Cell states beyond transcriptomics: Integrating structural organization and gene expression in hiPSC-derived cardiomyocytes
Cell states beyond transcriptomics: Integrating structural organization and gene expression in hiPSC-derived cardiomyocytes
复制标题
DOI：
10.1016/j.cels.2021.05.001
复制
发表时间：
2021-06-16
期刊：
影响因子：
9.3
通讯作者：
Gunawardane, Ruwanthi N.
中科院分区：
文献类型：
--
作者：
Gerbin, Kaytlyn A.;Grancharova, Tanya;Gunawardane, Ruwanthi N.
虽然一些细胞类型可以通过解剖学或生理功能来定义，但细胞状态的严格定义仍然难以捉摸。在这里，我们开发了一个定量的，基于成像的平台，用于单细胞亚细胞组织的系统和自动分类。我们使用这个平台来量化超过30，000个人诱导多能干细胞衍生的心肌细胞中的亚细胞组织和基因表达，产生了一个公开可用的数据集，描述了局部和全局肌节组织的群体分布，mRNA丰度以及这些特征之间的相关性。虽然一些表型重要基因的mRNA丰度与亚细胞组织相关（例如，β-肌球蛋白重链，MYH 7），这两种细胞度量是异质的并且通常不相关，这表明单独的基因表达不足以对细胞状态进行分类。相反，我们认为细胞状态应该通过观察单个细胞中定量的多维特征的完整分布来定义，这些特征也可以解释空间，时间和功能。
Although some cell types may be defined anatomically or by physiological function, a rigorous definition of cell state remains elusive. Here, we develop a quantitative, imaging-based platform for the systematic and automated classification of subcellular organization in single cells. We use this platform to quantify subcellular organization and gene expression in >30,000 individual human induced pluripotent stem cell-derived cardiomyocytes, producing a publicly available dataset that describes the population distributions of local and global sarcomere organization, mRNA abundance, and correlations between these traits. While the mRNA abundance of some phenotypically important genes correlates with subcellular organization (e.g., the beta-myosin heavy chain, MYH7), these two cellular metrics are heterogeneous and often uncorrelated, which suggests that gene expression alone is not sufficient to classify cell states. Instead, we posit that cell state should be defined by observing full distributions of quantitative, multidimensional traits in single cells that also account for space, time, and function.