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Results for “Functional proteome”

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PubMed2003

A functional proteomics approach to signal transduction.

The purpose of this review is to highlight how proteomics techniques can be used to answer specific questions related to signal transduction in a wide variety of systems. In our laboratory, we utilize proteomic technologies to elucidate signal transduction pathways involved in smooth muscle contraction and relaxation, cell growth and tumorigenesis, and the pathogenesis of malaria. We see the real application of this technology as a tool to enhance the power of existing approaches such as classical yeast and mouse genetics, tissue culture, protein expression systems, and site-directed mutagenesis. Our basic approach is to examine only those proteins that differ by some variable from the control sample. In this way, the number of proteins to be processed by electrophoresis, Edman degradation, or mass spectrometry is greatly reduced. In addition, since only those proteins that change in response to a given biological treatment are analyzed, the experimental outcome provides information about specific signaling pathways. Examples of typical experiments in our laboratory are measurement of changes in protein phosphorylation in response to treatment of cells with growth factors or specific drugs, characterization of proteins associated with a bait protein in a "pull-down" experiment, or measurement of changes in protein expression. Frequently, in these experiments, it is necessary to define complex protein mixtures. To achieve this goal, we utilize a variety of techniques to isolate specific types of proteins or "subproteomes" for further analysis. In this review, we discuss strategies used in our laboratory for studying signaling pathways, including subproteome isolation, proteome mining, and analysis of the phosphoproteome.

Amino Acid Sequence↗
PubMed2002

Study of therapy resistance in cancer cells with functional proteome analysis.

Different types of cancer are naturally resistant to many anticancer drugs. Additionally, these tumours develop acquired drug resistance, which includes the classical multidrug resistance (MDR) accompanied by the synthesis of P-glycoprotein, a member of the superfamily of ATP-binding cassette (ABC) transporters. Furthermore, atypical MDR is mediated by several different, some unknown, mechanisms. To overcome chemoresistance problems, antineoplastic drugs are often combined with other modes of therapy, e.g. hyperthermia, where good response has been reported in several experimental tumour models and in advanced cancer patients. The success of this combined anticancer treatment may be limited by an increase in chemoresistance and thermoresistance. A model system to study resistance phenomena is the use of chemoresistant and thermoresistant cancer cell lines. We have established chemoresistant cancer cell lines (gastric and pancreatic carcinoma, fibrosarcoma, melanoma) and now thermoresistant cell lines derived from gastric and pancreatic carcinoma cells and their counterparts that were resistant towards daunorubicin (classical MDR) and mitoxantrone (atypical MDR). Using proteomics, in this paper we evaluate the drug resistance of chemoresistant melanoma cells (parental cell line MeWo and sublines exhibiting drug resistance towards etoposide, cisplatin, fotemustine and vindesine) as a paradigm for analysis of drug resistance phenomena. Additionally, we investigate heat resistance and the interaction of chemoresistance and thermoresistance to identify common pathways using the parental and drug resistant stomach cancer cell lines EPG85-257, EPG85-257RNOV, EPG85-257RDB and their thermoresistant counterparts. Possible implications of differential protein expression will be discussed.

Databases as Topic↗
PubMed2000

A functional proteomics screen of proteases in colorectal carcinoma.

BACKGROUND: Proteases facilitate several steps in cancer progression. To identify proteases most suitable for drug targeting, actual enzyme activity and not messenger RNA levels or immunoassay of protein is the ideal assay readout. MATERIALS AND METHODS: An automated microtiter plate assay format was modified to allow detection of all four major classes of proteases in tissue samples. Fifteen sets of colorectal carcinoma biopsies representing primary tumor, adjacent normal colon, and liver metastases were screened for protease activity. RESULTS: The major proteases detected were matrix metalloproteases (MMP9, MMP2, and MMP1), cathepsin B, cathepsin D, and the mast cell serine proteases, tryptase and chymase. Matrix metalloproteases were expressed at higher levels in the primary tumor than in adjacent normal tissue. The mast cell proteases, in contrast, were at very high levels in adjacent normal tissue, and not detectable in the metastases. Cathepsin B activity was significantly higher in the primary tumor, and highest in the metastases. The major proteases detected by activity assays were then localized in biopsy sections by immunohistochemistry. Mast cell proteases were abundant in adjacent normal tissue, because of infiltration of the lamina propria by mast cells. Matrix metalloproteases were localized to the tumor cells themselves; whereas, cathepsin B was predominantly expressed by macrophages at the leading edge of invading tumors. Although only low levels of urinary plasminogen activator were detected by direct enzyme assay, immunohistochemistry showed abundant protein within the tumor. CONCLUSIONS: This analysis, surveying all major classes of proteases by assays of activity rather than immunolocalization or in situ hybridization alone, serves to identify proteases whose activity is not completely balanced by endogenous inhibitors and which may be essential for tumor progression. These proteases are logical targets for initial efforts to produce low molecular weight protease inhibitors as potential chemotherapy.

