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A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks
Metabolism underpins the pathogenic strategy of the causative agent of TB, Mycobacterium tuberculosis (Mtb), and therefore metabolic pathways have recently re-emerged as attractive drug targets. A powerful approach to study Mtb metabolism as a whole, rather than just individual enzymatic components,...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316355/ https://www.ncbi.nlm.nih.gov/pubmed/32542021 http://dx.doi.org/10.1371/journal.pcbi.1007533 |
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author | López-Agudelo, Víctor A. Mendum, Tom A. Laing, Emma Wu, HuiHai Baena, Andres Barrera, Luis F. Beste, Dany J. V. Rios-Estepa, Rigoberto |
author_facet | López-Agudelo, Víctor A. Mendum, Tom A. Laing, Emma Wu, HuiHai Baena, Andres Barrera, Luis F. Beste, Dany J. V. Rios-Estepa, Rigoberto |
author_sort | López-Agudelo, Víctor A. |
collection | PubMed |
description | Metabolism underpins the pathogenic strategy of the causative agent of TB, Mycobacterium tuberculosis (Mtb), and therefore metabolic pathways have recently re-emerged as attractive drug targets. A powerful approach to study Mtb metabolism as a whole, rather than just individual enzymatic components, is to use a systems biology framework, such as a Genome-Scale Metabolic Network (GSMN) that allows the dynamic interactions of all the components of metabolism to be interrogated together. Several GSMNs networks have been constructed for Mtb and used to study the complex relationship between the Mtb genotype and its phenotype. However, the utility of this approach is hampered by the existence of multiple models, each with varying properties and performances. Here we systematically evaluate eight recently published metabolic models of Mtb-H37Rv to facilitate model choice. The best performing models, sMtb2018 and iEK1011, were refined and improved for use in future studies by the TB research community. |
format | Online Article Text |
id | pubmed-7316355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-73163552020-06-30 A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks López-Agudelo, Víctor A. Mendum, Tom A. Laing, Emma Wu, HuiHai Baena, Andres Barrera, Luis F. Beste, Dany J. V. Rios-Estepa, Rigoberto PLoS Comput Biol Research Article Metabolism underpins the pathogenic strategy of the causative agent of TB, Mycobacterium tuberculosis (Mtb), and therefore metabolic pathways have recently re-emerged as attractive drug targets. A powerful approach to study Mtb metabolism as a whole, rather than just individual enzymatic components, is to use a systems biology framework, such as a Genome-Scale Metabolic Network (GSMN) that allows the dynamic interactions of all the components of metabolism to be interrogated together. Several GSMNs networks have been constructed for Mtb and used to study the complex relationship between the Mtb genotype and its phenotype. However, the utility of this approach is hampered by the existence of multiple models, each with varying properties and performances. Here we systematically evaluate eight recently published metabolic models of Mtb-H37Rv to facilitate model choice. The best performing models, sMtb2018 and iEK1011, were refined and improved for use in future studies by the TB research community. Public Library of Science 2020-06-15 /pmc/articles/PMC7316355/ /pubmed/32542021 http://dx.doi.org/10.1371/journal.pcbi.1007533 Text en © 2020 López-Agudelo et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 López-Agudelo, Víctor A. Mendum, Tom A. Laing, Emma Wu, HuiHai Baena, Andres Barrera, Luis F. Beste, Dany J. V. Rios-Estepa, Rigoberto A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks |
title | A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks |
title_full | A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks |
title_fullStr | A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks |
title_full_unstemmed | A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks |
title_short | A systematic evaluation of Mycobacterium tuberculosis Genome-Scale Metabolic Networks |
title_sort | systematic evaluation of mycobacterium tuberculosis genome-scale metabolic networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316355/ https://www.ncbi.nlm.nih.gov/pubmed/32542021 http://dx.doi.org/10.1371/journal.pcbi.1007533 |
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