A multi-tiered approach to assess fecal pollution in an urban watershed: Bacterial and viral indicators and sediment microbial communities.

Development of effective pollution mitigation strategies require an understanding of the pollution sources and factors influencing fecal pollution loading. Fecal contamination of Turkey Creek in Gulfport, Mississippi, one of the nation's most endangered creeks, was studied through a multi-tiered approach. Over a period of approximately two years, four stations across the watershed were analyzed for nutrients, enumeration of E. coli, male-specific coliphages and bioinformatic analysis of sediment microbial communities. The results demonstrated that two stations, one adjacent to a lift station and one just upstream from the wastewater-treatment plant, were the most impacted. The station adjacent to land containing a few livestock was the least impaired. While genotyping of male-specific coliphage viruses generally revealed a mixed viral signature (human and other animals), fecal contamination at the station near the wastewater treatment plant exhibited predominant impact by municipal sewage. Fecal indicator loadings were positively associated with antecedent rainfall for three of four stations. No associations were noted between fecal indicator loadings and any of the nutrients. Taxonomic signatures of creek sediment were unique to each sample station, but the sediment microbial community did overlap somewhat following major rain events. No presence of Escherichia coli (E. coli) or enterococci were found in the sediment. At some of the stations it was evident that rainfall was not always the primary driver of fecal transport. Repeated monitoring and analysis of a variety of parameters presented in this study determined that point and non-point sources of fecal pollution varied spatially in association with treated and/or untreated sewage.

Reduction in antimicrobial resistance in a watershed after closure of livestock farms.

Natural environments play a crucial role in transmission of antimicrobial resistance (AMR). Development of methods to manage antibiotic resistance genes (ARGs) in natural environments are usually limited to the laboratory or field scale, partially due to the complex dynamics of transmission between different environmental compartments. Here, we conducted a nine-year longitudinal profiling of ARGs at a watershed scale, and provide evidence that restrictions on livestock farms near water bodies significantly reduced riverine ARG abundance. Substantial reductions were revealed in the relative abundance of genes conferring resistance to aminoglycosides (42%), MLSB (36%), multidrug (55%), tetracyclines (53%), and other gene categories (59%). Additionally, improvements in water quality were observed, with distinct changes in concentrations of dissolved reactive phosphorus, ammonium, nitrite, pH, and dissolved oxygen. Antibiotic residues and other pharmaceuticals and personal care products (PPCPs) maintain at a similarly low level. Microbial source tracking demonstrates a significant decrease in swine fecal indicators, while human fecal pollution remains unchanged. These results suggest that the reduction in ARGs was due to a substantial reduction in input of antibiotic resistant bacteria and genes from animal excreta. Our findings highlight the watershed as a living laboratory for understanding the dynamics of AMR, and for evaluating the efficacy of environmental regulations, with implications for reducing environmental risks associated with AMR on a global scale.

A Unique Monitoring Method for Fecal and Sewage-Derived Chemical Pollution Utilizing International Pellet Watch Approach.

This study established a unique approach to assess fecal contamination by measuring fecal sterols, especially coprostanol (5ß-cholestanol-3ß-ol, 5ß) and cholestanol (5α-cholestan-3ß-ol, 5α) and their ratio 5ß/(5ß + 5α) alongside triclosan (TCS) and methyl-triclosan (MTC) in beached plastic pellets across 40 countries. Coprostanol concentrations ranged from 3.6 to 8190 ng/g pellet with extremely high levels in densely populated areas in African countries. The 5ß/(5ß + 5α) ratio was not affected by the difference in residence time of pellets in aquatic environments, and their spatial pattern showed a positive correlation with that of sedimentary sterols, demonstrating its reliability as an indicator of fecal contamination. Pellets from populated areas of economically developing countries, i.e., Africa and Asia, with lower coverage of wastewater treatment exhibited higher 5ß/(5ß + 5α) ratios (∼0.7) corresponding to ∼1% sewage in seawater, while pellets from developed countries, i.e., the USA, Canada, Japan, and Europe, with higher coverage of modern wastewater treatment displayed lower ratios (∼0.5), corresponding to the first contact limit. Triclosan levels were higher in developing countries (0.4-1298 ng/g pellet), whereas developed countries showed higher methyl-triclosan levels (0.5-70 ng/g pellet) due to TCS conversion during secondary treatment. However, some samples from Japan and Europe displayed higher TCS levels, suggesting contributions from combined sewage overflow (CSO). Combination of 5ß/(5ß + 5α) and MTC/TCS ratios revealed extreme fecal contamination from direct input of raw sewage due to inadequate treatment facilities in some African and South and Southeast Asian countries.

