Evidence map›Paper›PMID 34580430›Full record

ArticleThe ISME journal2022

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

Arthur Escalas, Fabiana S Paula, François Guilhaumon, Mengting Yuan, Yunfeng Yang, Linwei Wu, Feifei Liu, Jiaje Feng, Yuguang Zhang, Jizhong Zhou

Open access · bronzeAbstract read
In one paragraph

Article in The ISME journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
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  8. Microbial Journey: Mount Everest to Mars.Indian journal of microbiology · 2022
    Review
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 8 institutions in 4 countries.

Arthur EscalasMARBEC, Montpellier University-CNRS-IRD-IFREMER, Place Eugène Bataillon, Cedex 5, 34095, Montpellier, France. arthur.escalas@gmail.com.ORCID http://orcid.org/0000-0002-6450-5716
Fabiana S PaulaOceanographic Institute, University of São Paulo, São Paulo, 05508-120, Brazil.
François GuilhaumonMARBEC, Montpellier University-CNRS-IRD-IFREMER, Place Eugène Bataillon, Cedex 5, 34095, Montpellier, France.
Mengting YuanDepartment of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA, 94704.ORCID http://orcid.org/0000-0003-0017-3908
Yunfeng YangState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, 100084, Beijing, China.ORCID http://orcid.org/0000-0001-8274-6196
Linwei WuInstitute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, 73019, USA.
Feifei LiuInstitute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, 73019, USA.ORCID http://orcid.org/0000-0003-1966-8759
Jiaje FengInstitute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, 73019, USA.
Yuguang ZhangResearch Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, and the Key Laboratory of Biological Conservation of National Forestry and Grassland Administration, 100091, Beijing, China.ORCID http://orcid.org/0000-0001-9801-8556
Jizhong ZhouInstitute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, 73019, USA.ORCID http://orcid.org/0000-0003-2014-0564
Centre National de la Recherche Scientifique · FRUniversity of Oklahoma · USChinese Academy of Forestry · CNGuangdong Academy of Sciences · CNLawrence Berkeley National Laboratory · USState Key Joint Laboratory of Environment Simulation and Pollution Control · CNUniversidade de São Paulo · BRUniversity of California, Berkeley · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

MicrobiotaSoilBiodiversitySoil MicrobiologySoil

Identifiers

PMID34580430
PMCPMC8857198
OpenAlexW3203509868

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.