The Column
Protein/peptide discovery data obtained from data-dependent experiments have been used to increase the success rate of targeted quantification assays as well as automate method building.
Protein/peptide discovery data obtained from data-dependent experiments have been used to increase the success rate of targeted quantification assays as well as automate method building. The incorporation of a quality control (QC) peptide set for discovery experiments aids the determination of relative retention times, which are stored in spectral library entries with precursor and product ion information. The inclusion of both liquid chromatography (LC) and mass spectrometry (MS) data in spectral library entries enables software programs to accurately build targeted peptide acquisition methods for large lists of peptides. The efficiency of determining the relative retention times for a set of synthetic peptides was evaluated across a number of LC–MS methods.
Obtaining Allicin from Garlic with High-Speed Counter Current Chromatography
February 14th 2025High-speed counter current chromatography (HSCCC), an advanced liquid-liquid chromatography technique employing both a liquid stationary phase and a liquid mobile phase (effectively eliminating irreversible adsorption), was used to harvest allicin from garlic.
The Next Frontier for Mass Spectrometry: Maximizing Ion Utilization
January 20th 2025In this podcast, Daniel DeBord, CTO of MOBILion Systems, describes a new high resolution mass spectrometry approach that promises to increase speed and sensitivity in omics applications. MOBILion recently introduced the PAMAF mode of operation, which stands for parallel accumulation with mobility aligned fragmentation. It substantially increases the fraction of ions used for mass spectrometry analysis by replacing the functionality of the quadrupole with high resolution ion mobility. Listen to learn more about this exciting new development.
Identifying Microplastics in Tap Water with Py-GC/MS
February 12th 2025A pyrolysis gas chromatography-mass spectrometry (Py-GC/MS) methodology has been specifically developed for the identification and quantification of seven polymers commonly found in tap water. The researchers responsible for the approach state that it prioritizes both time and cost efficiency without compromising the thoroughness of marker spectrum detection and confirmation.