Disappearance and prevalence of extended-spectrum ß-lactamase-producing Escherichia coli and other coliforms in the wastewater treatment process.

Antibiotic-resistant bacteria (ARBs) can now be detected not only in clinical institutions but also in wastewater treatment plants (WWTPs), extending the range of emergence to residential areas. In this study, we investigated the change of antibiotic-resistant Escherichia coli (E. coli) and other coliforms in each treatment process at WWTPs. Throughout the treatment process, the numbers of E. coli and other coliforms were significantly reduced to less than 5.7 ± 0.5 CFU/100 ml and 2.4 ± 0.0×102 CFU/100 ml, respectively. However, ESBL-producing E. coli and other coliforms were detected in each treatment process (even after chlorination) at 5.6% and 4.8%, compared to the total E. coli and other coliforms counts. Then, ESBL-producing-related genes were identified via PCR analyses, and the most predominant gene was CTX-M-9 in both E. coli (47.2%) and other coliforms (47.3%). Although actual WWTPs greatly reduced the number of bacteria, the relative prevalence of ESBL-producing bacteria was increased, suggesting that ESBL-producing bacteria remain in the effluent at minimal concentrations and could be diffusing to water bodies.

Growth and Decay of Fecal Indicator Bacteria and Changes in the Coliform Composition on the Top Surface Sand of Coastal Beaches during the Rainy Season.

High counts of bacteria are present in beach sand, and human health threats attributable to contact with sand have been reported. In this study, we investigated fecal indicator bacteria in the top surface sand of coastal beaches. Monitoring investigations were performed during a monsoon when rainfall occurs randomly, and the composition of the coliforms was analyzed. The coliform count in the top surface sand (depth < 1 cm) increased by approximately 100 fold (26-2.23 × 103 CFU/100 g) with increasing water content because of precipitation. The composition of the coliforms in the top surface sand changed within 24 h of rainfall, with Enterobacter comprising more than 40% of the coliforms. Estimation of factors that changed the bacterial counts and composition revealed that coliform counts tended to increase with increasing water content in the top surface sand. However, the abundance of Enterobacter was independent of the sand surface temperature and water content. Coliform counts in the top surface sand rapidly increased and the composition showed remarkable variations because of the supply of water to the beach following rainfall. Among them, some bacteria with suspected pathogenicity were present. Controlling bacteria in coastal beaches is important for improving public health for beachgoers.

Contrasting adaptive genetic consequences of stream insects under changing climate.

Freshwater biodiversity undergoes degradation due to climate change. Researchers have inferred the effects of climate change on neutral genetic diversity, assuming the fixed spatial distributions of alleles. However, the adaptive genetic evolution of populations that may change the spatial distribution of allele frequencies along environmental gradients (i.e., evolutionary rescue) have largely been overlooked. We developed a modeling approach that projects the comparatively adaptive and neutral genetic diversities of four stream insects, using empirical neutral/ putative adaptive loci, ecological niche models (ENMs), and a distributed hydrological-thermal simulation at a temperate catchment under climate change. The hydrothermal model was used to generate hydraulic and thermal variables (e.g., annual current velocity and water temperature) at the present and the climatic change conditions, projected based on the eight general circulation models and the three representative concentration pathways scenarios for the two future periods (2031-2050, near future; 2081-2100, far future). The hydraulic and thermal variables were used for predictor variables of the ENMs and adaptive genetic modeling based on machine learning approaches. The increases in annual water temperature in the near- (+0.3-0.7 °C) and far-future (+0.4-3.2 °C) were projected. Of the studied species, with different ecologies and habitat ranges, Ephemera japonica (Ephemeroptera) was projected to lose rear-edge habitats (i.e., downstream) but retain the adaptive genetic diversity owing to evolutionary rescue. In contrast, the habitat range of the upstream-dwelling Hydropsyche albicephala (Trichoptera) was found to remarkably decline, resulting in decreases in the watershed genetic diversity. While the other two Trichoptera species expanded their habitat ranges, the genetic structures were homogenized over the watershed and experienced moderate decreases in gamma diversity. The findings emphasize the evolutionary rescue potential, depending on the extent of species-specific local adaptation.

