COREMIC: a web-tool to search for a niche associated CORE MICrobiome

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dc.contributor.authorRodrigues, Richard R.en
dc.contributor.authorRodgers, Nyle C.en
dc.contributor.authorWu, Xiaoweien
dc.contributor.authorWilliams, Mark A.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.contributor.departmentStatisticsen
dc.contributor.departmentFralin Life Sciences Instituteen
dc.contributor.departmentSchool of Plant and Environmental Sciencesen
dc.date.accessioned2019-07-24T17:26:15Zen
dc.date.available2019-07-24T17:26:15Zen
dc.date.issued2018-02-15en
dc.description.abstractMicrobial diversity on earth is extraordinary, and soils alone harbor thousands of species per, gram of soil. Understanding how this diversity is sorted and selected into habitat niches is a major focus of ecology and biotechnology but remains only vaguely understood. A systems-biology approach was used to mine information from databases to show how it can be used to answer questions related to the core microbiome of habitat-microbe relationships. By making use of the burgeoning growth of information from databases, our tool "COREMIC" meets a great need in the search for understanding niche partitioning and habitat-function relationships. The work is unique, furthermore because it provides a user-friendly statistically robust web-tool (hit p://cot eiruc2.appspot.corn or http://corc-mic.com), developed using Google App Engine, to help in the process of database mining to identify the "core microbiome" associated with a given habitat. A case study is presented using data from 31 switchgrass rhizosphere community habitats across a diverse set of soil and sampling environments. The methodology utilizes an outgroup of 28 non-switchgrass (other grasses and forbs) to identify a core switchgrass microbiome. Even across a diverse set of soils (five environments), and conservative statistical criteria (presence in more than 90% samples and FDR q-val <0.05% for Fisher's exact test) a core set of bacteria associated with switchgrass was observed. These included, among others, closely related taxa from Lysobacter spp., Mesorhizobium spp, and Chitinophagaceae. These bacteria have been shown to have functions related to the production of bacterial and fungal antibiotics and plant growth promotion. COREMIC can be used as a hypothesis generating or confirmatory tool that shows great potential for identifying taxa that may be irnportant to the functioning of a habitat (e.g. host plant). The case study, in conclusion, shows that COREMIC can identify key habitat-specific microbes across diverse samples, using currently available databases and a unique freely available software.en
dc.description.notesVirginia Tech's Genetics, Bioinformatics, and Computational Biology, Department of Horticulture provided personnel funding. Research was also partially funded by grants from USDA-NIFA (2011-03815). There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
dc.description.sponsorshipVirginia Tech's Genetics, Bioinformatics, and Computational Biology, Department of Horticultureen
dc.description.sponsorshipUSDA-NIFA [2011-03815]en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.7717/peerj.4395en
dc.identifier.issn2167-8359en
dc.identifier.othere4395en
dc.identifier.pmid29473009en
dc.identifier.urihttp://hdl.handle.net/10919/91979en
dc.identifier.volume6en
dc.language.isoenen
dc.publisherPeerJen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectRoot-zoneen
dc.subjectWeb-toolen
dc.subjectMeta-analysisen
dc.subjectDatabaseen
dc.subjectRhizosphereen
dc.subjectData miningen
dc.subjectAppen
dc.subjectSoftwareen
dc.subjectMicrobiomeen
dc.titleCOREMIC: a web-tool to search for a niche associated CORE MICrobiomeen
dc.title.serialPeerJen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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Scholarly Works, Electrical and Computer Engineering
Scholarly Works, Fralin Life Sciences Institute
Scholarly Works, School of Plant and Environmental Sciences
Scholarly Works, Statistics