Evidence map›Paper›PMID 40270433›Full record

ArticleAngewandte Chemie (International ed. in English)2025

LC-MS and High-Throughput Data Processing Solutions for Lipid Metabolic Tracing Using Bioorthogonal Click Chemistry.

Palina Nepachalovich, Stefano Bonciarelli, Gabriele Lombardi Bendoula, Jenny Desantis, Michela Eleuteri, Christoph Thiele, Laura Goracci, Maria Fedorova

Abstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

8 authors.

Palina NepachalovichCenter of Membrane Biochemistry and Lipid Research, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Tatzberg 47-49, Dresden, 01307, Germany.
Stefano BonciarelliMass Analytica, Av Cerdanyola 92-94, Sant Cugat del Vallés, 08173, Spain.
Gabriele Lombardi BendoulaCenter of Membrane Biochemistry and Lipid Research, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Tatzberg 47-49, Dresden, 01307, Germany.
Jenny DesantisDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, Perugia, 06123, Italy.
Michela EleuteriDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, Perugia, 06123, Italy.
Christoph ThieleLife & Medical Sciences Institute, University of Bonn, Carl-Troll-Straße 31, Bonn, 53115, Germany.
Laura GoracciDepartment of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, Perugia, 06123, Italy.
Maria FedorovaCenter of Membrane Biochemistry and Lipid Research, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Tatzberg 47-49, Dresden, 01307, Germany.

Funding

Bundesministerium für Bildung und Forschung 01EJ2205ABundesministerium für Bildung und Forschung 031L0315ADeutsche Forschungsgemeinschaft FE 1236/5-1Deutsche Forschungsgemeinschaft FE 1236/8-1European Cooperation in Science and TechnologySächsische AufbaubankSMWK
6 · The paper itself

Abstract

Tracing lipid metabolism in mammalian cells presents a significant technological challenge due to the vast structural diversity of lipids involved in multiple metabolic routes. Bioorthogonal approaches based on click chemistry have revolutionized analytical performance in lipid tracing. When adapted for mass spectrometry (MS), they enable highly specific and sensitive analyses of lipid transformations at the lipidome scale. Here, we advance this approach by integrating liquid chromatography (LC) prior to MS detection and developing a software-assisted workflow for high-throughput data processing. LC separation resolved labeled and unmodified lipids, enabling qualitative and quantitative analysis of both lipidome fractions, as well as isomeric lipid species. Using synthetic standards and endogenously produced alkyne lipids, we characterized LC-MS behavior, including preferential adduct formation and the extent of in-source fragmentation. Specific fragmentation rules, derived from tandem MS experiments for 23 lipid subclasses, were implemented in Lipostar2 software for high-throughput annotation and quantification of labeled lipids. Applying this platform, we traced metabolic pathways of palmitic and oleic acid alkynes, revealing distinct lipid incorporation patterns and metabolic bottlenecks. Altogether, here we provide an integrated analytical and bioinformatics platform for high-throughput tracing of lipid metabolism using LC-MS workflow.

Indexed as

Click ChemistryLipid MetabolismLipidsAlkynesChromatography, LiquidHigh-Throughput Screening AssaysHumansLiquid Chromatography-Mass SpectrometryMass SpectrometryTandem Mass SpectrometryAlkynesLipidsClick chemistryLC‐MSLipostar2SphingolipidsTracing lipid metabolism

Identifiers

PMID40270433
PMCPMC12207371

What OpenQuestion holds

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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.