DtaRefinery, a software tool for elimination of systematic errors from parent ion mass measurements in tandem mass spectra data sets.

Hybrid two-stage mass spectrometers capable of both highly accurate mass measurement and high throughput MS/MS fragmentation have become widely available in recent years, allowing for significantly better discrimination between true and false MS/MS peptide identifications by the application of a relatively narrow window for maximum allowable deviations of measured parent ion masses. To fully gain the advantage of highly accurate parent ion mass measurements, it is important to limit systematic mass measurement errors. Based on our previous studies of systematic biases in mass measurement errors, here, we have designed an algorithm and software tool that eliminates the systematic errors from the peptide ion masses in MS/MS data. We demonstrate that the elimination of the systematic mass measurement errors allows for the use of tighter criteria on the deviation of measured mass from theoretical monoisotopic peptide mass, resulting in a reduction of both false discovery and false negative rates of peptide identification. A software implementation of this algorithm called DtaRefinery reads a set of fragmentation spectra, searches for MS/MS peptide identifications using a FASTA file containing expected protein sequences, fits a regression model that can estimate systematic errors, and then corrects the parent ion mass entries by removing the estimated systematic error components. The output is a new file with fragmentation spectra with updated parent ion masses. The software is freely available.

Machine learning based prediction for peptide drift times in ion mobility spectrometry.

MOTIVATION: Ion mobility spectrometry (IMS) has gained significant traction over the past few years for rapid, high-resolution separations of analytes based upon gas-phase ion structure, with significant potential impacts in the field of proteomic analysis. IMS coupled with mass spectrometry (MS) affords multiple improvements over traditional proteomics techniques, such as in the elucidation of secondary structure information, identification of post-translational modifications, as well as higher identification rates with reduced experiment times. The high throughput nature of this technique benefits from accurate calculation of cross sections, mobilities and associated drift times of peptides, thereby enhancing downstream data analysis. Here, we present a model that uses physicochemical properties of peptides to accurately predict a peptide's drift time directly from its amino acid sequence. This model is used in conjunction with two mathematical techniques, a partial least squares regression and a support vector regression setting. RESULTS: When tested on an experimentally created high confidence database of 8675 peptide sequences with measured drift times, both techniques statistically significantly outperform the intrinsic size parameters-based calculations, the currently held practice in the field, on all charge states (+2, +3 and +4). AVAILABILITY: The software executable, imPredict, is available for download from http:/omics.pnl.gov/software/imPredict.php CONTACT: rds@pnl.gov SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Improving confidence in detection and characterization of protein N-glycosylation sites and microheterogeneity.

Protein glycosylation is one of the most common post-translational modifications, estimated to occur in over 50% of human proteins. Mass spectrometry (MS)-based approaches involving different fragmentation mechanisms have been frequently used to detect and characterize protein N-linked glycosylations. In addition to the popular Collision-Induced Dissociation (CID), high-energy C-trap dissociation (HCD) fragmentation, which is a feature of a linear ion trap orbitrap hybrid mass spectrometer (LTQ Orbitrap), has been recently used for the fragmentation of tryptic N-linked glycopeptides in glycoprotein analysis. The oxonium ions observed with high mass accuracy in the HCD spectrum of glycopeptides can be combined with characteristic fragmentation patterns in the CID spectrum resulting from consecutive glycosidic bond cleavages, to improve the detection and characterization of N-linked glycopeptides. As a means of automating this process, we describe here GlypID 2.0, a software tool that implements several algorithmic approaches to utilize MS information including accurate precursor mass and spectral patterns from both HCD and CID spectra, thus allowing for an unequivocal and accurate characterization of N-linked glycosylation sites of proteins.

An LC-IMS-MS platform providing increased dynamic range for high-throughput proteomic studies.

