Enhancing early-season detection of harmful algal blooms caused by sediment-borne overwintering cyanobacteria using metagenomic and qPCR tools.

Authors

Andrew D McQueen, Alyssa J Calomeni-Eck, Alyxandra S Cicerrella, Seung Ho Chung, Madeleine P Malmfeldt, Denise L Lindsay, Ping Gong

Published in

Harmful algae. Volume 158. Pages 103160. Epub Jun 08, 2026.

Abstract

To better inform adaptive management strategies for harmful algal blooms (HABs), there is a critical need to improve detection capabilities of bloom risks earlier in the growing season. Emerging molecular tools such as metagenomic Next-Generation Sequencing (NGS) and amplification-based quantitative polymerase chain reaction (qPCR) can accurately identify the taxonomy of cyanobacteria and akinetes of which the latter are particularly challenging to distinguish morphologically and estimate their abundance. This study aimed to evaluate the contribution of these advanced molecular tools to assessing the presence, density, and planktonic growth potential of overwintering cyanobacterial cells in sediments from historically HAB-impacted waterbodies in the USA. We conducted 14-day incubation experiments using field-collected lake sediments and characterized cyanobacterial taxonomy and abundance in the sediments (pre-incubation) and overlying water (post-incubation) using light microscopy, genus-specific qPCR, and 16S rRNA amplicon sequencing. By analyzing qualitative and quantitative results, we not only identified the prevailing cyanobacterial genera that moved from sediment to water column over the incubation but also determined their relative abundance and the cyanobacterial genera consistent between sediment and water column. This study demonstrated that metagenomic and qPCR tools provided additional lines of evidence to augment traditional microscopy and improved taxonomic identification and quantification. Our approach can better inform planktonic growth potential of problematic cyanobacteria to enhance early detection capabilities, and guide targeted countermeasures taken to improve preventative or remedial HAB management, reducing environmental and public health impacts.

PMID:
42595408
Bibliographic data and abstract were imported from PubMed on 14 Aug 2026.

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