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PubMed2003

[A novel method for fabrication of tissue microarray].

BACKGROUND & OBJECTIVE: Tissue chip (tissue microarray, TMA) is one of the most important biochip techniques, just following the gene chip and the protein chip, which is one of the most important functional genomics and proteomics research methods in the post-genomic era. However, the present TMA technology has certain shortcomings, such as lack of advanced instruments, tedious procedure, and low sampling accuracy, etc. This new method was designed to improve the technology of TMA. METHODS: A common microscope was installed with a special holing needle, a sampling needle, and a proper box to fix paraffin blocks on the microscope carrier. With the precise mechanical control of microscope, the holing procedure on the recipient paraffin blocks and sampling procedure of core tissue biopsies were performed with the re-equipped microscope. The precise observation and localization of sampling regions were also performed using the same microscope equipped with a stereoscope. RESULTS: The new method simplified TMA procedure, and the whole process of holing, locating, and sampling was performed with the same instrument on the same platform. The single-use holing and sampling needles were first applied to maintain higher accuracy and to avoid the tissue remains and contamination among different samples. And high-qualified tissue chips of colorectal tumors were produced successfully by the new method. CONCLUSION: Using the re-equipped common microscope to fabricate tissue microarrays is a simple, reliable, cost-effective,and well-applicable technique.

Histocytological Preparation Techniques↗
PubMed2003

Predicting antigenic peptides suitable for the selection of phage antibodies.

Selection from phage antibody libraries can be considered to be an in vitro immune system in which the antibody response is reduced to the bare minimum of antigen recognition. Using selections of antibodies on peptides from a phage antibody library, we investigated what constitutes peptide antigenicity in the context of the antibody-protein binding site. We selected polyclonal antibodies in a high throughput format against 44% of 90 overlapping peptides derived from three different proteins. Of these, 33% of peptides (epitopic peptides) were able to select antibodies that recognized the protein from which the peptides were derived. Although no algorithm was able to predict all epitopic peptides, solvent accessibility was the best predictor in this cell-free antibody selection context. We subsequently applied solvent accessibility to successfully predict epitopic peptides from p53 and Znf217, and showed that such peptide selected single-chain antibodies were able to recognize soluble p53 in ELISA and Znf217 in a western blot. This is likely to have considerable utility in functional genomics and proteomics where it should be possible to select antibodies against gene products on the basis of deduced amino acid sequence in a high throughput fashion.

Amino Acid Sequence↗
PubMed2004

The promise of metabolomics in cancer molecular therapeutics.

A systematic elucidation of cancer cell dysfunction and therapeutic mechanisms seems within reach with modern functional genomics and proteomics tools. However, for this potential to be realized, the metabolic consequences of gene expression and protein activity must be understood. 'Metabolomics' is currently a major missing component. It differs from classical metabolic studies by its greater breadth, depth and speed, enabled by the huge advances in analytical instrumentation (especially nuclear magnetic resonance and mass spectrometry) over the past two decades. Multiple metabolic pathways and networks can now be traced by the flow of atoms through metabolites, known as isotopomer analyses. Thus, metabolomics demands both high-throughput and high-information content analyses, and interpretation: the latter is currently a bottleneck. There are currently very few metabolomic studies in cancer therapeutics, despite this great need and potential.

Animals↗
PubMed2005

[A modern method for differential gene expression analysis and its significance for cancer diagnostics and therapy].

Contemporary approaches to diagnostics and therapy in oncology are nowadays tightly coupled to novel findings of biomedical science. One of the main trends in molecular medicine is the development of methodologies enabling parallel monitoring of expression of large quantities of genes or proteins--so called functional genomics and proteomics. These techniques allow determination of differential gene expression, i.e. evaluation of differences in gene expression between two or more cell or tissue samples of different types (e.g. normal or cancer cells) or coming from different culture conditions. These approaches help in elucidating causes of malignant transformation and can serve as a base for development of targeted anticancer gene therapy, monitoring of patient response to treatment and prediction of further disease development. Genomic approaches have undergone rapid development in the last few years--from differential and subtractive hybridisation through differential display all the way to serial analysis of gene expression and DNA microarrays. Besides that, tissue and protein arrays and other proteomic approaches have been also used. Currently DNA microarrays covering expression of the whole human genome, having significant potential in oncological research and clinical praxis, have been used more and more frequently. Many new tumor growth and progression markers were found using such approaches. Some of these markers have been already successfully used in clinical practice (e.g. in breast cancer) for therapy optimisation and minimisation of patient discomfort.

