Added value for tandem mass spectrometry shotgun proteomics data validation through isoelectric focusing of peptides

A very popular approach in proteomics is the so-called "shotgun LC-MS/MS" strategy. In its mostly used form, a total protein digest is separated by ion exchange fractionation in the first dimension followed by off- or on-line RP LC-MS/MS. We replaced the first dimension by isoelectric focusing in the liquid phase using the Off-Gel device producing 15 fractions. As peptides are separated by their isoelectric point in the first dimension and hydrophobicity in the second, those experimentally derived parameters (pI and R(T)) can be used for the validation of potentially identified peptides. We applied this strategy to a cellular extract of Drosophila Kc167 cells and identified peptides with two different database search engines, namely PHENYX and SEQUEST, with PeptideProphet validation of the SEQUEST results. PHENYX returned 7582 potential peptide identifications and SEQUEST 7629. The SEQUEST results were reduced to 2006 identifications by validation with PeptideProphet. Validation of the PeptideProphet, SEQUEST and PHENYX results by pI and R(T) parameters confirmed 1837 PeptideProphet identifications while in the remainder of the SEQUEST results another 1130 peptides were found to be likely hits. The validation on PHENYX resulted in the fixation of a solid p-value threshold of <1 x 10(-04) that sets by itself the correct identification confidence to >95%, and a final count of 2034 highly confident peptide identifications was achieved after pI and R(T) validation. Although the PeptideProphet and PHENYX datasets have a very high confidence the overlap of common identifications was only at 79.4%, to be explained by the fact that data interpretation was done searching different protein databases with two search engines of different algorithms. The approach used in this study allowed for an automated and improved data validation process for shotgun proteomics projects producing MS/MS peptide identification results of very high confidence.     

Evaluation of strong cation exchange versus isoelectric focusing of peptides for multidimensional liquid chromatography-tandem mass spectrometry

Shotgun proteome analysis platforms based on multidimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a powerful means to discover biomarker candidates in tissue specimens. Analysis platforms must balance sensitivity for peptide detection, reproducibility of detected peptide inventories and analytical throughput for protein amounts commonly present in tissue biospecimens (< 100 microg), such that platform stability is sufficient to detect modest changes in complex proteomes. We compared shotgun proteomics platforms by analyzing tryptic digests of whole cell and tissue proteomes using strong cation exchange (SCX) and isoelectric focusing (IEF) separations of peptides prior to LC-MS/MS analysis on a LTQ-Orbitrap hybrid instrument. IEF separations provided superior reproducibility and resolution for peptide fractionation from samples corresponding to both large (100 microg) and small (10 microg) protein inputs. SCX generated more peptide and protein identifications than did IEF with small (10 microg) samples, whereas the two platforms yielded similar numbers of identifications with large (100 microg) samples. In nine replicate analyses of tryptic peptides from 50 microg colon adenocarcinoma protein, overlap in protein detection by the two platforms was 77% of all proteins detected by both methods combined. IEF more quickly approached maximal detection, with 90% of IEF-detectable medium abundance proteins (those detected with a total of 3-4 peptides) detected within three replicate analyses. In contrast, the SCX platform required six replicates to detect 90% of SCX-detectable medium abundance proteins. High reproducibility and efficient resolution of IEF peptide separations make the IEF platform superior to the SCX platform for biomarker discovery via shotgun proteomic analyses of tissue specimens.     

The synaptic vesicle proteome: a comparative study in membrane protein identification

A proteomic analysis of the synaptic vesicle was undertaken to obtain a better understanding of vesicle regulation. Synaptic vesicles primarily consist of integral membrane proteins that are not well resolved on traditional isoelectric focusing/two-dimensional gel electrophoresis (IEF/2-DE) gels and are resistant to in-gel digestion with trypsin thereby reducing the number of peptides available for mass spectrometric analysis. To address these limitations, two complementary 2-DE methods were investigated in the proteome analysis: (a) IEF/sodium dodecyl sulfate-polyacrylamide gel electrophoresis (IEF/SDS-PAGE) for resolution of soluble proteins and, (b) Benzyl hexadecyl ammonium chloride/SDS-PAGE (16-BAC/SDS-PAGE) for resolution of integral membrane proteins. The IEF/SDS-PAGE method provided superior resolution of soluble proteins, but could only resolve membrane proteins with a single transmembrane domain. The 16-BAC/SDS-PAGE method improved separation, resolution and identification of integral membrane proteins with up to 12 transmembrane domains. Trypsin digestion of the integral membrane proteins was poor and fewer peptides were identified from these proteins. Analysis of both the peptide mass fingerprint and the tandem mass spectra using electrospray ionization quadrupole-time of flight mass spectrometry led to the positive identification of integral membrane proteins. Using both 2-DE separation methods, a total of 36 proteins were identified including seven integral membrane proteins, 17 vesicle regulatory proteins and four proteins whose function in vesicles is not yet known.     

