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Results for “proteome mapping”

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At least 451 records · Page 25Linked to original sources
PubMed2005

Proteomic analysis of neural differentiation of mouse embryonic stem cells.

Mouse embryonic stem cells (mESCs) can differentiate into different types of cells, and serve as a good model system to study human embryonic stem cells (hESCs). We showed that mESCs differentiated into two types of neurons with different time courses. To determine the global protein expression changes after neural differentiation, we employed a proteomic strategy to analyze the differences between the proteomes of ES cells (E14) and neurons. Using 2-DE plus LC/MS/MS, we have generated proteome reference maps of E14 cells and derived dopaminergic neurons. Around 23 proteins with an increase or decrease in expression or phosphorylation after differentiation have been identified. We confirmed the downregulation of translationally controlled tumor protein (TCTP) and upregulation of alpha-tubulin by Western blotting. We also showed that TCTP was further downregulated in derived motor neurons than in dopaminergic neurons, and its expression level was independent of extracellular Ca(2+) concentration during neural differentiation. Potential roles of TCTP in modulating neural differentiation through binding to Ca(2+), tubulin and Na,K-ATPase, as well as the functional significance of regulation of other proteins such as actin-related protein 3 (Arp3) and Ran GTPase are discussed. This study demonstrates that proteomic tools are valuable in studying stem cell differentiation and elucidating the underlying molecular mechanisms.

Animals↗
PubMed2003

Use of serological proteomic methods to find biomarkers associated with breast cancer.

New technologies for the detection and therapy of early stage breast cancer are urgently needed. Pathological changes in breast might be reflected in proteomic patterns in serum. A proteomic tool was used to identify proteomic patterns in serum that distinguishes neoplastic from non-neoplastic disease within the breast. Preliminary results derived from the serum analysis from 54 unaffected women and 76 patients with breast cancer were analyzed by two-dimensional (2-D) electrophoresis and matrix-assisted laser desorption/ionization-time of flight mass spectrometry, HSP27 was found up-regulated while 14-3-3 sigma was down-regulated in the serum of breast cancer patients. The two protein biomarkers were then used to classify an independent set of 104 masked serum samples. The results showed that the protein pattern on 2-D gels can completely segregate the serum of breast cancer from non-cancer. The discriminatory pattern correctly identified all 69 breast cancer cases in the masked set. Of the 35 cases of non-malignant disease, 34 were recognized as non-cancer. These findings justify a prospective population-based assessment of proteomic technology as a screening or diagnostic tool for breast cancer in high-risk and general populations. These two protein biomarkers could also be used as targets for further study in drug design and breast cancer therapy.

Adult↗
PubMed1999

Scanning the available Dictyostelium discoideum proteome for O-linked GlcNAc glycosylation sites using neural networks.

Dictyostelium discoideum has been suggested as a eukaryotic model organism for glycobiology studies. Presently, the characteristics of acceptor sites for the N-acetylglucosaminyl-transferases in Dictyostelium discoideum, which link GlcNAc in an alpha linkage to hydroxyl residues, are largely unknown. This motivates the development of a species specific method for prediction of O-linked GlcNAc glycosylation sites in secreted and membrane proteins of D. discoideum. The method presented here employs a jury of artificial neural networks. These networks were trained to recognize the sequence context and protein surface accessibility in 39 experimentally determined O-alpha-GlcNAc sites found in D. discoideum glycoproteins expressed in vivo. Cross-validation of the data revealed a correlation in which 97% of the glycosylated and nonglycosylated sites were correctly identified. Based on the currently limited data set, an abundant periodicity of two (positions-3, -1, +1, +3, etc.) in Proline residues alternating with hydroxyl amino acids was observed upstream and downstream of the acceptor site. This was a consequence of the spacing of the glycosylated residues themselves which were peculiarly found to be situated only at even positions with respect to each other, indicating that these may be located within beta-strands. The method has been used for a rapid and ranked scan of the fraction of the Dictyostelium proteome available in public databases, remarkably 25-30% of which were predicted glycosylated. The scan revealed acceptor sites in several proteins known experimentally to be O-glycosylated at unmapped sites. The available proteome was classified into functional and cellular compartments to study any preferential patterns of glycosylation. A sequence based prediction server for GlcNAc O-glycosylations in D. discoideum proteins has been made available through the WWW at http://www.cbs.dtu.dk/services/DictyOGlyc/ and via E-mail to DictyOGlyc@cbs.dtu.dk.

