Scientists have created small, synthetic living machines that self-organize from single cells, move quickly through different environments without the need for muscle cells, can remember their experiences, heal themselves when damaged, and exhibit herd behaviors.
Earlier, scientists have developed swarms of robots from synthetic materials and moving biological systems from muscle cells grown on precisely shaped scaffolds. But until now the creation of a self-directed living machine has remained beyond reach.
Biologists and computer scientists from Tufts University and the University of Vermont have created novel, tiny self-healing living machines from frog cells (Xenopus laevis) that they call “Xenobots.” These can move around, push a payload, and even exhibit collective behavior in a swarm.
In an article titled “A cellular platform for the development of synthetic living machines” published in the journal Science Robotics, the researchers report a method for creating these of Xenobots from frog cells. This cellular platform can be used to study self-organization, collective behavior, and bioengineering and provide versatile, soft-body, living machines for applications in biomedicine and environmental biology.
“We are witnessing the remarkable plasticity of cellular collectives, which build a rudimentary new ‘body’ that is quite distinct from their default—in this case, a frog— despite having a completely normal genome,” says Michael Levin, Distinguished Professor of Biology and director of the Allen Discovery Center at Tufts University, and corresponding author of the study. “In a frog embryo, cells cooperate to create a tadpole. Here, removed from that context, we see that cells can re-purpose their genetically encoded hardware, like cilia, for new functions such as locomotion. It is amazing that cells can spontaneously take on new roles and create new body plans and behaviors without long periods of evolutionary selection for those features.”
Xenobots can move around in a coordinated manner with the help of cilia present on their surface. These cilia grow through normal tissue patterning and do not require complicated architectural procedures such as scaffolding or microprinting, making the high-throughput production of Xenobots possible. And while the frog cells are organizing themselves into Xenobots, they are amenable to surgical, genetic, chemical, and optical stimulation. The researchers show that the Xenobots can maneuver through water, heal after damage and exhibit predictable collective behaviors.
The scientists also provide a proof of principle for a programmable molecular memory using a light-controlled protein that can record exposure to a specific wavelength of light.
Compared to their first edition, Xenobots 1.0, that were millimeter-sized automatons constructed in a “top down” approach by manual placement of tissue and surgical shaping of frog skin and cardiac cells to produce motion, this updated version of Xenobots 2.0 takes a “bottom up” approach. The biologists took stem cells from frog embryos and allowed them to self-assemble and grow into spheroids, where some of the cells after a few days differentiated to produce cilia—tiny hair-like projections that move back and forth or rotate in a specific way. Cilia act like legs to help the new spheroidal Xenobots move rapidly across a surface.
“In a way, the Xenobots are constructed much like a traditional robot. Only we use cells and tissues rather than artificial components to build the shape and create predictable behavior.” Says Doug Blackiston, PhD, senior scientist and co-first author on the study with research technician, Emma Lederer. “On the biology end, this approach is helping us understand how cells communicate as they interact with one another during development, and how we might better control those interactions.”
Scientists at UVM ran computer simulations that modeled different shapes of the Xenobots and analyzed its effects on individual and collective behavior. Robotics expert, Joshua Bongard, PhD, and a team of computer scientists used an evolutionary algorithm on the Deep Green supercomputer cluster at UVM’s Vermont Advanced Computing Core to simulate the behavior of the xenobots under numerous random environmental conditions. These simulations identified Xenobots that excelled at working together in swarms to gather large piles of debris in a field of particles.
“We know the task, but it’s not at all obvious—for people—what a successful design should look like. That is where the supercomputer comes in and searches over the space of all possible Xenobot swarms to find the swarm that does the job best,” says Bongard. “We want Xenobots to do useful work. Right now, we’re giving them simple tasks, but ultimately we’re aiming for a new kind of living tool that could, for example, clean up microplastics in the ocean or contaminants in soil.”
Xenobots can quickly collect garbage working together in a swarm to sweep through a petri dish and gather larger piles of iron oxide particles. They can also cover large flat surfaces and travel through narrow capillaries.
The Tufts scientists engineered the Xenobots with a memory capability to record one bit of information, using a fluorescent reporter protein called EosFP that glows green but when exposed to blue light at 390nm wavelength, the protein emits red light instead.
The researchers injected the cells of the frog embryos with messenger RNA coding for the EosFP protein before the stem cells were excised to create the Xenobots so that the mature Xenobots have a built-in fluorescent switch which can record exposure to blue light.
To test the memory capacity, the investigators, allowed 10 Xenobots to swim around a surface on which one spot is illuminated with a beam of blue light. After two hours, they found that three bots emitted red light. The rest remained their original green, effectively recording the “travel experience” of the bots. This molecular memory in Xenobots could be harnessed to detect the presence of radioactive contamination, chemical pollutants, drugs, or a disease condition.
“When we bring in more capabilities to the bots, we can use the computer simulations to design them with more complex behaviors and the ability to carry out more elaborate tasks,” said Bongard. “We could potentially design them not only to report conditions in their environment but also to modify and repair conditions in their environment.”
“The biological materials we are using have many features we would like to someday implement in the bots—cells can act like sensors, motors for movement, communication and computation networks, and recording devices to store information,” says Levin. “One thing the Xenobots and future versions of biological bots can do that their metal and plastic counterparts have difficulty doing is constructing their own body plan as the cells grow and mature, and then repairing and restoring themselves if they become damaged. Healing is a natural feature of living organisms, and it is preserved in Xenobot biology.”
Cells in a biological robot can also absorb and break down chemicals and work like tiny factories, synthesizing and excreting chemicals and proteins.