Microbial source tracking of fecal pollution to coral reef lagoons of Norfolk Island, Australia.

Fecal pollution contributes to global degradation of water quality and requires identification of the source(s) for predicting human health risk, tracking disease, and developing management strategies. While fecal indicator bacteria are commonly used to detect fecal pollution, they cannot identify sources. Novel approaches, such as microbial source tracking (MST), can be applied to evaluate the origin of fecal pollution. This study examined fecal pollution in the coral reef lagoons of Norfolk Island, Australia where reef health decline has been related to nutrient input. The primary objective of this study was to evaluate the host sensitivity and specificity of two human wastewater-associated marker genes (Bacteroides HF183 (HF183) and cross-assembly phage (crAssphage)) and four animal feces associated marker genes targeting avian, ruminant, dog, and pig (Helicobacter-associated GFD (GFD), Bacteroides BacR (BacR), Bacteroides DogBact (DogBact), and Bacteroides Pig-2-Bac (Pig-2-Bac)) in wastewater and animal fecal samples collected from Norfolk Island. The prevalence and concentrations of these marker genes along with enterococci genetic marker (ENT 23S rRNA) of general fecal pollution and human adenovirus (HAdV), which is considered predominantly a pathogen but also a human-wastewater associated marker gene, were determined in surface, ground, and marine water resources. A secondary objective of this study was to assess the sources and pathways of fecal pollution to a sensitive marine environment under rainfall events. HF183, crAssphage, HAdV, and BacR demonstrated absolute host sensitivity values of 1.00, while GFD and Pig-2-Bac had host sensitivity values of 0.60, and 0.20, respectively. Host specificity values were > 0.94 for all marker genes. Human and animal (avian, ruminant, dog) fecal sources were present in the coral reef lagoons and surface water whereas groundwater was polluted by human wastewater markers. This study provides understanding of fecal pollution in water resources on Norfolk Island, Australia after precipitation events. The results may aid in effective water quality management, mitigating potential adverse effects on both human and environmental health.

An overview of molecular markers for identification of non-human fecal pollution sources.

Identifying primary sources of fecal pollution is important for assessing public health risks and implementing effective remediation strategies. To date, one of the main molecular approaches for identifying sources of fecal pollution relies on detecting molecular markers within bacterial, viral, or mitochondrial nucleic acids, that are indicative of a particular host. With a primary focus on identifying fecal pollution originating from humans, the field of fecal source tracking often places less emphasis on livestock sources, frequently leaving the problem of wildlife fecal pollution unaddressed. In this review, we summarize 55 previously published and validated molecular assays and describe methods for the detection of molecular markers that are indicative of non-human hosts. They cover a range of 15 animal species/groups with a primary focus on domestic animals including cattle, pigs, dogs, and poultry. Among assays associated with wild animals, the majority are designed to detect bird feces, while the availability of assays for detecting feces of other wild animals is limited. Both domestic and wild animals can represent a zoonotic reservoir of human enteropathogens, emphasizing the importance of their role in public health. This review highlights the need to address the complexity of fecal contamination and to include a broader range of animal species into assay validation and marker identification.

Tracking the sources of Leptospira and nutrient flows in two urban watersheds of Puerto Rico.

