Using a combination of quantitative culture, molecular, and infrastructure data to rank potential sources of fecal contamination in Town Creek Estuary, North Carolina.

Estuarine water quality is declining worldwide due to increased tourism, coastal development, and a changing climate. Although well-established methods are in place to monitor water quality, municipalities struggle to use the data to prioritize infrastructure for monitoring and repair and to determine sources of contamination when they occur. The objective of this study was to assess water quality and prioritize sources of contamination within Town Creek Estuary (TCE), Beaufort, North Carolina, by combining culture, molecular, and geographic information systems (GIS) data into a novel contamination source ranking system. Water samples were collected from TCE at ten locations on eight sampling dates in Fall 2021 (n = 80). Microbiological water quality was assessed using US Environmental Protection Agency (U.S. EPA) approved culture-based methods for fecal indicator bacteria (FIB), including analysis of total coliforms (TC), Escherichia coli (EC), and Enterococcus spp. (ENT). The quantitative microbial source tracking (qMST) human-associated fecal marker, HF183, was quantified using droplet digital PCR (ddPCR). This information was combined with environmental data and GIS information detailing proximal sewer, septic, and stormwater infrastructure to determine potential sources of fecal contamination in the estuary. Results indicated FIB concentrations were significantly and positively correlated with precipitation and increased throughout the estuary following rainfall events (p < 0.01). Sampling sites with FIB concentrations above the U.S. EPA threshold also had the highest percentages of aged, less durable piping materials. Using a novel ranking system combining concentrations of FIB, HF183, and sewer infrastructure data at each site, we found that the two sites nearest the most aged sewage infrastructure and stormwater outflows were found to have the highest levels of measurable fecal contamination. This case study supports the inclusion of both traditional water quality measurements and local infrastructure data to support the current need for municipalities to identify, prioritize, and remediate failing infrastructure.

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.

Evaluating the impact of sample storage, handling, and technical ability on the decay and recovery of SARS-CoV-2 in wastewater.

Wastewater based epidemiology (WBE) is useful for tracking and monitoring the level of disease prevalence in a community and has been used extensively to complement clinical testing during the current COVID-19 pandemic. Despite the numerous benefits, sources of variability in sample storage, handling, and processing methods can make WBE data difficult to generalize. We performed an experiment to determine sources of variability in WBE data including the impact of storage time, handling, and processing techniques on the concentration of SARS-CoV-2 in wastewater influent from three wastewater treatment plants (WWTP) in North Carolina over 19 days. The SARS-CoV-2 concentration in influent samples held at 4°C did not degrade significantly over the 19-day experiment. Heat pasteurization did not significantly impact the concentration of SARS-CoV-2 at two of the three WWTP but did reduce viral recovery at the WWTP with the smallest population size served. On each processing date, one filter from each sample was processed immediately while a replicate filter was frozen at -80°C. Once processed, filters previously frozen were found to contain slightly higher concentrations (<0.2 log copies/L) than their immediately processed counterparts, indicating freezing filters is a viable method for delayed quantification and may even improve recovery at WWTP with low viral concentrations. Investigation of factors contributing to variability during sample processing indicated that analyst experience level contributed significantly (p<0.001) to accepted droplet generation while extraction efficiency and reverse transcription efficiency contributed significantly (p<0.05) to day-to-day SARS-CoV-2 variability. This study provides valuable practical information for minimizing decay and/or loss of SARS CoV-2 in wastewater influent while adhering to safety procedures, promoting efficient laboratory workflows, and accounting for sources of variability.

Recycled concrete aggregates are an economic form of urban riparian erosion management with limited impacts on freshwater chemistry and microbial diversity.

Urban streams are at high risk of riparian erosion which impacts adjacent infrastructure stability. Methods to prevent stream erosion have been proposed including using recycled concrete (RC) materials to help stabilize the streambed; however, little is known about the environmental and biological impacts of using RC in urban streams. RC, new concrete (NC), and river rock controls were evaluated for their impact on water chemistry, water quality, and microbial community composition over 6.5 months in controlled laboratory mesocosms. Concentrations of 19 metals, nutrients, and pH of mesocosms containing RC were not significantly different from the river rock mesocosm throughout the experiment; however, NC mesocosms contained significantly higher (p < 0.05) concentrations of Co, As, Al, and V in mesocosm water samples compared to both RC and the river rock control. Microbial community diversity was not significantly impacted by mesocosm treatment. Microbial sequences mapping to taxa including Rhodoferax, Acidovorax, Nitrosomonas, and Novosphingobium were significantly more abundant (p < 0.01) in RC and NC mesocosm samples; however, the overall microbial community structure was similar across treatment types. Results from this study suggest that RC does not significantly alter the stream environment including microbial community diversity and is a viable option for use in stream restoration projects.

