Evidence map›Paper›PMID 41081765›Full record

ArticleCurrent protocols2025

Design and Analysis of Untargeted Metabolomics Experiments.

Zane G Long, Rachel W Martin

Abstract read
In one paragraph

Article in Current protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Zane G LongDepartment of Chemistry, University of California, Irvine, California.ORCID https://orcid.org/0000-0002-3795-5551
Rachel W MartinDepartment of Chemistry, University of California, Irvine, California.ORCID https://orcid.org/0000-0001-9996-7411

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Untargeted metabolomics is a powerful approach for identifying small molecules from highly complex mixtures, such as biological tissues or environmental samples. This technology enables the relatively fast and inexpensive identification of metabolites in situations where many or most of the chemical species are unknown before the experiment begins. This situation often arises in biomedical and environmental research, as well as in the case described here, the discovery of metabolites from plants. The objective of this paper is to provide practical and technical knowledge about untargeted metabolomics using mass spectrometry as the detection method. Specifically, we focus on liquid chromatography tandem mass spectrometry (LC-MS/MS). We provide a consolidated protocol for new users, serving as a starting point for experimental design, data collection, and data analysis. We explain the terminology and technical details in the context of real experiments and samples. In addition to general background information, step-by-step protocols are provided for sample preparation, liquid chromatography-tandem mass spectrometry data collection, and data analysis, utilizing readily available and widely used software. The chosen example data set is based on plant metabolites with varying chemical properties; however, the approach is applicable to essentially any complex biological sample. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sample preparation for LC-MS/MS Support Protocol 1: Preparing a 'master mix' sample for assessment of liquid chromatography and sensitivity Basic Protocol 2: LC-MS/MS data collection Basic Protocol 3: Data analysis using the software MSConvert, MZMine, and SIRIUS Support Protocol 2: Using the MZMine batch file.

Indexed as

MetabolomicsResearch DesignTandem Mass SpectrometryChromatography, LiquidPlantsSoftwareelectrospray ionizationLC‐MS/MSmass spectrometryplant metabolitesuntargeted metabolomics

Identifiers

PMID41081765
PMCPMC12517316

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.