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TopPICR:用于自上而下蛋白质组学数据分析的R语言配套软件包。

TopPICR: A Companion R Package for Top-Down Proteomics Data Analysis.

作者信息

Martin Evan A, Fulcher James M, Zhou Mowei, Monroe Matthew E, Petyuk Vladislav A

机构信息

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States.

Environmental and Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington99352, United States.

出版信息

J Proteome Res. 2023 Feb 3;22(2):399-409. doi: 10.1021/acs.jproteome.2c00570. Epub 2023 Jan 11.

Abstract

Top-down proteomics is the analysis of proteins in their intact form without proteolysis, thus preserving valuable information about post-translational modifications, isoforms, and proteolytic processing. However, it is still a developing field due to limitations in the instrumentation, difficulties with the interpretation of complex mass spectra, and a lack of well-established quantification approaches. TopPIC is one of the popular tools for proteoform identification. We extended its capabilities into label-free proteoform quantification by developing a companion R package (TopPICR). Key steps in the TopPICR pipeline include filtering identifications, inferring a minimal set of protein accessions explaining the observed sequences, aligning retention times, recalibrating measured masses, clustering features across data sets, and finally compiling feature intensities using the match-between-runs approach. The output of the pipeline is an MSnSet object which makes downstream data analysis seamlessly compatible with packages from the Bioconductor project. It also provides the capability for visualizing proteoforms within the context of the parent protein sequence. The functionality of TopPICR is demonstrated on top-down LC-MS/MS data sets of 10 human-in-mouse xenografts of luminal and basal breast tumor samples.

摘要

自上而下的蛋白质组学是对完整形式的蛋白质进行分析,而不进行蛋白水解,从而保留有关翻译后修饰、异构体和蛋白水解加工的有价值信息。然而,由于仪器设备的局限性、复杂质谱解释的困难以及缺乏成熟的定量方法,它仍然是一个发展中的领域。TopPIC是用于蛋白异构体鉴定的流行工具之一。我们通过开发一个配套的R包(TopPICR)将其功能扩展到无标记的蛋白异构体定量。TopPICR流程中的关键步骤包括筛选鉴定结果、推断解释观察到的序列的最小蛋白登录号集、对齐保留时间、重新校准测量质量、跨数据集聚类特征,最后使用运行间匹配方法汇编特征强度。该流程的输出是一个MSnSet对象,它使下游数据分析与来自Bioconductor项目的包无缝兼容。它还提供了在亲本蛋白质序列背景下可视化蛋白异构体的功能。在管腔型和基底型乳腺肿瘤样本的10个人源化小鼠异种移植的自上而下LC-MS/MS数据集上展示了TopPICR的功能。

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