Identification of quantitative trait loci underlying proteome variation in human lymphoblastoid cells.

Population-based variability in protein expression patterns, especially in humans, is often observed but poorly understood. Moreover, very little is known about how interindividual genetic variation contributes to protein expression patterns. To begin to address this, we describe elements of technical and biological variations contributing to expression of 544 proteins in a population of 24 individual human lymphoblastoid cell lines that have been extensively genotyped as part of the International HapMap Project. We determined that expression levels of 10% of the proteins were tightly correlated to cell doubling rates. Using the publicly available genotypes for these lymphoblastoid cell lines, we applied a genetic association approach to identify quantitative trait loci associated with protein expression variation. Results identified 24 protein forms corresponding to 15 proteins for which genetic elements were responsible for >50% of the expression variation. The genetic variation associated with protein expression levels were located in cis with the gene coding for the transcript of the protein for 19 of these protein forms. Four of the genetic elements identified were coding non-synonymous single nucleotide polymorphisms that resulted in migration pattern changes in the two-dimensional gel. This is the first description of large scale proteomics analysis demonstrating the direct relationship between genome and proteome variations in human cells.

Systematic comparison of the human saliva and plasma proteomes.

The proteome of human salivary fluid has the potential to open new doors for disease biomarker discovery. A recent study to comprehensively identify and catalog the human ductal salivary proteome led to the compilation of 1166 proteins. The protein complexity of both saliva and plasma is large, suggesting that a comparison of these two proteomes will provide valuable insight into their physiological significance and an understanding of the unique and overlapping disease diagnostic potential that each fluid provides. To create a more comprehensive catalog of human salivary proteins, we have first compiled an extensive list of proteins from whole saliva (WS) identified through MS experiments. The WS list is thereafter combined with the proteins identified from the ductal parotid, and submandibular and sublingual (parotid/SMSL) salivas. In parallel, a core dataset of the human plasma proteome with 3020 protein identifications was recently released. A total of 1939 nonredundant salivary proteins were compiled from a total of 19 474 unique peptide sequences identified from whole and ductal salivas; 740 out of the total 1939 salivary proteins were identified in both whole and ductal saliva. A total of 597 of the salivary proteins have been observed in plasma. Gene ontology (GO) analysis showed similarities in the distributions of the saliva and plasma proteomes with regard to cellular localization, biological processes, and molecular function, but revealed differences which may be related to the different physiological functions of saliva and plasma. The comprehensive catalog of the salivary proteome and its comparison to the plasma proteome provides insights useful for future study, such as exploration of potential biomarkers for disease diagnostics.

Calculation of the isoelectric point of tryptic peptides in the pH 3.5-4.5 range based on adjacent amino acid effects.

Current algorithms for the calculation of peptide or protein pI, based on the charge associated with individual amino acids, can calculate pI values to within +/-0.2 pI units. Here, we present a new pI calculation algorithm that takes into account the effect of adjacent amino acids on the pI value. The algorithm accounts for the effect of adjacent amino acids+/-3 residues away from a charged aspartic or glutamic acid, as well as effects on the free C terminus, and applies a correction term to the corresponding pK values. The correction increments are derived from a 5000-peptide training set using a genetic optimization approach. The accuracy of the new pI values obtained with this method approaches the error associated with the manufacture of the IPG strip (<+/-0.03 pI units). The approach is demonstrated for cytosolic cell extracts derived from the breast-cancer cell line DU4475, and from membrane preparations from human lung-tissue samples. One potential application of a more highly accurate pI calculation is data filtering of MS/MS outputs that will allow for more complex database searches including gene finding, and validation, and detection of coding single-nucleotide polymorphisms in their expressed form.

Automated proteomics of E. coli via top-down electron-transfer dissociation mass spectrometry.

Electron-transfer dissociation (ETD) has recently been introduced as a fragmentation method for peptide and protein analysis. Unlike collisionally induced dissociation (CID), fragmentation by ETD occurs randomly along the peptide backbone. With the use of the sequences determined from the protein termini and the parent protein mass, intact proteins can be unambiguously identified. Because of the fast kinetics of these reactions, top-down proteomics can be performed using ETD in a linear ion trap mass spectrometer on a chromatographic time scale. Here we demonstrate the utility of ETD in high-throughput top-down proteomics using soluble extracts of E. coli. Development of a multidimensional fractionation platform, as well as a custom algorithm and scoring scheme specifically designed for this type of data, is described. The analysis resulted in the robust identification of 322 different protein forms representing 174 proteins, comprising one of the most comprehensive data sets assembled on intact proteins to date.

