Proteomic Mixtures Research Articles

Quantifying label enrichment from two mass isotopomers increases proteome coverage for in vivo protein turnover using heavy water metabolic labeling

Heavy water metabolic labeling followed by liquid chromatography coupled with mass spectrometry is a powerful high throughput technique for measuring the turnover rates of individual proteins in vivo. The turnover rate is obtained from the exponential decay modeling of the depletion of the monoisotopic relative isotope abundance. We provide theoretical formulas for the time course dynamics of six mass isotopomers and use the formulas to introduce a method that utilizes partial isotope profiles, only two mass isotopomers, to compute protein turnover rate. The use of partial isotope profiles alleviates the interferences from co-eluting contaminants in complex proteome mixtures and improves the accuracy of the estimation of label enrichment. In five different datasets, the technique consistently doubles the number of peptides with high goodness-of-fit characteristics of the turnover rate model. We also introduce a software tool, d2ome+, which automates the protein turnover estimation from partial isotope profiles.

Coisolation of Peptide Pairs for Peptide Identification and MS/MS-Based Quantification.

Stable-isotope labeling with amino acids in cell culture (SILAC)-based metabolic labeling is a widely adopted proteomics approach that enables quantitative comparisons among a variety of experimental conditions. Despite its quantitative capacity, SILAC experiments analyzed with data-dependent acquisition (DDA) do not fully leverage peptide pair information for identification and suffer from undersampling compared to label-free proteomic experiments. Herein, we developed a DDA strategy that coisolates and fragments SILAC peptide pairs and uses y-ions for their relative quantification. To facilitate the analysis of this type of data, we adapted the Comet sequence database search engine to make use of SILAC peptide paired fragments and developed a tool to annotate and quantify MS/MS spectra of coisolated SILAC pairs. This peptide pair coisolation approach generally improved expectation scores compared to the traditional DDA approach. Fragment ion quantification performed similarly well to precursor quantification in the MS1 and achieved more quantifications. Lastly, our method enables reliable MS/MS quantification of SILAC proteome mixtures with overlapping isotopic distributions. This study shows the feasibility of the coisolation approach. Coupling this approach with intelligent acquisition strategies has the potential to improve SILAC peptide sampling and quantification.

Organic Solvent-Based Protein Precipitation for Robust Proteome Purification Ahead of Mass Spectrometry.

While multiple advances in mass spectrometry (MS) instruments have improved qualitative and quantitative proteome analysis, more reliable front-end approaches to isolate, enrich, and process proteins ahead of MS are critical for successful proteome characterization. Low, inconsistent protein recovery and residual impurities such as surfactants are detrimental to MS analysis. Protein precipitation is often considered unreliable, time-consuming, and technically challenging to perform compared to other sample preparation strategies. These concerns are overcome by employing optimal protein precipitation protocols. For acetone precipitation, the combination of specific salts, temperature control, solvent composition, and precipitation time is critical, while the efficiency of chloroform/methanol/water precipitation depends on proper pipetting and vial manipulation. Alternatively, these precipitation protocols are streamlined and semi-automated within a disposable spin cartridge. The expected outcomes of solvent-based protein precipitation in the conventional format and using a disposable, two-stage filtration and extraction cartridge are illustrated in this work. This includes the detailed characterization of proteomic mixtures by bottom-up LC-MS/MS analysis. The superior performance of SDS-based workflows is also demonstrated relative to non-contaminated protein.

Chemical activation of divergent protein tyrosine phosphatase domains with cyanine-based biarsenicals

Strategies for the direct chemical activation of specific signaling proteins could provide powerful tools for interrogating cellular signal transduction. However, targeted protein activation is chemically challenging, and few broadly applicable activation strategies for signaling enzymes have been developed. Here we report that classical protein tyrosine phosphatase (PTP) domains from multiple subfamilies can be systematically sensitized to target-specific activation by the cyanine-based biarsenical compounds AsCy3 and AsCy5. Engineering of the activatable PTPs (actPTPs) is achieved by the introduction of three cysteine residues within a conserved loop of the PTP domain, and the positions of the sensitizing mutations are readily identifiable from primary sequence alignments. In the current study we have generated and characterized actPTP domains from three different subfamilies of both receptor and non-receptor PTPs. Biarsenical-induced stimulation of the actPTPs is rapid and dose-dependent, and is operative with both purified enzymes and complex proteomic mixtures. Our results suggest that a substantial fraction of the classical PTP family will be compatible with the act-engineering approach, which provides a novel chemical-biological tool for the control of PTP activity and the study of PTP function.

