2. Conventionally, TB drug resistance testing has relied on phenotypic methods based on the observation of growth or inhibition of a bacterial culture in the presence of a drug. These culture-based methods are comprehensive but have rigorous laboratory requirements, biosafety requirements and are highly time-consuming (6-8 weeks) given the slow growth rate of Mycobacterium tuberculosis (MTB), the bacterium that causes TB.^[1] Available rapid molecular or nucleic acid amplification tests (NAATs) detect some key mutations in one or few gene targets and can predict resistance mainly to first-line drugs and a couple of second-line drugs. Detection of resistance to all existing, new, and repurposed drugs would require interrogation of hundreds of mutations. This makes Next Generation Sequencing (NGS) highly suitable for comprehensive, molecular TB DST – NGS refers to high-throughput, massively parallel sequencing technologies that determine the nucleotide sequence of hundreds of genes or even an entire genome in a single biochemical reaction. Ideally, whole genome sequencing, which involves NGS to determine the complete genome sequence for a given organism at one time, would be the way to go, but even today it relies on culture isolates as the starting sample, which does not make it appropriate for rapid detection of drug resistance for clinical action. Targeted NGS (tNGS) has been shown to work directly from TB clinical samples and can allow detection of resistance to almost all TB drugs in a single test within a day or two, compared to the 6-8 weeks needed for culture-based DST. Thus, targeted NGS is a paradigm shift in the diagnosis of drug-resistant TB and could drastically improve clinical outcomes for DR-TB patients.

3. Successful molecular DST relies on prediction of drug resistance through accurate interpretation of genetic data generated from targeted sequencing and other molecular methods. The WHO Catalogue of mutations associated with TB drug resistance provides comprehensive guidance for harmonized interpretation of genetic data and enables development of novel molecular diagnostics based on validated genetic targets and a confidence-graded mutations list. The second edition of the catalogue published in November 2023 vastly expanded on the first edition in both geographic and drug coverage. The catalogue will continue to be updated as the knowledgebase of resistance strain data grows over time allowing for the discovery of additional mutations associated with drug resistance, especially for the new drugs.