Microbial source tracking (MST) has been recognised as an effective tool for determining the origins and sources of faecal contamination in various terrestrial and aquatic ecosystems. Thus, it has been widely applied in environmental DNA (eDNA) surveys to define specific animal- and human-associated faecal eDNA. In this context, identification of and differentiation between anthropogenic and zoogenic faecal pollution origins and sources are pivotal for the evaluation of waterborne microbial contamination transport and the associated human, animal, and environmental health risks. These concerns are particularly pertinent to diverse nature-based solutions (NBS) that are being applied specifically to secure water safety and human and ecosystem well-being, for example, constructed wetlands (CWs) for water and wastewater treatment. The research in this area has undergone a constant evolution, and there is a solid foundation of publications available across the world. Hence, there is an early opportunity to synthesise valuable information and relevant knowledge on this specific topic, which will greatly benefit future work by improving NBS design and performance. By selecting 15 representative research reports published over 20 years, we review the current state of MST technology applied for faecal-associated contamination measures in NBS/CWs throughout the world.

We used quantitative microbial risk assessment to estimate ingestion risk for intI1, erm(B), sul1, tet(A), tet(W), and tet(X) in private wells contaminated by human and/or livestock feces. Genes were quantified with five human-specific and six bovine-specific microbial source-tracking (MST) markers in 138 well-water samples from a rural Wisconsin county. Daily ingestion risk (probability of swallowing ≥1 gene) was based on daily water consumption and a Poisson exposure model. Calculations were stratified by MST source and soil depth over the aquifer where wells were drilled. Relative ingestion risk was estimated using wells with no MST detections and >6.1 m soil depth as a referent category. Daily ingestion risk varied from 0 to 8.8 × 10-1 by gene and fecal source (i.e., human or bovine). The estimated number of residents ingesting target genes from private wells varied from 910 (tet(A)) to 1,500 (intI1 and tet(X)) per day out of 12,000 total. Relative risk of tet(A) ingestion was significantly higher in wells with MST markers detected, including wells with ≤6.1 m soil depth contaminated by bovine markers (2.2 [90% CI: 1.1-4.7]), wells with >6.1 m soil depth contaminated by bovine markers (1.8 [1.002-3.9]), and wells with ≤6.1 m soil depth contaminated by bovine and human markers simultaneously (3.1 [1.7-6.5]). Antibiotic resistance genes (ARGs) were not necessarily present in viable microorganisms, and ingestion is not directly associated with infection. However, results illustrate relative contributions of human and livestock fecal sources to ARG exposure and highlight rural groundwater as a significant point of exposure.IMPORTANCEAntibiotic resistance is a global public health challenge with well-known environmental dimensions, but quantitative analyses of the roles played by various natural environments in transmission of antibiotic resistance are lacking, particularly for drinking water. This study assesses risk of ingestion for several antibiotic resistance genes (ARGs) and the class 1 integron gene (intI1) in drinking water from private wells in a rural area of northeast Wisconsin, United States. Results allow comparison of drinking water as an exposure route for antibiotic resistance relative to other routes like food and recreational water. They also enable a comparison of the importance of human versus livestock fecal sources in the study area. Our study demonstrates the previously unrecognized importance of untreated rural drinking water as an exposure route for antibiotic resistance and identifies bovine fecal material as an important exposure factor in the study setting.

Fecal pollution of surface water is a pervasive problem that negatively affects waterbodies concerning both public health and ecological functions. Current assessment methods monitor fecal indicator bacteria (FIB) to identify pollution sources using culture-based quantification and microbial source tracking (MST). These types of information assist stakeholders in identifying likely sources of fecal pollution, prioritizing them for remediation, and choosing appropriate best management practices. While both culture-based quantification and MST are useful, they yield different kinds of information, potentially increasing uncertainty in prioritizing sources for management. This study presents a conceptual framework that takes separate human health risk estimates based on measured MST and E. coli concentrations as inputs and produces an estimate of the overall fecal impairment risk as its output. The proposed framework is intended to serve as a supplemental screening tool for existing monitoring programs to aid in identifying and prioritizing sites for remediation. In this study, we evaluated the framework by applying it to two primarily agricultural watersheds and several freshwater recreational beaches using existing routine monitoring data. Based on a combination of E. coli and MST results, the proposed fecal impairment framework identified four sites in the watersheds as candidates for remediation and identified temporal trends in the beach application. As these case studies demonstrate, the proposed fecal impairment framework is an easy-to-use and cost-effective supplemental screening tool that provides actionable information to managers using existing routine monitoring data, without requiring specialized expertize.

