Microbial source tracking: state of the science

Urban stormwater green infrastructure: Evaluating the public health service role of bioretention using microbial source tracking and bacterial community analyses

Bioretention cells (BRCs) control stormwater flow on-site during precipitation, reducing runoff and improving water quality through chemical, physical, and biological processes. While BRCs are effective in these aspects, they provide habitats for wildlife and may face microbial hazards from fecal shedding, posing a potential threat to human health and the nearby environment. However, limited knowledge exists regarding the ability to control microbial hazards (e.g., beyond using typical indicator bacteria) through stormwater biofiltration. Therefore, the purpose of this study is to characterize changes in the bacterial community of urban stormwater undergoing bioretention treatment, with the goal of assessing the public health implications of these green infrastructure solutions. Samples from BRC inflow and outflow in Columbus, Ohio, were collected post-heavy storms from October 2021 to March 2022. Conventional culture-based E. coli monitoring and microbial source tracking (MST) were conducted to identify major fecal contamination extent and its sources (i.e., human, canine, avian, and ruminant). Droplet digital polymerase chain reaction (ddPCR) was utilized to quantify the level of host-associated fecal contamination in addition to three antibiotic resistant genes (ARGs): tetracycline resistance gene (tetQ), sulfonamide resistance gene (sul1), and Klebsiella pneumoniae carbapenemase resistance gene (blaKPC). Subsequently, 16S rRNA gene sequencing was conducted to characterize bacterial community differences between stormwater BRC inflow and outflow. Untreated urban stormwater reflects anthropogenic contamination, suggesting it as a potential source of contamination to waterbodies and urban environments. When comparing inlet and outlet BRC samples, urban stormwater treated via biofiltration did not increase microbial hazards, and changes in bacterial taxa and alpha diversity were negligible. Beta diversity results reveal a significant shift in bacterial community structure, while simultaneously enhancing the water quality (i.e., reduction of metals, total suspended solids, total nitrogen) of urban stormwater. Significant correlations were found between the bacterial community diversity of urban stormwater with fecal contamination (e.g. dog) and ARG (sul1), rainfall intensity, and water quality (hardness, total phosphorous). The study concludes that bioretention technology can sustainably maintain urban microbial water quality without posing additional public health risks, making it a viable green infrastructure solution for heavy rainfall events exacerbated by climate change.

Towards more accurate microbial source tracking via non-negative matrix factorization (NMF)

MOTIVATION

The microbiome of a sampled habitat often consists of microbial communities from various sources, including potential contaminants. Microbial source tracking (MST) can be used to discern the contribution of each source to the observed microbiome data, thus enabling the identification and tracking of microbial communities within a sample. Therefore, MST has various applications, from monitoring microbial contamination in clinical labs to tracing the source of pollution in environmental samples. Despite promising results in MST development, there is still room for improvement, particularly for applications where precise quantification of each source's contribution is critical.

RESULTS

In this study, we introduce a novel tool called SourceID-NMF towards more precise microbial source tracking. SourceID-NMF utilizes a non-negative matrix factorization (NMF) algorithm to trace the microbial sources contributing to a target sample. By leveraging the taxa abundance in both available sources and the target sample, SourceID-NMF estimates the proportion of available sources present in the target sample. To evaluate the performance of SourceID-NMF, we conducted a series of benchmarking experiments using simulated and real data. The simulated experiments mimic realistic yet challenging scenarios for identifying highly similar sources, irrelevant sources, unknown sources, low abundance sources, and noise sources. The results demonstrate the superior accuracy of SourceID-NMF over existing methods. Particularly, SourceID-NMF accurately estimated the proportion of irrelevant and unknown sources while other tools either over- or under-estimated them. In addition, the noise sources experiment also demonstrated the robustness of SourceID-NMF for MST.

AVAILABILITY AND IMPLEMENTATION

SourceID-NMF is available online at https://github.com/ZiyiHuang0708/SourceID-NMF.

Current status of microbial source tracking applications in constructed wetlands serving as nature-based solutions for water management and wastewater treatment

Microbial source tracking (MST) has been recognised as an effective tool for determining the origins and sources of faecal contamination in various terrestrial and aquatic ecosystems. Thus, it has been widely applied in environmental DNA (eDNA) surveys to define specific animal- and human-associated faecal eDNA. In this context, identification of and differentiation between anthropogenic and zoogenic faecal pollution origins and sources are pivotal for the evaluation of waterborne microbial contamination transport and the associated human, animal, and environmental health risks. These concerns are particularly pertinent to diverse nature-based solutions (NBS) that are being applied specifically to secure water safety and human and ecosystem well-being, for example, constructed wetlands (CWs) for water and wastewater treatment. The research in this area has undergone a constant evolution, and there is a solid foundation of publications available across the world. Hence, there is an early opportunity to synthesise valuable information and relevant knowledge on this specific topic, which will greatly benefit future work by improving NBS design and performance. By selecting 15 representative research reports published over 20 years, we review the current state of MST technology applied for faecal-associated contamination measures in NBS/CWs throughout the world.

Spatiotemporal assessment of pathogenic Leptospira in subtropical coastal watersheds

The World Health Organization classifies leptospirosis as a significant public health concern, predominantly affecting impoverished and unsanitary regions. By using the Pensacola Bay System as a case study, this study examines the underappreciated susceptibility of developed subtropical coastal ecosystems such as the Pensacola Bay System to neglected zoonotic pathogens such as Leptospira. We analyzed 132 water samples collected over 12 months from 44 distinct locations with high levels of Escherichia coli (>410 most probable number/100 mL). Fecal indicator bacteria (FIB) concentrations were assessed using IDEXX Colilert-18 and Enterolert-18, and an analysis of water physiochemical characteristics and rainfall intensity was conducted. The LipL32 gene was used as a quantitative polymerase chain reaction (qPCR) indicator to identify the distribution of Leptospira interrogans. The results revealed 12 instances of the presence of L. interrogans at sites with high FIB over various land cover and aquatic ecosystem types. Independent of specific rainfall events, a seasonal relationship between precipitation and elevated rates of fecal bacteria and leptospirosis was found. These findings highlight qPCR's utility in identifying pathogens in aquatic environments and the widespread conditions where it can be found in natural and developed areas.

New insight into identifying sediment phosphorus sources in multi-source polluted urban river: Effect of environmental-induced microbial community succession on stability of microbial source tracking results

Identifying sediment phosphorus sources, the key to control eutrophication, is hindered in multi-source polluted urban rivers by the lack of appropriate methods and data resolution. Community-based microbial source tracking (MST) offers new insight, but the bacterial communities could be affected by environmental fluctuations during the migration with sediments, which might induce instability of MST results. Therefore, the effects of environmental-induced community succession on the stability of MST were compared in this study. Liangxi River, a highly eutrophic urban river, was selected as the study area where sediment phosphorus sources are difficult to track because of multi-source pollution and complicated hydrodynamic conditions. Spearman correlation analysis (P < 0.05) was conducted to recognize a close relationship between sediment, bacterial communities and phosphorus, verifying the feasibility of MST for identify sediment phosphorus sources. Two distinct microbial community fingerprints were constructed based on whether excluded 113 vulnerable species, which were identified by analyzing the differences of microorganisms across a concentration gradient of exogenous phosphorus input in microbial environmental response experiment. Because of the lower unknown proportion and relative standard deviations, MST results were more stable and reliable when based on the fingerprints excluding species vulnerable to phosphorus. This study presents a novel insight on how to identify sediment phosphorus sources in multi-source polluted urban river, and would help to develop preferential control strategies for eutrophication management.

