Characterizing relationships among fecal indicator bacteria, microbial source tracking markers, and associated waterborne pathogen occurrence in stream water and sediments in a mixed land use watershed

HPB-Chip: An accurate high-throughput qPCR-based tool for rapidly profiling waterborne human pathogenic bacteria in the environment

Waterborne pathogens are threatening public health globally, but profiling multiple human pathogenic bacteria (HPBs) in various polluted environments is still a challenge due to the absence of rapid, high-throughput and accurate quantification tools. This work developed a novel chip, termed the HPB-Chip, based on high-throughput quantitative polymerase chain reactions (HT-qPCR). The HPB-Chip with 33-nL reaction volume could simultaneously complete 10,752 amplification reactions, quantifying 27 HPBs in up to 192 samples with two technical replicates (including those for generating standard curves). Specific positive bands of target genes across different species and single peak melting curves demonstrated high specificity of the HPB-Chip. The mixed plasmid serial dilution test validated its high sensitivity with the limit of quantification (LoD) of averaged 82 copies per reaction for 25 target genes. PCR amplification efficiencies and R2 coefficients of standard curves of the HPB-Chip averaged 101 % and 0.996, respectively. Moreover, a strong positive correlation (Pearson' r: 0.961-0.994, P < 0.001) of HPB concentrations (log10 copies/L) between HPB-Chip and conventional qPCR demonstrated high accuracy of the HPB-Chip. Subsequently, the HPB-Chip has been successfully applied to absolutely quantify 27 HPBs in municipal and hospital wastewater treatment plants (WWTPs) after PMA treatment. A total of 17 HPBs were detected in the 6 full-scale WWTPs, with an additional 19 in the hospital WWTP. Remarkably, Acinetobacter baumannii, Legionella pneumophila, and Arcobacter butzler were present in the final effluent of each municipal WWTP. Overall, the HPB-Chip is an efficient and accurate high-throughput quantification tool to comprehensively and rapidly quantify 27 HPBs in the environment.

Mitochondrial DNA marker: A PCR approach for tracking rat (Rattus rattus and Rattus norvegicus) fecal pollution in surface water systems

Rats act as reservoirs for a wide range of zoonotic pathogens and can negatively impact human health. In this study, we developed a novel dye base mitochondrial DNA (mtDNA) PCR-assay (RatMt) specifically targeting a 180 bp fragment of the NADH dehydrogenase subunit 2 gene for detecting fecal pollution from two species of rats (Rattus rattus and Rattus norvegicus) in environmental samples. Estimation of Escherichia coli concentrations in Rattus norvegicus fecal pellets suggested that there were approximately 2.24 × 10 4 ± 4.86 × 103 MPN/g of fecal pellet. The RatMt PCR assay was robust, had a detection limit of rat feces in water of 0.274 ± 0.14 mg/100 mL and was 100 % specific for detecting Rattus rattus and Rattus norvegicus fecal mtDNA. Fecal Indicator Bacteria (FIB) along an urbanized gradient in Pensacola-Bay was assessed by the IDEXX Colilert™ - 18 and indicated that the majority of the fifteen sampling sites in the Pensacola-Bay area had E. coli concentrations >410 MPN/100 mL. Rattus rattus and Rattus norvegicus mtDNA were detected in all the urban marine sites, three of the urban freshwater sampling areas, and three of the forested sampling sites. The RatMt PCR assay is a useful tool for rapidly detecting Rattus rattus and Rattus norvegicus fecal pollution in environmental samples.

Pathogen profile of Baiyangdian Lake sediments using metagenomic analysis and their correlation with environmental factors

Increasing concerns about public health and safety after covid-19 have raised pathogen studies, especially in aquatic environments. However, the extent to how different location and human activities affect geographic occurrence and distribution of pathogens in response to agricultural pollution, boat tourism disturbances and municipal wastewater inflow in a degraded lake remains unclear. Since the surrounding residents depend on the lake for their livelihood, understanding the pathogens reserved in lake sediment and the regulation possibility by environmental factors are challenges with far-reaching significance. Results showed that 187 pathogens were concurrently shared by the nine sediment samples, with Salmonella enterica and Pseudomonas aeruginosa being the most abundant. The similar composition of the pathogens suggests that lake sediment may act as reservoirs of generalist pathogens which may pose infection risk to a wide range of host species. Of the four virulence factors (VFs) types analyzed, offensive VFs were dominant (>46 % on average) in all samples, with dominant subtypes including adherence, secretion systems and toxins. Notably, the lake sediments under the impact of agricultural use (g1) showed significantly higher diversity and abundance of pathogen species and VFs than those under the impact of boat tourism (g2) and/or municipal wastewater inflow with reed marshes filtration (g3). From the co-occurrence networks, pathogens and pesticides, aggregate fractions, EC, pH, phosphatase have strong correlations. Strong positive correlations between pathogens and diazinon in g1 and ppDDT in g2 and g3 suggest higher pesticide-pathogen co-exposure risk. These findings highlight the need to explore pathogen - environmental factor interaction mechanisms in the human-impacted water environments where the control of pathogen invasion by environmental factors may accessible.

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.

Integrating fecal pollution markers and fluorescence analysis for water quality assessment of urban river

Human fecal contamination in urban rivers poses significant health risks, but their potential connections with other substances like dissolved organic matter (DOM) remain underexplored. In this study, five fecal pollution markers related to fecal Bacteroides or human fecal contamination (AllBac, HF183, BacH, Hum2, and Hum163) and DOM along an urban river were analyzed using quantitative polymerase chain reaction (qPCR) and three-dimensional excitation-emission (3D EEM) fluorescence spectrometry. All five markers were detected with average absolute abundance ranging from 2.51 to 6.28 lg gene copies/100 mL, showing a progressive increase along the river (R2 = 0.29-0.92, p < 0.05). Parallel factor analysis identified three dominant DOM components (humic acid-like, fulvic acid-like, and protein-like), with strong positive correlations between protein-like components and all fecal markers (R2 = 0.59-0.66, p < 0.001). Both fecal and DOM distributions consistently showed significant differences between upstream and downstream areas (p < 0.001), suggesting their complementary assessment. While DOM was more sensitive to environmental variables such as rainfall, rubber dam, and tidal dynamic, the combination of fecal pollution markers and 3D EEM analysis allowed a more comprehensive assessment of contamination levels, mitigating potential biases caused by the influence of multiple factors on a single method. Furthermore, due to the strong correlation between protein-like and fecal markers in the DOM, 3D EEM can be used as a pre-detection means for qPCR detection, reducing testing time and costs.

Short-term impacts of a large cultural event on the microbial pollution status of a pre-alpine river

Rivers are impacted by microbial faecal pollution from various sources. We report on a short-term faecal pollution event at the pre-alpine Austrian river Traisen caused by the large cultural event FM4 Frequency music festival, with around 200,000 visitors over 4 days. We observed a massive increase of the faecal indicator bacteria (FIB) intestinal enterococci during the event, while Escherichia coli concentrations were only slightly elevated. This increase poses a significant potential health threat to visitors and people recreating downstream of the festival area. A plausible explanation for the uncoupling of the two FIBs may have been a differential persistence caused by a combination of factors including water temperature, solar radiation, and the excessive presence of personal care products (PCPs) in the river water. However, a potential impact of PCPs on FIB assay performance cannot be ruled out. Our observations are relevant for other intensively used bathing sites; detailed investigations on persistence and assay performance of the FIB in response to different ingredients of PCPs are highly recommended. We conclude that for future festivals at this river or other festivals taking place under similar settings, a more effective management is necessary to reduce deterioration in water quality and minimise health risks.

Benthic sediment as stores and sources of bacteria and viruses in streams: A comparison of baseflow vs. stormflow longitudinal transport and residence times

The presence of bacteria and viruses in freshwater represents a global health risk. The substantial spatial and temporal variability of microbes leads to difficulties in quantifying the risks associated with their presence in freshwater. Fine particles, including bacteria and viruses are transported and accumulated into shallow streambed (i.e., benthic) sediment, delaying the downstream transmission during baseflow conditions but contributing to their resuspension and transport downstream during stormflow events. Direct measurements of pathogen accumulation in benthic sediments are rare. Until now, the dynamic role of benthic sediment as both a store and source of microbes, has not been quantified. In this study, we analyze microbial abundance in benthic sediment along a 1 km reach of an intermittent Mediterranean stream receiving inputs from the effluent of a wastewater treatment plant, a known point source of microbes in streams. We sampled benthic sediment during a summer drought when the wastewater effluent constituted 100 % of the stream flow, and thus, large accumulation and persistence of pathogens along the streambed was expected. We measured the abundance of total bacteria, Escherichia coli (as a fecal indicator), and presence of enteric rotavirus (RoV) and norovirus (NoV). The abundance of E. coli, based on qPCR detection, was high (4.99∙102 gc /cm2) along the first 100 m downstream of the wastewater effluent input and in general decreased with distance from the source, with presence of RoV and NoV along the study reach. A particle tracking model was applied, that uses stream water velocity as an input, and accounts for microbial exchange into, immobilization, degradation, and resuspension out of benthic sediment during baseflow and stormflow. Rates of exchange into benthic sediment were 3 orders of magnitude higher during stormflow, but residence times were proportionately lower, resulting in increased longitudinal connectivity from up to downstream during stormflow. Model simulations demonstrated mechanistically how the rates of exchange into and out of the benthic sediment resulted in benthic sediment to act as a store during baseflow and a source during stormflow.

