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蛋白质组消化特异性分析可用于合理设计扩展的自上而下和中间向下的蛋白质组学实验。

Proteome digestion specificity analysis for rational design of extended bottom-up and middle-down proteomics experiments.

机构信息

Biomolecular Mass Spectrometry Laboratory, Ecole Polytechnique Fédérale de Lausanne , 2 av. Forel, 1015 Lausanne, Switzerland.

出版信息

J Proteome Res. 2013 Dec 6;12(12):5558-69. doi: 10.1021/pr400522h. Epub 2013 Oct 30.

Abstract

Mass spectrometry (MS)-based bottom-up proteomics (BUP) is currently the method of choice for large-scale identification and characterization of proteins present in complex samples, such as cell lysates, body fluids, or tissues. Technically, BUP relies on MS analysis of complex mixtures of small, <3 kDa, peptides resulting from whole proteome digestion. Because of the extremely high sample complexity, further developments of detection methods and sample preparation techniques are necessary. In recent years, a number of alternative approaches such as middle-down proteomics (MDP, addressing up to 15 kDa peptides) and top-down proteomics (TDP, addressing proteins exceeding 15 kDa) have been gaining particular interest. Here we report on the bioinformatics study of both common and less frequently employed digestion procedures for complex protein mixtures specifically targeting the MDP approach. The aim of this study was to maximize the yield of protein structure information from MS data by optimizing peptide size distribution and sequence specificity. We classified peptides into four categories based on molecular weight: 0.6-3 (classical BUP), 3-7 (extended BUP), 7-15 kDa (MDP), and >15 kDa (TDP). Because of instrumentation-related considerations, we first advocate for the extended BUP approach as the potential near-future improvement of BUP. Therefore, we chose to optimize the number of unique peptides in the 3-7 kDa range while maximizing the number of represented proteins. The present study considers human, yeast, and bacterial proteomes. Results of the study can be further used for designing extended BUP or MDP experimental workflows.

摘要

基于质谱(MS)的自上而下蛋白质组学(BUP)是目前用于鉴定和描述复杂样品中蛋白质的首选方法,例如细胞裂解物、体液或组织。从技术上讲,BUP 依赖于对整个蛋白质组消化产生的小肽混合物(<3 kDa)的 MS 分析。由于样品复杂性极高,因此需要进一步开发检测方法和样品制备技术。近年来,一些替代方法,如中尺度蛋白质组学(MDP,可分析达 15 kDa 的肽)和自上而下蛋白质组学(TDP,可分析超过 15 kDa 的蛋白质)引起了特别关注。在此,我们报告了针对 MDP 方法的复杂蛋白质混合物的常用和较少使用的消化程序的生物信息学研究。本研究的目的是通过优化肽大小分布和序列特异性,从 MS 数据中最大程度地获取蛋白质结构信息。我们根据分子量将肽分为四类:0.6-3 kDa(经典 BUP)、3-7 kDa(扩展 BUP)、7-15 kDa(MDP)和>15 kDa(TDP)。由于仪器相关考虑因素,我们首先提倡扩展 BUP 方法作为 BUP 的潜在近期改进。因此,我们选择优化 3-7 kDa 范围内的独特肽数量,同时最大化代表蛋白质的数量。本研究考虑了人类、酵母和细菌蛋白质组。研究结果可进一步用于设计扩展 BUP 或 MDP 实验工作流程。

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