Freshwater Cyanobacterial Blooms Research Articles

Evaluation of Algal Control Measures in Eutrophic Reservoirs Based on Aquatic Ecosystem Models

The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact of the other factors on algal growth varies significantly among different reservoirs. Thus, it is crucial to assess the effectiveness of various algal control measures implemented in different reservoirs. This study conducted a comprehensive assessment by establishing a eutrophication model for the Shanzi Reservoir in Fuzhou City. The model incorporated meteorology, hydrology, carbon dynamics, nutrient cycling, and biological communities. The effectiveness of diverse management measures was systematically evaluated. The findings demonstrate that increasing the water level, reducing nutrient salts in sediments, and implementing ecological fish stocking effectively suppressed algal growth to varying degrees and improved nitrogen and phosphorus levels. Lower water levels and ecological fish stocking had a significant impact on algal reproduction, while sediment reduction had a minimal effect. Conversely, lower water levels and ecological fish stocking did not significantly improve nitrogen and phosphorus concentrations in the reservoir, whereas sediment reduction had a noticeable effect. Consequently, the management strategies for the Shanzi Reservoir should prioritize external control measures and the implementation of ecological fish stocking.

An assessment of a biosensor system for the quantification of microcystins in freshwater cyanobacterial blooms

Microcystin-producing cyanobacterial blooms are a global issue threatening drinking water supplies and recreation on lakes and beaches. Direct measurement of microcystins is the only way to ensure waters have concentrations below guideline concentrations; however, analyzing water for microcystins takes several hours to days to obtain data. We tested LightDeck Diagnostics’ bead beater cell lysis and two versions of the quantification system designed to give microcystin concentrations within 20 min and compared it to the standard freeze-thaw cycle lysis method and ELISA quantification. The bead beater lyser was only 30 % effective at extracting microcystins compared to freeze-thaw. When considering freeze-thaw samples analyzed in 2021, there was good agreement between ELISA and LightDeck version 2 (n = 152; R2 = 0.868), but the LightDeck slightly underestimated microcystins (slope of 0.862). However, we found poor relationships between LightDeck version 2 and ELISA in 2022 (n = 49, slopes 0.60 to 1.6; R2 < 0.6) and LightDeck version 1 (slope = 1.77 but also a high number of less than quantifiable concentrations). After the quantification issues are resolved, combining the LightDeck system with an already-proven rapid lysis method (such as microwaving) will allow beach managers and water treatment operators to make quicker, well-informed decisions.

Toward a Predictive Understanding of Cyanobacterial Harmful Algal Blooms through AI Integration of Physical, Chemical, and Biological Data.

Freshwater cyanobacterial harmful algal blooms (cyanoHABs) are a worldwide problem resulting in substantial economic losses, due to harm to drinking water supplies, commercial fishing, wildlife, property values, recreation, and tourism. Moreover, toxins produced from some cyanoHABs threaten human and animal health. Climate warming can affect the distribution of cyanoHABs, where rising temperatures facilitate more intense blooms and a greater distribution of cyanoHABs in inland freshwater. Nutrient runoff from adjacent watersheds is also a major driver of cyanoHAB formation. While some of the physicochemical factors behind cyanoHAB dynamics are known, there are still major gaps in our understanding of the conditions that trigger and sustain cyanoHABs over time. In this perspective, we suggest that sufficient data sets, as well as machine learning (ML) and artificial intelligence (AI) tools, are available to build a comprehensive model of cyanoHAB dynamics based on integrated environmental/climate, nutrient/water chemistry, and cyanoHAB microbiome and 'omics data to identify key factors contributing to HAB formation, intensity, and toxicity. By taking a holistic approach to the analysis of all available data, including the rapidly growing number of biological data sets, we can provide the foundational knowledge needed to address the increasing threat of cyanoHABs to the security of our water resources.

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.

