Fate and transport of pathogens in lakes and reservoirs

Urban landscape lakes with backwater hide higher antibiotic resistance risk than living water

The pollution of antibiotic resistance genes (ARGs) in urban landscape lakes threatens the aquatic ecosystems and public health. However, a comprehensive understanding of the fate of ARGs in different types of park landscape lakes (i.e., backwater and living water) remains deficient. Here, we profiled the distribution, diversity, origin and potential spread risk to human of ARGs in backwater and living water using metagenomics and 16S rRNA gene sequencing. Our results showed higher antibiotic resistance risk presented in backwater due to higher ARG diversity, while higher resistance transfer risk occurred in living water due to higher mobile genetic elements (MGEs) diversity. Source tracking analysis revealed Yellow River water was the main the dominant source of ARGs in both backwater and living water, with an average contribution of 41.06 % and 65.82 %, respectively. Notably, nine high-risk ARGs (such as mdtM and msrA) significantly enriched in human feces, implying possible spread risk from environment to human. Metagenomics binning revealed that MAGs carrying ARGs mainly belong to Actinobacteria, while MAGs carrying MGEs belong to Proteobacteria. Our study highlights the significance of healthy management of park landscape lakes to prevent the spread of resistomes to the public.

Effect of beaver dam analogs (BDAs) on waterborne protozoal pathogens Giardia duodenalis and Cryptosporidium parvum

Installing beaver dam analogs (BDAs) in freshwater ecosystems is a process-based restoration technique mimicking natural beaver dams to increase stream channel complexity, floodplain connectivity, and hydrological residence time. BDAs have been applied in recent years by resource managers to improve riparian habitats with beneficial effects on ecosystem services, including improved water quality. While BDAs have been shown to reduce suspended sediments and nutrients in surface waters, research is needed to evaluate BDA effects on waterborne fecal pathogens such as Giardia duodenalis (syn. G. lamblia, G. intestinalis) and Cryptosporidium parvum. At a California riparian field site, this study used an in situ release trial of inactivated protozoal (oo)cysts upstream of BDAs to compare the concentrations and loads detected above and below the BDAs. The median percent decrease in load-based recovery rates was 78% for G. duodenalis and 80% for C. parvum at sites with BDAs. Mixed-effect linear regression analyses showed a significant reduction (by 81%) of the G. duodenalis adjusted cyst concentrations in downstream surface waters at sites with BDAs compared to similar sites without BDAs. While a reduction of C. parvum oocysts was noted, it was not statistically significant. The improved surface water quality downstream of BDAs could be because the BDA structures promote hyporheic exchange and act as a passive filter to remove pathogenic protozoa from streams. If BDAs are used to aid the restoration of riparian meadow ecosystems to slow water and raise the water table, they may also help to promote cleaner and safer waters for communities downstream.

IMPORTANCE

Beaver dam analogs (BDAs) are a cost-effective, low-environmental impact technique for stream and riparian meadow restoration that provide a variety of beneficial ecosystem services; however, their impact on waterborne fecal protozoal pathogens has not been evaluated. This study used an in situ protozoal release trial to quantify the effect of BDAs on the load of Giardia duodenalis and Cryptosporidium parvum in streams in California. Results showed that G. duodenalis concentrations below BDAs were significantly reduced by 81%. The median percent decrease in load-based recovery rates below a BDA for G. duodenalis and C. parvum was 78% and 80%, respectively. This finding indicates that BDAs may promote passive filtration of waterborne pathogens, thereby improving water quality in downstream reaches and adding to the beneficial outcomes associated with using BDAs in stream and meadow restoration efforts. The potential benefit to resource managers and communities is immense.

Dam construction alters the traits of health-related microbes along the Yangtze River

Dams, constructed globally for energy production and water conservation, fragment rivers, and modify flow regimes, thereby altering the composition of biological communities and ecosystem functions. Despite the extensive use of dams, few studies have explored their potential health impacts, particularly concerning changes in health-related genes, such as antibiotic resistance genes (ARGs) and virulence factor genes (VFGs), and their hosts (i.e., ARB and potential pathogens). Understanding these health-related effects is crucial because they can impact human health through water quality and pathogen prevalence. In this study, we investigated the planktonic microbial community in the Three Gorges Reservoir (TGR) and adjacent upstream and downstream areas of the Yangtze River during both the dry and wet season. Our metagenomic analysis showed that dam construction significantly decreased the abundance of ARGs, but it had an insignificant effect on VFGs. The observed reduction in ARGs abundance could be mainly attributed to the decrease abundance of the major ARGs carrier - Limnohabitansin the TGR and downstream areas due to high grazing pressure and fitness cost. Conversely, the abundance of microbes carrying VFGs (potential pathogens) remained stable from upstream to the dam reservoir, which may explain the negligible impact on VFG abundance. Overall, our results provide a detailed understanding of the ecological health implications of dam construction in large river ecosystems.

Machine learning and explainable artificial intelligence for the prevention of waterborne cryptosporidiosis and giardiosis

Cryptosporidium and Giardia are important parasitic protozoa due to their zoonotic potential and impact on human health, and have often caused waterborne outbreaks of disease. Detection of (oo)cysts in water matrices is challenging and extremely costly, thus only few countries have legislated for regular monitoring of drinking water for their presence. Several attempts have been made trying to investigate the association between the presence of such (oo)cysts in waters with other biotic or abiotic factors, with inconclusive findings. In this regard, the aim of this study was the development of an holistic approach leveraging Machine Learning (ML) and eXplainable Artificial Intelligence (XAI) techniques, in order to provide empirical evidence related to the presence and prediction of Cryptosporidium oocysts and Giardia cysts in water samples. To meet this objective, we initially modelled the complex relationship between Cryptosporidium and Giardia (oo)cysts and a set of parasitological, microbiological, physicochemical and meteorological parameters via a model-agnostic meta-learner algorithm that provides flexibility regarding the selection of the ML model executing the fitting task. Based on this generic approach, a set of four well-known ML candidates were, empirically, evaluated in terms of their predictive capabilities. Then, the best-performed algorithms, were further examined through XAI techniques for gaining meaningful insights related to the explainability and interpretability of the derived solutions. The findings reveal that the Random Forest achieves the highest prediction performance when the objective is the prediction of both contamination and contamination intensity with Cryptosporidium oocysts in a given water sample, with meteorological/physicochemical and microbiological markers being informative, respectively. For the prediction of contamination with Giardia, the eXtreme Gradient Boosting with physicochemical parameters was the most efficient algorithm, while, the Support Vector Regression that takes into consideration both microbiological and meteorological markers was more efficient for evaluating the contamination intensity with cysts. The results of the study designate that the adoption of ML and XAI approaches can be considered as a valuable tool for unveiling the complicated correlation of the presence and contamination intensity with these zoonotic parasites that could constitute, in turn, a basis for the development of monitoring platforms and early warning systems for the prevention of waterborne disease outbreaks.

Effects of wastewater treatment plant effluent on microbial risks of pathogens and their antibiotic resistance in the receiving river

The increase in effluent discharge from wastewater treatment plants (WWTPs) into urban rivers has raised concerns about the potential effects on pathogen risks. This study utilized metagenomic sequencing combined with flow cytometry to analyze pathogen concentrations and antibiotic resistance in a typical effluent-receiving river. Quantitative microbial risk assessment (QMRA) was employed to assess the microbial risks of pathogens. The results indicated obvious spatial-temporal differences (i.e., summer vs. winter and effluent vs. river) in microbial composition. Microcystis emerged as a crucial species contributing to these variations. Pathogen concentrations were found to be higher in the river than in the effluent, with the winter exhibiting higher concentrations compared to the summer. The effluent discharge slightly increased the pathogen concentrations in the river in summer but dramatically reduced them in winter. The combined effects of cyanobacterial bloom and high temperature were considered key factors suppressing pathogen concentrations in summer. Moreover, the prevalence of antibiotic resistance of pathogens in the river was inferior to that in the effluent, with higher levels in winter than in summer. Three high-concentration pathogens (Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa) were selected for QMRA. The results showed that the risks of pathogens exceeded the recommended threshold value. Escherichia coli posed the highest risks. And the fishing scenario posed significantly higher risks than the walking scenario. Importantly, the effluent discharge helped reduce the microbial risks in the receiving river in winter. The study contributes to the management and decision-making regarding microbial risks in the effluent-receiving river.

