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At least 685 records · Page 38Linked to original sources
PubMed2005

Investigation of early protein changes in the urinary bladder following partial bladder outlet obstruction by proteomic approach.

We investigated the pathophysiological mechanism by proteomic approach as a possible tool to detect the marker proteins to develop lower urinary tract symptoms following bladder outlet obstruction (BOO). Rats were randomized into 3 groups; control, sham operation and BOO groups. BOO group was divided into 1, 3, and 5 day-group. Conventional proteomics was performed with high resolution 2-D gel electrophoresis followed by computational image analysis and protein identification using mass spectrometry using rat urinary bladders. A comparison of bladder of BOO group with control bladder showed that three proteins of optineurin, thioredoxin and preprohaptoglobin were over-expressed in the bladder of BOO group. In addition, four proteins, such as peroxiredoxin 2, transgelin, hippocampal cholinergic neurostimulating peptide (HCNP) and beta-galactoside-binding lectin, were under-expressed in the bladder of BOO group. These data supported that downregulation of HCNP might make detrusor muscle be supersensitive to acetylcholine, up-regulation of optineurin means the protection of nerve injury, and down-regulation of transgelin means the decreased contractility of detrusor muscle. Beside these proteins, other proteins are related to oxidative stress or have a nonspecific function in this study. However more information is needed in human bladder tissue for clinical usage.

Animals↗
PubMedDate not supplied

Proteomics. Concepts and perspectives.

Within the last five years the field of proteomics has changed the understanding of molecular biology. Proteins manifest physiological as well as pathophysiological processes in a cell or an organism, and proteomics describes the complete protein inventory in dependence on in vivo parameters. Disease mechanism or drug effects both affect a protein profile and, vice versa, characterising protein profiles reveals information for the understanding of disease and therapy. Analytical methods for proteomics are based on conventional tools for protein characterisation. The technical challenge is the complete coverage of physico-chemical properties for thousands of proteins. Nucleic acids display a relative chemical homogeneity and therefore genomics was considered more promising in the past than proteomics. Further improvements in proteomics technologies will likely change this course with proteomics complementing genomics as a tool to study life sciences.

Animals↗
PubMed2003

Proteomic approach to understanding antibiotic action.

We have used proteomic technology to elucidate the complex cellular responses of Bacillus subtilis to antimicrobial compounds belonging to classical and emerging antibiotic classes. We established on two-dimensional gels a comprehensive database of cytoplasmic proteins with pIs covering a range of 4 to 7 that were synthesized during treatment with antibiotics or agents known to cause generalized cell damage. Although each antibiotic showed an individual protein expression profile, overlaps in the expression of marker proteins reflected similarities in molecular drug mechanisms, suggesting that novel compounds with unknown mechanisms of action may be classified. Indeed, one such substance, a structurally novel protein synthesis inhibitor (BAY 50-2369), could be classified as a peptidyltransferase inhibitor. These results suggest that this technique gives new insights into the bacterial response toward classical antibiotics and hints at modes of action of novel compounds. Such a method should prove useful in the process of antibiotic drug discovery.

Anti-Bacterial Agents↗
PubMed2005

Target identification and validation in drug discovery: the role of proteomics.

Proteomics, the study of cellular protein expression, is an evolving technology platform that has the potential to identify novel proteins involved in key biological processes in the cell that may serve as potential drug targets. While proteomics has considerable theoretical promise, individual cells/tissues have the potential to generate many millions of proteins while the current analytical technologies that involve the use of time-consuming two dimensional gel electrophoresis (2DIGE) and various mass spectrometry (MS) techniques are unable to handle complex biological samples without multiple high-resolution purification steps to reduce their complexity. This can significantly limit the speed of data generation and replication and requires the use of bioinformatic algorithms to reconstitute the parent proteome, a process that does not always result in a reproducible outcome. In addition, membrane bound proteins, e.g., receptors and ion channels, that are the targets of many existing drugs, are not amenable to study due, in part, to limitations in current proteomic techniques and also to these being present in low abundance and thus disproportionally represented in proteome profiles. Subproteomes with reduced complexity have been used to generate data related to specific, hypothesis-driven questions regarding target identification, protein-interaction networks and signaling pathways. However progress to date, with the exception of diagnostic proteomics in the field of cancer, has been exceedingly slow with an inability to put such studies in the context of a larger proteome, limiting the value of the information. Additionally the pathway for target validation (which can be more accurately described at the preclinical level as target confidence building) remains unclear. It is important that the ability to measure and interrogate proteomes matches expectations, avoiding a repetition of the disappointment and subsequent skepticism that accompanied what proved to be unrealistic expectations for the rapid contribution of data based on the genome maps, to biomedical research.

