Tag: biology

Xenobots

The researchers let the cell clusters assemble in the right proportions and then used micro-manipulation tools to move or eliminate cells — essentially poking and carving them into shapes like those recommended by the algorithm. The resulting cell clusters showed the predicted ability to move over a surface in a nonrandom way.

The team dubbed these structures xenobots. While the prefix was derived from the Latin name of the African clawed frogs (Xenopus laevis) that supplied the cells, it also seemed fitting because of its relation to xenos, the ancient Greek for “strange.” These were indeed strange living robots: tiny masterpieces of cell craft fashioned by human design. And they hinted at how cells might be persuaded to develop new collective goals and assume shapes totally unlike those that normally develop from an embryo.

2021-11-29: And now they reproduce

The same team that built the first living robots (“Xenobots,” assembled from frog cells — reported in 2020) has discovered that these computer-designed and hand-assembled organisms can swim out into their tiny dish, find single cells, gather 100s of them together, and assemble “baby” Xenobots inside their Pac-Man-shaped “mouth” — that, a few days later, become new Xenobots that look and move just like themselves. And then these new Xenobots can go out, find cells, and build copies of themselves. Again and again. “These are frog cells replicating in a way that is very different from how frogs do it. No animal or plant known to science replicates in this way. We’ve found Xenobots that kinematically replicate. What else is out there?”

2023-07-04: Interview with Michael Levin about the amazing latent abilities of cells. This seems to be true recursively.

A big theme of your work has been that organisms have latent abilities—that the behavior we see in nature is contextual and that, by altering the circumstances, you coax them to do totally different things. What are some examples?

We are lulled into thinking that frog eggs always make frogs, and acorns always make oak trees. But the reality is that once you start messing around with their bioelectrical software, we can make tadpoles that look like other species of frogs. We can make planaria that look like other species of flatworms across 150 million years of evolutionary distance—no genetic change needed, same exact hardware. The same hardware can have multiple different software modes.

You can look at frog skin cells and say, “All they know how to do is how to be this protective layer around the outside. What else would they know how to do?” But it turns out that if you just remove the other cells that are forcing them to do that, you find out what they really want to do—which is to make a xenobot and have this really exciting life zipping around and doing kinematic self-replication. They have all these capacities that you don’t normally see. There’s so much there that we haven’t even begun to scratch the surface of.

Some object to speaking of what the cells “know” or “want” to do. Do you think that a concern about being anthropomorphic or anthropocentric has hindered research in this?

Incredibly so. I love to make up the words for this stuff because I think they need to exist—“teleophobia.’’ People go screaming when you say, “Well, it wants to do this.” People are very binary because they’re still carrying this pre-scientific holdover. Back in before-science times, you could be smart like humans and angels, or you could be dumb like everything else. That was fair enough for our first pass in 1700, but now we can do better. You don’t need to be at either of these endpoints. You could be somewhere in the middle. When I say this thing “wants to do XYZ,” I’m not saying it can write poetry about its dreams. It doesn’t necessarily have that kind of second-order metacognition; it doesn’t know what it wants. But it still wants.

Are the cells of our body continually measuring the payoff of cooperating vs. defecting, too?

Yes, but if you are a cell that’s connected strongly to its neighbors, you are not able to have these kinds of computations. “Well, what if I go off on my own? I could just leave this tissue. I could go somewhere else where life is better. I could set up my own little tumor.” You can’t have those thoughts because you are so tightly wired into the rest of the network. You can’t say, “Well, I’m going to ….” There is no I; there’s we. You can only have those thoughts, “What am I going to get?” when you’re not part of the group.

But as soon as there’s carcinogen exposure or maybe an oncogene that gets expressed, the electrical connection starts to weaken. It’s a feedback loop, because the more you have those thoughts, the more you’re like, “Well, maybe let me just turn that connection down a little bit. Now I’m really coming into my own. Now I’m out of here. I’m metastasizing.”

So a carcinogen would work in this case by disrupting the bioelectrical connections.

Exactly. What we’ve done in the frog system, and we’re now moving into human cells, is to show that [electrical weakening] happens, and that you can prevent it and prevent normalized tumors by artificially forcing the electrical connection. We can shoot up a frog with strong human oncogenes and then show that, even though those are blazingly strongly expressed, there’s no tumor because you’ve intervened. You’ve forced the cells to be in electrical communication despite what the oncogene is trying to get it to do.

