分类
单元格排序
表型
有丝分裂
计算生物学
生物
细胞
图像(数学)
计算机视觉
人工智能
细胞生物学
计算机科学
遗传学
基因
程序设计语言
作者
Daniel Schraivogel,Terra M. Kuhn,Benedikt Rauscher,Marta Rodríguez‐Martínez,Malte Paulsen,Keegan Owsley,Aaron Middlebrook,Christian Tischer,Beáta Ramasz,Diana Ordoñez‐Rueda,Martina Dees,Sara Cuylen‐Haering,Eric D. Diebold,Lars M. Steinmetz
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2022-01-20
卷期号:375 (6578): 315-320
被引量:175
标识
DOI:10.1126/science.abj3013
摘要
Fast and selective isolation of single cells with unique spatial and morphological traits remains a technical challenge. Here, we address this by establishing high-speed image-enabled cell sorting (ICS), which records multicolor fluorescence images and sorts cells based on measurements from image data at speeds up to 15,000 events per second. We show that ICS quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. We combine ICS with CRISPR-pooled screens to identify regulators of the nuclear factor κB (NF-κB) pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. By assessing complex cellular phenotypes, ICS substantially expands the phenotypic space accessible to cell-sorting applications and pooled genetic screening.
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