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The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models

Systems biology has long been interested in models capturing both metabolism and expression in a cell. We propose here an implementation of the metabolism and expression model formalism (ME-models), which we call ETFL, for Expression and Thermodynamics Flux models. ETFL is a hierarchical model formu...

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Autores principales: Salvy, Pierre, Hatzimanikatis, Vassily
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6959363/
https://www.ncbi.nlm.nih.gov/pubmed/31937763
http://dx.doi.org/10.1038/s41467-019-13818-7
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author Salvy, Pierre
Hatzimanikatis, Vassily
author_facet Salvy, Pierre
Hatzimanikatis, Vassily
author_sort Salvy, Pierre
collection PubMed
description Systems biology has long been interested in models capturing both metabolism and expression in a cell. We propose here an implementation of the metabolism and expression model formalism (ME-models), which we call ETFL, for Expression and Thermodynamics Flux models. ETFL is a hierarchical model formulation, from metabolism to RNA synthesis, that allows simulating thermodynamics-compliant intracellular fluxes as well as enzyme and mRNA concentration levels. ETFL formulates a mixed-integer linear problem (MILP) that enables both relative and absolute metabolite, protein, and mRNA concentration integration. ETFL is compatible with standard MILP solvers and does not require a non-linear solver, unlike the previous state of the art. It also accounts for growth-dependent parameters, such as relative protein or mRNA content. We present ETFL along with its validation using results obtained from a well-characterized E. coli model. We show that ETFL is able to reproduce proteome-limited growth. We also subject it to several analyses, including the prediction of feasible mRNA and enzyme concentrations and gene essentiality.
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spelling pubmed-69593632020-01-15 The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models Salvy, Pierre Hatzimanikatis, Vassily Nat Commun Article Systems biology has long been interested in models capturing both metabolism and expression in a cell. We propose here an implementation of the metabolism and expression model formalism (ME-models), which we call ETFL, for Expression and Thermodynamics Flux models. ETFL is a hierarchical model formulation, from metabolism to RNA synthesis, that allows simulating thermodynamics-compliant intracellular fluxes as well as enzyme and mRNA concentration levels. ETFL formulates a mixed-integer linear problem (MILP) that enables both relative and absolute metabolite, protein, and mRNA concentration integration. ETFL is compatible with standard MILP solvers and does not require a non-linear solver, unlike the previous state of the art. It also accounts for growth-dependent parameters, such as relative protein or mRNA content. We present ETFL along with its validation using results obtained from a well-characterized E. coli model. We show that ETFL is able to reproduce proteome-limited growth. We also subject it to several analyses, including the prediction of feasible mRNA and enzyme concentrations and gene essentiality. Nature Publishing Group UK 2020-01-13 /pmc/articles/PMC6959363/ /pubmed/31937763 http://dx.doi.org/10.1038/s41467-019-13818-7 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
Salvy, Pierre
Hatzimanikatis, Vassily
The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
title The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
title_full The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
title_fullStr The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
title_full_unstemmed The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
title_short The ETFL formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
title_sort etfl formulation allows multi-omics integration in thermodynamics-compliant metabolism and expression models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6959363/
https://www.ncbi.nlm.nih.gov/pubmed/31937763
http://dx.doi.org/10.1038/s41467-019-13818-7
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