Occurrence, transmission and risks assessment of pathogens in aquatic environments accessible to humans

Pathogens are ubiquitously detected in various natural and engineered water systems, posing potential threats to public health. However, it remains unclear which human-accessible waters are hotspots for pathogens, how pathogens transmit to these waters, and what level of health risk associated with pathogens in these environments. This review collaboratively focuses and summarizes the contamination levels of pathogens on the 5 water systems accessible to humans (natural water, drinking water, recreational water, wastewater, and reclaimed water). Then, we showcase the pathways, influencing factors and simulation models of pathogens transmission and survival. Further, we compare the health risk levels of various pathogens through Quantitative Microbial Risk Assessment (QMRA), and assess the limitations of water-associated QMRA application. Pathogen levels in wastewater are consistently higher than in other water systems, with no significant variation for Cryptosporidium spp. among five water systems. Hydraulic conditions primarily govern the transmission of pathogens into human-accessible waters, while environmental factors such as temperature impact pathogens survival. The median and mean values of computed public health risk levels posed by pathogens consistently surpass safety thresholds, particularly in the context of recreational waters. Despite the highest pathogens levels found in wastewater, the calculated health risk is significantly lower than in other water systems. Except pathogens concentration, variables like the exposure mode, extent, and frequency are also crucial factors influencing the public health risk in water systems. This review shares valuable insights to the more accurate assessment and comprehensive management of public health risk in human-accessible water environments.

Coastal Water Quality Modelling Using E. coli, Meteorological Parameters and Machine Learning Algorithms

In this study, machine learning models were implemented to predict the classification of coastal waters in the region of Eastern Macedonia and Thrace (EMT) concerning Escherichia coli (E. coli) concentration and weather variables in the framework of the Directive 2006/7/EC. Six sampling stations of EMT, located on beaches of the regional units of Kavala, Xanthi, Rhodopi, Evros, Thasos and Samothraki, were selected. All 1039 samples were collected from May to September within a 14-year follow-up period (2009-2021). The weather parameters were acquired from nearby meteorological stations. The samples were analysed according to the ISO 9308-1 for the detection and the enumeration of E. coli. The vast majority of the samples fall into category 1 (Excellent), which is a mark of the high quality of the coastal waters of EMT. The experimental results disclose, additionally, that two-class classifiers, namely Decision Forest, Decision Jungle and Boosted Decision Tree, achieved high Accuracy scores over 99%. In addition, comparing our performance metrics with those of other researchers, diversity is observed in using algorithms for water quality prediction, with algorithms such as Decision Tree, Artificial Neural Networks and Bayesian Belief Networks demonstrating satisfactory results. Machine learning approaches can provide critical information about the dynamic of E. coli contamination and, concurrently, consider the meteorological parameters for coastal waters classification.

Molecular characterization of waterborne protozoa in surface water and sediment in Brazil: a taxonomic survey of ciliated protozoa and their correlation with Giardia duodenalis and Cryptosporidium spp

The detection of Giardia duodenalis and Cryptosporidium spp. was performed, along with the identification of the ciliated protozoa biodiversity, to evaluate the correlation between these protozoa in freshwater quality monitoring. Water and sediment samples from two sites in the Atibaia River (Campinas, São Paulo, Brazil) were collected monthly for 2 years (n = 96). Pathogenic protozoa in water and sediment were detected by using immunomagnetic separation, followed by visualization by immunofluorescence assay (IFA). All positive aliquots in IFA were subjected to DNA extraction and subsequently nested PCR. Qualitative (in vivo observation and silver impregnation) and quantitative (in vivo enumeration) analyses were performed for the ciliated protozoa. Giardia cysts were detected in 62.5% of the surface water samples and Cryptosporidium spp. in 25.0%. In the sediment, cysts were detected in 35.4% samples and oocysts in 16.6%. A total of 57 samples positive for Giardia cysts were subjected to sequencing, 40 of which were harboring G. duodenalis (24 were characterized as sub-assemblage AII). For ciliated protozoa, 73 taxa belonging to 53 genera were identified over the period of the study. These results revealed a high degree of contamination by waterborne protozoa in the main water source which supplies drinking water for more than one million people in Campinas (São Paulo), highlighting the need for continuous monitoring of this catchment site. In addition, the present study provides important data regarding the sources of the water body degradation, i.e., fecal contamination of human origin, in addition to the survey of the ciliated protozoa.

Biosensors for the detection of disease outbreaks through wastewater-based epidemiology

Wastewater-Based Epidemiology (WBE) is a novel community-wide monitoring tool that provides comprehensive real-time data of the public and environmental health status and can contribute to public health interventions, including those related to infectious disease outbreaks (e.g., the ongoing COVID-19 pandemic). Nonetheless, municipalities without centralized laboratories are likely still not able to process WBE samples. Biosensors are a potentially cost-effective solution to monitor the development of diseases through WBE to prevent local outbreaks. This review discusses the economic and technical feasibility of eighteen recently developed biosensors for the detection and monitoring of infectious disease agents in wastewater, prospecting the prevention of future pandemics.

Can water composition and weather factors predict fecal indicator bacteria removal in retention ponds in variable weather conditions?

Retention ponds provide benefits including flood control, groundwater recharge, and water quality improvement, but changes in weather conditions could limit the effectiveness in improving microbial water quality metrics. The concentration of fecal indicator bacteria (FIB), which is used as regulatory standards to assess microbial water quality in retention ponds, could vary widely based on many factors including local weather and influent water chemistry and composition. In this critical review, we analyzed 7421 data collected from 19 retention ponds across North America listed in the International Stormwater BMP Database to examine if variable FIB removal in the field conditions can be predicted based on changes in these weather and water composition factors. Our analysis confirms that FIB removal in retention ponds is sensitive to weather conditions or seasons, but temperature and precipitation data may not describe the variable FIB removal. These weather conditions affect suspended solid and nutrient concentrations, which in turn could affect FIB concentration in the ponds. Removal of total suspended solids and total P only explained 5% and 12% of FIB removal data, respectively, and TN removal had no correlation with FIB removal. These results indicate that regression-based modeling with a single parameter as input has limited use to predict FIB removal due to the interactive nature of their effects on FIB removal. In contrast, machine learning algorithms such as the random forest method were able to predict 65% of the data. The overall analysis indicates that the machine learning model could play a critical role in predicting microbial water quality of surface waters under complex conditions where the variation of both water composition and weather conditions could deem regression-based modeling less effective.

Review of generic screening level assumptions for quantitative microbial risk assessment (QMRA) for estimating public health risks from Australian drinking water sources contaminated with Cryptosporidium by recreational activities

As urban communities continue to grow, demand for recreational access (including swimming) in drinking water sources have increased, yet relatively little is understood about the public health implications this poses for drinking water consumers. Preventative risk-based approaches to catchment management, informed by quantitative microbial risk assessment (QMRA), requires accurate input data to effectively model risks. A sound understanding of the knowledge gaps is also important to comprehend levels of uncertainty and help prioritise research needs. Cryptosporidium is one of the most important causes of waterborne outbreaks of gastroenteritis globally due to its resistance to chlorine. This review was undertaken by Water Research Australia to provide the most up-to-date information on current Cryptosporidium epidemiological data and underlying assumptions for exposure assessment, dose response and risk assessment for generic components of QMRA for Cryptosporidium and highlights priorities for common research. Key interim recommendations and guidelines for numerical values for relatively simple screening level QMRA modelling are provided to help support prospective studies of risks to drinking water consumers from Cryptosporidium due to body-contact recreation in source water. The review does not cover site-specific considerations, such as the levels of activity in the source water, the influence of dilution and inactivation in reservoirs, or water treatment. Although the focus is Australia, the recommendations and numerical values developed in this review, and the highlighted research priorities, are broadly applicable across all drinking source water sources that allow recreational activities.

