MorlonOConnorBryantEtAl2015

Reference

Morlon, H., O'Connor, T.K., Bryant, J.A., Charkoudian, L.K., Docherty, K.M., Jones, E., Kembel, S.W., Green, J.L., Bohannan, B.J.M. (2015) The biogeography of putative microbial antibiotic production. PLoS ONE, 10(6). (Scopus )

Abstract

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. © 2015 Morlon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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@ARTICLE { MorlonOConnorBryantEtAl2015,
    AUTHOR = { Morlon, H. and O'Connor, T.K. and Bryant, J.A. and Charkoudian, L.K. and Docherty, K.M. and Jones, E. and Kembel, S.W. and Green, J.L. and Bohannan, B.J.M. },
    TITLE = { The biogeography of putative microbial antibiotic production },
    JOURNAL = { PLoS ONE },
    YEAR = { 2015 },
    VOLUME = { 10 },
    NUMBER = { 6 },
    NOTE = { cited By 0 },
    ABSTRACT = { Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. © 2015 Morlon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. },
    ART_NUMBER = { e0130659 },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1371/journal.pone.0130659 },
    KEYWORDS = { Hexapoda; Magnoliophyta },
    SOURCE = { Scopus },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-84939125997&partnerID=40&md5=5a905de7a799b406349cade687d50c11 },
}

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