Wastewater surveillance provides 10-days forecasting of COVID-19 hospitalizations superior to cases and test positivity: A prediction study.

Background: The public health response to COVID-19 has shifted to reducing deaths and hospitalizations to prevent overwhelming health systems. The amount of SARS-CoV-2 RNA fragments in wastewater are known to correlate with clinical data including cases and hospital admissions for COVID-19. We developed and tested a predictive model for incident COVID-19 hospital admissions in New York State using wastewater data. Methods: Using county-level COVID-19 hospital admissions and wastewater surveillance covering 13.8 million people across 56 counties, we fit a generalized linear mixed model predicting new hospital admissions from wastewater concentrations of SARS-CoV-2 RNA from April 29, 2020 to June 30, 2022. We included covariates such as COVID-19 vaccine coverage in the county, comorbidities, demographic variables, and holiday gatherings. Findings: Wastewater concentrations of SARS-CoV-2 RNA correlated with new hospital admissions per 100,000 up to ten days prior to admission. Models that included wastewater had higher predictive power than models that included clinical cases only, increasing the accuracy of the model by 15%. Predicted hospital admissions correlated highly with observed admissions (r = 0.77) with an average difference of 0.013 hospitalizations per 100,000 (95% CI = [0.002, 0.025]). Interpretation: Using wastewater to predict future hospital admissions from COVID-19 is accurate and effective with superior results to using case data alone. The lead time of ten days could alert the public to take precautions and improve resource allocation for seasonal surges.

Wastewater Surveillance for Infectious Disease: A Systematic Review.

Wastewater surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been shown to be a valuable source of information regarding SARS-CoV-2 transmission and coronavirus disease 2019 (COVID-19) cases. Although the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens that have been surveilled through wastewater. Herein we identify the infectious diseases that have been previously studied via wastewater surveillance prior to the COVID-19 pandemic. Infectious diseases and pathogens were identified in 100 studies of wastewater surveillance across 38 countries, as were themes of how wastewater surveillance and other measures of disease transmission were linked. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and nonpolio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did, the value reported varied by study. Wastewater surveillance should be considered as a potential public health tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917.

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

High Sensitivity and Specificity of Dormitory-Level Wastewater Surveillance for COVID-19 during Fall Semester 2020 at Syracuse University, New York.

A residential building's wastewater presents a potential non-invasive method of surveilling numerous infectious diseases, including SARS-CoV-2. We analyzed wastewater from 16 different residential locations at Syracuse University (Syracuse, NY, USA) during fall semester 2020, testing for SARS-CoV-2 RNA twice weekly and compared the presence of clinical COVID-19 cases to detection of the viral RNA in wastewater. The sensitivity of wastewater surveillance to correctly identify dormitories with a case of COVID-19 ranged from 95% (95% confidence interval [CI] = 76-100%) on the same day as the case was diagnosed to 73% (95% CI = 53-92%), with 7 days lead time of wastewater. The positive predictive value ranged from 20% (95% CI = 13-30%) on the same day as the case was diagnosed to 50% (95% CI = 40-60%) with 7 days lead time. The specificity of wastewater surveillance to correctly identify dormitories without a case of COVID-19 ranged from 60% (95% CI = 52-67%) on the day of the wastewater sample to 67% (95% CI = 58-74%) with 7 days lead time. The negative predictive value ranged from 99% (95% CI = 95-100%) on the day of the wastewater sample to 84% (95% CI = 77-91%) with 7 days lead time. Wastewater surveillance for SARS-CoV-2 at the building level is highly accurate in determining if residents have a COVID-19 infection. Particular benefit is derived from negative wastewater results that can confirm a building is COVID-19 free.

Comparability of 24-hour composite and grab samples for detection of SARS-2-CoV RNA in wastewater.

