Extracellular matrix compression temporally regulates microvascular angiogenesis

Abstract

Mechanical cues influence tissue regeneration, and although vasculature is known to be mechanically sensitive, little is known about the effects of bulk extracellular matrix deformation on the nascent vessel networks found in healing tissues. Previously, we found that dynamic matrix compression in vivo potently regulated revascularization during bone tissue regeneration; however, whether matrix deformations directly regulate angiogenesis remained unknown. Here, we demonstrated that load initiation time, magnitude, and mode all regulate microvascular growth, as well as upstream angiogenic and mechanotransduction signaling pathways. Immediate load initiation inhibited angiogenesis and expression of early sprout tip cell selection genes, while delayed loading enhanced microvascular network formation and upstream signaling pathways. This research provides foundational understanding of how extracellular matrix mechanics regulate angiogenesis and has critical implications for clinical translation of new regenerative medicine therapies and physical rehabilitation strategies designed to enhance revascularization during tissue regeneration.

Fig. 1. Quantification of microvascular network length and branching under 5, 10, and 30% strain loading.

(A) Microvascular fragments were cultured in DCN-supplemented hydrogels. Gels were loaded continuously for either the first 5 days of culture (early loading) or the final 5 days of culture (delayed loading). Gels were loaded at either 5, 10, or 30% strain. (B) Gels were loaded in compression with platens having a diameter greater than that of the gel or in compressive indentation by platens with a diameter less than that of the gel that also introduced greater shear stress. (C to H) Quantification of microvascular network length and branching based on 3D confocal z stacks of 200-μm depth. *, significant difference from nonloaded; one-way ANOVA, *P < 0.05, **P < 0.01, and ***P < 0.001; #, two-way ANOVA with Bonferroni post hoc test; @, overall effect of loading type; ^, overall effect of time; post hoc, ^#P < 0.05, ^##P < 0.01, and ^###P < 0.001. n = 6 per group.

Fig. 2. Simulation of DCN-supplemented collagen hydrogels subjected to 5, 10, and 30% strain loading.

Spatial distributions of compressive and shear stress and strain are plotted for compression and indentation to show (A) maximum compressive stress (third principal; Pa/mm), (B) maximum shear stress (octahedral; Pa/mm), (C) maximum compressive strain (third principal Lagrange strain; 1/mm), and (D) maximum shear strain (octahedral Lagrange strain; 1/mm). Cross-sectional visualizations of collagen hydrogels (middle, right panels) were acquired from simulations of 30% applied displacement at full depression during dynamic equilibrium. Note that applied strains are engineering strains, while the strains presented in the figure are Green-Lagrange strains.

Fig. 3. Representative images of nonloaded microvascular networks and networks formed under early versus delayed 30% strain loading.

(A) At 30% strain, early compression and early indentation groups exhibit only very early stage sprouts (white arrows), whereas delayed indentation appears qualitatively more densely vascularized than the nonloaded or delayed compression groups. Maximum intensity z projections (200-μm depth) of samples stained with GS-1 lectin at day 10 of culture. Scale bars, 500 μm. (B) Microvascular fragments retained perivascular coverage under both early and delayed 30% indentation. White arrows denote tips of fragments, which exhibit sprouting endothelial filopodia under early nonloaded, delayed nonloaded, and delayed 30% strain conditions. Early 30% strain leads to primarily rounded, nonsprouting ends of fragments. Representative maximum intensity z projections (25-μm depth) of DAPI (blue; nuclei)–, αSMA (green; perivascular smooth muscle cells)–, and isolectin B4 (red; endothelial cells)–stained microvascular fragments at days 3 (early) and 7 (delayed). Scale bars, 100 μm.

Fig. 4. Effect of early versus delayed 30% strain loading on cell proliferation within microvascular networks.

Delayed loading increased the number of proliferating cells, and a significant interaction effect suggests that early loading decreased cell proliferation. (A) Image-based quantification of proliferation. Two-way ANOVA; ^^^, overall effect of time; P < 0.001; Bonferroni post hoc effect of loading, **P < 0.01. Significant interaction effect, P < 0.05. n = 3 gels per group per time point. (B) Representative maximum intensity z projections (25-μm depth) of DAPI (blue; all cells)– and EdU (red; proliferating cells)–stained microvascular fragments at days 3 (early) and 7 (delayed). Scale bars, 250 μm. (C) Representative maximum intensity z projections (5-μm depth) of microvascular fragments at day 7 of culture in either nonloaded or delayed 30% indentation conditions stained with DAPI (blue; nuclei, all cells), EdU (gray; nuclei, proliferating cells), isolectin B4 (red; endothelial cells), and αSMA⁺ (green; perivascular cells). EdU⁺ nuclei predominantly colocalize with αSMA⁺ perivascular cells. Scale bars, 100 μm.

Fig. 5. Effect of early versus delayed 30% strain loading on gene expression.

Gene expression array data were analyzed with PLSDA to reduce their dimensionality to an LV, which is composed of a weighted average of each individual gene. The gene expression profiles of loaded versus nonloaded microvasculature, which are represented by LV1, were significantly different for both early (A) and delayed (B) 30% strain loading. Plots of early loading LV1 (C) and delayed loading LV1 (D) demonstrate the weighted average relative contribution of each individual gene to the LV1. In both cases, genes with more positive values are more highly expressed by loaded microvascular networks, and genes with more negative values are more highly expressed by nonloaded microvascular networks. Individual genes are color-coded by angiogenic processes (e.g., sprout tip cell selection) they are known to be involved in. (E) When interleaved, the loading plots of early loading LV1 versus delayed loading LV1 reveal differential regulation of a number of genes. Genes strongly down-regulated by early loading (negative values in black bars) are often instead up-regulated by delayed loading (positive values in red bars), such as Mmp14, Timp3, and Cxcr4. n = 6 gels per group. Error bars represent mean ± SD of Monte Carlo subsampling without replacement.

Fig. 6. Expression of YAP/TAZ target genes Ctgf and Cyr61 due to 30% strain loading and to YAP/TAZ inhibition.

Early 30% indentation loading induced significant up-regulation of Ctgf, and delayed 30% indentation loading induced significant up-regulation of both Ctgf and Cyr61. YAP inhibitor, VP (5 μM), abrogated the delayed loading-induced up-regulation of both target genes. Expression is shown relative to mean expression of housekeeping genes. Two-way ANOVA, overall effect of loading, ^##P < 0.01; Bonferroni post hoc, *P < 0.05, **P < 0.01, and ***P < 0.001. Delayed Ctgf demonstrated significant interaction effect. n = 5 to 6 per group.