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Sample records for a-madman annotation-based microarray

  1. 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…

  2. M@IA: a modular open-source application for microarray workflow and integrative datamining.

    PubMed

    Le Béchec, Antony; Zindy, Pierre; Sierocinski, Thomas; Petritis, Dimitri; Bihouée, Audrey; Le Meur, Nolwenn; Léger, Jean; Théret, Nathalie

    2008-01-01

    Microarray technology is a widely used approach to gene expression analysis. Many tools for microarray management and data analysis have been developed, and recently new methods have been proposed for deciphering biological pathways by integrating microarray data with other data sources. However, to improve microarray analysis and provide meaningful gene interaction networks, integrated software solutions are still needed. Therefore, we developed M@IA, an environment for DNA microarray data analysis allowing gene network reconstruction. M@IA is a microarray integrated application which includes all of the steps of a microarray study, from MIAME-compliant raw data storage and processing gene expression analysis. Furthermore, M@IA allows automatic gene annotation based on ontology, metabolic/signalling pathways, protein interaction, miRNA and transcriptional factor associations, as well as integrative analysis of gene interaction networks. Statistical and graphical methods facilitate analysis, yielding new hypotheses on gene expression data. To illustrate our approach, we applied M@IA modules to microarray data taken from an experiment on liver tissue. We integrated differentially expressed genes with additional biological information, thus identifying new molecular interaction networks that are associated with fibrogenesis. M@IA is a new application for microarray management and data analysis, offering functional insights into microarray data by the combination of gene expression data and biological knowledge annotation based on interactive graphs. M@IA is an interactive multi-user interface based on a flexible modular architecture and it is freely available for academic users at http://maia.genouest.org.

  3. 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.

  4. Overview of Protein Microarrays

    PubMed Central

    Reymond Sutandy, FX; Qian, Jiang; Chen, Chien-Sheng; Zhu, Heng

    2013-01-01

    Protein microarray is an emerging technology that provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput way. Two major classes of protein microarrays are defined to describe their applications: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be fractionated and spotted on a slide to form a reverse-phase protein microarray. While the fabrication technology is maturing, applications of protein microarrays, especially functional protein microarrays, have flourished during the past decade. Here, we will first review recent advances in the protein microarray technologies, and then present a series of examples to illustrate the applications of analytical and functional protein microarrays in both basic and clinical research. The research areas will include detection of various binding properties of proteins, study of protein posttranslational modifications, analysis of host-microbe interactions, profiling antibody specificity, and identification of biomarkers in autoimmune diseases. 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:23546620

  5. Microarray in parasitic infections

    PubMed Central

    Sehgal, Rakesh; Misra, Shubham; Anand, Namrata; Sharma, Monika

    2012-01-01

    Modern biology and genomic sciences are rooted in parasitic disease research. Genome sequencing efforts have provided a wealth of new biological information that promises to have a major impact on our understanding of parasites. Microarrays provide one of the major high-throughput platforms by which this information can be exploited in the laboratory. Many excellent reviews and technique articles have recently been published on applying microarrays to organisms for which fully annotated genomes are at hand. However, many parasitologists work on organisms whose genomes have been only partially sequenced. This review is mainly focused on how to use microarray in these situations. PMID:23508469

  6. Multievidence microarray mining.

    PubMed

    Seifert, Martin; Scherf, Matthias; Epple, Anton; Werner, Thomas

    2005-10-01

    Microarray mining is a challenging task because of the superposition of several processes in the data. We believe that the combination of microarray data-based analyses (statistical significance analysis of gene expression) with array-independent analyses (literature-mining and promoter analysis) enables some of the problems of traditional array analysis to be overcome. As a proof-of-principle, we revisited publicly available microarray data derived from an experiment with platelet-derived growth factor (PDGF)-stimulated fibroblasts. Our strategy revealed results beyond the detection of the major metabolic pathway known to be linked to the PDGF response: we were able to identify the crosstalking regulatory networks underlying the metabolic pathway without using a priori knowledge about the experiment.

  7. DNA microarray technology. Introduction.

    PubMed

    Pollack, Jonathan R

    2009-01-01

    DNA microarray technology has revolutionized biological research by enabling genome-scale explorations. This chapter provides an overview of DNA microarray technology and its application to characterizing the physical genome, with a focus on cancer genomes. Specific areas discussed include investigations of DNA copy number alteration (and loss of heterozygosity), DNA methylation, DNA-protein (i.e., chromatin and transcription factor) interactions, DNA replication, and the integration of diverse genome-scale data types. Also provided is a perspective on recent advances and future directions in characterizing the physical genome.

  8. Protein Microarray Technology

    PubMed Central

    Hall, David A.; Ptacek, Jason

    2007-01-01

    Protein chips have emerged as a promising approach for a wide variety of applications including the identification of protein-protein interactions, protein-phospholipid interactions, small molecule targets, and substrates of proteins kinases. They can also be used for clinical diagnostics and monitoring disease states. This article reviews current methods in the generation and applications of protein microarrays. PMID:17126887

  9. 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…

  10. Annotation-based genome-wide SNP discovery in the large and complex Aegilops tauschii genome using next-generation sequencing without a reference genome sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An annotation-based, genome-wide SNP discovery pipeline is reported using NGS data for large and complex genomes without a reference genome sequence. Roche 454 shotgun reads with low genome coverage of one genotype are annotated in order to distinguish single-copy sequences and repeat junctions fr...

  11. Analyzing Microarray Data.

    PubMed

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Because there is no widely used software for analyzing RNA-seq data that has a graphical user interface, this protocol provides an example of analyzing microarray data using Babelomics. This analysis entails performing quantile normalization and then detecting differentially expressed genes associated with the transgenesis of a human oncogene c-Myc in mice. Finally, hierarchical clustering is performed on the differentially expressed genes using the Cluster program, and the results are visualized using TreeView.

  12. Membrane-based microarrays

    NASA Astrophysics Data System (ADS)

    Dawson, Elliott P.; Hudson, James; Steward, John; Donnell, Philip A.; Chan, Wing W.; Taylor, Richard F.

    1999-11-01

    Microarrays represent a new approach to the rapid detection and identification of analytes. Studies to date have shown that the immobilization of receptor molecules (such as DNA, oligonucleotides, antibodies, enzymes and binding proteins) onto silicon and polymeric substrates can result in arrays able to detect hundreds of analytes in a single step. The formation of the receptor/analyte complex can, itself, lead to detection, or the complex can be interrogated through the use of fluorescent, chemiluminescent or radioactive probes and ligands.

  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. Microarrays in cancer research.

    PubMed

    Grant, Geraldine M; Fortney, Amanda; Gorreta, Francesco; Estep, Michael; Del Giacco, Luca; Van Meter, Amy; Christensen, Alan; Appalla, Lakshmi; Naouar, Chahla; Jamison, Curtis; Al-Timimi, Ali; Donovan, Jean; Cooper, James; Garrett, Carleton; Chandhoke, Vikas

    2004-01-01

    Microarray technology has presented the scientific community with a compelling approach that allows for simultaneous evaluation of all cellular processes at once. Cancer, being one of the most challenging diseases due to its polygenic nature, presents itself as a perfect candidate for evaluation by this approach. Several recent articles have provided significant insight into the strengths and limitations of microarrays. Nevertheless, there are strong indications that this approach will provide new molecular markers that could be used in diagnosis and prognosis of cancers. To achieve these goals it is essential that there is a seamless integration of clinical and molecular biological data that allows us to elucidate genes and pathways involved in various cancers. To this effect we are currently evaluating gene expression profiles in human brain, ovarian, breast and hematopoetic, lung, colorectal, head and neck and biliary tract cancers. To address the issues we have a joint team of scientists, doctors and computer scientists from two Virginia Universities and a major healthcare provider. The study has been divided into several focus groups that include; Tissue Bank Clinical & Pathology Laboratory Data, Chip Fabrication, QA/QC, Tissue Devitalization, Database Design and Data Analysis, using multiple microarray platforms. Currently over 300 consenting patients have been enrolled in the study with the largest number being that of breast cancer patients. Clinical data on each patient is being compiled into a secure and interactive relational database and integration of these data elements will be accomplished by a common programming interface. This clinical database contains several key parameters on each patient including demographic (risk factors, nutrition, co-morbidity, familial history), histopathology (non genetic predictors), tumor, treatment and follow-up information. Gene expression data derived from the tissue samples will be linked to this database, which

  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. 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.

  17. Living-cell microarrays.

    PubMed

    Yarmush, Martin L; King, Kevin R

    2009-01-01

    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.

  18. Microarray simulator as educational tool.

    PubMed

    Ruusuvuori, Pekka; Nykter, Matti; Mäkiraatikka, Eeva; Lehmussola, Antti; Korpelainen, Tomi; Erkkilä, Timo; Yli-Harja, Olli

    2007-01-01

    As many real-world applications, microarray measurements are inapplicable for large-scale teaching purposes due to their laborious preparation process and expense. Fortunately, many phases of the array preparation process can be efficiently demonstrated by using a software simulator tool. Here we propose the use of microarray simulator as an aiding tool in teaching of computational biology. Three case studies on educational use of the simulator are presented, which demonstrate the effect of gene knock-out, synthetic time series, and effect of noise sources. We conclude that the simulator, used for teaching the principles of microarray measurement technology, proved to be a useful tool in education.

  19. Chemistry of Natural Glycan Microarray

    PubMed Central

    Song, Xuezheng; Heimburg-Molinaro, Jamie; Cummings, Richard D.; Smith, David F.

    2014-01-01

    Glycan microarrays have become indispensable tools for studying protein-glycan interactions. Along with chemo-enzymatic synthesis, glycans isolated from natural sources have played important roles in array development and will continue to be a major source of glycans. N- and O-glycans from glycoproteins, and glycans from glycosphingolipids can be released from corresponding glycoconjugates with relatively mature methods, although isolation of large numbers and quantities of glycans are still very challenging. Glycosylphosphatidylinositol (GPI)-anchors and glycosaminoglycans (GAGs) are less represented on current glycan microarrays. Glycan microarray development has been greatly facilitated by bifunctional fluorescent linkers, which can be applied in a “Shotgun Glycomics” approach to incorporate isolated natural glycans. Glycan presentation on microarrays may affect glycan binding by GBPs, often through multivalent recognition by the GBP. PMID:24487062

  20. Microarray Technologies in Fungal Diagnostics.

    PubMed

    Rupp, Steffen

    2017-01-01

    Microarray technologies have been a major research tool in the last decades. In addition they have been introduced into several fields of diagnostics including diagnostics of infectious diseases. Microarrays are highly parallelized assay systems that initially were developed for multiparametric nucleic acid detection. From there on they rapidly developed towards a tool for the detection of all kind of biological compounds (DNA, RNA, proteins, cells, nucleic acids, carbohydrates, etc.) or their modifications (methylation, phosphorylation, etc.). The combination of closed-tube systems and lab on chip devices with microarrays further enabled a higher automation degree with a reduced contamination risk. Microarray-based diagnostic applications currently complement and may in the future replace classical methods in clinical microbiology like blood cultures, resistance determination, microscopic and metabolic analyses as well as biochemical or immunohistochemical assays. In addition, novel diagnostic markers appear, like noncoding RNAs and miRNAs providing additional room for novel nucleic acid based biomarkers. Here I focus an microarray technologies in diagnostics and as research tools, based on nucleic acid-based arrays.

  1. 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.

  2. 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.

  3. 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,…

  4. The Current Status of DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manufacturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthesized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microarrays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  5. The Current Status of DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Shi, Leming; Perkins, Roger G.; Tong, Weida

    DNA microarray technology that allows simultaneous assay of thousands of genes in a single experiment has steadily advanced to become a mainstream method used in research, and has reached a stage that envisions its use in medical applications and personalized medicine. Many different strategies have been developed for manufacturing DNA microarrays. In this chapter, we discuss the manu facturing characteristics of seven microarray platforms that were used in a recently completed large study by the MicroArray Quality Control (MAQC) consortium, which evaluated the concordance of results across these platforms. The platforms can be grouped into three categories: (1) in situ synthesis of oligonucleotide probes on microarrays (Affymetrix GeneChip® arrays based on photolithography synthesis and Agilent's arrays based on inkjet synthesis); (2) spotting of presynthe-sized oligonucleotide probes on microarrays (GE Healthcare's CodeLink system, Applied Biosystems' Genome Survey Microarrays, and the custom microarrays printed with Operon's oligonucleotide set); and (3) deposition of presynthesized oligonucleotide probes on bead-based microarrays (Illumina's BeadChip microar-rays). We conclude this chapter with our views on the challenges and opportunities toward acceptance of DNA microarray data in clinical and regulatory settings.

  6. 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

  7. DNA microarray technology in dermatology.

    PubMed

    Kunz, Manfred

    2008-03-01

    In recent years, DNA microarray technology has been used for the analysis of gene expression patterns in a variety of skin diseases, including malignant melanoma, psoriasis, lupus erythematosus, and systemic sclerosis. Many of the studies described herein confirmed earlier results on individual genes or functional groups of genes. However, a plethora of new candidate genes, gene patterns, and regulatory pathways have been identified. Major progresses were reached by the identification of a prognostic gene pattern in malignant melanoma, an immune signaling cluster in psoriasis, and a so-called interferon signature in systemic lupus erythematosus. In future, interference with genes or regulatory pathways with the use of different RNA interference technologies or targeted therapy may not only underscore the functional significance of microarray data but also may open interesting therapeutic perspectives. Large-scale gene expression analyses may also help to design more individualized treatment approaches of cutaneous diseases.

  8. 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.

  9. 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

  10. Surface characterization of carbohydrate microarrays.

    PubMed

    Scurr, David J; Horlacher, Tim; Oberli, Matthias A; Werz, Daniel B; Kroeck, Lenz; Bufali, Simone; Seeberger, Peter H; Shard, Alexander G; Alexander, Morgan R

    2010-11-16

    Carbohydrate microarrays are essential tools to determine the biological function of glycans. Here, we analyze a glycan array by time-of-flight secondary ion mass spectrometry (ToF-SIMS) to gain a better understanding of the physicochemical properties of the individual spots and to improve carbohydrate microarray quality. The carbohydrate microarray is prepared by piezo printing of thiol-terminated sugars onto a maleimide functionalized glass slide. The hyperspectral ToF-SIMS imaging data are analyzed by multivariate curve resolution (MCR) to discern secondary ions from regions of the array containing saccharide, linker, salts from the printing buffer, and the background linker chemistry. Analysis of secondary ions from the linker common to all of the sugar molecules employed reveals a relatively uniform distribution of the sugars within the spots formed from solutions with saccharide concentration of 0.4 mM and less, whereas a doughnut shape is often formed at higher-concentration solutions. A detailed analysis of individual spots reveals that in the larger spots the phosphate buffered saline (PBS) salts are heterogeneously distributed, apparently resulting in saccharide concentrated at the rim of the spots. A model of spot formation from the evaporating sessile drop is proposed to explain these observations. Saccharide spot diameters increase with saccharide concentration due to a reduction in surface tension of the saccharide solution compared to PBS. The multivariate analytical partial least squares (PLS) technique identifies ions from the sugars that in the complex ToF-SIMS spectra correlate with the binding of galectin proteins.

  11. Diagnostic challenges for multiplexed protein microarrays.

    PubMed

    Master, Stephen R; Bierl, Charlene; Kricka, Larry J

    2006-11-01

    Multiplexed protein analysis using planar microarrays or microbeads is growing in popularity for simultaneous assays of antibodies, cytokines, allergens, drugs and hormones. However, this new assay format presents several new operational issues for the clinical laboratory, such as the quality control of protein-microarray-based assays, the release of unrequested test data and the use of diagnostic algorithms to transform microarray data into diagnostic results.

  12. 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.

  13. 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...

  14. 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

  15. Clustering Short Time-Series Microarray

    NASA Astrophysics Data System (ADS)

    Ping, Loh Wei; Hasan, Yahya Abu

    2008-01-01

    Most microarray analyses are carried out on static gene expressions. However, the dynamical study of microarrays has lately gained more attention. Most researches on time-series microarray emphasize on the bioscience and medical aspects but few from the numerical aspect. This study attempts to analyze short time-series microarray mathematically using STEM clustering tool which formally preprocess data followed by clustering. We next introduce the Circular Mould Distance (CMD) algorithm with combinations of both preprocessing and clustering analysis. Both methods are subsequently compared in terms of efficiencies.

  16. 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...

  17. 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...

  18. 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…

  19. 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

  20. Analysis of DNA microarray expression data.

    PubMed

    Simon, Richard

    2009-06-01

    DNA microarrays are powerful tools for studying biological mechanisms and for developing prognostic and predictive classifiers for identifying the patients who require treatment and are best candidates for specific treatments. Because microarrays produce so much data from each specimen, they offer great opportunities for discovery and great dangers or producing misleading claims. Microarray based studies require clear objectives for selecting cases and appropriate analysis methods. Effective analysis of microarray data, where the number of measured variables is orders of magnitude greater than the number of cases, requires specialized statistical methods which have recently been developed. Recent literature reviews indicate that serious problems of analysis exist a substantial proportion of publications. This manuscript attempts to provide a non-technical summary of the key principles of statistical design and analysis for studies that utilize microarray expression profiling.

  1. 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.

  2. In control: systematic assessment of microarray performance.

    PubMed

    van Bakel, Harm; Holstege, Frank C P

    2004-10-01

    Expression profiling using DNA microarrays is a powerful technique that is widely used in the life sciences. How reliable are microarray-derived measurements? The assessment of performance is challenging because of the complicated nature of microarray experiments and the many different technology platforms. There is a mounting call for standards to be introduced, and this review addresses some of the issues that are involved. Two important characteristics of performance are accuracy and precision. The assessment of these factors can be either for the purpose of technology optimization or for the evaluation of individual microarray hybridizations. Microarray performance has been evaluated by at least four approaches in the past. Here, we argue that external RNA controls offer the most versatile system for determining performance and describe how such standards could be implemented. Other uses of external controls are discussed, along with the importance of probe sequence availability and the quantification of labelled material.

  3. Chaotic mixer improves microarray hybridization.

    PubMed

    McQuain, Mark K; Seale, Kevin; Peek, Joel; Fisher, Timothy S; Levy, Shawn; Stremler, Mark A; Haselton, Frederick R

    2004-02-15

    Hybridization is an important aspect of microarray experimental design which influences array signal levels and the repeatability of data within an array and across different arrays. Current methods typically require 24h and use target inefficiently. In these studies, we compare hybridization signals obtained in conventional static hybridization, which depends on diffusional target delivery, with signals obtained in a dynamic hybridization chamber, which employs a fluid mixer based on chaotic advection theory to deliver targets across a conventional glass slide array. Microarrays were printed with a pattern of 102 identical probe spots containing a 65-mer oligonucleotide capture probe. Hybridization of a 725-bp fluorescently labeled target was used to measure average target hybridization levels, local signal-to-noise ratios, and array hybridization uniformity. Dynamic hybridization for 1h with 1 or 10ng of target DNA increased hybridization signal intensities approximately threefold over a 24-h static hybridization. Similarly, a 10- or 60-min dynamic hybridization of 10ng of target DNA increased hybridization signal intensities fourfold over a 24h static hybridization. In time course studies, static hybridization reached a maximum within 8 to 12h using either 1 or 10ng of target. In time course studies using the dynamic hybridization chamber, hybridization using 1ng of target increased to a maximum at 4h and that using 10ng of target did not vary over the time points tested. In comparison to static hybridization, dynamic hybridization reduced the signal-to-noise ratios threefold and reduced spot-to-spot variation twofold. Therefore, we conclude that dynamic hybridization based on a chaotic mixer design improves both the speed of hybridization and the maximum level of hybridization while increasing signal-to-noise ratios and reducing spot-to-spot variation.

  4. 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.

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

    PubMed Central

    Maurer, Michael; Molidor, Robert; Sturn, Alexander; Hartler, Juergen; Hackl, Hubert; Stocker, Gernot; Prokesch, Andreas; Scheideler, Marcel; Trajanoski, Zlatko

    2005-01-01

    Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System) provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS), a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at . PMID:15836795

  6. 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

  7. 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

  8. Mutational analysis using oligonucleotide microarrays

    PubMed Central

    Hacia, J.; Collins, F.

    1999-01-01

    The development of inexpensive high throughput methods to identify individual DNA sequence differences is important to the future growth of medical genetics. This has become increasingly apparent as epidemiologists, pathologists, and clinical geneticists focus more attention on the molecular basis of complex multifactorial diseases. Such undertakings will rely upon genetic maps based upon newly discovered, common, single nucleotide polymorphisms. Furthermore, candidate gene approaches used in identifying disease associated genes necessitate screening large sequence blocks for changes tracking with the disease state. Even after such genes are isolated, large scale mutational analyses will often be needed for risk assessment studies to define the likely medical consequences of carrying a mutated gene.
This review concentrates on the use of oligonucleotide arrays for hybridisation based comparative sequence analysis. Technological advances within the past decade have made it possible to apply this technology to many different aspects of medical genetics. These applications range from the detection and scoring of single nucleotide polymorphisms to mutational analysis of large genes. Although we discuss published scientific reports, unpublished work from the private sector12 could also significantly affect the future of this technology.


Keywords: mutational analysis; oligonucleotide microarrays; DNA chips PMID:10528850

  9. Integrating Microarray Data and GRNs.

    PubMed

    Koumakis, L; Potamias, G; Tsiknakis, M; Zervakis, M; Moustakis, V

    2016-01-01

    With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

  10. 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

  11. 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…

  12. PATMA: parser of archival tissue microarray.

    PubMed

    Roszkowiak, Lukasz; Lopez, Carlos

    2016-01-01

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

  13. PATMA: parser of archival tissue microarray

    PubMed Central

    2016-01-01

    Tissue microarrays are commonly used in modern pathology for cancer tissue evaluation, as it is a very potent technique. Tissue microarray slides are often scanned to perform computer-aided histopathological analysis of the tissue cores. For processing the image, splitting the whole virtual slide into images of individual cores is required. The only way to distinguish cores corresponding to specimens in the tissue microarray is through their arrangement. Unfortunately, distinguishing the correct order of cores is not a trivial task as they are not labelled directly on the slide. The main aim of this study was to create a procedure capable of automatically finding and extracting cores from archival images of the tissue microarrays. This software supports the work of scientists who want to perform further image processing on single cores. The proposed method is an efficient and fast procedure, working in fully automatic or semi-automatic mode. A total of 89% of punches were correctly extracted with automatic selection. With an addition of manual correction, it is possible to fully prepare the whole slide image for extraction in 2 min per tissue microarray. The proposed technique requires minimum skill and time to parse big array of cores from tissue microarray whole slide image into individual core images. PMID:27920955

  14. The Impact of Photobleaching on Microarray Analysis

    PubMed Central

    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

  15. 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

  16. Validation of affinity reagents using antigen microarrays.

    PubMed

    Sjöberg, Ronald; Sundberg, Mårten; Gundberg, Anna; Sivertsson, Asa; Schwenk, Jochen M; Uhlén, Mathias; Nilsson, Peter

    2012-06-15

    There is a need for standardised validation of affinity reagents to determine their binding selectivity and specificity. This is of particular importance for systematic efforts that aim to cover the human proteome with different types of binding reagents. One such international program is the SH2-consortium, which was formed to generate a complete set of renewable affinity reagents to the SH2-domain containing human proteins. Here, we describe a microarray strategy to validate various affinity reagents, such as recombinant single-chain antibodies, mouse monoclonal antibodies and antigen-purified polyclonal antibodies using a highly multiplexed approach. An SH2-specific antigen microarray was designed and generated, containing more than 6000 spots displayed by 14 identical subarrays each with 406 antigens, where 105 of them represented SH2-domain containing proteins. Approximately 400 different affinity reagents of various types were analysed on these antigen microarrays carrying antigens of different types. The microarrays revealed not only very detailed specificity profiles for all the binders, but also showed that overlapping target sequences of spotted antigens were detected by off-target interactions. The presented study illustrates the feasibility of using antigen microarrays for integrative, high-throughput validation of various types of binders and antigens.

