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Sample records for cells microarray analysis

  1. Assessment of centrifugation using for accelerated immunological microarray analysis for blood cells investigation

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    A. V. Shishkin

    2011-01-01

    Full Text Available Phase of incubation microarray with cell suspension is prolonged when cells are investigated. It takes from 20 to 60 min if cell sedimentation on the surface of microarray is the result of gravity . Decrease of this stage duration is possible due to centrifugation. In th is article influence of centrifugation on results of analysis is considered. Changes of morphological description of cells are estimated when they a re precipitatedwith different acceleration. Also availability of centrifugation using when it is necessary to obtain the high density of cell binding in test regions of microarray if cells concentration in sample is small is demonstrated.

  2. Addressable droplet microarrays for single cell protein analysis.

    Science.gov (United States)

    Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

    2014-11-07

    Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

  3. A cell spot microarray method for production of high density siRNA transfection microarrays

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    Mpindi John-Patrick

    2011-03-01

    Full Text Available Abstract Background High-throughput RNAi screening is widely applied in biological research, but remains expensive, infrastructure-intensive and conversion of many assays to HTS applications in microplate format is not feasible. Results Here, we describe the optimization of a miniaturized cell spot microarray (CSMA method, which facilitates utilization of the transfection microarray technique for disparate RNAi analyses. To promote rapid adaptation of the method, the concept has been tested with a panel of 92 adherent cell types, including primary human cells. We demonstrate the method in the systematic screening of 492 GPCR coding genes for impact on growth and survival of cultured human prostate cancer cells. Conclusions The CSMA method facilitates reproducible preparation of highly parallel cell microarrays for large-scale gene knockdown analyses. This will be critical towards expanding the cell based functional genetic screens to include more RNAi constructs, allow combinatorial RNAi analyses, multi-parametric phenotypic readouts or comparative analysis of many different cell types.

  4. Microarray Gene Expression Analysis to Evaluate Cell Type Specific Expression of Targets Relevant for Immunotherapy of Hematological Malignancies.

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    M J Pont

    Full Text Available Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage-restricted expression as potential targets for immunotherapy of hematological cancers.

  5. Gene targeting associated with the radiation sensitivity in squamous cell carcinoma by using microarray analysis

    International Nuclear Information System (INIS)

    Nimura, Yoshinori; Kumagai, Ken; Kouzu, Yoshinao; Higo, Morihiro; Kato, Yoshikuni; Seki, Naohiko; Yamada, Shigeru

    2005-01-01

    In order to identify a set of genes related to radiation sensitivity of squamous cell carcinoma (SCC) and establish a predictive method, we compared expression profiles of radio-sensitive/radio-resistant SCC cell lines, using the in-house cDNA microarray consisting of 2,201 human genes derived from full-length enriched SCC cDNA libraries and the Human oligo chip 30 K (Hitachi Software Engineering). Surviving fractions (SF) after irradiation of heavy iron were calculated by colony formation assay. Three pairs (TE2-TE13, YES5-YES6, and HSC3-HSC2), sensitive (SF1 0.6), were selected for the microarray analysis. The results of cDNA microarray analysis showed that 20 genes in resistant cell lines and 5 genes in sensitive cell lines were up regulated more than 1.5-fold compared with sensitive and resistant cell lines respectively. Fourteen out of 25 genes were confirmed the gene expression profiles by real-time polymerase chain reaction (PCR). Twenty-seven genes identified by Human oligo chip 30 K are candidate for the markers to distinguish radio-sensitive from radio-resistant. These results suggest that the isolated 27 genes are the candidates that might be used as specific molecular markers to predict radiation sensitivity. (author)

  6. Accurate detection of carcinoma cells by use of a cell microarray chip.

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    Shohei Yamamura

    Full Text Available BACKGROUND: Accurate detection and analysis of circulating tumor cells plays an important role in the diagnosis and treatment of metastatic cancer treatment. METHODS AND FINDINGS: A cell microarray chip was used to detect spiked carcinoma cells among leukocytes. The chip, with 20,944 microchambers (105 µm width and 50 µm depth, was made from polystyrene; and the formation of monolayers of leukocytes in the microchambers was observed. Cultured human T lymphoblastoid leukemia (CCRF-CEM cells were used to examine the potential of the cell microarray chip for the detection of spiked carcinoma cells. A T lymphoblastoid leukemia suspension was dispersed on the chip surface, followed by 15 min standing to allow the leukocytes to settle down into the microchambers. Approximately 29 leukocytes were found in each microchamber when about 600,000 leukocytes in total were dispersed onto a cell microarray chip. Similarly, when leukocytes isolated from human whole blood were used, approximately 89 leukocytes entered each microchamber when about 1,800,000 leukocytes in total were placed onto the cell microarray chip. After washing the chip surface, PE-labeled anti-cytokeratin monoclonal antibody and APC-labeled anti-CD326 (EpCAM monoclonal antibody solution were dispersed onto the chip surface and allowed to react for 15 min; and then a microarray scanner was employed to detect any fluorescence-positive cells within 20 min. In the experiments using spiked carcinoma cells (NCI-H1650, 0.01 to 0.0001%, accurate detection of carcinoma cells was achieved with PE-labeled anti-cytokeratin monoclonal antibody. Furthermore, verification of carcinoma cells in the microchambers was performed by double staining with the above monoclonal antibodies. CONCLUSION: The potential application of the cell microarray chip for the detection of CTCs was shown, thus demonstrating accurate detection by double staining for cytokeratin and EpCAM at the single carcinoma cell level.

  7. MARS: Microarray analysis, retrieval, and storage system

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    Scheideler Marcel

    2005-04-01

    Full Text Available Abstract Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS, a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.

  8. A Versatile Microarray Platform for Capturing Rare Cells

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    Brinkmann, Falko; Hirtz, Michael; Haller, Anna; Gorges, Tobias M.; Vellekoop, Michael J.; Riethdorf, Sabine; Müller, Volkmar; Pantel, Klaus; Fuchs, Harald

    2015-10-01

    Analyses of rare events occurring at extremely low frequencies in body fluids are still challenging. We established a versatile microarray-based platform able to capture single target cells from large background populations. As use case we chose the challenging application of detecting circulating tumor cells (CTCs) - about one cell in a billion normal blood cells. After incubation with an antibody cocktail, targeted cells are extracted on a microarray in a microfluidic chip. The accessibility of our platform allows for subsequent recovery of targets for further analysis. The microarray facilitates exclusion of false positive capture events by co-localization allowing for detection without fluorescent labelling. Analyzing blood samples from cancer patients with our platform reached and partly outreached gold standard performance, demonstrating feasibility for clinical application. Clinical researchers free choice of antibody cocktail without need for altered chip manufacturing or incubation protocol, allows virtual arbitrary targeting of capture species and therefore wide spread applications in biomedical sciences.

  9. Single-cell multiple gene expression analysis based on single-molecule-detection microarray assay for multi-DNA determination

    Energy Technology Data Exchange (ETDEWEB)

    Li, Lu [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Xianwei [School of Life Sciences, Shandong University, Jinan 250100 (China); Zhang, Xiaoli [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China); Wang, Jinxing [School of Life Sciences, Shandong University, Jinan 250100 (China); Jin, Wenrui, E-mail: jwr@sdu.edu.cn [School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100 (China)

    2015-01-07

    Highlights: • A single-molecule-detection (SMD) microarray for 10 samples is fabricated. • The based-SMD microarray assay (SMA) can determine 8 DNAs for each sample. • The limit of detection of SMA is as low as 1.3 × 10{sup −16} mol L{sup −1}. • The SMA can be applied in single-cell multiple gene expression analysis. - Abstract: We report a novel ultra-sensitive and high-selective single-molecule-detection microarray assay (SMA) for multiple DNA determination. In the SMA, a capture DNA (DNAc) microarray consisting of 10 subarrays with 9 spots for each subarray is fabricated on a silanized glass coverslip as the substrate. On the subarrays, the spot-to-spot spacing is 500 μm and each spot has a diameter of ∼300 μm. The sequence of the DNAcs on the 9 spots of a subarray is different, to determine 8 types of target DNAs (DNAts). Thus, 8 types of DNAts are captured to their complementary DNAcs at 8 spots of a subarray, respectively, and then labeled with quantum dots (QDs) attached to 8 types of detection DNAs (DNAds) with different sequences. The ninth spot is used to detect the blank value. In order to determine the same 8 types of DNAts in 10 samples, the 10 DNAc-modified subarrays on the microarray are identical. Fluorescence single-molecule images of the QD-labeled DNAts on each spot of the subarray are acquired using a home-made single-molecule microarray reader. The amounts of the DNAts are quantified by counting the bright dots from the QDs. For a microarray, 8 types of DNAts in 10 samples can be quantified in parallel. The limit of detection of the SMA for DNA determination is as low as 1.3 × 10{sup −16} mol L{sup −1}. The SMA for multi-DNA determination can also be applied in single-cell multiple gene expression analysis through quantification of complementary DNAs (cDNAs) corresponding to multiple messenger RNAs (mRNAs) in single cells. To do so, total RNA in single cells is extracted and reversely transcribed into their cDNAs. Three

  10. Previously unidentified changes in renal cell carcinoma gene expression identified by parametric analysis of microarray data

    International Nuclear Information System (INIS)

    Lenburg, Marc E; Liou, Louis S; Gerry, Norman P; Frampton, Garrett M; Cohen, Herbert T; Christman, Michael F

    2003-01-01

    Renal cell carcinoma is a common malignancy that often presents as a metastatic-disease for which there are no effective treatments. To gain insights into the mechanism of renal cell carcinogenesis, a number of genome-wide expression profiling studies have been performed. Surprisingly, there is very poor agreement among these studies as to which genes are differentially regulated. To better understand this lack of agreement we profiled renal cell tumor gene expression using genome-wide microarrays (45,000 probe sets) and compare our analysis to previous microarray studies. We hybridized total RNA isolated from renal cell tumors and adjacent normal tissue to Affymetrix U133A and U133B arrays. We removed samples with technical defects and removed probesets that failed to exhibit sequence-specific hybridization in any of the samples. We detected differential gene expression in the resulting dataset with parametric methods and identified keywords that are overrepresented in the differentially expressed genes with the Fisher-exact test. We identify 1,234 genes that are more than three-fold changed in renal tumors by t-test, 800 of which have not been previously reported to be altered in renal cell tumors. Of the only 37 genes that have been identified as being differentially expressed in three or more of five previous microarray studies of renal tumor gene expression, our analysis finds 33 of these genes (89%). A key to the sensitivity and power of our analysis is filtering out defective samples and genes that are not reliably detected. The widespread use of sample-wise voting schemes for detecting differential expression that do not control for false positives likely account for the poor overlap among previous studies. Among the many genes we identified using parametric methods that were not previously reported as being differentially expressed in renal cell tumors are several oncogenes and tumor suppressor genes that likely play important roles in renal cell

  11. Cell-Based Microarrays for In Vitro Toxicology

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    Wegener, Joachim

    2015-07-01

    DNA/RNA and protein microarrays have proven their outstanding bioanalytical performance throughout the past decades, given the unprecedented level of parallelization by which molecular recognition assays can be performed and analyzed. Cell microarrays (CMAs) make use of similar construction principles. They are applied to profile a given cell population with respect to the expression of specific molecular markers and also to measure functional cell responses to drugs and chemicals. This review focuses on the use of cell-based microarrays for assessing the cytotoxicity of drugs, toxins, or chemicals in general. It also summarizes CMA construction principles with respect to the cell types that are used for such microarrays, the readout parameters to assess toxicity, and the various formats that have been established and applied. The review ends with a critical comparison of CMAs and well-established microtiter plate (MTP) approaches.

  12. Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

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    Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

    2012-06-08

    Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

  13. Microarray analysis in the archaeon Halobacterium salinarum strain R1.

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    Jens Twellmeyer

    Full Text Available BACKGROUND: Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. METHODOLOGY/PRINCIPAL FINDINGS: We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. CONCLUSION/SIGNIFICANCE: This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis.

  14. Comparative RNA-Seq and microarray analysis of gene expression changes in B-cell lymphomas of Canis familiaris.

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    Marie Mooney

    Full Text Available Comparative oncology is a developing research discipline that is being used to assist our understanding of human neoplastic diseases. Companion canines are a preferred animal oncology model due to spontaneous tumor development and similarity to human disease at the pathophysiological level. We use a paired RNA sequencing (RNA-Seq/microarray analysis of a set of four normal canine lymph nodes and ten canine lymphoma fine needle aspirates to identify technical biases and variation between the technologies and convergence on biological disease pathways. Surrogate Variable Analysis (SVA provides a formal multivariate analysis of the combined RNA-Seq/microarray data set. Applying SVA to the data allows us to decompose variation into contributions associated with transcript abundance, differences between the technology, and latent variation within each technology. A substantial and highly statistically significant component of the variation reflects transcript abundance, and RNA-Seq appeared more sensitive for detection of transcripts expressed at low levels. Latent random variation among RNA-Seq samples is also distinct in character from that impacting microarray samples. In particular, we observed variation between RNA-Seq samples that reflects transcript GC content. Platform-independent variable decomposition without a priori knowledge of the sources of variation using SVA represents a generalizable method for accomplishing cross-platform data analysis. We identified genes differentially expressed between normal lymph nodes of disease free dogs and a subset of the diseased dogs diagnosed with B-cell lymphoma using each technology. There is statistically significant overlap between the RNA-Seq and microarray sets of differentially expressed genes. Analysis of overlapping genes in the context of biological systems suggests elevated expression and activity of PI3K signaling in B-cell lymphoma biopsies compared with normal biopsies, consistent with

  15. A microarray analysis of two distinct lymphatic endothelial cell populations

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    Bernhard Schweighofer

    2015-06-01

    Full Text Available We have recently identified lymphatic endothelial cells (LECs to form two morphologically different populations, exhibiting significantly different surface protein expression levels of podoplanin, a major surface marker for this cell type. In vitro shockwave treatment (IVSWT of LECs resulted in enrichment of the podoplaninhigh cell population and was accompanied by markedly increased cell proliferation, as well as 2D and 3D migration. Gene expression profiles of these distinct populations were established using Affymetrix microarray analyses. Here we provide additional details about our dataset (NCBI GEO accession number GSE62510 and describe how we analyzed the data to identify differently expressed genes in these two LEC populations.

  16. Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

    Czech Academy of Sciences Publication Activity Database

    Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

    -, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

  17. Microarray Analysis of Gene Expression Alteration in Human Middle Ear Epithelial Cells Induced by Asian Sand Dust.

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    Go, Yoon Young; Park, Moo Kyun; Kwon, Jee Young; Seo, Young Rok; Chae, Sung-Won; Song, Jae-Jun

    2015-12-01

    The primary aim of this study is to evaluate the gene expression profile of Asian sand dust (ASD)-treated human middle ear epithelial cell (HMEEC) using microarray analysis. The HMEEC was treated with ASD (400 µg/mL) and total RNA was extracted for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed. For selected genes, the changes in gene expression were confirmed by real-time polymerase chain reaction. A total of 1,274 genes were differentially expressed by ASD. Among them, 1,138 genes were 2 folds up-regulated, whereas 136 genes were 2 folds down-regulated. Up-regulated genes were mainly involved in cellular processes, including apoptosis, cell differentiation, and cell proliferation. Down-regulated genes affected cellular processes, including apoptosis, cell cycle, cell differentiation, and cell proliferation. The 10 genes including ADM, CCL5, EDN1, EGR1, FOS, GHRL, JUN, SOCS3, TNF, and TNFSF10 were identified as main modulators in up-regulated genes. A total of 11 genes including CSF3, DKK1, FOSL1, FST, TERT, MMP13, PTHLH, SPRY2, TGFBR2, THBS1, and TIMP1 acted as main components of pathway associated with 2-fold down regulated genes. We identified the differentially expressed genes in ASD-treated HMEEC. Our work indicates that air pollutant like ASD, may play an important role in the pathogenesis of otitis media.

  18. Fabrication of Biomolecule Microarrays for Cell Immobilization Using Automated Microcontact Printing.

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    Foncy, Julie; Estève, Aurore; Degache, Amélie; Colin, Camille; Cau, Jean Christophe; Malaquin, Laurent; Vieu, Christophe; Trévisiol, Emmanuelle

    2018-01-01

    Biomolecule microarrays are generally produced by conventional microarrayer, i.e., by contact or inkjet printing. Microcontact printing represents an alternative way of deposition of biomolecules on solid supports but even if various biomolecules have been successfully microcontact printed, the production of biomolecule microarrays in routine by microcontact printing remains a challenging task and needs an effective, fast, robust, and low-cost automation process. Here, we describe the production of biomolecule microarrays composed of extracellular matrix protein for the fabrication of cell microarrays by using an automated microcontact printing device. Large scale cell microarrays can be reproducibly obtained by this method.

  19. Senescent vs. non-senescent cells in the human annulus in vivo: Cell harvest with laser capture microdissection and gene expression studies with microarray analysis

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    Ingram Jane A

    2010-01-01

    Full Text Available Abstract Background Senescent cells are well-recognized in the aging/degenerating human disc. Senescent cells are viable, cannot divide, remain metabolically active and accumulate within the disc over time. Molecular analysis of senescent cells in tissue offers a special challenge since there are no cell surface markers for senescence which would let one use fluorescence-activated cell sorting as a method for separating out senescent cells. Methods We employed a novel laser capture microdissection (LCM design to selectively harvest senescent and non-senescent annulus cells in paraffin-embedded tissue, and compared their gene expression with microarray analysis. LCM was used to separately harvest senescent and non-senescent cells from 11 human annulus specimens. Results Microarray analysis revealed significant differences in expression levels in senescent cells vs non-senescent cells: 292 genes were upregulated, and 321 downregulated. Genes with established relationships to senescence were found to be significantly upregulated in senescent cells vs. non-senescent cells: p38 (MPAK14, RB-Associated KRAB zinc finger, Discoidin, CUB and LCCL domain, growth arrest and DNA-damage inducible beta, p28ING5, sphingosine-1-phosphate receptor 2 and somatostatin receptor 3; cyclin-dependent kinase 8 showed significant downregulation in senescent cells. Nitric oxidase synthase 1, and heat shock 70 kDa protein 6, both of which were significantly down-regulated in senescent cells, also showed significant changes. Additional genes related to cytokines, cell proliferation, and other processes were also identified. Conclusions Our LCM-microarray analyses identified a set of genes associated with senescence which were significantly upregulated in senescent vs non-senescent cells in the human annulus. These genes include p38 MAP kinase, discoidin, inhibitor of growth family member 5, and growth arrest and DNA-damage-inducible beta. Other genes, including genes

  20. Advanced Data Mining of Leukemia Cells Micro-Arrays

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    Richard S. Segall

    2009-12-01

    Full Text Available This paper provides continuation and extensions of previous research by Segall and Pierce (2009a that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM. As Segall and Pierce (2009a and Segall and Pierce (2009b the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is provided on the work of others pertaining to the applications of data mining to micro-array databases of Leukemia cells and micro-array databases in general. As noted in predecessor article by Segall and Pierce (2009a, micro-array databases are one of the most popular functional genomics tools in use today. This research in this paper is intended to use advanced data mining technologies for better interpretations and knowledge discovery as generated by the patterns of gene expressions of HL60, Jurkat, NB4 and U937 Leukemia cells. The advanced data mining performed entailed using other data mining tools such as cubic clustering criterion, variable importance rankings, decision trees, and more detailed examinations of data mining statistics and study of other self-organized maps (SOM clustering regions of workspace as generated by SAS Enterprise Miner version 4. Conclusions and future directions of the research are also presented.

  1. Microarray analysis of the gene expression profile in triethylene ...

    African Journals Online (AJOL)

    Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  2. NMD Microarray Analysis for Rapid Genome-Wide Screen of Mutated Genes in Cancer

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    Maija Wolf

    2005-01-01

    Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.

  3. Development of a cell microarray chip for detection of circulating tumor cells

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    Yamamura, S.; Yatsushiro, S.; Abe, K.; Baba, Y.; Kataoka, M.

    2012-03-01

    Detection of circulating tumor cells (CTCs) in the peripheral blood of metastatic cancer patients has clinical significance in earlier diagnosis of metastases. In this study, a novel cell microarray chip for accurate and rapid detection of tumor cells from human leukocytes was developed. The chip with 20,944 microchambers (105 μm diameter and 50 μm depth) was made from polystyrene, and the surface was rendered to hydrophilic by means of reactive-ion etching, which led to the formation of mono-layers of leukocytes on the microchambers. As the model of CTCs detection, we spiked human bronchioalveolar carcinoma (H1650) cells into human T lymphoblastoid leukemia (CEM) cells suspension and detected H1650 cells using the chip. A CEM suspension contained with H1650 cells was dispersed on the chip surface, followed by 10 min standing to allow the cells to settle down into the microchambers. About 30 CEM cells were accommodated in each microchamber, over 600,000 CEM cells in total being on a chip. We could detect 1 H1650 cell per 106 CEM cells on the microarray by staining with fluorescence-conjugated antibody (Anti-Cytokeratin) and cell membrane marker (DiD). Thus, this cell microarray chip has highly potential to be a novel tool of accurate and rapid detection of CTCs.

  4. Advanced Data Mining of Leukemia Cells Micro-Arrays

    OpenAIRE

    Richard S. Segall; Ryan M. Pierce

    2009-01-01

    This paper provides continuation and extensions of previous research by Segall and Pierce (2009a) that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM). As Segall and Pierce (2009a) and Segall and Pierce (2009b) the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is pro...

  5. The EADGENE Microarray Data Analysis Workshop

    DEFF Research Database (Denmark)

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø

    2007-01-01

    Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from...... 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays...... statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful...

  6. Microarray Analysis on Gene Regulation by Estrogen, Progesterone and Tamoxifen in Human Endometrial Stromal Cells

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    Chun-E Ren

    2015-03-01

    Full Text Available Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies.

  7. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

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    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  8. Microarray BASICA: Background Adjustment, Segmentation, Image Compression and Analysis of Microarray Images

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    Jianping Hua

    2004-01-01

    Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.

  9. Acidic preparations of lysed platelets upregulate proliferative pathways in osteoblast-like cells as demonstrated by genome-wide microarray analysis.

    Science.gov (United States)

    Wahlström, Ola; Linder, Cecilia Halling; Ansell, Anna; Kalén, Anders; Söderström, Mats; Magnusson, Per

    2011-01-01

    Platelets contain numerous growth factors essential for wound and fracture healing. We investigated the gene expression in human osteoblast-like cells stimulated with lysed platelets prepared in acidic, neutral, or alkaline buffers. Lysed platelets prepared in buffers at pH 5.4, 7.4, and 7.9, were added after neutralization to hFOB 1.19 cells. Genome-wide microarray analysis was performed using the Affymetrix GeneChip 7G Scanner. Biometric, cluster, and pathway analyses were performed with GeneSpring GX. Biometric analyses demonstrated that 53 genes were differentially regulated (p ≤ 0.005, ≥2-fold increase). Pathway analysis revealed 10 significant pathways of which eight are common ones regulating bone formation and cancer growth. Eleven genes were selected for quantitative real-time polymerase chain reaction (PCR) based on the microarray analysis of the lysed platelets prepared in the pH 5.4 experiments. In conclusion, acidic preparations of lysed platelet concentrates release factors essential for cell proliferation and particularly cell metabolism under hypoxic conditions. The genetic response from these factors was dominated by genes associated with the same pathways observed in bone formation and cancer growth. Activation of TGF-β in the acidic preparation could be a stimulatory key factor of cell proliferation. These results support the hypothesis that acidification of platelets modifies the stimulatory response of mesenchymal cells in vitro, which is analogous with the observed milieu of a low pH present in wound and fracture sites, as well as in growing tumors.

  10. Principles of gene microarray data analysis.

    Science.gov (United States)

    Mocellin, Simone; Rossi, Carlo Riccardo

    2007-01-01

    The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

  11. Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells.

    Science.gov (United States)

    Torun, D; Torun, Z Ö; Demirkaya, K; Sarper, M; Elçi, M P; Avcu, F

    2017-11-01

    Triethylene glycol dimethacrylate (TEGDMA) is an important resin monomer commonly used in the structure of dental restorative materials. Recent studies have shown that unpolymerized resin monomers may be released into the oral environment and cause harmful biological effects. We investigated changes in the gene expression profiles of TEGDMA-treated human dental pulp cells (hDPCs) following short- (1-day) and long-term (7-days) exposure. HDPCs were exposed to a noncytotoxic concentration of TEGDMA, and gene expression profiles were evaluated by microarray analysis. The results were confirmed by quantitative reverse-transcriptase PCR (qRT PCR). In total, 1282 and 1319 genes (up- or down-regulated) were differentially expressed compared with control group after the 1- and 7-day incubation periods, respectively. Biological ontology-based analyses revealed that metabolic, cellular, and developmental processes constituted the largest groups of biological functional processes. qRT-PCR analysis on bone morphogenetic protein-2 (BMP-2), BMP-4, secreted protein, acidic, cysteine-rich, collagen type I alpha 1, oxidative stress-induced growth inhibitor 1, MMP3, interleukin-6, and heme oxygenase-1 genes confirmed the changes in expression observed in the microarray analysis. Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  12. Polyadenylation state microarray (PASTA) analysis.

    Science.gov (United States)

    Beilharz, Traude H; Preiss, Thomas

    2011-01-01

    Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

  13. Protective Effect of Gwakhyangjeonggisan Herbal Acupuncture Solution in Glioblastoma Cells: Microarray Analysis of Gene Expression

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    Hong-Seok Lee

    2005-12-01

    Full Text Available Objectives : Neurological disorders have been one of main therapeutic targets of acupuncture. The present study investigated the protective effects of Gwakhyangjeonggisan herbal acupuncture solution (GHAS. Methods : We performed 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay in glioblastoma cells, and did microarray analysis with cells exposed to reactive oxigen species (ROS of hydrogen peroxide by 8.0 k Human cDNA, with cut-off level of 2-fold changes in gene expression. Results : MTT assay showed protective effect of GHAS on the glioblastoma cells exposed to hydrogen peroxide. When glioblastoma cells were exposed to hydrogen peroxide, 24 genes were downregulated. When the cells were pretreated with GHAS before exposure to hydrogen peroxide, 46 genes were downregulated. Many of the genes downregulated by hydrogen peroxide stimulation were decreased in the amount of downregulation or reversed to upregulation. Conclusions : The gene expression changes observed in the present study are supposed to be related to the protective molecular mechanism of GHAS in the glioblastoma cells exposed to ROS stress.

  14. Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells

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    Kim Han

    2012-07-01

    Full Text Available Abstract Background In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. Results Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1 was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2. Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. Conclusions Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that

  15. Extended -Regular Sequence for Automated Analysis of Microarray Images

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    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  16. Advanced spot quality analysis in two-colour microarray experiments

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    Vetter Guillaume

    2008-09-01

    Full Text Available Abstract Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5% than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.

  17. Short-term arginine deprivation results in large-scale modulation of hepatic gene expression in both normal and tumor cells: microarray bioinformatic analysis

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    Sabo Edmond

    2006-09-01

    Full Text Available Abstract Background We have reported arginine-sensitive regulation of LAT1 amino acid transporter (SLC 7A5 in normal rodent hepatic cells with loss of arginine sensitivity and high level constitutive expression in tumor cells. We hypothesized that liver cell gene expression is highly sensitive to alterations in the amino acid microenvironment and that tumor cells may differ substantially in gene sets sensitive to amino acid availability. To assess the potential number and classes of hepatic genes sensitive to arginine availability at the RNA level and compare these between normal and tumor cells, we used an Affymetrix microarray approach, a paired in vitro model of normal rat hepatic cells and a tumorigenic derivative with triplicate independent replicates. Cells were exposed to arginine-deficient or control conditions for 18 hours in medium formulated to maintain differentiated function. Results Initial two-way analysis with a p-value of 0.05 identified 1419 genes in normal cells versus 2175 in tumor cells whose expression was altered in arginine-deficient conditions relative to controls, representing 9–14% of the rat genome. More stringent bioinformatic analysis with 9-way comparisons and a minimum of 2-fold variation narrowed this set to 56 arginine-responsive genes in normal liver cells and 162 in tumor cells. Approximately half the arginine-responsive genes in normal cells overlap with those in tumor cells. Of these, the majority was increased in expression and included multiple growth, survival, and stress-related genes. GADD45, TA1/LAT1, and caspases 11 and 12 were among this group. Previously known amino acid regulated genes were among the pool in both cell types. Available cDNA probes allowed independent validation of microarray data for multiple genes. Among genes downregulated under arginine-deficient conditions were multiple genes involved in cholesterol and fatty acid metabolism. Expression of low-density lipoprotein receptor was

  18. Identification of Cell Surface Targets through Meta-analysis of Microarray Data

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    Henry Haeberle

    2012-07-01

    Full Text Available High-resolution image guidance for resection of residual tumor cells would enable more precise and complete excision for more effective treatment of cancers, such as medulloblastoma, the most common pediatric brain cancer. Numerous studies have shown that brain tumor patient outcomes correlate with the precision of resection. To enable guided resection with molecular specificity and cellular resolution, molecular probes that effectively delineate brain tumor boundaries are essential. Therefore, we developed a bioinformatics approach to analyze micro-array datasets for the identification of transcripts that encode candidate cell surface biomarkers that are highly enriched in medulloblastoma. The results identified 380 genes with greater than a two-fold increase in the expression in the medulloblastoma compared with that in the normal cerebellum. To enrich for targets with accessibility for extracellular molecular probes, we further refined this list by filtering it with gene ontology to identify genes with protein localization on, or within, the plasma membrane. To validate this meta-analysis, the top 10 candidates were evaluated with immunohistochemistry. We identified two targets, fibrillin 2 and EphA3, which specifically stain medulloblastoma. These results demonstrate a novel bioinformatics approach that successfully identified cell surface and extracellular candidate markers enriched in medulloblastoma versus adjacent cerebellum. These two proteins are high-value targets for the development of tumor-specific probes in medulloblastoma. This bioinformatics method has broad utility for the identification of accessible molecular targets in a variety of cancers and will enable probe development for guided resection.

  19. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

    In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.

  20. Microarray analysis of DNA damage repair gene expression profiles in cervical cancer cells radioresistant to 252Cf neutron and X-rays

    International Nuclear Information System (INIS)

    Qing, Yi; Wang, Ge; Wang, Dong; Yang, Xue-Qin; Zhong, Zhao-Yang; Lei, Xin; Xie, Jia-Yin; Li, Meng-Xia; Xiang, De-Bing; Li, Zeng-Peng; Yang, Zhen-Zhou

    2010-01-01

    The aim of the study was to obtain stable radioresistant sub-lines from the human cervical cancer cell line HeLa by prolonged exposure to 252 Cf neutron and X-rays. Radioresistance mechanisms were investigated in the resulting cells using microarray analysis of DNA damage repair genes. HeLa cells were treated with fractionated 252 Cf neutron and X-rays, with a cumulative dose of 75 Gy each, over 8 months, yielding the sub-lines HeLaNR and HeLaXR. Radioresistant characteristics were detected by clone formation assay, ultrastructural observations, cell doubling time, cell cycle distribution, and apoptosis assay. Gene expression patterns of the radioresistant sub-lines were studied through microarray analysis and verified by Western blotting and real-time PCR. The radioresistant sub-lines HeLaNR and HeLaXR were more radioresisitant to 252 Cf neutron and X-rays than parental HeLa cells by detecting their radioresistant characteristics, respectively. Compared to HeLa cells, the expression of 24 genes was significantly altered by at least 2-fold in HeLaNR cells. Of these, 19 genes were up-regulated and 5 down-regulated. In HeLaXR cells, 41 genes were significantly altered by at least 2-fold; 38 genes were up-regulated and 3 down-regulated. Chronic exposure of cells to ionizing radiation induces adaptive responses that enhance tolerance of ionizing radiation and allow investigations of cellular radioresistance mechanisms. The insights gained into the molecular mechanisms activated by these 'radioresistance' genes will lead to new therapeutic targets for cervical cancer

  1. AMDA: an R package for the automated microarray data analysis

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    Foti Maria

    2006-07-01

    Full Text Available Abstract Background Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and new experiments are constantly being performed. In spite of this fact, few and limited tools exist for quickly and easily analyzing the results. Microarray analysis can be challenging for researchers without the necessary training and it can be time-consuming for service providers with many users. Results To address these problems we have developed an automated microarray data analysis (AMDA software, which provides scientists with an easy and integrated system for the analysis of Affymetrix microarray experiments. AMDA is free and it is available as an R package. It is based on the Bioconductor project that provides a number of powerful bioinformatics and microarray analysis tools. This automated pipeline integrates different functions available in the R and Bioconductor projects with newly developed functions. AMDA covers all of the steps, performing a full data analysis, including image analysis, quality controls, normalization, selection of differentially expressed genes, clustering, correspondence analysis and functional evaluation. Finally a LaTEX document is dynamically generated depending on the performed analysis steps. The generated report contains comments and analysis results as well as the references to several files for a deeper investigation. Conclusion AMDA is freely available as an R package under the GPL license. The package as well as an example analysis report can be downloaded in the Services/Bioinformatics section of the Genopolis http://www.genopolis.it/

  2. The pathogenesis shared between abdominal aortic aneurysms and intracranial aneurysms: a microarray analysis.

    Science.gov (United States)

    Wang, Wen; Li, Hao; Zhao, Zheng; Wang, Haoyuan; Zhang, Dong; Zhang, Yan; Lan, Qing; Wang, Jiangfei; Cao, Yong; Zhao, Jizong

    2018-04-01

    Abdominal aortic aneurysms (AAAs) and intracranial saccular aneurysms (IAs) are the most common types of aneurysms. This study was to investigate the common pathogenesis shared between these two kinds of aneurysms. We collected 12 IAs samples and 12 control arteries from the Beijing Tiantan Hospital and performed microarray analysis. In addition, we utilized the microarray datasets of IAs and AAAs from the Gene Expression Omnibus (GEO), in combination with our microarray results, to generate messenger RNA expression profiles for both AAAs and IAs in our study. Functional exploration and protein-protein interaction (PPI) analysis were performed. A total of 727 common genes were differentially expressed (404 was upregulated; 323 was downregulated) for both AAAs and IAs. The GO and pathway analyses showed that the common dysregulated genes were mainly enriched in vascular smooth muscle contraction, muscle contraction, immune response, defense response, cell activation, IL-6 signaling and chemokine signaling pathways, etc. The further protein-protein analysis identified 35 hub nodes, including TNF, IL6, MAPK13, and CCL5. These hub node genes were enriched in inflammatory response, positive regulation of IL-6 production, chemokine signaling pathway, and T/B cell receptor signaling pathway. Our study will gain new insight into the molecular mechanisms for the pathogenesis of both types of aneurysms and provide new therapeutic targets for the patients harboring AAAs and IAs.

  3. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

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    Akshata Datar

    2015-10-01

    Full Text Available Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS, thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI. In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures.

  4. Identification of cytokinin-responsive genes using microarray meta-analysis and RNA-Seq in Arabidopsis.

    Science.gov (United States)

    Bhargava, Apurva; Clabaugh, Ivory; To, Jenn P; Maxwell, Bridey B; Chiang, Yi-Hsuan; Schaller, G Eric; Loraine, Ann; Kieber, Joseph J

    2013-05-01

    Cytokinins are N(6)-substituted adenine derivatives that play diverse roles in plant growth and development. We sought to define a robust set of genes regulated by cytokinin as well as to query the response of genes not represented on microarrays. To this end, we performed a meta-analysis of microarray data from a variety of cytokinin-treated samples and used RNA-seq to examine cytokinin-regulated gene expression in Arabidopsis (Arabidopsis thaliana). Microarray meta-analysis using 13 microarray experiments combined with empirically defined filtering criteria identified a set of 226 genes differentially regulated by cytokinin, a subset of which has previously been validated by other methods. RNA-seq validated about 73% of the up-regulated genes identified by this meta-analysis. In silico promoter analysis indicated an overrepresentation of type-B Arabidopsis response regulator binding elements, consistent with the role of type-B Arabidopsis response regulators as primary mediators of cytokinin-responsive gene expression. RNA-seq analysis identified 73 cytokinin-regulated genes that were not represented on the ATH1 microarray. Representative genes were verified using quantitative reverse transcription-polymerase chain reaction and NanoString analysis. Analysis of the genes identified reveals a substantial effect of cytokinin on genes encoding proteins involved in secondary metabolism, particularly those acting in flavonoid and phenylpropanoid biosynthesis, as well as in the regulation of redox state of the cell, particularly a set of glutaredoxin genes. Novel splicing events were found in members of some gene families that are known to play a role in cytokinin signaling or metabolism. The genes identified in this analysis represent a robust set of cytokinin-responsive genes that are useful in the analysis of cytokinin function in plants.

  5. An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

    Science.gov (United States)

    Zhang, Zhe; Fenstermacher, David

    2005-01-01

    Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.

  6. Microarrays for the evaluation of cell-biomaterial surface interactions

    Science.gov (United States)

    Thissen, H.; Johnson, G.; McFarland, G.; Verbiest, B. C. H.; Gengenbach, T.; Voelcker, N. H.

    2007-01-01

    The evaluation of cell-material surface interactions is important for the design of novel biomaterials which are used in a variety of biomedical applications. While traditional in vitro test methods have routinely used samples of relatively large size, microarrays representing different biomaterials offer many advantages, including high throughput and reduced sample handling. Here, we describe the simultaneous cell-based testing of matrices of polymeric biomaterials, arrayed on glass slides with a low cell-attachment background coating. Arrays were constructed using a microarray robot at 6 fold redundancy with solid pins having a diameter of 375 μm. Printed solutions contained at least one monomer, an initiator and a bifunctional crosslinker. After subsequent UV polymerisation, the arrays were washed and characterised by X-ray photoelectron spectroscopy. Cell culture experiments were carried out over 24 hours using HeLa cells. After labelling with CellTracker ® Green for the final hour of incubation and subsequent fixation, the arrays were scanned. In addition, individual spots were also viewed by fluorescence microscopy. The evaluation of cell-surface interactions in high-throughput assays as demonstrated here is a key enabling technology for the effective development of future biomaterials.

  7. Versatile High Resolution Oligosaccharide Microarrays for Plant Glycobiology and Cell Wall Research

    DEFF Research Database (Denmark)

    Pedersen, Henriette Lodberg; Fangel, Jonatan Ulrik; McCleary, Barry

    2012-01-01

    Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less establish...

  8. Microarray Dot Electrodes Utilizing Dielectrophoresis for Cell Characterization

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    Fatimah Ibrahim

    2013-07-01

    Full Text Available During the last three decades; dielectrophoresis (DEP has become a vital tool for cell manipulation and characterization due to its non-invasiveness. It is very useful in the trend towards point-of-care systems. Currently, most efforts are focused on using DEP in biomedical applications, such as the spatial manipulation of cells, the selective separation or enrichment of target cells, high-throughput molecular screening, biosensors and immunoassays. A significant amount of research on DEP has produced a wide range of microelectrode configurations. In this paper; we describe the microarray dot electrode, a promising electrode geometry to characterize and manipulate cells via DEP. The advantages offered by this type of microelectrode are also reviewed. The protocol for fabricating planar microelectrodes using photolithography is documented to demonstrate the fast and cost-effective fabrication process. Additionally; different state-of-the-art Lab-on-a-Chip (LOC devices that have been proposed for DEP applications in the literature are reviewed. We also present our recently designed LOC device, which uses an improved microarray dot electrode configuration to address the challenges facing other devices. This type of LOC system has the capability to boost the implementation of DEP technology in practical settings such as clinical cell sorting, infection diagnosis, and enrichment of particle populations for drug development.

  9. Network Expansion and Pathway Enrichment Analysis towards Biologically Significant Findings from Microarrays

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    Wu Xiaogang

    2012-06-01

    Full Text Available In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease, and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI database, and pathway enrichment from the human pathway database (HPD. We use a recently-published microarray dataset (GSE24215 related to insulin resistance and type 2 diabetes (T2D as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

  10. Integration of microarray analysis into the clinical diagnosis of hematological malignancies: How much can we improve cytogenetic testing?

    Science.gov (United States)

    Peterson, Jess F.; Aggarwal, Nidhi; Smith, Clayton A.; Gollin, Susanne M.; Surti, Urvashi; Rajkovic, Aleksandar; Swerdlow, Steven H.; Yatsenko, Svetlana A.

    2015-01-01

    Purpose To evaluate the clinical utility, diagnostic yield and rationale of integrating microarray analysis in the clinical diagnosis of hematological malignancies in comparison with classical chromosome karyotyping/fluorescence in situ hybridization (FISH). Methods G-banded chromosome analysis, FISH and microarray studies using customized CGH and CGH+SNP designs were performed on 27 samples from patients with hematological malignancies. A comprehensive comparison of the results obtained by three methods was conducted to evaluate benefits and limitations of these techniques for clinical diagnosis. Results Overall, 89.7% of chromosomal abnormalities identified by karyotyping/FISH studies were also detectable by microarray. Among 183 acquired copy number alterations (CNAs) identified by microarray, 94 were additional findings revealed in 14 cases (52%), and at least 30% of CNAs were in genomic regions of diagnostic/prognostic significance. Approximately 30% of novel alterations detected by microarray were >20 Mb in size. Balanced abnormalities were not detected by microarray; however, of the 19 apparently “balanced” rearrangements, 55% (6/11) of recurrent and 13% (1/8) of non-recurrent translocations had alterations at the breakpoints discovered by microarray. Conclusion Microarray technology enables accurate, cost-effective and time-efficient whole-genome analysis at a resolution significantly higher than that of conventional karyotyping and FISH. Array-CGH showed advantage in identification of cryptic imbalances and detection of clonal aberrations in population of non-dividing cancer cells and samples with poor chromosome morphology. The integration of microarray analysis into the cytogenetic diagnosis of hematologic malignancies has the potential to improve patient management by providing clinicians with additional disease specific and potentially clinically actionable genomic alterations. PMID:26299921

  11. Genes involved in immunity and apoptosis are associated with human presbycusis based on microarray analysis.

    Science.gov (United States)

    Dong, Yang; Li, Ming; Liu, Puzhao; Song, Haiyan; Zhao, Yuping; Shi, Jianrong

    2014-06-01

    Genes involved in immunity and apoptosis were associated with human presbycusis. CCR3 and GILZ played an important role in the pathogenesis of presbycusis, probably through regulating chemokine receptor, T-cell apoptosis, or T-cell activation pathways. To identify genes associated with human presbycusis and explore the molecular mechanism of presbycusis. Hearing function was tested by pure-tone audiometry. Microarray analysis was performed to identify presbycusis-correlated genes by Illumina Human-6 BeadChip using the peripheral blood samples of subjects. To identify biological process categories and pathways associated with presbycusis-correlated genes, bioinformatics analysis was carried out by Gene Ontology Tree Machine (GOTM) and database for annotation, visualization, and integrated discovery (DAVID). Quantitative RT-PCR (qRT-PCR) was used to validate the microarray data. Microarray analysis identified 469 up-regulated genes and 323 down-regulated genes. Both the dominant biological processes by Gene Ontology (GO) analysis and the enriched pathways by Kyoto encyclopedia of genes and genomes (KEGG) and BIOCARTA showed that genes involved in immunity and apoptosis were associated with presbycusis. In addition, CCR3, GILZ, CXCL10, and CX3CR1 genes showed consistent difference between groups for both the gene chip and qRT-PCR data. The differences of CCR3 and GILZ between presbycusis patients and controls were statistically significant (p < 0.05).

