Quantitative and multiplexed chemical-genetic phenotyping in mammalian cells with QMAP-Seq

Sonia Brockway, Geng Wang, Jasen M. Jackson, David R. Amici, Seesha R. Takagishi, Matthew R. Clutter, Elizabeth T. Bartom and Marc L. Mendillo ()
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Sonia Brockway: Northwestern University Feinberg School of Medicine
Geng Wang: Northwestern University Feinberg School of Medicine
Jasen M. Jackson: Northwestern University Feinberg School of Medicine
David R. Amici: Northwestern University Feinberg School of Medicine
Seesha R. Takagishi: Northwestern University Feinberg School of Medicine
Matthew R. Clutter: Northwestern University Feinberg School of Medicine
Elizabeth T. Bartom: Northwestern University Feinberg School of Medicine
Marc L. Mendillo: Northwestern University Feinberg School of Medicine

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract Chemical-genetic interaction profiling in model organisms has proven powerful in providing insights into compound mechanism of action and gene function. However, identifying chemical-genetic interactions in mammalian systems has been limited to low-throughput or computational methods. Here, we develop Quantitative and Multiplexed Analysis of Phenotype by Sequencing (QMAP-Seq), which leverages next-generation sequencing for pooled high-throughput chemical-genetic profiling. We apply QMAP-Seq to investigate how cellular stress response factors affect therapeutic response in cancer. Using minimal automation, we treat pools of 60 cell types—comprising 12 genetic perturbations in five cell lines—with 1440 compound-dose combinations, generating 86,400 chemical-genetic measurements. QMAP-Seq produces precise and accurate quantitative measures of acute drug response comparable to gold standard assays, but with increased throughput at lower cost. Moreover, QMAP-Seq reveals clinically actionable drug vulnerabilities and functional relationships involving these stress response factors, many of which are activated in cancer. Thus, QMAP-Seq provides a broadly accessible and scalable strategy for chemical-genetic profiling in mammalian cells.

Date: 2020
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DOI: 10.1038/s41467-020-19553-8

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