  17. Posttranslational Modification Assays on Functional Protein Microarrays.

    PubMed

    Neiswinger, Johnathan; Uzoma, Ijeoma; Cox, Eric; Rho, HeeSool; Jeong, Jun Seop; Zhu, Heng

    2016-10-03

    Protein microarray technology provides a straightforward yet powerful strategy for identifying substrates of posttranslational modifications (PTMs) and studying the specificity of the enzymes that catalyze these reactions. Protein microarray assays can be designed for individual enzymes or a mixture to establish connections between enzymes and substrates. Assays for four well-known PTMs-phosphorylation, acetylation, ubiquitylation, and SUMOylation-have been developed and are described here for use on functional protein microarrays. Phosphorylation and acetylation require a single enzyme and are easily adapted for use on an array. The ubiquitylation and SUMOylation cascades are very similar, and the combination of the E1, E2, and E3 enzymes plus ubiquitin or SUMO protein and ATP is sufficient for in vitro modification of many substrates.

  18. 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

  19. Overview of DNA microarrays: types, applications, and their future.

    PubMed

    Bumgarner, Roger

    2013-01-01

    This unit provides an overview of DNA microarrays. Microarrays are a technology in which thousands of nucleic acids are bound to a surface and are used to measure the relative concentration of nucleic acid sequences in a mixture via hybridization and subsequent detection of the hybridization events. This overview first discusses the history of microarrays and the antecedent technologies that led to their development. This is followed by discussion of the methods of manufacture of microarrays and the most common biological applications. The unit ends with a brief description of the limitations of microarrays and discusses how microarrays are being rapidly replaced by DNA sequencing technologies.

  20. 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).

  1. 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

  2. Would a madman have been so wise as this?" The effects of source credibility and message credibility on validation.

    PubMed

    Foy, Jeffrey E; LoCasto, Paul C; Briner, Stephen W; Dyar, Samantha

    2017-02-01

    Readers rapidly check new information against prior knowledge during validation, but research is inconsistent as to whether source credibility affects validation. We argue that readers are likely to accept highly plausible assertions regardless of source, but that high source credibility may boost acceptance of claims that are less plausible based on general world knowledge. In Experiment 1, participants read narratives with assertions for which the plausibility varied depending on the source. For high credibility sources, we found that readers were faster to read information confirming these assertions relative to contradictory information. We found the opposite patterns for low credibility characters. In Experiment 2, readers read claims from the same high or low credibility sources, but the claims were always plausible based on general world knowledge. Readers consistently took longer to read contradictory information, regardless of source. In Experiment 3, participants read modified versions of "The Tell-Tale Heart," which was narrated entirely by an unreliable source. We manipulated the plausibility of a target event, as well as whether high credibility characters within the story provided confirmatory or contradictory information about the narrator's description of the target event. Though readers rated the narrator as being insane, they were more likely to believe the narrator's assertions about the target event when it was plausible and corroborated by other characters. We argue that sourcing research would benefit from focusing on the relationship between source credibility, message credibility, and multiple sources within a text.

  3. 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...

  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.

  5. Annotating nonspecific SAGE tags with microarray data.

    PubMed

    Ge, Xijin; Jung, Yong-Chul; Wu, Qingfa; Kibbe, Warren A; Wang, San Ming

    2006-01-01

    SAGE (serial analysis of gene expression) detects transcripts by extracting short tags from the transcripts. Because of the limited length, many SAGE tags are shared by transcripts from different genes. Relying on sequence information in the general gene expression database has limited power to solve this problem due to the highly heterogeneous nature of the deposited sequences. Considering that the complexity of gene expression at a single tissue level should be much simpler than that in the general expression database, we reasoned that by restricting gene expression to tissue level, the accuracy of gene annotation for the nonspecific SAGE tags should be significantly improved. To test the idea, we developed a tissue-specific SAGE annotation database based on microarray data (). This database contains microarray expression information represented as UniGene clusters for 73 normal human tissues and 18 cancer tissues and cell lines. The nonspecific SAGE tag is first matched to the database by the same tissue type used by both SAGE and microarray analysis; then the multiple UniGene clusters assigned to the nonspecific SAGE tag are searched in the database under the matched tissue type. The UniGene cluster presented solely or at higher expression levels in the database is annotated to represent the specific gene for the nonspecific SAGE tags. The accuracy of gene annotation by this database was largely confirmed by experimental data. Our study shows that microarray data provide a useful source for annotating the nonspecific SAGE tags.

  6. Analytical Protein Microarrays: Advancements Towards Clinical Applications

    PubMed Central

    Sauer, Ursula

    2017-01-01

    Protein microarrays represent a powerful technology with the potential to serve as tools for the detection of a broad range of analytes in numerous applications such as diagnostics, drug development, food safety, and environmental monitoring. Key features of analytical protein microarrays include high throughput and relatively low costs due to minimal reagent consumption, multiplexing, fast kinetics and hence measurements, and the possibility of functional integration. So far, especially fundamental studies in molecular and cell biology have been conducted using protein microarrays, while the potential for clinical, notably point-of-care applications is not yet fully utilized. The question arises what features have to be implemented and what improvements have to be made in order to fully exploit the technology. In the past we have identified various obstacles that have to be overcome in order to promote protein microarray technology in the diagnostic field. Issues that need significant improvement to make the technology more attractive for the diagnostic market are for instance: too low sensitivity and deficiency in reproducibility, inadequate analysis time, lack of high-quality antibodies and validated reagents, lack of automation and portable instruments, and cost of instruments necessary for chip production and read-out. The scope of the paper at hand is to review approaches to solve these problems. PMID:28146048

  7. Analytical Protein Microarrays: Advancements Towards Clinical Applications.

    PubMed

    Sauer, Ursula

    2017-01-29

    Protein microarrays represent a powerful technology with the potential to serve as tools for the detection of a broad range of analytes in numerous applications such as diagnostics, drug development, food safety, and environmental monitoring. Key features of analytical protein microarrays include high throughput and relatively low costs due to minimal reagent consumption, multiplexing, fast kinetics and hence measurements, and the possibility of functional integration. So far, especially fundamental studies in molecular and cell biology have been conducted using protein microarrays, while the potential for clinical, notably point-of-care applications is not yet fully utilized. The question arises what features have to be implemented and what improvements have to be made in order to fully exploit the technology. In the past we have identified various obstacles that have to be overcome in order to promote protein microarray technology in the diagnostic field. Issues that need significant improvement to make the technology more attractive for the diagnostic market are for instance: too low sensitivity and deficiency in reproducibility, inadequate analysis time, lack of high-quality antibodies and validated reagents, lack of automation and portable instruments, and cost of instruments necessary for chip production and read-out. The scope of the paper at hand is to review approaches to solve these problems.

  8. 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…

  9. 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.

  10. 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...

  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. A Method of Microarray Data Storage Using Array Data Type

    PubMed Central

    Tsoi, Lam C.; Zheng, W. Jim

    2009-01-01

    A well-designed microarray database can provide valuable information on gene expression levels. However, designing an efficient microarray database with minimum space usage is not an easy task since designers need to integrate the microarray data with the information of genes, probe annotation, and the descriptions of each microarray experiment. Developing better methods to store microarray data can greatly improve the efficiency and usefulness of such data. A new schema is proposed to store microarray data by using array data type in an object-relational database management system – PostgreSQL. The implemented database can store all the microarray data from the same chip in an array data structure. The variable length array data type in PostgreSQL can store microarray data from same chip. The implementation of our schema can help to increase the data retrieval and space efficiency. PMID:17392028

  13. 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...

  14. 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.

  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. Design of a covalently bonded glycosphingolipid microarray.

    PubMed

    Arigi, Emma; Blixt, Ola; Buschard, Karsten; Clausen, Henrik; Levery, Steven B

    2012-01-01

    Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform for in vitro study of their functional interactions. However, with few exceptions, the most widely used microarray platforms display only the glycan moiety of GSLs, which not only ignores potential modulating effects of the lipid aglycone, but inherently limits the scope of application, excluding, for example, the major classes of plant and fungal GSLs. In this work, a prototype "universal" GSL-based covalent microarray has been designed, and preliminary evaluation of its potential utility in assaying protein-GSL binding interactions investigated. An essential step in development involved the enzymatic release of the fatty acyl moiety of the ceramide aglycone of selected mammalian GSLs with sphingolipid N-deacylase (SCDase). Derivatization of the free amino group of a typical lyso-GSL, lyso-G(M1), with a prototype linker assembled from succinimidyl-[(N-maleimidopropionamido)-diethyleneglycol] ester and 2-mercaptoethylamine, was also tested. Underivatized or linker-derivatized lyso-GSL were then immobilized on N-hydroxysuccinimide- or epoxide-activated glass microarray slides and probed with carbohydrate binding proteins of known or partially known specificities (i.e., cholera toxin B-chain; peanut agglutinin, a monoclonal antibody to sulfatide, Sulph 1; and a polyclonal antiserum reactive to asialo-G(M2)). Preliminary evaluation of the method indicated successful immobilization of the GSLs, and selective binding of test probes. The potential utility of this methodology for designing covalent microarrays that incorporate GSLs for serodiagnosis is discussed.

  17. Integrated analysis of microarray data and gene function information.

    PubMed

    Cui, Yan; Zhou, Mi; Wong, Wing Hung

    2004-01-01

    Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the microarray-derived gene groups and gene function categories, it captures the complex relations between biological information derived from microarray data and the existing knowledge about the gene function. Thus, homogeneity analysis provides a mathematical framework for integrating the analysis of microarray data and the existing biological knowledge.

  18. Viral diagnosis in Indian livestock using customized microarray chips

    PubMed Central

    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. PMID:26912948

  19. 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.

  20. Respiratory Tularemia: Francisella Tularensis and Microarray Probe Designing

    PubMed Central

    Ranjbar, Reza; Behzadi, Payam; Mammina, Caterina

    2016-01-01

    Background: Francisella tularensis (F. tularensis) is the etiological microorganism for tularemia. There are different forms of tularemia such as respiratory tularemia. Respiratory tularemia is the most severe form of tularemia with a high rate of mortality; if not treated. Therefore, traditional microbiological tools and Polymerase Chain Reaction (PCR) are not useful for a rapid, reliable, accurate, sensitive and specific diagnosis. But, DNA microarray technology does. DNA microarray technology needs to appropriate microarray probe designing. Objective: The main goal of this original article was to design suitable long oligo microarray probes for detection and identification of F. tularensis. Method: For performing this research, the complete genomes of F. tularensis subsp. tularensis FSC198, F. tularensis subsp. holarctica LVS, F. tularensis subsp. mediasiatica, F. tularensis subsp. novicida (F. novicida U112), and F. philomiragia subsp. philomiragia ATCC 25017 were studied via NCBI BLAST tool, GView and PanSeq Servers and finally the microarray probes were produced and processed via AlleleID 7.7 software and Oligoanalyzer tool, respectively. Results: In this in silico investigation, a number of long oligo microarray probes were designed for detecting and identifying F. tularensis. Among these probes, 15 probes were recognized as the best candidates for microarray chip designing. Conclusion: Calibrated microarray probes reduce the biasis of DNA microarray technology as an advanced, rapid, accurate and cost-effective molecular diagnostic tool with high specificity and sensitivity. Professional microarray probe designing provides us with much more facility and flexibility regarding preparation of a microarray diagnostic chip. PMID:28077973

  1. Detecting outlier samples in microarray data.

    PubMed

    Shieh, Albert D; Hung, Yeung Sam

    2009-01-01

    In this paper, we address the problem of detecting outlier samples with highly different expression patterns in microarray data. Although outliers are not common, they appear even in widely used benchmark data sets and can negatively affect microarray data analysis. It is important to identify outliers in order to explore underlying experimental or biological problems and remove erroneous data. We propose an outlier detection method based on principal component analysis (PCA) and robust estimation of Mahalanobis distances that is fully automatic. We demonstrate that our outlier detection method identifies biologically significant outliers with high accuracy and that outlier removal improves the prediction accuracy of classifiers. Our outlier detection method is closely related to existing robust PCA methods, so we compare our outlier detection method to a prominent robust PCA method.

  2. Molecular diagnosis and prognosis with DNA microarrays.

    PubMed

    Wiltgen, Marco; Tilz, Gernot P

    2011-05-01

    Microarray analysis makes it possible to determine thousands of gene expression values simultaneously. Changes in gene expression, as a response to diseases, can be detected allowing a better understanding and differentiation of diseases at a molecular level. By comparing different kinds of tissue, for example healthy tissue and cancer tissue, the microarray analysis indicates induced gene activity, repressed gene activity or when there is no change in the gene activity level. Fundamental patterns in gene expression are extracted by several clustering and machine learning algorithms. Certain kinds of cancer can be divided into subtypes, with different clinical outcomes, by their specific gene expression patterns. This enables a better diagnosis and tailoring of individual patient treatments.

  3. 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.

  4. 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

  5. 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.

  6. Ultrahigh density microarrays of solid samples.

    PubMed

    LeBaron, Matthew J; Crismon, Heidi R; Utama, Fransiscus E; Neilson, Lynn M; Sultan, Ahmed S; Johnson, Kevin J; Andersson, Eva C; Rui, Hallgeir

    2005-07-01

    We present a sectioning and bonding technology to make ultrahigh density microarrays of solid samples, cutting edge matrix assembly (CEMA). Maximized array density is achieved by a scaffold-free, self-supporting construction with rectangular array features that are incrementally scalable. This platform technology facilitates arrays of >10,000 tissue features on a standard glass slide, inclusion of unique sample identifiers for improved manual or automated tracking, and oriented arraying of stratified or polarized samples.

  7. 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.

  8. Methods for fabricating microarrays of motile bacteria.

    PubMed

    Rozhok, Sergey; Shen, Clifton K-F; Littler, Pey-Lih H; Fan, Zhifang; Liu, Chang; Mirkin, Chad A; Holz, Richard C

    2005-04-01

    Motile bacterial cell microarrays were fabricated by attaching Escherichia coli K-12 cells onto predesigned 16-mercaptohexadecanoic acid patterned microarrays, which were covalently functionalized with E. coli antibodies or poly-L-lysine. By utilizing 11-mercaptoundecyl-penta(ethylene glycol) or 11-mercapto-1-undecanol as passivating molecules, nonspecific binding of E. coli was significantly reduced. Microcontact printing and dip-pen nanolithography were used to prepare microarrays for bacterial adhesion, which was studied by optical fluorescence and atomic force microscopy. These data indicate that single motile E. coli can be attached to predesigned line or dot features and binding can occur via the cell body or the flagella of bacteria. Adherent bacteria are viable (remain alive and motile after adhesion to patterned surface features) for more than four hours. Individual motile bacterial cells can be placed onto predesigned surface features that are at least 1.3 microm in diameter or larger. The importance of controlling the adhesion of single bacterial cell to a surface is discussed with regard to biomotor design.

  9. A New Distribution Family for Microarray Data.

    PubMed

    Kelmansky, Diana Mabel; Ricci, Lila

    2017-02-10

    The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative stand point taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. Rcodes are available from the authors upon request.

  10. 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.

  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. Microarray Technology Applied to Human Allergic Disease

    PubMed Central

    Hamilton, Robert G.

    2017-01-01

    IgE antibodies serve as the gatekeeper for the release of mediators from sensitized (IgE positive) mast cells and basophils following a relevant allergen exposure which can lead to an immediate-type hypersensitivity (allergic) reaction. Purified recombinant and native allergens were combined in the 1990s with state of the art chip technology to establish the first microarray-based IgE antibody assay. Triplicate spots to over 100 allergenic molecules are immobilized on an amine-activated glass slide to form a single panel multi-allergosorbent assay. Human antibodies, typically of the IgE and IgG isotypes, specific for one or many allergens bind to their respective allergen(s) on the chip. Following removal of unbound serum proteins, bound IgE antibody is detected with a fluorophore-labeled anti-human IgE reagent. The fluorescent profile from the completed slide provides a sensitization profile of an allergic patient which can identify IgE antibodies that bind to structurally similar (cross-reactive) allergen families versus molecules that are unique to a single allergen specificity. Despite its ability to rapidly analyze many IgE antibody specificities in a single simple assay format, the chip-based microarray remains less analytically sensitive and quantitative than its singleplex assay counterpart (ImmunoCAP, Immulite). Microgram per mL quantities of allergen-specific IgG antibody can also complete with nanogram per mL quantities of specific IgE for limited allergen binding sites on the chip. Microarray assays, while not used in clinical immunology laboratories for routine patient IgE antibody testing, will remain an excellent research tool for defining sensitization profiles of populations in epidemiological studies. PMID:28134842

  14. Development of a microarray for identification of pathogenic Clostridium species

    PubMed Central

    Janvilisri, Tavan; Scaria, Joy; Gleed, Robin; Fubini, Susan; Bonkosky, Michelle M.; Gröhn, Yrjö T.; Chang, Yung-Fu

    2009-01-01

    In recent years, Clostridium species have rapidly reemerged as human and animal pathogens. The detection and identification of pathogenic Clostridium species is therefore critical for clinical diagnosis and antimicrobial therapy. Traditional diagnostic techniques for clostridia are laborious, time-consuming and may adversely affect the therapeutic outcome. In this study, we developed an oligonucleotide diagnostic microarray for pathogenic Clostridium species. The microarray specificity was tested against 65 Clostridium isolates. The applicability of this microarray in a clinical setting was assessed with the use of mock stool samples. The microarray was successful in discriminating at least four species with the limit of detection as low as 104 CFU/ml. In addition, the pattern of virulence and antibiotic resistance genes of tested strains were determined through the microarrays. This approach demonstrates the high-throughput detection and identification of Clostridium species and provides advantages over traditional methods. Microarray-based techniques are promising applications for clinical diagnosis and epidemiological investigations. PMID:19879710

  15. Application of DNA microarray technology to gerontological studies.

    PubMed

    Masuda, Kiyoshi; Kuwano, Yuki; Nishida, Kensei; Rokutan, Kazuhito

    2013-01-01

    Gene expression patterns change dramatically in aging and age-related events. The DNA microarray is now recognized as a useful device in molecular biology and widely used to identify the molecular mechanisms of aging and the biological effects of drugs for therapeutic purpose in age-related diseases. Recently, numerous technological advantages have led to the evolution of DNA microarrays and microarray-based techniques, revealing the genomic modification and all transcriptional activity. Here, we show the step-by-step methods currently used in our lab to handling the oligonucleotide microarray and miRNA microarray. Moreover, we introduce the protocols of ribonucleoprotein [RNP] immunoprecipitation followed by microarray analysis (RIP-chip) which reveal the target mRNA of age-related RNA-binding proteins.

  16. Tissue microarrays for early target evaluation.

    PubMed

    Simon, Ronald; Mirlacher, Martina; Sauter, Guido

    2004-09-01

    Early assessment of the probable biological importance of drug targets, the potential market size of a successful new drug, and possible treatment side effects are critical for risk management in drug development. A comprehensive molecular epidemiology analysis involving thousands of well-characterized human tissues will thus provide vital information for strategic decision-making. Tissue microarray (TMA) technology is ideally suited for such projects. The simultaneous analysis of thousands of tissues enables highly standardized, fast and affordable translational research studies of unprecedented scale.:

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Application of DNA microarrays in occupational health research.

    PubMed

    Koizumi, Shinji

    2004-01-01

    The profiling of gene expression patterns with DNA microarrays is recently being widely used not only in basic molecular biological studies but also in the practical fields. In clinical application, for example, this technique is expected to be quite useful in making a correct diagnosis. In the pharmacological area, the microarray analysis can be applied to drug discovery and individualized drug treatment. Although not so popular as these examples, DNA microarrays could also be a powerful tool in studies relevant to occupational health. This review will describe the outline of gene expression profiling with DNA microarrays and prospects in occupational health research.

  4. Zeptosens' protein microarrays: a novel high performance microarray platform for low abundance protein analysis.

    PubMed

    Pawlak, Michael; Schick, Eginhard; Bopp, Martin A; Schneider, Michael J; Oroszlan, Peter; Ehrat, Markus

    2002-04-01

    Protein microarrays are considered an enabling technology, which will significantly expand the scope of current protein expression and protein interaction analysis. Current technologies, such as two-dimensional gel electrophoresis (2-DE) in combination with mass spectrometry, allowing the identification of biologically relevant proteins, have a high resolving power, but also considerable limitations. As was demonstrated by Gygi et al. (Proc. Nat. Acad. Sci. USA 2000,97, 9390-9395), most spots in 2-DE, observed from whole cell extracts, are from high abundance proteins, whereas low abundance proteins, such as signaling molecules or kinases, are only poorly represented. Protein microarrays are expected to significantly expedite the discovery of new markers and targets of pharmaceutical interest, and to have the potential for high-throughput applications. Key factors to reach this goal are: high read-out sensitivity for quantification also of low abundance proteins, functional analysis of proteins, short assay analysis times, ease of handling and the ability to integrate a variety of different targets and new assays. Zeptosens has developed a revolutionary new bioanalytical system based on the proprietary planar waveguide technology which allows us to perform multiplexed, quantitative biomolecular interaction analysis with highest sensitivity in a microarray format upon utilizing the specific advantages of the evanescent field fluorescence detection. The analytical system, comprising an ultrasensitive fluorescence reader and microarray chips with integrated microfluidics, enables the user to generate a multitude of high fidelity data in applications such as protein expression profiling or investigating protein-protein interactions. In this paper, the important factors for developing high performance protein microarray systems, especially for targeting low abundant messengers of relevant biological information, will be discussed and the performance of the system will

  5. Manufacturing DNA microarrays from unpurified PCR products

    PubMed Central

    Diehl, Frank; Beckmann, Boris; Kellner, Nadine; Hauser, Nicole C.; Diehl, Susanne; Hoheisel, Jörg D.

