The Development of a Novel qPCR Assay-Set for Identifying Fecal Contamination Originating from Domestic Fowls and Waterfowl in Israel

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

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

Comparative Analysis of Fecal Microbiomes From Wild Waterbirds to Poultry, Cattle, Pigs, and Wastewater Treatment Plants for a Microbial Source Tracking Approach

Fecal pollution in coastal areas is of a high concern since it affects bathing and shellfish harvesting activities. Wild waterbirds are non-negligible in the overall signal of the detectable pollution. Yet, studies on wild waterbirds’ gut microbiota focus on migratory trajectories and feeding impact on their shape, rare studies address their comparison to other sources and develop quantitative PCR (qPCR)-based Microbial Source Tracking (MST) markers to detect such pollution. Thus, by using 16S rRNA amplicon high-throughput sequencing, the aims of this study were (i) to explore and compare fecal bacterial communities from wild waterbirds (i.e., six families and 15 species, n = 275 samples) to that of poultry, cattle, pigs, and influent/effluent of wastewater treatment plants (n = 150 samples) and (ii) to develop new MST markers for waterbirds. Significant differences were observed between wild waterbirds and the four other groups. We identified 7,349 Amplicon Sequence Variants (ASVs) from the hypervariable V3–V4 region. Firmicutes and Proteobacteria and, in a lesser extent, Actinobacteria and Bacteroidetes were ubiquitous while Fusobacteria and Epsilonbacteraeota were mainly present in wild waterbirds. The clustering of samples in non-metric multidimensional scaling (NMDS) ordination indicated a by-group clustering shape, with a high diversity within wild waterbirds. In addition, the structure of the bacterial communities was distinct according to bird and/or animal species and families (Adonis R² = 0.13, p = 10^–4, Adonis R² = 0.11, p = 10^–4, respectively). The Analysis of Composition of Microbiomes (ANCOM) showed that the wild waterbird group differed from the others by the significant presence of sequences from Fusobacteriaceae (W = 566) and Enterococcaceae (W = 565) families, corresponding to the Cetobacterium (W = 1427) and Catellicoccus (W = 1427) genera, respectively. Altogether, our results suggest that some waterbird members present distinct fecal microbiomes allowing the design of qPCR MST markers. For instance, a swan- and an oystercatcher-associated markers (named Swan_2 and Oyscab, respectively) have been developed. Moreover, bacterial genera harboring potential human pathogens associated to bird droppings were detected in our dataset, including enteric pathogens, i.e., Arcobacter, Clostridium, Helicobacter, and Campylobacter, and environmental pathogens, i.e., Burkholderia and Pseudomonas. Future studies involving other wildlife hosts may improve gut microbiome studies and MST marker development, helping mitigation of yet unknown fecal pollution sources.

Synergistic Application of Molecular Markers and Community-Based Microbial Source Tracking Methods for Identification of Fecal Pollution in River Water During Dry and Wet Seasons

It is important to track fecal sources from humans and animals that negatively influence the water quality of rural rivers and human health. In this study, microbial source tracking (MST) methods using molecular markers and the community-based FEAST (fast expectation–maximization microbial source tracking) program were synergistically applied to distinguish the fecal contributions of multiple sources in a rural river located in Beijing, China. The performance of eight markers were evaluated using 133 fecal samples based on real-time quantitative (qPCR) technique. Among them, six markers, including universal (BacUni), human-associated (HF183-1 and BacH), swine-associated (Pig-2-Bac), ruminant-associated (Rum-2-Bac), and avian-associated (AV4143) markers, performed well in the study. A total of 96 water samples from the river and outfalls showed a coordinated composition of fecal pollution, which revealed that outfall water might be a potential input of the Fsq River. In the FEAST program, bacterial 16S rRNA genes of 58 fecal and 12 water samples were sequenced to build the “source” library and “sink,” respectively. The relative contribution (<4.01% of sequence reads) of each source (i.e., human, swine, bovine, or sheep) was calculated based on simultaneous screening of the operational taxonomic units (OTUs) of sources and sinks, which indicated that community-based MST methods could be promising tools for identifying fecal sources from a more comprehensive perspective. Results of the qPCR assays indicated that fecal contamination from human was dominant during dry weather and that fecal sources from swine and ruminant were more prevalent in samples during the wet season than in those during the dry season, which were consistent with the findings predicted by the FEAST program using a very small sample size. Information from the study could be valuable for the development of improved regulation policies to reduce the levels of fecal contamination in rural rivers.

