Science.gov

Sample records for affymetrix microarray technology

  1. Affymetrix GeneChip microarray preprocessing for multivariate analyses.

    PubMed

    McCall, Matthew N; Almudevar, Anthony

    2012-09-01

    Affymetrix GeneChip microarrays are the most widely used high-throughput technology to measure gene expression, and a wide variety of preprocessing methods have been developed to transform probe intensities reported by a microarray scanner into gene expression estimates. There have been numerous comparisons of these preprocessing methods, focusing on the most common analyses-detection of differential expression and gene or sample clustering. Recently, more complex multivariate analyses, such as gene co-expression, differential co-expression, gene set analysis and network modeling, are becoming more common; however, the same preprocessing methods are typically applied. In this article, we examine the effect of preprocessing methods on some of these multivariate analyses and provide guidance to the user as to which methods are most appropriate.

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

    PubMed

    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

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

    PubMed

    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

  4. Analysis of discordant Affymetrix probesets casts serious doubt on idea of microarray data reutilization

    PubMed Central

    2014-01-01

    Background Affymetrix microarray technology allows one to investigate expression of thousands of genes simultaneously upon a variety of conditions. In a popular U133A microarray platform, the expression of 37% of genes is measured by more than one probeset. The discordant expression observed for two different probesets that match the same gene is a widespread phenomenon which is usually underestimated, ignored or disregarded. Results Here we evaluate the prevalence of discordant expression in data collected using Affymetrix HG-U133A microarray platform. In U133A, about 30% of genes annotated by two different probesets demonstrate a substantial correlation between independently measured expression values. To our surprise, sorting the probesets according to the nature of the discrepancy in their expression levels allowed the classification of the respective genes according to their fundamental functional properties, including observed enrichment by tissue-specific transcripts and alternatively spliced variants. On another hand, an absence of discrepancies in probesets that simultaneously match several different genes allowed us to pinpoint non-expressed pseudogenes and gene groups with highly correlated expression patterns. Nevertheless, in many cases, the nature of discordant expression of two probesets that match the same transcript remains unexplained. It is possible that these probesets report differently regulated sets of transcripts, or, in best case scenario, two different sets of transcripts that represent the same gene. Conclusion The majority of absolute gene expression values collected using Affymetrix microarrays may not be suitable for typical interpretative downstream analysis. PMID:25563078

  5. AffyTrees: facilitating comparative analysis of Affymetrix plant microarray chips.

    PubMed

    Frickey, Tancred; Benedito, Vagner Augusto; Udvardi, Michael; Weiller, Georg

    2008-02-01

    Microarrays measure the expression of large numbers of genes simultaneously and can be used to delve into interaction networks involving many genes at a time. However, it is often difficult to decide to what extent knowledge about the expression of genes gleaned in one model organism can be transferred to other species. This can be examined either by measuring the expression of genes of interest under comparable experimental conditions in other species, or by gathering the necessary data from comparable microarray experiments. However, it is essential to know which genes to compare between the organisms. To facilitate comparison of expression data across different species, we have implemented a Web-based software tool that provides information about sequence orthologs across a range of Affymetrix microarray chips. AffyTrees provides a quick and easy way of assigning which probe sets on different Affymetrix chips measure the expression of orthologous genes. Even in cases where gene or genome duplications have complicated the assignment, groups of comparable probe sets can be identified. The phylogenetic trees provide a resource that can be used to improve sequence annotation and detect biases in the sequence complement of Affymetrix chips. Being able to identify sequence orthologs and recognize biases in the sequence complement of chips is necessary for reliable cross-species microarray comparison. As the amount of work required to generate a single phylogeny in a nonautomated manner is considerable, AffyTrees can greatly reduce the workload for scientists interested in large-scale cross-species comparisons.

  6. MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

    PubMed Central

    2014-01-01

    Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

  7. affyPara-a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data.

    PubMed

    Schmidberger, Markus; Vicedo, Esmeralda; Mansmann, Ulrich

    2009-07-22

    Microarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly.This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays.affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org. A user guide and examples are provided with the package.

  8. A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

    PubMed Central

    Rème, Thierry; Hose, Dirk; De Vos, John; Vassal, Aurélien; Poulain, Pierre-Olivier; Pantesco, Véronique; Goldschmidt, Hartmut; Klein, Bernard

    2008-01-01

    Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM). Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks

  9. Methods comparison for high-resolution transcriptional analysis of archival material on Affymetrix Plus 2.0 and Exon 1.0 microarrays.

    PubMed

    Linton, Kim; Hey, Yvonne; Dibben, Sian; Miller, Crispin; Freemont, Anthony; Radford, John; Pepper, Stuart

    2009-07-01

    Microarray gene expression profiling of formalin-fixed paraffin-embedded (FFPE) tissues is a new and evolving technique. This report compares transcript detection rates on Affymetrix U133 Plus 2.0 and Human Exon 1.0 ST GeneChips across several RNA extraction and target labeling protocols, using routinely collected archival FFPE samples. All RNA extraction protocols tested (Ambion-Optimum, Ambion-RecoverAll, and Qiagen-RNeasy FFPE) provided extracts suitable for microarray hybridization. Compared with Affymetrix One-Cycle labeled extracts, NuGEN system protocols utilizing oligo(dT) and random hexamer primers, and cDNA target preparations instead of cRNA, achieved percent present rates up to 55% on Plus 2.0 arrays. Based on two paired-sample analyses, at 90% specificity this equalled an average 30 percentage-point increase (from 50% to 80%) in FFPE transcript sensitivity relative to fresh frozen tissues, which we have assumed to have 100% sensitivity and specificity. The high content of Exon arrays, with multiple probe sets per exon, improved FFPE sensitivity to 92% at 96% specificity, corresponding to an absolute increase of ~600 genes over Plus 2.0 arrays. While larger series are needed to confirm high correspondence between fresh-frozen and FFPE expression patterns, these data suggest that both Plus 2.0 and Exon arrays are suitable platforms for FFPE microarray expression analyses.

  10. Functional Protein Microarray Technology

    PubMed Central

    Hu, Shaohui; Xie, Zhi; Qian, Jiang; Blackshaw, Seth; Zhu, Heng

    2010-01-01

    Functional protein microarrays are emerging as a promising new tool for large-scale and high-throughput studies. In this article, we will review their applications in basic proteomics research, where various types of assays have been developed to probe binding activities to other biomolecules, such as proteins, DNA, RNA, small molecules, and glycans. We will also report recent progress of using functional protein microarrays in profiling protein posttranslational modifications, including phosphorylation, ubiquitylation, acetylation, and nitrosylation. Finally, we will discuss potential of functional protein microarrays in biomarker identification and clinical diagnostics. We strongly believe that functional protein microarrays will soon become an indispensible and invaluable tool in proteomics research and systems biology. PMID:20872749

  11. DNA Microarray Technology

    SciTech Connect

    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.

  12. Identification of biomarkers regulated by rexinoids (LGD1069, LG100268 and Ro25-7386) in human breast cells using Affymetrix microarray.

    PubMed

    Seo, Hye-Sook; Woo, Jong-Kyu; Shin, Yong Cheol; Ko, Seong-Gyu

    2015-07-01

    Retinoids possess anti-proliferative properties, which suggests that they possess chemopreventive and therapeutic potential against cancer. In the current study, genes modulated by rexinoids (retinoid X receptor (RXR)-pan agonists, LGD1069 and LG100268; and the RXRα agonist, Ro25-7386) were identified using an Affymetrix microarray in normal and malignant breast cells. It was observed that LGD1069, LG100268 and Ro25-7386 suppressed the growth of breast cells. Secondly, several rexinoid-regulated genes were identified, which are involved in cell death, cell growth/maintenance, signal transduction and response to stimulus. These genes may be associated with the growth-suppressive activity of rexinoids. Therefore, the identified genes may serve as biomarkers and novel molecular targets for the prevention and treatment of breast cancer.

  13. Comparison of Comparative Genomic Hybridization Technologies across Microarray Platforms

    EPA Science Inventory

    In the 2007 Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation (CNV) was analyzed ...

  14. Comparison of L1000 and Affymetrix Microarray for In Vitro Concentration-Response Gene Expression Profiling (SOT)

    EPA Science Inventory

    Advances in high-throughput screening technologies and in vitro systems have opened doors for cost-efficient evaluation of chemical effects on a diversity of biological endpoints. However, toxicogenomics platforms remain too costly to evaluate large libraries of chemicals in conc...

  15. Microarray technology for use in molecular epidemiology.

    PubMed

    Vernon, Suzanne D; Whistler, Toni

    2007-01-01

    Microarrays are a powerful laboratory tool for the simultaneous assessment of the activity of thousands genes. Remarkable advances in biological sample collection, preparation and automation of hybridization have enabled the application of microarray technology to large, population-based studies. Now, microarrays have the potential to serve as screening tools for the detection of altered gene expression activity that might contribute to diseases in human populations. Reproducible and reliable microarray results depend on multiple factors. In this chapter, biological sample parameters are introduced that should be considered for any microarray experiment. Then, the microarray technology that we have successfully applied to limited biological sample from all our molecular epidemiology studies is detailed. This reproducible and reliable approach for using microarrays should be applicable to any biological questions asked.

  16. Application of microarray technology in pulmonary diseases

    PubMed Central

    Tzouvelekis, Argyris; Patlakas, George; Bouros, Demosthenes

    2004-01-01

    Microarrays are a powerful tool that have multiple applications both in clinical and cell biology arenas of common lung diseases. To exemplify how this tool can be useful, in this review, we will provide an overview of the application of microarray technology in research relevant to common lung diseases and present some of the future perspectives. PMID:15585067

  17. Advancing Microarray Assembly with Acoustic Dispensing Technology

    PubMed Central

    Wong, E. Y.; Diamond, S. L.

    2011-01-01

    In the assembly of microarrays and microarray-based chemical assays and enzymatic bioassays, most approaches use pins for contact spotting. Acoustic dispensing is a technology capable of nanoliter transfers by using acoustic energy to eject liquid sample from an open source well. Although typically used for well plate transfers, when applied to microarraying it avoids drawbacks of undesired physical contact with sample, difficulty in assembling multicomponent reactions on a chip by readdressing, a rigid mode of printing that lacks patterning capabilities, and time-consuming wash steps. We demonstrated the utility of acoustic dispensing by delivering human cathepsin L in a drop-on-drop fashion into individual 50-nanoliter, pre-spotted reaction volumes to activate enzyme reactions at targeted positions on a microarray. We generated variable-sized spots ranging from 200 to 750 μm (and higher), and handled the transfer of fluorescent bead suspensions with increasing source well concentrations of 0.1 to 10 ×108 beads/mL in a linear fashion. There are no tips that can clog and liquid dispensing CVs are generally below 5%. This platform expands the toolbox for generating analytical arrays and meets needs associated with spatially-addressed assembly of multicomponent microarrays on the nanoliter scale. PMID:19035650

  18. Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues.

    PubMed

    Chen, Xi; Deane, Natasha G; Lewis, Keeli B; Li, Jiang; Zhu, Jing; Washington, M Kay; Beauchamp, R Daniel

    2016-01-01

    The prognosis of colorectal cancer (CRC) stage II and III patients remains a challenge due to the difficulties of finding robust biomarkers suitable for testing clinical samples. The majority of published gene signatures of CRC have been generated on fresh frozen colorectal tissues. Because collection of frozen tissue is not practical for routine surgical pathology practice, a clinical test that improves prognostic capabilities beyond standard pathological staging of colon cancer will need to be designed for formalin-fixed paraffin-embedded (FFPE) tissues. The NanoString nCounter® platform is a gene expression analysis tool developed for use with FFPE-derived samples. We designed a custom nCounter® codeset based on elements from multiple published fresh frozen tissue microarray-based prognostic gene signatures for colon cancer, and we used this platform to systematically compare gene expression data from FFPE with matched microarray array data from frozen tissues. Our results show moderate correlation of gene expression between two platforms and discovery of a small subset of genes as candidate biomarkers for colon cancer prognosis that are detectable and quantifiable in FFPE tissue sections. PMID:27176004

  19. Emergent FDA biodefense issues for microarray technology: process analytical technology.

    PubMed

    Weinberg, Sandy

    2004-11-01

    A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver.

  20. Enzyme Microarrays Assembled by Acoustic Dispensing Technology

    PubMed Central

    Wong, E. Y.; Diamond, S. L.

    2008-01-01

    Miniaturizing bioassays to the nanoliter scale for high-throughput screening reduces the consumption of reagents that are expensive or difficult to handle. Utilizing acoustic dispensing technology, nanodroplets containing 10 µM ATP (3 µCi/µL 32P) and reaction buffer in 10% glycerol were positionally dispensed to the surface of glass slides to form 40 nL compartments (100 droplets/slide) for Pim1 (Proviral integration site 1) kinase reactions. The reactions were activated by dispensing 4 nL of various levels of a pyridocarbazolo-cyclopentadienyl ruthenium-complex Pim1 inhibitor, followed by dispensing 4 nL of a Pim1 kinase and peptide substrate solution to achieve final concentrations of 150 nM enzyme and 10 µM substrate. The microarray was incubated at 30°C (97% Rh) for 1.5 hr. The spots were then blotted to phosphocellulose membranes to capture phosphorylated substrate. Using phosphor imaging to quantify the washed membranes, the assay showed that, for doses of inhibitor from 0.75 µM to 3 µM, Pim1 was increasingly inhibited. Signal-to-background ratios were as high as 165 and average coefficients of variation (CVs) for the assay were ~20%. CVs for dispensing typical working buffers were under 5%. Thus, microarrays assembled by acoustic dispensing are promising as cost-effective tools that can be used in protein assay development. PMID:18616925

  1. Surface free energy and microarray deposition technology.

    PubMed

    McHale, Glen

    2007-03-01

    Microarray techniques use a combinatorial approach to assess complex biochemical interactions. The fundamental goal is simultaneous, large-scale experimentation analogous to the automation achieved in the semiconductor industry. However, microarray deposition inherently involves liquids contacting solid substrates. Liquid droplet shapes are determined by surface and interfacial tension forces, and flows during drying. This article looks at how surface free energy and wetting considerations may influence the accuracy and reliability of spotted microarray experiments.

  2. New technologies for fabricating biological microarrays

    NASA Astrophysics Data System (ADS)

    Larson, Bradley James

    This dissertation contains the description of two technologies that we have developed to reduce the cost and improve the quality of spotted biological microarrays. The first is a device, called a fluid microplotter, that uses ultrasonics to deposit spots with diameters of less than 5 microns. It consists of a dispenser, composed of a micropipette fastened to a piece of PZT piezoelectric, attached to a precision positioning system. A gentle pumping of fluid to the surface occurs when the micropipette is driven at specific frequencies. Spots or continuous lines can be deposited in this manner. The small fluid features conserve expensive and limited-quantity biological reagents. We characterize the performance of the microplotter in depositing fluid and examine the theoretical underpinnings of its operation. We present an analytical expression for the diameter of a deposited spot as a function of droplet volume and wettability of a surface and compare it with experimental results. We also examine the resonant properties of the piezoelectric element used to drive the dispenser and relate that to the frequencies at which pumping occurs. Finally, we propose a mechanism to explain the pumping behavior within the microplotter dispenser. The second technology we present is a process that uses a cold plasma and a subsequent in vacuo vapor-phase reaction to terminate a variety of oxide surfaces with epoxide chemical groups. These epoxide groups can react with amine-containing biomolecules to form strong covalent linkages between the biomolecules and the treated surface. The use of a plasma activation step followed by an in vacuo vapor-phase reaction allows for the precise control of surface functional groups, rather than the mixture of functionalities normally produced. This process modifies a range of different oxide surfaces, is fast, consumes a minimal amount of reagents, and produces attachment densities for bound biomolecules that are comparable to or better than

  3. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

    Microarrays are revolutionizing genetics by making it possible to genotype hundreds of thousands of DNA markers and to assess the expression (RNA transcripts) of all of the genes in the genome. Microarrays are slides the size of a postage stamp that contain millions of DNA sequences to which single-stranded DNA or RNA can hybridize. This…

  4. DNA microarray technology for target identification and validation.

    PubMed

    Jayapal, Manikandan; Melendez, Alirio J

    2006-01-01

    1. Microarrays, a recent development, provide a revolutionary platform to analyse thousands of genes at once. They have enormous potential in the study of biological processes in health and disease and, perhaps, microarrays have become crucial tools in diagnostic applications and drug discovery. 2. Microarray based studies have provided the essential impetus for biomedical experiments, such as identification of disease-causing genes in malignancies and regulatory genes in the cell cycle mechanism. Microarrays can identify genes for new and unique potential drug targets, predict drug responsiveness for individual patients and, finally, initiate gene therapy and prevention strategies. 3. The present article reviews the principles and technological concerns, as well as the steps involved in obtaining and analysing of data. Furthermore, applications of microarray based experiments in drug target identifications and validation strategies are discussed. 4. To exemplify how this tool can be useful, in the present review we provide an overview of some of the past and potential future aspects of microarray technology and present a broad overview of this rapidly growing field.

  5. DNA microarray technology in nutraceutical and food safety.

    PubMed

    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.

  6. Application of Tissue Microarray Technology to Stem Cell Research

    PubMed Central

    Spada, Alberto La; Rainoldi, Barnaba; Blasio, Andrea De; Biunno, Ida

    2014-01-01

    There is virtually an unlimited number of possible Tissue Microarray (TMA) applications in basic and clinical research and ultimately in diagnostics. However, to assess the functional importance of novel markers, researchers very often turn to cell line model systems. The appropriate choice of a cell line is often a difficult task, but the use of cell microarray (CMA) technology enables a quick screening of several markers in cells of different origins, mimicking a genomic-scale analysis. In order to improve the morphological evaluations of the CMA slides we harvested the cells by conventional trypsinization, mechanical scraping and cells grown on coverslips. We show that mechanical scraping is a good evaluation method since keeps the real morphology very similar to those grown on coverslips. Immunofluorescence images are of higher quality, facilitating the reading of the biomarker cellular and subcellular localization. Here, we describe CMA technology in stem cell research.

  7. Impact of microarray technology in nutrition and food research.

    PubMed

    Spielbauer, Bettina; Stahl, Frank

    2005-10-01

    Microarrays have become standard tools for gene expression profiling as the mRNA levels of a large number of genes can be measured in a single assay. Many technical aspects concerning microarray production and laboratory usage have been addressed in great detail, but it remains still crucial to establish this technology in new research fields such as human nutrition and food-related areas. The correlation between diet and inter-individual variation in gene expression is an important and relatively unexplored issue in human nutrition. Therefore, nutritionists changed their research field dramatically from epidemiology and physiology towards the "omics" sciences. Nutrigenomics as a field of research is based on the complete knowledge of the human genome and refers to the entire spectrum of human genes that determine the interactions of nutrition with the organism. Nutrigenetics is based on the inter-individual, genetically determined differences in metabolism. Nutrigenomics and nutrigenetics carry the hope that individualized diet can improve human health and prevent nutrition-related diseases. In this article we give an overview of current DNA and protein microarray techniques (including fabrication, experimental procedure and data analysis), we describe their applications to nutrition and food research and point out the limitations, problems and pitfalls of microarray experiments. PMID:16189797

  8. The emergence and diffusion of DNA microarray technology

    PubMed Central

    Lenoir, Tim; Giannella, Eric

    2006-01-01

    The network model of innovation widely adopted among researchers in the economics of science and technology posits relatively porous boundaries between firms and academic research programs and a bi-directional flow of inventions, personnel, and tacit knowledge between sites of university and industry innovation. Moreover, the model suggests that these bi-directional flows should be considered as mutual stimulation of research and invention in both industry and academe, operating as a positive feedback loop. One side of this bi-directional flow – namely; the flow of inventions into industry through the licensing of university-based technologies – has been well studied; but the reverse phenomenon of the stimulation of university research through the absorption of new directions emanating from industry has yet to be investigated in much detail. We discuss the role of federal funding of academic research in the microarray field, and the multiple pathways through which federally supported development of commercial microarray technologies have transformed core academic research fields. Our study confirms the picture put forward by several scholars that the open character of networked economies is what makes them truly innovative. In an open system innovations emerge from the network. The emergence and diffusion of microarray technologies we have traced here provides an excellent example of an open system of innovation in action. Whether they originated in a startup company environment that operated like a think-tank, such as Affymax, the research labs of a large firm, such as Agilent, or within a research university, the inventors we have followed drew heavily on knowledge resources from all parts of the network in bringing microarray platforms to light. Federal funding for high-tech startups and new industrial development was important at several phases in the early history of microarrays, and federal funding of academic researchers using microarrays was fundamental

  9. 2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology

    EPA Science Inventory

    Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution and transformation, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. Th...

  10. Rawcopy: Improved copy number analysis with Affymetrix arrays

    PubMed Central

    Mayrhofer, Markus; Viklund, Björn; Isaksson, Anders

    2016-01-01

    Microarray data is subject to noise and systematic variation that negatively affects the resolution of copy number analysis. We describe Rawcopy, an R package for processing of Affymetrix CytoScan HD, CytoScan 750k and SNP 6.0 microarray raw intensities (CEL files). Noise characteristics of a large number of reference samples are used to estimate log ratio and B-allele frequency for total and allele-specific copy number analysis. Rawcopy achieves better signal-to-noise ratio and higher proportion of validated alterations than commonly used free and proprietary alternatives. In addition, Rawcopy visualizes each microarray sample for assessment of technical quality, patient identity and genome-wide absolute copy number states. Software and instructions are available at http://rawcopy.org. PMID:27796336

  11. Resequencing Microarray Technology for Genotyping Human Papillomavirus in Cervical Smears

    PubMed Central

    Berthet, Nicolas; Falguières, Michael; Filippone, Claudia; Bertolus, Chloé; Bole-Feysot, Christine; Brisse, Sylvain; Gessain, Antoine; Heard, Isabelle; Favre, Michel

    2014-01-01

    There are more than 40 human papillomaviruses (HPVs) belonging to the alpha genus that cause sexually transmitted infections; these infections are among the most frequent and can lead to condylomas and anogenital intra-epithelial neoplasia. At least 18 of these viruses are causative agents of anogenital carcinomas. We evaluated the performance of a resequencing microarray for the detection and genotyping of alpha HPV of clinical significance using cloned HPV DNA. To reduce the number of HPV genotypes tiled on microarray, we used reconstructed ancestral sequences (RASs) as they are more closely related to the various genotypes than the current genotypes are among themselves. The performance of this approach was tested by genotyping with a set of 40 cervical smears already genotyped using the commercial PapilloCheck kit. The results of the two tests were concordant for 70% (28/40) of the samples and compatible for 30% (12/40). Our findings indicate that RASs were able to detect and identify one or several HPV in clinical samples. Associating RASs with homonym sequences improved the genotyping of HPV present in cases of multiple infection. In conclusion, we demonstrate the diagnostic potential of resequencing technology for genotyping of HPV, and illustrate its value both for epidemiological studies and for monitoring the distribution of HPV in the post-vaccination era. PMID:25383888

  12. An ultralow background substrate for protein microarray technology.

    PubMed

    Feng, Hui; Zhang, Qingyang; Ma, Hongwei; Zheng, Bo

    2015-08-21

    We herein report an ultralow background substrate for protein microarrays. Conventional protein microarray substrates often suffer from non-specific protein adsorption and inhomogeneous spot morphology. Consequently, surface treatment and a suitable printing solution are required to improve the microarray performance. In the current work, we improved the situation by developing a new microarray substrate based on a fluorinated ethylene propylene (FEP) membrane. A polydopamine microspot array was fabricated on the FEP membrane, with proteins conjugated to the FEP surface through polydopamine. Uniform microspots were obtained on FEP without the application of a special printing solution. The modified FEP membrane demonstrated ultralow background signal and was applied in protein and peptide microarray analysis. PMID:26134063

  13. Application of Phenotype Microarray technology to soil microbiology

    NASA Astrophysics Data System (ADS)

    Mocali, Stefano

    2016-04-01

    It is well established that soil microorganisms are extremely diverse and only a small fraction has been successfully cultured in the laboratory. Furthermore, addressing the functionality of genomes is one of the most important and challenging tasks of today's biology. In particular the ability to link genotypes to corresponding phenotypes is of interest in the reconstruction and biotechnological manipulation of metabolic pathways. High-throughput culture in micro wells provides a method for rapid screening of a wide variety of growth conditions and commercially available plates contain a large number of substrates, nutrient sources, and inhibitors, which can provide an assessment of the phenotype of an organism. Thus, over the last years, Phenotype Microarray (PM) technology has been used to address many specific issues related to the metabolic functionality of microorganisms. However, computational tools that could directly link PM data with the gene(s) of interest followed by the extraction of information on gene-phenotype correlation are still missing. Here potential applications of phenotype arrays to soil microorganisms, use of the plates in stress response studies and for assessment of phenotype of environmental communities are described. Considerations and challenges in data interpretation and visualization, including data normalization, statistics, and curve fitting are also discussed. In particular, here we present DuctApe, a suite that allows the analysis of both genomic sequences and PM data, to find metabolic differences among PM experiments and to correlate them with KEGG pathways and gene presence/absence patterns.

  14. Using probe secondary structure information to enhance Affymetrix GeneChip background estimates

    PubMed Central

    Gharaibeh, Raad Z.; Fodor, Anthony A.; Gibas, Cynthia J.

    2007-01-01

    High-density short oligonucleotide microarrays are a primary research tool for assessing global gene expression. Background noise on microarrays comprises a significant portion of the measured raw data. A number of statistical techniques have been developed to correct for this background noise. Here, we demonstrate that probe minimum folding energy and structure can be used to enhance a previously existing model for background noise correction. We estimate that probe secondary structure accounts for up to 3% of all variation on Affymetrix microarrays. PMID:17387043

  15. MICROARRAY QUALITY CONTROL PROJECT: A COMPREHENSIVE GENE EXPRESSION TECHNOLOGY SURVEY DEMONSTRATES MEASURABLE CONSISTENCY AND CONCORDANT RESULTS BETWEEN PLATFORMS

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, h...

  16. Making a new technology work: the standardization and regulation of microarrays.

    PubMed

    Rogers, Susan; Cambrosio, Alberto

    2007-12-01

    The translation of laboratory innovations into clinical tools is dependent upon the development of regulatory arrangements designed to ensure that the new technology will be used reliably and consistently. A case study of a key post-genomic technology, gene chips or microarrays, exemplifies this claim. The number of microarray publications and patents has increased exponentially during the last decade and diagnostic microarray tests already are making their way into the clinic. Yet starting in the mid-1990s, scientific journals were overrun with criticism concerning the ambiguities involved in interpreting most of the assumptions of a microarray experiment. Questions concerning platform comparability and statistical calculations were and continue to be raised, in spite of the emergence by 2001 of an initial set of standards concerning several components of a microarray experiment. This article probes the history and ongoing efforts aimed at turning microarray experimentation into a viable, meaningful, and consensual technology by focusing on two related elements:1) The history of the development of the Microarray Gene Expression Data Society (MGED), a remarkable bottom-up initiative that brings together different kinds of specialists from academic, commercial, and hybrid settings to produce, maintain, and update microarray standards; and 2) The unusual mix of skills and expertise involved in the development and use of microarrays. The production, accumulation, storage, and mining of microarray data remain multi-skilled endeavors bridging together different types of scientists who embody a diversity of scientific traditions. Beyond standardization, the interfacing of these different skills has become a key issue for further development of the field. PMID:18449388

  17. Making a new technology work: the standardization and regulation of microarrays.

    PubMed

    Rogers, Susan; Cambrosio, Alberto

    2007-12-01

    The translation of laboratory innovations into clinical tools is dependent upon the development of regulatory arrangements designed to ensure that the new technology will be used reliably and consistently. A case study of a key post-genomic technology, gene chips or microarrays, exemplifies this claim. The number of microarray publications and patents has increased exponentially during the last decade and diagnostic microarray tests already are making their way into the clinic. Yet starting in the mid-1990s, scientific journals were overrun with criticism concerning the ambiguities involved in interpreting most of the assumptions of a microarray experiment. Questions concerning platform comparability and statistical calculations were and continue to be raised, in spite of the emergence by 2001 of an initial set of standards concerning several components of a microarray experiment. This article probes the history and ongoing efforts aimed at turning microarray experimentation into a viable, meaningful, and consensual technology by focusing on two related elements:1) The history of the development of the Microarray Gene Expression Data Society (MGED), a remarkable bottom-up initiative that brings together different kinds of specialists from academic, commercial, and hybrid settings to produce, maintain, and update microarray standards; and 2) The unusual mix of skills and expertise involved in the development and use of microarrays. The production, accumulation, storage, and mining of microarray data remain multi-skilled endeavors bridging together different types of scientists who embody a diversity of scientific traditions. Beyond standardization, the interfacing of these different skills has become a key issue for further development of the field.

  18. Systematic review of accuracy of prenatal diagnosis for abnormal chromosome diseases by microarray technology.

    PubMed

    Xu, H B; Yang, H; Liu, G; Chen, H

    2014-10-31

    The accuracy of prenatal diagnosis for abnormal chromosome diseases by chromosome microarray technology and karyotyping were compared. A literature search was carried out in the MEDLINE database with the keywords "chromosome" and "karyotype" and "genetic testing" and "prenatal diagnosis" and "oligonucleotide array sequence". The studies obtained were filtered by using the QUADAS tool, and studies conforming to the quality standard were fully analyzed. There was one paper conforming to the QUADAS standards including 4406 gravidas with adaptability syndromes of prenatal diagnosis including elderly parturient women, abnormal structure by type-B ultrasound, and other abnormalities. Microarray technology yielded successful diagnoses in 4340 cases (98.8%), and there was no need for tissue culture in 87.9% of the samples. All aneuploids and non-parallel translocations in 4282 cases of non-chimera identified by karyotyping could be detected using microarray analysis technology, whereas parallel translocations and fetal triploids could not be detected by microarray analysis technology. In the samples with normal karyotyping results, type-B ultrasound showed that 6% of chromosomal deficiencies or chromosome duplications could be detected by microarray technology, and the same abnormal chromosomes were detected in 1.7% of elderly parturient women and samples with positive serology screening results. In the prenatal diagnosis test, compared with karyotyping, microarray technology could identify the extra cell genetic information with clinical significance, aneuploids, and non-parallel translocations; however, its disadvantage is that it could not identify parallel translocations and triploids.

  19. MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

    PubMed Central

    Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

    2006-01-01

    Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and

  20. Low-density microarray technologies for rapid human norovirus genotyping

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Human noroviruses cause up to 21 million cases of foodborne disease in the United States annually and are the most common cause of acute gastroenteritis in industrialized countries. To reduce the burden of foodborne disease associated with viruses, the use of low density DNA microarrays in conjuncti...

  1. inSilicoDb: an R/Bioconductor package for accessing human Affymetrix expert-curated datasets from GEO.

    PubMed

    Taminau, Jonatan; Steenhoff, David; Coletta, Alain; Meganck, Stijn; Lazar, Cosmin; de Schaetzen, Virginie; Duque, Robin; Molter, Colin; Bersini, Hugues; Nowé, Ann; Weiss Solís, David Y

    2011-11-15

    Microarray technology has become an integral part of biomedical research and increasing amounts of datasets become available through public repositories. However, re-use of these datasets is severely hindered by unstructured, missing or incorrect biological samples information; as well as the wide variety of preprocessing methods in use. The inSilicoDb R/Bioconductor package is a command-line front-end to the InSilico DB, a web-based database currently containing 86 104 expert-curated human Affymetrix expression profiles compiled from 1937 GEO repository series. The use of this package builds on the Bioconductor project's focus on reproducibility by enabling a clear workflow in which not only analysis, but also the retrieval of verified data is supported.

  2. Perspectives of DNA microarray and next-generation DNA sequencing technologies.

    PubMed

    Teng, XiaoKun; Xiao, HuaSheng

    2009-01-01

    DNA microarray and next-generation DNA sequencing technologies are important tools for high-throughput genome research, in revealing both the structural and functional characteristics of genomes. In the past decade the DNA microarray technologies have been widely applied in the studies of functional genomics, systems biology and pharmacogenomics. The next-generation DNA sequencing method was first introduced by the 454 Company in 2003, immediately followed by the establishment of the Solexa and Solid techniques by other biotech companies. Though it has not been long since the first emergence of this technology, with the fast and impressive improvement, the application of this technology has extended to almost all fields of genomics research, as a rival challenging the existing DNA microarray technology. This paper briefly reviews the working principles of these two technologies as well as their application and perspectives in genome research.

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

    SciTech Connect

    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.

  4. Tiling Microarray Analysis Tools

    SciTech Connect

    Nix, Davis Austin

    2005-05-04

    TiMAT is a package of 23 command line Java applications for use in the analysis of Affymetrix tiled genomic microarray data. TiMAT enables: 1) Rebuilding the genome annotation for entire tiled arrays (repeat filtering, chromosomal coordinate assignment). 2) Post processing of oligo intensity values (quantile normalization, median scaling, PMMM transformation), 3) Significance testing (Wilcoxon rank sum and signed rank tests, intensity difference and ratio tests) and Interval refinement (filtering based on multiple statistics, overlap comparisons), 4) Data visualization (detailed thumbnail/zoomed view with Interval Plots and data export to Affymetrix's Integrated Genome Browser) and Data reports (spreadsheet summaries and detailed profiles)

  5. Interactome Mapping: Using Protein Microarray Technology to Reconstruct Diverse Protein Networks

    PubMed Central

    Uzoma, Ijeoma; Zhu, Heng

    2013-01-01

    A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein–DNA interactions, posttranslational protein modifications (PTMs), lectin–glycan recognition, pathogen–host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier. PMID:23395178

  6. Microarray technology to investigate genes associated with papillary thyroid carcinoma.

    PubMed

    Zhu, Xinyong; Yao, Jing; Tian, Wen

    2015-05-01

    DNA microarray data on thyroid tissue from patients with papillary thyroid carcinoma (PTC) and from healthy controls were compared in order to investigate the regulatory genes and uncover the underlying regulatory network in PTC. The DNA microarray data set, GSE3678, was downloaded from Gene Expression Omnibus database. This included seven thyroid tissue samples from patients with PTC and seven samples from healthy controls. Raw data were processed and differentially expressed genes (DEGs) were identified using corresponding R packages. Gene regulation analysis was conducted using TRANSFAC® and TRED. A total of 171 DEGs were obtained. A regulatory network was then established, using 104 of the DEGs. Subsequently, pathway enrichment analyses of the genes were conducted using Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. Three differentially expressed transcription factors were identified: Trefoil factor 3, cut‑like homeobox 2 and forkhead box protein A2. The most significant pathways involving the 104 DEGs were pathways involved in cancer. Biological process analysis using DAVID, suggested that these genes were associated with the positive regulation of gene expression, gene transcription and metabolic processes. The present study identified a range of genes associated with the development of PTC. The results of the present study were beneficial for understanding the regulatory mechanisms involved in PTC, and for developing clinical diagnostic and therapeutic approaches for this disease.

  7. Development and Validation of Protein Microarray Technology for Simultaneous Inflammatory Mediator Detection in Human Sera

    PubMed Central

    Negm, Ola H.; Hamed, Mohamed R.; Tubby, Carolyn; Todd, Ian; Tighe, Patrick J.; Harrison, Tim; Fairclough, Lucy C.

    2014-01-01

    Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA) guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL-) 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the “gold standard” ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays. PMID:25382942

  8. MADS+: discovery of differential splicing events from Affymetrix exon junction array data

    PubMed Central

    Shen, Shihao; Warzecha, Claude C.; Carstens, Russ P.; Xing, Yi

    2010-01-01

    Motivation: The Affymetrix Human Exon Junction Array is a newly designed high-density exon-sensitive microarray for global analysis of alternative splicing. Contrary to the Affymetrix exon 1.0 array, which only contains four probes per exon and no probes for exon–exon junctions, this new junction array averages eight probes per probeset targeting all exons and exon–exon junctions observed in the human mRNA/EST transcripts, representing a significant increase in the probe density for alternative splicing events. Here, we present MADS+, a computational pipeline to detect differential splicing events from the Affymetrix exon junction array data. For each alternative splicing event, MADS+ evaluates the signals of probes targeting competing transcript isoforms to identify exons or splice sites with different levels of transcript inclusion between two sample groups. MADS+ is used routinely in our analysis of Affymetrix exon junction arrays and has a high accuracy in detecting differential splicing events. For example, in a study of the novel epithelial-specific splicing regulator ESRP1, MADS+ detects hundreds of exons whose inclusion levels are dependent on ESRP1, with a RT-PCR validation rate of 88.5% (153 validated out of 173 tested). Availability: MADS+ scripts, documentations and annotation files are available at http://www.medicine.uiowa.edu/Labs/Xing/MADSplus/. Contact: yi-xing@uiowa.edu PMID:19933160

  9. Using semantic web technologies to annotate and align microarray designs.

    PubMed

    Szpakowski, Sebastian; McCusker, James; Krauthammer, Michael

    2009-01-01

    In this paper, we annotate and align two different gene expression microarray designs using the Genomic ELement Ontology (GELO). GELO is a new ontology that leverages an existing community resource, Sequence Ontology (SO), to create views of genomically-aligned data in a semantic web environment. We start the process by mapping array probes to genomic coordinates. The coordinates represent an implicit link between the probes and multiple genomic elements, such as genes, transcripts, miRNA, and repetitive elements, which are represented using concepts in SO. We then use the RDF Query Language (SPARQL) to create explicit links between the probes and the elements. We show how the approach allows us to easily determine the element coverage and genomic overlap of the two array designs. We believe that the method will ultimately be useful for integration of cancer data across multiple omic studies. The ontology and other materials described in this paper are available at http://krauthammerlab.med.yale.edu/wiki/Gelo.

  10. An overview of innovations and industrial solutions in Protein Microarray Technology.

    PubMed

    Gupta, Shabarni; Manubhai, K P; Kulkarni, Vishwesh; Srivastava, Sanjeeva

    2016-04-01

    The complexity involving protein array technology reflects in the fact that instrumentation and data analysis are subject to change depending on the biological question, technical compatibility of instruments and software used in each experiment. Industry has played a pivotal role in establishing standards for future deliberations in sustenance of these technologies in the form of protein array chips, arrayers, scanning devices, and data analysis software. This has enhanced the outreach of protein microarray technology to researchers across the globe. These have encouraged a surge in the adaptation of "nonclassical" approaches such as DNA-based protein arrays, micro-contact printing, label-free protein detection, and algorithms for data analysis. This review provides a unique overview of these industrial solutions available for protein microarray based studies. It aims at assessing the developments in various commercial platforms, thus providing a holistic overview of various modalities, options, and compatibility; summarizing the journey of this powerful high-throughput technology. PMID:27089056

  11. Technical Advances of the Recombinant Antibody Microarray Technology Platform for Clinical Immunoproteomics

    PubMed Central

    Delfani, Payam; Dexlin Mellby, Linda; Nordström, Malin; Holmér, Andreas; Ohlsson, Mattias; Borrebaeck, Carl A. K.; Wingren, Christer

    2016-01-01

    In the quest for deciphering disease-associated biomarkers, high-performing tools for multiplexed protein expression profiling of crude clinical samples will be crucial. Affinity proteomics, mainly represented by antibody-based microarrays, have during recent years been established as a proteomic tool providing unique opportunities for parallelized protein expression profiling. But despite the progress, several main technical features and assay procedures remains to be (fully) resolved. Among these issues, the handling of protein microarray data, i.e. the biostatistics parts, is one of the key features to solve. In this study, we have therefore further optimized, validated, and standardized our in-house designed recombinant antibody microarray technology platform. To this end, we addressed the main remaining technical issues (e.g. antibody quality, array production, sample labelling, and selected assay conditions) and most importantly key biostatistics subjects (e.g. array data pre-processing and biomarker panel condensation). This represents one of the first antibody array studies in which these key biostatistics subjects have been studied in detail. Here, we thus present the next generation of the recombinant antibody microarray technology platform designed for clinical immunoproteomics. PMID:27414037

  12. Technical Advances of the Recombinant Antibody Microarray Technology Platform for Clinical Immunoproteomics.

    PubMed

    Delfani, Payam; Dexlin Mellby, Linda; Nordström, Malin; Holmér, Andreas; Ohlsson, Mattias; Borrebaeck, Carl A K; Wingren, Christer

    2016-01-01

    In the quest for deciphering disease-associated biomarkers, high-performing tools for multiplexed protein expression profiling of crude clinical samples will be crucial. Affinity proteomics, mainly represented by antibody-based microarrays, have during recent years been established as a proteomic tool providing unique opportunities for parallelized protein expression profiling. But despite the progress, several main technical features and assay procedures remains to be (fully) resolved. Among these issues, the handling of protein microarray data, i.e. the biostatistics parts, is one of the key features to solve. In this study, we have therefore further optimized, validated, and standardized our in-house designed recombinant antibody microarray technology platform. To this end, we addressed the main remaining technical issues (e.g. antibody quality, array production, sample labelling, and selected assay conditions) and most importantly key biostatistics subjects (e.g. array data pre-processing and biomarker panel condensation). This represents one of the first antibody array studies in which these key biostatistics subjects have been studied in detail. Here, we thus present the next generation of the recombinant antibody microarray technology platform designed for clinical immunoproteomics.

  13. DMET-Analyzer: automatic analysis of Affymetrix DMET Data

    PubMed Central

    2012-01-01

    Background Clinical Bioinformatics is currently growing and is based on the integration of clinical and omics data aiming at the development of personalized medicine. Thus the introduction of novel technologies able to investigate the relationship among clinical states and biological machineries may help the development of this field. For instance the Affymetrix DMET platform (drug metabolism enzymes and transporters) is able to study the relationship among the variation of the genome of patients and drug metabolism, detecting SNPs (Single Nucleotide Polymorphism) on genes related to drug metabolism. This may allow for instance to find genetic variants in patients which present different drug responses, in pharmacogenomics and clinical studies. Despite this, there is currently a lack in the development of open-source algorithms and tools for the analysis of DMET data. Existing software tools for DMET data generally allow only the preprocessing of binary data (e.g. the DMET-Console provided by Affymetrix) and simple data analysis operations, but do not allow to test the association of the presence of SNPs with the response to drugs. Results We developed DMET-Analyzer a tool for the automatic association analysis among the variation of the patient genomes and the clinical conditions of patients, i.e. the different response to drugs. The proposed system allows: (i) to automatize the workflow of analysis of DMET-SNP data avoiding the use of multiple tools; (ii) the automatic annotation of DMET-SNP data and the search in existing databases of SNPs (e.g. dbSNP), (iii) the association of SNP with pathway through the search in PharmaGKB, a major knowledge base for pharmacogenomic studies. DMET-Analyzer has a simple graphical user interface that allows users (doctors/biologists) to upload and analyse DMET files produced by Affymetrix DMET-Console in an interactive way. The effectiveness and easy use of DMET Analyzer is demonstrated through different case studies regarding

  14. AMDA 2.13: A major update for automated cross-platform microarray data analysis.

    PubMed

    Kapetis, Dimos; Clarelli, Ferdinando; Vitulli, Federico; de Rosbo, Nicole Kerlero; Beretta, Ottavio; Foti, Maria; Ricciardi-Castagnoli, Paola; Zolezzi, Francesca

    2012-07-01

    Microarray platforms require analytical pipelines with modules for data pre-processing including data normalization, statistical analysis for identification of differentially expressed genes, cluster analysis, and functional annotation. We previously developed the Automated Microarray Data Analysis (AMDA, version 2.3.5) pipeline to process Affymetrix 3' IVT GeneChips. The availability of newer technologies that demand open-source tools for microarray data analysis has impelled us to develop an updated multi-platform version, AMDA 2.13. It includes additional quality control metrics, annotation-driven (annotation grade of Affymetrix NetAffx) and signal-driven (Inter-Quartile Range) gene filtering, and approaches to experimental design. To enhance understanding of biological data, differentially expressed genes have been mapped into KEGG pathways. Finally, a more stable and user-friendly interface was designed to integrate the requirements for different platforms. AMDA 2.13 allows the analysis of Affymetrix (cartridges and plates) and whole transcript probe design (Gene 1.0/1.1 ST and Exon 1.0 ST GeneChips), Illumina Bead Arrays, and one-channel Agilent 4×44 arrays. Relative to early versions, it supports various experimental designs and delivers more insightful biological understanding and up-to-date annotations.

  15. [The cell-free protein synthesis-based protein microarray technology].

    PubMed

    Lu, Linli; Lin, Bicheng

    2010-12-01

    The major bottle-neck in the way of constructing high density protein microarray is the availability and stability of proteins. The traditional methods of generating protein arrays require the in-vivo expression, purification and immobilization of hundreds or thousands of proteins. The cell-free protein array technology employs cell-free expression systems to produce proteins directly onto surface from co-distributed or pre-arrayed DNA or RNA, thus avoiding the laborious and often costly processes of protein preparation in the traditional approach. Here we provide an overview of recently developed novel technology in cell free based protein microarray and their applications in protein interaction analysis, in antibody specificity and vaccine screening, and in biomarker assay. PMID:21375003

  16. Microarray technology: an increasing variety of screening tools for proteomic research.

    PubMed

    Stoll, Dieter; Bachmann, Jutta; Templin, Markus F; Joos, Thomas O

    2004-12-15

    Protein microarray technology allows the simultaneous determination of a large variety of parameters from a minute amount of sample within a single experiment. Assay systems based on this technology are currently used for the identification, quantitation and functional analysis of proteins that are of interest for proteomic research in basic and applied biology and for diagnostic applications. Such novel assays are also of major interest for the pharmaceutical industry, focusing on the identification of biomarkers and the validation of potential target molecules. Sensitivity, reproducibility, robustness and automation have to be demonstrated before this technology will be suitable for high-throughput applications.

  17. Use of microarray technology to profile gene expression patterns important for reproduction in cattle.

    PubMed

    Evans, A C O; Forde, N; O'Gorman, G M; Zielak, A E; Lonergan, P; Fair, T

    2008-07-01

    Fertility in cattle is a major component of many agricultural enterprises and there is pressure to devise methods to improve this. A number of approaches are ongoing, one of which is to better understand the cellular and molecular events of the development of reproductive tissues and to use these as targets for developing new strategies. Microarray technologies now allow us the potential to determine the transcriptional profile of expressed genes in a given tissue. This review focuses on the types of microarrays available for studies in cattle and concludes that genes associated with one or more of the cellular processes of cell survival/death, intracellular signalling, transcription and translation, cell division and proliferation and cellular metabolism are the main transcriptional pathways that control the development of ovarian follicles, oocytes, early embryos and the uterine endometrium about the time of the establishment of pregnancy.

  18. Tiling Microarray Analysis Tools

    2005-05-04

    TiMAT is a package of 23 command line Java applications for use in the analysis of Affymetrix tiled genomic microarray data. TiMAT enables: 1) Rebuilding the genome annotation for entire tiled arrays (repeat filtering, chromosomal coordinate assignment). 2) Post processing of oligo intensity values (quantile normalization, median scaling, PMMM transformation), 3) Significance testing (Wilcoxon rank sum and signed rank tests, intensity difference and ratio tests) and Interval refinement (filtering based on multiple statistics, overlap comparisons),more » 4) Data visualization (detailed thumbnail/zoomed view with Interval Plots and data export to Affymetrix's Integrated Genome Browser) and Data reports (spreadsheet summaries and detailed profiles)« less

  19. Selective detection of live bacteria combining propidium monoazide sample treatment with microarray technology.

    PubMed

    Nocker, Andreas; Mazza, Alberto; Masson, Luke; Camper, Anne K; Brousseau, Roland

    2009-03-01

    The use of DNA-based molecular detection tools for bacterial diagnostics is hampered by the inability to distinguish signals originating from live and dead cells. The detection of live cells is typically most relevant in molecular diagnostics. DNA-intercalating dyes like ethidium monoazide and propidium monoazide (PMA) offer a possibility to selectively remove cells with compromised cell membranes from the analysis. Once these dyes enter a cell, they bind to DNA and can be covalently crosslinked to it by light exposure. PCR amplification of such modified DNA is strongly inhibited. In this study we evaluated the suitability of propidium monoazide treatment to exclude isopropanol-killed cells from detection in defined mixtures using diagnostic microarray technology. The organisms comprised Pseudomonas aeruginosa, Listeria monocytogenes, Salmonella typhimurium, Serratia marcescens, and Escherichia coli O157:H7. PCR products obtained from amplification of chaperonin 60 genes (cpn60; coding for GroEL) were hybridized to a custom-designed microarray containing strain-specific cpn60-based 35-mer oligonucleotide probes. Results were compared with data from quantitative PCR, which confirmed that PMA could successfully inhibit amplification of DNA from killed cells in the mixtures. Although microarray data based on analysis of end-point PCR amplicons is not quantitative, results showed a significant signal reduction when targeting killed cells and consistently agreed with qPCR results. Treatment of samples with PMA in combination with diagnostic microarray detection can therefore be considered beneficial when analyzing mixtures of intact and membrane-compromised cells. Minimization of detection signals deriving from dead cells will render data more relevant in studies including pathogen risk assessment.

  20. Microarray Analysis of Fluorescence Activated Cell Sorter-Derived Cells: Creating Harmony between Technologies

    PubMed Central

    Tighe, S.

    2011-01-01

    Although microarray technology is well-established in both the research and clinical fields, it continues to evolve into new areas that require new methods for the successful isolations of nucleic acid from non-traditional sources. Because RNA specifically is a labile molecule, special procedures and considerations must be implemented to avoid degradation from methods such as fluorescence activated cell sorting (FACS) and laser capture microdissection (LCM) to name a few. This presentation will discuss specific methodologies to maximize the success of nucleic acid recovery from these approaches including instrument preparation, extraction methods, and the use of special reagents to deal with problematic samples.

  1. Integrating data from heterogeneous DNA microarray platforms.

    PubMed

    Valente, Eduardo; Rocha, Miguel

    2015-01-01

    DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus. PMID:26673932

  2. ELISA microarray technology as a high-throughput system for cancer biomarker validation

    SciTech Connect

    Zangar, Richard C.; Daly, Don S.; White, Amanda M.

    2006-01-01

    A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue. Another major challenge with cancer screening is that most cancers are rare in the general population, meaning that the specificity of an assay must be very high if the number of false positive is not going to be much greater than the number of true positives. Because of these challenges with biomarker validation, it is necessary to analysis of thousands of samples before a clear idea of the utility of a screening assay can be determined. Enzyme-linked immunosorbent assay (ELISA) microarray technology can simultaneously quantify levels of multiple proteins and has the potential to accelerate biomarker validation. In this review, we discuss current ELISA microarray technology and the enabling advances needed to achieve the reproducibility and throughput that are required to evaluate cancer biomarkers.

  3. Potential use of microarray technology for rapid identification of central nervous system pathogens.

    PubMed

    Hanson, Eric H; Niemeyer, Debra M; Folio, Les; Agan, Brian K; Rowley, Robb K

    2004-08-01

    Outbreaks of central nervous system (CNS) diseases result in significant productivity and financial losses, threatening peace and wartime readiness capabilities. To meet this threat, rapid clinical diagnostic tools for detecting and identifying CNS pathogens are needed. Current tools and techniques cannot efficiently deal with CNS pathogen diversity; they cannot provide real-time identification of pathogen serogroups and strains, and they require days, sometimes weeks, for examination of tissue culture. Rapid and precise CNS pathogen diagnostics are needed to provide the opportunity for tailored therapeutic regimens and focused preventive efforts to decrease morbidity and mortality. Such diagnostics are available through genetic and genomic technologies, which have the potential for reducing the time required in serogroup or strain identification from 500+ hours for some viral cultures to less than 3 hours for all pathogens. In the near future, microarray diagnostics and future derivations of these technologies will change the paradigm used for outbreak investigations and will improve health care for all. PMID:15379069

  4. Quality Visualization of Microarray Datasets Using Circos

    PubMed Central

    Koch, Martin; Wiese, Michael

    2012-01-01

    Quality control and normalization is considered the most important step in the analysis of microarray data. At present there are various methods available for quality assessments of microarray datasets. However there seems to be no standard visualization routine, which also depicts individual microarray quality. Here we present a convenient method for visualizing the results of standard quality control tests using Circos plots. In these plots various quality measurements are drawn in a circular fashion, thus allowing for visualization of the quality and all outliers of each distinct array within a microarray dataset. The proposed method is intended for use with the Affymetrix Human Genome platform (i.e., GPL 96, GPL570 and GPL571). Circos quality measurement plots are a convenient way for the initial quality estimate of Affymetrix datasets that are stored in publicly available databases.

  5. Novel in silico technology in combination with microarrays: a state-of-the-art technology for allergy diagnosis and management?

    PubMed

    Melioli, Giovanni; Passalacqua, Giovanni; Canonica, Giorgio W

    2014-12-01

    'Allergen microarrays, in poly-sensitized allergic patients, represent a real value added in the accurate IgE profiling and in the identification of allergen(s) to administer for an effective allergen immunotherapy.' Allergen microarrays (AMA) were developed in the early 2000s to improve the diagnostic pathway of patients with allergic reactions. Nowadays, AMA are constituted by more than 100 different components (either purified or recombinant), representing genuine and cross-reacting molecules from plants and animals. The cost of the procedure had suggested its use as third-level diagnostics (following in vivo- and in vitro-specific IgE tests) in poly-sensitized patients. The complexity of the interpretation had inspired the development of in silico technologies to help clinicians in their work. Both machine learning techniques and expert systems are now available. In particular, an expert system that has been recently developed not only identifies positive and negative components but also lists dangerous components and classifies patients based on their potential responsiveness to allergen immunotherapy, on the basis of published algorithms. For these characteristics, AMA represents the state-of-the-art technology for allergy diagnosis in poly-sensitized patients.

  6. Improvements to previous algorithms to predict gene structure and isoform concentrations using Affymetrix Exon arrays

    PubMed Central

    2010-01-01

    Background Exon arrays provide a way to measure the expression of different isoforms of genes in an organism. Most of the procedures to deal with these arrays are focused on gene expression or on exon expression. Although the only biological analytes that can be properly assigned a concentration are transcripts, there are very few algorithms that focus on them. The reason is that previously developed summarization methods do not work well if applied to transcripts. In addition, gene structure prediction, i.e., the correspondence between probes and novel isoforms, is a field which is still unexplored. Results We have modified and adapted a previous algorithm to take advantage of the special characteristics of the Affymetrix exon arrays. The structure and concentration of transcripts -some of them possibly unknown- in microarray experiments were predicted using this algorithm. Simulations showed that the suggested modifications improved both specificity (SP) and sensitivity (ST) of the predictions. The algorithm was also applied to different real datasets showing its effectiveness and the concordance with PCR validated results. Conclusions The proposed algorithm shows a substantial improvement in the performance over the previous version. This improvement is mainly due to the exploitation of the redundancy of the Affymetrix exon arrays. An R-Package of SPACE with the updated algorithms have been developed and is freely available. PMID:21110835

  7. Evaluation of the Affymetrix CytoScan® Dx Assay for Developmental Delay

    PubMed Central

    Webb, Bryn D.; Scharf, Rebecca J.; Spear, Emily A.; Edelmann, Lisa J.; Stroustrup, Annemarie

    2015-01-01

    The goal of molecular cytogenetic testing for children presenting with developmental delay is to identify or exclude genetic abnormalities that are associated with cognitive, behavioral, and/or motor symptoms. Until 2010, chromosome analysis was the standard first-line genetic screening test for evaluation of patients with developmental delay when a specific syndrome was not suspected. In 2010, The American College of Medical Genetics and several other groups recommended chromosomal microarray (CMA) as the first-line test in children with developmental delays, multiple congenital anomalies, and/or autism. This test is able to detect regions of genomic imbalances at a much finer resolution than G-banded karyotyping. Until recently, no CMA testing had been approved by the United States Food and Drug Administration (FDA). This review will focus on the use of the Affymetrix CytoScan® Dx Assay, the first CMA to receive FDA approval for the genetic evaluation of individuals with developmental delay. PMID:25350348

  8. Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology.

    PubMed

    Strauß, Lena; Ruffing, Ulla; Abdulla, Salim; Alabi, Abraham; Akulenko, Ruslan; Garrine, Marcelino; Germann, Anja; Grobusch, Martin Peter; Helms, Volkhard; Herrmann, Mathias; Kazimoto, Theckla; Kern, Winfried; Mandomando, Inácio; Peters, Georg; Schaumburg, Frieder; von Müller, Lutz; Mellmann, Alexander

    2016-04-01

    Staphylococcus aureusis a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed anin silicotyping scheme for the software SeqSphere(+)(Ridom GmbH, Münster, Germany). The implemented target genes (n= 182) correspond to those queried by the IdentibacS. aureusGenotyping DNA microarray (Alere Technologies, Jena, Germany). Thein silicoscheme was evaluated by comparing the typing results of microarray and of WGS for 154 humanS. aureusisolates. A total of 96.8% (n= 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosomemecelement types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences.

