SEARCH · PubMed Health

Results for “Shotgun proteomics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2005

The continuing evolution of shotgun proteomics.

Shotgun proteomics has emerged as a powerful approach for the analysis of complex protein mixtures, including biofluids, tissues, cells, organelles or protein complexes. Having evolved from the integration of chromatography and mass spectrometry, innovations in sample preparation, multidimensional chromatography, mass spectrometry and proteomic informatics continually facilitate, enable and challenge shotgun proteomics. As a result, shotgun proteomics continues to evolve and enable new areas of biological research, and is beginning to impact human disease diagnosis and therapeutic intervention.

Chromatography, High Pressure Liquid↗

PubMed2005

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.

Chromatography, Ion Exchange↗

PubMed2006

Phosphorylation of B14.5a subunit from bovine heart complex I identified by titanium dioxide selective enrichment and shotgun proteomics.

Shotgun proteomics was used to study the steady phosphorylation state of NADH:ubiquinone oxidoreductase (complex I) subunits from bovine heart mitochondria. A total tryptic digestion of enzymatically active complex I was performed, and the resulting peptide mixture was subjected to phosphopeptide enrichment by the use of titanium dioxide (TiO2). The phosphopeptide-enriched fraction was separated and analyzed with nanoscale reverse-phase HPLC-ESI-MS/MS in single information-dependent acquisition. Hence two phosphorylated complex I subunits were detected: 42 kDa and B14.5a. Phosphorylation of 42-kDa subunit at Ser-59 has already been determined with fluorescent phosphoprotein-specific gel staining and mass spectrometry (Schilling, B., Aggeler, R., Schulenberg, B., Murray, J., Row, R. H., Capaldi, R. A., and Gibson, B. W. (2005) Mass spectrometric identification of novel phosphorylation site in subunit NDUFA10 of bovine mitochondrial complex I. FEBS Lett. 579, 2485-2490). In our work, this finding was confirmed using a non-gel-based approach. In addition, we report novel phosphorylation on B14.5a nuclear encoded subunit. We demonstrated evidence of the phosphorylation site at Ser-95 residue by collision-induced dissociation experiments on three different molecular ions of two tryptic phosphopeptides of B14.5a.

Amino Acid Sequence↗

PubMed2006

Comparison of a Salmonella typhimurium proteome defined by shotgun proteomics directly on an LTQ-FT and by proteome pre-fractionation on an LCQ-DUO.

Shotgun proteomics is rapidly becoming one of the most efficient and popular tools to examine protein expression in cells. Numerous laboratories now have a wide array of low- and high-performance mass spectrometry instrumentation necessary to complete proteome-wide projects. Often these laboratories have time and financial constraints that prohibit all projects from being conducted on high-performance state-of-the-art mass spectrometers. Here, we compare shotgun proteomic results using a direct 'lyse, digest and analyse' approach on a high-performance mass spectrometer (i.e. the LTQ-FT) with the results from a much lower-performance instrument (i.e. the LCQ-DUO) where, for the latter, various traditional protein pre-fractionation steps and gas-phase fractionation were used to increase the proteome coverage. Our results demonstrate that shotgun proteomic analyses conducted on the lower-performance LCQ-DUO mass spectrometer could adequately characterize a PhoP constitutive strain of Salmonella typhimurium if proteome pre-fractionation steps and gas-phase fractionation were included.

Chromatography, High Pressure Liquid↗

PubMed2003

A correlation algorithm for the automated quantitative analysis of shotgun proteomics data.

Quantitative shotgun proteomic analyses are facilitated using chemical tags such as ICAT and metabolic labeling strategies with stable isotopes. The rapid high-throughput production of quantitative "shotgun" proteomic data necessitates the development of software to automatically convert mass spectrometry-derived data of peptides into relative protein abundances. We describe a computer program called RelEx, which uses a least-squares regression for the calculation of the peptide ion current ratios from the mass spectrometry-derived ion chromatograms. RelEx is tolerant of poor signal-to-noise data and can automatically discard nonusable chromatograms and outlier ratios. We apply a simple correction for systematic errors that improves the accuracy of the quantitative measurement by 32 +/- 4%. Our automated approach was validated using labeled mixtures composed of known molar ratios and demonstrated in a real sample by measuring the effect of osmotic stress on protein expression in Saccharomyces cerevisiae.

