Fig. 6, O6 (red) and O11 (blue) bi-functional AuNPs could be modified by 17Em1, 17Em2 and E47 selectively and sequentially. As shown in Fig. 6, AuNPs capable of forming DNA-directed assembly with both (A and E), either (B, C and F), or neither (D) of the O9- and O10-functionalized AuNPs could be obtained by monitoring the significant increase of A700/A532 as indication of assembly formation (Fig. 7 and Table S2 in ESI†). Such a result, which is challenging to achieve by other techniques, can be used for the construction of tunable nanoassemblies for various applications.
Fig. 6 (a) Scheme showing stepwise modification of DNA sequences on multiply-functional gold nanoparticles by the collaboration of 17Em1 or 17Em2 and E47. (b) DNA sequences of O6–O8 and O11.
Fig. 7 Absorption spectra of DNA-functionalized gold nanoparticles (A–F) (Fig. 6a) in the presence of O9- and O10-functionalized AuNPs, respectively. The red-shift of the peak indicates the formation of AuNP aggregations due to the hybridization of complementary DNAs on the AuNPs.27 For the ratios of absorbance (A700/A532), see Table S2 in ESI.†
In summary, by putting together a cascade of two DNAzymes with cleaving and ligating activities, we have generated a new functionality for effective DNA modification. This function was applied in the conversion of a single misincorporated ribonucleotide into the corresponding dexoyribonucleotide in DNA and the modification of DNA sequences on the surface of gold nanoparticles to modify and control their self-assembly through DNA hybridization. The results suggest that combining DNAzymes with different catalytic activities may achieve more interesting functions and thus broaden the applications of DNAzymes.
Notes and references
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Peptides and anti-Cancer activity

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

PE and PS Lipids Synergistically Enhance Membrane Poration by a Peptide with Anticancer Properties

Natália Bueno Leite, Anders Aufderhorst-Roberts, Mario Sergio Palma, Simon D. Connell, João Ruggiero Neto, Paul A. Beales
Biophys J 1 Sept 2015; 109(5):936–947.   DOI: http://dx.doi.org/10.1016/j.bpj.2015.07.033
Polybia-MP1 (MP1) is a bioactive host-defense peptide with known anticancer properties. Its activity is attributed to excess serine (phosphatidylserine (PS)) on the outer leaflet of cancer cells. Recently, higher quantities of phosphatidylethanolamine (PE) were also found at these cells’ surface. We investigate the interaction of MP1 with model membranes in the presence and absence of POPS (PS) and DOPE (PE) to understand the role of lipid composition in MP1’s anticancer characteristics. Indeed we find that PS lipids significantly enhance the bound concentration of peptide on the membrane by a factor of 7–8. However, through a combination of membrane permeability assays and imaging techniques we find that PE significantly increases the susceptibility of the membrane to disruption by these peptides and causes an order-of-magnitude increase in membrane permeability by facilitating the formation of larger transmembrane pores. Significantly, atomic-force microscopy imaging reveals differences in the pore formation mechanism with and without the presence of PE. Therefore, PS and PE lipids synergistically combine to enhance membrane poration by MP1, implying that the combined enrichment of both these lipids in the outer leaflet of cancer cells is highly significant for MP1’s anticancer action. These mechanistic insights could aid development of novel chemotherapeutics that target pathological changes in the lipid composition of cancerous cells.

The antimicrobial peptide Polybia-MP1 (IDWKKLLDAAKQIL-NH2), or simply MP1, has unexpectedly been shown to exhibit selective inhibition against several types of cancerous cells and therefore could prove advantageous in the development of novel chemotherapies. Extracted from the Brazilian waspPolybia paulista, MP1 has a broad spectrum of bactericidal activities against Gram-negative and Gram-positive bacteria without being hemolytic and cytotoxic (1). Surprisingly, MP1 also selectively inhibits proliferating bladder and prostate cancer cells (2), and multidrug-resistant leukemic cells (3). Recently, it has been observed that this peptide is cytotoxic against leukemic T lymphocytes and very selective in recognizing these cells compared to healthy lymphocytes (4).

Cancer cell membranes are now known to lose the asymmetric transmembrane distribution of phospholipids that is observed in healthy cells (5, 6). In healthy mammalian cells, the anionic aminophospholipid PS (phosphatidylserine) is predominant in the inner membrane leaflet and zwitterionic phospholipids are predominant in outer membrane leaflet. In such cells, the phospholipid asymmetry is maintained by a family of aminophospholipid translocases that catalyze the transport of PS from the outer to the inner membrane leaflets (7). However, in apoptotic and cancer cells, PS is found to also be located in the outer monolayer of the plasma membrane in significant proportions (5, 6).

The molecular-scale mechanistic basis for MP1’s anticancer properties is yet to be established. Changes in the distribution and/or composition of lipids (e.g., PS) within the plasma membrane of malignant cells could be the origin of MP1’s cancer selectivity. This is a reasonable hypothesis, based upon the well-established selectivity of antimicrobial peptides for bacterial membranes over eukaryotic membranes due to their higher anionic lipid content (8, 9, 10, 11). Recently, the effect of PS on the pore-forming activity of MP1 was investigated by multiple techniques, namely, conductance measurements in planar bilayer lipid membranes, binding assays, and lytic activity on large unilamellar vesicles (4). Although an increase in affinity and lytic activity of MP1 for lipid vesicles containing PS was observed, MP1’s pore-formation activity in BLM showed no difference between PC (phosphatidylcholine) and mixed PC/PS bilayers. Significantly, it was recently reported that PE (phosphatidylethanolamine) lipids, naturally found on the inner plasma membrane of normal cells, are also externalized to the outer monolayer of the plasma membrane of apoptotic and tumor endothelial cells due to both PS and PE lipids being coregulated by the same transporters (7). These authors observed that the exposure to the outer monolayer of one of these phospholipids leads to the exposure of the other. Therefore, it is important for future work to establish the role of increased concentrations of both PE and PS lipids in the interaction of MP1 with membranes.

In this work, we address this challenge by establishing the roles of PE and PS lipids in the effects of MP1 on the structure and permeability of model membranes. Primarily, we study the permeability of giant unilamellar vesicles (GUVs) at the single vesicle level. Fluorescence confocal microscopy was used to determine the size-dependent macromolecular permeability of lipid membranes in GUV model systems by analyzing the influx of three fluorescent dyes with molecular masses of 0.37, 3.0, and 10.0 kDa into these vesicles (Fig. 1). We deconvolve the effects of PS and PE lipids by exploring their effects within DOPC (PC) membranes both separately and in combination: DOPC/POPS 80:20 (PC/PS), DOPC/DOPE 90:10 (PC/PE), and DOPC/DOPE/POPS 70:10:20 (PC/PE/PS). These experiments are corroborated by circular dichroism (CD) spectroscopy to quantify peptide binding to the membrane, fluorescence spectroscopy experiments to establish the leakage mechanism in an ensemble system of nanoscale large unilamellar vesicles (LUVs), and atomic-force microscopy (AFM) imaging of supported lipid bilayers to reveal the nanoscale perturbations of membrane structure induced by the peptide. By combining these approaches, we show that, while PS lipids significantly enhance MP1’s binding onto the membrane, PE lipids impart the most significant contribution to the rate and extent of membrane permeabilization by MP1, facilitating the opening of larger membrane defects than in bilayers lacking in PE.

Thumbnail image of Figure 1. Opens large image

http://www.cell.com/cms/attachment/2035808117/2051293431/gr1.jpgFigure 1

Schematic representation of membrane disruption by peptides and the experimental system. The helical peptide Polybia-MP1 is shown according to the helical wheel projections. Amino acids: (blue) polar with positive net charge; (purple) polar with negative net charge; (red) polar noncharged; and (green) nonpolar. Confocal microscopy was performed to investigate the influx of three dyes with distinct sizes in GUVs in the presence and absence of PE lipids: 0.37 kDa CF (green), 3k-CB (blue), 10k-AF647 (magenta), and the scale bars correspond to 10 μm. Lipid membranes are labeled with Rh-DOPE (red). The peptide interacts with the GUVs, disturbs their structure, and then enables the passage of fluorescent dyes by formation of pore-like structures. To see this figure in color, go online.