    2002-01-01

    For the production of DNA microarrays from PCR products, purification of the the DNA fragments prior to spotting is a major expense in cost and time. Also, a considerable amount of material is lost during this process and contamination might occur. Here, a protocol is presented that permits the manufacture of microarrays from unpurified PCR products on aminated surfaces such as glass slides coated with the widely used poly(l-lysine) or aminosilane. The presence of primer molecules in the PCR sample does not increase the non-specific signal upon hybridisation. Overall, signal intensity on arrays made of unpurified PCR products is 94% of the intensity obtained with the respective purified molecules. This slight loss in signal, however, is offset by a reduced variation in the amount of DNA present at the individual spot positions across an array, apart from the considerable savings in time and cost. In addition, a larger number of arrays can be made from one batch of amplification products. PMID:12177307

  6. 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.

  7. Solution processed organic microarray with inverted structure

    NASA Astrophysics Data System (ADS)

    Toglia, Patrick; Lewis, Jason; Lafalce, Evan; Jiang, Xiaomei

    2011-03-01

    We have fabricated inverted organic microarray using a novel solution-based technique. The array consists of 60 small (1 square mm) solar cells on a one inch by one inch glass substrate. The device utilizes photoactive materials such as a blend of poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM). Manipulation of active layer nanomorphology has been done by choice of solvents and annealing conditions. Detailed analysis of device physics including current voltage characteristics, external quantum efficiency and carrier recombinations will be presented and complimented by AFM images and glazing angle XRD of the active layer under different processing conditions. The procedure described here has the full potential for use in future fabrication of microarrays with single cell as small as 0.01 square mm for application in DC power supplies for electrostatic Microelectromechanical systems (MEMS) devices. This work was supported by New Energy Technology Inc. and Florida High Tech Corridor Matching Fund (FHT 09-18).

  8. Clickable Polymeric Coating for Glycan Microarrays.

    PubMed

    Zilio, Caterina; Sola, Laura; Cretich, Marina; Bernardi, Anna; Chiari, Marcella

    2017-01-01

    The interaction of carbohydrates with a variety of biological targets, including antibodies, proteins, viruses, and cells are of utmost importance in many aspects of biology. Glycan microarrays are increasingly used to determine the binding specificity of glycan-binding proteins. In this study, a novel microarray support is reported for the fabrication of glycan arrays that combines the higher sensitivity of a layered Si-SiO2 surface with a novel polymeric coating easily modifiable by subsequent click reaction. The alkyne-containing copolymer, adsorbed from an aqueous solution, produces a coating by a single step procedure and serves as a soft, tridimensional support for the oriented immobilization of carbohydrates via azide/alkyne Cu (I) catalyzed "click" reaction. The advantages of a functional 3D polymer coating making use of a click chemistry immobilization are combined with the high fluorescence sensitivity and superior signal-to-noise ratio of a Si-SiO2 substrate. The proposed approach enables the attachment of complex sugars on a silicon oxide surface by a method that does not require skilled personnel and chemistry laboratories.

  9. 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…

  10. 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

  11. 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.

  12. 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...

  13. 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.

  14. Giant Magnetoresistive Sensors for DNA Microarray

    PubMed Central

    Xu, Liang; Yu, Heng; Han, Shu-Jen; Osterfeld, Sebastian; White, Robert L.; Pourmand, Nader; Wang, Shan X.

    2009-01-01

    Giant magnetoresistive (GMR) sensors are developed for a DNA microarray. Compared with the conventional fluorescent sensors, GMR sensors are cheaper, more sensitive, can generate fully electronic signals, and can be easily integrated with electronics and microfluidics. The GMR sensor used in this work has a bottom spin valve structure with an MR ratio of 12%. The single-strand target DNA detected has a length of 20 bases. Assays with DNA concentrations down to 10 pM were performed, with a dynamic range of 3 logs. A double modulation technique was used in signal detection to reduce the 1/f noise in the sensor while circumventing electromagnetic interference. The logarithmic relationship between the magnetic signal and the target DNA concentration can be described by the Temkin isotherm. Furthermore, GMR sensors integrated with microfluidics has great potential of improving the sensitivity to 1 pM or below, and the total assay time can be reduced to less than 1 hour. PMID:20824116

  15. Uses of Dendrimers for DNA Microarrays

    PubMed Central

    Caminade, Anne-Marie; Padié, Clément; Laurent, Régis; Maraval, Alexandrine; Majoral, Jean-Pierre

    2006-01-01

    Biosensors such as DNA microarrays and microchips are gaining an increasing importance in medicinal, forensic, and environmental analyses. Such devices are based on the detection of supramolecular interactions called hybridizations that occur between complementary oligonucleotides, one linked to a solid surface (the probe), and the other one to be analyzed (the target). This paper focuses on the improvements that hyperbranched and perfectly defined nanomolecules called dendrimers can provide to this methodology. Two main uses of dendrimers for such purpose have been described up to now; either the dendrimer is used as linker between the solid surface and the probe oligonucleotide, or the dendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the first case the dendrimer generally induces a higher loading of probes and an easier hybridization, due to moving away the solid phase. In the second case the high number of localized labels (generally fluorescent) induces an increased sensitivity, allowing the detection of small quantities of biological entities.

  16. Meta-analysis of incomplete microarray studies.

    PubMed

    Zollinger, Alix; Davison, Anthony C; Goldstein, Darlene R

    2015-10-01

    Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information-providing only a ranked list of genes, for example-it is common to reduce all studies to ranked lists prior to combining them. Since this entails a loss of information, we consider a hierarchical Bayes approach to meta-analysis using different types of information from different studies: the full data matrix, summary statistics, or ranks. The model uses an informative prior for the parameter of interest to aid the detection of differentially expressed genes. Simulations show that the new approach can give substantial power gains compared with classical meta-analysis and list aggregation methods. A meta-analysis of 11 published studies with different data types identifies genes known to be involved in ovarian cancer and shows significant enrichment.

  17. Software and tools for microarray data analysis.

    PubMed

    Mehta, Jai Prakash; Rani, Sweta

    2011-01-01

    A typical microarray experiment results in series of images, depending on the experimental design and number of samples. Software analyses the images to obtain the intensity at each spot and quantify the expression for each transcript. This is followed by normalization, and then various data analysis techniques are applied on the data. The whole analysis pipeline requires a large number of software to accurately handle the massive amount of data. Fortunately, there are large number of freely available and commercial software to churn the massive amount of data to manageable sets of differentially expressed genes, functions, and pathways. This chapter describes the software and tools which can be used to analyze the gene expression data right from the image analysis to gene list, ontology, and pathways.

  18. Protein microarray applications: Autoantibody detection and posttranslational modification.

    PubMed

    Atak, Apurva; Mukherjee, Shuvolina; Jain, Rekha; Gupta, Shabarni; Singh, Vedita Anand; Gahoi, Nikita; K P, Manubhai; Srivastava, Sanjeeva

    2016-10-01

    The discovery of DNA microarrays was a major milestone in genomics; however, it could not adequately predict the structure or dynamics of underlying protein entities, which are the ultimate effector molecules in a cell. Protein microarrays allow simultaneous study of thousands of proteins/peptides, and various advancements in array technologies have made this platform suitable for several diagnostic and functional studies. Antibody arrays enable researchers to quantify the abundance of target proteins in biological fluids and assess PTMs by using the antibodies. Protein microarrays have been used to assess protein-protein interactions, protein-ligand interactions, and autoantibody profiling in various disease conditions. Here, we summarize different microarray platforms with focus on its biological and clinical applications in autoantibody profiling and PTM studies. We also enumerate the potential of tissue microarrays to validate findings from protein arrays as well as other approaches, highlighting their significance in proteomics.

  19. DNA microarray-based mutation discovery and genotyping.

    PubMed

    Gresham, David

    2011-01-01

    DNA microarrays provide an efficient means of identifying single-nucleotide polymorphisms (SNPs) in DNA samples and characterizing their frequencies in individual and mixed samples. We have studied the parameters that determine the sensitivity of DNA probes to SNPs and found that the melting temperature (T (m)) of the probe is the primary determinant of probe sensitivity. An isothermal-melting temperature DNA microarray design, in which the T (m) of all probes is tightly distributed, can be implemented by varying the length of DNA probes within a single DNA microarray. I describe guidelines for designing isothermal-melting temperature DNA microarrays and protocols for labeling and hybridizing DNA samples to DNA microarrays for SNP discovery, genotyping, and quantitative determination of allele frequencies in mixed samples.

  20. Image microarrays (IMA): Digital pathology's missing tool

    PubMed Central

    Hipp, Jason; Cheng, Jerome; Pantanowitz, Liron; Hewitt, Stephen; Yagi, Yukako; Monaco, James; Madabhushi, Anant; Rodriguez-canales, Jaime; Hanson, Jeffrey; Roy-Chowdhuri, Sinchita; Filie, Armando C.; Feldman, Michael D.; Tomaszewski, John E.; Shih, Natalie NC.; Brodsky, Victor; Giaccone, Giuseppe; Emmert-Buck, Michael R.; Balis, Ulysses J.

    2011-01-01

    Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. PMID:22200030

  1. Fluorescence detection in (sub-)nanoliter microarrays

    NASA Astrophysics Data System (ADS)

    van den Doel, L. Richard; Vellekoop, Michael J.; Sarro, Pasqualina M.; Picioreanu, S.; Moerman, R.; Frank, J.; van Dedem, G. W. K.; Hjelt, Kari H.; van Vliet, Lucas J.; Young, Ian T.

    1999-06-01

    The goal of our TU Delft interfaculty research program is to develop intelligent molecular diagnostic systems (IMDS) that can analyze liquid samples that contain a variety of biochemical compounds such as those associated with fermentation processes. One specific project within the IMDS program focuses on photon sensors. In order to analyze the liquid samples we use dedicated microarrays. At this stage, these are basically miniaturized micro titre plates. Typical dimensions of a vial are 200 X 200 X 20 micrometer3. These dimensions may be varied and the shape of the vials can be modified with a result that the volume of the vials varies from 0.5 to 1.6 nl. For all experiments, we have used vials with the shape of a truncated pyramid. These vials are fabricated in silicon by a wet etching process. For testing purposes the vials are filled with rhodamine solutions of various concentrations. To avoid evaporation glycerol-water (1:1, v/v) with a viscosity of 8.3 times the viscosity of water is used as solvent. We aim at wide field-of-view imaging at the expense of absolute sensitivity: the field-of-view increases quadratically with decreasing magnification. Small magnification, however, implies low Numerical Aperture (NA). The ability of a microscope objective to collect photons is proportional to the square of the NA. To image the entire microarray we have used an epi-illumination fluorescence microscope equipped with a low magnification (2.5 X/0.075) objective and a scientific CCD camera to integrate the photons emitted from the fluorescing particles in the solutions in the vials. From these experiments we found that for this setup the detection limit is on the order of micromolar concentrations of fluorescing particles. This translates to 108 molecules per vial.

  2. 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

  3. The application of protein microarray assays in psychoneuroimmunology.

    PubMed

    Ayling, K; Bowden, T; Tighe, P; Todd, I; Dilnot, E M; Negm, O H; Fairclough, L; Vedhara, K

    2017-01-01

    Protein microarrays are miniaturized multiplex assays that exhibit many advantages over the commonly used enzyme-linked immunosorbent assay (ELISA). This article aims to introduce protein microarrays to readers of Brain, Behavior, and Immunity and demonstrate its utility and validity for use in psychoneuroimmunological research. As part of an ongoing investigation of psychological and behavioral influences on influenza vaccination responses, we optimized a novel protein microarray to quantify influenza-specific antibody levels in human sera. Reproducibility was assessed by calculating intra- and inter-assay coefficients of variance on serially diluted human IgG concentrations. A random selection of samples was analyzed by microarray and ELISA to establish validity of the assay. For IgG concentrations, intra-assay and inter-assay precision profiles demonstrated a mean coefficient of variance of 6.7% and 11.5% respectively. Significant correlations were observed between microarray and ELISA for all antigens, demonstrating the microarray is a valid alternative to ELISA. Protein microarrays are a highly robust, novel assay method that could be of significant benefit for researchers working in psychoneuroimmunology. They offer high throughput, fewer resources per analyte and can examine concurrent neuro-immune-endocrine mechanisms.

  4. 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

  5. Protein Microarrays with Novel Microfluidic Methods: Current Advances.

    PubMed

    Dixit, Chandra K; Aguirre, Gerson R

    2014-07-01

    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.

  6. 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.

  7. Microarrays (DNA chips) for the classroom laboratory.

    PubMed

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

    2006-09-01

    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 adaptation is the use of a simulated cDNA target. The low density DNA array we discuss here was used to demonstrate differential expression of several Arabidopsis thaliana genes related to photosynthesis and photomorphogenesis. The methods we present here can be used with any biological organism whose sequence is known. Furthermore, these methods can be adapted to exhibit a variety of differential gene expression patterns under different experimental conditions. The materials and tools we discuss have been applied in classrooms at West High School in Madison, WI. We have also shared these materials with high school teachers attending professional development courses at the University of Wisconsin-Madison.

  8. Tissue Microarray Analysis Applied to Bone Diagenesis

    PubMed Central

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

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered. PMID:28051148

  9. Cell microarrays on photochemically modified polytetrafluoroethylene.

    PubMed

    Mikulikova, Regina; Moritz, Sieglinde; Gumpenberger, Thomas; Olbrich, Michael; Romanin, Christoph; Bacakova, Lucie; Svorcik, Vaclav; Heitz, Johannes

    2005-09-01

    We studied the adhesion, proliferation, and viability of human umbilical vein endothelial cells (HUVEC) and human embryonic kidney cells (HEK) on modified spots at polytetrafluoroethylene (PTFE) surfaces. The viability of the cells was assessed using an aqueous non-radioactive cell proliferation assay. Round spots with a diameter of 100 microm were modified by exposure to the ultraviolet (UV) light of a Xe(2)(*)-excimer lamp at a wavelength of 172 nm in an ammonia atmosphere employing a contact mask. The spots were arranged in a quadratic pattern with 300 microm center-to-center spot distances. With optimized degree of modification, the cells adhered to the modified spots with a high degree of selectivity (70-90%). The adhered cells on the spots proliferated. This resulted in a significant increase in the number of adhering HUVECS or HEK cells after seeding and in the formation of confluent cell clusters after 3-4 days. With higher start seeding density, these clusters were not only confined to the modified spots but extended several micrometer to the neighborhood. The high potential of the cell microarrays for gene analysis in living cells was demonstrated with HEK cells transfected by yellow fluorescent protein (YFP).

  10. Antibody microarrays for native toxin detection.

    PubMed

    Rucker, Victor C; Havenstrite, Karen L; Herr, Amy E

    2005-04-15

    We have developed antibody-based microarray techniques for the multiplexed detection of cholera toxin beta-subunit, diphtheria toxin, anthrax lethal factor and protective antigen, Staphylococcus aureus enterotoxin B, and tetanus toxin C fragment in spiked samples. Two detection schemes were investigated: (i) a direct assay in which fluorescently labeled toxins were captured directly by the antibody array and (ii) a competition assay that employed unlabeled toxins as reporters for the quantification of native toxin in solution. In the direct assay, fluorescence measured at each array element is correlated with labeled toxin concentration to yield baseline binding information (Langmuir isotherms and affinity constants). Extending from the direct assay, the competition assay yields information on the presence, identity, and concentration of toxins. A significant advantage of the competition assay over reported profiling assays is the minimal sample preparation required prior to analysis because the competition assay obviates the need to fluorescently label native proteins in the sample of interest. Sigmoidal calibration curves and detection limits were established for both assay formats. Although the sensitivity of the direct assay is superior to that of the competition assay, detection limits for unmodified toxins in the competition assay are comparable to values reported previously for sandwich-format immunoassays of antibodies arrayed on planar substrates. As a demonstration of the potential of the competition assay for unlabeled toxin detection, we conclude with a straightforward multiplexed assay for the differentiation and identification of both native S. aureus enterotoxin B and tetanus toxin C fragment in spiked dilute serum samples.

  11. Microarray analysis of DNA replication timing.

    PubMed

    Karnani, Neerja; Taylor, Christopher M; Dutta, Anindya

    2009-01-01

    Although all of the DNA in an eukaryotic cell replicates during the S-phase of cell cycle, there is a significant difference in the actual time in S-phase when a given chromosomal segment replicates. Methods are described here for generation of high-resolution temporal maps of DNA replication in synchronized human cells. This method does not require amplification of DNA before microarray hybridization and so avoids errors introduced during PCR. A major advantage of using this procedure is that it facilitates finer dissection of replication time in S-phase. Also, it helps delineate chromosomal regions that undergo biallelic or asynchronous replication, which otherwise are difficult to detect at a genome-wide scale by existing methods. The continuous TR50 (time of completion of 50% replication) maps of replication across chromosomal segments identify regions that undergo acute transitions in replication timing. These transition zones can play a significant role in identifying insulators that separate chromosomal domains with different chromatin modifications.

  12. Transcriptome Analysis of Zebrafish Embryogenesis Using Microarrays

    PubMed Central

    Mathavan, Sinnakaruppan; Lee, Serene G. P; Mak, Alicia; Miller, Lance D; Murthy, Karuturi Radha Krishna; Govindarajan, Kunde R; Tong, Yan; Wu, Yi Lian; Lam, Siew Hong; Yang, Henry; Ruan, Yijun; Korzh, Vladimir; Gong, Zhiyuan; Liu, Edison T; Lufkin, Thomas

    2005-01-01

    Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html). PMID:16132083

  13. Cell-Based Microarrays for In Vitro Toxicology.

    PubMed

    Wegener, Joachim

    2015-01-01

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

  14. Empirical evaluation of oligonucleotide probe selection for DNA microarrays.

    PubMed

    Mulle, Jennifer G; Patel, Viren C; Warren, Stephen T; Hegde, Madhuri R; Cutler, David J; Zwick, Michael E

    2010-03-29

    DNA-based microarrays are increasingly central to biomedical research. Selecting oligonucleotide sequences that will behave consistently across experiments is essential to the design, production and performance of DNA microarrays. Here our aim was to improve on probe design parameters by empirically and systematically evaluating probe performance in a multivariate context. We used experimental data from 19 array CGH hybridizations to assess the probe performance of 385,474 probes tiled in the Duchenne muscular dystrophy (DMD) region of the X chromosome. Our results demonstrate that probe melting temperature, single nucleotide polymorphisms (SNPs), and homocytosine motifs all have a strong effect on probe behavior. These findings, when incorporated into future microarray probe selection algorithms, may improve microarray performance for a wide variety of applications.

  15. Cell-Based Microarrays for In Vitro Toxicology

    NASA Astrophysics Data System (ADS)

    Wegener, Joachim

    2015-07-01

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

  16. 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

  17. DNA Microarrays for Aptamer Identification and Structural Characterization

    DTIC Science & Technology

    2012-09-01

    AFRL-RH-WP-TR-2013-0130 DNA MICROARRAYS FOR APTAMER IDENTIFICATION AND STRUCTURAL CHARACTERIZATION Jennifer A. Martin National Research Council...Interim September 2010 to September 2012 4. TITLE AND SUBTITLE DNA Microarrays for Aptamer Identification and Structural Characterization 5a. CONTRACT... Aptamers are ideal recognition elements, but integrating aptamers onto a sensor platform has two main challenges: (1) aptamers are selected in

  18. Celsius: a community resource for Affymetrix microarray data.

    PubMed

    Day, Allen; Carlson, Marc R J; Dong, Jun; O'Connor, Brian D; Nelson, Stanley F

    2007-01-01

    Celsius is a data warehousing system to aggregate Affymetrix CEL files and associated metadata. It provides mechanisms for importing, storing, querying, and exporting large volumes of primary and pre-processed microarray data. Celsius contains ten billion assay measurements and affiliated metadata. It is the largest publicly available source of Affymetrix microarray data, and through sheer volume it allows a sophisticated, broad view of transcription that has not previously been possible.

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

    PubMed

    Lodha, T D; Basak, J

    2012-01-01

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

  20. Analysis of Microarray and RNA-seq Expression Profiling Data.

    PubMed

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Gene expression profiling refers to the simultaneous measurement of the expression levels of a large number of genes (often all genes in a genome), typically in multiple experiments spanning a variety of cell types, treatments, or environmental conditions. Expression profiling is accomplished by assaying mRNA levels with microarrays or next-generation sequencing technologies (RNA-seq). This introduction describes normalization and analysis of data generated from microarray or RNA-seq experiments.

  1. Multipathogen oligonucleotide microarray for environmental and biodefense applications.

    PubMed

    Sergeev, Nikolay; Distler, Margaret; Courtney, Shannon; Al-Khaldi, Sufian F; Volokhov, Dmitriy; Chizhikov, Vladimir; Rasooly, Avraham

    2004-11-01

    Food-borne pathogens are a major health problem. The large and diverse number of microbial pathogens and their virulence factors has fueled interest in technologies capable of detecting multiple pathogens and multiple virulence factors simultaneously. Some of these pathogens and their toxins have potential use as bioweapons. DNA microarray technology allows the simultaneous analysis of thousands of sequences of DNA in a relatively short time, making it appropriate for biodefense and for public health uses. This paper describes methods for using DNA microarrays to detect and analyze microbial pathogens. The FDA-1 microarray was developed for the simultaneous detection of several food-borne pathogens and their virulence factors including Listeria spp., Campylobacter spp., Staphylococcus aureus enterotoxin genes and Clostridium perfringens toxin genes. Three elements were incorporated to increase confidence in the microarray detection system: redundancy of genes, redundancy of oligonucleotide probes (oligoprobes) for a specific gene, and quality control oligoprobes to monitor array spotting and target DNA hybridization. These elements enhance the reliability of detection and reduce the chance of erroneous results due to the genetic variability of microbes or technical problems with the microarray. The results presented demonstrate the potential of oligonucleotide microarrays for detection of environmental and biodefense relevant microbial pathogens.

