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Posts Tagged ‘VEGF receptors’


Contributions to Cardiomyocyte Interactions and Signaling

Author and Curator: Larry H Bernstein, MD, FCAP

and

Curator: Aviva Lev-Ari, PhD, RN

Introduction

This is Part II of the ongoing research in the Lee Laboratory, concerned with Richard T Lee’s dissection of the underlying problems that will lead to a successful resolution of myocardiocyte regeneration unhampered by toxicity, and having a suffuciently sustained effect for an evaluation and introduction to the clinic.  This would be a milestone in the treatment of heart failure, and an alternative to transplantation surgery.  This second presentation focuses on the basic science work underpinning the therapeutic investigations.  It is work that, if it was unsupported and did not occur because of insufficient funding, the Part I story could not be told.

Cardiomyocyte hypertrophy and degradation of connexin43 through spatially restricted autocrine/paracrine heparin-binding EGF

J Yoshioka, RN Prince, H Huang, SB Perkins, FU Cruz, C MacGillivray, DA Lauffenburger, and RT Lee *
Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; and Biological Engineering Division, MIT, Cambridge, MA
PNAS 2005; 302(30):10622-10627.  http://pnas.org/cgi/doi/10.1073/pnas.0501198102

Growth factor signaling can affect tissue remodeling through autocrine/paracrine mechanisms. Recent evidence indicates that EGF receptor transactivation by heparin-binding EGF (HB-EGF) contributes to hypertrophic signaling in cardiomyocytes. Here, we show that HB-EGF operates in a spatially restricted circuit in the extracellular space within the myocardium, revealing the critical nature of the local microenvironment in intercellular signaling. This highly localized microenvironment of HB-EGF signaling was demonstrated with 3D morphology, consistent with predictions from a computational model of EGF signaling. HB-EGF secretion by a given cardiomyocyte in mouse left ventricles led to cellular hypertrophy and reduced expression of connexin43 in the overexpressing cell and in immediately adjacent cells but not in cells farther away. Thus, HB-EGF acts as an autocrine and local paracrine cardiac growth factor that leads to loss of gap junction proteins within a spatially confined microenvironment. These findings demonstrate how cells can coordinate remodeling with their immediate neighboring cells with highly localized extracellular EGF signaling. Within 3D tissues, cells must coordinate remodeling in response to stress or growth signals, and this communication may occur by direct contact or by secreted signaling molecules. Cardiac hypertrophy is a physiological response that enables the heart to adapt to an initial stress; however, hypertrophy can ultimately lead to the deterioration in cardiac function and an increase in cardiac arrhythmias. Although considerable progress has been made in elucidating the molecular pathogenesis of cardiac hypertrophy, the precise mechanisms guiding the hypertrophic process remain unknown. Recent evidence suggests that myocardial heparin-binding (HB)-epidermal growth factor participates in the hypertrophic response. In cardiomyocytes, hypertrophic stimuli markedly increase expression of the HB-EGF gene, suggesting that HB-EGF can act as an autocrine trophic factor that contributes to cellular growth. HB-EGF is first synthesized as a membrane-anchored form (proHB-EGF), and subsequent ectodo-main shedding at the cell surface releases the soluble form of HB-EGF. Soluble HB-EGF is a diffusible factor that can be captured by the receptors to activate the intracellular EGF receptor signaling cascade. Indeed, EGF receptor (EGFR) transactivation, triggered by shedding of HB-EGF from the cell surface, plays an important role in cardiac hypertrophy resulting from pressure overload in the aortic-banding model. EGFR activation can occur through autocrine and paracrine signaling. In autocrine signaling, a cell produces and responds to the same signaling molecules. Paracrine signaling molecules can target groups of distant cells or act as localized mediators affecting only cells in the immediate environment of the signaling cell. Thus, although locally produced HB-EGF may travel through the extra-cellular space, it may also be recaptured by the EGFR close to the point where it was released from the cell surface. The impact of spatially localized microenvironments of signaling could be extensive heterogeneous tissue remodeling, which can be particularly important in an electrically coupled tissue like myocardium. Interestingly, recent data suggest that EGF can regulate protea-some-dependent degradation of connexin43 (Cx43), a major trans-membrane gap junction protein, in liver epithelial cells, along with a rapid inhibition of cell–cell communication through gap junctions. One of the critical potential myocardial effects of HB-EGF could therefore be to increase degradation of Cx43 and reduce electrical stability of the heart. Reduced content of Cx43 is commonly observed in chronic heart diseases such as hypertrophy, myocardial infarction, and failure. Thus, we hypothesized that HB-EGF signals may operate in a spatially restricted local circuit in the extracellular space. We also hypothesized that HB-EGF secretion by a given cardiomyocyte could create a local remodeling microenvironment of decreased Cx43 within the myocardium. To explore whether HB-EGF signaling is highly spatially constrained, we took advantage of the nonuniform gene transfer to cardiac myocytes in vivo, normally considered a pitfall of gene therapy. We also performed computational modeling to predict HB-EGF dynamics and developed a 3D approach to measure cardiomyocyte hypertrophy.

Results

Autocrine HB-EGF and Cardiomyocyte Growth.

To assess the effects of gene transfer of HB-EGF on cardiomyocyte hypertrophy, cells were infected with adenoviral vectors expressing GFP alone (Ad-GFP) or HB-EGF and GFP (Ad-HB-EGF). At this level of infection, 99% of cardiomyocytes were transduced. The incidence of apoptotic cell death (sub-G1 fraction) was not different between Ad-GFP cells, suggesting that expression of GFP by the adenoviral vector was not cardiotoxic in these conditions. Western analysis by using an anti-HB-EGF antibody confirmed successful gene transfer of HB-EGF in cardiomyocytes (18 ± 5-fold, n = 4, P < 0.01); HB-EGF appeared electrophoretically as several bands from 15 to 30 kDa (Fig. 1A). The strongest band corresponds to the soluble 20-kDa form of HB-EGF. To confirm that Ad-HB-EGF results in cellular hypertrophy, cell size and protein synthesis were measured. Ad-HB-EGF enlarged cardiomyocytes compared with Ad-GFP-infected cells by phase-contrast microscopy (24 ± 10% increase in cell surface area, n = 27, P < 0.05) and with flow cytometry analysis (26 ± 10% increase of Ad-GFP infected cells, P < 0.01, Fig. 1B). Overexpression of HB-EGF increased total protein synthesis in cardiomyocytes as measured by [3H]leucine uptake (34 ± 6% of Ad-GFP, n = 6, P < 0.01, Fig. 1C). Uninfected cells within the same dish (and thus sharing the same culture media) did not develop hypertrophy. Additionally, medium from cultures previously infected with Ad-HB-EGF for 48 h was collected and applied to adenovirus-free cultures. Conditioned medium from Ad-HB-EGF-infected cardiomyocytes failed to stimulate hypertrophy in naive cardiomyocytes (Fig. 1C), and there were no significant differences in cell size between noninfected cells from Ad-GFP and Ad-HB-EGF dishes. These results suggest that HB-EGF acts primarily as an autocrine growth factor in cardiomyocytes in vitro.
Because the dilution factor in culture media is important for autocrine/paracrine signaling, we determined the concentration of soluble HB-EGF in the conditioned medium and the effective concentration to stimulate cardiomyocyte growth. HB-EGF levels in the conditioned medium from Ad-HB-EGF dishes were 258 ± 73 pg/ml (n = 4), whereas HB-EGF levels from Ad-GFP dishes (n = 8) were below the limit of detection (6.7 pg/ml). The addition of 300 pg/ml of exogenous recombinant HB-EGF into fresh media failed to stimulate hypertrophy in cardiomyocytes as measured by [3H]leucine uptake (-12 ± 5.0% compared with control, n = 5,P = not significant), but 2,000 pg/ml of recombinant HB-EGF did result in a significant effect (+24 ± 5.5% compared with control, n = 6, P < 0.05). This comparison implies that the local concentration of autocrine ligand is substantially greater than that indicated by a bulk measurement of conditioned media, consistent with previous experimental and theoretical studies.

Fig. 1. Effects of gene transfer of HB-EGF on rat neonatal cardiomyocyte growth.

(A) Cells were infected with adenoviral vectors expressing GFP (Ad-GFP), or HB-EGF and GFP (Ad-HB-EGF). Western analysis showed the successful gene transfer of HB-EGF. (8) FACS analysis of 5,000 cardiomyocytes demonstrated that overexpression of HB-EGF produced a 26 ± 10% increase in cell size that was significantly greater than the overex-pression of GFP. Bar graphs with errors represent mean ± SEM from three independent experiments. **, P < 0.01 vs. Ad-HB-EGF-nonin-fected cells and Ad-GFP nonin-fected cells. , P < 0.05 vs. Ad-GFP infected cells. (C) Overexpression of HB-EGF resulted in a 34 ± 6% increase in [3H]leucine uptake compared with Ad-GFP (n = 6), whereas conditioned medium from Ad-HB-EGF cells caused an only insignificant increase. **, P < 0.05 vs. Ad-GFP control and conditioned medium Ad-GFP.

 Effects of HB-EGF on Cx43 Content in Cultured Cardiomyocytes

Because EGF can induce degradation of the gap junction protein Cx43 in other cells, we then determined whether Cx43 is regulated by HB-EGF in cardiomyocytes. Fig. 2A shows a representative immunoblot from three separate experiments in which Cx43 migrated as three major bands at 46, 43, and 41 kDa, as reported in ref. 16. Overexpression of HB-EGF decreased total Cx43 content (27 ± 11% compared with Ad-GFP, n = 4, P < 0.05) without affecting the intercellular adhesion protein, N-cadherin. The phosphorylation of ERK1/2, an intracellular signaling kinase downstream of EGFR transactivation, was augmented by HB-EGF (3.2 ± 1.0-fold compared with Ad-GFP, n = 4, P < 0.05). Northern analysis showed that HB-EGF did not reduce Cx43 gene expression, suggesting that HB-EGF decreases Cx43 by posttranslational modification (Fig. 2B). AG 1478 (10 iLM), a specific inhibitor of EGFR tyrosine kinase, abolished the effect of HB-EGF on Cx43 (Fig. 2C), indicating that the decrease in Cx43 content depends on EGFR transactivation by HB-EGF. The conditioned medium from Ad-HB-EGF-infected cells did not change expression of Cx43 in naive cells, even though ERK1/2 was slightly activated by the conditioned medium (Fig. 1D). These data are consistent with the hypertrophy data presented above, demonstrating that HB-EGF can act as a predominantly autocrine factor both in hypertrophy and in the reduction of Cx43 content in cardiomyocytes.

Computational Analysis Predicts HB-EGF Autocrine/Paracrine Signaling in Vivo.

Although these in vitro experiments showed HB-EGF as a predominantly autocrine cardiac growth factor, HB-EGF signaling in vivo takes place in a very different environment. Therefore, we sought to determine the extent that soluble HB-EGF may travel in the interstitial space of the myocardium with a simple 2D model of HB-EGF diffusion (Fig. 3A). An approximate geometric representation of myocytes in cross-section is a square (15 x 15 iLm), with each of the corners occupied by a capillary (diameter 5 iLm). The cell shape was chosen so that the extracellular matrix width (0.5 iLm), in which soluble HB-EGF is free to diffuse, was constant around all tissue features. This model geometry is based on a square array of capillaries; although a hexagonal pattern of capillary distribution is commonly accepted, the results are not expected to be substantially different with this simpler construction, because both have four capillaries surrounding each myocyte. The model represents a single central cell that is releasing HB-EGF at a constant rate, Rgen, (approximated from the HB-EGF concentration measurement in conditioned medium) into the extracellular space. HB-EGF then can diffuse throughout this space, or enter a capillary and leave the system. This system is governed by
  • the diffusion equation at steady state (DV2C = 0),
  • the boundary condition for the ligand producing cell (—DVC = Rgen),
  • the boundary condition for all other cells (—DVC = 0), and
  • the capillary boundary condition (DVC = h(C — Cblood)).

C denotes HB-EGF concentration, D is the diffusivity constant, h is the mass transfer coefficient, and Cblood is the concentration of HB-EGF in the blood, approximated to be zero.  The numerical solution in Fig. 3B illustrates that HB-EGF remained localized around the cell which produced it and did not diffuse farther because of the sink-like effect of the capillaries. The maximum concentration of soluble HB-EGF achieved is 0.27 nM, which is near the threshold level of HB-EGF measured to stimulate cardiomyocyte growth (2,000 pg/ml). Therefore, the central HB-EGF-producing cell only signals to its four adjacent neighbors where the HB-EGF concentration reaches this threshold. However, if the model geometry is altered to reflect a 50% and 150% increase in cross-sectional area in all cells because of hypertrophy, estimated from 1 and 4 weeks of transverse aortic constriction, the maximum concentration achieved increases slightly to 0.29 nM and 0.37 nM, respectively. As the cell width increases, HB-EGF must diffuse farther to reach a capillary, exposing adjacent cells to a higher concentration during hypertrophy. However, no additional cells are exposed to HB-EGF. 

Fig. 3. Computational modeling of HB-EGF diffusion in the myocardium.

Red areas represent capillaries, green represents the HB-EGF ligand producing cell, pink represents adjacent cells, and white is an extracellular matrix where HB-EGF is free to diffuse. (A) The model geometry where HB-EGF is generated by the ligand-producing cell at a constant rate, Rgen, and diffuses throughout the extracellular space or enters a capillary and leaves the system with a mass transfer coefficient, h. (B) Numerical solution of the steady-state HB-EGF concentration profile with Rgen = 10 cell-1s-1, D = 0.7 µm2/s, and h = 0.02 µm/s, where concentration is shown by the color scale and height depicted. The maximum concentration achieved with the stated parameters was 0.27 nM from a capillary. Myocyte length was assumed to be 100 µm.

The driving force that determined the extent to which HB-EGF traveled was the rate of HB-EGF transfer into the capillaries and the diffusivity of HB-EGF. The exact mechanism of macromolecule transport into capillaries is unknown; however, it is most likely through diffusion, transcytosis, or a combination of the two. In the case of diffusion, the mass transfer coefficient governing the flux of HB-EGF through the capillary wall is coupled to the diffusivity of HB-EGF, whereas the terms are uncoupled for the case of transcytosis. Therefore, this model assessed transcytosis as a conservative scenario for HB-EGF localization. Parameter perturbation with uncoupled diffusion and capillary mass transfer showed that HB-EGF remained localized around the origin of production and diffused only to immediate neighbors for mass transfer coefficients >0.002 µm/s. For values <0.002 µm/s, HB-EGF diffused distances more than two cells away from the origin. Although the actual mass transfer coefficient of ligands in the size range of HB-EGF is unknown, values for O2 (0.02 µm/s, 0.032 kDa) (19) and LDL (1.7 x 10-5 µm/s, 2,000–3,000 kDa) (20) have been reported, and we assumed HB-EGF is in the upper end of that range due to its small size. HB-EGF also binds to EGFRs, the extracellular matrix, and cell surface heparan sulfate proteoglycans. EGFR binding and internalization could serve to further localize HB-EGF. The number of extracellular binding sites does not affect the steady-state HB-EGF concentration profile if this binding is reversible. However, these binding sites could serve to localize HB-EGF as the cell begins to produce the ligand by slowing the travel of HB-EGF to the capillaries in the approach to the steady state, or as a source of HB-EGF as the cell slows or stops HB-EGF production. At a diffusivity of 0.7 µm2/s (21), HB-EGF traveled only one cell away, but traveled approximately five cells away at 51.8 µm2/s (22), with a peak concentration below the estimated threshold for stimulating.