Gene Expression Profiling↗
PubMed2005

Genomic studies in stem cell systems.

Stem cell research holds promise for future regenerative medicine. In recent years, much effort has been devoted to our understanding of stem cell self-renewal and differentiation at the molecular level. Important studies that have applied various genomic approaches, including genomics, functional genomics and proteomics, to gain molecular insights into stem cell development, are reviewed.

Expressed Sequence Tags↗
PubMed2004

Proteomic studies in plants.

Proteomics is a leading technology for the high-throughput analysis of proteins on a genome-wide scale. With the completion of genome sequencing projects and the development of analytical methods for protein characterization, proteomics has become a major field of functional genomics. The initial objective of proteomics was the large-scale identification of all protein species in a cell or tissue. The applications are currently being extended to analyze various functional aspects of proteins such as post-translational modifications, protein-protein interactions, activities and structures. Whereas the proteomics research is quite advanced in animals and yeast as well as Escherichia coli, plant proteomics is only at the initial phase. Major studies of plant proteomics have been reported on subcellular proteomes and protein complexes (e.g. proteins in the plasma membranes, chloroplasts, mitochondria and nuclei). Here several plant proteomics studies will be presented, followed by a recent work using multidimensional protein identification technology (MudPIT).

Cell Membrane↗
PubMed2006

AgBase: a unified resource for functional analysis in agriculture.

Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource 'AgBase' (www.agbase.msstate.edu). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The 'GO Consortium' gene association file contains the most rigorous GO annotations based solely on experimental data. The 'Community' gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations.

Agriculture↗
PubMed2002

Plant functional genomics.

Functional genome analysis of plants has entered the high-throughput stage. The complete genome information from key species such as Arabidopsis thaliana and rice is now available and will further boost the application of a range of new technologies to functional plant gene analysis. To broadly assign functions to unknown genes, different fast and multiparallel approaches are currently used and developed. These new technologies are based on known methods but are adapted and improved to accommodate for comprehensive, large-scale gene analysis, i.e. such techniques are novel in the sense that their design allows researchers to analyse many genes at the same time and at an unprecedented pace. Such methods allow analysis of the different constituents of the cell that help to deduce gene function, namely the transcripts, proteins and metabolites. Similarly the phenotypic variations of entire mutant collections can now be analysed in a much faster and more efficient way than before. The different methodologies have developed to form their own fields within the functional genomics technological platform and are termed transcriptomics, proteomics, metabolomics and phenomics. Gene function, however, cannot solely be inferred by using only one such approach. Rather, it is only by bringing together all the information collected by different functional genomic tools that one will be able to unequivocally assign functions to unknown plant genes. This review focuses on current technical developments and their impact on the field of plant functional genomics. The lower plant Physcomitrella is introduced as a new model system for gene function analysis, owing to its high rate of homologous recombination.

Databases, Factual↗
PubMed2006

The proteomes of neurotransmitter receptor complexes form modular networks with distributed functionality underlying plasticity and behaviour.

Neuronal synapses play fundamental roles in information processing, behaviour and disease. Neurotransmitter receptor complexes, such as the mammalian N-methyl-D-aspartate receptor complex (NRC/MASC) comprising 186 proteins, are major components of the synapse proteome. Here we investigate the organisation and function of NRC/MASC using a systems biology approach. Systematic annotation showed that the complex contained proteins implicated in a wide range of cognitive processes, synaptic plasticity and psychiatric diseases. Protein domains were evolutionarily conserved from yeast, but enriched with signalling domains associated with the emergence of multicellularity. Mapping of protein-protein interactions to create a network representation of the complex revealed that simple principles underlie the functional organisation of both proteins and their clusters, with modularity reflecting functional specialisation. The known functional roles of NRC/MASC proteins suggest the complex co-ordinates signalling to diverse effector pathways underlying neuronal plasticity. Importantly, using quantitative data from synaptic plasticity experiments, our model correctly predicts robustness to mutations and drug interference. These studies of synapse proteome organisation suggest that molecular networks with simple design principles underpin synaptic signalling properties with important roles in physiology, behaviour and disease.

