Assessing matrix assisted laser desorption/ ionization-time of flight-mass spectrometry as a means of rapid embryo protein identification in rice.

Rice embryo proteins were separated by two-dimensional gel electrophoresis (2-DE). A total of 105 spots were digested with trypsin and the resultant peptides were analyzed by matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS). Raw mass spectra were fully-automatically processed and searched with selected monoisotopic masses against SWISS-PROT/TrEMBL and NCBInr databases. High quality mass spectra were obtained from 53 spots, of which 36 spots were identified including 29 not registered in databases. Fifty percent of the rice embryo proteins resolved in 2-DE could not be identified, indicating more efficient sample preparation techniques need to be developed in the future. At least four to five matching peptides were found to be essential for unambiguous identification of rice embryo proteins; peptide matching of less than four lead to ambiguous results. The suitability of peptide mass fingerprinting method as a means of rapid embryo protein identification in rice was discussed.     

Feasibility of SU-8-based capillary electrophoresis-electrospray ionization mass spectrometry microfluidic chips for the analysis of human cell lysates

Monolithically integrated, polymer (SU-8) microchips comprising an electrophoretic separation unit, a sheath flow interface and an ESI emitter were developed to improve the speed and throughput of proteomics analyses. Validation of the microchip method was performed based on peptide mass fingerprinting and single peptide sequencing of selected protein standards. Rapid, yet reliable identification of four biologically important proteins (cytochrome C, β-lactoglobulin, ovalbumin and BSA) confirmed the applicability of the SU-8 microchips to ambitious proteomic applications and allowed their use in the analysis of human muscle cell lysates. The characteristic tryptic peptides were easily separated with plate numbers approaching 10(6), and with peak widths at half height as low as 0.6 s. The on-chip sheath flow interface was also exploited to the introduction of an internal mass calibrant along with the sheath liquid which enabled accurate mass measurements by high-resolution Q-TOF MS. Additionally, peptide structural characterization and protein identification based on MS/MS fragmentation data of a single tryptic peptide was obtained using an ion trap instrument. Protein sequence coverages exceeding 50% were routinely obtained without any pretreatment of the proteolytic samples and a typical total analysis time from sampling to detection was well below ten minutes. In conclusion, monolithically integrated, dead-volume-free, SU-8 microchips proved to be a promising platform for fast and reliable analysis of complex proteomic samples. Good analytical performance of the microchips was shown by performing both peptide mass fingerprinting of complex cell lysates and protein identification based on single peptide sequencing.     

Improving protein identification from peptide mass fingerprinting through a parameterized multi-level scoring algorithm and an optimized peak detection

We have developed a new algorithm to identify proteins by means of peptide mass fingerprinting. Starting from the matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) spectra and environmental data such as species, isoelectric point and molecular weight, as well as chemical modifications or number of missed cleavages of a protein, the program performs a fully automated identification of the protein. The first step is a peak detection algorithm, which allows precise and fast determination of peptide masses, even if the peaks are of low intensity or they overlap. In the second step the masses and environmental data are used by the identification algorithm to search in protein sequence databases (SWISS-PROT and/or TrEMBL) for protein entries that match the input data. Consequently, a list of candidate proteins is selected from the database, and a score calculation provides a ranking according to the quality of the match. To define the most discriminating scoring calculation we analyzed the respective role of each parameter in two directions. The first one is based on filtering and exploratory effects, while the second direction focuses on the levels where the parameters intervene in the identification process. Thus, according to our analysis, all input parameters contribute to the score, however with different weights. Since it is difficult to estimate the weights in advance, they have been computed with a generic algorithm, using a training set of 91 protein spectra with their environmental data. We tested the resulting scoring calculation on a test set of ten proteins and compared the identification results with those of other peptide mass fingerprinting programs.     

Protein identification based on matrix assisted laser desorption/ionization-post source decay-mass spectrometry.