Algorithms↗

PubMed2006

Shotgun proteomics using the iTRAQ isobaric tags.

Shotgun proteomic methods involving isobaric tagging of peptides enable high-throughput proteomic analysis. iTRAQ reagents allow simultaneous identification and quantitation of proteins in four different samples using tandem mass spectrometry (MS). In this article, we provide a brief description of proteome analysis using iTRAQ reagents and review the current applications of these reagents in proteomic studies. We also compare different aspects of protein identification including protein sequence coverage and proteome coverage obtained using iTRAQ reagents with those using other shotgun proteomic techniques. We briefly discuss the issue of isotope purity correction in measured peak areas during protein quantitation using iTRAQ reagents. Finally, we conclude with some of the current challenges in MS-based proteomic analysis that are limiting protein identifications obtained by different shotgun proteomic methods.

Animals↗

PubMed2005

Interpretation of shotgun proteomic data: the protein inference problem.

The shotgun proteomic strategy based on digesting proteins into peptides and sequencing them using tandem mass spectrometry and automated database searching has become the method of choice for identifying proteins in most large scale studies. However, the peptide-centric nature of shotgun proteomics complicates the analysis and biological interpretation of the data especially in the case of higher eukaryote organisms. The same peptide sequence can be present in multiple different proteins or protein isoforms. Such shared peptides therefore can lead to ambiguities in determining the identities of sample proteins. In this article we illustrate the difficulties of interpreting shotgun proteomic data and discuss the need for common nomenclature and transparent informatic approaches. We also discuss related issues such as the state of protein sequence databases and their role in shotgun proteomic analysis, interpretation of relative peptide quantification data in the presence of multiple protein isoforms, the integration of proteomic and transcriptional data, and the development of a computational infrastructure for the integration of multiple diverse datasets.

Amino Acid Sequence↗

PubMed2006

Shotgun proteomics of cyanobacteria--applications of experimental and data-mining techniques.

Cyanobacteria are photosynthetic bacteria notable for their ability to produce hydrogen and a variety of interesting secondary metabolites. As a result of the growing number of completed cyanobacterial genome projects, the development of post-genomics analysis for this important group has been accelerating. DNA microarrays and classical two-dimensional gel electrophoresis (2DE) were the first technologies applied in such analyses. In many other systems, 'shotgun' proteomics employing multi-dimensional liquid chromatography and tandem mass spectrometry has proven to be a powerful tool. However, this approach has been relatively under-utilized in cyanobacteria. This study assesses progress in cyanobacterial shotgun proteomics to date, and adds a new perspective by developing a protocol for the shotgun proteomic analysis of the filamentous cyanobacterium Anabaena variabilis ATCC 29413, a model for N(2) fixation. Using approaches for enhanced protein extraction, 646 proteins were identified, which is more than double the previous results obtained using 2DE. Notably, the improved extraction method and shotgun approach resulted in a significantly higher representation of basic and hydrophobic proteins. The use of protein bioinformatics tools to further mine these shotgun data is illustrated through the application of PSORTb for localization, the grand average hydropathy (GRAVY) index for hydrophobicity, LipoP for lipoproteins and the exponentially modified protein abundance index (emPAI) for abundance. The results are compared with the most well-studied cyanobacterium, Synechocystis sp. PCC 6803. Some general issues in shotgun proteome identification and quantification are then addressed.

Computational Biology↗

PubMed2006

Shotgun proteomics for the characterization of subunit composition of mitochondrial complex I.

