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metaGEM: reconstruction of genome scale metabolic models directly from metagenomes
Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643649/ https://www.ncbi.nlm.nih.gov/pubmed/34614189 http://dx.doi.org/10.1093/nar/gkab815 |
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author | Zorrilla, Francisco Buric, Filip Patil, Kiran R Zelezniak, Aleksej |
author_facet | Zorrilla, Francisco Buric, Filip Patil, Kiran R Zelezniak, Aleksej |
author_sort | Zorrilla, Francisco |
collection | PubMed |
description | Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses. |
format | Online Article Text |
id | pubmed-8643649 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86436492021-12-06 metaGEM: reconstruction of genome scale metabolic models directly from metagenomes Zorrilla, Francisco Buric, Filip Patil, Kiran R Zelezniak, Aleksej Nucleic Acids Res Computational Biology Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses. Oxford University Press 2021-10-06 /pmc/articles/PMC8643649/ /pubmed/34614189 http://dx.doi.org/10.1093/nar/gkab815 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Computational Biology Zorrilla, Francisco Buric, Filip Patil, Kiran R Zelezniak, Aleksej metaGEM: reconstruction of genome scale metabolic models directly from metagenomes |
title | metaGEM: reconstruction of genome scale metabolic models directly from metagenomes |
title_full | metaGEM: reconstruction of genome scale metabolic models directly from metagenomes |
title_fullStr | metaGEM: reconstruction of genome scale metabolic models directly from metagenomes |
title_full_unstemmed | metaGEM: reconstruction of genome scale metabolic models directly from metagenomes |
title_short | metaGEM: reconstruction of genome scale metabolic models directly from metagenomes |
title_sort | metagem: reconstruction of genome scale metabolic models directly from metagenomes |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643649/ https://www.ncbi.nlm.nih.gov/pubmed/34614189 http://dx.doi.org/10.1093/nar/gkab815 |
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