Terrestrial sources homogenize bacterial water quality during rainfall in two urbanized watersheds in Santa Barbara, CA

Spread Patterns of Antibiotic Resistance in Faecal Indicator Bacteria Contaminating an Urbanized Section of the Brda River

This paper presents the spatio-temporal distribution of faecal indicator bacteria (FIB) in the river section subject to anthropogenic stress and describes spread patterns of antibiotic resistance in the studied bacterial groups. The analysis involved 58 strains of Escherichia coli and 61 strains of enterococci. Antibiotic resistance profiles were prepared in accordance with the recommendations of the European Committee on Antimicrobial Susceptibility Testing (EUCAST). The results indicated a correlation between the location of a sampling site and the concentration of faecal bacteria. The highest average concentrations were recorded at the site located in the city centre, where the river is used mainly for recreation. Antibiotic resistance profiles showed that Escherichia coli had 100% sensitivity to tigecycline, levofloxacin and imipenem. The highest percentaage of strains (17%) were resistant to piperacillin. Enterococci were 100% sensitive to levofloxacin. No strains were vancomycin-resistant (VRE). The highest percentage of strains was resistant to imipenem (23%), and the lowest, to ampicillin (2%). The spatio-temporal distribution of antibiotic-resistant strains (ARS) indicated a high concentration of drug-resistant Escherichia coli (47%) in the summer season at the sampling site located in the last part of the river. At the same time, drug resistance in enterococci increased along the river course and was considerably higher in spring. There were no significant relationships between physico-chemical parameters of water and the levels of faecal bacteria. On the other hand, strong relationships were observed between the percentage of strains showing resistance to the applied antibiotics and physico-chemical and biological parameters of water. The percentage of antibiotic resistant strains of Escherichia coli was negatively correlated with dissolved oxygen concentration (r = - 0.9; p < 0.001) and BOD₅ (r = - 0.85; p < 0.05). The percentage of antibiotic resistant strains of enterococci was most strongly correlated with water pH (r = - 0.92; p < 0.001).

Improving the identification of the source of faecal pollution in water using a modelling approach: From multi-source to aged and diluted samples

The last decades have seen the development of several source tracking (ST) markers to determine the source of pollution in water, but none of them show 100% specificity and sensitivity. Thus, a combination of several markers might provide a more accurate classification. In this study Ichnaea® software was improved to generate predictive models, taking into account ST marker decay rates and dilution factors to reflect the complexity of ecosystems. A total of 106 samples from 4 sources were collected in 5 European regions and 30 faecal indicators and ST markers were evaluated, including E. coli, enterococci, clostridia, bifidobacteria, somatic coliphages, host-specific bacteria, human viruses, host mitochondrial DNA, host-specific bacteriophages and artificial sweeteners. Models based on linear discriminant analysis (LDA) able to distinguish between human and non-human faecal pollution and identify faecal pollution of several origins were developed and tested with 36 additional laboratory-made samples. Almost all the ST markers showed the potential to correctly target their host in the 5 areas, although some were equivalent and redundant. The LDA-based models developed with fresh faecal samples were able to differentiate between human and non-human pollution with 98.1% accuracy in leave-one-out cross-validation (LOOCV) when using 2 molecular human ST markers (HF183 and HMBif), whereas 3 variables resulted in 100% correct classification. With 5 variables the model correctly classified all the fresh faecal samples from 4 different sources. Ichnaea® is a machine-learning software developed to improve the classification of the faecal pollution source in water, including in complex samples. In this project the models were developed using samples from a broad geographical area, but they can be tailored to determine the source of faecal pollution for any user.

Spatial patterns of enzymatic activity in large water bodies: Ship-borne measurements of beta-D-glucuronidase activity as a rapid indicator of microbial water quality

This study used automated enzymatic activity measurements conducted from a mobile research vessel to detect the spatial variability of beta‑d‑glucuronidase (GLUC) activity in large freshwater bodies. The ship-borne observations provided the first high-resolution spatial data of GLUC activity in large water bodies as rapid indication of fecal pollution and were used to identify associations with hydrological conditions and land use. The utility of this novel approach for water quality screening was evaluated by surveys of the Columbia River, the Mississippi River and the Yahara Lakes, covering up to a 500 km river course and 50 km² lake area. The ship-borne measurements of GLUC activity correlated with standard E. coli analyses (R² = 0.71) and revealed the effects of (1) precipitation events and urban run-off on GLUC activity in surface waters, (2) localized point inlets of potential fecal pollution and (3) increasing GLUC signals along gradients of urbanization. We propose that this ship-borne water quality screening to be integrated into future water inventory programs as an initial or complementary tool (besides established fecal indicator parameters), due to its ability to provide near real-time spatial information on potential fecal contamination of large surface water resources and therefore being helpful to greatly reduce potential human health risks.