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

Results

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

PS lipids significantly enhance peptide binding to the membrane

The overall efficacy of a peptide at disrupting a target membrane can be broken down into the combination of two sequential steps: 1) binding of the peptide to the membrane surface, and 2) the efficiency of membrane disruption by the bound peptide resulting in membrane poration or leakage. First, we investigate the membrane binding isotherms of the MP1 peptide to our four lipid compositions of interest by CD spectroscopy by titrating a 10 μM MP1 solution with increasing lipid (LUV) concentrations (Fig. 2). Fitting these binding isotherms revealed that the partition coefficient (Kp) of the peptide was 7–8 times higher for membrane compositions containing PS (Kp values were PC 4600 M−1, PC/PE 4000 M−1, PC/PS 33,000 M−1, and PC/PE/PS 30,000 M−1). It is also interesting to note from this data that PE lipids slightly suppress peptide binding by a factor of ∼10%. Due to the cationic nature of MP1 (net charge of +2e), it is highly likely that the enhanced peptide binding to anionic-PS-containing membranes is primarily driven by electrostatic interactions.

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Figure 2

Binding isoterms show that MP1 has a higher affinity for PS-containing membranes. The binding isoterms and the partition coefficients (Kp) obtained using CD by lipid titration at 10 μM MP1 solution. LUVs are composed of (a) PC, (b) PC/PE, (c) PC/PS, and (d) PC/PE/PS.

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations

To investigate the efficiency of membrane disruption, we measured the leakage of macromolecules across GUV model membranes by confocal fluorescence microscopy. Fluorescent passive leakage markers of different sizes were simultaneously employed: 0.37 kDa carboxyfluorescein (CF), 3 kDa dextran labeled with Cascade Blue (3k-CB), and 10 kDa dextran labeled with Alexa Fluor 647 (10k-AF647). GUVs were composed of PC, PC/PS, PC/PE, or PC/PE/PS. The dose-response of the membranes to the addition of MP1 was characterized for each membrane composition and passive leakage marker by evaluating the normalized fluorescence intensities of the probes in the intravesicular lumen of the GUVs after 30 min incubation time (Fig. 3 and Fig. S1 in the Supporting Material). Each data point in Figs. 3 and S1 shows the mean leakage of 50 individual GUVs from a minimum of two independent experiments. For determining the percentage of leaked vesicles (Fig. 3), a threshold of 20% leakage (normalized to the background probe concentration) was used to define a filled vesicle. Alternatively, this data can be analyzed in terms of the average leakage into GUVs as a percentage of the probe concentration in the external medium (Fig. S1).

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Figure 3
Dose-response curves show increased leakage of PE containing GUVs at lower peptide concentrations. (a and c) Percentage of GUVs filled by CF (0.37 kDa) after 30 min incubation time with MP1. (b and d) Percentage of GUVs filled by 10k-AF647 after 30 min incubation time with MP1. All vesicles presenting >20% of dye entry were accounted as filled. The data is plotted as a function of (a and b) total peptide concentration and (c and d) the concentration of peptide bound to the membranes. Fifty GUVs were used to construct each data point. Vesicles are composed of PC, PC/PS, PC/PE, and PC/PE/PS. To see this figure in color, go online.

The integrity of membranes containing both PE and PS lipids is perturbed by lower concentrations of MP1 peptide than the other membrane compositions we investigated. PC/PE/PS GUVs show significant (40–65%) leakage to the CF probe at 0.4 and 1.2 μM MP1 concentrations, whereas other membrane compositions studied leaked <30% within this concentration range (Fig. S1a).

Larger pore defects, evidenced by leakage of the larger 10k-AF647 probe, are shown to be significantly enhanced in membranes containing 10% PE. Almost all GUVs (98%) containing PE lipids are observed to leak the 10k-AF647 probe when in the presence of 4.0 μM MP1, compared to <60% of GUVs for other membrane compositions at the same peptide concentration (Fig. 3b). This is the most significant enhancement in selective perturbation for specific lipid membrane compositions observed within the dose-response data in Figs. 3 andS1. At this MP1 concentration, membranes under native conditions would be susceptible to the leakage of biological macromolecules such as small proteins and RNAs.

Interestingly, we also plot the GUV leakage data as a function of the concentration of bound peptide on the membrane using the specific partition coefficients of the peptide for different lipid compositions that were calculated inFig. 2 (see also Figs. 3, c and d, and S1, c and d). This representation of the data clearly shows that PE lipids increase the susceptibility of PC membranes to disruption by the MP1 peptide, with PC/PE lipids leaking at significantly lower bound peptide concentrations. Due to the higher bound concentration of peptide to membranes containing PS lipids, this lipid decreases the apparent susceptibility of the membrane to leakage as observed by the onset of leakage shifting to higher bound peptide concentrations. For PC/PE/PS GUVs, the apparent competing effects of PE and PS lipids on the membrane’s leakage susceptibility roughly cancel each other out, leading to intermediate membrane disruption susceptibility for a given bound peptide concentration. However, the effect of increased bound peptide concentrations due to PS far outweighs its apparent inhibition of membrane leakage, making PC/PE/PS GUVs the most susceptible to leakage for a given total peptide concentration. Therefore, the combined roles of PS in increasing membrane binding and PE in increasing the susceptibility of the membrane are both important in increasing the membrane disruptive efficacy of MP1.

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

Confirmation of the pore-formation hypothesis in lipid vesicles

Fluorescence spectroscopy experiments using LUVs give ensemble-averaged measurements with high statistics on a large population of vesicles, complementing single-vesicle GUV imaging experiments that inherently have lower statistics but yield information on the distribution of behaviors and rare events within a sample. The fluorescence requenching method (18) enables us to distinguish the type of leakage mechanism induced by MP1 for the lipid compositions under investigation. One possibility is the all-or-none mechanism where some vesicles release all of their internal contents while the others remain intact. This is attributed to pore-formation mechanisms of membrane perturbation, or complete vesicle lysis. Another possibility is the gradual leakage mechanism where vesicles only release a fraction of their encapsulated contents during a leakage event. This is associated with transient perturbations of the membrane. A fluorophore (ANTS) and a quencher (DPX) are encapsulated within lipid vesicles at high concentrations such that the fluorescence is initially quenched; vesicle leakage results in the release of both ANTS and DPX, but quenching is decreased due to dilution of these probes. The externalized ANTS fluorescence can be suppressed by additional titration of DPX such that the remaining fluorescence signal is only due to the ANTS inside intact vesicles. The data can be represented by a plot of the degree of quenching (Qin) against the released ANTS fraction (fout). In the case of an all-or-none leakage mechanism, the plot of Qin versus fout will show no dependence of Qin on fout. In contrast, the gradual leakage mechanism causes release of only a fraction of the encapsulated contents within individual vesicles and so Qin increases with increasing fout (18).

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Figure 4

Fluorescence requenching assays for MP1 reveal all-or-none leakage in the four lipid compositions studied. Qin is constant as a function of fout for MP1, which is in agreement with the all-or-none mechanism of dye release.) (Lines) Theoretical curves for ideal graded and all-or-none dye release (18). To see this figure in color, go online.

Fig. 4 shows that the values of Qin remain constant with the increase of fout and the consequent increase of peptide/lipid molar ratios. This clearly shows that MP1 exhibits the all-or-none leakage mechanism for all lipid compositions studied, which is in contrast to what has been observed for antimicrobial peptides mastoparan X and mastoparan MP (19). We propose that this all-or-none leakage is related to peptide-induced pore formation (20, 21, 22, 23), where the vesicles are able to release all their internal contents through pore-like structures that are sufficiently long lived (23, 24, 25, 26, 27, 28). We do not solely attribute the all-or-none leakage to lysis of the vesicles because nonlysed, leaky vesicles are observed in our GUV experiments (Figs. 3 and S1). However, we do not discount the possibility that lysis might play a role in the LUV leakage at the highest peptide concentrations used in this assay. Furthermore, pore-like activity of MP1 has previously been identified from electrophysiology measurements in planar lipid bilayers composed of phytanoyl-PC and phytanoyl-PC/PS (70:30) (4).

