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Updated: Dec 11, 2025
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NF-κB-dependent Luciferase Activation and Quantification of Gene Expression in Salmonella Infected Tissue Culture Cells
Published on: January 12, 2020
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Information transmission from NFkB signaling dynamics to gene expression
Alok Maity1, Roy Wollman1,2
1Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, California, United States of America.
Plos Computational Biology
|August 16, 2020
Summary
Cellular signaling accurately transmits information to gene expression, even with dynamic patterns. Mathematical modeling shows gene expression can preserve ligand specificity, minimizing information loss from biochemical noise.
Area of Science:
- Cellular Biology
- Systems Biology
- Biophysics
Background:
- Dynamic signaling patterns encode extracellular information for cellular responses.
- Previous studies quantified information in signaling patterns, but transmission to gene expression remains unclear.
Purpose of the Study:
- To investigate the accuracy of information transmission from dynamic signaling patterns to gene expression using NFkB signaling as a model.
- To determine information loss between receptor-level signaling and gene expression dynamics.
Main Methods:
- Utilized a detailed mathematical model to simulate realistic NFkB signaling patterns with varying variability.
- Employed a simple gene expression model to analyze information transmission from simulated NFkB patterns.
- Quantified information loss due to biochemical noise and lack of specificity.
Main Results:
- Noise-free gene expression demonstrated minimal information loss, preserving specificity in NFkB patterns.
- Introduction of noise into gene expression models resulted in information loss.
- Specific parameter choices can significantly mitigate information loss caused by biochemical noise.
Conclusions:
- Gene expression possesses a high capacity for transmitting information from dynamic signaling patterns.
- Cellular responses can maintain accuracy and ligand specificity through effective information transfer.
- Understanding information transmission is crucial for deciphering cellular decision-making processes.
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