Here we propose shotgun proteomics as an alternative method to gel-based bottom-up proteomic platform for the structural characterization of mitochondrial NADH:ubiquinone oxidoreductase (complex I). The approach is based on simultaneous identification of subunits after global digestion of the intact complex. Resulting mixture of tryptic peptides is purified, concentrated, separated and online analyzed using nano-scale reverse-phase nano-ESI-MS/MS in a single information dependent acquisition mode. The usefulness of the method is demonstrated in our work on the well described model system of complex I from bovine heart mitochondria. The shotgun method led to the identification and partial sequence characterization of 42 subunits representing more than 95% coverage of the complex. In particular, almost all nuclear (except MLRQ) and 5 mitochondria DNA encoded subunits (except ND4L and ND6) were identified. Furthermore, it was possible to identify 30 co-purified proteins of the inner mitochondrial membrane structurally not belonging to complex I. The method's efficiency is shown by comparing it to two classical 1 D gel-based strategies. Shotgun proteomics is less laborious, significantly faster and requires less sample material with minimal treatment, facilitating the screening for post-translational modifications and quantitative and qualitative differences of complex I subunits in genetic disorders.

Animals↗

PubMed2004

Improving reproducibility and sensitivity in identifying human proteins by shotgun proteomics.

Identifying proteins in cell extracts by shotgun proteomics involves digesting the proteins, sequencing the resulting peptides by data-dependent mass spectrometry (MS/MS), and searching protein databases to identify the proteins from which the peptides are derived. Manual analysis and direct spectral comparison reveal that scores from two commonly used search programs (Sequest and Mascot) validate less than half of potentially identifiable MS/MS spectra (class positive) from shotgun analyses of the human erythroleukemia K562 cell line. Here we demonstrate increased sensitivity and accuracy using a focused search strategy along with a peptide sequence validation script that does not rely exclusively on XCorr or Mowse scores generated by Sequest or Mascot, but uses consensus between the search programs, along with chemical properties and scores describing the nature of the fragmentation spectrum (ion score and RSP). The approach yielded 4.2% false positive and 8% false negative frequencies in peptide assignments. The protein profile is then assembled from peptide assignments using a novel peptide-centric protein nomenclature that more accurately reports protein variants that contain identical peptide sequences. An Isoform Resolver algorithm ensures that the protein count is not inflated by variants in the protein database, eliminating approximately 25% of redundant proteins. Analysis of soluble proteins from a human K562 cells identified 5130 unique proteins, with approximately 100 false positive protein assignments.

Cell Line, Tumor↗

PubMed2001

An automated multidimensional protein identification technology for shotgun proteomics.

We describe an automated method for shotgun proteomics named multidimensional protein identification technology (MudPIT), which combines multidimensional liquid chromatography with electrospray ionization tandem mass spectrometry. The multidimensional liquid chromatography method integrates a strong cation-exchange (SCX) resin and reversed-phase resin in a biphasic column. We detail the improvements over a system described by Link et al. (Link, A. J.; Eng, J.; Schieltz, D. M.; Carmack, E.; Mize, G. J.; Morris, D. R.; Garvik, B. M.; Yates, J. R., III. Nat. Biotechnol. 1999, 17, 676-682) that separates and acquires tandem mass spectra for thousands of peptides. Peptides elute off the SCX phase by increasing pI, and elution off the SCX material is evenly distributed across an analysis. In addition, we describe the chromatographic benchmarks of MudPIT. MudPIT was reproducible within 0.5% between two analyses. Furthermore, a dynamic range of 10000 to 1 between the most abundant and least abundant proteins/peptides in a complex peptide mixture has been demonstrated. By improving sample preparation along with separations, the method improves the overall analysis of proteomes by identifying proteins of all functional and physical classes.

Autoanalysis↗

PubMed2005

Evaluation of "shotgun" proteomics for identification of biological threat agents in complex environmental matrixes: experimental simulations.

