Whole genome sequencing versus traditional genotyping for investigation of a Mycobacterium tuberculosis outbreak: a longitudinal molecular epidemiological study

Abstract

Background: Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains.

Methods and findings: During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed "Hamburg clone") started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance.

Conclusions: Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context.

Figure 1. Minimum spanning tree analysis.

Minimum spanning tree allowing hypothetical nodes of the Mtb outbreak in Hamburg and Schleswig-Holstein. The year of isolation is coded by color. HH, Hanseatic City of Hamburg; SH, Schleswig-Holstein. Asterisk indicates the root of the tree determined through comparison with an outgroup (H37Rv).

Figure 2. Contact tracing analysis.

Contact tracing data received from health authorities as mapped on the minimum spanning tree shown in Figure 1. Identified transmission chains were termed G1 to G8 (right panel), and information about nationality (N), being part of the bar milieu (M; black boxes indicate “yes”), residential situation (R; white boxes indicate homeless persons), alcoholism (A; black boxes indicate “yes”), and drug abuse (D; black boxes indicate “yes”) are included. Different SNP patterns are indicated in the right panel. Identical patterns within single transmission chains were marked with 0. DE, Germany; PL, Poland; TR,Turkey.

Figure 3. Spread of the Mtb outbreak in Hamburg and Schleswig-Holstein.

(A) Members of this outbreak have been continuously isolated over the past 14 y. Isolates of the two distinguishable parts, the “Hamburg clone” and the remaining unsuccessful strains, are shown. Black arrows indicate the first isolations of strains at different sites in Schleswig-Holstein in 2006 (Kiel [K]) and 2010 (Pinneberg [P]). (B) Time course of the Mtb cases and their least-squares regressions. Upper and bottom plots correspond to the Hamburg clone and unsuccessful strains, as shown in (A). Solid and dotted lines represent calculated regression lines and 95% confidence interval boundaries, respectively. Note that both the Hamburg clone and the unrelated strains did not significantly depart from linear growth on this temporal scale, implying that selection coefficients during the epidemic were fairly constant. (C) Explored environmental settings were mapped on the minimum spanning trees shown in Figure 1.