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.

There is no reference of microbiological water quality in the European Union\'s Water Framework Directive, adapted into English law, and consequently microbial water quality is not routinely monitored in English rivers, except for two recently designated bathing water sites. To address this knowledge gap, we developed an innovative monitoring approach for quantitative assessment of combined sewer overflow (CSO) impacts on the bacteriology of receiving rivers. Our approach combines conventional and environmental DNA (eDNA) based methods to generate multiple lines of evidence for assessing risks to public health. We demonstrated this approach by investigating spatiotemporal variation in the bacteriology of the Ouseburn in northeast England for different weather conditions in the summer and early autumn of the year 2021 across eight sampling locations that comprised rural, urban, and recreational land use settings. We characterized pollution source attributes by collecting sewage from treatment works and CSO discharge at the peak of a storm event. CSO discharge was characterized by log10 values per 100 mL (average ± stdev) of 5.12 ± 0.03 and 4.90 ± 0.03 for faecal coliforms and faecal streptococci, and 6.00 ± 0.11 and 7.78 ± 0.04 for rodA and HF183 genetic markers, for E. coli and human host associated Bacteroides, respectively, indicating about 5 % sewage content. SourceTracker analysis of sequencing data attributed 72-77 % of bacteria in the downstream section of the river during a storm event to CSO discharge sources, versus only 4-6 % to rural upstream sources. Data from sixteen summer sampling events in a public park exceeded various guideline values for recreational water quality. Quantitative microbial risk assessment (QMRA) predicted a median and 95th percentile risk of 0.03 and 0.39, respectively, of contracting a bacterial gastrointestinal disease when wading and splashing around in the Ouseburn. We show clearly why microbial water quality should be monitored where rivers flow through public parks, irrespective of their bathing water designation.

The WHO recognises antimicrobial resistance (AMR) as a global health threat. The environment can act as a reservoir, facilitating the exchange and the physical movement of resistance. Aquatic environments are at particular risk of pollution, with large rivers subject to pollution from nearby human, industrial or agricultural activities. The land uses associated with these activities can influence the type of pollution. One type of pollution and a likely contributor to AMR pollution that lowers water quality is faecal pollution. Both pose an acute health risk and could have implications for resistance circulating in communities. The effects of land use are typically studied using physiochemical parameters or in isolation of one another. However, this study aimed to investigate the impact of different land uses on riverine systems. We explored whether differences in sources of faecal contamination are reflected in AMR gene concentrations across agricultural and urban areas. Water quality from three rivers impacted by different land uses was assessed over one year by quantifying faecal indicator bacteria (FIB), microbial source tracking markers (MST) and AMR genes. In addition, a multiparametric analysis of AMR gene pollution was carried out to understand whether agricultural and urban areas are similarly impacted. Faecal indicators varied greatly, with the highest levels of FIB and the human MST marker observed in urban regions. In addition, these faecal markers correlated with AMR genes. Similarly, significant correlations between the ruminant MST marker and AMR gene levels in agriculture areas were observed. Overall, applying multiparametric analyses to include AMR gene levels, separation and clustering of sites were seen based on land use characterisation. This study suggests that differences in prescription of antimicrobials used in animal and human healthcare may influence environmental resistomes across agricultural and urban areas. In addition, public health risks due to exposure to faecal contamination and AMR genes are highlighted.

