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Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and signal-to-noise ratio for the analyte. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.
Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called collision-induced...
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Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics.

Katyeny Manuela da Silva1, Maria van de Lavoir1, Rani Robeyns1

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Summary

This study presents a workflow for creating a metabolite library using liquid chromatography ion mobility high-resolution mass spectrometry. The open-access library aids in accurate metabolite identification, improving untargeted metabolomics analysis.

Keywords:
Collision cross sectionIon mobilityOpen-sourceRMassBankRetention timeTandem mass spectrometry

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Area of Science:

  • Analytical Chemistry
  • Metabolomics
  • Computational Chemistry

Background:

  • Metabolite identification in untargeted metabolomics is challenging due to limited database information.
  • Retention Time (RT) and Collision Cross Section (CCS) data improve metabolite annotation confidence.
  • Machine learning advances necessitate high-quality experimental data for accurate CCS and RT predictions.

Purpose of the Study:

  • To develop an accessible workflow for generating in-house metabolite libraries.
  • To provide an open-access metabolite library with multidimensional data.
  • To evaluate CCS prediction tools and MS/MS spectral variations.

Main Methods:

  • Analysis of 100 metabolite standards using liquid chromatography ion mobility high-resolution mass spectrometry.
  • Development of a standardized workflow for library creation.
  • Generation of an open-access NIST-format metabolite library (.msp).

Main Results:

  • Creation of an open-access, multidimensional metabolite library in NIST format.
  • Evaluation of CCS prediction tools using the generated library.
  • Assessment of MS/MS spectral heterogeneities and RT reporting.

Conclusions:

  • The developed workflow facilitates the creation of valuable metabolite libraries.
  • The open-access library serves as a crucial resource for metabolomics research.
  • This work enhances metabolite annotation accuracy and aids in evaluating prediction tools.