In vivo termini amino acid labeling for quantitative proteomics

Quantitative proteomics is one of the research hotspots in the proteomics field and presently maturing rapidly into an important branch. The two most typical quantitative methods, stable isotope labeling with amino acids in cell culture (SILAC) and isobaric tags for relative and absolute quantification (iTRAQ), have been widely and effectively applied in solving various biological and medical problems. Here, we describe a novel quantitative strategy, termed "IVTAL", for in vivo termini amino acid labeling, which combines some advantages of the two methods above. The core of this strategy is a set of heavy amino acid (13)C(6)-arginine and (13)C(6)-lysine and specific endoproteinase Lys-N and Arg-C that yield some labeled isobaric peptides by cell culture and enzymatic digestion, which are indistinguishable in the MS scan but exhibit multiple MS/MS reporter b, y ion pairs in a full mass range that support quantitation. Relative quantification of cell states can be achieved by calculating the intensity ratio of the corresponding reporter b, y ions in the MS/MS scan. The experimental analysis for various proportions of mixed HeLa cell samples indicated that the novel strategy showed an abundance of reliable quantitative information, a high sensitivity, and a good dynamic range of nearly 2 orders of magnitude. IVTAL, as a highly accurate and reliable quantitative proteomic approach, is expected to be compatible with any cell culture system and to be especially effective for the analysis of multiple post-translational modificational sites in one peptide.     

Sequential interval motif search: unrestricted database surveys of global MS/MS data sets for detection of putative post-translational modifications

Tandem mass spectrometry is the prevailing approach for large-scale peptide sequencing in high-throughput proteomic profiling studies. Effective database search engines have been developed to identify peptide sequences from MS/MS fragmentation spectra. Since proteins are polymorphic and subject to post-translational modifications (PTM), however, computational methods for detecting unanticipated variants are also needed to achieve true proteome-wide coverage. Different from existing "unrestrictive" search tools, we present a novel algorithm, termed SIMS (for Sequential Motif Interval Search), that interprets pairs of product ion peaks, representing potential amino acid residues or "intervals", as a means of mapping PTMs or substitutions in a blind database search mode. An effective heuristic software program was likewise developed to evaluate, rank, and filter optimal combinations of relevant intervals to identify candidate sequences, and any associated PTM or polymorphism, from large collections of MS/MS spectra. The prediction performance of SIMS was benchmarked extensively against annotated reference spectral data sets and compared favorably with, and was complementary to, current state-of-the-art methods. An exhaustive discovery screen using SIMS also revealed thousands of previously overlooked putative PTMs in a compendium of yeast protein complexes and in a proteome-wide map of adult mouse cardiomyocytes. We demonstrate that SIMS, freely accessible for academic research use, addresses gaps in current proteomic data interpretation pipelines, improving overall detection coverage, and facilitating comprehensive investigations of the fundamental multiplicity of the expressed proteome.     

Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry as an alternative proteomics platform to ultraperformance liquid chromatography-electrospray ionization-tandem mass spectrometry for samples of intermediate complexity

We demonstrate the use of capillary zone electrophoresis with an electrokinetically pumped sheath-flow electrospray interface for the analysis of a tryptic digest of a sample of intermediate protein complexity, the secreted protein fraction of Mycobacterium marinum. For electrophoretic analysis, 11 fractions were generated from the sample using reverse-phase liquid chromatography; each fraction was analyzed by CZE-ESI-MS/MS, and 334 peptides corresponding to 140 proteins were identified in 165 min of mass spectrometer time at 95% confidence (FDR < 0.15%). In comparison, 388 peptides corresponding to 134 proteins were identified in 180 min of mass spectrometer time by triplicate UPLC-ESI-MS/MS analyses, each using 250 ng of the unfractionated peptide mixture, at 95% confidence (FDR < 0.15%). Overall, 62% of peptides identified in CZE-ESI-MS/MS and 67% in UPLC-ESI-MS/MS were unique. CZE-ESI-MS/MS favored basic and hydrophilic peptides with low molecular masses. Combining the two data sets increased the number of unique peptides by 53%. Our approach identified more than twice as many proteins as the previous record for capillary electrophoresis proteome analysis. CE-ESI-MS/MS is a useful tool for the analysis of proteome samples of intermediate complexity.     

