In settings where humans and animals closely coexist, the introduction of faecal material into unprotected water sources significantly increases the risk of contracting diarrhoeal and zoonotic waterborne diseases. The data were gathered from a survey conducted through interviews at randomly sampled villages; additionally, water samples were collected in randomly selected households and their associated feeder catchments. Molecular techniques were used, specifically qPCR, to run host-specific Bacteroides microbial source tracking (MST) assays for human, cattle, pig, chicken and dog faecal contamination. Unexpectedly, the qPCR assays revealed dogs to be the most prevalent (40.65%) depositor of faecal matter in unprotected surface water, followed by humans (40.63%); this finding was contradictory to survey findings indicating cattle as the leading source. At the household level, dogs (16.67%) and chickens (15.28%) played prominent roles, as was expected. Reflecting on some of the basic daily practices in households, nearly 89.00% of the population was found to store water due to erratic supply, in contrast to 93.23% using an improved water source. Additionally, a significant association was found between water, sanitation and hygiene (WASH) variables and the occurrence of MST markers after performing a bivariate linear regression. However, the inconsistency between the MST results and household surveys suggests pervasive sanitation issues, even in households without domesticated animals.

Commercial Hog Operations (CHOs) produce large amounts of fecal waste, which is often treated in lagoons and sprayed onto fields as fertilizer. The effects of these systems on proximal water quality compared to ambient conditions have not been well-studied, and are particularly important for understanding the dissemination of fecal bacteria and antimicrobial resistance. A longitudinal, case-control watershed study was designed to study effects of CHOs on microbial water quality among watersheds with similar soil, land use, human population, and area. We compared watersheds with (n = 13) and without (n = 9) CHOs over one year measuring fecal indicator bacteria (FIB), microbial source tracking (MST) fecal markers, and antimicrobial resistance in isolated Escherichia coli. E. coli concentrations were higher (p < 0.001) at sites downstream of CHOs (1284 CFU/100 mL, n = 103) compared to background sites (687 CFU/100 mL, n = 74). The human MST marker HF183 was detected at similarly low concentrations (PR = 1.3 (0.91, 1.8), p = 0.30). However, the swine MST marker pig-2-bac was found at more sites downstream of CHOs (PR = 3.5 (0.98, 12), p = 0.035) and at a significantly higher (p = 0.003) mean concentration at sites downstream of CHOs (283 copies/mL) compared to background sites (0.76 copies/mL). The presence of any antimicrobial resistance was observed more often for E. coli isolated downstream from CHOs (19%, n = 556) than background sites (6%, n = 356), with tetracycline resistance observed most often. Nine isolates from four sites downstream of CHOs and one isolate from a background site were confirmed β-lactamase-producing E. coli. Overall, these results show that fecal microbes and antimicrobial resistance from CHOs may be transported off-site, however more research is needed to characterize timing and conditions of off-site transport. Mitigation strategies such as optimizeation of waste treatment, buffers, and antibiotic stewardship could help reduce the contributions of microbial contaminants to surface water.

Coastal marine environments are increasingly affected by anthropogenic impacts, such as the release of sewage at outfall sites and agricultural run-off. Fecal pollution introduced to the sea through these activities poses risks of spreading microbial diseases and disseminating antibiotic resistant bacteria and their genes. The study area of this research, Bore beach, is situated between two such point sources, an outfall site where treated sewage is released 1 km off the coast and a stream that carries run-off from an agricultural area to the northern end of the beach. In order to investigate whether and to what extent fecal contamination from the sewage outfall reached the beach, we used microbial source tracking, based on whole community analysis. Samples were collected from sea water at varying distances from the sewage outfall site and along the beach, as well as from the sewage effluent and the stream. Amplicon sequencing of 16S rRNA genes from all the collected samples was carried out at two time points (June and September). In addition, the seawater at the sewage outfall site and the sewage effluent were subject to shotgun metagenomics. To estimate the contribution of the sewage effluent and the stream to the microbial communities at Bore beach, we employed SourceTracker2, a program that uses a Bayesian algorithm to perform such quantification. The SourceTracker2 results suggested that the sewage effluent is likely to spread fecal contamination towards the beach to a greater extent than anticipated based on the prevailing sea current. The estimated mixing proportions of sewage at the near-beach site (P4) were 0.22 and 0.035% in June and September, respectively. This was somewhat below that stream\'s contribution in June (0.028%) and 10-fold higher than the stream\'s contribution in September (0.004%). Our analysis identified a sewage signal in all the tested seawater samples.

