Combinatorial screening of 3D biomaterial properties that promote myofibrogenesis for mesenchymal stromal cell-based heart valve tissue engineering

Abstract

The physical and chemical properties of a biomaterial integrate with soluble cues in the cell microenvironment to direct cell fate and function. Predictable biomaterial-based control of integrated cell responses has been investigated with two-dimensional (2D) screening platforms, but integrated responses in 3D have largely not been explored systematically. To address this need, we developed a screening platform using polyethylene glycol norbornene (PEG-NB) as a model biomaterial with which the polymer wt% (to control elastic modulus) and adhesion peptide types (RGD, DGEA, YIGSR) and densities could be controlled independently and combinatorially in arrays of 3D hydrogels. We applied this platform and regression modeling to identify combinations of biomaterial and soluble biochemical (TGF-β1) factors that best promoted myofibrogenesis of human mesenchymal stromal cells (hMSCs) in order to inform our understanding of regenerative processes for heart valve tissue engineering. In contrast to 2D culture, our screens revealed that soft hydrogels (low PEG-NB wt%) best promoted spread myofibroblastic cells that expressed high levels of α-smooth muscle actin (α-SMA) and collagen type I. High concentrations of RGD enhanced α-SMA expression in the presence of TGF-β1 and cell spreading regardless of whether TGF-β1 was in the culture medium. Strikingly, combinations of peptides that maximized collagen expression depended on the presence or absence of TGF-β1, indicating that biomaterial properties can modulate MSC response to soluble signals. This combination of a 3D biomaterial array screening platform with statistical modeling is broadly applicable to systematically identify combinations of biomaterial and microenvironmental conditions that optimally guide cell responses.