Village Settlements in Mountainous Tropical Areas, Hotspots of Fecal Contamination as Evidenced by Escherichia coli and Stanol Concentrations in Stormwater Pulses

Fecal bacteria in surface water may indicate threats to human health. Our hypothesis is that village settlements in tropical rural areas are major hotspots of fecal contamination because of the number of domestic animals usually roaming in the alleys and the lack of fecal matter treatment before entering the river network. By jointly monitoring the dynamics of Escherichia coli and of seven stanol compounds during four flood events (July-August 2016) at the outlet of a ditch draining sewage and surface runoff out of a village of Northern Lao PDR, our objectives were (1) to assess the range of E. coli concentration in the surface runoff washing off from a village settlement and (2) to identify the major contributory sources of fecal contamination using stanol compounds during flood events. E. coli pulses ranged from 4.7 × 104 to 3.2 × 106 most probable number (MPN) 100 mL-1, with particle-attached E. coli ranging from 83 to 100%. Major contributory feces sources were chickens and humans (about 66 and 29%, respectively), with the highest percentage switching from the human pole to the chicken pole during flood events. Concentrations indicate a severe fecal contamination of surface water during flood events and suggest that villages may be considered as major hotspots of fecal contamination pulses into the river network and thus as point sources in hydrological models.

Ecological dynamics imposes fundamental challenges in community-based microbial source tracking

Quantifying the contributions of possible environmental sources ("sources") to a specific microbial community ("sink") is a classical problem in microbiology known as microbial source tracking (MST). Solving the MST problem will not only help us understand how microbial communities were formed, but also have far-reaching applications in pollution control, public health, and forensics. MST methods generally fall into two categories: target-based methods (focusing on the detection of source-specific indicator species or chemicals); and community-based methods (using community structure to measure similarity between sink samples and potential source environments). As next-generation sequencing becomes a standard community-assessment method in microbiology, numerous community-based computational methods, referred to as MST solvers hereafter have been developed and applied to various real datasets to demonstrate their utility across different contexts. Yet, those MST solvers do not consider microbial interactions and priority effects in microbial communities. Here, we revisit the performance of several representative MST solvers. We show compelling evidence that solving the MST problem using existing MST solvers is impractical when ecological dynamics plays a role in community assembly. In particular, we clearly demonstrate that the presence of either microbial interactions or priority effects will render the MST problem mathematically unsolvable for MST solvers. We further analyze data from fecal microbiota transplantation studies, finding that the state-of-the-art MST solvers fail to identify donors for most of the recipients. Finally, we perform community coalescence experiments to demonstrate that the state-of-the-art MST solvers fail to identify the sources for most of the sinks. Our findings suggest that ecological dynamics imposes fundamental challenges in MST. Interpretation of results of existing MST solvers should be done cautiously.

Investigation of microorganisms in cannabis after heating in a commercial vaporizer

Introduction

There are concerns about microorganisms present on cannabis materials used in clinical settings by individuals whose health status is already compromised and are likely more susceptible to opportunistic infections from microbial populations present on the materials. Most concerning is administration by inhalation where cannabis plant material is heated in a vaporizer, aerosolized, and inhaled to receive the bioactive ingredients. Heating to high temperatures is known to kill microorganisms including bacteria and fungi; however, microbial death is dependent upon exposure time and temperature. It is unknown whether the heating of cannabis at temperatures and times designated by a commercial vaporizer utilized in clinical settings will significantly decrease the microbial loads in cannabis plant material.

Methods

To assess this question, bulk cannabis plant material supplied by National Institute on Drug Abuse (NIDA) was used to assess the impact of heating by a commercial vaporizer. Initial method development studies using a cannabis placebo spiked with Escherichia coli were performed to optimize culture and recovery parameters. Subsequent studies were carried out using the cannabis placebo, low delta-9 tetrahydrocannabinol (THC) potency and high THC potency cannabis materials exposed to either no heat or heating for 30 or 70 seconds at 190°C. Phosphate-buffered saline was added to the samples and the samples agitated to suspend the microorganism. Microbial growth after no heat or heating was evaluated by plating on growth media and determining the total aerobic microbial counts and total yeast and mold counts.

Results and discussion

Overall, while there were trends of reductions in microbial counts with heating, these reductions were not statistically significant, indicating that heating using standard vaporization parameters of 70 seconds at 190°C may not eliminate the existing microbial bioburden, including any opportunistic pathogens. When cultured organisms were identified by DNA sequence analyses, several fungal and bacterial taxa were detected in the different products that have been associated with opportunistic infections or allergic reactions including Enterobacteriaceae, Staphylococcus, Pseudomonas, and Aspergillus.

Metagenomic insights into environmental risk of field microplastics in an urban river

Microplastics (MPs) are emerging as anthropogenic vectors for the colonization and transportation of microbial communities in aquatic ecosystems. However, the composition of the microbiome and its environmental risk on field MPs at watershed scale has rarely been explored. Here, geographical distributions of microbiome, antibiotic resistance genes (ARGs) and virulence factors (VFs) on field MPs at watershed scale were characterized and their potential environmental risks were evaluated based on the data from metagenomic analyzes. The succession of microbial communities on MPs was observed along the watershed, and some ARGs and VFs were significantly enriched on MPs in urban region in comparison with rural region. Potential environmental risk of MPs conducted by Projection Pursuit Regression model in midstream (peri-urban region) and downstream (urban region) were significantly higher than that in upstream (rural region), and exhibit close relationships with MPs concentration and water velocity. Furthermore, our source tracking results demonstrated that the microbiome, ARGs and VFs in urban region MPs were largely derived from rural region MPs. Our results caution us that special attention should be paid to the risks posed by MPs in urban water bodies, and highlight the threat of MPs from rural upstream areas.

Revised Iranian Water Quality Index (RIWQI): a tool for the assessment and management of water quality in Iran

Water quality indices use biological, chemical, and physical data and information to classify the condition of surface waters, ultimately contributing to their management. We used multicollinearity and principal components analyses to develop the Revised Iranian Water Quality Index (RIWQI) as an indicator of agricultural and urban effects in the Karun River Basin of southwestern Iran. Seasonal sampling and analysis of water quality parameters from 54 sites across 18 rivers of the Karun River Basin include fecal coliform, total dissolved solid, phosphate, biological and chemical oxygen demand, nitrate, dissolved oxygen saturation, turbidity, pH, and water temperature. This study updates the previous version of Iranian Water Quality Index (IWQI) by differentially weighting individual variables, refining the main sub-indices, adding phosphate (PO₄^-), biological oxygen demand (BOD), chemical oxygen demand (COD), and temperature (T), and improving the aggregation calculation. Sensitivity testing of the RIWQI resulted in a mean value for discrimination efficiency (DE) > 85.6%, the highest of other indices calculated with the same dataset.

Ontology-aware deep learning enables ultrafast and interpretable source tracking among sub-million microbial community samples from hundreds of niches

The taxonomic structure of microbial community sample is highly habitat-specific, making source tracking possible, allowing identification of the niches where samples originate. However, current methods face challenges when source tracking is scaled up. Here, we introduce a deep learning method based on the Ontology-aware Neural Network approach, ONN4MST, for large-scale source tracking. ONN4MST outperformed other methods with near-optimal accuracy when source tracking among 125,823 samples from 114 niches. ONN4MST also has a broad spectrum of applications. Overall, this study represents the first model-based method for source tracking among sub-million microbial community samples from hundreds of niches, with superior speed, accuracy, and interpretability. ONN4MST is available at https://github.com/HUST-NingKang-Lab/ONN4MST.

