Characterizing heterogeneous cellular responses to perturbations
Characterizing heterogeneous cellular responses to perturbations
复制标题
DOI：
10.1073/pnas.0807038105
复制
发表时间：
2008-12-09
影响因子：
11.1
通讯作者：
Altschuler, Steven J.
中科院分区：
文献类型：
--
作者：
Slacka, Michael D.;Martineza, Elisabeth D.;Altschuler, Steven J.
已经广泛观察到细胞群体对扰动的反应是不均匀的。然而，解释观察到的异质性是一个极具挑战性的问题，因为可能的细胞表型的复杂性，潜在的扰动的大尺寸，以及缺乏从噪声中分离有意义的生物信息的方法。在这里，我们开发了一种基于图像的方法来表征细胞表型的基础上的信号标记物共定位的模式。异质性细胞群体的特点是表型不同的亚群的混合物，并简要概括为这些混合物的概率再分布的扰动的反应。我们应用我们的方法来表征癌细胞对一组药物的异质性反应。我们发现，用（不）相似机制的药物处理的细胞表现出（不）相似的异质性模式。尽管在我们的数据中观察到细胞的表型多样性，但低复杂性的异质性模型足以区分大多数药物机制。我们的方法提供了一个计算框架，用于评估细胞异质性的复杂性，调查扰动诱导重新分配的程度有限，但不平凡的，剧目的基础状态和揭示功能的异质性反应的不同模式内包含的意义。
Cellular populations have been widely observed to respond heterogeneously to perturbation. However, interpreting the observed heterogeneity is an extremely challenging problem because of the complexity of possible cellular phenotypes, the large dimension of potential perturbations, and the lack of methods for separating meaningful biological information from noise. Here, we develop an image-based approach to characterize cellular phenotypes based on patterns of signaling marker colocalization. Heterogeneous cellular populations are characterized as mixtures of phenotypically distinct subpopulations, and responses to perturbations are summarized succinctly as probabilistic redistributions of these mixtures. We apply our method to characterize the heterogeneous responses of cancer cells to a panel of drugs. We find that cells treated with drugs of (dis-) similar mechanism exhibit (dis-) similar patterns of heterogeneity. Despite the observed phenotypic diversity of cells observed within our data, low-complexity models of heterogeneity were sufficient to distinguish most classes of drug mechanism. Our approach offers a computational framework for assessing the complexity of cellular heterogeneity, investigating the degree to which perturbations induce redistributions of a limited, but nontrivial, repertoire of underlying states and revealing functional significance contained within distinct patterns of heterogeneous responses.