Our fluorescence requenching results show that stable pores form with a lifetime that persists long enough for the dye efflux to reach equilibrium in LUV systems. However, this does not discount the possibility that pores might be transient over longer timescales, for example during the leakage of much larger vesicles such as GUVs where the encapsulated volume of dye that needs to be released during a leakage event is ∼106 times greater than for the LUV model system. Indeed, we will see some evidence for transient pore events and dynamic changes in membrane permeability in the single GUV leakage kinetics data that follows. Nevertheless, all-or-none leakage is clearly evident in GUVs after 30 min incubation with 1.2 and 4.0 μM MP1. Leakage histograms of the individual GUVs (an alternative representation of data shown in Figs. 3 and S1) predominantly show either Math Eq20% (unleaked) or Math Eq80% (fully leaked) leakage (Fig. S2).
Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

Synergistic enhancement of GUV leakage kinetics by PE and PS lipids

Analysis of the time delay from the start of our GUV experiments (addition of the peptide) to observations of the onset of GUV leakage reveals a synergistic reduction in this lag time for PC/PE/PS membranes (Table 1 and Fig. 5). In these GUV experiments, we add 4.0 μM MP1 to our samples and monitor the time taken for initial leakage events of GUVs to the 0.37 kDa CF probe to occur (t0tCF). This MP1 concentration is chosen as it causes significant leakage of GUVs within 30 min of peptide addition across all four lipid compositions of interest. The onset of leakage occurs approximately twice as quickly for PC/PE/PS GUVs than for other membrane compositions, with only a very slight reduction of the lag time for PC/PS membranes compared with PC/PE and PC GUVs. Therefore, this is not a purely electrostatic effect from the increased rate and extent of peptide binding to anionic PS-containing membranes; it also requires the presence of PE to significantly increase the susceptibility of the membrane to permeabilization.

Table 1Lag times between the onset of leakage of each dye and the time interval before the initial leakage takes place after the addition of peptide
Time Delays (s) PC/PE PC/PE/PS PC/PS PC
t0tCF 1600 ± 110 760 ± 120 1400 ± 60 1600
tCFt3k-CB 1.8 ± 0.6 1.5 ± 0.3 41 ± 5a 160 ± 110
tCFt10k-AF647 4.2 ± 1.5 2.0 ± 0.4 52 ± 6 220 ± 66
t3k-CBt10k-AF647 2.7 ± 0.9 1.4 ± 0.4 9.6 ± 1.2 60 ± 42

The errors represent the standard deviation of the observed GUV data set.

aFor PC/PS GUVs, the tCFt3k-CB data only includes GUVs that leaked to all three dyes; these sample conditions contained two distinct populations of GUV leakage behaviors where a second population of GUVs only leaked to the CF and 3k-CB dyes with a time delay of tCFt3k-CB = 4.8 ± 0.6 s.
large Image
Figure 5
GUV permeabilization kinetics are synergistically enhanced by PE and PS lipids. (a) Comparison between dye influx kinetics of three distinct dyes (CF-0.37kDa, 3k-CB, and 10k-AF647) for PC/PE/PS and PC/PS GUVs. The time axis represents the time after peptide addition. These individual GUV leakage profiles were chosen as they represent the average behavior of the GUVs observed under these conditions. (b) Schematic representation of the dye influx kinetics for PC/PS and PC/PE/PS GUVs in the presence of CF and 10k-AF647 passive leakage markers. This shows the average lag times for GUV leakage after the addition of 4.0 μM MP1 and the typical average leakage extent of the GUVs that resulted in these experiments. To see this figure in color, go online.
We also quantify the average delay times between leakage of the different-sized fluorescent probes between CF and 3k-CB (tCFt3k-CB), CF and 10k-AF647 (tCFt10k-AF647), and 3k-CB and 10k-AF647 (t3k-CBt10k-AF647). Once the initial leakage event occurs, PE-containing GUVs rapidly become leaky to fluorescent probes of larger sizes (3 and 10 kDa). For PC/PE/PS and PC/PE membranes, GUVs become leaky to larger 3k-CB, then 10k-AF647 passive leakage markers within seconds of permeabilization to the smallest CF (0.37 kDa) probe (Table 1). The consecutive delay times between CF and 3k-CB probes and 3k-CB and 10k-AF647 probes were approximately an order-of-magnitude longer for PC/PS membranes, and almost two orders-of-magnitude longer for purely PC membranes. This strongly implies that the presence of PE significantly enhances the favorability and rate of formation of larger membrane defects or pores.
Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

PE lipids significantly enhance pore size and membrane permeability

We use time-series confocal microscopy imaging to quantify the membrane permeability of GUVs during initial leakage. Quantification of the fluorescence intensity of the leakage markers in the intravesicular and extravesicular medium allows us to calculate the fractional leakage of individual GUVs as a function of time. The leakage kinetics of individual GUVs are monitored for up to 30 min after the addition of 4.0 μM MP1. This concentration is chosen as all lipid compositions show significant leakage within 30 min; a higher MP1 concentration of 10 μM is observed to induce significant lysis of GUV samples (Fig. S3). These experiments are conducted on GUVs of all four membrane compositions under investigation, using the CF, 3k-CB, and 10k-AF647 leakage markers simultaneously. This allows the time evolution of membrane permeability to different molecular sizes to be simultaneously measured for individual GUVs (Figs. 5a and S4). To the best of our knowledge, this is the first example of simultaneous size-dependent permeability measurements in GUVs for three different-sized leakage markers.

Typical leakage kinetic profiles for different membrane compositions and probe sizes are shown in Figs. S4 and 5a. It can be qualitatively seen from these example profiles that membrane compositions containing 10% PE exhibit full and rapid membrane leakage for all three sizes of leakage marker, consistent with the leakage kinetics data in Table 1, which is also outlined in Fig. 5b. For membrane compositions lacking PE, the leakage rates can sometimes be seen to increase and decrease intermittently, sometime plateauing before full leakage is achieved; this is particularly evident in the leakage profile of a single PC/PS GUV shown in Fig. S5. We attribute these observations to membrane self-healing events, where the pores/defects reseal and the membrane regains its permeability barrier, followed by later phases of increased leakage. This is particularly observed for the larger 3k-CB and 10k-AF647 leakage probes. Therefore, the membrane permeability for PC and PC/PS GUVs, in particular, can change dynamically during the observed leakage events; this is a result of the competition between the lipid bilayer and peptides in maintaining their barrier properties and inducing membrane pores, respectively (Fig. S5).

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Figure 6

PE lipids facilitate much greater membrane permeability in GUV membranes. (a) Typical log-linear plot of time-dependent dye influx: −R/3ln(1−c) (105) versus time, for the three dyes in a single GUV of PC/PS. (b) Distributions of the obtained permeabilities in single GUVs composed of PC/PS. (c) Typical log-linear plot of time-dependent dye influx: −R/3ln(1−c) (10−5) versus time, for the three dyes in a single GUV of PC/PE/PS. (d) Distributions of the obtained permeabilities in single GUVs composed of PC/PE/PS. The permeabilities are obtained from the slopes of the log-linear plots of the time-dependent influx of dyes into single GUVs. To see this figure in color, go online.

Our leakage kinetic profiles were used to calculate the membrane permeability to the different-sized probes using a diffusional model for membrane translocation (29); the membrane permeability is the gradient of the log-linear plot as seen in the example data in Fig. 6, a and c. Average permeability values for each membrane composition to each probe size during the initial leakage events are shown in Table 2. It can be seen that, for all membrane compositions tested, average permeability decreases with increasing probe size. However, the most significant finding from this data is the large, one-order-of-magnitude increase, in membrane permeability for membrane compositions containing 10% PE. This can be observed for all three leakage markers studied. It can also be seen that the presence of PS in the membrane imparts a modest, but significant, increase in permeability on the membranes upon perturbation by MP1. This effect can be seen further in Fig. 6, b and d, which show the distributions of permeability measurements for PC/PS and PC/PE/PS GUVs to the CF and 10k-AF647 leakage markers, respectively. For both probe sizes, the majority of permeability measurements for PC/PS membranes were in the 0–25 nm/s range, whereas when PE was included in the membrane formulations, a large proportion of permeability measurements were >500 nm/s.

