Correlation of Salmonella enterica and Listeria monocytogenes in Irrigation Water to Environmental Factors, Fecal Indicators, and Bacterial Communities

Fine-scale spatiotemporal variations in bacterial community diversity in agricultural pond water

Microbial communities in surface waters are affected by environmental conditions and can influence changes in water quality. To explore the hypothesis that the microbiome in agricultural waters associates with spatiotemporal variations in overall water quality and, in turn, has implications for resource monitoring and management, we characterized the relationships between the microbiota and physicochemical properties in a model irrigation pond as a factor of sampling time (i.e., 9:00, 12:00, 15:00) and location within the pond (i.e., bank vs. interior sites and cross-sectional depths at 0, 1, and 2 m). The microbial communities, which were defined by 16S rRNA gene sequencing analysis, significantly varied based on all sampling factors (PERMANOVA P < 0.05 for each). While the relative abundances of dominant phyla (e.g., Proteobacteria and Bacteroidetes) were relatively stable throughout the pond, subtle yet significant increases in α-diversity were observed as the day progressed (ANOVA P < 0.001). Key water quality properties that also increased between the morning and afternoon (i.e., pH, dissolved oxygen, and temperature) positively associated with relative abundances of Cyanobacteria, though were inversely proportional to Verrucomicrobia. These properties, among additional parameters such as bioavailable nutrients (e.g., NH3, NO3, PO4), chlorophyll, phycocyanin, conductivity, and colored dissolved organic matter, exhibited significant relationships with relative abundances of various bacterial genera as well. Further investigation of the microbiota in underlying sediments revealed significant differences between the bank and interior sites of the pond (P < 0.05 for α- and β-diversity). Overall, our findings emphasize the importance of accounting for time of day and water sampling location and depth when surveying the microbiomes of irrigation ponds and other small freshwater sources.

Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.IMPORTANCEThe microbial ecology of water is already complex, without the added complications of methodological differences between studies. This study highlights the difficulty in comparing water quality data from projects that used different sampling or laboratory methods. These findings have direct implications for end users as there is no clear way to generalize findings in order to characterize broad-scale ecological phenomenon and develop science-based guidance. To best support development of risk assessments and guidance for monitoring and managing waters, data collection and methods need to be standardized across studies. A minimum set of data attributes that all studies should collect and report in a standardized way is needed. Given the diversity of methods used within applied and environmental microbiology, similar studies are needed for other microbiology subfields to ensure that guidance and policy are based on a robust interpretation of the literature.

Colonization of Raphanus sativus by human pathogenic microorganisms

Contamination of vegetables with human pathogenic microorganisms (HPMOs) is considered one of the most important problems in the food industry, as current nutritional guidelines include increased consumption of raw or minimally processed organic vegetables due to healthy lifestyle promotion. Vegetables are known to be potential vehicles for HPMOs and sources of disease outbreaks. In this study, we tested the susceptibility of radish (Raphanus sativus) to colonization by different HPMOs, including Escherichia coli PCM 2561, Salmonella enterica subsp. enterica PCM 2565, Listeria monocytogenes PCM 2191 and Bacillus cereus PCM 1948. We hypothesized that host plant roots containing bactericidal compounds are less prone to HPMO colonization than shoots and leaves. We also determined the effect of selected pathogens on radish growth to check host plant-microbe interactions. We found that one-week-old radish is susceptible to colonization by selected HPMOs, as the presence of the tested HPMOs was demonstrated in all organs of R. sativus. The differences were noticed 2 weeks after inoculation because B. cereus was most abundant in roots (log10 CFU - 2.54), S. enterica was observed exclusively in stems (log10 CFU - 3.15), and L. monocytogenes and E. coli were most abundant in leaves (log10 CFU - 4.80 and 3.23, respectively). The results suggest that E. coli and L. monocytogenes show a higher ability to colonize and move across the plant than B. cereus and S. enterica. Based on fluorescence in situ hybridization (FISH) and confocal laser scanning microscopy (CLSM) approach HPMOs were detected in extracellular matrix and in some individual cells of all analyzed organs. The presence of pathogens adversely affected the growth parameters of one-week-old R. sativus, especially leaf and stem fresh weight (decreased by 47-66 and 17-57%, respectively). In two-week-old plants, no reduction in plant biomass development was noted. This observation may result from plant adaptation to biotic stress caused by the presence of HPMOs, but confirmation of this assumption is needed. Among the investigated HPMOs, L. monocytogenes turned out to be the pathogen that most intensively colonized the aboveground part of R. sativus and at the same time negatively affected the largest number of radish growth parameters.

