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Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 as New Binding Partners

Curator: Stephen J. Williams, Ph.D.

The following paper in Cells describes the discovery of protein interactors of endoglin, which is recruited to membranes at the TGF-β receptor complex upon TGF-β signaling. Interesting a carbohydrate binding protein, galectin-3, and an E3-ligase, TRIM21, were found to be unique interactors within this complex.

Gallardo-Vara E, Ruiz-Llorente L, Casado-Vela J, Ruiz-Rodríguez MJ, López-Andrés N, Pattnaik AK, Quintanilla M, Bernabeu C. Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 as New Binding Partners. Cells. 2019 Sep 13;8(9):1082. doi: 10.3390/cells8091082. PMID: 31540324; PMCID: PMC6769930.

Abstract

Endoglin is a 180-kDa glycoprotein receptor primarily expressed by the vascular endothelium and involved in cardiovascular disease and cancer. Heterozygous mutations in the endoglin gene (ENG) cause hereditary hemorrhagic telangiectasia type 1, a vascular disease that presents with nasal and gastrointestinal bleeding, skin and mucosa telangiectases, and arteriovenous malformations in internal organs. A circulating form of endoglin (alias soluble endoglin, sEng), proteolytically released from the membrane-bound protein, has been observed in several inflammation-related pathological conditions and appears to contribute to endothelial dysfunction and cancer development through unknown mechanisms. Membrane-bound endoglin is an auxiliary component of the TGF-β receptor complex and the extracellular region of endoglin has been shown to interact with types I and II TGF-β receptors, as well as with BMP9 and BMP10 ligands, both members of the TGF-β family. To search for novel protein interactors, we screened a microarray containing over 9000 unique human proteins using recombinant sEng as bait. We find that sEng binds with high affinity, at least, to 22 new proteins. Among these, we validated the interaction of endoglin with galectin-3, a secreted member of the lectin family with capacity to bind membrane glycoproteins, and with tripartite motif-containing protein 21 (TRIM21), an E3 ubiquitin-protein ligase. Using human endothelial cells and Chinese hamster ovary cells, we showed that endoglin co-immunoprecipitates and co-localizes with galectin-3 or TRIM21. These results open new research avenues on endoglin function and regulation.

Source: https://www.mdpi.com/2073-4409/8/9/1082/htm

Endoglin is an auxiliary TGF-β co-receptor predominantly expressed in endothelial cells, which is involved in vascular development, repair, homeostasis, and disease [1,2,3,4]. Heterozygous mutations in the human ENDOGLIN gene (ENG) cause hereditary hemorrhagic telangiectasia (HHT) type 1, a vascular disease associated with nasal and gastrointestinal bleeds, telangiectases on skin and mucosa and arteriovenous malformations in the lung, liver, and brain [4,5,6]. The key role of endoglin in the vasculature is also illustrated by the fact that endoglin-KO mice die in utero due to defects in the vascular system [7]. Endoglin expression is markedly upregulated in proliferating endothelial cells involved in active angiogenesis, including the solid tumor neovasculature [8,9]. For this reason, endoglin has become a promising target for the antiangiogenic treatment of cancer [10,11,12]. Endoglin is also expressed in cancer cells where it can behave as both a tumor suppressor in prostate, breast, esophageal, and skin carcinomas [13,14,15,16] and a promoter of malignancy in melanoma and Ewing’s sarcoma [17]. Ectodomain shedding of membrane-bound endoglin may lead to a circulating form of the protein, also known as soluble endoglin (sEng) [18,19,20]. Increased levels of sEng have been found in several vascular-related pathologies, including preeclampsia, a disease of high prevalence in pregnant women which, if left untreated, can lead to serious and even fatal complications for both mother and baby [2,18,19,21]. Interestingly, several lines of evidence support a pathogenic role of sEng in the vascular system, including endothelial dysfunction, antiangiogenic activity, increased vascular permeability, inflammation-associated leukocyte adhesion and transmigration, and hypertension [18,22,23,24,25,26,27]. Because of its key role in vascular pathology, a large number of studies have addressed the structure and function of endoglin at the molecular level, in order to better understand its mechanism of action.

 Galectin-3 Interacts with Endoglin in Cells

Galectin-3 is a secreted member of the lectin family with the capacity to bind membrane glycoproteins like endoglin and is involved in the pathogenesis of many human diseases [52]. We confirmed the protein screen data for galectin-3, as evidenced by two-way co-immunoprecipitation of endoglin and galectin-3 upon co-transfection in CHO-K1 cells. As shown in Figure 1A, galectin-3 and endoglin were efficiently transfected, as demonstrated by Western blot analysis in total cell extracts. No background levels of endoglin were observed in control cells transfected with the empty vector (Ø). By contrast, galectin-3 could be detected in all samples but, as expected, showed an increased signal in cells transfected with the galectin-3 expression vector. Co-immunoprecipitation studies of these cell lysates showed that galectin-3 was present in endoglin immunoprecipitates (Figure 1B). Conversely, endoglin was also detected in galectin-3 immunoprecipitates (Figure 1C).

Cells 08 01082 g001 550

Figure 1. Protein–protein association between galectin-3 and endoglin. (AC). Co-immunoprecipitation of galectin-3 and endoglin. CHO-K1 cells were transiently transfected with pcEXV-Ø (Ø), pcEXV–HA–EngFL (Eng) and pcDNA3.1–Gal-3 (Gal3) expression vectors. (A) Total cell lysates (TCL) were analyzed by SDS-PAGE under reducing conditions, followed by Western blot (WB) analysis using specific antibodies to endoglin, galectin-3 and β-actin (loading control). Cell lysates were subjected to immunoprecipitation (IP) with anti-endoglin (B) or anti-galectin-3 (C) antibodies, followed by SDS-PAGE under reducing conditions and WB analysis with anti-endoglin or anti-galectin-3 antibodies, as indicated. Negative controls with an IgG2b (B) and IgG1 (C) were included. (D) Protein-protein interactions between galectin-3 and endoglin using Bio-layer interferometry (BLItz). The Ni–NTA biosensors tips were loaded with 7.3 µM recombinant human galectin-3/6xHis at the C-terminus (LGALS3), and protein binding was measured against 0.1% BSA in PBS (negative control) or 4.1 µM soluble endoglin (sEng). Kinetic sensorgrams were obtained using a single channel ForteBioBLItzTM instrument.

Cells 08 01082 g002 550

Figure 2.Galectin-3 and endoglin co-localize in human endothelial cells. Human umbilical vein-derived endothelial cell (HUVEC) monolayers were fixed with paraformaldehyde, permeabilized with Triton X-100, incubated with the mouse mAb P4A4 anti-endoglin, washed, and incubated with a rabbit polyclonal anti-galectin-3 antibody (PA5-34819). Galectin-3 and endoglin were detected by immunofluorescence upon incubation with Alexa 647 goat anti-rabbit IgG (red staining) and Alexa 488 goat anti-mouse IgG (green staining) secondary antibodies, respectively. (A) Single staining of galectin-3 (red) and endoglin (green) at the indicated magnifications. (B) Merge images plus DAPI (nuclear staining in blue) show co-localization of galectin-3 and endoglin (yellow color). Representative images of five different experiments are shown.

Endoglin associates with the cullin-type E3 ligase TRIM21
Cells 08 01082 g003 550

Figure 3.Protein–protein association between TRIM21 and endoglin. (AE) Co-immunoprecipitation of TRIM21 and endoglin. A,B. HUVEC monolayers were lysed and total cell lysates (TCL) were subjected to SDS-PAGE under reducing (for TRIM21 detection) or nonreducing (for endoglin detection) conditions, followed by Western blot (WB) analysis using antibodies to endoglin, TRIM21 or β-actin (A). HUVECs lysates were subjected to immunoprecipitation (IP) with anti-TRIM21 or negative control antibodies, followed by WB analysis with anti-endoglin (B). C,D. CHO-K1 cells were transiently transfected with pDisplay–HA–Mock (Ø), pDisplay–HA–EngFL (E) or pcDNA3.1–HA–hTRIM21 (T) expression vectors, as indicated. Total cell lysates (TCL) were subjected to SDS-PAGE under nonreducing conditions and WB analysis using specific antibodies to endoglin, TRIM21, and β-actin (C). Cell lysates were subjected to immunoprecipitation (IP) with anti-TRIM21 or anti-endoglin antibodies, followed by SDS-PAGE under reducing (upper panel) or nonreducing (lower panel) conditions and WB analysis with anti-TRIM21 or anti-endoglin antibodies. Negative controls of appropriate IgG were included (D). E. CHO-K1 cells were transiently transfected with pcDNA3.1–HA–hTRIM21 and pDisplay–HA–Mock (Ø), pDisplay–HA–EngFL (FL; full-length), pDisplay–HA–EngEC (EC; cytoplasmic-less) or pDisplay–HA–EngTMEC (TMEC; cytoplasmic-less) expression vectors, as indicated. Cell lysates were subjected to immunoprecipitation with anti-TRIM21, followed by SDS-PAGE under reducing conditions and WB analysis with anti-endoglin antibodies, as indicated. The asterisk indicates the presence of a nonspecific band. Mr, molecular reference; Eng, endoglin; TRIM, TRIM21. (F) Protein–protein interactions between TRIM21 and endoglin using Bio-layer interferometry (BLItz). The Ni–NTA biosensors tips were loaded with 5.4 µM recombinant human TRIM21/6xHis at the N-terminus (R052), and protein binding was measured against 0.1% BSA in PBS (negative control) or 4.1 µM soluble endoglin (sEng). Kinetic sensorgrams were obtained using a single channel ForteBioBLItzTM instrument.

Table 1. Human protein-array analysis of endoglin interactors1.

Accession #Protein NameCellular Compartment
NM_172160.1Potassium voltage-gated channel, shaker-related subfamily, beta member 1 (KCNAB1), transcript variant 1Plasma membrane
Q14722
NM_138565.1Cortactin (CTTN), transcript variant 2Plasma membrane
Q14247
BC036123.1Stromal membrane-associated protein 1 (SMAP1)Plasma membrane
Q8IYB5
NM_173822.1Family with sequence similarity 126, member B (FAM126B)Plasma membrane, cytosol
Q8IXS8
BC047536.1Sciellin (SCEL)Plasma membrane, extracellular or secreted
O95171
BC068068.1Galectin-3Plasma membrane, mitochondrion, nucleus, extracellular or secreted
P17931
BC001247.1Actin-binding LIM protein 1 (ABLIM1)Cytoskeleton
O14639
NM_198943.1Family with sequence similarity 39, member B (FAM39B)Endosome, cytoskeleton
Q6VEQ5
NM_005898.4Cell cycle associated protein 1 (CAPRIN1), transcript variant 1Cytosol
Q14444
BC002559.1YTH domain family, member 2 (YTHDF2)Nucleus, cytosol
Q9Y5A9
NM_003141.2Tripartite motif-containing 21 (TRIM21)Nucleus, cytosol
P19474
BC025279.1Scaffold attachment factor B2 (SAFB2)Nucleus
Q14151
BC031650.1Putative E3 ubiquitin-protein ligase SH3RF2Nucleus
Q8TEC5
BC034488.2ATP-binding cassette, sub-family F (GCN20), member 1 (ABCF1)Nucleus
Q8NE71
BC040946.1Spliceosome-associated protein CWC15 homolog (HSPC148)Nucleus
Q9P013
NM_003609.2HIRA interacting protein 3 (HIRIP3)Nucleus
Q9BW71
NM_005572.1Lamin A/C (LMNA), transcript variant 2Nucleus
P02545
NM_006479.2RAD51 associated protein 1 (RAD51AP1)Nucleus
Q96B01
NM_014321.2Origin recognition complex, subunit 6 like (yeast) (ORC6L)Nucleus
Q9Y5N6
NM_015138.2RNA polymerase-associated protein RTF1 homolog (RTF1)Nucleus
Q92541
NM_032141.1Coiled-coil domain containing 55 (CCDC55), transcript variant 1Nucleus
Q9H0G5
BC012289.1Protein PRRC2B, KIAA0515Data not available
Q5JSZ5

1 Microarrays containing over 9000 unique human proteins were screened using recombinant sEng as a probe. Protein interactors showing the highest scores (Z-score ≥2.0) are listed. GeneBank (https://www.ncbi.nlm.nih.gov/genbank/) and UniProtKB (https://www.uniprot.org/help/uniprotkb) accession numbers are indicated with a yellow or green background, respectively. The cellular compartment of each protein was obtained from the UniProtKB webpage. Proteins selected for further studies (TRIM21 and galectin-3) are indicated in bold type with blue background.

Note: the following are from NCBI Genbank and Genecards on TRIM21

 From Genbank: https://www.ncbi.nlm.nih.gov/gene?Db=gene&Cmd=DetailsSearch&Term=6737

TRIM21 tripartite motif containing 21 [ Homo sapiens (human) ]

Gene ID: 6737, updated on 6-Sep-2022

Summary

Official Symbol TRIM21provided by HGNC Official Full Name tripartite motif containing 21provided by HGNC Primary source HGNC:HGNC:11312 See related Ensembl:ENSG00000132109MIM:109092;AllianceGenome:HGNC:11312 Gene type protein coding RefSeq status REVIEWED Organism Homo sapiens Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Primates; Haplorrhini; Catarrhini; Hominidae; Homo Also known as SSA; RO52; SSA1; RNF81; Ro/SSA Summary This gene encodes a member of the tripartite motif (TRIM) family. The TRIM motif includes three zinc-binding domains, a RING, a B-box type 1 and a B-box type 2, and a coiled-coil region. The encoded protein is part of the RoSSA ribonucleoprotein, which includes a single polypeptide and one of four small RNA molecules. The RoSSA particle localizes to both the cytoplasm and the nucleus. RoSSA interacts with autoantigens in patients with Sjogren syndrome and systemic lupus erythematosus. Alternatively spliced transcript variants for this gene have been described but the full-length nature of only one has been determined. [provided by RefSeq, Jul 2008] Expression Ubiquitous expression in spleen (RPKM 15.5), appendix (RPKM 13.2) and 24 other tissues See more Orthologs mouseall NEW Try the new Gene table
Try the new Transcript table

Genomic context

See TRIM21 in Genome Data Viewer Location:   11p15.4 Exon count:   7

Annotation releaseStatusAssemblyChrLocation
110currentGRCh38.p14 (GCF_000001405.40)11NC_000011.10 (4384897..4393702, complement)
110currentT2T-CHM13v2.0 (GCF_009914755.1)11NC_060935.1 (4449988..4458819, complement)
105.20220307previous assemblyGRCh37.p13 (GCF_000001405.25)11NC_000011.9 (4406127..4414932, complement)

Chromosome 11 – NC_000011.10Genomic Context describing neighboring genes

Bibliography

Related articles in PubMed

  1. TRIM21 inhibits the osteogenic differentiation of mesenchymal stem cells by facilitating K48 ubiquitination-mediated degradation of Akt.Xian J, et al. Exp Cell Res, 2022 Mar 15. PMID 35051432
  2. A Promising Intracellular Protein-Degradation Strategy: TRIMbody-Away Technique Based on Nanobody Fragment.Chen G, et al. Biomolecules, 2021 Oct 14. PMID 34680146, Free PMC Article
  3. Induced TRIM21 ISGylation by IFN-β enhances p62 ubiquitination to prevent its autophagosome targeting.Jin J, et al. Cell Death Dis, 2021 Jul 13. PMID 34257278, Free PMC Article
  4. TRIM21 Polymorphisms are associated with Susceptibility and Clinical Status of Oral Squamous Cell Carcinoma patients.Chuang CY, et al. Int J Med Sci, 2021. PMID 34220328, Free PMC Article
  5. TRIM21 inhibits porcine epidemic diarrhea virus proliferation by proteasomal degradation of the nucleocapsid protein.Wang H, et al. Arch Virol, 2021 Jul. PMID 33900472, Free PMC Article

From GeneCard:https://www.genecards.org/cgi-bin/carddisp.pl?gene=TRIM21

Entrez Gene Summary for TRIM21 Gene

  • This gene encodes a member of the tripartite motif (TRIM) family. The TRIM motif includes three zinc-binding domains, a RING, a B-box type 1 and a B-box type 2, and a coiled-coil region. The encoded protein is part of the RoSSA ribonucleoprotein, which includes a single polypeptide and one of four small RNA molecules. The RoSSA particle localizes to both the cytoplasm and the nucleus. RoSSA interacts with autoantigens in patients with Sjogren syndrome and systemic lupus erythematosus. Alternatively spliced transcript variants for this gene have been described but the full-length nature of only one has been determined. [provided by RefSeq, Jul 2008]

GeneCards Summary for TRIM21 Gene

TRIM21 (Tripartite Motif Containing 21) is a Protein Coding gene. Diseases associated with TRIM21 include Heart Block, Congenital and Sjogren Syndrome. Among its related pathways are Cytosolic sensors of pathogen-associated DNA and KEAP1-NFE2L2 pathway. Gene Ontology (GO) annotations related to this gene include identical protein binding and ligase activity. An important paralog of this gene is TRIM6.

UniProtKB/Swiss-Prot Summary for TRIM21 Gene

E3 ubiquitin-protein ligase whose activity is dependent on E2 enzymes, UBE2D1, UBE2D2, UBE2E1 and UBE2E2. Forms a ubiquitin ligase complex in cooperation with the E2 UBE2D2 that is used not only for the ubiquitination of USP4 and IKBKB but also for its self-ubiquitination. Component of cullin-RING-based SCF (SKP1-CUL1-F-box protein) E3 ubiquitin-protein ligase complexes such as SCF(SKP2)-like complexes. A TRIM21-containing SCF(SKP2)-like complex is shown to mediate ubiquitination of CDKN1B (‘Thr-187’ phosphorylated-form), thereby promoting its degradation by the proteasome. Monoubiquitinates IKBKB that will negatively regulates Tax-induced NF-kappa-B signaling. Negatively regulates IFN-beta production post-pathogen recognition by polyubiquitin-mediated degradation of IRF3. Mediates the ubiquitin-mediated proteasomal degradation of IgG1 heavy chain, which is linked to the VCP-mediated ER-associated degradation (ERAD) pathway. Promotes IRF8 ubiquitination, which enhanced the ability of IRF8 to stimulate cytokine genes transcription in macrophages. Plays a role in the regulation of the cell cycle progression. Enhances the decapping activity of DCP2. Exists as a ribonucleoprotein particle present in all mammalian cells studied and composed of a single polypeptide and one of four small RNA molecules. At least two isoforms are present in nucleated and red blood cells, and tissue specific differences in RO/SSA proteins have been identified. The common feature of these proteins is their ability to bind HY RNAs.2. Involved in the regulation of innate immunity and the inflammatory response in response to IFNG/IFN-gamma. Organizes autophagic machinery by serving as a platform for the assembly of ULK1, Beclin 1/BECN1 and ATG8 family members and recognizes specific autophagy targets, thus coordinating target recognition with assembly of the autophagic apparatus and initiation of autophagy. Acts as an autophagy receptor for the degradation of IRF3, hence attenuating type I interferon (IFN)-dependent immune responses (PubMed:26347139162978621631662716472766168805111802269418361920186413151884514219675099). Represses the innate antiviral response by facilitating the formation of the NMI-IFI35 complex through ‘Lys-63’-linked ubiquitination of NMI (PubMed:26342464). ( RO52_HUMAN,P19474 )

Molecular function for TRIM21 Gene according to UniProtKB/Swiss-Prot

Function:

  • E3 ubiquitin-protein ligase whose activity is dependent on E2 enzymes, UBE2D1, UBE2D2, UBE2E1 and UBE2E2.
    Forms a ubiquitin ligase complex in cooperation with the E2 UBE2D2 that is used not only for the ubiquitination of USP4 and IKBKB but also for its self-ubiquitination.
    Component of cullin-RING-based SCF (SKP1-CUL1-F-box protein) E3 ubiquitin-protein ligase complexes such as SCF(SKP2)-like complexes.
    A TRIM21-containing SCF(SKP2)-like complex is shown to mediate ubiquitination of CDKN1B (‘Thr-187’ phosphorylated-form), thereby promoting its degradation by the proteasome.
    Monoubiquitinates IKBKB that will negatively regulates Tax-induced NF-kappa-B signaling.
    Negatively regulates IFN-beta production post-pathogen recognition by polyubiquitin-mediated degradation of IRF3.
    Mediates the ubiquitin-mediated proteasomal degradation of IgG1 heavy chain, which is linked to the VCP-mediated ER-associated degradation (ERAD) pathway.
    Promotes IRF8 ubiquitination, which enhanced the ability of IRF8 to stimulate cytokine genes transcription in macrophages.
    Plays a role in the regulation of the cell cycle progression.

Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 as New Binding Partners

Gallardo-Vara E, Ruiz-Llorente L, Casado-Vela J, Ruiz-Rodríguez MJ, López-Andrés N, Pattnaik AK, Quintanilla M, Bernabeu C. Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 as New Binding Partners. Cells. 2019 Sep 13;8(9):1082. doi: 10.3390/cells8091082. PMID: 31540324; PMCID: PMC6769930.

Abstract

Endoglin is a 180-kDa glycoprotein receptor primarily expressed by the vascular endothelium and involved in cardiovascular disease and cancer. Heterozygous mutations in the endoglin gene (ENG) cause hereditary hemorrhagic telangiectasia type 1, a vascular disease that presents with nasal and gastrointestinal bleeding, skin and mucosa telangiectases, and arteriovenous malformations in internal organs. A circulating form of endoglin (alias soluble endoglin, sEng), proteolytically released from the membrane-bound protein, has been observed in several inflammation-related pathological conditions and appears to contribute to endothelial dysfunction and cancer development through unknown mechanisms. Membrane-bound endoglin is an auxiliary component of the TGF-β receptor complex and the extracellular region of endoglin has been shown to interact with types I and II TGF-β receptors, as well as with BMP9 and BMP10 ligands, both members of the TGF-β family. To search for novel protein interactors, we screened a microarray containing over 9000 unique human proteins using recombinant sEng as bait. We find that sEng binds with high affinity, at least, to 22 new proteins. Among these, we validated the interaction of endoglin with galectin-3, a secreted member of the lectin family with capacity to bind membrane glycoproteins, and with tripartite motif-containing protein 21 (TRIM21), an E3 ubiquitin-protein ligase. Using human endothelial cells and Chinese hamster ovary cells, we showed that endoglin co-immunoprecipitates and co-localizes with galectin-3 or TRIM21. These results open new research avenues on endoglin function and regulation.
 
 
Endoglin is an auxiliary TGF-β co-receptor predominantly expressed in endothelial cells, which is involved in vascular development, repair, homeostasis, and disease [1,2,3,4]. Heterozygous mutations in the human ENDOGLIN gene (ENG) cause hereditary hemorrhagic telangiectasia (HHT) type 1, a vascular disease associated with nasal and gastrointestinal bleeds, telangiectases on skin and mucosa and arteriovenous malformations in the lung, liver, and brain [4,5,6]. The key role of endoglin in the vasculature is also illustrated by the fact that endoglin-KO mice die in utero due to defects in the vascular system [7]. Endoglin expression is markedly upregulated in proliferating endothelial cells involved in active angiogenesis, including the solid tumor neovasculature [8,9]. For this reason, endoglin has become a promising target for the antiangiogenic treatment of cancer [10,11,12]. Endoglin is also expressed in cancer cells where it can behave as both a tumor suppressor in prostate, breast, esophageal, and skin carcinomas [13,14,15,16] and a promoter of malignancy in melanoma and Ewing’s sarcoma [17]. Ectodomain shedding of membrane-bound endoglin may lead to a circulating form of the protein, also known as soluble endoglin (sEng) [18,19,20]. Increased levels of sEng have been found in several vascular-related pathologies, including preeclampsia, a disease of high prevalence in pregnant women which, if left untreated, can lead to serious and even fatal complications for both mother and baby [2,18,19,21]. Interestingly, several lines of evidence support a pathogenic role of sEng in the vascular system, including endothelial dysfunction, antiangiogenic activity, increased vascular permeability, inflammation-associated leukocyte adhesion and transmigration, and hypertension [18,22,23,24,25,26,27]. Because of its key role in vascular pathology, a large number of studies have addressed the structure and function of endoglin at the molecular level, in order to better understand its mechanism of action.
 

 Galectin-3 Interacts with Endoglin in Cells

Galectin-3 is a secreted member of the lectin family with the capacity to bind membrane glycoproteins like endoglin and is involved in the pathogenesis of many human diseases [52]. We confirmed the protein screen data for galectin-3, as evidenced by two-way co-immunoprecipitation of endoglin and galectin-3 upon co-transfection in CHO-K1 cells. As shown in Figure 1A, galectin-3 and endoglin were efficiently transfected, as demonstrated by Western blot analysis in total cell extracts. No background levels of endoglin were observed in control cells transfected with the empty vector (Ø). By contrast, galectin-3 could be detected in all samples but, as expected, showed an increased signal in cells transfected with the galectin-3 expression vector. Co-immunoprecipitation studies of these cell lysates showed that galectin-3 was present in endoglin immunoprecipitates (Figure 1B). Conversely, endoglin was also detected in galectin-3 immunoprecipitates (Figure 1C).
Figure 1. Protein–protein association between galectin-3 and endoglin. (AC). Co-immunoprecipitation of galectin-3 and endoglin. CHO-K1 cells were transiently transfected with pcEXV-Ø (Ø), pcEXV–HA–EngFL (Eng) and pcDNA3.1–Gal-3 (Gal3) expression vectors. (A) Total cell lysates (TCL) were analyzed by SDS-PAGE under reducing conditions, followed by Western blot (WB) analysis using specific antibodies to endoglin, galectin-3 and β-actin (loading control). Cell lysates were subjected to immunoprecipitation (IP) with anti-endoglin (B) or anti-galectin-3 (C) antibodies, followed by SDS-PAGE under reducing conditions and WB analysis with anti-endoglin or anti-galectin-3 antibodies, as indicated. Negative controls with an IgG2b (B) and IgG1 (C) were included. (D) Protein-protein interactions between galectin-3 and endoglin using Bio-layer interferometry (BLItz). The Ni–NTA biosensors tips were loaded with 7.3 µM recombinant human galectin-3/6xHis at the C-terminus (LGALS3), and protein binding was measured against 0.1% BSA in PBS (negative control) or 4.1 µM soluble endoglin (sEng). Kinetic sensorgrams were obtained using a single channel ForteBioBLItzTM instrument.
Figure 2. Galectin-3 and endoglin co-localize in human endothelial cells. Human umbilical vein-derived endothelial cell (HUVEC) monolayers were fixed with paraformaldehyde, permeabilized with Triton X-100, incubated with the mouse mAb P4A4 anti-endoglin, washed, and incubated with a rabbit polyclonal anti-galectin-3 antibody (PA5-34819). Galectin-3 and endoglin were detected by immunofluorescence upon incubation with Alexa 647 goat anti-rabbit IgG (red staining) and Alexa 488 goat anti-mouse IgG (green staining) secondary antibodies, respectively. (A) Single staining of galectin-3 (red) and endoglin (green) at the indicated magnifications. (B) Merge images plus DAPI (nuclear staining in blue) show co-localization of galectin-3 and endoglin (yellow color). Representative images of five different experiments are shown.
  
Endoglin associates with the cullin-type E3 ligase TRIM21
 
Figure 3. Protein–protein association between TRIM21 and endoglin. (AE) Co-immunoprecipitation of TRIM21 and endoglin. A,B. HUVEC monolayers were lysed and total cell lysates (TCL) were subjected to SDS-PAGE under reducing (for TRIM21 detection) or nonreducing (for endoglin detection) conditions, followed by Western blot (WB) analysis using antibodies to endoglin, TRIM21 or β-actin (A). HUVECs lysates were subjected to immunoprecipitation (IP) with anti-TRIM21 or negative control antibodies, followed by WB analysis with anti-endoglin (B). C,D. CHO-K1 cells were transiently transfected with pDisplay–HA–Mock (Ø), pDisplay–HA–EngFL (E) or pcDNA3.1–HA–hTRIM21 (T) expression vectors, as indicated. Total cell lysates (TCL) were subjected to SDS-PAGE under nonreducing conditions and WB analysis using specific antibodies to endoglin, TRIM21, and β-actin (C). Cell lysates were subjected to immunoprecipitation (IP) with anti-TRIM21 or anti-endoglin antibodies, followed by SDS-PAGE under reducing (upper panel) or nonreducing (lower panel) conditions and WB analysis with anti-TRIM21 or anti-endoglin antibodies. Negative controls of appropriate IgG were included (D). E. CHO-K1 cells were transiently transfected with pcDNA3.1–HA–hTRIM21 and pDisplay–HA–Mock (Ø), pDisplay–HA–EngFL (FL; full-length), pDisplay–HA–EngEC (EC; cytoplasmic-less) or pDisplay–HA–EngTMEC (TMEC; cytoplasmic-less) expression vectors, as indicated. Cell lysates were subjected to immunoprecipitation with anti-TRIM21, followed by SDS-PAGE under reducing conditions and WB analysis with anti-endoglin antibodies, as indicated. The asterisk indicates the presence of a nonspecific band. Mr, molecular reference; Eng, endoglin; TRIM, TRIM21. (F) Protein–protein interactions between TRIM21 and endoglin using Bio-layer interferometry (BLItz). The Ni–NTA biosensors tips were loaded with 5.4 µM recombinant human TRIM21/6xHis at the N-terminus (R052), and protein binding was measured against 0.1% BSA in PBS (negative control) or 4.1 µM soluble endoglin (sEng). Kinetic sensorgrams were obtained using a single channel ForteBioBLItzTM instrument.
 
