Listeria species have been isolated from diverse environments, often at considerable prevalence, and are known to persist in food processing facilities. The presence of Listeria spp. has been suggested to be a marker for Listeria monocytogenes contamination. Therefore, a study was conducted to (i) determine the prevalence and diversity of Listeria spp. in produce production and natural environments and (ii) identify geographical and/or meteorological factors that affect the isolation of Listeria spp. in these environments. These data were also used to evaluate Listeria spp. as index organisms for L. monocytogenes in produce production environments. Environmental samples collected from produce production (n = 588) and natural (n = 734) environments in New York State were microbiologically analyzed to detect and isolate Listeria spp. The prevalence of Listeria spp. was approximately 33 and 34% for samples obtained from natural environments and produce production, respectively. Co-isolation of L. monocytogenes and at least one other species of Listeria in a given sample was recorded for 3 and 9% of samples from natural environments and produce production, respectively. Soil moisture and proximity to water and pastures were highly associated with isolation of Listeria spp. in produce production environments, while elevation, study site, and proximity to pastures were highly associated with isolation of Listeria spp. in natural environments, as determined by randomForest models. These data show that Listeria spp. were prevalent in both agricultural and nonagricultural environments and that geographical and meteorological factors associated with isolation of Listeria spp. were considerably different between the two environments.

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

Fresh produce outbreaks due to Shiga toxin-producing Escherichia coli (STEC) continue to occur in the United States (US). Manure-amended soils can pose a public health risk when used for growing raw agricultural commodities. Knowing the prevalence and concentration of STEC in untreated biological soil amendments of animal origin (BSAAO) is important to help guide the most appropriate pre-harvest interval(s) following application to limit risks from these soil amendments. Bovine manure samples were collected from 12 farms in Florida, including samples from piles, lagoons, barns, and screened solids. Two methods were used to detect stx1 / 2 and rfbE genes in samples. A prevalence rate of 9% for stx1 and/or stx2 and 19% for rfbE was observed from the 518 bovine manure samples evaluated. A most probable number (MPN) assay was performed on stx + samples when applicable. The geometric mean for stx+ samples (n = 20) was 3.37 MPN g -1 (0.53 log MPN g -1 ) with a maximum value of 6,800 MPN g -1 (3.83 log MPN g -1 ). This research was part of a larger nationwide geographical study on the prevalence and concentration of STEC in bovine manure to help guide regulations on feasible pre-harvest intervals for the application of untreated BSAAO.

The microbial quality of agricultural water is often assessed using fecal indicator bacteria (FIB) and physicochemical parameters. The presence, direction, and strength of associations between microbial and physicochemical parameters, and the presence of human pathogens in surface water vary across space (e.g., region) and time. This study was undertaken to understand these associations in two produce-growing regions in Florida, USA, and to examine the pathogen ecology in waterways used for produce production. The relationship between Salmonella presence, and microbial and physicochemical water quality; as well as weather and land use factors were evaluated. Water samples were collected from six sites in North Florida (N = 72 samples) and eight sites in South Florida (N = 96 samples) over 12 sampling months. Land use around each sampling site was characterized, and weather and water quality data were collected at each sampling. Salmonella, generic Escherichia coli, total coliform, and aerobic plate count bacteria populations were enumerated in each sample. Univariable and multivariable regression models were then developed to characterize associations between microbial water quality (i.e., E. coli levels and Salmonella presence), and water quality, weather, and land use factors separately for North and South Florida. The E. coli and total coliforms mean concentrations (log10 MPN/100 mL) were 1.8 ± 0.6 and >3.0 ± 0.4 in North and 1.3 ± 0.6 and >3.3 ± 0.2 in South Florida waterways, respectively. While Salmonella was detected in 23.6% (17/72) of North Florida and 28.1% (27/96) of South Florida samples, the concentration ranged between <0.48 and 1.4 log10 MPN/100 mL in North Florida, and <0.48 and 3.0 log10 MPN/100 mL in South Florida. Regression analyses showed no evidence of a correlation between either log10 total coliforms or E. coli levels, and if a sample was Salmonella-positive. The factors associated with Salmonella presence and log10E. coli levels in North Florida differed from those in South Florida; no factors retrained in multivariable regression models were the same for the North and South Florida models. The differences in associations between regions highlight the complexity of understanding pathogen ecology in freshwater environments and suggest substantial differences between intra-state regions in risk factors for Salmonella contamination of agricultural water.