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.     

Improving protein identification sensitivity by combining MS and MS/MS information for shotgun proteomics using LTQ-Orbitrap high mass accuracy data

We investigated and compared three approaches for shotgun protein identification by combining MS and MS/MS information using LTQ-Orbitrap high mass accuracy data. In the first approach, we employed a unique mass identifier method where MS peaks matched to peptides predicted from proteins identified from an MS/MS database search are first subtracted before using the MS peaks as unique mass identifiers for protein identification. In the second method, we used an accurate mass and time tag method by building a potential mass and retention time database from previous MudPIT analyses. For the third method, we used a peptide mass fingerprinting-like approach in combination with a randomized database for protein identification. We show that we can improve protein identification sensitivity for low-abundance proteins by combining MS and MS/MS information. Furthermore, "one-hit wonders" from MS/MS database searching can be further substantiated by MS information and the approach improves the identification of low-abundance proteins. The advantages and disadvantages for the three approaches are then discussed.     

Ultrahigh-throughput proteomics using fast RPLC separations with ESI-MS/MS

We describe approaches for proteomics analysis using electrospray ionization-tandem mass spectrometry coupled with fast reversed-phase liquid chromatography (RPLC) separations. The RPLC separations used 50-microm-i.d. fused-silica capillaries packed with submicrometer-sized C18-bonded porous silica particles and achieved peak capacities of 130-420 for analytes from proteome tryptic digests. When these separations were combined with linear ion trap tandem mass spectrometry measurements, approximately 1000 proteins could be identified in 50 min from approximately 4000 identified tryptic peptides; approximately 550 proteins in 20 min from approximately 1800 peptides; and approximately 250 proteins in 8 min from approximately 700 peptides for a S. oneidensis tryptic digest. The dynamic range for protein identification with the fast separations was determined to be approximately 3-4 orders of magnitude of relative protein abundance on the basis of known proteins in human blood plasma analyses. We found that 55% of the MS/MS spectra acquired during the entire analysis (and up to 100% of the MS/MS spectra acquired from the most data-rich zone) provided sufficient quality for identifying peptides. The results confirm that such analyses using very fast (minutes) RPLC separations based on columns packed with microsized porous particles are primarily limited by the MS/MS analysis speed.     

Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS

A novel MS/MS-based analysis strategy using isotopomer labels, referred to as "tandem mass tags" (TMTs), for the accurate quantification of peptides and proteins is described. The new tags are designed to ensure that identical peptides labeled with different TMTs exactly comigrate in all separations. The tags require novel methods of quantification analysis using tandem mass spectrometry. The new tags and analysis methods allow peptides from different samples to be identified by their relative abundance with greater ease and accuracy than other methods. The new TMTs permit simultaneous determination of both the identity and relative abundances of peptide pairs using a collision induced dissociation (CID)-based analysis method. Relative abundance measurements made in the MS/MS mode using the new tags are accurate and sensitive. Compared to MS-mode measurements, a very high signal-to-noise ratio is achieved with MS/MS based detection. The new tags should be applicable to a wide variety of peptide isolation methods.     

Shotgun protein sequencing by tandem mass spectra assembly

The analysis of mass spectrometry data is still largely based on identification of single MS/MS spectra and does not attempt to make use of the extra information available in multiple MS/MS spectra from partially or completely overlapping peptides. Analysis of MS/MS spectra from multiple overlapping peptides opens up the possibility of assembling MS/MS spectra into entire proteins, similarly to the assembly of overlapping DNA reads into entire genomes. In this paper, we present for the first time a way to detect, score, and interpret overlaps between uninterpreted MS/MS spectra in an attempt to sequence entire proteins rather than individual peptides. We show that this approach not only extends the length of reconstructed amino acid sequences but also dramatically improves the quality of de novo peptide sequencing, even for low mass accuracy MS/MS data.     

A method for the chemical generation of N-terminal peptide sequence tags for rapid protein identification

We describe a method for generating multiple small sequences from the N terminal of peptides in unseparated protein digests by stepwise thioacetylation and acid cleavage. The mass differences between a series of N-terminally degraded peptides give short sequences of defined length. Such short "sequence tags" together with the mass of the parent peptide can be used to identify the protein in a database. The sequence ladders are generated without the use of chain terminators or sample aliquoting and the degradation reagents are water soluble so that the chemistry can be carried out on peptides immobilized on C-18 reversed-phase supports without any peptide loss due to washing with organic solvents as occurs in Edman type sequencing. The entire procedure can be automated, and we describe a prototype device for the parallel analysis of multiple samples. We demonstrate the effectiveness of this chemical tagging method in a comparison with Edman sequencing, peptide mass fingerprinting, and MS/MS analysis of crude protein fractions obtained from an HPLC separation of the Escherichia coli ribosome complex which consists of 57 proteins. We show that chemical tagging is a viable first-pass high-throughput identification method to be used prior to an in depth MS/MS analysis.     

