Cyanobacterial Harmful Algal Mats (CyanoHAMs) in tropical rivers of central Mexico and their potential risks through toxin production.

Cyanobacteria inhabiting lotic environments have been poorly studied and characterized in Mexico, despite their potential risks from cyanotoxin production. This article aims to fill this knowledge gap by assessing the importance of benthic cyanobacteria as potential cyanotoxin producers in central Mexican rivers through: (i) the taxonomic identification of cyanobacteria found in these rivers, (ii) the environmental characterization of their habitats, and (iii) testing for the presence of toxin producing genes in the encountered taxa. Additionally, we introduce and discuss the use of the term "CyanoHAMs" for lotic water environments. Populations of cyanobacteria were collected from ten mountain rivers and identified using molecular techniques. Subsequently, these taxa were evaluated for genes producing anatoxins and microcystins via PCR. Through RDA analyses, the collected cyanobacteria were grouped into one of three categories based on their environmental preferences for the following: (1) waters with high ionic concentrations, (2) cold-temperate waters, or (3) waters with high nutrient enrichment. Populations from six locations were identified to genus level: Ancylothrix sp., Cyanoplacoma sp., and Oxynema sp. The latter was found to contain the gene that produces anatoxins and microcystins in siliceous rivers, while Oxynema tested positive for the gene that produces microcystins in calcareous rivers. Our results suggest that eutrophic environments are not necessarily required for toxin-producing cyanobacteria. Our records of Compactonostoc, Oxynema, and Ancylothrix represent the first for Mexico. Four taxa were identified to species level: Wilmottia aff. murrayi, Nostoc tlalocii, Nostoc montejanii, and Dichothrix aff. willei, with only the first testing positive using PCR for anatoxin and microcystin-producing genes in siliceous rivers. Due to the differences between benthic growths with respect to planktonic ones, we propose the adoption of the term Cyanobacterial Harmful Algal Mats (CyanoHAMs) as a more precise descriptor for future studies.

Prediction of microbial activity and abundance using interpretable machine learning models in the hyporheic zone of effluent-dominated receiving rivers.

Serving as a vital linkage between surface water and groundwater, the hyporheic zone (HZ) plays a fundamental role in improving water quality and maintaining ecological security. In arid or semi-arid areas, effluent discharge from wastewater treatment facilities could occupy a predominant proportion of the total base flow of receiving rivers. Nonetheless the relationship between microbial activity, abundance and environmental factors in the HZ of effluent-receiving rivers appear to be rarely addressed. In this study, a spatiotemporal field study was performed in two representative effluent-dominated receiving rivers in Xi'an, China. Land use data, physical and chemical water quality parameters of surface and subsurface water were used as predictive variables, while the microbial respiratory electron transport system activity (ETSA), the Chao1 and Shannon index of total microbial community, as well as the Chao1 and Shannon index of denitrifying bacteria community were used as response variables, while ETSA was used as response variables indicating ecological processes and Shannon and Chao1 were utilized as parameters indicating microbial diversity. Two machine learning models were utilized to provide evidence-based information on how environmental factors interact and drive microbial activity and abundance in the HZ at variable depths. The models with Chao1 and Shannon as response variables exhibited excellent predictive performances (R2: 0.754-0.81 and 0.783-0.839). Dissolved organic nitrogen (DON) was the most important factor affecting the microbial functions, and an obvious threshold value of ∼2 mg/L was observed. Credible predictions of models with Chao1 and Shannon index of denitrifying bacteria community as response variables were detected (R2: 0.484-0.624 and 0.567-0.638), with soluble reactive phosphorus (SRP) being the key influencing factor. Fe (Ⅱ) was favorable in predicting denitrifying bacteria community. The ESTA model highlighted the importance of total nitrogen in the ecological health monitoring in HZ. These findings provide novel insights in predicting microbial activity and abundance in highly-impacted areas such as the HZ of effluent-dominated receiving rivers.

Emerging threat: Antimicrobial resistance proliferation during epidemics - A case study of the SARS-CoV-2 pandemic in South Brazil.

