Quantitative Microbial Risk Assessment for Contaminated Private Wells in the Fractured Dolomite Aquifer of Kewaunee County, Wisconsin

Quantitative microbial risk assessment for ingestion of antibiotic resistance genes from private wells contaminated by human and livestock fecal sources

We used quantitative microbial risk assessment to estimate ingestion risk for intI1, erm(B), sul1, tet(A), tet(W), and tet(X) in private wells contaminated by human and/or livestock feces. Genes were quantified with five human-specific and six bovine-specific microbial source-tracking (MST) markers in 138 well-water samples from a rural Wisconsin county. Daily ingestion risk (probability of swallowing ≥1 gene) was based on daily water consumption and a Poisson exposure model. Calculations were stratified by MST source and soil depth over the aquifer where wells were drilled. Relative ingestion risk was estimated using wells with no MST detections and >6.1 m soil depth as a referent category. Daily ingestion risk varied from 0 to 8.8 × 10-1 by gene and fecal source (i.e., human or bovine). The estimated number of residents ingesting target genes from private wells varied from 910 (tet(A)) to 1,500 (intI1 and tet(X)) per day out of 12,000 total. Relative risk of tet(A) ingestion was significantly higher in wells with MST markers detected, including wells with ≤6.1 m soil depth contaminated by bovine markers (2.2 [90% CI: 1.1-4.7]), wells with >6.1 m soil depth contaminated by bovine markers (1.8 [1.002-3.9]), and wells with ≤6.1 m soil depth contaminated by bovine and human markers simultaneously (3.1 [1.7-6.5]). Antibiotic resistance genes (ARGs) were not necessarily present in viable microorganisms, and ingestion is not directly associated with infection. However, results illustrate relative contributions of human and livestock fecal sources to ARG exposure and highlight rural groundwater as a significant point of exposure.IMPORTANCEAntibiotic resistance is a global public health challenge with well-known environmental dimensions, but quantitative analyses of the roles played by various natural environments in transmission of antibiotic resistance are lacking, particularly for drinking water. This study assesses risk of ingestion for several antibiotic resistance genes (ARGs) and the class 1 integron gene (intI1) in drinking water from private wells in a rural area of northeast Wisconsin, United States. Results allow comparison of drinking water as an exposure route for antibiotic resistance relative to other routes like food and recreational water. They also enable a comparison of the importance of human versus livestock fecal sources in the study area. Our study demonstrates the previously unrecognized importance of untreated rural drinking water as an exposure route for antibiotic resistance and identifies bovine fecal material as an important exposure factor in the study setting.

Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework

Introduction

Antimicrobial resistance (AMR) is an increasing public health concern for humans, animals, and the environment. However, the contributions of spatially distributed sources of AMR in the environment are not well defined.

Methods

To identify the sources of environmental AMR, the novel microbial Find, Inform, and Test (FIT) model was applied to a panel of five antibiotic resistance-associated genes (ARGs), namely, erm(B), tet(W), qnrA, sul1, and intI1, quantified from riverbed sediment and surface water from a mixed-use region.

Results

A one standard deviation increase in the modeled contributions of elevated AMR from bovine sources or land-applied waste sources [land application of biosolids, sludge, and industrial wastewater (i.e., food processing) and domestic (i.e., municipal and septage)] was associated with 34-80% and 33-77% increases in the relative abundances of the ARGs in riverbed sediment and surface water, respectively. Sources influenced environmental AMR at overland distances of up to 13 km.

Discussion

Our study corroborates previous evidence of offsite migration of microbial pollution from bovine sources and newly suggests offsite migration from land-applied waste. With FIT, we estimated the distance-based influence range overland and downstream around sources to model the impact these sources may have on AMR at unsampled sites. This modeling supports targeted monitoring of AMR from sources for future exposure and risk mitigation efforts.

