The human plasma proteome: history, character, and diagnostic prospects

Effective depletion of albumin using a new peptide-based affinity medium

Blood plasma and serum are very useful samples for the detection, identification and quantitation of proteins associated with both health and disease. However, analysis of plasma and serum is a challenge because traces of interesting polypeptides and proteins can be dominated by the very high concentration of albumin present. Albumin may be depleted by adsorption to immunoaffinity columns or to columns containing dyes such as Cibacron Blue, or by ultrafiltration, but these methods are far from ideal. We describe a new peptide-based affinity medium which is effective for removing albumin and is very specific. The albumin-binding capacity is at least 14 mg per mL of gel. The material may be reused hundreds of times after a simple regeneration step involving NaOH, with full retention of specificity and capacity. The material was tested with human and monkey plasma and serum and rat serum, and has been used to deplete litre volumes of human plasma. The development of other peptide-based affinity media to deplete abundant proteins is briefly discussed.

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.

Proteomic analysis of human pleural effusion

Pleural effusion, an accumulation of pleural fluid, contains proteins originating from plasma filtrate and, especially when tissues are damaged, parenchymal interstitial spaces of lungs and/or other organs. This report presents data of the first global proteomic analysis of human pleural effusion. A composite sample was prepared by pooling pleural effusions from seven lung adenocarcinoma patients. Two-dimensional gel electrophoresis analysis of the composite sample revealed 472 silver-stained spots. 242 selected gel spots were subjected to protein identification by in-gel digestion, liquid chromatography-tandem mass spectrometry, and sequence database search. 44 proteins were identified with higher confidence levels (at least two unique peptide sequences matched), while 161 other proteins were identified at the minimal confidence level (only one unique peptide sequence matched). The data provide fundamental information on the composition of protein contents in human pleural effusion. Among these 44 proteins that were identified with higher confidence levels, 7 proteins, retinoblastoma binding protein 7, synaptic vesicle membrane protein, corticosteroid binding globulin precursor, PR-domain containing protein 11, envelope glycoprotein, MSIP043 protein, and titin have not been reported in plasma and may represent proteins specifically present in pleural effusion. These proteins could have originated from parenchymal interstitial spaces and represent potential candidates of useful biomarkers that could not be readily detected in plasma but in pleural effusion. Retinoblastoma binding protein 7 is of special interest since it may play a role in the regulation of cell proliferation and differentiation.

Workshop on Cancer Biometrics: Identifying Biomarkers and Surrogates of Cancer in Patients

The current excitement about molecular targeted therapies has driven much of the recent dialog in cancer diagnosis and treatment. Particularly in the biologic therapy of cancer, identifiable antigenic T-cell targets restricted by MHC molecules and the related novel stress molecules such as MICA/B and Letal allow a degree of precision previously unknown in cancer therapy. We have previously held workshops on immunologic monitoring and angiogenesis monitoring. This workshop was designed to discuss the state of the art in identification of biomarkers and surrogates of tumor in patients with cancer, with particular emphasis on assays within the blood and tumor. We distinguish this from immunologic monitoring in the sense that it is primarily a measure of the tumor burden as opposed to the immune response to it. Recommendations for intensive investigation and targeted funding to enable such strategies were developed in seven areas: genomic analysis; detection of molecular markers in peripheral blood and lymph node by tumor capture and RT-PCR; serum, plasma, and tumor proteomics; immune polymorphisms; high content screening using flow and imaging cytometry; immunohistochemistry and tissue microarrays; and assessment of immune infiltrate and necrosis in tumors. Concrete recommendations for current application and enabling further development in cancer biometrics are summarized. This will allow a more informed, rapid, and accurate assessment of novel cancer therapies.

Clinical-scale high-throughput human plasma proteome analysis: Lung adenocarcinoma

Clinical proteomics requires the stable and reproducible analysis of a large number of human samples. We report a high-throughput comprehensive protein profiling system comprising a fully automated, on-line, two-dimensional microflow liquid chromatography/tandem mass spectrometry (2-D microLC-MS/MS) system for use in clinical proteomics. A linear ion-trap mass spectrometer (ITMS) also known as a 2-D ITMS instrument, which is characterized by high scan speed, was incorporated into the microLC-MS/MS system in order to obtain highly improved sensitivity and resolution in MS/MS acquisition. This system was used to evaluate bovine serum albumin and human 26S proteasome. Application of these high-throughput microLC conditions and the 2-D ITMS resulted in a 10-fold increase in sensitivity in protein identification. Additionally, peptide fragments from the 26S proteasome were identified three-fold more efficiently than by the conventional 3-D ITMS instrument. In this study, the 2-D microLC-MS/MS system that uses linear 2-D ITMS has been applied for the plasma proteome analysis of a few samples from healthy individuals and lung adenocarcinoma patients. Using the 2-D and 1-D microLC-MS/MS analyses, approximately 250 and 100 different proteins were detected, respectively, in each HSA- and IgG-depleted sample, which corresponds to only 0.4 microL of blood plasma. Automatic operation enabled the completion of a single run of the entire 1-D and 2-D microLC-MS/MS analyses within 11 h. Investigation of the data extracted from the protein identification datasets of both healthy and adenocarcinoma groups revealed that several of the group-specific proteins could be candidate protein disease markers expressed in the human blood plasma. Consequently, it was demonstrated that this high-throughput microLC-MS/MS protein profiling system would be practically applicable to the discovery of protein disease markers, which is the primary objective in clinical plasma proteome projects.

Candidate-based proteomics in the search for biomarkers of cardiovascular disease

The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a 'directed proteomics' approach.