The escalating global concern of antimicrobial resistance poses a significant challenge to public health. This study delved into the occurrence of resistant bacteria and antimicrobial resistance genes in the waters and sediments of urban rivers and correlated this emergence and the heightened use of antimicrobials during the COVID-19 pandemic. Isolating 45 antimicrobial-resistant bacteria across 11 different species, the study identifies prevalent resistance patterns, with ceftriaxone resistance observed in 18 isolates and ciprofloxacin resistance observed in 13 isolates. The detection of extended-spectrum ß-lactamases, carbapenemases, and acquired quinolone resistance genes in all samples underscores the gravity of the situation. Comparison with a pre-pandemic study conducted in the same rivers in 2019 reveals the emergence of previously undetected new resistant species, and the noteworthy presence of new resistant species and alterations in resistance profiles among existing species. Notably, antimicrobial concentrations in rivers increased during the pandemic, contributing significantly to the scenario of antimicrobial resistance observed in these rivers. We underscore the substantial impact of heightened antimicrobial usage during epidemics, such as COVID-19, on resistance in urban rivers. It provides valuable insights into the complex dynamics of antimicrobial resistance in environmental settings and calls for comprehensive approaches to combat this pressing global health issue, safeguarding both public and environmental health.

Agricultural and urban practices are correlated to changes in the resistome of riverine systems.

The objective of this study was to comprehensively characterise the resistome, the collective set of antimicrobial resistance genes in a given environment, of two rivers, from their source to discharge into the sea, as these flow through areas of different land use. Our findings reveal significant differences in the riverine resistome composition in areas of different land uses, with increased abundance and diversity of AMR in downstream agricultural and urban locations, with the resistome in urban areas more similar to the resistome in wastewater. The changes in resistome were accompanied by changes in microbial communities, with a reduction in microbial diversity in downstream agricultural and urban affected areas, driven mostly by increased relative abundance in the phyla, Bacteroidetes and Proteobacteria. These results provide insight into how pollution associated with agricultural and urban activities affects microbial communities and influences AMR in aquatic water bodies. These results add valuable insights to form effective strategies for mitigating and preserving aquatic ecosystems. Overall, our study highlights the critical role of the environment in the development and dissemination of AMR and underscores the importance of adopting a One Health approach to address this global public health threat.

Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferation.

Tackling the impact of missing data in water management is crucial to ensure the reliability of scientific research that informs decision-making processes in public health. The goal of this study is to ascertain the root causes associated with cyanobacteria proliferation under major missing data scenarios. For this purpose, a dynamic missing data management methodology is proposed using Bayesian Machine Learning for accurate surface water quality prediction of a river from Limia basin (Spain). The methodology used entails a sequence of analytical steps, starting with data pre-processing, followed by the selection of a reliable dynamic Bayesian missing value prediction system, leading finally to a supervised analysis of the behavioral patterns exhibited by cyanobacteria. For that, a total of 2,118,844 data points were used, with 205,316 (9.69 %) missing values identified. The machine learning testing showed the iterative structural expectation maximization (SEM) as the best performing algorithm, above the dynamic imputation (DI) and entropy-based dynamic imputation methods (EBDI), enhancing in some cases the accuracy of imputations by approximately 50 % in R2, RMSE, NRMSE, and logarithmic loss values. These findings can impact how data on water quality is being processed and studied, thus, opening the door for more reliable water management strategies that better inform public health decisions.

A comparative study on antibiotic resistant Escherichia coli isolates from Austrian patients and wastewater-influenced Danube River water and biofilms.

Antimicrobial resistance (AMR) poses a major threat to human health worldwide. AMR can be introduced into natural aquatic ecosystems, for example, from clinical facilities via wastewater emissions. Understanding AMR patterns in environmental populations of bacterial pathogens is important to elucidate propagation routes and develop mitigation strategies. In this study, AMR patterns of Escherichia coli isolates from urinary tract infections and colonised urinary catheters of inpatients and outpatients were compared to isolates from the Danube River within the same catchment in Austria to potentially link environmental with clinical resistance patterns. Susceptibility to 20 antibiotics was tested for 697 patient, 489 water and 440 biofilm isolates. The resistance ratios in patient isolates were significantly higher than in the environmental isolates and higher resistance ratios were found in biofilm in comparison to water isolates. The role of the biofilm as potential sink of resistances was reflected by two extended-spectrum beta-lactamase (ESBL) producing isolates in the biofilm while none were found in water, and by higher amoxicillin/clavulanic acid resistance ratios in biofilm compared to patient isolates. Although, resistances to last-line antibiotics such as carbapenems and tigecycline were found in the patient and in the environmental isolates, they still occurred at low frequency.

