Human-Associated Indicator Bacteria and Human-Specific Viruses in Surface Water: A Spatial Assessment with Implications on Fate and Transport

Two risk assessments: Evaluating the use of indicator HF183 Bacteroides versus pathogen measurements for modelling recreational illness risks in an urban watershed

The purpose of this study was to evaluate the performance of HF183 Bacteroides for estimating pathogen exposures during recreational water activities. We compared the use of Bacteroides-based exposure assessment to exposure assessment that relied on pathogen measurements. We considered two types of recreational water sites: those impacted by combined sewer overflows (CSOs) and those not impacted by CSOs. Samples from CSO-impacted and non-CSO-impacted urban creeks were analysed by quantitative polymerase chain reaction (qPCR) for HF183 Bacteroides and eight human gastrointestinal pathogens. Exposure assessment was conducted two ways for each type of site (CSO-impacted vs. non-CSO impacted): 1) by estimating pathogen concentrations from HF183 Bacteroides concentrations using published ratios of HF183 to pathogens in sewage and 2) by estimating pathogen concentrations from qPCR measurements. QMRA (quantitative microbial risk assessment) was then conducted for swimming, wading, and fishing exposures. Overall, mean risk estimates varied from 0.27 to 53 illnesses per 1,000 recreators depending on exposure assessment, site, activity, and norovirus dose-response model. HF183-based exposure assessment identified CSO-impacted sites as higher risk, and the recommended HF183 risk-based threshold of 525 genomic copies per 100 mL was generally protective of public health at the CSO-impacted sites but was not as protective at the non-CSO-impacted sites. In the context of our urban watershed, HF183-based exposure assessment over- and under-estimated risk relative to exposure assessment based on pathogen measurements, and the etiology of predicted pathogen-specific illnesses differed significantly. Across all sites, the HF183 model overestimated risk for norovirus, adenovirus, and Campylobacter jejuni, and it underestimated risk for E. coli and Cryptosporidium. To our knowledge, this study is the first to directly compare health risk estimates using HF183 and empirical pathogen measurements from the same waterways. Our work highlights the importance of site-specific hazard identification and exposure assessment to decide whether HF183 is applicable for monitoring risk.

A multi-marker assessment of sewage contamination in streams using human-associated indicator bacteria, human-specific viruses, and pharmaceuticals

Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological (n = 21) and chemical (n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years. Five-day composite water samples (n = 98) were collected biweekly, and sewage influent samples (n = 25) were collected monthly at a Milwaukee, WI water reclamation facility. We found the vast majority of markers were not sensitive enough to detect sewage contamination. To compare analytes for monitoring applications, five consistently detected human sewage indicators were used to evaluate temporal patterns of sewage contamination, including microbiological (pepper mild mottle virus, human Bacteroides, human Lachnospiraceae) and chemical (acetaminophen, metformin) markers. The proportion of human sewage in each stream was estimated using the mean influent concentration from the water reclamation facility and the mean concentration of all stream samples for each sewage indicator marker. Estimates of instream sewage pollution varied by marker, differing by up to two orders of magnitude, but four of the five sewage markers characterized Underwood Creek (mean proportions of human sewage ranged 0.0025 % - 0.075 %) as less polluted than Menomonee River (proportions ranged 0.013 % - 0.14 %) by an order of magnitude more. Chemical markers correlated with each other and yielded higher estimates of sewage pollution than microbial markers, which exhibited greater temporal variability. Transport, attenuation, and degradation processes can influence chemical and microbial markers differently and cause variation in human sewage estimates. Given the range of potential human and ecological health effects of human sewage contamination, robust characterization of sewage contamination that uses multiple lines of evidence supports monitoring and research applications.