Enhanced characterization of complex proteomic samples using LC-MALDI MS/MS: exclusion of redundant peptides from MS/MS analysis in replicate runs

Due to the complexity of proteome samples, only a portion of peptides and thus proteins can be identified in a single LC-MS/MS analysis in current shotgun proteomics methodologies. It has been shown that replicate runs can be used to improve the comprehensiveness of the proteome analysis; however, high-intensity peptides tend to be analyzed repeatedly in different runs, thus reducing the chance of identifying low-intensity peptides. In contrast to commonly used online ESI-MS, offline MALDI decouples the separation from MS acquisition, thus allowing in-depth selection for specific precursor ions. Accordingly, we extended a strategy for offline LC-MALDI MS/MS analysis using a precursor ion exclusion list consisting of all identified peptides in preceding runs. The exclusion list eliminated redundant MS/MS acquisitions in subsequent runs, thus reducing MALDI sample depletion and allowing identification of a larger number of peptide identifications in the cumulative dataset. In the analysis of the digest of an Escherichia coli lysate, the exclusion list strategy resulted in a 25% increase in the number of unique peptide identifications in the second run, in contrast to simply pooling MS/MS data from two replicate runs. To reduce the increased LC analysis time for repeat runs, a four-column multiplexed LC system was developed to carry out separation simultaneously. The multiplexed LC-MALDI MS provides a high-throughput platform to utilize the exclusion list strategy in proteome analysis.     

Non-gel-based dual 18O labeling quantitative proteomics strategy

To improve the quantitation of target proteins in proteomic analyses, we developed a non-gel-based, dual (18)O labeling strategy. This global isotope labeling method utilizes an acylating chemical reagent with two anhydride functional groups, bicyclic anhydride diethylenetriamine-N,N,N', N' ',N' '-pentaacetic acid (DTPA) dianhydride. In the first (18)O labeling method (chemical (18)O labeling) of our dual strategy, one functional group was covalently coupled to the primary amines of the peptides and (18)O from H2(18)O was incorporated at the other functional group by hydrolysis. In the second (18)O labeling method (chemical and enzyme-catalyzed (18)O labeling), chemical (18)O labeling and enzyme-catalyzed (18)O labeling of the carboxyl- termini of the peptides were combined. The acylation reaction between DTPA and the model peptides was rapid and specific, and the DTPA-modified N-termini of the peptides promoted only y-series ions in MS/MS. The two methods of (18)O labeling were accurate in the range 0.1-10 of (16)O/(18)O peptide ratios. The deviations of the methods were <20%. In contrast to current proteolytic (18)O labeling methods, there was no (18)O to (16)O back-exchange in the first method and no isotope peaks in MS in the second method. The combination of chemical and proteolytic (18)O labeling improved the confidence of the quantitation results.     

Combinatorial peptide ligand library treatment followed by a dual-enzyme, dual-activation approach on a nanoflow liquid chromatography/orbitrap/electron transfer dissociation system for comprehensive analysis of swine plasma proteome