Characterization of the rat liver membrane proteome using peptide immobilized pH gradient isoelectric focusing

Membrane proteins are of particular interest in proteomics because of their potential therapeutic utility. Past proteomic approaches used to investigate membrane proteins have only been partially successful at providing a comprehensive analysis due to the inherently hydrophobic nature and low abundance for some of these proteins. Recently, these difficulties have been improved by analyzing membrane protein enriched samples using shotgun proteomics. In addition, the recent application of methanol-assisted trypsin digestion of membrane proteins has been shown to be a method to improve membrane protein identifications. In this study, a comparison of different concentrations of methanol was assessed for assisting membrane protein digestion with trypsin prior to analysis using a gel-based shotgun proteomics approach called peptide immobilized pH gradient isoelectric focusing (IPG-IEF). We demonstrate the use of peptide IEF on pH 3-10 IPG strips as the first dimension of two-dimensional shotgun proteomics for protein identifications from the membrane fraction of rat liver. Tryptic digestion of proteins was carried out in varying concentrations of methanol in 10 mM ammonium bicarbonate: 0% (v/v), 40% (v/v), and 60% (v/v). A total of 800 proteins were identified from 60% (v/v) methanol, which increased the protein identifications by 17% and 14% compared to 0% (v/v) methanol and 40% (v/v) methanol assisted digestion, respectively. In total, 1549 nonredundant proteins were identified from all three concentrations of methanol including 690 (42%) integral membrane proteins of which 626 of these proteins contained at least one transmembrane domain. Peptide IPG-IEF separation of peptides was successful as the peptides were separated into discrete pI regions with high resolution. The results from this study prove utility of 60% (v/v) methanol assisted digestion in conjunction with peptide IPG-IEF as an optimal shotgun proteomics technique for the separation and identification of previously unreported membrane proteins.     

Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification

Here we present the theoretical and experimental evaluation of peptide isoelectric point as a method to aid in the identification of peptides from complex mixtures. Predicted pI values were found to match closely the experimentally obtained data, resulting in the development of a unique filter that lowers the effective false positive rate for peptide identification. Due to the reduction of the false positive rate, the cross-correlation parameters Xcorr and deltaCn from the SEQUEST program can be lowered resulting in 25% more peptide identifications. This approach was successfully applied to analysis of the soluble fraction of the E. coli proteome, where 417 proteins were identified from 1022 peptides using just 20 microg of material.     

Effect of 2MEGA labeling on membrane proteome analysis using LC-ESI QTOF MS

One of the challenges associated with large-scale proteome analysis using tandem mass spectrometry (MS/MS) and automated database searching is to reduce the number of false positive identifications without sacrificing the number of true positives found. In this work, a systematic investigation of the effect of 2MEGA labeling (N-terminal dimethylation after lysine guanidination) on the proteome analysis of a membrane fraction of an Escherichia coli cell extract by 2-dimensional liquid chromatography MS/MS is presented. By a large-scale comparison of MS/MS spectra of native peptides with those from the 2MEGA-labeled peptides, the labeled peptides were found to undergo facile fragmentation with enhanced a1 or a1-related (a(1)-17 and a(1)-45) ions derived from all N-terminal amino acids in the MS/MS spectra; these ions are usually difficult to detect in the MS/MS spectra of nonderivatized peptides. The 2MEGA labeling alleviated the biased detection of arginine-terminated peptides that is often observed in MALDI and ESI MS experiments. 2MEGA labeling was found not only to increase the number of peptides and proteins identified but also to generate enhanced a1 or a1-related ions as a constraint to reduce the number of false positive identifications. In total, 640 proteins were identified from the E. coli membrane fraction, with each protein identified based on peptide mass and sequence match of one or more peptides using MASCOT database search algorithm from the MS/MS spectra generated by a quadrupole time-of-flight mass spectrometer. Among them, the subcellular locations of 336 proteins are presently known, including 258 membrane and membrane-associated proteins (76.8%). Among the classified proteins, there was a dramatic increase in the total number of integral membrane proteins identified in the 2MEGA-labeled sample (153 proteins) versus the unlabeled sample (77 proteins).     

