ArticleAnalytical and bioanalytical chemistry2023
Augmented region of interest for untargeted metabolomics mass spectrometry (AriumMS) of multi-platform-based CE-MS and LC-MS data.
Article in Analytical and bioanalytical chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Multi-omics insights into bacterial and fungal bioremediation of Potentially Toxic Elements (PTEs): a critical overview of their applications.World journal of microbiology & biotechnology · 2026Review
- Dimensionality reduction and metabolite panel derivation in urinary metabolomics based on Random Forest with Gini index feature selection.Analytical and bioanalytical chemistry · 2026Article
- Automated Near Real-Time QC for LC-HRMS.Rapid communications in mass spectrometry : RCM · 2026Article
- Flow Rate Determination of the Nanoflow Sheath Liquid CE-MS-Coupling Applying the nanoCEasy Interface.Electrophoresis · 2025Article
- Stable overexpression of native and artificial miRNAs for the production of differentially fucosylated antibodies in CHO cells.Engineering in life sciences · 2024Article
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
In mass spectrometry (MS)-based metabolomics, there is a great need to combine different analytical separation techniques to cover metabolites of different polarities and apply appropriate multi-platform data processing. Here, we introduce AriumMS (augmented region of interest for untargeted metabolomics mass spectrometry) as a reliable toolbox for multi-platform metabolomics. AriumMS offers augmented data analysis of several separation techniques utilizing a region-of-interest algorithm. To demonstrate the capabilities of AriumMS, five datasets were combined. This includes three newly developed capillary electrophoresis (CE)-Orbitrap MS methods using the recently introduced nanoCEasy CE-MS interface and two hydrophilic interaction liquid chromatography (HILIC)-Orbitrap MS methods. AriumMS provides a novel mid-level data fusion approach for multi-platform data analysis to simplify and speed up multi-platform data processing and evaluation. The key feature of AriumMS lies in the optimized data processing strategy, including parallel processing of datasets and flexible parameterization for processing of individual separation methods with different peak characteristics. As a case study, Saccharomyces cerevisiae (yeast) was treated with a growth inhibitor, and AriumMS successfully differentiated the metabolome based on the augmented multi-platform CE-MS and HILIC-MS investigation. As a result, AriumMS is proposed as a powerful tool to improve the accuracy and selectivity of metabolome analysis through the integration of several HILIC-MS/CE-MS techniques.
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