Water Quality and Microbiological Contamination across the Fish Marketing Chain: A Case Study in the Peruvian Amazon (Lagoon Yarinacocha)

The contamination of the surface water of lagoons is a common problem in developing countries, and can affect fishing activities. A case study was conducted on water quality and microbiological contamination of the fishing marketing chain in the Peruvian Amazon (Laguna de Yarinacocha). The microbiological, physical–chemical and parasitological parameters of the surface water were evaluated in three points of the lagoon near the landing stage; and microbiological parameters of facilities, handlers and three species of fish (Prochilodus nigricans, Mylossoma duriventre and Siluriforme spp.). In the water, there were coliform counts ≥ 23 (Most probable number—MPN)/100 mL, Escherichia coli ≥ 3.6 MPN/100 mL, and Pseudomona spp. up to 2.2 MPN/100 mL; high turbidity and variable amounts of parasites. In facilities and handlers, high levels of coliforms, mainly Escherichia coli, and Staphylococcus aureus and Escherichia coli, were found in M. duriventre meat. A poor quality of the surface water of the lagoon is concluded that compromises part of the fishing marketing chain, mainly facilities and manipulators. Furthermore, the levels of Staphylococcus aureus and Escherichia coli in fish meat show poor handling practices and possible risk of contamination by water sources.

Monsoon dilutes the concurrence but increases the correlation of viruses and Pharmaceuticals and Personal Care Products (PPCPs) in the urban waters of Guwahati, India: The context of pandemic viruses

Concurrence of pharmaceuticals and personal care products (PPCPs), pathogenic viruses, metals and microbial pollution along with their seasonal variations in the water environment are overarching in the context of existing pandemic, especially for tropical countries. The present study focuses on the seasonal influence on the vulnerability of urban water in Guwahati, the largest city in North-eastern India, through examining the concurrence of seven PPCPs, five viruses, faecal bacteria and nine metals in surface waters during monsoon (Summer-July 2017) and pre-monsoon (Winter-March 2018). Surface water sampling was carried out at different locations of the Brahmaputra River, its tributary Bharalu River (an unlined urban drain), and Dipor Bill Lake (Ramsar-recognized wetland). Both PPCPs and viruses were at high concentrations (e.g. up to 970 ng L^-1 caffeine, 2.5 × 10³ copies mL^-1 pepper mild mottle virus (PMMoV)) at the confluence points of urban drains and the river, while they were mostly undetectable at both upstream and downstream locations, implying strong self-purification ability of the river. All the analysed PPCPs and viruses were at much higher concentrations during pre-monsoon i.e., winter than during monsoon, implying heavy dilution and temperature effect during the monsoon. Overall, PPCPs and viruses were more correlated in monsoon but the risk quotient in the urban tributary was higher in pre-monsoon (e.g. 5061 in pre-monsoon and 1515 in monsoon for caffeine). PMMoV was found to be an excellent faecal pollution indicator due to its prevalence, detectability and specificity in all seasons. Overall, the seasonal fluctuations of the non-enveloped viruses monitored in this study is likely to be relevant for SARS-CoV-2. We contribute to address the literature scarcity pertaining to seasonal variations in the prevalence of viruses and their concurrences with contaminants of emerging concern.

Infrastructure alone cannot ensure resilience to weather events in drinking water supplies

Climate resilient water supplies are those that provide access to drinking water that is sustained through seasons and through extreme events, and where good water quality is also sustained. While surface and groundwater quality are widely understood to vary with rainfall, there is a gap in the evidence on the impact of weather and extremes in rainfall and temperature on drinking water quality, and the role of changes in water system management. A three-country (Bangladesh, Nepal and Tanzania) observational field study tracked 2353 households clustered around 685 water sources across seven different geographies over 14 months. Water quality (E. coli) data was modelled using GEE to account for clustering effects and repeated measures at households. All types of infrastructure were vulnerable to changes in weather, with differences varying between geographies; protected boreholes provided the greatest protection at the point of collection (PoC). Water quality at the point of use (PoU) was vulnerable to changes in weather, through changes in PoC water quality as well as changes in management behaviours, such as safe storage, treatment and cleaning. This is the first study to demonstrate the impact of rainfall and temperature extremes on water quality at the PoC, and the role that weather has on PoU water quality via management behaviours. Climate resilience for water supplies needs to consider the infrastructure as well as the management decisions that are taking place at a community and household level.

Learning hierarchical Bayesian networks to assess the interaction effects of controlling factors on spatiotemporal patterns of fecal pollution in streams

The dynamics of fecal indicator bacteria, such as fecal coliforms (FC) in streams, are influenced by the interactions of a myriad of factors. To predict complex spatiotemporal patterns of FC in streams and assess the relative importance of numerous controlling factors, the adoption of a hierarchical Bayesian network (HBN) was proposed in this study. By introducing latent variables correlated to the observed variables into a Bayesian network, the HBN can represent causal relationships among a large set of variables with a multilevel hierarchy. The study area encompasses 215 sites across the watersheds of the four major rivers in South Korea. The monitoring data collected during the 2012-2019 period included 32 input variables pertaining to meteorology, geography, soil characteristics, land cover, urbanization index, livestock density, and point sources. As model endpoints, the exceedance probability of the FC standard concentration as well as two pollution characteristics (i.e., pollution degree and type), derived from FC load duration curves were used. The probability of exceeding an FC threshold value (200 CFU/100 mL) showed spatiotemporal variations, whereas pollution degree and type showed spatial variations that represent long-term severity and relative dominance of nonpoint and point source fecal pollution, respectively. The conceptual model was validated using structural equation modeling to develop the HBN. The results demonstrate that the HBN effectively simplified the model structure, while showing strong model performance (AUC = 0.81, accuracy = 0.74). The results of the sensitivity analysis indicate that land cover is the most important factor in predicting the probability of exceedance and pollution degree, whereas the urbanization index explains most of the variability in pollution type. Furthermore, the results of the scenario analysis suggest that the HBN provides an interpretable framework in which the interaction of controlling factors has causal relationships at different levels that can be identified and visualized.

The Impact of Extreme Weather Events on Bacterial Communities and Opportunistic Pathogens in a Drinking Water Treatment Plant

Drinking water treatment processes are highly effective at improving water quality, but pathogens can still persist in treated water, especially after extreme weather events. To identify how extreme weather events affected bacterial populations in source and treated water, water samples were collected from the Yangtze River Delta area and a local full-scale drinking water treatment plant. Bacterial community structure and the occurrence of pathogens were investigated in samples using 16S rRNA sequencing and qPCR techniques. In this study, the results show that intense rainfall can significantly increase levels of bacteria and opportunistic pathogens in river and drinking water treatment processes (p < 0.05); in particular, the relative abundance of Cyanobacteria increased after a super typhoon event (p < 0.05). The biological activated carbon (BAC) tank was identified as a potential pathogen reservoir and was responsible for 52 ± 6% of the bacteria released downstream, according to Bayesian-based SourceTracker analysis. Our results provide an insight into the challenges faced by maintaining finished water quality under changing weather conditions.

Long-term changes in microbial water quality indicators in a hydro-power plant reservoir: The role of natural factors and socio-economic changes

Long-term changes, from 1984 to 2010, in the indicators of microbial pollution (total viable count, coliforms, Escherichia coli, enterococci, and Clostridium perfringens) are analysed in the Riga Hydropower Plant Reservoir, an essential source of drinking water for Riga, the capital of Latvia. Counts in microbial indicators fluctuated seasonally and were related to physicochemical parameters (nitrogen compounds, turbidity, temperature, and pH). The changes in microbial pollution were brought about by two major socio-economic developments. Firstly, Latvia's independence from the USSR in 1991 which facilitated a distinct reduction in most microorganism counts due to a sharp decline in industrial and agricultural production. This resulted in a significant drop in point and nonpoint pollution in the river basin. A further development was Latvia joining the European Union in 2004. The corresponding focus on water management, including wastewater treatment, was a major priority of environmental investment and lead to improvements in microbial water quality.

Seasonal dynamics in taxonomy and function within bacterial and viral metagenomic assemblages recovered from a freshwater agricultural pond

BACKGROUND

Ponds are important freshwater habitats that support both human and environmental activities. However, relative to their larger counterparts (e.g. rivers, lakes), ponds are understudied, especially with regard to their microbial communities. Our study aimed to fill this knowledge gap by using culture-independent, high-throughput sequencing to assess the dynamics, taxonomy, and functionality of bacterial and viral communities in a freshwater agricultural pond.

