Variable fecal source prioritization in recreational waters routinely monitored with viral and bacterial general indicators

Quantitative fecal pollution assessment with bacterial, viral, and molecular methods in small stream tributaries

Stream water quality can be impacted by a myriad of fecal pollution sources and waste management practices. Identifying origins of fecal contamination can be challenging, especially in high order streams where water samples are influenced by pollution from large drainage areas. Strategic monitoring of tributaries can be an effective strategy to identify conditions that influence local water quality. Water quality is assessed using fecal indicator bacteria (FIB); however, FIB cannot differentiate sources of fecal contamination nor indicate the presence of disease-causing viruses. Under different land use scenarios, three small stream catchments were investigated under 'wet' and 'dry' conditions (Scenario 1: heavy residential; Scenario 2: rural residential; and Scenario 3: undeveloped/agricultural). To identify fecal pollution trends, host-associated genetic targets HF183/BacR287 (human), Rum2Bac (ruminant), GFD (avian), and DG3 (canine) were analyzed along with FIB (Escherichia coli and enterococci), viral indicators (somatic and F+ coliphage), six general water quality parameters, and local rainfall. Levels of E. coli exceeded single sample maximum limits (235 CFU/100 mL) in 70.7 % of samples, enterococci (70 CFU/100 mL) in 100 % of samples, and somatic coliphage exceeded advisory thresholds (600 PFU/L) in 34.1 % of samples. The detection frequency for the human-associated genetic marker was highest in Scenario 3 (50 % of samples) followed by Scenario 2 (46 %), while the ruminant-associated marker was most prevalent in Scenario 1 (64 %). Due to the high proportion of qPCR-based measurements below the limit of quantification, a Bayesian data analysis approach was applied to investigate links between host-associated genetic marker occurrence with that of rainfall and fecal indicator levels. Multiple trends associated with small stream monitoring were revealed, emphasizing the role of rainfall, the utility of fecal source information to improve water quality management. And furthermore, water quality monitoring with bacterial or viral methodologies can alter the interpretation of fecal pollution sources in impaired waters.

A fecal score approximation model for analysis of real-time quantitative PCR fecal source identification measurements

Numerous qPCR-based methods are available to estimate the concentration of fecal pollution sources in surface waters. However, qPCR fecal source identification data sets often include a high proportion of non-detections (reactions failing to attain a prespecified minimal signal intensity for detection) and measurements below the assay lower limit of quantification (minimal signal intensity required to estimate target concentration), making it challenging to interpret results in a quantitative manner while accounting for error. In response, a Bayesian statistic based Fecal Score (FS) approach was developed that estimates the weighted average concentration of a fecal source identification genetic marker across a defined group of samples, mathematically incorporating qPCR measurements from all samples. Yet, implementation is technically demanding and computationally intensive requiring specialized training, the use of expert software, and access to high performance computing. To address these limitations, this study reports a novel approximation model for FS determination based on a frequentist approach. The performance of the Bayesian and Frequentist models are compared using fecal source identification qPCR data representative of different 'censored' data scenarios from a recently published study focusing on the impact of stormwater discharge in urban streams. In addition, data set eligibility recommendations for the responsible use of these models are presented. Findings indicate that the Frequentist model can generate similar average concentrations and uncertainty estimates for FS, compared to the original Bayesian approach. The Frequentist model should make calculations less computationally and technically intensive, allowing for the development of easier to use data analysis tools for fecal source identification applications.

Microbiological hazard identification in river waters used for recreational activities

