Mass spectral characterization of a protein-nucleic acid photocrosslink

A photocrosslink between basic fibroblast growth factor (bFGF155) and a high affinity ssDNA oligonucleotide was characterized by positive ion electrospray ionization mass spectrometry (ESIMS). The DNA was a 61-mer oligonucleotide photoaptamer bearing seven bromodeoxyuridines, identified by in vitro selection. Specific photocrosslinking of the protein to the oligonucleotide was achieved by 308 nm XeCl excimer laser excitation. The cross-linked protein nucleic acid complex was proteolyzed with trypsin. The resulting peptide crosslink was purified by PAGE, eluted, and digested by snake venom phosphodiesterase/alkaline phosphatase. Comparison of the oligonucleotide vs. the degraded peptide crosslink by high performance liquid chromatography coupled to an electrospray ionization triple quadrupole mass spectrometer showed a single ion unique to the crosslinked material. Sequencing by collision induced dissociation (MS/MS) on a triple quadrupole mass spectrometer revealed that this ion was the nonapeptide TGQYKLGSK (residues 130-138) crosslinked to a dinucleotide at Tyr133. The MS/MS spectrum indicated sequential fragmentation of the oligonucleotide to uracil covalently attached to the nonapeptide followed by fragmentation of the peptide bonds. Tyr133 is located within the heparin binding pocket, suggesting that the in vitro selection targeted this negative ion binding region of bFGF155.     

Protein identification from product ion spectra of peptides validated by correlation between measured and predicted elution times in liquid chromatography/mass spectrometry

Reversed-phase liquid chromatography (LC) directly coupled with electrospray-tandem mass spectrometry (MS/MS) is a successful choice to obtain a large number of product ion spectra from a complex peptide mixture. We describe a search validation program, ScoreRidge, developed for analysis of LC-MS/MS data. The program validates peptide assignments to product ion spectra resulting from usual probability-based searches against primary structure databases. The validation is based only on correlation between the measured LC elution time of each peptide and the deduced elution time from the amino acid sequence assigned to product ion spectra obtained from the MS/MS analysis of the peptide. Sufficient numbers of probable assignments gave a highly correlative curve. Any peptide assignments within a certain tolerance from the correlation curve were accepted for the following arrangement step to list identified proteins. Using this data validation program, host protein candidates responsible for interaction with human hepatitis B virus core protein were identified from a partially purified protein mixture. The present simple and practical program complements protein identification from usual product ion search algorithms and reduces manual interpretation of the search result data. It will lead to more explicit protein identification from complex peptide mixtures such as whole proteome digests from tissue samples.     

A Heuristic method for assigning a false-discovery rate for protein identifications from Mascot database search results

MS/MS and database searching has emerged as a valuable technology for rapidly analyzing protein expression, localization, and post-translational modifications. The probability-based search engine Mascot has found widespread use as a tool to correlate tandem mass spectra with peptides in a sequence database. Although the Mascot scoring algorithm provides a probability-based model for peptide identification, the independent peptide scores do not correlate with the significance of the proteins to which they match. Herein, we describe a heuristic method for organizing proteins identified at a specified false-discovery rate using Mascot-matched peptides. We call this method PROVALT, and it uses peptide matches from a random database to calculate false-discovery rates for protein identifications and reduces a complex list of peptide matches to a nonredundant list of homologous protein groups. This method was evaluated using Mascot-identified peptides from a Trypanosoma cruzi epimastigote whole-cell lysate, which was separated by multidimensional LC and analyzed by MS/MS. PROVALT was then compared with the two traditional methods of protein identification when using Mascot, the single peptide score and cumulative protein score methods, and was shown to be superior to both in regards to the number of proteins identified and the inclusion of lower scoring nonrandom peptide matches.     