Table 2Average permeability values (〈Pm〉) and the average fractional permeated area per vesicle (〈Ap〉/〈Av〉) obtained from the average permeability values for each probe size and membrane composition
PmCF(nm/s) Ap〉/〈AvCF(106) Pm3k-CB(nm/s) Ap〉/〈Av3k-CB(106) Pm10k-AF647(nm/s) Ap〉/〈Av10k-AF647 (106)
PC 46 ± 14 0.45 ± 0.14 17 ± 6 0.50 ± 0.16 8 ± 2 0.44 ± 0.08
PC/PS 59 ± 12 0.58 ± 0.12 29 ± 6 0.90 ± 0.20 23 ± 4 1.30 ± 0.20
PC/PE 466 ± 143 4.60 ± 1.40 207 ± 102 6.50 ± 3.40 158 ± 53 8.80 ± 2.90
PC/PE/PS 589 ± 142 5.80 ± 1.40 333 ± 73 10.40 ± 2.80 169 ± 52 9.40 ± 2.90

The errors represent the standard deviation of the observed GUV data set.

It should be noted that the observed permeability distributions (Fig. 6, b and d) are broad due to the fact that peptide-induced pores do not have well-defined structures, pore formation events are stochastic, and the membrane interfaces are fluid, giving rise to this wide distribution of individual permeability events when measured at the single vesicle level. Indeed, it has previously been reported that the initial pores that form during peptide-induced pore formation might be far from equilibrium and can, for example, relax to a smaller size over longer timescales as has been observed for the peptides Bax-α5 (23) and magainin 2 (30).

The permeability data was used to calculate the effective fractional permeable area of the membrane for each probe size using the expression (29)

Math Eq

where Ap is the permeable area of membrane on a GUV, Av is the total area of the vesicle, Pm is the permeability, and δ is the thickness of the membrane. The Stokes-Einstein diffusion constant of the leakage marker is D0 = kT/6πηR0, where kT is the thermal energy, η is the solvent viscosity, and R0 is the hydrodynamic radius of the fluorescent dye that was estimated with the relationR0 = 0.0332(Mw)0.463 in nanometers (31); Mw is the molecular weight of the dye. A brief derivation of this equation is presented in the Supporting Material. It should be noted that this equation is most accurate for the formation of large membrane pores as it assumes that the diffusion constant of the dye within the pore is the same as its diffusion constant in bulk solution. However, we believe this to be a reasonable assumption because these passive leakage markers will have a very short residence time within the pore itself due to the bilayer only being ∼5-nm thick; these solutes are not expected to interact strongly with the membrane itself.

Values of the fractional permeable areas are shown in Table 2. The fractional permeable areas were also found to be an order-of-magnitude greater for membrane compositions containing PE than for those that did not. Note that slightly larger permeable areas were measured for the larger leakage markers; these represent a later time point in the membrane disruption of GUVs by MP1 as the smaller leakage markers translocate the membrane at earlier times (Table 1). This extended delay time therefore allows for a greater area of membrane disruption to occur before the initiation of leakage to the larger Mw dyes.

Besides the order-of-magnitude increase in membrane permeabilization in the presence of PE lipids, we found an interesting correlation between PE content and membrane morphological response to MP1. Without PE, PC and PC/PS GUVs exhibited bright spots of fluorescent lipids at specific locations on the membrane surface in the presence of 4.0 μM MP1 (Fig. 7). We attribute these observations to local aggregation of peptides and lipids at the GUV surface. These peptide-induced lipid aggregates may be in competition with the pore-/defect-forming activity of the peptides. Such dense lipid structures were not seen on GUVs containing PE (PC/PE and PC/PE/PS) upon introduction of the peptide. Therefore, we speculate that the PE suppresses the intramembrane lipid aggregation by more easily facilitating the poration of the membrane.

large Image
Figure 7

Lipid aggregation is observed within the membranes of GUVs lacking in PE. Images of local lipid aggregation at the GUV surface (bright localized spots of fluorescence) seen after peptide addition (Cp = 4.0 μM). This effect is frequently observed in PC and PC/PS GUVs, but not for the lipid mixtures containing 10 mol % PE. To see this figure in color, go online.

While localized lipid aggregation was not observed on the surface of the PE-containing GUVs, these GUVs were observed to decrease in diameter by ∼10–15% over a period of ∼1 h after peptide addition (Fig. S6). Contrary to this, PC and PC/PS GUVs remained at a constant size for up to 2 h after addition of MP1. Therefore, MP1 results in the significant loss of lipid from only those GUVs that contain PE lipids.

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

Direct imaging of peptide-induced pores by AFM

AFM imaging of supported lipid bilayers confirms the role of PE in potentiating the formation of larger transmembrane pores. MP1 was added at 10 μM concentration to induce significant pore formation on the relatively small patches of membrane imaged by the AFM within a reasonable experimental timescale (<2 h); resultant pores/defects were observed to be much larger in PC/PE/PS membranes (250 ± 110 nm in diameter) compared to PC/PS (54 ± 30 nm in diameter) (Fig. 8). Similar-sized transmembrane pores were observed in PC/PE/PS and PC/PE membranes (290 ± 200 nm in diameter), but significantly fewer defects formed in PC/PE membranes. Note that the large standard deviations in these average pore diameters represent a significant size polydispersity in the defects formed. No pores were evident in PC membranes 2 h after peptide addition (Fig. S7); however, pores would need to be several nanometers in diameter to be observable by AFM, considerably larger than those that can be detected by passive dye influx into the GUVs we used to investigate the early stages of GUV poration.

Our AFM studies also clearly show a difference in pore formation and growth mechanisms dependent on the presence of PE. The large transmembrane pores in PC/PE/PS and PC/PE membranes are seen to grow by the stepwise loss of lipid aggregates from the edge of the pore, implying that vesicle micellization is important for pore growth in the these membranes (Fig. S8). This is consistent with the small decrease (within experimental error) in GUV size observed for PE-containing GUVs by phase contrast microscopy (Fig. S6). Conversely, in PC/PS membranes, raised areas of lipid are first seen to form on the membrane (Fig. S9), which may correlate to the dense lipid structures observed in Fig. 7. These raised areas of membrane later evolve into comparatively small pores; many of the defects seen in Fig. 8 (bottom left) only span half the bilayer, with only the center of a few of these defects showing full bilayer pores (Fig. S10). This indicates that pores in these membranes may form via a half-membrane intermediate state. Finally the timescale for observation of membrane defects by AFM was much faster for PC/PE/PS membranes than for other lipid mixtures, with defects observed almost immediately after peptide addition (Fig S7), compared with a few tens of minutes for other mixtures.

Discussion

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

Biophysical implications for MP1-lipid membrane interactions

We have shown a synergistic enhancement of the rate and extent of membrane permeabilization by MP1 peptides when PE and PS lipids are present in the lipid membrane. This picture is confirmed and corroborated by complementary experiments using three different model membrane systems: LUVs, GUVs, and planar-supported bilayers. We consider the perturbation of the membrane by MP1 peptides in two steps: 1) binding of the peptides to the membrane, and 2) perturbation of the bilayer structure by bound peptides to induce leakage.

Binding isotherms (Fig. 2) reveal that PS lipids cause a 7–8-fold increase in peptide bound to the membrane. This strongly outweighs the small ∼10% reduction in bound peptide concentration caused by the PE lipids. Therefore, we find that the dominant role of PS lipids’ contribution to the membrane disruption by MP1 is a large increase in peptide binding to the membrane.

