Toward Comprehensive Plasma Proteomics by Orthogonal Protease Digestion.
Toward Comprehensive Plasma Proteomics by Orthogonal Protease Digestion.
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DOI：
10.1021/acs.jproteome.1c00357
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发表时间：
2021-08-06
影响因子：
4.4
通讯作者：
Swaney DL
中科院分区：
文献类型：
--
作者：
Fossati A;Richards AL;Chen KH;Jaganath D;Cattamanchi A;Ernst JD;Swaney DL
在大型临床队列中快速和一致的蛋白质鉴定是临床蛋白质组学的重要目标。随着数据独立技术（DIA/SWATH-MS）的发展，现在可以分析数百个样品，具有很高的重现性和定量准确性。然而，该技术受益于经验推导的光谱库，其定义了肽和蛋白质的可检测集合。在这里，我们应用了一个简单的和可访问的提示为基础的工作流程的光谱库的生成提供了一个全面的概述在个人的血浆蛋白质组与活动性结核病（TB）。为了提高蛋白质覆盖率，我们使用了非传统的蛋白酶，如GluC和AspN以及金标准胰蛋白酶，鉴定了30，000多个肽，映射到3，309个蛋白质。应用该文库定量TB感染中的血浆蛋白质组差异在50分钟的MS采集中回收了超过400种蛋白质，包括先前主要通过基于抗体的测定可检测的诊断性结核分枝杆菌（Mtb）蛋白质和先前未描述为在血浆中的细胞内蛋白质。
Rapid and consistent protein identification across large clinical cohorts is an important goal for clinical proteomics. With the development of data-independent technologies (DIA/SWATH-MS), it is now possible to analyze hundreds of samples with great reproducibility and quantitative accuracy. However, this technology benefits from empirically derived spectral libraries that define the detectable set of peptides and proteins. Here we apply a simple and accessible tip-based workflow for the generation of spectral libraries to provide a comprehensive overview on the plasma proteome in individuals with and without active tuberculosis (TB). To boost protein coverage, we utilized non-conventional proteases such as GluC and AspN together with the gold standard trypsin, identifying more than 30,000 peptides mapping to 3,309 proteins. Application of this library to quantify plasma proteome differences in TB infection recovered more than 400 proteins in 50 minutes of MS-acquisition, including diagnostic Mycobacterium tuberculosis (Mtb) proteins that have previously been detectable primarily by antibody-based assays and intracellular proteins not previously described to be in plasma.
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影响因子：
64.8
作者：
Harris CR;Millman KJ;van der Walt SJ;Gommers R;Virtanen P;Cournapeau D;Wieser E;Taylor J;Berg S;Smith NJ;Kern R;Picus M;Hoyer S;van Kerkwijk MH;Brett M;Haldane A;Del Río JF;Wiebe M;Peterson P;Gérard-Marchant P;Sheppard K;Reddy T;Weckesser W;Abbasi H;Gohlke C;Oliphant TE
通讯作者：
Oliphant TE
影响因子：
7.4
作者：
Bian, Yangyang;Bayer, Florian P.;Kuster, Bernhard
通讯作者：
Kuster, Bernhard
影响因子：
4.4
作者：
Cox, Juergen;Neuhauser, Nadin;Mann, Matthias
通讯作者：
Mann, Matthias
影响因子：
7
作者：
Bruderer, Roland;Muntel, Jan;Reiter, Lukas
通讯作者：
Reiter, Lukas
影响因子：
3.2
作者：
Koul, A;Choidas, A;Ullrich, A
通讯作者：
Ullrich, A