An information-theoretic framework for deciphering pleiotropic and noisy biochemical signaling
File(s)
Published version
Author(s)
Jetka, Tomasz
Nienałtowski, Karol
Filippi, Sarah
Stumpf, Michael
Komorowski, Michal
Type
Journal Article
Abstract
Many components of signaling pathways are functionally pleiotropic, and signaling responses are marked with substantial cell-to-cell heterogeneity. Therefore, biochemical descriptions of signaling require quantitative support to explain how complex stimuli (inputs) are encoded in distinct activities of pathways effectors (outputs). A unique perspective of information theory cannot be fully utilized due to lack of modeling tools that account for the complexity of biochemical signaling, specifically for multiple inputs and outputs. Here, we develop a modeling framework of information theory that allows for efficient analysis of models with multiple inputs and outputs; accounts for temporal dynamics of signaling; enables analysis of how signals flow through shared network components; and is not restricted by limited variability of responses. The framework allows us to explain how identity and quantity of type I and type III interferon variants could be recognized by cells despite activating the same signaling effectors.
Date Issued
2018-11-02
Date Acceptance
2018-10-12
Citation
Nature Communications, 2018, 9
ISSN
2041-1723
Publisher
Nature Publishing Group
Journal / Book Title
Nature Communications
Volume
9
Copyright Statement
© 2018 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Sponsor
Biotechnology and Biological Sciences Research Council (BBSRC)
Grant Number
BB/G020434/1
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
KINETIC DIFFERENCES
SINGLE CELLS
INTERFERON
DYNAMICS
EXPRESSION
PATHWAY
CAPACITY
HEPATOCYTES
SENSITIVITY
NETWORKS
MD Multidisciplinary
Publication Status
Published
Article Number
ARTN 4591