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Advances in Detecting, Monitoring, Predicting, Managing and Controlling Harmful Algal...
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Advances in Detecting, Monitoring, Predicting, Managing and Controlling Harmful Algal Blooms

A special issue of Toxins (ISSN 2072-6651). This special issue belongs to the section "Marine and Freshwater Toxins".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 5690

Editor

Dr. Chenlin Hu

E-Mail Website
Guest Editor
College of Pharmacy, University of Houston, Houston, TX 77204, USA
Interests: public health microbiology; antimicrobial analysis and discovery; freshwater algal blooms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Harmful freshwater algal blooms have become a major environmental and public health issue worldwide. Freshwater cyanobacterial blooms can produce toxic substances (also known as cyanotoxins) that seriously threaten the lives of humans and animals. With global climate warming and anthropogenic eutrophication increasing, the intensity, duration, and magnitude of harmful algal blooms present an escalating trend in the water bodies around the world. So far, substantial efforts have been made to understand the nature, causes, and health impacts of cyanotoxin and harmful algal blooms. These efforts constitute the growing endeavor to guide the development of technologies to detect cyanotoxins and harmful cyanobacteria, and to monitor, forecast, control, and manage harmful algal blooms.

To highlight recent advances in studying freshwater algal blooms, this Special Issue covers a broad spectrum of cyanobacterial bloom research topics, from the nature and ecology of cyanotoxin and algal bloom, analytical technologies, causes, and health impacts, to monitoring, forecasting, managing, and controlling algal blooms, organized as follows:

  1. Analytical technologies (immunoassay, chromatography-based methods, etc.) for cyanotoxins (e.g., microcystin, anatoxin-a) and toxigenic cyanobacteria (e.g., microcystin-producing cyanobacteria);
  2. Ecology of cyanotoxins and cyanobacteria;
  3. Causes of cyanobacterial blooms;
  4. Health effects of cyanobacterial blooms;
  5. Monitoring cyanobacterial blooms using satellite remote monitoring technologies;
  6. Forecasting cyanobacterial blooms with various models (including artificial intelligence technology);
  7. Managing and controlling cyanotoxins and harmful algal blooms using various chemical, physical, and biological measures.

Dr. Chenlin Hu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Toxins is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cyanobacteria
  • algal bloom
  • cyanotoxin
  • cause detecting
  • monitoring
  • predicting
  • managing
  • controlling

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Published Papers (4 papers)

