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气相色谱/四极杆-轨道阱质谱仪的开发,第二部分:发现代谢组学的新方法

Development of a GC/Quadrupole-Orbitrap mass spectrometer, part II: new approaches for discovery metabolomics.

作者信息

Peterson Amelia C, Balloon Allison J, Westphall Michael S, Coon Joshua J

机构信息

Departments of Chemistry and ‡Biomolecular Chemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.

出版信息

Anal Chem. 2014 Oct 21;86(20):10044-51. doi: 10.1021/ac5014755. Epub 2014 Sep 10.

Abstract

Identification of unknown peaks in gas chromatography/mass spectrometry (GC/MS)-based discovery metabolomics is challenging, and remains necessary to permit discovery of novel or unexpected metabolites that may elucidate disease processes and/or further our understanding of how genotypes relate to phenotypes. Here, we introduce two new technologies and an analytical workflow that can facilitate the identification of unknown peaks. First, we report on a GC/Quadrupole-Orbitrap mass spectrometer that provides high mass accuracy, high resolution, and high sensitivity analyte detection. Second, with an "intelligent" data-dependent algorithm, termed molecular-ion directed acquisition (MIDA), we maximize the information content generated from unsupervised tandem MS (MS/MS) and selected ion monitoring (SIM) by directing the MS to target the ions of greatest information content, that is, the most-intact ionic species. We combine these technologies with (13)C- and (15)N-metabolic labeling, multiple derivatization and ionization types, and heuristic filtering of candidate elemental compositions to achieve (1) MS/MS spectra of nearly all intact ion species for structural elucidation, (2) knowledge of carbon and nitrogen atom content for every ion in MS and MS/MS spectra, (3) relative quantification between alternatively labeled samples, and (4) unambiguous annotation of elemental composition.

摘要

在基于气相色谱/质谱联用(GC/MS)的发现代谢组学中,识别未知峰具有挑战性,但对于发现可能阐明疾病过程和/或进一步加深我们对基因型与表型关系理解的新型或意外代谢物而言,这仍然是必要的。在此,我们介绍两种新技术和一种分析流程,它们有助于识别未知峰。首先,我们报告了一种气相色谱/四极杆-轨道阱质谱仪,它能提供高质量精度、高分辨率和高灵敏度的分析物检测。其次,通过一种名为分子离子导向采集(MIDA)的“智能”数据依赖算法,我们通过引导质谱仪靶向信息含量最高的离子,即最完整的离子物种,来最大化从无监督串联质谱(MS/MS)和选择离子监测(SIM)生成的信息内容。我们将这些技术与(13)C和(15)N代谢标记、多种衍生化和电离类型以及候选元素组成的启发式过滤相结合,以实现:(1)几乎所有完整离子物种的MS/MS光谱用于结构解析;(2)MS和MS/MS光谱中每个离子的碳和氮原子含量信息;(3)交替标记样品之间的相对定量;以及(4)元素组成的明确注释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f2d/4204910/b859aadfb564/ac-2014-014755_0002.jpg

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