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光谱库检索可提高人类血浆蛋白质组学中 TMTpro 标记肽的分配。

Spectral library search for improved TMTpro labelled peptide assignment in human plasma proteomics.

机构信息

Department of Clinical Biochemistry, Odense University Hospital, Odense, Denmark.

Computational and Experimental Biology Group, CEDOC, Chronic Diseases Research Centre, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Lisbon, Portugal.

出版信息

Proteomics. 2024 Mar;24(6):e2300236. doi: 10.1002/pmic.202300236. Epub 2023 Sep 14.

Abstract

Clinical biomarker discovery is often based on the analysis of human plasma samples. However, the high dynamic range and complexity of plasma pose significant challenges to mass spectrometry-based proteomics. Current methods for improving protein identifications require laborious pre-analytical sample preparation. In this study, we developed and evaluated a TMTpro-specific spectral library for improved protein identification in human plasma proteomics. The library was constructed by LC-MS/MS analysis of highly fractionated TMTpro-tagged human plasma, human cell lysates, and relevant arterial tissues. The library was curated using several quality filters to ensure reliable peptide identifications. Our results show that spectral library searching using the TMTpro spectral library improves the identification of proteins in plasma samples compared to conventional sequence database searching. Protein identifications made by the spectral library search engine demonstrated a high degree of complementarity with the sequence database search engine, indicating the feasibility of increasing the number of protein identifications without additional pre-analytical sample preparation. The TMTpro-specific spectral library provides a resource for future plasma proteomics research and optimization of search algorithms for greater accuracy and speed in protein identifications in human plasma proteomics, and is made publicly available to the research community via ProteomeXchange with identifier PXD042546.

摘要

临床生物标志物的发现通常基于人血浆样本的分析。然而,血浆的高动态范围和复杂性对基于质谱的蛋白质组学分析提出了重大挑战。目前,提高蛋白质鉴定的方法需要繁琐的分析前样本制备。在这项研究中,我们开发并评估了一种 TMTpro 特异性的光谱库,以提高人类血浆蛋白质组学中的蛋白质鉴定。该库通过 LC-MS/MS 分析高度分级的 TMTpro 标记的人血浆、人细胞裂解物和相关动脉组织构建。该库使用几个质量过滤进行了精心处理,以确保可靠的肽鉴定。我们的结果表明,与传统的序列数据库搜索相比,使用 TMTpro 光谱库进行光谱库搜索可提高血浆样品中蛋白质的鉴定。通过光谱库搜索引擎进行的蛋白质鉴定与序列数据库搜索引擎具有高度的互补性,表明在不进行额外的分析前样本制备的情况下,可以增加蛋白质鉴定的数量。TMTpro 特异性光谱库为未来的血浆蛋白质组学研究提供了资源,并优化了搜索算法,以提高人类血浆蛋白质组学中蛋白质鉴定的准确性和速度,该光谱库通过 ProteomeXchange 以标识符 PXD042546 向研究界公开。

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