Summer Phytoplankton Assemblages and Harmful Cyanobacterial Blooms in Freshwaters of New Jersey

Summer Phytoplankton Assemblages and Harmful Cyanobacterial Blooms in Freshwaters of New Jersey

Expression of Microcystis Biosynthetic Gene Clusters in Natural Populations Suggests Temporally Dynamic Synthesis of Novel and Known Secondary Metabolites in Western Lake Erie.

Microcystis spp. produce diverse secondary metabolites within freshwater cyanobacterial harmful algal blooms (cyanoHABs) around the world. In addition to the biosynthetic gene clusters (BGCs) encoding known compounds, Microcystis genomes harbor numerous BGCs of unknown function, indicating a poorly understood chemical repertoire. While recent studies show that Microcystis produces several metabolites in the lab and field, little work has focused on analyzing the abundance and expression of its broader suite of BGCs during cyanoHAB events. Here, we use metagenomic and metatranscriptomic approaches to track the relative abundance of Microcystis BGCs and their transcripts throughout the 2014 western Lake Erie cyanoHAB. The results indicate the presence of several transcriptionally active BGCs that are predicted to synthesize both known and novel secondary metabolites. The abundance and expression of these BGCs shifted throughout the bloom, with transcript abundance levels correlating with temperature, nitrate, and phosphorus concentrations and the abundance of co-occurring predatory and competitive eukaryotic microorganisms, suggesting the importance of both abiotic and biotic controls in regulating expression. This work highlights the need for understanding the chemical ecology and potential risks to human and environmental health posed by secondary metabolites that are produced but often unmonitored. It also indicates the prospects for identifying pharmaceutical-like molecules from cyanoHAB-derived BGCs. IMPORTANCE Microcystis spp. dominate cyanobacterial harmful algal blooms (cyanoHABs) worldwide and pose significant threats to water quality through the production of secondary metabolites, many of which are toxic. While the toxicity and biochemistry of microcystins and several other compounds have been studied, the broader suite of secondary metabolites produced by Microcystis remains poorly understood, leaving gaps in our understanding of their impacts on human and ecosystem health. We used community DNA and RNA sequences to track the diversity of genes encoding synthesis of secondary metabolites in natural Microcystis populations and assess patterns of transcription in western Lake Erie cyanoHABs. Our results reveal the presence of both known gene clusters that encode toxic secondary metabolites as well as novel ones that may encode cryptic compounds. This research highlights the need for targeted studies of the secondary metabolite diversity in western Lake Erie, a vital freshwater source to the United States and Canada.

Understanding the relationship between nutrient availability and freshwater cyanobacterial growth and abundance

ABSTRACT Anthropogenic eutrophication is a well-established cause of cyanobacterial blooms in freshwaters. Early studies proposed eutrophication control focused on phosphorus (P) as the key limiting nutrient. The rationale was that nitrogen (N) limitation is alleviated by diazotrophic cyanobacteria that fix atmospheric N. However, more recently, studies suggest that the importance of N fixation may have been overstated, and some call for anthropogenic N control as well as P. Reducing nutrient concentrations below critical levels clearly reduces phytoplankton biomass, but increasing evidence shows that cyanobacterial species can adapt to low and variable nutrient conditions, outcompeting eukaryotic phytoplankton. Strategies supporting cyanobacterial dominance include (1) high affinity P uptake, (2) preferencing cellular storage of P over immediate metabolic utilization for growth, (3) alternation between N fixation and inorganic N utilization as needed, and (4) use of organic nutrients when inorganic nutrient supplies are limited. Predicting the ecological responses of cyanobacteria to nutrients therefore requires more complex models than the simple resource models using inorganic nutrients widely used for contemporary studies. Additionally, many ecological studies are not conducted on timescales relevant to understanding how nutrient fluxes drive physiological responses. We advocate for greater use of high-frequency automated measurements of nutrients and cyanobacteria to address the timescale issue. Additionally, field-based experimental studies focused on nutrient cycling, fluxes, and pools are needed to validate laboratory findings and extrapolate them to in situ conditions. The challenge is to undertake these studies at sufficient spatial and temporal scales to predict large-scale responses of cyanobacteria to nutrients.

