Literature DB >> 34580430

Macroecological distributions of gene variants highlight the functional organization of soil microbial systems.

Arthur Escalas1,2, Fabiana S Paula3, François Guilhaumon4,5, Mengting Yuan6, Yunfeng Yang7, Linwei Wu8, Feifei Liu8,9,10, Jiaje Feng8, Yuguang Zhang11, Jizhong Zhou8,7,12,13.   

Abstract

The recent application of macroecological tools and concepts has made it possible to identify consistent patterns in the distribution of microbial biodiversity, which greatly improved our understanding of the microbial world at large scales. However, the distribution of microbial functions remains largely uncharted from the macroecological point of view. Here, we used macroecological models to examine how the genes encoding the functional capabilities of microorganisms are distributed within and across soil systems. Models built using functional gene array data from 818 soil microbial communities showed that the occupancy-frequency distributions of genes were bimodal in every studied site, and that their rank-abundance distributions were best described by a lognormal model. In addition, the relationships between gene occupancy and abundance were positive in all sites. This allowed us to identify genes with high abundance and ubiquitous distribution (core) and genes with low abundance and limited spatial distribution (satellites), and to show that they encode different sets of microbial traits. Common genes encode microbial traits related to the main biogeochemical cycles (C, N, P and S) while rare genes encode traits related to adaptation to environmental stresses, such as nutrient limitation, resistance to heavy metals and degradation of xenobiotics. Overall, this study characterized for the first time the distribution of microbial functional genes within soil systems, and highlight the interest of macroecological models for understanding the functional organization of microbial systems across spatial scales.
© 2021. The Author(s), under exclusive licence to International Society for Microbial Ecology.

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Year:  2021        PMID: 34580430      PMCID: PMC8857198          DOI: 10.1038/s41396-021-01120-8

Source DB:  PubMed          Journal:  ISME J        ISSN: 1751-7362            Impact factor:   10.302


  52 in total

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