Abstract
BackgroundTracking 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.MethodsThis 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.FindingsOur 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.InterpretationWith 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.
Highlights
Despite the large global efforts at curbing the spread of Mycobacterium tuberculosis complex (Mtbc) strains, 10.4 million new patients develop tuberculosis (TB) every year [1]
Bayesian phylodynamic dating approaches implemented in BEAST-2 [34] were utilised to assign timespans to the transmission events estimated by each genotyping method
To get a better understanding of the discriminatory power of different classical genotyping techniques and whole genome sequence (WGS)-based approaches in relation to outbreak timing, this study has performed an in-depth comparison of clustering rates and dated phylogenies obtained in a collection of 324 Mtbc strains from a high incidence setting (Kinshasa, Democratic Republic of Congo (DRC))
Summary
Despite the large global efforts at curbing the spread of Mycobacterium tuberculosis complex (Mtbc) strains, 10.4 million new patients develop tuberculosis (TB) every year [1]. The tracking and timing of recent transmission chains allows TB control programs to effectively pinpoint transmission hotspots and employ targeted intervention measures. 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. 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
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