Environmental risk assessment for fecal contamination sources in urban and peri-urban estuaries, in Escambia and Santa Rosa counties, FL, USA

Fecal pollution of estuaries and adjacent creeks and streams is of significant concern along the Gulf of Mexico. The prospective threat to human life and water quality impairment via fecal pollution is a substantial danger to the strength and resistance of coastline areas. Pensacola, FL, has a prosperous coastal tourism industry that is utilized for numerous other uses, such as recreational watersports and boating, seafood, and shellfish harvesting. However, the frequency and severity of fecal contamination present possible socio-economic issues, specifically financial hardships. Therefore, understanding the source, abundance, and fate of fecal microbial pollutants in aquatic systems signifies an imperative initial stage for detecting the host sources and techniques to lessen their transport from the landscape. This research aimed to quantify the fecal indicator bacteria (FIB), Escherichia coli, and perform microbiological fecal source tracking to verify if the fecal inputs are of either animal or human host origin. Surface water samples were taken from urban and peri-urban creeks for two sampling periods (February 2021 and January 2022), and IDEXX Colilert-18 (USEPA Standard Method 9223) was used for E. coli enumeration. DNA extractions were obtained from each sample, and quantitative PCR was utilized for fecal microbial source tracking (MST) to detect human, dog, ruminant, and bird host-specific Bacteroides DNA. The result indicates elevated quantities of FIB, E. coli, that surpass the threshold considered safe regarding human health. E. coli at six sites over the two sampling periods exceeded the impairment threshold, reaching as high as 866.4 MPN/100 ml. Fecal source tracking identified human host fecal contamination at four of nine sites, dogs at three of nine, and birds at one site. However, those sites with sources identified via MST all had E. coli levels below impairment thresholds. No sites were determined to be positive for ruminant as a source or for the pathogen Helicobacter pylori. No canine host fecal inputs were found in January 2022, and only one site with human sewage. Our results highlight the utility of MST in assessing bacterial inputs to water bodies and the challenges.

Host-Associated Bacteroides 16S rDNA-Based Markers for Source Tracking of Fecal Pollution in Laguna Lake, Philippines

Sources of fecal contamination in Laguna Lake, Philippines, were identified using a library-independent microbial source tracking method targeting host-associated Bacteroides 16S rDNA-based markers. Water samples from nine lake stations were assessed for the presence of the fecal markers HF183 (human), BoBac (cattle), Pig-2-Bac (swine), and DuckBac (duck) from August 2019 to January 2020. HF183 (average concentration = 1.91 log₁₀ copies/mL) was the most frequently detected, while Pig-2-Bac (average concentration = 2.47 log₁₀ copies/mL) was the most abundant. The detected marker concentrations in different stations corresponded to the land use patterns around the lake. Generally, all marker concentrations were higher during the wet season (August-October), suggesting the effect of rainfall-associated factors on the movement and retention of markers from sources. There was a significant association (ρ = 0.45; p < 0.001) between phosphate and the concentration of HF183, suggesting domestic sewage-derived pollution. The markers had acceptable sensitivity and specificity, i.e., HF183 (S = 0.88; R = 0.99), Pig-2-Bac (S = 1.00; R = 1.00), and DuckBac (S = 0.94; R = 1.00), and therefore may be used for the continuous monitoring of fecal pollution in the lake and in designing interventions to improve the quality of the lake water.

Molecular characterization of waterborne protozoa in surface water and sediment in Brazil: a taxonomic survey of ciliated protozoa and their correlation with Giardia duodenalis and Cryptosporidium spp

The detection of Giardia duodenalis and Cryptosporidium spp. was performed, along with the identification of the ciliated protozoa biodiversity, to evaluate the correlation between these protozoa in freshwater quality monitoring. Water and sediment samples from two sites in the Atibaia River (Campinas, São Paulo, Brazil) were collected monthly for 2 years (n = 96). Pathogenic protozoa in water and sediment were detected by using immunomagnetic separation, followed by visualization by immunofluorescence assay (IFA). All positive aliquots in IFA were subjected to DNA extraction and subsequently nested PCR. Qualitative (in vivo observation and silver impregnation) and quantitative (in vivo enumeration) analyses were performed for the ciliated protozoa. Giardia cysts were detected in 62.5% of the surface water samples and Cryptosporidium spp. in 25.0%. In the sediment, cysts were detected in 35.4% samples and oocysts in 16.6%. A total of 57 samples positive for Giardia cysts were subjected to sequencing, 40 of which were harboring G. duodenalis (24 were characterized as sub-assemblage AII). For ciliated protozoa, 73 taxa belonging to 53 genera were identified over the period of the study. These results revealed a high degree of contamination by waterborne protozoa in the main water source which supplies drinking water for more than one million people in Campinas (São Paulo), highlighting the need for continuous monitoring of this catchment site. In addition, the present study provides important data regarding the sources of the water body degradation, i.e., fecal contamination of human origin, in addition to the survey of the ciliated protozoa.

Implications for assessing sludge hygienization: Differential responses of the bacterial community, human pathogenic bacteria, and fecal indicator bacteria to sludge pretreatment-anaerobic digestion

Sewage sludge is the byproduct of wastewater treatment plants, which host enormous diversity of microbes including potential pathogens. However, there are still challenges in assessing hygienization during sludge stabilization due to the complex relationships between dominant microbes and human pathogenic bacteria (HPB), and the accuracy of fecal indicator bacteria (FIB) is also disputed. Here, the responses of the bacterial community, HPB, and FIB to sludge pretreatment-anaerobic digestion (AD) were comprehensively compared using culture-based and 16S rRNA gene molecular analysis methodologies. Bacterial and HPB communities differed in response to sludge pretreatment-AD. AD drove the variation of bacterial community, but led to the convergence of HPB communities in pretreated sludge, indicating the existence of ecological niches that favors HPB dissemination in digesters. The correlation analysis indicated that FIB was suitable for characterizing general pathogen removal instead of showing the real pattern of HPB (i.e., each HPB), implying the need for comprehensive assessment approaches. Moreover, AD-related parameters including pH, total solids destruction, and methane yield were found to play important role in assessing pathogen inactivation given their correlation. This work provides theoretical basis for the selection of appropriate sludge stabilization approaches and future supervision of biosolids biosafety, which finally benefits human health.

Simultaneous detection of various pathogenic Escherichia coli in water by sequencing multiplex PCR amplicons

Waterborne diseases due to pathogen contamination in water are a serious problem all over the world. Accurate and simultaneous detection of pathogens in water is important to protect public health. In this study, we developed a method to simultaneously detect various pathogenic Escherichia coli by sequencing the amplicons of multiplex PCR. Our newly designed multiplex PCR amplified five genes for pathogenic E. coli (uidA, stx1, stx2, STh gene, and LT gene). Additional two PCR assays (for aggR and eae) were also designed and included in the amplicon sequencing analysis. The same assays were also used for digital PCR (dPCR). Strong positive correlations were observed between the sequence read count and the dPCR results for most of the genes targeted, suggesting that our multiplex PCR-amplicon sequencing approach could provide quantitative information. The method was also successfully applied to monitor the level of pathogenic E. coli in river water and wastewater samples. The approach shown here could be expanded by targeting genes for other pathogens.

Fecal pollution source characterization in the surface waters of recharge and contributing zones of a karst aquifer using general and host-associated fecal genetic markers

Fecal pollution of surface waters in the karst-dominated Edwards aquifer is a serious concern as contaminated waters can rapidly transmit to groundwaters, which are used for domestic purposes. Although microbial source tracking (MST) detects sources of fecal pollution, integrating data related to environmental processes (precipitation) and land management practices (septic tanks) with MST can provide better understanding of fecal contamination fluxes to implement effective mitigation strategies. Here, we investigated fecal sources and their spatial origins at recharge and contributing zones of the Edwards aquifer and identified their relationship with nutrients in different environmental/land-use conditions. During March 2019 to March 2020, water samples (n = 295) were collected biweekly from 11 sampling sites across four creeks and analyzed for six physico-chemical parameters and ten fecal indicator bacteria (FIB) and MST-based qPCR assays targeting general (E. coli, Enterococcus, and universal Bacteroidales), human (BacHum and HF183), ruminant (Rum2Bac), cattle (BacCow), canine (BacCan), and avian (Chicken/Duck-Bac and GFD) fecal markers. Among physico-chemical parameters, nitrate-N (NO₃-N) concentrations at several sites were higher than estimated national background concentrations for streams. General fecal markers were detected in the majority of water samples, and among host-associated MST markers, GFD, BacCow, and Rum2Bac were more frequently detected than BacCan, BacHum, and HF183, indicating avian and ruminant fecal contamination is a major concern. Cluster analysis results indicated that sampling sites clustered based on precipitation and septic tank density showed significant correlation (p < 0.05) between nutrients and FIB/MST markers, indicating these factors are influencing the spatial and temporal variations of fecal sources. Overall, results emphasize that integration of environmental/land-use data with MST is crucial for a better understanding of nutrient loading and fecal contamination.