A comparison of immobilized pH gradient isoelectric focusing and strong-cation-exchange chromatography as a first dimension in shotgun proteomics

Recently, we have developed a high-resolution two-dimensional separation strategy for the analysis of complex peptide mixtures. This methodology employs isoelectric focusing of peptides on immobilized pH gradient (IPG) gels in the first dimension, followed by reversed-phase chromatography in the second dimension, and subsequent tandem mass spectrometry analysis. The traditional approach to this mixture problem employs strong-cation-exchange (SCX) chromatography in the first dimension. Here, we present a direct comparison of these two first-dimensional techniques using complex protein samples derived from the testis of Rattus norvegicus. It was found that the use of immobilized pH gradients (narrow range pH 3.5-4.5) for peptide separation in the first dimension yielded 13% more protein identifications than the optimized off-line SCX approach (employing the entire pI range of the sample). In addition, the IPG technique allows for a much more efficient use on mass spectrometer analysis time. Separation of a tryptic digest derived from a rat testis sample on a narrow range pH gradient (over the 3.5-4.5 pH range) yielded 7626 and 2750 peptides and proteins, respectively. Peptide and protein identification was performed with high confidence using SEQUEST in combination with a data filtering program employing pI and statistical based functions to remove false-positives from the data.     

Evaluation on the effect of different in-gel peptide isoelectric focusing parameters in global proteomic profiling

Peptide isoelectric focusing (IEF) is a common technique used in two-dimensional liquid chromatography tandem mass spectrometry (2D–LC–MS/MS) proteomic workflow, in which the tryptic peptide is first pre-fractionated based on pI values before being subjected to reverse phase LC–MS analysis. Although this method has been widely used by many research groups, a systemic study on the optimal conditions and fundamental parameters influencing the experimental outcomes has been lacking, including the effect of peptide extraction methods, the extent of pre-fractionation, and the choice of pH range. In this study, we compared the effect of different parameters on the numbers of peptides and proteins identified using two complex mouse proteomes. The results indicated that extraction of peptides from immobilized pH gradient (IPG) strips by sequential elution of increasingly organic solvents provided the highest number of peptide identification. In addition, we showed that approximately 45 more unique proteins were identified for every additional fraction collected during peptide IEF. Although narrow pH ranges provided higher resolution in peptide separation as expected, different pH ranges yielded similar numbers of peptide and protein identification. Overall, we demonstrated that the extraction solvent influenced the numbers of peptide and protein identification and quantitatively demonstrated the advantage of extensive fractionation and the performance of different pH ranges in practice.     

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.     

Trade-off between high sensitivity and increased potential for false positive peptide sequence matches using a two-dimensional linear ion trap for tandem mass spectrometry-based proteomics

Two-dimensional linear ion trap mass spectrometers are rapidly becoming the new workhorse instruments for shotgun proteomic analysis of complex peptide mixtures. The objective of this study was to compare the potential for false positive peptide sequence matches between a two-dimensional ion trap instrument and a traditional, three-dimensional ion trap instrument. Through the comparative analysis of a complex protein sample, we found that in order to minimize false positive sequence matches, sequence match scoring criteria must be more stringent for data from the two-dimensional ion trap compared to the three-dimensional ion trap data. Given this increased potential for false positives, we also investigated two potential filtering strategies to reduce the false positive matches for data derived from the two-dimensional ion trap, including trypsin enzyme cleavage filtering, and the addition of peptide physicochemical information as a constraint, specifically peptide isoelectric point. The results described here provide a cautionary tale to researchers, demonstrating the need for careful analysis of MS/MS data from this new class of ion trap instruments, as well as the effectiveness of trypsin enzyme cleavage filtering and peptide pI information in maximizing high confidence protein identifications from this powerful proteomic instrumentation.     

A hierarchical statistical model to assess the confidence of peptides and proteins inferred from tandem mass spectrometry

MOTIVATION: Statistical evaluation of the confidence of peptide and protein identifications made by tandem mass spectrometry is a critical component for appropriately interpreting the experimental data and conducting downstream analysis. Although many approaches have been developed to assign confidence measure from different perspectives, a unified statistical framework that integrates the uncertainty of peptides and proteins is still missing. RESULTS: We developed a hierarchical statistical model (HSM) that jointly models the uncertainty of the identified peptides and proteins and can be applied to any scoring system. With data sets of a standard mixture and the yeast proteome, we demonstrate that the HSM offers a reliable or at least conservative false discovery rate (FDR) estimate for peptide and protein identifications. The probability measure of HSM also offers a powerful discriminating score for peptide identification. AVAILABILITY: The algorithm is available upon request from the authors.     

