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PubMed2002

Proteomics and its impact upon biomedical science.

Proteomics is the protein equivalent of genomics and is the study of gene expression at a functional level. The proteome of an organism is the protein complement of its genome. However, unlike the genome, the proteome is dynamic: it varies according to the cell type and the functional state of the cell. In addition, the proteome shows characteristic perturbations in response to disease and external stimuli. Proteomics combines state of the art analytical methods with bioinformatics. Here, we review the concept and technology of proteomics with specific reference to applications in medical microbiology, cellular pathology, clinical chemistry, haematology/immunology, pharmacology and toxicology.

Computational Biology↗
PubMed2005

A hybrid LC-Gel-MS method for proteomics research and its application to protease functional pathway mapping.

Two-dimensional (2D) gel electrophoresis is the most common protein separation method in proteomics research. It can provide high resolution and high sensitivity. However, 2D gel methods have several limitations, such as labor-intensive procedures, poor reproducibility, and limited dynamic range of detection. In fact, many investigators have returned to couple the one-dimensional (1D) SDS-PAGE with mass spectrometry for protein identification. The limitation of this approach is the increased protein complexity in each one-dimensional gel band. To overcome this problem and provide reproducible quantitative information, we describe here a 2D method for protein mixture separation using a combination of high performance liquid chromatography (HPLC) and 1D SDS-PAGE. The study shows that the step-gradient fractionation method we have applied provides excellent reproducibility. In addition, high mass accuracy of LC-FTICR-MS can allow more confident protein identifications by high resolution and ultra-high mass measurement accuracy. This approach was applied to comparative proteomics since protein abundance level changes can be easily visualized with side-by-side vertical comparison in one gel. Furthermore, separation of multi-samples in the same gel significantly reduces run-to-run variation, as is shown with differential image gel electrophoresis (DIGE). Finally, this approach readily incorporates immunological methods to normalize relative abundances of multiple samples within a single gel. This paper presents the results of our developments and our initial application of this strategy for mapping protease function of beta amyloid cleaving enzyme (BACE) in biological systems.

Amyloid Precursor Protein Secretases↗
PubMed2006

HepatoProteomics: applying proteomic technologies to the study of liver function and disease.

The wealth of human genome sequence information now available, coupled with technological advances in robotics, nanotechnology, mass spectrometry, and information systems, has given rise to a method of scientific inquiry known as functional genomics. By using these technologies to survey gene expression and protein production on a near global scale, the goal of functional genomics is to assign biological function to genes with currently unknown roles in physiology. This approach carries particular appeal in disease research, where it can uncover the function of previously unknown genes and molecular pathways that are directly involved in disease progression. With this knowledge may come improved diagnostic techniques, prognostic capabilities, and novel therapeutic approaches. In this regard, the continuing evolution of proteomic technologies has resulted in an increasingly greater impact of proteome studies in many areas of research and hepatology is no exception. Our laboratory has been extremely active in this area, applying both genomic and proteomic technologies to the analysis of virus-host interactions in several systems, including the study of hepatitis C virus (HCV) infection and HCV-associated liver disease. Since proteomic technologies are foreign to many hepatologists (and to almost everyone else), this article will provide an overview of proteomic methods and technologies and describe how they are being used to study liver function and disease.

Humans↗
PubMed2004

[Results of proteomic-based study of the kidney, urine, plasma, and uremic ultrafiltrate. Potential applications of the results in nephrology].

Proteomics, a new branch of science studying proteins, only emerged in the postgenomic period. What makes so it important is that fact even the exciting recent insights into the genome have not furnished sufficient information about proteins, which are the main agents behind cellular, subcellular, and supracellular functions. The center of attention of proteomics is identification of proteins in complex protein mixtures with an emphasis on the identification of a large number of proteins at a time, search for interrelations between identified proteins, their more exact characterization, determination of quantity, and better understanding of their function. Proteomics in nephrology is still in its infancy. Although it makes use, like in other fields, of various methodological procedures, the principal techniques are two-dimensional gel electrophoresis and MALDI-TOF (matrix-assisted laser desorption/ionization-time of flight) mass spectrometry. Nephrology-related proteomic findings made to date inform about normal protein composition of renal parenchyma, urine and plasma, and on their alterations under the influence of physiological or pathological stimuli. Search is under way for uremic toxins in uremic infiltrate, and their elimination from the body of patients with renal failure using various dialysis membranes is being investigated. Findings have made it possible to formulate hypotheses regarding renal physiology and pathology. Current nephrology-related proteomics raises more questions than it answers. Its potential for improving the understanding of physiological processes, pathological states, non-invasive diagnosis, monitoring of therapy, development of drugs and therapeutic procedures is a major promise for future.

