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$1.1 million National Science Foundation grant awarded to UCR for nematode research

The challenge of unearthing and identifying more than 1 million species of nematodes or round worms living among us has been met with enthusiasm by a team of UC Riverside researchers. The $1.1 million, three-year, National Science Foundation grant will be used to identify and catalog nematodes, including those that can cause disease in humans, plants and animals.

An additional $500,000 in grant funding was awarded to collaborators at the Carnegie-Mellon University, the Elizabeth City State University and the University of New Hampshire.

“The estimates of nematode species run into the millions; comparable to insects," said Paul De Ley, associate professor and associate nematologist at UCR’s Department of Nematology and Agricultural Experiment Station, and a key member of the research team. “Currently, there are 26,000 species identified, which means we know less than 99.9 percent of all species.”

De Ley noted that even in California, where there is a high concentration of nematologists, it’s easy to find yet-to-be identified species.

“Where ever you put a shovel in the ground, you will find these nematodes – the desert, the mountains, the ocean – but because they are microscopic, you wouldn’t know about it,” he said.

Some nematodes cause significant damage to agriculture, while others do not. For example, the soybean cyst nematode causes one-third of total yield losses to all soybean pathogens worldwide. To the untrained eye it may look very similar to other cyst nematode species, but most of these others are quite harmless to soybeans. Knowing exactly which plant parasites occur in which field is essential for plant protection and crop rotation.

The multitude of different species creates a challenge for scientists because the main tools available to track these creatures are microscopes and literature. Literature is based on microscopic characters used to identify them, De Ley said. Most nematodes are transparent and look quite different under microscopes from the animals seen with the naked eye.

“So if you are unprepared on how to identify them you could be lost,” he said. “You have to train your eyes to find them. You must refer back to literature that is very technical. And, a large majority are probably not known so you can’t find them in books anyway. What you need is DNA and microscopic information; however, a microscope is something you need to learn how to use. It takes years of practice and personal experience.”

For the solution, De Ley turned to two colleagues, Michalis Faloutsos and Eamonn Keogh, both associate professors from UCR’s Bourns College of Engineering, Department of Computer Science and Engineering, who had the exact expertise needed to build and test a solution.

Keogh is a data mining specialist who has collaborated with an entomologist on insects, and an anthropologist on petroglyphs and arrowheads. Faloutsos is an expert in searches of the kinds of complex networks that will be used to organize nematode images.

“This research is focusing on nematodes but it can be a tool to catalog insects, birds and even inanimate objects,” Keogh said. “The system will be designed as a new and efficient way to view and compare large collections of images.”

Keogh explained that the user uploads an image of a nematode or asks that the system provide nine random nematode images. If the query nematode looks more like one than the other, the user will click on it and the system will provide nine more similar-looking choices, and so on. With just a few more clicks the user will find the best match to the actual specimen.

“It’s artificial intelligence that is watching you click,” he said. “And it picks up on the pattern and responds to your selections. It might notice that the user is only clicking on certain colors or shapes and it will then select only those images that match the search.”

In essence, it will be a system that learns how to search and after only five or six clicks zooms in on the right image. The result will be a much more efficient and quicker tool.

“What we are trying to do is to help people who don’t have any prior knowledge learn how to identify these nematodes,” said De Ley. “And, we want to make it available to a much larger population of people at a much younger age.”

In addition to Keogh, De Ley and Faloutsos, the research team is made up of Amit K. Roy-Chowdhury, assistant professor, Department of Electrical Engineering and Department of Computer Science and Engineering; James Gordon Baldwin, chair of UCR’s Department of Nematology, and Irma Tandingan De Ley, assistant specialist, Department of Nematology and Agricultural Experiment Station.

Other team members include Eyualem Abebe, assistant professor, Department of Biology, Elizabeth City State University; Christos Faloutsos, professor, Department of Computer Science, Carnegie-Mellon University; and William Kelley Thomas, Hubbard Chair in the Genomics Department of Biochemistry and Molecular Biology, and associate professor, Department of Biochemistry, University of New Hampshire.

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