Lili He, professor of food science, was perplexed when the director of the Massachusetts Pesticide Analysis Laboratory (MPAL) asked if the molecular spectroscopy technique she specializes in could be used to figure out the age of mosquitoes.
Credit: UMass Amherst
Lili He, professor of food science, was perplexed when the director of the Massachusetts Pesticide Analysis Laboratory (MPAL) asked if the molecular spectroscopy technique she specializes in could be used to figure out the age of mosquitoes.
“My first impression was, what? Why do we have to determine the age of mosquitoes,” recalls He, head of the food science department at the University of Massachusetts Amherst.
She then learned from John Clark, director of the UMass Amherst-based MPAL, that only older mosquitoes infected with pathogens can pass on infectious diseases like the West Nile, Zika and Chikungunya viruses, dengue fever and malaria, when they bite humans and livestock.
Mosquitoes can live up to a year. Before they are able to transmit disease, they must live long enough to be infected with a pathogen through a blood meal, survive through the varying incubation period of the pathogen and then pass it on by biting a person or livestock.
“Right now there is no very accurate and also cost-effective way to determine the age of mosquitoes,” He says. “Having that ability will enable quick assessment of the risk of mosquito-borne diseases in a particular area, which will enable rapid and effective mosquito-control strategies.”
To tackle the challenge, He has received a five-year, $1.71 million grant from the National Institutes of Health (NIH) to develop and test a novel approach to age-grade mosquitoes. Her multidisciplinary team includes experts in analytical development, mosquito biology, biochemistry, field studies and machine learning modeling.
Joining He in the project are Clark, based at the UMass Department of Veterinary and Animal Sciences (VASCI); Wei Zhu, assistant professor of mathematics and statistics; and entomologists Laura Harrington and Courtney Murdock, both of Cornell University, and Ponlawat Alongkot, chief of vector biology and control at the Armed Forces Research Institute of Medical Sciences in Bangkok, Thailand.
“This is a very collaborative project and a very strong team we have put together,” says He, director of the Institute for Applied Life Sciences’ (IALS) Raman, IR and XRF Core Facility. “Everyone has an important part.”
Harrington and Murdock – internationally recognized for their vector biology research – will raise mosquitoes in their labs under different conditions, controlling diet, temperature and infection status. Mosquitoes also will be gathered from the field in Florida and Thailand. He will be sent individual mosquitoes, which she will put in water and a centrifuge to break down the tissue. Then she uses a nanotechnology-integrated molecular fingerprinting technique called surface-enhanced Raman Spectroscopy (SERS) to analyze the molecular spectra of biomolecules from the mosquito water extract that are bound with silver nanoparticles (AgNPs). “It’s a very simple, quick technique,” He explains.
“Our central hypothesis is that AgNPs interact with specific age-related biomolecules enabling SERS to generate unique and predictable spectral information for machine learning models to determine the age of mosquitoes captured in the field,” He explains in the grant summary. “We have already established a basic SERS protocol and machine learning model and demonstrated the feasibility to quantitatively age-grade lab and field-collected Aedes aegypti mosquitoes with high accuracy.”
The mosquito data will be sent to Zhu, who will apply his expertise in a domain adaptation technique to make the data more comparable. “He can train a learning model to apply it to different data; in this case, data from mosquitoes in different locations. So that is extremely useful,” He says.
The team aims to set up protocols in the lab and the field, and to develop the ability to identify such factors as diet, infection status and location temperature, as well as establish modern machine learning models for age-grading mosquitoes.
“Malaria kills two to three million people and infects another 200 million or more people every year,” He says. “Mosquito-borne pathogens also threaten livestock production and animal food quality and sustainability. So this project has very broad significance.”