The role of PE lipids in MP1-induced membrane disruption is twofold: 1) PE increases the susceptibility of the membrane to permeabilization by bound peptides, and 2) PE facilitates the formation of larger transmembrane pores. First, when the extent of GUV leakage is normalized to bound peptide concentration in the dose-response curves in Fig. 3, c and d, it can be seen that 4–5 times lower bound peptide concentration is required to induce a similar leakage response compared to comparable GUVs without PE lipids. Second, GUV and AFM experiments corroborate the effect of larger pores forming in the presence of PE. Quantitative analysis of GUV leakage profiles in Fig. 6 andTable 2 reveal that the presence of PE increases the permeability of membranes by an order of magnitude compared to membranes lacking in PE. Furthermore, once pores formed in GUVs, they quickly (within seconds) grew large enough in size to allow larger macromolecules (3 and 10 kDa) to permeate the membrane (Table 1); this compared to several tens of seconds for larger pores to form in GUVs lacking PE. Crucially, the formation of larger pores for PE-containing membranes is directly visualized by AFM (Fig. 8), where the observed pore diameters are ∼5 times larger in the presence of PE (and hence ∼20–30 times larger in average pore area, consistent with the order-of-magnitude increase in permeability reported for the GUVs).

The formation of transmembrane pores was confirmed by complementary experimental systems and techniques. Rapid translocation of membrane-impermeable leakage markers across GUV membranes, an all-or-none LUV fluorescence leakage assay, and direct visualization of transmembrane defects by AFM imaging of planar bilayers, all confirm this to be true. While these pores are fairly long lived, the membranes were sometimes observed to temporarily reseal, regaining their barrier properties. This can clearly be seen in the leakage profiles of individual GUVs in Figs. 5a, S4, and S5. GUV and planar bilayer imaging experiments also strongly suggest differences in the mechanism of pore formation depending on whether PE lipids are present. Images of GUVs that did not contain PE lipids often exhibited bright spots of increased local lipid concentrations on the membrane, which we interpret to be local aggregation of peptides and lipid (Fig. 7). Similarly, AFM images showed locally raised regions of lipid scattered across the membrane for these lipid compositions (Fig. S9) before the formation of pores (Fig. S10). This contrasted to the pore-formation mechanism observed in the presence of PE, where local aggregates were not directly observed on the GUV surface and time-resolved AFM imaging showed pore growth to occur by the stepwise micellization and loss of lipid from the edge of the pores (Fig. S8).

Besides the increased binding due to PS and the increased membrane susceptibility and pore size due to PE, the synergistic enhancement of membrane disruption facilitated by these lipids can be observed in the kinetics of initial permeabilization events. GUV experiments showed that PC/PE/PS GUVs leaked a factor-of-two quicker than other membrane compositions (Table 1). This is again corroborated by the AFM studies where defects were observed in PC/PE/PS membranes almost immediately after peptide addition, whereas perturbations of other membrane compositions took a few 10 s of minutes to evolve. The complementary pore-promoting effects of PS on bound peptide concentrations and PE on membrane susceptibility far outweigh their slight inhibitory effects on each other’s roles (PE causes a slight reduction in binding affinity (Fig. 2) and PS causes a decrease in the membrane susceptibility to bound peptide (Fig. 3, c and d)). This is apparent from the effects of MP1 on GUVs, where PC/PE/PS membranes experience the greatest membrane perturbation for any given total peptide concentration (Fig. 3, a and b) and the larger number of pores observed on the membrane surface by AFM (Fig. 8). Therefore, our combined results provide a detailed mechanistic picture of the importance of increased PS and PE lipid concentrations in synergistically enhancing the membrane’s propensity for significant disruption of its barrier properties by MP1 peptides.

Variations in lipid composition are responsible for differences in membrane properties such as charge, fluidity, lateral pressure profiles, and mechanical moduli. Changes in these fundamental membrane properties directly affect their interactions with extraneous compounds, such as antimicrobial peptides. The cationic nature of the MP1 peptide is likely an important component in the initial step of peptide action, in which the peptide recognizes the target membrane due to electrostatic interactions and binds to it in a structured form, most of the time as a helix. Therefore, the inclusion of anionic PS lipids in these membranes increases these electrostatic interactions with the MP1 peptide (net charge = +2e). However, MP1-membrane interactions cannot be solely driven by electrostatics as these peptides were also found to disrupt zwitterionic PC and PC/PE membranes, likely through secondary hydrophobic initial binding interactions that lead to a significantly lower bound concentration of peptide compared to the anionic membranes.

Next, insertion of the peptide into the bilayer likely takes place due to the hydrophobic effect, where nonpolar MP1 residues insert into the bilayer core, and defects may then be opened within the membrane structure, leading to its disruption. Furthermore, taking account of the fact that MP1 is a short peptide (14 amino acids) and hence not long enough to form a bilayer-spanning barrel stave pore (9, 32), we anticipate that these pores will be disorganized toroidal structures formed by lipids and peptides, as described by many molecular-dynamics studies (33, 34). PE is known to significantly modulate the lateral pressure profile through membranes and thereby induce negative curvature stress in the bilayer. Negative curvature stress has been shown to enhance the formation of toroidal lipid pores within a membrane by stabilizing the curvature of these structures (35). Therefore, PE would be expected to favor the formation of pore-like defects in the membrane, consistent with the increase susceptibility of these membranes to MP1-induced poration and the order-of-magnitude increase in membrane permeability that we find for PE-containing membranes upon interaction with MP1 peptides.

Jump to Section
Introduction
Materials and Methods
  Materials
  Peptide synthesis and purification
  Mass spectrometry analysis
  GUV formation
  LUV preparation
  CD spectroscopy for binding isotherms
  Confocal microscopy
  Analysis of confocal images and movies
  ANTS/DPX requenching measurements
  AFM
  Phase contrast microscopy
Results
  PS lipids significantly enhance peptide binding to the membrane
  MP1 dose-response studies reveal that PE and PS lipids enhance membrane permeability at lower peptide concentrations
  Confirmation of the pore-formation hypothesis in lipid vesicles
  Synergistic enhancement of GUV leakage kinetics by PE and PS lipids
  PE lipids significantly enhance pore size and membrane permeability
  Direct imaging of peptide-induced pores by AFM
Discussion
  Biophysical implications for MP1-lipid membrane interactions
  Implications for the chemotherapeutic potential of MP1 peptides
Author Contributions
Supporting Material
References

Implications for the chemotherapeutic potential of MP1 peptides

The MP1 peptide has been shown to have selective inhibition against numerous cancer lines compared to healthy cells (2, 3). Such malignant cells are also known to have increased expression of PS and PE lipids on their outer plasma membrane (5, 6, 7). This study strongly correlates the enhanced tumor inhibitory effects of these peptides with this pathological change in plasma membrane lipid composition, where the upregulation of PS and PE lipids can synergistically enhance the membrane-permeabilizing activity of MP1. This membrane permeabilization is likely to be the primary mechanism of cancer cell death induced by these peptides.

This suggests that MP1 might be a candidate therapeutic for development of novel cancer therapies, or at least guide the development of novel lead compounds for treatment of these diseases. One challenge for the application of antimicrobial peptides in medicine is that they often do not show high enough selectivity to their target cells to result in a favorable therapeutic index for these compounds (36). However, MP1 does not exhibit hemolytic activity to rat erythrocytes but presents chemotaxis for polymorphonucleated leukocytes and potent antimicrobial action against Gram-positive and Gram-negative bacteria (12), suggesting it could have favorable selectivity. It may also be of interest to test MP1 in a combination therapy with other chemotherapeutics that have intracellular targets. The selectivity of the MP1 peptide to disrupt the membranes of cancer cells may act synergistically with these other drugs to significantly enhance the therapeutic potency. Therefore, the therapeutic potential of this and other membrane-active peptides within the field of oncology is worthy of further investigation.

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Obesity Variant Circuitry

Larry H. Bernstein, MD, FCAP, Curator

LPBI

2.2.17

2.2.17   Obesity Variant Circuitry, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair

FTO Obesity Variant Circuitry and Adipocyte Browning in Humans

Melina Claussnitzer,  Simon N. Dankel, Kyoung-Han Kim,  Gerald Quon,  Wouter Meuleman,  Christine Haugen,  Viktoria Glunk,  Isabel S. Sousa, et al.