  2. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

    PubMed Central

    Flannery, Andrea; Gerlach, Jared Q.; Joshi, Lokesh; Kilcoyne, Michelle

    2015-01-01

    Carbohydrates play a crucial role in host-microorganism interactions and many host glycoconjugates are receptors or co-receptors for microbial binding. Host glycosylation varies with species and location in the body, and this contributes to species specificity and tropism of commensal and pathogenic bacteria. Additionally, bacterial glycosylation is often the first bacterial molecular species encountered and responded to by the host system. Accordingly, characterising and identifying the exact structures involved in these critical interactions is an important priority in deciphering microbial pathogenesis. Carbohydrate-based microarray platforms have been an underused tool for screening bacterial interactions with specific carbohydrate structures, but they are growing in popularity in recent years. In this review, we discuss carbohydrate-based microarrays that have been profiled with whole bacteria, recombinantly expressed adhesins or serum antibodies. Three main types of carbohydrate-based microarray platform are considered; (i) conventional carbohydrate or glycan microarrays; (ii) whole mucin microarrays; and (iii) microarrays constructed from bacterial polysaccharides or their components. Determining the nature of the interactions between bacteria and host can help clarify the molecular mechanisms of carbohydrate-mediated interactions in microbial pathogenesis, infectious disease and host immune response and may lead to new strategies to boost therapeutic treatments. PMID:27600247

  3. A comparative analysis of DNA barcode microarray feature size

    PubMed Central

    Ammar, Ron; Smith, Andrew M; Heisler, Lawrence E; Giaever, Guri; Nislow, Corey

    2009-01-01

    Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO) collection used for screens of pooled yeast (Saccharomyces cerevisiae) deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density. PMID:19825181

  4. [Future aspect of cytogenetics using chromosomal microarray testing].

    PubMed

    Yamamoto, Toshiyuki

    2014-01-01

    With the advent of chromosomal microarray testing, microdeletions can be detected in approximately 17% of cases without any abnormality detectable by conventional karyotyping. Structural abnormalities frequently occur at the terminal regions of the chromosomes, called the subtelomeres, because of their structural features. Subtelomere deletions and unbalanced translocations between chromosomes are frequently observed. However, most microdeletions observed by chromosomal microarray testing are microdeletions in intermediate regions. Submicroscopic duplications reciprocal to the deletions seen in the microdeletion syndromes, such as the 16p11.2 region, have been revealed. Discovery of multi-hit chromosomal abnormalities is another achievement by chromosomal microarray testing. Chromosomal microarray testing can determine the ranges of chromosomal structural abnormalities at a DNA level. Thus, the effects of a specific gene deletion on symptoms can be revealed by comparing multiple patients with slightly different chromosomal deletions in the same region (genotype/phenotype correlation). Chromosomal microarray testing comprehensively determines the genomic copy number, but reveals no secondary structure, requiring verification by cytogenetics using FISH. To interpret the results, familial or benign copy number variations (CNV) should be taken into consideration. An appropriate system should be constructed to provide opportunities of chromosomal microarray testing for patients who need this examination and to facilitate the use of results for medical practice.

  5. Evaluating concentration estimation errors in ELISA microarray experiments

    SciTech Connect

    Daly, Don S.; White, Amanda M.; Varnum, Susan M.; Anderson, Kevin K.; Zangar, Richard C.

    2005-01-26

    Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Although propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.

  6. 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.

  7. DNA Microarray Characterization of Pathogens Associated with Sexually Transmitted Diseases

    PubMed Central

    Cao, Boyang; Wang, Suwei; Tian, Zhenyang; Hu, Pinliang; Feng, Lu; Wang, Lei

    2015-01-01

    This study established a multiplex PCR-based microarray to detect simultaneously a diverse panel of 17 sexually transmitted diseases (STDs)-associated pathogens including Neisseria gonorrhoeae, Chlamydia trachomatis, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma, Herpes simplex virus (HSV) types 1 and 2, and Human papillomavirus (HPV) types 6, 11, 16, 18, 31, 33, 35, 39, 54 and 58. The target genes are 16S rRNA gene for N. gonorrhoeae, M. genitalium, M. hominism, and Ureaplasma, the major outer membrane protein gene (ompA) for C. trachomatis, the glycoprotein B gene (gB) for HSV; and the L1 gene for HPV. A total of 34 probes were selected for the microarray including 31 specific probes, one as positive control, one as negative control, and one as positional control probe for printing reference. The microarray is specific as the commensal and pathogenic microbes (and closely related organisms) in the genitourinary tract did not cross-react with the microarray probes. The microarray is 10 times more sensitive than that of the multiplex PCR. Among the 158 suspected HPV specimens examined, the microarray showed that 49 samples contained HPV, 21 samples contained Ureaplasma, 15 contained M. hominis, four contained C. trachomatis, and one contained N. gonorrhoeae. This work reports the development of the first high through-put detection system that identifies common pathogens associated with STDs from clinical samples, and paves the way for establishing a time-saving, accurate and high-throughput diagnostic tool for STDs. PMID:26208181

  8. DNA Microarray Characterization of Pathogens Associated with Sexually Transmitted Diseases.

    PubMed

    Cao, Boyang; Wang, Suwei; Tian, Zhenyang; Hu, Pinliang; Feng, Lu; Wang, Lei

    2015-01-01

    This study established a multiplex PCR-based microarray to detect simultaneously a diverse panel of 17 sexually transmitted diseases (STDs)-associated pathogens including Neisseria gonorrhoeae, Chlamydia trachomatis, Mycoplasma genitalium, Mycoplasma hominis, Ureaplasma, Herpes simplex virus (HSV) types 1 and 2, and Human papillomavirus (HPV) types 6, 11, 16, 18, 31, 33, 35, 39, 54 and 58. The target genes are 16S rRNA gene for N. gonorrhoeae, M. genitalium, M. hominism, and Ureaplasma, the major outer membrane protein gene (ompA) for C. trachomatis, the glycoprotein B gene (gB) for HSV; and the L1 gene for HPV. A total of 34 probes were selected for the microarray including 31 specific probes, one as positive control, one as negative control, and one as positional control probe for printing reference. The microarray is specific as the commensal and pathogenic microbes (and closely related organisms) in the genitourinary tract did not cross-react with the microarray probes. The microarray is 10 times more sensitive than that of the multiplex PCR. Among the 158 suspected HPV specimens examined, the microarray showed that 49 samples contained HPV, 21 samples contained Ureaplasma, 15 contained M. hominis, four contained C. trachomatis, and one contained N. gonorrhoeae. This work reports the development of the first high through-put detection system that identifies common pathogens associated with STDs from clinical samples, and paves the way for establishing a time-saving, accurate and high-throughput diagnostic tool for STDs.

  9. Microarray oligonucleotide probe designer (MOPeD): A web service.

    PubMed

    Patel, Viren C; Mondal, Kajari; Shetty, Amol Carl; Horner, Vanessa L; Bedoyan, Jirair K; Martin, Donna; Caspary, Tamara; Cutler, David J; Zwick, Michael E

    2010-11-01

    Methods of genomic selection that combine high-density oligonucleotide microarrays with next-generation DNA sequencing allow investigators to characterize genomic variation in selected portions of complex eukaryotic genomes. Yet choosing which specific oligonucleotides to be use can pose a major technical challenge. To address this issue, we have developed a software package called MOPeD (Microarray Oligonucleotide Probe Designer), which automates the process of designing genomic selection microarrays. This web-based software allows individual investigators to design custom genomic selection microarrays optimized for synthesis with Roche NimbleGen's maskless photolithography. Design parameters include uniqueness of the probe sequences, melting temperature, hairpin formation, and the presence of single nucleotide polymorphisms. We generated probe databases for the human, mouse, and rhesus macaque genomes and conducted experimental validation of MOPeD-designed microarrays in human samples by sequencing the human X chromosome exome, where relevant sequence metrics indicated superior performance relative to a microarray designed by the Roche NimbleGen proprietary algorithm. We also performed validation in the mouse to identify known mutations contained within a 487-kb region from mouse chromosome 16, the mouse chromosome 16 exome (1.7 Mb), and the mouse chromosome 12 exome (3.3 Mb). Our results suggest that the open source MOPeD software package and website (http://moped.genetics.emory.edu/) will make a valuable resource for investigators in their sequence-based studies of complex eukaryotic genomes.

  10. 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

  11. Studies of patterned surfaces for biological microarrays

    NASA Astrophysics Data System (ADS)

    Gillmor, Susan Dale

    Over the past 10 years, biological microarrays have developed into an invaluable tool for genetic and protein research. The task to draw meaningful conclusions between variations of genes and their expression requires millions of comparisons between standard and stressed samples, usually the cDNA, RNA, or proteins within cells. For such a project, high-information-density, highly pure arrays are required. In fabricating an array on a uniform or an unpatterned substrate, droplets of solution, if placed too closely, can bleed into each other and can cross-contaminate several array sites. Therefore, a uniform surface limits the density of droplets that can be placed to create an array. When the surface is patterned with a barrier between the droplets, then the density of array sites can be significantly larger (uniform surface, ˜200--500mum center-to-center; patterned surface, 100mum center-to-center and less with present loading technology). We have explored the patterning of surfaces to construct biological microarrays, via altering the surface chemically to create array sites with gold-thiol chemistry, and via a template placed on the surface to outline the elements. In the template strategy, we have investigated poly(dimethyl siloxane) (PDMS) films (5--10mum) with holes in a regular array. However, the hydrophobic PDMS repels water to such an extent that the droplets do not wet the template and cannot travel down the wall of the PDMS hole to interact with the surface. As a consequence, if not accurately placed in the array sites, they also do not load into the holes to form filled features. Our current studies focus on altering the surface of the PDMS to allow the droplets to fall into the PDMS holes. To alter the surface and not the bulk, we have experimented with plasma chemistry. To create a temporary contact angle change, oxygen plasma has been employed. However, the PDMS recovers and reverts to it characteristically hydrophobic surface. When we expose PDMS

  12. Photopatterning of Hydrogel Microarrays in Closed Microchips.

    PubMed

    Gumuscu, Burcu; Bomer, Johan G; van den Berg, Albert; Eijkel, Jan C T

    2015-12-14

    To date, optical lithography has been extensively used for in situ patterning of hydrogel structures in a scale range from hundreds of microns to a few millimeters. The two main limitations which prevent smaller feature sizes of hydrogel structures are (1) the upper glass layer of a microchip maintains a large spacing (typically 525 μm) between the photomask and hydrogel precursor, leading to diffraction of UV light at the edges of mask patterns, (2) diffusion of free radicals and monomers results in irregular polymerization near the illumination interface. In this work, we present a simple approach to enable the use of optical lithography to fabricate hydrogel arrays with a minimum feature size of 4 μm inside closed microchips. To achieve this, we combined two different techniques. First, the upper glass layer of the microchip was thinned by mechanical polishing to reduce the spacing between the photomask and hydrogel precursor, and thereby the diffraction of UV light at the edges of mask patterns. The polishing process reduces the upper layer thickness from ∼525 to ∼100 μm, and the mean surface roughness from 20 to 3 nm. Second, we developed an intermittent illumination technique consisting of short illumination periods followed by relatively longer dark periods, which decrease the diffusion of monomers. Combination of these two methods allows for fabrication of 0.4 × 10(6) sub-10 μm sized hydrogel patterns over large areas (cm(2)) with high reproducibility (∼98.5% patterning success). The patterning method is tested with two different types of photopolymerizing hydrogels: polyacrylamide and polyethylene glycol diacrylate. This method enables in situ fabrication of well-defined hydrogel patterns and presents a simple approach to fabricate 3-D hydrogel matrices for biomolecule separation, biosensing, tissue engineering, and immobilized protein microarray applications.

  13. DNA Microarray Detection of 18 Important Human Blood Protozoan Species

    PubMed Central

    Chen, Jun-Hu; Feng, Xin-Yu; Chen, Shao-Hong; Cai, Yu-Chun; Lu, Yan; Zhou, Xiao-Nong; Chen, Jia-Xu; Hu, Wei

    2016-01-01

    Background Accurate detection of blood protozoa from clinical samples is important for diagnosis, treatment and control of related diseases. In this preliminary study, a novel DNA microarray system was assessed for the detection of Plasmodium, Leishmania, Trypanosoma, Toxoplasma gondii and Babesia in humans, animals, and vectors, in comparison with microscopy and PCR data. Developing a rapid, simple, and convenient detection method for protozoan detection is an urgent need. Methodology/Principal Findings The microarray assay simultaneously identified 18 species of common blood protozoa based on the differences in respective target genes. A total of 20 specific primer pairs and 107 microarray probes were selected according to conserved regions which were designed to identify 18 species in 5 blood protozoan genera. The positive detection rate of the microarray assay was 91.78% (402/438). Sensitivity and specificity for blood protozoan detection ranged from 82.4% (95%CI: 65.9% ~ 98.8%) to 100.0% and 95.1% (95%CI: 93.2% ~ 97.0%) to 100.0%, respectively. Positive predictive value (PPV) and negative predictive value (NPV) ranged from 20.0% (95%CI: 2.5% ~ 37.5%) to 100.0% and 96.8% (95%CI: 95.0% ~ 98.6%) to 100.0%, respectively. Youden index varied from 0.82 to 0.98. The detection limit of the DNA microarrays ranged from 200 to 500 copies/reaction, similar to PCR findings. The concordance rate between microarray data and DNA sequencing results was 100%. Conclusions/Significance Overall, the newly developed microarray platform provides a convenient, highly accurate, and reliable clinical assay for the determination of blood protozoan species. PMID:27911895

  14. A critical comparison of protein microarray fabrication technologies.

    PubMed

    Romanov, Valentin; Davidoff, S Nikki; Miles, Adam R; Grainger, David W; Gale, Bruce K; Brooks, Benjamin D

    2014-03-21

    Of the diverse analytical tools used in proteomics, protein microarrays possess the greatest potential for providing fundamental information on protein, ligand, analyte, receptor, and antibody affinity-based interactions, binding partners and high-throughput analysis. Microarrays have been used to develop tools for drug screening, disease diagnosis, biochemical pathway mapping, protein-protein interaction analysis, vaccine development, enzyme-substrate profiling, and immuno-profiling. While the promise of the technology is intriguing, it is yet to be realized. Many challenges remain to be addressed to allow these methods to meet technical and research expectations, provide reliable assay answers, and to reliably diversify their capabilities. Critical issues include: (1) inconsistent printed microspot morphologies and uniformities, (2) low signal-to-noise ratios due to factors such as complex surface capture protocols, contamination, and static or no-flow mass transport conditions, (3) inconsistent quantification of captured signal due to spot uniformity issues, (4) non-optimal protocol conditions such as pH, temperature, drying that promote variability in assay kinetics, and lastly (5) poor protein (e.g., antibody) printing, storage, or shelf-life compatibility with common microarray assay fabrication methods, directly related to microarray protocols. Conventional printing approaches, including contact (e.g., quill and solid pin), non-contact (e.g., piezo and inkjet), microfluidics-based, microstamping, lithography, and cell-free protein expression microarrays, have all been used with varying degrees of success with figures of merit often defined arbitrarily without comparisons to standards, or analytical or fiduciary controls. Many microarray performance reports use bench top analyte preparations lacking real-world relevance, akin to "fishing in a barrel", for proof of concept and determinations of figures of merit. This review critiques current protein

  15. Microarray studies of psychostimulant-induced changes in gene expression.

    PubMed

    Yuferov, Vadim; Nielsen, David; Butelman, Eduardo; Kreek, Mary Jeanne

    2005-03-01

    Alterations in the expression of multiple genes in many brain regions are likely to contribute to psychostimulant-induced behaviours. Microarray technology provides a powerful tool for the simultaneous interrogation of gene expression levels of a large number of genes. Several recent experimental studies, reviewed here, demonstrate the power, limitations and progress of microarray technology in the field of psychostimulant addiction. These studies vary in the paradigms of cocaine or amphetamine administration, drug doses, route and also mode of administration, duration of treatment, animal species, brain regions studied and time of tissue collection after final drug administration. The studies also utilize different microarray platforms and statistical techniques for analysis of differentially expressed genes. These variables influence substantially the results of these studies. It is clear that current microarray techniques cannot detect small changes reliably in gene expression of genes with low expression levels, including functionally significant changes in components of major neurotransmission systems such as glutamate, dopamine, opioid and GABA receptors, especially those that may occur after chronic drug administration or drug withdrawal. However, the microarray studies reviewed here showed cocaine- or amphetamine-induced alterations in the expression of numerous genes involved in the modulation of neuronal growth, cytoskeletal structures, synaptogenesis, signal transduction, apoptosis and cell metabolism. Application of laser capture microdissection and single-cell cDNA amplification may greatly enhance microarray studies of gene expression profiling. The combination of rapidly evolving microarray technology with established methods of neuroscience, molecular biology and genetics, as well as appropriate behavioural models of drug reinforcement, may provide a productive approach for delineating the neurobiological underpinnings of drug responses that lead to

  16. Robust and efficient synthetic method for forming DNA microarrays.

    PubMed

    Dolan, P L; Wu, Y; Ista, L K; Metzenberg, R L; Nelson, M A; Lopez, G P

    2001-11-01

    The field of DNA microarray technology has necessitated the cooperative efforts of interdisciplinary scientific teams to achieve its primary goal of rapidly measuring global gene expression patterns. A collaborative effort was established to produce a chemically reactive surface on glass slide substrates to which unmodified DNA will covalently bind for improvement of cDNA microarray technology. Using the p-aminophenyl trimethoxysilane (ATMS)/diazotization chemistry that was developed, microarrays were fabricated and analyzed. This immobilization method produced uniform spots containing equivalent or greater amounts of DNA than commercially available immobilization techniques. In addition, hybridization analyses of microarrays made with ATMS/diazotization chemistry showed very sensitive detection of the target sequence, two to three orders of magnitude more sensitive than the commercial chemistries. Repeated stripping and re-hybridization of these slides showed that DNA loss was minimal, allowing multiple rounds of hybridization. Thus, the ATMS/diazotization chemistry facilitated covalent binding of unmodified DNA, and the reusable microarrays that were produced showed enhanced levels of hybridization and very low background fluorescence.

  17. Revealing Transcriptome Landscape of Mouse Spermatogonial Cells by Tiling Microarray

    PubMed Central

    Lee, Tin-Lap.; Rennert, Owen M.; Chan, Wai-Yee.

    2014-01-01

    Summary Spermatogenesis is a highly regulated developmental process by which spermatogonia develop into mature spermatozoa. This process involves many testis- or male germ cell-specific events through tightly regulated gene expression programs. In the past decade the advent of microarray technologies has allowed functional genomic studies of male germ cell development, resulting in the identification of genes governing various processes. A major limitation with conventional gene expression microarray is that there is a bias from gene probe design. The gene probes for expression microarrays are usually represented by a small number probes located at the 3’ end of a transcirpt. Tiling microarrays eliminate such issue by interrogating the genome in an unbiased fashion through probes tiled for the entire genome. These arrays provide a higher genomic resolution and allow identification of novel transcripts. To reveal the complexity of the genomic landscape of developing male germ cells, we applied tiling microarray to evaluate the transcriptome in spermatogonial cells. Over 50% of the mouse and rat genome are expressed during testicular development. More than 47% of transcripts are uncharacterized. The results suggested the transcription machinery in spermaotogonial cells are more complex than previously envisioned. PMID:22144238

  18. Do DNA Microarrays Tell the Story of Gene Expression?

    PubMed Central

    Rosenfeld, Simon

    2010-01-01

    Poor reproducibility of microarray measurements is a major obstacle to their application as an instrument for clinical diagnostics. In this paper, several aspects of poor reproducibility are analyzed. All of them belong to the category of interpretive weaknesses of DNA microarray technology. First, the attention is drawn to the fact that absence of the information regarding post-transcriptional mRNA stability makes it impossible to evaluate the level of gene activity from the relative mRNA abundances, the quantities available from microarray measurements. Second, irreducible intracellular variability with persistent patterns of stochasticity and burstiness put natural limits to reproducibility. Third, strong interactions within intracellular biomolecular networks make it highly problematic to build a bridge between transcription rates of individual genes and structural fidelity of their genetic codes. For these reasons, the microarray measurements of relative mRNA abundances are more appropriate in laboratory settings as a tool for scientific research, hypotheses generating and producing the leads for subsequent validation through more sophisticated technologies. As to clinical settings, where firm conclusive diagnoses, not the leads for further experimentation, are required, microarrays still have a long way to go until they become a reliable instrument in patient-related decision making. PMID:20628535

  19. PNA microarrays for hybridisation of unlabelled DNA samples

    PubMed Central

    Brandt, Ole; Feldner, Julia; Stephan, Achim; Schröder, Markus; Schnölzer, Martina; Arlinghaus, Heinrich F.; Hoheisel, Jörg D.; Jacob, Anette

    2003-01-01

    Several strategies have been developed for the production of peptide nucleic acid (PNA) microarrays by parallel probe synthesis and selective coupling of full-length molecules. Such microarrays were used for direct detection of the hybridisation of unlabelled DNA by time-of-flight secondary ion mass spectrometry. PNAs were synthesised by an automated process on filter-bottom microtitre plates. The resulting molecules were released from the solid support and attached without any purification to microarray surfaces via the terminal amino group itself or via modifications, which had been chemically introduced during synthesis. Thus, only full-length PNA oligomers were attached whereas truncated molecules, produced during synthesis because of incomplete condensation reactions, did not bind. Different surface chemistries and fitting modifications of the PNA terminus were tested. For an examination of coupling selectivity, bound PNAs were cleaved off microarray surfaces and analysed by MALDI-TOF mass spectrometry. Additionally, hybridisation experiments were performed to compare the attachment chemistries, with fully acetylated PNAs spotted as controls. Upon hybridisation of unlabelled DNA to such microarrays, binding events could be detected by visualisation of phosphates, which are an integral part of nucleic acids but missing entirely in PNA probes. Overall best results in terms of selectivity and sensitivity were obtained with thiol-modified PNAs on maleimide surfaces. PMID:14500847

  20. Optimized T7 amplification system for microarray analysis.

    PubMed

    Pabón, C; Modrusan, Z; Ruvolo, M V; Coleman, I M; Daniel, S; Yue, H; Arnold, L J

    2001-10-01

    Glass cDNA microarray technologies offer a highly parallel approach for profiling expressed gene sequences in disease-relevant tissues. However, standard hybridization and detection protocols are insufficient for milligram quantities of tissue, such as those derived from needle biopsies. Amplification systems utilizing T7 RNA polymerase can provide multiple cRNA copies from mRNA transcripts, permitting microarray studies with reduced sample inputs. Here, we describe an optimized T7-based amplification system for microarray analysis that yields between 200- and 700-fold amplification. This system was evaluated with both mRNA and total RNA samples and provided microarray sensitivity and precision that are comparable to our standard production process without amplification. The size distributions of amplified cRNA ranged from 200 bp to 4 kb and were similar to original mRNA profiles. These amplified cRNA samples were fluorescently labeled by reverse transcription and hybridized to microarrays comprising approximately 10,000 cDNA targets using a dual-channel format. Replicate hybridization experiments were conducted with the same and different tissues in each channel to assess the sensitivity and precision of differential expression ratios. Statistical analysis of differential expression ratios showed the lower limit of detection to be about 2-fold within and between amplified data sets, and about 3-fold when comparing amplified data to unamplified data (99.5% confidence).

