4.5 Review

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

期刊

MASS SPECTROMETRY REVIEWS
卷 41, 期 5, 页码 722-765

出版社

WILEY
DOI: 10.1002/mas.21686

关键词

CCS; cIM-MS; collision cross-section; DTIM-MS; FAIM-MS; IM-MS; lipids; metabolites; MS imaging; MSI; spatial lipidomics; spatial metabolomics; TIM-MS; TWIM-MS

资金

  1. Regione Lombardia POR FESR
  2. Fondazione Gigi & Pupa Ferrari Onlus

向作者/读者索取更多资源

Researchers are utilizing ion mobility mass spectrometry (IM-MS) for metabolomics and lipidomics applications, which offers advantages such as measuring collision cross-section values, improving peak capacity and signal-to-noise ratio, and coupling with various fragmentation modes. These advancements provide a more robust tool for identification, quantification, and structural characterization in the field.
Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据