Ethics Statement

The AIDS Research Sub-Committee of the Uganda National Council of Science and Technology and the Institutional Review Boards at the University of Medicine and Dentistry of New Jersey and the London School of Hygiene & Tropical Medicine approved the study. All patients provided written consent.

Study population and patients

Uganda is one of 22 countries recognized as having a high burden of TB with an estimated 67,000 incident cases during 2011 [1]. MDR-TB is estimated at 1.4% in new cases (having received less than four weeks of therapy) and 12% in previously treated cases [1]. From July 2003 to April 2007, we conducted a cohort study of 439 previously treated pulmonary TB patients attending the NTLP treatment centre at Mulago Hospital in Kampala, an 85-bed inpatient facility that serves as the national referral centre and the largest TB treatment clinic in Kampala. The study was undertaken prior to the introduction of second line treatment for MDR-TB in Uganda. Data obtained has been presented elsewhere [5,21]. MDR-TB was found in 12.7% of retreatment cases and was the only common risk factor for death during follow-up for both HIV-infected and HIV uninfected patients. No association was observed between HIV positivity and MDR-TB [21]. During the study period fifty four patients had MDR-TB on enrolment and a further 5 were found to have MDR-TB following treatment. Mtb isolates obtained during the study were archived for future investigation. Not all isolates obtained were available for the study due to a lack of storage capacity in the isolating laboratory and samples were not available for 18 (30%) of patients identified as having MDR-TB during the study period.

Sample collection and drug susceptibility testing

We performed whole genome sequencing of a convenience sample of Mtb isolates (n=51) from 41 patients, including samples collected longitudinally from five patients (n=15) (Table 1). The patients had previously received treatment for TB and were presenting with a recurrence either as relapsed cases, treatment failures, or after defaulting treatment. On attending the Mulago Clinic all patients had received the standard WHO-recommended category II retreatment regimen composed of 2 months of streptomycin (S), rifampicin (R), isoniazid (H), ethambutol (E), and pyrazinamide (Z); 1 month of R,H,E and Z; and 5 months of R,H and E (2SRHEZ/1RHEZ/5RHE) [6]. Full treatment records for previous episodes of tuberculosis self-reported by patients were not available. Patients were selected because they were found by phenotypic susceptibility testing to have disease resistant to at least isoniazid and rifampicin, either at enrolment or following treatment.

Mtb isolates obtained by liquid culture were subjected to drug-susceptibility tests for streptomycin, isoniazid, rifampicin, pyrazinamide and ofloxacin using BACTEC 460 or MGIT 960 testing systems [22] at critical concentrations of 1, 0.1, 1.0, 100 µg/mL and 2 mg/mL respectively. Ethambutol was tested at 2.5 ug/ml in BACTEC 460 and 5 ug/ml in the MGIT 960. Isolates that were resistant to isoniazid and rifampicin were further tested for resistance to second-line drugs. Capreomycin, kanamycin, ethionamide, and para-aminosalicylic acid were tested using the Middlebrook 7H10 agar proportion method at critical concentrations of 10, 5, 5, and 2 mg/mL, respectively. After identification Mtb isolates were subcultured and aliquots stored frozen at minus 80°C prior to shipping to the LSHTM where they were subcultured on Lowenstein Jensen slopes. DNA for sequencing was extracted using the Bilthoven RFLP protocol[23]. Mtb grown on LJ slopes was treated with lysozyme, sodium dodecyl sulphate, proteinase K, N-cetyl-N,N,N-trimethyl ammonium bromide (CTAB) and chloroform-isoamyl alcohol prior to precipitation with isopropanol.

Sequencing and genetic variant analysis

Samples were subjected to whole genome sequencing and spoligotyping, a widely used Mtb genotyping tool based on the presence or absence of short spacer sequences in a region of direct repeats within the Mtb genome [24,25]. DNA for sequencing was extracted using a standardised protocol [23]. Spoligotypes were inferred in silico using the SpolPred software [26] and determined by the Kamerbeek methodology [24]. Spoligotypes were assigned following the International Data Base (SpolDB4) recommendations [27]. All samples (n=51) underwent whole genome sequencing with 76-base paired end reads, using Illumina HiSeq2000 technology [18]. The data processing pipeline used has been described previously [28]. The raw sequence data were mapped uniquely to a corrected H37Rv reference genome [29,30] using bwa [31]. The mappings allowed SNPs and small indels to be called using SAMtools/BCFtools [32] Larger indels were identified using a consensus from paired end mapping distance or split read approaches (Breakdancer [33], CREST [34], Pindel [35] and Delly [36]), followed by an assembly-validated strategy using Velvet software [37]. Only those variants of high quality (at least Q30, equating to 1 error per 1000) and supported by bi-directional reads were retained. In addition, we excluded polymorphisms with two or more missing genotypes as well all variants in highly variable gene families (e.g. PPE/PE loci) and non-unique regions established by assessing the uniqueness of 54-mers across the genome. Variation density maps were generated using Circos software (www.circos.com).

