Correlation between E. coli levels and the presence of foodborne pathogens in surface irrigation water: Establishment of a sampling program

Total coliforms, microbial diversity and multiple characteristics of Salmonella in soil-irrigation water-fresh vegetable system in Shaanxi, China

Global occurrences of foodborne disease outbreaks have been documented, involving fresh agricultural produce contaminated by various pathogens. This contamination can occur at any point in the supply chain. However, studies on the prevalence of total coliforms, Salmonella and microbial diversity in vegetable and associated environments are limited. This study aimed to assess 1) the number of total coliforms (n = 299) and diversity of microbial communities (n = 52); 2) the prevalence, antibiotic susceptibility, genomic characteristics, and potential transmission relationships of Salmonella in soil-irrigation water-vegetable system (n = 506). Overall, 84.28 % samples were positive to total coliforms, with most frequently detected in soil (100 %), followed by irrigation water (79.26 %) and vegetables (62.00 %). A seasonal trend in coliform prevalence was observed, with significantly higher levels in summer (P < 0.05). Detection rates of Salmonella in soil, vegetable and irrigation water were 2.21 %, 4.74 % and 9.40 %. Fourteen serotypes and sequence types (STs) were respectively annotated in 56 Salmonella isolates, ST13 S. Agona (30.36 %, 17/56), ST469 S. Rissen (25.00 %, 14/56), and ST36 S. Typhimurium (12.50 %, 7/56) were dominant serotypes and STs. Thirty-one (55.36 %) isolates were multi-drug resistant, and the resistance was most frequently found to ampicillin (55.36 %, 31/56), followed by to sulfamethoxazole (51.79 %, 29/56) and tetracycline (50.00 %, 28/56). The genomic characteristics and antibiotic resistance patterns of Salmonella isolates from soil, vegetables, and irrigation water within a coherent geographical locale exhibited remarkable similarities, indicating Salmonella may be transmitted among these environments or have a common source of contamination. Microbial alpha diversity indices in soil were significantly higher (P < 0.05) than that in vegetable and irrigation water. The microbial phylum in irrigation water covered that in the vegetable, demonstrating a significant overlap in the microbial communities between the vegetables and the irrigation water.

Traditional and new proposals for environmental microbial indicators-a review

The continuous increment in world population coupled with the greatest natural resource consumption and waste generation has an enormous impact on the environment. To date, using biological indicators (bioindicators) to evaluate the biological quality of natural environments is very common. Nonetheless, selecting those suitable for each ecosystem or contaminant is one of the most important issues for environmental sciences. Bacteria and helminths are mainly related to fecal contamination, while antibiotic-resistant bacteria, fungi, viruses, and microalgae are organisms used to determine deteriorated ecosystems by diverse contaminants. Nowadays, each bioindicator is used as a specific agent of different contaminant types, but detecting and quantifying these bioindicator microorganisms can be performed from simple microscopy and culture methods up to a complex procedure based on omic sciences. Developing new techniques based on the metabolism and physiological responses of traditional bioindicators is shown in a fast environmental sensitivity analysis. Therefore, the present review focuses on analyzing different bioindicators to facilitate developing suitable monitoring environmental systems according to different pollutant agents. The traditional and new methods proposed to detect and quantify different bioindicators are also discussed. Their vital role is considered in implementing efficient ecosystem bioprospection, restoration, and conservation strategies directed to natural resource management.

Microbiological hazards associated with the use of water in the post-harvest handling and processing operations of fresh and frozen fruits, vegetables and herbs (ffFVHs). Part 1 (outbreak data analysis, literature review and stakeholder questionnaire)

