Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: The yeast proteome
Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: The yeast proteome
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DOI：
10.1021/pr025556v
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发表时间：
2003-01-01
影响因子：
4.4
通讯作者：
Gygi, SP
中科院分区：
文献类型：
--
作者：
Peng, JM;Elias, JE;Gygi, SP
高度复杂的蛋白质混合物可以在蛋白质水解后通过液相色谱-串联质谱（LC-MS/MS）直接分析。在本文中，我们利用强阳离子交换（SCX）和反相（RP）色谱的组合，以实现二维分离之前的MS/MS。在80分钟洗脱期间每分钟收集一次级分。将80个级分的体积减少，然后使用排气柱（100 μ m i.d.）RP-LC-MS/MS分析方法。收集了超过162 000个MS/MS谱，其中26 815个与酵母肽匹配（7537个独特肽）。在该单一分析中明确鉴定了总共1504种酵母蛋白。我们将这个实验与Yates及其同事先前发表的酵母蛋白质组分析进行了比较（Washburn，M。P的; Wolters，D.;耶茨J.R.三.国家生物技术2001，19，242 -7）。此外，我们报告了使用Sequest算法和反向酵母蛋白质数据库与肽鉴定相关的假阳性率的深入分析。提出了新的标准，以减少假阳性小于1%，并大大减少了人工解释的需要，同时允许更多的蛋白质被确定。
Highly complex protein mixtures can be directly analyzed after proteolysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In this paper, we have utilized the combination of strong cation exchange (SCX) and reversed-phase (RP) chromatography to achieve two-dimensional separation prior to MS/MS. One milligram of whole yeast protein was proteolyzed and separated by SCX chromatography (2.1 mm i.d.) with fraction collection every minute during an 80-min elution. Eighty fractions were reduced in volume and then re-injected via an autosampler in an automated fashion using a vented-column (100 mum i.d.) approach for RP-LC-MS/MS analysis. More than 162 000 MS/MS spectra were collected with 26 815 matched to yeast peptides (7537 unique pepticles). A total of 1504 yeast proteins were unambiguously identified in this single analysis. We present a comparison of this experiment with a previously published yeast proteome analysis by Yates and colleagues (Washburn, M. P.; Wolters, D.; Yates, J.R., III. Nat. Biotechnol. 2001, 19,242-7). In addition, we report an in-depth analysis of the false-positive rates associated with peptide identification using the Sequest algorithm and a reversed yeast protein database. New criteria are proposed to decrease false-positives to less than 1% and to greatly reduce the need for manual interpretation while permitting more proteins to be identified.