This study investigated the relationship between nutrient levels, source of fecal contamination, and pathogenic Leptospira in Puerto Rico's northern coast and San Juan Bay Estuary (SJBE) aquatic ecosystems. Microbial source tracking (MST) was also used to investigate the connections between sources of feces contamination and the presence of Leptospira. Eighty-seven water samples were collected during the June (n=44) and August (n=43) in 2020. To quantify phosphorus and nitrogen concentrations, standard USEPA protocols were utilized, specifically Methods 365.4 for total and dissolved phosphorus, 351.2 for total Kjeldahl nitrogen and ammonium, and 353.2 for nitrate. Lipl32 gene-specific quantitative polymerase chain reaction (qPCR) was used to detect the presence of Leptospira. Human (HF183), canine (BacCan-UCD), and equine (HoF597) MST assays were utilized to trace the origins of fecal contamination. Forty one percent of the locations exceeded Puerto Rico's authorized total phosphorus limit of 160 g L-1, while 34% exceeded the total nitrogen limit of 1700 g L-1. Nearly half of the streams examined are affected by eutrophication. The MST analysis identified human and canine feces as the most prevalent contaminants, affecting approximately 50% of the sites. In addition, Leptospira was detected in 32% of the June samples. There was a significant correlation (r = 0.79) between the incidence of pathogenic Leptospira and the human bacterial marker (HF183). This study illuminates the central role of anthropogenic inputs in nutrient enrichment and pathogen proliferation in Puerto Rico's aquatic ecosystems.

Performance of bacterial and mitochondrial qPCR source tracking methods: A European multi-center study.

With the advent of molecular biology diagnostics, different quantitative PCR assays have been developed for use in Source Tracking (ST), with none of them showing 100% specificity and sensitivity. Most studies have been conducted at a regional level and mainly in fecal slurry rather than in animal wastewater. The use of a single molecular assay has most often proven to fall short in discriminating with precision the sources of fecal contamination. This work is a multicenter European ST study to compare bacterial and mitochondrial molecular assays and was set to evaluate the efficiency of nine previously described qPCR assays targeting human-, cow/ruminant-, pig-, and poultry-associated fecal contamination. The study was conducted in five European countries with seven fecal indicators and nine ST assays being evaluated in a total of 77 samples. Animal fecal slurry samples and human and non-human wastewater samples were analyzed. Fecal indicators measured by culture and qPCR were generally ubiquitous in the samples. The ST qPCR markers performed at high levels in terms of quantitative sensitivity and specificity demonstrating large geographical application. Sensitivity varied between 73% (PLBif) and 100% for the majority of the tested markers. On the other hand, specificity ranged from 53% (CWMit) and 97% (BacR). Animal-associated ST qPCR markers were generally detected in concentrations greater than those found for the respective human-associated qPCR markers, with mean concentration for the Bacteroides qPCR markers varying between 8.74 and 7.22 log10 GC/10 mL for the pig and human markers, respectively. Bacteroides spp. and mitochondrial DNA qPCR markers generally presented higher Spearman's rank coefficient in the pooled fecal samples tested, particularly the human fecal markers with a coefficient of 0.79. The evaluation of the performance of Bacteroides spp., mitochondrial DNA and Bifidobacterium spp. ST qPCR markers support advanced pollution monitoring of impaired aquatic environments, aiming to elaborate strategies for target-oriented water quality management.

The Tomato Brown Rugose Fruit Virus Movement Protein Gene Is a Novel Microbial Source Tracking Marker.

Microbial source tracking (MST) identifies sources of fecal contamination in the environment using host-associated fecal markers. While there are numerous bacterial MST markers that can be used herein, there are few such viral markers. Here, we designed and tested novel viral MST markers based on tomato brown rugose fruit virus (ToBRFV) genomes. We assembled eight nearly complete genomes of ToBRFV from wastewater and stool samples from the San Francisco Bay Area in the United States. Next, we developed two novel probe-based reverse transcription-PCR (RT-PCR) assays based on conserved regions of the ToBRFV genome and tested the markers' sensitivities and specificities using human and non-human animal stool as well as wastewater. The ToBRFV markers are sensitive and specific; in human stool and wastewater, they are more prevalent and abundant than a commonly used viral marker, the pepper mild mottle virus (PMMoV) coat protein (CP) gene. We used the assays to detect fecal contamination in urban stormwater samples and found that the ToBRFV markers matched cross-assembly phage (crAssphage), an established viral MST marker, in prevalence across samples. Taken together, these results indicate that ToBRFV is a promising viral human-associated MST marker. IMPORTANCE Human exposure to fecal contamination in the environment can cause transmission of infectious diseases. Microbial source tracking (MST) can identify sources of fecal contamination so that contamination can be remediated and human exposures can be reduced. MST requires the use of host-associated MST markers. Here, we designed and tested novel MST markers from genomes of tomato brown rugose fruit virus (ToBRFV). The markers are sensitive and specific to human stool and highly abundant in human stool and wastewater samples.