Pathogenic bacteria, viruses, and parasites can cause waterborne disease outbreaks. The study of coastal water quality contributes to identifying potential risks to human health and to improving water management practices. The Río de la Plata River, a wide estuary in South America, is used for recreational activities, as a water source for consumption and as a site for sewage discharges. In the present study, as the first step of a quantitative microbial risk assessment of the coastal water quality of this river, a descriptive study was performed to identify the microbial pathogens prevalent in its waters and in the sewage discharged into the river. Two sites, representing two different potential risk scenarios, were chosen: a heavily polluted beach and an apparently safe beach. Conductivity and fecal contamination indicators including enterococci, Escherichia coli, F + RNA bacteriophages, and human polyomaviruses showed high levels. Regarding enterococci, differences between sites were significant (p-values <0.001). 93.3% and 56.5% of the apparently safe beach exceeded the recreational water limits for E. coli and enterococci. Regarding pathogens, diarrheagenic E. coli, Salmonella, and noroviruses were detected with different frequencies between sites. The parasites Cryptosporidium spp. and Giardia duodenalis were frequently detected in both sites. The results regarding viral, bacterial, and parasitic pathogens, even without correlation with conventional indicators, showed the importance of monitoring a variety of microorganisms to determine water quality more reliably and accurately, and to facilitate further studies of health risk assessment. The taxonomic description of microbial pathogens in river waters allow identifying the microorganisms that infect the population living on its shores but also pathogens not previously reported by the clinical surveillance system.

Relationship between coliphage and Enterococcus at southern California beaches and implications for beach water quality management

Coliphage have been suggested as an alternative to fecal indicator bacteria for assessing recreational beach water quality, but it is unclear how frequently and at what types of beaches coliphage produces a different management outcome. Here we conducted side-by-side sampling of male-specific and somatic coliphage by the new EPA dead-end hollow fiber ultrafiltration (D-HFUF-SAL) method and Enterococcus at southern California beaches over two years. When samples were combined for all beach sites, somatic and male-specific coliphage both correlated with Enterococcus. When examined categorically, Enterococcus would have resulted in approximately two times the number of health advisories as somatic coliphage and four times that of male-specific coliphage,using recently proposed thresholds of 60 PFU/100 mL for somatic and 30 PFU/100 mL for male-specific coliphage. Overall, only 12% of total exceedances would have been for coliphage alone. Somatic coliphage exceedances that occurred in the absence of an Enterococcus exceedance were limited to a single site during south swell events, when this beach is known to be affected by nearby minimally treated sewage. Thus, somatic coliphage provided additional valuable health protection information, but may be more appropriate as a supplement to FIB measurements rather than as replacement because: (a) EPA-approved PCR methods for Enterococcus allow a more rapid response, (b) coliphage is more challenging owing to its greater sampling volume and laboratory time requirements, and (c) Enterococcus' long data history has yielded predictive management models that would need to be recreated for coliphage.

Validation of a modified IDEXX defined-substrate assay for detection of antimicrobial resistant E. coli in environmental reservoirs

The emergence of antimicrobial resistant (AMR) bacteria has been identified as one of the principal public health threats of the 21st century. The World Health Organization (WHO) has long recognized the threat of AMR bacteria and highlights environmental surveillance as a key step in understanding and combating the global rise of antimicrobial resistance. Here, we modified and validated an IDEXX defined-substrate assay commonly used for recreational water quality monitoring of E. coli to enumerate cefotaxime resistant E. coli in environmental reservoirs. We then applied this method to understand AMR trends in multiple environmental matrices over time. This modified IDEXX assay performed highly similarly to two widely accepted plating methods (TBX and MacConkey agar) for enumerating AMR bacteria in pure culture samples and environmental matrices, indicating it is a valid method for enumerating AMR E. coli in the environment. We detected AMR E. coli in urban surface water (63%, 15/24 samples), surface soil (35%, 8/23), and waterfowl feces (43%, 3/7). Sampling around a heavy rain event also revealed that concentrations of AMR E. coli and total E. coli co-vary over time in both surface water and surface soil. This novel method can reliably be performed outside of a laboratory setting and has very low equipment requirements, meaning it has tremendous potential to bolster global monitoring efforts, particularly in resource-restricted and highly rural settings.

