Top-down proteomics for rapid identification of intact microorganisms

We apply MALDI-TOF/TOF mass spectrometry for the rapid and high-confidence identification of intact Bacillus spore species. In this method, fragment ion spectra of whole (undigested) protein biomarkers are obtained without the need for biomarker prefractionation, digestion, separation, and cleanup. Laser-induced dissociation (unimolecular decay) of higher mass (>5 kDa) precursor ions in the first TOF analyzer is followed by reacceleration and subsequent high-resolution mass analysis of the resulting sequence-specific fragments in a reflectron TOF analyzer. In-house-developed software compares an experimental MS/MS spectrum with in silico-generated tandem mass spectra from all protein sequences, contained in a proteome database, with masses within a preset range around the precursor ion mass. A p-value, the probability that the observed matches between experimental and in silico-generated fragments occur by chance, is computed and used to rank the database proteins to identify the most plausible precursor protein. By inference, the source microorganism is then identified on the basis of the identification of individual, unique protein biomarker(s). As an example, intact Bacillus atrophaeus and Bacillus cereus spores, either pure or in mixtures, were unambiguously identified by this method after fragmenting and identifying individual small, acid-soluble spore proteins that are specific for each species. Factors such as experimental mass accuracy and number of detected fragment ions, precursor ion charge state, and sequence-specific fragmentation have been evaluated with the objective of extending the approach to other microorganisms. MALDI-TOF/TOF-MS in a lab setting is an efficient tool for in situ confirmation/verification of initial microorganism identification.     

MALDI analysis of Bacilli in spore mixtures by applying a quadrupole ion trap time-of-flight tandem mass spectrometer

A novel ion trap time-of-flight hybrid mass spectrometer (qIT-TOF MS) has been applied for peptide sequencing in proteolytic digests generated from spore mixtures of Bacilli. The method of on-probe solubilization and in situ proteolytic digestion of small, acid-soluble spore proteins has been recently developed in our laboratory, and microorganism identification in less than 20 min was accomplished. In this study, tryptic peptides were generated in situ from complex spore mixtures of B. subtilis 168, B. globigii, B. thuringiensis subs. Kurstaki, and B. cereus T, respectively. MALDI analysis of bacterial peptides generated was performed with an average mass resolving power of 6200 and a mass accuracy of up to 10 ppm using a trap-TOF tandem configuration. Precursor ions of interest were usually selected and stored in the quadrupole ion trap with their complete isotope distribution by choosing a window of +/- 2 Da. Sequence-specific information on isolated protonated peptides was gained via tandem MS experiments with an average mass resolving power of 4450 for product ion analysis, and protein and bacterial sources were identified by database searching.     

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

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

A hypergeometric probability model for protein identification and validation using tandem mass spectral data and protein sequence databases

We present a new probability-based method for protein identification using tandem mass spectra and protein databases. The method employs a hypergeometric distribution to model frequencies of matches between fragment ions predicted for peptide sequences with a specific (M + H)+ value (at some mass tolerance) in a protein sequence database and an experimental tandem mass spectrum. The hypergeometric distribution constitutes null hypothesis-all peptide matches to a tandem mass spectrum are random. It is used to generate a score characterizing the randomness of a database sequence match to an experimental tandem mass spectrum and to determine the level of significance of the null hypothesis. For each tandem mass spectrum and database search, a peptide is identified that has the least probability of being a random match to the spectrum and the corresponding level of significance of the null hypothesis is determined. To check the validity of the hypergeometric model in describing fragment ion matches, we used chi2 test. The distribution of frequencies and corresponding hypergeometric probabilities are generated for each tandem mass spectrum. No proteolytic cleavage specificity is used to create the peptide sequences from the database. We do not use any empirical probabilities in this method. The scores generated by the hypergeometric model do not have a significant molecular weight bias and are reasonably independent of database size. The approach has been implemented in a database search algorithm, PEP_PROBE. By using a large set of tandem mass spectra derived from a set of peptides created by digestion of a collection of known proteins using four different proteases, a false positive rate of 5% is demonstrated.     

