Advanced Sample Preparation Techniques for MS Analysis

Picó, Yolanda

doi:10.1002/9781119070771.ch3

Cited by 3 publications

(1 citation statement)

References 153 publications

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“…Metabolites are a direct consequence of gene expression, metabolism, dietary habits, and environmental exposure. 1,2 Endogenous and exogenous metabolites are involved in organism homeostasis, as well as pathological or toxic processes. Comprehensive or untargeted metabolomics involves the whole metabolites' compartment and is complicated due to the large variety of physicochemical properties the metabolites possess.…”

Section: Introductionmentioning

confidence: 99%

Sample preparation for polar metabolites in bioanalysis

Drouin

Rudaz

Schappler

2018

Analyst

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Sample preparation is a primary step of any bioanalytical workflow, especially in metabolomics analysis where maximum information has to be obtained without spoiling the analytical instrument. Because of their biological implication, highly polar metabolites, such as amino acids, nucleobases, and catecholamines seem to attract growing interest in the field of comprehensive metabolomics analysis although their extraction from the matrix remains a real challenge. In this paper, we discuss about the actual practice and issues of hydrophilic metabolites' extraction, including new solutions and perspectives to improve their phase transfer from a complex biological sample to a clean extract prior to analysis.

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Section: Introductionmentioning

confidence: 99%

Sample preparation for polar metabolites in bioanalysis

Drouin

Rudaz

Schappler

2018

Analyst

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Evaluation of ion mobility in capillary electrophoresis coupled to mass spectrometry for the identification in metabolomics

et al. 2020

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Currently, feature annotation remains one of the main challenges in untargeted metabolomics. In this context, the information provided by high‐resolution mass spectrometry (HRMS) in addition to accurate mass can improve the quality of metabolite annotation, and MS/MS fragmentation patterns are widely used. Accurate mass and a separation index, such as retention time or effective mobility (μeff), in chromatographic and electrophoretic approaches, respectively, must be used for unequivocal metabolite identification. The possibility of measuring collision cross‐section (CCS) values by using ion mobility (IM) is becoming increasingly popular in metabolomic studies thanks to the new generation of IM mass spectrometers. Based on their similar separation mechanisms involving electric field and the size of the compounds, the complementarity of DTCCSN2 and μeff needs to be evaluated. In this study, a comparison of DTCCSN2 and μeff was achieved in the context of feature identification ability in untargeted metabolomics by capillary zone electrophoresis (CZE) coupled with HRMS. This study confirms the high correlation of DTCCSN2 with the mass of the studied metabolites as well as the orthogonality between accurate mass and μeff, making this combination particularly interesting for the identification of several endogenous metabolites. The use of IM‐MS remains of great interest for facilitating the annotation of neutral metabolites present in the electroosmotic flow (EOF) that are poorly or not separated by CZE.

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