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知情蛋白质组学:用于自上而下蛋白质组学的开源软件包。

Informed-Proteomics: open-source software package for top-down proteomics.

作者信息

Park Jungkap, Piehowski Paul D, Wilkins Christopher, Zhou Mowei, Mendoza Joshua, Fujimoto Grant M, Gibbons Bryson C, Shaw Jared B, Shen Yufeng, Shukla Anil K, Moore Ronald J, Liu Tao, Petyuk Vladislav A, Tolić Nikola, Paša-Tolić Ljiljana, Smith Richard D, Payne Samuel H, Kim Sangtae

机构信息

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.

Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.

出版信息

Nat Methods. 2017 Sep;14(9):909-914. doi: 10.1038/nmeth.4388. Epub 2017 Aug 7.

Abstract

Top-down proteomics, the analysis of intact proteins in their endogenous form, preserves valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down liquid chromatography-tandem MS (LC-MS/MS) data sets is rapidly increasing on account of advances in instrumentation and sample-processing protocols. However, top-down mass spectra are substantially more complex than conventional bottom-up data. New algorithms and software tools for confident proteoform identification and quantification are needed. Here we present Informed-Proteomics, an open-source software suite for top-down proteomics analysis that consists of an LC-MS feature-finding algorithm, a database search algorithm, and an interactive results viewer. We compare our tool with several other popular tools using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.

摘要

自上而下的蛋白质组学,即对内源性完整蛋白质进行分析,保留了有关翻译后修饰、异构体和蛋白水解加工的宝贵信息。由于仪器设备和样品处理方案的进步,自上而下的液相色谱 - 串联质谱(LC-MS/MS)数据集的质量正在迅速提高。然而,自上而下的质谱比传统的自下而上的数据要复杂得多。因此需要新的算法和软件工具来进行可靠的蛋白质异构体鉴定和定量分析。在这里,我们展示了Informed-Proteomics,这是一个用于自上而下蛋白质组学分析的开源软件套件,它由一个LC-MS特征发现算法、一个数据库搜索算法和一个交互式结果查看器组成。我们使用人源化小鼠异种移植管腔型和基底型乳腺肿瘤样本,将我们的工具与其他几种流行工具进行比较,根据自下而上的分析,已知这些样本在蛋白质丰度上有显著差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c788/5578875/f6164ff4c149/nihms892925f1.jpg

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