River water pollution in Lebanon: the country's most underestimated public health challenge.

Background: Due to the several interconnected crises that Lebanon has been facing for the past 4 years, many important social and environmental issues have been overlooked until more "pressing" ones are dealt with. Consequently, water pollution in Lebanon continues to worsen. Aim: This study aimed to describe the microbiological and chemical properties of the 10 main rivers in Lebanon and to assess their suitability for irrigation, while exploring some of the solutions to the problem. Methods: This cross-sectional study evaluated the pollution level of water from 10 rivers in Lebanon in June 2023 and their suitability for irrigation. Samples were collected at 3°C and their quality parameters were measured. Statistical analysis was conducted using R statistical software version 4.0.2. Results: Compared to the Food and Agriculture Organization (FAO) guidelines for safe irrigation water use, 4 out of the 10 samples had pH levels exceeding the permissible threshold, resulting in severe limitations on their usability. Three rivers had nitrate concentrations that exceeded the approved range, thus constraining their severe usage. Among the rivers, 60% had Escherichia coli levels higher than the permissible spectrum and 40% had faecal coliform counts exceeding FAO's upper limit recommendation. All water sources, however, had total dissolved solid levels that were within the recommended range. Conclusions: Polluted water can have a negative impact on human, wildlife and ecosystem health. Most of the assessed rivers in our study contained bacterial colonies, above the maximum recommended internationally. There is therefore an urgent need to address pollution issues in Lebanese waters to make them suitable for irrigation and other uses.

New sensitive tools to characterize meta-metabolome response to short- and long-term cobalt exposure in dynamic river biofilm communities.

Untargeted metabolomics is a non-a priori analysis of biomolecules that characterizes the metabolome variations induced by short- and long-term exposures to stressors. Even if the metabolite annotation remains lacunar due to database gaps, the global metabolomic fingerprint allows for trend analyses of dose-response curves for hundreds of cellular metabolites. Analysis of dose/time-response curve trends (biphasic or monotonic) of untargeted metabolomic features would thus allow the use of all the chemical signals obtained in order to determine stress levels (defense or damage) in organisms. To develop this approach in a context of time-dependent microbial community changes, mature river biofilms were exposed for 1 month to four cobalt (Co) concentrations (from background concentration to 1 × 10-6 M) in an open system of artificial streams. The meta-metabolomic response of biofilms was compared against a multitude of biological parameters (including bioaccumulation, biomass, chlorophyll a content, composition and structure of prokaryotic and eukaryotic communities) monitored at set exposure times (from 1 h to 28 d). Cobalt exposure induced extremely rapid responses of the meta-metabolome, with time range inducing defense responses (TRIDeR) of around 10 s, and time range inducing damage responses (TRIDaR) of several hours. Even in biofilms whose structure had been altered by Co bioaccumulation (reduced biomass, chlorophyll a contents and changes in the composition and diversity of prokaryotic and eukaryotic communities), concentration range inducing defense responses (CRIDeR) with similar initiation thresholds (1.41 ± 0.77 × 10-10 M Co2+ added in the exposure medium) were set up at the meta-metabolome level at every time point. In contrast, the concentration range inducing damage responses (CRIDaR) initiation thresholds increased by 10 times in long-term Co exposed biofilms. The present study demonstrates that defense and damage responses of biofilm meta-metabolome exposed to Co are rapidly and sustainably impacted, even within tolerant and resistant microbial communities.

Meta-metabolomic responses of river biofilms to cobalt exposure and use of dose-response model trends as an indicator of effects.

The response of the meta-metabolome is rarely used to characterize the effects of contaminants on a whole community. Here, the meta-metabolomic fingerprints of biofilms were examined after 1, 3 and 7 days of exposure to five concentrations of cobalt (from background concentration to 1 × 10-5 M) in aquatic microcosms. The untargeted metabolomic data were processed using the DRomics tool to build dose-response models and to calculate benchmark-doses. This approach made it possible to use 100% of the chemical signal instead of being limited to the very few annotated metabolites (7%). These benchmark-doses were further aggregated into an empirical cumulative density function. A trend analysis of the untargeted meta-metabolomic feature dose-response curves after 7 days of exposure suggested the presence of a concentration range inducing defense responses between 1.7 × 10-9 and 2.7 × 10-6 M, and of a concentration range inducing damage responses from 2.7 × 10-6 M and above. This distinction was in good agreement with changes in the other biological parameters studied (biomass and chlorophyll content). This study demonstrated that the molecular defense and damage responses can be related to contaminant concentrations and represents a promising approach for environmental risk assessment of metals.

