Most of us think of DNA as being the ‘blueprint’ for the body: it encodes our personal traits, such as eye colour, as well as providing the overall instructions for cells on how to build, and repair, all of our organs. But Distinguished Professor Michael Levin of Tufts University is currently conducting research that may shift our understanding of the forces that drive such processes: and one that he and his team have identified is bioelectricity
Levin’s background was perhaps conducive to looking at the ‘software of life’ from a different angle: he began his research career by earning dual Bachelor degrees in Computer Science and Biology. And his interest in this topic was piqued by a particular mystery:
A few years ago, we found a pretty amazing phenomenon, which is that if you make so-called “Picasso frogs” – these are tadpoles where the jaws might be off to the side, the eyes are up here, the nostrils are moved, so everything is shifted – these tadpoles make largely normal frog faces.Now, this is amazing, because all of the organs start off in abnormal positions, and yet they still end up making a pretty good frog face.
And so what it turns out is that this system, like many living systems, is not a hardwired set of movements, but actually works to reduce the error between what’s going on now, and what it knows is a correct frog face configuration. This kind of decision-making, that involves flexible responses to new circumstances – in other contexts, we would call this intelligence.
And so what we need to understand now is not only the mechanisms by which these cells execute their movements and gene expression and so on, but we really have to understand the information flow: how do these cells cooperate with each other to build something large, and to stop building when that specific structure is created?
It turns out that all cells in the body – not just nerve cells – communicate with each other using electrical signals. And it is by this communication method that living systems are able to achieve specific goals, such as differentiating to build the different parts of an embryo, or regenerating limbs in animals that have this ability.
And Levin and his team have now figured out the basics of how to target and rewrite these ‘bio-software algorithms’ to make them do what researchers want them to do!
Basically, what happens is that these cells, by forming electrical networks much like networks in the brain, they form electrical networks, and these networks process information including pattern memories. They include representation of large-scale anatomical structures – where various organs will go, what the different axes of the animal, front and back, head and tail -are going to be, and these are literally held in the electrical circuits across large tissues, in the same way that brains hold other kinds of memories and learning.
So the ability to see these bioelectrical signals is giving us an entry point directly into the software that guides large-scale anatomy, which is a very different approach to medicine than to rewiring specific pathways inside of every cell.
What this means, in real-world terms, is that Levin and his research team are now able to manipulate the electrical states of groups of cells, in order to ‘program’ them to create entire, complex organs. In the video below, Levin shows off some of their work: cutting flatworms in half, and then choosing whether to regenerate the head or the tail (‘new programming’ that is then inherited by any progeny); creating entire, working eyes in the gut of tadpoles; adding extra limbs to tadpoles; and even creating a new novel life form from just the skin cells of a frog:
It’s an astounding discussion, that not only rewrites a lot of our understanding of biology, but also likely has huge implications for the future of medicine. It also makes me wonder whether this might have some explanatory potential for strange subjects like anomalistic mind-body phenomena (e.g. ‘Stigmata’ marks) and also some of the crazily specific forms of camouflage evolved by various animal species.