Scientists have shown how a new class of Turing patterns works by creating them from scratch in the laboratory using synthetic biology.
Shortly before his death, Alan Turing published a provocative paper in which he set out his theory of how complex, irregular patterns arise in nature – his version of how the leopard got its spots. These so-called Turing patterns have been observed in physics and chemistry, and there is increasing evidence that they also occur in biological systems. A team of Spanish scientists has now succeeded in optimizing E. coli in the laboratory so that the colonies have branched Turing patterns. This is evident from an article recently published in the journal Synthetic Biology.
"By using synthetic biology, we have a unique opportunity to study biological structures and their generative potential," said co-author Ricard Solé from the Universitat Pompeu Fabra in Barcelona, Spain, who is also an external professor at the Santa Fe Institute . "Are the patterns-generating mechanisms observed in nature the only solutions for generating them, or are there alternatives?" (Synthetic biology usually involves stitching together sections of DNA that are completely new in other organisms and inserting them into the genome of one organism.)
In synthetic biology, scientists usually sew long pieces of DNA together and insert them into the genome of an organism. These synthesized pieces of DNA could be genes found in other organisms or they could be entirely new.
As we previously reported, Turing sought to understand how natural, not random, patterns arise (like the stripes on a zebra or the spots on a leopard), and in his seminal 1952 work focused on chemicals known as morphogens. He developed a mechanism that involves the interaction between an activator chemical that expresses a unique property (like a tiger stripe) and an inhibitor chemical that occurs periodically to disrupt the expression of the activator.
Both activator and inhibitor diffuse through a system, much like gas atoms do in a closed box. It's a bit like squirting a drop of black ink into a beaker of water. Normally this would stabilize a system: the water would gradually turn an even gray. However, if the inhibitor diffuses faster than the activator, the process is destabilized. This mechanism creates what is known as a "Turing pattern": spots (like a leopard) or stripes (like a tiger).
James Murray, Professor Emeritus of Mathematical Biology at Oxford University and an applied mathematician at Princeton, imagined a field of dry grass with locusts for an article I wrote for Quanta in 2013:
If the grass were set on fire in multiple random locations and there was no moisture to contain the flames, the fires would strain the entire field, Murray said. However, if this scenario played out like a Turing Mechanism, the heat from the penetrating flames would cause some of the fleeing locusts to sweat, dampening the grass around them, and thereby regularly creating unburned spots in the otherwise burned field.
Scientists have tried to apply this basic concept to many different types of systems. For example, neurons in the brain could act as activators and inhibitors, depending on whether they increase or decrease the burning of other nearby neurons – possibly why we see certain patterns when we hallucinate. There is evidence of Turing mechanisms in zebrafish strips, the distance between hair follicles in mice, feather buds on the skin of a bird, the ridges on the roof of a mouse, and the numbers on the paw of a mouse. Certain species of Mediterranean ants will pile the ants' bodies in structures that appear to have Turing patterns, and there is evidence of Turing patterns in the movement of Azteca ant colonies on coffee farms in Mexico.
Essentially, it is a kind of symmetry breaking. Any two processes that act as activator and inhibitor generate periodic patterns and can be modeled using Turing's diffusion function. The challenge is to switch from Turing's admittedly simplified model to determine the exact mechanisms that serve in the activator and inhibitor roles. This is particularly challenging in biology, where scientists want to shed more light on how a complex embryo can be created from completely homogeneous tissue.
<img alt = "Petri dish with engineered E. coli Form Turing pattern. "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 "/> enlarge /. Petri dish with engineered E. coli that form Turing patterns.
For this latest study, Solé and his co-workers chose to work with colonies of E. coli, genetically engineered the bacteria to introduce a mechanism to create spatial patterns. "We wanted to build symmetry breaking that are never seen in E. coli colonies but can be seen in animal specimens, and then figure out what essential ingredients are needed to create those patterns," said co-author Salva Duran-Nebreda, now Postdoc at the Institut de Biologia Evolutiva in Barcelona.
They found inspiration in the underlying mechanisms of how ants and termites build their nests. Your altered E. coli system consisted of three critical components: a group of normal size cells that divided and diffused normally (the activator); a group of elongated cells that cannot divide or diffuse (the inhibitor); and a molecule known as lactone that regulates gene expression in E. coli and allows them to communicate using what is known as quorum sensing.
They watched the researchers as the colony grew and developed. The shape started out as a circle, but as the days went by, and after spreading outward, the colony sprouted regularly spaced "branches" around the edge, like a flower with petals, according to Turing's theory
"We have seen that we can induce symmetry breaks by modulating three ingredients. In essence, we have changed cell division, adhesion between cells and the ability to communicate at a distance (quorum sensing), that is, we have perceived when a collective decision is made," said Duran-Nebreda .
The authors hope to be able to transfer their findings to other biological systems such as social insects. Her work "provides a new conceptual framework for creating Turing-like patterns in microbial communities, and the relevance of this study goes well beyond this specific implementation," said Solé. "We suspect that the complexities of intricate gene interactions conceal the principles of self-organization envisaged by Turing."
DOI: Synthetic Biology, 2021. 10.1021 / acssynbio.0c00318 (About DOIs).
Listing picture by Ricard Solé