Animals↗
PubMed2001

Genetics of the Drosophila flight muscle myofibril: a window into the biology of complex systems.

This essay reviews the long tradition of experimental genetics of the Drosophila indirect flight muscles (IFM). It discusses how genetics can operate in tandem with multidisciplinary approaches to provide a description, in molecular terms, of the functional properties of the muscle myofibril. In particular, studies at the interface of genetics and proteomics address protein function at the cellular scale and offer an outstanding platform with which to elucidate how the myofibril works. Two generalizations can be enunciated from the studies reviewed. First, the study of mutant IFM proteomes provides insight into how proteins are functionally organized in the myofibril. Second, IFM mutants can give rise to structural and contractile defects that are unrelated, a reflection of the dual function that myofibrillar proteins play as fundamental components of the sarcomeric framework and biochemical "parts" of the contractile "engine".

Animals↗
PubMed2006

The Saccharomyces cerevisiae proteome of oxidized protein thiols: contrasted functions for the thioredoxin and glutathione pathways.

Protein thiol oxidation subserves important biological functions and constitutes a sequel of reactive oxygen species toxicity. We developed two distinct thiol-labeling approaches to identify oxidized cytoplasmic protein thiols in Saccharomyces cerevisiae. Inone approach, we used N-(6-(biotinamido)hexyl)-3'-(2'-pyridyldithio)-propionamide to purify oxidized protein thiols, and in the other, we used N-[(14)C]ethylmaleimide to quantify this oxidation. Both approaches showed a large number of the same proteins with oxidized thiols ( approximately 200), 64 of which were identified by mass spectrometry. We show that, irrespective of its mechanism, protein thiol oxidation is dependent upon molecular O(2). We also show that H(2)O(2) does not cause de novo protein thiol oxidation, but rather increases the oxidation state of a select group of proteins. Furthermore, our study reveals contrasted differences in the oxidized proteome of cells upon inactivation of the thioredoxin or GSH pathway suggestive of very distinct thiol redox control functions, assigning an exclusive role for thioredoxin in H(2)O(2) metabolism and the presumed thiol redox buffer function for GSH. Taken together, these results suggest the high selectivity of cytoplasmic protein thiol oxidation.

Biotin↗
PubMed2005

Decoding two-dimensional polyacrylamide gel electrophoresis complex maps by autocovariance function: a simplified approach useful for proteomics.

This paper describes a mathematical approach applied for decoding the complex signal of two-dimensional polyacrylamide gel electrophoresis maps of protein mixtures. The method is helpful in extracting analytical information since separation of all the proteins present in the sample is still far from being achieved and co-migrating proteins are generally present in the same spot. The simplified method described is based on the study of the 2-D autocovariance function (2D-ACVF) computed on an experimental digitized map. The first part of the 2D-ACVF allows for the estimation of the number of proteins present in the sample (2D-ACVF computed at the origin) and of the separation performance (mean spot size). Moreover, the 2D-ACVF plot is a powerful tool in identifying order in the spot position, and singling it out from the complex separation pattern. This method was validated on synthetic maps obtained by computer simulation to describe 2-D PAGE real maps and reference maps retrieved from the SWISS-2DPAGE database. The results obtained are discussed by focusing on specific information relevant in proteomics: sample complexity, separation performance, and identification of spot trains related to post-translational modifications.

Analysis of Variance↗
PubMed2003

Heterogeneity analysis of the human pituitary proteome.

