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At least 973 records · Page 54Linked to original sources
PubMed2006

Proteomics identification of differentially expressed proteins associated with pollen germination and tube growth reveals characteristics of germinated Oryza sativa pollen.

Mature pollen from most plant species is metabolically quiescent; however, after pollination, it germinates quickly and gives rise to a pollen tube to transport sperms into the embryo sac. Because methods for collecting a large amount of in vitro germinated pollen grains for transcriptomics and proteomics studies from model plants of Arabidopsis and rice are not available, molecular information about the germination developmental process is lacking. Here we describe a method for obtaining a large quantity of in vitro germinating rice pollen for proteomics study. Two-dimensional electrophoresis of approximately 2300 protein spots revealed 186 that were differentially expressed in mature and germinated pollen. Most showed a changed level of expression, and only 66 appeared to be specific to developmental stages. Furthermore 160 differentially expressed protein spots were identified on mass spectrometry to match 120 diverse protein species. These proteins involve different cellular and metabolic processes with obvious functional skew toward wall metabolism, protein synthesis and degradation, cytoskeleton dynamics, and carbohydrate/energy metabolism. Wall metabolism-related proteins are prominently featured in the differentially expressed proteins and the pollen proteome as compared with rice sporophytic proteomes. Our study also revealed multiple isoforms and differential expression patterns between isoforms of a protein. These results provide novel insights into pollen function specialization.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2006

On the proper use of mass accuracy in proteomics.

Mass measurement is the main outcome of mass spectrometry-based proteomics yet the potential of recent advances in accurate mass measurements remains largely unexploited. There is not even a clear definition of mass accuracy in the proteomics literature, and we identify at least three uses of this term: anecdotal mass accuracy, statistical mass accuracy, and the maximum mass deviation (MMD) allowed in a database search. We suggest using the second of these terms as the generic one. To make the best use of the mass precision offered by modern instruments we propose a series of simple steps involving recalibration of the data on "internal standards" contained in every proteomics data set. Each data set should be accompanied by a plot of mass errors from which the appropriate MMD can be chosen. More advanced uses of high mass accuracy include an MMD that depends on the signal abundance of each peptide. Adapting search engines to high mass accuracy in the MS/MS data is also a high priority. Proper use of high mass accuracy data can make MS-based proteomics one of the most "digital" and accurate post-genomics disciplines.

Mass Spectrometry↗
PubMed2003

Rice proteomics: a step toward functional analysis of the rice genome.

The technique of proteome analysis with two-dimensional PAGE has the power to monitor global changes that occur in the protein expression of tissues and organisms and/or expression that occurs under stresses. In this study, the catalogues of the rice proteome were constructed, and a functional characterization of some of these proteins was examined. Proteins extracted from tissues of rice and proteins extracted from rice under various kinds of stress were separated by two-dimensional PAGE. An image analyzer was used to reveal a total of 10,589 protein spots on 10 kinds of two-dimensional PAGE gels stained by Coomassie Brilliant Blue. The separated proteins were electroblotted onto a polyvinylidene difluoride membrane, and the N-terminal amino acid sequences of 272 of 905 proteins were determined. The internal amino acid sequences of 633 proteins were determined using a protein sequencer or mass spectrometry after enzyme digestion of the proteins. Finally, a data file of rice proteins that included information on amino acid sequences and sequence homologies was constructed. The major proteins involved in the growth and development of rice can be identified using the proteome approach. Some of these proteins, including a calcium-binding protein that turned out to be calreticulin and a gibberellin-binding protein, which is ribulose-1,5-bisphosphate carboxylase/oxygenase activase in rice, have functions in the signal transduction pathway. The information thus obtained from the rice proteome will be helpful in predicting the function of the unknown proteins and will aid in their molecular cloning.

Agrobacterium tumefaciens↗
PubMed2005

Proteomic profiling of pancreatic cancer for biomarker discovery.

