Integrated computational analysis for Escherichia coli prevalence, genetic evolution, and antimicrobial resistance evolution: Implications for public health and environmental sustainability in Asia
Year: 2025
Type: article
Abstract: BACKGROUND: Escherichia coli (E. coli), a common gut commensal, includes pathogenic strains responsible for gastrointestinal infections and hemolytic uremic syndrome (HUS). It spreads mainly through contaminated water and food, as well as direct human contact, with the risk being particularly high in densely populated regions. The growing emergence of antimicrobial-resistant (AMR) strains, particularly in Asia, poses serious public health challenges. METHODS: This study employed a multi-tiered computational framework comprising systematic review, quantitative evidence synthesis (meta-analysis), the Markov cluster algorithm with random walks on pan-genomics, and positive selection through evolutionary analysis, shedding light on the prevalence, geographical distribution, genomic diversity, and evolutionary dynamics of E. coli across Asia. RESULTS: =0.0, P = 0) in Asia. The E. coli incidences identified the Indian strain Ec40 collected in 2013 showed the highest genetic diversity, and the sequences collected between 2012 and 2019 displayed the most variation. The emrY gene, recurrently identified within the E. coli genomes, was subjected to evolutionary analysis. Codon-based selection models indicated adaptive evolution, with five codon sites under pervasive selection and twelve under episode selection (ω > 1), suggesting antimicrobial pressure as the main driver of regional adaptation. CONCLUSION: These findings underscore the urgent need for integrated prevention and control strategies, including robust surveillance systems to monitor infection trends, targeted interventions to curb transmission, and strengthened biosecurity measures aimed at reducing environmental contamination. Furthermore, the emergence of AMR variants calls for alternative treatment, e.g., bacteriophage therapy, to reduce the clinical and socioeconomic burden of E. coli infections in humans and animal populations.
Language: English
Subfield: Endocrinology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,310
OpenAlex ID: W7117558700
