Large Improvements in MS/MS-Based Peptide Identification Rates using a Hybrid Analysis
Large Improvements in MS/MS-Based Peptide Identification Rates using a Hybrid Analysis
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DOI：
10.1021/pr101130b
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发表时间：
2011-05-01
影响因子：
4.4
通讯作者：
Bryant, Donald A.
中科院分区：
文献类型：
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作者：
Cannon, William R.;Rawlins, Mitchell M.;Bryant, Donald A.
我们报告了一种结合数据库和光谱库搜索的混合搜索方法，该方法允许采用直接的方法来表征组合数据的错误率。使用这些方法，我们证明肽与串联质谱匹配的灵敏度和特异性显着提高。混合搜索方法将全球蛋白质组学研究中可分配给肽的光谱数量增加了 57-147%，估计错误发现率为 5%，显然还有更大的改进空间。该方法结合了使用数据库搜索方法典型的共识模型光谱的通用性和光谱库中包含的强度信息的准确性。使用基于连接数据分析和统计热力学的最新发展的通用评分指标，该指标允许对组合数据的错误率使用保守估计。我们将这种方法应用于聚球藻的蛋白质组学分析。 PCC 7002，一种蓝藻，是一种用于研究光合作用碳固定和生物燃料开发的生物体。这种方法增加的特异性和敏感性使我们能够识别出更多参与光自养生长重要过程的肽。
We report a hybrid search method combining database and spectral library searches that allows for a straightforward approach to characterizing the error rates from the combined data. Using these methods, we demonstrate significantly increased sensitivity and specificity in matching peptides to tandem mass spectra. The hybrid search method increased the number of spectra that can be assigned to a peptide in a global proteomics study by 57-147% at an estimated false discovery rate of 5%, with clear room for even greater improvements. The approach combines the general utility of using consensus model spectra typical of database search methods with the accuracy of the intensity information contained in spectral libraries. A common scoring metric based on recent developments linking data analysis and statistical thermodynamics is used, which allows the use of a conservative estimate of error rates for the combined data. We applied this approach to proteomics analysis of Synechococcus sp. PCC 7002, a cyanobacterium that is a mode:, organism for studies of photosynthetic carbon fixation and biofuels development. The increased specificity and sensitivity of this approach allowed us to identify many more peptides involved in the processes important for photoautotrophic growth.