Simultaneous detection of various pathogenic Escherichia coli in water by sequencing multiplex PCR amplicons.

Waterborne diseases due to pathogen contamination in water are a serious problem all over the world. Accurate and simultaneous detection of pathogens in water is important to protect public health. In this study, we developed a method to simultaneously detect various pathogenic Escherichia coli by sequencing the amplicons of multiplex PCR. Our newly designed multiplex PCR amplified five genes for pathogenic E. coli (uidA, stx1, stx2, STh gene, and LT gene). Additional two PCR assays (for aggR and eae) were also designed and included in the amplicon sequencing analysis. The same assays were also used for digital PCR (dPCR). Strong positive correlations were observed between the sequence read count and the dPCR results for most of the genes targeted, suggesting that our multiplex PCR-amplicon sequencing approach could provide quantitative information. The method was also successfully applied to monitor the level of pathogenic E. coli in river water and wastewater samples. The approach shown here could be expanded by targeting genes for other pathogens.

Prediction of Microcystis Occurrences and Analysis Using Machine Learning in High-Dimension, Low-Sample-Size and Imbalanced Water Quality Data.

Machine learning, Deep learning, and water quality data have been used in recent years to predict the outbreak of harmful algae, especially Microcystis, and analyze outbreak causes. However, for various reasons, water quality data are often High-Dimension, Low-Sample- Size (HDLSS), meaning the sample size is lower than the number of dimensions. Moreover, imbalance problems may arise due to bias in the occurrence frequency of Microcystis. These problems make predicting the occurrence of Microcystis and analyzing its causes with machine learning difficult. In this study, a machine learning model that applies Feature Engineering (FE) and Feature Selection (FS) algorithms are used to predict outbreaks of Microcystis and analyze the outbreak factors from imbalanced HDLSS water quality data. The prediction performance was verified with binary classification to determine whether Microcystis would occur in the future by applying three machine learning models to four data patterns. The cause analysis of Microcystis occurrence was performed by visualizing the results of applying FE and FS. For the test data, the predictive performance of FE and FS methods was significantly better than that of the conventional method, with an accuracy of .108 points and an F-value of .691 points higher than the conventional method. A prediction performance increase was observed with a smaller model capacity. Data-driven analysis suggested that total nitrogen, chemical oxygen demand, chlorophyll-a, dissolved oxygen saturation, and water temperature are associated with Microcystis occurrences. The results also indicated that basic statistics of the water quality distribution (especially mean, standard deviation, and skewness) over a year, not the concentrations of water components, are related to the occurrence of Microcystis. These are new findings not found in previous studies and are expected to contribute significantly to future studies of algae. This study provides a method for analyzing water quality data with high-dimensionality and small samples, imbalance problems, or both.

Antibiotic-resistant Escherichia coli isolated from dairy cows and their surrounding environment on a livestock farm practicing prudent antimicrobial use.

On a livestock farm where antimicrobial administration and its history had been managed for prudent use of antimicrobials, we surveyed antibiotic-resistant Escherichia coli strains isolated from cow feces and the surrounding environment (i.e., rat and crow feces, and water samples from a drainage pit and wastewater processing tank) every month for 1 year. Two strains (1.7%) in cow feces were resistant to tetracycline, whereas all other strains were susceptible to all other antimicrobials. Among 136 strains isolated from cows and wild animals, only one ampicillin-resistant strain was identified. The antibiotic resistance rate in the drainage from the barn was 8.3% (10/120), and all strains showed susceptibility for 8 months of the year. Tetracycline resistance was common in all resistant strains isolated from animal feces and water samples; all tetracycline-resistant strains carried tetA. These results strongly support the proper use and management of antibiotics on farms to minimize the outbreak and spread of antibiotic-resistant bacteria.

Enhancement of sunlight irradiation for wastewater disinfection by mixing with seawater.

