Biomedical subjects

Hsueh-Fen Juan

Publications and source records attributed to Hsueh-Fen Juan.

16 recordsLinked to original sources

PubMed2006

RINGdb: an integrated database for G protein-coupled receptors and regulators of G protein signaling.

BACKGROUND: Many marketed therapeutic agents have been developed to modulate the function of G protein-coupled receptors (GPCRs). The regulators of G-protein signaling (RGS proteins) are also being examined as potential drug targets. To facilitate clinical and pharmacological research, we have developed a novel integrated biological database called RINGdb to provide comprehensive and organized RGS protein and GPCR information. RESULTS: RINGdb contains information on mutations, tissue distributions, protein-protein interactions, diseases/disorders and other features, which has been automatically collected from the Internet and manually extracted from the literature. In addition, RINGdb offers various user-friendly query functions to answer different questions about RGS proteins and GPCRs such as their possible contribution to disease processes, the putative direct or indirect relationship between RGS proteins and GPCRs. RINGdb also integrates organized database cross-references to allow users direct access to detailed information. The database is now available at http://ringdb.csie.ncu.edu.tw/ringdb/. CONCLUSION: RINGdb is the only integrated database on the Internet to provide comprehensive RGS protein and GPCR information. This knowledge base will be useful for clinical research, drug discovery and GPCR signaling pathway research.

Amino Acid Sequence↗

PubMed2006

An agent-based system to discover protein-protein interactions, identify protein complexes and proteins with multiple peptide mass fingerprints.

Proteins "work together" by actually binding to form multicomponent complexes that carry out specific functions. Proteomic analyses based on the mass spectrum are now key methods to determine the components in protein complexes. The protein-protein interaction or functional association may be known to exist among the extracted protein spots while analyzing the proteins on the 2D gel. In this study, we develop an agent-based system, namely AgentMultiProtIdent, which integrated two protein identification tools and a variety of databases storing relations among proteins and used to discover protein-protein interactions and protein functional associations, and identify protein complexes and proteins with multiple peptide mass fingerprints as input. The system takes Multiple Peptide Mass Fingerprints (PMFs) as a whole in the protein complex or protein identification. With the relations among proteins, it may greatly improve the accuracy of identification of protein complexes. Also, possible relationship of the multiple peptide mass fingerprints, such as ontology relation, can be discovered by our system, especially in the identification of protein complexes. The agent-based system is now available on the Web at http://dbms104.csie.ncu.edu.tw/ approximately protein/NEW2/.

Animals↗

PubMed2006

Proteomics analysis of a novel compound: cyclic RGD in breast carcinoma cell line MCF-7.

In studies of cell adhesion, migration, growth, differentiation, and apoptosis, synthetic peptides containing the RGD (Arg-Gly-Asp) motif have been extensively used as the inhibitors of integrin-ligand interactions. The RGD motif is an integrin-recognition motif found in many ligands, so that the RGD-containing peptides can be used to probe integrin functions in various biological systems. A linear RGD is a tripeptide consisting of a flexible structure that makes the motif bind to its receptor with inefficient chelating affinity. Therefore, we designed a cyclic-RGD peptide (Tpa-RGDWPC, cRGD) with rigid skeleton to closely bind with its receptor. The cRGD was obtained by solid-phase peptide synthesis method using Rink amide resin. We showed that the cRGD exerts more potency than linear RGD on inhibiting cell growth of MCF-7 breast carcinoma cells. This stimulated us to question how cRGD inhibits cell growth of MCF-7 cells. Moreover, understanding what molecular mechanism underlies the effect that RGD motif exerts on MCF-7 cells is also of considerable importance. We used proteomics and bioinformatics to survey the global changes in proteins after cRGD treatment in MCF-7 cells. The classification of these proteins is shown according to the different biological processes in which they are involved. Most of the proteins that appear to be strongly influenced by cRGD treatment are involved in metabolism, cell growth, responsive to external stimulus, cell communication, reproduction and cell death. This is the first report which monitors the protein expression profile of MCF-7 cells in response to treatment with RGD-containing peptides in a time-course analysis. The clustering data indicated temporal patterns of altered protein expression that can be categorized into early, intermediate and late response proteins. These patterns of protein expression may be important for predicting its response to cRGD. In summary, these results provide a molecular explanation for the properties of cRGD in breast cancer cells and present a valuable in-depth description of their possible impact on breast cancer therapy.

