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Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity

BACKGROUND: The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs). RESULTS: To further examine the role of SLiM...

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Autores principales: Strome, Bob, Hsu, Ian Shenyen, Li Cheong Man, Mitchell, Zarin, Taraneh, Nguyen Ba, Alex, Moses, Alan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029073/
https://www.ncbi.nlm.nih.gov/pubmed/29970070
http://dx.doi.org/10.1186/s12918-018-0597-3
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author Strome, Bob
Hsu, Ian Shenyen
Li Cheong Man, Mitchell
Zarin, Taraneh
Nguyen Ba, Alex
Moses, Alan M.
author_facet Strome, Bob
Hsu, Ian Shenyen
Li Cheong Man, Mitchell
Zarin, Taraneh
Nguyen Ba, Alex
Moses, Alan M.
author_sort Strome, Bob
collection PubMed
description BACKGROUND: The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs). RESULTS: To further examine the role of SLiMs in signal transduction, we used a previously devised bioinformatics method to predict evolutionarily conserved SLiMs within a well-characterized pathway in S. cerevisiae. Using a single cell, reporter-based flow cytometry assay in conjunction with a fluorescent reporter driven by a pathway-specific promoter, we quantitatively assessed pathway output via systematic deletions of individual motifs. We found that, when deleted, 34% (10/29) of predicted SLiMs displayed a significant decrease in pathway output, providing evidence that these motifs play a role in signal transduction. Assuming that mutations in SLiMs have quantitative effects on mechanisms of signaling, we show that perturbations of parameters in a previously published stochastic model of HOG signaling could reproduce the quantitative effects of 4 out of 7 mutations in previously unknown SLiMs. CONCLUSIONS: Our study suggests that, even in well-characterized pathways, large numbers of functional elements remain undiscovered, and that challenges remain for application of systems biology models to interpret the effects of mutations in signaling pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0597-3) contains supplementary material, which is available to authorized users.
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spelling pubmed-60290732018-07-09 Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity Strome, Bob Hsu, Ian Shenyen Li Cheong Man, Mitchell Zarin, Taraneh Nguyen Ba, Alex Moses, Alan M. BMC Syst Biol Research Article BACKGROUND: The effort to characterize intrinsically disordered regions of signaling proteins is rapidly expanding. An important class of disordered interaction modules are ubiquitous and functionally diverse elements known as short linear motifs (SLiMs). RESULTS: To further examine the role of SLiMs in signal transduction, we used a previously devised bioinformatics method to predict evolutionarily conserved SLiMs within a well-characterized pathway in S. cerevisiae. Using a single cell, reporter-based flow cytometry assay in conjunction with a fluorescent reporter driven by a pathway-specific promoter, we quantitatively assessed pathway output via systematic deletions of individual motifs. We found that, when deleted, 34% (10/29) of predicted SLiMs displayed a significant decrease in pathway output, providing evidence that these motifs play a role in signal transduction. Assuming that mutations in SLiMs have quantitative effects on mechanisms of signaling, we show that perturbations of parameters in a previously published stochastic model of HOG signaling could reproduce the quantitative effects of 4 out of 7 mutations in previously unknown SLiMs. CONCLUSIONS: Our study suggests that, even in well-characterized pathways, large numbers of functional elements remain undiscovered, and that challenges remain for application of systems biology models to interpret the effects of mutations in signaling pathways. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12918-018-0597-3) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-03 /pmc/articles/PMC6029073/ /pubmed/29970070 http://dx.doi.org/10.1186/s12918-018-0597-3 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Strome, Bob
Hsu, Ian Shenyen
Li Cheong Man, Mitchell
Zarin, Taraneh
Nguyen Ba, Alex
Moses, Alan M.
Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity
title Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity
title_full Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity
title_fullStr Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity
title_full_unstemmed Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity
title_short Short linear motifs in intrinsically disordered regions modulate HOG signaling capacity
title_sort short linear motifs in intrinsically disordered regions modulate hog signaling capacity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029073/
https://www.ncbi.nlm.nih.gov/pubmed/29970070
http://dx.doi.org/10.1186/s12918-018-0597-3
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