On-chip microextraction for proteomic sample preparation of in-gel digests

Despite the high sensitivity and relatively high tolerance for contaminants of matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) there is often a need to purify and concentrate the sample solution, especially after in-gel digestion of proteins separated by two-dimensional gel electrophoresis (2-DE). A silicon microextraction chip (SMEC) for sample clean-up and trace enrichment of peptides was manufactured and investigated. The microchip structure was used to trap reversed-phase chromatography media (POROS R2 beads) that facilitates sample purification/enrichment of contaminated and dilute samples prior to the MALDI-TOF MS analysis. The validity of the SMEC sample preparation technique was successfully investigated by performing analysis on a 10 nM peptide mixture containing 2 m urea in 0.1 m phosphate-buffered saline with MALDI-TOF MS. It is demonstrated that the microchip sample clean-up and enrichment of peptides can facilitate identification of proteins from 2-DE separations. The microchip structure was also used to trap beads immobilized with trypsin, thereby effectively becoming a microreactor for enzymatic digestion of proteins. This microreactor was used to generate a peptide map from a 100 nM bovine serum albumin sample.     

Selective enrichment of tryptophan-containing peptides from protein digests employing a reversible derivatization with malondialdehyde and solid-phase capture on hydrazide beads

A method for the selective enrichment of tryptophan-containing peptides from complex peptide mixtures such as protein digests is presented. It is based on the reversible reaction of tryptophan with malondialdehyde and trapping of the derivatized Trp-peptides on hydrazide beads via the free aldehyde group of the modified peptides. The peptides are subsequently recovered in their native form by specific cleavage reactions for further (mass spectrometric) analysis. The method was optimized and evaluated using a tryptic digest of a mixture of 10 model proteins, demonstrating a significant reduction in sample complexity while still allowing the identification of all proteins. The applicability of the tryptophan-specific enrichment procedure to complex biological samples is demonstrated for a total yeast cell lysate. Analysis of the processed fraction by 1D-LC-MS/MS confirms the specificity of the enrichment procedure, as more than 85% of the peptides recovered from the enrichment step contained tryptophan. The reduction in sample complexity also resulted in the identification of additional proteins in comparison to the untreated lysate.     

Enrichment and analysis of nonenzymatically glycated peptides: boronate affinity chromatography coupled with electron-transfer dissociation mass spectrometry

Nonenzymatic glycation of peptides and proteins by d-glucose has important implications in the pathogenesis of diabetes mellitus, particularly in the development of diabetic complications. However, no effective high-throughput methods exist for identifying proteins containing this low-abundance post-translational modification in bottom-up proteomic studies. In this report, phenylboronate affinity chromatography was used in a two-step enrichment scheme to selectively isolate first glycated proteins and then glycated, tryptic peptides from human serum glycated in vitro. Enriched peptides were subsequently analyzed by alternating electron-transfer dissociation (ETD) and collision induced dissociation (CID) tandem mass spectrometry. ETD fragmentation mode permitted identification of a significantly higher number of glycated peptides (87.6% of all identified peptides) versus CID mode (17.0% of all identified peptides), when utilizing enrichment on first the protein and then the peptide level. This study illustrates that phenylboronate affinity chromatography coupled with LC-MS/MS and using ETD as the fragmentation mode is an efficient approach for analysis of glycated proteins and may have broad application in studies of diabetes mellitus.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma

The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000-5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273-283, FIBA 5-16, and LBN 306-313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens.     

In silico analysis of accurate proteomics, complemented by selective isolation of peptides

Protein identification by mass spectrometry is mainly based on MS/MS spectra and the accuracy of molecular mass determination. However, the high complexity and dynamic ranges for any species of proteomic samples, surpass the separation capacity and detection power of the most advanced multidimensional liquid chromatographs and mass spectrometers. Only a tiny portion of signals is selected for MS/MS experiments and a still considerable number of them do not provide reliable peptide identification. In this article, an in silico analysis for a novel methodology of peptides and proteins identification is described. The approach is based on mass accuracy, isoelectric point (pI), retention time (t(R)) and N-terminal amino acid determination as protein identification criteria regardless of high quality MS/MS spectra. When the methodology was combined with the selective isolation methods, the number of unique peptides and identified proteins increases. Finally, to demonstrate the feasibility of the methodology, an OFFGEL-LC-MS/MS experiment was also implemented. We compared the more reliable peptide identified with MS/MS information, and peptide identified with three experimental features (pI, t(R), molecular mass). Also, two theoretical assumptions from MS/MS identification (selective isolation of peptides and N-terminal amino acid) were analyzed. Our results show that using the information provided by these features and selective isolation methods we could found the 93% of the high confidence protein identified by MS/MS with false-positive rate lower than 5%.     

