They create living machines that reproduce as organic beings in the laboratory – Central Valley Business Journal


12/03/2021 at 18:04 CET
Researchers at the University of Vermont, in the United States, have created robots “living & rdquor; made in the laboratory that can reproduce spontaneously. Engineered by Artificial Intelligence (AI), they mark a new form of biological self-replication, especially promising for regenerative medicine.
The tiny robots are able to get out of the container in which they were developed, search for cells and “assemble & rdquor; a new robot, an exact copy that, after a few days, will acquire the same ability to replicate itself. The little machines were created from frog cells: these computer-engineered organisms collect individual cells inside a “mouth” and release Xenobot “hatchlings” with the same appearance and movements. In turn, the new specimens reproduce in the same way.
The embryonic cells used, which belong to a Xenopus laevis frog, would become skin in a natural context. They would serve to keep pathogens out and redistribute mucus on a tadpole’s skin, but American scientists have given it another “life”. By applying the right instructions through a computer program based on Artificial Intelligence, cells can be “redesigned & rdquor; in the lab and ready for a completely different role.
According to a press release, the researchers explained that the cells used have the genome of a frog, but when released from becoming tadpoles they use their collective intelligence, or a kind of cellular plasticity, to do something amazing: get together and create “living & rdquor; which in turn can produce exact copies of themselves. If at first it came to the attention of scientists that Xenobots could be designed to perform simple tasks, the new functions practically redefine the limits of what can be understood as biological reproduction.
These biological objects, which are basically a collection of computer-designed cells, replicate spontaneously, but including the complete and unaltered frog genome. This means that the original instructions present in the cell have managed to redirect themselves to fulfill a new objective: to group together and create an organism, which in turn will have the ability to replicate itself. Apparently we have not yet discovered all the ways in which life can reproduce itself, as perhaps we had thought.
Related topic: They create living cell robots with free will and their own personalities.
In the beginning, the father xenobot made up of about 3,000 cells, it forms a sphere. Without any “help”, the process will most likely stop there and playback will not continue. However, an Artificial Intelligence program working on the Deep Green supercomputer cluster at the University of Vermont made a difference.
When applying a evolutionary algorithm, it was possible to “test & rdquor; billions of simulated body shapes, such as triangles, squares or pyramids, until finding those that allowed cells to be more efficient in “kinematic” replication, that is, based on movement. From that achievement, the organisms managed to replicate without major problems from the father Xenobot.
In this sense, the scientists highlighted in the new study, recently published in the Proceedings of the National Academy of Sciences (PNAS), that cell groups, when released from a developing organism, can meet and combine with other similar loose cells, and furthermore this ability does not have to evolve or be specifically introduced by genetic manipulation.
At the same time, research shows that Artificial intelligence can help to design model organisms that reproduce better: this same concept can be applied in the future to “guide & rdquor; to human cells in the desired sense, for example by eliminating diseases, giving new life to organs that are no longer functional or creating new ones.
Kinematic self-replication in reconfigurable organisms. Sam Kriegman, Douglas Blackiston, Michael Levin and Josh Bongard. PNAS (2021). DOI: https: //doi.org/10.1073/pnas.2112672118
Photo: kalhh on Pixabay.
Video: University of Vermont / YouTube.
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