There is currently a great need for rapid detection and positive identification of biological threat agents, as well as microbial species in general, directly from complex environmental samples. This need is most urgent in the area of homeland security, but also extends into medical, environmental, and agricultural sciences. Mass-spectrometry-based analysis is one of the leading technologies in the field with a diversity of different methodologies for biothreat detection. Over the past few years, "shotgun"proteomics has become one method of choice for the rapid analysis of complex protein mixtures by mass spectrometry. Recently, it was demonstrated that this methodology is capable of distinguishing a target species against a large database of background species from a single-component sample or dual-component mixtures with relatively the same concentration. Here, we examine the potential of shotgun proteomics to analyze a target species in a background of four contaminant species. We tested the capability of a common commercial mass-spectrometry-based shotgun proteomics platform for the detection of the target species (Escherichia coli) at four different concentrations and four different time points of analysis. We also tested the effect of database size on positive identification of the four microbes used in this study by testing a small (13-species) database and a large (261-species) database. The results clearly indicated that this technology could easily identify the target species at 20% in the background mixture at a 60, 120, 180, or 240 min analysis time with the small database. The results also indicated that the target species could easily be identified at 20% or 6% but could not be identified at 0.6% or 0.06% in either a 240 min analysis or a 30 h analysis with the small database. The effects of the large database were severe on the target species where detection above the background at any concentration used in this study was impossible, though the three other microbes used in this study were clearly identified above the background when analyzed with the large database. This study points to the potential application of this technology for biological threat agent detection but highlights many areas of needed research before the technology will be useful in real world samples.

Biological Warfare↗

PubMed2005

Comparison of protein and peptide prefractionation methods for the shotgun proteomic analysis of Synechocystis sp. PCC 6803.

Proteome analysis by gel-free "shotgun" proteomics relies on the simplification of a peptide mixture before it is analyzed in a mass spectrometer. While separation on a reverse-phase (RP) liquid chromatographic column is widely employed, a variety of other methods have been used to fractionate both proteins and peptides before this step. We compared six different protein and peptide fractionation workflows, using Synechocystis sp. PCC 6803, a useful model cyanobacterium for potential exploitation to improve its production of hydrogen and other secondary metabolites. Pre-digestion protein separation was performed by strip-based isoelectric focusing, one-dimensional polyacrylamide gel electrophoresis, or weak anion exchange chromatography, while pre-RP peptide separation was accomplished by isoelectric focusing (IEF) or strong cation exchange chromatography. Peptides were identified using electrospray ionization quadrupole time of flight-tandem mass spectrometry. Mass spectrometry (MS) and tandem mass spectra were analyzed using ProID software employing both a single organism database and the entire NCBI non-redundant database, and a total of 776 proteins were identified using a stringent set of selection criteria. Method comparisons were made on the basis of the results obtained (number and types of proteins identified), as well as ease of use and other practical aspects. IEF-IEF protein and peptide fractionation prior to RP gave the best overall performance.

Chromatography, High Pressure Liquid↗

PubMedDate not supplied

Added value for tandem mass spectrometry shotgun proteomics data validation through isoelectric focusing of peptides.

A very popular approach in proteomics is the so-called "shotgun LC-MS/MS" strategy. In its mostly used form, a total protein digest is separated by ion exchange fractionation in the first dimension followed by off- or on-line RP LC-MS/MS. We replaced the first dimension by isoelectric focusing in the liquid phase using the Off-Gel device producing 15 fractions. As peptides are separated by their isoelectric point in the first dimension and hydrophobicity in the second, those experimentally derived parameters (pI and R(T)) can be used for the validation of potentially identified peptides. We applied this strategy to a cellular extract of Drosophila Kc167 cells and identified peptides with two different database search engines, namely PHENYX and SEQUEST, with PeptideProphet validation of the SEQUEST results. PHENYX returned 7582 potential peptide identifications and SEQUEST 7629. The SEQUEST results were reduced to 2006 identifications by validation with PeptideProphet. Validation of the PeptideProphet, SEQUEST and PHENYX results by pI and R(T) parameters confirmed 1837 PeptideProphet identifications while in the remainder of the SEQUEST results another 1130 peptides were found to be likely hits. The validation on PHENYX resulted in the fixation of a solid p-value threshold of <1 x 10(-04) that sets by itself the correct identification confidence to >95%, and a final count of 2034 highly confident peptide identifications was achieved after pI and R(T) validation. Although the PeptideProphet and PHENYX datasets have a very high confidence the overlap of common identifications was only at 79.4%, to be explained by the fact that data interpretation was done searching different protein databases with two search engines of different algorithms. The approach used in this study allowed for an automated and improved data validation process for shotgun proteomics projects producing MS/MS peptide identification results of very high confidence.

