Open AccessComputational Model of Secondary Palate Fusion and Disruption
Author(s) -
M. Shane Hutson,
Maxwell C.K. Leung,
Nancy Baker,
Richard M. Spencer,
Thomas B. Knudsen
Publication year - 2017
Publication title -
chemical research in toxicology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.031
H-Index - 156
eISSN - 1520-5010
pISSN - 0893-228X
DOI - 10.1021/acs.chemrestox.6b00350
Subject(s) - cell fusion , fusion , microbiology and biotechnology , bone morphogenetic protein , multicellular organism , biology , phenotype , cell , chemistry , neuroscience , genetics , linguistics , philosophy , gene
Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from chemical-induced cellular alterations, we built a multicellular agent-based model in CompuCell3D that recapitulates the cellular networks and collective cell behavior underlying growth and fusion of the mammalian secondary palate. The model incorporated multiple signaling pathways (TGFβ, BMP, FGF, EGF, and SHH) in a biological framework to recapitulate morphogenetic events from palatal outgrowth through midline fusion. It effectively simulated higher-level phenotypes (e.g., midline contact, medial edge seam (MES) breakdown, mesenchymal confluence, and fusion defects) in response to genetic or environmental perturbations. Perturbation analysis of various control features revealed model functionality with respect to cell signaling systems and feedback loops for growth and fusion, diverse individual cell behaviors and collective cellular behavior leading to physical contact and midline fusion, and quantitative analysis of the TGF/EGF switch that controls MES breakdown-a key event in morphogenetic fusion. The virtual palate model was then executed with theoretical chemical perturbation scenarios to simulate switch behavior leading to a disruption of fusion following chronic (e.g., dioxin) and acute (e.g., retinoic acid) chemical exposures. This computer model adds to similar systems models toward an integrative "virtual embryo" for simulation and quantitative prediction of adverse developmental outcomes following genetic perturbation and/or environmental disruption.