Proteome Profiling of Serum Exosomes from Newborns Delivered by Mothers with Preeclampsia

IF 0.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS Current Proteomics Pub Date : 2022-04-06 DOI:10.2174/1570164619666220406121420
Haiying Li, Xiaoqun Zhang, Xianhui Hong, Shuxuan Zhang, Haijun Tang, Jinlong Shi, Hui Peng, Youjia Wu
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Abstract

Preeclampsia (PE) is a common pregnancy-specific disease with potential adverse maternal and neonatal outcomes. We aimed to estimate proteomic profiles of serum-derived exosomes obtained from PE offspring with bioinformatics methods. Serum samples were collected from 12 h, 24 h, and 72 h newborns delivered by preeclamptic and normal pregnant women. Exosomes were extracted, and the concentration and size distribution were determined. The exosome surface markers CD9, CD63, CD81, and TSG101, were assayed by Western blot. The exosome proteins were screened by quantitative proteomics with tandem mass tag (TMT). All the identified proteins were subjected to the Weighted Gene Co-Expression Network Analysis (WGCNA), GO function, and KEGG pathway analysis. A protein-protein interaction network (PPI) was used to extract hub proteins through the Cytohubba plugin of Cytoscape The extracted exosomes were round or oval vesicular structures at a 100-200 nm concentration, and the size distribution was standard and uniform. Exosome surface markers CD9, CD63, and CD81 were detected, and TSG101 was not detected. A total of 450 expressed proteins were selected, and 444 proteins were mapped with gene names. A blue module with 66 proteins highly correlated with phenotype at 12 h. Functional analyses revealed that module proteins were mainly enriched in extracellular matrix. The top 10 selected hub proteins were identified as hub proteins, including COL6A2, HSPG2, COL4A1, COL3A1, etc. Our study provides important information for exploring molecular mechanisms of preeclampsia and potential biomarkers for future diagnosis and treatment in the clinic.
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子痫前期母亲所生新生儿血清外泌体的蛋白质组分析
子痫前期(PE)是一种常见的妊娠特异性疾病,具有潜在的不良孕产妇和新生儿结局。我们旨在用生物信息学方法估计从PE后代获得的血清来源的外泌体的蛋白质组学特征。采集子痫前期孕妇和正常孕妇分娩的12小时、24小时和72小时新生儿的血清样本。提取外泌体,测定其浓度和大小分布。Western blot检测外泌体表面标志物CD9、CD63、CD81和TSG101。采用串联质量标签(TMT)定量蛋白质组学技术筛选外泌体蛋白。所有鉴定的蛋白都进行了加权基因共表达网络分析(WGCNA)、GO功能和KEGG通路分析。采用蛋白-蛋白相互作用网络(protein-protein interaction network, PPI)技术,通过cytoscapea软件Cytohubba插件提取轮毂蛋白,提取的外泌体为圆形或椭圆形囊泡结构,浓度为100-200 nm,大小分布标准均匀。检测到外泌体表面标记CD9、CD63和CD81,未检测到TSG101。共筛选出450个表达蛋白,并绘制了444个蛋白的基因名称图谱。在12 h时,一个蓝色模块有66个蛋白与表型高度相关。功能分析显示模块蛋白主要富集在细胞外基质中。我们的研究为探索子痫前期的分子机制和潜在的生物标志物提供了重要的信息,为今后临床诊断和治疗提供了重要的信息。
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来源期刊
Current Proteomics
Current Proteomics BIOCHEMICAL RESEARCH METHODS-BIOCHEMISTRY & MOLECULAR BIOLOGY
CiteScore
1.60
自引率
0.00%
发文量
25
审稿时长
>0 weeks
期刊介绍: Research in the emerging field of proteomics is growing at an extremely rapid rate. The principal aim of Current Proteomics is to publish well-timed in-depth/mini review articles in this fast-expanding area on topics relevant and significant to the development of proteomics. Current Proteomics is an essential journal for everyone involved in proteomics and related fields in both academia and industry. Current Proteomics publishes in-depth/mini review articles in all aspects of the fast-expanding field of proteomics. All areas of proteomics are covered together with the methodology, software, databases, technological advances and applications of proteomics, including functional proteomics. Diverse technologies covered include but are not limited to: Protein separation and characterization techniques 2-D gel electrophoresis and image analysis Techniques for protein expression profiling including mass spectrometry-based methods and algorithms for correlative database searching Determination of co-translational and post- translational modification of proteins Protein/peptide microarrays Biomolecular interaction analysis Analysis of protein complexes Yeast two-hybrid projects Protein-protein interaction (protein interactome) pathways and cell signaling networks Systems biology Proteome informatics (bioinformatics) Knowledge integration and management tools High-throughput protein structural studies (using mass spectrometry, nuclear magnetic resonance and X-ray crystallography) High-throughput computational methods for protein 3-D structure as well as function determination Robotics, nanotechnology, and microfluidics.
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