Optimal Decharging and Clustering of Charge Ladders Generated in ESI-MS
Optimal Decharging and Clustering of Charge Ladders Generated in ESI-MS
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DOI：
10.1021/pr100177k
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发表时间：
2010-05-01
影响因子：
4.4
通讯作者：
Reinert, Knut
中科院分区：
文献类型：
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作者：
Bielow, Chris;Ruzek, Silke;Reinert, Knut
在电喷雾电离质谱（ESI-MS）中，肽和蛋白质离子通常以多个电荷状态被观察到。此外，多电荷物质与其他离子的加合经常导致单个分析物的相当复杂的信号模式，这显著地使从质谱导出定量信息复杂化。针对MS 1水平的标签策略进一步加剧了这种情况，因为必须同时表示健康或患病等多种生物状态。我们开发了一个整数线性规划（ILP）的方法，它可以聚类信号属于相同的肽或蛋白质。该算法是通用的，因为它对信号沿m/z轴沿着的所有可能移位进行建模。这些位移可以由化合物的不同电荷状态、加合物的存在（例如，钾或钠），和/或固定质量标记（例如，来自ICAT或烟酸标记），或上述的任何组合。我们表明，我们的方法可以用来推断更多的功能标记的数据集，纠正错误的电荷分配，即使在高分辨率MS，提高质量精度，并在不同的电荷状态和几个加合物类型的带电物种集群。
In electrospray ionization mass spectrometry (ESI-MS), peptide and protein ions are usually observed in multiple charge states. Moreover, adduction of the multiply charged species with other ions frequently results in quite complex signal patterns for a single analyte, which significantly complicates the derivation of quantitative information from the mass spectra. Labeling strategies targeting the MS1 level further aggravate this situation, as multiple biological states such as healthy or diseased must be represented simultaneously. We developed an integer linear programming (ILP) approach, which can cluster signals belonging to the same peptide or protein. The algorithm is general in that it models all possible shifts of signals along the m/z axis. These shifts can be induced by different charge states of the compound, the presence of adducts (e.g., potassium or sodium), and/or a fixed mass label (e.g., from ICAT or nicotinic acid labeling), or any combination of the above. We show that our approach can be used to infer more features in labeled data sets, correct wrong charge assignments even in high-resolution MS, improve mass precision, and cluster charged species in different charge states and several adduct types.