British scientist Alan Turing (1912-1954) contributed to the mathematical biology with the publication in 1952 of a single article (The Chemical Basis for Morphogenesis in Philosophical Transactions of the Royal Society of London) which led to the development of all a new area of research related to the creation of patterns in nature.

The mathematical discovered a system of two molecules that could, at least in theory, create patterns of spots or stripes if the molecules were diffused and chemically interact in a certain way.

formation of the fingers

The mathematical equations showed that, on a uniformity condition (e.g. a homogeneous distribution without patterns or designs), these molecules could self-organize spontaneously concentration in a repeating pattern. This theory has been accepted as an explanation of simple patterns such as spots or even zebras ridges that form in sand dunes, but in the field of embryology had not served as a satisfactory explanation of how structures form like fingers.

Now a group of researchers from the Laboratory of Biology of Multicellular Systems Center for Genomic Regulation (CRG), coordinated by James Sharpe, co-author, has achieved the much coveted enough data to confirm that the fingers and toes are modeled described by the Turing mechanism.

“This study complements an earlier one by the same group showing that the Hox genes and fibroblast growth factor (FGF) followed a hypothetical Turing pattern. However, at that time Turing molecules had not been identified yet and the key piece of the puzzle was still undiscovered. This new study solves the puzzle by showing how molecules act as the scientist predicted,” says James Sharpe.

The approach to the problem is performed using systems biology. The researchers combined data discovered in the experimental work on data from the mathematical model. Thus, the first study authors were able to verify his hypothesis based on empirical data and theoretical data. The work provided experimental data to the model and computer simulations gave predictions that should be tested with experiments.

Two key metabolic pathways

In reviewing the expression of certain genes, the researchers found two pathways that were eligible: BMP and WNT. Gradually building were minimal mathematical model compatible with the data and found that the two pathways were related through a molecule, the transcription factor Sox9.

Then calculated the effects of the inhibition of these pathways, either individually or by combination of both, predicting the change in the pattern of the fingers (predicted few fingers would have the embryo). When the same experiments were performed on the tips of limbs cultured in a petri dish, the same alterations were observed in finger patterns that were observed in the computer model.

This result effectively solves a question from the field of embryology, but its consequences affect many areas beyond the limb development. It allows a discussion of how the millions of cells in our body are able to self-organize into a three dimensional structure. Challenges as the domain of a deeply rooted idea called “positional information”, which says that the cells know what to do because they receive information about their coordinates in space (such as longitude and latitude on a map land).

The study published today highlights that, on the contrary, the local mechanisms of self-organization are more important than previously thought. Fully understand the organization of a multicellular organism is essential if we are to develop effective strategies for regenerative medicine and for example, to create a day of replacement tissues for our body. In the short term, these results explain why polydactyly, developing fingers more in hands and feet, it is a very common defect in humans: we now know that the system of Turing is accurate about the same as the alternative model in regulating the number of spots, stripes, fingers or any pattern.

According to the authors, the question of how an embryo seems to be related to computer problems or algorithms that are more related to Turing develops. However, responding to their legitimate interests by understanding the complex and ingenious machines in all of nature. In a way, Turing sought algorithms that life used to thrive. This study has confirmed a theory of embryology proposed 62 years ago, brings together the two greatest scientific interests.