N Engl J Med 2015; 373:895-907  Sept 3, 2015    DOI: http://dx.10.org1/056/NEJMoa1502214   http://www.nejm.org/doi/full/10.1056/NEJMoa1502214

BACKGROUND

Genomewide association studies can be used to identify disease-relevant genomic regions, but interpretation of the data is challenging. The FTO region harbors the strongest genetic association with obesity, yet the mechanistic basis of this association remains elusive.

Full Text of Background…

METHODS

We examined epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns, with the aim of dissecting the regulatory circuitry and mechanistic basis of the association between the FTO region and obesity. We validated our predictions with the use of directed perturbations in samples from patients and from mice and with endogenous CRISPR–Cas9 genome editing in samples from patients.

Full Text of Methods…

RESULTS

Our data indicate that the FTO allele associated with obesity represses mitochondrial thermogenesis in adipocyte precursor cells in a tissue-autonomous manner. The rs1421085 T-to-C single-nucleotide variant disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. This results in a cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5, as well as an increase in lipid storage. Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite. Knockdown of IRX3 or IRX5 in primary adipocytes from participants with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers. Repair of the ARID5B motif by CRISPR–Cas9 editing of rs1421085 in primary adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7.

Effect of the FTO Locus on IRX3 and IRX5 in Human Adipocyte Progenitor Cells

To identify the cell types in which the causal variant may act, we examined chromatin state maps15,16 of the FTO obesity region across 127 cell types. An unusually long enhancer (12.8 kb) in mesenchymal adipocyte progenitors indicated a major regulatory locus (Figure 1B; and Fig. S1A, S1B, and S1C in the Supplementary Appendix). Haplotype-specific enhancer assays showed activity in association with the risk haplotype that was 2.4 times as high as that associated with the nonrisk haplotype in human SGBS adipocytes (i.e., adipocytes derived from a patient with the Simpson–Golabi–Behmel syndrome), which indicated genetic control of enhancer activity (Figure 1C). Enhancers in brain cells and other cell types were considerably shorter than those in mesenchymal adipocyte progenitors and lacked allelic activity (Fig. S1C and S1D in the Supplementary Appendix).

Figure 1. Activation of a Superenhancer in Human Adipocyte Progenitors by the FTO Obesity Risk Haplotype.

http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2015/nejm_2015.373.issue-10/nejmoa1502214/20150828/images/small/nejmoa1502214_f1.gif

Panel A shows the genetic association with body-mass index (BMI) for all common FTO locus variants,14 including the reported single-nucleotide variant (SNV) rs1558902 (red diamond) and the predicted causal SNV rs1421085 (red square). Gray shading delineates consecutive 10-kb segments. CEU denotes a population of Utah residents with northern and western European ancestry, and LD linkage disequilibrium. Panel B shows chromatin state annotations for the locus across 127 reference epigenomes (rows) for cell and tissue types profiled by the Roadmap Epigenomics Project.15,16 For information on the colors used to denote chromatin states, see Figure S1A in the Supplementary Appendix. Vertical lines delineate the consecutive 10-kb segments shown in Panel A. ESC denotes embryonic stem cell, HSC hematopoietic stem cell, and iPSC induced pluripotent stem cell. Panel C shows human SGBS adipocyte enhancer activity, for 10-kb tiles, of the risk and nonrisk haplotypes with the use of relative luciferase expression. The boxes indicate means from seven triplicate experiments, and T bars indicate standard deviations.

To predict putative target genes, we examined large domains that had long-range three-dimensional chromatin interactions surrounding FTO and identified eight candidate genes (Figure 2A and 2B)

FIGURE 2   http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2015/nejm_2015.373.issue-10/nejmoa1502214/20150828/images/small/nejmoa1502214_f2.gif

Figure 2. Activation of IRX3 and IRX5 Expression in Human Adipocyte Progenitors by the FTO Obesity Risk Genotype.

Panel A shows gene annotations and LD with array tag variant rs9930506 in a 2.5-Mb window; LD is expressed as r2 values in the CEU population. Arrows indicate the direction of transcription of annotated genes in the locus. Panel B shows chromosome conformation capture (Hi-C) interactions contact probabilities in human IMR90 myofibroblasts,22 revealing a 2-Mb topologically associating domain, and LD mean r2 statistics for all SNV pairs at 40-kb resolution. Panel C shows box plots for expression levels, after 2 days of differentiation, in human adipose progenitors isolated from 20 risk-allele carriers and 18 nonrisk-allele carriers, evaluated by means of a quantitative polymerase-chain-reaction analysis for all genes in the 2.5-Mb locus. The horizontal line within each box represents the median, the top and bottom of each box indicate the 75th and 25th percentile, and I bars indicate the range.

Among them, the developmental regulators IRX3 and IRX5 had genotype-associated expression, which indicated long-range (1.2-Mb) genetic control in primary preadipocytes (Figure 2C). Genotype-associated expression was not observed in whole-adipose tissue, a finding consistent with previous reports23,24; this indicated that the effect was cell type–specific and restricted to preadipocytes, which represent a minority of cells in adipose tissue (Fig. S2A in the Supplementary Appendix).

Effect of the FTO Locus on Mitochondrial Thermogenesis and Lipid Storage

To identify the biologic processes affected by altered IRX3 and IRX5expression in adipocytes, we used genomewide expression patterns in brown adipocyte–containing perirenal adipose tissue from a separate cohort of 10 nongenotyped, healthy kidney donors to identify genes with expression that was positively or negatively correlated with IRX3 and IRX5 expression. Genes that are associated with mitochondrial functions were found to have a negative correlation with IRX3 and IRX5, and genes with FXR and RXR lipid-metabolism functions were found to have a positive correlation, which suggests thatIRX3 and IRX5 may play roles in energy dissipation and storage

Figure 3A

FIGURE 3   http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2015/nejm_2015.373.issue-10/nejmoa1502214/20150828/images/small/nejmoa1502214_f3.gif

Regulation of Obesity-Associated Cellular Phenotypes in Human Adipocytes by IRX3and IRX5., and Table S1 in the Supplementary Appendix). IRX3 and IRX5 had consistently higher mean expression in white adipose tissue from nine participants, as well as negative correlation with PGC1A and UCP1expression, as assessed with the use of interindividual expression patterns in perithyroid brown adipose tissue (Fig. S2B and S2C in the Supplementary Appendix); these findings indicated potential roles for IRX3 and IRX5 in the repression of thermogenesis.

To examine the trans-eQTL genetic control of energy balance by the FTOobesity locus, we used primary preadipocytes from risk-allele carriers and nonrisk-allele carriers to evaluate the genes with mitochondrial and FXR and RXR functions that had expression patterns most closely correlated with those of IRX3 and IRX5, as well as several known markers of energy-balance regulation (Fig. S2D and S2E in the Supplementary Appendix). As compared with nonrisk-allele carriers, risk-allele carriers had lower expression of mitochondrial, browning, and respiration genes and higher expression of lipid-storage markers, which indicated a shift from energy dissipation to energy storage.

These differences in expression were also reflected in the cellular signatures of obesity. Risk-allele carriers had increased adipocyte size, reduced mitochondrial DNA content, and a loss of UCP1 response to β-adrenergic stimulus or cold exposure (Figure 3B and 3C, and Fig. S2F in theSupplementary Appendix), as well as resistance to isoproterenol-mediated uncoupling, a decreased basal oxygen consumption rate, and a reduction in mitochondrial thermogenesis by a factor of 5 (Fig. S2G in the Supplementary Appendix); this indicated excessive accumulation of triglycerides, reduced mitochondrial oxidative capacity, reduced white adipocyte browning, and reduced thermogenesis.

