Trindade Fábio, Nogueira-Ferreira Rita, Bastos Paulo, Amado Francisco, Ferreira Rita, Vitorino Rui
iBiMED, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal.
Unidade de Investigação Cardiovascular (UnIC), Departamento de Cirurgia e Fisiologia, Faculdade de Medicina, Universidade do Porto, Porto, Portugal.
Methods Mol Biol. 2019;2044:393-553. doi: 10.1007/978-1-4939-9706-0_26.
Cerebrospinal fluid (CSF) is a source of valuable information concerning brain disorders. The technical advances of high-throughput omics platforms to analyze body fluids can generate a huge amount of data, whose translation to biological meaning is a challenge. Several bioinformatic tools have emerged to help handling this data into systems biology comprehensively. Herein, we describe a step-by-step tutorial for CSF proteome data analysis in the set of neurodegenerative diseases using (1) ClueGO+CluePedia tool to perform cluster-based analysis envisioning the characterization of the biological processes dysregulated in neurodegenerative diseases including Alzheimer's and Parkinson's diseases; (2) Cytoscape to map disease-specific proteins; (3) SecretomeP to inquire the secretion pathway of CSF proteins; and (4) STRING to identify biological processes modulated by secreted CSF proteins based on protein-protein interaction analysis. This step-by-step guide might help researchers to better characterize disease pathogenesis and to identify putative disease biomarkers.
脑脊液(CSF)是有关脑部疾病的宝贵信息来源。用于分析体液的高通量组学平台的技术进步能够产生海量数据,而将这些数据转化为生物学意义是一项挑战。已经出现了几种生物信息学工具来帮助全面地将这些数据处理成系统生物学。在此,我们描述了一套针对神经退行性疾病中脑脊液蛋白质组数据分析的分步教程,使用(1)ClueGO + CluePedia工具进行基于聚类的分析,以设想神经退行性疾病(包括阿尔茨海默病和帕金森病)中失调的生物过程的特征;(2)Cytoscape来绘制疾病特异性蛋白质图谱;(3)SecretomeP来探究脑脊液蛋白质的分泌途径;以及(4)STRING基于蛋白质 - 蛋白质相互作用分析来识别由分泌的脑脊液蛋白质调节的生物过程。这个分步指南可能有助于研究人员更好地描述疾病发病机制并识别潜在的疾病生物标志物。