Conditional Forest Models Built Using Metagenomic Data Accurately Predicted Salmonella Contamination in Northeastern Streams

The use of water contaminated with Salmonella for produce production contributes to foodborne disease burden. To reduce human health risks, there is a need for novel, targeted approaches for assessing the pathogen status of agricultural water. We investigated the utility of water microbiome data for predicting Salmonella contamination of streams used to source water for produce production. Grab samples were collected from 60 New York streams in 2018 and tested for Salmonella. Separately, DNA was extracted from the samples and used for Illumina shotgun metagenomic sequencing. Reads were trimmed and used to assign taxonomy with Kraken2. Conditional forest (CF), regularized random forest (RRF), and support vector machine (SVM) models were implemented to predict Salmonella contamination. Model performance was assessed using 10-fold cross-validation repeated 10 times to quantify area under the curve (AUC) and Kappa score. CF models outperformed the other two algorithms based on AUC (0.86, CF; 0.81, RRF; 0.65, SVM) and Kappa score (0.53, CF; 0.41, RRF; 0.12, SVM). The taxa that were most informative for accurately predicting Salmonella contamination based on CF were compared to taxa identified by ALDEx2 as being differentially abundant between Salmonella-positive and -negative samples. CF and differential abundance tests both identified Aeromonas salmonicida (variable importance [VI] = 0.012) and Aeromonas sp. strain CA23 (VI = 0.025) as the two most informative taxa for predicting Salmonella contamination. Our findings suggest that microbiome-based models may provide an alternative to or complement existing water monitoring strategies. Similarly, the informative taxa identified in this study warrant further investigation as potential indicators of Salmonella contamination of agricultural water. IMPORTANCE Understanding the associations between surface water microbiome composition and the presence of foodborne pathogens, such as Salmonella, can facilitate the identification of novel indicators of Salmonella contamination. This study assessed the utility of microbiome data and three machine learning algorithms for predicting Salmonella contamination of Northeastern streams. The research reported here both expanded the knowledge on the microbiome composition of surface waters and identified putative novel indicators (i.e., Aeromonas species) for Salmonella in Northeastern streams. These putative indicators warrant further research to assess whether they are consistent indicators of Salmonella contamination across regions, waterways, and years not represented in the data set used in this study. Validated indicators identified using microbiome data may be used as targets in the development of rapid (e.g., PCR-based) detection assays for the assessment of microbial safety of agricultural surface waters.

Salmonella Prevalence Is Strongly Associated with Spatial Factors while Listeria monocytogenes Prevalence Is Strongly Associated with Temporal Factors on Virginia Produce Farms

The heterogeneity of produce production environments complicates the development of universal strategies for managing preharvest produce safety risks. Understanding pathogen ecology in different produce-growing regions is important for developing targeted mitigation strategies. This study aimed to identify environmental and spatiotemporal factors associated with isolating Salmonella and Listeria from environmental samples collected from 10 Virginia produce farms. Soil (n = 400), drag swab (n = 400), and irrigation water (n = 120) samples were tested for Salmonella and Listeria, and results were confirmed by PCR. Salmonella serovar and Listeria species were identified by the Kauffmann-White-Le Minor scheme and partial sigB sequencing, respectively. Conditional forest analysis and Bayesian mixed models were used to characterize associations between environmental factors and the likelihood of isolating Salmonella, Listeria monocytogenes (LM), and other targets (e.g., Listeria spp. and Salmonella enterica serovar Newport). Surrogate trees were used to visualize hierarchical associations identified by the forest analyses. Salmonella and LM prevalence was 5.3% (49/920) and 2.3% (21/920), respectively. The likelihood of isolating Salmonella was highest in water samples collected from the Eastern Shore of Virginia with a dew point of >9.4°C. The likelihood of isolating LM was highest in water samples collected in winter from sites where <36% of the land use within 122 m was forest wetland cover. Conditional forest results were consistent with the mixed models, which also found that the likelihood of detecting Salmonella and LM differed between sample type, region, and season. These findings identified factors that increased the likelihood of isolating Salmonella- and LM-positive samples in produce production environments and support preharvest mitigation strategies on a regional scale. IMPORTANCE This study sought to examine different growing regions across the state of Virginia and to determine how factors associated with pathogen prevalence may differ between regions. Spatial and temporal data were modeled to identify factors associated with an increased pathogen likelihood in various on-farm sources. The findings of the study show that prevalence of Salmonella and L. monocytogenes is low overall in the produce preharvest environment but does vary by space (e.g., region in Virginia) and time (e.g., season), and the likelihood of pathogen-positive samples is influenced by different spatial and temporal factors. Therefore, the results support regional or scale-dependent food safety standards and guidance documents for controlling hazards to minimize risk. This study also suggests that water source assessments are important tools for developing monitoring programs and mitigation measures, as spatiotemporal factors differ on a regional scale.