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Research

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17 pages, 3432 KB  
Article
Predicting Algal Bloom Dynamics in Drinking Water Reservoirs Using High-Frequency In Situ Data and Machine Learning
by Jiangbin Wang, Min Jiang, Shuhua Wang, Zixin Wang, Yikun Cui, Ying Feng, Shanshan Zhang, Mingjiang Cai and Yanping Zhong
Toxins 2026, 18(5), 203; https://doi.org/10.3390/toxins18050203 - 28 Apr 2026
Viewed by 702
Abstract
Algal proliferation in subtropical drinking water reservoirs has become increasingly severe, and developing a reliable prediction for algal abundance through high-frequency in situ data is essential for early risk warning and effective management. This study analyzed the interannual variations in algal abundance in [...] Read more.
Algal proliferation in subtropical drinking water reservoirs has become increasingly severe, and developing a reliable prediction for algal abundance through high-frequency in situ data is essential for early risk warning and effective management. This study analyzed the interannual variations in algal abundance in the Shanmei (SM) Reservoir, located in Quanzhou City, Fujian Province, China, based on the high-frequency data between 2020 and 2025, and forecasted algal abundance 24 h ahead via the optimized Transformer model. Results revealed that the SM reservoir exhibited seasonal variability in environmental factors, with persistently elevated pH during spring and summer, ranging from 7.12 to 9.66, and relatively high total nitrogen concentrations, ranging from 1.17 to 2.28 mg/L. Overall, algal abundance increased throughout the study period, and the annual average algal abundance in 2025 was 8.18 × 106 cells/L, which was twice that in 2021. Model comparisons revealed that the optimized Transformer model exhibited the highest performance in terms of R2 = 0.88 when predicting the next hour using 12 days of data. Feature importance analysis based on SHapley Additive exPlanations (SHAPs) revealed that the predictions of algal dynamics were primarily influenced by previous-hours algal abundance, permanganate index, dissolved oxygen, air temperature, wind speed, and pH. This study revealed that the optimized independent learning model with integrated multi-scale features can significantly enhance the predictive performance of algal dynamics, offering a technical basis for early warning of algal blooms and refined reservoir management. Full article
(This article belongs to the Special Issue Advances in Detecting, Monitoring, Predicting, Managing and Controlling Harmful Algal Blooms)
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28 pages, 1112 KB  
Article
Microcystin-LR Drives Early NAFLD Pathogenesis via Hepatic Cholesterol Accumulation: Dysregulation of Ldlr and Abcg1 Expression Uncoupled from Srebp2
by Hideaki Kawahara, Yoshihito Koto, Yuuka Hitsuda, Koichi Kurata, Keisuke Yoshikiyo, Ayumi Hashiguchi, Hideaki Maseda, Kunihiro Okano, Norio Sugiura, Kazuya Shimizu and Hidehisa Shimizu
Toxins 2026, 18(2), 92; https://doi.org/10.3390/toxins18020092 - 11 Feb 2026
Cited by 1 | Viewed by 1445
Abstract
Chronic exposure to the cyanotoxin microcystin-LR is an emerging environmental driver of non-alcoholic fatty liver disease (NAFLD); however, the initiating molecular events at sub-lethal, environmentally relevant concentrations remain elusive. Current safety guidelines focus primarily on acute injury, potentially overlooking silent metabolic disruption. The [...] Read more.
Chronic exposure to the cyanotoxin microcystin-LR is an emerging environmental driver of non-alcoholic fatty liver disease (NAFLD); however, the initiating molecular events at sub-lethal, environmentally relevant concentrations remain elusive. Current safety guidelines focus primarily on acute injury, potentially overlooking silent metabolic disruption. The present study investigates the early metabolic toxicity of chronic low-dose microcystin-LR (10 µg/L) in a 7-week rat model, specifically focusing on pre-symptomatic perturbations in lipid homeostasis. By integrating biochemical profiling with multivariate systems toxicology (LASSO and PLS-DA), we identified a specific phenotype of “Silent Hepatic Total Cholesterol Accumulation” (T-CHOL +16%, p = 0.01) occurring in the absence of systemic dyslipidemia or overt liver injury. Mechanistic analysis revealed a specific dual failure of cholesterol homeostasis, characterized by the paradoxical upregulation of the influx transporter Ldlr (LASSO coef +0.661) and the suppression of the efflux transporter Abcg1 (PLS1 loading −0.358). Crucially, Ldlr upregulation occurred despite the concomitant transcriptional downregulation of Srebp2 (Spearman ρ = −0.585), indicating a regulatory uncoupling mechanism. We propose that microcystin-LR-induced protein phosphatase 2A (PP2A) inhibition likely drives this uncoupling via a post-transcriptional override—possibly involving ERK/RSK-mediated Ldlr mRNA stabilization. Concurrently, this inhibition appears to block LXR-mediated Abcg1 expression through sustained AMPK hyperactivation resulting from the loss of dephosphorylation. These findings indicate liver-specific cholesterol accumulation as the critical first step of environmental NAFLD pathogenesis, suggesting that current WHO guidelines (1 µg/L) may require re-evaluation regarding metabolic safety. We propose the hepatic Ldlr/Abcg1 ratio as a potential early biomarker for revised risk assessment. Full article
(This article belongs to the Special Issue Advances in Detecting, Monitoring, Predicting, Managing and Controlling Harmful Algal Blooms)
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14 pages, 595 KB  
Article
Limited Potential of Polystyrene Microplastic as a Vector of Microcystin-LR in Diluted Lysate of Microcystis aeruginosa Strain MASH01-A05 in Laboratory Freshwater and Brackish Water Conditions
by Sadia Sharmin, Siobhan J. Peters, Anne Colville, James N. Hitchcock, David J. Booth, David P. Bishop and Simon M. Mitrovic
Toxins 2026, 18(2), 87; https://doi.org/10.3390/toxins18020087 - 9 Feb 2026
Viewed by 1076
Abstract
Microplastics (MPs) and microcystins (MCs) frequently occur together in eutrophic environments. However, their interaction in aquatic systems is poorly understood. This study aimed to examine how MP particle size and salinity influence the adsorption behaviour of the cyanotoxin MC-LR onto polystyrene MPs (PS-MPs). [...] Read more.
Microplastics (MPs) and microcystins (MCs) frequently occur together in eutrophic environments. However, their interaction in aquatic systems is poorly understood. This study aimed to examine how MP particle size and salinity influence the adsorption behaviour of the cyanotoxin MC-LR onto polystyrene MPs (PS-MPs). Two particle size groups (180–500 µm and 700–1000 µm diameter) were mixed with a microcystin-LR (MC-LR) producing Microcystis aeruginosa lysate in either freshwater (salinity ≤ 0.05 g L−1) or brackish water (salinity 16.00 g L−1) and incubated at 25 °C in an orbital shaker for 48 h. MC-LR bound to PS-MPs was extracted and measured using triple quadrupole LC-MS/MS. The MC-LR adsorption rate exhibited a degree of oscillation throughout time, with peak adsorption observed for the smaller-sized PS-MPs at 1.60% in freshwater after 4 h and 4.60% in brackish water after 6 h. For the larger particle size of PS-MPs, peak adsorption occurred after 4 h, reaching 0.1% in freshwater and 1.3% in brackish water. This study provides evidence that PS-MPs have limited potential as vectors of MC-LR in eutrophic freshwater and brackish environments. Full article
(This article belongs to the Special Issue Advances in Detecting, Monitoring, Predicting, Managing and Controlling Harmful Algal Blooms)
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Review