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.     

Divinyl sulfone as a postdigestion modifier for enhancing the a(1) Ion in MS/MS and postsource decay: potential applications in proteomics

Divinyl sulfone reacts at pH 8-9 with the alpha-amino groups of N-terminal residues, proline, the epsilon-amino groups of lysine, and the histidine side chains of peptides. This reaction leads to great enhancement of the abundance of the normally weak or missing "a(1)" fragment ion in MS/MS analysis defining the N-terminal residue of a peptide in a digest. This provides "one-step Edman-like" information that, together with a fairly accurately determined mass, often enables one to correctly identify a protein or family of proteins. The applicability of this procedure in proteomics was demonstrated with several peptides and tryptic digests of protein mixtures by LC-MS/MS experiments using a QTOF and MALDI-PSD analyses. Advantages of this approach are its simple chemistry, retention of charge multiplicity, and possibly, shortening of database search time. Used with other MS/MS data, it provides higher confidence in the scores and identification of a protein found in peptide mass fingerprinting. Moreover, this approach has an advantage in "de novo" sequencing due to its ability to decipher the first amino acid of a peptide whose information is normally unavailable in MS/MS spectra.     

Identification of trichloroethanol visualized proteins from two-dimensional polyacrylamide gels by mass spectrometry

Proteins visualized by 2,2,2-trichloroethanol (TCE) on two-dimensional electrophoresis gels are efficiently identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and MS/MS. In a previous study, a method was developed that placed TCE in the polyacrylamide gel so that protein bands can be visualized without staining in less than 5 min. A visible fluorophore is generated by reaction of TCE with tryptophan that allows for protein visualization. In this study, MALDI-TOF MS and LC-MS/MS are used to identify randomly selected Escherichia coli proteins. The identification of TCE visualized proteins is compared to the identification of Coomassie brilliant blue (CBB) stained proteins from two-dimensional gel electrophoresis of E. coli proteins. This study demonstrated that TCE visualized proteins are compatible with protein identification by MALDI-TOF peptide mass fingerprinting. For 10 randomly selected spots, TCE visualization lead to statistically significant identification of 5 proteins and CBB visualization lead to identification of 6 proteins. TCE visualized proteins are also shown to be well suited for protein identification using LC-MS/MS. In 16 spots selected for MS/MS analysis, TCE samples lead to the identification of 79 peptides; while CBB samples lead to the identification of 65 peptides. TCE samples also supported the identification of more proteins. The low stoichiometry of labeling of tryptophan residues does not require inclusion of this modification for database searches. In addition to being a rapid visualization technique compatible with MS, TCE visualization utilizes rapid washing conditions for sample preparation of proteins spots excised from polyacrylamide gels.     

Enrichment by organomercurial agarose and identification of cys-containing peptides from yeast cell lysates

Dynamic range and the presence of highly abundant proteins limit the number of proteins that may be identified within a complex mixture. Cysteine (Cys) has unique chemical reactivity that may be exploited for chemical tagging/capture with biotin/avidin reagents or affinity chromatography allowing specific isolation and subsequent identification of peptide sequences by mass spectrometry. Organomercurial agarose (Hg-beads) specifically captures Cys-containing peptides and proteins from cell lysates. Tryptic peptides from yeast lysates containing Cys were captured and eluted from Hg-beads after incubation with TCEP and trypsin. From two 1 h nano 1-D LC DDA/MS of the eluate >700 proteins were identified with an estimated false positive rate of approximately 1%. Few peptides were identified with high confidence without Cys within their sequence after capture, and extensive washing, indicating little nonspecific binding. The number of fragmentation spectra was increased using automated 2-D nano-LC/MS and allowed identification of 1496 proteins with an estimated false positive rate of 1.1%. Approximately 4% of the proteins identified were from peptides that did not contain Cys, and these were biased toward higher abundance proteins. Comparison of the 1496 proteins to those reported previously showed that >25% were from yeast proteins not previously observed. Most proteins were identified from a single peptide, and sequence coverage was sacrificed by focusing only on identifying Cys-containing peptides, but large numbers of proteins were rapidly identified by eliminating many of the peptides from the higher abundance proteins.     

