Metabolomics goes one step beyond the knowledge acquired from genomics, transcriptomics and proteomics research by showing a snapshot of all biochemical reactions in a cell. Research areas such as personalized healthcare, drug discovery and plant breeding are increasingly turning to metabolomics data for novel insights.
Liquid chromatography combined with mass spectrometry (LC-MS) is frequently used to analyze thousands of metabolites per sample with high accuracy, however, challenges arise in data interpretation. Metabolite modifications, fragmentations, and background from primary samples increase data complexity, which makes it difficult to compare results obtained in different labs or on different instruments.
To address this complexity, libraries used for accurate metabolite identification should include as many characterization dimensions as possible, as well as explicit information about the methods used for data acquisition. Li and colleagues at the University of Alberta, Canada enhanced their mass spectrometry library of 800 compounds selected from the Human Metabolome Database (HMDB) with reversed-phase retention-time (RT) data.
For this, they spiked reference metabolites into both standard buffers and urine samples and then determined retention time and m/z values following a precisely defined LC-MS protocol. They also calculated correction factors for 26 compounds based on retention time shifts observed between standards and samples, and among different LC-MS instruments.
Results from their work point at several benefits from augmenting the library with retention time data.
Read more about how this retention time library was created and used.
Find out more about Bruker’s Ultra-High Resolution QTOF Mass Spectrometers