Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.

This genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios...

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Main Authors: Clémentine Dressaire, Christophe Gitton, Pascal Loubière, Véronique Monnet, Isabelle Queinnec, Muriel Cocaign-Bousquet
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2009-12-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC2787624?pdf=render
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spelling doaj-5008e1d02c7540bf84a505c1499d82882020-11-25T01:34:03ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582009-12-01512e100060610.1371/journal.pcbi.1000606Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.Clémentine DressaireChristophe GittonPascal LoubièreVéronique MonnetIsabelle QueinnecMuriel Cocaign-BousquetThis genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios of mRNA to protein were highly variable among proteins but also, for a given gene, between the different growth conditions. The modeling of cellular processes combined with a data fitting modeling approach allowed both translation efficiencies and degradation rates to be estimated for each protein in each growth condition. Estimated translational efficiencies and degradation rates strongly differed between proteins and were tested for their biological significance through statistical correlations with relevant parameters such as codon or amino acid bias. These efficiencies and degradation rates were not constant in all growth conditions and were inversely proportional to the growth rate, indicating a more efficient translation at low growth rate but an antagonistic higher rate of protein degradation. Estimated protein median half-lives ranged from 23 to 224 min, underlying the importance of protein degradation notably at low growth rates. The regulation of intracellular protein level was analysed through regulatory coefficient calculations, revealing a complex control depending on protein and growth conditions. The modeling approach enabled translational efficiencies and protein degradation rates to be estimated, two biological parameters extremely difficult to determine experimentally and generally lacking in bacteria. This method is generic and can now be extended to other environments and/or other micro-organisms.http://europepmc.org/articles/PMC2787624?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Clémentine Dressaire
Christophe Gitton
Pascal Loubière
Véronique Monnet
Isabelle Queinnec
Muriel Cocaign-Bousquet
spellingShingle Clémentine Dressaire
Christophe Gitton
Pascal Loubière
Véronique Monnet
Isabelle Queinnec
Muriel Cocaign-Bousquet
Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.
PLoS Computational Biology
author_facet Clémentine Dressaire
Christophe Gitton
Pascal Loubière
Véronique Monnet
Isabelle Queinnec
Muriel Cocaign-Bousquet
author_sort Clémentine Dressaire
title Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.
title_short Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.
title_full Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.
title_fullStr Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.
title_full_unstemmed Transcriptome and proteome exploration to model translation efficiency and protein stability in Lactococcus lactis.
title_sort transcriptome and proteome exploration to model translation efficiency and protein stability in lactococcus lactis.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2009-12-01
description This genome-scale study analysed the various parameters influencing protein levels in cells. To achieve this goal, the model bacterium Lactococcus lactis was grown at steady state in continuous cultures at different growth rates, and proteomic and transcriptomic data were thoroughly compared. Ratios of mRNA to protein were highly variable among proteins but also, for a given gene, between the different growth conditions. The modeling of cellular processes combined with a data fitting modeling approach allowed both translation efficiencies and degradation rates to be estimated for each protein in each growth condition. Estimated translational efficiencies and degradation rates strongly differed between proteins and were tested for their biological significance through statistical correlations with relevant parameters such as codon or amino acid bias. These efficiencies and degradation rates were not constant in all growth conditions and were inversely proportional to the growth rate, indicating a more efficient translation at low growth rate but an antagonistic higher rate of protein degradation. Estimated protein median half-lives ranged from 23 to 224 min, underlying the importance of protein degradation notably at low growth rates. The regulation of intracellular protein level was analysed through regulatory coefficient calculations, revealing a complex control depending on protein and growth conditions. The modeling approach enabled translational efficiencies and protein degradation rates to be estimated, two biological parameters extremely difficult to determine experimentally and generally lacking in bacteria. This method is generic and can now be extended to other environments and/or other micro-organisms.
url http://europepmc.org/articles/PMC2787624?pdf=render
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