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Signaling pathways as linear transmitters

Nunns, Harry and Goentoro, Lea (2018) Signaling pathways as linear transmitters. eLife, 7 . Art. No. e33617. ISSN 2050-084X. PMCID PMC6202053. doi:10.7554/eLife.33617.

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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, MAPK/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.

Item Type:Article
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URLURL TypeDescription CentralArticle
Goentoro, Lea0000-0002-3904-0195
Additional Information:© 2018 Nunns & Goentoro. 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. Received: 16 November 2017; Accepted: 09 September 2018; Published: 19 September 2018. We would like to thank Rob Oania for providing advice on experiments, Michael Abrams, Christopher Frick, Kibeom Kim, and Noah Olsman for comments on the manuscript, and Michael Elowitz and Richard Murray for discussions on the study. The authors declare that no competing interests exist. Funding: James S. McDonnell Foundation (220020365); National Science Foundation (NSF.145863); National Institutes of Health (5T32GM007616-37). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Funding AgencyGrant Number
James S. McDonnell Foundation220020365
NIH Predoctoral Fellowship5T32GM007616-37
PubMed Central ID:PMC6202053
Record Number:CaltechAUTHORS:20180924-140331977
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:89893
Deposited By: Tony Diaz
Deposited On:24 Sep 2018 22:47
Last Modified:16 Nov 2021 00:39

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