Label-free quantitative analysis of one-dimensional PAGE LC/MS/MS proteome: application on angiotensin II-stimulated smooth muscle cells secretome

A widely used method for protein identification couples prefractionation of protein samples by one-dimensional (1D) PAGE with LC/MS/MS. We developed a new label-free quantitative algorithm by combining measurements of spectral counting, ion intensity, and peak area on 1D PAGE-based proteomics. This algorithm has several improvements over other label-free quantitative algorithms: (i) Errors in peak detection are reduced because the retention time is based on each LC/MS/MS run and actual precursor m/z. (ii) Detection sensitivity is increased because protein quantification is based on the combination of peptide count, ion intensity, and peak area. (iii) Peak intensity and peak area are calculated in each LC/MS/MS run for all slices from 1D PAGE for every single identified protein and visualized as a Western blot image. The sensitivity and accuracy of this algorithm were demonstrated by using standard curves (17.4 fmol to 8.7 pmol), complex protein mixtures (30 fmol to 1.16 pmol) of known composition, and spiked protein (34.8 fmol to 17.4 pmol) in complex proteins. We studied the feasibility of this approach using the secretome of angiotensin II (Ang II)-stimulated vascular smooth muscle cells (VSMCs). From the VSMC-conditioned medium, 629 proteins were identified including 212 putative secreted proteins. 26 proteins were differently expressed in control and Ang II-stimulated VSMCs, including 18 proteins not previously reported. Proteins related to cell growth (CYR61, protein NOV, and clusterin) were increased, whereas growth arrest-specific 6 (GAS6) and growth/differentiation factor 6 were decreased by Ang II stimulation. Ang II-stimulated changes of plasminogen activator inhibitor-1, GAS6, cathepsin B, and periostin were validated by Western blot. In conclusion, a novel label-free quantitative analysis of 1D PAGE-LC/MS/MS-based proteomics has been successfully applied to the identification of new potential mediators of Ang II action and may provide an alternative to traditional protein staining methods.     

Rapid and sensitive identification of major histocompatibility complex class I-associated tumor peptides by Nano-LC MALDI MS/MS

Identification of major histocompatibility complex (MHC)-associated peptides recognized by T-lymphocytes is a crucial prerequisite for the detection and manipulation of specific immune responses in cancer, viral infections, and autoimmune diseases. Unfortunately immunogenic peptides are less abundant species present in highly complex mixtures of MHC-extracted material. Most peptide identification strategies use microcapillary LC coupled to nano-ESI MS/MS in a challenging on-line approach. Alternatively MALDI PSD analysis has been applied for this purpose. We report here on the first off-line combination of nanoscale (nano) LC and MALDI TOF/TOF MS/MS for the identification of naturally processed MHC peptide ligands. These peptides were acid-eluted from human leukocyte antigen (HLA)-A2, HLA-A3, and HLA-B/-C complexes separately isolated from a renal cell carcinoma cell lysate using HLA allele-specific antibodies. After reversed-phase HPLC, peptides were further fractionated via nano-LC. This additional separation step provided a substantial increase in the number of detectable candidate species within the complex peptide pools. MALDI MS/MS analysis on nano-LC-separated material was then sufficiently sensitive to rapidly identify more than 30 novel HLA-presented peptide ligands. Peptide sequences contained perfect anchor amino acid residues described previously for HLA-A2, HLA-A3, and HLA-B7. The most promising candidate for a T-cell epitope is an HLA-B7-binding nonamer peptide derived from the tumor-associated gene NY-BR-16. To demonstrate the sensitivity of our approach we characterized peptides binding to HLA-C molecules that are usually expressed at the cell surface at approximately only 10% the levels of HLA-A or HLA-B. In fact, multiple renal cell carcinoma peptides were identified that contained anchor amino acid residues of HLA-Cw5 and HLA-Cw7. We conclude that the nano-LC MALDI MS/MS approach is a sensitive tool for the rapid and automated identification of MHC-associated tumor peptides.     

Comparative evaluation of label-free SINQ normalized spectral index quantitation in the central proteomics facilities pipeline

Normalized spectral index quantification was recently presented as an accurate method of label‐free quantitation, which improved spectral counting by incorporating the intensities of peptide MS/MS fragment ions into the calculation of protein abundance. We present SINQ, a tool implementing this method within the framework of existing analysis software, our freely available central proteomics facilities pipeline (CPFP). We demonstrate, using data sets of protein standards acquired on a variety of mass spectrometers, that SINQ can rapidly provide useful estimates of the absolute quantity of proteins present in a medium‐complexity sample. In addition, relative quantitation of standard proteins spiked into a complex lysate background and run without pre‐fractionation produces accurate results at amounts above 1 fmol on column. We compare quantitation performance to various precursor intensity‐ and identification‐based methods, including the normalized spectral abundance factor (NSAF), exponentially modified protein abundance index (emPAI), MaxQuant, and Progenesis LC‐MS. We anticipate that the SINQ tool will be a useful asset for core facilities and individual laboratories that wish to produce quantitative MS data, but lack the necessary manpower to routinely support more complicated software workflows. SINQ is freely available to obtain and use as part of the central proteomics facilities pipeline, which is released under an open‐source license.     

