Abstract

Mass spectrometry combined with a range of on-line separation techniques has become a powerful tool for characterization of complex mixtures, including protein digests in proteomics studies. Accurate mass measurements can be compromised due to variations that occur in the course of an on-line separation, e.g., due to excessive space charge in an ion trap, temperature changes, or other sources of instrument "drift". We have developed a multidimensional recalibration approach that utilizes existing information on the likely mixture composition, taking into account variable conditions of mass measurements, and that corrects the mass calibration for sets of individual peaks binned by, for example, the total ion count for the mass spectrum, the individual peak abundance, m/z value, and liquid chromatography separation time. The multidimensional recalibration approach uses a statistical matching of measured masses in such measurements, often exceeding 105, to a significant number of putative known species likely to be present in the mixture (i.e., having known accurate masses), to identify a subset of the detected species that serve as effective calibrants. The recalibration procedure involves optimization of the mass accuracy distribution (histogram), to provide a more confident distinction between true and false identifications. We report the mass accuracy improvement obtained for data acquired using a TOF and several FTICR mass spectrometers. We show that the multidimensional recalibration better compensates for systematic mass measurement errors and also significantly reduces the mass error spread: i.e., both the accuracy and precision of mass measurements are improved. The mass measurement improvement is found to be virtually independent of the initial instrument calibration, allowing, for example, less frequent calibration. We show that this recalibration can provide sub-ppm mass measurement accuracy for measurements of a complex fungal proteome tryptic digest and provide improved confidence or numbers of peptide identifications.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call