Microbial source tracking markers associated with domestic rainwater harvesting systems: Correlation to indicator organisms

Domestic rainwater harvesting (tank water) systems were screened for the presence of a panel of microbial source tracking (MST) markers and traditional indicator organisms. The indicator organisms were enumerated utilizing traditional culture-based methods, while the MST markers were quantified by quantitative PCR (qPCR). The indicators Escherichia coli (E. coli) and enterococci were also quantified using qPCR. Correlations and concurrence between these parameters were then investigated to determine which markers could be utilized to supplement traditional indicator analysis. Quantitative PCR analysis indicated that Bacteroides HF183, adenovirus, Lachnospiraceae and E. coli were detected and quantifiable in 100% of the tank water samples collected throughout the sampling period, while human mitochondrial DNA (mtDNA) was quantifiable in 90% of the tank water samples and Bifidobacterium adolescentis (B. adolescentis) and enterococci were quantifiable in 67% of the tank water samples, respectively. Significant positive correlations were recorded for Lachnospiraceae versus heterotrophic bacteria (p = 0.000), adenovirus versus E. coli (culturing) (p = 0.000) and heterotrophic bacteria (p = 0.024), the HF183 marker versus E. coli (qPCR) (p = 0.024) and B. adolescentis versus fecal coliforms (p = 0.037). In addition, 100% concurrence was observed for the HF183 marker, adenovirus and Lachnospiraceae versus E. coli (qPCR), enterococci (qPCR) and heterotrophic bacteria, amongst others. Based on the correlations and the concurrence analysis, the HF183 marker, Lachnospiraceae and adenovirus may be utilized to supplement indicator organism analysis for the monitoring of harvested rainwater quality.

Regional Assessment of Human Fecal Contamination in Southern California Coastal Drainages

Host-associated genetic markers that allow for fecal source identification have been used extensively as a diagnostic tool to determine fecal sources within watersheds, but have not been used in routine monitoring to prioritize remediation actions among watersheds. Here, we present a regional assessment of human marker prevalence among drainages that discharge to the U.S. southern California coast. Approximately 50 samples were analyzed for the HF183 human marker from each of 22 southern California coastal drainages under summer dry weather conditions, and another 50 samples were targeted from each of 23 drainages during wet weather. The HF183 marker was ubiquitous, detected in all but two sites in dry weather and at all sites during wet weather. However, there was considerable difference in the extent of human fecal contamination among sites. Similar site ranking was produced regardless of whether the assessment was based on frequency of HF183 detection or site average HF183 concentration. However, site ranking differed greatly between dry and wet weather. Site ranking also differed greatly when based on enterococci, which do not distinguish between pollution sources, vs. HF183, which distinguishes higher risk human fecal sources from other sources, indicating the additional value of the human-associated marker as a routine monitoring tool.

Presence of microbial and chemical source tracking markers in roof-harvested rainwater and catchment systems for the detection of fecal contamination

Microbial source tracking (MST) and chemical source tracking (CST) markers were utilized to identify fecal contamination in harvested rainwater and gutter debris samples. Throughout the sampling period, Bacteroides HF183 was detected in 57.5 % of the tank water samples and 95 % of the gutter debris samples, while adenovirus was detected in 42.5 and 52.5 % of the tank water and gutter debris samples, respectively. Human adenovirus was then detected at levels ranging from below the detection limit to 316 and 1253 genome copies/μL in the tank water and debris samples, respectively. Results for the CST markers showed that salicylic acid (average 4.62 μg/L) was the most prevalent marker (100 %) in the gutter debris samples, caffeine (average 18.0 μg/L) was the most prevalent in the tank water samples (100 %) and acetaminophen was detected sporadically throughout the study period. Bacteroides HF183 and salicylic acid (95 %) and Bacteroides HF183 and caffeine (80 %) yielded high concurrence frequencies in the gutter debris samples. In addition, the highest concurrence frequency in the tank water samples was observed for Bacteroides HF183 and caffeine (60 %). The current study thus indicates that Bacteroides HF183, salicylic acid and caffeine may potentially be applied as source tracking markers in rainwater catchment systems in order to supplement fecal indicator analyses.

Ultrafiltration and Microarray for Detection of Microbial Source Tracking Marker and Pathogen Genes in Riverine and Marine Systems

Pathogen identification and microbial source tracking (MST) to identify sources of fecal pollution improve evaluation of water quality. They contribute to improved assessment of human health risks and remediation of pollution sources. An MST microarray was used to simultaneously detect genes for multiple pathogens and indicators of fecal pollution in freshwater, marine water, sewage-contaminated freshwater and marine water, and treated wastewater. Dead-end ultrafiltration (DEUF) was used to concentrate organisms from water samples, yielding a recovery efficiency of >95% for Escherichia coli and human polyomavirus. Whole-genome amplification (WGA) increased gene copies from ultrafiltered samples and increased the sensitivity of the microarray. Viruses (adenovirus, bocavirus, hepatitis A virus, and human polyomaviruses) were detected in sewage-contaminated samples. Pathogens such as Legionella pneumophila, Shigella flexneri, and Campylobacter fetus were detected along with genes conferring resistance to aminoglycosides, beta-lactams, and tetracycline. Nonmetric dimensional analysis of MST marker genes grouped sewage-spiked freshwater and marine samples with sewage and apart from other fecal sources. The sensitivity (percent true positives) of the microarray probes for gene targets anticipated in sewage was 51 to 57% and was lower than the specificity (percent true negatives; 79 to 81%). A linear relationship between gene copies determined by quantitative PCR and microarray fluorescence was found, indicating the semiquantitative nature of the MST microarray. These results indicate that ultrafiltration coupled with WGA provides sufficient nucleic acids for detection of viruses, bacteria, protozoa, and antibiotic resistance genes by the microarray in applications ranging from beach monitoring to risk assessment.

