Discovering known and unanticipated protein modifications using MS/MS database searching

We present an MS/MS database search algorithm with the following novel features: (1) a novel protein database structure containing extensive preindexing and (2) zone modification searching, which enables the rapid discovery of protein modifications of known (i.e., user-specified) and unanticipated delta masses. All of these features are implemented in Interrogator, the search engine that runs behind the Pro ID, Pro ICAT, and Pro QUANT software products. Speed benchmarks demonstrate that our modification-tolerant database search algorithm is 100-fold faster than traditional database search algorithms when used for comprehensive searches for a broad variety of modification species. The ability to rapidly search for a large variety of known as well as unanticipated modifications allows a significantly greater percentage of MS/MS scans to be identified. We demonstrate this with an example in which, out of a total of 473 identified MS/MS scans, 315 of these scans correspond to unmodified peptides, while 158 scans correspond to a wide variety of modified peptides. In addition, we provide specific examples where the ability to search for unanticipated modifications allows the scientist to discover: unexpected modifications that have biological significance; amino acid mutations; salt-adducted peptides in a sample that has nominally been desalted; peptides arising from nontryptic cleavage in a sample that has nominally been digested using trypsin; other unintended consequences of sample handling procedures.     

Protein identification with a single accurate mass of a cysteine-containing peptide and constrained database searching

A method for rapid and unambiguous identification of proteins by sequence database searching using the accurate mass of a single peptide and specific sequence constraints is described. Peptide masses were measured using electrospray ionization-Fourier transform ion cyclotron resonance mass spectrometry to an accuracy of 1 ppm. The presence of a cysteine residue within a peptide sequence was used as a database searching constraint to reduce the number of potential database hits. Cysteine-containing peptides were detected within a mixture of peptides by incorporating chlorine into a general alkylating reagent specific for cysteine residues. Secondary search constraints included the specificity of the protease used for protein digestion and the molecular mass of the protein estimated by gel electrophoresis. The natural isotopic distribution of chlorine encoded the cysteine-containing peptide with a distinctive isotopic pattern that allowed automatic screening of mass spectra. The method is demonstrated for a peptide standard and unknown proteins from a yeast lysate using all 6118 possible yeast open reading frames as a database. As judged by calculation of codon bias, low-abundance proteins were identified from the yeast lysate using this new method but not by traditional methods such as tandem mass spectrometry via data-dependent acquisition or mass mapping.     

Microorganism identification by mass spectrometry and protein database searches.

A method for rapid identification of microorganisms is presented, which exploits the wealth of information contained in prokaryotic genome and protein sequence databases. The method is based on determining the masses of a set of ions by MALDI TOF mass spectrometry of intact or treated cells. Subsequent correlation of each ion in the set to a protein, along with the organismic source of the protein, is performed by searching an Internet-accessible protein database. Convoluting the lists for all ions and ranking the organisms corresponding to matched ions results in the identification of the microorganism. The method has been successfully demonstrated on B. subtilis and E. coli, two organisms with completely sequenced genomes. The method has been also tested for identification from mass spectra of mixtures of microorganisms, from spectra of an organism at different growth stages, and from spectra originating at other laboratories. Experimental factors such as MALDI matrix preparation, spectral reproducibility, contaminants, mass range, and measurement accuracy on the database search procedure are addressed too. The proposed method has several advantages over other MS methods for microorganism identification.     

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.     

Increased identification of peptides by enhanced data processing of high-resolution MALDI TOF/TOF mass spectra prior to database searching

This paper presents application of sequential enhanced data processing procedures to high-resolution tandem mass spectra for identification of peptides using the Mascot database search algorithm. A strategy for (1) selection of fragment ion peaks from MS/MS spectra, (2) utilization of improved mass accuracy of the precursor ions, and (3) wavelet denoising of the mass spectra prior to fragment ion selection have been developed. The number of peptide identifications obtained using the enhanced processing was then compared with that obtained using software provided by the instrument manufacturer. Approximately 9000 MS/MS spectra acquired by the Applied Biosystems 4700 TOF/TOF MS instrument were used as a model data set. After application of the new processing, an increase of 33% unique peptides and 22% protein identifications with at least two unique peptides were found. The influence of the processing on the percentage of false positives, estimated by searching against a randomized database, was estimated to increase false positive identifications from 2.7 to 3.9%, which was still below the 5% error rate specified in the Mascot search. These data processing approaches increase the amount of information that can be extracted from LC-MS analysis without the necessity of additional experiments.     

