Large-scale whole genome sequencing of M. tuberculosis provides insights into transmission in a high prevalence area

Abstract

To improve understanding of the factors influencing tuberculosis transmission and the role of pathogen variation, we sequenced all available specimens from patients diagnosed over 15 years in a whole district in Malawi. Mycobacterium tuberculosis lineages were assigned and transmission networks constructed, allowing ≤10 single nucleotide polymorphisms (SNPs) difference. We defined disease as due to recent infection if the network-determined source was within 5 years, and assessed transmissibility from forward transmissions resulting in disease. High-quality sequences were available for 1687 disease episodes (72% of all culture-positive episodes): 66% of patients linked to at least one other patient. The between-patient mutation rate was 0.26 SNPs/year (95% CI 0.21–0.31). We showed striking differences by lineage in the proportion of disease due to recent transmission and in transmissibility (highest for lineage-2 and lowest for lineage-1) that were not confounded by immigration, HIV status or drug resistance. Transmissions resulting in disease decreased markedly over time.DOI: http://dx.doi.org/10.7554/eLife.05166.001

The epidemiology, pathogenesis, transmission, diagnosis, and management of multidrug-resistant, extensively drug-resistant, and incurable tuberculosis

“…First, on a population basis, strain typing identifies strain relatedness, thus identifying chains of transmission (a cluster of isolates with identical genotypes according to IS6110 DNA fingerprinting, 44 mycobacterial inter spersed repetitive units-variable numbers of tandem repeat [MIRU-VNTR] typing, 45 or whole-genome sequencing; 46 figure 2) and providing an indication of how well a tuberculosis control programme functions with respect to transmission control. 47,48 High clustering of drug-resistant tuberculosis strains is indicative of high levels of transmission, which might be because of the absence of appropriate case detection and diagnosis-associated delays (and hence treatment delays).…”

“…53 When using whole-genome sequencing, two isolates differing by several SNPs (commonly ≤10 SNPs) are hypothesised to reflect transmission provided resistance-conferring SNPs are identical (although additional resistance-conferring mutations might be present, reflecting amplification of resistance). 46 Unique Drug-resistant isolates with unique IS6110 RFLP banding patterns, spoligotype patterns, or MIRU-VNTR types, and drug-resistant isolates with identical IS6110 RFLP banding patterns, spoligotype patterns, or MIRU-VNTR types but different mutations conferring resistance, reflect the acquisition of drug resistance (ie, secondary resistance). 49 Similarly, isolates whose whole genome sequences differ by more than ten SNPs are interpreted to reflect the acquisition of resistance or reactivation of a previous drug-resistant tuberculosis infection or influx from a different community (migration).…”

“…137,138 As with other typing methods, transmission of M tuberculosis strains is measured by the relatedness of each strain's whole-genome sequencing results. Recent reports have suggested that strains differing by less than 10 single nucleotide variations reflect transmission 46,74,137,139,140 (figure 4). Deciphering tuberculosis transmission dynamics is crucial for the optimisation of local and global control measures and the early detection of MDR and XDR outbreaks.…”

Whole-genome sequencing identifies nosocomial transmission of extra-pulmonary M. tuberculosis

“…According to this paradigm pulmonary smear positive disease is considered more infectious than smear negative disease, 2 whereas extra-pulmonary disease, which should not generate droplet nuclei, is not considered infectious. To monitor tuberculosis transmission in Oxfordshire, UK, we have been prospectively whole-genome sequencing (WGS) all clinical M. tuberculosis isolates since 2011, and retrospectively to 2007 3 .…”

Genomic Analysis of Bacterial Outbreaks

“…One of these factors is mixed infections. The true extent of co-infections in high-burden countries is not clear and there is hope that whole genome data can distinguish between relapses and re-infections (Bryant et al, 2013a;Guerra-Assunção et al, 2015). This issue is critical to delineate transmission in high burden countries but also for clinical trials investigations because relapse is one of the end points of those investigations.…”