Overexpression of HB-EGF Causes Hypertrophy on the Infected Cell and Its Immediate Neighbor in Vivo.

To explore whether HB-EGF signals operate in a spatially restricted local circuit in the in vivo myocardial extracellular space as predicted by computational modeling, adenoviral vectors were injected directly into the left ventricular free wall in 26 male mice (Ad-GFP, n = 12; Ad-HB-EGF, n = 14). Of the 26 mice, 5 (4 Ad-GFP and 1 Ad-HB-EGF) mice died after the surgery. Gene expression was confirmed as positive cellular fluorescence in the presence of GFP, allowing determination of which cells were infected at 7 days (Fig. 4A). Immunohis-tochemical staining revealed that HB-EGF was localized on the Ad-HB-EGF-infected cell membrane or in the extracellular space around the overexpressing cell (Fig. 4A). For comparison, remote cells were defined as noninfected cells far (15–20 cell dimensions) from the adenovirus-infected area and in the same field as infected cells. Conventional 2D cross-sectional analysis blinded to treatment group (Fig. 4B) showed that Ad-GFP-infected cells (n = 102) resulted in no cellular hypertrophy compared with noninfected, adjacent (n = 92), or remote (n = 97) cells (2D myocyte cross-sectional area, 250 ± 7 versus 251 ± 7 or 255 ± 6 µm2, respectively). These data suggest that expression of GFP in these conditions does not cause cellular hypertrophy. However, overexpression of HB-EGF caused hypertrophy in both Ad-HB-EGF-infected cells (a 41 ± 5% increase of Ad-GFP-infected cells, n = 119, P < 0.01) and noninfected adjacent cells (a 33 ± 5% increase of Ad-GFP-adjacent cells, n = 97, P < 0.01) compared with remote cells (n = 109). Because 2D analysis of cardiomyocyte hypertrophy can be influenced by the plane of sectioning, we then developed a 3D histology approach that allowed reconstruction of cardiomyocytes in situ (Fig. 4C). We performed an independent 3D histology analysis of cardiomyocytes to determine cell volumes, blinded to treatment group (Fig. 4B). The volumes of both HB-EGF-infected cells (n = 19, 42,700 ± 4,000 µm3) and their adjacent cells (n = 11, 33,500 ± 3,300 µm3) were significantly greater than volumes of remote cells (n = 13, 18,600 ± 1,700 µm3, P < 0.01 vs. HB-EGF-infected cells and P < 0.05 vs. HB-EGF-adjacent cells, Fig. 4D). In contrast, cells treated with Ad-GFP (n = 12) showed no hypertrophy in the Ad-GFP-adjacent (n = 10) or remote cells (n = 9). These data demonstrate that HB-EGF acts as both an autocrine and local paracrine growth factor within myocardium, as predicted by computational modeling.

Degradation of Cx43 Through Local Autocrine/Paracrine HB-EGF

To determine whether the spatially confined effect of HB-EGF reduces local myocardial Cx43 in vivo, Cx43 was assessed with immunohistochemistry and confocal fluorescence imaging. Cells infected with Ad-HB-EGF had significant decreases in Cx43 immunoreactive signal compared with Ad-GFP cells, consistent with the results of in vitro immunoblotting (Fig. 5A). Quantitative digital image analyses of Cx43 in a total of 22 fields in 6 Ad-HB-EGF hearts and 19 fields in 4 Ad-GFP hearts were analyzed (Fig. 5B). Although Ad-GFP-infected cells showed immunoreactive Cx43 at the appositional membrane, overexpression of HB-EGF increased Cx43 in intracellular vesicle-like components (Fig. 5C), with reduced gap junction plaques (percent Cx43 area per cell area, 52 ± 8% of Ad-GFP control, P < 0.01). These data suggest that reduced expression of Cx43 can be attributed to an increased rate of internalization and degradation in gap junction plaques in cardiomyocytes. Interestingly, HB-EGF secretion by a given cardiomyocyte caused a 37 ± 13% reduction of Cx43 content in its adjacent cells compared with GFP controls (P < 0.05). As degradation of Cx43 may accompany structural changes with marked rearrangement of intercellular connections.  In contrast to Cx43, there was no significant difference in total area occupied by N-cadherin immunoreactive signal in between Ad-GFP (n = 19) and Ad-HB-EGF hearts (1.8 ± 0.5-fold compared with Ad-GFP, n = 17, P = not significant), indicating that HB-EGF has a selective effect on Cx43. Taken together, these data show that HB-EGF leads to cardiomyocyte hypertrophy and degradation of Cx43 in the infected cell and its immediately adjacent neighbors because of autocrine/ paracrine signaling. It should be noted, however, that quantifying the Cx43 from immunostaining could be limited by a nonlinear relation between the amount of Cx43 present and the area of staining.

Fig. 4. Effects of gene transfer of HB-EGF on cardiomyocyte hypertrophy in vivo.

(A) Adenoviral vectors (Ad-GFP or Ad-HB-EGF) were injected into the left ventricular free wall in mice. Myocytes were grouped as infected or noninfected on the basis of GFP fluorescence. Overex-pression of HB-EGF was confirmed by im-munohistochemistry. The presented image was pseudocolored with blue from that stained with Alexa Fluor 555 for the presence of HB-EGF. (Scale bars: 20 sm.) (B) 2D cross-sectional area of cardiomyo-cytes was measured in infected and non-infected cells in the same region of the same animal. Overexpression of HB-EGF caused cellular hypertrophy in both infected and adjacent cells. **, P < 0.01 vs. Ad-GFP infected; , P < 0.01 vs. Ad-HB-EGF remote; and §, P < 0.01 vs. Ad-GFP adjacent cells. GFP (infected 102 cells, adjacent 92 cells, and remote 97 cells from 5 mice), and HB-EGF (infected 119 cells, adjacent 97 cells, and remote 109 cells from 7 mice). The 3D histology also revealed cellular hypertrophy in both Ad-HB-EGF-infected cell and its adjacent cell. **, P < 0.01 vs. Ad-GFP infected; , P < 0.01; and *, P < 0.05 vs. Ad-HB-EGF remote cells. GFP (infected 12 cells, adjacent 10 cells, and remote 9 cells), and HB-EGF (infected 19 cells, adjacent 11 cells, and remote 13 cells). Statistical analysis was performed with one-way ANOVA. (C) Sample image of extracted myocytes in three dimensions.

Discussion

We have demonstrated in this study that HB-EGF secreted by cardiomyocytes leads to cellular growth and reduced expression of the principal ventricular gap junction protein Cx43 in a local autocrine/paracrine manner. Although proHB-EGF is biologically active as a juxtacrine growth factor that can signal to immediately neighboring cells in a nondiffusible mannerseveral studies have revealed the crucial role of metalloproteases in the enzymatic conversion of proHB-EGF to soluble HB-EGF, which binds to and activates the EGFR. Hypertrophic stimuli such as mechanical strain and G protein-coupled receptors agonists mediate cardiac hypertrophy through the shedding of membrane-bound proHB-EGF. Thus, an autocrine/paracrine loop, which requires the diffusible, soluble form of HB-EGF, is necessary for subsequent transactivation of the EGFR to produce the hypertrophic response.

To our knowledge, there have been no previous reports concerning the spatial extent of autocrine/paracrine ligand distribution and signaling in myocardial tissue. A theoretical analysis by Shvartsman et al. predicted, from computational modeling in an idealized cell culture environment, that autocrine ligands may remain highly localized, even within subcellular distances; this prediction has support from experimental data in the EGFR system. In contrast, a theoretical estimate by Francis and Palsson has suggested that cytokines might effectively communicate larger distances, approximated to be 200–300 m from the point of release. However, these studies have all focused on idealized cell culture systems, so our combined experimental and computational investigation here aimed at understanding both in vitro and in vivo situations offers insight.
Our computational model of diffusion in the extracellular space predicts that HB-EGF acts as both an autocrine and spatially restricted paracrine growth factor for neighboring cells. We studied the responses of the signaling cell and its immediate neighbors compared with more distant cells. For a paracrine signal to be delivered to its proper target, the secreted signaling molecules cannot diffuse too far; in vitro experiments, in fact, indicated that HB-EGF acts as a predominantly autocrine signal in cell culture, where diffusion into the medium is relatively unconstrained.
In contrast, in the extracellular space of the myocardium, HB-EGF is localized around the source of production because of tissue geometry, thereby acting in a local paracrine or autocrine manner only. Indeed, our results from in vivo gene transfer demonstrated that both the cell releasing soluble HB-EGF and its surrounding cells undergo hypertrophy. This localized conversation between neighboring cells may allow remodeling to be fine-tuned on a highly spatially restricted level within the myocardium and in other tissues.

Common genetic variation at the IL1RL1locus regulates IL-33/ST2 signaling

JE Ho, Wei-Yu Chen, Ming-Huei Chen, MG Larson, ElL McCabe, S Cheng, A Ghorbani, E Coglianese, V Emilsson, AD Johnson,….. CARDIoGRAM Consortium, CHARGE Inflammation Working Group, A Dehghan, C Lu, D Levy, C Newton-Cheh, CHARGE Heart Failure Working Group, …. JL Januzzi, RT Lee, and TJ Wang J Clin Invest Oct 2013; 123(10):4208-4218.  http://dx.doi.org/10.1172/JCI67119

Abstract and Introduction

The suppression of tumorigenicity 2/IL-33 (ST2/IL-33) pathway has been implicated in several immune and inflammatory diseases. ST2 is produced as 2 isoforms. The membrane-bound isoform (ST2L) induces an immune response when bound to its ligand, IL-33. The other isoform is a soluble protein (sST2) that is thought to be a decoy receptor for IL-33 signaling. Elevated sST2 levels in serum are associated with an increased risk for cardiovascular disease. We investigated the determinants of sST2 plasma concentrations in 2,991 Framing­ham Offspring Cohort participants. While clinical and environmental factors explained some variation in sST2 levels, much of the variation in sST2 production was driven by genetic factors. In a genome-wide associ­ation study (GWAS), multiple SNPs within IL1RL1 (the gene encoding ST2) demonstrated associations with sST2 concentrations. Five missense variants of IL1RL1 correlated with higher sST2 levels in the GWAS and mapped to the intracellular domain of ST2, which is absent in sST2. In a cell culture model, IL1RL1 missense variants increased sST2 expression by inducing IL-33 expression and enhancing IL-33 responsiveness (via ST2L). Our data suggest that genetic variation in IL1RL1 can result in increased levels of sST2 and alter immune and inflammatory signaling through the ST2/IL-33 pathway. Suppression of tumorigenicity 2 (ST2) is a member of the IL-1 receptor (IL-1R) family that plays a major role in immune and inflammatory responses. Alternative promoter activation and splicing produces both a membrane-bound protein (ST2L) and a soluble form (sST2). The transmembrane form of ST2 is selectively expressed on Th2- but not Th1-type T cells, and bind­ing of its ligand, IL-33, induces Th2 immune responses.  In contrast, the soluble form of ST2 acts as a decoy receptor by sequestering IL-33. The IL-33/ST2 pathway has important immunomodulatory effects. Clinically, the ST2/IL-33 signaling pathway participates in the pathophysiology of a number of inflammatory and immune diseases related to Th2 activation, including asthma, ulcera­tive colitis, and inflammatory arthritis. ST2 expression is also upregulated in cardiomyocytes in response to stress and appears to have cardioprotective effects in experimental studies. As a biomarker, circulating sST2 concentrations have been linked to worse prognosis in patients with heart failure, acute dyspnea, and acute coronary syndrome, and also predict mortality and incident cardiovascular events in individuals without existing cardiovascular disease. Both sST2 and its transmembrane form are encoded by IL-1R– like 1 (IL1RL1). Genetic variation in this pathway has been linked to a number of immune and inflammatory diseases. The contribution of IL1RL1 locus variants to interindividual variation in sST2 has not been investigated. The emergence of sST2 as an important predictor of cardiovascular risk and the important role outside of the ST2/IL-33 pathway in inflammatory diseases highlight the value of understanding genetic determinants of sST2. The fam­ily-based FHS cohort provides a unique opportunity to examine the heritability of sST2 and to identify specific variants involved using a genome-wide association study (GWAS). Thus, we per­formed a population-based study to examine genetic determinants of sST2 concentrations, coupled with experimental studies to elu­cidate the underlying molecular mechanisms.

Results

Clinical characteristics of the 2,991 FHS participants are presented in Supplemental Table 1 (supplemental material available online with this article; doi:10.1172/JCI67119DS1). The mean age of participants was 59 years, and 56% of participants were women. Soluble ST2 concentrations were higher in men compared with those in women (P < 0.001). Soluble ST2 concentrations were positively associated with age, systolic blood pressure, body-mass index, antihypertensive medication use, and diabetes mellitus (P < 0.05 for all). Together, these variables accounted for 14% of the variation in sST2 concentrations. The duration of hypertension or diabetes did not materially influence variation in sST2 concentra­tions. After additionally accounting for inflammatory conditions, clinical variables accounted for 14.8% of sST2 variation.

Heritability of sS72.

The age- and sex-adjusted heritability (h2) of sST2 was 0.45 (P = 5.3 x 10–16), suggesting that up to 45% of the vari­ation in sST2 not explained by clinical variables was attributable to genetic factors. Multivariable adjustment for clinical variables pre­viously shown to be associated with sST2 concentrations (21) did not attenuate the heritability estimate (adjusted h2 = 0.45, P = 8.2 x 10–16). To investigate the influence of shared environmental fac­tors, we examined the correlation of sST2 concentrations among 603 spousal pairs and found no significant correlation (r = 0.05, P = 0.25).

Genetic correlates of sS72.

We conducted a GWAS of circulating sST2 concentrations. Quantile-quantile, Manhattan, and regional linkage disequilibrium plots are shown in Supplemental Figures 1–3.  All genome-wide significant SNPs were located in a 400-kb linkage disequilibrium block that included IL1RL1 (the gene encoding ST2), IL1R1, IL1RL2, IL18R1, IL18RAP, and SLC9A4 (Figure 1). Results for 11 genome-wide significant “indepen­dent” SNPs, defined as pairwise r2 < 0.2, are shown in Table 1. In aggregate, these 11 “independent” genome-wide significant SNPs across the IL1RL1 locus accounted for 36% of heritability of sST2. In conditional analyses, 4 out of the 11 SNPs remained genome-wide significant, independent of each other (rs950880, rs13029918, rs1420103, and rs17639215), all within the IL1RL1 locus. The most significant SNP (rs950880, P = 7.1 x 10–94) accounted for 12% of the residual interindividual variability in circulating sST2 concentrations. Estimated mean sST2 concen­trations were 43% higher in major homozygotes (CC) compared with minor homozygotes (AA). Tree loci outside of the IL1RL1 locus had suggestive associations with sST2 (P < 1 x 10–6) and are displayed in Supplemental Table 3.

