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A cell cycle model for somitogenesis: mathematical formulation and numerical simulation.

J R Collier1, D Mcinerney, S Schnell

  • 1Centre for Mathematical Biology, Mathematical Institute, 24-29, St Giles', Oxford, OX1 3LB, U.K.

Journal of Theoretical Biology
|November 18, 2000
PubMed
Summary
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This study models embryonic development, proposing a cell cycle window gates somite formation. The mathematical model explains normal development and heat shock-induced abnormalities in somitogenesis.

Area of Science:

  • Developmental biology
  • Mathematical modeling
  • Cell cycle research

Background:

  • Somitogenesis, the formation of embryonic segments (somites), remains a key unresolved problem in developmental biology.
  • Existing models struggle to fully explain the periodic patterning of somite formation along the embryonic axis.

Purpose of the Study:

  • To present a mathematical formulation of a cell cycle model for somitogenesis.
  • To explain the discrete, periodic formation of somites during embryonic development.
  • To account for developmental abnormalities caused by external factors like heat shock.

Main Methods:

  • Developing a mathematical model based on the cell cycle of somite precursor cells.
  • Hypothesizing a specific time window within the cell cycle that gates pre-somite cells.

Related Experiment Videos

  • Analyzing the model's ability to simulate both normal somitogenesis and abnormal patterns.

    • Main Results:

    • The cell cycle model successfully explains the spatiotemporal patterning of somite formation.
    • The model accounts for periodic abnormalities in somitogenesis observed after heat shock treatment.
    • The model aligns with recent molecular data concerning somite formation.

    Conclusions:

    • A specific cell cycle gating mechanism can explain the discrete, periodic nature of somitogenesis.
    • The mathematical model provides a robust framework for understanding normal and abnormal embryonic segmentation.
    • This work integrates mathematical modeling with molecular data to advance the field of developmental biology.