Strategies for monitoring and managing mass populations of toxic cyanobacteria in recreational waters: a multi-interdisciplinary approach

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.

A novel cyanolytic bacterium, Pseudomonas fluorescens BG-E as a potential biological control agent for freshwater bloom-forming cyanobacteria Pseudanabaena spp

The majority of bacterial antagonists identified to date are active against Microcystis. Therefore, this study aimed to isolate and characterize novel cyanolytic bacterial strains antagonistic against bloom-forming filamentous cyanobacteria. The bacterial strain BG-E isolated from the Bandagiriya Wewa in Sri Lanka was identified as Pseudomonas fluorescens (MZ007859) based on the 16S rRNA gene sequencing. BG-E showed 82% and 73% cyanolytic activity (CA) against Pseudanabaena sp. LW2 (MW288948) and Pseudanabaena lonchoides LW1 (MW288940), respectively, after 10 days of inoculation. The light microscopic images affirmed the complete disintegration in the filamentous structures of the tested Pseudanabaena species. The bacterial cell density of 15% v/v showed the CA with 95% and 89% cell lysis, respectively, in P. lonchoides and Pseudanabaena sp. LW2. Moreover, the results showed that >50% CA could be achieved by 0.100 and 1.00 (OD₇₃₀ ) cell densities for these same species. The highest CA of the cell-free supernatant of BG-E against P. lonchoides and bacterial culture against Pseudanabaena sp. LW2 illustrated the species-specific mode of action of BG-E. Although BG-E efficiently lysed the tested cyanobacterial species, the results of the MC-biodegradation assay confirmed its inability to degrade MC-LR cyanotoxin. Further, the BG-E strain lacks the mlrABCD gene cluster which is known to be responsible for the enzymatic degradation of MCs. The overall findings highlighted the applicability of P. fluorescens BG-E as a biological controlling agent to terminate blooms of freshwater filamentous cyanobacteria genus Pseudanabaena. The incorporation of cyanotoxin-degrading heterotrophic bacteria is recommended as a means of controlling toxic Pseudanabaena blooms.

Comprehensive insights into the occurrence and toxicological issues of nodularins

The occurrence of cyanobacterial toxins is being increasingly reported. Nodularins (NODs) are one of the cyanotoxins group mainly produced by Nodularia spumigena throughout the world. NODs may exert adverse effects on animal and human health, and NOD-R variant is the most widely investigated. However, research focused on them is still limited. In order to understand the realistic risk well, the aim of this review is to compile the available information in the scientific literature regarding NODs, including their sources, distribution, structural characteristics, physicochemical properties, biosynthesis and degradation, adverse effects in vitro and vivo, and toxicokinetics. More data is urgently needed to integrate the cumulative or synergistic effects of NODs on different species and various cells to better understand, anticipate and aggressively manage their potential toxicity after both short- and long-term exposure in ecosystem, and to minimize or prevent the adverse effects on human health, environment and the economy.

A risk assessment method for remote sensing of cyanobacterial blooms in inland waters

The widespread occurrence of Cyanobacterial blooms (CABs) in inland waters is a typical and severe challenge for water resources management and environment protection. An accurate and spatially continuous risk assessment of CABs is critical for prediction and preparedness in advance. In this study, a multivariate integrated risk assessment (MIRA) method of CABs in inland waters was proposed. MIRA was simplified with the trophic levels, cyanobacterial and other aquatic plant condition using remote sensing indexes, including the Trophic State Index (TSI), Floating Algae Index (FAI) and Cyanobacteria and Macrophytes Index (CMI). First, the dates of risk assessment were carefully selected based on TSI. Then, we obtained the trophic levels, cyanobacterial, and other aquatic plant condition of water using TSI, CMI and FAI on the selected date, and further scored them pixel by pixel to quantify the risk value. Finally, the risk of CABs in water was accurately assessed based on the pixel risk value. Based on Landsat 8 OLI dataset, MIRA was executed and validated in three different lakes of Wuhan urban agglomeration (WUA) with different trophic states. The results demonstrated that the risk of CABs in Lake LongGan was overall higher than that in Lake LiangZi and Lake FuTou. And the risk of CABs in the east part of Lake LongGan was higher than the other parts. Seasonally, the risk level ranking in Lake LiangZi was the highest in summer, while lowest in winter. However, the seasonal risk ranking was spring, summer, autumn, and winter in Lake LongGan. Based on the comparisons with monthly water quality classification data and results of the existing study, including trophic level, ecology risk, and algal extent, the MIRA method was valuable for accurate and spatially continuous identifying the risk of CABs in inland waters with potential eutrophication trends.