Due to its very short analysis time, its high sensitivity and ease of automation, matrix-assisted laser desorption/ionization (MALDI)-peptide mass fingerprinting has become the preferred method for identifying proteins of which the sequences are available in databases. However, many protein samples cannot be unambiguously identified by exclusively using their peptide mass fingerprints (e.g., protein mixtures, heavily posttranslationally modified proteins and small proteins). In these cases, additional sequence information is needed and one of the obvious choices when working with MALDI-mass spectrometry (MS) is to choose for post source decay (PSD) analysis on selected peptides. This can be performed on the same sample which is used for peptide mass fingerprinting. Although in this type of peptide analysis, fragmentation yields are very low and PSD spectra are often very difficult to interpret manually, we here report upon our five years of experience with the use of PSD spectra for protein identification in sequence (protein or expressed sequence tag (EST)) databases. The combination of peptide mass fingerprinting and PSD and analysis described here generally leads to unambiguous protein identification in the amount of material range generally encountered in most proteome studies.     

Modeling peptide mass fingerprinting data using the atomic composition of peptides

The peptide mass fingerprinting technique is commonly used for identifying proteins analyzed by mass spectrometry (MS) after enzymatic digestion. Our goal is to build a theoretical model that predicts the mass spectra of such digestion products in order to improve the identification and characterization of proteins using this technique. We present here the first step towards a full MS model. We have modeled MS spectra using the atomic composition of peptides and evaluated the influence that this composition may have on the MS signals. Peptides deduced from the SWISS-PROT protein sequence database were used for the calculation. To validate the model, the variability of the peptide mass distribution in SWISS-PROT was compared to two theoretical, randomly generated databases. Functions have been built that describe the behavior of the isotopic distribution according to the mass of peptides. The variability of these functions was analyzed. In particular, the influence of sulfur was studied. This work, while representing only a first step in the construction of an MS model, yields immediate practical results, as the new isotopic distribution model significantly improves peak detection in MS spectra used by protein identification algorithms.     

Using a Poisson approximation to predict the isotopic distribution of sulphur-containing peptides in a peptide-centric proteomic approach

Breen et al. (Electrophoresis 2000; 21: 2243) proposed a method for finding monoisotopic peptide peaks in mass spectra based on an approximation of the distribution of different isotopic variants of a peptide by a Poisson distribution. They developed the method using all protein sequences from the SWISS-PROT database. We investigate the suitability of this method to predict the isotopic distribution in an environment which enriches for peptides carrying sulphur. More specifically, we focus on mass spectra obtained by a COmbined FRActional DIagonal Chromatography (COFRADIC) approach, developed by Gevaert et al. (Nature Biotechnology 2003; 21: 566), targeting a specific subset of peptides, in this case the N-terminal peptides. One can therefore ask whether the original results of Breen et al. apply to spectra generated by the particular COFRADIC method. We investigate whether the proposed approximation holds for N-terminal peptides. We also evaluate whether ignoring sulphur atoms while developing the approximation, as proposed by Breen et al., does not increase the risk of missing monoisotopic peaks corresponding to sulphur-containing peptides. Finally, we check the sensitivity of the quality of the approximation to optimization criteria used in the development process. The results are not simply restricted to a COFRADIC setting but are also applicable more generally, for any method which enriches for sulphur-containing peptides.     

Novel procedure for the identification of proteins by mass fingerprinting combining two-dimensional electrophoresis with fluorescent SYPRO red staining

The fluorescent sensitive SYPRO Red dye was successfully employed to stain proteins in two-dimensional gels for protein identification by peptide mass fingerprinting. Proteins which are not chemically modified during the SYPRO Red staining process are well digested enzymatically in the gel and hence the resulting peptides can be efficiently eluted and analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). A SYPRO Red two-dimensional gel of a complex protein extract from Candida albicans was analysed by MALDI-TOF MS. The validity of SYPRO Red staining was demonstrated by identifying, via peptide mass fingerprinting, 10 different C. albicans proteins from a total of 31 selected protein spots. The peptide mass signal intensity, the number of matched peptides and the percentage of coverage of protein sequences from SYPRO Red-stained proteins were similar to or greater than those obtained in parallel with the modified silver protein gel staining. This work demonstrates that fluorescent SYPRO Red staining is compatible with the identification of proteins separated on polyacrylamide gel and that it can be used as an alternative to silver staining. As far as we know, this is the first report in which C. albicans proteins separated using 2-D gels have been identified by peptide mass fingerprinting. The improved technique described here should be very useful for carrying out proteomic studies.     

