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An Integrated Directed Mass Spectrometric Approach for In-depth Characterization of Complex Peptide Mixtures

机译:一种用于复杂肽混合物深度表征的集成定向质谱方法

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摘要

LC-MS/MS has emerged as the method of choice for the identification and quantification of protein sample mixtures. For very complex samples such as complete proteomes, the most commonly used LC-MS/MS method, data-dependent acquisition (DDA) precursor selection, is of limited utility. The limited scan speed of current mass spectrometers along with the highly redundant selection of the most intense precursor ions generates a bias in the pool of identified proteins toward those of higher abundance. A directed LC-MS/MS approach that alleviates the limitations of DDA precursor ion selection by decoupling peak detection and sequencing of selected precursor ions is presented. In the first stage of the strategy, all detectable peptide ion signals are extracted from high resolution LC-MS feature maps or aligned sets of feature maps. The selected features or a subset thereof are subsequently sequenced in sequential, non-redundant directed LC-MS/MS experiments, and the MS/MS data are mapped back to the original LC-MS feature map in a fully automated manner. The strategy, implemented on an LTQ-FT MS platform, allowed the specific sequencing of 2,000 features per analysis and enabled the identification of more than 1,600 phosphorylation sites using a single reversed phase separation dimension without the need for time-consuming prefractionation steps. Compared with conventional DDA LC-MS/MS experiments, a substantially higher number of peptides could be identified from a sample, and this increase was more pronounced for low intensity precursor ions.
机译:LC-MS / MS已成为鉴定和定量蛋白质样品混合物的首选方法。对于非常复杂的样品,例如完整的蛋白质组,最常用的LC-MS / MS方法,即依赖数据采集(DDA)的前体选择,用途有限。当前质谱仪的有限扫描速度,以及对最强的前体离子的高度冗余选择,导致已识别蛋白质池中的蛋白质偏向高丰度的蛋白质。提出了一种直接的LC-MS / MS方法,该方法通过去耦峰检测和对选定前体离子的测序来减轻DDA前体离子选择的局限性。在该策略的第一阶段,从高分辨率LC-MS特征图或特征图的对齐集合中提取所有可检测到的肽离子信号。随后,在连续的,非冗余的定向LC-MS / MS实验中对选定的特征或其子集进行排序,然后以全自动方式将MS / MS数据映射回原始LC-MS特征图。该策略在LTQ-FT MS平台上实施,允许每个分析对2,000个特征进行特定的测序,并使用单一的反相分离尺寸即可识别1,600多个磷酸化位点,而无需耗时的预分离步骤。与常规DDA LC-MS / MS实验相比,可以从样品中鉴定出明显更多的肽,对于低强度前体离子,这种增加更为明显。

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