ArticlePeerJ2026
Rapid assessment of phytoplankton assemblages using Next Generation Sequencing and Barcode of Life Data System: a widely applicable HAB-ID toolkit for detecting and monitoring biodiversity loss and harmful algal blooms.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Article
- Spatio-Temporal Resolution of Microbial Functions and Taxa Associated With Cyanobacterial Harmful Algae Blooms Along a 500-Km Aquatic Continuum in the Lake Erie Watershed.Environmental microbiology · 2025Article
- Temporal and Depth-Driven Variability of Pelagic Bacterial Communities in Lake Erie: Biofilm and Plankton Dynamics.Environmental microbiology reports · 2025Article
- Spatio-temporal connectivity of the aquatic microbiome associated with cyanobacterial blooms along a Great Lake riverine-lacustrine continuum.Frontiers in microbiology · 2023Article
- Rapid on-site detection of harmful algal blooms: real-time cyanobacteria identification using Oxford Nanopore sequencing.Frontiers in microbiology · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Harmful algal blooms have important implications for the health, functioning, and services of aquatic ecosystems. Our ability to detect and monitor these events is often challenged by the lack of rapid and cost-effective methods to identify bloom-forming organisms and their potential for toxin production. Here, we developed and applied a combination of DNA barcoding and Next Generation Sequencing (NGS) for the rapid assessment of phytoplankton community composition with a focus on two important indicators of ecosystem health: toxigenic bloom-forming cyanobacteria and impaired planktonic biodiversity. To develop this molecular toolset for identification of cyanobacterial and algal species present in HABs (harmful algal blooms), hereafter called HAB-ID, we achieved three goals: creating a validated reference database, optimizing molecular protocols, and developing original bioinformatics pipeline tailored to uncertainty of algal taxonomy. The BOLD (Barcode of Life Data System) 16S reference database from cultures of 211 cyanobacterial and algal strains representing 102 species with particular focus on bloom and toxin producing taxa was constructed with Sanger sequencing and further refined using Single Molecule Real Time Sequencing (SMRT-sequencing). Using the new reference database of 16S rDNA sequences and constructed mock communities of mixed strains for protocol validation, we developed new NGS primer sets which can recover 16S from both cyanobacteria and eukaryotic algal chloroplasts. We also developed DNA extraction protocols for cultured algal strains and environmental samples, which match commercial kit performance and offer a cost-efficient solution for large scale ecological assessments of harmful blooms while giving benefits of reproducibility and increased accessibility. Our innovative bioinformatics pipeline was designed to handle low taxonomic resolution for problematic genera of cyanobacteria such as the
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