First we catalogued the polymorphisms and identified variants including single nucleotide polymorphisms (SNPs), insertions and deletions (indels) and large deletions. Second, using this genomic variation we assessed the degree of population structure. Third, we focused on identifying the incremental variant changes across clustered strains and in drug resistance profiles within patients over time. Clusters of samples with less than 50 SNPs variation were examined. Finally we assessed degree of similarity between isolates to infer possible transmission of drug resistant disease. For some analysis we investigated known drug candidate regions (Table 2).

A clustering dendrogram was constructed using R statistical software, using SNP and indel data [38]. To provide further phylogenetic analysis a best-scoring maximum likelihood tree was computed with RAxML (version 7.4.2) [39] using SNPdata.

Genomic variation

A total of 51 isolates collected from 41 patients were investigated (Table 1). All patients had been diagnosed with MDR-TB either at enrolment or following treatment, representing 69% of MDR-TB cases and 9.3% of patients enrolled in the cohort. Half of the patients came from Kampala District (50%), and the majority of the remainder from surrounding districts. Some patients reported living in the same parish (Table 2), but no two patients reported living in the same village (a collection of 50-70 households). Of the 38 patients for whom HIV status was known 11 (29%) were seropositive. In summary, sequencing yielded a median of 20.6 million 76 base-pair (bp) reads per sample. The reads mapped uniquely to more than 95% of the genome with in excess of 100-fold coverage (median 314) and 96% of the genome was covered at least 10-fold. Of 8269 putative SNPs 6857 (84.6%) were high quality and included in the analysis. Of these high quality SNPs, the majority (3667, 53.4%) were observed in single isolates. The majority were located in coding regions (median 71.5%, range 69.3 - 75.6%), and of those the majority lead to non-synonymous changes in amino acids (median 58.0%, range 54.5 - 60.6%). (See Table S1 for details) Identical non-synonymous SNP profiles were observed with pairs of samples isolated at the same point in time (n=2) and in general, low variation was seen in longitudinal samples from the same patient (Table 3).There was representation within drug resistance (DR) candidates (156) and putative efflux pump genes (41) (See Tables S2 and S3 for details). There was little evidence of mixed infection or cross contamination of samples (21 heterozygous genotypes, 1 per ~17000 SNP positions). However, it should be noted that isolates were sub-cultured at least twice prior to DNA extraction when selection of a dominant population may have occurred. The SNP density (average 2.4 per kb) tended to be greater in DR candidate genes (average 4.1 per kb), with two genes pncA and gid having over 20 SNP per kb (Figure S1 and Table S4).

We observed 737 indels in unique and non-highly variable genetic regions, including 14 in DR genes. Of the 92 large deletions identified in robust regions of the genome 31 (33.7%) were detected in single isolates. The median number of deletions per isolate was 22 (range 13 - 27). Deletions considered informative are presented in Figure 1 and the full list is provided in Figure S2. All raw data can be downloaded (short read archive, accession number ERP000520) and a full list of variants can be found on the http://pathogenseq.lshtm.ac.uk/polytb website.

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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].

https://doi.org/10.1371/journal.pone.0083012.g001

Population structure

The population structure of isolates based on SNP information separated samples into previously described lineages (Figure 1) [40]. Inclusion of larger variants did not change the clustering of samples which clustered to a first approximation by Spoligotype International Type (SIT), with EAI, LAM/T and Beijing/CAS ancestry separated [41]. Some divergance within isolates assigned by spoligotype to the T family was observed (samples A70620 and A70416). While over three hundred SNPs were informative for the CAS family (CAS1_DELHI, CAS2, CAS1_KILI) no informative SNP markers for the entire LAM family were identified, but there were strain-specific polymorphisms for LAM3&S convergent and LAM11_ZWE. Analysis of large deletions revealed putative markers for genotype families not previously reported, including SIT 59 and the larger LAM11_ZWE spoligotype family.