A cost-benefit analysis of multidimensional fractionation of affinity purification-mass spectrometry samples

Affinity purification coupled to mass spectrometry (AP-MS) is gaining widespread use for the identification of protein-protein interactions. It is unclear, however, whether typical AP sample complexity is limiting for the identification of all protein components using standard one-dimensional LC-MS/MS. Multidimensional sample separation is useful for reducing sample complexity prior to MS analysis and increases peptide and protein coverage of complex samples. Here, we monitored the effects of upstream protein or peptide separation techniques on typical mammalian AP-MS samples, generated by FLAG affinity purification of four baits with different biological functions and/or subcellular distribution. As a first separation step, we employed SDS-PAGE, strong cation exchange LC, or reversed-phase LC at basic pH. We also analyzed the benefits of using an instrument with a faster scan rate, the new TripleTOF 5600 mass spectrometer. While all multidimensional approaches yielded a clear increase in spectral counts, the increase in unique peptides and additional protein identification was modest and came at the cost of increased instrument and handling time. The use of a high duty-cycle instrument achieved similar benefits without these drawbacks. An increase in spectral counts is beneficial when data analysis methods relying on spectral counts, including Significance Analysis of INTeractome (SAINT), are used.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

Protein fragmentation via liquid chromatography-quadrupole time-of-flight mass spectrometry: the use of limited sequence information in structural characterization

Fragmentation and "top-down" sequencing of intact proteins by mass spectrometry (MS) is most commonly performed by infusion of protein solutions into Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers. However, the high cost of this instrumentation, coupled with the need to infuse "clean" solutions (lacking standard biological buffers), limits broad application of this technique. The current study describes an alternative approach to top-down sequencing using in-source fragmentation on quadrupole time-of-flight (Q-Tof) instrumentation coupled with reversed-phase liquid chromatography (LC). Application of this technique to purified recombinant samples yielded protein fragments during routine LC-MS analysis. The presence of multiple N- and C-terminal fragments allowed localization of structural modifications without proteolytic digestion. The method was extended to complex samples by using LC conditions that provided high-resolution protein separation. Utility of the method was illustrated by real-time monitoring of protein modifications occurring in reconstituted apoptosomes. These experiments illustrate that intact protein mass and limited sequence information can be obtained simultaneously on an LC timescale. This approach will allow a wide variety of laboratories to routinely apply top-down sequencing to problems in structural characterization, protein purification, and biomarker identification.     

Improving large-scale proteomics by clustering of mass spectrometry data

Tandem mass spectrometry (MS/MS), coupled with liquid chromatography (LC), is a powerful tool for the analysis and comparison of complex protein and peptide mixtures. However, the extremely large amounts of data that result from the process are very complex and difficult to analyze. We show how the clustering of similar spectra from multiple LC-MS/MS runs can help in data management and improve the analysis of complex peptide mixtures. The major effect of spectrum clustering is the reduction of the huge amounts of data to a manageable size. As a result, analysis time is shorter and more data can be stored for further analysis. Furthermore, spectrum quality improvement allows the identification of more peptides with greater confidence, the comparison of complex peptide mixtures is facilitated, and the entire proteomics project is presented in concise form. Pep-Miner is an advanced software tool that implements these clustering-based applications. It proved useful in several comparative proteomics projects involving lung cancer cells and various other cell types. In one of these projects, Pep-Miner reduced 517 000 spectra to 20 900 clusters and identified 2518 peptides derived from 830 proteins. Clustering and identification lasted less than two hours on an IBM Thinkpad T23 computer (laptop). Pep-Miner's unique properties make it a very useful tool for large-scale shotgun proteomics projects.     