  1. A facile method for the construction of oligonucleotide microarrays.

    PubMed

    Sethi, Dalip; Kumar, A; Gupta, K C; Kumar, P

    2008-11-19

    In recent years, the oligonucleotide-based microarray technique has emerged as a powerful and promising tool for various molecular biological studies. Here, a facile protocol for the construction of an oligonucleotide microarray is demonstrated that involves immobilization of oligonucleotide-trimethoxysilyl conjugates onto virgin glass microslides. The projected immobilization strategy reflects high immobilization efficiency ( approximately 36-40%) and signal-to-noise ratio ( approximately 98), and hybridization efficiency ( approximately 32-35%). Using the proposed protocol, aminoalkyl, mercaptoalkyl, and phosphorylated oligonucleotides were immobilized onto virgin glass microslides. Briefly, modified oligonucleotides were reacted first with 3-glycidyloxypropyltriethoxysilane (GOPTS), and subsequently, the resultant conjugates were directly immobilized onto the virgin glass surface by making use of silanization chemistry. The constructed microarrays were then used for discrimination of base mismatches. On subjecting to different pH and thermal conditions, the microarray showed sufficient stability. Application of this chemistry to manufacture oligonucleotide probe-based microarrays for detection of bacterial meningitis is demonstrated. Single-step reaction for the formation of conjugates with the commercially available reagent (GOPTS), omission of capping step and surface modification, and efficient immobilization of oligonucleotides onto the virgin glass surface are the key features of the proposed strategy.

  2. WebArray: an online platform for microarray data analysis

    PubMed Central

    Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

    2005-01-01

    Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

  3. Identification of immunodominant antigens of Chlamydia trachomatis using proteome microarrays

    PubMed Central

    Molina, Douglas M.; Pal, Sukumar; Kayala, Mathew A.; Teng, Andy; Kim, Paul J.; Baldi, Pierre; Felgner, Philip L.; Liang, Xiaowu; de la Maza, Luis M.

    2011-01-01

    Chlamydia trachomatis is the most common bacterial sexually transmitted pathogen in the world. In order to control this infection, there is an urgent need to formulate a vaccine. Identification of protective antigens is required to implement a subunit vaccine. To identify potential antigen vaccine candidates, three strains of mice, BALB/c, C3H/HeN and C57BL/6, were inoculated with live and inactivated C. trachomatis mouse pneumonitis (MoPn) by different routes of immunization. Using a protein microarray, serum samples collected after immunization were tested for the presence of antibodies against specific chlamydial antigens. A total of 225 open reading frames (ORF) of the C. trachomatis genome were cloned, expressed, and printed in the microarray. Using this protein microarray, a total of seven C. trachomatis dominant antigens were identified (TC0052, TC0189, TC0582, TC0660, TC0726, TC0816 and, TC0828) as recognized by IgG antibodies from all three strains of animals after immunization. In addition, the microarray was probed to determine if the antibody response exhibited a Th1 or Th2 bias. Animals immunized with live organisms mounted a predominant Th1 response against most of the chlamydial antigens while mice immunized with inactivated Chlamydia mounted a Th2-biased response. In conclusion, using a high throughput protein microarray we have identified a set of novel proteins that can be tested for their ability to protect against a chlamydial infection. PMID:20044059

  4. Polymer microfluidic chip for online monitoring of microarray hybridizations.

    PubMed

    Noerholm, Mikkel; Bruus, Henrik; Jakobsen, Mogens H; Telleman, Pieter; Ramsing, Niels B

    2004-02-01

    A disposable single use polymer microfluidics chip has been developed and manufactured by micro injection molding. The chip has the same outer dimensions as a standard microscope slide (25 x 76 x 1.1 mm) and is designed to be compatible with existing microscope slide handling equipment like microarray scanners. The chip contains an inlet, a 10 microL hybridization chamber capable of holding a 1000 spot array, a waste chamber and a vent to allow air to escape when sample is injected. The hybridization chamber ensures highly homogeneous hybridization conditions across the microarray. We describe the use of this chip in a flexible setup with fluorescence based detection, temperature control and liquid handling by computer controlled syringe pumps. The chip and the setup presented in this article provide a powerful tool for highly parallel studies of kinetics and thermodynamics of duplex formation in DNA microarrays. The experimental setup presented in this article enables the on-chip microarray to be hybridized and monitored at several different stringency conditions during a single assay. The performance of the chip and the setup is demonstrated by on-line measurements of a hybridization of a DNA target solution to a microarray. A presented numerical model indicates that the hybridization process in microfluidic hybridization assays is diffusion limited, due to the low values of the diffusion coefficients D of the DNA and RNA molecules involved.

  5. A Versatile Microarray Platform for Capturing Rare Cells

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  6. Short time-series microarray analysis: Methods and challenges

    PubMed Central

    Wang, Xuewei; Wu, Ming; Li, Zheng; Chan, Christina

    2008-01-01

    The detection and analysis of steady-state gene expression has become routine. Time-series microarrays are of growing interest to systems biologists for deciphering the dynamic nature and complex regulation of biosystems. Most temporal microarray data only contain a limited number of time points, giving rise to short-time-series data, which imposes challenges for traditional methods of extracting meaningful information. To obtain useful information from the wealth of short-time series data requires addressing the problems that arise due to limited sampling. Current efforts have shown promise in improving the analysis of short time-series microarray data, although challenges remain. This commentary addresses recent advances in methods for short-time series analysis including simplification-based approaches and the integration of multi-source information. Nevertheless, further studies and development of computational methods are needed to provide practical solutions to fully exploit the potential of this data. PMID:18605994

  7. A novel ensemble machine learning for robust microarray data classification.

    PubMed

    Peng, Yonghong

    2006-06-01

    Microarray data analysis and classification has demonstrated convincingly that it provides an effective methodology for the effective diagnosis of diseases and cancers. Although much research has been performed on applying machine learning techniques for microarray data classification during the past years, it has been shown that conventional machine learning techniques have intrinsic drawbacks in achieving accurate and robust classifications. This paper presents a novel ensemble machine learning approach for the development of robust microarray data classification. Different from the conventional ensemble learning techniques, the approach presented begins with generating a pool of candidate base classifiers based on the gene sub-sampling and then the selection of a sub-set of appropriate base classifiers to construct the classification committee based on classifier clustering. Experimental results have demonstrated that the classifiers constructed by the proposed method outperforms not only the classifiers generated by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods (bagging and boosting).

  8. 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

  9. Comparative analysis of genomic signal processing for microarray data clustering.

    PubMed

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  10. A Protein Microarray ELISA for Screening Biological Fluids

    SciTech Connect

    Varnum, Susan M.; Woodbury, Ronald L.; Zangar, Richard C.

    2004-02-01

    Protein microarrays permit the simultaneous measurement of many proteins in a small sample volume and therefore provide an attractive approach for the quantitative measurement of proteins in biological fluids, including serum. This chapter describes a microarray ELISA assay. Capture antibodies are immobilized onto a glass surface, the covalently attached antibodies bind a specific antigen from a sample overlaying the array. A second, biotinylated antibody that recognizes the same antigen as the first antibody but at a different epitope is then used for detection. Detection is based upon an enzymatic signal enhancement method known as tyramide signal amplification (TSA). By coupling a microarray-ELISA format with the signal amplification of tyramide deposition, the assay sensitivity is as low as sub-pg/ml.

  11. Hydrogel micro-arrays for multi-analyte detection

    NASA Astrophysics Data System (ADS)

    Rounds, Rebecca M.; Lee, Seungjoon; Jeffords, Sarah; Ibey, Bennett L.; Pishko, Michael V.; Coté, Gerard L.

    2007-02-01

    Fluorescent microarrays have the ability to detect and monitor multiple analytes simultaneously and noninvasively, following initial placement. This versatility is advantageous for several biological applications including drug discovery, biohazard detection, transplant organ preservation and cell culture monitoring. In this work, poly(ethylene glycol) hydrogel microarrays are described that can be used to measure multiple analytes, including H+ and dissolved oxygen. The array elements are created by filling micro-channels with a hydrogel precursor solution containing analyte specific fluorescent sensors. A photomask is used to create the microarray through UV polymerization of the PEG precursor solution. A compact imaging system composed of a CCD camera, high powered LED, and two optical filters is used to measure the change in fluorescence emission corresponding to analyte concentration. The proposed system was tested in aqueous solution by altering relevant analyte concentrations across their biological ranges.

  12. Integration of amplified differential gene expression (ADGE) and DNA microarray.

    PubMed

    Chen, Zhijian J; Gaté, Laurent; Davis, Warren; Ile, Kristina E; Tew, Kenneth D

    2002-12-01

    Amplified Differential Gene Expression (ADGE) provides a new concept that the ratios of differentially expressed genes are magnified before detection in order to improve both sensitivity and accuracy. This technology is now implemented with integration of DNA reassociation and PCR. The ADGE technique can be used either as a stand-alone method or in series with DNA microarray. ADGE is used in sample preprocessing and DNA microarray is used as a displaying system in the series combination. These two techniques are mutually synergistic: the quadratic magnification of ratios of differential gene expression achieved by ADGE improves the detection sensitivity and accuracy; the PCR amplification of templates enhances the signal intensity and reduces the requirement for large amounts of starting material; the high throughput for DNA microarray is maintained.

  13. Nanodroplet chemical microarrays and label-free assays.

    PubMed

    Gosalia, Dhaval; Diamond, Scott L

    2010-01-01

    The microarraying of chemicals or biomolecules on a glass surface allows for dense storage and miniaturized screening experiments and can be deployed in chemical-biology research or drug discovery. Microarraying allows the production of scores of replicate slides. Small molecule libraries are typically stored as 10 mM DMSO stock solutions, whereas libraries of biomolecules are typically stored in high percentages of glycerol. Thus, a method is required to print such libraries on microarrays, and then assay them against biological targets. By printing either small molecule libraries or biomolecule libraries in an aqueous solvent containing glycerol, each adherent nanodroplet remains fixed at a position on the microarray by surface tension without the use of wells, without evaporating, and without the need for chemically linking the compound to the surface. Importantly, glycerol is a high boiling point solvent that is fully miscible with DMSO and water and has the additional property of stabilizing various enzymes. The nanoliter volume of the droplet forms the reaction compartment once additional reagents are metered onto the microarray, either by aerosol spray deposition or by addressable acoustic dispensing. Incubation of the nanodroplet microarray in a high humidity environment controls the final water content of the reaction. This platform has been validated for fluorescent HTS assays of protease and kinases as well as for fluorogenic substrate profiling of proteases. Label-free HTS is also possible by running nanoliter HTS reactions on a MALDI target for mass spectrometry (MS) analysis without the need for desalting of the samples. A method is described for running nanoliter-scale multicomponent homogeneous reactions followed by label-free MALDI MS spectrometry analysis of the reactions.

  14. Karyotype versus Microarray Testing for Genetic Abnormalities after Stillbirth

    PubMed Central

    Reddy, Uma M.; Page, Grier P.; Saade, George R.; Silver, Robert M.; Thorsten, Vanessa R.; Parker, Corette B.; Pinar, Halit; Willinger, Marian; Stoll, Barbara J.; Heim-Hall, Josefine; Varner, Michael W.; Goldenberg, Robert L.; Bukowski, Radek; Wapner, Ronald J.; Drews-Botsch, Carolyn D.; O’Brien, Barbara M.; Dudley, Donald J.; Levy, Brynn

    2015-01-01

    Background Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. Methods The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. Results In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P = 0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P = 0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P = 0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Conclusions Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health

  15. Are glycan biosensors an alternative to glycan microarrays?

    PubMed Central

    Hushegyi, A.

    2016-01-01

    Complex carbohydrates (glycans) play an important role in nature and study of their interaction with proteins or intact cells can be useful for understanding many physiological and pathological processes. Such interactions have been successfully interrogated in a highly parallel way using glycan microarrays, but this technique has some limitations. Thus, in recent years glycan biosensors in numerous progressive configurations have been developed offering distinct advantages compared to glycan microarrays. Thus, in this review advances achieved in the field of label-free glycan biosensors are discussed. PMID:27231487

  16. An accelerated procedure for recursive feature ranking on microarray data.

    PubMed

    Furlanello, C; Serafini, M; Merler, S; Jurman, G

    2003-01-01

    We describe a new wrapper algorithm for fast feature ranking in classification problems. The Entropy-based Recursive Feature Elimination (E-RFE) method eliminates chunks of uninteresting features according to the entropy of the weights distribution of a SVM classifier. With specific regard to DNA microarray datasets, the method is designed to support computationally intensive model selection in classification problems in which the number of features is much larger than the number of samples. We test E-RFE on synthetic and real data sets, comparing it with other SVM-based methods. The speed-up obtained with E-RFE supports predictive modeling on high dimensional microarray data.

  17. Reply to 'Linking probe thermodynamics to microarray quantification'

    NASA Astrophysics Data System (ADS)

    Burden, Conrad J.; Binder, Hans

    2010-12-01

    We defend Langmuir-like models of microarrays from accusations by Li et al (2010 Phys. Biol. 7 048001) that they fail to link sequence-specific properties to hybridization signals. We argue that existing Langmuir-like models based on accepted principles of physical chemistry, together with a model of post-hybridization washing, are entirely consistent with various controlled experiments. Li et al's competitive hybridization model on the other hand is not verified experimentally using designs which allow for an unambiguous differentiation with respect to Langmuir-like models and exhibits no benefit in fitting microarray probe intensities.

  18. Hand-held portable microarray reader for biodetection

    DOEpatents

    Thompson, Deanna Lynn; Coleman, Matthew A; Lane, Stephen M; Matthews, Dennis L; Albala, Joanna; Wachsmann-Hogiu, Sebastian

    2013-04-23

    A hand-held portable microarray reader for biodetection includes a microarray reader engineered to be small enough for portable applications. The invention includes a high-powered light-emitting diode that emits excitation light, an excitation filter positioned to receive the excitation light, a slide, a slide holder assembly for positioning the slide to receive the excitation light from the excitation filter, an emission filter positioned to receive the excitation light from the slide, a lens positioned to receive the excitation light from the emission filter, and a CCD camera positioned to receive the excitation light from the lens.

  19. 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.

  20. The bioinformatics of microarrays to study cancer: Advantages and disadvantages

    NASA Astrophysics Data System (ADS)

    Rodríguez-Segura, M. A.; Godina-Nava, J. J.; Villa-Treviño, S.

    2012-10-01

    Microarrays are devices designed to analyze simultaneous expression of thousands of genes. However, the process will adds noise into the information at each stage of the study. To analyze these thousands of data is necessary to use bioinformatics tools. The traditional analysis begins by normalizing data, but the obtained results are highly dependent on how it is conducted the study. It is shown the need to develop new strategies to analyze microarray. Liver tissue taken from an animal model in which is chemically induced cancer is used as an example.

  1. The tissue microarray OWL schema: An open-source tool for sharing tissue microarray data

    PubMed Central

    Kang, Hyunseok P.; Borromeo, Charles D.; Berman, Jules J.; Becich, Michael J.

    2010-01-01

    Background: Tissue microarrays (TMAs) are enormously useful tools for translational research, but incompatibilities in database systems between various researchers and institutions prevent the efficient sharing of data that could help realize their full potential. Resource Description Framework (RDF) provides a flexible method to represent knowledge in triples, which take the form Subject-Predicate-Object. All data resources are described using Uniform Resource Identifiers (URIs), which are global in scope. We present an OWL (Web Ontology Language) schema that expands upon the TMA data exchange specification to address this issue and assist in data sharing and integration. Methods: A minimal OWL schema was designed containing only concepts specific to TMA experiments. More general data elements were incorporated from predefined ontologies such as the NCI thesaurus. URIs were assigned using the Linked Data format. Results: We present examples of files utilizing the schema and conversion of XML data (similar to the TMA DES) to OWL. Conclusion: By utilizing predefined ontologies and global unique identifiers, this OWL schema provides a solution to the limitations of XML, which represents concepts defined in a localized setting. This will help increase the utilization of tissue resources, facilitating collaborative translational research efforts. PMID:20805954

  2. Implementation of GenePattern within the Stanford Microarray Database.

    PubMed

    Hubble, Jeremy; Demeter, Janos; Jin, Heng; Mao, Maria; Nitzberg, Michael; Reddy, T B K; Wymore, Farrell; Zachariah, Zachariah K; Sherlock, Gavin; Ball, Catherine A

    2009-01-01

    Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

  3. Viral Discovery and Sequence Recovery Using DNA Microarrays

    PubMed Central

    Wang, David; Urisman, Anatoly; Liu, Yu-Tsueng; Springer, Michael; Ksiazek, Thomas G; Erdman, Dean D; Mardis, Elaine R; Hickenbotham, Matthew; Magrini, Vincent; Eldred, James; Latreille, J. Phillipe; Wilson, Richard K; Ganem, Don

    2003-01-01

    Because of the constant threat posed by emerging infectious diseases and the limitations of existing approaches used to identify new pathogens, there is a great demand for new technological methods for viral discovery. We describe herein a DNA microarray-based platform for novel virus identification and characterization. Central to this approach was a DNA microarray designed to detect a wide range of known viruses as well as novel members of existing viral families; this microarray contained the most highly conserved 70mer sequences from every fully sequenced reference viral genome in GenBank. During an outbreak of severe acute respiratory syndrome (SARS) in March 2003, hybridization to this microarray revealed the presence of a previously uncharacterized coronavirus in a viral isolate cultivated from a SARS patient. To further characterize this new virus, approximately 1 kb of the unknown virus genome was cloned by physically recovering viral sequences hybridized to individual array elements. Sequencing of these fragments confirmed that the virus was indeed a new member of the coronavirus family. This combination of array hybridization followed by direct viral sequence recovery should prove to be a general strategy for the rapid identification and characterization of novel viruses and emerging infectious disease. PMID:14624234

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

    PubMed

    Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

    2017-02-01

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

  5. Polychromatic microarrays: simultaneous multicolor array hybridization of eight samples.

    PubMed

    Shepard, Jason R E

    2006-04-15

    High-throughput microscale platforms have transformed modern analytical investigations. Traditional microarray analyses involve a comparative approach, with two samples, a known control and an unknown sample, hybridized side-by-side and then contrasted for genetic differences. The samples are labeled with separate dyes and hybridized together, providing a differential expression pattern based on the reporter intensities. In contrast, the fiber-optic microarray platform described herein is analyzed with a microscope, thereby enabling the use of virtually any reporter, including quantum dots. The instrumentation takes advantage of the narrow emission bands characteristic of quantum dots to perform multiplexed detection of Bacillus anthracis. Advancing beyond the standard red/green microarray experiment, a panel of eight reporters were linked to eight B. anthracis samples and simultaneously analyzed in a microarray format. The ability to employ an assortment of reporters, along with the capacity to simultaneously hybridize eight samples confers an unprecedented flexibility to array-based analyses, providing a 4-fold increase in throughput over standard two-color assays.

  6. Increasing hybridization rate and sensitivity of DNA microarrays using isotachophoresis.

    PubMed

    Han, Crystal M; Katilius, Evaldas; Santiago, Juan G

    2014-08-21

    We present an on-chip electrokinetic method to increase the reaction kinetics and sensitivity of DNA microarray hybridization. We use isotachophoresis (ITP) to preconcentrate target molecules in solution and transport them over the immobilized probe sites of a microarray, greatly increasing the binding reaction rate. We show theoretically and experimentally that ITP-enhanced microarrays can be hybridized much faster and with higher sensitivity than conventional methods. We demonstrate our assay using a microfluidic system consisting of a PDMS microchannel superstructure bonded onto a glass slide on which 60 spots of 20-27 nt ssDNA oligonucleotide probes are immobilized. Our 30 min assay results in an 8.2 fold higher signal than the conventional overnight hybridization at 100 fM target concentration. We show rapid and quantitative detection over 4 orders of magnitude dynamic range of target concentration with no increase in the nonspecific signal. Our technique can be further multiplexed for higher density microarrays and extended for other reactions of target-surface immobilized ligands.

  7. 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.

  8. Solution Processable Organic Solar Cell Microarrays for Use in MEMS

    NASA Astrophysics Data System (ADS)

    Trinh, Jennifer; Lewis, Jason; Toglia, Patrick; Jiang, Xiaomei

    2011-03-01

    We have developed an innovative way to fabricate organic solar arrays for application as DC power supplies in electrostatic MEMS devices. The generation 1 microarray consists of 20 small (1 mm2) solar cells connected in series (total device area of 2.2 cm2). The device uses an active layer of poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PC61 BM), which are mixed together (1:1 mass ratio) in appropriate solvent. We manipulated active layer nanomorphology by choice of solvents and annealing conditions. The optimized generation 1 device has an open-circuit voltage of 11.5V, short-circuit current density of 1 mA/cm2 , and a power conversion efficiency of 2% under simulated solar AM1.5 illumination. The generation 2 microarray has a new design with reduced series resistance and improved cell occupancy. The generation 2 arrays have demonstrated improved device efficiency and power output density. Detailed analysis of device physics in both generation microarrays will be presented. The procedure described has potential for producing microarrays as small as 0.01 mm2 . This work was supported by the NSF REU program (award No DMR-1004873). Authors at USF would like to thank New Energy Technology Inc. and Florida High Tech Corridor Matching Fund (FHT 09-18).

  9. Validation of the Swine Protein-Annotated Oligonucleotide Microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The specificity and utility of the Swine Protein-Annotated Oligonucleotide Microarray, or Pigoligoarray (www.pigoligoarray.org), has been evaluated by profiling the expression of transcripts from four porcine tissues. Tools for comparative analyses of expression on the Pigoligoarray were developed i...

  10. 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.

  11. 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...

  12. Profiling glycosyltransferase activities by tritium imaging of glycan microarrays.

    PubMed

    Serna, Sonia; Hokke, Cornelis H; Weissenborn, Martin; Flitsch, Sabine; Martin-Lomas, Manuel; Reichardt, Niels-Christian

    2013-05-10

    High-throughput microarray technology has been combined with ultrasensitive and high-resolution tritium autoradiography to create a new platform for the quantitative detection of glycosyltransferase activity on glycan arrays. In addition, we show full compatibility with the use of fluorescently labeled lectins to help with the stereochemical assignment of newly formed glycoside linkages.

  13. A microarray immunoassay for simultaneous detection of proteins and bacteria

    NASA Technical Reports Server (NTRS)

    Delehanty, James B.; Ligler, Frances S.

    2002-01-01

    We report the development and characterization of an antibody microarray biosensor for the rapid detection of both protein and bacterial analytes under flow conditions. Using a noncontact microarray printer, biotinylated capture antibodies were immobilized at discrete locations on the surface of an avidin-coated glass microscope slide. Preservation of capture antibody function during the deposition process was accomplished with the use of a low-salt buffer containing sucrose and bovine serum albumin. The slide was fitted with a six-channel flow module that conducted analyte-containing solutions over the array of capture antibody microspots. Detection of bound analyte was subsequently achieved using fluorescent tracer antibodies. The pattern of fluorescent complexes was interrogated using a scanning confocal microscope equipped with a 635-nm laser. This microarray system was employed to detect protein and bacterial analytes both individually and in samples containing mixtures of analytes. Assays were completed in 15 min, and detection of cholera toxin, staphylococcal enterotoxin B, ricin, and Bacillus globigii was demonstrated at levels as low as 8 ng/mL, 4 ng/mL, 10 ng/mL, and 6.2 x 10(4) cfu/mL, respectively. The assays presented here are very fast, as compared to previously published methods for measuring antibody-antigen interactions using microarrays (minutes versus hours).