  12. High-throughput mapping of cell-wall polymers within and between plants using novel microarrays

    DEFF Research Database (Denmark)

    Moller, Isabel Eva; Sørensen, Iben; Bernal Giraldo, Adriana Jimena

    2007-01-01

    We describe here a methodology that enables the occurrence of cell-wall glycans to be systematically mapped throughout plants in a semi-quantitative high-throughput fashion. The technique (comprehensive microarray polymer profiling, or CoMPP) integrates the sequential extraction of glycans from...... analysis of mutant and wild-type plants, as demonstrated here for the Arabidopsis thaliana mutants fra8, mur1 and mur3. CoMPP was also applied to Physcomitrella patens cell walls and was validated by carbohydrate linkage analysis. These data provide new insights into the structure and functions of plant...

  13. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2016-01-01

    Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

  14. DNA microarrays of baculovirus genomes: differential expression of viral genes in two susceptible insect cell lines.

    Science.gov (United States)

    Yamagishi, J; Isobe, R; Takebuchi, T; Bando, H

    2003-03-01

    We describe, for the first time, the generation of a viral DNA chip for simultaneous expression measurements of nearly all known open reading frames (ORFs) in the best-studied members of the family Baculoviridae, Autographa californica multiple nucleopolyhedrovirus (AcMNPV) and Bombyx mori nucleopolyhedrovirus (BmNPV). In this study, a viral DNA chip (Ac-BmNPV chip) was fabricated and used to characterize the viral gene expression profile for AcMNPV in different cell types. The viral chip is composed of microarrays of viral DNA prepared by robotic deposition of PCR-amplified viral DNA fragments on glass for ORFs in the NPV genome. Viral gene expression was monitored by hybridization to the DNA fragment microarrays with fluorescently labeled cDNAs prepared from infected Spodoptera frugiperda, Sf9 cells and Trichoplusia ni, TnHigh-Five cells, the latter a major producer of baculovirus and recombinant proteins. A comparison of expression profiles of known ORFs in AcMNPV elucidated six genes (ORF150, p10, pk2, and three late gene expression factor genes lef-3, p35 and lef- 6) the expression of each of which was regulated differently in the two cell lines. Most of these genes are known to be closely involved in the viral life cycle such as in DNA replication, late gene expression and the release of polyhedra from infected cells. These results imply that the differential expression of these viral genes accounts for the differences in viral replication between these two cell lines. Thus, these fabricated microarrays of NPV DNA which allow a rapid analysis of gene expression at the viral genome level should greatly speed the functional analysis of large genomes of NPV.

  15. DATE analysis: A general theory of biological change applied to microarray data.

    Science.gov (United States)

    Rasnick, David

    2009-01-01

    In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies. 2009 American Institute of Chemical Engineers Biotechnol.

  16. BASE - 2nd generation software for microarray data management and analysis

    Directory of Open Access Journals (Sweden)

    Nordborg Nicklas

    2009-10-01

    Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  17. BASE--2nd generation software for microarray data management and analysis.

    Science.gov (United States)

    Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

    2009-10-12

    Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  18. Analysis of baseline and cisplatin-inducible gene expression in Fanconi anemia cells using oligonucleotide-based microarrays

    Directory of Open Access Journals (Sweden)

    Liu Johnson M

    2002-11-01

    Full Text Available Abstract Background Patients with Fanconi anemia (FA suffer from multiple defects, most notably of the hematological compartment (bone marrow failure, and susceptibility to cancer. Cells from FA patients show increased spontaneous chromosomal damage, which is aggravated by exposure to low concentrations of DNA cross-linking agents such as mitomycin C or cisplatin. Five of the identified FA proteins form a nuclear core complex. However, the molecular function of these proteins remains obscure. Methods Oligonucleotide microarrays were used to compare the expression of approximately 12,000 genes from FA cells with matched controls. Expression profiles were studied in lymphoblastoid cell lines derived from three different FA patients, one from the FA-A and two from the FA-C complementation groups. The isogenic control cell lines were obtained by either transfecting the cells with vectors expressing the complementing cDNAs or by using a spontaneous revertant cell line derived from the same patient. In addition, we analyzed expression profiles from two cell line couples at several time points after a 1-hour pulse treatment with a discriminating dose of cisplatin. Results Analysis of the expression profiles showed differences in expression of a number of genes, many of which have unknown function or are difficult to relate to the FA defect. However, from a selected number of proteins involved in cell cycle regulation, DNA repair and chromatin structure, Western blot analysis showed that p21waf1/Cip1 was significantly upregulated after low dose cisplatin treatment in FA cells specifically (as well as being expressed at elevated levels in untreated FA cells. Conclusions The observed increase in expression of p21waf1/Cip1 after treatment of FA cells with crosslinkers suggests that the sustained elevated levels of p21waf1/Cip1 in untreated FA cells detected by Western blot analysis likely reflect increased spontaneous damage in these cells.

  19. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia adhesion

    Directory of Open Access Journals (Sweden)

    Faisal Mohamed

    2010-05-01

    Full Text Available Abstract Background The zebra mussel (Dreissena polymorpha has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. Results In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A, current velocity (Factor B, dissolved oxygen (Factor C, and byssogenesis status (Factor D. Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR. The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. Conclusions The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  20. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia) adhesion.

    Science.gov (United States)

    Xu, Wei; Faisal, Mohamed

    2010-05-28

    The zebra mussel (Dreissena polymorpha) has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A), current velocity (Factor B), dissolved oxygen (Factor C), and byssogenesis status (Factor D). Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR). The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  1. Characterization of fetal cells from the maternal circulation by microarray gene expression analysis - Could the extravillous trophoblasts be a target for future cell-based non-invasive prenatal diagnosis?

    DEFF Research Database (Denmark)

    Hatt, Lotte; Brinch, Marie; Singh, Ripudaman

    2014-01-01

    stem cell microarray analysis. Results: 39 genes were identified as candidates for unique fetal cell markers. More than half of these are genes known to be expressed in the placenta, especially in extravillous trophoblasts (EVTs). Immunohistochemical staining of placental tissue confirmed CD105......Introduction: Circulating fetal cells in maternal blood provide a tool for risk-free, non-invasive prenatal diagnosis. However, fetal cells in the maternal circulation are scarce, and to effectively isolate enough of them for reliable diagnostics, it is crucial to know which fetal cell type......(s) should be targeted. Materials and Methods: Fetal cells were enriched from maternal blood by magnetic-activated cell sorting using the endothelial cell marker CD105 and identified by XY fluorescence in situ hybridization. Expression pattern was compared between fetal cells and maternal blood cells using...

  2. Bystander effect: Biological endpoints and microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhry, M. Ahmad [Department of Medical Laboratory and Radiation Sciences, College of Nursing and Health Sciences, University of Vermont, 302 Rowell Building, Burlington, VT 05405 (United States) and DNA Microarray Facility, University of Vermont, Burlington, VT 05405 (United States)]. E-mail: mchaudhr@uvm.edu

    2006-05-11

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  3. Bystander effect: Biological endpoints and microarray analysis

    International Nuclear Information System (INIS)

    Chaudhry, M. Ahmad

    2006-01-01

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  4. Fibre optic microarrays.

    Science.gov (United States)

    Walt, David R

    2010-01-01

    This tutorial review describes how fibre optic microarrays can be used to create a variety of sensing and measurement systems. This review covers the basics of optical fibres and arrays, the different microarray architectures, and describes a multitude of applications. Such arrays enable multiplexed sensing for a variety of analytes including nucleic acids, vapours, and biomolecules. Polymer-coated fibre arrays can be used for measuring microscopic chemical phenomena, such as corrosion and localized release of biochemicals from cells. In addition, these microarrays can serve as a substrate for fundamental studies of single molecules and single cells. The review covers topics of interest to chemists, biologists, materials scientists, and engineers.

  5. Automating dChip: toward reproducible sharing of microarray data analysis

    Directory of Open Access Journals (Sweden)

    Li Cheng

    2008-05-01

    Full Text Available Abstract Background During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users. Results We report here implementation and application of the dChip automation module. Through this module, dChip automation files can be created to include menu steps, parameters, and data viewpoints to run automatically. A data-packaging function allows convenient transfer from one user to another of the dChip software, microarray data, and analysis procedures, so that the second user can reproduce the entire analysis session of the first user. An analysis report file can also be generated during an automated run, including analysis logs, user comments, and viewpoint screenshots. Conclusion The dChip automation module is a step toward reproducible research, and it can prompt a more convenient and reproducible mechanism for sharing microarray software, data, and analysis procedures and results. Automation data packages can also be used as publication supplements. Similar automation mechanisms could be valuable to the research community if implemented in other genomics and bioinformatics software packages.

  6. Identification of differentially expressed genes in cutaneous squamous cell carcinoma by microarray expression profiling

    Directory of Open Access Journals (Sweden)

    Sterry Wolfram

    2006-08-01

    Full Text Available Abstract Background Carcinogenesis is a multi-step process indicated by several genes up- or down-regulated during tumor progression. This study examined and identified differentially expressed genes in cutaneous squamous cell carcinoma (SCC. Results Three different biopsies of 5 immunosuppressed organ-transplanted recipients each normal skin (all were pooled, actinic keratosis (AK (two were pooled, and invasive SCC and additionally 5 normal skin tissues from immunocompetent patients were analyzed. Thus, total RNA of 15 specimens were used for hybridization with Affymetrix HG-U133A microarray technology containing 22,283 genes. Data analyses were performed by prediction analysis of microarrays using nearest shrunken centroids with the threshold 3.5 and ANOVA analysis was independently performed in order to identify differentially expressed genes (p vs. AK and SCC were observed for 118 genes. Conclusion The majority of identified differentially expressed genes in cutaneous SCC were previously not described.

  7. Universal Reference RNA as a standard for microarray experiments

    Directory of Open Access Journals (Sweden)

    Fero Michael

    2004-03-01

    Full Text Available Abstract Background Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR, developed with the goal of providing hybridization signal at each microarray probe location (spot. Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. Results Human, mouse and rat URR (UHRR, UMRR and URRR, respectively were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage. Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97. Conclusion Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and

  8. Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

    Directory of Open Access Journals (Sweden)

    Soares Fernando A

    2011-04-01

    Full Text Available Abstract Background Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+ and recurrent head and neck squamous cell carcinoma (HNSCC may increase our understanding of the complex biology of this disease. Methods Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative or tumor recurrence (recurrent or non-recurrent tumor after treatment (surgery with neck dissection followed by radiotherapy. Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results The most frequent alterations were the repression of modules in negative lymph node (N0 and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway

  9. Prediction of Pectin Yield and Quality by FTIR and Carbohydrate Microarray Analysis

    DEFF Research Database (Denmark)

    Baum, Andreas; Dominiak, Malgorzata Maria; Vidal-Melgosa, Silvia

    2017-01-01

    and carbohydrate microarray analysis were performed directly on the crude lime peel extracts during the time course of the extractions. Multivariate analysis of the data was carried out to predict final pectin yields. Fourier transform infrared spectroscopy (FTIR) was found applicable for determining the optimal...... extraction time for the enzymatic and acidic extraction processes, respectively. The combined results of FTIR and carbohydrate microarray analysis suggested major differences in the crude pectin extracts obtained by enzymatic and acid extraction, respectively. Enzymatically extracted pectin, thus, showed......, and that FTIR and carbohydrate microarray analysis have potential to be developed into online process analysis tools for prediction of pectin extraction yields and pectin features from measurements on crude pectin extracts....

  10. Microarray analysis identifies a common set of cellular genes modulated by different HCV replicon clones

    Directory of Open Access Journals (Sweden)

    Gerosolimo Germano

    2008-06-01

    Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful

  11. Microarray technology for major chemical contaminants analysis in food: current status and prospects.

    Science.gov (United States)

    Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen

    2012-01-01

    Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

  12. MAGMA: analysis of two-channel microarrays made easy.

    Science.gov (United States)

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

    The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

  13. CDNA Microarray Based Comparative Gene Expression Analysis of Primary Breast Tumors Versus In Vitro Transformed Neoplastic Breast Epithelium

    National Research Council Canada - National Science Library

    Szallasi, Zoltan

    2001-01-01

    .... The first group of clones is being sorted by their ability to form tumors. We are currently performing cDNA microarray analysis quantifying the expression level of about 15,000 genes in these cell lines...

  14. Droplet Microarray Based on Patterned Superhydrophobic Surfaces Prevents Stem Cell Differentiation and Enables High-Throughput Stem Cell Screening.

    Science.gov (United States)

    Tronser, Tina; Popova, Anna A; Jaggy, Mona; Bastmeyer, Martin; Levkin, Pavel A

    2017-12-01

    Over the past decades, stem cells have attracted growing interest in fundamental biological and biomedical research as well as in regenerative medicine, due to their unique ability to self-renew and differentiate into various cell types. Long-term maintenance of the self-renewal ability and inhibition of spontaneous differentiation, however, still remain challenging and are not fully understood. Uncontrolled spontaneous differentiation of stem cells makes high-throughput screening of stem cells also difficult. This further hinders investigation of the underlying mechanisms of stem cell differentiation and the factors that might affect it. In this work, a dual functionality of nanoporous superhydrophobic-hydrophilic micropatterns is demonstrated in their ability to inhibit differentiation of mouse embryonic stem cells (mESCs) and at the same time enable formation of arrays of microdroplets (droplet microarray) via the effect of discontinuous dewetting. Such combination makes high-throughput screening of undifferentiated mouse embryonic stem cells possible. The droplet microarray is used to investigate the development, differentiation, and maintenance of stemness of mESC, revealing the dependence of stem cell behavior on droplet volume in nano- and microliter scale. The inhibition of spontaneous differentiation of mESCs cultured on the droplet microarray for up to 72 h is observed. In addition, up to fourfold increased cell growth rate of mESCs cultured on our platform has been observed. The difference in the behavior of mESCs is attributed to the porosity and roughness of the polymer surface. This work demonstrates that the droplet microarray possesses the potential for the screening of mESCs under conditions of prolonged inhibition of stem cells' spontaneous differentiation. Such a platform can be useful for applications in the field of stem cell research, pharmacological testing of drug efficacy and toxicity, biomedical research as well as in the field of

  15. Microarray analysis of expression of cell death-associated genes in rat spinal cord cells exposed to cyclic tensile stresses in vitro

    Directory of Open Access Journals (Sweden)

    Roberts Sally

    2010-07-01

    Full Text Available Abstract Background The application of mechanical insults to the spinal cord results in profound cellular and molecular changes, including the induction of neuronal cell death and altered gene expression profiles. Previous studies have described alterations in gene expression following spinal cord injury, but the specificity of this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile stresses on cultured spinal cord cells from E15 Sprague-Dawley rats, using the FX3000® Flexercell Strain Unit. We examined cell morphology and viability over a 72 hour time course. Microarray analysis of gene expression was performed using the Affymetrix GeneChip System®, where categorization of identified genes was performed using the Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG systems. Changes in expression of 12 genes were validated with quantitative real-time reverse transcription polymerase chain reaction (RT-PCR. Results The application of cyclic tensile stress reduced the viability of cultured spinal cord cells significantly in a dose- and time-dependent manner. Increasing either the strain or the strain rate independently was associated with significant decreases in spinal cord cell survival. There was no clear evidence of additive effects of strain level with strain rate. GO analysis identified 44 candidate genes which were significantly related to "apoptosis" and 17 genes related to "response to stimulus". KEGG analysis identified changes in the expression levels of 12 genes of the mitogen-activated protein kinase (MAPK signaling pathway, which were confirmed to be upregulated by RT-PCR analysis. Conclusions We have demonstrated that spinal cord cells undergo cell death in response to cyclic tensile stresses, which were dose- and time-dependent. In addition, we have identified the up regulation of various genes, in particular of the MAPK pathway, which

  16. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  17. DNA microarray global gene expression analysis of influenza virus-infected chicken and duck cells

    Directory of Open Access Journals (Sweden)

    Suresh V. Kuchipudi

    2015-06-01

    Full Text Available The data described in this article pertain to the article by Kuchipudi et al. (2014 titled “Highly Pathogenic Avian Influenza Virus Infection in Chickens But Not Ducks Is Associated with Elevated Host Immune and Pro-inflammatory Responses” [1]. While infection of chickens with highly pathogenic avian influenza (HPAI H5N1 virus subtypes often leads to 100% mortality within 1 to 2 days, infection of ducks in contrast causes mild or no clinical signs. The rapid onset of fatal disease in chickens, but with no evidence of severe clinical symptoms in ducks, suggests underlying differences in their innate immune mechanisms. We used Chicken Genechip microarrays (Affymetrix to analyse the gene expression profiles of primary chicken and duck lung cells infected with a low pathogenic avian influenza (LPAI H2N3 virus and two HPAI H5N1 virus subtypes to understand the molecular basis of host susceptibility and resistance in chickens and ducks. Here, we described the experimental design, quality control and analysis that were performed on the data set. The data are publicly available through the Gene Expression Omnibus (GEOdatabase with accession number GSE33389, and the analysis and interpretation of these data are included in Kuchipudi et al. (2014 [1].

  18. Support vector machine and principal component analysis for microarray data classification

    Science.gov (United States)

    Astuti, Widi; Adiwijaya

    2018-03-01

    Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

  19. Significance analysis of lexical bias in microarray data

    Directory of Open Access Journals (Sweden)

    Falkow Stanley

    2003-04-01

    Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.

  20. Microarray Analysis in a Cell Death Resistant Glioma Cell Line to Identify Signaling Pathways and Novel Genes Controlling Resistance and Malignancy

    Energy Technology Data Exchange (ETDEWEB)

    Seznec, Janina; Naumann, Ulrike, E-mail: ulrike.naumann@uni-tuebingen.de [Laboratory of Molecular Neuro-Oncology, Department of General Neurology, Hertie-Institute for Clinical Brain Research and Center Neurology, University of Tuebingen, Otfried-Mueller-Str. 27, Tuebingen 72076 (Germany)

    2011-06-27

    Glioblastoma multiforme (GBM) is a lethal type of cancer mainly resistant to radio- and chemotherapy. Since the tumor suppressor p53 functions as a transcription factor regulating the expression of genes involved in growth inhibition, DNA repair and apoptosis, we previously assessed whether specific differences in the modulation of gene expression are responsible for the anti-tumor properties of a dominant positive p53, chimeric tumor suppressor (CTS)-1. CTS-1 is based on the sequence of p53 and designed to resist various mechanisms of inactivation which limit the activity of p53. To identify CTS-1-regulated cell death-inducing genes, we generated a CTS-1-resistant glioma cell line (229R). We used Affymetrix whole-genome microarray expression analysis to analyze alterations in gene expression and identified a variety of CTS-1 regulated genes involved in cancer-linked processes. 313 genes were differentially expressed in Adeno-CTS-1 (Ad-CTS-1)-infected and 700 genes in uninfected 229R cells compared to matching parental cells. Ingenuity Pathway Analysis (IPA) determined a variety of differentially expressed genes in Ad-CTS-1-infected cells that were members of the intracellular networks with central tumor-involved players such as nuclear factor kappa B (NF-κB), protein kinase B (PKB/AKT) or transforming growth factor beta (TGF-β). Differentially regulated genes include secreted factors as well as intracellular proteins and transcription factors regulating not only cell death, but also processes such as tumor cell motility and immunity. This work gives an overview of the pathways differentially regulated in the resistant versus parental glioma cells and might be helpful to identify candidate genes which could serve as targets to develop novel glioma specific therapy strategies.

  1. Microarray Analysis in a Cell Death Resistant Glioma Cell Line to Identify Signaling Pathways and Novel Genes Controlling Resistance and Malignancy

    International Nuclear Information System (INIS)

    Seznec, Janina; Naumann, Ulrike

    2011-01-01

    Glioblastoma multiforme (GBM) is a lethal type of cancer mainly resistant to radio- and chemotherapy. Since the tumor suppressor p53 functions as a transcription factor regulating the expression of genes involved in growth inhibition, DNA repair and apoptosis, we previously assessed whether specific differences in the modulation of gene expression are responsible for the anti-tumor properties of a dominant positive p53, chimeric tumor suppressor (CTS)-1. CTS-1 is based on the sequence of p53 and designed to resist various mechanisms of inactivation which limit the activity of p53. To identify CTS-1-regulated cell death-inducing genes, we generated a CTS-1-resistant glioma cell line (229R). We used Affymetrix whole-genome microarray expression analysis to analyze alterations in gene expression and identified a variety of CTS-1 regulated genes involved in cancer-linked processes. 313 genes were differentially expressed in Adeno-CTS-1 (Ad-CTS-1)-infected and 700 genes in uninfected 229R cells compared to matching parental cells. Ingenuity Pathway Analysis (IPA) determined a variety of differentially expressed genes in Ad-CTS-1-infected cells that were members of the intracellular networks with central tumor-involved players such as nuclear factor kappa B (NF-κB), protein kinase B (PKB/AKT) or transforming growth factor beta (TGF-β). Differentially regulated genes include secreted factors as well as intracellular proteins and transcription factors regulating not only cell death, but also processes such as tumor cell motility and immunity. This work gives an overview of the pathways differentially regulated in the resistant versus parental glioma cells and might be helpful to identify candidate genes which could serve as targets to develop novel glioma specific therapy strategies

  2. Robust gene selection methods using weighting schemes for microarray data analysis.

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  3. Radioactive cDNA microarray in neurospsychiatry

    International Nuclear Information System (INIS)

    Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon

    2003-01-01

    Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

  4. Radioactive cDNA microarray in neurospsychiatry

    Energy Technology Data Exchange (ETDEWEB)

    Choe, Jae Gol; Shin, Kyung Ho; Lee, Min Soo; Kim, Meyoung Kon [Korea University Medical School, Seoul (Korea, Republic of)

    2003-02-01

    Microarray technology allows the simultaneous analysis of gene expression patterns of thousands of genes, in a systematic fashion, under a similar set of experimental conditions, thus making the data highly comparable. In some cases arrays are used simply as a primary screen leading to downstream molecular characterization of individual gene candidates. In other cases, the goal of expression profiling is to begin to identify complex regulatory networks underlying developmental processes and disease states. Microarrays were originally used with cell lines or other simple model systems. More recently, microarrays have been used in the analysis of more complex biological tissues including neural systems and the brain. The application of cDNA arrays in neuropsychiatry has lagged behind other fields for a number of reasons. These include a requirement for a large amount of input probe RNA in fluorescent-glass based array systems and the cellular complexity introduced by multicellular brain and neural tissues. An additional factor that impacts the general use of microarrays in neuropsychiatry is the lack of availability of sequenced clone sets from model systems. While human cDNA clones have been widely available, high quality rat, mouse, and drosophilae, among others are just becoming widely available. A final factor in the application of cDNA microarrays in neuropsychiatry is cost of commercial arrays. As academic microarray facilitates become more commonplace custom made arrays will become more widely available at a lower cost allowing more widespread applications. In summary, microarray technology is rapidly having an impact on many areas of biomedical research. Radioisotope-nylon based microarrays offer alternatives that may in some cases be more sensitive, flexible, inexpensive, and universal as compared to other array formats, such as fluorescent-glass arrays. In some situations of limited RNA or exotic species, radioactive membrane microarrays may be the most

  5. Extended analysis of benchmark datasets for Agilent two-color microarrays

    Directory of Open Access Journals (Sweden)

    Kerr Kathleen F

    2007-10-01

    Full Text Available Abstract Background As part of its broad and ambitious mission, the MicroArray Quality Control (MAQC project reported the results of experiments using External RNA Controls (ERCs on five microarray platforms. For most platforms, several different methods of data processing were considered. However, there was no similar consideration of different methods for processing the data from the Agilent two-color platform. While this omission is understandable given the scale of the project, it can create the false impression that there is consensus about the best way to process Agilent two-color data. It is also important to consider whether ERCs are representative of all the probes on a microarray. Results A comparison of different methods of processing Agilent two-color data shows substantial differences among methods for low-intensity genes. The sensitivity and specificity for detecting differentially expressed genes varies substantially for different methods. Analysis also reveals that the ERCs in the MAQC data only span the upper half of the intensity range, and therefore cannot be representative of all genes on the microarray. Conclusion Although ERCs demonstrate good agreement between observed and expected log-ratios on the Agilent two-color platform, such an analysis is incomplete. Simple loess normalization outperformed data processing with Agilent's Feature Extraction software for accurate identification of differentially expressed genes. Results from studies using ERCs should not be over-generalized when ERCs are not representative of all probes on a microarray.

  6. The effects of radiation on p53-mutated glioma cells using cDNA microarray technique

    International Nuclear Information System (INIS)

    Ngo, F.Q.H.; Hsiao, Y.-Y.H.

    2003-01-01

    Full text: In this study, we investigated the effects of 10-Gy irradiation on cell-cycle arrest, apoptosis and clonogenic death in the p53-mutated human U138MG (malignant glioblastoma) cell line. In order to evaluate time-dependent events in cellular responses to radiation, we did a time course study by incubating cells ranging from 0.5 to 48 hours after irradiation. Cell-cycle distribution and apoptosis were evaluated by flow cytometry using propidium iodide (PI) and annexin-V plus PI staining. Cell viability and proliferative capacity were studied by colony formation assay. Dual fluorescence cDNA microarray technique was used to examine the differential expression patterns of the irradiated cells. The cDNA microarray chips used contained DNA sequences corresponding to 12,814 human genes. From the flow cytometry data, it can be observed that radiation induced G2/M phase arrest and that late apoptosis was more evident following G2/M arrest. After 36 hours, some cells underwent senescence and the remains continued on with the cell cycle. Microarray analyses revealed changes in the expression of a small number of cell-cycle-related genes (p21, cyclin B1, etc.) and cell-death genes (tumor necrosis factors, DDB2, etc.) suggesting their involvement in radiation-induced cell-cycle arrest and apoptosis. In silico interpretations of the molecular mechanisms responsible for these radiation effects are in progress

  7. Discovering biological progression underlying microarray samples.

    Directory of Open Access Journals (Sweden)

    Peng Qiu

    2011-04-01

    Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the

  8. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Hengxi Wei

    2015-01-01

    Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.

  9. From microarray to biology: an integrated experimental, statistical and in silico analysis of how the extracellular matrix modulates the phenotype of cancer cells

    OpenAIRE

    Centola Michael B; Dozmorov Igor; Buethe David D; Saban Ricardo; Hauser Paul J; Kyker Kimberly D; Dozmorov Mikhail G; Culkin Daniel J; Hurst Robert E

    2008-01-01

    Abstract A statistically robust and biologically-based approach for analysis of microarray data is described that integrates independent biological knowledge and data with a global F-test for finding genes of interest that minimizes the need for replicates when used for hypothesis generation. First, each microarray is normalized to its noise level around zero. The microarray dataset is then globally adjusted by robust linear regression. Second, genes of interest that capture significant respo...

  10. Bayesian meta-analysis models for microarray data: a comparative study

    Directory of Open Access Journals (Sweden)

    Song Joon J

    2007-03-01

    Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets

  11. Versatile High Throughput Microarray Analysis for Marine Glycobiology

    DEFF Research Database (Denmark)

    Asunción Salmeán, Armando

    to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...... in cell development. Another part of this work focused in the development of a novel methodology for the discovery of unknown algal polysaccharides and characterization of carbohydrate binding proteins. Based on the coevolution between alga and marine saprophytic microorganisms, which use the algal...

  12. Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

    International Nuclear Information System (INIS)

    Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan; Durmus, Naside Gozde

    2011-01-01

    Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

  13. Microengineering methods for cell-based microarrays and high-throughput drug-screening applications

    Energy Technology Data Exchange (ETDEWEB)

    Xu Feng; Wu Jinhui; Wang Shuqi; Gurkan, Umut Atakan; Demirci, Utkan [Department of Medicine, Demirci Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Center for Biomedical Engineering, Brigham and Women' s Hospital, Harvard Medical School, Boston, MA (United States); Durmus, Naside Gozde, E-mail: udemirci@rics.bwh.harvard.edu [School of Engineering and Division of Biology and Medicine, Brown University, Providence, RI (United States)

    2011-09-15

    Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.

  14. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

    Science.gov (United States)

    Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

    2014-01-01

    Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  15. Tissue Microarray Analysis Applied to Bone Diagenesis

    OpenAIRE

    Barrios Mello, Rafael; Regis Silva, Maria Regina; Seixas Alves, Maria Teresa; Evison, Martin; Guimarães, Marco Aurélio; Francisco, Rafaella Arrabaça; Dias Astolphi, Rafael; Miazato Iwamura, Edna Sadayo

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens....

  16. The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2010-03-01

    Full Text Available Abstract Background Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results The IronChip Evaluation Package (ICEP is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see "Additional Files" section and at: http://www.alice-dsl.net/evgeniy.vainshtein/ICEP/

  17. Tissue Microarray Analysis Applied to Bone Diagenesis.

    Science.gov (United States)

    Mello, Rafael Barrios; Silva, Maria Regina Regis; Alves, Maria Teresa Seixas; Evison, Martin Paul; Guimarães, Marco Aurelio; Francisco, Rafaella Arrabaca; Astolphi, Rafael Dias; Iwamura, Edna Sadayo Miazato

    2017-01-04

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered.

  18. Microarray analysis of gene expression alteration in human middle ear epithelial cells induced by micro particle.

    Science.gov (United States)

    Song, Jae-Jun; Kwon, Jee Young; Park, Moo Kyun; Seo, Young Rok

    2013-10-01

    The primary aim of this study is to reveal the effect of particulate matter (PM) on the human middle ear epithelial cell (HMEEC). The HMEEC was treated with PM (300 μg/ml) for 24 h. Total RNA was extracted and used for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed by using Pathway Studio 9.0 software. For selected genes, the changes in gene expression were confirmed by real-time PCR. A total of 611 genes were regulated by PM. Among them, 366 genes were up-regulated, whereas 245 genes were down-regulated. Up-regulated genes were mainly involved in cellular processes, including reactive oxygen species generation, cell proliferation, apoptosis, cell differentiation, inflammatory response and immune response. Down-regulated genes affected several cellular processes, including cell differentiation, cell cycle, proliferation, apoptosis and cell migration. A total of 21 genes were discovered as crucial components in potential signaling networks containing 2-fold up regulated genes. Four genes, VEGFA, IL1B, CSF2 and HMOX1 were revealed as key mediator genes among the up-regulated genes. A total of 25 genes were revealed as key modulators in the signaling pathway associated with 2-fold down regulated genes. Four genes, including IGF1R, TIMP1, IL6 and FN1, were identified as the main modulator genes. We identified the differentially expressed genes in PM-treated HMEEC, whose expression profile may provide a useful clue for the understanding of environmental pathophysiology of otitis media. Our work indicates that air pollution, like PM, plays an important role in the pathogenesis of otitis media. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  19. Expression profiling of cell cycle regulatory proteins in oropharyngeal carcinomas using tissue microarrays.

    Science.gov (United States)

    Ribeiro, Daniel A; Nascimento, Fabio D; Fracalossi, Ana Carolina C; Gomes, Thiago S; Oshima, Celina T F; Franco, Marcello F

    2010-01-01

    The aim of this study was to investigate the expressions of cell cycle regulatory proteins such as p53, p16, p21, and Rb in squamous cell carcinoma of the oropharynx and their relation to histological differentiation, staging of disease, and prognosis. Paraffin blocks from 21 primary tumors were obtained from archives of the Department of Pathology, Paulista Medical School, Federal University of Sao Paulo, UNIFESP/EPM. Immunohistochemistry was used to detect the expression of p53, p16, p21, and Rb by means of tissue microarrays. Expression of p53, p21, p16 and Rb was not correlated with the stage of disease, histopathological grading or recurrence in squamous cell carcinoma of the oropharynx. Taken together, our results suggest that p53, p16, p21 and Rb are not reliable biomarkers for prognosis of the tumor severity or recurrence in squamous cell carcinoma of the oropharynx as depicted by tissue microarrays and immunohistochemistry.

  20. Microarray analysis on human neuroblastoma cells exposed to aluminum, β(1-42-amyloid or the β(1-42-amyloid aluminum complex.

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    Valentina Gatta

    Full Text Available BACKGROUND: A typical pathological feature of Alzheimer's disease (AD is the appearance in the brain of senile plaques made up of β-amyloid (Aβ and neurofibrillary tangles. AD is also associated with an abnormal accumulation of some metal ions, and we have recently shown that one of these, aluminum (Al, plays a relevant role in affecting Aβ aggregation and neurotoxicity. METHODOLOGY: In this study, employing a microarray analysis of 35,129 genes, we investigated the effects induced by the exposure to the Aβ(1-42-Al (Aβ-Al complex on the gene expression profile of the neuronal-like cell line, SH-SY5Y. PRINCIPAL FINDINGS: The microarray assay indicated that, compared to Aβ or Al alone, exposure to Aβ-Al complex produced selective changes in gene expression. Some of the genes selectively over or underexpressed are directly related to AD. A further evaluation performed with Ingenuity Pathway analysis revealed that these genes are nodes of networks and pathways that are involved in the modulation of Ca(2+ homeostasis as well as in the regulation of glutamatergic transmission and synaptic plasticity. CONCLUSIONS AND SIGNIFICANCE: Aβ-Al appears to be largely involved in the molecular machinery that regulates neuronal as well as synaptic dysfunction and loss. Aβ-Al seems critical in modulating key AD-related pathways such as glutamatergic transmission, Ca(2+ homeostasis, oxidative stress, inflammation, and neuronal apoptosis.

  1. Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

    Science.gov (United States)

    Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

    2009-02-01

    Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

  2. Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

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    Jouventin Pierre

    2010-05-01

    Full Text Available Abstract Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.

  3. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.

    2003-01-01

    GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization...

  4. Bioinformatics and Microarray Data Analysis on the Cloud.

    Science.gov (United States)

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

  5. Evaluation of toxicity of the mycotoxin citrinin using yeast ORF DNA microarray and Oligo DNA microarray

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    Nobumasa Hitoshi

    2007-04-01

    Full Text Available Abstract Background Mycotoxins are fungal secondary metabolites commonly present in feed and food, and are widely regarded as hazardous contaminants. Citrinin, one of the very well known mycotoxins that was first isolated from Penicillium citrinum, is produced by more than 10 kinds of fungi, and is possibly spread all over the world. However, the information on the action mechanism of the toxin is limited. Thus, we investigated the citrinin-induced genomic response for evaluating its toxicity. Results Citrinin inhibited growth of yeast cells at a concentration higher than 100 ppm. We monitored the citrinin-induced mRNA expression profiles in yeast using the ORF DNA microarray and Oligo DNA microarray, and the expression profiles were compared with those of the other stress-inducing agents. Results obtained from both microarray experiments clustered together, but were different from those of the mycotoxin patulin. The oxidative stress response genes – AADs, FLR1, OYE3, GRE2, and MET17 – were significantly induced. In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated. In the category of "metabolism", genes involved in the glutathione synthesis pathway were activated, and in the category of "cell rescue, defense and virulence", the ABC transporter genes were induced. To alleviate the induced stress, these cells might pump out the citrinin after modification with glutathione. While, the citrinin treatment did not induce the genes involved in the DNA repair. Conclusion Results from both microarray studies suggest that citrinin treatment induced oxidative stress in yeast cells. The genotoxicity was less severe than the patulin, suggesting that citrinin is less toxic than patulin. The reproducibility of the expression profiles was much better with the Oligo DNA microarray. However, the Oligo DNA microarray did not completely overcome cross

  6. DNA microarray data and contextual analysis of correlation graphs

    Directory of Open Access Journals (Sweden)

    Hingamp Pascal

    2003-04-01

    Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

  7. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

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    Kazuhide Watanabe

    Full Text Available Deregulation of canonical Wnt/CTNNB1 (beta-catenin pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells.We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis.Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  8. Grating coupled SPR microarray analysis of proteins and cells in blood from mice with breast cancer.

    Science.gov (United States)

    Mendoza, A; Torrisi, D M; Sell, S; Cady, N C; Lawrence, D A

    2016-01-21

    Biomarker discovery for early disease diagnosis is highly important. Of late, much effort has been made to analyze complex biological fluids in an effort to develop new markers specific for different cancer types. Recent advancements in label-free technologies such as surface plasmon resonance (SPR)-based biosensors have shown promise as a diagnostic tool since there is no need for labeling or separation of cells. Furthermore, SPR can provide rapid, real-time detection of antigens from biological samples since SPR is highly sensitive to changes in surface-associated molecular and cellular interactions. Herein, we report a lab-on-a-chip microarray biosensor that utilizes grating-coupled surface plasmon resonance (GCSPR) and grating-coupled surface plasmon coupled fluorescence (GCSPCF) imaging to detect circulating tumor cells (CTCs) from a mouse model (FVB-MMTV-PyVT). GCSPR and GCSPCF analysis was accomplished by spotting antibodies to surface cell markers, cytokines and stress proteins on a nanofabricated GCSPR microchip and screening blood samples from FVB control mice or FVB-MMTV-PyVT mice with developing mammary carcinomas. A transgenic MMTV-PyVT mouse derived cancer cell line was also analyzed. The analyses indicated that CD24, CD44, CD326, CD133 and CD49b were expressed in both cell lines and in blood from MMTV-PyVT mice. Furthermore, cytokines such as IL-6, IL-10 and TNF-α, along with heat shock proteins HSP60, HSP27, HSc70(HSP73), HSP90 total, HSP70/HSc70, HSP90, HSP70, HSP90 alpha, phosphotyrosine and HSF-1 were overexpressed in MMTV-PyVT mice.

  9. Microarray studies on lager brewer's yeasts reveal cell status in the process of autolysis.

    Science.gov (United States)

    Xu, Weina; Wang, Jinjing; Li, Qi

    2014-08-01

    In this work, we performed DNA microarray studies on lager brewer's yeast Saccharomyces pastorianus to investigate changes in gene expression in the process of autolysis. The two strains we used were Qing2 and 5-2. Strain 5-2 is a mutant of Qing2 and autolyzes much more slowly than its parent strain. Four samples of these two strains during different autolysis stages (0% and 15%) were tested using DNA microarray containing > 10,000 yeast's genes. Analysis of genes with the same transcription pattern (up- or down-regulated in both strains) showed that the same 99 genes were up-regulated (transcription levels were increased), and the same 97 genes were down-regulated (transcription levels were decreased) by fivefold or more during autolysis. Genes involved in energy production/utilization, protein anabolism, and stress response were down-regulated. Genes related to cell wall organization and biogenesis, starvation response and DNA damage response were up-regulated. Analysis of genes with opposite transcription patterns (up-regulated in one strain and down-regulated in the other one) showed that 246 genes were up-regulated in 5-2 (autolyzes slowly) and down-regulated in Qing2 (autolyzes rapidly). Another 18 genes had opposite transcription levels, indicating that the strain which autolyzes slowly had better cell vitality despite the same autolysis stage. These findings might further promote the global understanding of autolysis in yeast. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  10. DNA microarray analyses reveal a post-irradiation differential time-dependent gene expression profile in yeast cells exposed to X-rays and gamma-rays.

    Science.gov (United States)

    Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep; Iwahashi, Hitoshi

    2006-07-21

    Ionizing radiation (IR) is the most enigmatic of genotoxic stress inducers in our environment that has been around from the eons of time. IR is generally considered harmful, and has been the subject of numerous studies, mostly looking at the DNA damaging effects in cells and the repair mechanisms therein. Moreover, few studies have focused on large-scale identification of cellular responses to IR, and to this end, we describe here an initial study on the transcriptional responses of the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C), by cDNA microarray. The effect of two different IR, X-rays, and gamma (gamma)-rays, was investigated by irradiating the yeast cells cultured in YPD medium with 50 Gy doses of X- and gamma-rays, followed by resuspension of the cells in YPD for time-course experiments. The samples were collected for microarray analysis at 20, 40, and 80 min after irradiation. Microarray analysis revealed a time-course transcriptional profile of changed gene expressions. Up-regulated genes belonged to the functional categories mainly related to cell cycle and DNA processing, cell rescue defense and virulence, protein and cell fate, and metabolism (X- and gamma-rays). Similarly, for X- and gamma-rays, the down-regulated genes belonged to mostly transcription and protein synthesis, cell cycle and DNA processing, control of cellular organization, cell fate, and C-compound and carbohydrate metabolism categories, respectively. This study provides for the first time a snapshot of the genome-wide mRNA expression profiles in X- and gamma-ray post-irradiated yeast cells and comparatively interprets/discusses the changed gene functional categories as effects of these two radiations vis-à-vis their energy levels.

  11. Identification of late O{sub 3}-responsive genes in Arabidopsis thaliana by cDNA microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    D' Haese, D. [Univ. of Antwerp, Dept. of Biology, Antwerp (BE) and Univ. of Newcastle, School of Biology and Psychology, Div. of Biology, Newcastle-Upon-Tyne (United Kingdom); Horemans, N.; Coen, W. De; Guisez, Y. [Univ. of Antwerp, Dept. of Biology, Antwerp (Belgium)

    2006-09-15

    To better understand the response of a plant to 0{sub 3} stress, an integrated microarray analysis was performed on Arabidopsis plants exposed during 2 days to purified air or 150 nl l{sup -1} O{sub 3}, 8 h day-l. Agilent Arabidopsis 2 Oligo Microarrays were used of which the reliability was confirmed by quantitative real-time PCR of nine randomly selected genes. We confirmed the O{sub 3} responsiveness of heat shock proteins (HSPs), glutathione-S-tranferases and genes involved in cell wall stiffening and microbial defence. Whereas, a previous study revealed that during an early stage of the O{sub 3} stress response, gene expression was strongly dependent on jasmonic acid and ethylene, we report that at a later stage (48 h) synthesis of jasrnonic acid and ethylene was downregulated. In addition, we observed the simultaneous induction of salicylic acid synthesis and genes involved in programmed cell death and senescence. Also typically, the later stage of the response to O{sub 3} appeared to be the induction of the complete pathway leading to the biosynthesis of anthocyanin diglucosides and the induction of thioredoxin-based redox control. Surprisingly absent in the list of induced genes were genes involved in ASC-dependent antioxidation, few of which were found to be induced after 12 h of 0{sub 3} exposure in another study. We discuss these and other particular results of the microarray analysis and provide a map depicting significantly affected genes and their pathways highlighting their interrelationships and subcellular localization. (au)

  12. GEPAS, a web-based tool for microarray data analysis and interpretation

    Science.gov (United States)

    Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín

    2008-01-01

    Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806

  13. Immunohistochemistry - Microarray Analysis of Patients with Peritoneal Metastases of Appendiceal or Colorectal Origin

    Directory of Open Access Journals (Sweden)

    Danielle E Green

    2015-01-01

    Full Text Available BackgroundThe value of immunohistochemistry (IHC-microarray analysis of pathological specimens in the management of patients is controversial although preliminary data suggests potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM and the feasibility of this technique in this population.MethodsWe retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular IntelligenceTM testing. IHC, microarray, FISH and mutational analysis were included and stratified by PCI score, histology and treatment characteristics. Statistical analysis was performed using non-parametric tests.ResultsOur study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65 years, with 11(68% female. The median PCI score of the patients was 17(IQR 10-25. Hyperthermic intra-peritoneal chemoperfusion (HIPEC was performed in 4 (80% patients with appendiceal primary tumors and 4 (36% with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p=0.06. IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n=7 patients, which was not associated with previous use of chemotherapy (p>0.20 for 5-FU/LV, Irinotecan and Oxaliplatin.ConclusionsIn a small sample of patients with peritoneal metastases, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.