Computational Biology↗
PubMedDate not supplied

Integrating a functional proteomic approach into the target discovery process.

Functional proteomics is a promising technique for the rational identification of novel therapeutic targets by elucidation of the function of newly identified proteins in disease-relevant cellular pathways. Of the recently described high-throughput approaches for analyzing protein-protein interactions, the yeast two-hybrid (Y2H) system has turned out to be one of the most suitable for genome-wide analysis. However, this system presents a challenging technical problem: the high prevalence of false positives and false negatives in datasets due to intrinsic limitations of the technology and the use of a high-throughput, genetic assay. We discuss here the different experimental strategies applied to Y2H assays, their general limitations and advantages. We also address the issue of the contribution of protein interaction mapping to functional biology, especially when combined with complementary genomic and proteomic analyses. Finally, we illustrate how the combination of protein interaction maps with relevant functional assays can provide biological support to large-scale protein interaction datasets and contribute to the identification and validation of potential therapeutic targets.

Animals↗
PubMed2000

Relationship between whole proteome aminoacid composition and static DNA curvature.

To study possible relationships between an organism's genomic DNA curvature and the aminoacid composition of its proteome, every peptidic sequence from fully determined genomes was retrotranslated using the E. coli codon preferences, and the curvature profiles of the resulting DNA sequences were calculated and compared. A clear interdependence between these two variables was observed, as each retrotranslated proteome presented a distinctive, statistically significant DNA curvature profile biased toward its natural DNA curvature profile. In addition, by comparing the profiles arising from real and randomly permuted proteomes, we also found a position-dependent contribution of the peptidic sequence to DNA curvature. The implications of these results support the idea of a possible selection toward a specific global curvature of genomes.

Amino Acids↗
PubMed2002

Characterisation of global protein expression by two-dimensional electrophoresis and mass spectrometry: proteomics of Toxoplasma gondii.

The development of tools for the analysis of global gene expression is vital for the optimal exploitation of the data on parasite genomes that are now being generated in abundance. Recent advances in two-dimensional electrophoresis (2-DE), mass spectrometry and bioinformatics have greatly enhanced the possibilities for mapping and characterisation of protein populations. We have employed these developments in a proteomics approach for the analysis of proteins expressed in the tachyzoite stage of Toxoplasma gondii. Over 1000 polypeptides were reproducibly separated by high-resolution 2-DE using the pH ranges 4-7 and 6-11. Further separations using narrow range gels suggest that at least 3000-4000 polypeptides should be resolvable by 2-DE using multiple single pH unit gels. Mass spectrometry was used to characterise a variety of protein spots on the 2-DE gels. Peptide mass fingerprints, acquired by matrix-assisted laser desorption/ionisation-(MALDI) mass spectrometry, enabled unambiguous protein identifications to be made where full gene sequence information was available. However, interpretation of peptide mass fingerprint data using the T. gondii expressed sequence tag (EST) database was less reliable. Peptide fragmentation data, acquired by post-source decay mass spectrometry, proved a more successful strategy for the putative identification of proteins using the T. gondii EST database and protein databases from other organisms. In some instances, several protein spots appeared to be encoded by the same gene, indicating that post-translational modification and/or alternative splicing events may be a common feature of functional gene expression in T. gondii. The data demonstrate that proteomic analyses are now viable for T. gondii and other protozoa for which there are good EST databases, even in the absence of complete genome sequence. Moreover, proteomics is of great value in interpreting and annotating EST databases.

Animals↗
PubMed2005

Qualified predictions for microarray and proteomics pattern diagnostics with confidence machines.

We focus on the problem of prediction with confidence and describe a recently developed learning algorithm called transductive confidence machine for making qualified region predictions. Its main advantage, in comparison with other classifiers, is that it is well-calibrated, with number of prediction errors strictly controlled by a given predefined confidence level. We apply the transductive confidence machine to the problems of acute leukaemia and ovarian cancer prediction using microarray and proteomics pattern diagnostics, respectively. We demonstrate that the algorithm performs well, yielding well-calibrated and informative predictions whilst maintaining a high level of accuracy.

