Nematodes may be the most abundant creatures on Earth, but analyzing communities of the wormlike animals is difficult because they're microscopic and many species look alike.
Computer-assisted genetic analysis could change that, say University of Florida scientists who have completed a demonstration study of a new method. It was published online in the journal Molecular Ecology Resources.
The method, known as massively parallel sequencing, reveals small parts of the DNA code for multiple nematodes simultaneously, says Dorota Porazinska, a courtesy assistant professor with UF's Fort Lauderdale Research and Education Center. It can do the same for other invertebrates that live alongside nematodes, including bacteria, fungi and mites.
There may be more than 1 million nematode species, but only about 20,000 have been formally described. Nematodes live in almost every environment on Earth. Some species are parasites that prey on plants, animals or people.
By providing “who's who” information on micro-organisms in crop fields, lawns and golf courses, the method may help explain why harmful nematodes attack plants in some sites but not others. It could also provide clues on how to keep sites healthy.
“We often look at agricultural systems only in terms of the organisms we think are bad,” says Porazinska, the study's lead author. “But we skip over what's being done by other organisms that don't bother us. And they may be doing things to assist in the system.”
Once scientists know which micro-organisms live in a plot of land, they can begin manipulating variables and developing agricultural practices that discourage pest species, says Robin Giblin-Davis, a professor at the Fort Lauderdale center and another author.
In the study, UF researchers took a new approach to an instrument called a genome sequencer, commonly used to sequence the DNA structure of a single organism. Here, they sequenced small bits of DNA from samples taken from an artificially assembled community of known nematodes. Then they checked the results against DNA databases used to identify nematodes.
The study showed massively parallel sequencing identified nematode species with a high degree of accuracy. But it didn't perform as well at determining how many individual nematodes the samples contained. So the researchers are working to refine their approach.
When massively parallel sequencing is used in the field, any nematodes that don't match known species can be isolated for further study, Giblin-Davis says.
Previously, researchers identified nematodes one at a time — an approach that worked but was painfully slow, because genetic and morphological analysis was often required to confirm the species.
“With the traditional method, in two years we identified 360 nematodes from a tropical rainforest and now we can get thousands,” Giblin-Davis says. “This will give us a good chance, hopefully, of not only recovering what's there commonly, but the rare things.”
The UF approach is an exciting development for scientists studying nematode populations, says Paul De Ley, an assistant professor with the University of California, Riverside.
“This is an approach that is likely to be adopted in the U.S., Western Europe and some Asian countries,” says De Ley, who researches nematode genetics. “The major limiting factor is that these kinds of sequencers are not widely available yet.”
Because the technology is costly, it may be difficult to employ in tropical regions where crop plants are often attacked by nematodes, he says. However, if government officials streamline current import policies, researchers may be able to easily transport soil samples from tropical regions to laboratories in industrialized nations, solving the problem.