The contamination of water used in post-harvest handling and processing operations of fresh and frozen fruit, vegetables and herbs (ffFVHs) is a global concern. The most relevant microbial hazards associated with this water are: Listeria monocytogenes, Salmonella spp., human pathogenic Escherichia coli and enteric viruses, which have been linked to multiple outbreaks associated with ffFVHs in the European Union (EU). Contamination (i.e. the accumulation of microbiological hazards) of the process water during post-harvest handling and processing operations is affected by several factors including: the type and contamination of the FVHs being processed, duration of the operation and transfer of microorganisms from the product to the water and vice versa, etc. For food business operators (FBOp), it is important to maintain the microbiological quality of the process water to assure the safety of ffFVHs. Good manufacturing practices (GMP) and good hygienic practices (GHP) related to a water management plan and the implementation of a water management system are critical to maintain the microbiological quality of the process water. Identified hygienic practices include technical maintenance of infrastructure, training of staff and cooling of post-harvest process water. Intervention strategies (e.g. use of water disinfection treatments and water replenishment) have been suggested to maintain the microbiological quality of process water. Chlorine-based disinfectants and peroxyacetic acid have been reported as common water disinfection treatments. However, given current practices in the EU, evidence of their efficacy under industrial conditions is only available for chlorine-based disinfectants. The use of water disinfection treatments must be undertaken following an appropriate water management strategy including validation, operational monitoring and verification. During operational monitoring, real-time information on process parameters related to the process and product, as well as the water and water disinfection treatment(s) are necessary. More specific guidance for FBOp on the validation, operational monitoring and verification is needed.

Reduction of pathogenic bacteria from irrigation water through a copper-loaded porous ceramic emitter

The increasing pathogenic bacteria threat in irrigation water has become a worldwide concern, prompting efforts to discover a new cost-effective method for pathogenic bacteria eradication, different than those currently in use. In this study, a novel copper-loaded porous ceramic emitter (CPCE) was developed via molded sintering method to kill bacteria from irrigation water. The material performance and hydraulic properties of CPCE are discussed herein, and the antibacterial effect against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) was evaluated. The incremental copper content in CPCE improved flexural strength and pore size, which was conducive to enhancing CPCE discharge. Moreover, antibacterial tests showed that CPCE displayed efficient antimicrobial activity, killing 99.99% and more than 70% of S. aureus and E. coli, respectively. The results reveal that CPCE, with both irrigation and sterilization functions, can provide a low-cost and effective solution for bacterial removal from irrigation water.

ESBL Producing Escherichia coli in Faecal Sludge Treatment Plants: An Invisible Threat to Public Health in Rohingya Camps, Cox's Bazar, Bangladesh

Introduction: Human faecal sludge contains diverse harmful microorganisms, making it hazardous to the environment and public health if it is discharged untreated. Faecal sludge is one of the major sources of E. coli that can produce extended-spectrum β-lactamases (ESBLs).

Objective: This study aimed to investigate the prevalence and molecular characterization of ESBL-producing E. coli in faecal sludge samples collected from faecal sludge treatment plants (FSTPs) in Rohingya camps, Bangladesh.

Methods: ESBL producing E. coli were screened by cultural as well as molecular methods and further characterized for their major ESBL genes, plasmid profiles, pathotypes, antibiotic resistance patterns, conjugation ability, and genetic similarity.

Results: Of 296 isolates, 180 were phenotypically positive for ESBL. All the isolates, except one, contained at least one ESBL gene that was tested (bla_CTX−M−1, bla_CTX−M−2, bla_CTX−M−8, bla_CTX−M−9, bla_CTX−M−15, bla_CTX−M−25, bla_TEM, and bla_SHV). From plasmid profiling, it was observed that plasmids of 1–211 MDa were found in 84% (151/180) of the isolates. Besides, 13% (24/180) of the isolates possessed diarrhoeagenic virulence genes. From the remaining isolates, around 51% (79/156) harbored at least one virulence gene that is associated with the extraintestinal pathogenicity of E. coli. Moreover, 4% (3/156) of the isolates were detected to be potential extraintestinal pathogenic E. coli (ExPEC) strains. Additionally, all the diarrhoeagenic and ExPEC strains showed resistance to three or more antibiotic groups which indicate their multidrug-resistant potential. ERIC-PCR differentiated these pathogenic isolates into seven clusters. In addition to this, 16 out of 35 tested isolates transferred plasmids of 32–112 MDa to E. coli J53 recipient strain.

Conclusion: The present study implies that the faecal sludge samples examined here could be a potential origin for spreading MDR pathogenic ESBL-producing E. coli. The exposure of Rohingya individuals, living in overcrowded camps, to these organisms poses a severe threat to their health.