  9. Detecting Staphylococcus aureus Virulence and Resistance Genes: a Comparison of Whole-Genome Sequencing and DNA Microarray Technology

    PubMed Central

    Strauß, Lena; Ruffing, Ulla; Abdulla, Salim; Alabi, Abraham; Akulenko, Ruslan; Garrine, Marcelino; Germann, Anja; Grobusch, Martin Peter; Helms, Volkhard; Herrmann, Mathias; Kazimoto, Theckla; Kern, Winfried; Mandomando, Inácio; Peters, Georg; Schaumburg, Frieder; von Müller, Lutz

    2016-01-01

    Staphylococcus aureus is a major bacterial pathogen causing a variety of diseases ranging from wound infections to severe bacteremia or intoxications. Besides host factors, the course and severity of disease is also widely dependent on the genotype of the bacterium. Whole-genome sequencing (WGS), followed by bioinformatic sequence analysis, is currently the most extensive genotyping method available. To identify clinically relevant staphylococcal virulence and resistance genes in WGS data, we developed an in silico typing scheme for the software SeqSphere+ (Ridom GmbH, Münster, Germany). The implemented target genes (n = 182) correspond to those queried by the Identibac S. aureus Genotyping DNA microarray (Alere Technologies, Jena, Germany). The in silico scheme was evaluated by comparing the typing results of microarray and of WGS for 154 human S. aureus isolates. A total of 96.8% (n = 27,119) of all typing results were equally identified with microarray and WGS (40.6% present and 56.2% absent). Discrepancies (3.2% in total) were caused by WGS errors (1.7%), microarray hybridization failures (1.3%), wrong prediction of ambiguous microarray results (0.1%), or unknown causes (0.1%). Superior to the microarray, WGS enabled the distinction of allelic variants, which may be essential for the prediction of bacterial virulence and resistance phenotypes. Multilocus sequence typing clonal complexes and staphylococcal cassette chromosome mec element types inferred from microarray hybridization patterns were equally determined by WGS. In conclusion, WGS may substitute array-based methods due to its universal methodology, open and expandable nature, and rapid parallel analysis capacity for different characteristics in once-generated sequences. PMID:26818676

  10. Tissue Microarrays.

    PubMed

    Dancau, Ana-Maria; Simon, Ronald; Mirlacher, Martina; Sauter, Guido

    2016-01-01

    Modern next-generation sequencing and microarray technologies allow for the simultaneous analysis of all human genes on the DNA, RNA, miRNA, and methylation RNA level. Studies using such techniques have lead to the identification of hundreds of genes with a potential role in cancer or other diseases. The validation of all of these candidate genes requires in situ analysis of high numbers of clinical tissues samples. The tissue microarray technology greatly facilitates such analysis. In this method minute tissue samples (typically 0.6 mm in diameter) from up to 1000 different tissues can be analyzed on one microscope glass slide. All in situ methods suitable for histological studies can be applied to TMAs without major changes of protocols, including immunohistochemistry, fluorescence in situ hybridization, or RNA in situ hybridization. Because all tissues are analyzed simultaneously with the same batch of reagents, TMA studies provide an unprecedented degree of standardization, speed, and cost efficiency.

  11. Chromosome Microarray.

    PubMed

    Anderson, Sharon

    2016-01-01

    Over the last half century, knowledge about genetics, genetic testing, and its complexity has flourished. Completion of the Human Genome Project provided a foundation upon which the accuracy of genetics, genomics, and integration of bioinformatics knowledge and testing has grown exponentially. What is lagging, however, are efforts to reach and engage nurses about this rapidly changing field. The purpose of this article is to familiarize nurses with several frequently ordered genetic tests including chromosomes and fluorescence in situ hybridization followed by a comprehensive review of chromosome microarray. It shares the complexity of microarray including how testing is performed and results analyzed. A case report demonstrates how this technology is applied in clinical practice and reveals benefits and limitations of this scientific and bioinformatics genetic technology. Clinical implications for maternal-child nurses across practice levels are discussed. PMID:27276104

  12. Manufacturing of microarrays.

    PubMed

    Petersen, David W; Kawasaki, Ernest S

    2007-01-01

    DNA microarray technology has become a powerful tool in the arsenal of the molecular biologist. Capitalizing on high precision robotics and the wealth of DNA sequences annotated from the genomes of a large number of organisms, the manufacture of microarrays is now possible for the average academic laboratory with the funds and motivation. Microarray production requires attention to both biological and physical resources, including DNA libraries, robotics, and qualified personnel. While the fabrication of microarrays is a very labor-intensive process, production of quality microarrays individually tailored on a project-by-project basis will help researchers shed light on future scientific questions.

  13. Advances in allergen-microarray technology for diagnosis and monitoring of allergy: the MeDALL allergen-chip.

    PubMed

    Lupinek, Christian; Wollmann, Eva; Baar, Alexandra; Banerjee, Srinita; Breiteneder, Heimo; Broecker, Barbara M; Bublin, Merima; Curin, Mirela; Flicker, Sabine; Garmatiuk, Tetiana; Hochwallner, Heidrun; Mittermann, Irene; Pahr, Sandra; Resch, Yvonne; Roux, Kenneth H; Srinivasan, Bharani; Stentzel, Sebastian; Vrtala, Susanne; Willison, Leanna N; Wickman, Magnus; Lødrup-Carlsen, Karin C; Antó, Josep Maria; Bousquet, Jean; Bachert, Claus; Ebner, Daniel; Schlederer, Thomas; Harwanegg, Christian; Valenta, Rudolf

    2014-03-01

    Allergy diagnosis based on purified allergen molecules provides detailed information regarding the individual sensitization profile of allergic patients, allows monitoring of the development of allergic disease and of the effect of therapies on the immune response to individual allergen molecules. Allergen microarrays contain a large variety of allergen molecules and thus allow the simultaneous detection of allergic patients' antibody reactivity profiles towards each of the allergen molecules with only minute amounts of serum. In this article we summarize recent progress in the field of allergen microarray technology and introduce the MeDALL allergen-chip which has been developed for the specific and sensitive monitoring of IgE and IgG reactivity profiles towards more than 170 allergen molecules in sera collected in European birth cohorts. MeDALL is a European research program in which allergen microarray technology is used for the monitoring of the development of allergic disease in childhood, to draw a geographic map of the recognition of clinically relevant allergens in different populations and to establish reactivity profiles which are associated with and predict certain disease manifestations. We describe technical advances of the MeDALL allergen-chip regarding specificity, sensitivity and its ability to deliver test results which are close to in vivo reactivity. In addition, the usefulness and numerous advantages of allergen microarrays for allergy research, refined allergy diagnosis, monitoring of disease, of the effects of therapies, for improving the prescription of specific immunotherapy and for prevention are discussed.

  14. VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

    NASA Technical Reports Server (NTRS)

    Moseyko, Nick; Feldman, Lewis J.

    2002-01-01

    SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu.

  15. A New Way to Introduce Microarray Technology in a Lecture/Laboratory Setting by Studying the Evolution of This Modern Technology

    ERIC Educational Resources Information Center

    Rowland-Goldsmith, Melissa

    2009-01-01

    DNA microarray is an ordered grid containing known sequences of DNA, which represent many of the genes in a particular organism. Each DNA sequence is unique to a specific gene. This technology enables the researcher to screen many genes from cells or tissue grown in different conditions. We developed an undergraduate lecture and laboratory…

  16. Facilitating functional annotation of chicken microarray data

    PubMed Central

    2009-01-01

    Background Modeling results from chicken microarray studies is challenging for researchers due to little functional annotation associated with these arrays. The Affymetrix GenChip chicken genome array, one of the biggest arrays that serve as a key research tool for the study of chicken functional genomics, is among the few arrays that link gene products to Gene Ontology (GO). However the GO annotation data presented by Affymetrix is incomplete, for example, they do not show references linked to manually annotated functions. In addition, there is no tool that facilitates microarray researchers to directly retrieve functional annotations for their datasets from the annotated arrays. This costs researchers amount of time in searching multiple GO databases for functional information. Results We have improved the breadth of functional annotations of the gene products associated with probesets on the Affymetrix chicken genome array by 45% and the quality of annotation by 14%. We have also identified the most significant diseases and disorders, different types of genes, and known drug targets represented on Affymetrix chicken genome array. To facilitate functional annotation of other arrays and microarray experimental datasets we developed an Array GO Mapper (AGOM) tool to help researchers to quickly retrieve corresponding functional information for their dataset. Conclusion Results from this study will directly facilitate annotation of other chicken arrays and microarray experimental datasets. Researchers will be able to quickly model their microarray dataset into more reliable biological functional information by using AGOM tool. The disease, disorders, gene types and drug targets revealed in the study will allow researchers to learn more about how genes function in complex biological systems and may lead to new drug discovery and development of therapies. The GO annotation data generated will be available for public use via AgBase website and will be updated on regular

  17. COMPARISON OF TRANSCRIPTIONAL RESONSES FROM AVIAN GUT TISSUES AFTER EIMERIA ACERVULINA AND E. MAXIMA INFECTIONS USING cDNA MICROARRAY TECHNOLOGY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Understanding the host response during pathogen infection will extend our knowledge of pathogenesis and enhance the development of novel preventive methodologies against important infectious diseases. Microarray technology is a powerful tool to analyze host transcriptional responses. Coccidiosis re...

  18. eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

    NASA Astrophysics Data System (ADS)

    Liu, Robin H.; Longiaru, Mathew

    2009-05-01

    DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

  19. High-throughput variation detection and genotyping using microarrays.

    PubMed

    Cutler, D J; Zwick, M E; Carrasquillo, M M; Yohn, C T; Tobin, K P; Kashuk, C; Mathews, D J; Shah, N A; Eichler, E E; Warrington, J A; Chakravarti, A

    2001-11-01

    The genetic dissection of complex traits may ultimately require a large number of SNPs to be genotyped in multiple individuals who exhibit phenotypic variation in a trait of interest. Microarray technology can enable rapid genotyping of variation specific to study samples. To facilitate their use, we have developed an automated statistical method (ABACUS) to analyze microarray hybridization data and applied this method to Affymetrix Variation Detection Arrays (VDAs). ABACUS provides a quality score to individual genotypes, allowing investigators to focus their attention on sites that give accurate information. We have applied ABACUS to an experiment encompassing 32 autosomal and eight X-linked genomic regions, each consisting of approximately 50 kb of unique sequence spanning a 100-kb region, in 40 humans. At sufficiently high-quality scores, we are able to read approximately 80% of all sites. To assess the accuracy of SNP detection, 108 of 108 SNPs have been experimentally confirmed; an additional 371 SNPs have been confirmed electronically. To access the accuracy of diploid genotypes at segregating autosomal sites, we confirmed 1515 of 1515 homozygous calls, and 420 of 423 (99.29%) heterozygotes. In replicate experiments, consisting of independent amplification of identical samples followed by hybridization to distinct microarrays of the same design, genotyping is highly repeatable. In an autosomal replicate experiment, 813,295 of 813,295 genotypes are called identically (including 351 heterozygotes); at an X-linked locus in males (haploid), 841,236 of 841,236 sites are called identically.

  20. Application of DNA microarray technology in determining breast cancer prognosis and therapeutic response.

    PubMed

    Brennan, Donal J; O'Brien, Sallyann L; Fagan, Ailís; Culhane, Aedín C; Higgins, Desmond G; Duffy, Michael J; Gallagher, William M

    2005-08-01

    There are > 1.15 million cases of breast cancer diagnosed worldwide annually, and it is the second leading cause of cancer death in the European Union. The optimum management of patients with breast cancer requires accurate prognostic and predictive factors. At present, only a small number of such factors are used clinically. DNA microarrays have the potential to measure the expression of tens of thousands of genes simultaneously. Recent preliminary findings suggest that DNA microarray-based gene expression profiling can provide powerful and independent prognostic information in patients with newly diagnosed breast cancer. As well as providing prognostic information, emerging results suggest that DNA microarrays can also be used for predicting response or resistance to treatment, especially to neoadjuvant chemotherapy. Prior to clinical application, these preliminary findings must be validated using large-scale prospective studies. This article reviews these advances and also examines the role of DNA microarrays in reducing the number of patients who receive inappropriate chemotherapy. The most recent data supporting the integration of various publicly available data sets is also reviewed in detail.

  1. Multivariate curve resolution for hyperspectral image analysis :applications to microarray technology.

    SciTech Connect

    Van Benthem, Mark Hilary; Sinclair, Michael B.; Haaland, David Michael; Martinez, M. Juanita (University of New Mexico, Albuquerque, NM); Timlin, Jerilyn Ann; Werner-Washburne, Margaret C. (University of New Mexico, Albuquerque, NM); Aragon, Anthony D. (University of New Mexico, Albuquerque, NM)

    2003-01-01

    Multivariate curve resolution (MCR) using constrained alternating least squares algorithms represents a powerful analysis capability for a quantitative analysis of hyperspectral image data. We will demonstrate the application of MCR using data from a new hyperspectral fluorescence imaging microarray scanner for monitoring gene expression in cells from thousands of genes on the array. The new scanner collects the entire fluorescence spectrum from each pixel of the scanned microarray. Application of MCR with nonnegativity and equality constraints reveals several sources of undesired fluorescence that emit in the same wavelength range as the reporter fluorphores. MCR analysis of the hyperspectral images confirms that one of the sources of fluorescence is due to contaminant fluorescence under the printed DNA spots that is spot localized. Thus, traditional background subtraction methods used with data collected from the current commercial microarray scanners will lead to errors in determining the relative expression of low-expressed genes. With the new scanner and MCR analysis, we generate relative concentration maps of the background, impurity, and fluorescent labels over the entire image. Since the concentration maps of the fluorescent labels are relatively unaffected by the presence of background and impurity emissions, the accuracy and useful dynamic range of the gene expression data are both greatly improved over those obtained by commercial microarray scanners.

  2. ChIP-on-chip analysis methods for Affymetrix tiling arrays.

    PubMed

    Yoder, Sean J

    2015-01-01

    Although the ChIP-sequencing has gained significant attraction recently, ChIP analysis using microarrays is still an attractive option due to the low cost, ease of analysis, and access to legacy and public data sets. The analysis of ChIP-Chip data entails a multistep approach that requires several different applications to progress from the initial stages of raw data analysis to the identification and characterization of ChIP binding sites. There are multiple approaches to data analysis and there are several applications available for each stage of the analysis pipeline. Each application must be evaluated for its suitability for the particular experiment as well as the investigator's background with computational tools. This chapter is a review of the commonly available applications for Affymetrix ChIP-Chip data analysis, as well as the general workflow of a ChIP-Chip analysis approach. The purpose of the chapter is to allow the researcher to better select the appropriate applications and provide them with the direction necessary to proceed with a ChIP-Chip analysis.

  3. Antibody Colocalization Microarray: A Scalable Technology for Multiplex Protein Analysis in Complex Samples*

    PubMed Central

    Pla-Roca, M.; Leulmi, R. F.; Tourekhanova, S.; Bergeron, S.; Laforte, V.; Moreau, E.; Gosline, S. J. C.; Bertos, N.; Hallett, M.; Park, M.; Juncker, D.

    2012-01-01

    DNA microarrays were rapidly scaled up from 256 to 6.5 million targets, and although antibody microarrays were proposed earlier, sensitive multiplex sandwich assays have only been scaled up to a few tens of targets. Cross-reactivity, arising because detection antibodies are mixed, is a known weakness of multiplex sandwich assays that is mitigated by lengthy optimization. Here, we introduce (1) vulnerability as a metric for assays. The vulnerability of multiplex sandwich assays to cross-reactivity increases quadratically with the number of targets, and together with experimental results, substantiates that scaling up of multiplex sandwich assays is unfeasible. We propose (2) a novel concept for multiplexing without mixing named antibody colocalization microarray (ACM). In ACMs, both capture and detection antibodies are physically colocalized by spotting to the same two-dimensional coordinate. Following spotting of the capture antibodies, the chip is removed from the arrayer, incubated with the sample, placed back onto the arrayer and then spotted with the detection antibodies. ACMs with up to 50 targets were produced, along with a binding curve for each protein. The ACM was validated by comparing it to ELISA and to a small-scale, conventional multiplex sandwich assay (MSA). Using ACMs, proteins in the serum of breast cancer patients and healthy controls were quantified, and six candidate biomarkers identified. Our results indicate that ACMs are sensitive, robust, and scalable. PMID:22171321

  4. Development and Use of Integrated Microarray-Based Genomic Technologies for Assessing Microbial Community Composition and Dynamics

    SciTech Connect

    Zhou, J.; Wu, L.; Gentry, T.; Schadt, C.; He, Z.; Li, X.

    2006-04-05

    different microbial communities and processes at the NABIR-FRC in Oak Ridge, TN. One project involves the monitoring of the development and dynamics of the microbial community of a fluidized bed reactor (FBR) used for reducing nitrate and the other project monitors microbial community responses to stimulation of uranium reducing populations via ethanol donor additions in situ and in a model system. Additionally, we are developing novel strategies for increasing microarray hybridization sensitivity. Finally, great improvements to our methods of probe design were made by the development of a new computer program, CommOligo. CommOligo designs unique and group-specific oligo probes for whole-genomes, metagenomes, and groups of environmental sequences and uses a new global alignment algorithm to design single or multiple probes for each gene or group. We are now using this program to design a more comprehensive functional gene array for environmental studies. Overall, our results indicate that the 50mer-based microarray technology has potential as a specific and quantitative tool to reveal the composition of microbial communities and their dynamics important to processes within contaminated environments.

  5. Development and Use of Integrated Microarray-Based Genomic Technologies for Assessing Microbial Community Composition and Dynamics

    SciTech Connect

    J. Zhou; S.-K. Rhee; C. Schadt; T. Gentry; Z. He; X. Li; X. Liu; J. Liebich; S.C. Chong; L. Wu

    2004-03-17

    different microbial communities and processes at the NABIR-FRC in Oak Ridge, TN. One project involves the monitoring of the development and dynamics of the microbial community of a fluidized bed reactor (FBR) used for reducing nitrate and the other project monitors microbial community responses to stimulation of uranium reducing populations via ethanol donor additions in situ and in a model system. Additionally, we are developing novel strategies for increasing microarray hybridization sensitivity. Finally, great improvements to our methods of probe design were made by the development of a new computer program, CommOligo. CommOligo designs unique and group-specific oligo probes for whole-genomes, metagenomes, and groups of environmental sequences and uses a new global alignment algorithm to design single or multiple probes for each gene or group. We are now using this program to design a more comprehensive functional gene array for environmental studies. Overall, our results indicate that the 50mer-based microarray technology has potential as a specific and quantitative tool to reveal the composition of microbial communities and their dynamics important to processes within contaminated environments.

  6. Evaluation of Gel-Pad Oligonucleotide Microarray Technology by Using Artificial Neural Networks†

    PubMed Central

    Pozhitkov, Alex; Chernov, Boris; Yershov, Gennadiy; Noble, Peter A.

    2005-01-01

    Past studies have suggested that thermal dissociation analysis of nucleic acids hybridized to DNA microarrays would improve discrimination among duplex types by scanning through a broad range of stringency conditions. To more fully constrain the utility of this approach using a previously described gel-pad microarray format, artificial neural networks (NNs) were trained to recognize noisy or low-quality data, as might derive from nonspecific fluorescence, poor hybridization, or compromised data collection. The NNs were trained to classify dissociation profiles (melts) into groups based on selected characteristics (e.g., initial signal intensity, area under the curve) using a data set of 21,044 profiles derived from 186 probes hybridized to a study set of RNA extracted from 32 microbes common to the human oral cavity. Three melt profile groups were identified: one group consisted mostly of ideal melt profiles; another group consisted mostly of poor melt profiles; and, the remainder were difficult to classify. Screening of melting profiles of perfect-match hybrids revealed inconsistencies in the form of melting profiles even for identical probes on the same microarray hybridized to same target rRNA. Approximately 18% of perfect-match duplex types were correctly classified as poor. Experimental variability and deviation from ideal melt behavior were shown to be attributable primarily to a method of local background subtraction that was very sensitive to displacement of the grid frames used for image capture (both determined by the image analysis system) and duplexes with low binding constants. Additional results showed that long RNA fragments limit the discriminating power among duplex types. PMID:16332861

  7. Phosphoprotein Stability in Clinical Tissue and Its Relevance for Reverse Phase Protein Microarray Technology

    PubMed Central

    Espina, Virginia; Mueller, Claudius; Liotta, Lance A.

    2013-01-01

    Phosphorylated proteins reflect the activity of specific cell signaling nodes in biological kinase protein networks. Cell signaling pathways can be either activated or deactivated depending on the phosphorylation state of the constituent proteins. The state of these kinase pathways reflects the in vivo activity of the cells and tissue at any given point in time. As such, cell signaling pathway information can be extrapolated to infer which phosphorylated proteins/pathways are driving an individual tumor’s growth. Reverse Phase Protein Microarrays (RPMA) are a sensitive and precise platform that can be applied to the quantitative measurement of hundreds of phosphorylated signal proteins from a small sample of tissue. Pre-analytical variability originating from tissue procurement and preservation may cause significant variability and bias in downstream molecular analysis. Depending on the ex vivo delay time in tissue processing, and the manner of tissue handling, protein biomarkers such as signal pathway phosphoproteins will be elevated or suppressed in a manner that does not represent the biomarker levels at the time of excision. Consequently, assessment of the state of these kinase networks requires stabilization, or preservation, of the phosphoproteins immediately post tissue procurement. We have employed reverse phase protein microarray analysis of phosphoproteins to study the factors influencing stability of phosphoproteins in tissue following procurement. Based on this analysis we have established tissue procurement guidelines for clinical research with an emphasis on quantifying phosphoproteins by RPMA. PMID:21901591

  8. DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Nguyen, C.; Gidrol, X.

    Genomics has revolutionised biological and biomedical research. This revolution was predictable on the basis of its two driving forces: the ever increasing availability of genome sequences and the development of new technology able to exploit them. Up until now, technical limitations meant that molecular biology could only analyse one or two parameters per experiment, providing relatively little information compared with the great complexity of the systems under investigation. This gene by gene approach is inadequate to understand biological systems containing several thousand genes. It is essential to have an overall view of the DNA, RNA, and relevant proteins. A simple inventory of the genome is not sufficient to understand the functions of the genes, or indeed the way that cells and organisms work. For this purpose, functional studies based on whole genomes are needed. Among these new large-scale methods of molecular analysis, DNA microarrays provide a way of studying the genome and the transcriptome. The idea of integrating a large amount of data derived from a support with very small area has led biologists to call these chips, borrowing the term from the microelectronics industry. At the beginning of the 1990s, the development of DNA chips on nylon membranes [1, 2], then on glass [3] and silicon [4] supports, made it possible for the first time to carry out simultaneous measurements of the equilibrium concentration of all the messenger RNA (mRNA) or transcribed RNA in a cell. These microarrays offer a wide range of applications, in both fundamental and clinical research, providing a method for genome-wide characterisation of changes occurring within a cell or tissue, as for example in polymorphism studies, detection of mutations, and quantitative assays of gene copies. With regard to the transcriptome, it provides a way of characterising differentially expressed genes, profiling given biological states, and identifying regulatory channels.

  9. Tissue Microarray Technology for Molecular Applications: Investigation of Cross-Contamination between Tissue Samples Obtained from the Same Punching Device

    PubMed Central

    Vassella, Erik; Galván, José A.; Zlobec, Inti

    2015-01-01

    Background: Tissue microarray (TMA) technology allows rapid visualization of molecular markers by immunohistochemistry and in situ hybridization. In addition, TMA instrumentation has the potential to assist in other applications: punches taken from donor blocks can be placed directly into tubes and used for nucleic acid analysis by PCR approaches. However, the question of possible cross-contamination between samples punched with the same device has frequently been raised but never addressed. Methods: Two experiments were performed. (1) A block from mycobacterium tuberculosis (TB) positivetissue and a second from an uninfected patient were aligned side-by-side in an automated tissue microarrayer. Four 0.6 mm punches were cored from each sample and placed inside their corresponding tube. Between coring of each donor block, a mechanical cleaning step was performed by insertion of the puncher into a paraffin block. This sequence of coring and cleaning was repeated three times, alternating between positive and negative blocks. A fragment from the 6110 insertion sequence specific for mycobacterium tuberculosis was analyzed; (2) Four 0.6 mm punches were cored from three KRAS mutated colorectal cancer blocks, alternating with three different wild-type tissues using the same TMA instrument (sequence of coring: G12D, WT, G12V, WT, G13D and WT). Mechanical cleaning of the device between each donor block was made. Mutation analysis by pyrosequencing was carried out. This sequence of coring was repeated manually without any cleaning step between blocks. Results/Discussion: In both analyses, all alternating samples showed the expected result (samples 1, 3 and 5: positive or mutated, samples 2, 4 and 6: negative or wild-type). Similar results were obtained without cleaning step. These findings suggest that no cross-contamination of tissue samples occurs when donor blocks are punched using the same device, however a cleaning step is nonetheless recommended. Our result supports

  10. Microarrays in Glycoproteomics Research

    PubMed Central

    Yue, Tingting; Haab, Brian B.

    2009-01-01

    Microarrays have been extremely useful for investigating binding interactions among diverse types of molecular species, with the main advantage being the ability to examine many interactions using small amount of samples and reagents. Microarrays are increasingly being used to advance research in the field of glycobiology, which is the study of the nature and function and carbohydrates in health and disease. Several types of microarrays are being used in the study of glycans and proteins in glycobiology, including glycan arrays to study the recognition of carbohydrates, lectin arrays to determine carbohydrate expression on purified proteins or on cells, and antibody arrays to examine the variation in particular glycan structures on specific proteins. This review will cover the technology and applications of these types of microarrays, as well as their use for obtaining complementary information on various aspects of glycobiology. PMID:19389548

  11. DNA Microarray-Based Diagnostics.

    PubMed

    Marzancola, Mahsa Gharibi; Sedighi, Abootaleb; Li, Paul C H

    2016-01-01

    The DNA microarray technology is currently a useful biomedical tool which has been developed for a variety of diagnostic applications. However, the development pathway has not been smooth and the technology has faced some challenges. The reliability of the microarray data and also the clinical utility of the results in the early days were criticized. These criticisms added to the severe competition from other techniques, such as next-generation sequencing (NGS), impacting the growth of microarray-based tests in the molecular diagnostic market.Thanks to the advances in the underlying technologies as well as the tremendous effort offered by the research community and commercial vendors, these challenges have mostly been addressed. Nowadays, the microarray platform has achieved sufficient standardization and method validation as well as efficient probe printing, liquid handling and signal visualization. Integration of various steps of the microarray assay into a harmonized and miniaturized handheld lab-on-a-chip (LOC) device has been a goal for the microarray community. In this respect, notable progress has been achieved in coupling the DNA microarray with the liquid manipulation microsystem as well as the supporting subsystem that will generate the stand-alone LOC device.In this chapter, we discuss the major challenges that microarray technology has faced in its almost two decades of development and also describe the solutions to overcome the challenges. In addition, we review the advancements of the technology, especially the progress toward developing the LOC devices for DNA diagnostic applications.

  12. Unsupervised assessment of microarray data quality using a Gaussian mixture model

    PubMed Central

    Howard, Brian E; Sick, Beate; Heber, Steffen

    2009-01-01

    Background Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny. Results We show how an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and the naïve Bayes model can be used to automate microarray quality assessment. The method is flexible and can be easily adapted to accommodate alternate quality statistics and platforms. We evaluate our approach using Affymetrix 3' gene expression and exon arrays and compare the performance of this method to a similar supervised approach. Conclusion This research illustrates the efficacy of an unsupervised classification approach for the purpose of automated microarray data quality assessment. Since our approach requires only unannotated training data, it is easy to customize and to keep up-to-date as technology evolves. In contrast to other "black box" classification systems, this method also allows for intuitive explanations. PMID:19545436

  13. Surface chemistries for antibody microarrays

    SciTech Connect

    Seurynck-Servoss, Shannon L.; Baird, Cheryl L.; Rodland, Karin D.; Zangar, Richard C.

    2007-05-01

    Enzyme-linked immunosorbent assay (ELISA) microarrays promise to be a powerful tool for the detection of disease biomarkers. The original technology for printing ELISA microarray chips and capturing antibodies on slides was derived from the DNA microarray field. However, due to the need to maintain antibody structure and function when immobilized, surface chemistries used for DNA microarrays are not always appropriate for ELISA microarrays. In order to identify better surface chemistries for antibody capture, a number of commercial companies and academic research groups have developed new slide types that could improve antibody function in microarray applications. In this review we compare and contrast the commercially available slide chemistries, as well as highlight some promising recent advances in the field.

  14. Development of Microarrays-Based Metagenomics Technology for Monitoring Sulfate-Reducing Bacteria in Subsurface Environments

    SciTech Connect

    Cindy, Shi

    2015-07-17

    At the contaminated DOE sites, sulfate-reducing bacteria (SRB) are a significant population and play an important role in the microbial community during biostimulation for metal reduction. However, the diversity, structure and dynamics of SRB communities are poorly understood. Therefore, this project aims to use high throughput sequencing-based metagenomics technologies for characterizing the diversity, structure, functions, and activities of SRB communities by developing genomic and bioinformatics tools to link the SRB biodiversity with ecosystem functioning.

  15. The Genopolis Microarray Database

    PubMed Central

    Splendiani, Andrea; Brandizi, Marco; Even, Gael; Beretta, Ottavio; Pavelka, Norman; Pelizzola, Mattia; Mayhaus, Manuel; Foti, Maria; Mauri, Giancarlo; Ricciardi-Castagnoli, Paola

    2007-01-01

    Background Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood. Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions. Results The Genopolis Database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip® platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users. Conclusion The Genopolis Database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local

  16. Monitoring of malaria parasite resistance to chloroquine and sulphadoxine-pyrimethamine in the Solomon Islands by DNA microarray technology

    PubMed Central

    2010-01-01

    Background Little information is available on resistance to anti-malarial drugs in the Solomon Islands (SI). The analysis of single nucleotide polymorphisms (SNPs) in drug resistance associated parasite genes is a potential alternative to classical time- and resource-consuming in vivo studies to monitor drug resistance. Mutations in pfmdr1 and pfcrt were shown to indicate chloroquine (CQ) resistance, mutations in pfdhfr and pfdhps indicate sulphadoxine-pyrimethamine (SP) resistance, and mutations in pfATPase6 indicate resistance to artemisinin derivatives. Methods The relationship between the rate of treatment failure among 25 symptomatic Plasmodium falciparum-infected patients presenting at the clinic and the pattern of resistance-associated SNPs in P. falciparum infecting 76 asymptomatic individuals from the surrounding population was investigated. The study was conducted in the SI in 2004. Patients presenting at a local clinic with microscopically confirmed P. falciparum malaria were recruited and treated with CQ+SP. Rates of treatment failure were estimated during a 28-day follow-up period. In parallel, a DNA microarray technology was used to analyse mutations associated with CQ, SP, and artemisinin derivative resistance among samples from the asymptomatic community. Mutation and haplotype frequencies were determined, as well as the multiplicity of infection. Results The in vivo study showed an efficacy of 88% for CQ+SP to treat P. falciparum infections. DNA microarray analyses indicated a low diversity in the parasite population with one major haplotype present in 98.7% of the cases. It was composed of fixed mutations at position 86 in pfmdr1, positions 72, 75, 76, 220, 326 and 356 in pfcrt, and positions 59 and 108 in pfdhfr. No mutation was observed in pfdhps or in pfATPase6. The mean multiplicity of infection was 1.39. Conclusion This work provides the first insight into drug resistance markers of P. falciparum in the SI. The obtained results indicated the

  17. Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ricard-Blum, S.

    Proteins are key actors in the life of the cell, involved in many physiological and pathological processes. Since variations in the expression of messenger RNA are not systematically correlated with variations in the protein levels, the latter better reflect the way a cell functions. Protein microarrays thus supply complementary information to DNA chips. They are used in particular to analyse protein expression profiles, to detect proteins within complex biological media, and to study protein-protein interactions, which give information about the functions of those proteins [3-9]. They have the same advantages as DNA microarrays for high-throughput analysis, miniaturisation, and the possibility of automation. Section 18.1 gives a brief overview of proteins. Following this, Sect. 18.2 describes how protein microarrays can be made on flat supports, explaining how proteins can be produced and immobilised on a solid support, and discussing the different kinds of substrate and detection method. Section 18.3 discusses the particular format of protein microarrays in suspension. The diversity of protein microarrays and their applications are then reported in Sect. 18.4, with applications to therapeutics (protein-drug interactions) and diagnostics. The prospects for future developments of protein microarrays are then outlined in the conclusion. The bibliography provides an extensive list of reviews and detailed references for those readers who wish to go further in this area. Indeed, the aim of the present chapter is not to give an exhaustive or detailed analysis of the state of the art, but rather to provide the reader with the basic elements needed to understand how proteins are designed and used.

  18. Identifying the impact of G-quadruplexes on Affymetrix 3' arrays using cloud computing.

    PubMed

    Memon, Farhat N; Owen, Anne M; Sanchez-Graillet, Olivia; Upton, Graham J G; Harrison, Andrew P

    2010-01-15

    A tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips. In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3' arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google. We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3' arrays.

  19. Identification of SNPs and INDELS in swine transcribed sequences using short oligonucleotide microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to...

  20. Nanotechnologies in protein microarrays.

    PubMed

    Krizkova, Sona; Heger, Zbynek; Zalewska, Marta; Moulick, Amitava; Adam, Vojtech; Kizek, Rene

    2015-01-01

    Protein microarray technology became an important research tool for study and detection of proteins, protein-protein interactions and a number of other applications. The utilization of nanoparticle-based materials and nanotechnology-based techniques for immobilization allows us not only to extend the surface for biomolecule immobilization resulting in enhanced substrate binding properties, decreased background signals and enhanced reporter systems for more sensitive assays. Generally in contemporarily developed microarray systems, multiple nanotechnology-based techniques are combined. In this review, applications of nanoparticles and nanotechnologies in creating protein microarrays, proteins immobilization and detection are summarized. We anticipate that advanced nanotechnologies can be exploited to expand promising fields of proteins identification, monitoring of protein-protein or drug-protein interactions, or proteins structures. PMID:26039143

  1. The Microarray Revolution: Perspectives from Educators

    ERIC Educational Resources Information Center

    Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

    2004-01-01

    In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

  2. THE ABRF MARG MICROARRAY SURVEY 2005: TAKING THE PULSE ON THE MICROARRAY FIELD

    EPA Science Inventory

    Over the past several years microarray technology has evolved into a critical component of any discovery based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a pr...

  3. Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data

    PubMed Central

    2010-01-01

    Background Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is to reliably identify and localize genomic regions that bind a specific protein. Further investigation compares binding profiles of functionally related proteins, or binding profiles of the same proteins in different genetic backgrounds or experimental conditions. Ultimately, the goal is to gain a mechanistic understanding of the effects of DNA binding events on gene expression. Results We present a free, open-source R/Bioconductor package Starr that facilitates comparative analysis of ChIP-chip data across experiments and across different microarray platforms. The package provides functions for data import, quality assessment, data visualization and exploration. Starr includes high-level analysis tools such as the alignment of ChIP signals along annotated features, correlation analysis of ChIP signals with complementary genomic data, peak-finding and comparative display of multiple clusters of binding profiles. It uses standard Bioconductor classes for maximum compatibility with other software. Moreover, Starr automatically updates microarray probe annotation files by a highly efficient remapping of microarray probe sequences to an arbitrary genome. Conclusion Starr is an R package that covers the complete ChIP-chip workflow from data processing to binding pattern detection. It focuses on the high-level data analysis, e.g., it provides methods for the integration and combined statistical analysis of binding profiles and complementary functional genomics data. Starr enables systematic assessment of binding behaviour for groups of genes that are alingned along arbitrary genomic features. PMID:20398407

  4. Microarray platform for omics analysis

    NASA Astrophysics Data System (ADS)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

    Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

  5. User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org.

    PubMed

    Eijssen, Lars M T; Jaillard, Magali; Adriaens, Michiel E; Gaj, Stan; de Groot, Philip J; Müller, Michael; Evelo, Chris T

    2013-07-01

    Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards. PMID:23620278

  6. User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org.

    PubMed

    Eijssen, Lars M T; Jaillard, Magali; Adriaens, Michiel E; Gaj, Stan; de Groot, Philip J; Müller, Michael; Evelo, Chris T

    2013-07-01

    Quality control (QC) is crucial for any scientific method producing data. Applying adequate QC introduces new challenges in the genomics field where large amounts of data are produced with complex technologies. For DNA microarrays, specific algorithms for QC and pre-processing including normalization have been developed by the scientific community, especially for expression chips of the Affymetrix platform. Many of these have been implemented in the statistical scripting language R and are available from the Bioconductor repository. However, application is hampered by lack of integrative tools that can be used by users of any experience level. To fill this gap, we developed a freely available tool for QC and pre-processing of Affymetrix gene expression results, extending, integrating and harmonizing functionality of Bioconductor packages. The tool can be easily accessed through a wizard-like web portal at http://www.arrayanalysis.org or downloaded for local use in R. The portal provides extensive documentation, including user guides, interpretation help with real output illustrations and detailed technical documentation. It assists newcomers to the field in performing state-of-the-art QC and pre-processing while offering data analysts an integral open-source package. Providing the scientific community with this easily accessible tool will allow improving data quality and reuse and adoption of standards.

  7. Quality control in microarray assessment of gene expression in human airway epithelium

    PubMed Central

    Raman, Tina; O'Connor, Timothy P; Hackett, Neil R; Wang, Wei; Harvey, Ben-Gary; Attiyeh, Marc A; Dang, David T; Teater, Matthew; Crystal, Ronald G

    2009-01-01

    Background Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥ 7.0; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3) the multi-chip normalization scaling factor ≤ 10.0. Results Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3%) passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6%) passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04) were significantly lower (p < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria. Conclusion Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation. PMID:19852842

  8. Microarrays under the microscope

    PubMed Central

    Wildsmith, S E; Elcock, F J

    2001-01-01

    Microarray technology is a rapidly advancing area, which is gaining popularity in many biological disciplines from drug target identification to predictive toxicology. Over the past few years, there has been a dramatic increase in the number of methods and techniques available for carrying out this form of gene expression analysis. The techniques and associated peripherals, such as slide types, deposition methods, robotics, and scanning equipment, are undergoing constant improvement, helping to drive the technology forward in terms of robustness and ease of use. These rapid developments, combined with the number of options available and the associated hyperbole, can prove daunting for the new user. This review aims to guide the researcher through the various steps of conducting microarray experiments, from initial strategy to analysing the data, with critical examination of the benefits and disadvantages along the way. PMID:11212888

  9. Contributions to Statistical Problems Related to Microarray Data

    ERIC Educational Resources Information Center

    Hong, Feng

    2009-01-01

    Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

  10. Assessing Agreement between miRNA Microarray Platforms

    PubMed Central

    Bassani, Niccolò P.; Ambrogi, Federico; Biganzoli, Elia M.

    2014-01-01

    Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland–Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland–Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland–Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.

  11. MOLECULAR METHODS (E.G., MICROARRAYS) APPLIED TO PLANT GENOMES FOR ASSESSING GENETIC CHANGE AND ENVIRONMENTAL STRESS

    EPA Science Inventory

    This is a technical document that presents a detailed sample standard operating procedure (S.O.P.) for preparing plant nucleic acid samples for microarray analyses using commercial ¿chips¿ such as those sold by Affymetrix. It also presents the application of a commercially availa...

  12. Highly parallel microbial diagnostics using oligonucleotide microarrays.

    PubMed

    Loy, Alexander; Bodrossy, Levente

    2006-01-01

    Oligonucleotide microarrays are highly parallel hybridization platforms, allowing rapid and simultaneous identification of many different microorganisms and viruses in a single assay. In the past few years, researchers have been confronted with a dramatic increase in the number of studies reporting development and/or improvement of oligonucleotide microarrays for microbial diagnostics, but use of the technology in routine diagnostics is still constrained by a variety of factors. Careful development of microarray essentials (such as oligonucleotide probes, protocols for target preparation and hybridization, etc.) combined with extensive performance testing are thus mandatory requirements for the maturation of diagnostic microarrays from fancy technological gimmicks to robust and routinely applicable tools.

  13. Evaluation of gene expression in MG63 human osteoblastlike cells exposed to tantalum powder by microarray technology.

    PubMed

    Sollazzo, Vincenzo; Pezzetti, Furio; Massari, Leo; Palmieri, Annalisa; Brunelli, Giorgio; Zollino, Ilaria; Lucchese, Alessandra; Caruso, Gaetano; Carinci, Francesco

    2011-01-01

    Conventional orthopedic implants are composed from titanium. To improve some characteristics (ie, volumetric porosity, modulus of elasticity, frictional modulus), a new porous tantalum biomaterial has been developed and its biocompatibility reported. By using DNA microarrays containing 20,000 genes, several genes whose expression were significantly up- or down-regulated were identified in an osteoblastlike cell line (MG63) cultured with tantalum powder (TP). The differentially expressed genes cover a broad range of functional activities: signaling transduction; transcription; cell cycle regulation, proliferation, and apoptosis; and cytoskeleton formation. To the authors' knowledge, the data reported represent the first genetic portrait of TP.

  14. Aptamer Microarrays

    SciTech Connect

    Angel-Syrett, Heather; Collett, Jim; Ellington, Andrew D.

    2009-01-02

    In vitro selection can yield specific, high-affinity aptamers. We and others have devised methods for the automated selection of aptamers, and have begun to use these reagents for the construction of arrays. Arrayed aptamers have proven to be almost as sensitive as their solution phase counterparts, and when ganged together can provide both specific and general diagnostic signals for proteins and other analytes. We describe here technical details regarding the production and processing of aptamer microarrays, including blocking, washing, drying, and scanning. We will also discuss the challenges involved in developing standardized and reproducible methods for binding and quantitating protein targets. While signals from fluorescent analytes or sandwiches are typically captured, it has proven possible for immobilized aptamers to be uniquely coupled to amplification methods not available to protein reagents, thus allowing for protein-binding signals to be greatly amplified. Into the future, many of the biosensor methods described in this book can potentially be adapted to array formats, thus further expanding the utility of and applications for aptamer arrays.

  15. An imputation approach for oligonucleotide microarrays.

    PubMed

    Li, Ming; Wen, Yalu; Lu, Qing; Fu, Wenjiang J

    2013-01-01

    Oligonucleotide microarrays are commonly adopted for detecting and qualifying the abundance of molecules in biological samples. Analysis of microarray data starts with recording and interpreting hybridization signals from CEL images. However, many CEL images may be blemished by noises from various sources, observed as "bright spots", "dark clouds", and "shadowy circles", etc. It is crucial that these image defects are correctly identified and properly processed. Existing approaches mainly focus on detecting defect areas and removing affected intensities. In this article, we propose to use a mixed effect model for imputing the affected intensities. The proposed imputation procedure is a single-array-based approach which does not require any biological replicate or between-array normalization. We further examine its performance by using Affymetrix high-density SNP arrays. The results show that this imputation procedure significantly reduces genotyping error rates. We also discuss the necessary adjustments for its potential extension to other oligonucleotide microarrays, such as gene expression profiling. The R source code for the implementation of approach is freely available upon request.

  16. Gene expression profiles in the rat streptococcal cell wall-induced arthritis model identified using microarray analysis.

    PubMed

    Rioja, Inmaculada; Clayton, Chris L; Graham, Simon J; Life, Paul F; Dickson, Marion C

    2005-01-01

    Experimental arthritis models are considered valuable tools for delineating mechanisms of inflammation and autoimmune phenomena. Use of microarray-based methods represents a new and challenging approach that allows molecular dissection of complex autoimmune diseases such as arthritis. In order to characterize the temporal gene expression profile in joints from the reactivation model of streptococcal cell wall (SCW)-induced arthritis in Lewis (LEW/N) rats, total RNA was extracted from ankle joints from naive, SCW injected, or phosphate buffered saline injected animals (time course study) and gene expression was analyzed using Affymetrix oligonucleotide microarray technology (RAE230A). After normalization and statistical analysis of data, 631 differentially expressed genes were sorted into clusters based on their levels and kinetics of expression using Spotfire profile search and K-mean cluster analysis. Microarray-based data for a subset of genes were validated using real-time PCR TaqMan analysis. Analysis of the microarray data identified 631 genes (441 upregulated and 190 downregulated) that were differentially expressed (Delta > 1.8, P < 0.01), showing specific levels and patterns of gene expression. The genes exhibiting the highest fold increase in expression on days -13.8, -13, or 3 were involved in chemotaxis, inflammatory response, cell adhesion and extracellular matrix remodelling. Transcriptome analysis identified 10 upregulated genes (Delta > 5), which have not previously been associated with arthritis pathology and are located in genomic regions associated with autoimmune disease. The majority of the downregulated genes were associated with metabolism, transport and regulation of muscle development. In conclusion, the present study describes the temporal expression of multiple disease-associated genes with potential pathophysiological roles in the reactivation model of SCW-induced arthritis in Lewis (LEW/N) rat. These findings improve our understanding of

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

    PubMed

    Schweighofer, Bernhard; Rohringer, Sabrina; Pröll, Johannes; Holnthoner, Wolfgang

    2015-06-01

    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 podoplanin(high) 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.

  18. Microarray data analysis and mining approaches.

    PubMed

    Cordero, Francesca; Botta, Marco; Calogero, Raffaele A

    2007-12-01

    Microarray based transcription profiling is now a consolidated methodology and has widespread use in areas such as pharmacogenomics, diagnostics and drug target identification. Large-scale microarray studies are also becoming crucial to a new way of conceiving experimental biology. A main issue in microarray transcription profiling is data analysis and mining. When microarrays became a methodology of general use, considerable effort was made to produce algorithms and methods for the identification of differentially expressed genes. More recently, the focus has switched to algorithms and database development for microarray data mining. Furthermore, the evolution of microarray technology is allowing researchers to grasp the regulative nature of transcription, integrating basic expression analysis with mRNA characteristics, i.e. exon-based arrays, and with DNA characteristics, i.e. comparative genomic hybridization, single nucleotide polymorphism, tiling and promoter structure. In this article, we will review approaches used to detect differentially expressed genes and to link differential expression to specific biological functions.

  19. Microarrays Made Simple: "DNA Chips" Paper Activity

    ERIC Educational Resources Information Center

    Barnard, Betsy

    2006-01-01

    DNA microarray technology is revolutionizing biological science. DNA microarrays (also called DNA chips) allow simultaneous screening of many genes for changes in expression between different cells. Now researchers can obtain information about genes in days or weeks that used to take months or years. The paper activity described in this article…

  20. Progress in the application of DNA microarrays.

    PubMed Central

    Lobenhofer, E K; Bushel, P R; Afshari, C A; Hamadeh, H K

    2001-01-01

    Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field. PMID:11673116

  1. DNA microarray technology in the evaluation of weight management potential of a novel calcium-potassium salt of (-)-hydroxycitric Acid.

    PubMed

    Bagchi, Manashi; Zafra-Stone, Shirley; Sen, Chandan K; Roy, Sashwati; Bagchi, Debasis

    2006-01-01

    Quality and quantity of diet and nutrients are key factors of human health and disease prevention. Molecular diagnostics and cellular signaling play a fundamental role in the usefulness of novel nutraceuticals and functional foods. Increasing knowledge of the genes and molecules involved in the development of obesity is creating new methods of obesity regulation. Traditional herbal medicines may have some potential in weight management. Botanical dietary supplements often contain complex mixtures of phytochemicals that have additive or synergistic interactions. Evidence from numerous human and animal dietary studies has demonstrated the potential therapeutic effects of traditional herbal medicines in controlling obesity. We analyzed the effects of low-dose oral administration of calcium-potassium salt of (-)-hydroxycitric acid (HCA-SX) on the body weight and abdominal fat transcriptome in rats. HCA-SX restricted body weight gain in rats and lowered abdominal fat leptin expression. High-density microarray analysis of 9960 genes and ESTs present in the fat tissue identified a small set of specific genes sensitive to dietary HCA-SX. Mitochondrial/nuclear proteins necessary for fundamental support of the tissue were not affected by HCA-SX, further demonstrating its safety. Functional characterization of HCA-SX sensitive genes revealed that up-regulation of genes encoding serotonin receptors represents a distinct effect of HCA-SX on appetite suppression. PMID:20021004

  2. Protein microarrays: prospects and problems.

    PubMed

    Kodadek, T

    2001-02-01

    Protein microarrays are potentially powerful tools in biochemistry and molecular biology. Two types of protein microarrays are defined. One, termed a protein function array, will consist of thousands of native proteins immobilized in a defined pattern. Such arrays can be utilized for massively parallel testing of protein function, hence the name. The other type is termed a protein-detecting array. This will consist of large numbers of arrayed protein-binding agents. These arrays will allow for expression profiling to be done at the protein level. In this article, some of the major technological challenges to the development of protein arrays are discussed, along with potential solutions.

  3. Microarray Applications in Microbial Ecology Research.

    SciTech Connect

    Gentry, T.; Schadt, C.; Zhou, J.

    2006-04-06

    Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. This review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.

  4. Comparing Bacterial DNA Microarray Fingerprints

    SciTech Connect

    Willse, Alan R.; Chandler, Darrell P.; White, Amanda M.; Protic, Miroslava; Daly, Don S.; Wunschel, Sharon C.

    2005-08-15

    Detecting subtle genetic differences between microorganisms is an important problem in molecular epidemiology and microbial forensics. In a typical investigation, gel electrophoresis is used to compare randomly amplified DNA fragments between microbial strains, where the patterns of DNA fragment sizes are proxies for a microbe's genotype. The limited genomic sample captured on a gel is often insufficient to discriminate nearly identical strains. This paper examines the application of microarray technology to DNA fingerprinting as a high-resolution alternative to gel-based methods. The so-called universal microarray, which uses short oligonucleotide probes that do not target specific genes or species, is intended to be applicable to all microorganisms because it does not require prior knowledge of genomic sequence. In principle, closely related strains can be distinguished if the number of probes on the microarray is sufficiently large, i.e., if the genome is sufficiently sampled. In practice, we confront noisy data, imperfectly matched hybridizations, and a high-dimensional inference problem. We describe the statistical problems of microarray fingerprinting, outline similarities with and differences from more conventional microarray applications, and illustrate the statistical fingerprinting problem for 10 closely related strains from three Bacillus species, and 3 strains from non-Bacillus species.

  5. Study on the antiendotoxin action of Pulsatillae Decoction using an Affymetrix rat genome array.

    PubMed

    Hu, Yiyi; Chen, Xi; Lin, Hong; Hu, Yuanliang; Mu, Xiang

    2009-01-01

    A high-throughput and efficient Affymetrix rat genome array was used to investigate the pharmacological mechanism of the traditional Chinese medicine, Pulsatillae Decoction (PD), used for the treatment of diseases induced by lipopolysaccharide (LPS). Rat intestinal microvascular endothelial cells (RIMECs) were challenged with 1mug/ml LPS for 3h, and then treated with PD at a concentration of 1mg/ml for 24h. Total RNA from each treatment group was extracted from cultured RIMECs for detection by the Affymetrix Rat Genome 230 2.0 Array. The results showed that 36 genes were upregulated and 33 genes were downregulated in the LPS group vs. the blank control group; 566 genes were upregulated and 12 genes were downregulated in the PD-treated group vs. the LPS group; and 93 genes were upregulated and 29 genes were downregulated in the PD-treated group vs. the blank control group. The analysis of these data suggested that PD specifically and effectively reduce damage induced by LPS, and improved physiological and biochemical responses to counteract the effects of LPS.

  6. ACNE: a summarization method to estimate allele-specific copy numbers for Affymetrix SNP arrays

    PubMed Central

    Ortiz-Estevez, Maria; Bengtsson, Henrik; Rubio, Angel

    2010-01-01

    Motivation: Current algorithms for estimating DNA copy numbers (CNs) borrow concepts from gene expression analysis methods. However, single nucleotide polymorphism (SNP) arrays have special characteristics that, if taken into account, can improve the overall performance. For example, cross hybridization between alleles occurs in SNP probe pairs. In addition, most of the current CN methods are focused on total CNs, while it has been shown that allele-specific CNs are of paramount importance for some studies. Therefore, we have developed a summarization method that estimates high-quality allele-specific CNs. Results: The proposed method estimates the allele-specific DNA CNs for all Affymetrix SNP arrays dealing directly with the cross hybridization between probes within SNP probesets. This algorithm outperforms (or at least it performs as well as) other state-of-the-art algorithms for computing DNA CNs. It better discerns an aberration from a normal state and it also gives more precise allele-specific CNs. Availability: The method is available in the open-source R package ACNE, which also includes an add on to the aroma.affymetrix framework (http://www.aroma-project.org/). Contact: arubio@ceit.es Supplementaruy information: Supplementary data are available at Bioinformatics online. PMID:20529889

  7. Microarrays, Integrated Analytical Systems

    NASA Astrophysics Data System (ADS)

    Combinatorial chemistry is used to find materials that form sensor microarrays. This book discusses the fundamentals, and then proceeds to the many applications of microarrays, from measuring gene expression (DNA microarrays) to protein-protein interactions, peptide chemistry, carbodhydrate chemistry, electrochemical detection, and microfluidics.

  8. Benchmarking the CATMA Microarray. A Novel Tool forArabidopsis Transcriptome Analysis1[w

    PubMed Central

    Allemeersch, Joke; Durinck, Steffen; Vanderhaeghen, Rudy; Alard, Philippe; Maes, Ruth; Seeuws, Kurt; Bogaert, Tom; Coddens, Kathleen; Deschouwer, Kirsten; Van Hummelen, Paul; Vuylsteke, Marnik; Moreau, Yves; Kwekkeboom, Jeroen; Wijfjes, André H.M.; May, Sean; Beynon, Jim; Hilson, Pierre; Kuiper, Martin T.R.

    2005-01-01

    Transcript profiling is crucial to study biological systems, and various platforms have been implemented to survey mRNAs at the genome scale. We have assessed the performance of the CATMA microarray designed for Arabidopsis (Arabidopsis thaliana) transcriptome analysis and compared it with the Agilent and Affymetrix commercial platforms. The CATMA array consists of gene-specific sequence tags of 150 to 500 bp, the Agilent (Arabidopsis 2) array of 60mer oligonucleotides, and the Affymetrix gene chip (ATH1) of 25mer oligonucleotide sets. We have matched each probe repertoire with the Arabidopsis genome annotation (The Institute for Genomic Research release 5.0) and determined the correspondence between them. Array performance was analyzed by hybridization with labeled targets derived from eight RNA samples made of shoot total RNA spiked with a calibrated series of 14 control transcripts. CATMA arrays showed the largest dynamic range extending over three to four logs. Agilent and Affymetrix arrays displayed a narrower range, presumably because signal saturation occurred for transcripts at concentrations beyond 1,000 copies per cell. Sensitivity was comparable for all three platforms. For Affymetrix GeneChip data, the RMA software package outperformed Microarray Suite 5.0 for all investigated criteria, confirming that the information provided by the mismatch oligonucleotides has no added value. In addition, taking advantage of replicates in our dataset, we conducted a robust statistical analysis of the platform propensity to yield false positive and false negative differentially expressed genes, and all gave satisfactory results. The results establish the CATMA array as a mature alternative to the Affymetrix and Agilent platforms. PMID:15710687

  9. Sensing immune responses with customized peptide microarrays.

    PubMed

    Schirwitz, Christopher; Loeffler, Felix F; Felgenhauer, Thomas; Stadler, Volker; Breitling, Frank; Bischoff, F Ralf

    2012-12-01

    The intent to solve biological and biomedical questions in high-throughput led to an immense interest in microarray technologies. Nowadays, DNA microarrays are routinely used to screen for oligonucleotide interactions within a large variety of potential interaction partners. To study interactions on the protein level with the same efficiency, protein and peptide microarrays offer similar advantages, but their production is more demanding. A new technology to produce peptide microarrays with a laser printer provides access to affordable and highly complex peptide microarrays. Such a peptide microarray can contain up to 775 peptide spots per cm², whereby the position of each peptide spot and, thus, the amino acid sequence of the corresponding peptide, is exactly known. Compared to other techniques, such as the SPOT synthesis, more features per cm² at lower costs can be synthesized which paves the way for laser printed peptide microarrays to take on roles as efficient and affordable biomedical sensors. Here, we describe the laser printer-based synthesis of peptide microarrays and focus on an application involving the blood sera of tetanus immunized individuals, indicating the potential of peptide arrays to sense immune responses.

  10. Global Expression Patterns of Three Festuca Species Exposed to Different Doses of Glyphosate Using the Affymetrix GeneChip Wheat Genome Array.

    PubMed

    Cebeci, Ozge; Budak, Hikmet

    2009-01-01

    Glyphosate has been shown to act as an inhibitor of an aromatic amino acid biosynthetic pathway, while other pathways that may be affected by glyphosate are not known. Cross species hybridizations can provide a tool for elucidating biological pathways conserved among organisms. Comparative genome analyses have indicated a high level of colinearity among grass species and Festuca, on which we focus here, and showed rearrangements common to the Pooideae family. Based on sequence conservation among grass species, we selected the Affymetrix GeneChip Wheat Genome Array as a tool for the analysis of expression profiles of three Festuca (fescue) species with distinctly different tolerances to varying levels of glyphosate. Differences in transcript expression were recorded upon foliar glyphosate application at 1.58 mM and 6.32 mM, representing 5% and 20%, respectively, of the recommended rate. Differences highlighted categories of general metabolic processes, such as photosynthesis, protein synthesis, stress responses, and a larger number of transcripts responded to 20% glyphosate application. Differential expression of genes encoding proteins involved in the shikimic acid pathway could not be identified by cross hybridization. Microarray data were confirmed by RT-PCR and qRT-PCR analyses. This is the first report to analyze the potential of cross species hybridization in Fescue species and the data and analyses will help extend our knowledge on the cellular processes affected by glyphosate.

