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At least 1,081 records · Page 60Linked to original sources
PubMed2003

Exploring the functional complexity of cellular proteins by protein knockout.

Comprehensive dissection of protein functions entails more complicated manipulations than simply eliminating the protein of interest. Established knockdown technologies, such as RNA interference, antisense oligodeoxynucleotides, or ribozymes, are limited for specific applications such as modulating protein levels or specific targeting of a posttranslationally modified subpopulation. Here we show that the engineered Skp1, Cullin 1, and F-box-containing betaTrCP substrate receptor ubiquitin-proteolytic system, designated protein knockout, could achieve not only total elimination but also rapid and systematic reduction of a given cellular protein. Stable expression of a single engineered betaTrCP demonstrated simultaneous and sustained degradation of the entire retinoblastoma family proteins. Furthermore, the engineered betaTrCP was capable of selecting hypo- but not hyperphosphorylated forms of retinoblastoma for degradation. The engineered betaTrCP has been extensively modified to increase its specificity in substrate selection. This optimized protein-knockout system offers a powerful and versatile proteomic tool to dissect diverse functional properties of cellular proteins in somatic cells.

Catalytic Domain↗
PubMed2005

Enrichment and analysis of peptide subsets using fluorous affinity tags and mass spectrometry.

Although mass spectrometry has become a powerful tool for the functional analysis of biological systems, complete proteome characterization cannot yet be achieved. Instead, the sheer complexity of living organisms demands fractionation of cellular extracts to enable more targeted analyses. Here, we introduce the concept of "fluorous proteomics," whereby specific peptide subsets from samples of biological origin are tagged with perfluorinated moieties and subsequently enriched by solid-phase extraction over a fluorous-functionalized stationary phase. This approach is extremely selective, yet can readily be tailored to enrich different subsets of peptides. Additionally, this methodology overcomes many of the limitations of traditional bioaffinity-based enrichment strategies, while enabling new affinity enrichment schemes impossible to implement with bioaffinity reagents. The potential of this methodology is demonstrated by the facile enrichment of peptides bearing particular side-chain functionalities or post-translational modifications from tryptic digests of individual proteins as well as whole cell lysates.

Affinity Labels↗
PubMed2003

Characterization of the human heart mitochondrial proteome.

To gain a better understanding of the critical role of mitochondria in cell function, we have compiled an extensive catalogue of the mitochondrial proteome using highly purified mitochondria from normal human heart tissue. Sucrose gradient centrifugation was employed to partially resolve protein complexes whose individual protein components were separated by one-dimensional PAGE. Total in-gel processing and subsequent detection by mass spectrometry and rigorous bioinformatic analysis yielded a total of 615 distinct protein identifications. All protein pI values, molecular weight ranges, and hydrophobicities were represented. The coverage of the known subunits of the oxidative phosphorylation machinery within the inner mitochondrial membrane was >90%. A significant proportion of identified proteins are involved in signaling, RNA, DNA, and protein synthesis, ion transport, and lipid metabolism. The biochemical roles of 19% of the identified proteins have not been defined. This database of proteins provides a comprehensive resource for the discovery of novel mitochondrial functions and pathways.

Adolescent↗
PubMed2004

Detection and mapping of widespread intermolecular protein disulfide formation during cardiac oxidative stress using proteomics with diagonal electrophoresis.

Regulation of protein function by reversible cysteine-targeted oxidation can be achieved by multiple mechanisms, such as S-glutathiolation, S-nitrosylation, sulfenic acid, sulfinic acid, and sulfenyl amide formation, as well as intramolecular disulfide bonding of vicinal thiols. Another cysteine oxidation state with regulatory potential involves the formation of intermolecular protein disulfides. We utilized two-dimensional sequential non-reducing/reducing SDS-PAGE (diagonal electrophoresis) to investigate intermolecular protein disulfide formation in adult cardiac myocytes subjected to a series of interventions (hydrogen peroxide, S-nitroso-N-acetylpenicillamine, doxorubicin, simulated ischemia, or metabolic inhibition) that alter the redox status of the cell. More detailed experiments were undertaken with the thiol-specific oxidant diamide (5 mm), a concentration that induces a mild non-injurious oxidative stress. This increase in cellular oxidation potential caused global intermolecular protein disulfide formation in cytosolic, membrane, and myofilament/cytoskeletal compartments. A large number of proteins that undergo these associations were identified using liquid chromatography-mass spectrometry/mass spectrometry. These associations, which involve metabolic and antioxidant enzymes, structural proteins, signaling molecules, and molecular chaperones, were confirmed by assessing "shifts" on non-reducing immunoblots. The observation of widespread protein-protein disulfides indicates that these oxidative associations are likely to be fundamental in how cells respond to redox changes.