[Distribution of Typical Resistant Bacteria and Resistance Genes in Source Water of the Middle and Lower Reaches of the Yellow River].

The Yellow River water of an urban area located in the middle and lower reaches of the Yellow River was taken as the research object， in which the seasonal and along-range distribution of total culturable bacteria， typical antibiotic resistant bacteria （amoxicillin resistant bacteria and sulfamethoxazole-resistant bacteria）， and their corresponding typical resistance genes ï¼»ß-lactam resistance gene （blaCTX-M） and sulfamamide resistance genes （sulI and sulⅡ）， as well as intⅠ1 were investigated. The results showed that the total culturable bacteria， ß-lactam-resistant bacteria and sulfonamide-resistant bacteria in the Yellow River Basin were significantly affected by temperature and human activities. The composition and quantity of their genera had obvious spatiotemporal distribution characteristics， in which Bacillus and Pseudomonas were dominant in the composition and number of bacteria. The abundance of resistance genes decreased with the decrease in temperature. The proportion of ß-lactam resistance genes in the total genes was higher than that of sulfanilamide genes， and sulI was the dominant gene in sulfanilamide genes. Correlation analysis showed that class Ⅰ integron played an important role in accelerating the spread of resistance genes. This study offers insight into the status quo of water resistance pollution in the Yellow River and provides theoretical support for the risk assessment of resistance genes in the middle and lower reaches of the Yellow River Basin.

Contrary effects of increasing temperatures on the spread of antimicrobial resistance in river biofilms.

River microbial communities regularly act as the first barrier of defense against the spread of antimicrobial resistance genes (ARGs) that enter environmental microbiomes through wastewater. However, how the invasion dynamics of wastewater-borne ARGs into river biofilm communities will shift due to climate change with increasing average and peak temperatures remains unknown. Here, we aimed to elucidate the effects of increasing temperatures on the naturally occurring river biofilm resistome, as well as the invasion success of foreign ARGs entering through wastewater. Natural biofilms were grown in a low-anthropogenic impact river and transferred to artificial laboratory recirculation flume systems operated at three different temperatures (20°C, 25°C, and 30°C). After 1 week of temperature acclimatization, significant increases in the abundance of the naturally occurring ARGs in biofilms were detected at higher temperatures. After this acclimatization period, biofilms were exposed to a single pulse of wastewater, and the invasion dynamics of wastewater-borne ARGs were analyzed over 2 weeks. After 1 day, wastewater-borne ARGs were able to invade the biofilms successfully with no observable effect of temperature on their relative abundance. However, thereafter, ARGs were lost at a far increased rate at 30°C, with ARG levels dropping to the initial natural levels after 14 days. Contrary to the lower temperatures, ARGs were either lost at slower rates or even able to establish themselves in biofilms with stable relative abundances above natural levels. Hence, higher temperatures come with contrary effects on river biofilm resistomes: naturally occurring ARGs increase in abundance, while foreign, invading ARGs are lost at elevated speeds.IMPORTANCEInfections with bacteria that gained resistance to antibiotics are taking millions of lives annually, with the death toll predicted to increase. River microbial communities act as a first defense barrier against the spread of antimicrobial resistance genes (ARGs) that enter the environment through wastewater after enrichment in human and animal microbiomes. The global increase in temperature due to climate change might disrupt this barrier effect by altering microbial community structure and functions. We consequently explored how increasing temperatures alter ARG spread in river microbial communities. At higher temperatures, naturally occurring ARGs increased in relative abundance. However, this coincided with a decreased success rate of invading foreign ARGs from wastewater to establish themselves in the communities. Therefore, to predict the effects of climate change on ARG spread in river microbiomes, it is imperative to consider if the river ecosystem and its resistome are dominated by naturally occurring or invading foreign ARGs.

