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dc.contributor.authorMeehan, Conor J.
dc.contributor.authorMoris, P.
dc.contributor.authorKohl, T.A.
dc.contributor.authorPečerska, J.
dc.contributor.authorAkter, S.
dc.contributor.authorMerker, M.
dc.contributor.authorUtpatel, C.
dc.contributor.authorBeckert, P.
dc.contributor.authorGehre, F.
dc.contributor.authorLempens, P.
dc.contributor.authorStadler, T.
dc.contributor.authorKaswa, M.K.
dc.contributor.authorKühnert, D.
dc.contributor.authorNiemann, S.
dc.contributor.authorde Jong, B.C.
dc.date.accessioned2020-01-16T10:00:53Z
dc.date.available2020-01-16T10:00:53Z
dc.date.issued2018-11
dc.identifier.citationMeehan CJ, Moris P, Kohl TA et al (2018) The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology. EBioMedicine. 37: 410-416.en_US
dc.identifier.urihttp://hdl.handle.net/10454/17571
dc.descriptionYesen_US
dc.description.abstractBackground: Tracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult. Methods: This study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005–2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated. Findings: Our results suggest that clusters based on Spoligotyping could encompass transmission events that occurred almost 200 years prior to sampling while 24-loci-MIRU-VNTR often represented three decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events, e.g. in timespans of up to 10 years for a 5 SNP/allele cut-off. Interpretation: With the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.en_US
dc.description.sponsorshipERC grant [INTERRUPTB; no. 311725] to BdJ, FG and CJM; an ERC grant to TS [PhyPD; no. 335529]; an FWO PhD fellowship to PM [grant number 1141217N]; the Leibniz Science Campus EvolLUNG for MM and SN; the German Centre for Infection Research (DZIF) for TAK, MM, CU, PB and SN; a SNF SystemsX grant (TBX) to JP and TS and a Marie Heim-Vögtlin fellowship granted to DK by the Swiss National Science Foundation. The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government – department EWI.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1016/j.ebiom.2018.10.013en_US
dc.rights© 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license. (http://creativecommons.org/licenses/by/4.0/).en_US
dc.subjectMycobacterium tuberculosisen_US
dc.subjectMDR-TB molecular epidemiologyen_US
dc.subjectTransmissionen_US
dc.subjectSpoligotypingen_US
dc.subjectMIRU-VNTRen_US
dc.subjectMLSTen_US
dc.subjectWhole genome sequencingen_US
dc.subjectOutbreak detectionen_US
dc.titleThe relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiologyen_US
dc.status.refereedYesen_US
dc.date.Accepted2018-10-03
dc.date.application2018-10-16
dc.typeArticleen_US
dc.type.versionPublished versionen_US
refterms.dateFOA2020-01-16T10:00:53Z


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