Geographic isolation of Escherichia coli genotypes in sediments and water of the Seven Mile Creek - A constructed riverine watershed

One Health Perspectives on Food Safety in Minimally Processed Vegetables and Fruits: From Farm to Fork

While food markets and food production chains are experiencing exponential growth, global attention to food safety is steadily increasing. This is particularly crucial for ready-to-eat products such as fresh-cut salads and fruits, as these items are consumed raw without prior heat treatment, making the presence of pathogenic microorganisms quite frequent. Moreover, many studies on foodborne illnesses associated with these foods often overlook the transmission links from the initial contamination source. The prevention and control of the dissemination of foodborne pathogens should be approached holistically, involving agricultural production, processing, transport, food production, and extending to final consumption, all while adopting a One Health perspective. In this context, our objective is to compile available information on the challenges related to microbiological contamination in minimally handled fruits and vegetables. This includes major reported outbreaks, specific bacterial strains, and associated statistics throughout the production chain. We address the sources of contamination at each stage, along with issues related to food manipulation and disinfection. Additionally, we provide potential solutions to promote a healthier approach to fresh-cut fruits and vegetables. This information will be valuable for both researchers and food producers, particularly those focused on ensuring food safety and quality.

Prevalence and Diversity of Antibiotic Resistant Escherichia coli From Anthropogenic-Impacted Larut River

Aquatic environments, under frequent anthropogenic pressure, could serve as reservoirs that provide an ideal condition for the acquisition and dissemination of antibiotic resistance genetic determinants. We investigated the prevalence and diversity of antibiotic-resistant Escherichia coli by focusing on their genetic diversity, virulence, and resistance genes in anthropogenic-impacted Larut River. The abundance of E. coli ranged from (estimated count) Est 1 to 4.7 × 105 (colony-forming units per 100 ml) CFU 100 ml−1 to Est 1 to 4.1 × 105 CFU 100 ml−1 with phylogenetic group B1 (46.72%), and A (34.39%) being the most predominant. The prevalence of multiple antibiotic resistance phenotypes of E. coli, with the presence of tet and sul resistance genes, was higher in wastewater effluents than in the river waters. These findings suggested that E. coli could be an important carrier of the resistance genes in freshwater river environments. The phylogenetic composition of E. coli and resistance genes was associated with physicochemical properties and antibiotic residues. These findings indicated that the anthropogenic inputs exerted an effect on the E. coli phylogroup composition, diversification of multiple antibiotic resistance phenotypes, and the distribution of resistance genes in the Larut River.

Evaluation of E. coli in sediment for assessing irrigation water quality using machine learning

Fresh produce irrigated with contaminated water poses a substantial risk to human health. This study evaluated the impact of incorporating sediment information on improving the performance of machine learning models to quantify E. coli level in irrigation water. Field samples were collected from irrigation canals in the Southwest U.S., for which meteorological, chemical, and physical water quality variables as well as three additional flow and sediment properties: the concentration of E. coli in sediment, sediment median size, and bed shear stress. Water quality was classified based on E. coli concentration exceeding two standard levels: 1 E. coli and 126 E. coli colony forming units (CFU) per 100 ml of irrigation water. Two series of features, including (FIS) and excluding (FES) sediment features, were selected using multi-variant filter feature selection. The correlation analysis revealed the inclusion of sediment features improves the correlation with the target standards for E. coli compared to the models excluding these features. Support vector machine, logistic regression, and ridge classifier were tested in this study. The support vector machine model performed the best for both targeted standards. Besides, incorporating sediment features improved all models' performance. Therefore, the concentration of E. coli in sediment and bed shear stress are major factors influencing E. coli concentration in irrigation water.

Fecal indicator bacteria from environmental sources; strategies for identification to improve water quality monitoring

