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亲水作用色谱代谢组学的源内 CID 升压和协变离子分析。

In-Source CID Ramping and Covariant Ion Analysis of Hydrophilic Interaction Chromatography Metabolomics.

机构信息

Department of Medicine, Rutgers-Robert Wood Johnson Medical School, New Brunswick, New Jersey 08901, United States.

Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey 08903, United States.

出版信息

Anal Chem. 2020 Apr 7;92(7):4829-4837. doi: 10.1021/acs.analchem.9b04181. Epub 2020 Mar 13.

Abstract

A large proportion of the complexity and redundancy of LC-MS metabolomics data comes from adduct formation. To reduce such redundancy, many tools have been developed to recognize and annotate adduct ions. These tools rely on predefined adduct lists that are generated empirically from reversed-phase LC-MS studies. In addition, hydrophilic interaction chromatography (HILIC) is gaining popularity in metabolomics studies due to its enhanced performance over other methods for polar compounds. HILIC methods typically use high concentrations of buffer salts to improve chromatographic performance. Therefore, it is necessary to analyze adduct formation in HILIC metabolomics. To this end, we developed ariant o nalysis (COVINA) to investigate metabolite adduct formation. Using this tool, we completely annotated 201 adduct and fragment ions from 10 metabolites. Many of the metabolite adduct ions were found to contain cluster ions corresponding to mobile phase additives. We further utilized COVINA to find the major ionized forms of metabolites. Our results show that for some metabolites, the adduct ion signals can be >200-fold higher than the signals from the deprotonated form, offering better sensitivity for targeted metabolomics analysis. Finally, we developed an in-source CID ramping (InCIDR) method to analyze the intensity changes of the adduct and fragment ions from metabolites. Our analysis demonstrates a promising method to distinguish the protonated and deprotonated ions of metabolites from the adduct and fragment ions.

摘要

LC-MS 代谢组学数据的复杂性和冗余性很大一部分来自于加合物的形成。为了减少这种冗余,已经开发了许多工具来识别和注释加合物离子。这些工具依赖于经验上从反相 LC-MS 研究中生成的预定义加合物列表。此外,亲水作用色谱(HILIC)由于其对极性化合物的性能优于其他方法,在代谢组学研究中越来越受欢迎。HILIC 方法通常使用高浓度的缓冲盐来提高色谱性能。因此,有必要分析 HILIC 代谢组学中的加合物形成。为此,我们开发了 ariant o nalysis (COVINA) 来研究代谢物加合物的形成。使用此工具,我们完全注释了 10 种代谢物中的 201 种加合物和碎片离子。许多代谢物加合物离子被发现含有与流动相添加剂相对应的簇离子。我们进一步利用 COVINA 来寻找代谢物的主要电离形式。我们的结果表明,对于一些代谢物,加合物离子信号可以比去质子化形式的信号高 200 倍以上,为靶向代谢组学分析提供了更好的灵敏度。最后,我们开发了一种源内 CID 斜坡(InCIDR)方法来分析代谢物的加合物和碎片离子的强度变化。我们的分析表明,这是一种有前途的方法,可以区分代谢物的质子化和去质子化离子与加合物和碎片离子。

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