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Top-down proteomics, the analysis of intact proteins in their endogenous form, preserves valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down liquid chromatography-tandem MS (LC-MS/MS) data sets is rapidly increasing on account of advances in instrumentation and sample-processing protocols. However, top-down mass spectra are substantially more complex than conventional bottom-up data. New algorithms and software tools for confident proteoform identification and quantification are needed. Here we present Informed-Proteomics, an open-source software suite for top-down proteomics analysis that consists of an LC-MS feature-finding algorithm, a database search algorithm, and an interactive results viewer. We compare our tool with several other popular tools using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.

Various proteoforms may be generated from a single gene due to primary structure alterations (PSAs) such as genetic variations, alternative splicing, and post-translational modifications (PTMs). Top-down mass spectrometry is capable of analyzing intact proteins and identifying patterns of multiple PSAs, making it the method of choice for studying complex proteoforms. In top-down proteomics, proteoform identification is often performed by searching tandem mass spectra against a protein sequence database that contains only one reference protein sequence for each gene or transcript variant in a proteome. Because of the incompleteness of the protein database, an identified proteoform may contain unknown PSAs compared with the reference sequence. Proteoform characterization is to identify and localize PSAs in a proteoform. Although many software tools have been proposed for proteoform identification by top-down mass spectrometry, the characterization of proteoforms in identified proteoform-spectrum matches still relies mainly on manual annotation. We propose to use the Modification Identification Score (MIScore), which is based on Bayesian models, to automatically identify and localize PTMs in proteoforms. Experiments showed that the MIScore is accurate in identifying and localizing one or two modifications.

There are several notable challenges inherent for fully characterizing the entirety of the human saliva proteome using bottom-up approaches, including polymorphic isoforms, PTMs, unique splice variants, deletions, and truncations. To address these challenges, we have developed a top-down based LC-MS/MS approach, which cataloged 20 major human salivary proteins with a total of 83 proteoforms, containing a broad range of PTMs. Among these proteins, several previously reported disease biomarker proteins were identified at the intact protein level, such as beta-2 microglobulin. In addition, intact glycosylated proteoforms of several saliva proteins were also characterized, including intact N-glycosylated protein prolactin inducible protein and O-glycosylated acidic protein rich protein. These characterized proteoforms constitute an intact saliva proteoform database, which was used for quantitative comparison of intact salivary proteoforms among six healthy individuals. Human parotid and submandibular/sublingual gland secretion samples (2 μg of protein each) from six healthy individuals were compared using RPLC coupled with the 12T FT-ICR mass spectrometer. Significantly different proteoform profiles were resolved with high reproducibility between parotid secretion and submandibular/sublingual glands. The results from this study provide further insight into the potential mechanisms of PTM pathways in oral glandular secretion, expanding our knowledge of this complex yet easily accessible fluid. Intact protein LC-MS approach presented herein can potentially be applied for rapid and accurate identification of biomarkers from only a few microliters of human glandular saliva., (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Background: Cancer invasion and metastasis are closely associated with activities within the degradome; however, little is known about whether these activities can be detected in the blood of cancer patients., Methodology and Principal Findings: The peptidome-degradome profiles of pooled blood plasma sampled from 15 breast cancer patients (BCP) and age, race, and menopausal status matched control healthy persons (HP) were globally characterized using advanced comprehensive separations combined with tandem Fourier transform mass spectrometry and new data analysis approaches that facilitated top-down peptidomic analysis. The BCP pool displayed 71 degradome protein substrates that encompassed 839 distinct peptidome peptides. In contrast, the HP 50 degradome substrates found encompassed 425 peptides. We find that the ratios of the peptidome peptide relative abundances can vary as much as >4000 fold between BCP and HP. The experimental results also show differential degradation of substrates in the BCP sample in their functional domains, including the proteolytic and inhibitory sites of the plasmin-antiplasmin and thrombin-antithrombin systems, the main chains of the extracellular matrix protection proteins, the excessive degradation of innate immune system key convertases and membrane attack complex components, as well as several other cancer suppressor proteins., Conclusions: Degradomics-peptidomics profiling of blood plasma is highly sensitive to changes not evidenced by conventional bottom-up proteomics and potentially provides unique signatures of possible diagnostic utility.

Identifying proteins and their modification states and with known levels of confidence remains as a significant challenge for proteomics. Random or decoy peptide databases are increasingly being used to estimate the false discovery rate (FDR), e.g., from liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyses of tryptic digests. We show that this approach can significantly underestimate the FDR and describe an approach for more confident protein identifications that uses unique partial sequences derived from a combination of database searching and amino acid residue sequencing using high-accuracy MS/MS data. Applied to a Saccharomyces cerevisiae tryptic digest, the approach provided 3 132 confident peptide identifications ( approximately 5% modified in some fashion), covering 575 proteins with an estimated zero FDR. The conventional approach provided 3 359 peptide identifications and 656 proteins with 0.3% FDR based upon a decoy database analysis. However, the present approach revealed approximately 5% of the 3 359 identifications to be incorrect and many more as potentially ambiguous (e.g., due to not considering certain amino acid substitutions and modifications). In addition, 677 peptides and 39 proteins were identified that had been missed by conventional analysis, including nontryptic peptides, peptides with a variety of expected/unexpected chemical modifications, known/unknown post-translational modifications, single nucleotide polymorphisms or gene encoding errors, and multiple modifications of individual peptides.

