美国博德研究所Anne E. Carpenter团队绘制出用匹配的化学和遗传扰动处理细胞的三百万张图像和形态图谱。该研究于2024年4月9日在线发表于国际一流学术期刊《自然—方法学》。

研究人员创建了一个资源数据集CPJUMP1，其中每个受扰动基因的产物都是数据集中至少两种化合物的已知靶标。研究人员系统地探索了以特定基因编码的相同蛋白质为靶标的扰动之间的相关性，并发现识别化学扰动和遗传扰动之间的匹配是一项具有挑战性的任务。

这些数据集和基线分析为评估测量扰动相似性和影响的方法提供了基准，更广泛地说，为从显微镜图像中学习细胞状态的有效表征提供了基准。这种进步将加速基于图像的细胞状态分析的应用，如揭示药物作用模式或探测功能基因组学。

研究人员表示，识别对细胞形态具有相似影响的遗传和化学扰动，可以阐明化合物的作用机制或遗传途径的新型调节因子。由于缺乏经过精心设计和完善注释的化学和遗传扰动处理细胞图像集，有关识别此类相似性方法的研究一直滞后。

附：英文原文

Title: Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

Author: Chandrasekaran, Srinivas Niranj, Cimini, Beth A., Goodale, Amy, Miller, Lisa, Kost-Alimova, Maria, Jamali, Nasim, Doench, John G., Fritchman, Briana, Skepner, Adam, Melanson, Michelle, Kalinin, Alexandr A., Arevalo, John, Haghighi, Marzieh, Caicedo, Juan C., Kuhn, Daniel, Hernandez, Desiree, Berstler, James, Shafqat-Abbasi, Hamdah, Root, David E., Swalley, Susanne E., Garg, Sakshi, Singh, Shantanu, Carpenter, Anne E.

Issue&Volume: 2024-04-09

Abstract: The identification of genetic and chemical perturbations with similar impacts on cell morphology can elucidate compounds’ mechanisms of action or novel regulators of genetic pathways. Research on methods for identifying such similarities has lagged due to a lack of carefully designed and well-annotated image sets of cells treated with chemical and genetic perturbations. Here we create such a Resource dataset, CPJUMP1, in which each perturbed gene’s product is a known target of at least two chemical compounds in the dataset. We systematically explore the directionality of correlations among perturbations that target the same protein encoded by a given gene, and we find that identifying matches between chemical and genetic perturbations is a challenging task. Our dataset and baseline analyses provide a benchmark for evaluating methods that measure perturbation similarities and impact, and more generally, learn effective representations of cellular state from microscopy images. Such advancements would accelerate the applications of image-based profiling of cellular states, such as uncovering drug mode of action or probing functional genomics.

DOI: 10.1038/s41592-024-02241-6

Source: https://www.nature.com/articles/s41592-024-02241-6