Algorithms↗
PubMed2005

Proteomic mass spectra classification using decision tree based ensemble methods.

MOTIVATION: Modern mass spectrometry allows the determination of proteomic fingerprints of body fluids like serum, saliva or urine. These measurements can be used in many medical applications in order to diagnose the current state or predict the evolution of a disease. Recent developments in machine learning allow one to exploit such datasets, characterized by small numbers of very high-dimensional samples. RESULTS: We propose a systematic approach based on decision tree ensemble methods, which is used to automatically determine proteomic biomarkers and predictive models. The approach is validated on two datasets of surface-enhanced laser desorption/ionization time of flight measurements, for the diagnosis of rheumatoid arthritis and inflammatory bowel diseases. The results suggest that the methodology can handle a broad class of similar problems.

Algorithms↗
PubMed2004

Proteomic profiling of bone marrow mesenchymal stem cells upon transforming growth factor beta1 stimulation.

Bone marrow mesenchymal stem cells (MSCs) can differentiate into different types of cells and have tremendous potential for cell therapy and tissue engineering. Transforming growth factor beta1 (TGF-beta) plays an important role in cell differentiation and vascular remodeling. We showed that TGF-beta induced cell morphology change and an increase in actin fibers in MSCs. To determine the global effects of TGF-beta on MSCs, we employed a proteomic strategy to analyze the effect of TGF-beta on the human MSC proteome. By using two-dimensional gel electrophoresis and electrospray ionization coupled to quadrupole/time-of-flight tandem mass spectrometers, we have generated a proteome reference map of MSCs, and we identified approximately 30 proteins with an increase or decrease in expression or phosphorylation in response to TGF-beta. The proteins regulated by TGF-beta included cytoskeletal proteins, matrix synthesis proteins, membrane proteins, metabolic enzymes, etc. TGF-beta increased the expression of smooth muscle alpha-actin and decreased the expression of gelsolin. Overexpression of gelsolin inhibited TGF-beta-induced assembly of smooth muscle alpha-actin; on the other hand, knocking down gelsolin expression enhanced the assembly of alpha-actin and actin filaments without significantly affecting alpha-actin expression. These results suggest that TGF-beta coordinates the increase of alpha-actin and the decrease of gelsolin to promote MSC differentiation. This study demonstrates that proteomic tools are valuable in studying stem cell differentiation and elucidating the underlying molecular mechanisms.

Actins↗
PubMed2006

Multivariable difference gel electrophoresis and mass spectrometry: a case study on transforming growth factor-beta and ERBB2 signaling.

Multivariable DIGE/MS was used to investigate proteins altered in expression and/or post-translational modification in response to activation of transforming growth factor (TGF)-beta receptors in MCF10A mammary epithelial cells overexpressing the HER2/Neu (ErbB2) oncogene. Proteome changes were monitored in response to exogenous TGF-beta over time (0, 8, 24, and 40 h), and proteins were resolved using medium range (pH 4-7) and narrow range (pH 5.3-6.5) isoelectric focusing combined with up to 2 mg of protein to allow inspection of lower abundance proteins. Triplicate samples were prepared independently and analyzed together across multiple DIGE gels using a pooled sample internal standard to quantify expression changes with statistical confidence. Unsupervised principle component analysis and hierarchical clustering of the individual DIGE proteome expression maps provided independent confirmation of distinct expression patterns from the individual experiments and demonstrated high reproducibility between replicate samples. Fifty-nine proteins (including some isoforms) that exhibited significant kinetic expression changes were identified using mass spectrometry and database interrogation and were mapped to existing biological networks involved in TGF-beta signaling. Several proteins with a potential role in breast cancer, such as maspin and cathepsin D, were identified as novel molecules associated with TGF-beta signaling.