Algorithms for automatic interpretation of high resolution mass spectra

Automated interpretation of high-resolution mass spectra in a reliable and efficient manner represents a highly challenging computational problem. This work aims at developing methods for reducing a high-resolution mass spectrum into its monoisotopic peak list, and automatically assigning observed masses to known fragment ion masses if the protein sequence is available. The methods are compiled into a suite of data reduction algorithms which is called MasSPIKE (Mass Spectrum Interpretation and Kernel Extraction). MasSPIKE includes modules for modeling noise across the spectrum, isotopic cluster identification, charge state determination, separation of overlapping isotopic distributions, picking isotopic peaks, aligning experimental and theoretical isotopic distributions for estimating a monoisotopic peak's location, generating the monoisotopic mass list, and assigning the observed monoisotopic masses to possible protein fragments. The method is tested against a complex top-down spectrum of bovine carbonic anhydrase. Results of each of the individual modules are compared with previously published work.     

Generation of mass tags by the inherent electrochemistry of electrospray for protein mass spectrometry

We present herein a review of our work on the on-line electrochemical generation of mass tags toward cysteine residues in peptides and proteins. Taking advantage of the inherent electrochemical nature of electrospray generated from a microfabricated microspray emitter, selective probes for cysteine were developed and tested for on-line nonquantitative mass tagging of peptides and proteins. The nonquantitative aspect of the covalent tagging thus allows direct counting of free cysteines in the mass spectrum of a biomolecule through additional adduct peaks. Several substituted hydroquinones were investigated in terms of electrochemical properties, and their usefulness for on-line mass tagging during microspray experiments were assessed with L-cysteine, peptides, and intact proteins. Complementarily, numerical simulations were performed to properly understand the respective roles of mass transport, kinetics of electrochemical-chemical reactions, and design of the microspray emitter in the mass tagging overall efficiency. Finally, the on-line electrochemical tagging of cysteine residues was applied to the analysis of tryptic peptides of purified model proteins for protein identification through peptide mass fingerprinting.     

Diagnostic protein discovery using proteolytic peptide targeting and identification

Plasma protein profiling with mass spectrometry is currently being evaluated as a diagnostic tool for cancer and other diseases. These experiments consist of three steps: plasma protein fractionation, analysis with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS), and comparisons of the MALDI profiles to develop diagnostic fingerprints using bioinformatic techniques. While preliminary results appear promising in small sample groups, the method is limited by the sensitivity of MALDI-MS for intact proteins, the limited mass range of MALDI-MS, and difficulties associated with isolating individual proteins for identification to validate the diagnostic fingerprint. Here we present an alternative and improved method directed toward diagnostic protein discovery, which incorporates proteolytic peptide profiling, bioinformatic targeting of ion signals, and MALDI tandem mass spectrometry (MS/MS) peptide sequencing, rather than fingerprinting. Pancreatic cancer patients, pancreatitis patients, and controls are used as the model system. Profiling peptides after enzymatic digestion improves sensitivity and extends the accessible protein molecular weight range when compared to intact protein profiling. The first step is to extract and fractionate the proteins from plasma. Each fraction is digested with trypsin and subsequently analyzed by MALDI-MS. Rather than using bioinformatic analysis as a pattern-matching technique, peptides are targeted based on the disease to control peak intensity ratios measured in the averages of all mass spectra in each group and t-tests of the intensity of each individual peak. The targeted peptide ion signals are subsequently identified using MALDI-MS/MS in quadrupole-TOF and tandem-TOF instruments. This study found not only the proteins targeted and identified by a previous protein profiling experiment, but also detected additional proteins. These initial results are consistent with the known biology of pancreatic cancer or pancreatitis, but are not specific to those diseases.     

