Using a shotgun strategy coupled with high-throughput data mining to map the proteome of normal huma

来源 :中华医学会第十一次全国呼吸病学术会议 | 被引量 : 0次 | 上传用户:rewyuh
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  Physiological processes are often associated with changes in protein expression,post-translational modification,and/or subcellular sorting.With this investigation we meant to establish the global expression protein profile associated with normal lung.Normal bronchial and alveolar epithelial cells from six samples of lung tissues were purified by laser capture rnicrodissection (LCM).The proteome was analyzed with different bioinformatics tools.Using stringent filter parameters to avoid redundancy,a total of 862 distinct proteins were identified.Various physico-chemical properties,including molecular weight (MW),isoelectric point(pI),subcellular localization,grand average of hydropathy(GRAVY),and presence of trans-membrane helices (TMH) ,were analyzed in detail.Function classifications,including cellular component,molecular function and biological process,were based on Gene Ontology (GO) annotation terms.A total of 778identified proteins could be related to 139 KEGG reference pathways.Enrichment analysis included four different classes.Protein-protein interaction (PPI) was analyzed through GENE GO maps.Different algorithms consistently revealed that cell adhesion was a physiological process present at a statistically significant level in normal human lung ceils.These data may set a baseline standard and contribute to a better understanding of the physiological mechanisms in normal lung.
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