Understanding the preferences of water users in a context of cyanobacterial blooms in Quebec

Algal blooms, whether they are harmful or more akin to a nuisance, do pose negative impacts on human well-being. In the province of Quebec, excessive phosphorus that contributes to the problem of cyanobacterial blooms comes mainly from non-point sources. Limited regulation on the management of this nutrient leads to its strong accumulation in soils and, combined to climate change effects, contributes to increasing the magnitude of the effects of algal blooms on humans and the environment. The presence of cyanobacteria in water has impacts on its colour, texture and odour, in addition to posing threats to the health of recreationists, as some cyanobacteria are known to release toxins during blooms. This research focuses on studying the impacts of algal bloom events on recreationists and people living close to affected waterbodies. More specifically, we explore the preferences of individuals for different ecosystem services (ES), mainly cultural ES, provided by waterbodies (i.e., recreational activities, aesthetic aspects, and ecological health). We also estimate the average willingness to pay, financed through an increase in municipal taxation, for mechanisms that would allow the resolution of this issue. To achieve these objectives, we use a choice experiment approach, enclosed in a questionnaire that was carried out in person to 252 people. Conditional logit with and without interactions, and a random parameter logit (mixed logit) are alternatively used. Results show that individuals value first their ability to perform recreational activities, followed by the ecological health of waterbodies, and the aesthetic aspects (i.e., odour and visual aspects). Interestingly, the fact that people reported taking part in fishing activities influenced the way they prioritized ES in the choice modelling exercises. Based on the most robust model, we estimate the average willingness to pay at CA$353/household per year to fund a suite of solutions aimed at improving overall water quality.

Autonomous In Situ Measurements of Noncontaminant Water Quality Indicators and Sample Collection with a UAV

The objective of this research was to conduct in situ measurements of electrical conductivity (EC), pH, dissolved oxygen (DO), and temperature, and collect water samples simultaneously at different depths using an unmanned aerial vehicle (UAV). The UAV system consists of a hexacopter, water sampling cartridges (WSC), and a sensor node. Payload capacity and endurance of the UAV were determined using an indoor test station. The UAV was able to produce 106 N of thrust for 10 min with 6.3 kg of total takeoff weight. The thrust-to-weight ratio of the UAV was 2.5 at 50% throttle. The decision for activating the water sampling cartridges and sensor node was made autonomously from an onboard microcontroller. System functions were verified at 0.5 m and 3.0 m depths in 6 locations over a 1.1 ha agricultural pond. Average measurements of EC, pH, DO, and temperature at 0.5 m depth were 42 µS/cm, 5.6, 8.2 mg/L, and 31 °C, while the measurements at 3 m depth were 80 µS/cm, 5.3, 5.34 mg/L, and 24 °C, respectively. The UAV-assisted autonomous water sampling system (UASS) successfully activated the WSC at each sampling location. The UASS would reduce the duration of water quality assessment and help practitioners and researchers to conduct observations with lower operational costs. The developed system would be useful for sampling and monitoring of water reservoirs, lakes, rivers, and ponds periodically or after natural disasters.

Design of Amphibious Vehicle for Unmanned Mission in Water Quality Monitoring Using Internet of Things

Unmanned aerial vehicles (UAVs) have gained significant attention in recent times due to their suitability for a wide variety of civil, military, and societal missions. Development of an unmanned amphibious vehicle integrating the features of a multi-rotor UAV and a hovercraft is the focus of the present study. Components and subsystems of the amphibious vehicle are developed with due consideration for aerodynamic, structural, and environmental aspects. Finite element analysis (FEA) on static thrust conditions and skirt pressure are performed to evaluate the strength of the structure. For diverse wind conditions and angles of attack (AOA), computational fluid dynamic (CFD) analysis is carried out to assess the effect of drag and suitable design modification is suggested. A prototype is built with a 7 kg payload capacity and successfully tested for stable operations in flight and water-borne modes. Internet of things (IoT) based water quality measurement is performed in a typical lake and water quality is measured using pH, dissolved oxygen (DO), turbidity, and electrical conductivity (EC) sensors. The developed vehicle is expected to meet functional requirements of disaster missions catering to the water quality monitoring of large water bodies.

