ZFIN ID: ZDB-PUB-191128-6
Evaluation of BMP-mediated patterning in a 3D mathematical model of the zebrafish blastula embryo
Li, L., Wang, X., Mullins, M.C., Umulis, D.M.
Date: 2019
Source: Journal of mathematical biology   80(1-2): 505-520 (Journal)
Registered Authors: Mullins, Mary C.
Keywords: BMP, Morphogen gradient, PDE, Pattern formation, Zebrafish
MeSH Terms:
  • Animals
  • Blastula/embryology*
  • Body Patterning/physiology*
  • Bone Morphogenetic Proteins/metabolism*
  • Glycoproteins/metabolism
  • Intercellular Signaling Peptides and Proteins/metabolism
  • Models, Biological*
  • Signal Transduction/physiology
  • Spatio-Temporal Analysis
  • Zebrafish/embryology
  • Zebrafish/genetics
  • Zebrafish Proteins/metabolism*
PubMed: 31773243 Full text @ J. Math. Biol.
Bone Morphogenetic Proteins (BMPs) play an important role in dorsal-ventral (DV) patterning of the early zebrafish embryo. BMP signaling is regulated by a network of extracellular and intracellular factors that impact the range and signaling of BMP ligands. Recent advances in understanding the mechanism of pattern formation support a source-sink mechanism, however it is not clear how the source-sink mechanism shapes patterns in 3D, nor how sensitive the pattern is to biophysical rates and boundary conditions along both the anteroposterior (AP) and DV axes of the embryo. We propose a new three-dimensional growing Partial Differential Equation (PDE)-based model to simulate the BMP patterning process during the blastula stage. This model provides a starting point to elucidate how different mechanisms and components work together in 3D to create and maintain the BMP gradient in the embryo. We also show how the 3D model fits the BMP signaling gradient data at multiple time points along both axes. Furthermore, sensitivity analysis of the model suggests that the spatiotemporal patterns of Chordin and BMP ligand gene expression are dominant drivers of shape in 3D and more work is needed to quantify the spatiotemporal profiles of gene and protein expression to further refine the models.