Animals↗
PubMedDate not supplied

Biology of the cold adapted archaeon, Methanococcoides burtonii determined by proteomics using liquid chromatography-tandem mass spectrometry.

Genome sequence data of the cold-adapted archaeon, Methanococcoides burtonii, was linked to liquid chromatography-mass spectrometry analysis of the expressed-proteome to define the key biological processes functioning at 4 degrees C. 528 proteins ranging in pI from 3.5 to 13.2, and 3.5-230 kDa, were identified. 133 identities were for hypothetical proteins, and the analysis of these is described separately (Goodchild et al. manuscript in preparation). DNA replication and cell division involves eucaryotic-like histone and MC1-family DNA binding proteins, and 2 bacterial-like FtsZ proteins. Eucaryotic-like, core RNA polymerase machinery, a bacterial-like antiterminator, and numerous bacterial-like regulators enable transcription. Motility involves flagella synthesis regulated by a bacterial-like chemotaxis system. Lsmalpha and Lsmgamma were coexpressed raising the possibility of homo- and hetero-oligomeric complexes functioning in RNA processing. Expression of FKBP-type and cyclophilin-type peptidyl-prolyl cis-trans isomerases highlights the importance of protein folding, and novel characteristics of folding in the cold. Thirteen proteins from a superoperon system encoding proteasome and exosome subunits were expressed, supporting the functional interaction of transcription and translation pathways in archaea. Proteins involved in every step of methylotropic methanogenesis were identified. CO(2) appears to be fixed by a modified Calvin cycle, and by carbon monoxide dehydrogenase. Biosynthesis involves acetyl-CoA conversion to pyruvate by a non-oxidative pentose phosphate pathway, and gluconeogenesis for the conversion of pyruvate to carbohydrates. An incomplete TCA cycle may supply biosynthetic intermediates for amino acid biosynthesis. A novel finding was the expression of Tn11- and Tn12-family transposases, which has implications for genetic diversity and fitness of natural populations. Characteristics of the fundamental cellular processes inferred from the expressed-proteome highlight the evolutionary and functional complexity existing in this domain of life.

Adaptation, Physiological↗
PubMed2005

Proteomic analysis of parkin knockout mice: alterations in energy metabolism, protein handling and synaptic function.

Parkin knockout (KO) mice show behavioural and biochemical changes that reproduce some of the presymptomatic aspects of Parkinson's disease, in the absence of neuronal degeneration. To provide insight into the pathogenic mechanisms underlying the preclinical stages of parkin-related parkinsonism, we searched for possible changes in the brain proteome of parkin KO mice by means of fluorescence two-dimensional difference gel electrophoresis and mass spectrometry. We identified 87 proteins that differed in abundance between wild-type and parkin KO mice by at least 45%. A high proportion of these proteins were related to energy metabolism. The levels of several proteins involved in detoxification, stress-related chaperones and components of the ubiquitin-proteasome pathway were also altered. These differences might reflect adaptive mechanisms aimed at compensating for the presence of reactive oxygen species and the accumulation of damaged proteins in parkin KO mice. Furthermore, the up-regulation of several members of the membrane-associated guanylate kinase family of synaptic scaffold proteins and several septins, including the Parkin substrate cell division control related protein 1 (CDCRel-1), may contribute to the abnormalities in neurotransmitter release previously observed in parkin KO mice. This study provides clues into possible compensatory mechanisms that protect dopaminergic neurones from death in parkin KO mice and may help us understand the preclinical deficits observed in parkin-related parkinsonism.

Animals↗
PubMed2006

Characterization of human liver cytochromes P450 by combining the biochemical and proteomic approaches.

