Prevalence of STEC virulence markers and Salmonella as a function of abiotic factors in agricultural water in the southeastern United States

• DOI: 10.3389/fmicb.2024.1320168
• Publication Date: 2024-05-20T04:28:20Z
• Authors: Zoila R. Chevez; Laurel L. Dunn; Andre L. B. R. da...; Camila Rodrigues
• Keywords: 0303 health sciences; 03 medical and health sciences; produce safety; agricultural water; Escherichia coli; Salmonella enterica; Microbiology; irrigation; QR1-502

Fresh produce can be contaminated by enteric pathogens throughout crop production, including through contact with contaminated agricultural water. The most common outbreaks and recalls in fresh produce are due to contamination by Salmonella enterica and Shiga toxin-producing E. coli (STEC). Thus, the objectives of this study were to investigate the prevalence of markers for STEC (wzy, hly, fliC, eaeA, rfbE, stx-I, stx-II) and Salmonella (invA) in surface water sources (n = 8) from produce farms in Southwest Georgia and to determine correlations among the prevalence of virulence markers for STEC, water nutrient profile, and environmental factors. Water samples (500 mL) from eight irrigation ponds were collected from February to December 2021 (n = 88). Polymerase chain reaction (PCR) was used to screen for Salmonella and STEC genes, and Salmonella samples were confirmed by culture-based methods. Positive samples for Salmonella were further serotyped. Particularly, Salmonella was detected in 6/88 (6.81%) water samples from all ponds, and the following 4 serotypes were detected: Saintpaul 3/6 (50%), Montevideo 1/6 (16.66%), Mississippi 1/6 (16.66%), and Bareilly 1/6 (16.66%). Salmonella isolates were only found in the summer months (May-Aug.). The most prevalent STEC genes were hly 77/88 (87.50%) and stx-I 75/88 (85.22%), followed by fliC 54/88 (61.63%), stx-II 41/88 (46.59%), rfbE 31/88 (35.22%), and eaeA 28/88 (31.81%). The wzy gene was not detected in any of the samples. Based on a logistic regression analysis, the odds of codetection for STEC virulence markers (stx-I, stx-II, and eaeA) were negatively correlated with calcium and relative humidity (p < 0.05). A conditional forest analysis was performed to assess predictive performance (AUC = 0.921), and the top predictors included humidity, nitrate, calcium, and solar radiation. Overall, information from this research adds to a growing body of knowledge regarding the risk that surface water sources pose to produce grown in subtropical environmental conditions and emphasizes the importance of understanding the use of abiotic factors as a holistic approach to understanding the microbial quality of water.