POST ANALYSIS DATA ACQUISITION FOR THE ITERATIVE MS/MS SAMPLING OF PROTEOMICS MI

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 随着快速扫描质谱仪、数据采集和数据库检索算法的发展，利用微毛细管液相色谱-串联质谱仪(LC-MS/MS)鉴定多肽已成为常规方法。然而，尽管质谱仪的动态范围和峰容量有限，但由于MS/MS采样速度的限制，质谱仪检测限内的许多多肽仍然无法识别。我们开发了一种自动化方法，使用高分辨率LC-MS数据的质谱图来确定混合物中存在的分子物种，并将MS/MS谱图的获取定向到先前分析中遗漏的前体。这种方法增加了MS/MS采样的分子物种的覆盖率，从而增加了在使用简单的一维色谱分离获取技术或生物复制品期间识别的多肽和蛋白质的数量。独特的工作流程和定制软件的结合有助于改进在复杂蛋白质混合物的蛋白质组学实验中检测到的分子特征的识别。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The identification of peptides by microcapillary liquid chromatography-tandem mass spectrometry (?LC-MS/MS) has become routine because of the development of fast scanning mass spectrometers, data-dependent acquisition, and database searching algorithms. However, many peptides within the detection limit of the mass spectrometer remain unidentified because of limitations in MS/MS sampling speed despite the dynamic range and peak capacity of the instrument. We have developed an automated approach that uses the mass spectra from high resolution ?LC-MS data to define the molecular species present in the mixture and directs the acquisition of MS/MS spectra to precursors that were missed in prior analyses. This approach increases the coverage of the molecular species sampled by MS/MS and consequently the number of peptides and proteins identified during the acquisition of technical or biological replicates using a simple one-dimensional chromatographic separation. The combination of a unique workflow and custom software contribute to the improved identification of molecular features detected in proteomics experiments of complex protein mixtures.