High throughput screening of disulfide‐containing proteins in a complex mixture

The formation of disulfide bonds between cysteine residues is crucial for the stabilization of native protein structures and, thus, determination of disulfide linkages is an important facet of protein structural characterization. Nonetheless, the identification of disulfide bond linkages remains a significant analytical challenge, particularly in large proteins with complex disulfide patterns. Herein, we have developed a new LC/MS strategy for rapid screening of disulfides in an intact protein mixture after a straightforward reduction step with tris(2‐carboxyethyl)phosphine. LC/MS analysis of reduced and nonreduced protein mixtures quickly revealed disulfide‐containing proteins owing to a 2 Da mass increase per disulfide reduction and, subsequently, the total number of disulfide bonds in the intact proteins could be determined. We have demonstrated the effectiveness of this method in a protein mixture composed of both disulfide‐containing and disulfide‐free proteins. Our method is simple (no need for proteolytic digestion, alkylation, or the removal of reducing agents prior to MS analysis), high throughput (fast on‐line LC/MS analysis), and reliable (no S–S scrambling), underscoring its potential as a rapid disulfide screening method for proteomics applications.     

Effect of mass spectrometric parameters on peptide and protein identification rates for shotgun proteomic experiments on an LTQ-orbitrap mass analyzer

The success of a shotgun proteomic experiment relies heavily on the performance and optimization of both the LC and the MS systems. Despite this, little consideration has, so far, been given to the importance of evaluating and optimizing the MS instrument settings during data‐dependent acquisition mode. Moreover, during data‐dependent acquisition, the users have to decide and choose among various MS parameters and settings, making a successful analysis even more challenging. We have systematically investigated and evaluated the effect of enabling and disabling the preview mode for FTMS scan, the number of microscans per MS/MS scan, the number of MS/MS events, the maximum ion injection time for MS/MS, and the automatic gain control target value for MS and MS/MS events on protein and peptide identification rates on an LTQ‐Orbitrap using the Saccharomyces cerevisiae proteome. Our investigations aimed to assess the significance of each MS parameter to improve proteome analysis and coverage. We observed that higher identification rates were obtained at lower ion injection times i.e. 50–150 ms, by performing one microscan and 12–15 MS/MS events. In terms of ion population, optimal automatic gain control target values were at 5×10⁵–1×10⁶ ions for MS and 3×10³–1×10⁴ ions for MS/MS. The preview mode scan had a minimal effect on identification rates. Using optimized MS settings, we identified 1038 (±2.3%) protein groups with a minimum of two peptide identifications and an estimated false discovery rate of ～1% at both peptide and protein level in a 160‐min LC‐MS/MS analysis.     

Protein identification assisted by the prediction of retention time in liquid chromatography/tandem mass spectrometry

Two-dimensional liquid chromatography (2D-LC) coupled on-line with electrospray ionization tandem mass spectrometry (2D-LC-ESI-MS/MS) is a new platform for analysis and identification of proteome. Peptides are separated by 2D-LC and then performed MS/MS analysis by tandem MS/MS. The MS/MS data are searched against database for protein identification. In one 2D-LC-ESI-MS/MS run, we obtained not only the structural information of peptides directly from MS/MS, but also the retention time of peptides eluted from LC. Information on the chromatographic behavior of peptides can assist protein identification in the new platform for proteomics. The retention time of the matching peptides of the identified protein was predicted by the hydrophobic contribute of each amino acid on reversed-phase liquid chromatography (RPLC). By using this strategy proteins were identified by four types of information: peptide mass fingerprinting (PMF), sequence query, and MS/MS ions searched and the predicted retention time. This additional information obtained from LC could assist protein identification with no extra experimental cost.     

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

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

Differentially isotope-coded N-terminal protein sulphonation: combining protein identification and quantification

Most proteomic labelling technologies intend to improve protein quantification and/or facilitate (de novo) peptide sequencing. We present here a novel stable-isotope labelling method to simultaneously identify and quantify protein components in complex mixtures by specifically derivatizing the N-terminus of proteins with 4-sulphophenyl isothiocyanate (SPITC). Our approach combines protein identification with quantification through differential isotope-coded labelling at the protein N-terminus prior to digestion. The isotope spacing of 6 Da (unlabelled vs. six-fold 13C-labelled tag) between derivatized peptide pairs enables the detection on different MS platforms (MALDI and ESI). Optimisation of the reaction conditions using SPITC was performed on three model proteins. Improved detection of the N-terminally derivatized peptide compared to the native analogue was observed in negative-ion MALDI-MS. Simpler fragmentation patterns compared to native peptides facilitated protein identification. The 13C-labelled SPITC resulted in convenient peptide pair spacing without isotopic overlap and hence facilitated relative quantification by MALDI-TOF/TOF and LC-ESI-MS/MS. The combination of facilitated identification and quantification achieved by differentially isotope-coded N-terminal protein tagging with light/heavy SPITC represents, to our knowledge, a new approach to quantitative proteomics.     