Genetic fecal source identification in urban streams impacted by municipal separate storm sewer system discharges

Municipal stormwater systems are designed to collect, transport, and discharge precipitation from a defined catchment area into local surface waters. However, these discharges may contain unsafe levels of fecal waste. Paired measurements of Escherichia coli, precipitation, three land use metrics determined by geographic information system (GIS) mapping, and host-associated genetic markers indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), dog (DG3), and avian (GFD) fecal sources were assessed in 231 urban stream samples impacted by two or more municipal stormwater outfalls. Receiving water samples were collected twice per month (n = 24) and after rain events (n = 9) from seven headwaters of the Anacostia River in the District of Columbia (United States) exhibiting a gradient of impervious surface, residential, and park surface areas. Almost 50% of stream samples (n = 103) were impaired, exceeding the local E. coli single sample maximum assessment level (410 MPN/100 ml). Fecal scores (average log10 copies per 100 ml) were determined to prioritize sites by pollution source and to evaluate potential links with land use, rainfall, and E. coli levels using a recently developed censored data analysis approach. Dog, ruminant, and avian fecal scores were almost always significantly increased after rain or when E. coli levels exceeded the local benchmark. Human fecal pollution trends showed the greatest variability with detections ranging from 9.1% to 96.7% across sites. Avian fecal scores exhibited the closest connection to land use, significantly increasing in catchments with larger residential areas after rain events (p = 0.038; R2 = 0.62). Overall, results demonstrate that combining genetic fecal source identification methods with GIS mapping complements routine E. coli monitoring to improve management of urban streams impacted by stormwater outfalls.

Developing a novel Bifidobacterium phage quantitative polymerase chain reaction-based assay for tracking untreated wastewater

Microbial source tracking (MST) tools provide insights on fecal pollution levels in aquatic environments using predominantly quantitative PCR (qPCR) assays that target host-associated molecular marker genes. Existing wastewater-associated marker genes have shown limited or significant cross-reactions with non-human fecal samples. In this study, we mined the current Gut Phage Database (GPD) and designed a novel untreated wastewater-specific Bifidobacterium phage qPCR assay (i.e., Bifi assay). The sensitivity and specificity of the Bifi marker genes were assessed by collectively analyzing untreated (n = 33) and treated (n = 15) wastewater and non-human fecal samples (i.e., Rabbit, mouse, cow, horse, pig, chicken, sheep, dog, deer, kangaroos; n = 113) in Shenzhen, Guangdong Province, China and Brisbane, Australia. Bifi assay revealed 100% host-specificity against non-human fecal samples collected from Shenzhen and Brisbane. Furthermore, this marker gene was also detected in all untreated and treated wastewater samples, whose concentrations ranged from 5.54 to 6.83 log₁₀ GC/L. In Shenzhen, the concentrations of Bifi marker gene were approximately two orders of magnitude lower than Bacteroides (HF183/BacR287 assay) and CrAssphage (CPQ_56 assay). The concentration of Bifi marker gene in untreated wastewater from Brisbane was 1.35 log₁₀ greater than those in Shenzhen. Our results suggest that Bifi marker gene has the potential to detect and quantify the levels of human fecal pollution in Shenzhen and Brisbane. If additional detection sensitivity is required for environmental studies, Bifi marker gene should be paired with either CrAssphage or HF183/BacR287 marker genes.

Molecular microbiological approaches reduce ambiguity about the sources of faecal pollution and identify microbial hazards within an urbanised coastal environment