Woronichinia naegeliana: A common nontoxigenic component of temperate freshwater cyanobacterial blooms with 30% of its genome in transposons

Monitoring in the U.S. state of Washington across the period 2007–2019 showed that Woronichinia has been present in many lakes state-wide. This cyanobacterium was commonly dominant or sub-dominant in cyanobacterial blooms in the wet temperate region west of the Cascade Mountains. In these lakes, Woronichinia often co-existed with Microcystis, Dolichospermum and Aphanizomenon flos-aquae and the cyanotoxin microcystin has often been present in those blooms, although it has not been known whether Woronichinia is a toxin producer. We report the first complete genome of Woronichinia naegeliana WA131, assembled from the metagenome of a sample collected from Wiser Lake, Washington, in 2018. The genome contains no genes for cyanotoxin biosynthesis or taste-and-odor compounds, but there are biosynthetic gene clusters for other bioactive peptides, including anabaenopeptins, cyanopeptolins, microginins and ribosomally produced, post-translationally modified peptides. Genes for photosynthesis, nutrient acquisition, vitamin synthesis and buoyancy that are typical of bloom-forming cyanobacteria are present, although nitrate and nitrite reductase genes are conspicuously absent. However, the 7.9 Mbp genome is 3–4 Mbp larger than those of the above-mentioned frequently co-existing cyanobacteria. The increased genome size is largely due to an extraordinary number of insertion sequence elements (transposons), which account for 30.3% of the genome and many of which are present in multiple copies. The genome contains a relatively large number of pseudogenes, 97% of which are transposase genes. W. naegeliana WA131 thus seems to be able to limit the potentially deleterious effects of high rates of recombination and transposition to the mobilome fraction of its genome.

Cyanobacterial Harmful Bloom Lipopolysaccharides Induce Pro-Inflammatory Effects in Immune and Intestinal Epithelial Cells In Vitro.

Freshwater cyanobacterial harmful blooms (CyanoHABs) produce a variety of toxic and bioactive compounds including lipopolysaccharides (LPSs). The gastrointestinal tract can be exposed to them via contaminated water even during recreational activities. However, there is no evidence of an effect of CyanoHAB LPSs on intestinal cells. We isolated LPSs of four CyanoHABs dominated by different cyanobacterial species and LPSs of four laboratory cultures representing the respective dominant cyanobacterial genera. Two intestinal and one macrophage cell lines were used to detect in vitro pro-inflammatory activity of the LPS. All LPSs isolated from CyanoHABs and laboratory cultures induced cytokines production in at least one in vitro model, except for LPSs from the Microcystis PCC7806 culture. LPSs isolated from cyanobacteria showed unique migration patterns in SDS-PAGE that were qualitatively distinct from those of endotoxins from Gram-negative bacteria. There was no clear relationship between the biological activity of the LPS and the share of genomic DNA of Gram-negative bacteria in the respective biomass. Thus, the total share of Gram-negative bacteria, or the presence of Escherichia coli-like LPSs, did not explain the observed pro-inflammatory activities. The pro-inflammatory properties of environmental mixtures of LPSs from CyanoHABs indicate their human health hazards, and further attention should be given to their assessment and monitoring.