Whole protein dissociation in a quadrupole ion trap: identification of an a priori unknown modified protein

A protein mixture derived from a whole cell lysate fraction of Saccharomyces cerevisiae, which contains roughly 19 proteins, has been analyzed to identify an a priori unknown modified protein using a quadrupole ion trap tandem mass spectrometer. Collection of the experimental data was facilitated by collision-induced dissociation and ion/ion proton-transfer reactions in multistage mass spectrometry procedures. Ion/ion reactions were used to manipulate charge states of both parent ions and product ions for the purpose of concentrating charge into the parent ion of interest and to reduce the product ion charge states for determination of product ion mass and abundance. The identification of the protein was achieved by matching the uninterpreted product ion spectrum against protein sequence databases with varying degrees of annotation, coupled with a scoring scheme weighted for the relative abundances of the experimentally observed product ions and the frequency of fragmentations occurring at preferential sites. The protein was identified to be an acetylated yeast heat shock protein, HS12_Yeast (11.6 kDa), with the initiating methionine residue removed. This constitutes the first example of the identification of an a priori unknown protein that is not present in an annotated protein database using a "top-down" approach with a quadrupole ion trap. This example illustrates the utility of relatively low cost instrumentation with modest mass analysis characteristics for the identification of modified proteins without recourse to enzymatic digestion. It also illustrates how experimental data can be used interactively with protein databases when the modified protein of interest is not initially present in the database.     

MultiTag: multiple error-tolerant sequence tag search for the sequence-similarity identification of proteins by mass spectrometry

The characterization of proteomes by mass spectrometry is largely limited to organisms with sequenced genomes. To identify proteins from organisms with unsequenced genomes, database sequences from related species must be employed for sequence-similarity protein identifications. Peptide sequence tags (Mann, 1994) have been used successfully for the identification of proteins in sequence databases using partially interpreted tandem mass spectra of tryptic peptides. We have extended the ability of sequence tag searching to the identification of proteins whose sequences are yet unknown but are homologous to known database entries. The MultiTag method presented here assigns statistical significance to matches of multiple error-tolerant sequence tags to a database entry and ranks alignments by their significance. The MultiTag approach has the distinct advantage over other sequence-similarity approaches of being able to perform sequence-similarity identifications using only very short (2-4) amino acid residue stretches of peptide sequences, rather than complete peptide sequences deduced by de novo interpretation of tandem mass spectra. This feature facilitates the identification of low abundance proteins, since noisy and low-intensity tandem mass spectra can be utilized.     

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.     

MALDI quadrupole time-of-flight mass spectrometry: a powerful tool for proteomic research

A MALDI QqTOF mass spectrometer has been used to identify proteins separated by one-dimensional or two-dimensional gel electrophoresis at the femtomole level. The high mass resolution and the high mass accuracy of this instrument in both MS and MS/MS modes allow identification of a protein either by peptide mass fingerprinting of the protein digest or from tandem mass spectra acquired by collision-induced dissociation of individual peptide precursors. A peptide mass map of the digest and tandem mass spectra of multiple peptide precursor ions can be acquired from the same sample in the course of a single experiment. Database searching and acquisition of MS and MS/MS spectra can be combined in an interactive fashion, increasing the information value of the analytical data. The approach has demonstrated its usefulness in the comprehensive characterization of protein in-gel digests, in the dissection of complex protein mixtures, and in sequencing of a low molecular weight integral membrane protein. Proteins can be identified in all types of sequence databases, including an EST database. Thus, MALDI QqTOF mass spectrometry promises to have remarkable potential for advancing proteomic research.     

