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Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation

Empirical kinetic models such as the Monod equation have been widely applied to relate the cell growth with substrate availability. The Monod equation shares a similar form with the mechanistically-based Michaelis-Menten kinetics for enzymatic processes, which has provoked long-standing and un-concl...

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Autores principales: Zeng, Hong, Yang, Aidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062752/
https://www.ncbi.nlm.nih.gov/pubmed/32152336
http://dx.doi.org/10.1038/s41598-020-61174-0
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author Zeng, Hong
Yang, Aidong
author_facet Zeng, Hong
Yang, Aidong
author_sort Zeng, Hong
collection PubMed
description Empirical kinetic models such as the Monod equation have been widely applied to relate the cell growth with substrate availability. The Monod equation shares a similar form with the mechanistically-based Michaelis-Menten kinetics for enzymatic processes, which has provoked long-standing and un-concluded conjectures on their relationship. In this work, we integrated proteome allocation principles into a Flux Balance Analysis (FBA) model of Escherichia coli, which quantitatively revealed potential mechanisms that underpin the phenomenological Monod parameters: the maximum specific growth rate could be dictated by the abundance of growth-controlling proteome and growth-pertinent proteome cost; more importantly, the Monod constant (K(s)) was shown to relate to the Michaelis constant for substrate transport (K(m,g)), with the link being dependent on the cell’s metabolic strategy. Besides, the proposed model was able to predict glucose uptake rate at given external glucose concentration through the size of available proteome resource for substrate transport and its enzymatic cost, while growth rate and acetate overflow were accurately simulated for two E. coli strains. Bridging the enzymatic kinetics of substrate intake and overall growth phenotypes, this work offers a mechanistic interpretation to the empirical Monod law, and demonstrates the potential of coupling local and global cellular constrains in predictive modelling.
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spelling pubmed-70627522020-03-18 Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation Zeng, Hong Yang, Aidong Sci Rep Article Empirical kinetic models such as the Monod equation have been widely applied to relate the cell growth with substrate availability. The Monod equation shares a similar form with the mechanistically-based Michaelis-Menten kinetics for enzymatic processes, which has provoked long-standing and un-concluded conjectures on their relationship. In this work, we integrated proteome allocation principles into a Flux Balance Analysis (FBA) model of Escherichia coli, which quantitatively revealed potential mechanisms that underpin the phenomenological Monod parameters: the maximum specific growth rate could be dictated by the abundance of growth-controlling proteome and growth-pertinent proteome cost; more importantly, the Monod constant (K(s)) was shown to relate to the Michaelis constant for substrate transport (K(m,g)), with the link being dependent on the cell’s metabolic strategy. Besides, the proposed model was able to predict glucose uptake rate at given external glucose concentration through the size of available proteome resource for substrate transport and its enzymatic cost, while growth rate and acetate overflow were accurately simulated for two E. coli strains. Bridging the enzymatic kinetics of substrate intake and overall growth phenotypes, this work offers a mechanistic interpretation to the empirical Monod law, and demonstrates the potential of coupling local and global cellular constrains in predictive modelling. Nature Publishing Group UK 2020-03-09 /pmc/articles/PMC7062752/ /pubmed/32152336 http://dx.doi.org/10.1038/s41598-020-61174-0 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zeng, Hong
Yang, Aidong
Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
title Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
title_full Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
title_fullStr Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
title_full_unstemmed Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
title_short Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
title_sort bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062752/
https://www.ncbi.nlm.nih.gov/pubmed/32152336
http://dx.doi.org/10.1038/s41598-020-61174-0
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