In tropical to temperate environments, fecal indicator bacteria (FIB), such as enterococci and Escherichia coli, can persist and potentially multiply, far removed from their natural reservoir of the animal gut. FIB isolated from environmental reservoirs such as stream sediments, beach sand and vegetation have been termed "naturalized" FIB. In addition, recent research suggests that the intestines of poikilothermic animals such as fish may be colonized by enterococci and E. coli, and therefore, these animals may contribute to FIB concentrations in the aquatic environment. Naturalized FIB that are derived from fecal inputs into the environment, and subsequently adapted to maintain their population within the non-host environment are termed "naturalized enteric FIB". In contrast, an additional theory suggests that some "naturalized" FIB diverged from enteric FIB many millions of years ago and are now normal inhabitants of the environment where they are referred to as "naturalized non-enteric FIB". In the case of the Escherichia genus, the naturalized non-enteric members are identified as E. coli during routine water quality monitoring. An over-estimation of the health risk could result when these naturalized, non-enteric FIB, (that is, not derived from avian or mammalian fecal contamination), contribute to water quality monitoring results. It has been postulated that these environmental FIB belonging to the genera Escherichia and Enterococcus can be differentiated from enteric FIB by genetic methods because they lack some of the genes required for colonization of the host intestine, and have acquired genes that aid survival in the environment. Advances in molecular tools such as next generation sequencing will aid the identification of genes peculiar or "enriched" in particular habitats to discriminate between enteric and environmental FIB. In this appraisal, we have reviewed the research studying "naturalized" FIB, and discussed the techniques for their differentiation from enteric FIB. This differentiation includes the important distinction between enteric FIB derived from fresh and non-recent fecal inputs, and those truly non-enteric environmental microbes, which are currently identified as FIB during routine water quality monitoring. The inclusion of tools for the identification of naturalized FIB (enteric or environmental) would be a valuable resource for future studies assessing water quality.

Accounting for the Three-Dimensional Distribution of Escherichia coli Concentrations in Pond Water in Simulations of the Microbial Quality of Water Withdrawn for Irrigation

Evaluating the microbial quality of irrigation water is essential for the prevention of foodborne illnesses. Generic Escherichia coli (E. coli) is used as an indicator organism to estimate the microbial quality of irrigation water. Monitoring E. coli concentrations in irrigation water sources is commonly performed using water samples taken from a single depth. Vertical gradients of E. coli concentrations are typically not measured or are ignored; however, E. coli concentrations in water bodies can be expected to have horizontal and vertical gradients. The objective of this work was to research 3D distributions of E. coli concentrations in an irrigation pond in Maryland and to estimate the dynamics of E. coli concentrations at the water intake during the irrigation event using hydrodynamic modeling in silico. The study pond is about 22 m wide and 200 m long, with an average depth of 1.5 m. Three transects sampled at 50-cm depth intervals, along with intensive nearshore sampling, were used to develop the initial concentration distribution for the application of the environmental fluid dynamic code (EFDC) model. An eight-hour irrigation event was simulated using on-site data on the wind speed and direction. Substantial vertical and horizontal variations in E. coli concentrations translated into temporally varying concentrations at the intake. Additional simulations showed that the E. coli concentrations at the intake reflect the 3D distribution of E. coli in the limited pond section close to the intake. The 3D sampling revealed E. coli concentration hot spots at different depths across the pond. Measured and simulated 3D E. coli concentrations provide improved insights into the expected microbial water quality of irrigation water compared with 1D or 2D representations of the spatial variability of the indicator concentration.

Temporal stability of E. coli and Enterococci concentrations in a Pennsylvania creek

Microbial quality of irrigation waters is a substantial food safety factor. Escherichia coli (E. coli) and Enterococci are used as the fecal indicator bacteria (FIB) to assess microbial water quality. Analysis of temporally stable patterns of FIB can facilitate effective monitoring of microbial water quality. The objectives of this study were (1) to investigate the spatiotemporal variation of E. coli and Enterococci concentrations in a large creek traversing diverse land use areas and (2) to explore the presence of temporally stable FIB concentration patterns along the creek. Concentrations of both FIB were measured weekly at five water monitoring locations along the 20-km long creek reach in Pennsylvania at baseflow for three years. The temporal stability was assessed using mean relative deviations of logarithms of FIB concentration from the average across the reach measured at the same time. The Spearman rank correlation coefficients between logarithms of FIB concentrations on consecutive sampling times was another metric used to assess the temporal stability of FIB concentration patterns. Logarithms of FIB concentrations had sinusoidal dependence on time and significantly correlated with temperature at all locations Both FIB exhibited temporal stability of concentrations. The two most downstream locations in urbanized areas tended to have logarithms of concentrations higher than the average along the observation reach. The location in the upstream forested area had mostly lower concentrations (log E. coli 1.59, log Enterococci 1.69) than average (log E. coli 2.07, log Enterococci 2.20). concentrations in colony-forming units (CFU) (100 mL)^-1. Two locations in the agricultural and sparsely urbanized area had these logarithm values close to the average. The temporal stability was more pronounced in cold seasons than in warm seasons. No significant difference was found between pattern determined for each of three observation years and for the entire three-year observation period. The Spearman rank correlations between observations on consecutive dates showed moderate to very strong relationships in most cases. Existence of the temporal stability of FIB concentrations in the creek indicates locations that inform about the average logarithm of concentrations or the geometric mean concentrations along the entire observation reach.

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation.