Antineoplastic Agents↗

PubMed2006

Lipopolysaccharide-stimulated responses in rat aortic endothelial cells by a systems biology approach.

The vascular endothelium plays an important role in regulating immune and inflammatory responses to resist pathogens infection. Although it has been known that lipopolysaccharide (LPS) is a critical inducer of sepsis or endotoxemia, the systematic responses of LPS-stimulation in endothelial cells (ECs) are still unclear. The present study aims to analyze the late-phase responses of LPS-induced rat aortic ECs by using systematic biology approaches, including rat cDNA microarray, 2-DE and MALDI-TOF MS/MS, and cytokine protein array. Furthermore, to improve the efficiency of analysis of the bulk systematic data of rat, we designed a set of bioinformatic tools to convert and integrate these rat data into the corresponding human genes or proteins IDs based on BioCarta, KEGG, and Gene Ontology databases. Using the systematic analysis, it was shown that LPS could promote some signaling or metabolic pathways as well as pathophysiologic phenomena of proliferation, atherogenesis, inflammation, and apoptosis through activated nuclear factor-kappaB pathway in ECs. Interestingly, ECs also activated the mediators of anti-inflammation, antiapoptosis, and antioxidation to protect themselves. Moreover, the expressions of altered genes, proteins, and their involvement in the hypothetical signaling pathway can provide further understanding of inflammation associated responses in ECs.

Animals↗

PubMed2006

Quantitative proteomic and genomic profiling reveals metastasis-related protein expression patterns in gastric cancer cells.

Gastric cancer is a leading cause of death worldwide, and patients have an overall 5-year survival rate of less than 10%. Using quantitative proteomic techniques together with microarray chips, we have established comprehensive proteome and transcriptome profiles of the metastatic gastric cancer TMC-1 cells and the noninvasive gastric cancer SC-M1 cell. Our qualitative protein profiling strategy offers the first comprehensive analysis of the gastric cancer cell proteome, identifying 926 and 909 proteins from SC-M1 and TMC-1 cells, respectively. Cleavable isotope-coded affinity tagging analysis allows quantitation of a total of 559 proteins (with a protein false-positive rate of <0.005), and 240 proteins were differentially expressed (>1.3-fold) between the SC-M1 and TMC-1 cells. We identified numerous proteins not previously associated with gastric cancer. Notably, a large subset of differentially expressed proteins was associated with tumor metastasis, including proteins functioning in cell-cell and cell-extracellular matrix (cell-ECM) adhesion, cell motility, proliferation, and tumor immunity. Gene expression profiling by DNA microarray revealed differential expression (of >2-fold) of about 1000 genes. The weak correlation observed between protein and mRNA profiles highlights the important complementarities of DNA microarray and proteomics approaches. These comparative data enabled us to map the disease-perturbed cell-cell and cell-ECM adhesion and Rho GTPase-mediated cytoskeletal pathways. Further validation of a subset of genes suggests the potential use of vimentin and galectin 1 as markers for metastasis. We demonstrate that combining proteomic and genomic approaches not only provides a rapid, robust, and sensitive platform to elucidate the molecular mechanisms underlying gastric cancer metastasis but also may identify candidate diagnostic markers and therapeutic targets.

Biomarkers, Tumor↗

PubMed2006

A proteomics study of the mung bean epicotyl regulated by brassinosteroids under conditions of chilling stress.

Mung bean CYP90A2 is a putative brassinosteroid (BR) synthetic gene that shares 77% identity with the Arabidopsis CPD gene. It was strongly suppressed by chilling stress. This implies that exogenous treatment with BR could allow the plant to recover from the inhibited growth caused by chilling. In this study, we used proteomics to investigate whether the mung bean epicotyl can be regulated by brassinosteroids under conditions of chilling stress. Mung bean epicotyls whose growth was initially suppressed by chilling partly recovered their ability to elongate after treatment with 24-epibrassinolde; 17 proteins down-regulated by this chilling were re-up-regulated. These up-regulated proteins are involved in methionine assimilation, ATP synthesis, cell wall construction and the stress response. This is consistent with the re-up-regulation of methionine synthase and S-adenosyl-L-methionine synthetase, since chilling-inhibited mung bean epicotyl elongation could be partially recovered by exogenous treatment with DL-methionine. This is the first proteome established for the mung bean species. The regulatory relationship between brassinosteroids and chilling conditions was investigated, and possible mechanisms are discussed herein.