The Use of Ribosomal RNA as a Microbial Source Tracking Target Highlights the Assay Host-Specificity Requirement in Water Quality Assessments

For microbial source tracking (MST), the 16S ribosomal RNA genes (rDNA) of host-specific bacteria and mitochondrial DNA (mtDNA) of animal species, known to cause fecal contamination of water, have been commonly used as molecular targets. However, low levels of contamination might remain undetected by using these DNA-based qPCR assays. The high copy numbers of ribosomal RNA (rRNA) could offer a solution for such applications of MST. This study compared the performance of eight MST assays: GenBac3 (general Bacteroidales), HF183 (human), BacCan (dog), Rum-2-Bac (ruminant), Pig-2-Bac (swine), Gull4 (gull), GFD, and Av4143 (birds) between rRNA-based and rDNA-based approaches. Three mtDNA-based approaches were tested: DogND5, SheepCytB, and HorseCytB. A total of 151 animal fecal samples and eight municipal sewage samples from four regions of Finland were collected for the marker evaluation. The usability of these markers was tested by using a total of 95 surface water samples with an unknown pollution load. Overall, the performance (specificity, sensitivity, and accuracy) of mtDNA-based assays was excellent (95–100%), but these markers were very seldom detected from the tested surface water samples. The rRNA template increased the sensitivity of assays in comparison to the rDNA template. All rRNA-based assays (except Av4143) had more than 80% sensitivity. In contrast, only half (HF183, Rum-2-Bac, Pig-2-Bac, and Gull4) of rDNA-based assays reached this value. For markers targeted to bird feces, the use of the rRNA-based assay increased or at least did not change the performance. Regarding specificity, all the assays had >95% specificity with a DNA template, except the BacCan assay (71%). While using the RNA template for the assays, HF183 and BacCan exhibited only a low level of specificity (54 and 55%, respectively). Further, the HF183 assay amplified from multiple non-targeted animal fecal samples with the RNA template and the marker showed cross-amplification with the DNA template as well. This study recommends using the rRNA-based approach for MST assays targeting bird fecal contamination. In the case of mammal-specific MST assays, the use of the rRNA template increases the sensitivity but may reduce the specificity and accuracy of the assay. The finding of increased sensitivity calls for a further need to develop better rRNA-based approaches to reach the required assay performance.

Associations among Household Animal Ownership, Infrastructure, and Hygiene Characteristics with Source Attribution of Household Fecal Contamination in Peri-Urban Communities of Iquitos, Peru

Using previously validated microbial source tracking markers, we detected and quantified fecal contamination from avian species and avian exposure, dogs, and humans on household cooking tables and floors. The association among contamination, infrastructure, and socioeconomic covariates was assessed using simple and multiple ordinal logistic regressions. The presence of Campylobacter spp. in surface samples was linked to avian markers. Using molecular methods, animal feces were detected in 75.0% and human feces in 20.2% of 104 households. Floors were more contaminated than tables as detected by the avian marker Av4143, dog marker Bactcan, and human marker Bachum. Wood tables were consistently more contaminated than non-wood surfaces, specifically with the mitochondrial avian markers ND5 and CytB, fecal marker Av4143, and canine marker Bactcan. Final multivariable models with socioeconomic and infrastructure characteristics included as covariates indicate that detection of avian feces and avian exposure was associated with the presence of chickens, maternal age, and length of tenancy, whereas detection of human markers was associated with unimproved water source. Detection of Campylobacter in surface samples was associated with the avian fecal marker Av4143. We highlight the critical need to detect and measure the burden of animal fecal waste when evaluating household water, hygiene, and sanitation interventions, and the possibility of decreasing risk of exposure through the modification of surfaces to permit more effective household disinfection practices. Animals may be a more important source of household fecal contamination than humans in many low-resource settings, although interventions have historically focused almost exclusively on managing human waste.

Metagenomic Sequencing and Quantitative Real-Time PCR for Fecal Pollution Assessment in an Urban Watershed