Iterative data analysis is the key for exhaustive analysis of peptide mass fingerprints from proteins separated by two-dimensional electrophoresis

Peptide mass fingerprinting (PMF) is a powerful tool for identification of proteins separated by two-dimensional electrophoresis (2-DE). With the increase in sensitivity of peptide mass determination it becomes obvious that even spots looking well separated on a 2-DE gel may consist of several proteins. As a result the number of mass peaks in PMFs increased dramatically leaving many unassigned after a first database search. A number of these are caused by experiment-specific contaminants or by neighbor spots, as well as by additional proteins or post-translational modifications. To understand the complete protein composition of a spot we suggest an iterative procedure based on large numbers of PMFs, exemplified by PMFs of 480 Helicobacter pylori protein spots. Three key iterations were applied: (1) Elimination of contaminant mass peaks determined by MS-Screener (a software developed for this purpose) followed by reanalysis; (2) neighbor spot mass peak determination by cluster analysis, elimination from the peak list and repeated search; (3) re-evaluation of contaminant peaks. The quality of the identification was improved and spots previously unidentified were assigned to proteins. Eight additional spots were identified with this procedure, increasing the total number of identified spots to 455.     

Tandem mass spectrometry methods for definitive protein identification in proteomics research

Optimized procedures have been developed for the addition of sulfonic acid groups to the N-termini of low-level peptides. These procedures have been applied to peptides produced by tryptic digestion of proteins that have been separated by two-dimensional (2-D) gel electrophoresis. The derivatized peptides were sequenced using matrix-assisted laser desorption/ionization (MALDI) post-source decay (PSD) and electrospray ionization-tandem mass spectrometry methods. Reliable PSD sequencing results have been obtained starting with sub-picomole quantities of protein. We estimate that the current PSD sequencing limit is about 300 fmol of protein in the gel. The PSD mass spectra of the derivatized peptides usually allow much more specific protein sequence database searches than those obtained without derivatization. We also report initial automated electrospray ionization-tandem mass spectrometry sequencing of these novel peptide derivatives. Both types of tandem mass spectra provide predictable fragmentation patterns for arginine-terminated peptides. The spectra are easily interpreted de novo, and they facilitate error-tolerant identification of proteins whose sequences have been entered into databases.     

Automated deconvolution and deisotoping of electrospray mass spectra

Electrospray ionization (ESI) of peptides and proteins produces a series of multiply charged ions with a mass/charge (m/z) ratio between 500 and 2000. The resulting mass spectra are crowded by these multiple charge values for each molecular mass and an isotopic cluster for each nominal m/z value. Here, we report a new algorithm simultaneously to deconvolute and deisotope ESI mass spectra from complex peptide samples based on their mass-dependent isotopic mean pattern. All signals corresponding to one peptide in the sample were reduced to one singly charged monoisotopic peak, thereby significantly reducing the number of signals, increasing the signal intensity and improving the signal-to-noise ratio. The mass list produced could be used directly for database searching. The developed algorithm also simplified interpretation of fragment ion spectra of multiply charged parent ions.     

High sequence-coverage detection of proteolytic peptides using a bis(terpyridine)ruthenium(II) complex

The use of a bis(terpyridine)ruthenium(ii) complex for peptide labeling (Ru-CO labeling) supplied high intensity peaks in mass spectrometry (MS) analysis that overcame the contribution of protonation or sodiated adduction to peptides. Ru-CO-labeled insulin A- and B-chains were detected simultaneously in comparable peak abundance by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The mass spectra of chymotryptic peptide fragments of Ru-CO-labeled insulin also simultaneously indicated both N-terminal fragment ions, and amino acid sequences were determined easily by matrix-assisted laser desorption/ionization post-source-decay (MALDI-PSD). The sensitivity of detecting Ru-CO-labeled peptide fragment ions was not dependent on the length or the sequences of the peptides. The Ru-CO labeling method was applied to tryptic myoglobin fragments. The method indicated that each fragment ion is detected nearly equal in abundance and enabled the desired fragment ions to be distinguished from matrix clusters or their in-source fragments in lower mass regions. The desired fragment ions can be found in the mass region higher than 670.70 (= Ru-CO). This method provided a high sequence coverage (96%) by peptide mass fingerprinting (PMF). Application of this method to a protein mixture (myoglobin, lysozyme and ubiquitin) successfully achieved high sequence-coverage characterization (>90%) of these proteins simultaneously.     

