Automatic Analysis of Dividing Cells in Live Cell Movies to Detect Mitotic Delays and Correlate Phenotypes in Time

Overview

Journal Genome Res

Specialty Genetics

Date 2009 Oct 3

PMID 19797680

Citations 30

Authors

Nathalie Harder

Felipe Mora-Bermudez

William J Godinez

Annelie Wunsche

Roland Eils

Jan Ellenberg

Karl Rohr

Affiliations

Soon will be listed here.

Abstract

Live-cell imaging allows detailed dynamic cellular phenotyping for cell biology and, in combination with small molecule or drug libraries, for high-content screening. Fully automated analysis of live cell movies has been hampered by the lack of computational approaches that allow tracking and recognition of individual cell fates over time in a precise manner. Here, we present a fully automated approach to analyze time-lapse movies of dividing cells. Our method dynamically categorizes cells into seven phases of the cell cycle and five aberrant morphological phenotypes over time. It reliably tracks cells and their progeny and can thus measure the length of mitotic phases and detect cause and effect if mitosis goes awry. We applied our computational scheme to annotate mitotic phenotypes induced by RNAi gene knockdown of CKAP5 (also known as ch-TOG) or by treatment with the drug nocodazole. Our approach can be readily applied to comparable assays aiming at uncovering the dynamic cause of cell division phenotypes.

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