The plasma proteome holds enormous clinical potential, yet an in-depth analysis of the plasma proteome remains a daunting challenge due to its high complexity and the extremely wide dynamic range in protein concentrations. Furthermore, existing antibody-based approaches for depleting high-abundance proteins are not adaptable to the analysis of the animal plasma proteome, which is often essential for experimental pathology/pharmacology. Here we describe a highly comprehensive method for the investigation of the animal plasma proteome which employs an optimized combinatorial peptide ligand library (CPLL) treatment to reduce the protein concentration dynamic range and a dual-enzyme, dual-activation strategy to achieve high proteomic coverage. The CPLL treatment enriched the lower abundance proteins by >100-fold when the samples were loaded in moderately denaturing conditions with multiple loading-washing cycles. The native and the CPLL-treated plasma were digested in parallel by two enzymes (trypsin and GluC) carrying orthogonal specificities. By performing this differential proteolysis, the proteome coverage is improved where peptides produced by only one enzyme are poorly detectable. Digests were fractionated with high-resolution strong cation exchange chromatography and then resolved on a long, heated nano liquid chromatography column. MS analysis was performed on a linear triple quadrupole/orbitrap with two complementary activation methods (collisionally induced dissociation (CID) and electron transfer dissociation). We applied this optimized strategy to investigate the plasma proteome from swine, a prominent animal model for cardiovascular diseases (CVDs). This large-scale analysis results in identification of a total of 3421 unique proteins, spanning a concentration range of 9-10 orders of magnitude. The proteins were identified under a set of commonly accepted criteria, including a precursor mass error of <15 ppm, Xcorr cutoffs, and ≥2 unique peptides at a peptide probability of ≥95% and a protein probability of ≥99%, and the peptide false-positive rate of the data set was 1.8% as estimated by searching the reversed database. CPLL treatment resulted in 55% more identified proteins over those from native plasma; moreover, compared with using only trypsin and CID, the dual-enzyme/activation approach enabled the identification of 2.6-fold more proteins and substantially higher sequence coverage for most individual proteins. Further analysis revealed 657 proteins as significantly associated with CVDs (p < 0.05), which constitute five CVD-related pathways. This study represents the first in-depth investigation of a nonhuman plasma proteome, and the strategy developed here is adaptable to the comprehensive analysis of other highly complex proteomes.     

Identification of in-gel digested proteins by complementary peptide mass fingerprinting and tandem mass spectrometry data obtained on an electrospray ionization quadrupole time-of-flight mass spectrometer

The present study reports a procedure developed for the identification of SDS-polyacrylamide gel electrophoretically separated proteins using an electrospray ionization quadrupole time-of-flight mass spectrometer (Q-TOF MS) equipped with pressurized sample introduction. It is based on in-gel digestion of the proteins without previous reduction/alkylation and on the capability of the Q-TOF MS to provide data suitable for peptide mass fingerprinting database searches and for tandem mass spectrometry (MS/MS) database searches (sequence tags). Omitting the reduction/alkylation step reduces sample contamination and sample loss, resulting in increased sensitivity. Omitting this step can leave disulfide-connected peptides in the analyte that can lead to misleading or ambiguous results from the peptide mass fingerprinting database search. This uncertainty, however, is overcome by MS/MS analysis of the peptides. Furthermore, the two complementary MS approaches increase the accuracy of the assignment of the unknown protein. This procedure is thus, highly sensitive, accurate, and rapid. In combination with pressurized nanospray sample introduction, it is suitable for automated sample handling. Here, we apply this approach to identify protein contaminants observed during the purification of the yeast DNA mismatch repair protein Mlh 1.     

Utility of accurate mass tags for proteome-wide protein identification

An enabling capability for proteomics would be the ability to study protein expression on a global scale. While several different separation and analysis options are being investigated to advance the practice of proteomics, mass spectrometry (MS) is rapidly becoming the core instrumental technology used to characterize the large number of proteins that constitute a proteome. To be most effective, proteomic measurements must be high-throughput, ideally allowing thousands of proteins to be identified on a time scale of hours. Most strategies of identification by MS rely on the analysis of enzymatically produced peptides originating from an isolated protein followed by either peptide mapping or tandem MS (MS/MS) to obtain sequence information for a single peptide. In the case of peptide mapping, several peptide masses are needed to unambiguously identify a protein with the typically achieved mass measurement accuracies (MMA). The ability to identify proteins based on the mass of a single peptide (i.e., an accurate mass tag; AMT) is proposed and is largely dependent on the MMA that can be achieved. To determine the MMA necessary to enable the use of AMTs for proteome-wide protein identification, we analyzed the predicted proteins and their tryptic fragments from Saccharomyces cerevisiae and Caenorhabditis elegans. The results show that low ppm (i.e., approximately 1 ppm) level measurements have practical utility for analysis of small proteomes. Additionally, up to 85% of the peptides predicted from these organisms can function as AMTs at sub-ppm MMA levels attainable using Fourier transform ion cyclotron resonance MS. Additional information, such as sequence constraints, should enable even more complex proteomes to be studied at more modest mass measurement accuracies. Once AMTs are established, subsequent high-throughput measurements of proteomes (e.g., after perturbations) will be greatly facilitated.     

