Optimal Settings of Mass Spectrometry Open Search Strategy for Higher Confidence
Optimal Settings of Mass Spectrometry Open Search Strategy for Higher Confidence
复制标题
DOI：
10.1021/acs.jproteome.8b00352
复制
发表时间：
2018-11-01
影响因子：
4.4
通讯作者：
Zhang, Gong
中科院分区：
文献类型：
--
作者：
Li, Dehua;Lu, Shaohua;Zhang, Gong
在大多数蛋白质组质谱分析实验中，超过一半的质谱不能被识别，主要是由于各种修饰。开放搜索策略允许更大的前体容忍度来利用更多的光谱，特别是那些具有翻译后修饰的光谱；然而，缺乏基于独立信息的彻底质量控制。在这里，我们使用基于翻译组测序（RNC-seq）的“可疑发现率（SDR）”作为独立来源，参考稳态细胞中蛋白质组开放搜索结果。我们发现开放搜索策略提高了光谱利用率，但代价是增加了缺乏翻译证据的可疑识别。我们进一步发现，将多肽FDR限制在0.1%以下可以有效地控制开放搜索方法的可疑鉴定，从而提高多肽鉴定的可信度，其修改程度与传统窄窗搜索的水平相当。然后，我们展示了成功的和有效的鉴定27个单氨基酸变异从两个细胞系使用开放的搜索策略，没有预定义的数据库。这些结果验证了开放搜索方法对高质量蛋白质组鉴定的正确使用，这些鉴定包含翻译后修饰和单氨基酸多态性的信息。
In most proteome mass spectrometry experiments, more than half of the mass spectra cannot be identified, mainly because of various modifications. The open search strategy allows for a larger precursor tolerance to utilize more spectra, especially those with post-translational modifications; however, thorough quality control based on independent information is lacking. Here, we used the "Suspicious Discovery Rate (SDR)" based on translatome sequencing (RNC-seq) as an independent source to reference the proteome open search results in steady-state cells. We found that the open search strategy increased the spectra utilization with the cost of increased suspicious identifications that lack translation evidence. We further found that restricting the peptide FDR below 0.1% efficiently controlled the suspicious identifications of open search methods and thus enhanced the confidence of the peptide identification with modifications comparable to the level of the traditional narrow window search. We then demonstrated the successful and validated identification of 27 single amino acid variations from the spectra of two cell lines using the open search strategy without a predefined database. These results validated the proper use of open search methods for higher-quality proteome identifications with information on post-translational modifications and single amino acid polymorphisms.