Health impacts from cyanobacteria harmful algae blooms: Implications for the North American Great Lakes

Microcystin-LR in drinking water: An emerging role of mitochondrial-induced epigenetic modifications and possible mitigation strategies

Algal blooms are a serious menace to freshwater bodies all over the world. These blooms typically comprise cyanobacterial outgrowths that produce a heptapeptide toxin, Microcystin-LR (MC-LR). Chronic MC-LR exposure impairs mitochondrial-nuclear crosstalk, ROS generation, activation of DNA damage repair pathways, apoptosis, and calcium homeostasis by interfering with PC/MAPK/RTK/PI3K signaling. The discovery of the toxin's biosynthesis pathways paved the way for the development of molecular techniques for the early detection of microcystin. Phosphatase inhibition-based bioassays, high-performance liquid chromatography, and enzyme-linked immunosorbent tests have recently been employed to identify MC-LR in aquatic ecosystems. Biosensors are an exciting alternative for effective on-site analysis and field-based characterization. Here, we present a synthesis of evidence supporting MC-LR as a mitotoxicant, examine various detection methods, and propose a novel theory for the relevance of MC-LR-induced breakdown of mitochondrial machinery and its myriad biological ramifications in human health and disease.

Machine learning predicts the growth of cyanobacterial genera in river systems and reveals their different environmental responses

Cyanobacterial blooms are a common and serious problem in global freshwater environments. However, the response mechanisms of various cyanobacterial genera to multiple nutrients and pollutants, as well as the factors driving their competitive dominance, remain unclear or controversial. The relative abundance and cell density of two dominant cyanobacterial genera (i.e., Cyanobium and Microcystis) in river ecosystems along a gradient of anthropogenic disturbance were predicted by random forest with post-interpretability based on physicochemical indices. Results showed that the optimized predictions all reached strong fitting with R2 > 0.75, and conventional water quality indices played a dominant role. One-dimensional and two-dimensional partial dependence plot (PDP) revealed that the responses of Cyanobium and Microcystis to nutrients and temperature were similar, but they showed differences in preferrable nutrient utilization and response to pollutants. Further prediction and PDP for the ratio of Cyanobium and Microcystis unveiled that their distinct responses to PAHs and SPAHs were crucial drivers for their competitive dominance over each other. This study presents a new way for analyzing the response of cyanobacterial genera to multiple environmental factors and their dominance relationships by interpretable machine learning, which is suitable for the identification and interpretation of high-dimensional nonlinear ecosystems with complex interactions.

Epidemiologic and clinical features of cyanobacteria harmful algal bloom exposures reported to the National Poison Data System, United States, 2010-2022: a descriptive analysis

BACKGROUND

Harmful algal bloom occurrences have been increasingly reported globally and over time. Exposure to the variety of toxins and co-contaminants that may be present in harmful algal blooms can cause illness and even death. Poison control data is a valuable public health information source that has been used to characterize many types of toxin exposures, including harmful algal blooms. Prior studies have been limited by location and time, and knowledge gaps remain regarding cyanobacteria harmful algal bloom (cyanoHAB) exposure circumstances, and the breadth and severity of associated clinical effect.

METHODS

The objective of this study was to characterize epidemiologic and clinical features of cyanoHAB exposure cases reported to 55 US poison control centers and available in the National Poison Data System (NPDS). We identified 4260 NPDS cyanoHAB exposure cases reported from 2010 to 2022, including symptomatic exposure cases with and without clinical effects related to the exposure and asymptomatic exposure cases. We assessed demographics; exposure routes, locations, chronicity; clinical effects; and medical outcomes. We calculated case rates annually and 13-year case rates by US geographic division.

RESULTS

Over half of cyanoHAB exposure cases were children < 20 years old (n = 2175). Most cyanoHABs exposures occurred in a "public area" (n = 2902, 68.1%); most were acute (≤ 8 h) (n = 3824, 89.8%). Dermal and ingestion routes and gastrointestinal effects predominated. 2% (n = 102) of cases experienced a moderate or major medical outcome; no deaths were reported. National rates increased from 0.4 cases/1 million (1 M) person-years in 2010 to 1.4 cases/1 M person-years in 2022. The Mountain division had the highest 13-year rate (7.8 cases/1 M person-years).

CONCLUSIONS

CyanoHAB exposure case rates increased 2010-2022, despite a decrease in all-cause exposure cases during the same period. NPDS data provide valuable public health information for characterization of cyanoHAB exposures, an emerging public health challenge.

Study on the applicability of FAI linear fitting model in the extraction of cyanobacterial blooms

Currently, more and more lakes around the world are experiencing outbreaks of cyanobacterial blooms, and high-precision and rapid monitoring of the spatial distribution of algae in water bodies is an important task. Remote sensing technology is one of the effective means for monitoring algae in water bodies. Studies have shown that the Floating Algae Index (FAI) is superior to methods such as the Standardized Differential Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in monitoring cyanobacterial blooms. However, compared to the NDVI method, the FAI method has difficulty in determining the threshold, and how to choose the threshold with the highest classification accuracy is challenging. In this study, FAI linear fitting model (FAI-L) is selected to solve the problem that FAI threshold is difficult to determine. Innovatively combine FAI index and NDVI index, and use NDVI index to find the threshold of FAI index. In order to analyze the applicability of FAI-L to extract cyanobacterial blooms, this paper selected multi-temporal Landsat8, HJ-1B, and Sentinel-2 remote sensing images as data sources, and took Chaohu Lake and Taihu Lake in China as research areas to extract cyanobacterial blooms. The results show that (1) the accuracy of extracting cyanobacterial bloom by FAI-L method is generally higher than that by NDVI and FAI. Under different data sources and different research areas, the average accuracy of extracting cyanobacterial blooms by FAI-L method is 95.13%, which is 6.98% and 18.43% higher than that by NDVI and FAI respectively. (2) The average accuracy of FAI-L method for extracting cyanobacterial blooms varies from 84.09 to 99.03%, with a standard deviation of 4.04, which is highly stable and applicable. (3) For simultaneous multi-source image data, the FAI-L method has the highest average accuracy in extracting cyanobacterial blooms, at 95.93%, which is 6.77% and 13.26% higher than NDVI and FAI methods, respectively. In this paper, it is found that FAI-L method shows high accuracy and stability in extracting cyanobacterial blooms, and it can extract the spatial distribution of cyanobacterial blooms well, which can provide a new method for monitoring cyanobacterial blooms.

Smartphone as an alternative to measure chlorophyll-a concentration in small waterbodies

Monitoring chlorophyll-a concentrations (Chl-a, μg·L-1) in aquatic ecosystems has attracted much attention due to its direct link to harmful algal blooms. However, there has been a lack of a cost-effective method for measuring Chl-a in small waterbodies. Inspired by the increase of smartphone photography, a Smartphone-based convolutional neural networks (CNN) framework (SCCA) was developed to estimate Chl-a in Aquatic ecosystem. To evaluate the performance of SCCA, 238 paired records (a smartphone image with a 12-color background and a measured Chl-a value) were collected from diverse aquatic ecosystems (e.g., rivers, lakes and ponds) across China in 2023. Our performance-evaluation results revealed a NS and R2 value of 0.90 and 0.94 in Chl-a estimation, demonstrating a satisfactory (NS = 0.84, R2 = 0.86) model fit in lower Chl-a (<30 μg L-1) conditions. SCCA had involved a realtime-update method with hyperparameter optimization technology. In comparison with the existing methods of measuring Chl-a, SCCA provides a useful screening tool for cost-effective measurement of Chl-a and has the potential for being an algal bloom screening means in small waterbodies, using Huajin River as a case study, especially under limited resources for water measurement. Overall, we highlight that the SCCA can be potentially integrated into a smartphone application in the future to diverse waterbodies in environmental management.

Critical review on toxic contaminants in surface water ecosystem: sources, monitoring, and its impact on human health

Surface water pollution is a critical and urgent global issue that demands immediate attention. Surface water plays a crucial role in supporting and sustaining life on the earth, but unfortunately, till now, we have less understanding of its spatial and temporal dynamics of discharge and storage variations at a global level. The contamination of surface water arises from various sources, classified into point and non-point sources. Point sources are specific, identifiable origins of pollution that release pollutants directly into water bodies through pipes or channels, allowing for easier identification and management, e.g., industrial discharges, sewage treatment plants, and landfills. However, non-point sources originate from widespread activities across expansive areas and present challenges due to its diffuse nature and multiple pathways of contamination, e.g., agricultural runoff, urban storm water runoff, and atmospheric deposition. Excessive accumulation of heavy metals, persistent organic pollutants, pesticides, chlorination by-products, pharmaceutical products in surface water through different pathways threatens food quality and safety. As a result, there is an urgent need for developing and designing new tools for identifying and quantifying various environmental contaminants. In this context, chemical and biological sensors emerge as fascinating devices well-suited for various environmental applications. Numerous chemical and biological sensors, encompassing electrochemical, magnetic, microfluidic, and biosensors, have recently been invented by hydrological scientists for the detection of water pollutants. Furthermore, surface water contaminants are monitored through different sensors, proving their harmful effects on human health.