  14. Evaluation of chronic lymphocytic leukemia by BAC-based microarray analysis

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    McDaniel Lisa D

    2011-02-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.

  15. Expression microarray identifies the unliganded glucocorticoid receptor as a regulator of gene expression in mammary epithelial cells

    International Nuclear Information System (INIS)

    Ritter, Heather D; Mueller, Christopher R

    2014-01-01

    While glucocorticoids and the liganded glucocorticoid receptor (GR) have a well-established role in the maintenance of differentiation and suppression of apoptosis in breast tissue, the involvement of unliganded GR in cellular processes is less clear. Our previous studies implicated unliganded GR as a positive regulator of the BRCA1 tumour suppressor gene in the absence of glucocorticoid hormone, which suggested it could play a similar role in the regulation of other genes. An shRNA vector directed against GR was used to create mouse mammary cell lines with depleted endogenous levels of this receptor in order to further characterize the role of GR in breast cells. An expression microarray screen for targets of unliganded GR was performed using our GR-depleted cell lines maintained in the absence of glucocorticoids. Candidate genes positively regulated by unliganded GR were identified, classified by Gene Ontology and Ingenuity Pathway Analysis, and validated using quantitative real-time reverse transcriptase PCR. Chromatin immunoprecipitation and dual luciferase expression assays were conducted to further investigate the mechanism through which unliganded GR regulates these genes. Expression microarray analysis revealed 260 targets negatively regulated and 343 targets positively regulated by unliganded GR. A number of the positively regulated targets were involved in pro-apoptotic networks, possibly opposing the activity of liganded GR targets. Validation and further analysis of five candidates from the microarray indicated that two of these, Hsd11b1 and Ch25h, were regulated by unliganded GR in a manner similar to Brca1 during glucocorticoid treatment. Furthermore, GR was shown to interact directly with and upregulate the Ch25h promoter in the absence, but not the presence, of hydrocortisone (HC), confirming our previously described model of gene regulation by unliganded GR. This work presents the first identification of targets of unliganded GR. We propose that

  16. Comparing independent microarray studies: the case of human embryonic stem cells

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    Hemmati-Brivanlou Ali

    2005-07-01

    Full Text Available Abstract Background Microarray studies of the same phenomenon in different labs often appear at variance because the published lists of regulated transcripts have disproportionately small intersections. We demonstrate that comparing studies by intersecting lists in this manner is methodologically flawed by reanalyzing three studies of the molecular signature of "stemness" in human embryonic stem cells. There are only 7 genes common to all three published lists, suggesting disagreement. Results Carefully reanalyzing all three together from the raw data we detect 111 genes upregulated and 95 downregulated in all three studies. The upregulated list was subject to rtRTPCR analysis and 75% of the genes were confirmed. Conclusion Our findings show that the three studies have a substantial core of common genes, which is missed if only the published lists are examined. Combined analysis of multiple experiments can be a powerful way to distil coherent conclusions.

  17. miRNAs modified by dietary lipids in Caco-2 cells. A microarray screening

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    Lidia Daimiel

    2015-09-01

    Full Text Available We performed a screening of miRNAs regulated by dietary lipids in a cellular model of enterocytes, Caco-2 cells. Our aim was to describe new lipid-modified miRNAs with an implication in lipid homeostasis and cardiovascular disease [1,2]. For that purpose, we treated differentiated Caco-2 cells with micelles containing the assayed lipids (cholesterol, conjugated linoleic acid and docosahexaenoic acid and the screening of miRNAs was carried out by microarray using the μParaflo®Microfluidic Biochip Technology of LC Sciences (Huston, TX, USA. Experimental design, microarray description and raw data have been made available in the GEO database with the reference number of GSE59153. Here we described in detail the experimental design and methods used to obtain the relative expression data.

  18. Microarray profiling of mononuclear peripheral blood cells identifies novel candidate genes related to chemoradiation response in rectal cancer.

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    Pablo Palma

    Full Text Available Preoperative chemoradiation significantly improves oncological outcome in locally advanced rectal cancer. However there is no effective method of predicting tumor response to chemoradiation in these patients. Peripheral blood mononuclear cells have emerged recently as pathology markers of cancer and other diseases, making possible their use as therapy predictors. Furthermore, the importance of the immune response in radiosensivity of solid organs led us to hypothesized that microarray gene expression profiling of peripheral blood mononuclear cells could identify patients with response to chemoradiation in rectal cancer. Thirty five 35 patients with locally advanced rectal cancer were recruited initially to perform the study. Peripheral blood samples were obtained before neaodjuvant treatment. RNA was extracted and purified to obtain cDNA and cRNA for hybridization of microarrays included in Human WG CodeLink bioarrays. Quantitative real time PCR was used to validate microarray experiment data. Results were correlated with pathological response, according to Mandard´s criteria and final UICC Stage (patients with tumor regression grade 1-2 and downstaging being defined as responders and patients with grade 3-5 and no downstaging as non-responders. Twenty seven out of 35 patients were finally included in the study. We performed a multiple t-test using Significance Analysis of Microarrays, to find those genes differing significantly in expression, between responders (n = 11 and non-responders (n = 16 to CRT. The differently expressed genes were: BC 035656.1, CIR, PRDM2, CAPG, FALZ, HLA-DPB2, NUPL2, and ZFP36. The measurement of FALZ (p = 0.029 gene expression level determined by qRT-PCR, showed statistically significant differences between the two groups. Gene expression profiling reveals novel genes in peripheral blood samples of mononuclear cells that could predict responders and non-responders to chemoradiation in patients with

  19. Prognostic value of matrix metalloproteinase 9 expression in patients with juvenile nasopharyngeal angiofibroma: tissue microarray analysis.

    Science.gov (United States)

    Sun, Xicai; Guo, Limin; Wang, Jingjing; Wang, Huan; Liu, Zhuofu; Liu, Juan; Yu, Huapeng; Hu, Li; Li, Han; Wang, Dehui

    2014-08-01

    Although JNA is a benign neoplasm histopathologically, it has a propensity for locally destructive growth and remains a higher postoperative recurrence rate. The aim of this study was to analyze the expression and localization of MMP-9 in JNA using tissue microarray to elucidate its correlation with clinicopathological features and recurrence. The expression of MMP-9 was assessed by immunohistochemistry in a tissue microarray from 70 patients with JNA and 10 control subjects. Correlation between the levels of MMP-9 expression and clinicopathologic variables, as well as tumor recurrence, were analyzed. MMP-9 was detected in perivascular and extravascular less differentiated cells and stromal cells of patients with JNA but not in the matured vascular endothelial cells of these patients. The presence of MMP-9 expression in JNA was correlated with patient's age (p=0.001). Spearman correlation analysis suggested that high expression of MMP-9 in JNA had negative correlation with patient's age (r=-0.412, p<0.001). The recurrence rate in JNA patients with high MMP-9 expression was significantly higher than those with low MMP-9 expression (p=0.002). In multivariate and ROC curve analysis, MMP-9 was a good prognostic factor for tumor recurrence of JNA. Higher MMP-9 expression is a poor prognostic factor for patients with JNA who have been surgically treated. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  20. Microarray data re-annotation reveals specific lncRNAs and their potential functions in non-small cell lung cancer subtypes

    OpenAIRE

    Zhou, Dongbo; Xie, Mingxuan; He, Baimei; Gao, Ying; Yu, Qiao; He, Bixiu; Chen, Qiong

    2017-01-01

    Non-small-cell lung cancer (NSCLC) is a leading cause of cancer mortality worldwide. The most common subtypes of NSCLC are adenocarcinoma (AC) and squamous cell carcinoma (SCC). However, the pathophysiological mechanisms contributing to AC and SCC are still largely unknown, especially the roles of long non-coding RNAs (lncRNAs). The present study identified differentially expressed lncRNAs between lung AC and SCC by re-annotation of NSCLC microarray data analysis profiling. The potential func...

  1. Microarray-based apoptosis gene screening technique in trichostatin A-induced drug-resisted lung cancer A549/CDDP cells

    Directory of Open Access Journals (Sweden)

    Ya-jun WANG

    2016-09-01

    Full Text Available Objective  To detect the expression profile changes of apoptosis-related genes in trichostatin A (TSA-induced drug-resisted lung cancer cells A549/CDDP by microarray, in order to screen the target genes in TSA treating cisplatin-resisted lung cancer. Methods  A549/CDDP cells were treated by TSA for 24 hours. Total RNA was extracted and reversely transcribed into cDNA. Gene expression levels were detected by the NimbleGen whole genome microarray. Differences of expression profiles between TSA-treated and control group were measured by NimbleScan 2.5 software and GO analysis. Apoptosis and proliferation related genes were screened from the expression changed genes. Results  Compared with the control group, 85 apoptosis-related genes were up-regulated and 43 growth or proliferation related genes were down-regulated in the TSA-treated group. GO analysis showed that the functions of these genes are mainly regulating apoptosis, cell resistance to chem ical stimuli protein, as well as regulating cell growth, proliferation and the biological process of maintaining the cell biological quality. TSA-activated not only the mitochondrial apoptotic pathways, but also the death receptor related apoptosis pathway, and down-regulated the drug resistance related genes BAG3 and ABCC2. Conclusion  TSA may cause the expression changes of apoptotic and proliferation genes in A549/CDDP cells, these genes may play a role in TSA treating cisplatin-resisted lung cancer. DOI: 10.11855/j.issn.0577-7402.2016.08.07

  2. A signature-based method for indexing cell cycle phase distribution from microarray profiles

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    Mizuno Hideaki

    2009-03-01

    Full Text Available Abstract Background The cell cycle machinery interprets oncogenic signals and reflects the biology of cancers. To date, various methods for cell cycle phase estimation such as mitotic index, S phase fraction, and immunohistochemistry have provided valuable information on cancers (e.g. proliferation rate. However, those methods rely on one or few measurements and the scope of the information is limited. There is a need for more systematic cell cycle analysis methods. Results We developed a signature-based method for indexing cell cycle phase distribution from microarray profiles under consideration of cycling and non-cycling cells. A cell cycle signature masterset, composed of genes which express preferentially in cycling cells and in a cell cycle-regulated manner, was created to index the proportion of cycling cells in the sample. Cell cycle signature subsets, composed of genes whose expressions peak at specific stages of the cell cycle, were also created to index the proportion of cells in the corresponding stages. The method was validated using cell cycle datasets and quiescence-induced cell datasets. Analyses of a mouse tumor model dataset and human breast cancer datasets revealed variations in the proportion of cycling cells. When the influence of non-cycling cells was taken into account, "buried" cell cycle phase distributions were depicted that were oncogenic-event specific in the mouse tumor model dataset and were associated with patients' prognosis in the human breast cancer datasets. Conclusion The signature-based cell cycle analysis method presented in this report, would potentially be of value for cancer characterization and diagnostics.

  3. cDNA microarray analysis of human keratinocytes cells of patients submitted to chemoradiotherapy and oral photobiomodulation therapy: pilot study.

    Science.gov (United States)

    Antunes, Heliton S; Wajnberg, Gabriel; Pinho, Marcos B; Jorge, Natasha Andressa Nogueira; de Moraes, Joyce Luana Melo; Stefanoff, Claudio Gustavo; Herchenhorn, Daniel; Araújo, Carlos M M; Viégas, Celia Maria Pais; Rampini, Mariana P; Dias, Fernando L; de Araujo-Souza, Patricia Savio; Passetti, Fabio; Ferreira, Carlos G

    2018-01-01

    Oral mucositis is an acute toxicity that occurs in patients submitted to chemoradiotherapy to treat head and neck squamous cell carcinoma. In this study, we evaluated differences in gene expression in the keratinocytes of the oral mucosa of patients treated with photobiomodulation therapy and tried to associate the molecular mechanisms with clinical findings. From June 2009 to December 2010, 27 patients were included in a randomized double-blind pilot study. Buccal smears from 13 patients were obtained at days 1 and 10 of chemoradiotherapy, and overall gene expression of samples from both dates were analyzed by complementary DNA (cDNA) microarray. In addition, samples from other 14 patients were also collected at D1 and D10 of chemoradiotherapy for subsequent validation of cDNA microarray findings by qPCR. The expression array analysis identified 105 upregulated and 60 downregulated genes in our post-treatment samples when compared with controls. Among the upregulated genes with the highest fold change, it was interesting to observe the presence of genes related to keratinocyte differentiation. Among downregulated genes were observed genes related to cytotoxicity and immune response. The results indicate that genes known to be induced during differentiation of human epidermal keratinocytes were upregulated while genes associated with cytotoxicity and immune response were downregulated in the laser group. These results support previous clinical findings indicating that the lower incidence of oral mucositis associated with photobiomodulation therapy might be correlated to the activation of genes involved in keratinocyte differentiation.

  4. Application of Microarray technology in research and diagnostics

    DEFF Research Database (Denmark)

    Helweg-Larsen, Rehannah Borup

    The overall purpose of this thesis is to evaluate the use of microarray analysis to investigate the transcriptome of human cancers and human follicular cells and define the correlation between expression of human genes and specific cancer types as well as the developmental competence of the oocyte...

  5. SegMine workflows for semantic microarray data analysis in Orange4WS

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    Kulovesi Kimmo

    2011-10-01

    Full Text Available Abstract Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases. Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

  6. Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

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    Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

    2009-10-27

    The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

  7. Annotating breast cancer microarray samples using ontologies

    Science.gov (United States)

    Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

    2008-01-01

    As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

  8. Microarray and cDNA sequence analysis of transcription during nerve-dependent limb regeneration

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    Bryant Susan V

    2009-01-01

    Full Text Available Abstract Background Microarray analysis and 454 cDNA sequencing were used to investigate a centuries-old problem in regenerative biology: the basis of nerve-dependent limb regeneration in salamanders. Innervated (NR and denervated (DL forelimbs of Mexican axolotls were amputated and transcripts were sampled after 0, 5, and 14 days of regeneration. Results Considerable similarity was observed between NR and DL transcriptional programs at 5 and 14 days post amputation (dpa. Genes with extracellular functions that are critical to wound healing were upregulated while muscle-specific genes were downregulated. Thus, many processes that are regulated during early limb regeneration do not depend upon nerve-derived factors. The majority of the transcriptional differences between NR and DL limbs were correlated with blastema formation; cell numbers increased in NR limbs after 5 dpa and this yielded distinct transcriptional signatures of cell proliferation in NR limbs at 14 dpa. These transcriptional signatures were not observed in DL limbs. Instead, gene expression changes within DL limbs suggest more diverse and protracted wound-healing responses. 454 cDNA sequencing complemented the microarray analysis by providing deeper sampling of transcriptional programs and associated biological processes. Assembly of new 454 cDNA sequences with existing expressed sequence tag (EST contigs from the Ambystoma EST database more than doubled (3935 to 9411 the number of non-redundant human-A. mexicanum orthologous sequences. Conclusion Many new candidate gene sequences were discovered for the first time and these will greatly enable future studies of wound healing, epigenetics, genome stability, and nerve-dependent blastema formation and outgrowth using the axolotl model.

  9. Microarray Expression Profile and Functional Analysis of Circular RNAs in Osteosarcoma

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    Weihai Liu

    2017-09-01

    Full Text Available Background/Aims: Osteosarcoma (OS is the most common primary malignant bone tumor in children and adolescents. However, the molecular mechanisms regulating osteosarcoma tumorigenesis and progression are still poorly understood. Circular RNAs (circRNAs have been identified as microRNA sponges and are involved in many important biological processes. This study aims to investigate the global changes in the expression pattern of circRNAs in osteosarcoma and provide a comprehensive understanding of differentially expressed circRNAs. Methods: Microarray based circRNA expression was determined in osteosarcoma cell lines and compared with hFOB1.19, which was used as the normal control. We confirmed the microarray data by real time-qPCR in both osteosarcoma cell lines and tissues. The circRNA/microRNA/mRNA interaction network was predicted using bioinformatics. Gene Ontology analysis and 4 annotation tools for pathway analysis (KEGG, Biocarta, PANTHER and Reactome were used to predict the functions of differentially expressed circRNAs. Results: We revealed a number of differentially expressed circRNAs and 12 of them were confirmed, which suggests a potential role of circRNAs in OS. Among these differentially expressed circRNAs, hsa_circRNA_103801 was up-regulated in both osteosarcoma cell lines and tissues, while hsa_circRNA_104980 was down-regulated. The most likely potential target miRNAs for hsa_circRNA_103801 include hsa-miR-370-3p, hsa-miR-338-3p and hsa-miR-877-3p, while the most potential target miRNAs of hsa_circRNA_104980 consist of hsa-miR-1298-3p and hsa-miR-660-3p. Functional analysis found that hsa_circRNA_103801 was involved in pathways in cancer, such as the HIF-1, VEGF and angiogenesis pathway, the Rap1 signaling pathway and the PI3K-Akt signaling pathway, while hsa_circRNA_104980 was related to some pathways such as the tight junction pathway. Conclusions: This study has identified the comprehensive expression profile of circRNAs in

  10. A statistical framework for differential network analysis from microarray data

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    Datta Somnath

    2010-02-01

    Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the

  11. Creation of antifouling microarrays by photopolymerization of zwitterionic compounds for protein assay and cell patterning.

    Science.gov (United States)

    Sun, Xiuhua; Wang, Huaixin; Wang, Yuanyuan; Gui, Taijiang; Wang, Ke; Gao, Changlu

    2018-04-15

    Nonspecific binding or adsorption of biomolecules presents as a major obstacle to higher sensitivity, specificity and reproducibility in microarray technology. We report herein a method to fabricate antifouling microarray via photopolymerization of biomimetic betaine compounds. In brief, carboxybetaine methacrylate was polymerized as arrays for protein sensing, while sulfobetaine methacrylate was polymerized as background. With the abundant carboxyl groups on array surfaces and zwitterionic polymers on the entire surfaces, this microarray allows biomolecular immobilization and recognition with low nonspecific interactions due to its antifouling property. Therefore, low concentration of target molecules can be captured and detected by this microarray. It was proved that a concentration of 10ngmL -1 bovine serum albumin in the sample matrix of bovine serum can be detected by the microarray derivatized with anti-bovine serum albumin. Moreover, with proper hydrophilic-hydrophobic designs, this approach can be applied to fabricate surface-tension droplet arrays, which allows surface-directed cell adhesion and growth. These light controllable approaches constitute a clear improvement in the design of antifouling interfaces, which may lead to greater flexibility in the development of interfacial architectures and wider application in blood contact microdevices. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Microarray analysis of peripheral blood lymphocytes from ALS patients and the SAFE detection of the KEGG ALS pathway

    Science.gov (United States)

    2011-01-01

    Background Sporadic amyotrophic lateral sclerosis (sALS) is a motor neuron disease with poorly understood etiology. Results of gene expression profiling studies of whole blood from ALS patients have not been validated and are difficult to relate to ALS pathogenesis because gene expression profiles depend on the relative abundance of the different cell types present in whole blood. We conducted microarray analyses using Agilent Human Whole Genome 4 × 44k Arrays on a more homogeneous cell population, namely purified peripheral blood lymphocytes (PBLs), from ALS patients and healthy controls to identify molecular signatures possibly relevant to ALS pathogenesis. Methods Differentially expressed genes were determined by LIMMA (Linear Models for MicroArray) and SAM (Significance Analysis of Microarrays) analyses. The SAFE (Significance Analysis of Function and Expression) procedure was used to identify molecular pathway perturbations. Proteasome inhibition assays were conducted on cultured peripheral blood mononuclear cells (PBMCs) from ALS patients to confirm alteration of the Ubiquitin/Proteasome System (UPS). Results For the first time, using SAFE in a global gene ontology analysis (gene set size 5-100), we show significant perturbation of the KEGG (Kyoto Encyclopedia of Genes and Genomes) ALS pathway of motor neuron degeneration in PBLs from ALS patients. This was the only KEGG disease pathway significantly upregulated among 25, and contributing genes, including SOD1, represented 54% of the encoded proteins or protein complexes of the KEGG ALS pathway. Further SAFE analysis, including gene set sizes >100, showed that only neurodegenerative diseases (4 out of 34 disease pathways) including ALS were significantly upregulated. Changes in UBR2 expression correlated inversely with time since onset of disease and directly with ALSFRS-R, implying that UBR2 was increased early in the course of ALS. Cultured PBMCs from ALS patients accumulated more ubiquitinated proteins

  13. High-throughput microarray mapping of cell wall polymers in roots and tubers during the viscosity-reducing process

    DEFF Research Database (Denmark)

    Huang, Yuhong; Willats, William George Tycho; Lange, Lene

    2016-01-01

    the viscosity-reducing process are poorly characterized. Comprehensive microarray polymer profiling, which is a high-throughput microarray, was used for the first time to map changes in the cell wall polymers of sweet potato (Ipomoea batatas), cassava (Manihot esculenta), and Canna edulis Ker. over the entire...... viscosity-reducing process. The results indicated that the composition of cell wall polymers among these three roots and tubers was markedly different. The gel-like matrix and glycoprotein network in the C. edulis Ker. cell wall caused difficulty in viscosity reduction. The obvious viscosity reduction......Viscosity reduction has a great impact on the efficiency of ethanol production when using roots and tubers as feedstock. Plant cell wall-degrading enzymes have been successfully applied to overcome the challenges posed by high viscosity. However, the changes in cell wall polymers during...

  14. In Silico Analysis of Microarray-Based Gene Expression Profiles Predicts Tumor Cell Response to Withanolides

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    Thomas Efferth

    2012-05-01

    Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.

  15. A flexible representation of omic knowledge for thorough analysis of microarray data

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    Demura Taku

    2006-03-01

    Full Text Available Abstract Background In order to understand microarray data reasonably in the context of other existing biological knowledge, it is necessary to conduct a thorough examination of the data utilizing every aspect of available omic knowledge libraries. So far, a number of bioinformatics tools have been developed. However, each of them is restricted to deal with one type of omic knowledge, e.g., pathways, interactions or gene ontology. Now that the varieties of omic knowledge are expanding, analysis tools need a way to deal with any type of omic knowledge. Hence, we have designed the Omic Space Markup Language (OSML that can represent a wide range of omic knowledge, and also, we have developed a tool named GSCope3, which can statistically analyze microarray data in comparison with the OSML-formatted omic knowledge data. Results In order to test the applicability of OSML to represent a variety of omic knowledge specifically useful for analysis of Arabidopsis thaliana microarray data, we have constructed a Biological Knowledge Library (BiKLi by converting eight different types of omic knowledge into OSML-formatted datasets. We applied GSCope3 and BiKLi to previously reported A. thaliana microarray data, so as to extract any additional insights from the data. As a result, we have discovered a new insight that lignin formation resists drought stress and activates transcription of many water channel genes to oppose drought stress; and most of the 20S proteasome subunit genes show similar expression profiles under drought stress. In addition to this novel discovery, similar findings previously reported were also quickly confirmed using GSCope3 and BiKLi. Conclusion GSCope3 can statistically analyze microarray data in the context of any OSML-represented omic knowledge. OSML is not restricted to a specific data type structure, but it can represent a wide range of omic knowledge. It allows us to convert new types of omic knowledge into datasets that can be

  16. Microarray evaluation of age-related changes in human dental pulp.

    Science.gov (United States)

    Tranasi, Michelangelo; Sberna, Maria Teresa; Zizzari, Vincenzo; D'Apolito, Giuseppe; Mastrangelo, Filiberto; Salini, Luisa; Stuppia, Liborio; Tetè, Stefano

    2009-09-01

    The dental pulp undergoes age-related changes that could be ascribed to physiological, defensive, or pathological irritant-induced changes. These changes are regulated by pulp cell activity and by a variety of extracellular matrix (ECM) macromolecules, playing important roles in growth regulation, tissue differentiation and organization, formation of calcified tissue, and defense mechanisms and reactions to inflammatory stimuli. The aim of this research was to better understand the genetic changes that underlie the histological modification of the dental pulp in aging. The gene expression profile of the human dental pulp in young and older subjects was compared by RNA microarray analysis that allowed to simultaneously analyze the expression levels of thousands of genes. Data were statistically analyzed by Significance Analysis of Microarrays (SAM) Ingenuity Pathway Analysis (IPA) software. Semiquantitative and real-time reverse-transcriptase polymerase chain reaction analyses were performed to confirm the results. Microarray analysis revealed several differentially expressed genes that were categorized in growth factors, transcription regulators, apoptosis regulators, and genes of the ECM. The comparison analysis showed a high expression level of the biological functions of cell and tissue differentiation, development, and proliferation and of the immune, lymphatic, and hematologic system in young dental pulp, whereas the pathway of apoptosis was highly expressed in older dental pulp. Expression profile analyses of human dental pulp represent a sensible and useful tool for the study of mechanisms involved in differentiation, growth and aging of human dental pulp in physiological and pathological conditions.

  17. Analysis of gene expression during odontogenic differentiation of cultured human dental pulp cells

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    Min-Seock Seo

    2012-08-01

    Full Text Available Objectives We analyzed gene-expression profiles after 14 day odontogenic induction of human dental pulp cells (DPCs using a DNA microarray and sought candidate genes possibly associated with mineralization. Materials and Methods Induced human dental pulp cells were obtained by culturing DPCs in odontogenic induction medium (OM for 14 day. Cells exposed to normal culture medium were used as controls. Total RNA was extracted from cells and analyzed by microarray analysis and the key results were confirmed selectively by reverse-transcriptase polymerase chain reaction (RT-PCR. We also performed a gene set enrichment analysis (GSEA of the microarray data. Results Six hundred and five genes among the 47,320 probes on the BeadChip differed by a factor of more than two-fold in the induced cells. Of these, 217 genes were upregulated, and 388 were down-regulated. GSEA revealed that in the induced cells, genes implicated in Apoptosis and Signaling by wingless MMTV integration (Wnt were significantly upregulated. Conclusions Genes implicated in Apoptosis and Signaling by Wnt are highly connected to the differentiation of dental pulp cells into odontoblast.

  18. Cell cycle, apoptosis, cellular uptake and whole-transcriptome microarray gene expression analysis of HeLa cells treated with a ruthenium(II)-arene complex with an isoquinoline-3-carboxylic acid ligand.

    Science.gov (United States)

    Jovanović, Katarina K; Tanić, Miljana; Ivanović, Ivanka; Gligorijević, Nevenka; Dojčinović, Biljana P; Radulović, Siniša

    2016-10-01

    Ruthenium(II)-arene complexes are promising drug candidates for the therapy of solid tumors. In previous work, seven new compounds of the general formula [Ru(η 6 -p-cymene)(L 1-7 )Cl] were synthesized and characterized, of which the complex with L=isoquinoline-3-carboxylic acid (RuT 7 ) was two times as active on HeLa cells compared to normal cell line MRC-5, as indicated by IC 50 values determined after 48h of incubation (45.4±3.0 vs. 84.2±5.7μM, respectively). In the present study, cell cycle analysis of HeLa cells treated with RuT 7 showed S phase arrest and an increase in sub-G1 population. The apoptotic potential of the title compound was confirmed with the Annexin V-FITC/PI assay together with a morphological evaluation of cells using fluorescent microscopy. Analysis of the intracellular accumulation of ruthenium showed 8.9ng Ru/10 6 cells after 6h of incubation. To gain further insight in the molecular mechanism of action of RuT 7 on HeLa cells, a whole-transcriptome microarray gene expression analysis was performed. Analysis of functional categories and signaling and biochemical pathways associated with the response of HeLa cells to treatment with RuT 7 showed that it leads the cells through the intrinsic (mitochondrial) apoptotic pathway, via indirect DNA damage due to the action of reactive oxygen species, and through direct DNA binding of RuT 7 . Statistical analysis for enrichment of gene sets associated with known drug-induced toxicities identified fewer associated toxicity profiles in RuT 7 -treated cells compared to cisplatin treatment. Altogether these results provide the basis for further development of RuT 7 in animal and pre-clinical studies as a potential drug candidate. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

    Science.gov (United States)

    Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

    2017-06-06

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

  20. ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

    DEFF Research Database (Denmark)

    Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo

    2017-01-01

    and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation....... The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots...

  1. Microarray analysis of gene expression profiles in ripening pineapple fruits.

    Science.gov (United States)

    Koia, Jonni H; Moyle, Richard L; Botella, Jose R

    2012-12-18

    Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit

  2. Carbonic Anhydrase IX is Not a Predictor of Outcomes in Non-Metastatic Clear Cell Renal Cell Carcinoma - A Digital Analysis of Tissue Microarray

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    Marcelo Zerati

    2013-07-01

    Full Text Available Introduction The knowledge about the molecular biology of clear cell renal cell carcinoma (ccRCC is evolving, and Carbonic Anhydrase type IX (CA-IX has emerged as a potential prognostic marker in this challenging disease. However, most of the literature about CA-IX on ccRCC comes from series on metastatic cancer, with a lack of series on non-metastatic cancer. The objective is to evaluate the expression of CA-IX in a cohort of non-metastatic ccRCC, correlating with 1 overall survival, and 2 with established prognostic parameters (T stage, tumor size, Fuhrman nuclear grade, microvascular invasion and peri-renal fat invasion. Materials and Methods This is a retrospective cohort study. We evaluated 95 patients with non-metastatic clear cell renal cell carcinoma, as to the expression of CA-IX. The analyzed parameters where: overall survival (OS, TNM stage, tumor size (TS, Fuhrman nuclear grade (FNG, microvascular invasion (MVI, peri-renal fat invasion (PFI. We utilized a custom built tissue microarray, and the immunoexpression was digitally quantified using the Photoshop® software. Results: Th e mean follow-up time was 7.9 years (range 1.9 to 19.5 years. The analysis of CA-IX expression against the selected prognostic parameters showed no correlation. The results are as follows: Overall survival (p = 0.790; T stage (p = 0.179; tumor size (p = 0.143; grouped Fuhrman nuclear grade (p = 0.598; microvascular invasion (p = 0.685, and peri-renal fat invasion (p = 0.104. Conclusion Carbonic anhydrase type IX expression does not correlate with overall survival and conventional prognostic parameters in non-metastatic clear cell renal cell carcinoma.

  3. DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

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    Tewfik Ahmed H

    2006-01-01

    Full Text Available Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

  4. Amygdala-enriched genes identified by microarray technology are restricted to specific amygdaloid subnuclei

    OpenAIRE

    Zirlinger, M.; Kreiman, Gabriel; Anderson, D. J.

    2001-01-01

    Microarray technology represents a potentially powerful method for identifying cell type- and regionally restricted genes expressed in the brain. Here we have combined a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray, with in situ hybridization. On average, 0.3% of the 34,000 genes interrogated were highly enriched in each of the five regions...

  5. Development and application of a microarray meter tool to optimize microarray experiments

    Directory of Open Access Journals (Sweden)

    Rouse Richard JD

    2008-07-01

    Full Text Available Abstract Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a a measure of variability in the signal intensities, b a measure of the signal dynamic range and c a measure of variability of the spot morphologies.

  6. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

    Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

  7. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

    Science.gov (United States)

    Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

    2010-05-21

    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

  8. Goober: A fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists

    Directory of Open Access Journals (Sweden)

    Luo Wen

    2009-03-01

    Full Text Available Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  9. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

    Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

  10. Plant cell wall polysaccharide analysis during cell elongation

    DEFF Research Database (Denmark)

    Guo, Xiaoyuan

    Plant cell walls are complex structures whose composition and architecture are important to various cellular activities. Plant cell elongation requires a high level of rearrangement of the cell wall polymers to enable cell expansion. However, the cell wall polysaccharides dynamics during plant cell...... elongation is poorly understood. This PhD project aims to elucidate the cell wall compositional and structural change during cell elongation by using Comprehensive Microarray Polymer Profiling (CoMPP), microscopic techniques and molecular modifications of cell wall polysaccharide. Developing cotton fibre......, pea and Arabidopsis thaliana were selected as research models to investigate different types of cell elongation, developmental elongation and tropism elongation. A set of comprehensive analysis covering 4 cotton species and 11 time points suggests that non-cellulosic polysaccharides contribute...

  11. ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2009-10-01

    Full Text Available Abstract Background Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

  12. Integrating Multiple Microarray Data for Cancer Pathway Analysis Using Bootstrapping K-S Test

    Directory of Open Access Journals (Sweden)

    Bing Han

    2009-01-01

    Full Text Available Previous applications of microarray technology for cancer research have mostly focused on identifying genes that are differentially expressed between a particular cancer and normal cells. In a biological system, genes perform different molecular functions and regulate various biological processes via interactions with other genes thus forming a variety of complex networks. Therefore, it is critical to understand the relationship (e.g., interactions between genes across different types of cancer in order to gain insights into the molecular mechanisms of cancer. Here we propose an integrative method based on the bootstrapping Kolmogorov-Smirnov test and a large set of microarray data produced with various types of cancer to discover common molecular changes in cells from normal state to cancerous state. We evaluate our method using three key pathways related to cancer and demonstrate that it is capable of finding meaningful alterations in gene relations.

  13. Expression microarray meta-analysis identifies genes associated with Ras/MAPK and related pathways in progression of muscle-invasive bladder transition cell carcinoma.

    Directory of Open Access Journals (Sweden)

    Jonathan A Ewald

    Full Text Available The effective detection and management of muscle-invasive bladder Transition Cell Carcinoma (TCC continues to be an urgent clinical challenge. While some differences of gene expression and function in papillary (Ta, superficial (T1 and muscle-invasive (≥T2 bladder cancers have been investigated, the understanding of mechanisms involved in the progression of bladder tumors remains incomplete. Statistical methods of pathway-enrichment, cluster analysis and text-mining can extract and help interpret functional information about gene expression patterns in large sets of genomic data. The public availability of patient-derived expression microarray data allows open access and analysis of large amounts of clinical data. Using these resources, we investigated gene expression differences associated with tumor progression and muscle-invasive TCC. Gene expression was calculated relative to Ta tumors to assess progression-associated differences, revealing a network of genes related to Ras/MAPK and PI3K signaling pathways with increased expression. Further, we identified genes within this network that are similarly expressed in superficial Ta and T1 stages but altered in muscle-invasive T2 tumors, finding 7 genes (COL3A1, COL5A1, COL11A1, FN1, ErbB3, MAPK10 and CDC25C whose expression patterns in muscle-invasive tumors are consistent in 5 to 7 independent outside microarray studies. Further, we found increased expression of the fibrillar collagen proteins COL3A1 and COL5A1 in muscle-invasive tumor samples and metastatic T24 cells. Our results suggest that increased expression of genes involved in mitogenic signaling may support the progression of muscle-invasive bladder tumors that generally lack activating mutations in these pathways, while expression changes of fibrillar collagens, fibronectin and specific signaling proteins are associated with muscle-invasive disease. These results identify potential biomarkers and targets for TCC treatments, and

  14. [Diagnosis of a case with Williams-Beuren syndrome with nephrocalcinosis using chromosome microarray analysis].

    Science.gov (United States)

    Jin, S J; Liu, M; Long, W J; Luo, X P

    2016-12-02

    Objective: To explore the clinical phenotypes and the genetic cause for a boy with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders. Method: Routine G-banding and chromosome microarray analysis were applied to a child with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders treated in the Department of Pediatrics of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in September 2015 and his parents to conduct the chromosomal karyotype analysis and the whole genome scanning. Deleted genes were searched in the Decipher and NCBI databases, and their relationships with the clinical phenotypes were analyzed. Result: A six-month-old boy was refered to us because of unexplained growth retardation and feeding intolerance.The affected child presented with abnormal manifestation such as special face, umbilical hernia, growth retardation, hypothyroidism, congenital heart disease, right ear sensorineural deafness, hypercalcemia and nephrocalcinosis. The child's karyotype was 46, XY, 16qh + , and his parents' karyotypes were normal. Chromosome microarray analysis revealed a 1 436 kb deletion on the 7q11.23(72701098_74136633) region of the child. This region included 23 protein-coding genes, which were reported to be corresponding to Williams-Beuren syndrome and its certain clinical phenotypes. His parents' results of chromosome microarray analysis were normal. Conclusion: A boy with characteristic manifestation of Williams-Beuren syndrome and rare nephrocalcinosis was diagnosed using chromosome microarray analysis. The deletion on the 7q11.23 might be related to the clinical phenotypes of Williams-Beuren syndrome, yet further studies are needed.

  15. Validation of tissue microarray technology in squamous cell carcinoma of the esophagus

    NARCIS (Netherlands)

    Boone, Judith; van Hillegersberg, Richard; van Diest, Paul J.; Offerhaus, G. Johan A.; Borel Rinkes, Inne H. M.; ten Kate, Fiebo J. W.

    2008-01-01

    Tissue microarray (TMA) technology has been developed to facilitate high-throughput immunohistochemical and in situ hybridization analysis of tissues by inserting small tissue biopsy cores into a single paraffin block. Several studies have revealed novel prognostic biomarkers in esophageal squamous

  16. Carbohydrate microarrays

    DEFF Research Database (Denmark)

    Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola

    2012-01-01

    In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray...... of substrate specificities of glycosyltransferases. This review covers the construction of carbohydrate microarrays, detection methods of carbohydrate microarrays and their applications in biological and biomedical research....

  17. Herpesvirus of turkeys: microarray analysis of host gene responses to infection

    International Nuclear Information System (INIS)

    Karaca, Gamze; Anobile, Jonathan; Downs, Danielle; Burnside, Joan; Schmidt, Carl J.

    2004-01-01

    Herpesvirus of turkeys (HVT) provides an economically important live vaccine for prevention of Marek's disease (MD) of chickens. MD, characterized by both immunosuppression and T-cell lymphoma, is caused by another herpesvirus termed Marek's disease virus (MDV). Microarrays were used to investigate the response of chicken embryonic fibroblasts (CEF) to infection with HVT. Genes responding to HVT infection include several induced by interferon along with others modulating signal transduction, transcription, scaffolding proteins, and the cytoskeleton. Results are compared with earlier studies examining the responses of CEF cells to infection with MDV

  18. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

    Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html

  19. Strategies for cell manipulation and skeletal tissue engineering using high-throughput polymer blend formulation and microarray techniques.

    Science.gov (United States)

    Khan, Ferdous; Tare, Rahul S; Kanczler, Janos M; Oreffo, Richard O C; Bradley, Mark

    2010-03-01

    A combination of high-throughput material formulation and microarray techniques were synergistically applied for the efficient analysis of the biological functionality of 135 binary polymer blends. This allowed the identification of cell-compatible biopolymers permissive for human skeletal stem cell growth in both in vitro and in vivo applications. The blended polymeric materials were developed from commercially available, inexpensive and well characterised biodegradable polymers, which on their own lacked both the structural requirements of a scaffold material and, critically, the ability to facilitate cell growth. Blends identified here proved excellent templates for cell attachment, and in addition, a number of blends displayed remarkable bone-like architecture and facilitated bone regeneration by providing 3D biomimetic scaffolds for skeletal cell growth and osteogenic differentiation. This study demonstrates a unique strategy to generate and identify innovative materials with widespread application in cell biology as well as offering a new reparative platform strategy applicable to skeletal tissues. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

  20. Microarray analysis reveals genetic pathways modulated by tipifarnib in acute myeloid leukemia

    International Nuclear Information System (INIS)

    Raponi, Mitch; Belly, Robert T; Karp, Judith E; Lancet, Jeffrey E; Atkins, David; Wang, Yixin

    2004-01-01

    Farnesyl protein transferase inhibitors (FTIs) were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA™, R115777) has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML). Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity

  1. The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

    Science.gov (United States)

    Beaudet, Arthur L.

    2013-01-01

    Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

  2. The application of DNA microarrays in gene expression analysis.

    Science.gov (United States)

    van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

    2000-03-31

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

  3. Nanotechnology: moving from microarrays toward nanoarrays.

    Science.gov (United States)

    Chen, Hua; Li, Jun

    2007-01-01

    Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.

  4. Investigating the effect of paralogs on microarray gene-set analysis

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

    Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

  5. arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

    Directory of Open Access Journals (Sweden)

    Moreau Yves

    2005-05-01

    Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

  6. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    Science.gov (United States)

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

  7. Bacterial identification and subtyping using DNA microarray and DNA sequencing.

    Science.gov (United States)

    Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

    2012-01-01

    The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

  8. Simulation of microarray data with realistic characteristics

    Directory of Open Access Journals (Sweden)

    Lehmussola Antti

    2006-07-01

    Full Text Available Abstract Background Microarray technologies have become common tools in biological research. As a result, a need for effective computational methods for data analysis has emerged. Numerous different algorithms have been proposed for analyzing the data. However, an objective evaluation of the proposed algorithms is not possible due to the lack of biological ground truth information. To overcome this fundamental problem, the use of simulated microarray data for algorithm validation has been proposed. Results We present a microarray simulation model which can be used to validate different kinds of data analysis algorithms. The proposed model is unique in the sense that it includes all the steps that affect the quality of real microarray data. These steps include the simulation of biological ground truth data, applying biological and measurement technology specific error models, and finally simulating the microarray slide manufacturing and hybridization. After all these steps are taken into account, the simulated data has realistic biological and statistical characteristics. The applicability of the proposed model is demonstrated by several examples. Conclusion The proposed microarray simulation model is modular and can be used in different kinds of applications. It includes several error models that have been proposed earlier and it can be used with different types of input data. The model can be used to simulate both spotted two-channel and oligonucleotide based single-channel microarrays. All this makes the model a valuable tool for example in validation of data analysis algorithms.

  9. Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

    Directory of Open Access Journals (Sweden)

    Yamada Yoichi

    2012-12-01

    Full Text Available Abstract Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO. MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO correctly identified (p Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively.

