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Related Concept Videos

Tandem Mass Spectrometry01:21

Tandem Mass Spectrometry

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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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Updated: Jun 24, 2025

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Tidy-Direct-to-MS: An Open-Source Data-Processing Pipeline for Direct Mass Spectrometry-Based Metabolomics

Christoph Bueschl1, Gabriel Riquelme1, Nicolás Zabalegui1

  • 1Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD Ciudad de Buenos Aires, Argentina.

Journal of Proteome Research
|June 4, 2024
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Summary
This summary is machine-generated.

A new open-source tool, Tidy-Direct-to-MS, simplifies biochemical fingerprinting using direct-to-mass spectrometry. This Python-based software enhances data processing for untargeted metabolomics studies, improving feature detection and analysis.

Keywords:
DARTTidyMSdata processingmass spectrometrymetabolomicsquality control

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Area of Science:

  • Analytical Chemistry
  • Biochemistry
  • Computational Biology

Background:

  • Direct-to-Mass Spectrometry (MS) and ambient ionization techniques offer rapid biochemical fingerprinting.
  • Current data processing relies heavily on vendor-specific software, limiting flexibility and accessibility.
  • Untargeted metabolomics studies require robust and user-friendly data analysis tools.

Purpose of the Study:

  • To develop and introduce Tidy-Direct-to-MS, a novel open-source software for processing direct-to-MS data.
  • To provide a user-friendly platform for biochemical fingerprinting and metabolomics data analysis.
  • To enhance the efficiency and accuracy of data processing in ambient MS-based studies.

Main Methods:

  • Development of Tidy-Direct-to-MS as a Python-based library (part of TidyMS).
  • Implementation of modules for sample position detection, m/z drift correction, consensus spectra calculation, and feature abundance determination.
  • Automated parameter optimization for maximizing feature detection and validating reference features.

Main Results:

  • Tidy-Direct-to-MS enables fast and user-friendly processing of direct-to-MS datasets.
  • The tool facilitates automated comparison of parameters to optimize feature detection.
  • Demonstrated utility in a marine metabolomics study using transmission mode Direct Analysis in Real Time-Mass Spectrometry (TM-DART-MS).

Conclusions:

  • Tidy-Direct-to-MS simplifies and enhances the workflow for untargeted ambient MS-based metabolomics.
  • The open-source nature of the tool allows for easy extension and integration.
  • This functionality aids in data quality review and subsequent analysis, improving research reproducibility.