In silico association with expression SNPs.

The top 10 sST2 SNPs (among 11 listed in Table 1) were explored in collected gene expression databases. There were 5 genome-wide significant sST2 SNPs associated with gene expression across a variety of tissue types (Table 2). Specifically, rs13001325 was associated with IL1RL1 gene expression (the gene encoding both soluble and transmembrane ST2) in several subtypes of brain tissue (prefrontal cortex, P = 1.95 x 10–12; cerebellum, P = 1.54 x 10–5; visual cortex, P = 1.85 x 10–7). The CC genotype of rs13001325 was associated with a higher IL1RL1 gene expression level as well as a higher circulating sST2 concentration when compared with the TT genotype (Supplemental Figure 4). Other ST2 variants were significantly associated with IL18RAP (P = 8.50 x 10–41, blood) and IL18R1 gene expression (P = 2.99 x 10–12, prefrontal cortex).

In silico association with clinical phenotypes in published data

The G allele of rs1558648 was associated with lower sST2 concentra­tions in the FHS (0.88-fold change per G allele, P = 3.94 x 10–16) and higher all-cause mortality (hazard ratio [HR] 1.10 per G allele, 95% CI 1.03–1.16, P = 0.003) in the CHARGE consortium, which observed 8,444 deaths in 25,007 participants during an average fol­low-up of 10.6 years (22). The T allele of rs13019803 was associated with lower sST2 concentrations in the FHS (0.87-fold change per G allele, P = 5.95 x 10–20), higher mortality in the CHARGE consor­tium (HR 1.06 per C allele, 95% CI 1.01–1.12, P = 0.03), and higher risk of coronary artery disease (odds ratio 1.06, 95% CI 1.00–1.11, P = 0.035) in the CARDIoGRAM consortium, which included 22,233 individuals with coronary artery disease and 64,762 controls (23). In relating sST2 SNPs to other clinical phenotypes (including blood pressure, body-mass index, lipids, fasting glucose, natriuretic peptides, C-reactive protein, and echocardiographic traits) in pre­viously published studies, we found nominal associations with C-reactive protein for 2 SNPs (Supplemental Table 4).

Putative functional variants.

Using GeneCruiser, we examined nonsynonymous SNPs (nSNPs) (missense variants) that had at least suggestive association with sST2 (P < 1 x 10–4), includ­ing SNPs that served as proxies (r2 = 1.0) for nSNPs within the 1000 Genomes Pilot 1 data set (ref. 24 and Table 3). There were 6 missense variants located within the IL1RL1 gene, 5 of which had genome-wide significant associations with sST2 concen­trations, including rs6749114 (proxy for rs10192036, Q501K), rs4988956 (A433T), rs10204137 (Q501R), rs10192157 (T549I), rs10206753 (L551S), and rs1041973 (A78AE). Base substitutions and corresponding amino acid changes for these coding muta­tions are listed in Table 3. In combination, these 6 missense muta­tions accounted for 5% of estimated heritability, with an effect estimate of 0.23 (standard error [s.e.] 0.02, P = 2.4 x 10–20). When comparing major homozygotes with minor homozygotes, the esti­mated sST2 concentrations for these missense variants differed by 11% to 15% according to genotype (Supplemental Table 5). In conditional analyses, intracellular and extracellular variants appeared to be independently associated with sST2. For instance, in a model containing rs4988956 (A433T) and rs1041973 (A78E), both SNPs remained significantly associated with sST2 (P = 2.61 x 10–24 and P = 7.67 x 10–15, respectively). In total, missence variants added little to the proportion of sST2 variance explained by the 11 genome-wide significant nonmissense variants listed in Table 1. In relating these 6 missense variants to other clinical phenotypes in large consortia, we found an association with asthma for 4 out of the 6 variants (lowest P = 4.8 x 10–12 for rs10204137) (25).

Homology map of IL1RL1 missense variants and ST2 structure.

Of the 6 missense variants mapping to IL1RL1, 5 were within the cytoplas­mic Toll/IL-1R (TIR) domain of the transmembrane ST2 receptor (Figure 2A), and these intracellular variants are thus not part of the circulating sST2 protein. Of these cytoplasmic domain variants, A433T was located within the “box 2” region of sequence conserva­tion, described in the IL-1R1 TIR domain as important for IL-1 sig­naling . Q501R/K was within a conserved motif called “box 3,” but mutants of IL-1R1 in box 3 did not significantly affect IL-1 signaling in previous experiments (26). Both T549I and L551S were near the C terminus of the transmembrane ST2 receptor and were not predicted to alter signaling function based on previous exper­iments with the IL-1R . The A78E SNP was located within the extracellular domain of ST2 and is thus present in both the sST2 isoform and the transmembrane ST2 receptor. In models of the ST2/IL-33/IL-1RAcP complex derived from a crystal structure of the IL-1RII/IL-1β/IL-1RAcP complex (protein data bank ID 1T3G and 3O4O), A78E was predicted to be located on a surface loop within the first immunoglobulin-like domain (Figure 2B), distant from the putative IL-33 binding site or the site of interaction with IL-1RAcP. There were 2 rare extracellular variants that were not cap­tured in our GWAS due to low minor allele frequencies (A80E, MAF 0.008; A176T, MAF 0.002). Both were distant from the IL-33 bind­ing site on homology mapping and unlikely to affect IL-33 binding.

Functional effects of IL1RL1 missense variants on sST2 expression and promoter activity.

Since 5 of the IL1RL1 missense variants asso­ciated with sST2 levels mapped to the intracellular domain of ST2L and hence are not present on sST2 itself, we hypothesized that these missense variants exert effects via intracellular mecha­nisms downstream of ST2 transmembrane receptor signaling to regulate sST2 levels. To investigate the effect of IL1RL1 missense variants (identified by GWAS) on sST2 expression, stable cell lines expressing WT ST2L, IL1RL1 variants (A78E, A433T, T549I, Q501K, Q501R, and L551S), and a construct containing the 5 IL1RL1 intracellular domain variants (5-mut) were generated. Expression of ST2L mRNA and protein (detected in membrane fractions) was confirmed (Supplemental Figures 5 and 6). Eight different stable clones in each group were analyzed to reduce bias from clonal selection. Intracellular domain variants (A433T, T549I, Q501K, Q501R, L551S, and 5-mut), but not the extracellular domain variant (A78E), were associated with increased basal sST2 expression when compared with WT expression (P < 0.05 for all, Figure 3A). sST2 expression was highest in the 5-mut construct, suggesting that intracellular ST2L variants cooperatively regulate sST2 levels. This same pattern was consistent across different cell types (U937, Jurkat T, and A549 cells; Supplemental Figure 7). These findings suggest that intracellular domain variants of the transmembrane ST2 receptor may functionally regulate downstream signaling.   IL1RL1 transcription may occur via two alternative promoters (proximal vs. distal), which leads to differential expression of the soluble versus membrane-bound ST2 proteins. Similar to the sST2 protein expression results above, the intracellular domain variants, but not the extracellular domain variant, were associated with higher basal proximal promoter activity. Dis­tal promoter activity was also increased for most intracellular domain variants (Supplemental Figure 8).

IL1RL1 intracellular missense variants resulted in higher IL-33 pro­tein levels.

In addition to upregulation of sST2 protein levels, IL1RL1 intracellular missense variants caused increased basal IL-33 protein expression (Figure 3B), suggesting a possible autoregulatory loop whereby IL-33 signaling positively induces sST2 expression. IL-33 induced sST2 protein expression in cells expressing both WT and IL1RL1 missense variants. Interest­ingly, this effect was particularly pronounced in the A433T and Q501R variants (Supplemental Figure 9A).

Enhanced IL-33 responsiveness is mediated by IL-113 in A433T and Q501R variants.

Interaction among IL-33, sST2, and IL-113.

Inhibition of IL-113 by anti–IL-113 mAb reduced basal expression of sST2 (Supplemental Figure 11A). Blocking of IL-33 by sST2 did not reduce the induction of IL-113 levels by the IL1RL1 variants (Supplemental Figure 11B). Furthermore, inhibition of IL-113 by anti–IL-113 reduced the basal IL-33 levels. IL-33 itself upregulated sST2 levels, which in turn reduced IL-33 levels (Supplemental Figure 11C). Our results revealed that both IL-33 and IL-113 drive sST2 expression and that IL-113 acts as an upstream inducer of IL-33 and maintains IL-33 expression by intracellular IL1RL1 vari­ants (Supplemental Figure 11D). This suggests that IL1RL1 vari­ants upregulated sST2 mainly through IL-33 autoregulation and that the enhanced IL-33 responsiveness by A433T and Q501R was mediated by IL-113 upregulation.

IL1RL1 missense variants modulate ST2 signaling pathways

The effect of IL1RL1 missense variants on known ST2 downstream regulatory pathways, including NF-KB, AP-1/c-Jun, AKT, and STAT3 , was examined in the presence and absence of IL-33 (Figure 4 and Supplemental Figure 12). The IL1RL1 intracellular missense vari­ants (A433T, T549I, Q501K, Q501R, and L551S) were associated with higher basal phospho–NF-KB p65 and phospho–c-Jun levels (Figure 4, A and B). Consistent with enhanced IL-33 responsive­ness in A433T and Q501R cells, levels of IL-33–induced NF-KB and c-Jun phosphorylation were enhanced in these 2 variants (Figure 4, B and D). In contrast, A433T and Q501R variants showed lower basal phospho-AKT levels (Figure 4E). ……….. The majority of sST2 gene variants in our study were located within or near IL1RL1, the gene coding for both transmembrane ST2 and sST2. IL1RL1 resides within a linkage disequilibrium block of 400 kb on chromosome 2q12, a region that includes a number of other cytokines, including IL-18 receptor 1 (IL18R1) and IL-18 receptor accessory protein (IL18RAP). Polymorphisms in this gene cluster have been associated previously with a num­ber of immune and inflammatory conditions, including asthma, celiac disease, and type 1 diabetes mellitus . Many of these variants were associated with sST2 concentrations in our analysis (Supplemental Table 6). The immune effects of ST2 are corroborated by experimental evidence: membrane-bound ST2 is selectively expressed on Th2- but not Th1-type T helper cells, and activation of the ST2/IL-33 axis elaborates Th2 responses. In general, the allergic phenotypes above are thought to be Th2-mediated processes, in contrast to atherosclerosis, which appears to be a Th1-driven process.

Fig 2  Models of ST2 illustrate IL1RL1 missense variant locations.

Figure 2 Models of ST2 illustrate IL1RL1 missense variant locations.

Models of the (A) intracellular TIR domain (ST2-TIR) and the (B) extracellular domain (ST2-ECD) of ST2 (protein data bank codes 3O4O and 1T3G, respectively). Domains of ST2 are shown in yellow, with identified mis-sense SNP positions represented as red spheres and labels. Note that positions 549 and 551 are near the C terminus of ST2, which is not defined in the crystal structure (protein data bank ID 1T3G, shown as dashed black line in A). Arrows point toward the transmembrane domain, which is also not observed in crystal structures.

Fig 3 IL1RL1 intracellular missense variants resulted in higher sST2 and IL-33.

Figure 3   IL1RL1 intracellular missense variants resulted in higher sST2 and IL-33.

Media from KU812 cells expressing WT and IL1RL1 missense variants were collected for ELISA analysis of (A) sST2, (B) IL-33, and (C) IL-113 levels. Horizontal bars indicate mean values, and symbols represent indi­vidual variants. *P < 0.05, **P < 0.01 vs. WT. (D) Effect of anti–IL-113 mAb on IL-33–induced sST2 expression. Dashed line indicates PBS-treated cells as referent group. Error bars represent mean ± SEM from 2 independent experiments. *P < 0.05 vs. IL-33.

Fig 4  IL1RL1 missense variants modulated ST2 signaling pathways

Figure 4  IL1RL1 missense variants modulated ST2 signaling pathways. 

KU812 cells expressing WT or IL1RL1 variants were treated with PBS or IL-33. Levels of the following phosphorylated proteins were detected in cell lysates using ELISA: (A and B) phospho-NF-KB p65; (C and D) phospho-c-Jun activity; and (E and F) phospho-AKT. (A, C, and E) White bars represent basal levels, and (B, D, and F) gray bars represent relative fold increase (compared with PBS-treated group) after IL-33 treatment. *P < 0.05 vs. WT; **P < 0.01 vs. PBS-treated group. Dashed line in B, D, and F represents PBS-treated cells as referent group. Error bars represent mean ± SEM from 2 independent experiments. Fig 5   IL-33–induced sST2 expression is enhanced with mTOR inhibition and occurs via ST2L-dependent signaling.

Figure 5  IL-33–induced sST2 expression is enhanced with mTOR inhibition and occurs via ST2L-dependent signaling.

(A) sST2 mRNA expression in KU812 cells after treatment with DMSO, IL-33, or IL-33 plus signal inhibitors (wortmannin, LY294002, rapamycin, PD98059, SP60125, BAY11-7082, or SR11302). (B) ST2L mRNA and (C) sST2 mRNA expression in KU812 cells treated with PBS (white columns), rapamycin (rapa), anti-ST2 mAb, IL-33, IL-33 plus anti-ST2, IL-33 plus rapamycin, IL-33 plus rapamycin plus anti-ST2 mAb, or rapamycin plus anti-ST2. (D) IL33 mRNA expression in KU812 cells after treatment with DMSO, signal inhibitors, IL-33 plus signal inhibitors, and IL-1n plus signal inhibitors. *P < 0.05 vs. PBS-treated group; #P < 0.05 vs. IL-33–treated group; &P < 0.05 vs. IL-1n–treated group. Error bars represent mean ± SEM from 2 independent experiments. (E) A schematic model illustrating the regulation of sST2 expression by IL1RL1 missense variants through enhanced induction of IL-33 via enhanced NF-KB and AP-1 signaling and enhanced IL-33 responsiveness via increasing ST2L expression.