  11. Living-Cell Microarrays

    PubMed Central

    Yarmush, Martin L.; King, Kevin R.

    2011-01-01

    Living cells are remarkably complex. To unravel this complexity, living-cell assays have been developed that allow delivery of experimental stimuli and measurement of the resulting cellular responses. High-throughput adaptations of these assays, known as living-cell microarrays, which are based on microtiter plates, high-density spotting, microfabrication, and microfluidics technologies, are being developed for two general applications: (a) to screen large-scale chemical and genomic libraries and (b) to systematically investigate the local cellular microenvironment. These emerging experimental platforms offer exciting opportunities to rapidly identify genetic determinants of disease, to discover modulators of cellular function, and to probe the complex and dynamic relationships between cells and their local environment. PMID:19413510

  12. Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data

    PubMed Central

    Baross, Ágnes; Delaney, Allen D; Li, H Irene; Nayar, Tarun; Flibotte, Stephane; Qian, Hong; Chan, Susanna Y; Asano, Jennifer; Ally, Adrian; Cao, Manqiu; Birch, Patricia; Brown-John, Mabel; Fernandes, Nicole; Go, Anne; Kennedy, Giulia; Langlois, Sylvie; Eydoux, Patrice; Friedman, JM; Marra, Marco A

    2007-01-01

    Background Genomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequently in unaffected individuals as polymorphisms. Affymetrix GeneChip whole genome sampling analysis (WGSA) combined with 100 K single nucleotide polymorphism (SNP) genotyping arrays is one of several microarray-based approaches that are now being used to detect such structural genomic changes. The popularity of this technology and its associated open source data format have resulted in the development of an increasing number of software packages for the analysis of copy number changes using these SNP arrays. Results We evaluated four publicly available software packages for high throughput copy number analysis using synthetic and empirical 100 K SNP array data sets, the latter obtained from 107 mental retardation (MR) patients and their unaffected parents and siblings. We evaluated the software with regards to overall suitability for high-throughput 100 K SNP array data analysis, as well as effectiveness of normalization, scaling with various reference sets and feature extraction, as well as true and false positive rates of genomic copy number variant (CNV) detection. Conclusion We observed considerable variation among the numbers and types of candidate CNVs detected by different analysis approaches, and found that multiple programs were needed to find all real aberrations in our test set. The frequency of false positive deletions was substantial, but could be greatly reduced by using the SNP genotype information to confirm loss of heterozygosity. PMID:17910767

  13. [THE POSSIBILITIES OF APPLICATION OF TECHNOLOGY PROTEIN MICROARRAY (MICROCHIPS) FOR ANALYSIS OF PROTEIN COMPOSITION OF BLOOD SERUM].

    PubMed

    Gumanova, N G; Klimushina, M V; Metelskaya, V A; Boitsov, S A

    2015-10-01

    The microchip technology represents convenient and relatively economic tool of analyzing specific biomarkers with the purpose to diagnose diseases, to evaluate effectiveness of therapy and to investigate signaling pathways. To analyze protein composition of blood serum certain types of finished microchips which were not applied previously on the territory of Russia. The detection from 2% to 5% out of matrix of chips depending on their variety was managed without preliminary depletion of serum (removal of proteins of major fractions). Hence, partial protein composition of blood serum can be analyzed with microchips even without preliminary removal of proteins of major fractions. PMID:26841666

  14. [THE POSSIBILITIES OF APPLICATION OF TECHNOLOGY PROTEIN MICROARRAY (MICROCHIPS) FOR ANALYSIS OF PROTEIN COMPOSITION OF BLOOD SERUM].

    PubMed

    Gumanova, N G; Klimushina, M V; Metelskaya, V A; Boitsov, S A

    2015-10-01

    The microchip technology represents convenient and relatively economic tool of analyzing specific biomarkers with the purpose to diagnose diseases, to evaluate effectiveness of therapy and to investigate signaling pathways. To analyze protein composition of blood serum certain types of finished microchips which were not applied previously on the territory of Russia. The detection from 2% to 5% out of matrix of chips depending on their variety was managed without preliminary depletion of serum (removal of proteins of major fractions). Hence, partial protein composition of blood serum can be analyzed with microchips even without preliminary removal of proteins of major fractions.

  15. THE MAQC PROJECT: ESTABLISHING QC METRICS AND THRESHOLDS FOR MICROARRAY QUALITY CONTROL

    EPA Science Inventory

    Microarrays represent a core technology in pharmacogenomics and toxicogenomics; however, before this technology can successfully and reliably be applied in clinical practice and regulatory decision-making, standards and quality measures need to be developed. The Microarray Qualit...

  16. Microarrays in hematology.

    PubMed

    Walker, Josef; Flower, Darren; Rigley, Kevin

    2002-01-01

    Microarrays are fast becoming routine tools for the high-throughput analysis of gene expression in a wide range of biologic systems, including hematology. Although a number of approaches can be taken when implementing microarray-based studies, all are capable of providing important insights into biologic function. Although some technical issues have not been resolved, microarrays will continue to make a significant impact on hematologically important research. PMID:11753074

  17. Advancing translational research with next-generation protein microarrays.

    PubMed

    Yu, Xiaobo; Petritis, Brianne; LaBaer, Joshua

    2016-04-01

    Protein microarrays are a high-throughput technology used increasingly in translational research, seeking to apply basic science findings to enhance human health. In addition to assessing protein levels, posttranslational modifications, and signaling pathways in patient samples, protein microarrays have aided in the identification of potential protein biomarkers of disease and infection. In this perspective, the different types of full-length protein microarrays that are used in translational research are reviewed. Specific studies employing these microarrays are presented to highlight their potential in finding solutions to real clinical problems. Finally, the criteria that should be considered when developing next-generation protein microarrays are provided. PMID:26749402

  18. Development and application of a 6.5 million feature Affymetrix Genechip® for massively parallel discovery of single position polymorphisms in lettuce (Lactuca spp.)

    PubMed Central

    2012-01-01

    Background High-resolution genetic maps are needed in many crops to help characterize the genetic diversity that determines agriculturally important traits. Hybridization to microarrays to detect single feature polymorphisms is a powerful technique for marker discovery and genotyping because of its highly parallel nature. However, microarrays designed for gene expression analysis rarely provide sufficient gene coverage for optimal detection of nucleotide polymorphisms, which limits utility in species with low rates of polymorphism such as lettuce (Lactuca sativa). Results We developed a 6.5 million feature Affymetrix GeneChip® for efficient polymorphism discovery and genotyping, as well as for analysis of gene expression in lettuce. Probes on the microarray were designed from 26,809 unigenes from cultivated lettuce and an additional 8,819 unigenes from four related species (L. serriola, L. saligna, L. virosa and L. perennis). Where possible, probes were tiled with a 2 bp stagger, alternating on each DNA strand; providing an average of 187 probes covering approximately 600 bp for each of over 35,000 unigenes; resulting in up to 13 fold redundancy in coverage per nucleotide. We developed protocols for hybridization of genomic DNA to the GeneChip® and refined custom algorithms that utilized coverage from multiple, high quality probes to detect single position polymorphisms in 2 bp sliding windows across each unigene. This allowed us to detect greater than 18,000 polymorphisms between the parental lines of our core mapping population, as well as numerous polymorphisms between cultivated lettuce and wild species in the lettuce genepool. Using marker data from our diversity panel comprised of 52 accessions from the five species listed above, we were able to separate accessions by species using both phylogenetic and principal component analyses. Additionally, we estimated the diversity between different types of cultivated lettuce and distinguished morphological types

  19. Development of an immunohistochemical protein quantification system in conjunction with tissue microarray technology for identifying predictive biomarkers for phosphatidylinositol 3-kinase inhibitors.

    PubMed

    Isoyama, Sho; Yoshimi, Hisashi; Dan, Shingo; Okamura, Mutsumi; Seki, Mariko; Irimura, Tatsuro; Yamori, Takao

    2012-01-01

    The phosphatidylinositol 3-kinase (PI3K) pathway is frequently activated in human cancers by gain-of-function mutations of phosphoinositide-3-kinase, catalytic, alpha polypeptide (PIK3CA) or dysfunction of phosphatase and tensin homolog deleted on chromosome 10 (PTEN). Therefore PI3K is thought to be a promising target for cancer therapy. Many agents targeting PI3K have been developed and some of them have been evaluated in clinical trials. In recent years, development of predictive biomarkers as companion diagnostics for molecular targeted drugs has become an important requirement for clinical development; however, no clinically established biomarkers that predict the efficacy of PI3K inhibitors have been found. We previously reported that expression of phosphorylated Akt determined by immunoblot analysis correlated with the antitumor efficacy of a PI3K inhibitor ZSTK474 in vitro and in vivo, suggesting that it might be used as a predictive biomarker. In this study, to evaluate biomarker candidates in in vivo tumor samples, we developed an immunohistochemical protein detection/quantification system in conjunction with the tissue microarray technology using a panel of 24 human tumor xenografts (JFCR24). We have clearly demonstrated that expression levels of phosphorylated v-akt murine thymoma viral oncogene homolog (Akt) and mitogen-activated protein kinase (MAPK) determined by this system significantly correlated with those determined by immunoblot analysis. As expected, PTEN status correlated with expression of phosphorylated Akt but not MAPK. Finally, we confirmed that phosphorylated Akt levels determined using this system correlated with the in vivo efficacy of ZSTK474. The present results indicate that the immunohistochemical protein detection/quantification system could be used to quantify expression of biomarker proteins in xenografted tumor tissues as well as in human tumor specimens to predict drug efficacy in future clinical trials. PMID:22975517

  20. Microarray analysis of gene expression in mouse (strain 129) embryonic stem cells after typical synthetic musk exposure.

    PubMed

    Shi, Jiachen; Li, Ming; Jiao, Zhihao; Zhang, Jing; Feng, Yixing; Shao, Bing

    2013-01-01

    Synthetic musks are widely used in personal-care products and can readily accumulate in the adipose tissue, breast milk, and blood of humans. In this study, the Affymetrix Mouse Genome GeneChip was used to identify alterations in gene expression of embryonic stem cells from the 129 strain of the laboratory mouse after treatment with the synthetic musk tonalide (AHTN). Among the 45,037 transcripts in the microarray, 2,879 genes were differentially expressed. According to the microarray analysis, the potential influence of AHTN on the development to embryo should be of concern, and the toxicological effects of it and related musk compounds should be studied further.

  1. The Affymetrix DMET Plus Platform Reveals Unique Distribution of ADME-Related Variants in Ethnic Arabs

    PubMed Central

    Wakil, Salma M.; Nguyen, Cao; Muiya, Nzioka P.; Andres, Editha; Lykowska-Tarnowska, Agnieszka; Baz, Batoul; Meyer, Brian F.; Morahan, Grant

    2015-01-01

    Background. The Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus Premier Pack has been designed to genotype 1936 gene variants thought to be essential for screening patients in personalized drug therapy. These variants include the cytochrome P450s (CYP450s), the key metabolizing enzymes, many other enzymes involved in phase I and phase II pharmacokinetic reactions, and signaling mediators associated with variability in clinical response to numerous drugs not only among individuals, but also between ethnic populations. Materials and Methods. We genotyped 600 Saudi individuals for 1936 variants on the DMET platform to evaluate their clinical potential in personalized medicine in ethnic Arabs. Results. Approximately 49% each of the 437 CYP450 variants, 56% of the 581 transporters, 56% of 419 transferases, 48% of the 104 dehydrogenases, and 58% of the remaining 390 variants were detected. Several variants, such as rs3740071, rs6193, rs258751, rs6199, rs11568421, and rs8187797, exhibited significantly either higher or lower minor allele frequencies (MAFs) than those in other ethnic groups. Discussion. The present study revealed some unique distribution trends for several variants in Arabs, which displayed partly inverse allelic prevalence compared to other ethnic populations. The results point therefore to the need to verify and ascertain the prevalence of a variant as a prerequisite for engaging it in clinical routine screening in personalized medicine in any given population. PMID:25802476

  2. PMD: A Resource for Archiving and Analyzing Protein Microarray data.

    PubMed

    Xu, Zhaowei; Huang, Likun; Zhang, Hainan; Li, Yang; Guo, Shujuan; Wang, Nan; Wang, Shi-Hua; Chen, Ziqing; Wang, Jingfang; Tao, Sheng-Ce

    2016-01-27

    Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is specifically designed for archiving and analyzing protein microarray data. In PMD, users can easily browse and search the entire database by experimental name, protein microarray type, and sample information. Additionally, PMD integrates several data analysis tools and provides an automated data analysis pipeline for users. With just one click, users can obtain a comprehensive analysis report for their protein microarray data. The report includes preliminary data analysis, such as data normalization, candidate identification, and an in-depth bioinformatics analysis of the candidates, which include functional annotation, pathway analysis, and protein-protein interaction network analysis. PMD is now freely available at www.proteinmicroarray.cn.

  3. PMD: A Resource for Archiving and Analyzing Protein Microarray data

    PubMed Central

    Xu, Zhaowei; Huang, Likun; Zhang, Hainan; Li, Yang; Guo, Shujuan; Wang, Nan; Wang, Shi-hua; Chen, Ziqing; Wang, Jingfang; Tao, Sheng-ce

    2016-01-01

    Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is specifically designed for archiving and analyzing protein microarray data. In PMD, users can easily browse and search the entire database by experimental name, protein microarray type, and sample information. Additionally, PMD integrates several data analysis tools and provides an automated data analysis pipeline for users. With just one click, users can obtain a comprehensive analysis report for their protein microarray data. The report includes preliminary data analysis, such as data normalization, candidate identification, and an in-depth bioinformatics analysis of the candidates, which include functional annotation, pathway analysis, and protein-protein interaction network analysis. PMD is now freely available at www.proteinmicroarray.cn. PMID:26813635

  4. Phenotypic MicroRNA Microarrays

    PubMed Central

    Kwon, Yong-Jun; Heo, Jin Yeong; Kim, Hi Chul; Kim, Jin Yeop; Liuzzi, Michel; Soloveva, Veronica

    2013-01-01

    Microarray technology has become a very popular approach in cases where multiple experiments need to be conducted repeatedly or done with a variety of samples. In our lab, we are applying our high density spots microarray approach to microscopy visualization of the effects of transiently introduced siRNA or cDNA on cellular morphology or phenotype. In this publication, we are discussing the possibility of using this micro-scale high throughput process to study the role of microRNAs in the biology of selected cellular models. After reverse-transfection of microRNAs and siRNA, the cellular phenotype generated by microRNAs regulated NF-κB expression comparably to the siRNA. The ability to print microRNA molecules for reverse transfection into cells is opening up the wide horizon for the phenotypic high content screening of microRNA libraries using cellular disease models.

  5. Self-Assembling Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ramachandran, Niroshan; Hainsworth, Eugenie; Bhullar, Bhupinder; Eisenstein, Samuel; Rosen, Benjamin; Lau, Albert Y.; C. Walter, Johannes; LaBaer, Joshua

    2004-07-01

    Protein microarrays provide a powerful tool for the study of protein function. However, they are not widely used, in part because of the challenges in producing proteins to spot on the arrays. We generated protein microarrays by printing complementary DNAs onto glass slides and then translating target proteins with mammalian reticulocyte lysate. Epitope tags fused to the proteins allowed them to be immobilized in situ. This obviated the need to purify proteins, avoided protein stability problems during storage, and captured sufficient protein for functional studies. We used the technology to map pairwise interactions among 29 human DNA replication initiation proteins, recapitulate the regulation of Cdt1 binding to select replication proteins, and map its geminin-binding domain.

  6. LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

    PubMed

    He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

    2006-05-01

    Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

  7. cDNA microarray screening in food safety.

    PubMed

    Roy, Sashwati; Sen, Chandan K

    2006-04-01

    The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests.

  8. Protein Microarrays: Novel Developments and Applications

    PubMed Central

    Berrade, Luis; Garcia, Angie E.

    2011-01-01

    Protein microarray technology possesses some of the greatest potential for providing direct information on protein function and potential drug targets. For example, functional protein microarrays are ideal tools suited for the mapping of biological pathways. They can be used to study most major types of interactions and enzymatic activities that take place in biochemical pathways and have been used for the analysis of simultaneous multiple biomolecular interactions involving protein-protein, protein-lipid, protein-DNA and protein-small molecule interactions. Because of this unique ability to analyze many kinds of molecular interactions en masse, the requirement of very small sample amount and the potential to be miniaturized and automated, protein microarrays are extremely well suited for protein profiling, drug discovery, drug target identification and clinical prognosis and diagnosis. The aim of this review is to summarize the most recent developments in the production, applications and analysis of protein microarrays. PMID:21116694

  9. The Impact of Photobleaching on Microarray Analysis.

    PubMed

    von der Haar, Marcel; Preuß, John-Alexander; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2015-01-01

    DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner's laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube's voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results. PMID:26378589

  10. Evaluation of Surface Chemistries for Antibody Microarrays

    SciTech Connect

    Seurynck-Servoss, Shannon L.; White, Amanda M.; Baird, Cheryl L.; Rodland, Karin D.; Zangar, Richard C.

    2007-12-01

    Antibody microarrays are an emerging technology that promises to be a powerful tool for the detection of disease biomarkers. The current technology for protein microarrays has been primarily derived from DNA microarrays and is not fully characterized for use with proteins. For example, there are a myriad of surface chemistries that are commercially available for antibody microarrays, but no rigorous studies that compare these different surfaces. Therefore, we have used an enzyme-linked immunosorbent assay (ELISA) microarray platform to analyze 16 different commercially available slide types. Full standard curves were generated for 24 different assays. We found that this approach provides a rigorous and quantitative system for comparing the different slide types based on spot size and morphology, slide noise, spot background, lower limit of detection, and reproducibility. These studies demonstrate that the properties of the slide surface affect the activity of immobilized antibodies and the quality of data produced. Although many slide types can produce useful data, glass slides coated with poly-L-lysine or aminosilane, with or without activation with a crosslinker, consistently produce superior results in the ELISA microarray analyses we performed.

  11. Microarray Analysis in Glioblastomas

    PubMed Central

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

    Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930–2942, 2012)To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013)To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59–70, 2013; Verhaak et al., Cancer Cell 17(1):98–110, 2010) While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463

  12. Microarray Analysis in Glioblastomas.

    PubMed

    Bhawe, Kaumudi M; Aghi, Manish K

    2016-01-01

    Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: i. To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930-2942, 2012). ii. To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013). iii. To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59-70, 2013; Verhaak et al., Cancer Cell 17(1):98-110, 2010). While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463

  13. Applications of Functional Protein Microarrays in Basic and Clinical Research

    PubMed Central

    Zhu, Heng; Qian, Jiang

    2013-01-01

    The protein microarray technology provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput manner. It is viewed as a new tool that overcomes the limitation of DNA microarrays. On the basis of its application, protein microarrays fall into two major classes: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be directly spotted on a slide to form the so-called “reverse-phase” protein microarray. In the last decade, applications of functional protein microarrays in particular have flourished in studying protein function and construction of networks and pathways. In this chapter, we will review the recent advancements in the protein microarray technology, followed by presenting a series of examples to illustrate the power and versatility of protein microarrays in both basic and clinical research. As a powerful technology platform, it would not be surprising if protein microarrays will become one of the leading technologies in proteomic and diagnostic fields in the next decade. PMID:22989767

  14. Lectin microarrays for glycomic analysis.

    PubMed

    Gupta, Garima; Surolia, Avadhesha; Sampathkumar, Srinivasa-Gopalan

    2010-08-01

    Glycomics is the study of comprehensive structural elucidation and characterization of all glycoforms found in nature and their dynamic spatiotemporal changes that are associated with biological processes. Glycocalyx of mammalian cells actively participate in cell-cell, cell-matrix, and cell-pathogen interactions, which impact embryogenesis, growth and development, homeostasis, infection and immunity, signaling, malignancy, and metabolic disorders. Relative to genomics and proteomics, glycomics is just growing out of infancy with great potential in biomedicine for biomarker discovery, diagnosis, and treatment. However, the immense diversity and complexity of glycan structures and their multiple modes of interactions with proteins pose great challenges for development of analytical tools for delineating structure function relationships and understanding glyco-code. Several tools are being developed for glycan profiling based on chromatography, mass spectrometry, glycan microarrays, and glyco-informatics. Lectins, which have long been used in glyco-immunology, printed on a microarray provide a versatile platform for rapid high throughput analysis of glycoforms of biological samples. Herein, we summarize technological advances in lectin microarrays and critically review their impact on glycomics analysis. Challenges remain in terms of expansion to include nonplant derived lectins, standardization for routine clinical use, development of recombinant lectins, and exploration of plant kingdom for discovery of novel lectins. PMID:20726799

  15. Lectin microarrays for glycomic analysis.

    PubMed

    Gupta, Garima; Surolia, Avadhesha; Sampathkumar, Srinivasa-Gopalan

    2010-08-01

    Glycomics is the study of comprehensive structural elucidation and characterization of all glycoforms found in nature and their dynamic spatiotemporal changes that are associated with biological processes. Glycocalyx of mammalian cells actively participate in cell-cell, cell-matrix, and cell-pathogen interactions, which impact embryogenesis, growth and development, homeostasis, infection and immunity, signaling, malignancy, and metabolic disorders. Relative to genomics and proteomics, glycomics is just growing out of infancy with great potential in biomedicine for biomarker discovery, diagnosis, and treatment. However, the immense diversity and complexity of glycan structures and their multiple modes of interactions with proteins pose great challenges for development of analytical tools for delineating structure function relationships and understanding glyco-code. Several tools are being developed for glycan profiling based on chromatography, mass spectrometry, glycan microarrays, and glyco-informatics. Lectins, which have long been used in glyco-immunology, printed on a microarray provide a versatile platform for rapid high throughput analysis of glycoforms of biological samples. Herein, we summarize technological advances in lectin microarrays and critically review their impact on glycomics analysis. Challenges remain in terms of expansion to include nonplant derived lectins, standardization for routine clinical use, development of recombinant lectins, and exploration of plant kingdom for discovery of novel lectins.

  16. Parallel characterization of anaerobic toluene- and ethylbenzene-degrading microbial consortia by PCR-denaturing gradient gel electrophoresis, RNA-DNA membrane hybridization, and DNA microarray technology

    NASA Technical Reports Server (NTRS)

    Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Said; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.

    2002-01-01

    A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis.

  17. An Automatic and Power Spectra-based Rotate Correcting Algorithm for Microarray Image.

    PubMed

    Deng, Ning; Duan, Huilong

    2005-01-01

    Microarray image analysis, an important aspect of microarray technology, faces vast amount of data processing. At present, the speed of microarray image analysis is quite limited by excessive manual intervention. The geometric structure of microarray determines that, while being analyzed, microarray image should be collimated in the scanning vertical orientation. If rotation or tilt happens in microarray image, the analysis result may be incorrect. Although some automatic image analysis algorithms are used for microarray, still few methods are reported to calibrate the microarray image rotation problem. In this paper, an automatic rotate correcting algorithm is presented which aims at the deflective problem of microarray image. This method is based on image power spectra. Examined by hundreds of samples of clinical data, the algorithm is proved to achieve high precision. As a result, adopting this algorithm, the overall procedure automation in microarray image analysis can be realized.

  18. Microarrays, antiobesity and the liver

    PubMed Central

    Castro-Chávez, Fernando

    2013-01-01

    In this review, the microarray technology and especially oligonucleotide arrays are exemplified with a practical example taken from the perilipin−/− mice and using the dChip software, available for non-lucrative purposes. It was found that the liver of perilipin−/− mice was healthy and normal, even under high-fat diet when compared with the results published for the scd1−/− mice, which under high-fat diets had a darker liver, suggestive of hepatic steatosis. Scd1 is required for the biosynthesis of monounsaturated fatty acids and plays a key role in the hepatic synthesis of triglycerides and of very-low-density lipoproteins. Both models of obesity resistance share many similar phenotypic antiobesity features, however, the perilipin−/− mice had a significant downregulation of stearoyl CoA desaturases scd1 and scd2 in its white adipose tissue, but a normal level of both genes inside the liver, even under high-fat diet. Here, different microarray methodologies are discussed, and also some of the most recent discoveries and perspectives regarding the use of microarrays, with an emphasis on obesity gene expression, and a personal remark on my findings of increased expression for hemoglobin transcripts and other hemo related genes (hemo-like), and for leukocyte like (leuko-like) genes inside the white adipose tissue of the perilipin−/− mice. In conclusion, microarrays have much to offer in comparative studies such as those in antiobesity, and also they are methodologies adequate for new astounding molecular discoveries [free full text of this article PMID:15657555

  19. Protein Microarrays for the Detection of Biothreats

    NASA Astrophysics Data System (ADS)

    Herr, Amy E.

    Although protein microarrays have proven to be an important tool in proteomics research, the technology is emerging as useful for public health and defense applications. Recent progress in the measurement and characterization of biothreat agents is reviewed in this chapter. Details concerning validation of various protein microarray formats, from contact-printed sandwich assays to supported lipid bilayers, are presented. The reviewed technologies have important implications for in vitro characterization of toxin-ligand interactions, serotyping of bacteria, screening of potential biothreat inhibitors, and as core components of biosensors, among others, research and engineering applications.

  20. IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

    EPA Science Inventory

    Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

  1. DNA microarrays in neuropsychopharmacology.

    PubMed

    Marcotte, E R; Srivastava, L K; Quirion, R

    2001-08-01

    Recent advances in experimental genomics, coupled with the wealth of sequence information available for a variety of organisms, have the potential to transform the way pharmacological research is performed. At present, high-density DNA microarrays allow researchers to quickly and accurately quantify gene-expression changes in a massively parallel manner. Although now well established in other biomedical fields, such as cancer and genetics research, DNA microarrays have only recently begun to make significant inroads into pharmacology. To date, the major focus in this field has been on the general application of DNA microarrays to toxicology and drug discovery and design. This review summarizes the major microarray findings of relevance to neuropsychopharmacology, as a prelude to the design and analysis of future basic and clinical microarray experiments. The ability of DNA microarrays to monitor gene expression simultaneously in a large-scale format is helping to usher in a post-genomic age, where simple constructs about the role of nature versus nurture are being replaced by a functional understanding of gene expression in living organisms. PMID:11479006

  2. Protein Microarrays with Novel Microfluidic Methods: Current Advances

    PubMed Central

    Dixit, Chandra K.; Aguirre, Gerson R.

    2014-01-01

    Microfluidic-based micromosaic technology has allowed the pattering of recognition elements in restricted micrometer scale areas with high precision. This controlled patterning enabled the development of highly multiplexed arrays multiple analyte detection. This arraying technology was first introduced in the beginning of 2001 and holds tremendous potential to revolutionize microarray development and analyte detection. Later, several microfluidic methods were developed for microarray application. In this review we discuss these novel methods and approaches which leverage the property of microfluidic technologies to significantly improve various physical aspects of microarray technology, such as enhanced imprinting homogeneity, stability of the immobilized biomolecules, decreasing assay times, and reduction of the costs and of the bulky instrumentation.

  3. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    PubMed

    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.

  4. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories

    PubMed Central

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-01-01

    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. PMID:27657141

  5. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    PubMed

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-01-01

    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. PMID:27657141

  6. The use of antigen microarrays in antibody profiling.

    PubMed

    Papp, Krisztián; Prechl, József

    2012-01-01

    Technological advances in the field of microarray production and analysis lead to the development of protein microarrays. Of these, antigen microarrays are one particular format that allows the study of antigen-antibody interactions in a miniaturized and highly multiplexed fashion. Here, we describe the parallel detection of antibodies with different specificities in human serum, a procedure also called antibody profiling. Autoantigens printed on microarray slides are reacted with test sera and the bound antibodies are identified by fluorescently labeled secondary reagents. Reactivity patterns generated this way characterize individuals and can help design novel diagnostic tools.

  7. Experimental Approaches to Microarray Analysis of Tumor Samples

    ERIC Educational Resources Information Center

    Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

    2008-01-01

    Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

  8. The Importance of Normalization on Large and Heterogeneous Microarray Datasets

    EPA Science Inventory

    DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

  9. DNA microarray analyses in higher plants.

    PubMed

    Galbraith, David W

    2006-01-01

    DNA microarrays were originally devised and described as a convenient technology for the global analysis of plant gene expression. Over the past decade, their use has expanded enormously to cover all kingdoms of living organisms. At the same time, the scope of applications of microarrays has increased beyond expression analyses, with plant genomics playing a leadership role in the on-going development of this technology. As the field has matured, the rate-limiting step has moved from that of the technical process of data generation to that of data analysis. We currently face major problems in dealing with the accumulating datasets, not simply with respect to how to archive, access, and process the huge amounts of data that have been and are being produced, but also in determining the relative quality of the different datasets. A major recognized concern is the appropriate use of statistical design in microarray experiments, without which the datasets are rendered useless. A vigorous area of current research involves the development of novel statistical tools specifically for microarray experiments. This article describes, in a necessarily selective manner, the types of platforms currently employed in microarray research and provides an overview of recent activities using these platforms in plant biology.

  10. Microarrays meet the Voltaire challenge: Drug discovery on a chip?

    PubMed

    Jackson, David B; Stein, Martin A; Merino, Alejandro; Eils, Roland

    2006-01-01

    The co-emergence of microarray technologies with systems oriented approaches to discovery is testament to the technological and conceptual advancements of recent years. By providing a platform for massively parallelized reductionism, microarrays are enabling us to examine the functional features of diverse classes of bio-system components in a contextually meaningful manner. Yet, to provide economic impact, future development of these technologies demands intimate alignment with the goal of producing safer and more efficacious drugs.: PMID:24980402

  11. DNA Microarray Analysis of Estrogen-Responsive Genes.

    PubMed

    Eyster, Kathleen M

    2016-01-01

    DNA microarray is a powerful, non-biased discovery technology that allows the analysis of the expression of thousands of genes at a time. The technology can be used for the identification of differential gene expression, genetic mutations associated with diseases, DNA methylation, single-nucleotide polymorphisms, and microRNA expression, to name a few. This chapter describes microarray technology for the analysis of differential gene expression in response to estrogen treatment.

  12. Examining microarray slide quality for the EPA using SNL's hyperspectral microarray scanner.

    SciTech Connect

    Rohde, Rachel M.; Timlin, Jerilyn Ann

    2005-11-01

    This report summarizes research performed at Sandia National Laboratories (SNL) in collaboration with the Environmental Protection Agency (EPA) to assess microarray quality on arrays from two platforms of interest to the EPA. Custom microarrays from two novel, commercially produced array platforms were imaged with SNL's unique hyperspectral imaging technology and multivariate data analysis was performed to investigate sources of emission on the arrays. No extraneous sources of emission were evident in any of the array areas scanned. This led to the conclusions that either of these array platforms could produce high quality, reliable microarray data for the EPA toxicology programs. Hyperspectral imaging results are presented and recommendations for microarray analyses using these platforms are detailed within the report.

  13. Microarrays (DNA Chips) for the Classroom Laboratory

    ERIC Educational Resources Information Center

    Barnard, Betsy; Sussman, Michael; BonDurant, Sandra Splinter; Nienhuis, James; Krysan, Patrick

    2006-01-01

    We have developed and optimized the necessary laboratory materials to make DNA microarray technology accessible to all high school students at a fraction of both cost and data size. The primary component is a DNA chip/array that students "print" by hand and then analyze using research tools that have been adapted for classroom use. The primary…

  14. DISC-BASED IMMUNOASSAY MICROARRAYS. (R825433)

    EPA Science Inventory

    Microarray technology as applied to areas that include genomics, diagnostics, environmental, and drug discovery, is an interesting research topic for which different chip-based devices have been developed. As an alternative, we have explored the principle of compact disc-based...

  15. Workflows for microarray data processing in the Kepler environment

    PubMed Central

    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

  16. Photo-Generation of Carbohydrate Microarrays

    NASA Astrophysics Data System (ADS)

    Carroll, Gregory T.; Wang, Denong; Turro, Nicholas J.; Koberstein, Jeffrey T.

    The unparalleled structural diversity of carbohydrates among biological molecules has been recognized for decades. Recent studies have highlighted carbohydrate signaling roles in many important biological processes, such as fertilization, embryonic development, cell differentiation and cellȁ4cell communication, blood coagulation, inflammation, chemotaxis, as well as host recognition and immune responses to microbial pathogens. In this chapter, we summarize recent progress in the establishment of carbohydrate-based microarrays and the application of these technologies in exploring the biological information content in carbohydrates. A newly established photochemical platform of carbohydrate microarrays serves as a model for a focused discussion.

  17. Genomic-Wide Analysis with Microarrays in Human Oncology

    PubMed Central

    Inaoka, Kenichi; Inokawa, Yoshikuni; Nomoto, Shuji

    2015-01-01

    DNA microarray technologies have advanced rapidly and had a profound impact on examining gene expression on a genomic scale in research. This review discusses the history and development of microarray and DNA chip devices, and specific microarrays are described along with their methods and applications. In particular, microarrays have detected many novel cancer-related genes by comparing cancer tissues and non-cancerous tissues in oncological research. Recently, new methods have been in development, such as the double-combination array and triple-combination array, which allow more effective analysis of gene expression and epigenetic changes. Analysis of gene expression alterations in precancerous regions compared with normal regions and array analysis in drug-resistance cancer tissues are also successfully performed. Compared with next-generation sequencing, a similar method of genome analysis, several important differences distinguish these techniques and their applications. Development of novel microarray technologies is expected to contribute to further cancer research.

  18. Tissue Microarrays in Clinical Oncology

    PubMed Central

    Voduc, David; Kenney, Challayne; Nielsen, Torsten O.

    2008-01-01

    The tissue microarray is a recently-implemented, high-throughput technology for the analysis of molecular markers in oncology. This research tool permits the rapid assessment of a biomarker in thousands of tumor samples, using commonly available laboratory assays such as immunohistochemistry and in-situ hybridization. Although introduced less than a decade ago, the TMA has proven to be invaluable in the study of tumor biology, the development of diagnostic tests, and the investigation of oncological biomarkers. This review describes the impact of TMA-based research in clinical oncology and its potential future applications. Technical aspects of TMA construction, and the advantages and disadvantages inherent to this technology are also discussed. PMID:18314063

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

    PubMed

    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.

  20. Re-Annotator: Annotation Pipeline for Microarray Probe Sequences.

    PubMed

    Arloth, Janine; Bader, Daniel M; Röh, Simone; Altmann, Andre

    2015-01-01

    Microarray technologies are established approaches for high throughput gene expression, methylation and genotyping analysis. An accurate mapping of the array probes is essential to generate reliable biological findings. However, manufacturers of the microarray platforms typically provide incomplete and outdated annotation tables, which often rely on older genome and transcriptome versions that differ substantially from up-to-date sequence databases. Here, we present the Re-Annotator, a re-annotation pipeline for microarray probe sequences. It is primarily designed for gene expression microarrays but can also be adapted to other types of microarrays. The Re-Annotator uses a custom-built mRNA reference database to identify the positions of gene expression array probe sequences. We applied Re-Annotator to the Illumina Human-HT12 v4 microarray platform and found that about one quarter (25%) of the probes differed from the manufacturer's annotation. In further computational experiments on experimental gene expression data, we compared Re-Annotator to another probe re-annotation tool, ReMOAT, and found that Re-Annotator provided an improved re-annotation of microarray probes. A thorough re-annotation of probe information is crucial to any microarray analysis. The Re-Annotator pipeline is freely available at http://sourceforge.net/projects/reannotator along with re-annotated files for Illumina microarrays HumanHT-12 v3/v4 and MouseRef-8 v2.

  1. Microarrays for Undergraduate Classes

    ERIC Educational Resources Information Center

    Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

    2006-01-01

    A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

  2. A microarray analysis for differential gene expression in the soybean genome using Bioconductor and R.

    PubMed

    Gregory Alvord, W; Roayaei, Jean A; Quiñones, Octavio A; Schneider, Katherine T

    2007-11-01

    This article describes specific procedures for conducting quality assessment of Affymetrix GeneChip(R) soybean genome data and for performing analyses to determine differential gene expression using the open-source R programming environment in conjunction with the open-source Bioconductor software. We describe procedures for extracting those Affymetrix probe set IDs related specifically to the soybean genome on the Affymetrix soybean chip and demonstrate the use of exploratory plots including images of raw probe-level data, boxplots, density plots and M versus A plots. RNA degradation and recommended procedures from Affymetrix for quality control are discussed. An appropriate probe-level model provides an excellent quality assessment tool. To demonstrate this, we discuss and display chip pseudo-images of weights, residuals and signed residuals and additional probe-level modeling plots that may be used to identify aberrant chips. The Robust Multichip Averaging (RMA) procedure was used for background correction, normalization and summarization of the AffyBatch probe-level data to obtain expression level data and to discover differentially expressed genes. Examples of boxplots and MA plots are presented for the expression level data. Volcano plots and heatmaps are used to demonstrate the use of (log) fold changes in conjunction with ordinary and moderated t-statistics for determining interesting genes. We show, with real data, how implementation of functions in R and Bioconductor successfully identified differentially expressed genes that may play a role in soybean resistance to a fungal pathogen, Phakopsora pachyrhizi. Complete source code for performing all quality assessment and statistical procedures may be downloaded from our web source: http://css.ncifcrf.gov/services/download/MicroarraySoybean.zip.

  3. Array2BIO: A Comprehensive Suite of Utilities for the Analysis of Microarray Data

    SciTech Connect

    Loots, G G; Chain, P G; Mabery, S; Rasley, A; Garcia, E; Ovcharenko, I

    2006-02-13

    We have developed an integrative and automated toolkit for the analysis of Affymetrix microarray data, named Array2BIO. It identifies groups of coexpressed genes using two complementary approaches--comparative analysis of signal versus control microarrays and clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on the Gene Ontology classification, and a detection of corresponding KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods to quantify the odds of observations, including the Benjamini-Hochberg and Bonferroni multiple testing corrections. Automated interface with the ECR Browser provides evolutionary conservation analysis of identified gene loci while the interconnection with Creme allows high-throughput analysis of human promoter regions and prediction of gene regulatory elements that underlie the observed expression patterns. Array2BIO is publicly available at http://array2bio.dcode.org.

  4. A Perspective on DNA Microarrays in Pathology Research and Practice

    PubMed Central

    Pollack, Jonathan R.

    2007-01-01

    DNA microarray technology matured in the mid-1990s, and the past decade has witnessed a tremendous growth in its application. DNA microarrays have provided powerful tools for pathology researchers seeking to describe, classify, and understand human disease. There has also been great expectation that the technology would advance the practice of pathology. This review highlights some of the key contributions of DNA microarrays to experimental pathology, focusing in the area of cancer research. Also discussed are some of the current challenges in translating utility to clinical practice. PMID:17600117

  5. Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm

    PubMed Central

    Dawson, Kevin; Rodriguez, Raymond L; Malyj, Wasyl

    2005-01-01

    Background Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear [1]. Microarray data is one representation of the nonlinear interactions among genes and genes and environmental factors. Still most microarray studies use linear methods for the interpretation of nonlinear data. In this study, we apply Isomap, a nonlinear method of dimensionality reduction, to analyze three independent large Affymetrix high-density oligonucleotide microarray data sets. Results Isomap discovered low-dimensional structures embedded in the Affymetrix microarray data sets. These structures correspond to and help to interpret biological phenomena present in the data. This analysis provides examples of temporal, spatial, and functional processes revealed by the Isomap algorithm. In a spinal cord injury data set, Isomap discovers the three main modalities of the experiment – location and severity of the injury and the time elapsed after the injury. In a multiple tissue data set, Isomap discovers a low-dimensional structure that corresponds to anatomical locations of the source tissues. This model is capable of describing low- and high-resolution differences in the same model, such as kidney-vs.-brain and differences between the nuclei of the amygdala, respectively. In a high-throughput drug screening data set, Isomap discovers the monocytic and granulocytic differentiation of myeloid cells and maps several chemical compounds on the two-dimensional model. Conclusion Visualization of Isomap models provides useful tools for exploratory analysis of microarray data sets. In most instances, Isomap models explain more of the variance present in the microarray data than PCA or MDS. Finally, Isomap is a promising new algorithm for class discovery and class prediction in high-density oligonucleotide data sets. PMID:16076401

  6. Navigating public microarray databases.

    PubMed

    Penkett, Christopher J; Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources.

  7. Use of Microarray to Analyze Gene Expression Profiles of Acute Effects of Prochloraz on Fathead Minnows Pimephales promelas

    EPA Science Inventory

    Microarray technology is a powerful tool to investigate the gene expression profiles for thousands of genes simultaneously. In recent years, microarrays have been used to characterize environmental pollutants and identify molecular mode(s) of action of chemicals including endocri...

  8. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

    EPA Science Inventory

    Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, ...

  9. Application of DNA Microarray to Clinical Diagnostics.

    PubMed

    Patel, Ankita; Cheung, Sau W

    2016-01-01

    Microarray-based technology to conduct array comparative genomic hybridization (aCGH) has made a significant impact on the diagnosis of human genetic diseases. Such diagnoses, previously undetectable by traditional G-banding chromosome analysis, are now achieved by identifying genomic copy number variants (CNVs) using the microarray. Not only can hundreds of well-characterized genetic syndromes be detected in a single assay, but new genomic disorders and disease-causing genes can also be discovered through the utilization of aCGH technology. Although other platforms such as single nucleotide polymorphism (SNP) arrays can be used for detecting CNVs, in this chapter we focus on describing the methods for performing aCGH using Agilent oligonucleotide arrays for both prenatal (e.g., amniotic fluid and chorionic villus sample) and postnatal samples (e.g., blood).

  10. Diagnostic Oligonucleotide Microarray Fingerprinting of Bacillus Isolates

    SciTech Connect

    Chandler, Darrell P.; Alferov, Oleg; Chernov, Boris; Daly, Don S.; Golova, Julia; Perov, Alexander N.; Protic, Miroslava; Robison, Richard; Shipma, Matthew; White, Amanda M.; Willse, Alan R.

    2006-01-01

    A diagnostic, genome-independent microbial fingerprinting method using DNA oligonucleotide microarrays was used for high-resolution differentiation between closely related Bacillus strains, including two strains of Bacillus anthracis that are monomorphic (indistinguishable) via amplified fragment length polymorphism fingerprinting techniques. Replicated hybridizations on 391-probe nonamer arrays were used to construct a prototype fingerprint library for quantitative comparisons. Descriptive analysis of the fingerprints, including phylogenetic reconstruction, is consistent with previous taxonomic organization of the genus. Newly developed statistical analysis methods were used to quantitatively compare and objectively confirm apparent differences in microarray fingerprints with the statistical rigor required for microbial forensics and clinical diagnostics. These data suggest that a relatively simple fingerprinting microarray and statistical analysis method can differentiate between species in the Bacillus cereus complex, and between strains of B. anthracis. A synthetic DNA standard was used to understand underlying microarray and process-level variability, leading to specific recommendations for the development of a standard operating procedure and/or continued technology enhancements for microbial forensics and diagnostics.

  11. Shrinkage covariance matrix approach for microarray data

    NASA Astrophysics Data System (ADS)

    Karjanto, Suryaefiza; Aripin, Rasimah

    2013-04-01

    Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n < p. This leads to a biased estimate of the covariance matrix. In this study, the Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.

  12. Minimizing DNA microarrays to a single molecule per spot: using zero-mode waveguide technology to obtain kinetic data for a large number of short oligonucleotide hybridization reactions

    NASA Astrophysics Data System (ADS)

    Sobek, Jens; Rehrauer, Hubert; Kuhn, Gerrit; Schlapbach, Ralph

    2016-03-01

    We have shown recently that the hybridization of short oligonucleotides can be studied in a zero-mode waveguide nanostructure (ZMW) chip using a modified DNA sequencer.[1] Here we present an extension of this method enabling the parallel measurement of kinetic constants of a large number of hybridization reactions on a single chip. This can be achieved by immobilization of a mixture of oligonucleotides, which leads to a statistical and random distribution of single molecules in the 150'000 ZMWs of a SMRT™ cell. This setup is comparable to a classical microarray with ZMWs in place of spots but unknown allocation of probes. The probe surface density is reduced by a factor of ~1010 allowing the study of hybridization in the absence of interactions with neighboring probes. Hybridization with a dye labelled oligonucleotide results in trains of fluorescence pulses from which interpulse durations (IPDs) and pulse widths (PWs) can be extracted. Since the identity of a probe in a ZMW is unknown, the immobilized oligonucleotide is sequenced in a subsequent step. After mapping the fluorescence traces to the sequence, the association and dissociation rate constant for each oligonucleotide can be calculated. By selecting suitable probes, the method can be used to determine rate constants of hybridization for a large number of mismatch oligonucleotides in a single measurement and at single-molecule level.

  13. Development and Applications of the Lectin Microarray.

    PubMed

    Hirabayashi, Jun; Kuno, Atsushi; Tateno, Hiroaki

    2015-01-01

    The lectin microarray is an emerging technology for glycomics. It has already found maximum use in diverse fields of glycobiology by providing simple procedures for differential glycan profiling in a rapid and high-throughput manner. Since its first appearance in the literature in 2005, many application methods have been developed essentially on the same platform, comprising a series of glycan-binding proteins immobilized on an appropriate substrate such as a glass slide. Because the lectin microarray strategy does not require prior liberation of glycans from the core protein in glycoprotein analysis, it should encourage researchers not familiar with glycotechnology to use glycan analysis in future work. This feasibility should provide a broader range of experimental scientists with good opportunities to investigate novel aspects of glycoscience. Applications of the technology include not only basic sciences but also the growing fields of bio-industry. This chapter describes first the essence of glycan profiling and the basic fabrication of the lectin microarray for this purpose. In the latter part the focus is on diverse applications to both structural and functional glycomics, with emphasis on the wide applicability now available with this new technology. Finally, the importance of developing advanced lectin engineering is discussed.

  14. Ecotoxicogenomics: Microarray interlaboratory comparability.

    PubMed

    Vidal-Dorsch, Doris E; Bay, Steven M; Moore, Shelly; Layton, Blythe; Mehinto, Alvine C; Vulpe, Chris D; Brown-Augustine, Marianna; Loguinov, Alex; Poynton, Helen; Garcia-Reyero, Natàlia; Perkins, Edward J; Escalon, Lynn; Denslow, Nancy D; Cristina, Colli-Dula R; Doan, Tri; Shukradas, Shweta; Bruno, Joy; Brown, Lorraine; Van Agglen, Graham; Jackman, Paula; Bauer, Megan

    2016-02-01

    Transcriptomic analysis can complement traditional ecotoxicology data by providing mechanistic insight, and by identifying sub-lethal organismal responses and contaminant classes underlying observed toxicity. Before transcriptomic information can be used in monitoring and risk assessment, it is necessary to determine its reproducibility and detect key steps impacting the reliable identification of differentially expressed genes. A custom 15K-probe microarray was used to conduct transcriptomics analyses across six laboratories with estuarine amphipods exposed to cyfluthrin-spiked or control sediments (10 days). Two sample types were generated, one consisted of total RNA extracts (Ex) from exposed and control samples (extracted by one laboratory) and the other consisted of exposed and control whole body amphipods (WB) from which each laboratory extracted RNA. Our findings indicate that gene expression microarray results are repeatable. Differentially expressed data had a higher degree of repeatability across all laboratories in samples with similar RNA quality (Ex) when compared to WB samples with more variable RNA quality. Despite such variability a subset of genes were consistently identified as differentially expressed across all laboratories and sample types. We found that the differences among the individual laboratory results can be attributed to several factors including RNA quality and technical expertise, but the overall results can be improved by following consistent protocols and with appropriate training.

  15. Identifying Fishes through DNA Barcodes and Microarrays

    PubMed Central

    Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N.; Weber, Hannes; Blohm, Dietmar

    2010-01-01

    Background International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. Methodology/Principal Findings This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of “DNA barcoding” and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the “position of label” effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Conclusions/Significance Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products. PMID

  16. Microarray analysis at single molecule resolution

    PubMed Central

    Mureşan, Leila; Jacak, Jarosław; Klement, Erich Peter; Hesse, Jan; Schütz, Gerhard J.

    2010-01-01

    Bioanalytical chip-based assays have been enormously improved in sensitivity in the recent years; detection of trace amounts of substances down to the level of individual fluorescent molecules has become state of the art technology. The impact of such detection methods, however, has yet not fully been exploited, mainly due to a lack in appropriate mathematical tools for robust data analysis. One particular example relates to the analysis of microarray data. While classical microarray analysis works at resolutions of two to 20 micrometers and quantifies the abundance of target molecules by determining average pixel intensities, a novel high resolution approach [1] directly visualizes individual bound molecules as diffraction limited peaks. The now possible quantification via counting is less susceptible to labeling artifacts and background noise. We have developed an approach for the analysis of high-resolution microarray images. It consists first of a single molecule detection step, based on undecimated wavelet transforms, and second, of a spot identification step via spatial statistics approach (corresponding to the segmentation step in the classical microarray analysis). The detection method was tested on simulated images with a concentration range of 0.001 to 0.5 molecules per square micron and signal-to-noise ratio (SNR) between 0.9 and 31.6. For SNR above 15 the false negatives relative error was below 15%. Separation of foreground/background proved reliable, in case foreground density exceeds background by a factor of 2. The method has also been applied to real data from high-resolution microarray measurements. PMID:20123580

  17. A brief introduction to tiling microarrays: principles, concepts, and applications.

    PubMed

    Lemetre, Christophe; Zhang, Zhengdong D

    2013-01-01

    Technological achievements have always contributed to the advancement of biomedical research. It has never been more so than in recent times, when the development and application of innovative cutting-edge technologies have transformed biology into a data-rich quantitative science. This stunning revolution in biology primarily ensued from the emergence of microarrays over two decades ago. The completion of whole-genome sequencing projects and the advance in microarray manufacturing technologies enabled the development of tiling microarrays, which gave unprecedented genomic coverage. Since their first description, several types of application of tiling arrays have emerged, each aiming to tackle a different biological problem. Although numerous algorithms have already been developed to analyze microarray data, new method development is still needed not only for better performance but also for integration of available microarray data sets, which without doubt constitute one of the largest collections of biological data ever generated. In this chapter we first introduce the principles behind the emergence and the development of tiling microarrays, and then discuss with some examples how they are used to investigate different biological problems.

  18. Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

    PubMed Central

    Biyani, Manish; Ichiki, Takanori

    2015-01-01

    Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era.

  19. [Genomic medicine. Polymorphisms and microarray applications].

    PubMed

    Spalvieri, Mónica P; Rotenberg, Rosa G

    2004-01-01

    This update shows new concepts related to the significance of DNA variations among individuals, as well as to their detection by using a new technology. The sequencing of the human genome is only the beginning of what will enable us to understand genetic diversity. The unit of DNA variability is the polymorphism of a single nucleotide (SNP). At present, studies on SNPs are restricted to basic research but the large number of papers on this subject makes feasible their entrance into clinical practice. We illustrate here the use of SNPs as molecular markers in ethnical genotyping, gene expression in some diseases and as potential targets in pharmacological response, and also introduce the technology of arrays. Microarrays experiments allow the quantification and comparison of gene expression on a large scale, at the same time, by using special chips and array designs. Conventional methods provide data from up to 20 genes, while a single microarray may provide information about thousands of them simultaneously, leading to a more rapid and accurate genotyping. Biotechnology improvements will facilitate our knowledge of each gene sequence, the frequency and exact location of SNPs and their influence on cellular behavior. Although experimental efficiency and validity of results from microarrays are still controversial, the knowledge and characterization of a patient's genetic profile will lead, undoubtedly, to advances in prevention, diagnosis, prognosis and treatment of human diseases. PMID:15637833

  20. Protein Microarrays with Novel Microfluidic Methods: Current Advances

    PubMed Central

    Dixit, Chandra K.; Aguirre, Gerson R.

    2014-01-01

    Microfluidic-based micromosaic technology has allowed the pattering of recognition elements in restricted micrometer scale areas with high precision. This controlled patterning enabled the development of highly multiplexed arrays multiple analyte detection. This arraying technology was first introduced in the beginning of 2001 and holds tremendous potential to revolutionize microarray development and analyte detection. Later, several microfluidic methods were developed for microarray application. In this review we discuss these novel methods and approaches which leverage the property of microfluidic technologies to significantly improve various physical aspects of microarray technology, such as enhanced imprinting homogeneity, stability of the immobilized biomolecules, decreasing assay times, and reduction of the costs and of the bulky instrumentation. PMID:27600343

  1. Statistical Considerations for Analysis of Microarray Experiments

    PubMed Central

    Owzar, Kouros; Barry, William T.; Jung, Sin-Ho

    2014-01-01

    Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generate a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results. PMID:22212230

  2. A Flexible Microarray Data Simulation Model

    PubMed Central

    Dembélé, Doulaye

    2013-01-01

    Microarray technology allows monitoring of gene expression profiling at the genome level. This is useful in order to search for genes involved in a disease. The performances of the methods used to select interesting genes are most often judged after other analyzes (qPCR validation, search in databases...), which are also subject to error. A good evaluation of gene selection methods is possible with data whose characteristics are known, that is to say, synthetic data. We propose a model to simulate microarray data with similar characteristics to the data commonly produced by current platforms. The parameters used in this model are described to allow the user to generate data with varying characteristics. In order to show the flexibility of the proposed model, a commented example is given and illustrated. An R package is available for immediate use.

  3. Profiling protein function with small molecule microarrays

    PubMed Central

    Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

    2002-01-01

    The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

  4. 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

    EPA Science Inventory

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

  5. Isolation of Microarray-Grade Total RNA, MicroRNA, and DNA from a Single PAXgene Blood RNA Tube

    PubMed Central

    Kruhøffer, Mogens; Dyrskjøt, Lars; Voss, Thorsten; Lindberg, Raija L.P.; Wyrich, Ralf; Thykjaer, Thomas; Orntoft, Torben F.

    2007-01-01

    We have developed a procedure for isolation of microRNA and genomic DNA in addition to total RNA from whole blood stabilized in PAXgene Blood RNA tubes. The procedure is based on automatic extraction on a BioRobot MDx and includes isolation of DNA from a fraction of the stabilized blood and recovery of small RNA species that are otherwise lost. The procedure presented here is suitable for large-scale experiments and is amenable to further automation. Procured total RNA and DNA was tested using Affymetrix Expression and single-nucleotide polymorphism GeneChips, respectively, and isolated microRNA was tested using spotted locked nucleic acid-based microarrays. We conclude that the yield and quality of total RNA, microRNA, and DNA from a single PAXgene blood RNA tube is sufficient for downstream microarray analysis. PMID:17690207

  6. Applications in high-content functional protein microarrays.

    PubMed

    Moore, Cedric D; Ajala, Olutobi Z; Zhu, Heng

    2016-02-01

    Protein microarray technology provides a versatile platform for characterization of hundreds to thousands of proteins in a parallel and high-throughput manner. Over the last decade, applications of functional protein microarrays in particular have flourished in studying protein function at a systems level and have led to the construction of networks and pathways describing these functions. Relevant areas of research include the detection of various binding properties of proteins, the study of enzyme-substrate relationships, the analysis of host-microbe interactions, and profiling antibody specificity. In addition, discovery of novel biomarkers in autoimmune diseases and cancers is emerging as a major clinical application of functional protein microarrays. In this review, we will summarize the recent advances of functional protein microarrays in both basic and clinical applications. PMID:26599287

  7. Basic Concepts of Microarrays and Potential Applications in Clinical Microbiology

    PubMed Central

    Miller, Melissa B.; Tang, Yi-Wei

    2009-01-01

    Summary: The introduction of in vitro nucleic acid amplification techniques, led by real-time PCR, into the clinical microbiology laboratory has transformed the laboratory detection of viruses and select bacterial pathogens. However, the progression of the molecular diagnostic revolution currently relies on the ability to efficiently and accurately offer multiplex detection and characterization for a variety of infectious disease pathogens. Microarray analysis has the capability to offer robust multiplex detection but has just started to enter the diagnostic microbiology laboratory. Multiple microarray platforms exist, including printed double-stranded DNA and oligonucleotide arrays, in situ-synthesized arrays, high-density bead arrays, electronic microarrays, and suspension bead arrays. One aim of this paper is to review microarray technology, highlighting technical differences between them and each platform's advantages and disadvantages. Although the use of microarrays to generate gene expression data has become routine, applications pertinent to clinical microbiology continue to rapidly expand. This review highlights uses of microarray technology that impact diagnostic microbiology, including the detection and identification of pathogens, determination of antimicrobial resistance, epidemiological strain typing, and analysis of microbial infections using host genomic expression and polymorphism profiles. PMID:19822891

  8. Gene expression in the rat brain during sleep deprivation and recovery sleep: an Affymetrix GeneChip study.

    PubMed

    Terao, A; Wisor, J P; Peyron, C; Apte-Deshpande, A; Wurts, S W; Edgar, D M; Kilduff, T S

    2006-01-01

    Previous studies have demonstrated that macromolecular synthesis in the brain is modulated in association with the occurrence of sleep and wakefulness. Similarly, the spectral composition of electroencephalographic activity that occurs during sleep is dependent on the duration of prior wakefulness. Since this homeostatic relationship between wake and sleep is highly conserved across mammalian species, genes that are truly involved in the electroencephalographic response to sleep deprivation might be expected to be conserved across mammalian species. Therefore, in the rat cerebral cortex, we have studied the effects of sleep deprivation on the expression of immediate early gene and heat shock protein mRNAs previously shown to be upregulated in the mouse brain in sleep deprivation and in recovery sleep after sleep deprivation. We find that the molecular response to sleep deprivation and recovery sleep in the brain is highly conserved between these two mammalian species, at least in terms of expression of immediate early gene and heat shock protein family members. Using Affymetrix Neurobiology U34 GeneChips , we also screened the rat cerebral cortex, basal forebrain, and hypothalamus for other genes whose expression may be modulated by sleep deprivation or recovery sleep. We find that the response of the basal forebrain to sleep deprivation is more similar to that of the cerebral cortex than to the hypothalamus. Together, these results suggest that sleep-dependent changes in gene expression in the cerebral cortex are similar across rodent species and therefore may underlie sleep history-dependent changes in sleep electroencephalographic activity.