Site-specific mass tagging with stable isotopes in proteins for accurate and efficient protein identification

Proteolytic peptide mass mapping as measured by mass spectrometry provides a major approach for the identification of proteins. A protein is usually identified by the best match between the measured and calculated m/z values of the proteolytic peptides. A unique identification is, however, heavily dependent upon the mass accuracy and sequence coverage of the fragment ions generated by peptide ionization. Without ultrahigh instrumental accuracy, it is possible to increase the specificity of the assignments of particular proteolytic peptides by the incorporation of selected amino acid residue(s) enriched with stable isotope(s) into the protein sequence. Here we report this novel method of generating residue-specific mass-tagged proteolytic peptides for accurate and efficient protein identification. Selected amino acids are labeled with 13C/15N/2H and incorporated into proteins in a sequence-specific manner during cell culturing. Each of these labeled amino acids carries a defined mass change encoded in its monoisotopic distribution pattern. Through their characteristic patterns, the peptides with mass tags can then be readily distinguished from other peptides in mass spectra. This method of identifying unique proteins can also be extended to protein complexes and will significantly increase data search specificity, efficiency, and accuracy for protein identifications.     

18O-labeling of N-glycosylation sites to improve the identification of gel-separated glycoproteins using peptide mass mapping and database searching

Peptide mass mapping using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry in conjunction with interrogation of sequence databases is a powerful tool for the identification of proteins. Glycosylated proteins often yield poor MALDI peptide maps due to shielding of proteolytic cleavage sites and the presence of modified peptides. Here we demonstrate that enzymatic removal of N-linked glycans with simultaneous partial (50%) 18O-labeling of glycosylated asparagine residues prior to proteolysis and MALDI peptide mass mapping can overcome these problems. As a result, more peptides are observed in MALDI spectra which, in turn, increases the specificity of subsequent database searches. Furthermore, the detection of a labeled peptide directly translates into partial sequence information as N-linked carbohydrates are exclusively attached to asparagine residues that form part of the NXS/T sequence. The mass of the formerly glycosylated peptide together with the NXS/T sequence pattern represents a discriminating criterion for database searching which, on average, increases the search specificity by a factor of 100. This procedure allows the unambiguous identification of glycoproteins that would otherwise require sequencing and, at the same time, enables the identification of N-glycosylation sites with higher sensitivity than previously possible.     

Open tubular immobilized metal ion affinity chromatography combined with MALDI MS and MS/MS for identification of protein phosphorylation sites

Protein phosphorylation is one of the most important known posttranslational modifications. Tandem mass spectrometry has become an important tool for mapping out the phosphorylation sites. However, when a peptide generated from the enzymatic or chemical digestion of a phosphoprotein is highly phosphorylated or contains many potential phosphorylation residues, phosphorylation site assignment becomes difficult. Separation and enrichment of phosphopeptides from a digest mixture is desirable and often a critical step for MS/MS-based site determination. In this work, we present a novel open tubular immobilized metal ion affinity chromatography (OT-IMAC) method, which is found to be more effective and reproducible for phosphopeptide enrichment, compared to a commonly used commercial product, Ziptip from Millipore. A strategy based on a combination of OT-IMAC, sequential dual-enzyme digestion, and matrix-assisted laser desorption/ionization (MALDI) quadrupole time-of-flight tandem mass spectrometry for phosphoprotein characterization is presented. It is shown that MALDI MS/MS with collision-induced dissociation can be very effective in generating fragment ion spectra containing rich structural information, which enables the identification of phosphorylation sites even from highly phosphorylated peptides. The applicability of this method for real world applications is demonstrated in the characterization and identification of phosphorylation sites of a Na(+)/H(+) exchanger fusion protein, His182, which was phosphorylated in vitro using the kinase Erk2.     