Microbial contamination of recreation waters is a major concern globally, with pollutants originating from many sources, including human and other animal wastes often introduced during storm events. Fecal contamination is traditionally monitored by employing culture methods targeting fecal indicator bacteria (FIB), namely E. coli and enterococci, which provides only limited information of a few microbial taxa and no information on their sources. Host-associated qPCR and metagenomic DNA sequencing are complementary methods for FIB monitoring that can provide enhanced understanding of microbial communities and sources of fecal pollution. Whole metagenome sequencing (WMS), quantitative real-time PCR (qPCR), and culture-based FIB tests were performed in an urban watershed before and after a rainfall event to determine the feasibility and application of employing a multi-assay approach for examining microbial content of ambient source waters. Cultivated E. coli and enterococci enumeration confirmed presence of fecal contamination in all samples exceeding local single sample recreational water quality thresholds (E. coli, 410 MPN/100 mL; enterococci, 107 MPN/100 mL) following a rainfall. Test results obtained with qPCR showed concentrations of E. coli, enterococci, and human-associated genetic markers increased after rainfall by 1.52-, 1.26-, and 1.11-fold log₁₀ copies per 100 mL, respectively. Taxonomic analysis of the surface water microbiome and detection of antibiotic resistance genes, general FIB, and human-associated microorganisms were also employed. Results showed that fecal contamination from multiple sources (human, avian, dog, and ruminant), as well as FIB, enteric microorganisms, and antibiotic resistance genes increased demonstrably after a storm event. In summary, the addition of qPCR and WMS to traditional surrogate techniques may provide enhanced characterization and improved understanding of microbial pollution sources in ambient waters.

Validation of microbial source tracking markers for the attribution of fecal contamination in indoor-household environments of the Peruvian Amazon

The performance of eight microbial source tracking (MST) markers was evaluated in a low-resource, tropical community located in Iquitos, Peru. Fecal samples from humans, dogs, cats, rats, goats, buffalos, guinea-pigs, chickens, ducks, pigeons, and parrots were collected (n = 117). All samples were tested with human (BacHum, HF183-Taqman), dog (BactCan), pig (Pig-2-Bac), and avian (LA35, Av4143, ND5, cytB) markers using quantitative PCR (qPCR). Internal validity metrics were calculated using all animal fecal samples, as well as animal fecal samples contextually relevant for the Peruvian Amazon. Overall, Pig-2-Bac performed best, with 100% sensitivity and 88.5% specificity to detect the correct fecal source. Human-associated markers showed a sensitivity of 80.0% and 76.7%, and specificity of 66.2% and 67.6%. When limiting the analysis to contextually relevant animal fecal samples for the Peruvian Amazon, Av143 surpassed cytB with 95.7% sensitivity and 81.8% specificity. BactCan demonstrated 100% sensitivity and 47.4% specificity. The gene copy number detected by BacHum and HF183-Taqman were positively correlated (Pearson's correlation coefficient: 0.785), as well as avian markers cytB with Av4143 (Pearson's correlation coefficient: 0.508) and nd5 (Pearson's correlation coefficient: 0.949). These findings suggest that markers such as Av4143, Pig2Bac, cytb and BacHum have acceptable performance to be impactful in source attribution studies for zoonotic enteric disease transmission in this and similar low-resource communities.

Uneven genotypic diversity of Escherichia coli in fecal sources limits the performance of a library-dependent method of microbial source tracking on the southwestern French Atlantic coast

To develop a library-dependent method of tracking fecal sources of contamination of beaches on the Atlantic coast of southwestern France, a library of 6368 Escherichia coli isolates was constructed from samples of feces, from 40 known human or animal sources collected in the vicinity of Arcachon Bay in 2010, and in French Basque Country, Landes, and Béarn, between 2017 and 2018. Different schemes of source identification were tested: use of the complete or filtered reference library; characterization of the isolates by genotypic or proteomic profiling based on ERIC-PCR or MALDI-TOF mass spectrometry, respectively; isolate by isolate assignment using either classifiers based on the Pearson similarity or SVM (support vector machine). With the exception of one source identification scheme, which was discarded since it used self-assignment, all tested schemes resulted in low rates of correct classification (<35%) and significant rates of incorrect classification (>15%). The heterogeneous coverage of E. coli genotypic diversity between sources and the uneven distribution of E. coli genotypes in the library likely explain the difficulties encountered in identifying the sources of fecal contamination. Shannon diversity index of sources ranged from 0 for several wildlife species sampled once to 3.03 for sewage treatment plant effluents sampled on various occasions, showing discrepancies between sources. The uneven genotypic composition of the library was attested by the value of the Pielou index (0.54), the high proportion of nondiscriminatory genotypes (>91% of the isolates), and the very low proportion of discriminatory genotypes (<3%). Since efforts made to constitute such a library are not affordable for routine analyses, the results question the relevance of developing such a method for identifying sources of fecal contamination on such a coastline.