  9. Profiling in situ microbial community structure with an amplification microarray.

    PubMed

    Chandler, Darrell P; Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H; Peacock, Aaron D; Long, Philip E

    2013-02-01

    The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO(3)(-)) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO(3), but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications.

  10. Profiling In Situ Microbial Community Structure with an Amplification Microarray

    PubMed Central

    Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

    2013-01-01

    The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

  11. Comparison of microarray preprocessing methods.

    PubMed

    Shakya, K; Ruskin, H J; Kerr, G; Crane, M; Becker, J

    2010-01-01

    Data preprocessing in microarray technology is a crucial initial step before data analysis is performed. Many preprocessing methods have been proposed but none has proved to be ideal to date. Frequently, datasets are limited by laboratory constraints so that the need is for guidelines on quality and robustness, to inform further experimentation while data are yet restricted. In this paper, we compared the performance of four popular methods, namely MAS5, Li & Wong pmonly (LWPM), Li & Wong subtractMM (LWMM), and Robust Multichip Average (RMA). The comparison is based on the analysis carried out on sets of laboratory-generated data from the Bioinformatics Lab, National Institute of Cellular Biotechnology (NICB), Dublin City University, Ireland. These experiments were designed to examine the effect of Bromodeoxyuridine (5-bromo-2-deoxyuridine, BrdU) treatment in deep lamellar keratoplasty (DLKP) cells. The methodology employed is to assess dispersion across the replicates and analyze the false discovery rate. From the dispersion analysis, we found that variability is reduced more effectively by LWPM and RMA methods. From the false positive analysis, and for both parametric and nonparametric approaches, LWMM is found to perform best. Based on a complementary q-value analysis, LWMM approach again is the strongest candidate. The indications are that, while LWMM is marginally less effective than LWPM and RMA in terms of variance reduction, it has considerably improved discrimination overall.

  12. AMIC@: All MIcroarray Clusterings @ once.

    PubMed

    Geraci, Filippo; Pellegrini, Marco; Renda, M Elena

    2008-07-01

    The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica.

  13. Transcript-Specific Expression Profiles Derived from Sequence-Based Analysis of Standard Microarrays

    PubMed Central

    Moll, Anton G.; Lindenmeyer, Maja T.; Kretzler, Matthias; Nelson, Peter J.; Zimmer, Ralf; Cohen, Clemens D.

    2009-01-01

    Background Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the re-analysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression levels of specific transcripts. Methodology/Principal Findings In the present study alignment of probe sequences of the Affymetrix microarray HG-U133A with Ensembl transcript sequences was performed to define transcript-specific probe sets. Out of a total of 247,965 perfect match probes, 95,008 were designated “transcript-specific”, i.e. showing complete sequence alignment, no cross-hybridization, and transcript-, not only gene-specificity. These probes were grouped into 7,941 transcript-specific probe sets and 15,619 gene-specific probe sets, respectively. The former were used to differentiate 445 alternative transcripts of 215 genes. For selected transcripts, predicted by this analysis to be differentially expressed in the human kidney, confirmatory real-time RT-PCR experiments were performed. First, the expression of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was determined by the transcript-specific array analysis and confirmed by real-time RT-PCR. Secondly, disease-specific differential expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and Q5VYS0_HUMAN) was computed from the available array data sets and confirmed by transcript-specific real-time RT-PCR. Conclusions Transcript-specific analysis of microarray experiments can be employed to study gene-regulation on the transcript level using conventional microarray data. In this study, predictions based on sufficient probe set size and

  14. Fine-scaled human genetic structure revealed by SNP microarrays.

    PubMed

    Xing, Jinchuan; Watkins, W Scott; Witherspoon, David J; Zhang, Yuhua; Guthery, Stephen L; Thara, Rangaswamy; Mowry, Bryan J; Bulayeva, Kazima; Weiss, Robert B; Jorde, Lynn B

    2009-05-01

    We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure. PMID:19411602

  15. Fine-scaled human genetic structure revealed by SNP microarrays.

    PubMed

    Xing, Jinchuan; Watkins, W Scott; Witherspoon, David J; Zhang, Yuhua; Guthery, Stephen L; Thara, Rangaswamy; Mowry, Bryan J; Bulayeva, Kazima; Weiss, Robert B; Jorde, Lynn B

    2009-05-01

    We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure.

  16. GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox1[w

    PubMed Central

    Zimmermann, Philip; Hirsch-Hoffmann, Matthias; Hennig, Lars; Gruissem, Wilhelm

    2004-01-01

    High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch. PMID:15375207

  17. Microarray analysis in gastric cancer: A review

    PubMed Central

    D’Angelo, Giovanna; Di Rienzo, Teresa; Ojetti, Veronica

    2014-01-01

    Gastric cancer is one of the most common tumors worldwide. Although several treatment options have been developed, the mortality rate is increasing. Lymph node involvement is considered the most reliable prognostic indicator in gastric cancer. Early diagnosis improves the survival rate of patients and increases the likelihood of successful treatment. The most reliable diagnostic method is endoscopic examination, however, it is expensive and not feasible in poorer countries. Therefore, many innovative techniques have been studied to develop a new non-invasive screening test and to identify specific serum biomarkers. DNA microarray analysis is one of the new technologies able to measure the expression levels of a large number of genes simultaneously. It is possible to define the gene expression profile of the tumor and to correlate it with the prognosis and metastasis formation. Several studies in the literature have been published on the role of microarray analysis in gastric cancer and the mechanisms of proliferation and metastasis formation. The aim of this review is to analyze the importance of microarray analysis and its clinical applications to better define the genetic characteristics of gastric cancer and its possible implications in a more decisive treatment. PMID:25232233

  18. High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses.

    PubMed

    Abd El-Rehim, Dalia M; Ball, Graham; Pinder, Sarah E; Rakha, Emad; Paish, Claire; Robertson, John F R; Macmillan, Douglas; Blamey, Roger W; Ellis, Ian O

    2005-09-01

    Recent studies on gene molecular profiling using cDNA microarray in a relatively small series of breast cancer have identified biologically distinct groups with apparent clinical and prognostic relevance. The validation of such new taxonomies should be confirmed on larger series of cases prior to acceptance in clinical practice. The development of tissue microarray (TMA) technology provides methodology for high-throughput concomitant analyses of multiple proteins on large numbers of archival tumour samples. In our study, we have used immunohistochemistry techniques applied to TMA preparations of 1,076 cases of invasive breast cancer to study the combined protein expression profiles of a large panel of well-characterized commercially available biomarkers related to epithelial cell lineage, differentiation, hormone and growth factor receptors and gene products known to be altered in some forms of breast cancer. Using hierarchical clustering methodology, 5 groups with distinct patterns of protein expression were identified. A sixth group of only 4 cases was also identified but deemed too small for further detailed assessment. Further analysis of these clusters was performed using multiple layer perceptron (MLP)-artificial neural network (ANN) with a back propagation algorithm to identify key biomarkers driving the membership of each group. We have identified 2 large groups by their expression of luminal epithelial cell phenotypic characteristics, hormone receptors positivity, absence of basal epithelial phenotype characteristics and lack of c-erbB-2 protein overexpression. Two additional groups were characterized by high c-erbB-2 positivity and negative or weak hormone receptors expression but showed differences in MUC1 and E-cadherin expression. The final group was characterized by strong basal epithelial characteristics, p53 positivity, absent hormone receptors and weak to low luminal epithelial cytokeratin expression. In addition, we have identified significant

  19. Microarray Analysis of Microbial Weathering

    NASA Astrophysics Data System (ADS)

    Olsson-Francis, K.; van Houdt, R.; Leys, N.; Mergeay, M.; Cockell, C. S.

    2010-04-01

    Microarray analysis of the heavy metal resistant bacterium, Cupriavidus metallidurans CH34 was used to investigate the genes involved in the weathering. The results demonstrated that large porin and membrane transporter genes were unregulated.

  20. Microarray analysis of the AHR system: Tissue-specific flexibility in signal and target genes

    SciTech Connect

    Frericks, Markus; Meissner, Marc; Esser, Charlotte . E-mail: chesser@uni-duesseldorf.de

    2007-05-01

    Data mining published microarray experiments require that expression profiles are directly comparable. We performed linear global normalization on the data of 1967 Affymetrix U74av2 microarrays, i.e. the transcriptomes of > 100 murine tissues or cell types. The mathematical transformation effectively nullifies inter-experimental or inter-laboratory differences between microarrays. The correctness of expression values was validated by quantitative RT-PCR. Using the database we analyze components of the aryl hydrocarbon receptor (AHR) signaling pathway in various tissues. We identified lineage and differentiation specific variant expression of AHR, ARNT, and HIF1{alpha} in the T-cell lineage and high expression of CYP1A1 in immature B cells and dendritic cells. Performing co-expression analysis we found unorthodox expression of the AHR in the absence of ARNT, particularly in stem cell populations, and can reject the hypothesis that ARNT2 takes over and is highly expressed when ARNT expression is low or absent. Furthermore the AHR shows no co-expression with any other transcript present on the chip. Analysis of differential gene expression under 308 conditions revealed 53 conditions under which the AHR is regulated, numerous conditions under which an intrinsic AHR action is modified as well as conditions activating the AHR even in the absence of known AHR ligands. Thus meta-analysis of published expression profiles is a powerful tool to gain novel insights into known and unknown systems.

  1. Optimization of gene expression microarray protocol for formalin-fixed paraffin-embedded tissues.

    PubMed

    Belder, Nevin; Coşkun, Öznur; Erdoğan, Beyza Doğanay; Savaş, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-03-01

    Formalin-fixed paraffin-embedded (FFPE) tissue is a widely available clinical specimen for retrospective studies. The possibility of long-term clinical follow-up of FFPE samples makes them a valuable source to evaluate links between molecular and clinical information. Working with FFPE samples in the molecular research area, especially using high-throughput molecular techniques such as microarray gene expression profiling, has come into prominence. Because of the harmful effects of formalin fixation process such as degradation of nucleic acids, cross-linking with proteins, and chemical modifications on DNA and RNA, there are some limitations in gene expression profiling studies using FFPE samples. To date many studies have been conducted to evaluate gene expression profiling using microarrays (Thomas et al., Thomas et al. (2013) [1]; Scicchitano et al., Scicchitano et al. (2006) [2]; Frank et al., Frank et al. (2007) [3]; Fedorowicz et al., Fedorowicz et al. (2009) [4]). However, there is still no generally accepted, efficient and standardized procedure for microarray analysis of FFPE samples. This paper describes the microarray data presented in our recently accepted to be published article showing a standard protocol from deparaffinization of FFPE tissue sections and RNA extraction to microarray gene expression analysis. Here we represent our data in detail, deposited in the gene expression omnibus (GEO) database with the accession number GSE73883. Four combinations of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) were evaluated to determine which combination gives the best percentage of present call. The study presents a dataset for comparative analysis which has a potential in terms of providing a robust protocol for gene expression profiling with FFPE tissue samples. PMID:26981433

  2. Optimization of gene expression microarray protocol for formalin-fixed paraffin-embedded tissues.

    PubMed

    Belder, Nevin; Coşkun, Öznur; Erdoğan, Beyza Doğanay; Savaş, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-03-01

    Formalin-fixed paraffin-embedded (FFPE) tissue is a widely available clinical specimen for retrospective studies. The possibility of long-term clinical follow-up of FFPE samples makes them a valuable source to evaluate links between molecular and clinical information. Working with FFPE samples in the molecular research area, especially using high-throughput molecular techniques such as microarray gene expression profiling, has come into prominence. Because of the harmful effects of formalin fixation process such as degradation of nucleic acids, cross-linking with proteins, and chemical modifications on DNA and RNA, there are some limitations in gene expression profiling studies using FFPE samples. To date many studies have been conducted to evaluate gene expression profiling using microarrays (Thomas et al., Thomas et al. (2013) [1]; Scicchitano et al., Scicchitano et al. (2006) [2]; Frank et al., Frank et al. (2007) [3]; Fedorowicz et al., Fedorowicz et al. (2009) [4]). However, there is still no generally accepted, efficient and standardized procedure for microarray analysis of FFPE samples. This paper describes the microarray data presented in our recently accepted to be published article showing a standard protocol from deparaffinization of FFPE tissue sections and RNA extraction to microarray gene expression analysis. Here we represent our data in detail, deposited in the gene expression omnibus (GEO) database with the accession number GSE73883. Four combinations of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) were evaluated to determine which combination gives the best percentage of present call. The study presents a dataset for comparative analysis which has a potential in terms of providing a robust protocol for gene expression profiling with FFPE tissue samples.

  3. Label and Label-Free Detection Techniques for Protein Microarrays

    PubMed Central

    Syahir, Amir; Usui, Kenji; Tomizaki, Kin-ya; Kajikawa, Kotaro; Mihara, Hisakazu

    2015-01-01

    Protein microarray technology has gone through numerous innovative developments in recent decades. In this review, we focus on the development of protein detection methods embedded in the technology. Early microarrays utilized useful chromophores and versatile biochemical techniques dominated by high-throughput illumination. Recently, the realization of label-free techniques has been greatly advanced by the combination of knowledge in material sciences, computational design and nanofabrication. These rapidly advancing techniques aim to provide data without the intervention of label molecules. Here, we present a brief overview of this remarkable innovation from the perspectives of label and label-free techniques in transducing nano-biological events.

  4. A protein multiplex microarray substrate with high sensitivity and specificity

    PubMed Central

    Fici, Dolores A.; McCormick, William; Brown, David W.; Herrmann, John E.; Kumar, Vikram; Awdeh, Zuheir L.

    2010-01-01

    The problems that have been associated with protein multiplex microarray immunoassay substrates and existing technology platforms include: binding, sensitivity, a low signal to noise ratio, target immobilization and the optimal simultaneous detection of diverse protein targets. Current commercial substrates for planar multiplex microarrays rely on protein attachment chemistries that range from covalent attachment to affinity ligand capture, to simple adsorption. In this pilot study, experimental performance parameters for direct monoclonal mouse IgG detection were compared for available two and three dimensional slide surface coatings with a new colloidal nitrocellulose substrate. New technology multiplex microarrays were also developed and evaluated for the detection of pathogen specific antibodies in human serum and the direct detection of enteric viral antigens. Data supports the nitrocellulose colloid as an effective reagent with the capacity to immobilize sufficient diverse protein target quantities for increased specificory signal without compromising authentic protein structure. The nitrocellulose colloid reagent is compatible with the array spotters and scanners routinely used for microarray preparation and processing. More importantly, as an alternate to fluorescence, colorimetric chemistries may be used for specific and sensitive protein target detection. The advantages of the nitrocellulose colloid platform indicate that this technology may be a valuable tool for the further development and expansion of multiplex microarray immunoassays in both the clinical and research laborat environment. PMID:20974147

  5. eSensor®: A Microarray Technology Based on Electrochemical Detection of Nucleic Acids and Its Application to Cystic Fibrosis Carrier Screening

    NASA Astrophysics Data System (ADS)

    Reed, Michael R.; Coty, William A.

    We have developed a test for identification of carriers for cystic fibrosis using the eSensor® DNA detection technology. Oligonucleotide probes are deposited within self-assembled monolayers on gold electrodes arrayed upon printed circuit boards. These probes allow sequence-specific capture of amplicons containing a panel of mutation sites associated with cystic fibrosis. DNA targets are detected and mutations genotyped using a “sandwich” assay methodology employing electrochemical detection of ferrocene-labeled oligonucleotides for discrimination of carrier and non-carrier alleles. Performance of the cystic fibrosis application demonstrates sufficient accuracy and reliability for clinical diagnostic use, and the procedure can be performed by trained medical technologists available in the hospital laboratory.

  6. [Protein microarrays and personalized medicine].

    PubMed

    Yu, Xiabo; Schneiderhan-Marra, Nicole; Joos, Thomas O

    2011-01-01

    Over the last 10 years, DNA microarrays have achieved a robust analytical performance, enabling their use for analyzing the whole transcriptome or for screening thousands of single-nucleotide polymorphisms in a single experiment. DNA microarrays allow scientists to correlate gene expression signatures with disease progression, to screen for disease-specific mutations, and to treat patients according to their individual genetic profiles; however, the real key is proteins and their manifold functions. It is necessary to achieve a greater understanding of not only protein function and abundance but also their role in the development of diseases. Protein concentrations have been shown to reflect the physiological and pathologic state of an organ, tissue, or cells far more directly than DNA, and proteins can be profiled effectively with protein microarrays, which require only a small amount of sample material. Protein microarrays have become wellestablished tools in basic and applied research, and the first products have already entered the in vitro diagnostics market. This review focuses on protein microarray applications for biomarker discovery and validation, disease diagnosis, and use within the area of personalized medicine. Protein microarrays have proved to be reliable research tools in screening for a multitude of parameters with only a minimal quantity of sample and have enormous potential in applications for diagnostic and personalized medicine.

  7. Design and analysis of mismatch probes for long oligonucleotide microarrays

    SciTech Connect

    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

  8. Emerging Use of Gene Expression Microarrays in Plant Physiology

    DOE PAGES

    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 weremore » 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.« less

  9. Emerging Use of Gene Expression Microarrays in Plant Physiology

    PubMed Central

    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. PMID:18629133

  10. Human papilloma virus strain detection utilising custom-designed oligonucleotide microarrays.

    PubMed

    Ayers, Duncan; Platt, Mark; Javad, Farzad; Day, Philip J R

    2011-01-01

    Within the past 15 years, the utilisation of microarray technology for the detection of specific pathogen strains has increased rapidly. Presently, it is possible to simply purchase a pre-manufactured "off the shelf " oligonucleotide microarray bearing a wide variety of known signature DNA sequences previously identified in the organism being studied. Consequently, a hybridisation analysis may be used to pinpoint which strain/s is present in any given clinical sample. However, there exists a problem if the study necessitates the identification of novel sequences which are not represented in commercially available microarray chips. Ideally, such investigations require an in situ oligonucleotide microarray platform with the capacity to synthesise microarrays bearing probe sequences designed solely by the researcher. This chapter will focus on the employment of the Combimatrix® B3 CustomArray™ for the synthesis of reusable, bespoke microarrays for the purpose of discerning multiple Human Papilloma Virus strains. PMID:20938834

  11. A lectin-based cell microarray approach to analyze the mammalian granulosa cell surface glycosylation profile.

    PubMed

    Accogli, Gianluca; Desantis, Salvatore; Martino, Nicola Antonio; Dell'Aquila, Maria Elena; Gemeiner, Peter; Katrlík, Jaroslav

    2016-10-01

    The high complexity of glycome, the repertoire of glycans expressed in a cell or in an organism, is difficult to analyze and the use of new technologies has accelerated the progress of glycomics analysis. In the last decade, the microarray approaches, and in particular glycan and lectin microarrays, have provided new insights into evaluation of cell glycosylation status. Here we present a cell microarray method based on cell printing on microarray slides for the analysis of the glycosylation pattern of the cell glycocalyx. In order to demonstrate the reliability of the developed method, the glycome profiles of equine native uncultured mural granulosa cells (uGCs) and in vitro cultured mural granulosa cells (cGCs) were determined and compared. The method consists in the isolation of GCs, cell printing into arrays on microarray slide, incubation with a panel of biotinylated lectins, reaction with fluorescent streptavidin and signal intensity detection by a microarray scanner. Cell microarray technology revealed that glycocalyx of both uGCs and cGCs contains N-glycans, sialic acid terminating glycans, N-acetylglucosamine and O-glycans. The comparison of uGCs and cGCs glycan signals indicated an increase in the expression of sialic acids, N-acetylglucosamine, and N-glycans in cGCs. Glycan profiles determined by cell microarray agreed with those revealed by lectin histochemistry. The described cell microarray method represents a simple and sensitive procedure to analyze cell surface glycome in mammalian cells.

  12. Changes in the peripheral blood transcriptome associated with occupational benzene exposure identified by cross-comparison on two microarray platforms

    SciTech Connect

    McHale, Cliona M.; Zhang, Luoping; Lan, Qing; Li, Guilan; Hubbard, Alan E.; Forrest, Matthew S.; Vermeulen, Roel; Chen, Jinsong; Shen, Min; Rappaport, Stephen M.; Yin, Songnian; Smith, Martyn T.; Rothman, Nathaniel

    2009-03-01

    Benzene is an established cause of leukemia and a possible cause of lymphoma in humans but the molecular pathways underlying this remain largely undetermined. This study sought to determine if the use of two different microarray platforms could identify robust global gene expression and pathway changes associated with occupational benzene exposure in the peripheral blood mononuclear cell (PBMC) gene expression of a population of shoe-factory workers with well-characterized occupational exposures to benzene. Microarray data was analyzed by a robust t-test using a Quantile Transformation (QT) approach. Differential expression of 2692 genes using the Affymetrix platform and 1828 genes using the Illumina platform was found. While the overall concordance in genes identified as significantly associated with benzene exposure between the two platforms was 26% (475 genes), the most significant genes identified by either array were more likely to be ranked as significant by the other platform (Illumina = 64%, Affymetrix = 58%). Expression ratios were similar among the concordant genes (mean difference in expression ratio = 0.04, standard deviation = 0.17). Four genes (CXCL16, ZNF331, JUN and PF4), which we previously identified by microarray and confirmed by real-time PCR, were identified by both platforms in the current study and were among the top 100 genes. Gene Ontology analysis showed over representation of genes involved in apoptosis among the concordant genes while Ingenuity{reg_sign} Pathway Analysis (IPA) identified pathways related to lipid metabolism. Using a two-platform approach allows for robust changes in the PBMC transcriptome of benzene-exposed individuals to be identified.

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

    PubMed

    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.

  14. MACRORESULTS THROUGH MICROARRAYS

    EPA Science Inventory

    The third enactment of Cambridge Healthtech Institute's "Macroresults through Macroarrays" meeting was held in Boston, MA, from April 29th-May 1st, 2002. The subtheme of this year's meeting was "advancing drug discovery," a widely touted application for array technology. The agen...

  15. A biomimetic algorithm for the improved detection of microarray features

    NASA Astrophysics Data System (ADS)

    Nicolau, Dan V., Jr.; Nicolau, Dan V.; Maini, Philip K.

    2007-02-01

    One the major difficulties of microarray technology relate to the processing of large and - importantly - error-loaded images of the dots on the chip surface. Whatever the source of these errors, those obtained in the first stage of data acquisition - segmentation - are passed down to the subsequent processes, with deleterious results. As it has been demonstrated recently that biological systems have evolved algorithms that are mathematically efficient, this contribution attempts to test an algorithm that mimics a bacterial-"patented" algorithm for the search of available space and nutrients to find, "zero-in" and eventually delimitate the features existent on the microarray surface.

  16. Unravelling Microbial Communities with DNA-Microarrays: Challengesand Future Directions.

    SciTech Connect

    Wagner, Michael; Smidt, Hauke; Loy, Alexander; Zhou, Jizhong

    2007-03-08

    High-throughput technologies are urgently needed formonitoring the formidable biodiversity and functional capabilities ofmicroorganisms in the environment. Ten years ago, DNA microarrays,miniaturized platforms for highly parallel hybridization reactions, foundtheir way into environmental microbiology and raised great expectationsamong researchers in the field. In this article, we briefly summarize thestate-of-the-art of microarray approaches in microbial ecology researchand discuss in more detail crucial problems and promising solutions.Finally, we outline scenarios for an innovative combination ofmicroarrays with other molecular tools for structure-function analysis ofcomplex microbial communities.

  17. ADAPTING MICROARRAY TECHNOLOGY FOR USE IN ECOTOXICOGENOMICS

    EPA Science Inventory

    Ecotoxicogenomics includes research to identify differential gene expression in laboratory and field animals exposed to toxicants, and ultimately, to link the earliest indicators of exposure to adverse effects in organisms and populations. The USEPA National Exposure Research La...

  18. CLUM: a cluster program for analyzing microarray data.

    PubMed

    Irigoien, I; Fernandez, E; Vives, S; Arenas, C

    2008-08-01

    Microarray technology is increasingly being applied in biological and medical research to address a wide range of problems. Cluster analysis has proven to be a very useful tool for investigating the structure of microarray data. This paper presents a program for clustering microarray data, which is based on the so call path-distance. The algorithm gives in each step a partition in two clusters and no prior assumptions on the structure of clusters are required. It assigns each object (gene or sample) to only one cluster and gives the global optimum for the function that quantifies the adequacy of a given partition of the sample into k clusters. The program was tested on experimental data sets, showing the robustness of the algorithm. PMID:18825964

  19. Analysis-Driven Lossy Compression of DNA Microarray Images.

    PubMed

    Hernández-Cabronero, Miguel; Blanes, Ian; Pinho, Armando J; Marcellin, Michael W; Serra-Sagristà, Joan

    2016-02-01

    DNA microarrays are one of the fastest-growing new technologies in the field of genetic research, and DNA microarray images continue to grow in number and size. Since analysis techniques are under active and ongoing development, storage, transmission and sharing of DNA microarray images need be addressed, with compression playing a significant role. However, existing lossless coding algorithms yield only limited compression performance (compression ratios below 2:1), whereas lossy coding methods may introduce unacceptable distortions in the analysis process. This work introduces a novel Relative Quantizer (RQ), which employs non-uniform quantization intervals designed for improved compression while bounding the impact on the DNA microarray analysis. This quantizer constrains the maximum relative error introduced into quantized imagery, devoting higher precision to pixels critical to the analysis process. For suitable parameter choices, the resulting variations in the DNA microarray analysis are less than half of those inherent to the experimental variability. Experimental results reveal that appropriate analysis can still be performed for average compression ratios exceeding 4.5:1.

  20. Microarray Developed on Plastic Substrates.

    PubMed

    Bañuls, María-José; Morais, Sergi B; Tortajada-Genaro, Luis A; Maquieira, Ángel

    2016-01-01

    There is a huge potential interest to use synthetic polymers as versatile solid supports for analytical microarraying. Chemical modification of polycarbonate (PC) for covalent immobilization of probes, micro-printing of protein or nucleic acid probes, development of indirect immunoassay, and development of hybridization protocols are described and discussed. PMID:26614067

  1. Microfluidic microarray systems and methods thereof

    SciTech Connect

    West, Jay A. A.; Hukari, Kyle W.; Hux, Gary A.

    2009-04-28

    Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

  2. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    NASA Astrophysics Data System (ADS)

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

    2014-09-01

    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.

  3. ASSESSING THE USE OF OLIGONUCLEOTIDE MICROARRAYS FOR FATHEAD MINNOW (PIMEPHALES PROMELAS) TO EXAMINE EXPOSURE VARIABLES

    EPA Science Inventory

    Microarray technology has proven to be a useful tool for analyzing the transcriptome of various organisms representing conditions such as disease states, developmental stages, and responses to chemical exposure. Although most commercially available arrays are limited to organism...

  4. Flow-pattern Guided Fabrication of High-density Barcode Antibody Microarray.

    PubMed

    Ramirez, Lisa S; Wang, Jun

    2016-01-06

    Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications.

  5. Recent advances and future applications of microfluidic live-cell microarrays.

    PubMed

    Rothbauer, Mario; Wartmann, David; Charwat, Verena; Ertl, Peter

    2015-11-01

    Microfluidic live-cell microarrays show much promise as screening tools for biomedical research because they could shed light on key biological processes such as cell signaling and cell-to-cell and cell-to-substrate dynamic responses. While miniaturization reduces the need for expensive clinical grade reagents, the integration of functional components including micropumps, biosensors, actuators, mixers and gradient generators results in improved assay reliability, reproducibility and well-defined cell culture conditions. The present review addresses recent technological advances in microfluidic live-cell microarray technology with a special focus on the applications of microfluidic single-cell, multi-cell and 3D cell microarrays.

  6. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

    PubMed Central

    Gürgan, Muazzez; Afşar Erkal, Nilüfer; Özgür, Ebru; Gündüz, Ufuk; Eroglu, Inci; Yücel, Meral

    2015-01-01

    Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C) and heat (42 °C) stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F). The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS) bacteria under temperature stress. PMID:26086826

  7. Clinical and microarray analysis of breast cancers of all subtypes from two prospective preoperative chemotherapy studies

    PubMed Central

    Okuma, H S; Koizumi, F; Hirakawa, A; Nakatochi, M; Komori, O; Hashimoto, J; Kodaira, M; Yunokawa, M; Yamamoto, H; Yonemori, K; Shimizu, C; Fujiwara, Y; Tamura, K

    2016-01-01

    Background: We aimed to analyse clinical and gene expression profiles to predict pathologic complete response and disease-free survival using two consecutive, prospective, preoperative chemotherapy trial cohorts. Methods: Clinicopathological and gene expression data were evaluated in a cohort from two consecutive phase II preoperative studies that included patients with stage IIA–IIIC breast cancer of all subtypes. Analysed specimens were obtained before preoperative chemotherapy, and cDNA microarray analyses were performed using the Affymetrix Gene Chip U133 plus 2.0. Results: Between December 2005 and December 2010, 122 patients were analysed. The pathologic complete response rate was significantly higher in HER2+ and HR−/HER2− cancers. Age, pathologic complete response, HR−/HER2− status, and lymph node positivity (⩾4) were significant poor prognostic factors for disease-free survival. For the cDNA microarray analyses, sufficient tumour samples were available from 78 of the 107 patients (73%). An 8-gene signature predictive of pathologic complete response and a 17-gene signature predictive of prognosis were identified. Patients were categorised into low-risk (n=45) and high-risk groups (n=33) (HR 70.0, P=0.004). Conclusions: This study yielded preliminary data on the expression of specific genes predicting pathologic complete response and disease-free survival in a cohort of chemonaïve breast cancer patients. Further validation may distinguish those who would benefit most from perioperative chemotherapy as well as those needing further intervention. PMID:27415010

  8. Comparison of High-Level Microarray Analysis Methods in the Context of Result Consistency

    PubMed Central

    Chrominski, Kornel; Tkacz, Magdalena

    2015-01-01

    Motivation When we were asked for help with high-level microarray data analysis (on Affymetrix HGU-133A microarray), we faced the problem of selecting an appropriate method. We wanted to select a method that would yield "the best result" (detected as many "really" differentially expressed genes (DEGs) as possible, without false positives and false negatives). However, life scientists could not help us – they use their "favorite" method without special argumentation. We also did not find any norm or recommendation. Therefore, we decided to examine it for our own purpose. We considered whether the results obtained using different methods of high-level microarray data analyses – Significant Analysis of Microarrays, Rank Products, Bland-Altman, Mann-Whitney test, T test and the Linear Models for Microarray Data – would be in agreement. Initially, we conducted a comparative analysis of the results on eight real data sets from microarray experiments (from the Array Express database). The results were surprising. On the same array set, the set of DEGs by different methods were significantly different. We also applied the methods to artificial data sets and determined some measures that allow the preparation of the overall scoring of tested methods for future recommendation. Results We found a very low level concordance of results from tested methods on real array sets. The number of common DEGs (detected by all six methods on fixed array sets, checked on eight array sets) ranged from 6 to 433 (22,283 total array readings). Results on artificial data sets were better than those on the real data. However, they were not fully satisfying. We scored tested methods on accuracy, recall, precision, f-measure and Matthews correlation coefficient. Based on the overall scoring, the best methods were SAM and LIMMA. We also found TT to be acceptable. The worst scoring was MW. Based on our study, we recommend: 1. Carefully taking into account the need for study when choosing a

  9. Disc-based microarrays: principles and analytical applications.

    PubMed

    Morais, Sergi; Puchades, Rosa; Maquieira, Ángel

    2016-07-01

    The idea of using disk drives to monitor molecular biorecognition events on regular optical discs has received considerable attention during the last decade. CDs, DVDs, Blu-ray discs and other new optical discs are universal and versatile supports with the potential for development of protein and DNA microarrays. Besides, standard disk drives incorporated in personal computers can be used as compact and affordable optical reading devices. Consequently, a CD technology, resulting from the audio-video industry, has been used to develop analytical applications in health care, environmental monitoring, food safety and quality assurance. The review presents and critically evaluates the current state of the art of disc-based microarrays with illustrative examples, including past, current and future developments. Special mention is made of the analytical developments that use either chemically activated or raw standard CDs where proteins, oligonucleotides, peptides, haptens or other biological probes are immobilized. The discs are also used to perform the assays and must maintain their readability with standard optical drives. The concept and principle of evolving disc-based microarrays and the evolution of disk drives as optical detectors are also described. The review concludes with the most relevant uses ordered chronologically to provide an overview of the progress of CD technology applications in the life sciences. Also, it provides a selection of important references to the current literature. Graphical Abstract High density disc-based microarrays. PMID:26922341

  10. Reverse phase protein microarrays advance to use in clinical trials

    PubMed Central

    Mueller, Claudius; Liotta, Lance A.; Espina, Virginia

    2010-01-01

    Individualizing cancer therapy for molecular targeted inhibitors requires a new class of molecular profiling technology that can map the functional state of the cancer cell signal pathways containing the drug targets. Reverse phase protein microarrays (RPMA) are a technology platform designed for quantitative, multiplexed analysis of specific phosphorylated, cleaved, or total (phosphorylated and non-phosphorylated) forms of cellular proteins from a limited amount of sample. This class of microarray can be used to interrogate tissue samples, cells, serum, or body fluids. RPMA were previously a research tool; now this technology has graduated to use in research clinical trials with clinical grade sensitivity and precision. In this review we describe the application of RPMA for multiplexed signal pathway analysis in therapeutic monitoring, biomarker discovery, and evaluation of pharmaceutical targets, and conclude with a summary of the technical aspects of RPMA construction and analysis. PMID:20974554

  11. Microarray analysis in pulmonary hypertension.

    PubMed

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea; Kwapiszewska, Grazyna

    2016-07-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance. PMID:27076594

  12. Microarray analysis in pulmonary hypertension

    PubMed Central

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea

    2016-01-01

    Microarrays are a powerful and effective tool that allows the detection of genome-wide gene expression differences between controls and disease conditions. They have been broadly applied to investigate the pathobiology of diverse forms of pulmonary hypertension, namely group 1, including patients with idiopathic pulmonary arterial hypertension, and group 3, including pulmonary hypertension associated with chronic lung diseases such as chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis. To date, numerous human microarray studies have been conducted to analyse global (lung homogenate samples), compartment-specific (laser capture microdissection), cell type-specific (isolated primary cells) and circulating cell (peripheral blood) expression profiles. Combined, they provide important information on development, progression and the end-stage disease. In the future, system biology approaches, expression of noncoding RNAs that regulate coding RNAs, and direct comparison between animal models and human disease might be of importance. PMID:27076594

  13. ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

    PubMed

    Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

    2016-01-01

    Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. PMID:27423857

  14. A platform for combined DNA and protein microarrays based on total internal reflection fluorescence.

    PubMed

    Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

    2012-01-01

    We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax.

  15. A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

    PubMed Central

    Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

    2012-01-01

    We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

  16. A comprehensive study design reveals treatment- and transcript abundance–dependent concordance between RNA-seq and microarray data

    PubMed Central

    Wang, Charles; Gong, Binsheng; Bushel, Pierre R.; Thierry-Mieg, Jean; Thierry-Mieg, Danielle; Xu, Joshua; Fang, Hong; Hong, Huixiao; Shen, Jie; Su, Zhenqiang; Meehan, Joe; Li, Xiaojin; Yang, Lu; Li, Haiqing; Łabaj, Paweł P.; Kreil, David P.; Megherbi, Dalila; Florian, Caiment; Gaj, Stan; van Delft, Joost; Kleinjans, Jos; Scherer, Andreas; Viswanath, Devanarayan; Wang, Jian; Yang, Yong; Qian, Hui-Rong; Lancashire, Lee J.; Bessarabova, Marina; Nikolsky, Yuri; Furlanello, Cesare; Chierici, Marco; Albanese, Davide; Jurman, Giuseppe; Riccadonna, Samantha; Filosi, Michele; Visintainer, Roberto; Zhang, Ke K.; Li, Jianying; Hsieh, Jui-Hua; Svoboda, Daniel L.; Fuscoe, James C.; Deng, Youping; Shi, Leming; Paules, Richard S.; Auerbach, Scott S.; Tong, Weida

    2014-01-01

    RNA-seq facilitates unbiased genome-wide gene-expression profiling. However, its concordance with the well-established microarray platform must be rigorously assessed for confident uses in clinical and regulatory application. Here we use a comprehensive study design to generate Illumina RNA-seq and Affymetrix microarray data from the same set of liver samples of rats under varying degrees of perturbation by 27 chemicals representing multiple modes of action (MOA). The cross-platform concordance in terms of differentially expressed genes (DEGs) or enriched pathways is highly correlated with treatment effect size, gene-expression abundance and the biological complexity of the MOA. RNA-seq outperforms microarray (90% versus 76%) in DEG verification by quantitative PCR and the main gain is its improved accuracy for low expressed genes. Nonetheless, predictive classifiers derived from both platforms performed similarly. Therefore, the endpoint studied and its biological complexity, transcript abundance, and intended application are important factors in transcriptomic research and for decision-making. PMID:25150839

  17. Robin: An Intuitive Wizard Application for R-Based Expression Microarray Quality Assessment and Analysis1[W][OA

    PubMed Central

    Lohse, Marc; Nunes-Nesi, Adriano; Krüger, Peter; Nagel, Axel; Hannemann, Jan; Giorgi, Federico M.; Childs, Liam; Osorio, Sonia; Walther, Dirk; Selbig, Joachim; Sreenivasulu, Nese; Stitt, Mark; Fernie, Alisdair R.; Usadel, Björn

    2010-01-01

    The wide application of high-throughput transcriptomics using microarrays has generated a plethora of technical platforms, data repositories, and sophisticated statistical analysis methods, leaving the individual scientist with the problem of choosing the appropriate approach to address a biological question. Several software applications that provide a rich environment for microarray analysis and data storage are available (e.g. GeneSpring, EMMA2), but these are mostly commercial or require an advanced informatics infrastructure. There is a need for a noncommercial, easy-to-use graphical application that aids the lab researcher to find the proper method to analyze microarray data, without this requiring expert understanding of the complex underlying statistics, or programming skills. We have developed Robin, a Java-based graphical wizard application that harnesses the advanced statistical analysis functions of the R/BioConductor project. Robin implements streamlined workflows that guide the user through all steps of two-color, single-color, or Affymetrix microarray analysis. It provides functions for thorough quality assessment of the data and automatically generates warnings to notify the user of potential outliers, low-quality chips, or low statistical power. The results are generated in a standard format that allows ready use with both specialized analysis tools like MapMan and PageMan and generic spreadsheet applications. To further improve user friendliness, Robin includes both integrated help and comprehensive external documentation. To demonstrate the statistical power and ease of use of the workflows in Robin, we present a case study in which we apply Robin to analyze a two-color microarray experiment comparing gene expression in tomato (Solanum lycopersicum) leaves, flowers, and roots. PMID:20388663

  18. "Per cell" normalization method for mRNA measurement by quantitative PCR and microarrays

    PubMed Central

    Kanno, Jun; Aisaki, Ken-ichi; Igarashi, Katsuhide; Nakatsu, Noriyuki; Ono, Atsushi; Kodama, Yukio; Nagao, Taku

    2006-01-01

    Background Transcriptome data from quantitative PCR (Q-PCR) and DNA microarrays are typically obtained from a fixed amount of RNA collected per sample. Therefore, variations in tissue cellularity and RNA yield across samples in an experimental series compromise accurate determination of the absolute level of each mRNA species per cell in any sample. Since mRNAs are copied from genomic DNA, the simplest way to express mRNA level would be as copy number per template DNA, or more practically, as copy number per cell. Results Here we report a method (designated the "Percellome" method) for normalizing the expression of mRNA values in biological samples. It provides a "per cell" readout in mRNA copy number and is applicable to both quantitative PCR (Q-PCR) and DNA microarray studies. The genomic DNA content of each sample homogenate was measured from a small aliquot to derive the number of cells in the sample. A cocktail of five external spike RNAs admixed in a dose-graded manner (dose-graded spike cocktail; GSC) was prepared and added to each homogenate in proportion to its DNA content. In this way, the spike mRNAs represented absolute copy numbers per cell in the sample. The signals from the five spike mRNAs were used as a dose-response standard curve for each sample, enabling us to convert all the signals measured to copy numbers per cell in an expression profile-independent manner. A series of samples was measured by Q-PCR and Affymetrix GeneChip microarrays using this Percellome method, and the results showed up to 90 % concordance. Conclusion Percellome data can be compared directly among samples and among different studies, and between different platforms, without further normalization. Therefore, "percellome" normalization can serve as a standard method for exchanging and comparing data across different platforms and among different laboratories. PMID:16571132

  19. A general framework for designing and validating oligomer-based DNA microarrays and its application to Clostridium acetobutylicum.

    PubMed

    Paredes, Carlos J; Senger, Ryan S; Spath, Iwona S; Borden, Jacob R; Sillers, Ryan; Papoutsakis, Eleftherios T

    2007-07-01

    While DNA microarray analysis is widely accepted as an essential tool for modern biology, its use still eludes many researchers for several reasons, especially when microarrays are not commercially available. In that case, the design, construction, and use of microarrays for a sequenced organism constitute substantial, time-consuming, and expensive tasks. Recently, it has become possible to construct custom microarrays using industrial manufacturing processes, which offer several advantages, including speed of manufacturing, quality control, no up-front setup costs, and need-based microarray ordering. Here, we describe a strategy for designing and validating DNA microarrays manufactured using a commercial process. The 22K microarrays for the solvent producer Clostridium acetobutylicum ATCC 824 are based on in situ-synthesized 60-mers employing the Agilent technology. The strategy involves designing a large library of possible oligomer probes for each target (i.e., gene or DNA sequence) and experimentally testing and selecting the best probes for each target. The degenerate C. acetobutylicum strain M5 lacking the pSOL1 megaplasmid (with 178 annotated open reading frames [genes]) was used to estimate the level of probe cross-hybridization in the new microarrays and to establish the minimum intensity for a gene to be considered expressed. Results obtained using this microarray design were consistent with previously reported results from spotted cDNA-based microarrays. The proposed strategy is applicable to any sequenced organism.

  20. Uropathogenic Escherichia coli virulence genes: invaluable approaches for designing DNA microarray probes

    PubMed Central

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Elham

    2015-01-01

    Introduction The pathotypes of uropathogenic Escherichia coli (UPEC) cause different types of urinary tract infections (UTIs). The presence of a wide range of virulence genes in UPEC enables us to design appropriate DNA microarray probes. These probes, which are used in DNA microarray technology, provide us with an accurate and rapid diagnosis and definitive treatment in association with UTIs caused by UPEC pathotypes. The main goal of this article is to introduce the UPEC virulence genes as invaluable approaches for designing DNA microarray probes. Material and methods Main search engines such as Google Scholar and databases like NCBI were searched to find and study several original pieces of literature, review articles, and DNA gene sequences. In parallel with in silico studies, the experiences of the authors were helpful for selecting appropriate sources and writing this review article. Results There is a significant variety of virulence genes among UPEC strains. The DNA sequences of virulence genes are fabulous patterns for designing microarray probes. The location of virulence genes and their sequence lengths influence the quality of probes. Conclusions The use of selected virulence genes for designing microarray probes gives us a wide range of choices from which the best probe candidates can be chosen. DNA microarray technology provides us with an accurate, rapid, cost-effective, sensitive, and specific molecular diagnostic method which is facilitated by designing microarray probes. Via these tools, we are able to have an accurate diagnosis and a definitive treatment regarding UTIs caused by UPEC pathotypes. PMID:26855801

  1. Interpreting Microarray Data to Build Models of Microbial Genetic Regulation Networks

    SciTech Connect

    Sokhansanj, B; Garnham, J B; Fitch, J P

    2002-01-23

    Microarrays and DNA chips are an efficient, high-throughput technology for measuring temporal changes in the expression of message RNA (mRNA) from thousands of genes (often the entire genome of an organism) in a single experiment. A crucial drawback of microarray experiments is that results are inherently qualitative: data are generally neither quantitatively repeatable, nor may microarray spot intensities be calibrated to in vivo mRNA concentrations. Nevertheless, microarrays represent by the far the cheapest and fastest way to obtain information about a cells global genetic regulatory networks. Besides poor signal characteristics, the massive number of data produced by microarray experiments poses challenges for visualization, interpretation and model building. Towards initial model development, we have developed a Java tool for visualizing the spatial organization of gene expression in bacteria. We are also developing an approach to inferring and testing qualitative fuzzy logic models of gene regulation using microarray data. Because we are developing and testing qualitative hypotheses that do not require quantitative precision, our statistical evaluation of experimental data is limited to checking for validity and consistency. Our goals are to maximize the impact of inexpensive microarray technology, bearing in mind that biological models and hypotheses are typically qualitative.

  2. Genomic and microarray approaches to coral reef conservation biology

    NASA Astrophysics Data System (ADS)

    Forêt, S.; Kassahn, K. S.; Grasso, L. C.; Hayward, D. C.; Iguchi, A.; Ball, E. E.; Miller, D. J.

    2007-09-01

    New technologies based on DNA microarrays and comparative genomics hold great promise for providing the background biological information necessary for effective coral reef conservation and management. Microarray analysis has been used in a wide range of applications across the biological sciences, most frequently to examine simultaneous changes in the expression of large numbers of genes in response to experimental manipulation or environmental variation. Other applications of microarray methods include the assessment of divergence in gene sequences between species and the identification of fast-evolving genes. Arrays are presently available for only a limited range of species, but with appropriate controls they can be used for related species, thus avoiding the considerable costs associated with development of a system de novo. Arrays are in use or preparation to study stress responses, early development, and symbiosis in Acropora and Montastraea. Ongoing projects on several corals are making available large numbers of expressed gene sequences, enabling the identification of candidate genes for studies on gamete specificity, allorecognition and symbiont interactions. Over the next few years, microarray and comparative genomic approaches are likely to assume increasingly important and widespread use to study many aspects of the biology of coral reef organisms. Application of these genomic approaches to enhance our understanding of genetic and physiological correlates during stress, environmental disturbance and disease bears direct relevance to the conservation of coral reef ecosystems.

  3. See what you eat--broad GMO screening with microarrays.

    PubMed

    von Götz, Franz

    2010-03-01

    Despite the controversy of whether genetically modified organisms (GMOs) are beneficial or harmful for humans, animals, and/or ecosystems, the number of cultivated GMOs is increasing every year. Many countries and federations have implemented safety and surveillance systems for GMOs. Potent testing technologies need to be developed and implemented to monitor the increasing number of GMOs. First, these GMO tests need to be comprehensive, i.e., should detect all, or at least the most important, GMOs on the market. This type of GMO screening requires a high degree of parallel tests or multiplexing. To date, DNA microarrays have the highest number of multiplexing capabilities when nucleic acids are analyzed. This trend article focuses on the evolution of DNA microarrays for GMO testing. Over the last 7 years, combinations of multiplex PCR detection and microarray detection have been developed to qualitatively assess the presence of GMOs. One example is the commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com), which is the only GMO screening system successfully validated in a multicenter study. With use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative. PMID:19862507

  4. See what you eat--broad GMO screening with microarrays.

    PubMed

    von Götz, Franz

    2010-03-01

    Despite the controversy of whether genetically modified organisms (GMOs) are beneficial or harmful for humans, animals, and/or ecosystems, the number of cultivated GMOs is increasing every year. Many countries and federations have implemented safety and surveillance systems for GMOs. Potent testing technologies need to be developed and implemented to monitor the increasing number of GMOs. First, these GMO tests need to be comprehensive, i.e., should detect all, or at least the most important, GMOs on the market. This type of GMO screening requires a high degree of parallel tests or multiplexing. To date, DNA microarrays have the highest number of multiplexing capabilities when nucleic acids are analyzed. This trend article focuses on the evolution of DNA microarrays for GMO testing. Over the last 7 years, combinations of multiplex PCR detection and microarray detection have been developed to qualitatively assess the presence of GMOs. One example is the commercially available DualChip GMO (Eppendorf, Germany; http://www.eppendorf-biochip.com), which is the only GMO screening system successfully validated in a multicenter study. With use of innovative amplification techniques, promising steps have recently been taken to make GMO detection with microarrays quantitative.

  5. Electrostatic readout of DNA microarrays with charged microspheres

    SciTech Connect

    Clack, Nathan G.; Salaita, Khalid; Groves, Jay T.

    2008-06-29

    DNA microarrays are used for gene-expression profiling, single-nucleotide polymorphism detection and disease diagnosis. A persistent challenge in this area is the lack of microarray screening technology suitable for integration into routine clinical care. In this paper, we describe a method for sensitive and label-free electrostatic readout of DNA or RNA hybridization on microarrays. The electrostatic properties of the microarray are measured from the position and motion of charged microspheres randomly dispersed over the surface. We demonstrate nondestructive electrostatic imaging with 10-μm lateral resolution over centimeter-length scales, which is four-orders of magnitude larger than that achievable with conventional scanning electrostatic force microscopy. Changes in surface charge density as a result of specific hybridization can be detected and quantified with 50-pM sensitivity, single base-pair mismatch selectivity and in the presence of complex background. Lastly, because the naked eye is sufficient to read out hybridization, this approach may facilitate broad application of multiplexed assays.

  6. Analysis of microarray experiments of gene expression profiling

    PubMed Central

    Tarca, Adi L.; Romero, Roberto; Draghici, Sorin

    2008-01-01

    The study of gene expression profiling of cells and tissue has become a major tool for discovery in medicine. Microarray experiments allow description of genome-wide expression changes in health and disease. The results of such experiments are expected to change the methods employed in the diagnosis and prognosis of disease in obstetrics and gynecology. Moreover, an unbiased and systematic study of gene expression profiling should allow the establishment of a new taxonomy of disease for obstetric and gynecologic syndromes. Thus, a new era is emerging in which reproductive processes and disorders could be characterized using molecular tools and fingerprinting. The design, analysis, and interpretation of microarray experiments require specialized knowledge that is not part of the standard curriculum of our discipline. This article describes the types of studies that can be conducted with microarray experiments (class comparison, class prediction, class discovery). We discuss key issues pertaining to experimental design, data preprocessing, and gene selection methods. Common types of data representation are illustrated. Potential pitfalls in the interpretation of microarray experiments, as well as the strengths and limitations of this technology, are highlighted. This article is intended to assist clinicians in appraising the quality of the scientific evidence now reported in the obstetric and gynecologic literature. PMID:16890548

  7. Integrated Amplification Microarrays for Infectious Disease Diagnostics

    PubMed Central

    Chandler, Darrell P.; Bryant, Lexi; Griesemer, Sara B.; Gu, Rui; Knickerbocker, Christopher; Kukhtin, Alexander; Parker, Jennifer; Zimmerman, Cynthia; George, Kirsten St.; Cooney, Christopher G.

    2012-01-01

    This overview describes microarray-based tests that combine solution-phase amplification chemistry and microarray hybridization within a single microfluidic chamber. The integrated biochemical approach improves microarray workflow for diagnostic applications by reducing the number of steps and minimizing the potential for sample or amplicon cross-contamination. Examples described herein illustrate a basic, integrated approach for DNA and RNA genomes, and a simple consumable architecture for incorporating wash steps while retaining an entirely closed system. It is anticipated that integrated microarray biochemistry will provide an opportunity to significantly reduce the complexity and cost of microarray consumables, equipment, and workflow, which in turn will enable a broader spectrum of users to exploit the intrinsic multiplexing power of microarrays for infectious disease diagnostics.

  8. Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

    NASA Technical Reports Server (NTRS)

    Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark

    2005-01-01

    Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

  9. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

    2005-09-01

    The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

  10. Microarray analysis of relative gene expression stability for selection of internal reference genes in the rhesus macaque brain

    PubMed Central

    2010-01-01

    Background Normalization of gene expression data refers to the comparison of expression values using reference standards that are consistent across all conditions of an experiment. In PCR studies, genes designated as "housekeeping genes" have been used as internal reference genes under the assumption that their expression is stable and independent of experimental conditions. However, verification of this assumption is rarely performed. Here we assess the use of gene microarray analysis to facilitate selection of internal reference sequences with higher expression stability across experimental conditions than can be expected using traditional selection methods. We recently demonstrated that relative gene expression from qRT-PCR data normalized using GAPDH, ALG9 and RPL13A expression values mirrored relative expression using quantile normalization in Robust Multichip Analysis (RMA) on the Affymetrix® GeneChip® rhesus Macaque Genome Array. Having shown that qRT-PCR and Affymetrix® GeneChip® data from the same hormone replacement therapy (HRT) study yielded concordant results, we used quantile-normalized gene microarray data to identify the most stably expressed among probe sets for prospective internal reference genes across three brain regions from the HRT study and an additional study of normally menstruating rhesus macaques (cycle study). Gene selection was limited to 575 previously published human "housekeeping" genes. Twelve animals were used per study, and three brain regions were analyzed from each animal. Gene expression stabilities were determined using geNorm, NormFinder and BestKeeper software packages. Results Sequences co-annotated for ribosomal protein S27a (RPS27A), and ubiquitin were among the most stably expressed under all conditions and selection criteria used for both studies. Higher annotation quality on the human GeneChip® facilitated more targeted analysis than could be accomplished using the rhesus GeneChip®. In the cycle study, multiple

  11. Optimised laser microdissection of the human ocular surface epithelial regions for microarray studies

    PubMed Central

    2013-01-01

    concentration of these samples ranged from 10.88 ng/12 μl to 25.8 ng/12 μl, with the RNA integrity numbers (RIN) for these samples from 3.3 to 7.9. RNA samples with RIN values below 2, that had failed to amplify satisfactorily were discarded. Conclusions The optimised protocol for sample collection and laser microdissection improved the RNA yield of the insitu ocular surface epithelial regions for effective microarray studies on spotted oligonucleotide and affymetrix platforms. PMID:24160452

  12. Analysis of environmental transcriptomes by DNA microarrays.

    PubMed

    Parro, Víctor; Moreno-Paz, Mercedes; González-Toril, Elena

    2007-02-01

    In this work we investigated the correlations between global gene expression patterns and environmental parameters in natural ecosystems. We studied the preferential gene expression of the iron oxidizer bacterium Leptospirillum ferrooxidans to adapt its physiology to changes in the physicochemical parameters in its natural medium. Transcriptome analysis by DNA microarrays can proportionate an instant picture about the preferential gene expression between two different environmental samples. However, this type of analysis is very difficult and complex in natural ecosystems, mainly because of the broad biodiversity and multiple environmental parameters that may affect gene expression. The necessity of high-quality RNA preparations as well as complicated data analysis are also technological limitations. The low prokaryotic diversity of the extremely acidic and iron-rich waters of the Tinto River (Spain) ecosystem, where L. ferrooxidans is abundant, allows the opportunity to achieve global gene expression studies and to associate gene function with environmental parameters. We applied a total RNA amplification protocol validated previously for the amplification of the environmental transcriptome (meta-transcriptome). The meta-transcriptome of two sites from the Tinto River mainly differing in the salt and oxygen contents were amplified and analysed by a L. ferrooxidans DNA microarray. The results showed a clear preferential induction of genes involved in certain physicochemical parameters like: high salinity (ectAB, otsAB), low oxygen concentration (cydAB), iron uptake (fecA-exbBD-tonB), oxidative stress (carotenoid synthesis, oxyR, recG), potassium (kdpBAC) or phosphate concentrations (pstSCAB), etc. We conclude that specific gene expression patterns can be useful indicators for the physiological conditions in a defined ecosystem. Also, the upregulation of certain genes and operons reveals information about the environmental conditions (nutrient limitations, stresses

  13. Genomewide expression analysis in amino acid-producing bacteria using DNA microarrays.

    PubMed

    Polen, Tino; Wendisch, Volker F

    2004-01-01

    DNA microarray technology has become an important research tool for biotechnology and microbiology. It is now possible to characterize genetic diversity and gene expression in a genomewide manner. DNA microarrays have been applied extensively to study the biology of many bacteria including Escherichia coli, but only recently have they been developed for the Gram-positive Corynebacterium glutamicum. Both bacteria are widely used for biotechnological amino acid production. In this article, in addition to the design and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, we describe recent applications of DNA microarray technology regarding amino acid production in C. glutamicum and E. coli. We also discuss the impact of functional genomics studies on fundamental as well as applied aspects of amino acid production with C. glutamicum and E. coli. PMID:15304751

  14. A Liposome-Based Approach to the Integrated Multi-Component Antigen Microarrays

    PubMed Central

    Wang, Denong

    2015-01-01

    This report describes an experimental procedure for constructing integrated lipid, carbohydrate, and protein microarrays. In essence, it prints liposomes on nitrocellulose-coated micro-glass slides, a biochip substrate for spotting protein and carbohydrate microarrays, and the substances that can form liposomes (homo-liposomes) or can be incorporated into liposomes (hetero-liposomes) are suitable for microarray construction using existing microarray spotting devices. Importantly, this technology allows simultaneous detection of serum antibody activities among the three major classes of antigens, i.e., lipids, carbohydrates, and proteins. The potential of this technology is illustrated by its use in revealing a broad-spectrum of pre-existing anti-lipid antibodies in blood circulation and monitoring the epitope spreading of autoantibody reactivities among protein, carbohydrate, and lipid antigens in experimental autoimmune encephalomyelitis (EAE).