Jump to: Research

25 pages, 591 KB  
Review
Microorganism-Based Strategies for the Control of Cyanobacterial Blooms: A Review of Recent Progress
by Wangle Zhang, Shiyuan Meng, Xiaoxu Wu, Hong Shen, Dongqin Wang, Tong Qiu, Weijie Li, Jiping Chen, Ling Li, Bingbing Liang, Mengdi Zhao, Xuwei Deng and Chi Zhou
Toxins 2025, 17(12), 604; https://doi.org/10.3390/toxins17120604 - 17 Dec 2025
Cited by 5 | Viewed by 1627
Abstract
Cyanobacterial blooms, which are increasingly exacerbated by eutrophication and climate change, pose threats to ecosystems and public health. This paper systematically reviews recent advances in microbial intervention strategies for controlling cyanobacterial blooms. Current approaches primarily comprise direct lysis methods, indirect suppression methods, and [...] Read more.
Cyanobacterial blooms, which are increasingly exacerbated by eutrophication and climate change, pose threats to ecosystems and public health. This paper systematically reviews recent advances in microbial intervention strategies for controlling cyanobacterial blooms. Current approaches primarily comprise direct lysis methods, indirect suppression methods, and integrated strategies. Direct algicide methods rapidly lyse cyanobacterial cells and degrade toxins, although their application is constrained by environmental sensitivity and host specificity. Indirect approaches offer sustainable preventive strategies by inhibiting cyanobacterial growth, yet require careful environmental management. Integrated methods combine microbial strategies with other technologies, enhancing both the efficiency and ecological safety of managing cyanobacterial blooms. While microbial strategies demonstrate significant potential, practical implementation faces challenges, including environmental adaptability, ecological safety, and regulatory frameworks. Future research should focus on integrating synthetic biology, intelligent delivery systems, and multi-omics technologies to achieve more effective and environmentally friendly management of cyanobacterial blooms. Full article
(This article belongs to the Special Issue Advances in Detecting, Monitoring, Predicting, Managing and Controlling Harmful Algal Blooms)
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