Literature DB >> 34293862

Study of Substituted Phenethylamine Fragmentation Induced by Electrospray Ionization Mass Spectrometry and Its Application for Highly Sensitive Analysis of Neurotransmitters in Biological Samples.

Daiki Asakawa1, Eiji Sugiyama2, Hajime Mizuno2, Kenichiro Todoroki2.   

Abstract

Although liquid chromatography-tandem mass spectrometry (LC-MS/MS) equipped with electrospray ionization (ESI) is widely employed for metabolite analysis, substituted phenethylamines commonly undergo fragmentation during ESI in-source collision-induced dissociation (CID). Unexpected fragmentation hampers not only unambiguous identification but also accurate metabolite quantification. ESI in-source CID induces N-Cα bond dissociation in substituted phenethylamines lacking a β-hydroxy group to produce fragment ions with a spiro[2.5]octadienylium motif. In contrast, phenethylamines with a β-hydroxy group generate substituted 2-phenylaziridium through ESI in-source CID-induced H2O loss. The fragment ion yield produced by ESI in-source CID can be estimated by the dissociation rate constant and internal energy of the analyte ion, determined by employing density functional theory calculations and the survival yield method using a thermometer ion, respectively. Fragmentation is strongly enhanced by the presence of an β-hydroxy group, whereas N-methylation suppresses fragmentation. In particular, octopamine and noradrenaline, which contain an β-hydroxy and primary amine groups, produce more intense fragment ion signals than protonated molecules. Regarding the quantitative analysis of phenethylamines present in the mouse brain, the noradrenaline fragment ion used as the precursor in multiple reaction monitoring (MRM) provided a higher signal-to-noise ratio in the resulting spectra than protonated noradrenaline. The present method allows for the quantitative analysis of substituted phenethylamines with high sensitivity.

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Keywords:  Catecholamine; DFT; ESI in-source CID; RRKM; Survival yield

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Year:  2021        PMID: 34293862     DOI: 10.1021/jasms.1c00173

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  1 in total

1.  Utilization of Machine Learning for the Differentiation of Positional NPS Isomers with Direct Analysis in Real Time Mass Spectrometry.

Authors:  Jennifer L Bonetti; Saer Samanipour; Arian C van Asten
Journal:  Anal Chem       Date:  2022-03-17       Impact factor: 6.986

  1 in total

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