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Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation

The role of pro-inflammatory macrophage activation in cardiovascular disease (CVD) is a complex one amenable to network approaches. While an indispensible tool for elucidating the molecular underpinnings of complex diseases including CVD, the interactome is limited in its utility as it is not specif...

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Autores principales: Halu, Arda, Wang, Jian-Guo, Iwata, Hiroshi, Mojcher, Alexander, Abib, Ana Luisa, Singh, Sasha A, Aikawa, Masanori, Sharma, Amitabh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6179386/
https://www.ncbi.nlm.nih.gov/pubmed/30303482
http://dx.doi.org/10.7554/eLife.37059
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author Halu, Arda
Wang, Jian-Guo
Iwata, Hiroshi
Mojcher, Alexander
Abib, Ana Luisa
Singh, Sasha A
Aikawa, Masanori
Sharma, Amitabh
author_facet Halu, Arda
Wang, Jian-Guo
Iwata, Hiroshi
Mojcher, Alexander
Abib, Ana Luisa
Singh, Sasha A
Aikawa, Masanori
Sharma, Amitabh
author_sort Halu, Arda
collection PubMed
description The role of pro-inflammatory macrophage activation in cardiovascular disease (CVD) is a complex one amenable to network approaches. While an indispensible tool for elucidating the molecular underpinnings of complex diseases including CVD, the interactome is limited in its utility as it is not specific to any cell type, experimental condition or disease state. We introduced context-specificity to the interactome by combining it with co-abundance networks derived from unbiased proteomics measurements from activated macrophage-like cells. Each macrophage phenotype contributed to certain regions of the interactome. Using a network proximity-based prioritization method on the combined network, we predicted potential regulators of macrophage activation. Prediction performance significantly increased with the addition of co-abundance edges, and the prioritized candidates captured inflammation, immunity and CVD signatures. Integrating the novel network topology with transcriptomics and proteomics revealed top candidate drivers of inflammation. In vitro loss-of-function experiments demonstrated the regulatory role of these proteins in pro-inflammatory signaling.
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spelling pubmed-61793862018-10-17 Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation Halu, Arda Wang, Jian-Guo Iwata, Hiroshi Mojcher, Alexander Abib, Ana Luisa Singh, Sasha A Aikawa, Masanori Sharma, Amitabh eLife Computational and Systems Biology The role of pro-inflammatory macrophage activation in cardiovascular disease (CVD) is a complex one amenable to network approaches. While an indispensible tool for elucidating the molecular underpinnings of complex diseases including CVD, the interactome is limited in its utility as it is not specific to any cell type, experimental condition or disease state. We introduced context-specificity to the interactome by combining it with co-abundance networks derived from unbiased proteomics measurements from activated macrophage-like cells. Each macrophage phenotype contributed to certain regions of the interactome. Using a network proximity-based prioritization method on the combined network, we predicted potential regulators of macrophage activation. Prediction performance significantly increased with the addition of co-abundance edges, and the prioritized candidates captured inflammation, immunity and CVD signatures. Integrating the novel network topology with transcriptomics and proteomics revealed top candidate drivers of inflammation. In vitro loss-of-function experiments demonstrated the regulatory role of these proteins in pro-inflammatory signaling. eLife Sciences Publications, Ltd 2018-10-10 /pmc/articles/PMC6179386/ /pubmed/30303482 http://dx.doi.org/10.7554/eLife.37059 Text en © 2018, Halu et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Halu, Arda
Wang, Jian-Guo
Iwata, Hiroshi
Mojcher, Alexander
Abib, Ana Luisa
Singh, Sasha A
Aikawa, Masanori
Sharma, Amitabh
Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
title Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
title_full Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
title_fullStr Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
title_full_unstemmed Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
title_short Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
title_sort context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6179386/
https://www.ncbi.nlm.nih.gov/pubmed/30303482
http://dx.doi.org/10.7554/eLife.37059
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