An evaluation of statistical models of microcystin detection in lakes applied forward under varying climate conditions

Algal blooms can threaten human health if cyanotoxins such as microcystin are produced by cyanobacteria. Regularly monitoring microcystin concentrations in recreational waters to inform management action is a tool for protecting public health; however, monitoring cyanotoxins is resource- and time-intensive. Statistical models that identify waterbodies likely to produce microcystin can help guide monitoring efforts, but variability in bloom severity and cyanotoxin production among lakes and years makes prediction challenging. We evaluated the skill of a statistical classification model developed from water quality surveys in one season with low temporal replication but broad spatial coverage to predict if microcystin is likely to be detected in a lake in subsequent years. We used summertime monitoring data from 128 lakes in Iowa (USA) sampled between 2017 and 2021 to build and evaluate a predictive model of microcystin detection as a function of lake physical and chemical attributes, watershed characteristics, zooplankton abundance, and weather. The model built from 2017 data identified pH, total nutrient concentrations, and ecogeographic variables as the best predictors of microcystin detection in this population of lakes. We then applied the 2017 classification model to data collected in subsequent years and found that model skill declined but remained effective at predicting microcystin detection (area under the curve, AUC ≥ 0.7). We assessed if classification skill could be improved by assimilating the previous years' monitoring data into the model, but model skill was only minimally enhanced. Overall, the classification model remained reliable under varying climatic conditions. Finally, we tested if early season observations could be combined with a trained model to provide early warning for late summer microcystin detection, but model skill was low in all years and below the AUC threshold for two years. The results of these modeling exercises support the application of correlative analyses built on single-season sampling data to monitoring decision-making, but similar investigations are needed in other regions to build further evidence for this approach in management application.

Review of the occurrence, treatment technologies, and detection methods for saxitoxins in freshwaters

The increasing occurrence of saxitoxins in freshwaters is becoming a concern for water treatment facilities owing to its structural properties which make it resistant to oxidation at pH < 8. Hence, it is crucial to be able to monitor these toxins in surface and drinking water to protect public health. This review aims to outline the current state of knowledge related to the occurrence of saxitoxins in freshwaters and its removal strategies and provide a critical assessment of the detection methods to provide a basis for further development. Temperature and nutrient content are some of the factors that influence the production of saxitoxins in surface waters. A high dose of sodium hypochlorite with sufficient contact time or activated carbon has been shown to efficiently remove extracellular saxitoxins to meet the drinking water guidelines. While HILIC-MS has proven to be a powerful technology for more sensitive and reliable detection of saxitoxin and variants after solid phase extraction, ELISA is cost-effective and easy to use and is used by Ohio EPA for surveillance with a limit of detection of 0.015 μg/L. However, there is a need for the development of cost-effective and sensitive techniques that can quantify the variants of saxitoxin.

Microbial diversity, genomics, and phage-host interactions of cyanobacterial harmful algal blooms

The occurrence of cyanobacterial harmful algal blooms (cyanoHABs) is related to their physical and chemical environment. However, less is known about their associated microbial interactions and processes. In this study, cyanoHABs were analyzed as a microbial ecosystem, using 1 year of 16S rRNA sequencing and 70 metagenomes collected during the bloom season from Lake Okeechobee (Florida, USA). Biogeographical patterns observed in microbial community composition and function reflected ecological zones distinct in their physical and chemical parameters that resulted in bloom "hotspots" near major lake inflows. Changes in relative abundances of taxa within multiple phyla followed increasing bloom severity. Functional pathways that correlated with increasing bloom severity encoded organic nitrogen and phosphorus utilization, storage of nutrients, exchange of genetic material, phage defense, and protection against oxidative stress, suggesting that microbial interactions may promote cyanoHAB resilience. Cyanobacterial communities were highly diverse, with picocyanobacteria ubiquitous and oftentimes most abundant, especially in the absence of blooms. The identification of novel bloom-forming cyanobacteria and genomic comparisons indicated a functionally diverse cyanobacterial community with differences in its capability to store nitrogen using cyanophycin and to defend against phage using CRISPR and restriction-modification systems. Considering blooms in the context of a microbial ecosystem and their interactions in nature, physiologies and interactions supporting the proliferation and stability of cyanoHABs are proposed, including a role for phage infection of picocyanobacteria. This study displayed the power of "-omics" to reveal important biological processes that could support the effective management and prediction of cyanoHABs.

IMPORTANCE

Cyanobacterial harmful algal blooms pose a significant threat to aquatic ecosystems and human health. Although physical and chemical conditions in aquatic systems that facilitate bloom development are well studied, there are fundamental gaps in the biological understanding of the microbial ecosystem that makes a cyanobacterial bloom. High-throughput sequencing was used to determine the drivers of cyanobacteria blooms in nature. Multiple functions and interactions important to consider in cyanobacterial bloom ecology were identified. The microbial biodiversity of blooms revealed microbial functions, genomic characteristics, and interactions between cyanobacterial populations that could be involved in bloom stability and more coherently define cyanobacteria blooms. Our results highlight the importance of considering cyanobacterial blooms as a microbial ecosystem to predict, prevent, and mitigate them.

Unpredicted ecosystem response to compound human impacts in a European river

Climate change elevates the threat of compound heat and drought events, with their ecological and socioeconomic impacts exacerbated by human ecosystem alterations such as eutrophication, salinization, and river engineering. Here, we study how multiple stressors produced an environmental disaster in a large European river, the Oder River, where a toxic bloom of the brackish-water planktonic haptophyte Prymnesium parvum (the "golden algae") killed approximately 1000 metric tons of fish and most mussels and snails. We uncovered the complexity of this event using hydroclimatic data, remote sensing, cell counts, hydrochemical and toxin analyses, and genetics. After incubation in impounded upstream channels with drastically elevated concentrations of salts and nutrients, only a critical combination of chronic salt and nutrient pollution, acute high water temperatures, and low river discharge during a heatwave enabled the riverine mass proliferation of B-type P. parvum along a 500 km river section. The dramatic losses of large filter feeders and the spreading of vegetative cells and resting stages make the system more susceptible to new harmful algal blooms. Our findings show that global warming, water use intensification, and chronic ecosystem pollution could increase likelihood and severity of such compound ecoclimatic events, necessitating consideration in future impact models.

Smart proteins as a new paradigm for meeting dietary protein sufficiency of India: a critical review on the safety and sustainability of different protein sources

India, a global leader in agriculture, faces sustainability challenges in feeding its population. Although primarily a vegetarian population, the consumption of animal derived proteins has tremendously increased in recent years. Excessive dependency on animal proteins is not environmentally sustainable, necessitating the identification of alternative smart proteins. Smart proteins are environmentally benign and mimic the properties of animal proteins (dairy, egg and meat) and are derived from plant proteins, microbial fermentation, insects and cell culture meat (CCM) processes. This review critically evaluates the technological, safety, and sustainability challenges involved in production of smart proteins and their consumer acceptance from Indian context. Under current circumstances, plant-based proteins are most favorable; however, limited land availability and impending climate change makes them unsustainable in the long run. CCM is unaffordable with high input costs limiting its commercialization in near future. Microbial-derived proteins could be the most sustainable option for future owing to higher productivity and ability to grow on low-cost substrates. A circular economy approach integrating agri-horti waste valorization and C1 substrate synthesis with microbial biomass production offer economic viability. Considering the use of novel additives and processing techniques, evaluation of safety, allergenicity, and bioavailability of smart protein products is necessary before large-scale adoption.

Exudates of Microcystis aeruginosa on oxidative stress and inflammatory responses in gills of Sinocyclocheilus grahami

Early cyanobacterial blooms studies observed that exposure to blue-green algae led to fish gills impairment. The objective of this work was to evaluate the toxic mechanisms of exudates of Microcystis aeruginosa (MaE) on fish gills. In this study, the toxic mechanism of MaE (2×106 cells/mL) and one of its main components phytosphingosine (PHS) with two concentrations 2.9 ng/mL and 145 ng/mL were conducted by integrating histopathology, biochemical biomarkers, and transcriptomics techniques in Sinocyclocheilus grahami (S. grahami) for 96 h exposure. Damaged gill tissue with epithelial hyperplasia and hypertrophy, remarkable Na+/K+-ATPase (NKA) enzyme activity, disrupted the redox homeostats including lipid peroxidation and inflammatory responses were observed in the fish of MaE exposure group. Compare to MaE exposure, two concentrations of PHS exposure appeared to be a trend of lower degree of tissue damage, NKA activity and oxidative stress, but induced obviously lipid metabolism disorder with higher triglycerides, total cholesterol and total bile acid, which might be responsible for inflammation responses in fish gill. By transcriptome analysis, MaE exposure were primarily enriched in pathways related to gill function and immune response. PHS exposure, with higher number of differentially expressed genes (DEGs), were enriched in Toll-like receptor (TLR), Mitogen-Activated Protein Kinase (MAPK) and NOD-like receptor protein 3 (NLRP3) pathways. We concluded that MaE and PHS were induced the inflammatory responses, with oxidative stress-induced inflammation for MaE exposure but lipid metabolism disorder-induced inflammation for PHS exposure. The present study provided two toxin-induced gill inflammation response pathways under cyanobacterial blooms, which could be a scientific basis for the ecological and health risk assessment in the aquatic environment.