  15. Living Cell Microarrays: An Overview of Concepts.

    PubMed

    Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

    2016-01-01

    Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

  16. Living Cell Microarrays: An Overview of Concepts

    PubMed Central

    Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

    2016-01-01

    Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

  17. Living Cell Microarrays: An Overview of Concepts

    PubMed Central

    Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

    2016-01-01

    Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays.

  18. High-Density Microarray of Small-Subunit Ribosomal DNA Probes

    PubMed Central

    Wilson, Kenneth H.; Wilson, Wendy J.; Radosevich, Jennifer L.; DeSantis, Todd Z.; Viswanathan, Vijay S.; Kuczmarski, Thomas A.; Andersen, Gary L.

    2002-01-01

    Ribosomal DNA sequence analysis, originally conceived as a way to provide a universal phylogeny for life forms, has proven useful in many areas of biological research. Some of the most promising applications of this approach are presently limited by the rate at which sequences can be analyzed. As a step toward overcoming this limitation, we have investigated the use of photolithography chip technology to perform sequence analyses on amplified small-subunit rRNA genes. The GeneChip (Affymetrix Corporation) contained 31,179 20-mer oligonucleotides that were complementary to a subalignment of sequences in the Ribosomal Database Project (RDP) (B. L. Maidak et al., Nucleic Acids Res. 29:173-174, 2001). The chip and standard Affymetrix software were able to correctly match small-subunit ribosomal DNA amplicons with the corresponding sequences in the RDP database for 15 of 17 bacterial species grown in pure culture. When bacteria collected from an air sample were tested, the method compared favorably with cloning and sequencing amplicons in determining the presence of phylogenetic groups. However, the method could not resolve the individual sequences comprising a complex mixed sample. Given these results and the potential for future enhancement of this technology, it may become widely useful. PMID:11976131

  19. THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

    EPA Science Inventory

    Over the past several years, the field of microarrays has grown and evolved drastically. In its continued efforts to track this evolution, the ABRF-MARG has once again conducted a survey of international microarray facilities and individual microarray users. The goal of the surve...

  20. DNA microarrays: experimental issues, data analysis, and application to bacterial systems.

    PubMed

    Dharmadi, Yandi; Gonzalez, Ramon

    2004-01-01

    DNA microarrays are currently used to study the transcriptional response of many organisms to genetic and environmental perturbations. Although there is much room for improvement of this technology, its potential has been clearly demonstrated in the past 5 years. The general consensus is that the bottleneck is now located in the processing and analysis of transcriptome data and its use for purposes other than the quantification of changes in gene expression levels. In this article we discuss technological aspects of DNA microarrays, statistical and biological issues pertinent to the design of microarray experiments, and statistical tools for microarray data analysis. A review on applications of DNA microarrays in the study of bacterial systems is presented. Special attention is given to studies in the following areas: (1) bacterial response to environmental changes; (2) gene identification, genome organization, and transcriptional regulation; and (3) genetic and metabolic engineering. Soon, the use of DNA microarray technologies in conjunction with other genome/system-wide analyses (e.g., proteomics, metabolomics, fluxomics, phenomics, etc.) will provide a better assessment of genotype-phenotype relationships in bacteria, which serve as a basis for understanding similar processes in more complex organisms.

  1. Improved detection of differentially expressed genes in microarray experiments through multiple scanning and image integration

    PubMed Central

    Romualdi, Chiara; Trevisan, Silvia; Celegato, Barbara; Costa, Germano; Lanfranchi, Gerolamo

    2003-01-01

    The variability of results in microarray technology is in part due to the fact that independent scans of a single hybridised microarray give spot images that are not quite the same. To solve this problem and turn it to our advantage, we introduced the approach of multiple scanning and of image integration of microarrays. To this end, we have developed specific software that creates a virtual image that statistically summarises a series of consecutive scans of a microarray. We provide evidence that the use of multiple imaging (i) enhances the detection of differentially expressed genes; (ii) increases the image homogeneity; and (iii) reveals false-positive results such as differentially expressed genes that are detected by a single scan but not confirmed by successive scanning replicates. The increase in the final number of differentially expressed genes detected in a microarray experiment with this approach is remarkable; 50% more for microarrays hybridised with targets labelled by reverse transcriptase, and 200% more for microarrays developed with the tyramide signal amplification (TSA) technique. The results have been confirmed by semi-quantitative RT–PCR tests. PMID:14627839

  2. Studying bovine early embryo transcriptome by microarray.

    PubMed

    Dufort, Isabelle; Robert, Claude; Sirard, Marc-André

    2015-01-01

    Microarrays represent a significant advantage when studying gene expression in early embryo because they allow for a speedy study of a large number of genes even if the sample of interest contains small quantities of genetic material. Here we describe the protocols developed by the EmbryoGENE Network to study the bovine transcriptome in early embryo using a microarray experimental design.

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

    PubMed

    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. PMID:17517778

  4. Real-time DNA microarray analysis

    PubMed Central

    Hassibi, Arjang; Vikalo, Haris; Riechmann, José Luis; Hassibi, Babak

    2009-01-01

    We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays. PMID:19723688

  5. Real-time DNA microarray analysis.

    PubMed

    Hassibi, Arjang; Vikalo, Haris; Riechmann, José Luis; Hassibi, Babak

    2009-11-01

    We present a quantification method for affinity-based DNA microarrays which is based on the real-time measurements of hybridization kinetics. This method, i.e. real-time DNA microarrays, enhances the detection dynamic range of conventional systems by being impervious to probe saturation in the capturing spots, washing artifacts, microarray spot-to-spot variations, and other signal amplitude-affecting non-idealities. We demonstrate in both theory and practice that the time-constant of target capturing in microarrays, similar to all affinity-based biosensors, is inversely proportional to the concentration of the target analyte, which we subsequently use as the fundamental parameter to estimate the concentration of the analytes. Furthermore, to empirically validate the capabilities of this method in practical applications, we present a FRET-based assay which enables the real-time detection in gene expression DNA microarrays. PMID:19723688

  6. DNA Microarrays for Identifying Fishes

    PubMed Central

    Nölte, M.; Weber, H.; Silkenbeumer, N.; Hjörleifsdottir, S.; Hreggvidsson, G. O.; Marteinsson, V.; Kappel, K.; Planes, S.; Tinti, F.; Magoulas, A.; Garcia Vazquez, E.; Turan, C.; Hervet, C.; Campo Falgueras, D.; Antoniou, A.; Landi, M.; Blohm, D.

    2008-01-01

    In many cases marine organisms and especially their diverse developmental stages are difficult to identify by morphological characters. DNA-based identification methods offer an analytically powerful addition or even an alternative. In this study, a DNA microarray has been developed to be able to investigate its potential as a tool for the identification of fish species from European seas based on mitochondrial 16S rDNA sequences. Eleven commercially important fish species were selected for a first prototype. Oligonucleotide probes were designed based on the 16S rDNA sequences obtained from 230 individuals of 27 fish species. In addition, more than 1200 sequences of 380 species served as sequence background against which the specificity of the probes was tested in silico. Single target hybridisations with Cy5-labelled, PCR-amplified 16S rDNA fragments from each of the 11 species on microarrays containing the complete set of probes confirmed their suitability. True-positive, fluorescence signals obtained were at least one order of magnitude stronger than false-positive cross-hybridisations. Single nontarget hybridisations resulted in cross-hybridisation signals at approximately 27% of the cases tested, but all of them were at least one order of magnitude lower than true-positive signals. This study demonstrates that the 16S rDNA gene is suitable for designing oligonucleotide probes, which can be used to differentiate 11 fish species. These data are a solid basis for the second step to create a “Fish Chip” for approximately 50 fish species relevant in marine environmental and fisheries research, as well as control of fisheries products. PMID:18270778

  7. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    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. PMID:25863787

  8. Application of DNA microarray for screening metagenome library clones.

    PubMed

    Park, Soo-Je; Chae, Jong-Chan; Rhee, Sung-Keun

    2010-01-01

    Sequence-based screening tools of a metagenome library can expedite metagenome researches considering tremendous metagenome diversities. Several critical disadvantages of activity-based screening of metagenome libraries could be overcome by sequence-based screening approaches. DNA microarray technology widely used for monitoring environmental genes can be employed for screening environmental fosmid and BAC clones harboring target genes due to its high throughput nature. DNAs of fosmid clones are extracted and spotted on a glass slide and fluorescence-labeled probes are hybridized to the microarray. Specific hybridization signals can be obtained only for the fosmid clones that contain the target gene with high sensitivity (10 ng/μL of fosmid clone DNA) and quantitativeness. PMID:20830574

  9. MatArray: a Matlab toolbox for microarray data.

    PubMed

    Venet, David

    2003-03-22

    The microarray technology allows the high-throughput quantification of the mRNA level of thousands of genes under dozens of conditions, generating a wealth of data which must be analyzed using some form of computational means. A popular framework for such analysis is Matlab, a powerful computing language for which many functions have been written. However, although complex topics like neural networks or principal component analysis are freely available in Matlab, functions to perform more basic tasks like data normalization or hierarchical clustering in an efficient manner are not. The MatArray toolbox aims at filling this gap by offering efficient implementations of the most needed functions for microarray analysis. The functions in the toolbox are command-line only, since it is geared toward seasoned Matlab users.

  10. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    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.

  11. NAPPA as a Real New Method for Protein Microarray Generation

    PubMed Central

    Díez, Paula; González-González, María; Lourido, Lucía; Dégano, Rosa M.; Ibarrola, Nieves; Casado-Vela, Juan; LaBaer, Joshua; Fuentes, Manuel

    2015-01-01

    Nucleic Acid Programmable Protein Arrays (NAPPA) have emerged as a powerful and innovative technology for the screening of biomarkers and the study of protein-protein interactions, among others possible applications. The principal advantages are the high specificity and sensitivity that this platform offers. Moreover, compared to conventional protein microarrays, NAPPA technology avoids the necessity of protein purification, which is expensive and time-consuming, by substituting expression in situ with an in vitro transcription/translation kit. In summary, NAPPA arrays have been broadly employed in different studies improving knowledge about diseases and responses to treatments. Here, we review the principal advances and applications performed using this platform during the last years.

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

    PubMed

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

    2013-04-01

    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

  13. Detection of genomic deletions in rice using oligonucleotide microarrays

    PubMed Central

    Bruce, Myron; Hess, Ann; Bai, Jianfa; Mauleon, Ramil; Diaz, M Genaleen; Sugiyama, Nobuko; Bordeos, Alicia; Wang, Guo-Liang; Leung, Hei; Leach, Jan E

    2009-01-01

    Background The induction of genomic deletions by physical- or chemical- agents is an easy and inexpensive means to generate a genome-saturating collection of mutations. Different mutagens can be selected to ensure a mutant collection with a range of deletion sizes. This would allow identification of mutations in single genes or, alternatively, a deleted group of genes that might collectively govern a trait (e.g., quantitative trait loci, QTL). However, deletion mutants have not been widely used in functional genomics, because the mutated genes are not tagged and therefore, difficult to identify. Here, we present a microarray-based approach to identify deleted genomic regions in rice mutants selected from a large collection generated by gamma ray or fast neutron treatment. Our study focuses not only on the utility of this method for forward genetics, but also its potential as a reverse genetics tool through accumulation of hybridization data for a collection of deletion mutants harboring multiple genetic lesions. Results We demonstrate that hybridization of labeled genomic DNA directly onto the Affymetrix Rice GeneChip® allows rapid localization of deleted regions in rice mutants. Deletions ranged in size from one gene model to ~500 kb and were predicted on all 12 rice chromosomes. The utility of the technique as a tool in forward genetics was demonstrated in combination with an allelic series of mutants to rapidly narrow the genomic region, and eventually identify a candidate gene responsible for a lesion mimic phenotype. Finally, the positions of mutations in 14 mutants were aligned onto the rice pseudomolecules in a user-friendly genome browser to allow for rapid identification of untagged mutations . Conclusion We demonstrate the utility of oligonucleotide arrays to discover deleted genes in rice. The density and distribution of deletions suggests the feasibility of a database saturated with deletions across the rice genome. This community resource can continue

  14. Microarray-Based Phospho-Proteomic Profiling of Complex Biological Systems12

    PubMed Central

    Goodwin, C. Rory; Woodard, Crystal L.; Zhou, Xin; Pan, Jianbo; Olivi, Alessandro; Xia, Shuli; Bettegowda, Chetan; Sciubba, Daniel M.; Pevsner, Jonathan; Zhu, Heng; Laterra, John

    2016-01-01

    Protein microarray technology has been successfully used for identifying substrates of purified activated kinases. We used protein microarrays to globally interrogate the effects of PTEN and Akt activity on the phospho-kinome of in vitro and in vivo glioma models and validated results in clinical pathological specimens. Whole cell lysates extracted from tumor samples can be applied to human kinome chip microarrays to profile the global kinase phosphorylation patterns in a high-throughput manner and identify novel substrates inherent to the tumor cell and the interactions with tumor microenvironment. Our findings identify a novel microarray-based method for assessing intracellular signaling events applicable to human oncogenesis and other pathophysiologic states. PMID:27084428

  15. New protocol for oligonucleotide microarray fabrication using SU-8-coated glass microslides.

    PubMed

    Sethi, D; Kumar, A; Gandhi, R P; Kumar, P; Gupta, K C

    2010-09-15

    Microarray technology has become an important tool for detection and analysis of nucleic acid targets. Immobilization of modified and unmodified oligonucleotides on epoxy-functionalized glass surfaces is often used in microarray fabrication. Here, we demonstrate a protocol that employs coating of SU-8 (glycidyl ether of bisphenol A) onto glass microslides to obtain high density of epoxy functions for efficient immobilization of aminoalkyl-, thiophosphoryl-, and phosphorylated oligonucleotides with uniform spot morphology. The resulting microarrays exhibited high immobilization (∼65%) and hybridization efficiency (30-36%) and were sufficiently stable over a range of temperature and pH conditions. The prominent feature of the protocol is that spots can be visualized distinctly at 0.05 μM probe (a 20-mer oligonucleotide) concentration. The constructed microarrays were subsequently used for detection of base mismatches and bacterial diseases (meningitis and typhoid).

  16. Microarray-Based Phospho-Proteomic Profiling of Complex Biological Systems.

    PubMed

    Goodwin, C Rory; Woodard, Crystal L; Zhou, Xin; Pan, Jianbo; Olivi, Alessandro; Xia, Shuli; Bettegowda, Chetan; Sciubba, Daniel M; Pevsner, Jonathan; Zhu, Heng; Laterra, John

    2016-04-01

    Protein microarray technology has been successfully used for identifying substrates of purified activated kinases. We used protein microarrays to globally interrogate the effects of PTEN and Akt activity on the phospho-kinome of in vitro and in vivo glioma models and validated results in clinical pathological specimens. Whole cell lysates extracted from tumor samples can be applied to human kinome chip microarrays to profile the global kinase phosphorylation patterns in a high-throughput manner and identify novel substrates inherent to the tumor cell and the interactions with tumor microenvironment. Our findings identify a novel microarray-based method for assessing intracellular signaling events applicable to human oncogenesis and other pathophysiologic states. PMID:27084428

  17. Microarray Analysis of Human Liver Cells irradiated by 80MeV/u Carbon Ions

    NASA Astrophysics Data System (ADS)

    Wang, Xiao; Tian, Xiaoling; Kong, Fuquan; Li, Qiang; Jin, Xiaodong; Dai, Zhongying; Zhang, Hong; Yang, Mingjian; Zhao, Kui

    Objective Biological effect of heavy ion beam has the important significance for cancer therapy and space exploring owing its high LET and RBE, low OER, especially forming Bragg spike at the end of the tracks of charged particles. More serious damage for cells are induced by heavy ions and difficult repair than other irradiation such as X-ray and ν-ray . To explore the molecular mechanism of biological effect caused by heavy ionizing radiation (HIR) and to construct the gene expression profile database of HIR-induced human liver cells L02 by microarray analysis. Methods In this study, L02 cells were irradiated by 80MeV/u carbon ions at 5 Gy delivered by HIRFL (Heavy Ion Research Facility in Lanzhou) at room temperature. Total RNAs of cells incubated 6 hours and 24hours after irradiation were extracted with Trizol. Unirradiated cells were used as a control. RNAs were transcripted into cDNA by reverse transcription and labelled with cy5-dCTP and cy3-dCTP respectively. A human genome oligonucleotide set consisting of 5 amino acid-modified 70-mer probes and representing 21,329 well-characterized Homo sapiens genes was selected for microarray analysis and printed on amino-silaned glass slides. Arrays were fabricated using an OmniGrid microarrayer. Only genes whose alteration tendency was consistent in both microarrays were selected as differentially expressed genes. The Affymetrix's short oligonucleotide (25-mer) HG U133A 2.0 array analyses were performed per the manufacturer's instructions. Results Of the 21,329 genes tested, 37 genes showed changes in expression level with ratio higher than 2.0 and lower than 0.5 at 6hrs after irradiation. There were 19 genes showing up-regulation in radiated L02 cells, whereas 18 genes showing down-regulation; At 24hrs after irradiation, 269 genes showed changes in expression level with ratio higher than 2.0 and lower than 0.5. There were 67 genes showing up-regulation in radiated L02 cells, whereas 202 genes showing down

  18. Microarray-integrated optoelectrofluidic immunoassay system.

    PubMed

    Han, Dongsik; Park, Je-Kyun

    2016-05-01

    A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

  19. hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine

    PubMed Central

    Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H. Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

    2016-01-01

    Background Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. Results This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. Conclusions The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays. PMID:27701436

  20. Microarray analysis of thyroid hormone-induced changes in mRNA expression in the adult rat brain.

    PubMed

    Haas, Michael J; Mreyoud, Amjad; Fishman, Miriam; Mooradian, Arshag D

    2004-07-15

    To determine which genes in the adult rat brain are regulated by thyroid hormone (TH), we used microarrays to examine the effect of hyperthyroidism on neuron-specific gene expression. Four-month-old male Fisher 344 rats were rendered hyperthyroid by intraperitoneal injection of 3,5,3'-L-triiodothyronine (T3, 15 microg/100 g body weight) for 10 consecutive days. To minimize interindividual variability, pooled cerebral tissue RNA from four-control and five-hyperthyroid rats was hybridized in duplicates to the Affymetrix (Santa Clara, CA) U34N rat neurobiology microarray, which contains probes for 1224 neural-specific genes. Changes in gene expression were considered significant only if they were observed in both pair-wise comparisons as well as by Northern blot analysis. Hyperthyroidism was associated with modest changes in the expression of only 11 genes. The expression of the phosphodiesterase Enpp2, myelin oligodendrocyte glycoprotein (Mog), microtubule-associated protein 2 (MAP2), growth hormone (GH), Ca(2+)/calmodulin-dependent protein kinase beta-subunit (Camk2b), neuron-specific protein PEP-19 (Pcp4), a sodium-dependent neurotransmitter, and the myelin-associated glycoprotein (S-MAG) was significantly increased. Three genes were suppressed by hyperthyroidism, including the activity and neurotransmitter-induced early genes-1 and -7 (ANIA-1 and ANIA-7) and the guanine nucleotide-binding protein one (Gnb1). The present study underscores the paucity of TH responsive genes in adult cerebral tissue. PMID:15234464

  1. DNA Microarrays in Herbal Drug Research

    PubMed Central

    Chavan, Preeti; Joshi, Kalpana; Patwardhan, Bhushan

    2006-01-01

    Natural products are gaining increased applications in drug discovery and development. Being chemically diverse they are able to modulate several targets simultaneously in a complex system. Analysis of gene expression becomes necessary for better understanding of molecular mechanisms. Conventional strategies for expression profiling are optimized for single gene analysis. DNA microarrays serve as suitable high throughput tool for simultaneous analysis of multiple genes. Major practical applicability of DNA microarrays remains in DNA mutation and polymorphism analysis. This review highlights applications of DNA microarrays in pharmacodynamics, pharmacogenomics, toxicogenomics and quality control of herbal drugs and extracts. PMID:17173108

  2. Microarray studies of genomic oxidative stress and cell cycle responses in obstructive sleep apnea.

    PubMed

    Hoffmann, Michal S; Singh, Prachi; Wolk, Robert; Romero-Corral, Abel; Raghavakaimal, Sreekumar; Somers, Virend K

    2007-06-01

    Obstructive sleep apnea (OSA), the commonest form of sleep-disordered breathing, is characterized by recurrent episodes of intermittent hypoxia and sleep fragmentation. This study evaluated microarray measures of gene transcript levels in OSA subjects compared to age and BMI matched healthy controls. Measurements were obtained before and after: (a) a night of normal sleep in controls; and (b) a night of untreated apnea in OSA patients. All subjects underwent full polysomnography. mRNA from the whole blood samples was analyzed by HG-U133A and B Affymetrix GeneChip arrays using Spotfire 7.2 data analysis platform. After sleep in OSA patients, changes were noted in several genes involved in modulation of reactive oxygen species (ROS), including heme oxygenase 1, superoxide dismutase 1 and 2, and catalase. Changes were also observed in genes involved in cell growth, proliferation, and the cell cycle such as cell division cycle 25B, signaling lymphocyte activating molecule (SLAM), calgizzarin S100A11, B-cell translocation gene, Src-like adapter protein (SLAP), and eukaryotic translation initiation factor 4E binding protein 2. These overnight changes in OSA patients are suggestive of activation of several mechanisms to modulate, and adapt to, increased ROS developing in response to the frequent episodes of intermittent hypoxia.

  3. Use of Genomic DNA as A Reference in DNA Microarrays

    SciTech Connect

    Yang, Yunfeng

    2009-01-01

    DNA microarray has become a mainstream technology to explore gene expression profiles, identify novel genes involved in a biological process of interest and predict their function, and determine biomarkers that are relevant to a given phenotype or disease. Typical two-channel microarray studies use an experimental design called the complementary DNA (cDNA) reference method, in which samples from test and control conditions are compared directly on a microarray slide. A substantial limitation of this strategy is that it is nearly impossible to compare data between experiments because the reference sample composition is subjected to changes at the level of experimental design and thereby not consistent from one experiment to another. Using genomic DNA as common reference will effectively overcome this limitation. This chapter describes detailed methods to prepare genomic DNA of high quality, label with fluorescent dye, co-hybridize with cDNA samples, and the subsequent data analyses. In addition, notes are provided to help the readers to obtain optimal results using the procedure.

  4. [Microarray CGH: principle and use for constitutional disorders].

    PubMed

    Sanlaville, D; Lapierre, J M; Coquin, A; Turleau, C; Vermeesch, J; Colleaux, L; Borck, G; Vekemans, M; Aurias, A; Romana, S P

    2005-10-01

    Chips technology has allowed to miniaturize process making possible to realize in one step and using the same device a lot of chemical reactions. The application of this technology to molecular cytogenetics resulted in the development of comparative genomic hybridization (CGH) on microarrays technique. Using this technique it is possible to detect very small genetic imbalances anywhere in the genome. Its usefulness has been well documented in cancer and more recently in constitutional disorders. In particular it has been used to detect interstitial and subtelomeric submicroscopic imbalances, to characterize their size at the molecular level or to define the breakpoints of translocation. The challenge today is to transfer this technology in laboratory medicine. Nevertheless this technology remains expensive and the existence of numerous sequence polymorphisms makes its interpretation difficult. Finally its is unlikely that it will make karyotyping obsolete as it does not allow to detect balanced rearrangements which after meiotic segregation might result in genome imbalance in the progeny. PMID:16153813

  5. Microarray gene expression analysis of fixed archival tissue permits molecular classification and identification of potential therapeutic targets in diffuse large B-cell lymphoma.

    PubMed

    Linton, Kim; Howarth, Christopher; Wappett, Mark; Newton, Gillian; Lachel, Cynthia; Iqbal, Javeed; Pepper, Stuart; Byers, Richard; Chan, Wing John; Radford, John

    2012-01-01

    Refractory/relapsed diffuse large B-cell lymphoma (DLBCL) has a poor prognosis. Novel drugs targeting the constitutively activated NF-κB pathway characteristic of ABC-DLBCL are promising, but evaluation depends on accurate activated B cell-like (ABC)/germinal center B cell-like (GCB) molecular classification. This is traditionally performed on gene microarray expression profiles of fresh biopsies, which are not routinely collected, or by immunohistochemistry on formalin-fixed, paraffin-embedded (FFPE) tissue, which lacks reproducibility and classification accuracy. We explored the possibility of using routine archival FFPE tissue for gene microarray applications. We examined Affymetrix HG U133 Plus 2.0 gene expression profiles from paired archival FFPE and fresh-frozen tissues of 40 ABC/GCB-classified DLBCL cases to compare classification accuracy and test the potential for this approach to aid the discovery of therapeutic targets and disease classifiers in DLBCL. Unsupervised hierarchical clustering of unselected present probe sets distinguished ABC/GCB in FFPE with remarkable accuracy, and a Bayesian classifier correctly assigned 32 of 36 cases with >90% probability. Enrichment for NF-κB genes was appropriately seen in ABC-DLBCL FFPE tissues. The top discriminatory genes expressed in FFPE separated cases with high statistical significance and contained novel biology with potential therapeutic insights, warranting further investigation. These results support a growing understanding that archival FFPE tissues can be used in microarray experiments aimed at molecular classification, prognostic biomarker discovery, and molecular exploration of rare diseases.

  6. Microarray long oligo probe designing for Escherichia coli: an in-silico DNA marker extraction

    PubMed Central

    Behzadi, Payam; Najafi, Ali; Behzadi, Elham

    2016-01-01

    Introduction Urinary tract infections are predominant diseases which may be caused by different pathogenic microorganisms, particularly Escherichia coli (E.coli). DNA microarray technology is an accurate, rapid, sensitive, and specific diagnostic tool which may lead to definite diagnosis and treatment of several infectious diseases. DNA microarray is a multi-process method in which probe designing plays an important. Therefore, the authors of the present study have tried to design a range of effective and proper long oligo microarray probes for detection and identification of different strains of pathogenic E.coli and in particular, uropathogenic E.coli (UPEC). Material and methods E.coli O26 H11 11368 uid41021 was selected as the standard strain for probe designing. This strain encompasses the largest nucleotide sequence and the most number of genes among other pathogenic strains of E.coli. For performing this in silico survey, NCBI database, GReview Server, PanSeq Server, Oligoanalyzer tool, and AlleleID 7.7 were used to design accurate, appropriate, effective, and flexible long oligo microarray probes. Moreover, the genome of E.coli and its closely related microorganisms were compared. Results In this study, 15 long oligo microarray probes were designed for detecting and identifying different strains of E.coli such as UPEC. These probes possessed the best physico-chemical characteristics. The functional and structural properties of the designed probes were recognized by practical tools and softwares. Conclusions The use of reliable advanced technologies and methodologies for probe designing guarentees the high quality of microarray probes and makes DNA microarray technology more flexible and an effective diagnostic technique. PMID:27123336

  7. Assembly of ordered microsphere arrays: Platforms for microarrays

    NASA Astrophysics Data System (ADS)

    Xu, Wanling

    Microarrays are powerful tools in gene expression assessment, protein profiling, and protein function screening, as well as cell and tissue analysis. With thousands of small array spots assembled in an ordered array, these small devices makes it possible to screen for multiple targets in a fast, parallel, high-throughput manner. The well-developed technology of DNA microarrays, also called DNA chips, has proved successful in all kinds of biological experiments, including the human genome-sequencing project. The development of protein arrays has lagged behind that of DNA arrays mainly because of the greater complexity of proteins. Some parts of the microarray technology can be transplanted into the realm of protein arrays, while others cannot. The challenges from the complexity of protein targets demand more robust and powerful devices. Traditional planar arrays, in which proteins bind directly to a planar surface, have a drawback in that some proteins will be denatured or cluster together after immobilization. Microsphere-based microarrays represent a more advanced strategy. The functional proteins are first attached to microspheres; these microspheres are then immobilized in arrays on a planar surface. In this dissertation, two approaches to assembling arrays of microspheres will be discussed. The hydrodynamic approach uses surface micromachining and Deep Reactive Ion Etching techniques to form an array of channels through a silicon wafer. By drawing fluid containing the microspheres through the channels they become trapped in the channels and thereby immobilized. In the magnetic approach, permalloy films are deposited on a silicon substrate and subsequently patterned to form magnetic attachment sites. An external magnetic field is then applied and the magnetic microspheres then assemble on these sites. Both devices are able to immobilize microspheres in an ordered array, as opposed to coarsely grouping them in array spots. The assembled arrays are robust in that

  8. Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

    PubMed Central

    2011-01-01

    Breast cancer comprises a collection of diseases with distinctive clinical, histopathological, and molecular features. Importantly, tumors with similar histological features may display disparate clinical behaviors. Gene expression profiling using microarray technologies has improved our understanding of breast cancer biology and has led to the development of a breast cancer molecular taxonomy and of multigene 'signatures' to predict outcome and response to systemic therapies. The use of these prognostic and predictive signatures in routine clinical decision-making remains controversial. Here, we review the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management. PMID:21787441

  9. Automated analytical microarrays: a critical review.

    PubMed

    Seidel, Michael; Niessner, Reinhard

    2008-07-01

    Microarrays provide a powerful analytical tool for the simultaneous detection of multiple analytes in a single experiment. The specific affinity reaction of nucleic acids (hybridization) and antibodies towards antigens is the most common bioanalytical method for generating multiplexed quantitative results. Nucleic acid-based analysis is restricted to the detection of cells and viruses. Antibodies are more universal biomolecular receptors that selectively bind small molecules such as pesticides, small toxins, and pharmaceuticals and to biopolymers (e.g. toxins, allergens) and complex biological structures like bacterial cells and viruses. By producing an appropriate antibody, the corresponding antigenic analyte can be detected on a multiplexed immunoanalytical microarray. Food and water analysis along with clinical diagnostics constitute potential application fields for multiplexed analysis. Diverse fluorescence, chemiluminescence, electrochemical, and label-free microarray readout systems have been developed in the last decade. Some of them are constructed as flow-through microarrays by combination with a fluidic system. Microarrays have the potential to become widely accepted as a system for analytical applications, provided that robust and validated results on fully automated platforms are successfully generated. This review gives an overview of the current research on microarrays with the focus on automated systems and quantitative multiplexed applications.

  10. Optical transfer function for an f-theta lens based confocal fluorescent microarray analyzer

    NASA Astrophysics Data System (ADS)

    Shi, Yan; Ni, Xuxiang; Xu, Guoxiong; Li, Chen; Zhang, Xi; Lu, Zukang

    2005-01-01

    Optical transfer function is widely used to evaluate the imaging performance of an optical system. Combined with confocal scanning technology, f-theta lens can increase the reading speed for microarrays greatly in guarantee of sufficient resolution and fluorescence collection efficiency, compared with micro-array analyzers that adopting mechanical scanning. In this paper, the characteristics of a confocal scanning f-theta objective lens, which was used in micro-array analyzing instrument, were analyzed by means of optical transfer function. In the whole system, laser passed through the f-theta lens, and arrived at the microarray slide where fluorophores were excited. Fluorescence emitting from the micro-array slide was collected by the same f-theta lens, and was captured by a detector. As a laser illumination system, the objective lens had a smaller stop aperture. As a fluorescence collection system, it had a bigger stop aperture. In conclusion, optical transfer function for the whole system, from source to detector, is the combination of that of the laser illumination, a coherent system, and that of the fluorescence collection system, an incoherent system. Uniformity of laser illumination at the micro-array slide was analyzed using optical transfer function during the course of scanning. The influence of aberrations on optical transfer function is given. The simulating results for above characteristics are also presented.

  11. Biochemical pathways analysis of microarray results: regulation of myogenesis in pigs

    PubMed Central

    te Pas, Marinus FW; Hulsegge, Ina; Coster, Albart; Pool, Marco H; Heuven, Henri H; Janss, Luc LG

    2007-01-01

    Background Combining microarray results and biological pathway information will add insight into biological processes. Pathway information is widely available in databases through the internet. Mammalian muscle formation has been previously studied using microarray technology in pigs because these animals are an interesting animal model for muscle formation due to selection for increased muscle mass. Results indicated regulation of the expression of genes involved in proliferation and differentiation of myoblasts, and energy metabolism. The aim of the present study was to analyse microarrays studying myogenesis in pigs. It was necessary to develop methods to search biochemical pathways databases. Results PERL scripts were developed that used the names of the genes on the microarray to search databases. Synonyms of gene names were added to the list by searching the Gene Ontology database. The KEGG database was searched for pathway information using this updated gene list. The KEGG database returned 88 pathways. Most genes were found in a single pathway, but others were found in up to seven pathways. Combining the pathways and the microarray information 21 pathways showed sufficient information content for further analysis. These pathways were related to regulation of several steps in myogenesis and energy metabolism. Pathways regulating myoblast proliferation and muscle fibre formation were described. Furthermore, two networks of pathways describing the formation of the myoblast cytoskeleton and regulation of the energy metabolism during myogenesis were presented. Conclusion Combining microarray results and pathways information available through the internet provide biological insight in how the process of porcine myogenesis is regulated. PMID:17567520

  12. Development, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray

    PubMed Central

    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 (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower 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. PMID:23110046

  13. Identification of chromosomal errors in human preimplantation embryos with oligonucleotide DNA microarray.

    PubMed

    Liang, Lifeng; Wang, Cassie T; Sun, Xiaofang; Liu, Lian; Li, Man; Witz, Craig; Williams, Daniel; Griffith, Jason; Skorupski, Josh; Haddad, Ghassan; Gill, Jimmy; Wang, Wei-Hua

    2013-01-01

    A previous study comparing the performance of different platforms for DNA microarray found that the oligonucleotide (oligo) microarray platform containing 385K isothermal probes had the best performance when evaluating dosage sensitivity, precision, specificity, sensitivity and copy number variations border definition. Although oligo microarray platform has been used in some research fields and clinics, it has not been used for aneuploidy screening in human embryos. The present study was designed to use this new microarray platform for preimplantation genetic screening in the human. A total of 383 blastocysts from 72 infertility patients with either advanced maternal age or with previous miscarriage were analyzed after biopsy and microarray. Euploid blastocysts were transferred to patients and clinical pregnancy and implantation rates were measured. Chromosomes in some aneuploid blastocysts were further analyzed by fluorescence in-situ hybridization (FISH) to evaluate accuracy of the results. We found that most (58.1%) of the blastocysts had chromosomal abnormalities that included single or multiple gains and/or losses of chromosome(s), partial chromosome deletions and/or duplications in both euploid and aneuploid embryos. Transfer of normal euploid blastocysts in 34 cycles resulted in 58.8% clinical pregnancy and 54.4% implantation rates. Examination of abnormal blastocysts by FISH showed that all embryos had matching results comparing microarray and FISH analysis. The present study indicates that oligo microarray conducted with a higher resolution and a greater number of probes is able to detect not only aneuploidy, but also minor chromosomal abnormalities, such as partial chromosome deletion and/or duplication in human embryos. Preimplantation genetic screening of the aneuploidy by DNA microarray is an advanced technology used to select embryos for transfer and improved embryo implantation can be obtained after transfer of the screened normal embryos.

  14. Probe Region Expression Estimation for RNA-Seq Data for Improved Microarray Comparability.

    PubMed

    Uziela, Karolis; Honkela, Antti

    2015-01-01

    Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. Although RNA-sequencing (RNA-seq) is attracting the most attention, at present, the rate of new microarray studies submitted to public databases far exceeds the rate of new RNA-seq studies. There is clearly a need for methods that make it easier to combine data from different technologies. In this paper, we propose a new method for processing RNA-seq data that yields gene expression estimates that are much more similar to corresponding estimates from microarray data, hence greatly improving cross-platform comparability. The method we call PREBS is based on estimating the expression from RNA-seq reads overlapping the microarray probe regions, and processing these estimates with standard microarray summarisation algorithms. Using paired microarray and RNA-seq samples from TCGA LAML data set we show that PREBS expression estimates derived from RNA-seq are more similar to microarray-based expression estimates than those from other RNA-seq processing methods. In an experiment to retrieve paired microarray samples from a database using an RNA-seq query sample, gene signatures defined based on PREBS expression estimates were found to be much more accurate than those from other methods. PREBS also allows new ways of using RNA-seq data, such as expression estimation for microarray probe sets. An implementation of the proposed method is available in the Bioconductor package "prebs."

  15. Development, characterization and experimental validation of a cultivated sunflower (Helianthus annuus L.) gene expression oligonucleotide microarray.

    PubMed

    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 (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower 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. PMID:23110046

  16. Microarray-based understanding of normal and malignant plasma cells

    PubMed Central

    De Vos, John; Hose, Dirk; Rème, Thierry; Tarte, Karin; Moreaux, Jérôme; Mahtouk, Karéne; Jourdan, Michel; Goldschmidt, Hartmut; Rossi, Jean-François; Cremer, Friedrich W.; Klein, Bernard

    2006-01-01

    Plasma cells develop from B-lymphocytes following stimulation by antigen and express a genetic program aimed at the synthesis of immunoglobulins. This program includes the induction of genes coding for transcription factors such as PRDM1 and XBP1, cell-surface molecules such as CD138/syndecan-1 and for the unfolded protein response (UPR). We review how the microarray technology has recently contributed to the understanding of the biology of this rare but essential cell population and its transformation into pre-malignant and malignant plasma cells. PMID:16623766

  17. Multiplexed electrospray deposition for protein microarray with micromachined silicon device

    NASA Astrophysics Data System (ADS)

    Bhatnagar, Parijat

    2007-07-01

    Multiplexed electrospray deposition device capable of delivering picoliter volumes made by silicon micromachining technology has been developed as a deposition tool for making protein microarrays in a noncontact mode. Upon application of potential difference in the range of 7-9kV, biomolecules dissolved in suitable buffer with nonionic surfactant and loaded on the electrospray tips were dispensed on the substrate with microfabricated hydrogel features (1-10μm) in cone-jet mode. Schiff base chemistry followed by reductive amination was utilized for covalent immobilization.

  18. Microarray-Based Maps of Copy-Number Variant Regions in European and Sub-Saharan Populations

    PubMed Central

    Röthlisberger, Benno; Huber, Andreas; Filges, Isabel; Miny, Peter; Auschra, Bianca; Stetak, Attila; Demougin, Philippe; Vukojevic, Vanja; Kolassa, Iris-Tatjana; Elbert, Thomas; de Quervain, Dominique J.-F.; Papassotiropoulos, Andreas

    2010-01-01

    The genetic basis of phenotypic variation can be partially explained by the presence of copy-number variations (CNVs). Currently available methods for CNV assessment include high-density single-nucleotide polymorphism (SNP) microarrays that have become an indispensable tool in genome-wide association studies (GWAS). However, insufficient concordance rates between different CNV assessment methods call for cautious interpretation of results from CNV-based genetic association studies. Here we provide a cross-population, microarray-based map of copy-number variant regions (CNVRs) to enable reliable interpretation of CNV association findings. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to scan the genomes of 1167 individuals from two ethnically distinct populations (Europe, N = 717; Rwanda, N = 450). Three different CNV-finding algorithms were tested and compared for sensitivity, specificity, and feasibility. Two algorithms were subsequently used to construct CNVR maps, which were also validated by processing subsamples with additional microarray platforms (Illumina 1M-Duo BeadChip, Nimblegen 385K aCGH array) and by comparing our data with publicly available information. Both algorithms detected a total of 42669 CNVs, 74% of which clustered in 385 CNVRs of a cross-population map. These CNVRs overlap with 862 annotated genes and account for approximately 3.3% of the haploid human genome. We created comprehensive cross-populational CNVR-maps. They represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies. PMID:21179565

  19. Microarray-based maps of copy-number variant regions in European and sub-Saharan populations.

    PubMed

    Vogler, Christian; Gschwind, Leo; Röthlisberger, Benno; Huber, Andreas; Filges, Isabel; Miny, Peter; Auschra, Bianca; Stetak, Attila; Demougin, Philippe; Vukojevic, Vanja; Kolassa, Iris-Tatjana; Elbert, Thomas; de Quervain, Dominique J-F; Papassotiropoulos, Andreas

    2010-12-16

    The genetic basis of phenotypic variation can be partially explained by the presence of copy-number variations (CNVs). Currently available methods for CNV assessment include high-density single-nucleotide polymorphism (SNP) microarrays that have become an indispensable tool in genome-wide association studies (GWAS). However, insufficient concordance rates between different CNV assessment methods call for cautious interpretation of results from CNV-based genetic association studies. Here we provide a cross-population, microarray-based map of copy-number variant regions (CNVRs) to enable reliable interpretation of CNV association findings. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to scan the genomes of 1167 individuals from two ethnically distinct populations (Europe, N=717; Rwanda, N=450). Three different CNV-finding algorithms were tested and compared for sensitivity, specificity, and feasibility. Two algorithms were subsequently used to construct CNVR maps, which were also validated by processing subsamples with additional microarray platforms (Illumina 1M-Duo BeadChip, Nimblegen 385K aCGH array) and by comparing our data with publicly available information. Both algorithms detected a total of 42669 CNVs, 74% of which clustered in 385 CNVRs of a cross-population map. These CNVRs overlap with 862 annotated genes and account for approximately 3.3% of the haploid human genome.We created comprehensive cross-populational CNVR-maps. They represent an extendable framework that can leverage the detection of common CNVs and additionally assist in interpreting CNV-based association studies.

  20. Transcriptomic response of murine liver to severe injury and hemorrhagic shock: a dual-platform microarray analysis

    PubMed Central

    Edmonds, Rebecca D.; Lagoa, Claudio; Dutta-Moscato, Joyeeta; Yang, Yawching; Fink, Mitchell P.; Levy, Ryan M.; Prince, Jose M.; Kaczorowski, David J.; Tseng, George C.; Billiar, Timothy R.

    2011-01-01

    Trauma-hemorrhagic shock (HS/T) is a complex process that elicits numerous molecular pathways. We hypothesized that a dual-platform microarray analysis of the liver, an organ that integrates immunology and metabolism, would reveal key pathways engaged following HS/T. C57BL/6 mice were divided into five groups (n = 4/group), anesthetized, and surgically treated to simulate a time course and trauma severity model: 1) nonmanipulated animals, 2) minor trauma, 3) 1.5 h of hemorrhagic shock and severe trauma (HS/T), 4) 1.5 h HS/T followed by 1 h resuscitation (HS/T+1.0R), 5) 1.5 h HS/T followed by 4.5 h resuscitation (HS/T+4.5R). Liver RNA was hybridized to CodeLink and Affymetrix mouse whole genome microarray chips. Common genes with a cross-platform correlation >0.6 (2,353 genes in total) were clustered using k-means clustering, and clusters were analyzed using Ingenuity Pathways Analysis. Genes involved in the stress response and immunoregulation were upregulated early and remained upregulated throughout the course of the experiment. Genes involved in cell death and inflammatory pathways were upregulated in a linear fashion with elapsed time and in severe injury compared with minor trauma. Three of the six clusters contained genes involved in metabolic function; these were downregulated with elapsed time. Transcripts involved in amino acid metabolism as well as signaling pathways associated with glucocorticoid receptors, IL-6, IL-10, and the acute phase response were elevated in a severity-dependent manner. This is the first study to examine the postinjury response using dual-platform microarray analysis, revealing responses that may enable novel therapies or diagnostics. PMID:21828244

  1. Gene regulation induced in the C57BL/6J mouse retina by hyperoxia: a temporal microarray study

    PubMed Central

    Provis, Jan; Valter, Krisztina; Stone, Jonathan

    2008-01-01

    Purpose Hyperoxia is specifically toxic to photoreceptors, and this toxicity may be important in the progress of retinal dystrophies. This study examines gene expression induced in the C57BL/6J mouse retina by hyperoxia over the 14-day period during which photoreceptors first resist, then succumb to, hyperoxia. Methods Young adult C57BL/6J mice were exposed to hyperoxia (75% oxygen) for up to 14 days. On day 0 (control), day 3, day 7, and day 14, retinal RNA was extracted and processed on Affymetrix GeneChip® Mouse Genome 430 2.0 arrays. Microarray data were analyzed using GCOS Version 1.4 and GeneSpring Version 7.3.1. For 15 genes, microarray data were confirmed using relative quantitative real-time reverse transcription polymerase chain reaction techniques. Results The overall numbers of hyperoxia-regulated genes increased monotonically with exposure. Within that increase, however, a distinctive temporal pattern was apparent. At 3 days exposure, there was prominent upregulation of genes associated with neuroprotection. By day 14, these early-responsive genes were downregulated, and genes related to cell death were strongly expressed. At day 7, the regulation of these genes was mixed, indicating a possible “transition period” from stability at day 3 to degeneration at day 14. When functional groupings of genes were analyzed separately, there was significant regulation in genes responsive to stress, genes known to cause human photoreceptor dystrophies and genes associated with apoptosis. Conclusions Microarray analysis of the response of the retina to prolonged hyperoxia demonstrated a temporal pattern involving early neuroprotection and later cell death, and provided insight into the mechanisms involved in the two phases of response. As hyperoxia is a consistent feature of the late stages of photoreceptor degenerations, understanding the mechanisms of oxygen toxicity may be important therapeutically. PMID:18989387

  2. Microbial forensics: fiber optic microarray subtyping of Bacillus anthracis

    NASA Astrophysics Data System (ADS)

    Shepard, Jason R. E.

    2009-05-01

    The past decade has seen increased development and subsequent adoption of rapid molecular techniques involving DNA analysis for detection of pathogenic microorganisms, also termed microbial forensics. The continued accumulation of microbial sequence information in genomic databases now better positions the field of high-throughput DNA analysis to proceed in a more manageable fashion. The potential to build off of these databases exists as technology continues to develop, which will enable more rapid, cost effective analyses. This wealth of genetic information, along with new technologies, has the potential to better address some of the current problems and solve the key issues involved in DNA analysis of pathogenic microorganisms. To this end, a high density fiber optic microarray has been employed, housing numerous DNA sequences simultaneously for detection of various pathogenic microorganisms, including Bacillus anthracis, among others. Each organism is analyzed with multiple sequences and can be sub-typed against other closely related organisms. For public health labs, real-time PCR methods have been developed as an initial preliminary screen, but culture and growth are still considered the gold standard. Technologies employing higher throughput than these standard methods are better suited to capitalize on the limitless potential garnered from the sequence information. Microarray analyses are one such format positioned to exploit this potential, and our array platform is reusable, allowing repetitive tests on a single array, providing an increase in throughput and decrease in cost, along with a certainty of detection, down to the individual strain level.

  3. 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.

    PubMed

    Morgan, Kevin T; Ni, Hong; Brown, H Roger; Yoon, Lawrence; Qualls, Charles W; Crosby, Lynn M; Reynolds, Randall; Gaskill, Betty; Anderson, Steven P; Kepler, Thomas B; Brainard, Tracy; Liv, Nik; Easton, Marilyn; Merrill, Christine; Creech, Don; Sprenger, Dirk; Conner, Gary; Johnson, Paul R; Fox, Tony; Sartor, Maureen; Richard, Erika; Kuruvilla, Sabu; Casey, Warren; Benavides, Gina

    2002-01-01

    Large-scale analysis of gene expression using cDNA microarrays promises the rapid detection of the mode of toxicity for drugs and other chemicals. cDNA microarrays were used to examine chemically induced alterations of gene expression in HepG2 cells exposed to a diverse group of toxicants at an equitoxic exposure concentration. The treatments were ouabain (43 microM), lauryl sulfate (260 microM), dimethylsulfoxide (1.28 M), cycloheximide (62.5 microM), tolbutamide (12.8 mM), sodium fluoride (3 mM), diethyl maleate (1.25 mM), buthionine sulfoximine (30 mM), potassium bromate (2.5 mM), sodium selenite (30 microM), alloxan (130 mM), adriamycin (40 microM), hydrogen peroxide (4 mM), and heat stress (45 degrees C x 30 minutes). Patterns of gene expression were correlated with morphologic and biochemical indicators of toxicity. Gene expression responses were characteristically different for each treatment. Patterns of expression were consistent with cell cycle arrest, DNA damage, diminished protein synthesis, and oxidative stress. Based upon these results, we concluded that gene expression changes provide a useful indicator of oxidative stress, as assessed by the GSH:GSSG ratio. Under the conditions of this cell culture test system, oxidative stress upregulated 5 genes, HMOX1, p21(waf1/cip1), GCLM, GR, TXNR1 while downregulating CYP1A1 and TOPO2A. Primers and probes for these genes were incorporated into the design of a 7-gene plate for RT-PCR. The plate design permitted statistical analysis and allowed clear discrimination between chemicals inducing oxidative vs nonoxidative stress. A simple oxidative stress score (0-1), based on the responses by the 7 genes (including p-value) on the RT-PCR plate, was correlated with the GSH:GSSG ratio using linear regression and ranking (Pearson product) procedures. These analyses yielded correlation coefficients of 0.74 and 0.87, respectively, for the treatments tested (when 1 outlier was excluded), indicating a good correlation

  4. Influence of oxygen limitation, absence of the cytochrome bc(1) complex and low pH on global gene expression in Gluconobacter oxydans 621H using DNA microarray technology.

    PubMed

    Hanke, Tanja; Richhardt, Janine; Polen, Tino; Sahm, Hermann; Bringer, Stephanie; Bott, Michael

    2012-02-10

    The genome-wide transcriptional responses of the strictly aerobic α-proteobacterium Gluconobacter oxydans 621H to oxygen limitation, to the absence of the cytochrome bc(1) complex, and to low pH were studied using DNA microarray analyses. Oxygen limitation caused expression changes of 486 genes, representing 20% of the chromosomal genes. Genes with an increased mRNA level included those for terminal oxidases, the cytochrome bc(1) complex, transhydrogenase, two alcohol dehydrogenases, heme biosynthesis, PTS proteins, proteins involved in cyclic diGMP synthesis and degradation, two sigma factors, flagella and chemotaxis proteins, several stress proteins, and a putative exporter protein. The downregulated genes comprised those for respiratory dehydrogenases, enzymes of central metabolism, PQQ biosynthesis, outer membrane receptors, Sec proteins, and proteins involved in transcription and translation. A ΔqrcABC mutant of G. oxydans showed a growth defect during cultivation on mannitol at pH 4 under oxygen saturation. Comparison of the transcriptomes of this mutant versus the wild type under these conditions revealed 51 differentially expressed genes. Interestingly, almost all of the 45 genes with increased expression in the ΔqrcABC mutant at pH 4 were also upregulated in the wild type grown at pH 6 under oxygen limitation. These results support an active role of the cytochrome bc(1) complex in G. oxydans respiration. The transcriptome comparison of G. oxydans wild type at pH 4 versus pH 6 in mannitol medium under oxygen-saturated conditions uncovered only 72 differentially expressed genes. The 35 upregulated genes included those for cytochrome bd oxidase, major polyol dehydrogenase, iron storage and oxidative stress proteins. Among the 37 downregulated genes were some encoding enzymes dealing with carbon dioxide, such as biotin carboxylase, biotin carboxyl carrier protein, and carboanhydrase. These results give first insights into global transcriptional responses of

  5. Influence of oxygen limitation, absence of the cytochrome bc(1) complex and low pH on global gene expression in Gluconobacter oxydans 621H using DNA microarray technology.

    PubMed

    Hanke, Tanja; Richhardt, Janine; Polen, Tino; Sahm, Hermann; Bringer, Stephanie; Bott, Michael

    2012-02-10

    The genome-wide transcriptional responses of the strictly aerobic α-proteobacterium Gluconobacter oxydans 621H to oxygen limitation, to the absence of the cytochrome bc(1) complex, and to low pH were studied using DNA microarray analyses. Oxygen limitation caused expression changes of 486 genes, representing 20% of the chromosomal genes. Genes with an increased mRNA level included those for terminal oxidases, the cytochrome bc(1) complex, transhydrogenase, two alcohol dehydrogenases, heme biosynthesis, PTS proteins, proteins involved in cyclic diGMP synthesis and degradation, two sigma factors, flagella and chemotaxis proteins, several stress proteins, and a putative exporter protein. The downregulated genes comprised those for respiratory dehydrogenases, enzymes of central metabolism, PQQ biosynthesis, outer membrane receptors, Sec proteins, and proteins involved in transcription and translation. A ΔqrcABC mutant of G. oxydans showed a growth defect during cultivation on mannitol at pH 4 under oxygen saturation. Comparison of the transcriptomes of this mutant versus the wild type under these conditions revealed 51 differentially expressed genes. Interestingly, almost all of the 45 genes with increased expression in the ΔqrcABC mutant at pH 4 were also upregulated in the wild type grown at pH 6 under oxygen limitation. These results support an active role of the cytochrome bc(1) complex in G. oxydans respiration. The transcriptome comparison of G. oxydans wild type at pH 4 versus pH 6 in mannitol medium under oxygen-saturated conditions uncovered only 72 differentially expressed genes. The 35 upregulated genes included those for cytochrome bd oxidase, major polyol dehydrogenase, iron storage and oxidative stress proteins. Among the 37 downregulated genes were some encoding enzymes dealing with carbon dioxide, such as biotin carboxylase, biotin carboxyl carrier protein, and carboanhydrase. These results give first insights into global transcriptional responses of

  6. A multivariate approach for high throughput pectin profiling by combining glycan microarrays with monoclonal antibodies.

    PubMed

    Sousa, António G; Ahl, Louise I; Pedersen, Henriette L; Fangel, Jonatan U; Sørensen, Susanne O; Willats, William G T

    2015-05-29

    Pectin-one of the most complex biomacromolecules in nature has been extensively studied using various techniques. This has been done so in an attempt to understand the chemical composition and conformation of pectin, whilst discovering and optimising new industrial applications of the polymer. For the last decade the emergence of glycan microarray technology has led to a growing capacity of acquiring simultaneous measurements related to various carbohydrate characteristics while generating large collections of data. Here we used a multivariate analysis approach in order to analyse a set of 359 pectin samples probed with 14 different monoclonal antibodies (mAbs). Principal component analysis (PCA) and partial least squares (PLS) regression were utilised to obtain the most optimal qualitative and quantitative information from the spotted microarrays. The potential use of microarray technology combined with chemometrics for the accurate determination of degree of methyl-esterification (DM) and degree of blockiness (DB) was assessed. PMID:25950120

  7. The Potentials and Pitfalls of Microarrays in Neglected Tropical Diseases: A Focus on Human Filarial Infections.

    PubMed

    Kwarteng, Alexander; Ahuno, Samuel Terkper

    2016-01-01

    Data obtained from expression microarrays enables deeper understanding of the molecular signatures of infectious diseases. It provides rapid and accurate information on how infections affect the clustering of gene expression profiles, pathways and networks that are transcriptionally active during various infection states compared to conventional diagnostic methods, which primarily focus on single genes or proteins. Thus, microarray technologies offer advantages in understanding host-parasite interactions associated with filarial infections. More importantly, the use of these technologies can aid diagnostics and helps translate current genomic research into effective treatment and interventions for filarial infections. Studying immune responses via microarray following infection can yield insight into genetic pathways and networks that can have a profound influence on the development of anti-parasitic vaccines. PMID:27600086

  8. The Potentials and Pitfalls of Microarrays in Neglected Tropical Diseases: A Focus on Human Filarial Infections

    PubMed Central

    Kwarteng, Alexander; Ahuno, Samuel Terkper

    2016-01-01

    Data obtained from expression microarrays enables deeper understanding of the molecular signatures of infectious diseases. It provides rapid and accurate information on how infections affect the clustering of gene expression profiles, pathways and networks that are transcriptionally active during various infection states compared to conventional diagnostic methods, which primarily focus on single genes or proteins. Thus, microarray technologies offer advantages in understanding host-parasite interactions associated with filarial infections. More importantly, the use of these technologies can aid diagnostics and helps translate current genomic research into effective treatment and interventions for filarial infections. Studying immune responses via microarray following infection can yield insight into genetic pathways and networks that can have a profound influence on the development of anti-parasitic vaccines. PMID:27600086

  9. Monitoring Protein Kinase Expression and Phosphorylation in Cell Lysates with Antibody Microarrays.

    PubMed

    Zhang, Hong; Shi, Xiaoqing; Pelech, Steven

    2016-01-01

    Fuelled by advances in our understanding of the human kinome and phosphoproteome and the increasing availability of pan- and phosphosite-specific antibodies, antibody microarrays have emerged as powerful tools for interrogating protein phosphorylation-mediated signaling systems in ex vivo studies. This economical platform permits ultra-sensitive, semiquantitative measurements of the levels of hundreds of protein kinases and their substrates along with their phosphorylation status simultaneously with minute amounts of specimens. Recent technological innovations in the design and fabrication of antibody microarrays and sample preparation have permitted further refinements of the technology to yield improvements in data quality. In this chapter, we describe a detailed protocol that we have developed for tracking the expression and phosphorylation of protein kinases and their substrates in crude cell lysate samples using a high-content antibody microarray.

