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2019-07-23Zeitschriftenartikel DOI: 10.25646/6292
Where did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisation
dc.contributor.authorSeiler, Enrico
dc.contributor.authorTrappe, Kathrin
dc.contributor.authorRenard, Bernhard Y.
dc.date.accessioned2019-09-20T10:18:18Z
dc.date.available2019-09-20T10:18:18Z
dc.date.issued2019-07-23none
dc.identifier.other10.1371/journal.pcbi.1007208
dc.identifier.urihttp://edoc.rki.de/176904/6306
dc.description.abstractAbstract Horizontal gene transfer (HGT) has changed the way we regard evolution. Instead of waiting for the next generation to establish new traits, especially bacteria are able to take a shortcut via HGT that enables them to pass on genes from one individual to another, even across species boundaries. The tool Daisy offers the first HGT detection approach based on read mapping that provides complementary evidence compared to existing methods. However, Daisy relies on the acceptor and donor organism involved in the HGT being known. We introduce DaisyGPS, a mapping-based pipeline that is able to identify acceptor and donor reference candidates of an HGT event based on sequencing reads. Acceptor and donor identification is akin to species identification in metagenomic samples based on sequencing reads, a problem addressed by metagenomic profiling tools. However, acceptor and donor references have certain properties such that these methods cannot be directly applied. DaisyGPS uses MicrobeGPS, a metagenomic profiling tool tailored towards estimating the genomic distance between organisms in the sample and the reference database. We enhance the underlying scoring system of MicrobeGPS to account for the sequence patterns in terms of mapping coverage of an acceptor and donor involved in an HGT event, and report a ranked list of reference candidates. These candidates can then be further evaluated by tools like Daisy to establish HGT regions. We successfully validated our approach on both simulated and real data, and show its benefits in an investigation of an outbreak involving Methicillin-resistant Staphylococcus aureus data. Author summary Evolution is traditionally viewed as a process where changes are only vertically inherited from parent to offspring across generations. Many principles such as phylogenetic trees and even the “tree of life” are based on that doctrine. The concept of horizontal gene transfer changed the way we regard evolution completely. Horizontal gene transfer is the movement of genetic information between distantly related organisms of the same generation. Genome sequencing not only provided further evidence complementing experimental evidence but also shed light onto the frequency and prominence of this concept. Especially the rapid spread of antimicrobial resistance genes is a prominent example for the impact that horizontal gene transfer can have for public health. Next generation sequencing brought means for quick and relatively cheap analysis of even complex metagenomic samples where horizontal gene transfer is bound to happen frequently. Methods to directly detect and characterise horizontal gene transfer from such sequencing data, however, are still lacking. We here provide a method to identify organisms potentially involved in horizontal gene transfer events to be used in downstream analysis that enables a characterisation of a horizontal gene transfer event in terms of impact and prevalence.ger
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC BY 3.0 DE) Namensnennung 3.0 Deutschlandger
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titleWhere did you come from, where did you go: Refining metagenomic analysis tools for horizontal gene transfer characterisationnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:0257-176904/6306-1
dc.identifier.doihttp://dx.doi.org/10.25646/6292
dc.type.versionpublishedVersionnone
local.edoc.container-titlePLoS Computational Biologynone
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttps://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007208none
local.edoc.container-publisher-namePublic Library of Sciencenone
local.edoc.container-volume15none
local.edoc.container-issue7none
local.edoc.container-reportyear2019none
local.edoc.container-year2019none
local.edoc.container-firstpage1none
local.edoc.container-lastpage26none
local.edoc.rki-departmentMethodenentwicklung und Forschungsinfrastrukturnone
dc.description.versionPeer Reviewednone

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