SARS-CoV-2 肽谱文库可快速、灵敏地鉴定复杂生物样本中的病毒肽。
A SARS-CoV-2 Peptide Spectral Library Enables Rapid, Sensitive Identification of Virus Peptides in Complex Biological Samples.
机构信息
Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2C4, Canada.
Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 1L7, Canada.
出版信息
J Proteome Res. 2021 May 7;20(5):2187-2194. doi: 10.1021/acs.jproteome.1c00048. Epub 2021 Mar 8.
On the basis of an analysis of (i) SARS-CoV-2 virions, (ii) SARS-CoV-2-infected VeroE6 cell lysates, and (iii) recombinant SARS-CoV-2 proteins expressed in HEK 293 cells, here we present a comprehensive SARS-CoV-2 peptide spectrum compendium, comprising 1682 high confidence peptide consensus spectra derived from 1170 peptides (of various charge states) spanning 23 virus proteins. This high quality reference set can be used, e.g., for the selection of commonly observed virus peptides for use in targeted proteomics or data-independent acquisition (DIA) approaches. Using this rich resource, we also demonstrate that a spectral matching search approach yields improved performance over the use of standard database search engines alone for the identification of virus peptides in complex biological samples.
在分析（i）SARS-CoV-2 病毒粒子、（ii）SARS-CoV-2 感染的 VeroE6 细胞裂解物和（iii）在 HEK 293 细胞中表达的重组 SARS-CoV-2 蛋白的基础上，我们在此呈现了一份全面的 SARS-CoV-2 肽谱总集，其中包含了源自 1170 条肽段（具有各种电荷状态）的 1682 条高可信度肽段共识谱，这些肽段跨越 23 种病毒蛋白。该高质量参考集可用于选择常用于靶向蛋白质组学或数据非依赖性采集（DIA）方法的常见观察到的病毒肽段。利用这一丰富的资源，我们还证明，与仅使用标准数据库搜索引擎进行病毒肽段鉴定相比，基于谱图匹配搜索的方法可显著提高在复杂生物样本中鉴定病毒肽段的性能。
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