Applying in-silico retention index and mass spectra matching for identification of unknown metabolites in accurate mass GC-TOF mass spectrometry

One of the major obstacles in metabolomics is the identification of unknown metabolites. We tested constraints for reidentifying the correct structures of 29 known metabolite peaks from GCT premier accurate mass chemical ionization GC-TOF mass spectrometry data without any use of mass spectral libraries. Correct elemental formulas were retrieved within the top-3 hits for most molecular ion adducts using the "Seven Golden Rules" algorithm. An average of 514 potential structures per formula was downloaded from the PubChem chemical database and in-silico-derivatized using the ChemAxon software package. After chemical curation, Kovats retention indices (RI) were predicted for up to 747 potential structures per formula using the NIST MS group contribution algorithm and corrected for contribution of trimethylsilyl groups using the Fiehnlib RI library. When matching the range of predicted RI values against the experimentally determined peak retention, all but three incorrect formulas were excluded. For all remaining isomeric structures, accurate mass electron ionization spectra were predicted using the MassFrontier software and scored against experimental spectra. Using a mass error window of 10 ppm for fragment ions, 89% of all isomeric structures were removed and the correct structure was reported in 73% within the top-5 hits of the cases.     

Prediction of chromatographic retention and protein identification in liquid chromatography/mass spectrometry

Liquid chromatography coupled on- or off-line with mass spectrometry is rapidly advancing as a tool in proteomics capable of dealing with the inherent complexity in biology and complementing conventional approaches based on two-dimensional gel electrophoresis. Proteins can be identified by proteolytic digestion and peptide mass fingerprinting or by searching databases using short-sequence tags generated by tandem mass spectrometry. This paper shows that information on the chromatographic behavior of peptides can assist protein identification by peptide mass fingerprinting in liquid chromatography/mass spectrometry. This additional information is significant and already available at no extra experimental cost.     

IR-MALDI-mass analysis of electroblotted proteins directly from the membrane: comparison of different membranes, application to on-membrane digestion, and protein identification by database searching.

A systematic membrane study investigating different neutral, cationic derivatized, and hydrophilic PVDF membranes for their suitability to carry out on-membrane tryptic digestions and to obtain infrared-matrix-assisted laser desorption/ionization (IR-MALDI) mass information on the proteolytic fragments directly from the membrane was performed. Clearly, the Immobilon CD membrane (Millipore) showed the most reproducible results over a protein mass range from 12 to 66 kDa. Typical protein load to SDS-PAGE was in the 1-2 micrograms range. The protein amount used for enzymatic treatment was estimated to be in the low picomole range. Now both the intact protein mass and the masses of the specific proteolytic fragments are available directly from the membrane. Protein databases can be searched via search algorithms on the Internet using the information on the intact protein mass and the masses, e.g., of its tryptic fragments. Investigations were performed to search for neutral, enzyme-compatible IR matrixes which allow the enzymatic treatment (on-membrane digestion) while the membrane is matrix-incubated. Thiourea could be tolerated during enzymatic cleavage in solution in concentrations of 15 g/L and resulted in high-quality spectra of intact protein signals and turned, therefore, out to be the most promising candidate.     

Lookup peaks: a hybrid of de novo sequencing and database search for protein identification by tandem mass spectrometry

A powerful technique for peptide and protein identification is tandem mass spectrometry followed by database search using a program such as SEQUEST or Mascot. These programs, however, become slow and lose sensitivity when allowing nonspecific cleavages or peptide modifications. De novo sequencing and hybrid methods such as sequence tagging offer speed and robustness for wider searches, yet these approaches require better spectra with more complete and consecutive fragmentation and, hence, are less sensitive to low-abundance peptides. Here we describe a new hybrid method that retains the sensitivity of pure database search. The method uses a small amount of de novo analysis to identify likely b- and y-ion peaks--"lookup peaks"--that can then be used to extract candidate peptides from the database, with the number of candidates tunable to fit a computing budget. We describe a program called ByOnic that implements this method, and we benchmark ByOnic on several data sets, including one of mouse blood plasma spiked with low concentrations of recombinant human proteins. We demonstrate that ByOnic is more sensitive than sequence tagging and, indeed, more sensitive than the three most popular pure database search tools--SEQUEST, Mascot, and X!Tandem--on both the peptide and protein levels. On the mouse plasma samples, ByOnic consistently found spiked proteins missed by the other tools.     

