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

Orphanet Journal of Rare Diseases

Óscar González-Velasco¹  Jesus Lacal²  María Isidoro-García³  Javier-Fernando Montero-Bullón⁴ 

[1] Bioinformatics and Functional Genomics Group, IBMCC Cancer Research Center, Campus Miguel de Unamuno, 37007, Salamanca, Spain;Institute for Biomedical Research of Salamanca (IBSAL), 37007, Salamanca, Spain;Molecular Genetics of Human Diseases Group, Department of Microbiology and Genetics, Faculty of Biology, University of Salamanca, 37007, Salamanca, Spain;Institute for Biomedical Research of Salamanca (IBSAL), 37007, Salamanca, Spain;Network for Cooperative Research in Health–RETICS ARADyAL, 37007, Salamanca, Spain;Department of Clinical Biochemistry, University Hospital of Salamanca, 37007, Salamanca, Spain;Department of Medicine, University of Salamanca, 37007, Salamanca, Spain;Metabolic Engineering Group, Department of Microbiology and Genetics, Faculty of Biology, University of Salamanca, 37007, Salamanca, Spain;

关键词: Phosphoproteomics;    Interactomics;    RASopathies;    Neurofibromatosis;    Noonan syndrome;    Mass spectrometry;    Rare diseases;   

DOI  :  10.1186/s13023-021-01934-x

来源: Springer

【 摘 要 】

BackgroundRASopathies 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.MethodsAn 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.ResultsIn 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.ConclusionsThis 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.

【 授权许可】

CC BY