Evidence map›Paper›PMID 36627043›Full record

ArticleAnalytical biochemistry2023

Systematic analysis of in-source modifications of primary metabolites during flow-injection time-of-flight mass spectrometry.

Niklas Farke, Thorben Schramm, Andreas Verhülsdonk, Johanna Rapp, Hannes Link

Abstract read
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Article in Analytical biochemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Niklas FarkeBacterial Metabolomics, CMFI, University Tübingen, Auf der Morgenstelle 24, 7206, Tübingen, Germany.
Thorben SchrammBacterial Metabolomics, CMFI, University Tübingen, Auf der Morgenstelle 24, 7206, Tübingen, Germany.
Andreas VerhülsdonkBacterial Metabolomics, CMFI, University Tübingen, Auf der Morgenstelle 24, 7206, Tübingen, Germany.
Johanna RappBacterial Metabolomics, CMFI, University Tübingen, Auf der Morgenstelle 24, 7206, Tübingen, Germany.
Hannes LinkBacterial Metabolomics, CMFI, University Tübingen, Auf der Morgenstelle 24, 7206, Tübingen, Germany. Electronic address: hannes.link@uni-tuebingen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flow-injection mass spectrometry (FI-MS) enables metabolomics studies with a very high sample-throughput. However, FI-MS is prone to in-source modifications of analytes because samples are directly injected into the electrospray ionization source of a mass spectrometer without prior chromatographic separation. Here, we spiked authentic standards of 160 primary metabolites individually into an Escherichia coli metabolite extract and measured the thus derived 160 spike-in samples by FI-MS. Our results demonstrate that FI-MS can capture a wide range of chemically diverse analytes within 30 s measurement time. However, the data also revealed extensive in-source modifications. Across all 160 spike-in samples, we identified significant increases of 11,013 ion peaks in positive and negative mode combined. To explain these unknown m/z features, we connected them to the m/z feature of the (de-)protonated metabolite using information about mass differences and MS2 spectra. This resulted in networks that explained on average 49 % of all significant features. The networks showed that a single metabolite undergoes compound specific and often sequential in-source modifications like adductions, chemical reactions, and fragmentations. Our results show that FI-MS generates complex MS1 spectra, which leads to an overestimation of significant features, but neutral losses and MS2 spectra explain many of these features.

Indexed as

MetabolomicsSpectrometry, Mass, Electrospray IonizationMass SpectrometryElectrospray ionizationFeature networkFlow-injection mass spectrometryIn-source modificationsMetabolomics

Identifiers

PMID36627043
PMCPMC9902335

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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.