Browsing UA Faculty Research by Subjects
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Assessing the Food Safety Risk Posed by Birds Entering Leafy Greens Fields in the US SouthwestIn the US Southwest, it is common to observe birds in leafy green fields, though the risk they contribute to foodborne outbreaks remains unclear. In this study, we investigated and recorded the relationship between birds near leafy green fields and the risk for contaminated irrigation water or leafy green plants. We monitored the presence of birds for over two years and performed cloacal swab analysis for non-pathogenic Escherichia coli, E. coli O157:H7 and Salmonellaenterica, while also monitoring the incidence of other microbial indicators. We also assessed the risks from bird feces by performing observations in a commercial field reported with Salmonella positive samples and by analyzing the survival of foodborne pathogens in bird feces. Our results showed that most of the birds near the crop fields were resident small birds. We did not observe a correlation between the number of birds in sites and the incidence of indicator bacteria (e.g., coliforms, E. coli) in irrigation canal water, with the exception of one out of four sites where water flow was low or stagnant. Using walk-in-traps, 305 birds were captured and placed in short-term captivity to determine the presence of various bacteria. None of the birds tested positive for E. coli O157:H7 or Salmonella. However, nearly 40% of the birds captured were confirmed positive for non-pathogenic E. coli. We found no correlation between age (young, adult, unknown), gender (male, female, unknown) and the incidence of E. coli positive birds, but we observed significantly higher probability of incidence during October-December. The role of relative humidity and temperature on bacterial survival appeared to play a key role in the survival of Salmonella on the leaves of spinach plants in a commercial field. This was also confirmed in laboratory conditions where Salmonella inoculated in bird feces and exposed to 15 °C and 80% RH(Relative humidity) survived beyond 133 days, while at 26 °C and 40% RH, the organism was undetectable after 63 days. Our results suggest that local birds associated with leafy green fields likely pose a minimal impact of risk for food contamination, but also points out the need for increased analysis specifically for E. coli O157:H7. Furthermore, our study suggests the need for expanding research that addresses risks associated with large migratory birds, especially in areas where stagnated water sources would be used for overhead sprinkle irrigation.
Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural WaterAgricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between Escherichia coli levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of Salmonella detection (Odds Ratio [OR] = 2.18), and eaeA-stx codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR = 50.2) and NY (OR = 18.4), and Salmonella detection in AZ (OR = 4.4) were significantly associated with E. coli levels, while Salmonella detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli levels alone may not be a suitable indicator of food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and E. coli levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.
Cross-Validation Indicates Predictive Models May Provide an Alternative to Indicator Organism Monitoring for Evaluating Pathogen Presence in Southwestern US Agricultural WaterPathogen contamination of agricultural water has been identified as a probable cause of recalls and outbreaks. However, variability in pathogen presence and concentration complicates the reliable identification of agricultural water at elevated risk of pathogen presence. In this study, we collected data on the presence of Salmonella and genetic markers for enterohemorrhagic E. coli (EHEC; PCR-based detection of stx and eaeA) in southwestern US canal water, which is used as agricultural water for produce. We developed and assessed the accuracy of models to predict the likelihood of pathogen contamination of southwestern US canal water. Based on 169 samples from 60 surface water canals (each sampled 1–3 times), 36% (60/169) and 21% (36/169) of samples were positive for Salmonella presence and EHEC markers, respectively. Water quality parameters (e.g., generic E. coli level, turbidity), surrounding land-use (e.g., natural cover, cropland cover), weather conditions (e.g., temperature), and sampling site characteristics (e.g., canal type) data were collected as predictor variables. Separate conditional forest models were trained for Salmonella isolation and EHEC marker detection, and cross-validated to assess predictive performance. For Salmonella, turbidity, day of year, generic E. coli level, and % natural cover in a 500–1,000 ft (~150–300 m) buffer around the sampling site were the top 4 predictors identified by the conditional forest model. For EHEC markers, generic E. coli level, day of year, % natural cover in a 250–500 ft (~75–150 m) buffer, and % natural cover in a 500–1,000 ft (~150–300 m) buffer were the top 4 predictors. Predictive performance measures (e.g., area under the curve [AUC]) indicated predictive modeling shows potential as an alternative method for assessing the likelihood of pathogen presence in agricultural water. Secondary conditional forest models with generic E. coli level excluded as a predictor showed < 0.01 difference in AUC as compared to the AUC values for the original models (i.e., with generic E. coli level included as a predictor) for both Salmonella (AUC = 0.84) and EHEC markers (AUC = 0.92). Our data suggests models that do not require the inclusion of microbiological data (e.g., indicator organism) show promise for real-time prediction of pathogen contamination of agricultural water (e.g., in surface water canals). Copyright © 2021 Belias, Brassill, Roof, Rock, Wiedmann and Weller.
A dynamic charge-charge interaction modulates PP2A:B56 substrate recruitmentThe recruitment of substrates by the ser/thr protein phosphatase 2A (PP2A) is poorly understood, limiting our understanding of PP2A-regulated signaling. Recently, the first PP2A:B56 consensus binding motif, LxxIxE, was identified. However, most validated LxxIxE motifs bind PP2A: B56 with micromolar affinities, suggesting that additional motifs exist to enhance PP2A:B56 binding. Here, we report the requirement of a positively charged motif in a subset of PP2A:B56 interactors, including KIF4A, to facilitate B56 binding via dynamic, electrostatic interactions. Using molecular and cellular experiments, we show that a conserved, negatively charged groove on B56 mediates dynamic binding. We also discovered that this positively charged motif, in addition to facilitating KIF4A dephosphorylation, is essential for condensin I binding, a function distinct and exclusive from PP2A-B56 binding. Together, these results reveal how dynamic, charge-charge interactions fine-tune the interactions mediated by specific motifs, providing a new framework for understanding how PP2A regulation drives cellular signaling.