Drinking water safety improvement and future challenge of lakes and reservoirs

To meet the Sustainable Development Goal (SDG) target 6.1, China has undertaken significant initiatives to address the uneven distribution of water resources and to enhance water quality. Since 2000, China has invested heavily in the water infrastructure of numerous reservoirs, with a total storage capacity increase of 4.704 × 1011 m3 (an increase of 90.8%). These reservoirs have significantly enhanced the available freshwater resources for drinking water. Concurrently, efforts to improve water quality in lakes and reservoirs, facilitated by nationwide water quality monitoring, have been successful. As a result, an increasing lakes and reservoirs are designated as centralized drinking water sources (CDWSs) in China. Among the 3,441 CDWSs across all provinces, 40.8% are sourced from lakes and reservoirs, 32.6% from rivers, and 26.6% from groundwater in 2023. Notably, from 2016 to 2023, the percentage of lakes and reservoirs categorized as CDWSs has increased consistently across all 29 provinces. This progress has enabled 561.4 million urban residents to access improved drinking water sources in 2022, compared to 303.4 million in 2004. Our findings underscore the pivotal role of water infrastructure construction and water quality improvement jointly promoting lakes and reservoirs as vital drinking water sources. Nevertheless, the nationwide occurrence of algal blooms has surged by 113.7% from the 2000s to the 2010s , which is a considerable challenge to drinking water safety. Fortunately, algal blooms have been markedly alleviated in past four years. However, it is still crucial to acknowledge that lakes and reservoirs face the challenges of algal blooms, and associated toxic microcystin and odor compounds.

Burden of recreational water illness due to exposure to cyanobacteria and their toxins in freshwater beaches in Canada: protocol of a prospective cohort study

INTRODUCTION

Cyanobacterial blooms are increasingly common in freshwater sources used for swimming and other recreational water contact activities in Canada. Many species of cyanobacteria can produce toxins that affect human and animal health, but there are limited data on the risk of illness associated with water contact at impacted beaches.

METHODS AND ANALYSIS

This study will investigate the incidence of recreational water illness due to exposure to cyanobacterial blooms and their toxins in four targeted and popular freshwater beaches in Ontario, Manitoba and Nova Scotia, Canada. A prospective cohort design and One Health approach will be used. On-site recruitment of recreational water users will be conducted at two beaches per year during the summers of 2024 and 2025. The population of interest includes recreational water users of any age and their pet dogs. After enrolment, an in-person survey will determine beach exposures and confounding factors, and a 3-day follow-up survey will ascertain any acute illness outcomes experienced by participants or their dogs. The target sample size is 2500 recreational water users. Water samples will be taken each recruitment day and analysed for cyanobacterial indicators (pigments), cell counts and toxin levels. Bayesian regression analysis will be conducted to estimate the association with water contact, cyanobacterial levels and risks of different acute illness outcomes.

ETHICS AND DISSEMINATION

This study has been approved by the Toronto Metropolitan University Research Ethics Board (REB 2023-461). Study results will be published in a peer-reviewed journal and as infographics on a project website.

16S rRNA gene amplicon sequencing data from an Australian wastewater treatment plant

Amplicon sequencing data of the 16S rRNA (V1-V3) gene from 56 effluent and sediment samples from an Australian wastewater treatment plant are reported. Proteobacteria (3.50%-90.09%), Actinobacteria (0.02%-45.71%), and Cyanobacteria (0.05%-63.73%) were dominant in the effluent. The sediment samples were dominated by Proteobacteria (13.14%-84.83%), Chloroflexi (0.84%-42.52%), and Firmicutes (1.54%-17.21%).

Exposure to microcystin-LR promotes astrocyte proliferation both in vitro and in vivo via Hippo signaling pathway

Microcystins (MCs) are toxic to the central nervous system of mammals. However, the direct toxicity of MCs on mammalian brain cells and the involved molecular mechanisms are not fully elucidated. Here, we incubated primary astrocytes, the major glial cell-type in the brain, with 0-12.5 μM concentrations of MC-LR for 48 h, and the impairment was evaluated. We found that MC-LR caused significant increases in the cell viability at the range of 0.05-1 μM concentrations with the highest density at 0.1 μM concentration. Treatment with 0.1 μM MC-LR induced YAP nuclear translocation and decreased the ratio of p-YAP to YAP. It also decreased mRNA levels of the upstream regulator (AMOT), and enhanced expressions of YAP interacted genes (Egfr, Tead1, and Ctgf) in primary astrocytes. Overexpression of AMOT significantly attenuated the increase of MC-LR-induced astrocyte proliferation and the expression of YAP downstream genes. These results indicate that Hippo signaling contributed to MC-LR-caused astrocyte proliferation. Further, reactive astrogliosis was observed in the mice brain after MC-LR exposure to environmentally relevant concentrations (20 or 100 μg/L) through drinking water for 16 weeks. Pathological observations revealed that 100 μg/L MC-LR exposure caused neuronal damages with characteristics of shrunken or vacuolation in the region of the cerebral cortex, striatum and cerebellum. These results were accompanied with increased oxidative stress and inflammatory response. Our data reveal the potential astrocytic mechanisms in MC-induced neurotoxicity and raise an alarm for neurodegenerative disease risk following daily exposure to MC-LR.

Assessment of estrogenic potential from exudates of microcystin-producing and non-microcystin-producing Microcystis by metabolomics, machine learning and E-screen assay

Cyanobacterial blooms, often dominated by Microcystis aeruginosa, are capable of producing estrogenic effects. It is important to identify specific estrogenic compounds produced by cyanobacteria, though this can prove challenging owing to the complexity of exudate mixtures. In this study, we used untargeted metabolomics to compare components of exudates from microcystin-producing and non-microcystin-producing M. aeruginosa strains that differed with respect to their ability to produce microcystins, and across two growth phases. We identified 416 chemicals and found that the two strains produced similar components, mainly organoheterocyclic compounds (20.2%), organic acids and derivatives (17.3%), phenylpropanoids and polyketides (12.7%), benzenoids (12.0%), lipids and lipid-like molecules (11.5%), and organic oxygen compounds (10.1%). We then predicted estrogenic compounds from this group using random forest machine learning. Six compounds (daidzin, biochanin A, phenylethylamine, rhein, o-Cresol, and arbutin) belonging to phenylpropanoids and polyketides (3), benzenoids (2), and organic oxygen compound (1) were tested and exhibited estrogenic potency based upon the E-screen assay. This study confirmed that both Microcystis strains produce exudates that contain compounds with estrogenic properties, a growing concern in cyanobacteria management.

Adverse effects of Microcystis aeruginosa exudates on the filtration, digestion, and reproduction organs of benthic bivalve Corbicula fluminea

Cyanobacteria bloom and the secondary metabolites released by the microorganism are extremely harmful to aquatic animals, yet study on their adverse effects in zoobenthos is rare. Corbicula fluminea widely distributed in freshwater environment with algal blooms. It is a typical filter feeding zoobenthos that may be affected by the secondary metabolites of cyanobacteria due to its high filtering rate. In this study, C. fluminea was exposed to Microcystis aeruginosa exudates (MaE) for 96 h, which was obtained from 5 × 105 cells/mL and 2.5 × 106 cells/mL exponential stage M. aeruginosa culture solution that represented cyanobacteria cell density needs environmental risk precaution control and emergent control, respectively. The responses of C. fluminea critical organs to MaE were analyzed and evaluated based on histopathological sections, antitoxicity biomarkers, and organ function biomarkers. The results showed that all the organs underwent structural disorders, cell vacuolization, apoptosis, and necrosis, and the damage levels increased as MaE concentration increased. The detoxification and antioxidant defense systems biomarkers in each organ response to MaE exposure differently and the level of reaction improved when MaE concentration increased. The siphon rate and acetylcholinesterase activity showed that the filtration function decreased significantly as the MaE concentration increased. Increased activity of glutathione S-transferase and amylase in the digestive gland indicate that it is the major detoxification organ of C. fluminea. Increased vitellogenin concentration and enlarged oocytes in the gonad indicate that MaE may have an estrogenic effect on C. fluminea. This study demonstrates that cyanobacteria threat benthic bivalves by inducing oxidative stress, inhibiting filtering feeding system, and disturbing digestion system and reproduction potential of C. fluminea.

Summer heatwaves promote harmful algal blooms in the Fuchunjiang Reservoir, an important drinking water source

Extensive outbreaks of harmful algal blooms (HABs) occurred in the Fuchunjiang Reservoir in 2022, a crucial urban drinking water source, coinciding with extreme summer heatwaves. We hypothesize that these heatwaves contributed to HABs formation and expansion. Leveraging Landsat 8 and Sentinel-2 data, we employed clustering and machine learning methods to quantify the HABs distribution and area. Concurrent meteorological and water quality data aided in uncovering the effects of heatwave on HABs. When applying different methods to extract HABs from remote sensing images, random forest (RF) analyses indicated accuracies of 99.3% and 99.8% for Landsat 8 and Sentinel-2 data, respectively, while classification and regression tree (CART) analyses indicated 99.1% and 99.7% accuracies, respectively. Support vector machine (SVM) exhibited lower accuracies (83.5% and 97.4%). Thus RF, given its smaller differences between satellites and high accuracy, was selected for further analysis. Both satellites detected extensive HABs in 2022, with Sentinel-2 recording a peak area of 24.13 km2 (44.6% of cloud-free water area) on August 11, 2022. Increasing trends with amplified durations were observed for summer heatwaves in Jiande and Tonglu around the Fuchunjiang Reservoir. Notably, these areas experienced extreme heatwaves for 63 and 58 days in 2022, respectively, more than double the 1980-2022 average. From June 1 to October 8, 2022, water temperature peaks significantly coincided with expansive HABs and elevated chlorophyll a (Chl-a) concentration from 4.8 μg/L to 119.2 μg/L during the summer heatwaves. Our findings indicated that the reservoir became more HAB-prone during heatwave events, escalating the drinking water safety risk. These results emphasize the challenges faced by reservoir managers in dealing with climate-induced extreme heatwaves and underscore the urgency for heightened attention from water source management departments.