Wastewater surveillance is a cost-effective way to monitor pathogen prevalence and transmission patterns in the entire community. Here, we compare 24-hour composite and grab samples collected during September 2020 from several municipalities in New York State to detect SARS-CoV-2. A total of 45 paired samples (90 total samples) from three counties and 14 wastewater treatment plants were available for analysis. The categorical comparison (SARS-CoV-2 genetic material detected and quantifiable, genetic material detected but below the limits of quantification, and genetic material not detected) between the grab and composite samples was quite strong, with 91.1% agreement (kappa P-value < .001). The correlations among the quantifiable grab and composite samples were statistically significant yet modest for SARS2-CoV RNA (Pearson correlation = 0.44, P = .02), crAssphage cDNA (Pearson correlation = 0.36, P = .02), and crAssphage DNA (Pearson correlation = 0.46, P = .002). We found good comparison between grab and 24-hour composite samples for detecting SARS-CoV-2 RNA from municipal wastewater treatment plants. Grab sampling is an efficient and cost-effective method to monitor for the presence of SARS-CoV-2 in the entire community.

Stable, high-rate anaerobic digestion through vacuum stripping of digestate.

This study coupled anaerobic digestion with vacuum stripping to achieve stable digestion at higher organic loading rates. Besides mitigation of ammonia inhibition, vacuum stripping of digestate improves solids solubilization and dewaterability due to vacuum-enhanced low-temperature thermal and mild-alkaline treatment under the vacuum stripping conditions (65 °C, 25-27 kPa, and pH 9). Batch vacuum stripping for 8 h removed 97.4-99.4% of ammonia, increased the dissolved fraction of volatile solids (VS) by 72.5%, and improved dewaterability with 30% decreases in time-to-filter and viscosity. The digesters having 2.9% of digestate replaced daily by vacuum stripped digestate were stable up to organic loading rate of 4.3 g-VS/Lreactor/d with biogas production at 3.15 L/Lreactor/d, while the digesters without stripping attained biogas production of 1.90 L/Lreactor/d at its highest stable organic loading rate of 2.5 g-VS/Lreactor/d. Acetoclastic Methanosaeta were the dominant methanogens, which became more resistant to ammonia stress in the digesters with vacuum stripping.

Coupling freedom from disease principles and early warning from wastewater surveillance to improve health security.

Infectious disease surveillance is vitally important to maintaining health security, but these efforts are challenged by the pace at which new pathogens emerge. Wastewater surveillance can rapidly obtain population-level estimates of disease transmission, and we leverage freedom from disease principles to make use of nondetection of SARS-CoV-2 in wastewater to estimate the probability that a community is free from SARS-CoV-2 transmission. From wastewater surveillance of 24 treatment plants across upstate New York from May through December of 2020, trends in the intensity of SARS-CoV-2 in wastewater correlate with trends in COVID-19 incidence and test positivity (⍴ > 0.5), with the greatest correlation observed for active cases and a 3-day lead time between wastewater sample date and clinical test date. No COVID-19 cases were reported 35% of the time the week of a nondetection of SARS-CoV-2 in wastewater. Compared to the United States Centers for Disease Control and Prevention levels of transmission risk, transmission risk was low (no community spared) 50% of the time following nondetection, and transmission risk was moderate or lower (low community spread) 92% of the time following nondetection. Wastewater surveillance can demonstrate the geographic extent of the transmission of emerging pathogens, confirming that transmission risk is either absent or low and alerting of an increase in transmission. If a statewide wastewater surveillance platform had been in place prior to the onset of the COVID-19 pandemic, policymakers would have been able to complement the representative nature of wastewater samples to individual testing, likely resulting in more precise public health interventions and policies.

Wastewater monitoring, surveillance and epidemiology: a review of terminology for a common understanding.

