Improving Qualitative and Quantitative Performance for MSE-based Label-free Proteomics
Improving Qualitative and Quantitative Performance for MSE-based Label-free Proteomics
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DOI：
10.1021/pr300776t
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发表时间：
2013-06-01
影响因子：
4.4
通讯作者：
Gatto, Laurent
中科院分区：
文献类型：
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作者：
Bond, Nicholas J.;Shliaha, Pavel V.;Gatto, Laurent
由于质谱分析的高技术重复性，数据无关方法(例如MSE)的无标记定量越来越受欢迎。最近推出的Synapt混合仪器能够将离子迁移率分离结合到质谱分析中，现在可以获取高清晰度MSE数据(HDMSE)。与MSE相比，HDMSE能够实现更深的蛋白质组覆盖和更有信心的多肽识别，而后者提供了更高的定量动态范围。我们已经开发了Synapter AS，这是一种多功能工具，可以更好地评估Waters仪器上独立于数据的采集结果。我们证明，Synapter可以用于结合HDMSE和MSE数据，以实现HDMSE提供的更深层次的蛋白质组覆盖，以及由MSE提供的更准确的高强度多肽的定量。对于喜欢只在一种模式下运行样本的用户，Synapter允许其他有用的功能，如错误发现率估计、对肽匹配类型和质量错误的过滤，以及填充缺失值。我们的软件与现有工具集成，从而允许我们通过一系列不同的方法轻松地将多肽定量信息结合到蛋白质定量中。
Label-free quantitation by data independent methods (for instance MSE) is growing in popularity due to the high technical reproducibility of mass spectrometry analysis. The recent introduction of Synapt hybrid instruments capable of incorporating ion mobility separation within mass spectrometry analysis now allows acquisition of high definition MSE data (HDMSE). HDMSE enables deeper proteome coverage and more confident peptide identifications when compared to MSE, while the latter offers a higher dynamic range for quantitation. We have developed synapter as, a versatile tool to better evaluate the results of data independent acquisitions on Waters instruments. We demonstrate that synapter can be used to combine HDMSE and MSE data to achieve deeper proteome coverage delivered by HDMSE and more accurate quantitation for high intensity peptides, delivered by MSE. For users who prefer to run samples exclusively in one mode, synapter allows other useful functionality like false discovery rate estimation, filtering on peptide match type and mass error, and filling missing values. Our software integrates with existing tools, thus permitting us to easily combine peptide quantitation information into protein quantitation by a range of different approaches.