DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans-Pseudomonas aeruginosa infection model
DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans-Pseudomonas aeruginosa infection model
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DOI：
10.1007/s00216-014-8331-5
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发表时间：
2015-02-01
影响因子：
4.3
通讯作者：
Schmitt-Kopplin, Philippe
中科院分区：
文献类型：
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作者：
Witting, Michael;Lucio, Marianna;Schmitt-Kopplin, Philippe
在代谢组学中，对更快、更全面的分析方法的需求不断增长，以应对不断扩大的生物学研究规模。直接注入离子回旋共振傅立叶变换光谱 (DI-ICR-FT-MS) 用于非靶向代谢组学，以获得系统代谢状态的高分辨率快照。我们将该技术应用于秀丽隐杆线虫-铜绿假单胞菌感染模型，并优化了培养和质谱分析所需的时间。我们的结果表明，DI-ICR-FT-MS 是一种很有前景的高通量深度非靶向代谢组学工具。我们进行了全线虫代谢组学，并恢复了秀丽隐杆线虫与病原体相互作用引起的诱导代谢变化的标记。在这项研究中，我们揭示了复杂的代谢表型，能够根据挑战进行聚类。具体来说，我们观察到铜绿假单胞菌感染后氨基酸代谢显着降低，而肠道沙门氏菌感染后糖代谢显着增加。我们还能够区分有毒野生型假单胞菌感染和减毒突变体感染，从而可以在更大的遗传筛选中使用这种方法来识别影响感染代谢表型的宿主和病原体效应子。
In metabolomics there is an ever-growing need for faster and more comprehensive analysis methods to cope with the increasing size of biological studies. Direct-infusion ion-cyclotron-resonance Fourier-transform spectrometry (DI-ICR-FT-MS) is used in non-targeted metabolomics to obtain high-resolution snapshots of the metabolic state of a system. We applied this technology to a Caenorhabditis elegans-Pseudomonas aeruginosa infection model and optimized times needed for cultivation and mass-spectrometric analysis. Our results reveal that DI-ICR-FT-MS is a promising tool for high-throughput in-depth non-targeted metabolomics. We performed whole-worm metabolomics and recovered markers of the induced metabolic changes in C. elegans brought about by interaction with pathogens. In this investigation, we reveal complex metabolic phenotypes enabling clustering based upon challenge. Specifically, we observed a marked decrease in amino-acid metabolism with infection by P. aeruginosa and a marked increase in sugar metabolism with infection by Salmonella enterica. We were also able to discriminate between infection with a virulent wild-type Pseudomonas and with an attenuated mutant, making it possible to use this method in larger genetic screens to identify host and pathogen effectors affecting the metabolic phenotype of infection.