Adipocyte-Autonomous Effects of IRX3 and IRX5 on Energy Balance

We next quantified the effect that manipulation of IRX3 and IRX5 expression had on thermogenesis in primary preadipocytes that were isolated from both risk-allele carriers and nonrisk-allele carriers. In preadipocytes from risk-allele carriers, IRX3 and IRX5 knockdown restored oxygen consumption and thermogenesis response to nonrisk levels, increased thermogenesis by a factor of 7 (Figure 3D), and restored UCP1 expression levels (Fig. S3A in the Supplementary Appendix). In preadipocytes from nonrisk-allele carriers, IRX3 and IRX5 overexpression reduced basal respiration and thermogenesis to risk-allele levels (with thermogenesis reduced by a factor of 8) (Figure 3D) and decreased the expression of UCP1, other regulators of mitochondrial function and thermogenesis (PGC1A, PGC1B, and PRDM16), and the β-adrenergic receptor (ADRB3), which also regulates UCP1-independent thermogenesis programs (Fig. S3B and S3C in the Supplementary Appendix). These manipulations had no significant effect on preadipocytes from participants with the reciprocal genotypes, which indicated that IRX3 and IRX5 levels recapitulate the effect that the FTO genetic variant has on thermogenesis.

http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2015/nejm_2015.373.issue-10/nejmoa1502214/20150828/images/small/nejmoa1502214_f4.gif

To examine the organism-level effects of the repression of Irx3 in adipose tissue, we used adipose Irx3 dominant-negative (aP2-Irx3DN) mice. These mice had pronounced antiobesity characteristics, including reduced body size, body weight, fat mass, white and brown fat depots, and adipocyte size (Fig. S4A through S4G in the Supplementary Appendix). These aP2-Irx3DN mice also had resistance to weight gain on a high-fat diet, increased energy expenditure both at night and during the day, and increased oxygen consumption both at room temperature (22°C) and in thermoneutral conditions (30°C), but they did not have significant differences from control mice in food intake or locomotor activity (Fig. S4A and S4H through S4L in the Supplementary Appendix). At the molecular and cellular levels, these mice had increased mitochondrial activity and thermogenesis marker expression, reduced lipid-storage marker expression in both white and brown fat compartments, and markedly smaller adipocytes than did control mice (Fig. S4M, S4N, and S4O in the Supplementary Appendix).

Figure 4. Disruption of a Conserved ARID5B Repressor Motif by Causal SNV rs1421085 in Humans.

Panel A shows disruption of an ARID5B repressor motif in the evolutionarily conserved motif module surrounding rs1421085. The sequences shown at the top of the panel indicate the frequencies of each nucleotide, with the size scaled to indicate the information content (measured as entropy) at each position. Panel B shows adapted phylogenetic module complexity analysis (PMCA)25 scores in the FTO region for all 82 noncoding SNPs in LD (r2≥0.8) with tag SNV rs1558902, which was identified in a genomewide association study26; rs1421085 had the maximal score. Chromatin state annotation is shown for Roadmap Epigenomics reference genome E025, which corresponds to adipose-derived mesenchymal stem cells; for information on the colors used to denote chromatin states, see Figure S1A in the Supplementary Appendix. Panel C shows increased endogenous expression of IRX3 and IRX5 on single-nucleotide T-to-C editing of rs1421085 in the nonrisk haplotype of a nonrisk-allele carrier, using CRISPR–Cas9 (five clonal expansions). CRISPR–Cas9 re-editing from the engineered C risk allele back to a T nonrisk allele with the use of an alternative single guide RNA restores low endogenous IRX3 and IRX5 gene expression. Panel D shows reduced expression of IRX3 and IRX5 on C-to-T editing of the risk allele in adipocyte progenitors from a risk-allele carrier. Knockdown of ARID5B increases IRX3 and IRX5 levels, as compared….

We next evaluated the tissue-autonomous versus brain-mediated roles of Irx3 by comparing the aP2-Irx3DN mice with hypothalamus dominant-negative Ins2-Irx3DN mice.19 The aP2-Irx3DN mice had a reduction in fat-mass ratio that was 3 times as great as that in Ins2-Irx3DN mice (a reduction of 57% vs. 19%), despite the fact that transgene expression in the hypothalamus was 3 times lower than that in Ins2-Irx3DN mice (Fig. S4P and S4Q in the Supplementary Appendix), which indicated that Irx3 has a hypothalamus-independent regulatory role in whole-body energy regulation. The phenotypic effects of Irx3 repression in aP2-Irx3DN mice were also stronger than those in whole-body Irx3 knockout mice, which suggested potential dominant repressor effects in adipocytes or other tissues, and were independent of Fto gene expression, which did not change (Fig. S4P and S4R in the Supplementary Appendix).

Our findings indicate that both Irx3 and Irx5 have cell-autonomous roles: manipulation of Irx3 andIrx5 led to energy-balance differences in three mouse cellular models, including mouse embryonic fibroblast–derived adipocytes, white 3T3-L1 preadipocytes, and β-adrenergic–stimulated beige ME3 preadipocytes (Fig. S5 in the Supplementary Appendix). In each case, our results indicated that Irx3 and Irx5 induced adipocyte lipid accumulation and repressed thermogenesis in a cell-autonomous way.

Determination of the Causal Variant and Disruption of Repression by ARID5B

To predict the causal variant, the disruption of which is necessary and sufficient to cause IRX3 andIRX5 dysregulation in human preadipocytes, we used phylogenetic module complexity analysis (PMCA)25

(Figure 4A 

FIGURE 4  http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2015/nejm_2015.373.issue-10/nejmoa1502214/20150828/images/small/nejmoa1502214_f4.gif

Disruption of a Conserved ARID5B Repressor Motif by Causal SNV rs1421085 in Humans., and Fig. S6A and S6B in the Supplementary Appendix). The highest PMCA score was found for the rs1421085 T-to-C SNV, which is in perfect linkage disequilibrium with the most significant reported SNV, rs1558902, across multiple populations (1000 Genomes Phase 1 data), a finding that is consistent with a potentially causal role.

To evaluate whether rs1421085 plays a causal role in enhancer activity, we introduced the C allele into the nonrisk haplotype in our luciferase reporter assay. The T-to-C single-nucleotide alteration increased enhancer activity levels for 10-kb and 1-kb segments centered on the variant, in both orientations and both upstream and downstream of the transcription start, which indicated a gain of enhancer activity in association with the rs1421085 risk allele (Fig. S6C and S6D in the Supplementary Appendix).

To evaluate the effect of the variant on regulator binding, we used electrophoretic mobility-shift assays (EMSAs) of adipocyte nuclear extract with probes for the risk allele and the nonrisk allele of rs1421085. We found binding for the nonrisk allele, T, which lacked enhancer activity, but no binding for the risk allele, C; this indicated that the increased enhancer activity associated with the risk allele is probably due to a loss of repressor binding rather than to a gain of activator binding (Fig. S6E in the Supplementary Appendix).

We examined disrupted motifs and regulator expression to identify potential upstream regulators. The T-to-C substitution disrupted conserved motifs for NKX6-3, LHX6, and the ARID family of regulators (Figure 4A). Among them, ARID5B had the highest expression in adipose tissue and adipocytes and was bound specifically to the nonrisk allele in EMSA competition experiments (Fig. S6E and S6F in the Supplementary Appendix). ARID5B is known to play both repressive and activating roles and was previously implicated in adipogenesis and lipid metabolism in mice.27,28. Among nonrisk-allele carriers, expression of ARID5B was negatively correlated with expression ofIRX3 and IRX5, a finding consistent with ARID5B having a repressive role. No correlation was found in risk-allele carriers, which indicates a loss of ARID5B regulation (Fig. S6G in the Supplementary Appendix).

To evaluate the causal role of ARID5B, we next examined the effects of its knockdown and overexpression on IRX3 and IRX5. ARID5B knockdown increased IRX3 and IRX5 expression in primary preadipocytes from nonrisk-allele carriers to risk-allele levels, which indicates a loss of repression, but it had no effect on preadipocytes from risk-allele carriers, which indicates epistasis with the obesity-risk haplotype (Fig. S6H in the Supplementary Appendix). Consistent with this finding, in SGBS enhancer assays, ARID5B knockdown increased the activity of preadipocytes with the nonrisk allele to risk-allele levels, which indicates a loss of repression, but had no effect on risk-allele constructs, indicating epistasis with the rs1421085 risk allele (Fig. S6I in the Supplementary Appendix). ARID5B overexpression further reduced IRX3 and IRX5 levels in nonrisk-allele carriers, which indicated that repression was strengthened, but had no significant effect on risk-allele carriers, a finding consistent with impaired ARID5B repression in association with the risk haplotype (Fig. S6J in the Supplementary Appendix).

