Scherl Alexander, Shaffer Scott A, Taylor Gregory K, Kulasekara Hemantha D, Miller Samuel I, Goodlett David R
Department of Medicinal Chemistry, University of Washington, Seattle, WA 98195, USA.
Anal Chem. 2008 Feb 15;80(4):1182-91. doi: 10.1021/ac701680f. Epub 2008 Jan 23.
Gas-phase fractionation (GPF) is an efficient and straightforward method to increase proteome coverage. In this report, optimal m/z ranges were calculated based on genomic complexity and experimental data. Then, theoretical precursor ion densities were calculated in silico from various organisms' genomes and found to corroborate the empirical selection of m/z ranges based on ion density mapping. According to both calculations, the choice of m/z range for most efficient GPF coverage in the lower m/z range should be very narrow and increase as m/z value increases. Next, a systematic LC-MS/MS analysis was performed to confirm this observation. The behavior of data-dependent precursor ion selection and the origin of the observed variability was investigated under three different scan modes of an LTQ-Orbitrap hybrid mass spectrometer. Finally, GPF combined with data-dependent analysis was compared to a targeted, pseudo-multiple reaction monitoring analysis of proteotypic peptides that should be, based on empirical observation of LC-ESI-MS/MS data, detectable. The result of the latter experiment supported our conclusion that data-dependent analysis using rational gas-phase fractionation was sufficient for comprehensive proteomic analysis of the proteotypic peptides in an unfractionated cell lysate.
气相分级分离(GPF)是一种提高蛋白质组覆盖率的有效且直接的方法。在本报告中,基于基因组复杂性和实验数据计算了最佳质荷比范围。然后,从各种生物体的基因组中通过计算机模拟计算理论前体离子密度,发现其证实了基于离子密度映射对质荷比范围的经验性选择。根据这两种计算,在较低质荷比范围内实现最有效GPF覆盖率的质荷比范围选择应非常窄,并随着质荷比数值的增加而增大。接下来,进行了系统的液相色谱 - 串联质谱分析以证实这一观察结果。在LTQ - Orbitrap混合质谱仪的三种不同扫描模式下,研究了数据依赖型前体离子选择的行为以及观察到的变异性的来源。最后,将GPF与数据依赖型分析相结合,与基于液相色谱 - 电喷雾电离 - 串联质谱数据的经验观察应可检测到的蛋白型肽段的靶向、伪多反应监测分析进行了比较。后一实验的结果支持了我们的结论,即使用合理的气相分级分离进行数据依赖型分析足以对未分级细胞裂解物中的蛋白型肽段进行全面的蛋白质组分析。