Sniatynski Matthew J, Rogalski Jason C, Hoffman Michael D, Kast Juergen
Biomedical Research Centre, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.
Anal Chem. 2006 Apr 15;78(8):2600-7. doi: 10.1021/ac051639u.
As proteomics continues to establish itself as an effective postgenomic research tool, there is an increasingly urgent need for efficient, automated analysis techniques capable of effectively dealing with the vast amounts of data generated via mass spectrometry. Wholesale analysis packages, often used to deal with these enormous amounts of data, may benefit from supplementary, targeted analyses as current research begins to emphasize posttranscriptional/translational protein modifications, protein truncations, and poorly characterized mutations. We demonstrate the application of a new analysis technique based on mathematical correlation that is computationally efficient and robust against different instruments, noise levels, and experimental conditions. We have previously shown that this technique is able to extract pertinent mass shift signals from MS data, corresponding to the neutral loss of a modification from a peptide, e.g., a loss of 79.97 Th from phosphorylated tyrosine. Here we show that an extension of this method is applicable to MS and MS/MS data in general, allowing visualization of ions that produce a particular mass shift signal, be it from differential stable isotope labeling, overlap of fragment ions in a series, or ions that produce a neutral loss. The application of this method allows the researcher to discover individual features, such as the presence of specific modified or isotopically labeled peptides, to eliminate overlapping fragment ion series, and to localize specific sites of modification.
随着蛋白质组学作为一种有效的后基因组研究工具不断确立自身地位，对于能够有效处理通过质谱产生的大量数据的高效、自动化分析技术的需求日益迫切。常用于处理这些海量数据的整体分析软件包，可能会受益于补充性的靶向分析，因为当前研究开始强调转录后/翻译后蛋白质修饰、蛋白质截短以及特征不明的突变。我们展示了一种基于数学相关性的新分析技术的应用，该技术计算效率高，并且对不同仪器、噪声水平和实验条件具有鲁棒性。我们之前已经表明，该技术能够从质谱数据中提取相关的质量位移信号，这些信号对应于肽段上修饰的中性丢失，例如磷酸化酪氨酸的79.97道尔顿的丢失。在此我们表明，该方法的扩展通常适用于质谱和串联质谱数据，允许可视化产生特定质量位移信号的离子，无论该信号来自差异稳定同位素标记、一系列碎片离子的重叠，还是产生中性丢失的离子。该方法的应用使研究人员能够发现个体特征，例如特定修饰或同位素标记肽段的存在，消除重叠的碎片离子系列，并定位特定的修饰位点。
