A Study on the Possibility of Early Warning for Cochlodinium polykrikoides Blooms, Using Molecular Methods

• Published in: Water (Basel) 2022-10, Vol.14 (19), p.3115
• Main Authors: Kang, Hye-Eun, Yoon, Tae-Ho, Park, Jong-Woo, Lim, Weol-Ae, Kang, Chang-Keun, Kim, Hyun-Woo
• Format: Article
• Language: English
• Subjects: Algae; Aquaculture; Bacteria; Biological activity; Chemical activity; Coastal waters; Cochlodinium polykrikoides; Community structure; Cyanobacteria; DNA barcoding; Environmental factors; Methods; Microbial activity; Microorganisms; Nutrients; Phytoplankton; Plankton; Plasmids; Thermal cycling; Water analysis; Water chemistry; Water quality; Water sampling
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w14193115

The occurrence of HABs is known to be affected by multiple environmental factors such as temperature, salinity, nutrients, light, water chemistry, and biological activity. This study aimed to study the possibility of early warning for Cochlodinium polykrikoides blooms in southern Korean waters using qPCR and metabarcoding analysis. We were able to detect C. polykrikoides via a sensitive technique, and confirmed the early warning potential of C. polykrikoides by quantitative PCR. To identify the microbial organisms related to the bloom caused by C. polykrikoides, metabarcoding analysis was conducted using 18 water samples collected from bloom sites in southern Korean waters between 2018 and 2019. Although there was no single group that could explain the successive blooms of C. polykrikoides, four taxa, including Gamma proteobacteria (0.588, p < 0.01), Verrucomicrobia (0.874, p < 0.01), Cyanobacteria (0.975, p < 0.01), and Cryptophyta, were related to C. polykrikoides blooms. When the HABs that occurred were caused by C. polykrikoides, although there were sites where the cells of C. polykrikoides were not detected, similar functions of the microbial communities operated in all southern Korean coastal waters. We identified that the phytoplankton community structure was divided into three or four, using metabarcoding analysis by sampling years.