Table 1. Human protein-array analysis of endoglin interactors1.
Accession # Protein Name Cellular Compartment
NM_172160.1 Potassium voltage-gated channel, shaker-related subfamily, beta member 1 (KCNAB1), transcript variant 1 Plasma membrane
Q14722
NM_138565.1 Cortactin (CTTN), transcript variant 2 Plasma membrane
Q14247
BC036123.1 Stromal membrane-associated protein 1 (SMAP1) Plasma membrane
Q8IYB5
NM_173822.1 Family with sequence similarity 126, member B (FAM126B) Plasma membrane, cytosol
Q8IXS8
BC047536.1 Sciellin (SCEL) Plasma membrane, extracellular or secreted
O95171
BC068068.1 Galectin-3 Plasma membrane, mitochondrion, nucleus, extracellular or secreted
P17931
BC001247.1 Actin-binding LIM protein 1 (ABLIM1) Cytoskeleton
O14639
NM_198943.1 Family with sequence similarity 39, member B (FAM39B) Endosome, cytoskeleton
Q6VEQ5
NM_005898.4 Cell cycle associated protein 1 (CAPRIN1), transcript variant 1 Cytosol
Q14444
BC002559.1 YTH domain family, member 2 (YTHDF2) Nucleus, cytosol
Q9Y5A9
NM_003141.2 Tripartite motif-containing 21 (TRIM21) Nucleus, cytosol
P19474
BC025279.1 Scaffold attachment factor B2 (SAFB2) Nucleus
Q14151
BC031650.1 Putative E3 ubiquitin-protein ligase SH3RF2 Nucleus
Q8TEC5
BC034488.2 ATP-binding cassette, sub-family F (GCN20), member 1 (ABCF1) Nucleus
Q8NE71
BC040946.1 Spliceosome-associated protein CWC15 homolog (HSPC148) Nucleus
Q9P013
NM_003609.2 HIRA interacting protein 3 (HIRIP3) Nucleus
Q9BW71
NM_005572.1 Lamin A/C (LMNA), transcript variant 2 Nucleus
P02545
NM_006479.2 RAD51 associated protein 1 (RAD51AP1) Nucleus
Q96B01
NM_014321.2 Origin recognition complex, subunit 6 like (yeast) (ORC6L) Nucleus
Q9Y5N6
NM_015138.2 RNA polymerase-associated protein RTF1 homolog (RTF1) Nucleus
Q92541
NM_032141.1 Coiled-coil domain containing 55 (CCDC55), transcript variant 1 Nucleus
Q9H0G5
BC012289.1 Protein PRRC2B, KIAA0515 Data not available
Q5JSZ5
1 Microarrays containing over 9000 unique human proteins were screened using recombinant sEng as a probe. Protein interactors showing the highest scores (Z-score ≥2.0) are listed. GeneBank (https://www.ncbi.nlm.nih.gov/genbank/) and UniProtKB (https://www.uniprot.org/help/uniprotkb) accession numbers are indicated with a yellow or green background, respectively. The cellular compartment of each protein was obtained from the UniProtKB webpage. Proteins selected for further studies (TRIM21 and galectin-3) are indicated in bold type with blue background.
  

Note: the following are from NCBI Genbank and Genecards on TRIM21

TRIM21 tripartite motif containing 21 [ Homo sapiens (human) ]

Gene ID: 6737, updated on 6-Sep-2022

Summary
Official Symbol
TRIM21provided by HGNC
Official Full Name
tripartite motif containing 21provided by HGNC
Primary source
HGNC:HGNC:11312
See related
Ensembl:ENSG00000132109 MIM:109092; AllianceGenome:HGNC:11312
Gene type
protein coding
RefSeq status
REVIEWED
Organism
Homo sapiens
Lineage
Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Primates; Haplorrhini; Catarrhini; Hominidae; Homo
Also known as
SSA; RO52; SSA1; RNF81; Ro/SSA
Summary
This gene encodes a member of the tripartite motif (TRIM) family. The TRIM motif includes three zinc-binding domains, a RING, a B-box type 1 and a B-box type 2, and a coiled-coil region. The encoded protein is part of the RoSSA ribonucleoprotein, which includes a single polypeptide and one of four small RNA molecules. The RoSSA particle localizes to both the cytoplasm and the nucleus. RoSSA interacts with autoantigens in patients with Sjogren syndrome and systemic lupus erythematosus. Alternatively spliced transcript variants for this gene have been described but the full-length nature of only one has been determined. [provided by RefSeq, Jul 2008]
Expression
Ubiquitous expression in spleen (RPKM 15.5), appendix (RPKM 13.2) and 24 other tissues See more
Orthologs
NEW
Try the new Gene table
Try the new Transcript table
Genomic context
 
See TRIM21 in Genome Data Viewer
Location:
11p15.4
Exon count:
7
Annotation release Status Assembly Chr Location
110 current GRCh38.p14 (GCF_000001405.40) 11 NC_000011.10 (4384897..4393702, complement)
110 current T2T-CHM13v2.0 (GCF_009914755.1) 11 NC_060935.1 (4449988..4458819, complement)
105.20220307 previous assembly GRCh37.p13 (GCF_000001405.25) 11 NC_000011.9 (4406127..4414932, complement)

Chromosome 11 – NC_000011.10Genomic Context describing neighboring genes

Neighboring gene olfactory receptor family 52 subfamily B member 4 Neighboring gene olfactory receptor family 52 subfamily B member 3 pseudogene Neighboring gene olfactory receptor family 51 subfamily R member 1 pseudogene Neighboring gene olfactory receptor family 52 subfamily P member 2 pseudogene

 

Entrez Gene Summary for TRIM21 Gene

  • This gene encodes a member of the tripartite motif (TRIM) family. The TRIM motif includes three zinc-binding domains, a RING, a B-box type 1 and a B-box type 2, and a coiled-coil region. The encoded protein is part of the RoSSA ribonucleoprotein, which includes a single polypeptide and one of four small RNA molecules. The RoSSA particle localizes to both the cytoplasm and the nucleus. RoSSA interacts with autoantigens in patients with Sjogren syndrome and systemic lupus erythematosus. Alternatively spliced transcript variants for this gene have been described but the full-length nature of only one has been determined. [provided by RefSeq, Jul 2008]

GeneCards Summary for TRIM21 Gene

TRIM21 (Tripartite Motif Containing 21) is a Protein Coding gene. Diseases associated with TRIM21 include Heart Block, Congenital and Sjogren Syndrome. Among its related pathways are Cytosolic sensors of pathogen-associated DNA and KEAP1-NFE2L2 pathway. Gene Ontology (GO) annotations related to this gene include identical protein binding and ligase activity. An important paralog of this gene is TRIM6.

UniProtKB/Swiss-Prot Summary for TRIM21 Gene

E3 ubiquitin-protein ligase whose activity is dependent on E2 enzymes, UBE2D1, UBE2D2, UBE2E1 and UBE2E2. Forms a ubiquitin ligase complex in cooperation with the E2 UBE2D2 that is used not only for the ubiquitination of USP4 and IKBKB but also for its self-ubiquitination. Component of cullin-RING-based SCF (SKP1-CUL1-F-box protein) E3 ubiquitin-protein ligase complexes such as SCF(SKP2)-like complexes. A TRIM21-containing SCF(SKP2)-like complex is shown to mediate ubiquitination of CDKN1B (‘Thr-187’ phosphorylated-form), thereby promoting its degradation by the proteasome. Monoubiquitinates IKBKB that will negatively regulates Tax-induced NF-kappa-B signaling. Negatively regulates IFN-beta production post-pathogen recognition by polyubiquitin-mediated degradation of IRF3. Mediates the ubiquitin-mediated proteasomal degradation of IgG1 heavy chain, which is linked to the VCP-mediated ER-associated degradation (ERAD) pathway. Promotes IRF8 ubiquitination, which enhanced the ability of IRF8 to stimulate cytokine genes transcription in macrophages. Plays a role in the regulation of the cell cycle progression. Enhances the decapping activity of DCP2. Exists as a ribonucleoprotein particle present in all mammalian cells studied and composed of a single polypeptide and one of four small RNA molecules. At least two isoforms are present in nucleated and red blood cells, and tissue specific differences in RO/SSA proteins have been identified. The common feature of these proteins is their ability to bind HY RNAs.2. Involved in the regulation of innate immunity and the inflammatory response in response to IFNG/IFN-gamma. Organizes autophagic machinery by serving as a platform for the assembly of ULK1, Beclin 1/BECN1 and ATG8 family members and recognizes specific autophagy targets, thus coordinating target recognition with assembly of the autophagic apparatus and initiation of autophagy. Acts as an autophagy receptor for the degradation of IRF3, hence attenuating type I interferon (IFN)-dependent immune responses (PubMed:26347139162978621631662716472766168805111802269418361920186413151884514219675099). Represses the innate antiviral response by facilitating the formation of the NMI-IFI35 complex through ‘Lys-63’-linked ubiquitination of NMI (PubMed:26342464). ( RO52_HUMAN,P19474 )

Molecular function for TRIM21 Gene according to UniProtKB/Swiss-Prot

Function:
  • E3 ubiquitin-protein ligase whose activity is dependent on E2 enzymes, UBE2D1, UBE2D2, UBE2E1 and UBE2E2.
    Forms a ubiquitin ligase complex in cooperation with the E2 UBE2D2 that is used not only for the ubiquitination of USP4 and IKBKB but also for its self-ubiquitination.
    Component of cullin-RING-based SCF (SKP1-CUL1-F-box protein) E3 ubiquitin-protein ligase complexes such as SCF(SKP2)-like complexes.
    A TRIM21-containing SCF(SKP2)-like complex is shown to mediate ubiquitination of CDKN1B (‘Thr-187’ phosphorylated-form), thereby promoting its degradation by the proteasome.
    Monoubiquitinates IKBKB that will negatively regulates Tax-induced NF-kappa-B signaling.
    Negatively regulates IFN-beta production post-pathogen recognition by polyubiquitin-mediated degradation of IRF3.
    Mediates the ubiquitin-mediated proteasomal degradation of IgG1 heavy chain, which is linked to the VCP-mediated ER-associated degradation (ERAD) pathway.
    Promotes IRF8 ubiquitination, which enhanced the ability of IRF8 to stimulate cytokine genes transcription in macrophages.
    Plays a role in the regulation of the cell cycle progression.

Other Articles in this Open Access Scientific Journal on Galectins and Proteosome Include

Synthetic Biology Software for Drug Design in Glycobiology Internship

AI enabled Drug Discovery and Development: The Challenges and the Promise

Cell Death Pathway Insights

Ubiquitin researchers win Nobel

Read Full Post »

@MIT Artificial intelligence system rapidly predicts how two proteins will attach: The model called Equidock, focuses on rigid body docking — which occurs when two proteins attach by rotating or translating in 3D space, but their shapes don’t squeeze or bend

Reporter: Aviva Lev-Ari, PhD, RN

This paper introduces a novel SE(3) equivariant graph matching network, along with a keypoint discovery and alignment approach, for the problem of protein-protein docking, with a novel loss based on optimal transport. The overall consensus is that this is an impactful solution to an important problem, whereby competitive results are achieved without the need for templates, refinement, and are achieved with substantially faster run times.
28 Sept 2021 (modified: 18 Nov 2021)ICLR 2022 SpotlightReaders:  Everyone Show BibtexShow Revisions
 
Keywords:protein complexes, protein structure, rigid body docking, SE(3) equivariance, graph neural networks
AbstractProtein complex formation is a central problem in biology, being involved in most of the cell’s processes, and essential for applications such as drug design or protein engineering. We tackle rigid body protein-protein docking, i.e., computationally predicting the 3D structure of a protein-protein complex from the individual unbound structures, assuming no three-dimensional flexibility during binding. We design a novel pairwise-independent SE(3)-equivariant graph matching network to predict the rotation and translation to place one of the proteins at the right location and the right orientation relative to the second protein. We mathematically guarantee that the predicted complex is always identical regardless of the initial placements of the two structures, avoiding expensive data augmentation. Our model approximates the binding pocket and predicts the docking pose using keypoint matching and alignment through optimal transport and a differentiable Kabsch algorithm. Empirically, we achieve significant running time improvements over existing protein docking software and predict qualitatively plausible protein complex structures despite not using heavy sampling, structure refinement, or templates.
One-sentence SummaryWe perform rigid protein docking using a novel independent SE(3)-equivariant message passing mechanism that guarantees the same resulting protein complex independent of the initial placement of the two 3D structures.
 
SOURCE
 

MIT researchers created a machine-learning model that can directly predict the complex that will form when two proteins bind together. Their technique is between 80 and 500 times faster than state-of-the-art software methods, and often predicts protein structures that are closer to actual structures that have been observed experimentally.

This technique could help scientists better understand some biological processes that involve protein interactions, like DNA replication and repair; it could also speed up the process of developing new medicines.

Deep learning is very good at capturing interactions between different proteins that are otherwise difficult for chemists or biologists to write experimentally. Some of these interactions are very complicated, and people haven’t found good ways to express them. This deep-learning model can learn these types of interactions from data,” says Octavian-Eugen Ganea, a postdoc in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and co-lead author of the paper.

Ganea’s co-lead author is Xinyuan Huang, a graduate student at ETH Zurich. MIT co-authors include Regina Barzilay, the School of Engineering Distinguished Professor for AI and Health in CSAIL, and Tommi Jaakkola, the Thomas Siebel Professor of Electrical Engineering in CSAIL and a member of the Institute for Data, Systems, and Society. The research will be presented at the International Conference on Learning Representations.

Significance of the Scientific Development by the @MIT Team

EquiDock wide applicability:

  • Our method can be integrated end-to-end to boost the quality of other models (see above discussion on runtime importance). Examples are predicting functions of protein complexes [3] or their binding affinity [5], de novo generation of proteins binding to specific targets (e.g., antibodies [6]), modeling back-bone and side-chain flexibility [4], or devising methods for non-binary multimers. See the updated discussion in the “Conclusion” section of our paper.

 

Advantages over previous methods:

  • Our method does not rely on templates or heavy candidate sampling [7], aiming at the ambitious goal of predicting the complex pose directly. This should be interpreted in terms of generalization (to unseen structures) and scalability capabilities of docking models, as well as their applicability to various other tasks (discussed above).

 

  • Our method obtains a competitive quality without explicitly using previous geometric (e.g., 3D Zernike descriptors [8]) or chemical (e.g., hydrophilic information) features [3]. Future EquiDock extensions would find creative ways to leverage these different signals and, thus, obtain more improvements.

   

Novelty of theory:

  • Our work is the first to formalize the notion of pairwise independent SE(3)-equivariance. Previous work (e.g., [9,10]) has incorporated only single object Euclidean-equivariances into deep learning models. For tasks such as docking and binding of biological objects, it is crucial that models understand the concept of multi-independent Euclidean equivariances.

  • All propositions in Section 3 are our novel theoretical contributions.

  • We have rewritten the Contribution and Related Work sections to clarify this aspect.

   


Footnote [a]: We have fixed an important bug in the cross-attention code. We have done a more extensive hyperparameter search and understood that layer normalization is crucial in layers used in Eqs. 5 and 9, but not on the h embeddings as it was originally shown in Eq. 10. We have seen benefits from training our models with a longer patience in the early stopping criteria (30 epochs for DIPS and 150 epochs for DB5). Increasing the learning rate to 2e-4 is important to speed-up training. Using an intersection loss weight of 10 leads to improved results compared to the default of 1.

 

Bibliography:

[1] Protein-ligand blind docking using QuickVina-W with inter-process spatio-temporal integration, Hassan et al., 2017

[2] GNINA 1.0: molecular docking with deep learning, McNutt et al., 2021

[3] Protein-protein and domain-domain interactions, Kangueane and Nilofer, 2018

[4] Side-chain Packing Using SE(3)-Transformer, Jindal et al., 2022

[5] Contacts-based prediction of binding affinity in protein–protein complexes, Vangone et al., 2015

[6] Iterative refinement graph neural network for antibody sequence-structure co-design, Jin et al., 2021

[7] Hierarchical, rotation-equivariant neural networks to select structural models of protein complexes, Eismann et al, 2020

[8] Protein-protein docking using region-based 3D Zernike descriptors, Venkatraman et al., 2009

[9] SE(3)-transformers: 3D roto-translation equivariant attention networks, Fuchs et al, 2020

[10] E(n) equivariant graph neural networks, Satorras et al., 2021

[11] Fast end-to-end learning on protein surfaces, Sverrisson et al., 2020

SOURCE

https://openreview.net/forum?id=GQjaI9mLet

Read Full Post »

The Map of human proteins drawn by artificial intelligence and PROTAC (proteolysis targeting chimeras) Technology for Drug Discovery

Curators: Dr. Stephen J. Williams and Aviva Lev-Ari, PhD, RN

UPDATED on 11/5/2021

Introducing Isomorphic Labs

I believe we are on the cusp of an incredible new era of biological and medical research. Last year DeepMind’s breakthrough AI system AlphaFold2 was recognised as a solution to the 50-year-old grand challenge of protein folding, capable of predicting the 3D structure of a protein directly from its amino acid sequence to atomic-level accuracy. This has been a watershed moment for computational and AI methods for biology.
Building on this advance, today, I’m thrilled to announce the creation of a new Alphabet company –  Isomorphic Labs – a commercial venture with the mission to reimagine the entire drug discovery process from the ground up with an AI-first approach and, ultimately, to model and understand some of the fundamental mechanisms of life.

For over a decade DeepMind has been in the vanguard of advancing the state-of-the-art in AI, often using games as a proving ground for developing general purpose learning systems, like AlphaGo, our program that beat the world champion at the complex game of Go. We are at an exciting moment in history now where these techniques and methods are becoming powerful and sophisticated enough to be applied to real-world problems including scientific discovery itself. One of the most important applications of AI that I can think of is in the field of biological and medical research, and it is an area I have been passionate about addressing for many years. Now the time is right to push this forward at pace, and with the dedicated focus and resources that Isomorphic Labs will bring.

An AI-first approach to drug discovery and biology
The pandemic has brought to the fore the vital work that brilliant scientists and clinicians do every day to understand and combat disease. We believe that the foundational use of cutting edge computational and AI methods can help scientists take their work to the next level, and massively accelerate the drug discovery process. AI methods will increasingly be used not just for analysing data, but to also build powerful predictive and generative models of complex biological phenomena. AlphaFold2 is an important first proof point of this, but there is so much more to come. 
At its most fundamental level, I think biology can be thought of as an information processing system, albeit an extraordinarily complex and dynamic one. Taking this perspective implies there may be a common underlying structure between biology and information science – an isomorphic mapping between the two – hence the name of the company. Biology is likely far too complex and messy to ever be encapsulated as a simple set of neat mathematical equations. But just as mathematics turned out to be the right description language for physics, biology may turn out to be the perfect type of regime for the application of AI.

What’s next for Isomorphic Labs
This is just the beginning of what we hope will become a radical new approach to drug discovery, and I’m incredibly excited to get this ambitious new commercial venture off the ground and to partner with pharmaceutical and biomedical companies. I will serve as CEO for Isomorphic’s initial phase, while remaining as DeepMind CEO, partially to help facilitate collaboration between the two companies where relevant, and to set out the strategy, vision and culture of the new company. This will of course include the building of a world-class multidisciplinary team, with deep expertise in areas such as AI, biology, medicinal chemistry, biophysics, and engineering, brought together in a highly collaborative and innovative environment. (We are hiring!
As pioneers in the emerging field of ‘digital biology’, we look forward to helping usher in an amazingly productive new age of biomedical breakthroughs. Isomorphic’s mission could not be a more important one: to use AI to accelerate drug discovery, and ultimately, find cures for some of humanity’s most devastating diseases.

SOURCE

https://www.isomorphiclabs.com/blog

DeepMind creates ‘transformative’ map of human proteins drawn by artificial intelligence

DeepMind plans to release hundreds of millions of protein structures for free

James Vincent July 22, 2021 11:00 am

AI research lab DeepMind has created the most comprehensive map of human proteins to date using artificial intelligence. The company, a subsidiary of Google-parent Alphabet, is releasing the data for free, with some scientists comparing the potential impact of the work to that of the Human Genome Project, an international effort to map every human gene.

Proteins are long, complex molecules that perform numerous tasks in the body, from building tissue to fighting disease. Their purpose is dictated by their structure, which folds like origami into complex and irregular shapes. Understanding how a protein folds helps explain its function, which in turn helps scientists with a range of tasks — from pursuing fundamental research on how the body works, to designing new medicines and treatments.
 “the culmination of the entire 10-year-plus lifetime of DeepMind” 
Previously, determining the structure of a protein relied on expensive and time-consuming experiments. But last year DeepMind showed it can produce accurate predictions of a protein’s structure using AI software called AlphaFold. Now, the company is releasing hundreds of thousands of predictions made by the program to the public.
“I see this as the culmination of the entire 10-year-plus lifetime of DeepMind,” company CEO and co-founder Demis Hassabis told The Verge. “From the beginning, this is what we set out to do: to make breakthroughs in AI, test that on games like Go and Atari, [and] apply that to real-world problems, to see if we can accelerate scientific breakthroughs and use those to benefit humanity.”



Two examples of protein structures predicted by AlphaFold (in blue) compared with experimental results (in green). 
Image: DeepMind


There are currently around 180,000 protein structures available in the public domain, each produced by experimental methods and accessible through the Protein Data Bank. DeepMind is releasing predictions for the structure of some 350,000 proteins across 20 different organisms, including animals like mice and fruit flies, and bacteria like 
E. coli. (There is some overlap between DeepMind’s data and pre-existing protein structures, but exactly how much is difficult to quantify because of the nature of the models.) Most significantly, the release includes predictions for 98 percent of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. It isn’t the first public dataset of human proteins, but it is the most comprehensive and accurate.

If they want, scientists can download the entire human proteome for themselves, says AlphaFold’s technical lead John Jumper. “There is a HumanProteome.zip effectively, I think it’s about 50 gigabytes in size,” Jumper tells The Verge. “You can put it on a flash drive if you want, though it wouldn’t do you much good without a computer for analysis!”
 “anyone can use it for anything” 
After launching this first tranche of data, DeepMind plans to keep adding to the store of proteins, which will be maintained by Europe’s flagship life sciences lab, the European Molecular Biology Laboratory (EMBL). By the end of the year, DeepMind hopes to release predictions for 100 million protein structures, a dataset that will be “transformative for our understanding of how life works,” according to Edith Heard, director general of the EMBL.
The data will be free in perpetuity for both scientific and commercial researchers, says Hassabis. “Anyone can use it for anything,” the DeepMind CEO noted at a press briefing. “They just need to credit the people involved in the citation.”

The benefits of protein folding


Understanding a protein’s structure is useful for scientists across a range of fields. The information can help design new medicines, synthesize novel enzymes that break down waste materials, and create crops that are resistant to viruses or extreme weather. Already, DeepMind’s protein predictions are being used for medical research, including studying the workings of SARS-CoV-2, the virus that causes COVID-19.
 “it will definitely have a huge impact for the scientific community” 
New data will speed these efforts, but scientists note it will still take a lot of time to turn this information into real-world results. “I don’t think it’s going to be something that changes the way patients are treated within the year, but it will definitely have a huge impact for the scientific community,” Marcelo C. Sousa, a professor at the University of Colorado’s biochemistry department, told The Verge.
Scientists will have to get used to having such information at their fingertips, says DeepMind senior research scientist Kathryn Tunyasuvunakool. “As a biologist, I can confirm we have no playbook for looking at even 20,000 structures, so this [amount of data] is hugely unexpected,” Tunyasuvunakool told The Verge. “To be analyzing hundreds of thousands of structures — it’s crazy.”

Notably, though, DeepMind’s software produces predictions of protein structures rather than experimentally determined models, which means that in some cases further work will be needed to verify the structure. DeepMind says it spent a lot of time building accuracy metrics into its AlphaFold software, which ranks how confident it is for each prediction.

Example protein structures predicted by AlphaFold.
Image: DeepMind
Predictions of protein structures are still hugely useful, though. Determining a protein’s structure through experimental methods is expensive, time-consuming, and relies on a lot of trial and error. That means even a low-confidence prediction can save scientists years of work by pointing them in the right direction for research.
Helen Walden, a professor of structural biology at the University of Glasgow, tells The Verge that DeepMind’s data will “significantly ease” research bottlenecks, but that “the laborious, resource-draining work of doing the biochemistry and biological evaluation of, for example, drug functions” will remain.
Sousa, who has previously used data from AlphaFold in his work, says for scientists the impact will be felt immediately. “In our collaboration we had with DeepMind, we had a dataset with a protein sample we’d had for 10 years, and we’d never got to the point of developing a model that fit,” he says. “DeepMind agreed to provide us with a structure, and they were able to solve the problem in 15 minutes after we’d been sitting on it for 10 years.”

Why protein folding is so difficult

Proteins are constructed from chains of amino acids, which come in 20 different varieties in the human body. As any individual protein can be comprised of hundreds of individual amino acids, each of which can fold and twist in different directions, it means a molecule’s final structure has an incredibly large number of possible configurations. One estimate is that the typical protein can be folded in 10^300 ways — that’s a 1 followed by 300 zeroes.

 Protein folding has been a “grand challenge” of biology for decades 

Because proteins are too small to examine with microscopes, scientists have had to indirectly determine their structure using expensive and complicated methods like nuclear magnetic resonance and X-ray crystallography. The idea of determining the structure of a protein simply by reading a list of its constituent amino acids has been long theorized but difficult to achieve, leading many to describe it as a “grand challenge” of biology.
In recent years, though, computational methods — particularly those using artificial intelligence — have suggested such analysis is possible. With these techniques, AI systems are trained on datasets of known protein structures and use this information to create their own predictions.

DeepMind’s AlphaFold software has significantly increased the accuracy of computational protein-folding, as shown by its performance in the CASP competition. 
Image: DeepMind
Many groups have been working on this problem for years, but DeepMind’s deep bench of AI talent and access to computing resources allowed it to accelerate progress dramatically. Last year, the company competed in an international protein-folding competition known as CASP and blew away the competition. Its results were so accurate that computational biologist John Moult, one of CASP’s co-founders, said that “in some sense the problem [of protein folding] is solved.”

DeepMind’s AlphaFold program has been upgraded since last year’s CASP competition and is now 16 times faster. “We can fold an average protein in a matter of minutes, most cases seconds,” says Hassabis.

@@@@@@@

The company also released the underlying code for AlphaFold last week as open-source, allowing others to build on its work in the future.

@@@@@@@

Liam McGuffin, a professor at Reading University who developed some of the UK’s leading protein-folding software, praised the technical brilliance of AlphaFold, but also noted that the program’s success relied on decades of prior research and public data. “DeepMind has vast resources to keep this database up to date and they are better placed to do this than any single academic group,” McGuffin told The Verge. “I think academics would have got there in the end, but it would have been slower because we’re not as well resourced.”

Why does DeepMind care?

Many scientists The Verge spoke to noted the generosity of DeepMind in releasing this data for free. After all, the lab is owned by Google-parent Alphabet, which has been pouring huge amounts of resources into commercial healthcare projects. DeepMind itself loses a lot of money each year, and there have been numerous reports of tensions between the company and its parent firm over issues like research autonomy and commercial viability.

Hassabis, though, tells The Verge that the company always planned to make this information freely available, and that doing so is a fulfillment of DeepMind’s founding ethos. He stresses that DeepMind’s work is used in lots of places at Google — “almost anything you use, there’s some of our technology that’s part of that under the hood” — but that the company’s primary goal has always been fundamental research.
 “There’s many ways value can be attained.” 

“The agreement when we got acquired is that we are here primarily to advance the state of AGI and AI technologies and then use that to accelerate scientific breakthroughs,” says Hassabis. “[Alphabet] has plenty of divisions focused on making money,” he adds, noting that DeepMind’s focus on research “brings all sorts of benefits, in terms of prestige and goodwill for the scientific community. There’s many ways value can be attained.”
Hassabis predicts that AlphaFold is a sign of things to come — a project that shows the huge potential of artificial intelligence to handle messy problems like human biology.

“I think we’re at a really exciting moment,” he says. “In the next decade, we, and others in the AI field, are hoping to produce amazing breakthroughs that will genuinely accelerate solutions to the really big problems we have here on Earth.”


SOURCE

https://www.theverge.com/platform/amp/2021/7/22/22586578/deepmind-alphafold-ai-protein-folding-human-proteome-released-for-free?__twitter_impression=true

Potential Use of Protein Folding Predictions for Drug Discovery

PROTAC Technology: Opportunities and Challenges

  • Hongying Gao
  • Xiuyun Sun
  • Yu Rao*

Cite this: ACS Med. Chem. Lett. 2020, 11, 3, 237–240Publication Date:March 12, 2020https://doi.org/10.1021/acsmedchemlett.9b00597Copyright © 2020 American Chemical Society

Abstract

PROTACs-induced targeted protein degradation has emerged as a novel therapeutic strategy in drug development and attracted the favor of academic institutions, large pharmaceutical enterprises (e.g., AstraZeneca, Bayer, Novartis, Amgen, Pfizer, GlaxoSmithKline, Merck, and Boehringer Ingelheim, etc.), and biotechnology companies. PROTACs opened a new chapter for novel drug development. However, any new technology will face many new problems and challenges. Perspectives on the potential opportunities and challenges of PROTACs will contribute to the research and development of new protein degradation drugs and degrader tools.

Although PROTAC technology has a bright future in drug development, it also has many challenges as follows:
(1)
Until now, there is only one example of PROTAC reported for an “undruggable” target; (18) more cases are needed to prove the advantages of PROTAC in “undruggable” targets in the future.
(2)
“Molecular glue”, existing in nature, represents the mechanism of stabilized protein–protein interactions through small molecule modulators of E3 ligases. For instance, auxin, the plant hormone, binds to the ligase SCF-TIR1 to drive recruitment of Aux/IAA proteins and subsequently triggers its degradation. In addition, some small molecules that induce targeted protein degradation through “molecular glue” mode of action have been reported. (21,22) Furthermore, it has been recently reported that some PROTACs may actually achieve target protein degradation via a mechanism that includes “molecular glue” or via “molecular glue” alone. (23) How to distinguish between these two mechanisms and how to combine them to work together is one of the challenges for future research.
(3)
Since PROTAC acts in a catalytic mode, traditional methods cannot accurately evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) properties of PROTACs. Thus, more studies are urgently needed to establish PK and PD evaluation systems for PROTACs.
(4)
How to quickly and effectively screen for target protein ligands that can be used in PROTACs, especially those targeting protein–protein interactions, is another challenge.
(5)
How to understand the degradation activity, selectivity, and possible off-target effects (based on different targets, different cell lines, and different animal models) and how to rationally design PROTACs etc. are still unclear.
(6)
The human genome encodes more than 600 E3 ubiquitin ligases. However, there are only very few E3 ligases (VHL, CRBN, cIAPs, and MDM2) used in the design of PROTACs. How to expand E3 ubiquitin ligase scope is another challenge faced in this area.

PROTAC technology is rapidly developing, and with the joint efforts of the vast number of scientists in both academia and industry, these problems shall be solved in the near future.

