A Profile Hidden Markov Model to investigate the distribution and frequency of LanB-encoding lantibiotic modification genes in the human oral and gut microbiome

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dc.contributor.author Walsh, Calum J.
dc.contributor.author Guinane, Caitriona M.
dc.contributor.author O'Toole, Paul W.
dc.contributor.author Cotter, Paul D.
dc.date.accessioned 2017-05-11T10:57:12Z
dc.date.available 2017-05-11T10:57:12Z
dc.date.issued 2017-04-27
dc.identifier.citation Walsh, C. J., Guinane, C. M., O’Toole, P.W. and Cotter, P. D. (2017) ‘A Profile Hidden Markov Model to investigate the distribution and frequency of LanB-encoding lantibiotic modification genes in the human oral and gut microbiome’, PeerJ, 5:e3254 (19 pp). doi:10.7717/peerj.3254 en
dc.identifier.volume 5 en
dc.identifier.startpage 1 en
dc.identifier.endpage 19 en
dc.identifier.issn 2167-8359
dc.identifier.uri http://hdl.handle.net/10468/3943
dc.identifier.doi 10.7717/peerj.3254
dc.description.abstract Background: The human microbiota plays a key role in health and disease, and bacteriocins, which are small, bacterially produced, antimicrobial peptides, are likely to have an important function in the stability and dynamics of this community. Here we examined the density and distribution of the subclass I lantibiotic modification protein, LanB, in human oral and stool microbiome datasets using a specially constructed profile Hidden Markov Model (HMM). Methods: The model was validated by correctly identifying known lanB genes in the genomes of known bacteriocin producers more effectively than other methods, while being sensitive enough to differentiate between different subclasses of lantibiotic modification proteins. This approach was compared with two existing methods to screen both genomic and metagenomic datasets obtained from the Human Microbiome Project (HMP). Results: Of the methods evaluated, the new profile HMM identified the greatest number of putative LanB proteins in the stool and oral metagenome data while BlastP identified the fewest. In addition, the model identified more LanB proteins than a pre-existing Pfam lanthionine dehydratase model. Searching the gastrointestinal tract subset of the HMP reference genome database with the new HMM identified seven putative subclass I lantibiotic producers, including two members of the Coprobacillus genus. Conclusions: These findings establish custom profile HMMs as a potentially powerful tool in the search for novel bioactive producers with the power to benefit human health, and reinforce the repertoire of apparent bacteriocin-encoding gene clusters that may have been overlooked by culture-dependent mining efforts to date. en
dc.description.sponsorship Science Foundation Ireland (SFI Grant Number 11/PI/1137) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher PeerJ en
dc.rights © 2017, Walsh et al. Distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. en
dc.rights.uri https://creativecommons.org/licenses/by/4.0/ en
dc.subject Hidden Markov Model en
dc.subject Lantibiotic en
dc.subject Bacteriocin en
dc.subject Metagenomic en
dc.subject Microbiota en
dc.title A Profile Hidden Markov Model to investigate the distribution and frequency of LanB-encoding lantibiotic modification genes in the human oral and gut microbiome en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Paul O'Toole, Microbiology, University College Cork, Cork, Ireland. +353-21-490-3000 Email: pwotoole@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2017-05-11T10:43:21Z
dc.description.version Published Version en
dc.internal.rssid 394616040
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.identifier.journaltitle PeerJ en
dc.internal.copyrightchecked Yes en
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress pwotoole@ucc.ie en
dc.identifier.articleid e3254


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© 2017, Walsh et al. Distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Except where otherwise noted, this item's license is described as © 2017, Walsh et al. Distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.
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