Protein Identification in Complex Mixtures

This paper investigates the prospects of successful mass spectrometric protein identification based on mass data from proteolytic digests of complex protein mixtures. Sets of proteolytic peptide masses representing various numbers of digested proteins in a mixture were generated in silico. In each set, different proteins were selected from a protein sequence collection and for each protein the sequence coverage was randomly selected within a particular regime (15-30% or 30-60%). We demonstrate that the Probity algorithm, which is characterized by an optimal tolerance for random interference, employed in an iterative procedure can correctly identify >95% of proteins at a desired significance level in mixtures composed of hundreds of yeast proteins under realistic mass spectrometric experimental constraints. By using a model of the distribution of protein abundance, we demonstrate that the very high efficiency of identification of protein mixtures that can be achieved by appropriate choices of informatics procedures is hampered by limitations of the mass spectrometric dynamic range. The results stress the desire to choose carefully experimental protocols for comprehensive proteome analysis, focusing on truly critical issues such as the dynamic range, which potentially limits the possibilities of identifying low abundance proteins.

Integrated Microfluidic Device for Mass Spectrometry-Based Proteomics and Its Application to Biomarker Discovery Programs

The present investigation describes the analytical performances of a microfluidic device comprising an enrichment column, a reversed-phase separation channel, and a nanoelectrospray emitter embedded altogether in polyimide layers. This configuration minimizes transfer lines and connections and reduces postcolumn peak broadening and dead volumes. This compact and versatile modular nanoLC-chip system was interfaced to both ion trap and time-of-flight mass spectrometers, and its analytical potentials were evaluated in the context of proteomics applications. The figures of merit of this system in terms of peak capacity, reproducibility, sensitivity, and linear dynamic range of peptide detection were determined using tryptic digests of complex protein extracts including albumin- and immunoglobulin-depleted rat plasma samples. The analysis of peak profiles for more than 600 peptide ions reproducibly detected across replicate nanoLC-chip-MS runs (n = 10) indicated that this system provided good reproducibility of retention time and peak intensity with RSD values of less than 0.5 and 9.1%, respectively. Variation in peptide abundance as low as 2-fold changes was identified for spiked tryptic digests present at levels of 2-5 fmol in plasma samples. Sensitivity measurements were performed on dilution series of protein digests spiked into rat plasma samples and provided a detection limit of 1-5 fmol. The modular concept of the microfluidic systems also facilitated the integration of two-dimensional chromatography (strong cation exchange/C18) thereby increasing the sample loading and selectivity of the nanoLC-chip-MS system. The application of this integrated device was evaluated for complex rat plasma samples to compare the number of protein identifications obtained using one- and two-dimensional nanoLC-chip-MS/MS.

How to Bring the “Unseen” Proteome to the Limelight via Electrophoretic Pre-Fractionation Techniques

The present review reports a panoply of electrophoretic methods as pre-fractionation tools in proteomic investigations in preparation for mass spectrometry or two-dimensional electrophoresis map analysis. Such electrophoretic pre-fractionation protocols include all those electrokinetic methodologies which are performed in free solution, most of them relying on isoelectric focusing steps (although some approaches based on gels and granulated media are also discussed). Devices associated with electrophoretic separations are multi-chamber apparatuses, such as the multi-compartment electrolyzers equipped with either isoelectric membranes or with isoelectric beads, Off-Gel electrophoresis in a multi-cup device and the Rotofor, an instrument also based on a multi-chamber system but exploiting the conventional technique of carrier-ampholyte-focusing. Other free-flow systems, as well as miniaturized chambers, are also described.

Isoelectric beads for proteome pre-fractionation. II: Experimental evaluation in a multicompartment electrolyzer

Proteome pre-fractionation in multicompartment electrolyzers is proposed here, with substantial modifications as compared to the standard technique. First of all, the classical isoelectric, buffering membranes, delimiting each compartment and acting, in pairs, as isoelectric traps, have been replaced by isoelectric buffering beads, operating on the same principle, but allowing unhindered migration of proteins (lack of sieving properties, contrary to typical continuous membrane barriers). Secondly, the isoelectric beads are not made in the conventional manner, with ionic acrylamide derivative monomers throughout their central core, but are composed of a hard, ceramic core, coated with an amphoteric buffering polymer. This minimizes mass transfer resistance of proteins that are transiently adsorbed onto the beads. As a result, significantly reduced separation times, of the order of ca. 3 h, are required for developing steady-state patterns, as compared to the lengthy times (overnight and much longer) in conventional multicompartment electrolyzers operating with isoelectric membranes. Examples of separation of standard marker proteins, as well as entire Escherichia coli lysates and human serum proteins, are given. The obtained fractions are analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis, two-dimensional gel electrophoresis and by surface enhanced laser desorption/ionization mass spectrometry.

Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry

There is significant interest in characterization of the human plasma proteome due to its potential for providing biomarkers applicable to clinical diagnosis and treatment and for gaining a better understanding of human diseases. We describe here a strategy for comparative proteome analyses of human plasma, which is applicable to biomarker identifications for various disease states. Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been applied to make comparative proteome analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Peptide peak areas and the number of peptide identifications for each protein were used to evaluate the reproducibility of LC-MS/MS and to compare relative changes in protein concentration between the samples following LPS treatment. A total of 804 distinct plasma proteins (not including immunoglobulins) were confidently identified with 32 proteins observed to be significantly increased in concentration following LPS administration, including several known inflammatory response or acute-phase mediators such as C-reactive protein, serum amyloid A and A2, LPS-binding protein, LPS-responsive and beige-like anchor protein, hepatocyte growth factor activator, and von Willebrand factor, and thus, constituting potential biomarkers for inflammatory response.