  10. Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

    Science.gov (United States)

    Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

    2010-01-18

    The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

  11. Examination of gene expression in mice exposed to low dose radiation using affymetrix cDNA microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Morris, D.; Knox, D.; Lavoie, J.; Lemon, J.; Boreham, D. [McMaster Univ., Hamilton, Ontario (Canada)

    2005-07-01

    'Full text:' Gamma radiation acts via the indirect effect to damage cells by producing reactive oxygen species (ROS). These ROS are capable damaging macromolecules and, altering signal pathways and gene transcription. Cells have evolved enzymes and mechanisms to scavenge ROS and repair oxidative damage. Microarrays allow the survey of the gene transcription activity of thousands of genes simultaneously. Messenger RNA is extracted from cells, hybridized with the complementary DNA (cDNA) of a microarray chip, and examined with a chip reader. Affymetrix microarray chips have been produced by the CSCHAH in Winnipeg containing 26000 murine genes. Groups of female mice have been exposed to low dose whole body chronic gamma radiation exposures of 0,50,100, and 120 mGy, corresponding to 15,30,60, and 75 weeks, respectively. MRNA from mice brain tissue has been extracted, isolated, converted to cDNA and labeled. Gene expression in each irradiated mouse was compared to the pooled expression of the control mice. Analysis of gene expression levels are performed with microarray analytical software, Array Pro by Media Cybernetics, and powerful statistical software, BRB microarray tools. Differences in gene expressions, focusing on genes for cytokines, DNA repair mechanisms, immuno-modulators, apoptosis pathways, and enzymatic anti-oxidant systems, are being examined and will be reported. (author)

  12. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  13. Computational biology of genome expression and regulation--a review of microarray bioinformatics.

    Science.gov (United States)

    Wang, Junbai

    2008-01-01

    Microarray technology is being used widely in various biomedical research areas; the corresponding microarray data analysis is an essential step toward the best utilizing of array technologies. Here we review two components of the microarray data analysis: a low level of microarray data analysis that emphasizes the designing, the quality control, and the preprocessing of microarray experiments, then a high level of microarray data analysis that focuses on the domain-specific microarray applications such as tumor classification, biomarker prediction, analyzing array CGH experiments, and reverse engineering of gene expression networks. Additionally, we will review the recent development of building a predictive model in genome expression and regulation studies. This review may help biologists grasp a basic knowledge of microarray bioinformatics as well as its potential impact on the future evolvement of biomedical research fields.

  14. 3D Biomaterial Microarrays for Regenerative Medicine

    DEFF Research Database (Denmark)

    Gaharwar, Akhilesh K.; Arpanaei, Ayyoob; Andresen, Thomas Lars

    2015-01-01

    Three dimensional (3D) biomaterial microarrays hold enormous promise for regenerative medicine because of their ability to accelerate the design and fabrication of biomimetic materials. Such tissue-like biomaterials can provide an appropriate microenvironment for stimulating and controlling stem...... for tissue engineering and drug screening applications....... cell differentiation into tissue-specifi c lineages. The use of 3D biomaterial microarrays can, if optimized correctly, result in a more than 1000-fold reduction in biomaterials and cells consumption when engineering optimal materials combinations, which makes these miniaturized systems very attractive...

  15. Preparation of oligonucleotide microarray for radiation-associated gene expression detection and its application in lung cancer cell lines

    International Nuclear Information System (INIS)

    Guo Wanfeng; Lin Ruxian; Huang Jian; Guo Guozhen; Wang Shengqi

    2005-01-01

    Objective: The response of tumor cell to radiation is accompanied by complex change in patterns of gene expression. It is highly probable that a better understanding of molecular and genetic changes can help to sensitize the radioresistant tumor cells. Methods: Oligonucleotide microarray provides a powerful tool for high-throughput identifying a wider range of genes involved in the radioresistance. Therefore, the authors designed one oligonucleotide microarray according to the biological effect of IR. By using different radiosensitive lung cancer cell lines, the authors identified genes showing altered expression in lung cancer cell lines. To provide independent confirmation of microarray data, semi-quantitative RT-PCR was performed on a selection of genes. Results: In radioresistant A549 cell lines, a total of 18 genes were selected as having significant fold-changes compared to NCI-H446, 8 genes were up-regulated and 10 genes were down-regulated. Subsequently, A549 and NCI-H446 cells were delivered by ionizing radiation. In A549 cell line, we found 22 (19 up-regulated and 3 down-regulated) and 26 (8 up-regulated and 18 down-regulated) differentially expressed genes at 6h and 24h after ionizing radiation. In NCI-H446 cell line, we identified 17 (9 up-regulated and 8 down-regulated) and 18 (6 up-regulated and 12 down-regulated) differentially expressed genes at 6 h and 24 h after ionizing radiation. The authors tested seven genes (MDM2, p53, XRCC5, Bcl-2, PIM2, NFKBIA and Cyclin B1) for RT-PCR, and found that the results were in good agreement with those from the microarray data except for NFKBIA gene, even though the value for each mRNA level might be different between the two measurements. In present study, the authors identified some genes with cell proliferation and anti-apoptosis, such as MdM2, BCL-2, PKCz and PIM2 expression levels increased in A549 cells and decreased in NCI-H446 cells after radiation, and other genes with DNA repair, such as XRCC5, ERCC5

  16. The application of DNA microarrays in gene expression analysis

    NARCIS (Netherlands)

    Hal, van N.L.W.; Vorst, O.; Houwelingen, van A.M.M.L.; Kok, E.J.; Peijnenburg, A.A.C.M.; Aharoni, A.; Tunen, van A.J.; Keijer, J.

    2000-01-01

    DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed.

  17. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    Directory of Open Access Journals (Sweden)

    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  18. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

    Science.gov (United States)

    Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

    2009-12-21

    Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

  19. Early Gene Expression in Wounded Human Keratinocytes Revealed by DNA Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Pascal Barbry

    2006-04-01

    Full Text Available Wound healing involves several steps: spreading of the cells, migration and proliferation. We have profiled gene expression during the early events of wound healing in normal human keratinocytes with a home-made DNA microarray containing about 1000 relevant human probes. An original wounding machine was used, that allows the wounding of up to 40% of the surface of a confluent monolayer of cultured cells grown on a Petri dish (compared with 5% with a classical ‘scratch’ method. The two aims of the present study were: (a to validate a limited number of genes by comparing the expression levels obtained with this technique with those found in the literature; (b to combine the use of the wounding machine with DNA microarray analysis for large-scale detection of the molecular events triggered during the early stages of the wound-healing process. The time-courses of RNA expression observed at 0.5, 1.5, 3, 6 and 15 h after wounding for genes such as c-Fos, c-Jun, Egr1, the plasminogen activator PLAU (uPA and the signal transducer and transcription activator STAT3, were consistent with previously published data. This suggests that our methodologies are able to perform quantitative measurement of gene expression. Transcripts encoding two zinc finger proteins, ZFP36 and ZNF161, and the tumour necrosis factor α-induced protein TNFAIP3, were also overexpressed after wounding. The role of the p38 mitogen-activated protein kinase (p38MAPK in wound healing was shown after the inhibition of p38 by SB203580, but our results also suggest the existence of surrogate activating pathways.

  20. Quantitative profiling of housekeeping and Epstein-Barr virus gene transcription in Burkitt lymphoma cell lines using an oligonucleotide microarray

    Directory of Open Access Journals (Sweden)

    Niggli Felix K

    2006-06-01

    Full Text Available Abstract Background The Epstein-Barr virus (EBV is associated with lymphoid malignancies, including Burkitt's lymphoma (BL, and can transform human B cells in vitro. EBV-harboring cell lines are widely used to investigate lymphocyte transformation and oncogenesis. Qualitative EBV gene expression has been extensively described, but knowledge of quantitative transcription is lacking. We hypothesized that transcription levels of EBNA1, the gene essential for EBV persistence within an infected cell, are similar in BL cell lines. Results To compare quantitative gene transcription in the BL cell lines Namalwa, Raji, Akata, Jijoye, and P3HR1, we developed an oligonucleotide microarray chip, including 17 housekeeping genes, six latent EBV genes (EBNA1, EBNA2, EBNA3A, EBNA3C, LMP1, LMP2, and four lytic EBV genes (BZLF1, BXLF2, BKRF2, BZLF2, and used the cell line B95.8 as a reference for EBV gene transcription. Quantitative polymerase chain reaction assays were used to validate microarray results. We found that transcription levels of housekeeping genes differed considerably among BL cell lines. Using a selection of housekeeping genes with similar quantitative transcription in the tested cell lines to normalize EBV gene transcription data, we showed that transcription levels of EBNA1 were quite similar in very different BL cell lines, in contrast to transcription levels of other EBV genes. As demonstrated with Akata cells, the chip allowed us to accurately measure EBV gene transcription changes triggered by treatment interventions. Conclusion Our results suggest uniform EBNA1 transcription levels in BL and that microarray profiling can reveal novel insights on quantitative EBV gene transcription and its impact on lymphocyte biology.

  1. Employing image processing techniques for cancer detection using microarray images.

    Science.gov (United States)

    Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

    2017-02-01

    Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Surface-enhanced Raman scattering detection of bacteria on microarrays at single cell levels using silver nanoparticles

    International Nuclear Information System (INIS)

    Zhou, Haibo; Yang, Danting; Mircescu, Nicoleta E.; Ivleva, Natalia P.; Schwarzmeier, Kathrin; Niessner, Reinhard; Haisch, Christoph; Wieser, Andreas; Schubert, Sören

    2015-01-01

    We describe a method for the synthesis of SERS-active silver nanoparticles (AgNPs) directly on the surface of bacteria (bacteria-AgNPs), specifically of E. coli cells. This straightforward strategy allows for the sensitive determination of bacteria on a microarray platform. Antibodies were used as selective receptors on the microarray surface. The Raman signal of bacteria-AgNPs is about 10 times higher than that obtained previously with microarrays based on mixing bacteria and AgNPs (bacteria+AgNPs). The optimum SERS enhancement of bacteria-AgNPs is obtained under 633-nm laser excitation, and this most likely is due to the plasmonic interaction of aggregated AgNPs. The method allows for an identification and quantification even of single E. coli bacteria. In our perception, this straightforward approach represents a most valuable tool for the detection of E. coli and, conceivably, of other bacteria, and thus has a large potential in environmental monitoring, medical diagnosis, and in food safety and quality control. (author)

  3. Supervised group Lasso with applications to microarray data analysis

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-02-01

    Full Text Available Abstract Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods.

  4. A quantitative comparison of cell-type-specific microarray gene expression profiling methods in the mouse brain.

    Directory of Open Access Journals (Sweden)

    Benjamin W Okaty

    Full Text Available Expression profiling of restricted neural populations using microarrays can facilitate neuronal classification and provide insight into the molecular bases of cellular phenotypes. Due to the formidable heterogeneity of intermixed cell types that make up the brain, isolating cell types prior to microarray processing poses steep technical challenges that have been met in various ways. These methodological differences have the potential to distort cell-type-specific gene expression profiles insofar as they may insufficiently filter out contaminating mRNAs or induce aberrant cellular responses not normally present in vivo. Thus we have compared the repeatability, susceptibility to contamination from off-target cell-types, and evidence for stress-responsive gene expression of five different purification methods--Laser Capture Microdissection (LCM, Translating Ribosome Affinity Purification (TRAP, Immunopanning (PAN, Fluorescence Activated Cell Sorting (FACS, and manual sorting of fluorescently labeled cells (Manual. We found that all methods obtained comparably high levels of repeatability, however, data from LCM and TRAP showed significantly higher levels of contamination than the other methods. While PAN samples showed higher activation of apoptosis-related, stress-related and immediate early genes, samples from FACS and Manual studies, which also require dissociated cells, did not. Given that TRAP targets actively translated mRNAs, whereas other methods target all transcribed mRNAs, observed differences may also reflect translational regulation.

  5. Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

    International Nuclear Information System (INIS)

    Karaçali, Bilge; Tözeren, Aydin

    2007-01-01

    Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest

  6. ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

    DEFF Research Database (Denmark)

    Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo

    2017-01-01

    -reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification...

  7. cDNA Microarray Analysis of Serially Sampled Cervical Cancer Specimens From Patients Treated With Thermochemoradiotherapy

    International Nuclear Information System (INIS)

    Borkamo, Erling Dahl; Schem, Baard-Christian; Fluge, Oystein; Bruland, Ove; Dahl, Olav; Mella, Olav

    2009-01-01

    Purpose: To elucidate changes in gene expression after treatment with regional thermochemoradiotherapy in locally advanced squamous cell cervical cancer. Methods and Materials: Tru-Cut biopsy specimens were serially collected from 16 patients. Microarray gene expression levels before and 24 h after the first and second trimodality treatment sessions were compared. Pathway and network analyses were conducted by use of Ingenuity Pathways Analysis (IPA; Ingenuity Systems, Redwood City, CA). Single gene expressions were analyzed by quantitative real-time reverse transcription-polymerase chain reaction. Results: We detected 53 annotated genes that were differentially expressed after trimodality treatment. Central in the three top networks detected by IPA were interferon alfa, interferon beta, and interferon gamma receptor; nuclear factor κB; and tumor necrosis factor, respectively. These genes encode proteins that are important in regulation cell signaling, proliferation, gene expression, and immune stimulation. Biological processes over-represented among the 53 genes were fibrosis, tumorigenesis, and immune response. Conclusions: Microarrays showed minor changes in gene expression after thermochemoradiotherapy in locally advanced cervical cancer. We detected 53 differentially expressed genes, mainly involved in fibrosis, tumorigenesis, and immune response. A limitation with the use of serial biopsy specimens was low quality of ribonucleic acid from tumors that respond to highly effective therapy. Another 'key limitation' is timing of the post-treatment biopsy, because 24 h may be too late to adequately assess the impact of hyperthermia on gene expression.

  8. Endoglin (CD105) expression on microvessel endothelial cells in juvenile nasopharyngeal angiofibroma: tissue microarray analysis and association with prognostic significance.

    Science.gov (United States)

    Wang, Jing-Jing; Sun, Xi-Cai; Hu, Li; Liu, Zhuo-Fu; Yu, Hua-Peng; Li, Han; Wang, Shu-Yi; Wang, De-Hui

    2013-12-01

    The purpose of this study was to examine endoglin (CD105) expression on microvessel endothelial cells (ECs) in juvenile nasopharyngeal angiofibroma (JNA) and its relationship with recurrence. Immunohistochemistry was performed to detect CD105 expression in a tissue microarray from 70 patients with JNA. Correlation between CD105 expression on microvessel ECs and clinicopathological features, as well as tumor recurrence, were analyzed. Immunohistochemistry revealed CD105 expression on ECs but not in stroma of patients with JNA. Chi-square analysis indicated CD105-based microvessel density (MVD) was correlated with JNA recurrence (p = .013). Univariate and multivariate analyses determined that MVD was a significant predictor of time to recurrence (p = .009). The CD105-based MVD was better for predicting disease recurrence (AUROC: 0.673; p = .036) than other clinicopathological features. MVD is a useful predictor for poor prognosis of patients with JNA after curative resection. Angiogenesis, which may play an important role in the occurrence and development of JNA, is therefore a potential therapeutic target for JNA. Copyright © 2013 Wiley Periodicals, Inc., A Wiley Company.

  9. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  10. Analyses of Aloe polysaccharides using carbohydrate microarray profiling

    DEFF Research Database (Denmark)

    Isager Ahl, Louise; Grace, Olwen M; Pedersen, Henriette Lodberg

    2018-01-01

    As the popularity of Aloe vera extracts continues to rise, a desire to fully understand the individual polymer components of the leaf mesophyll, their relation to one another and the effects they have on the human body are increasing. Polysaccharides present in the leaf mesophyll have been...... identified as the components responsible for the biological activities of Aloe vera, and they have been widely studied in the past decades. However, the commonly used methods do not provide the desired platform to conduct large comparative studies of polysaccharide compositions as most of them require...... a complete or near-complete fractionation of the polymers. The objective for this study was to assess whether carbohydrate microarrays could be used for the high-throughput analysis of cell wall polysaccharides in Aloe leaf mesophyll. The method we chose is known as Comprehensive Microarray Polymer Profiling...

  11. Microarray analysis of gender- and parasite-specific gene transcription in Strongyloides ratti

    NARCIS (Netherlands)

    Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve

    2008-01-01

    The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown

  12. Engineering of red cells of Arabidopsis thaliana and comparative genome-wide gene expression analysis of red cells versus wild-type cells.

    Science.gov (United States)

    Shi, Ming-Zhu; Xie, De-Yu

    2011-04-01

    We report metabolic engineering of Arabidopsis red cells and genome-wide gene expression analysis associated with anthocyanin biosynthesis and other metabolic pathways between red cells and wild-type (WT) cells. Red cells of A. thaliana were engineered for the first time from the leaves of production of anthocyanin pigment 1-Dominant (pap1-D). These red cells produced seven anthocyanin molecules including a new one that was characterized by LC-MS analysis. Wild-type cells established as a control did not produce anthocyanins. A genome-wide microarray analysis revealed that nearly 66 and 65% of genes in the genome were expressed in the red cells and wild-type cells, respectively. In comparison with the WT cells, 3.2% of expressed genes in the red cells were differentially expressed. The expression levels of 14 genes involved in the biosynthetic pathway of anthocyanin were significantly higher in the red cells than in the WT cells. Microarray and RT-PCR analyses demonstrated that the TTG1-GL3/TT8-PAP1 complex regulated the biosynthesis of anthocyanins. Furthermore, most of the genes with significant differential expression levels in the red cells versus the WT cells were characterized with diverse biochemical functions, many of which were mapped to different metabolic pathways (e.g., ribosomal protein biosynthesis, photosynthesis, glycolysis, glyoxylate metabolism, and plant secondary metabolisms) or organelles (e.g., chloroplast). We suggest that the difference in gene expression profiles between the two cell lines likely results from cell types, the overexpression of PAP1, and the high metabolic flux toward anthocyanins.

  13. Global Gene Expression Analysis of Yeast Cells during Sake Brewing▿ †

    Science.gov (United States)

    Wu, Hong; Zheng, Xiaohong; Araki, Yoshio; Sahara, Hiroshi; Takagi, Hiroshi; Shimoi, Hitoshi

    2006-01-01

    During the brewing of Japanese sake, Saccharomyces cerevisiae cells produce a high concentration of ethanol compared with other ethanol fermentation methods. We analyzed the gene expression profiles of yeast cells during sake brewing using DNA microarray analysis. This analysis revealed some characteristics of yeast gene expression during sake brewing and provided a scaffold for a molecular level understanding of the sake brewing process. PMID:16997994

  14. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    Directory of Open Access Journals (Sweden)

    Brett Trost

    Full Text Available Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA, a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

  15. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    Science.gov (United States)

    Trost, Brett; Kindrachuk, Jason; Määttänen, Pekka; Napper, Scott; Kusalik, Anthony

    2013-01-01

    Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca.

  16. Emerging Use of Gene Expression Microarrays in Plant Physiology

    Directory of Open Access Journals (Sweden)

    Stephen P. Difazio

    2006-04-01

    Full Text Available Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  17. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

    DEFF Research Database (Denmark)

    Tan, Qihua; Thomassen, Mads; Burton, Mark

    2017-01-01

    the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

  18. The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

    Science.gov (United States)

    Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

    2015-01-01

    Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

  19. Microarray analysis of thioacetamide-treated type 1 diabetic rats

    International Nuclear Information System (INIS)

    Devi, Sachin S.; Mehendale, Harihara M.

    2006-01-01

    It is well known that diabetes imparts high sensitivity to numerous hepatotoxicants. Previously, we have shown that a normally non-lethal dose of thioacetamide (TA, 300 mg/kg) causes 90% mortality in type 1 diabetic (DB) rats due to inhibited tissue repair allowing progression of liver injury. On the other hand, DB rats exposed to 30 mg TA/kg exhibit delayed tissue repair and delayed recovery from injury. The objective of this study was to investigate the mechanism of impaired tissue repair and progression of liver injury in TA-treated DB rats by using cDNA microarray. Gene expression pattern was examined at 0, 6, and 12 h after TA challenge, and selected mechanistic leads from microarray experiments were confirmed by real-time RT-PCR and further investigated at protein level over the time course of 0 to 36 h after TA treatment. Diabetic condition itself increased gene expression of proteases and decreased gene expression of protease inhibitors. Administration of 300 mg TA/kg to DB rats further elevated gene expression of proteases and suppressed gene expression of protease inhibitors, explaining progression of liver injury in DB rats after TA treatment. Inhibited expression of genes involved in cell division cycle (cyclin D1, IGFBP-1, ras, E2F) was observed after exposure of DB rats to 300 mg TA/kg, explaining inhibited tissue repair in these rats. On the other hand, DB rats receiving 30 mg TA/kg exhibit delayed expression of genes involved in cell division cycle, explaining delayed tissue repair in these rats. In conclusion, impaired cyclin D1 signaling along with increased proteases and decreased protease inhibitors may explain impaired tissue repair that leads to progression of liver injury initiated by TA in DB rats

  20. Microarray analysis in the zebrafish (Danio rerio) liver and telencephalon after exposure to low concentration of 17alpha-ethinylestradiol

    Energy Technology Data Exchange (ETDEWEB)

    Martyniuk, Christopher J. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Gerrie, Emily R. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Popesku, Jason T. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Ekker, Marc [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Trudeau, Vance L. [Centre for Advanced Research in Environmental Genomics, 30 Marie Curie, Department of Biology, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada)]. E-mail: trudeauv@uottawa.ca

    2007-08-15

    17alpha-ethinylestradiol (EE2) is detected in sewage effluent at concentrations that can disrupt normal reproductive function in fish. The objectives of this study were to identify novel genomic responses to EE2 exposure using microarray and real-time RT-PCR analysis in the liver and telencephalon of male zebrafish. Zebrafish were exposed to an environmentally relevant nominal concentration of 10 ng/L EE2 for a 21-day period. In the liver, common biomarkers for estrogenic exposure such as vitellogenin 1 and 3 (vtg1; vtg3), estrogen receptor alpha (esr1), and apolipoprotein A1 (apoA1) mRNA were identified by microarray analysis as being differentially regulated. Real-time RT-PCR confirmed that vtg1 was induced {approx}700-fold, vtg3 was induced {approx}100-fold and esr1 was induced {approx}20-fold. As determined by microarray analysis, ATPase Na+/K+ alpha 1a.4 (atp1a1a.4) and ATPase Na+/K+ beta 1a (atp1b1a) mRNA were down-regulated in the liver. Gene ontology (GO) analysis revealed that there were common biological processes and molecular functions regulated by EE2 in both tissues (e.g. electron transport and cell communication) but there were tissue specific changes in gene categories. For example, genes involved in protein metabolism, carbohydrate metabolism were down-regulated in the liver but were induced in the telencephalon. This study demonstrates that (1) tissues exhibit different gene responses to low EE2 exposure; (2) there are pronounced genomic effects in the liver and (3) multi-tissue gene profiling is needed to improve understanding of the effects of human pharmaceuticals on aquatic organisms.

  1. Systematic validation and atomic force microscopy of non-covalent short oligonucleotide barcode microarrays.

    Directory of Open Access Journals (Sweden)

    Michael A Cook

    Full Text Available BACKGROUND: Molecular barcode arrays provide a powerful means to analyze cellular phenotypes in parallel through detection of short (20-60 base unique sequence tags, or "barcodes", associated with each strain or clone in a collection. However, costs of current methods for microarray construction, whether by in situ oligonucleotide synthesis or ex situ coupling of modified oligonucleotides to the slide surface are often prohibitive to large-scale analyses. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate that unmodified 20mer oligonucleotide probes printed on conventional surfaces show comparable hybridization signals to covalently linked 5'-amino-modified probes. As a test case, we undertook systematic cell size analysis of the budding yeast Saccharomyces cerevisiae genome-wide deletion collection by size separation of the deletion pool followed by determination of strain abundance in size fractions by barcode arrays. We demonstrate that the properties of a 13K unique feature spotted 20 mer oligonucleotide barcode microarray compare favorably with an analogous covalently-linked oligonucleotide array. Further, cell size profiles obtained with the size selection/barcode array approach recapitulate previous cell size measurements of individual deletion strains. Finally, through atomic force microscopy (AFM, we characterize the mechanism of hybridization to unmodified barcode probes on the slide surface. CONCLUSIONS/SIGNIFICANCE: These studies push the lower limit of probe size in genome-scale unmodified oligonucleotide microarray construction and demonstrate a versatile, cost-effective and reliable method for molecular barcode analysis.

  2. APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

    Science.gov (United States)

    Large-scale analysis of gene expression using cDNA microarrays promises therapid detection of the mode of toxicity for drugs and other chemicals. cDNAmicroarrays were used to examine chemically-induced alterations of geneexpression in HepG2 cells exposed to oxidative ...

  3. Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

    Science.gov (United States)

    Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

    2014-01-01

    The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

  4. RoboSCell: An automated single cell arraying and analysis instrument

    KAUST Repository

    Sakaki, Kelly

    2009-09-09

    Single cell research has the potential to revolutionize experimental methods in biomedical sciences and contribute to clinical practices. Recent studies suggest analysis of single cells reveals novel features of intracellular processes, cell-to-cell interactions and cell structure. The methods of single cell analysis require mechanical resolution and accuracy that is not possible using conventional techniques. Robotic instruments and novel microdevices can achieve higher throughput and repeatability; however, the development of such instrumentation is a formidable task. A void exists in the state-of-the-art for automated analysis of single cells. With the increase in interest in single cell analyses in stem cell and cancer research the ability to facilitate higher throughput and repeatable procedures is necessary. In this paper, a high-throughput, single cell microarray-based robotic instrument, called the RoboSCell, is described. The proposed instrument employs a partially transparent single cell microarray (SCM) integrated with a robotic biomanipulator for in vitro analyses of live single cells trapped at the array sites. Cells, labeled with immunomagnetic particles, are captured at the array sites by channeling magnetic fields through encapsulated permalloy channels in the SCM. The RoboSCell is capable of systematically scanning the captured cells temporarily immobilized at the array sites and using optical methods to repeatedly measure extracellular and intracellular characteristics over time. The instrument\\'s capabilities are demonstrated by arraying human T lymphocytes and measuring the uptake dynamics of calcein acetoxymethylester-all in a fully automated fashion. © 2009 Springer Science+Business Media, LLC.

  5. Identification of bovine leukemia virus tax function associated with host cell transcription, signaling, stress response and immune response pathway by microarray-based gene expression analysis

    Directory of Open Access Journals (Sweden)

    Arainga Mariluz

    2012-03-01

    Full Text Available Abstract Background Bovine leukemia virus (BLV is associated with enzootic bovine leukosis and is closely related to human T-cell leukemia virus type I. The Tax protein of BLV is a transcriptional activator of viral replication and a key contributor to oncogenic potential. We previously identified interesting mutant forms of Tax with elevated (TaxD247G or reduced (TaxS240P transactivation effects on BLV replication and propagation. However, the effects of these mutations on functions other than transcriptional activation are unknown. In this study, to identify genes that play a role in the cascade of signal events regulated by wild-type and mutant Tax proteins, we used a large-scale host cell gene-profiling approach. Results Using a microarray containing approximately 18,400 human mRNA transcripts, we found several alterations after the expression of Tax proteins in genes involved in many cellular functions such as transcription, signal transduction, cell growth, apoptosis, stress response, and immune response, indicating that Tax protein has multiple biological effects on various cellular environments. We also found that TaxD247G strongly regulated more genes involved in transcription, signal transduction, and cell growth functions, contrary to TaxS240P, which regulated fewer genes. In addition, the expression of genes related to stress response significantly increased in the presence of TaxS240P as compared to wild-type Tax and TaxD247G. By contrast, the largest group of downregulated genes was related to immune response, and the majority of these genes belonged to the interferon family. However, no significant difference in the expression level of downregulated genes was observed among the Tax proteins. Finally, the expression of important cellular factors obtained from the human microarray results were validated at the RNA and protein levels by real-time quantitative reverse transcription-polymerase chain reaction and western blotting

  6. Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

    Science.gov (United States)

    Guzzi, Pietro Hiram; Cannataro, Mario

    2013-08-01

    A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power

  7. SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

    Directory of Open Access Journals (Sweden)

    Davies Jonathan J

    2006-12-01

    Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.

  8. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    Bacterial adhesion is often mediated by complex polymeric surface structures referred to as fimbriae. Type I fimbriae of Escherichia coli represent the archetypical and best characterised fimbrial system. These adhesive organelles mediate binding to D-mannose and are directly associated...... we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  9. Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

    Science.gov (United States)

    Hu, Wenchao; Liu, Yuting; Yan, Jun

    2014-01-01

    Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240

  10. Tissue microarray immunohistochemical detection of brachyury is not a prognostic indicator in chordoma.

    Directory of Open Access Journals (Sweden)

    Linlin Zhang

    Full Text Available Brachyury is a marker for notochord-derived tissues and neoplasms, such as chordoma. However, the prognostic relevance of brachyury expression in chordoma is still unknown. The improvement of tissue microarray technology has provided the opportunity to perform analyses of tumor tissues on a large scale in a uniform and consistent manner. This study was designed with the use of tissue microarray to determine the expression of brachyury. Brachyury expression in chordoma tissues from 78 chordoma patients was analyzed by immunohistochemical staining of tissue microarray. The clinicopathologic parameters, including gender, age, location of tumor and metastatic status were evaluated. Fifty-nine of 78 (75.64% tumors showed nuclear staining for brachyury, and among them, 29 tumors (49.15% showed 1+ (<30% positive cells staining, 15 tumors (25.42% had 2+ (31% to 60% positive cells staining, and 15 tumors (25.42% demonstrated 3+ (61% to 100% positive cells staining. Brachyury nuclear staining was detected more frequently in sacral chordomas than in chordomas of the mobile spine. However, there was no significant relationship between brachyury expression and other clinical variables. By Kaplan-Meier analysis, brachyury expression failed to produce any significant relationship with the overall survival rate. In conclusion, brachyury expression is not a prognostic indicator in chordoma.

  11. A microarray analysis of the rice transcriptome and its comparison to Arabidopsis

    DEFF Research Database (Denmark)

    Ma, Ligeng; Chen, Chen; Liu, Xigang

    2005-01-01

    Arabidopsis and rice are the only two model plants whose finished phase genome sequence has been completed. Here we report the construction of an oligomer microarray based on the presently known and predicted gene models in the rice genome. This microarray was used to analyze the transcriptional...... with similar genome-wide surveys of the Arabidopsis transcriptome, our results indicate that similar proportions of the two genomes are expressed in their corresponding organ types. A large percentage of the rice gene models that lack significant Arabidopsis homologs are expressed. Furthermore, the expression...... patterns of rice and Arabidopsis best-matched homologous genes in distinct functional groups indicate dramatic differences in their degree of conservation between the two species. Thus, this initial comparative analysis reveals some basic similarities and differences between the Arabidopsis and rice...

  12. The use of microarrays in microbial ecology

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

    2009-09-15

    Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

  13. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2015-05-01

    Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

  14. Multiplexed Analysis of Serum Breast and Ovarian Cancer Markers by Means of Suspension Bead-quantum Dot Microarrays

    Science.gov (United States)

    Brazhnik, Kristina; Sokolova, Zinaida; Baryshnikova, Maria; Bilan, Regina; Nabiev, Igor; Sukhanova, Alyona

    Multiplexed analysis of cancer markers is crucial for early tumor diagnosis and screening. We have designed lab-on-a-bead microarray for quantitative detection of three breast cancer markers in human serum. Quantum dots were used as bead-bound fluorescent tags for identifying each marker by means of flow cytometry. Antigen-specific beads reliably detected CA 15-3, CEA, and CA 125 in serum samples, providing clear discrimination between the samples with respect to the antigen levels. The novel microarray is advantageous over the routine single-analyte ones due to the simultaneous detection of various markers. Therefore the developed microarray is a promising tool for serum tumor marker profiling.

  15. A Java-based tool for the design of classification microarrays.

    Science.gov (United States)

    Meng, Da; Broschat, Shira L; Call, Douglas R

    2008-08-04

    Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for

  16. PATMA: parser of archival tissue microarray

    Directory of Open Access Journals (Sweden)

    Lukasz Roszkowiak

    2016-12-01

    Full Text Available Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images.

  17. Analysis of Chromothripsis by Combined FISH and Microarray Analysis.

    Science.gov (United States)

    MacKinnon, Ruth N

    2018-01-01

    Fluorescence in situ hybridization (FISH) to metaphase chromosomes, in conjunction with SNP array, array CGH, or whole genome sequencing, can help determine the organization of abnormal genomes after chromothripsis and other types of complex genome rearrangement. DNA microarrays can identify the changes in copy number, but they do not give information on the organization of the abnormal chromosomes, balanced rearrangements, or abnormalities of the centromeres and other regions comprised of highly repetitive DNA. Many of these details can be determined by the strategic use of metaphase FISH. FISH is a single-cell technique, so it can identify low-frequency chromosome abnormalities, and it can determine which chromosome abnormalities occur in the same or different clonal populations. These are important considerations in cancer. Metaphase chromosomes are intact, so information about abnormalities of the chromosome homologues is preserved. Here we describe strategies for working out the organization of highly rearranged genomes by combining SNP array data with various metaphase FISH methods. This approach can also be used to address some of the uncertainties arising from whole genome or mate-pair sequencing data.

  18. Analysis of gene expression in prostate cancer epithelial and interstitial stromal cells using laser capture microdissection

    International Nuclear Information System (INIS)

    Gregg, Jennifer L; Brown, Kathleen E; Mintz, Eric M; Piontkivska, Helen; Fraizer, Gail C

    2010-01-01

    The prostate gland represents a multifaceted system in which prostate epithelia and stroma have distinct physiological roles. To understand the interaction between stroma and glandular epithelia, it is essential to delineate the gene expression profiles of these two tissue types in prostate cancer. Most studies have compared tumor and normal samples by performing global expression analysis using a mixture of cell populations. This report presents the first study of prostate tumor tissue that examines patterns of differential expression between specific cell types using laser capture microdissection (LCM). LCM was used to isolate distinct cell-type populations and identify their gene expression differences using oligonucleotide microarrays. Ten differentially expressed genes were then analyzed in paired tumor and non-neoplastic prostate tissues by quantitative real-time PCR. Expression patterns of the transcription factors, WT1 and EGR1, were further compared in established prostate cell lines. WT1 protein expression was also examined in prostate tissue microarrays using immunohistochemistry. The two-step method of laser capture and microarray analysis identified nearly 500 genes whose expression levels were significantly different in prostate epithelial versus stromal tissues. Several genes expressed in epithelial cells (WT1, GATA2, and FGFR-3) were more highly expressed in neoplastic than in non-neoplastic tissues; conversely several genes expressed in stromal cells (CCL5, CXCL13, IGF-1, FGF-2, and IGFBP3) were more highly expressed in non-neoplastic than in neoplastic tissues. Notably, EGR1 was also differentially expressed between epithelial and stromal tissues. Expression of WT1 and EGR1 in cell lines was consistent with these patterns of differential expression. Importantly, WT1 protein expression was demonstrated in tumor tissues and was absent in normal and benign tissues. The prostate represents a complex mix of cell types and there is a need to analyze

  19. Identification of potential biomarkers from microarray experiments using multiple criteria optimization

    International Nuclear Information System (INIS)

    Sánchez-Peña, Matilde L; Isaza, Clara E; Pérez-Morales, Jaileene; Rodríguez-Padilla, Cristina; Castro, José M; Cabrera-Ríos, Mauricio

    2013-01-01

    Microarray experiments are capable of determining the relative expression of tens of thousands of genes simultaneously, thus resulting in very large databases. The analysis of these databases and the extraction of biologically relevant knowledge from them are challenging tasks. The identification of potential cancer biomarker genes is one of the most important aims for microarray analysis and, as such, has been widely targeted in the literature. However, identifying a set of these genes consistently across different experiments, researches, microarray platforms, or cancer types is still an elusive endeavor. Besides the inherent difficulty of the large and nonconstant variability in these experiments and the incommensurability between different microarray technologies, there is the issue of the users having to adjust a series of parameters that significantly affect the outcome of the analyses and that do not have a biological or medical meaning. In this study, the identification of potential cancer biomarkers from microarray data is casted as a multiple criteria optimization (MCO) problem. The efficient solutions to this problem, found here through data envelopment analysis (DEA), are associated to genes that are proposed as potential cancer biomarkers. The method does not require any parameter adjustment by the user, and thus fosters repeatability. The approach also allows the analysis of different microarray experiments, microarray platforms, and cancer types simultaneously. The results include the analysis of three publicly available microarray databases related to cervix cancer. This study points to the feasibility of modeling the selection of potential cancer biomarkers from microarray data as an MCO problem and solve it using DEA. Using MCO entails a new optic to the identification of potential cancer biomarkers as it does not require the definition of a threshold value to establish significance for a particular gene and the selection of a normalization

  20. Deciphering cellular morphology and biocompatibility using polymer microarrays

    International Nuclear Information System (INIS)

    Pernagallo, Salvatore; Unciti-Broceta, Asier; DIaz-Mochon, Juan Jose; Bradley, Mark

    2008-01-01

    A quantitative and qualitative analysis of cellular adhesion, morphology and viability is essential in understanding and designing biomaterials such as those involved in implant surfaces or as tissue-engineering scaffolds. As a means to simultaneously perform these studies in a high-throughput (HT) manner, we report a normalized protocol which allows the rapid analysis of a large number of potential cell binding substrates using polymer microarrays and high-content fluorescence microscopy. The method was successfully applied to the discovery of optimal polymer substrates from a 214-member polyurethane library with mouse fibroblast cells (L929), as well as simultaneous evaluation of cell viability and cellular morphology. Analysis demonstrated high biocompatibility of the binding polymers and permitted the identification of several different cellular morphologies, showing that specific polymer interactions may provoke changes in cell shape. In addition, SAR studies showed a clear correspondence between cellular adhesion and polymer structure. The approach can be utilized to perform multiple experiments (up to 1024 single experiments per slide) in a highly reproducible manner, leading to the generation of vast amounts of data in a short time period (48-72 h) while reducing dramatically the quantities of polymers, reagents and cells used

  1. High-density polymer microarrays: identifying synthetic polymers that control human embryonic stem cell growth.

    Science.gov (United States)

    Hansen, Anne; Mjoseng, Heidi K; Zhang, Rong; Kalloudis, Michail; Koutsos, Vasileios; de Sousa, Paul A; Bradley, Mark

    2014-06-01

    The fabrication of high-density polymer microarray is described, allowing the simultaneous and efficient evaluation of more than 7000 different polymers in a single-cellular-based screen. These high-density polymer arrays are applied in the search for synthetic substrates for hESCs culture. Up-scaling of the identified hit polymers enables long-term cellular cultivation and promoted successful stem-cell maintenance. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. DNA microarray technology in nutraceutical and food safety.

    Science.gov (United States)

    Liu-Stratton, Yiwen; Roy, Sashwati; Sen, Chandan K

    2004-04-15

    The quality and quantity of diet is a key determinant of health and disease. Molecular diagnostics may play a key role in food safety related to genetically modified foods, food-borne pathogens and novel nutraceuticals. Functional outcomes in biology are determined, for the most part, by net balance between sets of genes related to the specific outcome in question. The DNA microarray technology offers a new dimension of strength in molecular diagnostics by permitting the simultaneous analysis of large sets of genes. Automation of assay and novel bioinformatics tools make DNA microarrays a robust technology for diagnostics. Since its development a few years ago, this technology has been used for the applications of toxicogenomics, pharmacogenomics, cell biology, and clinical investigations addressing the prevention and intervention of diseases. Optimization of this technology to specifically address food safety is a vast resource that remains to be mined. Efforts to develop diagnostic custom arrays and simplified bioinformatics tools for field use are warranted.

  3. BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.

    Science.gov (United States)

    Geeleher, Paul; Morris, Dermot; Hinde, John P; Golden, Aaron

    2009-06-01

    BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).

  4. A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

    Science.gov (United States)

    De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

    2010-01-11

    Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

  5. A synthetic glycan microarray enables epitope mapping of plant cell wall glycan-directed antibodies

    DEFF Research Database (Denmark)

    Ruprecht, Colin; Bartetzko, Max P; Senf, Deborah

    2017-01-01

    In the last three decades, more than 200 monoclonal antibodies have been raised against most classes of plant cell wall polysaccharides by different laboratories world-wide. These antibodies are widely used to identify differences in plant cell wall components in mutants, organ and tissue types......, and developmental stages. Despite their importance and broad use, the precise binding epitope for only a few of these antibodies has been determined. Here, we use a plant glycan microarray equipped with 88 synthetic oligosaccharides to comprehensively map the epitopes of plant cell wall glycan-directed antibodies....... Our results reveal the binding epitopes for 78 arabinogalactan-, rhamnogalacturonan-, xylan-, and xyloglucan-directed antibodies. We demonstrate that, with knowledge of the exact epitopes recognized by individual antibodies, specific glycosyl hydrolases can be implemented into immunological cell wall...

  6. Spot detection and image segmentation in DNA microarray data.

    Science.gov (United States)

    Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

    2005-01-01

    Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

  7. Microarrays in brain research: the good, the bad and the ugly.

    Science.gov (United States)

    Mirnics, K

    2001-06-01

    Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

  8. Microarray-based analysis of IncA/C plasmid-associated genes from multidrug-resistant Salmonella enterica.

    Science.gov (United States)

    Lindsey, Rebecca L; Frye, Jonathan G; Fedorka-Cray, Paula J; Meinersmann, Richard J

    2011-10-01

    In the family Enterobacteriaceae, plasmids have been classified according to 27 incompatibility (Inc) or replicon types that are based on the inability of different plasmids with the same replication mechanism to coexist in the same cell. Certain replicon types such as IncA/C are associated with multidrug resistance (MDR). We developed a microarray that contains 286 unique 70-mer oligonucleotide probes based on sequences from five IncA/C plasmids: pYR1 (Yersinia ruckeri), pPIP1202 (Yersinia pestis), pP99-018 (Photobacterium damselae), pSN254 (Salmonella enterica serovar Newport), and pP91278 (Photobacterium damselae). DNA from 59 Salmonella enterica isolates was hybridized to the microarray and analyzed for the presence or absence of genes. These isolates represented 17 serovars from 14 different animal hosts and from different geographical regions in the United States. Qualitative cluster analysis was performed using CLUSTER 3.0 to group microarray hybridization results. We found that IncA/C plasmids occurred in two lineages distinguished by a major insertion-deletion (indel) region that contains genes encoding mostly hypothetical proteins. The most variable genes were represented by transposon-associated genes as well as four antimicrobial resistance genes (aphA, merP, merA, and aadA). Sixteen mercury resistance genes were identified and highly conserved, suggesting that mercury ion-related exposure is a stronger pressure than anticipated. We used these data to construct a core IncA/C genome and an accessory genome. The results of our studies suggest that the transfer of antimicrobial resistance determinants by transfer of IncA/C plasmids is somewhat less common than exchange within the plasmids orchestrated by transposable elements, such as transposons, integrating and conjugative elements (ICEs), and insertion sequence common regions (ISCRs), and thus pose less opportunity for exchange of antimicrobial resistance.

  9. Importance of the efficiency of double-stranded DNA formation in cDNA synthesis for the imprecision of microarray expression analysis.