Highly purified human liver microsomes were processed by a combination of the biochemical and proteomic methods. Microsomes were purified from the morphologically normal liver tissue obtained from the resected and discarded masses of surrounding liver upon surgical treatment for hemangioma (control) or hepatic metastases arising from colon cancer (pathology). Proteins of each sample were separated by two-dimensional (2-DE) and one-dimensional electrophoresis (1-DE); selected gel regions were excised, in-gel digested and analyzed by matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry. Analysis of collected fingerprints has revealed a total of 13 microsomal membrane proteins involved in the biotransformation of xenobiotics. These were disulfide isomerase, flavine monooxygenase, NADPH-cytochrome P450 reductase and 10 cytochrome P450 forms, namely: CYPs 1B1, 2A6, 2E1, 2C8, 2C9, 2C10, 2D6, 3A4, 4A11, 4F2. These same samples were characterized by the enzymatic assays using the marker substrates for CYPs 1A, 2B, 3A4, 2C and 2E1. Correlations between mass spectrometric data and enzymatic activities were investigated to demonstrate the manner in which the functional and structural aspects of proteomics meet each other in the field of cytochromes P450.

Cytochrome P-450 Enzyme System↗
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↗
PubMed2002

Analytical and biological variances associated with proteomic studies of Medicago truncatula by two-dimensional polyacrylamide gel electrophoresis.

Two-dimensional polyacrylamide gel electrophoresis (2-DE) and mass spectrometry are being used as proteomic tools in an integrated functional genomics program focused on the model legume Medicago truncatula. Due to the perceived high levels of indeterminate error associated with 2-DE we deemed it necessary to quantify the coefficient of variance (or relative standard deviation) for both analytical and biological sources associated with 2-DE of Medicago truncatula leaf protein extracts. Leaf protein extracts were chosen because of their biological significance and due to the more challenging nature of green tissues. Analytical variance was calculated for fifty proteins from ten replicate 2-DE gels of the same protein extract. Biological variance was calculated for the same fifty proteins from ten independent 2-DE gel analyses of ten independent but similar plants grown under identical conditions. Average analytical and biological variances were calculated for both data sets and represent the average variance of approximately 500 independent measurements of protein concentration. Analytical variance was determined to be 16.2% and biological variance was determined to be 24.2%. These average variances provide a quantified and statistical basis for evaluation of protein expression changes in future comparative proteomic investigations. It is proposed that 2-DE measured protein expression levels should differ by a minimum of 3.92sigma (i.e. /+/-2sigma/ and sigma = standard deviation), or 94.7% based on our measured variances, for the difference to be significant at the 95% confidence level.

Data Interpretation, Statistical↗
PubMed2002

Proteome analysis of Aspergillus nidulans reveals proteins associated with the response to the antibiotic concanamycin A, produced by Streptomyces species.

Competition between microbes is common to all ecosystems, but the exact nature of the competition is in most cases unknown. We have previously studied the antagonism between Streptomyces halstedii and several fungi at both the organismal and gene expression levels. Here we analysed the effect of an antibiotic produced by Streptomyces, concanamycin A, on protein levels in the filamentous fungus Aspergillus nidulans. Two-dimensional gel electrophoresis revealed that 20 proteins either increased or decreased in abundance upon treatment of the fungus with the antibiotic. Five of the most prominent proteins which changed in abundance were identified based on peptide analysis by mass spectrometry. Two of these correspond to proteins previously described in A. nidulans, and three others are homologous to proteins found in other organisms. Of these, one down-regulated protein was identified as glyceraldehyde dehydrogenase, a protein involved in general metabolic pathways. A second down-regulated protein, CpcB, affects the initiation of sexual development. Among the proteins not previously described in A. nidulans, all of them up-regulated by concanamycin A, we found two proteins with described homologues in other fungal species. The first is homologous to a cadmium-induced protein in Candida sp. The second protein is homologous to LovC, an enoyl transferase involved in the biosynthesis of lovastatin, a secondary metabolite identified in A. terreus. A third protein has a homologue in A. niger, which is of unknown function. This study indicates that proteome analysis may be a useful method for studying effects on gene expression during competitive interactions between bacteria and filamentous fungi.

Amino Acid Sequence↗
PubMed2003

Proteomic prediction of disease outcome in cancer : clinical framework and current status.