Amino Acid Sequence↗
PubMed2006

Ultra-fast tandem mass spectrometry scanning combined with monolithic column liquid chromatography increases throughput in proteomic analysis.

Liquid chromatography combined with electrospray ionization mass spectrometry (LC/ESI-MS) has been used successfully for the characterization of biomolecules in proteomics in the last few years. This methodology relied largely on the use of reversed-phase chromatography, in particular C18-based resins, which are suitable for separation of peptides. Here we show that polymeric [polystyrene divinylbenzene] monolithic columns can be used to separate peptide mixtures faster and at a higher resolution. For 500 fmol bovine serum albumin, up to 68% sequence coverage and Mascot Mowse scores of >2000 were obtained using a 9 min gradient on a monolithic column coupled to an ion trap mass spectrometer with ultra-fast MS/MS scan rates. In order to achieve similar results using C18 columns, it was necessary to extend gradient times to 30 min. In addition, we demonstrate the utility of this approach for the analysis of whole Escherichia coli cell lysates by one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE) in combination with LC/MS/MS using 4 min gradients on monolithic columns. Our results indicate higher throughput capabilities of monolithic columns (3-fold gain in time or more) for conventional proteomics applications, such as protein identification and high sequence coverage usually required for detection of post-translational modifications (PTMs). Further optimization of sensitivity and quality of sequence information is discussed, in particular when combined with mass spectrometers that have very fast MS-MS/MS switching and scanning capabilities.

Animals↗
PubMed2006

Proteomic analysis of human immunodeficiency virus using liquid chromatography/tandem mass spectrometry effectively distinguishes specific incorporated host proteins.

A major challenge to studying virus-incorporated host proteins is the fact that they are not encoded by the viral genome. We used Liquid Chromatography/Tandem Mass Spectrometry (LC-MS/MS) on whole virions to obtain a snapshot of the HIV-1 proteome. We identified known viral and host-cellular proteins and also identified novel components of HIV-1 and confirm these by traditional biochemical methods. Our comparison of wild-type and mutant viruses demonstrates that LC-MS/MS has the specificity to distinguish the presence/absence of a single host protein in intact virions.

Amino Acid Sequence↗
PubMed2004

Bioinformatics and cellular signaling.

The understanding of cellular function requires an integrated analysis of context-specific, spatiotemporal data from diverse sources. Recent advances in describing the genomic and proteomic 'parts list' of the cell and deciphering the interrelationship of these parts are described, including genome-wide location analysis, standards for microarray data analysis, and two-hybrid and mass spectrometry approaches. This information is being collected and curated in databases such as the Alliance for Cellular Signaling (AfCS) Molecule Pages, which will serve as vital tools for the reconstruction and analysis of cellular signaling networks.

Cell Physiological Phenomena↗
PubMed2007

Proteome profile of cytosolic component of zebrafish liver generated by LC-ESI MS/MS combined with trypsin digestion and microwave-assisted acid hydrolysis.

The zebrafish genome has recently been sequenced and annotated allowing for high-throughput proteomic analysis. Here, we report for the first time a proteomic subset of zebrafish liver, an important organ for metabolizing toxins. Using a newly developed analytical procedure, we have identified 1204 proteins from the cytosolic component of a zebrafish liver tissue sample. Our methods involve cell-compartment fractionation of liver tissue samples, four levels of protein digestion, and off-line two-dimensional liquid chromatography (2-D LC) separations of resultant peptides. Proteins are identified using an electrospray ionization quadrupole time-of-flight tandem mass spectrometer (ESI-QTOF MS/MS), which provides high-resolution and high-accuracy mass measurement of peptide ions and their fragment ions. We demonstrate that greater proteome coverage can be achieved by combining the results obtained from four methods of protein digestion: three tryptic digests (one in buffer, one in methanol, and another in SDS), and a microwave-assisted acid hydrolysate of the protein extracts. Identified proteins--which included several groups of established protein biomarkers--were functionally classified. We discuss the functions and implications of these biomarkers within the context of zebrafish toxicology.