High confidence and sensitivity four-dimensional fractionation for human plasma proteome analysis

Reducing the complexity of plasma proteome through complex multidimensional fractionation protocols is critical for the detection of low abundance proteins that have the potential to be the most specific disease biomarkers. Therefore, we examined a four dimension profiling method, which includes low abundance protein enrichment, tryptic digestion and peptide fractionation by IEF, SCX and RP-LC. The application of peptide pI filtering as an additional criterion for the validation of the identifications allows to minimize the false discovery rate and to optimize the best settings of the protein identification database search engine. This sequential approach allows for the identification of low abundance proteins, such as angiogenin (10^?9 g/L), pigment epithelium growth factor (10^?8 g/L), hepatocyte growth factor activator (10^?7 g/L) and thrombospondin-1 (10^?6 g/L), having concentrations similar to those of many other growth factors and cytokines involved in disease pathophysiology.     

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.     

Analysis of human serum proteins by liquid phase isoelectric focusing and matrix-assisted laser desorption/ionization-mass spectrometry

Direct matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) analysis of human serum yielded ion signals from only a fraction of the total number of peptides and proteins expected to be in the sample. We increased the number of peptide and protein ion signals observed in the MALDI-TOF mass spectra analysis of human serum by using a prefractionation protocol based on liquid phase isoelectric focusing electrophoresis. This pre-fractionation technique facilitated the MALDI-TOF MS detection of as many as 262 different peptide and protein ion signals from human serum. The results obtained from three replicate fractionation experiments on the same serum sample indicated that 148 different peptide and protein ion signals were reproducibly detected using our isoelectric focusing and MALDI-TOF MS protocol.     

DETECTION AND DEMONSTRATION OF INHIBITORY ACTIVITIES OF BACTERIOCINS BY ISOELECTRIC FOCUSING

A technique utilizing isoelectric focusing (IEF) was developed and compared with a modified Bhunia's sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) method for directly detecting antimicrobial activities of inhibitory peptides or proteins (bacteriocins). In IEF, the gel containing separated peptide or protein bands was directly overlaid with indicator bacteria without any fixation or rinsing as done in the SDS-PAGE method. The IEF gave clear zones of inhibition surrounding inhibitory bands. Bhunia's method was modified to reduce the time for fixation and rinsing, and a 15-min fixation followed by 2-h rinsing with dd H₂O was determined to be necessary for a detection similar to the IEF. In addition, results of this study showed that denaturation of bacteriocins and, subsequently, failure to detect the presence of a bacteriocin could occur in the SDS-PAGE analysis while little denaturation was observed in the IEF assay. Therefore, the IEF assay developed in this study was more rapid and less destructive as compared with the SDS-PAGE method.     

A predictive model for identifying proteins by a single peptide match

MOTIVATION: Tandem mass-spectrometry of trypsin digests, followed by database searching, is one of the most popular approaches in high-throughput proteomics studies. Peptides are considered identified if they pass certain scoring thresholds. To avoid false positive protein identification, > or = 2 unique peptides identified within a single protein are generally recommended. Still, in a typical high-throughput experiment, hundreds of proteins are identified only by a single peptide. We introduce here a method for distinguishing between true and false identifications among single-hit proteins. The approach is based on randomized database searching and usage of logistic regression models with cross-validation. This approach is implemented to analyze three bacterial samples enabling recovery 68-98% of the correct single-hit proteins with an error rate of < 2%. This results in a 22-65% increase in number of identified proteins. Identifying true single-hit proteins will lead to discovering many crucial regulators, biomarkers and other low abundance proteins. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Optimized peptide separation and identification for mass spectrometry based proteomics via free-flow electrophoresis

Multidimensional LC-MS based shotgun proteomics experiments at the peptide level have traditionally been carried out by ion exchange in the first dimension and reversed-phase liquid chromatography in the second. Recently, it has been shown that isoelectric focusing (IEF) is an interesting alternative approach to ion exchange separation of peptides in the first dimension. Here we present an improved protocol for peptide separation by continuous free-flow electrophoresis (FFE) as the first dimension in a two-dimensional peptide separation work flow. By the use of a flat pI gradient and a mannitol and urea based separation media we were able to perform high-throughput proteome analysis with improved interfacing between FFE and RPLC-MS/MS. The developed protocol was applied to a cytosolic fraction from Schneider S2 cells from Drosophila melanogaster, resulting in the identification of more than 10,000 unique peptides with high probability. To improve the accuracy of the peptide identification following FFE-IEF we incorporated the pI information as an additional parameter into a statistical model for discrimination between correct and incorrect peptide assignments to MS/MS spectra.     

