Nutrient Microenvironments Reprogram Pigment Epithelium Metabolism and Phenotype
Rayne R. LimiD, Emily Zhao, Daniel T. HassiD, Yekai Wang, Mark EminhizeriD, Davide OrtolaniD, Sheldon Niernberger, Aspen Tong, Bree R Nelson, Marcos Nazario, Vishya Adipudi, Kapil BhartiiD, James B. HurleyiD, Jianhai DuiD, Jennifer R. ChaoiD
Abstract
Induced pluripotent stem cell-derived retinal pigment epithelium (iPSC RPE) has become a widely used model for studying the mechanisms of age-related macular degeneration (AMD). However, the nutrient composition of currently used RPE culture media is highly variable, posing a major challenge to reproducibility in RPE metabolism and phenotype. We systematically investigate how six distinct nutrient microenvironments shape RPE phenotype, function and metabolism in both iPSC RPE and fetal RPE (fRPE). These included MEM, DMEM-HG/F12 basal media, physiological human plasma-like medium (HPLM) supplemented with FBS or B27, and X-VIVO 10. Although canonical RPE markers were expressed across all conditions, B27 supplementation and X-VIVO 10 increased RPE cell size, hexagonality, and transepithelial resistance. Culture in HPLM+FBS induced accumulation of lipid droplets and sub-RPE deposits, whereas X-VIVO 10 resulted in the formation of large intracellular vacuoles. B27 supplementation enhanced basal respiration, while X-VIVO 10 increased glycolytic capacity. Amino acid consumption was broadly conserved across media types, including complete depletion of proline in all conditions by 48 hours; however, lipid and nucleotide metabolism varied substantially between conditions. Notably, B27 supplementation in specific media types reversed the net direction of several metabolites, with creatine, serine and taurine shifting from consumption to production, while riboflavin and guanine shifted from production to consumption. These findings establish the nutrient environment as a key determinant of RPE phenotype, function and metabolism. Our work provides a valuable resource for media selection and interpretation of cellular and metabolic phenotypes relevant to RPE disease modeling.
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