The protein homeostasis (proteostasis) network, a critical cytoprotective system that restores homeostasis in response to molecular stress, comprises distinct pathways, including the heat-shock response, unfolded protein response, oxidative stress response, and autophagy. These distinct pathways are all co-opted by tumor cells to cope with cancer-associated stress, and their activation in many cancer types is associated with decreased patient survival. The pathways, however, are typically studied in isolation, and the functional relationship within and between them remains largely unexplored. Moreover, there are few therapies that target these pathways. Thus, we sought a strategy that would simultaneously identify drug vulnerabilities dependent on the activation status of individual proteostasis factors and provide a better understanding of the functional relationship within and between the subnetworks of this complex biological system. Chemical-genetic interaction profiling in model organisms has proven powerful in providing insights into compound mechanism of action, gene function, and the relationship between networks of biological processes. However, identifying chemical-genetic interactions in mammalian systems is currently 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 in mammalian cells. Using minimal automation, we treat pools of 60 cell types—comprising 12 genetic perturbations in critical proteostasis factors and their isogenic controls in five cell lines—with 1,440 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, including a synthetic lethal relationship between the proteasome inhibitor, Carfilzomib, and knockout of diverse proteostasis factors. Our method uncovers functional relationships involving these proteostasis factors, such as a high degree of similarity between the chemical-genetic profiles of HSF1 and HSF2, two heat-shock transcription factors with a previously unresolved functional relationship. Thus, QMAP-Seq provides a broadly accessible and scalable strategy for chemical-genetic profiling in mammalian cells, as we demonstrate for the proteostasis network.

Creator

• Brockway, Sonia Susan

DOI

• https://doi.org/10.21985/n2-ev1p-q089

Subject

• Pharmacology
• Genetics
• Biology

Language

• en

Alternate Identifier

• etdadmin_upload_780926
• http://dissertations.umi.com/northwestern:15412

Date created

• 2020-01-01

Resource type

• Dissertation

Rights statement

• In Copyright