Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition
Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition
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DOI：
10.1074/mcp.ra119.001705
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发表时间：
2020-02-01
影响因子：
7
通讯作者：
Reiter, Lukas
中科院分区：
文献类型：
--
作者：
Huang, Ting;Bruderer, Roland;Reiter, Lukas
在自下而上的无标记发现蛋白质组学中，生物样品以数据依赖（DDA）或数据独立（DIA）的方式获得，肽信号以完整（MS 1）和片段（MS 2）的形式记录。虽然DDA仅具有用于定量的MS 1空间，但DIA包含高定量质量的MS 1和MS 2。复杂生物基质（如组织或细胞）的DIA图谱可能包含定量干扰，并且MS 1和MS 2信号处的干扰通常是独立的。当比较生物条件时，干扰可能会损害差异肽或蛋白质丰度的检测，并导致假阳性或假阴性结论。我们假设MS 1和MS 2定量信号的组合使用可以提高我们检测差异丰度蛋白质的能力。因此，我们开发了一个统计程序，将MS 1和MS 2的DIA的定量信息。我们基准的性能的MS 1-MS 2-组合的方法，单独使用MS 1或MS 2的DIA使用四个以前公布的控制混合物，以及在两个以前未公布的控制混合物。在大多数比较中，联合方法优于单独使用MS 1或MS 2。这对于低倍数变化、少量重复以及MS 1和MS 2质量相似的情况下的比较尤其如此。当应用于以前未发表的肺癌研究时，MS 1-MS 2组合方法增加了已知激活途径的覆盖率。由于最近的技术发展继续提高MS 1信号的质量（例如，使用Orbitrap仪器的BoxCar扫描模式），MS 1和MS 2信息的组合对于未来DIA数据的统计分析具有很高的潜力。
In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.