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Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry

机译:液相色谱-质谱联用分析肿瘤组织的深层蛋白质组和磷酸化蛋白质组的可重复工作流程

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摘要

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in −4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.
机译:在这里,我们为组织或细胞系的全局蛋白质组和磷酸化蛋白质组分析提供了一种优化的工作流程,该流程使用等压标签(TMT(串联质量标签)-10)进行多重分析和相对定量分析,并且吞吐量比iTRAQ(等压标签为3倍)高。绝对和相对定量)基于4的方法,具有实验室内和实验室间的高重复性。使用来自患者异种移植模型的两种截然不同的乳腺癌亚型,对三个独立实验室的工作流进行了系统地表征和基准测试,从而能够评估蛋白质组和磷酸化蛋白质组的深度和定量重现性。每个丛由十个样品组成,每个样品都是300μg来源于<50 mg湿重组织的肽。在每个样品中定量的10,000种蛋白质中,我们可以区分出7700种源自肿瘤细胞的人类蛋白质和3100种源自周围基质和血液的小鼠蛋白质。重复和实验室间的最大偏差为<7%,两种亚型的基于TMT比的实验室间相关性为r> 0.88。在整个实验室中,磷酸化蛋白质组覆盖率的最大偏差<24%,每个样品平均> 37,000个定量磷酸化位点,且r> 0.72的定量差异相关性。完整的过程(包括样品处理和数据生成)可以在10天内完成10个组织样品的采样,并且可以使用一台LC-MS / MS仪器在−4个月内分析100个样品。在实验室内和实验室间获得的数据的高质量,深度和可重复性,应使人们能够从基于质谱的细胞和组织蛋白质组学分析以及蛋白质组学数据集成中获得新的生物学见解。

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