Biopsy↗
PubMed2003

Organelle proteomics: implications for subcellular fractionation in proteomics.

Functional proteome analysis is not restricted to the sequence information but includes the broad spectrum of structural modifications and quantitative changes of proteins to which they are subjected in different tissues and cell organelles and during the development of an organism. Cell biology has provided the means required for the analysis of the composition and properties of purified cellular elements. Subcellular fractionation is an approach universal across all cell types and tissues, including cardiac and vascular system. Subcellular fractionation and proteomics form an ideal partnership when it comes to enrichment and analysis of intracellular organelles and low abundant multiprotein complexes. Subcellular fractionation is a flexible and adjustable approach resulting in reduced sample complexity and is most efficiently combined with high-resolution 2D gel/mass spectrometry analysis as well as with gel-independent techniques. In this study we introduce state of the art subcellular fractionation techniques and discuss their suitability, advantages, and limitations for proteomics research.

Animals↗
PubMed2005

Global approach to perinatal medicine: functional genomics and proteomics.

Functional genomics (transcriptomics and proteomics) is a global, systematic and comprehensive approach to the identification and description of the processes and pathways involved in normal and abnormal physiological states. The functional genomics methods most applied today are DNA microarrays and proteomics methods, primarily two-dimensional gel electrophoresis coupled with mass spectrometry. To date, interesting research has been carried out, representing milestones for future implementation of functional genomics/proteomics in perinatal medicine. For instance, possible biomarkers of pre-eclampsia, preterm labor and gestational trophoblastic diseases have been discovered. Further systematic examination of differentially regulated genes and proteins in maternal and fetal tissues and fluids will be required. However, high-throughput technologies reflect biological fluctuations and methodological errors. Large amounts of such different data challenge the performance and capacity of the statistical tools and software available at present. Further major developments in this field are pending and the intellectual investment will certainly result in clinical advances.

Female↗
PubMed2006

Organization of brain complexity--synapse proteome form and function.

Proteomic study of the synapse has generated an extensive list of molecular components, revealing one of the most complex functional systems currently known to cell biology. While fundamental to neural information processing, behaviour and disease, the molecular organisation of the synapse and its relation to higher-level function has yet to be clearly understood. Neurotransmitter receptor complexes, such as the N-methyl-D-aspartate receptor complex (NRC/MASC), are major components of the synaptic proteome. We have recently completed a detailed study of MASC, its functional organisation and involvement in behaviour and disease. This pointed to simple design principles underlying synaptic organisation. Drawing together the results of proteomic and analytical study, we sketch out a model for synaptic functional organisation.

Animals↗
PubMed2002

From combinatorial chemistry to chemical microarray.

Combinatorial chemistry was first applied to the generation of peptide arrays in 1984. Since then, the field of combinatorial chemistry has evolved rapidly into a new discipline. There is a great need for the development of methods to examine the proteome functionally at a global level. Using many of the techniques and instruments developed for DNA microarrays, chemical microarray methods have advanced significantly in the past three years. High-density chemical microarrays can now be synthesized in situ on glass slides or be printed through covalent linkage or non-specific adsorption to the surface of the solid-support with fully automatic arrayers. Microfabrication methods enable one to generate arrays of microsensors at the end of optical fibers or arrays of microwells on a flat surface. In conjunction with the one-bead one-compound combinatorial library method, chemical microarrays have proven to be very useful in lead identification and optimization. High-throughput protein expression systems, robust high-density protein, peptide and small-molecule microarray systems, and automatic mass spectrometers are critical tools for the field of functional proteomics.

