Scientists are creating a new class of “Turing patterns” in E. coli colonies

Scientists have shown how a new class of Turing patterns works using synthetic biology to create them from scratch in the lab.

Shortly before his death, Alan Turing published a provocative paper in which he set out his theory of how complex, irregular patterns appear in nature – his version of how a leopard got its place. These so-called Turing patterns have been observed in physics and chemistry, and there is growing evidence that they also occur in biological systems. Now a team of Spanish scientists has managed to adapt E. coli in the laboratory, so that the colonies show Turing branching patterns, according to a recent paper published in the journal Synthetic Biology.

“Using synthetic biology, we have a unique opportunity to examine biological structures and their generative potential,” said co-author Ricard Solé of Pompeu Fabra University in Barcelona, ​​Spain, who is also an external professor at the Santa Fe Institute. “Are the observed mechanisms found in nature to create patterns, the only solution to generate them, or are there alternatives?” (Synthetic biology usually involves merging pieces of DNA – which can be found in other organisms and which are completely new – and inserting them into the organism’s genome.)

In synthetic biology, scientists usually connect long pieces of DNA and insert them into the organism’s genome. These synthesized parts of DNA may be genes found in other organisms or they could be completely new.

As we reported earlier, Turing tried to understand how natural, not random patterns (such as zebra stripes or leopard spots) emerge, and in his basic 1952 paper he focused on chemicals known as morphogens. He devised a mechanism that involves the interaction between an activator chemical that expresses a unique characteristic (such as a tiger stripe) and an inhibitor chemical that occasionally activates to stop activator expression.

Both the activator and the inhibitor diffuse through the system, much like gas atoms in a closed box will do. It’s a bit like injecting drops of black ink into a glass of water. Usually this would stabilize the system: the water would gradually become uniformly gray. But if the inhibitor diffuses faster than the activator, the process is destabilized. This mechanism will create the so-called “Turing pattern:” spots (like a leopard) or stripes (like a tiger).

James Murray, emeritus professor of mathematical biology at Oxford University and an applied mathematician at Princeton, envisioned a field of dry grass dotted with locusts for an article I wrote back in 2013 for Quanta:

If the grass had been set on fire at several random points and there had been no moisture to prevent the flames, Murray said, the fires would have burned the entire field. If this scenario were to play out like a Turing mechanism, the heat from the flames that would engulf it would cause the sweat of some of the fleeing locusts to sweat, moistening the grass around them and thus creating periodically unburned spots in the otherwise burnt field.

Scientists have tried to apply this basic concept to many different types of systems. For example, neurons in the brain can serve as activators and inhibitors, depending on whether they amplify or dampen the firing of other nearby neurons – probably the reason we see certain patterns when we hallucinate. There is evidence of Turing mechanisms acting on zebra-fish stripes, spacing between hair follicles in mice, feather buds on bird skin, mouse palate ridges, and digits on mouse paws. Certain species of Mediterranean ants accumulate dead ant bodies into structures that appear to show Turing patterns, and there is evidence of Turing patterns in the movement of Aztec ant colonies on coffee farms in Mexico.

It is basically a kind of symmetry break. Either two processes acting as activator and inhibitor will produce periodic patterns and can be modeled using the Turing diffusion function. The challenge ranges from Turing’s, albeit simplified model, to the precise determination of the mechanisms that serve as activators and inhibitors. This is especially challenging in biology, where scientists want to shed more light on the question of how a complex embryo can emerge from tissue that is completely homogeneous.

E. coli formation of Turing patterns. “> E. coli formation of Turing patterns. “src =” https://cdn.arstechnica.net/wp-content/uploads/2021/02/turing1-640×370.jpg “width =” 640 “height =” 370 “srcset =” https: / /cdn.arstechnica .net / wp-content / uploads / 2021/02 / turing1.jpg 2x “/>
Zoom in / Petri dish with constructed E. coli formation of Turing patterns.

Ricard Solé

For this latest study, Solé and his collaborators decided to work with colonies E. coli, by genetic engineering of bacteria to introduce a mechanism for generating spatial patterns. “We wanted to build a break in symmetry like never seen before in the colonies E. coli, but it is seen on animal samples and then to discover what essential ingredients are needed to create these patterns, ”said co-author Salva Duran-Nebreda, now a postdoc at the Evolutiva Institute of Biology in Barcelona.

They found inspiration in the basic mechanisms of how ants and termites build their nests. Their modified E. coli the system consisted of three critical components: groups of cells of regular size that normally divided and diffused (activator); a group of elongated cells incapable of division or diffusion (inhibitor); and a molecule known as a lactone that helps regulate gene expression in E. coli, enabling them to communicate through so-called quorum detection.

They researchers observed how the colony grew and evolved. The shape began as a circle, but as the days wore on and kept expanding outward, the colony began to sprout regularly arranged “branches” around the edge, according to Turing’s theory – like a flower with petals

“We saw that by modulating the three ingredients we could cause a symmetry violation. Basically, we changed cell division, cell adhesion and the ability to communicate over long distances (quorum feeling), or perception when there is a collective decision,” Duran-Nebreda said.

The authors hope to apply their findings to other biological systems, such as social insects. Their work provides a “new conceptual framework for creating Turing-like patterns in microbial communities, and the importance of this study goes far beyond this specific implementation,” Solé said. “We doubt that in the complexity of intertwined genetic interactions lies the kind of principle of self-organization that Turing envisioned.”

DOI: Synthetic Biology, 2021. 10.1021 / acssynbio.0c00318 (About DOIs).

Picture on the Ricard Solé list

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