RESULTS

Water samples (n = 14) were collected from a Mid-Atlantic agricultural pond between June 2017 and May 2018 and filtered sequentially through 1 and 0.2 μm filter membranes. Total DNA was then extracted from each filter, pooled, and subjected to 16S rRNA gene and shotgun sequencing on the Illumina HiSeq 2500 platform. Additionally, on eight occasions water filtrates were processed for viral metagenomes (viromes) using chemical concentration and then shotgun sequenced. A ubiquitous freshwater phylum, Proteobacteria was abundant at all sampling dates throughout the year. However, environmental characteristics appeared to drive the structure of the community. For instance, the abundance of Cyanobacteria (e.g. Nostoc) increased with rising water temperatures, while a storm event appeared to trigger an increase in overall bacterial diversity, as well as the relative abundance of Bacteroidetes. This event was also associated with an increase in the number of antibiotic resistance genes. The viral fractions were dominated by dsDNA of the order Caudovirales, namely Siphoviridae and Myovirdae.

CONCLUSIONS

Overall, this study provides one of the largest datasets on pond water microbial ecology to date, revealing seasonal trends in the microbial taxonomic composition and functional potential.

High Prevalence of Human-Associated Escherichia coli in Wetlands Located in Eastern France

Escherichia coli that are present in the rivers are mostly brought by human and animal feces. Contamination occurs mostly through wastewater treatment plant (WWTP) outflows and field amendment with sewage sludge or manure. However, the survival of these isolates in river-associated wetlands remains unknown. Here, we assessed E. coli population structure in low-anthropized wetlands located along three floodplains to identify the major source of contamination of wetlands, whose functioning is different from the rivers. We retrieved 179 E. coli in water samples collected monthly from 19 sites located in eastern France over 1 year. Phylogroups B1 and B2 were dominant in the E. coli population, while phylogroup A was dominant in isolates resistant to third-generation cephalosporins, which harbored the extended-spectrum β-lactamase (ESBL) encoding genes bla_CTX–M–15 and bla_CTX–M–27 in half of the cases. The high proportion of isolates from human source can be attributed to WWTP outflows and the spread of sewage sludge. We analyzed the distribution of the isolates belonging to the most human-associated phylogroups (B2 and D) on a phylogenetic tree of the whole species and compared it with that of isolates retrieved from patients and from WWTP outflows. The distribution of the three E. coli populations was similar, suggesting the absence of a specific population in the environment. Our results suggest that a high proportion of E. coli isolates that reach and survive in low-anthropized environments such as wetlands are from human source. To the best of our knowledge, this is the first study assessing E. coli contamination and resistance genes in natural freshwater wetlands.

Cryptosporidium and Giardia in surface water and drinking water: Animal sources and towards the use of a machine-learning approach as a tool for predicting contamination

Cryptosporidium and Giardia are important parasites due to their zoonotic potential and impact on human health, often causing waterborne outbreaks of disease. Detection of (oo)cysts in water matrices is challenging and few countries have legislated water monitoring for their presence. The aim of this study was to investigate the presence and origin of these parasites in different water sources in Northern Greece and identify interactions between biotic/abiotic factors in order to develop risk-assessment models. During a 2-year period, using a longitudinal, repeated sampling approach, 12 locations in 4 rivers, irrigation canals, and a water production company, were monitored for Cryptosporidium and Giardia, using standard methods. Furthermore, 254 faecal samples from animals were collected from 15 cattle and 12 sheep farms located near the water sampling points and screened for both parasites, in order to estimate their potential contribution to water contamination. River water samples were frequently contaminated with Cryptosporidium (47.1%) and Giardia (66.2%), with higher contamination rates during winter and spring. During a 5-month period, (oo)cysts were detected in drinking-water (<1/litre). Animals on all farms were infected by both parasites, with 16.7% of calves and 17.2% of lambs excreting Cryptosporidium oocysts and 41.3% of calves and 43.1% of lambs excreting Giardia cysts. The most prevalent species identified in both water and animal samples were C. parvum and G. duodenalis assemblage AII. The presence of G. duodenalis assemblage AII in drinking water and C. parvum IIaA15G2R1 in surface water highlights the potential risk of waterborne infection. No correlation was found between (oo)cyst counts and faecal-indicator bacteria. Machine-learning models that can predict contamination intensity with Cryptosporidium (75% accuracy) and Giardia (69% accuracy), combining biological, physicochemical and meteorological factors, were developed. Although these prediction accuracies may be insufficient for public health purposes, they could be useful for augmenting and informing risk-based sampling plans.

Occurrence and ecological determinants of the contamination of floodplain wetlands with Klebsiella pneumoniae and pathogenic or antibiotic-resistant Escherichia coli

The survival and multiplication of human pathogenic and antibiotic-resistant bacteria in ecosystems is of increasing concern but has been little explored. Wetlands can be contaminated by water fluxes from rivers and may present environmental conditions leading to bacterial survival and multiplication. To test this hypothesis, we sampled 16 wetlands located along three rivers of the Jura Massif, France. The bacterial contamination of the wetland and river waters was measured monthly over a one-year cycle together with the water physico-chemical characteristics. We assessed the abundance of three pathogenic species: Escherichia coli,Klebsiella pneumoniaeand Pseudomonas aeruginosa. The concentrations of E. coli producing extended-spectrum β-lactamase (ESBL E. coli) or belonging to the phylogenetic group B2 (E. coli B2–more pathogenic) were also measured. We found that rivers carried total E. coli, ESBL E. coli, and K. pneumoniae to wetlands. ESBL E. coli poorly survived in wetlands, whereas total E. coli and K. pneumoniae possibly met favourable physico-chemical conditions for survival and multiplication in these habitats. K. pneumoniae peaked in summer in warm and shallow wetlands. Total E. coli and E. coli B2 potentially reached wetlands through sources other than rivers (hillslope groundwater or leaching from contaminated fields).

Meteolakes: An operational online three-dimensional forecasting platform for lake hydrodynamics

Environmental management depends on high-quality monitoring and its meaningful interpretation. The combination of local weather dynamics, regional anthropogenic stresses and global environmental changes make the evaluation of monitoring information in dynamic freshwater systems a challenging task. While the lake ecosystems gather many complex biogeochemical interactions, they remain constrained by the same physical environment of mixing and transport. It is therefore crucial to obtain high-quality physical system insight. Three-dimensional hydrodynamic models are perfectly suited for providing such information. However, these models are complex to implement, and their use is often limited to modellers. Here, we aim to provide model output via a user-friendly platform to a broad audience ranging from scientists to public and governmental stakeholders. We present a unified approach merging the apparently diverse interests through meteolakes.ch, an online platform openly disseminating lake observations and three-dimensional numerical simulations in near real-time with short-term forecasts and data assimilation. Meteolakes is scalable to a broad range of devices, modular and distributed, hence allowing its expansion to other regions and hardware infrastructures. Since 2016, the platform has continuously provided timely synoptic lake information to more than 250,000 users. This web-based system was built not only to provide guidance to scientists in the design and analysis of field experiments and to foster interdisciplinary lake studies, but also to assist governmental agencies and professionals in the long-term policy and planning of water resources management. Finally, our system aimed at promoting awareness and understanding of the complexity of lakes and providing information to the public through user-friendly interfaces. This article details the design and operation of such a platform and its products. Applications are demonstrated by examples of a recent upwelling and a storm event. Both cases illustrate how Meteolakes help scientists in their quest for process understanding as well as water professionals and civil society in providing specific warnings.

Concurrence of antibiotic resistant bacteria (ARB), viruses, pharmaceuticals and personal care products (PPCPs) in ambient waters of Guwahati, India: Urban vulnerability and resilience perspective

Multi-drug resistant microbes, pathogenic viruses, metals, and pharmaceuticals and personal care products (PPCPs) in water has become the crux of urban sustainability issues. However, vulnerability due to pollutant concurrences, source apportionment, and identification of better faecal indicators needs to be better understood. The present study focuses on the vulnerability of urban Guwahati, the largest city in Northeastern India, through analyzing the concurrence of PPCPs, enteric viruses, antibiotic resistant bacteria, metal, and faecal contamination in water. The study strives to identify a relevant marker of anthropogenic pollution for the Indian scenario. Samples from the Brahmaputra River (n = 4), tributary Bharalu River (an unlined urban drain; n = 3), and Ramsar recognized Lake (Dipor Bil; n = 1) indicate caffeine > acetaminophen > theophylline > carbamazepine > crotamiton for PPCPs and pepper mild mottle virus (PMMoV) > aichi > hepatitis A > norovirus GII > norovirus GI for enteric viruses. PMMoV was the better indicator of faecal pollution due to its prevalence, specificity and ease of detection. Antibiotic resistance was neither correlated with the prevalence of PPCPs nor E. coli. As, Co and Mn appear to be inducing antibiotic resistance in E. coli. While the risk quotient of the urban drain (Bharalu River) indicates one order higher magnitude than reported for other Indian rivers, the Lake exhibited the least pollution and better resilience. The concurrence of pollutants and multi-drug resistant E. coli, owing to the complete absence of wastewater treatment, puts the city in a highly vulnerable state. Pollution is being regulated only by the dilution capability of the Brahmaputra River, which needs to be further researched for seasonal variation.

