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Contribution of genome‐scale metabolic modelling to niche theory
Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome‐scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organ...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324083/ https://www.ncbi.nlm.nih.gov/pubmed/35384214 http://dx.doi.org/10.1111/ele.13954 |
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author | Régimbeau, Antoine Budinich, Marko Larhlimi, Abdelhalim Pierella Karlusich, Juan José Aumont, Olivier Memery, Laurent Bowler, Chris Eveillard, Damien |
author_facet | Régimbeau, Antoine Budinich, Marko Larhlimi, Abdelhalim Pierella Karlusich, Juan José Aumont, Olivier Memery, Laurent Bowler, Chris Eveillard, Damien |
author_sort | Régimbeau, Antoine |
collection | PubMed |
description | Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome‐scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so‐called metabolic niche resumes well‐known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence–absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome‐scale description in ecological studies. |
format | Online Article Text |
id | pubmed-9324083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93240832022-07-30 Contribution of genome‐scale metabolic modelling to niche theory Régimbeau, Antoine Budinich, Marko Larhlimi, Abdelhalim Pierella Karlusich, Juan José Aumont, Olivier Memery, Laurent Bowler, Chris Eveillard, Damien Ecol Lett Letters Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome‐scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so‐called metabolic niche resumes well‐known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence–absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome‐scale description in ecological studies. John Wiley and Sons Inc. 2022-04-05 2022-06 /pmc/articles/PMC9324083/ /pubmed/35384214 http://dx.doi.org/10.1111/ele.13954 Text en © 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Letters Régimbeau, Antoine Budinich, Marko Larhlimi, Abdelhalim Pierella Karlusich, Juan José Aumont, Olivier Memery, Laurent Bowler, Chris Eveillard, Damien Contribution of genome‐scale metabolic modelling to niche theory |
title | Contribution of genome‐scale metabolic modelling to niche theory |
title_full | Contribution of genome‐scale metabolic modelling to niche theory |
title_fullStr | Contribution of genome‐scale metabolic modelling to niche theory |
title_full_unstemmed | Contribution of genome‐scale metabolic modelling to niche theory |
title_short | Contribution of genome‐scale metabolic modelling to niche theory |
title_sort | contribution of genome‐scale metabolic modelling to niche theory |
topic | Letters |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324083/ https://www.ncbi.nlm.nih.gov/pubmed/35384214 http://dx.doi.org/10.1111/ele.13954 |
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