There is a need for developing a simple and easy-to-maintain disinfection technique for sewage treatment for use in developing countries and disaster-affected areas. We propose a novel disinfection technology that inactivates bacteria in wastewater via sunlight irradiation under high salt concentration by mixing with seawater. The disinfection efficiency of the proposed method was quantitatively evaluated and examined using fecal indicator bacteria. When the salinity in wastewater was adjusted to 30 practical salinity units by mixing with seawater, the constant of inactivation irradiation energy Ks (m2/MJ) was 1.6-2.2-fold greater than that without seawater for total coliforms and Escherichia coli. By contrast, although enterococci were inactivated by sunlight irradiation, an increase in salinity did not enhance disinfection. On setting the irradiation energy of sunlight to 5.5 MJ/m2, >99% of the fecal indicator bacteria were inactivated. Finally, we examined the relationship between the attenuation of irradiance and water depth and accordingly proposed a design of a treatment system wherein wastewater and seawater were adequately mixed and passed via a disinfection tank under the natural flow with sunlight irradiation.

Comparison of Antibiotic Resistance Profile of Escherichia coli between Pristine and Human-Impacted Sites in a River.

Information on the actual existence of antibiotic-resistant bacteria in rivers where sewage, urban wastewater, and livestock wastewater do not load is essential to prevent the spread of antibiotic-resistant bacteria in water environments. This study compared the antibiotic resistance profile of Escherichia coli upstream and downstream of human habitation. The survey was conducted in the summer, winter, and spring seasons. Resistance to one or more antibiotics at upstream and downstream sites was on average 18% and 20%, respectively, and no significant difference was observed between the survey sites. The resistance rates at the upstream site (total of 98 isolated strains) to each antibiotic were cefazolin 17%, tetracycline 12%, and ampicillin 8%, in descending order. Conversely, for the downstream site (total of 89 isolated strains), the rates were ampicillin 16%, cefazolin 16%, and tetracycline 1% in descending order. The resistance rate of tetracycline in the downstream site was significantly lower than that of the upstream site. Furthermore, phylogenetic analysis revealed that many strains showed different resistance profiles even in the same cluster of the Pulsed-Field Gel Electrophoresis (PFGE) pattern. Moreover, the resistance profiles differed in the same cluster of the upstream and the downstream sites. In flowing from the upstream to the downstream site, it is plausible that E. coli transmitted or lacked the antibiotic resistance gene.

Dengue disease dynamics are modulated by the combined influences of precipitation and landscape: A machine learning approach.

BACKGROUND: Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints. OBJECTIVES: To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence. METHODS: Entomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence. RESULTS: The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas. CONCLUSIONS: Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.

Plant debris are hotbeds for pathogenic bacteria on recreational sandy beaches.

On recreational sandy beaches, there are guidelines for the management of bacterial pollution in coastal waters regarding untreated sewage, urban wastewater, and industrial wastewater. However, terrestrial plant debris on coastal beaches can be abundant especially after floods and whilst it has rarely been considered a concern, the bacterial population associated with this type of pollution from the viewpoint of public health has not been adequately assessed. In this study, microbes associated with plant debris drifting onto Kizaki Beach in Japan were monitored for 8 months throughout the rainy season, summer, typhoon season, and winter. Here we show that faecal-indicator bacteria in the plant debris and sand under the debris were significantly higher than the number of faecal bacteria in the sand after a 2015 typhoon. When we focused on specific pathogenic bacteria, Brevundimonas vesicularis and Pseudomonas alcaligenes were commonly detected only in the plant debris and sand under the debris during the survey period. The prompt removal of plant debris would therefore help create safer beaches.

The level of antimicrobial resistance of sewage isolates is higher than that of river isolates in different Escherichia coli lineages.

