Chirality-induced Lineage Enforcement of Mechanosensitive Mesenchymal Stem Cells Across Germ Layer Boundaries

Abstract

Mesenchymal to epithelial transition (MET) is instrumental in embryogenesis, tissue repair, and wound healing while the epithelial to mesenchymal transition (EMT) plays role in carcinogenesis. Alteration in microenvironment can modulate cellular signaling and induce EMT and MET. However, modulation of microenvironment to induce MET has been relatively less explored. In this work, effect of matrix stiffness in mediating MET in umbilical cord-derived mesenchymal stem cells (UCMSC) is investigated. Differential segregation of cell fate determinant proteins is one of the key factors in mediating altered stem cell fates through MET even though the genesis of apicobasal polarity remains ambiguous. Herein, it is also attempted to decipher if microenvironment-induced asymmetric cell division has a role to play in driving the cells toward MET. UCMSC cultured on stiffer PDMS matrices resulted in significantly (p < 0.05) higher expression of mechanotransduction proteins. It was also observed that stiffer matrices mediated significant (p < 0.05) upregulation of the polarity proteins and cell fate determinant protein, and epithelial marker proteins over lesser stiff substrates. On the contrary, expression of inflammatory and mesenchymal markers was reduced significantly (p < 0.05) on the stiffer matrices. Cell cycle analysis showed a significant increase in the G1 phase among the cells seeded on stiffer matrices. Transcriptomic studies validated higher expression of epithelial markers genes and lower expression of EMT markers. The transition from mesenchymal to epithelial phenotype depending on the gradation in matrix stiffness is successfully demonstrated. A computational machine learning model was developed to validate stiffness-MET correlation with 94% accuracy. The cross-boundary trans-lineage differentiation capability of MSC on bioengineered substrates can be used as a potential tool in tissue regeneration, organogenesis, and wound healing applications. In our present study, we deciphered the correlation between YAP/TAZ mechanotransduction pathway, EMT signaling pathway, and asymmetric cell division in mediating MET in MSC in a substrate stiffness-dependent manner. It is inferred that the stiffer PDMS matrices facilitate the transition from mesenchymal to epithelial state of MSC. Further, our study also proposed a scoring system to sort MSC from an intermediate hybrid E/M population while undergoing graded MET on matrices of different stiffnesses using a machine learning technique. This proposed scoring system can provide information regarding the E/M state of MSC on different bioengineered constructs based on their biophysical properties which may help in the proper choice of biomaterials in complex tissue-engineering applications.

Keywords: Asymmetric cell division; Machine learning; Mechanotransduction proteins; Mesenchymal stem cells; Mesenchymal to epithelial transition; Polarity proteins.