Response to the COVID-19 (coronavirus disease 2019) pandemic saw an unprecedented uptake in bottom-up efforts to incorporate community wastewater testing to inform public health. While not a new strategy, various specialized scientific advancements were achieved to establish links between wastewater concentrations of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and public health outcomes. Maximizing public health benefit requires collaboration among a broad range of disciplinary experts, each bringing their own historical context to the central goal of protecting human health. One challenge has been a lack of shared terminology. Standardized terminology would provide common ground for this rapidly growing field. Based on the review herein, we recommend categorical usage of the term 'wastewater-based epidemiology' to describe the science of relating microbes, chemicals or other analytes in wastewater to public health. We further recommend the term 'wastewater surveillance' to describe continuous monitoring of health outcomes (either microbes or chemicals) via wastewater. We suggest that 'wastewater tracking' and 'wastewater tracing' be used in more narrow ways, specifically when trying to find the source of a health risk. Finally, we suggest that the phrase 'wastewater monitoring' be abandoned, except in rare circumstances when ensuring wastewater discharge is safe from a public health perspective.

Integrative Survey of 68 Non-overlapping Upstate New York Watersheds Reveals Stream Features Associated With Aquatic Fecal Contamination.

Aquatic fecal contamination poses human health risks by introducing pathogens in water that may be used for recreation, consumption, or agriculture. Identifying fecal contaminant sources, as well as the factors that affect their transport, storage, and decay, is essential for protecting human health. However, identifying these factors is often difficult when using fecal indicator bacteria (FIB) because FIB levels in surface water are often the product of multiple contaminant sources. In contrast, microbial source-tracking (MST) techniques allow not only the identification of predominant contaminant sources but also the quantification of factors affecting the transport, storage, and decay of fecal contaminants from specific hosts. We visited 68 streams in the Finger Lakes region of Upstate New York, United States, between April and October 2018 and collected water quality data (i.e., Escherichia coli, MST markers, and physical-chemical parameters) and weather and land-use data, as well as data on other stream features (e.g., stream bed composition), to identify factors that were associated with fecal contamination at a regional scale. We then applied both generalized linear mixed models and conditional inference trees to identify factors and combinations of factors that were significantly associated with human and ruminant fecal contamination. We found that human contaminants were more likely to be identified when the developed area within the 60 m stream buffer exceeded 3.4%, the total developed area in the watershed exceeded 41%, or if stormwater outfalls were present immediately upstream of the sampling site. When these features were not present, human MST markers were more likely to be found when rainfall during the preceding day exceeded 1.5 cm. The presence of upstream campgrounds was also significantly associated with human MST marker detection. In addition to rainfall and water quality parameters associated with rainfall (e.g., turbidity), the minimum distance to upstream cattle operations, the proportion of the 60 m buffer used for cropland, and the presence of submerged aquatic vegetation at the sampling site were all associated based on univariable regression with elevated levels of ruminant markers. The identification of specific features associated with host-specific fecal contaminants may support the development of broader recommendations or policies aimed at reducing levels of aquatic fecal contamination.

Co-quantification of crAssphage increases confidence in wastewater-based epidemiology for SARS-CoV-2 in low prevalence areas.

Wastewater surveillance of SARS-CoV-2 RNA is increasingly being incorporated into public health efforts to respond to the COVID-19 pandemic. In order to obtain the maximum benefit from these efforts, approaches to wastewater monitoring need to be rapid, sensitive, and relatable to relevant epidemiological parameters. In this study, we present an ultracentrifugation-based method for the concentration of SARS-CoV-2 wastewater RNA and use crAssphage, a bacteriophage specific to the human gut, to help account for RNA loss during transit in the wastewater system and sample processing. With these methods, we were able to detect, and sometimes quantify, SARS-CoV-2 RNA from 20 mL wastewater samples within as little as 4.5 hours. Using known concentrations of bovine coronavirus RNA and deactivated SARS-CoV-2, we estimate recovery rates of approximately 7-12% of viral RNA using our method. Results from 24 sewersheds across Upstate New York during the spring and summer of 2020 suggested that stronger signals of SARS-CoV-2 RNA from wastewater may be indicative of greater COVID-19 incidence in the represented service area approximately one week in advance. SARS-CoV-2 wastewater RNA was quantifiable in some service areas with daily positives tests of less than 1 per 10,000 people or when weekly positive test rates within a sewershed were as low as 1.7%. crAssphage DNA concentrations were significantly lower during periods of high flow in almost all areas studied. After accounting for flow rate and population served, crAssphage levels per capita were estimated to be about 1.35 × 1011 and 2.42 × 108 genome copies per day for DNA and RNA, respectively. A negative relationship between per capita crAssphage RNA and service area size was also observed likely reflecting degradation of RNA over long transit times. Our results reinforce the potential for wastewater surveillance to be used as a tool to supplement understanding of infectious disease transmission obtained by traditional testing and highlight the potential for crAssphage co-detection to improve interpretations of wastewater surveillance data.

