Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49...
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Autor*in:	Levering, Jennifer [verfasserIn] Fiedler, Tomas Sieg, Antje van Grinsven, Koen W A Hering, Silvio Veith, Nadine Olivier, Brett G Klett, Lara Hugenholtz, Jeroen Teusink, Bas Kreikemeyer, Bernd Kummer, Ursula

Format:	Artikel
Sprache:	Englisch

Erschienen:	2016

Rechteinformationen:	Nutzungsrecht: Copyright © 2016 Elsevier B.V. All rights reserved.

Übergeordnetes Werk:	Enthalten in: Journal of biotechnology - Amsterdam : Elsevier, 1984, 232(2016), Seite 25
Übergeordnetes Werk:	volume:232 ; year:2016 ; pages:25

Links:	Link aufrufen

Katalog-ID:	OLC1980370877

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title	Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets
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title_full	Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets
author_sort	Levering, Jennifer
journal	Journal of biotechnology
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title_sort	genome-scale reconstruction of the streptococcus pyogenes m49 metabolic network reveals growth requirements and indicates potential drug targets
title_auth	Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets
abstract	Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets.
abstractGer	Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets.
abstract_unstemmed	Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets.
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title_short	Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets
url	http://www.ncbi.nlm.nih.gov/pubmed/26970054
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author2	Fiedler, Tomas Sieg, Antje van Grinsven, Koen W A Hering, Silvio Veith, Nadine Olivier, Brett G Klett, Lara Hugenholtz, Jeroen Teusink, Bas Kreikemeyer, Bernd Kummer, Ursula
author2Str	Fiedler, Tomas Sieg, Antje van Grinsven, Koen W A Hering, Silvio Veith, Nadine Olivier, Brett G Klett, Lara Hugenholtz, Jeroen Teusink, Bas Kreikemeyer, Bernd Kummer, Ursula
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up_date	2024-07-04T02:58:11.986Z
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