2024-01-22: Basal cognition

Regular cells—not just highly specialized brain cells such as neurons—have the ability to store information and act on it. Now Levin has shown that the cells do so by using subtle changes in electric fields as a type of memory. These revelations have put the biologist at the vanguard of a new field called basal cognition. Researchers in this burgeoning area have spotted hallmarks of intelligence—learning, memory, problem-solving—outside brains as well as within them. Basal cognition offers an escape from the trap of assuming that future intelligences must mimic the brain-centric human model. For medical specialists, there are tantalizing hints of ways to awaken cells’ innate powers of healing and regeneration. “What we are is intelligent machines made of intelligent machines made of intelligent machines all the way down.”

Animals do not get lost

the more we learn about how animals travel the more we can help them keep doing so. Knowing that salmon follow the scent of their natal stream, scientists added an odor to hatcheries and used it to lure the fish back to the Great Lakes, years after pollution levels there, now ameliorated, caused a local extinction. Knowing that peak songbird migration lasts no more than 6 or 7 days in a given area, ornithologists have led successful efforts to dim lights during the relevant time frame. Knowing that a shorebird migrating 32K km a year uses less than 2.5m2 of land along the way has helped conservationists engage in smaller, more affordable, more effective preservation.

6x aging differences

Some humans age faster than others. Variation in biological aging can be measured in midlife, but the implications of this variation are poorly understood. We tested associations between midlife biological aging and indicators of future frailty risk in the Dunedin cohort of 1037 infants born the same year and followed to age 45. Participants’ ‘Pace of Aging’ was quantified by tracking declining function in 19 biomarkers indexing the cardiovascular, metabolic, renal, immune, dental and pulmonary systems across ages 26, 32, 38 and 45 years. At age 45, participants with faster Pace of Aging had more cognitive difficulties, signs of advanced brain aging, diminished sensory–motor functions, older appearances and more pessimistic perceptions of aging. The slowest ager gained only 0.4 ‘biological years’ for each chronological year in age; in contrast, the fastest-aging participant gained nearly 2.5 biological years for every chronological year.

A Fitbit for an Elephant

Understanding energy expenditure can help scientists understand how well animals are doing and whether they are going to be able to hunt, reproduce, and survive. Wilson has used accelerometers to study all sorts of animals including sea turtles, sheep, bats, hawks, and penguins. He combines the accelerometer data with inputs from other sensors that measure temperature, magnetic force, and geolocation to understand exactly what the animal is doing and where it is. The technology allows him to track penguins as they sit on their nests, get up, waddle to the ocean, and dive in. His sensors can stay on the animals for weeks, and after he retrieves the devices, he can follow along as the penguins swim and dive and fish, all from 1000s of km away.

Immune System Arms Race

The challenge for the immune system is that mammals do not evolve as fast as viruses. How then, in the face of this disadvantage, can the immune system hope to keep pace with viral evolution? If a protein is fragile, even small changes can render it completely unable to do its job. TRIM5α is not fragile; most random mutations increased, rather than decreased, the protein’s ability to prevent viral infection. TRIM5α can readily gain antiviral activity and, once gained, does not lose it easily during subsequent mutation.

2022-12-02: And new infections can be filmed

The early stages of the virus–cell interaction have long evaded observation by existing microscopy methods due to the rapid diffusion of virions in the extracellular space and the large 3D cellular structures involved. We present an active-feedback single-particle tracking method with simultaneous volumetric imaging of the live cell environment called 3D-TrIm to address this knowledge gap. 3D-TrIm captures the extracellular phase of the infectious cycle in what we believe is unprecedented detail. We report previously unobserved phenomena in the early stages of the virus–cell interaction, including skimming contact events at the millisecond timescale, orders of magnitude change in diffusion coefficient upon binding and cylindrical and linear diffusion modes along cellular protrusions. We demonstrate how this method can move single-particle tracking from simple monolayer culture toward more tissue-like conditions by tracking single virions in tightly packed epithelial cells. This multiresolution method presents opportunities for capturing fast, 3D processes in biological systems.

Single cell learning

The question of whether single cells can learn led to much debate in the early 20th century. The view prevailed that they were capable of non-associative learning but not of associative learning, such as Pavlovian conditioning. Experiments indicating the contrary were considered either non-reproducible or subject to more acceptable interpretations. Recent developments suggest that the time is right to reconsider this consensus.