Fecal indicators and antibiotic resistance genes exhibit diurnal trends in the Chattahoochee River: Implications for water quality monitoring

Water bodies that serve as sources of drinking or recreational water are routinely monitored for fecal indicator bacteria (FIB) by state and local agencies. Exceedances of monitoring thresholds set by those agencies signal likely elevated human health risk from exposure, but FIB give little information about the potential source of contamination. To improve our understanding of how within-day variation could impact monitoring data interpretation, we conducted a study at two sites along the Chattahoochee River that varied in their recreational usage and adjacent land-use (natural versus urban), collecting samples every 30 min over one 24-h period. We assayed for three types of microbial indicators: FIB (total coliforms and Escherichia coli); human fecal-associated microbial source tracking (MST) markers (crAssphage and HF183/BacR287); and a suite of clinically relevant antibiotic resistance genes (ARGs; blaCTX-M, blaCMY, MCR, KPC, VIM, NDM) and a gene associated with antibiotic resistance (intl1). Mean levels of FIB and clinically relevant ARGs (blaCMY and KPC) were similar across sites, while MST markers and intI1 occurred at higher mean levels at the natural site. The human-associated MST markers positively correlated with antibiotic resistant-associated genes at both sites, but no consistent associations were detected between culturable FIB and any molecular markers. For all microbial indicators, generalized additive mixed models were used to examine diurnal variability and whether this variability was associated with environmental factors (water temperature, turbidity, pH, and sunlight). We found that FIB peaked during morning and early afternoon hours and were not associated with environmental factors. With the exception of HF183/BacR287 at the urban site, molecular MST markers and intI1 exhibited diurnal variability, and water temperature, pH, and turbidity were significantly associated with this variability. For blaCMY and KPC, diurnal variability was present but was not correlated with environmental factors. These results suggest that differences in land use (natural or urban) both adjacent and upstream may impact overall levels of microbial contamination. Monitoring agencies should consider matching sample collection times with peak levels of target microbial indicators, which would be in the morning or early afternoon for the fecal associated indicators. Measuring multiple microbial indicators can lead to clearer interpretations of human health risk associated with exposure to contaminated water.

Sources and Drivers of ARGs in Urban Streams in Atlanta, Georgia, USA

The spread of antibiotic resistance genes (ARGs) in the aquatic environment is an emerging concern in the interest of protecting public health. Stemming the environmental dissemination of ARGs will require a better understanding of the sources and drivers of ARGs in the water environment. In this study, we used direct measurement of sewage-associated molecular markers, the class 1 integron gene, standard water quality parameters, and watershed characteristics to evaluate the sources and drivers of ARGs in an urban watershed impacted by a gradient of human activities. Quantitative polymerase chain reaction (qPCR) was used to quantify the abundance of the sewage-associated HF183, the E. coli fecal indicator, class 1 integron gene (int1), and the ARGs sulI, sulII, tetW, tetM, ampC, and blaSHV in stream water samples collected from the Proctor Creek watershed in Atlanta, Georgia. Our findings show that ARGs were widely distributed, with detection frequencies of 96% (sulI and sulII), 82% (tetW and tetM), and 49% (ampC and blaSHV). All the ARGs were positively and significantly correlated (r > 0.5) with the HF183 and E. coli markers. Non-linear machine learning models developed using generalized boosting show that more than 70% of the variation in ARG loads in the watershed could be explained by fecal source loading, with other factors such as class 1 integron, which is associated with acquired antibiotic resistance, and environmental factors contributing < 30% to ARG variation. These results suggest that input from fecal sources is a more critical driver of ARG dissemination than environmental stressors or horizontal gene transfer in aquatic environments highly impacted by anthropogenic pollution. Finally, our results provide local watershed managers and stakeholders with information to mitigate the burden of ARGs and fecal bacteria in urban streams.

Environmental and anthropogenic factors associated with the likelihood of detecting Salmonella in agricultural watersheds

Surface water is one of the primary sources of irrigation water for produce production; therefore, its contamination by foodborne pathogens, such as Salmonella, may substantially impact public health. In this study, we determined the presence of Salmonella in surface water and characterized the relationship between Salmonella detection and environmental and anthropogenic factors. From April 2019 to February 2020, 120 samples from 30 sites were collected monthly in four watersheds located in two different central Chile agricultural regions (N = 1080). Water samples from rivers, canals, streams, and ponds linked to each watershed were obtained. Surface water (10 L) was filtrated in situ, and samples were analyzed for the presence of Salmonella. Salmonella was detected every month in all watersheds, with a mean detection percentage of 28% (0%-90%) across sampling sites, regardless of the season. Overall, similar detection percentages were observed for both regions: 29.1% for Metropolitan and 27.0% for Maule. Salmonella was most often detected in summer (39.8% of all summer samples tested positive) and least often in winter (14.4% of winter samples). Random forest analysis showed that season, water source, and month, followed by latitude and river, were the most influential factors associated with Salmonella detection. The influences of water pH and temperature (categorized as environmental factors) and factors associated with human activity (categorized as anthropogenic factors) registered at the sampling site were weakly or not associated with Salmonella detection. In conclusion, Salmonella was detected in surface water potentially used for irrigation, and its presence was linked to season and water source factors. Interventions are necessary to prevent contamination of produce, such as water treatment before irrigation.

Observations and Correlations from a 3-Year Study of Fecal Indicator Bacteria in the Mohawk River in Upstate NY

Fecal indicator bacteria (FIB), such as E. coli and Enterococci, are used to indicate the potential of fecal contamination in waterways. One known source of FIB in urbanized areas is the occurrence of combined sewer overflows (CSOs). To explore the impact of CSOs on local water quality and FIB presence, sampling was conducted during the summers of 2017–2019 of two cities, one with CSOs and one without, on the Mohawk River in upstate New York, USA. Sampling included in situ physiochemical parameters of pH, temperature, and dissolved oxygen and laboratory tests for E. coli, Enterococci, nitrates, and total organic carbon (TOC). Correlations between parameters were explored using the Wilcoxon rank sum test and Spearman’s Rank correlation with and without considerations of site and city location. Overall, positive correlations between FIB and rainfall were identified in one city but were less significant in the other, suggesting a buffering of FIB concentrations likely due to inflow contributions from a reservoir. Samples collected downstream from an active CSO reached the detection limit of the FIB tests, demonstrating a 2-log or greater increase in FIB concentrations from dry weather conditions. The city with CSOs demonstrated greater FIB concentrations, which are likely a combination of greater urban runoff, CSOs, and the potential resuspension of sediment during high flow events. Due to the widespread presence of FIB in the region, future research includes utilizing microbial source tracking to identify the sources of contamination in the region.

Modeling Contaminant Microbes in Rivers During Both Baseflow and Stormflow

Rivers transport contaminant microorganisms (including fecal indicator bacteria and human pathogens) long distances downstream of diffuse and point sources, posing a human health risk. We present a mobile-immobile model that incorporates transport as well as immobilization and remobilization of contaminant microbes and other fine particles during baseflow and stormflow. During baseflow conditions, hyporheic exchange flow causes particles to accumulate in streambed sediments. Remobilization of stored particles from streambed sediments occurs slowly during baseflow via hyporheic exchange flow, while remobilization is vastly increased during stormflow. Model predictions are compared to observations over a range of artificial and natural flood events in the dairy contaminated Topehaehae Stream, New Zealand. The model outputs closely matched timing and magnitude of E. coli and turbidity observations through multiple high-flow events. By accounting for both state-of-flow and hyporheic exchange processes, the model provides a valuable framework for predicting particle and contaminant microbe behavior in streams.

Partitioning and sources of microbial pollution in the Venice Lagoon

Microbial pollutants are a serious threat to human and environmental health in coastal areas. Based on the hypothesis that pollution from multiple sources may produce a distinct microbial signature and that microbial pollutants seem to distribute between a free-living and a particle-attached fraction, we investigated the occurrence, partitioning and sources of microbial pollutants in water samples collected in the Venice Lagoon (Italy). The area was taken as a case study of an environment characterized by a long history of industrial pollution and by growing human pressure. We found a variety of pollutants from several sources, with sewage-associated and faecal bacteria accounting for up to 5.98% of microbial communities. Sewage-associated pollutants were most abundant close to the city centre. Faecal pollution was highest in the area of the industrial port and was dominated by human inputs, whereas contamination from animal faeces was mainly detected at the interface with the mainland. Microbial pollutants were almost exclusively associated with the particle-attached fraction. The samples also contained other potential pathogens. Our findings stress the need for monitoring and managing microbial pollution in highly urbanized lagoon and semi-enclosed systems and suggest that management plans to reduce microbial inputs to the waterways should include measures to reduce particulate matter inputs to the lagoon. Finally, High-Throughput Sequencing combined with computational approaches proved critical to assess water quality and appears to be a valuable tool to support the monitoring of waterborne diseases.

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.

Genetic Sequence Data Evidence that Human Fecal‐associated HF183 sequences Are on Human Skin and in Urine

Aims

The DNA marker HF183 is a partial 16S rRNA gene sequence highly specific to human‐associated Bacteroides including Bacteroides dorei. While HF183 is used to assess human faecal contamination in aquatic environments worldwide, little is known about the existence of HF183 and B. dorei in human microbiomes outside of the human gastrointestinal tract and faeces.

Methods and Results

Previously published human skin and urine microbiome data sets from five independent human body skin studies, the Human Microbiome Project (HMP) and three independent human urine studies were analysed. The HF183 gene sequence was detected in all skin data sets, with the ratios of positive samples ranging from 0.5% to 36.3%. Popliteal fossa (knee), volar forearm and inguinal (groin) creases were identified as hot spots. HF183 was detected in two of three urine data sets, with ratios of positive samples ranging from 0% to 37.5%. All HF183‐containing sequences from these data sets were classified as associated with B. dorei.