Probability-Based Evaluation of Peptide and Protein Identifications from Tandem Mass Spectrometry and SEQUEST Analysis: The Human Proteome

Large-scale protein identifications from highly complex protein mixtures have recently been achieved using multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) and subsequent database searching with algorithms such as SEQUEST. Here, we describe a probability-based evaluation of false positive rates associated with peptide identifications from three different human proteome samples. Peptides from human plasma, human mammary epithelial cell (HMEC) lysate, and human hepatocyte (Huh)-7.5 cell lysate were separated by strong cation exchange (SCX) chromatography coupled offline with reversed-phase capillary LC-MS/MS analyses. The MS/MS spectra were first analyzed by SEQUEST, searching independently against both normal and sequence-reversed human protein databases, and the false positive rates of peptide identifications for the three proteome samples were then analyzed and compared. The observed false positive rates of peptide identifications for human plasma were significantly higher than those for the human cell lines when identical filtering criteria were used, suggesting that the false positive rates are significantly dependent on sample characteristics, particularly the number of proteins found within the detectable dynamic range. Two new sets of filtering criteria are proposed for human plasma and human cell lines, respectively, to provide an overall confidence of >95% for peptide identifications. The new criteria were compared, using a normalized elution time (NET) criterion (Petritis et al. Anal. Chem. 2003, 75, 1039-1048), with previously published criteria (Washburn et al. Nat. Biotechnol. 2001, 19, 242-247). The results demonstrate that the present criteria provide significantly higher levels of confidence for peptide identifications from mammalian proteomes without greatly decreasing the number of identifications.

Biomarkers: mining the biofluid proteome

Proteomics has brought with it the hope of identifying novel biomarkers for diseases such as cancer. This hope is built on the ability of proteomic technologies, such as mass spectrometry (MS), to identify hundreds of proteins in complex biofluids such as plasma and serum. There are many factors that make this research very challenging beginning with the lack of standardization of sample collection and continuing through the entire analytical process. Fortunately the advances made in the characterization of biofluids using proteomic techniques have been rapid and suggest that these mainly discovery driven approaches will lead to the development of highly specific platforms for diagnosing diseases and monitoring responses to different treatments in the near future.

Proteomic profiling of pancreatic cancer for biomarker discovery

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.

Proteomic patterns: their potential for disease diagnosis

Alterations in proteins abundance, structure, or function, act as useful indicators of pathological abnormalities prior to development of clinical symptoms and as such are often useful diagnostic and prognostic biomarkers. The underlying mechanism of diseases such as cancer are, however, quite complicated in that often multiple dysregulated proteins are involved. It is for this reason that recent hypotheses suggest that detection of panels of biomarkers may provide higher sensitivities and specificities for disease diagnosis than is afforded with single markers. Recently, a novel approach based on the analysis of protein patterns has emerged that may provide a more effective means to diagnose diseases, such as ovarian and prostate cancer. The method is based on the use of surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry (TOF-MS) to detect differentially captured proteins from clinical samples, such as serum and plasma. This analysis results in the detection of "proteomic" patterns that have been shown in recent investigations to distinguish diseased and unaffected subjects to varying degrees. This review will discuss the basics of SELDI protein chip technology and highlight its recent applications in disease biomarker discovery with emphasis on cancer diagnosis.

Proteomic patterns for early cancer detection

The advent of proteomics has brought with it the hope of discovering novel biomarkers that can be used to diagnose diseases, predict susceptibility, and monitor progression. Much of this effort has focused on the mass spectral identification of the thousands of proteins that populate complex biosystems such as serum and tissues. A revolutionary approach in proteomic pattern analysis has emerged as an effective method for the early diagnosis of diseases such as ovarian, breast, and prostate cancer. This technology is capable of analyzing hundreds of clinical samples per day and has the potential to be a novel, highly sensitive diagnostic tool for the early detection of diseases, or as a predictor of response to therapy.

Development of Field Modulation in a Split-Field Drift Tube for High-Throughput Multidimensional Separations

A field modulation approach for high-throughput ion mobility/time-of-flight analyses of complex mixtures has been developed using a split-field drift tube. In this approach, complex mixtures of peptides, such as those that arise from tryptic digestion of protein mixtures, are separated by nanocolumn liquid chromatography, ionized by electrospray ionization, and analyzed by ion mobility/time-of-flight techniques. The split-field drift tube allows parent ions to be separated based on differences in their low-field mobilities through the first-field region before entering the second region. For increased throughput, the magnitude of the field in the second region can be modulated throughout an LC separation in order to favor transmission of different types of ions: parent ions at low fields; fragments from primarily [M+3H]3+ peptides at moderate fields; or, fragmentation of [M+3H]3+ and [M+2H]2+ species at higher fields. We demonstrate the approach with two examples: a mixture of tryptic peptides from digestion of hemoglobin; and a complex mixture of tryptic peptides from digestion of human plasma.

Pharmacoproteomics

Proteomics, the comprehensive analysis of the protein complement of the genome of an organism, is becoming an increasingly important discipline for the identification of disease targets. In addition, the effects of drug treatment and metabolism can now be studied on the protein level in a comprehensive manner.

Heart-Fatty Acid-Binding Protein as a Marker for Early Detection of Acute Myocardial Infarction and Stroke

Heart-fatty acid-binding protein (H-FABP) is a small cytosolic protein involved in intracellular fatty acid transport. This protein, highly concentrated in the heart, is quickly released into plasma after myocardial injury. Results from numerous studies suggest that H-FABP is an excellent marker for the early detection of myocardial damage. H-FABP is also expressed in the brain, although in lower concentrations than in the heart. Recent preliminary studies also investigated the usefulness of H-FABP for the diagnosis of acute and chronic neurological disorders. These potential applications of H-FABP in clinical practice are reviewed in this article, with a strong focus on the early diagnosis of acute myocardial infarction and stroke.