    Science.gov (United States)

    Thormar, Hans G; Gudmundsson, Bjarki; Eiriksdottir, Freyja; Kil, Siyoen; Gunnarsson, Gudmundur H; Magnusson, Magnus Karl; Hsu, Jason C; Jonsson, Jon J

    2013-04-01

    The causes of imprecision in microarray expression analysis are poorly understood, limiting the use of this technology in molecular diagnostics. Two-dimensional strandness-dependent electrophoresis (2D-SDE) separates nucleic acid molecules on the basis of length and strandness, i.e., double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), and RNA·DNA hybrids. We used 2D-SDE to measure the efficiency of cDNA synthesis and its importance for the imprecision of an in vitro transcription-based microarray expression analysis. The relative amount of double-stranded cDNA formed in replicate experiments that used the same RNA sample template was highly variable, ranging between 0% and 72% of the total DNA. Microarray experiments showed an inverse relationship between the difference between sample pairs in probe variance and the relative amount of dsDNA. Approximately 15% of probes showed between-sample variation (P cDNA synthesized can be an important component of the imprecision in T7 RNA polymerase-based microarray expression analysis. © 2013 American Association for Clinical Chemistry

  10. Plant-pathogen interactions: what microarray tells about it?

    Science.gov (United States)

    Lodha, T D; Basak, J

    2012-01-01

    Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

  11. Layered signaling regulatory networks analysis of gene expression involved in malignant tumorigenesis of non-resolving ulcerative colitis via integration of cross-study microarray profiles.

    Science.gov (United States)

    Fan, Shengjun; Pan, Zhenyu; Geng, Qiang; Li, Xin; Wang, Yefan; An, Yu; Xu, Yan; Tie, Lu; Pan, Yan; Li, Xuejun

    2013-01-01

    Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups. In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks. Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one. The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis

  12. A Java-based tool for the design of classification microarrays

    Directory of Open Access Journals (Sweden)

    Broschat Shira L

    2008-08-01

    Full Text Available Abstract Background Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. Results The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. Conclusion In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays–and mixed-plasmid microarrays in particular–it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm, several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text, and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff. Weights

  13. Design issues in toxicogenomics using DNA microarray experiment

    International Nuclear Information System (INIS)

    Lee, Kyoung-Mu; Kim, Ju-Han; Kang, Daehee

    2005-01-01

    The methods of toxicogenomics might be classified into omics study (e.g., genomics, proteomics, and metabolomics) and population study focusing on risk assessment and gene-environment interaction. In omics study, microarray is the most popular approach. Genes falling into several categories (e.g., xenobiotics metabolism, cell cycle control, DNA repair etc.) can be selected up to 20,000 according to a priori hypothesis. The appropriate type of samples and species should be selected in advance. Multiple doses and varied exposure durations are suggested to identify those genes clearly linked to toxic response. Microarray experiments can be affected by numerous nuisance variables including experimental designs, sample extraction, type of scanners, etc. The number of slides might be determined from the magnitude and variance of expression change, false-positive rate, and desired power. Instead, pooling samples is an alternative. Online databases on chemicals with known exposure-disease outcomes and genetic information can aid the interpretation of the normalized results. Gene function can be inferred from microarray data analyzed by bioinformatics methods such as cluster analysis. The population study often adopts hospital-based or nested case-control design. Biases in subject selection and exposure assessment should be minimized, and confounding bias should also be controlled for in stratified or multiple regression analysis. Optimal sample sizes are dependent on the statistical test for gene-to-environment or gene-to-gene interaction. The design issues addressed in this mini-review are crucial in conducting toxicogenomics study. In addition, integrative approach of exposure assessment, epidemiology, and clinical trial is required

  14. Combination of Small Molecule Microarray and Confocal Microscopy Techniques for Live Cell Staining Fluorescent Dye Discovery

    Directory of Open Access Journals (Sweden)

    Attila Bokros

    2013-08-01

    Full Text Available Discovering new fluorochromes is significantly advanced by high-throughput screening (HTS methods. In the present study a combination of small molecule microarray (SMM prescreening and confocal laser scanning microscopy (CLSM was developed in order to discover novel cell staining fluorescent dyes. Compounds with high native fluorescence were selected from a 14,585-member library and further tested on living cells under the microscope. Eleven compartment-specific, cell-permeable (or plasma membrane-targeted fluorochromes were identified. Their cytotoxicity was tested and found that between 1–10 micromolar range, they were non-toxic even during long-term incubations.

  15. Microarray-based screening of heat shock protein inhibitors.

    Science.gov (United States)

    Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

    2014-06-20

    Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Evaluation of gene importance in microarray data based upon probability of selection

    Directory of Open Access Journals (Sweden)

    Fu Li M

    2005-03-01

    Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

  17. The prognostic implication of the expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in primary locally advanced oral squamous cell carcinoma cases: a tissue microarray study.

    Science.gov (United States)

    Solomon, Monica Charlotte; Vidyasagar, M S; Fernandes, Donald; Guddattu, Vasudev; Mathew, Mary; Shergill, Ankur Kaur; Carnelio, Sunitha; Chandrashekar, Chetana

    2016-12-01

    Oral squamous cell carcinomas comprise a heterogeneous tumor cell population with varied molecular characteristics, which makes prognostication of these tumors a complex and challenging issue. Thus, molecular profiling of these tumors is advantageous for an accurate prognostication and treatment planning. This is a retrospective study on a cohort of primary locally advanced oral squamous cell carcinomas (n = 178) of an Indian rural population. The expression of EGFR, p53, cyclin D1, Bcl-2 and p16 in a cohort of primary locally advanced oral squamous cell carcinomas was evaluated. A potential biomarker that can predict the tumor response to treatment was identified. Formalin-fixed paraffin-embedded tumor blocks of (n = 178) of histopathologically diagnosed cases of locally advanced oral squamous cell carcinomas were selected. Tissue microarray blocks were constructed with 2 cores of 2 mm diameter from each tumor block. Four-micron-thick sections were cut from these tissue microarray blocks. These tissue microarray sections were immunohistochemically stained for EGFR, p53, Bcl-2, cyclin D1 and p16. In this cohort, EGFR was the most frequently expressed 150/178 (84%) biomarker of the cases. Kaplan-Meier analysis showed a significant association (p = 0.038) between expression of p53 and a poor prognosis. A Poisson regression analysis showed that tumors that expressed p53 had a two times greater chance of recurrence (unadjusted IRR-95% CI 2.08 (1.03, 4.5), adjusted IRR-2.29 (1.08, 4.8) compared with the tumors that did not express this biomarker. Molecular profiling of oral squamous cell carcinomas will enable us to categorize our patients into more realistic risk groups. With biologically guided tumor characterization, personalized treatment protocols can be designed for individual patients, which will improve the quality of life of these patients.

  18. Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout.

    Directory of Open Access Journals (Sweden)

    Sophie Depiereux

    Full Text Available Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L of ethynylestradiol (EE2 and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs, which were subjected to over-representation analysis methods (ORA. Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and

  19. Iterative Bayesian Model Averaging: a method for the application of survival analysis to high-dimensional microarray data

    Directory of Open Access Journals (Sweden)

    Raftery Adrian E

    2009-02-01

    Full Text Available Abstract Background Microarray technology is increasingly used to identify potential biomarkers for cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian Model Averaging (BMA algorithm for use in classification. Here, we extend the iterative BMA algorithm for application to survival analysis on high-dimensional microarray data. The main goal in applying survival analysis to microarray data is to determine a highly predictive model of patients' time to event (such as death, relapse, or metastasis using a small number of selected genes. Our multivariate procedure combines the effectiveness of multiple contending models by calculating the weighted average of their posterior probability distributions. Our results demonstrate that our iterative BMA algorithm for survival analysis achieves high prediction accuracy while consistently selecting a small and cost-effective number of predictor genes. Results We applied the iterative BMA algorithm to two cancer datasets: breast cancer and diffuse large B-cell lymphoma (DLBCL data. On the breast cancer data, the algorithm selected a total of 15 predictor genes across 84 contending models from the training data. The maximum likelihood estimates of the selected genes and the posterior probabilities of the selected models from the training data were used to divide patients in the test (or validation dataset into high- and low-risk categories. Using the genes and models determined from the training data, we assigned patients from the test data into highly distinct risk groups (as indicated by a p-value of 7.26e-05 from the log-rank test. Moreover, we achieved comparable results using only the 5 top selected genes with 100% posterior probabilities. On the DLBCL data, our iterative BMA procedure selected a total of 25 genes across 3 contending models from the training data. Once again, we assigned the patients in the validation set to significantly distinct risk groups (p

  20. Development of a cell-defined siRNA microarray for analysis of gene function in human bone marrow stromal cells

    Directory of Open Access Journals (Sweden)

    Hi Chul Kim

    2016-03-01

    The efficiency of this CDSM was verified using three siRNAs (targeting p65, Slug, and N-cadherin, with persistent gene silencing for 5 days. We obtained the significant and reliable data with effective knock-down in our condition, and suggested our method as the qualitatively improved siRNA microarray screening method for hBMSCs.

  1. Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

    International Nuclear Information System (INIS)

    Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon

    2001-01-01

    Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with 33 P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells

  2. Gene expression of panaxydol-treated human melanoma cells using radioactive cDNA microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Joong Youn; Yu, Su Jin; Soh, Jeong Won; Kim, Meyoung Kon [College of Medicine, Korea Univ., Seoul (Korea, Republic of)

    2001-07-01

    Polyacetylenic alcohols derived from Panax ginseng have been studied to be an anticancer reagent previously. One of the Panax ginseng polyacetylenic alcohols, i.e., panaxydol, has been studied to possess an antiproliferative effect on human melanoma cell line (SK-MEL-1). In ths study, radioactive cDNA microarrays enabled an efficient approach to analyze the pattern of gene expression (3.194 genes in a total) simultaneously. The bioinformatics selection of human cDNAs, which is specifically designed for immunology, apoptosis and signal transduction, were arrayed on nylon membranes. Using with {sup 33}P labeled probes, this method provided highly sensitive gene expression profiles of our interest including apoptosis, cell proliferation, cell cycle, and signal transduction. Gene expression profiles were also classified into several categories in accordance with the duration of panaxydol treatment. Consequently, the gene profiles of our interest were significantly up (199 genes, > 2.0 of Z-ratio) or down-(196 genes, < 2.0 of Z-ratio) regulated in panaxydol-treated human melanoma cells.

  3. IsoGeneGUI : Multiple approaches for dose-response analysis of microarray data using R

    NARCIS (Netherlands)

    Otava, Martin; Sengupta, Rudradev; Shkedy, Ziv; Lin, Dan; Pramana, Setia; Verbeke, Tobias; Haldermans, Philippe; Hothorn, Ludwig A.; Gerhard, Daniel; Kuiper, Rebecca M.; Klinglmueller, Florian; Kasim, Adetayo

    2017-01-01

    The analysis of transcriptomic experiments with ordered covariates, such as dose-response data, has become a central topic in bioinformatics, in particular in omics studies. Consequently, multiple R packages on CRAN and Bioconductor are designed to analyse microarray data from various perspectives

  4. Novel R pipeline for analyzing Biolog Phenotypic MicroArray data.

    Directory of Open Access Journals (Sweden)

    Minna Vehkala

    Full Text Available Data produced by Biolog Phenotype MicroArrays are longitudinal measurements of cells' respiration on distinct substrates. We introduce a three-step pipeline to analyze phenotypic microarray data with novel procedures for grouping, normalization and effect identification. Grouping and normalization are standard problems in the analysis of phenotype microarrays defined as categorizing bacterial responses into active and non-active, and removing systematic errors from the experimental data, respectively. We expand existing solutions by introducing an important assumption that active and non-active bacteria manifest completely different metabolism and thus should be treated separately. Effect identification, in turn, provides new insights into detecting differing respiration patterns between experimental conditions, e.g. between different combinations of strains and temperatures, as not only the main effects but also their interactions can be evaluated. In the effect identification, the multilevel data are effectively processed by a hierarchical model in the Bayesian framework. The pipeline is tested on a data set of 12 phenotypic plates with bacterium Yersinia enterocolitica. Our pipeline is implemented in R language on the top of opm R package and is freely available for research purposes.

  5. Transcriptomic analysis of mouse EL4 T cells upon T cell activation and in response to protein synthesis inhibition via cycloheximide treatment

    Directory of Open Access Journals (Sweden)

    Pek Siew Lim

    2016-03-01

    Full Text Available T cell activation involves the recognition of a foreign antigen complexed to the major histocompatibility complex on the antigen presenting T cell to the T cell receptor. This leads to activation of signaling pathways, which ultimately leads to induction of key cytokine genes responsible for eradication of foreign antigens. We used the mouse EL4 T cell as a model system to study genes that are induced as a result of T cell activation using phorbol myristate acetate (PMA and calcium ionomycin (I as stimuli. We were also interested to examine the importance of new protein synthesis in regulating the expression of genes involved in T cell activation. Thus we have pre-treated mouse EL4 T cells with cycloheximide, a protein synthesis inhibitor, and left the cells unstimulated or stimulated with PMA/I for 4 h. We performed microarray expression profiling of these cells to correlate the gene expression with chromatin state of T cells upon T cell activation [1]. Here, we detail further information and analysis of the microarray data, which shows that T cell activation leads to differential expression of genes and inducible genes can be further classified as primary and secondary response genes based on their protein synthesis dependency. The data is available in the Gene Expression Omnibus under accession number GSE13278. Keywords: EL4 T cell, Microarray, T cell activation, Inducible genes

  6. Microarray gene expression profiling and analysis in renal cell carcinoma

    Directory of Open Access Journals (Sweden)

    Sadhukhan Provash

    2004-06-01

    Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most

  7. Mining meiosis and gametogenesis with DNA microarrays.

    Science.gov (United States)

    Schlecht, Ulrich; Primig, Michael

    2003-04-01

    Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.

  8. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Hybridization of labeled cDNA to microarrays is an intuitively simple and a vastly underestimated process. If it is not performed, optimized, and standardized with the same attention to detail as e.g., RNA amplification, information may be overlooked or even lost. Careful balancing of the amount ...

  9. Investigation of cellular signalling responses to non-ionising radiation in melanocytes by microarray analysis

    International Nuclear Information System (INIS)

    Boyle, G.M.; Pedley, J.; Martyn, A.C.; Fraser, L.M.; Banducci, K.J.; Parsons, P.G.; Breit, S.N.

    2003-01-01

    Melanoma is a highly aggressive cancer resulting from the abnormal proliferation and spread of specialised pigment cells in the skin, known as melanocytes. Extensive epidemiological and molecular evidence suggests that a major risk factor for melanoma formation is exposure to non-ionising radiation in the form of solar ultra-violet (UV) light. However, the exact role of solar UV in the development of melanoma is unclear. To elucidate the molecular events that occur in melanocytes following solar UV exposure and determine how they lead to melanoma development, cDNA microarray analysis was used to analyse the gene expression profile of normal melanocytes, melanocytes exposed to simulated solar UV and melanoma cells. The development of cDNA microarray technology has allowed gene expression profiling at the mRNA level to be conducted for many thousands of genes simultaneously by hybridising an array of known sequences with labelled cDNA reverse transcribed form the sample RNA. Gene expression analysis was performed for over 13,000 genes. More than 500 genes were identified as differentially expressed in melanocytes following a single UV exposure, although overall there was a general suppression of transcription. Genes that were up-regulated included oncogenes and cytoskeletal genes; in contrast, genes encoding protein tyrosine kinases and apoptosis effectors were down-regulated. Many of the genes identified as being differentially expressed represent novel UV-regulated targets. Repeated exposure to solar UV resulted in the elevation in expression of a novel member of the transforming growth factor-b (TGF-b) superfamily, the Macrophage Inhibitory Cytokine-1 (MIC-1). Our results have shown that MIC-1 is up-regulated by solar UV in melanocytes, and is highly expressed (>3 fold) in a number of metastatic melanoma cell lines (31/61) in comparison to primary melanocytes. Furthermore functional, dimerised MIC-1 was found to be secreted by melanocytes, and secreted levels were

  10. Characterization of pancreatic transcription factor Pdx-1 binding sites using promoter microarray and serial analysis of chromatin occupancy

    OpenAIRE

    Keller, David M; McWeeney, Shannon; Arsenlis, Athanasios; Drouin, Jacques; Wright, Christopher V E; Wang, Haiyan; Wollheim, Claes; White, Peter; Kaestner, Klaus H; Goodman, Richard H

    2007-01-01

    The homeobox transcription factor Pdx-1 is necessary for pancreas organogenesis and beta cell function, however, most Pdx-1-regulated genes are unknown. To further the understanding of Pdx-1 in beta cell biology, we have characterized its genomic targets in NIT-1 cells, a mouse insulinoma cell line. To identify novel targets, we developed a microarray that includes traditional promoters as well as non-coding conserved elements, micro-RNAs, and elements identified through an unbiased approach ...

  11. Prediction of transcriptional regulatory elements for plant hormone responses based on microarray data

    Directory of Open Access Journals (Sweden)

    Yamaguchi-Shinozaki Kazuko

    2011-02-01

    Full Text Available Abstract Background Phytohormones organize plant development and environmental adaptation through cell-to-cell signal transduction, and their action involves transcriptional activation. Recent international efforts to establish and maintain public databases of Arabidopsis microarray data have enabled the utilization of this data in the analysis of various phytohormone responses, providing genome-wide identification of promoters targeted by phytohormones. Results We utilized such microarray data for prediction of cis-regulatory elements with an octamer-based approach. Our test prediction of a drought-responsive RD29A promoter with the aid of microarray data for response to drought, ABA and overexpression of DREB1A, a key regulator of cold and drought response, provided reasonable results that fit with the experimentally identified regulatory elements. With this succession, we expanded the prediction to various phytohormone responses, including those for abscisic acid, auxin, cytokinin, ethylene, brassinosteroid, jasmonic acid, and salicylic acid, as well as for hydrogen peroxide, drought and DREB1A overexpression. Totally 622 promoters that are activated by phytohormones were subjected to the prediction. In addition, we have assigned putative functions to 53 octamers of the Regulatory Element Group (REG that have been extracted as position-dependent cis-regulatory elements with the aid of their feature of preferential appearance in the promoter region. Conclusions Our prediction of Arabidopsis cis-regulatory elements for phytohormone responses provides guidance for experimental analysis of promoters to reveal the basis of the transcriptional network of phytohormone responses.

  12. Parallel scan hyperspectral fluorescence imaging system and biomedical application for microarrays

    International Nuclear Information System (INIS)

    Liu Zhiyi; Ma Suihua; Liu Le; Guo Jihua; He Yonghong; Ji Yanhong

    2011-01-01

    Microarray research offers great potential for analysis of gene expression profile and leads to greatly improved experimental throughput. A number of instruments have been reported for microarray detection, such as chemiluminescence, surface plasmon resonance, and fluorescence markers. Fluorescence imaging is popular for the readout of microarrays. In this paper we develop a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. Coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. The mechanism of quasi-confocal imaging provides a high signal-to-noise ratio, and parallel scan makes this approach a high throughput technique for microarray analysis. This system is improved with a specifically designed spectrometer which can offer a spectral resolution of 0.2 nm, and operates with spatial resolutions ranging from 2 to 30 μm . Finally, the application of the system is demonstrated by reading out microarrays for identification of bacteria.

  13. Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease

    Directory of Open Access Journals (Sweden)

    van Ommen Gert-Jan B

    2008-06-01

    Full Text Available Abstract Background Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. Results While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. Conclusion Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases.

  14. Understanding plant cell-wall remodelling during the symbiotic interaction between Tuber melanosporum and Corylus avellana using a carbohydrate microarray.

    Science.gov (United States)

    Sillo, Fabiano; Fangel, Jonatan U; Henrissat, Bernard; Faccio, Antonella; Bonfante, Paola; Martin, Francis; Willats, William G T; Balestrini, Raffaella

    2016-08-01

    A combined approach, using a carbohydrate microarray as a support for genomic data, has revealed subtle plant cell-wall remodelling during Tuber melanosporum and Corylus avellana interaction. Cell walls are involved, to a great extent, in mediating plant-microbe interactions. An important feature of these interactions concerns changes in the cell-wall composition during interaction with other organisms. In ectomycorrhizae, plant and fungal cell walls come into direct contact, and represent the interface between the two partners. However, very little information is available on the re-arrangement that could occur within the plant and fungal cell walls during ectomycorrhizal symbiosis. Taking advantage of the Comprehensive Microarray Polymer Profiling (CoMPP) technology, the current study has had the aim of monitoring the changes that take place in the plant cell wall in Corylus avellana roots during colonization by the ascomycetous ectomycorrhizal fungus T. melanosporum. Additionally, genes encoding putative plant cell-wall degrading enzymes (PCWDEs) have been identified in the T. melanosporum genome, and RT-qPCRs have been performed to verify the expression of selected genes in fully developed C. avellana/T. melanosporum ectomycorrhizae. A localized degradation of pectin seems to occur during fungal colonization, in agreement with the growth of the ectomycorrhizal fungus through the middle lamella and with the fungal gene expression of genes acting on these polysaccharides.

  15. Microarray-based DNA methylation study of Ewing's sarcoma of the bone.

    Science.gov (United States)

    Park, Hye-Rim; Jung, Woon-Won; Kim, Hyun-Sook; Park, Yong-Koo

    2014-10-01

    Alterations in DNA methylation patterns are a hallmark of malignancy. However, the majority of epigenetic studies of Ewing's sarcoma have focused on the analysis of only a few candidate genes. Comprehensive studies are thus lacking and are required. The aim of the present study was to identify novel methylation markers in Ewing's sarcoma using microarray analysis. The current study reports the microarray-based DNA methylation study of 1,505 CpG sites of 807 cancer-related genes from 69 Ewing's sarcoma samples. The Illumina GoldenGate Methylation Cancer Panel I microarray was used, and with the appropriate controls (n=14), a total of 92 hypermethylated genes were identified in the Ewing's sarcoma samples. The majority of the hypermethylated genes were associated with cell adhesion, cell regulation, development and signal transduction. The overall methylation mean values were compared between patients who survived and those that did not. The overall methylation mean was significantly higher in the patients who did not survive (0.25±0.03) than in those who did (0.22±0.05) (P=0.0322). However, the overall methylation mean was not found to significantly correlate with age, gender or tumor location. GDF10 , OSM , APC and HOXA11 were the most significant differentially-methylated genes, however, their methylation levels were not found to significantly correlate with the survival rate. The DNA methylation profile of Ewing's sarcoma was characterized and 92 genes that were significantly hypermethylated were detected. A trend towards a more aggressive behavior was identified in the methylated group. The results of this study indicated that methylation may be significant in the development of Ewing's sarcoma.

  16. Microarray analysis of androgen-regulated gene expression in testis: the use of the androgen-binding protein (ABP-transgenic mouse as a model

    Directory of Open Access Journals (Sweden)

    Grossman Gail

    2005-12-01

    Full Text Available Abstract Background Spermatogenesis is an androgen-dependent process, yet the molecular mechanisms of androgens' actions in testis are poorly understood. Transgenic mice overexpressing rat androgen-binding protein (ABP in their testes have reduced levels of intratesticular androgens and, as a result, show a progressive impairment of spermatogenesis. We used this model to characterize changes in global gene expression in testis in response to reduced bioavailability of androgens. Methods Total RNA was extracted from testes of 30-day old transgenic and wild-type control mice, converted to cRNA, labeled with biotin, and hybridized to oligonucleotide microarrays. Microarray results were confirmed by real-time reverse transcription polymerase chain reaction. Results Three-hundred-eighty-one genes (3.05% of all transcripts represented on the chips were up-regulated and 198 genes (1.59% were down-regulated by at least a factor of 2 in the androgen-deficient animals compared to controls. Genes encoding membrane proteins, intracellular signaling molecules, enzymes, proteins participating in the immune response, and those involved in cytoskeleton organization were significantly overrepresented in the up-regulated group. Among the down-regulated transcripts, those coding for extracellular proteins were overrepresented most dramatically, followed by those related to proteolysis, cell adhesion, immune response, and growth factor, cytokine, and ion channel activities. Transcripts with the greatest potential impact on cellular activities included several transcription factors, intracellular signal transducers, secreted signaling molecules and enzymes, and various cell surface molecules. Major nodes in the up-regulated network were IL-6, AGT, MYC, and A2M, those in the down-regulated network were IL-2, -4, and -10, MAPK8, SOCS1, and CREB1. Conclusion Microarray analysis followed by gene ontology profiling and connectivity analysis identified several functional

  17. Gametogenesis in the Pacific oyster Crassostrea gigas: a microarrays-based analysis identifies sex and stage specific genes.

    Directory of Open Access Journals (Sweden)

    Nolwenn M Dheilly

    Full Text Available BACKGROUND: The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011 representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. METHODOLOGY/PRINCIPAL FINDINGS: Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters

  18. Replicate high-density rat genome oligonucleotide microarrays reveal hundreds of regulated genes in the dorsal root ganglion after peripheral nerve injury.

    Directory of Open Access Journals (Sweden)

    Mannion James W

    2002-10-01

    Full Text Available Abstract Background Rat oligonucleotide microarrays were used to detect changes in gene expression in the dorsal root ganglion (DRG 3 days following sciatic nerve transection (axotomy. Two comparisons were made using two sets of triplicate microarrays, naïve versus naïve and naïve versus axotomy. Results Microarray variability was assessed using the naïve versus naïve comparison. These results support use of a P 1.5-fold expression change and P 1.5-fold and P in situ hybridization verified the expression of 24 transcripts. These data showed an 83% concordance rate with the arrays; most mismatches represent genes with low expression levels reflecting limits of array sensitivity. A significant correlation was found between actual mRNA differences and relative changes between microarrays (r2 = 0.8567. Temporal patterns of individual genes regulation varied. Conclusions We identify parameters for microarray analysis which reduce error while identifying many putatively regulated genes. Functional classification of these genes suggest reorganization of cell structural components, activation of genes expressed by immune and inflammatory cells and down-regulation of genes involved in neurotransmission.

  19. Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf

    2009-01-01

    Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two...... technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate...... better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification....

  20. Comparative analysis of gene expression by microarray analysis of male and female flowers of Asparagus officinalis.

    Science.gov (United States)

    Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.

  1. ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data.

    Directory of Open Access Journals (Sweden)

    Daniel L Roden

    Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.

  2. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

    2009-01-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing

  3. Complete gene expression profiling of Saccharopolyspora erythraea using GeneChip DNA microarrays

    Directory of Open Access Journals (Sweden)

    Bordoni Roberta

    2007-11-01

    Full Text Available Abstract Background The Saccharopolyspora erythraea genome sequence, recently published, presents considerable divergence from those of streptomycetes in gene organization and function, confirming the remarkable potential of S. erythraea for producing many other secondary metabolites in addition to erythromycin. In order to investigate, at whole transcriptome level, how S. erythraea genes are modulated, a DNA microarray was specifically designed and constructed on the S. erythraea strain NRRL 2338 genome sequence, and the expression profiles of 6494 ORFs were monitored during growth in complex liquid medium. Results The transcriptional analysis identified a set of 404 genes, whose transcriptional signals vary during growth and characterize three distinct phases: a rapid growth until 32 h (Phase A; a growth slowdown until 52 h (Phase B; and another rapid growth phase from 56 h to 72 h (Phase C before the cells enter the stationary phase. A non-parametric statistical method, that identifies chromosomal regions with transcriptional imbalances, determined regional organization of transcription along the chromosome, highlighting differences between core and non-core regions, and strand specific patterns of expression. Microarray data were used to characterize the temporal behaviour of major functional classes and of all the gene clusters for secondary metabolism. The results confirmed that the ery cluster is up-regulated during Phase A and identified six additional clusters (for terpenes and non-ribosomal peptides that are clearly regulated in later phases. Conclusion The use of a S. erythraea DNA microarray improved specificity and sensitivity of gene expression analysis, allowing a global and at the same time detailed picture of how S. erythraea genes are modulated. This work underlines the importance of using DNA microarrays, coupled with an exhaustive statistical and bioinformatic analysis of the results, to understand the transcriptional

  4. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis

    Science.gov (United States)

    Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

    2016-01-01

    A high phosphorus (HP) diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus) or a HP diet (containing 1.2% phosphorus). Gene Ontology analysis of differentially expressed genes (DEGs) revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054) in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty acids

  5. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis.

    Directory of Open Access Journals (Sweden)

    Sunwoo Chun

    Full Text Available A high phosphorus (HP diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus or a HP diet (containing 1.2% phosphorus. Gene Ontology analysis of differentially expressed genes (DEGs revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα, a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054 in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty

  6. DNA Microarray Technologies: A Novel Approach to Geonomic Research

    Energy Technology Data Exchange (ETDEWEB)

    Hinman, R.; Thrall, B.; Wong, K,

    2002-01-01

    A cDNA microarray allows biologists to examine the expression of thousands of genes simultaneously. Researchers may analyze the complete transcriptional program of an organism in response to specific physiological or developmental conditions. By design, a cDNA microarray is an experiment with many variables and few controls. One question that inevitably arises when working with a cDNA microarray is data reproducibility. How easy is it to confirm mRNA expression patterns? In this paper, a case study involving the treatment of a murine macrophage RAW 264.7 cell line with tumor necrosis factor alpha (TNF) was used to obtain a rough estimate of data reproducibility. Two trials were examined and a list of genes displaying either a > 2-fold or > 4-fold increase in gene expression was compiled. Variations in signal mean ratios between the two slides were observed. We can assume that erring in reproducibility may be compensated by greater inductive levels of similar genes. Steps taken to obtain results included serum starvation of cells before treatment, tests of mRNA for quality/consistency, and data normalization.

  7. Microarray analysis of toxicogenomic effects of Ortho-phenylphenol in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Toghrol Freshteh

    2008-09-01

    Full Text Available Abstract Background Staphylococcus aureus (S. aureus, is responsible for many infectious diseases, ranging from benign skin infections to life-threatening endocarditis and toxic shock syndrome. Ortho-phenylphenol (OPP is an antimicrobial agent and an active ingredient of EPA-registered disinfectants with wide human exposure in various agricultural, hospital and veterinary disinfectant products. Despite many uses, an understanding of a cellular response to OPP and it's mechanism of action, targeted genes, and the connectivity between targeted genes and the rest of cell metabolism remains obscure. Results Herein, we performed a genome-wide transcriptome analysis of the cellular responses of S. aureus when exposed to 0.82 mM of OPP for 20 and 60 min. Our data indicated that OPP downregulated the biosynthesis of many amino acids, which are required for protein synthesis. In particular, the genes encoding the enzymes of the diaminopimelate (DAP pathway which results in lysine biosynthesis were significantly downregualted. Intriguingly, we revealed that the transcription of genes encoding ribosomal proteins was upregulated by OPP and at the same time, the genes encoding iron acquisition and transport were downregulated. The genes encoding virulence factors were upregulated and genes encoding phospholipids were downregulated upon 20 min exposure to OPP. Conclusion By using microarray analysis that enables us to simultaneously and globally examine the complete transcriptome during cellular responses, we have revealed novel information regarding the mode of action of OPP on Staphylococcus: OPP inhibits anabolism of many amino acids and highly downregulates the genes that encode the enzymes involved in the DAP pathway. Lysine and DAP are essential for building up the peptidoglycan cell wall. It was concluded that the mode of action of OPP is similar to the mechanism of action of some antibiotics. The discovery of this phenomenon provides useful

  8. Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray.

    Science.gov (United States)

    Ávila-Fernández, Almudena; Cantalapiedra, Diego; Aller, Elena; Vallespín, Elena; Aguirre-Lambán, Jana; Blanco-Kelly, Fiona; Corton, M; Riveiro-Álvarez, Rosa; Allikmets, Rando; Trujillo-Tiebas, María José; Millán, José M; Cremers, Frans P M; Ayuso, Carmen

    2010-12-03

    Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. 272 unrelated Spanish families, 107 with autosomal recessive RP (arRP) and 165 with sporadic RP (sRP), were studied using the APEX genotyping microarray. The families were also classified by clinical criteria: 86 juveniles and 186 typical RP families. Haplotype and sequence analysis were performed to identify the second mutated allele. At least one-gene variant was found in 14% and 16% of the juvenile and typical RP groups respectively. Further study identified four new mutations, providing both causative changes in 11% of the families. Retinol Dehydrogenase 12 (RDH12) was the most frequently mutated gene in the juvenile RP group, and Usher Syndrome 2A (USH2A) and Ceramide Kinase-Like (CERKL) were the most frequently mutated genes in the typical RP group. The only variant found in CERKL was p.Arg257Stop, the most frequent mutation. The genotyping microarray combined with segregation and sequence analysis allowed us to identify the causative mutations in 11% of the families. Due to the low number of characterized families, this approach should be used in tandem with other techniques.

  9. Production of DNA microarray and expression analysis of genes from Xylella fastidiosa in different culture media

    Directory of Open Access Journals (Sweden)

    Regiane de Fátima Travensolo

    2009-06-01

    Full Text Available DNA Microarray was developed to monitor the expression of many genes from Xylella fastidiosa, allowing the side by-side comparison of two situations in a single experiment. The experiments were performed using X. fastidiosa cells grown in two culture media: BCYE and XDM2. The primers were synthesized, spotted onto glass slides and the array was hybridized against fluorescently labeled cDNAs. The emitted signals were quantified, normalized and the data were statistically analyzed to verify the differentially expressed genes. According to the data, 104 genes were differentially expressed in XDM2 and 30 genes in BCYE media. The present study showed that DNA microarray technique efficiently differentiate the expressed genes under different conditions.DNA Microarray foi desenvolvida para monitorar a expressão de muitos genes de Xylella fastidiosa, permitindo a comparação de duas situações distintas em um único experimento. Os experimentos foram feitos utilizando células de X. fastidiosa cultivada em dois meios de cultura: BCYE e XDM2. Pares de oligonucleotídeos iniciadores foram sintetizados, depositados em lâminas de vidro e o arranjo foi hibridizado contra cDNAs marcados fluorescentemente. Os sinais emitidos foram quantificados, normalizados e os dados foram estatisticamente analisados para verificar os genes diferencialmente expressos. De acordo com nossos dados, 104 genes foram diferencialmente expressos para o meio de cultura XDM2 e 30 genes para o BCYE. No presente estudo, nós demonstramos que a técnica de DNA microarrays eficientemente diferencia genes expressos sob diferentes condições de cultivo.

  10. Incorporation of gene-specific variability improves expression analysis using high-density DNA microarrays

    Directory of Open Access Journals (Sweden)

    Spitznagel Edward

    2003-11-01

    Full Text Available Abstract Background The assessment of data reproducibility is essential for application of microarray technology to exploration of biological pathways and disease states. Technical variability in data analysis largely depends on signal intensity. Within that context, the reproducibility of individual probe sets has not been hitherto addressed. Results We used an extraordinarily large replicate data set derived from human placental trophoblast to analyze probe-specific contribution to variability of gene expression. We found that signal variability, in addition to being signal-intensity dependant, is probe set-specific. Importantly, we developed a novel method to quantify the contribution of this probe set-specific variability. Furthermore, we devised a formula that incorporates a priori-computed, replicate-based information on probe set- and intensity-specific variability in determination of expression changes even without technical replicates. Conclusion The strategy of incorporating probe set-specific variability is superior to analysis based on arbitrary fold-change thresholds. We recommend its incorporation to any computation of gene expression changes using high-density DNA microarrays. A Java application implementing our T-score is available at http://www.sadovsky.wustl.edu/tscore.html.

  11. Microarray and pathway analysis reveal distinct mechanisms underlying cannabinoid-mediated modulation of LPS-induced activation of BV-2 microglial cells.

    Directory of Open Access Journals (Sweden)

    Ana Juknat

    Full Text Available Cannabinoids are known to exert immunosuppressive activities. However, the mechanisms which contribute to these effects are unknown. Using lipopolysaccharide (LPS to activate BV-2 microglial cells, we examined how Δ(9-tetrahydrocannabinol (THC, the major psychoactive component of marijuana, and cannabidiol (CBD the non-psychoactive component, modulate the inflammatory response. Microarray analysis of genome-wide mRNA levels was performed using Illumina platform and the resulting expression patterns analyzed using the Ingenuity Pathway Analysis to identify functional subsets of genes, and the Ingenuity System Database to denote the gene networks regulated by CBD and THC. From the 5338 transcripts that were differentially expressed across treatments, 400 transcripts were found to be upregulated by LPS, 502 by CBD+LPS and 424 by THC+LPS, while 145 were downregulated by LPS, 297 by CBD+LPS and 149 by THC+LPS, by 2-fold or more (p≤0.005. Results clearly link the effects of CBD and THC to inflammatory signaling pathways and identify new cannabinoid targets in the MAPK pathway (Dusp1, Dusp8, Dusp2, cell cycle related (Cdkn2b, Gadd45a as well as JAK/STAT regulatory molecules (Socs3, Cish, Stat1. The impact of CBD on LPS-stimulated gene expression was greater than that of THC. We attribute this difference to the fact that CBD highly upregulated several genes encoding negative regulators of both NFκB and AP-1 transcriptional activities, such as Trib3 and Dusp1 known to be modulated through Nrf2 activation. The CBD-specific expression profile reflected changes associated with oxidative stress and glutathione depletion via Trib3 and expression of ATF4 target genes. Furthermore, the CBD affected genes were shown to be controlled by nuclear factors usually involved in regulation of stress response and inflammation, mainly via Nrf2/Hmox1 axis and the Nrf2/ATF4-Trib3 pathway. These observations indicate that CBD, and less so THC, induce a cellular stress

  12. Workflows for microarray data processing in the Kepler environment

    Science.gov (United States)

    2012-01-01

    Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or

  13. Workflows for microarray data processing in the Kepler environment

    Directory of Open Access Journals (Sweden)

    Stropp Thomas

    2012-05-01

    Full Text Available Abstract Background Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. Results We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data and therefore are close to

  14. Workflows for microarray data processing in the Kepler environment.

    Science.gov (United States)

    Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

    2012-05-17

    Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R

  15. Single-gene testing combined with single nucleotide polymorphism microarray preimplantation genetic diagnosis for aneuploidy: a novel approach in optimizing pregnancy outcome.

    Science.gov (United States)

    Brezina, Paul R; Benner, Andrew; Rechitsky, Svetlana; Kuliev, Anver; Pomerantseva, Ekaterina; Pauling, Dana; Kearns, William G

    2011-04-01

    To describe a method of amplifying DNA from blastocyst trophectoderm cells (two or three cells) and simultaneously performing 23-chromosome single nucleotide polymorphism microarrays and single-gene preimplantation genetic diagnosis. Case report. IVF clinic and preimplantation genetic diagnostic centers. A 36-year-old woman, gravida 2, para 1011, and her husband who both were carriers of GM(1) gangliosidosis. The couple wished to proceed with microarray analysis for aneuploidy detection coupled with DNA sequencing for GM(1) gangliosidosis. An IVF cycle was performed. Ten blastocyst-stage embryos underwent trophectoderm biopsy. Twenty-three-chromosome microarray analysis for aneuploidy and specific DNA sequencing for GM(1) gangliosidosis mutations were performed. Viable pregnancy. After testing, elective single embryo transfer was performed followed by an intrauterine pregnancy with documented fetal cardiac activity by ultrasound. Twenty-three-chromosome microarray analysis for aneuploidy detection and single-gene evaluation via specific DNA sequencing and linkage analysis are used for preimplantation diagnosis for single-gene disorders and aneuploidy. Because of the minimal amount of genetic material obtained from the day 3 to 5 embryos (up to 6 pg), these modalities have been used in isolation of each other. The use of preimplantation genetic diagnosis for aneuploidy coupled with testing for single-gene disorders via trophectoderm biopsy is a novel approach to maximize pregnancy outcomes. Although further investigation is warranted, preimplantation genetic diagnosis for aneuploidy and single-gene testing seem destined to be used increasingly to optimize ultimate pregnancy success. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  16. Direct calibration of PICKY-designed microarrays

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    Ronald Pamela C

    2009-10-01

    Full Text Available Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

  17. Microarrays for Universal Detection and Identification of Phytoplasmas

    DEFF Research Database (Denmark)

    Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

    2013-01-01

    Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...... and differentiate all types of phytoplasmas in one assay. The present protocol describes a microarray-based method for identification of phytoplasmas to 16Sr group level....

  18. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    International Nuclear Information System (INIS)

    Herbáth, Melinda; Balogh, Andrea; Matkó, János; Papp, Krisztián; Prechl, József

    2014-01-01

    Protein microarray technology is becoming the method of choice for identifying protein interaction partners, detecting specific proteins, carbohydrates and lipids, or for characterizing protein interactions and serum antibodies in a massively parallel manner. Availability of the well-established instrumentation of DNA arrays and development of new fluorescent detection instruments promoted the spread of this technique. Fluorescent detection has the advantage of high sensitivity, specificity, simplicity and wide dynamic range required by most measurements. Fluorescence through specifically designed probes and an increasing variety of detection modes offers an excellent tool for such microarray platforms. Measuring for example the level of antibodies, their isotypes and/or antigen specificity simultaneously can offer more complex and comprehensive information about the investigated biological phenomenon, especially if we take into consideration that hundreds of samples can be measured in a single assay. Not only body fluids, but also cell lysates, extracted cellular components, and intact living cells can be analyzed on protein arrays for monitoring functional responses to printed samples on the surface. As a rapidly evolving area, protein microarray technology offers a great bulk of information and new depth of knowledge. These are the features that endow protein arrays with wide applicability and robust sample analyzing capability. On the whole, protein arrays are emerging new tools not just in proteomics, but glycomics, lipidomics, and are also important for immunological research. In this review we attempt to summarize the technical aspects of planar fluorescent microarray technology along with the description of its main immunological applications. (topical review)

  19. Seeded Bayesian Networks: Constructing genetic networks from microarray data

    Directory of Open Access Journals (Sweden)

    Quackenbush John

    2008-07-01

    Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

  20. Single-Nucleotide Polymorphism-Microarray Ploidy Analysis of Paraffin-Embedded Products of Conception in Recurrent Pregnancy Loss Evaluations.

    Science.gov (United States)

    Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

    2015-07-01

    To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal

  1. An Overview of DNA Microarray Grid Alignment and Foreground Separation Approaches

    Directory of Open Access Journals (Sweden)

    Bajcsy Peter

    2006-01-01

    Full Text Available This paper overviews DNA microarray grid alignment and foreground separation approaches. Microarray grid alignment and foreground separation are the basic processing steps of DNA microarray images that affect the quality of gene expression information, and hence impact our confidence in any data-derived biological conclusions. Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis. In the past, the grid alignment and foreground separation steps have not been covered extensively in the survey literature. We present several classifications of existing algorithms, and describe the fundamental principles of these algorithms. Challenges related to automation and reliability of processed image data are outlined at the end of this overview paper.