In Situ Water Quality Measurements Using an Unmanned Aerial Vehicle (UAV) System

An unmanned aerial vehicle-assisted water quality measurement system (UAMS) was developed for in situ surface water quality measurement. A custom-built hexacopter was equipped with an open-source electronic sensors platform to measure the temperature, electrical conductivity (EC), dissolved oxygen (DO), and pH of water. Electronic components of the system were coated with a water-resistant film, and the hexacopter was assembled with flotation equipment. The measurements were made at thirteen sampling waypoints within a 1.1 ha agricultural pond. Measurements made by an open-source multiprobe meter (OSMM) attached to the unmanned aerial vehicle (UAV) were compared to the measurements made by a commercial multiprobe meter (CMM). Percent differences between the OSMM and CMM measurements for DO, EC, pH, and temperature were 2.1 %, 3.43 %, 3.76 %, and <1.0 %, respectively. The collected water quality data was used to interpret the spatial distribution of measurements in the pond. The UAMS successfully made semiautonomous in situ water quality measurements from predetermined waypoints. Water quality maps showed homogeneous distribution of measured constituents across the pond. The concept presented in this paper can be applied to the monitoring of water quality in larger surface waterbodies.

Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, Korea

Understanding harmful algal blooms is imperative to protect aquatic ecosystems and human health. This study describes the spatial and temporal distributions of cyanobacterial blooms to identify the relations between blooms and environmental factors in the Baekje Reservoir. Two-year cyanobacterial cell data at one fixed station and four remotely sensed distributions of phycocyanin (PC) concentrations based on hyperspectral images (HSIs) were used to describe the relation between the spatial and temporal variations in the blooms and the affecting factors. An artificial neural network model and a three-dimensional hydrodynamic model were implemented to estimate the PC concentrations using remotely sensed HSIs and simulate the hydrodynamics, respectively. The statistical test results showed that the variations in the cyanobacterial biomass depended significantly on variations in the water temperature (slope = 0.13, p-value < 0.01), total nitrogen (slope = -0.487, p-value < 0.01), and total phosphorus (slope = 20.7, p-value < 0.05), whereas the variation in the biomass was moderately dependent on the variation in the outflow (slope = -0.0097, p-value = 0.065). Water temperature was the main factor affecting variations in the PC concentrations for the three months from August to October and was significantly different for the three months (p-value < 0.01). Hydrodynamic parameters also had a partial effect on the variations in the PC concentrations in those three months. Overall, this study helps to describe spatial and temporal variations in cyanobacterial blooms and identify the factors affecting the variation in the blooms. This study may play an important role as a basis for developing strategies to reduce bloom frequency and severity.

MODIS observations of cyanobacterial risks in a eutrophic lake: Implications for long-term safety evaluation in drinking-water source

The occurrence and related risks from cyanobacterial blooms have increased world-wide over the past 40 years. Information on the abundance and distribution of cyanobacteria is fundamental to support risk assessment and management activities. In the present study, an approach based on Empirical Orthogonal Function (EOF) analysis was used to estimate the concentrations of chlorophyll a (Chla) and the cyanobacterial biomarker pigment phycocyanin (PC) using data from the MODerate resolution Imaging Spectroradiometer (MODIS) in Lake Chaohu (China's fifth largest freshwater lake). The approach was developed and tested using fourteen years (2000-2014) of MODIS images, which showed significant spatial and temporal variability of the PC:Chla ratio, an indicator of cyanobacterial dominance. The results had unbiased RMS uncertainties of <60% for Chla ranging between 10 and 300 μg/L, and unbiased RMS uncertainties of <65% for PC between 10 and 500 μg/L. Further analysis showed the importance of nutrient and climate conditions for this dominance. Low TN:TP ratios (<29:1) and elevated temperatures were found to influence the seasonal shift of phytoplankton community. The resultant MODIS Chla and PC products were then used for cyanobacterial risk mapping with a decision tree classification model. The resulting Water Quality Decision Matrix (WQDM) was designed to assist authorities in the identification of possible intake areas, as well as specific months when higher frequency monitoring and more intense water treatment would be required if the location of the present intake area remained the same. Remote sensing cyanobacterial risk mapping provides a new tool for reservoir and lake management programs.

