Human Plasma-Like Medium Promotes Maturation of Human Pluripotent Stem Cell-Derived Cardiomyocytes
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Maturing human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) in vitro is critical for advancing drug discovery and cardiotoxicity screening applications of these cells. However, the metabolic compositions of basal media used for hPSC-CM culture typically offer limited relevance to human cardiac physiology. Here, we examined how culture in Human Plasma-Like Medium (HPLM) versus conventional basal media affects the behavior of hPSC-CMs. Starting with Day 16 hPSC-CMs, we cultured cells for two weeks in either HPLM or RPMI-based media and then assessed maturation outcomes at Day 30. Compared to RPMI/B27 media containing either RPMI-defined (11.1 mM) or physiologic glucose levels (5 mM), HPLM/B27 markedly enhanced hPSC-CM maturity as evinced by concerted transcriptomic, structural, functional, and metabolic phenotypes. These effects included a higher extent of myosin heavy chain isoform switching (α-MHC to β-MHC), accelerated ventricular-specific myosin light chain isoform switching (MLC2a to MLC2v), elongated sarcomeres, increased multinucleation, enhanced calcium transient kinetics, and coordinated activation of oxidative and glycolytic metabolism. Collectively, these findings demonstrate that medium composition has substantial effects on hPSC-CM biology and also establish HPLM as a tool for driving hPSC-CM maturation in vitro .
Translational Impact Statement
HPLM was designed to more closely recapitulate the metabolic composition of human plasma and thus provides a physiological platform to promote hPSC-CM maturation. By enhancing structural, functional, and metabolic maturity, HPLM-cultured hPSC-CMs better approximate cardiac physiology, positioning them as improved models for cardiovascular disease research, drug-induced cardiotoxicity screening, and personalized therapeutic testing. This medium can integrate with existing maturation strategies, accelerating the translation of basic cardiac research into clinically predictive tools for the drug development pipeline.