Bifunctional Molecular Probes for Activity-Based Visualization of Quinone-Dependent Amine Oxidases.

The design, synthesis, and evaluation of two bifunctional molecular probes that can be used to visualize quinone-dependent amine oxidase enzymes in an activity-dependent manner are described. These probes use alkylhydrazines to irreversibly bind the target enzymes, which can then be visualized with either Western blotting or in-gel fluorescence. The results show that the Western blotting readout, which utilizes commercially available anti-nitrophenyl antibodies to detect a simple dinitrophenyl antigen, provides a stronger readout than the fluorescein-based fluorescence readout. This visualization strategy can be used to measure the potency of enzyme inhibitors by selectively visualizing the active enzyme that remains after treatment with an inhibitor. Looking forward, this probe molecule and visualization strategy will enable activity-based protein-profiling experiments, such as determining inhibitor selectivity values within full proteome mixtures, for this family of amine oxidase enzymes.

Highly parallel single-molecule identification of proteins in zeptomole-scale mixtures.

The identification and quantification of proteins lags behind DNA sequencing methods in scale, sensitivity and dynamic range. Here we show that sparse amino acid sequence information can be obtained for individual protein molecules for thousands to millions of molecules in parallel. We demonstrate selective fluorescent labeling of cysteine and lysine residues in peptide samples, immobilization of labeled peptides on a glass surface, and imaging by total internal reflection microscopy to monitor reductions in each molecule’s fluorescence following consecutive rounds of Edman degradation. The obtained sparse fluorescent sequence of each molecule was then assigned to its parent protein in a reference database. We demonstrate the method on synthetic and naturally-derived peptide molecules in zeptomole-scale quantities. We also fluorescently label phosphoserines and demonstrate single-molecule, positional readout of the phosphorylated sites. We measured >93% efficiencies for dye labeling, survival, and cleavage; further improvements should empower studies of increasingly complex proteomic mixtures, with the high sensitivity and digital quantification offered by single molecule sequencing.

Activation of Engineered Protein Tyrosine Phosphatases with the Biarsenical Compound AsCy3-EDT2.

Methods for activating signaling enzymes hold significant potential for the study of cellular signal transduction. Here we present a strategy for engineering chemically activatable protein tyrosine phosphatases (actPTPs). To generate actPTP1B, we introduced three cysteine point mutations in the enzyme's WPD loop. Biarsenical compounds were screened for the capability to bind actPTP1B's WPD loop and increase its phosphatase activity. We identified AsCy3-EDT2 as a robust activator that selectively targets actPTP1B in proteomic mixtures and intact cells. Introduction of the corresponding mutations in T-cell PTP also generates an enzyme (actTCPTP) that is strongly activated by AsCy3-EDT2 . Given the conservation of WPD-loop structure among the classical PTPs, our results potentially provide the groundwork of a widely generalizable approach for generating actPTPs as tools for elucidating PTP signaling roles as well as connections between dysregulated PTP activity and human disease.

