Protecting fish against harmful algal blooms

Office of Research Affairs and Knowledge Transfer Research Achievements Protecting fish against harmful algal blooms

Protecting fish against harmful algal blooms

The University's efforts to cultivate an active applied research culture are paying off across the board. A project funded by the Research Grants Council's Faculty Development Scheme and led by Professor Fred Lee, Head of Department of Science, who specialises in employing molecular and proteomic approaches in the study of harmful algal blooms (HABs) — or red tides — and the associated toxin production mechanisms, promises to shed light on strategies to protect fish against such blooms and hence contribute to food security. HABs cause massive economic losses in the fish farming and shellfish industries.
 

The project is focused on one particular species of fish-killing algae, known as Karenia mikimotoi, which has recently been blooming in Chinese waters every few years. In 2012, an enormous bloom of the species caused the death of at least US$300 billion's worth of abalone in Fujian, while in 2016, more than 200 tons of fish in several fish farming zones in Hong Kong suffered. Despite the abundance of studies on Karenia mikimotoi over the past decades, the exact mechanism by which it kills fish and shellfish remains unclear.
 
To alleviate the problem, the project aimed to understand how fish gills respond to the species at the molecular level. The project team has succeeded in identifying the relationship between the Karenia mikimotoi originating from different geographical locations, and developing an efficient, straightforward and inexpensive approach to optimise the growing conditions of the cell culture of Karenia mikimotoi. The results will help to formulate preventive measures or proactive strategies against fish-killing incidents, which will have significant implications on the local, mainland and even international fish farming and shellfish industries in the long run.
 
More details about the project results can be found at the following publications generated from the project: