高血糖状态下胰岛β细胞外泌体的蛋白质组学分析

IF 1.2 Q3 Computer Science Bio-Algorithms and Med-Systems Pub Date : 2022-12-01 DOI:10.2478/bioal-2022-0085
Carina Rząca, U. Jankowska, E. Stępień
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引用次数: 1

摘要

引言细胞外小泡携带的货物被认为是一种很有前途的诊断标志物,尤其是蛋白质。EVs根据其大小和生物发生方式可分为外泌体(直径<200nm)和外泌体。外泌体被认为是内吞起源的,外泌体是通过质膜出芽和脱落产生的[1]。方法本研究的第一步是对外来体样品进行表征。使用可调谐电阻脉冲传感(qNano)测量了尺寸分布和浓度。外泌体的平均大小为120±9.17nm。在本研究中,使用纳米液相色谱-串联质谱联用(nanoLCMS/MS)来比较在正常葡萄糖(NG,5 mM D-葡萄糖)和高糖(HG,25 mM D-葡糖)条件下生长的胰腺β细胞(1.1B4)分泌的外泌体的蛋白质谱。裂解EV样品,并使用与UltiMate 3000 RSLC纳米系统耦合的Q-Exactive质谱仪对蛋白质进行变性、消化和分析。使用MaxQuant软件对照SwissProt智人数据库搜索nanoLC MS/MS数据,并通过MaxLFQ算法进行蛋白质定量。使用Perseus软件进行统计分析。使用FunRich 3.1.4软件和UniProt蛋白质数据库和String[2]进行进一步的生物信息学分析。结果通过nanoLC MS/MS分析,每个样品中鉴定并定量了1000多种蛋白质。外泌体中鉴定的蛋白质的平均数量为1397个。无标记定量分析表明,在NG和HG条件下分离的外泌体组成显著不同。HG中的许多途径被下调,尤其是泛素-蛋白酶体途径。此外,在HG中观察到Ras蛋白途径的显著上调。结论我们对外泌体蛋白质含量及其相关功能的描述首次揭示了EV的相互作用机制及其在葡萄糖不耐受发展和糖尿病并发症中的作用。结果还表明EV蛋白作为体内循环生物标志物的潜力可用于进一步研究。
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Proteomic profiling of exosomes derived from pancreatic beta-cells cultured under hyperglycemia
Introduction Cargo carried by extracellular vesicles (EVs) is considered a promising diagnostic marker, especially proteins. EVs can be divided according to their size and way of biogenesis into exosomes (diameter < 200 nm) and ectosomes (diameter > 200 nm). Exosomes are considered to be of endocytic origin, and ectosomes are produced by budding and shedding from the plasma membrane [1]. Methods The first step of this study was a characterization of the exosome sample. Using Tunable Resistive Pulse Sensing (qNano) size distribution and concentration were measured. The mean size of exosomes was 120±9.17 nm. In the present study, a nano liquid chromatography coupled with tandem mass spectrometry (nanoLCMS/MS) was used to compare protein profiles of exosomes secreted by pancreatic beta cells (1.1B4) grown under normal glucose (NG, 5 mM D-glucose) and high glucose (HG, 25 mM D-glucose) conditions. The EV samples were lysed, and proteins were denatured, digested, and analyzed using a Q-Exactive mass spectrometer coupled with the UltiMate 3000 RSLC nano system. The nanoLC-MS/MS data were searched against the SwissProt Homo sapiens database using MaxQuant software and protein quantitation was done by the MaxLFQ algorithm. Statistical analysis was carried out with Perseus software. Further bioinformatic analysis was performed using the FunRich 3.1.4 software with the UniProt protein database and String [2]. Results As a result of the nanoLC-MS/MS analysis more than 1,000 proteins were identified and quantified in each sample. The average number of identified proteins in exosomes was 1,397. Label-free quantitative analysis showed that exosome composition differed significantly between those isolated under NG and HG conditions. Many pathways were down-regulated in HG, particularly the ubiquitin-proteasome pathway. In addition, a significant up-regulation of the Ras-proteins pathway was observed in HG. Conclusion Our description of exosomes protein content and its related functions provides the first insight into the EV interactome and its role in glucose intolerance development and diabetic complications. The results also indicate the applicability of EV proteins for further investigation regarding their potential as circulating in vivo biomarkers.
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来源期刊
Bio-Algorithms and Med-Systems
Bio-Algorithms and Med-Systems MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
3
期刊介绍: The journal Bio-Algorithms and Med-Systems (BAMS), edited by the Jagiellonian University Medical College, provides a forum for the exchange of information in the interdisciplinary fields of computational methods applied in medicine, presenting new algorithms and databases that allows the progress in collaborations between medicine, informatics, physics, and biochemistry. Projects linking specialists representing these disciplines are welcome to be published in this Journal. Articles in BAMS are published in English. Topics Bioinformatics Systems biology Telemedicine E-Learning in Medicine Patient''s electronic record Image processing Medical databases.
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