Algorithms↗
PubMed2005

Comparative proteomic analysis using samples obtained with laser microdissection and saturation dye labelling.

Comparative proteomic methods are rapidly being applied to many different biological systems including complex tissues. One pitfall of these methods is that in some cases, such as oncology and neuroscience, tissue complexity requires isolation of specific cell types and sample is limited. Laser microdissection (LMD) is commonly used for obtaining such samples for proteomic studies. We have combined LMD with sensitive thiol-reactive saturation dye labelling of protein samples and 2-D DIGE to identify protein changes in a test system, the isolated CA1 pyramidal neurone layer of a transgenic (Tg) rat carrying a human amyloid precursor protein transgene. Saturation dye labelling proved to be extremely sensitive with a spot map of over 5,000 proteins being readily produced from 5 mug total protein, with over 100 proteins being significantly altered at p < 0.0005. Of the proteins identified, all showed coherent changes associated with transgene expression. It was, however, difficult to identify significantly different proteins using PMF and MALDI-TOF on gels containing less than 500 mug total protein. The use of saturation dye labelling of limiting samples will therefore require the use of highly sensitive MS techniques to identify the significantly altered proteins isolated using methods such as LMD.

Alzheimer Disease↗
PubMed2005

Bioinformatics challenges in proteomics.

A little after the genomic revolution had been celebrated, it seemed as if a competition began to found new -omics disciplines that ultimately all have the same goal, the understanding of biological function. There are many similar definitions for proteomics that can be summarized as follows: proteomics is a large-scale study of structure and function of proteins in an organism or cell. Importantly, the proteome is much more variable than the genome through its interactions with the genome and secondary modifications. It differs depending on the tissue and stage in life-cycle. Hence, proteomics is a very diverse discipline that uses a variety of experimental set-ups and targets in order to elucidate function. Its dissociation from other disciplines can only remain artificial. The bioinformatics applied to proteomics are equally varied. In this review we will focus mainly on a few areas of bioinformatics that seem to us as particularly noteworthy or characteristic for proteomics research, for example in 2DE analysis or mass spectrometry. Another important task of bioinformatics is the prediction of functional properties. We will summarize the approaches taken in order to predict protein networks, which are based on the extensive integration of several kinds of -omics data. We will give a short overview of a demanding field in computational biology, the analysis and prediction of protein 3D structures. In order to provide a broader perspective we will close this review with a generalized description of activities and databases in the realm of proteomics.

Animals↗
PubMed2006

Proteome informatics II: bioinformatics for comparative proteomics.

The present review attempts to cover the most recent initiatives directed towards representing, storing, displaying and processing protein-related data suited to undertake "comparative proteomics" studies. Data interpretation is brought into focus. Efforts invested into analysing and interpreting experimental data increasingly express the need for adding meaning. This trend is perceptible in work dedicated to determining ontologies, modelling interaction networks, etc. In parallel, technical advances in computer science are spurred by the development of the Web and the growing need to channel and understand massive volumes of data. Biology benefits from these advances as an application of choice for many generic solutions. Some examples of bioinformatics solutions are discussed and directions for on-going and future work conclude the review.

Algorithms↗
PubMedDate not supplied

Data input module for Birth Defects Systems Manager.

The need for a computational bioinformatics infrastructure to manage the vast digital information from functional genomics and proteomics motivated us to develop Birth Defects Systems Manager (BDSM) as an open resource to facilitate analysis and discovery in developmental biology and developmental toxicity. This report describes the design, development and implementation of the data loading module of BDSM, referred to as LoadBDSM. It includes a shared data directory resource that can be granted various levels of security for different research groups or investigators to manage experimental datasets individually or in groups. LoadBDSM allows the upload of data and experiment details using controlled semantics for developmental exposure (toxicant, dosing scenario, intervention), biological sample (species, tissue, stage) and disease outcome (time, risk, phenotype). It adheres to existing controlled vocabulary plus rules of inference (ontologies) for experiment, data and metadata annotations. LoadBDSM extends the capabilities of BDSM to support the emergence of "embryo-formatics" defined here as the data, information and knowledge from genomic sciences applied to, or derived from, an embryological context. This includes, but is not limited to, delineating pathways and biological regulatory networks for specific chemicals or classes of developmental toxicants, developing novel biomarkers indicative of exposure and/or predictive of adverse effects, and integrating modern computing and information technology with data from molecular biology.