Viral diversity and potential environmental risk in microplastic at watershed scale: Evidence from metagenomic analysis of plastisphere

Microplastics (MPs) have been considered as a new vector for the long-distance transport of pathogens in aquatic ecosystems. However, the composition of viral communities attached on MPs and their environmental risk are largely unknown. Here, we profiled the viral diversity and potential risk in five different MPs collected from the Beilun River based on metagenomic analysis. Nearly 2863 million raw reads were produced and assembled, and annotation resulted in the identification of 1719 different species of viruses in MPs. Viruses in polypropylene (PP) displayed the highest diversity, with about 250 specific viruses detected. Source tracking of viruses in MPs by the fast expectation-maximization microbial source tracking method (FEAST) demonstrated that viruses in upstream and downstream MPs are two major sources of viruses in estuary. Furthermore, the MP-type-dependent potential environmental risk of viruses was significant based on both antibiotic resistance genes (ARGs) and virulence factors (VFs) detected in viral metagenomes, and PP was confirmed with the highest potential environmental risk. This study reveals the high diversity and potential environmental risk of viruses in different MPs, and provides an important guidance for future environmental monitoring and understanding the potential risks associated with both viral transmission and MPs pollution.

Effect of Wastewater Treatment on Bacterial Community, Antibiotic-Resistant Bacteria and Endoparasites

Wastewater and wastewater treatment plants serve as urban reservoirs of pathogenic microorganisms. Wastewaters frequently contain bacteria, antibiotic-resistant bacteria, and developmental stages of parasites with significant zoonotic potential. Five wastewater treatment plants in the central part of Slovakia were investigated to determine the effect of treatment on bacterial community, antibiotic-resistant bacteria, and the occurrence of helminth eggs. Although all monitored chemical factors (chemical oxygen demand, biochemical oxygen demand, N-NH4, total nitrogen, and total phosphorus) in the effluent were in line with the legislative standards for discharge into public waterways, the results of minimal inhibitory concentrations show that reclaimed water harbors E. coli resistant to several commonly used antibiotics (ampicillin, piperacillin, and tazobactam, combine ampicillin and sulbactam, cefotaxime, tetracycline). The presence of endoparasite developmental stages in wastewater and sludge (Ascaris spp., Hymenolepis nana, eggs from the Ancylostomatidae family, Giardia duodenalis) indicates potential health risks for humans and workers at these sites. Treatment such as composting before applying sludge to land is necessary to reduce human pathogens.

Prevalence, diversity and genetic structure of Escherichia coli isolates from septic tanks

The present study investigated the diversity and genetic structure of Escherichia coli isolates from 100 septic tanks in the Canberra region, Australia. The physicochemical characteristics of the septic tanks were determined to examine the extent to which environmental factors might influence E. coli prevalence, diversity and population structure. The results of this study indicated that the temperature of the septic tank could explain some of the variation observed in the number of E. coli isolates recovered per septic tank, whereas pH was an important driver of E. coli diversity. Conductivity, pH and household size had a significant impact on E. coli population structure, and household size significantly affected the probability of detecting human-associated E. coli lineages [sequence types (STs) 69, 73, 95 and 131] in septic tanks. Phylogroup A and B1 strains were not randomly distributed among septic tanks, and the strong negative association between them may indicate intraspecific competition. The findings of this study suggest that the combination of environmental factors and intraspecific interactions may influence the distribution and genetic structure of E. coli in the environment.

Removal of Pathogens in Onsite Wastewater Treatment Systems: A Review of Design Considerations and Influencing Factors

Conventional onsite wastewater treatment systems (OWTSs) could potentially contribute to the transmission of infectious diseases caused by waterborne pathogenic microorganisms and become an important human health concern, especially in the areas where OWTSs are used as the major wastewater treatment units. Although previous studies suggested the OWTSs could reduce chemical pollutants as well as effectively reducing microbial contaminants from onsite wastewater, the microbiological quality of effluents and the factors potentially affecting the removal are still understudied. Therefore, the design and optimization of pathogen removal performance necessitate a better mechanistic understanding of the hydrological, geochemical, and biological processes controlling the water quality in OWTSs. To fill the knowledge gaps, the sources of pathogens and common pathogenic indicators, along with their major removal mechanisms in OWTSs were discussed. This review evaluated the effectiveness of pathogen removal in state-of-art OWTSs and investigated the contributing factors for efficient pathogen removal (e.g., system configurations, filter materials, environmental and operational conditions), with the aim to guide the future design for optimized treatment performance.

Tracking Major Sources of Water Contamination Using Machine Learning

Current microbial source tracking techniques that rely on grab samples analyzed by individual endpoint assays are inadequate to explain microbial sources across space and time. Modeling and predicting host sources of microbial contamination could add a useful tool for watershed management. In this study, we tested and evaluated machine learning models to predict the major sources of microbial contamination in a watershed. We examined the relationship between microbial sources, land cover, weather, and hydrologic variables in a watershed in Northern California, United States. Six models, including K-nearest neighbors (KNN), Naïve Bayes, Support vector machine (SVM), simple neural network (NN), Random Forest, and XGBoost, were built to predict major microbial sources using land cover, weather and hydrologic variables. The results showed that these models successfully predicted microbial sources classified into two categories (human and non-human), with the average accuracy ranging from 69% (Naïve Bayes) to 88% (XGBoost). The area under curve (AUC) of the receiver operating characteristic (ROC) illustrated XGBoost had the best performance (average AUC = 0.88), followed by Random Forest (average AUC = 0.84), and KNN (average AUC = 0.74). The importance index obtained from Random Forest indicated that precipitation and temperature were the two most important factors to predict the dominant microbial source. These results suggest that machine learning models, particularly XGBoost, can predict the dominant sources of microbial contamination based on the relationship of microbial contaminants with daily weather and land cover, providing a powerful tool to understand microbial sources in water.

An assessment of contamination fingerprinting techniques for determining the impact of domestic wastewater treatment systems on private well supplies

Private wells in Ireland and elsewhere have been shown to be prone to microbial contamination with the main suspected sources being practices associated with agriculture and domestic wastewater treatment systems (DWWTS). While the microbial quality of private well water is commonly assessed using faecal indicator bacteria, such as Escherichia coli, such organisms are not usually source-specific, and hence cannot definitively conclude the exact origin of the contamination. This research assessed a range of different chemical contamination fingerprinting techniques (ionic ratios, artificial sweeteners, caffeine, fluorescent whitening compounds, faecal sterol profiles and pharmaceuticals) as to their use to apportion contamination of private wells between human wastewater and animal husbandry wastes in rural areas of Ireland. A one-off sampling and analysis campaign of 212 private wells found that 15% were contaminated with E. coli. More extensive monitoring of 24 selected wells found 58% to be contaminated with E. coli on at least one occasion over a 14-month period. The application of fingerprinting techniques to these monitored wells found that the use of chloride/bromide and potassium/sodium ratios is a useful low-cost fingerprinting technique capable of identifying impacts from human wastewater and organic agricultural contamination, respectively. The artificial sweetener acesulfame was detected on several occasions in a number of monitored wells, indicating its conservative nature and potential use as a fingerprinting technique for human wastewater. However, neither fluorescent whitening compounds nor caffeine were detected in any wells, and faecal sterol profiles proved inconclusive, suggesting limited suitability for the conditions investigated.