Flow cytometric assessments of metabolic activity in bacterial assemblages provide insight into ecosystem condition along the Buffalo National River, Arkansas

The Buffalo National River (BNR), on karst terrain in Arkansas, is considered an extraordinary water resource. Water collected in Spring 2017 along BNR was metagenomically analyzed using 16S rDNA, and for 17 months (5/2017-11/2018), bacterial responses were measured in relation to nutrients sampled along a stretch of BNR near a concentrated animal feed operation (CAFO) on Big Creek. Because cell count and esterase activity can increase proportionally with organic enrichment, they were hypothesized to be elevated near the CAFO. Counts (colony forming units; CFUs) were different among sites for 73 % of the months; Big Creek generated highest CFUs 27 % of the time, with the closest downstream site at 13.3 %. Esterase activity was different among sites 94 % of the time, with Big Creek exhibiting lowest activity 71 % of the time. Over the months, activity was similar across sites at ~70 % active, except at Big Creek (56 %). The α-diversity of BNR microbial consortia near a wastewater treatment plant (WWTP) and the CAFO was related to distance from the WWTP and CAFO. The inverse relationship between high CFUs and low esterase activity at Big Creek (r = -0.71) actuated in vitro exposures of bacteria to organic wastewater contaminants (OWC) previously identified in the watershed. Exponential-phase Escherichia coli (stock strain), Streptococcus suis (avirulent, from swine), and S. dysgalactiae (virulent, from silver carp, Hypophthalmichthys molitrix) were incubated with atrazine, pharmaceuticals (17 α-ethynylestradiol and trenbolone), and antimicrobials (tylosin and butylparaben). Bacteria were differentially responsive. Activity varied with exposure time and OWC type, but not concentration; atrazine decreased it most. Taken together - the metagenomic taxonomic similarities along BNR, slightly higher bacterial growth and lower bacterial esterase at the CAFO, and the lab exposures of bacterial strains showing that OWC altered metabolism - the results indicated that bioactive OWC entering the watershed can strongly influence microbial processes in the aquatic ecosystem.

A cryptic plasmid is among the most numerous genetic elements in the human gut

Plasmids are extrachromosomal genetic elements that often encode fitness-enhancing features. However, many bacteria carry "cryptic" plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes and is 14 times as numerous as crAssphage, currently established as the most abundant extrachromosomal genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales, and although it does not appear to impact bacterial host fitness in vivo, it can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an alternative approach to track human colonic inflammatory states.

Methodological differences between studies confound one-size-fits-all approaches to managing surface waterways for food and water safety

Even though differences in methodology (e.g., sample volume and detection method) have been shown to affect observed microbial water quality, multiple sampling and laboratory protocols continue to be used for water quality monitoring. Research is needed to determine how these differences impact the comparability of findings to generate best management practices and the ability to perform meta-analyses. This study addresses this knowledge gap by compiling and analyzing a data set representing 2,429,990 unique data points on at least one microbial water quality target (e.g., Salmonella presence and Escherichia coli concentration). Variance partitioning analysis was used to quantify the variance in likelihood of detecting each pathogenic target that was uniquely and jointly attributable to non-methodological versus methodological factors. The strength of the association between microbial water quality and select methodological and non-methodological factors was quantified using conditional forest and regression analysis. Fecal indicator bacteria concentrations were more strongly associated with non-methodological factors than methodological factors based on conditional forest analysis. Variance partitioning analysis could not disentangle non-methodological and methodological signals for pathogenic Escherichia coli, Salmonella, and Listeria. This suggests our current perceptions of foodborne pathogen ecology in water systems are confounded by methodological differences between studies. For example, 31% of total variance in likelihood of Salmonella detection was explained by methodological and/or non-methodological factors, 18% was jointly attributable to both methodological and non-methodological factors. Only 13% of total variance was uniquely attributable to non-methodological factors for Salmonella, highlighting the need for standardization of methods for microbiological water quality testing for comparison across studies.IMPORTANCEThe microbial ecology of water is already complex, without the added complications of methodological differences between studies. This study highlights the difficulty in comparing water quality data from projects that used different sampling or laboratory methods. These findings have direct implications for end users as there is no clear way to generalize findings in order to characterize broad-scale ecological phenomenon and develop science-based guidance. To best support development of risk assessments and guidance for monitoring and managing waters, data collection and methods need to be standardized across studies. A minimum set of data attributes that all studies should collect and report in a standardized way is needed. Given the diversity of methods used within applied and environmental microbiology, similar studies are needed for other microbiology subfields to ensure that guidance and policy are based on a robust interpretation of the literature.

Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

A highly conserved and globally prevalent cryptic plasmid is among the most numerous mobile genetic elements in the human gut

Plasmids are extrachromosomal genetic elements that often encode fitness enhancing features. However, many bacteria carry 'cryptic' plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes, and is 14 times as numerous as crAssphage, currently established as the most abundant genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales and although it does not appear to impact bacterial host fitness in vivo, can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an inexpensive alternative for detecting human colonic inflammatory states.

Optical Properties of Water for Prediction of Wastewater Contamination, Human-Associated Bacteria, and Fecal Indicator Bacteria in Surface Water at Three Watershed Scales

Relations between spectral absorbance and fluorescence properties of water and human-associated and fecal indicator bacteria were developed for facilitating field sensor applications to estimate wastewater contamination in waterways. Leaking wastewater conveyance infrastructure commonly contaminates receiving waters. Methods to quantify such contamination can be time consuming, expensive, and often nonspecific. Human-associated bacteria are wastewater specific but require discrete sampling and laboratory analyses, introducing latency. Human sewage has fluorescence and absorbance properties different than those of natural waters. To assist real-time field sensor development, this study investigated optical properties for use as surrogates for human-associated bacteria to estimate wastewater prevalence in environmental waters. Three spatial scales were studied: Eight watershed-scale sites, five subwatershed-scale sites, and 213 storm sewers and open channels within three small watersheds (small-scale sites) were sampled (996 total samples) for optical properties, human-associated bacteria, fecal indicator bacteria, and, for selected samples, human viruses. Regression analysis indicated that bacteria concentrations could be estimated by optical properties used in existing field sensors for watershed and subwatershed scales. Human virus occurrence increased with modeled human-associated bacteria concentration, providing confidence in these regressions as surrogates for wastewater contamination. Adequate regressions were not found for small-scale sites to reliably estimate bacteria concentrations likely due to inconsistent local sanitary sewer inputs.

Effects of natural sunlight on antimicrobial-resistant bacteria (AMRB) and antimicrobial-susceptible bacteria (AMSB) in wastewater and river water

The effects of natural sunlight on antimicrobial-resistant bacteria (AMRB) and antimicrobial-susceptible bacteria (AMSB) were investigated in three types of water: sewage treatment plant (STP) influent, STP secondary effluent, and river water in an urban area of Japan. The AMRB were grouped into six classes: carbapenem-resistant Enterobacteriaceae (CRE), extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (ESBL-E), multi-drug-resistant Acinetobacter (MDRA), multi-drug-resistant Pseudomonas aeruginosa (MDRP), methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant Enterococcus (VRE). The amount of each group of bacteria present was estimated using specific chromogenic agar formulations. AMRB were detected in all water samples, with 13-2,407 colony-forming units (CFU)/mL in the STP influent, N.D. to 202 CFU/mL in the secondary STP effluent, and N.D. to 207 CFU/mL in the river water. The distribution profiles of the AMSB in water samples were similar to those of AMRB. The degree to which AMRB and AMSB present in the river water were inactivated by natural sunlight was tested as the main aim of this study. Irradiation by natural sunlight was found to inactivate almost 100% of all the target AMRB after 5 h of exposure, with no significant differences (P < 0.05) observed in the effects that sunlight had on AMSB and AMRB. Analysis of the bacterial community structure based on 16S rRNA gene sequencing showed that the structure of the bacterial community was apparently not affected by the exposure to sunlight. In addition, the taxonomic diversity in the STP secondary effluent did not change as a result of additional disinfection with chlorine. The results of this study suggest that it is possible that exposure to sunlight could be used as an alternative to disinfection via chlorine. To our knowledge, this is the first report to demonstrate the mitigation of AMSB and AMRB pollution in a river environment via the exposure to natural sunlight.