We also evaluated the cellular effects of ARID5B-directed perturbations in primary preadipocytes from risk-allele carriers and nonrisk-allele carriers. In preadipocytes from nonrisk-allele carriers,ARID5B knockdown reduced basal oxygen consumption and lipolysis (Fig. S6K and S6L in theSupplementary Appendix) and shifted expression patterns from mitochondrial to lipid markers (Fig. S2E in the Supplementary Appendix), which indicated that ARID5B plays causal roles in energy-balance regulation. In contrast, ARID5B knockdown had no effect on preadipocytes from risk-allele carriers, a finding consistent with a loss of ARID5B control.

These results suggest that the FTO obesity variant acts through disruption of ARID5B binding in the risk haplotype, leading to a loss of repression, a gain of enhancer activity, and increases inIRX3 and IRX5 expression (Fig. S6M in the Supplementary Appendix).

C-to-T Editing of the rs1421085 Risk Variant and the Effect on Thermogenesis

Targeted genome editing technology involving CRISPR–Cas929 makes it possible to test the phenotypic effect of altering the predicted causal nucleotide rs1421085 in its endogenous genomic context, in isolation from the other obesity-associated genetic variants in the same haplotype. We used CRISPR–Cas9 in primary preadipocytes with two separate guide RNAs, one for rs1421085 C-to-T rescue of the ARID5B motif disruption in risk-allele carriers and one for rs1421085 T-to-C disruption of the ARID5B motif in nonrisk-allele carriers.

We first evaluated the effect of rs1421085 editing on IRX3 and IRX5 expression levels. Starting from preadipocytes of a nonrisk-allele carrier, T-to-C editing doubled endogenous IRX3 and IRX5expression, to levels seen in risk-allele carriers; starting from the edited preadipocytes, C-to-T re-editing back to the nonrisk allele restored low expression levels (Figure 4C). Starting from the risk haplotype, C-to-T editing reduced IRX3 and IRX5 to nonrisk-allele levels, but only in the presence of ARID5B (Figure 4D); this established that disruption of ARID5B repression by rs1421085 is the mechanistic basis of the IRX3 and IRX5 dysregulatory event that mediates the effects of the FTOlocus on obesity.

Next, we evaluated the role of rs1421085 editing during differentiation of white and beige adipocytes, by studying differences in expression between edited and unedited preadipocytes during differentiation. Unedited adipocytes from a risk-allele carrier had a peak in IRX3 and IRX5expression during days 0 and 2 of preadipocyte differentiation into adipocytes; expression during early differentiation was reduced to nonrisk-allele levels by rs1421085 editing, which indicated a causal role of rs1421085 in developmental gene expression programs.

(Figure 5A

FIGURE 5 http://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/2015/nejm_2015.373.issue-10/nejmoa1502214/20150828/images/small/nejmoa1502214_f5.gif

Rescue of Metabolic Effects on Adipocyte Thermogenesis through Editing of SNV rs1421085 in a Risk-Allele Carrier. The causal role of rs1421085 was further reflected in a significant increase in the expression of thermogenesis regulators (ADRB3, DIO2, PGC1A, and UCP1) and mitochondrial markers (NDUFA10, COX7A, and CPT1) in differentiating preadipocytes (Figure 5B), which indicated that C-to-T editing of the risk allele rescued thermogenesis regulatory programs.

Last, we evaluated the role of rs1421085 editing in cellular signatures of obesity by quantifying phenotypic differences between edited and unedited adipocytes. A causal role in the regulation of energy balance was indicated by the fact that C-to-T rescue of rs1421085 in edited adipocytes resulted in a reduction in gene expression for lipid storage and lipolytic markers (Fig. S2E and S8A in the Supplementary Appendix), an increase by a factor of 4 in basal metabolic rate and β-adrenergic oxygen consumption, and an increase by a factor of 7 in thermogenesis (Figure 5C, and Fig. S7B in the Supplementary Appendix). In particular, rescue of the ARID5B motif in C-to-T edited preadipocytes restored the strong dependence of mitochondrial respiration on ARID5B that is seen in nonrisk-allele carriers (Fig. S7C in the Supplementary Appendix).

These results indicate that the rs1421085 T-to-C single-nucleotide alteration underlies the association between FTO and obesity by disrupting ARID5B-mediated repression of IRX3 andIRX5. This disruption leads to a developmental shift from browning to whitening programs and loss of mitochondrial thermogenesis (Figure 5D).

DISCUSSION

Our work elucidates a potential mechanistic basis for the genetic association between FTO and obesity and indicates that the causal variant rs1421085 can disrupt ARID5B repressor binding; this disruption results in derepression of IRX3 and IRX5 during early adipocyte differentiation. This process could lead to a cell-autonomous shift from white adipocyte browning and thermogenesis to lipid storage, increased fat stores, and body-weight gain.

To translate the results of genomewide association studies into mechanistic insights, we combined public resources (epigenomic annotations, chromosome conformation, and regulatory motif conservation), targeted experiments for risk and nonrisk haplotypes (enhancer tiling, gene expression, and cellular profiling), and directed perturbations in human primary cells and mouse models (regulator–target knockdown and overexpression and CRISPR–Cas9 genome editing). These methods are specific to the elucidation of noncoding variants, which constitute the majority of signals in genomewide association studies; 80% of the trait-associated loci identified in such studies lack protein-altering variants, and 93% of the top hits are noncoding.30

The FTO association with obesity is unusual in many ways. First, rs1421085 has both a high frequency and a strong effect size,31 which suggests positive selection or bottlenecks (e.g., 44% frequency in European populations vs. 5% in African populations). Second, rs1421085 has switchlike behavior in enhancer activity, target-gene expression, and cellular phenotypes, possibly because of selective pressures on energy-balance control for rapid adaptation. Third, rs1421085 acts specifically in the early differentiation of preadipocytes, which emphasizes the importance of profiling diverse tissues, cell types, and developmental stages. Fourth, enhancer activity is found only for the risk allele, which emphasizes the importance of profiling both alleles. Finally, rs1421085 leads to a gain of function (increased enhancer, IRX3, and IRX5 activity); this is a rare property in protein-coding variants but may be common in noncoding variants.

The apparent genetic link between obesity and cell-autonomous adipocyte browning suggests a central role of beige adipocyte thermogenesis in whole-body energy metabolism in humans, a role that is consistent with that suggested in recent reports on PRDM16 in mice.9 IRX3 and IRX5 have evolutionarily conserved roles, and the ARID5B motif lies in a module that is functionally conserved across multiple mammalian species; this indicates that adaptive thermogenesis circuits are conserved, and IRX3 and IRX5 probably play both UCP1-dependent and UCP1-independent roles. Even though IRX3 and IRX5 dysregulation by rs1421085 was restricted to early differentiation, their effects persisted in mature adipocytes, and the targeting of these genes can have broader effects.

Last, we found that direct manipulation of the ARID5B–rs1421085–IRX3/IRX5 regulatory axis in primary cell cultures of adipocytes from patients reversed the signatures of obesity. This indicates that in addition to changes in physical activity and nutrition, manipulation of mitochondrial thermogenesis26 offers a potential third pathway for shifting between energy storage and expenditure in a brain-independent and tissue-autonomous way in humans.

In summary, our work elucidates a mechanistic basis for the strongest genetic association with obesity. Our results indicate that the SNV rs1421085 underlies the genetic association between theFTO locus and obesity. The SNV disrupts an evolutionarily conserved motif for the ARID5B repressor, which leads to loss of binding, derepression of a potent preadipocyte superenhancer, and activation of downstream targets IRX3 and IRX5 during early differentiation of mesenchymal progenitors into adipocyte subtypes. This results in a cell-autonomous shift from white adipocyte browning to lipid-storage gene expression programs and to repression of basal mitochondrial respiration, a decrease in thermogenesis in response to stimulus, and an increase in adipocyte size. Manipulation of the uncovered pathway, including knockdown or overexpression of the upstream regulator ARID5B, genome editing of the predicted causal variant rs1421085, and knockdown or overexpression of target genes IRX3 and IRX5, had a significant effect on obesity phenotypes.

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