Animals↗
PubMedDate not supplied

Defining mitogen-activated protein kinase pathways with mass spectrometry-based approaches.

Mitogen-activated protein kinases are a group of ubiquitously expressed kinase pathways that have been conserved from yeast through humans. They control a large number of critical cell functions. Identification of targets of those kinases is necessary to define signal transduction pathways that lead to cell responses. The application of a number of mass spectrometry-based techniques to the identification of phosphoproteins is reviewed. A new proteomic approach is described for the identification of the downstream targets of specific kinases that combines phosphorylation of cell lysates in in vitro kinase reactions by active recombinant kinase with protein separation by two-dimensional (2D) gel electrophoresis or SDS-PAGE and phosphoprotein identification by MALDI-TOF mass spectrometry or by phosphopeptide enrichment and tandem mass spectrometry. The results suggested that a combination of multiple approaches will be required to fully identify phosphoproteomes.

Animals↗
PubMedDate not supplied

Proteolytic 18O-labeling strategies for quantitative proteomics.

A number of proteomic techniques have been developed to quantify proteins in biological systems. This review focuses on the quantitative proteomic technique known as "proteolytic 18O-labeling." This technique utilizes a protease and H(2)18O to produce labeled peptides, with subsequent chromatographic and mass spectrometric analysis to identify and quantify (relative) the proteins from which the peptides originated. The technique determines the ratio of individual protein's expression level between two samples relative to each other, and can be used to quantitatively examine protein expression (comparative proteomics) and post-translational modifications, and to study protein-protein interactions. The present review discusses various aspects of the 18O-labeling technique, including: its history, the advantages and disadvantages of the proteolytic 18O-labeling technique compared to other techniques, enzymatic considerations, the problem of variable incorporation of 18O atoms into peptides with a discussion on recent advancements of the technique to overcome it, computational tools to interpret the data, and a review of the biological applications.

Gene Expression Profiling↗
PubMed2005

Protein identification assisted by the prediction of retention time in liquid chromatography/tandem mass spectrometry.

Two-dimensional liquid chromatography (2D-LC) coupled on-line with electrospray ionization tandem mass spectrometry (2D-LC-ESI-MS/MS) is a new platform for analysis and identification of proteome. Peptides are separated by 2D-LC and then performed MS/MS analysis by tandem MS/MS. The MS/MS data are searched against database for protein identification. In one 2D-LC-ESI-MS/MS run, we obtained not only the structural information of peptides directly from MS/MS, but also the retention time of peptides eluted from LC. Information on the chromatographic behavior of peptides can assist protein identification in the new platform for proteomics. The retention time of the matching peptides of the identified protein was predicted by the hydrophobic contribute of each amino acid on reversed-phase liquid chromatography (RPLC). By using this strategy proteins were identified by four types of information: peptide mass fingerprinting (PMF), sequence query, and MS/MS ions searched and the predicted retention time. This additional information obtained from LC could assist protein identification with no extra experimental cost.

Amino Acid Sequence↗
PubMed2006

Proteomic approaches to bacterial differentiation.

Mass spectrometry-based proteomics has been used extensively to explore the proteomes of various organisms, and this technology is now being applied to the characterization of bacterial species. Predominantly, two methods emerge as leaders in this application. Intact protein profiling creates fingerprints of bacterial species which can be used for differentiation and tracking over time. Peptide-centric approaches, analyzed after enzymatic digestion, enable high-throughput proteome characterization in addition to species determination from the identification of peptides distinctive to a species. Highlighted herein is an application of a peptide-centric approach to the identification and quantitation of species-specific peptide identifiers using an in silico exploration and an experimental mass spectrometry-based method. The application to microbial communities is addressed with an in silico analysis of an artificial complex community of 25 microorganisms.