PROTACs have opened a new chapter for the development of new drugs and novel chemical knockdown tools and brought unprecedented opportunities to the industry and academia, which are mainly reflected in the following aspects:
(1)
Overcoming drug resistance of cancer. In addition to traditional chemotherapy, kinase inhibitors have been developing rapidly in the past 20 years. (12) Although kinase inhibitors are very effective in cancer therapy, patients often develop drug resistance and disease recurrence, consequently. PROTACs showed greater advantages in drug resistant cancers through degrading the whole target protein. For example, ARCC-4 targeting androgen receptor could overcome enzalutamide-resistant prostate cancer (13) and L18I targeting BTK could overcome C481S mutation. (14)
(2)
Eliminating both the enzymatic and nonenzymatic functions of kinase. Traditional small molecule inhibitors usually inhibit the enzymatic activity of the target, while PROTACs affect not only the enzymatic activity of the protein but also nonenzymatic activity by degrading the entire protein. For example, FAK possesses the kinase dependent enzymatic functions and kinase independent scaffold functions, but regulating the kinase activity does not successfully inhibit all FAK function. In 2018, a highly effective and selective FAK PROTAC reported by Craig M. Crews’ group showed a far superior activity to clinical candidate drug in cell migration and invasion. (15) Therefore, PROTAC can expand the druggable space of the existing targets and regulate proteins that are difficult to control by traditional small molecule inhibitors.
(3)
Degrade the “undruggable” protein target. At present, only 20–25% of the known protein targets (include kinases, G protein-coupled receptors (GPCRs), nuclear hormone receptors, and iron channels) can be targeted by using conventional drug discovery technologies. (16,17) The proteins that lack catalytic activity and/or have catalytic independent functions are still regarded as “undruggable” targets. The involvement of Signal Transducer and Activator of Transcription 3 (STAT3) in the multiple signaling pathway makes it an attractive therapeutic target; however, the lack of an obviously druggable site on the surface of STAT3 limited the development of STAT3 inhibitors. Thus, there are still no effective drugs directly targeting STAT3 approved by the Food and Drug Administration (FDA). In November 2019, Shaomeng Wang’s group first reported a potent PROTAC targeting STAT3 with potent biological activities in vitro and in vivo. (18) This successful case confirms the key potential of PROTAC technology, especially in the field of “undruggable” targets, such as K-Ras, a tricky tumor target activated by multiple mutations as G12A, G12C, G12D, G12S, G12 V, G13C, and G13D in the clinic. (19)
(4)
Fast and reversible chemical knockdown strategy in vivo. Traditional genetic protein knockout technologies, zinc-finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), or CRISPR-Cas9, usually have a long cycle, irreversible mode of action, and high cost, which brings a lot of inconvenience for research, especially in nonhuman primates. In addition, these genetic animal models sometimes produce phenotypic misunderstanding due to potential gene compensation or gene mutation. More importantly, the traditional genetic method cannot be used to study the function of embryonic-lethal genes in vivo. Unlike DNA-based protein knockout technology, PROTACs knock down target proteins directly, rather than acting at the genome level, and are suitable for the functional study of embryonic-lethal proteins in adult organisms. In addition, PROTACs provide exquisite temporal control, allowing the knockdown of a target protein at specific time points and enabling the recovery of the target protein after withdrawal of drug treatment. As a new, rapid and reversible chemical knockdown method, PROTAC can be used as an effective supplement to the existing genetic tools. (20)

SOURCE

PROTAC Technology: Opportunities and Challenges
  • Hongying Gao
  • Xiuyun Sun
  • Yu Rao*

Cite this: ACS Med. Chem. Lett. 2020, 11, 3, 237–240

Goal in Drug Design: Eliminating both the enzymatic and nonenzymatic functions of kinase.

Work-in-Progress

Induction and Inhibition of Protein in Galectins Drug Design

Work-in-Progress

Screening Proteins in DeepMind’s AlphaFold DataBase

The company also released the underlying code for AlphaFold last week as open-source, allowing others to build on its work in the future.

Work-in-Progress

Other related research published in this Open Access Online Journal include the following:

Synthetic Biology in Drug Discovery

Peroxisome proliferator-activated receptor (PPAR-gamma) Receptors Activation: PPARγ transrepression  for Angiogenesis in Cardiovascular Disease and PPARγ transactivation for Treatment of Diabetes

Read Full Post »

New avenues for research in membrane biology reveals the mobility of protein at work

Curator and Reporter: Dr. Premalata Pati, Ph.D., Postdoc

Membrane proteins (MPs) are proteins that exist in the plasma membrane and conduct a variety of biological functions such as ion transport, substrate transport, and signal transduction. MPs undergo function-related conformational changes on time intervals spanning from nanoseconds to seconds. Many MP structures have been solved thanks to recent developments in structural biology, particularly in single-particle cryo-Electron Microscopy (cryo-EM). Obtaining time-resolved dynamic information on MPs in their membrane surroundings, on the other hand, remains a significant difficulty.

OmpG (Open state) in a fully hydrated dimyristoylphosphatidylcholine (DMPC) bilayer. The protein is shown in light green cartoon. Lipids units are depicted in yellow, while their phosphate and choline groups are illustrated as orange and green van der Waals spheres, respectively. Potassium and chloride counterions are shown in green and purple, respectively. A continuous and semi-transparent cyan representation is used for water.
https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-021-24660-1/MediaObjects/41467_2021_24660_MOESM1_ESM.pdf

Weill Cornell Medicine (WCM) researchers have found that they can record high-speed protein movements while linking them to function. The accomplishment should allow scientists to examine proteins in more depth than ever before, and in theory, it should allow for the development of drugs that work better by hitting their protein targets much more effectively.

The researchers utilized High-Speed Atomic Force Microscopy (HS-AFM) to record the rapid motions of a channel protein and published in a report in Nature Communications on July 16. Such proteins generally create channel or tube-like structures in cell membranes, which open to allow molecules to flow under particular conditions. The researchers were able to record the channel protein’s rapid openings and closings with the same temporal resolution as single channel recordings, a typical technique for recording the intermittent passage of charged molecules through the channel.

Senior author Simon Scheuring, professor of physiology and biophysics in anesthesiology at WCM, said,

There has been a significant need for a tool like this that achieves such a high bandwidth that it can ‘see’ the structural variations of molecules as they work.

Researchers can now produce incredibly detailed photographs of molecules using techniques like X-ray crystallography and electron microscopy, showing their structures down to the atomic scale. The average or dominant structural positionings, or conformations, of the molecules, are depicted in these “images,” which are often calculated from thousands of individual photos. In that way, they’re similar to the long-exposure still photos from the dawn of photography.

Many molecules, on the other hand, are flexible and always-moving machinery rather than fixed structures. Scientists need to generate videos, not still photos, to reveal how such molecules move as they work, to see how their motion translates to function to catch their critical functional conformations, which may only exist for a brief moment. Current techniques for dynamic structural imaging, on the other hand, have several drawbacks, one of which being the requirement for fluorescent tags to be inserted on the molecules being photographed in many cases.

Scheuring and his lab were early adopters of the tag-free HS-AFM approach for studying molecular dynamics. The technology, which can photograph molecules in a liquid solution similar to a genuine cellular environment, employs an extremely sensitive probe, similar to a record player’s stylus, to feel its way over a molecule and therefore build up a picture of its structure. Standard HS-AFM isn’t quick enough to capture the high-speed dynamics of many proteins, but Scheuring and colleagues have developed a modified version, HS-AFM height spectroscopy (HS-AFM-HS), that works much faster by collecting dynamic changes in only one dimension: height.

The researchers used HS-AFM-HS to record the opening and closing of a relatively simple channel protein, OmpG, found in bacteria and widely studied as a model channel protein in the new study, led by the first author Raghavendar Reddy Sanganna Gari, a postdoctoral research associate in Scheuring’s laboratory. They were able to monitor OmpG gating at an effective rate of roughly 20,000 data points per second, seeing how it transitioned from open to closed states or vice versa as the acidity of the surrounding fluid varied.

More significantly, they were able to correlate structural dynamics with functional dynamics in a membrane protein of this size for the first time in a partnership with Crina Nimigean, professor of physiology and biophysics in anesthesiology, and her group at WCM.

The demonstration opens the door for a wider application of this method in basic biology and drug development.

Sanganna Gari stated,

We’re now in an exciting period of HS-AFM technology, for example using this technique to study how some drugs modulate the structural dynamics of the channel proteins they target.

Main Source

Technique reveals proteins moving as they work. By Jim Schnabel in Cornell Chronicle, August 16, 2021.

https://news.cornell.edu/stories/2021/08/technique-reveals-proteins-moving-they-work

Other Related Articles published in this Open Access Online Scientific Journal include the following:

Cryo-EM disclosed how the D614G mutation changes SARS-CoV-2 spike protein structure.

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

https://pharmaceuticalintelligence.com/2021/04/10/cryo-em-disclosed-how-the-d614g-mutation-changes-sars-cov-2-spike-protein-structure/

Proteins, Imaging and Therapeutics

Larry H Bernstein, MD, FCAP, Curator, LPBI

https://pharmaceuticalintelligence.com/2015/10/01/proteins-imaging-and-therapeutics/

From High-Throughput Assay to Systems Biology: New Tools for Drug Discovery

Curator: Stephen J. Williams, PhD

https://pharmaceuticalintelligence.com/2021/07/19/from-high-throughput-assay-to-systems-biology-new-tools-for-drug-discovery/

Imaging break-through: Fusion of microscopy and mass spectrometry produces detailed map of protein distribution

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/03/18/imaging-break-through-fusion-of-microscopy-and-mass-spectrometry-produces-detailed-map-of-protein-distribution/

Advanced Microscopic Imaging

Larry H Bernstein, MD, FCAP, Curator, LPBI

https://pharmaceuticalintelligence.com/2016/02/07/advanced-microscopic-imaging/

Read Full Post »

Cryo-EM disclosed how the D614G mutation changes SARS-CoV-2 spike protein structure.

Reporter: Dr. Premalata Pati, Ph.D., Postdoc

SARS-CoV-2, the virus that causes COVID-19, has had a major impact on human health globally; infecting a massive quantity of people around 136,046,262 (John Hopkins University); causing severe disease and associated long-term health sequelae; resulting in death and excess mortality, especially among older and prone populations; altering routine healthcare services; disruptions to travel, trade, education, and many other societal functions; and more broadly having a negative impact on peoples physical and mental health.

It’s need of the hour to answer the questions like what allows the variants of SARS-CoV-2 first detected in the UK, South Africa, and Brazil to spread so quickly? How can current COVID-19 vaccines better protect against them?

Scientists from the Harvard Medical School and the Boston Children’s Hospital help answer these urgent questions. The team reports its findings in the journal “Science a paper entitled Structural impact on SARS-CoV-2 spike protein by D614G substitution. The mutation rate of the SARS-CoV-2 virus has rapidly evolved over the past few months, especially at the Spike (S) protein region of the virus, where the maximum number of mutations have been observed by the virologists.

Bing Chen, HMS professor of pediatrics at Boston Children’s, and colleagues analyzed the changes in the structure of the spike proteins with the genetic change by D614G mutation by all three variants. Hence they assessed the structure of the coronavirus spike protein down to the atomic level and revealed the reason for the quick spreading of these variants.


This model shows the structure of the spike protein in its closed configuration, in its original D614 form (left) and its mutant form (G614). In the mutant spike protein, the 630 loop (in red) stabilizes the spike, preventing it from flipping open prematurely and rendering SARS-CoV-2 more infectious.

Fig. 1. Cryo-EM structures of the full-length SARS-CoV-2 S protein carrying G614.

(A) Three structures of the G614 S trimer, representing a closed, three RBD-down conformation, an RBD-intermediate conformation and a one RBD-up conformation, were modeled based on corresponding cryo-EM density maps at 3.1-3.5Å resolution. Three protomers (a, b, c) are colored in red, blue and green, respectively. RBD locations are indicated. (B) Top views of superposition of three structures of the G614 S in (A) in ribbon representation with the structure of the prefusion trimer of the D614 S (PDB ID: 6XR8), shown in yellow. NTD and RBD of each protomer are indicated. Side views of the superposition are shown in fig. S8.

IMAGE SOURCE: Bing Chen, Ph.D., Boston Children’s Hospital, https://science.sciencemag.org/content/early/2021/03/16/science.abf2303

The work

The mutant spikes were imaged by Cryo-Electron microscopy (cryo-EM), which has resolution down to the atomic level. They found that the D614G mutation (substitution of in a single amino acid “letter” in the genetic code for the spike protein) makes the spike more stable as compared with the original SARS-CoV-2 virus. As a result, more functional spikes are available to bind to our cells’ ACE2 receptors, making the virus more contagious.


Fig. 2. Cryo-EM revealed how the D614G mutation changes SARS-CoV-2 spike protein structure.

IMAGE SOURCE:  Zhang J, et al., Science

Say the original virus has 100 spikes,” Chen explained. “Because of the shape instability, you may have just 50 percent of them functional. In the G614 variants, you may have 90 percent that is functional. So even though they don’t bind as well, the chances are greater and you will have an infection

Forthcoming directions by Bing Chen and Team

The findings suggest the current approved COVID-19 vaccines and any vaccines in the works should include the genetic code for this mutation. Chen has quoted:

Since most of the vaccines so far—including the Moderna, Pfizer–BioNTech, Johnson & Johnson, and AstraZeneca vaccines are based on the original spike protein, adding the D614G mutation could make the vaccines better able to elicit protective neutralizing antibodies against the viral variants

Chen proposes that redesigned vaccines incorporate the code for this mutant spike protein. He believes the more stable spike shape should make any vaccine based on the spike more likely to elicit protective antibodies. Chen also has his sights set on therapeutics. He and his colleagues are further applying structural biology to better understand how SARS-CoV-2 binds to the ACE2 receptor. That could point the way to drugs that would block the virus from gaining entry to our cells.

In January, the team showed that a structurally engineered “decoy” ACE2 protein binds to SARS-CoV-2 200 times more strongly than the body’s own ACE2. The decoy potently inhibited the virus in cell culture, suggesting it could be an anti-COVID-19 treatment. Chen is now working to advance this research into animal models.

Main Source:

Abstract

Substitution for aspartic acid by glycine at position 614 in the spike (S) protein of severe acute respiratory syndrome coronavirus 2 appears to facilitate rapid viral spread. The G614 strain and its recent variants are now the dominant circulating forms. We report here cryo-EM structures of a full-length G614 S trimer, which adopts three distinct prefusion conformations differing primarily by the position of one receptor-binding domain. A loop disordered in the D614 S trimer wedges between domains within a protomer in the G614 spike. This added interaction appears to prevent premature dissociation of the G614 trimer, effectively increasing the number of functional spikes and enhancing infectivity, and to modulate structural rearrangements for membrane fusion. These findings extend our understanding of viral entry and suggest an improved immunogen for vaccine development.

https://science.sciencemag.org/content/early/2021/03/16/science.abf2303?rss=1

Other Related Articles published in this Open Access Online Scientific Journal include the following:

COVID-19-vaccine rollout risks and challenges

Reporter : Irina Robu, PhD

https://pharmaceuticalintelligence.com/2021/02/17/covid-19-vaccine-rollout-risks-and-challenges/

COVID-19 Sequel: Neurological Impact of Social isolation been linked to poorer physical and mental health

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/03/30/covid-19-sequel-neurological-impact-of-social-isolation-been-linked-to-poorer-physical-and-mental-health/

Comparing COVID-19 Vaccine Schedule Combinations, or “Com-COV” – First-of-its-Kind Study will explore the Impact of using eight different Combinations of Doses and Dosing Intervals for Different COVID-19 Vaccines

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2021/02/08/comparing-covid-19-vaccine-schedule-combinations-or-com-cov-first-of-its-kind-study-will-explore-the-impact-of-using-eight-different-combinations-of-doses-and-dosing-intervals-for-diffe/

COVID-19 T-cell immune response map, immunoSEQ T-MAP COVID for research of T-cell response to SARS-CoV-2 infection

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2020/11/20/covid-19-t-cell-immune-response-map-immunoseq-t-map-covid-for-research-of-t-cell-response-to-sars-cov-2-infection/

Tiny biologic drug to fight COVID-19 show promise in animal models

Reporter : Irina Robu, PhD

https://pharmaceuticalintelligence.com/2020/10/11/tiny-biologic-drug-to-fight-covid-19-show-promise-in-animal-models/

Miniproteins against the COVID-19 Spike protein may be therapeutic

Reporter: Stephen J. Williams, PhD

https://pharmaceuticalintelligence.com/2020/09/30/miniproteins-against-the-covid-19-spike-protein-may-be-therapeutic/

Read Full Post »

 

Healing Powers of Fibrinogen

Reporter: Irina Robu, PhD

Recent research from University of Alberta is looking at the role of fibrinogen, the substrate of thrombin in regulating a natural defense mechanism in the body. Fibrinogen is a well-known protein that is essential for wound healing and blood clotting in the body. Levels of fibrinogen increase in inflammatory states as part of the acute-phase response.

However, daily variation in plasma fibrinogen levels weakens its potential as a biomarker of cardiovascular risk. The discovery is expected to contribute to enhanced diagnosis and treatments for patients in a variety of diseases ranging from inflammation, to heart failure, to cancer.

Yet, a study published in Scientific Reports in March 2019 show that fibrinogen can also be a natural inhibitor of an enzyme named MMP2, which is important for normal organ development and repair. The researchers believe an essential function of fibrinogen is to allow or disallow the enzyme to carry out its normal functions. Nevertheless, high levels of fibrinogen may disproportionately inhibit MMP2, that could result in arthritic and cardiac disorders.

The researcher highlights the inner workings of the MMP family of enzymes by having a greater understanding of how MMPs are regulated. They hypothesize that abnormal MMP2 activity could be an unwelcome side effect of common medications such as the cholesterol-lowering drugs and the antibiotic doxycycline, both of which are known to inhibit MMPs. They also emphasize that future therapeutic developments must strike a balance between the levels of MMPs and their inhibitors, such as fibrinogen, so that net MMP activity in the body remains at nearly normal levels.

SOURCE

https://www.technologynetworks.com/biopharma/news/healing-protein-also-hinders-320533?utm_campaign=NEWSLETTER_TN_Breaking%20Science%20News

Read Full Post »

Medical Scientific Discoveries for the 21st Century & Interviews with Scientific Leaders at https://www.amazon.com/dp/B078313281 – electronic Table of Contents 

Author, Curator and Editor: Larry H Bernstein, MD, FCAP

Available on Kindle Store @ Amazon.com since 12/9/2017

List of Contributors & Contributors’ Biographies

Volume Author, Curator and Editor

Larry H Bernstein, MD, FCAP

Preface, all Introductions, all Summaries and Epilogue

Part One:

1.4, 1.5, 1.6, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.2.1, 2.2.2, 2.2.3, 2.3, 2.4, 2.4.1, 2.4.2, 2.5, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.7, 2.8, 2.9, 2.10, 3.1, 3.2, 3.3, 3.4, 4.1, 4.2, 4.3

Part Two:

5.2, 5.3, 5.6, 6.1.2, 6.1.4, 6.2.1, 6.2.2, 6.3.2, 6.3.4, 6.3.5, 6.3.6, 6.3.8, 6.3.10, 6.4.1, 6.4.2, 6.5.1.2, 6.5.1.3, 6.5.2.2, 7.1, 7.2, 7.3, 7.4, 7.5, 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 8.9.1, 8.9.3, 8.9.4, 8.9.5, 8.9.6, 8.10.1, 8.10.2, 8.10.3, 8.10.4, 9.2, 9.3, 9.5, 9.6, 9.7, 9.8, 9.9, 9.10, 9.11, 9.12, 9.13, 9.14, 9.15, 9.16, 10.2, 10.5, 10.6, 10.7, 10.8, 10.10, 10.11, 11.1, 11.2, 11.3, 11.5, 11.6, 11.7, 12.1, 12.2, 12.3, 12.4, 12.5, 12.7, 12.8, 12.9, 12.10, 12.11, 12.12, 13.1, 13.2, 13.3, 13.6, 13.12, 13.13, 14.1, 14.2

Guest Authors:

Pnina Abir-Am, PhD Part Two: 6.1.1

Stephen J Williams, PhDPart Two: 6.2.6, 6.5.2.2, 10.4, 10.9, 13.4

Aviva Lev-Ari, PhD, RN:

Part One:

1.1, 1.2, 1.3, 1.4, 1.5, 1.7, 2.2.1, 2.3

Part Two:

5.1, 5.4, 5.5, 5.7, 5.8, 5.9, 5.10, 5.11, 6.1.3, 6.2.3, 6.2.4, 6.2.5, 6.3.1, 6.3.3, 6.3.7, 6.3.9, 6.4.3, 6.5.1.1, 6.5.2.1, 6.5.2.2, 6.5.3.1, 6.5.4, 6.5.5, 6,5,6, 8.9.2, 8.10.2, 9.1, 9.4, 10.1, 10.3, 11.4, 12.6, 13.5, 13.7, 13.8, 13.9, 13.10, 13.11

Adam Sonnenberg, BSC, MSc(c)Part Two: 13.9

 

electronic Table of Contents

PART ONE:

Physician as Authors, Writers in Medicine and Educator in Public Health

 

Chapter 1: Physicians as Authors

Introduction

1.1  The Young Surgeon and The Retired Pathologist: On Science, Medicine and HealthCare Policy – Best writers Among the WRITERS

1.2 Atul Gawande: Physician and Writer

1.3 Editorial & Publication of Articles in e-Books by  Leaders in Pharmaceutical Business Intelligence:  Contributions of Larry H Bernstein, MD, FCAP

1.4 Abraham Verghese, MD, Physician and Notable Author

1.5 Eric Topol, M.D.

1.6 Gregory House, MD

1.7 Peter Mueller, MD  Professor of Radiology @MGH & HMS – 2015 Synergy’s Honorary Award Recipient

Summary

Chapter 2: Professional Recognition

Introduction

2.1 Proceedings

2.1.1 Research Presentations

2.1.2 Proceedings of the NYAS

2.1.3 Cold Spring Harbor Conference Meetings

2.1.4 Young Scientist Seminars

2.2 Meet Great Minds

2.2.1 Meet the Laureates

2.2.2 Richard Feynman, Genius and Laureate

2.2.3 Fractals and Heat Energy

2.3 MacArthur Foundation Awards

2.4 Women’s Contributions went beyond Rosie the Riveter

2.4.1 Secret Maoist Chinese Operation Conquered Malaria

2.4.2 Antiparasite Drug Developers Win Nobel

2.5 Impact Factors and Achievement

2.6   RAPsodisiac Medicine

2.6.1 Outstanding-achievements-in-radiology-or-radiotherapy

2.6.2 Outstanding-achievement-in-anesthesiology

2.6.3 Outstanding-achievement-in-pathology

2.6.4 Topics in Pathology – Special Issues from Medscape Pathology

2.7 How to win the Nobel Prize

2.8 Conversations about Medicine

2.9 Current Advances in Medical Technology

2.10 Atul Butte, MD, PhD

Summary

Chapter 3:  Medical and Allied Health Sciences Education

Introduction

3.1 National Outstanding Medical Student Award Winners

3.2 Outstanding Awards in Medical Education

3.3 Promoting Excellence in Physicians and Nurses

3.4 Excellence in mentoring

Summary

Chapter 4: Science Teaching in Math and Technology (STEM)

Introduction

4.1 Science Teaching in Math and Technology

4.2 Television as a Medium for Science Education

4.2.1 Science Discovery TV

4.3 From Turing to Watson

Summary

PART TWO:

Medical Scientific Discoveries Interviews with Scientific Leaders

Chapter 5: Cardiovascular System

Introduction

5.1 Physiologist, Professor Lichtstein, Chair in Heart Studies at The Hebrew University elected Dean of the Faculty of Medicine at The Hebrew University of Jerusalem

5.2 Mitochondrial Dysfunction and Cardiac Disorders

5.3 Notable Contributions to Regenerative Cardiology

5.4 For Accomplishments in Cardiology and Cardiovascular Diseases: The Arrigo Recordati International Prize for Scientific Research

5.5 Becoming a Cardiothoracic Surgeon: An Emerging Profile in the Surgery Theater and through Scientific Publications

5.6 Diagnostics and Biomarkers: Novel Genomics Industry Trends vs Present Market Conditions and Historical Scientific Leaders Memoirs

5.7 CVD Prevention and Evaluation of Cardiovascular Imaging Modalities: Coronary Calcium Score by CT Scan Screening to justify or not the Use of Statin

5.8 2013 as A Year of Revolutionizing Medicine and Top 11 Cardiology Stories

5.9 Bridging the Gap in Medical Innovations – Elazer Edelman @ TEDMED 2013

5.10 Development of a Pancreatobiliary Chemotherapy Eluting Stent for Pancreatic Ductal Adenocarcinoma PIs: Jeffrey Clark (MGH), Robert Langer (Koch), Elazer Edelman (Harvard:MIT HST Program)

5.11 Publications on Heart Failure by Prof. William Gregory Stevenson, M.D., BWH

Summary

Chapter 6: Genomics

Introduction
6.1 Genetics before the Human Genome Project

6.1.1 Why did Pauling Lose the “Race” to James Watson and Francis Crick? How Crick Describes his Discovery in a Letter to his Son

6.1.2 John Randall’s MRC Research Unit and Rosalind Franklin’s role at Kings College

6.1.3 Interview with the co-discoverer of the structure of DNA: Watson on The Double Helix and his changing view of Rosalind Franklin

6.1.4 The Initiation and Growth of Molecular Biology and Genomics, Part I

6.2 The Human Genome Project: Articles of Note  @ pharmaceuticalintelligence.com by multiple authors

6.2.1 CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

6.2.2 What comes after finishing the Euchromatic Sequence of the Human Genome?

6.2.3 Human Genome Project – 10th Anniversary: Interview with Kevin Davies, PhD – The $1000 Genome

6.2.4 University of California Santa Cruz’s Genomics Institute will create a Map of Human Genetic Variations

6.2.5 Exceptional Genomes: The Process to find them

6.2.6 Multiple Lung Cancer Genomic Projects Suggest New Targets, Research Directions for Non-Small Cell Lung Cancer

6.3 The Impact of Genome Sequencing on Biology and Medicine

6.3.1 Genomics in Medicine – Establishing a Patient-Centric View of Genomic Data

6.3.2 Modification of genes by homologous recombination – Mario Capecchi, Martin Evans, Oliver Smithies

6.3.3 AAAS February 14-18, 2013, Boston: Symposia – The Science of Uncertainty in Genomic Medicine

6.3.4 The Metabolic View of Epigenetic Expression

6.3.5  Pharmacogenomics

6.3.6 Neonatal Pathophysiology

6.3.7 Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

6.3.8 3D mapping of genome in combine FISH and RNAi

6.3.9 Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence

6.3.10 DNA mutagenesis and DNA repair

6.4 Scientific Leadership Recognition for Contributions to Genomics

6.4.1 Interview with Elizabeth H. Blackburn, Carol W. Greider and Jack W. Szostak (44 minutes)

6.4.2 DNA Repair Pioneers Win Nobel – Tomas Lindahl, Paul Modrich, and Aziz Sancar 2015 Nobel Prize in Chemistry for the mechanisms of DNA repair

6.4.3  Richard Lifton, MD, PhD of Yale University and Howard Hughes Medical Institute: Recipient of 2014 Breakthrough Prizes Awarded in Life Sciences for the Discovery of Genes and Biochemical Mechanisms that cause Hypertension

6.5 Contemporary Field Leaders in Genomics

6.5.1 ROBERT LANGER

6.5.1.1 2014 Breakthrough Prizes Awarded in Fundamental Physics and Life Sciences for a Total of $21 Million – MIT’s Robert Langer gets $3 Million

6.5.1.2 National Medal of Science – 2006 Robert S. Langer

6.5.1.3  Confluence of Chemistry, Physics, and Biology

6.5.2 JENNIFER DOUDNA

6.5.2.1 Jennifer Doudna, cosmology teams named 2015 Breakthrough Prize winners

6.5.2.2 UPDATED – Medical Interpretation of the Genomics Frontier – CRISPR – Cas9: Gene Editing Technology for New Therapeutics

6.5.3 ERIC LANDER

6.5.3.1  2012 Harvey Prize in April 30: at the Technion-Israel Institute of Technology to Eric S. Lander @MIT & Eli Yablonovitch @UC, Berkeley

6.5.4 2013 Genomics: The Era Beyond the Sequencing of the Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

6.5.5 Recognitions for Contributions in Genomics by Dan David Prize Awards

6.5.6   65 Nobel Laureates meet 650 young scientists covering the fields of physiology and medicine, physics, and chemistry, 28 June – 3 July, 2015, Lindau & Mainau Island, Germany

Summary

Chapter 7: The RNAs

Introduction

7.1 RNA polymerase – molecular basis for DNA transcription – Roger Kornberg, MD

7.2  One gene, one protein – Charles Yanofsky

7.3 Turning genetic information into working proteins – James E. Darnell Jr.

7.4 Small but mighty RNAs – Victor Ambros, David Baulcombe, and Gary Ruvkun, Phillip A. Sharp

7.5 Stress-response gene networks – Nina V. Fedoroff

Summary

Chapter 8: Proteomics, Protein-folding, and Cell Regulation
Introduction.