The impact of blood contamination on the proteome of cerebrospinal fluid

Human cerebrospinal fluid (CSF) is in direct contact with the brain extracellular space. Beside the secretion of CSF by the choroid plexus the fluid also derives directly from the brain by the ependymal lining of the ventricular system and the glial membrane and from blood vessels in the arachnoid. Therefore, biochemical change in the brain may be reflected in the CSF. CSF is a potential source of protein molecular indices of central nervous system function and pathology. However, various amounts of blood contamination in CSF may arise during sample acquisition. The concentration of protein in the CSF is only 0.2 to 0.5% that of blood. Minor contamination of CSF with blood during collection of the fluid may dramatically alter the protein profile confounding the identification of potential biomarkers. We have analyzed CSF and CSF spiked with increasing amounts of whole blood using proteomic techniques. We detected at least four blood specific highly abundant proteins: hemoglobin, catalase, peroxiredoxin and carbonic anhydrase I. These proteins can be used as blood contamination markers for proteomic analysis of CSF. Proteins in blood contaminated CSF samples were less stable compared to neat CSF at 37 degrees C suggesting that blood borne protease may induce protein degradation in CSF during sample acquisition. This analysis was aimed at identification of proteins found primarily in CSF, those found primarily in blood and assessment of the impact of blood contamination on those proteins found in both fluids.

Serum protein profiling by miniaturized solid-phase extraction and matrix-assisted laser desorption/ionization mass spectrometry

Serum profiling by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) holds promise as a clinical tool for early diagnosis of cancer and other human diseases. Sample preparation is key to achieving reproducible and well-resolved signals in MALDI-MS; a prerequisite for translation of MALDI-MS based diagnostic methods to clinical applications. We have investigated a number of MALDI matrices and several miniaturized solid-phase extraction (SPE) methods for serum protein concentration and desalting with the aim of generating reproducible, high-quality protein profiles by MALDI-MS. We developed a simple protocol for serum profiling that combines a matrix mixture of 2,5-dihydroxybenzoic acid and alpha-cyano-4-hydroxycinnamic acid with miniaturized SPE and MALDI-MS. Functionalized membrane discs with hydrophobic, ion-exchange or chelating properties allowed reproducible MALDI mass spectra (m/z 1000-12,000) to be obtained from serum. In a proof-of-principle application, SPE with chelating material and MALDI-MS identified protein peaks in serum that had been previously reported for distinguishing a person diagnosed with breast cancer from a control. These preliminary results indicate that this simple SPE/MALDI-MS method for serum profiling provides a versatile and scalable platform for clinical proteomics.

Integrating disease knowledge and technology to deliver protein targets and biomarkers into drug discovery projects

Biomarker discovery is dependent upon two disciplines: the field of clinical bioanalysis linked to disease aetiology and the application of high level technology platforms for identifying proteins/peptides in complex samples. However, diagnostic biomarker measurements require certain definitions of context that can only be achieved by combining protein science with clinical science. The evaluation of biomarkers requires careful attention to match (1) a specific biological question with (2) the appropriate clinical sample and (3) high resolution technology systems which link protein identities to clinical informatics.:

A new strategy for identification of N-glycosylated proteins and unambiguous assignment of their glycosylation sites using HILIC enrichment and partial deglycosylation

Characterization of glycoproteins using mass spectrometry ranges from determination of carbohydrate-protein linkages to the full characterization of all glycan structures attached to each glycosylation site. In a novel approach to identify N-glycosylation sites in complex biological samples, we performed an enrichment of glycosylated peptides through hydrophilic interaction liquid chromatography (HILIC) followed by partial deglycosylation using a combination of endo-beta-N-acetylglucosaminidases (EC 3.2.1.96). After hydrolysis with these enzymes, a single N-acetylglucosamine (GlcNAc) residue remains linked to the asparagine residue. The removal of the major part of the glycan simplifies the MS/MS fragment ion spectra of glycopeptides, while the remaining GlcNAc residue enables unambiguous assignment of the glycosylation site together with the amino acid sequence. We first tested our approach on a mixture of known glycoproteins, and subsequently the method was applied to samples of human plasma obtained by lectin chromatography followed by 1D gel-electrophoresis for determination of 62 glycosylation sites in 37 glycoproteins.

High throughput quantitative analysis of serum proteins using glycopeptide capture and liquid chromatography mass spectrometry

It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible, and robust to detect potential biomarkers below the level of highly expressed proteins, generate data sets that are comparable between experiments and laboratories, and have high throughput to support statistical studies. Here we report a method for high throughput quantitative analysis of serum proteins. It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these now deglycosylated peptides by liquid chromatography electrospray ionization mass spectrometry, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We provide data that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen-induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. We further identify, by tandem mass spectrometry, some of the peptides that were consistently elevated in cancer mice compared with their control littermates.

Plasma proteome of severe acute respiratory syndrome analyzed by two-dimensional gel electrophoresis and mass spectrometry

We have investigated the plasma proteome by using 2D gel electrophoresis and MS from patients with severe acute respiratory syndrome (SARS). A complete proteomic analysis was performed on four patients with SARS in different time courses, and a total of 38 differential spots were selected for protein identification. Most of the proteins identified are acute phase proteins, and their presence represents the consequence of serial cascades initiated by SARS-coronavirus infection. There are several proteins that have never been identified in plasma before using 2D gel electrophoresis, among which peroxiredoxin II was chosen for further study by analyzing additional 20 plasma samples from patients with probable and suspected SARS and patients with fever, respectively. The results showed that the level of plasma peroxiredoxin II in patients with SARS is significantly high and could be secreted by T cells. Taken together, our findings indicate that active innate immune responses, along with the oxidation-associated injuries, may play a major role in the pathogenesis of SARS.

Serum peptide profiling by magnetic particle-assisted, automated sample processing and MALDI-TOF mass spectrometry

Human serum contains a complex array of proteolytically derived peptides (serum peptidome) that may provide a correlate of biological events occurring in the entire organism; for instance, as a diagnostic for solid tumors (Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro, V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.; Kohn, E. C.; Liotta, L. Lancet 2002, 359, 572-577). Here, we describe a novel, automated technology platform for the simultaneous measurement of serum peptides that is simple, scalable, and generates highly reproducible patterns. Peptides are captured and concentrated using reversed-phase (RP) batch processing in a magnetic particle-based format, automated on a liquid handling robot, and followed by a MALDI TOF mass spectrometric readout. The protocol is based on a detailed investigation of serum handling, RP ligand and eluant selection, small-volume robotics design, an optimized spectral acquisition program, and consistent peak extraction plus binning across a study set. The improved sensitivity and resolution allowed detection of 400 polypeptides (0.8-15-kDa range) in a single droplet (approximately 50 microL) of serum, and almost 2000 unique peptides in larger sample sets, which can then be analyzed using common microarray data analysis software. A pilot study indicated that sera from brain tumor patients can be distinguished from controls based on a pattern of 274 peptide masses. This, in turn, served to create a learning algorithm that correctly predicted 96.4% of the samples as either normal or diseased.

