Dataset Information

Partitioning of Antibiotic Resistance Genes and Fecal Indicators Varies Intra and Inter-Storm during Combined Sewer Overflows.

ABSTRACT: Combined sewer overflows (CSOs) degrade water quality through the release of microbial contaminants in CSO effluent. Improved understanding of the partitioning of microbial contaminants onto settleable particles can provide insight into their fate in end-of-pipe treatment systems or following release during CSO events. Sampling was performed across the hydrograph for three storm events as well as during baseflow and wet weather in three surface waters impacted by CSO. qPCR was performed for select antibiotic resistance genes (ARG) and a marker gene for human fecal indicator organisms (BacHum) in samples processed the partitioning of microbial contaminants on settleable particles versus suspended in the aqueous phase. Amplicon sequencing was performed on both fractions of storm samples to further define the timing and partitioning of microbial contaminants released during CSO events. Samples collected at the CSO outfall exhibited microbial community signatures of wastewater at select time points early or late in the storm events. CSOs were found to be a source of ARG. In surrounding surface waters, sul1 was higher in samples from select locations during wet weather compared to baseflow. Otherwise, ARG concentrations were variable with no differences between baseflow and wet weather conditions. The majority of ARG at the CSO outfall were observed on the attached fraction of samples: 64-79% of sul1 and 59-88% of tet(G). However, the timing of peak ARG and human fecal indicator marker gene BacHum did not necessarily coincide with observation of the microbial signature of wastewater in CSO effluent. Therefore, unit processes that remove settleable particles (e.g., hydrodynamic separators) operated throughout a CSO event would achieve up to (0.5-0.9)-log removal of ARG and fecal indicators by removing the attached fraction of measured genes. Secondary treatment would be required if greater removal of these targets is needed.

SUBMITTER: Eramo A

PROVIDER: S-EPMC5655003 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Partitioning of Antibiotic Resistance Genes and Fecal Indicators Varies Intra and Inter-Storm during Combined Sewer Overflows.

Eramo Alessia A Delos Reyes Hannah H Fahrenfeld Nicole L NL

Frontiers in microbiology 20171020

Combined sewer overflows (CSOs) degrade water quality through the release of microbial contaminants in CSO effluent. Improved understanding of the partitioning of microbial contaminants onto settleable particles can provide insight into their fate in end-of-pipe treatment systems or following release during CSO events. Sampling was performed across the hydrograph for three storm events as well as during baseflow and wet weather in three surface waters impacted by CSO. qPCR was performed for sele ...[more]

PMID: 29104562

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Project description:BackgroundCombined sewer overflows (CSOs) discharge untreated sewage into surface and recreational water, often following heavy precipitation. Given projected increases in frequency and intensity of precipitation due to climate change, it is important to understand the health impacts of CSOs and mediating effects of sewerage systems.ObjectivesIn this study we estimate associations of CSO events and emergency department (ED) visits for gastrointestinal (GI) illness among City of Atlanta, Georgia, residents and explore how these associations vary with sewerage improvements.MethodsWe estimate associations using Poisson generalized linear models, controlling for time trends. We categorized CSOs by overflow volume and assessed effects of CSO events prior to ED visits with 1-, 2- and 3-wk lags. Similarly, we evaluated effects of weekly cumulative precipitation greater than the 90th percentile at the same lags. We also evaluated effect modification by ZIP Code Tabulation Area (ZCTA)-level poverty and infrastructure improvement period using interaction terms.ResultsOccurrence of a large volume CSO in the previous week was associated with a 9% increase in daily ED visits for GI illness. We identified significant interaction by ZCTA-level poverty, with stronger CSO-GI illness associations in low than high poverty areas. Among areas with low poverty, we observed associations at 1-wk and longer lags, following both large and lower volume CSO events. We did not observe significant interaction by infrastructure improvement period for CSO- nor precipitation-GI illness associations; however, the number of CSO events decreased from 2.31 per week before improvements to 0.49 after improvements.DiscussionOur findings suggest that CSOs contribute to acute GI illness burden in Atlanta and that the magnitude of this risk may be higher among populations living in areas of low poverty. We did not find a protective effect of sewerage system improvements. Nonetheless, observed reductions in CSO frequency may lower the absolute burden of GI illness attributable to these events. https://doi.org/10.1289/EHP10399.

Project description:Water bodies that serve as sources of drinking or recreational water are routinely monitored for fecal indicator bacteria (FIB) by state and local agencies. Exceedances of monitoring thresholds set by those agencies signal likely elevated human health risk from exposure, but FIB give little information about the potential source of contamination. To improve our understanding of how within-day variation could impact monitoring data interpretation, we conducted a study at two sites along the Chattahoochee River that varied in their recreational usage and adjacent land-use (natural versus urban), collecting samples every 30 min over one 24-h period. We assayed for three types of microbial indicators: FIB (total coliforms and Escherichia coli); human fecal-associated microbial source tracking (MST) markers (crAssphage and HF183/BacR287); and a suite of clinically relevant antibiotic resistance genes (ARGs; blaCTX-M, blaCMY, MCR, KPC, VIM, NDM) and a gene associated with antibiotic resistance (intl1). Mean levels of FIB and clinically relevant ARGs (blaCMY and KPC) were similar across sites, while MST markers and intI1 occurred at higher mean levels at the natural site. The human-associated MST markers positively correlated with antibiotic resistant-associated genes at both sites, but no consistent associations were detected between culturable FIB and any molecular markers. For all microbial indicators, generalized additive mixed models were used to examine diurnal variability and whether this variability was associated with environmental factors (water temperature, turbidity, pH, and sunlight). We found that FIB peaked during morning and early afternoon hours and were not associated with environmental factors. With the exception of HF183/BacR287 at the urban site, molecular MST markers and intI1 exhibited diurnal variability, and water temperature, pH, and turbidity were significantly associated with this variability. For blaCMY and KPC, diurnal variability was present but was not correlated with environmental factors. These results suggest that differences in land use (natural or urban) both adjacent and upstream may impact overall levels of microbial contamination. Monitoring agencies should consider matching sample collection times with peak levels of target microbial indicators, which would be in the morning or early afternoon for the fecal associated indicators. Measuring multiple microbial indicators can lead to clearer interpretations of human health risk associated with exposure to contaminated water.

Dataset Information

Partitioning of Antibiotic Resistance Genes and Fecal Indicators Varies Intra and Inter-Storm during Combined Sewer Overflows.

Publications

Partitioning of Antibiotic Resistance Genes and Fecal Indicators Varies Intra and Inter-Storm during Combined Sewer Overflows.

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