8.1 The Life and Work of Allan Wilson

8.2 Proteomics

8.3 More Complexity in Protein Evolution

8.4 Proteins: An evolutionary record of diversity and adaptation

8.5 Heroes in Basic Medical Research – Leroy Hood

8.6 Ubiquitin researchers win Nobel – Ciechanover, Hershko, and Rose awarded for discovery of ubiquitin-mediated proteolysis

8.7 Buffering of genetic modules involved in tricarboxylic acid cycle metabolism provides homeostatic regulation

8.8 Dynamic Protein Profiling

8.9 Protein folding

8.9.1 Protein misfolding and prions – Susan L. Lindquist, Stanley B. Prusiner

8.9.2 A Curated Census of Autophagy-Modulating Proteins and Small Molecules Candidate Targets for Cancer Therapy

8.9.3 Voluntary and Involuntary S-Insufficiency

8.9.4 Transthyretin and Lean Body Mass in Stable and Stressed State

8.9.5 The matter of stunting in the Ganges Plains

8.9.6 Proteins, Imaging and Therapeutics

8.10 Protein Folding and Vesicle Cargo

8.10.1 Heat Shock Proteins (HSP) and Molecular Chaperones

8.10.2 Collagen-binding Molecular Chaperone HSP47: Role in Intestinal Fibrosis – colonic epithelial cells and sub epithelial myofibroblasts

8.10.3 Biology, Physiology and Pathophysiology of Heat Shock Proteins

8.10.4 The Role of Exosomes in Metabolic Regulation 


Summary

Chapter 9:  Neuroscience

Introduction

9.1 Nobel Prize in Physiology or Medicine 2013 for Cell Transport: James E. Rothman of Yale University; Randy W. Schekman of the University of California, Berkeley; and Dr. Thomas C. Südhof of Stanford University

9.2 Proteins that control neurotransmitter release – Richard H. Scheller

9.3 Heroes in Basic Medical Research – Robert J. Lefkowitz

9.4 MIND AND MEMORY: BIOLOGICAL AND DIGITAL – 2014 Dan David Prize Symposium

9.5 A new way of moving – Michael Sheetz, James Spudich, Ronald Vale

9.6 Role the basal ganglia

9.7 The Neurogenetics of Language – Patricia Kuhl – 2015 George A. Miller Award

9.8 The structure of our visual system

9.9 Outstanding Achievement in Schizophrenia Research

9.10 George A. Miller, a Pioneer in Cognitive Psychology, Is Dead at 92

9.11 – To understand what happens in the brain to cause mental illness

9.12 Brain and Cognition

9.13 – To reduce symptoms of mental illness and retrain the brain

9.14 Behavior

9.15 Notable Papers in Neurosciences

9.16 Pyrroloquinoline quinone (PQQ) – an unproved supplement

Summary

Chapter 10: Microbiology & Immunology

Introduction

10.1 Reference Genes in the Human Gut Microbiome: The BGI Catalogue

10.2 Malnutrition in India, high newborn death rate and stunting of children age under five years

10.3 In His Own Words: Leonard Herzenberg, The Immunologist Who Revolutionized Research, Dies at 81

10.4 Heroes in Medical Research: Dr. Robert Ting, Ph.D. and Retrovirus in AIDS and Cancer

10.5 Tang Prize for 2014: Immunity and Cancer

10.6 Halstedian model of cancer progression

10.7 The History of Hematology and Related Sciences

10.8 Pathology Emergence in the 21st Century

10.9 Heroes in Medical Research: Barnett Rosenberg and the Discovery of Cisplatin

10.10  T cell-mediated immune responses & signaling pathways activated by TLRs – Bruce A. Beutler, Jules A. Hoffmann, Ralph M. Steinman

10.11 Roeder – the coactivator OCA-B, the first cell-specific coactivator, discovered by Roeder in 1992, is unique to immune system B cells

Summary

Chapter 11: Endocrine Hormones

Introduction

11.1 Obesity – 2010 Douglas L. ColemanJeffrey M. Friedman

11.2 Lonely Receptors: RXR – Jensen, Chambon, and Evans – Nuclear receptors provoke RNA production in response to steroid hormones

11.3 The Fred Conrad Koch Lifetime Achievement Award—the Society’s highest honor—recognizes the lifetime achievements and exceptional contributions of an individual to the field of endocrinology

11.4 Gerald D Aurbach Award for Outstanding Translational Research

11.5 Roy O. Greep Award for Outstanding Research in Endocrinology – Martin M. Matzuk

11.6 American Physiology Society Awards

11.7 Solomon Berson and Rosalyn Yalow

Summary

Chapter 12. Stem Cells

Introduction

12.1 Mature cells can be reprogrammed to become pluripotent – John Gurdon and Shinya Yamanaka

12.2 Observing the spleen colonies in mice and proving the existence of stem cells – Till and McCulloch

12.3 McEwen Award for Innovation: Irving Weissman, M.D., Stanford School of Medicine, and Hans Clevers, M.D., Ph.D., Hubrecht Institute

12.4 Developmental biology

12.5  CRISPR/Cas-mediated genome engineering – Rudolf Jaenisch

12.6 Ribozymes and RNA Machines –  Work of Jennifer A. Doudna

12.7 Ralph Brinster, ‘Father of Transgenesis’

12.8 Targeted gene modification

12.9 Stem Cells and Cancer

12.10 ALPSP Awards

12.11 Eppendorf Award for Young European Investigators

12.12 Breaking news about genomic engineering, T2DM and cancer treatments

Summary
Chapter 13: 3D Printing and Medical Application

Introduction

13.1 3D Printing

13.2 What is 3D printing?

13.3 The Scientist Who Is Making 3D Printing More Human

13.4 Join These Medical 3D Printing Groups on Twitter and LinkedIn for great up to date news

13.5 Neri Oxman and her Mediated Matter group @MIT Media Lab have developed a technique for 3D-printing Molten Glass

13.6 The ‘chemputer’ that could print out any drug

13.7 3-D-Bioprinting in use to Create Cardiac Living Tissue: Print your Heart out

13.8 LPBI’s Perspective on Medical and Life Sciences Applications – 3D Printing: BioInks, BioMaterials-BioPolymer

13.9 Medical MEMS, Sensors and 3D Printing: Frontier in Process Control of BioMaterials

13.10 NIH and FDA on 3D Printing in Medical Applications: Views for On-demand Drug Printing, in-Situ direct Tissue Repair and Printed Organs for Live Implants

13.11 ‘Pop-up’ fabrication technique trumps 3D printing

13.12 Augmentation of the ONTOLOGY of the 3D Printing Research

13.13 Superresolution Microscopy

Summary

Chapter 14: Synthetic Medicinal Chemistry

Introduction

14.1 Insights in Biological and Synthetic Medicinal Chemistry

14.2 Breakthrough work in cancer

Summary to Part Two

Volume Summary and Conclusions

EPILOGUE

 

 

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Familial transthyretin amyloid polyneuropathy

Curator: Larry H. Bernstein, MD, FCAP

 

UPDATED on 6/3/2020

Treatment of Cardiac Transthyretin Amyloidosis

Authors:
Emdin M, Aimo A, Rapezzi C, et al.
Citation:
Treatment of Cardiac Transthyretin Amyloidosis: An Update. Eur Heart J 2019;40:3699-3706.

The following are key points to remember from this update on the treatment of cardiac transthyretin amyloidosis:

  1. Transthyretin (TTR) is a highly conserved protein involved in transportation of thyroxine (T4) and retinol-binding protein. TTR is synthesized mostly by the liver and is rich in beta strands with an intrinsic propensity to aggregate into insoluble amyloid fibers, which deposit within tissue leading to the development of TTR-related amyloidosis (ATTR). ATTR can follow the deposition of either variant TTR (ATTRv, previously known as mutant ATTR) or wild type TTR (ATTRwt).
  2. Cardiac ATTR has a favorable survival rate compared to light chain (AL) amyloidosis, with a median survival of 75 versus 11 months. However, ATTR cardiomyopathy is a progressive disorder but newer therapeutic options include tafamidis (positive phase 3 clinical trial), and possibly patisiran and inotersen.

Inhibition of the Synthesis of Mutated Transthyretin

  1. Liver transplantation removes the source of mutated TTR molecules and prolongs survival, with a 20-year survival of 55.3%. However, tissue accumulation of TTR can continue after liver transplantation because TTR amyloid fibers promote subsequent deposition of ATTRwt. Combined liver–heart transplantation is feasible in younger patients with ATTRv cardiomyopathy and a small series suggests better prognosis than cardiac transplantation.
  2. Inhibition of TTR gene expression: Patisiran is a small interfering RNA blocking the expression of both variant and wt TTR. On the basis of the APOLLO trial, it was approved for therapy of adults with ATTRv-related polyneuropathy both in the United States and European Union. In this trial, patisiran promoted favorable myocardial remodeling based on echocardiographic and N-terminal B-type natriuretic peptide (NT-BNP) changes (this effect was not demonstrated for inotersen) and is still under investigation for tafamidis.
  3. Antisense oligonucleotides inotersen inhibits the production of both variant and wt TTR. Based on the findings of the NEURO-TTR trial, the Food and Drug Administration (FDA) approved this agent for patients with ATTRv-related polyneuropathy. In the NEURO-TTR trial, cardiomyopathy was present in 63%, but the study was not powered to measure effects of inotersen on heart disease. Inotersen can cause thrombocytopenia and must be used cautiously with bleeding risk.

Tetramer Stabilization

  1. Selective stabilizers include tafamidis and AG10. Tafamidis is a benzoxazole and a small molecule that inhibits the dissociation of TTR tetramers by binding the T4-binding sites. The phase ATTR-ACT study showed that when comparing the pooled tafamidis arms (80 and 20 mg) with the placebo arm, tafamidis was associated with lower all-cause mortality than placebo (78 of 264 [29.5%] vs. 76 of 177 [42.9%]; hazard ratio, 0.70; 95% confidence interval, 0.51-0.96) and a lower rate of cardiovascular hospitalizations. Based on the results of the ATTR-ACT trial, it has received Breakthrough Therapy designation from the FDA for treatment of ATTR cardiomyopathy.
  2. Nonselective agents: Diflunisal, a nonsteroidal anti-inflammatory drug, is reported to stabilize TTR tetramers. More studies are needed to confirm its clinical efficacy.

Inhibition of Oligomer Aggregation and Oligomer Disruption

  1. Epigallocatechin gallate is the most abundant catechin in green tea. One single-center open-label 12-month study did not show survival benefits or any change in echocardiographic parameters or NT-BNP compared to baseline.

Degradation and Reabsorption of Amyloid Fibers

  1. Doxycycline-taurosodeoxycholic acid (TUDCA) has been evaluated in two small studies and the results appear to be modest. More data are needed to confirm its efficacy.
  2. Antibodies targeting serum amyloid P protein or amyloid fibrils: Patient enrollment for miridesap followed by anti-SAP antibodies was suspended, and this approach is not being evaluated currently. However, a monoclonal antibody designed to specifically target TTR amyloid deposits (PRX004) has entered clinical evaluation, with an ongoing phase 1 study on ATTRv.

Supportive Treatment of Cardiac Involvement

  1. Drug therapies: Although angiotensin-converting enzyme (ACE) inhibitors/angiotensin-receptor blockers (ARBs) and beta-blockers may have been poorly tolerated in the ATTR-ACT trial, 30% of the patients were on ACE inhibitors/ARBs. There are no data with digoxin in TTR amyloid, and non-dihydropyridine calcium channel blockers are contraindicated due to negative inotropy.
  2. Implantable cardioverter-defibrillators (ICDs): In one study, which included 53 patients with amyloid, ICD shocks occurred exclusively in the AL amyloid group and none in the TTR amyloid patients. Higher defibrillation thresholds and complication rates are of concern.
  3. Cardiac pacing: In a large series of ATTRv-related polyneuropathy (n = 262), a pacemaker was implanted in 110 patients with His ventricular interval >700 ms. The authors recommend that any conduction disturbance on 12-lead electrocardiogram (ECG) warrants further investigation with Holter monitoring to determine candidacy for a pacemaker.
  4. Left ventricular assist device (LVAD): Although an LVAD is technically feasible, it is associated with high short-term mortality and worse outcomes than in dilated cardiomyopathy.
  5. Cardiac transplantation: This is a valuable option for patients with end-stage heart failure when significant extracardiac disease is excluded. In one study with 10 patients, only episodes of amyloid recurrence occurred.

This is an outstanding overview of this topic and recommended reading for anyone who cares for patients with cardiac transthyretin amyloid.

 

First-Ever Evidence that Patisiran Reduces Pathogenic, Misfolded TTR Monomers and Oligomers in FAP Patients

We reported data from our ongoing Phase 2 open-label extension (OLE) study of patisiran, an investigational RNAi therapeutic targeting transthyretin (TTR) for the treatment of TTR-mediated amyloidosis (ATTR amyloidosis) patients with familial amyloidotic polyneuropathy (FAP). Alnylam scientists and collaborators from The Scripps Research Institute and Misfolding Diagnostics, Inc. were able to measure the effects of patisiran on pathogenic, misfolded TTR monomers and oligomers in FAP patients. Results showed a rapid and sustained reduction in serum non-native conformations of TTR (NNTTR) of approximately 90%. Since NNTTR is pathogenic in ATTR amyloidosis and the level of NNTTR reduction correlated with total TTR knockdown, these results provide direct mechanistic evidence supporting the therapeutic hypothesis that TTR knockdown has the potential to result in clinical benefit. Furthermore, complete 12-month data from all 27 patients that enrolled in the patisiran Phase 2 OLE study showed sustained mean maximum reductions in total serum TTR of 91% for over 18 months and a mean 3.1-point decrease in mNIS+7 at 12 months, which compares favorably to an estimated increase in mNIS+7 of 13 to 18 points at 12 months based upon analysis of historical data sets in untreated FAP patients with similar baseline characteristics. Importantly, patisiran administration continues to be generally well tolerated out to 21 months of treatment.

Read our press release

View the non-native TTR poster (480 KB PDF)

View the complete 12-month patisiran Phase 2 OLE data presentation (620 KB PDF)

We are encouraged by these new data that provide continued support for our hypothesis that patisiran has the potential to halt neuropathy progression in patients with FAP. If these results are replicated in a randomized, double-blind, placebo-controlled study, we believe that patisiran could emerge as an important treatment option for patients suffering from this debilitating, progressive and life-threatening disease.

 

Hereditary ATTR Amyloidosis with Polyneuropathy (hATTR-PN)

ATTR amyloidosis is a progressive, life-threatening disease caused by misfolded transthyretin (TTR) proteins that accumulate as amyloid fibrils in multiple organs, but primarily in the peripheral nerves and heart. ATTR amyloidosis can lead to significant morbidity, disability, and mortality. The TTR protein is produced primarily in the liver and is normally a carrier for retinol binding protein – one of the vehicles used to transport vitamin A around the body.  Mutations in the TTR gene cause misfolding of the protein and the formation of amyloid fibrils that typically contain both mutant and wild-type TTR that deposit in tissues such as the peripheral nerves and heart, resulting in intractable peripheral sensory neuropathy, autonomic neuropathy, and/or cardiomyopathy.

Click to Enlarge

 

ATTR represents a major unmet medical need with significant morbidity and mortality. There are over 100 reported TTR mutations; the particular TTR mutation and the site of amyloid deposition determine the clinical manifestations of the disease whether it is predominantly symptoms of neuropathy or cardiomyopathy.

Specifically, hereditary ATTR amyloidosis with polyneuropathy (hATTR-PN), also known as familial amyloidotic polyneuropathy (FAP), is an inherited, progressive disease leading to death within 5 to 15 years. It is due to a mutation in the transthyretin (TTR) gene, which causes misfolded TTR proteins to accumulate as amyloid fibrils predominantly in peripheral nerves and other organs. hATTR-PN can cause sensory, motor, and autonomic dysfunction, resulting in significant disability and death.

It is estimated that hATTR-PN, also known as FAP, affects approximately 10,000 people worldwide.  Patients have a life expectancy of 5 to 15 years from symptom onset, and the only treatment options for early stage disease are liver transplantation and TTR stabilizers such as tafamidis (approved in Europe) and diflunisal.  Unfortunately liver transplantation has limitations, including limited organ availability as well as substantial morbidity and mortality. Furthermore, transplantation eliminates the production of mutant TTR but does not affect wild-type TTR, which can further deposit after transplantation, leading to cardiomyopathy and worsening of neuropathy. There is a significant need for novel therapeutics to treat patients who have inherited mutations in the TTR gene.

Our ATTR program is the lead effort in our Genetic Medicine Strategic Therapeutic Area (STAr) product development and commercialization strategy, which is focused on advancing innovative RNAi therapeutics toward genetically defined targets for the treatment of rare diseases with high unmet medical need.  We are developing patisiran (ALN-TTR02), an intravenously administered RNAi therapeutic, to treat the hATTR-PN form of the disease.

Patisiran for the Treatment hATTR-PN

APOLLO Phase 3 Trial

In 2012, Alnylam entered into an exclusive alliance with Genzyme, a Sanofi company, to develop and commercialize RNAi therapeutics, including patisiran and revusiran, for the treatment of ATTR amyloidosis in Japan and the broader Asian-Pacific region. In early 2014, this relationship was extended as a significantly broader alliance to advance RNAi therapeutics as genetic medicines. Under this new agreement, Alnylam will lead development and commercialization of patisiran in North America and Europe while Genzyme will develop and commercialize the product in the rest of world.

 

Hereditary ATTR Amyloidosis with Cardiomyopathy (hATTR-CM)

ATTR amyloidosis is a progressive, life-threatening disease caused by misfolded transthyretin (TTR) proteins that accumulate as amyloid fibrils in multiple organs, but primarily in the peripheral nerves and heart. ATTR amyloidosis can lead to significant morbidity, disability, and mortality. The TTR protein is produced primarily in the liver and is normally a carrier for retinol binding protein – one of the vehicles used to transport vitamin A around the body.  Mutations in the TTR gene cause misfolding of the protein and the formation of amyloid fibrils that typically contain both mutant and wild-type TTR that deposit in tissues such as the peripheral nerves and heart, resulting in intractable peripheral sensory neuropathy, autonomic neuropathy, and/or cardiomyopathy.

Click to Enlarge                            http://www.alnylam.com/web/assets/tetramer.jpg

ATTR represents a major unmet medical need with significant morbidity and mortality. There are over 100 reported TTR mutations; the particular TTR mutation and the site of amyloid deposition determine the clinical manifestations of the disease, whether it is predominantly symptoms of neuropathy or cardiomyopathy.

Specifically, hereditary ATTR amyloidosis with cardiomyopathy (hATTR-CM), also known as familial amyloidotic cardiomyopathy (FAC), is an inherited, progressive disease leading to death within 2 to 5 years. It is due to a mutation in the transthyretin (TTR) gene, which causes misfolded TTR proteins to accumulate as amyloid fibrils primarily in the heart. Hereditary ATTR amyloidosis with cardiomyopathy can result in heart failure and death.

While the exact numbers are not known, it is estimated hATTR-CM, also known as FAC affects at least 40,000 people worldwide.  hATTR-CM is fatal within 2 to 5 years of diagnosis and treatment is currently limited to supportive care.  Wild-type ATTR amyloidosis (wtATTR amyloidosis), also known as senile systemic amyloidosis, is a nonhereditary, progressive disease leading to death within 2 to 5 years. It is caused by misfolded transthyretin (TTR) proteins that accumulate as amyloid fibrils in the heart. Wild-type ATTR amyloidosis can cause cardiomyopathy and result in heart failure and death. There are no approved therapies for the treatment of hATTR-CM or SSA; hence there is a significant unmet need for novel therapeutics to treat these patients.

Our ATTR program is the lead effort in our Genetic Medicine Strategic Therapeutic Area (STAr) product development and commercialization strategy, which is focused on advancing innovative RNAi therapeutics toward genetically defined targets for the treatment of rare diseases with high unmet medical need.  We are developing revusiran (ALN-TTRsc), a subcutaneously administered RNAi therapeutic for the treatment of hATTR-CM.

Revusiran for the Treatment of hATTR-CM

ENDEAVOUR Phase 3 Trial

In 2012, Alnylam entered into an exclusive alliance with Genzyme, a Sanofi company, to develop and commercialize RNAi therapeutics, including patisiran and revusiran, for the treatment of ATTR amyloidosis in Japan and the broader Asian-Pacific region. In early 2014, this relationship was extended as a broader alliance to advance RNAi therapeutics as genetic medicines. Under this new agreement, Alnylam and Genzyme have agreed to co-develop and co-commercialize revusiran in North America and Europe, with Genzyme developing and commercializing the product in the rest of world. This broadened relationship on revusiran is aimed at expanding and accelerating the product’s global value.

Pre-Clinical Data and Advancement of ALN-TTRsc02 for Transthyretin-Mediated Amyloidosis

We presented pre-clinical data with ALN-TTRsc02, an investigational RNAi therapeutic targeting transthyretin (TTR) for the treatment of TTR-mediated amyloidosis (ATTR amyloidosis).  In pre-clinical studies, including those in non-human primates (NHPs), ALN-TTRsc02 achieved potent and highly durable knockdown of serum TTR of up to 99% with multi-month durability achieved after just a single dose, supportive of a potentially once quarterly dose regimen. Results from studies comparing TTR knockdown activity of ALN-TTRsc02 to that of revusiran showed that ALN-TTRsc02 has a markedly superior TTR knockdown profile.  Further, in initial rat toxicology studies, ALN-TTRsc02 was found to be generally well tolerated with no significant adverse events at doses as high as 100 mg/kg.

Read our press release

View the presentation

http://www.alnylam.com/product-pipeline/hereditary-attr-amyloidosis-with-cardiomyopathy/

 

Emerging Therapies for Transthyretin Cardiac Amyloidosis Could Herald a New Era for the Treatment of HFPEF

Oct 14, 2015   |  Adam Castano, MDDavid Narotsky, MDMathew S. Maurer, MD, FACC

http://www.acc.org/latest-in-cardiology/articles/2015/10/13/08/35/emerging-therapies-for-transthyretin-cardiac-amyloidosis#sthash.9xzc0rIe.dpuf

Heart failure with a preserved ejection fraction (HFPEF) is a clinical syndrome that has no pharmacologic therapies approved for this use to date. In light of failed medicines, cardiologists have refocused treatment strategies based on the theory that HFPEF is a heterogeneous clinical syndrome with different etiologies. Classification of HFPEF according to etiologic subtype may, therefore, identify cohorts with treatable pathophysiologic mechanisms and may ultimately pave the way forward for developing meaningful HFPEF therapies.1

A wealth of data now indicates that amyloid infiltration is an important mechanism underlying HFPEF. Inherited mutations in transthyretin cardiac amyloidosis (ATTRm) or the aging process in wild-type disease (ATTRwt) cause destabilization of the transthyretin (TTR) protein into monomers or oligomers, which aggregate into amyloid fibrils. These insoluble fibrils accumulate in the myocardium and result in diastolic dysfunction, restrictive cardiomyopathy, and eventual congestive heart failure (Figure 1). In an autopsy study of HFPEF patients, almost 20% without antemortem suspicion of amyloid had left ventricular (LV) TTR amyloid deposition.2 Even more resounding evidence for the contribution of TTR amyloid to HFPEF was a study in which 120 hospitalized HFPEF patients with LV wall thickness ≥12 mm underwent technetium-99m 3,3-diphosphono-1,2-propranodicarboxylic acid (99mTc-DPD) cardiac imaging,3,4 a bone isotope known to have high sensitivity and specificity for diagnosing TTR cardiac amyloidosis.5,6 Moderate-to-severe myocardial uptake indicative of TTR cardiac amyloid deposition was detected in 13.3% of HFPEF patients who did not have TTR gene mutations. Therefore, TTR cardiac amyloid deposition, especially in older adults, is not rare, can be easily identified, and may contribute to the underlying pathophysiology of HFPEF.

Figure 1

As no U.S. Food and Drug Administration-approved drugs are currently available for the treatment of HFPEF or TTR cardiac amyloidosis, the development of medications that attenuate or prevent TTR-mediated organ toxicity has emerged as an important therapeutic goal. Over the past decade, a host of therapies and therapeutic drug classes have emerged in clinical trials (Table 1), and these may herald a new direction for treating HFPEF secondary to TTR amyloid.

Table 1

TTR Silencers (siRNA and Antisense Oligonucleotides)

siRNA

Ribonucleic acid interference (RNAi) has surfaced as an endogenous cellular mechanism for controlling gene expression. Small interfering RNAs (siRNAs) delivered into cells can disrupt the production of target proteins.7,8 A formulation of lipid nanoparticle and triantennary N-acetylgalactosamine (GalNAc) conjugate that delivers siRNAs to hepatocytes is currently in clinical trials.9 Prior research demonstrated these GalNAc-siRNA conjugates result in robust and durable knockdown of a variety of hepatocyte targets across multiple species and appear to be well suited for suppression of TTR gene expression and subsequent TTR protein production.

The TTR siRNA conjugated to GalNAc, ALN-TTRSc, is now under active investigation as a subcutaneous injection in phase 3 clinical trials in patients with TTR cardiac amyloidosis.10 Prior phase 2 results demonstrated that ALN-TTRSc was generally well tolerated in patients with significant TTR disease burden and that it reduced both wild-type and mutant TTR gene expression by a mean of 87%. Harnessing RNAi technology appears to hold great promise for treating patients with TTR cardiac amyloidosis. The ability of ALN-TTRSc to lower both wild-type and mutant proteins may provide a major advantage over liver transplantation, which affects the production of only mutant protein and is further limited by donor shortage, cost, and need for immunosuppression.

Antisense Oligonucleotides

Antisense oligonucleotides (ASOs) are under clinical investigation for their ability to inhibit hepatic expression of amyloidogenic TTR protein. Currently, the ASO compound, ISIS-TTRRx, is under investigation in a phase 3 multicenter, randomized, double-blind, placebo-controlled clinical trial in patients with familial amyloid polyneuropathy (FAP).11 The primary objective is to evaluate its efficacy as measured by change in neuropathy from baseline relative to placebo. Secondary measures will evaluate quality of life (QOL), modified body mass index (mBMI) by albumin, and pharmacodynamic effects on retinol binding protein. Exploratory objectives in a subset of patients with LV wall thickness ≥13 mm without a history of persistent hypertension will examine echocardiographic parameters, N-terminal pro–B-type natriuretic peptide (NT-proBNP), and polyneuropathy disability score relative to placebo. These data will facilitate analysis of the effect of antisense oligonucleotide-mediated TTR suppression on the TTR cardiac phenotype with a phase 3 trial anticipated to begin enrollment in 2016.

TTR Stabilizers (Diflunisal, Tafamidis)

Diflunisal

Several TTR-stabilizing agents are in various stages of clinical trials. Diflunisal, a traditionally used and generically available nonsteroidal anti-inflammatory drug (NSAID), binds and stabilizes familial TTR variants against acid-mediated fibril formation in vitro and is now in human clinical trials.12,13 The use of diflunisal in patients with TTR cardiac amyloidosis is controversial given complication of chronic inhibition of cyclooxygenase (COX) enzymes, including gastrointestinal bleeding, renal dysfunction, fluid retention, and hypertension that may precipitate or exacerbate heart failure in vulnerable individuals.14-17 In TTR cardiac amyloidosis, an open-label cohort study suggested that low-dose diflunisal with careful monitoring along with a prophylactic proton pump inhibitor could be safely administered to compensated patients.18 An association was observed, however, between chronic diflunisal use and adverse changes in renal function suggesting that advanced kidney disease may be prohibitive in diflunisal therapy.In FAP patients with peripheral or autonomic neuropathy randomized to diflunisal or placebo, diflunisal slowed progression of neurologic impairment and preserved QOL over two years of follow-up.19 Echocardiography demonstrated cardiac involvement in approximately 50% of patients.20 Longer-term safety and efficacy data over an average 38 ± 31 months in 40 Japanese patients with hereditary ATTR amyloidosis who were not candidates for liver transplantation showed that diflunisal was mostly well tolerated.12 The authors cautioned the need for attentive monitoring of renal function and blood cell counts. Larger multicenter collaborations are needed to determine diflunisal’s true efficacy in HFPEF patients with TTR cardiac amyloidosis.

Tafamidis

Tafamidis is under active investigation as a novel compound that binds to the thyroxine-binding sites of the TTR tetramer, inhibiting its dissociation into monomers and blocking the rate-limiting step in the TTR amyloidogenesis cascade.21 The TTR compound was shown in an 18-month double-blind, placebo-controlled trial to slow progression of neurologic symptoms in patients with early-stage ATTRm due to the V30M mutation.22 When focusing on cardiomyopathy in a phase 2, open-label trial, tafamidis also appeared to effectively stabilize TTR tetramers in non-V30M variants, wild-type and V122I, as well as biochemical and echocardiographic parameters.23,24 Preliminary data suggests that clinically stabilized patients had shorter disease duration, lower cardiac biomarkers, less myocardial thickening, and higher EF than those who were not stabilized, suggesting early institution of therapy may be beneficial. A phase 3 trial has completed enrollment and will evaluate the efficacy, safety, and tolerability of tafamidis 20 or 80 mg orally vs. placebo.25 This will contribute to long-term safety and efficacy data needed to determine the therapeutic effects of tafamidis among ATTRm variants.

Amyloid Degraders (Doxycycline/TUDCA and Anti-SAP Antibodies)

Doxycycline/TUDCA

While silencer and stabilizer drugs are aimed at lowering amyloidogenic precursor protein production, they cannot remove already deposited fibrils in an infiltrated heart. Removal of already deposited fibrils by amyloid degraders would be an important therapeutic strategy, particularly in older adults with heavily infiltrated hearts reflected by thick walls, HFPEF, systolic heart failure, and restrictive cardiomyopathy. Combined doxycycline and tauroursodeoxycholic acid (TUDCA) disrupt TTR amyloid fibrils and appeared to have an acceptable safety profile in a small phase 2 open-label study among 20 TTR patients. No serious adverse reactions or clinical progression of cardiac or neuropathic involvement was observed over one year.26 An active phase 2, single-center, open-label, 12-month study will assess primary outcome measures including mBMI, neurologic impairment score, and NT-proBNP.27 Another phase 2 study is examining the tolerability and efficacy of doxycycline/TUDCA over an 18-month period in patients with TTR amyloid cardiomyopathy.28 Additionally, a study in patients with TTR amyloidosis is ongoing to determine the effect of doxycycline alone on neurologic function, cardiac biomarkers, echocardiographic parameters, modified body mass index, and autonomic neuropathy.29

Anti-SAP Antibodies

In order to safely clear established amyloid deposits, the role of the normal, nonfibrillar plasma glycoprotein present in all human amyloid deposits, serum amyloid P component (SAP), needs to be more clearly understood.30 In mice with amyloid AA type deposits, administration of antihuman SAP antibody triggered a potent giant cell reaction that removed massive visceral amyloid deposits without adverse effects.31 In humans with TTR cardiac amyloidosis, anti-SAP antibody treatments could be feasible because the bis-D proline compound, CPHPC, is capable of clearing circulating human SAP, which allow anti-SAP antibodies to reach residual deposited SAP. In a small, open-label, single-dose-escalation, phase 1 trial involving 15 patients with systemic amyloidosis, none of whom had clinical evidence of cardiac amyloidosis, were treated with CPHPC followed by human monoclonal IgG1 anti-SAP antibody.32 No serious adverse events were reported and amyloid deposits were cleared from the liver, kidney, and lymph node. Anti-SAP antibodies hold promise as a potential amyloid therapy because of their potential to target all forms of amyloid deposits across multiple tissue types.

Mutant or wild-type TTR cardiac amyloidoses are increasingly recognized as a cause of HFPEF. Clinicians need to be aware of this important HFPEF etiology because the diverse array of emerging disease-modifying agents for TTR cardiac amyloidosis in human clinical trials has the potential to herald a new era for the treatment of HFPEF.