Reference-facilitated phosphoproteomics: fast and reliable phosphopeptide validation by microLC-ESI-Q-TOF MS/MS

Recent advances in instrument control and enrichment procedures have enabled us to quantify large numbers of phosphoproteins and record site-specific phosphorylation events. An intriguing problem that has arisen with these advances is to accurately validate where phosphorylation events occur, if possible, in an automated manner. The problem is difficult because MS/MS spectra of phosphopeptides are generally more complicated than those of unmodified peptides. For large scale studies, the problem is even more evident because phosphorylation sites are based on single peptide identifications in contrast to protein identifications where at least two peptides from the same protein are required for identification. To address this problem we have developed an integrated strategy that increases the reliability and ease for phosphopeptide validation. We have developed an off-line titanium dioxide (TiO(2)) selective phosphopeptide enrichment procedure for crude cell lysates. Following enrichment, half of the phosphopeptide fractionated sample is enzymatically dephosphorylated, after which both samples are subjected to LC-MS/MS. From the resulting MS/MS analyses, the dephosphorylated peptide is used as a reference spectrum against the original phosphopeptide spectrum, in effect generating two peptide spectra for the same amino acid sequence, thereby enhancing the probability of a correct identification. The integrated procedure is summarized as follows: 1) enrichment for phosphopeptides by TiO(2) chromatography, 2) dephosphorylation of half the sample, 3) LC-MS/MS-based analysis of phosphopeptides and corresponding dephosphorylated peptides, 4) comparison of peptide elution profiles before and after dephosphorylation to confirm phosphorylation, and 5) comparison of MS/MS spectra before and after dephosphorylation to validate the phosphopeptide and its phosphorylation site. This phosphopeptide identification represents a major improvement as compared with identifications based only on single MS/MS spectra and probability-based database searches. We investigated an applicability of this method to crude cell lysates and demonstrate its application on the large scale analysis of phosphorylation sites in differentiating mouse myoblast cells.     

Statistical identification of differentially labeled peptides from liquid chromatography tandem mass spectrometry

LC-MS/MS with certain labeling techniques such as isotope-coded affinity tag (ICAT) enables quantitative analysis of paired protein samples. However, current identification and quantification of differentially expressed peptides (and proteins) are not reliable for large proteomics screening of complex biological samples. The number of replicates is often limited because of the high cost of experiments and the limited supply of samples. Traditionally, a simple fold change cutoff is used, which results in a high rate of false positives. Standard statistical methods such as the two-sample t-test are unreliable and severely underpowered due to high variability in LC-MS/MS data, especially when only a small number of replicates are available. Using an advanced error pooling technique, we propose a novel statistical method that can reliably identify differentially expressed proteins while maintaining a high sensitivity, particularly with a small number of replicates. The proposed method was applied both to an extensive simulation study and a proteomics comparison between microparticles (MPs) generated from platelet (platelet MPs) and MPs isolated from plasma (plasma MPs). In these studies, we show a significant improvement of our statistical analysis in the identification of proteins that are differentially expressed but not detected by other statistical methods. In particular, several important proteins - two peptides for beta-globin and three peptides for von Willebrand Factor (vWF) - were identified with very small false discovery rates (FDRs) by our method, while none was significant when other conventional methods were used. These proteins have been reported with their important roles in microparticles in human blood cells: vWF is a platelet and endothelial cell product that binds to P-selectin, GP1b, and GP IIb/IIIa, and beta-globin is one of the peptides of hemoglobin involved in the transportation of oxygen by red blood cells.     

