人类多能干细胞衍生的心肌细胞(hPSC-CM)正在推进心血管发育和疾病建模,药物测试,和再生疗法。然而,hPSC-CM的产生受到分化过程中的显著可变性的阻碍。建立早期质量标记以监测谱系进展和预测终末分化结果将解决hPSC-CM生产中的这种稳健性和可重复性障碍。整合的转录组和表观基因组分析评估心脏祖细胞(CPC)的属性如何影响CM分化结果。结果分析确定了产生高纯度CM批次的CPC的预测性标志物,包括TTN,TRIM55,DGKI,MEF2C,MAB21L2、MYL7、LDB3、SLC7A11、MAB21L2和CALD1。从这些基因开发的预测模型在确定CPC阶段的最终CM纯度方面提供了高准确性。Further,阐明了对批次失败机制和在失败批次中产生的主要非CM细胞类型的见解。即EMT,MAPK,和WNT信号成为批次差异的重要驱动因素,产生成纤维细胞/壁细胞的脱靶群体,骨骼肌细胞,心外膜细胞,和非CPCSLC7A11亚群。这项研究证明了祖细胞的综合多组分析如何识别祖细胞的质量属性并预测分化结果。从而改进了区分方案并增加了过程的鲁棒性。
Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are advancing cardiovascular development and disease modeling, drug testing, and regenerative therapies. However, hPSC-CM production is hindered by significant variability in the differentiation process. Establishment of early quality markers to monitor lineage progression and predict terminal differentiation outcomes would address this robustness and reproducibility roadblock in hPSC-CM production. An integrated transcriptomic and epigenomic analysis assesses how attributes of the cardiac progenitor cell (CPC) affect CM differentiation outcome. Resulting analysis identifies predictive markers of CPCs that give rise to high purity CM batches, including TTN, TRIM55, DGKI, MEF2C, MAB21L2, MYL7, LDB3, SLC7A11, MAB21L2, and CALD1. Predictive models developed from these genes provide high accuracy in determining terminal CM purities at the CPC stage. Further, insights into mechanisms of batch failure and dominant non-CM cell types generated in failed batches are elucidated. Namely EMT, MAPK, and WNT signaling emerge as significant drivers of batch divergence, giving rise to off-target populations of fibroblasts/mural cells, skeletal myocytes, epicardial cells, and a non-CPC SLC7A11+ subpopulation. This study demonstrates how integrated multi-omic analysis of progenitor cells can identify quality attributes of that progenitor and predict differentiation outcomes, thereby improving differentiation protocols and increasing process robustness.