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Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms

Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-deri...

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Autores principales: Hessler, Tomas, Huddy, Robert J., Sachdeva, Rohan, Lei, Shufei, Harrison, Susan T. L., Diamond, Spencer, Banfield, Jillian F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10409787/
https://www.ncbi.nlm.nih.gov/pubmed/37553333
http://dx.doi.org/10.1038/s41467-023-40360-4
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author Hessler, Tomas
Huddy, Robert J.
Sachdeva, Rohan
Lei, Shufei
Harrison, Susan T. L.
Diamond, Spencer
Banfield, Jillian F.
author_facet Hessler, Tomas
Huddy, Robert J.
Sachdeva, Rohan
Lei, Shufei
Harrison, Susan T. L.
Diamond, Spencer
Banfield, Jillian F.
author_sort Hessler, Tomas
collection PubMed
description Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-derived laboratory microbial consortia grown under dozens of conditions. The network is overlaid with metagenomic information about functional capacities to generate testable hypotheses. We develop a metric to predict the importance of each node within its local network environments relative to correlated vitamin auxotrophs, and predict that a Variovorax species is a hub as an important source of thiamine. Quantification of thiamine during the growth of Variovorax in minimal media show high levels of thiamine production, up to 100 mg/L. A few of the correlated thiamine auxotrophs are predicted to produce pantothenate, which we show is required for growth of Variovorax, supporting that a subset of vitamin-dependent interactions are mutualistic. A Cryptococcus yeast produces the B-vitamin pantothenate, and co-culturing with Variovorax leads to a 90-130-fold fitness increase for both organisms. Our study demonstrates the predictive power of metagenome-informed, microbial consortia-based network analyses for identifying microbial interactions that underpin the structure and functioning of microbial communities.
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spelling pubmed-104097872023-08-10 Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms Hessler, Tomas Huddy, Robert J. Sachdeva, Rohan Lei, Shufei Harrison, Susan T. L. Diamond, Spencer Banfield, Jillian F. Nat Commun Article Metagenomic or metabarcoding data are often used to predict microbial interactions in complex communities, but these predictions are rarely explored experimentally. Here, we use an organism abundance correlation network to investigate factors that control community organization in mine tailings-derived laboratory microbial consortia grown under dozens of conditions. The network is overlaid with metagenomic information about functional capacities to generate testable hypotheses. We develop a metric to predict the importance of each node within its local network environments relative to correlated vitamin auxotrophs, and predict that a Variovorax species is a hub as an important source of thiamine. Quantification of thiamine during the growth of Variovorax in minimal media show high levels of thiamine production, up to 100 mg/L. A few of the correlated thiamine auxotrophs are predicted to produce pantothenate, which we show is required for growth of Variovorax, supporting that a subset of vitamin-dependent interactions are mutualistic. A Cryptococcus yeast produces the B-vitamin pantothenate, and co-culturing with Variovorax leads to a 90-130-fold fitness increase for both organisms. Our study demonstrates the predictive power of metagenome-informed, microbial consortia-based network analyses for identifying microbial interactions that underpin the structure and functioning of microbial communities. Nature Publishing Group UK 2023-08-08 /pmc/articles/PMC10409787/ /pubmed/37553333 http://dx.doi.org/10.1038/s41467-023-40360-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Hessler, Tomas
Huddy, Robert J.
Sachdeva, Rohan
Lei, Shufei
Harrison, Susan T. L.
Diamond, Spencer
Banfield, Jillian F.
Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
title Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
title_full Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
title_fullStr Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
title_full_unstemmed Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
title_short Vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
title_sort vitamin interdependencies predicted by metagenomics-informed network analyses and validated in microbial community microcosms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10409787/
https://www.ncbi.nlm.nih.gov/pubmed/37553333
http://dx.doi.org/10.1038/s41467-023-40360-4
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