BACKGROUND: A human proteome is relatively dynamic compared with its corresponding genome. Our aim was to study the heterogeneity of a human pituitary proteome as a function of gender, age, and race. METHODS: Pituitary control tissues (n = 8) were used to extract proteins; each control tissue was analyzed (n = 3-5) with two-dimensional gel electrophoresis (2DGE) and PDQuest software. We obtained 30 high-resolution 2DGE gels and conducted a comparative analysis as a function of gender, age, and race. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography-electrospray ionization-quadrupole-ion trap tandem mass spectrometry were used to characterize the protein in each differential spot. RESULTS: We detected approximately 1000 protein spots in each 2DGE map, and 51 differential spots (7 differing with gender, 17 with age, 15 with race, and 12 with the coeffect of age and race). Among those 51, we characterized 28 proteins [5 differing with gender, 8 with age, 6 with race, 8 with the coeffect of age and race, and 1 (somatotropin chain 1) with all of these]. Somatotropin was related to gender, age, and race, and prolactin was higher in females than males. The differentially expressed proteins that were related to age were mainly those proteins associated with cell growth, proliferation, differentiation, apoptosis, and death; those proteins showed no difference with gender and race. Age and race affected some proteins associated with hormone regulation (e.g., follistatin, thyroid hormone receptor beta-2, adenylate cyclase-inhibiting Galpha protein). CONCLUSIONS: A heterogeneity exists in the human pituitary proteome as a function of gender, age, and race. These findings will serve as a basis for our comparative proteomics studies of human pituitary adenomas.

Adult↗
PubMed2005

Viewing the proteome from oligopeptides and prediction of protein function.

Our research activity of making the lexicon of relatively short oligopeptides has been one of the first steps to view the world of proteome from the perspective of oligopeptides. We propose a new method for the prediction of protein function, especially GeneOntology terms (GO terms), based on statistical characteristics of oligopeptides as an application of the lexicon. In the lexicon, a known function of a protein is inherited to its oligopeptides, and the correspondence between oligopeptides and the function is calculated in the whole proteins. In our method, unknown functions of proteins are predicted by means of the correspondence automatically. We measured the prediction performance using the 28,520 whole human proteins registered in RefSeq for several GO terms by recall-precision graphs. The GO terms include 'membrane', 'nucleus', 'ATP binding', 'hydorolase activity', 'GTP binding', 'intracellular signaling cascade' and 'ubiquitin cycle'. In most cases, it scores 70% recall with 80% precision. The prediction for ATP binding and GTP binding results in quite high performance: it scores 80% recall with 80% precision. Even in the worst case (ubiquitin cycle), it scores 62.6% recall with 80% precision. These results suggest that the proposed method is quite efficient for predicting GO terms.

Computational Biology↗
PubMed2000

Genomics and medicine: an anticipation. From Boolean Mendelian genetics to multifactorial molecular medicine.

The major impact of the completion of the human genome sequence will be the understanding of diseases, with deduced therapy. In the field of genetic disorders, we will complete the catalogue of monogenic diseases, also called Mendelian diseases because they obey the Boolean logic of Mendel's laws. The major challenge now is to decipher the polygenic and multifactorial etiology of common diseases, such as cancer, cardio-vascular, nutritional, allergic, auto-immune and degenerative diseases. In fact, every gene, when mutated, is a potential disease gene, and we end up with the new concept of 'reverse medicine'; i.e., deriving new diseases or pathogenic pathways from the knowledge of the structure and function of every gene. By going from sequence to function (functional genomics and proteomics) we will gain insight into basic mechanisms of major functions such as cell proliferation, differentiation and development, which are perturbed in many pathological processes. By learning the meaning of some non-coding and of regulatory sequences our understanding will gain in complexity, generating a molecular and supramolecular integrated physiology, helping to build a molecular patho-physiology of the different syndromes. Besides those cognitive advances, there are also other issues at stake, such as: progress in diagnostic and prediction (predictive medicine); progress in therapy (pharmacogenomics and gene-based therapy); ethical issues; impact on business.