References

  1. Maurer MS, Mancini D. HFpEF: is splitting into distinct phenotypes by comorbidities the pathway forward? J Am Coll Cardiol 2014;64:550-2.
  2. Mohammed SF, Mirzoyev SA, Edwards WD, et al. Left ventricular amyloid deposition in patients with heart failure and preserved ejection fraction. JACC Heart Fail 2014;2:113-22.
  3. González-López E, Gallego-Delgado M, Guzzo-Merello G, et al. Wild-type transthyretin amyloidosis as a cause of heart failure with preserved ejection fraction. Eur Heart J 2015.
  4. Castano A, Bokhari S, Maurer MS. Unveiling wild-type transthyretin cardiac amyloidosis as a significant and potentially modifiable cause of heart failure with preserved ejection fraction. Eur Heart J 2015 Jul 28. [Epub ahead of print]
  5. Rapezzi C, Merlini G, Quarta CC, et al. Systemic cardiac amyloidoses: disease profiles and clinical courses of the 3 main types. Circulation 2009;120:1203-12.
  6. Bokhari S, Castano A, Pozniakoff T, Deslisle S, Latif F, Maurer MS. (99m)Tc-pyrophosphate scintigraphy for differentiating light-chain cardiac amyloidosis from the transthyretin-related familial and senile cardiac amyloidoses. Circ Cardiovasc Imaging 2013;6:195-201.
  7. Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 1998;391:806-11.
  8. Elbashir SM, Harborth J, Lendeckel W, Yalcin A, Weber K, Tuschl T. Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 2001;411:494-8.
  9. Kanasty R, Dorkin JR, Vegas A, Anderson D. Delivery materials for siRNA therapeutics. Nature Mater 2013;12:967-77.
  10. U.S. National Institutes of Health. Phase 2 Study to Evaluate ALN-TTRSC in Patients With Transthyretin (TTR) Cardiac Amyloidosis (ClinicalTrials.gov website). 2014. Available at: https://www.clinicaltrials.gov/ct2/show/NCT01981837. Accessed 8/19/2015.
  11. U.S. National Institutes of Health. Efficacy and Safety of ISIS-TTRRx in Familial Amyloid Polyneuropathy (Clinical Trials.gov Website. 2013. Available at: http://www.clinicaltrials.gov/ct2/show/NCT01737398. Accessed 8/19/2015.
  12. Sekijima Y, Dendle MA, Kelly JW. Orally administered diflunisal stabilizes transthyretin against dissociation required for amyloidogenesis. Amyloid 2006;13:236-49.
  13. Tojo K, Sekijima Y, Kelly JW, Ikeda S. Diflunisal stabilizes familial amyloid polyneuropathy-associated transthyretin variant tetramers in serum against dissociation required for amyloidogenesis. Neurosci Res 2006;56:441-9.
  14. Epstein M. Non-steroidal anti-inflammatory drugs and the continuum of renal dysfunction. J Hypertens Suppl 2002;20:S17-23.
  15. Wallace JL. Pathogenesis of NSAID-induced gastroduodenal mucosal injury. Best Pract Res Clin Gastroenterol 2001;15:691-703.
  16. Mukherjee D, Nissen SE, Topol EJ. Risk of cardiovascular events associated with selective COX-2 inhibitors. JAMA 2001;286:954-9.
  17. Page J, Henry D. Consumption of NSAIDs and the development of congestive heart failure in elderly patients: an underrecognized public health problem. Arch Intern Med 2000;160:777-84.
  18. Castano A, Helmke S, Alvarez J, Delisle S, Maurer MS. Diflunisal for ATTR cardiac amyloidosis. Congest Heart Fail 2012;18:315-9.
  19. Berk JL, Suhr OB, Obici L, et al. Repurposing diflunisal for familial amyloid polyneuropathy: a randomized clinical trial. JAMA 2013;310:2658-67.
  20. Quarta CCF, Solomon RH Suhr SD, et al. The prevalence of cardiac amyloidosis in familial amyloidotic polyneuropathy with predominant neuropathy: The Diflunisal Trial. International Symposium on Amyloidosis 2014:88-9.
  21. Hammarstrom P, Jiang X, Hurshman AR, Powers ET, Kelly JW. Sequence-dependent denaturation energetics: A major determinant in amyloid disease diversity. Proc Natl Acad Sci U S A 2002;99 Suppl 4:16427-32.
  22. Coelho T, Maia LF, Martins da Silva A, et al. Tafamidis for transthyretin familial amyloid polyneuropathy: a randomized, controlled trial. Neurology 2012;79:785-92.
  23. Merlini G, Plante-Bordeneuve V, Judge DP, et al. Effects of tafamidis on transthyretin stabilization and clinical outcomes in patients with non-Val30Met transthyretin amyloidosis. J Cardiovasc Transl Res 2013;6:1011-20.
  24. Maurer MS, Grogan DR, Judge DP, et al. Tafamidis in transthyretin amyloid cardiomyopathy: effects on transthyretin stabilization and clinical outcomes. Circ Heart Fail 2015;8:519-26.
  25. U.S. National Institutes of Health. Safety and Efficacy of Tafamidis in Patients With Transthyretin Cardiomyopathy (ATTR-ACT) (ClinicalTrials.gov website). 2014. Available at: http://www.clinicaltrials.gov/show/NCT01994889. Accessed 8/19/2015.
  26. Obici L, Cortese A, Lozza A, et al. Doxycycline plus tauroursodeoxycholic acid for transthyretin amyloidosis: a phase II study. Amyloid 2012;19 Suppl 1:34-6.
  27. U.S. National Institutes of Health. Safety, Efficacy and Pharmacokinetics of Doxycycline Plus Tauroursodeoxycholic Acid in Transthyretin Amyloidosis (ClinicalTrials.gov website). 2011. Available at: http://www.clinicaltrials.gov/ct2/show/NCT01171859. Accessed 8/19/2015.
  28. U.S. National Institutes of Health. Tolerability and Efficacy of a Combination of Doxycycline and TUDCA in Patients With Transthyretin Amyloid Cardiomyopathy (ClinicalTrials.gov website). 2013. Available at: http://www.clinicaltrials.gov/ct2/show/NCT01855360. Accessed 8/19/2015.
  29. U.S. National Institutes of Health. Safety and Effect of Doxycycline in Patients With Amyloidosis (ClinicalTrials.gov website).2015. Available at: https://clinicaltrials.gov/ct2/show/NCT01677286. Accessed 8/19/2015.
  30. Pepys MB, Dash AC. Isolation of amyloid P component (protein AP) from normal serum as a calcium-dependent binding protein. Lancet 1977;1:1029-31.
  31. Bodin K, Ellmerich S, Kahan MC, et al. Antibodies to human serum amyloid P component eliminate visceral amyloid deposits. Nature 2010;468:93-7.
  32. Richards DB, Cookson LM, Berges AC, et al. Therapeutic Clearance of Amyloid by Antibodies to Serum Amyloid P Component. N Engl J Med 2015;373:1106-14.

 

The Acid-Mediated Denaturation Pathway of Transthyretin Yields a Conformational Intermediate That Can Self-Assemble into Amyloid

Zhihong Lai , Wilfredo Colón , and Jeffery W. Kelly *
Department of Chemistry, Texas A&M University, College Station, Texas 77843-3255
Biochemistry199635 (20), pp 6470–6482   http://dx.doi.org:/10.1021/bi952501g
Publication Date (Web): May 21, 1996  Copyright © 1996 American Chemical Society

Transthyretin (TTR) amyloid fibril formation is observed during partial acid denaturation and while refolding acid-denatured TTR, implying that amyloid fibril formation results from the self-assembly of a conformational intermediate. The acid denaturation pathway of TTR has been studied in detail herein employing a variety of biophysical methods to characterize the intermediate(s) capable of amyloid fibril formation. At physiological concentrations, tetrameric TTR remains associated from pH 7 to pH 5 and is incapable of amyloid fibril formation. Tetrameric TTR dissociates to a monomer in a process that is dependent on both pH and protein concentration below pH 5. The extent of amyloid fibril formation correlates with the concentration of the TTR monomer having an altered, but defined, tertiary structure over the pH range of 5.0−3.9. The inherent Trp fluorescence-monitored denaturation curve of TTR exhibits a plateau over the pH range where amyloid fibril formation is observed (albeit at a higher concentration), implying that a steady-state concentration of the amyloidogenic intermediate with an altered tertiary structure is being detected. Interestingly, 1-anilino-8-naphthalenesulfonate fluorescence is at a minimum at the pH associated with maximal amyloid fibril formation (pH 4.4), implying that the amyloidogenic intermediate does not have a high extent of hydrophobic surface area exposed, consistent with a defined tertiary structure. Transthyretin has two Trp residues in its primary structure, Trp-41 and Trp-79, which are conveniently located far apart in the tertiary structure of TTR. Replacement of each Trp with Phe affords two single Trp containing variants which were used to probe local pH-dependent tertiary structural changes proximal to these chromophores. The pH-dependent fluorescence behavior of the Trp-79-Phe mutant strongly suggests that Trp-41 is located near the site of the tertiary structural rearrangement that occurs in the formation of the monomeric amyloidogenic intermediate, likely involving the C-strand−loop−D-strand region. Upon further acidification of TTR (below pH 4.4), the structurally defined monomeric amyloidogenic intermediate begins to adopt alternative conformations that are not amyloidogenic, ultimately forming an A-state conformation below pH 3 which is also not amyloidogenic. In summary, analytical equilibrium ultracentrifugation, SDS−PAGE, far- and near-UV CD, fluorescence, and light scattering studies suggest that the amyloidogenic intermediate is a monomeric predominantly β-sheet structure having a well-defined tertiary structure.

 

Prevention of Transthyretin Amyloid Disease by Changing Protein Misfolding Energetics

Per Hammarström*, R. Luke Wiseman*, Evan T. Powers, Jeffery W. Kelly   + Author Affiliations

Science  31 Jan 2003; 299(5607):713-716   http://dx.doi.org:/10.1126/science.1079589

Genetic evidence suggests that inhibition of amyloid fibril formation by small molecules should be effective against amyloid diseases. Known amyloid inhibitors appear to function by shifting the aggregation equilibrium away from the amyloid state. Here, we describe a series of transthyretin amyloidosis inhibitors that functioned by increasing the kinetic barrier associated with misfolding, preventing amyloidogenesis by stabilizing the native state. The trans-suppressor mutation, threonine 119 → methionine 119, which is known to ameliorate familial amyloid disease, also functioned through kinetic stabilization, implying that this small-molecule strategy should be effective in treating amyloid diseases.

 

Rational design of potent human transthyretin amyloid disease inhibitors

Thomas Klabunde1,2, H. Michael Petrassi3, Vibha B. Oza3, Prakash Raman3, Jeffery W. Kelly3 & James C. Sacchettini1

Nature Structural & Molecular Biology 2000; 7: 312 – 321.                http://dx.doi.org:/10.1038/74082

The human amyloid disorders, familial amyloid polyneuropathy, familial amyloid cardiomyopathy and senile systemic amyloidosis, are caused by insoluble transthyretin (TTR) fibrils, which deposit in the peripheral nerves and heart tissue. Several nonsteroidal anti-inflammatory drugs and structurally similar compounds have been found to strongly inhibit the formation of TTR amyloid fibrils in vitro. These include flufenamic acid, diclofenac, flurbiprofen, and resveratrol. Crystal structures of the protein–drug complexes have been determined to allow detailed analyses of the protein–drug interactions that stabilize the native tetrameric conformation of TTR and inhibit the formation of amyloidogenic TTR. Using a structure-based drug design approach ortho-trifluormethylphenyl anthranilic acid and N-(meta-trifluoromethylphenyl) phenoxazine 4,6-dicarboxylic acid have been discovered to be very potent and specific TTR fibril formation inhibitors. This research provides a rationale for a chemotherapeutic approach for the treatment of TTR-associated amyloid diseases.

 

First European consensus for diagnosis, management, and treatment of transthyretin familial amyloid polyneuropathy

Adams, Davida; Suhr, Ole B.b; Hund, Ernstc; Obici, Laurad; Tournev, Ivailoe,f; Campistol, Josep M.g; Slama, Michel S.h; Hazenberg, Bouke P.i; Coelho, Teresaj; from the European Network for TTR-FAP (ATTReuNET)

Current Opin Neurol: Feb 2016; 29 – Issue – p S14–S26      http://dx.doi.org:/10.1097/WCO.0000000000000289

Purpose of review: Early and accurate diagnosis of transthyretin familial amyloid polyneuropathy (TTR-FAP) represents one of the major challenges faced by physicians when caring for patients with idiopathic progressive neuropathy. There is little consensus in diagnostic and management approaches across Europe.

Recent findings: The low prevalence of TTR-FAP across Europe and the high variation in both genotype and phenotypic expression of the disease means that recognizing symptoms can be difficult outside of a specialized diagnostic environment. The resulting delay in diagnosis and the possibility of misdiagnosis can misguide clinical decision-making and negatively impact subsequent treatment approaches and outcomes.

Summary: This review summarizes the findings from two meetings of the European Network for TTR-FAP (ATTReuNET). This is an emerging group comprising representatives from 10 European countries with expertise in the diagnosis and management of TTR-FAP, including nine National Reference Centres. The current review presents management strategies and a consensus on the gold standard for diagnosis of TTR-FAP as well as a structured approach to ongoing multidisciplinary care for the patient. Greater communication, not just between members of an individual patient’s treatment team, but also between regional and national centres of expertise, is the key to the effective management of TTR-FAP.

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Transthyretin familial amyloid polyneuropathy (TTR-FAP) is a highly debilitating and irreversible neurological disorder presenting symptoms of progressive sensorimotor and autonomic neuropathy [1▪,2▪,3]. TTR-FAP is caused by misfolding of the transthyretin (TTR) protein leading to protein aggregation and the formation of amyloid fibrils and, ultimately, to amyloidosis (commonly in the peripheral and autonomic nervous system and the heart) [4,5]. TTR-FAP usually proves fatal within 7–12 years from the onset of symptoms, most often due to cardiac dysfunction, infection, or cachexia [6,7▪▪].

The prevalence and disease presentation of TTR-FAP vary widely within Europe. In endemic regions (northern Portugal, Sweden, Cyprus, and Majorca), patients tend to present with a distinct genotype in large concentrations, predominantly a Val30Met substitution in the TTR gene [8–10]. In other areas of Europe, the genetic footprint of TTR-FAP is more varied, with less typical phenotypic expression [6,11]. For these sporadic or scattered cases, a lack of awareness among physicians of variable clinical features and limited access to diagnostic tools (i.e., pathological studies and genetic screening) can contribute to high rates of misdiagnosis and poorer patient outcomes [1▪,11]. In general, early and late-onset variants of TTR-FAP, found within endemic and nonendemic regions, present several additional diagnostic challenges [11,12,13▪,14].

Delay in the time to diagnosis is a major obstacle to the optimal management of TTR-FAP. With the exception of those with a clearly diagnosed familial history of FAP, patients still invariably wait several years between the emergence of first clinical signs and accurate diagnosis [6,11,14]. The timely initiation of appropriate treatment is particularly pertinent, given the rapidity and irreversibility with which TTR-FAP can progress if left unchecked, as well as the limited effectiveness of available treatments during the later stages of the disease [14]. This review aims to consolidate the existing literature and present an update of the best practices in the management of TTR-FAP in Europe. A summary of the methods used to achieve a TTR-FAP diagnosis is presented, as well as a review of available treatments and recommendations for treatment according to disease status.

Patients with TTR-FAP can present with a range of symptoms [11], and care should be taken to acquire a thorough clinical history of the patient as well as a family history of genetic disease. Delay in diagnosis is most pronounced in areas where TTR-FAP is not endemic or when there is no positive family history [1▪]. TTR-FAP and TTR-familial amyloid cardiomyopathy (TTR-FAC) are the two prototypic clinical disease manifestations of a broader disease spectrum caused by an underlying hereditary ATTR amyloidosis [19]. In TTR-FAP, the disease manifestation of neuropathy is most prominent and definitive for diagnosis, whereas cardiomyopathy often suggests TTR-FAC. However, this distinction is often superficial because cardiomyopathy, autonomic neuropathy, vitreous opacities, kidney disease, and meningeal involvement all may be present with varying severity for each patient with TTR-FAP.

Among early onset TTR-FAP with usually positive family history, symptoms of polyneuropathy present early in the disease process and usually predominate throughout the progression of the disease, making neurological testing an important diagnostic aid [14]. Careful clinical examination (e.g., electromyography with nerve conduction studies and sympathetic skin response, quantitative sensation test, quantitative autonomic test) can be used to detect, characterize, and scale the severity of neuropathic abnormalities involving small and large nerve fibres [10]. Although a patient cannot be diagnosed definitively with TTR-FAP on the basis of clinical presentation alone, symptoms suggesting the early signs of peripheral neuropathy, autonomic dysfunction, and cardiac conduction disorders or infiltrative cardiomyopathy are all indicators that further TTR-FAP diagnostic investigation is warranted. Late-onset TTR-FAP often presents as sporadic cases with distinct clinical features (e.g., milder autonomic dysfunction) and can be more difficult to diagnose than early-onset TTR-FAP (Table 2) [1▪,11,12,13▪,14,20].

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Genetic testing is carried out to allow detection of specific amyloidogenic TTR mutations (Table 1), using varied techniques depending on the expertise and facilities available in each country (Table S2, http://links.lww.com/CONR/A39). A targeted approach to detect a specific mutation can be used for cases belonging to families with previous diagnosis. In index cases of either endemic and nonendemic regions that do not have a family history of disease, are difficult to confirm, and have atypical symptoms, TTR gene sequencing is required for the detection of both predicted and new amyloidogenic mutations [26,27].

Following diagnosis, the neuropathy stage and systemic extension of the disease should be determined in order to guide the next course of treatment (Table 4) [3,30,31]. The three stages of TTR-FAP severity are graded according to a patient’s walking disability and degree of assistance required [30]. Systemic assessment, especially of the heart, eyes, and kidney, is also essential to ensure all aspects of potential impact of the disease can be detected [10].

Table 4

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The goals of cardiac investigations are to detect serious conduction disorders with the risk of sudden death and infiltrative cardiomyopathy. Electrocardiograms (ECG), Holter-ECG, and intracardiac electrophysiology study are helpful to detect conduction disorders. Echocardiograms, cardiac magnetic resonance imaging, scintigraphy with bone tracers, and biomarkers (e.g., brain natriuretic peptide, troponin) can all help to diagnose infiltrative cardiomyopathy[10]. An early detection of cardiac abnormalities has obvious benefits to the patient, given that the prophylactic implantation of pacemakers was found to prevent 25% of major cardiac events in TTR-FAP patients followed up over an average of 4 years [32▪▪]. Assessment of cardiac denervation with 123-iodine meta-iodobenzylguanidine is a powerful prognostic marker in patients diagnosed with FAP [33].

…..

Tafamidis

Tafamidis is a first-in-class therapy that slows the progression of TTR amyloidogenesis by stabilizing the mutant TTR tetramer, thereby preventing its dissociation into monomers and amyloidogenic and toxic intermediates [55,56]. Tafamidis is currently indicated in Europe for the treatment of TTR amyloidosis in adult patients with stage I symptomatic polyneuropathy to delay peripheral neurological impairment [57].

In an 18-month, double-blind, placebo-controlled study of patients with early-onset Val30Met TTR-FAP, tafamidis was associated with a 52% lower reduction in neurological deterioration (P = 0.027), a preservation of nerve function, and TTR stabilization versus placebo [58▪▪]. However, only numerical differences were found for the coprimary endpoints of neuropathy impairment [neuropathy impairment score in the lower limb (NIS-LL) responder rates of 45.3% tafamidis vs 29.5% placebo; P = 0.068] and quality of life scores [58▪▪]. A 12-month, open-label extension study showed that the reduced rates of neurological deterioration associated with tafamidis were sustained over 30 months, with earlier initiation of tafamidis linking to better patient outcomes (P = 0.0435) [59▪]. The disease-slowing effects of tafamidis may be dependent on the early initiation of treatment. In an open-label study with Val30Met TTR-FAP patients with late-onset and advanced disease (NIS-LL score >10, mean age 56.4 years), NIS-LL and disability scores showed disease progression despite 12 months of treatment with tafamidis, marked by a worsening of neuropathy stage in 20% and the onset of orthostatic hypotension in 22% of patients at follow-up [60▪].

Tafamidis is not only effective in patients exhibiting the Val30Met mutation; it also has proven efficacy, in terms of TTR stabilization, in non-Val30Met patients over 12 months [61]. Although tafamidis has demonstrated safe use in patients with TTR-FAP, care should be exercised when prescribing to those with existing digestive problems (e.g., diarrhoea, faecal incontinence) [60▪].

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Diflunisal

Diflunisal is a nonsteroidal anti-inflammatory drug (NSAID) that, similar to tafamidis, slows the rate of amyloidogenesis by preventing the dissociation, misfolding, and misassembly of the mutated TTR tetramer [62,63]. Off-label use has been reported for patients with stage I and II disease, although diflunisal is not currently licensed for the treatment of TTR-FAP.

Evidence for the clinical effectiveness of diflunisal in TTR-FAP derives from a placebo-controlled, double-blind, 24-month study in 130 patients with clinically detectable peripheral or autonomic neuropathy[64▪]. The deterioration in NIS scores was significantly more pronounced in patients receiving placebo compared with those taking diflunisal (P = 0.001), and physical quality of life measures showed significant improvement among diflunisal-treated patients (P = 0.001). Notable during this study was the high rate of attrition in the placebo group, with 50% more placebo-treated patients dropping out of this 2-year study as a result of disease progression, advanced stage of the disease, and varied mutations.

One retrospective analysis of off-label use of diflunisal in patients with TTR-FAP reported treatment discontinuation in 57% of patients because of adverse events that were largely gastrointestinal [65]. Conclusions on the safety of diflunisal in TTR-FAP will depend on further investigations on the impact of known cardiovascular and renal side-effects associated with the NSAID drug class [66,67].

 

 

 

 

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Signaling through the T Cell Receptor (TCR) Complex and the Co-stimulatory Receptor CD28

Curator: Larry H. Bernstein, MD, FCAP

 

 

New connections: T cell actin dynamics

Fluorescence microscopy is one of the most important tools in cell biology research because it provides spatial and temporal information to investigate regulatory systems inside cells. This technique can generate data in the form of signal intensities at thousands of positions resolved inside individual live cells. However, given extensive cell-to-cell variation, these data cannot be readily assembled into three- or four-dimensional maps of protein concentration that can be compared across different cells and conditions. We have developed a method to enable comparison of imaging data from many cells and applied it to investigate actin dynamics in T cell activation. Antigen recognition in T cells by the T cell receptor (TCR) is amplified by engagement of the costimulatory receptor CD28. We imaged actin and eight core actin regulators to generate over a thousand movies of T cells under conditions in which CD28 was either engaged or blocked in the context of a strong TCR signal. Our computational analysis showed that the primary effect of costimulation blockade was to decrease recruitment of the activator of actin nucleation WAVE2 (Wiskott-Aldrich syndrome protein family verprolin-homologous protein 2) and the actin-severing protein cofilin to F-actin. Reconstitution of WAVE2 and cofilin activity restored the defect in actin signaling dynamics caused by costimulation blockade. Thus, we have developed and validated an approach to quantify protein distributions in time and space for the analysis of complex regulatory systems.

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Triple-Color FRET Analysis Reveals Conformational Changes in the WIP-WASp Actin-Regulating Complex

 

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T cell activation by antigens involves the formation of a complex, highly dynamic, yet organized signaling complex at the site of the T cell receptors (TCRs). Srikanth et al. found that the lymphocyte-specific large guanosine triphosphatase of the Rab family CRACR2A-a associated with vesicles near the Golgi in unstimulated mouse and human CD4+ T cells. Upon TCR activation, these vesicles moved to the immunological synapse (the contact region between a T cell and an antigen-presenting cell). The guanine nucleotide exchange factor Vav1 at the TCR complex recruited CRACR2A-a to the complex. Without CRACR2A-a, T cell activation was compromised because of defective calcium and kinase signaling.

More than 60 members of the Rab family of guanosine triphosphatases (GTPases) exist in the human genome. Rab GTPases are small proteins that are primarily involved in the formation, trafficking, and fusion of vesicles. We showed that CRACR2A (Ca2+ release–activated Ca2+ channel regulator 2A) encodes a lymphocyte-specific large Rab GTPase that contains multiple functional domains, including EF-hand motifs, a proline-rich domain (PRD), and a Rab GTPase domain with an unconventional prenylation site. Through experiments involving gene silencing in cells and knockout mice, we demonstrated a role for CRACR2A in the activation of the Ca2+ and c-Jun N-terminal kinase signaling pathways in response to T cell receptor (TCR) stimulation. Vesicles containing this Rab GTPase translocated from near the Golgi to the immunological synapse formed between a T cell and a cognate antigen-presenting cell to activate these signaling pathways. The interaction between the PRD of CRACR2A and the guanidine nucleotide exchange factor Vav1 was required for the accumulation of these vesicles at the immunological synapse. Furthermore, we demonstrated that GTP binding and prenylation of CRACR2A were associated with its localization near the Golgi and its stability. Our findings reveal a previously uncharacterized function of a large Rab GTPase and vesicles near the Golgi in TCR signaling. Other GTPases with similar domain architectures may have similar functions in T cells.

 

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Novel Discoveries in Molecular Biology and Biomedical Science, 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)

Novel Discoveries in Molecular Biology and Biomedical Science

Curator: Larry H. Bernstein, MD, FCAP

 

UPDATED on 6/1/2016  

The following is a collection of current articles on noncoding DNA, synthetic genome engineering, protein regulation of apoptosis, drug design, and geometrics.

 

No longer ‘junk DNA’ — shedding light on the ‘dark matter’ of the genome

A new tool called “LIGR-Seq” enables scientists to explore in depth what non-coding RNAs actually do in human cells   May 23, 2016

http://www.kurzweilai.net/no-longer-junk-dna-shedding-light-on-the-dark-matter-of-the-genome

http://www.kurzweilai.net/images/LIGR-seq-method.png

he LIGR-seq method for global-scale mapping of RNA-RNA interactions in vivo to reveal unexpected functions for uncharacterized RNAs that act via base-pairing interactions (credit: University of Toronto)

What used to be dismissed by many as “junk DNA” has now become vitally important, as accelerating genomic data points to the importance of non-coding RNAs (ncRNAs) — a genome’s messages that do not specifically code for proteins — in development and disease.

But our progress in understanding these molecules has been slow because of the lack of technologies that allow for systematic mapping of their functions.

Now, professor Benjamin Blencowe’s team at the University of Toronto’s Donnelly Centre has developed a method called “LIGR-seq” that enables scientists to explore in depth what ncRNAs do in human cells.

The study, described in Molecular Cell, was published on May 19, along with two other papers, in Molecular Cell and Cell, respectively, from Yue Wan’s group at the Genome Institute of Singapore and Howard Chang’s group at Stanford University in California, who developed similar methods to study RNAs in different organisms.

So what exactly do ncRNAs do?

http://www.kurzweilai.net/images/ncRNA.png

mRNAs vs. ncRNAs (credit: Thomas Shafee/CC)

Of the 3 billion letters in the human genome, only two per cent make up the protein-coding genes. The genes are copied, or transcribed, into messenger RNA (mRNA) molecules, which provide templates for building proteins that do most of the work in the cell. Much of the remaining 98 per cent of the genome was initially considered by some as lacking in functional importance. However, large swaths of the non-coding genome — between half and three quarters of it — are also copied into RNA.

So then what might the resulting ncRNAs do? That depends on whom you ask. Some researchers believe that most ncRNAs have no function, that they are just a by-product of the genome’s powerful transcription machinery that makes mRNA. However, it is emerging that many ncRNAs do have important roles in gene regulation — some ncRNAs act as carriages for shuttling the mRNAs around the cell, or provide a scaffold for other proteins and RNAs to attach to and do their jobs.

But the majority of available data has trickled in piecemeal or through serendipitous discovery. And with emerging evidence that ncRNAs could drive disease progression, such as cancer metastasis, there was a great need for a technology that would allow a systematic functional analysis of ncRNAs.

Up until now, with existing methods, you had to know what you are looking for because they all require you to have some information about the RNA of interest. The power of our method is that you don’t need to preselect your candidates; you can see what’s occurring globally in cells, and use that information to look at interesting things we have not seen before and how they are affecting biology,” says Eesha Sharma, a PhD candidate in Blencowe’s group who, along with postdoctoral fellow Tim Sterne-Weiler, co-developed the method.

A new ncRNA identification tool

http://www.kurzweilai.net/images/rna-rna-interactions.jpg

The human RNA-RNA interactome, showing interactions detected by LIGR-seq (credit: University of Toronto)

The new ‘‘LIGation of interacting RNA and high-throughput sequencing’’ (LIGR-seq) tool captures interactions between different RNA molecules. When two RNA molecules have matching sequences — strings of letters copied from the DNA blueprint — they will stick together like Velcro. With LIGR-seq, the paired RNA structures are removed from cells and analyzed by state-of-the-art sequencing methods to precisely identify the RNAs that are stuck together.

Most researchers in the life sciences agree that there’s an urgent need to understand what ncRNAs do. This technology will open the door to developing a new understanding of ncRNA function,” says Blencowe, who is also a professor in the Department of Molecular Genetics.

Not having to rely on pre-existing knowledge will boost the discovery of RNA pairs that have never been seen before. Scientists can also, for the first time, look at RNA interactions as they occur in living cells, in all their complexity, unlike in the juices of mashed up cells that they had to rely on before. This is a bit like moving on to explore marine biology from collecting shells on the beach to scuba-diving among the coral reefs, where the scope for discovery is so much bigger.

Actually, ncRNAs come in multiple flavors: there’s rRNA, tRNA, snRNA, snoRNA, piRNA, miRNA, and lncRNA, to name a few, where prefixes reflect the RNA’s place in the cell or some aspect of its function. But the truth is that no one really knows the extent to which these ncRNAs control what goes on in the cell, or how they do this.

Discoveries

Nonetheless, the new technology developed by Blencowe’s group has been able to pick up new interactions involving all classes of RNAs and has already revealed some unexpected findings.

The team discovered new roles for small nucleolar RNAs (snoRNAs), which normally guide chemical modifications of other ncRNAs. It turns out that some snoRNAs can also regulate stability of a set of protein-coding mRNAs. In this way, snoRNAs can also directly influence which proteins are made, as well as their abundance, adding a new level of control in cell biology.

And this is only the tip of the iceberg; the researchers plan to further develop and apply their technology to investigate the ncRNAs in different settings.

“We would like to understand how ncRNAs function during development. We are particularly interested in their role in the formation of neurons. But we will also use our method to discover and map changes in RNA-RNA interactions in the context of human diseases,” says Blencowe.