Association between private drinking water wells and the incidence of Campylobacteriosis in Maryland: An ecological analysis using Foodborne Diseases Active Surveillance Network (FoodNet) data (2007-2016)

Campylobacter is a leading cause of bacterial foodborne illness in the United States. Campylobacter infections have most often been associated with food-related risk factors, such as the consumption of poultry and raw milk. Socioeconomic, agricultural and environmental factors, including drinking water source, can also influence the risk of campylobacteriosis. Approximately 19% of Maryland residents rely on private wells as their sole source of water. Given that the federal Safe Drinking Water Act does not regulate the water quality of private wells, these could be important non-foodborne transmission pathways for Campylobacter. To address this issue, data on the number of culture-confirmed cases of Campylobacter infection in Maryland between 2007 and 2016 were obtained from the Foodborne Diseases Active Surveillance Network. Cases were linked by zip code with data from the Maryland well permits registry, the 2010 U.S. Census, the 2016 American Community Survey, and the USDA Agricultural Census. Campylobacteriosis incidence rates and well prevalence were calculated by zip code. Negative binomial regression models were then constructed to evaluate the association between the prevalence of private wells, presence/absence of animal feeding operations and the incidence of campylobacteriosis across the physiographic provinces in Maryland. From 2007 to 2016, a total of 5746 cases of campylobacteriosis were reported in Maryland, and annual incidence rates ranged from 6.65 to 11.59 per 100,000 people. In our statewide analysis, a significant positive association was observed between well prevalence and increased campylobacteriosis incidence at the zip code level (Incidence Rate Ratio (IRR) = 1.35, 95% Confidence Interval (CI) = 1.11, 1.63). A significant positive association was also observed between well prevalence and increased campylobacteriosis incidence in the Appalachian and Coastal provinces of Maryland (IRR = 2.94, 95% CI = 1.11, 7.76 and IRR = 1.70, 95% CI = 1.25, 2.31, respectively). The presence of broiler chicken operations, increasing median age and percentage of residents living in poverty were also significantly associated with campylobacteriosis incidence at the zip code level in some physiographic provinces in Maryland. To our knowledge, these are the first US data to demonstrate an association between prevalence of private wells and campylobacteriosis incidence at the zip code level.

Meta-SourceTracker: application of Bayesian source tracking to shotgun metagenomics

Background

Microbial source tracking methods are used to determine the origin of contaminating bacteria and other microorganisms, particularly in contaminated water systems. The Bayesian SourceTracker approach uses deep-sequencing marker gene libraries (16S ribosomal RNA) to determine the proportional contributions of bacteria from many potential source environments to a given sink environment simultaneously. Since its development, SourceTracker has been applied to an extensive diversity of studies, from beach contamination to human behavior.

Methods

Here, we demonstrate a novel application of SourceTracker to work with metagenomic datasets and tested this approach using sink samples from a study of coastal marine environments. Source environment metagenomes were obtained from metagenomics studies of gut, freshwater, marine, sand and soil environments. As part of this effort, we implemented features for determining the stability of source proportion estimates, including precision visualizations for performance optimization, and performed domain-specific source-tracking analyses (i.e., Bacteria, Archaea, Eukaryota and viruses). We also applied SourceTracker to metagenomic libraries generated from samples collected from the International Space Station (ISS).

Results

SourceTracker proved highly effective at predicting the composition of known sources using shotgun metagenomic libraries. In addition, we showed that different taxonomic domains sometimes presented highly divergent pictures of environmental source origins for both the coastal marine and ISS samples. These findings indicated that applying SourceTracker to separate domains may provide a deeper understanding of the microbial origins of complex, mixed-source environments, and further suggested that certain domains may be preferable for tracking specific sources of contamination.

Detection of human fecal pollution in environmental waters using human mitochondrial DNA and correlation with general and human-associated fecal genetic markers

Human mitochondrial DNA (mtDNA) genetic markers are abundant in sewage and highly human-specific, suggesting a great potential for the environmental application as human fecal pollution indicators. Limited data are available on the occurrence and co-occurrence of human mtDNA with fecal bacterial markers in surface waters, and how the abundance of these markers is influenced by rain events. A 1-year sampling study was conducted in a suburban watershed impacted by human sewage contamination to evaluate the performance of a human mtDNA-based marker along with the bacterial genetic markers for human-associated Bacteroidales (BacHum and HF183) and Escherichia coli. Additionally, the human mtDNA-based assay was correlated with rain events and other markers. The mtDNA marker was detected in 92% of samples (n = 140) with a mean concentration of 2.96 log₁₀ copies/100 ml throughout the study period. Human mtDNA was detected with greater abundance than human-associated Bacteroidales that could be attributed to differences in the decay of these markers in the environment. The abundance of all markers was positively correlated with rain events, and human mtDNA abundance was significantly correlated with various bacterial markers. In general, these results should support future risk assessment for impacted watersheds, particularly those affected by human fecal pollution, by evaluating the performance of these markers during rain events.

Microbial indicators and molecular markers used to differentiate the source of faecal pollution in the Bogotá River (Colombia)

Intestinal pathogenic microorganisms are introduced into the water by means of faecal contamination, thus creating a threat to public health and to the environment. Detecting these contaminants has been difficult due to such an analysis being costly and time-intensive; as an alternative, microbiological indicators have been used for this purpose, although they cannot differentiate between human or animal sources of contamination because these indicators are part of the digestive tracts of both. To identify the sources of faecal pollution, the use of chemical, microbiological and molecular markers has been proposed. Currently available markers present some geographical specificity. The aim of this study was to select microbial and molecular markers that could be used to differentiate the sources of faecal pollution in the Bogotá River and to use them as tools for the evaluation and identification of the origin of discharges and for quality control of the water. In addition to existing microbial source markers, a phage host strain (PZ8) that differentiates porcine contamination was isolated from porcine intestinal content. The strain was identified biochemically and genotypically as Bacteroides. The use of this strain as a microbial source tracking indicator was evaluated in bovine and porcine slaughterhouse wastewaters, raw municipal wastewaters and the Bogotá River. The results obtained indicate that the selected microbial and molecular markers enable the determination of the source of faecal contamination in the Bogotá River by using different algorithms to develop prediction models.

Antibiotic resistance and genotyping of gram-negative bacteria causing hospital-acquired infection in patients referred to Children's Medical Center

Background and aim

Hospital-acquired infection (HAI) is a major problem worldwide. Understanding patterns of bacterial etiology and antibiotic susceptibility is vital to combating HAI. Besides, typing of isolates is important to establish the intra-hospital surveillance of resistant clones. In this study, we aimed to evaluate antibiotic resistance and genotyping of a number of gram-negative bacteria (GNB) causing HAI in patients who were referred to Children’s Medical Center.

Methods

During the 6-month period, antimicrobial susceptibility profiles of GNB isolates recovered from patients in Children’s Medical Center were determined. Typing of common GNB was performed by random amplified polymorphic DNA (RAPD) analysis and the results were analyzed by Gelcompar II software.

Results

In total, 142 (1.1%) gram-negative bacterial strains were isolated, among which 59.2% were from males. The most organisms were isolated from blood (63%) followed by wounds (13.7%). The greatest proportion of strains came from intensive care units (51%). Low sensitivity of Acinetobacter baumannii to common antibiotics and high resistance of Enterobacter spp. To cefotaxime (100%) were reported. The most efficient antibiotics for Escherichia coli strains were amikacin (84%) and gentamycin (81%). However, just 12.5% of Serratia marcescens strains were resistant to trimethoprim-sulfamethoxazole. The analysis of RAPD-typing revealed the presence of one clone in A. baumannii and E. coli and two clones in Klebsiella pneumoniae, whereas the trend varied completely in Pseudomonas aeruginosa strains and Enterobacter spp.