Technical innovations for the automated identification of gel-separated proteins by MALDI-TOF mass spectrometry

The combination of gel-based two-dimensional protein separations with protein identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) is the workhorse for the large-scale analyses of proteomes. Such high-throughput proteomic approaches require automation of all post-separation steps and the in-gel digest of proteins especially is often the bottleneck in the protein identification workflow. With the objective of reaching the same high performance of manual low-throughput in-gel digest procedures, we have developed a novel stack-type digestion device and implemented it into a commercially available robotic liquid handling system. This modified system is capable of performing in-gel digest, extraction of proteolytic peptides, and subsequent sample preparation for MALDI-MS without any manual intervention, but with a performance at least identical to manual procedures as indicated on the basis of the sequence coverage obtained by peptide mass fingerprinting. For further refinement of the automated protein identification workflow, we have also developed a motor-operated matrix application device to reproducibly obtain homogenous matrix preparation of high quality. This matrix preparation was found to be suitable for the automated acquisition of both peptide mass fingerprint and fragment ion spectra from the same sample spot, a prerequisite for high confidence protein identifications on the basis of peptide mass and sequence information. Due to the implementation of the stack-type digestion device and the motor-operated matrix application device, the entire platform works in a reliable, cost-effective, and sensitive manner, yielding high confidence protein identifications even for samples in the concentration range of as low as 100 fmol protein per gel plug.      

Improved peptide sequencing using isotope information inherent in tandem mass spectra

We demonstrate here the use of natural isotopic 'labels' in peptides to aid in the identification of peptides with a de novo algorithm. Using data from ion trap tandem mass spectrometric (MS/MS) analysis of 102 tryptic peptides, we have analyzed multiple series of peaks within LCQ MS/MS spectra that 'spell' peptide sequences. Isotopic peaks from naturally abundant isotopes are particularly prominent even after peak centroiding on y- and b-series ions and lead to increased confidence in the identification of the precursor peptides. Sequence analysis of the MS/MS data is accomplished by finding sequences and subsequences in a hierarchical manner within the spectra.     

Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research

Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.     

CHASE, a charge-assisted sequencing algorithm for automated homology-based protein identifications with matrix-assisted laser desorption/ionization time-of-flight post-source decay fragmentation data

We describe CHASE, a novel algorithm for automated de novo sequencing based on the mass spectrometric (MS) fragmentation analysis of tryptic peptides. This algorithm is used for protein identification from sequence similarity criteria and consists of four steps: (1) derivatization of tryptic peptides at the N-terminus with a negatively charged reagent; (2) post-source decay (PSD) fragmentation analysis of peptides; (3) interpretation of the mass peaks with the CHASE algorithm and reconstruction of the amino acid sequence; (4) transfer of these data to software for protein identifications based on sequence homology (Basic Local Alignment Search Tool, BLAST). This procedure deduced the correct amino acid sequence of tryptic peptide samples and also was able to deduce the correct sequence from difficult mass patterns and identify the amino acid sequence. This allows complete automation of the process starting from MS fragmentation of complex peptide mixtures at low concentration (e.g. from silver-stained gel bands) to identification of the protein. We also show that if PSD data are collected in a single spectrum (instead of the segmented mode offered by conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instrumentation), the complete workflow from MS-PSD data acquisition to similarity-based identification can be completely automated. This strategy may be applied to proteomic studies for protein identification based on automated de novo sequencing instead of MS or tandem MS patterns. We describe the Charge Assisted Sequencing Engine (CHASE) algorithm, the working protocol, the performance of the algorithm on spectra from MALDI-TOFMS and the data comparison between a TOF and a TOF-TOF instrument.