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Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli
Omics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in thi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10295088/ https://www.ncbi.nlm.nih.gov/pubmed/37370567 http://dx.doi.org/10.3390/bioengineering10060636 |
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author | Kuriya, Yuki Murata, Masahiro Yamamoto, Masaki Watanabe, Naoki Araki, Michihiro |
author_facet | Kuriya, Yuki Murata, Masahiro Yamamoto, Masaki Watanabe, Naoki Araki, Michihiro |
author_sort | Kuriya, Yuki |
collection | PubMed |
description | Omics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in this study, we aimed to extract and estimate important variables and necessary numbers for predicting metabolic flux distribution as the state of cell metabolism by flux sampling using a genome-scale metabolic model (GSM) and its analysis. Acetic acid production from glucose in Escherichia coli with GSM iJO1366 was used as a case study. Flux sampling obtained by OptGP using 1000 pattern constraints on substrate, product, and growth fluxes produced a wider sample than the default case. The analysis also suggested that the fluxes of iron ions, O(2), CO(2), and NH(4)(+), were important for predicting the metabolic flux distribution. Additionally, the comparison with the literature value of (13)C-MFA using CO(2) emission flux as an example of an important flux suggested that the important flux obtained by this method was valid for the prediction of flux distribution. In this way, the method of this research was useful for extracting variables that were important for predicting flux distribution, and as a result, the possibility of contributing to the reduction of measurement variables in experiments was suggested. |
format | Online Article Text |
id | pubmed-10295088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102950882023-06-28 Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli Kuriya, Yuki Murata, Masahiro Yamamoto, Masaki Watanabe, Naoki Araki, Michihiro Bioengineering (Basel) Article Omics data was acquired, and the development and research of metabolic simulation and analysis methods using them were also actively carried out. However, it was a laborious task to acquire such data each time the medium composition, culture conditions, and target organism changed. Therefore, in this study, we aimed to extract and estimate important variables and necessary numbers for predicting metabolic flux distribution as the state of cell metabolism by flux sampling using a genome-scale metabolic model (GSM) and its analysis. Acetic acid production from glucose in Escherichia coli with GSM iJO1366 was used as a case study. Flux sampling obtained by OptGP using 1000 pattern constraints on substrate, product, and growth fluxes produced a wider sample than the default case. The analysis also suggested that the fluxes of iron ions, O(2), CO(2), and NH(4)(+), were important for predicting the metabolic flux distribution. Additionally, the comparison with the literature value of (13)C-MFA using CO(2) emission flux as an example of an important flux suggested that the important flux obtained by this method was valid for the prediction of flux distribution. In this way, the method of this research was useful for extracting variables that were important for predicting flux distribution, and as a result, the possibility of contributing to the reduction of measurement variables in experiments was suggested. MDPI 2023-05-24 /pmc/articles/PMC10295088/ /pubmed/37370567 http://dx.doi.org/10.3390/bioengineering10060636 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kuriya, Yuki Murata, Masahiro Yamamoto, Masaki Watanabe, Naoki Araki, Michihiro Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli |
title | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli |
title_full | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli |
title_fullStr | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli |
title_full_unstemmed | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli |
title_short | Prediction of Metabolic Flux Distribution by Flux Sampling: As a Case Study, Acetate Production from Glucose in Escherichia coli |
title_sort | prediction of metabolic flux distribution by flux sampling: as a case study, acetate production from glucose in escherichia coli |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10295088/ https://www.ncbi.nlm.nih.gov/pubmed/37370567 http://dx.doi.org/10.3390/bioengineering10060636 |
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