Biopython-assisted in-Silico profiling and antimicrobial evaluation of chitosan nanoparticles against antibiotic-resistant pathogenic bacteria from lake ecosystems

Freshwater bodies in urban areas are emerging as reservoirs of antibiotic-resistant pathogenic bacteria, posing a growing threat to environmental and public health. This study explores the antimicrobial potential of chitosan nanoparticles (CNPs) against multidrug-resistant (MDR) bacteria isolated from lake water samples collected across Chennai. Bacterial strains, including, Ralstonia picketti, Aeromonas caviae, Coronobacter sakazakii, Bacillus subtilis were isolated and identified using standard microbiological and molecular techniques. Their resistance profiles were determined through antibiotic susceptibility testing. To understand resistance mechanisms at the molecular level, Biopython was employed to perform genomic and transcriptomic data analysis of resistance genes NDM-1. In-silico
molecular docking studies were conducted to assess the binding efficiency of chitosan molecules to key resistance-related bacterial proteins. Chitosan nanoparticles were synthesized and characterized, then evaluated for their antibacterial efficacy through assays such as MIC determination, bacterial viability. The results reveal that CNPs exhibit strong inhibitory effects against MDR isolates, indicating their potential as eco-friendly bioremediation agents. The integration of computational and experimental approaches underscores the value of nanoparticle-based strategies in mitigating antimicrobial resistance in aquatic environments.
Keywords: Lake water, MDR bacteria, Chitosan nanoparticles,
Biopython, Molecular Docking.