Modelling Microcystis Cell Density in a Mediterranean Shallow Lake of Northeast Algeria (Oubeira Lake), Using Evolutionary and Classic Programming

Caused by excess levels of nutrients and increased temperatures, freshwater cyanobacterial blooms have become a serious global issue. However, with the development of artificial intelligence and extreme learning machine methods, the forecasting of cyanobacteria blooms has become more feasible. We explored the use of multiple techniques, including both statistical [Multiple Regression Model (MLR) and Support Vector Machine (SVM)] and evolutionary [Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Bird Swarm Algorithm (BSA)], to approximate models for the prediction of Microcystis density. The data set was collected from Oubeira Lake, a natural shallow Mediterranean lake in the northeast of Algeria. From the correlation analysis of ten water variables monitored, six potential factors including temperature, ammonium, nitrate, and ortho-phosphate were selected. The performance indices showed; MLR and PSO provided the best results. PSO gave the best fitness but all techniques performed well. BSA had better fitness but was very slow across generations. PSO was faster than the other techniques and at generation 20 it passed BSA. GA passed BSA a little further, at generation 50. The major contributions of our work not only focus on the modelling process itself, but also take into consideration the main factors affecting Microcystis blooms, by incorporating them in all applied models.

Identification of neurotoxic compounds in cyanobacteria exudate mixtures.

Release of toxic cyanobacterial secondary metabolites threatens biosecurity, foodwebs and public health. Microcystis aeruginosa (Ma), the dominant species in global freshwater cyanobacterial blooms, produces exudates (MaE) that cause adverse outcomes including nerve damage. Previously, we identified > 300 chemicals in MaE. It is critical to investigate neurotoxicity mechanisms of active substances among this suite of Ma compounds. Here, we screened 103 neurotoxicity assays from the ToxCast database to reveal targets of action of MaE using machine learning. We then built a potential Adverse Outcome Pathway (AOP) to identify neurotoxicity mechanisms of MaE as well as key targets. Finally, we selected potential neurotoxins matched with those targets using molecular docking. We found 38 targets that were inhibited and eight targets that were activated, collectively mainly related to neurotransmission (i.e. cholinergic, dopaminergic and serotonergic neurotransmitter systems). The potential AOP of MaE neurotoxicity could be caused by blocking calcium voltage-gated channel (CACNA1A), because of antagonizing neurotransmitter receptors, or because of inhibiting solute carrier transporters. We identified nine neurotoxic MaE compounds with high affinity to those targets, including LysoPC(16:0), 2-acetyl-1-alkyl-sn-glycero-3-phosphocholine, egonol glucoside, polyoxyethylene (600) monoricinoleate, and phytosphingosine. Our study enhances understanding of neurotoxicity mechanisms and identifies neurotoxins in cyanobacterial bloom exudates, which may help identify priority compounds for cyanobacteria management.

Paradox versus paradigm: A disconnect between understanding and management of freshwater cyanobacterial harmful algae blooms

AbstractFreshwater cyanobacterial harmful algae blooms (cHABs) are a major threat to human and environmental health and are increasing globally in frequency and severity. To manage this threat in a timely manner, science must focus on increasing our ability to predict the growth and toxigenicity of specific taxa of cyanobacteria.Recent molecular research has revealed striking genomic and metabolic diversity among the many morphologically indistinguishable sub‐species and strains of cyanobacteria. Assemblage‐level molecular metabolic capability surveys promise to improve our ability to predict cyanobacterial responses to environmental forcing, but many of these cutting‐edge techniques are not widely available or cost‐effective enough to be employed in routine monitoring programmes to support management decisions. Taxonomic ambiguity, cryptic functional specialisation, incongruence between genomic capability and phylogeny, and genomic flexibility impose severe challenges to our ability to ascribe autecological attributes at a level of taxonomic resolution that is attainable under current management strategies (i.e. Linnaean species). This lack of knowledge prohibits reliable predictions of species' responses to environmental stressors.Cyanobacterial species comprise consortia of metabolically diverse, morphologically indistinct strains that span a range of ecological specialisation. Under current, broadly applied taxonomic concepts, these species functionally embody a generalist ecological strategy—persisting and/or proliferating where other specialised competitors are negatively impacted.We postulate that within current management frameworks, characterising of cyanobacterial species as competing generalists, as well as considering abundance trajectories of well‐characterised, non‐cyanobacterial specialist phytoplankton will generate more scalable, mechanistic, and management‐relevant insight into increasing cHAB frequency and severity in suitable time frames.Here we recommend that cHAB management considers the competitive framework of phytoplankton communities, including cyanobacteria, wherein diverse environmental changes lead to deterministic responses by readily identifiable, documented specialist taxa. Characterising these changes in community structure will quantify the relative importance of altered stressors and resource availability that can be exploited by metabolically flexible cyanobacteria.

