Tuberculosis (TB) remains a global health challenge, causing substantial mortality, exacerbated by drug-resistant strains. Conventional phenotypic testing for Mycobacterium involves assessing observable characteristics in a laboratory setting, commonly employed for drug susceptibility testing (DST). This method evaluates the bacteria’s response to various anti-tuberculosis drugs, determining susceptibility or resistance. While providing crucial insights into actual bacterial responses, phenotypic testing is time-consuming, taking several weeks for results.
Addressing this issue is the GeneXpert MTB/RIF and GeneXpert Ultra assays, revolutionizing TB diagnosis by rapidly detecting infection and rifampicin resistance within 1–2 hours. These tests, while pivotal, have limitations in assessing all relevant drugs or gene regions.
Next-generation sequencing (NGS), particularly whole genome sequencing (WGS), has emerged as a comprehensive method. WGS offers unparalleled insights into potential drug-resistant mutations, facilitating personalized treatment. Advancements in NGS enable precise detection of drug resistance-associated genomic variants in M. tuberculosis. Single nucleotide polymorphisms (SNPs) and small insertions/deletions mediate drug resistances, resulting in accurate genotypic DST.
Its advantages extend to tracking mixed infections, heteroresistance, transmission patterns, outbreaks, and identifying superspreaders. However, widespread adoption in high TB burden areas faces challenges due to resource constraints. Specialized facilities, intricate workflows, skilled personnel, and data analysis capabilities are prerequisites. The current WGS process involves cultivating Mycobacterium tuberculosis from a sputum sample, extracting DNA, preparing a DNA library, and utilizing short-read sequencing methods for analysis.
As mutation catalogs improve, genotypic DST may potentially replace a significant portion of phenotypic testing for clinical M. tuberculosis strains. Integrating both phenotypic and genotypic testing methods emerges as a comprehensive approach in managing tuberculosis, optimizing diagnostic accuracy and treatment strategies.