Cross-correlation algorithm for calculation of peptide molecular weight from tandem mass spectra

We have developed an approach to identify the molecular weight of a peptide ion directly from its corresponding tandem mass spectrum using a cross-correlation function. We have shown that the monoisotopic molecular weight can be calculated for approximately 90% of tandem mass spectra identified from tryptic digests of complex protein mixtures. The accuracy of the calculated monoisotopic masses was dependent on the resolution and mass accuracy of the spectra analyzed, but was typically <0.25 amu for linear ion trap mass spectra. The ability to calculate accurate monoisotopic molecular weights for low-resolution ion trap data should significantly improve both the speed and performance of database searches for which typical mass accuracies of approximately 3 amu are employed. In addition, this strategy can also be used to identify the precursor ion for tandem mass spectra acquired using large ion selection windows in data-independent collision-activated dissociation and has the potential to identify multiplexed tandem mass spectra.     

Microorganism identification by matrix-assisted laser/desorption ionization mass spectrometry and model-derived ribosomal protein biomarkers

An improved data analysis method is described for rapid identification of intact microorganisms from MALDI-TOF-MS data. The method makes no use of mass spectral fingerprints. Instead, a microorganism database is automatically generated that contains biomarker masses derived from ribosomal protein sequences and a model of N-terminal Met loss. We quantitatively validate the method via a blind study that seeks to identify microorganisms with known ribosomal protein sequences. We also include in the database microorganisms with incompletely known sets of ribosomal proteins to test the specificity of the method. With an optimal MALDI protocol, and at the 95% confidence level, microorganisms represented in the database with 20 or more biomarkers (i.e., those with complete or nearly completely sequenced genomes) are correctly identified from their spectra 100% of the time, with no incorrect identifications. Microorganisms with seven or less biomarkers (i.e., incompletely sequenced genomes) are either not identified or misidentified. Robustness with respect to variations in sample preparation protocol and mass analysis protocol is demonstrated by collecting data with two different matrixes and under two different ion-mode configurations. Statistical analysis suggests that, even without further improvement, the method described here would successfully scale up to microorganism databases with roughly 1000 microorganisms. The results demonstrate that microorganism identification based on proteome data and modeling can perform as well as methods based on mass spectral fingerprinting.     

Mass defect labeling of cysteine for improving peptide assignment in shotgun proteomic analyses

A method for improving the identification of peptides in a shotgun proteome analysis using accurate mass measurement has been developed. The improvement is based upon the derivatization of cysteine residues with a novel reagent, 2,4-dibromo-(2'-iodo)acetanilide. The derivitization changes the mass defect of cysteine-containing proteolytic peptides in a manner that increases their identification specificity. Peptide masses were measured using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron mass spectrometry. Reactions with protein standards show that the derivatization of cysteine is rapid and quantitative, and the data suggest that the derivatized peptides are more easily ionized or detected than unlabeled cysteine-containing peptides. The reagent was tested on a 15N-metabolically labeled proteome from M. maripaludis. Proteins were identified by their accurate mass values and from their nitrogen stoichiometry. A total of 47% of the labeled peptides are identified versus 27% for the unlabeled peptides. This procedure permits the identification of proteins from the M. maripaludis proteome that are not usually observed by the standard protocol and shows that better protein coverage is obtained with this methodology.     

Identification of bacteriophage MS2 coat protein from E. coli lysates via ion trap collisional activation of intact protein ions

Collisional activation of the intact MS2 viral capsid protein with subsequent ion/ion reactions has been used to identify the presence of this virus in E. coli lysates. Tandem ion trap mass spectrometry experiments on the +7, +8, and +9 charge states, followed by ion/ion reactions, provided the necessary sequence tag information (and molecular weight data) needed for protein identification via database searching. The most directly informative structural information is obtained from those charge states that produce a series of product ions arising from fragmentation at adjacent residues. The formation of these product ions via dissociation at adjacent amino acid residues depends greatly on the charge state of the parent ion. Database searching of the charge-state-specific sequence tags was performed by two different search engines: the ProteinInfo program from the Protein information Retrieval On-line World Wide Web Lab or PROWL and the TagIdent program from the ExPASy molecular biology server. These search engines were used in conjunction with the sequence tag information generated via collisional activation of the intact viral coat protein. These programs were used to evaluate the feasibility of generating sequence tags from collisional activation of intact multiply charged protein ions in a quadrupole ion trap.     