Viral indicators of human-fecal contamination in wastewaters and environmental waters have been getting much attention in the past decade. Cross-assembly phage (crAssphage) is the most abundant DNA virus in human feces. Recently, the usefulness of crAssphage as a microbial source tracking and water quality monitoring tool for human-fecal contamination has been highlighted. Here, we conducted a comprehensive review on crAssphage in water, focusing on detection methodology, concentration range in various waters and wastewaters, specificity to human-fecal contamination, and reduction in wastewater treatment systems. This review highlights that crAssphage is globally distributed in wastewaters and various fecal-contaminated water bodies at high concentrations without seasonal fluctuations. CrAssphage is highly specific to human-fecal contamination and is rarely found in animal feces. It also has a good potential as a performance indicator to ensure virus reduction in wastewater treatment systems. Accordingly, crAssphage could be an effective tool for monitoring of human-fecal contamination and potential presence of fecal pathogenic microbes in environmental waters. Bridging the research gaps highlighted in this review would make crAssphage a powerful tool to support the control of water-related health risks.

Beach sand may act as a reservoir for numerous microorganisms, including enteric pathogens. Several of these pathogens originate in human or animal feces, which may pose a public health risk. In August 2019, high levels of fecal indicator bacteria (FIB) were detected in the sand of the Azorean beach Prainha, Terceira Island, Portugal. Remediation measures were promptly implemented, including sand removal and the spraying of chlorine to restore the sand quality. To determine the source of the fecal contamination, during the first campaign, supratidal sand samples were collected from several sites along the beach, followed by microbial source tracking (MST) analyses of Bacteroides marker genes for five animal species, including humans. Some of the sampling sites revealed the presence of marker genes from dogs, seagulls, and ruminants. Making use of the information on biological sources originating partially from dogs, the municipality enforced restrictive measures for dog-walking at the beach. Subsequent sampling campaigns detected low FIB contamination due to the mitigation and remediation measures that were undertaken. This is the first case study where the MST approach was used to determine the contamination sources in the supratidal sand of a coastal beach. Our results show that MST can be an essential tool to determine sources of fecal contamination in the sand. This study shows the importance of holistic management of beaches that should go beyond water quality monitoring for FIB, putting forth evidence for beach sand monitoring.

Unsheltered homelessness is rapidly becoming a critical issue in many cities worldwide. The worsening situation not only highlights the socioeconomic plight, but it also raises awareness of ancillary issues such as the potential implications for urban water quality. The objective of this study was to simultaneously leverage diverse source tracking tools to develop a chemical and microbial fingerprint describing the relative contribution of direct human inputs into Las Vegas\' tributary washes. By evaluating a wide range of urban water matrices using general water quality parameters, fecal indicator bacteria (FIB), human-associated microbial markers [e.g., HF183, crAssphage, and pepper mild mottle virus (PMMoV)], 16S rRNA gene sequencing data, and concentrations of 52 anthropogenic trace organic compounds (TOrCs), this study was able to differentiate principal sources of these constituents, including contributions from unsheltered homelessness. For example, HF183 (31% vs. 0%), crAssphage (61% vs. 5%), and PMMoV (72% vs. 55%) were more frequently detected in tributary washes with higher homeless census counts vs. \'control\' tributary washes. Illicit drugs or their metabolites (e.g., heroin, acetylmorphine, amphetamine, and cocaine) and select TOrCs (e.g., acetaminophen, caffeine, ibuprofen, and naproxen) were also detected more frequently and at higher concentrations in the more anthropogenically-impacted washes. These data can be used to raise awareness of the shared interests between the broader community and those who are experiencing homelessness, notably the importance of protecting environmental health and water quality. Ultimately, this may lead to more rapid adoption of proven strategies for achieving functional zero homelessness, or at least additional resources for unsheltered individuals.

The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification of the niches where samples originate. However, current methods face challenges when source tracking is scaled up. Here, we introduce a deep learning method based on the Ontology-aware Neural Network approach, ONN4MST, for large-scale source tracking. ONN4MST outperformed other methods with near-optimal accuracy when source tracking among 125,823 samples from 114 niches. ONN4MST also has a broad spectrum of applications. Overall, this study represents the first model-based method for source tracking among sub-million microbial community samples from hundreds of niches, with superior speed, accuracy, and interpretability. ONN4MST is available at https://github.com/HUST-NingKang-Lab/ONN4MST .