Effects of an acidic environment on coagulation dynamics

Background Disruption of hydrogen ion homeostasis is a consequence of traumatic injury often associated with clinical coagulopathy. Mechanisms by which acidification of the blood leads to aberrant coagulation require further elucidation. Objective To examine the effects of acidified conditions on coagulation dynamics using in vitro models of increasing complexity. Methods Coagulation dynamics were assessed at pH 7.4 and 7.0 as follows: (i) tissue factor (TF)-initiated coagulation proteome mixtures (±factor [F]XI, ±fibrinogen/FXIII), with reaction progress monitored as thrombin generation or fibrin formation; (ii) enzyme/inhibitor reactions; and (iii) TF-dependent or independent clot dynamics in contact pathway-inhibited blood via viscoelastometry. Results Rate constants for antithrombin inhibition of FXa and thrombin were reduced by ~ 25-30% at pH 7.0. At pH 7.0 (+FXI), TF-initiated thrombin generation showed a 20% increase in maximum thrombin levels and diminished thrombin clearance rates. Viscoelastic analyses showed a 25% increase in clot time and a 25% reduction in maximum clot firmness (MCF). A similar MCF reduction was observed at pH 7.0 when fibrinogen/FXIII were reacted with thrombin. In contrast, in contact pathway-inhibited blood (n = 6) at pH 7.0, MCF values were elevated 6% (95% confidence interval [CI]: 1%-11%) in TF-initiated blood and 15% (95% CI: 1%- 29%) in the absence of TF. Clot times at pH 7.0 decreased 32% (95% CI: 15%-49%) in TF-initiated blood and 51% (95% CI: 35%-68%) in the absence of TF. Conclusions Despite reported decreased procoagulant catalysis at pH 7.0, clot formation dynamics are slightly enhanced in blood ex vivo and suppression of thrombin generation is not observed. A decrease in antithrombin reactivity is one potential mechanism contributing to these outcomes.

Automated SDS Depletion for Mass Spectrometry of Intact Membrane Proteins though Transmembrane Electrophoresis.

Membrane proteins are underrepresented in proteome analysis platforms because of their hydrophobic character, contributing to decreased solubility. Sodium dodecyl sulfate is a favored denaturant in proteomic workflows, facilitating cell lysis and protein dissolution; however, SDS impedes MS detection and therefore must be removed prior to analysis. Although strategies exist for SDS removal, they provide low recovery, purity, or reproducibility. Here we present a simple automated device, termed transmembrane electrophoresis (TME), incorporating the principles of membrane filtration, but with an applied electric current to ensure near-complete (99.9%) removal of the surfactant, including protein-bound SDS. Intact proteins are recovered in solution phase in high yield (90-100%) within 1 h of operation. The strategy is applied to protein standards and proteome mixtures, including an enriched membrane fraction from E. coli, resulting in quality MS spectra free of SDS adducts. The TME platform is applicable to both bottom-up MS/MS as well as LC-ESI-MS analysis of intact proteins. SDS-depleted fractions reveal a similar number of protein identifications (285) compared wit a non-SDS control (280), being highly correlated in terms of protein spectral counts. This fully automated approach to SDS removal presents a viable tool for proteome sample processing ahead of MS analysis. Data are available via ProteomeXchange, identifier PXD003941.

Effects of stem cell therapy on protein profile of parkinsonian rats using an(18) O-labeling quantitative proteomic approach.

The application of neural stem cell (NSC) research to neurodegenerative diseases has led to promising clinical trials. Currently, NSC therapy is most promising for Parkinson's disease (PD). We conducted behavioral tests and immunoassays for the profiling of a PD model in rats to assess the therapeutic effects of NSC treatments. Further, using a multiple sample comparison workflow, combined with (18) O-labeled proteome mixtures, we compared the differentially expressed proteins from control, PD, and NSC-treated PD rats. The results were analyzed bioinformatically and verified by Western blot. Based on our initial findings, we believe that the proteomic approach is a valuable tool in evaluating the therapeutic effects of NSC transplantation on neurodegenerative disorders.

Computational phosphoproteomics: from identification to localization.

Analysis of the phosphoproteome by MS has become a key technology for the characterization of dynamic regulatory processes in the cell, since kinase and phosphatase action underlie many major biological functions. However, the addition of a phosphate group to a suitable side chain often confounds informatic analysis by generating product ion spectra that are more difficult to interpret (and consequently identify) relative to unmodified peptides. Collectively, these challenges have motivated bioinformaticians to create novel software tools and pipelines to assist in the identification of phosphopeptides in proteomic mixtures, and help pinpoint or “localize” the most likely site of modification in cases where there is ambiguity. Here we review the challenges to be met and the informatics solutions available to address them for phosphoproteomic analysis, as well as highlighting the difficulties associated with using them and the implications for data standards.