Low antimicrobial resistance in Escherichia coli isolates from two large Austrian alpine karstic spring catchments.

The increasing occurrence of antibiotic resistant bacteria poses a threat to global public health. Clinically relevant resistances also spread through the environment. Aquatic ecosystems in particular represent important dispersal pathways. In the past, pristine water resources have not been a study focus, although ingestion of resistant bacteria through water consumption constitutes a potentially important transmission route. This study assessed antibiotic resistances in Escherichia coli populations in two large well-protected and well-managed Austrian karstic spring catchments representing essential groundwater resources for water supply. E. coli were detected seasonally only during the summer period. By screening a representative number of 551 E. coli isolates from 13 sites in two catchments, it could be shown that the prevalence of antibiotic resistance in this study area is low. 3.4 % of the isolates showed resistances to one or two antibiotic classes, 0.5 % were resistant to three antibiotic classes. No resistances to critical and last-line antibiotics were detected. By integrating fecal pollution assessment and microbial source tracking, we could infer that ruminants were the main hosts for antibiotic resistant bacteria in the studied catchment areas. A comparison with other studies on antibiotic resistances in karstic or mountainous springs highlighted the low contamination status of the model catchments studied here, most likely due to the high protection and careful management while other, less pristine catchments showed much higher antibiotic resistances. We demonstrate that studying easily accessible karstic springs allows a holistic view on large catchments concerning the extent and origin of fecal pollution as well as antibiotic resistance. This representative monitoring approach is also in line with the proposed update of the EU Groundwater Directive (GWD).

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.

Using watershed characteristics to enhance fecal source identification.

Fecal pollution is one of the most prevalent forms of pollution affecting waterbodies worldwide, threatening public health and negatively impacting aquatic environments. Microbial source tracking (MST) applies polymerase chain reaction (PCR) technology to help identify the source of fecal pollution. In this study, we combine spatial data for two watersheds with general and host-associated MST markers to target human (HF183/BacR287), bovine (CowM2), and general ruminant (Rum2Bac) sources. Concentrations of MST markers in samples were determined with droplet digital PCR (ddPCR). The three MST markers were detected at all sites (n = 25), but bovine and general ruminant markers were significantly associated with watershed characteristics. MST results, combined with watershed characteristics, suggest that streams draining areas with low-infiltration soil groups and high agricultural land use are at an increased risk for fecal contamination. Microbial source tracking has been applied in numerous studies to aid in identifying the sources of fecal contamination, but these studies usually lack information on the involvement of watershed characteristics. Our study combined watershed characteristics with MST results to provide more comprehensive insight into the factors that influence fecal contamination in order to implement the most effective best management practices.

Unraveling the influence of human fecal pollution on antibiotic resistance gene levels in different receiving water bodies using crAssphage indicator gene.

Discharged wastewater treatment plant (WWTP) effluents can contaminate receiving water bodies with human feces and alter the abundance of antibiotic resistance genes (ARGs). In this study, we examined the co-occurrence of ARGs, human fecal pollution indicator crAssphage, and antibiotics in human feces and a series of connected receiving water bodies affected by human feces, including water from different treatment units of a WWTP, river, lake, and tap waters. Results showed that crAssphage was detected in 68.2 % of the studied water bodies, confirming widespread human fecal contamination. Both ARG and crAssphage abundances exhibited a distance-decay effect from the emission source to the receiving environment. Interestingly, the detected ARG abundance in the water bodies was significantly correlated with crAssphage abundance but not with the residual antibiotic concentration, demonstrating that the presence of ARG could largely be explained by the extent of fecal pollution, with no clear signs of antibiotic selection. In addition, 14 ARGs co-shared by human feces and water bodies were significantly correlated with crAssphage. Furthermore, a close evolutionary relationship was observed between the blaTEM-1 gene from human feces and aquatic environments. These results imply a potential ARG exchange between human feces and receiving water bodies. Overall, this study provides important insights into the distribution and sources of ARGs in water bodies affected by human fecal contamination.

