Simon J Perry1, Szilárd Nász1, Mansoor Saeed1. 1. SYNGENTA, Product Metabolism and Analytical Sciences, Jealott's Hill International Research Centre, Bracknell, RG42 6EY, UK.
Abstract
RATIONALE: This paper describes a strategy for the profiling and identification of metabolites based on chemical group classification using high-resolution accurate mass (HR/AM) full scan mass spectrometry (MS) and All-Ion fragmentation (AIF) MS2 data. METHODS: The proposed strategy uses a hybrid quadrupole Orbitrap (Q-Exactive) employing stepped normalised collision energy (NCE) at 35% and 80% to produce key chemically diagnostic product ions from full coverage of the product ion spectrum. This approach allows filtering of high-resolution AIF MS2 data in order to identify parent-related compounds produced following incubation in rat liver microsomes (RLMs). RESULTS: An antidepressant drug, nefazodone (NEF), was selected as the model test compound to demonstrate the proposed workflow for metabolite profiling. This resulted in the identification of three indicative chemical groups within NEF: triazolone, phenoxy and chlorophenylpiperazine. High-resolution mass spectrometry provides increased specificity to distinguish between two characteristic product ion masses m/z 154.0975 (C7 H12 N3 O) and 154.0419 (C8 H9 NCl), which are not fully resolved by spectrometers operating at nominal mass resolution, indicative of compounds containing the triazolone and chlorophenylpiperazine moieties, respectively. CONCLUSIONS: This post-acquisition processing strategy provides comprehensive detection and identification of high- and low-level metabolites from an 'all-in-one' analysis. This enables functional groups to be systematically traced across a wide range of metabolites, leading to the successful identification of 28 in vitro NEF-related metabolites. In our hands this approach has been applied to agrochemical environmental fate and dietary metabolism studies, as well as metabolomics and biomarker analysis.
RATIONALE: This paper describes a strategy for the profiling and identification of metabolites based on chemical group classification using high-resolution accurate mass (HR/AM) full scan mass spectrometry (MS) and All-Ion fragmentation (AIF) MS2 data. METHODS: The proposed strategy uses a hybrid quadrupole Orbitrap (Q-Exactive) employing stepped normalised collision energy (NCE) at 35% and 80% to produce key chemically diagnostic product ions from full coverage of the product ion spectrum. This approach allows filtering of high-resolution AIF MS2 data in order to identify parent-related compounds produced following incubation in rat liver microsomes (RLMs). RESULTS: An antidepressant drug, nefazodone (NEF), was selected as the model test compound to demonstrate the proposed workflow for metabolite profiling. This resulted in the identification of three indicative chemical groups within NEF: triazolone, phenoxy and chlorophenylpiperazine. High-resolution mass spectrometry provides increased specificity to distinguish between two characteristic product ion masses m/z 154.0975 (C7 H12 N3 O) and 154.0419 (C8 H9 NCl), which are not fully resolved by spectrometers operating at nominal mass resolution, indicative of compounds containing the triazolone and chlorophenylpiperazine moieties, respectively. CONCLUSIONS: This post-acquisition processing strategy provides comprehensive detection and identification of high- and low-level metabolites from an 'all-in-one' analysis. This enables functional groups to be systematically traced across a wide range of metabolites, leading to the successful identification of 28 in vitro NEF-related metabolites. In our hands this approach has been applied to agrochemical environmental fate and dietary metabolism studies, as well as metabolomics and biomarker analysis.