Maximizing recovery of water-soluble proteins through acetone precipitation

Solvent precipitation is commonly used to purify protein samples, as seen with the removal of sodium dodecyl sulfate through acetone precipitation. However, in its current practice, protein loss is believed to be an inevitable consequence of acetone precipitation. We herein provide an in depth characterization of protein recovery through acetone precipitation. In 80% acetone, the precipitation efficiency for six of 10 protein standards was poor (ca. ≤15%). Poor recovery was also observed for proteome extracts, including bacterial and mammalian cells. As shown in this work, increasing the ionic strength of the solution dramatically improves the precipitation efficiency of individual proteins, and proteome mixtures (ca. 80–100% yield). This is obtained by including 1–30mM NaCl, together with acetone (50–80%) which maximizes protein precipitation efficiency. The amount of salt required to restore the recovery correlates with the amount of protein in the sample, as well as the intrinsic protein charge, and the dielectric strength of the solution. This synergistic approach to protein precipitation in acetone with salt is consistent with a model of ion pairing in organic solvent, and establishes an improved method to recover proteins and proteome mixtures in high yield.

ISPTM: An Iterative Search Algorithm for Systematic Identification of Post-translational Modifications from Complex Proteome Mixtures

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear matrix proteins with unknown modifications. ISPTM revealed that many chemical PTMs were introduced by urea and iodoacetamide during sample preparation and many biological PTMs, including dimethylation of arginine and lysine, were significantly activated by Adriamycin treatment in nuclear matrix associated proteins. ISPTM increased the MS/MS spectral identification rate substantially, displayed significantly better sensitivity for systematic PTM identification compared with that of the conventional all-in-one search approach, and offered PTM identification results that were complementary to InsPecT and MODa, both of which are established PTM identification algorithms. In summary, ISPTM is a new and powerful tool for unbiased identification of many different PTMs with high confidence from complex proteome mixtures.

A Nano LC-MALDI Mass Spectrometry Droplet Interface for the Analysis of Complex Protein Samples

The integration of matrix-assisted laser desorption ionization (MALDI) mass spectrometry with an upstream analytical separations (such as liquid chromatography and electrophoresis) has opened up new opportunities for the automated investigation of complex protein and peptide mixtures. The ability to efficiently analyze complex proteomic mixtures in this manner is primarily determined by the ability to preserve spatial discrimination of sample components as they leave the separation column. Current interfacing methods are problematic in this respect since minimum fraction volumes are limited to several microliters. Herein we show for the first time an LC-MALDI interface based on the formation, processing and destruction of a segmented flow. The interface consists of a droplet-generator to fractionate LC effluent into nL-volume droplets and a deposition probe that transfers the sample (and MALDI matrix) onto a conventional MALDI-MS target. The efficacy of the method is demonstrated through the analysis of Trypsin digests of both BSA and Cytochrome C, with a 50% enhancement in analytical performance when compared to conventional interface technology.

Network-based inference from complex proteomic mixtures using SNIPE

Proteomics presents the opportunity to provide novel insights about the global biochemical state of a tissue. However, a significant problem with current methods is that shotgun proteomics has limited success at detecting many low abundance proteins, such as transcription factors from complex mixtures of cells and tissues. The ability to assay for these proteins in the context of the entire proteome would be useful in many areas of experimental biology. We used network-based inference in an approach named SNIPE (Software for Network Inference of Proteomics Experiments) that selectively highlights proteins that are more likely to be active but are otherwise undetectable in a shotgun proteomic sample. SNIPE integrates spectral counts from paired case-control samples over a network neighbourhood and assesses the statistical likelihood of enrichment by a permutation test. As an initial application, SNIPE was able to select several proteins required for early murine tooth development. Multiple lines of additional experimental evidence confirm that SNIPE can uncover previously unreported transcription factors in this system. We conclude that SNIPE can enhance the utility of shotgun proteomics data to facilitate the study of poorly detected proteins in complex mixtures. An implementation for the R statistical computing environment named snipeR has been made freely available at http://genetics.bwh.harvard.edu/snipe/. ssunyaev@rics.bwh.harvard.edu Supplementary data are available at Bioinformatics online.