Conclusion

The results of this study showed a possibility of an outbreak in the Children’s Medical Center. Since there is a possibility of transmission of an infection from one patient to another, high attention should be paid to the basic methods of preventing infection.

Species-specific qPCR assays allow for high-resolution population assessment of four species avian schistosome that cause swimmer's itch in recreational lakes

Swimmer's itch is an allergic condition that occurs when the motile and infectious stage of avian schistosomes penetrate the skin of an individual. Flatworm parasites that cause swimmer's itch belong to the family Schistosomatidae. They utilize a variety of different species of bird and mammal as definitive hosts, and rely on different species of snail, in which they complete their larval development to culminate in a motile, aquatic, infectious stage called a cercaria. Recently, qPCR-based assays have been developed to monitor for swimmer's itch-causing trematodes in recreational water. This environmental DNA approach has been useful for quantifying the abundance of the free-living cercaria, the causative agent of swimmer's itch. However, the existing qPCR test amplifies from all known schistosome species, making it excellent for assessing a site for swimmer's itch potential, but not useful in determining the specific species contributing to swimmer's itch or the likely hosts (snail and bird) of the swimmer's itch-causing parasites. Thus, species-specific resolution built into a qPCR test would be useful in answering ecological questions about swimmer's itch cause, and efficacy of control efforts. This paper details bird, snail, and cercaria surveys conducted in the summer of 2018, that culminated in the development and deployment of four species-specific qPCR assays, capable of detecting Trichobilharzia stagnicolae, Trichobilharzia szidati, Trichobilharzia physellae, and Anserobilharzia brantae in recreational water. These assays were used to assess the relative abundance of each parasite in water samples collected from lakes in Northern Michigan.

Linking landscape patterns to sources of water contamination: Implications for tracking fecal contaminants with geospatial and Bayesian approaches

Microbial source tracking (MST) techniques have been designed to identify the host source of fecal contamination in water. However, current MST techniques cannot provide geographic origins of particular sources because they do not provide any spatial information beyond the points of observation. In this study, the associations between landscape patterns and the major sources of microbial contamination were examined and the application of geospatial techniques (e.g., remote sensing and geographic information systems) and Bayesian modeling was explored to track microbial sources over the landscape. The land cover information of three watersheds (the lower Dungeness Watershed, the Middle Rio Grande Watershed, and the Arroyo Burro Watershed) in the United States was obtained either by classifying high resolution satellite images or directly using land cover datasets (e.g., National Land Cover Dataset, 2006 and 2011). Then, the relationship between land use/land cover (LULC) and microbial sources from these three geographically disparate watersheds were analyzed using Bayesian hierarchical models. The results showed the predictive positive associations between human sources of fecal contamination and developed area, between dog sources and grassland, and between bird sources and water, but negative associations between human sources and forest and water areas. Furthermore, the diversity of microbial sources had positive associations with landscape fragmentation and diversity indices. This study demonstrates associations between landscape patterns and major microbial sources and offers new insight in tracking the dominant sources of fecal contamination in water using geospatial and Bayesian techniques.

Bacteroidales as Indicators and Source Trackers of Fecal Contamination in Tomatoes and Strawberries

Most methods that investigate fecal contamination of vegetables do not address the origin of contamination. Because host-specific sequences are conserved in their genomes, bacteria of the order Bacteroidales are regarded as alternative indicators for tracking sources of contamination of produce. The objective of this study was to determine the efficacy of host-specific Bacteroidales markers to identify sources of fecal contamination and to determine whether detection of Bacteroidales markers correlated with traditional fecal indicator bacteria (FIB) in strawberries and tomatoes. Tomato and strawberry samples were artificially contaminated with human and animal feces, which contained 6 to 7 log CFU Bacteroidales per 100 mL and 3 to 6 log CFU/100 mL of the bacterial indicators Escherichia coli, total coliforms, and Enterococcus. FIB were enumerated by standard procedures. Universal and host-specific Bacteroidales markers were detected and quantified by quantitative PCR, and the detection range was 1.35 to 10.35 logarithmic gene copies, which corresponds to a limit of detection of two Bacteroidales cells. Few correlations between levels of Bacteroidales and levels of FIB were observed. For most of the contaminated tomato and strawberry samples, Bacteroidales levels were higher than FIB levels, and detection of FIB was highly variable. Detection of Bacteroidales markers was similar to total coliforms when ≥0.1 mg of feces was inoculated. These indicators were better than E. coli and Enterococcus for detection of fecal contamination in produce. The host-associated Bacteroidales markers were detected at an inoculum of 1 mg of feces per produce item (except those from bovine feces in strawberry). All of the host-associated Bacteroidales markers were detected at an inoculum of 10 mg of feces per produce item. Thus, Bacteroidales markers are promising tools to identify sources of fecal contamination; however, more research is required for their potential use to reduce the risks of contamination of produce.

Prevalence of Microbiological and Chemical Contaminants in Private Drinking Water Wells in Maryland, USA

Although many U.S. homes rely on private wells, few studies have investigated the quality of these water sources. This cross-sectional study evaluated private well water quality in Maryland, and explored possible environmental sources that could impact water quality. Well water samples (n = 118) were collected in four Maryland counties and were analyzed for microbiological and chemical contaminants. Data from the U.S. Census of Agriculture were used to evaluate associations between the presence of animal feeding operations and well water quality at the zip code level using logistic regression. Overall, 43.2% of tested wells did not meet at least one federal health-based drinking water standard. Total coliforms, fecal coliforms, enterococci, and Escherichia coli were detected in 25.4%, 15.3%, 5.1%, and 3.4% of tested wells, respectively. Approximately 26%, 3.4%, and <1% of wells did not meet standards for pH, nitrate-N, and total dissolved solids, respectively. There were no statistically significant associations between the presence of cattle, dairy, broiler, turkey, or aquaculture operations and the detection of fecal indicator bacteria in tested wells. In conclusion, nearly half of tested wells did not meet federal health-based drinking water standards, and additional research is needed to evaluate factors that impact well water quality. However, homeowner education on well water testing and well maintenance could be important for public health.

Fecal pollution: new trends and challenges in microbial source tracking using next-generation sequencing

In this minireview, we expand upon traditional microbial source tracking (MST) methods by discussing two recently developed, next-generation-sequencing (NGS)-based MST approaches to identify sources of fecal pollution in recreational waters. One method defines operational taxonomic units (OTUs) that are specific to a fecal source, e.g., humans and animals or shared among multiple fecal sources to determine the magnitude and likely source association of fecal pollution. The other method uses SourceTracker, a program using a Bayesian algorithm, to determine which OTUs have contributed to an environmental community based on the composition of microbial communities in multiple fecal sources. Contemporary NGS-based MST tools offer a promising avenue to rapidly characterize fecal source contributions for water monitoring and remediation efforts at a broader and more efficient scale than previous molecular MST methods. However, both NGS methods require optimized sequence processing methodologies (e.g. quality filtering and clustering algorithms) and are influenced by primer selection for amplicon sequencing. Therefore, care must be taken when extrapolating data or combining datasets. Furthermore, traditional limitations of library-dependent MST methods, including differential decay of source material in environmental waters and spatiotemporal variation in source communities, remain to be fully understood. Nevertheless, increasing use of these methods, as well as expanding fecal taxon libraries representative of source communities, will help improve the accuracy of these methods and provide promising tools for future MST investigations.