Whole genome searching with shotgun proteomic data: applications for genome annotation.

High-throughput genome sequencing continues to accelerate the rate at which complete genomes are available for biological research. Many of these new genome sequences have little or no genome annotation currently available and hence rely upon computational predictions of protein coding genes. Evidence of translation from proteomic techniques could facilitate experimental validation of protein coding genes, but the techniques for whole genome searching with MS/MS data have not been adequately developed to date. Here we describe GENQUEST, a novel method using peptide isoelectric focusing and accurate mass to greatly reduce the peptide search space, making fast, accurate, and sensitive whole human genome searching possible on common desktop computers. In an initial experiment, almost all exonic peptides identified in a protein database search were identified when searching genomic sequence. Many peptides identified exclusively in the genome searches were incorrectly identified or could not be experimentally validated, highlighting the importance of orthogonal validation. Experimentally validated peptides exclusive to the genomic searches can be used to reannotate protein coding genes. GENQUEST represents an experimental tool that can be used by the proteomics community at large for validating computational approaches to genome annotation.

Detection and validation of non-synonymous coding SNPs from orthogonal analysis of shotgun proteomics data.

Orthogonal analysis of amino acid substitutions as a result of SNPs in existing proteomic datasets provides a critical foundation for the emerging field of population-based proteomics. Large-scale proteomics datasets, derived from shotgun tandem MS analysis of complex cellular protein mixtures, contain many unassigned spectra that may correspond to alternate alleles coded by SNPs. The purpose of this work was to identify tandem MS spectra in LC-MS/MS shotgun proteomics datasets that may represent coding nonsynonymous SNPs (nsSNP). To this end, we generated a tryptic peptide database created from allelic information found in NCBI's dbSNP. We searched this database with tandem MS spectra of tryptic peptides from DU4475 breast tumor cells that had been fractioned by pI in the first-dimension and reverse-phase LC in the second dimension. In all we identified 629 nsSNPs, of which 36 were of alternate SNP alleles not found in the reference NCBI or IPI protein databases. Searches for SNP-peptides carry a high risk of false positives due both to mass shifts caused by modifications and because of multiple representations of the same peptide within the genome. In this work, false positives were filtered using a novel peptide pI prediction algorithm and characterized using a decoy database developed by random substitution of similarly sized reference peptides. Secondary validation by sequencing of corresponding genomic DNA confirmed the presence of the predicted SNP in 8 of 10 SNP-peptides. This work highlights that the usefulness of interpreting unassigned spectra as polymorphisms is highly reliant on the ability to detect and filter false positives.

Minimizing back exchange in 18O/16O quantitative proteomics experiments by incorporation of immobilized trypsin into the initial digestion step.

Differential labeling of peptides via the use of the 18O-water proteolytic labeling method has been widely adopted for quantitative shotgun proteomics studies due to its simplicity and low reagent costs. In this report, the use of immobilized trypsin in the initial digestion step, in addition to the initial digestion step, is explored as a means to minimize postlabeling back exchange of 18O-labeled peptides into the 16O form when multidimensional peptide separation methods (here, isoelectric focusing of peptides) are incorporated into the sample workflow. Examples are shown with a mixture of standard proteins and a sample from an ongoing clinical proteomics study.

A comparison of immobilized pH gradient isoelectric focusing and strong-cation-exchange chromatography as a first dimension in shotgun proteomics.

Recently, we have developed a high-resolution two-dimensional separation strategy for the analysis of complex peptide mixtures. This methodology employs isoelectric focusing of peptides on immobilized pH gradient (IPG) gels in the first dimension, followed by reversed-phase chromatography in the second dimension, and subsequent tandem mass spectrometry analysis. The traditional approach to this mixture problem employs strong-cation-exchange (SCX) chromatography in the first dimension. Here, we present a direct comparison of these two first-dimensional techniques using complex protein samples derived from the testis of Rattus norvegicus. It was found that the use of immobilized pH gradients (narrow range pH 3.5-4.5) for peptide separation in the first dimension yielded 13% more protein identifications than the optimized off-line SCX approach (employing the entire pI range of the sample). In addition, the IPG technique allows for a much more efficient use on mass spectrometer analysis time. Separation of a tryptic digest derived from a rat testis sample on a narrow range pH gradient (over the 3.5-4.5 pH range) yielded 7626 and 2750 peptides and proteins, respectively. Peptide and protein identification was performed with high confidence using SEQUEST in combination with a data filtering program employing pI and statistical based functions to remove false-positives from the data.

