Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks: a retrospective observational study

Abstract

SummaryBackgroundTuberculosis incidence in the UK has risen in the past decade. Disease control depends on epidemiological data, which can be difficult to obtain. Whole-genome sequencing can detect microevolution within Mycobacterium tuberculosis strains. We aimed to estimate the genetic diversity of related M tuberculosis strains in the UK Midlands and to investigate how this measurement might be used to investigate community outbreaks.MethodsIn a retrospective observational study, we used Illumina technology to sequence M tuberculosis genomes from an archive of frozen cultures. We characterised isolates into four groups: cross-sectional, longitudinal, household, and community. We measured pairwise nucleotide differences within hosts and between hosts in household outbreaks and estimated the rate of change in DNA sequences. We used the findings to interpret network diagrams constructed from 11 community clusters derived from mycobacterial interspersed repetitive-unit–variable-number tandem-repeat data.FindingsWe sequenced 390 separate isolates from 254 patients, including representatives from all five major lineages of M tuberculosis. The estimated rate of change in DNA sequences was 0·5 single nucleotide polymorphisms (SNPs) per genome per year (95% CI 0·3–0·7) in longitudinal isolates from 30 individuals and 25 families. Divergence is rarely higher than five SNPs in 3 years. 109 (96%) of 114 paired isolates from individuals and households differed by five or fewer SNPs. More than five SNPs separated isolates from none of 69 epidemiologically linked patients, two (15%) of 13 possibly linked patients, and 13 (17%) of 75 epidemiologically unlinked patients (three-way comparison exact p<0·0001). Genetic trees and clinical and epidemiological data suggest that super-spreaders were present in two community clusters.InterpretationWhole-genome sequencing can delineate outbreaks of tuberculosis and allows inference about direction of transmission between cases. The technique could identify super-spreaders and predict the existence of undiagnosed cases, potentially leading to early treatment of infectious patients and their contacts.FundingMedical Research Council, Wellcome Trust, National Institute for Health Research, and the Health Protection Agency.

Substantial molecular evolution and mutation rates in prolonged latent Mycobacterium tuberculosis infection in humans

“…Thus, we find an average molecular clock rate of 0.2 -0.3 SNPs per genome per year. Interestingly, this compares quite well to rates of mutation acquisition observed previously in Lineage 4, both in vitro (Ford et al, 2011;Ford et al, 2013) and in several independent retrospective outbreak studies (Eldholm et al, 2015;Guerra-Assuncao et al, 2015;Walker et al, 2013). While current models of Mtb during latency assume that there is little or no growth or mutation of the infecting bacteria, a recent in vitro study using a macaque model has provided evidence that Mtb mutates at a fixed rate over time, and that mutation rates are comparable between latent and active disease (Ford et al, 2011).…”

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

“…SNP=single-nucleotide polymorphism. [74][75][76][77][78] Comprehensive analysis of the genome of the pathogen Requires culture (or specimen enrichment); more expensive; might be computationally demanding or complex Identification of transmission chains, mutations conferring resistance, heteroresistance (low resolution), mixed infections, specimen heterogeneity, and intrapatient evolution 82,85,90 ahpC, 93 and 16S rRNA. 94 Highly transmissible MDR outbreak clones with specific combinations of low-cost resistance and compensatory mutations have already emerged in several areas of the world.…”

“…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.…”

Insights into the processes that drive the evolution of drug resistance in Mycobacterium tuberculosis

“…Mycobacterium tuberculosis is characterized by a low mutation rate (about 2 × 10 −10 mutations/bp/generation) (Ford et al., 2011), with an estimated evolutionary rate of 0.4—0.5 single nucleotide polymorphisms (SNPs)/genome/year and a divergence rarely higher than five SNPs in 3 years (Roetzer et al., 2013; Walker et al., 2013). Despite this low mutation rate, the number of drug resistant, especially MDR and XDR TB cases, due to the acquisition of mutations, is progressively increasing worldwide.…”