Quantitating subcellular metabolism with multi-isotope imaging mass spectrometry

ML Steinhauser, A Bailey, SE Senyo, C Guillermier, TS Perlstein, AP Gould, RT Lee, and CP Lechene
Department of Medicine, Divisions of Cardiovascular Medicine & Genetics, Brigham and Women’s Hospital, Harvard Medical School & Harvard Stem Cell Institute Division of Physiology and Metabolism, Medical Research Council National Institute for Medical Research, Mill Hill, London, UK National Resource for Imaging Mass Spectroscopy
Nature 2012;481(7382): 516–519.   http://dx. do.org/10.1038/nature10734

Mass spectrometry with stable isotope labels has been seminal in discovering the dynamic state of living matter, but is limited to bulk tissues or cells. We developed multi-isotope imaging mass spectrometry (MIMS) that allowed us to view and measure stable isotope incorporation with sub-micron resolution. Here we apply MIMS to diverse organisms, including Drosophila, mice, and humans. We test the “immortal strand hypothesis,” which predicts that during asymmetric stem cell division chromosomes containing older template DNA are segregated to the daughter destined to remain a stem cell, thus insuring lifetime genetic stability. After labeling mice with 15N-thymidine from gestation through post-natal week 8, we find no 15N label retention by dividing small intestinal crypt cells after 4wk chase. In adult mice administered 15N-thymidine pulse-chase, we find that proliferating crypt cells dilute label consistent with random strand segregation. We demonstrate the broad utility of MIMS with proof-of-principle studies of lipid turnover in Drosophila and translation to the human hematopoietic system. These studies show that MIMS provides high-resolution quantitation of stable isotope labels that cannot be obtained using other techniques and that is broadly applicable to biological and medical research. MIMS combines ion microscopy with secondary ion mass spectrometry (SIMS), stable isotope reporters, and intensive computation (Supplemental Fig 1). MIMS allows imaging and measuring stable isotope labels in cell domains smaller than one micron cubed. We tested the potential of MIMS to quantitatively track DNA labeling with 15N-thymidine in vitro. In proliferating fibroblasts, we detected label incorporation within the nucleus by an increase in the 15N/14N ratio above natural ratio (Fig 1a). The labeling pattern resembled chromatin with either stable isotope-tagged thymidine or thymidine analogs (Fig 1b). We measured dose-dependent incorporation of 15N-thymidine over three orders of magnitude (Fig 1d, Supplemental Fig 2). We also tracked fibroblast division after a 24-hour label-free chase (Fig 1d,e, Supplemental Fig 3). Cells segregated into two populations, one indistinguishable from control cells suggesting no division, the other with halving of label, consistent with one division during chase. We found similar results by tracking cell division in vivo in the small intestine (Fig 1f,g, Supplemental Figs 4–6). We measured dose-dependent 15N-thymidine incorporation within nuclei of actively dividing crypt cells (Fig 1g, Supplemental Fig 4), down to a dose of 0.1µg/ g (Supplemental Fig 2). The cytoplasm was slightly above natural ratio, likely due to low level soluble 15N-thymidine or mitochondrial incorporation (Supplemental Fig 2). We measured halving of label with each division during label-free chase (Supplemental Fig 6). We then tested the “immortal strand hypothesis,” a concept that emerged from autoradiographic studies and that predicted long-term label retaining cells in the small intestinal crypt. It proposes that asymmetrically dividing stem cells also asymmetrically segregate DNA, such that older template strands are retained by daughter cells that will remain stem cells and newer strands are passed to daughters committed to differentiation (Supplemental Fig 7)5,6. Modern studies continue to argue both for or against the hypothesis, leading to the suggestion that definitive resolution of the debate will require a new experimental approach. Although prior evidence suggests a concentration of label-retaining cells in the +4 anatomic position, we searched for DNA label retention irrespective of anatomic position or molecular identity. We labeled mice with 15N-thymidine for the first 8 wks of life when intestinal stem cells are proposed to form. After a 4-wk chase, mice received bromodeoxyuridine (BrdU) for 24h prior to sacrifice to identify proliferating cells(Fig 2a, Supplemental Fig 8: Exp 1), specifically crypt base columnar (CBC) cells and transit amplifying cells (TA) (Supplemental Fig 9), which cycle at a rate of one and two times per 24h, respectively (Supplemental Fig 10). All crypt cell nuclei were highly labeled upon completion of 15N-thymidine; after a four-week chase, however, we found no label retention by non-Paneth crypt cells (Fig 2b–f; n=3 mice, 136 crypts analysed). 15N-labeling in BrdU/15N+ Paneth and mesenchymal cells was equivalent to that measured at pulse completion (Fig2b,c) suggesting quiescence during the chase (values above 15N/14N natural ratio: Paneth pulse=107.8 +/− 5.0% s.e.m. n=51 vs Paneth pulse-chase=96.3+/−2.8% s.e.m. n=218; mesenchymal pulse=92.0+/−5.0% s.e.m. n=89 vs mesenchymal pulse-chase=90.5+/ −2.2% s.e.m. n=543). The number of randomly selected crypt sections was sufficient to detect a frequency as low as one label-retaining stem cell per crypt irrespective of anatomic location within the crypt. Because each anatomic level contains approximately 16 circumferentially arrayed cells, a 2-dimensional analysis captures approximately 1/8th of the cells at each anatomic position (one on each side of the crypt; Supplemental Fig 9a). Therefore, assuming only 1 label-retaining stem cell per crypt we should have found 17 label-retaining cells in the 136 sampled crypts (1/8th of 136); we found 0 (binomial test p<0.0001). The significance of this result held after lowering the expected frequency of label-retaining cells by 25% to account for the development of new crypts, a process thought to continue into adulthood. In three additional experiments, using shorter labeling periods and including in utero development, we also found no label-retaining cells in the crypt other than Paneth cells (Supplemental Fig 8, Exps 2–4).

Fig 1 post-natal human DNA synthesis in the heart

In recent years, several protocols have been developed experimentally in an attempt to identify novel therapeutic interventions aiming at the reduction of infarct size and prevention of short and long term negative ventricular remodeling following ischemic myocardial injury. Three main strategies have been employed and a significant amount of work is being conducted to determine the most effective form of action for acute ischemic heart failure. The delivery of bone marrow progenitor cells (BMCs) has been highly controversial, but recent clinical data have shown improvement in ventricular performance and clinical outcome. These observations have not changed the nature of the debate concerning the efficacy of this cell category for the human disease and the mechanisms involved in the impact of BMCs on cardiac structure and function. Whether BMCs transdifferentiate and acquire the cardiomyocyte lineage has faced strong opposition and data in favor and against this possibility have been reported. However, this is the only cell class which has been introduced in the treatment of heart failure in patients and large clinical trials are in progress.
Human embryonic stem cells (ESCs) have repeatedly been utilized in animal models to restore the acutely infarcted myocardium, but limited cell engraftment, modest ability to generate vascular structures, teratoma formation and the apparent transient beneficial effects on cardiac hemodynamics have questioned the current feasibility of this approach clinically. Tremendous efforts are being performed to reduce the malignant tumorigenic potential of ESCs and promote their differentiation into cardiomyocytes with the expectation that these extremely powerful cells may be applied to human beings in the future. Additionally, the study of ESCs may provide unique understanding of the mechanisms of embryonic development that may lead to therapeutic interventions in utero and the correction of congenital malformations.
The recognition that a pool of primitive cells with the characteristics of stem cells resides in the myocardium and that these cells form myocytes, ECs and SMCs has provided a different perspective of the biology of the heart and mechanisms of cardiac homeostasis and tissue repair. Regeneration implies that dead cells are replaced by newly formed cells restoring the original structure of the organ. In adulthood, this process occurs during physiological cell turnover, in the absence of injury. However, myocardial damage interferes with recapitulation of cell turnover and restitutio ad integrum of the organ. Because of the inability of the adult heart to regenerate itself after infarction, previous studies have promoted tissue repair by injecting exogenously expanded CPCs in proximity of the necrotic myocardium or by activating resident CPCs through the delivery of growth factors known to induce cell migration and differentiation. These strategies have attenuated ventricular dilation and the impairment in cardiac function and in some cases have decreased animal mortality.

Although various subsets of CPCs have been used to reconstitute the infarcted myocardium and different degrees of muscle mass regeneration have been obtained, in all cases the newly formed cardiomyocytes possessed fetal-neonatal characteristics and failed to acquire the adult cell phenotype. In the current study, to enhance myocyte growth and differentiation, we have introduced cell therapy together with the delivery of self-assembly peptide nanofibers to provide a specific and prolonged local myocardial release of IGF-1. IGF-1 increases CPC growth and survival in vitro and in vivo and this effect resulted here in a major increase in the formation of cardiomyocytes and coronary vessels, decreasing infarct size and restoring partly cardiac performance. This therapeutic approach was superior to the administration of CPCs or NF-IGF-1 only. Combination therapy appeared to be additive; it promoted myocardial regeneration through the activation and differentiation of resident and exogenously delivered CPCs. Additionally, the strategy implemented here may be superior to the utilization of BMCs for cardiac repair. CPCs are destined to form myocytes, and vascular SMCs and ECs and, in contrast to BMCs, do not have to transdifferentiate to acquire cardiac cell lineages. Transdifferentiation involves chromatin reorganization with activation and silencing of transcription factors and epigenetic modifications.

Selected References

  1. Hsieh PC, Davis ME, Gannon J, MacGillivray C, Lee RT. Controlled delivery of PDGF-BB for myocardial protection using injectable self-assembling peptide nanofibers. J Clin Invest 2006;116:237–248. [PubMed: 16357943]
  2. Davis ME, Hsieh PC, Takahashi T, Song Q, Zhang S, Kamm RD, Grodzinsky AJ, Anversa P, Lee RT. Local myocardial insulin-like growth factor 1 (IGF-1) delivery with biotinylated peptide nanofibers improves cell therapy for myocardial infarction. Proc Natl Acad Sci USA 2006;103:8155–8160. [PubMed: 16698918]
  3. Beltrami AP, Barlucchi L, Torella D, Baker M, Limana F, Chimenti S, Kasahara H, Rota M, Musso E, Urbanek K, Leri A, Kajstura J, Nadal-Ginard B, Anversa P. Adult cardiac stem cells are multipotent and support myocardial regeneration. Cell 2003;114:763–776. [PubMed: 14505575]
  4. Rota M, Padin-Iruegas ME, Misao Y, De Angelis A, Maestroni S, Ferreira-Martins J, Fiumana E, Rastaldo R, Arcarese ML, Mitchell TS, Boni A, Bolli R, Urbanek K, Hosoda T, Anversa P, Leri A, Kajstura J. Local activation or implantation of cardiac progenitor cells rescues scarred infarcted myocardium improving cardiac function. Circ Res 2008;103:107–116. [PubMed: 18556576]

Cardiac anatomy.

Figure 2.  Cardiac anatomy.

(A and B) Cardiac weights and infarct size. R and L correspond, respectively, to the number of myocytes remaining and lost after infarction. (C–G) LV dimensions. Sham-operated: SO. *Indicates P<0.05 vs SO; **vs untreated infarcts (UN); †vs infarcts treated with CPCs; ‡vs infarcts treated with NF-IGF-1.

Ventricular function

Figure 3.  Ventricular function.

Combination therapy (CPC-NF-IGF-1) attenuated the most the negative impact of myocardial infarction on cardiac performance. See Figure 2 for symbols.

Endothelial Cells Promote Cardiac Myocyte Survival and Spatial Reorganization: Implications for Cardiac Regeneration

Daria A. Narmoneva, Rada Vukmirovic, Michael E. Davis, Roger D. Kamm,  and Richard T. Lee
Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, and the Division of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA
Circulation. 2004 August 24; 110(8): 962–968.        http://dx.doi.org/10.1161/01.CIR.0000140667.37070.07

Background

Endothelial-cardiac myocyte (CM) interactions play a key role in regulating cardiac function, but the role of these interactions in CM survival is unknown. This study tested the hypothesis that endothelial cells (ECs) promote CM survival and enhance spatial organization in a 3-dimensional configuration.

Methods and Results

Microvascular ECs and neonatal CMs were seeded on peptide hydrogels in 1 of 3 experimental configurations:

  1. CMs alone,
  2. CMs mixed with ECs (coculture), or
  3. CMs seeded on preformed EC networks (prevascularized).

Capillary-like networks formed by ECs promoted marked CM reorganization along the EC structures, in contrast to limited organization of CMs cultured alone. The presence of ECs markedly inhibited CM apoptosis and necrosis at all time points. In addition, CMs on preformed EC networks resulted in significantly less CM apoptosis and necrosis compared with simultaneous EC-CM seeding (P<0.01, ANOVA). Furthermore, ECs promoted synchronized contraction of CMs as well as connexin 43 expression.

Conclusions

These results provide direct evidence for a novel role of endothelium in survival and organization of nearby CMs. Successful strategies for cardiac regeneration may therefore depend on establishing functional CM-endothelium interactions.

Keywords:  endothelium; cardiomyopathy; heart failure; tissue

Introduction

Recent studies suggest that the mammalian heart possesses some ability to regenerate itself through several potential mechanisms, including generation of new cardiomyocytes (CMs) from extracardiac progenitors, CM proliferation, or fusion with stem cells with subsequent hybrid cell division. These mechanisms are insufficient to regenerate adequate heart tissue in humans, although some vertebrates can regenerate large volumes of injured myocardium.
Several approaches in cell transplantation and cardiac tissue engineering have been investigated as potential treatments to enhance cardiac function after myocardial injury. Implantation of skeletal muscle cells, bone marrow cells, embryonic stem cell-derived CMs, and myoblasts can enhance cardiac function. Cell-seeded grafts have been used instead of isolated cells for in vitro cardiac tissue growth or in vivo transplantation. These grafts can develop a high degree of myocyte spatial organization, differentiation, and spontaneous and coordinated contractions. On implantation in vivo, cardiac grafts can integrate into the host tissue and neovascularization can develop. However, the presence of scar tissue and the death of cells in the graft can limit the amount of new myocardium formed, most likely due to ischemia. Therefore, creating a favorable environment to promote survival of transplanted cells and differentiation of progenitor cells remains one of the most important steps in regeneration of heart tissue.
One of the key factors for myocardial regeneration is revascularization of damaged tissue. In the normal heart, there is a capillary next to almost every CM, and endothelial cells (ECs) outnumber cardiomyocytes by ≈3:1. Developmental biology experiments reveal that myocardial cell maturation and function depend on the presence of endocardial endothelium at an early stage. Experiments with inactivation or overexpression of vascular endothelial growth factor (VEGF) demonstrated that at later stages, either an excess or a deficit in blood vessel formation results in lethality due to cardiac dysfunction. Both endocardium and myocardial capillaries have been shown to modulate cardiac performance, rhythmicity, and growth. In addition, a recent study showed the critical importance of CM-derived VEGF in paracrine regulation of cardiac morphogenesis. These findings and others highlight the significance of interactions between CMs and endothelium for normal cardiac function. However, little is known about the specific mechanisms for these interactions, as well as the role of a complex, 3-dimensional organization of myocytes, ECs, and fibroblasts in the maintenance of healthy cardiac muscle.
The critical relation of CMs and the microvasculature suggests that successful cardiac regeneration will require a strategy that promotes survival of both ECs and CMs. The present study explored the hypothesis that ECs (both as preexisting capillary-like structures and mixed with myocytes at the time of seeding) promote myocyte survival and enhance spatial reorganization in a 3-dimensional configuration. The results demonstrate that CM interactions with ECs markedly decrease myocyte death and show that endothelium may be important not only for the delivery of blood and oxygen but also for the formation and maintenance of myocardial structure.