  14. Gene expression profiling in peanut using oligonucleotide microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently have a moderately significant number of ESTs been released into the public domain. Utilization of these ESTs for the oligonucleotide microarrays provides a means to investigate l...

  15. Gene expression profiling of mouse embryos with microarrays

    PubMed Central

    Sharov, Alexei A.; Piao, Yulan; Ko, Minoru S. H.

    2011-01-01

    Global expression profiling by DNA microarrays provides a snapshot of cell and tissue status and becomes an essential tool in biological and medical sciences. Typical questions that can be addressed by microarray analysis in developmental biology include: (1) to find a set of genes expressed in a specific cell type; (2) to identify genes expressed commonly in multiple cell types; (3) to follow the time-course changes of gene expression patterns; (4) to demonstrate cell’s identity by showing similarities or differences among two or multiple cell types; (5) to find regulatory pathways and/or networks affected by gene manipulations, such as overexpression or repression of gene expression; (6) to find downstream target genes of transcription factors; (7) to find downstream target genes of cell signaling; (8) to examine the effects of environmental manipulation of cells on gene expression patterns; and (9) to find the effects of genetic manipulation in embryos and adults. Here we describe strategies for executing these experiments and monitoring changes of cell state with gene expression microarrays in application to mouse embryology. Both statistical assessment and interpretation of data are discussed. We also present a protocol for performing microarray analysis on a small amount of embryonic materials. PMID:20699157

  16. CONFIRMING MICROARRAY DATA--IS IT REALLY NECESSARY?

    EPA Science Inventory

    The generation of corroborative data has become a commonly used approach for ensuring the veracity of microarray data. Indeed, the need to conduct corroborative studies has now become official editorial policy for at least two journals, and several more are considering introducin...

  17. Genetic mapping in grapevine using a SNP microarray: intensity values

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genotyping microarrays are widely used for genome wide association studies, but in high-diversity organisms, the quality of SNP calls can be diminished by genetic variation near the assayed nucleotide. To address this limitation in grapevine, we developed a simple heuristic that uses hybridization i...

  18. Fundamental Patterns Underlying Neurotoxicity Revealed by DNA Microarray Expression Profiling

    DTIC Science & Technology

    2004-09-01

    microarray analysis of the dopaminergic cell line, SN4741 , revealed induction of stress indices following MPP* treatment (Chun et al., 2001). To...response to a wide range of cellular stresses including oxidative insult of the nigral dopaminergic cell line SN4741 with hydrogen peroxide or MPP* (Salinas

  19. A Customized DNA Microarray for Microbial Source Tracking ...

    EPA Pesticide Factsheets

    It is estimated that more than 160, 000 miles of rivers and streams in the United States are impaired due to the presence of waterborne pathogens. These pathogens typically originate from human and other animal fecal pollution sources; therefore, a rapid microbial source tracking (MST) method is needed to facilitate water quality assessment and impaired water remediation. We report a novel qualitative DNA microarray technology consisting of 453 probes for the detection of general fecal and host-associated bacteria, viruses, antibiotic resistance, and other environmentally relevant genetic indicators. A novel data normalization and reduction approach is also presented to help alleviate false positives often associated with high-density microarray applications. To evaluate the performance of the approach, DNA and cDNA was isolated from swine, cattle, duck, goose and gull fecal reference samples, as well as soiled poultry liter and raw municipal sewage. Based on nonmetric multidimensional scaling analysis of results, findings suggest that the novel microarray approach may be useful for pathogen detection and identification of fecal contamination in recreational waters. The ability to simultaneously detect a large collection of environmentally important genetic indicators in a single test has the potential to provide water quality managers with a wide range of information in a short period of time. Future research is warranted to measure microarray performance i

  20. Microarray data analysis for differential expression: a tutorial.

    PubMed

    Suárez, Erick; Burguete, Ana; Mclachlan, Geoffrey J

    2009-06-01

    DNA microarray is a technology that simultaneously evaluates quantitative measurements for the expression of thousands of genes. DNA microarrays have been used to assess gene expression between groups of cells of different organs or different populations. In order to understand the role and function of the genes, one needs the complete information about their mRNA transcripts and proteins. Unfortunately, exploring the protein functions is very difficult, due to their unique 3-dimentional complicated structure. To overcome this difficulty, one may concentrate on the mRNA molecules produced by the gene expression. In this paper, we describe some of the methods for preprocessing data for gene expression and for pairwise comparison from genomic experiments. Previous studies to assess the efficiency of different methods for pairwise comparisons have found little agreement in the lists of significant genes. Finally, we describe the procedures to control false discovery rates, sample size approach for these experiments, and available software for microarray data analysis. This paper is written for those professionals who are new in microarray data analysis for differential expression and want to have an overview of the specific steps or the different approaches for this sort of analysis.

  1. Microtiter plate-based antibody microarrays for bacteria and toxins

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Research has focused on the development of rapid biosensor-based, high-throughput, and multiplexed detection of pathogenic bacteria in foods. Specifically, antibody microarrays in 96-well microtiter plates have been generated for the purpose of selective detection of Shiga toxin-producing E. coli (...

  2. Electrostatic readout of DNA microarrays with charged microspheres

    PubMed Central

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

    2014-01-01

    DNA microarrays are used for gene-expression profiling, single-nucleotide polymorphism detection and disease diagnosis1–3. A persistent challenge in this area is the lack of microarray screening technology suitable for integration into routine clinical care4,5. Here, 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. Because the naked eye is sufficient to read out hybridization, this approach may facilitate broad application of multiplexed assays. PMID:18587384

  3. Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

    SciTech Connect

    Gregory Stephanopoulos

    2004-07-31

    Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

  4. 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.

  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. Broad spectrum microarray for fingerprint-based bacterial species identification

    PubMed Central

    2010-01-01

    Background Microarrays are powerful tools for DNA-based molecular diagnostics and identification of pathogens. Most target a limited range of organisms and are based on only one or a very few genes for specific identification. Such microarrays are limited to organisms for which specific probes are available, and often have difficulty discriminating closely related taxa. We have developed an alternative broad-spectrum microarray that employs hybridisation fingerprints generated by high-density anonymous markers distributed over the entire genome for identification based on comparison to a reference database. Results A high-density microarray carrying 95,000 unique 13-mer probes was designed. Optimized methods were developed to deliver reproducible hybridisation patterns that enabled confident discrimination of bacteria at the species, subspecies, and strain levels. High correlation coefficients were achieved between replicates. A sub-selection of 12,071 probes, determined by ANOVA and class prediction analysis, enabled the discrimination of all samples in our panel. Mismatch probe hybridisation was observed but was found to have no effect on the discriminatory capacity of our system. Conclusions These results indicate the potential of our genome chip for reliable identification of a wide range of bacterial taxa at the subspecies level without laborious prior sequencing and probe design. With its high resolution capacity, our proof-of-principle chip demonstrates great potential as a tool for molecular diagnostics of broad taxonomic groups. PMID:20163710

  7. 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.

  8. 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 ...

  9. DNA Microarray-based Ecotoxicological Biomarker Discovery in a Small Fish Model Species

    EPA Science Inventory

    This paper addresses several issues critical to use of zebrafish oligonucleotide microarrays for computational toxicology research on endocrine disrupting chemicals using small fish models, and more generally, the use of microarrays in aquatic toxicology.

  10. 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...

  11. 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.

  12. 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...

  13. Independent component analysis of Alzheimer's DNA microarray gene expression data

    PubMed Central

    Kong, Wei; Mou, Xiaoyang; Liu, Qingzhong; Chen, Zhongxue; Vanderburg, Charles R; Rogers, Jack T; Huang, Xudong

    2009-01-01

    Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA) and independent component analysis (ICA) have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD) hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In comparison to the PCA and support

  14. Comparison of gene coverage of mouse oligonucleotide microarray platforms

    PubMed Central

    Verdugo, Ricardo A; Medrano, Juan F

    2006-01-01

    Background The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform. Results A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene. Conclusion The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the

  15. DNA Microarray-Based PCR Ribotyping of Clostridium difficile

    PubMed Central

    Ehricht, Ralf; Slickers, Peter; Baier, Vico; Neubauer, Heinrich; Zimmermann, Stefan; Rabold, Denise; Lübke-Becker, Antina; Seyboldt, Christian

    2014-01-01

    This study presents a DNA microarray-based assay for fast and simple PCR ribotyping of Clostridium difficile strains. Hybridization probes were designed to query the modularly structured intergenic spacer region (ISR), which is also the template for conventional and PCR ribotyping with subsequent capillary gel electrophoresis (seq-PCR) ribotyping. The probes were derived from sequences available in GenBank as well as from theoretical ISR module combinations. A database of reference hybridization patterns was set up from a collection of 142 well-characterized C. difficile isolates representing 48 seq-PCR ribotypes. The reference hybridization patterns calculated by the arithmetic mean were compared using a similarity matrix analysis. The 48 investigated seq-PCR ribotypes revealed 27 array profiles that were clearly distinguishable. The most frequent human-pathogenic ribotypes 001, 014/020, 027, and 078/126 were discriminated by the microarray. C. difficile strains related to 078/126 (033, 045/FLI01, 078, 126, 126/FLI01, 413, 413/FLI01, 598, 620, 652, and 660) and 014/020 (014, 020, and 449) showed similar hybridization patterns, confirming their genetic relatedness, which was previously reported. A panel of 50 C. difficile field isolates was tested by seq-PCR ribotyping and the DNA microarray-based assay in parallel. Taking into account that the current version of the microarray does not discriminate some closely related seq-PCR ribotypes, all isolates were typed correctly. Moreover, seq-PCR ribotypes without reference profiles available in the database (ribotype 009 and 5 new types) were correctly recognized as new ribotypes, confirming the performance and expansion potential of the microarray. PMID:25411174

  16. Sex determination of bovine preimplantation embryos by oligonucleotide microarray.

    PubMed

    Yang, Hua; Zhong, Fagang; Yang, Yonglin; Wang, Xinhua; Liu, Shouren; Zhu, Bin

    2013-06-01

    The aim has been to set up a rapid and accurate microarray assay using sandwich mode for sex determination of bovine preimplantation embryos. Twelve sequence-specific oligonucleotide capture probes used to discriminate 12 samples were spotted onto the aldehyde-modified glass slides by Arrayer. The 2 recognition probes used to identify coding regions of the sex-determining region of the Y chromosome gene (SRY) and β-casein (CSN2) reference gene were coupled with biotin. The assay was optimized by using genomic DNA extracted from blood samples of known sex individuals. Polymerase chain reaction (PCR) was used to amplify the fragments in the HMG box region of SRY gene and CSN2 gene with sequence-specific primers. The sex of samples was identified by detecting both the SRY and CSN2 genes simultaneously in 2 reaction cells of microarrays, with the male having SRY and CSN2 signals and the female only CSN2. The sex of 20 bovine preimplantation embryos was determined by oligonucleotide microarray. The protocol was run with a blind test that showed a 100% (82/82) specificity and accuracy in sexing of leukocytes. The bovine embryos were transferred into 20 bovine recipients, with a pregnant rate of 40% (8/20). Three calves were born at term, and 5 fetuses were miscarried. Their sexes were fully in accordance with the embryonic sex predetermination predicted by oligonucleotide microarray. This suggests that the oligonucleotide microarray method of SRY gene analysis can be used in early sex prediction of bovine embryos in breeding programs.

  17. Avian oncogenic virus differential diagnosis in chickens using oligonucleotide microarray.

    PubMed

    Wang, Lih-Chiann; Huang, Dean; Pu, Chang-En; Wang, Ching-Ho

    2014-12-15

    Avian oncogenic viruses include the avian leukosis virus (ALV), reticuloendotheliosis virus (REV) and Marek's disease virus (MDV). Multiple oncogenic viral infections are frequently seen, with even Marek's disease vaccines reported to be contaminated with ALV and REV. The gross lesions caused by avian oncogenic viruses often overlap, making differentiation diagnosis based on histopathology difficult. The objective of this study is to develop a rapid approach to simultaneously differentiate, subgroup and pathotype the avian oncogenic viruses. The oligonucleotide microarray was employed in this study. Particular DNA sequences were recognized using specific hybridization between the DNA target and probe on the microarray, followed with colorimetric development through enzyme reaction. With 10 designed probes, ALV-A, ALV-E, ALV-J, REV, MDV pathogenic and vaccine strains were clearly discriminated on the microarray with the naked eyes. The detection limit was 27 copy numbers, which was 10-100 times lower than multiplex PCR. Of 102 field samples screened using the oligonucleotide microarray, 32 samples were positive for ALV-E, 17 samples were positive for ALV-J, 6 samples were positive for REV, 4 samples were positive for MDV, 7 samples were positive for both ALV-A and ALV-E, 5 samples were positive for ALV-A, ALV-E and ALV-J, one sample was positive for both ALV-J and MDV, and 3 samples were positive for both REV and MDV. The oligonucleotide microarray, an easy-to-use, high-specificity, high-sensitivity and extendable assay, presents a potent technique for rapid differential diagnosis of avian oncogenic viruses and the detection of multiple avian oncogenic viral infections under field conditions.

  18. Recommendations for the use of microarrays in prenatal diagnosis.

    PubMed

    Suela, Javier; López-Expósito, Isabel; Querejeta, María Eugenia; Martorell, Rosa; Cuatrecasas, Esther; Armengol, Lluis; Antolín, Eugenia; Domínguez Garrido, Elena; Trujillo-Tiebas, María José; Rosell, Jordi; García Planells, Javier; Cigudosa, Juan Cruz

    2017-04-07

    Microarray technology, recently implemented in international prenatal diagnosis systems, has become one of the main techniques in this field in terms of detection rate and objectivity of the results. This guideline attempts to provide background information on this technology, including technical and diagnostic aspects to be considered. Specifically, this guideline defines: the different prenatal sample types to be used, as well as their characteristics (chorionic villi samples, amniotic fluid, fetal cord blood or miscarriage tissue material); variant reporting policies (including variants of uncertain significance) to be considered in informed consents and prenatal microarray reports; microarray limitations inherent to the technique and which must be taken into account when recommending microarray testing for diagnosis; a detailed clinical algorithm recommending the use of microarray testing and its introduction into routine clinical practice within the context of other genetic tests, including pregnancies in families with a genetic history or specific syndrome suspicion, first trimester increased nuchal translucency or second trimester heart malformation and ultrasound findings not related to a known or specific syndrome. This guideline has been coordinated by the Spanish Association for Prenatal Diagnosis (AEDP, «Asociación Española de Diagnóstico Prenatal»), the Spanish Human Genetics Association (AEGH, «Asociación Española de Genética Humana») and the Spanish Society of Clinical Genetics and Dysmorphology (SEGCyD, «Sociedad Española de Genética Clínica y Dismorfología»).

  19. DNA microarray-based PCR ribotyping of Clostridium difficile.

    PubMed

    Schneeberg, Alexander; Ehricht, Ralf; Slickers, Peter; Baier, Vico; Neubauer, Heinrich; Zimmermann, Stefan; Rabold, Denise; Lübke-Becker, Antina; Seyboldt, Christian

    2015-02-01

    This study presents a DNA microarray-based assay for fast and simple PCR ribotyping of Clostridium difficile strains. Hybridization probes were designed to query the modularly structured intergenic spacer region (ISR), which is also the template for conventional and PCR ribotyping with subsequent capillary gel electrophoresis (seq-PCR) ribotyping. The probes were derived from sequences available in GenBank as well as from theoretical ISR module combinations. A database of reference hybridization patterns was set up from a collection of 142 well-characterized C. difficile isolates representing 48 seq-PCR ribotypes. The reference hybridization patterns calculated by the arithmetic mean were compared using a similarity matrix analysis. The 48 investigated seq-PCR ribotypes revealed 27 array profiles that were clearly distinguishable. The most frequent human-pathogenic ribotypes 001, 014/020, 027, and 078/126 were discriminated by the microarray. C. difficile strains related to 078/126 (033, 045/FLI01, 078, 126, 126/FLI01, 413, 413/FLI01, 598, 620, 652, and 660) and 014/020 (014, 020, and 449) showed similar hybridization patterns, confirming their genetic relatedness, which was previously reported. A panel of 50 C. difficile field isolates was tested by seq-PCR ribotyping and the DNA microarray-based assay in parallel. Taking into account that the current version of the microarray does not discriminate some closely related seq-PCR ribotypes, all isolates were typed correctly. Moreover, seq-PCR ribotypes without reference profiles available in the database (ribotype 009 and 5 new types) were correctly recognized as new ribotypes, confirming the performance and expansion potential of the microarray.

  20. 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

  1. ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

    SciTech Connect

    White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.; Daly, Don S.; Zangar, Richard C.

    2009-06-15

    ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

  2. Key aspects of analyzing microarray gene-expression data.

    PubMed

    Chen, James J

    2007-05-01

    One major challenge with the use of microarray technology is the analysis of massive amounts of gene-expression data for various applications. This review addresses the key aspects of the microarray gene-expression data analysis for the two most common objectives: class comparison and class prediction. Class comparison mainly aims to select which genes are differentially expressed across experimental conditions. Gene selection is separated into two steps: gene ranking and assigning a significance level. Class prediction uses expression profiling analysis to develop a prediction model for patient selection, diagnostic prediction or prognostic classification. Development of a prediction model involves two components: model building and performance assessment. It also describes two additional data analysis methods: gene-class testing and multiple ordering criteria.

  3. Novel Fluorescent Glycan Microarray Strategy Reveals Ligands for Galectins

    PubMed Central

    Song, Xuezheng; Xia, Baoyun; Stowell, Sean R.; Lasanajak, Yi; Smith, David F.; Cummings, Richard D.

    2009-01-01

    Summary Galectin-1 (Gal-1) and galectin-3 (Gal-3) are widely expressed galectins with immunoregulatory functions in animals. To explore their glycan specificity, we developed microarrays of naturally occurring glycans using a novel bifunctional fluorescent linker, 2-amino-N-(2-aminoethyl)-benzamide (AEAB), directly conjugated through its arylamine group by reductive amination to free glycans to form glycan-AEABs (GAEABs). Glycans from natural sources were used to prepare over 200 GAEABs, which were purified by multidimensional HPLC and covalently immobilized onto NHS-activated glass slides via their free alkylamine. Fluorescence-based screening demonstrated that Gal-1 recognizes a wide variety of complex N-glycans, whereas Gal-3 primarily recognizes poly-N-acetyllactosamine-containing glycans independent of N-glycan presentation. GAEABs provide a general solution to glycan microarray preparation from natural sources for defining the specificity of glycan-binding proteins. PMID:19171304

  4. 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.

  5. Microarray analysis of gene expression in medicinal plant research.

    PubMed

    Youns, M; Efferth, T; Hoheisel, J D

    2009-10-01

    Expression profiling analysis offers great opportunities for the identification of novel molecular targets, drug discovery, development, and validation. The beauty of microarray analysis of gene expression is that it can be used to screen the expression of tens of thousands of genes in parallel and to identify appropriate molecular targets for therapeutic intervention. Toward identifying novel therapeutic options, natural products, notably from medicinal plants used in traditional Chinese medicine (TCM), have been thoroughly investigated. Increased knowledge of the molecular mechanisms of TCM-derived drugs could be achieved through application of modern molecular technologies including transcript profiling. In the present review, we introduce a brief introduction to the field of microarray technology and disclose its role in target identification and validation. Moreover, we provide examples for applications regarding molecular target discovery in medicinal plants derived TCM. This could be an attractive strategy for the development of novel and improved therapeutics.

  6. Groundtruth approach to accurate quantitation of fluorescence microarrays

    SciTech Connect

    Mascio-Kegelmeyer, L; Tomascik-Cheeseman, L; Burnett, M S; van Hummelen, P; Wyrobek, A J

    2000-12-01

    To more accurately measure fluorescent signals from microarrays, we calibrated our acquisition and analysis systems by using groundtruth samples comprised of known quantities of red and green gene-specific DNA probes hybridized to cDNA targets. We imaged the slides with a full-field, white light CCD imager and analyzed them with our custom analysis software. Here we compare, for multiple genes, results obtained with and without preprocessing (alignment, color crosstalk compensation, dark field subtraction, and integration time). We also evaluate the accuracy of various image processing and analysis techniques (background subtraction, segmentation, quantitation and normalization). This methodology calibrates and validates our system for accurate quantitative measurement of microarrays. Specifically, we show that preprocessing the images produces results significantly closer to the known ground-truth for these samples.

  7. Quantitative Oligonucleotide Microarray Fingerprinting of Salmonella enterica isolates

    SciTech Connect

    Willse, Alan R.; Straub, Tim M.; Wunschel, Sharon C.; Small, Jack A.; Call, Douglas R.; Daly, Don S.; Chandler, Darrell P.

    2004-03-22

    We report on a genome-independent microbial fingerprinting method using nucleic acid microarrays for microbial forensics and epidemiology applications. We demonstrate that the microarray method provides high-resolution differentiation between closely related microorganisms using Salmonella enterica strains. In replicate trials we used a simple 192-probe nonamer array to construct a fingerprint library of 25 closely related Salmonella isolates. Controlling false discovery rate for multiple testing at alpha =.05, at least 295 of 300 pairs of S. enterica isolate fingerprints were found to be statistically distinct using a modified Hotelling Tsquared test. Although we find most pairs of Salmonella fingerprints to be distinct, forensic applications will also require a protocol for library construction and reliable microbial classification against a fingerprint library. We outline additional steps required to produce a protocol for library construction and reliable classification of unknown organisms.

  8. Comparative examination of probe labeling methods for microarray hybridization

    NASA Astrophysics Data System (ADS)

    Burke, David I.; Woodward, Karen; Setterquist, Robert A.; Kawasaki, Ernest S.

    2001-06-01

    For detection of differential gene expression, confocal laser based scanners are now capable of analyzing microarrays using one to five wavelengths. This allows investigators to choose among several labeling methods. Here we compare direct incorporation and indirect methods (amino-allyl and dendrimers) for labeling cDNA probes. We assessed reproducible sensitivity of each probe preparation method in two ways. First, by comparing hybridization intensities for limit of signal detection and second by measuring the lowest detectable concentration of a known ratio of mixed DNA (spikes). Limit of detection assay was done using arrays of mixed targets consisting of a serially diluted human specific gene fragment (HU1) and an undiluted DNA of chloramphenicol acetyl tranferase (CAT) gene. Then, individual single target arrays of CAT and HU1 DNA were used to determine the lowest detectable spike ratio of each labeling method. The results of this study will be presented and their significance for the analysis of microarrays will be discussed.