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.

Similarities in Virulence and Extended Spectrum Beta-Lactamase Gene Profiles among Cefotaxime-Resistant Escherichia coli Wastewater and Clinical Isolates.

The World Health Organization has identified antibiotic resistance as one of the largest threats to human health and food security. In this study, we compared antibiotic resistance patterns between ESBL-producing Escherichia coli from human clinical diseases and cefotaxime-resistant environmental strains, as well as their potential to be pathogenic. Antibiotic susceptibility was tested amongst clinical isolates (n = 11), hospital wastewater (n = 22), and urban wastewater (n = 36, both influent and treated effluents). Multi-drug resistance predominated (>70%) among hospitalwastewater and urban wastewater influent isolates. Interestingly, isolates from clinical and urban treated effluents showed similar multi-drug resistance rates (~50%). Most hospital wastewater isolates were Phylogroup A, while clinical isolates were predominately B2, with a more diverse phylogroup population in urban wastewater. ESBL characterization of cefotaxime-resistant populations identified blaCTX-M-1 subgroup as the most common, whereby blaKPC was more associated with ceftazidime and ertapenem resistance. Whole-genome sequencing of a carbapenemase-producing hospital wastewater E. coli strain revealed plasmid-mediated blaKPC-2. Among cefotaxime-resistant populations, over 60% of clinical and 30% of treated effluent E. coli encoded three or more virulence genes exhibiting a pathogenic potential. Together, the similarity among treated effluent E. coli populations and clinical strains suggest effluents could serve as a reservoir for future multi-drug resistant E. coli clinical infections.

Manure derived nutrients alter microbial community composition and increase the presence of potential pathogens in freshwater sediment.

AIM: To determine the impact of an acute, pulse disturbance of nutrients from manure on freshwater sediment microbiomes in an experimental system. METHODS AND RESULTS: A controlled freshwater mesocosm experiment was designed to compare the effect of disturbance from nutrients derived from sterile manure (SM), disturbance from equivalent concentrations of laboratory-derived nutrients, and a nondisturbed control on freshwater sediment microbial community composition and function using 16S rRNA amplicon sequencing. Sediment microbiomes impacted by nutrients from SM showed no sign of compositional recovery after 28 days but those impacted by laboratory-derived chemicals lead to a new steady-state (p < 0.05). Carbon and nitrate sources within disturbed mesocosms were the primary drivers of altered microbial community composition. Additionally, multiple potential pathogens (based on exact sequence matching at the species level) were enriched in mesocosms treated with SM. CONCLUSIONS: Nutrient disturbance from SM, in the absence of the manure microbial community, alters the microbiome of sediments without recovery after 28 days and enriches potential pathogens. SIGNIFICANCE AND IMPACT OF THE STUDY: These results suggest manure land application practices should be re-evaluated to account for impact of nutrient disturbance on environmental microbiomes in addition to the impact of the manure microbial community.

Microbial Find, Inform, and Test Model for Identifying Spatially Distributed Contamination Sources: Framework Foundation and Demonstration of Ruminant Bacteroides Abundance in River Sediments.

Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) markers help to assess the microbial risks by linking hosts to contamination but do not identify the source locations. Land-use regression (LUR) models have been used to screen the source locations using spatial predictors but could be improved by characterizing transport (i.e., hauling, decay overland, and downstream). We introduce the microbial Find, Inform, and Test (FIT) framework, which expands previous LUR approaches and develops novel spatial predictor models to characterize the transported contributions. We applied FIT to characterize the sources of BoBac, a ruminant Bacteroides MST marker, quantified in riverbed sediment samples from Kewaunee County, Wisconsin. A 1 standard deviation increase in contributions from land-applied manure hauled from animal feeding operations (AFOs) was associated with a 77% (p-value <0.05) increase in the relative abundance of ruminant Bacteroides (BoBac-copies-per-16S-rRNA-copies) in the sediment. This is the first work finding an association between the upstream land-applied manure and the offsite bovine-associated fecal markers. These findings have implications for the sediment as a reservoir for microbial pollution associated with AFOs (e.g., pathogens and antibiotic-resistant bacteria). This framework and application advance statistical analysis in MST and water quality modeling more broadly.

