A molecular snapshot of clinical extra-intestinal Escherichia coli strains in South India – Virulence factors, phylogrouping and resistance trends

Introduction: E. coli is a frequently encountered clinical pathogen, and periodic monitoring of antimicrobial resistance and virulence profiles is crucial for defining roadmaps for both infection prevention and control practices. Objective: We aimed to compare the proportions of key phylogenetic groups, virulence associated genes (VAGs), and antimicrobial susceptibility (AST) patterns of E. coli isolated from various clinical samples and compare expression levels of key VAGs in patients with uncomplicated UTI versus those with UTI + bacteraemia in a tertiary-care hospital in South India. Methods: Clinical E. coli isolates, confirmed using the MALDI-TOF MS, and satisfying the National Healthcare Safety Network(NHSN) criteria for infections were included. Phylogenetic grouping and VAGs detection were performed using multiplex-PCR and targeted gene expression was carried out using quantitative RT-qPCR. AST was determined using VITEK 2 system. Results: The included 288E. coli isolates (144 from bacteraemia and non-bacteraemia cases each) predominately showed phylogroup B2 (52 %), followed by D (23 %), and most prevalent virulence genes were chuA (74.7 %), fimH(63.3 %), traT(63.2 %), and kpsMTII(54.2 %). fimH, fyuA, and hlyD were significantly associated with bacteraemia, and gene expression of these genes and the analysis demonstrated that hlyD expression was significantly higher (p = 0.012) in UTI + bacteraemia patients when compared to patients with uncomplicated UTI. Phylogroup B2 carried the highest median number of VAGs (7), followed by D (6). Highest susceptibility was towards tigecycline (99.7 %), followed by amikacin (91.7 %) and meropenem (90.0 %). Conclusion: We focused on prevalent virulent genes and their expression, leading to bacteraemia, providing a comprehensive overview of an existing concern. Focusing on bacterial gene expression along with integrated surveillance of antimicrobial resistance helps in designing further research so that strategies can be planned that will later help in early risk stratification and informed clinical decision-making to prevent severe complications including secondary bacteraemia and other severe patient morbidities.