Abnormalities, Drug-Induced↗
PubMed2003

Bacillus subtilis during feast and famine: visualization of the overall regulation of protein synthesis during glucose starvation by proteome analysis.

Dual channel imaging and warping of two-dimensional (2D) protein gels were used to visualize global changes of the gene expression patterns in growing Bacillus subtilis cells during entry into the stationary phase as triggered by glucose exhaustion. The 2D gels only depict single moments during the cells' growth cycle, but a sequential series of overlays obtained at specific points of the growth curve facilitates visualization of the developmental processes at the proteomics scale. During glucose starvation a substantial reprogramming of the protein synthesis pattern was found, with 150 proteins synthesized de novo and cessation of the synthesis of almost 400 proteins. Proteins induced following glucose starvation belong to two main regulation groups: general stress/starvation responses induced by different stresses or starvation stimuli (sigma(B)-dependent general stress regulon, stringent response, sporulation), and glucose-starvation-specific responses (drop in glycolysis, utilization of alternative carbon sources, gluconeogenesis). Using the dual channel approach, it was not only possible to identify those regulons or stimulons, but also to follow the fate of each single protein by the three-color code: red, newly induced but not yet accumulated; yellow, synthesized and accumulated; and green, still present, but no longer being synthesized. These green proteins, which represent a substantial part of the protein pool in the nongrowing cell, are not accessible by using DNA arrays. The combination of 2D gel electrophoresis and MALDI TOF mass spectrometry with the dual channel imaging technique provides a new and comprehensive view of the physiology of growing or starving bacterial cell populations, here for the case of the glucose-starvation response.

Bacillus subtilis↗
PubMed2003

What is the relevance of bioinformatics to pharmacology?

Although bioinformatics achieved prominence because of its central role in genome data storage, management and analysis, its focus has shifted as the life sciences exploit these data. In pharmacology, genomic, transcriptomic and proteomic data are being used in the quest for drugs that fulfill unmet medical needs, are disease modifying or curative and are more effective and safer than current drugs. Bioinformatics is used in drug target identification and validation and in the development of biomarkers and toxicogenomic and pharmacogenomic tools to maximize the therapeutic benefit of drugs. Now that the 'parts list' of cellular signalling pathways is available, integrated computational and experimental programmes are being developed, with the goal of enabling in silico pharmacology by linking the genome, transcriptome and proteome to cellular pathophysiology.

Computational Biology↗
PubMed2006

Proteomic analysis on the alteration of protein expression in the placental villous tissue of early pregnancy loss.

Early pregnancy loss is the most common complication of human reproduction. Given the complexities of early development, it is likely that many mechanisms are involved. Knowledge of differences in protein expression in parallel profiling is essential to understand the comprehensive pathophysiological mechanism underlying early pregnancy loss. To identify proteins with different expression profiles related to early pregnancy loss, we applied a proteomic approach and performed two-dimensional gel electrophoresis (2-DE) on six placental villous tissues from patients with early pregnancy loss and six from normal pregnant women, followed by comparison of the silver-stained 2-DE profiles. It was found that 13 proteins were downregulated and 5 proteins were upregulated significantly (P < 0.05) in early pregnancy loss as determined by spot volume. Among them, 10 downregulated and 2 upregulated spots were identified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Anomalies of these proteins, including three principal antioxidant enzymes (copper/zinc-superoxide dismutase, peroxiredoxin 3, and thioredoxin-like 1 protein), S100 calcium binding protein, galectin-1, chorionic somatomammotropin hormone 1, transthyretin, fas inhibitory molecule, eukaryotic translation elongation factor, RNA-binding protein, ubiquitin-conjugating enzyme E2N, and proteasome beta-subunit, indicate widespread failure in cell regulations and processes such as antioxidative defense, differentiation, cell proliferation, metabolism, apoptosis, transcription, and proteolysis in early pregnancy loss. This study has identified several proteins that are associated with placentation and early development, shedding a new insight into the proteins that may be potentially involved in the pathophysiological mechanisms underlying early pregnancy loss.

Abortion, Spontaneous↗
PubMedDate not supplied

Proteomic analysis of the sarcosine-insoluble outer membrane fraction of Pseudomonas aeruginosa responding to ampicilin, kanamycin, and tetracycline resistance.