Development of a protein chip: a MS-based method for quantitation of protein expression and modification levels using an immunoaffinity approach

Protein chip technology permits analysis of the expression and modification status of numerous targeted proteins within a single experiment, mainly through the use of antibody-based microarrays. Despite recent improvements in these protein chips, their applications are still limited for a variety of reasons, which include technical challenges in fabrication of the antibody chips as well as the very low specificity achieved by current detection methods. We have developed a unique approach for relative and/or absolute quantitation of protein expression and modification based on the capture of epitope peptides on affinity beads, which can be used to develop a mass-spectrometry-based protein chip technology. This new method, which utilizes antibodies immobilized on beads for the capture of target peptides, instead of proteins, eliminates many of the problems previously associated with protein chips. We present here several proof-of-principle experiments examining model peptides by this technique. These experiments show that the method is capable of (i). detecting peptides bound to a single antibody bead, (ii). detecting peptides at low (fmol) levels, (iii). producing MS/MS data of suitable quality for protein identification via database searching or de novo sequencing, (iv). quantitating peptides affinity-bound to antibody beads, (v). specifically detecting target peptides in complex mixtures over wide dynamic ranges, and (vi) is compatible with a microarray format for high-throughput analysis. Because our novel method uses antibody beads instead of a derivatized capture surface, and peptides instead of proteins for affinity capture, it can overcome many of the pitfalls of previous protein chip fabrications. Therefore, this method offers an improved approach to protein chip technology that should prove useful for diagnostics and drug development applications.     

Efficient identification of phosphorylation by mass spectrometric phosphopeptide fingerprinting

We describe a rapid and efficient method for the identification of phosphopeptides, which we term mass spectrometric (MS) phosphopeptide fingerprinting. The method involves quantitative comparison of proteolytic peptides from native versus completely dephosphorylated proteins. Dephosphorylation of serine, threonine, and tyrosine residues is achieved by in-gel treatment of the separated proteins with hydrogen fluoride (HF). This chemical dephosphorylation results in enrichment of those unmodified peptides that correspond to previously phosphorylated peptides. Quantitative comparison of the signal-to-noise ratios of peaks in the treated versus untreated samples are used to identify phosphopeptides, which can be confirmed and further studied by tandem mass spectrometry (MS/MS). We have applied this method to identify eight known phosphorylation sites of Xenopus Aurora A kinase, as well as several novel sites in the Xenopus chromosome passenger complex (CPC).     

Practical implementation of 2D HPLC scheme with accurate peptide retention prediction in both dimensions for high-throughput bottom-up proteomics

We describe the practical implementation of a new RP (pH 10 - pH 2) 2D HPLC-ESI/MS scheme for large-scale bottom-up analysis in proteomics. When compared to the common SCX-RP approach, it provides a higher separation efficiency in the first dimension and increases the number of identified peptides/proteins. We also employed the methodology of our sequence-specific retention calculator (SSRCalc) and developed peptide retention prediction algorithms for both LC dimensions. A diverse set of approximately 10,000 tryptic peptides from the soluble protein fraction of whole NK-type cells gave retention time versus hydrophobicity correlations, with R (2) values of 0.95 for pH 10 and 0.945 for pH 2 (formic acid) separation modes. The superior separation efficiency and the ability to use retention prediction to filter out false-positive MS/MS identifications gives promise that this approach will be a method of choice for large-scale proteomics analyses in the future. Finally, the "semi-orthogonal" separation selectivity permits the concatenation of fractions in the first dimension of separation before the final LC-ESI MS step, effectively cutting the analysis time in half, while resulting in a minimal reduction in protein identification.     