Temporal stability of Salmonella enterica and Listeria monocytogenes in surface waters used for irrigation in the Mid-Atlantic United States

Enteric bacterial pathogen levels can influence the suitability of irrigation water sources for fruits and vegetables. We hypothesize that stable spatial patterns of Salmonella enterica and Listeria monocytogenes levels may exist across surface water sources in the Mid-Atlantic U.S. Water samples were collected at four streams and two pond sites in the mid-Atlantic U.S. over 2 years, biweekly during the fruit and vegetable growing seasons, and once a month during nongrowing seasons. Two stream sites and one pond site had significantly different mean concentrations in growing and nongrowing seasons. Stable spatial patterns were determined for relative differences between the site concentrations and average concentration of both pathogens across the study area. Mean relative differences were significantly different from zero at four of the six sites for S. enterica and three of six sites for L. monocytogenes. There was a similarity between the mean relative difference distribution between sites over growing season, nongrowing season, and the entire observation period. Mean relative differences were determined for temperature, oxidation-reduction potential, specific electrical conductance, pH, dissolved oxygen, turbidity, and cumulative rainfall. A moderate-to-strong Spearman correlation (r_s > 0.657) was found between spatial patterns of S. enterica and 7-day rainfall, and between relative difference patterns of L. monocytogenes and temperature (r_s = 0.885) and dissolved oxygen (r_s = -0.885). Persistence in ranking sampling sites by the concentrations of the two pathogens was also observed. Finding spatially stable patterns in pathogen concentrations highlights spatiotemporal dynamics of these microorganisms across the study area can facilitate the design of an effective microbial water quality monitoring program for surface irrigation water.

A longitudinal study to examine the influence of farming practices and environmental factors on pathogen prevalence using structural equation modeling

The contamination of fresh produce with foodborne pathogens has been an on-going concern with outbreaks linked to these commodities. Evaluation of farm practices, such as use of manure, irrigation water source, and other factors that could influence pathogen prevalence in the farming environment could lead to improved mitigation strategies to reduce the potential for contamination events. Soil, water, manure, and compost were sampled from farms in Ohio and Georgia to identify the prevalence of Salmonella, Listeria monocytogenes (Lm), Campylobacter, and Shiga-toxin-producing Escherichia coli (STEC), as well as Arcobacter, an emerging human pathogen. This study investigated agricultural practices to determine which influenced pathogen prevalence, i.e., the percent positive samples. These efforts identified a low prevalence of Salmonella, STEC, and Campylobacter in soil and water (< 10%), preventing statistical modeling of these pathogens. However, Lm and Arcobacter were found in soil (13 and 7%, respectively), manure (49 and 32%, respectively), and water samples (18 and 39%, respectively) at a comparatively higher prevalence, suggesting different dynamics are involved in their survival in the farm environment. Lm and Arcobacter prevalence data, soil chemical characteristics, as well as farm practices and weather, were analyzed using structural equation modeling to identify which factors play a role, directly or indirectly, on the prevalence of these pathogens. These analyses identified an association between pathogen prevalence and weather, as well as biological soil amendments of animal origin. Increasing air temperature increased Arcobacter and decreased Lm. Lm prevalence was found to be inversely correlated with the use of surface water for irrigation, despite a high Lm prevalence in surface water suggesting other factors may play a role. Furthermore, Lm prevalence increased when the microbiome's Simpson's Diversity Index decreased, which occurred as soil fertility increased, leading to an indirect positive effect for soil fertility on Lm prevalence. These results suggest that pathogen, environment, and farm management practices, in addition to produce commodities, all need to be considered when developing mitigation strategies. The prevalence of Arcobacter and Lm versus the other pathogens suggests that multiple mitigation strategies may need to be employed to control these pathogens.

