Elucidating emergence and transmission of multidrug-resistant tuberculosis in treatment experienced patients by whole genome sequencing

Abstract

Background: Understanding the emergence and spread of multidrug-resistant tuberculosis (MDR-TB) is crucial for its control. MDR-TB in previously treated patients is generally attributed to the selection of drug resistant mutants during inadequate therapy rather than transmission of a resistant strain. Traditional genotyping methods are not sufficient to distinguish strains in populations with a high burden of tuberculosis and it has previously been difficult to assess the degree of transmission in these settings. We have used whole genome analysis to investigate M. tuberculosis strains isolated from treatment experienced patients with MDR-TB in Uganda over a period of four years.

Methods and findings: We used high throughput genome sequencing technology to investigate small polymorphisms and large deletions in 51 Mycobacterium tuberculosis samples from 41 treatment-experienced TB patients attending a TB referral and treatment clinic in Kampala. This was a convenience sample representing 69% of MDR-TB cases identified over the four year period. Low polymorphism was observed in longitudinal samples from individual patients (2-15 SNPs). Clusters of samples with less than 50 SNPs variation were examined. Three clusters comprising a total of 8 patients were found with almost identical genetic profiles, including mutations predictive for resistance to rifampicin and isoniazid, suggesting transmission of MDR-TB. Two patients with previous drug susceptible disease were found to have acquired MDR strains, one of which shared its genotype with an isolate from another patient in the cohort.

Conclusions: Whole genome sequence analysis identified MDR-TB strains that were shared by more than one patient. The transmission of multidrug-resistant disease in this cohort of retreatment patients emphasises the importance of early detection and need for infection control. Consideration should be given to rapid testing for drug resistance in patients undergoing treatment to monitor the emergence of resistance and permit early intervention to avoid onward transmission.

Figure 1. Population structure using SNP and small indel data with tabulated larger deletions.

Clustering dendrogram constructed using R statistical software, based on a pair-wise identity. On average there are 860 SNP alleles and 64 small indels differences between any two isolates. Large deletions were identified using a consensus from paired end mapping distance or split read approaches followed by an assembly-validated strategy using Velvet software[37]. Only deletions considered informative are shown. SIT numbers were assigned in accordance in the international database SITVITWEB[41].

Figure 2. Radial phylogram constructed using SNPs and showing clustered samples.

The best-scoring maximum likelihood phylogenetic tree was constructed using the set of 6,847 SNP sites. Support values computed from 100 bootstrap replicates provide assessment of confidence for each clade and are shown at the nodes of the tree. SNP variations within the clusters are summarised in Table 3.

Figure 3. Episodes of tuberculosis for clustered patients.

D = Date of diagnosis of initial TB episode as self reported by patient; S = date collection of sequenced sample; Black shading = Microbiologically proven TB; Grey shading = Duration of symptoms prior to diagnosis for episode when the sequenced sample was collected, as reported by patient; Bold = strain implicated in transmission of MDR.