en
Doctoral thesis
English

Accurate mass spectral libraries and predicted liquid chromatography retention times in bioanalysis and data independent metabolomics

ContributorsBruderer, Tobias
Defense date2016-02-12
Abstract

Analytical workflows and tools were developed to identify low molecular weight compounds in complex samples by liquid chromatography mass spectrometry in metabolomics and bioanalysis. An in-silico strategy allowed the comprehensive screening for comedication interferences in quantitative bioanalysis with LC-MS in selection reaction monitoring (SRM) mode. For non-targeted metabolomics, data independent (SWATH) analysis has emerged as a powerful tool for comprehensive qualitative and quantitative data acquisition. An accurate mass spectral library was created for SWATH metabolomics analysis with emphasis on quality control. The use of composite fragment spectra over a large range of collision energies allowed to minimize experimental setting bias and to ensure high identification score. Predicted retention windows were applied if a good fragment match was not sufficient for metabolite identification. Multiplexed fragment spectra from coeluting precursor ions can be an issue in SWATH analysis. We evaluated the use of variable Q1 windows and observed an improvement in selectivity.

eng
Keywords
  • Metabolomics
  • Metabolites
  • High Resolution Mass Spectrometry
  • SWATH
  • Mass Spectral Library
  • Library
  • Database
  • Data Independent Analysis
  • SWATH
  • SwathTUNER
  • Proteomics
  • Liquid Chromatography
  • Retention Time Prediction
  • Predicted Retention Time Windows
  • Bioanalysis
  • Comedications
  • Screening Strategy
  • Biofluids
  • Urine
  • Plasma
Citation (ISO format)
BRUDERER, Tobias. Accurate mass spectral libraries and predicted liquid chromatography retention times in bioanalysis and data independent metabolomics. 2016. doi: 10.13097/archive-ouverte/unige:80935
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Creation2016/02/12 10:51:00
First validation2016/02/12 10:51:00
Update time2023/03/15 00:09:27
Status update2023/03/15 00:09:27
Last indexation2024/01/29 20:41:47
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