A precision overview of genomic resistance screening in isolates of Mycobacterium tuberculosis using web-based bioinformatics tools.

Tuberculosis (TB) is among the most deadly diseases that affect worldwide, its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, non-adherence to treatment and circulation of previously resistant isolates of Mycobacterium tuberculosis. The aim in this study was evaluate the performance and functionalities of web-based tools: Mykrobe, TB-profiler, PhyReSse, KvarQ, and SAM-TB for detecting resistance in isolate of Mycobacterium tuberculosis in comparison with conventional drug susceptibility tests. We used 88 M. tuberculosis isolates which were drug susceptibility tested and subsequently fully sequenced and web-based tools analysed. Statistical analysis was performed to determine the correlation between genomic and phenotypic analysis. Our data show that the main sub-lineage was LAM (44.3%) followed by X-type (23.0%) within isolates evaluated. Mykrobe has a higher correlation with DST (98% of agreement and 0.941Cohens Kappa) for global resistance detection, but SAM-TB, PhyReSse and Mykrobe had a better correlation with DST for first-line drug analysis individually. We have identified that 50% of mutations characterised by all web-based tools were canonical in rpoB, katG, embB, pncA, gyrA and rrs regions. Our findings suggest that SAM-TB, PhyReSse and Mykrobe were the web-based tools more efficient to determine canonical resistance-related mutations, however more analysis should be performed to improve second-line detection. The improvement of surveillance programs for the TB isolates applying WGS tools against first line drugs, MDR-TB and XDR-TB are priorities to discern the molecular epidemiology of this disease in the country. ImportanceTuberculosis, an infectious disease caused by Mycobacterium tuberculosis, which most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, the patient adherence, long duration of treatment, and late diagnosis, have reduced the effectiveness of therapy and raised the drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, have highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying the more efficient and friendly web-based tool to characterise the resistance in Mycobacterium tuberculosis by whole genome sequencing, which will allow apply it more routinely to improve TB strain surveillance programs locally.