Lipid profiling by multiple precursor and neutral loss scanning driven by the data-dependent acquisition.

Data-dependent acquisition of MS/MS spectra from lipid precursors enables to emulate the simultaneous acquisition of an unlimited number of precursor and neutral loss scans in a single analysis. This approach takes full advantage of rich fragment patterns in tandem mass spectra of lipids and enables their profiling by complex (Boolean) scans, in which masses of several fragment ions are considered within a single logical framework. No separation of lipids is required, and the accuracy of identification and quantification is not compromised, compared to conventional precursor and neutral loss scanning.

The power and the limitations of cross-species protein identification by mass spectrometry-driven sequence similarity searches.

Mass spectrometry-driven BLAST (MS BLAST) is a database search protocol for identifying unknown proteins by sequence similarity to homologous proteins available in a database. MS BLAST utilizes redundant, degenerate, and partially inaccurate peptide sequence data obtained by de novo interpretation of tandem mass spectra and has become a powerful tool in functional proteomic research. Using computational modeling, we evaluated the potential of MS BLAST for proteome-wide identification of unknown proteins. We determined how the success rate of protein identification depends on the full-length sequence identity between the queried protein and its closest homologue in a database. We also estimated phylogenetic distances between organisms under study and related reference organisms with completely sequenced genomes that allow substantial coverage of unknown proteomes.