Software for quantitative proteomic analysis using stable isotope labeling and data independent acquisition

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

Single peptide-based protein identification in human proteome through MALDI-TOF MS coupled with amino acids coded mass tagging

Identification of proteins with low sequence coverage using mass spectrometry (MS) requires tandem MS/MS peptide sequencing. It is very challenging to obtain a complete or to interpret an incomplete tandem MS/MS spectrum from fragmentation of a weak peptide ion signal for sequence assignment. Here, we have developed an effective and high-throughput MALDI-TOF-based method for the identification of membrane and other low-abundance proteins with a simple, one-dimensional separation step. In this approach, several stable isotope-labeled amino acid precursors were selected to mass-tag, in parallel, the human proteome of human skin fibroblast cells in a residue-specific manner during in vivo cell culturing. These labeled residues can be recognized by their characteristic isotope patterns in MALDI-TOF MS spectra. The isotope pattern of particular peptides induced by the different labeled precursors provides information about their amino acid compositions. The specificity of peptide signals in a peptide mass mapping is thus greatly enhanced, resolving a high degree of mass degeneracy of proteolytic peptides derived from the complex human proteome. Further, false positive matches in database searching can be eliminated. More importantly, proteins can be accurately identified through a single peptide with its m/z value and partial amino acid composition. With the increased solubility of hydrophobic proteins in SDS, we have demonstrated that our approach is effective for the identification of membrane and low-abundant proteins with low sequence coverage and weak signal intensity, which are often difficult for obtaining informative fragment patterns in tandem MS/MS peptide sequencing analysis.     

Primary structure determination of peptides and enzymatically digested proteins using capillary liquid chromatography/mass spectrometry and rapid linked-scan techniques

Primary protein sequences were determined for both peptides and enzymatically digested proteins by rapid linked-scan (B/E) liquid chromatography/mass spectrometry/mass spectrometry (LC/MS/MS) at the low-picomole level (10-50 pmol). During the course of a single LC/MS/MS analysis, we demonstrated that it is possible to generate interpretable collision-induced dissociation spectra of the eluting proteolytic peptides. Molecular weights of tryptic peptides were established by using 1/10 of the protein digest by operating in the capillary LC/frit-FABMS mode. Peptides exhibiting the strongest MH+ ions were then selected for subsequent LC/MS/MS analysis (typically 1/5 of the remaining protein digest). Elution times for each chromatographic peak were generally greater than 30 s. It was therefore possible to obtain a minimum of six B/E fast linked-scan spectra during the course of elution of each peptide component. Typically, B/E linked scans of the greatest ion abundance (obtained at the chromatographic peak maximum) were averaged to enhance the signal/noise ratio at these low-picomole levels. Unit resolution was observed for product ions below m/z 1000. Rapid linked scanning by LC/frit-FABMS/MS provided mass assignments for product ions within 0.2-0.3 amu of theoretical values. Side-chain fragment ions (wn and dn) were also observed, which allowed for the differentiation of isobaric amino acids (e.g., leucine and isoleucine). Examples of the application of this fast linked-scan technique to LC/MS/MS are presented for complex mixtures of unknown peptides and the tryptic digestion of phosphorylated beta-casein.     

