Bridging Speed and Confidence in Metabolomics: A Retention Time and MS2-Guided HILIC-Orbitrap Workflow

Abstract Personalized treatment strategies are rising within modern medicine approaches to dynamic and heterogeneous diseases such as cancer. Human metabolism is important for the understanding of these diseases and their mechanisms, but metabolomics remains often unused in multiomics approaches due to practical challenges in sample analysis and, more importantly, data analysis. Automated feature analysis with many false-positive annotations and a rather long analysis time is effectively hindering rapid metabolite screening, as it would be needed in medical research. Here, we report a novel and efficient workflow for rapid metabolite screening with the capability of yielding high-quality metabolomics data, including data analysis. Therefore, a HILIC (superficially porous sulfobetaine) method has been optimized to separate polar metabolites in complex samples in less than 9 min, and an open-source compatible retention time database has been implemented for this rapid screening method, including about 400 metabolites in central metabolic pathways. The method operates on a Q-Exactive Plus Orbitrap in DDA full-scan acquisition based on an inclusion list and has been shown to be highly repeatable and sensitive. Moreover, false-positive annotations could be severely reduced, enabling a simplified and slim data analysis approach. Using the supplied database and the code for data filtering, a rapid metabolite screening can be conducted, suitable for the application as a rapid metabolic profiling strategy in biological and medical research.

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Publication Details

Journal
Journal of the American Society for Mass Spectrometry
Published
2026-09-08
DOI
https://doi.org/10.1021/jasms.6c00203
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
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article

Bridging Speed and Confidence in Metabolomics: A Retention Time and MS2-Guided HILIC-Orbitrap Workflow

Jonas Rösler, Oliver J. Schmitz, Alpaslan Tasdogan, Feyza Cansiz et al.
Journal of the American Society for Mass Spectrometry
Metabolomics and Mass Spectrometry Studies
article

Bridging Speed and Confidence in Metabolomics: A Retention Time and MS2-Guided HILIC-Orbitrap Workflow

Jonas Rösler, Oliver J. Schmitz, Alpaslan Tasdogan, Feyza Cansiz, Sven W. Meckelmann, Jaqueline Leddin, Constantin P. Krempe, Friederike Jahr, Jost Guinand
article en

Abstract

Abstract Personalized treatment strategies are rising within modern medicine approaches to dynamic and heterogeneous diseases such as cancer. Human metabolism is important for the understanding of these diseases and their mechanisms, but metabolomics remains often unused in multiomics approaches due to practical challenges in sample analysis and, more importantly, data analysis. Automated feature analysis with many false-positive annotations and a rather long analysis time is effectively hindering rapid metabolite screening, as it would be needed in medical research. Here, we report a novel and efficient workflow for rapid metabolite screening with the capability of yielding high-quality metabolomics data, including data analysis. Therefore, a HILIC (superficially porous sulfobetaine) method has been optimized to separate polar metabolites in complex samples in less than 9 min, and an open-source compatible retention time database has been implemented for this rapid screening method, including about 400 metabolites in central metabolic pathways. The method operates on a Q-Exactive Plus Orbitrap in DDA full-scan acquisition based on an inclusion list and has been shown to be highly repeatable and sensitive. Moreover, false-positive annotations could be severely reduced, enabling a simplified and slim data analysis approach. Using the supplied database and the code for data filtering, a rapid metabolite screening can be conducted, suitable for the application as a rapid metabolic profiling strategy in biological and medical research.

Journal of the American Society for Mass Spectrometry
German Cancer Research Center (DE), University of Duisburg-Essen (DE)
Openalex Percentile: Top 18%
Metabolomics and Mass Spectrometry Studies
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