Pancreatic cancer is a uniformly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. In recent years, there has been a substantial interest in applying proteomics technologies to identify protein biomarkers for early detection of cancer. Quantitative proteomic profiling of body fluids, tissues, or other biological samples to identify differentially expressed proteins represents a very promising approach for improving the outcome of this disease. Proteins associated with pancreatic cancer identified through proteomic profiling technologies could be useful as biomarkers for the early diagnosis, therapeutic targets, and disease response markers. In this article, we discuss recent progress and challenges for applying quantitative proteomics technologies for biomarker discovery in pancreatic cancer.

Biomarkers, Tumor↗
PubMed2006

Proteomics in clinical trials and practice: present uses and future promise.

The study of clinical proteomics is a promising new field that has the potential to have many applications, including the identification of biomarkers and monitoring of disease, especially in the field of oncology. Expression proteomics evaluates the cellular production of proteins encoded by a particular gene and exploits the differential expression and post-translational modifications of proteins between healthy and diseased states. These biomarkers may be applied towards early diagnosis, prognosis, and prediction of response to therapy. Functional proteomics seeks to decipher protein-protein interactions and biochemical pathways involved in disease biology and targeted by newer molecular therapeutics. Advanced spectrometry technologies and new protein array formats have improved these analyses and are now being applied prospectively in clinical trials. Further advancement of proteomics technology could usher in an era of personalized molecular medicine, where diseases are diagnosed at earlier stages and where therapies are more effective because they are tailored to the protein expression of a patient's malignancy.

Clinical Trials as Topic↗
PubMed2006

Proteomics-based expression library screening (PELS): a novel method for rapidly defining microbial immunoproteomes.

Current methodologies for global identification of microbial proteins that elicit host humoral immune responses have several limitations and are not ideally suited for use in the postgenomic era. Here we describe a novel application of proteomics, proteomics-based expression library screening, to rapidly define microbial immunoproteomes. Proteomics-based expression library screening is broadly applicable to any cultivable, sequenced pathogen eliciting host antibody responses and hence is ideal for rapidly mining microbial proteomes for targets with diagnostic, prophylactic, and therapeutic potential. In this report, we demonstrate "proof-of-principle" by identifying 207 proteins of the Escherichia coli O157:H7 immunome in bovine reservoirs in only 3 weeks.

Animals↗
PubMed2005

Proteomics in nutrition research: principles, technologies and applications.

The global profiling of the whole protein complement of the genome expressed in a particular cell or organ, or in plasma or serum, makes it possible to identify biomarkers that respond to alterations in diet or to treatment, and that may have predictive value for the modelling of biological processes. Proteomics has not yet been applied on a large scale in nutritional studies, yet it has advantages over transcriptome profiling techniques in that it directly assesses the entities that carry out the biological functions. The present review summarizes the different approaches in proteomics research, with special emphasis on the current technical 'workhorses': two-dimensional (2D)-PAGE with immobilized pH gradients and protein identification by MS. Using a work-flow approach, we provide information and advice on sample handling and preparation, protein solubilization and pre-fractionation, protein separation by 2D-PAGE, detection and quantification via computer-assisted analysis of gels, and protein identification and characterization techniques by means of MS. Examples from nutritional studies employing proteomics are provided to demonstrate not only the advantages but also the limitations of current proteome analysis platforms.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2005

Vectorial proteomics.

Vectorial proteomics is a methodology for the differential identification and characterization of proteins and their domains exposed to the opposite sides of biological membranes. Proteomics of membrane vesicles from defined isolated membranes automatically determine cellular localization of the identified proteins and reduce complexity of protein characterizations. The enzymatic shaving of naturally-oriented, or specifically-inverted sealed membrane vesicles, release the surface-exposed peptides from membrane proteins. These soluble peptides are amenable to various chromatographic separations and to sequencing by mass spectrometry, which provides information on the topology of membrane proteins and on their posttranslational modifications. The membrane shaving techniques have made a breakthrough in the identification of in vivo protein phosphorylation sites in membrane proteins form plant photosynthetic and plasma membranes, and from caveolae membrane vesicles of human fat cells. This approach has also allowed investigation of dynamics for in vivo protein phosphorylation in membranes from cells exposed to different conditions. Vectorial proteomics of membrane vesicles with retained peripheral proteins identify extrinsic proteins associated with distinct membrane surfaces, as well as a variety of posttranslational modifications in these proteins. The rapid integration of versatile vectorial proteomics techniques in the functional characterization of biological membranes is anticipated to bring significant insights in cell biology.