Comparison of fluorescence, laser-induced fluorescence, and ultraviolet absorbance detection for measuring HPLC fractionated protein/peptide mixtures

Proteomics is the study of all proteins in a biological sample. High-pressure liquid chromatography coupled online with mass spectrometry (HPLC/MS) is currently the method of choice for proteomic analysis. Proteins are extracted, separated at the protein or peptide level (after enzymatic digestion), and fractions are analyzed by HPLC/MS. Detection during off-line fractionation is generally conducted using UV-vis, which is not sensitive enough to distinguish fractions having the largest concentration of proteins/peptides and should not be combined prior to HPLC/MS. To overcome this deficiency, we utilize fluorescence or UV-laser induced fluorescence (UV-LIF) detection for measuring proteins/peptides during the off-line fractionation. Fluorescence detection allows low-abundance proteins/peptides that contain aromatic amino acids to be measured. In this study, peptide/protein samples fractionated using ion-exchange chromatography were detected using UV absorbance, fluorescence, and UV-LIF. The results indicated that fluorescence and UV-LIF were able to detect the lower abundance proteins/peptides to give a more representative chromatogram, allowing the analyst to decide which fractions should be combined prior to HPLC/tandem mass spectrometry (MS/MS) analysis.     

Artificial neural network analysis for evaluation of peptide MS/MS spectra in proteomics

The aim of the work was to explore usefulness of artificial neural network (ANN) analysis for the evaluation of proteomics data. The analysis was applied to the data generated by the widely used protein identification program Sequest, completed with several structural parameters readily calculated from peptide molecular formulas. Proteins from yeast cells were identified based on the MS/MS spectra of peptides. The constructed ANN was demonstrated to classify automatically as either "good" or "bad" the peptide MS/MS spectra otherwise classified manually. An appropriately trained ANN proves to be a high-throughput tool facilitating examination of Sequest's results. ANNs are recommended as a means of automatic processing of large amounts of MS/MS data, which normally must be considered in the analysis of complex mixtures of proteins in proteomics.     

Coumarin tags for analysis of peptides by MALDI-TOF MS and MS/MS. 2. Alexa Fluor 350 tag for increased peptide and protein Identification by LC-MALDI-TOF/TOF MS

The goal of this study was the development of N-terminal tags to improve peptide identification using high-throughput MALDI-TOF/TOF MS. Part 1 of the study was focused on the influence of derivatization on the intensities of MALDI-TOF MS signals of peptides. In part 2, various derivatization approaches for the improvement of peptide fragmentation efficiency in MALDI-TOF/TOF MS are explored. We demonstrate that permanent cation tags, while significantly improving signal intensity in the MS mode, lead to severe suppression of MS/MS fragmentation, making these tags unsuitable for high-throughput MALDI-TOF/TOF MS analysis. In the present work, it was found that labeling with Alexa Fluor 350, a coumarin tag containing a sulfo group, along with guanidation of epsilon-amino groups of Lys, could enhance unimolecular fragmentation of peptides with the formation of a high-intensity y-ion series, while the peptide intensities in the MS mode were not severely affected. LC-MALDI-TOF/TOF MS analysis of tryptic peptides from the SCX fractions of an E. coli lysate revealed improved peptide scores, a doubling of the total number of peptides, and a 30% increase in the number of proteins identified, as a result of labeling. Furthermore, by combining the data from native and labeled samples, confidence in correct identification was increased, as many proteins were identified by different peptides in the native and labeled data sets. Additionally, derivatization was found not to impair chromatographic behavior of peptides. All these factors suggest that labeling with Alexa Fluor 350 is a promising approach to the high-throughput LC-MALDI-TOF/TOF MS analysis of proteomic samples.     

Isotope-tagged cross-linking reagents. A new tool in mass spectrometric protein interaction analysis

In protein interaction analysis, one promising method to identify the involved proteins and to characterize interacting sites at the same time is the mass spectrometric analysis of enzymatic hydrolysates of covalently cross-linked complexes. While protein identification can be accomplished by the methodology developed for proteome analysis, the unequivocal detection and characterization of cross-linked sites remained involved without selection criteria for linked peptides in addition to mass. To provide such criteria, we incorporated cross-links with a distinct isotope pattern into the microtubule-destabilizing protein Op18/stathmin (Op18) and into complexes formed by Op18 with tubulin. The deuterium-labeled cross-linking reagents bis(sulfosuccinimidyl)-glutarate-d4, -pimelate-d4, and -sebacate-d4 were prepared together with their undeuterated counterparts and applied as a 1:1 mixture of the respective d0 and d4 isotopomers. The resulting d0/d4 isotope tags allowed a straightforward mass spectrometric detection of peptides carrying the linker even in complex enzymatic protein hydrolysates. In the structure elucidation of the linked peptides by MS/MS, the assignment of the linked amino acids was again greatly facilitated by the d0/d4 tag. By applying two cross-linkers with similar reactivity but different spacer length in parallel, even doublets with very low intensity could be assigned with high confidence in MS and MS/MS spectra. Since in the Op18-tubulin complexes only a limited number of peptides carried the linker, the identification of the involved proteins per se was not impeded, thus accomplishing both protein identification and characterization of interacting sites in the same experiment. This novel methodology allowed us to significantly refine the current view of the complex between Op18 and tubulin corroborating the tubulin "capping" activity of the N-terminal domain of Op18.     