Monitoring bacterial indicators of water quality in a tidally influenced delta: A Sisyphean pursuit

The Sacramento-San Joaquin Delta Estuary (Delta) is the confluence of two major watersheds draining the Western Sierra Nevada mountains into the Central Valley of California, ultimately terminating into San Francisco Bay. We sampled 88 sites once a month for two years (2006-2008) over 87 separate sampling events for a total of 1740 samples. Water samples were analyzed for fecal indicator bacteria (Escherichia coli, enterococci and fecal coliforms), and 53 other physiochemical, land use, and environmental characteristics. The purpose of the study was to create a baseline of microbial water quality in the Delta and to identify various factors (climatic, land use, tidal, etc.) that were associated with elevated concentrations of indicator bacteria. Fecal indicator bacteria generally had weak to modest relationships to environmental conditions; the strength and direction of which varied for each microbial indicator, drainage region, and across seasons. Measured and unmeasured, site-specific effects accounted for large portions of variance in model predictions (ρ=0.086 to 0.255), indicating that spatial autocorrelation was a major component of water quality outcomes. The effects of tidal cycling and lack of connectivity between waterways and surrounding landscapes likely contributed to the lack of association between local land uses and microbial outcomes, though weak associations may also be indicative of mismatched spatiotemporal scales. The complex nature of this system necessitates continued monitoring and regular updates to statistical models designed to predict microbial water quality.

Evidence of Naturalized Stress-Tolerant Strains of Escherichia coli in Municipal Wastewater Treatment Plants

Escherichia coli has been proposed to have two habitats—the intestines of mammals/birds and the nonhost environment. Our goal was to assess whether certain strains of E. coli have evolved toward adaptation and survival in wastewater. Raw sewage samples from different treatment plants were subjected to chlorine stress, and ∼59% of the surviving E. coli strains were found to contain a genetic insertion element (IS30) located within the uspC-flhDC intergenic region. The positional location of the IS30 element was not observed across a library of 845 E. coli isolates collected from various animal hosts or within GenBank or whole-genome reference databases for human and animal E. coli isolates (n = 1,177). Phylogenetics clustered the IS30 element-containing wastewater E. coli isolates into a distinct clade, and biomarker analysis revealed that these wastewater isolates contained a single nucleotide polymorphism (SNP) biomarker pattern that was specific for wastewater. These isolates belonged to phylogroup A, possessed generalized stress response (RpoS) activity, and carried the locus of heat resistance, features likely relevant to nonhost environmental survival. Isolates were screened for 28 virulence genes but carried only the fimH marker. Our data suggest that wastewater contains a naturalized resident population of E. coli. We developed an endpoint PCR targeting the IS30 element within the uspC-flhDC intergenic region, and all raw sewage samples (n = 21) were positive for this marker. Conversely, the prevalence of this marker in E. coli-positive surface and groundwater samples was low (≤5%). This simple PCR assay may represent a convenient microbial source-tracking tool for identification of water samples affected by municipal wastewater.

IMPORTANCE The results of this study demonstrate that some strains of E. coli appear to have evolved to become naturalized populations in the wastewater environment and possess a number of stress-related genetic elements likely important for survival in this nonhost environment. The presence of non-host-adapted strains in wastewater challenges our understanding of using E. coli as a microbial indicator of wastewater treatment performance, suggesting that the E. coli strains present in human and animal feces may be very different from those found in treated wastewater.

Sediments and Soils Act as Reservoirs for Taxonomic and Functional Bacterial Diversity in the Upper Mississippi River

In this study, we utilized Illumina next-generation sequencing of 16S rDNA to characterize the bacterial communities in water, sediments, and soils at four sites along the Mississippi River and Minnesota River, in Minnesota, in order to evaluate community exchanges between these habitats. Communities in water and sediment were hypothesized to show greater taxonomic similarity than those in soil, while microbial communities in sediment and soil would show greater functional similarity. Habitat-specific communities showed significant differences in phylogenetic structure and β-diversity (P < 0.001), but site-specific differences in community structures within a single habitat type did not differ greatly (P ≥ 0.083). Community exchange among habitats generally influenced < 5% of the total community composition in a single sample, with the exception of the sediment community at the Minnesota River site, which contributed to a mean of 14% of the microbial community in the water column. Communities from all habitat types were significantly correlated with each other (r = 0.44-0.64, P ≤ 0.004). Furthermore, approximately 33% of the taxonomic units were found in all samples and comprised at least 40% of the bacterial community. Functional annotation of shotgun sequencing data revealed similar functional profiles for sediment and soil communities that were distinct from those in the water. Results of this study suggest that sediments, when disturbed, contribute significantly to bacterial communities in the water and that a core bacterial community may be supported in the soils and sediments. Furthermore, a high degree of functional redundancy results in similar functional profiles in sediment and soil communities.