Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes

ABSTRACT It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to...

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Autores principales:	Tobias B. Alter, Lars M. Blank, Birgitta E. Ebert
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	constraint-based modeling enzyme kinetics metabolic engineering protein allocation transcriptional control Escherichia coli Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/ddd90b43a0c84683b83c8f217806a7ef
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spelling	oai:doaj.org-article:ddd90b43a0c84683b83c8f217806a7ef2021-12-02T19:22:27ZProteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes10.1128/mSystems.00625-202379-5077https://doaj.org/article/ddd90b43a0c84683b83c8f217806a7ef2021-04-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00625-20https://doaj.org/toc/2379-5077ABSTRACT It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to environmental changes. To account for the growth condition-dependent proteome in the constraint-based metabolic modeling of Escherichia coli, we consolidated a coarse-grained protein allocation approach with the explicit consideration of enzymatic constraints on reaction fluxes. Besides representing physiologically relevant wild-type phenotypes and flux distributions, the resulting protein allocation model (PAM) advances the predictability of the metabolic responses to genetic perturbations. A main driver of mutant phenotypes was ascribed to inherited regulation patterns in protein distribution among metabolic enzymes. Moreover, the PAM correctly reflected metabolic responses to an augmented protein burden imposed by the heterologous expression of green fluorescent protein. In summary, we were able to model the effects of important and frequently applied metabolic engineering approaches on microbial metabolism. Therefore, we want to promote the integration of protein allocation constraints into classical constraint-based models to foster their predictive capabilities and application for strain analysis and engineering purposes. IMPORTANCE Predictive metabolic models are important, e.g., for generating biological knowledge and designing microbes with superior performance for target compound production. Yet today’s whole-cell models either show insufficient predictive capabilities or are computationally too expensive to be applied to metabolic engineering purposes. By linking the inherent genotype-phenotype relationship to a complete representation of the proteome, the PAM advances the accuracy of simulated phenotypes and intracellular flux distributions of E. coli. Being equally computationally lightweight as classical stoichiometric models and allowing for the application of established in silico tools, the PAM and related simulation approaches will foster the use of a model-driven metabolic research. Applications range from the investigation of mechanisms of microbial evolution to the determination of optimal strain design strategies in metabolic engineering, thus supporting basic scientists and engineers alike.Tobias B. AlterLars M. BlankBirgitta E. EbertAmerican Society for Microbiologyarticleconstraint-based modelingenzyme kineticsmetabolic engineeringprotein allocationtranscriptional controlEscherichia coliMicrobiologyQR1-502ENmSystems, Vol 6, Iss 2 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	constraint-based modeling enzyme kinetics metabolic engineering protein allocation transcriptional control Escherichia coli Microbiology QR1-502
spellingShingle	constraint-based modeling enzyme kinetics metabolic engineering protein allocation transcriptional control Escherichia coli Microbiology QR1-502 Tobias B. Alter Lars M. Blank Birgitta E. Ebert Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes
description	ABSTRACT It is generally recognized that proteins constitute the key cellular component in shaping microbial phenotypes. Due to limited cellular resources and space, optimal allocation of proteins is crucial for microbes to facilitate maximum proliferation rates while allowing a flexible response to environmental changes. To account for the growth condition-dependent proteome in the constraint-based metabolic modeling of Escherichia coli, we consolidated a coarse-grained protein allocation approach with the explicit consideration of enzymatic constraints on reaction fluxes. Besides representing physiologically relevant wild-type phenotypes and flux distributions, the resulting protein allocation model (PAM) advances the predictability of the metabolic responses to genetic perturbations. A main driver of mutant phenotypes was ascribed to inherited regulation patterns in protein distribution among metabolic enzymes. Moreover, the PAM correctly reflected metabolic responses to an augmented protein burden imposed by the heterologous expression of green fluorescent protein. In summary, we were able to model the effects of important and frequently applied metabolic engineering approaches on microbial metabolism. Therefore, we want to promote the integration of protein allocation constraints into classical constraint-based models to foster their predictive capabilities and application for strain analysis and engineering purposes. IMPORTANCE Predictive metabolic models are important, e.g., for generating biological knowledge and designing microbes with superior performance for target compound production. Yet today’s whole-cell models either show insufficient predictive capabilities or are computationally too expensive to be applied to metabolic engineering purposes. By linking the inherent genotype-phenotype relationship to a complete representation of the proteome, the PAM advances the accuracy of simulated phenotypes and intracellular flux distributions of E. coli. Being equally computationally lightweight as classical stoichiometric models and allowing for the application of established in silico tools, the PAM and related simulation approaches will foster the use of a model-driven metabolic research. Applications range from the investigation of mechanisms of microbial evolution to the determination of optimal strain design strategies in metabolic engineering, thus supporting basic scientists and engineers alike.
format	article
author	Tobias B. Alter Lars M. Blank Birgitta E. Ebert
author_facet	Tobias B. Alter Lars M. Blank Birgitta E. Ebert
author_sort	Tobias B. Alter
title	Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes
title_short	Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes
title_full	Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes
title_fullStr	Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes
title_full_unstemmed	Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes
title_sort	proteome regulation patterns determine <named-content content-type="genus-species">escherichia coli</named-content> wild-type and mutant phenotypes
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/ddd90b43a0c84683b83c8f217806a7ef
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Proteome Regulation Patterns Determine <named-content content-type="genus-species">Escherichia coli</named-content> Wild-Type and Mutant Phenotypes

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