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Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins

BACKGROUND: RASopathies are a group of syndromes showing clinical overlap caused by mutations in genes affecting the RAS-MAPK pathway. Consequent disruption on cellular signaling leads and is driven by phosphoproteome remodeling. However, we still lack a comprehensive picture of the different key pl...

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Autores principales: Montero-Bullón, Javier-Fernando, González-Velasco, Óscar, Isidoro-García, María, Lacal, Jesus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8258961/
https://www.ncbi.nlm.nih.gov/pubmed/34229750
http://dx.doi.org/10.1186/s13023-021-01934-x
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author Montero-Bullón, Javier-Fernando
González-Velasco, Óscar
Isidoro-García, María
Lacal, Jesus
author_facet Montero-Bullón, Javier-Fernando
González-Velasco, Óscar
Isidoro-García, María
Lacal, Jesus
author_sort Montero-Bullón, Javier-Fernando
collection PubMed
description BACKGROUND: RASopathies are a group of syndromes showing clinical overlap caused by mutations in genes affecting the RAS-MAPK pathway. Consequent disruption on cellular signaling leads and is driven by phosphoproteome remodeling. However, we still lack a comprehensive picture of the different key players and altered downstream effectors. METHODS: An in silico interactome of RASopathy proteins was generated using pathway enrichment analysis/STRING tool, including identification of main hub proteins. We also integrated phosphoproteomic and immunoblotting studies using previous published information on RASopathy proteins and their neighbors in the context of RASopathy syndromes. Data from Phosphosite database (www.phosphosite.org) was collected in order to obtain the potential phosphosites subjected to regulation in the 27 causative RASopathy proteins. We compiled a dataset of dysregulated phosphosites in RASopathies, searched for commonalities between syndromes in harmonized data, and analyzed the role of phosphorylation in the syndromes by the identification of key players between the causative RASopathy proteins and the associated interactome. RESULTS: In this study, we provide a curated data set of 27 causative RASopathy genes, identify up to 511 protein–protein associations using pathway enrichment analysis/STRING tool, and identify 12 nodes as main hub proteins. We found that a large group of proteins contain tyrosine residues and their biological processes include but are not limited to the nervous system. Harmonizing published RASopathy phosphoproteomic and immunoblotting studies we identified a total of 147 phosphosites with increased phosphorylation, whereas 47 have reduced phosphorylation. The PKB signaling pathway is the most represented among the dysregulated phosphoproteins within the RASopathy proteins and their neighbors, followed by phosphoproteins implicated in the regulation of cell proliferation and the MAPK pathway. CONCLUSIONS: This work illustrates the complex network underlying the RASopathies and the potential of phosphoproteomics for dissecting the molecular mechanisms in these syndromes. A combined study of associated genes, their interactome and phosphorylation events in RASopathies, elucidates key players and mechanisms to direct future research, diagnosis and therapeutic windows. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-01934-x.
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spelling pubmed-82589612021-07-06 Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins Montero-Bullón, Javier-Fernando González-Velasco, Óscar Isidoro-García, María Lacal, Jesus Orphanet J Rare Dis Research BACKGROUND: RASopathies are a group of syndromes showing clinical overlap caused by mutations in genes affecting the RAS-MAPK pathway. Consequent disruption on cellular signaling leads and is driven by phosphoproteome remodeling. However, we still lack a comprehensive picture of the different key players and altered downstream effectors. METHODS: An in silico interactome of RASopathy proteins was generated using pathway enrichment analysis/STRING tool, including identification of main hub proteins. We also integrated phosphoproteomic and immunoblotting studies using previous published information on RASopathy proteins and their neighbors in the context of RASopathy syndromes. Data from Phosphosite database (www.phosphosite.org) was collected in order to obtain the potential phosphosites subjected to regulation in the 27 causative RASopathy proteins. We compiled a dataset of dysregulated phosphosites in RASopathies, searched for commonalities between syndromes in harmonized data, and analyzed the role of phosphorylation in the syndromes by the identification of key players between the causative RASopathy proteins and the associated interactome. RESULTS: In this study, we provide a curated data set of 27 causative RASopathy genes, identify up to 511 protein–protein associations using pathway enrichment analysis/STRING tool, and identify 12 nodes as main hub proteins. We found that a large group of proteins contain tyrosine residues and their biological processes include but are not limited to the nervous system. Harmonizing published RASopathy phosphoproteomic and immunoblotting studies we identified a total of 147 phosphosites with increased phosphorylation, whereas 47 have reduced phosphorylation. The PKB signaling pathway is the most represented among the dysregulated phosphoproteins within the RASopathy proteins and their neighbors, followed by phosphoproteins implicated in the regulation of cell proliferation and the MAPK pathway. CONCLUSIONS: This work illustrates the complex network underlying the RASopathies and the potential of phosphoproteomics for dissecting the molecular mechanisms in these syndromes. A combined study of associated genes, their interactome and phosphorylation events in RASopathies, elucidates key players and mechanisms to direct future research, diagnosis and therapeutic windows. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13023-021-01934-x. BioMed Central 2021-07-06 /pmc/articles/PMC8258961/ /pubmed/34229750 http://dx.doi.org/10.1186/s13023-021-01934-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Montero-Bullón, Javier-Fernando
González-Velasco, Óscar
Isidoro-García, María
Lacal, Jesus
Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins
title Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins
title_full Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins
title_fullStr Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins
title_full_unstemmed Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins
title_short Integrated in silico MS-based phosphoproteomics and network enrichment analysis of RASopathy proteins
title_sort integrated in silico ms-based phosphoproteomics and network enrichment analysis of rasopathy proteins
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8258961/
https://www.ncbi.nlm.nih.gov/pubmed/34229750
http://dx.doi.org/10.1186/s13023-021-01934-x
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