Quantitative Proteomic Analysis of Mouse Embryonic Fibroblasts and Induced Pluripotent Stem Cells Using 16O/18O Labeling

Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here, we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC. This platform consists of 16O/18O labeling, multidimensional peptide separation coupled with tandem mass spectrometry, and data analysis with UNiquant software. With this platform, a total of 2481 proteins were identified and quantified from the 16O/18O-labeled MEF-iPSC proteome mixtures with a false discovery rate of 0.01. Among them, 218 proteins were significantly upregulated, while 247 proteins were significantly downregulated in iPSC compared to MEF. Many nuclear proteins, including Hdac1, Dnmt1, Pcna, Ccnd1, Smarcc1, and subunits in DNA replication and RNA polymerase II complex, were found to be enhanced in iPSC. Protein network analysis revealed that Pcna functions as a hub orchestrating complicated mechanisms including DNA replication, epigenetic inheritance (Dnmt1), and chromatin remodeling (Smarcc1) to reprogram MEF and maintain stemness of iPSC.

Rapid glycopeptide enrichment and N-glycosylation site mapping strategies based on amine-functionalized magnetic nanoparticles

Glycoproteins secreted or expressed on the cell surface at specific pathophysiological stages are well-recognized disease biomarkers and therapeutic targets. While mapping of specific glycan structures can be performed at the level of released glycans, site-specific glycosylation and identification of specific protein carriers can only be determined by analysis of glycopeptides. A key enabling step in mass spectrometry (MS)-based glycoproteomics is the ability to selectively or non-selectively enrich for the glycopeptides from a total pool of a digested proteome for MS analysis since the highly heterogeneous glycopeptides are usually present at low abundance and ionize poorly compared with non-glycosylated peptides. Among the most common approaches for non-destructive and non-glycan-selective glycopeptide enrichment are strategies based on various forms of hydrophilic interaction liquid chromatography (HILIC). We present here a variation of this method using amine-derivatized Fe(3)O(4) nanoparticles, in concert with in situ peptide N-glycosidase F digestion for direct matrix-assisted laser desorption/ionization–mass spectrometry analysis of N-glycosylation sites and the released glycans. Conditions were also optimized for efficient elution of the enriched glycopeptides from the nanoparticles for on-line nanoflow liquid chromatography–MS/MS analysis. Successful applications to single glycoproteins as well as total proteomic mixtures derived from biological fluids established the unrivaled practical versatility of this method, with enrichment efficiency comparable to other HILIC-based methods.