Spatial distribution of fecal pollution indicators in sewage sludge flocs and their removal and inactivation as revealed by qPCR/viability-qPCR during potassium ferrate treatment.

Sludge reuse and utilization is one of important routines of disseminating fecal pollution to surface water and groundwater. However, it remains unclear the spatial distribution of fecal pollution indicators in sludge flocs and their reductions during sludge treatment processes. In this study, the abundances of fecal pollution indicators including cross-assembly phage (crAssphage), JC and BK polyomavirus (JCPyV, BKPyV), human adenovirus (HAdV), the human-specific HF183 Bacteroides (HF183) and Escherichia coli (EC) in soluble extracellular polymeric substances (S-EPS), loosely-bound EPS (LB-EPS), tightly-bound EPS (TB-EPS), and pellets of sludge flocs were determined, and the effect of potassium ferrate (PF) treatment on their removal and inactivation was investigated by using both qPCR and viability-qPCR. Results showed that all investigated indicators were detected in each fraction of sludge flocs. The PF treatment led to a great migration of indicators from sludge pellets to sludge EPS and some extent of their inactivation in each fraction of sludge flocs. The overall reductions of human fecal indicators in sludge determined by qPCR were 0-1.30 logs, which were 0-2 orders of magnitude lower than those of 0.69-2.39 logs detected by viability-qPCR, implying their inactivation by PF treatment to potentially alleviate the associated human health risks.

Distribution of human fecal marker genes and their association with pathogenic viruses in untreated wastewater determined using quantitative PCR.

Quantitative microbial risk assessment (QMRA) of human health risks using human fecal marker genes (HFMGs) is an useful water quality management tool. To inform accurate QMRA analysis, generation of probability distribution functions for HFMGs, and reference pathogenic viruses can be improved by input of correlation and ratios based upon measurement of HFMGs and gene copies (GC) of pathogenic viruses in untreated wastewater. The concentrations of four HFMGs (Bacteroides HF183, Lachnospiraceae Lachno3, CrAssphage and pepper mild mottle virus (PMMoV)), and GC of three reference pathogenic viruses human adenovirus 40/41 (HAdV 40/41), human norovirus GI + GII HNoV GI + GII and enterovirus (EV) were measured in untreated wastewater samples collected over a period of 12 months from two wastewater treatment plants in Sydney, Australia using quantitative polymerase chain reaction (qPCR) and reverse transcription qPCR (RT-qPCR). Over the course of the study, the GC of potential pathogenic viruses were 3-5 orders of magnitude lower than HFMGs in untreated wastewater. The GC of pathogenic viruses were highly variable over the course of the study, which contrasted with the concentrations of HFMGs that were quite stable with little variation observed within and between WWTPs. Among the HFMGs, HF183, CrAssphage and PMMoV correlated well with pathogenic virus GC, whereas weak or negative correlations were observed between Lachno3 and pathogenic virus GC. While the two assessed WWTPs had dissimilar population service sizes, the ratios between log10 transformed pathogenic virus GC and HFMGs demonstrated similar central tendency and variability for the same combinations between WWTP A and WWTP B with no difference between the WWTPs. This suggests the widespread presence of these HFMGs in both populations serviced by these two WWTPs. The observed correlation and ratios of HFMGs and GC of reference pathogenic viruses can contribute to improved QMRA of human health risks in environmental waters subject to fresh sewer overflows.

Distribution and correlation between antibiotic resistance genes and host-associated markers before and after swine fever in the longjiang watershed.

