Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community

As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biologic...

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Published in:PLoS ONE
Main Authors: Xu, Zhuofei, Hansen, Martin Asser, Hansen, Lars H., Jacquiod, Samuel, Sørensen, Søren J.
Format: Text
Language:English
Published: Public Library of Science 2014
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972102
http://www.ncbi.nlm.nih.gov/pubmed/24691166
https://doi.org/10.1371/journal.pone.0093445
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spelling ftpubmed:oai:pubmedcentral.nih.gov:3972102 2023-05-15T15:05:14+02:00 Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community Xu, Zhuofei Hansen, Martin Asser Hansen, Lars H. Jacquiod, Samuel Sørensen, Søren J. 2014-04-01 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972102 http://www.ncbi.nlm.nih.gov/pubmed/24691166 https://doi.org/10.1371/journal.pone.0093445 en eng Public Library of Science http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972102 http://www.ncbi.nlm.nih.gov/pubmed/24691166 http://dx.doi.org/10.1371/journal.pone.0093445 This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. CC-BY Research Article Text 2014 ftpubmed https://doi.org/10.1371/journal.pone.0093445 2014-04-06T01:20:34Z As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function. Text Arctic PubMed Central (PMC) Arctic PLoS ONE 9 4 e93445
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Research Article
spellingShingle Research Article
Xu, Zhuofei
Hansen, Martin Asser
Hansen, Lars H.
Jacquiod, Samuel
Sørensen, Søren J.
Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
topic_facet Research Article
description As is well known, soil is a complex ecosystem harboring the most prokaryotic biodiversity on the Earth. In recent years, the advent of high-throughput sequencing techniques has greatly facilitated the progress of soil ecological studies. However, how to effectively understand the underlying biological features of large-scale sequencing data is a new challenge. In the present study, we used 33 publicly available metagenomes from diverse soil sites (i.e. grassland, forest soil, desert, Arctic soil, and mangrove sediment) and integrated some state-of-the-art computational tools to explore the phylogenetic and functional characterizations of the microbial communities in soil. Microbial composition and metabolic potential in soils were comprehensively illustrated at the metagenomic level. A spectrum of metagenomic biomarkers containing 46 taxa and 33 metabolic modules were detected to be significantly differential that could be used as indicators to distinguish at least one of five soil communities. The co-occurrence associations between complex microbial compositions and functions were inferred by network-based approaches. Our results together with the established bioinformatic pipelines should provide a foundation for future research into the relation between soil biodiversity and ecosystem function.
format Text
author Xu, Zhuofei
Hansen, Martin Asser
Hansen, Lars H.
Jacquiod, Samuel
Sørensen, Søren J.
author_facet Xu, Zhuofei
Hansen, Martin Asser
Hansen, Lars H.
Jacquiod, Samuel
Sørensen, Søren J.
author_sort Xu, Zhuofei
title Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
title_short Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
title_full Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
title_fullStr Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
title_full_unstemmed Bioinformatic Approaches Reveal Metagenomic Characterization of Soil Microbial Community
title_sort bioinformatic approaches reveal metagenomic characterization of soil microbial community
publisher Public Library of Science
publishDate 2014
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972102
http://www.ncbi.nlm.nih.gov/pubmed/24691166
https://doi.org/10.1371/journal.pone.0093445
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3972102
http://www.ncbi.nlm.nih.gov/pubmed/24691166
http://dx.doi.org/10.1371/journal.pone.0093445
op_rights This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
op_rightsnorm CC-BY
op_doi https://doi.org/10.1371/journal.pone.0093445
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