Literature DB >> 29127264

Protein Moonlighting Revealed by Noncatalytic Phenotypes of Yeast Enzymes.

Adriana Espinosa-Cantú1, Diana Ascencio1, Selene Herrera-Basurto1, Jiewei Xu2, Assen Roguev2, Nevan J Krogan2, Alexander DeLuna3.   

Abstract

A single gene can partake in several biological processes, and therefore gene deletions can lead to different-sometimes unexpected-phenotypes. However, it is not always clear whether such pleiotropy reflects the loss of a unique molecular activity involved in different processes or the loss of a multifunctional protein. Here, using Saccharomyces cerevisiae metabolism as a model, we systematically test the null hypothesis that enzyme phenotypes depend on a single annotated molecular function, namely their catalysis. We screened a set of carefully selected genes by quantifying the contribution of catalysis to gene deletion phenotypes under different environmental conditions. While most phenotypes were explained by loss of catalysis, slow growth was readily rescued by a catalytically inactive protein in about one-third of the enzymes tested. Such noncatalytic phenotypes were frequent in the Alt1 and Bat2 transaminases and in the isoleucine/valine biosynthetic enzymes Ilv1 and Ilv2, suggesting novel "moonlighting" activities in these proteins. Furthermore, differential genetic interaction profiles of gene deletion and catalytic mutants indicated that ILV1 is functionally associated with regulatory processes, specifically to chromatin modification. Our systematic study shows that gene loss phenotypes and their genetic interactions are frequently not driven by the loss of an annotated catalytic function, underscoring the moonlighting nature of cellular metabolism.
Copyright © 2018 by the Genetics Society of America.

Entities:  

Keywords:  Saccharomyces cerevisiae; amino acid biosynthesis; metabolism; phenotype; pleiotropy; protein moonlighting; systems genetics

Mesh:

Substances:

Year:  2017        PMID: 29127264      PMCID: PMC5753873          DOI: 10.1534/genetics.117.300377

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


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