ArticleAnalytical and bioanalytical chemistry2022
N-Alkylpyridinium sulfonates for retention time indexing in reversed-phase-liquid chromatography-mass spectrometry-based metabolomics.
Article in Analytical and bioanalytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Times are changing but order matters: transferable prediction of small-molecule liquid chromatography retention times.Nature methods · 2026Article
- ToxBase: A Multidimensional ToxCast Reference Database for High-Throughput Human Exposome Analysis.Environmental science & technology · 2026Article
- Integrated bioactivity assessment of the cyanobacterium plectonema terebrans extract: an in vitro and in silico study.Antonie van Leeuwenhoek · 2026Article
- Identifying Food Packaging Migrants: Current Analytical Capabilities, Challenges, and Future Prospects.Comprehensive reviews in food science and food safety · 2026Review
- Metabolite Annotation and Identification in R.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Do experimental projection methods outcompete retention time prediction models in non-target screening? A case study on LC/HRMS interlaboratory comparison data.The Analyst · 2025Article
- Comprehensive profiling of folates across polyglutamylation and one-carbon states.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- [Construction of a machine learning ensemble prediction model for gas chromatographic retention index on stationary phases with different polarities].Se pu = Chinese journal of chromatography · 2025Article
- Nontargeted Metabolomics Using the Sciex ZenoTOF 7600.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Bio- and Chemoinformatic Approaches for Metabolomics Data Analysis.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Navigating common pitfalls in metabolite identification and metabolomics bioinformatics.Metabolomics : Official journal of the Metabolomic Society · 2024Review
- [Alignment method for metabolite chromatographic peaks using anSe pu = Chinese journal of chromatography · 2024Article
- Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data.Briefings in bioinformatics · 2023Article
- Prediction of Retention Time and Collision Cross Section (CCSJournal of chemical information and modeling · 2022Article
- Critical assessment of chromatographic metadata in publicly available metabolomics data repositories.Metabolomics : Official journal of the Metabolomic Society · 2022Article
- Development of Liquid Chromatographic Retention Index Based on Cocamide Diethanolamine Homologous Series (C(Analytical chemistry · 2022Article
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5 authors.
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Abstract
Chromatographic retention time information is valuable, orthogonal information to MS and MS/MS data that can be used in metabolite identification. However, while comparison of MS data between different instruments is possible to a certain degree, retention times (RTs) can vary extensively, even when nominally the same phase system is used. Different factors such as column dead volumes, system extra column volume, and gradient dwell volume can influence absolute retention times. Retention time indexing (RTI), routinely employed in gas chromatography (e.g., Kovats index), allows compensation for deviations in experimental conditions. Different systems have been reported for RTI in liquid chromatography, but none of them have been applied to metabolomics to the same extent as they have with GC. Recently, a more universal RTI system has been reported based on a homologous series of N-alkylpyridinium sulfonates (NAPS). These reference standards ionize in both positive and negative ionization modes and are UV-active. We demonstrate the NAPS can be used for retention time indexing in reversed-phase-liquid chromatography-mass spectrometry (RP-LC-MS)-based metabolomics. Having measured >500 metabolite standards and varying flow rate and column dimension, we show that conversion of RT to retention indices (RI) substantially improves comparability of retention information and enables to use of RI for metabolite annotation and identification. Graphical Abstract.
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