Animals↗
PubMed2002

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and proteomics: a new era in anaerobic microbiology.

Genome sequence data provide a framework for predicting potential microbial activities; however, the proteome content of the cell dictates its response to its environment. Microbiology is witnessing a major initiative to elucidate the nature of the proteome of large numbers of species. The tool driving the proteomic revolution is matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. During the analysis process, proteins are ionized and separated on the basis of their mass-to-charge ratios, which results in a characteristic mass-spectral profile. Because of the dynamic nature of the cell and the large number of external parameters that could influence its mass-spectral profile, considerable work was needed initially to optimize sample analysis and obtain consistent and reproducible results. For many anaerobes that grow poorly or are nonreactive in most diagnostic systems, proteome analysis is likely to have a major impact on microbial diagnosis and the delineation of centers of diversity associated with infections.

Bacteria, Anaerobic↗
PubMed2003

Application of proteomics technology to the field of neurotrauma.

Near-completion of the Human Genome Project has stimulated scientists to begin looking for the next step in unraveling normal and abnormal functions within biological systems. Consequently, there is new focus on the role of proteins in these processes. Proteomics is a burgeoning field that may provide a valuable approach to evaluate the post-traumatic central nervous system (CNS). Although we cannot provide a comprehensive assessment of all methods for protein analysis, this report summarizes some of the newer proteomic technologies that have propelled this field into the limelight and that are available to most researchers in neurotrauma. Three technical approaches (two-dimensional gel electrophoresis, direct analysis by mass spectrometry, including two-dimensional chromatography coupled to mass spectrometry and isotope coded affinity tags, and antibody technologies) are reviewed, and their advantages and disadvantages presented. A discussion of proteomic technology in the context of brain and spinal cord trauma follows, addressing current and future challenges. Proteomics will likely be very useful for developing diagnostic predictors after CNS injury and for mapping changes in proteins after injury in order to identify new therapeutic targets. Neurotrauma results in complex alterations to the biological systems within the nervous system, and these changes evolve over time. Exploration of the "new nervous system" that follows injury will require methods that can both fully assess and simplify this complexity.

Antibodies↗
PubMed2002

The use of accurate mass tags for high-throughput microbial proteomics.

We describe and review progress towards a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements for microbial systems based upon the use of polypeptide accurate mass tags (AMTs) produced by global protein enzymatic digestions. The two-stage strategy exploits high accuracy mass measurements using Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate polypeptide AMTs for a specific organism, from potential mass tags tentatively identified using tandem mass spectrometry (MS/MS), providing the basis for subsequent measurements without the need for routine MS/MS. A high-resolution capillary liquid chromatography separation combined with high sensitivity, and high-resolution accurate FTICR measurements is shown to be capable of characterizing polypeptide mixtures of more than 10(5) components, sufficient for broad protein identification using AMTs. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, and the capability for stable-isotope labeling methods for precise relative protein abundance measurements. The strategy has been initially evaluated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Additional developments, including the use of multiplexed-MS/MS capabilities and methods for dynamic range expansion of proteome measurements that promise to further extend the quality of proteomics measurements, are also described.