Comparison of pathogen-derived 'total risk' with indicator-based correlations for recreational (swimming) exposure

Typical recreational water risk to swimmers is assessed using epidemiologically derived correlations by means of fecal indicator bacteria (FIB). It has been documented that concentrations of FIB do not necessarily correlate well with protozoa and viral pathogens, which pose an actual threat of illness and thus sometimes may not adequately assess the overall microbial risks from water resources. Many of the known pathogens have dose-response relationships; however, measuring water quality for all possible pathogens is impossible. In consideration of a typical freshwater receiving secondarily treated effluent, we investigated the level of consistency between the indicator-derived correlations and the sum of risks from six reference pathogens using a quantitative microbial risk assessment (QMRA) approach. Enterococci and E. coli were selected as the benchmark FIBs, and norovirus, human adenovirus (HAdV), Campylobacter jejuni, Salmonella enterica, Cryptosporidium spp., and Giardia spp. were selected as the reference pathogens. Microbial decay rates in freshwater and uncertainties in exposure relationships were considered in developing our analysis. Based on our exploratory assessment, the total risk was found within the range of risk estimated by the indicator organisms, with viral pathogens as dominant risk agents, followed by protozoan and bacterial pathogens. The risk evaluated in this study captured the likelihood of gastrointestinal illnesses only, and did not address the overall health risk potential of recreational waters with respect to other disease endpoints. Since other highly infectious pathogens like hepatitis A and Legionella spp. were not included in our analysis, these estimates should be interpreted with caution.

Opportunities and Challenges for the Sustainability of Lakes and Reservoirs in Relation to the Sustainable Development Goals (SDGs)

Emerging global threats, such as biological invasions, climate change, land use intensification, and water depletion, endanger the sustainable future of lakes and reservoirs. To deal with these threats, a multidimensional view on the protection and exploitation of lakes and reservoirs is needed. The holistic approach needs to contain not just the development of economy and society but also take into account the negative impacts of this growth on the environment, from that, the balance between the three dimensions can be sustained to reach a sustainable future. As such, this paper provides a comprehensive review on future opportunities and challenges for the sustainable development of lakes and reservoirs via a critical analysis on their contribution to individual and subsets of the Sustainable Development Goals (SDGs). Currently, lakes and reservoirs are key freshwater resources. They play crucial roles in human societies for drinking water provision, food production (via fisheries, aquaculture, and the irrigation of agricultural lands), recreation, energy provision (via hydropower dams), wastewater treatment, and flood and drought control. Because of the (mostly) recent intensive exploitations, many lakes and reservoirs are severely deteriorated. In recent years, physical (habitat) degradation has become very important while eutrophication remains the main issue for many lakes and ponds worldwide. Besides constant threats from anthropogenic activities, such as urbanization, industry, aquaculture, and watercourse alterations, climate change and emerging contaminants, such as microplastics and antimicrobial resistance, can generate a global problem for the sustainability of lakes and reservoirs. In relation to the SDGs, the actions for achieving the sustainability of lakes and reservoirs have positive links with the SDGs related to environmental dimensions (Goals 6, 13, 14, and 15) as they are mutually reinforcing each other. On the other hand, these actions have direct potential conflicts with the SDGs related to social and economic dimensions (Goals 1, 2, 3 and 8). From these interlinkages, we propose 22 indicators that can be used by decision makers for monitoring and assessing the sustainable development of lakes and reservoirs.

Impact of copper sulphate, potassium permanganate, and hydrogen peroxide on Pseudanabaena galeata cell integrity, release and degradation of 2-methylisoborneol

Frequent off-flavor events caused by geosmin and 2-methylisoborneol have caused concern among consumers about the quality of potable water. Pseudanabaena galeata, a filamentous cyanobacterium, is a known producer of 2-methylisoborneol in lakes and reservoirs. The use of algicides to control cyanobacteria must consider the potential release of contaminants into the water. This is the first study to systematically investigate the effectiveness of copper sulphate (CuSO₄), potassium permanganate (KMnO₄), and hydrogen peroxide (H₂O₂) on the cell viability and integrity of Pseudanabaena galeata. Following algicide or oxidant treatment, the release and degradation of 2-methylisoborneol was also examined. It is evident that all of these chemicals can decrease Pseudanabaena galeata viability and damage cell membranes and the filamentous Pseudanabaena galeata was more susceptible to treatment by these three algicides than unicellular colonial Microcystis aeruginosa. Of the three compounds used, KMnO₄ showed the stronger ability to compromise cell integrity and 5.0 mg/L KMnO₄ could induce 91 ± 1.5% lysis of Pseudanabaena galeata within 2 h. It was found that H₂O₂ had the potential to degrade 2-methylisoborneol with 16.0 ± 0.4% degraded by 20.0 mg/L H₂O₂ within 8 h. In contrast, 2-methylisoborneol could not be degraded by CuSO₄ (dosage: ≤ 1.5 mg/L; reaction time: ≤ 8 h) and KMnO₄ (dosage: ≤ 5.0 mg/L; reaction time: ≤ 3 h) basically. Results showed that the oxidation capacity of H₂O₂ against Pseudanabaena galeata was enhanced under sunlight. The results will help drinking water utilities to better understand the risk of Pseudanabaena galeata lysis and 2-methylisoborneol release during raw water treatment.

Diversity and abundance of bacterial pathogens in urban rivers impacted by domestic sewage

In developing countries, many urban rivers are suffering from heavy contamination by untreated sewage, which implies great microbial risks. However, information regarding the bacterial pathogen diversity and distribution in urban rivers is highly limited. In this study, 41 water samples of fifteen rivers and eight samples from two sewage treatment plants in Changzhou City of Yangtze River Delta were sampled. Next-generation sequencing and a self-built reference pathogen database were used to investigate the diversity of enteric and environmental pathogens. The results indicated that the studied urban rivers were harboring diverse potential pathogen species, which primarily included enteric pathogens in Arcobacter and Bacteroides, and environmental pathogens in Acinetobacter, Aeromonas and Pseudomonas. Quantification of twelve pathogens/indicators of interest by qPCR showed that Escherichia coli, Enterococcus faecalis, Campylobacter jejuni, Arcobacter cryaerophilus, Acinetobacter johnsonii, Acinetobacter lwoffii and Aeromonas spp. were abundant, with median values ranging from 3.30 to 5.85 log₁₀ copies/100 mL, while Salmonella, Legionella pheumophila, Mycobacterium avium, Pseudomonas aeruginosa and Staphylococcus aureus were infrequently quantified. The pollution of nutrients and human intestinal microorganisms indicated by specific markers were found to be prevalent but with different levels in the rivers. The correlation analyses revealed that the diversity (p < 0.01) and concentrations (p < 0.05) of the enteric pathogens highly correlated to the human fecal marker abundances, which indicated that the enteric pathogens in the urban rivers were likely to have originated from domestic sewage. The environmental pathogens, which are different from the enteric ones, showed various distribution patterns, and some of them were more abundant in the rivers of rich nutrient. Our findings provide a comprehensive understanding of the bacterial pathogen distribution and influencing factors in urban rivers that are impacted by domestic sewage, thereby establishing the foundation for urban water management.