Is it functional?

This report describes the first scientific meeting of the British Society for Proteome Research (BSPR), which was organised jointly with the European Bioinformatics Institute (EBI) and held in July 2004. The focus of the conference was functional proteomics with an emphasis on possible clinical application. The main subjects described here are: the need to simplify samples, the use of biological fluids versus tissue, consideration of biological and experimental variation and the creation of databases to achieve meaningful functional analysis.

Mass spectrometric protein structure characterization reveals cause of migration differences of haptoglobin ? chains in two-dimensional gel electrophoresis

Haptoglobin belongs to the major constituents of plasma and acts as hemoglobin-binding and acute-phase protein. Due to the occurrence of three major allelic variants and further structural modifications, the alpha chains of haptoglobin form varying spot patterns in two-dimensional gel electrophoresis (2-DE) gels, which is generally observed in differential proteome analyses using plasma or related body fluids of humans. In the present study plasma samples from 10 donors of initially unknown haptoglobin phenotype were separated by 2-DE and tryptic digests of excised haptoglobin alpha chain spots were analyzed by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) and MALDI-quadrupole ion trap TOF-MS. Haptoglobin alpha1S, alpha1F, as well as alpha2 chains were found to occur each with at least three structurally differing protein species: (i) the unmodified form, which corresponds to the sequence database entries; (ii) derivatives, in which asparagine at position five is deamidated to aspartic acid; and (iii) derivatives with an additional C-terminal arginine residue. These structural variants account for the most commonly observed spot patterns of haptoglobin alpha chains in Coomassie-stained gels. Additionally, a minor derivative of the haptoglobin alpha2 chain carrying both modifications, deamidation at position five and the C-terminal arginine residue, was identified. Theoretical pI values of the characterized structural variants are, consistent with their observed migration in the 2-DE gels.

Reversed-Phase HPLC Separation of Human Serum Employing a Novel Saw-Tooth Gradient: Toward Multidimensional Proteome Analysis

A novel reversed-phase (RP-) HPLC gradient profile applicable to multidimensional separations of complex protein mixtures is reported. This gradient profile elutes small numbers of proteins from the RP-HPLC column in discrete intervals while minimizing the amount of band broadening between elution intervals and maintaining constant flow through the HPLC column. Eluting the proteins in discrete intervals eases the instrumental requirements necessary for performing multidimensional separations and can be used to aid in the collection of well-defined fractions. The saw-tooth gradient was applied to the successful isolation of albumin from less abundant proteins in whole human serum and provides adequate separation of proteins in a low-molecular weight (LMW) fraction of human serum with resolution comparable to that achieved using a typical linear gradient profile.

Proteomics in cancer screening and management in gynecologic cancer

Biomarkers are used routinely for population screening, disease diagnosis and prognosis, monitoring of therapy, and prediction of therapeutic response. Unfortunately, most biomarkers have low sensitivity and specificity and little predictive value. Novel techniques for better screening and early diagnosis of ovarian cancer are urgently needed. Proteomics, the study of the cellular proteins and their activation states, integrates some fundamental techniques, including high-throughput protein purification and profiling, genomic and proteomic databases, and mass spectrometry. In oncology, proteomics will contribute greatly to our understanding of gene functions in tumor development and provide information in clinical applications. This article reviews proteomic techniques and their potential applications in gynecologic cancer screening and management.

Proteomic analysis of blood level of proteins before and after operation in patients with esophageal squamous cell carcinoma at high-incidence area in Henan Province

AIM: To characterize the protein files in blood from same patients with esophageal squamous cell carcinoma (ESCC) before and after operation at the high-incidence area for ESCC in Henan Province, China.

METHODS: Two-dimensional electrophoresis, silver staining and ImageMaster 2-DE analysis software were applied to the determination of protein files in the blood obtained from normal controls and ESCC patients before and after operation.

RESULTS: A total of 655, 662 and 677 protein spots were identified, respectively, from the normal controls and ESCC patients before and after operation. No significant difference in the number of protein spots was observed between the normal group and ESCC patients. A total of seven protein spots were identified with a dramatic difference among the samples before and after operation. Six protein spots were up-regulated and one protein spot was down-regulated in the group after operation compared with those in normal and before operation. Three protein spots were further characterized by matrix-assisted laser desorption/ionization time of flying mass spectrometry (MALDI-TOF-MS). The proteins from these three spots were identified as serum amyloid A (SAA), amyloid related serum protein and haptoglobin.

CONCLUSION: serum amyloid A, amyloid related serum protein and haptoglobin may be related with ESCC and/or surgery. The significance of these proteins needs to be further characterized. The present study provides informative data for the establishment of serum protein profiles related with ESCC.

New directions of miniaturization within the biomarker research area

An overview of the current trends within protein expression profiling is given where multidimensional separation of both gel and liquid phase techniques linked to mass spectrometry is viewed as a major route in the global proteome mapping. A clear trend in these biochemical developments is the effort to sequence and identify low-abundant protein expressions where assay miniaturization and integrated sample processing play a central role. Two areas of miniaturization within the proteomics field are addressed: (i) sample cleanup and enrichment, and (ii) silicon microstructure developments for protein chip microarrays.