Combination of LC/TOF-MS and LC/Ion trap MS/MS for the identification of diphenhydramine in sediment samples

Diphenhydramine (Benadryl) is a popular over-the-counter antihistaminic medication used for the treatment of allergies. After consumption, excretion, and subsequent discharge from wastewater treatment plants, it is possible that diphenhydramine will be found in environmental sediments due to its hydrophobicity (log P = 3.27). This work describes a methodology for the first unequivocal determination of diphenhydramine bound to environmental sediments. The drug is removed from the sediments by accelerated solvent extraction and then analyzed by liquid chromatography with a time-of-flight mass spectrometer and an ion trap mass spectrometer. This combination of techniques provided unequivocal identification and confirmation of diphenhydramine in two sediment samples. The accurate mass measurements of the protonated molecules were m/z 256.1703 and 256.1696 compared to the calculated mass of m/z 256.1701, resulting in errors of 0.8 and 2.3 ppm. This mass accuracy was sufficient to verify the elemental composition of diphenhydramine in each sample. Furthermore, accurate mass measurements of the primary fragment ion were obtained. This work is the first application of time-of-flight mass spectrometry for the identification of diphenhydramine and shows the accumulation of an over-the-counter medication in aquatic sediments at five different locations.     

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.     

Quantitation and accurate mass analysis of pesticides in vegetables by LC/TOF-MS

A quantitative method consisting of solvent extraction followed by liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS) analysis was developed for the identification and quantitation of three chloronicotinyl pesticides (imidacloprid, acetamiprid, thiacloprid) commonly used on salad vegetables. Accurate mass measurements within 3 ppm error were obtained for all the pesticides studied in various vegetable matrixes (cucumber, tomato, lettuce, pepper), which allowed an unequivocal identification of the target pesticides. Calibration curves covering 2 orders of magnitude were linear over the concentration range studied, thus showing the quantitative ability of TOF-MS as a monitoring tool for pesticides in vegetables. Matrix effects were also evaluated using matrix-matched standards showing no significant interferences between matrixes and clean extracts. Intraday reproducibility was 2-3% relative standard deviation (RSD) and interday values were 5% RSD. The precision (standard deviation) of the mass measurements was evaluated and it was less than 0.23 mDa between days. Detection limits of the chloronicotinyl insecticides in salad vegetables ranged from 0.002 to 0.01 mg/kg. These concentrations are equal to or better than the EU directives for controlled pesticides in vegetables showing that LC/TOF-MS analysis is a powerful tool for identification of pesticides in vegetables. Robustness and applicability of the method was validated for the analysis of market vegetable samples. Concentrations found in these samples were in the range of 0.02-0.17 mg/kg of vegetable.     

Low-attomole electrospray ionization MS and MS/MS analysis of protein tryptic digests using 20-microm-i.d. polystyrene-divinylbenzene monolithic capillary columns

This work explores the use of 20-microm-i.d. polymeric polystyrene-divinylbenzene monolithic nanocapillary columns for the LC-ESI-MS analysis of tryptic digest peptide mixtures. In contrast to the packing of microparticles, capillary columns were prepared, without the need of high pressure, in fused-silica capillaries, by thermally induced in situ copolymerization of styrene and divinylbenzene. The polymerization conditions and mobile-phase composition were optimized for chromatographic performance leading to efficiencies over 100000 plates/m for peptide separations. High mass sensitivity (approximately 10 amol of peptides) in the MS and MS/MS modes using an ion trap MS was found, a factor of up to 20-fold improvement over 75-microm-i.d. nanocolumns. A wide linear dynamic range (approximately 4 orders of magnitude) was achieved, and good run-to-run and column-to-column reproducibility of isocratic and gradient elution separations were found. As samples, both model proteins and tissue extracts were employed. Gradient nano-LC-MS analysis of a proteolytic digest of a tissue extract, equivalent to a sample size of approximately 1000 cells injected, is presented.     