Antibiotic resistance genes (ARGs) are abundantly shed in feces. Thus, it is crucial to identify their host sources so that ARG pollution can be effectively mitigated and aquatic ecosystems can be properly conserved. Here, spatiotemporal variations and sources of ARGs in the Longjiang watershed of South China were investigated by linking them with microbial source tracker (MST) indicators. The most frequently detected ARGs (>90%) were sulI, sulII, blaTEM, tetW, ermF, and the mobile element intI1. Spatial distribution analyses showed that tributaries contributed significantly more sulI, sulII, and ermF contamination to the Longjiang watershed than the main channel. MST indicator analysis revealed that the Longjiang watershed was contaminated mainly by human fecal pollution. Livestock- and poultry-associated fecal pollution significantly declined after the swine fever outbreak. The occurrence of most ARGs is largely explained by human fecal pollution. In contrast, pig fecal pollution might account for the prevalence of tetO. Moreover, combined human-pig fecal pollution contributed to the observed blaNDM-1 distribution in the Longjiang watershed. Subsequent analysis of the characteristics of MST markers disclosed that the relatively lower specificities of BacHum and Rum-2-Bac may lead to inaccurate results of tracking ARG pollution source. The present study determined spatiotemporal variations and ARG origins in the Longjiang watershed by combining MST markers. It also underscored the necessity of using multiple MST markers simultaneously to identify and characterize ARG pollution sources accurately.

Effective coastal Escherichia coli monitoring by unmanned aerial vehicles (UAV) thermal infrared images.

Coastal Escherichia coli (E. coli) significantly influence ocean safety and public health, thus requiring an effective E. coli pollution monitoring. However conventional detection relying on manual field sampling is time-consuming. Here, this study established an E. coli estimation model based on thermal remote sensing of unmanned aerial vehicles (UAV). This model was developed against one-year comprehensive field work in a representative sandy beach and further validated against 50 beaches in Hong Kong to evaluate its applicability. The estimated E. coli concentrations were in a reliable agreement with direct measurements. For this model, this study deployed the radon-222 (222Rn) as a bridging tracer to couple UAV thermal images and coastal E. coli concentrations. Coastal 222Rn can be reflected on the UAV thermal images, and there was a good positive correlation between the 222Rn activity and coastal E. coli concentration via one-year field data. Hence, coupling the 222Rn activity estimated from UAV thermal images and the relationship between 222Rn and E. coli, this study can readily monitor coastal E. coli by UAV. These findings highlighted that UAV technology is an effective approach to measure the E. coli concentrations and can further pave the way for an efficient coastal E. coli monitoring and public health risk warning.

Escherichia cryptic clade II through clade VIII: Rapid detection and prevalence in feces and surface water.

Bacteria of the cryptic lineage of genus Escherichia, or Escherichia cryptic clades (cryptic clades), are phenotypically indistinguishable from Escherichia coli (E. coli) using standard biochemical tests. Except for clade I (C-I), cryptic clades were hypothetically believed to be environmental but not enteric. If so, they would hinder the interpretation of current E. coli-based water quality (fecal pollution) monitoring in the United States because environmental bacteria do not indicate the presence of harmful fecal material. This study was performed to develop a rapid method for the detection of cryptic clades and to investigate their potential impact on water quality monitoring. By whole-genome comparison, one gene, named ecc (Escherichiacryptic clades), was identified to be unique to C-II through C-VIII. An end-point polymerase chain reaction (PCR) method, eccPCR, was developed by targeting the ecc. The results of in-silico and wet tests demonstrated 100 % sensitivity and specificity of the eccPCR to detect C-II through C-VIII. Based on the EPA Method 1603, 519 presumptive E. coli isolates were obtained from the fecal samples of 13 different host species and 192 isolates from surface water samples taken at four locations in a watershed of mid-Missouri. As indicated by the eccPCR amplification, the overall prevalence of C-II through C-VIII in the presumptive E. coli isolates was estimated to be about 0.6 % in the fecal samples and about 1.6 % in the water samples. Therefore, the potential impact of cryptic clades on water quality monitoring may be limited if EPA Method 1603 is used. Furthermore, clades C-II through C-VIII in stream water samples were found repeatedly only at a single sampling site, but neither at the upstream sites nor five kilometers downstream of the site. The data do not support nor reject the environmental hypothesis about cryptic clades. Further study is needed to determine the implication of the observation.