Proteomics for hepatocellular carcinoma marker discovery

Refinements of serological markers and screening of patients at high risk for developing hepatocellular carcinoma (HCC) may lead to better HCC detection, earlier intervention, and successful treatment, improving long-term outcomes. Proteomics promises the discovery of biomarkers for early HCC detection and diagnosis. Proteomic-based profiling uniquely allows delineation of global changes in expression patterns resulting from transcriptional and posttranscriptional control, posttranslational modifications, and shifts in proteins between cellular compartments. Approaches to that effect include direct serum protein profiling and comparative analysis of protein expression in normal, precancerous, and early-stage tumor tissues. Identification of panels of tumor antigens that elicit a humoral response also may contribute to the discovery of new markers for HCC screening and diagnosis. Today, 2-dimensional polyacrylamide gel electrophoresis, multidimensional liquid chromatography, mass spectrometry, and protein microarrays are among the proteomic tools available for biomarker and drug target discovery. We review these technologies and their application to the study of HCC. Our objective is to provide a framework for appreciating the promise, while at the same time understanding the challenges behind translating proteomics discovery into novel diagnostic tests.

The use of proteomics for the assessment of clinical samples in research

Proteomics, the analysis of expressed proteins, has been an important developing area of research for the past two decades [Anderson, NG, Anderson, NL. Twenty years of two-dimensional electrophoresis: past, present and future. Electrophoresis 1996;17:443-453]. Advances in technology have led to a rapid increase in applications to a wide range of samples; from initial experiments using cell lines, more complex tissues and biological fluids are now being assessed to establish changes in protein expression. A primary aim of clinical proteomics is the identification of biomarkers for diagnosis and therapeutic intervention of disease, by comparing the proteomic profiles of control and disease, and differing physiological states. This expansion into clinical samples has not been without difficulties owing to the complexity and dynamic range in plasma and human tissues including tissue biopsies. The most widely used techniques for analysis of clinical samples are surface-enhanced laser desorption/ionisation mass spectrometry (SELDI-MS) and 2-dimensional gel electrophoresis (2-DE) coupled to matrix-assisted laser desorption ionisation [Person, MD, Monks, TJ, Lau, SS. An integrated approach to identifying chemically induced posttranslational modifications using comparative MALDI-MS and targeted HPLC-ESI-MS/MS. Chem. Res. Toxicol. 2003;16:598-608]-mass spectroscopy (MALDI-MS). This review aims to summarise the findings of studies that have used proteomic research methods to analyse samples from clinical studies and to assess the impact that proteomic techniques have had in assessing clinical samples.

Fully automated online multi-dimensional protein profiling system for complex mixtures

For high throughput proteome analysis of highly complex protein mixtures, we have constructed a fully automated online system for multi-dimensional protein profiling, which utilizes a combination of two-dimensional liquid chromatography and tandem mass spectrometry (2D-LC-MS-MS), based on our well-established offline system described previously [K. Fujii, T. Nakano, T. Kawamura, F. Usui, Y. Bando, R. Wang, T. Nishimura, J. Proteome Res. 3 (2004) 712]. A two-valve switching system on a programmable auto sample injector is utilized for online two-dimensional chromatography with strong cation-exchange (SCX) and reversed-phase (RP) separations. The SCX separation is carried out during the equilibration of RP chromatography and the entire sequence of analysis was performed under fully automated conditions within 4 h, based on six SCX fractionations, and 40 min running time for the two-dimensional RP chromatography. In order to evaluate its performance in the detection and identification of proteins, digests of six standard proteins and yeast 20S proteasome have been analyzed and their results were compared to those obtained by the one-dimensional reversed-phase chromatography system (ID-LC-MS-MS). The 2D-LC-MS-MS system demonstrated that both the number of peptide fragments detected and the protein coverage had more than doubled. Furthermore, this multi-dimensional protein profiling system was also applied to the human 26S proteasome, which is one of the highly complex protein mixtures. Consequently, 723 peptide fragments were identified as 31 proteasome components, together with other coexisting proteins in the sample. The identification could be comprehensively performed with a 63% sequence coverage on an average, and additionally, with modifications at the N-terminus. These results indicated that the online 2D-LC-MS-MS system being described here is capable of analyzing highly complex protein mixtures in a high throughput manner, and that it would be applicable to dynamic proteomics.

Probity: a protein identification algorithm with accurate assignment of the statistical significance of the results

An algorithm for protein identification based on mass spectrometric proteolytic peptide mapping and genome database searching is presented. The algorithm ranks database proteins based on direct calculation of the probability of random matching and assigns the statistical significance to each result. We investigate the performance of the algorithm by simulation and show that the algorithm responds to random data in the desired manner and that the statistical significance computed indicates the risk that a particular identification result is false.

Affinity separation: divide and conquer the proteome

A major challenge in protein target discovery and validation is how to specifically dissect complex protein mixtures and measure trace targets. Immunoaffinity-based protein capture, separation and detection have proven to be one of the most effective approaches. Avian IgY antibody microbeads (Seppro™), representing a type of novel and specific protein sorbent, have several distinct advantages over IgG. Their utility and applications are compared with those of IgG and other affinity reagents.:

On the technicalities of discovering and applying protein biomarkers for cancer prevention

Primary prevention of cancer is one of the key approaches used to combat cancer. By identifying people at high risk of developing cancer, it becomes possible to develop intervention efforts on prevention rather than treatment. Prevention includes avoiding exposure to known cancer-causing agents, enhancement of host-defence mechanisms, modifying lifestyle and chemoprevention. The latter is the use of specific agents to suppress or reverse carcinogenesis and thereby prevent the development of cancers. Understanding primary molecular events in tumour development is therefore the key. The causes of cancer first produce reversible changes in the target cells, and a long interval is expected between cancer induction and the presentation of disease. Up to now, we had no reliable biomarkers to monitor these primary events, to select high-risk groups and individuals likely to get cancer, and to monitor preventive treatments or strategies to normalize these markers and prevent the individual from getting cancer. Recent developments in proteomic research, however, promise to deliver on these major needs. We here describe the technological armatorium of, and the recent advances in the field of protein biomarker discovery and discuss the future use of protein biomarkers for (1) reliable identification of high-risk groups; (2) clinical guidance of preventive strategies; and (3) elucidation of the mechanism of action for novel (natural product) prevention therapies and regimens.

