Feedbacks, Receptor Clustering, and Receptor Restriction to Single Cells yield large Turing Spaces for Ligand-receptor based Turing Models

TL;DR

This paper demonstrates that receptor clustering, feedback mechanisms, and cellular receptor restrictions significantly enlarge the parameter space for ligand-receptor Turing patterns, making their biological evolution more plausible and robust.

Contribution

It reveals that cellular receptor restrictions and feedbacks greatly expand Turing spaces in ligand-receptor models, supporting their role in biological pattern formation.

Findings

Receptor clustering enlarges Turing space.

Feedback mechanisms increase pattern robustness.

Receptor restriction to single cells enhances pattern evolution.

Abstract

Turing mechanisms can yield a large variety of patterns from noisy, homogenous initial conditions and have been proposed as patterning mechanism for many developmental processes. However, the molecular components that give rise to Turing patterns have remained elusive, and the small size of the parameter space that permits Turing patterns to emerge makes it difficult to explain how Turing patterns could evolve. We have recently shown that Turing patterns can be obtained with a single ligand if the ligand-receptor interaction is taken into account. Here we show that the general properties of ligand-receptor systems result in very large Turing spaces. Thus, the restriction of receptors to single cells, negative feedbacks, regulatory interactions between different ligand-receptor systems, and the clustering of receptors on the cell surface all greatly enlarge the Turing space. We further show that the feedbacks that occur in the FGF10/SHH network that controls lung branching morphogenesis are sufficient to result in large Turing spaces. We conclude that the cellular restriction of receptors provides a mechanism to sufficiently increase the size of the Turing space to make the evolution of Turing patterns likely. Additional feedbacks may then have further enlarged the Turing space. Given their robustness and flexibility, we propose that receptor-ligand based Turing mechanisms present a general mechanism for patterning in biology.