Combinatorial Chemistry Techniques↗
PubMed2026

3D Proteomics: Structural, Functional, Chemical and Biomarker Discovery Proteomics With LiP-MS.

Protein structural dynamics drive changes in protein function, making the capture of such dynamics essential for interrogating biological systems. Here we review limited proteolysis coupled to mass spectrometry (LiP-MS), a structural and chemical proteomics method that uses changes in susceptibility to protease cleavage to profile proteome-wide protein structural changes within complex biological samples. In the decade since its development, LiP-MS has become a broadly used structural proteomics method, with peptide-level resolution. It has identified drug targets, delineated altered cellular pathways in response to complex perturbations, revealed structural information on otherwise challenging protein targets, and demonstrated the new concept of structural biomarkers of disease. Because LiP-MS simultaneously probes numerous types of molecular events, such as molecular binding, changes in enzyme activity, chemical modifications, allosteric conformational changes, aggregation, and unfolding, it supports a new proteomics workflow which we term 3D proteomics. This workflow enables the detection of specific functional sites within proteins that are altered upon perturbation, thereby guiding the generation of molecular hypotheses. Further, by globally profiling structural in addition to protein abundance changes, LiP-MS has proven able to greatly increase the information content of functional proteomics screens. In sum, LiP-MS has supported the development of a novel conceptual framework for generating, visualizing, and interpreting structural proteomics data with peptide level resolution, thereby comprehensively probing biological systems. Here we survey the applications of LiP-MS, discuss methodological variants developed by us and others, and describe the use of this new type of omics readout for structural, functional, chemical, and biomarker discovery proteomics.

Proteomics↗
PubMed2004

Broad-based proteomic strategies: a practical guide to proteomics and functional screening.

Proteomics, the study of the proteome (the collection of all the proteins expressed from the genome in all isoforms, polymorphisms and post-translational modifications), is a rapidly developing field in which there are numerous new and often expensive technologies, making it imperative to use the most appropriate technology for the biological system and hypothesis being addressed. This review provides some guidelines on approaching a broad-based proteomics project, including strategies on refining hypotheses, choosing models and proteomic approaches with an emphasis on aspects of sample complexity (including abundance and protein characteristics), and separation technologies and their respective strengths and weaknesses. Finally, issues related to quantification, mass spectrometry and informatics strategies are discussed. The goal of this review is therefore twofold: the first section provides a brief outline of proteomic technologies, specifically with respect to their applications to broad-based proteomic approaches, and the second part provides more details about the application of these technologies in typical scenarios dealing with physiological and pathological processes. Proteomics at its best is the integration of carefully planned research and complementary techniques with the advantages of powerful discovery technologies that has the potential to make substantial contributions to the understanding of disease and disease processes.

Animals↗
PubMedDate not supplied

Interaction proteomics.

The term proteome is traditionally associated with the identification of a large number of proteins within complex mixtures originating from a given organelle, cell or even organism. Current proteome investigations are basically focused on two major areas, expression proteomics and functional proteomics. Both approaches rely on the fractionation of protein mixtures essentially by two-dimensional polyacrylamide gel electrophoresis (2D-gel) and the identification of individual protein bands by mass spectrometric techniques (2D-MS). Functional proteomics approaches are basically addressing two main targets, the elucidation of the biological function of unknown proteins and the definition of cellular mechanisms at the molecular level. In the cell many processes are governed not only by the relative abundance of proteins but also by rapid and transient regulation of activity, association and localization of proteins and protein complexes. The association of an unknown protein with partners belonging to a specific protein complex involved in a particular process would then be strongly suggestive of its biological function. The identification of interacting proteins in stable complexes in a cellular system is essentially achieved by affinity-based procedures. Different strategies relying on this simple concept have been developed and a brief overview of the main approaches presently used in functional proteomics studies is described.

Chromatography, Affinity↗
PubMed2003

Proteomics: advanced technology for the analysis of cellular function.