Improved precision of iTRAQ and TMT quantification by an axial extraction field in an Orbitrap HCD cell

Improving analytical precision is a major goal in quantitative differential proteomics as high precision ensures low numbers of outliers, a source of false positives with regard to quantification. In addition, higher precision increases statistical power, i.e., the probability to detect significant differences. With chemical labeling using isobaric tags for relative and absolute quantitation (iTRAQ) or tandem mass tag (TMT) reagents, quantification is based on the extraction of reporter ions from tandem mass spectrometry (MS/MS) spectra. We compared the performance of two versions of the LTQ Orbitrap higher energy collisional dissociation (HCD) cell with and without an axial electric field with regard to reporter ion quantification. The HCD cell with the axial electric field was designed to push fragment ions into the C-trap and this version is mounted in current Orbitrap XL ETD and Orbitrap Velos instruments. Our goal was to evaluate whether the purported improvement in ion transmission had a measurable impact on the precision of MS/MS based quantification using peptide labeling with isobaric tags. We show that the axial electric field led to an increased percentage of HCD spectra in which the complete set of reporter ions was detected and, even more important, to a reduction in overall variance, i.e., improved analytical precision of the acquired data. Notably, adequate precision of HCD-based quantification was maintained even for low precursor ion intensities of a complex biological sample. These findings may help researchers in their design of quantitative proteomics studies using isobaric tags and establish HCD-based quantification on the LTQ Orbitrap as a highly precise approach in quantitative proteomics.     

Identification of bacteria using tandem mass spectrometry combined with a proteome database and statistical scoring

Detection and identification of pathogenic bacteria and their protein toxins play a crucial role in a proper response to natural or terrorist-caused outbreaks of infectious diseases. The recent availability of whole genome sequences of priority bacterial pathogens opens new diagnostic possibilities for identification of bacteria by retrieving their genomic or proteomic information. We describe a method for identification of bacteria based on tandem mass spectrometric (MS/MS) analysis of peptides derived from bacterial proteins. This method involves bacterial cell protein extraction, trypsin digestion, liquid chromatography MS/MS analysis of the resulting peptides, and a statistical scoring algorithm to rank MS/MS spectral matching results for bacterial identification. To facilitate spectral data searching, a proteome database was constructed by translating genomes of bacteria of interest with fully or partially determined sequences. In this work, a prototype database was constructed by the automated analysis of 87 publicly available, fully sequenced bacterial genomes with the GLIMMER gene finding software. MS/MS peptide spectral matching for peptide sequence assignment against this proteome database was done by SEQUEST. To gauge the relative significance of the SEQUEST-generated matching parameters for correct peptide assignment, discriminant function (DF) analysis of these parameters was applied and DF scores were used to calculate probabilities of correct MS/MS spectra assignment to peptide sequences in the database. The peptides with DF scores exceeding a threshold value determined by the probability of correct peptide assignment were accepted and matched to the bacterial proteomes represented in the database. Sequence filtering or removal of degenerate peptides matched with multiple bacteria was then performed to further improve identification. It is demonstrated that using a preset criterion with known distributions of discriminant function scores and probabilities of correct peptide sequence assignments, a test bacterium within the 87 database microorganisms can be unambiguously identified.     

Pro-CrossLink. Software tool for protein cross-linking and mass spectrometry

To facilitate structural analysis of proteins and protein-protein interactions, we developed Pro-CrossLink, a suite of software tools consisting of three programs (Figure 1), DetectShift, IdentifyXLink, and AssignXLink. DetectShift was developed to detect ions of cross-linked peptide pairs in a mixture of 18O-labeled peptides obtained from protein proteolytic digests. The selected candidate ions of cross-linked peptide pairs subsequently undergo tandem mass spectrometric (MS/MS) analysis for sequence determination. Based on the masses of candidate ions as well as y- and b-type ions in the tandem mass spectra, IdentifyXLink assigns the candidate ions to cross-linked peptide pairs. For an identified cross-linked peptide pair, AssignXLink generates an extensive fragment ion list, including a-, b-, c-type, x-, y-, z-type, internal, and immonium ions with associated common losses of H2O, NH3, CO, and CO2, and facilitates a precise location of the cross-linked residues. Pro-CrossLink is automated, highly configurable by the user, and applicable to many studies that map low-resolution protein structures and molecular interfaces in protein complexes.     