Asymptomatic Carriage of Listeria monocytogenes by Animals and Humans and Its Impact on the Food Chain

Humans and animals can become asymptomatic carriers of Listeria monocytogenes and introduce the pathogen into their environment with their feces. In turn, this environmental contamination can become the source of food- and feed-borne illnesses in humans and animals, with the food production chain representing a continuum between the farm environment and human populations that are susceptible to listeriosis. Here, we update a review from 2012 and summarize the current knowledge on the asymptomatic carrier statuses in humans and animals. The data on fecal shedding by species with an impact on the food chain are summarized, and the ways by which asymptomatic carriers contribute to the risk of listeriosis in humans and animals are reviewed.

Gut microbiome interactions with graphene based nanomaterials: Challenges and opportunities

Rapid growth of nanotechnology has accelerated immense possibility of engineered nanomaterials (ENMs) exposure by human and living organisms. In this context, wide range applications of graphene based nanomaterials (GBNMs) may inevitably cause their release into the environment. Consequently, potential risks to the ecological system and human health is consistently increasing due to the probable ingestion of GBNMs by mean of contaminated water or food sources. Further, gut microbiome is known to play a profound impact on the health status of human being and has been recognized as the most exciting advancement in the biomedical science. Recent studies has shown vital role of ENMs to alter gut microbiome and thereby changed pathological status of organisms. Therefore, in this review results of numerous studies dedicated to explore the impact of GBNMs on gut microbiome and thereby various pathological status have been summarized. Dietary exposure of different types of GBNMs [e.g. graphene, graphene oxide (GO), partially reduced graphene oxide (PRGO), graphene quantum dots (GQDs)] have been evaluated on the gut microbiome through numerous in vitro and in vivo models. Moreover, emphasis has been made to evaluate different physiological responses with the short/long-term exposure of GBNMs, particularly in gastrointestinal tract (GIT) and its correlation with gut microbiome and the health status. It is reviewed that exposure of GBNMs can exert significant impact which alter the composition, diversity and function of gut microbiome. This may further appear in terms of enteric disorder along with numerous pathological changes e.g. IEC (intestinal epithelial cells) colitis, lysosomal dysfunction, inflammation, shortened colon, resorbed embryo, retardation in skeletal development, low weight of fetus, early or late dead of fetus and IBD (inflammatory bowel disease) like symptoms. Finally, potential health risks due to the exposure of GBNMs have been discussed with future perspective.

Wastewater reuse for irrigation of produce: A review of research, regulations, and risks

The burden of disease caused by the contamination of ready-to-eat produce with common waterborne microbial pathogens suggests that irrigation supplies should be closely monitored and regulated. Simultaneously freshwater resources have become increasingly scarce worldwide while global demand continues to grow. Since the turn of the 20th century with the advent of modern wastewater treatment plants, the reuse of treated wastewater is considered a safe and viable water source for irrigation of ready-to-eat vegetables. However strict, and often costly, treatment regimens mean that only a fraction of the world's wastewater supplies are being put to reuse. The purpose of this review is to explore the available literature on the risks associated with reuse water for ready-to-eat produce production including different approaches to reducing those risks as the demand for reuse water increases. It is not the intent of the authors to determine which methods of treatment should be applied, which pathogens should be considered of greatest concern, or which regulations should be applied. Rather, it is meant to be a discussion of the evolving guidelines governing irrigation with reuse water, potential risks from known pathogens common to produce production and recommendations for improving the adoption of water reuse moving forward. To date, there is little evidence to suggest that adequately treated reuse water poses more risk for produce-related illness or outbreaks than other sources of irrigation water. However, multiple epidemiological and quantitative risk assessment models suggest that guidelines for the use of reuse water should be regionally specific and based on local growing practices, available technologies for wastewater treatment, and overall population health. Though research suggests water reuse is generally safe, the assumptions of risk are both personal and of public interest, they should be considered carefully before water reuse is either allowed or disallowed in produce production environments.

Prevalence and Clonal Diversity of over 1,200 Listeria monocytogenes Isolates Collected from Public Access Waters near Produce Production Areas on the Central California Coast during 2011 to 2016

