Abstract
The evaluation of protein localization changes on a systematic level is a powerful tool for understanding how cells respond to environmental, chemical, or genetic perturbations. To date, work in understanding these proteomic responses through high-throughput imaging has catalogued localization changes independently for each perturbation. To distinguish changes that are targeted responses to the specific perturbation or more generalized programs, we developed a scalable approach to visualize the localization behavior of proteins across multiple experiments as a quantitative pattern. By applying this approach to 24 experimental screens consisting of nearly 400,000 images, we differentiated specific responses from more generalized ones, discovered nuance in the localization behavior of stress-responsive proteins, and formed hypotheses by clustering proteins that have similar patterns. Previous approaches aim to capture all localization changes for a single screen as accurately as possible, whereas our work aims to integrate large amounts of imaging data to find unexpected new cell biology.
Highlights
The ability to control the subcellular localization of proteins has long been understood as an important component of a cell’s regulatory toolkit in response to perturbations (Cyert, 2001; Bauer et al, 2015; Protter and Parker, 2016), such as drug treatments, genetic mutations, or environmental stressors
We show that some protein localization changes are accompanied by transcriptional or protein abundance changes, subcellular localization is in general an independent layer of regulation, and that shared patterns of localization changes cannot be explained by physical interactions or subcellular compartments
We start with two sets of micrographs of yeast cells, one of cells under untreated wildtype conditions and another under perturbation, where the protein of interest has been tagged with green fluorescent protein (GFP), and where a cytosolic RFP has been expressed to facilitate cell identification
Summary
The ability to control the subcellular localization of proteins has long been understood as an important component of a cell’s regulatory toolkit in response to perturbations (Cyert, 2001; Bauer et al, 2015; Protter and Parker, 2016), such as drug treatments, genetic mutations, or environmental stressors. Towards the goal of systematically characterizing these proteome dynamics, high-throughput technologies have been employed to gather data about protein localization in cells (Yuet and Tirrell, 2014; Dephoure and Gygi, 2012; Nagaraj et al, 2012). We focus on the analysis of images from screens of libraries of yeast strains expressing green fluorescent protein (GFP)-tagged proteins generated using automated high-throughput microscopy (Mattiazzi Usaj et al, 2016; Caicedo et al, 2016) These experiments yield terabyte-scale image datasets (Koh et al, 2015; Riffle and Davis, 2010; Breker et al, 2014) that show changes in the subcellular localization of the proteome in response to varied perturbations (Chong et al, 2015; Tkach et al, 2012; Kraus et al, 2017; Breker et al, 2013)
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