High-throughput wastewater analysis for substance use assessment in central New York during the COVID-19 pandemic.

Wastewater entering sewer networks represents a unique source of pooled epidemiological information. In this study, we coupled online solid-phase extraction with liquid chromatography-high resolution mass spectrometry to achieve high-throughput analysis of health and lifestyle-related substances in untreated municipal wastewater during the coronavirus disease 2019 (COVID-19) pandemic. Twenty-six substances were identified and quantified in influent samples collected from six wastewater treatment plants during the COVID-19 pandemic in central New York. Over a 12 week sampling period, the mean summed consumption rate of six major substance groups (i.e., antidepressants, antiepileptics, antihistamines, antihypertensives, synthetic opioids, and central nervous system stimulants) correlated with disparities in household income, marital status, and age of the contributing populations as well as the detection frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater and the COVID-19 test positivity in the studied sewersheds. Nontarget screening revealed the covariation of piperine, a nontarget substance, with SARS-CoV-2 RNA in wastewater collected from one of the sewersheds. Overall, this proof-of-the-concept study demonstrated the utility of high-throughput wastewater analysis for assessing the population-level substance use patterns during a public health crisis such as COVID-19.

Landscape, Water Quality, and Weather Factors Associated With an Increased Likelihood of Foodborne Pathogen Contamination of New York Streams Used to Source Water for Produce Production.

There is a need for science-based tools to (i) help manage microbial produce safety hazards associated with preharvest surface water use, and (ii) facilitate comanagement of agroecosystems for competing stakeholder aims. To develop these tools an improved understanding of foodborne pathogen ecology in freshwater systems is needed. The purpose of this study was to identify (i) sources of potential food safety hazards, and (ii) combinations of factors associated with an increased likelihood of pathogen contamination of agricultural water Sixty-eight streams were sampled between April and October 2018 (196 samples). At each sampling event separate 10-L grab samples (GS) were collected and tested for Listeria, Salmonella, and the stx and eaeA genes. A 1-L GS was also collected and used for Escherichia coli enumeration and detection of four host-associated fecal source-tracking markers (FST). Regression analysis was used to identify individual factors that were significantly associated with pathogen detection. We found that eaeA-stx codetection [Odds Ratio (OR) = 4.2; 95% Confidence Interval (CI) = 1.3, 13.4] and Salmonella isolation (OR = 1.8; CI = 0.9, 3.5) were strongly associated with detection of ruminant and human FST markers, respectively, while Listeria spp. (excluding Listeria monocytogenes) was negatively associated with log10 E. coli levels (OR = 0.50; CI = 0.26, 0.96). L. monocytogenes isolation was not associated with the detection of any fecal indicators. This observation supports the current understanding that, unlike enteric pathogens, Listeria is not fecally-associated and instead originates from other environmental sources. Separately, conditional inference trees were used to identify scenarios associated with an elevated or reduced risk of pathogen contamination. Interestingly, while the likelihood of isolating L. monocytogenes appears to be driven by complex interactions between environmental factors, the likelihood of Salmonella isolation and eaeA-stx codetection were driven by physicochemical water quality (e.g., dissolved oxygen) and temperature, respectively. Overall, these models identify environmental conditions associated with an enhanced risk of pathogen presence in agricultural water (e.g., rain events were associated with L. monocytogenes isolation from samples collected downstream of dairy farms; P = 0.002). The information presented here will enable growers to comanage their operations to mitigate the produce safety risks associated with preharvest surface water use.