Cryptosporidium and Giardia in Wastewater and Surface Water Environments

and spp. are significant contributors to the global waterborne disease burden. Waterways used as sources of drinking water and for recreational activity can become contaminated through the introduction of fecal materials derived from humans and animals. Multiple studies have reported the occurence or concentrations of these pathogens in the environment. However, this information has not been comprehensively reviewed. Quantitative microbial risk assessment (QMRA) for and can be beneficial, but it often relies on the concentrations in environmental sources reported from the literature. A thorough literature review was conducted to develop an inventory of reported and concentrations in wastewater and surface water available in the literature. This information can be used to develop QMRA inputs. and (oo)cyst concentrations in untreated wastewater were up to 60,000 oocysts L and 100,000 cysts L, respectively. The maximum reported concentrations for and in surface water were 8400 oocysts L and 1000 cysts L, respectively. A summary of the factors for interpretation of concentration information including common quantification methods, survival and persistence, biofilm interactions, genotyping, and treatment removal is provided in this review. This information can help in identifying assumptions implicit in various QMRA parameters, thus providing the context and rationale to guide model formulation and application. Additionally, it can provide valuable information for water quality practitioners striving to meet the recreational water quality or treatment criteria. The goal is for the information provided in the current review to aid in developing source water protection and monitoring strategies that will minimize public health risks.

Occurrence of Traditional and Alternative Fecal Indicators in Tropical Urban Environments under Different Land Use Patterns

This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli, Enterococcus spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; P < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; P < 0.01) compared to traditional FIB (rho = 0.583; P < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; P < 0.05).IMPORTANCE The results of this study may support the hypothesis of using PMMoV as an alternative indicator of human fecal contamination in tropical surface waters from the perspective of land use patterns. The predictive result of the occurrence of human fecal indicators with high accuracy may reflect the source and transportation of human fecal pollution, which are directly related to the risk to human health, and thereafter, steps can be taken to mitigate these risks.

Simulating the fate of indigenous antibiotic resistant bacteria in a mild slope wastewater polluted stream

The fate of indigenous surface-water and wastewater antibiotic resistant bacteria in a mild slope stream simulated through a hydraulic channel was investigated in outdoor experiments. The effect of (i) natural (dark) decay, (ii) sunlight, (iii) cloudy cover, (iv) adsorption to the sediment, (v) hydraulic conditions, (vi) discharge of urban wastewater treatment plant (UWTP) effluent and (vii) bacterial species (presumptive Escherichia coli and enterococci) was evaluated. Half-life time (T_1/2) of E. coli under sunlight was in the range 6.48-27.7min (initial bacterial concentration of 10⁵CFU/mL) depending on hydraulic and sunlight conditions. E. coli inactivation was quite similar in sunny and cloudy day experiments in the early 2hr, despite of the light intensity gradient was in the range of 15-59W/m²; but subsequently the inactivation rate decreased in the cloudy day experiment (T_1/2=23.0min) compared to sunny day (T_1/2=17.4min). The adsorption of bacterial cells to the sediment (biofilm) increased in the first hour and then was quite stable for the remaining experimental time. Finally, when the discharge of an UWTP effluent in the stream was simulated, the proportion of indigenous antibiotic resistant E. coli and enterococci was found to increase as the exposure time increased, thus showing a higher resistance to solar inactivation compared to the respective total populations.

Particle attached and free floating pathogens survival kinetics under typical stream and thermal spring temperature conditions

Improved understanding of pathogen survival in the stream environment is needed to enhance existing predictive models of stream pathogen populations. Further, the increasing use of thermal springs for bathing necessitates additional studies focused on not only typical streams but also thermal spring conditions, where water temperature is relatively higher than typical streams. This study was conducted to assess the survival of E. coli O157:H7 and Salmonella Typhimurium in stream water under free floating and particle-attached conditions at a range of temperature. A series of microcosm studies were conducted to determine pathogen decay rates. In bench-scale experiments, water circulation and sediment resuspension mimicked natural stream and thermal spring conditions, with continuous air flow providing aeration, constant mixing and turbulent conditions, and improved water circulation. Data on E. coli O157:H7 and Salmonella survival were subsequently used to determine first-order decay equations for calculating the rate constant and decimal reduction time for the modeled experimental conditions. Results showed that at 40 °C, the survival of particle attached E. coli O157:H7 was longer than that of particle attached Salmonella. Under free floating condition, Salmonella survived longer than E. coli O157:H7. At 50 °C, survival of particle attached E. coli O157:H7 and Salmonella was longer than that of free floating E. coli and Salmonella. At 60 °C, survival of particle attached Salmonella was longer than that of free floating Salmonella. Similarly at 60 °C, the survival of E. coli O157:H7  under particle attached condition was longer than that of the free floating condition. The findings of this study suggest that the survival of E. coli O157:H7 differs than the survival of Salmonella in stream water and thermal spring conditions, and the assumption used in previous studies to estimate survival of bacteria in stream environment could result in over/underestimation if the impact of particle attachment on pathogen survival is not accounted for.

Occurrence and molecular characterization of Giardia duodenalis cysts and Cryptosporidium oocysts in raw water samples from the Rímac River, Peru

Giardia and Cryptosporidium are potentially pathogenic protozoa which are ubiquitous in ambient surface water. The present study included 60 samples of surface water from three sampling sites from the Rímac River, Lima and Callao, Peru, to detect the occurrence of Giardia spp. and Cryptosporidium spp. and to perform molecular characterization of specimens found. Water samples were concentrated using the membrane filtration technique, and following elution, cysts and oocysts were visualized by direct immunofluorescence assay (IFA). For molecular characterization, tpi and bg gene fragments and 18S rRNA were amplified by nested PCR for Giardia and Cryptosporidium, respectively, followed by sequencing and phylogenetic analysis. Giardia cysts were found in 93.3% of the analyzed samples, whereas Cryptosporidium oocysts were detected in 15%. The positivity of the Giardia cysts was 86.6% (n = 26) in 2014, while Cryptosporidium oocysts were not detected. In 2015, both protozoa were found in raw water samples, with all 30 samples collected positive for Giardia cysts (100.0%) and 9 positive for Cryptosporidium oocysts (30.0%). Oocysts were detected in 20.0% of water samples from sites 1 (mean 5.25 oocysts/L) and 2 (mean 52.3 oocysts/L), while at site 3, oocysts were detected in 50.0% of raw water samples (mean 193.6 oocysts/L). The presence of Giardia duodenalis assemblage A was confirmed in several samples by the phylogenetic positioning of the bg and tpi genes, and the sub-assemblage AII was predominant (8/9). Sequencing for Cryptosporidium resulted in profiles compatible with Cryptosporidium hominis, Cryptosporidium meleagridis, and Cryptosporidium baileyi. This is the first time that the presence of G. duodenalis assemblage A/sub-assemblage AII and Cryptosporidium species has been reported in surface water samples in Peru. These Cryptosporidium species and the Giardia duodenalis assemblage are associated with human disease which highlights the potential risk to public health and the need to increase environmental monitoring measures to protect this water body.

Antagonistic Microbial Interactions: Contributions and Potential Applications for Controlling Pathogens in the Aquatic Systems

Despite the active and intense treatment of wastewater, pathogenic microorganisms and viruses are frequently introduced into the aquatic environment. For most human pathogens, however, this is a rather hostile place, where starvation, continuous inactivation, and decay generally occur, rather than successful reproduction. Nevertheless, a great diversity of the pathogenic microorganisms can be detected, in particular, in the surface waters receiving wastewater. Pathogen survival depends majorly on abiotic factors such as irradiation, changes in water ionic strength, temperature, and redox state. In addition, inactivation is enhanced by the biotic interactions in the environment. Although knowledge of the antagonistic biotic interactions has been available since a long time, certain underlying processes and mechanisms still remain unclear. Others are well-appreciated and increasingly are applied to the present research. Our review compiles and discusses the presently known biotic interactions between autochthonous microbes and pathogens introduced into the aquatic environment, including protozoan grazing, virus-induced bacterial cell lysis, antimicrobial substances, and predatory bacteria. An overview is provided on the present knowledge, as well as on the obvious research gaps. Individual processes that appear promising for future applications in the aquatic environment are presented and discussed.