Comparison of methods to examine the endogenous peptides of fetal calf serum

There is a great desire to relate the patterns of endogenous peptides in blood to human disease and drug response. The best practices for the preparation of blood fluids for analysis are not clear and also relatively few of the peptides in blood have been identified by tandem mass spectrometry. We compared a number of sample preparation methods to extract endogenous peptides including C18 reversed phase, precipitation, and ultrafiltration. We examined the results of these sample preparation methods by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and liquid chromatography-tandem mass spectrometry (MS/MS) using MALDI-TOF/TOF and electrospray ionization-ion trap. Peptides from solid-phase extraction with C18 in the range of hundreds of femtomoles per spot were detected from the equivalent of 1 μL of serum by MALDI-TOF. We observed endogenous serum peptides from fibrinogen α- and β-chain, complement C3, α-2-HS-glycoprotein, albumin, serine (or cysteine) proteinase inhibitor, factor VIII, plasminogen, immunoglobulin, and other abundant blood proteins. However, we also recorded significant MS/MS spectra from tumor necrosis factor-α-, major histocompatibility complex-, and angiotensin-related peptides, as well as peptides from collagens and other low-abundance proteins. Amino acid substitutions were detected and a phosphorylated peptide was also observed. This is the first time the endogenous peptides of fetal serum have been examined by MS and where peptides from low-abundance proteins, phosphopeptides, and amino acid substitutions were detected.     

Enrichment of low molecular weight fraction of serum for MS analysis of peptides associated with hepatocellular carcinoma

A challenging aspect of biomarker discovery in serum is the interference of abundant proteins with identification of disease-related proteins and peptides. This study describes enrichment of serum by denaturing ultrafiltration, which enables an efficient profiling and identification of peptides up to 5 kDa. We consistently detect several hundred peptide-peaks in MALDI-TOF and SELDI-TOF spectra of enriched serum. The sample preparation is fast and reproducible with an average CV for all 276 peaks in the MALDI-TOF spectrum of 11%. Compared to unenriched serum, the number of peaks in enriched spectra is 4 times higher at an S/N ratio of 5 and 20 times higher at an S/N ratio of 10. To demonstrate utility of the methods, we compared 20 enriched sera of patients with hepatocellular carcinoma (HCC) and 20 age-matched controls using MALDI-TOF. The comparison of 332 peaks at p < 0.001 identified 45 differentially abundant peaks that classified HCC with 90% accuracy in this small pilot study. Direct TOF/TOF sequencing of the most abundant peptide matches with high probability des-Ala-fibrinopeptide A. This study shows that enrichment of the low molecular weight fraction of serum facilitates an efficient discovery of peptides that could serve as biomarkers for detection of HCC as well as other diseases.     

The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments

Background  

Isotope-coded affinity tags (ICAT) is a method for quantitative proteomics based on differential isotopic labeling, sample digestion and mass spectrometry (MS). The method allows the identification and relative quantification of proteins present in two samples and consists of the following phases. First, cysteine residues are either labeled using the ICAT Light or ICAT Heavy reagent (having identical chemical properties but different masses). Then, after whole sample digestion, the labeled peptides are captured selectively using the biotin tag contained in both ICAT reagents. Finally, the simplified peptide mixture is analyzed by nanoscale liquid chromatography-tandem mass spectrometry (LC-MS/MS). Nevertheless, the ICAT LC-MS/MS method still suffers from insufficient sample-to-sample reproducibility on peptide identification. In particular, the number and the type of peptides identified in different experiments can vary considerably and, thus, the statistical (comparative) analysis of sample sets is very challenging. Low information overlap at the peptide and, consequently, at the protein level, is very detrimental in situations where the number of samples to be analyzed is high.     

Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.     

Evaluation of prefractionation methods as a preparatory step for multidimensional based chromatography of serum proteins

Prefractionations of proteins prior to their proteolysis, chromatography, and MS/MS analyses help reduce complexity and increase the yield of protein identifications. A number of methods were evaluated here for prefractionating serum samples distributed to the participating laboratories as part of the human Plasma Proteome Project. These methods include strong cation exchange (SCX) chromatography, slicing of SDS-PAGE gel bands, and liquid-phase IEF of the proteins. The fractionated proteins were trypsinized and the resulting peptides were resolved and analyzed by multidimensional protein identification technology coupled to IT MS/MS. The MS/MS spectra were clustered, combined, and searched against the IPI protein databank using Pep-Miner. The identification results were evaluated for the efficacy of the different prefractionation methodologies to identify larger numbers of proteins at higher confidence and to achieve the best coverage of the proteins with the identified peptides. Prefractionation based on SCX resulted in the largest number of identified proteins, followed by gel slices and then the liquid-phase IEF. An important observation was that each of the methods revealed a set of unique proteins, some identified with high confidence. Therefore, for comprehensive identification of the serum proteins, several different prefractionation approaches should be used in parallel.     