Abstract of Global Mapping of Human RNA-RNA Interactions

The majority of the human genome is transcribed into non-coding (nc)RNAs that lack known biological functions or else are only partially characterized. Numerous characterized ncRNAs function via base pairing with target RNA sequences to direct their biological activities, which include critical roles in RNA processing, modification, turnover, and translation. To define roles for ncRNAs, we have developed a method enabling the global-scale mapping of RNA-RNA duplexes crosslinked in vivo, “LIGation of interacting RNA followed by high-throughput sequencing” (LIGR-seq). Applying this method in human cells reveals a remarkable landscape of RNA-RNA interactions involving all major classes of ncRNA and mRNA. LIGR-seq data reveal unexpected interactions between small nucleolar (sno)RNAs and mRNAs, including those involving the orphan C/D box snoRNA, SNORD83B, that control steady-state levels of its target mRNAs. LIGR-seq thus represents a powerful approach for illuminating the functions of the myriad of uncharacterized RNAs that act via base-pairing interactions.

references:

 

Venter’s Research Team Creates an Artificial Cell and Reports That 32% of Genes Are Life-Essential but Contain Unknown Functions
http://www.radmailer.com/t/r-l-sttullk-ykogyktt-k/
May 27, 2016

Understanding the unknown functions of these genes may lead to the creation of new diagnostic tests for clinical laboratories and anatomic pathology groups

Once again, J. Craig Venter, PhD, is charting new ground in gene sequencing andgenomic science. This time his research team has built upon the first synthetic cell they created in 2010 to build a more sophisticated synthetic cell. Their findings from this work may give pathologists and medical laboratory scientists new tools to diagnose disease.

Recently the research team at the J. Craig Venter Institute (JCVI) and Synthetic Genomics, Inc. (SGI) published their latest findings. Among the things they learned is that science still does not understand the functions of about a third of the genes required for their synthetic cells to function.

JCVI-syn3.0 Could Radically Alter Understanding of Human Genome

Based in La Jolla, Calif., and Rockville, Md., JCVI is a not-for-profit research institute aiming to advance genomics. Building upon its first synthetic cell—Mycoplasma mycoides (M. mycoides) JCVI-syn1.0, which JCVI constructed in 2010—the same team of scientists created the first minimal synthetic bacterial cell, which they calledJCVI-syn3.0. This new artificial cell contains 531,560 base pairs and just 473 genes, which means it is the smallest genome of any organism that can be grown in laboratory media, according to a JCVI-SGI statement.

For pathologists and medical laboratory leaders, the creation of a synthetic life form is a milestone toward better understanding genome sequencing and how this new knowledge may help advance both diagnostics and therapeutics.

“What we’ve done is important because it is a step toward completely understanding how a living cell works,” Clyde Hutchison III, PhD, told New Scientist. “If we can really understand how the cell works, then we will be able to design cells efficiently for the production of pharmaceutical and other useful products.” Hutchison is Professor Emeritus of Microbiology and Immunology at the University of North Carolina at Chapel Hill, Distinguished Professor at the J. Craig Venter Institute, a member of the National Academy of Sciences, and a fellow of the American Academy of Arts and Sciences.

Click here to see images

Clyde Hutchison, III, PhD (above), Professor Emeritus of Microbiology and Immunology at the University of North Carolina at Chapel Hill and Distinguished Professor at the J. Craig Venter Institute, stated that his team’s “goal is to have a cell for which the precise biological function of every gene is known.” (Photo credit: JCVI.)

Understanding a Gene’s True Purpose

According to the JCVI researchers, 149 genes have no known purpose. They are, however, necessary for life and health.

“We know about two-thirds of the essential biology, and we’re missing a third,” stated J. Craig Venter, PhD, Founder and CEO of JCVI, in a story published by MedPage Today.

This knowledge is based upon decades of research. JCVI seeks to create a minimal cell operating system to understand biology, while also providing what the JCVI statement called a “chassis for use in industrial applications.”

What Do these Genes Do Anyway?

The JCVI team found that among most genes’ biological functions:

“JCVI-syn3.0 is a working approximation of a minimal cellular genome—a compromise between a small genome size and a workable growth rate for an experimental organism. It retains almost all the genes that are involved in the synthesis and processing of macromolecules. Unexpectedly, it also contains 149 genes with unknown biological functions, suggesting the presence of undiscovered functions that are essential for life,” the researchers told the journal Science.

More research is needed, the scientists say, into the 149 genes that appear to lack specific biologic functions.

Unlocking Mystery of the 149 Genes Could Lead to Advances in Genomic Science

“Finding so many genes without a known function is unsettling, but it’s exciting because it’s left us with much still to learn. It’s like the ‘dark matter’ of biology,” said Alistair Elfick, PhD, Chair of Synthetic Biological Engineering, University of Edinburgh, UK, in the New Scientist article.

Studies such as JCVI’s research is key to broadening understanding and framing appropriate questions about scientific, ethical, and economic implications of synthetic biology.

The creation of a synthetic cell will have a profound and positive impact on understanding of biology and how life works, JCVI said.

Such research may inspire new whole genome synthesis tools and semi-automated processes that could dramatically affect clinical laboratory procedures. It also could lead to new techniques and tools for advanced vaccine and pharmaceuticals, JCVI pointed out.

—Donna Marie Pocius

Related Information:

First Minimal Synthetic Bacterial Cell Designed and Constructed by Scientists at Venter Institute and Synthetic Genomics, Inc.

 

CRISPR Versatility Inspires Molecular Biology Innovation

GEN Tech Focus: CRISPR/Gene Editing
           
No single technique has set the molecular biology field ablaze with excitement and potential like the CRISPR-Cas9 genome editing system has following its introduction only a few short years ago. The following articles represent the flexibility of this technique to potentially treat a host of genetic disorders and possibly even prevent the onset of disease.

 

CRISPR Moves from Butchery to Surgery

 

Scientists recently convened at the CRISPR Precision Gene Editing Congress, held in Boston, to discuss the new technology. As with any new technique, scientists have discovered that CRISPR comes with its own set of challenges, and the Congress focused its discussion around improving specificity, efficiency, and delivery.

 

New CRISPR System Targets Both DNA and RNA

With a staggering number of papers published in the past several years involving the characterization and use of the CRISPR/Cas9 gene editing system, it is surprising that researchers are still finding new features of the versatile molecular scissor enzyme.

 

High-Fidelity CRISPR-Cas9 Nucleases Virtually Free of Off-Target Noise

If a Cas9 nuclease variant could be engineered that was less grabby, it might loosen its grip on DNA sequences throughout the genome—except those sequences representing on-target sites. That’s the assumption that guided a new investigation by researchers at Massachusetts General Hospital.

 

CRISPR Works Well but Needs Upgrades

The gene-editing technology known as CRISPR-Cas9 is starting to raise expectations in the therapeutic realm. In fact, CRISPR-Cas9 and other CRISPR systems are moving so close to therapeutic uses that the technology’s ethical implications are starting to attract notice.

 

A Guide to CRISPR Gene Activation
http://www.technologynetworks.com/rnai/news.aspx?ID=191776

Published: Tuesday, May 24, 2016
A comparison of synthetic gene-activating Cas9 proteins can help guide research and development of therapeutic approaches.

The CRISPR-Cas9 system has come to be known as the quintessential tool that allows researchers to edit the DNA sequences of many organisms and cell types. However, scientists are also increasingly recognizing that it can be used to activate the expression of genes. To that end, they have built a number of synthetic gene activating Cas9 proteins to study gene functions or to compensate for insufficient gene expression in potential therapeutic approaches.

“The possibility to selectively activate genes using various engineered variants of the CRISPR-Cas9 system left many researchers questioning which of the available synthetic activating Cas9 proteins to use for their purposes. The main challenge was that all had been uniquely designed and tested in different settings; there was no side-by-side comparison of their relative potentials,” said George Church, Ph.D., who is Core Faculty Member at the Wyss Institute for Biologically Inspired Engineering at Harvard University, leader of its Synthetic Biology Platform, and Professor of Genetics at Harvard Medical School. “We wanted to provide that side-by-side comparison to the biomedical research community.”

In a study published on 23 May in Nature Methods, the Wyss Institute team reports how it rigorously compared and ranked the most commonly used artificial Cas9 activators in different cell types from organisms including humans, mice and flies. The findings provide a valuable guide to researchers, allowing them to streamline their endeavors.

The team also included Wyss Core Faculty Member James Collins, Ph.D., who also is the Termeer Professor of Medical Engineering & Science and Professor of Biological Engineering at the Massachusetts Institute of Technology (MIT)’s Department of Biological Engineering and Norbert Perrimon, Ph.D., a Professor of Genetics at Harvard Medical School.

Gene activating Cas9 proteins are fused to variable domains borrowed from proteins with well-known gene activation potentials and engineered so that the DNA editing ability is destroyed. In some cases, the second component of the CRISPR-Cas9 system, the guide RNA that targets the complex to specific DNA sequences, also has been engineered to bind gene-activating factors.

“We first surveyed seven advanced Cas9 activators, comparing them to each other and the original Cas9 activator that served to provide proof-of-concept for the gene activation potential of CRISPR-Cas9. Three of them, provided much higher gene activation than the other candidates while maintaining high specificities toward their target genes,” said Marcelle Tuttle, Research Fellow at the Wyss and a co-lead author of the study.

The team went on to show that the three top candidates were comparable in driving the highest level of gene expression in cells from humans, mice and fruit flies, irrespective of their tissue and developmental origins. The researchers also pinpointed ways to further maximize gene activation employing the three leading candidates.

“In some cases, maximum possible activation of a target gene is necessary to achieve a cellular or therapeutic effect. We managed to cooperatively enhance expression of specific genes when we targeted them with three copies of a top performing activator using three different guide RNAs,” said Alejandro Chavez, Ph.D., a Postdoctoral Fellow and the study’s co-first author.

“The ease of use of CRISPR-Cas9 offers enormous potential for development of genome therapeutics. This study provides valuable new design criteria that will help enable synthetic biologists and bioengineers to develop more effective targeted genome engineering technologies in the future,” said Wyss Institute Founding Director Donald Ingber, M.D., Ph.D., who is the Judah Folkman Professor of Vascular Biology at Harvard Medical School and the Vascular Biology Program at Boston Children’s Hospital, and also Professor of Bioengineering at the Harvard John A. Paulson School of Engineering and Applied Sciences.

 

Engineering T Cells to Functionally Cure HIV-1 Infection

Rachel S Leibman and James L Riley
Molecular Therapy (21 April 2015) |    http://dx.doi.org:/10.1038/mt.2015.70

Despite the ability of antiretroviral therapy to minimize human immunodeficiency virus type 1 (HIV-1) replication and increase the duration and quality of patients’ lives, the health consequences and financial burden associated with the lifelong treatment regimen render a permanent cure highly attractive. Although T cells play an important role in controlling virus replication, they are themselves targets of HIV-mediated destruction. Direct genetic manipulation of T cells for adoptive cellular therapies could facilitate a functional cure by generating HIV-1–resistant cells, redirecting HIV-1–specific immune responses, or a combination of the two strategies. In contrast to a vaccine approach, which relies on the production and priming of HIV-1–specific lymphocytes within a patient’s own body, adoptive T-cell therapy provides an opportunity to customize the therapeutic T cells prior to administration. However, at present, it is unclear how to best engineer T cells so that sustained control over HIV-1 replication can be achieved in the absence of antiretrovirals. This review focuses on T-cell gene-engineering and gene-editing strategies that have been performed in efforts to inhibit HIV-1 replication and highlights the requirements for a successful gene therapy–mediated functional cure.

 

Automated top-down design technique simplifies creation of DNA origami nanostructures

http://www.kurzweilai.net/automated-top-down-design-technique-simplifies-creation-of-dna-origami-nanostructures

Nanoparticles for drug delivery and cell targeting, nanoscale robots, custom-tailored optical devices, and DNA as a storage medium are among the possible applications

May 27, 2016

The boldfaced line, known as a spanning tree, follows the desired geometric shape of the target DNA origami design method, touching each vertex just once. A spanning tree algorithm is used to map out the proper routing path for the DNA strand. (credit: Public Domain)

MITBaylor College of Medicine, and Arizona State University Biodesign Institute researchers have developed a radical new top-down DNA origami* design method based on a computer algorithm that allows for creating designs for DNA nanostructures by simply inputting a target shape.

DNA origami (using DNA to design and build geometric structures) has already proven wildly successful in creating myriad forms in 2- and 3- dimensions, which conveniently self-assemble when the designed DNA sequences are mixed together. The tricky part is preparing the proper DNA sequence and routing design for scaffolding and staple strands to achieve the desired target structure. Typically, this is painstaking work that must be carried out manually.

The new algorithm, which is reported together with a novel synthesis approach in the journal Science, promises to eliminate all that and expands the range of possible applications of DNA origami in biomolecular science and nanotechnology. Think nanoparticles for drug delivery and cell targeting, nanoscale robots in medicine and industry, custom-tailored optical devices, and most interesting: DNA as a storage medium, offering retention times in the millions of years.**

 

Shape-shifting, top-down software

Unlike traditional DNA origami, in which the structure is built up manually by hand, the team’s radical top-down autonomous design method begins with an outline of the desired form and works backward in stages to define the required DNA sequence that will properly fold to form the finished product.

“The Science paper turns the problem around from one in which an expert designs the DNA needed to synthesize the object, to one in which the object itself is the starting point, with the DNA sequences that are needed automatically defined by the algorithm,” said Mark Bathe, an associate professor of biological engineering at MIT, who led the research. “Our hope is that this automation significantly broadens participation of others in the use of this powerful molecular design paradigm.”

The algorithm, which is known as DAEDALUS (DNA Origami Sequence Design Algorithm for User-defined Structures) after the Greek craftsman and artist who designed labyrinths that resemble origami’s complex scaffold structures, can build any type of 3-D shape, provided it has a closed surface. This can include shapes with one or more holes, such as a torus.

A simplified version of the  top-down procedure used to design scaffolded DNA origami nanostructures. It starts with a polygon corresponding to the target shape. Software translates a wireframe version of this structure into a plan for routing DNA scaffold and staple strands. That enables a 3D DNA-based atomic-level structural model that is then validated using 3D cryo-EM reconstruction. (credit: adapted from Biodesign Institute images)

With the new technique, the target geometric structure is first described in terms of a wire mesh made up of polyhedra, with a network of nodes and edges. A DNA scaffold using strands of custom length and sequence is generated, using a “spanning tree” algorithm — basically a map that will automatically guide the routing of the DNA scaffold strand through the entire origami structure, touching each vertex in the geometric form once. Complementary staple strands are then assigned and the final DNA structural model or nanoparticle self-assembles, and is then validated using 3D cryo-EM reconstruction.

The software allows for fabricating a variety of geometric DNA objects, including 35 polyhedral forms (Platonic, Archimedean, Johnson and Catalan solids), six asymmetric structures, and four polyhedra with nonspherical topology, using inverse design principles — no manual base-pair designs needed.

To test the method, simpler forms known as Platonic solids were first fabricated, followed by increasingly complex structures. These included objects with nonspherical topologies and unusual internal details, which had never been experimentally realized before. Further experiments confirmed that the DNA structures produced were potentially suitable for biological applications since they displayed long-term stability in serum and low-salt conditions.

Biological research uses

The research also paves the way for designing nanoscale systems mimicking the properties of viruses, photosynthetic organisms, and other sophisticated products of natural evolution. One such application is a scaffold for viral peptides and proteins for use as vaccines. The surface of the nanoparticles could be designed with any combination of peptides and proteins, located at any desired location on the structure, in order to mimic the way in which a virus appears to the body’s immune system.

The researchers demonstrated that the DNA nanoparticles are stable for more than six hours in serum, and are now attempting to increase their stability further.

The nanoparticles could also be used to encapsulate the CRISPR-Cas9 gene editing tool. The CRISPR-Cas9 tool has enormous potential in therapeutics, thanks to its ability to edit targeted genes. However, there is a significant need to develop techniques to package the tool and deliver it to specific cells within the body, Bathe says.

This is currently done using viruses, but these are limited in the size of package they can carry, restricting their use. The DNA nanoparticles, in contrast, are capable of carrying much larger gene packages and can easily be equipped with molecules that help target the right cells or tissue.

The most exciting aspect of the work, however, is that it should significantly broaden participation in the application of this technology, Bathe says, much like 3-D printing has done for complex 3-D geometric models at the macroscopic scale.

Hao Yan directs the Biodesign Center for Molecular Design and Biomimetics at Arizona State University and is the Milton D. Glick Distinguished Professor, College of Liberal Arts and Sciences, School of Molecular Sciences at ASU.

DNA origami brings the ancient Japanese method of paper folding down to the molecular scale. The basics are simple: Take a length of single-stranded DNA and guide it into a desired shape, fastening the structure together using shorter “staple strands,” which bind in strategic places along the longer length of DNA. The method relies on the fact that DNA’s four nucleotide letters—A, T, C, & G stick together in a consistent manner — As always pairing with Ts and Cs with Gs.

The DNA molecule in its characteristic double stranded form is fairly stiff, compared with single-stranded DNA, which is flexible. For this reason, single stranded DNA makes for an ideal lace-like scaffold material. Further, its pairing properties are predictable and consistent (unlike RNA).

https://vimeo.com/22349631

** A single gram of DNA can store about 700 terabytes of information — an amount equivalent to 14,000 50-gigabyte Blu-ray disks — and could potentially be operated with a fraction of the energy required for other information storage options.

 

Essential role of miRNAs in orchestrating the biology of the tumor microenvironment

Jamie N. Frediani and Muller Fabbri
Molecular Cancer (2016) 15:42   http://dx.doi.org:/10.1186/s12943-016-0525-3

MicroRNAs (miRNAs) are emerging as central players in shaping the biology of the Tumor Microenvironment (TME). They do so both by modulating their expression levels within the different cells of the TME and by being shuttled among different cell populations within exosomes and other extracellular vesicles. This review focuses on the state-of-the-art knowledge of the role of miRNAs in the complexity of the TME and highlights limitations and challenges in the field. A better understanding of the mechanisms of action of these fascinating micro molecules will lead to the development of new therapeutic weapons and most importantly, to an improvement in the clinical outcome of cancer patients. Keywords: Exosomes, microRNAs, Tumor microenvironment, Cancer

While cancer treatment and survival have improved worldwide, the need for further understanding of the underlying tumor biology remains. In recent years, there has been a significant shift in scientific focus towards the role of the tumor microenvironment (TME) on the development, growth, and metastatic spread of malignancies. The TME is defined as the surrounding cellular environment enmeshed around the tumor cells including endothelial cells, lymphocytes, macrophages, NK cells, other cells of the immune system, fibroblasts, mesenchymal stem cells (MSCs), and the extracellular matrix (ECM). Each of these components interacts with and influences the tumor cells, continually shifting the balance between pro- and anti-tumor phenotype. One of the predominant methods of communication between these cells is through extracellular vesicles and their microRNA (miRNA) cargo. Extracellular vesicles (EVs) are between 30 nm to a few microns in diameter, are surrounded by a phospholipid bilayer membrane, and are released from a variety of cell types into the local environment. There are three well characterized groups of EVs: 1) exosomes, typically 30–100 nm, 2) microvesicles (or ectosomes), typically 100–1000 nm, and 3) large oncosomes, typically 1–10 μm. Each of these categories has a distinctly unique biogenesis and purpose in cellcell communication despite the fact that current laboratory methods do not always allow precise differentiation. EVs are found to be enriched with membrane-bound proteins, lipid raft-associated and cytosolic proteins, lipids, DNA, mRNAs, and miRNAs, all of which can be transferred to the recipient cell upon fusion to allow cell-cell communications [1]. Of these, miRNAs have been of particular interest in cancer research, both as modifiers of transcription and translation as well as direct inhibitors or enhancers of key regulatory proteins. These miRNAs are a large family of small non-coding RNAs (19–24 nucleotides) and are known to be aberrantly expressed, both in terms of content as well as number, in both the tumor cells and the cells of the TME. Synthesis of these mature miRNA is a complex process, starting with the transcription of long, capped, and polyadenylated pri-miRNA by RNA polymerase II. These are cropped into a 60–100 nucleotide hairpinstructure pre-miRNA by the microprocessor, a heterodimer of Drosha (a ribonuclease III enzyme) and DGCR8 (DiGeorge syndrome critical region gene 8). The premiRNA is then exported to the cytoplasm by exportin 5, cleaved by Dicer, and separated into single strands by helicases. The now mature miRNA are incorporated into the RNA-induced silencing complex (RISC), a cytoplasmic effector machine of the miRNA pathway. The primary mechanism of action of the mature miRNA-RISC complex is through their binding to the 3’ untranslated region, or less commonly the 5’ untranslated region, of target mRNA, leading to protein downregulation either via translational repression or mRNA degradation. More recently, it has been shown that miRNAs can also upregulate the expression of target genes [2]. MiRNA genes are mostly intergenic and are transcribed by independent promoters [3] but can also be encoded by introns, sharing the same promoter of their host gene [4]. MiRNAs undergo the same regulatory mechanisms of any other protein coding gene (promoter methylation, histone modifications, etc.…) [5, 6]. Interestingly, each miRNA may have contradictory effects both within varying tumor cell lines and within different cells of the TME. In this review, we provide a state-of-the-art description of the key role that miRNAs have in the communication between tumor cells and the TME and their subsequent effects on the malignant phenotype. Finally, this review has made every effort to clarify, whenever possible, whether the reference is to the −3p or the -5p miRNA. Whenever such clarification has not been provided, this indicates that it was not possible to infer such information from the cited bibliography.

Angiogenesis and miRNAs Cellular plasticity, critical in the development of malignancy, includes the many diverse mechanisms elicited by cancer cells to increase their malignant potential and develop increasing treatment resistance. One such mechanism, angiogenesis, is critical to the development of metastatic disease, affecting both the growth of malignant cells locally and their survival at distant sites. In the last ten years, miRNAs, often packaged in tumor cell-derived exosomes, have emerged as important contributors to the complicated regulation and balance of pro- and anti-angiogenic factors.

Most commonly, miRNAs derived from cancer cells have oncogenic activity, promoting angiogenesis and tumor growth and survival. The most-well characterized of the pro-angiogenic miRNAs, the miR-17-92 cluster encoding six miRNAs (miR-17, −18a, −19a, −19b, −20a, and −92a), is found on chromosome 13, and is highly conserved among vertebrates [7]. The complex and multifaceted functions of the miR-17-92 cluster are summarized in Fig. 1. Amplification, both at the genetic and RNA level, of miR-17-92 was initially found in several lymphoma cell lines and has subsequently been observed in multiple mouse tumor models [7].

https://static-content.springer.com/image/art%3A10.1186%2Fs12943-016-0525-3/MediaObjects/12943_2016_525_Fig1_HTML.gif

Fig. 1   https://static-content.springer.com/image/art%3A10.1186%2Fs12943-016-0525-3/MediaObjects/12943_2016_525_Fig1_HTML.gif

Central role of the miR-17-92 cluster in the biology of the TME. The miR-17-92 cluster encoding miR-17, −18a, −19b, −20a, and -92a is upregulated in multiple tumor types and interacts with various components of the TME to finely “tune” the TME through a complex combination of pro- and anti-tumoral effects

Most commonly, miRNAs derived from cancer cells have oncogenic activity, promoting angiogenesis and tumor growth and survival. The most-well characterized of the pro-angiogenic miRNAs, the miR-17-92 cluster encoding six miRNAs (miR-17, −18a, −19a, −19b, −20a, and −92a), is found on chromosome 13, and is highly conserved among vertebrates [7]. The complex and multifaceted functions of the miR-17-92 cluster are summarized in Fig. 1. Amplification, both at the genetic and RNA level, of miR-17-92 was initially found in several lymphoma cell lines and has subsequently been observed in multiple mouse tumor models [7]. Up-regulation of this particular locus has further been confirmed in miRnome analysis across multiple different tumor types, including lung, breast, stomach, prostate, colon, and pancreatic cancer [8]. The miR-17-92 cluster is directly activated by Myc and modulates a variety of downstream transcription factors important in cell cycle regulation and apoptosis including activation of E2F family and Cyclin-dependent kinase inhibitor (CDKN1A) and downregulation of BCL2L11/BIM and p21 [7]. In addition to promoting cell cycle progression and inhibiting apoptosis, the miR-17-92 cluster also downregulates thrombospondin-1 (Tsp1) and connective tissue growth factor (CTGF), important antiangiogenic proteins [7]. Similarly, microvesicles from colorectal cancer cells contain miR-1246 and TGF-β which are transferred to endothelial cells to silence promyelocytic leukemia protein (PML) and activate Smad 1/5/8 signaling promoting proliferation and migration [9]. Likewise, lung cancer cell line derived microvesicles contain miR-494, in response to hypoxia, which targets PTEN in the endothelial cells promoting angiogenesis through the Akt/eNOS pathway [10]. Lastly, exosomal miR-135b from multiple myeloma cells suppresses the HIF-1/FIH-1 pathway in endothelial cells, increasing angiogenesis [11]. A summary of the studies showing the functions of exosomal miRNAs in shaping the biology of the TME is provided in Table 1.

 

Table 1

Actions of exosomal miRNAs exchanged between cells of the TME

 

Angiogenesis:

 miRNA

Cell of origin

Accepting cell

Pathway/target

Effect on TME

Ref.

 miR-135b

Multiple myeloma

Endothelial cells

HIF-1/FIH-1

↑angiogenesis

[11]

 miR-494

Lung cancer

Endothelial cells

PTEN/AKT/eNOS

↑angiogenesis

[10]

 miR-503

Endothelial cells

Breast cancer

Cyclin D2 and D3

↓Tumor growth and invasion

[22]

 miR-1246

Colorectal cancer

Endothelial Cells

PML/Smad 1/5/8

↑ Growth & migration

[9]

Stromal compartment:

 miR-105

Breast cancer

Endothelial cells

ZO-1

↓Tight junctions

↑Metastatic progression

[68]

 miR-202-3p

CLL

Stromal cells

c-fos/ATM

↑Tumor growth

[53]

Immune system:

 miR-29a

NSCLC

TAM

TLR8/NF-κB

↑Growth & metastasis

[75]

 miR-21

NSCLC

TAM

TLR8/NF-κB

↑Growth & metastasis

[75]

NBL

TAM

TLR8/NF-κB

↑miR-155

[76]

 miR-155

TAM

NBL

TERF1

↑ Drug resistance

[76]

 miR-23a

Hypoxic tumor derived

NK cells

CD107a

↓ NK cell response

[95]

 miR-210

 miR-214

Tumor cells (various)

Regulatory T cells

PTEN

↑Immunosuppression

[96]

 miR-223

TAM

Breast cancer

Mef2c/β-catenin

↑ Invasion

[82]

Abbreviations: TAMs Tumor Associated Macrophages, CLL chronic lymphocytic leukemia, NSCLCnon-small cell lung cancer, NBL Neuroblastoma

The most common target of anti-angiogenic therapy is VEGF, and not unsurprisingly, multiple miRNAs (including miR-9, miR-20b, miR-130, miR-150, and miR-497) promote angiogenesis through the induction of the VEGF pathway. The most studied of these is the up-regulation of miR-9 which has been linked to a poor prognosis in multiple tumor types, including breast cancer, non-small cell lung cancer, and melanoma [12]. The two oncogenes MYC and MYCN activate miR-9 and cause E-cadherin downregulation resulting in the upregulated transcription of VEGF [13]. In addition, miR-9 has been shown to upregulate the JAK-STAT pathway, supporting endothelial cell migration and tumor angiogenesis [13]. Both amplification of miR-20b and miR-130 as well as miR-497 suppression regulate VEGF through hypoxia inducible factor 1α (HIF-1α) supporting increased angiogenesis [14, 15, 16, 17]. …..

The pivotal discovery in 2012 by Mitra et al. laid the ground-work for our current knowledge on the interactions between tumor-derived miRNAs and fibroblasts. In combination, the down-regulation of miR-214 and miR-31 and the up-regulation of miR-155 trigger the reprogramming of quiescent fibroblasts to CAFs [32]. As expected, the reverse regulation of these miRNAs reduced the migration and invasion of co-cultured ovarian cancer cells [32]. While the pathway of miR-155’s involvement in CAF biology is still being elucidated, the pathways of miR-214 and miR-31 have been established. In endometrial cancer, miR-31 was found to target the homeobox gene SATB2, leading to enhanced tumor cell migration and invasion [33]. MiR-214 similarly has an inverse correlation with its chemokine target, C-C motif Ligand 5 (CCL5) [32]. CCL5 secretion has been associated with enhanced motility, invasion, and metastatic potential through NF-κB-mediated MMP9 activation and through generation and differentiation of myeloid-derived suppressor cells (MDSCs) [34, 35, 36]. Furthermore, miR-210 and miR-133b overexpression and miR-149 suppression have been subsequently found to independently trigger the conversion to CAFs, possibly through paracrine stimulation, and to additionally promote EMT in prostate and gastric cancer, respectively [37, 38,39]. MiR-210 additionally enlists monocytes and encourages angiogenesis [37].   …

Another function of CAFs is the destruction of the ECM and its remodeling with a tumor-supportive composition and structure which includes modulation of specific integrins and metalloproteinases as some of the most studied miRNA targets. The 23 matrix metalloproteinases (MMPs) are critical in the ECM degradation, disruption of the growth signal balance, resistance to apoptosis, establishment of a favorable metastatic niche, and promotion of angiogenesis [54]. As expected, miRNAs have been found to regulate the actions of MMPs, together working to promote cancer cell growth, invasiveness, and metastasis. In HCC, MMP2 and 9 expression is up-regulated by miR-21 via PTEN pathway downregulation. Similarly, in cholangiocarcinoma it was observed that reduced levels of miR-138 induced up-regulation of RhoC, leading to increased levels of the same two MMPs [55, 56]. ….

As has been shown throughout this review, miRNAs have an important and varied effect on human carcinogenesis by shaping the biology of the TME towards a more permissive pro-tumoral phenotype. The complex events leading to such an outcome are currently quite universally defined as the “educational” process of cancer cells on the surrounding TME. While the initial focus was on the direction from the cancer cell to the surrounding TME, increasingly interest is centered on the implications of a more dynamic bidirectional exchange of genetic information. MiRNAs represent only part of the cargo of the extracellular vesicles, but an increasing scientific literature points towards their pivotal role in creating the micro-environmental conditions for cancer cell growth and dissemination. The nearby future will have to address several questions still unanswered. First, it is absolutely necessary to clarify which miRNAs and to what extent they are involved in this process. The contradictory results of some studies can be explained by the differences in tumor-types and by different concentrations of miRNAs used for functional studies. Understanding whether different concentrations of the same miRNA elicit different target effects and therefore changes the biology of the TME, will represent a significant consideration in the development of this field. It is certainly very attractive (especially in an attempt to develop new and desperately needed better cancer biomarkers) to think that concentrations of miRNAs within the TME are reflected systemically in the circulating levels of that same miRNA, however this has not yet been irrefutably demonstrated. Moreover, the study of the paracrine interactions among different cell populations of the TME and their reciprocal effects has been limited to two, maximum three cell populations. This is still way too far from describing the complexity of the TME and only the development of new tridimensional models of the TME will be able to cast a more conclusive light on such complexity. Finally, the pharmacokinetics of miRNA-containing vesicles is in its infancy at best, and needs to be further developed if the goal is development of new therapies based on the use of exosomic miRNAs. Therefore, the future of miRNA research, particularly in its role in the TME, holds still a lot of questions that need answering. However, for these exact same reasons, this is an incredibly exciting time for research in this field. We can envision a not too far future in which these concerns will be satisfactorily addressed and our understanding of the role of miRNAs within the TME will allow us to use them as new therapeutic weapons to successfully improve the clinical outcome of cancer patients.

