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Small Molecule LC-MS/MS Fragmentation Data Analysis and Application to Siderophore Identification

In: Applications from Engineering with MATLAB Concepts

Author

Listed:
  • Oliver Baars
  • David H. Perlman

Abstract

Rapid developments in tandem liquid chromatography-mass spectrometry (LC-MS/MS) have created wide interest in applications for the analysis of small molecule mixtures. MS/MS spectra can contain rich structural information, but because of the structural diversity of small molecules and different data acquisition methods, analysis algorithms and workflows frequently need to be tailored to individual research questions. This chapter shows how MATLAB can be used for LC-MS/MS-based structural characterization of small molecules. Starting with the import of raw data, ways for visualization and the creation of graphical user interfaces (GUIs) for individual applications are demonstrated. A selection of frequently used algorithms for pre-processing and data analysis is reviewed in context of their MATLAB implementation. The approaches are then tailored and applied to the analysis of iron-binding peptides (peptidic siderophores) by high-resolution LC-MS/MS. The method uses a database with siderophore structures to exploit prior knowledge about siderophore structural diversity for the interpretation of MS/MS spectra from known and new siderophores.

Suggested Citation

  • Oliver Baars & David H. Perlman, 2016. "Small Molecule LC-MS/MS Fragmentation Data Analysis and Application to Siderophore Identification," Chapters, in: Jan Valdman (ed.), Applications from Engineering with MATLAB Concepts, IntechOpen.
    • Handle: RePEc:ito:pchaps:101175
    DOI: 10.5772/63018
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    File URL: https://www.intechopen.com/chapters/50607
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    More about this item

    Keywords

    small molecules; metabolomics; fragmentation spectra; LC-MS/MS; liquid chromatography tandem mass spectrometry; neutral-loss; fragment-ion; auto-convolution spectra; molecular networks; secondary metabolites; siderophores; iron; nonribosomal peptides; MATLAB;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General

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