Automated 20 kpsi RPLC-MS and MS/MS with chromatographic peak capacities of 1000-1500 and capabilities in proteomics and metabolomics

Proteomics analysis based-on reversed-phase liquid chromatography (RPLC) is widely practiced; however, variations providing cutting-edge RPLC performance have generally not been adopted even though their benefits are well established. Here, we describe an automated format 20 kpsi RPLC system for proteomics and metabolomics that includes on-line coupling of micro-solid phase extraction for sample loading and allows electrospray ionization emitters to be readily replaced. The system uses 50 microm i.d. x 40-200 cm fused-silica capillaries packed with 1.4-3-microm porous C18-bonded silica particles to obtain chromatographic peak capacities of 1000-1500 for complex peptide and metabolite mixtures. This separation quality provided high-confidence identifications of >12 000 different tryptic peptides from >2000 distinct Shewanella oneidensis proteins (approximately 40% of the proteins predicted for the S. oneidensis proteome) in a single 12-h ion trap tandem mass spectrometry (MS/MS) analysis. The protein identification reproducibility approached 90% between replicate experiments. The average protein MS/MS identification rate exceeded 10 proteins/min, and 1207 proteins were identified in 120 min through assignment of 5944 different peptides. The proteomic analysis dynamic range of the 20 kpsi RPLC-ion trap MS/MS was approximately 10(6) based on analyses of a human blood plasma sample, for which 835 distinct proteins were identified with high confidence in a single 12-h run. A single run of the 20 kpsi RPLC-accurate mass MS detected >5000 different compounds from a metabolomics sample.     

On the utility of isotopic fine structure mass spectrometry in protein identification

Modern mass spectrometry (MS)-based protein identification and characterization relies upon accurate mass measurements of the (13)C isotopic distributions of the enzymatically produced peptides. Interestingly, obtaining peptide elemental composition information from its isotopic fine structure mass spectrum to increase the confidence in peptide and protein identification has not yet been developed into a bottom-up proteomics-grade analytical approach. Here, we discuss the possible utility and limitations of the isotopic fine structure MS for peptide and protein identification. First, we in silico identify the peptides from the E. coli tryptic digest and show the increased confidence in peptide identification by consideration of the isotopic fine structures of these peptides as a function of mass and abundance accuracies. In the following, we demonstrate that the state-of-the-art high magnetic field Fourier transform ion cyclotron resonance (FT-ICR) MS allows a routine acquisition of the isotopic fine structure information of a number of isobaric peptide pairs, including a pair of peptides originating from E. coli. Finally, we address the practical limitation of the isotopic fine structure MS implementation in the time-constraint experiments by applying an advanced signal processing technique, filter diagonalization method, to the experimental transients to overcome the resolution barrier set by the typically applied Fourier transformation. We thus demonstrate that the isotopic fine structures of peptides may indeed improve the peptide and possibly protein identification, can be produced in a routine experiment by the state-of-the-art high resolution mass spectrometers, and can be potentially obtained on a chromatographic time-scale of a typical bottom-up proteomics experiment. The latter one requires at least an order of magnitude increase in sensitivity of ion detection, which presumably can be realized using high-field Orbitrap FTMS and/or future generation of ultrahigh magnetic field FT-ICR MS equipped with harmonized ICR cells.     

N-terminal isotope tagging strategy for quantitative proteomics: results-driven analysis of protein abundance changes