Better than gene sequencing or quantitative amplification, proteomics tools allow the study of tumor phenotype. Indeed, most current prognostic tests in cancer (carcinoembryonary antigen [CEA], prostate-specific antigen [PSA], CA 19-1, CA 125, alpha-fetoprotein [AFP], etc.) are based on the detection and quantification of single proteins in body fluids. However, a common characteristic of these tests is their relatively low predictive value, so that they are usually complemented with other procedures such as biopsy and/or endoscopy. Recently, improved analytical and bioinformatics tools have driven the attention on pattern recognition approaches rather then single-marker tests for prognostic forecasting. It is expected that predicting metastasization on the basis of tumoral protein patterns will soon be a reality. However, currently available technologies either limit the number of proteins that can be analyzed simultaneously or they are expensive, difficult, and time-consuming. Moreover, the tools adapted for expression proteomics might not be the same as those for prognostic studies that require investigation of protein function over time. We believe that clinical proteomics research designed within a precise clinical and pathology framework should be strongly supported, since many prognostic factors are determined not by the tumor itself, but by the patient, the treatment and the environment.

Animals↗
PubMed2001

[Progress in proteomics].

Proteomics, the large-scale analysis of proteins, will contribute greatly to our understanding of gene function in the post-genome era. Proteomics uses a combination of sophisticated techniques including two-dimensional(2D) gel electrophoresis, mass spectrometry, yeast two-hybrid system, bioinformatics, etc. to characterize, to quantify, and to analyze cellular proteins in a global way. The application of proteomics provides major opportunities to elucidate disease mechanisms and to identify new therapeutic targets. This review aims to explain the definition of proteomics and then to outline proteomic techniques. Finally, applications to the study of human disease are briefly discussed.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2006

Prediction of yeast protein-protein interaction network: insights from the Gene Ontology and annotations.

A map of protein-protein interactions provides valuable insight into the cellular function and machinery of a proteome. By measuring the similarity between two Gene Ontology (GO) terms with a relative specificity semantic relation, here, we proposed a new method of reconstructing a yeast protein-protein interaction map that is solely based on the GO annotations. The method was validated using high-quality interaction datasets for its effectiveness. Based on a Z-score analysis, a positive dataset and a negative dataset for protein-protein interactions were derived. Moreover, a gold standard positive (GSP) dataset with the highest level of confidence that covered 78% of the high-quality interaction dataset and a gold standard negative (GSN) dataset with the lowest level of confidence were derived. In addition, we assessed four high-throughput experimental interaction datasets using the positives and the negatives as well as GSPs and GSNs. Our predicted network reconstructed from GSPs consists of 40,753 interactions among 2259 proteins, and forms 16 connected components. We mapped all of the MIPS complexes except for homodimers onto the predicted network. As a result, approximately 35% of complexes were identified interconnected. For seven complexes, we also identified some nonmember proteins that may be functionally related to the complexes concerned. This analysis is expected to provide a new approach for predicting the protein-protein interaction maps from other completely sequenced genomes with high-quality GO-based annotations.

Databases, Genetic↗
PubMed2006

Toward the complete yeast mitochondrial proteome: multidimensional separation techniques for mitochondrial proteomics.

Proteomic analyses of different subcellular compartments, so-called organellar proteomics, facilitate the understanding of cellular functions on a molecular level. In this work, various orthogonal multidimensional separation techniques both on the protein and on the peptide level are compared with regard to the number of identified proteins as well as the classes of proteins accessible by the respective methodology. The most complete overview was achieved by a combination of such orthogonal techniques as shown by the analysis of the yeast mitochondrial proteome. A total of 851 different proteins (PROMITO dataset) were identified by use of multidimensional LC-MS/MS, 1D-SDS-PAGE combined with nano-LC-MS/MS and 2D-PAGE with subsequent MALDI-mass fingerprinting. Our PROMITO approach identified the 749 proteins, which were found in the largest previous study on the yeast mitochondrial proteome, and additionally 102 proteins including 42 open reading frames with unknown function, providing the basis for a more detailed elucidation of mitochondrial processes. Comparison of the different approaches emphasizes a bias of 2D-PAGE against proteins with very high isoelectric points as well as large and hydrophobic proteins, which can be accessed more appropriately by the other methods. While 2D-PAGE has advantages in the possible separation of protein isoforms and quantitative differential profiling, 1D-SDS-PAGE with nano-LC-MS/MS and multidimensional LC-MS/MS are better suited for efficient protein identification as they are less biased against distinct classes of proteins. Thus, comprehensive proteome analyses can only be realized by a combination of such orthogonal approaches, leading to the largest dataset available for the mitochondrial proteome of yeast.