Little is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens such as Shiga toxin-producing Escherichia coli (STEC) originating from these practices remains poorly quantified. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley of California was sampled over a 9-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and have functional and taxonomic diversity comparable to that observed in soils. With our sequencing effort (∼4 Gbp per library), we were unable to detect any pathogenic E. coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low abundance. Furthermore, there were no significant differences in the abundance of human- or cow-specific gut microbiome sequences in the downstream impacted sites compared to that in upstream more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, the high number of metagenomic reads carrying antibiotic resistance genes (ARGs) found in all samples was significantly higher than ARG reads in other available freshwater and soil metagenomes, suggesting that these communities may be natural reservoirs of ARGs. The work presented here should serve as a guide for sampling volumes, amount of sequencing to apply, and what bioinformatics analyses to perform when using metagenomics for public health risk studies of environmental samples such as sediments.IMPORTANCE Current agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food- and waterborne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health are assessed by culture-based tests for the intestinal bacterium Escherichia coli However, the accuracy of these traditional methods (e.g., low accuracy in quantification, and false-positive signal when PCR based) and their suitability for sediments remain unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the United States in order to assess how agricultural runoff affects the native microbial communities and if the presence of Shiga toxin-producing Escherichia coli (STEC) in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments.

Floor materials in indoor environments are known to be reservoirs of microbes. We focused on examining bacterial community composition, antibiotic resistance (AR) and microbial source tracking (MST) of fecal bacteria on the floor surfaces. Swab samples were collected from carpet and vinyl floors in three different buildings (medical, veterinary, and office buildings) from high and low traffic areas. Bacterial communities were determined with 16S rRNA sequencing, and AR (tetracycline (tetQ), sulfonamide, and carbapenem (KPC)) and MST (human-, canine-, avian-, and ruminant-specific fecal bacteria) were examined with quantitative polymerase chain reaction (PCR). The results show that Proteobacteria and Actinobacteria were the most abundant phyla. Traffic level significantly affected the number of operational taxonomic units. Traffic level was a key factor for distinctive bacterial community in the medical center. Targeted ARGs were detected from all buildings and tetQ concentration was related with traffic level, and KPC was only detected from the medical center. Most of the floor surfaces showed the presence of dog-specific fecal bacteria (83%) followed by bird-specific fecal bacteria (75%). The results suggest that traffic levels affected the bacterial levels and fecal contamination is prevalent on the floor surfaces. This is the first study that reports KPC presence on the floor surfaces.

This study investigated causes of persistent fecal indicator bacteria (FIB) in beach sand under the pier in Santa Monica, CA. FIB levels were up to 1,000 times higher in sand underneath the pier than that collected from adjacent to the pier, with the highest concentrations under the pier in spring and fall. Escherichia coli (EC) and enterococci (ENT) under the pier were significantly positively correlated with moisture (ρ = 0.61, p < 0.001, n = 59; ρ = 0.43, p < 0.001, n = 59, respectively), and ENT levels measured by qPCR (qENT) were much higher than those measured by membrane filtration (cENT). Microcosm experiments tested the ability of EC, qENT, cENT, and general Bacteroidales (GenBac) to persist under in-situ moisture conditions (10% and 0.1%). Decay rates of qENT, cENT, and GenBac were not significantly different from zero at either moisture level, while decay rates for EC were relatively rapid during the microcosm at 10% moisture (k = 0.7 days-1). Gull/pelican marker was detected at eight of 12 sites and no human-associated markers (TaqHF183 and HumM2) were detected at any site during a one-day site survey. Results from this study indicate that the high levels of FIB observed likely stem from environmental sources combined with high persistence of FIB under the pier.

Fecal indicator bacteria used to assess illness risks in recreational waters (e.g., Escherichia coli, Enterococci) cannot discriminate among pollution sources. To address this limitation, human-associated Bacteroides markers have been proposed, but the risk of illness associated with the presence of these markers in recreational waters is unclear. Our objective was to estimate associations between human-associated Bacteroides markers in water and self-reported illness among swimmers at 6 U.S. beaches spanning 2003-2007.
We used data from a prospectively-enrolled cohort of 12,060 swimmers surveyed about beach activities and water exposure on the day of their beach visit. Ten to twelve days later, participants reported gastroinestinal, diarrheal, and respiratory illnesses experienced since the visit. Daily water samples were analyzed for the presence of human-associated Bacteroides genetic markers: HF183, BsteriF1, BuniF2, HumM2. We used model-based standardization to estimate risk differences (RD) and 95% confidence intervals (CI). We assessed whether the presence of Bacteroides markers were modifiers of the association between general Enterococcus and illness among swimmers using interaction contrast.
Overall we observed inconsistent associations between the presence of Bacteroides markers and illness. There was a pattern of increased risks of gastrointestinal (RD = 1.9%; 95% CI: 0.1%, 3.7%), diarrheal (RD = 1.3%; 95% CI: -0.2%, 2.7%), and respiratory illnesses (RD = 1.1%; 95% CI: -0.2%, 2.5%) associated with BsteriF1. There was no evidence that Bacteroides markers acted as modifiers of Enterococcus and illness. Patterns were similar when stratified by water matrix.
Quantitative measures of fecal pollution using Bacteroides, rather than presence-absence indicators, may be necessary to accurately assess human risk specific to the presence of human fecal pollution.

