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在大脑中动脉闭塞(MCAO)小鼠模型中对蛋白质组和转录组进行综合分析,揭示了中风进展过程中的分子图景。

Integrated analysis of the proteome and transcriptome in a MCAO mouse model revealed the molecular landscape during stroke progression.

作者信息

Li Litao, Dong Lipeng, Xiao Zhen, He Weiliang, Zhao Jingru, Pan Henan, Chu Bao, Cheng Jinming, Wang Hebo

机构信息

Department of Neurology, Hebei General Hospital, Shijiazhuang 050051, Hebei, China.

College of Life Sciences, Shanghai Normal University, Shanghai 200234, China.

出版信息

J Adv Res. 2020 Jan 12;24:13-27. doi: 10.1016/j.jare.2020.01.005. eCollection 2020 Jul.

Abstract

Strokes usually results in long-term disability and death, and they occur worldwide. Recently, increased research on both on the physiopathological mechanisms and the transcriptome during stroke progression, have highlighted the relationship between stroke progression and immunity, with a special focus on inflammation. Here, we applied proteome analysis to a middle carotid artery occlusion (MCAO) mouse model at 0 h, 6 h, 12 h and 24 h, in which proteome profiling was performed with 23 samples, and 41 differentially expressed proteins (DEPs) were identified. Bioinformatics studies on our data revealed the importance of the immune response and particularly identified the inflammatory response, cytokine- cytokine receptor interactions, the innate immune response and reactive oxygen species (ROS) during stroke progression. In addition, we compared our data with multiple gene expression omnibus (GEO) datasets with and without a time series, in which similar pathways were identified, and three proteins, C3, Apoa4 and S100a9, were highlighted as markers or drug targets for stroke; these three proteins were significantly upregulated in the MCAO model, both in our proteomic data and in the GEO database.

摘要

中风通常会导致长期残疾和死亡,且在全球范围内都有发生。最近,对中风进展过程中的生理病理机制和转录组的研究不断增加,突出了中风进展与免疫之间的关系,尤其关注炎症。在此,我们对大脑中动脉闭塞(MCAO)小鼠模型在0小时、6小时、12小时和24小时进行了蛋白质组分析,用23个样本进行了蛋白质组分析,鉴定出41种差异表达蛋白(DEP)。对我们的数据进行的生物信息学研究揭示了免疫反应的重要性,并特别确定了中风进展过程中的炎症反应、细胞因子-细胞因子受体相互作用、先天免疫反应和活性氧(ROS)。此外,我们将我们的数据与多个有或没有时间序列的基因表达综合数据库(GEO)进行了比较,在这些数据库中识别出了相似的途径,三种蛋白质C3、Apoa4和S100a9被突出显示为中风的标志物或药物靶点;在我们的蛋白质组数据和GEO数据库中,这三种蛋白质在MCAO模型中均显著上调。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b11/7063112/2591f783d359/ga1.jpg

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