Correlation value determined to increase Salmonella prediction success of deep neural network for agricultural waters

The use of computer-based tools has been becoming popular in the field of produce safety. Various algorithms have been applied to predict the population and presence of indicator microorganisms and pathogens in agricultural water sources. The purpose of this study is to improve the Salmonella prediction success of deep feed-forward neural network (DFNN) in agricultural surface waters with a determined correlation value based on selected features. Datasets were collected from six agricultural ponds in Central Florida. The most successful physicochemical and environmental features were selected by the gain ratio for the prediction of generic Escherichia coli population with machine learning algorithms (decision tree, random forest, support vector machine). Salmonella prediction success of DFNN was evaluated with dataset including selected environmental and physicochemical features combined with predicted E. coli populations with and without correlation value. The performance of correlation value was evaluated with all possible mathematical dataset combinations (nCr) of six ponds. The higher accuracy performances (%) were achieved through DFNN analyses with correlation value between 88.89 and 98.41 compared to values with no correlation value from 83.68 to 96.99 for all dataset combinations. The findings emphasize the success of determined correlation value for the prediction of Salmonella presence in agricultural surface waters.

Prediction of E. coli Concentrations in Agricultural Pond Waters: Application and Comparison of Machine Learning Algorithms

The microbial quality of irrigation water is an important issue as the use of contaminated waters has been linked to several foodborne outbreaks. To expedite microbial water quality determinations, many researchers estimate concentrations of the microbial contamination indicator Escherichia coli (E. coli) from the concentrations of physiochemical water quality parameters. However, these relationships are often non-linear and exhibit changes above or below certain threshold values. Machine learning (ML) algorithms have been shown to make accurate predictions in datasets with complex relationships. The purpose of this work was to evaluate several ML models for the prediction of E. coli in agricultural pond waters. Two ponds in Maryland were monitored from 2016 to 2018 during the irrigation season. E. coli concentrations along with 12 other water quality parameters were measured in water samples. The resulting datasets were used to predict E. coli using stochastic gradient boosting (SGB) machines, random forest (RF), support vector machines (SVM), and k-nearest neighbor (kNN) algorithms. The RF model provided the lowest RMSE value for predicted E. coli concentrations in both ponds in individual years and over consecutive years in almost all cases. For individual years, the RMSE of the predicted E. coli concentrations (log10 CFU 100 ml-1) ranged from 0.244 to 0.346 and 0.304 to 0.418 for Pond 1 and 2, respectively. For the 3-year datasets, these values were 0.334 and 0.381 for Pond 1 and 2, respectively. In most cases there was no significant difference (P > 0.05) between the RMSE of RF and other ML models when these RMSE were treated as statistics derived from 10-fold cross-validation performed with five repeats. Important E. coli predictors were turbidity, dissolved organic matter content, specific conductance, chlorophyll concentration, and temperature. Model predictive performance did not significantly differ when 5 predictors were used vs. 8 or 12, indicating that more tedious and costly measurements provide no substantial improvement in the predictive accuracy of the evaluated algorithms.

New standards at European Union level on water reuse for agricultural irrigation: Are the Spanish wastewater treatment plants ready to produce and distribute reclaimed water within the minimum quality requirements?

The new European regulation on minimum quality requirements (MQR) for water reuse (EU, 2020/741) was launched in May 2020 and describes the directives for the use of reclaimed water for agricultural irrigation. This Regulation will be directly applicable in all Member States from 26 June 2023. Since its publication in 2020, concerns have raised about potential non-compliance situations in water reuse systems. The present study represents a case study where three different water reuse systems have been monitored to establish their compliance with the MQR. Each water reuse system includes a wastewater treatment plant (WWTP), a distribution/storage system and an end-user point, where water is used for irrigation of leafy greens. The selected water reuse systems allowed us to compare the efficacy of water treatments implemented in two WWTPs as well as the impact of three different irrigation systems (drip, furrow and overhead irrigation). The presence and concentration of indicator microorganisms (Escherichia coli and C. perfringens spores) as well as pathogenic bacteria (Shiga toxin-producing, E. coli (STEC), E. coli O157:H7, and Salmonella spp.) were monitored in different sampling points (influent and effluent of the WWTPs, water reservoirs located at the distribution system and the end-user point at the irrigation system as well as in the leafy greens during their growing cycle. Average levels of E. coli (0.73 ± 1.20 log cfu E. coli/100 mL) obtained at the point where the WWTP operator delivers reclaimed water to the next actor in the chain, defined in the European regulation as the 'point of compliance', were within the established MQR (<1 log cfu/100 mL) (EU, 2020/741). On the other hand, average levels of E. coli at the end-user point (1.0 ± 1.2 log cfu/100 mL) were below the recommended threshold (2 log cfu E. coli/100 mL) for irrigation water based on the guidance document on microbiological risks in fresh fruits and vegetables at primary production (EC, 2017/C_163/01). However, several outlier points were observed among the samples taken at the irrigation point, which were linked to a specific cross-contamination event within the distribution/storage system. Regarding pathogenic bacteria, water samples from the influent of the WWTPs showed a 100% prevalence, while only 5% of the effluent samples were positive for any of the monitored pathogenic bacteria. Obtained results indicate that reclaimed water produced in the selected water reuse system is suitable to be used as irrigation water. However, efforts are necessary not only in the establishment of advance disinfection treatments but also in the maintenance of the distribution/storage systems.