Proteomics developed initially from the decade-long study of comprehensive protein visualization on two-dimensional electrophoresis gels has been expanded by mass spectrometry and the growth in searchable sequence databases. Currently, by use of more sophisticated technology such as a combination of multidimensional chromatography and mass spectrometry, thousands of proteins can automatically be identified in a day along with semiquantitative information on differential-protein expression. As with differential gene expression by cDNA-chips, the differential-protein analysis is useful for monitoring and identifying proteins involved in various physiological changes in cells or organisms, although the analysis alone does not necessarily provide information regarding the cause of the change or the function of the proteins. However, proteomics also provides the tools to expand into more sophisticated biochemical approaches, such as the study of protein interactions that can be determined directly by performing a pull-down assay with a bait protein followed by mass spectrometric identification of the bound proteins. Proteomics, thus, is useful for both large-scale surveys of proteins and detailed studies of the functional relationships among the proteins of interest. Certainly this approach can be applicable to the assessment of amino acid adequacy and safety.

Animals↗
PubMed2003

Bioverse: Functional, structural and contextual annotation of proteins and proteomes.

Functional annotation is routinely performed for large-scale genomics projects and databases. Researchers working on more specific problems, for instance on an individual pathway or complex, also need to be able to quickly, completely and accurately annotate sequences. The Bioverse sequence annotation server (http://bioverse.compbio.washington.edu) provides a web-based interface to allow users to submit protein sequences to the Bioverse framework. Sequences are functionally and structurally annotated and potential contextual annotations are provided. Researchers can also submit candidate genomes for annotation of all proteins encoded by the genome (proteome).

Internet↗
PubMed2004

Proteomic strategies and their application in studies of renal function.

Proteomics is a promising new tool for functional genomics. In addition to two-dimensional gel electrophoresis, other methods that are based on liquid chromatography and mass spectrometry are now available to study proteins. In this brief article, we review the strengths and limitations of the proteomic approaches currently available to the researcher, and we provide examples of how proteomics has been, and can in the future be, used to study the kidney.

Animals↗
PubMed2006

Quantitative PCR-based approach for rapid phage display analysis: a foundation for high throughput vascular proteomic profiling.

Functional proteomic strategies offer unique advantages over current molecular array approaches, as the epitopes identified can directly provide bioactive peptides for investigational and/or translational applications. The vascular endothelium is well suited to proteomic assessment by in vivo phage display, but extensive enrichment and sequencing steps limit its application for high throughput molecular profiling. To overcome these limitations we developed a quantitative PCR (Q-PCR) strategy to allow the rapid quantification of in vivo phage binding. Primers were designed for distinct clones selected from a defined phage pool to probe for age-associated changes in cardiac vascular epitopes. Sensitivity and specificity of the primer sets were tested and confirmed in vitro. Q-PCR quantification of phage in vivo confirmed the preferential homing of all phage clones to the young rather than old cardiac vasculature and demonstrated a close correlation with phage measurements previously determined using traditional bacterial-based titration methods. This Q-PCR approach provides quantification of phage within hours of phage injection and may therefore be used for rapid, high throughput analysis of binding of defined phage sequences both in vivo and in vitro, complementing nonbiased phage approaches for the proteomic mapping of vascular beds and other tissues.

Aging↗
PubMed2004

Proteome-wide functional classification and identification of prokaryotic transmembrane proteins by transmembrane topology similarity comparison.

We propose a new method for classifying and identifying transmembrane (TM) protein functions in proteome-scale by applying a single-linkage clustering method based on TM topology similarity, which is calculated simply from comparing the lengths of loop regions. In this study, we focused on 87 prokaryotic TM proteomes consisting of 31 proteobacteria, 22 gram-positive bacteria, 19 other bacteria, and 15 archaea. Prior to performing the clustering, we first categorized individual TM protein sequences as "known," "putative" (similar to "known" sequences), or "unknown" by using the homology search and the sequence similarity comparison against SWISS-PROT to assess the current status of the functional annotation of the TM proteomes based on sequence similarity only. More than three-quarters, that is, 75.7% of the TM protein sequences are functionally "unknown," with only 3.8% and 20.5% of them being classified as "known" and "putative," respectively. Using our clustering approach based on TM topology similarity, we succeeded in increasing the rate of TM protein sequences functionally classified and identified from 24.3% to 60.9%. Obtained clusters correspond well to functional superfamilies or families, and the functional classification and identification are successfully achieved by this approach. For example, in an obtained cluster of TM proteins with six TM segments, 109 sequences out of 119 sequences annotated as "ATP-binding cassette transporter" are properly included and 122 "unknown" sequences are also contained.

Algorithms↗