Prevalence and whole-genome sequencing characterization of Salmonella in urban karst groundwater and predominantly groundwater-fed surface waters for serotypes and antimicrobial resistance

Karst aquifers provide a significant source of drinking water around the world; however, they are prone to bacterial contamination. We investigated the prevalence, serotypes, and antimicrobial resistance genes (ARGs) of Salmonella in urban karst groundwater and groundwater-fed surface waters. Weekly water samples (n = 443) were collected from nine groundwater sites and the Barren River in Bowling Green, KY. Additionally, cross-sectional samples were collected from 45 sites, including groundwaters and two rivers, in Tampa, FL. Salmonella was detected in 14.5% of Bowling Green samples resulting in 176 isolates representing 18 serotypes. Two (4.4%) of the Tampa samples were positive yielding eight isolates representing two serotypes. In Bowling Green, Salmonella prevalence varied by sampling site, week, month, and season, with the highest prevalence in surface water in the month of November and during summer. Salmonella Newport was the most common serotype detected. Nine of the serotypes detected in the study were among the top 20 serotypes commonly associated with human infections in the United States. Isolates were clustered with human clinical isolates, or isolates obtained from food animals, suggesting the importance of humans and agricultural practices as a source of water contamination. ARGs were detected in 12.5% (n = 176) of the Bowling Green isolates; overall, 81.8% (n = 22) of these were multidrug-resistant (resistance to ≥3 antimicrobial classes). Notably, the four Salmonella Agona isolates were resistant to four antimicrobial classes, mercury, and quaternary ammonium compounds. Seasonality and the widespread occurrence of Salmonella both in the groundwater and groundwater-fed surface waters is a potential risk to public health.

Producing ratio measures of effect with quantitative microbial risk assessment

Estimating the risk of infections or other outcomes incident to pathogen exposure is a primary goal of quantitative microbial risk assessment (QMRA). Such estimates are useful to predict population-level risks, to evaluate exposures based on normative or tolerable risk guidelines, and to interpret the likely public health relevance of microbial measurements in environmental media. To evaluate alternative control measures (interventions), ratio estimates of effect (e.g., odds and risk ratios) are needed that are more broadly interpretable in the health sciences and consistent with convention in epidemiology. In this paper, we propose a general method for estimating widely used ratio measures of effect derived from stochastic QMRA approaches, including the generation of appropriate confidence intervals. Such QMRA-derived ratios can be used as a basis for evaluating interventions via hypothesis testing and for inclusion in systematic reviews and meta-analyses in a form consistent with risk estimation approaches commonly used in epidemiology.

Producing ratio measures of effect with quantitative microbial risk assessment

Estimating the risk of infections or other outcomes incident to pathogen exposure is a primary goal of quantitative microbial risk assessment (QMRA). Such estimates are useful to predict population-level risks, to evaluate exposures based on normative or tolerable risk guidelines, and to interpret the likely public health relevance of microbial measurements in environmental media. To evaluate alternative control measures (interventions), ratio estimates of effect (e.g., odds and risk ratios) are needed that are more broadly interpretable in the health sciences and consistent with convention in epidemiology. In this paper, we propose a general method for estimating widely used ratio measures of effect derived from stochastic QMRA approaches, including the generation of appropriate confidence intervals. Such QMRA-derived ratios can be used as a basis for evaluating interventions via hypothesis testing and for inclusion in systematic reviews and meta-analyses in a form consistent with risk estimation approaches commonly used in epidemiology.

Juxtaposition of intensive agriculture, vulnerable aquifers, and mixed chemical/microbial exposures in private-well tapwater in northeast Iowa

