Human pluripotent stem cells (hPSCs) are uniquely dependent on aerobic glycolysis to generate ATP. However, the importance of oxidative phosphorylation (OXPHOS) has not been elucidated. Detailed amino acid profiling has revealed that glutamine is indispensable for the survival of hPSCs. Under glucose- and glutamine-depleted conditions, hPSCs quickly died due to the loss of ATP. Metabolome analyses showed that hPSCs oxidized pyruvate poorly and that glutamine was the main energy source for OXPHOS. hPSCs were unable to utilize pyruvate-derived citrate due to negligible expression of aconitase 2 (ACO2) and isocitrate dehydrogenase 2/3 (IDH2/3) and high expression of ATP-citrate lyase. Cardiomyocytes with mature mitochondria were not able to survive without glucose and glutamine, although they were able to use lactate to synthesize pyruvate and glutamate. This distinguishing feature of hPSC metabolism allows preparation of clinical-grade cell sources free of undifferentiated hPSCs, which prevents tumor formation during stem cell therapy.

SummaryCardiac regenerative therapies utilizing human induced pluripotent stem cells (hiPSCs) are hampered by ineffective large-scale culture. hiPSCs were cultured in multilayer culture plates (CPs) with active gas ventilation (AGV), resulting in stable proliferation and pluripotency. Seeding of 1 × 106 hiPSCs per layer yielded 7.2 × 108 hiPSCs in 4-layer CPs and 1.7 × 109 hiPSCs in 10-layer CPs with pluripotency. hiPSCs were sequentially differentiated into cardiomyocytes (CMs) in a two-dimensional (2D) differentiation protocol. The efficiency of cardiac differentiation using 10-layer CPs with AGV was 66%–87%. Approximately 6.2–7.0 × 108 cells (4-layer) and 1.5–2.8 × 109 cells (10-layer) were obtained with AGV. After metabolic purification with glucose- and glutamine-depleted and lactate-supplemented media, a massive amount of purified CMs was prepared. Here, we present a scalable 2D culture system using multilayer CPs with AGV for hiPSC-derived CMs, which will facilitate clinical applications for severe heart failure in the near future.

SummaryDeep learning technology is rapidly advancing and is now used to solve complex problems. Here, we used deep learning in convolutional neural networks to establish an automated method to identify endothelial cells derived from induced pluripotent stem cells (iPSCs), without the need for immunostaining or lineage tracing. Networks were trained to predict whether phase-contrast images contain endothelial cells based on morphology only. Predictions were validated by comparison to immunofluorescence staining for CD31, a marker of endothelial cells. Method parameters were then automatically and iteratively optimized to increase prediction accuracy. We found that prediction accuracy was correlated with network depth and pixel size of images to be analyzed. Finally, K-fold cross-validation confirmed that optimized convolutional neural networks can identify endothelial cells with high performance, based only on morphology.

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Summary The role of lipid metabolism in human pluripotent stem cells (hPSCs) is poorly understood. We have used large-scale targeted proteomics to demonstrate that undifferentiated hPSCs express different fatty acid (FA) biosynthesis-related enzymes, including ATP citrate lyase and FA synthase (FASN), than those expressed in hPSC-derived cardiomyocytes (hPSC-CMs). Detailed lipid profiling revealed that inhibition of FASN resulted in significant reduction of sphingolipids and phosphatidylcholine (PC); moreover, we found that PC was the key metabolite for cell survival in hPSCs. Inhibition of FASN induced cell death in undifferentiated hPSCs via mitochondria-mediated apoptosis; however, it did not affect cell survival in hPSC-CMs, neurons, or hepatocytes as there was no significant reduction of PC. Furthermore, we did not observe tumor formation following transplantation of FASN inhibitor-treated cells. Our findings demonstrate the importance of de novo FA synthesis in the survival of undifferentiated hPSCs and suggest applications for FASN inhibition in regenerative medicine.