Mitochondrial Proteins↗
PubMed2002

Clustering of proximal sequence space for the identification of protein families.

MOTIVATION: The study of sequence space, and the deciphering of the structure of protein families and subfamilies, has up to now been required for work in comparative genomics and for the prediction of protein function. With the emergence of structural proteomics projects, it is becoming increasingly important to be able to select protein targets for structural studies that will appropriately cover the space of protein sequences, functions and genomic distribution. These problems are the motivation for the development of methods for clustering protein sequences and building families of potentially orthologous sequences, such as those proposed here. RESULTS: First we developed a clustering strategy (Ncut algorithm) capable of forming groups of related sequences by assessing their pairwise relationships. The results presented for the ras super-family of proteins are similar to those produced by other clustering methods, but without the need for clustering the full sequence space. The Ncut clusters are then used as the input to a process of reconstruction of groups with equilibrated genomic composition formed by closely-related sequences. The results of applying this technique to the data set used in the construction of the COG database are very similar to those derived by the human experts responsible for this database. AVAILABILITY: The analysis of different systems, including the COG equivalent 21 genomes are available at http://www.pdg.cnb.uam.es/GenoClustering.html.

Algorithms↗
PubMed2004

Mitochondrial dysfunction in schizophrenia: evidence for compromised brain metabolism and oxidative stress.

The etiology and pathophysiology of schizophrenia remain unknown. A parallel transcriptomics, proteomics and metabolomics approach was employed on human brain tissue to explore the molecular disease signatures. Almost half the altered proteins identified by proteomics were associated with mitochondrial function and oxidative stress responses. This was mirrored by transcriptional and metabolite perturbations. Cluster analysis of transcriptional alterations showed that genes related to energy metabolism and oxidative stress differentiated almost 90% of schizophrenia patients from controls, while confounding drug effects could be ruled out. We propose that oxidative stress and the ensuing cellular adaptations are linked to the schizophrenia disease process and hope that this new disease concept may advance the approach to treatment, diagnosis and disease prevention of schizophrenia and related syndromes.

Brain↗
PubMed2003

Characterizing proteolytic cleavage site activity using bio-basis function neural networks.

MOTIVATION: In protein chemistry, proteomics and biopharmaceutical development, there is a desire to know not only where a protein is cleaved by a protease, but also the susceptibility of its cleavage sites. The current tools for proteolytic cleavage prediction have often relied purely on regular expressions, or involve models that do not represent biological data well. RESULTS: A novel methodology for characterizing proteolytic cleavage site activities has been developed, which incorporates two fundamental features: activity class prediction and the use of an amino acid similarity matrix for (non-parametric) neural learning. The first solved the problem of predicting proteolytic efficiency. The second significantly improved the robustness in prediction and reduced the time complexity for learning. This study shows that activity class prediction is successful when applying this methodology to the prediction and characterization of Trypsin cleavage sites and the prediction of HIV protease cleavage sites. AVAILABILITY: Requests for software and data should be made respectively to Dr Zheng Rong Yang and Miss Rebecca Thomson.

Amino Acid Sequence↗
PubMed2000

Proteomics: a link between genomics, genetics and physiology.

Thanks to spectacular advances in the techniques for identifying proteins separated by two-dimensional electrophoresis and in methods for large-scale analysis of proteome variations, proteomics is becoming an essential methodology in various fields of plant biology. In the study of pleiotropic effects of mutants and in the analysis of responses to hormones and to environmental changes, the identification of involved metabolic pathways can be deduced from the function of affected proteins. In molecular quantitative genetics, proteomics can be used to map translated genes and loci controlling their expression, which can be used to identify proteins accounting for the variation of complex phenotypic traits. Linking gene expression to cell metabolism on the one hand and to genetic maps on the other, proteomics is a central tool for functional genomics.

Genomics↗