 

 

 

Triggering the protein that programs cancer cells to kill themselves
http://www.kurzweilai.net/triggering-the-protein-that-programs-cancer-cells-to-kill-themselves

May 24, 2016

https://youtu.be/DR80Huxp4y8
WEHI | Apoptosis

Researchers at the Walter and Eliza Hall Institute in Australia have discovered a new way to trigger cell death that could lead to drugs to treat cancer and autoimmune disease.

Programmed cell death (a.k.a. apoptosis) is a natural process that removes unwanted cells from the body. Failure of apoptosis can allow cancer cells to grow unchecked or immune cells to inappropriately attack the body.

The protein known as Bak is central to apoptosis. In healthy cells, Bak sits in an inert state but when a cell receives a signal to die, Bak transforms into a killer protein that destroys the cell.

Triggering the cancer-apoptosis trigger

Institute researchers Sweta Iyer, PhD, Ruth Kluck, PhD, and colleagues unexpectedly discovered that an antibody they had produced to study Bak actually bound to the Bak protein and triggered its activation. They hope to use this discovery to develop drugs that promote cell death.

The researchers used information about Bak’s three-dimensional structure to find out precisely how the antibody activated Bak. “It is well known that Bak can be activated by a class of proteins called ‘BH3-only proteins’ that bind to a groove on Bak. We were surprised to find that despite our antibody binding to a completely different site on Bak, it could still trigger activation,” Kluck said.  “The advantage of our antibody is that it can’t be ‘mopped up’ and neutralized by pro-survival proteins in the cell, potentially reducing the chance of drug resistance occurring.”

Drugs that target this new activation site could be useful in combination with other therapies that promote cell death by mimicking the BH3-only proteins. The researchers are now working with collaborators to develop their antibody into a drug that can access Bak inside cells.

Their findings have just been published in the open-access journal Nature Communications. The research was supported by the National Health and Medical Research Council, the Australian Research Council, the Victorian State Government Operational Infrastructure Support Scheme, and the Victorian Life Science Computation Initiative.

Abstract of Identification of an activation site in Bak and mitochondrial Bax triggered by antibodies

During apoptosis, Bak and Bax are activated by BH3-only proteins binding to the α2–α5 hydrophobic groove; Bax is also activated via a rear pocket. Here we report that antibodies can directly activate Bak and mitochondrial Bax by binding to the α1–α2 loop. A monoclonal antibody (clone 7D10) binds close to α1 in non-activated Bak to induce conformational change, oligomerization, and cytochrome c release. Anti-FLAG antibodies also activate Bak containing a FLAG epitope close to α1. An antibody (clone 3C10) to the Bax α1–α2 loop activates mitochondrial Bax, but blocks translocation of cytosolic Bax. Tethers within Bak show that 7D10 binding directly extricates α1; a structural model of the 7D10 Fab bound to Bak reveals the formation of a cavity under α1. Our identification of the α1–α2 loop as an activation site in Bak paves the way to develop intrabodies or small molecules that directly and selectively regulate these proteins.

references:

 

Catching metastatic cancer cells before they grow into tumors: a new implant shows promise

https://62e528761d0685343e1c-f3d1b99a743ffa4142d9d7f1978d9686.ssl.cf2.rackcdn.com/files/122764/width926/image-20160516-15899-18cgw3m.jpg

Cure” is a word that’s dominated the rhetoric in the war on cancer for decades. But it’s a word that medical professionals tend to avoid. While the American Cancer Society reports that cancer treatment has improved markedly over the decades and the five-year survival rate is impressively high for many cancers, oncologists still refrain from declaring their cancer-free patients cured. Why?

Patients are declared cancer-free (also called complete remission) when there are no more signs of detectable disease.

However, minuscule clusters of cancer cells below the detection level can remain in a patient’s body after treatment. Moreover, such small clusters of straggler cells may undergo metastasis, where they escape from the initial tumor into the bloodstream and ultimately settle in a distant site, often a vital organ such as the lungs, liver or brain.

Cancer cells can move throughout the body, like these metastatic melanoma cells. NIH Image Gallery/FlickrCC BY

When a colony of these metastatic cells reaches a detectable size, the patient is diagnosed with recurrent metastatic cancer. About one in three breast cancer patients diagnosed with early-stage cancer later develop metastatic disease, usually within five years of initial remission.

By the time metastatic cancer becomes evident, it is much more difficult to treat than when it was originally diagnosed.

What if these metastatic cells could be detected earlier, before they established a “foothold” in a vital organ? Better yet, could these metastatic cancer cells be intercepted, preventing them them from lodging in a vital organ in the first place?

To catch a cancer cell

With these goals in mind, our biomaterials lab joined forces with surgical oncologist Jacqueline Jeruss to create an implantable medical device that acts as a metastatic cancer cell trap.

The implant is a tiny porous polymer disc (basically a miniature sponge, no larger than a pencil eraser) that can be inserted just under a patient’s skin. Implantation triggers the immune system’s “foreign body response,” and the implant starts to soak up immune cells that travel to it. If the implant can catch mobile immune cells, then why not mobile metastatic cancer cells?

The disc can detect cancer cells in mice. Lab mouse via www.shutterstock.com.

We gave implants to mice specially bred to model metastatic breast cancer. When the mice had palpable tumors but no evidence of metastatic disease, the implant was removed and analyzed.

Cancer cells were indeed present in the implant, while the other organs (potential destinations for metastatic cells) still appeared clean. This means that the implant can be used to spot previously undetectable metastatic cancer before it takes hold in an organ.

For patients with cancer in remission, an implant that can detect tumor cells as they move through the body would be a diagnostic breakthrough. But having to remove it to see if it has captured any cancer cells is not the most convenient or pleasant detection method for human patients.

Detecting cancer cells with noninvasive imaging

There could be a way around this, though: a special imaging method under development at Northwestern University called Inverse Spectroscopic Optical Coherence Tomography (ISOCT). ISOCT detects molecular-level differences in the way cells in the body scatter light. And when we scan our implant with ISOCT, the light scatter pattern looks different when it’s full of normal cells than when cancer cells are present. In fact, the difference is apparent when even as few as 15 out of the hundreds of thousands of cells in the implant are cancer cells.

There’s a catch – ISOCT cannot penetrate deep into tissue. That means it is not a suitable imaging technology for finding metastatic cells buried deep in internal organs. However, when the cancer cell detection implant is located just under the skin, it may be possible to detect cancer cells trapped in it using ISOCT. This could offer an early warning sign that metastatic cells are on the move.

This early warning could prompt doctors to monitor their patients more closely or perform additional tests. Conversely, if no cells are detected in the implant, a patient still in remission could be spared from unneeded tests.

The ISOCT results show that noninvasive imaging of the implant is feasible. But it’s a method still under development, and thus it’s not widely available. To make scanning easier and more accessible, we’re working to adapt more ubiquitous imaging technologies like ultrasound to detect tiny quantities of tumor cells in the implant.

Detect and capture. Joseph Xu, Michigan EngineeringCC BY-NC-ND

Not just detecting, but quarantining cancer

Besides providing a way to detect tiny numbers of cancer cells before they can form new tumors in other parts of the body, our implant offers an even more intriguing possibility: diverting metastatic cells away from vital organs, and sequestering them where they cannot cause any damage.

In our mouse studies, we found that metastatic cells got caught in the implant before they were apparent in vital organs. When metastatic cells eventually made their way into the organs, the mice with implants still had significantly fewer tumor cells in their organs than implant-free controls. Thus, the implant appears to provide a therapeutic benefit, most likely by taking the metastatic cells it catches out of the circulation, preventing them from lodging anywhere vital.

Interestingly, we have not seen cancer cells leave the implant once trapped, or form a secondary tumor in the implant. Ongoing work aims to learn why this is. Whether the cells can stay safely immobilized in the implant or if it would need to be removed periodically will be important questions to answer before the implant could be used in human patients.

What the future may hold

For now, our work aims to make the implant more effective at drawing and detecting cancer cells. Since we tested the implant with metastatic breast cancer cells, we also want to see if it will work on other types of cancer. Additionally, we’re studying the cells the implant traps, and learning how the implant interacts with the body as a whole. This basic research should give us insight into the process of metastasis and how to treat it.

In the future (and it might still be far off), we envision a world where recovering cancer patients can receive a detector implant to stand guard for disease recurrence and prevent it from happening. Perhaps the patient could even scan their implant at home with a smartphone and get treatment early, when the disease burden is low and the available therapies may be more effective. Better yet, perhaps the implant could continually divert all the cancer cells away from vital organs on its own, like Iron Man’s electromagnet that deflects shrapnel from his heart.

This solution is still not a “cure.” But it would transform a formidable disease that one out of three cancer survivors would otherwise ultimately die from into a condition with which they could easily live.

 

New PSA Test Examines Protein Structures to Detect Prostate Cancers

5/16/2016  by Cleveland Clinic

A promising new test is detecting prostate cancer more precisely than current tests, by identifying molecular changes in the prostate specific antigen (PSA) protein, according to Cleveland Clinic research presented today at the American Urological Association annual meeting.

The study – part of an ongoing multicenter prospective clinical trial – found that the IsoPSATM test can also differentiate between high-risk and low-risk disease, as well as benign conditions.

Although widely used, the current PSA test relies on detection strategies that have poor specificity for cancer – just 25 percent of men who have a prostate biopsy due to an elevated PSA level actually have prostate cancer, according to the National Cancer Institute – and an inability to determine the aggressiveness of the disease.

The IsoPSA test, however, identifies prostate cancer in a new way. Developed by Cleveland Clinic, in collaboration with Cleveland Diagnostics, Inc., IsoPSA identifies the molecular structural changes in protein biomarkers. It is able to detect cancer by identifying these structural changes, as opposed to current tests that simply measure the protein’s concentration in a patient’s blood.

“While the PSA test has undoubtedly been one of the most successful biomarkers in history, its limitations are well known. Even currently available prostate cancer diagnostic tests rely on biomarkers that can be affected by physiological factors unrelated to cancer,” said Eric Klein, M.D., chair of Cleveland Clinic’s Glickman Urological & Kidney Institute. “These study results show that using structural changes in PSA protein to detect cancer is more effective and can help prevent unneeded biopsies in low-risk patients.”

The clinical trial involves six healthcare institutions and 132 patients, to date. It examined the ability of IsoPSA to distinguish patients with and without biopsy-confirmed evidence of cancer. It also evaluated the test’s precision in differentiating patients with high-grade (Gleason = 7) cancer from those with low-grade (Gleason = 6) disease and benign findings after standard ultrasound-guided biopsy of the prostate.

Substituting the IsoPSA structure-based composite index for the standard PSA resulted in improvement in diagnostic accuracy. Compared with serum PSA testing, IsoPSA performed better in both sensitivity and specificity.

“We took an ‘out of the box’ approach that has shown success in detecting prostate cancer but also has the potential to address other clinically important questions such as clinical surveillance of patients after treatment,” said Mark Stovsky, M.D., staff member, Cleveland Clinic Glickman Urological & Kidney Institute’s Department of Urology. Stovsky has a leadership position (Chief Medical Officer) and investment interest in Cleveland Diagnostics, Inc. “In general, the clinical utility of prostate cancer early detection and screening tests is often limited by the fact that biomarker concentrations may be affected by physiological processes unrelated to cancer, such as inflammation, as well as the relative lack of specificity of these biomarkers to the cancer phenotype. In contrast, clinical research data suggests that the IsoPSA assay can interrogate the entire PSA isoform distribution as a single stand-alone diagnostic tool which can reliably identify structural changes in the PSA protein that correlate with the presence or absence and aggressiveness of prostate cancer.”

 

Point of Care, Highly Accurate Cervical Cancer Screening

5/20/2016 by Avi Rosenzweig, VP of Business Development, Biop Medical
http://www.mdtmag.com/article/2016/05/point-care-highly-accurate-cervical-cancer-screening

Fifty-five million times a year, American women go to their gynecologist for a Pap Smear. After waiting a few weeks for the results, more than 3.5 million of them are called back to the physician for a follow up visualization of the cervix. Beyond the stress related to possibly having cancer, the women are then subjected to a colposcopic exam, and all too often, a painful biopsy. Then more stressful waiting for a final diagnosis from the pathologist.

Cervical cancer develops slowly, allowing for successful treatment, when identified on time. Regions with high screening compliancy have low mortality rates from this cancer. In the US, for instance, where screening rates are close to 90%, only 4,200 women die from cervical cancer, annually, or 2.6 women per 100,000. However, the screening process in the developed world is long, complicated and not optimized.

In developing regions however, cervical cancer is a leading cause of women death. Over 85% of the total deaths from this cancer are in developing countries. Regions suffering from low screening rates include not only Africa, India and China, but many Eastern European countries as well. According to an OECD report from 2014, the cervical cancer screening rates in Romania and Hungary are as low as 14.6% and 36.7% respectively. The mortality rates in these countries are high, 16 in 100,000 women in Romania and 7.7 in 100,000 in Hungary.

The current screening process for cervical cancer detection is long, beginning with a Pap or HPV test. Cytology results take weeks to receive. A positive result requires follow-up testing by colposcopy and often biopsy. In countries where there is little access to medical care, or where screening compliancy is low, the chances of successful detection via this multi-step process are small. Developing regions and non-compliant countries require a point of care diagnostic method, which eliminates the need for return visits.

Additional limitations to cervical cancer screening are the low sensitivity and specificity rates of Pap tests and the high false positive rates of HPV test, leading to unnecessary colposcopies. Both cytology and colposcopy testing are highly dependent on operator proficiency for accurate diagnosis.

Biop has developed a new technology for the optimization of this process, into one, three minute, painless optical scan. The vaginal probe uses advanced optical, imaging and non-imaging technologies to identify and classify epithelium based cancers and pre-cancerous lesions. The probe is inserted into the vaginal canal, and scans the entire cervix. The resulting images and optical signatures created from the light, and captured by the sensors, are analyzed by the proprietary algorithm. The result is two pictures, on the physician’s screen; a high resolution photograph of the patient’s cervix, immediately next to a hot/cold map indicating a precise classification and location of any diseased lesions.

 

Deep learning applied to drug discovery and repurposing

May 27, 2016  http://www.kurzweilai.net/deep-learning-applied-to-drug-discovery-and-repurposing

Deep neural networks for drug discovery (credit: Insilico Medicine, Inc.)

Scientists from Insilico Medicine, Inc. have trained deep neural networks (DNNs) to predict the potential therapeutic uses of 678 drugs, using gene-expression data obtained from high-throughput experiments on human cell lines from Broad Institute’s LINCS databases and NIH MeSH databases.

The supervised deep-learning drug-discovery engine used the properties of small molecules, transcriptional data, and literature to predict efficacy, toxicity, tissue-specificity, and heterogeneity of response.

“We used LINCS data from Broad Institute to determine the effects on cell lines before and after incubation with compounds, co-author and research scientist Polina Mamoshina explained to KurzweilIAI.

“We used gene expression data of total mRNA from cell lines extracted and measured before incubation with compound X and after incubation with compound X to identify the response on a molecular level. The goal is to understand how gene expression (the transcriptome) will change after drug uptake. It is a differential value, so we need a reference (molecular state before incubation) to compare.”

The research is described in a paper in the upcoming issue of the journal Molecular Pharmaceutics.

Helping pharmas accelerate R&D

Alex Zhavoronkov, PhD, Insilico Medicine CEO, who coordinated the study, said the initial goal of their research was to help pharmaceutical companies significantly accelerate their R&D and increase the number of approved drugs. “In the process we came up with more than 800 strong hypotheses in oncology, cardiovascular, metabolic, and CNS spaces and started basic validation,” he said.

The team measured the “differential signaling pathway activation score for a large number of pathways to reduce the dimensionality of the data while retaining biological relevance.” They then used those scores to train the deep neural networks.*

“This study is a proof of concept that DNNs can be used to annotate drugs using transcriptional response signatures, but we took this concept to the next level,” said Alex Aliper, president of research, Insilico Medicine, Inc., lead author of the study.

Via Pharma.AI, a newly formed subsidiary of Insilico Medicine, “we developed a pipeline for in silico drug discovery — which has the potential to substantially accelerate the preclinical stage for almost any therapeutic — and came up with a broad list of predictions, with multiple in silico validation steps that, if validated in vitro and in vivo, can almost double the number of drugs in clinical practice.”

Despite the commercial orientation of the companies, the authors agreed not to file for intellectual property on these methods and to publish the proof of concept.

Deep-learning age biomarkers

According to Mamoshina, earlier this month, Insilico Medicine scientists published the first deep-learned biomarker of human age — aiming to predict the health status of the patient — in a paper titled “Deep biomarkers of human aging: Application of deep neural networks to biomarker development” by Putin et al, in Aging; and an overview of recent advances in deep learning in a paper titled “Applications of Deep Learning in Biomedicine” by Mamoshina et al., also in Molecular Pharmaceutics.

Insilico Medicine is located in the Emerging Technology Centers at Johns Hopkins University in Baltimore, Maryland, in collaboration with Datalytic Solutions and Mind Research Network.

* In this study, scientists used the perturbation samples of 678 drugs across A549, MCF-7 and PC-3 cell lines from the Library of Integrated Network-Based Cellular Signatures (LINCS) project developed by the National Institutes of Health (NIH) and linked those to 12 therapeutic use categories derived from MeSH (Medical Subject Headings) developed and maintained by the National Library of Medicine (NLM) of the NIH.

To train the DNN, scientists utilized both gene level transcriptomic data and transcriptomic data processed using a pathway activation scoring algorithm, for a pooled dataset of samples perturbed with different concentrations of the drug for 6 and 24 hours. Cross-validation experiments showed that DNNs achieve 54.6% accuracy in correctly predicting one out of 12 therapeutic classes for each drug.

One peculiar finding of this experiment was that a large number of drugs misclassified by the DNNs had dual use, suggesting possible application of DNN confusion matrices in drug repurposing.
FutureTechnologies Media Group | Video presentation Insilico medicine

Abstract of Deep learning applications for predicting pharmacological properties of drugs and drug repurposing using transcriptomic data

Deep learning is rapidly advancing many areas of science and technology with multiple success stories in image, text, voice and video recognition, robotics and autonomous driving. In this paper we demonstrate how deep neural networks (DNN) trained on large transcriptional response data sets can classify various drugs to therapeutic categories solely based on their transcriptional profiles. We used the perturbation samples of 678 drugs across A549, MCF-7 and PC-3 cell lines from the LINCS project and linked those to 12 therapeutic use categories derived from MeSH. To train the DNN, we utilized both gene level transcriptomic data and transcriptomic data processed using a pathway activation scoring algorithm, for a pooled dataset of samples perturbed with different concentrations of the drug for 6 and 24 hours. When applied to normalized gene expression data for “landmark genes,” DNN showed cross-validation mean F1 scores of 0.397, 0.285 and 0.234 on 3-, 5- and 12-category classification problems, respectively. At the pathway level DNN performed best with cross-validation mean F1 scores of 0.701, 0.596 and 0.546 on the same tasks. In both gene and pathway level classification, DNN convincingly outperformed support vector machine (SVM) model on every multiclass classification problem. For the first time we demonstrate a deep learning neural net trained on transcriptomic data to recognize pharmacological properties of multiple drugs across different biological systems and conditions. We also propose using deep neural net confusion matrices for drug repositioning. This work is a proof of principle for applying deep learning to drug discovery and development.

references:

 

Transistor-based biosensor detects molecules linked to cancer, Alzheimer’s, and Parkinson’s

May 23, 2016  http://www.kurzweilai.net/transistor-based-biosensor-detects-molecules-linked-to-cancer-alzheimers-and-parkinsons

An inexpensive portable biosensor developed by researchers at Brazil’s National Nanotechnology Laboratory (credit: LNNano)  http://www.kurzweilai.net/images/Biosensor-LNNano.jpg

A novel nanoscale organic transistor-based biosensor that can detect molecules associated with neurodegenerative diseases and some types of cancer has been developed by researchers at the National Nanotechnology Laboratory (LNNano) in Brazil.

The transistor, mounted on a glass slide, contains the reduced form of the peptide glutathione (GSH), which reacts in a specific way when it comes into contact with the enzyme glutathione S-transferase (GST), linked to Parkinson’s, Alzheimer’s and breast cancer, among other diseases.

http://www.kurzweilai.net/images/CuPc-transistor.png

Sensitive water-gated copper phthalocyanine (CuPc) thin-film transistor (credit: Rafael Furlan de Oliveira et al./Organic Electronics)

“The device can detect such molecules even when they’re present at very low levels in the examined material, thanks to its nanometric sensitivity,” explained Carlos Cesar Bof Bufon, Head of LNNano’s Functional Devices & Systems Lab (DSF).

Bufon said the system can be adapted to detect other substances by replacing the analytes (detection compounds). The team is working on paper-based biosensors to further lower the cost, improve portability, and facilitate fabrication and disposal.

The research is published in the journal Organic Electronics.

Abstract of Water-gated phthalocyanine transistors: Operation and transduction of the peptide–enzyme interaction

The use of aqueous solutions as the gate medium is an attractive strategy to obtain high charge carrier density (1012 cm−2) and low operational voltages (<1 V) in organic transistors. Additionally, it provides a simple and favorable architecture to couple both ionic and electronic domains in a single device, which is crucial for the development of novel technologies in bioelectronics. Here, we demonstrate the operation of transistors containing copper phthalocyanine (CuPc) thin-films gated with water and discuss the charge dynamics at the CuPc/water interface. Without the need for complex multilayer patterning, or the use of surface treatments, water-gated CuPc transistors exhibited low threshold (100 ± 20 mV) and working voltages (<1 V) compared to conventional CuPc transistors, along with similar charge carrier mobilities (1.2 ± 0.2) x 10−3 cm2 V−1 s−1. Several device characteristics such as moderate switching speeds and hysteresis, associated with high capacitances at low frequencies upon bias application (3.4–12 μF cm−2), indicate the occurrence of interfacial ion doping. Finally, water-gated CuPc OTFTs were employed in the transduction of the biospecific interaction between tripeptide reduced glutathione (GSH) and glutathione S-transferase (GST) enzyme, taking advantage of the device sensitivity and multiparametricity.

references:

 

First Large-Scale Proteogenomic Study of Breast Cancer    

Tues, May 31, 2016     http://www.technologynetworks.com/rnai/news.aspx?ID=191934

The study offers understanding of potential therapeutic targets.

Building on data from The Cancer Genome Atlas (TCGA) project, a multi-institutional team of scientists have completed the first large-scale “proteogenomic” study of breast cancer, linking DNA mutations to protein signaling and helping pinpoint the genes that drive cancer. Conducted by members of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), including Baylor College of Medicine, Broad Institute of MIT and Harvard, Fred Hutchinson Cancer Research Center, New York University Langone Medical Center, and Washington University School of Medicine, the study takes aim at proteins, the workhorses of the cell, and their modifications to better understand cancer.

Appearing in the Advance Online Publication of Nature, the study illustrates the power of integrating genomic and proteomic data to yield a more complete picture of cancer biology than either analysis could do alone. The effort produced a broad overview of the landscape of the proteome (all the proteins found in a cell) and the phosphoproteome (the sites at which proteins are tagged by phosphorylation, a chemical modification that drives communication in the cell) across a set of 77 breast cancer tumors that had been genomically characterized in the TCGA project. Although the TCGA produced an extensive catalog of somatic mutations found in cancer, the effects of many of those mutations on cellular functions or patients’ outcomes are unknown.

In addition, not all mutated genes are true “drivers” of cancer — some are merely “passenger” mutations that have little functional consequence. And some mutations are found within very large DNA regions that are deleted or present in extra copies, so winnowing the list of candidate genes by studying the activity of their protein products can help identify therapeutic targets. “We don’t fully understand how complex cancer genomes translate into the driving biology that causes relapse and mortality,” said Matthew Ellis, director of the Lester and Sue Smith Breast Center at Baylor College of Medicine and a senior author of the paper.

“These findings show that proteogenomic integration could one day prove to be a powerful clinical tool, allowing us to traverse the large knowledge gap between cancer genomics and clinical action.” In this study, the researchers at the Broad Institute analyzed breast tumors using accurate mass, high-resolution mass spectrometry, a technology that extends the coverage of the proteome far beyond the coverage that can be achieved by traditional antibody-based methods. This allowed them to scale their efforts and quantify more than 12,000 proteins and 33,000 phosphosites, an extremely deep level of coverage.

 

Breakthrough Approach to Breast Cancer Treatment

May 24, 2016    http://www.technologynetworks.com/rnai/news.aspx?ID=191771

Scripps scientists have designed a drug candidate that decreases growth of breast cancer cells.

In a development that could lead to a new generation of drugs to precisely treat a range of diseases, scientists from the Florida campus of The Scripps Research Institute (TSRI) have for the first time designed a drug candidate that decreases the growth of tumor cells in animal models in one of the hardest to treat cancers—triple negative breast cancer.

“This is the first example of taking a genetic sequence and designing a drug candidate that works effectively in an animal model against triple negative breast cancer,” said TSRI Professor Matthew Disney. “The study represents a clear breakthrough in precision medicine, as this molecule only kills the cancer cells that express the cancer-causing gene—not healthy cells. These studies may transform the way the lead drugs are identified—by using the genetic makeup of a disease.”

The study, published by the journal Proceedings of the National Academy of Sciences, demonstrates that the Disney lab’s compound, known as Targaprimir-96, triggers breast cancer cells to kill themselves via programmed cell death by precisely targeting a specific RNA that ignites the cancer.

Short-Cut to Drug Candidates

While the goal of precision medicine is to identify drugs that selectively affect disease-causing biomolecules, the process has typically involved time-consuming and expensive high-throughput screens to test millions of potential drug candidates to identify those few that affect the target of interest. Disney’s approach eliminates these screens.

The new study uses the lab’s computational approach called Inforna, which focuses on developing designer compounds that bind to RNA folds, particularly microRNAs.

MicroRNAs are short molecules that work within all animal and plant cells, typically functioning as a “dimmer switch” for one or more genes, binding to the transcripts of those genes and preventing protein production. Some microRNAs have been associated with diseases. For example, microRNA-96, which was the target of the new study, promotes cancer by discouraging programmed cell death, which can rid the body of cells that grow out of control.

In the new study, the drug candidate was tested in animal models over a 21-day course of treatment. Results showed decreased production of microRNA-96 and increased programmed cell death, significantly reducing tumor growth. Since targaprimir-96 was highly selective in its targeting, healthy cells were unaffected.

In contrast, Disney noted, a typical cancer therapeutic targets and kills cells indiscriminately, often leading to side effects that can make these drugs difficult for patients to tolerate.

Benjamin Zealley and Aubrey D.N.J. de Grey
Commentary on Some Recent Theses Relevant to Combating Aging: June 2015

REJUVENATION RESEARCH 2015; 18(3), 282 – 287   http://dx.doi.org:/10.1089/rej.2015.1728

Cancer Autoantibody Biomarker Discovery and Validation Using Nucleic Acid Programmable Protein Array
Jie Wang, PhD, Arizona State University

Currently in the United States, many patients with cancer do not benefit from population-based screening due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the potential to detect diseases in a non-invasive way. Proteins released from small early tumors may only be present intermittently and are diluted to tiny concentrations in the blood, making them difficult to use as biomarkers. However, they can induce autoantibody (AAb) responses, which can amplify the signal and persist in the blood even if the antigen is gone. Circulating autoantibodies are a promising class of molecules that have the potential to serve as early detection biomarkers for cancers. This PhD thesis aims to screen for autoantibody biomarkers for the early detection of two deadly cancers, basal-like breast cancer and lung adenocarcinoma. First, a method was developed to display proteins in both native and denatured conformations on a protein array. This method adopted a novel protein tag technology, called a HaloTag, to immobilize proteins covalently on the surface of a glass slide. The covalent attachment allowed these proteins to endure harsh treatment without becoming dissociated from the slide surface, which enabled the profiling of antibody responses against both conformational and linear epitopes. Next, a plasma screening protocol was optimized to increase significantly the signal-to-noise ratio of protein array–based AAb detection. Following this, the AAb responses in basal-like breast cancer were explored using nucleic acid programmable protein arrays (NAPPA) containing 10,000 full-length human proteins in 45 cases and 45 controls. After verification in a large sample set (145 basal-like breast cancer cases, 145 controls, 70 non-basal breast cancer) by enzyme-linked immunosorbent assay (ELISA), a 13-AAb classifier was developed to differentiate patients from controls with a sensitivity of 33% at 98% specificity. A similar approach was also applied to the lung cancer study to identify AAbs that distinguished lung cancer patients from computed tomography–positive benign pulmonary nodules (137 lung cancer cases, 127 smoker controls, 170 benign controls). In this study, two panels of AAbs were discovered that showed promising sensitivity and specificity. Six out of eight AAb targets were also found to have elevated mRNA levels in lung adenocarcinoma patients using TCGA data. These projects as a whole provide novel insights into the association between AAbs and cancer, as well as general B cell antigenicity against self-proteins.

Comment: There are two widely supported models for cancer development and progression—the clonal evolution (CE) model and the cancer stem cell (CSC) model. Briefly, the former claims that most or all cells in a tumor contribute to its maintenance; as newer and more aggressive clones develop by random mutation, they become responsible for driving growth. The range of different mutational profiles generated is assumed to be large enough to account for disease recurrence after therapy (due to rare resistant clones) and metastasis (clones arising with the ability to travel to distant sites). The CSC model instead asserts that a small number of mutated stem cells are the origin of the primary cell mass, drive metastasis through the intermittent release of undifferentiated, highly mobile progeny, and account for recurrence due to a generally quiescent metabolic profile conferring potent resistance to chemotherapy. In either case, the immunological visibility of an early tumor may be highly sporadic. Clones arising early in CE differ little in proteomic terms from healthy host cells; those that do trigger a response are unlikely to have acquired robust resistance to immune attack, so are destroyed quickly in favor of their stealthier brethren. Likewise, CSCs share some of the immune privilege of normal stem cells and, due to their inherent ability to produce differentiated progeny with distinct proteomic signatures, are partially protected from attacks on their descendants. Consequently, such well-hidden cells may remain in the body for years to decades. The autoantibody panel developed in this study for basal-like breast cancer exhibits exceptional specificity despite a comparatively small training set. Given its ease of application, this suggests great promise for a more exhaustively trained classifier as a populationlevel screening tool.

