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The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks

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  • Michael Chevalier
  • Ophelia Venturelli
  • Hana El-Samad

Abstract

Stochastic fluctuations in signaling and gene expression limit the ability of cells to sense the state of their environment, transfer this information along cellular pathways, and respond to it with high precision. Mutual information is now often used to quantify the fidelity with which information is transmitted along a cellular pathway. Mutual information calculations from experimental data have mostly generated low values, suggesting that cells might have relatively low signal transmission fidelity. In this work, we demonstrate that mutual information calculations might be artificially lowered by cell-to-cell variability in both initial conditions and slowly fluctuating global factors across the population. We carry out our analysis computationally using a simple signaling pathway and demonstrate that in the presence of slow global fluctuations, every cell might have its own high information transmission capacity but that population averaging underestimates this value. We also construct a simple synthetic transcriptional network and demonstrate using experimental measurements coupled to computational modeling that its operation is dominated by slow global variability, and hence that its mutual information is underestimated by a population averaged calculation.Author Summary: This work demonstrates how different sources of variability within biochemical networks impact the interpretation of information transmission. These sources are the intrinsic noise generated within the pathway of a single cell, variability due to initial conditions and/or global parameters across the population. A theoretical analysis of a simple signaling pathway and experimental exploration of a synthetic circuit are used to discuss the contributions of these sources of variability to information transmission using mutual information as a metric.

Suggested Citation

  • Michael Chevalier & Ophelia Venturelli & Hana El-Samad, 2015. "The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-21, October.
  • Handle: RePEc:plo:pcbi00:1004462
    DOI: 10.1371/journal.pcbi.1004462
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    1. Richard C. Yu & C. Gustavo Pesce & Alejandro Colman-Lerner & Larry Lok & David Pincus & Eduard Serra & Mark Holl & Kirsten Benjamin & Andrew Gordon & Roger Brent, 2008. "Negative feedback that improves information transmission in yeast signalling," Nature, Nature, vol. 456(7223), pages 755-761, December.
    2. Ioannis Lestas & Glenn Vinnicombe & Johan Paulsson, 2010. "Fundamental limits on the suppression of molecular fluctuations," Nature, Nature, vol. 467(7312), pages 174-178, September.
    3. Alejandro Colman-Lerner & Andrew Gordon & Eduard Serra & Tina Chin & Orna Resnekov & Drew Endy & C. Gustavo Pesce & Roger Brent, 2005. "Regulated cell-to-cell variation in a cell-fate decision system," Nature, Nature, vol. 437(7059), pages 699-706, September.
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    Cited by:

    1. Alok Maity & Roy Wollman, 2020. "Information transmission from NFkB signaling dynamics to gene expression," PLOS Computational Biology, Public Library of Science, vol. 16(8), pages 1-16, August.

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