The dissemination of antimicrobial-resistant bacteria in environmental water is an emerging concern in medical and industrial settings. Here, we analysed the antimicrobial resistance of Escherichia coli isolates from river water and sewage by the use of a combined experimental phenotypic and whole-genome-based genetic approach. Among the 283 tested strains, 52 were phenotypically resistant to one or more antimicrobial agents. The E. coli isolates from the river and sewage samples were phylogenetically indistinguishable, and the antimicrobial-resistant strains were dispersedly distributed in a whole-genome-based phylogenetic tree. The prevalence of antimicrobial-resistant strains as well as the number of antimicrobials to which they were resistant were higher in sewage samples than in river samples. Antimicrobial resistance genes were more frequently detected in strains from sewage samples than in those from river samples. We also found that 16 river isolates that were classified as Escherichia cryptic clade V were susceptible to all the antimicrobials tested and were negative for antimicrobial resistance genes. Our results suggest that E. coli strains may acquire antimicrobial resistance genes more frequently and/or antimicrobial-resistant E. coli strains may have higher rates of accumulation and positive selection in sewage than in rivers, irrespective of their phylogenetic distribution.

Gradients of flow regulation shape community structures of stream fishes and insects within a catchment subject to typhoon events.

Alterations in natural flow regimes caused by dams can significantly alter the aquatic habitats of stream organisms. However, few studies have characterized flow regulation to assess its impacts on stream fauna in the context of interannually variable extreme floods. This study aims to understand the variation in stream animals along flow regulation gradients due to hydropower dams in a catchment experiencing typhoons. We observed freshwater fishes and stream insects at fully regulated sites (receiving residual flow), moderately regulated sites (receiving hydropower outflow), and nonregulated site (tributary) in the Mimi River catchment in southern Japan, in summer and winter from 2010 to 2018. We computed indicators of hydrologic alteration (IHA) in each calendar/water (July to June) year from 2007 to 2017 and selected subsets of IHA based on principal component analysis (PCA) and variance inflation factor. The largest variance was mainly explained by minimum discharge levels (e.g., 30-day annual minimum) and flow variability among IHAs, distinguishing the moderately regulated and nonregulated sites from fully regulated sites because of residual flow and suppressed high pulses in the fully regulated sites. Generalized additive models revealed that annual maxima of specific discharge were most significant predictors of fish and insect metrics while its effects were generally inconsistent between summer and winter. Non-metric multidimensional scaling revealed that insect communities were clustered into the regulation extents in both seasons. The differences in winter fauna between the regulated and nonregulated sites, characterized by Ephemeroptera-Plecoptera-Trichoptera abundance, were associated with maximum discharge and high pulse numbers. Fish community variation did not correspond to flow regime gradients. Our findings on mechanistic ecohydrological consequences of various flow regulations, supported by long-term observations, will be useful for river managers attempting to compensate for alterations in flow regime and ecological integrity.

Are bacteria potential sources of fish environmental DNA?

The environmental DNA (eDNA) method is being increasingly applied in various environments. Although eDNA undergoes rapid degradation in aqueous environments, it has been detected in streams up to 10 km downstream from its source. As environmental bacteria can uptake free DNA, transfer their genetic traits, and amplify, there is a potential risk that they, rather than a target aquatic species, could become a source of measured eDNA. This study examined whether bacteria with incorporated fish DNA could be such a source by investigating the detectability of fish DNA generated by bacteria inhabiting river water and riverbed sediment. We attempted to detect common carp (Cyprinus carpio) eDNA in stream water and sediment samples and the DNA of common carp produced by bacterial colonies (Escherichia coli, total coliform, and heterotrophic bacteria) cultured from the samples. The eDNA was detected in the environmental samples but the carp DNA from the targeted bacteria was rarely detected in both water and riverbed sediment samples. Our results suggest that the risk of bacterium-induced false positive detection for fish eDNA is negligible.

Fast, sensitive, and reliable detection of waterborne pathogens by digital PCR after coagulation and foam concentration.

