MorphoGrad: A MATLAB toolbox for simulating steady-state morphogen gradients under cell-to-cell variability.

Area of Science:

• Developmental biology
• Computational biology
• Systems biology

Background:

• Accurately modeling morphogen gradients in silico is crucial for understanding tissue patterning.
• Biological variability at the cellular level presents a significant challenge for computational models.

Purpose of the Study:

• To present a MATLAB-based protocol for simulating steady-state morphogen gradients in 1D and 2D tissues.
• To incorporate and analyze cell-to-cell variability in model parameters within these simulations.

Main Methods:

• Development of a MATLAB protocol detailing steps for simulation setup.
• Configuration of cell-based geometries and reaction-diffusion equations.
• Implementation of stochastic parameter variability and analysis of resulting gradients.

Main Results:

• Successful simulation of steady-state morphogen gradients in silico.
• Quantification of patterning precision under conditions of stochastic parameter variability.
• Demonstration of the protocol's applicability to both one- and two-dimensional tissue models.

Conclusions:

• The developed protocol provides a robust framework for in silico study of morphogen gradient dynamics.
• Accounting for cell-to-cell variability is essential for realistic simulations of tissue patterning.
• This tool aids in dissecting the contribution of parameter stochasticity to developmental robustness.