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.

Salmonella Genomics and Population Analyses Reveal High Inter- and Intraserovar Diversity in Freshwater

Freshwater can support the survival of the enteric pathogen Salmonella, though temporal Salmonella diversity in a large watershed has not been assessed. At 28 locations within the Susquehanna River basin, 10-liter samples were assessed in spring and summer over 2 years. Salmonella prevalence was 49%, and increased river discharge was the main driver of Salmonella presence. The amplicon-based sequencing tool, CRISPR-SeroSeq, was used to determine serovar population diversity and detected 25 different Salmonella serovars, including up to 10 serovars from a single water sample. On average, there were three serovars per sample, and 80% of Salmonella-positive samples contained more than one serovar. Serovars Give, Typhimurium, Thompson, and Infantis were identified throughout the watershed and over multiple collections. Seasonal differences were evident: serovar Give was abundant in the spring, whereas serovar Infantis was more frequently identified in the summer. Eight of the ten serovars most commonly associated with human illness were detected in this study. Crucially, six of these serovars often existed in the background, where they were masked by a more abundant serovar(s) in a sample. Serovars Enteritidis and Typhimurium, especially, were masked in 71 and 78% of samples where they were detected, respectively. Whole-genome sequencing-based phylogeny demonstrated that strains within the same serovar collected throughout the watershed were also very diverse. The Susquehanna River basin is the largest system where Salmonella prevalence and serovar diversity have been temporally and spatially investigated, and this study reveals an extraordinary level of inter- and intraserovar diversity.IMPORTANCE Salmonella is a leading cause of bacterial foodborne illness in the United States, and outbreaks linked to fresh produce are increasing. Understanding Salmonella ecology in freshwater is of importance, especially where irrigation practices or recreational use occur. As the third largest river in the United States east of the Mississippi, the Susquehanna River is the largest freshwater contributor to the Chesapeake Bay, and it is the largest river system where Salmonella diversity has been studied. Rainfall and subsequent high river discharge rates were the greatest indicators of Salmonella presence in the Susquehanna and its tributaries. Several Salmonella serovars were identified, including eight commonly associated with foodborne illness. Many clinically important serovars were present at a low frequency within individual samples and so could not be detected by conventional culture methods. The technologies employed here reveal an average of three serovars in a 10-liter sample of water and up to 10 serovars in a single sample.

Application of QMRA to MAR operations for safe agricultural water reuses in coastal areas

A pathogenic Escherichia coli (E.coli) O157:H7 and O26:H11 dose-response model was set up for a quantitative microbial risk assessment (QMRA) of the waterborne diseases associated with managed aquifer recharge (MAR) practices in semiarid regions. The MAR facility at Forcatella (Southern Italy) was selected for the QMRA application. The target counts of pathogens incidentally exposed to hosts by eating contaminated raw crops or while bathing at beaches of the coastal area were determined by applying the Monte Carlo Markov Chain (MCMC) Bayesian method to the water sampling results. The MCMC provided the most probable pathogen count reaching the target and allowed for the minimization of the number of water samplings, and hence, reducing the associated costs. The sampling stations along the coast were positioned based on the results of a groundwater flow and pathogen transport model, which highlighted the preferential flow pathways of the transported E. coli in the fractured coastal aquifer. QMRA indicated tolerable (<10^-6 DALY) health risks for bathing at beaches and irrigation with wastewater, with 0.4 infectious diseases per year (11.4% probability of occurrence) associated with the reuse of reclaimed water via soil irrigation even though exceeding the E. coli regulation limit of 10 CFU/100 mL by five times. The results show negligible health risk and insignificant impacts on the coastal water quality due to pathogenic E. coli in the wastewater used for MAR. However, droughts and reclaimed water quality can be considered the main issues of MAR practices in semiarid regions suggesting additional reclaimed water treatments and further stress-tests via QMRAs by considering more persistent pathogens than E. coli.