Adaptation, Physiological↗

PubMed2005

A new application of microwave technology to proteomics.

Two-dimensional electrophoresis (2-DE) combined with mass spectrometry has significantly improved the possibilities of large-scale identification of proteins. However, 2-DE is limited by its inability to speed up the in-gel digestion process. We have developed a new approach to speed up the protein identification process utilizing microwave technology. Proteins excised from gels are subjected to in-gel digestion with endoprotease trypsin by microwave irradiation, which rapidly produces peptide fragments. The peptide fragments were further analyzed by matrix-assisted laser desorption/ionization technique for protein identification. The efficacy of this technique for protein mapping was demonstrated by the mass spectral analyses of the peptide fragmentation of several proteins, including lysozyme, albumin, conalbumin, and ribonuclease A. The method reduced the required time for in-gel digestion of proteins from 16 hours to as little as five minutes. This new application of microwave technology to protein identification will be an important advancement in biotechnology and proteome research.

Albumins↗

PubMed2004

GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data.

UNLABELLED: Inferring genetic network architecture from time series data generated from high-throughput experimental technologies, such as cDNA microarray, can help us to understand the system behavior of living organisms. We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes. GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models. A simple graphical user interface enables rapid, intuitive mapping and analysis of the reconstructed network allowing biologists to explore gene relationships at the system level. AVAILABILITY: Download from http://genenetwork.sbl.bc.sinica.edu.tw/. SUPPLEMENTARY INFORMATION: Supplement documentation of algorithms for the four approaches is downloadable at the above location.

Algorithms↗

PubMed2004

ProteMiner-SSM: a web server for efficient analysis of similar protein tertiary substructures.

Analysis of protein-ligand interactions is a fundamental issue in drug design. As the detailed and accurate analysis of protein-ligand interactions involves calculation of binding free energy based on thermodynamics and even quantum mechanics, which is highly expensive in terms of computing time, conformational and structural analysis of proteins and ligands has been widely employed as a screening process in computer-aided drug design. In this paper, a web server called ProteMiner-SSM designed for efficient analysis of similar protein tertiary substructures is presented. In one experiment reported in this paper, the web server has been exploited to obtain some clues about a biochemical hypothesis. The main distinction in the software design of the web server is the filtering process incorporated to expedite the analysis. The filtering process extracts the residues located in the caves of the protein tertiary structure for analysis and operates with O(nlogn) time complexity, where n is the number of residues in the protein. In comparison, the alpha-hull algorithm, which is a widely used algorithm in computer graphics for identifying those instances that are on the contour of a three-dimensional object, features O(n2) time complexity. Experimental results show that the filtering process presented in this paper is able to speed up the analysis by a factor ranging from 3.15 to 9.37 times. The ProteMiner-SSM web server can be found at http://proteminer.csie.ntu.edu.tw/. There is a mirror site at http://p4.sbl.bc.sinica.edu.tw/proteminer/.

Binding Sites↗

PubMed2004

Small molecules targeting severe acute respiratory syndrome human coronavirus.

Severe acute respiratory syndrome (SARS) is an infectious disease caused by a novel human coronavirus. Currently, no effective antiviral agents exist against this type of virus. A cell-based assay, with SARS virus and Vero E6 cells, was developed to screen existing drugs, natural products, and synthetic compounds to identify effective anti-SARS agents. Of >10,000 agents tested, approximately 50 compounds were found active at 10 microM; among these compounds, two are existing drugs (Reserpine 13 and Aescin 5) and several are in clinical development. These 50 active compounds were tested again, and compounds 2-6, 10, and 13 showed active at 3 microM. The 50% inhibitory concentrations for the inhibition of viral replication (EC(50)) and host growth (CC(50)) were then measured and the selectivity index (SI = CC(50)/EC(50)) was determined. The EC(50), based on ELISA, and SI for Reserpine, Aescim, and Valinomycin are 3.4 microM (SI = 7.3), 6.0 microM (SI = 2.5), and 0.85 microM (SI = 80), respectively. Additional studies were carried out to further understand the mode of action of some active compounds, including ELISA, Western blot analysis, immunofluorescence and flow cytometry assays, and inhibition against the 3CL protease and viral entry. Of particular interest are the two anti-HIV agents, one as an entry blocker and the other as a 3CL protease inhibitor (K(i) = 0.6 microM).

Animals↗

PubMed2004

Incremental generation of summarized clustering hierarchy for protein family analysis.

