ArticleAnalytical chemistry2013
An untargeted metabolomic workflow to improve structural characterization of metabolites.
Article in Analytical chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- ENVnet provides a global molecular resource of dissolved organic matter.Nature biotechnology · 2026Article
- Enhancing Chimeric Fragmentation Spectra Deconvolution Using Direct Infusion-Tandem Mass Spectrometry Across High-Resolution Mass Spectrometric Platforms.Rapid communications in mass spectrometry : RCM · 2026Article
- TidyMass2: advancing LC-MS untargeted metabolomics through metabolite origin inference and metabolic feature-based functional module analysis.Nature communications · 2026Article
- Detecting and Grouping In-Source Fragments with Low-Energy Stepped HCD, Together with MSMetabolites · 2026Article
- Development of an untargeted metabolomics analytical protocol for fecal samples by liquid chromatography-mass spectrometry.Journal of food and drug analysis · 2025Article
- Highly reliable LC-MS lipidomics database for efficient human plasma profiling based on NIST SRM 1950.Journal of lipid research · 2024Article
- Plant Metabolomics: The Future of Anticancer Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2024Review
- High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage.Environmental science & technology · 2024Review
- Revealing novel biomarkers for diagnosing chronic kidney disease in pediatric patients.Scientific reports · 2024Article
- Automated Composition Assessment of Natural Extracts: Untargeted Mass Spectrometry-Based Metabolite Profiling Integrating Semiquantitative Detection.Journal of agricultural and food chemistry · 2023Article
- BUDDY: molecular formula discovery via bottom-up MS/MS interrogation.Nature methods · 2023Article
- Simultaneous Quantitation and Discovery (SQUAD) Analysis: Combining the Best of Targeted and Untargeted Mass Spectrometry-Based Metabolomics.Metabolites · 2023Review
- Resolving isobaric interferences in direct infusion tandem mass spectrometry.Rapid communications in mass spectrometry : RCM · 2022Article
- Metabolomics Tools Assisting Classic Screening Methods in Discovering New Antibiotics from Mangrove Actinomycetia in Leizhou Peninsula.Marine drugs · 2021Article
- DecoID improves identification rates in metabolomics through database-assisted MS/MS deconvolution.Nature methods · 2021Article
- Targeting unique biological signals on the fly to improve MS/MS coverage and identification efficiency in metabolomics.Analytica chimica acta · 2021Article
- The potential pathways underlying the association of propyl-paraben exposure with aeroallergen sensitization and EASI score using metabolomics analysis.Scientific reports · 2021Article
- Creating a Reliable Mass Spectral-Retention Time Library for All Ion Fragmentation-Based Metabolomics.Metabolites · 2019Article
- Article
- The metaRbolomics Toolbox in Bioconductor and beyond.Metabolites · 2019Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Mass spectrometry-based metabolomics relies on MS(2) data for structural characterization of metabolites. To obtain the high-quality MS(2) data necessary to support metabolite identifications, ions of interest must be purely isolated for fragmentation. Here, we show that metabolomic MS(2) data are frequently characterized by contaminating ions that prevent structural identification. Although using narrow-isolation windows can minimize contaminating MS(2) fragments, even narrow windows are not always selective enough, and they can complicate data analysis by removing isotopic patterns from MS(2) spectra. Moreover, narrow windows can significantly reduce sensitivity. In this work, we introduce a novel, two-part approach for performing metabolomic identifications that addresses these issues. First, we collect MS(2) scans with less stringent isolation settings to obtain improved sensitivity at the expense of specificity. Then, by evaluating MS(2) fragment intensities as a function of retention time and precursor mass targeted for MS(2) analysis, we obtain deconvolved MS(2) spectra that are consistent with pure standards and can therefore be used for metabolite identification. The value of our approach is highlighted with metabolic extracts from brain, liver, astrocytes, as well as nerve tissue, and performance is evaluated by using pure metabolite standards in combination with simulations based on raw MS(2) data from the METLIN metabolite database. A R package implementing the algorithms used in our workflow is available on our laboratory website ( http://pattilab.wustl.edu/decoms2.php ).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.