  2. Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton

    Science.gov (United States)

    Muller, Jean; Mehlen, André; Vetter, Guillaume; Yatskou, Mikalai; Muller, Arnaud; Chalmel, Frédéric; Poch, Olivier; Friederich, Evelyne; Vallar, Laurent

    2007-01-01

    Background The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton. Results Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not. Conclusion Our data demonstrate that

  3. Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

    Science.gov (United States)

    Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

    2006-06-01

    Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

  4. Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

    Science.gov (United States)

    Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

    The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

  5. Multivariate analysis of microarray data: differential expression and differential connection.

    Science.gov (United States)

    Kiiveri, Harri T

    2011-02-01

    Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  6. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    Science.gov (United States)

    Tra, Yolande V.; Evans, Irene M.

    2010-01-01

    "BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

  7. Implementation of mutual information and bayes theorem for classification microarray data

    Science.gov (United States)

    Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

    2018-03-01

    Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

  8. Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

    Science.gov (United States)

    Weitzeal, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

    2016-01-01

    Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASAs GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-boxkelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASAs VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

  9. High-throughput screening of monoclonal antibodies against plant cell wall glycans by hierarchical clustering of their carbohydrate microarray binding profiles

    DEFF Research Database (Denmark)

    Moller, Isabel Eva; Marcus, Susan E.; Haeger, Ash

    2008-01-01

    Antibody-producing hybridoma cell lines were created following immunisation with a crude extract of cell wall polymers from the plant Arabidopsis thaliana. In order to rapidly screen the specificities of individual monoclonal antibodies (mAbs), their binding to microarrays containing 50 cell wall...... investigated using subsequent immunochemical and biochemical analyses and two novel mAbs are described in detail. mAb LM13 binds to an arabinanase-sensitive pectic epitope and mAb LM14, binds to an epitope occurring on arabinogalactan-proteins. Both mAbs display novel patterns of recognition of cell walls...

  10. A pilot study of transcription unit analysis in rice using oligonucleotide tiling-path microarray

    DEFF Research Database (Denmark)

    Stolc, Viktor; Li, Lei; Wang, Xiangfeng

    2005-01-01

    As the international efforts to sequence the rice genome are completed, an immediate challenge and opportunity is to comprehensively and accurately define all transcription units in the rice genome. Here we describe a strategy of using high-density oligonucleotide tiling-path microarrays to map...... transcription of the japonica rice genome. In a pilot experiment to test this approach, one array representing the reverse strand of the last 11.2 Mb sequence of chromosome 10 was analyzed in detail based on a mathematical model developed in this study. Analysis of the array data detected 77% of the reference...... gene models in a mixture of four RNA populations. Moreover, significant transcriptional activities were found in many of the previously annotated intergenic regions. These preliminary results demonstrate the utility of genome tiling microarrays in evaluating annotated rice gene models...

  11. Transcriptome analysis of the human T lymphocyte cell line Jurkat and human peripheral blood mononuclear cells exposed to deoxynivalenol (DON): New mechanistic insights

    Energy Technology Data Exchange (ETDEWEB)

    Katika, Madhumohan R. [RIKILT-Institute of Food Safety, Wageningen University and Research Centre, Wageningen (Netherlands); Department of Health Risk Analysis and Toxicology, Maastricht University (Netherlands); Netherlands Toxicogenomics Centre (Netherlands); Hendriksen, Peter J.M. [RIKILT-Institute of Food Safety, Wageningen University and Research Centre, Wageningen (Netherlands); Netherlands Toxicogenomics Centre (Netherlands); Shao, Jia [RIKILT-Institute of Food Safety, Wageningen University and Research Centre, Wageningen (Netherlands); Department of Health Risk Analysis and Toxicology, Maastricht University (Netherlands); Netherlands Toxicogenomics Centre (Netherlands); Loveren, Henk van [Department of Health Risk Analysis and Toxicology, Maastricht University (Netherlands); National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Netherlands Toxicogenomics Centre (Netherlands); Peijnenburg, Ad, E-mail: ad.peijnenburg@wur.nl [RIKILT-Institute of Food Safety, Wageningen University and Research Centre, Wageningen (Netherlands); Netherlands Toxicogenomics Centre (Netherlands)

    2012-10-01

    Deoxynivalenol (DON) or vomitoxin is a commonly encountered type-B trichothecene mycotoxin, produced by Fusarium species predominantly found in cereals and grains. DON is known to exert toxic effects on the gastrointestinal, reproductive and neuroendocrine systems, and particularly on the immune system. Depending on dose and exposure time, it can either stimulate or suppress immune function. The main objective of this study was to obtain a deeper insight into DON-induced effects on lymphoid cells. For this, we exposed the human T-lymphocyte cell line Jurkat and human peripheral blood mononuclear cells (PBMCs) to various concentrations of DON for various times and examined gene expression changes by DNA microarray analysis. Jurkat cells were exposed to 0.25 and 0.5 μM DON for 3, 6 and 24 h. Biological interpretation of the microarray data indicated that DON affects various processes in these cells: It upregulates genes involved in ribosome structure and function, RNA/protein synthesis and processing, endoplasmic reticulum (ER) stress, calcium-mediated signaling, mitochondrial function, oxidative stress, the NFAT and NF-κB/TNF-α pathways, T cell activation and apoptosis. The effects of DON on the expression of genes involved in ER stress, NFAT activation and apoptosis were confirmed by qRT-PCR. Other biochemical experiments confirmed that DON activates calcium-dependent proteins such as calcineurin and M-calpain that are known to be involved in T cell activation and apoptosis. Induction of T cell activation was also confirmed by demonstrating that DON activates NFATC1 and induces its translocation from the cytoplasm to the nucleus. For the gene expression profiling of PBMCs, cells were exposed to 2 and 4 μM DON for 6 and 24 h. Comparison of the Jurkat microarray data with those obtained with PBMCs showed that most of the processes affected by DON in the Jurkat cell line were also affected in the PBMCs. -- Highlights: ► The human T cell line Jurkat and human

  12. Analysis of gene expression profile microarray data in complex regional pain syndrome.

    Science.gov (United States)

    Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

    2017-09-01

    The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

  13. Carbohydrate Microarrays in Plant Science

    DEFF Research Database (Denmark)

    Fangel, Jonatan Ulrik; Pedersen, H.L.; Vidal-Melgosa, S.

    2012-01-01

    Almost all plant cells are surrounded by glycan-rich cell walls, which form much of the plant body and collectively are the largest source of biomass on earth. Plants use polysaccharides for support, defense, signaling, cell adhesion, and as energy storage, and many plant glycans are also important...... industrially and nutritionally. Understanding the biological roles of plant glycans and the effective exploitation of their useful properties requires a detailed understanding of their structures, occurrence, and molecular interactions. Microarray technology has revolutionized the massively high...... for plant research and can be used to map glycan populations across large numbers of samples to screen antibodies, carbohydrate binding proteins, and carbohydrate binding modules and to investigate enzyme activities....

  14. DNA Microarrays: a Powerful Genomic Tool for Biomedical and Clinical Research

    OpenAIRE

    Trevino, Victor; Falciani, Francesco; Barrera-Saldaña, Hugo A

    2007-01-01

    Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred to as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, they reveal differences in genetic makeup, regulat...

  15. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

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    Karen S. Ho

    2016-12-01

    Full Text Available Copy number variants (CNVs detected by chromosomal microarray analysis (CMA significantly contribute to understanding the etiology of autism spectrum disorder (ASD and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID and/or multiple congenital anomalies (MCA. The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.

  16. Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

    DEFF Research Database (Denmark)

    Novak, Jaroslav P; Kim, Seon-Young; Xu, Jun

    2006-01-01

    BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have...

  17. Extending the scope of diagnostic chromosome analysis: detection of single gene defects using high-resolution SNP microarrays.

    Science.gov (United States)

    Bruno, Damien L; Stark, Zornitza; Amor, David J; Burgess, Trent; Butler, Kathy; Corrie, Sylvea; Francis, David; Ganesamoorthy, Devika; Hills, Louise; James, Paul A; O'Rielly, Darren; Oertel, Ralph; Savarirayan, Ravi; Prabhakara, Krishnamurthy; Salce, Nicholas; Slater, Howard R

    2011-12-01

    Microarray analysis has provided significant advances in the diagnosis of conditions resulting from submicroscopic chromosome abnormalities. It has been recommended that array testing should be a "first tier" test in the evaluation of individuals with intellectual disability, developmental delay, congenital anomalies, and autism. The availability of arrays with increasingly high probe coverage and resolution has increased the detection of decreasingly small copy number changes (CNCs) down to the intragenic or even exon level. Importantly, arrays that genotype SNPs also detect extended regions of homozygosity. We describe 14 examples of single gene disorders caused by intragenic changes from a consecutive set of 6,500 tests using high-resolution SNP microarrays. These cases illustrate the increased scope of cytogenetic testing beyond dominant chromosome rearrangements that typically contain many genes. Nine of the cases confirmed the clinical diagnosis, that is, followed a "phenotype to genotype" approach. Five were diagnosed by the laboratory analysis in the absence of a specific clinical diagnosis, that is, followed a "genotype to phenotype" approach. Two were clinically significant, incidental findings. The importance of astute clinical assessment and laboratory-clinician consultation is emphasized to optimize the value of microarrays in the diagnosis of disorders caused by single gene copy number and sequence mutations. © 2011 Wiley-Liss, Inc.

  18. Integrative missing value estimation for microarray data.

    Science.gov (United States)

    Hu, Jianjun; Li, Haifeng; Waterman, Michael S; Zhou, Xianghong Jasmine

    2006-10-12

    Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. We present the integrative Missing Value Estimation method (iMISS) by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS) imputation algorithm by up to 15% improvement in our benchmark tests. We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

  19. A Reliable and Distributed LIMS for Efficient Management of the Microarray Experiment Environment

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2007-03-01

    Full Text Available A microarray is a principal technology in molecular biology. It generates thousands of expressions of genotypes at once. Typically, a microarray experiment contains many kinds of information, such as gene names, sequences, expression profiles, scanned images, and annotation. So, the organization and analysis of vast amounts of data are required. Microarray LIMS (Laboratory Information Management System provides data management, search, and basic analysis. Recently, microarray joint researches, such as the skeletal system disease and anti-cancer medicine have been widely conducted. This research requires data sharing among laboratories within the joint research group. In this paper, we introduce a web based microarray LIMS, SMILE (Small and solid MIcroarray Lims for Experimenters, especially for shared data management. The data sharing function of SMILE is based on Friend-to-Friend (F2F, which is based on anonymous P2P (Peer-to-Peer, in which people connect directly with their “friends”. It only allows its friends to exchange data directly using IP addresses or digital signatures you trust. In SMILE, there are two types of friends: “service provider”, which provides data, and “client”, which is provided with data. So, the service provider provides shared data only to its clients. SMILE provides useful functions for microarray experiments, such as variant data management, image analysis, normalization, system management, project schedule management, and shared data management. Moreover, it connections with two systems: ArrayMall for analyzing microarray images and GENAW for constructing a genetic network. SMILE is available on http://neobio.cs.pusan.ac.kr:8080/smile.

  20. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    Sinnakaruppan Mathavan

    2005-08-01

    Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.

  1. Measuring O-GlcNAc cleavage by OGA and cell lysates on a peptide microarray.

    Science.gov (United States)

    Sharif, Suhela; Shi, Jie; Bourakba, Mostafa; Ruijtenbeek, Rob; Pieters, Roland J

    2017-09-01

    O-GlcNAcylation is a post-translational modification resulting from the addition of an N-acetylglucosamine moiety to the hydroxyl groups of serine and threonine residues of nuclear and cytoplasmic proteins. In addition, O-GlcNAcylated proteins can be phosphorylated, which suggests the possibility for crosstalk between O-GlcNAcylation and phosphorylation. Dysregulation of O-GlcNAcylation affects cell signaling, transcriptional regulation, cell cycle control and can e.g. lead to tumorigenesis and tumor metastasis. There is a strong demand for efficient analytical techniques to better detect and investigate this abundant modification and its role in cancer. Herein we demonstrated the utility of an O-GlcNAcylated peptide array to examine O-GlcNAcase (OGA) activity and substrate specificity of both purified protein as well cell lysates of different cancer cell lines. Using this microarray, we clearly observed OGA activity and also inhibition thereof by OGA inhibitor thiamet G. Interestingly, different levels of OGA activity were observed of lysates derived from different cancer cell lines. This suggests that the tool may be useful in cancer research and biomarker development. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Multivariate analysis of microarray data: differential expression and differential connection

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    Kiiveri Harri T

    2011-02-01

    Full Text Available Abstract Background Typical analysis of microarray data ignores the correlation between gene expression values. In this paper we present a model for microarray data which specifically allows for correlation between genes. As a result we combine gene network ideas with linear models and differential expression. Results We use sparse inverse covariance matrices and their associated graphical representation to capture the notion of gene networks. An important issue in using these models is the identification of the pattern of zeroes in the inverse covariance matrix. The limitations of existing methods for doing this are discussed and we provide a workable solution for determining the zero pattern. We then consider a method for estimating the parameters in the inverse covariance matrix which is suitable for very high dimensional matrices. We also show how to construct multivariate tests of hypotheses. These overall multivariate tests can be broken down into two components, the first one being similar to tests for differential expression and the second involving the connections between genes. Conclusion The methods in this paper enable the extraction of a wealth of information concerning the relationships between genes which can be conveniently represented in graphical form. Differentially expressed genes can be placed in the context of the gene network and places in the gene network where unusual or interesting patterns have emerged can be identified, leading to the formulation of hypotheses for future experimentation.

  3. Gene expression profiling and secretome analysis differentiate adult-derived human liver stem/progenitor cells and human hepatic stellate cells.

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    Silvia Berardis

    Full Text Available Adult-derived human liver stem/progenitor cells (ADHLSC are obtained after primary culture of the liver parenchymal fraction. The cells are of fibroblastic morphology and exhibit a hepato-mesenchymal phenotype. Hepatic stellate cells (HSC derived from the liver non-parenchymal fraction, present a comparable morphology as ADHLSC. Because both ADHLSC and HSC are described as liver stem/progenitor cells, we strived to extensively compare both cell populations at different levels and to propose tools demonstrating their singularity. ADHLSC and HSC were isolated from the liver of four different donors, expanded in vitro and followed from passage 5 until passage 11. Cell characterization was performed using immunocytochemistry, western blotting, flow cytometry, and gene microarray analyses. The secretion profile of the cells was evaluated using Elisa and multiplex Luminex assays. Both cell types expressed α-smooth muscle actin, vimentin, fibronectin, CD73 and CD90 in accordance with their mesenchymal origin. Microarray analysis revealed significant differences in gene expression profiles. HSC present high expression levels of neuronal markers as well as cytokeratins. Such differences were confirmed using immunocytochemistry and western blotting assays. Furthermore, both cell types displayed distinct secretion profiles as ADHLSC highly secreted cytokines of therapeutic and immuno-modulatory importance, like HGF, interferon-γ and IL-10. Our study demonstrates that ADHLSC and HSC are distinct liver fibroblastic cell populations exhibiting significant different expression and secretion profiles.

  4. Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning. Analysis of Space Grown Arabidopsis with Microarray Data from GeneLab: Identification of Genes Important in Vascular Patterning

    Science.gov (United States)

    Weitzel, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

    2016-01-01

    Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photo-assimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be up-regulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS (Auxin-Regulated Gene Involved in Organ Size)-like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm up-regulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

  5. Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

    Science.gov (United States)

    Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

    2012-01-01

    Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of

  6. Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells

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    Montalescot Gilles

    2008-06-01

    Full Text Available Abstract Background In this study we assessed the respective ability of Affymetrix and Illumina microarray methodologies to answer a relevant biological question, namely the change in gene expression between resting monocytes and macrophages derived from these monocytes. Five RNA samples for each type of cell were hybridized to the two platforms in parallel. In addition, a reference list of differentially expressed genes (DEG was generated from a larger number of hybridizations (mRNA from 86 individuals using the RNG/MRC two-color platform. Results Our results show an important overlap of the Illumina and Affymetrix DEG lists. In addition, more than 70% of the genes in these lists were also present in the reference list. Overall the two platforms had very similar performance in terms of biological significance, evaluated by the presence in the DEG lists of an excess of genes belonging to Gene Ontology (GO categories relevant for the biology of monocytes and macrophages. Our results support the conclusion of the MicroArray Quality Control (MAQC project that the criteria used to constitute the DEG lists strongly influence the degree of concordance among platforms. However the importance of prioritizing genes by magnitude of effect (fold change rather than statistical significance (p-value to enhance cross-platform reproducibility recommended by the MAQC authors was not supported by our data. Conclusion Functional analysis based on GO enrichment demonstrates that the 2 compared technologies delivered very similar results and identified most of the relevant GO categories enriched in the reference list.

  7. A systems biology approach to the pathogenesis of obesity-related nonalcoholic fatty liver disease using reverse phase protein microarrays for multiplexed cell signaling analysis.

    Science.gov (United States)

    Calvert, Valerie S; Collantes, Rochelle; Elariny, Hazem; Afendy, Arian; Baranova, Ancha; Mendoza, Michael; Goodman, Zachary; Liotta, Lance A; Petricoin, Emanuel F; Younossi, Zobair M

    2007-07-01

    Nonalcoholic fatty liver disease (NAFLD) is a common cause of chronic liver disease. Omental adipose tissue, a biologically active organ secreting adipokines and cytokines, may play a role in the development of NAFLD. We tested this hypothesis with reverse-phase protein microarrays (RPA) for multiplexed cell signaling analysis of adipose tissue from patients with NAFLD. Omental adipose tissue was obtained from 99 obese patients. Liver biopsies obtained at the time of surgery were all read by the same hepatopathologist. Adipose tissue was exposed to rapid pressure cycles to extract protein lysates. RPA was used to investigate intracellular signaling. Analysis of 54 different kinase substrates and cell signaling endpoints showed that an insulin signaling pathway is deranged in different locations in NAFLD patients. Furthermore, components of insulin receptor-mediated signaling differentiate most of the conditions on the NAFLD spectrum. For example, PKA (protein kinase A) and AKT/mTOR (protein kinase B/mammalian target of rapamycin) pathway derangement accurately discriminates patients with NASH from those with the non-progressive forms of NAFLD. PKC (protein kinase C) delta, AKT, and SHC phosphorylation changes occur in patients with simple steatosis. Amounts of the FKHR (forkhead factor Foxo1)phosphorylated at S256 residue were significantly correlated with AST/ALT ratio in all morbidly obese patients. Furthermore, amounts of cleaved caspase 9 and pp90RSK S380 were positively correlated in patients with NASH. Specific insulin pathway signaling events are altered in the adipose tissue of patients with NASH compared with patients with nonprogressive forms of NAFLD. These findings provide evidence for the role of omental fat in the pathogenesis, and potentially, the progression of NAFLD.

  8. Microarray data re-annotation reveals specific lncRNAs and their potential functions in non-small cell lung cancer subtypes.

    Science.gov (United States)

    Zhou, Dongbo; Xie, Mingxuan; He, Baimei; Gao, Ying; Yu, Qiao; He, Bixiu; Chen, Qiong

    2017-10-01

    Non‑small‑cell lung cancer (NSCLC) is a leading cause of cancer mortality worldwide. The most common subtypes of NSCLC are adenocarcinoma (AC) and squamous cell carcinoma (SCC). However, the pathophysiological mechanisms contributing to AC and SCC are still largely unknown, especially the roles of long non‑coding RNAs (lncRNAs). The present study identified differentially expressed lncRNAs between lung AC and SCC by re‑annotation of NSCLC microarray data analysis profiling. The potential functions of lncRNAs were predicted by using coding‑non‑coding gene co‑expressing network. Reverse transcription-quantitative polymerase chain reaction (RT‑qPCR) was used to investigate lncRNA expression levels in AC cell lines (A549 and L78), SCC cell lines (H226 and H520) and normal cells (NL‑20). Western blotting analysis was used to investigate the protein expression levels in these cell lines. A total of 65 lncRNAs were differentially expressed between AC and SCC including 28 lncRNAs that were downregulated in SCC subtypes compared with those in AC ones, and 37 upregulated lncRNAs in SCC subtypes compared with AC subtypes. Three lncRNAs, sex determining region Y‑box 2 overlapping transcript (SOX2‑OT), NCBP2 antisense RNA 2 (NCBP2‑AS2) and ubiquitin like with PHD and ring finger domains 1 (UHRF1), were predicted to be associated with lung cancer; RT‑qPCR confirmed that SOX2‑OT and NCBP2‑AS2 were associated with lung cancer. Finally, western blot assays demonstrated that there was no difference in β‑catenin and glycogen synthase kinase 3β (GSK‑3β) expression in cancer cells compared with NL‑20, but increased phosphorylated (p‑)β‑catenin and p‑GSK‑3β was detected in lung cancer cell lines compared with NL‑20, particularly in A549 cells. Although these results require further experimental verification, the analysis of lncRNA signatures between AC and SCC has provided insights into the regulatory mechanism of NSCLC development.

  9. Identification of rat lung-specific microRNAs by microRNA microarray: valuable discoveries for the facilitation of lung research

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    Chintagari Narendranath

    2007-01-01

    Full Text Available Abstract Background An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs. These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. Results In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM and Tukey Honestly Significant Difference (HSD revealed 2 miRNAs (miR-195 and miR-200c expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. Conclusion The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung.

  10. Identification of rat lung-specific microRNAs by micoRNA microarray: valuable discoveries for the facilitation of lung research.

    Science.gov (United States)

    Wang, Yang; Weng, Tingting; Gou, Deming; Chen, Zhongming; Chintagari, Narendranath Reddy; Liu, Lin

    2007-01-24

    An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs). These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM) and Tukey Honestly Significant Difference (HSD) revealed 2 miRNAs (miR-195 and miR-200c) expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung.

  11. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    Science.gov (United States)

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  12. Microarray expression profiling of human dental pulp from single subject.

    Science.gov (United States)

    Tete, Stefano; Mastrangelo, Filiberto; Scioletti, Anna Paola; Tranasi, Michelangelo; Raicu, Florina; Paolantonio, Michele; Stuppia, Liborio; Vinci, Raffaele; Gherlone, Enrico; Ciampoli, Cristian; Sberna, Maria Teresa; Conti, Pio

    2008-01-01

    Microarray is a recently developed simultaneous analysis of expression patterns of thousand of genes. The aim of this research was to evaluate the expression profile of human healthy dental pulp in order to find the presence of genes activated and encoding for proteins involved in the physiological process of human dental pulp. We report data obtained by analyzing expression profiles of human tooth pulp from single subjects, using an approach based on the amplification of the total RNA. Experiments were performed on a high-density array able to analyse about 21,000 oligonucleotide sequences of about 70 bases in duplicate, using an approach based on the amplification of the total RNA from the pulp of a single tooth. Obtained data were analyzed using the S.A.M. system (Significance Analysis of Microarray) and genes were merged according to their molecular functions and biological process by the Onto-Express software. The microarray analysis revealed 362 genes with specific pulp expression. Genes showing significant high expression were classified in genes involved in tooth development, protoncogenes, genes of collagen, DNAse, Metallopeptidases and Growth factors. We report a microarray analysis, carried out by extraction of total RNA from specimens of healthy human dental pulp tissue. This approach represents a powerful tool in the study of human normal and pathological pulp, allowing minimization of the genetic variability due to the pooling of samples from different individuals.

  13. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

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    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

  14. Prenatal chromosomal microarray analysis in fetuses with congenital heart disease: a prospective cohort study.

    Science.gov (United States)

    Wang, Yan; Cao, Li; Liang, Dong; Meng, Lulu; Wu, Yun; Qiao, Fengchang; Ji, Xiuqing; Luo, Chunyu; Zhang, Jingjing; Xu, Tianhui; Yu, Bin; Wang, Leilei; Wang, Ting; Pan, Qiong; Ma, Dingyuan; Hu, Ping; Xu, Zhengfeng

    2018-02-01

    Currently, chromosomal microarray analysis is considered the first-tier test in pediatric care and prenatal diagnosis. However, the diagnostic yield of chromosomal microarray analysis for prenatal diagnosis of congenital heart disease has not been evaluated based on a large cohort. Our aim was to evaluate the clinical utility of chromosomal microarray as the first-tier test for chromosomal abnormalities in fetuses with congenital heart disease. In this prospective study, 602 prenatal cases of congenital heart disease were investigated using single nucleotide polymorphism array over a 5-year period. Overall, pathogenic chromosomal abnormalities were identified in 125 (20.8%) of 602 prenatal cases of congenital heart disease, with 52.0% of them being numerical chromosomal abnormalities. The detection rates of likely pathogenic copy number variations and variants of uncertain significance were 1.3% and 6.0%, respectively. The detection rate of pathogenic chromosomal abnormalities in congenital heart disease plus additional structural anomalies (48.9% vs 14.3%, P congenital heart disease group. Additionally, the detection rate in congenital heart disease with additional structural anomalies group was significantly higher than that in congenital heart disease with soft markers group (48.9% vs 19.8%, P congenital heart disease with additional structural anomalies and congenital heart disease with intrauterine growth retardation groups (48.9% vs 50.0%), congenital heart disease with soft markers and congenital heart disease with intrauterine growth retardation groups (19.8% vs 50.0%), or congenital heart disease with soft markers and isolated congenital heart disease groups (19.8% vs 14.3%). The detection rate in fetuses with congenital heart disease plus mild ventriculomegaly was significantly higher than in those with other types of soft markers (50.0% vs 15.6%, P congenital heart disease in clinical practice. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Transcriptional profiling of endocrine cerebro-osteodysplasia using microarray and next-generation sequencing.

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    Piya Lahiry

    Full Text Available BACKGROUND: Transcriptome profiling of patterns of RNA expression is a powerful approach to identify networks of genes that play a role in disease. To date, most mRNA profiling of tissues has been accomplished using microarrays, but next-generation sequencing can offer a richer and more comprehensive picture. METHODOLOGY/PRINCIPAL FINDINGS: ECO is a rare multi-system developmental disorder caused by a homozygous mutation in ICK encoding intestinal cell kinase. We performed gene expression profiling using both cDNA microarrays and next-generation mRNA sequencing (mRNA-seq of skin fibroblasts from ECO-affected subjects. We then validated a subset of differentially expressed transcripts identified by each method using quantitative reverse transcription-polymerase chain reaction (qRT-PCR. Finally, we used gene ontology (GO to identify critical pathways and processes that were abnormal according to each technical platform. Methodologically, mRNA-seq identifies a much larger number of differentially expressed genes with much better correlation to qRT-PCR results than the microarray (r² = 0.794 and 0.137, respectively. Biologically, cDNA microarray identified functional pathways focused on anatomical structure and development, while the mRNA-seq platform identified a higher proportion of genes involved in cell division and DNA replication pathways. CONCLUSIONS/SIGNIFICANCE: Transcriptome profiling with mRNA-seq had greater sensitivity, range and accuracy than the microarray. The two platforms generated different but complementary hypotheses for further evaluation.

  16. Integrative missing value estimation for microarray data

    Directory of Open Access Journals (Sweden)

    Zhou Xianghong

    2006-10-01

    Full Text Available Abstract Background Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples. Results We present the integrative Missing Value Estimation method (iMISS by incorporating information from multiple reference microarray datasets to improve missing value estimation. For each gene with missing data, we derive a consistent neighbor-gene list by taking reference data sets into consideration. To determine whether the given reference data sets are sufficiently informative for integration, we use a submatrix imputation approach. Our experiments showed that iMISS can significantly and consistently improve the accuracy of the state-of-the-art Local Least Square (LLS imputation algorithm by up to 15% improvement in our benchmark tests. Conclusion We demonstrated that the order-statistics-based integrative imputation algorithms can achieve significant improvements over the state-of-the-art missing value estimation approaches such as LLS and is especially good for imputing microarray datasets with a limited number of samples, high rates of missing data, or very noisy measurements. With the rapid accumulation of microarray datasets, the performance of our approach can be further improved by incorporating larger and more appropriate reference datasets.

  17. Clonal diversity analysis using SNP microarray: a new prognostic tool for chronic lymphocytic leukemia.

    Science.gov (United States)

    Zhang, Linsheng; Znoyko, Iya; Costa, Luciano J; Conlin, Laura K; Daber, Robert D; Self, Sally E; Wolff, Daynna J

    2011-12-01

    Chronic lymphocytic leukemia (CLL) is a clinically heterogeneous disease. The methods currently used for monitoring CLL and determining conditions for treatment are limited in their ability to predict disease progression, patient survival, and response to therapy. Although clonal diversity and the acquisition of new chromosomal abnormalities during the disease course (clonal evolution) have been associated with disease progression, their prognostic potential has been underappreciated because cytogenetic and fluorescence in situ hybridization (FISH) studies have a restricted ability to detect genomic abnormalities and clonal evolution. We hypothesized that whole genome analysis using high resolution single nucleotide polymorphism (SNP) microarrays would be useful to detect diversity and infer clonal evolution to offer prognostic information. In this study, we used the Infinium Omni1 BeadChip (Illumina, San Diego, CA) array for the analysis of genetic variation and percent mosaicism in 25 non-selected CLL patients to explore the prognostic value of the assessment of clonal diversity in patients with CLL. We calculated the percentage of mosaicism for each abnormality by applying a mathematical algorithm to the genotype frequency data and by manual determination using the Simulated DNA Copy Number (SiDCoN) tool, which was developed from a computer model of mosaicism. At least one genetic abnormality was identified in each case, and the SNP data was 98% concordant with FISH results. Clonal diversity, defined as the presence of two or more genetic abnormalities with differing percentages of mosaicism, was observed in 12 patients (48%), and the diversity correlated with the disease stage. Clonal diversity was present in most cases of advanced disease (Rai stages III and IV) or those with previous treatment, whereas 9 of 13 patients without detected clonal diversity were asymptomatic or clinically stable. In conclusion, SNP microarray studies with simultaneous evaluation

  18. Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.

    Science.gov (United States)

    Azumi, Kaoru; Takahashi, Hiroki; Miki, Yasufumi; Fujie, Manabu; Usami, Takeshi; Ishikawa, Hisayoshi; Kitayama, Atsusi; Satou, Yutaka; Ueno, Naoto; Satoh, Nori

    2003-10-01

    A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.

  19. Microarray analysis of pancreatic gene expression during biotin repletion in biotin-deficient rats.

    Science.gov (United States)

    Dakshinamurti, Krishnamurti; Bagchi, Rushita A; Abrenica, Bernard; Czubryt, Michael P

    2015-12-01

    Biotin is a B vitamin involved in multiple metabolic pathways. In humans, biotin deficiency is relatively rare but can cause dermatitis, alopecia, and perosis. Low biotin levels occur in individuals with type-2 diabetes, and supplementation with biotin plus chromium may improve blood sugar control. The acute effect on pancreatic gene expression of biotin repletion following chronic deficiency is unclear, therefore we induced biotin deficiency in adult male rats by feeding them a 20% raw egg white diet for 6 weeks. Animals were then randomized into 2 groups: one group received a single biotin supplement and returned to normal chow lacking egg white, while the second group remained on the depletion diet. After 1 week, pancreata were removed from biotin-deficient (BD) and biotin-repleted (BR) animals and RNA was isolated for microarray analysis. Biotin depletion altered gene expression in a manner indicative of inflammation, fibrosis, and defective pancreatic function. Conversely, biotin repletion activated numerous repair and anti-inflammatory pathways, reduced fibrotic gene expression, and induced multiple genes involved in pancreatic endocrine and exocrine function. A subset of the results was confirmed by quantitative real-time PCR analysis, as well as by treatment of pancreatic AR42J cells with biotin. The results indicate that biotin repletion, even after lengthy deficiency, results in the rapid induction of repair processes in the pancreas.

  20. ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

    Science.gov (United States)

    Giancarlo, R; Scaturro, D; Utro, F

    2015-02-01

    The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Metabolic enzyme microarray coupled with miniaturized cell-culture array technology for high-throughput toxicity screening.

    Science.gov (United States)

    Lee, Moo-Yeal; Dordick, Jonathan S; Clark, Douglas S

    2010-01-01

    Due to poor drug candidate safety profiles that are often identified late in the drug development process, the clinical progression of new chemical entities to pharmaceuticals remains hindered, thus resulting in the high cost of drug discovery. To accelerate the identification of safer drug candidates and improve the clinical progression of drug candidates to pharmaceuticals, it is important to develop high-throughput tools that can provide early-stage predictive toxicology data. In particular, in vitro cell-based systems that can accurately mimic the human in vivo response and predict the impact of drug candidates on human toxicology are needed to accelerate the assessment of drug candidate toxicity and human metabolism earlier in the drug development process. The in vitro techniques that provide a high degree of human toxicity prediction will be perhaps more important in cosmetic and chemical industries in Europe, as animal toxicity testing is being phased out entirely in the immediate future.We have developed a metabolic enzyme microarray (the Metabolizing Enzyme Toxicology Assay Chip, or MetaChip) and a miniaturized three-dimensional (3D) cell-culture array (the Data Analysis Toxicology Assay Chip, or DataChip) for high-throughput toxicity screening of target compounds and their metabolic enzyme-generated products. The human or rat MetaChip contains an array of encapsulated metabolic enzymes that is designed to emulate the metabolic reactions in the human or rat liver. The human or rat DataChip contains an array of 3D human or rat cells encapsulated in alginate gels for cell-based toxicity screening. By combining the DataChip with the complementary MetaChip, in vitro toxicity results are obtained that correlate well with in vivo rat data.

  2. Multi-gene detection and identification of mosquito-borne RNA viruses using an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Nathan D Grubaugh

    Full Text Available BACKGROUND: Arthropod-borne viruses are important emerging pathogens world-wide. Viruses transmitted by mosquitoes, such as dengue, yellow fever, and Japanese encephalitis viruses, infect hundreds of millions of people and animals each year. Global surveillance of these viruses in mosquito vectors using molecular based assays is critical for prevention and control of the associated diseases. Here, we report an oligonucleotide DNA microarray design, termed ArboChip5.1, for multi-gene detection and identification of mosquito-borne RNA viruses from the genera Flavivirus (family Flaviviridae, Alphavirus (Togaviridae, Orthobunyavirus (Bunyaviridae, and Phlebovirus (Bunyaviridae. METHODOLOGY/PRINCIPAL FINDINGS: The assay utilizes targeted PCR amplification of three genes from each virus genus for electrochemical detection on a portable, field-tested microarray platform. Fifty-two viruses propagated in cell-culture were used to evaluate the specificity of the PCR primer sets and the ArboChip5.1 microarray capture probes. The microarray detected all of the tested viruses and differentiated between many closely related viruses such as members of the dengue, Japanese encephalitis, and Semliki Forest virus clades. Laboratory infected mosquitoes were used to simulate field samples and to determine the limits of detection. Additionally, we identified dengue virus type 3, Japanese encephalitis virus, Tembusu virus, Culex flavivirus, and a Quang Binh-like virus from mosquitoes collected in Thailand in 2011 and 2012. CONCLUSIONS/SIGNIFICANCE: We demonstrated that the described assay can be utilized in a comprehensive field surveillance program by the broad-range amplification and specific identification of arboviruses from infected mosquitoes. Furthermore, the microarray platform can be deployed in the field and viral RNA extraction to data analysis can occur in as little as 12 h. The information derived from the ArboChip5.1 microarray can help to establish

  3. Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.

    Science.gov (United States)

    Leavey, Katherine; Bainbridge, Shannon A; Cox, Brian J

    2015-01-01

    Preeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups. To address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia. Our analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.

  4. Analysis of gene expression in a human-derived glial cell line exposed to 2.45 GHz continuous radiofrequency electromagnetic fields

    International Nuclear Information System (INIS)

    Sakurai, Tomonori; Narita, Eijiro; Miyakoshi, Junji; Kiyokawa, Tomoko; Suzuki, Yukihisa; Taki, Masao

    2011-01-01

    The increasing use of mobile phones has aroused public concern regarding the potential health risks of radiofrequency (RF) fields. We investigated the effects of exposure to RF fields (2.45 GHz, continuous wave) at specific absorption rate (SAR) of 1, 5, and 10 W/kg for 1, 4, and 24 h on gene expression in a normal human glial cell line, SVGp12, using DNA microarray. Microarray analysis revealed 23 assigned gene spots and 5 non-assigned gene spots as prospective altered gene spots. Twenty-two genes out of the 23 assigned gene spots were further analyzed by reverse transcription-polymerase chain reaction to validate the results of microarray, and no significant alterations in gene expression were observed. Under the experimental conditions used in this study, we found no evidence that exposure to RF fields affected gene expression in SVGp12 cells. (author)

  5. Fuzzy C-means method for clustering microarray data.

    Science.gov (United States)

    Dembélé, Doulaye; Kastner, Philippe

    2003-05-22

    Clustering analysis of data from DNA microarray hybridization studies is essential for identifying biologically relevant groups of genes. Partitional clustering methods such as K-means or self-organizing maps assign each gene to a single cluster. However, these methods do not provide information about the influence of a given gene for the overall shape of clusters. Here we apply a fuzzy partitioning method, Fuzzy C-means (FCM), to attribute cluster membership values to genes. A major problem in applying the FCM method for clustering microarray data is the choice of the fuzziness parameter m. We show that the commonly used value m = 2 is not appropriate for some data sets, and that optimal values for m vary widely from one data set to another. We propose an empirical method, based on the distribution of distances between genes in a given data set, to determine an adequate value for m. By setting threshold levels for the membership values, genes which are tigthly associated to a given cluster can be selected. Using a yeast cell cycle data set as an example, we show that this selection increases the overall biological significance of the genes within the cluster. Supplementary text and Matlab functions are available at http://www-igbmc.u-strasbg.fr/fcm/

  6. Development of a novel multiplex DNA microarray for Fusarium graminearum and analysis of azole fungicide responses

    Directory of Open Access Journals (Sweden)

    Deising Holger B

    2011-01-01

    Full Text Available Abstract Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024 groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide

  7. Serum reactome induced by Bordetella pertussis infection and Pertussis vaccines: qualitative differences in serum antibody recognition patterns revealed by peptide microarray analysis.

    Science.gov (United States)

    Valentini, Davide; Ferrara, Giovanni; Advani, Reza; Hallander, Hans O; Maeurer, Markus J

    2015-07-01

    Pertussis (whooping cough) remains a public health problem despite extensive vaccination strategies. Better understanding of the host-pathogen interaction and the detailed B. pertussis (Bp) target recognition pattern will help in guided vaccine design. We characterized the specific epitope antigen recognition profiles of serum antibodies ('the reactome') induced by whooping cough and B. pertussis (Bp) vaccines from a case-control study conducted in 1996 in infants enrolled in a Bp vaccine trial in Sweden (Gustafsson, NEJM, 1996, 334, 349-355). Sera from children with whooping cough, vaccinated with Diphtheria Tetanus Pertussis (DTP) whole-cell (wc), acellular 5 (DPTa5), or with the 2 component (a2) vaccines and from infants receiving only DT (n=10 for each group) were tested with high-content peptide microarrays containing 17 Bp proteins displayed as linear (n=3175) peptide stretches. Slides were incubated with serum and peptide-IgG complexes detected with Cy5-labeled goat anti-human IgG and analyzed using a GenePix 4000B microarray scanner, followed by statistical analysis, using PAM (Prediction Analysis for Microarrays) and the identification of uniquely recognized peptide epitopes. 367/3,085 (11.9%) peptides were recognized in 10/10 sera from children with whooping cough, 239 (7.7%) in DTPwc, 259 (8.4%) in DTPa5, 105 (3.4%) DTPa2, 179 (5.8%) in the DT groups. Recognition of strongly recognized peptides was similar between whooping cough and DPTwc, but statistically different between whooping cough vs. DTPa5 (p<0.05), DTPa2 and DT (p<0.001 vs. both) vaccines. 6/3,085 and 2/3,085 peptides were exclusively recognized in (10/10) sera from children with whooping cough and DTPa2 vaccination, respectively. DTPwc resembles more closely the whooping cough reactome as compared to acellular vaccines. We could identify a unique recognition signature common for each vaccination group (10/10 children). Peptide microarray technology allows detection of subtle differences in

  8. Classification across gene expression microarray studies

    Directory of Open Access Journals (Sweden)

    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  9. Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

    Science.gov (United States)

    Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

    2017-11-03

    In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

  10. Cyclin D1 and Ewing's sarcoma/PNET: A microarray analysis.

    Science.gov (United States)

    Fagone, Paolo; Nicoletti, Ferdinando; Salvatorelli, Lucia; Musumeci, Giuseppe; Magro, Gaetano

    2015-10-01

    Recent immunohistochemical analyses have showed that cyclin D1 is expressed in soft tissue Ewing's sarcoma/peripheral neuroectodermal tumor (PNET) of childhood and adolescents, while it is undetectable in both embryonal and alveolar rhabdomyosarcoma. In the present paper, microarray analysis provided evidence of a significant upregulation of cyclin D1 in Ewing's sarcoma as compared to normal tissues. In addition, we confirmed our previous findings of a significant over-expression of cyclin D1 in Ewing sarcoma as compared to rhabdomyosarcoma. Bioinformatic analysis also allowed to identify some other genes, strongly correlated to cyclin D1, which, although not previously studied in pediatric tumors, could represent novel markers for the diagnosis and prognosis of Ewing's sarcoma/PNET. The data herein provided support not only the use of cyclin D1 as a diagnostic marker of Ewing sarcoma/PNET but also the possibility of using drugs targeting cyclin D1 as potential therapeutic strategies. Copyright © 2015 Elsevier GmbH. All rights reserved.

  11. Identification of circulating fetal cell markers by microarray analysis

    DEFF Research Database (Denmark)

    Brinch, Marie; Hatt, Lotte; Singh, Ripudaman

    2012-01-01

    identified by XY fluorescence in situ hybridization and confirmed by reverse-color fluorescence in situ hybridization were shot off microscope slides by laser capture microdissection. The expression pattern of a subset of expressed genes was compared between fetal cells and maternal blood cells using stem...

  12. Cell Biochips

    Science.gov (United States)

    Pioufle, B. Le; Picollet-D'Hahan, N.

