Evolution Algorithms? Scientists create first living machine made of 100% frog DNA

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Scientists used computer algorithms to mimic evolution made of 100% frog DNA. Well, it kind of evolved since it’s not really a frog. Researchers instead call it the world’s first “living machine.”

The stem cells came from the African clawed frog and can move independently and collectively, can self-heal wounds and survive for weeks at a time, and could potentially be used to transport medicines inside a patient’s body.

“They’re neither a traditional robot nor a known species of animal,” study co-author Joshua Bongard, a computer scientist and robotics expert at the University of Vermont, said in a statement. “It’s a new class of artifact: a living, programmable organism.”

The study authors brought these designs to life, piecing stem cells together to form self-powered 3D shapes designed by the evolution algorithm. Skin cells held the xenobots together, and the beating of heart tissue in specific parts of their “bodies” propelled the ‘bots through water in a petri dish for days, and even weeks at a stretch, without needing additional nutrients, according to the study. The ‘bots were even able to repair significant damage.

“We can imagine many useful applications of these living robots that other machines can’t do,” said study co-author Michael Levin, director of the Center for Regenerative and Developmental Biology at Tufts University in Massachusetts. These might include targeting toxic spills or radioactive contamination, collecting marine microplastics or even excavating plaque from human arteries, Levin said.

The prospect of living robots and using technology to create living organisms raises concerns for some, “That fear is not unreasonable,” Levin said. “When we start to mess around with complex systems that we don’t understand, we’re going to get unintended consequences.”

Nevertheless, building on simple organic forms like the xenobots could also lead to beneficial discoveries, he added.

“If humanity is going to survive into the future, we need to better understand how complex properties, somehow, emerge from simple rules,” Levin said.

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