A new Bayesian approach for managing bathing water quality at river bathing locations vulnerable to short-term pollution.

Short-term fecal pollution events are a major challenge for managing microbial safety at recreational waters. Long turn-over times of current laboratory methods for analyzing fecal indicator bacteria (FIB) delay water quality assessments. Data-driven models have been shown to be valuable approaches to enable fast water quality assessments. However, a major barrier towards the wider use of such models is the prevalent data scarcity at existing bathing waters, which questions the representativeness and thus usefulness of such datasets for model training. The present study explores the ability of five data-driven modelling approaches to predict short-term fecal pollution episodes at recreational bathing locations under data scarce situations and imbalanced datasets. The study explicitly focuses on the potential benefits of adopting an innovative modeling and risk-based assessment approach, based on state/cluster-based Bayesian updating of FIB distributions in relation to different hydrological states. The models are benchmarked against commonly applied supervised learning approaches, particularly linear regression, and random forests, as well as to a zero-model which closely resembles the current way of classifying bathing water quality in the European Union. For model-based clustering we apply a non-parametric Bayesian approach based on a Dirichlet Process Mixture Model. The study tests and demonstrates the proposed approaches at three river bathing locations in Germany, known to be influenced by short-term pollution events. At each river two modelling experiments ("longest dry period", "sequential model training") are performed to explore how the different modelling approaches react and adapt to scarce and uninformative training data, i.e., datasets that do not include event pollution information in terms of elevated FIB concentrations. We demonstrate that it is especially the proposed Bayesian approaches that are able to raise correct warnings in such situations (> 90 % true positive rate). The zero-model and random forest are shown to be unable to predict contamination episodes if pollution episodes are not present in the training data. Our research shows that the investigated Bayesian approaches reduce the risk of missed pollution events, thereby improving bathing water safety management. Additionally, the approaches provide a transparent solution for setting minimum data quality requirements under various conditions. The proposed approaches open the way for developing data-driven models for bathing water quality prediction against the reality that data scarcity is common problem at existing and prospective bathing waters.

Environmental Factors Impacting the Development of Toxic Cyanobacterial Proliferations in a Central Texas Reservoir.

Cyanobacterial harmful algal proliferations (cyanoHAPs) are increasingly associated with dog and livestock deaths when benthic mats break free of their substrate and float to the surface. Fatalities have been linked to neurotoxicosis from anatoxins, potent alkaloids produced by certain genera of filamentous cyanobacteria. After numerous reports of dog illnesses and deaths at a popular recreation site on Lady Bird Lake, Austin, Texas in late summer 2019, water and floating mat samples were collected from several sites along the reservoir. Water quality parameters were measured and mat samples were maintained for algal isolation and DNA identification. Samples were also analyzed for cyanobacterial toxins using LC-MS. Dihydroanatoxin-a was detected in mat materials from two of the four sites (0.6-133 ng/g wet weight) while water samples remained toxin-free over the course of the sampling period; no other cyanobacterial toxins were detected. DNA sequencing analysis of cyanobacterial isolates yielded a total of 11 genera, including Geitlerinema, Tyconema, Pseudanabaena, and Phormidium/Microcoleus, taxa known to produce anatoxins, including dihydroanatoxin, among other cyanotoxins. Analyses indicate that low daily upriver dam discharge, higher TP and NO3 concentrations, and day of the year were the main parameters associated with the presence of toxic floating cyanobacterial mats.

Metagenomics analysis of water samples collected from the Yamuna River of Agra city, India.

Yamuna River water in Agra city of India is contaminated with toxic pollutants, including heavy metals that cause damage to the environment and human health. At present, the direct use of river water for drinking purposes and household activities lead to the direct exposure of society to the contaminants. In this study, Yamuna River water samples were collected from three different sites in Agra city during the monsoon, summer, and winter seasons. The physico-chemical parameters were estimated along with heavy metals. In physico-chemical parameter, the values found were mostly above the permissible limits. The results water samples contain high levels of cadmium, chromium, lead, and nickel above the desirable levels in most cases. The metagenomic analysis revealed that Proteobacteria, Bacteroidetes, Verrucomicrobia, Actinobacteria, and Planctobacteria were the most abundant phyla with a relative abundance of 61%, 9.34%, 5.23%, 4.64%, and 4.3%, respectively. The Comamonadaceae, the most abundant family consists of the genera involved in hydrogen oxidation, iron reduction, degraders of polycyclic aromatic hydrocarbons, and fermentation. The presence of Pseudomonas, Nitrosomonas sp., Thauera humireducens and Dechloromonas denitrificans (decomposition of sewage and organic matter) and Pseudomonas aeruginosa indicates the presence of heavy metal degrading bacteria in water sample. Functional prediction showed the presence of genes responsible for different metabolic pathways that could help developing new bioremediation strategies. The study concludes the status of water contamination, the presence of complex microbial community and suggests the futuristic use and their role in bioremediation.