The occurrence and human health risk assessment of microcystins in diverse food matrixes during production

Globally, the presence of cyanotoxins in water supplies and food has been widely investigated for over a decade. Cyanotoxins are harmful metabolites produced by toxic cyanobacterial genera. These metabolites belong to diverse chemical classes, with a variety of physicochemical properties, chemical structures, and toxic activities. The present study seeks to investigate the occurrence of cyanotoxins in water supplies destined for food processing and assess the human health risk from exposure to cyanotoxins. To achieve this, a simple, sensitive, and reliable analytical method was developed for the determination of microcystins (MC-RR, MC-LR, MC-YR) in process water, raw maize meal, and cooked maize (porridge) at ppb (parts per billion) levels. These compounds were extracted using Solid Phase Extraction (SPE) with optimized parameters; thereafter, Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) was used for the rapid determination of the analytes selected for the present study. The method developed was applied to samples collected from the meal grinding station located in Mawoni village in South Africa; and was able to detect and quantify all the target cyanotoxins. MC-LR, MC-YR and MC-RR were detected at concentrations ranging from 10 to 11.2 μg/L, 9.1-9.4 μg/L, and 2.3-3.5 μg/L, in water samples, respectively. However, MC-YR was not detected in ground water sample. Moreover, MC-LR, MC-YR, and MC-RR concentrations in maize and porridge samples ranged between 9.2 and 11.2, 5.5-8.6, and 6.3-9.3 μg/kg dry weight, respectively. The hazard quotient index (HQi) levels found in the present study ranged between 2.2 - 8.4 and 0.11-8.9 for adults and children, respectively, representing potential risks to human health. Findings from LC-MS/MS reveal that cyanotoxins can be transferred from water to food during food processing using cyanotoxins contaminated water. Furthermore, the methods developed can be used by environmental and health agencies to strengthen the monitoring of cyanotoxins in water and food.

Microcystin Contamination in Irrigation Water and Health Risk

Microcystins (MCs), natural hepatotoxic compounds produced by cyanobacteria, pose significant risks to water quality, ecosystem stability, and the well-being of animals, plants, and humans when present in elevated concentrations. The escalating contamination of irrigation water with MCs presents a growing threat to terrestrial plants. The customary practice of irrigating crops from local water sources, including lakes and ponds hosting cyanobacterial blooms, serves as a primary conduit for transferring these toxins. Due to their high chemical stability and low molecular weight, MCs have the potential to accumulate in various parts of plants, thereby increasing health hazards for consumers of agricultural products, which serve as the foundation of the Earth's food chain. MCs can bioaccumulate, migrate, potentially biodegrade, and pose health hazards to humans within terrestrial food systems. This study highlights that MCs from irrigation water reservoirs can bioaccumulate and come into contact with plants, transferring into the food chain. Additionally, it investigates the natural mechanisms that organisms employ for conjugation and the microbial processes involved in MC degradation. To gain a comprehensive understanding of the role of MCs in the terrestrial food chain and to elucidate the specific health risks associated with consuming crops irrigated with water contaminated with these toxins, further research is necessary.

Microbial Diversity Impacts Non-Protein Amino Acid Production in Cyanobacterial Bloom Cultures Collected from Lake Winnipeg

Lake Winnipeg in Manitoba, Canada is heavily impacted by harmful algal blooms that contain non-protein amino acids (NPAAs) produced by cyanobacteria: N-(2-aminoethyl)glycine (AEG), β-aminomethyl-L-alanine (BAMA), β-N-methylamino-L-alanine (BMAA), and 2,4-diaminobutyric acid (DAB). Our objective was to investigate the impact of microbial diversity on NPAA production by cyanobacteria using semi-purified crude cyanobacterial cultures established from field samples collected by the Lake Winnipeg Research Consortium between 2016 and 2021. NPAAs were detected and quantified by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) using validated analytical methods, while Shannon and Simpson alpha diversity scores were determined from 16S rRNA metagenomic sequences. Alpha diversity in isolate cultures was significantly decreased compared to crude cyanobacterial cultures (p < 0.001), indicating successful semi-purification. BMAA and AEG concentrations were higher in crude compared to isolate cultures (p < 0.0001), and AEG concentrations were correlated to the alpha diversity in cultures (r = 0.554; p < 0.0001). BAMA concentrations were increased in isolate cultures (p < 0.05), while DAB concentrations were similar in crude and isolate cultures. These results demonstrate that microbial community complexity impacts NPAA production by cyanobacteria and related organisms.

Upstream nitrogen availability determines the Microcystis salt tolerance and influences microcystins release in brackish water

The occurrence of large Microcystis biomass in brackish waters is primarily caused by its downward transportation from the upstream freshwater lakes and reservoirs through rivers rather than due to in situ bloom formation. Factors that determine the survival of freshwater cyanobacteria in brackish waters have not been well investigated. Here, we studied the spatiotemporal variability of inorganic nitrogen in an upstream lake and conducted laboratory and in-situ experiments to assess the role of nitrogen availability on the salt tolerance of Microcystis and the release of microcystins. A series of field experiments were carried out during bloom seasons to evaluate the salt tolerance of natural Microcystis colonies. The salt tolerance threshold varied from 7 to 17 and showed a positive relationship with intracellular carbohydrate content and a negative relationship with nitrogen availability in water. In August when upstream nitrogen availability was lower, the Microcystis colonies could maintain their biomass even after a sudden increase in salinity from 4 to 10. Laboratory-cultivated Microcystis that accumulated higher carbohydrate content at lower nitrogen availability showed better cell survival at higher salinity. The sharp release of microcystins into the surrounding water occurred when salinity exceeded the salt tolerance threshold of the Microcystis. Thus, Microcystis with higher salt tolerance can accumulate more toxins in cells. The obtained results suggest that the cell survival and toxin concentration in brackish waters depend on the physiological properties of Microcystis formed in the upstream waters. Thus, the life history of Microcystis in upstream waters could have a significant impact on its salt tolerance in downstream brackish waters, where the ecological risk of the salt-tolerant Microcystis requires special and careful management in summer at low nitrogen availability.

Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach

Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencoder (HCVAE) is proposed as an efficient and accurate deep learning (DL) based bio-optical model. To demonstrate its usefulness in retrieving algal pigments, the HCVAE is applied to bloom-prone regions in Daecheong Lake, South Korea. By abstracting the similarity between highly related features using layer-wise clique-based latent-feature extraction, HCVAE reduces the computational loads in deriving outputs while preventing performance degradation. Graph-based clique-detection uses information theory-based criteria to group the related reflectance spectra. Consequently, six latent features were extracted from 79 spectral bands to consist of a multilevel hierarchy of HCVAE that can simultaneously estimate concentrations of chlorophyll-a (Chl-a) and phycocyanin (PC). Despite the parsimonious model architecture, the Chl-a and PC concentrations estimated by HCVAE closely agree with the measured concentrations, with test R2 values of 0.76 and 0.82, respectively. In addition, spatial distribution maps of algal pigments obtained from HCVAE using drone-borne reflectance successfully capture the blooming spots. Based on its multilevel hierarchical architecture, HCVAE can provide the importance of latent features along with their individual wavelengths using Shapley additive explanations. The most important latent features covered the spectral regions associated with both Chl-a and PC. The lightweight neural network DNNsel, which uses only the spectral bands of highest importance in latent-feature extraction, performed comparably to HCVAE. The study results demonstrate the utility of the multilevel hierarchical architecture as a comprehensive assessment model for near-real-time drone-borne sensing of HABs. Moreover, HCVAE is applicable to a wide range of environmental big data, as it can handle numerous sets of features.

Cyanopeptolins and Anabaenopeptins Are the Dominant Cyanopeptides from Planktothrix Strains Collected in Canadian Lakes

Common bloom-forming cyanobacteria produce complex strain-specific mixtures of secondary metabolites. The beneficial and toxic properties of these metabolite mixtures have attracted both research and public health interest. The advancement of mass spectrometry-based platforms and metabolomics data processing has accelerated the identification of new metabolites and feature dereplication from microbial sources. The objective of this study was to use metabolomics data processing to decipher the intracellular cyanopeptide diversity of six Planktothrix strains collected from Canadian lakes. Data-dependent acquisition experiments were used to collect a non-targeted high-resolution mass spectrometry dataset. Principal component analysis and factor loadings were used to visualize cyanopeptide variation between strains and identified features contributing to the observed variation. GNPS molecular networking was subsequently used to show the diversity of cyanopeptides produced by the Planktothrix strains. Each strain produced a unique mixture of cyanopeptides, and a total of 225 cyanopeptides were detected. Planktothrix sp. CPCC 735 produced the most (n = 68) cyanopeptides, and P. rubescens CPCC 732 produced the fewest (n = 27). Microcystins and anabaenopeptins were detected from all strains. Cyanopeptolins, microviridins and aeruginosins were detected from five, four and two strains, respectively. Cyanopeptolin (n = 80) and anabaenopeptin (n = 61) diversity was the greatest, whereas microcystins (n = 21) were the least diverse. Interestingly, three of the P. rubescens strains had different cyanopeptide profiles, despite being collected from the same lake at the same time. This study highlights the diversity of cyanopeptides produced by Planktothrix and further hints at the underestimated cyanopeptide diversity from subpopulations of chemotypic cyanobacteria in freshwater lakes.