Urbanised beaches are regularly impacted by faecal pollution, but management actions to resolve the causes of contamination are often obfuscated by the inability of standard Faecal Indicator Bacteria (FIB) analyses to discriminate sources of faecal material or detect other microbial hazards, including antibiotic resistance genes (ARGs). We aimed to determine the causes, spatial extent, and point sources of faecal contamination within Rose Bay, a highly urbanised beach within Sydney, Australia's largest city, using molecular microbiological approaches. Sampling was performed across a network of transects originating at 9 stormwater drains located on Rose Bay beach over the course of a significant (67.5 mm) rainfall event, whereby samples were taken 6 days prior to any rain, on the day of initial rainfall (3.8 mm), three days later after 43 mm of rain and then four days after any rain. Quantitative PCR (qPCR) was used to target marker genes from bacteria (i.e., Lachnospiraceae and Bacteroides) that have been demonstrated to be specific to human faeces (sewage), along with gene sequences from Heliobacter and Bacteriodes that are specific to bird and dog faeces respectively, and ARGs (sulI, tetA, qnrS, dfrA1 and vanB). 16S rRNA gene amplicon sequencing was also used to discriminate microbial signatures of faecal contamination. Prior to the rain event, low FIB levels (mean: 2.4 CFU/100 ml) were accompanied by generally low levels of the human and animal faecal markers, with the exception of one transect, potentially indicative of a dry weather sewage leak. Following 43 mm of rain, levels of both human faecal markers increased significantly in stormwater drain and seawater samples, with highest levels of these markers pinpointing several stormwater drains as sources of sewage contamination. During this time, sewage contamination was observed up to 1000 m from shore and was significantly and positively correlated with often highly elevated levels of the ARGs dfrA1, qnrS, sulI and vanB. Significantly elevated levels of the dog faecal marker in stormwater drains at this time also indicated that rainfall led to increased input of dog faecal material from the surrounding catchment. Using 16S rRNA gene amplicon sequencing, several indicator taxa for stormwater contamination such as Arcobacter spp. and Comamonadaceae spp. were identified and the Bayesian SourceTracker tool was used to model the relative impact of specific stormwater drains on the surrounding environment, revealing a heterogeneous contribution of discrete stormwater drains during different periods of the rainfall event, with the microbial signature of one particular drain contributing up to 50% of bacterial community in the seawater directly adjacent. By applying a suite of molecular microbiological approaches, we have precisely pinpointed the causes and point-sources of faecal contamination and other associated microbiological hazards (e.g., ARGs) at an urbanised beach, which has helped to identify the most suitable locations for targeted management of water quality at the beach.

An Overview of Microbial Source Tracking Using Host-Specific Genetic Markers to Identify Origins of Fecal Contamination in Different Water Environments

Fecal contamination of water constitutes a serious health risk to humans and environmental ecosystems. This is mainly due to the fact that fecal material carries a variety of enteropathogens, which can enter and circulate in water bodies through fecal pollution. In this respect, the prompt identification of the polluting source(s) is pivotal to guiding appropriate target-specific remediation actions. Notably, microbial source tracking (MST) is widely applied to determine the host origin(s) contributing to fecal water pollution through the identification of zoogenic and/or anthropogenic sources of fecal environmental DNA (eDNA). A wide array of host-associated molecular markers have been developed and exploited for polluting source attribution in various aquatic ecosystems. This review is intended to provide the most up-to-date overview of genetic marker-based MST studies carried out in different water types, such as freshwaters (including surface and groundwaters) and seawaters (from coasts, beaches, lagoons, and estuaries), as well as drinking water systems. Focusing on the latest scientific progress/achievements, this work aims to gain updated knowledge on the applicability and robustness of using MST for water quality surveillance. Moreover, it also provides a future perspective on advancing MST applications for environmental research.

Performance of NIST SRM® 2917 with 13 recreational water quality monitoring qPCR assays

Fecal pollution remains a significant challenge for recreational water quality management worldwide. In response, there is a growing interest in the use of real-time quantitative PCR (qPCR) methods to achieve same-day notification of recreational water quality and associated public health risk as well as to characterize fecal pollution sources for targeted mitigation. However, successful widespread implementation of these technologies requires the development of and access to a high-quality standard control material. Here, we report a single laboratory qPCR performance assessment of the National Institute of Standards and Technology Standard Reference Material 2917 (NIST SRM® 2917), a linearized plasmid DNA construct that functions with 13 recreational water quality qPCR assays. Performance experiments indicate the generation of standard curves with amplification efficiencies ranging from 0.95 ± 0.006 to 0.99 ± 0.008 and coefficient of determination values (R2) ≥ 0.980. Regardless of qPCR assay, variability in repeated measurements at each dilution level were very low (quantification threshold standard deviations ≤ 0.657) and exhibited a heteroscedastic trend characteristic of qPCR standard curves. The influence of a yeast carrier tRNA added to the standard control material buffer was also investigated. Findings demonstrated that NIST SRM® 2917 functions with all qPCR methods and suggests that the future use of this control material by scientists and water quality managers should help reduce variability in concentration estimates and make results more consistent between laboratories.