In pasture-based systems, changes in dairy herd habitat due to seasonality results in the exposure of animals to different environmental niches. These niches contain distinct microbial communities that may be transferred to raw milk, with potentially important food quality and safety implications for milk producers. It is postulated that the extent to which these microorganisms are transferred could be limited by the inclusion of a teat preparation step prior to milking. High-throughput sequencing on a variety of microbial niches on farms was used to study the patterns of microbial movement through the dairy production chain and, in the process, to investigate the impact of seasonal housing and the inclusion/exclusion of a teat preparation regime on the raw milk microbiota from the same herd over two sampling periods, i.e., indoor and outdoor. Beta diversity and network analyses showed that environmental and milk microbiotas separated depending on whether they were sourced from an indoor or outdoor environment. Within these respective habitats, similarities between the milk microbiota and that of teat swab samples and, to a lesser extent, fecal samples were apparent. Indeed, SourceTracker identified the teat surface as the most significant source of contamination, with herd feces being the next most prevalent source of contamination. In milk from cows grazing outdoors, teat prep significantly increased the numbers of total bacteria present. In summary, sequence-based microbiota analysis identified possible sources of raw milk contamination and highlighted the influence of environment and farm management practices on the raw milk microbiota.
The composition of the raw milk microbiota is an important consideration from both a spoilage perspective and a food safety perspective and has implications for milk targeted for direct consumption and for downstream processing. Factors that influence contamination have been examined previously, primarily through the use of culture-based techniques. We describe here the extensive application of high-throughput DNA sequencing technologies to study the relationship between the milk production environment and the raw milk microbiota. The results show that the environment in which the herd was kept was the primary driver of the composition of the milk microbiota composition.

Gulls were reported as sources of fecal pollution in coastal environments and potential vectors of human infections. Microbial source tracking (MST) methods were rarely tested to identify this pollution origin. This study was conducted to ascertain the source of water fecal contamination in the Berlenga Island, Portugal. A total of 169 Escherichia coli isolates from human sewage, 423 isolates from gull feces and 334 water isolates were analyzed by BOX-PCR. An average correct classification of 79.3% was achieved. When an 85% similarity cutoff was applied 24% of water isolates were present in gull feces against 2.7% detected in sewage. Jackknifing resulted in 29.3% of water isolates classified as gull, and 10.8% classified as human. Results indicate that gulls constitute a major source of water contamination in the Berlenga Island. This study validated a methodology to differentiate human and gull fecal pollution sources in a real case of a contaminated beach.

A number of PCR-based methods for detecting human fecal material in environmental waters have been developed over the past decade, but these methods have rarely received independent comparative testing in large multi-laboratory studies. Here, we evaluated ten of these methods (BacH, BacHum-UCD, Bacteroides thetaiotaomicron (BtH), BsteriF1, gyrB, HF183 endpoint, HF183 SYBR, HF183 Taqman(®), HumM2, and Methanobrevibacter smithii nifH (Mnif)) using 64 blind samples prepared in one laboratory. The blind samples contained either one or two fecal sources from human, wastewater or non-human sources. The assay results were assessed for presence/absence of the human markers and also quantitatively while varying the following: 1) classification of samples that were detected but not quantifiable (DNQ) as positive or negative; 2) reference fecal sample concentration unit of measure (such as culturable indicator bacteria, wet mass, total DNA, etc); and 3) human fecal source type (stool, sewage or septage). Assay performance using presence/absence metrics was found to depend on the classification of DNQ samples. The assays that performed best quantitatively varied based on the fecal concentration unit of measure and laboratory protocol. All methods were consistently more sensitive to human stools compared to sewage or septage in both the presence/absence and quantitative analysis. Overall, HF183 Taqman(®) was found to be the most effective marker of human fecal contamination in this California-based study.