Reversibility of propionic acid inhibition to anaerobic digestion: Inhibition kinetics and microbial mechanism.

Anaerobic digestion is a technology that simultaneously treats waste and generates energy in the form of biogas. Unfortunately, when a high organic loading rate is applied, anaerobic digestion can suffer from volatile fatty acid accumulation that results in pH drop and decreased biogas production. In particular, propionic acid has shown to inhibit biogas production even at a very low concentration. Therefore, the kinetics of biogas production in relation to propionic acid concentration needs to be investigated. In batch experiments on anaerobic co-digestion of food waste and dairy manure in the present study, cumulative biogas production showed little inhibition by propionic acid in the concentration range of 6.5-14.6 mM, but a lag phase of 9.4, 16.3 and 60.8 d was detected in the digesters with initial propionic acid concentrations of 22.7, 36.2, and 56.4 mM, respectively. After the lag phase, these digesters accelerated to specific biogas yields of 0.59-0.70 L g-VS-1. The similar specific biogas yields across all of the digesters at initial propionic acid concentrations of 6.5-56.4 mM indicated reversibility of the inhibition. The reversibility was made possible by microbial acclimation and the shift to hydrogenotrophic methanogenesis in syntrophy with acetogenic bacteria. Evidently, an increase of hydrogenotrophic Methanobacterium and Methanoculleus abundances was found at 36.2 and 56.4 mM. Batch digestion experiments must be extended beyond the lag phase in order to fully reveal the inhibition kinetics. This paper highlights the need for a standard protocol that experimentally evaluates inhibition in anaerobic digestion.

Development and validation of rapid environmental DNA (eDNA) detection methods for bog turtle (Glyptemys muhlenbergii).

Bog turtles (Glyptemys muhlenbergii) are listed as Species of Greatest Conservation Need (SGCN) for wildlife action plans in every state it occurs and multi-state efforts are underway to better characterize extant populations and prioritize restoration efforts. However, traditional sampling methods can be ineffective due to the turtle's wetland habitat, small size, and burrowing nature. Molecular methods, such as qPCR, provide the ability to overcome this challenge by effectively quantifying minute amounts of turtle DNA left behind in its environment (eDNA). Developing such methods for bog turtles has proved difficult partly because of the high sequence similarity between bog turtles and closely-related, cohabitating species, most often wood turtles (Glyptemys insculpta). Additionally, substrates containing bog turtle eDNA are often rich in organics or other substances that frequently inhibit both DNA extraction and qPCR amplification. Here, we describe the development and validation of a qPCR assay, BT3, targeting the mitochondrial cytochrome oxidase I gene that correctly identifies bog turtles with 100% specificity and sensitivity when tested on 201 blood samples collected from six species over a wide geographic range. We also developed a full-process internal control employing a genetically modified strain of Caenorhabditis elegans to improve DNA extraction methods, limit false negative results due to qPCR inhibition, and measure total DNA recovery from each sample. Using the internal control, we found that DNA recovery varied by over an order of magnitude between samples and likely explains the lack of bog turtle detection in some cases. Methods presented herein are highly-specific and may offer a more cost effective, non-invasive tool to supplement bog turtle population assessments in the Eastern United States. Poor or differential DNA recovery, which remains unmeasured in the vast majority of eDNA studies, significantly reduced the ability to detect bog turtle in their natural environment.

Microbial Source-Tracking Reveals Origins of Fecal Contamination in a Recovering Watershed.