Freshwater Sediment Microbial Communities Are Not Resilient to Disturbance From Agricultural Land Runoff.

Microorganisms are critically important for the function of surface water ecosystems but are frequently subjected to anthropogenic disturbances at either acute (pulse) or long-term (press) scales. Response and recovery of microbial community composition and function following pulse disturbance is well-studied in controlled, laboratory scale experiments but is less well-understood in natural environments undergoing continual press disturbance. The objectives of this study were to determine the drivers of sediment microbial compositional and functional changes in freshwaters receiving continual press disturbance from agricultural land runoff and to evaluate the ability of the native microbial community to resist disturbance related changes as a proxy for freshwater ecosystem health. Freshwater sediments were collected seasonally over 1 year in Kewaunee County, Wisconsin, a region impacted by concentrated dairy cattle farming, manure fertilization, and associated agricultural runoff which together serve as a press disturbance. Using 16S rRNA gene amplicon sequencing, we found that sediments in locations strongly impacted by intensive agriculture contain significantly higher abundances (p < 0.01) of the genera Thiobacillus, Methylotenera, Crenotrhix, Nitrospira, and Rhodoferax compared to reference sediments, and functions including nitrate reduction, nitrite reduction, and nitrogen respiration are significantly higher (p < 0.05) at locations in close proximity to large farms. Nine species-level potential human pathogens were identified in riverine sediments including Acinetobacer lwoffi and Arcobacter skirrowii, two pathogens associated with the cattle microbiome. Microbial community composition at locations in close proximity to intensive agriculture was not resistant nor resilient to agricultural runoff disturbance within 5 months post-disturbance but did reach a new, stable microbial composition. From this data, we conclude that sediment microbial community composition is sensitive and shifts in response to chemical and microbial pollution from intensive agriculture, has a low capacity to resist infiltration by non-native, harmful bacteria and, overall, the natural buffering capacity of freshwater ecosystems is unable to fully resist the impacts from agricultural press disturbance.

Survivor microbial populations in post-chlorinated wastewater are strongly associated with untreated hospital sewage and include ceftazidime and meropenem resistant populations.

Wastewater treatment plant (WWTP) effluent has been implicated in the spread of antibiotic resistant bacteria (ARB), including pathogens, as the WWTP environment contains multiple selective pressures that may increase mutation rates, pathogen survivability, and induce gene transfer between bacteria. In WWTPs receiving hospital sewage, this selective effect may be more pronounced due to increased concentrations of antibiotics, ARB, and clinical pathogens from hospital sewage. To determine the extent to which hospital sewage contributes to the microbial community of disinfected wastewater which is released into the environment, we used 16S rRNA sequencing of hospital sewage, WWTP influent, primary effluent, Post-Chlorinated Effluent, and receiving sediments in a combined sewage system to track changes in microbial community composition. We also sequenced the culturable survivor community resistant to ß-lactam antibiotics within disinfected effluent. Using molecular source tracking, we found that the hospital sewage microbiome contributes an average of 11.49% of the microbial community in Post-Chlorinated Effluents, suggesting microorganisms identified within hospital sewage can survive or are enriched by the chlorination disinfection process. Additionally, we identified 28 potential pathogens to the species level, seven of which remained detectable in Post-Chlorinated Effluent and environmental sediments. When Post-Chlorinated Effluents were cultured on media containing ß-lactam antibiotics ceftazidime and meropenem, a diverse antibiotic resistant survivor community was identified including potential human pathogens Bacillus cereus, Bacillus pumilus, and Chryseobacterium indologenes. Together, these results indicate that although wastewater treatment does significantly reduce pathogenic loads and ARBs, their continual presence in disinfected wastewater and receiving sediments suggests additional treatment and microbial tracking systems are needed to reduce human and animal health risks.