Methods

  • Three-Dimensional Culture
  • Immunohistochemistry and Cell Death Assays
  • Evaluation of Contractile Areas

Results

  • EC-CM Interactions Affect Myocyte Reorganization
  • ECs Improve Survival of CMs
  • Preformed Endothelial Networks Promote Coordinated, Spontaneous Contractions
  • ECs Promote Cx43 Expression

EC-CM Interactions Affect Myocyte Reorganization

To explore interactions between CMs and ECs in 3-dimensional culture, we used peptide hydrogels, a tissue engineering scaffold. Cells seeded on the surface of the hydrogel attach and then migrate into the hydrogel. When CMs alone were used, cells attached on day 1 and then formed small clusters of cells at days 3 and 7 (Figure 1). In contrast, when CMs were seeded together with ECs, cells formed interconnected linear networks, as commonly seen with ECs in 3-dimensional culture environments, with increasing spatial organization from day 1 to day 7 (Figure 1).

Figure 1.  ECs promote CM reorganization. 

When CMs were cultured alone (left column), they aggregated into sparse clusters. When CMs were cultured with ECs (center), cells organized into capillary-like networks. There was no difference in morphological appearance between coculture or prevascularized cultures (not shown) and ECs alone (right column). Bar=100 μm. Abbreviations are as defined in text.

To establish whether preformed endothelial networks enhanced the organization of myocytes, we also seeded ECs 1 day before myocytes were added. These ECs formed similar interconnected networks in the absence of myocytes; preforming the vascular network did not lead to significant differences in morphology (data not shown). Furthermore, to exclude the possibility that the increasing cell density of added ECs caused the spatial organization, we also performed control experiments with varying numbers and combinations of cells; there was no effect of doubling or halving cell numbers, indicating that the spatial organization effect was specifically due to ECs. To establish that both myocytes and ECs were forming networks together, we performed immunofluorescence studies with specific antibodies, as well as analysis of cross sections of CM-EC cocultures, whereby cells were labeled with CellTracker dyes before seeding. Immunofluorescent staining demonstrated that >95% of CMs were present within these networks, suggesting that CMs preferentially migrate to or survive better near ECs (Figure 2).

Figure 2.  CMs appear on outside of endothelial networks.

CMs appear on outside of endothelial networks. High-magnification, double-immunofluorescence image of structures formed in EC-CM coculture at day 7 demonstrating CMs (sarcomeric actinin, red) spread on top of ECs (von Willebrand factor, green) with no myocytes present outside structure. Bar=100 μm. Abbreviations are as defined in text.

The analysis of cross sections demonstrated the presence of what appeared to be EC-derived, tubelike structures (Figure 3), with myocytes spread on the outer part of the capillary wall. Along with the capillary-like structures, clusters of intermingled cells (both myocytes and ECs) not containing the lumen were also observed (not shown). However, when the lumen was present, ECs were always on the inner side and myocytes on the outer side of the structure.

Figure 3.  ECs form tubelike structures with myocytes spreading on outer wall.

Cross section of paraffin-embedded sample of 3-day coculture of myocytes (red) and ECs (green) incubated in CellTracker dye before seeding on hydrogel. Bar=50 μm. Abbreviations are as defined in text.

In CM-fibroblast cocultures, cells rapidly (within 24 hours) formed large clusters consisting of cells of both types (not shown). At later time points, fibroblast proliferation resulted in their migration outside the clusters and spreading on the hydrogel without any pattern. However, in contrast to EC-CM cocultures, CMs remained in the clusters and demonstrated only limited spreading. Immunofluorescent staining revealed that there was no orientation of myocytes relative to the fibroblasts in the clusters. In cultures with EC-conditioned medium, myocyte morphology and spatial organization remained similar to those of myocyte controls.

ECs Improve Survival of CMs

To test the hypothesis that ECs promote CM survival, we assessed apoptosis and necrosis in the 3-dimensional cultures. Quantitative analyses of CMs positive for TUNEL and necrosis staining demonstrated significantly decreased myocyte apoptosis and necrosis when cultured with ECs, compared with CM-only cultures (Figure 4, P<0.01). This effect was observed at all 3 time points, although the decreased necrosis was most pronounced at day 1. In addition, CMs seeded on the preformed EC networks had a lower rate of apoptosis at day 1 relative to same-time seeding cultures (P<0.05, post hoc test), suggesting that early EC-CM interactions provided by the presence of well-attached and prearranged ECs may further promote CM survival. In contrast to the ECs, cardiac fibroblasts did not affect myocyte survival (P>0.05, Figure 4), with ratios for myocyte apoptosis and necrosis in the myocyte-fibroblast cocultures being similar to those for myocyte-only controls. However, addition of EC-conditioned medium resulted in a significant decrease in apoptosis and necrosis ratios of myocytes (P<0.01). Interestingly, the effect of conditioned medium on myocyte necrosis was similar in magnitude to the effect of ECs, whereas myocyte apoptosis ratios in the conditioned-medium group were only partially decreased compared with those in the presence of ECs. These results suggest that the prosurvival effect of ECs on CMs may not only be merely due to the local interactions between myocytes and ECs during myocyte attachment but may also involve direct signaling between myocytes and ECs.

Figure 4.  ECs prolong survival of CMs

Top, dual immunostaining of CMs and EC-myocyte prevascularized groups at day 3 in culture, with TUNEL-positive cells in red; green indicates sarcomeric actinin; blue, DAPI. Bottom, presence of ECs decreased CM apoptosis and necrosis, both in coculture conditions and when cultures were prevascularized by seeding with ECs 1 day before CMs (mean±SD, P<0.01). EC-conditioned medium decreased myocyte apoptosis and necrosis (P<0.01), whereas fibroblasts did not have any effect (P>0.05). *Different from myocytes alone; **different from EC-myocyte coculture and pre-vascularized. Bar=100 μm. Abbreviations are as defined in text.

Preformed Endothelial Networks Promote Coordinated, Spontaneous Contractions

In the prevascularized group with preformed vascular structures, synchronized, spontaneous contractions of large areas (Figure 5, top panels) were detected as early as days 2 to 3after seeding, in contrast to the coculture group, wherein such contractions were observed on days 6 to 7. In CM-only cultures, beating of separate cells and small cell clusters was also detected at days 2 to 3, similar to that in the prevascularized group. However, the average area of synchronized beating at day 3 in the myocyte-only group (3.5±0.5×102 μm2) was nearly 3 orders of magnitude smaller than the synchronously contracting area in the prevascularized group (4.3±2.5×105 μm2, mean±SD, n=5). These data suggest that ECs promote synchronized CM contraction, particularly when vascular networks are already formed.

Figure 5.  ECs promote large-scale, synchronized contraction of CMs.

Left, phase-contrast video of beating areas in CM-only and prevascularized groups (day 3). Right, motion analysis of video showing regions of synchronized contractions (connected areas in purple are contracting synchronously) and nonmoving areas in blue. Bars=100 μm. Abbreviations are as defined in text.

ECs Promote Cx43 Expression

Staining for Cx43 showed striking differences in the distribution pattern of this gap junction protein between EC-CM cocultures and CMs cultured alone. In myocyte-only cultures, Cx43 expression was barely detectable at day 1 (not shown); at days 3 and 7, Cx43 expression was sparse throughout the cell clusters (Figure 6). In the presence of ECs (in both coculture and prevascularized groups), Cx43 staining was evident at day 1, both between ECs and distributed among CMs. As early as day 3 in culture, patches of localized junction-like Cx43, in addition to diffuse staining, were observed for myocytes in the coculture group (Figure 6). In the prevascularized group at day 3, wherein spontaneous contractions were already observed, more junction-like patches of Cx43 were observed compared with the coculture group, indicating electrical connections between myocytes (Figure 6). In addition to junctions between myocytes, there was also evidence of Cx43 localized at the interface between ECs and myocytes (Figure 6) detected in both the coculture group (at day 7) and the preculture group (as early as day 3). When myocytes and myocyte-EC coculture groups were cultured for 3 days with or without addition of 100 ng/mL of neutralizing anti-mouse VEGF antibody (R&D Systems), we observed no differences in either apoptosis or Cx43 staining between VEGF antibody-containing cultures and controls.

Figure 6. ECs promote Cx43 expression

Cultures at 3 days immunostained for Cx43 (red) and anti-sarcomeric actinin (green); nuclei are stained with DAPI (blue). For CMs alone (left), Cx43 staining is diffuse and sparse, with no evidence of gap junctions; for coculture (center), both diffuse (yellow arrow) and patchlike (thin, white arrow) Cx43 staining is observed; for prevascularized (right), increased patchlike staining indicates presence of gap junctions. Thick arrow-heads indicate junctions between myocytes and ECs. Bar=50 μm. Abbreviations are as defined in text.

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Endothelial-Cardiomyocyte Interactions in Cardiac Development and Repair: Implications for Cardiac Regeneration

Patrick C.H. Hsieh, Michael E. Davis, Laura K. Lisowski, and Richard T. Lee

Cardiovascular Division, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
Annu Rev Physiol.    PMC 2009 September 30

The ongoing molecular conversation between endothelial cells and cardiomyocytes is highly relevant to the recent excitement in promoting cardiac regeneration. The ultimate goal of myocardial regeneration is to rebuild a functional tissue that closely resembles mature myocardium, not just to improve systolic function transiently. Thus, regenerating myocardium will require rebuilding the vascular network along with the cardiomyocyte architecture. Here we review evidence demonstrating crucial molecular interactions between endothelial cells and cardiomyocytes. We first discuss endothelial-cardiomyocyte interactions during embryonic cardiogenesis, followed with morphological and functional characteristics of endothelial-cardiomyocyte interactions in mature myocardium. Finally, we consider strategies exploiting endothelial-cardiomyocyte interplay for cardiac regeneration.

Signaling from Cardiomyocytes to Endothelial Cells

The examples of neuregulin-1, NF1, and PDGF-B demonstrate that signals from endothelial cells regulate the formation of primary myocardium. Similarly, signaling from myocardial cells to endothelial cells is also required for cardiac development. Two examples of myocardial-to-endothelial signaling are vascular endothelial growth factor (VEGF)-A and angiopoietin-1.

VASCULAR ENDOTHELIAL GROWTH FACTOR-A

VEGF-A is a key regulator of angiogenesis during embryogenesis. In mice, a mutation in VEGF-A causes endocardial detachment from an underdeveloped myocardium. A mutation in VEGF receptor-2 (or Flk-1) also results in failure of the endocardium and myocardium to develop (18). Furthermore, cardiomyocyte-specific deletion of VEGF-A results in defects in vasculogenesis/angiogenesis and a thinned ventricular wall, further confirming reciprocal signaling from the myocardial cell to the endothelial cell during cardiac development. Interestingly, this cardiomyocyte-selective VEGF-A-deletion mouse has underdeveloped myocardial microvasculature but preserved coronary artery structure, implying a different signaling mechanism for vasculogenesis/angiogenesis in the myocardium and in the epicardial coronary arteries.
Cardiomyocyte-derived VEGF-A also inhibits cardiac endocardial-to-mesenchymal transformation. This process is essential in the formation of the cardiac cushions and requires delicate control of VEGF-A concentration. A minimal amount of VEGF initiates endocardial-to-mesenchymal transformation, whereas higher doses of VEGF-A terminate this transformation. Interestingly, this cardiomyocyte-derived VEGF-A signaling for endocardial-to-mesenchymal transformation may be controlled by an endothelial-derived feedback mechanism through the calcineurin/NFAT pathway (24), demonstrating the importance of endothelial-cardiomyocyte interactions for cardiac morphogenesis.

ANGIOPOIETIN-1

Another mechanism of cardiomyocyte control of endothelial cells during cardiac development is the angiopoietin-Tie-2 system. Both angiopoietin-1 and angiopoietin-2 may bind to Tie-2 receptors in a competitive manner, but with opposite effects: Angiopoietin-1 activates the Tie-2 receptor and prevents vascular edema, whereas angiopoietin-2 blocks Tie-2 phosphorylation and increases vascular permeability. During angiogenesis/vasculogenesis, angiopoietin-1 is produced primarily by pericytes, and Tie-2 receptors are expressed on endothelial cells. Angiopoietin-1 regulates the stabilization and maturation of neovasculature; genetic deletion of angiopoietin-1 or Tie-2 causes a defect in early vasculogenesis/angiogenesis and is lethal.
Cardiac endocardium is one of the earliest vascular components (along with the dorsal aorta and yolk sac vessels) and the adult heart can be regarded as a fully vascularized organ, angiopoietin-Tie-2 signaling may also be required for early cardiac development. Indeed, mice with mutations in Tie-2 have underdeveloped endocardium and myocardium. These Tie-2 knockout mice display defects in the endocardium but have normal vascular morphology at E10.5, suggesting that the endocardial defect is the fundamental cause of death. In addition, a recent study showed that overexpression, and not deletion, of angiopoietin-1 from cardiomyocytes caused embryonic death between E12.5-15.5 due to cardiac hemorrhage. The mice had defects in the endocardium and myocardium and lack of coronary arteries, suggesting that, as with VEGF-A, a delicate control of angiopoietin-1 concentration is critical for early heart development.

ENDOTHELIAL-CARDIOMYOCYTE INTERACTIONS IN NORMAL CARDIAC FUNCTION

Cardiac Endothelial Cells Regulate Cardiomyocyte Contraction

The vascular endothelium senses the shear stress of flowing blood and regulates vascular smooth muscle contraction. It is therefore not surprising that cardiac endothelial cells—the endocardial endothelial cells as well as the endothelial cells of intramyocardial capillaries— regulate the contractile state of cardiomyocytes. Autocrine and paracrine signaling molecules released or activated by cardiac endothelial cells are responsible for this contractile response (Figure 2).

NITRIC OXIDE

Three different nitric oxide synthase isoenzymes synthesize nitric oxide (NO) from L-arginine. The neuronal and endothelial NO synthases (nNOS and eNOS, respectively) are expressed in normal physiological conditions, whereas the inducible NO synthase is induced by stress or cytokines. Like NO in the vessel, which causes relaxation of vascular smooth muscle, NO in the heart affects the onset of ventricular relaxation, which allows for a precise optimization of pump function beat by beat. Although NO is principally a paracrine effector secreted by cardiac endothelial cells, cardiomyocytes also express both nNOS and eNOS. Endothelial expression of eNOS exceeds that in cardiomyocytes by greater than 4:1. Cardiomyocyte autocrine eNOS signaling can regulate β-adrenergic and muscarinic control of contractile state.
Barouch et al. demonstrated that cardiomyocyte nNOS and eNOS may have opposing effects on cardiac structure and function. Using mice with nNOS or eNOS deficiency, they found that nNOS and eNOS have not only different localization in cardiomyocytes but also opposite effects on cardiomyocyte contractility; eNOS localizes to caveolae and inhibits L-type Ca2+ channels, leading to negative inotropy, whereas nNOS is targeted to the sarcoplasmic reticulum and facilitates Ca2+ release and thus positive inotropy (31). These results demonstrate that spatial confinement of different NO synthase isoforms contribute independently to the maintenance of cardiomyocyte structure and phenotype.
As indicated above, mutation of neuregulin or either of two of its cognate receptors, erbB2 and erbB4, causes embryonic death during mid-embryogenesis due to aborted development of myocardial trabeculation . Neuregulin also appears to play a role in fully developed myocardium. In adult mice, cardiomyocyte-specific deletion of erbB2 leads to dilated cardiomyopathy. Neuregulin from endothelial cells may induce a negative inotropic effect in isolated rabbit papillary muscles. This suggests that, along with NO, the neuregulin signaling pathway acts as an endothelial-derived regulator of cardiac inotropism.  In fact, the negative inotropic effect of neuregulin may require NO synthase because L-NMMA, an inhibitor of NO synthase, significantly attenuates the negative inotropy of neuregulin.