A high-throughput approach and platform using 15 min reversed-phase capillary liquid chromatography (RPLC) separations in conjunction with ion mobility spectrometry-mass spectrometry (IMS-MS) measurements was evaluated for the rapid analysis of complex proteomics samples. To test the separation quality of the short LC gradient, a sample was prepared by spiking 20 reference peptides at varying concentrations from 1 ng/mL to 10 microg/mL into a tryptic digest of mouse blood plasma and analyzed with both a LC-Linear Ion Trap Fourier Transform (FT) MS and LC-IMS-TOF MS. The LC-FT MS detected 13 out of the 20 spiked peptides that had concentrations >or=100 ng/mL. In contrast, the drift time selected mass spectra from the LC-IMS-TOF MS analyses yielded identifications for 19 of the 20 peptides with all spiking levels present. The greater dynamic range of the LC-IMS-TOF MS system could be attributed to two factors. First, the LC-IMS-TOF MS system enabled drift time separation of the low concentration spiked peptides from the high concentration mouse peptide matrix components, reducing signal interference and background, and allowing species to be resolved that would otherwise be obscured by other components. Second, the automatic gain control (AGC) in the linear ion trap of the hybrid FT MS instrument limits the number of ions that are accumulated to reduce space charge effects and achieve high measurement accuracy, but in turn limits the achievable dynamic range compared to the IMS-TOF instrument.

DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectra.

UNLABELLED: DeconMSn accurately determines the monoisotopic mass and charge state of parent ions from high-resolution tandem mass spectrometry data, offering significant improvement for LTQ_FT and LTQ_Orbitrap instruments over the commercially delivered Thermo Fisher Scientific's extract_msn tool. Optimal parent ion mass tolerance values can be determined using accurate mass information, thus improving peptide identifications for high-mass measurement accuracy experiments. For low-resolution data from LCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-based charge detection algorithm that identifies the most likely charge of a parent species through peak characteristics of its fragmentation pattern. AVAILABILITY: http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/.

An efficient data format for mass spectrometry-based proteomics.

The diverse range of mass spectrometry (MS) instrumentation along with corresponding proprietary and nonproprietary data formats has generated a proteomics community driven call for a standardized format to facilitate management, processing, storing, visualization, and exchange of both experimental and processed data. To date, significant efforts have been extended towards standardizing XML-based formats for mass spectrometry data representation, despite the recognized inefficiencies associated with storing large numeric datasets in XML. The proteomics community has periodically entertained alternate strategies for data exchange, e.g., using a common application programming interface or a database-derived format. However, these efforts have yet to gain significant attention, mostly because they have not demonstrated significant performance benefits over existing standards, but also due to issues such as extensibility to multidimensional separation systems, robustness of operation, and incomplete or mismatched vocabulary. Here, we describe a format based on standard database principles that offers multiple benefits over existing formats in terms of storage size, ease of processing, data retrieval times, and extensibility to accommodate multidimensional separation systems.

Proteomic profiling of intact proteins using WAX-RPLC 2-D separations and FTICR mass spectrometry.

We investigated the combination of weak anion exchange (WAX) fractionation and on-line reversed-phase liquid chromatography (RPLC) separation using a 12 T FTICR mass spectrometer for the detection of intact proteins from a Shewanella oneidensis MR-1 cell lysate. This work aimed at optimizing intact protein detection for profiling proteins at a level that incorporates their modification state. A total of 715 intact proteins were detected, and the combined results from the WAX fractions and the unfractionated cell lysate were aligned using LC-MS features to facilitate protein abundance measurements. Protein identifications and post-translational modifications were assigned for approximately 10% of the detected proteins by comparing intact protein mass measurements to proteins identified in peptide MS/MS analysis of an aliquot of the same fraction. Intact proteins were also detected for S. oneidensis lysates obtained from cells grown on 13C-, 15N-depleted media under aerobic and sub-oxic conditions. The strategy can be readily applied for measuring differential protein abundances and provides a platform for high-throughput selection of biologically relevant targets for further characterization.