Signaling pathways as linear transmitters
Abstract
One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2 and 3.
Article and author information
Author details
Funding
James S. McDonnell Foundation (220020365)
- Lea Goentoro
National Science Foundation (NSF.145863)
- Lea Goentoro
National Institutes of Health (5T32GM007616-37)
- Harry Nunns
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Wenying Shou, Fred Hutchinson Cancer Research Center, United States
Version history
- Received: November 16, 2017
- Accepted: September 9, 2018
- Accepted Manuscript published: September 17, 2018 (version 1)
- Accepted Manuscript updated: September 18, 2018 (version 2)
- Accepted Manuscript updated: September 19, 2018 (version 3)
- Version of Record published: October 25, 2018 (version 4)
Copyright
© 2018, Goentoro & Nunns
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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