Animals↗
PubMed2003

Fungal proteomics: mapping the mitochondrial proteins of a Trichoderma harzianum strain applied for biological control.

Mitochondria are essential for cellular functions across organisms. A proteomic approach was taken to separate and identify mitochondrial proteins from a strain of Trichoderma harzianum with well established biocontrol properties. We optimized a method for the preparation of a sample enriched with mitochondria by ensuring efficient cell lysis and including several washing steps to minimize cytoplasmic contamination. We separated hundreds of proteins, using two-dimensional gel electrophoresis and identified 31 protein spots from T. harzianum, using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and liquid chromatrography with mass spectrometry. Over 50% of the identified proteins were known to localize in the mitochondria. Three protein spots were identified from T. harzianum and a further five protein spots from the genera Trichoderma and Hypocrea. The remaining protein spots were identified by cross-species identification from other filamentous fungi, including Neurospora crassa and Aspergillus spp, and yeasts, including Saccharomyces cerevisiae and Schizosaccharomyces pombe. In total, we identified 25 protein spots from T. harzianum, representing proteins that have not been characterized in existing Trichoderma protein databases. To our knowledge, this is the first two-dimensional mitochondrial protein map of a filamentous fungus.

Chromatography, Liquid↗
PubMed2003

ST7 is a novel low-density lipoprotein receptor-related protein (LRP) with a cytoplasmic tail that interacts with proteins related to signal transduction pathways.

In 1997, McCormick and co-workers identified a novel putative tumor suppressor gene, designated ST7, encoding a unique protein with transmembrane receptor characteristics [Qing et al. (1999) Oncogene 18, 335-342]. Using degenerate primers corresponding to the highly conserved region of the ligand-binding domains of members of the low-density lipoprotein receptor (LDLR) superfamily, Ishii et al. [Genomics (1998) 51, 132-135] discovered a low-density lipoprotein receptor-related protein (LRP) that closely resembles ST7. Later, another LRP closely resembling ST7 and LRP3 was found (murine LRP9) [Sugiyama et al. (2000) Biochemistry 39, 15817-15825]. These results strongly suggested that ST7 was also a novel member of the low-density lipoprotein receptor superfamily. Proteins of this superfamily have been shown to function in endocytosis and/or signal transduction. To evaluate the relationship of ST7 to the LDLR superfamily proteins and to determine whether ST7 may function in endocytosis and/or signal transduction, we used proteomic tools to analyze the functional motifs present in the protein. Our results indicate that ST7 is a member of a subfamily of the LDLR superfamily and that its cytoplasmic domain contains several motifs implicated in endocytosis and signal transduction. Use of the yeast two-hybrid system to identify proteins that associate with ST7's cytoplasmic domain revealed that this domain interacts with three proteins involved in signal transduction and/or endocytosis, viz., receptor for activated protein C kinase 1 (RACK1), muscle integrin binding protein (MIBP), and SMAD anchor for receptor activation (SARA), suggesting that ST7, like other proteins in the LDLR superfamily, functions in these two pathways. Clearly, ST7 is an LRP, and therefore, it should now be referred to as LRP12.

Amino Acid Motifs↗
PubMed2005

Expression clustering reveals detailed co-expression patterns of functionally related proteins during B cell differentiation: a proteomic study using a combination of one-dimensional gel electrophoresis, LC-MS/MS, and stable isotope labeling by amino acids in cell culture (SILAC).

B cells play an essential role in the immune response. Upon activation they may differentiate into plasma cells that secrete specific antibodies against potentially pathogenic non-self antigens. To identify the cellular proteins that are important for efficient production of these antibodies we set out to study the B cell differentiation process at the proteome level. We performed an in-depth proteomic study to quantify dynamic relative protein expression patterns of several hundreds of proteins at five consecutive time points after lipopolysaccharide-induced activation of B lymphocytes. The proteome analysis was performed using a combination of stable isotope labeling using [13C6]leucine added to the murine B cell cultures, one-dimensional gel electrophoresis, and LC-MS/MS. In this study we identified 1,001 B cell proteins. We were able to quantify the expression levels of a quarter of all identified proteins (i.e. 234) at each of the five different time points. Nearly all proteins revealed changes in expression patterns. The quantitative dataset was further analyzed using an unbiased clustering method. Based on their expression profiles, we grouped the entire set of 234 quantified proteins into a limited number of 12 distinct clusters. Functionally related proteins showed a strong correlation in their temporal expression profiles. The quality of the quantitative data allowed us to even identify subclusters within functionally related classes of proteins such as in the endoplasmic reticulum proteins that are involved in antibody production.

