Researchers Awarded $1M NSF Grant to Help Protect Aquaculture Industry, Coastal Communities
Project Will Use Low-Cost Biosensors to Detect Presence of Pathogens
By Edwin L. Aguirre
The National Science Foundation (NSF) has awarded a three-year, $1 million grant to a team of researchers led by Electrical Engineering Prof. Yan Luo to develop a data analytics platform that uses biosensors to detect harmful organisms such as Vibrio and Pseudomonas in aquaculture farms and coastal waters.
“This is critical in safeguarding public health, particularly in vulnerable coastal areas that provide communities with food, recreation and protection from storms,” says Luo.
According to the U.S. National Oceanic and Atmospheric Administration (NOAA) Fisheries, in 2020, marine and freshwater aquaculture farms in the United States produced a total of 658 million pounds of fish, crustaceans, shellfish and algae valued at $1.5 billion. Based on value, more than 80% of that aquaculture consists of bivalve mollusks such as oysters, clams and mussels, with salmon and shrimp making up most of the rest.
Waterborne pathogens can occur naturally in the environment or be transmitted from infected species or from human activities. Luo says human pathogens such as norovirus and E. coli enter aquatic ecosystems through sewage discharges and farm runoff.
“This contamination can threaten fisheries, recreational areas and the sustainability of the increasingly important aquaculture industry,” he says. “Aquatic pathogens that infect commercially cultivated animals can cause disease outbreaks that can wipe out entire aquaculture farms.”
An Early Warning System for Pathogens
According to the researchers, the economic burden caused by waterborne diseases exceeds $3 billion in direct health care costs each year in the United States. Worldwide, aquaculture losses reach more than $6 billion a year.
That is why Luo and his team are developing BioSPACE – to give farmers, environmental agencies and water-reliant industries a rapid, portable, easy-to-use and monitoring and early warning system that is low in cost, yet sensitive.
“Existing technologies for detecting waterborne pathogens – such as the polymerase chain reaction, or PCR, test – are too slow and costly for large-scale deployment,” Luo says. “Delayed test results can lead to the spread of pathogens, which can progress to coastal contamination and extensive aquaculture losses.”
Assisting in the lab research are UML Ph.D. students Calvin Ng (electrical engineering) and Nerissa Molejon (environmental engineering), as well as master’s student Dmitri Hunt (electrical engineering) and senior students Chloe Chanthompalit (electrical engineering) and Alex Ryzi (environmental engineering).