Abstract
Human induced pluripotent stem cells (iPSCs) have the potential to repair/regenerate smooth muscle cells (SMCs) in different organs. However, there are many challenges in their translation to clinical therapies. In this study, we describe our observations of in vitro SMC differentiation in three iPSC lines derived from human fibroblasts using retroviral, episomal, and mRNA/miRNA reprogramming methods. We sought to elucidate correlations between differentiation characteristics and efficiencies that can facilitate large-scale production of differentiated cells for clinical applications, and to report differences in pluripotency marker expression in differentiated cells from different iPSC lines. A standardized SMC differentiation protocol was used to induce the CD31+/CD34+ vascular progenitor cell phenotype. These were sorted by magnetic-activated (MACS) and fluorescence-activated cell sorting (FACS), and then treated with PDGF-BB and smooth muscle growth medium for further differentiation into smooth muscle progenitor cells (pSMCs). The expression of SMC and pluripotency markers in early- and late-passage (P1 and P4) pSMCs was analyzed. A total of 36 differentiation runs was performed on the three patient iPSC lines. All pSMC populations expressed SMC markers and Ki67 consistent with the progenitor phenotype. Initial iPSC density correlated positively with the sorted cell FACS efficiency, and this correlation could be fit to a quadratic equation. We also observed that a specific "honeycomb" pattern of the starting cultured iPSCs cultured correlated with higher efficiency in all three iPSC lines. Pluripotency marker expression decreased significantly to nearly undetectable levels in all three lines. There was no significant change in SMC and pluripotent marker expression between passage 1 and 4. In summary, our observations suggest that the method of iPSC reprogramming does not affect iPSC differentiation into pSMCs. Protocol efficiency can be modeled mathematically and coupled with the initial "honeycomb" cell pattern to optimize production of large cell numbers for clinical therapies.
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