Quantification of Microbial Source Tracking and Pathogenic Bacterial Markers in Water and Sediments of Tiaoxi River (Taihu Watershed)

Taihu Lake is one of the largest freshwater lakes in China, serving as an important source of drinking water; >60% of source water to this lake is provided by the Tiaoxi River. This river faces serious fecal contamination issues, and therefore, a comprehensive investigation to identify the sources of fecal contamination was carried out and is presented here. The performance of existing universal (BacUni and GenBac), human (HF183-Taqman, HF183-SYBR, BacHum, and Hum2), swine (Pig-2-Bac), ruminant (BacCow), and avian (AV4143 and GFD) associated microbial source tracking (MST) markers was evaluated prior to their application in this region. The specificity and sensitivity results indicated that BacUni, HF183-TaqMan, Pig-2-Bac, and GFD assays are the most suitable in identifying human and animal fecal contamination. Therefore, these markers along with marker genes specific to selected bacterial pathogens were quantified in water and sediment samples of the Tiaoxi River, collected from 15 locations over three seasons during 2014 and 2015. Total/universal Bacteroidales markers were detected in all water and sediment samples (mean concentration 6.22 log10 gene copies/100 ml and 6.11 log10 gene copies/gram, respectively), however, the detection of host-associated MST markers varied. Human and avian markers were the most frequently detected in water samples (97 and 89%, respectively), whereas in sediment samples, only human-associated markers were detected more often (86%) than swine (64%) and avian (8.8%) markers. The results indicate that several locations in the Tiaoxi River are heavily polluted by fecal contamination and this correlated well with land use patterns. Among the five bacterial pathogens tested, Shigella spp. and Campylobacter jejuni were the most frequently detected pathogens in water (60% and 62%, respectively) and sediment samples (91% and 53%, respectively). Shiga toxin-producing Escherichia coli (STEC) and pathogenic Leptospira spp. were less frequently detected in water samples (55% and 33%, respectively) and sediment samples (51% and 13%, respectively), whereas E. coli O157:H7 was only detected in sediment samples (11%). Overall, the higher prevalence and concentrations of Campylobacter jejuni, Shigella spp., and STEC, along with the MST marker detection at a number of locations in the Tiaoxi River, indicates poor water quality and a significant human health risk associated with this watercourse. GRAPHICAL ABSTRACTTracking fecal contamination and pathogens in watersheds using molecular methods.

Performance evaluation of Bacteroidales genetic markers for human and animal microbial source tracking in tropical agricultural watersheds

Microbial source tracking (MST) DNA-based assays have been used to successfully solve fecal pollution problems in many countries, particularly in developed nations. However, their application in developing countries has been limited but continues to increase. In this study, sixteen endpoint and quantitative PCR (qPCR) assays targeting universal and human-, swine-, and cattle-specific Bacteroidales gene markers were modified for endpoint PCR, evaluated for their performance with sewage and fecal samples from the Tha Chin watershed and subsequently validated with samples from the Chao Phraya watershed, Thailand. Sample sizes of 81 composite samples (from over 1620 individual samples) of farm animals of each type as well as 19 human sewage samples from the Tha Chin watershed were calculated using a stratified random sampling design to achieve a 90% confidence interval and an expected prevalence (i.e., desired assay's sensitivity) of 0.80. The best universal and human-, swine-, and cattle-specific fecal markers were BacUni EP, HF183/BFDrev EP, Pig-2-Bac EP, and Bac3 assays, respectively. The detection limits for these assays ranged from 30 to 3000 plasmid copies per PCR. The positive predictive values were high in universal and swine- and cattle-specific markers (85-100%), while the positive predictive value of the human-specific assay was 52.2%. The negative predictive values in all assays were relatively high (90.8-100%). A suite of PCR assays in Thailand was established for potential MST use in environmental waters, which supports the worldwide applicability of Bacteroidales gene markers. This study also emphasizes the importance of using a proper sample size in assessing the performance of MST markers in a new geographic region.

Quantitative detection of fecal contamination with domestic poultry feces in environments in China

Poultry are an important source of fecal contamination in environments. However, tools for detecting and tracking this fecal contamination are in the early stages of development. In practice, we have found that source tracking methods targeting the 16S rRNA genes of poultry-specific microbiota are not sufficiently sensitive. We therefore developed two quantitative PCR assays for detection of poultry fecal contamination, by targeting chicken and duck mitochondrial genes: NADH dehydrogenase subunit 5 (ND5) and cytochrome b (cytb). The sensitivity of both assays was 100% when tested on 50 chicken and duck fecal samples from 10 provinces of China. These assays were also tested in field samples, including soil and water collected adjacent to duck farms, and soils fertilized with chicken manure. Poultry mitochondrial DNA was detected in most of these samples, indicating that the assays are a robust method for monitoring environmental contamination with poultry feces. Complemented with existing indicators of fecal contamination, these markers should improve the efficiency and accuracy of microbial source tracking.