Bioavailable Nutrients (N and P) and Precipitation Patterns Drive Cyanobacterial Blooms in Missisquoi Bay, Lake Champlain

The impact of ammonia and microcystin-LR on neurobehavior and glutamate/gamma-aminobutyric acid balance in female zebrafish (Danio rerio): ROS and inflammation as key pathways

Ammonia and microcystin-LR (MC-LR) are both toxins that can be in eutrophic waters during cyanobacterial blooms. While previous studies have focused on the effects of ammonia exposure on fish neurobehavioral toxicity, little attention has been given to the effects of MC-LR and combined exposures to both. This study exposed adult female zebrafish to ammonia (30 mg/L) and MC-LR (10 μg/L) alone and in combination for 30 days to investigate their neurotoxic effects and underlying mechanisms. Behavioral results showed that exposure to ammonia and MC-LR, both alone and in combination, led to decreased locomotor activity and increased anxiety in fish. Histomorphological analysis revealed the formation of thrombi and vacuolization in the brain across all exposure groups. Exposure to ammonia and MC-LR resulted in significant increases in MDA contents, decreases in Mn-SOD activities, and alterations in GSH contents compared to the control. Single and combined exposure to ammonia and MC-LR also induced the release of inflammatory factors (IL-1β and TNF-α) by activating the NOD/NF-κB signaling pathway. Furthermore, both ammonia and MC-LR significantly changed the expression of genes related to the glutamatergic and GABAergic systems, elevated Glu and GABA contents, as well as increased the Glu/GABA ratio, indicating that a shift towards increased Glu levels. Overall, these findings suggested that exposure to MC-LR and ammonia, individually and in combination, could decrease locomotor activity and increase anxiety of female zebrafish. This was likely due to brain damage from over-activated ROS and the release of pro-inflammatory cytokines, which led to a disruption in the balance of glutamatergic and GABAergic systems. However, there was no significant interaction between MC-LR and ammonia in fish neurobehavioral toxicity.

Hysteresis analysis reveals how phytoplankton assemblage shifts with the nutrient dynamics during and between precipitation patterns

The escalation of global eutrophication has significantly increased due to the impact of climate change, particularly the increased frequency of extreme rainfall events. Predicting and managing eutrophication requires understanding the consequences of precipitation events on algal dynamics. Here, we assessed the influence of precipitation events throughout the year on nutrient and phytoplankton dynamics in a drinking water reservoir from January 2020 to January 2022. Four distinct precipitation patterns, namely early spring flood rain (THX), Plum rain (MY), Typhoon rain (TF), and Dry season (DS), were identified based on rainfall intensity, duration time, and cumulative rainfall. The study findings indicate that rainfall is the primary driver of algal dynamics by altering nutrient levels and TN:TP ratios during wet seasons, while water temperature becomes more critical during the Dry season. Combining precipitation characteristics with the lag periods between algal proliferation and rainfall occurrence is essential for accurately assessing the impact of rainfall on algal blooms. The highest algae proliferation occurred approximately 20 and 30 days after the peak rainfall during the MY and DS periods, respectively. This was influenced by the intensity and cumulative precipitation. The reservoir exhibited two distinct TN/TP ratio stages, with average values of 52 and 19, respectively. These stages were determined by various forms of nitrogen and phosphorus in rainfall-driven inflows and were associated with shifts from Bacillariophyta-dominated to Cyanophyta-dominated blooms during the MY and DS seasons. Our findings underscore the interconnected effects of nutrients, temperature, and hydrological conditions driven by diverse rainfall patterns in shaping algal dynamics. This study provides valuable insights into forecasting algal bloom risks in the context of climate change and developing sustainable strategies for lake or reservoir restoration.

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.

New insights into endocrine reproductive toxicity of Microcystis aeruginosa combined with ammonia exposure in zebrafish

The ecological risk posed by MCs-producing M. aeruginosa and elevated ammonia to fish in actual aquatic environments remains uncertain. To address this knowledge gap, we conducted simulations to investigate the endocrine-reproductive toxicity of prolonged exposure (45 d) to Microcystis aeruginosa (2 × 10^6 cells/mL) and 30 mg/L total ammonia nitrogen (TAN) in zebrafish under environmentally relevant conditions. Our results showed that exposure to M. aeruginosa significantly inhibited the body weight, increased gonadosomatic index (GSI), delayed oocyte development, and disrupted endocrine hormonal balance (reduced gonadotropin-releasing hormone (GnRH), and increased estradiol (E2) and testosterone (T)). Mechanistically, it should be attributed to the over-expression of hypothalamic-pituitary-gonadal-liver (HPGL) axis-related genes (cyp11a and cyp17) induced by M. aeruginosa. On the other hand, TAN exposure caused mild damage to zebrafish ovarian tissue and promoted an increase of T levels by inducing the upregulation of steroid hormone synthesis gene (3βhsd) expression in the ovary. It is worth noting that the dysregulation of E2/T ratio in zebrafish ovaries may be attributed to the inhibition of cyp19a1a by both M. aeruginosa and TAN. These results were further confirmed by changes in steroidogenic enzymes activities in the M. aeruginosa or TAN treated groups. Our findings indicated that exposure to M. aeruginosa and TAN had adverse impacts on the reproductive system of zebrafish. And the combined exposure of M. aeruginosa and TAN had more severe effects on the body weight, GSI, pathological changes, hormone levels and HPGL-axis related gene expression in female zebrafish. These results provide compelling evidence regarding the potential risks for reproductive health associated with M. aeruginosa and TAN in eutrophic water bodies experiencing M. aeruginosa blooms, and contribute to the development of effective strategies for monitoring and managing these toxins in aquatic ecosystems.

Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs

This forecasting approach may be useful for water managers and associated public health managers to predict near-term future high-risk cyanobacterial harmful algal blooms (cyanoHAB) occurrence. Freshwater cyanoHABs may grow to excessive concentrations and cause human, animal, and environmental health concerns in lakes and reservoirs. Knowledge of the timing and location of cyanoHAB events is important for water quality management of recreational and drinking water systems. No quantitative tool exists to forecast cyanoHABs across broad geographic scales and at regular intervals. Publicly available satellite monitoring has proven effective in detecting cyanobacteria biomass near-real time within the United States. Weekly cyanobacteria abundance was quantified from the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite as the response variable. An Integrated Nested Laplace Approximation (INLA) hierarchical Bayesian spatiotemporal model was applied to forecast World Health Organization (WHO) recreation Alert Level 1 exceedance >12 μg L-1 chlorophyll-a with cyanobacteria dominance for 2192 satellite resolved lakes in the United States across nine climate zones. The INLA model was compared against support vector classifier and random forest machine learning models; and Dense Neural Network, Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Gneural Network (GNU) neural network models. Predictors were limited to data sources relevant to cyanobacterial growth, readily available on a weekly basis, and at the national scale for operational forecasting. Relevant predictors included water surface temperature, precipitation, and lake geomorphology. Overall, the INLA model outperformed the machine learning and neural network models with prediction accuracy of 90% with 88% sensitivity, 91% specificity, and 49% precision as demonstrated by training the model with data from 2017 through 2020 and independently assessing predictions with data from the 2021 calendar year. The probability of true positive responses was greater than false positive responses and the probability of true negative responses was less than false negative responses. This indicated the model correctly assigned lower probabilities of events when they didn't exceed the WHO Alert Level 1 threshold and assigned higher probabilities when events did exceed the threshold. The INLA model was robust to missing data and unbalanced sampling between waterbodies.

Community structure and niche differentiation of endosphere bacterial microbiome in Camellia oleifera

IMPORTANCE

Microorganisms inhabited various tissues of plants and play a key role in promoting plant growth, nutritional absorption, and resistance. Our research indicates that the diversity of Camellia oleifera endophytic bacterial communities is highly dependent on the plant compartment. Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Chloroflexi, and Verrucomicrobia are dominant bacteria phyla. The tissues of Camellia oleifera contain various bacteria with nitrogen fixation potential, host life promotion, and plant defense. This study provides a scientific theoretical basis for an in-depth discussion of plant-endosphere microbial interaction and better exploration of benign interaction of beneficial microorganisms and plants.

Perceptions of Freshwater Algal Blooms, Causes and Health among New Brunswick Lakefront Property Owners

Changes to water conditions due to eutrophication and climate change have resulted in the proliferation of algae blooms in freshwater and marine environments globally, including in Canadian lakes. We developed and administered an online survey to evaluate the awareness of these blooms and the perceptions of health risks in a sample of New Brunswick waterfront cottage and homeowners. The survey was distributed to lake and cottage associations in New Brunswick and was completed by 186 eligible respondents (18 years of age or older). Participants were asked about the water quality of their lake, awareness about algae blooms, sociodemographic and cottage characteristics, and to complete a self-rated measure of physical and mental health. While approximately 73% of participants reported that the quality of their lake water was good or very good, 41% indicated a concern about algae blooms. We found no differences in self-reported physical or mental health between those who were aware of algae blooms at their cottage and those who were not (p > 0.05). Participants expressed concerns about the impacts of algae blooms on the health of their pets, and wildlife. While climate change was the most frequently identified cause of algae blooms, there was substantial heterogeneity in the responses. In addition, the reporting of the presence and frequency of algae bloom varied between respondents who lived on the same lake. Taken together, the findings from our survey suggest that cottage owners in New Brunswick are aware and concerned about the impacts of algae blooms, however, there is a need to provide additional information to them about the occurrence and causes of these blooms.