A 5-year survey of public access surface waters in an agricultural region of the Central California Coast was done to assess the prevalence of the foodborne pathogen Listeria monocytogenes. In nature, L. monocytogenes lives as a saprophyte in soil and water, which are reservoirs for contamination of preharvest produce. Moore swabs were deployed biweekly in lakes, ponds, streams, and rivers during 2011 to 2016. L. monocytogenes was recovered in 1,224 of 2,922 samples, resulting in 41.9% prevalence. Multiple subtypes were isolated from 97 samples, resulting in 1,323 L. monocytogenes isolates. Prevalence was higher in winter and spring and after rain events in some waterways. Over 84% of the isolates were serotype 4b. Whole-genome sequencing was done on 1,248 isolates, and in silico multilocus sequence typing revealed 74 different sequence types (STs) and 39 clonal complexes (CCs). The clones most isolated, CC639, CC183, and CC1, made up 27%, 19%, and 13%, respectively, of the sequenced isolates. Other types were CC663, CC6, CC842, CC4, CC2, CC5, and CC217. All sequenced isolates contained intact copies of core L. monocytogenes virulence genes, and pathogenicity islands LIPI-3 and LIPI-4 were identified in 73% and 63%, respectively, of the sequenced isolates. The virulence factor internalin A was predicted to be intact in all but four isolates, while genes important for sanitizer and heavy metal resistance were found in <5% of the isolates. These waters are not used for crop irrigation directly, but they are available to wildlife and can flood fields during heavy rains. IMPORTANCE Listeria monocytogenes serotype 4b and 1/2a strains are implicated in most listeriosis, and hypervirulent listeriosis stems from strains containing pathogenicity islands LIPI-3 and LIPI-4. The waters and sediments in the Central California Coast agricultural region contain widespread and diverse L. monocytogenes populations, and all the isolates contain intact virulence genes. Emerging clones CC183 and CC639 were the most abundant clones, and major clones CC1, CC4, and CC6 were well represented. CC183 was responsible for three produce-related outbreaks in the last 7 years. Most of the isolates in the survey differ from those of lesser virulence that are often isolated from foods and food processing plants because they contain genes encoding an intact virulence factor, internalin A, and most did not contain genes for sanitizer and heavy metal resistance. This isolate collection is important for understanding L. monocytogenes populations in agricultural and natural regions.

Salmonella enterica Serovar Diversity, Distribution, and Prevalence in Public Access Waters from a Central California Coastal Leafy Green Growing Region during 2011 - 2016

Prevalence and serovar diversity of Salmonella enterica was measured during a five-year survey of surface waters in a 500 mi^2 agricultural region of the Central California Coast. Rivers, streams, lakes, and ponds were sampled bimonthly resulting in 2,979 samples. Overall prevalence was 56.4% with higher levels detected in Spring than in Fall. Small, but significant, differences in prevalence were detected based on sample locations. Detection of Salmonella was correlated positively with both significant rain events and, in some environments, levels of generic Escherichia coli. Analysis of 1,936 isolates revealed significant serovar diversity, with 91 different serovars detected. The most common isolated serovars were S. enterica subsp. enterica serovars I 6,8:d:- (406 isolates, 21.0%, and potentially monophasic Salmonella Muenchen), Give (334 isolates, 17.3%), Muenchen (158 isolates, 8.2%), Typhimurium (227 isolates, 11.7%), Oranienburg (106 isolates, 5.5%), and Montevideo (78 isolates, 4%). Sixteen of the 24 most common serovars detected in the region are among the serovars reported to cause the most human salmonellosis in the United States. Some of the serovars were associated with location and seasonal bias. Analysis of XbaI Pulsed Field Gel Electrophoresis (PFGE) patterns of strains of serovars Typhimurium, Oranienburg, and Montevideo showed significant intra-serovar diversity. PFGE pulsotypes were identified in the region for multiple years of the survey, indicating persistence or regular re-introduction to the region. Importance Non-typhoidal Salmonella is the among the leading causes of bacterial foodborne illness and increasing numbers of outbreaks and recalls are due to contaminated produce. High prevalence and 91 different serovars were detected in this leafy green growing region. Seventeen serovars that cause most of the human salmonellosis in the United States were detected, with 16 of those serovars detected in multiple locations and multiple years of the 5-year survey. Understanding the widespread prevalence and diversity of Salmonella in the region will assist in promoting food safety practices and intervention methods for growers and regulators.

Prevalence and Antimicrobial Resistance Profiles of Foodborne Pathogens Isolated from Dairy Cattle and Poultry Manure Amended Farms in Northeastern Ohio, the United States

