Genomic profiling of antimicrobial resistance genes in clinical isolates of Salmonella Typhi from patients infected with Typhoid fever in India.

The development of multidrug resistance in Salmonella enterica serovar Typhi currently forms a major roadblock for the treatment of enteric fever. This poses a major health problem in endemic regions and extends to travellers returning from developing countries. The appearance of fluoroquinolone non-susceptible strains has resulted in use of ceftriaxone as drug of choice with azithromycin being recommended for uncomplicated cases of typhoid fever. A recent sporadic instance of decreased susceptibility to the latest drug regime has necessitated a detailed analysis of antimicrobial resistance genes and possible relationships with their phenotypes to facilitate selection of future treatment regimes. Whole genome sequencing (WGS) was conducted for 133 clinical isolates from typhoid patients. Sequence output files were processed for pan-genome analysis and prediction of antimicrobial resistance genes. The WGS analyses disclosed the existence of fluoroquinolone resistance conferring mutations in gyrA, gyrB, parC and parE genes of all strains. Acquired resistance determining mechanisms observed included catA1 genes for chloramphenicol resistance, dfrA7, dfrA15, sul1 and sul2 for trimethoprim-sulfamethoxazole and bla/bla genes for amoxicillin. No resistance determinants were found for ceftriaxone and cefixime. The genotypes were further correlated with their respective phenotypes for chloramphenicol, ampicillin, co-trimoxazole, ciprofloxacin and ceftriaxone. A high correlation was observed between genotypes and phenotypes in isolates of S. Typhi. The pan-genome analysis revealed that core genes were enriched in metabolic functions and accessory genes were majorly implicated in pathogenesis and antimicrobial resistance. The pan-genome of S. Typhi appears to be closed (B  =  0.09) as analysed by Heap's law. Simpson's diversity index of 0.51 showed a lower level of genetic diversity among isolates of S. Typhi. Overall, this study augments the present knowledge that WGS can help predict resistance genotypes and eventual correlation with phenotypes, enabling the chance to spot AMR determinants for fast diagnosis and prioritize antibiotic use directly from sequence.