Bacteria↗
PubMed2004

Protein expression patterns in primary carcinoma of the vagina.

Protein patterns in six samples from primary vaginal cancers, in five from normal vaginal tissue and in five primary cervical cancers, were analysed using two-dimensional polyacrylamide gel electrophoresis (2-DE). Protein expression profile was evaluated by computer-assisted image analysis (PDQUEST) and proteins were subsequently identified using matrix-assisted laser desorption/ionisation mass spectrometry. The aim was to analyse the protein expression profiles using the hierarchical clustering method in vaginal carcinoma and to compare them with the protein pattern in cervical carcinoma in order to find a helpful tool for correct classification and for increased biomedical knowledge. Protein expression data of a distinct set of 33 protein spots were differentially expressed. These differences were statistically significant (Mann-Whitney signed-Ranked Test, P<0.05) between normal tissue, vaginal and cervical cancer. Furthermore, protein profiles of pairs of primary vaginal and cervical cancers were found to be very similar. Some of the protein spots that have so far been identified include Tropomyosin 1, cytokeratin 5, 15 and 17, Apolipoprotein A1, Annexin V, Glutathione-S-transferase. Others are the stress-related proteins, calreticulin, HSP 27 and HSP 70. We conclude that cluster analysis of proteomics data allows accurate discrimination between normal vaginal mucosa, primary vaginal and primary cervical cancer. However, vaginal and cervical carcinomas also appear to be relatively homogeneous in their gene expression, indicating similar carcinogenic pathways. There might, further, be a possibility to identify tumour-specific markers among the proteins that are differentially expressed. The results from this study have to be confirmed by more comprehensive studies in the future.

Adenocarcinoma↗
PubMed2006

Global topological features of cancer proteins in the human interactome.

MOTIVATION: The study of interactomes, or networks of protein-protein interactions, is increasingly providing valuable information on biological systems. Here we report a study of cancer proteins in an extensive human protein-protein interaction network constructed by computational methods. RESULTS: We show that human proteins translated from known cancer genes exhibit a network topology that is different from that of proteins not documented as being mutated in cancer. In particular, cancer proteins show an increase in the number of proteins they interact with. They also appear to participate in central hubs rather than peripheral ones, mirroring their greater centrality and participation in networks that form the backbone of the proteome. Moreover, we show that cancer proteins contain a high ratio of highly promiscuous structural domains, i.e., domains with a high propensity for mediating protein interactions. These observations indicate an underlying evolutionary distinction between the two groups of proteins, reflecting the central roles of proteins, whose mutations lead to cancer. CONTACT: paul.bates@cancer.org.uk SUPPLEMENTARY INFORMATION: The interactome data are available though the PIP (Potential Interactions of Proteins) web server at http://bmm.cancerresearchuk.org/servers/pip. Further additional material is available at http://bmm.cancerresearchuk.org/servers/pip/bioinformatics/

Algorithms↗
PubMed2003

Functional genomics and proteomics as a foundation for systems biology.

Developments in high-throughput measurement technologies for biological molecules have created a paradigm shift in modern life science research. The field of systems biology attempts to provide a systems-level understanding by systematically organising the genomic, functional genomic and proteomic data obtained from genetic and environmental perturbations of interest and using the data to build a descriptive and mechanistic model of the biological phenomena. The goal is to build a mathematical framework with some predictive abilities. This review highlights the need for system-level understanding, lists some of the high-throughput measurement tools of importance in systems biology, reviews various types of experimental and computational approaches being used in systems biology research and attempts to address some of the challenges facing this research community.

Animals↗
PubMed2002

[Analysis of the proteomic changes of the serum of the Smad3 targeted deficient mice].

We have studied the proteomic changes of the serum of the Smad3 targeted deficient mice using 2-DE and PMF approaches. 7 proteins expressed at different level in wild type mice and the Smad3 deficient mice were identified. These results would benefit the research on diagnosis and therapy of osteoarthritis and provided clues to studying the important function of Smad3 mediated TGF-beta signals during the skeletal development.

Animals↗