Integrating Metagenomic and Bayesian Analyses to Evaluate the Performance and Confidence of CrAssphage as an Indicator for Tracking Human Sewage Contamination in China

Recently, crAssphage has been proposed as a human-specific marker for tracking fecal contamination. However, its performance has always been validated in a limited number of host samples, which may obscure our understanding of its utility. Furthermore, few studies have quantified confidence of fecal contamination when using crAssphage. Here, we evaluate the performance and confidence of crAssphage by analyzing a large panel of metagenomic data sets combined with Bayesian analyses. Results demonstrate that crAssphage exhibits superior performance with high host sensitivity and specificity, indicating its suitability for tracking human fecal sources. With the marker, a high confidence (>90%) can be obtained and particularly, multiple samples with positive results provide a near certainty of confidence. The application of crAssphage in the sediments of three Chinese urban rivers shows a high confidence of >97% of human fecal contamination, suggesting the serious challenge of sewage pollution in these environments. Additionally, significant correlation is observed between crAssphage and antibiotic resistance genes (ARGs), expanding the utilization of crAssphage for pollution management of ARGs. This study highlights the benefit of using metagenomic-based analysis for evaluating the performance and confidence of microbial source tracking markers in the coming era of big data with increasing resources in available metagenomic data.

Examining coastal dynamics and recreational water quality by quantifying multiple sewage specific markers in a North Carolina estuary

Fecal contamination is observed downstream of municipal separate storm sewer systems in coastal North Carolina. While it is well accepted that wet weather contributes to this phenomenon, less is understood about the contribution of the complex hydrology in this low-lying coastal plain. A quantitative microbial assessment was conducted in Beaufort, North Carolina to identify trends and potential sources of fecal contamination in stormwater receiving waters. Fecal indicator concentrations were significantly higher in receiving water downstream of a tidally submerged outfall compared to an outfall that was permanently submerged (p < 0.001), though tidal height was not predictive of human-specific microbial source tracking (MST) marker concentrations at the tidally submerged site. Short-term rainfall (i.e. <12 h) was predictive of E. coli, Enterococcus spp., and human-specific MST marker concentrations (Fecal Bacteroides, BacHum, and HF183) in receiving waters. The strong correlation between 12-hr antecedent rainfall and Enterococcus spp. (r = 0.57, p < 0.001, n = 92) suggests a predictive model could be developed based on rainfall to communicate risk for bathers. Additional molecular marker data indicates that the delivery of fecal sources is complex and highly variable, likely due to the influence of tidal influx (saltwater intrusion from the estuary) into the low-lying stormwater pipes. In particular, elevated MST marker concentrations (up to 2.56 × 10⁴ gene copies HF183/mL) were observed in standing water near surcharging street storm drain. These data are being used to establish a baseline for stormwater dynamics prior to dramatic rainfall in 2018 and to characterize the interaction between complex stormwater dynamics and water quality impairment in coastal NC.

The challenges of microbial source tracking at urban beaches for Quantitative Microbial Risk Assessment (QMRA)

Urban beaches are frequently impacted from multiple sources of fecal contamination. This along with high beach usage underscores the importance of appropriate management that protects swimmer health. The USEPA has enabled the use of QMRA as a tool for quantifying swimmer health risk and setting site-specific water quality objectives. This study illustrates the challenges associated with human and non-human source identification and how these challenges influence the decision of whether QMRA at typical urban beaches for water quality management is appropriate. In this study, a similar and correlated spatial relationship with elevated Enterococcus and avian-specific markers was observed, suggesting shorebirds as a primary source of FIB. However, human-associated markers were also detected frequently but at low concentrations. Ultimately, a QMRA was not conducted because pathogen loading from potential human sources could not be confidently quantified, having consequences for health risk in receiving waters where recreational contact occurs.