Predictive modeling of microbiological seawater quality in karst region using cascade model.

This paper presents an in-depth analysis of seawater quality measurements during the bathing seasons from year 2009 to 2020 in the city of Rijeka, Croatia. Due to rare occurrences of measurements with less than excellent water quality, considered dataset is deeply imbalanced. Additionally, it incorporates measurements under the influence of submerged groundwater discharges (SGD), which were observed in some bathing locations. These discharges were previously thought to dry up during the summer season and are now suspected to be one of the causes of increased Escherichia coli values. Consequently, and in view of the fact that the accuracy of prediction models can be significantly influenced by temporal and spatial variation of the input data, a novel cascade prediction modeling strategy was proposed. It consists of a sequence of prediction models which tend to identify general environmental conditions which confidently lead to excellent bathing water quality. The proposed model uses environmental features which can rather easily be estimated or obtained from the weather forecast. The model was trained on a highly biased dataset, consisting of data from locations with and without SGD influence, and for the time period spanning extremely dry and warm seasons, extremely wet seasons, as well as normal seasons. To simulate realistic application, the model was tested using temporal and spatial stratification of data. The cascade strategy was shown to be a good approach for reliably detecting environmental parameters which produce excellent water quality. Proposed model is designed as a filter method, where instances classified as less-than-excellent water quality require further analysis. The cascade model provides great flexibility as it can be customized to the particular needs of the investigated area and dataset specifics.

Non-point source fecal contamination from aging wastewater infrastructure is a primary driver of antibiotic resistance in surface waters.

Antibiotic resistance is a global threat to human health. Many surface water resources are environmental hotspots of antibiotic resistant gene (ARG) transfer, with agricultural runoff and human waste highlighted as common sources of ARGs to aquatic systems. Here we quantified fecal marker genes and ARGs in 992 stream water samples collected seasonally during a 5-year period from 115 sites across the Upper Oconee watershed (Georgia, USA), an area characterized by gradients of agricultural and urban development. Widespread fecal contamination was found from humans (48% of samples), ruminants (55%), and poultry (19%), and 73% of samples tested positive for at least one of the six targeted ARGs (ermB, tet(B), blaCTX-M-1, blaKPC, blaSHV, and qnrS). While ARGs were strongly correlated with human fecal markers, many highly contaminated samples were not associated with sewage outfalls, an expected source of fecal and ARG pollution. To determine sources of contamination, we synthesized ARG and fecal marker data with geospatial data on land use/land cover and wastewater infrastructure across the watershed. This novel analysis found strong correlations between ARGs and measures of sewer density, sewer length, and septic system age within sample watersheds, indicating non-point sources of fecal contamination from aging wastewater infrastructure can be critical disseminators of anthropogenic ARGs in the environment.

Connecting microbial, nutrient, physiochemical, and land use variables for the evaluation of water quality within mixed use watersheds.

As non-point sources of pollution begin to overtake point sources in watersheds, source identification and complicating variables such as rainfall are growing in importance. Microbial source tracking (MST) allows for identification of fecal contamination sources in watersheds; when combined with data on land use and co-occuring variables (e.g., nutrients, sediment runoff) MST can provide a basis for understanding how to effectively remediate water quality. To determine spatial and temporal trends in microbial contamination and correlations between MST and nutrients, water samples (n = 136) were collected between April 2017 and May of 2018 during eight sampling events from 17 sites in 5 mixed-use watersheds. These samples were analyzed for three MST markers (human - B. theta; bovine - CowM2; porcine - Pig2Bac) along with E. coli, nutrients (nitrogen and phosphorus species), and physiochemical paramaters. These water quality variables were then paired with data on land use, streamflow, precipitation and management practices (e.g., tile drainage, septic tank density, tillage practices) to determine if any significant relationships existed between the observed microbial contamination and these variables. The porcine marker was the only marker that was highly correlated (p value <0.05) with nitrogen and phosphorus species in multiple clustering schemes. Significant relationships were also identified between MST markers and variables that demonstrated temporal trends driven by precipitation and spatial trends driven by septic tanks and management practices (tillage and drainage) when spatial clustering was employed.