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Noisy signaling through promoter logic gates.

Moritz Gerstung1, Jens Timmer, Christian Fleck

  • 1Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. moritz.gerstung@bsse.ethz.ch

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|March 5, 2009
PubMed
Summary

Transcription factor noise impacts gene regulation by altering promoter element binding probabilities. This study quantifies noise effects on gene expression, revealing insights into molecular fluctuations and cis-regulatory logic.

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Biophysics

Background:

  • Gene regulation relies on transcription factor (TF) binding to cis-regulatory elements.
  • These elements function like biological logic gates, processing TF binding probabilities.
  • TF binding dynamics are inherently noisy, influencing gene expression outcomes.

Purpose of the Study:

  • To investigate how noisy TF signals affect the function of cis-regulatory promoter elements.
  • To develop a mathematical framework for quantifying noise effects on promoter occupancy.
  • To analyze the impact of different noise sources and gate architectures on gene regulation.

Main Methods:

  • Analytical solutions derived for TF binding probabilities using input functions.
  • Modeling cis-regulatory elements as biological logic gates (AND, OR).
  • Numerical simulations to validate analytical predictions and analyze the E. coli Lac operon.

Main Results:

  • TF noise causes deviations from equilibrium binding probabilities due to nonlinear input functions.
  • Single binding sites show reduced occupancy, while complex promoters depend on signal correlations and gate geometry.
  • AND gates and correlated fluctuations exhibit larger noise-induced corrections.

Conclusions:

  • A consistent mathematical method is presented to separate and quantify noise sources affecting promoter occupation.
  • Internal (Poissonian) molecular fluctuations do not contribute to the noise-induced correction, unlike external fluctuations.
  • The study provides a quantitative understanding of noise in gene regulation and its impact on biological logic gates.