Cyanobacteria and cyanotoxins in the environment and water intakes: Reports, diversity of congeners, detection by mass spectrometry and their impact on health

Cyanobacteria are aquatic microorganisms of high interest for research due to the production of secondary metabolites, among which the most popular are cyanotoxins, responsible for causing severe poisoning in humans and animals through ingestion or contact with contaminated water bodies. Monitoring the number of cyanobacteria in water and concentrations of secreted cyanotoxins with the aid of sensitive and reliable methods is considered the primary action for evaluating potentially toxic blooms. There is a great diversity of methods to detect and identify these types of micro contaminants in water, differing by the degree of sophistication and information provided. Mass Spectrometry stands out for its accuracy and sensitivity in identifying toxins, making it possible to identify and characterize toxins produced by individual species of cyanobacteria, in low quantities. In this review, we seek to update some information about cyanobacterial peptides, their effects on biological systems, and the importance of the main Mass Spectrometry methods used for detection, extraction, identification and monitoring of cyanotoxins.

Projected climate change impact on cyanobacterial bloom phenology in temperate rivers based on temperature dependency

Climate warming is linked to earlier onset and extended duration of cyanobacterial blooms in temperate rivers. This causes an unpredictable extent of harm to the functioning of the ecosystem and public health. We used Microcystis spp. cell density data monitored for seven years (2016-2022) in ten sites across four temperate rivers of the Republic of Korea to define the phenology of cyanobacterial blooms and elucidate the climatic effect on their pattern. The day of year marking the onset, peak, and end of Microcystis growth were estimated using a Weibull function, and linear mixed-effect models were employed to analyze their relationships with environmental variables. These models identified river-specific temperatures at the beginning and end dates of cyanobacterial blooms. Furthermore, the most realistic models were employed to project future Microcystis bloom phenology, considering downscaled and quantile-mapped regional air temperatures from a general circulation model. Daily minimum and daily maximum air temperatures (mintemp and maxtemp) primarily drove the timing of the beginning and end of the bloom, respectively. The models successfully captured the spatiotemporal variations of the beginning and end dates, with mintemp and maxtemp predicted to be 24℃ (R2 = 0.68) and 16℃ (R2 = 0.35), respectively. The beginning and end dates were projected to advance considerably in the future under the Representative Concentration Pathway 2.6, 4.5, and 8.5. The simulations suggested that the largest uncertainty lies in the timing of when the bloom ends, whereas the timing of when blooming begins has less variation. Our study highlights the dependency of cyanobacterial bloom phenology on temperatures and earlier and prolonged bloom development.

Non-linear impacts of harmful algae blooms on the coastal tourism economy

Harmful algae blooms (HABs) occur in water bodies throughout the globe and can have multi-faceted impacts on tourism. However, little is known of the magnitude of economic losses to the tourism sector as a result of HABs. There is limited understanding of the empirical relationships between HAB intensity and duration, and the effects of this phenomenon on the tourism sector. This study is based in the state of Florida, USA, a notable sun, sand, and sea destination in the western hemisphere, where blooms of a marine harmful algae are a recurrent threat to coastal tourism. The empirical framework is based on a month and county-level panel database that combines sales by tourism-related businesses with observations from the official HAB surveillance system of the state of Florida. We use time and space fixed-effects regressions to estimate the loss in tourism revenue associated with one additional day of red tide. Results indicate that impacts of HABs on tourism do not follow a linear pattern with increasing HAB concentrations, but rather appear to follow an inverted-U pattern. In other words, higher concentrations of the HAB organism do not necessarily imply higher economic losses, suggesting that the impacts of HABs on tourism are not driven solely by the biophysical element of cell density. Rather, these impacts appear to be mediated and amplified by human dimensions. The loss to tourism-related businesses due to the 2018 Florida red tide bloom was estimated to be $2.7 billion USD, which implies that HABs and their impact on tourism can be considered as a potential 'billion-dollar' disaster.

Microbiome analysis reveals Microcystis blooms endogenously seeded from benthos within wastewater maturation ponds

Toxigenic Microcystis blooms periodically disrupt the stabilization ponds of wastewater treatment plants (WWTPs). Dense proliferations of Microcystis cells within the surface waters (SWs) impede the water treatment process by reducing the treatment efficacy of the latent WWTP microbiome. Further, water quality is reduced when conventional treatment leads to Microcystis cell lysis and the release of intracellular microcystins into the water column. Recurrent seasonal Microcystis blooms cause significant financial burdens for the water industry and predicting their source is vital for bloom management strategies. We investigated the source of recurrent toxigenic Microcystis blooms at Australia's largest lagoon-based municipal WWTP in both sediment core (SC) and SW samples between 2018 and 2020. Bacterial community composition of the SC and SW samples according to 16S rRNA gene amplicon sequencing showed that Microcystis sp. was dominant within SW samples throughout the period and reached peak relative abundances (32%) during the summer. The same Microcystis Amplicon sequence variants were present within the SC and SW samples indicating a potential migratory population that transitions between the sediment water and SWs during bloom formation events. To investigate the potential of the sediment to act as a repository of viable Microcystis cells for recurrent bloom formation, a novel in-vitro bloom model was established featuring sediments and sterilized SW collected from the WWTP. Microcystin-producing Microcystis blooms were established through passive resuspension after 12 weeks of incubation. These results demonstrate the capacity of Microcystis to transition between the sediments and SWs in WWTPs, acting as a perennial inoculum for recurrent blooms.IMPORTANCECyanobacterial blooms are prevalent to wastewater treatment facilities owing to the stable, eutrophic conditions. Cyanobacterial proliferations can disrupt operational procedures through the blocking of filtration apparatus or altering the wastewater treatment plant (WWTP) microbiome, reducing treatment efficiency. Conventional wastewater treatment often results in the lysis of cyanobacterial cells and the release of intracellular toxins which pose a health risk to end users. This research identifies a potential seeding source of recurrent toxigenic cyanobacterial blooms within wastewater treatment facilities. Our results demonstrate the capacity of Microcystis to transition between the sediments and surface waters (SWs) of wastewater treatment ponds enabling water utilities to develop adequate monitoring and management strategies. Further, we developed a novel model to demonstrate benthic recruitment of toxigenic Microcystis under laboratory conditions facilitating future research into the genetic mechanisms behind bloom development.

Control of cyanobacterial bloom and purification of bloom-laden water by sequential electro-oxidation and electro-oxidation-coagulation

The outbreaks of cyanobacterial blooms have caused severe threat to aquatic ecosystem and public health. In this work, electrochemical technology with RuO2/IrO2/Ti (RIT) or/and Al as anode for cyanobacterial bloom control and simultaneous water purification were studied. Compared with RIT-Al and Al electrodes, RIT exhibited the highest effects on bloom algae inactivation and inhibition of algae regrowth. Live/dead analysis, SEM, intracellular reactive oxygen species (ROS) and antioxidant system activities revealed that RIT could disintegrate bloom flocs and damage embedded algal cells due to high intensity of oxidation. With the lysis of cyanobacterial bloom, high content of intracellular compounds containing organic carbon, nitrogen and phosphorus released, necessitating water quality restoration. In the subsequent water purification process, RIT-Al overtook RIT and Al in removal of organic and nutrient pollutants due to the complex effects of electro-oxidation, coagulation, co-precipitation, electro-nitrification and electro-denitrification. Therefore, sequential electro-oxidation and electro-oxidation-coagulation process was an effective method for control cyanobacteria bloom and simultaneous removal of DOM, microcystin-LR (MC-LR), nitrogen and phosphorus, which is a promising technology.

Magnetically recyclable Cu2+ doped Fe3O4@biochar for in-situ inactivation of Microcystis aeruginosa: Performance and reusability

Harmful cyanobacterial blooms in eutrophic water bodies have frequently occurred worldwide and become a major environmental concern. Therefore, it is imperative to develop a stable and efficient algaecide to solve this issue. In this study, our purpose was to investigate the efficacy and mechanism of a newly developed Cu2+ doped Fe3O4@Biochar magnetic composite (Cu-Mag-BC) in in-situ inactivation of Microcystis aeruginosa (M. aeruginosa). We successfully synthesized the Cu-Mag-BC by coating Cu2+ onto Fe3O4@Biochar. Cu-Mag-BC exhibited superparamagnetic behavior and was uniformly impregnated by Cu2+. Cu-Mag-BC (5 mg/L), rapidly inactivated chlorophyll-a (Chl-a) in M. aeruginosa with low Fe and Cu leaching, during which time the OD264 value and malondialdehyde (MDA) content increased, while the activities of superoxide dismutase (SOD) and catalase (CAT) first increased and then decreased, due to oxidative stress induced by over-generated reactive oxygen species (ROS). Quantitative results showed that ·O2- and ·OH were the main ROS species produced from Cu-Mag-BC. Inactivation efficiency was maintained at approximately 80 % after three consecutive runs and total Chl-a removal efficiency reached 2.84 g/g, indicating good reusability and stability. A possible inactivation mechanism is proposed; amino groups and adipose chain were the primary oxidation sites. Thus, Cu-Mag-BC shows potential as a candidate for simultaneously inactivating harmful cyanobacteria and preventing secondary pollution.

