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Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus
Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8241996/ https://www.ncbi.nlm.nih.gov/pubmed/34188046 http://dx.doi.org/10.1038/s41540-021-00188-4 |
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author | Renz, Alina Dräger, Andreas |
author_facet | Renz, Alina Dräger, Andreas |
author_sort | Renz, Alina |
collection | PubMed |
description | Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes. Furthermore, all models were quality-controlled using MEMOTE, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains. |
format | Online Article Text |
id | pubmed-8241996 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82419962021-07-16 Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus Renz, Alina Dräger, Andreas NPJ Syst Biol Appl Review Article Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes. Furthermore, all models were quality-controlled using MEMOTE, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains. Nature Publishing Group UK 2021-06-29 /pmc/articles/PMC8241996/ /pubmed/34188046 http://dx.doi.org/10.1038/s41540-021-00188-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Renz, Alina Dräger, Andreas Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus |
title | Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus |
title_full | Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus |
title_fullStr | Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus |
title_full_unstemmed | Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus |
title_short | Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus |
title_sort | curating and comparing 114 strain-specific genome-scale metabolic models of staphylococcus aureus |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8241996/ https://www.ncbi.nlm.nih.gov/pubmed/34188046 http://dx.doi.org/10.1038/s41540-021-00188-4 |
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