Accurate information transmission through dynamic biochemical signaling networks

Author:

Selimkhanov Jangir1,Taylor Brooks1,Yao Jason2,Pilko Anna2,Albeck John3,Hoffmann Alexander45,Tsimring Lev46,Wollman Roy247

Affiliation:

1. Department of Bioengineering, University of California–San Diego, La Jolla, CA 92093, USA.

2. Department of Chemistry and Biochemistry, University of California–San Diego, La Jolla, CA 92093, USA.

3. Department of Molecular and Cellular Biology, University of California–Davis, Davis 95616, USA.

4. San Diego Center for Systems Biology, La Jolla, CA 92093, USA.

5. Institute for Quantitative and Computational Biosciences and Department of Microbiology, Immunology, and Molecular Genetics, University of California–Los Angeles, Los Angeles, CA 90025, USA.

6. BioCircuits Institute, University of California–San Diego, La Jolla, CA 92093, USA.

7. Cell and Developmental Biology Section, Division of Biological Sciences, University of California–San Diego, La Jolla, CA 92093, USA.

Abstract

Stochasticity inherent to biochemical reactions (intrinsic noise) and variability in cellular states (extrinsic noise) degrade information transmitted through signaling networks. We analyzed the ability of temporal signal modulation—that is, dynamics—to reduce noise-induced information loss. In the extracellular signal–regulated kinase (ERK), calcium (Ca 2+ ), and nuclear factor kappa-B (NF-κB) pathways, response dynamics resulted in significantly greater information transmission capacities compared to nondynamic responses. Theoretical analysis demonstrated that signaling dynamics has a key role in overcoming extrinsic noise. Experimental measurements of information transmission in the ERK network under varying signal-to-noise levels confirmed our predictions and showed that signaling dynamics mitigate, and can potentially eliminate, extrinsic noise–induced information loss. By curbing the information-degrading effects of cell-to-cell variability, dynamic responses substantially increase the accuracy of biochemical signaling networks.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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