Antimicrobial Resistance Traits of Escherichia coli Isolated from Dairy Manure and Freshwater Ecosystems Are Similar to One Another but Differ from Associated Clinical Isolates.

Antimicrobial resistance (AMR) is a prevalent global health problem across human and veterinary medicine. The One Health approach to AMR is necessary to mitigate transmission between sources of resistance and decrease the spread of resistant bacteria among humans, animals, and the environment. Our primary goal was to identify associations in resistance traits between Escherichia coli isolated from clinical (n = 103), dairy manure (n = 65), and freshwater ecosystem (n = 64) environments within the same geographic location and timeframe. Clinical E. coli isolates showed the most phenotypic resistance (47.5%), followed by environmental isolates (15.6%) and manure isolates (7.7%), with the most common resistances to ampicillin, ampicillin-sulbactam, and cefotaxime antibiotics. An isolate subset was screened for extended spectrum beta-lactamase (ESBL) production resulting in the identification of 35 ESBL producers. The most common ESBL gene identified was blaTEM-1. Additionally, we found nine different plasmid replicon types including IncFIA-FIB, which were frequently associated with ESBL producer isolates. Molecular phylotyping revealed a significant portion of clinical E. coli were associated with phylotype B2, whereas manure and environmental isolates were more diverse. Manure and environmental isolates were significantly different from clinical isolates based on analyzed traits, suggesting more transmission occurs between these two sources in the sampled environment.

Agricultural contamination impacts antibiotic resistance gene abundances in river bed sediment temporally.

Kewaunee County, Wisconsin is an agricultural area dominated by concentrated animal feeding operations and manure fertilized cropland. The objective of this study was to characterize chemical and antibiotic resistance gene (ARG) profiles of 20 surface water locations in Kewaunee County to better understand relationships between agricultural contamination and ARG abundance over one year. Surface water (n = 101) and bed sediment (n = 93) were collected from 20 sites during five timepoints between July 2016 and May 2017. Samples were analyzed for six genes (erm(B), tet(W), sul1, qnrA, intI1 and 16S rRNA) and water chemistry and pollution indicators. qnrA, intI1 and sul1 genes in surface water were significantly higher than erm(B) and tet(W); however, no difference was present in sediment samples. Redundancy analysis identified positive correlations of nitrate, Escherichia coli, and coliforms with tet(W) and intI1 genes in sediment and intI1, sul1 and tet(W) genes in water. Temporal patterns of ARG abundance were identified with significantly higher gene abundances found in sediment during Kewaunee County's manure fertilization period; however, surface water patterns were not distinct. Together, these results suggest Kewaunee County sediments serve as a site of accumulation for non-point source agricultural pollution and ARGs on a temporal scale associated with manure fertilization.

Quantitative analysis of the extent of heavy-metal contamination in soils near Picher, Oklahoma, within the Tar Creek Superfund Site.

The Tri-State Mining District of Missouri, Kansas and Oklahoma was the site of large-scale mining operations primarily for lead and zinc until the mid-1950s. Although mining across the area has ceased, high concentrations of heavy metals remain in the region's soil and water systems. The town of Picher, Ottawa County, OK, lies within this district and was included in the Tar Creek Superfund Site by the U.S. Environmental Protection Agency in 1980 due to extensive contamination. To elucidate the extent of heavy-metal contamination, a soil-chemistry survey of the town of Picher was conducted. Samples (n = 111) were collected from mine tailings, locally known as chat, in Picher and along cardinal-direction transects within an 8.05-km radius of the town in August 2015. Samples were analyzed for soil pH, moisture, and metal content. Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) analyses of 20 metals showed high concentrations of lead (>1000 ppm), cadmium (>40 ppm) and zinc (>4000 ppm) throughout the sampled region. Soil moisture content ranged from 0.30 to 35.9%, and pH values ranged from 5.14 to 7.42. MANOVA of metal profiles determined that soils collected from the north transect and chat were significantly different (p < 0.01) than other sampled directions. Lead, cadmium and zinc were correlated with one another. These data show an unequal distribution of contamination surrounding the Picher mining site. Mapping heavy-metal contamination in these soils represents the first step in understanding the distribution of these contaminants at the Picher mining site.