The Composition of Microbial Communities in Six Streams, and Its Association With Environmental Conditions, and Foodborne Pathogen Isolation

Surface water used for produce production is a potential source of pre-harvest contamination with foodborne pathogens. Decisions on how to mitigate food safety risks associated with pre-harvest water use currently rely on generic Escherichia coli-based water quality tests, although multiple studies have suggested that E. coli levels are not a suitable indicator of the food safety risks under all relevant environmental conditions. Hence, improved understanding of spatiotemporal variability in surface water microbiota composition is needed to facilitate identification of alternative or supplementary indicators that co-occur with pathogens. To this end, we aimed to characterize the composition of bacterial and fungal communities in the sediment and water fractions of 68 agricultural water samples collected from six New York streams. We investigated potential associations between the composition of microbial communities, environmental factors and Salmonella and/or Listeria monocytogenes isolation. We found significantly different composition of fungal and bacterial communities among sampled streams and among water fractions of collected samples. This indicates that geography and the amount of sediment in a collected water sample may affect its microbial composition, which was further supported by identified associations between the flow rate, turbidity, pH and conductivity, and microbial community composition. Lastly, we identified specific microbial families that were weakly associated with the presence of Salmonella or Listeria monocytogenes, however, further studies on samples from additional streams are needed to assess whether identified families may be used as indicators of pathogen presence.

Reviving the "Moore Swab": a Classic Environmental Surveillance Tool Involving Filtration of Flowing Surface Water and Sewage Water To Recover Typhoidal Salmonella Bacteria

The “Moore swab” is a classic environmental surveillance tool whereby a gauze pad tied with string is suspended in flowing water or wastewater contaminated with human feces and harboring enteric pathogens that pose a human health threat. In contrast to single volume “grab” samples, Moore swabs act as continuous filters to “trap” microorganisms, which are subsequently isolated and confirmed using appropriate laboratory methods. Continuous filtration is valuable for the isolation of transiently present pathogens such as human-restricted Salmonella enterica serovars Typhi and Paratyphi A and B.

The “Moore swab” is a classic environmental surveillance tool whereby a gauze pad tied with string is suspended in flowing water or wastewater contaminated with human feces and harboring enteric pathogens that pose a human health threat. In contrast to single volume “grab” samples, Moore swabs act as continuous filters to “trap” microorganisms, which are subsequently isolated and confirmed using appropriate laboratory methods. Continuous filtration is valuable for the isolation of transiently present pathogens such as human-restricted Salmonella enterica serovars Typhi and Paratyphi A and B. The technique was first proposed (1948) to trace Salmonella Paratyphi B systematically through sewers to pinpoint the residence of a chronic carrier responsible for sporadic outbreaks of paratyphoid fever. From 1948 to 1986, Moore swabs proved instrumental to identify long-term human reservoirs (chronic carriers) and long-cycle environmental transmission pathways of S. Typhi and Paratyphi, for example, to decipher endemic transmission in Santiago, Chile, during the 1980s. Despite limitations such as intermittent shedding of typhoidal Salmonella by humans and the effects of dilution, S. Typhi and S. Paratyphi have been recovered from sewers, surface waters, irrigation canals, storm drains, flush toilets, and septic tanks by using Moore swabs. Driven by the emergence of multiple antibiotic-resistant S. Typhi and S. Paratyphi A strains that limit treatment options, several countries are embarking on accelerated typhoid control programs using vaccines and environmental interventions. Moore swabs, which are regaining appreciation as important components of the public health/environmental microbiology toolbox, can enhance environmental surveillance for typhoidal Salmonella, thereby contributing to the control of typhoid fever.