The quantification of pathogens is important for assessing water safety and preventing disease outbreaks. Culture-independent approaches, such as quantitative PCR (qPCR) and digital PCR (dPCR), are useful techniques for quantifying pathogens in water samples. However, since pathogens are usually present at low concentrations in water, it is necessary to concentrate microbial cells before extracting their DNA. Many existing microbial concentration methods are inefficient or take a long time to perform. In this study, we applied a coagulation and foam separation method to concentrate environmental water samples of between 1000 and 5000 mL to 100 µL of DNA (i.e., a 1-5 × 104-fold concentration). The concentration process took <1 h. The DNA samples were then used to quantify various target pathogens using dPCR. One gene, the Shiga toxin gene (stx2) of Shiga toxin-producing Escherichia coli, was detected at 32 copies/100 mL in a river water sample. The coagulation and foam concentration method followed by dPCR reported herein is a fast, sensitive, and reliable method to quantify pathogen genes in environmental water samples.

Growth and antibiotic resistance acquisition of Escherichia coli in a river that receives treated sewage effluent.

Wastewater treatment plants could discharge Escherichia coli and antibiotic resistant bacteria to the environment adjacent to, or downstream of their discharge point. However, their discharge also contains nutrients which could promote growth of E. coli in water environments. This study was done to clarify the potential of growth and antibiotic resistance acquisition of E. coli in a river environment. Levels of E. coli were monitored in a river that receives treated sewage effluent for over four years. River water, periphyton and sediment samples were collected at sites upstream and downstream of treated sewage inflow. Concentrations of E. coli increased in river water and periphyton at the sites downstream of the treated sewage inflow, although levels of E. coli were very low or below detection limit in the treated sewage samples. Concentrations of Chlorophyll a increased at the downstream sites, likely due to nutrient input from the treated sewage. Based on pulsed field gel electrophoresis, identical genotype occurred at multiple sites both upstream and downstream of the treated sewage inflow. However, strains resistant to antibiotics such as ampicillin, cefazolin, ciprofloxacin, and chloramphenicol were more frequently obtained from the downstream sites than the upstream sites. Multidrug resistant E. coli strains were detected in periphyton and sediment samples collected at the downstream sites. Non-resistant strains with PDGE genotype identical to the multi-drug strains were also detected, indicating that E. coli might have become resistant to antibiotics by acquiring resistance genes via horizontal gene transfer. Laboratory incubation experiment showed the growth of E. coli in periphyton or sediment-fed river water samples. These results suggest that the wastewater treatment inflow did not directly provide E. coli to the river water, but could promote the growth of periphyton, which could lead to the elevated levels of E. coli and the emergence of antibiotic resistant E. coli.

Simulating the Advection and Degradation of the Environmental DNA of Common Carp along a River.

The environmental DNA (eDNA) method is a novel technique for precise and efficient biological surveillance. Although eDNA has been widely used to monitor various freshwater organisms, eDNA dynamics in streams remain poorly understood. In this study, we investigated the eDNA dynamics of common carp ( Cyprinus carpio) in a forested headwater stream affected by the effluent from a carp farm. We evaluated the longitudinal variation in carp eDNA along a river downstream from the farm and performed a temporal eDNA decay experiment using digital polymerase chain reaction. On the basis of the resulting decay constants, we built a model to simulate the advection and degradation of eDNA along the studied river. The observed eDNA flux (concentration multiplied by flow rate) decreased exponentially with distance downstream from the farm, and eDNA was detected 3 km downstream of the farm. Although the water temperatures were similar, the eDNA decay constant was lower in autumn than in summer. The simulated eDNA concentration was markedly larger (>10 times) than the observed concentration, suggesting that eDNA removal is accelerated in the stream environment compared to in conventional experimental settings.

Projection of invertebrate populations in the headwater streams of a temperate catchment under a changing climate.

