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Mapping connections in signaling networks with ambiguous modularity

Modular Response Analysis (MRA) is a suite of methods that under certain assumptions permits the precise reconstruction of both the directions and strengths of connections between network modules from network responses to perturbations. Standard MRA assumes that modules are insulated, thereby neglec...

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Autores principales: Lill, Daniel, Rukhlenko, Oleksii S., Mc Elwee, Anthony James, Kashdan, Eugene, Timmer, Jens, Kholodenko, Boris N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533310/
https://www.ncbi.nlm.nih.gov/pubmed/31149348
http://dx.doi.org/10.1038/s41540-019-0096-1
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author Lill, Daniel
Rukhlenko, Oleksii S.
Mc Elwee, Anthony James
Kashdan, Eugene
Timmer, Jens
Kholodenko, Boris N.
author_facet Lill, Daniel
Rukhlenko, Oleksii S.
Mc Elwee, Anthony James
Kashdan, Eugene
Timmer, Jens
Kholodenko, Boris N.
author_sort Lill, Daniel
collection PubMed
description Modular Response Analysis (MRA) is a suite of methods that under certain assumptions permits the precise reconstruction of both the directions and strengths of connections between network modules from network responses to perturbations. Standard MRA assumes that modules are insulated, thereby neglecting the existence of inter-modular protein complexes. Such complexes sequester proteins from different modules and propagate perturbations to the protein abundance of a downstream module retroactively to an upstream module. MRA-based network reconstruction detects retroactive, sequestration-induced connections when an enzyme from one module is substantially sequestered by its substrate that belongs to a different module. Moreover, inferred networks may surprisingly depend on the choice of protein abundances that are experimentally perturbed, and also some inferred connections might be false. Here, we extend MRA by introducing a combined computational and experimental approach, which allows for a computational restoration of modular insulation, unmistakable network reconstruction and discrimination between solely regulatory and sequestration-induced connections for a range of signaling pathways. Although not universal, our approach extends MRA methods to signaling networks with retroactive interactions between modules arising from enzyme sequestration effects.
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spelling pubmed-65333102019-05-30 Mapping connections in signaling networks with ambiguous modularity Lill, Daniel Rukhlenko, Oleksii S. Mc Elwee, Anthony James Kashdan, Eugene Timmer, Jens Kholodenko, Boris N. NPJ Syst Biol Appl Article Modular Response Analysis (MRA) is a suite of methods that under certain assumptions permits the precise reconstruction of both the directions and strengths of connections between network modules from network responses to perturbations. Standard MRA assumes that modules are insulated, thereby neglecting the existence of inter-modular protein complexes. Such complexes sequester proteins from different modules and propagate perturbations to the protein abundance of a downstream module retroactively to an upstream module. MRA-based network reconstruction detects retroactive, sequestration-induced connections when an enzyme from one module is substantially sequestered by its substrate that belongs to a different module. Moreover, inferred networks may surprisingly depend on the choice of protein abundances that are experimentally perturbed, and also some inferred connections might be false. Here, we extend MRA by introducing a combined computational and experimental approach, which allows for a computational restoration of modular insulation, unmistakable network reconstruction and discrimination between solely regulatory and sequestration-induced connections for a range of signaling pathways. Although not universal, our approach extends MRA methods to signaling networks with retroactive interactions between modules arising from enzyme sequestration effects. Nature Publishing Group UK 2019-05-23 /pmc/articles/PMC6533310/ /pubmed/31149348 http://dx.doi.org/10.1038/s41540-019-0096-1 Text en © The Author(s) 2019 Open Access 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/.
spellingShingle Article
Lill, Daniel
Rukhlenko, Oleksii S.
Mc Elwee, Anthony James
Kashdan, Eugene
Timmer, Jens
Kholodenko, Boris N.
Mapping connections in signaling networks with ambiguous modularity
title Mapping connections in signaling networks with ambiguous modularity
title_full Mapping connections in signaling networks with ambiguous modularity
title_fullStr Mapping connections in signaling networks with ambiguous modularity
title_full_unstemmed Mapping connections in signaling networks with ambiguous modularity
title_short Mapping connections in signaling networks with ambiguous modularity
title_sort mapping connections in signaling networks with ambiguous modularity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6533310/
https://www.ncbi.nlm.nih.gov/pubmed/31149348
http://dx.doi.org/10.1038/s41540-019-0096-1
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