MOTIVATION: Protein sequence clustering has been widely exploited to facilitate in-depth analysis of protein functions and families. For some applications of protein sequence clustering, it is highly desirable that a hierarchical structure, also referred to as dendrogram, which shows how proteins are clustered at various levels, is generated. However, as the sizes of contemporary protein databases continue to grow at rapid rates, it is of great interest to develop some summarization mechanisms so that the users can browse the dendrogram and/or search for the desired information more effectively. RESULTS: In this paper, the design of a novel incremental clustering algorithm aimed at generating summarized dendrograms for analysis of protein databases is described. The proposed incremental clustering algorithm employs a statistics-based model to summarize the distributions of the similarity scores among the proteins in the database and to control formation of clusters. Experimental results reveal that, due to the summarization mechanism incorporated, the proposed incremental clustering algorithm offers the users highly concise dendrograms for analysis of protein clusters with biological significance. Another distinction of the proposed algorithm is its incremental nature. As the sizes of the contemporary protein databases continue to grow at fast rates, due to the concern of efficiency, it is desirable that cluster analysis of a protein database can be carried out incrementally, when the protein database is updated. Experimental results with the Swiss-Prot protein database reveal that the time complexity for carrying out incremental clustering with k new proteins added into the database containing n proteins is O(n2betalogn), where beta congruent with 0.865, provided that k << n. AVAILABILITY: The Linux executable is available on the following supplementary page.

Algorithms↗

PubMed2004

Identification of tumor-associated plasma biomarkers using proteomic techniques: from mouse to human.

In an effort to identify tumor-associated proteins from plasma of tumor-bearing mice that may be used as diagnostic biomarkers, we developed a strategy that combines a tumor xenotransplantation model in nude mice with comparative proteomic technology. Five human cancer cell lines (SC-M1, HONE-1, CC-M1, OECM1, GBM 8401) derived from stomach, nasopharyngeal, colon, oral and brain cancers were subcutaneously inoculated into nude mice and compared to control nude mice injected with phosphate-buffered saline. One month later, plasma from mice inoculated with cancer cells was collected for proteomic analysis using two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS). Comparison of plasma 2-DE maps from tumor-bearing mice with those produced from control mice revealed the overexpression of several mouse acute phase proteins (APPs) such as haptoglobin. Another APP, serum amyloid A (SAA), was found only in mice bearing tumors induced by the stomach cancer cell line SC-M1, which has not previously been demonstrated in xenotransplatation experiment. Furthermore, by using immunohistochemistry, SAA and haptoglobin were found to originate from the mouse hosts and not from the human cancer cell line donors. The protein alterations were further confirmed on patients with stomach cancers where up-regulated levels of SAA were also observed. These results indicate that APPs may be used as nonspecific tumor-associated serum markers. SAA in particular may serve as a potential marker for detecting stomach cancer. Taken together, the combination of the xenotransplatation model in nude mice and proteomics analysis provided a valuable impact for clinical applications in cancer diagnostics. In addition, our findings demonstrate that a panel of APPs might serve as screening biomarkers for early cancer detection.

Amino Acid Sequence↗

PubMed2003

Immunomodulatory effect of decoy receptor 3 on the differentiation and function of bone marrow-derived dendritic cells in nonobese diabetic mice: from regulatory mechanism to clinical implication.

To investigate the regulatory effects of decoy receptor 3 (DcR3) on the differentiation and function of dendritic cells (DCs), bone marrow-derived DCs (BM-DCs) from nonobese diabetic (NOD) mice were cultured with recombinant DcR3.Fc protein. Their differentiating phenotypes and T cell-stimulating functions were then evaluated. Expression of CD11c, CD40, CD54, and major histocompatibility complex I-A(g7) was reduced in cells cultured with additional DcR3.Fc, compared with DCs incubated with granulocyte macrophage-colony stimulating factor and interleukin (IL)-4, indicating that DcR3 interferes with the differentiation and maturation of BM-DCs. One of the most striking effects of DcR3.Fc on the differentiation of DCs was the up-regulation of CD86 and down-regulation of CD80, suggesting a modulatory potential to skew the T cell response toward the T helper cell type 2 (Th2) phenotype. Consistent with this, the proliferation of CD4(+) T cells cocultured with DcR3.Fc-treated DCs was significantly reduced compared with that of T cells stimulated by normal DCs. Moreover, the secretion of interferon-gamma from T cells cocultured with DcR3.Fc-treated DCs was profoundly suppressed, indicating that DcR3 exerts a Th1-suppressing effect on differentiating DCs. Furthermore, adoptive transfer experiments revealed that NOD/severe combined immunodeficiency mice received DcR3.Fc-treated DCs, and subsequently, autoreactive T cells showed delayed onset of diabetes and a decrease in diabetic severity compared with mice that received normal DCs and T cells, suggesting a future therapeutic potential in autoimmune diabetes. Data from two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization-time-of-flight analysis show an up-regulation of some proteins-such as mitogen-activated protein kinase p38 beta, cyclin-dependent kinase 6, and signal-induced proliferation-associated gene 1-and a down-regulation of the IL-17 precursor; tumor necrosis factor-related apoptosis-inducing ligand family member-associated nuclear factor-kappaB activator-binding kinase 1; and Golgi S-nitroso-N-acetylpenicillamine in cells treated with DcR3, further demonstrating its effect on DC differentiation and function.

