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MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis.

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Area of Science:

  • Analytical Chemistry
  • Metabolomics
  • Bioinformatics

Background:

  • Data-independent acquisition (DIA) offers comprehensive untargeted molecular data acquisition in liquid chromatography-tandem mass spectrometry (LC-MS/MS).
  • Accurate identification and quantification of small molecules are crucial for various biological and chemical analyses.

Purpose of the Study:

  • To introduce MS-DIAL, an open-source software pipeline for small molecule identification and quantification using DIA-based mass spectral deconvolution.
  • To demonstrate the utility of MS-DIAL in analyzing complex biological samples, specifically algal strains.

Main Methods:

  • Development and application of the MS-DIAL software pipeline.
  • Utilizing data-independent acquisition (DIA) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS).
  • Employing mass spectral deconvolution for small molecule analysis with an enriched LipidBlast library.

Main Results:

  • MS-DIAL successfully identified 1,023 lipid compounds from reversed-phase LC-MS/MS analysis of nine algal strains.
  • The identified lipid profiles highlighted significant chemotaxonomic relationships among the analyzed algal strains.
  • The software pipeline proved effective for untargeted small molecule analysis.

Conclusions:

  • MS-DIAL is a powerful open-source tool for DIA-based small molecule identification and quantification.
  • The software facilitates the exploration of molecular data, aiding in the understanding of biological systems and relationships.
  • This approach enhances the analysis of complex lipidomics data in microbial studies.