Fecal contamination of waterbodies due to poorly managed human and animal waste is a pervasive problem that can be particularly costly to address, especially if mitigation strategies are ineffective at sufficiently reducing the level of contamination. Identifying the most worrisome sources of contamination is particularly difficult in periurban streams with multiple land uses and requires the distinction of municipal, agricultural, domestic pet, and natural (i.e., wildlife) wastes. Microbial source-tracking (MST) methods that target host-specific members of the bacterial order Bacteroidales and others have been used worldwide to identify the origins of fecal contamination. We conducted a dry-weather study of Onondaga Creek, NY, where reducing fecal contamination has been approached mainly by mitigating combined sewer overflow events (CSOs). Over three sampling dates, we measured in-stream concentrations of fecal indicator bacteria; MST markers targeting human, ruminant, and canine sources; and various physical-chemical parameters to identify contaminants not attributable to CSOs or stormwater runoff. We observed that despite significant ruminant inputs upstream, these contaminants eventually decayed and/or were diluted out and that high levels of urban bacterial contamination are most likely due to failing infrastructure and/or illicit discharges independent of rain events. Similar dynamics may control other streams that transition from agricultural to urban areas with failing infrastructure.

Identification of Specialists and Abundance-Occupancy Relationships among Intestinal Bacteria of Aves, Mammalia, and Actinopterygii.

The coalescence of next-generation DNA sequencing methods, ecological perspectives, and bioinformatics analysis tools is rapidly advancing our understanding of the evolution and function of vertebrate-associated bacterial communities. Delineation of host-microbe associations has applied benefits ranging from clinical treatments to protecting our natural waters. Microbial communities follow some broad-scale patterns observed for macroorganisms, but it remains unclear how the specialization of intestinal vertebrate-associated communities to a particular host environment influences broad-scale patterns in microbial abundance and distribution. We analyzed the V6 region of 16S rRNA genes amplified from 106 fecal samples spanning Aves, Mammalia, and Actinopterygii (ray-finned fish). We investigated the interspecific abundance-occupancy relationship, where widespread taxa tend to be more abundant than narrowly distributed taxa, among operational taxonomic units (OTUs) within and among host species. In a separate analysis, we identified specialist OTUs that were highly abundant in a single host and rare in all other hosts by using a multinomial model without excluding undersampled OTUs a priori. We show that intestinal microbes in humans and other vertebrates display abundance-occupancy relationships, but because intestinal host-associated communities have undergone intense specialization, this trend is violated by a disproportionately large number of specialist taxa. Although it is difficult to distinguish the effects of dispersal limitations, host selection, historical contingency, and stochastic processes on community assembly, results suggest that intestinal bacteria can be shared among diverse hosts in ways that resemble the distribution of "free-living" bacteria in the extraintestinal environment.

Comparison of Sewage and Animal Fecal Microbiomes by Using Oligotyping Reveals Potential Human Fecal Indicators in Multiple Taxonomic Groups.

Most DNA-based microbial source tracking (MST) approaches target host-associated organisms within the order Bacteroidales, but the gut microbiota of humans and other animals contain organisms from an array of other taxonomic groups that might provide indicators of fecal pollution sources. To discern between human and nonhuman fecal sources, we compared the V6 regions of the 16S rRNA genes detected in fecal samples from six animal hosts to those found in sewage (as a proxy for humans). We focused on 10 abundant genera and used oligotyping, which can detect subtle differences between rRNA gene sequences from ecologically distinct organisms. Our analysis showed clear patterns of differential oligotype distributions between sewage and animal samples. Over 100 oligotypes of human origin occurred preferentially in sewage samples, and 99 human oligotypes were sewage specific. Sequences represented by the sewage-specific oligotypes can be used individually for development of PCR-based assays or together with the oligotypes preferentially associated with sewage to implement a signature-based approach. Analysis of sewage from Spain and Brazil showed that the sewage-specific oligotypes identified in U.S. sewage have the potential to be used as global alternative indicators of human fecal pollution. Environmental samples with evidence of prior human fecal contamination had consistent ratios of sewage signature oligotypes that corresponded to the trends observed for sewage. Our methodology represents a promising approach to identifying new bacterial taxa for MST applications and further highlights the potential of the family Lachnospiraceae to provide human-specific markers. In addition to source tracking applications, the patterns of the fine-scale population structure within fecal taxa suggest a fundamental relationship between bacteria and their hosts.

