Affiliation:
1. Switch Laboratory, Center for Brain and Disease Research, VIB
2. Department of Cellular and Molecular Medicine, KULeuven, Leuven Belgium
Abstract
Abstract
Motivation
Despite intense effort, it has been difficult to explain chaperone dependencies of proteins from sequence or structural properties.
Results
We constructed a database collecting all publicly available data of experimental chaperone interaction and dependency data for the Escherichia coli proteome, and enriched it with an extensive set of protein-specific as well as cell-context-dependent proteostatic parameters. Employing this new resource, we performed a comprehensive meta-analysis of the key determinants of chaperone interaction. Our study confirms that GroEL client proteins are biased toward insoluble proteins of low abundance, but for client proteins of the Trigger Factor/DnaK axis, we instead find that cellular parameters such as high protein abundance, translational efficiency and mRNA turnover are key determinants. We experimentally confirmed the finding that chaperone dependence is a function of translation rate and not protein-intrinsic parameters by tuning chaperone dependence of Green Fluorescent Protein (GFP) in E.coli by synonymous mutations only. The juxtaposition of both protein-intrinsic and cell-contextual chaperone triage mechanisms explains how the E.coli proteome achieves combining reliable production of abundant and conserved proteins, while also enabling the evolution of diverging metabolic functions.
Availability and implementation
The database will be made available via http://phdb.switchlab.org.
Supplementary information
Supplementary data are available at Bioinformatics online.
Funder
European Research Council
European Union’s Horizon 2020 Framework Programme
Flanders Institute for Biotechnology
University of Leuven
Funds for Scientific Research Flanders
FWO
Flanders Agency for Innovation by Science and Technology
Federal Office for Scientific Affairs of Belgium
Erasmus Mundus fellowship
IWT
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Cited by
7 articles.
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