A Multi-well Combinatorial Hydrogel Array For High-throughput Analysis of Cell-ECM Interactions

Biophysical cues in the extracellular matrix (ECM) regulate cell behavior in a complex, non-linear, and interdependent manner. To quantify these important regulatory relationships and gain a comprehensive understanding of mechanotransduction, there is a need for high-throughput matrix platforms that...

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Published inACS biomaterials science & engineering Vol. 7; no. 6; pp. 2453 - 2465
Main Authors Lei, Ruoxing, Akins, Erin A., Wong, Kelly C. Y., Repina, Nicole A., Wolf, Kayla J., Dempsey, Garrett E., Schaffer, David V., Stahl, Andreas, Kumar, Sanjay
Format Journal Article
LanguageEnglish
Published 24.05.2021
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Summary:Biophysical cues in the extracellular matrix (ECM) regulate cell behavior in a complex, non-linear, and interdependent manner. To quantify these important regulatory relationships and gain a comprehensive understanding of mechanotransduction, there is a need for high-throughput matrix platforms that enable parallel culture and analysis of cells in various matrix conditions. Here we describe a multi-well hyaluronic acid (HA) platform in which cells are cultured on combinatorial arrays of hydrogels spanning a range of elasticities and adhesivities. Our strategy utilizes orthogonal photopatterning of stiffness and adhesivity gradients, with the stiffness gradient implemented by a programmable light illumination system. The resulting platform allows individual treatment and analysis of each matrix environment while eliminating contributions of haptotaxis and durotaxis. In human mesenchymal stem cells (hMSCs), our platform recapitulates expected relationships between matrix stiffness, adhesivity and cell mechanosensing. We further applied the platform to show that as integrin ligand density falls, cell adhesion and migration depend more strongly on CD44-mediated interactions with the HA backbone. We anticipate that our system could bear great value for mechanistic discovery and screening where matrix mechanics and adhesivity are expected to influence phenotype.
ISSN:2373-9878
DOI:10.1021/acsbiomaterials.1c00065