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Fast automated reconstruction of genome-scale metabolic models for microbial species and communities

Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism, for model-guided re-engineering, and unraveling cross-feeding in microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging behind the av...

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Autores principales: Machado, Daniel, Andrejev, Sergej, Tramontano, Melanie, Patil, Kiran Raosaheb
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125623/
https://www.ncbi.nlm.nih.gov/pubmed/30192979
http://dx.doi.org/10.1093/nar/gky537
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author Machado, Daniel
Andrejev, Sergej
Tramontano, Melanie
Patil, Kiran Raosaheb
author_facet Machado, Daniel
Andrejev, Sergej
Tramontano, Melanie
Patil, Kiran Raosaheb
author_sort Machado, Daniel
collection PubMed
description Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism, for model-guided re-engineering, and unraveling cross-feeding in microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual curation required to obtain good quality models. Here, we present an automated tool, CarveMe, for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We show that CarveMe models perform closely to manually curated models in reproducing experimental phenotypes (substrate utilization and gene essentiality). Additionally, we build a collection of 74 models for human gut bacteria and test their ability to reproduce growth on a set of experimentally defined media. Finally, we create a database of 5587 bacterial models and demonstrate its potential for fast generation of microbial community models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.
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spelling pubmed-61256232018-09-11 Fast automated reconstruction of genome-scale metabolic models for microbial species and communities Machado, Daniel Andrejev, Sergej Tramontano, Melanie Patil, Kiran Raosaheb Nucleic Acids Res Computational Biology Genome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism, for model-guided re-engineering, and unraveling cross-feeding in microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual curation required to obtain good quality models. Here, we present an automated tool, CarveMe, for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We show that CarveMe models perform closely to manually curated models in reproducing experimental phenotypes (substrate utilization and gene essentiality). Additionally, we build a collection of 74 models for human gut bacteria and test their ability to reproduce growth on a set of experimentally defined media. Finally, we create a database of 5587 bacterial models and demonstrate its potential for fast generation of microbial community models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities. Oxford University Press 2018-09-06 2018-06-21 /pmc/articles/PMC6125623/ /pubmed/30192979 http://dx.doi.org/10.1093/nar/gky537 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Machado, Daniel
Andrejev, Sergej
Tramontano, Melanie
Patil, Kiran Raosaheb
Fast automated reconstruction of genome-scale metabolic models for microbial species and communities
title Fast automated reconstruction of genome-scale metabolic models for microbial species and communities
title_full Fast automated reconstruction of genome-scale metabolic models for microbial species and communities
title_fullStr Fast automated reconstruction of genome-scale metabolic models for microbial species and communities
title_full_unstemmed Fast automated reconstruction of genome-scale metabolic models for microbial species and communities
title_short Fast automated reconstruction of genome-scale metabolic models for microbial species and communities
title_sort fast automated reconstruction of genome-scale metabolic models for microbial species and communities
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6125623/
https://www.ncbi.nlm.nih.gov/pubmed/30192979
http://dx.doi.org/10.1093/nar/gky537
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