  9. Microarrays for Public Health: Genomic Epidemiology of Tuberculosis

    PubMed Central

    Shafi, Jamila; Andrew, Peter W.

    2002-01-01

    In response to a large local school-based outbreak of tuberculosis, we have been evaluating the utility of microarray bacterial genomic analysis in outbreak management. After initial comparison of the isolate from the index case with Mycobacterium tuberculosis H37Rv, it was possible to design robust PCRs directed towards strain-specific deletions. Rapid PCR analysis of isolates proved valuable in determining whether or not other isolates were compatible with the outbreak strain and further microarray studies revealed genetic markers that could be used to discriminate between locally circulating strains.We suggest that this approach forms the basis for developing rapid local genotyping schemes applicable to M. tuberculosis and that application to other pathogens warrants consideration. PMID:18629269

  10. Low-Cost Peptide Microarrays for Mapping Continuous Antibody Epitopes.

    PubMed

    McBride, Ryan; Head, Steven R; Ordoukhanian, Phillip; Law, Mansun

    2016-01-01

    With the increasing need for understanding antibody specificity in antibody and vaccine research, pepscan assays provide a rapid method for mapping and profiling antibody responses to continuous epitopes. We have developed a relatively low-cost method to generate peptide microarray slides for studying antibody binding. Using a setup of an IntavisAG MultiPep RS peptide synthesizer, a Digilab MicroGrid II 600 microarray printer robot, and an InnoScan 1100 AL scanner, the method allows the interrogation of up to 1536 overlapping, alanine-scanning, and mutant peptides derived from the target antigens. Each peptide is tagged with a polyethylene glycol aminooxy terminus to improve peptide solubility, orientation, and conjugation efficiency to the slide surface.

  11. Stripping custom microRNA microarrays and the lessons learned about probe-slide interactions.

    PubMed

    Zhang, Xiaoxiao; Xu, Wayne; Tan, Jiankang; Zeng, Yan

    2009-03-15

    Microarrays have been used extensively in gene expression profiling and genotyping studies. To reduce the high cost and enhance the consistency of microarray experiments, it is often desirable to strip and reuse microarray slides. Our genome-wide analysis of microRNA expression involves the hybridization of fluorescently labeled nucleic acids to custom-made, spotted DNA microarrays based on GAPSII-coated slides. We describe here a simple and effective method to regenerate such custom microarrays that uses a very low-salt buffer to remove labeled nucleic acids from microarrays. Slides can be stripped and reused multiple times without significantly compromising data quality. Moreover, our analyses of the performance of regenerated slides identifies parameters that influence the attachment of oligonucleotide probes to GAPSII slides, shedding light on the interactions between DNA and the microarray surface and suggesting ways in which to improve the design of oligonucleotide probes.

  12. Optimizing scan parameters for antibody microarray experiments: accelerating robust systems diagnostics for life sciences.

    PubMed

    Gu, Qiang; Sivanandam, Thamil Mani

    2014-06-01

    Microarray experiments are a centerpiece of postgenomics life sciences and the current efforts to develop systems diagnostics for personalized medicine. The majority of antibody microarray experiments are fluorescence-based, which utilizes a scanner to convert target signals into image files for subsequent quantification. Certain scan parameters such as the laser power and photomultiplier tube gain (PMT) can influence the readout of fluorescent intensities and thus may affect data quantitation. To date, however, there is no consensus of how to determine the optimal settings of microarray scanners. Here we show that different settings of the laser power and PMT not only affect the signal intensities but also the accuracy of antibody microarray experiments. More importantly, we demonstrate an experimental approach using two fluorescent dyes to determine optimal settings of scan parameters for microarray experiments. These measures provide added quality control of microarray experiments, and thus help to improve the accuracy of quantitative outcome in microarray experiments in the above contexts.

  13. Gel-forming reagents and uses thereof for preparing microarrays

    DOEpatents

    Golova, Julia; Chernov, Boris; Perov, Alexander

    2010-11-09

    New gel-forming reagents including monomers and cross-linkers, which can be applied to gel-drop microarray manufacturing by using co-polymerization approaches are disclosed. Compositions for the preparation of co-polymerization mixtures with new gel-forming monomers and cross-linker reagents are described herein. New co-polymerization compositions and cross-linkers with variable length linker groups between unsaturated C.dbd.C bonds that participate in the formation of gel networks are disclosed.

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

    PubMed Central

    2012-01-01

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

  15. Fecal source tracking in water using a mitochondrial DNA microarray.

    PubMed

    Vuong, Nguyet-Minh; Villemur, Richard; Payment, Pierre; Brousseau, Roland; Topp, Edward; Masson, Luke

    2013-01-01

    A mitochondrial-based microarray (mitoArray) was developed for rapid identification of the presence of 28 animals and one family (cervidae) potentially implicated in fecal pollution in mixed activity watersheds. Oligonucleotide probes for genus or subfamily-level identification were targeted within the 12S rRNA - Val tRNA - 16S rRNA region in the mitochondrial genome. This region, called MI-50, was selected based on three criteria: 1) the ability to be amplified by universal primers 2) these universal primer sequences are present in most commercial and domestic animals of interest in source tracking, and 3) that sufficient sequence variation exists within this region to meet the minimal requirements for microarray probe discrimination. To quantify the overall level of mitochondrial DNA (mtDNA) in samples, a quantitative-PCR (Q-PCR) universal primer pair was also developed. Probe validation was performed using DNA extracted from animal tissues and, for many cases, animal-specific fecal samples. To reduce the amplification of potentially interfering fish mtDNA sequences during the MI-50 enrichment step, a clamping PCR method was designed using a fish-specific peptide nucleic acid. DNA extracted from 19 water samples were subjected to both array and independent PCR analyses. Our results confirm that the mitochondrial microarray approach method could accurately detect the dominant animals present in water samples emphasizing the potential for this methodology in the parallel scanning of a large variety of animals normally monitored in fecal source tracking.

  16. New 3-D microarray platform based on macroporous polymer monoliths.

    PubMed

    Rober, M; Walter, J; Vlakh, E; Stahl, F; Kasper, C; Tennikova, T

    2009-06-30

    Polymer macroporous monoliths are widely used as efficient sorbents in different, mostly dynamic, interphase processes. In this paper, monolithic materials strongly bound to the inert glass surface are suggested as operative matrices at the development of three-dimensional (3-D) microarrays. For this purpose, several rigid macroporous copolymers differed by reactivity and hydrophobic-hydrophilic properties were synthesized and tested: (1) glycidyl methacrylate-co-ethylene dimethacrylate (poly(GMA-co-EDMA)), (2) glycidyl methacrylate-co-glycerol dimethacrylate (poly(GMA-co-GDMA)), (3) N-hydroxyphthalimide ester of acrylic acid-co-glycidyl methacrylate-co-ethylene dimethacrylate (poly(HPIEAA-co-GMA-co-EDMA)), (4) 2-cyanoethyl methacrylate-co-ethylene dimethacrylate (poly(CEMA-co-EDMA)), and (5) 2-cyanoethyl methacrylate-co-2-hydroxyethyl methacrylate-co-ethylene dimethacrylate (poly(CEMA-co-HEMA-co-EDMA)). The constructed devices were used as platforms for protein microarrays construction and model mouse IgG-goat anti-mouse IgG affinity pair was used to demonstrate the potential of developed test-systems, as well as to optimize microanalytical conditions. The offered microarray platforms were applied to detect the bone tissue marker osteopontin directly in cell culture medium.

  17. Automated target preparation for microarray-based gene expression analysis.

    PubMed

    Raymond, Frédéric; Metairon, Sylviane; Borner, Roland; Hofmann, Markus; Kussmann, Martin

    2006-09-15

    DNA microarrays have rapidly evolved toward a platform for massively paralleled gene expression analysis. Despite its widespread use, the technology has been criticized to be vulnerable to technical variability. Addressing this issue, recent comparative, interplatform, and interlaboratory studies have revealed that, given defined procedures for "wet lab" experiments and data processing, a satisfactory reproducibility and little experimental variability can be achieved. In view of these advances in standardization, the requirement for uniform sample preparation becomes evident, especially if a microarray platform is used as a facility, i.e., by different users working in the laboratory. While one option to reduce technical variability is to dedicate one laboratory technician to all microarray studies, we have decided to automate the entire RNA sample preparation implementing a liquid handling system coupled to a thermocycler and a microtiter plate reader. Indeed, automated RNA sample preparation prior to chip analysis enables (1) the reduction of experimentally caused result variability, (2) the separation of (important) biological variability from (undesired) experimental variation, and (3) interstudy comparison of gene expression results. Our robotic platform can process up to 24 samples in parallel, using an automated sample preparation method that produces high-quality biotin-labeled cRNA ready to be hybridized on Affymetrix GeneChips. The results show that the technical interexperiment variation is less pronounced than with manually prepared samples. Moreover, experiments using the same starting material showed that the automated process yields a good reproducibility between samples.

  18. Application of nanostructured biochips for efficient cell transfection microarrays

    NASA Astrophysics Data System (ADS)

    Akkamsetty, Yamini; Hook, Andrew L.; Thissen, Helmut; Hayes, Jason P.; Voelcker, Nicolas H.

    2007-01-01

    Microarrays, high-throughput devices for genomic analysis, can be further improved by developing materials that are able to manipulate the interfacial behaviour of biomolecules. This is achieved both spatially and temporally by smart materials possessing both switchable and patterned surface properties. A system had been developed to spatially manipulate both DNA and cell growth based upon the surface modification of highly doped silicon by plasma polymerisation and polyethylene grafting followed by masked laser ablation for formation of a pattered surface with both bioactive and non-fouling regions. This platform has been successfully applied to transfected cell microarray applications with the parallel expression of genes by utilising its ability to direct and limit both DNA and cell attachment to specific sites. One of the greatest advantages of this system is its application to reverse transfection, whereupon by utilising the switchable adsorption and desorption of DNA using a voltage bias, the efficiency of cell transfection can be enhanced. However, it was shown that application of a voltage also reduces the viability of neuroblastoma cells grown on a plasma polymer surface, but not human embryonic kidney cells. This suggests that the application of a voltage may not only result in the desorption of bound DNA but may also affect attached cells. The characterisation of a DNA microarray by contact printing has also been investigated.

  19. Glycan profiling of endometrial cancers using lectin microarray.

    PubMed

    Nishijima, Yoshihiro; Toyoda, Masashi; Yamazaki-Inoue, Mayu; Sugiyama, Taro; Miyazawa, Masaki; Muramatsu, Toshinari; Nakamura, Kyoko; Narimatsu, Hisashi; Umezawa, Akihiro; Mikami, Mikio

    2012-10-01

    Cell surface glycans change during the process of malignant transformation. To characterize and distinguish endometrial cancer and endometrium, we performed glycan profiling using an emerging modern technology, lectin microarray analysis. The three cell lines, two from endometrial cancers [well-differentiated type (G1) and poorly differentiated type (G3)] and one from normal endometrium, were successfully categorized into three independent groups by 45 lectins. Furthermore, in cancer cells, a clear difference between G1 and G3 type was observed for the glycans recognized with six lectins, Ulex europaeus agglutinin I (UEA-I), Sambucus sieboldiana agglutinin (SSA), Sambucus nigra agglutinin (SNA), Trichosanthes japonica agglutinin I (TJA-I), Amaranthus caudatus agglutinin (ACA), and Bauhinia purpurea lectin (BPL). The lectin microarray analysis using G3 type tissues demonstrated that stage I and stage III or IV were distinguished depending on signal pattern of three lectins, Dolichos biflorus agglutinin (DBA), BPL, and ACA. In addition, the analysis of the glycans on the ovarian cancer cells showed that only anticancer drug-sensitive cell lines had almost no activities to specific three lectins. Glycan profiling by the lectin microarray may be used to assess the characteristics of tumors and potentially to predict the success of chemotherapy treatment.

  20. Classification of large microarray datasets using fast random forest construction.

    PubMed

    Manilich, Elena A; Özsoyoğlu, Z Meral; Trubachev, Valeriy; Radivoyevitch, Tomas

    2011-04-01

    Random forest is an ensemble classification algorithm. It performs well when most predictive variables are noisy and can be used when the number of variables is much larger than the number of observations. The use of bootstrap samples and restricted subsets of attributes makes it more powerful than simple ensembles of trees. The main advantage of a random forest classifier is its explanatory power: it measures variable importance or impact of each factor on a predicted class label. These characteristics make the algorithm ideal for microarray data. It was shown to build models with high accuracy when tested on high-dimensional microarray datasets. Current implementations of random forest in the machine learning and statistics community, however, limit its usability for mining over large datasets, as they require that the entire dataset remains permanently in memory. We propose a new framework, an optimized implementation of a random forest classifier, which addresses specific properties of microarray data, takes computational complexity of a decision tree algorithm into consideration, and shows excellent computing performance while preserving predictive accuracy. The implementation is based on reducing overlapping computations and eliminating dependency on the size of main memory. The implementation's excellent computational performance makes the algorithm useful for interactive data analyses and data mining.

  1. Sequencing ebola and marburg viruses genomes using microarrays.

    PubMed

    Hardick, Justin; Woelfel, Roman; Gardner, Warren; Ibrahim, Sofi

    2016-08-01

    Periodic outbreaks of Ebola and Marburg hemorrhagic fevers have occurred in Africa over the past four decades with case fatality rates reaching as high as 90%. The latest Ebola outbreak in West Africa in 2014 raised concerns that these infections can spread across continents and pose serious health risks. Early and accurate identification of the causative agents is necessary to contain outbreaks. In this report, we describe sequencing-by-hybridization (SBH) technique using high density microarrays to identify Ebola and Marburg viruses. The microarrays were designed to interrogate the sequences of entire viral genomes, and were evaluated with three species of Ebolavirus (Reston, Sudan, and Zaire), and three strains of Marburgvirus (Angola, Musoke, and Ravn). The results showed that the consensus sequences generated with four or more hybridizations had 92.1-98.9% accuracy over 95-99% of the genomes. Additionally, with SBH microarrays it was possible to distinguish between different strains of the Lake Victoria Marburgvirus. J. Med. Virol. 88:1303-1308, 2016. © 2016 Wiley Periodicals, Inc.

  2. Classification of Microarray Data Using Kernel Fuzzy Inference System.

    PubMed

    Kumar, Mukesh; Kumar Rath, Santanu

    2014-01-01

    The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function.

  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. A Versatile Microarray Platform for Capturing Rare Cells

    PubMed Central

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

    2015-01-01

    Analyses of rare events occurring at extremely low frequencies in body fluids are still challenging. We established a versatile microarray-based platform able to capture single target cells from large background populations. As use case we chose the challenging application of detecting circulating tumor cells (CTCs) – about one cell in a billion normal blood cells. After incubation with an antibody cocktail, targeted cells are extracted on a microarray in a microfluidic chip. The accessibility of our platform allows for subsequent recovery of targets for further analysis. The microarray facilitates exclusion of false positive capture events by co-localization allowing for detection without fluorescent labelling. Analyzing blood samples from cancer patients with our platform reached and partly outreached gold standard performance, demonstrating feasibility for clinical application. Clinical researchers free choice of antibody cocktail without need for altered chip manufacturing or incubation protocol, allows virtual arbitrary targeting of capture species and therefore wide spread applications in biomedical sciences. PMID:26493176

  5. A New Distribution Family for Microarray Data †

    PubMed Central

    Kelmansky, Diana Mabel; Ricci, Lila

    2017-01-01

    The traditional approach with microarray data has been to apply transformations that approximately normalize them, with the drawback of losing the original scale. The alternative standpoint taken here is to search for models that fit the data, characterized by the presence of negative values, preserving their scale; one advantage of this strategy is that it facilitates a direct interpretation of the results. A new family of distributions named gpower-normal indexed by p∈R is introduced and it is proven that these variables become normal or truncated normal when a suitable gpower transformation is applied. Expressions are given for moments and quantiles, in terms of the truncated normal density. This new family can be used to model asymmetric data that include non-positive values, as required for microarray analysis. Moreover, it has been proven that the gpower-normal family is a special case of pseudo-dispersion models, inheriting all the good properties of these models, such as asymptotic normality for small variances. A combined maximum likelihood method is proposed to estimate the model parameters, and it is applied to microarray and contamination data. R codes are available from the authors upon request. PMID:28208652

  6. 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.

  7. 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.

  8. Chemical microarray: a new tool for drug screening and discovery.

    PubMed

    Ma, Haiching; Horiuchi, Kurumi Y

    2006-07-01

    HTS with microtiter plates has been the major tool used in the pharmaceutical industry to explore chemical diversity space and to identify active compounds and pharmacophores for specific biological targets. However, HTS faces a daunting challenge regarding the fast-growing numbers of drug targets arising from genomic and proteomic research, and large chemical libraries generated from high-throughput synthesis. There is an urgent need to find new ways to profile the activity of large numbers of chemicals against hundreds of biological targets in a fast, low-cost fashion. Chemical microarray can rise to this challenge because it has the capability of identifying and evaluating small molecules as potential therapeutic reagents. During the past few years, chemical microarray technology, with different surface chemistries and activation strategies, has generated many successes in the evaluation of chemical-protein interactions, enzyme activity inhibition, target identification, signal pathway elucidation and cell-based functional analysis. The success of chemical microarray technology will provide unprecedented possibilities and capabilities for parallel functional analysis of tremendous amounts of chemical compounds.

  9. A microarray scanner for the real-time quantitative detection

    NASA Astrophysics Data System (ADS)

    Liu, Quanjun; Zhuang, Ying; Wu, Lingwei; Wu, Zhongwei; Hu, Song; Lu, Zuhong

    2007-05-01

    The real-time and quantitative detection assay is important for the gene detection. With the TaqMan probes for the detection based polymerase chain reaction (PCR), four targets could be checked in a single process in solution assay. A new method is developed to immobilize the TaqMan probes on a microarray, which could be used to the multi-target gene fragment quantitative detection with PCR. A new type microarray scanner is designed for the assay. A thermocycler system was built into the scanner platform. A new type of the vessel sealed with the gene amplification solution which could perform the thermo-cycling and scanning. To decrease the background intensity a confocal system was used as the fluorescent intensity detection in the scanner. To calculate the gene quantity, a standard liner graph was draw with the fluorescent intensity versus the cycles. From the standard liner, the quantity of the original gene fragment could be calculated in time with the cycles. This scanner offers the great advantage of real-time quantitative detection of DNA targets in a microarray.

  10. A microarray-based method to perform nucleic acid selections.

    PubMed

    Aminova, Olga; Disney, Matthew D

    2010-01-01

    This method describes a microarray-based platform to perform nucleic acid selections. Chemical ligands to which a nucleic acid binder is desired are immobilized onto an agarose microarray surface; the array is then incubated with an RNA library. Bound RNA library members are harvested directly from the array surface via gel excision at the position on the array where a ligand was immobilized. The RNA is then amplified via RT-PCR, cloned, and sequenced. This method has the following advantages over traditional resin-based Systematic Evolution of Ligands by Exponential Enrichment (SELEX): (1) multiple selections can be completed in parallel on a single microarray surface; (2) kinetic biases in the selections are mitigated since all RNA binders are harvested from an array via gel excision; (3) the amount of chemical ligand needed to perform a selection is minimized; (4) selections do not require expensive resins or equipment; and (5) the matrix used for selections is inexpensive and easy to prepare. Although this protocol was demonstrated for RNA selections, it should be applicable for any nucleic acid selection.

  11. A Glance at DNA Microarray Technology and Applications

    PubMed Central

    Saei, Amir Ata; Omidi, Yadollah

    2011-01-01

    Introduction Because of huge impacts of “OMICS” technologies in life sciences, many researchers aim to implement such high throughput approach to address cellular and/or molecular functions in response to any influential intervention in genomics, proteomics, or metabolomics levels. However, in many cases, use of such technologies often encounters some cybernetic difficulties in terms of knowledge extraction from a bunch of data using related softwares. In fact, there is little guidance upon data mining for novices. The main goal of this article is to provide a brief review on different steps of microarray data handling and mining for novices and at last to introduce different PC and/or web-based softwares that can be used in preprocessing and/or data mining of microarray data. Methods To pursue such aim, recently published papers and microarray softwares were reviewed. Results It was found that defining the true place of the genes in cell networks is the main phase in our understanding of programming and functioning of living cells. This can be obtained with global/selected gene expression profiling. Conclusion Studying the regulation patterns of genes in groups, using clustering and classification methods helps us understand different pathways in the cell, their functions, regulations and the way one component in the system affects the other one. These networks can act as starting points for data mining and hypothesis generation, helping us reverse engineer. PMID:23678411

  12. 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

  13. Identification of candidate genes in osteoporosis by integrated microarray analysis

    PubMed Central

    Li, J. J.; Wang, B. Q.; Yang, Y.; Li, D.

    2016-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and

  14. The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

    EPA Science Inventory

    The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

  15. 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

  16. Microarray identification of bacterial species in peritonsillar abscesses.

    PubMed

    Wikstén, J E; Laakso, S; Mäki, M; Mäkitie, A A; Pitkäranta, A; Blomgren, K

    2015-05-01

    Peritonsillar abscess (PTA) is the most common otorhinolaryngological infection, requiring management at the special healthcare level. The microbiological findings vary due to geographical, etiological, and methodological factors. This study aimed to identify the bacterial species of PTAs by using a novel polymerase chain reaction (PCR)- and microarray-based assay, and to find causative cofactors among patients with different pathogens. We determined the bacterial findings of aspirates of pus prospectively collected from 180 PTA patients. Samples were pretreated prior to nucleic acid extraction and analyzed with a PCR- and microarray-based assay or DNA sequencing. Both methods were based on the gyrB/parE topoisomerase genes. Patients answered symptom questionnaires at admission, and their medical records were reviewed later. Altogether, 160 (89 %) aspirates of pus tested positive for bacteria, and a bacterial species was identified in 149 (83 %) of the samples. A polybacterial species was detected in 20 (13 %) and anaerobic bacteria in 77 (52 %) of the 149 samples. Fusobacterium necrophorum patients were younger (p < 0 .001) and had more severe symptoms (p = 0.04) than patients with other pathogens. Gender, smoking, or preadmission antibiotics showed no correlation with any of the pathogens. Although requiring some optimization, this microarray assay seems feasible and fast for bacterial identification directly from pus samples, and confirms the diversity of PTA pathogens. Young patients with more severe symptoms may require special attention. Species-specific antibiotic treatment of PTA remains challenging due to bacterial variations; the present assay may aid in specifying PTA antibiotic treatment in the future.