Amino Acid Sequence↗
PubMed2004

Genomic and proteomic expression patterns in HPV-16 E6 gene transfected stable human carcinoma cell lines.

cDNA microarray and proteomics studies were performed to analyze the genomic and proteomic expression patterns in HPV-16 E6 gene transfected stable human carcinoma cell lines. Among 1024 known genes and ESTs tested by cDNA microarray, we found 50 upregulated and 35 downregulated genes in RC10.1 HPV-16 E6 transfected human colon adenocarcinoma cells compared to RKO cells, and 27 upregulated and 43 downregulated genes in A549E6 HPV-16 E6 transfected human lung adenocarcinoma cells compared to A549 cells. Employing two dimensional gel electrophoresis and MALDI-TOF-MS, the global pattern of protein expressions in RC10.1 human colon adenocarcinoma and A549E6 human lung adenocarcinoma cell lines stably expressing the HPV 16-E6 gene were compared with those of RKO and A549 cell lines to generate a differential protein expression catalog. We found 13 upregulated and 13 downregulated proteins in RC10.1 (E6-expressing RKO) cells compared to RKO cells and 12 upregulated and 14 downregulated proteins in A549E6 (E6-expressing A549) cells compared to A549 cells. The identified genes and proteins were classified into several groups according to the subcellular function. Expressing pattern of three genes and proteins (CDK5, Bak, and I-TRAF) were matched in both analyses of cDNA microarray and proteomics. These powerful approaches using cDNA microarray and proteomics could provide in-depth information on the impact of HPV-16 E6-related genes and proteins. Differential gene and protein expression patterns by transfection of HPV-16 E6 will provide the nucleus of valuable resource for investigation of the biochemical basis of cervical carcinogenesis. Further understanding of this data base may provide valuable resources for developing novel diagnostic markers and therapeutic targets of cervical cancer.

Adenocarcinoma↗
PubMed2004

Organellar proteomics reveals Golgi arginine dimethylation.

The Golgi complex functions to posttranslationally modify newly synthesized proteins and lipids and to sort them to their sites of function. In this study, a stacked Golgi fraction was isolated by classical cell fractionation, and the protein complement (the Golgi proteome) was characterized using multidimensional protein identification technology. Many of the proteins identified are known residents of the Golgi, and 64% of these are predicted transmembrane proteins. Proteins localized to other organelles also were identified, strengthening reports of functional interfacing between the Golgi and the endoplasmic reticulum and cytoskeleton. Importantly, 41 proteins of unknown function were identified. Two were selected for further analysis, and Golgi localization was confirmed. One of these, a putative methyltransferase, was shown to be arginine dimethylated, and upon further proteomic analysis, arginine dimethylation was identified on 18 total proteins in the Golgi proteome. This survey illustrates the utility of proteomics in the discovery of novel organellar functions and resulted in 1) a protein profile of an enriched Golgi fraction; 2) identification of 41 previously uncharacterized proteins, two with confirmed Golgi localization; 3) the identification of arginine dimethylated residues in Golgi proteins; and 4) a confirmation of methyltransferase activity within the Golgi fraction.

Amino Acid Sequence↗
PubMed2006

Proteomic analysis of the yeast mitochondrial outer membrane reveals accumulation of a subclass of preproteins.

Mitochondria consist of four compartments-outer membrane, intermembrane space, inner membrane, and matrix--with crucial but distinct functions for numerous cellular processes. A comprehensive characterization of the proteome of an individual mitochondrial compartment has not been reported so far. We used a eukaryotic model organism, the yeast Saccharomyces cerevisiae, to determine the proteome of highly purified mitochondrial outer membranes. We obtained a coverage of approximately 85% based on the known outer membrane proteins. The proteome represents a rich source for the analysis of new functions of the outer membrane, including the yeast homologue (Hfd1/Ymr110c) of the human protein causing Sjögren-Larsson syndrome. Surprisingly, a subclass of proteins known to reside in internal mitochondrial compartments were found in the outer membrane proteome. These seemingly mislocalized proteins included most top scorers of a recent genome-wide analysis for mRNAs that were targeted to mitochondria and coded for proteins of prokaryotic origin. Together with the enrichment of the precursor form of a matrix protein in the outer membrane, we conclude that the mitochondrial outer membrane not only contains resident proteins but also accumulates a conserved subclass of preproteins destined for internal mitochondrial compartments.