Advanced proteomic research efforts involving areas such as systems biology or biomarker discovery are enabled by the use of high level informatics tools that allow the effective analysis of large quantities of differing types of data originating from various studies. Performing such analyses on a large scale is not feasible without a computational platform that performs data processing and management tasks. Such a platform must be able to provide high-throughput operation while having sufficient flexibility to accommodate evolving data analysis tools and methodologies. The Proteomics Research Information Storage and Management system (PRISM) provides a platform that serves the needs of the accurate mass and time tag approach developed at Pacific Northwest National Laboratory. PRISM incorporates a diverse set of analysis tools and allows a wide range of operations to be incorporated by using a state machine that is accessible to independent, distributed computational nodes. The system has scaled well as data volume has increased over several years, while allowing adaptability for incorporating new and improved data analysis tools for more effective proteomics research.

This work focuses on the development of a multidimensional electrokinetic-based separation/concentration platform coupled with electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry (ESI-FTICR-MS) for achieving the high resolution and ultrasensitive analysis of complex protein/peptide mixtures. A microdialysis junction is employed as the interface for on-line combination of capillary isoelectric focusing (CIEF) with transient capillary isotachophoresis/zone electrophoresis (CITP/CZE) in an integrated platform. Besides the excellent resolving power afforded by both CIEF and CZE separations, the electrokinetic focusing/stacking effects of CIEF and CITP greatly enhance the dynamic range and detection sensitivity of MS for protein identification. The constructed multidimensional separation/concentration platform is demonstrated for the analysis of Shewanella oneidensis proteome, which has considerable implications toward the bioremediation of environmental pollutants. The electrokinetic-based platform offers the overall peak capacity comparable to those obtained using multidimensional chromatography systems, but with a much shorter run time and no need for column regeneration. Most importantly, a total of 1174 unique proteins, corresponding to 26.5% proteome coverage, are identified from the cytosolic fraction of S. oneidensis, while requiring <500 ng of proteolytic digest loaded in the CIEF capillary. The ultrasensitive capabilities of electrokinetic-based proteome approach are attributed to the concentration effect in CIEF, the electrokinetic stacking of CITP, the nanoscale peak volume in CZE, the "accurate mass tag" strategy for protein/peptide identification, and the high-sensitivity, high-resolution, and high-mass measurement accuracy of FTICR-MS.

A primary challenge in proteome measurements is to be able to detect, identify, and quantify the extremely complex mixtures of proteins. The relative abundances of interest span at least six orders of magnitude for mammalian proteomes, and this constitutes an intractable challenge for high throughput proteome studies. We have recently described a new approach, Dynamic Range Enhancement Applied to Mass Spectrometry (DREAMS), which is based upon the selective ejection of the most abundant species to expand the dynamic range of Fourier transform ion cyclotron resonanace (FTICR) measurements. The basis of our approach is on-the-fly data-dependent selective ejection of highly abundant species, followed by prolonged accumulation of remaining low-abundance species in a quadrupole external to the FTICR ion trap. Here we report the initial implementation of this approach with high efficiency capillary reverse phase LC separations and high magnetic field electrospray ionization FTICR mass spectrometry for obtaining enhanced coverage in quantitative measurements for mammalian proteomes. We describe the analysis of a sample derived from a tryptic digest of proteins from mouse B16 cells cultured in both natural isotopic abundance and 15N-labeled media. The FTICR mass spectrometric analysis allows the assignment of peptide pairs (corresponding to the two distinctive versions of each peptide), and thus provides the basis for quantiative measurements when one of the two proteomes in the mixture is perturbed or altered in some fashion. We show that implementation of the DREAMS approach allows assignment of approximately 80% more peptide pairs, thus providing quantitative information for approximately 18,000 peptide pairs in a single analysis.

We report on the design and application of a high-efficiency multiple-capillary liquid chromatography (LC) system for high-throughput proteome analysis. The multiple-capillary LC system using commercial LC pumps was operated at a pressure of 10,000 psi to deliver mobile phases through a novel passive feedback valve arrangement that permitted mobile-phase flow path switching and efficient sample introduction. The multiple-capillary LC system uses several serially connected dual-capillary column devices. The dual-capillary column approach eliminates the time delays for column regeneration (or equilibration) since one capillary column was used for a separation while the other was being washed. Several serially connected dual-capillary columns and electrospray ionization (ESI) sources were operated independently and can be used either for "backup" operation or for parallel operation with other mass spectrometers. This high-efficiency multiple-capillary LC system utilizes switching valves for all operations, enabling automated operation. The separation efficiency of the dual-capillary column arrangement, optimal capillary dimensions (column length and packed particle size), capillary regeneration conditions, and mobile-phase compositions and their compatibility with electrospray ionization were investigated. A high magnetic field (11.4 T) Fourier transform ion cyclotron resonance (FTICR) mass spectrometer was coupled on-line with this high-efficiency multiple-capillary LC system using an ESI interface. The capillary LC provided a peak capacity of approximately 650, and the 2-D capillary LC-FTICR analysis provided a combined resolving power of > 6 x 10(7) components. For yeast cytosolic tryptic digests > 100,000 polypeptides were detected, and approximately 1,000 proteins could be characterized from a single capillary LC-FTICR analysis using the high mass measurement accuracy (approximately 1 ppm) of FTICR, and likely more if LC retention time information were also exploited for peptide identification.