In a study released last week, computer scientist Selim Akl of Queens University demonstrated that slime mold is fantastically efficient at finding the quickest route to food. When he placed rolled oats over the country’s population centers and a slime mold culture over Toronto, the organism grew its way across the Canadian map, sprouting tentacles that mimicked the Canadian highway system. It’s an experiment that’s been replicated globally several times now — in Japan, the UK, and the United States — all with a similar outcome.
So what is slime mold, and how does it do this?
Slime mold is not a plant or animal. It’s not a fungus, though it sometimes resembles one. Slime mold, in fact, is a soil-dwelling amoeba, a brainless, single-celled organism, often containing multiple nuclei.
Slime molds were likely an inspiration for the 1958 science-fiction film, “The Blob,” scientists say. And it’s in these plasmodial, “blob” states that they spread like highway networks and even solve mazes.
When ripped in half, the halves continue to grow independently and the nuclei in each half continue to divide and develop in sync. This makes the organism uniquely appealing to cancer drug research, said Jonatha Gott at Case Western University, because it provides researchers with multiple identical samples dividing at the same time.
Plus, unlike other organisms, the amoeba’s genetic information makes an uncommonly large number of corrections during the RNA editing phase, Gott said. She compared it to a contractor continually making changes to an architect’s plans.
“As it’s making a copy of the DNA, it changes it,” Gott said, “It’s incredibly precise and incredibly accurate. If it doesn’t do this, it dies. It’s a really crazy way to express genes.”
Computer scientists like Akl also study slime mold to better understand how nature “computes.” The hope is that these amoebas will teach them how to develop better algorithms for delivering information.
The highway experiments, for example, show that slime mold is capable of computing optimal coverage of the map while using the least amount of energy, Akl said.
Nature, in this case, was able to compute an efficient network in less time than humans could. If we could harness the algorithm to do so, we could build more efficient systems, he added.
“We are always searching for the best way to connect people…yet here is this lowly species that can do it,” Akl said.