With two exceptions, little variation was seen in isolates taken from the same patient over time (2-15 SNPs). For two patients (A70011 and A70067) longditudinal sampling indicated subsequent infection with a different strain of Mtb. (Table 3) In both cases the initial strain was drug sensitive and the second strain was MDR. A total of 37 (90%) patients had TB spoligotype patterns identical to those from one or more other patients. Of these 20 (54%) were found to be unique, having an excess of 50 SNPs variation and these stains were not implicated in transmission to other patients in the study. Six clusters (17 patients) with variation of less than 50 SNPs and the five sets of londitudinal samples were examined to ascertain the relatedness of the strains. Results are summarised in Table 3 and show a preponderance of SNPs in genes associated with drug resistance. In samples collected from the same patient over time there was a trend to increased numbers of SNPs. For clustered isolates orginating from different patients no correration was observed between incremental SNP and the date of sample collection (Spearman‘s correlation [42]).

Analysis of SNP differences found two paired samples from different patients (Cluster 6 and 10) with differing mutations predictive of MDR in rpoB and katG (resistance to rifampicin and isoniazid respectively), suggesting resistance had emerged independently in these strains and excluding the possibility of transmission of MDR-TB (Table S5). The phylogeny of the remaining four clusters is presented in Figure 2. All isolates shared polymorphisms in katG predictive of resistance to isoniazid (S315T) but there was variation in rpoB predictive of resistance to rifampicin. Review of base calls did not reveal evidence of subpopulations in these samples. In cluster 7 whereas the four isolates shared polymorphisms in katG sample A700582 had discordant polymorphisms in rpoB suggesting independant emergence of MDR within this cluster. In cluster 9 there was strong evidence of transmission of MDR-TB, where two isolates (A70376 and A70730) differed by a single SNP and shared polymorphisms in rpoB and katG. The third isolate (A70329) had differing polymorphism in rpoB and thus was not part of a common MDR transmission chain. Cluster 11 also provided evidence suggestive of transmision of MDR, with 4 isolates from 3 patients exhibiting identical polymorphims at two loci for both rpoB and katG and a single pncA loci. Evidence of the continued acquisiton of polymorphisms was evident as the 2004 sample from patient A70144 exhibited a different mutation (S450Stop) from the two samples collected in 2006, (A70769 and A70780) which shared an additional rpoB mutation S450L.

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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.

https://doi.org/10.1371/journal.pone.0083012.g002

Cluster 8 included four isolates from three patients assigned SIT 4 (3) and SIT125 (1) by spoligotyping. The spoligotype pattern for sample A70785 lacked spacer 39, an observation seen both in silico analysis using SpolPred software and by the Kamerbeek methodology. Nineteen large deletions were common to all four isolates. Two additional deletions were observed in sample A70260 (Figure S2). SNPs in genes associated with MDR-TB (rpoB and katG) were common across the 4 isolates and it is probable that these strains resulted from a common source of MDR-TB.

Opportunities for transmission between clustered patients where transmission is suspected are not obvious as they resided in different neigbourhoods within the Kampala district. Examination of admission and discharge dates for patients admitted to the wards during the period of study suggest that clustered patients were not hospitalised concurrently (Table S6) Examination of cases histories and previous episodes of TB revealed concurrent episodes of disease raising the possibility of noscomial transmission during attendance at treatment clinics (Table 4 and Figure 3).

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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.

https://doi.org/10.1371/journal.pone.0083012.g003

Drug resistance

Of the 51 isolates, 47 had phenotypic data on susceptibility to first line anti-tuberculosis drugs and 31 to second line drugs (Table 5). Isolates collected from three patients were reported phenotypically sensitive to all drugs tested and the remainder were resistant to at least two drugs. Forty two isolates were reported as MDR-TB, and 2 were resistant to isoniazid but not rifampicin In MDR-TB isolates the most common SNPs were katG S315T (28/42, 66.7%) and rpoB S531L (21/40, 52.5%), respectively (rpoB E. coli codon numbering). (Table S2 for details). Mutations not previously associated with drug resistance were identified in DR genes of strains found resistant. SNPs were observed in genes such as rpoC, suspected of compensatory properties [43-45]. In addition to the SNPs, 11 indels were observed in DR genes. Deletion analysis revealed five patient isolates lacked the gene ethA/etaA (Rv3854c) required for activation of ethionamide [46,47]. Similarly katG, required for catalase-peroxidase activation of isoniazid was deleted in two strains. Neither of the isolates deletions were implicated in transmission, possibly reflecting reduced fitness of these strains [48,49]. It should be noted that polymorphisms in DR genes were not observed in all samples found resistant by phenotypic testing. Three isoniazid resistant isolates contained no detectable mutation in the isoniazid candidate genes, two isolates had the R463L mutation in katG, which is not associated with isoniazid resistance [50]. Three isolates resistant to rifampicin by phenotypic methods (liquid culture) contained no detectable mutation in rpoB.