SELDI-TOF-based serum proteomic pattern diagnostics for early detection of cancer

Proteomics is more than just generating lists of proteins that increase or decrease in expression as a cause or consequence of pathology. The goal should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. The nature of this information can be a cause, or a consequence, of disease and toxicity-based processes. Serum proteomic pattern diagnostics is a new type of proteomic platform in which patterns of proteomic signatures from high dimensional mass spectrometry data are used as a diagnostic classifier. This approach has recently shown tremendous promise in the detection of early-stage cancers. The biomarkers found by SELDI-TOF-based pattern recognition analysis are mostly low molecular weight fragments produced at the specific tumor microenvironment.

Serum diagnosis of pancreatic adenocarcinoma using surface-enhanced laser desorption and ionization mass spectrometry

PURPOSE

Each year in the United States, approximately 30,000 people die from pancreatic cancer. Fewer than 5% of patients survive >5 years after diagnosis, because most patients present with advanced disease. Early diagnosis may improve the prognosis of patients with pancreatic cancer.

EXPERIMENTAL DESIGN

In an attempt to improve on current approaches to the serological diagnosis of pancreatic cancer, we analyzed serum samples from patients with and without pancreatic cancer using surface-enhanced laser desorption and ionization (SELDI) protein chip mass spectrometry. Using a case-control study design, serum samples from 60 patients with resectable pancreatic adenocarcinoma were compared with samples from 60 age- and sex-matched patients with nonmalignant pancreatic diseases, as well as 60 age- and sex-matched healthy controls. To increase the number of proteins potentially identifiable, serum was fractionated using anion exchange and profiled on two ProteinChip surfaces (metal affinity capture and weak cation exchange).

RESULTS

We determined a minimum set of protein peaks able to discriminate between patient groups and used the unified maximum separability algorithm to compare the performance of the individual marker panels alone or in conjunction with CA19-9. Among the peaks identified by SELDI profiling that had the ability to distinguish between patient groups, the 2 most discriminating protein peaks could differentiate patients with pancreatic cancer from healthy controls with a sensitivity of 78% and specificity of 97%. These 2 markers performed significantly better than the current standard serum marker, CA19-9 (P < 0.05). The diagnostic accuracy of the 2 markers was improved by using them in combination with CA 19-9. Similarly, a combination of 3 SELDI markers and CA19-9 was superior to CA19-9 alone in distinguishing individuals with pancreatic cancer from the combined pancreatic disease controls and healthy subject groups (P = 0.078). SELDI markers were also better than CA19-9 in distinguishing patients with pancreatic cancer from those with pancreatitis.

CONCLUSION

SELDI profiling of serum can be used to accurately differentiate patients with pancreatic cancer from those with other pancreatic diseases and from healthy controls.

PROTEOMICS

The genome sequences of important model systems are available and the focus is now shifting to large-scale experiments enabled by this data. Following in the footsteps of genomics, we have functional genomics, proteomics, and even metabolomics, roughly paralleling the biological hierarchy of the transcription, translation, and production of small molecules. Proteomics is initially concerned with determining the structure, expression, localization, biochemical activity, interactions, and cellular roles of as many proteins as possible. There has been great progress owing to novel instrumentation, experimental strategies, and bioinformatics methods. The area of protein-protein interactions has been especially fruitful. First pass interaction maps of some model organisms exist, and the proteins in many important organelles are about to be determined. Researchers are also beginning to integrate large-scale data sets from various "omics" disciplines in targeted investigations of specific biomedical areas and in pursuit of a general framework for systems biology.

Systems biology, proteomics, and the future of health care: toward predictive, preventative, and personalized medicine

The emergence of systems biology is bringing forth a new set of challenges for advancing science and technology. Defining ways of studying biological systems on a global level, integrating large and disparate data types, and dealing with the infrastructural changes necessary to carry out systems biology, are just a few of the extraordinary tasks of this growing discipline. Despite these challenges, the impact of systems biology will be far-reaching, and significant progress has already been made. Moving forward, the issue of how to use systems biology to improve the health of individuals must be a priority. It is becoming increasingly apparent that the field of systems biology and one of its important disciplines, proteomics, will have a major role in creating a predictive, preventative, and personalized approach to medicine. In this review, we define systems biology, discuss the current capabilities of proteomics and highlight some of the necessary milestones for moving systems biology and proteomics into mainstream health care.

Clinical proteomics: revolutionizing disease detection and patient tailoring therapy

The evolving discipline of Clinical Proteomics is more than simply describing and enumerating the systematic changes in the protein constituency of a cell, or just generating lists of proteins that increase or decrease in expression as a cause or consequence of disease. Clinical applications of proteomics involve the use of proteomic technologies at the bedside with the ultimate goal to characterize the information flow through the intra- and extracellular molecular protein networks that interconnect organ and circulatory systems together. These networks are both new targets for therapeutics themselves as well as underpin the dynamic changes that give rise to cascades of new diagnostic biomarkers. The analysis of human cancer can be used as a model for how clinical proteomics is having an impact at the bedside for early detection, rational therapeutic targeting, and patient-tailored therapy.

