Different ion mobility‐mass spectrometry coupling techniques to promote metabolomics. Issue 5 (25th January 2021)

• Record Type: Journal Article
• Authors: Delvaux, Aurélie; Rathahao‐Paris, Estelle; Alves, Sandra
• Is Part Of: Mass spectrometry reviews. Volume 41:Issue 5(2022)
• Page Start: 695
• Page End: 721
• Publication Date: 2021-01-25
• Subjects: hyphenated method -- Ion mobility‐mass spectrometry -- metabolomics -- multidimensional data; Mass spectrometry -- Periodicals; 543
• DOI: 10.1002/mas.21685
• Languages: English
• ISSNs: 0277-7037

Abstract

Abstract: Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas‐phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.