Immunoaffinity enrichments followed by mass spectrometric detection for studying global protein tyrosine phosphorylation

Phosphorylation of protein tyrosine residues regulates important cell functions and is, when dysregulated, often crucially involved in oncogenesis. It is therefore important to develop and evaluate methods for identifying and studying tyrosine phosphorylated (P-Tyr) proteins. P-Tyr proteins are present at very low concentrations within cells, requiring highly selective enrichment methods to be detected. In this study, we applied immunoaffinity as enrichment step for P-Tyr proteins. Five selected anti-phosphotyrosine antibodies (monoclonal antibodies 4G10, PY100, PYKD1, 13F9 and one polyclonal antiserum) were evaluated with respect to their capability to enrich P-Tyr proteins from cell extracts of the K562 leukemia cell line. The enrichment resulted in the detection of a group of proteins that potentially were tyrosine-phosphorylated (putative P-Tyr proteins). High accuracy identification of actual P-Tyr sites were performed using a highly selective and sensitive liquid chromatography Fourier transform mass spectrometer (LC-FTMS) setup with complementary collision activated dissociation (CAD) and electron capture dissociation (ECD) fragmentations. 4G10 and PY100 antibodies recognized the greatest number of putative P-Tyr proteins in initial screening experiments and were therefore further evaluated and compared in immunoaffinity enrichment of both P-Tyr proteins and peptides. Using the 4G10 antibody for enrichment of proteins, we identified 459 putative P-Tyr proteins by MS. Out of these proteins, 12 were directly verified as P-Tyr proteins by MS analysis of the actual site. Using the PY100 antibody for enrichment of peptides, we detected 67 P-Tyr peptides (sites) and 89 putative P-Tyr proteins. Generally, enrichment at the peptide level made it difficult to reliably determine the identity of the proteins. In contrast, protein identification following immunoaffinity enrichment at the protein level gave greater sequence coverage and thus a higher confidence in the protein identification. By combining all available information, 40 proteins were identified as true P-Tyr proteins from the K562 cell line. In conclusion, this study showed that a combination of immunoaffinity enrichment using multiple antibodies of both intact and digested proteins in parallel experiments is required for best possible coverage of all possible P-Tyr proteins in a sample.     

A protein processing filter method for bacterial identification by mass spectrometry-based proteomics

A "one-pot" alternative method for processing proteins and isolating peptide mixtures from bacterial samples is presented for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and data reduction. The conventional in-solution digestion of the protein contents of bacteria is compared to a small disposable filter unit placed inside a centrifuge vial for processing and digestion of bacterial proteins. Each processing stage allows filtration of excess reactants and unwanted byproduct while retaining the proteins. Upon addition of trypsin, the peptide mixture solution is passed through the filter while retaining the trypsin enzyme. The peptide mixture is then analyzed by LC-MS/MS with an in-house BACid algorithm for a comparison of the experimental unique peptides to a constructed proteome database of bacterial genus, specie, and strain entries. The concentration of bacteria was varied from 10 × 10(7) to 3.3 × 10(3) cfu/mL for analysis of the effect of concentration on the ability of the sample processing, LC-MS/MS, and data analysis methods to identify bacteria. The protein processing method and dilution procedure result in reliable identification of pure suspensions and mixtures at high and low bacterial concentrations.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

Technical evaluation of MALDI-TOF mass spectrometry for quantitative proteomic profiling matrix formulation and application

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has been recently used to identify disease markers by directly profiling and quantifying the peptide/proteins in biological samples under different physiological or experimental conditions. The information of reproducibility of such quantitative profiling method has not been available. It is important to evaluate and reduce error from technical variation. In this study, an unbiased signal acquisition strategy was used to evaluate the effects of three sample-matrix spotting methods and two matrix chemicals, α-cyano-4-hydroxycinnamic acid (CHCA) and sinapinic acid, on the reproducibility of the peptide/protein signal intensities. The sandwich spotting method using 0.1% nitrocellulose coating film and CHCA gave the best quantitative results for the standard peptides and proteins with mass<66.5 kDa. The normalized signal intensities of the standard peptides and proteins were directly proportional to their concentrations with intra-assay (within-day) coefficient of variations (CVs) ranging from 6.5% to 17%. When analyzing serum peptides <6000 m/z, the interassay (between-days) CVs of all the evaluated peptide peaks were <15%. These data indicate that with the right MS analysis conditions, MALDI-TOF MS appears to be a feasible tool for directly profiling and quantifying the peptide/ proteins in biological samples.     

