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尿液蛋白质组库生成方法在数据非依赖采集质谱分析中的评估及其在正常尿液蛋白质组分析中的应用

Evaluation of Urinary Proteome Library Generation Methods on Data-Independent Acquisition MS Analysis and its Application in Normal Urinary Proteome Analysis.

作者信息

Zhao Mindi, Liu Xiang, Sun Haidan, Guo Zhengguang, Liu Xiaoyan, Sun Wei

机构信息

Department of Laboratory Medicine, Beijing Hospital, National Center of Gerontology, Beijing, 100730, China.

Core Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.

出版信息

Proteomics Clin Appl. 2019 Sep;13(5):e1800152. doi: 10.1002/prca.201800152. Epub 2019 May 2.

DOI:10.1002/prca.201800152
PMID:31017348
Abstract

PURPOSE

As an important part of the data-independent acquisition-mass spectrometry (DIA-MS) analysis approach, spectral library generation is closely related to the final protein identification and quantitation.

EXPERIMENTAL DESIGN

In this study, an attempt is made to evaluate the influence of different sample separation methods (reversed-phase liquid chromatography (RPLC) linear gradient elution and spin column step gradient fractionation) and data acquisition modes (data-dependent acquisition (DDA) and DIA) on library generation of the human urine proteome.

RESULTS

The RPLC separation method provides more proteins for generating the library than the spin column; however, the spin column library leads to identification of more proteins when used for the urine proteome analysis. The DDA mode can provide a larger spectral library than the DIA mode and the DDA-library leads to more protein identifications in the study. Use of a combined urinary protein library provides the most complete protein and peptide information, and the DIA approach can provide accurate protein quantitative information even for low-abundance proteins.

CONCLUSIONS AND CLINICAL RELEVANCE

When the combined library is used to analyze the normal individual urine proteome (18 males and 18 females), gender-related and age-related proteins are discovered and functionally analyzed. This strategy may benefit urine proteome DIA analysis.

摘要

目的

作为非数据依赖采集质谱(DIA-MS)分析方法的重要组成部分,谱图库生成与最终的蛋白质鉴定和定量密切相关。

实验设计

在本研究中,尝试评估不同的样品分离方法(反相液相色谱(RPLC)线性梯度洗脱和旋转柱阶梯梯度分级分离)以及数据采集模式(数据依赖采集(DDA)和DIA)对人尿蛋白质组谱图库生成的影响。

结果

RPLC分离方法比旋转柱能为生成谱图库提供更多蛋白质;然而,旋转柱谱图库用于尿蛋白质组分析时能鉴定出更多蛋白质。DDA模式比DIA模式能提供更大的谱图库,且在本研究中DDA谱图库能鉴定出更多蛋白质。使用组合尿蛋白质谱图库可提供最完整的蛋白质和肽信息,并且DIA方法即使对于低丰度蛋白质也能提供准确的蛋白质定量信息。

结论及临床意义

当使用组合谱图库分析正常个体尿蛋白质组(18名男性和18名女性)时,发现了与性别和年龄相关的蛋白质并进行了功能分析。该策略可能有益于尿蛋白质组DIA分析。

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