Digit patterning during limb development as a result of the BMP-receptor interaction

Abstract

Turing models have been proposed to explain the emergence of digits during limb development. However, so far the molecular components that would give rise to Turing patterns are elusive. We have recently shown that a particular type of receptor-ligand interaction can give rise to Schnakenberg-type Turing patterns, which reproduce patterning during lung and kidney branching morphogenesis. Recent knock-out experiments have identified Smad4 as a key protein in digit patterning. We show here that the BMP-receptor interaction meets the conditions for a Schnakenberg-type Turing pattern, and that the resulting model reproduces available wildtype and mutant data on the expression patterns of BMP, its receptor, and Fgfs in the apical ectodermal ridge (AER) when solved on a realistic 2D domain that we extracted from limb bud images of E11.5 mouse embryos. We propose that receptor-ligand-based mechanisms serve as a molecular basis for the emergence of Turing patterns in many developing tissues.

References in corpus (2)

• Branch Mode Selection during Early Lung Development
• Simulating Organogenesis in COMSOL

Cited by in corpus (12)

• LBIBCell: A Cell-Based Simulation Environment for Morphogenetic Problems
• Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes
• Perspectives on the mathematics of biological patterning and morphogenesis
• Feedbacks, Receptor Clustering, and Receptor Restriction to Single Cells yield large Turing Spaces for Ligand-receptor based Turing Models
• Inter-dependent Tissue Growth and Turing Patterning in a Model for Long Bone Development
• Numerical approximation of a mechanochemical interface model for skin appendage
• Simulating Organogenesis in COMSOL: Parameter Optimization for PDE-based models
• Simulating Organogenesis in COMSOL: Cell-based Signaling Models
• Simulating Organogenesis in COMSOL: Image-based Modeling
• Optimizing Bone Scaffold Porosity Distributions
• Growth Mode Selection of Radially Growing Turing Patterns
• Simulating Organogenesis: Algorithms for the Image-based Determination of Displacement Fields