An information-theoretic framework for deciphering pleiotropic and noisy biochemical signaling

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...

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Bibliographic Details
Published in:Nature communications 2018-11, Vol.9 (1), p.4591-9, Article 4591
Main Authors: Jetka, Tomasz, Nienałtowski, Karol, Filippi, Sarah, Stumpf, Michael P. H., Komorowski, Michał
Format: Article
Language:English
Subjects:
631/250/127/1212
631/553/1044
631/553/1806
631/553/2708
631/553/2709
Biochemistry
Coding
Complexity
Effectors
Genetic Pleiotropy
Heterogeneity
Humanities and Social Sciences
Information Theory
Interferon
Interferon Type I - metabolism
Interferons - metabolism
Kinetics
Modelling
Models, Biological
multidisciplinary
Science
Science (multidisciplinary)
Signal Transduction
Signaling
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Summary: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. Signalling responses are marked by substantial cell-to-cell variability. Here, the authors propose an information theoretic framework that accounts for multiple inputs and temporal dynamics to analyse how signals flow through shared network components.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-018-07085-1