High-sensitivity electron capture dissociation tandem FTICR mass spectrometry of microelectrosprayed peptides

Electron capture dissociation (ECD) has previously been shown by other research groups to result in greater peptide sequence coverage than other ion dissociation techniques and to localize labile posttranslational modifications. Here, ECD has been achieved for 10-13-mer peptides microelectrosprayed from 10 nM (10 fmol/microL) solutions and for tryptic peptides from a 50 nM unfractionated digest of a 28-kDa protein. Tandem Fourier transform ion cyclotron resonance (FTICR) mass spectra contain fragment ions corresponding to cleavages at all possible peptide backbone amine bonds, except on the N-terminal side of proline, for substance P and neurotensin. For luteinizing hormone-releasing hormone, all but two expected backbone amine bond cleavages are observed. The tandem FTICR mass spectra of the tryptic peptides contain fragment ions corresponding to cleavages at 6 of 12 (1545.7-Da peptide) and 8 of 21 (2944.5-Da peptide) expected backbone amine bonds. The present sensitivity is 200-2000 times higher than previously reported. These results show promise for ECD as a tool to produce sequence tags for identification of peptides in complex mixtures available only in limited amounts, as in proteomics.     

Role of accurate mass measurement (+/- 10 ppm) in protein identification strategies employing MS or MS/MS and database searching.

We describe the impact of advances in mass measurement accuracy, +/- 10 ppm (internally calibrated), on protein identification experiments. This capability was brought about by delayed extraction techniques used in conjunction with matrix-assisted laser desorption ionization (MALDI) on a reflectron time-of-flight (TOF) mass spectrometer. This work explores the advantage of using accurate mass measurement (and thus constraint on the possible elemental composition of components in a protein digest) in strategies for searching protein, gene, and EST databases that employ (a) mass values alone, (b) fragment-ion tagging derived from MS/MS spectra, and (c) de novo interpretation of MS/MS spectra. Significant improvement in the discriminating power of database searches has been found using only molecular weight values (i.e., measured mass) of > 10 peptide masses. When MALDI-TOF instruments are able to achieve the +/- 0.5-5 ppm mass accuracy necessary to distinguish peptide elemental compositions, it is possible to match homologous proteins having > 70% sequence identity to the protein being analyzed. The combination of a +/- 10 ppm measured parent mass of a single tryptic peptide and the near-complete amino acid (AA) composition information from immonium ions generated by MS/MS is capable of tagging a peptide in a database because only a few sequence permutations > 11 AA's in length for an AA composition can ever be found in a proteome. De novo interpretation of peptide MS/MS spectra may be accomplished by altering our MS-Tag program to replace an entire database with calculation of only the sequence permutations possible from the accurate parent mass and immonium ion limited AA compositions. A hybrid strategy is employed using de novo MS/MS interpretation followed by text-based sequence similarity searching of a database.     

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.     

Web and database software for identification of intact proteins using "top down" mass spectrometry

For the identification and characterization of proteins harboring posttranslational modifications (PTMs), a "top down" strategy using mass spectrometry has been forwarded recently but languishes without tailored software widely available. We describe a Web-based software and database suite called ProSight PTM constructed for large-scale proteome projects involving direct fragmentation of intact protein ions. Four main components of ProSight PTM are a database retrieval algorithm (Retriever), MySQL protein databases, a file/data manager, and a project tracker. Retriever performs probability-based identifications from absolute fragment ion masses, automatically compiled sequence tags, or a combination of the two, with graphical rendering and browsing of the results. The database structure allows known and putative protein forms to be searched, with prior or predicted PTM knowledge used during each search. Initial functionality is illustrated with a 36-kDa yeast protein identified from a processed cell extract after automated data acquisition using a quadrupole-FT hybrid mass spectrometer. A +142-Da delta(m) on glyceraldehyde-3-phosphate dehydrogenase was automatically localized between Asp90 and Asp192, consistent with its two cystine residues (149 and 153) alkylated by acrylamide (+71 Da each) during the gel-based sample preparation. ProSight PTM is the first search engine and Web environment for identification of intact proteins (https://prosightptm.scs.uiuc.edu/).     

