PNNL

Abstract

Hybrid FTMS instruments, such as the LTQ-FTTM and LTQ-OrbitrapTM, are capable of generating fast duty cycle linear ion trap MS/MS data along with high resolution information without compromising the overall throughput of measurements. Combined with online LC separations, these instruments represent powerful and flexible tools for proteomics research. In the present work, we explore strategies for high throughput, high coverage proteomics measurements using hybrid FTMS instruments. Our accurate mass and time tag (AMT tag) strategy enables identification of thousands of peptides in a single LC-FTMS analysis by comparing accurate molecular mass and LC elution time information from the analysis to a reference database. An alternative strategy considered here employs linear ion trap (low resolution) MS/MS identifications generated by an appropriate search engine, such as SEQUEST; the high resolution precursor ion spectra were used to refine the MS/MS identifications, an approach termed Accurate Precursor Mass Filter (APMF). The APMF results can be additionally filtered using the LC elution time information from the AMT tag database, which constitutes a Precursor Mass and Time Filter (PMTF), the third approach implemented in this study. Both the APMF and the PMTF approaches are evaluated for coverage and confidence of peptide identifications and contrasted with the current AMT tag strategy. Two separate methodologies were used to reliably quantify identification confidence: a commonly used decoy database method and an alternative method based on the mass accuracy histogram. The two methodologies produced consistent results, confirming the validity of the identification confidence evaluations. Comparison of the three approaches has shown that the AMT tag data analysis approach may be preferential for studies giving a priority to the highest achievable coverage. The APMF approach by itself does not require AMT tag database and provides a moderate coverage combined with acceptable confidence values of ~99%.The PMTF approach yielded a significantly better peptide identification confidence, >99.9%, that essentially excluded any false peptide identifications. The results suggest that even with a perfect peptide ID (0% FDR in the peptide MS/MS database), the peak matching FDR is a function of the database size, so smaller high confidence databases are the goal. Thus a combined strategy can implement multi-pass APMF approach to generate high confidence AMT tag databases, which can be then validated using PMTF approach; the compact high quality databases will be used for subsequent high-throughput, high coverage AMT tag studies.