Mass spectrometric quantitation of peptides and proteins using Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA)

A method (denoted SISCAPA) for quantitation of peptides in complex digests is described. In the method, anti-peptide antibodies immobilized on 100 nanoliter nanoaffinity columns are used to enrich specific peptides along with spiked stable-isotope-labeled internal standards of the same sequence. Upon elution from the anti-peptide antibody supports, electrospray mass spectrometry is used to quantitate the peptides (natural and labeled). In a series of pilot experiments, tryptic test peptides were chosen for four proteins of human plasma (hemopexin, alpha1 antichymotrypsin, interleukin-6, and tumor necrosis factor-alpha) from a pool of 10,203 in silico tryptic peptide candidates representing 237 known plasma components. Rabbit polyclonal antibodies raised against the chosen peptide sequences were affinity purified and covalently immobilized on POROS supports. Binding and elution from these supports was shown to provide an average 120-fold enrichment of the antigen peptide relative to others, as measured by selected ion monitoring (SIM) or selected reaction monitoring (SRM) electrospray mass spectrometry. The columns could be recycled with little loss in binding capacity, and generated peptide ion current measurements with cycle-to-cycle coefficients of variation near 5%. Anti-peptide antibody enrichment will contribute to increased sensitivity of MS-based assays, particularly for lower abundance proteins in plasma, and may ultimately allow substitution of a rapid bind/elute process for the time-consuming reverse phase separation now used as a prelude to online MS peptide assays. The method appears suitable for rapid generation of assays for defined proteins, and should find application in the validation of diagnostic protein panels in large sample sets.

Identification and proteomic profiling of exosomes in human urine

Urine provides an alternative to blood plasma as a potential source of disease biomarkers. One urinary biomarker already exploited in clinical studies is aquaporin-2. However, it remains a mystery how aquaporin-2 (an integral membrane protein) and other apical transporters are delivered to the urine. Here we address the hypothesis that these proteins reach the urine through the secretion of exosomes [membrane vesicles that originate as internal vesicles of multivesicular bodies (MVBs)]. Low-density urinary membrane vesicles from normal human subjects were isolated by differential centrifugation. ImmunoGold electron microscopy using antibodies directed to cytoplasmic or anticytoplasmic epitopes revealed that the vesicles are oriented "cytoplasmic-side inward," consistent with the unique orientation of exosomes. The vesicles were small (<100 nm), consistent with studies of MVBs and exosomes from other tissues. Proteomic analysis of urinary vesicles through nanospray liquid chromatography-tandem mass spectrometry identified numerous protein components of MVBs and of the endosomal pathway in general. Full liquid chromatography-tandem MS analysis revealed 295 proteins, including multiple protein products of genes already known to be responsible for renal and systemic diseases, including autosomal dominant polycystic kidney disease, Gitelman syndrome, Bartter syndrome, autosomal recessive syndrome of osteopetrosis with renal tubular acidosis, and familial renal hypomagnesemia. The results indicate that exosome isolation may provide an efficient first step in biomarker discovery in urine.

Cancer proteomics: Serum diagnostics for tumor marker discovery

Cancer proteomics is an exciting field that is witnessing many new developments in recent years. It is hoped that these advances will result in decreased cancer death rates, which have not declined dramatically in the last several decades. Some of the problems with current tumor markers include the lack of sensitivity and specificity, factors that prevent their use in population-based screening of disease. Thus, there is an urgent need to identify novel biomarkers that can faithfully detect the disease state. As we are now in the post-genome era, many opportunities have been created. Genomic sequence data are available for human, as well as several other species. We are now poised to mine these data and to determine the functions of the encoded proteins constituting the human genome. Proteomics affords this opportunity by providing enhanced procedures and tools for discovery and also a framework for understanding these components in terms of pathogenesis. New technologies and improvements in existing methodologies will allow for the rapid growth in the identification and characterization of peptides and proteins that are unique to various clinical states. This technology can be successfully applied to clinical specimens for the identification of new tumor markers.

Pathology of pulmonary hypertension

This article briefly discusses the traditional concepts of severe pulmonary hypertension and then details how the concept of severe pulmonary hypertension has moved from a vasoconstrictive to an angioproliferative disorder.

Proteomics in reproductive medicine: the technology for separation and identification of proteins

With the near completion of the human genome project, reproductive biology is poised to enter the vastly more complex arena of proteomics. Proteomics involves the identification, characterization and quantitation of all proteins present in a cell at a particular metabolic state. Although the number of genes in the human genome is estimated to be about 27,000 +/- 5000, the number of proteins produced by humans is unknown, with estimates ranging as high as 1,500,000 distinct molecular entities. In order to address problems in the early stages of reproduction, proteomics must be scaled down to work with very few numbers of cells, termed zeptoproteomics. Mass spectrometry has rapidly become the key technology in proteomics, enabling rapid and facile identification and quantitation of femtomole and attomole quantities of a protein.

Application of Peptide LC Retention Time Information in a Discriminant Function for Peptide Identification by Tandem Mass Spectrometry

We describe the application of a peptide retention time reversed phase liquid chromatography (RPLC) prediction model previously reported (Petritis et al. Anal. Chem. 2003, 75, 1039) for improved peptide identification. The model uses peptide sequence information to generate a theoretical (predicted) elution time that can be compared with the observed elution time. Using data from a set of known proteins, the retention time parameter was incorporated into a discriminant function for use with tandem mass spectrometry (MS/MS) data analyzed with the peptide/protein identification program SEQUEST. For singly charged ions, the number of confident identifications increased by 12% when the elution time metric is included compared to when mass spectral data is the sole source of information in the context of a Drosophila melanogaster database. A 3-4% improvement was obtained for doubly and triply charged ions for the same biological system. Application to the larger Rattus norvegicus (rat) and human proteome databases resulted in an 8-9% overall increase in the number of confident identifications, when both the discriminant function and elution time are used. The effect of adding "runner-up" hits (peptide matches that are not the highest scoring for a spectra) from SEQUEST is also explored, and we find that the number of confident identifications is further increased by 1% when these hits are also considered. Finally, application of the discriminant functions derived in this work with approximately 2.2 million spectra from over three hundred LC-MS/MS analyses of peptides from human plasma protein resulted in a 16% increase in confident peptide identifications (9022 vs 7779) using elution time information. Further improvements from the use of elution time information can be expected as both the experimental control of elution time reproducibility and the predictive capability are improved.