Drivers of cyanotoxin and taste-and-odor compound presence within the benthic algae of human-disturbed rivers.

Freshwater benthic algae form complex mat matrices that can confer ecosystem benefits but also produce harmful cyanotoxins and nuisance taste-and-odor (T&O) compounds. Despite intensive study of the response of pelagic systems to anthropogenic change, the environmental factors controlling toxin presence in benthic mats remain uncertain. Here, we present a unique dataset from a rapidly urbanizing community (Kansas City, USA) that spans environmental, toxicological, taxonomic, and genomic indicators to identify the prevalence of three cyanotoxins (microcystin, anatoxin-a, and saxitoxin) and two T&O compounds (geosmin and 2-methylisoborneol). Thereafter, we construct a random forest model informed by game theory to assess underlying drivers. Microcystin (11.9 ± 11.6 µg/m2), a liver toxin linked to animal fatalities, and geosmin (0.67 ± 0.67 µg/m2), a costly-to-treat malodorous compound, were the most abundant compounds and were present in 100 % of samples, irrespective of land use or environmental conditions. Anatoxin-a (8.1 ± 11.6 µg/m2) and saxitoxin (0.18 ± 0.39 µg/m2), while not always detected, showed a systematic tradeoff in their relative importance with season, an observation not previously reported in the literature. Our model indicates that microcystin concentrations were greatest where microcystin-producing genes were present, whereas geosmin concentrations were high in the absence of geosmin-producing genes. Together, these results suggest that benthic mats produce microcystin in situ but that geosmin production may occur ex situ with its presence in mats attributable to adsorption by organic matter. Our study broadens the awareness of benthic cyanobacteria as a source of harmful and nuisance metabolites and highlights the importance of benthic monitoring for sustaining water quality standards in rivers.

Distinct Assembly Processes Structure Planktonic Bacterial Communities Among Near- and Offshore Ecosystems in the Yangtze River Estuary.

The estuarine system functions as natural filters due to its ability to facilitate material transformation, planktonic bacteria play a crucial role in the cycling of complex nutrients and pollutants within estuaries, and understanding the community composition and assembly therein is crucial for comprehending bacterial ecology within estuaries. Despite extensive investigations into the composition and community assembly of two bacterial fractions (free-living, FLB; particle-attached, PAB), the process by which bacterioplankton communities in these two habitats assemble in the nearshore and offshore zones of estuarine ecosystems remains poorly understood. In this study, we conducted sampling in the Yangtze River Estuary (YRE) to investigate potential variations in the composition and community assembly of FLB and PAB in nearshore and offshore regions. We collected 90 samples of surface, middle, and bottom water from 16 sampling stations and performed 16S rRNA gene amplicon analysis along with environmental factor measurements. The results unveiled that the nearshore communities demonstrated significantly greater species richness and Chao1 indices compared to the offshore communities. In contrast, the nearshore communities had lower values of Shannon and Simpson indices. When compared to the FLB, the PAB exhibit a higher level of biodiversity and abundance. However, no distinct alpha and beta diversity differences were observed between the bottom, middle, and surface water layers. The community assembly analysis indicated that nearshore communities are predominantly shaped by deterministic processes, particularly due to heterogeneous selection of PAB; In contrast, offshore communities are governed more by stochastic processes, largely due to homogenizing dispersal of FLB. Consequently, the findings of this study demonstrate that nearshore and PAB communities exhibit higher levels of species diversity, while stochastic and deterministic processes exert distinct influences on communities among near- and offshore regions. This study further sheds new light on our understanding of the mechanisms governing bacterial communities in estuarine ecosystems.

