Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry.
Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry.
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DOI：
10.1038/s41596-018-0006-9
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发表时间：
2018-07
期刊：
影响因子：
14.8
通讯作者：
Carr SA
中科院分区：
文献类型：
--
作者：
Mertins P;Tang LC;Krug K;Clark DJ;Gritsenko MA;Chen L;Clauser KR;Clauss TR;Shah P;Gillette MA;Petyuk VA;Thomas SN;Mani DR;Mundt F;Moore RJ;Hu Y;Zhao R;Schnaubelt M;Keshishian H;Monroe ME;Zhang Z;Udeshi ND;Mani D;Davies SR;Townsend RR;Chan DW;Smith RD;Zhang H;Liu T;Carr SA
在这里，我们提出了一个优化的工作流程，用于组织或细胞系的全局蛋白质组和磷酸化蛋白质组分析，该工作流程使用同量异位素标签（TMT（串联质量标签）-10）进行多重分析和相对定量，并提供比iTRAQ（绝对和相对定量同量异位素标签）-4高3倍的通量，具有高的实验室内和实验室间重现性。使用来自患者来源的异种移植模型的两种不同的乳腺癌亚型，在三个独立实验室中系统地表征和基准化工作流程，以评估蛋白质组和磷酸化蛋白质组的深度和定量再现性。每个复合物由十个样品组成，每个样品为300 μg来源于<50 mg湿重组织的肽。在每个样品定量的10，000种蛋白质中，我们可以区分7，700种来自肿瘤细胞的人类蛋白质和3100种来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<7%，两种乳腺癌亚型基于TMT比率比较的实验室间相关性r > 0.88。磷酸化蛋白质组覆盖率的最大偏差在各实验室中<24%，每个样品的平均定量磷酸化位点> 37，000个，差异定量相关性r > 0.72。整个过程，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，100个样品可以在−4个月内使用一个LC-MS/MS仪器进行分析。实验室内和实验室间获得的高质量、深度和可重复性的数据应该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基因组学数据集成中获得新的生物学见解。
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.
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影响因子：
7.4
作者：
Pichler P;Köcher T;Holzmann J;Mazanek M;Taus T;Ammerer G;Mechtler K
通讯作者：
Mechtler K
影响因子：
48
作者：
Mertins, Philipp;Qiao, Jana W.;Patel, Jinal;Udeshi, Namrata D.;Clauser, Karl R.;Mani, D. R.;Burgess, Michael W.;Gillette, Michael A.;Jaffe, Jacob D.;Carr, Steven A.
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Carr, Steven A.
影响因子：
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通讯作者：
Carr, Steven A.
影响因子：
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作者：
Delmotte, Nathanael;Lasaosa, Maria;Huber, Christian G.
通讯作者：
Huber, Christian G.
影响因子：
4.4
作者：
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通讯作者：
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