Effects of bifenthrin on microcrustaceans grazing behavior on a phytoplankton assemblage dominated by Cyanobacteria

Insecticides are widely used for pest control and frequently reach aquatic systems, imposing a risk to the biota. In this work, the effect of environmental concentrations of bifenthrin on the grazing capacity of Simocephalus vetulus (Cladocera) and Argyrodiaptomus falcifer (Copepoda) on phytoplankton was evaluated. Fifteen microcrustacean individuals and a natural phytoplankton assemblage dominated by Cyanobacteria were exposed during 46 h to three concentrations of bifenthrin (C0 0 μg L-1, C1 0.02 μg L-1, and C2 0.05 μg L-1). A significant decrease in both microcrustaceans grazing rates on total phytoplankton was observed in C2 compared to C0 and C1. The filtration rate (ml ind-1 h-1) of S. vetulus decreased significantly for the cyanobacteria Anabaenopsis arnoldii, Dolichospermum circinale, and Glaucospira sp. in C2 compared to C0 and C1. The ingestion rate (org ind-1 h-1) of A. falcifer decreased significantly in C1 and C2 compared to C0 only for A. arnoldii. Regarding phytoplankton morphological groups, the filtration rate of S. vetulus decreased in C1 and C2 compared to C0 for Colonies and Coenobiums in C2 concerning C0 and C1 for Filaments and in C2 compared to C0 for Silicified. For A. falcifer, the ingestion rate was reduced in C2 compared to C0 for Silicified, Flagellated, and Sessile. The results showed that bifenthrin affected both microcrustaceans grazing capacity on phytoplankton, especially at the highest insecticide concentration.

Cyanobacterial anatoxin-a does not induce in vitro developmental neurotoxicity, but changes gene expression patterns in co-exposure with all-trans retinoic acid

Cyanobacterial blooms are increasing in frequency and intensity globally, and impacting recreational waters as well as waters used for drinking water provisioning. They are sources of bioactive metabolites including retinoids and the neurotoxin anatoxin-a. Here, we investigated the effects of anatoxin-a on a differentiating in vitro human neural stem cell model previously characterised with retinoic acids. Effects on protein and gene expression upon exposure for 9 or 18 days to anatoxin-a alone or in co-exposure with all-trans retinoic acid were evaluated using a panel of neural and glial differentiation biomarkers. Anatoxin-a did not cause distinct developmental neurotoxicity alone, or in co-exposure with retinoic acid. However, in line with its excitotoxicity, in co-exposure with 200 nM all-trans retinoic acid it reduced the differentiation of acetylcholinergic neuron subtypes in the culture at 1000 nM (highest tested concentration). While this could have substantial functional implications for the developing nervous system, there is no indication for developmental neurotoxicity beyond its (excito-)toxicity to acetylcholinergic neurons, which only occurred in co-exposure to all-trans retinoic acid.

Aerosolized Cyanobacterial Harmful Algal Bloom Toxins: Microcystin Congeners Quantified in the Atmosphere

Cyanobacterial harmful algal blooms (cHABs) have the potential to adversely affect public health through the production of toxins such as microcystins, which consist of numerous molecularly distinct congeners. Microcystins have been observed in the atmosphere after emission from freshwater lakes, but little is known about the health effects of inhaling microcystins and the factors contributing to microcystin aerosolization. This study quantified total microcystin concentrations in water and aerosol samples collected around Grand Lake St. Marys (GLSM), Ohio. Microcystin concentrations in water samples collected on the same day ranged from 13 to 23 μg/L, dominated by the d-Asp3-MC-RR congener. In particulate matter <2.5 μm (PM2.5), microcystin concentrations up to 156 pg/m3 were detected; the microcystins were composed primarily of d-Asp3-MC-RR, with additional congeners (d-Asp3-MC-HtyR and d-Asp3-MC-LR) observed in a sample collected prior to a storm event. The PM size fraction containing the highest aerosolized MC concentration ranged from 0.44 to 2.5 μm. Analysis of total bacteria by qPCR targeting 16S rDNA revealed concentrations up to 9.4 × 104 gc/m3 in aerosol samples (≤3 μm), while a marker specific to cyanobacteria was not detected in any aerosol samples. Concentrations of aerosolized microcystins varied even when concentrations in water were relatively constant, demonstrating the importance of meteorological conditions (wind speed and direction) and aerosol generation mechanism(s) (wave breaking, spillway, and aeration systems) when evaluating inhalation exposure to microcystins and subsequent impacts on human health.

Effects of Harmful Cyanobacteria on Drinking Water Source Quality and Ecosystems

A seasonal plethora of cyanobacteria in the plankton community can have severe implications, not only for water ecosystems but also for the availability of treated water. The catchment of the Obrzyca River (a source of drinking water) is seasonally exposed to harmful cyanobacterial bloom. Previous studies (2008-2012; 2019) revealed that the most polluted water of the Obrzyca River was Uście, close to the outlet of Rudno Lake (at the sampling point). Therefore, the effect on this lake was specifically examined in this study. Sampling was performed from May to September at that site and from July to September 2020 at Rudno Lake. The conducted analysis revealed a massive growth of Aphanizomenon gracile, especially in Rudno Lake. The results showed not only the distinct impact of cyanobacterial bloom on phytoplankton biodiversity but also the presence of microcystins and other cyanopeptides in both sampling points. The maximal total concentration of microcystins (dmMC-RR, MC-RR, dmMC-LR, MC-LR, MC-LY, MC-YR) equaled 57.3 μg/L and the presence of cyanopeptides (aeruginosin, anabaenopeptin) was originally determined in Rudno Lake, August 2021. The presence of these toxins was highlighted in our results for the first time. The same samples from the lake were the most toxic in biotoxicological investigations using the planarian Dugesia tigrina. The performed bioassays proved that D. tigrina is a sensitive bioindicator for cyanotoxins. The physical and chemical indicators of water quality, i.e., color, temperature, total suspended solids, and total nitrogen and phosphorus, showed a significant correlation among each other and towards cyanobacterial abundance and microcystin concentrations.

One-Week-Ahead Prediction of Cyanobacterial Harmful Algal Blooms in Iowa Lakes

Cyanobacterial harmful algal blooms (CyanoHABs) pose serious risks to inland water resources. Despite advancements in our understanding of associated environmental factors and modeling efforts, predicting CyanoHABs remains challenging. Leveraging an integrated water quality data collection effort in Iowa lakes, this study aimed to identify factors associated with hazardous microcystin levels and develop one-week-ahead predictive classification models. Using water samples from 38 Iowa lakes collected between 2018 and 2021, feature selection was conducted considering both linear and nonlinear properties. Subsequently, we developed three model types (Neural Network, XGBoost, and Logistic Regression) with different sampling strategies using the nine selected variables (mcyA_M, TKN, % hay/pasture, pH, mcyA_M:16S, % developed, DOC, dewpoint temperature, and ortho-P). Evaluation metrics demonstrated the strong performance of the Neural Network with oversampling (ROC-AUC 0.940, accuracy 0.861, sensitivity 0.857, specificity 0.857, LR+ 5.993, and 1/LR- 5.993), as well as the XGBoost with downsampling (ROC-AUC 0.944, accuracy 0.831, sensitivity 0.928, specificity 0.833, LR+ 5.557, and 1/LR- 11.569). This study exhibited the intricacies of modeling with limited data and class imbalances, underscoring the importance of continuous monitoring and data collection to improve predictive accuracy. Also, the methodologies employed can serve as meaningful references for researchers tackling similar challenges in diverse environments.

Ecological implications of fish removal: Insights from gut-content analysis of roach (Rutilus rutilus) and European perch (Perca fluviatilis) in a eutrophic shallow lake

Large reductions in fish biomass are common both as a method of managing lake ecosystems by fish removals (biomanipulation) and as naturally occurring fish kills. To further understand how fish reductions change feeding patterns of fish, we studied the diets of small- to medium-sized roach (Rutilus rutilus) and European perch (Perca fluviatilis) on a monthly basis using gut-content analysis during an 18-month period before and after a whole-lake fish removal in a eutrophic shallow lake. Further, we performed in-depth analyses of zoobenthos communities of the profundal and littoral zones, as well as analysed the zooplankton community in the littoral and pelagic parts of the lake to estimate abundance and biomass of potential diet items. We found that, in general, there was a trend toward increased zoobenthivory in both species and among all-sized fish after fish removal, regardless of prior diet preference. Reduced piscivory among larger perch (>150 mm) and reduced zooplanktivory among smaller perch and roach (<150 mm) were also observed. Moreover, during a short period of high zooplankton biomass after fish removal, both perch and roach (all sizes) shifted their diet toward daphnids, which likely caused a decrease in daphnid population. We suggest that such change toward periodical zooplanktivory across fish species and size groups may lead to unexpectedly high top-down control by fish after lake restoration by fish removal.

Bioavailable iron concentrations regulate phytoplankton growth and bloom formation in low-nutrient lakes

The growth of phytoplankton in lakes is thought to be primarily controlled by macronutrient concentrations, but the availability of trace metal micronutrients, such as iron (Fe), are increasingly recognised as important regulators of lake primary production. This study evaluates the role of Fe in regulating phytoplankton growth in lakes of different nutrient status in New Zealand. The results of this unique year-long study, combining highly sensitive trace metal concentration analysis of waters and particulates with advanced trace metal bioavailability and speciation modelling, constrains thresholds for bioavailable Fe and colloidal Fe of 0.8 nmol·L-1 and 30 nmol·L-1, respectively, below which phytoplankton growth-limitation occurs. These thresholds specifically control diatom bloom formation and termination in lakes, thereby exerting a strong influence on freshwater carbon sequestration, given the dominance of diatoms in lake bloom assemblages. Importantly, potentially toxic cyanobacteria thrived only after events of bottom water anoxia, when additional dissolved Fe in concentrations ≥4 nmol·L-1 was released into the water column. These new thresholds for bioavailable and colloidal Fe offer the potential to manage micronutrient levels in lakes for the purpose of regulating algal bloom formation and carbon sequestration, while at the same time, suppressing the formation of harmful cyanobacterial blooms.