Conclusions

HF183 is widespread on human skin and present in urine.

Significance and Impact of Study

Skin and urine microbiomes could be sources of HF183 to environmental waters. Such non‐faecal sources of HF183 might explain low concentrations of HF183 in recreational waters when swimmers are present.

Suspended particles are hotspots for pathogen-related bacteria and ARGs in coastal beach waters of northern China

Marine suspended particles are unique micro-habitats for diverse microbes and also hotspots of microbially metabolic activities. However, the association of bacterial pathogens, especially those carrying antibiotic resistance genes (ARGs), with these particles remain largely unknown in coastal habitats. This study investigated the distribution of pathogen-related bacteria and ARGs in particle-associated (PA) and free-living (FL) fractions of samples collected at three coastal beaches using NextGen sequencing and qPCR. Suspended particles were found to harbor significantly higher abundances of bacteria of pathogen-related genera and ARGs than their counterparts. Functional analysis of microbial community suggested that antibiotic biosynthetic pathways were also more abundant among PA microbiome comparing to FL microbial community, which further facilitated the spread of ARGs. Additionally, 13 pathogen-related genera co-occurred with ARG in PA fraction while only 2 pathogen-related genera co-occurred with ARGs in FL fraction. Overall, our research revealed suspended particles harbored more abundant pathogen-related genera and ARGs comparing with surrounding waters. Thus, suspended particles are hotspots for pathogen-related genera and ARGs and may pose a greater threat to human health in coastal beach.

Difference responses of soil fungal communities to cattle and chicken manure composting application

AIMS

Cattle and poultry manure composting are often applied on agricultural lands but the fungal community composition before and after application in soils is still unclear. Describe soil fungal diversity after manure applications contribute to the correct resource use of livestock and poultry manures.

METHODS AND RESULTS

Fresh manure samples were obtained from 10 beef cow farms and 12 egg-laying poultry farms at five distinct phases of rearing. Surface soil samples were collected from vegetable plots within the farms after manure application at 15, 30 and 45 t hm^-2 . Using high-throughput sequencing techniques, the ITS region was utilized to describe soil fungus populations. The fungal OTUs, Chao1 and ACE of cattle manure were relative higher in fattening stage (>12 months), the OTUs and ACE of chicken manure were the highest in the initial laying stage (16-24 weeks). The fungal diversity indices of vegetable soils hadn't linear change after cow or chicken manure application compared with the control. Ascomycota (84.7% of total sequences), Neocallimastigomycota (9.69%), and Basidiomycota (4.6%) were the dominant phyla in cattle manure. Ascomycota (88.9%) also predominated in chicken manure, followed by Basidiomycota (8.9%). Following both cattle and chicken manure application, the abundance of Ascomycota decreased, while Basidiomycota and Chytridiomycota increased in the soils. None of the dominant genus increased or decreased linearly with the increase of cattle and chicken composting application rate. The fungal dominant genera of the soils with and without manure composting application were mostly affected by soil pH and EC than manure. Pearson's correlation analysis revealed that organic matter, Cu and Hg contents were strongly linked to the fungal diversity and the abundance of specific taxa in cattle manure. In chicken manure, OM, TN and Zn were major factors controlling the fungal diversity and community composition. Soil pH, EC, and Cu, Zn, Cd, Hg and As content had pronounced effects on beneficial and pathogenic genus in soil with and without manure composting. Beneficial fungal genus such as Aspergillus, Plectosphaerella, Acremonium, Meyerozyma and fungal pathogenic like Fusarium, Cladosporium, Verticillium were sensitive to properties (EC, pH, OM) and heavy metals (Cu, Zn, Hg) contents of environment, relatively. The study can serve as an applicable contribution helping in farms management (especially to cattle and poultry breeding) and improve their resource use of livestock and poultry manure.

CONCLUSIONS

Soil heterogeneity rather than manure determines fungal communities in the vegetable fields, but we can encourage the sensible use of cattle and chicken manure in agroecosystems.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study will help the farmers regulate the dosage of feed components which can increase the number of beneficial fungal genus or reduce the number of pathogenic fungal genus, improve their resource use of livestock and poultry manure, and encourage the sensible use of cattle and chicken manure in agroecosystems.

Removal of Fecal Indicator Bacteria by River Networks

Fecal contamination is a significant source of water quality impairment globally. Aquatic ecosystems can provide an important ecosystem service of fecal contamination removal. Understanding the processes that regulate the removal of fecal contamination among river networks across flow conditions is critical. We applied a river network model, the Framework for Aquatic Modeling in the Earth System (FrAMES-Ecoli), to quantify removal of fecal indicator bacteria by river networks across flow conditions during summers in a series of New England watersheds of different characteristics. FrAMES-Ecoli simulates sources, transport, and riverine removal of Escherichia coli (E. coli). Aquatic E. coli removal was simulated in both the water column and the hyporheic zone, and is a function of hydraulic conditions, flow exchange rates with the hyporheic zone, and die-off in each compartment. We found that, at the river network scale during summers, removal by river networks can be high (19–99%) with variability controlled by hydrologic conditions, watershed size, and distribution of sources in the watershed. Hydrology controls much of the variability, with 68–99% of network scale inputs removed under base flow conditions and 19–85% removed during storm events. Removal by the water column alone could not explain the observed pattern in E. coli, suggesting that processes such as hyporheic removal must be considered. These results suggest that river network removal of fecal indicator bacteria should be taken into consideration in managing fecal contamination at critical downstream receiving waters.

Bacterial Indicators Are Ubiquitous Members of Pelagic Microbiome in Anthropogenically Impacted Coastal Ecosystem

Coastal zones are exposed to various anthropogenic impacts, such as different types of wastewater pollution, e.g., treated wastewater discharges, leakage from sewage systems, and agricultural and urban runoff. These various inputs can introduce allochthonous organic matter and microbes, including pathogens, into the coastal marine environment. The presence of fecal bacterial indicators in the coastal environment is usually monitored using traditional culture-based methods that, however, fail to detect their uncultured representatives. We have conducted a year-around in situ survey of the pelagic microbiome of the dynamic coastal ecosystem, subjected to different anthropogenic pressures to depict the seasonal and spatial dynamics of traditional and alternative fecal bacterial indicators. To provide an insight into the environmental conditions under which bacterial indicators thrive, a suite of environmental factors and bacterial community dynamics were analyzed concurrently. Analyses of 16S rRNA amplicon sequences revealed that the coastal microbiome was primarily structured by seasonal changes regardless of the distance from the wastewater pollution sources. On the other hand, fecal bacterial indicators were not affected by seasons and accounted for up to 34% of the sequence proportion for a given sample. Even more so, traditional fecal indicator bacteria (Enterobacteriaceae) and alternative wastewater-associated bacteria (Lachnospiraceae, Ruminococcaceae, Arcobacteraceae, Pseudomonadaceae and Vibrionaceae) were part of the core coastal microbiome, i.e., present at all sampling stations. Microbial source tracking and Lagrangian particle tracking, which we employed to assess the potential pollution source, revealed the importance of riverine water as a vector for transmission of allochthonous microbes into the marine system. Further phylogenetic analysis showed that the Arcobacteraceae in our data set was affiliated with the pathogenic Arcobacter cryaerophilus, suggesting that a potential exposure risk for bacterial pathogens in anthropogenically impacted coastal zones remains. We emphasize that molecular analyses combined with statistical and oceanographic models may provide new insights for environmental health assessment and reveal the potential source and presence of microbial indicators, which are otherwise overlooked by a cultivation approach.

Evaluation of the Effectiveness of the SED-BIO System in Reducing the Inflow of Selected Physical, Chemical and Biological Pollutants to a Lake

The aim of this study was to assess the efficiency of the innovative SED-BIO system in limiting the inflow of pollutants to Jelonek Lake. The analyses were conducted in the Gniezno Lake District in Greater Poland (the western part of Poland). Physical and chemical analyses were conducted in the years 2016–2019. The results demonstrate that the system is highly effective in the reduction of such nutrients as nitrogen (NO3−—63%; NH4+—14.9%) and phosphorus (PO43−—19.3%). Although the presence of cyanobacteria was confirmed practically throughout the whole monitoring period of the system (2016), the specimens found in most samples were not toxigenic genotypes with a potential to produce microcystins. Microcystins (3 µg·L−1) were detected only once, immediately after the SED-BIO system had been installed in the river and pond, which demonstrates that this natural toxin was eliminated from the additional pool of contaminants that might be transported to Jelonek Lake.