Climate change places considerable stress on riverine ecosystems by altering flow regimes and increasing water temperature. This study evaluated how water temperature increases under climate change scenarios will affect stream invertebrates in pristine headwater streams. The studied headwater-stream sites were distributed within a temperate catchment of Japan and had similar hydraulic-geographical conditions, but were subject to varying temperature conditions due to altitudinal differences (100 to 850 m). We adopted eight general circulation models (GCMs) to project air temperature under conservative (RCP2.6), intermediate (RCP4.5), and extreme climate scenarios (RCP8.5) during the near (2031-2050) and far (2081-2100) future. Using the water temperature of headwater streams computed by a distributed hydrological-thermal model as a predictor variable, we projected the population density of stream invertebrates in the future scenarios based on generalized linear models. The mean decrease in the temporally averaged population density of Plecoptera was 61.3% among the GCMs, even under RCP2.6 in the near future, whereas density deteriorated even further (90.7%) under RCP8.5 in the far future. Trichoptera density was also projected to greatly deteriorate under RCP8.5 in the far future. We defined taxa that exhibited temperature-sensitive declines under climate change as cold stenotherms and found that most Plecoptera taxa were cold stenotherms in comparison to other orders. Specifically, the taxonomic families that only distribute in Palearctic realm (e.g., Megarcys ochracea and Scopura longa) were selectively assigned, suggesting that Plecoptera family with its restricted distribution in the Palearctic might be a sensitive indicator of climate change. Plecoptera and Trichoptera populations in the headwaters are expected/anticipated to decrease over the considerable geographical range of the catchment, even under the RCP2.6 in the near future. Given headwater invertebrates play important roles in streams, such as contributing to watershed productivity, our results provide useful information for managing streams at the catchment-level.

Effects of bacterial pollution caused by a strong typhoon event and the restoration of a recreational beach: Transitions of fecal bacterial counts and bacterial flora in beach sand.

To determine the effects of bacteria pollution associated with a strong typhoon event and to assess the restoration of the normal bacterial flora, we used conventional filtration methods and nextgeneration sequencing of 16S rRNA genes to analyze the transition of fecal and total bacterial counts in water and core sand samples collected from a recreational beach. Immediately after the typhoon event, Escherichia coli counts increased to 82 CFU/100 g in the surface beach sand. E. coli was detected through the surface to sand 85-cm deep at the land side point (10-m land side from the high-water line). However, E. coli disappeared within a month from the land side point. The composition of the bacterial flora in the beach sand at the land point was directly influenced by the typhoon event. Pseudomonas was the most prevalent genus throughout the sand layers (0-102-cm deep) during the typhoon event. After 3 months, the population of Pseudomonas significantly decreased, and the predominant genus in the surface layer was Kaistobacter, although Pseudomonas was the major genus in the 17- to 85-cm layer. When the beach conditions stabilized, the number of pollutant Pseudomonas among the 10 most abundant genera decreased to lower than the limit of detection. The bacterial population of the sand was subsequently restored to the most populous pre-event orders at the land point. A land-side beach, where users directly contact the sand, was significantly affected by bacterial pollution caused by a strong typhoon event. We show here that the normal bacterial flora of the surface sand was restored within 1 month.

Bacterial flora analysis of coliforms in sewage, river water, and ground water using MALDI-TOF mass spectrometry.

The aim of this study was to rapidly and effectively analyze coliforms, which are the most fundamental indicators of water quality for fecal pollution, using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Coliform bacteria were isolated from municipal sewage, river water, and groundwater. For each sample, 100 isolates were determined by MALDI-TOF MS. In addition, these same 100 isolates were also identified via 16S rRNA gene sequence analysis. Obtained MALDI-TOF MS data were compared with the 16S rRNA sequencing analysis, and the validity of MALDI-TOF MS for classification of coliform bacteria was examined. The concordance rate of bacterial identification for the 100 isolates obtained by MALDI-TOF MS analysis and 16S rRNA gene sequence analysis for sewage, river water, and ground water were 96%, 74%, and 62% at the genus level, respectively. Among the sewage, river water, and ground water samples, the coliform bacterial flora were distinct. The dominant genus of coliforms in sewage, river water, and groundwater were Klebsiella spp., Enterobacter spp., and Serratia spp., respectively. We determined that MALDI-TOF MS is a rapid and accurate tool that can be used to identify coliforms. Therefore, without using conventional 16S rRNA sequencing, it is possible to rapidly and effectively classify coliforms in water using MALDI-TOF MS.