The Self-Bleaching Process of Microcystis aeruginosa is Delayed by a Symbiotic Bacterium Pseudomonas sp. MAE1-K and Promoted by Methionine Deficiency.

ABSTRACTVarious interactions between marine cyanobacteria and heterotrophic bacteria have been known, but the symbiotic relationships between Microcystis and heterotrophic bacteria remain unclear. An axenic M. aeruginosa culture (NIES-298) was quickly bleached after exponential growth, whereas a xenic M. aeruginosa culture (KW) showed a normal growth curve, suggesting that some symbiotic bacteria may delay this bleaching. The bleaching process of M. aeruginosa was distinguished from the phenomena of previously proposed chlorosis and programmed cell death in various characteristics. Bleached cultures of NIES-298 quickly bleached actively growing M. aeruginosa cultures, suggesting that M. aeruginosa itself produces bleach-causing compounds. Pseudomonas sp. MAE1-K delaying the bleaching of NIES-298 cultures was isolated from the KW culture. Bleached cultures of NIES-298 treated with strain MAE1-K lost their bleaching ability, suggesting that strain MAE1-K rescues M. aeruginosa from bleaching via inactivation of bleaching compounds. From Tn5 transposon mutant screening, a metZ mutant of strain MAE1-K (F-D3) unable to synthesize methionine, promoting the bleaching of NIES-298 cultures but capable of inactivating bleaching compounds, was obtained. The bleaching process of NIES-298 cultures was promoted with the coculture of mutant F-D3 and delayed by methionine supplementation, suggesting that the bleaching process of M. aeruginosa is promoted by methionine deficiency.IMPORTANCE Cyanobacterial blooms in freshwaters represent serious global concerns for the ecosystem and human health. In this study, we found that one of the major species in cyanobacterial blooms, Microcystis aeruginosa, was quickly collapsed after exponential growth by producing self-bleaching compounds and that a symbiotic bacterium, Pseudomonas sp. MAE1-K delayed the bleaching process via the inactivation of bleaching compounds. In addition, we found that a metZ mutant of strain MAE1-K (F-D3) causing methionine deficiency promoted the bleaching process of M. aeruginosa, suggesting that methionine deficiency may induce the production of bleaching compounds. These results will provide insights into the symbiotic relationships between M. aeruginosa and heterotrophic bacteria that will contribute to developing novel strategies to control cyanobacterial blooms.

Biological control of Freshwater Cyanobacterial blooms; A Review

Journal of the University of Ruhuna is published biannually as an online journal by University of Ruhuna. Research articles, Short communications, Research notes and Review articles in all fields of Science and Technology, Management and Social Sciences are accepted any time during the year to be considered for publication.

Subtropical Freshwater Cyanobacterial Blooms as Hydrogen Peroxide Hot Spots

In aquatic environments, chemical and biological processes represent major sources of reactive oxygen species (ROS) such as hydrogen peroxide. Diurnal patterns of hydrogen peroxide in surface water may suggest photochemical processes affect ROS dynamics. We hypothesized that thin surface hydrogen peroxide maxima could be detected through millimeter-scale depth profiling. These maxima were previously overlooked because they cannot be detected using standard surface water sampling techniques. Combined field and laboratory experiments demonstrated that cyanobacterial blooms could create extremely high concentrations of hydrogen peroxide in a thin layer of surface water (5–60 mm). Hydrogen peroxide concentrations were higher within surface scums of Microcystis aeruginosa than in areas without scum. The cyanobacterial scum increased the temperature of the ambient water, and hydrogen peroxide concentrations were higher at locations exposed to sunlight that at locations in the shade. We found that scum samples directly collected from the field could release hydrogen peroxide to the surrounding water when the biomass was exposed by the light, while 20 laboratory cultures tested did not. The production of hydrogen peroxide from cyanobacteria may depend on the physiological condition of cells. Overall, we identified thin surface water layers during subtropical freshwater cyanobacterial blooms as hydrogen peroxide hot spots.