Adjuvants, Immunologic↗

PubMed2002

Bioinformatics, functional genomics, and proteomics study of Bacillus sp.

The ability of bioinformatics to characterize genomic and proteomic sequences from bacteria Bacillus sp. for prediction of genes and proteins has been evaluated. Genomics coupling with proteomics, which is relied on integration of the significant advances recently achieved in two-dimensional (2-D) electrophoretic separation of proteins and mass spectrometry (MS), are now important and high throughput techniques for qualifying and analyzing gene and protein expression, discovering new gene or protein products, and understanding of gene and protein functions including post-genomic study. In addition, the bioinformatics of Bacillus sp. is embraced into many databases that will facilitate to rapidly search the information of Bacillus sp. in both genomics and proteomics. It is also possible to highlight sites for post-translational modifications based on the specific protein sequence motifs that play important roles in the structure, activity and compartmentalization of proteins. Moreover, the secreted proteins from Bacillus sp. are interesting and widely used in many applications especially biomedical applications that are the highly advantages for their potential therapeutic values.

Bacillus↗

PubMed2002

Biomic study of human myeloid leukemia cells differentiation to macrophages using DNA array, proteomic, and bioinformatic analytical methods.

A biomic approach by integrating three independent methods, DNA microarray, proteomics and bioinformatics, is used to study the differentiation of human myeloid leukemia cell line HL-60 into macrophages when induced by 12-O-tetradecanoyl-phorbol-13-acetate (TPA). Analysis of gene expression changes at the RNA level using cDNA against an array of 6033 human genes showed that 5950 (98.6%) of the genes were expressed in the HL-60 cells. A total of 624 genes (10.5%) were found to be regulated during HL-60 cell differentiation. Most of these genes have not been previously associated with HL-60 cells and include genes encoded for secreted proteins as well as genes involved in cell adhesion, signaling transduction, and metabolism. Protein analysis using two-dimensional gel electrophoresis showed a total of 682 distinct protein spots; 136 spots (19.9%) exhibited quantitative changes between HL-60 control and macrophages. These differentially expressed proteins were identified by mass spectrometry. We developed a bioinformatics program, the Bulk Gene Search System (BGSS, http://www.sinica.edu.tw:8900/perl/genequery.pl) to search for the functions of genes and proteins identified by cDNA microarrays and proteomics. The identified regulated proteins and genes were classified into seven groups according to subcellular locations and functions. This powerful holistic biomic approach using cDNA microarray, proteomics coupled to bioinformatics can provide in-depth information on the impact and importance of the regulated genes and proteins for HL-60 differentiation.

Cell Differentiation↗

PubMedDate not supplied

MultiProtIdent: identifying proteins using database search and protein-protein interactions.

Protein identification is important in proteomics. Proteomic analyses based on mass spectra (MS) constitute innovative ways to identify the components of protein complexes. Instruments can obtain the mass spectrum to an accuracy of 0.01 Da or better, but identification errors are inevitable. This study shows a novel tool, MultiProtIdent, which can identify proteins using additional information about protein-protein interactions and protein functional associations. Both single and multiple Peptide Mass Fingerprints (PMFs) are input to MultiProtIdent, which matches the PMFs to a theoretical peptide mass database. The relationships or interactions among proteins are considered to reduce false positives in PMF matching. Experiments to identify protein complexes reveal that MultiProtIdent is highly promising. The website associated with this study is http://dbms104.csie.ncu.edu.tw/.

Algorithms↗