Algorithms↗

PubMed2004

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.

Cytosol↗

PubMedDate not supplied

Analysis of shotgun proteomics and RNA profiling data from Arabidopsis thaliana chloroplasts.

The integration of data from transcriptional profiling and shotgun proteomics experiments provides additional information about the identified proteins that goes beyond their plain detection. We have analyzed results from MS/MS shotgun detection of 426 Arabidopsis chloroplast proteins and genome-wide RNA profiling to identify correlations between gene expression, protein abundance and protein characteristics that influence their detection in high-throughput proteome analyses. The integrated data analysis revealed a significant molecular mass bias for the detection of proteins that were expressed at low transcript levels. Overall, the sequence coverage of most of the identified proteins increases with transcript levels indicating a positive correlation between transcript and relative protein abundance. This does not apply to a subset of the identified proteins suggesting specific properties that alter their detection in shotgun proteomics. This integrative comparison is a suitable strategy to validate large scale proteomics data and offers an assessment of the depth of the proteome analysis and the confidence in protein identification.

Arabidopsis↗

PubMed2003

Strategic shotgun proteomics approach for efficient construction of an expression map of targeted protein families in hepatoma cell lines.

An expression map of the most abundant proteins in human hepatoma HepG2 cells was established by a combination of complementary shotgun proteomics approaches. Two-dimensional liquid chromatography (LC)-nano electrospray ionization (ESI) tandem mass spectrometry (MS/MS) as well as one-dimensional LC-matrix-assisted laser desorption/ionization MS/MS were evaluated and shown that additional separation introduced at the peptide level was not as efficient as simple prefractionation of protein extracts in extending the range and total number of proteins identified. Direct LC-nanoESI MS/MS analyses of peptides from total solubilized fraction and the excised gel bands from one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis fractionated insolubilized fraction afforded the best combination in efficient construction of a nonredundant cell map. Compiling data from multiple variations of rapid shotgun proteomics analyses is nonetheless useful to increase sequence coverage and confidence of hits especially for those proteins identified primarily by a single or two peptide matches. While the returned hit score in general reflects the abundance of the respective proteins, it is not a reliable index for differential expression. Using another closely related hepatoma Hep3B as a comparative basis, 16 proteins with more than two-fold difference in expression level as defined by spot intensity in two-dimensional gel electrophoresis analysis were identified which notably include members of the heat shock protein (Hsp) and heterogeneous nuclear ribonucleoprotein (hnRPN) families. The observed higher expression level of hnRNP A2/B1 and Hsp90 in Hep3B led to a search for reported functional roles mediated in concert by both these multifunctional cellular chaperones. In agreement with the proposed model for telomerase and telomere bound proteins in promoting their interactions, data was obtained which demonstrated that the expression proteomics data could be correlated with longer telomeric length in tumorigenic Hep3B. This biological significance constitutes the basis for further delineation of the dynamic interactions and modifications of the two protein families and demonstrated how proteomic and biological investigation could be mutually substantiated in a productive cycle of hypothesis and pattern driven research.

Carcinoma, Hepatocellular↗

PubMed2006

Detecting differential and correlated protein expression in label-free shotgun proteomics.

Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomyces cerevisiae and prokaryotic Rhodopseudomonas palustris label-free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S. cerevisiae data set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R. palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed than those from different operons. Combining cluster analysis with existing protein functional annotations, we identified six protein clusters with known biological significance. In summary, the proposed generalized G-test using spectral count sampling statistics is a viable methodology for robust quantification of relative protein abundance and for sensitive detection of biologically significant differential protein expression under multiple experimental conditions in label-free shotgun proteomics.

Bacterial Proteins↗