Ethics, Medical↗
PubMed2006

A regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data.

BACKGROUND: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. METHODS: In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN) algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. RESULTS: We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM) algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly CONCLUSION: Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.

Algorithms↗
PubMed1998

Determination of plasmid-encoded functions in Rhizobium leguminosarum biovar trifolii using proteome analysis of plasmid-cured derivatives.

We have used proteome analysis of derivatives of R. leguminosarum biovar trifolii strain ANU843, cured of indigenous plasmids by a direct selection system, to investigate plasmid-encoded functions. Under the conditions used, the plasmid-encoded gene products contributed to only a small proportion of the 2000 proteins visualised in the two-dimensional (2-D) protein map of strain ANU843. The level of synthesis of thirty-nine proteins was affected after curing of either plasmid a, c or e. The differences observed upon plasmid curing included: protein loss, up/down-regulation of specific proteins and novel synthesis of some proteins. This suggests that a complex interplay between the cured plasmid and the remaining replicons is occurring. Twenty-two proteins appeared to be absent in the cured strains and these presumably are encoded by plasmid genes. Of these, a small heat shock protein, a cold shock protein, a hypothetical YTFG-29.7 kDa protein, and the alpha and beta subunits of the electron transfer flavoprotein were identified by N-terminal microsequencing and predicted to be encoded by plasmid e. Four of the sequenced proteins putatively encoded on plasmid e and two encoded on plasmid c were novel. In addition, curing of plasmid e and c consistently decreased the levels of 3-isopropylmalate dehydratase and malate dehydrogenase, respectively, suggesting that levels of these proteins may be influenced by plasmid-encoded functions. A protein with homology to 4-oxalocrotonate tautomerase, which is involved in the biodegradation of phenolic compounds, was found to be newly synthesised in the strain cured of plasmid e. Proteome analysis provides a sensitive tool to examine the functional organisation of the Rhizobium genome and the global gene interactions which occur between the different replicons.

Bacterial Proteins↗
PubMed2002

Structural characterization of the human proteome.

This paper reports an analysis of the encoded proteins (the proteome) of the genomes of human, fly, worm, yeast, and representatives of bacteria and archaea in terms of the three-dimensional structures of their globular domains together with a general sequence-based study. We show that 39% of the human proteome can be assigned to known structures. We estimate that for 77% of the proteome, there is some functional annotation, but only 26% of the proteome can be assigned to standard sequence motifs that characterize function. Of the human protein sequences, 13% are transmembrane proteins, but only 3% of the residues in the proteome form membrane-spanning regions. There are substantial differences in the composition of globular domains of transmembrane proteins between the proteomes we have analyzed. Commonly occurring structural superfamilies are identified within the proteome. The frequencies of these superfamilies enable us to estimate that 98% of the human proteome evolved by domain duplication, with four of the 10 most duplicated superfamilies specific for multicellular organisms. The zinc-finger superfamily is massively duplicated in human compared to fly and worm, and occurrence of domains in repeats is more common in metazoa than in single cellular organisms. Structural superfamilies over- and underrepresented in human disease genes have been identified. Data and results can be downloaded and analyzed via web-based applications at http://www.sbg.bio.ic.ac.uk.

Algorithms↗
PubMed2005

Proteomics of boar seminal plasma - current studies and possibility of their application in biotechnology of animal reproduction.

Proteomics is critical to identify the properties and functions of proteins involved in the mechanism regulating the male reproductive tract function. This approach is important in male fertility assessment and clinical diagnosis of the physiological state of individual reproductive organs. Proteomics also provides a tool to understand the interactions of seminal plasma proteins with spermatozoa, which could provide a useful model for studying ligand-cell interaction occurring at the sperm cell surface. This review covers a selection of advances in the realm of functional proteomics of boar seminal plasma proteins and is focused on some fundamental proteomic technologies. Also, this review explores key themes in proteomics and their application in animal reproductive techniques.

Animals↗
PubMed2005

PA-GOSUB: a searchable database of model organism protein sequences with their predicted Gene Ontology molecular function and subcellular localization.

