PT  - JOURNAL ARTICLE
AU  - Conor J Meehan
AU  - Pieter Moris
AU  - Thomas A. Kohl
AU  - Jūlija Pečerska
AU  - Suriya Akter
AU  - Matthias Merker
AU  - Christian Utpatel
AU  - Patrick Beckert
AU  - Florian Gehre
AU  - Pauline Lempens
AU  - Tanja Stadler
AU  - Michel K. Kaswa
AU  - Denise Kühnert
AU  - Stefan Niemann
AU  - Bouke C de Jong
TI  - The relationship between transmission time and clustering methods in <em>Mycobacterium tuberculosis</em> epidemiology
AID  - 10.1101/302232
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 302232
4099  - http://biorxiv.org/content/early/2018/04/16/302232.short
4100  - http://biorxiv.org/content/early/2018/04/16/302232.full
AB  - Tracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple approaches exist for detecting recent transmission chains, usually by clustering strains based on the similarity of their genotyping results. However, each method gives varying estimates of transmission cluster sizes and inferring when transmission events within these clusters occurred is almost impossible. This study combines whole genome sequence (WGS) data derived from a high endemic setting with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Our results suggest that clusters based on spoligotyping could encompass transmission events that occurred hundreds of years prior to sampling while 24-loci-MIRU-VNTR often represented decades of transmission. Instead, WGS based genotyping applying a low SNP thresholds allows for estimation of recent transmission events. These findings can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period.