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Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils
Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540551/ https://www.ncbi.nlm.nih.gov/pubmed/28767679 http://dx.doi.org/10.1371/journal.pone.0181826 |
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author | Alvarez-Silva, María Camila Álvarez-Yela, Astrid Catalina Gómez-Cano, Fabio Zambrano, María Mercedes Husserl, Johana Danies, Giovanna Restrepo, Silvia González-Barrios, Andrés Fernando |
author_facet | Alvarez-Silva, María Camila Álvarez-Yela, Astrid Catalina Gómez-Cano, Fabio Zambrano, María Mercedes Husserl, Johana Danies, Giovanna Restrepo, Silvia González-Barrios, Andrés Fernando |
author_sort | Alvarez-Silva, María Camila |
collection | PubMed |
description | Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community. |
format | Online Article Text |
id | pubmed-5540551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55405512017-08-12 Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils Alvarez-Silva, María Camila Álvarez-Yela, Astrid Catalina Gómez-Cano, Fabio Zambrano, María Mercedes Husserl, Johana Danies, Giovanna Restrepo, Silvia González-Barrios, Andrés Fernando PLoS One Research Article Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community. Public Library of Science 2017-08-02 /pmc/articles/PMC5540551/ /pubmed/28767679 http://dx.doi.org/10.1371/journal.pone.0181826 Text en © 2017 Alvarez-Silva 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 Alvarez-Silva, María Camila Álvarez-Yela, Astrid Catalina Gómez-Cano, Fabio Zambrano, María Mercedes Husserl, Johana Danies, Giovanna Restrepo, Silvia González-Barrios, Andrés Fernando Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
title | Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
title_full | Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
title_fullStr | Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
title_full_unstemmed | Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
title_short | Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
title_sort | compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540551/ https://www.ncbi.nlm.nih.gov/pubmed/28767679 http://dx.doi.org/10.1371/journal.pone.0181826 |
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