Concentration of total microcystins associates with nitrate and nitrite, and may disrupt the nitrogen cycle, in warm-monomictic lakes of the southcentral United States

Cyanobacterial blooms and the toxins they produce pose a growing threat worldwide. Mitigation of such events has primarily focused on phosphorus management and has largely neglected the role of nitrogen. Previous bloom research and proposed management strategies have primarily focused on temperate, dimictic lakes, and less on warm-monomictic systems like those at subtropical latitudes. The in-lake conditions, concentration of total microcystins, and microbial functioning of twenty warm-monomictic lakes in the southcentral United States were explored in the spring and summer of 2021. Our data revealed widespread microcystins in lakes across this region, some of which exceeded regulatory limits. Microcystins were higher in the spring compared to the summer, indicating that warm-monomictic lakes, even across a large range of precipitation, do not follow the trends of temperate dimictic lakes. Microcystins were found in surface waters and bottom waters well below the photic zone, reflecting the persistence of these toxins in the environment. Principal components analyses showed a strong association between microcystins, nitrate + nitrite, and Planktothrix relative abundance and transcriptional activity. Many systems exhibited stronger denitrification in the spring, perhaps contributing to the decreased toxin concentrations in the summer. Counter to most sampled lakes, one lake with the highest concentration of total microcystins indicated nitrogen cycle disruption, including inhibited denitrification. These findings are relevant to mitigating cyanobacterial blooms and toxin production in warm-monomictic systems, and suggests a need to consider nitrogen, and not solely phosphorus, in nutrient management discussions.

A Case Series of Potential Pediatric Cyanotoxin Exposures Associated with Harmful Algal Blooms in Northwest Ohio

Cyanobacterial harmful algal blooms (CyanoHABs) are increasing in prevalence and severity in the Great Lakes region, as well as both globally and locally. CyanoHABs have the potential to cause adverse effects on human health due to the production of cyanotoxins from cyanobacteria. Common routes of exposure include recreational exposure (swimming, skiing, and boating), ingestion, and aerosolization of contaminated water sources. Cyanotoxins have been shown to adversely affect several major organ systems contributing to hepatotoxicity, gastrointestinal distress, and pulmonary inflammation. We present three pediatric case reports that coincided with CyanoHABs exposure with a focus on presentation of illness, diagnostic work-up, and treatment of CyanoHAB-related illnesses. Potential cyanotoxin exposure occurred while swimming in the Maumee River and Maumee Bay of Lake Erie in Ohio during the summer months with confirmed CyanoHAB activity. Primary symptoms included generalized macular rash, fever, vomiting, diarrhea, and severe respiratory distress. Significant labs included leukocytosis and elevated C-reactive protein. All patients ultimately recovered with supportive care. Symptoms following potential cyanotoxin exposure coincide with multiple disease states representing an urgent need to develop specific diagnostic tests of exposure.

Important Role of Overland Flows and Tile Field Pathways in Nutrient Transport

Nitrogen and phosphorus pollution is of great concern to aquatic life and human well-being. While most of these nutrients are applied to the landscape, little is known about the complex interplay among nutrient applications, transport attenuation processes, and coastal loads. Here, we enhance and apply the Spatially Explicit Nutrient Source Estimate and Flux model (SENSEflux) to simulate the total annual nitrogen and phosphorus loads from the US Great Lakes Basin to the coastline, identify nutrient delivery hotspots, and estimate the relative contributions of different sources and pathways at a high resolution (120 m). In addition to in-stream uptake, the main novelty of this model is that SENSEflux explicitly describes nutrient attenuation through four distinct pathways that are seldom described jointly in other models: runoff from tile-drained agricultural fields, overland runoff, groundwater flow, and septic plumes within groundwater. Our analysis shows that agricultural sources are dominant for both total nitrogen (TN) (58%) and total phosphorus (TP) (46%) deliveries to the Great Lakes. In addition, this study reveals that the surface pathways (sum of overland flow and tile field drainage) dominate nutrient delivery, transporting 66% of the TN and 76% of the TP loads to the US Great Lakes coastline. Importantly, this study provides the first basin-wide estimates of both nonseptic groundwater (TN: 26%; TP: 5%) and septic-plume groundwater (TN: 4%; TP: 2%) deliveries of nutrients to the lakes. This work provides valuable information for environmental managers to target efforts to reduce nutrient loads to the Great Lakes, which could be transferred to other regions worldwide that are facing similar nutrient management challenges.

Recent Advances in Cyanotoxin Synthesis and Applications: A Comprehensive Review

Over the past few decades, nearly 300 known cyanotoxins and more than 2000 cyanobacterial secondary metabolites have been reported from the environment. Traditional studies have focused on the toxic cyanotoxins produced by harmful cyanobacteria, which pose a risk to both human beings and wildlife, causing acute and chronic poisoning, resulting in diarrhea, nerve paralysis, and proliferation of cancer cells. Actually, the biotechnological potential of cyanotoxins is underestimated, as increasing studies have demonstrated their roles as valuable products, including allelopathic agents, insecticides and biomedicines. To promote a comprehensive understanding of cyanotoxins, a critical review is in demand. This review aims to discuss the classifications; biosynthetic pathways, especially heterogenous production; and potential applications of cyanotoxins. In detail, we first discuss the representative cyanotoxins and their toxic effects, followed by an exploration of three representative biosynthetic pathways (non-ribosomal peptide synthetases, polyketide synthetases, and their combinations). In particular, advances toward the heterologous biosynthesis of cyanotoxins in vitro and in vivo are summarized and compared. Finally, we indicate the potential applications and solutions to bottlenecks for cyanotoxins. We believe that this review will promote a comprehensive understanding, synthetic biology studies, and potential applications of cyanotoxins in the future.

Immunotoxicity of cynobacterial toxin Microcystin-LR is mitigated by Quercitin and himalaya tonic Liv52

Microcystin-LR (MC-LR) has received worldwide concern for its hepatotoxicity with maximum acceptable daily intake of 0.0015 mg/L (1.5 μg/L) [Federal-Provinicial-Territorial-Committee-on-drinking-water-2002]. Comprehensive immunotoxicity data is still deficient with MC-LR. To curb the menace of MC-LR, Quercitin (QE), himalaya made hepatotonic Liv52 were studied. To investigate the immunotoxic properties of MC-LR, QE and Liv52, primary splenocyte cells prepared, cultured, and immunoproliferation assay with mitogens lipopolysaccharide (LPS) or concanavalin A, (Con A) was done for, immunophenotyping, cell cycle and apoptotic studies. In current study, we have divided the splenocytes into 4 groups, i.e., Group I: Normal saline, Group II: MC-LR (0.1 μM), Group III: MC-LR (0.1 μM) + QE (20 μM), and Group IV: MC-LR (0.1 μM) + Liv52 (25 μg/ml) and treated with maximum < CC50 concentration. MC-LR enhanced proliferation of Con A and LPS stirred splenocytes at 24 h, whereas QE and Liv52 both act as antimitogenic. With combined mixture of MC-LR + QE, a significant increase in proliferation compared to mitogen or MC-LR was observed. MC-LR down-regulated expression of CD19+, CD3e+, CD4+, CD8+, (1.05%), (18.9%), (8.9%), and (7.8%) respectively in comparison to Group I. Down-regulation of 10% and 28% is observed in CD19+ and CD4+ populations with MC-LR and QE. The Liv52 addition concealed MC-LR adverse properties in most effective way. MC-LR induced G1-phase significant declined cell cycle arrest at S phase (9.26%) and G2/M phase (26.31%) was observed. QE and Liv52 mask the activity of MC-LR. Further apoptotic study revealed that MC-LR treatment decreases late apoptotic cells compared to control with no significant change in live and early apoptotic cells. Although QE increased live cells and Liv52 significantly increased late apoptotic cells, these results suggest that a Collapse

Key Words

• Cynobacterial toxin
• FACS analysis
• Immunomodulation
• Immunophenotyping
• MC-LR

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MESH Headings

• Lipopolysaccharides
• Microcystins/toxicity
• Cell Cycle

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Affiliation(s)

Kriti Shrinet School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005, India; School of Biotechnology, IFTM University, Moradabad, Uttar Pradesh, 244102, India
Arvind Kumar School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, Uttar Pradesh, 221005, India.

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Determining the Spectral Requirements for Cyanobacteria Detection for the CyanoSat Hyperspectral Imager with Machine Learning

This study determines an optimal spectral configuration for the CyanoSat imager for the discrimination and retrieval of cyanobacterial pigments using a simulated dataset with machine learning (ML). A minimum viable spectral configuration with as few as three spectral bands enabled the determination of cyanobacterial pigments phycocyanin (PC) and chlorophyll-a (Chl-a) but may not be suitable for determining cyanobacteria composition. A spectral configuration with about nine ideally positioned spectral bands enabled estimation of the cyanobacteria-to-algae ratio (CAR) and pigment concentrations with almost the same accuracy as using all 300 spectral channels. A narrower spectral band full-width half-maximum (FWHM) did not provide improved performance compared to the nominal 12 nm configuration. In conclusion, continuous sampling of the visible spectrum is not a requirement for cyanobacterial detection, provided that a multi-spectral configuration with ideally positioned, narrow bands is used. The spectral configurations identified here could be used to guide the selection of bands for future ocean and water color radiometry sensors.

