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Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways

Measuring the concentrations of metabolites and estimating the reaction rates of each reaction step consisting of metabolic pathways are significant for an improvement in microorganisms used in maximizing the production of materials. Although the reaction pathway must be identified for such an impro...

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Autores principales: Tominaga, Daisuke, Kawaguchi, Hideo, Hori, Yoshimi, Hasunuma, Tomohisa, Ogino, Chiaki, Aburatani, Sachiyo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5958428/
https://www.ncbi.nlm.nih.gov/pubmed/29795980
http://dx.doi.org/10.1177/1177932218775076
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author Tominaga, Daisuke
Kawaguchi, Hideo
Hori, Yoshimi
Hasunuma, Tomohisa
Ogino, Chiaki
Aburatani, Sachiyo
author_facet Tominaga, Daisuke
Kawaguchi, Hideo
Hori, Yoshimi
Hasunuma, Tomohisa
Ogino, Chiaki
Aburatani, Sachiyo
author_sort Tominaga, Daisuke
collection PubMed
description Measuring the concentrations of metabolites and estimating the reaction rates of each reaction step consisting of metabolic pathways are significant for an improvement in microorganisms used in maximizing the production of materials. Although the reaction pathway must be identified for such an improvement, doing so is not easy. Numerous reaction steps have been reported; however, the actual reaction steps activated vary or change according to the conditions. Furthermore, to build mathematical models for a dynamical analysis, the reaction mechanisms and parameter values must be known; however, to date, sufficient information has yet to be published for many cases. In addition, experimental observations are expensive. A new mathematical approach that is applicable to small sample data, and that requires no detailed reaction information, is strongly needed. S-system is one such model that can use smaller samples than other ordinary differential equation models. We propose a simplified S-system to apply minimal quantities of samples for a dynamic analysis of the metabolic pathways. We applied the model to the phenyl lactate production pathway of Escherichia coli. The model obtained suggests that actually activated reaction steps and feedback are inhibitions within the pathway.
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spelling pubmed-59584282018-05-24 Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways Tominaga, Daisuke Kawaguchi, Hideo Hori, Yoshimi Hasunuma, Tomohisa Ogino, Chiaki Aburatani, Sachiyo Bioinform Biol Insights Original Research Measuring the concentrations of metabolites and estimating the reaction rates of each reaction step consisting of metabolic pathways are significant for an improvement in microorganisms used in maximizing the production of materials. Although the reaction pathway must be identified for such an improvement, doing so is not easy. Numerous reaction steps have been reported; however, the actual reaction steps activated vary or change according to the conditions. Furthermore, to build mathematical models for a dynamical analysis, the reaction mechanisms and parameter values must be known; however, to date, sufficient information has yet to be published for many cases. In addition, experimental observations are expensive. A new mathematical approach that is applicable to small sample data, and that requires no detailed reaction information, is strongly needed. S-system is one such model that can use smaller samples than other ordinary differential equation models. We propose a simplified S-system to apply minimal quantities of samples for a dynamic analysis of the metabolic pathways. We applied the model to the phenyl lactate production pathway of Escherichia coli. The model obtained suggests that actually activated reaction steps and feedback are inhibitions within the pathway. SAGE Publications 2018-05-16 /pmc/articles/PMC5958428/ /pubmed/29795980 http://dx.doi.org/10.1177/1177932218775076 Text en © The Author(s) 2018 http://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Tominaga, Daisuke
Kawaguchi, Hideo
Hori, Yoshimi
Hasunuma, Tomohisa
Ogino, Chiaki
Aburatani, Sachiyo
Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways
title Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways
title_full Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways
title_fullStr Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways
title_full_unstemmed Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways
title_short Mathematical Model for Small Size Time Series Data of Bacterial Secondary Metabolic Pathways
title_sort mathematical model for small size time series data of bacterial secondary metabolic pathways
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5958428/
https://www.ncbi.nlm.nih.gov/pubmed/29795980
http://dx.doi.org/10.1177/1177932218775076
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