High-throughput peptide identification from protein digests using data-dependent multiplexed tandem FTICR mass spectrometry coupled with capillary liquid chromatography

Tandem mass spectrometry (MS/MS) plays an important role in the unambiguous identification and structural elucidation of biomolecules. In contrast to conventional MS/MS approaches for protein identification where an individual polypeptide is sequentially selected and dissociated, a multiplexed-MS/MS approach increases throughput by selecting several peptides for simultaneous dissociation using either infrared multiphoton dissociation (IRMPD) or multiple frequency sustained off-resonance irradiation (SORI) collisionally induced dissociation (CID). The high mass measurement accuracy and resolution of FTICR combined with knowledge of peptide dissociation pathways allows the fragments arising from several different parent ions to be assigned. Herein we report the application of multiplexed-MS/MS coupled with on-line separations for the identification of peptides present in complex mixtures (i.e., whole cell lysate digests). Software was developed to enable "on-the-fly" data-dependent peak selection of a subset of polypeptides from each FTICR MS acquisition. In the subsequent MS/MS acquisitions, several coeluting peptides were fragmented simultaneously using either IRMPD or SORI-CID techniques. The utility of this approach has been demonstrated using a bovine serum albumin tryptic digest separated by capillary LC where multiple peptides were readily identified in single MS/MS acquisitions. We also present initial results from multiplexed-MS/MS analysis of a D. radiodurans whole cell digest to illustrate the utility of this approach for high-throughput analysis of a bacterial proteome.     

Exploring the precursor ion exclusion feature of liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry for improving protein identification in shotgun proteome analysis

In shotgun proteome analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS), not all coeluting peptides at a given retention time are subjected to MS/MS due to the limitation of spectral acquisition speed of a mass spectrometer. In this work, precursor ion exclusion (PIE) in an electrospray ionization (ESI) quadrupole time-of-flight (QTOF) mass spectrometer was explored as a means of mitigating the undersampling problem. This strategy is based on running replicates of the sample where the precursor ions detected in the initial run(s) are excluded for MS/MS in the subsequent run. Four PIE methods as well as running replicates without PIE were investigated and compared for their effectiveness in identifying peptides and proteins. In the analysis of an MCF-7 breast cancer cell lysate digest by three replicate 2 h gradient LC-ESI runs, the first PIE method used a list of precursor ions detected in the initial run(s) for exclusion and identified a total of 572 proteins from the three runs combined with an average of 3.59 peptides matched to a protein. The second PIE method involved in the generation of a list of m/ z values of precursor ions along with their retention time information from the initial run(s), followed by entering these ions with retention times into the ion exclusion program of the QTOF control software for exclusion at a predefined retention time window (i.e., +/-150 s). In comparison to the first PIE method, this method reduced the possibility of excluding different peptide ions of the same m/ z (within a mass tolerance window) eluted at different retention windows. A total of 657 proteins were identified with an average of 3.75 peptides matched to a protein. The third PIE method studied relied on the exclusion of the precursor ions of peptides identified through database search of the MS/MS spectra generated in the initial run(s). This selective PIE method identified a total of 681 proteins with an average of 3.68 peptides matched to a protein. The final PIE method investigated involves the expansion of the selective PIE list by including nonidentifiable peptide ions found in the database search. This complete PIE method identified a total of 726 proteins with an average of 3.66 peptides per protein. In the case of three replicate runs without PIE, a total of 460 proteins were identified with an average of 3.51 peptides matched to a protein. Thus, the use of an optimal PIE strategy significantly increased the number of proteins identified from replicate runs (i.e., 726 vs 460 or a 58% increase). It is further demonstrated that this PIE strategy also improves protein identification efficiency in the analysis of a yeast whole cell lysate digesta less complex proteome digest. A total of 533 proteins identified from five replicate runs with complete PIE, compared to 353 proteins identified from the five replicate runs without PIE, representing a 51% increase in the number of proteins identified.