Quantitative analysis of modified proteins by LC-MS/MS of peptides labeled with phenyl isocyanate

Stable isotope tagging methods have enabled relative quantitation of proteins between samples in LC-MS/MS analyses. However, most such methods are not applicable to the differential quantitation of modified proteins because the isotope tagging reagents only react with certain peptides or because the reagents incorporate a mass increment that is too small to allow reliable quantitation on low resolution ion trap MS instruments. Here, we describe the use of d0- and d5-phenyl isocyanate (PIC) as N-terminal reactive tags for essentially all peptides in proteolytic digests. PIC reacts quantitatively with peptide N-terminal amines within minutes at neutral pH and the PIC-labeled peptides undergo informative MS/MS fragmentation. Ratios of d0- and d5-PIC-labeled derivatives of several model peptides were linear across a 10000-fold range of peptide concentration ratios, thus indicating a wide dynamic range for quantitation. Application of PIC labeling enabled relative quantitation of several styrene oxide adducts of human hemoglobin in LC-MS/MS analyses. PIC labeling offers a versatile means of quantifying changes in modified or variant protein forms in paired samples.     

Proteomic analysis of maternal serum in down syndrome: identification of novel protein biomarkers

Down syndrome (DS) is the most prevalent chromosomal disorder, accounting for significant morbidity and mortality. Definitive diagnosis requires invasive amniocentesis, and current maternal serum-based testing requires a false-positive rate of about 5% to detect 85% of affected pregnancies. We have performed a comprehensive proteomic analysis to identify potential serum biomarkers to detect DS. First- and second-trimester maternal serum samples of DS and gestational age-matched controls were analyzed using multiple, complementary proteomic approaches, including fluorescence 2-dimensional gel electrophoresis (2D-DIGE), 2-dimensional liquid chromatography-chromatofocusing (2D-CF), multidimensional protein identification technology (MudPIT; LC/LC-MS/MS), and MALDI-TOF-MS peptide profiling. In total, 28 and 26 proteins were differentially present in first- and second-trimester samples, respectively. Of these, 19 were specific for the first trimester and 16 for the second trimester, and 10 were differentially present in both trimesters. Analysis of MALDI-TOF-MS peptide profiles with pattern-recognition software also discriminated between DS and controls in both trimesters, with an average recognition capability approaching 96%. A majority of the biomarkers identified are serum glycoproteins that may play a role in cellular differentiation and growth of fetus. Further characterization and quantification of these markers in a larger cohort of subjects may provide the basis for new tests for improved DS screening.     

Characterization of the low molecular weight human serum proteome

Serum potentially carries an archive of important histological information whose determination could serve to improve early disease detection. The analysis of serum, however, is analytically challenging due to the high dynamic concentration range of constituent protein/peptide species, necessitating extensive fractionation prior to mass spectrometric analyses. The low molecular weight (LMW) serum proteome is that protein/peptide fraction from which high molecular weight proteins, such as albumin, immunoglobulins, transferrin, and lipoproteins, have been removed. This LMW fraction is made up of several classes of physiologically important proteins such as cytokines, chemokines, peptide hormones, as well as proteolytic fragments of larger proteins. Centrifugal ultrafiltration of serum was used to remove the large constituent proteins resulting in the enrichment of the LMW proteins/peptides. Because albumin is known to bind and transport small molecules and peptides within the circulatory system, the centrifugal ultrafiltration was conducted under solvent conditions effecting the disruption of protein-protein interactions. The LMW serum proteome sample was digested with trypsin, fractionated by strong cation exchange chromatography, and analyzed by microcapillary reversed-phase liquid chromatography coupled on-line with electrospray ionization tandem mass spectrometry. Analysis of the tandem mass spectra resulted in the identification of over 340 human serum proteins; however, not a single peptide from serum albumin was observed. The large number of proteins identified demonstrates the efficacy of this method for the removal of large abundant proteins and the enrichment of the LMW serum proteome.