Simultaneous biodegradation of harmful Cylindrospermopsis raciborskii and cylindrospermopsin toxin in batch culture by single Bacillus strain.

This study investigates the capability of a Bacillus flexus strain isolated from decayed cyanobacterial blooms for the bioremediation of Cylindrospermopsis raciborskii and cylindrospermopsin (CYN) toxin. The algicidal activity of this strain was tested by co-cultivation with C. raciborskii cultures. CYN biodegradation was investigated in the presence of living and heat-inactivated bacterial cells or bacterial filtrate. Living bacterial cells inhibited C. raciborskii growth after 2 days of incubation with complete cell death at day 5. Bacterial filtrate caused a rapid reduction in C. raciborskii growth at the first day, with complete cell lysis at day 3. Only living cells of SSZ01 caused reduction in CYN released into the medium during the bacterial decay of C. raciborskii cells. The biodegradation rate of CYN by SSZ01 relied on initial toxin concentrations. The highest rate (42 μg CYN L-1 day-1) was obtained at the higher initial concentration (300 μg L-1), and the lowest (4μg CYN L-1 day-1) was at lower concentration (50 μg L-1). These results suggest that this bacterial strain could be employed to bioremediate cyanobacterial blooms in freshwaters. Also, the application of this bacterium in slow sand filters would give possibilities for degradation and bioremediation of cyanotoxins in drinking water treatment plants.

Long-term seasonal and temporal changes of hydrogen peroxide from cyanobacterial blooms in fresh waters

In water, hydrogen peroxide (H2O2) is produced through abiotic and biotic reactions with organic matter, including algal cells. The production of H2O2 is influenced by harmful algal cell communities and toxicity. However, only a few studies have been conducted on H2O2 concentrations in natural water. Particularly, the seasonal and temporal patterns of H2O2 concentration suggest that H2O2 generation from aquatic microorganisms could be identified to compare of photochemical production from dissolved organic matter. Study area is a source of raw water and is a large artificial lake located near a metropolitan city. Due to various environmental conditions, harmful algal blooms frequently occur in summer. The purpose of this study was to trace the H2O2 concentration and water quality parameters of study area where algal bloom occurs and what factors directly affect the H2O2 concentration. Experiments were performed on the influencing factors via water samples from study area and lab-scale culture tank. The lake produces an average of 553 nM H2O2, which increases by more than three times (1460 nM) in summer compared the winter. The lake (18.6–23.8 nMh−1) produced more H2O2 than streams (7.4–9.0 nMh−1) during daylight hours. All water sites presented the lowest production rates in dark conditions (1.1–1.5 nMh−1). Daytime environment increased the generation rate more than the nighttime. The trend of H2O2 produced by algal cells was similar to that of the growth of algal cells. The exposure to external substances (heavy metals and antibiotics) increased the incidence by approximately five times; antibiotics were more influential than heavy metals.

Simultaneous Removal of the Freshwater Bloom-Forming Cyanobacterium Microcystis and Cyanotoxin Microcystins via Combined Use of Algicidal Bacterial Filtrate and the Microcystin-Degrading Enzymatic Agent, MlrA.