A Syringe-Based Biosensor to Rapidly Detect Low Levels of Escherichia Coli (ECOR13) in Drinking Water Using Engineered Bacteriophages

A sanitized drinking water supply is an unconditional requirement for public health and the overall prosperity of humanity. Potential microbial and chemical contaminants of drinking water have been identified by a joint effort between the World Health Organization (WHO) and the United Nations Children's Fund (UNICEF), who together establish guidelines that define, in part, that the presence of Escherichia coli (E. coli) in drinking water is an indication of inadequate sanitation and a significant health risk. As E. coli is a nearly ubiquitous resident of mammalian gastrointestinal tracts, no detectable counts in 100 mL of drinking water is the standard used worldwide as an indicator of sanitation. The currently accepted EPA method relies on filtration, followed by growth on selective media, and requires 24-48 h from sample to results. In response, we developed a rapid bacteriophage-based detection assay with detection limit capabilities comparable to traditional methods in less than a quarter of the time. We coupled membrane filtration with selective enrichment using genetically engineered bacteriophages to identify less than 20 colony forming units (CFU) E. coli in 100 mL drinking water within 5 h. The combination of membrane filtration with phage infection produced a novel assay that demonstrated a rapid, selective, and sensitive detection of an indicator organism in large volumes of drinking water as recommended by the leading world regulatory authorities.

Complex Interactions Between Weather, and Microbial and Physicochemical Water Quality Impact the Likelihood of Detecting Foodborne Pathogens in Agricultural Water

Agricultural 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.

Landscape, Water Quality, and Weather Factors Associated With an Increased Likelihood of Foodborne Pathogen Contamination of New York Streams Used to Source Water for Produce Production

There is a need for science-based tools to (i) help manage microbial produce safety hazards associated with preharvest surface water use, and (ii) facilitate comanagement of agroecosystems for competing stakeholder aims. To develop these tools an improved understanding of foodborne pathogen ecology in freshwater systems is needed. The purpose of this study was to identify (i) sources of potential food safety hazards, and (ii) combinations of factors associated with an increased likelihood of pathogen contamination of agricultural water Sixty-eight streams were sampled between April and October 2018 (196 samples). At each sampling event separate 10-L grab samples (GS) were collected and tested for Listeria, Salmonella, and the stx and eaeA genes. A 1-L GS was also collected and used for Escherichia coli enumeration and detection of four host-associated fecal source-tracking markers (FST). Regression analysis was used to identify individual factors that were significantly associated with pathogen detection. We found that eaeA-stx codetection [Odds Ratio (OR) = 4.2; 95% Confidence Interval (CI) = 1.3, 13.4] and Salmonella isolation (OR = 1.8; CI = 0.9, 3.5) were strongly associated with detection of ruminant and human FST markers, respectively, while Listeria spp. (excluding Listeria monocytogenes) was negatively associated with log10 E. coli levels (OR = 0.50; CI = 0.26, 0.96). L. monocytogenes isolation was not associated with the detection of any fecal indicators. This observation supports the current understanding that, unlike enteric pathogens, Listeria is not fecally-associated and instead originates from other environmental sources. Separately, conditional inference trees were used to identify scenarios associated with an elevated or reduced risk of pathogen contamination. Interestingly, while the likelihood of isolating L. monocytogenes appears to be driven by complex interactions between environmental factors, the likelihood of Salmonella isolation and eaeA-stx codetection were driven by physicochemical water quality (e.g., dissolved oxygen) and temperature, respectively. Overall, these models identify environmental conditions associated with an enhanced risk of pathogen presence in agricultural water (e.g., rain events were associated with L. monocytogenes isolation from samples collected downstream of dairy farms; P = 0.002). The information presented here will enable growers to comanage their operations to mitigate the produce safety risks associated with preharvest surface water use.

Irrigation Water Quality—A Contemporary Perspective

In the race to enhance agricultural productivity, irrigation will become more dependent on poorly characterized and virtually unmonitored sources of water. Increased use of irrigation water has led to impaired water and soil quality in many areas. Historically, soil salinization and reduced crop productivity have been the primary focus of irrigation water quality. Recently, there is increasing evidence for the occurrence of geogenic contaminants in water. The appearance of trace elements and an increase in the use of wastewater has highlighted the vulnerability and complexities of the composition of irrigation water and its role in ensuring proper crop growth, and long-term food quality. Analytical capabilities of measuring vanishingly small concentrations of biologically-active organic contaminants, including steroid hormones, plasticizers, pharmaceuticals, and personal care products, in a variety of irrigation water sources provide the means to evaluate uptake and occurrence in crops but do not resolve questions related to food safety or human health effects. Natural and synthetic nanoparticles are now known to occur in many water sources, potentially altering plant growth and food standard. The rapidly changing quality of irrigation water urgently needs closer attention to understand and predict long-term effects on soils and food crops in an increasingly fresh-water stressed world.