    A cell biochip is a microsystem, equipped with electronic and microfluidic functions, designed to manipulate or analyse living cells. The first publications in this emerging area of research appeared toward the end of the 1980s. In 1989 Washizu described a biochip designed to fuse two cells by electropermeabilisation of the cytoplasmic membrane [1]. Research centers have devised a whole range of cell chip structures, for simultaneous or sequential analysis of single cells, cell groups, or cell tissues reconstituted on the chip. The cells are arranged in a square array on a parallel cell chip for parallel analysis, while they are examined and processed one by one in a microchannel in the case of a series cell chip. In contrast to these biochips for high-throughput analysis of a large number of cells, single-cell chips focus on the analysis of a single isolated cell. As in DNA microarrays, where a large number of oligonucleotides are ordered in a matrix array, parallel cell chips order living cells in a similar way. At each point of the array, the cells can be isolated, provided that the cell type allows this, e.g., blood cells, or cultivated in groups (most adhesion cells can only survive in groups). The aim is to allow massively parallel analysis or processing. Le Pioufle et al. describe a microdevice for the culture of single cells or small groups of cells in a micropit array [2]. Each pit is equipped to stimulate the cell or group of cells either electrically or fluidically. Among the applications envisaged are gene transfer, cell sorting, and screening in pharmacology. A complementary approach, combining the DNA microarray and cell biochip ideas, has been put forward by Bailey et al. [3]. Genes previously arrayed on the chip transfect the cultured cells on the substrate depending on their position in the array (see Fig. 19.1). This way of achieving differential lipofection on a chip was then taken up again by Yoshikawa et al. [4] with primary cells, more

  13. Exon microarray analysis of human dorsolateral prefrontal cortex in alcoholism.

    Science.gov (United States)

    Manzardo, Ann M; Gunewardena, Sumedha; Wang, Kun; Butler, Merlin G

    2014-06-01

    Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function, and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC; Brodmann area 9) of 7 adult alcoholic (6 males, 1 female, mean age 49 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using quantitative reverse transcription polymerase chain reaction, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN), and signaling (e.g., RASGRP3, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease and development including cellular assembly and organization impacting on psychological disorders. Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation, and signaling that targets white matter of the brain. Copyright © 2014 by the Research Society on Alcoholism.

  14. Performance analysis of clustering techniques over microarray data: A case study

    Science.gov (United States)

    Dash, Rasmita; Misra, Bijan Bihari

    2018-03-01

    Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with this problem a grading approach is introduced over many clustering techniques to identify a stable technique. But the grading approach depends on the characteristic of dataset as well as on the validity indices. So a two stage grading approach is implemented. In this study the grading approach is implemented over five clustering techniques like hybrid swarm based clustering (HSC), k-means, partitioning around medoids (PAM), vector quantization (VQ) and agglomerative nesting (AGNES). The experimentation is conducted over five microarray datasets with seven validity indices. The finding of grading approach that a cluster technique is significant is also established by Nemenyi post-hoc hypothetical test.

  15. Washing scaling of GeneChip microarray expression

    Directory of Open Access Journals (Sweden)

    Krohn Knut

    2010-05-01

    Full Text Available Abstract Background Post-hybridization washing is an essential part of microarray experiments. Both the quality of the experimental washing protocol and adequate consideration of washing in intensity calibration ultimately affect the quality of the expression estimates extracted from the microarray intensities. Results We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM and mismatch (MM probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values. Conclusions Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental

  16. Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

    Energy Technology Data Exchange (ETDEWEB)

    Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

    2012-08-24

    Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

  17. Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

    Energy Technology Data Exchange (ETDEWEB)

    Gardner, S; Jaing, C

    2012-03-27

    The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interim report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.

  18. Transcriptomic Analysis and Meta-Analysis of Human Granulosa and Cumulus Cells.

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    Tanja Burnik Papler

    Full Text Available Specific gene expression in oocytes and its surrounding cumulus (CC and granulosa (GC cells is needed for successful folliculogenesis and oocyte maturation. The aim of the present study was to compare genome-wide gene expression and biological functions of human GC and CC. Individual GC and CC were derived from 37 women undergoing IVF procedures. Gene expression analysis was performed using microarrays, followed by a meta-analysis. Results were validated using quantitative real-time PCR. There were 6029 differentially expressed genes (q < 10-4; of which 650 genes had a log2 FC ≥ 2. After the meta-analysis there were 3156 genes differentially expressed. Among these there were genes that have previously not been reported in human somatic follicular cells, like prokineticin 2 (PROK2, higher expressed in GC, and pregnancy up-regulated nonubiquitous CaM kinase (PNCK, higher expressed in CC. Pathways like inflammatory response and angiogenesis were enriched in GC, whereas in CC, cell differentiation and multicellular organismal development were among enriched pathways. In conclusion, transcriptomes of GC and CC as well as biological functions, are distinctive for each cell subpopulation. By describing novel genes like PROK2 and PNCK, expressed in GC and CC, we upgraded the existing data on human follicular biology.

  19. Microarray-based analysis of plasma cirDNA epigenetic modification profiling in xenografted mice exposed to intermittent hypoxia

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    Rene Cortese

    2015-09-01

    Full Text Available Intermittent hypoxia (IH during sleep is one of the major abnormalities occurring in patients suffering from obstructive sleep apnea (OSA, a highly prevalent disorder affecting 6–15% of the general population, particularly among obese people. IH has been proposed as a major determinant of oncogenetically-related processes such as tumor growth, invasion and metastasis. During the growth and expansion of tumors, fragmented DNA is released into the bloodstream and enters the circulation. Circulating tumor DNA (cirDNA conserves the genetic and epigenetic profiles from the tumor of origin and can be isolated from the plasma fraction. Here we report a microarray-based epigenetic profiling of cirDNA isolated from blood samples of mice engrafted with TC1 epithelial lung cancer cells and controls, which were exposed to IH during sleep (XenoIH group, n = 3 or control conditions, (i.e., room air (RA; XenoRA group, n = 3 conditions. To prepare the targets for microarray hybridization, we applied a previously developed method that enriches the modified fraction of the cirDNA without amplification of genomic DNA. Regions of differential cirDNA modification between the two groups were identified by hybridizing the enriched fractions for each sample to Affymetrix GeneChip Human Promoter Arrays 1.0R. Microarray raw and processed data were deposited in NCBI's Gene Expression Omnibus (GEO database (accession number: GSE61070.

  20. A tiling microarray for global analysis of chloroplast genome expression in cucumber and other plants

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    Pląder Wojciech

    2011-09-01

    Full Text Available Abstract Plastids are small organelles equipped with their own genomes (plastomes. Although these organelles are involved in numerous plant metabolic pathways, current knowledge about the transcriptional activity of plastomes is limited. To solve this problem, we constructed a plastid tiling microarray (PlasTi-microarray consisting of 1629 oligonucleotide probes. The oligonucleotides were designed based on the cucumber chloroplast genomic sequence and targeted both strands of the plastome in a non-contiguous arrangement. Up to 4 specific probes were designed for each gene/exon, and the intergenic regions were covered regularly, with 70-nt intervals. We also developed a protocol for direct chemical labeling and hybridization of as little as 2 micrograms of chloroplast RNA. We used this protocol for profiling the expression of the cucumber chloroplast plastome on the PlasTi-microarray. Owing to the high sequence similarity of plant plastomes, the newly constructed microarray can be used to study plants other than cucumber. Comparative hybridization of chloroplast transcriptomes from cucumber, Arabidopsis, tomato and spinach showed that the PlasTi-microarray is highly versatile.

  1. Transcriptomic analysis of mouse EL4 T cells upon T cell activation and in response to protein synthesis inhibition via cycloheximide treatment.

    Science.gov (United States)

    Lim, Pek Siew; Hardy, Kristine; Peng, Kaiman; Shannon, Frances M

    2016-03-01

    T cell activation involves the recognition of a foreign antigen complexed to the major histocompatibility complex on the antigen presenting T cell to the T cell receptor. This leads to activation of signaling pathways, which ultimately leads to induction of key cytokine genes responsible for eradication of foreign antigens. We used the mouse EL4 T cell as a model system to study genes that are induced as a result of T cell activation using phorbol myristate acetate (PMA) and calcium ionomycin (I) as stimuli. We were also interested to examine the importance of new protein synthesis in regulating the expression of genes involved in T cell activation. Thus we have pre-treated mouse EL4 T cells with cycloheximide, a protein synthesis inhibitor, and left the cells unstimulated or stimulated with PMA/I for 4 h. We performed microarray expression profiling of these cells to correlate the gene expression with chromatin state of T cells upon T cell activation [1]. Here, we detail further information and analysis of the microarray data, which shows that T cell activation leads to differential expression of genes and inducible genes can be further classified as primary and secondary response genes based on their protein synthesis dependency. The data is available in the Gene Expression Omnibus under accession number GSE13278.

  2. Chromosomal microarrays testing in children with developmental disabilities and congenital anomalies

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    Guillermo Lay-Son

    2015-04-01

    Full Text Available OBJECTIVES: Clinical use of microarray-based techniques for the analysis of many developmental disorders has emerged during the last decade. Thus, chromosomal microarray has been positioned as a first-tier test. This study reports the first experience in a Chilean cohort. METHODS: Chilean patients with developmental disabilities and congenital anomalies were studied with a high-density microarray (CytoScan(tm HD Array, Affymetrix, Inc., Santa Clara, CA, USA. Patients had previous cytogenetic studies with either a normal result or a poorly characterized anomaly. RESULTS: This study tested 40 patients selected by two or more criteria, including: major congenital anomalies, facial dysmorphism, developmental delay, and intellectual disability. Copy number variants (CNVs were found in 72.5% of patients, while a pathogenic CNV was found in 25% of patients and a CNV of uncertain clinical significance was found in 2.5% of patients. CONCLUSION: Chromosomal microarray analysis is a useful and powerful tool for diagnosis of developmental diseases, by allowing accurate diagnosis, improving the diagnosis rate, and discovering new etiologies. The higher cost is a limitation for widespread use in this setting.

  3. Microarray mRNA expression analysis of Fanconi anemia fibroblasts.

    Science.gov (United States)

    Galetzka, D; Weis, E; Rittner, G; Schindler, D; Haaf, T

    2008-01-01

    Fanconi anemia (FA) cells are generally hypersensitive to DNA cross-linking agents, implying that mutations in the different FANC genes cause a similar DNA repair defect(s). By using a customized cDNA microarray chip for DNA repair- and cell cycle-associated genes, we identified three genes, cathepsin B (CTSB), glutaredoxin (GLRX), and polo-like kinase 2 (PLK2), that were misregulated in untreated primary fibroblasts from three unrelated FA-D2 patients, compared to six controls. Quantitative real-time RT PCR was used to validate these results and to study possible molecular links between FA-D2 and other FA subtypes. GLRX was misregulated to opposite directions in a variety of different FA subtypes. Increased CTSB and decreased PLK2 expression was found in all or almost all of the analyzed complementation groups and, therefore, may be related to the defective FA pathway. Transcriptional upregulation of the CTSB proteinase appears to be a secondary phenomenon due to proliferation differences between FA and normal fibroblast cultures. In contrast, PLK2 is known to play a pivotal role in processes that are linked to FA defects and may contribute in multiple ways to the FA phenotype: PLK2 is a target gene for TP53, is likely to function as a tumor suppressor gene in hematologic neoplasia, and Plk2(-/-) mice are small because of defective embryonal development. (c) 2008 S. Karger AG, Basel.

  4. Comparative analysis of human conjunctival and corneal epithelial gene expression with oligonucleotide microarrays.

    Science.gov (United States)

    Turner, Helen C; Budak, Murat T; Akinci, M A Murat; Wolosin, J Mario

    2007-05-01

    To determine global mRNA expression levels in corneal and conjunctival epithelia and identify transcripts that exhibit preferential tissue expression. cDNA samples derived from human conjunctival and corneal epithelia were hybridized in three independent experiments to a commercial oligonucleotide array representing more than 22,000 transcripts. The resultant signal intensities and microarray software transcript present/absent calls were used in conjunction with the local pooled error (LPE) statistical method to identify transcripts that are preferentially or exclusively expressed in one of the two tissues at significant levels (expression >1% of the beta-actin level). EASE (Expression Analysis Systematic Explorer software) was used to identify biological systems comparatively overrepresented in either epithelium. Immuno-, and cytohistochemistry was performed to validate or expand on selected results of interest. The analysis identified 332 preferential and 93 exclusive significant corneal epithelial transcripts. The corresponding numbers of conjunctival epithelium transcripts were 592 and 211, respectively. The overrepresented biological processes in the cornea were related to cell adhesion and oxiredox equilibria and cytoprotection activities. In the conjunctiva, the biological processes that were most prominent were related to innate immunity and melanogenesis. Immunohistochemistry for antigen-presenting cells and melanocytes was consistent with these gene signatures. The transcript comparison identified a substantial number of genes that have either not been identified previously or are not known to be highly expressed in these two epithelia, including testican-1, ECM1, formin, CRTAC1, and NQO1 in the cornea and, in the conjunctiva, sPLA(2)-IIA, lipocalin 2, IGFBP3, multiple MCH class II proteins, and the Na-Pi cotransporter type IIb. Comparative gene expression profiling leads to the identification of many biological processes and previously unknown genes that

  5. Application of fluorescent monocytes for probing immune complexes on antigen microarrays.

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    Zoltán Szittner

    Full Text Available Microarrayed antigens are used for identifying serum antibodies with given specificities and for generating binding profiles. Antibodies bind to these arrayed antigens forming immune complexes and are conventionally identified by secondary labelled antibodies.In the body immune complexes are identified by bone marrow derived phagocytic cells, such as monocytes. In our work we were looking into the possibility of replacing secondary antibodies with monocytoid cells for the generation of antibody profiles. Using the human monocytoid cell line U937, which expresses cell surface receptors for immune complex components, we show that cell adhesion is completely dependent on the interaction of IgG heavy chains and Fcγ receptors, and this recognition is susceptible to differences between heavy chain structures and their glycosylation. We also report data on a possible application of this system in autoimmune diagnostics.Compared to secondary antibodies, fluorescent monocytesas biosensors are superior in reflecting biological functions of microarray-bound antibodies and represent an easy and robust alternative for profiling interactions between serum proteins and antigens.

  6. Transcriptional profiling of MEF2-regulated genes in human neural progenitor cells derived from embryonic stem cells

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    Shing Fai Chan

    2015-03-01

    Full Text Available The myocyte enhancer factor 2 (MEF2 family of transcription factors is highly expressed in the brain and constitutes a key determinant of neuronal survival, differentiation, and synaptic plasticity. However, genome-wide transcriptional profiling of MEF2-regulated genes has not yet been fully elucidated, particularly at the neural stem cell stage. Here we report the results of microarray analysis comparing mRNAs isolated from human neural progenitor/stem cells (hNPCs derived from embryonic stem cells expressing a control vector versus progenitors expressing a constitutively-active form of MEF2 (MEF2CA, which increases MEF2 activity. Microarray experiments were performed using the Illumina Human HT-12 V4.0 expression beadchip (GEO#: GSE57184. By comparing vector-control cells to MEF2CA cells, microarray analysis identified 1880 unique genes that were differentially expressed. Among these genes, 1121 genes were up-regulated and 759 genes were down-regulated. Our results provide a valuable resource for identifying transcriptional targets of MEF2 in hNPCs.

  7. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

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    Pistoia Vito

    2008-10-01

    Full Text Available Abstract Background Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to environmental stimuli. In such studies, genes showing similar mean expression values between two or more groups are considered as not differentially expressed, even if hidden subclasses with different expression values may exist. In this paper we propose a new method for identifying differentially expressed genes, based on the area between the ROC curve and the rising diagonal (ABCR. ABCR represents a more general approach than the standard area under the ROC curve (AUC, because it can identify both proper (i.e., concave and not proper ROC curves (NPRC. In particular, NPRC may correspond to those genes that tend to escape standard selection methods. Results We assessed the performance of our method using data from a publicly available database of 4026 genes, including 14 normal B cell samples (NBC and 20 heterogeneous lymphomas (namely: 9 follicular lymphomas and 11 chronic lymphocytic leukemias. Moreover, NBC also included two sub-classes, i.e., 6 heavily stimulated and 8 slightly or not stimulated samples. We identified 1607 differentially expressed genes with an estimated False Discovery Rate of 15%. Among them, 16 corresponded to NPRC and all escaped standard selection procedures based on AUC and t statistics. Moreover, a simple inspection to the shape of such plots allowed to identify the two subclasses in either one class in 13 cases (81%. Conclusion NPRC represent a new useful tool for the analysis of microarray data.

  8. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

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    E. V. Thomas

    2009-01-01

    Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

  9. A Parallel Software Pipeline for DMET Microarray Genotyping Data Analysis

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    Giuseppe Agapito

    2018-06-01

    Full Text Available Personalized medicine is an aspect of the P4 medicine (predictive, preventive, personalized and participatory based precisely on the customization of all medical characters of each subject. In personalized medicine, the development of medical treatments and drugs is tailored to the individual characteristics and needs of each subject, according to the study of diseases at different scales from genotype to phenotype scale. To make concrete the goal of personalized medicine, it is necessary to employ high-throughput methodologies such as Next Generation Sequencing (NGS, Genome-Wide Association Studies (GWAS, Mass Spectrometry or Microarrays, that are able to investigate a single disease from a broader perspective. A side effect of high-throughput methodologies is the massive amount of data produced for each single experiment, that poses several challenges (e.g., high execution time and required memory to bioinformatic software. Thus a main requirement of modern bioinformatic softwares, is the use of good software engineering methods and efficient programming techniques, able to face those challenges, that include the use of parallel programming and efficient and compact data structures. This paper presents the design and the experimentation of a comprehensive software pipeline, named microPipe, for the preprocessing, annotation and analysis of microarray-based Single Nucleotide Polymorphism (SNP genotyping data. A use case in pharmacogenomics is presented. The main advantages of using microPipe are: the reduction of errors that may happen when trying to make data compatible among different tools; the possibility to analyze in parallel huge datasets; the easy annotation and integration of data. microPipe is available under Creative Commons license, and is freely downloadable for academic and not-for-profit institutions.

  10. Analysis of gene expression data from non-small cell lung carcinoma cell lines reveals distinct sub-classes from those identified at the phenotype level.

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    Andrew R Dalby

    Full Text Available Microarray data from cell lines of Non-Small Cell Lung Carcinoma (NSCLC can be used to look for differences in gene expression between the cell lines derived from different tumour samples, and to investigate if these differences can be used to cluster the cell lines into distinct groups. Dividing the cell lines into classes can help to improve diagnosis and the development of screens for new drug candidates. The micro-array data is first subjected to quality control analysis and then subsequently normalised using three alternate methods to reduce the chances of differences being artefacts resulting from the normalisation process. The final clustering into sub-classes was carried out in a conservative manner such that sub-classes were consistent across all three normalisation methods. If there is structure in the cell line population it was expected that this would agree with histological classifications, but this was not found to be the case. To check the biological consistency of the sub-classes the set of most strongly differentially expressed genes was be identified for each pair of clusters to check if the genes that most strongly define sub-classes have biological functions consistent with NSCLC.

  11. Nonlinear matching measure for the analysis of on-off type DNA microarray images

    Science.gov (United States)

    Kim, Jong D.; Park, Misun; Kim, Jongwon

    2003-07-01

    In this paper, we propose a new nonlinear matching measure for automatic analysis of the on-off type DNA microarray images in which the hybridized spots are detected by the template matching method. The targeting spots of HPV DNA chips are designed for genotyping the human papilloma virus(HPV). The proposed measure is obtained by binarythresholding over the whole template region and taking the number of white pixels inside the spotted area. This measure is evaluated in terms of the accuracy of the estimated marker location to show better performance than the normalized covariance.

  12. MICROARRAY IMAGE GRIDDING USING GRID LINE REFINEMENT TECHNIQUE

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    V.G. Biju

    2015-05-01

    Full Text Available An important stage in microarray image analysis is gridding. Microarray image gridding is done to locate sub arrays in a microarray image and find co-ordinates of spots within each sub array. For accurate identification of spots, most of the proposed gridding methods require human intervention. In this paper a fully automatic gridding method which enhances spot intensity in the preprocessing step as per a histogram based threshold method is used. The gridding step finds co-ordinates of spots from horizontal and vertical profile of the image. To correct errors due to the grid line placement, a grid line refinement technique is proposed. The algorithm is applied on different image databases and results are compared based on spot detection accuracy and time. An average spot detection accuracy of 95.06% depicts the proposed method’s flexibility and accuracy in finding the spot co-ordinates for different database images.

  13. Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France

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    Linda K. Medlin

    2013-03-01

    Full Text Available Harmful algal blooms (HABs occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae—an FP7-funded EU project—used rRNA genes (SSU and LSU as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR and compared with an enzyme-linked immunosorbent assay (ELISA. In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3 and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts.

  14. Understanding plant cell-wall remodelling during the symbiotic interaction between Tuber melanosporum and Corylus avellana using a carbohydrate microarray

    DEFF Research Database (Denmark)

    Sillo, Fabiano; Fangel, Jonatan Ulrik; Henrissat, Bernard

    2016-01-01

    . An important feature of these interactions concerns changes in the cell-wall composition during interaction with other organisms. In ectomycorrhizae, plant and fungal cell walls come into direct contact, and represent the interface between the two partners. However, very little information is available...... on the re-arrangement that could occur within the plant and fungal cell walls during ectomycorrhizal symbiosis. Taking advantage of the Comprehensive Microarray Polymer Profiling (CoMPP) technology, the current study has had the aim of monitoring the changes that take place in the plant cell wall in Corylus...

  15. Xylella fastidiosa gene expression analysis by DNA microarrays

    OpenAIRE

    Travensolo,Regiane F.; Carareto-Alves,Lucia M.; Costa,Maria V.C.G.; Lopes,Tiago J.S.; Carrilho,Emanuel; Lemos,Eliana G.M.

    2009-01-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcrip...

  16. The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

    Science.gov (United States)

    van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.

    2015-01-01

    Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674

  17. Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes

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    Elvezia Maria Paraboschi

    2015-09-01

    Full Text Available Abnormalities in RNA metabolism and alternative splicing (AS are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls, followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p = 0.0015 by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

  18. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

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    Viti Federica

    2008-04-01

    Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

  19. Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

    Science.gov (United States)

    Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

    2013-01-01

    DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

  20. Microarray-based method for the parallel analysis of genotypes and expression profiles of wood-forming tissues in Eucalyptus grandis

    CSIR Research Space (South Africa)

    Barros, E

    2009-05-01

    Full Text Available of Eucalyptus grandis planting stock that exhibit preferred wood qualities is thus a priority of the South African forestry industry. The researchers used microarray-based DNA-amplified fragment length polymorphism (AFLP) analysis in combination with expression...

  1. Transcription analysis of apple fruit development using cDNA microarrays

    NARCIS (Netherlands)

    Soglio, V.; Costa, F.; Molthoff, J.W.; Weemen-Hendriks, M.; Schouten, H.J.; Gianfranceschi, L.

    2009-01-01

    The knowledge of the molecular mechanisms underlying fruit quality traits is fundamental to devise efficient marker-assisted selection strategies and to improve apple breeding. In this study, cDNA microarray technology was used to identify genes whose expression changes during fruit development and

  2. Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

    Science.gov (United States)

    The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

  3. Microarray analysis of early adipogenesis in C3H10T1/2 cells: Cooperative inhibitory effects of growth factors and 2,3,7,8-tetrachlorodibenzo-p-dioxin

    International Nuclear Information System (INIS)

    Hanlon, Paul R.; Cimafranca, Melissa A.; Liu Xueqing; Cho, Young C.; Jefcoate, Colin R.

    2005-01-01

    C3H10T1/2 mouse embryo fibroblasts differentiate into adipocytes when stimulated by a standard hormonal mixture (IDMB). 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), via the aryl hydrocarbon receptor (AhR), inhibits induction of the key adipogenic gene peroxisome proliferator-activated receptor γ (PPARγ) and subsequent adipogenesis. This TCDD-mediated inhibition requires activation of the extracellular signal-regulated kinase (ERK) pathway, which can be accomplished by serum, epidermal growth factor (EGF), or fibroblast growth factor (FGF). In the absence of serum or growth factors, IDMB induced adipogenesis without mitosis. Microarray analysis identified 200 genes that exhibited expression changes of at least twofold after 24 h of IDMB treatment. This time precedes most PPARγ stimulation but follows the period of TCDD/ERK cooperation and periods of increased cell contraction and DNA synthesis. Functionally related gene clusters include genes associated with cell structure, triglyceride and cholesterol metabolism, oxidative regulation, and secreted proteins. In the absence of growth factors TCDD inhibited 30% of these IDMB responses without inhibiting the process of differentiation. A combination of EGF and TCDD that blocks differentiation cooperatively blocked a further 44 IDMB-responsive genes, most of which have functional links to differentiation, including PPARγ. Cell cycle regulators that are stimulated by EGF were substantially inhibited by IDMB but these responses were unaffected by TCDD. By contrast, TCDD and EGF cooperatively reversed IDMB-induced changes in cell adhesion complexes immediately prior to increases in PPARγ1 expression. Changes in adhesion-linked signaling may play a key role in TCDD affects on differentiation

  4. Carbon ion irradiation of the human prostate cancer cell line PC3: A whole genome microarray study

    Science.gov (United States)

    SUETENS, ANNELIES; MOREELS, MARJAN; QUINTENS, ROEL; CHIRIOTTI, SABINA; TABURY, KEVIN; MICHAUX, ARLETTE; GRÉGOIRE, VINCENT; BAATOUT, SARAH

    2014-01-01

    Hadrontherapy is a form of external radiation therapy, which uses beams of charged particles such as carbon ions. Compared to conventional radiotherapy with photons, the main advantage of carbon ion therapy is the precise dose localization along with an increased biological effectiveness. The first results obtained from prostate cancer patients treated with carbon ion therapy showed good local tumor control and survival rates. In view of this advanced treatment modality we investigated the effects of irradiation with different beam qualities on gene expression changes in the PC3 prostate adenocarcinoma cell line. For this purpose, PC3 cells were irradiated with various doses (0.0, 0.5 and 2.0 Gy) of carbon ions (LET=33.7 keV/μm) at the beam of the Grand Accélérateur National d’Ions Lourds (Caen, France). Comparative experiments with X-rays were performed at the Belgian Nuclear Research Centre. Genome-wide gene expression was analyzed using microarrays. Our results show a downregulation in many genes involved in cell cycle and cell organization processes after 2.0 Gy irradiation. This effect was more pronounced after carbon ion irradiation compared with X-rays. Furthermore, we found a significant downregulation of many genes related to cell motility. Several of these changes were confirmed using qPCR. In addition, recurrence-free survival analysis of prostate cancer patients based on one of these motility genes (FN1) revealed that patients with low expression levels had a prolonged recurrence-free survival time, indicating that this gene may be a potential prognostic biomarker for prostate cancer. Understanding how different radiation qualities affect the cellular behavior of prostate cancer cells is important to improve the clinical outcome of cancer radiation therapy. PMID:24504141

  5. Microarray data analyses of yeast RNA Pol I subunit RPA12 deletion strain

    Directory of Open Access Journals (Sweden)

    Kamlesh Kumar Yadav

    2016-06-01

    Full Text Available The ribosomal RNA (rRNA biosynthesis is the most energy consuming process in all living cells and the majority of total transcription activity is dedicated for synthesizing rRNA. The cells may adjust the synthesis of rRNA with the availability of resources. rRNA is mainly synthesized by RNA polymerase I that is composed of 14 subunits. Deletion of RPA12, 14, 39 and 49 are viable. RPA12 is a very small protein (13.6 kDa, and the amount of protein in the cells is very high (12,000 molecules per cell, but the role of this protein is unknown in other cellular metabolic processes (Kulak et al., 2014 [1]. RPA12 consists of two zinc-binding domains and it is required for the termination of rRNA synthesis (Mullem et al., 2002 [2]. Deletions of RPA12 in Saccharomyces cerevisiae and Schizosaccharomyces pombe cause a conditional growth defect (Nogi et al., 1993 [3]. In S. pombe, C-terminal deletion behaves like wild-type (Imazawa et al., 2001 [4]. This prompted us to investigate in detail the physiological role of RPA12 in S. cerevisiae, we performed the microarray of rpa12∆ strain and deposited into Gene Expression Omnibus under GSE68731. The analysis of microarray data revealed that the expression of major cellular metabolism genes is high. The amino acid biosynthesis, nonpolar lipid biosynthesis and glucose metabolic genes are highly expressed. The analyses also revealed that the rpa12∆ cells have an uncontrolled synthesis of cell metabolites, so RPA12 could be a master regulator for whole cellular metabolism.

  6. Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

    Science.gov (United States)

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

    2015-10-06

    Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

  7. Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

    Science.gov (United States)

    Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.

    2013-01-01

    While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185

  8. Translating microarray data for diagnostic testing in childhood leukaemia

    International Nuclear Information System (INIS)

    Hoffmann, Katrin; Firth, Martin J; Beesley, Alex H; Klerk, Nicholas H de; Kees, Ursula R

    2006-01-01

    Recent findings from microarray studies have raised the prospect of a standardized diagnostic gene expression platform to enhance accurate diagnosis and risk stratification in paediatric acute lymphoblastic leukaemia (ALL). However, the robustness as well as the format for such a diagnostic test remains to be determined. As a step towards clinical application of these findings, we have systematically analyzed a published ALL microarray data set using Robust Multi-array Analysis (RMA) and Random Forest (RF). We examined published microarray data from 104 ALL patients specimens, that represent six different subgroups defined by cytogenetic features and immunophenotypes. Using the decision-tree based supervised learning algorithm Random Forest (RF), we determined a small set of genes for optimal subgroup distinction and subsequently validated their predictive power in an independent patient cohort. We achieved very high overall ALL subgroup prediction accuracies of about 98%, and were able to verify the robustness of these genes in an independent panel of 68 specimens obtained from a different institution and processed in a different laboratory. Our study established that the selection of discriminating genes is strongly dependent on the analysis method. This may have profound implications for clinical use, particularly when the classifier is reduced to a small set of genes. We have demonstrated that as few as 26 genes yield accurate class prediction and importantly, almost 70% of these genes have not been previously identified as essential for class distinction of the six ALL subgroups. Our finding supports the feasibility of qRT-PCR technology for standardized diagnostic testing in paediatric ALL and should, in conjunction with conventional cytogenetics lead to a more accurate classification of the disease. In addition, we have demonstrated that microarray findings from one study can be confirmed in an independent study, using an entirely independent patient cohort

  9. Vaccine-induced modulation of gene expression in turbot peritoneal cells. A microarray approach.

    Science.gov (United States)

    Fontenla, Francisco; Blanco-Abad, Verónica; Pardo, Belén G; Folgueira, Iria; Noia, Manuel; Gómez-Tato, Antonio; Martínez, Paulino; Leiro, José M; Lamas, Jesús

    2016-07-01

    We used a microarray approach to examine changes in gene expression in turbot peritoneal cells after injection of the fish with vaccines containing the ciliate parasite Philasterides dicentrarchi as antigen and one of the following adjuvants: chitosan-PVMMA microspheres, Freund́s complete adjuvant, aluminium hydroxide gel or Matrix-Q (Isconova, Sweden). We identified 374 genes that were differentially expressed in all groups of fish. Forty-two genes related to tight junctions and focal adhesions and/or actin cytoskeleton were differentially expressed in free peritoneal cells. The profound changes in gene expression related to cell adherence and cytoskeleton may be associated with cell migration and also with the formation of cell-vaccine masses and their attachment to the peritoneal wall. Thirty-five genes related to apoptosis were differentially expressed. Although most of the proteins coded by these genes have a proapoptotic effect, others are antiapoptotic, indicating that both types of signals occur in peritoneal leukocytes of vaccinated fish. Interestingly, many of the genes related to lymphocytes and lymphocyte activity were downregulated in the groups injected with vaccine. We also observed decreased expression of genes related to antigen presentation, suggesting that macrophages (which were abundant in the peritoneal cavity after vaccination) did not express these during the early inflammatory response in the peritoneal cavity. Finally, several genes that participate in the inflammatory response were differentially expressed, and most participated in resolution of inflammation, indicating that an M2 macrophage response is generated in the peritoneal cavity of fish one day post vaccination. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Development and application of an oligonucleotide microarray and real-time quantitative PCR for detection of wastewater bacterial pathogens

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Dae-Young [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada)], E-mail: daeyoung.lee@ec.gc.ca; Lauder, Heather; Cruwys, Heather; Falletta, Patricia [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada); Beaudette, Lee A. [Environmental Science and Technology Centre, Environment Canada, 335 River Road South, Ottawa, Ontario, K1A 0H3 (Canada)], E-mail: lee.beaudette@ec.gc.ca

    2008-07-15

    Conventional microbial water quality test methods are well known for their technical limitations, such as lack of direct pathogen detection capacity and low throughput capability. The microarray assay has recently emerged as a promising alternative for environmental pathogen monitoring. In this study, bacterial pathogens were detected in municipal wastewater using a microarray equipped with short oligonucleotide probes targeting 16S rRNA sequences. To date, 62 probes have been designed against 38 species, 4 genera, and 1 family of pathogens. The detection sensitivity of the microarray for a waterborne pathogen Aeromonas hydrophila was determined to be approximately 1.0% of the total DNA, or approximately 10{sup 3}A. hydrophila cells per sample. The efficacy of the DNA microarray was verified in a parallel study where pathogen genes and E. coli cells were enumerated using real-time quantitative PCR (qPCR) and standard membrane filter techniques, respectively. The microarray and qPCR successfully detected multiple wastewater pathogen species at different stages of the disinfection process (i.e. secondary effluents vs. disinfected final effluents) and at two treatment plants employing different disinfection methods (i.e. chlorination vs. UV irradiation). This result demonstrates the effectiveness of the DNA microarray as a semi-quantitative, high throughput pathogen monitoring tool for municipal wastewater.

  11. Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

    Directory of Open Access Journals (Sweden)

    Gravelat Fabrice

    2010-09-01

    Full Text Available Abstract Background Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. Results First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality can be used to study a complex environment efficiently. Conclusions We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments

  12. Xylella fastidiosa gene expression analysis by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Regiane F. Travensolo

    2009-01-01

    Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

  13. 16S rRNA based microarray analysis of ten periodontal bacteria in patients with different forms of periodontitis.

    Science.gov (United States)

    Topcuoglu, Nursen; Kulekci, Guven

    2015-10-01

    DNA microarray analysis is a computer based technology, that a reverse capture, which targets 10 periodontal bacteria (ParoCheck) is available for rapid semi-quantitative determination. The aim of this three-year retrospective study was to display the microarray analysis results for the subgingival biofilm samples taken from patient cases diagnosed with different forms of periodontitis. A total of 84 patients with generalized aggressive periodontitis (GAP,n:29), generalized chronic periodontitis (GCP, n:25), peri-implantitis (PI,n:14), localized aggressive periodontitis (LAP,n:8) and refractory chronic periodontitis (RP,n:8) were consecutively selected from the archives of the Oral Microbiological Diagnostic Laboratory. The subgingival biofilm samples were analyzed by the microarray-based identification of 10 selected species. All the tested species were detected in the samples. The red complex bacteria were the most prevalent with very high levels in all groups. Fusobacterium nucleatum was detected in all samples at high levels. The green and blue complex bacteria were less prevalent compared with red and orange complex, except Aggregatibacter actinomycetemcomitas was detected in all LAP group. Positive correlations were found within all the red complex bacteria and between red and orange complex bacteria especially in GCP and GAP groups. Parocheck enables to monitoring of periodontal pathogens in all forms of periodontal disease and can be alternative to other guiding and reliable microbiologic tests. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. A Lateral Flow Protein Microarray for Rapid and Sensitive Antibody Assays

    Directory of Open Access Journals (Sweden)

    Helene Andersson-Svahn

    2011-11-01

    Full Text Available Protein microarrays are useful tools for highly multiplexed determination of presence or levels of clinically relevant biomarkers in human tissues and biofluids. However, such tools have thus far been restricted to laboratory environments. Here, we present a novel 384-plexed easy to use lateral flow protein microarray device capable of sensitive (< 30 ng/mL determination of antigen-specific antibodies in ten minutes of total assay time. Results were developed with gold nanobeads and could be recorded by a cell-phone camera or table top scanner. Excellent accuracy with an area under curve (AUC of 98% was achieved in comparison with an established glass microarray assay for 26 antigen-specific antibodies. We propose that the presented framework could find use in convenient and cost-efficient quality control of antibody production, as well as in providing a platform for multiplexed affinity-based assays in low-resource or mobile settings.

  15. Microfluidic extraction and microarray detection of biomarkers from cancer tissue slides

    Science.gov (United States)

    Nguyen, H. T.; Dupont, L. N.; Jean, A. M.; Géhin, T.; Chevolot, Y.; Laurenceau, E.; Gijs, M. A. M.

    2018-03-01

    We report here a new microfluidic method allowing for the quantification of human epidermal growth factor receptor 2 (HER2) expression levels from formalin-fixed breast cancer tissues. After partial extraction of proteins from the tissue slide, the extract is routed to an antibody (Ab) microarray for HER2 titration by fluorescence. Then the HER2-expressing cell area is evaluated by immunofluorescence (IF) staining of the tissue slide and used to normalize the fluorescent HER2 signal measured from the Ab microarray. The number of HER2 gene copies measured by fluorescence in situ hybridization (FISH) on an adjacent tissue slide is concordant with the normalized HER2 expression signal. This work is the first study implementing biomarker extraction and detection from cancer tissue slides using microfluidics in combination with a microarray system, paving the way for further developments towards multiplex and precise quantification of cancer biomarkers.

  16. Autoantibody profiling on human proteome microarray for biomarker discovery in cerebrospinal fluid and sera of neuropsychiatric lupus.

    Directory of Open Access Journals (Sweden)

    Chaojun Hu

    Full Text Available Autoantibodies in cerebrospinal fluid (CSF from patients with neuropsychiatric systemic lupus erythematosus (NPSLE may be potential biomarkers for prediction, diagnosis, or prognosis of NPSLE. We used a human proteome microarray with~17,000 unique full-length human proteins to investigate autoantibodies associated with NPSLE. Twenty-nine CSF specimens from 12 NPSLE, 7 non-NPSLE, and 10 control (non-systemic lupus erythematosuspatients were screened for NPSLE-associated autoantibodies with proteome microarrays. A focused autoantigen microarray of candidate NPSLE autoantigens was applied to profile a larger cohort of CSF with patient-matched sera. We identified 137 autoantigens associated with NPSLE. Ingenuity Pathway Analysis revealed that these autoantigens were enriched for functions involved in neurological diseases (score = 43.Anti-proliferating cell nuclear antigen (PCNA was found in the CSF of NPSLE and non-NPSLE patients. The positive rates of 4 autoantibodies in CSF specimens were significantly different between the SLE (i.e., NPSLE and non-NPSLE and control groups: anti-ribosomal protein RPLP0, anti-RPLP1, anti-RPLP2, and anti-TROVE2 (also known as anti-Ro/SS-A. The positive rate for anti-SS-A associated with NPSLE was higher than that for non-NPSLE (31.11% cf. 10.71%; P = 0.045.Further analysis showed that anti-SS-A in CSF specimens was related to neuropsychiatric syndromes of the central nervous system in SLE (P = 0.009. Analysis with Spearman's rank correlation coefficient indicated that the titers of anti-RPLP2 and anti-SS-A in paired CSF and serum specimens significantly correlated. Human proteome microarrays offer a powerful platform to discover novel autoantibodies in CSF samples. Anti-SS-A autoantibodies may be potential CSF markers for NPSLE.

  17. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

    Science.gov (United States)

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (psunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.

  18. Using microarray analysis as a prognostic and predictive tool in oncology: focus on breast cancer and normal tissue toxicity

    NARCIS (Netherlands)

    Nuyten, Dimitry S. A.; van de Vijver, Marc J.

    2008-01-01

    Microarray analysis makes it possible to study the expression levels of tens of thousands of genes in one single experiment and is widely available for research purposes. Gene expression profiling is currently being used in many research projects aimed at identifying gene expression signatures in

  19. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  20. DNA microarrays : a molecular cloning manual

    National Research Council Canada - National Science Library

    Sambrook, Joseph; Bowtell, David

    2002-01-01

    .... DNA Microarrays provides authoritative, detailed instruction on the design, construction, and applications of microarrays, as well as comprehensive descriptions of the software tools and strategies...

  1. Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays.

    Science.gov (United States)

    Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter

    2017-01-17

    Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing - enlisting help from the public - is a sufficiently accurate method to score such samples. We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers - bladder/ki67, lung/EGFR, and oesophageal/CD8 - to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains.

  2. GeneAnalytics: An Integrative Gene Set Analysis Tool for Next Generation Sequencing, RNAseq and Microarray Data.

    Science.gov (United States)

    Ben-Ari Fuchs, Shani; Lieder, Iris; Stelzer, Gil; Mazor, Yaron; Buzhor, Ella; Kaplan, Sergey; Bogoch, Yoel; Plaschkes, Inbar; Shitrit, Alina; Rappaport, Noa; Kohn, Asher; Edgar, Ron; Shenhav, Liraz; Safran, Marilyn; Lancet, Doron; Guan-Golan, Yaron; Warshawsky, David; Shtrichman, Ronit

    2016-03-01

    Postgenomics data are produced in large volumes by life sciences and clinical applications of novel omics diagnostics and therapeutics for precision medicine. To move from "data-to-knowledge-to-innovation," a crucial missing step in the current era is, however, our limited understanding of biological and clinical contexts associated with data. Prominent among the emerging remedies to this challenge are the gene set enrichment tools. This study reports on GeneAnalytics™ ( geneanalytics.genecards.org ), a comprehensive and easy-to-apply gene set analysis tool for rapid contextualization of expression patterns and functional signatures embedded in the postgenomics Big Data domains, such as Next Generation Sequencing (NGS), RNAseq, and microarray experiments. GeneAnalytics' differentiating features include in-depth evidence-based scoring algorithms, an intuitive user interface and proprietary unified data. GeneAnalytics employs the LifeMap Science's GeneCards suite, including the GeneCards®--the human gene database; the MalaCards-the human diseases database; and the PathCards--the biological pathways database. Expression-based analysis in GeneAnalytics relies on the LifeMap Discovery®--the embryonic development and stem cells database, which includes manually curated expression data for normal and diseased tissues, enabling advanced matching algorithm for gene-tissue association. This assists in evaluating differentiation protocols and discovering biomarkers for tissues and cells. Results are directly linked to gene, disease, or cell "cards" in the GeneCards suite. Future developments aim to enhance the GeneAnalytics algorithm as well as visualizations, employing varied graphical display items. Such attributes make GeneAnalytics a broadly applicable postgenomics data analyses and interpretation tool for translation of data to knowledge-based innovation in various Big Data fields such as precision medicine, ecogenomics, nutrigenomics, pharmacogenomics, vaccinomics

  3. Different responsiveness to a high-fat/cholesterol diet in two inbred mice and underlying genetic factors: a whole genome microarray analysis

    Directory of Open Access Journals (Sweden)

    Jin Gang

    2009-10-01

    Full Text Available Abstract Background To investigate different responses to a high-fat/cholesterol diet and uncover their underlying genetic factors between C57BL/6J (B6 and DBA/2J (D2 inbred mice. Methods B6 and D2 mice were fed a high-fat/cholesterol diet for a series of time-points. Serum and bile lipid profiles, bile acid yields, hepatic apoptosis, gallstones and atherosclerosis formation were measured. Furthermore, a whole genome microarray was performed to screen hepatic genes expression profile. Quantitative real-time PCR, western blot and TUNEL assay were conducted to validate microarray data. Results After fed the high-fat/cholesterol diet, serum and bile total cholesterol, serum cholesterol esters, HDL cholesterol and Non-HDL cholesterol levels were altered in B6 but not significantly changed in D2; meanwhile, biliary bile acid was decreased in B6 but increased in D2. At the same time, hepatic apoptosis, gallstones and atherosclerotic lesions occurred in B6 but not in D2. The hepatic microarray analysis revealed distinctly different genes expression patterns between B6 and D2 mice. Their functional pathway groups included lipid metabolism, oxidative stress, immune/inflammation response and apoptosis. Quantitative real time PCR, TUNEL assay and western-blot results were consistent with microarray analysis. Conclusion Different genes expression patterns between B6 and D2 mice might provide a genetic basis for their distinctive responses to a high-fat/cholesterol diet, and give us an opportunity to identify novel pharmaceutical targets in related diseases in the future.