A Perspective on Removal of Cyanotoxins from Water Through Advanced Oxidation Processes

This perspective discusses the challenges associated with the removal of cyanotoxins from raw water sources for drinking water treatment and the emergence of sulfate radical-based advanced oxidation processes (SR-AOPs) as an effective treatment technique. The advantage of SR-AOPs is that they can be activated using a variety of methods, including heat, UV radiation, and transition metal catalysts, allowing for greater flexibility in treatment design and optimization. In addition, the byproducts of SR-AOPs are less harmful than those generated by •OH-AOPs, which reduces the risk of secondary contamination. SR-AOPs generate sulfate radicals (SO4 •-) that are highly selective to certain organic contaminants and have lower reactivity to background water constituents, resulting in higher efficiency and selectivity of the process. The presence of natural organic matter and transition metals in the natural water body increases the degradation efficiency of SR-AOPs for the cyanotoxins. The bromate formation is also suppressed when the water contaminated with cyanotoxins is treated with SR-AOPs.

Climate change amplifies the risk of potentially toxigenic cyanobacteria

Cyanobacterial blooms pose a significant threat to water security, with anthropogenic forcing being implicated as a key driver behind the recent upsurge and global expansion of cyanobacteria in modern times. The potential effects of land-use alterations and climate change can lead to complicated, less-predictable scenarios in cyanobacterial management, especially when forecasting cyanobacterial toxin risks. There is a growing need for further investigations into the specific stressors that stimulate cyanobacterial toxins, as well as resolving the uncertainty surrounding the historical or contemporary nature of cyanobacterial-associated risks. To address this gap, we employed a paleolimnological approach to reconstruct cyanobacterial abundance and microcystin-producing potential in temperate lakes situated along a human impact gradient. We identified breakpoints (i.e., points of abrupt change) in these time series and examined the impact of landscape and climatic properties on their occurrence. Our findings indicate that lakes subject to greater human influence exhibited an earlier onset of cyanobacterial biomass by 40 years compared to less-impacted lakes, with land-use change emerging as the dominant predictor. Moreover, microcystin-producing potential increased in both high- and low-impact lakes around the 1980s, with climate warming being the primary driver. Our findings chronicle the importance of climate change in increasing the risk of toxigenic cyanobacteria in freshwater resources.

Spatiotemporal variation in the water quality of Vembanad Lake, Kerala, India: a remote sensing approach

Water quality is one of the essential parameters of environmental monitoring; even a slight variation in its characteristics may significantly influence the ecosystem. The water quality of Vembanad Lake is affected by anthropogenic effects such as industrial effluents and tourism. The optical parameters representing water quality, such as diffuse attenuation (Kd), turbidity, suspended particulate matter (SPM), and chlorophyll-a (Chl-a), are considered in this study to evaluate the water quality of Vembanad Lake, Kerala, India. As this lake is regarded as of ecological importance by the Ramsar Convention and has faced severe concerns over recent years, there was a substantial change in the water quality during the lockdowns of the COVID-19 pandemic. This research is aimed at examining the change in water quality using optical data from Sentinel-2 satellites in the ACOLITE processing software from 2016 to 2021. The analyses showed a 2.5% decrease in the values of Kd, whereas SPM and turbidity show a reduction of about 4.3% from the year 2016 to 2021. The flood and the COVID lockdown had an impact on the improvement in the quality of water from 2018 to 2021. The findings indicated that the reduction in industrial activities and tourism had a more significant effect on the improvement in the water quality of the lake. There was no substantial change in the Chl-a until 2020, whereas an average decrease of 12% in Chl-a values was observed throughout 2021. This decrease can be attributed to the reduction in the lake's hydrological residence time (HRT). Thus, these findings will be a valuable reference to help the government and non-government organizations (NGO) during strategic planning.

Geographic Variability, Seasonality, and Increase in ASPCA Animal Poison Control Center Harmful Blue-Green Algae Calls-United States and Canada, 2010-2022

Harmful cyanobacteria (blue-green algae) exposures can cause illness or death in humans and animals. We characterized American Society for the Prevention of Cruelty to Animals (ASPCA) Animal Poison Control Center (APCC) harmful blue-green algae (HBGA) call data, compared it to a measure of harmful algal bloom public awareness, and considered its suitability as a public health information source. ASPCA APCC dog and cat "HBGA exposure" calls made 1 January 2010-31 December 2022 were included. We calculated annual HBGA call percentages and described calls (species, month, origin, exposure route). We characterized public awareness by quantifying Nexis Uni® (LexisNexis Academic; New York, NY, USA)-indexed news publications (2010-2022) pertaining to "harmful algal bloom(s)". Call percentage increased annually, from 0.005% (2010) to 0.070% (2022). Of 999 HBGA calls, 99.4% (n = 993) were dog exposures. Over 65% (n = 655) of calls were made July-September, largely from the New England (n = 154 (15.4%)) and Pacific (n = 129 (12.9.%)) geographic divisions. Oral and dermal exposures predominated (n = 956 (95.7%)). Harmful algal bloom news publications increased overall, peaking in 2019 (n = 1834). Higher call volumes in summer and in the New England and Pacific geographic divisions drove HBGA call increases; public awareness might have contributed. Dogs and humans have similar exposure routes. ASPCA APCC HBGA call data could serve as a public health information source.

Fuzzy-based global water quality assessment and water quality cells identification using satellite data

The water environmental impact assessment and management programs increasingly rely on accurate and quantitative estimates of water quality parameters through remote sensing, owing to the limitation of the time-consuming field-based approaches. Numerous studies have utilised the remote-derived water-quality products and existing water quality index WQI models, but they are typically site-specific and yield significant errors for the accurate assessment and monitoring of coastal and inland water bodies. This study presents a generalized WQI model that incorporates a flexible number of parameters, simplifying them to produce comprehensive water quality index values with the fuzzy logic approach. To derive these index values, three major water quality parameters such as Chl, TSS and aCDOM443 were estimated using new remote-sensing models, and the corresponding indices Trophic State Index (TSI), Total Suspended Solids Index (TSSI) and CDOM Index (CI) were produced by a generalized index model. Finally, WQI products were derived based on the Mamdani-based Fuzzy Inference System (FIS) and individual contribution of the water quality parameters to WQI was analysed to establish 'Water Quality Cells' WQcells, which are represented by the dominant WQ parameter. The new models were tested on MODIS-Aqua and Sentinel-3 OLCI data in different regional and global oceanic waters. Further, a time series analysis was performed in regional coastal oceanic waters (along the Indian coast) to study the seasonal variations of individual water quality parameters and WQI over the period from 2011 to 2020. The results demonstrated that the FIS is efficient in handling the parameters with varying units and their relative importance. The water quality cells were identified in the bloom-dominated (Arabian Sea), TSS-dominated (Point Calimere, India and Yangtze River estuary, China) and CDOM-dominated (South Carolina coast, USA) regions. The time series analysis revealed that the water quality of the Indian coast exhibits cyclic seasonal variations due to the annual occurrence of the south-west and north-east monsoons. These results are critical for monitoring and assessing the quality of surface waters in coastal and inland environments and enabling water resources managers to formulate and implement management plans for a variety of water bodies cost-effectively.

Predicting water quality variability in a Mediterranean hypereutrophic monomictic reservoir using Sentinel 2 MSI: the importance of considering model functional form

Anthropogenic eutrophication is a global environmental problem threatening the ecological functions of many inland freshwaters and diminishing their abilities to meet their designated uses. Water authorities worldwide are being pressed to improve their abilities to monitor, predict, and manage the incidence of harmful algal blooms (HABs). While most water quality management decisions are still based on conventional monitoring programs that lack the needed spatio-temporal resolution for effective lake/reservoir management, recent advances in remote sensing are providing new opportunities towards better understanding water quality variability in these important freshwater systems. This study assessed the potential of using the Sentinel 2 Multispectral Instrument to predict and assess the spatio-temporal variability in the water quality of the Qaraoun Reservoir, a poorly monitored Mediterranean hypereutrophic monomictic reservoir that is subject to extensive periods of HABs. The work first evaluated the ability to transfer and recalibrate previously developed reservoir-specific Landsat 7 and 8 water quality models when used with Sentinel 2 data. The results showed poor transferability between Landsat and Sentinel 2, with most models experiencing a significant drop in their predictive skill even after recalibration. Sentinel 2 models were then developed for the reservoir based on 153 water quality samples collected over 2 years. The models explored different functional forms, including multiple linear regressions (MLR), multivariate adaptive regression splines (MARS), random forests (RF), and support vector regressions (SVR). The results showed that the RF models outperformed their MLR, MARS, and SVR counterparts with regard to predicting chlorophyll-a, total suspended solids, Secchi disk depth, and phycocyanin. The coefficient of determination (R2) for the RF models varied between 85% for TSS up to 95% for SDD. Moreover, the study explored the potential of quantifying cyanotoxin concentrations indirectly from the Sentinel 2 MSI imagery by benefiting from the strong relationship between cyanotoxin levels and chlorophyll-a concentrations.