Foodborne pathogens significantly impact public health globally. Excessive antimicrobial use plays a significant role in the development of the public health crisis of antibiotic resistance. Here, we determined the prevalence and antimicrobial resistance profiles of E. coli O157, Salmonella, L. monocytogenes, and Campylobacter isolated between 2016 and 2020 from small scale agricultural settings that were amended with dairy cattle or poultry manure in Northeastern Ohio. The total prevalence of the foodborne pathogens was 19.3%: Campylobacter 8%, Listeria monocytogenes 7.9%, Escherichia coli O157 1.8%, and Salmonella 1.5%. The prevalence was significantly higher in dairy cattle (87.7%) compared to poultry (12.2%) manure amended farms. Furthermore, the prevalence was higher in manure samples (84%) compared to soil samples (15.9%; p < 0.05). Multiple drug resistance was observed in 73%, 77%, 100%, and 57.3% of E. coli O157, Salmonella, L. monocytogenes, and Campylobacter isolates recovered, respectively. The most frequently observed resistance genes were mphA, aadA, and aphA1 in E. coli O157; blaTEM, tet(B), and strA in Salmonella; penA, ampC, lde, ermB, tet(O), and aadB in L. monocytogenes and blaOXA-61, tet(O), and aadE in Campylobacter. Our results highlight the critical need to address the dissemination of foodborne pathogens and antibiotic resistance in agricultural settings.

The Persistence of Bacterial Pathogens in Surface Water and Its Impact on Global Food Safety

Water is vital to agriculture. It is essential that the water used for the production of fresh produce commodities be safe. Microbial pathogens are able to survive for extended periods of time in water. It is critical to understand their biology and ecology in this ecosystem in order to develop better mitigation strategies for farmers who grow these food crops. In this review the prevalence, persistence and ecology of four major foodborne pathogens, Shiga toxin-producing Escherichia coli (STEC), Salmonella, Campylobacter and closely related Arcobacter, and Listeria monocytogenes, in water are discussed. These pathogens have been linked to fresh produce outbreaks, some with devastating consequences, where, in a few cases, the contamination event has been traced to water used for crop production or post-harvest activities. In addition, antimicrobial resistance, methods improvements, including the role of genomics in aiding in the understanding of these pathogens, are discussed. Finally, global initiatives to improve our knowledge base of these pathogens around the world are touched upon.

Pathogen and Surrogate Survival in Relation to Fecal Indicator Bacteria in Freshwater Mesocosms

The microbial quality of agricultural water for fresh produce production is determined by the presence of the fecal indicator bacterium (FIB) Escherichia coli, despite poor correlations with pathogen presence. Additional FIB, such as enterococci, have been utilized for assessing water quality. The study objective was to determine the survival times (first time to detect zero or censored) of FIB (E. coli and enterococci), surrogates (Listeria innocua, Listeria seeligeri, Salmonella enterica serovar Typhimurium, and PRD1), and pathogens (four strains each of pathogenic E. coli and Listeria monocytogenes and five Salmonella serovars) simultaneously inoculated in freshwater mesocosms exposed to diel and seasonal variations. Six separate mesocosm experiments were conducted for ≤28 days each season, with samples (sediment/water) collected each day for the first 7 days and weekly thereafter. Microorganisms survived significantly longer in sediment than in water (hazard ratio [HR] for water/sediment is 2.2; 95% confidence interval [CI], 1.79 to 2.71). Also, FIB E. coli survived significantly longer than FIB enterococcus (HR for enterococci/E. coli is 12.9 [95% CI, 8.18 to 20.37]) after adjusting for the sediment/water and lake/river effects. Differences in the area under the curve (calculated from log CFU or PFU over time) were used to assess pathogen and surrogate survival in relation to FIB. Despite sample type (sediment/water) and seasonal influences, survival rates of pathogenic Salmonella serovars were similar to those of FIB E. coli, and survival rates of L. monocytogenes and pathogenic E. coli were similar to those of FIB enterococci. Further investigation of microbial survival in water and sediment is needed to determine which surrogates are best suited to assess pathogen survival in agricultural water used in irrigation water for fresh produce. IMPORTANCE Contamination of fresh produce via agricultural water is well established. This research demonstrates that survival of fecal indicator bacteria, pathogenic microorganisms, and other bacterial and viral surrogates in freshwater differs by sample type (sediment/water) and season. Our work highlights potential risks associated with pathogen accumulation and survival in sediment and the possibility for resuspension and contamination of agricultural water used in fresh produce production. Specifically, a greater microbial persistence in sediments than in water over time was observed, along with differences in survival among microorganisms in relation to the fecal indicator bacteria E. coli and enterococci. Previous studies compared data among microbial groups in different environments. Conversely, fecal indicator bacteria, surrogates, and pathogenic microorganisms were assessed within the same water and sediment mesocosms in the present study during four seasons, better representing the agricultural aquatic environment. These data should be considered when agricultural microbial water quality criteria in fresh produce operations are being determined.