Value of using multiple proteases for large-scale mass spectrometry-based proteomics.
Value of using multiple proteases for large-scale mass spectrometry-based proteomics.
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DOI：
10.1021/pr900863u
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发表时间：
2010-03-05
影响因子：
4.4
通讯作者：
Coon, Joshua J.
中科院分区：
文献类型：
--
作者：
Swaney, Danielle L.;Wenger, Craig D.;Coon, Joshua J.
大规模的蛋白质测序方法依赖于对复杂蛋白质混合物的酶消化来产生一组用于质谱分析的多肽。在这里，我们研究了多种蛋白酶(胰酶、LysC、ARGC、AspN和GluC)的使用，以改进模式生物酿酒酵母中的蛋白质识别和表征。使用基于数据依赖的决策树算法对多肽前体进行MS2片段划分，我们以1%的错误发现率(FDR)识别了92,095个唯一的多肽(总计609,665个)，映射到3,908个蛋白质。这些结果是对单一蛋白酶消化(胰酶)的数据的显著改进-27,822个独特的多肽对应于3,313个蛋白质。额外的595个蛋白质鉴定主要来自低丰度的蛋白质(即1,000拷贝/细胞)；这些蛋白质的序列覆盖率同样提高了近3倍。我们证明，在用单一的蛋白酶消化后，蛋白质组的大部分是无法获得的，并且多个蛋白酶，而不是技术上的复制，提供了一条增加蛋白质鉴定和蛋白质组序列覆盖率的直接途径。
Large-scale protein sequencing methods rely on enzymatic digestion of complex protein mixtures to generate a collection of peptides for mass spectrometric analysis. Here we examine the use of multiple proteases (trypsin, LysC, ArgC, AspN, and GluC) to improve both protein identification and characterization in the model organism Saccharomyces cerevisiae. Using a data-dependent, decision tree-based algorithm to tailor MS2 fragmentation method to peptide precursor, we identified 92,095 unique peptides (609,665 total) mapping to 3,908 proteins at a 1% false discovery rate (FDR). These results were a significant improvement upon data from a single protease digest (trypsin) – 27,822 unique peptides corresponding to 3,313 proteins. The additional 595 protein identifications were mainly from those at low abundances (i.e., < 1,000 copies/cell); sequence coverage for these proteins was likewise improved nearly 3-fold. We demonstrate that large portions of the proteome are simply inaccessible following digestion with a single protease and that multiple proteases, rather than technical replicates, provide a direct route to increase both protein identifications and proteome sequence coverage.
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影响因子：
4.4
作者：
McAlister, Graeme C.;Berggren, W. Travis;Griep-Raming, Jens;Horning, Stevan;Makarov, Alexander;Phanstiel, Doug;Stafford, George;Swaney, Danielle L.;Syka, John E. P.;Zabrouskov, Vlad;Coon, Joshua J.
通讯作者：
Coon, Joshua J.
影响因子：
7.4
作者：
Schlosser, A;Vanselow, JT;Kramer, A
通讯作者：
Kramer, A
影响因子：
7.4
作者：
Wang, Bin;Malik, Rainer;Koerner, Roman
通讯作者：
Koerner, Roman
DOI：
10.1073/pnas.84.20.6970
发表时间：
1987-10-01
影响因子：
11.1
作者：
AEBERSOLD, RH;LEAVITT, J;KENT, SBH
通讯作者：
KENT, SBH
影响因子：
4.4
作者：
Choudhary, G;Wu, SL;Hancock, WS
通讯作者：
Hancock, WS