 

Condition-Specific Differential Sub-Network Analysis for Biological Systems
Deepali Jhamb, PhD, Indiana University

Biological systems behave differently under different conditions. Advances in sequencing technology over the last decade have led to the generation of enormous amounts of condition-specific data. However, these measurements often fail to identify low-abundance genes and proteins that can be biologically crucial. In this work, a novel textmining system was first developed to extract condition-specific proteins from the biomedical literature. The literaturederived data was then combined with proteomics data to construct condition-specific protein interaction networks. Furthermore, an innovative condition-specific differential analysis approach was designed to identify key differences, in the form of sub-networks, between any two given biological systems. The framework developed here was implemented to understand the differences between limb regenerationcompetent Ambystoma mexicanum and regeneration-deficient Xenopus laevis. This study provides an exhaustive systems-level analysis to compare regeneration competent and deficient sub-networks to show how different molecular entities inter-connect with each other and are rewired during the formation of an accumulation blastema in regenerating axolotl limbs. This study also demonstrates the importance of literature-derived knowledge, specific to limb regeneration, to augment the systems biology analysis. Our findings show that although the proteins might be common between the two given biological conditions, they can have a high dissimilarity based on their biological and topological properties in the sub-network. The knowledge gained from the distinguishing features of limb regeneration in amphibians can be used in future to induce regeneration chemically in mammalian systems. The approach developed in this dissertation is scalable and adaptable to understanding differential sub-networks between any two biological systems. This methodology will not only facilitate the understanding of biological processes and molecular functions that govern a given system, but will also provide novel intuitions about the pathophysiology of diseases/conditions.

Comment: We have long advocated a principle of directly comparing young and old bodies as a means to identify the classes of physical damage that accumulate in the body during aging. This approach circumvents our ignorance of the full etiology of each particular disease manifestation, a phenomenally difficult question given the ethical issues of experimenting on human subjects, the lengthy ‘‘incubation time’’ of aging-related diseases, and the complex interconnections between their risk factors—innate and environmental. Repairing such damage has the potential to prevent pathology before symptoms appear, an approach now becoming increasingly mainstream.11 However, a naı¨ve comparison faces a number of difficulties, even given a sufficiently large sample set to compensate for inter-individual variation. Most importantly, the causal significance of a given species cannot be reliably determined from its simple prevalence.12 The catalytic nature of cell biology means that those entities whose abundance changes the most profoundly in absolute terms are quite unlikely to be the drivers of that change and may even spontaneously revert to baseline levels in the absence of on-going stimulation. Meanwhile, functionality is often heavily influenced independently of abundance by post-translational modifications that may escape direct detection. Sub-network analysis uses computational means to identify groups of genes and/or proteins that vary in a synchronized way with some parameter, indicating functional connectivity. The application of methods such as those developed here to the comparison of a wide range of younger and older conditions will facilitate the identification of processes—not merely individual factors—that are impaired with age, and thus will help greatly in identifying the optimal points for intervention.

 

Development of a Light Actuated Drug Delivery-on-Demand System
Chase Linsley, PhD, University of California, Los Angeles

The need for temporal–spatial control over the release of biologically active molecules has motivated efforts to engineer novel drug delivery-on-demand strategies actuated via light irradiation. Many systems, however, have been limited to in vitro proof-of-concept due to biocompatibility issues with the photo-responsive moieties or the light wavelength, intensity, and duration. To overcome these limitations, the objective of this dissertation was to design a light-actuated drug delivery-on-demand strategy that uses biocompatible chromophores and safe wavelengths of light, thereby advancing the clinical prospects of light-actuated drug delivery-on-demand systems. This was achieved by: (1) Characterizing the photothermal response of biocompatible visible light and near-infrared-responsive chromophores and demonstrating the feasibility and functionality of the light actuated on-demand drug delivery system in vitro; and (2) designing a modular drug delivery-on-demand system that could control the release of biologically active molecules over an extended period of time. Three biocompatible chromophores—Cardiogreen, Methylene Blue, and riboflavin—were identified and demonstrated significant photothermal response upon exposure to near-infrared and visible light, and the amount of temperature change was dependent upon light intensity, wavelength, as well as chromophore concentration. As a proof-of-concept, pulsatile release of a model protein from a thermally responsive delivery vehicle fabricated from poly(N-isopropylacrylamide) was achieved over 4 days by loading the delivery vehicle with Cardiogreen and irradiating with near-infrared light. To extend the useful lifetime of the light-actuated drug delivery-on-demand system, a modular, reservoir-valve system was designed. Using poly(ethylene glycol) as a reservoir for model small molecule drugs combined with a poly(N-isopropylacrylamide) valve spiked with chromophore-loaded liposomes, pulsatile release was achieved over 7 days upon light irradiation. Ultimately, this drug delivery strategy has potential for clinical applications that require explicit control over the presentation of biologically active molecules. Further research into the design and fabrication of novel biocompatible thermally responsive delivery vehicles will aid in the advancement of the light-actuated drug delivery-on-demand strategy described here. Comment: Our combined comments on this thesis and the next one appear after the next abstract.

 

Light-Inducible Gene Regulation in Mammalian Cells
Lauren Toth, PhD, Duke University

The growing complexity of scientific research demands further development of advanced gene regulation systems. For instance, the ultimate goal of tissue engineering is to develop constructs that functionally and morphologically resemble the native tissue they are expected to replace. This requires patterning of gene expression and control of cellular phenotype within the tissue-engineered construct. In the field of synthetic biology, gene circuits are engineered to elucidate mechanisms of gene regulation and predict the behavior of more complex systems. Such systems require robust gene switches that can quickly turn gene expression on or off. Similarly, basic science requires precise genetic control to perturb genetic pathways or understand gene function. Additionally, gene therapy strives to replace or repair genes that are responsible for disease. The safety and efficacy of such therapies require control of when and where the delivered gene is expressed in vivo.

Unfortunately, these fields are limited by the lack of gene regulation systems that enable both robust and flexible cellular control. Most current gene regulation systems do not allow for the manipulation of gene expression that is spatially defined, temporally controlled, reversible, and repeatable. Rather, they provide incomplete control that forces the user to choose to control gene expression in either space or time, and whether the system will be reversible or irreversible. The recent emergence of the field of optogenetics—the ability to control gene expression using light—has made it possible to regulate gene expression with spatial, temporal, and dynamic control. Light-inducible systems provide the tools necessary to overcome the limitations of other gene regulation systems, which can be slow, imprecise, or cumbersome to work with. However, emerging light-inducible systems require further optimization to increase their efficiency, reliability, and ease of use.

Initially, we engineered a light-inducible gene regulation system that combines zinc finger protein technology and the light-inducible interaction between Arabidopsis thaliana plant proteins GIGANTEA (GI) and the light oxygen voltage (LOV) domain of FKF1. Zinc finger proteins (ZFPs) can be engineered to target almost any DNA sequence through tandem assembly of individual zinc finger domains that recognize a specific 3-bp DNA sequence. Fusion of three different ZFPs to GI (GI-ZFP) successfully targeted the fusion protein to the specific DNA target sequence of the ZFP. Due to the interaction between GI and LOV, co-expression of GI-ZFP with a fusion protein consisting of LOV fused to three copies of the VP16 transactivation domain (LOV-VP16) enabled blue-light dependent recruitment of LOV-VP16 to the ZFP target sequence. We showed that placement of three to nine copies of a ZFP target sequence upstream of a luciferase or enhanced green fluorescent protein (eGFP) transgene enabled expression of the transgene in response to blue light. Gene activation was both reversible and tunable on the basis of duration of light exposure, illumination intensity, and the number of ZFP binding sites upstream of the transgene. Gene expression could also be patterned spatially by illuminating the cell culture through photomasks containing various patterns.

Although this system was useful for controlling the expression of a transgene, for many applications it is useful to control the expression of a gene in its natural chromosomal position. Therefore, we capitalized on recent advances in programmed gene activation to engineer an optogenetic tool that could easily be targeted to new, endogenous DNA sequences without re-engineering the light inducible proteins. This approach took advantage of CRISPR/Cas9 technology, which uses a gene-specific guide RNA (gRNA) to facilitate Cas9 targeting and binding to a desired sequence, and the light-inducible heterodimerizers CRY2 and CIB1 from Arabidopsis thaliana to engineer a lightactivated CRISPR/Cas9 effector (LACE) system. We fused the full-length (FL) CRY2 to the transcriptional activator VP64 (CRY2FL-VP64) and the amino-terminal fragment of CIB1 to the amino, carboxyl, or amino and carboxyl terminus of a catalytically inactive Cas9. When CRY2-VP64 and one of the CIBN/dCas9 fusion proteins are expressed with a gRNA, the CIBN/dCas9 fusion protein localizes to the gRNA target. In the presence of blue light, CRY2FL binds to CIBN, which translocates CRY2FL-VP64 to the gene target and activates transcription. Unlike other optogenetic systems, the LACE system can be targeted to new endogenous loci by solely manipulating the specificity of the gRNA without having to re-engineer the light-inducible proteins. We achieved light-dependent activation of the IL1RN, HBG1/2, or ASCL1 genes by delivery of the LACE system and four gene-specific gRNAs per promoter region. For some gene targets, we achieved equivalent activation levels to cells that were transfected with the same gRNAs and the synthetic transcription factor dCas9-VP64. Gene activation was also shown to be reversible and repeatable through modulation of the duration of blue light exposure, and spatial patterning of gene expression was achieved using an eGFP reporter and a photomask.

Finally, we engineered a light-activated genetic ‘‘on’’ switch (LAGOS) that provides permanent gene expression in response to an initial dose of blue light illumination. LAGOS is a lentiviral vector that expresses a transgene only upon Cre recombinase–mediated DNA recombination. We showed that this vector, when used in conjunction with a light-inducible Cre recombinase system, could be used to express MyoD or the synthetic transcription factor VP64- MyoD in response to light in multiple mammalian cell lines, including primary mouse embryonic fibroblasts. We achieved light-mediated up-regulation of downstream myogenic markers myogenin, desmin, troponin T, and myosin heavy chains I and II as well as fusion of C3H10T1/2 cells into myotubes that resembled a skeletal muscle cell phenotype. We also demonstrated LAGOS functionality in vivo by engineering the vector to express human VEGF165 and human ANG1 in response to light. HEK 293T cells stably expressing the LAGOS vector and transiently expressing the light-inducible Cre recombinase proteins were implanted into mouse dorsal window chambers. Mice that were illuminated with blue light had increased micro-vessel density compared to mice that were not illuminated. Analysis of human vascular endothelial growth factor (VEGF) and human ANG1 levels by enzyme-linked immunosorbent assay (ELISA) revealed statistically higher levels of VEGF and ANG1 in illuminated mice compared to non-illuminated mice.

In summary, the objective of this work was to engineer robust light-inducible gene regulation systems that can control genes and cellular fate in a spatial and temporal manner. These studies combine the rapid advances in gene targeting and activation technology with natural light-inducible plant protein interactions. Collectively, this thesis presents several optogenetic systems that are expected to facilitate the development of multicellular cell and tissue constructs for use in tissue engineering, synthetic biology, gene therapy, and basic science both in vitro and in vivo.

Comment: Although it is easy to characterize technological progress as following in the wake of scientific discoveries, the reverse is almost equally true; advances in technique open the door to types of experiment previously intractable or impossible. Such is currently the case for the field of optically controlled biotechnology, which has exploded into prominence, particularly over the last half-decade. Light of an appropriate wavelength can penetrate mammalian tissues to a depth of up to a couple of centimeters, rendering much of the living body accessible to optical study and control—still more if the detector/source is integrated into an endoscopic or fiber optic probe. Techniques borrowed from the semiconductor industry allow patterns of illumination to be controlled down to the nanometer scale, ideal for addressing individual cells. The highly controlled time course of such experiments, as compared to traditional means of gene activation, such as the addition of a chemical agent to the medium, eliminates confounding variables, and simplifies data analysis. Furthermore, this level of immediate control opens the door to closed-loop systems where the activity of entities under optical control can be continuously tuned in relation to some parameter(s). In the first of these two illuminating theses, a vehicle is developed that permits light-driven release of a small molecule. Such a system could be employed to target a systemically administered antibiotic or anti-neoplastic agent to a site of infection or cancer while sparing other bodily tissues from toxicity. Because most modern drugs cannot be produced in the body, even given arbitrarily good control of cellular biochemistry, this technique will have lasting value in numerous clinical contexts. In the second thesis, the level of precision achieved is even more profound; the CRISPR/Cas9 system has received much recent attention13 in its own right for its capacity to target arbitrary genetic sequences without an arduous protein-engineering step. The LACE system described stands to permit genetic manipulation with almost arbitrarily good spatial, temporal, and genomic site-specific control, using only means available to a typical university laboratory.

 

Targeting T Cells for the Immune-Modulation of Human Diseases
Regina Lin, PhD, Duke University

Dysregulated inflammation underlies the pathogenesis of a myriad of human diseases ranging from cancer to autoimmunity. As coordinators, executers, and sentinels of host immunity, T cells represent a compelling target population for immune-modulation. In fact, the antigen-specificity, cytotoxicity, and promise of long-lived of immune-protection make T cells ideal vehicles for cancer immunotherapy. Interventions for autoimmune disorders, on the other hand, aim to dampen T cell–mediated inflammation and promote their regulatory functions. Although significant strides have been made in targeting T cells for immune modulation, current approaches remain less than ideal and leave room for improvement. In this dissertation, I seek to improve on current T cell-targeted immunotherapies, by identifying and pre-clinically characterizing their mechanisms of action and in vivo therapeutic efficacy.

CD8+ cytotoxic T cells have potent anti-tumor activity and therefore are leading candidates for use in cancer immunotherapy. The application of CD8+ T cells for clinical use has been limited by the susceptibility of ex vivo– expanded CD8+ T cells to become dysfunctional in response to immunosuppressive microenvironments. To enhance the efficacy of adoptive cell transfer therapy (ACT), we established a novel microRNA (miRNA)-targeting approach that augments CTL cytotoxicity and preserves immunocompetence. Specifically, we screened for miRNAs that modulate cytotoxicity and identified miR-23a as a strong functional repressor of the transcription factor Blimp-1, which promotes CTL cytotoxicity and effector cell differentiation. In a cohort of advanced lung cancer patients, miR- 23a was up-regulated in tumor-infiltrating CD8+ T cells, and its expression correlated with impaired anti-tumor potential of patient CD8+ T cells. We determined that tumor-derived transforming growth factor-b (TGF-b) directly suppresses CD8+ T cell immune function by elevating miR-23a and down-regulating Blimp-1. Functional blockade of miR-23a in human CD8+ T cells enhanced granzyme B expression; and in mice with established tumors, immunotherapy with just a small number of tumor-specific CD8+ T cells in which miR-23a was inhibited robustly hindered tumor progression. Together, our findings provide a miRNA-based strategy that subverts the immunosuppression of CD8+ T cells that is often observed during adoptive cell transfer tumor immunotherapy and identify a TGF-bmediated tumor immune-evasion pathway

Having established that miR-23a-inhibition can enhance the quality and functional resilience of anti-tumor CD8+ T cells, especially within the immune-suppressive tumor microenvironment, we went on to interrogate the translational applicability of this strategy in the context of chimeric antigen receptor (CAR)-modified CD8+ T cells. Although CAR T cells hold immense promise for ACT, CAR T cells are not completely curative due to their in vivo functional suppression by immune barriers—such as TGF-b—within the tumor microenvironment. Because TGF-b poses a substantial immune barrier in the tumor microenvironment, we sought to investigate whether inhibiting miR-23a in CAR T cells can confer immune competence to afford enhanced tumor clearance. To this end, we retrovirally transduced wild-type and miR-23a–deficient CD8+ T cells with the EGFRvIII-CAR, which targets the PepvIII tumorspecific epitope expressed by glioblastomas (GBM). Our in vitro studies demonstrated that while wild-type EGFRvIIICAR T cells were vulnerable to functional suppression by TGF-b, miR-23a abrogation rendered EGFRvIII-CAR T cells immune-resistant to TGF-b. Rigorous preclinical studies are currently underway to evaluate the efficacy of miR-23adeficient EGFRvIII-CAR T cells for GBM immunotherapy.

Last, we explored novel immune-suppressive therapies by the biological characterization of pharmacological agents that could target T cells. Although immune-suppressive drugs are classical therapies for a wide range of autoimmune diseases, they are accompanied by severe adverse effects. This motivated our search for novel immunesuppressive agents that are efficacious and lack undesirable side effects. To this end, we explored the potential utility of subglutinol A, a natural product isolated from the endophytic fungus Fusarium subglutinans. We showed that subglutinol A exerts multimodal immune-suppressive effects on activated T cells in vitro. Subglutinol A effectively blocked T cell proliferation and survival, while profoundly inhibiting pro-inflammatory interferon-c (IFN-c) and interleukin-17 (IL-17) production by fully differentiated effector Th1 and Th17 cells. Our data further revealed that subglutinol A might exert its anti-inflammatory effects by exacerbating mitochondrial damage in T cells, but not in innate immune cells or fibroblasts. Additionally, we demonstrated that subglutinol A significantly reduced lymphocytic infiltration into the footpad and ameliorated footpad swelling in the mouse model of Th1-driven delayed-type hypersensitivity. These results suggest the potential of subglutinol A as a novel therapeutic for inflammatory diseases.

Comment: Immunotherapy is among the most promising approaches to cancer treatment, having the specificity and scope to selectively target transformed cells wherever they may reside within the body and the potential to install a permanent defense against disease recurrence. By the time a typical cancer is clinically diagnosed, however, it has already found means to survive a prolonged period of potential immune attack. The mechanisms by which tumors evade immune surveillance are beginning to be elucidated,15,16 and include both direct suppression of effector cells and progressive editing of the host’s immune repertoire to disfavor future attack. It is inherently difficult to interfere with these defenses directly, due to the selection pressures in genetically heterogeneous neoplastic tissue. Much effort is thus being focused on methods for rendering therapeutically delivered immune cells resistant to their effects. The cytokine TGF-b is paradoxically known to function as both a tumor suppressor in healthy tissue and as a tumorderived species associated with multiple cancer-promoting activities, including enhanced immune evasion. This work identifies the pathway by which TGF-b compromises cytotoxic T cell function in the tumor microenvironment, and demonstrates an effective method for blocking this signal. In many clinical cases, however, editing of the patient’s immune repertoire has already removed or rendered anergic those immune cells able to recognize their cancer. Thus, the finding that blocking TGF-b signaling also appears to enhance the effectiveness of CAR-modified T cells— engineered with an antibody fragment targeting them with high affinity to a particular tumor-associated epitope—is a welcome addition to these already promising results.

 

Novel Fibonacci and non-Fibonacci structure in the sunflower: results of a citizen science experiment

Jonathan Swinton, Erinma Ochu, The MSI Turing’s Sunflower Consortium

Published 18 May 2016. DOI http://dx.doi.org:/10.1098/rsos.160091

This citizen science study evaluates the occurrence of Fibonacci structure in the spirals of sunflower (Helianthus annuus) seedheads. This phenomenon has competing biomathematical explanations, and our core premise is that observation of both Fibonacci and non-Fibonacci structure is informative for challenging such models. We collected data on 657 sunflowers. In our most reliable data subset, we evaluated 768 clockwise or anticlockwise parastichy numbers of which 565 were Fibonacci numbers, and a further 67 had Fibonacci structure of a predefined type. We also found more complex Fibonacci structures not previously reported in sunflowers. This is the third, and largest, study in the literature, although the first with explicit and independently checkable inclusion and analysis criteria and fully accessible data. This study systematically reports for the first time, to the best of our knowledge, seedheads without Fibonacci structure. Some of these are approximately Fibonacci, and we found in particular that parastichy numbers equal to one less than a Fibonacci number were present significantly more often than those one more than a Fibonacci number. An unexpected further result of this study was the existence of quasi-regular heads, in which no parastichy number could be definitively assigned.

  1. Introduction

Fibonacci structure can be found in hundreds of different species of plants [1]. This has led to a variety of competing conceptual and mathematical models that have been developed to explain this phenomenon. It is not the purpose of this paper to survey these: reviews can be found in [14], with more recent work including [510]. Instead, we focus on providing empirical data useful for differentiating them.

These models are in some ways now very mathematically satisfying in that they can explain high Fibonacci numbers based on a small number of plausible assumptions, though they are not so satisfying to experimental scientists [11]. Despite an increasingly detailed molecular and biophysical understanding of plant organ positioning [1214], the very parsimony and generality of the mathematical explanations make the generation and testing of experimental hypotheses difficult. There remains debate about the appropriate choice of mathematical models, and whether they need to be central to our understanding of the molecular developmental biology of the plant. While sunflowers provide easily the largest Fibonacci numbers in phyllotaxis, and thus, one might expect, some of the stronger constraints on any theory, there is a surprising lack of systematic data to support the debate. There have been only two large empirical studies of spirals in the capitulum, or head, of the sunflower: Weisse [15] and Schoute [16], which together counted 459 heads; Schoute found numbers from the main Fibonacci sequence 82% of the time and Weise 95%. The original motivation of this study was to add a third replication to these two historical studies of a widely discussed phenomenon. Much more recently, a study of a smaller sample of 21 seedheads was carried out by Couder [17], who specifically searched for non-Fibonacci examples, whereas Ryan et al. [18] studied the arrangement of seeds more closely in a small sample of Helianthus annuus and a sample of 33 of the related perennial H. tuberosus.

Neither the occurrence of Fibonacci structure nor the developmental biology leading to it are at all unique to sunflowers. As common in other species, the previous sunflower studies found not only Fibonacci numbers, but also the occasional occurrence of the double Fibonacci numbers, Lucas numbers and F4 numbers defined below [1]. It is worth pointing out the warning of Cooke [19] that numbers from these sequences make up all but three of the first 17 integers. This means that it is particularly valuable to look at specimens with large parastichy numbers, such as the sunflowers, where the prevalence of Fibonacci structure is at its most striking.

Neither Schoute nor Weisse reported their precise technique for assigning parastichy numbers to their samples, and it is noteworthy that neither author reported any observation of non-Fibonacci structure. One of the objectives of this study was to rigorously define Fibonacci structure in advance and to ensure that the assignment method, though inevitably subjective, was carefully documented.

This paper concentrates on the patterning of seeds towards the outer rim of sunflower seedheads. The number of ray florets (the ‘petals’, typically bright yellow) or the green bracts behind them tends to have a looser distribution around a Fibonacci number. In the only mass survey of these, Majumder & Chakravarti [20] counted ray florets on 1002 sunflower heads and found a distribution centred on 21.

This citizen science study evaluates the occurrence of Fibonacci structure in the spirals of sunflower (Helianthus annuus) seedheads. This phenomenon has competing biomathematical explanations, and our core premise is that observation of both Fibonacci and non-Fibonacci structure is informative for challenging such models. We collected data on 657 sunflowers. In our most reliable data subset, we evaluated 768 clockwise or anticlockwise parastichy numbers of which 565 were Fibonacci numbers, and a further 67 had Fibonacci structure of a predefined type. We also found more complex Fibonacci structures not previously reported in sunflowers. This is the third, and largest, study in the literature, although the first with explicit and independently checkable inclusion and analysis criteria and fully accessible data. This study systematically reports for the first time, to the best of our knowledge, seedheads without Fibonacci structure. Some of these are approximately Fibonacci, and we found in particular that parastichy numbers equal to one less than a Fibonacci number were present significantly more often than those one more than a Fibonacci number. An unexpected further result of this study was the existence of quasi-regular heads, in which no parastichy number could be definitively assigned.

Incorporation of irregularity into the mathematical models of phyllotaxis is relatively recent: [17] gave an example of a disordered pattern arising directly from the deterministic model while more recently the authors have begun to consider the effects of stochasticity [10,21]. Differentiating between these models will require data that go beyond capturing the relative prevalence of different types of Fibonacci structure, so this study was also designed to yield the first large-scale sample of disorder in the head of the sunflower.

The Fibonacci sequence is the sequence of integers 1,2,3,5,8,13,21,34,55,89,144… in which each member after the second is the sum of the two preceding. The Lucas sequence is the sequence of integers 1,3,4,7,11,18,29,47,76,123… obeying the same rule but with a different starting condition; the F4 sequence is similarly 1,4,5,9,14,23,37,60,97,…. The double Fibonacci sequence 2,4,6,10,16,26,42,68,110,… is double the Fibonacci sequence. We say that a parastichy number which is any of these numbers has Fibonacci structure. The sequencesF5=1,5,6,11,17,28,45,73,… and F8=1,8,9,17,26,43,69,112… also arise from the same rule, but as they had not been previously observed in sunflowers we did not include these in the pre-planned definition of Fibonacci structure for parsimony. One example of adjacent pairs from each of these sequences was, in fact, observed but both examples are classified as non-Fibonacci below. A parastichy number which is any of 12,20,33,54,88,143 is also not classed as having Fibonacci structure but is distinguished as a Fibonacci number minus one in some of the analyses, and similarly 14,22,35,56,90,145 as Fibonacci plus one.

When looking at a seedhead such as in figure 1 the eye naturally picks out at least one family of parastichies or spirals: in this case, there is a clockwise family highlighted in blue in the image on the right-hand side.

http://d3hu9binmobce5.cloudfront.net/content/royopensci/3/5/160091/F1.medium.gif

Distribution and type of parastichy pairs

Figure 5 plots the individual pairs observed. On the reference line, the ratio of the numbers is equal to the golden ratio so departures from the line mark departures from Fibonacci structure, which are less evident in the more reliable photoreviewed dataset. It can be seen from table 3 that Fibonacci pairings dominate the dataset.

 

http://d3hu9binmobce5.cloudfront.net/content/royopensci/3/5/160091/F5.medium.gif

Table 3.

Observed pairings of Fibonacci types of clockwise and anticlockwise parastichy numbers. Other means any parastichy number which neither has Fibonacci structure nor is Fibonacci ±1. Of all the Fibonacci ±1/Fibonacci pairs, only sample 191, a (21,20) pair, was not close to an adjacent Fibonacci pair.

One typical example of a Fibonacci pair is shown in figure 6, with a double Fibonacci case infigure 1 and a Lucas one in figure 7. There was no photoreviewed example of an F4 pairing. The sole photoreviewed assignment of a parastichy number to the F4 sequence was the anticlockwise parastichy number 37 in sample 570, which was relatively disordered. The clockwise parastichy number was 55, lending support to the idea this may have been a perturbation of a (34,55) pattern. We also found adjacent members of higher-order Fibonacci series. Figures 8 and 9 each show well-ordered examples with parastichy counts found adjacent in the F5 and F8 series, respectively: neither of these have been previously reported in the sunflower.

Figure 6.

 

http://d3hu9binmobce5.cloudfront.net/content/royopensci/3/5/160091/F6.medium.gif

Sunflower 095. An (89,55) example with 89 clockwise parastichies and 55 anticlockwise ones, extending right to the rim of the head. Because these are clear and unambiguous, the other parastichy families which are visible towards the centre are not counted here.

Figure 7.   Sunflower 171. A Lucas series (76,47) example.

Sunflower 667. Anticlockwise parastichies only, showing competing parastichy families which are distinct but in some places overlapping.

Our core results are twofold. First, and unsurprisingly, Fibonacci numbers, and Fibonacci structure more generally, are commonly found in the patterns in the seedheads of sunflowers. Given the extent to which Fibonacci patterns have attracted pseudo-scientific attention [33], this substantial replication of limited previous studies needs no apology. We have also published, for the first time, examples of seedheads related to the F5 and F8 sequences but by themselves they do not add much to the evidence base. Our second core result, though, is a systematic survey of cases where Fibonacci structure, defined strictly or loosely, did not appear. Although not common, such cases do exist and should shed light on the underlying developmental mechanisms. This paper does not attempt to shed that light, but we highlight the observations that any convincing model should explain. First, the prevalence of Lucas numbers is higher than those of double Fibonacci numbers in all three large datasets in the literature, including ours, and there are sporadic appearances of F4, F5 and F8 sequences. Second, counts near to but not exactly equal to Fibonacci structure are also observable: we saw a parastichy count of 54 more often than the most common Lucas count of 47. Sometimes, ambiguity arises in the counting process as to whether an exact Fibonacci-structured number might be obtained instead, but there are sufficiently many unambiguous cases to be confident this is a genuine phenomenon. Third, among these approximately Fibonacci counts, those which are a Fibonacci number minus one are significantly more likely to be seen than a Fibonacci number plus one. Fourth, it is not uncommon for the parastichy families in a seedhead to have strong departures from rotational symmetry: this can have the effect of yielding parastichy numbers which have large departures from Fibonacci structure or which are completely uncountable. This is related to the appearance of competing parastichy families. Fifth, it is common for the parastichy count in one direction to be more orderly and less ambiguous than that in the other. Sixth, seedheads sometimes possess completely disordered regions which make the assignment of parastichy numbers impossible. Some of these observations are unsurprising, some can be challenged by different counting protocols, and some are likely to be easily explained by the mathematical properties of deformed lattices, but taken together they pose a challenge for further research.

It is in the nature of this crowd-sourced experiment with multiple data sources that it is much easier to show variability than it is to find correlates of that variability. We tried a number of cofactor analyses that found no significant effect of geography, growing conditions or seed type but if they do influence Fibonacci structure, they are likely to be much easier to detect in a single-experimenter setting.

We have been forced by our results to extend classifications of seedhead patterns beyond structured Fibonacci to approximate Fibonacci ones. Clearly, the more loose the definition of approximate Fibonacci, the easier it is to explain away departures from model predictions. Couder [17] found one case of a (54,87) pair that he interpreted as a triple Lucas pair 3×(18,29). While mathematically true, in the light of our data, it might be more compellingly be thought of as close to a (55,89) ideal than an exact triple Lucas one. Taken together, this need to accommodate non-exact patterns, the dominance of one less over one more than Fibonacci numbers, and the observation of overlapping parastichy families suggest that models that explicitly represent noisy developmental processes may be both necessary and testable for a full understanding of this fascinating phenomenon. In conclusion, this paper provides a testbed against which a new generation of mathematical models can and should be built.

 

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