Variability of E. coli in streambed sediment and its implication for sediment sampling

E. coli is the number one cause for water quality impairments in rivers and streams in South Dakota and the United States. Stream bottom sediments can be a reservoir for bacteria, including pathogenic organisms and fecal indicator bacteria (FIB), due to the favorable conditions provided by sediments for survival. Despite this, little is known about the variability of E. coli in sediments which should be considered when developing a sampling regime. This study examines the spatial variability of E. coli in sediment across the stream cross-section, the temporal stability of E. coli in sediment samples, and the implications for sediment sampling and processing. Five locations were sampled for sediment E. coli along two tributaries to the Big Sioux River in eastern South Dakota, four along Skunk Creek (Sk1, Sk2, Sk3, and Sk4), and one in Sixmile Creek (SM). In Skunk Creek, site Sk1 has direct cattle access where the other three sites (Sk2, Sk3, and Sk4) are under Seasonal Riparian Area Management (SRAM), a strategy that limits the cattle access to the stream. E. coli concentrations in the sediment ranged from 4 to 997 CFU g^-1 (8.5 × 10² to 2.1 × 10⁵ CFU 100 mL^-1). The highest and lowest E. coli concentrations observed were at sites Sk1 and Sk4, respectively. The E. coli concentration decreased from the upstream cattle crossing site (Sk1) through the downstream SRAM sites. Analyzing the stream cross-section analysis revealed no significant difference in E. coli concentration between the edge and the middle of the stream. Sediment samples can be held up to 24 h after sample collection in refrigerated conditions (37 °F) in the majority of cases (80%) without significant changes in E. coli concentrations. The sample size analysis indicated the spatial variability of E. coli across the stream cross-section is high and a single grab sample may not be able to provide adequate representation of E. coli concentrations in sediment without substantial error. The findings provide insight for designing E. coli monitoring projects and promote the awareness of unconventional sources of microbiological water quality impairment which are often overlooked.

Integrated analyses of fecal indicator bacteria, microbial source tracking markers, and pathogens for Southeast Asian beach water quality assessment

The degradation of coastal water quality from fecal pollution poses a health risk to visitors at recreational beaches. Fecal indicator bacteria (FIB) are a proxy for fecal pollution; however the accuracy of their representation of fecal pollution health risks at recreational beaches impacted by non-point sources is disputed due to non-human derivation. This study aimed to investigate the relationship between FIB and a range of culturable and molecular-based microbial source tracking (MST) markers and pathogenic bacteria, and physicochemical parameters and rainfall. Forty-two marine water samples were collected from seven sampling stations during six events at two tourist beaches in Thailand. Both beaches were contaminated with fecal pollution as evident from the GenBac3 marker at 88%-100% detection and up to 8.71 log₁₀ copies/100 mL. The human-specific MST marker human polyomaviruses JC and BK (HPyVs) at up to 4.33 log₁₀ copies/100 mL with 92%-94% positive detection indicated that human sewage was likely the main contamination source. CrAssphage showed lower frequencies and concentrations; its correlations with the FIB group (i.e., total coliforms, fecal coliforms, and enterococci) and GenBac3 diminished its use as a human-specific MST marker for coastal water. Human-specific culturable AIM06 and SR14 bacteriophages and general fecal indicator coliphages also showed less sensitivity than the human-specific molecular assays. The applicability of the GenBac3 endpoint PCR assay as a lower-cost prescreening step prior to the GenBac3 qPCR assay was supported by its 100% positive predictive value, but its limited negative predictive values required subsequent qPCR confirmation. Human enteric adenovirus and Vibrio cholerae were not found in any of the samples. The HPyVs related to Vibrio parahaemolyticus, Vibrio vulnificus, and 5-d rainfall records, all of which were more prevalent and concentrated during the wet season. More monitoring is therefore recommended during wet periods. Temporal differences but no spatial differences were observed, suggesting the need for a sentinel site at each beach for routine monitoring. The exceedance of FIB water quality standards did not indicate increased prevalence or concentrations of the HPyVs or Vibrio spp. pathogen group, so the utility of FIB as an indicator of health risks at tropical beaches maybe challenged. Accurate assessment of fecal pollution by incorporating MST markers could lead to developing a more effective water quality monitoring plan to better protect human health risks in tropical recreational beaches.

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.

Impacts of Event-Based Recharge on the Vulnerability of Public Supply Wells

Dynamic recharge events related to extreme rainfall or snowmelt are becoming more common due to climate change. The vulnerability of public supply wells to water quality degradation may temporarily increase during these types of events. The Walkerton, ON, Canada, tragedy (2000) highlighted the threat to human health associated with the rapid transport of microbial pathogens to public supply wells during dynamic recharge events. Field research at the Thornton (Woodstock, ON, Canada) and Mannheim West (Kitchener, ON, Canada) well fields, situated in glacial overburden aquifers, identified a potential increase in vulnerability due to event-based recharge phenomena. Ephemeral surface water flow and local ponding containing microbial pathogen indicator species were observed and monitored within the capture zones of public supply wells following heavy rain and/or snowmelt. Elevated recharge rates beneath these temporary surface water features were estimated to range between 40 and 710 mm over two-week periods using analytical and numerical modelling based on the water level, soil moisture, and temperature data. Modelling also suggested that such events could reduce contaminant travel times to a supply well, increasing vulnerability to water quality degradation. These studies suggest that event-based recharge processes occurring close to public supply wells may enhance the vulnerability of the wells to surface-sourced contaminants.

Impacts of rapid urbanization on characteristics, sources and variation of fecal coliform at watershed scale

Microbial pollution is an environmental problem of growing concern for threatening human health. However, the impacts of rapid urbanization on characteristics, sources and variation of fecal coliform (FC) at watershed scale have not been fully explored. In this study, FC characteristics were monitored monthly for 2 years at 21 river sections in an urbanizing watershed, while the sources and continuously annual variation were quantified by integrating two commonly-used models. The results showed that FC varied from 10³ to 10⁶ MPN/L, indicating a great spatiotemporal variation at watershed scale. Peak FC occurred in summer and autumn among upstream and downstream areas, respectively. Besides, 65% impermeable surface was identified as the threshold of urban level, beyond which the key FC source would shift from agriculture to urban. It was also found that the changes of urban landscape patterns had poor correlation with annual variation of FC. In comparison, urbanization speed was identified as the major driver with the threshold of 30% for deteriorating FC pollution. The Low Impact Development could result in a 5.13%-97.59% reduction of FC at watershed scale.

Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to Predict E. coli Levels in Agricultural Water

Since E. coli is considered a fecal indicator in surface water, government water quality standards and industry guidance often rely on E. coli monitoring to identify when there is an increased risk of pathogen contamination of water used for produce production (e.g., for irrigation). However, studies have indicated that E. coli testing can present an economic burden to growers and that time lags between sampling and obtaining results may reduce the utility of these data. Models that predict E. coli levels in agricultural water may provide a mechanism for overcoming these obstacles. Thus, this proof-of-concept study uses previously published datasets to train, test, and compare E. coli predictive models using multiple algorithms and performance measures. Since the collection of different feature data carries specific costs for growers, predictive performance was compared for models built using different feature types [geospatial, water quality, stream traits, and/or weather features]. Model performance was assessed against baseline regression models. Model performance varied considerably with root-mean-squared errors and Kendall's Tau ranging between 0.37 and 1.03, and 0.07 and 0.55, respectively. Overall, models that included turbidity, rain, and temperature outperformed all other models regardless of the algorithm used. Turbidity and weather factors were also found to drive model accuracy even when other feature types were included in the model. These findings confirm previous conclusions that machine learning models may be useful for predicting when, where, and at what level E. coli (and associated hazards) are likely to be present in preharvest agricultural water sources. This study also identifies specific algorithm-predictor combinations that should be the foci of future efforts to develop deployable models (i.e., models that can be used to guide on-farm decision-making and risk mitigation). When deploying E. coli predictive models in the field, it is important to note that past research indicates an inconsistent relationship between E. coli levels and foodborne pathogen presence. Thus, models that predict E. coli levels in agricultural water may be useful for assessing fecal contamination status and ensuring compliance with regulations but should not be used to assess the risk that specific pathogens of concern (e.g., Salmonella, Listeria) are present.

Antimicrobial Resistance in Escherichia coli and Enterococcal Isolates From Irrigation Return Flows in a High-Desert Watershed

Irrigation return flows (IRFs) collect surface runoff and subsurface drainage, causing them to have elevated contaminant and bacterial levels, and making them a potential source of pollutants. The purpose of this study was to determine antimicrobial susceptibility among Escherichia coli and enterococcal isolates that were collected from IRFs in a south-central Idaho watershed. Environmental isolates can be a potentially important source of antimicrobial resistance (AMR) and IRFs may be one way resistance genes are transported out of agroecosystems. Water samples were collected from nine IRFs and one background site (canal water from Snake River) on a biweekly basis during 2018. Escherichia coli and enterococci were enumerated via a most probable number (MPN) technique, then subsamples were plated on selective media to obtain isolates. Isolates of E. coli (187) or enterococci (185) were tested for antimicrobial susceptibility using Sensititre broth microdilution plates. For E. coli, 13% (25/187) of isolates were resistant to tetracycline, with fewer numbers being resistant to 13 other antimicrobials, with none resistant to gentamicin. While 75% (141/187) of the E. coli isolates were pan-susceptible, 12 multidrug resistance (MDR) patterns with 17 isolates exhibiting resistance to up to seven drug classes (10 antimicrobials). For the enterococcal species, only 9% (16/185) of isolates were pan-susceptible and the single highest resistance was to lincomycin (138/185; 75%) followed by nitrofurantoin (56/185; 30%) and quinupristin/dalfopristin (34/185; 18%). In addition, 13 enterococcal isolates belonging to Enterococcus faecalis, Enterococcus faecium, Enterococcus casseliflavus, and Enterococcus thailandicus, were determined to be MDR to up to six different antimicrobial drug classes. None of the enterococcal isolates were resistant to gentamycin, linezolid, tigecycline, and vancomycin.

