Mass Spectrometry-Based Quantification of Tau in Human Cerebrospinal Fluid Using a Complementary Tryptic Peptide Standard

化学 胰蛋白酶 等压标记 质谱法 精氨酸 色谱法 同位素 赖氨酸 串联质量标签 定量蛋白质组学 串联质谱法 同位素稀释 肽序列 氨基酸 生物化学 蛋白质组学 蛋白质质谱法 基因 物理 量子力学
作者
Maotian Zhou,Duc M. Duong,Erik C. B. Johnson,Jingting Dai,James J. Lah,Allan I. Levey,Nicholas T. Seyfried
出处
期刊:Journal of Proteome Research [American Chemical Society]
卷期号:18 (6): 2422-2432 被引量:16
标识
DOI:10.1021/acs.jproteome.8b00920
摘要

Here, we report a method for the generation of complementary tryptic (CompTryp) isotope-labeled peptide standards for the relative and absolute quantification of proteins by mass spectrometry (MS). These standards can be digested in parallel with either trypsin (Tryp-C) or trypsin-N (Tryp-N), to generate peptides that significantly overlap in primary sequence having C- and N-terminal arginine and lysine residues, respectively. As a proof of concept, an isotope-labeled CompTryp standard was synthesized for Tau, a well-established biomarker in Alzheimer's disease (AD), which included both N- and C-terminal heavy isotope-labeled (15N and 13C) arginine residues and flanking amino acid sequences to monitor proteolytic digestion. Despite having the exact same mass, the N- and C-terminal heavy Tau peptides are distinguishable by retention time and MS/MS fragmentation profiles. The isotope-labeled Tau CompTryp standard was added to human cerebrospinal fluid (CSF) followed by parallel digestion with Tryp-N and Tryp-C. The native and isotope-labeled peptide pairs were quantified by parallel reaction monitoring (PRM) in a single assay. Notably, both tryptic peptides were effective at quantifying Tau in human CSF, and both showed a significant difference in CSF Tau levels between AD and controls. Treating these CompTryp Tau peptide measurements as independent replicates also improved the coefficient of variation and correlation with Tau immunoassays. More broadly, we propose that CompTryp standards can be generated for any protein of interest, providing an efficient method to improve the robustness and reproducibility for MS analysis of clinical and research samples.
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