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High-Throughput Fractionation Coupled to Mass Spectrometry for Improved Quantitation in Metabolomics

[Image: see text] Metabolomics is emerging as an important field in life sciences. However, a weakness of current mass spectrometry (MS) based metabolomics platforms is the time-consuming analysis and the occurrence of severe matrix effects in complex mixtures. To overcome this problem, we have deve...

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Detalles Bibliográficos
Autores principales: van der Laan, Tom, Dubbelman, Anne-Charlotte, Duisters, Kevin, Kindt, Alida, Harms, Amy C., Hankemeier, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7871441/
https://www.ncbi.nlm.nih.gov/pubmed/33054161
http://dx.doi.org/10.1021/acs.analchem.0c01375
Descripción
Sumario:[Image: see text] Metabolomics is emerging as an important field in life sciences. However, a weakness of current mass spectrometry (MS) based metabolomics platforms is the time-consuming analysis and the occurrence of severe matrix effects in complex mixtures. To overcome this problem, we have developed an automated and fast fractionation module coupled online to MS. The fractionation is realized by the implementation of three consecutive high performance solid-phase extraction columns consisting of a reversed phase, mixed-mode anion exchange, and mixed-mode cation exchange sorbent chemistry. The different chemistries resulted in an efficient interaction with a wide range of metabolites based on polarity, charge, and allocation of important matrix interferences like salts and phospholipids. The use of short columns and direct solvent switches allowed for fast screening (3 min per polarity). In total, 50 commonly reported diagnostic or explorative biomarkers were validated with a limit of quantification that was comparable with conventional LC–MS(/MS). In comparison with a flow injection analysis without fractionation, ion suppression decreased from 89% to 25%, and the sensitivity was 21 times higher. The validated method was used to investigate the effects of circadian rhythm and food intake on several metabolite classes. The significant diurnal changes that were observed stress the importance of standardized sampling times and fasting states when metabolite biomarkers are used. Our method demonstrates a fast approach for global profiling of the metabolome. This brings metabolomics one step closer to implementation into the clinic.