Pericyte dynamics during angiogenesis: new insights from new identities

Abstract

Therapies aimed at manipulating the microcirculation require the ability to control angiogenesis, defined as the sprouting of new capillaries from existing vessels. Blocking angiogenesis would be beneficial in many pathologies (e.g. cancer, retinopathies and rheumatoid arthritis). In others (e.g. myocardial infarction, stroke and hypertension), promoting angiogenesis would be desirable. We know that vascular pericytes elongate around endothelial cells (ECs) and are functionally associated with regulating vessel stabilization, vessel diameter and EC proliferation. During angiogenesis, bidirectional pericyte-EC signaling is critical for capillary sprout formation. Observations of pericytes leading capillary sprouts also implicate their role in EC guidance. As such, pericytes have recently emerged as a therapeutic target to promote or inhibit angiogenesis. Advancing our basic understanding of pericytes and developing pericyte-related therapies are challenged, like in many other fields, by questions regarding cell identity. This review article discusses what we know about pericyte phenotypes and the opportunity to advance our understanding by defining the specific pericyte cell populations involved in capillary sprouting.

Figure 1

Pericyte dynamics involved in angiogenesis. Pericyte dynamics include recruitment, ECM modulation, and growth factor presentation (secretion and binding). During recruitment, nearby pericytes or interstitial cell populations (i.e. fibroblasts or resident precursor cells – depicted as the blue cell) migrate to the endothelial cell-lined capillary sprout. Pericytes can also directly interact with endothelial cells via NG2 transmembrane protein binding to β1 integrins to influence their behavior [29, 36, 89]. Each dynamic represents a specific pericyte function critical for regulating capillary sprouting.

Figure 2

Pericyte marker heterogeneity across a microvascular network. Examples of NG2 and SMA labeling along arterioles (A), venules (V) and capillaries (c) in adult rat mesenteric networks undergoing angiogenesis. NG2 labeling identifies SMA positive SMCs along arterioles, but not SMA positive SMCs along venules. At the capillary level, pericytes are positive for NG2 and negative for SMA. Scale bars = 25 µm.

Figure 3

Do pericytes change their phenotype during angiogenesis? Pericytes play a role in vessel stabilization during unstimulated (non-angiogenic) scenarios and capillary sprouting during pro-angiogenic scenarios. The question remains whether a subpopulation of pericytes emerge to perform functions unique to angiogenesis.

Figure 4

Pericyte differentiation during angiogenesis. This represents an example of the changing of phenotype by pericytes from an unstimulated (non-angiogenic) to an angiogenic scenario in adult rat mesenteric microvascular networks. In unstimulated microvascular networks, class III β-tubulin labeling is nerve specific and does not identify perivascular cells along PECAM positive arterioles, venules (V), or capillaries (c). During angiogenesis, perivascular cells along all vessels change their phenotype to become class III β-tubulin positive (arrows). The transient upregulation of class III β-tubulin by pericytes during angiogenesis highlights the potential for specialized pericyte subpopulations. Scale bars = 25 µm.

Figure 5

Pericytes in vitro express class III β-tubulin. Commercially available human brainderived vascular pericytes from ScienCell positively labeled for class III β-tubulin when cultured in Pericyte Medium containing 2% fetal bovine serum, 1% pericyte growth supplements and 1% 100x penicillin/streptomycin. (A; scale bar = 50 µm). B Higher magnification images display class III β-tubulin localization in tubule structures (Scale bar = 20 µm). C All human brainderived pericytes co-expressed the pericyte marker NG2 (Scale bar = 50 µm).

Figure 6

Class III β-tubulin regulates pericyte migration. A–C Class III β-tubulin and DAPI nucleic acid labeling in the human brain-derived pericytes 6 hours after a scratch wound was applied (scale bars = 200 µm). Inhibition of class III β-tubulin was confirmed qualitatively by the reduction in class III β-tubulin positive cells (C) compared to control groups (A, B). D Quantification of scratch closure for the Control Sham, Control siRNA, and class III β-tubulin Target siRNA groups. At 72 hours (24 hour transfection + 48 hours for gene suppression to manifest), each monolayer was scratched and imaged. After 6 hours, scratches were again imaged and the change in scratch area was blindly quantified for 8 wells per group (n=8 per group).Scratch wound closure fractions were compared using a one-way ANOVA followed by a Student-Newman-Keuls pairwise comparison test. *, + represent significant differences (p<0.05) from Control Sham and Control siRNA groups, respectively. E Quantification of the fraction of class III β-tubulin positive cells inside the initial scratch area compared to the general population outside the scratch area (n= 8 per group). Statistical comparison between the two groups was made using a Student’s t-test. * represents a significant difference (p<0.05). F Example of class III β-tubulin and DAPI nucleic acid labeling along the leading of a scratch-wound in the Target siRNA group. Class III β-tubulin positive versus negative cells were more prone to migrate into the wound area. * indicates class III β-tubulin negative cell nuclei. Arrows indicate class III β-tubulin positive cells (scale bar = 50 µm). Values are presented as means +/− SEM.