Human Pathogenic Bacteria Detected in Rainwater: Risk Assessment and Correlation to Microbial Source Tracking Markers and Traditional Indicators

Roof-harvested rainwater (RHRW) was investigated for the presence of the human pathogenic bacteria Mycobacterium tuberculosis (M. tuberculosis), Yersinia spp. and Listeria monocytogenes (L. monocytogenes). While Yersinia spp. were detected in 92% (n = 25) of the RHRW samples, and L. monocytogenes and M. tuberculosis were detected in 100% (n = 25) of the samples, a significantly higher mean concentration (1.4 × 10³ cells/100 mL) was recorded for L. monocytogenes over the sampling period. As the identification of appropriate water quality indicators is crucial to ensure access to safe water sources, correlation of the pathogens to traditional indicator organisms [Escherichia coli (E. coli) and Enterococcus spp.] and microbial source tracking (MST) markers (Bacteroides HF183, adenovirus and Lachnospiraceae) was conducted. A significant positive correlation was then recorded for E. coli versus L. monocytogenes (r = 0.6738; p = 0.000), and Enterococcus spp. versus the Bacteroides HF183 marker (r = 0.4071; p = 0.043), while a significant negative correlation was observed for M. tuberculosis versus the Bacteroides HF183 marker (r = −0.4558; p = 0.022). Quantitative microbial risk assessment indicated that the mean annual risk of infection posed by L. monocytogenes in the RHRW samples exceeded the annual infection risk benchmark limit (1 × 10^–4 infections per person per year) for intentional drinking (∼10^–4). In comparison, the mean annual risk of infection posed by E. coli was exceeded for intentional drinking (∼10^–1), accidental consumption (∼10^–3) and cleaning of the home (∼10^–3). However, while the risk posed by M. tuberculosis for the two relevant exposure scenarios [garden hosing (∼10^–5) and washing laundry by hand (∼10^–5)] was below the benchmark limit, the risk posed by adenovirus for garden hosing (∼10^–3) and washing laundry by hand (∼10^–3) exceeded the benchmark limit. Thus, while the correlation analysis confirms that traditional indicators and MST markers should be used in combination to accurately monitor the pathogen-associated risk linked to the utilisation of RHRW, the integration of QMRA offers a more site-specific approach to monitor and estimate the human health risks associated with the use of RHRW.

Sediment and fecal indicator bacteria loading in a mixed land use watershed: Contributions from suspended sediment and bedload transport

Overland transport of fecal bacteria in water and their resuspension from bed sediments are important transport mechanisms that help explain the transport of enteric pathogens in watersheds. In this study, multiyear monitoring along with regression relationships between sediment and fecal indicator bacteria (FIB) were used to investigate annual loading in the South Fork Broad River watershed, located in northeastern Georgia, USA. Suspended transport was the dominant transport mechanism contributing to in-stream total annual loads for sediment (81.4-98.1%) and FIB (>98%). Annual bedload transport of FIB was small and Escherichia coli (up to 1.8%) contributed more to annual bedload FIB than enterococci (≤0.03%). Bedload contributions of FIB increased with the duration of critical discharge exceedance, indicating a prolonged risk of exposure to enteric pathogens during extended periods of high flows, which is important during major storm events. The risk of exposure to enteric pathogens through pathways such as recreational use and drinking water treatment could be much greater because fecal bacteria are released from sediment during higher flows and dominantly transported in suspension when bedload are not actively moving. Therefore, the combined contribution of fecal bacteria from overland and bedload-associated transport should be considered in risk assessments. Discharge, bedload, and FIB data collected over 2 yr in this study can supplement future hydrologic modeling and microbial risk assessment modeling efforts.

Identification of new eligible indicator organisms for combined sewer overflow via 16S rRNA gene amplicon sequencing in Kanda River, Tokyo

Fecal indicator bacteria (FIB) are commonly used to evaluate the pollution impact of combined sewer overflows (CSOs) in urban rivers. Although water quality assessment with FIB has a long tradition, recent studies demonstrated that FIB have a low correlation with pathogens and therefore are not accurate enough for the assessment of potential human hazards in water. Consequently, new eligible and more specific indicators have to be identified, which was done in this study via sequencing of genetic markers from total community DNA. To identify potential microbiome-based indicators, microbial communities in samples from an urban river in Tokyo under different climatic conditions (dry and rainy) were compared with the influent and effluent of three domestic wastewater treatment plants (WWTPs) by analyzing 16 S rRNA gene amplicon libraries. In the first part of this study, physicochemical parameters and FIB quantification with selective culture techniques facilitated the identification of samples contaminated with CSO, sewage, or both. This allowed the grouping of samples into CSO-contaminated and non-contaminated samples, an essential step prior to the microbiome comparison between samples. Increased turbidity, ammonia concentrations, and E. coli [up to (9.37 ± 0.95) × 10² CFU/mL after 11.5 mm of rainfall] were observed in CSO-contaminated river samples. Comparison of dry weather (including WWTP samples) and rainy weather samples showed a reduction in microbial diversity in CSO-contaminated samples. Furthermore, the results of this study suggest Bacteroides spp. as a novel indicator of sewage pollution in surface waters.

Occurrence and distributions of human-associated markers in an impacted urban watershed

Numerous genetic markers for microbial source tracking (MST) have been evaluated by testing a panel of target and nontarget faecal samples. However, the performance of MST markers may vary between faecal and water samples, thereby resulting in inaccurate water quality assessment. In this study, a 30-day sampling study was conducted in an urban river impacted by human- and sewage-associated pollution to evaluate the performance of different human-associated markers in environmental water. Additionally, marker decay was assessed via a microcosms approach. Overall, Bacteroidales 16sRNA and crAssphage markers exhibited higher prevalence in the study area, and their detection frequencies exceeded 90%. In contrast, Bacteroidales protein markers exhibited poor detection frequencies compared to other markers, with the prevalence of Hum2 and Hum163 reaching only 63% and 84%, respectively. Regarding marker abundance, there was no significant difference in the detection concentrations between Bacteroidales 16sRNA and crAssphage markers (p > 0.05); however, the concentrations of Bacteroidales protein markers were nearly 1 order of magnitude lower than those of other MST markers. The microcosm experiments indicated that the decay rate of crAssphage markers was significantly lower than that of other bacterial target markers, which may improve their detectability when the pollution source is located far from the sampling site. Due to the observed differences in performance and decay patterns among Bacteroidales 16sRNA, crAssphage, and Bacteroidales protein markers, we recommend the simultaneous use of multiple markers from different target microorganisms to obtain a more comprehensive understanding of the pollution sources. This approach would also provide an accurate assessment of pollution levels and health risks.

Feral swine as sources of fecal contamination in recreational waters

Recreational waters are primary attractions at many national and state parks where feral swine populations are established, and thus are possible hotspots for visitor exposure to feral swine contaminants. Microbial source tracking (MST) was used to determine spatial and temporal patterns of fecal contamination in Congaree National Park (CONG) in South Carolina, U.S.A., which has an established population of feral swine and is a popular destination for water-based recreation. Water samples were collected between December 2017 and June 2019 from 18 surface water sites distributed throughout CONG. Host specific MST markers included human (HF183), swine (Pig2Bac), ruminant (Rum2Bac), cow (CowM3), chicken (CL), and a marker for shiga toxin producing Escherichia coli (STEC; stx2). Water samples were also screened for culturable Escherichia coli (E. coli) as part of a citizen science program. Neither the cow nor chicken MST markers were detected during the study. The human marker was predominantly detected at boundary sites or could be attributed to upstream sources. However, several detections within CONG without concurrent detections at upstream external sites suggested occasional internal contamination from humans. The swine marker was the most frequently detected of all MST markers, and was present at sites located both internal and external to the Park. Swine MST marker concentrations ≥ 43 gene copies/mL were associated with culturable E. coli concentrations greater than the U.S. Environmental Protection Agency beach action value for recreational waters. None of the MST markers showed a strong association with detection of the pathogenic marker (stx2). Limited information about the health risk from exposure to fecal contamination from non-human sources hampers interpretation of the human health implications.

Small Produce Farm Environments Can Harbor Diverse Listeria monocytogenes and Listeria spp. Populations

ABSTRACT

A comprehensive understanding of foodborne pathogen diversity in preharvest environments is necessary to effectively track pathogens on farms and identify sources of produce contamination. As such, this study aimed to characterize Listeria diversity in wildlife feces and agricultural water collected from a New York state produce farm over a growing season. Water samples were collected from a pond (n = 80) and a stream (n = 52). Fecal samples (n = 77) were opportunistically collected from areas <5 m from the water sources; all samples were collected from a <0.5-km2 area. Overall, 86 (41%) and 50 (24%) of 209 samples were positive for Listeria monocytogenes and Listeria spp. (excluding L. monocytogenes), respectively. For each positive sample, one L. monocytogenes or Listeria spp. isolate was speciated by sequencing the sigB gene, thereby allowing for additional characterization based on the sigB allelic type. The 86 L. monocytogenes and 50 Listeria spp. isolates represented 8 and 23 different allelic types, respectively. A subset of L. monocytogenes isolates (n = 44) from pond water and pond-adjacent feces (representing an ∼5,000-m2 area) were further characterized by pulsed-field gel electrophoresis (PFGE); these 44 isolates represented 22 PFGE types, which is indicative of considerable diversity at a small spatial scale. Ten PFGE types were isolated more than once, suggesting persistence or reintroduction of PFGE types in this area. Given the small spatial scale, the prevalence of L. monocytogenes and Listeria spp., as well as the considerable diversity among isolates, suggests traceback investigations may be challenging. For example, traceback of finished product or processing facility contamination with specific subtypes to preharvest sources may require collection of large sample sets and characterization of a considerable number of isolates. Our data also support the adage "absence of evidence does not equal evidence of absence" as applies to L. monocytogenes traceback efforts at the preharvest level.

