Abstract
BackgroundThe combination of time-lapse imaging of live cells with high-throughput perturbation assays is a powerful tool for genetics and cell biology. The Mitocheck project employed this technique to associate thousands of genes with transient biological phenotypes in cell division, cell death and migration. The original analysis of these data proceeded by assigning nuclear morphologies to cells at each time-point using automated image classification, followed by description of population frequencies and temporal distribution of cellular states through event-order maps. One of the choices made by that analysis was not to rely on temporal tracking of the individual cells, due to the relatively low image sampling frequency, and to focus on effects that could be discerned from population-level behaviour.ResultsHere, we present a variation of this approach that employs explicit modelling by dynamic differential equations of the cellular state populations. Model fitting to the time course data allowed reliable estimation of the penetrance and time of appearance of four types of disruption of the cell cycle: quiescence, mitotic arrest, polynucleation and cell death. Model parameters yielded estimates of the duration of the interphase and mitosis phases. We identified 2190 siRNAs that induced a disruption of the cell cycle at reproducible times, or increased the durations of the interphase or mitosis phases.ConclusionsWe quantified the dynamic effects of the siRNAs and compiled them as a resource that can be used to characterize the role of their target genes in cell death, mitosis and cell cycle regulation. The described population-based modelling method might be applicable to other large-scale cell-based assays with temporal readout when only population-level measures are available.
Highlights
The combination of time-lapse imaging of live cells with high-throughput perturbation assays is a powerful tool for genetics and cell biology
Four controls were repeatedly used on each slide: siScrambled, a non-targeting negative control; siKIF11, targeting the gene KIF11, which encodes a kinesin needed for centrosome segregation; siCOPB1, targeting an essential protein binding to the Golgi vesicle and siINCENP, targeting a centromere-associated protein coding gene required for proper chromosome segregation and cytokinesis
In order to quantify the phenotypic effect induced by small interfering RNA (siRNA) treatments, we grouped the 16 nuclear morphologies into four cellular states recapitulating the cell cycle: interphase, mitotic, polynucleated and dead
Summary
The combination of time-lapse imaging of live cells with high-throughput perturbation assays is a powerful tool for genetics and cell biology. The Mitocheck project employed this technique to associate thousands of genes with transient biological phenotypes in cell division, cell death and migration. The Mitocheck project performed a time-lapse imaging assay that employed siRNAs to test the implication of human genes in transient biological processes such as cell division or migration genome-wide [8]. In this experiment, HeLa cells stably expressing core histone 2B tagged with green fluorescent protein (GFP) were seeded on siRNA-spotted slides, incubated for 18 h and imaged with automated fluorescence microscopy for 48 h. Further validation experiments were done using independent siRNAs (“validation screen”) and rescue of 16 gene products using orthologous mouse genes
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