Quantum Dot-Based Molecularly Imprinted Polymers on Three-Dimensional Origami Paper Microfluidic Chip for Fluorescence Detection of Phycocyanin

In this work, we developed a novel strategy using fluorescent quantum dots (QDs) combined with molecularly imprinted polymers (MIPs) on three-dimensional (3D) origami paper-based microfluidic devices for specific recognition and sensitive detection of phycocyanin. This method can realize the liquid phase of QDs@MIPs being transferred to the solid-phase paper base and achieve easy portability for the analysis. Under optimal conditions, we successfully demonstrated the proposed paper@QDs@MIPs 3D microfluidic chip for the sensitive and selective detection of phycocyanin protein target in a simple and robust manner. Our results revealed that the method exhibited a dynamic response to phycocyanin in the range of 10-50 mg/L with a limit of detection of 2 mg/L. Importantly, this device could provide quantitative information very conveniently and show great potential to be further extended to the detection of other proteins or biomarkers for environmental and food safety research.

Bloom Dynamics of Cyanobacteria and Their Toxins: Environmental Health Impacts and Mitigation Strategies

Cyanobacteria are ecologically one of the most prolific groups of phototrophic prokaryotes in both marine and freshwater habitats. Both the beneficial and detrimental aspects of cyanobacteria are of considerable significance. They are important primary producers as well as an immense source of several secondary products, including an array of toxic compounds known as cyanotoxins. Abundant growth of cyanobacteria in freshwater, estuarine, and coastal ecosystems due to increased anthropogenic eutrophication and global climate change has created serious concern toward harmful bloom formation and surface water contamination all over the world. Cyanobacterial blooms and the accumulation of several cyanotoxins in water bodies pose severe ecological consequences with high risk to aquatic organisms and global public health. The proper management for mitigating the worldwide incidence of toxic cyanobacterial blooms is crucial for maintenance and sustainable development of functional ecosystems. Here, we emphasize the emerging information on the cyanobacterial bloom dynamics, toxicology of major groups of cyanotoxins, as well as a perspective and integrative approach to their management.

Early physiological and biochemical responses of rice seedlings to low concentration of microcystin-LR

Microcystin-leucine and arginine (microcystin-LR) is a cyanotoxin produced by cyanobacteria like Microcystis aeruginosa, and it's considered a threat to water quality, agriculture, and human health. Rice (Oryza sativa) is a plant of great importance in human food consumption and economy, with extensive use around the world. It is therefore important to assess the possible effects of using water contaminated with microcystin-LR to irrigate rice crops, in order to ensure a safe, high quality product to consumers. In this study, 12 and 20-day-old plants were exposed during 2 or 7 days to a M. aeruginosa extract containing environmentally relevant microcystin-LR concentrations, 0.26-78 μg/L. Fresh and dry weight of roots and leaves, chlorophyll fluorescence, glutathione S-transferase and glutathione peroxidase activities, and protein identification by mass spectrometry through two-dimensional gel electrophoresis from root and leaf tissues, were evaluated in order to gauge the plant's physiological condition and biochemical response after toxin exposure. Results obtained from plant biomass, chlorophyll fluorescence, and enzyme activity assays showed no significant differences between control and treatment groups. However, proteomics data indicates that plants respond to M. aeruginosa extract containing environmentally relevant microcystin-LR concentrations by changing their metabolism, responding differently to different toxin concentrations. Biological processes most affected were related to protein folding and stress response, protein biosynthesis, cell signalling and gene expression regulation, and energy and carbohydrate metabolism which may denote a toxic effect induced by M. aeruginosa extract and microcystin-LR. The implications of the metabolic alterations in plant physiology and growth require further elucidation.