HIGHLIGHTS

A catchment-scale assessment of the sanitary condition of treated wastewater and river water based on fecal indicators and carbapenem-resistant Acinetobacter spp

Urbanization and population growth have created considerable sanitation challenges in cities and communities in many parts of Europe and the world. As such, it is imperative to identify the most environmentally-harmful microbiological and chemical sources of pollution, these being wastewater treatment plants (WWTPs) which release wastewater of low quality. In the present manuscript, an extensive study was performed of the sanitary conditions of river water and treated wastewater from seventeen WWTPs of various sizes along the Pilica River catchment in central Poland, with the aim of identifying "hot spots" in terms of most serious sources of sanitary hazards. The bacteriological risk for the river, including fecal indicator bacteria (FIB) such as coliforms, E.coli, enterococci, C. perfringens, and carbapenem-resistant Acinetobacter spp. (CRA) were assessed using classical microbiological methods, and the physicochemical parameters were also tested. The WWTPs, particularly the small ones (<2000 people equivalent, PE) demonstrated significant variation regarding the physicochemical parameters. Carbapenem-resistant Acinetobacter spp. bacteria growing at 42 °C were found in the effluent wastewaters of all tested municipal WWTPs, and in most of the Pilica River water samples, presenting a potential hazard to public health. A positive correlation was identified between E. coli and CRA abundance in treated wastewater; however, no such relationship was found in river water. It was found that seven small treatment plants discharged wastewater with very different microbiological parameters. Moreover, three small treatment plants serving only 0.56% of the population in the studied area continuously released extremely high microbiological contamination, constituting as much as 54-82% of fecal indicator bacteria loads in the area studied. Our findings show that this type of comprehensive analysis may enable assessment of the use of the entire catchment area, thus identifying the most serious threats to surface water quality and guiding the actions needed to improve the worst operating WWTPs.

Assessing the faecal source sensitivity and specificity of ruminant and human genetic microbial source tracking markers in the central Ethiopian highlands

This study tested genetic microbial source tracking (MST) methods for identifying ruminant‐ (BacR) and human‐associated (HF183/BacR287, BacHum) bacterial faecal contaminants in Ethiopia in a newly created regional faecal sample bank (n = 173). BacR performed well, and its marker abundance was high (100% sensitivity (Sens), 95% specificity (Spec), median log₁₀ 8·1 marker equivalents (ME) g⁻¹ ruminant faeces). Human‐associated markers tested were less abundant in individual human samples (median: log₁₀ 5·4 and 4·2 (ME + 1) g⁻¹) and were not continuously detected (81% Sens, 91% Spec for BacHum; 77% Sens, 91% Spec for HF183/BacR287). Furthermore, the pig‐associated Pig2Bac assay was included and performed excellent (100% Sens, 100% Spec). To evaluate the presence of MST targets in the soil microbiome, representative soil samples were tested during a whole seasonal cycle (n = 60). Only BacR could be detected, but was limited to the dry season and to sites of higher anthropogenic influence (log₁₀ 3·0 to 4·9 (ME + 1) g⁻¹ soil). In conclusion, the large differences in marker abundances between target and non‐target faecal samples (median distances between distributions ≥log₁₀ 3 to ≥log₁₀ 7) and their absence in pristine soil indicate that all tested assays are suitable candidates for diverse MST applications in the Ethiopian area.

An Open-Source Program (Haplo-ST) for Whole-Genome Sequence Typing Shows Extensive Diversity among Listeria monocytogenes Isolates in Outdoor Environments and Poultry Processing Plants

A reliable and standardized classification of Listeria monocytogenes is important for accurate strain identification during outbreak investigations. Current whole-genome sequencing (WGS)-based approaches for strain characterization are either difficult to standardize, rendering them less suitable for data exchange, or are not freely available. Thus, we developed a portable and open-source tool, Haplo-ST, to improve standardization and provide maximum discriminatory potential to WGS data tied to a multilocus sequence typing (MLST) framework. Haplo-ST performs whole-genome MLST (wgMLST) for L. monocytogenes while allowing for data exchangeability worldwide. This tool takes in (i) raw WGS reads as input, (ii) cleans the raw data according to user-specified parameters, (iii) assembles genes across loci by mapping to genes from reference strains, and (iv) assigns allelic profiles to assembled genes and provides a wgMLST subtyping for each isolate. Data exchangeability relies on the tool assigning allelic profiles based on a centralized nomenclature defined by the widely used BIGSdb-Lm database. Tests of Haplo-ST's performance with simulated reads from L. monocytogenes reference strains demonstrated high sensitivity (97.5%), and coverage depths of ≥20× were found to be sufficient for wgMLST profiling. We then used Haplo-ST to characterize and differentiate between two groups of L. monocytogenes isolates derived from the natural environment and poultry processing plants. Phylogenetic reconstruction identified lineages within each group, and no lineage specificity was observed with isolate phenotypes (transient versus persistent) or origins. Genetic differentiation analyses between isolate groups identified 21 significantly differentiated loci, potentially enriched for adaptation and persistence of L. monocytogenes within poultry processing plants.IMPORTANCE We have developed an open-source tool (https://github.com/swarnalilouha/Haplo-ST) that provides allele-based subtyping of L. monocytogenes isolates at the whole-genome level. Along with allelic profiles, this tool also generates allele sequences and identifies paralogs, which is useful for phylogenetic tree reconstruction and deciphering relationships between closely related isolates. More broadly, Haplo-ST is flexible and can be adapted to characterize the genome of any haploid organism simply by installing an organism-specific gene database. Haplo-ST also allows for scalable subtyping of isolates; fewer reference genes can be used for low-resolution typing, whereas higher resolution can be achieved by increasing the number of genes used in the analysis. Our tool enabled clustering of L. monocytogenes isolates into lineages and detection of potential loci for adaptation and persistence in food processing environments. Findings from these analyses highlight the effectiveness of Haplo-ST in subtyping and evaluating relationships among isolates in studies of bacterial population genetics.

Evaluation of the soil and water assessment tool (SWAT) for simulating E. coli concentrations at the watershed-scale

Water quality management at the watershed level requires a framework to identify sources, apportion water quality risks and develop mitigation strategies to reduce health risks. Watershed-scale models have been used as a support tool to understand the sources, fate and transport of fecal bacteria and pathogens in the environment. The Soil and Water Assessment Tool (SWAT) model was applied in this study to understand the sources and drivers of microbial water quality in the Clouds Creek watershed in Georgia, USA. A criterion to evaluate the performance of the SWAT bacterial model was also developed in this study using the Nash-Sutcliffe Efficiency (NSE) performance measure. The SWAT model was successfully calibrated and validated for flow with Nash-Sutcliffe Efficiency (NSE) of 0.81 and 0.55, respectively. Escherichia coli (E. coli) predictions were good with NSE of 0.32 and 0.34 for the calibration and validation timeframes, respectively. Based on the criteria developed in this study, SWAT bacterial model for E. coli and fecal coliform can be judged as "satisfactory" when NSE > 0.20. The contribution of sources followed this order: in-stream cattle manure deposition > cattle manure application > poultry manure application > septic systems > wildlife manure, suggesting that a reduction in livestock access to streams would be the most effective approach to reduce fecal bacterial loads in this watershed and others impacted by fecal contamination. Finally, our results suggest that the SWAT model is capable of simulating E. coli dynamics in the Clouds Creek watershed and can provide insights into source impacts for risk management.

The challenges of microbial source tracking at urban beaches for Quantitative Microbial Risk Assessment (QMRA)

Urban beaches are frequently impacted from multiple sources of fecal contamination. This along with high beach usage underscores the importance of appropriate management that protects swimmer health. The USEPA has enabled the use of QMRA as a tool for quantifying swimmer health risk and setting site-specific water quality objectives. This study illustrates the challenges associated with human and non-human source identification and how these challenges influence the decision of whether QMRA at typical urban beaches for water quality management is appropriate. In this study, a similar and correlated spatial relationship with elevated Enterococcus and avian-specific markers was observed, suggesting shorebirds as a primary source of FIB. However, human-associated markers were also detected frequently but at low concentrations. Ultimately, a QMRA was not conducted because pathogen loading from potential human sources could not be confidently quantified, having consequences for health risk in receiving waters where recreational contact occurs.

Predictive Models May Complement or Provide an Alternative to Existing Strategies for Assessing the Enteric Pathogen Contamination Status of Northeastern Streams Used to Provide Water for Produce Production

While the Food Safety Modernization Act established standards for the use of surface water for produce production, water quality is known to vary over space and time. Targeted approaches for identifying hazards in water that account for this variation may improve growers’ ability to address pre-harvest food safety risks. Models that utilize publicly-available data (e.g., land-use, real-time weather) may be useful for developing these approaches. The objective of this study was to use pre-existing datasets collected in 2017 (N = 181 samples) and 2018 (N = 191 samples) to train and test models that predict the likelihood of detecting Salmonella and pathogenic E. coli markers (eaeA, stx) in agricultural water. Four types of features were used to train the models: microbial, physicochemical, spatial and weather. “Full models” were built using all four features types, while “nested models” were built using between one and three types. Twenty learners were used to develop separate full models for each pathogen. Separately, to assess information gain associated with using different feature types, six learners were randomly selected and used to develop nine, nested models each. Performance measures for each model were then calculated and compared against baseline models where E. coli concentration was the sole covariate. In the methods, we outline the advantages and disadvantages of each learner. Overall, full models built using ensemble (e.g., Node Harvest) and “black-box” (e.g., SVMs) learners out-performed full models built using more interpretable learners (e.g., tree- and rule-based learners) for both outcomes. However, nested eaeA-stx models built using interpretable learners and microbial data performed almost as well as these full models. While none of the nested Salmonella models performed as well as the full models, nested models built using spatial data consistently out-performed models that excluded spatial data. These findings demonstrate that machine learning approaches can be used to predict when and where pathogens are likely to be present in agricultural water. This study serves as a proof-of-concept that can be built upon once larger datasets become available and provides guidance on the learner-data combinations that should be the foci of future efforts (e.g., tree-based microbial models for pathogenic E. coli).