Integrated approach for manual evaluation of peptides identified by searching protein sequence databases with tandem mass spectra

Quantitative proteomics relies on accurate protein identification, which often is carried out by automated searching of a sequence database with tandem mass spectra of peptides. When these spectra contain limited information, automated searches may lead to incorrect peptide identifications. It is therefore necessary to validate the identifications by careful manual inspection of the mass spectra. Not only is this task time-consuming, but the reliability of the validation varies with the experience of the analyst. Here, we report a systematic approach to evaluating peptide identifications made by automated search algorithms. The method is based on the principle that the candidate peptide sequence should adequately explain the observed fragment ions. Also, the mass errors of neighboring fragments should be similar. To evaluate our method, we studied tandem mass spectra obtained from tryptic digests of E. coli and HeLa cells. Candidate peptides were identified with the automated search engine Mascot and subjected to the manual validation method. The method found correct peptide identifications that were given low Mascot scores (e.g., 20-25) and incorrect peptide identifications that were given high Mascot scores (e.g., 40-50). The method comprehensively detected false results from searches designed to produce incorrect identifications. Comparison of the tandem mass spectra of synthetic candidate peptides to the spectra obtained from the complex peptide mixtures confirmed the accuracy of the evaluation method. Thus, the evaluation approach described here could help boost the accuracy of protein identification, increase number of peptides identified, and provide a step toward developing a more accurate next-generation algorithm for protein identification.     

Molecular heterogeneity of the subclasses of islet-activating protein (pertussis toxin)-sensitive GTP-binding proteins in porcine thyroid tissue

From porcine thyroid cell membranes, we purified five GTP-binding proteins (G-proteins); Nos. 1 to 3 have 41-kDa alpha-subunits, and Nos. 4 and 5 have 40-kDa alpha-subunits. They were chromatographically (Mono Q) separable and served as specific substrates for islet-activating protein (pertussis toxin). G-proteins 1 and 2 were indistinguishable from porcine brain Gi1 with respect to three criteria, i.e., mobility on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), pI of the ADP-ribosylated alpha-subunit, and immunoreactivity. G-protein 3 was identified as Gi3 by immunoreactivity. The SDS-PAGE and isoelectric focusing (IEF) analyses identified G-proteins 4 and 5 as being chromatographically heterogeneous subtypes of Gi2 in comparison with a pure porcine brain preparation. The IEF analysis also disclosed that each of the Gi1, Gi2, and Gi3 subspecies isolated in the present study has a minor component characterized by a slightly lower pI of its alpha-subunit. We conclude that porcine thyroid tissue contains at least Gi1, Gi2, and Gi3, and that each is made up of heterogeneous populations.     

Exploitation of specific properties of trifluoroethanol for extraction and separation of membrane proteins

Hydrophobic proteins are difficult to analyze by two-dimensional electrophoresis (2-DE) because of their intrinsic tendency to self-aggregate during the first dimension (isoelectric focusing, IEF) or the equilibration steps. This aggregation renders their redissolution for the second dimension uncertain and results in the reduction of the number and intensity of protein spots, and in undesirable vertical and horizontal streaks across gels. Trifluoroethanol (TFE) is traditionally used at high concentration to solubilize peptides and proteins for NMR studies. Depending upon its concentration, TFE strongly affects the three-dimensional structure of proteins. We report here a phase separation system based on TFE/CHCl(3), which is able to extract a number of intrinsic membrane proteins. The addition of TFE in the in-gel sample rehydration buffer to improve membrane protein IEF separation is also presented. The procedure using urea, thiourea, and sulfobetaine as chaotropic agents was modified by the addition of TFE and removing of sulfobetaine at an optimized concentration in the solubilization medium used for the first dimension. When using membrane fractions isolated from Escherichia coli, the intensity and the number of spots detected from 2-DE gels that used TFE in the solubilization medium were significantly increased. The majority of the proteins identified using peptide mass fingerprinting and tandem mass spectrometry (MS/MS) were intrinsic membrane proteins, proteins of beta barrel structure or transmembrane proteins.