In the United States and globally, contaminant exposure in unregulated private-well point-of-use tapwater (TW) is a recognized public-health data gap and an obstacle to both risk-management and homeowner decision making. To help address the lack of data on broad contaminant exposures in private-well TW from hydrologically-vulnerable (alluvial, karst) aquifers in agriculturally-intensive landscapes, samples were collected in 2018-2019 from 47 northeast Iowa farms and analyzed for 35 inorganics, 437 unique organics, 5 in vitro bioassays, and 11 microbial assays. Twenty-six inorganics and 51 organics, dominated by pesticides and related transformation products (35 herbicide-, 5 insecticide-, and 2 fungicide-related), were observed in TW. Heterotrophic bacteria detections were near ubiquitous (94 % of the samples), with detection of total coliform bacteria in 28 % of the samples and growth on at least one putative-pathogen selective media across all TW samples. Health-based hazard index screening levels were exceeded frequently in private-well TW and attributed primarily to inorganics (nitrate, uranium). Results support incorporation of residential treatment systems to protect against contaminant exposure and the need for increased monitoring of rural private-well homes. Continued assessment of unmonitored and unregulated private-supply TW is needed to model contaminant exposures and human-health risks.

Study design and methods of the Wells and Enteric disease Transmission (WET) Trial: a randomised controlled trial

INTRODUCTION

The burden of disease attributed to drinking water from private wells is not well characterised. The Wells and Enteric disease Transmission trial is the first randomised controlled trial to estimate the burden of disease that can be attributed to the consumption of untreated private well water. To estimate the attributable incidence of gastrointestinal illness (GI) associated with private well water, we will test if the household treatment of well water by ultraviolet light (active UV device) versus sham (inactive UV device) decreases the incidence of GI in children under 5 years of age.

METHODS AND ANALYSIS

The trial will enrol (on a rolling basis) 908 families in Pennsylvania, USA, that rely on private wells and have a child 3 years old or younger. Participating families are randomised to either an active whole-house UV device or a sham device. During follow-up, families will respond to weekly text messages to report the presence of signs and symptoms of gastrointestinal or respiratory illness and will be directed to an illness questionnaire when signs/symptoms are present. These data will be used to compare the incidence of waterborne illness between the two study groups. A randomly selected subcohort submits untreated well water samples and biological specimens (stool and saliva) from the participating child in both the presence and absence of signs/symptoms. Samples are analysed for the presence of common waterborne pathogens (stool and water) or immunoconversion to these pathogens (saliva).

ETHICS

Approval has been obtained from Temple University's Institutional Review Board (Protocol 25665). The results of the trial will be published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04826991.

Microbial source tracking and land use associations for antibiotic resistance genes in private wells influenced by human and livestock fecal sources

Antimicrobial resistance is a growing public health problem that requires an integrated approach among human, agricultural, and environmental sectors. However, few studies address all three components simultaneously. We investigated the occurrence of five antibiotic resistance genes (ARGs) and the class 1 integron gene (intI1) in private wells drawing water from a vulnerable aquifer influenced by residential septic systems and land-applied dairy manure. Samples (n = 138) were collected across four seasons from a randomized sample of private wells in Kewaunee County, Wisconsin. Measurements of ARGs and intI1 were related to microbial source tracking (MST) markers specific to human and bovine feces; they were also related to 54 risk factors for contamination representing land use, rainfall, hydrogeology, and well construction. ARGs and intI1 occurred in 5%-40% of samples depending on target. Detection frequencies for ARGs and intI1 were lowest in the absence of human and bovine MST markers (1%-30%), highest when co-occurring with human and bovine markers together (11%-78%), and intermediate when co-occurring with just one type of MST marker (4%-46%). Gene targets were associated with septic system density more often than agricultural land, potentially because of the variable presence of manure on the landscape. Determining ARG prevalence in a rural setting with mixed land use allowed an assessment of the relative contribution of human and bovine fecal sources. Because fecal sources co-occurred with ARGs at similar rates, interventions intended to reduce ARG occurrence may be most effective if both sources are considered.