Factor XI Activation In Tissue Factor-Initiated Blood Coagulation

Abstract 2239 Introduction.In in vitro models of tissue factor (TF)-initiated coagulation, FXI activation has been linked to increased thrombin generation. However the effects of FXI in experimental models of normal hemostasis have often been subtle, prompting ongoing investigations to define contributing cofactors, potential collaborating activators and/or reaction conditions (e.g. low TF concentrations). In this study, predictions from a computational model of TF-initiated thrombin generation that includes thrombin dependent FXI activation are used to direct an investigation of the role of FXI in two empirical models of TF-initiated coagulation. Methods. FXI activation and FXIa interactions were computationally modeled by adding the appropriate sets of equations describing thrombin activation of FXI, FXIa activation of FIX, antithrombin inhibition of FXIa, and high molecular weight kininogen binding to FXI to the existing framework of differential equations. The efficacy of FXIa in promoting thrombin generation (α- thrombin-antithrombin, αTAT) was assessed via titration in contact pathway inhibited whole blood and compared to activation by TF, FIXa, FXa and α-thrombin. TF-initiated reactions and their resupply were performed as described previously (Orfeo T et al. J. Biol. Chem., 2008) in either contact pathway inhibited blood ± an inhibitory anti-FXI antibody) or in synthetic coagulation proteome (SCP) mixtures (± FXI), allowing FXI effects on both the TF dependent phase and the resulting procoagulant pool of catalysts to be evaluated. Results. The computational model (± FXI pathway) was validated by showing congruence between computational thrombin generation profiles initiated with 5 pM TF and corresponding SCP reconstructions, which showed the lag phase shortened by 30 to 60 s and maximum thrombin levels increased when FXI was present. Similarly there was good correspondence between computational and SCP thrombin generation when FXIa (4 pM by active site) was the initiator. A computational analysis provided the following ranking of effectiveness in initiating thrombin generation: FXIa>TF>FIXa>FXa>α-thrombin. When tested in contact pathway inhibited blood, addition of 5 pM FXIa (by active site) resulted in clot times and 20 min αTAT levels similar to those observed with 5 pM TF, while similar outcomes required 25 pM FIXa, 100 pM FXa or between 10–100 nM α-thrombin. The computational modeling made clear two consequences of FXI feedback activation. The first was mechanistic, demonstrating that the amplification of thrombin generation was achieved by better coordinating the initial activations of FIX and FVIII; limited early initiation phase activation of FXI (<0.01% zymogen activation) increases the amount of FIXa available during the activation of FVIII, yielding higher concentrations of intrinsic tenase earlier in the initiation phase. The second consequence was increased FIXa accumulation as the reaction proceeds. This prediction was confirmed in two ways: 1) Western blot analysis of SCP reactions containing FXI showed ∼20% consumption of FIX over 20 min compared to no detectable FIX consumption in reactions without FXI; and 2) Resupply of TF-initiated SCP reactions (± 30 nM FXI) demonstrated that both the FVIII dependence and the long-term stability of the observed re-initiation of thrombin generation depended on the presence of FXI. Resupply studies were then performed in contact pathway inhibited blood (N=4 individuals) by using an inhibitory anti-FXI antibody to negate FXI contributions to both the TF-initiated and resupply dynamics. No effect of blocking FXI function on the time courses of αTAT formation was observed in the TF initiated phase. Two of the four individuals showed attenuated αTAT formation upon resupply when FXI function was blocked from the onset of TF initiation. Conclusions. FXIa is a potent initiator of coagulation, and the computational and SCP analyses predict the potential for feedback activation by thrombin after TF initiation to somewhat enhance the propagation phase of thrombin generation and more dramatically enhance the resupply response. However in contact pathway inhibited blood, FXI contributions to Tf-initiated thrombin generation are not discernible and the effect on the resupply response is variable between individuals suggesting additional mechanisms suppressing FXI activation in blood. Disclosures:Mann:Haematologic Technologies: Chairman of the Board, Equity Ownership, Membership on an entity’s Board of Directors or advisory committees; corn trypsin inhibitor: Patents & Royalties; NIH, DOD, Baxter: Research Funding; Merck, Daiichi Sankyo, Baxter, GTI: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau.

Software for Quantitative Proteomic Analysis Using Stable Isotope Labeling and Data Independent Acquisition

Many software tools have been developed for analyzing stable isotope labeling (SIL)-based quantitative proteomic data using data dependent acquisition (DDA). However, programs for analyzing SIL-based quantitative proteomics data obtained with data independent acquisition (DIA) have yet to be reported. Here, we demonstrated the development of a new software for analyzing SIL data using the DIA method. Performance of the DIA on SYNAPT G2MS was evaluated using SIL-labeled complex proteome mixtures with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10) and compared with the DDA on linear ion trap (LTQ)-Orbitrap MS. The DIA displays relatively high quantitation accuracy for peptides cross all intensity regions, while the DDA shows an intensity dependent distribution of H/L ratios. For the three proteome mixtures, the number of detected SIL-peptide pairs and dynamic range of protein intensities using DIA drop stepwise, whereas no significant changes in these aspects using DDA were observed. The new software was applied to investigate the proteome difference between mouse embryonic fibroblasts (MEFs) and MEF-derived induced pluripotent stem cells (iPSCs) using (16)O/(18)O labeling. Our study expanded the capacities of our UNiquant software pipeline and provided valuable insight into the performance of the two cutting-edge MS platforms for SIL-based quantitative proteomic analysis today.

UNiquant, a Program for Quantitative Proteomics Analysis Using Stable Isotope Labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.