Toward Forensic Uses of Microbial Source Tracking

The science of microbial source tracking has allowed researchers and watershed managers to go beyond general indicators of fecal pollution in water such as coliforms and enterococci, and to move toward an understanding of specific contributors to water quality issues. The premise of microbial source tracking is that characteristics of microorganisms that are strongly associated with particular host species can be used to trace fecal pollution to particular animal species (including humans) or groups, e.g., ruminants or birds. Microbial source tracking methods are practiced largely in the realm of research, and none are approved for regulatory uses on a federal level. Their application in the conventional sense of forensics, i.e., to investigate a crime, has been limited, but as some of these methods become standardized and recognized in a regulatory context, they will doubtless play a larger role in applications such as total maximum daily load assessment, investigations of sewage spills, and contamination from agricultural practices.

Quantitative detection of fecal contamination with domestic poultry feces in environments in China

Poultry are an important source of fecal contamination in environments. However, tools for detecting and tracking this fecal contamination are in the early stages of development. In practice, we have found that source tracking methods targeting the 16S rRNA genes of poultry-specific microbiota are not sufficiently sensitive. We therefore developed two quantitative PCR assays for detection of poultry fecal contamination, by targeting chicken and duck mitochondrial genes: NADH dehydrogenase subunit 5 (ND5) and cytochrome b (cytb). The sensitivity of both assays was 100% when tested on 50 chicken and duck fecal samples from 10 provinces of China. These assays were also tested in field samples, including soil and water collected adjacent to duck farms, and soils fertilized with chicken manure. Poultry mitochondrial DNA was detected in most of these samples, indicating that the assays are a robust method for monitoring environmental contamination with poultry feces. Complemented with existing indicators of fecal contamination, these markers should improve the efficiency and accuracy of microbial source tracking.

MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage

Wastewater treatment plants (WWTPs) functioned as the intersection between the human society and nature environment, are receiving increasingly more attention on risk assessment of the acquisition of environmental antibiotic resistance genes (ARGs) by pathogenetic populations during treatment. However, because of the general lack of robust resistome profiling methods, genotype, and resistance phenotype is still poorly correlated in human pathogens of sewage samples. Here we applied MinION sequencing to quantify the resistance genes of multiple antibiotic resistant (MAR) coliform bacteria, a common indicator for human enteric pathogens in sewage samples. Our pipeline could deliver the results within 30 h from sample collection and the resistome quantification was consistent to that based on the Illumina platform. Additionally, the long nanopore reads not only enabled a simultaneous identification of the carrier populations of ARGs detected, but also facilitated the genome reconstruction of a representative MAR strain, from which we identified an instance of chromosomal integration of environmental resistance gene obtained by plasmid exchange with a porcine pathogen. This study demonstrated the utilization of MinION sequencing in quick monitoring and simultaneous phylogenetic tracking of environmental ARGs to address potential health risk associated with them.

Modelling the transport and decay processes of microbial tracers in a macro-tidal estuary

The Loughor Estuary is a macro-tidal coastal basin, located along the Bristol Channel, in the South West of the U.K. The maximum spring tidal range in the estuary is up to 7.5 m, near Burry Port Harbour. This estuarine region can experience severe coastal flooding during high spring tides, including extreme flooding of the intertidal saltmarshes at Llanrhidian, as well as the lower industrial and residential areas at Llanelli and Gowerton. The water quality of this estuarine basin needs to comply with the designated standards for safe recreational bathing and shellfish harvesting industries. The waterbody however, potentially receives overloading of bacterial inputs that enter the estuarine system from both point and diffuse sources. Therefore, a microbial tracer study was carried out to get a better understanding of the faecal bacteria sources and to enable a hydro-environmental model to be refined and calibrated for both advection and dispersion transport. A two-dimensional hydro-environmental model has been refined and extended to predict the highest water level covering the intertidal floodplains of the Loughor Estuary. The validated hydrodynamic model for both water levels and currents, was included with the injected mass of microbial tracer, i.e. MS2 coliphage from upstream of the estuary, and modelled as a non-conservative tracer over several tidal cycles through the system. The calibration and validation of the transport and decay of microbial tracer was undertaken, by comparing the model results and the measured data at two different sampling locations. The refined model developed as a part of this study, was used to acquire a better understanding of the water quality processes and the potential sources of bacterial pollution in the estuary.

A High-Throughput DNA-Sequencing Approach for Determining Sources of Fecal Bacteria in a Lake Superior Estuary

Current microbial source-tracking (MST) methods, employed to determine sources of fecal contamination in waterways, use molecular markers targeting host-associated bacteria in animal or human feces. However, there is a lack of knowledge about fecal microbiome composition in several animals and imperfect marker specificity and sensitivity. To overcome these issues, a community-based MST method has been developed. Here, we describe a study done in the Lake Superior-Saint Louis River estuary using SourceTracker, a program that calculates the source contribution to an environment. High-throughput DNA sequencing of microbiota from a diverse collection of fecal samples obtained from 11 types of animals (wild, agricultural, and domesticated) and treated effluent (n = 233) was used to generate a fecal library to perform community-based MST. Analysis of 319 fecal and environmental samples revealed that the community compositions in water and fecal samples were significantly different, allowing for the determination of the presence of fecal inputs and identification of specific sources. SourceTracker results indicated that fecal bacterial inputs into the Lake Superior estuary were primarily attributed to wastewater effluent and, to a lesser extent, geese and gull wastes. These results suggest that a community-based MST method may be another useful tool for determining sources of aquatic fecal bacteria.

A case study characterizing animal fecal sources in surface water using a mitochondrial DNA marker

Water quality impairment by fecal waste in coastal watersheds is a public health issue. The present study provided evidence for the use of a mitochondrial (mtDNA) marker to detect animal fecal sources in surface water. The accurate identification of fecal pollution is based on the notion that fecal microorganisms preferentially inhabit a host animal's gut environment. In contrast, mtDNA host-specific markers are inherent to eukaryotic host cells, which offers the advantage by detecting DNA from the host rather than its fecal bacteria. The present study focused on sampling water presumably from non-point sources (NPS), which can increase bacterial and nitrogen concentrations to receiving water bodies. Stream sampling sites located within the Piscataqua River Watershed (PRW), New Hampshire, USA, were sampled from a range of sites that experienced nitrogen inputs such as sewer and septic systems and suburban runoff. Three mitochondrial (mtDNA) gene marker assays (human, bovine, and canine) were tested from surface water. Nineteen sites were sampled during an 18-month period. Analyses of the combined single and multiplex assay results showed that the proportion of occurrence was highest for bovine (15.6%; n = 77) compared to canine (5.6%; n = 70) and human (5.7%; n = 107) mtDNA gene markers. For the human mtDNA marker, there was a statistically significant relationship between presence vs. absence and land use (Fisher's test p = 0.0031). This result was evident particularly for rural suburban septic, which showed the highest proportion of presence (19.2%) compared to the urban sewered (3.3%), suburban sewered (0%), and agricultural (0%) as well as forested septic (0%) sites. Although further testing across varied land use is needed, our study provides evidence for using the mtDNA marker in large watersheds.