PA-GOSUB (Proteome Analyst: Gene Ontology Molecular Function and Subcellular Localization) is a publicly available, web-based, searchable and downloadable database that contains the sequences, predicted GO molecular functions and predicted subcellular localizations of more than 107,000 proteins from 10 model organisms (and growing), covering the major kingdoms and phyla for which annotated proteomes exist (http://www.cs.ualberta.ca/~bioinfo/PA/GOSUB). The PA-GOSUB database effectively expands the coverage of subcellular localization and GO function annotations by a significant factor (already over five for subcellular localization, compared with Swiss-Prot v42.7), and more model organisms are being added to PA-GOSUB as their sequenced proteomes become available. PA-GOSUB can be used in three main ways. First, a researcher can browse the pre-computed PA-GOSUB annotations on a per-organism and per-protein basis using annotation-based and text-based filters. Second, a user can perform BLAST searches against the PA-GOSUB database and use the annotations from the homologs as simple predictors for the new sequences. Third, the whole of PA-GOSUB can be downloaded in either FASTA or comma-separated values (CSV) formats.

Amino Acid Sequence↗
PubMedDate not supplied

[A proteomic approach to study of the function of the Sec14p-like p45 protein].

We undertook a search for proteins interacting with protein p45 by the method of two-hybrid screening in order to determine the function of the Sec14p-like protein p45. A screening of the yeast library of rat lung cDNA, six proteins specifically activating the reporter genes of a two-hybrid system and 21 unlikely protein partners of protein p45 were identified. The most likely candidate for the role of a p45 partner is the surfactant protein C (Sftpc). These results and previous studies led us to the hypothesis that protein p45 fulfills its protective function by participating in the biogenesis of cell membranes. The English version of the paper: Russian Journal of Bioorganic Chemistry, 2005, vol. 31, no. 3; see also http://www.maik.ru.

Animals↗
PubMed2003

C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression.

To verify the genome annotation and to create a resource to functionally characterize the proteome, we attempted to Gateway-clone all predicted protein-encoding open reading frames (ORFs), or the 'ORFeome,' of Caenorhabditis elegans. We successfully cloned approximately 12,000 ORFs (ORFeome 1.1), of which roughly 4,000 correspond to genes that are untouched by any cDNA or expressed-sequence tag (EST). More than 50% of predicted genes needed corrections in their intron-exon structures. Notably, approximately 11,000 C. elegans proteins can now be expressed under many conditions and characterized using various high-throughput strategies, including large-scale interactome mapping. We suggest that similar ORFeome projects will be valuable for other organisms, including humans.

Alternative Splicing↗
PubMed2002

Applied proteomics: mitochondrial proteins and effect on function.

The identification of a majority of the polypeptides in mitochondria would be invaluable because they play crucial and diverse roles in many cellular processes and diseases. The endogenous production of reactive oxygen species (ROS) is a major limiter of life as illustrated by studies in which the transgenic overexpression in invertebrates of catalytic antioxidant enzymes results in increased lifespans. Mitochondria have received considerable attention as a principal source---and target---of ROS. Mitochondrial oxidative stress has been implicated in heart disease including myocardial preconditioning, ischemia/reperfusion, and other pathologies. In addition, oxidative stress in the mitochondria is associated with the pathogenesis of Alzheimer's disease, Parkinson's disease, prion diseases, and amyotrophic lateral sclerosis (ALS) as well as aging itself. The rapidly emerging field of proteomics can provide powerful strategies for the characterization of mitochondrial proteins. Current approaches to mitochondrial proteomics include the creation of detailed catalogues of the protein components in a single sample or the identification of differentially expressed proteins in diseased or physiologically altered samples versus a reference control. It is clear that for any proteomics approach prefractionation of complex protein mixtures is essential to facilitate the identification of low-abundance proteins because the dynamic range of protein abundance within cells has been estimated to be as high as 10(7). The opportunities for identification of proteins directly involved in diseases associated with or caused by mitochondrial dysfunction are compelling. Future efforts will focus on linking genomic array information to actual protein levels in mitochondria.

Animals↗