Differences of bacterioplankton communities between the source and upstream regions of the Yangtze River: microbial structure, co-occurrence pattern, and environmental influencing factors.

The source area of the Yangtze River is located in the hinterland of the Qinghai-Tibet Plateau, which is known as the "Earth's third pole." It is the water conservation area and the natural barrier of the ecosystem of the Yangtze River basin. It is also the most sensitive area of the natural ecosystem, and the ecological environment is very fragile. Microorganisms play key roles in the biogeochemical processes of water. In this paper, the bacterioplankton communities in the source and upstream regions of the Yangtze River were studied based on 16S rRNA high-throughput sequencing, and their environmental influencing factors were further analyzed. Results showed that the upstream region had higher richness and diversity than the source region. The predominant bacterial phyla in the source and upstream regions were Proteobacteria, Firmicutes, and Actinobacteriota. The bacterial phyla associated with municipal pollution and opportunistic pathogen, such as Firmicutes and Actinobacteriota, were more abundant in the upstream. By contrast, distinct planktonic bacterial genera associated with mining pollution, such as Acidiphilium and Acidithiobacillus, were more abundant in the source region. The co-occurrence network showed that the interaction of bacterioplankton community is more frequent in the upstream. The bacterioplankton community compositions, richness, and functional profiles were affected by the spatial heterogeneity. Moreover, variation partitioning analysis further confirmed that the amount of variation in the source region independently explained by variables of altitude was the largest, followed by water nutrient. This paper revealed the spatial distribution of planktonic bacterial communities in the source and upstream regions of the Yangtze River and its correlation with environmental factors, providing information support for ensuring the health and safety of aquatic ecosystems in the Yangtze River Basin.

Dieback and Replacement of Riparian Trees May Impact Stream Ecosystem Functioning.

Alders are nitrogen (N)-fixing riparian trees that promote leaf litter decomposition in streams through their high-nutrient leaf litter inputs. While alders are widespread across Europe, their populations are at risk due to infection by the oomycete Phytophthora ×alni, which causes alder dieback. Moreover, alder death opens a space for the establishment of an aggressive N-fixing invasive species, the black locust (Robinia pseudoacacia). Shifts from riparian vegetation containing healthy to infected alder and, eventually, alder loss and replacement with black locust may alter the key process of leaf litter decomposition and associated microbial decomposer assemblages. We examined this question in a microcosm experiment comparing three types of leaf litter mixtures: one representing an original riparian forest composed of healthy alder (Alnus lusitanica), ash (Fraxinus angustifolia), and poplar (Populus nigra); one with the same species composition where alder had been infected by P. ×alni; and one where alder had been replaced with black locust. The experiment lasted six weeks, and every two weeks, microbially driven decomposition, fungal biomass, reproduction, and assemblage structure were measured. Decomposition was highest in mixtures with infected alder and lowest in mixtures with black locust, reflecting differences in leaf nutrient concentrations. Mixtures with alder showed distinct fungal assemblages and higher sporulation rates than mixtures with black locust. Our results indicate that alder loss and its replacement with black locust may alter key stream ecosystem processes and assemblages, with important changes already occurring during alder infection. This highlights the importance of maintaining heathy riparian forests to preserve proper stream ecosystem functioning.

Proliferation and anatoxin production of benthic cyanobacteria associated with canine mortalities along a stream-lake continuum.

Proliferations of benthic cyanobacteria are increasingly in the public eye, with rising animal deaths associated with benthic rather than planktonic blooms. In early June 2021, two dogs died after consuming material on the shore of Shubenacadie Grand Lake, Nova Scotia. Preliminary investigations indicated anatoxins produced by benthic cyanobacterial mats were responsible for the deaths. In this study, we monitored the growth of a toxic benthic cyanobacterial species (Microcoleus sp.) along a stream-lake continuum where the canine poisonings occurred. We found that the species was able to proliferate in both lentic and lotic environments, but temporal growth dynamics and the predominant sub-species were influenced by habitat type, and differed with hydrodynamic setting, nutrient and sunlight availability. Toxin concentration was greatest in cyanobacterial mats growing in the oligotrophic lakeshore environment (maximum measured total anatoxins (ATXs) >20 mg·kg-1 wet weight). This corresponded with a shift in the profile of ATX analogues, which also indicated changing sub-species dominance along the stream-lake transition.

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.