Comparing the relative abundance of each protein present in two or more complex samples can be accomplished using isotope-coded tags incorporated at the peptide level. Here we describe a chemical labeling strategy for the incorporation of a single isotope label per peptide, which is completely sequence-independent so that it potentially labels every peptide from a protein including those containing posttranslational modifications. It is based on a gentle chemical labeling strategy that specifically labels the N-terminus of all peptides in a digested sample with either a d5- or d0-propionyl group. Lysine side chains are blocked by guanidination prior to N-terminal labeling to prevent the incorporation of multiple labels. In this paper, we describe the optimization of this N-terminal isotopic tagging strategy and validate its use for peptide-based protein abundance measurements with a 10-protein standard mixture. Using a results-driven strategy, which targets proteins for identification based on MALDI TOF-MS analysis of isotopically labeled peptide pairs, we also show that this labeling strategy can detect a small number of differentially expressed proteins in a mixture as complex as a yeast cell lysate. Only peptides that show a difference in relative abundance are targeted for identification by tandem MS. Despite the fact that many peptides are quantitated, only those few showing a difference in abundance are targeted for protein identification. Proteins are identified by either targeted LC-ES MS/MS or MALDI TOF/TOF. Identifications can be accomplished equally well by either technique on the basis of multiple peptides. This increases the confidence level for both identification and quantitation. The merits of ES MS/MS or MALDI MS/MS for protein identification in a results-driven strategy are discussed.     

Reactive-electrospray-assisted laser desorption/ionization for characterization of peptides and proteins

Electrospray-assisted laser desorption/ionization (ELDI) is a soft ionization method for mass spectrometry (MS) and combines features of both electrospray ionization (ESI) and matrix-assisted laser desorption/ionization to generate ESI-like multiply charged molecules. The ELDI process is based on merging ESI-generated, charged droplets with particles UV laser desorbed from dried or wet sample deposits. We previously reported that ELDI is amenable for MS-based protein identification of large peptides and small proteins using top-down and bottom-up techniques (Peng, I. X.; Shiea, J.; Ogorzalek Loo, R. R.; Loo, J. A. Rapid Commun. Mass Spectrom. 2007, 21, 2541-2546). We have extended our studies by applying collisionally activated dissociation and electron-transfer dissociation MS ( n ) to protein analysis and show that ELDI is capable of multistage MS to MS (4) for top-down characterization of large proteins such as 29 kDa carbonic anhydrase. Multiply charged proteins generated by the ELDI mechanism can be shifted to higher charge by increasing the organic content in the ESI solvent to denature the protein molecules, or by adding m-nitrobenzyl alcohol to the ESI solvent. Furthermore, we introduce "reactive-ELDI", which supports chemical reactions during the ELDI process. Preliminary data for online disulfide bond reduction using dithiothreitol on oxidized glutathione and insulin show reactive-ELDI to be effective. These data provide evidence that the laser-desorbed particles merge with the ESI-generated charge droplets to effect chemical reactions prior to online MS detection. This capability should allow other chemical and enzymatic reactions to be exploited as online protein characterization tools, as well as extending them to flexible, spatially resolved tissue screening and imaging. Also, these reactive-ELDI disulfide reduction experiments enable direct top-down protein identification for proteomic study, side stepping laborious, time-consuming sample preparation steps such as in-solution reduction and alkylation.     

Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus

A new method for proteolytic stable isotope labeling is introduced to provide quantitative and concurrent comparisons between individual proteins from two entire proteome pools or their subfractions. Two 18O atoms are incorporated universally into the carboxyl termini of all tryptic peptides during the proteolytic cleavage of all proteins in the first pool. Proteins in the second pool are cleaved analogously with the carboxyl termini of the resulting peptides containing two 16O atoms (i.e., no labeling). The two peptide mixtures are pooled for fractionation and separation, and the masses and isotope ratios of each peptide pair (differing by 4 Da) are measured by high-resolution mass spectrometry. Short sequences and/or accurate mass measurements combined with proteomics software tools allow the peptides to be related to the precursor proteins from which they are derived. Relative signal intensities of paired peptides quantify the expression levels of their precursor proteins from proteome pools to be compared, using an equation described in the paper. Observation of individual (unpaired) peptides is mainly interpreted as differential modification or sequence variation for the protein from the respective proteome pool. The method is evaluated here in a comparison of virion proteins for two serotypes (Ad5 and Ad2) of adenovirus, taking advantage of information already available about protein sequences and concentrations. In general, proteolytic 18O labeling enables a shotgun approach for proteomic studies with quantitation capability and is proposed as a useful tool for comparative proteomic studies of very complex protein mixtures.     

Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search

We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.