Abstract
Aims and objectives: Selection pressure, such as drug treatment or host microenvironment, drives the evolution of M. tuberculosis in vivo. The emergence of drug resistance by the accumulation of mutations leading to drug target modifications, drug transport or activation pathways inactivation, is the leading cause of treatment failure. Besides that, secondary mutations involved in bacterial adaptation, fitness-compensation, and resistance level were identified in the genome by microevolution studies. Methods: Whole-genome sequencing data of 2212 clinical isolates of M. tuberculosis with resistance data were downloaded from SRA. Identification of single nucleotide variations (SNVs) was performed using BWA-MEM and C-Sibelia scripts using AL123456.3 as reference. The SNVs database handling and calculations were performed with custom Python scripts. Fisher test analysis was performed as for individual mutations, also for mutation combinations. Pairs of mutations were joined using logical AND function. Thus, n^2/2 records were analyzed for correlation with resistance, where n – total number of mutations in the database. Resistance to the rifampicin, isoniazid, and ethionamide was analyzed. Results: A novel approach for GWAS was developed: we studied the correlation of simultaneous occurrence of mutations pairs and phenotypic resistance for all possible pairs. We identified several SNVs associated with resistance in combinations with other mutations, and its statistical significance was below the threshold when analyzed separately. Conclusions: Fisher exact test for mutation combinations allows for the identification of genetic determinants missed by conventional GWAS approach. Further evaluation of novel resistance determinants using other sets of clinical isolates data from various world regions is needed. Acknowledgements This study was supported by the Russian Foundation for Basic Research (project 20-015-00463).
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