Amino Acids↗
PubMed2006

Update and challenges on proteomics in rice.

Rice is not only an important agricultural resource but also a model plant for biological research. Our previous review highlighted different aspects of the construction of rice proteome database, cataloguing rice proteins of different tissues and organelle, differential proteomics using 2-DE and functional characterization of some of the proteins identified (Komatsu, S., Tanaka, N., Proteomics 2005, 5, 938-949). In this review, the powerfulness and weaknesses of proteomic technologies as a whole and limitations of the currently used techniques in rice proteomics are discussed. The information obtained from these techniques regarding proteins modification, protein-protein interaction and the development of new methods for differential proteomics will aid in deciphering more precisely the functions of known and/or unknown proteins in rice.

Cluster Analysis↗
PubMed2002

[Comparative genomics and proteomics of Drosophila, Brenner's nematode, and Arabidopsis: identification of functionally similar genes and proteins of meiotic chromosome synapsis].

The published principles of computer analysis of genomes and protein sets in taxonomically distant eukaryotes are expounded. The authors developed a search strategy to identify in genomes of such organisms genes and proteins nonhomologous in primary structure but having similar functions in cells dividing by meiosis. This strategy based on the combined principles of genomics, proteomics, and morphometric analysis of subcellular structures was applied to a computer search for genes encoding the proteins of synaptonemal complexes in genomes of Drosophila melanogaster, the nematode Caenorhabditis elegans, and the plant Arabidopsis thaliana. These proteins proved to be functionally similar to their counterparts in yeast Saccharomyces cerevisiae (protein Zip1p) and mammals (protein SCP1).

Animals↗
PubMed2001

Hepatocellular carcinoma: from bedside to proteomics.

Hepatocellular carcinoma (HCC or hepatoma) is the most common primary cancer of the liver. It is responsible for approximately one million deaths each year, mainly in underdeveloped and developing countries. The aetiological factors identified in the development of HCC included persistent infection by hepatitis B and hepatitis C viruses, and exposure to aflatoxins. Although immunization can protect individuals from being infected by the hepatitis B virus, the early detection of HCC in those who have been infected by the virus remains a challenge. Thus most HCCs present late and are not suitable for curative treatment. Hence there is a tremendous interest and urgency to identify novel HCC diagnostic marker(s) for early detection, and tumour specific disease associated proteins as potential therapeutic targets in the treatment of HCC. Screening for these HCC proteins has been facilitated by proteomics, a key technology in the global analysis of protein expression and understanding gene function. Present and earlier proteome analyses of HCC have used predominantly experimental in vitro systems. The protein expression profiles of several hepatoma cell lines such as HepG2, Huh7, SK-Hep1, and Hep3B have been compared with normal liver, and nontransformed cell lines (Chang and WRL-68), while a comprehensive proteome analysis to create a protein database was carried out for the cell line HCC-M. In the future, proteome analyses utilizing tumour tissues, which reflect the pathological state of HCC more closely, will be undertaken. This work will complement the gene expression studies of HCC which are already underway. Efforts have also been directed at the proteome analysis of hepatic stellate cells, as these cells play an important role in liver fibrosis. Since liver fibrosis is reversible but not cirrhosis, it is of considerable importance to identify therapeutic targets that can slow its progression.

Amino Acid Sequence↗
PubMed2006

Study of proteins associated with the Eimeria tenella refractile body by a proteomic approach.

