利用差分信号滤波(DSF)和图像结构滤波(ISF)方法对细菌代谢物进行非目标质谱成像。

IF 3.1 2区 化学 Q2 BIOCHEMICAL RESEARCH METHODS
Pierre Burguet, Raphaël La Rocca, Christopher Kune, Déborah Tellatin, Nudzejma Stulanovic, Augustin Rigolet, Johann Far, Marc Ongena, Sébastien Rigali, Loïc Quinton
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引用次数: 0

摘要

基质辅助激光解吸电离(MALDI)质谱成像(MSI)是一种无标记技术,可生成像素包含质谱的图像。该技术可将组织切片或细菌培养基等表面上从代谢物到蛋白质等(生物)分子的空间分布可视化。MALDI-MSI 的一个特别令人兴奋的应用实例是,它可以定位微生物相互作用和化学交流过程中产生的离子化化合物,提供特定时间代谢组的分子快照。由于生成的 MSI 数据量大且复杂,因此数据处理具有挑战性,需要使用计算方法。尽管最近取得了一些进展,但目前可用的商业软件主要依靠统计工具来识别数据集内的模式、相似性和差异。然而,根据微生物学背景(如共培养实验)对给定数据集特有的 m/z 值进行分组仍然需要繁琐的人工分析。在此,我们提出了一种利用阴性对照和受测实验条件之间的差异信号(即差异信号过滤法(Differential Signal Filtering,DSF))的非靶向方法,以及利用图像结构过滤法(Image Structure Filtering,ISF)对离子图像进行评分,并结合对照和相关条件之间的折叠变化分数。这些方法首先被应用于大肠杆菌和共生链霉菌的共培养实验,揭示了细菌相互作用过程中的特定 MS 信号。此外,还对两个案例进行了研究:(i) 纤维素生物糖介导的疥疮链霉菌致病性诱导,疥疮链霉菌是根茎作物常见疮痂病的致病菌;(ii) 铁抑制疥疮链霉菌嗜苷酸盐的产生。本报告提出了适用于微生物学情况的 MALDI-MSI 数据处理指南,并加强了特定培养条件下的离子峰注释。报告讨论了这些方法的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Exploiting Differential Signal Filtering (DSF) and Image Structure Filtering (ISF) Methods for Untargeted Mass Spectrometry Imaging of Bacterial Metabolites.

Exploiting Differential Signal Filtering (DSF) and Image Structure Filtering (ISF) Methods for Untargeted Mass Spectrometry Imaging of Bacterial Metabolites.

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a label-free technique, producing images where pixels contain mass spectra. The technique allows the visualization of the spatial distribution of (bio)molecules from metabolites to proteins, on surfaces such as tissues sections or bacteria culture media. One particularly exciting example of MALDI-MSI use rests on its potential to localize ionized compounds produced during microbial interactions and chemical communication, offering a molecular snapshot of metabolomes at a given time. The huge size and the complexity of generated MSI data make the processing of the data challenging, which requires the use of computational methods. Despite recent advances, currently available commercial software relies mainly on statistical tools to identify patterns, similarities, and differences within data sets. However, grouping m/z values unique to a given data set according to microbiological contexts, such as coculture experiments, still requires tedious manual analysis. Here we propose a nontargeted method exploiting the differential signals between negative controls and tested experimental conditions, i.e., differential signal filtering (DSF), and a scoring of the ion images using image structure filtering (ISF) coupled with a fold change score between the controls and the conditions of interest. These methods were first applied to coculture experiments involving Escherichia coli and Streptomyces coelicolor, revealing specific MS signals during bacterial interaction. Two case studies were also investigated: (i) cellobiose-mediated induction for the pathogenicity of Streptomyces scabiei, the causative agent of common scab on root and tuber crops, and (ii) iron-repressed production of siderophores of S. scabiei. This report proposes guidelines for MALDI-MSI data treatment applied in the case of microbiology contexts, with enhanced ion peak annotation in specific culture conditions. The strengths and weaknesses of the methods are discussed.

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来源期刊
CiteScore
5.50
自引率
9.40%
发文量
257
审稿时长
1 months
期刊介绍: The Journal of the American Society for Mass Spectrometry presents research papers covering all aspects of mass spectrometry, incorporating coverage of fields of scientific inquiry in which mass spectrometry can play a role. Comprehensive in scope, the journal publishes papers on both fundamentals and applications of mass spectrometry. Fundamental subjects include instrumentation principles, design, and demonstration, structures and chemical properties of gas-phase ions, studies of thermodynamic properties, ion spectroscopy, chemical kinetics, mechanisms of ionization, theories of ion fragmentation, cluster ions, and potential energy surfaces. In addition to full papers, the journal offers Communications, Application Notes, and Accounts and Perspectives
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