Complementary analysis of the Mycobacterium tuberculosis proteome by two-dimensional electrophoresis and isotope-coded affinity tag technology

Classical proteomics combined two-dimensional gel electrophoresis (2-DE) for the separation and quantification of proteins in a complex mixture with mass spectrometric identification of selected proteins. More recently, the combination of liquid chromatography (LC), stable isotope tagging, and tandem mass spectrometry (MS/MS) has emerged as an alternative quantitative proteomics technology. We have analyzed the proteome of Mycobacterium tuberculosis, a major human pathogen comprising about 4,000 genes, by (i) 2-DE and mass spectrometry (MS) and by (ii) the isotope-coded affinity tag (ICAT) reagent method and MS/MS. The data obtained by either technology were compared with respect to their selectivity for certain protein types and classes and with respect to the accuracy of quantification. Initial datasets of 60,000 peptide MS/MS spectra and 1,800 spots for the ICAT-LC/MS and 2-DE/MS methods, respectively, were reduced to 280 and 108 conclusively identified and quantified proteins, respectively. ICAT-LC/MS showed a clear bias for high M(r) proteins and was complemented by the 2-DE/MS method, which showed a preference for low M(r) proteins and also identified cysteine-free proteins that were transparent to the ICAT-LC/MS method. Relative quantification between two strains of the M. tuberculosis complex also revealed that the two technologies provide complementary quantitative information; whereas the ICAT-LC/MS method quantifies the sum of the protein species of one gene product, the 2-DE/MS method quantifies at the level of resolved protein species, including post-translationally modified and processed polypeptides. Our data indicate that different proteomic technologies applied to the same sample provide complementary types of information that contribute to a more complete understanding of the biological system studied.     

Increased proteome coverage by combining PAGE and peptide isoelectric focusing: Comparative study of gel‐based separation approaches

The in‐depth analysis of complex proteome samples requires fractionation of the sample into subsamples prior to LC‐MS/MS in shotgun proteomics experiments. We have established a 3D workflow for shotgun proteomics that relies on protein separation by 1D PAGE, gel fractionation, trypsin digestion, and peptide separation by in‐gel IEF, prior to RP‐HPLC‐MS/MS. Our results show that applying peptide IEF can significantly increase the number of proteins identified from PAGE subfractionation. This method delivers deeper proteome coverage and provides a large degree of flexibility in experimentally approaching highly complex mixtures by still relying on protein separation according to molecular weight in the first dimension.     

MALDI‐TOF and nESI Orbitrap MS/MS identify orthogonal parts of the phosphoproteome

Phosphorylation is a reversible posttranslational protein modification which plays a pivotal role in intracellular signaling. Despite extensive efforts, phosphorylation site mapping of proteomes is still incomplete motivating the exploration of alternative methods that complement existing workflows. In this study, we compared tandem mass spectrometry (MS/MS) on matrix assisted laser desorption/ionization time‐of‐flight (MALDI‐TOF) and nano‐electrospray ionization (nESI) Orbitrap instruments with respect to their ability to identify phosphopeptides from complex proteome digests. Phosphopeptides were enriched from tryptic digests of cell lines using Fe‐IMAC column chromatography and subjected to LC‐MS/MS analysis. We found that the two analytical workflows exhibited considerable orthogonality. For instance, MALDI‐TOF MS/MS favored the identification of phosphopeptides encompassing clear motif signatures for acidic residue directed kinases. The extent of orthogonality of the two LC‐MS/MS systems was comparable to that of using alternative proteases such as Asp‐N, Arg‐C, chymotrypsin, Glu‐C and Lys‐C on just one LC‐MS/MS instrument. Notably, MALDI‐TOF MS/MS identified an unexpectedly high number and percentage of phosphotyrosine sites (～20% of all sites), possibly as a direct consequence of more efficient ionization. The data clearly show that LC‐MALDI MS/MS can be a useful complement to LC‐nESI MS/MS for phosphoproteome mapping and particularly so for acidic and phosphotyrosine containing peptides.