Mr Linus Lo1, Dr. Jinping Cheng1
1Department of Science and Environmental Studies and State Key Laboratory of Marine Pollution, The Education University Of Hong Kong, New Territories, Hong Kong
Biography:
Mr. Linus Lo received his B.Sc in Biology from Imperial College London and his M.Sc in Environmental Health and Safety from the Hong Kong University of Science and Technology. He is currently a PhD candidate at The Education University of Hong Kong. Mr. Lo’s research interests revolve around environmental microbiomes and their interaction within marine food webs and with emerging pollutants. His current research focuses on methods to detect and screen for harmful microorganisms in coastal marine waters to make his future scuba dives that much safer.
Abstract:
The coastal environments are vital, however, Globally, increasing diversity and occurrence of harmful biota in coastal and mariculture areas has posed significant economic and public health risks in the form of disease outbreaks and harmful algal blooms. Continuous monitoring efforts are imperative to understand the anthropogenic impact on coastal ecosystems. The use of environmental DNA (eDNA) as a biomonitoring tool has great potential to complement traditional surveys in better capturing regional biodiversity and specifically the potentially hidden and unculturable micro-biodiversity for the detection of harmful agents such as bacterial pathogens, bloom-forming phytoplankton and micro-eukaryotic protists. Effective screening for harmful agents is therefore important for revealing underlying risks to ecosystem biosecurity and foundational for mapping large biological monitoring datasets to actualized risks. In this presentation, we describe our ongoing efforts to streamline eDNA biomonitoring efforts and provide accessible functional databases with updated taxonomy for currently over 650 algae and bacterial pathogens harmful to various aquatic organisms, humans, and/or the environment. By applying such front-end screening, we empowered eDNA biomonitoring data to characterize regional harmful biota profiles and reveal atypical spatiotemporal occurrence of, for example, Vibrio pathogens and Karlodinium dinoflagellates associated with human activities and nutrient loads that were potentially overlooked, providing beneficial insights to constructing predictions and measures against harmful events.