Utility of accurate mass tags for proteome-wide protein identification

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

Mass spectrometric methods for generation of protein mass database used for bacterial identification

The availability of a suitable database is critical in a proteomic approach for bacterial identification by mass spectrometry (MS). The major limitation of the present public proteome database is the lack of extensive low-mass bacterial protein entries with masses experimentally verified for most bacteria. Here, we present a method based on mass spectrometry to create protein mass tables specifically tailored for bacterial identification. Several issues related to the detection of bacterial proteins for the purpose of database creation are addressed. Three species of bacteria, namely, Escherichia coli, Bacillus megaterium, and Citrobacter freundii, which can be found in the ambient environment, were chosen for this study. Direct matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS analysis of each bacterial extract reveals 20-29 protein components in the mass range from 2000 to 20,000 Da. HPLC fractionation of bacterial extracts followed by off-line MALDI-TOF analysis of individual fractions detects 156-423 components. Analysis of the extracts by HPLC/electrospray ionization MS shows the number of detectable proteins in the range of 46-59. Although a number of components were common to the three detection schemes employed, some unique components were found using each of these techniques. In addition, for E. coli where a large proteome database exists in the public domain, a number of masses detected by the mass spectrometric methods do not match with the proteome database. Compared to the public proteome database, the mass tables generated in this work are demonstrated to be more useful for bacterial identification in an application where the bacteria of interest have limited protein entries in the public database. The implication of this work for future development of a comprehensive mass database is discussed.     

MASPIC: intensity-based tandem mass spectrometry scoring scheme that improves peptide identification at high confidence

Algorithmic search engines bridge the gap between large tandem mass spectrometry data sets and the identification of proteins associated with biological samples. Improvements in these tools can greatly enhance biological discovery. We present a new scoring scheme for comparing tandem mass spectra with a protein sequence database. The MASPIC (Multinomial Algorithm for Spectral Profile-based Intensity Comparison) scorer converts an experimental tandem mass spectrum into a m/z profile of probability and then scores peak lists from potential candidate peptides using a multinomial distribution model. The MASPIC scoring scheme incorporates intensity, spectral peak density variations, and m/z error distribution associated with peak matches into a multinomial distribution. The scoring scheme was validated on two standard protein mixtures and an additional set of spectra collected on a complex ribosomal protein mixture from Rhodopseudomonas palustris. The results indicate a 5-15% improvement over Sequest for high-confidence identifications. The performance gap grows as sequence database size increases. Additional tests on spectra from proteinase-K digest data showed similar performance improvements demonstrating the advantages in using MASPIC for studying proteins digested with less specific proteases. All these investigations show MASPIC to be a versatile and reliable system for peptide tandem mass spectral identification.     

Use of deuterium-labeled lysine for efficient protein identification and peptide de novo sequencing

Here, we describe a method for protein identification and de novo peptide sequencing. Through in vivo cell culturing, the deuterium-labeled lysine residue (Lys-d4) introduces a 4-Da mass tag at the carboxyl terminus of proteolytic peptides when cleaved by certain proteases. The 4-Da mass difference between the unlabeled and the deuterated lysine assigns a mass signature to all lysine-containing peptides in any pool of proteolytic peptides for protein identification directly through peptide mass mapping. Furthermore, it was used to distinguish between N- and C-terminal fragments for accurate assignments of daughter ions in tandem MS/MS spectra for sequence assignment. This technique simplifies the labeling scheme and the interpretation of the MS/MS spectra by assigning different series of fragment ions correctly and easily and is very useful in de novo peptide sequencing. We have also successfully implemented this approach to the analysis of protein mixtures derived from the human proteome.