Prevalence and abundance of traditional and host-associated fecal indicators in urban estuarine sediments: Potential implications for estuarine water quality monitoring

This study aimed to determine the prevalence and abundance of sewage and animal fecal contamination of sediment at seven estuarine locations in Sydney, NSW, Australia. Sediment samples were tested for the occurrence of microbial targets including molecular marker genes of enterococci (ENT), Bacteroides HF183 (HF183), Methanobrevibacter smithii (nifH), human adenovirus (HAdV) and emerging sewage-associated marker genes crAssphage (CPQ_056) and Lachnospiraceae (Lachno3) and animal feces-associated marker genes, including avian feces-associated Helicobacter spp. (GFD), canine-feces associated Bacteroides (DogBact), cattle-feces associated (cowM2) and horse feces-associated Bacteroides (HoF597). Results from this study showed that urban estuarine sediment can act as a reservoir of fecal indicator bacteria (FIB) and several microbial source tracking (MST) marker genes, including previously unreported Lachno3. The sewage-associated marker gene CPQ_056 was most prevalent, in 63.8% of sediment samples, while the avian associated marker gene GFD had the highest mean abundance. The GFD marker gene was highly abundant and widely detected in sediment samples from all seven locations compared to the other animal feces-associated marker genes. In all, 31 (44.9%) sediment samples were positive for at least two sewage-associated marker genes. However, the non-quantifiable detection of the HAdV marker gene did not always align with the detection of two or more sewage-associated marker genes. In addition, the most frequent wet weather overflow exposure occurred at locations that did not have a consistent pattern of detection of the sewage-associated marker genes, suggesting sediments may not be a suitable measure of recent sewage contamination. To assist water quality and public health managers better understand past microbial contamination of estuarine sediment, further studies seem justified to explore the role of decay of MST marker genes in sediment. Further work is also needed on the role of resuspension of MST marker genes from sediment during storm events to the water column as a source of contamination for both the GFD and sewage-associated marker genes.

Bacteroides spp. and traditional fecal indicator bacteria in water quality assessment - An integrated approach for hydric resources management in urban centers

As part of a sustainable water resources management, the Lisbon municipality identified groundwater and treated wastewater use increase as two opportunities for better and sustainable water use, with natural safeguard for public health as a priority. In this context, the aim of our research was to assess the suitability of the human-associated marker gene Bacteroides HF183 and the cattle feces-associated CowM2, in routine water quality monitoring as indicators for water use and reuse, providing a tool to more accurately assess public health risks. To this intent, Real-Time quantitative PCR was used for detection of human-associated marker gene Bacteroides HF183 and the bovine-associated CowM2, in a total of 67 samples - groundwater and wastewater at three different treatment stages of a Waste Water Treatment Plant, in Lisbon. HF183 marker gene was detected in treated and untreated wastewater samples, with significant concentration reductions from untreated (6,07 E+07 copies/mL) to secondary treated effluent (1,86 E+05 copies/mL) and a further decrease in tertiary treatment (5,74 E+04 copies/mL). In groundwater samples, this marker was also detected in concentrations ranging from 2,63 E+02 copies/mL to 2,24 E+03 copies/mL. CowM2 marker gene on the other hand was only detected in wastewater samples, with concentrations ranging from 2,47 E+02 copies/mL to 1,17 E+04 copies/mL. Our research indicates that the use of Bacteroides spp. in association with traditional fecal indicator bacteria (FIB) is advantageous for water managing entities in urban settings, such as Lisbon, were drainage system failures may occur. An integrated approach thus provides crucial and more adequate information towards mitigation and correction measures when fecal contamination is detected in environmental waters.

Association between private drinking water wells and the incidence of Campylobacteriosis in Maryland: An ecological analysis using Foodborne Diseases Active Surveillance Network (FoodNet) data (2007-2016)

Campylobacter is a leading cause of bacterial foodborne illness in the United States. Campylobacter infections have most often been associated with food-related risk factors, such as the consumption of poultry and raw milk. Socioeconomic, agricultural and environmental factors, including drinking water source, can also influence the risk of campylobacteriosis. Approximately 19% of Maryland residents rely on private wells as their sole source of water. Given that the federal Safe Drinking Water Act does not regulate the water quality of private wells, these could be important non-foodborne transmission pathways for Campylobacter. To address this issue, data on the number of culture-confirmed cases of Campylobacter infection in Maryland between 2007 and 2016 were obtained from the Foodborne Diseases Active Surveillance Network. Cases were linked by zip code with data from the Maryland well permits registry, the 2010 U.S. Census, the 2016 American Community Survey, and the USDA Agricultural Census. Campylobacteriosis incidence rates and well prevalence were calculated by zip code. Negative binomial regression models were then constructed to evaluate the association between the prevalence of private wells, presence/absence of animal feeding operations and the incidence of campylobacteriosis across the physiographic provinces in Maryland. From 2007 to 2016, a total of 5746 cases of campylobacteriosis were reported in Maryland, and annual incidence rates ranged from 6.65 to 11.59 per 100,000 people. In our statewide analysis, a significant positive association was observed between well prevalence and increased campylobacteriosis incidence at the zip code level (Incidence Rate Ratio (IRR) = 1.35, 95% Confidence Interval (CI) = 1.11, 1.63). A significant positive association was also observed between well prevalence and increased campylobacteriosis incidence in the Appalachian and Coastal provinces of Maryland (IRR = 2.94, 95% CI = 1.11, 7.76 and IRR = 1.70, 95% CI = 1.25, 2.31, respectively). The presence of broiler chicken operations, increasing median age and percentage of residents living in poverty were also significantly associated with campylobacteriosis incidence at the zip code level in some physiographic provinces in Maryland. To our knowledge, these are the first US data to demonstrate an association between prevalence of private wells and campylobacteriosis incidence at the zip code level.

Recovery of thermophilic Campylobacter by three sampling methods from river sites in Northeast Georgia, USA, and their antimicrobial resistance genes

Sixteen sites in the watershed of the South Fork of the Broad River (SFBR) in Northeastern Georgia, USA, were sampled in two seasons to detect Campylobacter. Sites were classified as mostly influenced by forest, pasture, wastewater pollution control plants (WPC) or mixed use. Sampling was repeated in the late spring and late fall for 2 years for a total of 126 samples. Free-catch water and sediment grab samples were taken at each site; Moore's swabs were placed for up to 3 days at most sites. A total of 56 isolates of thermophilic Campylobacter were recovered. Thirteen samplings were positive by two or three methods, and 26 samplings were positive by only one method; once by Moore's swab only and 25 times by free-catch water only. Campylobacter was detected at 58% of cattle pasture sites, 30% of forested sites and 81% of WPC sites. Twenty-one of the isolates carried antimicrobial resistance genes, mostly blaOXA-61. Free-catch water samples were more efficient than Moore's swabs or sediment samples for recovery of Campylobacter, which was more likely to be detected in streams near cattle pastures and human communities than in forested land. SIGNIFICANCE AND IMPACT OF THE STUDY: The role of environmental water in transmitting Campylobacter was investigated, and methods for recovery of the organism were compared. The sequence types of recovered Campylobacter correlated with adjacent land use without regard to the method used to isolate the organisms. Sequence types and antimicrobial resistance genes associated with cattle were most prevalent near pastures. Even though types were recurrent at a given site, types appeared to be lost or replaced as the water flowed downstream.

Microbial Water Quality Conditions Associated with Livestock Grazing, Recreation, and Rural Residences in Mixed-Use Landscapes

Contamination of surface waters with microbial pollutants from fecal sources is a significant human health issue. Identification of relative fecal inputs from the mosaic of potential sources common in rural watersheds is essential to effectively develop and deploy mitigation strategies. We conducted a cross-sectional longitudinal survey of fecal indicator bacteria (FIB) concentrations associated with extensive livestock grazing, recreation, and rural residences in three rural, mountainous watersheds in California, USA during critical summer flow conditions. Overall, we found that 86% to 87% of 77 stream sample sites across the study area were below contemporary Escherichia coli-based microbial water quality standards. FIB concentrations were lowest at recreation sites, followed closely by extensive livestock grazing sites. Elevated concentrations and exceedance of water quality standards were highest at sites associated with rural residences, and at intermittently flowing stream sites. Compared to national and state recommended E. coli-based water quality standards, antiquated rural regional policies based on fecal coliform concentrations overestimated potential fecal contamination by as much as four orders of magnitude in this landscape, hindering the identification of the most likely fecal sources and thus the efficient targeting of mitigation practices to address them.