'Information-Based-Acquisition' (IBA) technique with an ion-trap/time-of-flight mass spectrometer for high-throughput and reliable protein profiling

Abstract

Highly complex protein mixtures can be analyzed after proteolysis using liquid chromatography/mass spectrometry (LC/MS). In an LC/MS run, intense peptide ions originating from high-abundance proteins are preferentially analyzed using tandem mass spectrometry (MS(2)), so obtaining the MS(2) spectra of peptide ions from low-abundance proteins is difficult even if such ions are detected. Furthermore, the MS(2) spectra may produce insufficient information to identify the peptides or proteins. To solve these problems, we have developed a real-time optimization technique for MS(2), called the Information-Based-Acquisition (IBA) system. In a preliminary LC/MS run, a few of the most intense ions detected in every MS spectrum are selected as precursors for MS(2) and their masses, charge states and retention times are automatically registered in an internal database. In the next run, a sample similar to that used in the first run is analyzed using database searching. Then, the ions registered in the database are excluded from the precursor ion selection to avoid duplicate MS(2) analyses. Furthermore, real-time de novo sequencing is performed just after obtaining the MS(2) spectrum, and an MS(3) spectrum is obtained for accurate peptide identification when the number of interpreted amino acids in the MS(2) spectrum is less than five. We applied the IBA system to a yeast cell lysate which is a typical crude sample, using a nanoLC/ion-trap time-of flight (IT/TOF) mass spectrometer, repeating the same LC/MS run five times. The obtained MS(2) and MS(3) spectra were analyzed by applying the Mascot (Matrix Science, Boston, MA, USA) search engine to identify proteins from the sequence database. The total number of identified proteins in five LC/MS runs was three times higher than that in the first run and the ion scores for peptide identification also significantly increased, by about 70%, when the MS(3) spectra were used, combined with the MS(2) spectra, before being subjected to Mascot analysis.