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Stochastic gene expression as a many-body problem.

Masaki Sasai1, Peter G Wolynes

  • 1Graduate School of Human Informatics, Nagoya University, Nagoya 464-8601, Japan.

Proceedings of the National Academy of Sciences of the United States of America
|February 28, 2003
PubMed
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Stochastic gene expression, driven by single molecules, can be modeled using quantum many-body physics. This approach reveals how network structure, particularly "frustration," influences cell type determination.

Area of Science:

  • * Theoretical biology and biophysics.
  • * Quantum mechanics and statistical physics applications in biological systems.

Background:

  • * Gene expression exhibits inherent randomness due to the low copy numbers of molecules involved.
  • * Understanding this stochasticity is crucial for comprehending cellular processes and cell fate decisions.

Purpose of the Study:

  • * To establish a framework for modeling gene expression noise using quantum many-body physics.
  • * To investigate the relationship between network topology, stochasticity, and the emergence of distinct cell states.

Main Methods:

  • * Mapping gene expression dynamics to quantum mechanical models, specifically the spin-boson model.
  • * Employing variational principles to approximate gene regulatory networks as quantum spin systems.
  • * Analyzing the concept of 'frustration' within these quantum gene network models.

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Main Results:

  • * The dynamics of single gene switches are analogous to quantum polaron or electron transfer models.
  • * Gene networks can be effectively represented as quantum spin systems.
  • * Network 'frustration' significantly impacts the landscape of stable gene expression states (attractors).
  • * Weakly frustrated networks exhibit a reduced number of attractors compared to random networks, suggesting more defined cell fates.

Conclusions:

  • * Quantum many-body physics provides a powerful theoretical lens for understanding gene expression noise.
  • * Network design, incorporating controlled frustration, can precisely regulate the number of possible cell types.
  • * This work bridges quantum physics and systems biology, offering new insights into cellular differentiation and robustness.