Su Zhi-Duan, Sheng Quan-Hu, Li Qing-Run, Chi Hao, Jiang Xi, Yan Zheng, Fu Ning, He Si-Min, Khaitovich Philipp, Wu Jia-Rui, Zeng Rong
Key Laboratory of Systems Biology, Chinese Academy of Sciences, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Shanghai 200031, China.
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
J Mol Cell Biol. 2014 Oct;6(5):421-33. doi: 10.1093/jmcb/mju031. Epub 2014 Jul 9.
The detection of single amino-acid variants (SAVs) usually depends on single-nucleotide polymorphisms (SNPs) database. Here, we describe a novel method that discovers SAVs at proteome level independent of SNPs data. Using mass spectrometry-based de novo sequencing algorithm, peptide-candidates are identified and compared with theoretical protein database to generate SAVs under pairing strategy, which is followed by database re-searching to control false discovery rate. In human brain tissues, we can confidently identify known and novel protein variants with diverse origins. Combined with DNA/RNA sequencing, we verify SAVs derived from DNA mutations, RNA alternative splicing, and unknown post-transcriptional mechanisms. Furthermore, quantitative analysis in human brain tissues reveals several tissue-specific differential expressions of SAVs. This approach provides a novel access to high-throughput detection of protein variants, which may offer the potential for clinical biomarker discovery and mechanistic research.
单氨基酸变体(SAV)的检测通常依赖于单核苷酸多态性(SNP)数据库。在此,我们描述了一种新方法,该方法可在蛋白质组水平上独立于SNP数据发现SAV。使用基于质谱的从头测序算法,鉴定肽候选物并与理论蛋白质数据库进行比较,以在配对策略下生成SAV,随后进行数据库重新搜索以控制错误发现率。在人脑组织中,我们可以可靠地鉴定出具有不同来源的已知和新型蛋白质变体。结合DNA/RNA测序,我们验证了源自DNA突变、RNA可变剪接和未知转录后机制的SAV。此外,在人脑组织中的定量分析揭示了几种SAV的组织特异性差异表达。这种方法为蛋白质变体的高通量检测提供了一种新途径,这可能为临床生物标志物发现和机制研究提供潜力。