  10. MicroGen: a MIAME compliant web system for microarray experiment information and workflow management

    PubMed Central

    Burgarella, Sarah; Cattaneo, Dario; Pinciroli, Francesco; Masseroli, Marco

    2005-01-01

    Background Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. Results We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. Conclusion MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production. PMID:16351755

  11. Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

    PubMed Central

    Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

    2013-01-01

    Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

  12. Gene expression profiling of RNA extracted from FFPE tissues: NuGEN technologies' whole-transcriptome amplification system.

    PubMed

    Turner, Leah; Heath, Joe Don; Kurn, Nurith

    2011-01-01

    Gene expression profiling of RNA isolated from formalin fixed, paraffin-embedded (FFPE) tissue samples has been historically challenging. Yet FFPE samples are sought-after because of the in-depth retrospective records typically associated with them rendering these samples a valuable resource for translational medicine studies. Extensive degradation, chemical modifications, and cross-linking have made it difficult to isolate RNA of sufficient quality required for large-scale gene expression profiling studies. NuGEN Technologies' WT-Ovation™ FFPE System linearly amplifies RNA from FFPE samples through a robust and simple whole-transcriptome approach using as little as 50 ng total RNA isolated from FFPE samples. The amplified material may be labeled with validated kits and/or protocols from NuGEN for analysis on any of the major gene expression microarray platforms, including: Affymetrix, Agilent, and Illumina gene expression arrays. Results compare well with those obtained using RNA from fresh-frozen samples. RNA quality from FFPE samples varies significantly and neither sample age nor sample size analysis via gel electrophoresis or the Agilent Bioanalyzer system accurately predict materials suitable for amplification. Therefore, NuGEN has validated a correlative qPCR-based analytical method for the RNA derived from FFPE samples which effectively predicts array results. The NuGEN approach enables fast and successful analysis of samples previously thought to be too degraded for gene expression analysis.

  13. Lithographic techniques and surface chemistries for the fabrication of PEG-passivated protein microarrays

    PubMed Central

    Kannan, Balaji; Castelino, Kenneth; Chen, Fanqing Frank

    2009-01-01

    This article presents a new technique to fabricate patterns of functional molecules surrounded by a coating of the inert poly(ethylene glycol) (PEG) on glass slides for applications in protein microarray technology. The chief advantages of this technique are that it is based entirely on standard lithography processes, makes use of glass slides employing surface chemistries that are standard in the microarray community, and has the potential to massively scale up the density of microarray spots. It is shown that proteins and antibodies can be made to self-assemble on the functional patterns in a microarray format, with the PEG coating acting as an effective passivating agent to prevent non-specific protein adsorption. Various standard surface chemistries such as aldehyde, epoxy and amine are explored for the functional layer, and it is conclusively demonstrated that only an amine-terminated surface satisfies all the process constraints imposed by the lithography process sequence. The effectiveness of this microarray technology is demonstrated by patterning fluorescent streptavidin and a fluorescent secondary antibody using the well-known and highly specific interaction between biotin and streptavidin. PMID:16457998

  14. Oligonucleotide microarrays in constitutional genetic diagnosis.

    PubMed

    Keren, Boris; Le Caignec, Cedric

    2011-06-01

    Oligonucleotide microarrays such as comparative genomic hybridization arrays and SNP microarrays enable the identification of genomic imbalances - also termed copy-number variants - with increasing resolution. This article will focus on the most significant applications of high-throughput oligonucleotide microarrays, both in genetic diagnosis and research. In genetic diagnosis, the method is becoming a standard tool for investigating patients with unexplained developmental delay/intellectual disability, autism spectrum disorders and/or with multiple congenital anomalies. Oligonucleotide microarray have also been recently applied to the detection of genomic imbalances in prenatal diagnosis either to characterize a chromosomal rearrangement that has previously been identified by standard prenatal karyotyping or to detect a cryptic genomic imbalance in a fetus with ultrasound abnormalities and a normal standard prenatal karyotype. In research, oligonucleotide microarrays have been used for a wide range of applications, such as the identification of new genes responsible for monogenic disorders and the association of a copy-number variant as a predisposing factor to a common disease. Despite its widespread use, the interpretation of results is not always straightforward. We will discuss several unexpected results and ethical issues raised by these new methods.

  15. A Synthetic Kinome Microarray Data Generator

    PubMed Central

    Maleki, Farhad; Kusalik, Anthony

    2015-01-01

    Cellular pathways involve the phosphorylation and dephosphorylation of proteins. Peptide microarrays called kinome arrays facilitate the measurement of the phosphorylation activity of hundreds of proteins in a single experiment. Analyzing the data from kinome microarrays is a multi-step process. Typically, various techniques are possible for a particular step, and it is necessary to compare and evaluate them. Such evaluations require data for which correct analysis results are known. Unfortunately, such kinome data is not readily available in the community. Further, there are no established techniques for creating artificial kinome datasets with known results and with the same characteristics as real kinome datasets. In this paper, a methodology for generating synthetic kinome array data is proposed. The methodology relies on actual intensity measurements from kinome microarray experiments and preserves their subtle characteristics. The utility of the methodology is demonstrated by evaluating methods for eliminating heterogeneous variance in kinome microarray data. Phosphorylation intensities from kinome microarrays often exhibit such heterogeneous variance and its presence can negatively impact downstream statistical techniques that rely on homogeneity of variance. It is shown that using the output from the proposed synthetic data generator, it is possible to critically compare two variance stabilization methods. PMID:27600233

  16. Protein microarrays for parasite antigen discovery.

    PubMed

    Driguez, Patrick; Doolan, Denise L; Molina, Douglas M; Loukas, Alex; Trieu, Angela; Felgner, Phil L; McManus, Donald P

    2015-01-01

    The host serological profile to a parasitic infection, such as schistosomiasis, can be used to define potential vaccine and diagnostic targets. Determining the host antibody response using traditional approaches is hindered by the large number of putative antigens in any parasite proteome. Parasite protein microarrays offer the potential for a high-throughput host antibody screen to simplify this task. In order to construct the array, parasite proteins are selected from available genomic sequence and protein databases using bioinformatic tools. Selected open reading frames are PCR amplified, incorporated into a vector for cell-free protein expression, and printed robotically onto glass slides. The protein microarrays can be probed with antisera from infected/immune animals or humans and the antibody reactivity measured with fluorophore labeled antibodies on a confocal laser microarray scanner to identify potential targets for diagnosis or therapeutic or prophylactic intervention. PMID:25388117

  17. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

    PubMed Central

    Sîrbu, Alina; Crane, Martin; Ruskin, Heather J.

    2015-01-01

    Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  18. Microarray as a First Genetic Test in Global Developmental Delay: A Cost-Effectiveness Analysis

    ERIC Educational Resources Information Center

    Trakadis, Yannis; Shevell, Michael

    2011-01-01

    Aim: Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with…

  19. DNA microarray detection of antimicrobial resistance genes in Detection and Characterization of Antibiotic Resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Detection of antimicrobial resistance genes is essential for research and an important tool for clinical diagnostics. Most techniques used to identify resistance genes can only detect one or a few genes per assay, whereas DNA microarray technology can detect thousands of genes in a single assay. Sev...

  20. Validation and implementation of a method for microarray gene expression profiling of minor B-cell subpopulations in man

    PubMed Central

    2014-01-01

    Background This report describes a method for the generation of global gene expression profiles from low frequent B-cell subsets by using fluorescence-activated cell sorting and RNA amplification. However, some of the differentiating compartments involve a low number of cells and therefore it is important to optimize and validate each step in the procedure. Methods Normal lymphoid tissues from blood, tonsils, thymus and bone marrow were immunophenotyped by the 8-colour Euroflow panel using multiparametric flow cytometry. Subsets of B-cells containing cell numbers ranging from 800 to 33,000 and with frequencies varying between 0.1 and 10 percent were sorted, subjected to mRNA purification, amplified by the NuGEN protocol and finally analysed by the Affymetrix platform. Results Following a step by step strategy, each step in the workflow was validated and the sorting/storage conditions optimized as described in this report. First, an analysis of four cancer cell lines on Affymetrix arrays, using either 100 ng RNA labelled with the Ambion standard protocol or 1 ng RNA amplified and labelled by the NuGEN protocol, revealed a significant correlation of gene expressions (r ≥ 0.9 for all). Comparison of qPCR data in samples with or without amplification for 8 genes showed that a relative difference between six cell lines was preserved (r ≥ 0.9). Second, a comparison of cells sorted into PrepProtect, RNAlater or directly into lysis/binding buffer showed a higher yield of purified mRNA following storage in lysis/binding buffer (p < 0.001). Third, the identity of the B-cell subsets validated by the cluster of differentiation (CD) membrane profile was highly concordant with the transcriptional gene expression (p-values <0.001). Finally, in normal bone marrow and tonsil samples, eight evaluated genes were expressed in accordance with the biology of lymphopoiesis (p-values < 0.001), which enabled the generation of a gene-specific B-cell atlas. Conclusion A

  1. Hybridization and Selective Release of DNA Microarrays

    SciTech Connect

    Beer, N R; Baker, B; Piggott, T; Maberry, S; Hara, C M; DeOtte, J; Benett, W; Mukerjee, E; Dzenitis, J; Wheeler, E K

    2011-11-29

    DNA microarrays contain sequence specific probes arrayed in distinct spots numbering from 10,000 to over 1,000,000, depending on the platform. This tremendous degree of multiplexing gives microarrays great potential for environmental background sampling, broad-spectrum clinical monitoring, and continuous biological threat detection. In practice, their use in these applications is not common due to limited information content, long processing times, and high cost. The work focused on characterizing the phenomena of microarray hybridization and selective release that will allow these limitations to be addressed. This will revolutionize the ways that microarrays can be used for LLNL's Global Security missions. The goals of this project were two-fold: automated faster hybridizations and selective release of hybridized features. The first study area involves hybridization kinetics and mass-transfer effects. the standard hybridization protocol uses an overnight incubation to achieve the best possible signal for any sample type, as well as for convenience in manual processing. There is potential to significantly shorten this time based on better understanding and control of the rate-limiting processes and knowledge of the progress of the hybridization. In the hybridization work, a custom microarray flow cell was used to manipulate the chemical and thermal environment of the array and autonomously image the changes over time during hybridization. The second study area is selective release. Microarrays easily generate hybridization patterns and signatures, but there is still an unmet need for methodologies enabling rapid and selective analysis of these patterns and signatures. Detailed analysis of individual spots by subsequent sequencing could potentially yield significant information for rapidly mutating and emerging (or deliberately engineered) pathogens. In the selective release work, optical energy deposition with coherent light quickly provides the thermal energy to

  2. Analysis of High-Throughput ELISA Microarray Data

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Zangar, Richard C.

    2011-02-23

    Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

  3. Pineal Function: Impact of Microarray Analysis

    PubMed Central

    Klein, David C.; Bailey, Michael J.; Carter, David A.; Kim, Jong-so; Shi, Qiong; Ho, Anthony; Chik, Constance; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F.; Møller, Morten; Sugden, David; Rangel, Zoila G.; Munson, Peter J.; Weller, Joan L.; Coon, Steven L.

    2009-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-hour schedule. This effort has highlighted surprising similarity to the retina and has provided reason to explore new avenues of study including intracellular signaling, signal transduction, transcriptional cascades, thyroid/retinoic acid hormone signaling, metal biology, RNA splicing, and the role the pineal gland plays in the immune/inflammation response. The new foundation that microarray analysis has provided will broadly support future research on pineal function. PMID:19622385

  4. The use of microarrays in microbial ecology

    SciTech Connect

    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

  5. MicroRNA expression profiling using microarrays.

    PubMed

    Love, Cassandra; Dave, Sandeep

    2013-01-01

    MicroRNAs are small noncoding RNAs which are able to regulate gene expression at both the transcriptional and translational levels. There is a growing recognition of the role of microRNAs in nearly every tissue type and cellular process. Thus there is an increasing need for accurate quantitation of microRNA expression in a variety of tissues. Microarrays provide a robust method for the examination of microRNA expression. In this chapter, we describe detailed methods for the use of microarrays to measure microRNA expression and discuss methods for the analysis of microRNA expression data. PMID:23666707

  6. SNP microarray-based 24 chromosome aneuploidy screening is significantly more consistent than FISH

    PubMed Central

    Treff, Nathan R.; Levy, Brynn; Su, Jing; Northrop, Lesley E.; Tao, Xin; Scott, Richard T.

    2010-01-01

    Many studies estimate that chromosomal mosaicism within the cleavage-stage human embryo is high. However, comparison of two unique methods of aneuploidy screening of blastomeres within the same embryo has not been conducted and may indicate whether mosaicism has been overestimated due to technical inconsistency rather than the biological phenomena. The present study investigates the prevalence of chromosomal abnormality and mosaicism found with two different single cell aneuploidy screening techniques. Thirteen arrested cleavage-stage embryos were studied. Each was biopsied into individual cells (n = 160). The cells from each embryo were randomized into two groups. Those destined for FISH-based aneuploidy screening (n = 75) were fixed, one cell per slide. Cells for SNP microarray-based aneuploidy screening (n = 85) were put into individual tubes. Microarray was significantly more reliable (96%) than FISH (83%) for providing an interpretable result (P = 0.004). Markedly different results were obtained when comparing microarray and FISH results from individual embryos. Mosaicism was significantly less commonly observed by microarray (31%) than by FISH (100%) (P = 0.0005). Although FISH evaluated fewer chromosomes per cell and fewer cells per embryo, FISH still displayed significantly more unique genetic diagnoses per embryo (3.2 ± 0.2) than microarray (1.3 ± 0.2) (P < 0.0001). This is the first prospective, randomized, blinded and paired comparison between microarray and FISH-based aneuploidy screening. SNP microarray-based 24 chromosome aneuploidy screening provides more complete and consistent results than FISH. These results also suggest that FISH technology may overestimate the contribution of mitotic error to the origin of aneuploidy at the cleavage stage of human embryogenesis. PMID:20484246

  7. ILOOP – a web application for two-channel microarray interwoven loop design

    PubMed Central

    Pirooznia, Mehdi; Gong, Ping; Yang, Jack Y; Yang, Mary Qu; Perkins, Edward J; Deng, Youping

    2008-01-01

    Microarray technology is widely applied to address complex scientific questions. However, there remain fundamental issues on how to design experiments to ensure that the resulting data enables robust statistical analysis. Interwoven loop design has several advantages over other designs. However it suffers in the complexity of design. We have implemented an online web application which allows users to find optimal loop designs for two-color microarray experiments. Given a number of conditions (such as treatments or time points) and replicates, the application will find the best possible design of the experiment and output experimental parameters. It is freely available from . PMID:18831776

  8. Polypyrrole-peptide microarray for biomolecular interaction analysis by SPR imaging

    PubMed Central

    Villiers, Marie-Bernadette; Cortès, Sandra; Brakha, Carine; Marche, Patrice; Roget, André; Livache, Thierry

    2009-01-01

    Nowadays, high-throughput analysis of biological events is a great challenge which could take benefit of the recent development of microarray devices. The great potential of such technology is related to the availability of a chip bearing a large set of probes, stable and easy to obtain, and suitable for ligand binding detection. Here, we described a new method based on polypyrrole chemistry and allowing the covalent immobilization of peptides in a microarray format and on a gold surface compatible with the use of Surface Plasmon Resonance. This technique is then illustrated by the detection and characterization of antibodies induced by hepatitis C virus and present in patients’serums. PMID:19649603

  9. Microarrays: molecular allergology and nanotechnology for personalised medicine (I).

    PubMed

    Lucas, J M

    2010-01-01

    The diagnosis of antibody-mediated allergic disorders is based on the clinical findings and the detection of allergen-specific IgE based on in vitro and in vivo techniques, together with allergen provocation tests. In vitro diagnostic techniques have progressed enormously following the introduction of the advances made in proteomics and nanotechnology--offering tools for the diagnosis and investigation of allergy at molecular level. The most advanced developments are the microarray techniques, which in genomics allowed rapid description of the human genetic code, and which now have been applied to proteomics, broadening the field for research and clinical use. Together with these technological advances, the characterisation of most of the different proteins generating specific IgE and which conform each natural allergen, as well as their purification or genetic engineering-based synthesis, have been crucial elements--offering the possibility of identifying disease-causing allergens at molecular level, establishing a component-resolved diagnosis (CRD), using them to study the natural course of the disease, and applying them to improvements in specific immunotherapy. Microarrays of allergic components offer results relating to hundreds of these allergenic components in a single test, and use a small amount of serum that can be obtained from capillary blood. The availability of new molecules will allow the development of panels including new allergenic components and sources, which will require evaluation for clinical use. The present study reviews these new developments, component-resolved diagnosis, and the development of microarray techniques as a critical element for furthering our knowledge of allergic disease.

  10. A DNA microarray-based assay to detect dual infection with two dengue virus serotypes.

    PubMed

    Díaz-Badillo, Alvaro; Muñoz, María de Lourdes; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G; Martínez-Muñoz, Jorge P; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

    2014-01-01

    Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples. PMID:24776933

  11. A DNA Microarray-Based Assay to Detect Dual Infection with Two Dengue Virus Serotypes

    PubMed Central

    Díaz-Badillo, Alvaro; de Lourdes Muñoz, María; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G.; Martínez-Muñoz, Jorge P.; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

    2014-01-01

    Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples. PMID:24776933

  12. A DNA microarray-based assay to detect dual infection with two dengue virus serotypes.

    PubMed

    Díaz-Badillo, Alvaro; Muñoz, María de Lourdes; Perez-Ramirez, Gerardo; Altuzar, Victor; Burgueño, Juan; Mendoza-Alvarez, Julio G; Martínez-Muñoz, Jorge P; Cisneros, Alejandro; Navarrete-Espinosa, Joel; Sanchez-Sinencio, Feliciano

    2014-01-01

    Here; we have described and tested a microarray based-method for the screening of dengue virus (DENV) serotypes. This DNA microarray assay is specific and sensitive and can detect dual infections with two dengue virus serotypes and single-serotype infections. Other methodologies may underestimate samples containing more than one serotype. This technology can be used to discriminate between the four DENV serotypes. Single-stranded DNA targets were covalently attached to glass slides and hybridised with specific labelled probes. DENV isolates and dengue samples were used to evaluate microarray performance. Our results demonstrate that the probes hybridized specifically to DENV serotypes; with no detection of unspecific signals. This finding provides evidence that specific probes can effectively identify single and double infections in DENV samples.

  13. Innovative instrumentation for microarray scanning and analysis: application for characterization of oligonucleotide duplexes behavior.

    PubMed

    Khomyakova, E B; Dreval, E V; Tran-Dang, M; Potier, M C; Soussaline, F P

    2004-05-01

    Accuracy in microarray technology requires new approaches to microarray reader development. A microarray reader system (optical scanning array or OSA reader) based on automated microscopy with large field of view, high speed 3 axis scanning at multiple narrow-band spectra of excitation light has been developed. It allows fast capture of high-resolution, multi-fluorescence images and is characterized by a linear dynamic range and sensitivity comparable to commonly used photo-multiplier tube (PMT)-based laser scanner. Controlled by high performance software, the instrument can be used for scanning and quantitative analysis of any type of dry microarray. Studies implying temperature-controlled hybridization chamber containing a microarray can also be performed. This enables the registration of kinetics and melting curves. This feature is required in a wide range of on-chip chemical and enzymatic reactions including on-chip PCR amplification. We used the OSA reader for the characterization of hybridization and melting behaviour of oligonucleotide:oligonucleotide duplexes on three-dimensional Code Link slides. PMID:15209342

  14. High-quality gene assembly directly from unpurified mixtures of microarray-synthesized oligonucleotides

    PubMed Central

    Borovkov, Alex Y.; Loskutov, Andrey V.; Robida, Mark D.; Day, Kristen M.; Cano, Jose A.; Le Olson, Tien; Patel, Hetal; Brown, Kevin; Hunter, Preston D.; Sykes, Kathryn F.

    2010-01-01

    To meet the growing demand for synthetic genes more robust, scalable and inexpensive gene assembly technologies must be developed. Here, we present a protocol for high-quality gene assembly directly from low-cost marginal-quality microarray-synthesized oligonucleotides. Significantly, we eliminated the time- and money-consuming oligonucleotide purification steps through the use of hybridization-based selection embedded in the assembly process. The protocol was tested on mixtures of up to 2000 oligonucleotides eluted directly from microarrays obtained from three different chip manufacturers. These mixtures containing <5% perfect oligos, and were used directly for assembly of 27 test genes of different sizes. Gene quality was assessed by sequencing, and their activity was tested in coupled in vitro transcription/translation reactions. Genes assembled from the microarray-eluted material using the new protocol matched the quality of the genes assembled from >95% pure column-synthesized oligonucleotides by the standard protocol. Both averaged only 2.7 errors/kb, and genes assembled from microarray-eluted material without clonal selection produced only 30% less protein than sequence-confirmed clones. This report represents the first demonstration of cost-efficient gene assembly from microarray-synthesized oligonucleotides. The overall cost of assembly by this method approaches 5¢ per base, making gene synthesis more affordable than traditional cloning. PMID:20693531

  15. BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE

    PubMed Central

    Rao, Archana N.; Grainger, David W.

    2014-01-01

    Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA’s persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools. PMID:24765522

  16. BIOPHYSICAL PROPERTIES OF NUCLEIC ACIDS AT SURFACES RELEVANT TO MICROARRAY PERFORMANCE.

    PubMed

    Rao, Archana N; Grainger, David W

    2014-04-01

    Both clinical and analytical metrics produced by microarray-based assay technology have recognized problems in reproducibility, reliability and analytical sensitivity. These issues are often attributed to poor understanding and control of nucleic acid behaviors and properties at solid-liquid interfaces. Nucleic acid hybridization, central to DNA and RNA microarray formats, depends on the properties and behaviors of single strand (ss) nucleic acids (e.g., probe oligomeric DNA) bound to surfaces. ssDNA's persistence length, radius of gyration, electrostatics, conformations on different surfaces and under various assay conditions, its chain flexibility and curvature, charging effects in ionic solutions, and fluorescent labeling all influence its physical chemistry and hybridization under assay conditions. Nucleic acid (e.g., both RNA and DNA) target interactions with immobilized ssDNA strands are highly impacted by these biophysical states. Furthermore, the kinetics, thermodynamics, and enthalpic and entropic contributions to DNA hybridization reflect global probe/target structures and interaction dynamics. Here we review several biophysical issues relevant to oligomeric nucleic acid molecular behaviors at surfaces and their influences on duplex formation that influence microarray assay performance. Correlation of biophysical aspects of single and double-stranded nucleic acids with their complexes in bulk solution is common. Such analysis at surfaces is not commonly reported, despite its importance to microarray assays. We seek to provide further insight into nucleic acid-surface challenges facing microarray diagnostic formats that have hindered their clinical adoption and compromise their research quality and value as genomics tools.

  17. Construction and evaluation of a Clostridium thermocellum ATCC 27405 whole-genome oligonucleotide microarray

    SciTech Connect

    Brown, Steven David; Raman, Babu; McKeown, Catherine K; Kale, Shubhangi P; He, Zhili; Mielenz, Jonathan R

    2007-04-01

    Clostridium thermocellum is an anaerobic, thermophilic bacterium that can directly convert cellulosic substrates into ethanol. Microarray technology is a powerful tool to gain insights into cellular processes by examining gene expression under various physiological states. Oligonucleotide microarray probes were designed for 96.7% of the 3163 C. thermocellum ATCC 27405 candidate protein-encoding genes and then a partial-genome microarray containing 70 C. thermocellum specific probes was constructed and evaluated. We detected a signal-to-noise ratio of three with as little as 1.0 ng of genomic DNA and only low signals from negative control probes (nonclostridial DNA), indicating the probes were sensitive and specific. In order to further test the specificity of the array we amplified and hybridized 10 C. thermocellum polymerase chain reaction products that represented different genes and found gene specific hybridization in each case. We also constructed a whole-genome microarray and prepared total cellular RNA from the same point in early-logarithmic growth phase from two technical replicates during cellobiose fermentation. The reliability of the microarray data was assessed by cohybridization of labeled complementary DNA from the cellobiose fermentation samples and the pattern of hybridization revealed a linear correlation. These results taken together suggest that our oligonucleotide probe set can be used for sensitive and specific C. thermocellum transcriptomic studies in the future.

  18. Fully automated analysis of multi-resolution four-channel micro-array genotyping data

    NASA Astrophysics Data System (ADS)

    Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

    2006-03-01

    We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

  19. Protein microarrays for the diagnosis of allergic diseases: state-of-the-art and future development.

    PubMed

    Harwanegg, Christian; Hiller, Reinhard

    2005-01-01

    In the emerging field of Functional Proteomics, protein microarrays are considered to be one of the most promising tools for the simultaneous analysis of the a) abundance, b) function, and c) interaction of proteins on a system-wide scale. Resting on the technological grounds of widely used DNA biochips, the great power of microarray-based miniature solid-phase immunoassays lies in their potential to investigate in parallel large numbers of analyte pairs in a variety of biological samples. Consequently, this has fueled aspirations that protein microarrays may serve as tools for the high-throughput functional investigation of complete proteomes and, moreover, that they will develop into promising candidates for innovative in-vitro diagnostic (IVD) applications. To date, published examples of protein microarrays for IVD purposes have included tests for allergy, autoimmune and infectious diseases. Here, we discuss recent advancements in the development of protein microarrays for the profiling of IgE antibodies in the diagnosis of Type 1-related allergic diseases.

  20. A new method for gridding DNA microarrays.

    PubMed

    Charalambous, Christoforos C; Matsopoulos, George K

    2013-10-01

    In this paper, a new methodological scheme for the gridding of DNA microarrays is proposed. The scheme composes of a series of processes applied sequentially. Each DNA microarray image is pre-processed to remove any noise and the center of each spot is detected using a template matching algorithm. Then, an initial gridding is automatically placed on the DNA microarray image by 'building' rectangular pyramids around the detected spots' centers. The gridlines "move" between the pyramids, horizontally and vertically, forming this initial grid. Furthermore, a refinement process is applied composing of a five-step approach in order to correct gridding imperfections caused by its initial placement, both in non-spot cases and in more than one spot enclosure cases. The proposed gridding scheme is applied on DNA microarray images under known transformations and on real-world DNA data. Its performance is compared against the projection pursuit method, which is often used due to its speed and simplicity, as well as against a state-of-the-art method, the Optimal Multi-level Thresholding Gridding (OMTG). According to the obtained results, the proposed gridding scheme outperforms both methods, qualitatively and quantitatively.

  1. Data Analysis Strategies for Protein Microarrays

    PubMed Central

    Díez, Paula; Dasilva, Noelia; González-González, María; Matarraz, Sergio; Casado-Vela, Juan; Orfao, Alberto; Fuentes, Manuel

    2012-01-01

    Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.

  2. Data Analysis Strategies for Protein Microarrays

    PubMed Central

    Díez, Paula; Dasilva, Noelia; González-González, María; Matarraz, Sergio; Casado-Vela, Juan; Orfao, Alberto; Fuentes, Manuel

    2012-01-01

    Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation. PMID:27605336

  3. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

    Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...

  4. Raman-based microarray readout: a review.

    PubMed

    Haisch, Christoph

    2016-07-01

    For a quarter of a century, microarrays have been part of the routine analytical toolbox. Label-based fluorescence detection is still the commonest optical readout strategy. Since the 1990s, a continuously increasing number of label-based as well as label-free experiments on Raman-based microarray readout concepts have been reported. This review summarizes the possible concepts and methods and their advantages and challenges. A common label-based strategy is based on the binding of selective receptors as well as Raman reporter molecules to plasmonic nanoparticles in a sandwich immunoassay, which results in surface-enhanced Raman scattering signals of the reporter molecule. Alternatively, capture of the analytes can be performed by receptors on a microarray surface. Addition of plasmonic nanoparticles again leads to a surface-enhanced Raman scattering signal, not of a label but directly of the analyte. This approach is mostly proposed for bacteria and cell detection. However, although many promising readout strategies have been discussed in numerous publications, rarely have any of them made the step from proof of concept to a practical application, let alone routine use. Graphical Abstract Possible realization of a SERS (Surface-Enhanced Raman Scattering) system for microarray readout. PMID:26973235

  5. PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

    EPA Science Inventory

    Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

  6. Development of a Novel Peptide Microarray for Large Scale Epitope Mapping of Food Allergens

    PubMed Central

    Lin, Jing; Bardina, Ludmilla; Shreffler, Wayne G.; Andreae, Doerthe A.; Ge, Yongchao; Wang, Julie; Bruni, Francesca M.; Fu, Zhiyan; Han, Youngshin; Sampson, Hugh A.

    2009-01-01

    Background The peptide microarray is a novel assay which facilitates high-throughput screening of peptides with a small quantity of sample. Objective We sought to use overlapping peptides of milk allergenic proteins as a model system to establish a reliable and sensitive peptide microarray-based immunoassay for large scale epitope mapping of food allergens. Methods A milk peptide microarray was developed using commercially synthesized peptides (20-mers, 3 offset) covering the primary sequences of αs1-, αs2-, β-, and κ-caseins, and β-lactoglobulin. Conditions for printing and immunolabeling were optimized using a serum pool of five milk-allergic patients. Reproducibility of the milk peptide microarray was evaluated using replicate arrays immunolabeled with the serum pool, whereas specificity and sensitivity were assessed using serial dilution of the serum pool and a peptide inhibition assay. Results Our results show that epitopes identified by the peptide microarray were mostly consistent with those identified previously by SPOT membrane technology, but with specific binding to a few newly identified epitopes of milk allergens. Data from replicate arrays were reproducible (R≥0.92) regardless of printing lots, immunolabeling and serum pool batches. Using the serially diluted serum pool, we confirmed that IgE antibody binding detected in the array was specific. Peptide inhibition of IgE binding to the same peptide and overlapping peptides further confirmed the specificity of the array. Conclusions A reliable peptide microarray was established for large scale IgE epitope mapping of milk allergens and this robust technology could be applied for epitope mapping of other food allergens. PMID:19577281

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

    PubMed Central

    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

  8. Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts.

    PubMed

    Trost, Brett; Moir, Catherine A; Gillespie, Zoe E; Kusalik, Anthony; Mitchell, Jennifer A; Eskiw, Christopher H

    2015-09-01

    DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibroblasts, we measured changes in transcript abundance as cells transitioned from proliferative growth to quiescence using both DNA microarrays and RNA-seq. The internal reproducibility of the RNA-seq data was greater than that of the microarray data. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarray values were moderate. The two technologies had good agreement when considering probes with the largest (both positive and negative) fold change (FC) values. An independent technique, quantitative reverse-transcription PCR (qRT-PCR), was used to measure the FC of 76 genes between proliferative and quiescent samples, and a higher correlation was observed between the qRT-PCR data and the RNA-seq data than between the qRT-PCR data and the microarray data.

  9. A novel surface modification approach for protein and cell microarrays

    NASA Astrophysics Data System (ADS)

    Kurkuri, Mahaveer D.; Driever, Chantelle; Thissen, Helmut W.; Voelcker, Nicholas H.

    2007-01-01

    Tissue engineering and stem cell technologies have led to a rapidly increasing interest in the control of the behavior of mammalian cells growing on tissue culture substrates. Multifunctional polymer coatings can assist research in this area in many ways, for example, by providing low non-specific protein adsorption properties and reactive functional groups at the surface. The latter can be used for immobilization of specific biological factors that influence cell behavior. In this study, glass slides were coated with copolymers of glycidyl methacrylate (GMA) and poly(ethylene glycol) methacrylate (PEGMA). The coatings were prepared by three different methods based on dip and spin coating as well as polymer grafting procedures. Coatings were characterized by X-ray photoelectron spectroscopy, surface sensitive infrared spectroscopy, ellipsometry and contact angle measurements. A fluorescently labelled protein was deposited onto reactive coatings using a contact microarrayer. Printing of a model protein (fluorescein labeled bovine serum albumin) was performed at different protein concentrations, pH, temperature, humidity and using different micropins. The arraying of proteins was studied with a microarray scanner. Arrays printed at a protein concentration above 50 μg/mL prepared in pH 5 phosphate buffer at 10°C and 65% relative humidity gave the most favourable results in terms of the homogeneity of the printed spots and the fluorescence intensity.

  10. Gene set analyses for interpreting microarray experiments on prokaryotic organisms.

    SciTech Connect

    Tintle, Nathan; Best, Aaron; Dejongh, Matthew; VanBruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C.

    2008-11-05

    Background: Recent advances in microarray technology have brought with them the need for enhanced methods of biologically interpreting gene expression data. Recently, methods like Gene Set Enrichment Analysis (GSEA) and variants of Fisher’s exact test have been proposed which utilize a priori biological information. Typically, these methods are demonstrated with a priori biological information from the Gene Ontology. Results: Alternative gene set definitions are presented based on gene sets inferred from the SEED: open-source software environment for comparative genome annotation and analysis of microbial organisms. Many of these gene sets are then shown to provide consistent expression across a series of experiments involving Salmonella Typhimurium. Implementation of the gene sets in an analysis of microarray data is then presented for the Salmonella Typhimurium data. Conclusions: SEED inferred gene sets can be naturally defined based on subsystems in the SEED. The consistent expression values of these SEED inferred gene sets suggest their utility for statistical analyses of gene expression data based on a priori biological information

  11. Quantum Dots-based Reverse Phase Protein Microarray

    SciTech Connect

    Shingyoji, Masato; Gerion, Daniele; Pinkel, Dan; Gray, Joe W.; Chen, Fanqing

    2005-07-15

    CdSe nanocrystals, also called quantum dots (Qdots) are a novel class of fluorophores, which have a diameter of a few nanometers and possess high quantum yield, tunable emission wavelength and photostability. They are an attractive alternative to conventional fluorescent dyes. Quantum dots can be silanized to be soluble in aqueous solution under biological conditions, and thus be used in bio-detection. In this study, we established a novel Qdot-based technology platform that can perform accurate and reproducible quantification of protein concentration in a crude cell lysate background. Protein lysates have been spiked with a target protein, and a dilution series of the cell lysate with a dynamic range of three orders of magnitude has been used for this proof-of-concept study. The dilution series has been spotted in microarray format, and protein detection has been achieved with a sensitivity that is at least comparable to standard commercial assays, which are based on horseradish peroxidase (HRP) catalyzed diaminobenzidine (DAB) chromogenesis. The data obtained through the Qdot method has shown a close linear correlation between relative fluorescence unit and relative protein concentration. The Qdot results are in almost complete agreement with data we obtained with the well-established HRP-DAB colorimetric array (R{sup 2} = 0.986). This suggests that Qdots can be used for protein quantification in microarray format, using the platform presented here.

  12. Microarray Dot Electrodes Utilizing Dielectrophoresis for Cell Characterization

    PubMed Central

    Yafouz, Bashar; Kadri, Nahrizul Adib; Ibrahim, Fatimah

    2013-01-01

    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. PMID:23857266

  13. Cell-based microarrays: current progress, future prospects.

    PubMed

    Palmer, Ella; Freeman, Tom

    2005-07-01

    Cell-based microarrays were first described by Ziauddin and Sabatini in 2001 as a novel method for performing high-throughput screens of gene function. In this study, expression vectors containing the open reading frame of human genes were printed onto glass microscope slides to form a microarray. Transfection reagents were added pre- or post-spotting, and cells grown over the surface of the array. They demonstrated that cells growing in the immediate vicinity of the expression vectors underwent 'reverse transfection', and that subsequent alterations in cell function could then be detected by secondary assays performed on the array. Subsequent publications have adapted the technique to a variety of applications, and have also shown that the approach works when arrays are fabricated using short interfering RNAs and compounds. The potential of this method for performing analyses of gene function and for identifying novel therapeutic agents has been clearly demonstrated, and current efforts are focused on improving and harnessing this technology for high-throughput screening applications. PMID:16014002

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

    NASA Astrophysics Data System (ADS)

    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.

  15. Molecular Sub-Classification of Renal Epithelial Tumors Using Meta-Analysis of Gene Expression Microarrays

    PubMed Central

    Sanford, Thomas; Chung, Paul H.; Reinish, Ariel; Valera, Vladimir; Srinivasan, Ramaprasad; Linehan, W. Marston; Bratslavsky, Gennady

    2011-01-01

    Purpose To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures. Experimental Design 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. Results 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. Conclusions 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. PMID:21818257

  16. Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas

    PubMed Central

    Turkheimer, Federico E; Roncaroli, Federico; Hennuy, Benoit; Herens, Christian; Nguyen, Minh; Martin, Didier; Evrard, Annick; Bours, Vincent; Boniver, Jacques; Deprez, Manuel

    2006-01-01

    Background Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets. Results We have devised a novel mathematical technique (CHROMOWAVE) based on the Haar wavelet transform and applied it to a dataset obtained with the Affymetrix® HG-U133_Plus_2 array in 27 gliomas. CHROMOWAVE generated multi-chromosomal pattern featuring low expression in chromosomes 1p, 4, 9q, 13, 18, and 19q. This pattern was not only statistically robust but also clinically relevant as it was predictive of favourable outcome. This finding was replicated on a data-set independently acquired by another laboratory. FISH analysis indicated that monosomy 1p and 19q was a frequent feature of tumours displaying the CHROMOWAVE pattern but that allelic loss on chromosomes 4, 9q, 13 and 18 was much less common. Conclusion The ability to detect expression changes of spatially related genes and to map their position on chromosomes makes CHROMOWAVE a valuable screening method for the identification and display of regional gene expression changes of clinical relevance. In this study, FISH data showed that monosomy was frequently associated with diffuse low gene expression on chromosome 1p and 19q but not on chromosomes 4, 9q, 13 and 18. Comparative genomic hybridisation, allelic polymorphism analysis and methylation studies are in progress in order to identify the various mechanisms involved in this multi-chromosomal expression pattern. PMID:17140431

  17. Microarray profiling of secretory-phase endometrium from patients with recurrent miscarriage.

    PubMed

    Othman, Rosfayati; Omar, Mohd Hashim; Shan, Lim Pei; Shafiee, Mohd Nasir; Jamal, Rahman; Mokhtar, Norfilza Mohd

    2012-07-01

    The aim of the present study was to identify differentially expressed genes and their related biological pathways in the secretory phase endometrium from patients with recurrent miscarriage (RM) and fertile subjects. Endometrial samples from RM and fertile patients were analyzed using the Affymetrix GeneChip® ST Array. The bioinformatic analysis using the Partek Genomic Suite revealed 346 genes (175 up-regulated and 171 down-regulated) that were differentially expressed in the endometrium of RM patients compared to the fertile subjects (fold change ≥1.5, p<0.005). Validation step using quantitative real-time polymerase chain reaction (qPCR) confirmed a similar expression pattern of four exemplary genes: one up-regulated gene (fibroblast growth factor 9, FGF9) and three down-regulated genes: integrin β3 (ITGB3), colony stimulating factor 1 (CSF1) and matrix-metalloproteinases 19 (MMP19). The Gene Set Enrichment Analysis (GSEA) and the Pathway Studio software have found 101 signaling pathways (p<0.05) associated with the affected genes including the FGFR3 /signal transducer and activator of transcription (STAT) pathway and the CSF1R/STAT pathway. Cell adhesion, cell differentiation and angiogenesis were among biological processes indicated by this system. In conclusion, microarray technique is a useful tool to study gene expression in the secretory phase-endometrium of RM patients. The differences in endometrial gene expressions between healthy and RM subjects contribute to an increase in our knowledge on molecular mechanisms of RM development and may improve the outcome of pregnancies in high-risk women with RM.

  18. Transformation of metabolism with age and lifestyle in Antarctic seals: a case study of systems biology approach to cross-species microarray experiment

    PubMed Central

    2010-01-01

    Background The metabolic transformation that changes Weddell seal pups born on land into aquatic animals is not only interesting for the study of general biology, but it also provides a model for the acquired and congenital muscle disorders which are associated with oxygen metabolism in skeletal muscle. However, the analysis of gene expression in seals is hampered by the lack of specific microarrays and the very limited annotation of known Weddell seal (Leptonychotes weddellii) genes. Results Muscle samples from newborn, juvenile, and adult Weddell seals were collected during an Antarctic expedition. Extracted RNA was hybridized on Affymetrix Human Expression chips. Preliminary studies showed a detectable signal from at least 7000 probe sets present in all samples and replicates. Relative expression levels for these genes was used for further analysis of the biological pathways implicated in the metabolism transformation which occurs in the transition from newborn, to juvenile, to adult seals. Cytoskeletal remodeling, WNT signaling, FAK signaling, hypoxia-induced HIF1 activation, and insulin regulation were identified as being among the most important biological pathways involved in transformation. Conclusion In spite of certain losses in specificity and sensitivity, the cross-species application of gene expression microarrays is capable of solving challenging puzzles in biology. A Systems Biology approach based on gene interaction patterns can compensate adequately for the lack of species-specific genomics information. PMID:20920245

  19. Heterologous oligonucleotide microarrays for transcriptomics in a non-model species; a proof-of-concept study of drought stress in Musa

    PubMed Central

    Davey, Mark W; Graham, Neil S; Vanholme, Bartel; Swennen, Rony; May, Sean T; Keulemans, Johan

    2009-01-01

    Background 'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip® microarrays to profile the response of the banana (Musa spp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts. Results Following cross-hybridisation of Musa gDNA to the Rice GeneChip® Genome Array, ~33,700 gene-specific probe-sets had a sufficiently high degree of homology to be retained for transcriptomic analyses. In a proof-of-concept approach, pooled RNA representing a single biological replicate of control and drought stressed leaves of the Musa cultivar 'Cachaco' were hybridised to the Affymetrix Rice Genome Array. A total of 2,910 Musa gene homologues with a >2-fold difference in expression levels were subsequently identified. These drought-responsive transcripts included many functional classes associated with plant biotic and abiotic stress responses, as well as a range of regulatory genes known to be involved in coordinating abiotic stress responses. This latter group included members of the ERF, DREB, MYB, bZIP and bHLH transcription factor families. Fifty-two of these drought-sensitive Musa transcripts were homologous to genes underlying QTLs for drought and cold tolerance in rice, including in 2 instances QTLs associated with a single underlying gene. The list of drought-responsive transcripts also included genes identified in publicly-available comparative transcriptomics experiments. Conclusion Our results demonstrate that despite the general paucity of nucleotide sequence data in

  20. Construction and Validation of the Rhodobacter sphaeroides 2.4.1 DNA Microarray: Transcriptome Flexibility at Diverse Growth Modes

    SciTech Connect

    Pappas, Christopher T.; Sram, Jakub; Moskvin, Oleg V.; Ivanov, Pavel S.; Mackenzie, Christopher; Choudhary, Madhusudan; Land, Miriam L; Larimer, Frank W; Kaplan, Samuel; Gomelsky, Mark

    2004-07-01

    A high-density oligonucleotide DNA microarray, a genechip, representing the 4.6-Mb genome of the facultative phototrophic proteobacterium, Rhodobacter sphaeroides 2.4.1, was custom-designed and manufactured by Affymetrix, Santa Clara, Calif. The genechip contains probe sets for 4,292 open reading frames (ORFs), 47 rRNA and tRNA genes, and 394 intergenic regions. The probe set sequences were derived from the genome annotation generated by Oak Ridge National Laboratory after extensive revision, which was based primarily upon codon usage characteristic of this GC-rich bacterium. As a result of the revision, numerous missing ORFs were uncovered, nonexistent ORFs were deleted, and misidentified start codons were corrected. To evaluate R. sphaeroides transcriptome flexibility, expression profiles for three diverse growth modes-aerobic respiration, anaerobic respiration in the dark, and anaerobic photosynthesis-were generated. Expression levels of one-fifth to one-third of the R. sphaeroides ORFs were significantly different in cells under any two growth modes. Pathways involved in energy generation and redox balance maintenance under three growth modes were reconstructed. Expression patterns of genes involved in these pathways mirrored known functional changes, suggesting that massive changes in gene expression are the major means used by R. sphaeroides in adaptation to diverse conditions. Differential expression was observed for genes encoding putative new participants in these pathways (additional photosystem genes, duplicate NADH dehydrogenase, ATP synthases), whose functionality has yet to be investigated. The DNA microarray data correlated well with data derived from quantitative reverse transcription-PCR, as well as with data from the literature, thus validating the R. sphaeroides genechip as a powerful and reliable tool for studying unprecedented metabolic versatility of this bacterium.

  1. DNA Microarray and Signal Transduction Analysis in Pulmonary Artery Smooth Muscle Cells From Heritable and Idiopathic Pulmonary Arterial Hypertension Subjects

    PubMed Central

    Yu, Jun; Wilson, Jamie; Taylor, Linda; Polgar, Peter

    2015-01-01

    Pulmonary arterial hypertension (PAH) is characterized by increased pulmonary vascular smooth muscle contraction and proliferation. Here, we analyze genome-wide mRNA expression in human pulmonary arterial smooth muscle cells (HPASMC) isolated from three control, three hereditary (HPAH), and three idiopathic PAH (IPAH) subjects using the Affymetrix Human Gene ST 1.0 chip. The microarray analysis reveals the expression of 537 genes in HPAH and 1024 genes in IPAH changed compared with control HPASMC. Among those genes, 227 genes show similar directionality of expression in both HPAH and IPAH HPASMC. Ingenuity™ Pathway Analysis (IPA) suggests that many of those genes are involved in cellular growth/proliferation and cell cycle regulation and that signaling pathways such as the mitotic activators, polo-like kinases, ATM signaling are activated under PAH conditions. Furthermore, the analysis demonstrates downregulated mRNA expression of certain vasoactive receptors such as bradykinin receptor B2 (BKB2R). Using real time PCR, we verified the downregulated BKB2R expression in the PAH cells. Bradykinin-stimulated calcium influx is also decreased in PAH PASMC. IPA also identified transcriptional factors such p53 and Rb as downregulated, and FoxM1 and Myc as upregulated in both HPAH and IPAH HPASMC. The decreased level of phospho-p53 in PAH cells was confirmed with a phospho-protein array; and we experimentally show a dysregulated proliferation of both HPAH and IPAH PASMC. Together, the microarray experiments and bioinformatics analysis highlight an aberrant proliferation and cell cycle regulation in HPASMC from PAH subjects. These newly identified pathways may provide new targets for the treatment of both hereditary and idiopathic PAH. PMID:25290246

  2. Microarray Analysis of LTR Retrotransposon Silencing Identifies Hdac1 as a Regulator of Retrotransposon Expression in Mouse Embryonic Stem Cells

    PubMed Central

    Madej, Monika J.; Taggart, Mary; Gautier, Philippe; Garcia-Perez, Jose Luis; Meehan, Richard R.; Adams, Ian R.

    2012-01-01

    Retrotransposons are highly prevalent in mammalian genomes due to their ability to amplify in pluripotent cells or developing germ cells. Host mechanisms that silence retrotransposons in germ cells and pluripotent cells are important for limiting the accumulation of the repetitive elements in the genome during evolution. However, although silencing of selected individual retrotransposons can be relatively well-studied, many mammalian retrotransposons are seldom analysed and their silencing in germ cells, pluripotent cells or somatic cells remains poorly understood. Here we show, and experimentally verify, that cryptic repetitive element probes present in Illumina and Affymetrix gene expression microarray platforms can accurately and sensitively monitor repetitive element expression data. This computational approach to genome-wide retrotransposon expression has allowed us to identify the histone deacetylase Hdac1 as a component of the retrotransposon silencing machinery in mouse embryonic stem cells, and to determine the retrotransposon targets of Hdac1 in these cells. We also identify retrotransposons that are targets of other retrotransposon silencing mechanisms such as DNA methylation, Eset-mediated histone modification, and Ring1B/Eed-containing polycomb repressive complexes in mouse embryonic stem cells. Furthermore, our computational analysis of retrotransposon silencing suggests that multiple silencing mechanisms are independently targeted to retrotransposons in embryonic stem cells, that different genomic copies of the same retrotransposon can be differentially sensitive to these silencing mechanisms, and helps define retrotransposon sequence elements that are targeted by silencing machineries. Thus repeat annotation of gene expression microarray data suggests that a complex interplay between silencing mechanisms represses retrotransposon loci in germ cells and embryonic stem cells. PMID:22570599

  3. Viral diagnosis in Indian livestock using customized microarray chips.

    PubMed

    Yadav, Brijesh S; Pokhriyal, Mayank; Ratta, Barkha; Kumar, Ajay; Saxena, Meeta; Sharma, Bhaskar

    2015-01-01

    Viral diagnosis in Indian livestock using customized microarray chips is gaining momentum in recent years. Hence, it is possible to design customized microarray chip for viruses infecting livestock in India. Customized microarray chips identified Bovine herpes virus-1 (BHV-1), Canine Adeno Virus-1 (CAV-1), and Canine Parvo Virus-2 (CPV-2) in clinical samples. Microarray identified specific probes were further confirmed using RT-PCR in all clinical and known samples. Therefore, the application of microarray chips during viral disease outbreaks in Indian livestock is possible where conventional methods are unsuitable. It should be noted that customized application requires a detailed cost efficiency calculation.

  4. Microarray analysis of cultured human brain aggregates following cortisol exposure: implications for cellular functions relevant to mood disorders.

    PubMed

    Salaria, S; Chana, G; Caldara, F; Feltrin, E; Altieri, M; Faggioni, F; Domenici, E; Merlo-Pich, E; Everall, I P

    2006-09-01

    Increased cortisol levels in humans are often observed in patients suffering from mood disorders. In this study human fetal brain aggregates were exposed to cortisol at 500 nM for 3 weeks, as an in-vitro model of chronic cortisol exposure. Microarray analysis on extracted mRNA using the Affymetrix U133A platform was then performed. Our results demonstrated a significant effect of cortisol on 1648 transcripts; 736 up-regulated and 912 down-regulated genes. The most differentially regulated biological categories were: RNA processing, protein metabolism, and cell growth. Within these categories we observed a down-regulation of fibroblast growth factor 2 (FGF2) (-1.5-fold) and aquaporin4 (AQP4) (-1.7-fold), alongside an up-regulation of fibroblast growth factor 9 (FGF9) (+1.7-fold) and vesicle associated membrane protein2 (VAMP2) (+1.7-fold). FGF2, FGF9, AQP4 and VAMP2 changes were confirmed at the protein level by immunohistochemistry. Alterations in FGF transcripts are in keeping with recent literature demonstrating such effects in patients with mood disorders. PMID:16844382

  5. Profiling Pre-MicroRNA and Mature MicroRNA Expressions Using a Single Microarray and Avoiding Separate Sample Preparation

    PubMed Central

    Gan, Lin; Denecke, Bernd

    2013-01-01

    Mature microRNA is a crucial component in the gene expression regulation network. At the same time, microRNA gene expression and procession is regulated in a precise and collaborated way. Pre-microRNAs mediate products during the microRNA transcription process, they can provide hints of microRNA gene expression regulation or can serve as alternative biomarkers. To date, little effort has been devoted to pre-microRNA expression profiling. In this study, three human and three mouse microRNA profile data sets, based on the Affymetrix miRNA 2.0 array, have been re-analyzed for both mature and pre-microRNA signals as a primary test of parallel mature/pre-microRNA expression profiling on a single platform. The results not only demonstrated a glimpse of pre-microRNA expression in human and mouse, but also the relationship of microRNA expressions between pre- and mature forms. The study also showed a possible application of currently available microRNA microarrays in profiling pre-microRNA expression in a time and cost effective manner.

  6. Routine Chromosomal Microarray Analysis is Necessary in Korean Patients With Unexplained Developmental Delay/Mental Retardation/Autism Spectrum Disorder

    PubMed Central

    Shin, Saeam; Yu, Nae; Choi, Jong Rak; Jeong, Seri

    2015-01-01

    Background All over the world, chromosomal microarray (CMA) is now the first tier diagnostic assay for genetic testing to evaluate developmental delay (DD), mental retardation (MR), and autism spectrum disorder (ASD) with unknown etiology. The average diagnostic yield of the CMA test is known to be about 12.2%, while that of conventional G-banding karyotype is below 3%. This study aimed to assess the usefulness of CMA for the purpose of clinical diagnostic testing in the Korean population. Methods We performed CMA and multiplex ligation-dependent probe amplification (MLPA) tests in 96 patients with normal karyotype and unexplained DD, MR, or ASD. The CMA was conducted with CytoScan 750K array (Affymetrix, USA) with an average resolution of 100 kb. Results Pathogenic copy number variations (CNVs) were detected in 15 patients by CMA and in two patients by MLPA for four known microdeletion syndromes (Prader-Willi/Angelman syndrome, DiGeorge syndrome, Miller-Dieker syndrome and Williams syndrome) designated by National Health Insurance system in Korea. The diagnostic yield was 15.6% and 2.1%, respectively. Thirteen (13.5%) patients (excluding cases with pathogenic CNVs) had variants of uncertain clinical significance. There was one patient with a 17.1-megabase (Mb) region of homozygosity on chromosome 4q. Conclusions Our findings suggest the necessity of CMA as a routine diagnostic test for unexplained DD, MR, and ASD in Korea. PMID:26206688

  7. Pigeons: A Novel GUI Software for Analysing and Parsing High Density Heterologous Oligonucleotide Microarray Probe Level Data

    PubMed Central

    Lai, Hung-Ming; May, Sean T.; Mayes, Sean

    2014-01-01

    Genomic DNA-based probe selection by using high density oligonucleotide arrays has recently been applied to heterologous species (Xspecies). With the advent of this new approach, researchers are able to study the genome and transcriptome of a non-model or an underutilised crop species through current state-of-the-art microarray platforms. However, a software package with a graphical user interface (GUI) to analyse and parse the oligonucleotide probe pair level data is still lacking when an experiment is designed on the basis of this cross species approach. A novel computer program called Pigeons has been developed for customised array data analysis to allow the user to import and analyse Affymetrix GeneChip® probe level data through XSpecies. One can determine empirical boundaries for removing poor probes based on genomic hybridisation of the test species to the Xspecies array, followed by making a species-specific Chip Description File (CDF) file for transcriptomics in the heterologous species, or Pigeons can be used to examine an experimental design to identify potential Single-Feature Polymorphisms (SFPs) at the DNA or RNA level. Pigeons is also focused around visualization and interactive analysis of the datasets. The software with its manual (the current release number version 1.2.1) is freely available at the website of the Nottingham Arabidopsis Stock Centre (NASC).

  8. QA/QC issues to aid regulatory acceptance of microarray gene expression data.

    PubMed

    Fuscoe, James C; Tong, Weida; Shi, Leming

    2007-06-01

    The U.S. Food and Drug Administration is responsible for (1) promoting and protecting public health by assuring the safety and effectiveness of medicines and medical devices and (2) advancing public health by helping to speed innovations that make medicines and foods safer, more effective, and more affordable. The genomics revolution has dramatically increased our knowledge of basic biology but this has not resulted in the expected acceleration of new medical product development. The Agency's Critical Path to New Medical Products stresses that new tools are needed to address this pipeline problem. Microarray technology is one of these promising tools although questions have risen about the reproducibility of measurements. The Microarray Quality Control (MAQC) Project was initiated by FDA scientists to address this issue. This large project, which evaluated reference RNA samples on seven microarray platforms, found good intralaboratory repeatability and interlaboratory reproducibility. In addition, there was high cross-platform consistency. All data are available free of cost and the reference RNA samples are available for proficiency testing. Thus, current microarray technology appears to provide both reliability and consistency for regulatory submissions. PMID:17567852

  9. Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

    PubMed

    Yu, Hualong; Hong, Shufang; Yang, Xibei; Ni, Jun; Dan, Yuanyuan; Qin, Bin

    2013-01-01

    DNA microarray technology can measure the activities of tens of thousands of genes simultaneously, which provides an efficient way to diagnose cancer at the molecular level. Although this strategy has attracted significant research attention, most studies neglect an important problem, namely, that most DNA microarray datasets are skewed, which causes traditional learning algorithms to produce inaccurate results. Some studies have considered this problem, yet they merely focus on binary-class problem. In this paper, we dealt with multiclass imbalanced classification problem, as encountered in cancer DNA microarray, by using ensemble learning. We utilized one-against-all coding strategy to transform multiclass to multiple binary classes, each of them carrying out feature subspace, which is an evolving version of random subspace that generates multiple diverse training subsets. Next, we introduced one of two different correction technologies, namely, decision threshold adjustment or random undersampling, into each training subset to alleviate the damage of class imbalance. Specifically, support vector machine was used as base classifier, and a novel voting rule called counter voting was presented for making a final decision. Experimental results on eight skewed multiclass cancer microarray datasets indicate that unlike many traditional classification approaches, our methods are insensitive to class imbalance. PMID:24078908

  10. Microarray Analysis of Port Wine Stains Before and After Pulsed Dye Laser Treatment

    PubMed Central

    Laquer, Vivian T.; Hevezi, Peter A.; Albrecht, Huguette; Chen, Tina S.; Zlotnik, Albert; Kelly, Kristen M.