Immobilized pH gradient isoelectric focusing as a first-dimension separation in shotgun proteomics.

Shotgun proteomics, where a tryptic digest of a complex proteome sample is directly analyzed by either single dimensional or multidimensional liquid chromatography tandem mass spectrometry, has gained acceptance in the proteomics community at large and is widely used in core facilities. Here we review the development in our laboratory of an alternative first-dimension separation technique for shotgun proteomics, immobilized pH gradient isoelectric focusing (IPG-IEF). The key advantages of the technology over other multidimensional separation formats (simplicity, high resolution, and high sensitivity) are discussed. The concept of using peptide pI to filter large shotgun proteomics datasets generated by the IPG-IEF technique to minimize false positives and negatives is also introduced. Finally, an account of the comparison of the technique with the established gold standard for multidimensional separation of peptides, strong cation exchange chromatography, is presented, along with the prospects for the use of peptide pI along with accurate mass measurement for the identification of peptides.

Potential for false positive identifications from large databases through tandem mass spectrometry.

The biomedical research community at large is increasingly employing shotgun proteomics for large-scale identification of proteins from enzymatic digests. Typically, the approach used to identify proteins and peptides from tandem mass spectral data is based on the matching of experimentally generated tandem mass spectra to the theoretical best match from a protein database. Here, we present the potential difficulties of using such an approach without statistical consideration of the false positive rate, especially when large databases, as are encountered in eukaryotes are considered. This is illustrated by searching a dataset generated from a multidimensional separation of a eukaryotic tryptic digest against an in silico generated random protein database, which generated a significant number of positive matches, even when previously suggested score filtering criteria are used.

Immobilized pH gradients as a first dimension in shotgun proteomics and analysis of the accuracy of pI predictability of peptides.

In this work, we demonstrate the potential use of immobilized pH gradient isoelectric focusing as a first dimension in shotgun proteomics. The high resolving power and resulting reduction in matrix ionization effects due to analyzing peptides with almost the exact same physiochemical properties, represents a significant improvement in performance over traditional strong cation-exchange first-dimensional analysis associated with the shotgun proteomics approach. For example, using this technology, we were able to identify more than 6000 peptides and > 1200 proteins from the cytosolic fraction of Escherichia coli from approximately 10 microg of material analyzed in the second-dimensional liquid chromatography-tandem mass spectrometry experiment. Sample loads on the order of 1 mg can be resolved to 0.25 isoelectric point (pI) units, which make it possible to analyze organisms with significantly larger genomes/proteomes. Accurate pI prediction can then be employed using currently available algorithms to very effectively filter data for peptide/protein identification, and thus lowering the false-positive rate for cross-correlation-based peptide identification algorithms. By simplifying the protein mixture problem to tryptic peptides, the effect of specific amino acids on pI prediction can be evaluated as a function of their position in the peptide chain.

Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification.

Here we present the theoretical and experimental evaluation of peptide isoelectric point as a method to aid in the identification of peptides from complex mixtures. Predicted pI values were found to match closely the experimentally obtained data, resulting in the development of a unique filter that lowers the effective false positive rate for peptide identification. Due to the reduction of the false positive rate, the cross-correlation parameters Xcorr and deltaCn from the SEQUEST program can be lowered resulting in 25% more peptide identifications. This approach was successfully applied to analysis of the soluble fraction of the E. coli proteome, where 417 proteins were identified from 1022 peptides using just 20 microg of material.

An alternative to tandem mass spectrometry: isoelectric point and accurate mass for the identification of peptides.

