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Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling
Genome-scale metabolic models (GEMs) are mathematical representations of metabolism that allow for in silico simulation of metabolic phenotypes and capabilities. A prerequisite for these predictions is an accurate representation of the biomolecular composition of the cell necessary for replication a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794083/ https://www.ncbi.nlm.nih.gov/pubmed/35085271 http://dx.doi.org/10.1371/journal.pone.0262450 |
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author | Simensen, Vetle Schulz, Christian Karlsen, Emil Bråtelund, Signe Burgos, Idun Thorfinnsdottir, Lilja Brekke García-Calvo, Laura Bruheim, Per Almaas, Eivind |
author_facet | Simensen, Vetle Schulz, Christian Karlsen, Emil Bråtelund, Signe Burgos, Idun Thorfinnsdottir, Lilja Brekke García-Calvo, Laura Bruheim, Per Almaas, Eivind |
author_sort | Simensen, Vetle |
collection | PubMed |
description | Genome-scale metabolic models (GEMs) are mathematical representations of metabolism that allow for in silico simulation of metabolic phenotypes and capabilities. A prerequisite for these predictions is an accurate representation of the biomolecular composition of the cell necessary for replication and growth, implemented in GEMs as the so-called biomass objective function (BOF). The BOF contains the metabolic precursors required for synthesis of the cellular macro- and micromolecular constituents (e.g. protein, RNA, DNA), and its composition is highly dependent on the particular organism, strain, and growth condition. Despite its critical role, the BOF is rarely constructed using specific measurements of the modeled organism, drawing the validity of this approach into question. Thus, there is a need to establish robust and reliable protocols for experimental condition-specific biomass determination. Here, we address this challenge by presenting a general pipeline for biomass quantification, evaluating its performance on Escherichia coli K-12 MG1655 sampled during balanced exponential growth under controlled conditions in a batch-fermentor set-up. We significantly improve both the coverage and molecular resolution compared to previously published workflows, quantifying 91.6% of the biomass. Our measurements display great correspondence with previously reported measurements, and we were also able to detect subtle characteristics specific to the particular E. coli strain. Using the modified E. coli GEM iML1515a, we compare the feasible flux ranges of our experimentally determined BOF with the original BOF, finding that the changes in BOF coefficients considerably affect the attainable fluxes at the genome-scale. |
format | Online Article Text |
id | pubmed-8794083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87940832022-01-28 Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling Simensen, Vetle Schulz, Christian Karlsen, Emil Bråtelund, Signe Burgos, Idun Thorfinnsdottir, Lilja Brekke García-Calvo, Laura Bruheim, Per Almaas, Eivind PLoS One Research Article Genome-scale metabolic models (GEMs) are mathematical representations of metabolism that allow for in silico simulation of metabolic phenotypes and capabilities. A prerequisite for these predictions is an accurate representation of the biomolecular composition of the cell necessary for replication and growth, implemented in GEMs as the so-called biomass objective function (BOF). The BOF contains the metabolic precursors required for synthesis of the cellular macro- and micromolecular constituents (e.g. protein, RNA, DNA), and its composition is highly dependent on the particular organism, strain, and growth condition. Despite its critical role, the BOF is rarely constructed using specific measurements of the modeled organism, drawing the validity of this approach into question. Thus, there is a need to establish robust and reliable protocols for experimental condition-specific biomass determination. Here, we address this challenge by presenting a general pipeline for biomass quantification, evaluating its performance on Escherichia coli K-12 MG1655 sampled during balanced exponential growth under controlled conditions in a batch-fermentor set-up. We significantly improve both the coverage and molecular resolution compared to previously published workflows, quantifying 91.6% of the biomass. Our measurements display great correspondence with previously reported measurements, and we were also able to detect subtle characteristics specific to the particular E. coli strain. Using the modified E. coli GEM iML1515a, we compare the feasible flux ranges of our experimentally determined BOF with the original BOF, finding that the changes in BOF coefficients considerably affect the attainable fluxes at the genome-scale. Public Library of Science 2022-01-27 /pmc/articles/PMC8794083/ /pubmed/35085271 http://dx.doi.org/10.1371/journal.pone.0262450 Text en © 2022 Simensen et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Simensen, Vetle Schulz, Christian Karlsen, Emil Bråtelund, Signe Burgos, Idun Thorfinnsdottir, Lilja Brekke García-Calvo, Laura Bruheim, Per Almaas, Eivind Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling |
title | Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling |
title_full | Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling |
title_fullStr | Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling |
title_full_unstemmed | Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling |
title_short | Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling |
title_sort | experimental determination of escherichia coli biomass composition for constraint-based metabolic modeling |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794083/ https://www.ncbi.nlm.nih.gov/pubmed/35085271 http://dx.doi.org/10.1371/journal.pone.0262450 |
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