Urban microbial ecology of a freshwater estuary of Lake Michigan

Freshwater estuaries throughout the Great Lakes region receive stormwater runoff and riverine inputs from heavily urbanized population centers. While human and animal feces contained in this runoff are often the focus of source tracking investigations, non-fecal bacterial loads from soil, aerosols, urban infrastructure, and other sources are also transported to estuaries and lakes. We quantified and characterized this non-fecal urban microbial component using bacterial 16S rRNA gene sequences from sewage, stormwater, rivers, harbor/estuary, and the lake surrounding Milwaukee, WI, USA. Bacterial communities from each of these environments had a distinctive composition, but some community members were shared among environments. We used a statistical biomarker discovery tool to identify the components of the microbial community that were most strongly associated with stormwater and sewage to describe an "urban microbial signature," and measured the presence and relative abundance of these organisms in the rivers, estuary, and lake. This urban signature increased in magnitude in the estuary and harbor with increasing rainfall levels, and was more apparent in lake samples with closest proximity to the Milwaukee estuary. The dominant bacterial taxa in the urban signature were Acinetobacter, Aeromonas, and Pseudomonas, which are organisms associated with pipe infrastructure and soil and not typically found in pelagic freshwater environments. These taxa were highly abundant in stormwater and sewage, but sewage also contained a high abundance of Arcobacter and Trichococcus that appeared in lower abundance in stormwater outfalls and in trace amounts in aquatic environments. Urban signature organisms comprised 1.7% of estuary and harbor communities under baseflow conditions, 3.5% after rain, and >10% after a combined sewer overflow. With predicted increases in urbanization across the Great Lakes, further alteration of freshwater communities is likely to occur with potential long term impacts on the function of estuarine and nearshore ecosystems.

Sewage pollution in urban stormwater runoff as evident from the widespread presence of multiple microbial and chemical source tracking markers

The concurrence of human sewage contamination in urban stormwater runoff (n=23) from six urban catchments across Australia was assessed by using both microbial source tracking (MST) and chemical source tracking (CST) markers. Out of 23 stormwater samples human adenovirus (HAv), human polyomavirus (HPv) and the sewage-associated markers; Methanobrevibacter smithii nifH and Bacteroides HF183 were detected in 91%, 56%, 43% and 96% of samples, respectively. Similarly, CST markers paracetamol (87%), salicylic acid (78%) acesulfame (96%) and caffeine (91%) were frequently detected. Twenty one samples (91%) were positive for six to eight sewage related MST and CST markers and remaining two samples were positive for five and four markers, respectively. A very good consensus (>91%) observed between the concurrence of the HF183, HAv, acesulfame and caffeine suggests good predictability of the presence of HAv in samples positive for one of the three markers. High prevalence of HAv (91%) also suggests that other enteric viruses may also be present in the stormwater samples which may pose significant health risks. This study underscores the benefits of employing a set of MST and CST markers which could include monitoring for HF183, adenovirus, caffeine and paracetamol to accurately detect human sewage contamination along with credible information on the presence of human enteric viruses, which could be used for more reliable public health risk assessments. Based on the results obtained in this study, it is recommended that some degree of treatment of captured stormwater would be required if it were to be used for non-potable purposes.

Evaluation of the nifH gene marker of Methanobrevibacter smithii for the detection of sewage pollution in environmental waters in Southeast Queensland, Australia

This study aimed at evaluating the host-specificity and -sensitivity of the nifH gene marker of Methanobrevibacter smithii by screening 272 fecal and wastewater samples from 11 animal species including humans in Southeast Queensland (SEQ), Australia. In addition, environmental water samples (n = 21) were collected during the dry and wet weather conditions and tested for the presence of the nifH marker along with other sewage-associated markers, namely, enterococci surface protein (esp) found in Enterococci faecium, Bacteroides HF183, adenoviruses (AVs), and polyomaviruses (PVs). The overall host-specificity of the nifH marker to differentiate between human and animal feces was 0.96 (maximum value of 1), while the overall sensitivity of this marker in human sourced feces and wastewater was 0.81 (maximum value of 1). Among the 21 environmental water samples tested, 2 (10%), 3 (14%), 12 (57%), 6 (29%), and 6 (29%) were positive for the nifH, esp, HF183, AVs and PVs markers, respectively. The prevalence of the nifH marker in environmental water samples, however, was low compared to other markers, suggesting that the use of this marker alone may not be sensitive enough to detect fecal pollution in environmental waters. The nifH marker, however, appears to be sewage-specific in SEQ, Australia, and therefore, it is recommended that this marker should be used as an additional marker in combination with the HF183 or viral markers such as AVs or PVs for accurate and sensitive detection of fecal pollution in SEQ waterways.