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Hierarchical modelling of microbial communities

SUMMARY: The human body harbours a plethora of microbes that play a fundamental role in the well-being of the host. Still, the contribution of many microorganisms to human health remains undiscovered. To understand the composition of their communities, the accurate genome-scale metabolic network mod...

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Autores principales: Glöckler, Manuel, Dräger, Andreas, Mostolizadeh, Reihaneh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887087/
https://www.ncbi.nlm.nih.gov/pubmed/36655763
http://dx.doi.org/10.1093/bioinformatics/btad040
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author Glöckler, Manuel
Dräger, Andreas
Mostolizadeh, Reihaneh
author_facet Glöckler, Manuel
Dräger, Andreas
Mostolizadeh, Reihaneh
author_sort Glöckler, Manuel
collection PubMed
description SUMMARY: The human body harbours a plethora of microbes that play a fundamental role in the well-being of the host. Still, the contribution of many microorganisms to human health remains undiscovered. To understand the composition of their communities, the accurate genome-scale metabolic network models of participating microorganisms are integrated to construct a community that mimics the normal bacterial flora of humans. So far, tools for modelling the communities have transformed the community into various optimization problems and model compositions. Therefore, any knockout or modification of each submodel (each species) necessitates the up-to-date creation of the community to incorporate rebuildings. To solve this complexity, we refer to the context of SBML in a hierarchical model composition, wherein each species’s genome-scale metabolic model is imported as a submodel in another model. Hence, the community is a model composed of submodels defined in separate files. We combine all these files upon parsing to a so-called ‘flattened’ model, i.e., a comprehensive and valid SBML file of the entire community that COBRApy can parse for further processing. The hierarchical model facilitates the analysis of the whole community irrespective of any changes in the individual submodels. AVAILABILITY AND IMPLEMENTATION: The module is freely available at https://github.com/manuelgloeckler/ncmw.
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spelling pubmed-98870872023-01-31 Hierarchical modelling of microbial communities Glöckler, Manuel Dräger, Andreas Mostolizadeh, Reihaneh Bioinformatics Applications Note SUMMARY: The human body harbours a plethora of microbes that play a fundamental role in the well-being of the host. Still, the contribution of many microorganisms to human health remains undiscovered. To understand the composition of their communities, the accurate genome-scale metabolic network models of participating microorganisms are integrated to construct a community that mimics the normal bacterial flora of humans. So far, tools for modelling the communities have transformed the community into various optimization problems and model compositions. Therefore, any knockout or modification of each submodel (each species) necessitates the up-to-date creation of the community to incorporate rebuildings. To solve this complexity, we refer to the context of SBML in a hierarchical model composition, wherein each species’s genome-scale metabolic model is imported as a submodel in another model. Hence, the community is a model composed of submodels defined in separate files. We combine all these files upon parsing to a so-called ‘flattened’ model, i.e., a comprehensive and valid SBML file of the entire community that COBRApy can parse for further processing. The hierarchical model facilitates the analysis of the whole community irrespective of any changes in the individual submodels. AVAILABILITY AND IMPLEMENTATION: The module is freely available at https://github.com/manuelgloeckler/ncmw. Oxford University Press 2023-01-19 /pmc/articles/PMC9887087/ /pubmed/36655763 http://dx.doi.org/10.1093/bioinformatics/btad040 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Glöckler, Manuel
Dräger, Andreas
Mostolizadeh, Reihaneh
Hierarchical modelling of microbial communities
title Hierarchical modelling of microbial communities
title_full Hierarchical modelling of microbial communities
title_fullStr Hierarchical modelling of microbial communities
title_full_unstemmed Hierarchical modelling of microbial communities
title_short Hierarchical modelling of microbial communities
title_sort hierarchical modelling of microbial communities
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9887087/
https://www.ncbi.nlm.nih.gov/pubmed/36655763
http://dx.doi.org/10.1093/bioinformatics/btad040
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