Cyanotoxin-Encoding Genes as Markers to Predict Cyanobacterial Harmful Algal Blooms and Cyanotoxins
Citation:
Lu, J. Cyanotoxin-Encoding Genes as Markers to Predict Cyanobacterial Harmful Algal Blooms and Cyanotoxins. HABs, Hypoxia, and Nutrients Webinar, Cincinnati (virtual), OH, March 27, 2024.
Impact/Purpose:
1) Public concern over cyanobacterial blooms has increased due to their higher frequency of occurrences and their potential ecological and health impacts. 2) Cyanobacteria are becoming a focus for their cyanotoxin production in freshwater ecosystems. Preventing cyanotoxin production is essential to protect aquatic ecosystems and public health. However, the information of prediction of cyanobacterial bloom (HCB) is limited. 3) This study is to provide our study result of cyanotoxin-encoding genes as markers to predict HCBs and cyanotoxin production. 4) OW, regional offices, scientists and water quality managers could be interested in the results.
Description:
Cyanobacterial harmful algal blooms (CyanoHABs) produce excessive amounts of cyanotoxins, mainly microcystins (MCs) and anatoxins (ATXs), significantly threatening aquatic ecosystems and public health. Accurately predicting CyanoHABs is essential to develop effective CyanoHAB prevention strategies, but current CyanoHAB prediction approaches are limited, complicated, and difficult to use. To address this need, we recently reported to use cyanotoxin encoding genes as targets for an early warning system that can predict cyanotoxin production in various lakes in United States. Results obtained from studies at an inland and a west coastal freshwater lake with typical reoccurring MC- and ATX-producing CyanoHABs, respectively, revealed that Microcystis as the major MC producers in June and July in the inland lake, while Dolichospermum as the major ATX producers proliferated in May and June in the coastal lake, leading to a MC- or ATX-dominated HAB event. The abundance of MC or ATX encoding genes and their transcript levels also significantly correlated with total cyanotoxin concentrations detected, when expressed in logistic equations, which accurately forecasted cyanotoxin production. Furthermore, an association between the quantity of cyanotoxin producing genes and expressions of critical nutrient metabolisms associated genes were also observed revealing intense cyanotoxin production co-occurred with pronounced cyanobacterial nutrient metabolic activities during a CyanoHAB event. Overall, these studies elucidated the potential drivers during the CyanoHAB event. More importantly, we have shown the feasibility of using our early warning system in forecasting a CyanoHAB event and as a useful tool to guide CyanoHAB prevention and mitigation practices in inland and coastal freshwater lakes.