Programmatically selected multidrug-resistant strains drive the emergence of extensively drug-resistant tuberculosis in South Africa

Abstract

Background: South Africa shows one of the highest global burdens of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis (TB). Since 2002, MDR-TB in South Africa has been treated by a standardized combination therapy, which until 2010 included ofloxacin, kanamycin, ethionamide, ethambutol and pyrazinamide. Since 2010, ethambutol has been replaced by cycloserine or terizidone. The effect of standardized treatment on the acquisition of XDR-TB is not currently known.

Methods: We genetically characterized a random sample of 4,667 patient isolates of drug-sensitive, MDR and XDR-TB cases collected from three South African provinces, namely, the Western Cape, Eastern Cape and KwaZulu-Natal. Drug resistance patterns of a subset of isolates were analyzed for the presence of commonly observed resistance mutations.

Results: Our analyses revealed a strong association between distinct strain genotypes and the emergence of XDR-TB in three neighbouring provinces of South Africa. Strains predominant in XDR-TB increased in proportion by more than 20-fold from drug-sensitive to XDR-TB and accounted for up to 95% of the XDR-TB cases. A high degree of clustering for drug resistance mutation patterns was detected. For example, the largest cluster of XDR-TB associated strains in the Eastern Cape, affecting more than 40% of all MDR patients in this province, harboured identical mutations concurrently conferring resistance to isoniazid, rifampicin, pyrazinamide, ethambutol, streptomycin, ethionamide, kanamycin, amikacin and capreomycin.

Conclusions: XDR-TB associated genotypes in South Africa probably were programmatically selected as a result of the standard treatment regimen being ineffective in preventing their transmission. Our findings call for an immediate adaptation of standard treatment regimens for M/XDR-TB in South Africa.

Figure 1. Selection of study population.

Grey boxes indicate sample sets used to analyze the strain population structures in the three South African provinces. Boxes with striped pattern indicate sample sets used to characterize drug resistance mutation patterns among XDR-TB associated genotypes. ^a) Computer-based random sampling was applied. ^b) Review of an extensive collection of data generated within multiple previous studies.

Figure 2. Strain population structure of drug-sensitive (DS), mono-/poly-resistant (DR), sensu stricto multidrug-resistant (MDR s.s.; excluding identified pre-XDR and XDR isolates), pre-extensively drug-resistant (pre-XDR) and extensively drug resistant (XDR) isolates in three provinces of South Africa.

The R220, R86 and F15/LAM4/KZN genotypes, respectively, represent a subgroup of the typical Beijing, “atypical” Beijing and LAM4 family –, –. Based on similar IS6110 RFLP patterns and whole genome sequencing data it was previously shown that “atypical” Beijing strains in the Western and Eastern Cape, unlike in other parts of the world, represent one single genotype herein referred to as R86 , , . The specific presence of R220 and F15/LAM4/KZN genotypes was only assessed in the Western Cape and KwaZulu-Natal, respectively, where these genotypes were known to be frequent among XDR-TB cases .

Figure 3. Drug resistance mutation pattern in a random selection of 193 MDR R86 isolates from the Eastern Cape.

Different colours indicate different drug resistance associated genes. The area of the circles is proportional to the number of isolates (indicated in the centre of each circle) harbouring an identical drug resistance mutation for the respective resistance gene as well as all circles connected to the left. Principal branches of the tree were defined by resistance mutations in pncA. Other first-line drug resistance mutations were connected by logical deduction to maximize clustering and were followed by second-line resistance mutations. However, the order of acquisition of resistance mutations may remain debatable in some cases.

Figure 4. Drug resistance mutation pattern in a convenience sample of 41 MDR Beijing isolates from the Western Cape.

No data was available for the streptomycin resistance determining region in rrs (Table 1). For more information see figure legend of Figure 3.

Figure 5. Model for the evolution of XDR-TB associated strain families.