The traditional approach to the identification of peptides in complex biological samples integrally involves the use of tandem mass spectrometry to generate a unique fragmentation pattern in order to accurately assign its identity to a particular protein. In this article we describe the theoretical basis for a new paradigm for the identification of peptides and proteins. This methodology employs the use of accurate mass and peptide isoelectric point (pI) as identification criteria, and represents a change in focus from current tandem mass spectrometry-dominated approaches. A mathematical derivation of the false positive rate associated with accurate mass and pI measurements is presented to demonstrate the utility of the technique. The equations for calculation of the experimental false positive rate allow for the determination of the validity of the data. The false positive rate issue examined in detail here is not restricted to accurate mass-based approaches, but also has application to the tandem mass spectrometry community as well. The theoretical proteomes of Escherichia coli and Rattus norvegicus are used to evaluate the efficacy of this approach. The power of the technique is demonstrated by analyzing a series of peptides with the same monoisotopic masses but with differing isoelectric points. Finally, the speed of algorithm when combined with the experimental peptide analysis has the potential to rapidly accelerate the protein identification process.

Synthesis/degradation ratio mass spectrometry for measuring relative dynamic protein turnover.

One of the major unanswered questions in quantitative proteomics is that of dynamic protein turnover in the cell. Here we present a new approach to quantitative proteomics that measures the relative dynamic turnover of proteins in cellular systems. In this approach, termed synthesis/degradation ratio mass spectrometry, stable isotope labeling is employed to calculate a relative synthesis/degradation ratio that reflects the relative rate at which 13C is incorporated into individual proteins in the cell. This synthesis/degradation ratio calculation is based on a Poisson distribution model that is designed to support high-throughput analysis. Protein separation and analysis is accomplished by utilizing one-dimensional SDS-PAGE gel electrophoresis followed by cutting the gel into a series of bands for in-gel digestion. The resulting peptide mixtures are analyzed via solid-phase MALDI LC-MS and LC-MS/MS using a tandem time-of-flight mass spectrometer. A portion of the soluble protein fraction from an E. coli K-12 strain was analyzed with synthesis/degradation ratios varying from approximately 0.1 to 4.4 for a variety of different proteins. Unlike other quantitative techniques, synthesis/degradation ratio mass spectrometry requires only a single cell culture to obtain useful biological information about the processes occurring inside a cell. This technique is highly amenable to shotgun proteomics-based approaches and thus should allow relative turnover measurements for whole proteomes in the future.

Fourier-transform mass spectrometry for automated fragmentation and identification of 5-20 kDa proteins in mixtures.

When presented with a mixture of intact proteins, electrospray ionization with Fourier-transform mass spectrometry (ESI-FTMS) has the capability to obtain direct fragmentation information from isolated ions. However, the automation of this capability has not been achieved to date. We have developed software for unattended acquisition of protein tandem mass spectrometry (MS/MS) data and batch processing of the resulting files for identification of whole proteins. Mixtures of both protein standards (8-29 kDa) and Methanococcus jannaschii cytosolic proteins (up to six components + 20 kDa) were infused via an autosampler, and MS/MS data were acquired without human intervention. The acquisition software recognizes ESI charge state patterns, generates protein-specific isolation waveforms on-the-fly, and fragments ions using two different infrared laser times. In addition to protein standards, five wild-type proteins (7-14 kDa) were identified automatically with 100% sequence coverage from the M. jannaschii database. The software underpins a measurement platform for sample-dependent acquisition of MS/MS data for whole proteins, a critical step to realize proteomics with 100% sequence coverage in a higher throughput setting.

Processing complex mixtures of intact proteins for direct analysis by mass spectrometry.

For analysis of intact proteins by mass spectrometry (MS), a new twist to a two-dimensional approach to proteome fractionation employs an acid-labile detergent instead of sodium dodecyl sulfate during continuous-elution gel electrophoresis. Use of this acid-labile surfactant (ALS) facilitates subsequent reversed-phase liquid chromatography (RPLC) for a net two-dimensional fractionation illustrated by transforming thousands of intact proteins from Saccharomyces cerevisiae to mixtures of 5-20 components (all within approximately 5 kDa of one another) for presentation via electrospray ionization (ESI) to a Fourier transform MS (FTMS). Between 3 and 13 proteins have been detected directly using ESI-FTMS (or MALDI-TOF), and the fractionation showed a peak capacity of approximately 400 between 0 and 70 kDa. A probability-based identification was made automatically from raw MS/MS data (obtained using a quadrupole-FTMS hybrid instrument) for one protein that differed from that predicted in a yeast database of approximately 19,000 protein forms. This ALS-PAGE/RPLC approach to proteome processing ameliorates the "front end" problem that accompanies direct analysis of whole proteins and assists the future realization of protein identification with 100% sequence coverage in a high-throughput format.