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开源软件,用于高分辨率 MALDI-MS 光谱的自动注释和可视化。

: Open-Source Software for Automated Annotation and Visualization of High Resolution MALDI-MS Spectra.

机构信息

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.

Environmental Molecular Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.

出版信息

J Am Soc Mass Spectrom. 2023 Sep 6;34(9):2061-2064. doi: 10.1021/jasms.3c00180. Epub 2023 Jul 31.

DOI:10.1021/jasms.3c00180
PMID:37523489
Abstract

Due to its speed, accuracy, and adaptability to various sample types, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has become a popular method to identify molecular isotope profiles from biological samples. Often MALDI-MS data do not include tandem MS fragmentation data, and thus the identification of compounds in samples requires external databases so that the accurate mass of detected signals can be matched to known molecular compounds. Most relevant MALDI-MS software tools developed to confirm compound identifications are focused on small molecules (., metabolites, lipids) and cannot be easily adapted to protein data due to their more complex isotopic distributions. Here, we present an R package called for the automated annotation of MALDI-MS data for multiple datatypes: intact proteins, peptides, and glycans. This tool accepts already derived molecular formulas or, for proteomics applications, can derive molecular formulas from a list of input peptides or proteins including proteins with post-translational modifications. Visualization of all matched isotopic profiles is provided in a highly accessible HTML format called a trelliscope display, which allows users to filter and sort by several parameters such as match scores and the number of peaks matched. simplifies the annotation and visualization of MALDI-MS data for downstream analyses.

摘要

由于其速度、准确性和对各种样本类型的适应性,基质辅助激光解吸/电离质谱(MALDI-MS)已成为一种从生物样本中识别分子同位素分布的流行方法。通常情况下,MALDI-MS 数据不包括串联 MS 碎片数据,因此,样品中化合物的鉴定需要外部数据库,以便检测到的信号的精确质量能够与已知的分子化合物相匹配。大多数用于确认化合物鉴定的相关 MALDI-MS 软件工具都专注于小分子(例如代谢物、脂质),由于其更复杂的同位素分布,因此不能轻易适用于蛋白质数据。在这里,我们提出了一个名为的 R 包,用于自动注释 MALDI-MS 数据的多种数据类型:完整蛋白质、肽和聚糖。该工具接受已经推导出来的分子公式,或者对于蛋白质组学应用,可以从输入的肽或蛋白质列表中推导分子公式,包括具有翻译后修饰的蛋白质。所有匹配的同位素分布都以一种名为 trelliscope 显示的高度可访问的 HTML 格式提供,允许用户根据匹配分数和匹配的峰数等多个参数进行过滤和排序。简化了 MALDI-MS 数据的注释和可视化,以便进行下游分析。

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