Phormidium autumnale growth and anatoxin-a production under iron and copper stress

Studies on planktonic cyanobacteria have shown variability in cyanotoxin production, in response to changes in growth phase and environmental factors. Few studies have investigated cyanotoxin regulation in benthic mat-forming species, despite increasing reports on poisoning events caused by ingestion of these organisms. In this study, a method was developed to investigate changes in cyanotoxin quota in liquid cultures of benthic mat-forming cyanobacteria. Iron and copper are important in cellular processes and are well known to affect growth and selected metabolite production in cyanobacteria and algae. The effect of iron (40–4000 μg L⁻¹) and copper (2.5–250 μg L⁻¹) on growth and anatoxin-a quota in Phormidium autumnale was investigated in batch culture. These concentrations were chosen to span those found in freshwater, as well as those previously reported to be toxic to cyanobacteria. Anatoxin-a concentrations varied throughout the growth curve, with a maximum quota of between 0.49 and 0.55 pg cell⁻¹ measured within the first two weeks of growth. Growth rates were significantly affected by copper and iron concentrations (P < 0.0001); however, no statistically significant difference between anatoxin-a quota maxima was observed. When the iron concentrations were 800 and 4000 μg L⁻¹, the P.autumnale cultures did not firmly attach to the substratum. At 250 μg L⁻¹ copper or either 40 or 4000 μg L⁻¹ iron, growth was suppressed.

Monitoring approaches for a toxic cyanobacterial bloom

Cyanobacterial blooms, dominated by Microcystis sp. and associated microcystin variants, have been implicated in illnesses of humans and animals. Little is known regarding the formation of blooms and the presence of cyanotoxin variants in water bodies. Furthermore, the role played by ecological parameters, in regulating Microcystis blooms is complicate and diverse. Local authorities responsible for water management are often faced with the challenging task of dealing with cyanobacterial blooms. Therefore, the development of suitable monitoring approaches to characterize cyanobacterial blooms is an important goal. Currently, various biological, biochemical and physicochemical methods/approaches are being used to monitor cyanobacterial blooms and detect microcystins in freshwater bodies. Because these methods can vary as to the information they provide, no single approach seemed to be sufficient to accurately monitor blooms. For example, immunosensors are more suited for monitoring the presence of toxins in clear water bodies while molecular methods are more suited to detect potentially toxic strains. Thus, monitoring approaches should be tailored for specific water bodies using methods based on economic feasibility, speed, sensitivity and field applicability. This review critically evaluates monitoring approaches that are applicable to cyanobacterial blooms, especially those that focus on the presence of Microcystis, in freshwater bodies. Further, they were characterized and ranked according to their cost, speed, sensitivity and selectivity. Suggested improvements were offered as well as future research endeavors to accommodate anticipated environmental changes.

Is exposure to cyanobacteria an environmental risk factor for amyotrophic lateral sclerosis and other neurodegenerative diseases?

There is a broad scientific consensus that amyotrophic lateral sclerosis (ALS) is caused by gene-environment interactions. Mutations in genes underlying familial ALS (fALS) have been discovered in only 5-10% of the total population of ALS patients. Relatively little attention has been paid to environmental and lifestyle factors that may trigger the cascade of motor neuron death leading to the syndrome of ALS, although exposure to chemicals including lead and pesticides, and to agricultural environments, smoking, certain sports, and trauma have all been identified with an increased risk of ALS. There is a need for research to quantify the relative roles of each of the identified risk factors for ALS. Recent evidence has strengthened the theory that chronic environmental exposure to the neurotoxic amino acid β-N-methylamino-L-alanine (BMAA) produced by cyanobacteria may be an environmental risk factor for ALS. Here we describe methods that may be used to assess exposure to cyanobacteria, and hence potentially to BMAA, namely an epidemiologic questionnaire and direct and indirect methods for estimating the cyanobacterial load in ecosystems. Rigorous epidemiologic studies could determine the risks associated with exposure to cyanobacteria, and if combined with genetic analysis of ALS cases and controls could reveal etiologically important gene-environment interactions in genetically vulnerable individuals.