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Growth rate is a dominant factor predicting the rhizosphere effect
The root microbiome is shaped by plant root activity, which selects specific microbial taxa from the surrounding soil. This influence on the microorganisms and soil chemistry in the immediate vicinity of the roots has been referred to as the rhizosphere effect. Understanding the traits that make bac...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432406/ https://www.ncbi.nlm.nih.gov/pubmed/37322285 http://dx.doi.org/10.1038/s41396-023-01453-6 |
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author | López, José L. Fourie, Arista Poppeliers, Sanne W. M. Pappas, Nikolaos Sánchez-Gil, Juan J. de Jonge, Ronnie Dutilh, Bas E. |
author_facet | López, José L. Fourie, Arista Poppeliers, Sanne W. M. Pappas, Nikolaos Sánchez-Gil, Juan J. de Jonge, Ronnie Dutilh, Bas E. |
author_sort | López, José L. |
collection | PubMed |
description | The root microbiome is shaped by plant root activity, which selects specific microbial taxa from the surrounding soil. This influence on the microorganisms and soil chemistry in the immediate vicinity of the roots has been referred to as the rhizosphere effect. Understanding the traits that make bacteria successful in the rhizosphere is critical for developing sustainable agriculture solutions. In this study, we compared the growth rate potential, a complex trait that can be predicted from bacterial genome sequences, to functional traits encoded by proteins. We analyzed 84 paired rhizosphere- and soil-derived 16S rRNA gene amplicon datasets from 18 different plants and soil types, performed differential abundance analysis, and estimated growth rates for each bacterial genus. We found that bacteria with higher growth rate potential consistently dominated the rhizosphere, and this trend was confirmed in different bacterial phyla using genome sequences of 3270 bacterial isolates and 6707 metagenome-assembled genomes (MAGs) from 1121 plant- and soil-associated metagenomes. We then identified which functional traits were enriched in MAGs according to their niche or growth rate status. We found that predicted growth rate potential was the main feature for differentiating rhizosphere and soil bacteria in machine learning models, and we then analyzed the features that were important for achieving faster growth rates, which makes bacteria more competitive in the rhizosphere. As growth rate potential can be predicted from genomic data, this work has implications for understanding bacterial community assembly in the rhizosphere, where many uncultivated bacteria reside. |
format | Online Article Text |
id | pubmed-10432406 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104324062023-08-18 Growth rate is a dominant factor predicting the rhizosphere effect López, José L. Fourie, Arista Poppeliers, Sanne W. M. Pappas, Nikolaos Sánchez-Gil, Juan J. de Jonge, Ronnie Dutilh, Bas E. ISME J Article The root microbiome is shaped by plant root activity, which selects specific microbial taxa from the surrounding soil. This influence on the microorganisms and soil chemistry in the immediate vicinity of the roots has been referred to as the rhizosphere effect. Understanding the traits that make bacteria successful in the rhizosphere is critical for developing sustainable agriculture solutions. In this study, we compared the growth rate potential, a complex trait that can be predicted from bacterial genome sequences, to functional traits encoded by proteins. We analyzed 84 paired rhizosphere- and soil-derived 16S rRNA gene amplicon datasets from 18 different plants and soil types, performed differential abundance analysis, and estimated growth rates for each bacterial genus. We found that bacteria with higher growth rate potential consistently dominated the rhizosphere, and this trend was confirmed in different bacterial phyla using genome sequences of 3270 bacterial isolates and 6707 metagenome-assembled genomes (MAGs) from 1121 plant- and soil-associated metagenomes. We then identified which functional traits were enriched in MAGs according to their niche or growth rate status. We found that predicted growth rate potential was the main feature for differentiating rhizosphere and soil bacteria in machine learning models, and we then analyzed the features that were important for achieving faster growth rates, which makes bacteria more competitive in the rhizosphere. As growth rate potential can be predicted from genomic data, this work has implications for understanding bacterial community assembly in the rhizosphere, where many uncultivated bacteria reside. Nature Publishing Group UK 2023-06-15 2023-09 /pmc/articles/PMC10432406/ /pubmed/37322285 http://dx.doi.org/10.1038/s41396-023-01453-6 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article López, José L. Fourie, Arista Poppeliers, Sanne W. M. Pappas, Nikolaos Sánchez-Gil, Juan J. de Jonge, Ronnie Dutilh, Bas E. Growth rate is a dominant factor predicting the rhizosphere effect |
title | Growth rate is a dominant factor predicting the rhizosphere effect |
title_full | Growth rate is a dominant factor predicting the rhizosphere effect |
title_fullStr | Growth rate is a dominant factor predicting the rhizosphere effect |
title_full_unstemmed | Growth rate is a dominant factor predicting the rhizosphere effect |
title_short | Growth rate is a dominant factor predicting the rhizosphere effect |
title_sort | growth rate is a dominant factor predicting the rhizosphere effect |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432406/ https://www.ncbi.nlm.nih.gov/pubmed/37322285 http://dx.doi.org/10.1038/s41396-023-01453-6 |
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