    2014-01-01

    Background and Objectives Neither the pathogenesis of port wine stain (PWS) birthmarks nor tissue effects of pulsed dye laser (PDL) treatment of these lesions is fully understood. There are few published reports utilizing gene expression analysis in human PWS skin. We aim to compare gene expression in PWS before and after PDL, using DNA microarrays that represent most, if not all, human genes to obtain comprehensive molecular profiles of PWS lesions and PDL-associated tissue effects. Materials and Methods Five human subjects had PDL treatment of their PWS. One week later, three biopsies were taken from each subject: normal skin (N); untreated PWS (PWS); PWS post-PDL (PWS + PDL). Samples included two lower extremity lesions, two facial lesions, and one facial nodule. High-quality total RNA isolated from skin biopsies was processed and applied to Affymetrix Human gene 1.0ST microarrays for gene expression analysis. We performed a 16 pair-wise comparison identifying either up- or down-regulated genes between N versus PWS and PWS versus PWS + PDL for four of the donor samples. The PWS nodule (nPWS) was analyzed separately. Results There was significant variation in gene expression profiles between individuals. By doing pair-wise comparisons between samples taken from the same donor, we were able to identify genes that may participate in the formation of PWS lesions and PDL tissue effects. Genes associated with immune, epidermal, and lipid metabolism were up-regulated in PWS skin. The nPWS exhibited more profound differences in gene expression than the rest of the samples, with significant differential expression of genes associated with angiogenesis, tumorigenesis, and inflammation. Conclusion In summary, gene expression profiles from N, PWS, and PWS + PDL demonstrated significant variation within samples from the same donor and between donors. By doing pair-wise comparisons between samples taken from the same donor and comparing these results between donors, we were

  11. Technology.

    ERIC Educational Resources Information Center

    Callison, Daniel

    2002-01-01

    Discussion of technology focuses on instructional technology. Topics include inquiry and technology; curriculum development; reflection and curriculum evaluation; criteria for technological innovations that will increase student motivation; standards; impact of new technologies on library media centers; software; and future trends. (LRW)

  12. Plasmonically amplified fluorescence bioassay with microarray format

    NASA Astrophysics Data System (ADS)

    Gogalic, S.; Hageneder, S.; Ctortecka, C.; Bauch, M.; Khan, I.; Preininger, Claudia; Sauer, U.; Dostalek, J.

    2015-05-01

    Plasmonic amplification of fluorescence signal in bioassays with microarray detection format is reported. A crossed relief diffraction grating was designed to couple an excitation laser beam to surface plasmons at the wavelength overlapping with the absorption and emission bands of fluorophore Dy647 that was used as a label. The surface of periodically corrugated sensor chip was coated with surface plasmon-supporting gold layer and a thin SU8 polymer film carrying epoxy groups. These groups were employed for the covalent immobilization of capture antibodies at arrays of spots. The plasmonic amplification of fluorescence signal on the developed microarray chip was tested by using interleukin 8 sandwich immunoassay. The readout was performed ex situ after drying the chip by using a commercial scanner with high numerical aperture collecting lens. Obtained results reveal the enhancement of fluorescence signal by a factor of 5 when compared to a regular glass chip.

  13. Microarrays: how many do you need?

    PubMed

    Zien, Alexander; Fluck, Juliane; Zimmer, Ralf; Lengauer, Thomas

    2003-01-01

    We estimate the number of microarrays that is required in order to gain reliable results from a common type of study: the pairwise comparison of different classes of samples. We show that current knowledge allows for the construction of models that look realistic with respect to searches for individual differentially expressed genes and derive prototypical parameters from real data sets. Such models allow investigation of the dependence of the required number of samples on the relevant parameters: the biological variability of the samples within each class, the fold changes in expression that are desired to be detected, the detection sensitivity of the microarrays, and the acceptable error rates of the results. We supply experimentalists with general conclusions as well as a freely accessible Java applet at www.scai.fhg.de/special/bio/howmanyarrays/ for fine tuning simulations to their particular settings. PMID:12935350

  14. Weighted analysis of general microarray experiments

    PubMed Central

    Sjögren, Anders; Kristiansson, Erik; Rudemo, Mats; Nerman, Olle

    2007-01-01

    Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods. PMID:17937807

  15. Undetected sex chromosome aneuploidy by chromosomal microarray.

    PubMed

    Markus-Bustani, Keren; Yaron, Yuval; Goldstein, Myriam; Orr-Urtreger, Avi; Ben-Shachar, Shay

    2012-11-01

    We report on a case of a female fetus found to be mosaic for Turner syndrome (45,X) and trisomy X (47,XXX). Chromosomal microarray analysis (CMA) failed to detect the aneuploidy because of a normal average dosage of the X chromosome. This case represents an unusual instance in which CMA may not detect chromosomal aberrations. Such a possibility should be taken into consideration in similar cases where CMA is used in a clinical setting.

  16. Microarray testing for the presence of toxic algae monitoring programme in Galicia (NW Spain).

    PubMed

    Dittami, Simon M; Pazos, Yolanda; Laspra, Melchor; Medlin, Linda K

    2013-10-01

    Rapid and reliable detection of harmful algae in coastal areas and shellfish farms is an important requirement of monitoring programmes. Monitoring of toxic algae by means of traditional methods, i.e., light microscopy, can be time consuming when many samples have to be routinely analysed. Reliable species identification requires expensive equipment and trained personnel to carry out the analyses. However, all techniques for the monitoring of harmful algae usually require transportation of samples to specialised laboratories. In many monitoring laboratories, results are usually obtained within five working days after receiving the sample and therefore preventative measures are not always possible. Molecular technologies are rapidly improving the detection of phytoplankton and their toxins and the speed at which the results can be obtained. Assays are based on the discrimination of the genetic differences of the different species and species-specific probes can be designed. Such probes have been adapted to a microarray or phylochip format and assessed in several EU monitoring sites. Microarray results are presented for 1 year of field samples validated with cell counts from concentrated samples taken during toxic events from the weekly sampling of the Galician Monitoring Programme done by INTECMAR. The Galician monitoring laboratory does their own counting and their results are posted on their web site within 24 h. There was good correlation between cells present and microarray signals. In the few cases of false negatives, these can be attributed to poor RNA extraction of the target species, viz. Prorocentrum or Dinophysis. Where potential false positives were encountered, the smaller volume taken for cell counts as compared to the upto 300 times more volume taken for RNA extraction for the microarray is likely the cause for these differences, making the microarray more sensitive. The microarray was able to provide better species resolution in Alexandrium and Pseudo

  17. Progress of science from microscopy to microarrays (part 1): diagnosis of parasitic diseases.

    PubMed

    Dey, Ayan; Singh, Sarman

    2009-01-01

    Even though description of the magnifying glass goes back to 1021 by an Arabic physicist in his book, Antony van Leeuwenhoek was the first man to improve the then simple microscope for viewing biological specimens in 1674. This suggests that every discovery has scope for improvement, be it physics or be it biology. In the field of biology, scientists have long studied gene expression as a hallmark of gene activities reflecting the current cell conditions and response to host immune defense systems. These studies have been cumbersome, technically demanding and time-consuming. Application of microarrays has revolutionized this field and help understand the simultaneous expression of thousands of genes in a single sample put onto a single solid support. It is also now possible to compare gene expression in two different cell types, different stages of life cycle or two tissue samples, such as in healthy and diseased ones. Thus microarrays are beginning to dominate other conventional and molecular diagnostic technologies. The microarrays consist of solid supports onto which the nucleic acid sequences from thousands of different genes are immobilized, or attached at fixed locations. These solid supports themselves are usually glass slides, silicon chips or nylon membranes. The nucleic acids are spotted or synthesized directly onto the support. Application of microarrays is new for parasites. Most of these applications are done for monitoring parasite gene expression, to predict the functions of uncharacterized genes, probe the physiologic adaptations made under various environmental conditions, identify virulence-associated genes and test the effects of drug targets. The best examples are vector-borne parasites, such as Plasmodium, Trypanosoma and Leishmania, in which genes expressed, during mammalian and insect host stages, have been elucidated. Microarrays have also been successfully applied to understand the factors responsible to induce transformation from

  18. Microarray testing for the presence of toxic algae monitoring programme in Galicia (NW Spain).

    PubMed

    Dittami, Simon M; Pazos, Yolanda; Laspra, Melchor; Medlin, Linda K

    2013-10-01

    Rapid and reliable detection of harmful algae in coastal areas and shellfish farms is an important requirement of monitoring programmes. Monitoring of toxic algae by means of traditional methods, i.e., light microscopy, can be time consuming when many samples have to be routinely analysed. Reliable species identification requires expensive equipment and trained personnel to carry out the analyses. However, all techniques for the monitoring of harmful algae usually require transportation of samples to specialised laboratories. In many monitoring laboratories, results are usually obtained within five working days after receiving the sample and therefore preventative measures are not always possible. Molecular technologies are rapidly improving the detection of phytoplankton and their toxins and the speed at which the results can be obtained. Assays are based on the discrimination of the genetic differences of the different species and species-specific probes can be designed. Such probes have been adapted to a microarray or phylochip format and assessed in several EU monitoring sites. Microarray results are presented for 1 year of field samples validated with cell counts from concentrated samples taken during toxic events from the weekly sampling of the Galician Monitoring Programme done by INTECMAR. The Galician monitoring laboratory does their own counting and their results are posted on their web site within 24 h. There was good correlation between cells present and microarray signals. In the few cases of false negatives, these can be attributed to poor RNA extraction of the target species, viz. Prorocentrum or Dinophysis. Where potential false positives were encountered, the smaller volume taken for cell counts as compared to the upto 300 times more volume taken for RNA extraction for the microarray is likely the cause for these differences, making the microarray more sensitive. The microarray was able to provide better species resolution in Alexandrium and Pseudo

  19. Comparison of Alexa Fluor and CyDye for practical DNA microarray use.

    PubMed

    Ballard, Joanne L; Peeva, Violet K; deSilva, Christopher J S; Lynch, Jessica L; Swanson, Nigel R

    2007-07-01

    Microarrays are a powerful tool for comparison and understanding of gene expression levels in healthy and diseased states. The method relies upon the assumption that signals from microarray features are a reflection of relative gene expression levels of the cell types under investigation. It has previously been reported that the classical fluorescent dyes used for microarray technology, Cy3 and Cy5, are not ideal due to the decreased stability and fluorescence intensity of the Cy5 dye relative to the Cy3, such that dye bias is an accepted phenomena necessitating dye swap experimental protocols and analysis of differential dye affects. The incentive to find new fluorophores is based on alleviating the problem of dye bias through synonymous performance between counterpart dyes. Alexa Fluor 555 and Alexa Fluor 647 are increasingly promoted as replacements for CyDye in microarray experiments. Performance relates to the molecular and steric similarities, which will vary for each new pair of dyes as well as the spectral integrity for the specific application required. Comparative analysis of the performance of these two competitive dye pairs in practical microarray applications is warranted towards this end. The findings of our study showed that both dye pairs were comparable but that conventional CyDye resulted in significantly higher signal intensities (P < 0.05) and signal minus background levels (P < 0.05) with no significant difference in background values (P > 0.05). This translated to greater levels of differential gene expression with CyDye than with the Alexa Fluor counterparts. However, CyDye fluorophores and in particular Cy5, were found to be less photostable over time and following repeated scans in microarray experiments. These results suggest that precautions against potential dye affects will continue to be necessary and that no one dye pair negates this need.

  20. Repeatability of published microarray gene expression analyses.

    PubMed

    Ioannidis, John P A; Allison, David B; Ball, Catherine A; Coulibaly, Issa; Cui, Xiangqin; Culhane, Aedín C; Falchi, Mario; Furlanello, Cesare; Game, Laurence; Jurman, Giuseppe; Mangion, Jon; Mehta, Tapan; Nitzberg, Michael; Page, Grier P; Petretto, Enrico; van Noort, Vera

    2009-02-01

    Given the complexity of microarray-based gene expression studies, guidelines encourage transparent design and public data availability. Several journals require public data deposition and several public databases exist. However, not all data are publicly available, and even when available, it is unknown whether the published results are reproducible by independent scientists. Here we evaluated the replication of data analyses in 18 articles on microarray-based gene expression profiling published in Nature Genetics in 2005-2006. One table or figure from each article was independently evaluated by two teams of analysts. We reproduced two analyses in principle and six partially or with some discrepancies; ten could not be reproduced. The main reason for failure to reproduce was data unavailability, and discrepancies were mostly due to incomplete data annotation or specification of data processing and analysis. Repeatability of published microarray studies is apparently limited. More strict publication rules enforcing public data availability and explicit description of data processing and analysis should be considered.

  1. High-Throughput Enzyme Kinetics Using Microarrays

    SciTech Connect

    Guoxin Lu; Edward S. Yeung

    2007-11-01

    We report a microanalytical method to study enzyme kinetics. The technique involves immobilizing horseradish peroxidase on a poly-L-lysine (PLL)- coated glass slide in a microarray format, followed by applying substrate solution onto the enzyme microarray. Enzyme molecules are immobilized on the PLL-coated glass slide through electrostatic interactions, and no further modification of the enzyme or glass slide is needed. In situ detection of the products generated on the enzyme spots is made possible by monitoring the light intensity of each spot using a scientific-grade charged-coupled device (CCD). Reactions of substrate solutions of various types and concentrations can be carried out sequentially on one enzyme microarray. To account for the loss of enzyme from washing in between runs, a standard substrate solution is used for calibration. Substantially reduced amounts of substrate solution are consumed for each reaction on each enzyme spot. The Michaelis constant K{sub m} obtained by using this method is comparable to the result for homogeneous solutions. Absorbance detection allows universal monitoring, and no chemical modification of the substrate is needed. High-throughput studies of native enzyme kinetics for multiple enzymes are therefore possible in a simple, rapid, and low-cost manner.

  2. Metadata management and semantics in microarray repositories.

    PubMed

    Kocabaş, F; Can, T; Baykal, N

    2011-12-01

    The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework. PMID:24052712

  3. Chicken sperm transcriptome profiling by microarray analysis.

    PubMed

    Singh, R P; Shafeeque, C M; Sharma, S K; Singh, R; Mohan, J; Sastry, K V H; Saxena, V K; Azeez, P A

    2016-03-01

    It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21,639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.

  4. Exhaustive Search for Fuzzy Gene Networks from Microarray Data

    SciTech Connect

    Sokhansanj, B A; Fitch, J P; Quong, J N; Quong, A A

    2003-07-07

    Recent technological advances in high-throughput data collection allow for the study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are required to interpret large and complex data sets. Rationally designed system perturbations (e.g. gene knock-outs, metabolite removal, etc) can be used to iteratively refine hypothetical models, leading to a modeling-experiment cycle for high-throughput biological system analysis. We use fuzzy logic gene network models because they have greater resolution than Boolean logic models and do not require the precise parameter measurement needed for chemical kinetics-based modeling. The fuzzy gene network approach is tested by exhaustive search for network models describing cyclin gene interactions in yeast cell cycle microarray data, with preliminary success in recovering interactions predicted by previous biological knowledge and other analysis techniques. Our goal is to further develop this method in combination with experiments we are performing on bacterial regulatory networks.

  5. Using Kepler for Tool Integration in Microarray Analysis Workflows

    PubMed Central

    Gan, Zhuohui; Stowe, Jennifer C.; Altintas, Ilkay; McCulloch, Andrew D.; Zambon, Alexander C.

    2015-01-01

    Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines. PMID:26605000

  6. High throughput screening of starch structures using carbohydrate microarrays.

    PubMed

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Motawia, Mohammed Saddik; Shaik, Shahnoor Sultana; Mikkelsen, Maria Dalgaard; Krunic, Susanne Langgaard; Fangel, Jonatan Ulrik; Willats, William George Tycho; Blennow, Andreas

    2016-01-01

    In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated maltooligosaccharides, pure starch samples including a variety of different structures with variations in the amylopectin branching pattern, amylose content and phosphate content, enzymatically modified starches and glycogen were included. Using this technique, different important structures, including amylose content and branching degrees could be differentiated in a high throughput fashion. The screening method was validated using transgenic barley grain analysed during development and subjected to germination. Typically, extreme branching or linearity were detected less than normal starch structures. The method offers the potential for rapidly analysing resistant and slowly digested dietary starches. PMID:27468930

  7. High throughput screening of starch structures using carbohydrate microarrays

    PubMed Central

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Motawia, Mohammed Saddik; Shaik, Shahnoor Sultana; Mikkelsen, Maria Dalgaard; Krunic, Susanne Langgaard; Fangel, Jonatan Ulrik; Willats, William George Tycho; Blennow, Andreas

    2016-01-01

    In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated maltooligosaccharides, pure starch samples including a variety of different structures with variations in the amylopectin branching pattern, amylose content and phosphate content, enzymatically modified starches and glycogen were included. Using this technique, different important structures, including amylose content and branching degrees could be differentiated in a high throughput fashion. The screening method was validated using transgenic barley grain analysed during development and subjected to germination. Typically, extreme branching or linearity were detected less than normal starch structures. The method offers the potential for rapidly analysing resistant and slowly digested dietary starches. PMID:27468930

  8. Visualization of Growth Curve Data from Phenotype MicroarrayExperiments

    SciTech Connect

    Jacobsen, Janet S.; Joyner, Dominique C.; Borglin, Sharon E.; Hazen, Terry C.; Arkin, Adam P.; Bethel, E. Wes

    2007-04-19

    Phenotype microarrays provide a technology to simultaneouslysurvey the response of an organism to nearly 2,000 substrates, includingcarbon, nitrogen and potassium sources; varying pH; varying saltconcentrations; and antibiotics. In order to more quickly and easily viewand compare the large number of growth curves produced by phenotypemicroarray experiments, we have developed software to produce and displaycolor images, each of which corresponds to a set of 96 growth curves.Using color images to represent growth curves data has proven to be avaluable way to assess experiment quality, compare replicates, facilitatecomparison of the responses of different organisms, and identifysignificant phenotypes. The color images are linked to traditional plotsof growth versus time, as well as to information about the experiment,organism, and substrate. In order to share and view information and dataproject-wide, all information, plots, and data are accessible using onlya Web browser.

  9. A review of statistical methods for preprocessing oligonucleotide microarrays.

    PubMed

    Wu, Zhijin

    2009-12-01

    Microarrays have become an indispensable tool in biomedical research. This powerful technology not only makes it possible to quantify a large number of nucleic acid molecules simultaneously, but also produces data with many sources of noise. A number of preprocessing steps are therefore necessary to convert the raw data, usually in the form of hybridisation images, to measures of biological meaning that can be used in further statistical analysis. Preprocessing of oligonucleotide arrays includes image processing, background adjustment, data normalisation/transformation and sometimes summarisation when multiple probes are used to target one genomic unit. In this article, we review the issues encountered in each preprocessing step and introduce the statistical models and methods in preprocessing.

  10. The comparison of different pre- and post-analysis filters for determination of exon-level alternative splicing events using Affymetrix arrays.

    PubMed

    Whistler, Toni; Chiang, Cheng-Feng; Lin, Jin-Mann; Lonergan, William; Reeves, William C

    2010-04-01

    Understanding the biologic significance of alternative splicing has been impeded by the difficulty in systematically identifying and validating transcript isoforms. Current exon array workflows suggest several different filtration steps to reduce the number of tests and increase the detection of alternative splicing events. In this study, we examine the effects of the suggested pre-analysis filtration by detection above background P value or signal intensity. This is followed post-analytically by restriction of exon expression to a fivefold change between groups, limiting the analysis to known alternative splicing events, or using the intersection of the results from different algorithms. Combinations of the filters are also examined. We find that none of the filtering methods reduces the number of technical false-positive calls identified by visual inspection. These include edge effects, nonresponsive probe sets, and inclusion of intronic and untranslated region probe sets into transcript annotations. Modules for filtering the exon microarray data on the basis of annotation features are needed. We propose new approaches to data filtration that would reduce the number of technical false-positives and therefore, impact the time spent performing visual inspection of the exon arrays.

  11. DNA Microarray for Detection of Gastrointestinal Viruses

    PubMed Central

    Martínez, Miguel A.; Soto-del Río, María de los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y.; Greninger, Alexander L.; Contreras, Juan Francisco; López, Susana; Arias, Carlos F.

    2014-01-01

    Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 103 virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

  12. DNA microarray for detection of gastrointestinal viruses.

    PubMed

    Martínez, Miguel A; Soto-Del Río, María de Los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y; Greninger, Alexander L; Contreras, Juan Francisco; López, Susana; Arias, Carlos F; Isa, Pavel

    2015-01-01

    Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 10(3) virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

  13. Ribosomal RNA depletion or exclusion has negligible effect on the detection of viruses in a pan viral microarray.

    PubMed

    McGowan, Sarah; Nunez-Garcia, Javier; Steinbach, Falko; La Rocca, Anna; Blake, Damer; Dastjerdi, Akbar

    2014-10-01

    Pan viral DNA microarrays, which can detect known, novel and multiple viral infections, are major laboratory assets contributing to the control of infectious diseases. The large quantity of ribosomal RNA (rRNA) found in tissue samples is thought to be a major factor contributing to the comparatively lower sensitivity of detecting RNA viruses, as a sequence-independent PCR is used to amplify unknown samples for microarray analysis. This study aimed to determine whether depletion or exclusion of rRNA can improve microarray detection and simplify its analysis. Therefore, two different rRNA depletion and exclusion protocols, RiboMinus™ technology and non-rRNA binding hexanucleotides, were applied to the microarray sample processing and the outcome was compared with those of the sequence-independent amplification protocol. This study concludes that the two procedures, described to deplete or exclude rRNA, have negligible effect on the microarrays detection and analysis and might only in combination with further techniques result in a significant enhancement of sensitivity. Currently, existing protocols of random amplification and background adjustment are pertinent for the purpose of sample processing for microarray analysis.

  14. Monitoring enzyme-catalyzed reactions in micromachined nanoliter wells using a conventional microscope-based microarray reader

    NASA Astrophysics Data System (ADS)

    van den Doel, L. Richard; Moerman, R.; van Dedem, G. W. K.; Young, Ian T.; van Vliet, Lucas J.

    2002-06-01

    Yeast-Saccharomyces cerevisiae - it widely used as a model system for other higher eukaryotes, including man. One of the basic fermentation processes in yeast is the glycolytic pathway, which is the conversion of glucose to ethanol and carbon dioxide. This pathway consists of 12 enzyme-catalyzed reactions. With the approach of microarray technology we want to explore the metabolic regulation of this pathway in yeast. This paper will focus on the design of a conventional microscope based microarray reader, which is used to monitor these enzymatic reactions in microarrays. These microarrays are fabricated in silicon and have sizes of 300 by 300 micrometers 2. The depth varies from 20 to 50 micrometers . Enzyme activity levels can be derived by monitoring the production or consumption rate of NAD(P)H, which is excited at 360nm and emits around 450nm. This fluorophore is involved in all 12 reactions of the pathway. The microarray reader is equipped with a back-illuminated CCD camera in order to obtain a high quantum efficiency for the lower wavelengths. The dynamic range of our microarray reader varies form 5(mu) Molar to 1mMolar NAD(P)H. With this microarray reader enzyme activity levels down to 0.01 unit per milliliter can be monitored. The acquisition time per well is 0.1s. The total scan cycle time for a 5 X 5 microarray is less than half a minute. The number of cycles for a proper estimation of the enzyme activity is inversely proportional to the enzyme activity: long measurement times are needed to determine low enzyme activity levels.

  15. Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity.

    PubMed

    Hsu, Jason C; Chang, Jane; Wang, Tao; Steingrímsson, Eiríkur; Magnússon, Magnús Karl; Bergsteinsdottir, Kristin

    2007-01-01

    Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarray studies in various cancers have reported such gene signatures. However, the overlap of gene signatures in the same disease has been limited so far, and some reported signatures have not been reproduced in other populations. Clearly, the methods used for verifying novel gene signatures need improvement. In this article, we describe an experiment in which microarrays and sample hybridization are designed according to the statistical principles of randomization, replication and blocking. Our results show that such designs provide unbiased estimation of differential expression levels as well as powerful tests for them.

  16. Comments on selected fundamental aspects of microarray analysis.

    PubMed

    Riva, Alessandra; Carpentier, Anne-Sophie; Torrésani, Bruno; Hénaut, Alain

    2005-10-01

    Microarrays are becoming a ubiquitous tool of research in life sciences. However, the working principles of microarray-based methodologies are often misunderstood or apparently ignored by the researchers who actually perform and interpret experiments. This in turn seems to lead to a common over-expectation regarding the explanatory and/or knowledge-generating power of microarray analyses. In this note we intend to explain basic principles of five (5) major groups of analytical techniques used in studies of microarray data and their interpretation: the principal component analysis (PCA), the independent component analysis (ICA), the t-test, the analysis of variance (ANOVA), and self organizing maps (SOM). We discuss answers to selected practical questions related to the analysis of microarray data. We also take a closer look at the experimental setup and the rules, which have to be observed in order to exploit microarrays efficiently. Finally, we discuss in detail the scope and limitations of microarray-based methods. We emphasize the fact that no amount of statistical analysis can compensate for (or replace) a well thought through experimental setup. We conclude that microarrays are indeed useful tools in life sciences but by no means should they be expected to generate complete answers to complex biological questions. We argue that even well posed questions, formulated within a microarray-specific terminology, cannot be completely answered with the use of microarray analyses alone.

  17. An advanced application of protein microarrays: cell-based assays for functional genomics.

    PubMed

    Carbone, Roberta

    2009-01-01

    Microarrays have become common tools for approaching different experimental questions: DNA, protein and peptide arrays offer the power of multiplexing the assay and by means of miniaturization technology, the possibility to reduce cost and amount of samples and reagents. Recently, a novel technology for functional assays has been proposed. Sabatini and co-workers have shown a cell-based microarrays method (1) that relies on the deposition and immobilization of an array of cDNA plasmids on a slide where cells are subsequently plated; the cDNA is then internalized by "reverse transfection" and cells overexpress or downregulate in each single spot the genes of interest. This approach allows the screening of different phenotypes in living cells of many genes in parallel on a single slide. To overcome some relevant limitations of this approach, we have implemented the technology by means of viral immobilization (2) on a novel surface of cluster-assembled nanostructured TiO2 (3) previously functionalized with an array of a docking protein. In this work, we present the detailed development of the "reverse infection cell-microarray based technology" in U2OS cells on a novel coated slide that represents an advanced application of protein arrays.

  18. Development and Assessment of Whole-Genome Oligonucleotide Microarrays to Analyze an Anaerobic Microbial Community and its Responses to Oxidative Stress

    SciTech Connect

    Scholten, Johannes C.; Culley, David E.; Nie, Lei; Munn, Kyle J.; Chow, Lely; Brockman, Fred J.; Zhang, Weiwen

    2007-06-29

    The application of DNA microarray technology to investigate multiple-species microbial community presents great challenges. In this study, we reported the design and quality assessment of four whole genome oligonucleotide microarrays for two syntroph bacteria, Desulfovibrio vulgaris and Syntrophobacter fumaroxidans, and two archaeal methanogens, Methanosarcina barkeri and Methanospirillum hungatei, and their application to analyze global gene expression of this four-species microbial community in response to oxidative stress. In order to minimize the possible cross-hybridization, cross-genome comparison was performed to assure all probes unique to each genome so that the microarrays could provide species-level resolution. Microarray quality was validated by the good reproducibility of experimental measurements of multiple biological and analytical replicates. Microarray analysis showed that S. fumaroxidans and M. hungatei responded to the stress with up-regulation of several genes known to be involved in ROS detoxification, such as catalase and rubrerythrin in S. fumaroxidans and thioredoxin and heat shock protein Hsp20 in M. hungatei. Consistent with previous study in pure culture, the microarray analysis showed that genes involved in methane production and energy metabolism were down-regulated by oxidative stress in M. barkeri. However, D. vulgaris seemed less sensitive to the oxidative stress when grown in a community, with almost no gene up-regulated. The study demonstrated the successful application of microarray technology to multiple-species microbial community, and our preliminary results indicated that the approach can provide novel insights on the metabolic and regulatory networks within microbial communities.

  19. DNA microarray analysis of functionally discrete human brain regions reveals divergent transcriptional profiles

    PubMed Central

    Evans, S.J.; Choudary, P.V.; Vawter, M.P.; Li, J.; Meador-Woodruff, J.H.; Lopez, J.F.; Burke, S.M.; Thompson, R.C.; Myers, R.M.; Jones, E.G.; Bunney, W.E.; Watson, S.J.; Akil, H.

    2010-01-01

    Transcriptional profiles within discrete human brain regions are likely to reflect structural and functional specialization. Using DNA microarray technology, this study investigates differences in transcriptional profiles of highly divergent brain regions (the cerebellar cortex and the cerebral cortex) as well as differences between two closely related brain structures (the anterior cingulate cortex and the dorsolateral prefrontal cortex). Replication of this study across three independent laboratories, to address false-positive and false-negative results using microarray technology, is also discussed. We find greater than a thousand transcripts to be differentially expressed between cerebellum and cerebral cortex and very few transcripts to be differentially expressed between the two neocortical regions. We further characterized transcripts that were found to be specifically expressed within brain regions being compared and found that ontological classes representing signal transduction machinery, neurogenesis, synaptic transmission, and transcription factors were most highly represented. PMID:14572446

  20. Carbohydrate Cluster Microarrays Fabricated on 3-Dimensional Dendrimeric Platforms for Functional Glycomics Exploration

    PubMed Central

    Zhou, Xichun; Turchi, Craig; Wang, Denong

    2009-01-01

    We reported here a novel, ready-to-use bioarray platform and methodology for construction of sensitive carbohydrate cluster microarrays. This technology utilizes a 3-dimensional (3-D) poly(amidoamine) starburst dendrimer monolayer assembled on glass surface, which is functionalized with terminal aminooxy and hydrazide groups for site-specific coupling of carbohydrates. A wide range of saccharides, including monosaccharides, oligosaccharides and polysaccharides of diverse structures, are applicable for the 3-D bioarray platform without prior chemical derivatization. The process of carbohydrate coupling is effectively accelerated by microwave radiation energy. The carbohydrate concentration required for microarray fabrication is substantially reduced using this technology. Importantly, this bioarray platform presents sugar chains in defined orientation and cluster configurations. It is, thus, uniquely useful for exploration of the structural and conformational diversities of glyco-epitope and their functional properties. PMID:19791771

  1. A custom microarray platform for analysis of microRNA gene expression.

    PubMed

    Thomson, J Michael; Parker, Joel; Perou, Charles M; Hammond, Scott M

    2004-10-01

    MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.

  2. Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

    PubMed

    Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

    2005-05-18

    To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

  3. Single-Stranded DNA Catalyzes Hybridization of PCR-Products to Microarray Capture Probes

    PubMed Central

    Dally, Simon; Rupp, Steffen; Lemuth, Karin; Hartmann, Stefan C.; Hiller, Ekkehard; Bailer, Susanne M.; Knabbe, Cornelius; Weile, Jan

    2014-01-01

    Since its development, microarray technology has evolved to a standard method in the biotechnological and medical field with a broad range of applications. Nevertheless, the underlying mechanism of the hybridization process of PCR-products to microarray capture probes is still not completely understood, and several observed phenomena cannot be explained with current models. We investigated the influence of several parameters on the hybridization reaction and identified ssDNA to play a major role in the process. An increase of the ssDNA content in a hybridization reaction strongly enhanced resulting signal intensities. A strong influence could also be observed when unlabeled ssDNA was added to the hybridization reaction. A reduction of the ssDNA content resulted in a massive decrease of the hybridization efficiency. According to these data, we developed a novel model for the hybridization mechanism. This model is based on the assumption that single stranded DNA is necessary as catalyst to induce the hybridization of dsDNA. The developed hybridization model is capable of giving explanations for several yet unresolved questions regarding the functionality of microarrays. Our findings not only deepen the understanding of the hybridization process, but also have immediate practical use in data interpretation and the development of new microarrays. PMID:25025686

  4. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays

    PubMed Central

    Gerdtsson, Anna S.; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A. K.; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. PMID:27600082

  5. Dye-Doped Silica Nanoparticle Labels/Protein Microarray for Detection of Protein Biomarkers

    SciTech Connect

    Wu, Hong; Huo, Qisheng; Varnum, Susan M.; Liu, Guodong; Wang, Jun; Nie, Zimin; Liu, Jun; Lin, Yuehe

    2008-10-20

    Biomarkers serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Interleukin-6 (IL-6), a biomarker with its important biological and pathological functions, has been studied for decades. Conventional fluorescence immunoassay has been widely used for analysis of biomakers like IL-6. However, single fluorophore labeling shows its limitations of low intensity and poor stability. We report a dye-encapsulated silica nanoparticle as a label, with the advantages of high fluorescence intensity, photostability, and biocompatibility, in conjunction with microarray technology for sensitive immunoassay of IL-6 on a microarray format. The tris (2,2’-bipyridyl)ruthenium (II)chloride hexahydrate (Rubpy) dye incorporated into silica nanoparticles using a simple one-step microemulsion synthesis step. The nanoparticles are uniform in size with a diameter of 50 nm. The microarray fluorescent immunoassay approach based on dye-doped silica nanoparticle labels has high sensitivity for practical applications with a limit of detection for IL-6 down to 0.1 ng mL-1. The calibration curve is linear over the range from 0.1 ng mL-1 to 10 ng mL-1. Furthermore, results illustrated that the assay is highly specific for IL-6 in the presence of range of cytokines or proteins. The RuDS dye-labeled nanoparticles in connection with protein microarrays show the promise for clinical diagnosis of biomarkers.

  6. Use of Microarrays as a High-Throughput Platform for Label-Free Biosensing.

    PubMed

    Sun, Yung-Shin

    2015-08-01

    In recent years, various label-free biosensing technologies have been developed for studying the real-time kinetics of diverse biomolecular interactions. These biosensors partially take the place of fluorescence-based methods by providing a comparable sensitivity as well as retaining the conformational and functional integrality of biomolecules to be investigated. However, to completely eliminate the need of fluorescence, throughput is the next big consideration. Microarrays provide a high-throughput platform for screening tens of thousands of biomolecular interactions simultaneously, and many compatible fluorescent scanners have been commercially available. The combination of microarrays and label-free biosensors will be of great interest to researchers in related fields. Microarrays are fabricated by spotting, imprinting, or directly synthesizing biomolecules on solid supports such as glasses, silicon wafers, and other functionalized substrates, and they have been applied to detect DNAs, proteins, toxins, and so on in surface plasmon resonance (SPR) imaging systems and oblique-incidence reflectivity difference (OI-RD) microscopes. Current challenges include increasing sensitivity, reducing sampling time, improving surface chemistry, identifying captured molecules, and minimizing reagent consumption. Future research directions are to improve the instruments themselves, modify the microarray surface for more efficient analyte capture, and combine the systems with mass spectrometry and microfluidics. PMID:25812567

  7. Dye-Doped Silica Nanoparticle Labels/Protein Microarray for Detection of Protein Biomarkers

    PubMed Central

    Wu, Hong; Huo, Qisheng; Varnum, Susan; Wang, Jun; Liu, Guodong; Nie, Zimin; Liu, Jun; Lin, Yuehe

    2008-01-01

    We report a dye-encapsulated silica nanoparticle as a label, with the advantages of high fluorescence intensity, photostability, and biocompatibility, in conjunction with microarray technology for sensitive immunoassay of a biomarker, Interleukin-6 (IL-6), on a microarray format. The tris (2,2’-bipyridyl)ruthenium (II)chloride hexahydrate (Rubpy) dye was incorporated into silica nanoparticles using a simple one-step microemulsion synthesis. In this synthesis process, Igepal CA520 was used as the surfactant, therefore, no requirement of cosolvent during the synthesis and the particle size was reduced comparing to the commonly used Triton surfactant system. The nanoparticles are uniform in size with a diameter of 50 nm. The microarray fluorescent immunoassay approach based on dye-doped silica nanoparticle labels has high sensitivity for practical applications with a limit of detection for IL-6 down to 0.1 ng mL−1. The calibration curve is linear over the range from 0.1 ng mL−1 to 10 ng mL−1. Furthermore, results illustrated that the assay is highly specific for IL-6 in the presence of range of cytokines or proteins. The RuDS dye-labeled nanoparticles in connection with protein microarrays show the promise for clinical diagnosis of biomarkers. PMID:18936832

  8. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities

    PubMed Central

    Berger, Michael F.; Philippakis, Anthony A.; Qureshi, Aaron M.; He, Fangxue S.; Estep, Preston W.; Bulyk, Martha L.

    2015-01-01

    Transcription factors (TFs) regulate the expression of genes involved in myriad cellular processes through sequence-specific interactions with DNA. In order to predict DNA regulatory elements and the TFs targeting them with greater accuracy, detailed knowledge of the binding preferences of TFs is needed. Protein binding microarray (PBM) technology permits rapid, high-throughput characterization of the in vitro DNA binding specificities of proteins1. Here, we present a novel, maximally compact, synthetic DNA sequence design that represents all possible DNA sequence variants of a given length k (i.e., all “k-mers”) on a single, universal microarray. We constructed such all k-mer microarrays covering all 10 base pair (bp) binding sites by converting high-density single-stranded oligonucleotide arrays to double-stranded DNA arrays. Using these microarrays, we comprehensively determined the binding specificities over a full range of affinities for five TFs of diverse structural classes from yeast, worm, mouse, and human. Importantly, the unbiased coverage of all k-mers permits an interrogation of binding site preferences, including nucleotide interdependencies, at unprecedented resolution. PMID:16998473

  9. Baculovirus display for discovery of low-affinity extracellular receptor-ligand interactions using protein microarrays.

    PubMed

    Tom, Irene; Estevez, Alberto; Bowman, Krista; Gonzalez, Lino C

    2015-06-15

    When used in conjunction with multivalent protein probes, protein microarrays offer a robust technology for discovery of low-affinity extracellular protein-protein interactions. Probes for receptor-matching screens generally consist of purified extracellular domains fused to affinity tags. Given that approximately two-thirds of extracellular proteins are transmembrane domain-containing proteins, it would be desirable to develop a system to express and display probe receptors in a native-like membrane environment. Toward this end, we evaluated baculovirus display as a platform for generating multivalent probes for protein microarray screens. Virion particles were generated displaying single-transmembrane domain receptors BTLA, CD200, and EFNB2, representing a range of affinities for their interacting partners. Virions directly labeled with Cy5 fluorophore were screened against a microarray containing more than 600 extracellular proteins, and the results were compared with data derived from soluble Fc protein or probe-coated protein A microbeads. An optimized protocol employing a blocking step with a nonrelated probe-expressing control baculovirus allowed identification of the expected interactions with a signal-to-noise ratio similar to or higher than those obtained with the other formats. Our results demonstrate that baculovirus display is suitable for detection of high- and low-affinity extracellular protein-protein interactions on protein microarrays. This platform eliminates the need for protein purification and provides a native-like lipid environment for membrane-associated receptors. PMID:25797350

  10. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays

    PubMed Central

    Gerdtsson, Anna S.; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A. K.; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts.

  11. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays.

    PubMed

    Gerdtsson, Anna S; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A K; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. PMID:27600082

  12. Using DNA Microarrays to Detect Multiple Pathogen Threats in Water.

    SciTech Connect

    Straub, Tim M.; Quinonez-Diaz, Maria D.; Valdez, Catherine O.; Call, Douglas R.; Chandler, Darrell P.

    2004-06-01

    Currently, there is no single method to collect, process, and analyze a water sample for all pathogenic microorganisms of interest. Some of the difficulties in developing a universal method include the physical differences between the major pathogen groups (viruses, bacteria, protozoa), efficiently concentrating large volume water samples to detect low target concentrations of certain pathogen groups, removing co-concentrated inhibitors from the sample, and standardizing a culture-independent endpoint detection method. Integrating the disparate technologies into a single, universal, simple method and detection system would represent a significant advance in public health and microbiological water quality analysis. Recent advances in sample collection, on-line sample processing and purification, and DNA microarray technologies may form the basis of a universal method to detect known and emerging waterborne pathogens. This review discusses some of the challenges in developing a universal pathogen detection method, current technology that may be employed to overcome these challenges, and the remaining needs for developing an integrated pathogen detection and monitoring system for source or finished water.

  13. High-throughput allogeneic antibody detection using protein microarrays.

    PubMed

    Paul, Jed; Sahaf, Bita; Perloff, Spenser; Schoenrock, Kelsi; Wu, Fang; Nakasone, Hideki; Coller, John; Miklos, David

    2016-05-01

    Enzyme-linked immunosorbent assays (ELISAs) have traditionally been used to detect alloantibodies in patient plasma samples post hematopoietic cell transplantation (HCT); however, protein microarrays have the potential to be multiplexed, more sensitive, and higher throughput than ELISAs. Here, we describe the development of a novel and sensitive microarray method for detection of allogeneic antibodies against minor histocompatibility antigens encoded on the Y chromosome, called HY antigens. Six microarray surfaces were tested for their ability to bind recombinant protein and peptide HY antigens. Significant allogeneic immune responses were determined in male patients with female donors by considering normal male donor responses as baseline. HY microarray results were also compared with our previous ELISA results. Our overall goal was to maximize antibody detection for both recombinant protein and peptide epitopes. For detection of HY antigens, the Epoxy (Schott) protein microarray surface was both most sensitive and reliable and has become the standard surface in our microarray platform. PMID:26902899

  14. Formation and characterization of DNA microarrays at silicon nitride substrates.

    PubMed

    Manning, Mary; Redmond, Gareth

    2005-01-01

    A versatile method for direct, covalent attachment of DNA microarrays at silicon nitride layers, previously deposited by chemical vapor deposition at silicon wafer substrates, is reported. Each microarray fabrication process step, from silicon nitride substrate deposition, surface cleaning, amino-silanation, and attachment of a homobifunctional cross-linking molecule to covalent immobilization of probe oligonucleotides, is defined, characterized, and optimized to yield consistent probe microarray quality, homogeneity, and probe-target hybridization performance. The developed microarray fabrication methodology provides excellent (high signal-to-background ratio) and reproducible responsivity to target oligonucleotide hybridization with a rugged chemical stability that permits exposure of arrays to stringent pre- and posthybridization wash conditions through many sustained cycles of reuse. Overall, the achieved performance features compare very favorably with those of more mature glass based microarrays. It is proposed that this DNA microarray fabrication strategy has the potential to provide a viable route toward the successful realization of future integrated DNA biochips.

  15. Microarray profiling of gene expression patterns in glomerular cells of astaxanthin-treated diabetic mice: a nutrigenomic approach.

    PubMed

    Naito, Yuji; Uchiyama, Kazuhiko; Mizushima, Katsura; Kuroda, Masaaki; Akagiri, Satomi; Takagi, Tomohisa; Handa, Osamu; Kokura, Satoshi; Yoshida, Norimasa; Ichikawa, Hiroshi; Takahashi, Jiro; Yoshikawa, Toshikazu

    2006-10-01

    We have demonstrated that astaxanthin reduces glomerular oxidative stress as well as inhibits the increase in urinary albumin in diabetic db/db mice. The aim of the present study was to determine the gene expression patterns in the glomerular cells of the diabetic mouse kidney, and to investigate the effects of astaxanthin on the expression of these genes using a high-density DNA microarray. The diet administered to the astaxanthin-supplementation group was prepared by mixing a control powder with astaxanthin at a concentration of 0.02%. Glomerular cells were obtained from the kidneys of mice by laser capture microdissection. Preparation of cRNA and target hybridization were performed according to the Affymetrix GeneChip eukaryotic small sample target labeling assay protocol. The gene expression profile was evaluated by the mouse expression set 430A GeneChip. Array data analysis was carried out using Affymetrix GeneChip operating and Ingenuity Pathway analysis software. Comparison between diabetic db/db and non-diabetic db/m mice revealed that 779 probes (3.1%) were significantly affected, i.e. 550 probes were up-regulated, and 229 probes were down-regulated, both at levels of >/=1.5-fold in the diabetic mice. Ingenuity signal analysis of 550 up-regulated probes revealed the mitochondrial oxidative phosphorylation pathway as the most significantly affected caronical pathway. The affected genes were associated with complexes I, III, and IV located on the mitochondrial inner membrane, and the expression levels of these genes were decreased in mice treated with astaxanthin as compared to the levels in the control mice. In addition, the expression of many genes associated with oxidative stress, collagen synthesis, and transforming growth factor-beta signaling was enhanced in the diabetic mice, and this enhancement was slightly inhibited in the astaxanthin-treated mice. In conclusion, this genome-wide nutrigenomics approach provided insight into genes and putative

  16. SNOMAD (Standardization and NOrmalization of MicroArray Data): web-accessible gene expression data analysis.

    PubMed

    Colantuoni, Carlo; Henry, George; Zeger, Scott; Pevsner, Jonathan

    2002-11-01

    SNOMAD is a collection of algorithms for the normalization and standardization of gene expression datasets derived from diverse biological and technological sources. In addition to conventional transformations and visualization tools, SNOMAD includes two non-linear transformations which correct for bias and variance which are non-uniformly distributed across the range of microarray element signal intensities: (1). Local mean normalization; and (2). Local variance correction (Z-score generation using a locally calculated standard deviation).

  17. ProMAT: protein microarray analysis tool

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Varnum, Susan M.; Anderson, Kevin K.; Bollinger, Nikki; Zangar, Richard C.

    2006-04-04

    Summary: ProMAT is a software tool for statistically analyzing data from ELISA microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code. Availability: ProMAT is available at http://www.pnl.gov/statistics/ProMAT. ProMAT requires Java version 1.5.0 and R version 1.9.1 (or more recent versions) which are distributed with the tool.

  18. Protein Microarrays--Without a Trace

    SciTech Connect

    Camarero, J A

    2007-04-05

    Many experimental approaches in biology and biophysics, as well as applications in diagnosis and drug discovery, require proteins to be immobilized on solid supports. Protein microarrays, for example, provide a high-throughput format to study biomolecular interactions. The technique employed for protein immobilization is a key to the success of these applications. Recent biochemical developments are allowing, for the first time, the selective and traceless immobilization of proteins generated by cell-free systems without the need for purification and/or reconcentration prior to the immobilization step.

  19. Protein Microarrays-Based Strategies for Life Detection in Astrobiology

    NASA Astrophysics Data System (ADS)

    Parro, Víctor; Rivas, Luis A.; Gómez-Elvira, Javier

    2008-03-01

    The detection of organic molecules of unambiguous biological origin is fundamental for the confirmation of present or past life. Planetary exploration requires the development of miniaturized apparatus for in situ life detection. Analytical techniques based on mass spectrometry have been traditionally used in space science. Following the Viking landers, gas chromatography-mass spectrometry (GC-MS) for organic detection has gained general acceptance and has been used successfully in the Cassini-Huygens mission to Titan. Microfluidics allows the development of miniaturized capillary electrophoresis devices for the detection of important molecules for life, like amino acids or nucleobases. Recently, a new approach is gaining acceptance in the space science community: the application of the well-known, highly specific, antibody-antigen affinity interaction for the detection and identification of organics and biochemical compounds. Antibodies can specifically bind a plethora of structurally different compounds of a broad range of molecular sizes, from amino acids level to whole cells. Antibody microarray technology allows us to look for the presence of thousands of different compounds in a single assay and in just one square centimeter. Herein, we discuss several important issues—most of which are common with other instruments dealing with life signature detection in the solar system—that must be addressed in order to use antibody microarrays for life detection and planetary exploration. These issues include (1) preservation of biomarkers, (2) the extraction techniques for biomarkers, (3) terrestrial analogues, (4) the antibody stability under space environments, (5) the selection of unequivocal biomarkers for the antibody production, or (6) the instrument design and implementation.

  20. Protein Microarrays-Based Strategies for Life Detection in Astrobiology

    NASA Astrophysics Data System (ADS)

    Parro, Víctor; Rivas, Luis A.; Gómez-Elvira, Javier

    The detection of organic molecules of unambiguous biological origin is fundamental for the confirmation of present or past life. Planetary exploration requires the development of miniaturized apparatus for in situ life detection. Analytical techniques based on mass spectrometry have been traditionally used in space science. Following the Viking landers, gas chromatography-mass spectrometry (GC-MS) for organic detection has gained general acceptance and has been used successfully in the Cassini-Huygens mission to Titan. Microfluidics allows the development of miniaturized capillary electrophoresis devices for the detection of important molecules for life, like amino acids or nucleobases. Recently, a new approach is gaining acceptance in the space science community: the application of the well-known, highly specific, antibody-antigen affinity interaction for the detection and identification of organics and biochemical compounds. Antibodies can specifically bind a plethora of structurally different compounds of a broad range of molecular sizes, from amino acids level to whole cells. Antibody microarray technology allows us to look for the presence of thousands of different compounds in a single assay and in just one square centimeter. Herein, we discuss several important issues—most of which are common with other instruments dealing with life signature detection in the solar system—that must be addressed in order to use antibody microarrays for life detection and planetary exploration. These issues include (1) preservation of biomarkers, (2) the extraction techniques for biomarkers, (3) terrestrial analogues, (4) the antibody stability under space environments, (5) the selection of unequivocal biomarkers for the antibody production, or (6) the instrument design and implementation.

  1. Low-Density microarray technologies for rapid human norovirus genotyping

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Human noroviruses (HuNoV) are the most common cause of food borne disease and viruses are likely responsible for a large proportion of foodborne diseases of unknown etiology. Recent advancements in molecular biology, bioinformatics, epidemiology, and risk analysis have aided the study of these agent...

  2. COMPARISON OF COMPARATIVE GENOMIC HYBRIDIZATIONS TECHNOLOGIES ACROSS MICROARRAY PLATFORMS

    EPA Science Inventory

    Comparative Genomic Hybridization (CGH) measures DNA copy number differences between a reference genome and a test genome. The DNA samples are differentially labeled and hybridized to an immobilized substrate. In early CGH experiments, the DNA targets were hybridized to metaphase...

  3. Refractive index change detection based on porous silicon microarray

    NASA Astrophysics Data System (ADS)

    Chen, Weirong; Jia, Zhenhong; Li, Peng; Lv, Guodong; Lv, Xiaoyi

    2016-05-01

    By combining photolithography with the electrochemical anodization method, a microarray device of porous silicon (PS) photonic crystal was fabricated on the crystalline silicon substrate. The optical properties of the microarray were analyzed with the transfer matrix method. The relationship between refractive index and reflectivity of each array element of the microarray at 633 nm was also studied, and the array surface reflectivity changes were observed through digital imaging. By means of the reflectivity measurement method, reflectivity changes below 10-3 can be observed based on PS microarray. The results of this study can be applied to the detection of biosensor arrays.

  4. Chemiluminescence microarrays in analytical chemistry: a critical review.

    PubMed

    Seidel, Michael; Niessner, Reinhard

    2014-09-01

    Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

  5. Studying cellular processes and detecting disease with protein microarrays

    SciTech Connect

    Zangar, Richard C.; Varnum, Susan M.; Bollinger, Nikki

    2005-10-31

    Protein microarrays are a rapidly developing analytic tool with diverse applications in biomedical research. These applications include profiling of disease markers or autoimmune responses, understanding molecular pathways, protein modifications and protein activities. One factor that is driving this expanding usage is the wide variety of experimental formats that protein microarrays can take. In this review, we provide a short, conceptual overview of the different approaches for protein microarray. We then examine some of the most significant applications of these microarrays to date, with an emphasis on how global protein analyses can be used to facilitate biomedical research.

  6. Segmentation of prostate cancer tissue microarray images

    NASA Astrophysics Data System (ADS)

    Cline, Harvey E.; Can, Ali; Padfield, Dirk

    2006-02-01

    Prostate cancer is diagnosed by histopathology interpretation of hematoxylin and eosin (H and E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade. The morphological features vary with the advance of cancer where the epithelial regions grow into the stroma. An efficient pathology slide image analysis method involved using a tissue microarray with known disease stages. Digital 24-bit RGB images were acquired for each tissue element on the slide with both 10X and 40X objectives. Initial segmentation at low magnification was accomplished using prior spectral characteristics from a training tissue set composed of four tissue clusters; namely, glands, epithelia, stroma and nuclei. The segmentation method was automated by using the training RGB values as an initial guess and iterating the averaging process 10 times to find the four cluster centers. Labels were assigned to the nearest cluster center in red-blue spectral feature space. An automatic threshold algorithm separated the glands from the tissue. A visual pseudo color representation of 60 segmented tissue microarray image was generated where white, pink, red, blue colors represent glands, epithelia, stroma and nuclei, respectively. The higher magnification images provided refined nuclei morphology. The nuclei were detected with a RGB color space principle component analysis that resulted in a grey scale image. The shape metrics such as compactness, elongation, minimum and maximum diameters were calculated based on the eigenvalues of the best-fitting ellipses to the nuclei.

  7. Inferring genetic networks from microarray data.

    SciTech Connect

    May, Elebeoba Eni; Davidson, George S.; Martin, Shawn Bryan; Werner-Washburne, Margaret C.; Faulon, Jean-Loup Michel

    2004-06-01

    In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three major challenges are: (1) inferring the network; (2) estimating the stability of the inferred network; and (3) making the network visually accessible to the user. Here we describe a method, tested on publicly available time series microarray data, which addresses these concerns. The inference of genetic networks from genome-wide experimental data is an important biological problem which has received much attention. Approaches to this problem have typically included application of clustering algorithms [6]; the use of Boolean networks [12, 1, 10]; the use of Bayesian networks [8, 11]; and the use of continuous models [21, 14, 19]. Overviews of the problem and general approaches to network inference can be found in [4, 3]. Our approach to network inference is similar to earlier methods in that we use both clustering and Boolean network inference. However, we have attempted to extend the process to better serve the end-user, the biologist. In particular, we have incorporated a system to assess the reliability of our network, and we have developed tools which allow interactive visualization of the proposed network.

  8. Intensity-based segmentation of microarray images.

    PubMed

    Nagarajan, Radhakrishnan

    2003-07-01

    The underlying principle in microarray image analysis is that the spot intensity is a measure of the gene expression. This implicitly assumes the gene expression of a spot to be governed entirely by the distribution of the pixel intensities. Thus, a segmentation technique based on the distribution of the pixel intensities is appropriate for the current problem. In this paper, clustering-based segmentation is described to extract the target intensity of the spots. The approximate boundaries of the spots in the microarray are determined by manual adjustment of rectilinear grids. The distribution of the pixel intensity in a grid containing a spot is assumed to be the superposition of the foreground and the local background. The k-means clustering technique and the partitioning around medoids (PAM) were used to generate a binary partition of the pixel intensity distribution. The median (k-means) and the medoid (PAM) of the cluster members are chosen as the cluster representatives. The effectiveness of the clustering-based segmentation techniques was tested on publicly available arrays generated in a lipid metabolism experiment (Callow et al., 2000). The results are compared against those obtained using the region-growing approach (SPOT) (Yang et al., 2001). The effect of additive white Gaussian noise is also investigated. PMID:12906242

  9. Microarray analysis of the developing cortex.

    PubMed

    Semeralul, Mawahib O; Boutros, Paul C; Likhodi, Olga; Okey, Allan B; Van Tol, Hubert H M; Wong, Albert H C

    2006-12-01

    Abnormal development of the prefrontal cortex (PFC) is associated with a number of neuropsychiatric disorders that have an onset in childhood or adolescence. Although the basic laminar structure of the PFC is established in utero, extensive remodeling continues into adolescence. To map the overall pattern of changes in cortical gene transcripts during postnatal development, we made serial measurements of mRNA levels in mouse PFC using oligonucleotide microarrays. We observed changes in mRNA transcripts consistent with known postnatal morphological and biochemical events. Overall, most transcripts that changed significantly showed a progressive decrease in abundance after birth, with the majority of change between postnatal weeks 2 and 4. Genes with cell proliferative, cytoskeletal, extracellular matrix, plasma membrane lipid/transport, protein folding, and regulatory functions had decreases in mRNA levels. Quantitative PCR verified the microarray results for six selected genes: DNA methyltransferase 3A (Dnmt3a), procollagen, type III, alpha 1 (Col3a1), solute carrier family 16 (monocarboxylic acid transporters), member 1 (Slc16a1), MARCKS-like 1 (Marcksl1), nidogen 1 (Nid1) and 3-hydroxybutyrate dehydrogenase (heart, mitochondrial) (Bdh).

  10. Laser direct writing of biomolecule microarrays

    NASA Astrophysics Data System (ADS)

    Serra, P.; Fernández-Pradas, J. M.; Berthet, F. X.; Colina, M.; Elvira, J.; Morenza, J. L.

    Protein-based biosensors are highly efficient tools for protein detection and identification. The production of these devices requires the manipulation of tiny amounts of protein solutions in conditions preserving their biological properties. In this work, laser induced forward transfer (LIFT) was used for spotting an array of a purified bacterial antigen in order to check the viability of this technique for the production of protein microarrays. A pulsed Nd:YAG laser beam (355 nm wavelength, 10 ns pulse duration) was used to transfer droplets of a solution containing the Treponema pallidum 17 kDa protein antigen on a glass slide. Optical microscopy showed that a regular array of micrometric droplets could be precisely and uniformly spotted onto a solid substrate. Subsequently, it was proved that LIFT deposition of a T. pallidum 17 kDa antigen onto nylon-coated glass slides preserves its antigenic reactivity and diagnostic properties. These results support that LIFT is suitable for the production of protein microarrays and pave the way for future diagnostics applications.

  11. Label-free detection repeatability of protein microarrays by oblique-incidence reflectivity difference method

    NASA Astrophysics Data System (ADS)

    Dai, Jun; Li, Lin; Wang, JingYi; He, LiPing; Lu, HuiBin; Ruan, KangCheng; Jin, KuiJuan; Yang, GuoZhen

    2012-12-01

    We examine the repeatabilities of oblique-incidence reflectivity difference (OIRD) method for label-free detecting biological molecular interaction using protein microarrays. The experimental results show that the repeatabilities are the same in a given microarray or microarray-microarray and are consistent, indicating that OIRD is a promising label-free detection technique for biological microarrays.