Concentration and quantification of somatic and F+ coliphages from recreational waters

Somatic and F+ coliphages are promising alternative fecal indicators, but current detection methods are hindered by lower levels of coliphages in surface waters compared to traditional bacterial fecal indicators. We evaluated the ability of dead-end hollow fiber ultrafiltration (D-HFUF) and single agar layer (SAL) procedure to concentrate and enumerate coliphages from 1L and 10L volumes of ambient surface waters (lake, river, marine), river water with varying turbidities (3.74–118.7 NTU), and a simulated combined sewer overflow (CSO) event. Percentage recoveries for surface waters were 40–79% (somatic) and 35–94% (F + ). The method performed equally well in all three matrices at 1L volumes, but percent recoveries were significantly higher in marine waters at 10L volumes when compared to freshwater. Percent recoveries at 1L and 10L were similar, except in river water where recoveries were significantly lower at higher volume. In highly turbid waters, D-HFUF-SAL had a recovery range of 25–77% (somatic) and 21–80% (F + ). The method produced detectable levels of coliphages in diluted wastewater and in unspiked surface waters, emphasizing its applicability to CSO events and highlighting its utility in recovery of low coliphage densities from surface waters. Thus D-HFUF-SAL is a good candidate method for routine water quality monitoring of coliphages.

Quantifying pathogen risks associated with potable reuse: A risk assessment case study for Cryptosporidium

This study evaluated the reliability and equivalency of three different potable reuse paradigms: (1) surface water augmentation via de facto reuse with conventional wastewater treatment; (2) surface water augmentation via planned indirect potable reuse (IPR) with ultrafiltration, pre-ozone, biological activated carbon (BAC), and post-ozone; and (3) direct potable reuse (DPR) with ultrafiltration, ozone, BAC, and UV disinfection. A quantitative microbial risk assessment (QMRA) was performed to (1) quantify the risk of infection from Cryptosporidium oocysts; (2) compare the risks associated with different potable reuse systems under optimal and sub-optimal conditions; and (3) identify critical model/operational parameters based on sensitivity analyses. The annual risks of infection associated with the de facto and planned IPR systems were generally consistent with those of conventional drinking water systems [mean of (9.4 ± 0.3) × 10^-5 to (4.5 ± 0.1) × 10^-4], while DPR was clearly superior [mean of (6.1 ± 67) × 10^-9 during sub-optimal operation]. Because the advanced treatment train in the planned IPR system was highly effective in reducing Cryptosporidium concentrations, the associated risks were generally dominated by the pathogen loading already present in the surface water. As a result, risks generally decreased with higher recycled water contributions (RWCs). Advanced treatment failures were generally inconsequential either due to the robustness of the advanced treatment train (i.e., DPR) or resiliency provided by the environmental buffer (i.e., planned IPR). Storage time in the environmental buffer was important for the de facto reuse system, and the model indicated a critical storage time of approximately 105 days. Storage times shorter than the critical value resulted in significant increases in risk. The conclusions from this study can be used to inform regulatory decision making and aid in the development of design or operational criteria for IPR and DPR systems.

Evaluation of bacterial pathogen diversity, abundance and health risks in urban recreational water by amplicon next-generation sequencing and quantitative PCR

The microbial quality of urban recreational water is of great concern to public health. The monitoring of indicator organisms and several pathogens alone is not sufficient to accurately and comprehensively identify microbial risks. To assess the levels of bacterial pathogens and health risks in urban recreational water, we analyzed pathogen diversity and quantified four pathogens in 46 water samples collected from waterbodies in Beijing Olympic Forest Park in one year. The pathogen diversity revealed by 16S rRNA gene targeted next-generation sequencing (NGS) showed that 16 of 40 genera and 13 of 76 reference species were present. The most abundant species were Acinetobacter johnsonii, Mycobacterium avium and Aeromonas spp. Quantitative polymerase chain reaction (qPCR) of Escherichia coli (uidA), Aeromonas (aerA), M. avium (16S rRNA), Pseudomonas aeruginosa (oaa) and Salmonella (invA) showed that the aerA genes were the most abundant, occurring in all samples with concentrations of 10^4-6 genome copies/100mL, followed by oaa, invA and M. avium. In total, 34.8% of the samples harbored all genes, indicating the prevalence of these pathogens in this recreational waterbody. Based on the qPCR results, a quantitative microbial risk assessment (QMRA) showed that the annual infection risks of Salmonella, M. avium and P. aeruginosa in five activities were mostly greater than the U.S. EPA risk limit for recreational contacts, and children playing with water may be exposed to the greatest infection risk. Our findings provide a comprehensive understanding of bacterial pathogen diversity and pathogen abundance in urban recreational water by applying both NGS and qPCR.

The effect of anthropogenic pressure shown by microbiological and chemical water quality indicators on the main rivers of Podhale, southern Poland

This study was aimed to determine the spatial variation in anthropogenic pressure exerted on surface water in the Podhale region (southern Poland), which is one of the most popular tourist destinations in Poland. The assessment was based on the dynamics and relationships between microbiological and chemical indicators of water quality throughout the major rivers of this region-Dunajec, Czarny Dunajec, Biały Dunajec, and Białka. Another aim was to assess the effect of land use on the quality of water in the studied rivers. The study was conducted over 1 year at 21 sampling sites distributed from the uppermost sections of rivers in the Tatra National Park through main tourist resorts until mouths of the considered rivers to the Czorsztyńskie Lake. Microbiological analysis comprised the prevalence of total and fecal types of coliforms and Escherichia coli, mesophilic, and psychrophilic bacteria. Chemical assays determined the concentrations of Na+, K+, NH4+, Cl-, NO3-, and PO43-. Temperature, electrical conductivity, and pH were measured onsite. It was demonstrated that there is a significant relationship between the predominant types of land use within individual catchments, which results in evident differences in the pollution of waters between the catchments. The results showed that increased share of built-up areas and arable land results in significant deterioration of water quality. Thus, waters of Czarny Dunajec were the cleanest, while Biały Dunajec was the most heavily contaminated. Also, spatial diversity in water quality was shown-the cleanest waters were sampled in the Tatra National Park and the pollution increased with the course of rivers. Point sources of pollution such as effluents from treatment plants or discharge of untreated sewage from households proved to be more important than non-point sources, such as surface runoff. Moreover, the important role of the Czorsztyńskie Lake in the purification of water was demonstrated.

Spatio-temporal distribution of fecal indicators in three rivers of the Haihe River Basin, China

Because of their significant impact on public health, waterborne pathogens, especially bacteria and viruses, are frequently monitored in surface water to assess microbial quality of water bodies. However, more than one billion people worldwide currently lack access to safe drinking water, and a diversity of waterborne outbreaks caused by pathogens is reported in nations at all levels of economic development. Spatio-temporal distribution of conventional pollutants and five pathogenic microorganisms were discussed for the Haihe River Basin. Land use and socio-economic assessments were coupled with comprehensive water quality monitoring. Physical, chemical, and biological parameters were measured at 20 different sites in the watershed for 1 year, including pH, temperature, conductivity, dissolved oxygen, turbidity, chemical oxygen demand, ammonia-N, total and fecal coliforms, E. coli, and Enterococcus. The results highlighted the high spatio-temporal variability in pathogen distribution at watershed scale: high concentration of somatic coliphages and fecal indicator bacteria in March and December and their very low concentration in June and September. All pathogens were positively correlated to urban/rural residential/industrial land and negatively correlated to other four land use types. Microbial pollution was greatly correlated with population density, urbanization rate, and percentage of the tertiary industry in the gross domestic product. In the future, river microbial risk control strategy should focus more on the effective management of secondary effluent of wastewater treatment plant and land around rivers.

Water flow buffers shifts in bacterial community structure in heat-stressed Acropora muricata

Deterioration of coral health and associated change in the coral holobiont’s bacterial community are often a result of different environmental stressors acting synergistically. There is evidence that water flow is important for a coral’s resistance to elevated seawater temperature, but there is no information on how water flow affects the coral-associated bacterial community under these conditions. In a laboratory cross-design experiment, Acropora muricata nubbins were subjected to interactive effects of seawater temperature (27 °C to 31 °C) and water flow (0.20 m s⁻¹ and 0.03 m s⁻¹). In an in situ experiment, water flow manipulation was conducted with three colonies of A. muricata during the winter and summer, by partially enclosing each colony in a clear plastic mesh box. 16S rRNA amplicon pyrosequencing showed an increase in the relative abundance of Flavobacteriales and Rhodobacterales in the laboratory experiment, and Vibrio spp. in the in situ experiment when corals were exposed to elevated temperature and slow water flow. In contrast, corals that were exposed to faster water flow under laboratory and in situ conditions had a stable bacterial community. These findings indicate that water flow plays an important role in the maintenance of specific coral-bacteria associations during times of elevated thermal stress.