Development of rapid canine fecal source identification PCR-based assays.

The extent to which dogs contribute to aquatic fecal contamination is unknown despite the potential for zoonotic transfer of harmful human pathogens. We used genome fragment enrichment (GFE) to identify novel nonribosomal microbial genetic markers potentially useful for detecting dog fecal contamination with PCR-based methods in environmental samples. Of the 679 sequences obtained from GFE, we used 84 for the development of PCR assays targeting putative canine-associated genetic markers. Twelve genetic markers were shown to be prevalent among dog fecal samples and were rarely found in other animals. Three assays, DG3, DG37, and DG72, performed best in terms of specificity and sensitivity and were used for the development of SYBR Green and TaqMan quantitative PCR (qPCR) assays. qPCR analysis of 244 fecal samples collected from a wide geographic range indicated that marker concentrations were below limits of detection in noncanine hosts. As a proof-of-concept, these markers were detected in urban stormwater samples, suggesting a future application of newly developed methods for water quality monitoring.

Improved HF183 quantitative real-time PCR assay for characterization of human fecal pollution in ambient surface water samples.

Quantitative real-time PCR (qPCR) assays that target the human-associated HF183 bacterial cluster within members of the genus Bacteroides are among the most widely used methods for the characterization of human fecal pollution in ambient surface waters. In this study, we show that a current TaqMan HF183 qPCR assay (HF183/BFDrev) routinely forms nonspecific amplification products and introduce a modified TaqMan assay (HF183/BacR287) that alleviates this problem. The performance of each qPCR assay was compared in head-to-head experiments investigating limits of detection, analytical precision, predicted hybridization to 16S rRNA gene sequences from a reference database, and relative marker concentrations in fecal and sewage samples. The performance of the modified HF183/BacR287 assay is equal to or improves upon that of the original HF183/BFDrev assay. In addition, a qPCR chemistry designed to combat amplification inhibition and a multiplexed internal amplification control are included. In light of the expanding use of PCR-based methods that rely on the detection of extremely low concentrations of DNA template, such as qPCR and digital PCR, the new TaqMan HF183/BacR287 assay should provide more accurate estimations of human-derived fecal contaminants in ambient surface waters.

Enterococcus and Escherichia coli fecal source apportionment with microbial source tracking genetic markers--is it feasible?

Fecal pollution is measured in surface waters using culture-based measurements of enterococci and Escherichia coli bacteria. Source apportionment of these two fecal indicator bacteria is an urgent need for prioritizing remediation efforts and quantifying health risks associated with source-specific pathogens. There are a number of quantitative real-time PCR (QPCR) assays that estimate concentrations of source-associated genetic markers; however, their concentrations are not necessarily amenable to source apportionment because the markers may differ in prevalence across sources. Here we mathematically derive and test, under ideal conditions, a method that utilizes the ratios of fecal source-associated genetic markers and culture and molecular measurements of general fecal indicators to apportion enterococci and E. coli. The source contribution is approximately equal to the ratio of the source-associated and the general fecal indicator concentrations in a water sample divided by their ratio in the source material, so long as cross-reactivity is negligible. We illustrate the utility of the ratio method using samples consisting of mixtures of various fecal pollution sources. The results from the ratio method correlated well with the actual source apportionment in artificial samples. However, aging of contamination can confound source allocation predictions. In particular, culturable enterococci and E. coli, the organisms presently regulated in the United States and much of the world, decay at different rates compared to source-associated markers and as a result cannot be apportioned using this method. However, limited data suggest a similar decay rate between source-associated and QPCR-measured Enterococcus and E. coli genetic markers, indicating that apportionment may be possible for these organisms; however further work is needed to confirm.