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Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains

Different strains of a microorganism growing in the same environment display a wide variety of growth rates and growth yields. We developed a coarse-grained model to test the hypothesis that different resource allocation strategies, corresponding to different compositions of the proteome, can accoun...

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Autores principales: Baldazzi, Valentina, Ropers, Delphine, Gouzé, Jean-Luc, Gedeon, Tomas, de Jong, Hidde
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270689/
https://www.ncbi.nlm.nih.gov/pubmed/37255080
http://dx.doi.org/10.7554/eLife.79815
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author Baldazzi, Valentina
Ropers, Delphine
Gouzé, Jean-Luc
Gedeon, Tomas
de Jong, Hidde
author_facet Baldazzi, Valentina
Ropers, Delphine
Gouzé, Jean-Luc
Gedeon, Tomas
de Jong, Hidde
author_sort Baldazzi, Valentina
collection PubMed
description Different strains of a microorganism growing in the same environment display a wide variety of growth rates and growth yields. We developed a coarse-grained model to test the hypothesis that different resource allocation strategies, corresponding to different compositions of the proteome, can account for the observed rate-yield variability. The model predictions were verified by means of a database of hundreds of published rate-yield and uptake-secretion phenotypes of Escherichia coli strains grown in standard laboratory conditions. We found a very good quantitative agreement between the range of predicted and observed growth rates, growth yields, and glucose uptake and acetate secretion rates. These results support the hypothesis that resource allocation is a major explanatory factor of the observed variability of growth rates and growth yields across different bacterial strains. An interesting prediction of our model, supported by the experimental data, is that high growth rates are not necessarily accompanied by low growth yields. The resource allocation strategies enabling high-rate, high-yield growth of E. coli lead to a higher saturation of enzymes and ribosomes, and thus to a more efficient utilization of proteomic resources. Our model thus contributes to a fundamental understanding of the quantitative relationship between rate and yield in E. coli and other microorganisms. It may also be useful for the rapid screening of strains in metabolic engineering and synthetic biology.
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spelling pubmed-102706892023-06-16 Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains Baldazzi, Valentina Ropers, Delphine Gouzé, Jean-Luc Gedeon, Tomas de Jong, Hidde eLife Computational and Systems Biology Different strains of a microorganism growing in the same environment display a wide variety of growth rates and growth yields. We developed a coarse-grained model to test the hypothesis that different resource allocation strategies, corresponding to different compositions of the proteome, can account for the observed rate-yield variability. The model predictions were verified by means of a database of hundreds of published rate-yield and uptake-secretion phenotypes of Escherichia coli strains grown in standard laboratory conditions. We found a very good quantitative agreement between the range of predicted and observed growth rates, growth yields, and glucose uptake and acetate secretion rates. These results support the hypothesis that resource allocation is a major explanatory factor of the observed variability of growth rates and growth yields across different bacterial strains. An interesting prediction of our model, supported by the experimental data, is that high growth rates are not necessarily accompanied by low growth yields. The resource allocation strategies enabling high-rate, high-yield growth of E. coli lead to a higher saturation of enzymes and ribosomes, and thus to a more efficient utilization of proteomic resources. Our model thus contributes to a fundamental understanding of the quantitative relationship between rate and yield in E. coli and other microorganisms. It may also be useful for the rapid screening of strains in metabolic engineering and synthetic biology. eLife Sciences Publications, Ltd 2023-05-31 /pmc/articles/PMC10270689/ /pubmed/37255080 http://dx.doi.org/10.7554/eLife.79815 Text en © 2023, Baldazzi et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Baldazzi, Valentina
Ropers, Delphine
Gouzé, Jean-Luc
Gedeon, Tomas
de Jong, Hidde
Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
title Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
title_full Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
title_fullStr Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
title_full_unstemmed Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
title_short Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
title_sort resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270689/
https://www.ncbi.nlm.nih.gov/pubmed/37255080
http://dx.doi.org/10.7554/eLife.79815
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