Nosocomial wound infections by antibiotic-resistant Pseudomonas aeruginosa strains have increasing importance in hospitals. Outer membrane proteins of the bacterium have strong influence on its resistance to antibiotics. In the current study, a parallel proteomic approach was applied to analysis of sarcosine-insoluble outer membrane fraction of P. aeruginosa responding to ampicilin, kanamycin and tetracycline resistances. Eleven differential proteins with 15 spots were determined and then identified by MALDI-TOF/MS, in which four with increased OprF, MexA, OmpH, and decreased hypothetical protein (NCBI No. 15599856), six with increased OprF, OmpH, hypothetical protein (NCBI No. 15599183) and decreased OprG, MexA, conserved hypothetical protein (NCBI No. 15600371), and eight with increased OprF, MexA, OprL, probable Omp (NCBI No. 15599856), probable secretion protein (NCBI No. 15600167), OprD and decreased OprG, conserved hypothetical protein (NCBI No. 15600371) responded to ampicilin, kanamycin, and tetracycline resistances, respectively. With the exception of OprF, the other differential proteins did not show the same behaviors against the three antibiotic resistances. Compared with our previous report on E. coli Omps responding to ampicilin and tetracycline resistances, which was only a protein difference in quality between the two antibiotics, P. aeruginosa showed significant diversity against the three antibiotics. Our findings might provide valuable data for an understanding of antibiotic-resistant difference between different species of bacteria. Meanwhile, these proteins shared by different bacteria or a bacterium against different antibiotics may provide universal targets for the development of new drugs that control antibiotic-resistant bacteria.

Ampicillin↗
PubMed2001

Proteome analysis of a human heptocellular carcinoma cell line, HCC-M: an update.

Recently, we reported the proteome analysis of a human hepatocellular carcinoma cell line, HCC-M (Electrophoresis 2000, 21, 1787-1813), using two-dimensional gel electrophoresis (2-DE) and matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS). From a total of 408 unique spots excised from the 2-DE gel, 301 spots yielded good MALDI spectra. Out of these, 272 spots had matches returned from the database search leading to the identification of these proteins. Here, we report the results on the identification of the remaining 29 spots using nanoelectrospray ionization-tandem mass spectrometry (nESI-MS/MS). First, "peptide tag sequencing" was performed to obtain partial amino acid sequences of the peptides to search the SWISS-PROTand NCBI nonredundant protein databases. Spots that were still not able to find any matches from the databases were subjected to de novo peptide sequencing. The tryptic peptide sequences were used to search for homologues in the protein and nucleotide databases with the NCBI Basic Local Alignment Search Tool (BLAST), which was essential for the characterization of novel or post-translationally modified proteins. Using this approach, all the 29 spots were unambiguously identified. Among them, phosphotyrosyl phosphatase activator (PTPA), RNA-binding protein regulatory subunit, replication protein A 32 kDa subunit (RP-A) and N-acetylneuraminic acid phosphate synthase were reported to be cancer-related proteins.

Carcinoma, Hepatocellular↗
PubMed2003

High-content proteomics: fluorescence multiplexing using an integrated, high-sensitivity, multiwavelength charge-coupled device imaging system.

The detection of proteins in 2-D gels and their subsequent identification by MS is still the "gold standard" in proteomics. Fluorescent detection has increasingly replaced colorimetric and radiometric detection on gels and blots. The reasons for this are multiple and varied and include higher sensitivity, better quantitation, increased dynamic range, speed, safety and ease of use. Unlike other methods, fluorescent protein detection is also typically very consistent in response from protein to protein and in many cases is compatible with MS methods for protein identification. The superior sensitivity and benefits achieved by fluorescent techniques have spurred the development of instrumentation capable of delivering precise, sensitive, high-resolution image acquisition over a wide variety of excitation and emission wavelengths. This report focuses on applications using the highly sensitive, charge-coupled device based ProXPRESS multilabel imager, readily configurable for image acquisition over a wide variety of wavelengths (380-700 nm and ultraviolet (UV)) using xenon lamp or UV excitation. The ability to simultaneously detect enzyme activities or protein modifications with different color fluorescent probes in addition to total protein amounts (multiplexing) allows the further mining of proteomic data content from a single set of protein samples. To this end, the development of instrumentation that enables a multiplexing strategy will become central to in-depth proteomic studies. The ProXPRESS maximizes the efficiency of experimental strategies that require flexibility and multicolor fluorescence detection.

Electrophoresis, Gel, Two-Dimensional↗