Studies to date indicate that cardiac regeneration in mammals may be feasible, but the response is inadequate to preserve myocardial function after a substantial injury. Thus, understanding how normal myocardial structure can be regenerated in adult hearts is essential. It is clear that endothelial cells play a role in cardiac morphogenesis and most likely also in survival and function of mature cardiomyocytes. Initial attempts to promote angiogenesis in myocardium were based on the premise that persistent ischemia could be alleviated. However, it is also possible that endothelial-cardiomyocyte interactions are essential in normal cardiomyocyte function and for protection from injury. Understanding the molecular and cellular mechanisms controlling these cell-cell interactions will not only enhance our understanding of the establishment of vascular network in the heart but also allow the development of new targeted therapies for cardiac regeneration by improving cardiomyocyte survival and maturation.

Endothelial-cardiomyocyte assembly

Figure 1.  Endothelial-cardiomyocyte assembly in adult mouse myocardium.
Normal adult mouse myocardium is stained with intravital perfusion techniques to demonstrate cardiomyocyte (outlined in red) and capillary (green; stained with isolectin-fluorescein) assembly. Nuclei are blue (Hoechst). Original magnification: 600X

Endothelial dysfunction

Intramyocardial Fibroblast – Myocyte Communication

Rahul Kakkar, M.D. and Richard T. Lee, M.D.
From the Cardiology Division, Massachusetts General Hospital and the Cardiovascular Division, Brigham and Women’s Hospital, Department of Medicine, Harvard Medical School, Boston, MA
Circ Res. 2010 January 8; 106(1): 47–57.    http://dx.doi.org/10.1161/CIRCRESAHA.109.207456

Cardiac fibroblasts have received relatively little attention compared to their more famous neighbors, the cardiomyocytes. Cardiac fibroblasts are often regarded as the “spotters”, nonchalantly watching the cardiomyocytes do the real weight-lifting, and waiting for a catastrophe that requires their actions. However, emerging data now reveal the fibroblast as not only a critical player in the response to injury, but also as an active participant in normal cardiac function.
Interest in cardiac fibroblasts has grown with the recognition that cardiac fibrosis is a prominent contributor to diverse forms of myocardial disease. In the early 1990’s, identification of angiotensin receptors on the surface of cardiac fibroblasts linked the renin-angiotensin-aldosterone system directly with pathologic myocardial and matrix extracellular remodeling.  Fibroblasts were also revealed as a major source of not only extracellular matrix, but the proteases that regulate and organize matrix. New research has uncovered paracrine and well as direct cell-to-cell interactions between fibroblasts and their cardiomyocyte neighbors, and cardiac fibroblasts appear to be dynamic participants in ventricular physiology and pathophysiology.
This review will focus on several aspects of fibroblast-myocyte communication, including mechanisms of paracrine communication.  Ongoing efforts at regeneration of cardiac tissue focus primarily on increasing the number of cardiomyocytes in damaged myocardium. Although getting cardiomyocytes into myocardium is an important goal, understanding intercellular paracrine communication between different cell types, including endothelial cells but also fibroblasts, may prove crucial to regenerating stable myocardium that responds to physiological conditions appropriately.

An area of active research in cardiovascular therapeutics is the attempt to engineer, ex vivo, functional myocardial tissue that may be engrafted onto areas of injured ventricle. Recent data suggests that the inclusion of cardiac fibroblasts in three-dimensional cultures greatly enhances the stability and growth of the nascent myocardium. Cardiac fibroblasts when included in polymer scaffolds seeded with myocytes and endothelial cells have the ability to promote and stabilize vascular structures. Naito and colleagues constructed three dimensional cultures of neonatal rat cell isolates on collagen type I and Matrigel (a basement membrane protein mixture), and isolates of a mixed cell population versus a myocyte-enriched population were compared. The mixed population cultures, which contained a higher fraction of cardiac fibroblasts than the myocyte-enriched cultures, displayed improved contractile force generation and greater inotropic response despite an equivalent overall cell number. Greater vascularity was also seen in the mixed-pool cultures.(160) Building on this, Nichol and colleagues demonstrated that in a self-assembling nanopeptide scaffold, embedded rat neonatal cardiomyocytes exhibit greater cellular alignment and reduced apoptosis when cardiac fibroblasts were included in the initial culture. A similar result was noted when polymer scaffolds were pre-treated with cardiac fibroblasts before myocyte seeding, suggesting a persistent paracrine effect. These data reinforce the concept that engineering functional myocardium, either in situ or ex vivo will require attention to the nature of cell-cell interactions, including fibroblasts.

To date, a broad initial sketch of cardiac fibroblast-myocyte interactions has been drawn. Future studies in this field will better describe these interactions. How do multiple paracrine factors interact to produce a cohesive and coordinated communication scheme? What are the changes in coordinated bidirectional signaling that during development promotes myocyte progenitor proliferation but have different roles in the adult? Might fibroblasts actually be required for improved cardiac repair and regeneration?
Recent studies have begun to apply genetic and cellular fate-mapping techniques to document the origins of cardiac fibroblasts, the dynamic nature of their population, and how that population may be in flux during time of injury or pressure overload. It is crucial to define on a more specific molecular basis the origins and fates of cardiac fibroblasts. Do fibroblasts that have been resident within the ventricle since development fundamentally differ from those that arise from endothelial transition or that infiltrate from the bone marrow during adulthood? Do fibroblasts with these different origins behave differently or take on different roles in the face of ventricular strain or injury?

Our understanding of the nature of the cardiac fibroblast is evolving from the concept of the fibroblast as a bystander that causes unwanted fibrosis to the picture of a more complex role of fibroblasts in the healthy as well as diseased heart. The pathways used by cardiac fibroblasts to communicate with their neighboring myocytes are only partially described, but the data to date indicate that these pathways will be important for cardiac repair and regeneration.

. Paracrine bidirectional cardiac fibroblast-myocyte crosstalk

Figure 2. Paracrine bidirectional cardiac fibroblast-myocyte crosstalk

Under biomechanical overload, cardiac fibroblasts and myocytes respond to an altered environment via multiple mechanisms including integrin-extracellular matrix interactions and renin-angiotensin-aldosterone axis activation. Cardiac fibroblasts increase synthesis of matrix proteins and secrete a variety of paracrine factors that can stimulate myocyte hypertrophy. Cardiac myocytes similarly respond by secreting a conglomerate of factors. Hormones such as TGFβ1, FGF-2, and the IL-6 family members LIF and CT-1 have all been implicated in this bidirectional fibroblast-myocyte hormonal crosstalk.

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Cardiovascular Outcomes: Function of circulating Endothelial Progenitor Cells (cEPCs): Exploring Pharmaco-therapy targeted at Endogenous Augmentation of cEPCs

Author and Curator: Aviva Lev-Ari, PhD, RN

UPDATED on 1/25/2018

The secret to building a strong heart lies in blood vessels, Stanford researcher find

Curiously, blood flow through those missing vessels – and the oxygen it provides – is only part of the story. In a follow-up experiment, the researchers grew heart muscles in a dish along with endothelial cells that had not yet formed into blood vessels. The team found that when those endothelial cells produced no Ino80, the heart muscle didn’t develop properly. Apparently, Red-Horse said, “endothelial cells are producing something that’s a growth factor” for cardiac muscle cells. “The next step is to identify that factor.”

https://news.stanford.edu/2018/01/25/secret-building-strong-heart-blood-vessels/

This is a post in Clinical Cardiology Frontiers:

  • Resident-Cell-based Therapy and
  • Molecular Cardiology

An Overview of the State of  Science on Circulating Endothelial Progenitor Cells (cEPCs) and Cardiovascular Outcomes: Exploring Pharmaco-therapy targeted at Endogenous augmentation of cEPCs

 

Werner (2005) reported that after 12 months a total of 43 participants died, 23 from cardiovascular(CV) causes. A first major cardiovascular event occurred in 214 patients in 519 patients with coronary artery disease as confirmed on angiography. Endothelial progenitor cells (EPCs) derived from bone marrow are believed to support the integrity of the vascular endothelium. His study identified that the number and function of endothelial progenitor cells correlate inversely with cardiovascular risk factors, but the prognostic value associated with circulating endothelial progenitor cells has not been defined. The level of circulating CD34+KDR+endothelial progenitor cells predicts the occurrence of cardiovascular events and death from cardiovascular causes and may help to identify patients at increased cardiovascular risk. The number of endothelial progenitor cells positive for CD34 and kinase insert domain receptor (KDR) was determined with the use of flow cytometry, they evaluated the association between baseline levels of endothelial progenitor cells and death from cardiovascular causes, the occurrence of a first major cardiovascular event (myocardial infarction, hospitalization, revascularization, or death from cardiovascular causes), revascularization, hospitalization, and death from all causes (italics added).

Werner (2005) reported that after 12 months a total of 43 participants died, 23 from cardiovascular(CV) causes. A first major cardiovascular event occurred in 214 patients in 519 patients with coronary artery disease as confirmed on angiography. Endothelial progenitor cells (EPCs) derived from bone marrow are believed to support the integrity of the vascular endothelium. His study identified that the number and function of endothelial progenitor cells correlate inversely with cardiovascular risk factors, but the prognostic value associated with circulating endothelial progenitor cells has not been defined. The level of circulating CD34+KDR+endothelial progenitor cells predicts the occurrence of cardiovascular events and death from cardiovascular causes and may help to identify patients at increased cardiovascular risk. The number of endothelial progenitor cells positive for CD34 and kinase insert domain receptor (KDR) was determined with the use of flow cytometry, they evaluated the association between baseline levels of endothelial progenitor cells and death from cardiovascular causes, the occurrence of a first major cardiovascular event (myocardial infarction, hospitalization, revascularization, or death from cardiovascular causes), revascularization, hospitalization, and death from all causes (italics added).

In light of the inverse correlation found between CV risk and enumeration and function of cEPCs, this study proposes a pharmaco-therapeutic method to enhance the cell count by a method of endogenous augmentation as presented in Part II and called ElectEagle.

 

Phenotypic Identification of Circulating Endothelial Progenitor Cells (cEPCs)

 

In the current state of science on cEPCs, the definition of these cells is ambiguous, as found in Fadini et al. (2004) letter to the Editors of Heart. On this subject, additional five letters were addressed to NEJM Editor in 2005, in reference to Werner et al. (2005) article Correspondence titled: Circulation Endothelial Progenitor Cells. Werner et al. (2005) was in fact the stimulant for this project which takes his result as a starting point and carries the research into pharmaco-therapy and device design for diagnostic based on a quantitative model derived from Werner’s data.

In the article in Heart, peripheral blood CD34+ cells are defined as endothelial progenitor cells. In Fadini’s concern he notes that cEPCs represent a subset of peripheral blood mononuclear cells (PBMNCs) expressing immature surface markers common to hematopoietic stem cells and endothelial lineage markers. By contrast CD34 represents a marker of immature staminal cells that may be used to characterize EPCs together with other surface antigens, but that identifies not only EPCs. Peripheral blood CD34+ cells form a very heterogeneous pool containing also CD45+ cells (lymphatic precursors), CD14+ cells (monocyte/macrophage lineage precursors) and other non-hematopoietic cells not belonging to the endothelial lineage.

Fadini’s concern is supported by George et al. (2006), who concluded that current methods for quantitatively assessing numbers of circulating EPC are not correlated. George’s findings may suggest that CD34/KDR is more appropriate for the definition of circulating EPC, whereas CFU (colony forming Unit) numbers are more likely to reflect their ability to proliferate. Fadini’s research supports the percentage of EPCs among the CD34+ pool vary widely from patient to patient and, in the same patient, under different pathophysiological conditions, indicating possible peripheral differentiation rather than bone-marrow mobilization. His observation is supported by Lapidot & Petit (2002) and Hur et al., (2004).

Furthermore, CD133 is considered the best surface marker to define, identify and isolate circulating EPCs. Even if the exact phenotype of EPCs has not been clearly established, additional markers reflecting endothelial commitment, including Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2 or KDR), Platelet-Endothelial Cells Adhesion Molecule-1 (PECAM-1 or CD31), Vascular Endothelial-Cadherin, von Willebrand Factor, c-kit, Tie-2 and VEGFR-1, are required. Using flow cytometry less than 0,001% of PBMNCs is identified as EPCs, but two or three markers are needed to avoid unspecific count. Thus minimal requirement to identify EPCs should be the parallel use of CD34 (or CD133) and KDR expression, as supported by George (2006).

Thus, he suggests that PBMNCs-derived CD34+ cells may not be used to identify EPCs. Fadini suggests that if we consider that EPCs or CD34+ cells stimulate angiogenesis in a paracrine way by means of producing growth factors, then, it would be more appropriate to call them “Circulating Angiogenic Cells” (CACs) as already proposed. EPCs reduction and endothelial dysfunction as observed by circulating cells and vascular wall cells of diabetic patients are exposed to high oxidative stress, thus increased apoptosis or reduced peripheral differentiation are likely to explain low EPCs counts. Several other clinical conditions characterized by poor endothelial function, like diabetes mellitus, obesity, hypertension, autoimmune disorders (such as Systemic Lupus Erythematosus), chronic renal diseases, etc., all are likely to be influenced by EPCs reduction (Fadini, 2004).

The five letters to NEJM Editor, Kim et al (2005) are of great scientific merit and of great interest to this project. We are developing new intellectual property (IP) in several forms in Part II and Part III. The IP in Part III is actually using Werner et al. (2005a) data, for our method called ElectEagle. Therefore, here, Werner’s (2005b) points will be considered as his reply to the five letter correspondence and no discussion of the content of the five letters is presented.