Contemporary nucleic acid-based molecular techniques for detection, identification, and characterization of Bifidobacterium

Bifidobacteria are one of the most important bacterial groups found in the gastrointestinal tract of humans. Medical and food industry researchers have focused on bifidobacteria because of their health-promoting properties. Researchers have historically relied on classic phenotypic approaches (culture and biochemical tests) for detection and identification of bifidobacteria. Those approaches still have values for the identification and detection of some bifidobacterial species, but they are often labor-intensive and time-consuming and can be problematic in differentiating closely related species. Rapid, accurate, and reliable methods for detection, identification, and characterization of bifidobacteria in a mixed bacterial population have become a major challenge. The advent of nucleic acid-based molecular techniques has significantly advanced isolation and detection of bifidobacteria. Diverse nucleic acid-based molecular techniques have been employed, including hybridization, target amplification, and fingerprinting. Certain techniques enable the detection, characterization, and identification at genus-, species-, and strains-levels, whereas others allow typing of species or strains of bifidobacteria. In this review, an overview of methodological principle, technique complexity, and application of various nucleic acid-based molecular techniques for detection, identification, and characterization of bifidobacteria is presented. Advantages and limitations of each technique are discussed, and significant findings based on particular techniques are also highlighted.

Application of quantitative real-time PCR compared to filtration methods for the enumeration of Escherichia coli in surface waters within Vietnam

Surface water samples in Vietnam were collected from the Saigon River, rural and suburban canals, and urban runoff canals in Ho Chi Minh City, Vietnam, and were processed to enumerate Escherichia coli. Quantification was done through membrane filtration and quantitative real-time polymerase chain reaction (PCR). Mean log colony-forming unit (CFU)/100 ml E. coli counts in the dry season for river/suburban canals and urban canals were log 2.8 and 3.7, respectively, using a membrane filtration method, while using Taqman quantitative real-time PCR they were log 2.4 and 2.8 for river/suburban canals and urban canals, respectively. For the wet season, data determined by the membrane filtration method in river/suburban canals and urban canals samples had mean counts of log 3.7 and 4.1, respectively. While mean log CFU/100 ml counts in the wet season using quantitative PCR were log 3 and 2, respectively. Additionally, the urban canal samples were significantly lower than those determined by conventional culture methods for the wet season. These results show that while quantitative real-time PCR can be used to determine levels of fecal indicator bacteria in surface waters, there are some limitations to its application and it may be impacted by sources of runoff based on surveyed samples.

Source tracking using microbial community fingerprints: Method comparison with hydrodynamic modelling

Urban estuaries around the world are experiencing contamination from diffuse and point sources, which increases risks to public health. To mitigate and manage risks posed by elevated levels of contamination in urban waterways, it is critical to identify the primary water sources of contamination within catchments. Source tracking using microbial community fingerprints is one tool that can be used to identify sources. However, results derived from this approach have not yet been evaluated using independent datasets. As such, the key objectives of this investigation were: (1) to identify the major sources of water responsible for bacterial loadings within an urban estuary using microbial source tracking (MST) using microbial communities; and (2) to evaluate this method using a 3-dimensional hydrodynamic model. The Yarra River estuary, which flows through the city of Melbourne in South-East Australia was the focus of this study. We found that the water sources contributing to the bacterial community in the Yarra River estuary varied temporally depending on the estuary's hydrodynamic conditions. The water source apportionment determined using microbial community MST correlated to those determined using a 3-dimensional hydrodynamic model of the transport and mixing of a tracer in the estuary. While there were some discrepancies between the two methods, this investigation demonstrated that MST using bacterial community fingerprints can identify the primary water sources of microorganisms in an estuarine environment. As such, with further optimization and improvements, microbial community MST has the potential to become a powerful tool that could be practically applied in the mitigation of contaminated aquatic systems.

The Microbiota of Recreational Freshwaters and the Implications for Environmental and Public Health

The microbial communities in recreational freshwaters play important roles in both environmental and public health perspectives. In this study, the bacterial community structure and its associations with freshwater environments were investigated by analyzing the summertime microbiomes of three beach waters in Ohio (East Fork, Delaware, and Madison lakes) together with environmental and microbial water quality parameters. From the swimming season of 2009, 21 water samples were collected from the three freshwater beaches. From the samples, 110,000 quality-checked bacterial 16S rRNA gene sequences were obtained and analyzed, resulting in an observation of 4500 bacterial operational taxonomic units (OTUs). The most abundant bacteria were Mycobacterium and Arthrobacter of the Actinobacteria (33.2%), Exiguobacterium and Paenisporosarcina of the Firmicutes (23.4%), Planktothrix and Synechococcus of the Cyanobacteria (20.8%), and Methylocystis and Polynucleobacter of the Proteobacteria (16.3%). Considerable spatial and temporal variations were observed in the bacterial community of Actinobacteria, Cyanobacteria, and Firmicutes, where the bacterial community structure was greatly influenced by hydrological and weather conditions. The most influential factors were (1) water inflow for Bacteroidia and Clostridia, (2) turbidity for Gammaproteobacteria, (3) precipitation for Bacilli, and (4) temperature and pH for Cyanobacteria. One noticeable microbial interaction in the bacterial community was a significant negative relationship between Cyanobacteria and Bacilli (P < 0.05). Concerning beach water quality, the level of the genetic markers for cyanobacterial toxin (mcyA) was linked to the abundance of Cyanobacteria. In addition, unique distributions of the genera Enterococcus, Staphylococcus, Streptococcus, Bacteroides, Clostridium, Finegoldia, Burkholderia, and Klebsiella, together with a high density of fecal indicator Escherichia coli, were markedly observed in the sample from Madison Lake on July 13, suggesting a distinctly different source of bacterial loading into the lake, possibly fecal contamination. In conclusion, deep sequencing-based microbial community analysis can provide detailed profiles of bacterial communities and information on potential public health risks at freshwater beaches.

Restructuring of the Aquatic Bacterial Community by Hydric Dynamics Associated with Superstorm Sandy

Bacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter- and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in which Betaproteobacteria and Gammaproteobacteria decreased in 16S rRNA gene relative abundance, while the relative abundance of members of the Firmicutes increased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains of Legionella, Campylobacter, Arcobacter, and Helicobacter, as well as bacteria of fecal origin (e.g., Bacteroides), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event.

IMPORTANCE

In order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study investigated the bacterial communities during and after Superstorm Sandy to provide fine time point resolution of dynamic changes in bacterial composition. This study adds to the current literature by revealing the variation in bacterial community structure during the course of a storm. This study employed high-throughput DNA sequencing, which generated a deep analysis of inter- and intracommunity responses during a significant storm event. This study has highlighted the utility of applying high-throughput sequencing for water quality monitoring purposes, as this approach enabled a more comprehensive investigation of the bacterial community structure. Altogether, these data suggest a drastic restructuring of the stream bacterial community during a storm event and highlight the potential of high-throughput sequencing approaches for assessing the microbiological quality of our environment.