  4. Overexpression of Periostin and Lumican in Esophageal Squamous Cell Carcinoma

    International Nuclear Information System (INIS)

    Kashyap, Manoj Kumar; Marimuthu, Arivusudar; Peri, Suraj; Kumar, Ghantasala S. Sameer; Jacob, Harrys K.C.; Prasad, Thottethodi Subrahmanya Keshava; Mahmood, Riaz; Kumar, K. V. Veerendra; Kumar, M. Vijaya; Meltzer, Stephen J.; Montgomery, Elizabeth A.; Kumar, Rekha V.; Pandey, Akhilesh

    2010-01-01

    To identify biomarkers for early detection for esophageal squamous cell carcinoma (ESCC), we previously carried out a genome-wide gene expression profiling study using an oligonucleotide microarray platform. This analysis led to identification of several transcripts that were significantly upregulated in ESCC compared to the adjacent normal epithelium. In the current study, we performed immunohistochemical analyses of protein products for two candidates genes identified from the DNA microarray analysis, periostin (POSTN) and lumican (LUM), using tissue microarrays. Increased expression of both periostin and lumican was observed in 100% of 137 different ESCC samples arrayed on tissue microarrays. Increased expression of periostin and lumican was observed in carcinoma as well as in stromal cell in the large majority of cases. These findings suggest that these candidates can be investigated in the sera of ESCC patients using ELISA or multiple reaction monitoring (MRM) type assays to further explore their utility as biomarkers

  5. Current Knowledge on Microarray Technology - An Overview

    African Journals Online (AJOL)

    Erah

    This paper reviews basics and updates of each microarray technology and serves to .... through protein microarrays. Protein microarrays also known as protein chips are nothing but grids that ... conditioned media, patient sera, plasma and urine. Clontech ... based antibody arrays) is similar to membrane-based antibody ...

  6. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Christensen, C.B.V.

    2005-01-01

    DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the post...

  7. Elimination of heparin interference during microarray processing of fresh and biobank-archived blood samples.

    Science.gov (United States)

    Hebels, Dennie G A J; van Herwijnen, Marcel H M; Brauers, Karen J J; de Kok, Theo M C M; Chalkiadaki, Georgia; Kyrtopoulos, Soterios A; Kleinjans, Jos C S

    2014-07-01

    In the context of environmental health research, biobank blood samples have recently been identified as suitable for high-throughput omics analyses enabling the identification of new biomarkers of exposure and disease. However, blood samples containing the anti-coagulant heparin could complicate transcriptomic analysis because heparin may inhibit RNA polymerase causing inefficient cRNA synthesis and fluorophore labelling. We investigated the inhibitory effect of heparin and the influence of storage conditions (0 or 3 hr bench times, storage at room temperature or -80°C) on fluorophore labelling in heparinized fresh human buffy coat and whole blood biobank samples during the mRNA work-up protocol for microarray analysis. Subsequently, we removed heparin by lithium chloride (LiCl) treatment and performed a quality control analysis of LiCl-treated biobank sample microarrays to prove their suitability for downstream data analysis. Both fresh and biobank samples experienced varying degrees of heparin-induced inhibition of fluorophore labelling, making most samples unusable for microarray analysis. RNA derived from EDTA and citrate blood was not inhibited. No effect of bench time was observed but room temperature storage gave slightly better results. Strong correlations were observed between original blood sample RNA yield and the amount of synthesized cRNA. LiCl treatment restored sample quality to normal standards in both fresh and biobank samples and the previously identified correlations disappeared. Microarrays hybridized with LiCl-treated biobank samples were of excellent quality with no identifiable influence of heparin. We conclude that, to obtain high quality results, in most cases heparin removal is essential in blood-derived RNA samples intended for microarray analysis. Copyright © 2014 Wiley Periodicals, Inc.

  8. Antimicrobial resistance determinant microarray for analysis of multi-drug resistant isolates

    Science.gov (United States)

    Taitt, Chris Rowe; Leski, Tomasz; Stenger, David; Vora, Gary J.; House, Brent; Nicklasson, Matilda; Pimentel, Guillermo; Zurawski, Daniel V.; Kirkup, Benjamin C.; Craft, David; Waterman, Paige E.; Lesho, Emil P.; Bangurae, Umaru; Ansumana, Rashid

    2012-06-01

    The prevalence of multidrug-resistant infections in personnel wounded in Iraq and Afghanistan has made it challenging for physicians to choose effective therapeutics in a timely fashion. To address the challenge of identifying the potential for drug resistance, we have developed the Antimicrobial Resistance Determinant Microarray (ARDM) to provide DNAbased analysis for over 250 resistance genes covering 12 classes of antibiotics. Over 70 drug-resistant bacteria from different geographic regions have been analyzed on ARDM, with significant differences in patterns of resistance identified: genes for resistance to sulfonamides, trimethoprim, chloramphenicol, rifampin, and macrolide-lincosamidesulfonamide drugs were more frequently identified in isolates from sources in Iraq/Afghanistan. Of particular concern was the presence of genes responsible for resistance to many of the last-resort antibiotics used to treat war traumaassociated infections.

  9. Geiger mode avalanche photodiodes for microarray systems

    Science.gov (United States)

    Phelan, Don; Jackson, Carl; Redfern, R. Michael; Morrison, Alan P.; Mathewson, Alan

    2002-06-01

    New Geiger Mode Avalanche Photodiodes (GM-APD) have been designed and characterized specifically for use in microarray systems. Critical parameters such as excess reverse bias voltage, hold-off time and optimum operating temperature have been experimentally determined for these photon-counting devices. The photon detection probability, dark count rate and afterpulsing probability have been measured under different operating conditions. An active- quench circuit (AQC) is presented for operating these GM- APDs. This circuit is relatively simple, robust and has such benefits as reducing average power dissipation and afterpulsing. Arrays of these GM-APDs have already been designed and together with AQCs open up the possibility of having a solid-state microarray detector that enables parallel analysis on a single chip. Another advantage of these GM-APDs over current technology is their low voltage CMOS compatibility which could allow for the fabrication of an AQC on the same device. Small are detectors have already been employed in the time-resolved detection of fluorescence from labeled proteins. It is envisaged that operating these new GM-APDs with this active-quench circuit will have numerous applications for the detection of fluorescence in microarray systems.

  10. Microarray-based analysis of differential gene expression between infective and noninfective larvae of Strongyloides stercoralis.

    Directory of Open Access Journals (Sweden)

    Roshan Ramanathan

    2011-05-01

    Full Text Available Differences between noninfective first-stage (L1 and infective third-stage (L3i larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose.Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest.A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights regarding differences between infective and

  11. Discovery of possible gene relationships through the application of self-organizing maps to DNA microarray databases.

    Science.gov (United States)

    Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres

    2014-01-01

    DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques--an unsupervised artificial neural network called a Self-Organizing Map (SOM)-which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms.

  12. The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling

    Directory of Open Access Journals (Sweden)

    Johana A. Luna Coronell

    2018-02-01

    Full Text Available Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 “CRC genes.” These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology. Keywords: Autoantibody tumor biomarker, Cancer immunology, Colorectal cancer, Immunomics, Protein microarray

  13. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  14. On the classification techniques in data mining for microarray data classification

    Science.gov (United States)

    Aydadenta, Husna; Adiwijaya

    2018-03-01

    Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

  15. Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis

    International Nuclear Information System (INIS)

    Turashvili, Gulisa; Srovnal, Josef; Hajduch, Marian; Murray, Paul; Kolar, Zdenek; Bouchal, Jan; Baumforth, Karl; Wei, Wenbin; Dziechciarkova, Marta; Ehrmann, Jiri; Klein, Jiri; Fridman, Eduard; Skarda, Jozef

    2007-01-01

    Invasive ductal and lobular carcinomas (IDC and ILC) are the most common histological types of breast cancer. Clinical follow-up data and metastatic patterns suggest that the development and progression of these tumors are different. The aim of our study was to identify gene expression profiles of IDC and ILC in relation to normal breast epithelial cells. We examined 30 samples (normal ductal and lobular cells from 10 patients, IDC cells from 5 patients, ILC cells from 5 patients) microdissected from cryosections of ten mastectomy specimens from postmenopausal patients. Fifty nanograms of total RNA were amplified and labeled by PCR and in vitro transcription. Samples were analysed upon Affymetrix U133 Plus 2.0 Arrays. The expression of seven differentially expressed genes (CDH1, EMP1, DDR1, DVL1, KRT5, KRT6, KRT17) was verified by immunohistochemistry on tissue microarrays. Expression of ASPN mRNA was validated by in situ hybridization on frozen sections, and CTHRC1, ASPN and COL3A1 were tested by PCR. Using GCOS pairwise comparison algorithm and rank products we have identified 84 named genes common to ILC versus normal cell types, 74 named genes common to IDC versus normal cell types, 78 named genes differentially expressed between normal ductal and lobular cells, and 28 named genes between IDC and ILC. Genes distinguishing between IDC and ILC are involved in epithelial-mesenchymal transition, TGF-beta and Wnt signaling. These changes were present in both tumor types but appeared to be more prominent in ILC. Immunohistochemistry for several novel markers (EMP1, DVL1, DDR1) distinguished large sets of IDC from ILC. IDC and ILC can be differentiated both at the gene and protein levels. In this study we report two candidate genes, asporin (ASPN) and collagen triple helix repeat containing 1 (CTHRC1) which might be significant in breast carcinogenesis. Besides E-cadherin, the proteins validated on tissue microarrays (EMP1, DVL1, DDR1) may represent novel

  16. PMA-PhyloChip DNA Microarray to Elucidate Viable Microbial Community Structure

    Science.gov (United States)

    Venkateswaran, Kasthuri J.; Stam, Christina N.; Andersen, Gary L.; DeSantis, Todd

    2011-01-01

    in the dark. Thereafter, the sample is exposed to visible light for five minutes, so that the DNA from dead cells will be cross-linked. Following this PMA treatment step, the sample is concentrated by centrifugation and washed (to remove excessive PMA) before DNA is extracted. The 16S rRNA gene fragments will be amplified by PCR to screen the total microbial community using PhyloChip DNA microarray analysis. This approach will detect only the viable microbial community since the PMA intercalated DNA from dead cells would be unavailable for PCR amplification. The total detection time including PCR reaction for low biomass samples will be a few hours. Numerous markets may use this technology. The food industry uses spore detection to validate new alternative food processing technologies, sterility, and quality. Pharmaceutical and medical equipment companies also detect spores as a marker for sterility. This system can be used for validating sterilization processes, water treatment systems, and in various public health and homeland security applications.

  17. A Customized DNA Microarray for Microbial Source Tracking ...

    Science.gov (United States)

    It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

  18. Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2004-12-01

    Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

  19. DNA microarray-based PCR ribotyping of Clostridium difficile.

    Science.gov (United States)

    Schneeberg, Alexander; Ehricht, Ralf; Slickers, Peter; Baier, Vico; Neubauer, Heinrich; Zimmermann, Stefan; Rabold, Denise; Lübke-Becker, Antina; Seyboldt, Christian

    2015-02-01

    This study presents a DNA microarray-based assay for fast and simple PCR ribotyping of Clostridium difficile strains. Hybridization probes were designed to query the modularly structured intergenic spacer region (ISR), which is also the template for conventional and PCR ribotyping with subsequent capillary gel electrophoresis (seq-PCR) ribotyping. The probes were derived from sequences available in GenBank as well as from theoretical ISR module combinations. A database of reference hybridization patterns was set up from a collection of 142 well-characterized C. difficile isolates representing 48 seq-PCR ribotypes. The reference hybridization patterns calculated by the arithmetic mean were compared using a similarity matrix analysis. The 48 investigated seq-PCR ribotypes revealed 27 array profiles that were clearly distinguishable. The most frequent human-pathogenic ribotypes 001, 014/020, 027, and 078/126 were discriminated by the microarray. C. difficile strains related to 078/126 (033, 045/FLI01, 078, 126, 126/FLI01, 413, 413/FLI01, 598, 620, 652, and 660) and 014/020 (014, 020, and 449) showed similar hybridization patterns, confirming their genetic relatedness, which was previously reported. A panel of 50 C. difficile field isolates was tested by seq-PCR ribotyping and the DNA microarray-based assay in parallel. Taking into account that the current version of the microarray does not discriminate some closely related seq-PCR ribotypes, all isolates were typed correctly. Moreover, seq-PCR ribotypes without reference profiles available in the database (ribotype 009 and 5 new types) were correctly recognized as new ribotypes, confirming the performance and expansion potential of the microarray. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  20. Evaluation of gene expression data generated from expired Affymetrix GeneChip® microarrays using MAQC reference RNA samples

    Directory of Open Access Journals (Sweden)

    Tong Weida

    2010-10-01

    Full Text Available Abstract Background The Affymetrix GeneChip® system is a commonly used platform for microarray analysis but the technology is inherently expensive. Unfortunately, changes in experimental planning and execution, such as the unavailability of previously anticipated samples or a shift in research focus, may render significant numbers of pre-purchased GeneChip® microarrays unprocessed before their manufacturer’s expiration dates. Researchers and microarray core facilities wonder whether expired microarrays are still useful for gene expression analysis. In addition, it was not clear whether the two human reference RNA samples established by the MAQC project in 2005 still maintained their transcriptome integrity over a period of four years. Experiments were conducted to answer these questions. Results Microarray data were generated in 2009 in three replicates for each of the two MAQC samples with either expired Affymetrix U133A or unexpired U133Plus2 microarrays. These results were compared with data obtained in 2005 on the U133Plus2 microarray. The percentage of overlap between the lists of differentially expressed genes (DEGs from U133Plus2 microarray data generated in 2009 and in 2005 was 97.44%. While there was some degree of fold change compression in the expired U133A microarrays, the percentage of overlap between the lists of DEGs from the expired and unexpired microarrays was as high as 96.99%. Moreover, the microarray data generated using the expired U133A microarrays in 2009 were highly concordant with microarray and TaqMan® data generated by the MAQC project in 2005. Conclusions Our results demonstrated that microarray data generated using U133A microarrays, which were more than four years past the manufacturer’s expiration date, were highly specific and consistent with those from unexpired microarrays in identifying DEGs despite some appreciable fold change compression and decrease in sensitivity. Our data also suggested that the

  1. Hierarchical information representation and efficient classification of gene expression microarray data

    OpenAIRE

    Bosio, Mattia

    2014-01-01

    In the field of computational biology, microarryas are used to measure the activity of thousands of genes at once and create a global picture of cellular function. Microarrays allow scientists to analyze expression of many genes in a single experiment quickly and eficiently. Even if microarrays are a consolidated research technology nowadays and the trends in high-throughput data analysis are shifting towards new technologies like Next Generation Sequencing (NGS), an optimum method for sample...

  2. Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

    Directory of Open Access Journals (Sweden)

    Thomas Sanford

    Full Text Available To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%. The correct classification by subtype was 19/20 (95% for clear cell, 14/14 (100% for papillary, 17/19 (89% for chromophobe, 18/19 (95% for oncocytomas.Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.

  3. Elucidation of the antibacterial mechanism of the Curvularia haloperoxidase system by DNA microarray profiling

    DEFF Research Database (Denmark)

    Hansen, E.H.; Schembri, Mark; Klemm, Per

    2004-01-01

    was the wild type. Our results demonstrate that DNA microarray technology cannot be used as the only technique to investigate the mechanisms of action of new antimicrobial compounds. However, by combining DNA microarray analysis with the subsequent creation of knockout mutants, we were able to pinpoint one...

  4. Transcriptome Analysis of Mycobacteria-Specific CD4+ T Cells Identified by Activation-Induced Expression of CD154.

    Science.gov (United States)

    Kunnath-Velayudhan, Shajo; Goldberg, Michael F; Saini, Neeraj K; Johndrow, Christopher T; Ng, Tony W; Johnson, Alison J; Xu, Jiayong; Chan, John; Jacobs, William R; Porcelli, Steven A

    2017-10-01

    Analysis of Ag-specific CD4 + T cells in mycobacterial infections at the transcriptome level is informative but technically challenging. Although several methods exist for identifying Ag-specific T cells, including intracellular cytokine staining, cell surface cytokine-capture assays, and staining with peptide:MHC class II multimers, all of these have significant technical constraints that limit their usefulness. Measurement of activation-induced expression of CD154 has been reported to detect live Ag-specific CD4 + T cells, but this approach remains underexplored and, to our knowledge, has not previously been applied in mycobacteria-infected animals. In this article, we show that CD154 expression identifies adoptively transferred or endogenous Ag-specific CD4 + T cells induced by Mycobacterium bovis bacillus Calmette-Guérin vaccination. We confirmed that Ag-specific cytokine production was positively correlated with CD154 expression by CD4 + T cells from bacillus Calmette-Guérin-vaccinated mice and show that high-quality microarrays can be performed from RNA isolated from CD154 + cells purified by cell sorting. Analysis of microarray data demonstrated that the transcriptome of CD4 + CD154 + cells was distinct from that of CD154 - cells and showed major enrichment of transcripts encoding multiple cytokines and pathways of cellular activation. One notable finding was the identification of a previously unrecognized subset of mycobacteria-specific CD4 + T cells that is characterized by the production of IL-3. Our results support the use of CD154 expression as a practical and reliable method to isolate live Ag-specific CD4 + T cells for transcriptomic analysis and potentially for a range of other studies in infected or previously immunized hosts. Copyright © 2017 by The American Association of Immunologists, Inc.

  5. DNA microarray profiling of genes differentially regulated by the histone deacetylase inhibitors vorinostat and LBH589 in colon cancer cell lines

    Directory of Open Access Journals (Sweden)

    Lenz Heinz-Josef

    2009-11-01

    Full Text Available Abstract Background Despite the significant progress made in colon cancer chemotherapy, advanced disease remains largely incurable and novel efficacious chemotherapies are urgently needed. Histone deacetylase inhibitors (HDACi represent a novel class of agents which have demonstrated promising preclinical activity and are undergoing clinical evaluation in colon cancer. The goal of this study was to identify genes in colon cancer cells that are differentially regulated by two clinically advanced hydroxamic acid HDACi, vorinostat and LBH589 to provide rationale for novel drug combination partners and identify a core set of HDACi-regulated genes. Methods HCT116 and HT29 colon cancer cells were treated with LBH589 or vorinostat and growth inhibition, acetylation status and apoptosis were analyzed in response to treatment using MTS, Western blotting and flow cytometric analyses. In addition, gene expression was analyzed using the Illumina Human-6 V2 BeadChip array and Ingenuity® Pathway Analysis. Results Treatment with either vorinostat or LBH589 rapidly induced histone acetylation, cell cycle arrest and inhibited the growth of both HCT116 and HT29 cells. Bioinformatic analysis of the microarray profiling revealed significant similarity in the genes altered in expression following treatment with the two HDACi tested within each cell line. However, analysis of genes that were altered in expression in the HCT116 and HT29 cells revealed cell-line-specific responses to HDACi treatment. In addition a core cassette of 11 genes modulated by both vorinostat and LBH589 were identified in both colon cancer cell lines analyzed. Conclusion This study identified HDACi-induced alterations in critical genes involved in nucleotide metabolism, angiogenesis, mitosis and cell survival which may represent potential intervention points for novel therapeutic combinations in colon cancer. This information will assist in the identification of novel pathways and targets

  6. Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

    Science.gov (United States)

    Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

    2017-10-01

    A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

  7. Microarray-Based Identification of Transcription Factor Target Genes

    NARCIS (Netherlands)

    Gorte, M.; Horstman, A.; Page, R.B.; Heidstra, R.; Stromberg, A.; Boutilier, K.A.

    2011-01-01

    Microarray analysis is widely used to identify transcriptional changes associated with genetic perturbation or signaling events. Here we describe its application in the identification of plant transcription factor target genes with emphasis on the design of suitable DNA constructs for controlling TF

  8. The role of metalloendopeptidases in oropharyngeal carcinomas assessed by tissue microarray.

    Science.gov (United States)

    Ribeiro, Daniel A; Nascimento, Fabio D; Fracalossi, Ana Carolina C; Noguti, Juliana; Oshima, Celina T F; Ihara, Silvia S M; Franco, Marcello F

    2011-01-01

    The goal of this study was to investigate the expression of some metalloendopeptidases in squamous cell carcinomas of the oropharynx as well as its relation to histological differentiation, staging of disease, and prognosis. Paraffin blocks from 21 primary tumors were obtained from archives of the Department of Pathology, Paulista Medical School, Federal University of Sao Paulo, UNIFESP/EPM. Immunohistochemistry was used to detect the expression of EP24.15 and EP24.16 by means of tissue microarrays. Expression of EP24.15 or EP24.16 was not correlated with the stage of disease, histopathological grading or recurrence in squamous cell carcinomas of the oropharynx. In summary, our results support the notion that EP24.15 and EP24.16 are expressed in carcinoma of the oropharynx; however, these do not appear to be suitable biomarkers for histological grading, disease stage or recurrence as depicted by tissue microarrays and immunohistochemistry.

  9. Tumour auto-antibody screening: performance of protein microarrays using SEREX derived antigens

    International Nuclear Information System (INIS)

    Stempfer, René; Weinhäusel, Andreas; Syed, Parvez; Vierlinger, Klemens; Pichler, Rudolf; Meese, Eckart; Leidinger, Petra; Ludwig, Nicole; Kriegner, Albert; Nöhammer, Christa

    2010-01-01

    The simplicity and potential of minimal invasive testing using serum from patients make auto-antibody based biomarkers a very promising tool for use in diagnostics of cancer and auto-immune disease. Although several methods exist for elucidating candidate-protein markers, immobilizing these onto membranes and generating so called macroarrays is of limited use for marker validation. Especially when several hundred samples have to be analysed, microarrays could serve as a good alternative since processing macro membranes is cumbersome and reproducibility of results is moderate. Candidate markers identified by SEREX (serological identification of antigens by recombinant expression cloning) screenings of brain and lung tumour were used for macroarray and microarray production. For microarray production recombinant proteins were expressed in E. coli by autoinduction and purified His-tag (histidine-tagged) proteins were then used for the production of protein microarrays. Protein arrays were hybridized with the serum samples from brain and lung tumour patients. Methods for the generation of microarrays were successfully established when using antigens derived from membrane-based selection. Signal patterns obtained by microarrays analysis of brain and lung tumour patients' sera were highly reproducible (R = 0.92-0.96). This provides the technical foundation for diagnostic applications on the basis of auto-antibody patterns. In this limited test set, the assay provided high reproducibility and a broad dynamic range to classify all brain and lung samples correctly. Protein microarray is an efficient means for auto-antibody-based detection when using SEREX-derived clones expressing antigenic proteins. Protein microarrays are preferred to macroarrays due to the easier handling and the high reproducibility of auto-antibody testing. Especially when using only a few microliters of patient samples protein microarrays are ideally suited for validation of auto

  10. SCK-CEN Genomic Platform: the microarray technology

    International Nuclear Information System (INIS)

    Benotmane, R.

    2006-01-01

    The human body contains approximately 10 14 cells, wherein each one is a nucleus. The nucleus contains 2x23 chromosomes, or two complete sets of the human genome, one set coming from the mother and the other from the father. In principle each set includes 30.000-40.000 genes. If the genome was a book, it would be twenty-three chapters, called chromosomes,each chapter with several thousand stories, called genes. Each story made up of paragraphs, called exons and introns. Each paragraph made up of 3 letter words, called codons. Each word is written with letters called bases (AGCT). But the whole is written in a single very long sentence, which is the DNA molecule or deoxy nucleic acid. The usual state of DNA is two complementary strands intertwined forming a double helix. In the cell, DNA is duplicated during each cell division to ensure the transmission of the genome to the daughter cells. For expression, the DNA is transcribed to messenger RNA. The RNA is edited and finally translated to a protein, each three bases coding for one amino acid. When the whole message is translated, the chain of amino acids folds itself up into a distinctive shape that depends on its sequence. Proteins are the effectors of the genes, and are responsible for all metabolic, hormonal and enzymatic reactions in the cells. The expressed RNA determines the amount of proteins to be produced and subsequently the desired effect (strong or weak) in the cell. The microarray technology aims at quantifying the amount of RNA present in the cell from each expressed gene, and at evaluating the changes of these amounts after exposure of the cell to toxic chemicals, ionising radiation or other stress components. The global picture of expressed genes helps to understand the affected genetic pathways in the cell at the molecular level. The microarray technology is used in the Radiobiology and Microbiology topics to study the effect of ionising radiation on human cells and mouse tissue, as well as the

  11. Microarrays in ecological research: A case study of a cDNA microarray for plant-herbivore interactions

    Directory of Open Access Journals (Sweden)

    Gase Klaus

    2004-09-01

    Full Text Available Abstract Background Microarray technology allows researchers to simultaneously monitor changes in the expression ratios (ERs of hundreds of genes and has thereby revolutionized most of biology. Although this technique has the potential of elucidating early stages in an organism's phenotypic response to complex ecological interactions, to date, it has not been fully incorporated into ecological research. This is partially due to a lack of simple procedures of handling and analyzing the expression ratio (ER data produced from microarrays. Results We describe an analysis of the sources of variation in ERs from 73 hybridized cDNA microarrays, each with 234 herbivory-elicited genes from the model ecological expression system, Nicotiana attenuata, using procedures that are commonly used in ecologic research. Each gene is represented by two independently labeled PCR products and each product was arrayed in quadruplicate. We present a robust method of normalizing and analyzing ERs based on arbitrary thresholds and statistical criteria, and characterize a "norm of reaction" of ERs for 6 genes (4 of known function, 2 of unknown with different ERs as determined across all analyzed arrays to provide a biologically-informed alternative to the use of arbitrary expression ratios in determining significance of expression. These gene-specific ERs and their variance (gene CV were used to calculate array-based variances (array CV, which, in turn, were used to study the effects of array age, probe cDNA quantity and quality, and quality of spotted PCR products as estimates of technical variation. Cluster analysis and a Principal Component Analysis (PCA were used to reveal associations among the transcriptional "imprints" of arrays hybridized with cDNA probes derived from mRNA from N. attenuata plants variously elicited and attacked by different herbivore species and from three congeners: N. quadrivalis, N. longiflora and N. clevelandii. Additionally, the PCA

  12. High quality protein microarray using in situ protein purification

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    Fleischmann Robert D

    2009-08-01

    Full Text Available Abstract Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC. This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents

  13. Global pathway analysis using DNA microarrays in skeletal muscle of women with polycystic ovary syndrome

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    (study 1), to investigate whether pioglitazone therapy could reverse abnormalities in the transcriptional profile of muscle associated with insulin resistance in skeletal muscle of obese PCOS patients (study 2), and to develop a microarray platform for global gene expression profiling (study 3). In study...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....

  14. Microarray data reveal relationship between Jag1 and Ddr1 in mouse liver.

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    Lara A Underkoffler

    Full Text Available Alagille syndrome is an autosomal dominant disorder involving bile duct paucity and cholestasis in addition to cardiac, skeletal, ophthalmologic, renal and vascular manifestations. Mutations in JAG1, encoding a ligand in the Notch signaling pathway, are found in 95% of patients meeting clinical criteria for Alagille syndrome. In order to define the role of Jag1 in the bile duct developmental abnormalities seen in ALGS, we previously created a Jag1 conditional knockout mouse model. Mice heterozygous for the Jag1 conditional and null alleles demonstrate abnormalities in postnatal bile duct growth and remodeling, with portal expansion and increased numbers of malformed bile ducts. In this study we report the results of microarray analysis and identify genes and pathways differentially expressed in the Jag1 conditional/null livers as compared with littermate controls. In the initial microarray analysis, we found that many of the genes up-regulated in the Jag1 conditional/null mutant livers were related to extracellular matrix (ECM interactions, cell adhesion and cell migration. One of the most highly up-regulated genes was Ddr1, encoding a receptor tyrosine kinase (RTK belonging to a large RTK family. We have found extensive co-localization of Jag1 and Ddr1 in bile ducts and blood vessels in postnatal liver. In addition, co-immunoprecipitation data provide evidence for a novel protein interaction between Jag1 and Ddr1. Further studies will be required to define the nature of this interaction and its functional consequences, which may have significant implications for bile duct remodeling and repair of liver injury.

  15. Efficient Generation of Human Embryonic Stem Cell-Derived Corneal Endothelial Cells by Directed Differentiation.

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    Kathryn L McCabe

    Full Text Available To generate human embryonic stem cell derived corneal endothelial cells (hESC-CECs for transplantation in patients with corneal endothelial dystrophies.Feeder-free hESC-CECs were generated by a directed differentiation protocol. hESC-CECs were characterized by morphology, expression of corneal endothelial markers, and microarray analysis of gene expression.hESC-CECs were nearly identical morphologically to primary human corneal endothelial cells, expressed Zona Occludens 1 (ZO-1 and Na+/K+ATPaseα1 (ATPA1 on the apical surface in monolayer culture, and produced the key proteins of Descemet's membrane, Collagen VIIIα1 and VIIIα2 (COL8A1 and 8A2. Quantitative PCR analysis revealed expression of all corneal endothelial pump transcripts. hESC-CECs were 96% similar to primary human adult CECs by microarray analysis.hESC-CECs are morphologically similar, express corneal endothelial cell markers and express a nearly identical complement of genes compared to human adult corneal endothelial cells. hESC-CECs may be a suitable alternative to donor-derived corneal endothelium.

  16. The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

    Science.gov (United States)

    Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

    2009-01-01

    We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

  17. Increasing the specificity and function of DNA microarrays by processing arrays at different stringencies

    DEFF Research Database (Denmark)

    Dufva, Martin; Petersen, Jesper; Poulsen, Lena

    2009-01-01

    DNA microarrays have for a decade been the only platform for genome-wide analysis and have provided a wealth of information about living organisms. DNA microarrays are processed today under one condition only, which puts large demands on assay development because all probes on the array need to f...

  18. Gene expression analysis of cell death induction by Taurolidine in different malignant cell lines

    International Nuclear Information System (INIS)

    Chromik, Ansgar M; Weyhe, Dirk; Mittelkötter, Ulrich; Uhl, Waldemar; Hahn, Stephan A; Daigeler, Adrien; Flier, Annegret; Bulut, Daniel; May, Christina; Harati, Kamran; Roschinsky, Jan; Sülberg, Dominique

    2010-01-01

    The anti-infective agent Taurolidine (TRD) has been shown to have cell death inducing properties, but the mechanism of its action is largely unknown. The aim of this study was to identify potential common target genes modulated at the transcriptional level following TRD treatment in tumour cell lines originating from different cancer types. Five different malignant cell lines (HT29, Chang Liver, HT1080, AsPC-1 and BxPC-3) were incubated with TRD (100 μM, 250 μM and 1000 μM). Proliferation after 8 h and cell viability after 24 h were analyzed by BrdU assay and FACS analysis, respectively. Gene expression analyses were carried out using the Agilent -microarray platform to indentify genes which displayed conjoint regulation following the addition of TRD in all cell lines. Candidate genes were subjected to Ingenuity Pathways Analysis and selected genes were validated by qRT-PCR and Western Blot. TRD 250 μM caused a significant inhibition of proliferation as well as apoptotic cell death in all cell lines. Among cell death associated genes with the strongest regulation in gene expression, we identified pro-apoptotic transcription factors (EGR1, ATF3) as well as genes involved in the ER stress response (PPP1R15A), in ubiquitination (TRAF6) and mitochondrial apoptotic pathways (PMAIP1). This is the first conjoint analysis of potential target genes of TRD which was performed simultaneously in different malignant cell lines. The results indicate that TRD might be involved in different signal transduction pathways leading to apoptosis

  19. Microarray Analysis of microRNA Expression during Axolotl Limb Regeneration

    Science.gov (United States)

    Holman, Edna C.; Campbell, Leah J.; Hines, John; Crews, Craig M.

    2012-01-01

    Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum) has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression) of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum (“Amex”) miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3′UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes. PMID:23028429

  20. Microarray analysis of microRNA expression during axolotl limb regeneration.

    Directory of Open Access Journals (Sweden)

    Edna C Holman

    Full Text Available Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum ("Amex" miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3'UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes.

  1. Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovarian and breast cancer

    Directory of Open Access Journals (Sweden)

    Dermody James J

    2004-11-01

    Full Text Available Abstract Background A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identify potential targets for drug development, and can aid in evaluating treatment efficacy and predicting patient outcome. Microarray technology has enabled marker discovery from human cells by permitting measurement of steady-state mRNA levels derived from thousands of genes. However many challenging and unresolved issues regarding the acquisition and analysis of microarray data remain, such as accounting for both experimental and biological noise, transcripts whose expression profiles are not normally distributed, guidelines for statistical assessment of false positive/negative rates and comparing data derived from different research groups. This study addresses these issues using Affymetrix HG-U95A and HG-U133 GeneChip data derived from different research groups. Results We present here a simple non parametric approach coupled with noise filtering to identify sets of genes differentially expressed between the normal and cancer states in oral, breast, lung, prostate and ovarian tumors. An important feature of this study is the ability to integrate data from different laboratories, improving the analytical power of the individual results. One of the most interesting findings is the down regulation of genes involved in tissue differentiation. Conclusions This study presents the development and application of a noise model that suppresses noise, limits false positives in the results, and allows integration of results from individual studies derived from different research groups.

  2. Microarray analysis of gene expression profiles of Schistosoma japonicum derived from less-susceptible host water buffalo and susceptible host goat.

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    Jianmei Yang

    Full Text Available BACKGROUND: Water buffalo and goats are natural hosts for S. japonicum in endemic areas of China. The susceptibility of these two hosts to schistosome infection is different, as water buffalo are less conducive to S. japonicum growth and development. To identify genes that may affect schistosome development and survival, we compared gene expression profiles of schistosomes derived from these two natural hosts using high-throughput microarray technology. RESULTS: The worm recovery rate was lower and the length and width of worms from water buffalo were smaller compared to those from goats following S. japonicum infection for 7 weeks. Besides obvious morphological difference between the schistosomes derived from the two hosts, differences were also observed by scanning and transmission electron microscopy. Microarray analysis showed differentially expressed gene patterns for parasites from the two hosts, which revealed that genes related to lipid and nucleotide metabolism, as well as protein folding, sorting, and degradation were upregulated, while others associated with signal transduction, endocrine function, development, immune function, endocytosis, and amino acid/carbohydrate/glycan metabolism were downregulated in schistosomes from water buffalo. KEGG pathway analysis deduced that the differentially expressed genes mainly involved lipid metabolism, the MAPK and ErbB signaling pathways, progesterone-mediated oocyte maturation, dorso-ventral axis formation, reproduction, and endocytosis, etc. CONCLUSION: The microarray gene analysis in schistosomes derived from water buffalo and goats provide a useful platform to disclose differences determining S. japonicum host compatibility to better understand the interplay between natural hosts and parasites, and identify schistosome target genes associated with susceptibility to screen vaccine candidates.

  3. Application of microarray analysis on computer cluster and cloud platforms.

    Science.gov (United States)

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  4. DNA Microarray Technology; TOPICAL

    International Nuclear Information System (INIS)

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

    Collaboration between Sandia National Laboratories and the University of New Mexico Biology Department resulted in the capability to train students in microarray techniques and the interpretation of data from microarray experiments. These studies provide for a better understanding of the role of stationary phase and the gene regulation involved in exit from stationary phase, which may eventually have important clinical implications. Importantly, this research trained numerous students and is the basis for three new Ph.D. projects

  5. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Science.gov (United States)

    Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

    2015-06-25

    Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

  6. Normalization for triple-target microarray experiments

    Directory of Open Access Journals (Sweden)

    Magniette Frederic

    2008-04-01

    Full Text Available Abstract Background Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. Results We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. Conclusion The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

  7. Hypoxia-Inducible Factor-1α (HIF-1α) Expression on Endothelial Cells in Juvenile Nasopharyngeal Angiofibroma: A Review of 70 cases and Tissue Microarray Analysis.

    Science.gov (United States)

    Song, Xiaole; Yang, Chenhe; Zhang, Huankang; Wang, Jingjing; Sun, Xicai; Hu, Li; Liu, Zhuofu; Wang, Dehui

    2018-06-01

    To examine the expression of hypoxia-inducible factor-1α (HIF-1α) and its related molecules (cellular repressor of E1A-stimulated genes [CREG], osteopontin [OPN], proto-oncogene tyrosine-protein kinase Src [c-Src], and vascular endothelial growth factor [VEGF]) in juvenile nasopharyngeal angiofibroma (JNA) and explore the correlation between clinical prognosis and HIF-1α expression. The study performed a retrospective review of the clinical records of patients with JNA treated between 2003 and 2007. Specimens were analyzed by immunohistochemistry for HIF-1α, CREG, OPN, c-Src, and VEGF expression, and microvessel density (MVD) was assessed by tissue microarray. The correlation between expression levels and clinicopathological features including age, tumor stage, intraoperative blood loss, and recurrence was analyzed. HIF-1α, CREG, OPN, c-Src, and VEGF were upregulated in endothelial cells (ECs) of patients with JNA, and strong correlations in the expression of these molecules were observed. HIF-1α expression was higher in young patients ( P = .032) and in recurrent cases ( P = .01). Survival analysis showed that low HIF-1α levels in ECs predicted longer time to recurrence (log rank test P = .006). Receiver operating characteristic curve analysis showed that HIF-1α was a prognostic factor for recurrence (area under the curve = 0.690, P = .019). No correlation was found between the expression of molecules and Radkowski stage or intraoperative blood loss. In cases of JNA treated surgically, HIF-1α expression in ECs is a useful prognostic factor for tumor recurrence.

  8. Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays.

    Science.gov (United States)

    Kanie, Kei; Kondo, Yuto; Owaki, Junki; Ikeda, Yurika; Narita, Yuji; Kato, Ryuji; Honda, Hiroyuki

    2016-11-19

    The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM) provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV), an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I), and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides.

  9. Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays

    Directory of Open Access Journals (Sweden)

    Kei Kanie

    2016-11-01

    Full Text Available The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV, an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I, and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides.

  10. Microarray profile of seizure damage-refractory hippocampal CA3 in a mouse model of epileptic preconditioning.

    Science.gov (United States)

    Hatazaki, S; Bellver-Estelles, C; Jimenez-Mateos, E M; Meller, R; Bonner, C; Murphy, N; Matsushima, S; Taki, W; Prehn, J H M; Simon, R P; Henshall, D C

    2007-12-05

    A neuroprotected state can be acquired by preconditioning brain with a stimulus that is subthreshold for damage (tolerance). Acquisition of tolerance involves coordinate, bi-directional changes to gene expression levels and the re-programmed phenotype is determined by the preconditioning stimulus. While best studied in ischemic brain there is evidence brief seizures can confer tolerance against prolonged seizures (status epilepticus). Presently, we developed a model of epileptic preconditioning in mice and used microarrays to gain insight into the transcriptional phenotype within the target hippocampus at the time tolerance had been acquired. Epileptic tolerance was induced by an episode of non-damaging seizures in adult C57Bl/6 mice using a systemic injection of kainic acid. Neuron and DNA damage-positive cell counts 24 h after status epilepticus induced by intraamygdala microinjection of kainic acid revealed preconditioning given 24 h prior reduced CA3 neuronal death by approximately 45% compared with non-tolerant seizure mice. Microarray analysis of over 39,000 transcripts (Affymetrix 430 2.0 chip) from microdissected CA3 subfields was undertaken at the point at which tolerance was acquired. Results revealed a unique profile of small numbers of equivalently up- and down-regulated genes with biological functions that included transport and localization, ubiquitin metabolism, apoptosis and cell cycle control. Select microarray findings were validated post hoc by real-time polymerase chain reaction and Western blotting. The present study defines a paradigm for inducing epileptic preconditioning in mice and first insight into the global transcriptome of the seizure-damage refractory brain.

  11. The Arabidopsis co-expression tool (act): a WWW-based tool and database for microarray-based gene expression analysis

    DEFF Research Database (Denmark)

    Jen, C. H.; Manfield, I. W.; Michalopoulos, D. W.

    2006-01-01

    be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots......We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (act) , based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression...

  12. A novel synthetic peptide microarray assay detects Chlamydia species-specific antibodies in animal and human sera.

    Science.gov (United States)

    Sachse, Konrad; Rahman, Kh Shamsur; Schnee, Christiane; Müller, Elke; Peisker, Madlen; Schumacher, Thomas; Schubert, Evelyn; Ruettger, Anke; Kaltenboeck, Bernhard; Ehricht, Ralf

    2018-03-16

    Serological analysis of Chlamydia (C.) spp. infections is still mainly based on micro-immunofluorescence and ELISA. To overcome the limitations of conventional serology, we have designed a novel microarray carrying 52 synthetic peptides representing B-cell epitopes from immunodominant proteins of all 11 chlamydial species. The new assay has been validated using monospecific mouse hyperimmune sera. Subsequently, serum samples from cattle, sheep and humans with a known history of chlamydial infection were examined. For instance, the specific humoral response of sheep to treatment with a C. abortus vaccine has been visualized against a background of C. pecorum carriership. In samples from humans, dual infection with C. trachomatis and C. pneumoniae could be demonstrated. The experiments revealed that the peptide microarray assay was capable of simultaneously identifying specific antibodies to each Chlamydia spp. The actual assay represents an open platform test that can be complemented through future advances in Chlamydia proteome research. The concept of the highly parallel multi-antigen microarray proven in this study has the potential to enhance our understanding of antibody responses by defining not only a single quantitative response, but also the pattern of this response. The added value of using peptide antigens will consist in unprecedented serodiagnostic specificity.

  13. Fisetin and hesperetin induced apoptosis and cell cycle arrest in chronic myeloid leukemia cells accompanied by modulation of cellular signaling.

    Science.gov (United States)

    Adan, Aysun; Baran, Yusuf

    2016-05-01

    Fisetin and hesperetin, naturally occurring flavonoids, have been reported as novel antioxidants with chemopreventive/chemotherapeutic potential against various types of cancer. However, their mechanism of action in CML is still unknown. This particular study aims to evaluate the therapeutic potentials of fisetin and hesperetin and their effects on cell proliferation, apoptosis, and cell cycle progression in human K562 CML cells. The results indicated that fisetin and hes