Freshwater cyanobacterial blooms (e.g., Microcystis blooms) constitute a major global environmental problem because of their risks to public health and aquatic ecological systems. Current physicochemical treatments of toxic cyanobacteria cause the significant release of cyanotoxin microcystins from damaged cells. Biological control is a promising eco-friendly technology to manage harmful cyanobacteria and cyanotoxins. Here, we demonstrated an efficient biological control strategy at the laboratory scale to simultaneously remove Microcystis and microcystins via the combined use of the algicidal bacterial filtrate and the microcystin-degrading enzymatic agent. The algicidal indigenous bacterium Paenibacillus sp. SJ-73 was isolated from the sediment of northern Lake Taihu, China, and the microcystin-degrading enzymatic agent (MlrA) was prepared via the heterologous expression of the mlrA gene in the indigenous microcystin-degrading bacterium Sphingopyxis sp. HW isolated from Lake Taihu. The single use of a fermentation filtrate (5%, v/v) of Paenibacillus sp. SJ-73 for seven days removed the unicellular Microcystis aeruginosa PCC 7806 and the native colonial Microcystis strain TH1701 in Lake Taihu by 84% and 92%, respectively, whereas the single use of MlrA removed 85% of microcystins. Used in combination, the fermentation filtrate and MlrA removed Microcystis TH1701 and microcystins by 92% and 79%, respectively. The present biological control thus provides an important technical basis for the further development of safe, efficient, and effective measures to manage Microcystis blooms and microcystins in natural waterbodies.

What drives the dominance and distribution of Cyanobacteria and Dinoflagellata in reservoirs of Sri Lanka?

Frequent records and health concerns in recent times have directed more attention on freshwater cyanobacterial and dinoflagellate blooms in Sri Lanka. Physico-chemical factors influencing phytoplankton growth are still under debate. This necessitates understanding environmental trends governing the dominance and distribution of algal blooms. Hence this study aimed to assess the dominance of Cyanobacteria and Dinoflagellata in reservoirs of Sri Lanka covering the three major climatic regions of the country, the Wet, Intermediate and Dry Zones. Plankton samples were collected using open type 20 µm plankton net and identified using standard phytoplankton keys. Ninety-one species belonging to three phyla of phytoplankton were identified. Phylum Chlorophyta represented the highest species number followed by Bacillariophyta and Cyanophyta. Fourteen genera of Cyanobacteria were recorded and eleven of them were potentially toxigenic. The widest distribution was shown by Chroococcus and Merismopedia. Cylindrospermopsis raciborskii with the highest mean relative abundance was recorded in Intermediate and Dry Zone reservoirs. Peridinium aciculiferum was the only dinoflagellate species recorded during the study with the highest abundance in the Isinbessagala rocky pond. Except sixteen reservoirs which were mesoeutrophic, all the other studied reservoirs were found to be either eutrophic or hypereutrophic. Iranamadu tank recorded the highest TP concentration (236 µg L-1) value. NO3-:TP ratio revealed the phosphate limited conditions in Wet and Dry Zone reservoirs whereas N was a limited factor in Intermediate Zone. Canonical Correspondence Analysis (CCA) results revealed that Secchi depth and area of water spread are important in determining both site and species variations in reservoirs of Sri Lanka.

Removal of cyanobacteria and cyanotoxins by ferrate from polluted lake water.

Freshwater cyanobacterial blooms are becoming increasingly problematic microbiological pollutants, especially for the water resource and surface natural lakes. Cyanobacterial blooms, which produce toxins and microcystins, negatively affect the quality of water, animal, and human health, and they have also negative impact on recreational activities. The effect of electrochemically prepared potassium ferrate (green oxidation agent) on the water polluted by cyanobacteria and cyanotoxins was studied. The two most frequently occurring cyanobacterial genus Microcystis and Anabaena and the most toxic and abundant microcystin MC-LR were successfully inactivated and treated by ferrate. Potassium ferrates were applied at different conditions, such as varied hydrodynamics flow of samples, pH, and Fe(VI) concentrations. High detected elimination efficiency was consequently tested on the real water matrix from microbiological polluted natural lake Šaštín-Gazárka in Slovakia. The ferrate application leads to the better chemical, biological, microbiological, and ecotoxicological outcomes.