ArticleMicrobiologyOpen2026
Genomic Epidemiology and Machine Learning-Based Drug Discovery for Antimicrobial Resistant Diarrheagenic Escherichia coli.
Article in MicrobiologyOpen, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
Diarrheagenic Escherichia coli (DEC) is a leading cause of pediatric diarrhea, with antimicrobial resistance (AMR) complicating treatment. This study analyzed 350 E. coli isolates (175 DEC and 175 non-DEC) to determine molecular pathotypes, resistance patterns, and therapeutic targets. Polymerase chain reaction and 16S ribosomal RNA sequencing identified enteropathogenic E. coli as the most prevalent DEC pathotype (35%), followed by enterotoxigenic E. coli (25%), enterohemorrhagic E. coli (15%), enteroinvasive E. coli (10%), and diffusely adherent E. coli (20%). Phylogenetic analysis confirmed distinct clustering between DEC and non-DEC strains, revealing their evolutionary relationships. Antimicrobial susceptibility testing showed high resistance to ampicillin (87.6%), trimethoprim-sulfamethoxazole (75.5%), and erythromycin (100%), while carbapenems and colistin retained effectiveness. Functional analysis using phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) indicated enhanced metabolic and immune-related functions in DEC strains, differentiating them from non-DEC strains. Machine learning and bioinformatics-driven drug discovery identified Alatamide and Isosativan as potential therapeutic compounds, exhibiting strong binding affinities and structural stability against DEC virulence targets through molecular docking and molecular dynamics simulations. This study provides critical insights into the epidemiology, genetic diversity, and resistance patterns of DEC and non-DEC strains. The integration of bioinformatics and machine learning offers a promising strategy for discovering alternative treatments. Continuous AMR surveillance, responsible antibiotic use, and further experimental validation of identified drug candidates are essential to managing E. coli-associated diarrheal infections in pediatric populations and mitigating the global burden of multidrug-resistant pathogens.
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