Refractile bodies (RB), whose function is still unknown, are specific structures of Eimeriidae parasites. In order to study their proteome, RB were purified from Eimeria tenella sporozoites by a new procedure using a reversible fixation followed by centrifugation. RB proteins were resolved by two-dimensional electrophoresis. Around 76 and 89 spots were detected on RB two-dimensional gels using gradients in the 3-10 and 4-7 range, respectively. RB proteins were located mainly between pH 5 and 7. RB gels were then compared with previously established maps of the entire sporozoite proteome. Proteins appearing in new spots were identified by mass spectrometry. Thirty protein isoforms were located in RB. Added to the already known RB proteins such as Eimepsin and SO7', the new RB proteins were defined as haloacid dehalogenase, hydrolase, subtilase, lactacte dehydrogenase or ubiquitin family proteins. The RB proteome analysis confirmed the hypothesis that this structure is a reservoir for proteins necessary to invasion but also suggests that RB have energetic and metabolic functions.

Animals↗
PubMed2005

A tandem orthogonal proteolysis strategy for high-content chemical proteomics.

The field of proteomics aims to assign functions to the numerous protein products encoded by eukaryotic and prokaryotic genomes. Toward this end, chemical strategies have emerged as a powerful means to enrich specific classes of proteins based on shared functional properties, such as catalytic activity [activity-based protein profiling (ABPP)], and post-translational modification state. The theoretical information content in chemical proteomic experiments greatly exceeds the actual data procured, due in large part to limitations in existing analytical technologies. Here, we present a tandem orthogonal proteolysis (TOP) strategy for high-content chemical proteomics that enables the parallel characterization of probe-labeled proteins and sites of probe modification. The TOP approach exploits "click chemistry" to introduce a multifunctional tag onto probe-labeled proteins that contains both a biotin group for protein enrichment and a tobacco etch virus (TEV) protease cleavage site for selective release of probe-modified peptides. Following capture on streptavidin beads, protein targets of probes and their sites of labeling are sequentially identified by a two-step proteolysis strategy (trypsin and TEV, respectively). We apply the TOP method to characterize targets of sulfonate ester ABPP probes in tissue proteomes, resulting in the discovery of numerous active site-labeled enzymes. Enzymes modified on regulatory sites and proteins of unknown function were also identified. These findings indicate that a wide range of functional residues are targeted by sulfonate ester probes and highlight the value of TOP-based chemical proteomics for the characterization of proteins and the residues that regulate their activity.

Amino Acid Sequence↗
PubMed2006

Simple sequence proteins in prokaryotic proteomes.

BACKGROUND: The structural and functional features associated with Simple Sequence Proteins (SSPs) are non-globularity, disease states, signaling and post-translational modification. SSPs are also an important source of genetic and possibly phenotypic variation. Analysis of 249 prokaryotic proteomes offers a new opportunity to examine the genomic properties of SSPs. RESULTS: SSPs are a minority but they grow with proteome size. This relationship is exhibited across species varying in genomic GC, mutational bias, life style, and pathogenicity. Their proportion in each proteome is strongly influenced by genomic base compositional bias. In most species simple duplications is favoured, but in a few cases such as Mycobacteria, large families of duplications occur. Amino acid preference in SSPs exhibits a trend towards low cost of biosynthesis. In SSPs and in non-SSPs, Alanine, Glycine, Leucine, and Valine are abundant in species widely varying in genomic GC whereas Isoleucine and Lysine are rich only in organisms with low genomic GC. Arginine is abundant in SSPs of two species and in the non-SSPs of Xanthomonas oryzae. Asparagine is abundant only in SSPs of low GC species. Aspartic acid is abundant only in the non-SSPs of Halobacterium sp NRC1. The abundance of Serine in SSPs of 62 species extends over a broader range compared to that of non-SSPs. Threonine(T) is abundant only in SSPs of a couple of species. SSPs exhibit preferential association with Cell surface, Cell membrane and Transport functions and a negative association with Metabolism. Mesophiles and Thermophiles display similar ranges in the content of SSPs. CONCLUSION: Although SSPs are a minority, the genomic forces of base compositional bias and duplications influence their growth and pattern in each species. The preferences and abundance of amino acids are governed by low biosynthetic cost, evolutionary age and base composition of codons. Abundance of charged amino acids Arginine and Aspartic acid is severely restricted. SSPs preferentially associate with cell surface and interface functions as opposed to metabolism, wherein proteins of high sequence complexity with globular structures are preferred. Mesophiles and Thermophiles are similar with respect to the content of SSPs. Our analysis serves to expand the commonly held views on SSPs.

Amino Acid Sequence↗