Perennial grassland agriculture restores critical ecosystem functions in the U.S. Upper Midwest

Dominant forms of agricultural production in the U.S. Upper Midwest are undermining human health and well being. Restoring critical ecosystem functions to agriculture is key to stabilizing climate, reducing flooding, cleaning water, and enhancing biodiversity. We used simulation models to compare ecosystem functions (food-energy production, nutrient retention, and water infiltration) provided by vegetation associated with continuous corn, corn-soybean rotation, and perennial grassland producing feed for dairy livestock. Compared to continuous corn, most ecosystem functions dramatically improved in the perennial grassland system (nitrate leaching reduced ~90%, phosphorus loss reduced ~88%, drainage increased ~25%, evapotranspiration reduced ~29%), which will translate to improved ecosystem services. Our results emphasize the need to incentivize multiple ecosystem services when managing agricultural landscapes.

An Overview of Microbial Source Tracking Using Host-Specific Genetic Markers to Identify Origins of Fecal Contamination in Different Water Environments

Fecal contamination of water constitutes a serious health risk to humans and environmental ecosystems. This is mainly due to the fact that fecal material carries a variety of enteropathogens, which can enter and circulate in water bodies through fecal pollution. In this respect, the prompt identification of the polluting source(s) is pivotal to guiding appropriate target-specific remediation actions. Notably, microbial source tracking (MST) is widely applied to determine the host origin(s) contributing to fecal water pollution through the identification of zoogenic and/or anthropogenic sources of fecal environmental DNA (eDNA). A wide array of host-associated molecular markers have been developed and exploited for polluting source attribution in various aquatic ecosystems. This review is intended to provide the most up-to-date overview of genetic marker-based MST studies carried out in different water types, such as freshwaters (including surface and groundwaters) and seawaters (from coasts, beaches, lagoons, and estuaries), as well as drinking water systems. Focusing on the latest scientific progress/achievements, this work aims to gain updated knowledge on the applicability and robustness of using MST for water quality surveillance. Moreover, it also provides a future perspective on advancing MST applications for environmental research.

Statewide Quantitative Microbial Risk Assessment for Waterborne Viruses, Bacteria, and Protozoa in Public Water Supply Wells in Minnesota

Infection risk from waterborne pathogens can be estimated via quantitative microbial risk assessment (QMRA) and forms an important consideration in the management of public groundwater systems. However, few groundwater QMRAs use site-specific hazard identification and exposure assessment, so prevailing risks in these systems remain poorly defined. We estimated the infection risk for 9 waterborne pathogens based on a 2-year pathogen occurrence study in which 964 water samples were collected from 145 public wells throughout Minnesota, USA. Annual risk across all nine pathogens combined was 3.3 × 10^-1 (95% CI: 2.3 × 10^-1 to 4.2 × 10^-1), 3.9 × 10^-2 (2.3 × 10^-2 to 5.4 × 10^-2), and 1.2 × 10^-1 (2.6 × 10^-2 to 2.7 × 10^-1) infections person^-1 year^-1 for noncommunity, nondisinfecting community, and disinfecting community wells, respectively. Risk estimates exceeded the U.S. benchmark of 10^-4 infections person^-1 year^-1 in 59% of well-years, indicating that the risk was widespread. While the annual risk for all pathogens combined was relatively high, the average daily doses for individual pathogens were low, indicating that significant risk results from sporadic pathogen exposure. Cryptosporidium dominated annual risk, so improved identification of wells susceptible to Cryptosporidium contamination may be important for risk mitigation.

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework

Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water. Thus, we implemented the newly developed microbial find, inform, and test framework to identify spatial sources and their impacts on human (HuBac) and bovine (BoBac) MST markers, quantified from both riverbed sediment and surface water in a bovine-dense region. Dairy feeding operations and low-intensity developed land-cover were associated with 99% (p-value < 0.05) and 108% (p-value < 0.05) increases, respectively, in the relative abundance of BoBac in sediment, and with 79% (p-value < 0.05) and 39% increases in surface water. Septic systems were associated with a 48% increase in the relative abundance of HuBac in sediment and a 56% increase in surface water. Stronger source signals were observed for sediment responses compared to water. By defining source locations, predicting river impacts, and estimating source influence ranges in a Great Lakes region, this work informs pollution mitigation strategies of local and global significance.