  •           Werner & Nickenig (2005b) disagree with Bertolini et al. that CD34+KDR+ cells are mature circulating endothelial cells. Endothelial cells are predominantly identified by the presence of CD146 (and results of Boos et al., as described in their letter).
  •           In Werner et al (2005a), CD146+ circulating endothelial cells were not predictive of cardiovascular outcomes, which indicates that CD34+KDR+ cells differ substantially from circulating endothelial cells (unpublished data). It is an accepted standard to identify circulating endothelial progenitor cells by the presence of CD34 and KDR.
  •           To confirm the results, Werner et al (2005a) measured CD133+ endothelial progenitor cells and obtained similar results, which appear in the online Supplementary Appendix to our article.
  •           Drs. Ott and Taylor suggest calculating the absolute number of endothelial progenitor cells with the use of peripheral-blood mononuclear cells or lymphocytes. However, absolute cell counts measured by flow cytometry can be determined only with the use of enumeration systems (e.g., flow count beads).
  •           At present, we cannot think of a major advantage to measuring the absolute number of endothelial progenitor cells. The method provided allows a single measurement that is easy to perform, highly predictive, and transferable to other laboratories.
  •           Dr. Kim and Dr. Leu and colleagues address  the role of endothelial progenitor cells in acute coronary syndromes and acute myocardial infarction. Only one study has investigated the mobilization of CD34+KDR+ endothelial progenitor cells in myocardial infarction, whereas other studies have measured CD34+ cells or non–endothelial progenitor cell subfractions.
  •           None of the studies have systematically looked at the time course directly after acute myocardial infarction, owing to the fact that the exact onset of myocardial infarction is difficult to determine. Treatment of myocardial infarction requires the administration of multiple drugs that may influence the number of endothelial progenitor cells. Therefore, current data on progenitor cells in myocardial infarction are questionable.
  •           In order to elucidate the mobilization of endothelial progenitor cells after myocardial infarction, Werner et al (2005a) measured the number of CD34+KDR+ cells in patients undergoing transcoronary ablation of septal hypertrophy (unpublished data). Preliminary results indicate that directly after myocardial infarction, the number of endothelial progenitor cells decreases as a result of consumption of cells within the ischemic region. The increase in cells described previously may be due to medical treatment.
  •           No patient who was included in the study had had a recent ischemic event, so misclassification of patients was not an issue.
  •           Werner et al. (2005a) did not find an association between high sensitivity CRP measures and the number of endothelial progenitor cells. To their knowledge, there are no data available on the association between endothelial progenitor cells and inflammatory markers in a similar population of patients. Data that are available come from in vitro, animal, and small-scale studies investigating the role of endothelial progenitor cells in acute coronary syndromes. Since their study population consisted mainly of patients with stable coronary artery disease, this may explain the lack of an association.

Circulating Endothelial Cells (cECs) and Circulating Endothelial Progenitor Cells (cEPCs)

Vascular endothelial cells (EC) respond to numerous pathophysiological stimuli such as growth factors, cytokines, lipoproteins, and oxidative stress. Prolonged or unregulated activation of these cells often results in a loss of EC integrity and, thus, dysfunction—a process that can be assessed by the use of specific plasma markers such as von Willebrand factor (vWf), tissue plasminogen activator, soluble EC protein C receptor, soluble E selectin, and soluble thrombomodulin, as well as physiological techniques such as flow-mediated dilatation (FMD). Indeed, endothelial perturbation in cancer may well contribute to an increased risk of thrombosis in these patients. (Goon et al., 2006)

The presence of circulating endothelial cells (cECs) has recently been recognized as a useful marker of vascular damage. Usually absent in the blood of healthy individuals, cECs counts are elevated in diseases hallmarked by the presence of vascular insult, such as sickle cell anemia, acute myocardial infarction, Cytomegalovirus (CMV) infection, endotoxemia, and neoplastic processes. Current opinion suggests toxemia, that cECs are cells driven from the intima after vascular insult, and are thus the consequence—rather than the initiator—of a particular pathology (Goon et al., 2006).

A related circulating cell population are endothelial progenitor cells (cEPCs), which originate from the bone marrow, rather than from vessel walls. Seen in small numbers in healthy individuals, their numbers tend to increase following vascular injury. So far, experiments have established the ability of EPCs to form colonies in vitro, suggesting a role in both angio-genesis and in the, maintenance of existing vessel walls.

CEC are generally accepted as cells expressing endothelial markers [e.g., vWf, CD146, and vascular endothelial cadherin (VE-cadherin)] in the absence of hematopoietic (CD45 and CD14) and progenitor (CD133) markers. Interestingly, the progenitor marker CD34 is also present on mature cECs. Although CD146 is widely regarded as the principal marker for cECs (mature cell form), it has also been described in trophoblasts, mesenchymal stem cells, periodontal and malignant (prostatic cancer and melanoma) tissues, and activated lymphocytes (Goon et al., 2006).

Optimal Method for cECs and cEPCs Quantification (Cell Count) Remains Unknown

Together with EPCs, cECs only represent between 0.01% and 0.0001% of mononuclear cells in normal peripheral blood (Khan et al. (2005), making it very difficult to accurately quantify their numbers. To do this, it is often necessary to employ cell enrichment techniques combined with specific cell marker labeling.  The immunobead capture method (immunomagnetic beads bearing CD146 antibodies) developed by George et al. (1992) is the most widely used. Immunobeads have been successfully employed by other investigators, albeit with modifications [e.g., addition of EDTA and albumin to minimize cECs autoaggregation; drying cECs on a glass slide before counting (this enables storage at room temperature and secondary labeling); use of UEA-1 (an EC-specific stain); addition of an Fc receptor blocking agent, and double labeling for further analyses (e.g., for CD31 and CD34)]. After cell separation, either fluorescence microscopy, immunocyto-chemistry, or flow cytometry is used to confirm the endothelial chemistry, phenotype of the cells. Other methods used to concentrate mononuclear cell suspensions include standard and density (Lymphoprep, Axis-Shield, Oslo, Norway; Percoll, Sigma, St. Louis, MO; Ficoll, Sigma) centrifugation and mononuclear cell culturing on fibronectin-coated plates. The main alter- alternative to the immunobead method is flow cytometry” (Goon, 2006).

Werner et al. (2005a) used the following method for Flow Cytometry — For fluorescence-activated cell-sorting analysis, mononuclear cells were resuspended in 100 µl of a fluorescence-activated cell-sorting buffer containing phosphate-buffered saline, 0.1 percent bovine albumin, and aprotinin (20 µl per milliliter). Immunofluorescent cell staining was performed with the use of the fluorescent conjugated antibody CD34–fluorescein isothiocyanate (FITC) (10 µl; Becton Dickinson), KDR (kinase insert domain receptor), and CD133–phycoerythrin (PE) (10 µl; Miltenyi). For the identification of KDR+ cells, indirect immunolabeling was performed with the use of a biotinylated goat mononuclear antibody against the extracellular domain of human KDR (R&D Systems). IgG2a–FITC–PE antibody (Becton Dickinson) served as a negative control. For staining of KDR, extensive blocking was required with the use of human immunoglobulin (polyglobulin, 10 percent; Bayer) and goat serum (Sigma-Aldrich). Cell fluorescence was measured immediately after staining, and data were analyzed with the use of CellQuest software (FACS Calibur, Becton Dickinson). Units of all measured components are absolute cell counts obtained after the measurement of 10,000 events in the lymphocyte gate. To assess the reproducibility of the measurements, two separate blood samples were obtained, on days 0 and 7, from 10 subjects. The intraclass correlation between the two probes was 0.94. Probes were measured at the same time of day, with identical instrument settings, by two investigators. For each patient, a corresponding negative control with IgG2a–FITC–PE antibody was obtained.

Colony-Forming Units of Endothelial Cells (Werner et al. 2005a)

In an endothelial basal medium (CellSystems) with supplements, 1×107 mononuclear cells were seeded on human fibronectin–coated plates (Sigma-Aldrich). After 48 hours, 1×106 nonadherent cells were transferred into new fibronectin-coated wells to avoid contamination with mature endothelial cells and nonprogenitor cells.22 After seven days in vitro, endothelial colony-forming units in at least three wells were counted by two independent investigators. Colony-forming units of endothelial cells are expressed as absolute numbers of colonies per well. (Werner, et al. 2005)

George et al. (2006) reports using the following method while performing an analysis of several methods used for cEPCs assessment and correlated them with humoral factors known to influence their numbers:

Peripheral blood mononuclear cells were obtained and stained for FACS analysis with antibodies to CD34, CD45, CD133, and KDR and the remaining cells grown under endothelial cell conditions for assessment of colony-forming unit (CFU) numbers and adhesive properties. Levels of circulating vascular endothelial growth factor (VEGF), erythropoietin (EPO), and C-reactive protein (CRP) were determined and correlated with each of the EPC markers.

Pathophysiology of cECs

The endothelium can be viewed as a membrane-like layer lining the circulatory system, its primary function being the maintenance of vessel wall permeability and integrity. The EC layer is relatively quiescent, with an estimated cell turnover period of between 47 and 23,000 days, as shown by labeling studies. Proliferation seems to occur mainly at sites of vasculature branching and turbulent flow. cECs are thought to have ‘‘sloughed off’’ vessel walls, indicating severe endothelial damage. Thus, unsurprisingly, cECs have been shown to correlate with various endothelial dysfunction and inflammatory markers.

Although not fully understood, it would appear that cECs detachment from the endothelium involves multiple factors, such as mechanical injury, alteration of endothelial cellular adhesion molecules (such as integrin alphaVbeta3), defective binding to anchoring matrix proteins (such as fibronectin, laminin, or type IV collagen), and cellular apoptosis with decreased survival of cytoskeletal proteins. The net effect is a reduced interaction between the EC and basement membrane proteins, with subsequent cellular detachment (Goon et al. 2006).

 

Pathophysiology of cEPCs

In Science 1997, Asahara et al. was the first to isolate EPC in human peripheral blood, using anti-CD34 monoclonal antibodies. With the use of CD133, an antigen specifically identifying primitive stem cells, a novel means to precisely delineate mature (cECs) from immature (cEPCs) EC forms was possible (Asahara et al. 1997), although this antigen is only present in human EPCs and cannot be applied to mouse EPCs (Rafii et al. 2003). To detect cEPCs in peripheral blood, Flow Cytometry and culture have become the principal methods employed. Other markers used include vWf, VE-cadherin, vascular endothelial growth factor receptor-2 (VEGFR-KDR) and binding by lectins and acetylated low-density lipoproteins (Peichev et al. 2000, Rafii et al. 2003).

cEPCs are potentially crucial for neovascularization and may be recruited from the bone marrow after tissue ischemia, vascular insult, or tumor growth (Rafii et al. 2003). They possess the ability to migrate, colonize, proliferate, and, ultimately, differentiate into endothelial lineage cells. These cells have yet to acquire mature ECs characteristics while appearing to contribute to vascular homeostasis.

cEPCs have been isolated previously from human umbilical cord blood, adult bone marrow, human fetal liver cells, and cytokine-mobilized peripheral blood, and an increase in cEPCs follows in vivo administration of the angiogenic growth factor VEGF. When incubated with VEGF, fibroblast growth factor-2 (FGF-2), and insulin-like growth factor, CD133+ cells differentiated into mature-type adherent EC, expressing endothelial-specific cell markers (vWf and VE-VE cadherin) and abolishing CD133 expression (Goon, 2006). Generation of endothelial outgrowths that are positive for CD146, vWf (mature endothelial growth markers), and CD36 (a representative scavenger receptor marker as well as a microvascular marker) markers from circulating mononuclear cells (of donor genotype in bone marrow transplant patients), strongly suggests the viability and proliferative potential of cEPCs.

cEPCs recruitment and mobilization have been positively correlated with increased levels of angiogenic growth factors such as VEGF which induces the proliferation, differentiation, and chemotaxis of cEPCs, and is essential for hematopoiesis, angiogenesis, and, ultimately, survival.  cEPCs influence cells mainly by interactions with VEGFR-1 and VEGFR-2, both being receptors expressed on hematopoietic stem cells (HSC) and cEPCs. In another study, granulocyte colony-colony stimulating factor also increased the number of CD34 stimulating CD34+ cells, potentially stimulating neovascularization in areas of is- ischemic myocardium Other angiogenic growth factors stimulating cEPCs mobilization include angiopoietin-1, FGF, SDF-1, PlGF, and (in mice) macrophage colony-stimulating factor. After mobilization, cEPCs appear to “home in” and become incorporated into sites of vascular injury and ischemia, with evidence of improvement in the function and viability of tissue (e.g., after acute myocardial infarction) (Kocher et al. 2001).

Chemotactic agents responsible for this process include VEGF and SDF-1, but others may also be involved. In the clinical setting, moderate exercise of patients with stable coronary artery diseases leads to a significant increase in cEPCs (Laufs et al. 2004). Furthermore, cEPCs and HSC introduced into the circulation of acute and chronic cardiovascular disease patients through injection have shown vascular encouraging preliminary results, with evidence of improved cardiovascular function and tissue perfusion Tse et al. (2003); as of yet, there are no randomized control trial!

Recent reports suggest that cECs and cEPCs enumeration can be used to monitor antiangiogenesis drug therapy with some success. This exciting prospect needs to be fully corroborated in a clinical setting. In addition, cECs and cEPCs monitoring would need to be efficient, specific, robust, and reproducible. Therefore, it is vital to reach a general consensus regarding definitions and techniques for cECs and cEPCs quantification, in order to validate further reports that have implications for future clinical trials involving these markers (Goon, 2006).

In 2002, matrix metalloproteinase-9 (MMP-9) was identified as the molecular key to the release of EPCs from the bone-marrow compartment via cleavage of membrane kit ligand (Heissig et al., 2002). MMP-9 activity has also been shown to be upregulated by SDF-1alpha, VEGF, and hypoxia. Hypoxia is a potent stimulus for neovascularization, ischemia-induced growth, EPC trafficking and upregulation, vascular malformations and malignant endothelial cell tumors. This include activation of two upstream mediators of vasculogenesis, SDF-1 alpha and MMP-9, during the proliferative phase via EPC mediated vasculogenesis when these stem cells may rapidly proliferate in the ischemic tissue resulting in growth.

How a mobilized population of progenitor cells homes to ischemic tissue under repair was examined using bone-marrow transplantation studies. Following this procedure, reconstitution is regulated by chemokine ligand-receptor pair, stromal-cell derived factor 1 (SDF-1) and CXCR4 (Lapidot & Petit, 2002 reporting their discovery of 1999). EPCs express CXCR4, CXCR4/SDF-1 signal for EPC homing to peripheral sites of neovascularization. EPC SDF-1alpha expression was increased in proportion to reduced oxygen tension and this correlated with EPC localization in the most ischemic tissue sections (Kleinman, et al. 2005).

Table 1: Humoral factors known to influence eCPCs numbers

CD34 CD45 CD133 KDR CD34/KDRMost appropriate Definition of cEPCs CD34/CD133/KDR CD34/CD133 Adhesive properpies
VEGF level corr Positive correlation
EPO
CRP
CFU Colony forming unit numbersReflects cEPCs ability to proliferate No corr No corr Negative correlation Positive correlation
Adhesive properties No corr No corr No corr No corr
CD34
CD45
CD133
KDR
CD34/CD133/KDR Positive correlation
CD34/CD133 No corr

 SOURCE:

Table 1 is constructed from data in George et al. (2005),(2006) who concluded that current methods for quantitatively assessing numbers of circulating EPC are not correlated. VEGF serum levels are associated only with CD34/KDR and CD34/ CD133/KDR, whereas CFU numbers correlate with EPC functional properties. These findings may suggest that CD34/KDR is more appropriate for the definition of circulating EPC, whereas CFU numbers are more likely to reflect their ability to proliferate.

