Using network analysis to explore co-occurrence patterns in soil microbial communities View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2012-02

AUTHORS

Albert Barberán, Scott T Bates, Emilio O Casamayor, Noah Fierer

ABSTRACT

Exploring large environmental datasets generated by high-throughput DNA sequencing technologies requires new analytical approaches to move beyond the basic inventory descriptions of the composition and diversity of natural microbial communities. In order to investigate potential interactions between microbial taxa, network analysis of significant taxon co-occurrence patterns may help to decipher the structure of complex microbial communities across spatial or temporal gradients. Here, we calculated associations between microbial taxa and applied network analysis approaches to a 16S rRNA gene barcoded pyrosequencing dataset containing >160 000 bacterial and archaeal sequences from 151 soil samples from a broad range of ecosystem types. We described the topology of the resulting network and defined operational taxonomic unit categories based on abundance and occupancy (that is, habitat generalists and habitat specialists). Co-occurrence patterns were readily revealed, including general non-random association, common life history strategies at broad taxonomic levels and unexpected relationships between community members. Overall, we demonstrated the potential of exploring inter-taxa correlations to gain a more integrated understanding of microbial community structure and the ecological rules guiding community assembly. More... »

PAGES

ismej2011119

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/ismej.2011.119

    DOI

    http://dx.doi.org/10.1038/ismej.2011.119

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1039602901

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/21900968


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    RDF/XML is a standard XML format for linked data.

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