Characterization of microbial diversity, chemical hazards and antimicrobial resistant bacteria in wash water from a...

This study investigated the quality of process wash water (PWW) in an industrial fresh-cut produce facility. Traditional microbiological and physico-chemical parameters, such as aerobic mesophilic counts, coliforms, molds and yeasts, pH, free chlorine, oxidation-reduction potential, and organic matter indicators, were monitored to contextualize water quality dynamics across the workday. Additionally, untargeted analyses were performed to characterize the microbiome and resistome and identify chemical hazards in PWW, highlighting the occurrence of antimicrobial-resistant bacteria and the presence of some pesticides at low levels, including chlorantraniliprole, cyprodinil, fludioxonil, and propyzamide, in a real-world processing environment. Antimicrobial susceptibility tests and whole genome sequencing of twelve coliform isolates revealed multidrug-resistant strains, including Enterobacter mori, Enterobacter ludwigii, and Klebsiella oxytoca, carrying resistance genes such as oqxB, fosA, and blaACT-12, as well as the plasmid-borne blaOXY-2-2. Metagenome analyses revealed a microbial community dominated by the genus Pseudomonas, together with high abundance of Rheinheimera mangrovi and Pantoea agglomerans. Moreover, resistome analysis disclosed that 83% of detected antimicrobial resistance genes were associated with beta-lactam resistance. Additionally, the efficacy of chlorine against one K. oxytoca isolate obtained from PWW using a dynamic system simulating a produce washing operation confirmed that maintaining pH at 6.5 and stable free chlorine levels of 6 mg/L was sufficient for complete inactivation. These findings demonstrate the importance of implementing proper wash water management practices in fresh produce processing, including preventing excessive organic matter accumulation through adequate water replenishment and maintaining chemical parameters within the validated operational range, supported by systematic verification and monitoring.