  12. A Chemiluminescent Protein Microarray Method for Determining the Seroglycoid Fucosylation Index.

    PubMed

    Zhang, Aiying; Skog, Sven; Wang, Shengqi; Ke, Yang; Zhang, Yonghong; Li, Kang; He, Ellen; Li, Ning

    2016-01-01

    The Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) is widely used to screen for hepatocellular carcinoma (HCC) in Japan and China. We developed a chemiluminescent protein microarray for determining the AFP-L3/AFP index (the ratio of AFP-L3 to total AFP, AFP-L3%) by fixing AFP-specific antibodies and Lens culinaris lectin on aldehyde-coated glass slides. Serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA) to validate the microarray. AFP-L3 was detected using Hotgen Biotech glycosyl capture spin column pretreatment technology and ELISA. When the AFP cut-off value was set to 20 ng/ml, the protein microarray displayed 89.74% sensitivity and 100% specificity for HCC diagnosis, and the ELISA displayed 87.17% sensitivity and 100% specificity. When the AFP-L3% cut-off value was set to 0.1, the protein microarray displayed 56.41% sensitivity and 100% specificity for HCC diagnosis, and the ELISA displayed 53.84% sensitivity and 100% specificity. The ROC curve for the HCC diagnosis showed that the AFP area under the ROC curve (AUC = 0.996; 95% CI: 0.986-1.005) was much higher than that of AFP-L3 (AUC = 0.857; 95% CI: 0.769-0.94) and AFP-L3% (AUC = 0.827; CI: 0.730-0.924). The microarray assay used in this study is a highly sensitive, accurate, and efficient assay for the determination of the AFP-L3%. PMID:27528397

  13. DNA methylation analysis using CpG microarrays is impaired in benzopyrene exposed cells

    SciTech Connect

    Sadikovic, Bekim; Andrews, Joseph; Rodenhiser, David I.

    2007-12-15

    Epigenetic alterations have emerged as a key mechanism involved in tumorigenesis. These disruptions are partly due to environmental factors that change normal DNA methylation patterns necessary for transcriptional regulation and chromatin compaction. Microarray technologies are allowing environmentally susceptible epigenetic patterns to be mapped and the precise targets of environmentally induced alterations to be identified. Previously, we observed BaP-induced epigenetic events and cell cycle disruptions in breast cancer cell lines that included time- and concentration-dependent loss of proliferation as well as sequence-specific hypo- and hypermethylation events. In this present report, we further characterized epigenetic changes in BaP-exposed MCF-7 cells. We analyzed DNA methylation on a CpG island microarray platform with over 5400 unique genomic regions. Depleted and enriched microarray targets, representative of putative DNA methylation changes, were identified across the genome; however, subsequent sodium bisulfite analyses revealed no changes in DNA methylation at a number of these loci. Instead, we found that the identification of DNA methylation changes using this restriction enzyme-based microarray approach corresponded with the regions of DNA bound by the BaP derived DNA adducts. This DNA adduct formation occurs at both methylated and unmethylated CpG dinucleotides and affects PCR amplification during sample preparation. Our data suggest that caution should be exercised when interpreting data from comparative microarray experiments that rely on enzymatic reactions. These results are relevant to genome screening approaches involving environmental exposures in which DNA adduct formation at specific nucleotide sites may bias target acquisition and compromise the correct identification of epigenetically responsive genes.

  14. A Chemiluminescent Protein Microarray Method for Determining the Seroglycoid Fucosylation Index

    PubMed Central

    Zhang, Aiying; Skog, Sven; Wang, Shengqi; Ke, Yang; Zhang, Yonghong; Li, Kang; He, Ellen; Li, Ning

    2016-01-01

    The Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3) is widely used to screen for hepatocellular carcinoma (HCC) in Japan and China. We developed a chemiluminescent protein microarray for determining the AFP-L3/AFP index (the ratio of AFP-L3 to total AFP, AFP-L3%) by fixing AFP-specific antibodies and Lens culinaris lectin on aldehyde-coated glass slides. Serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA) to validate the microarray. AFP-L3 was detected using Hotgen Biotech glycosyl capture spin column pretreatment technology and ELISA. When the AFP cut-off value was set to 20 ng/ml, the protein microarray displayed 89.74% sensitivity and 100% specificity for HCC diagnosis, and the ELISA displayed 87.17% sensitivity and 100% specificity. When the AFP-L3% cut-off value was set to 0.1, the protein microarray displayed 56.41% sensitivity and 100% specificity for HCC diagnosis, and the ELISA displayed 53.84% sensitivity and 100% specificity. The ROC curve for the HCC diagnosis showed that the AFP area under the ROC curve (AUC = 0.996; 95% CI: 0.986–1.005) was much higher than that of AFP-L3 (AUC = 0.857; 95% CI: 0.769–0.94) and AFP-L3% (AUC = 0.827; CI: 0.730–0.924). The microarray assay used in this study is a highly sensitive, accurate, and efficient assay for the determination of the AFP-L3%. PMID:27528397

  15. Interpretation of microarray data: trudging out of the abyss towards elucidation of biological significance.

    PubMed

    Smith, G W; Rosa, G J M

    2007-03-01

    The recent development of tools for expression profiling in livestock has availed reproductive biologists of new opportunities to examine global changes in gene expression during key developmental events, in response to hormonal or other treatments, and as a tool for phenotyping or predicting developmental potential. Such experiments often yield lists of tens to thousands of modulated genes, transcripts of interest, or both. Some argue that such technological advances signal a move from hypothesis-driven research to descriptive discovery research, resulting in information overload at the expense of biological significance. One can easily spend hours staring into the abyss, wondering if the results are real and what they mean. However, microarrays can be more than a high throughput and expensive screening tool. Many factors contribute to the success of expression profiling experiments and the yield of interpretable data, including the nature of the hypothesis or objective of the study, the microarray platform, the complexity of the tissue of interest, the experimental design, and the incorporation of the best available strategies for data analysis and interpretation of the biological themes. Although challenging due to the lack of extensive annotation or ontology classification for genes in livestock species, functional categories of coregulated genes and gene pathways can be determined, and hypotheses about common regulatory elements or the functional significance can be formulated. We have applied cDNA microarray technology to studies of follicular growth, oocyte quality, and the periovulatory period in cattle. Lessons learned from such experiments and a review of the available literature form the basis for the strategies described to facilitate successful application of microarray technology to studies of reproductive biology of livestock species.

  16. Effect of data normalization on fuzzy clustering of DNA microarray data

    PubMed Central

    Kim, Seo Young; Lee, Jae Won; Bae, Jong Sung

    2006-01-01

    Background Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. Clustering is an important tool for finding groups of genes with similar expression patterns in microarray data analysis. However, hard clustering methods, which assign each gene exactly to one cluster, are poorly suited to the analysis of microarray datasets because in such datasets the clusters of genes frequently overlap. Results In this study we applied the fuzzy partitional clustering method known as Fuzzy C-Means (FCM) to overcome the limitations of hard clustering. To identify the effect of data normalization, we used three normalization methods, the two common scale and location transformations and Lowess normalization methods, to normalize three microarray datasets and three simulated datasets. First we determined the optimal parameters for FCM clustering. We found that the optimal fuzzification parameter in the FCM analysis of a microarray dataset depended on the normalization method applied to the dataset during preprocessing. We additionally evaluated the effect of normalization of noisy datasets on the results obtained when hard clustering or FCM clustering was applied to those datasets. The effects of normalization were evaluated using both simulated datasets and microarray datasets. A comparative analysis showed that the clustering results depended on the normalization method used and the noisiness of the data. In particular, the selection of the fuzzification parameter value for the FCM method was sensitive to the normalization method used for datasets with large variations across samples. Conclusion Lowess normalization is more robust for clustering of genes from general microarray data than the two common scale and location adjustment methods

  17. Diffractive micro-arrays for active spectroscopy and interconnect applications

    NASA Astrophysics Data System (ADS)

    Castracane, James; Xu, Bai; Gutin, Olga N.; Lavrijsen, Rein; Stollenwerk, Andrew

    2002-06-01

    The use of Micro-Electro-Mechanical Systems (MEMS) technology has opened the door for many applications. In particular, by exploiting the reconfigurability of optical surfaces fabricated with this technology, many sensor, communication and spectroscopic systems can benefit. The controlled re-direction of single or multiple optical input sources can lend itself to high throughput sample analysis or massively parallel optical connectivity. In addition, the change in a MEMS-based optical surface can result in a flexible spectral analysis of incoming radiation. We report on the recent advances in our projects which are focused on the design/simulation, materials processing and integration issues involved with the creation and optimized operation of such diffractive micro-arrays. In this presentation, the state of the art in such devices will be presented which will include the process flow associated with production, structural metrology, optical performance, and parallel switching capabilities of the systems. The use of numerous materials including polysilicon, silicon dioxide and selected polymers as structural layers has enabled the production of devices which can be tailored for specific, performance related applications. Examples to be presented include diffractive surfaces with substantial (1 cm x 1 cm) active areas as well as large arrays with sub-micron feature sizes. Functional integration of the prototype devices include optical interconnects, active spectroscopy and bio/chem diagnostic systems.

  18. Comparison of hepatocellular carcinoma miRNA expression profiling as evaluated by next generation sequencing and microarray.

    PubMed

    Murakami, Yoshiki; Tanahashi, Toshihito; Okada, Rina; Toyoda, Hidenori; Kumada, Takashi; Enomoto, Masaru; Tamori, Akihiro; Kawada, Norifumi; Taguchi, Y-h; Azuma, Takeshi

    2014-01-01

    MicroRNA (miRNA) expression profiling has proven useful in diagnosing and understanding the development and progression of several diseases. Microarray is the standard method for analyzing miRNA expression profiles; however, it has several disadvantages, including its limited detection of miRNAs. In recent years, advances in genome sequencing have led to the development of next-generation sequencing (NGS) technologies, which significantly advance genome sequencing speed and discovery. In this study, we compared the expression profiles obtained by next generation sequencing (NGS) with the profiles created using microarray to assess if NGS could produce a more accurate and complete miRNA profile. Total RNA from 14 hepatocellular carcinoma tumors (HCC) and 6 matched non-tumor control tissues were sequenced with Illumina MiSeq 50-bp single-end reads. Micro RNA expression profiles were estimated using miRDeep2 software. As a comparison, miRNA expression profiles for 11 out of 14 HCCs were also established by microarray (Agilent human microRNA microarray). The average total sequencing exceeded 2.2 million reads per sample and of those reads, approximately 57% mapped to the human genome. The average correlation for miRNA expression between microarray and NGS and subtraction were 0.613 and 0.587, respectively, while miRNA expression between technical replicates was 0.976. The diagnostic accuracy of HCC, p-value, and AUC were 90.0%, 7.22×10(-4), and 0.92, respectively. In summary, NGS created an miRNA expression profile that was reproducible and comparable to that produced by microarray. Moreover, NGS discovered novel miRNAs that were otherwise undetectable by microarray. We believe that miRNA expression profiling by NGS can be a useful diagnostic tool applicable to multiple fields of medicine.

  19. Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray

    PubMed Central

    Linger, Yvonne; Kukhtin, Alexander; Golova, Julia; Perov, Alexander; Qu, Peter; Knickerbocker, Christopher; Cooney, Christopher G.; Chandler, Darrell P.

    2014-01-01

    Simplifying microarray workflow is a necessary first step for creating MDR-TB microarray-based diagnostics that can be routinely used in lower-resource environments. An amplification microarray combines asymmetric PCR amplification, target size selection, target labeling, and microarray hybridization within a single solution and into a single microfluidic chamber. A batch processing method is demonstrated with a 9-plex asymmetric master mix and low-density gel element microarray for genotyping multi-drug resistant Mycobacterium tuberculosis (MDR-TB). The protocol described here can be completed in 6 hr and provide correct genotyping with at least 1,000 cell equivalents of genomic DNA. Incorporating on-chip wash steps is feasible, which will result in an entirely closed amplicon method and system. The extent of multiplexing with an amplification microarray is ultimately constrained by the number of primer pairs that can be combined into a single master mix and still achieve desired sensitivity and specificity performance metrics, rather than the number of probes that are immobilized on the array. Likewise, the total analysis time can be shortened or lengthened depending on the specific intended use, research question, and desired limits of detection. Nevertheless, the general approach significantly streamlines microarray workflow for the end user by reducing the number of manually intensive and time-consuming processing steps, and provides a simplified biochemical and microfluidic path for translating microarray-based diagnostics into routine clinical practice. PMID:24796567

  20. Demonstrating a multi-drug resistant Mycobacterium tuberculosis amplification microarray.

    PubMed

    Linger, Yvonne; Kukhtin, Alexander; Golova, Julia; Perov, Alexander; Qu, Peter; Knickerbocker, Christopher; Cooney, Christopher G; Chandler, Darrell P

    2014-04-25

    Simplifying microarray workflow is a necessary first step for creating MDR-TB microarray-based diagnostics that can be routinely used in lower-resource environments. An amplification microarray combines asymmetric PCR amplification, target size selection, target labeling, and microarray hybridization within a single solution and into a single microfluidic chamber. A batch processing method is demonstrated with a 9-plex asymmetric master mix and low-density gel element microarray for genotyping multi-drug resistant Mycobacterium tuberculosis (MDR-TB). The protocol described here can be completed in 6 hr and provide correct genotyping with at least 1,000 cell equivalents of genomic DNA. Incorporating on-chip wash steps is feasible, which will result in an entirely closed amplicon method and system. The extent of multiplexing with an amplification microarray is ultimately constrained by the number of primer pairs that can be combined into a single master mix and still achieve desired sensitivity and specificity performance metrics, rather than the number of probes that are immobilized on the array. Likewise, the total analysis time can be shortened or lengthened depending on the specific intended use, research question, and desired limits of detection. Nevertheless, the general approach significantly streamlines microarray workflow for the end user by reducing the number of manually intensive and time-consuming processing steps, and provides a simplified biochemical and microfluidic path for translating microarray-based diagnostics into routine clinical practice.

  1. Structured oligonucleotides for target indexing to allow single-vessel PCR amplification and solid support microarray hybridization.

    PubMed

    Girard, Laurie D; Boissinot, Karel; Peytavi, Régis; Boissinot, Maurice; Bergeron, Michel G

    2015-02-01

    The combination of molecular diagnostic technologies is increasingly used to overcome limitations on sensitivity, specificity or multiplexing capabilities, and provide efficient lab-on-chip devices. Two such techniques, PCR amplification and microarray hybridization are used serially to take advantage of the high sensitivity and specificity of the former combined with high multiplexing capacities of the latter. These methods are usually performed in different buffers and reaction chambers. However, these elaborate methods have high complexity and cost related to reagent requirements, liquid storage and the number of reaction chambers to integrate into automated devices. Furthermore, microarray hybridizations have a sequence dependent efficiency not always predictable. In this work, we have developed the concept of a structured oligonucleotide probe which is activated by cleavage from polymerase exonuclease activity. This technology is called SCISSOHR for Structured Cleavage Induced Single-Stranded Oligonucleotide Hybridization Reaction. The SCISSOHR probes enable indexing the target sequence to a tag sequence. The SCISSOHR technology also allows the combination of nucleic acid amplification and microarray hybridization in a single vessel in presence of the PCR buffer only. The SCISSOHR technology uses an amplification probe that is irreversibly modified in presence of the target, releasing a single-stranded DNA tag for microarray hybridization. Each tag is composed of a 3-nucleotide sequence-dependent segment and a unique "target sequence-independent" 14-nucleotide segment allowing for optimal hybridization with minimal cross-hybridization. We evaluated the performance of five (5) PCR buffers to support microarray hybridization, compared to a conventional hybridization buffer. Finally, as a proof of concept, we developed a multiplexed assay for the amplification, detection, and identification of three (3) DNA targets. This new technology will facilitate the design

  2. Technology.

    ERIC Educational Resources Information Center

    Giorgis, Cyndi; Johnson, Nancy J.

    2002-01-01

    Presents annotations of 30 works of children's literature that support the topic of technology and its influences on readers' daily lives. Notes some stories tell about a time when simple tools enabled individuals to accomplish tasks, and others feature visionaries who used technology to create buildings, bridges, roads, and inventions. Considers…

  3. Automated and Multiplexed Soft Lithography for the Production of Low-Density DNA Microarrays.

    PubMed

    Fredonnet, Julie; Foncy, Julie; Cau, Jean-Christophe; Séverac, Childérick; François, Jean Marie; Trévisiol, Emmanuelle

    2016-09-26

    Microarrays are established research tools for genotyping, expression profiling, or molecular diagnostics in which DNA molecules are precisely addressed to the surface of a solid support. This study assesses the fabrication of low-density oligonucleotide arrays using an automated microcontact printing device, the InnoStamp 40(®). This automate allows a multiplexed deposition of oligoprobes on a functionalized surface by the use of a MacroStamp(TM) bearing 64 individual pillars each mounted with 50 circular micropatterns (spots) of 160 µm diameter at 320 µm pitch. Reliability and reuse of the MacroStamp(TM) were shown to be fast and robust by a simple washing step in 96% ethanol. The low-density microarrays printed on either epoxysilane or dendrimer-functionalized slides (DendriSlides) showed excellent hybridization response with complementary sequences at unusual low probe and target concentrations, since the actual probe density immobilized by this technology was at least 10-fold lower than with the conventional mechanical spotting. In addition, we found a comparable hybridization response in terms of fluorescence intensity between spotted and printed oligoarrays with a 1 nM complementary target by using a 50-fold lower probe concentration to produce the oligoarrays by the microcontact printing method. Taken together, our results lend support to the potential development of this multiplexed microcontact printing technology employing soft lithography as an alternative, cost-competitive tool for fabrication of low-density DNA microarrays.

  4. Automated and Multiplexed Soft Lithography for the Production of Low-Density DNA Microarrays.

    PubMed

    Fredonnet, Julie; Foncy, Julie; Cau, Jean-Christophe; Séverac, Childérick; François, Jean Marie; Trévisiol, Emmanuelle

    2016-01-01

    Microarrays are established research tools for genotyping, expression profiling, or molecular diagnostics in which DNA molecules are precisely addressed to the surface of a solid support. This study assesses the fabrication of low-density oligonucleotide arrays using an automated microcontact printing device, the InnoStamp 40(®). This automate allows a multiplexed deposition of oligoprobes on a functionalized surface by the use of a MacroStamp(TM) bearing 64 individual pillars each mounted with 50 circular micropatterns (spots) of 160 µm diameter at 320 µm pitch. Reliability and reuse of the MacroStamp(TM) were shown to be fast and robust by a simple washing step in 96% ethanol. The low-density microarrays printed on either epoxysilane or dendrimer-functionalized slides (DendriSlides) showed excellent hybridization response with complementary sequences at unusual low probe and target concentrations, since the actual probe density immobilized by this technology was at least 10-fold lower than with the conventional mechanical spotting. In addition, we found a comparable hybridization response in terms of fluorescence intensity between spotted and printed oligoarrays with a 1 nM complementary target by using a 50-fold lower probe concentration to produce the oligoarrays by the microcontact printing method. Taken together, our results lend support to the potential development of this multiplexed microcontact printing technology employing soft lithography as an alternative, cost-competitive tool for fabrication of low-density DNA microarrays. PMID:27681742

  5. Selective recognition of DNA from olive leaves and olive oil by PNA and modified-PNA microarrays

    PubMed Central

    Rossi, Stefano; Calabretta, Alessandro; Tedeschi, Tullia; Sforza, Stefano; Arcioni, Sergio; Baldoni, Luciana; Corradini, Roberto; Marchelli, Rosangela

    2012-01-01

    PNA probes for the specific detection of DNA from olive oil samples by microarray technology were developed. The presence of as low as 5% refined hazelnut (Corylus avellana) oil in extra-virgin olive oil (Olea europaea L.) could be detected by using a PNA microarray. A set of two single nucleotide polymorphisms (SNPs) from the Actin gene of Olive was chosen as a model for evaluating the ability of PNA probes for discriminating olive cultivars. Both unmodified and C2-modified PNAs bearing an arginine side-chain were used, the latter showing higher sequence specificity. DNA extracted from leaves of three different cultivars (Ogliarola leccese, Canino and Frantoio) could be easily discriminated using a microarray with unmodified PNA probes, whereas discrimination of DNA from oil samples was more challenging, and could be obtained only by using chiral PNA probes. PMID:22772038

  6. Finding dominant sets in microarray data.

    PubMed

    Fu, Xuping; Teng, Li; Li, Yao; Chen, Wenbin; Mao, Yumin; Shen, I-Fan; Xie, Yi

    2005-01-01

    Clustering allows us to extract groups of genes that are tightly coexpressed from Microarray data. In this paper, a new method DSF_Clust is developed to find dominant sets (clusters). We have preformed DSF_Clust on several gene expression datasets and given the evaluation with some criteria. The results showed that this approach could cluster dominant sets of good quality compared to kmeans method. DSF_Clust deals with three issues that have bedeviled clustering, some dominant sets being statistically determined in a significance level, predefining cluster structure being not required, and the quality of a dominant set being ensured. We have also applied this approach to analyze published data of yeast cell cycle gene expression and found some biologically meaningful gene groups to be dug out. Furthermore, DSF_Clust is a potentially good tool to search for putative regulatory signals.

  7. Digital microarray analysis for digital artifact genomics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

    We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

  8. A New Generation Microarray for the Simultaneous Detection and Identification of Yersinia pestis and Bacillus anthracis in Food

    PubMed Central

    Goji, Noriko; MacMillan, Trevor; Amoako, Kingsley Kwaku

    2012-01-01

    The use of microarrays as a multiple analytic system has generated increased interest and provided a powerful analytical tool for the simultaneous detection of pathogens in a single experiment. A wide array of applications for this technology has been reported. A low density oligonucleotide microarray was generated from the genetic sequences of Y. pestis and B. anthracis and used to fabricate a microarray chip. The new generation chip, consisting of 2,240 spots in 4 quadrants with the capability of stripping/rehybridization, was designated as “Y-PESTIS/B-ANTHRACIS 4x2K Array.” The chip was tested for specificity using DNA from a panel of bacteria that may be potentially present in food. In all, 37 unique Y. pestis-specific and 83 B. anthracis-specific probes were identified. The microarray assay distinguished Y. pestis and B. anthracis from the other bacterial species tested and correctly identified the Y. pestis-specific oligonucleotide probes using DNA extracted from experimentally inoculated milk samples. Using a whole genome amplification method, the assay was able to detect as low as 1 ng genomic DNA as the start sample. The results suggest that oligonucleotide microarray can specifically detect and identify Y. pestis and B. anthracis and may be a potentially useful diagnostic tool for detecting and confirming the organisms in food during a bioterrorism event. PMID:23125935

  9. SAMMD: Staphylococcus aureus Microarray Meta-Database

    PubMed Central

    Nagarajan, Vijayaraj; Elasri, Mohamed O

    2007-01-01

    Background Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD) which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. Description SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL). Conclusion SAMMD is hosted and available at . Currently there are over 9500 entries for regulated genes, from 67 microarray experiments. SAMMD will help staphylococcal scientists to analyze their

  10. Lipid Microarray Biosensor for Biotoxin Detection.

    SciTech Connect

    Singh, Anup K.; Throckmorton, Daniel J.; Moran-Mirabal, Jose C.; Edel, Joshua B.; Meyer, Grant D.; Craighead, Harold G.

    2006-05-01

    We present the use of micron-sized lipid domains, patterned onto planar substrates and within microfluidic channels, to assay the binding of bacterial toxins via total internal reflection fluorescence microscopy (TIRFM). The lipid domains were patterned using a polymer lift-off technique and consisted of ganglioside-populated DSPC:cholesterol supported lipid bilayers (SLBs). Lipid patterns were formed on the substrates by vesicle fusion followed by polymer lift-off, which revealed micron-sized SLBs containing either ganglioside GT1b or GM1. The ganglioside-populated SLB arrays were then exposed to either Cholera toxin subunit B (CTB) or Tetanus toxin fragment C (TTC). Binding was assayed on planar substrates by TIRFM down to 1 nM concentration for CTB and 100 nM for TTC. Apparent binding constants extracted from three different models applied to the binding curves suggest that binding of a protein to a lipid-based receptor is strongly affected by the lipid composition of the SLB and by the substrate on which the bilayer is formed. Patterning of SLBs inside microfluidic channels also allowed the preparation of lipid domains with different compositions on a single device. Arrays within microfluidic channels were used to achieve segregation and selective binding from a binary mixture of the toxin fragments in one device. The binding and segregation within the microfluidic channels was assayed with epifluorescence as proof of concept. We propose that the method used for patterning the lipid microarrays on planar substrates and within microfluidic channels can be easily adapted to proteins or nucleic acids and can be used for biosensor applications and cell stimulation assays under different flow conditions. KEYWORDS. Microarray, ganglioside, polymer lift-off, cholera toxin, tetanus toxin, TIRFM, binding constant.4

  11. Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial) Pathogens.

    PubMed

    Kostić, Tanja; Sessitsch, Angela

    2011-10-14

    Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples.

  12. High-throughput identification of proteins with AMPylation using self-assembled human protein (NAPPA) microarrays

    PubMed Central

    Yu, Xiaobo; LaBaer, Joshua

    2015-01-01

    Summary AMPylation (adenylylation) has been recognized as an important post translational modification employed by pathogens to regulate host cellular proteins and their associated signaling pathways. AMPylation has potential functions in various cellular processes and is widely conserved across both prokaryotes and eukaryotes. However, despite the identification of many AMPylators, relatively few candidate substrates of AMPylation are known. This is changing with the recent development of a robust and reliable method to identify new substrates using protein microarrays, which can significantly expand the list of potential substrates. Here, we describe procedures to detect AMPylated and auto-AMPylated proteins in a sensitive, high throughput, and non-radioactive manner. The approach employs high-density protein microarrays fabricated using NAPPA (Nucleic Acid Programmable Protein Arrays) technology, which enables the highly successful display of fresh recombinant human proteins in situ. The modification of target proteins is determined via copper-catalyzed azide–alkyne cycloaddition. The assay can be accomplished within 11 hours. PMID:25881200

  13. The Peptide Microarray-Based Resonance Light Scattering Assay for Sensitively Detecting Intracellular Kinase Activity.

    PubMed

    Li, Tao; Liu, Xia; Liu, Dianjun; Wang, Zhenxin

    2016-01-01

    The peptide microarray technology is a robust, reliable, and efficient technique for large-scale determination of enzyme activities, and high-throughput profiling of substrate/inhibitor specificities of enzymes. Here, the activities of cyclic adenosine monophosphate (cAMP)-dependent protein kinase A (PKA) in different cell lysates have been detected by a peptide microarray-based resonance light scattering (RLS) assay with gold nanoparticle (GNP) probes. Highly sensitive detection of PKA activity in 0.1 μg total cell proteins of SHG-44 (human glioma cell) cell lysate (corresponding to 200 cells) is achieved by a selected peptide substrate. The experimental results also demonstrate that the RLS assay can be employed to evaluate the chemical regulation of intracellular kinase activity. PMID:26490469

  14. Controlling microarray DNA hybridization efficiency by probe-surface distance and external surface electrostatics

    NASA Astrophysics Data System (ADS)

    Qamhieh, K.; Pettitt, B. Montgomery

    2015-03-01

    DNA microarrays are analytical devices designed to determine the composition of multicomponent solutions of nucleic acids, DNA or RNA. These devices are promising technology for diverse applications, including sensing, diagnostics, and drug/gene delivery. Here, we modify a hybridization adsorption isotherm to study the effects of probe-surface distance and the external electrostatic fields, on the oligonucleotide hybridization in microarray and how these effects are varies depending on surface probe density and target concentration. This study helps in our understanding on-surface hybridization mechanisms, and from it we can observe a significant effect of the probe-surface distance, and the external electrostatic fields, on the hybridization yield. In addition we present a simple new criteria to control the oligonucleotide hybridization efficiency by providing a chart illustrating the effects of all factors on the DNA-hybridization efficiency.

  15. Fluorescent Protein Nanowire-Mediated Protein Microarrays for Multiplexed and Highly Sensitive Pathogen Detection.

    PubMed

    Men, Dong; Zhou, Juan; Li, Wei; Leng, Yan; Chen, Xinwen; Tao, Shengce; Zhang, Xian-En

    2016-07-13

    Protein microarrays are powerful tools for high-throughput and simultaneous detection of different target molecules in complex biological samples. However, the sensitivity of conventional fluorescence-labeling protein detection methods is limited by the availability of signal molecules for binding to the target molecule. Here, we built a multifunctional fluorescent protein nanowire (FNw) by harnessing self-assembly of yeast amyloid protein. The FNw integrated a large number of fluorescent molecules, thereby enhancing the fluorescent signal output in target detection. The FNw was then combined with protein microarray technology to detect proteins derived from two pathogens, including influenza virus (hemagglutinin 1, HA1) and human immunodeficiency virus (p24 and gp120). The resulting detection sensitivity achieved a 100-fold improvement over a commercially available detection reagent. PMID:27315221

  16. Rapid and Facile Microwave-Assisted Surface Chemistry for Functionalized Microarray Slides

    PubMed Central

    Lee, Jeong Heon; Hyun, Hoon; Cross, Conor J.; Henary, Maged; Nasr, Khaled A.; Oketokoun, Rafiou; Choi, Hak Soo; Frangioni, John V.

    2011-01-01

    We describe a rapid and facile method for surface functionalization and ligand patterning of glass slides based on microwave-assisted synthesis and a microarraying robot. Our optimized reaction enables surface modification 42-times faster than conventional techniques and includes a carboxylated self-assembled monolayer, polyethylene glycol linkers of varying length, and stable amide bonds to small molecule, peptide, or protein ligands to be screened for binding to living cells. We also describe customized slide racks that permit functionalization of 100 slides at a time to produce a cost-efficient, highly reproducible batch process. Ligand spots can be positioned on the glass slides precisely using a microarraying robot, and spot size adjusted for any desired application. Using this system, we demonstrate live cell binding to a variety of ligands and optimize PEG linker length. Taken together, the technology we describe should enable high-throughput screening of disease-specific ligands that bind to living cells. PMID:23467787

  17. Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial) Pathogens

    PubMed Central

    Kostić, Tanja; Sessitsch, Angela

    2011-01-01

    Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples.

  18. Harnessing the power of gene microarrays for the study of brain aging and Alzheimer's disease: statistical reliability and functional correlation.

    PubMed

    Blalock, E M; Chen, K-C; Stromberg, A J; Norris, C M; Kadish, I; Kraner, S D; Porter, N M; Landfield, P W

    2005-11-01

    During normal brain aging, numerous alterations develop in the physiology, biochemistry and structure of neurons and glia. Aging changes occur in most brain regions and, in the hippocampus, have been linked to declining cognitive performance in both humans and animals. Age-related changes in hippocampal regions also may be harbingers of more severe decrements to come from neurodegenerative disorders such as Alzheimer's disease (AD). However, unraveling the mechanisms underlying brain aging, AD and impaired function has been difficult because of the complexity of the networks that drive these aging-related changes. Gene microarray technology allows massively parallel analysis of most genes expressed in a tissue, and therefore is an important new research tool that potentially can provide the investigative power needed to address the complexity of brain aging/neurodegenerative processes. However, along with this new analytic power, microarrays bring several major bioinformatics and resource problems that frequently hinder the optimal application of this technology. In particular, microarray analyses generate extremely large and unwieldy data sets and are subject to high false positive and false negative rates. Concerns also have been raised regarding their accuracy and uniformity. Furthermore, microarray analyses can result in long lists of altered genes, most of which may be difficult to evaluate for functional relevance. These and other problems have led to some skepticism regarding the reliability and functional usefulness of microarray data and to a general view that microarray data should be validated by an independent method. Given recent progress, however, we suggest that the major problem for current microarray research is no longer validity of expression measurements, but rather, the reliability of inferences from the data, an issue more appropriately redressed by statistical approaches than by validation with a separate method. If tested using statistically

  19. A Grid-based solution for management and analysis of microarrays in distributed experiments

    PubMed Central

    Porro, Ivan; Torterolo, Livia; Corradi, Luca; Fato, Marco; Papadimitropoulos, Adam; Scaglione, Silvia; Schenone, Andrea; Viti, Federica

    2007-01-01

    Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip® Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of

  20. A microarray analysis of retinal transcripts that are controlled by image contrast in mice

    PubMed Central

    Brand, Christine; Schaeffel, Frank

    2007-01-01

    Purpose The development of myopia is controlled by still largely unknown retinal signals. The aim of this study was to investigate the changes in retinal mRNA expression after different periods of visual deprivation in mice, while controlling for retinal illuminance. Methods Each group consisted of three male C57BL/6 mice. Treatment periods were 30 min, 4 h, and 6+6 h. High spatial frequencies were filtered from the retinal image by frosted diffusers over one eye while the fellow eyes were covered by clear neutral density (ND) filters that exhibited similar light attenuating properties (0.1 log units) as the diffusers. For the final 30 min of the respective treatment period mice were individually placed in a clear Perspex cylinder that was positioned in the center of a rotating (60 degrees) large drum. The inside of the drum was covered with a 0.1 cyc/degree vertical square wave grating. This visual environment was chosen to standardize illuminances and contrasts seen by the mice. Labeled cRNA was prepared and hybridized to Affymetrix GeneChip® Mouse Genome 430 2.0 arrays. Alterations in mRNA expression levels of candidate genes with potential biological relevance were confirmed by semi-quantitative real-time reverse transcription polymerase chain reaction (RT-PCR). Results In all groups, Egr-1 mRNA expression was reduced in diffuser-treated eyes. Furthermore, the degradation of the spatial frequency spectrum also changed the cFos mRNA level, with reduced expression after 4 h of diffuser treatment. Other interesting candidates were Akt2, which was up-regulated after 30 min of deprivation and Mapk8ip3, a neuron specific JNK binding and scaffolding protein that was temporally regulated in the diffuser-treated eyes only. Conclusions The microarray analysis demonstrated a pattern of differential transcriptional changes, even though differences in the retinal images were restricted to spatial features. The candidate genes may provide further insight into the

  1. Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

    PubMed Central

    Pérot, Philippe; Cheynet, Valérie; Decaussin-Petrucci, Myriam; Oriol, Guy; Mugnier, Nathalie; Rodriguez-Lafrasse, Claire; Ruffion, Alain; Mallet, François

    2013-01-01

    The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1

  2. Microarrays for identifying binding sites and probing structure of RNAs

    PubMed Central

    Kierzek, Ryszard; Turner, Douglas H.; Kierzek, Elzbieta

    2015-01-01

    Oligonucleotide microarrays are widely used in various biological studies. In this review, application of oligonucleotide microarrays for identifying binding sites and probing structure of RNAs is described. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for determination of secondary structures of RNAs have also been developed. Those methods, however, do not reveal binding sites for oligonucleotides. In contrast, microarrays directly determine binding sites while also providing structural insights. Microarray mapping can be used over a wide range of experimental conditions, including temperature, pH, various cations at different concentrations and the presence of other molecules. Moreover, it is possible to make universal microarrays suitable for investigations of many different RNAs, and readout of results is rapid. Thus, microarrays are used to provide insight into oligonucleotide sequences potentially able to interfere with biological function. Better understanding of structure–function relationships of RNA can be facilitated by using microarrays to find RNA regions capable to bind oligonucleotides. That information is extremely important to design optimal sequences for antisense oligonucleotides and siRNA because both bind to single-stranded regions of target RNAs. PMID:25505162

  3. The EADGENE Microarray Data Analysis Workshop (Open Access publication)

    PubMed Central

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø; Watson, Michael; Channing, Caroline; Hulsegge, Ina; Pool, Marco H; Buitenhuis, Bart; Hedegaard, Jakob; Hornshøj, Henrik; Jiang, Li; Sørensen, Peter; Marot, Guillemette; Delmas, Céline; Cao, Kim-Anh Lê; San Cristobal, Magali; Baron, Michael D; Malinverni, Roberto; Stella, Alessandra; Brunner, Ronald M; Seyfert, Hans-Martin; Jensen, Kirsty; Mouzaki, Daphne; Waddington, David; Jiménez-Marín, Ángeles; Pérez-Alegre, Mónica; Pérez-Reinado, Eva; Closset, Rodrigue; Detilleux, Johanne C; Dovč, Peter; Lavrič, Miha; Nie, Haisheng; Janss, Luc

    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 from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using 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 in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses. PMID:18053572

  4. Novel microarrays for simultaneous serodiagnosis of multiple antiviral antibodies.

    PubMed

    Sivakumar, Ponnurengam Malliappan; Moritsugu, Nozomi; Obuse, Sei; Isoshima, Takashi; Tashiro, Hideo; Ito, Yoshihiro

    2013-01-01

    We developed an automated diagnostic system for the detection of virus-specific immunoglobulin Gs (IgGs) that was based on a microarray platform. We compared efficacies of our automated system with conventional enzyme immunoassays (EIAs). Viruses were immobilized to microarrays using a radical cross-linking reaction that was induced by photo-irradiation. A new photoreactive polymer containing perfluorophenyl azide (PFPA) and poly(ethylene glycol) methacrylate was prepared and coated on plates. Inactivated measles, rubella, mumps, Varicella-Zoster and recombinant Epstein-Barr viruse antigen were added to coated plates, and irradiated with ultraviolet light to facilitate immobilization. Virus-specific IgGs in healthy human sera were assayed using these prepared microarrays and the results obtained compared with those from conventional EIAs. We observed high correlation (0.79-0.96) in the results between the automated microarray technique and EIAs. The microarray-based assay was more rapid, involved less reagents and sample, and was easier to conduct compared with conventional EIA techniques. The automated microarray system was further improved by introducing reagent storage reservoirs inside the chamber, thereby conserving the use of expensive reagents and antibodies. We considered the microarray format to be suitable for rapid and multiple serological diagnoses of viral diseases that could be developed further for clinical applications. PMID:24367491

  5. Screening of differentially expressed genes in the growth plate of broiler chickens with Tibial Dyschondroplasia by microarray analysis

    PubMed Central

    2013-01-01

    Background Tibial dyschondroplasia (TD) is a common skeletal disorder in broiler chickens. It is characterized by the presence of a non-vascularized and unmineralized cartilage in the growth plate. Previous studies have investigated differential expression of genes related to cartilage development during latter stages of TD. The aim of our study was to identify differentially expressed genes (DEGs) in the growth plate of broiler chickens, which were associated with early stage TD. We induced TD using tetramethylthiuram disulfide (thiram) for 1, 2, and 6 days and determined DEGs with chicken Affymetrix GeneChip assays. The identified DEGs were verified by quantitative polymerase chain reaction (qPCR) assays. Results We identified 1630 DEGs, with 82, 1385, and 429 exhibiting at least 2.0-fold changes (P < 0.05) at days 1, 2, and 6, respectively. These DEGs participate in a variety of biological processes, including cytokine production, oxidation reduction, and cell surface receptor linked signal transduction on day 1; lipid biosynthesis, regulation of growth, cell cycle, positive and negative gene regulation, transcription and transcription regulation, and anti-apoptosis on day 2; and regulation of cell proliferation, transcription, dephosphorylation, catabolism, proteolysis, and immune responses on day 6. The identified DEGs were associated with the following pathways: neuroactive ligand-receptor interaction on day 1; synthesis and degradation of ketone bodies, terpenoid backbone biosynthesis, ether lipid metabolism, JAK-STAT, GnRH signaling pathway, ubiquitin mediated proteolysis, TGF-β signaling, focal adhesion, and Wnt signaling on day 2; and arachidonic acid metabolism, mitogen-activated protein kinase (MAPK) signaling, JAK-STAT, insulin signaling, and glycolysis on day 6. We validated seven DEGs by qPCR. Conclusions Our findings demonstrate previously unrecognized changes in gene transcription associated with early stage TD. The DEGs we identified by

  6. Microarray-based detection and expression analysis of extracellular matrix proteins in drug‑resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Ruciński, Marcin; Zabel, Maciej

    2014-11-01

    Ovarian cancer is the most lethal gynecological malignancy. Multiple drug resistance (MDR) development leads to resistance of cancer cells to chemotherapy. Microarray methods can provide information regarding new candidate genes that can play a role in resistance to cytostatic drugs. Extracellular matrix (ECM) can influence drug resistance by inhibiting the penetration of the drug into cancer tissue as well as increased apoptosis resistance. In the present study, we report changes in the ECM and related gene expression pattern in methotrexate-, cisplatin-, doxorubicin-, vincristine-, topotecan- and paclitaxel-resistant variants of the W1 ovarian cancer cell line. The resistant variants of the W1 cell line were generated by stepwise selection of cells with an increasing concentration of the indicated drugs. Affymetrix GeneChip® Human Genome U219 Array Strips were used for hybridizations. Independent t-tests were used to determinate the statistical significance of results. Genes whose expression levels were higher than the assumed threshold (upregulated, >5-fold and downregulated, <5-fold) were visualized using the scatter plot method, selected and listed in the tables. Among the investigated genes, expression of 24 genes increased, expression of 14 genes decreased and expression of three genes increased or decreased depending on the cell line. Among the increased genes, expression of 10 increased very significantly, >20-fold. These genes were: ITGB1BP3, COL3A1, COL5A2, COL15A1, TGFBI, DCN, LUM, MATN2, POSTN and EGFL6. The expression of seven genes decreased very significantly: ITGA1, COL1A2, LAMA2, GPC3, KRT23, VIT and HMCN1. The expression pattern of ECM and related genes provided the preliminary view into the role of ECM components in cytostatic drug resistance of cancer cells. The exact role of the investigated genes in drug resistance requires further investigation.

  7. Microarray analysis of gene expression in vestibular schwannomas reveals SPP1/MET signaling pathway and androgen receptor deregulation

    PubMed Central

    TORRES-MARTIN, MIGUEL; LASSALETTA, LUIS; SAN-ROMAN-MONTERO, JESUS; DE CAMPOS, JOSE M.; ISLA, ALBERTO; GAVILAN, JAVIER; MELENDEZ, BARBARA; PINTO, GIOVANNY R.; BURBANO, ROMMEL R.; CASTRESANA, JAVIER S.; REY, JUAN A.

    2013-01-01

    Vestibular schwannomas are benign neoplasms that arise from the vestibular nerve. The hallmark of these tumors is the biallelic inactivation of neurofibromin 2 (NF2). Transcriptomic alterations, such as the neuregulin 1 (NRG1)/ErbB2 pathway, have been described in schwannomas. In this study, we performed a whole transcriptome analysis in 31 vestibular schwannomas and 9 control nerves in the Affymetrix Gene 1.0 ST platform, validated by quantitative real-time PCR (qRT-PCR) using TaqMan Low Density arrays. We performed a mutational analysis of NF2 by PCR/denaturing high-performance liquid chromatography (dHPLC) and multiplex ligation-dependent probe amplification (MLPA), as well as a microsatellite marker analysis of the loss of heterozygosity (LOH) of chromosome 22q. The microarray analysis demonstrated that 1,516 genes were deregulated and 48 of the genes were validated by qRT-PCR. At least 2 genetic hits (allelic loss and/or gene mutation) in NF2 were found in 16 tumors, seven cases showed 1 hit and 8 tumors showed no NF2 alteration. MET and associated genes, such as integrin, alpha 4 (ITGA4)/B6, PLEXNB3/SEMA5 and caveolin-1 (CAV1) showed a clear deregulation in vestibular schwannomas. In addition, androgen receptor (AR) downregulation may denote a hormonal effect or cause in this tumor. Furthermore, the osteopontin gene (SPP1), which is involved in merlin protein degradation, was upregulated, which suggests that this mechanism may also exert a pivotal role in schwannoma merlin depletion. Finally, no major differences were observed among tumors of different size, histological type or NF2 status, which suggests that, at the mRNA level, all schwannomas, regardless of their molecular and clinical characteristics, may share common features that can be used in their treatment. PMID:23354516

  8. Microarray-based detection and expression analysis of ABC and SLC transporters in drug-resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Andrzejewska, Małgorzata; Ruciński, Marcin; Zabel, Maciej

    2013-04-01

    Multiple drug resistance of cancer cells is multifactorial. A microarray technique may provide information about new candidate genes playing a role in drug resistance. Drug membrane transporters from ABC and SLC families play a main role in this phenomenon. This study demonstrates alterations in ABC and SLC gene expression levels in methotrexate, cisplatin, doxorubicin, vincristine, topotecan and paclitaxel-resistant variant of W1 ovarian cancer cell line. Resistant W1 cell lines were derived by stepwise selection of cells in increasing concentration of drugs. Affymetrix GeneChip(®) Human Genome U219 Array Strip was used for hybridizations. Statistical significance was determined by independent sample t-test. The genes having altered expression levels in drug-resistant sublines were selected and filtered by scater plot. Genes up/downregulated more than threefolds were selected and listed. Among ABC genes, seven were upregulated and three were downregulated. Three genes: ABCB1, ABCB4 and ABCG2 were upregulated very significantly (over tenfold). One ABCA8 was significantly downregulated. Among 38 SLC genes, 18 were upregulated, 16 were downregulated and four were up- or downregulated dependent on the cell line. Expression of 10 SLC genes was changed very significantly (over tenfold). Four genes were significantly increased: SLC6A1, SLC9A2, SLC12A1, SLC16A6 and six genes were significantly decreased: SLC2A14, SLC7A3, SLC7A8, SLC7A11, SLC16A14, SLC38A9. Based on the expression profiles, our results provide a preliminary insight into the relationship between drug resistance and expression of membrane transporters involved in drug resistance. Correlation of specific drug transporter with drug resistance requires further analysis.

  9. Microarray-based detection and expression analysis of extracellular matrix proteins in drug‑resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Ruciński, Marcin; Zabel, Maciej

    2014-11-01

    Ovarian cancer is the most lethal gynecological malignancy. Multiple drug resistance (MDR) development leads to resistance of cancer cells to chemotherapy. Microarray methods can provide information regarding new candidate genes that can play a role in resistance to cytostatic drugs. Extracellular matrix (ECM) can influence drug resistance by inhibiting the penetration of the drug into cancer tissue as well as increased apoptosis resistance. In the present study, we report changes in the ECM and related gene expression pattern in methotrexate-, cisplatin-, doxorubicin-, vincristine-, topotecan- and paclitaxel-resistant variants of the W1 ovarian cancer cell line. The resistant variants of the W1 cell line were generated by stepwise selection of cells with an increasing concentration of the indicated drugs. Affymetrix GeneChip® Human Genome U219 Array Strips were used for hybridizations. Independent t-tests were used to determinate the statistical significance of results. Genes whose expression levels were higher than the assumed threshold (upregulated, >5-fold and downregulated, <5-fold) were visualized using the scatter plot method, selected and listed in the tables. Among the investigated genes, expression of 24 genes increased, expression of 14 genes decreased and expression of three genes increased or decreased depending on the cell line. Among the increased genes, expression of 10 increased very significantly, >20-fold. These genes were: ITGB1BP3, COL3A1, COL5A2, COL15A1, TGFBI, DCN, LUM, MATN2, POSTN and EGFL6. The expression of seven genes decreased very significantly: ITGA1, COL1A2, LAMA2, GPC3, KRT23, VIT and HMCN1. The expression pattern of ECM and related genes provided the preliminary view into the role of ECM components in cytostatic drug resistance of cancer cells. The exact role of the investigated genes in drug resistance requires further investigation. PMID:25199881

  10. Development of a porcine (Sus scofa) embryo-specific microarray: array annotation and validation

    PubMed Central

    2012-01-01

    Background The domestic pig is an important livestock species and there is strong interest in the factors that affect the development of viable embryos and offspring in this species. A limited understanding of the molecular mechanisms involved in early embryonic development has inhibited our ability to fully elucidate these factors. Next generation deep sequencing and microarray technologies are powerful tools for delineation of molecular pathways involved in the developing embryo. Results Here we present the development of a porcine-embryo-specific microarray platform created from a large expressed sequence tag (EST) analysis generated by Roche/454 next-generation sequencing of cDNAs constructed from critical stages of in vivo or in vitro porcine preimplantation embryos. Two cDNA libraries constructed from in vitro and in vivo produced preimplantation porcine embryos were normalized and sequenced using 454 Titanium pyrosequencing technology. Over one million high-quality EST sequences were obtained and used to develop the EMbryogene Porcine Version 1 (EMPV1) microarray composed of 43,795 probes. Based on an initial probe sequence annotation, the EMPV1 features 17,409 protein-coding, 473 pseudogenes, 46 retrotransposed, 2,359 non-coding RNA, 4,121 splice variants in 2,862 genes and a total of 12,324 Novel Transcript Regions (NTR). After re-annotation, the total unique genes increased from 11,961 to 16,281 and 1.9% of them belonged to a large olfactory receptor (OR) gene family. Quality control on the EMPV1 was performed and revealed an even distribution of ten clusters of spiked-in control spots and array to array (dye-swap) correlation was 0.97. Conclusions Using next-generation deep sequencing we have produced a large EST dataset to allow for the selection of probe sequences for the development of the EMPV1 microarray platform. The quality of this embryo-specific array was confirmed with a high-level of reproducibility using current Agilent microarray technology

  11. Deciphering the glycosaminoglycan code with the help of microarrays.

    PubMed

    de Paz, Jose L; Seeberger, Peter H

    2008-07-01

    Carbohydrate microarrays have become a powerful tool to elucidate the biological role of complex sugars. Microarrays are particularly useful for the study of glycosaminoglycans (GAGs), a key class of carbohydrates. The high-throughput chip format enables rapid screening of large numbers of potential GAG sequences produced via a complex biosynthesis while consuming very little sample. Here, we briefly highlight the most recent advances involving GAG microarrays built with synthetic or naturally derived oligosaccharides. These chips are powerful tools for characterizing GAG-protein interactions and determining structure-activity relationships for specific sequences. Thereby, they contribute to decoding the information contained in specific GAG sequences. PMID:18563243

  12. Deciphering the glycosaminoglycan code with the help of microarrays.

    PubMed

    de Paz, Jose L; Seeberger, Peter H

    2008-07-01

    Carbohydrate microarrays have become a powerful tool to elucidate the biological role of complex sugars. Microarrays are particularly useful for the study of glycosaminoglycans (GAGs), a key class of carbohydrates. The high-throughput chip format enables rapid screening of large numbers of potential GAG sequences produced via a complex biosynthesis while consuming very little sample. Here, we briefly highlight the most recent advances involving GAG microarrays built with synthetic or naturally derived oligosaccharides. These chips are powerful tools for characterizing GAG-protein interactions and determining structure-activity relationships for specific sequences. Thereby, they contribute to decoding the information contained in specific GAG sequences.

  13. Imaging combined autoimmune and infectious disease microarrays

    NASA Astrophysics Data System (ADS)

    Ewart, Tom; Raha, Sandeep; Kus, Dorothy; Tarnopolsky, Mark

    2006-09-01

    Bacterial and viral pathogens are implicated in many severe autoimmune diseases, acting through such mechanisms as molecular mimicry, and superantigen activation of T-cells. For example, Helicobacter pylori, well known cause of stomach ulcers and cancers, is also identified in ischaemic heart disease (mimicry of heat shock protein 65), autoimmune pancreatitis, systemic sclerosis, autoimmune thyroiditis (HLA DRB1*0301 allele susceptibility), and Crohn's disease. Successful antibiotic eradication of H.pylori often accompanies their remission. Yet current diagnostic devices, and test-limiting cost containment, impede recognition of the linkage, delaying both diagnosis and therapeutic intervention until the chronic debilitating stage. We designed a 15 minute low cost 39 antigen microarray assay, combining autoimmune, viral and bacterial antigens1. This enables point-of-care serodiagnosis and cost-effective narrowly targeted concurrent antibiotic and monoclonal anti-T-cell and anti-cytokine immunotherapy. Arrays of 26 pathogen and 13 autoimmune antigens with IgG and IgM dilution series were printed in triplicate on epoxysilane covalent binding slides with Teflon well masks. Sera diluted 1:20 were incubated 10 minutes, washed off, anti-IgG-Cy3 (green) and anti-IgM-Dy647 (red) were incubated for 5 minutes, washed off and the slide was read in an ArrayWoRx(e) scanning CCD imager (Applied Precision, Issaquah, WA). As a preliminary model for the combined infectious disease-autoimmune diagnostic microarray we surveyed 98 unidentified, outdated sera that were discarded after Hepatitis B antibody testing. In these, significant IgG or IgM autoantibody levels were found: dsDNA 5, ssDNA 11, Ro 2, RNP 7, SSB 4, gliadin 2, thyroglobulin 13 cases. Since control sera showed no autoantibodies, the high frequency of anti-DNA and anti-thyroglobulin antibodies found in infected sera lend increased support for linkage of infection to subsequent autoimmune disease. Expansion of the antigen

  14. A Combinational Clustering Based Method for cDNA Microarray Image Segmentation.

    PubMed

    Shao, Guifang; Li, Tiejun; Zuo, Wangda; Wu, Shunxiang; Liu, Tundong

    2015-01-01

    Microarray technology plays an important role in drawing useful biological conclusions by analyzing thousands of gene expressions simultaneously. Especially, image analysis is a key step in microarray analysis and its accuracy strongly depends on segmentation. The pioneering works of clustering based segmentation have shown that k-means clustering algorithm and moving k-means clustering algorithm are two commonly used methods in microarray image processing. However, they usually face unsatisfactory results because the real microarray image contains noise, artifacts and spots that vary in size, shape and contrast. To improve the segmentation accuracy, in this article we present a combination clustering based segmentation approach that may be more reliable and able to segment spots automatically. First, this new method starts with a very simple but effective contrast enhancement operation to improve the image quality. Then, an automatic gridding based on the maximum between-class variance is applied to separate the spots into independent areas. Next, among each spot region, the moving k-means clustering is first conducted to separate the spot from background and then the k-means clustering algorithms are combined for those spots failing to obtain the entire boundary. Finally, a refinement step is used to replace the false segmentation and the inseparable ones of missing spots. In addition, quantitative comparisons between the improved method and the other four segmentation algorithms--edge detection, thresholding, k-means clustering and moving k-means clustering--are carried out on cDNA microarray images from six different data sets. Experiments on six different data sets, 1) Stanford Microarray Database (SMD), 2) Gene Expression Omnibus (GEO), 3) Baylor College of Medicine (BCM), 4) Swiss Institute of Bioinformatics (SIB), 5) Joe DeRisi's individual tiff files (DeRisi), and 6) University of California, San Francisco (UCSF), indicate that the improved approach is

  15. A Combinational Clustering Based Method for cDNA Microarray Image Segmentation

    PubMed Central

    Shao, Guifang; Li, Tiejun; Zuo, Wangda; Wu, Shunxiang; Liu, Tundong

    2015-01-01

    Microarray technology plays an important role in drawing useful biological conclusions by analyzing thousands of gene expressions simultaneously. Especially, image analysis is a key step in microarray analysis and its accuracy strongly depends on segmentation. The pioneering works of clustering based segmentation have shown that k-means clustering algorithm and moving k-means clustering algorithm are two commonly used methods in microarray image processing. However, they usually face unsatisfactory results because the real microarray image contains noise, artifacts and spots that vary in size, shape and contrast. To improve the segmentation accuracy, in this article we present a combination clustering based segmentation approach that may be more reliable and able to segment spots automatically. First, this new method starts with a very simple but effective contrast enhancement operation to improve the image quality. Then, an automatic gridding based on the maximum between-class variance is applied to separate the spots into independent areas. Next, among each spot region, the moving k-means clustering is first conducted to separate the spot from background and then the k-means clustering algorithms are combined for those spots failing to obtain the entire boundary. Finally, a refinement step is used to replace the false segmentation and the inseparable ones of missing spots. In addition, quantitative comparisons between the improved method and the other four segmentation algorithms--edge detection, thresholding, k-means clustering and moving k-means clustering--are carried out on cDNA microarray images from six different data sets. Experiments on six different data sets, 1) Stanford Microarray Database (SMD), 2) Gene Expression Omnibus (GEO), 3) Baylor College of Medicine (BCM), 4) Swiss Institute of Bioinformatics (SIB), 5) Joe DeRisi’s individual tiff files (DeRisi), and 6) University of California, San Francisco (UCSF), indicate that the improved approach is

  16. A Combinational Clustering Based Method for cDNA Microarray Image Segmentation.

    PubMed

    Shao, Guifang; Li, Tiejun; Zuo, Wangda; Wu, Shunxiang; Liu, Tundong

    2015-01-01

    Microarray technology plays an important role in drawing useful biological conclusions by analyzing thousands of gene expressions simultaneously. Especially, image analysis is a key step in microarray analysis and its accuracy strongly depends on segmentation. The pioneering works of clustering based segmentation have shown that k-means clustering algorithm and moving k-means clustering algorithm are two commonly used methods in microarray image processing. However, they usually face unsatisfactory results because the real microarray image contains noise, artifacts and spots that vary in size, shape and contrast. To improve the segmentation accuracy, in this article we present a combination clustering based segmentation approach that may be more reliable and able to segment spots automatically. First, this new method starts with a very simple but effective contrast enhancement operation to improve the image quality. Then, an automatic gridding based on the maximum between-class variance is applied to separate the spots into independent areas. Next, among each spot region, the moving k-means clustering is first conducted to separate the spot from background and then the k-means clustering algorithms are combined for those spots failing to obtain the entire boundary. Finally, a refinement step is used to replace the false segmentation and the inseparable ones of missing spots. In addition, quantitative comparisons between the improv