Aldehyde Oxidoreductases↗
PubMed2002

Operomics: integrated genomic and proteomic profiling of cells and tissues.

In the post-genome era, technologies are becoming available that allow the profiling of tissues and cell populations at multiple levels including genomic (DNA and RNA), proteomic (proteins and peptides) and post-proteomic (eg metabolomic). Operomics refers to the molecular analysis of tissues and cells at the three levels that are connected through the coding process - namely, DNA, RNA and protein. The premise is that no one level or type of analysis fully captures gene expression and that functional changes at the proteome level cannot be simply predicted from analyses at the DNA or RNA levels. An important determinant that weakens a direct link between RNA and protein levels is translational control that differentially regulates mRNA translation. In this paper, the approaches for genomic and proteomic profiling and the contribution of translational control are reviewed.

DNA Methylation↗
PubMed2002

Adapting chromophore-assisted laser inactivation for high throughput functional proteomics.

Recent advances in genomics and proteomics have generated a change in emphasis from hypothesis-based to discovery-based investigations. Genomic and proteomic studies based on differential expression microarrays or comparative proteomics often provide many potential candidates for functionally important roles in normal and diseased cells. High throughput technologies to address protein and gene function in situ are still necessary to exploit these emerging advances in gene and protein discovery in order to validate these identified targets. The pharmaceutical industry is particularly interested in target validation, and has identified it as the critical early step in drug discovery. An especially powerful approach to target validation is a direct protein knockdown strategy called chromophore-assisted laser inactivation (CALI) which is a means of testing the role of specific proteins in particular cellular processes. Recent developments in CALI allow for its high throughput application to address many proteins in tandem. Thus, CALI may have applications for high throughput hypothesis testing, target validation or proteome-wide screening.

Drug Industry↗
PubMed2006

Transcriptomics, proteomics and interactomics: unique approaches to track the insights of bioremediation.

Microbial mediated bioremediation has a great potential to effectively restore contaminated environment, but the lack of information about factors regulating the growth and metabolism of various microbial communities in polluted environment often limits its implementation. Newly seeded techniques such as transcriptomics, proteomics and interactomics offer remarkable promise as tools to address longstanding questions regarding the molecular mechanisms involved in the control of mineralization pathways. During mineralization, transcript structures and their expression have been studied using high-throughput transcriptomic techniques with microarrays. Generally however, transcripts have no ability to operate any physiological response; rather, they must be translated into proteins with significant functional impact. These proteins can be identified by proteomic techniques using powerful two-dimensional polyacrylamide gel electrophoresis (2-DE). Towards the establishment of functional proteomics, the current advances in mass spectrometry (MS) and protein microarrays play a central role in the proteomics approach. Exploring the differential expression of a wide variety of proteins and screening of the entire genome for proteins that interact with particular mineralization regulatory factors would help us to gain insights into bioremediation.

Biodegradation, Environmental↗
PubMed2005

Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps.

MOTIVATION: Determining protein function is one of the most important problems in the post-genomic era. For the typical proteome, there are no functional annotations for one-third or more of its proteins. Recent high-throughput experiments have determined proteome-scale protein physical interaction maps for several organisms. These physical interactions are complemented by an abundance of data about other types of functional relationships between proteins, including genetic interactions, knowledge about co-expression and shared evolutionary history. Taken together, these pairwise linkages can be used to build whole-proteome protein interaction maps. RESULTS: We develop a network-flow based algorithm, FunctionalFlow, that exploits the underlying structure of protein interaction maps in order to predict protein function. In cross-validation testing on the yeast proteome, we show that FunctionalFlow has improved performance over previous methods in predicting the function of proteins with few (or no) annotated protein neighbors. By comparing several methods that use protein interaction maps to predict protein function, we demonstrate that FunctionalFlow performs well because it takes advantage of both network topology and some measure of locality. Finally, we show that performance can be improved substantially as we consider multiple data sources and use them to create weighted interaction networks. AVAILABILITY: http://compbio.cs.princeton.edu/function

Algorithms↗