Human-, Ovine-, and Bovine-Specific Viral Source Tracking Tools to Discriminate Between the Major Fecal Sources in Agricultural Waters

This study evaluated the sources of fecal contamination in different river catchments, using a combination of microbial source tracking tools, for human, ruminant, ovine and bovine livestock, in order to define appropriate water management strategies. Every source of waterway pollution was evaluated in river water samples from one urban river catchment and two important farming regions in New Zealand. Fecal pollution was initially measured by testing Escherichia coli and evaluating the presence of human- and ruminant-associated DNA markers of Bacteroidales (BiAdo, BacHum-UCD, BacH, and BacR) and human and ruminant fecal sterols/stanols ratios. Then specific fecal pollution sources were assessed with previously reported quantitative PCR assays targeting human-, bovine-, and ovine-specific viruses: human adenoviruses (HAdV), human JC polyomaviruses, bovine polyomaviruses (BPyV), and ovine polyomaviruses (OPyV). High level of ruminant fecal contamination was detected all over the farming areas, whereas no ruminant sources were identified in the urban river sampling sites. BacR was the most frequently observed ruminant marker and OPyV and BPyV allowed the identification of ovine and bovine fecal sources. The human fecal viral marker (HAdV) was the most frequently observed human marker, highly abundant in the urban sites, and also present in farming areas. This is the first study using simultaneously the ovine and the bovine viral markers to identify and quantify both bovine and ovine fecal pollution.

Next-generation sequencing (NGS) for assessment of microbial water quality: current progress, challenges, and future opportunities

Water quality is an emergent property of a complex system comprised of interacting microbial populations and introduced microbial and chemical contaminants. Studies leveraging next-generation sequencing (NGS) technologies are providing new insights into the ecology of microbially mediated processes that influence fresh water quality such as algal blooms, contaminant biodegradation, and pathogen dissemination. In addition, sequencing methods targeting small subunit (SSU) rRNA hypervariable regions have allowed identification of signature microbial species that serve as bioindicators for sewage contamination in these environments. Beyond amplicon sequencing, metagenomic and metatranscriptomic analyses of microbial communities in fresh water environments reveal the genetic capabilities and interplay of waterborne microorganisms, shedding light on the mechanisms for production and biodegradation of toxins and other contaminants. This review discusses the challenges and benefits of applying NGS-based methods to water quality research and assessment. We will consider the suitability and biases inherent in the application of NGS as a screening tool for assessment of biological risks and discuss the potential and limitations for direct quantitative interpretation of NGS data. Secondly, we will examine case studies from recent literature where NGS based methods have been applied to topics in water quality assessment, including development of bioindicators for sewage pollution and microbial source tracking, characterizing the distribution of toxin and antibiotic resistance genes in water samples, and investigating mechanisms of biodegradation of harmful pollutants that threaten water quality. Finally, we provide a short review of emerging NGS platforms and their potential applications to the next generation of water quality assessment tools.

Microbial source markers assessment in the Bogotá River basin (Colombia)

The microbiological indicators traditionally used to assess fecal contamination are insufficient to identify the source. The aim of this study was to detect microbial markers to identify the source of fecal pollution in the Bogotá River (Colombia). For this, we determined non-discriminating indicators such as Escherichia coli, somatic coliphages and phages infecting strain RYC2056 of Bacteroides, and potential source tracking markers as phages infecting strains GA17, HB13, and CA8 of Bacteroides, sorbitol-fermenting bifidobacteria, and molecular markers of Bifidobacterium adolescentis, Bifiodobacterium dentium, and Bacteroidetes in raw municipal wastewaters, slaughterhouse wastewaters, and the Bogotá River. Bacteriophages infecting Bacteroides strain GA17 and the molecular markers identified the wastewater sources. In contrast, sorbitol-fermenting bifidobacteria failed regarding specificity. In the Bogotá River, phages infecting strain GA17 were detected in all samples downstream of Bogotá, whereas they should be concentrated from 1 l samples in upstream samples containing less than 10(3) E. coli/100 ml to be detected. In the river water, the fraction of positive detections of molecular markers was lower than that of phages infecting strain GA17. The ratio SOMCPH/GA17PH was shown also to be a good marker. These results provide information that will allow focusing measures for sanitation of the Bogotá River.

Microbial indicators, pathogens and methods for their monitoring in water environment

Water is critical for life, but many people do not have access to clean and safe drinking water and die because of waterborne diseases. The analysis of drinking water for the presence of indicator microorganisms is key to determining microbiological quality and public health safety. However, drinking water-related illness outbreaks are still occurring worldwide. Moreover, different indicator microorganisms are being used in different countries as a tool for the microbiological examination of drinking water. Therefore, it becomes very important to understand the potentials and limitations of indicator microorganisms before implementing the guidelines and regulations designed by various regulatory agencies. This review provides updated information on traditional and alternative indicator microorganisms with merits and demerits in view of their role in managing the waterborne health risks as well as conventional and molecular methods proposed for monitoring of indicator and pathogenic microorganisms in the water environment. Further, the World Health Organization (WHO) water safety plan is emphasized in order to develop the better approaches designed to meet the requirements of safe drinking water supply for all mankind, which is one of the major challenges of the 21st century.

Predicting fecal sources in waters with diverse pollution loads using general and molecular host-specific indicators and applying machine learning methods

In this study we use a machine learning software (Ichnaea) to generate predictive models for water samples with different concentrations of fecal contamination (point source, moderate and low). We applied several MST methods (host-specific Bacteroides phages, mitochondrial DNA genetic markers, Bifidobacterium adolescentis and Bifidobacterium dentium markers, and bifidobacterial host-specific qPCR), and general indicators (Escherichia coli, enterococci and somatic coliphages) to evaluate the source of contamination in the samples. The results provided data to the Ichnaea software, that evaluated the performance of each method in the different scenarios and determined the source of the contamination. Almost all MST methods in this study determined correctly the origin of fecal contamination at point source and in moderate concentration samples. When the dilution of the fecal pollution increased (below 3 log10 CFU E. coli/100 ml) some of these indicators (bifidobacterial host-specific qPCR, some mitochondrial markers or B. dentium marker) were not suitable because their concentrations decreased below the detection limit. Using the data from source point samples, the software Ichnaea produced models for waters with low levels of fecal pollution. These models included some MST methods, on the basis of their best performance, that were used to determine the source of pollution in this area. Regardless the methods selected, that could vary depending on the scenario, inductive machine learning methods are a promising tool in MST studies and may represent a leap forward in solving MST cases.

An environmental survey of surface waters using mitochondrial DNA from human, bovine and porcine origin as fecal source tracking markers

Fecal contamination of surface waters is one the major sources of waterborne pathogens and consequently, is an important concern for public health. For reliable fecal source tracking (FST) monitoring, there is a need for a multi-marker toolbox as no single all-encompassing method currently exists. Mitochondrial DNA (mtDNA) as a source tracking marker has emerged as a promising animal-specific marker. However, very few comprehensive field studies were done on the occurrence of this marker in surface waters. In this report, water samples were obtained from 82 sites in different watersheds over a six year period. The samples were analyzed for the presence of human, bovine and porcine mtDNA by endpoint nested PCR, along with the human-specific Bacteroidales HF183 marker. These sites represented a mix of areas with different anthropogenic activities, natural, urban and agricultural. The occurrences of mitoHu (human), mitoBo (bovine), mitoPo (porcine) and HF183 specific PCR amplifications from the samples were 46%, 23%, 6% and 50%, respectively. The occurrence of mitoHu and HF183 was high in all environment types with higher occurrence in the natural and urban areas, whereas the occurrence of mitoBo was higher in agricultural areas. FST marker concentrations were measured by real-time PCR for samples positive for these markers. The concentration of the mitoHu markers was one order of magnitude lower than HF183. There was co-linearity between the concentrations of the mitoHu and HF183 markers. Co-linearity was also observed between HF183 concentration and fecal coliform levels. Such a relationship was not observed between the mitoHu concentration and fecal coliform levels. In summary, our results showed a high incidence of human fecal pollution throughout the environment while demonstrating the potential of mtDNA as suitable FST markers.