Effects of Water Quality and Post-Harvest Handling on Microbiological Contamination of Lettuce at Urban and Peri-Urban Locations of Ouagadougou, Burkina Faso

Vegetable production in urban gardens of Ouagadougou contributes to food security, but water for irrigation is often of low quality. This is particularly acute if irrigation water is taken from wastewater polluted channels. This study aimed at (i) verifying to what degree irrigation water quality is correlated with contamination of lettuce with Escherichia coli, total coliforms, and Salmonella spp., and (ii) assessing effects of post-harvest handling on pathogen development during the trade chain. We tested pathogen removal efficiency on lettuce by applying post-harvest washing. Irrigation water of production areas in Ouagadougou (n = 10) showed a mean E. coli load of 2.1 × 10⁵ CFU 100 mL⁻¹. In 60% of the cases, irrigation water did not meet the standards of the World Health Organization (WHO) for safe irrigation water, and in 30% of the cases, irrigation water was contaminated with Salmonella spp. Loads of total coliforms on lettuce leaves ranged from 2.9 × 10³ CFU g⁻¹ to 1.3 × 10⁶ CFU g⁻¹, while E. coli averaged 1.1 × 10² CFU g⁻¹. Results on post-harvest handling revealed that microbial loads increased along the trade chain. Overall, half of all lettuce samples (n = 60) were tested positively for Salmonella spp. The experiment showed that appropriate post-harvest handling could prevent the increase of total coliforms.

Epidemiological Evidence and Health Risks Associated With Agricultural Reuse of Partially Treated and Untreated Wastewater: A Review

The use of partially treated and untreated wastewater for irrigation is beneficial in agriculture but may be associated with human health risks. Reports from different locations globally have linked microbial outbreaks with agricultural reuse of wastewater. This article reviews the epidemiological evidence and health risks associated with this practice, aiming toward evidence-based conclusions. Exposure pathways that were addressed in this review included those relevant to agricultural workers and their families, consumers of crops, and residents close to areas irrigated with wastewater (partially treated or untreated). A meta-analysis gave an overall odds ratio of 1.65 (95% CI: 1.31, 2.06) for diarrheal disease and 5.49 (95% CI: 2.49, 12.10) for helminth infections for exposed agricultural workers and family members. The risks were higher among children and immunocompromised individuals than in immunocompetent adults. Predominantly skin and intestinal infections were prevalent among individuals infected mainly via occupational exposure and ingestion. Food-borne outbreaks as a result of crops (fruits and vegetables) irrigated with partially or untreated wastewater have been widely reported. Contamination of crops with enteric viruses, fecal coliforms, and bacterial pathogens, parasites including soil-transmitted helminthes (STHs), as well as occurrence of antibiotic residues and antibiotic resistance genes (ARGs) have also been evidenced. The antibiotic residues and ARGs may get internalized in crops along with pathogens and may select for antibiotic resistance, exert ecotoxicity, and lead to bioaccumulation in aquatic organisms with high risk quotient (RQ). Appropriate mitigation lies in adhering to existing guidelines such as the World Health Organization wastewater reuse guidelines and to Sanitation Safety Plans (SSPs). Additionally, improvement in hygiene practices will also provide measures against adverse health impacts.

Microbial Water Quality: Monitoring and Modeling

Microbial water quality lies in the nexus of human, animal, and environmental health. Multidisciplinary efforts are under way to understand how microbial water quality can be monitored, predicted, and managed. This special collection of papers in the was inspired by the idea of creating a special section containing the panoramic view of advances and challenges in the arena of microbial water quality research. It addresses various facets of health-related microorganism release, transport, and survival in the environment. The papers analyze the spatiotemporal variability of microbial water quality, selection of predictors of the spatiotemporal variations, the role of bottom sediments and biofilms, correlations between concentrations of indicator and pathogenic organisms and the role for risk assessment techniques, use of molecular markers, subsurface microbial transport as related to microbial water quality, antibiotic resistance, real-time monitoring and nowcasting, watershed scale modeling, and monitoring design. Both authors and editors represent international experience in the field. The findings underscore the challenges of observing and understanding microbial water quality; they also suggest promising research directions for improving the knowledge base needed to protect and improve our water sources.