Insight into the risk of replenishing urban landscape ponds with reclaimed wastewater

Increasing use of reclaimed wastewater (RW) for replenishing urban landscape ponds has aroused public concern about the water quality. Three ponds replenished with RW in three cities in China were chosen to investigate 22 indexes of water quality in five categories. This was achieved by comparing three pairs of ponds in the three different cities, where one pond in each pair was replenished with RW and the other with surface water (SW). The nutrients condition, heavy metal concentration and ecotoxicity did not differ significantly between RW- and SW-replenished ponds. By contrast, significant differences were observed in algal growth and pathogen risk. RW ponds presented a Cyanophyta-Chlorophyta-Bacillariophyta type with high algal diversity while SW ponds presented a Cyanophyta type with low diversity. Regrowth of bacterial pathogens and especially survival of viral pathogens in RW, was the main driver behind the higher risk for RW ponds compared with SW ones. The duration of RW replenishment was proved to have a marked impact on the algal growth and pathogen risk. With continued RW replenishment, non-dominant algal species subjected to decrease while dominant species were enhanced resulting in the biomass increasing but diversity declining, and the risk posed by viral pathogens might become greater.

Human-Driven Microbiological Contamination of Benthic and Hyporheic Sediments of an Intermittent Peri-Urban River Assessed from MST and 16S rRNA Genetic Structure Analyses

Rivers are often challenged by fecal contaminations. The barrier effect of sediments against fecal bacteria was investigated through the use of a microbial source tracking (MST) toolbox, and by Next Generation Sequencing (NGS) of V5-V6 16S rRNA gene (rrs) sequences. Non-metric multi-dimensional scaling analysis of V5-V6 16S rRNA gene sequences differentiated bacteriomes according to their compartment of origin i.e., surface water against benthic and hyporheic sediments. Classification of these reads showed the most prevalent operating taxonomic units (OTU) to be allocated to Flavobacterium and Aquabacterium. Relative numbers of Gaiella, Haliangium, and Thermoleophilum OTU matched the observed differentiation of bacteriomes according to river compartments. OTU patterns were found impacted by combined sewer overflows (CSO) through an observed increase in diversity from the sewer to the hyporheic sediments. These changes appeared driven by direct transfers of bacterial contaminants from wastewaters but also by organic inputs favoring previously undetectable bacterial groups among sediments. These NGS datasets appeared more sensitive at tracking community changes than MST markers. The human-specific MST marker HF183 was strictly detected among CSO-impacted surface waters and not river bed sediments. The ruminant-specific DNA marker was more broadly distributed but intense bovine pollution was required to detect transfers from surface water to benthic and hyporheic sediments. Some OTU showed distribution patterns in line with these MST datasets such as those allocated to the Aeromonas, Acinetobacter, and Pseudomonas. Fecal indicators (Escherichia coli and total thermotolerant coliforms) were detected all over the river course but their concentrations were not correlated with MST ones. Overall, MST and NGS datasets suggested a poor colonization of river sediments by bovine and sewer bacterial contaminants. No environmental outbreak of these bacterial contaminants was detected.

Cumulative effects of fecal contamination from combined sewer overflows: Management for source water protection

The quality of a drinking water source depends largely on upstream contaminant discharges. Sewer overflows can have a large influence on downstream drinking water intakes as they discharge untreated or partially treated wastewaters that may be contaminated with pathogens. This study focuses on the quantification of Escherichia coli discharges from combined sewer overflows (CSOs) and the dispersion and diffusion in receiving waters in order to prioritize actions for source water protection. E. coli concentrations from CSOs were estimated from monitoring data at a series of overflow structures and then applied to the 42 active overflow structures between 2009 and 2012 using a simple relationship based upon the population within the drainage network. From these estimates, a transport-dispersion model was calibrated with data from a monitoring program from both overflow structures and downstream drinking water intakes. The model was validated with 15 extreme events such as a large number of overflows (n > 8) or high concentrations at drinking water intakes. Model results demonstrated the importance of the cumulative effects of CSOs on the degradation of water quality downstream. However, permits are typically issued on a discharge point basis and do not consider cumulative effects. Source water protection plans must consider the cumulative effects of discharges and their concentrations because the simultaneous discharge of multiple overflows can lead to elevated E. coli concentrations at a drinking water intake. In addition, some CSOs have a disproportionate impact on peak concentrations at drinking water intakes. As such, it is recommended that the management of CSOs move away from frequency based permitting at the discharge point to focus on the development of comprehensive strategies to reduce cumulative and peak discharges from CSOs upstream of drinking water intakes.

First report of predation of Giardia sp. cysts by ciliated protozoa and confirmation of predation of Cryptosporidium spp. oocysts by ciliate species

Ciliated protozoa are important components of the microbial food web in various habitats, especially aquatic environments. These organisms are useful bioindicators for both environmental quality assessment and the wastewater purification process. The pathogenic parasitic protozoan species Giardia and Cryptosporidium represent a significant concern for human health, being responsible for numerous disease outbreaks worldwide. The predation of cysts and oocysts in 15 ciliate species from water and sewage samples collected in Campinas, São Paulo, Brazil were verified under laboratory conditions. The ciliated protozoan species were selected based on their mode of nutrition, and only bacterivorous and suspension-feeders were considered for the experiments. The species Blepharisma sinuosum, Euplotes aediculatus, Sterkiella cavicola, Oxytricha granulifera, Vorticella infusionum, Spirostomum minus, and Stentor coeruleus ingested cysts and oocysts, the resistance forms of Giardia spp. and Cryptosporidium spp., respectively. This is the first time that the ingestion of Giardia cysts by ciliated protozoa has been reported. These findings may contribute to a better understanding of the biological removal of these pathogens from aquatic environments.

Tracking Strains in the Microbiome: Insights from Metagenomics and Models

Transmission usually refers to the movement of pathogenic organisms. Yet, commensal microbes that inhabit the human body also move between individuals and environments. Surprisingly little is known about the transmission of these endogenous microbes, despite increasing realizations of their importance for human health. The health impacts arising from the transmission of commensal bacteria range widely, from the prevention of autoimmune disorders to the spread of antibiotic resistance genes. Despite this importance, there are outstanding basic questions: what is the fraction of the microbiome that is transmissible? What are the primary mechanisms of transmission? Which organisms are the most highly transmissible? Higher resolution genomic data is required to accurately link microbial sources (such as environmental reservoirs or other individuals) with sinks (such as a single person's microbiome). New computational advances enable strain-level resolution of organisms from shotgun metagenomic data, allowing the transmission of strains to be followed over time and after discrete exposure events. Here, we highlight the latest techniques that reveal strain-level resolution from raw metagenomic reads and new studies that are tracking strains across people and environments. We also propose how models of pathogenic transmission may be applied to study the movement of commensals between microbial communities.

Removal of Fecal Indicators, Pathogenic Bacteria, Adenovirus, Cryptosporidium and Giardia (oo)cysts in Waste Stabilization Ponds in Northern and Eastern Australia

Maturation ponds are used in rural and regional areas in Australia to remove the microbial loads of sewage wastewater, however, they have not been studied intensively until present. Using a combination of culture-based methods and quantitative real-time PCR, we assessed microbial removal rates in maturation ponds at four waste stabilization ponds (WSP) with (n = 1) and without (n = 3) baffles in rural and remote communities in Australia. Concentrations of total coliforms, E. coli, enterococci, Campylobacter spp., Salmonella spp., F+ RNA coliphage, adenovirus, Cryptosporidium spp. and Giardia (oo) cysts in maturation ponds were measured at the inlet and outlet. Only the baffled pond demonstrated a significant removal of most of the pathogens tested and therefore was subjected to further study by analyzing E. coli and enterococci concentrations at six points along the baffles over five sampling rounds. Using culture-based methods, we found a decrease in the number of E. coli and enterococci from the initial values of 100,000 CFU per 100 mL in the inlet samples to approximately 1000 CFU per 100 mL in the outlet samples for both bacterial groups. Giardia cysts removal was relatively higher than fecal indicators reduction possibly due to sedimentation.