Integration of phenotypic, qPCR and genome sequencing methodologies for the detection of antimicrobial resistance and virulence in clinical isolates of a tertiary hospital, India.

Abstract

The emergence of antimicrobial resistance (AMR) and virulence in clinical isolates is a significant public health concern. The rapid and accurate detection of these traits in clinical isolates is essential for effective infection control and treatment. We demonstrated the integration of multiple detection methodologies, including phenotypic testing, quantitative polymerase chain reaction (qPCR), and genome sequencing, to detect AMR and virulence in clinical isolates. One hundred sixty-two gram-negative bacterial clinical isolates were selected for this study from the Shri Vinoba Bhave Civil Hospital, Silvassa, a tertiary government hospital. Antimicrobial susceptibility was detected by determining the Minimum Inhibitory Concentration (MIC) using Vitek-2, whereas the combined disk (CD) method was used for phenotypic detection of carbapenemase activity. The highest sensitivity rates were obtained for antibiotics colistin 87.93%, amikacin 67.52%, tigecycline 63.39%, nitrofurantoin 60.87%, and gentamycin 56.08%. The most resistant antibiotics were ceftazidime (71.93%), ciprofloxacin (67.95%) and trimethoprim/sulfamethoxazole (65.56%). Approximately 46.91% (76) of all the isolates were MBL isolates. The qPCR results confirmed the presence of blaNDM-1 in 29.01% of the isolates. The blaNDM-1 harbouring isolates in descending order, were Acinetobacter, Enterobacter cloacae, and Klebsiella pneumoniae. Klebsiella and Acinetobacter isolates were extensively drug-resistant. Whole genome sequencing performed on one of the Klebsiella pneumoniae isolates revealed the presence of many virulence factors, which increased the pathogenicity of the clinical isolates. The results showed that antimicrobial resistance, including carbapenem resistance, blaNDM-1, and virulence factors, was highly prevalent among isolates from tertiary clinical hospitals. The integration of multiple detection methodologies can potentially improve the detection of AMR and virulence in clinical isolates, leading to better patient outcomes and a reduced spread of these essential traits.