Computational profiling of hiPSC-derived heart organoids reveals chamber defects associated with NKX2-5 deficiency.
Computational profiling of hiPSC-derived heart organoids reveals chamber defects associated with NKX2-5 deficiency.
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hiPSC 衍生的心脏类器官的计算分析揭示了与 NKX2-5 缺陷相关的心室缺陷。
DOI：
10.1038/s42003-022-03346-4
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发表时间：
2022-04-29
影响因子：
5.9
通讯作者：
Li G
中科院分区：
文献类型：
--
作者：
Feng W;Schriever H;Jiang S;Bais A;Wu H;Kostka D;Li G
心脏类器官具有产生初级心脏样解剖结构的潜力，作为心脏疾病的体外模型具有很大的前景。然而，它们的性质尚未得到充分的研究，这阻碍了它们的广泛应用。在这里，我们报告了心室和心房心脏类器官分化系统的发展，使心脏疾病与房室缺陷的研究成为可能。我们展示了我们的系统产生了由主要心脏细胞类型组成的室特异性类器官，我们使用单细胞RNA测序和样品多路复用来表征我们产生的细胞。为此，我们开发了一种机器学习标签转移方法，利用可用于原代人类胎儿心脏细胞的细胞类型、腔室和侧边性注释。然后，我们使用该模型分析了NKX2-5中携带Ebstein异常相关遗传变异的等基因系的类器官细胞，并成功再现了该疾病的房源性心室缺陷。总之，我们已经建立了一个整合心脏类器官和计算分析的工作流程来模拟正常和疾病状态下的心脏发育。人类心脏类器官系统，结合单细胞RNA测序和机器学习转录表型，被开发。这使得研究与Ebstein异常（一种伴有腔室缺陷的先天性心脏病）相关的基因变异成为可能。
Heart organoids have the potential to generate primary heart-like anatomical structures and hold great promise as in vitro models for cardiac disease. However, their properties have not yet been fully studied, which hinders their wide spread application. Here we report the development of differentiation systems for ventricular and atrial heart organoids, enabling the study of heart diseases with chamber defects. We show that our systems generate chamber-specific organoids comprising of the major cardiac cell types, and we use single cell RNA sequencing together with sample multiplexing to characterize the cells we generate. To that end, we developed a machine learning label transfer approach leveraging cell type, chamber, and laterality annotations available for primary human fetal heart cells. We then used this model to analyze organoid cells from an isogeneic line carrying an Ebstein’s anomaly associated genetic variant in NKX2-5, and we successfully recapitulated the disease’s atrialized ventricular defects. In summary, we have established a workflow integrating heart organoids and computational analysis to model heart development in normal and disease states. A human cardiac organoid system, coupled with single cell RNA sequencing and machine learning for transcriptional phenotyping, was developed. This allowed investigation of a genetic variant associated with Ebstein’s Anomaly, a congenital heart disease with chamber defects.
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影响因子：
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作者：
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通讯作者：
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影响因子：
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通讯作者：
Elliott DA
影响因子：
16.6
作者：
Chen Q;Zhang H;Liu Y;Adams S;Eilken H;Stehling M;Corada M;Dejana E;Zhou B;Adams RH
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