 

Trans-Endothelium Cell Migration

Lapidot and Petit in a recent review of the stem cell mobilization research field concluded that the following are the seminal processes at work in the facilitation of transendothelium cell migration. These processes could mediate stem cell release and remodeling of the bone marrow microenvironment, followed by stem cell migration via the circulation, homing back to the bone marrow and repopulation of damaged/restructured sites in an organ as part of the continuous replenishment of the blood with new immature and maturing cells while maintaining undifferentiated stem cells (Lapidot and Petit, 2002).

  •       Regulation of hematopoietic stem cell release, migration, and homing to the bone marrow, as well as the mechanism of different mobilization pathways, involve a complex interplay between adhesion molecules, chemokines, cytokines, proteolytic enzymes, stromal cells, and hematopoietic cells, the mechanism is not fully understood;
  •       The chemokine, stromal derived factor-1 (SDF-1)and its receptor CXCR4 play a major role in stem cell mobilization, including granulocyte colony-stimulating factor (G-CSF) and G-CSF with the chemotherapeutic agents cyclophosphamide Cy-induced mobilization, as well as in stem cell homing to the bone marrow and anchorage (i.e., activation of adhesion interactions in order to retain stem cells within the organ).
  •       They suggested that in addition to SDF-1 degradation and inactivation within the bone marrow by proteolytic enzymes such as neutrophil elastase, which is essential for optimal stem cell mobilization, interactions between this chemokine and its receptor are also needed for stem cell release and mobilization. For example, they suggested that IL-8, which is secreted in response to SDF-1 stimulation, and MMP-2 and MMP-9, which are mostly secreted by neutrophils but are also secreted by immature human CD34+ progenitor cells in response to stimulation with this chemokine, can also lead to migration away from the bone marrow across the endothelium into the circulation also in the absence of or against a gradient of SDF-1 under shear flow forces within the extravascular space of the bone marrow (Cinamon et al., 2001).
  •        They suggest that in order to maintain stem cells in the circulation low levels of surface CXCR4 are required and may be achieved by factors in the blood plasma such as proteolytic enzymes that can also cleave CXCR4 in addition to SDF-1 . Valenzuela-Fernandez (2002). Furthermore, increase in the levels of CXCR4 expression on the surface of stem cells in the circulation will mediate their homing and reengraftment of the bone marrow as part of homeostatic regulation of leukocyte trafficking as well as steady-state hematopoiesis and stem cell self-renewal, which go hand in hand with bone destruction and bone remodeling. However, this hypothesis is also an oversimplification of a much more complex and dynamic situation with physiological steady-state homeostatic as well as stress-induced mobilization situations in which the mechanisms and mode of regulation are still poorly understood.
  •        A significant number of studies in the past few years have revealed insights into regulation of hematopoietic stem cell release, migration, and homing as well as the mechanism of different mobilization pathways. However, the exact sequence of events involving many different molecules is still not clear. More importantly, in addition to results from clinical mobilization protocols using Cy and G-CSF, which demonstrate a role for SDF-1 and CXCR4 interactions in immature human CD34+ cell mobilization, two recent reports also demonstrate a role for these interactions in autologous and allogenic CD34+ cell homing and repopulation.
  •        Taken together, these results suggest that stem cell homing and release or mobilization are mirror images utilizing a similar mechanism and suggest manipulation of SDF-1/CXCR4 interactions in order to improve stem cell mobilization or to target migration of transplanted cells to specific organs. These results strongly support the idea that increasing the migration potential of immature human CD34+ cells prior to transplantation, either by short term stimulation with SCF and IL-6 and/or by cotransplantation with accessory cells. It could also increase homing and repopulation in transplanted patients, leading to improved treatment efficiencies and cure rates in clinical protocols.

 

Prospects and Limitations of Exogenous methods for cEPCs Augmentation

ElectEagle represents a conceptual formulation for several strategies to increase cEPCs number endogenously.

Additional posts on this Scientific Web Site on related topics are:

Lev-Ari, A., (2012S). Endothelial Dysfunction, Diminished Availability of cEPCs, Increasing CVD Risk for Macrovascular Disease – Therapeutic Potential of cEPCs

https://pharmaceuticalintelligence.com/2012/08/27/endothelial-dysfunction-diminished-availability-of-cepcs-increasing-cvd-risk-for-macrovascular-disease-therapeutic-potential-of-cepcs/

Lev-Ari, A., (2012T). Vascular Medicine and Biology: CLASSIFICATION OF FAST ACTING THERAPY FOR PATIENTS AT HIGH RISK FOR MACROVASCULAR EVENTS Macrovascular Disease – Therapeutic Potential of cEPCs

https://pharmaceuticalintelligence.com/2012/08/24/vascular-medicine-and-biology-classification-of-fast-acting-therapy-for-patients-at-high-risk-for-macrovascular-events-macrovascular-disease-therapeutic-potential-of-cepcs/

Below, this method is contrasted with exogenous methods involving the cell-based vascular therapy approaches currently applied for angiogenesis (mature cell-derived generation of new vessels), vasculogenesis (EPC-dependent generation of new vessels), neovascularization (ischemic tissue) and re-endothelialization (injured blood vessel.)  The majority of these methods are exogenous involving implantation or transplantation of various kinds: genetically engineered vein grafts, vascular bioprosthesis, retroviral transduction of genetic modifications to over-express a therapeutic gene(s).Despite the hurdles quoted below, the outlook for EPC-based therapy for cardiovascular disease is promising.Among the remaining outstanding issues in this fast growing research discipline, Dzau et al., chart a perspective for future research directions (Dzau et al. 2005)

“Despite the encouraging results regarding the therapeutic potential of EPCs, several issues currently stand in the way of their wide clinical application. Strategies need to be developed to enhance the number of EPCs to allow the harvesting of adequate number for therapeutic application. The limited ability to expand PB-MNC–derived EPCs in culture to yield sufficient number for clinical application indicates that alternative sources of cells (i.e., chord blood) or strategies to increase their number endogenously need to be explored. We believe that further characterization of the biology of EPCs, the nature of the mobilizing, migratory and homing signals, and the mechanisms of differentiation and incorporation into the target tissues need to be identified and further characterized. Strategies to improve retention and survival of the transplanted cells need to be developed as well. The issues of the timing of cell administration, the appropriate clinical condition, the optimal cell number, and, most importantly, the safety of cell transplantation must be defined. There is urgent need to standardize the protocols for isolation, cultivation, and therapeutic application for cell-based therapy. Finally, large-scale randomized, controlled, multi-centric trials will be essential to evaluate the long-term safety and efficacy of EPC therapy for treatment of tissue ischemia and vessel repair amid concerns of potential side effects such as neovascularization of occult neoplasias and the development of age- and diabetes-related vasculopathies. Despite these hurdles, the outlook for EPC-based therapies for tissue ischemia and blood vessel repair appears promising. Genetic engineering of EPC may provide an important strategy to enhance EPC mobilization, survival, engraftment, and function, thereby rendering these cells efficient therapeutic modalities for cardiovascular diseases.” (italics added).

In the Brief Review in Hypertension, Dzau et al., list several serious potential problems with therapeutic use of EPCs (Dzau et al. 2005)

“Although the preclinical and clinical studies reviewed here generally lend support to the therapeutic potential of autologous EPCs in the treatment of tissue ischemia and repair of injured blood vessels, the clinical application of EPCs is limited by several factors. First, the scarcity of cEPCs makes it difficulty to expand sufficient number of cells for therapeutic application without incurring the risk of cell senescence and change in phenotype (Asahara, et al., 1997, 1999). Furthermore, EPCs from patients with cardiovascular diseases display varying degrees of functional impairment (Vasa et al., 2001a, 2001b), (Hill et al., 2003), (Heeschen et al., 2004), (George et al., 2003), (Loomans et al., 2004), (Tepper et al., 2002). Aging and diabetes markedly reduce the availability and impair the function of EPCs (Hill et al., 2003), (Loomans et al., 2004), (Tepper et al., 2002), (Schatteman et al., 2000), (Scheubel et al., 2003), (Edelberg et al., 2002). Because older and diabetic patients are the most vulnerable populations for cardiovascular diseases, this severely restricts the ability to treat with autologous EPCs the patients who theoretically need them most.

The purity and developmental stage of the cells used for transplantation are important factors. Yoon et al reported recently that injection of total bone marrow cells into the heart of infarcted rats could potentially lead to severe intramyocardial calcifications (Yoon et al., 2004). In contrast, animals receiving the same number of clonally expanded bone marrow cells did not show myocardial calcification. Thus, this finding brings attention to the potential risks of transplanting unselected bone marrow cells and cautions against their premature use in the clinical setting.

Exogenous mobilization of bone marrow with hematopoietic growth factors and other endothelial cell growth factors may recruit progenitor cells to sites of occult neoplasia, leading to vascularization of dormant tumors. In addition, mobilization could potentially accelerate progression of atherosclerotic plaque by recruiting inflammatory and vascular smooth muscle cell progenitor cells into the plaque, contributing to neointima hyperplasia and transplant arteriopathy (Caplice et al., 2003), (Sata et al., 2002). Increased rate of in-stent restenosis led recently to the cancellation of the MAGIC clinical trial using G-CSF for endogenous mobilization of progenitor cells in patients with myocardial infarction.120 Finally, there has been one study that has shown evidence that EPC may themselves contribute to allograft vasculopathy by promoting neovascularization of the plaque(Hu et al., 2003). However, another study failed to show evidence that EPCs contribute significantly to transplant arteriosclerosis (Hillebrands et al., 2003).”

In accordance with this account is the latest review of EPC as therapeutic vectors in CV disorders covering experimental models and human trials (Ben-Shoshan and George, 2006).

The conceptual formulation for several strategies to increase cEPCs number endogenously presented in this investigation is complementary to methods currently applied or are still in clinical trials, as reviewed by Dzau et al. (2005). However, our approach, ElectEagle, involves endogenous augmentation of cEPCs by development of a concept-based protocol for therapeutic treatment using three components:

  •                Inhibition of ET1, ETB
  •                Induction of NO production and stimulation of eNOS
  •                Treatment Regimen with PPAR-gamma agonists (TZD) 

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Reporter: Sudipta Saha, Ph.D.

Assessment of the propensity for vascular events has been based on measurement of risk factors predisposing one to vascular injury. These assessments are based on the strong associations between risk factors such as hypertension, cholesterol levels, smoking, and diabetes which were first described almost a half century ago. The more recent discovery of the relationship between ongoing inflammation and clinical outcomes has led to a variety of blood-based assays which may impart additional knowledge about an individual’s propensity for future cardiovascular events. Vascular health is now better represented as a balance between ongoing injury and resultant vascular repair, mediated at least in part by circulating endothelial progenitor cells (http://www.ncbi.nlm.nih.gov/pubmed/19124422). Accurate enumeration of circulating endothelial progenitor cells is essential for their potential application as biomarkers of angiogenesis. Different stem cell markers (CD34, CD133) and endothelial cell antigens (KDR/VEGFR-2, CD31) in different flow cytometric protocols are assessed for the purpose of circulating progenitor endothelial cell quantification (http://www.ncbi.nlm.nih.gov/pubmed/20381496). Enumeration of circulating progenitor endothelial cells are used in the assessment of various diseases and physiological states, such as: type 2 diabetes patients with peripheral vascular disease, certain phases during congestive heart failure, acute myocardial infarction, atherosclerosis, cardiovascular disease, physical training, cessation of smoking. Two modern instruments used now-a-days to measure the circulating progenitor endothelial cells are discussed below:

MACSQuant® Analyzer:

Circulating progenitor endothelial cells are defined by co-expression of the markers CD34, CD309 (VEGFR-2/KDR), and CD133, though CD133 expression is lost during maturation to endothelial cells.8-10 Since circulating progenitor endothelial cells are rare in peripheral blood, EPC enumeration protocols are rather extensive and laborious. To obtain reliable enumeration results for these rare cells, the sensitivity of flow cytometric analysis needs to be increased. This has been achieved by magnetic enrichment of circulating progenitor endothelial cells prior to flow cytometric analysis, which reduces the number of events that have to be analyzed. The circulating progenitor endothelial cell Enrichment and Enumeration Kit have been designed for enumeration of circulating progenitor endothelial cells from peripheral blood, cord blood, bone marrow, or leukapheresis products. In combination with magnetic pre-enrichment and flow cytometric analysis on the MACSQuant® Analyzer, this kit overcomes some of the limitations of circulating progenitor endothelial cell analysis and offers a simple and time effective solution for EPC enumeration. The circulating progenitor endothelial cell Enrichment and Enumeration Kit in combination with pre-enrichment and flow cytometric analysis on the MACSQuant Analyzer is an effective method to enumerate circulating progenitor endothelial cells in 10 mL of whole blood. Based on the calculated starting number of cells, the circulating progenitor endothelial cell Express Mode analysis template automatically calculates the absolute number and concentration of circulating progenitor endothelial cells in 10 mL of starting material, i.e., whole blood, bone marrow, cord blood, or leukapheresis products. The MACSQuant Analyzer has the ability to enrich cells using MACS technology. This capability makes the enumeration of circulating progenitor endothelial cells fast and easy. The entire process takes less than 2 hours to perform from blood draw to analyzed data and drastically reduces the time and difficulty of such a protocol by combining magnetic enrichment and flow cytometric analysis in one streamlined experiment (http://www.miltenyibiotec.com/downloads/6760/6764/18602/31184/MQ_ApplicationFlyer_EPC.pdf).

Attune® Acoustic Focusing Cytometer:

In cancer research, circulating progenitor endothelial cells have been suggested as a noninvasive biomarker for angiogenic activity, providing insight into tumor regrowth, resistance to chemotherapy, early recurrence, and metastasis during or after chemotherapy. In healthy individuals, circulating progenitor endothelial cells are reported to be present in very low numbers: 0.01%–0.0001% of all peripheral blood mononuclear cells. Flow cytometry offers the necessary collection and analysis capabilities for detection of circulating progenitor endothelial cells, but is subject to numerous technical challenges. In comparison to traditional hydrodynamic focusing cytometers, the Attune® Acoustic Focusing Cytometer, with its fast acquisition times and increased precision, overcomes the technological hurdles involved in analyzing circulating progenitor endothelial cells. The method includes a number of conventional ways to improve rare-event detection: a blocking step, a viability stain (SYTOX® AADvanced™ Dead Cell Stain), and the use of a dump channel to eliminate unwanted cells and decrease background fluorescence. The challenge of collecting a large enough number of events in a reasonable amount of time is met by using a collection rate of 1,000 μL/min with the Attune® cytometer. This setting enables the collection of more than 4,000,000 live white blood cell (WBC) events in just 35 minutes; the acquisition time using a traditional hydrodynamic focusing cytometer would be 10–12 times longer, close to 6 hours. Furthermore, this method delivers additional time savings by eliminating wash steps to avoid sample loss and employing a simpler sample preparation method. (http://zh.invitrogen.com/etc/medialib/files/Cell-Analysis/PDFs.Par.54318.File.tmp/CO24210-Human-CEC_cancer.pdf)

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