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Diagnosing Pulmonary Tuberculosis with the Xpert MTB/RIF Test
Published on: April 9, 2012
Undetected rifampicin-resistant tuberculosis associated with rpoB I491F and V170F mutations in Botswana: Diagnostic
Tuelo Mogashoa1, Justice T Ngom2, Johannes Loubser2
1Research Laboratory, Botswana Harvard Health Partnership, Gaborone, Botswana; South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Background:
Undetected rifampicin resistance is a threat to global tuberculosis (TB) control efforts by delaying effective treatment. In different studies, non-canonical rpoB mutations outside the rifampicin resistance-determining region have been reported at varying prevalences by country. Here, we report cases of rifampicin resistance in Botswana that were missed by the routine molecular diagnostic assays.
Methods:
Individuals were tested under routine programme conditions, in accordance with national guidelines, at four designated drug-resistant TB clinics from 2017 to 2022. Initial testing at the facilities included GeneXpert MTB/RIF ultra and later phenotypic drug susceptibility testing (pDST), as well as the Hain MTBDRsl line probe assay, at the National Tuberculosis Reference Laboratory. A total of nine isolates were subsequently sequenced on the Illumina NextSeq 2000 instrument.
Results:
At the point of care, routine molecular tests classified all nine individuals as susceptible to rifampicin. Subsequent culture and phenotypic drug susceptibility testing confirmed rifampicin resistance. Whole-genome sequencing identified non-canonical rpoB mutations outside the rifampicin resistance-determining region I49F and V170F, which are associated with low-level rifampicin resistance. Of the nine isolates sequenced, 4 (44%) harboured the rpoB V170F mutation, while 5 (56%) harboured the rpoB I491F mutation.
Conclusions:
These results highlight a diagnostic gap within the current algorithms and show the value of sequencing-based approaches for accurately detecting drug resistance. Incorporating sequencing into routine clinical practice could help guide the selection of TB treatment and improve treatment outcomes in patients who do not respond to first-line therapy.
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