MI-Pack: Increased confidence of metabolite identification in mass spectra by integrating accurate masses and metabolic pathways

Metabolite identification is of central importance to metabolomics as it provides the route to new knowledge. Automated identification of the thousands of peaks detected by high resolution mass spectrometry is currently not possible, largely due to the finite mass accuracy of the spectrometer and the complexity that one peak can be assigned to one or more empirical formula(e) and each formula maps to one or more metabolites. Biological samples are not, however, composed of random metabolite mixtures, but instead comprise of thousands of compounds related through specific chemical transformations. Here we evaluate if prior biological knowledge of these transformations can improve metabolite identification accuracy.Our identification algorithm - which uses metabolite interconnectivity from the KEGG database to putatively identify metabolites by name - is based on mapping an experimentally-derived empirical formula difference for a pair of peaks to a known empirical formula difference between substrate-product pairs derived from KEGG, termed transformation mapping (TM). To maximize identification accuracy, we also developed a novel semi-automated method to calculate a mass error surface associated with experimental peak-pair differences. The TM algorithm with mass error surface has been extensively validated using simulated and experimental datasets by calculating false positive and false negative rates of metabolite identification. Compared to the traditional identification method of database searching accurate masses on a single-peak-by-peak basis, the TM algorithm reduces the false positive rate of identification by > 4-fold, while maintaining a minimal false negative rate. The mass error surface, putative identification of metabolite names, and calculation of false positive and false negative rates collectively advance and improve upon related previous research on this topic [1, 2]. We conclude that inclusion of prior biological knowledge in the form of metabolic pathways provides one route to more accurate metabolite identification.     

Peptide electroextraction for direct coupling of in-gel digests with capillary LC-MS/MS for protein identification and sequencing

An electrophoretic method has been developed for the extraction of peptides following in-gel digests of SDS-PAGE separated proteins. During electroextraction, the peptides are trapped on a strong cation-exchange microcartridge, before analysis by capillary LC--ESI-tandem mass spectrometry. The spectra obtained by tandem mass spectrometry are searched directly against a protein database for identification of the protein from which the peptide originated. By minimizing surface exposure of the peptides during electroextraction, a reduction of the detection limits for protein identification is realized. The performance of the peptide electroextraction was compared directly with the standard extraction method for in-gel protein digests, using a standard dilution series of phosphorylase B and carbonic anhydrase, separated by SDS-PAGE. The lowest gel loading in which phosphorylase B was identified using the standard extraction method was 2.5 ng or 25 fmol, and the lowest gel loading in which phosphorylase B was identified using electroextraction was 1.25 ng or 12.5 fmol. The design of the microextraction cartridge allows for direct interfacing with capillary LC, which is crucial for maintaining low detection limits. Furthermore, this method can be used for high-throughput proteomics since it can be easily multiplexed and requires only voltage control and low pressures (approximately 15 psi) for operation. We believe that peptide electroextraction is a significant advance for identification of proteins separated by one-dimensional or two-dimensional gel electrophoresis, as it can be easily automated and requires less protein than conventional methods.     

BIA/MS of epitope-tagged peptides directly from E. coli lysate: multiplex detection and protein identification at low-femtomole to subfemtomole levels.

The use of biomolecular interaction analysis mass spectrometry to selectively isolate, detect, and characterize epitope-tagged peptides present in total cell lysates is demonstrated. Epitope-tagged tryptic peptides were captured via affinity interactions with either chelated Ni2+ or monoclonal antibodies and detected using surface plasmon resonance biomolecular interaction analysis (SPR-BIA). After SPR-BIA the tagged peptides were either eluted from the biosensor chips for mass spectrometric analysis or analyzed directly from the biosensor chip using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Protein database searches were performed using the masses of the tagged tryptic peptides, resulting in identification of the protein into which the epitope tag was inserted. Detection limits for both SPR-BIA and MALDI-TOF were at the low-femtomole to subfemtomole level. The approach represents a (multiplexed) high-sensitivity chip-based technique capable of identifying epitope-tagged proteins as they are present in complex mixtures.