Global and gene-specific translational regulation in Escherichia coli across different conditions.

TitleGlobal and gene-specific translational regulation in Escherichia coli across different conditions.
Publication TypeJournal Article
Year of Publication2022
AuthorsZhang, D, Li, SHsin-Jung, King, CG, Wingreen, NS, Gitai, Z, Li, Z
JournalPLoS Comput Biol
Volume18
Issue10
Paginatione1010641
Date Published2022 Oct
ISSN1553-7358
KeywordsEscherichia coli, Escherichia coli Proteins, Protein Biosynthesis, Proteomics, RNA, Messenger
Abstract

<p>How well mRNA transcript levels represent protein abundances has been a controversial issue. Particularly across different environments, correlations between mRNA and protein exhibit remarkable variability from gene to gene. Translational regulation is likely to be one of the key factors contributing to mismatches between mRNA level and protein abundance in bacteria. Here, we quantified genome-wide transcriptome and relative translation efficiency (RTE) under 12 different conditions in Escherichia coli. By quantifying the mRNA-RTE correlation both across genes and across conditions, we uncovered a diversity of gene-specific translational regulations, cooperating with transcriptional regulations, in response to carbon (C), nitrogen (N), and phosphate (P) limitations. Intriguingly, we found that many genes regulating translation are themselves subject to translational regulation, suggesting possible feedbacks. Furthermore, a random forest model suggests that codon usage partially predicts a gene's cross-condition variability in translation efficiency; such cross-condition variability tends to be an inherent quality of a gene, independent of the specific nutrient limitations. These findings broaden the understanding of translational regulation under different environments and provide novel strategies for the control of translation in synthetic biology. In addition, our data offers a resource for future multi-omics studies.</p>

DOI10.1371/journal.pcbi.1010641
Alternate JournalPLoS Comput Biol
PubMed ID36264977
PubMed Central IDPMC9624429
Grant ListR01 GM082938 / GM / NIGMS NIH HHS / United States
DP1 AI124669 / AI / NIAID NIH HHS / United States