  17. Etiological yield of SNP microarrays in idiopathic intellectual disability.

    PubMed

    Utine, G Eda; Haliloğlu, Göknur; Volkan-Salancı, Bilge; Çetinkaya, Arda; Kiper, Pelin Ö; Alanay, Yasemin; Aktaş, Dilek; Anlar, Banu; Topçu, Meral; Boduroğlu, Koray; Alikaşifoğlu, Mehmet

    2014-05-01

    Intellectual disability (ID) has a prevalence of 3% and is classified according to its severity. An underlying etiology cannot be determined in 75-80% in mild ID, and in 20-50% of severe ID. After it has been shown that copy number variations involving short DNA segments may cause ID, genome-wide SNP microarrays are being used as a tool for detecting submicroscopic copy number changes and uniparental disomy. This study was performed to investigate the presence of copy number changes in patients with ID of unidentified etiology. Affymetrix(®) 6.0 SNP microarray platform was used for analysis of 100 patients and their healthy parents, and data were evaluated using various databases and literature. Etiological diagnoses were made in 12 patients (12%). Homozygous deletion in NRXN1 gene and duplication in IL1RAPL1 gene were detected for the first time. Two separate patients had deletions in FOXP2 and UBE2A genes, respectively, for which only few patients have recently been reported. Interstitial and subtelomeric copy number changes were described in 6 patients, in whom routine cytogenetic tools revealed normal results. In one patient uniparental disomy type of Angelman syndrome was diagnosed. SNP microarrays constitute a screening test able to detect very small genomic changes, with a high etiological yield even in patients already evaluated using traditional cytogenetic tools, offer analysis for uniparental disomy and homozygosity, and thereby are helpful in finding novel disease-causing genes: for these reasons they should be considered as a first-tier genetic screening test in the evaluation of patients with ID and autism.

  18. Environmental microarray analyses of Antarctic soil microbial communities.

    PubMed

    Yergeau, Etienne; Schoondermark-Stolk, Sung A; Brodie, Eoin L; Déjean, Sébastien; DeSantis, Todd Z; Gonçalves, Olivier; Piceno, Yvette M; Andersen, Gary L; Kowalchuk, George A

    2009-03-01

    Antarctic ecosystems are fascinating in their limited trophic complexity, with decomposition and nutrient cycling functions being dominated by microbial activities. Not only are Antarctic habitats exposed to extreme environmental conditions, the Antarctic Peninsula is also experiencing unequalled effects of global warming. Owing to their uniqueness and the potential impact of global warming on these pristine systems, there is considerable interest in determining the structure and function of microbial communities in the Antarctic. We therefore utilized a recently designed 16S rRNA gene microarray, the PhyloChip, which targets 8741 bacterial and archaeal taxa, to interrogate microbial communities inhabiting densely vegetated and bare fell-field soils along a latitudinal gradient ranging from 51 degrees S (Falkland Islands) to 72 degrees S (Coal Nunatak). Results indicated a clear decrease in diversity with increasing latitude, with the two southernmost sites harboring the most distinct Bacterial and Archaeal communities. The microarray approach proved more sensitive in detecting the breadth of microbial diversity than polymerase chain reaction-based bacterial 16S rRNA gene libraries of modest size ( approximately 190 clones per library). Furthermore, the relative signal intensities summed for phyla and families on the PhyloChip were significantly correlated with the relative occurrence of these taxa in clone libraries. PhyloChip data were also compared with functional gene microarray data obtained earlier, highlighting numerous significant relationships and providing evidence for a strong link between community composition and functional gene distribution in Antarctic soils. Integration of these PhyloChip data with other complementary methods provides an unprecedented understanding of the microbial diversity and community structure of terrestrial Antarctic habitats.

  19. Optimized LOWESS normalization parameter selection for DNA microarray data

    PubMed Central

    Berger, John A; Hautaniemi, Sampsa; Järvinen, Anna-Kaarina; Edgren, Henrik; Mitra, Sanjit K; Astola, Jaakko

    2004-01-01

    Background Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail. Results and discussion In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies. Conclusions Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical

  20. 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.

  1. Design issues in toxicogenomics using DNA microarray experiment

    SciTech Connect

    Lee, Kyoung-Mu; Kim, Ju-Han; Kang, Daehee . E-mail: dhkang@snu.ac.kr

    2005-09-01

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

  2. Network theory to understand microarray studies of complex diseases.

    PubMed

    Benson, Mikael; Breitling, Rainer

    2006-09-01

    Complex diseases, such as allergy, diabetes and obesity depend on altered interactions between multiple genes, rather than changes in a single causal gene. DNA microarray studies of a complex disease often implicate hundreds of genes in the pathogenesis. This indicates that many different mechanisms and pathways are involved. How can we understand such complexity? How can hypotheses be formulated and tested? One approach is to organize the data in network models and to analyze these in a top-down manner. Globally, networks in nature are often characterized by a small number of highly connected nodes, while the majority of nodes have few connections. The highly connected nodes serve as hubs that affect many other nodes. Such hubs have key roles in the network. In yeast cells, for example, deletion of highly connected proteins is associated with increased lethality, compared to deletion of less connected proteins. This suggests the biological relevance of networks. Moving down in the network structure, there may be sub-networks or modules with specific functions. These modules may be further dissected to analyze individual nodes. In the context of DNA microarray studies of complex diseases, gene-interaction networks may contain modules of co-regulated or interacting genes that have distinct biological functions. Such modules may be linked to specific gene polymorphisms, transcription factors, cellular functions and disease mechanisms. Genes that are reliably active only in the context of their modules can be considered markers for the activity of the modules and may thus be promising candidates for biomarkers or therapeutic targets. This review aims to give an introduction to network theory and how it can be applied to microarray studies of complex diseases.

  3. Protein microarrays and quantum dot probes for early cancer detection.

    PubMed

    Zajac, Aleksandra; Song, Dansheng; Qian, Wei; Zhukov, Tatyana

    2007-08-01

    We describe here a novel approach for detection of cancer markers using quantum dot protein microarrays. Both relatively new technologies; quantum dots and protein microarrays, offer very unique features that together allow detection of cancer markers in biological specimens (serum, plasma, body fluids) at pg/ml concentration. Quantum dots offer remarkable photostability and brightness. They do not exhibit photobleaching common to organic fluorophores. Moreover, the high emission amplitude for QDs results in a marked improvement in the signal to noise ratio of the final image. Protein microarrays allow highly parallel quantitation of specific proteins in a rapid, low-cost and low sample volume format. Furthermore the multiplexed assay enables detection of many proteins at once in one sample, making it a powerful tool for biomarker analysis and early cancer diagnostics. In a series of multiplexing experiments we investigated ability of the platform to detect six different cytokines in protein solution. We were able to detect TNF-alpha, IL-8, IL-6, MIP-1beta, IL-13 and IL-1beta down to picomolar concentration, demonstrating high sensitivity of the investigated detection system. We have also constructed and investigated two different models of quantum dot probes. One by conjugation of nanocrystals to antibody specific to the selected marker--IL-10, and the second by use of streptavidin coated quantum dots and biotinylated detector antibody. Comparison of those two models showed better performance of streptavidin QD-biotinylated detector antibody model. Data quantitated using custom designed computer program (CDAS) show that proposed methodology allows monitoring of changes in biomarker concentration in physiological range.

  4. Up-to-Date Applications of Microarrays and Their Way to Commercialization

    PubMed Central

    Schumacher, Sarah; Muekusch, Sandra; Seitz, Harald

    2015-01-01

    This review addresses up-to-date applications of Protein Microarrays. Protein Microarrays play a significant role in basic research as well as in clinical applications and are applicable in a lot of fields, e.g., DNA, proteins and small molecules. Additionally they are on the way to enter clinics in routine diagnostics. Protein Microarrays can be powerful tools to improve healthcare. An overview of basic characteristics to mediate essential knowledge of this technique is given. To reach this goal, some challenges still have to be addressed. A few applications of Protein Microarrays in a medical context are shown. Finally, an outlook, where the potential of Protein Microarrays is depicted and speculations how the future of Protein Microarrays will look like are made. PMID:27600220

  5. Optimization of Cyanine Dye Stability and Analysis of FRET Interaction on DNA Microarrays

    PubMed Central

    von der Haar, Marcel; Heuer, Christopher; Pähler, Martin; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2016-01-01

    The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs. PMID:27916881

  6. Development of a protein microarray using sequence-specific DNA binding domain on DNA chip surface

    SciTech Connect

    Choi, Yoo Seong; Pack, Seung Pil; Yoo, Young Je . E-mail: yjyoo@snu.ac.kr

    2005-04-22

    A protein microarray based on DNA microarray platform was developed to identify protein-protein interactions in vitro. The conventional DNA chip surface by 156-bp PCR product was prepared for a substrate of protein microarray. High-affinity sequence-specific DNA binding domain, GAL4 DNA binding domain, was introduced to the protein microarray as fusion partner of a target model protein, enhanced green fluorescent protein. The target protein was oriented immobilized directly on the DNA chip surface. Finally, monoclonal antibody of the target protein was used to identify the immobilized protein on the surface. This study shows that the conventional DNA chip can be used to make a protein microarray directly, and this novel protein microarray can be applicable as a tool for identifying protein-protein interactions.

  7. Fabrication of carbohydrate microarrays on a poly(2-hydroxyethyl methacrylate)-based photoactive substrate.

    PubMed

    Sundhoro, Madanodaya; Wang, Hui; Boiko, Scott T; Chen, Xuan; Jayawardena, H Surangi N; Park, JaeHyeung; Yan, Mingdi

    2016-01-21

    We report the fabrication of carbohydrate microarrays on a photoactive polymer, poly(HEMA-co-HEMA-PFPA), synthesized by RAFT copolymerization of 2-hydroxyethyl methacrylate (HEMA) and perfluorophenyl azide (PFPA)-derivatized HEMA (HEMA-PFPA). PFPA allows the covalent immobilization of carbohydrates whereas the HEMA polymer provides an antifouling surface, thus the microarrays can be used directly without pretreating the array with a blocking agent. The microarrays were prepared by spin-coating the polymer followed by printing the carbohydrates. Subsequent irradiation simultaneously immobilized the carbohydrates and crosslinked the polymer matrix. The obtained 3D carbohydrate microarrays showed enhanced fluorescence signals upon treating with a fluorescent lectin in comparison with a 2D microarray. The signals were acquired at a lower lectin concentration and a shorter incubation time. When treated with E. coli bacteria, the carbohydrate microarray showed results that were consistent with their binding patterns.

  8. Up-to-Date Applications of Microarrays and Their Way to Commercialization.

    PubMed

    Schumacher, Sarah; Muekusch, Sandra; Seitz, Harald

    2015-04-23

    This review addresses up-to-date applications of Protein Microarrays. Protein Microarrays play a significant role in basic research as well as in clinical applications and are applicable in a lot of fields, e.g., DNA, proteins and small molecules. Additionally they are on the way to enter clinics in routine diagnostics. Protein Microarrays can be powerful tools to improve healthcare. An overview of basic characteristics to mediate essential knowledge of this technique is given. To reach this goal, some challenges still have to be addressed. A few applications of Protein Microarrays in a medical context are shown. Finally, an outlook, where the potential of Protein Microarrays is depicted and speculations how the future of Protein Microarrays will look like are made.

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

    PubMed

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

    2015-04-24

    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.

  10. Technical Considerations in using DNA Microarrays to Define Regulons

    PubMed Central

    Rhodius, Virgil A.; Wade, Joseph T.

    2009-01-01

    Transcription is the major regulatory target of gene expression in bacteria, and is controlled by many regulatory proteins and RNAs. Microarrays are a powerful tool to study the regulation of transcription on a genomic scale. Here we describe the use of transcription profiling and ChIP-chip to study transcriptional regulation in bacteria. Transcription profiling determines the outcome of regulatory events whereas ChIP-chip identifies the protein-DNA interactions that determine these events. Together they can provide detailed information on transcriptional regulatory systems. PMID:18955146

  11. Phenotype microarray technology and its application in industrial biotechnology.

    PubMed

    Greetham, Darren

    2014-06-01

    Phenotype microarray (PM) technology provides an insight into the metabolic profiling of microbial cells within 96-well plate system. The PM assay allows for cells to be assessed for utilisation of nutrients or sensitivity to toxic compounds. The assay utilises a redox sensitive tetrazolium dye which becomes irreversibly reduced upon detection of cellular metabolic output, detection is synchronous with a colour change from colourless to purple. Output from PM technology can be measured visually or quantified by reader the absorbance in each well. PM technology has highlighted differences in growth requirements, nutrient utilisation, sensitivity to toxins, and genetic diversity in bacteria, fungi and mammalian cells.

  12. Dielectrophoretic Manipulation and Separation of Microparticles Using Microarray Dot Electrodes

    PubMed Central

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

    2014-01-01

    This paper introduces a dielectrophoretic system for the manipulation and separation of microparticles. The system is composed of five layers and utilizes microarray dot electrodes. We validated our system by conducting size-dependent manipulation and separation experiments on 1, 5 and 15 μm polystyrene particles. Our findings confirm the capability of the proposed device to rapidly and efficiently manipulate and separate microparticles of various dimensions, utilizing positive and negative dielectrophoresis (DEP) effects. Larger size particles were repelled and concentrated in the center of the dot by negative DEP, while the smaller sizes were attracted and collected by the edge of the dot by positive DEP. PMID:24705632

  13. High quality epoxysilane substrate for clinical multiplex serodiagnostic proteomic microarrays

    NASA Astrophysics Data System (ADS)

    Ewart, Tom; Carmichael, Stuart; Lea, Peter

    2005-09-01

    Polylysine and aminopropylsilane treated glass comprised the majority of substrates employed in first generation genetic microarray substrates. Second generation single stranded long oligo libraries with amino termini provided for controlled terminal specific attachment, and rationally designed unique sequence libraries with normalized melting temperatures. These libraries benefit from active covalent coupling surfaces such as Epoxysilane. The latter's oxime ring shows versatile reactivity with amino-, thiol- and hydroxyl- groups thus encompassing small molecule, oligo and proteomic microarray applications. Batch-to-batch production uniformity supports entry of the Epoxysilane process into clinical diagnostics. We carried out multiple print runs of 21 clinically relevant bacterial and viral antigens at optimized concentrations, plus human IgG and IgM standards in triplicate on multiple batches of Epoxysilane substrates. A set of 45 patient sera were assayed in a 35 minute protocol using 10 microliters per array in a capillary-fill format (15 minute serum incubation, wash, 15 minute incubation with Cy3-labeled anti-hIgG plus Dy647-labeled anti-hIgM, final wash). The LOD (3 SD above background) was better than 1 microgram/ml for IgG, and standard curves were regular and monotonically increasing over the range 0 to 1000 micrograms/ml. Ninety-five percent of the CVs for the standards were under 10%, and 90% percent of CVs for antigen responses were under 10% across all batches of Epoxysilane and print runs. In addition, where SDs are larger than expected, microarray images may be readily reviewed for quality control purposes and pin misprints quickly identified. In order to determine the influence of stirring on sensitivity and speed of the microarray assay, we printed 10 common ToRCH antigens (H. pylori, T. gondii, Rubella, Rubeola, C. trachomatis, Herpes 1 and 2, CMV, C. jejuni, and EBV) in Epoxysilane-activated slide-wells. Anti-IgG-Cy3 direct binding to printed Ig

  14. Oligonucleotide microarray for subtyping of influenza A viruses

    NASA Astrophysics Data System (ADS)

    Klotchenko, S. A.; Vasin, A. V.; Sandybaev, N. T.; Plotnikova, M. A.; Chervyakova, O. V.; Smirnova, E. A.; Kushnareva, E. V.; Strochkov, V. M.; Taylakova, E. T.; Egorov, V. V.; Koshemetov, J. K.; Kiselev, O. I.; Sansyzbay, A. R.

    2012-02-01

    Influenza is one of the most widespread respiratory viral diseases, infecting humans, horses, pigs, poultry and some other animal populations. Influenza A viruses (IAV) are classified into subtypes on the basis of the surface hemagglutinin (H1 to H16) and neuraminidase (N1 to N9) glycoproteins. The correct determination of IAV subtype is necessary for clinical and epidemiological studies. In this article we propose an oligonucleotide microarray for subtyping of IAV using universal one-step multisegment RT-PCR fluorescent labeling of viral gene segments. It showed to be an advanced approach for fast detection and identification of IAV.

  15. Glycan Microarrays of Fluorescently-Tagged Natural Glycans

    PubMed Central

    Song, Xuezheng; Heimburg-Molinaro, Jamie; Smith, David F.; Cummings, Richard D.

    2015-01-01

    This review discusses the challenges facing research in ‘functional glycomics’ and the novel technologies that are being developed to advance the field. The structural complexity of glycans and glycoconjugates makes studies of both their structures and recognition difficult. However, these intricate structures can be captured from their natural sources, isolated and fluorescently-tagged for detailed structural analysis and for presentation on glycan microarrays for functional recognition by glycan-binding proteins. These advances in glycan preparation and manipulation enable the streamlining of functional glycomics studies and will help to propel the field forward in studying natural, biologically relevant glycans. PMID:25877830

  16. E-Predict: a computational strategy for species identification based on observed DNA microarray hybridization patterns.

    PubMed

    Urisman, Anatoly; Fischer, Kael F; Chiu, Charles Y; Kistler, Amy L; Beck, Shoshannah; Wang, David; DeRisi, Joseph L

    2005-01-01

    DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications.

  17. Sandwich ELISA Microarrays: Generating Reliable and Reproducible Assays for High-Throughput Screens

    SciTech Connect

    Gonzalez, Rachel M.; Varnum, Susan M.; Zangar, Richard C.

    2009-05-11

    The sandwich ELISA microarray is a powerful screening tool in biomarker discovery and validation due to its ability to simultaneously probe for multiple proteins in a miniaturized assay. The technical challenges of generating and processing the arrays are numerous. However, careful attention to possible pitfalls in the development of your antibody microarray assay can overcome these challenges. In this chapter, we describe in detail the steps that are involved in generating a reliable and reproducible sandwich ELISA microarray assay.

  18. A model of base-call resolution on broad-spectrum pathogen detection resequencing DNA microarrays.

    PubMed

    Malanoski, Anthony P; Lin, Baochuan; Stenger, David A

    2008-06-01

    Oligonucleotide microarrays offer the potential to efficiently test for multiple organisms, an excellent feature for surveillance applications. Among these, resequencing microarrays are of particular interest, as they possess additional unique capabilities to track pathogens' genetic variations and perform detailed discrimination of closely related organisms. However, this potential can only be realized if the costs of developing the detection microarray are kept at a manageable level. Selection and verification of the probes are key factors affecting microarray design costs that can be reduced through the development and use of in silico modeling. Models created for other types of microarrays do not meet all the required criteria for this type of microarray. We describe here in silico methods for designing resequencing microarrays targeted for multiple organism detection. The model development presented here has focused on accurate base-call prediction in regions that are applicable to resequencing microarrays designed for multiple organism detection, a variation from other uses of a predictive model in which perfect prediction of all hybridization events is necessary. The model will assist in simplifying the design of resequencing microarrays and in reduction of the time and costs required for their development for new applications.

  19. 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.

  20. Structural analysis of hepatitis C RNA genome using DNA microarrays

    PubMed Central

    Martell, María; Briones, Carlos; de Vicente, Aránzazu; Piron, María; Esteban, Juan I.; Esteban, Rafael; Guardia, Jaime; Gómez, Jordi

    2004-01-01

    Many studies have tried to identify specific nucleotide sequences in the quasispecies of hepatitis C virus (HCV) that determine resistance or sensitivity to interferon (IFN) therapy, unfortunately without conclusive results. Although viral proteins represent the most evident phenotype of the virus, genomic RNA sequences determine secondary and tertiary structures which are also part of the viral phenotype and can be involved in important biological roles. In this work, a method of RNA structure analysis has been developed based on the hybridization of labelled HCV transcripts to microarrays of complementary DNA oligonucleotides. Hybridizations were carried out at non-denaturing conditions, using appropriate temperature and buffer composition to allow binding to the immobilized probes of the RNA transcript without disturbing its secondary/tertiary structural motifs. Oligonucleotides printed onto the microarray covered the entire 5′ non-coding region (5′NCR), the first three-quarters of the core region, the E2–NS2 junction and the first 400 nt of the NS3 region. We document the use of this methodology to analyse the structural degree of a large region of HCV genomic RNA in two genotypes associated with different responses to IFN treatment. The results reported here show different structural degree along the genome regions analysed, and differential hybridization patterns for distinct genotypes in NS2 and NS3 HCV regions. PMID:15247323

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

    NASA Astrophysics Data System (ADS)

    Tchagang, Alain B.; Tewfik, Ahmed H.

    2006-12-01

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

  2. 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.

  3. 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

  4. Portable system for microbial sample preparation and oligonucleotide microarray analysis.

    SciTech Connect

    Bavykin, S. G.; Akowski, J. P.; Zakhariev, V. M.; Barsky, V. E.; Mirzabekov, A. D.; Perov, A. N.; Biochip Technology Center; Engelhardt Inst. of Molecular Biology

    2001-02-01

    We have developed a three-component system for microbial identification that consists of (i) a universal syringe-operated silica minicolumn for successive DNA and RNA isolation, fractionation, fragmentation, fluorescent labeling, and removal of excess free label and short oligonucleotides; (ii) microarrays of immobilized oligonucleotide probes for 16S rRNA identification; and (iii) a portable battery-powered device for imaging the hybridization of fluorescently labeled RNA fragments with the arrays. The minicolumn combines a guanidine thiocyanate method of nucleic acid isolation with a newly developed hydroxyl radical-based technique for DNA and RNA labeling and fragmentation. DNA and RNA can also be fractionated through differential binding of double- and single-stranded forms of nucleic acids to the silica. The procedure involves sequential washing of the column with different solutions. No vacuum filtration steps, phenol extraction, or centrifugation is required. After hybridization, the overall fluorescence pattern is captured as a digital image or as a Polaroid photo. This three-component system was used to discriminate Escherichia coli, Bacillus subtilis, Bacillus thuringiensis, and human HL60 cells. The procedure is rapid: beginning with whole cells, it takes approximately 25 min to obtain labeled DNA and RNA samples and an additional 25 min to hybridize and acquire the microarray image using a stationary image analysis system or the portable imager.

  5. 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

  6. Kinship Testing Based on SNPs Using Microarray System

    PubMed Central

    Cho, Sohee; Seo, Hee Jin; Lee, Jihyun; Yu, Hyung Jin; Lee, Soong Deok

    2016-01-01

    Background Kinship testing using biallelic SNP markers has been demonstrated to be a promising approach as a supplement to standard STR typing, and several systems, such as pyrosequencing and microarray, have been introduced and utilized in real forensic cases. The Affymetrix microarray containing 169 autosomal SNPs developed for forensic application was applied to our practical case for kinship analysis that had remained inconclusive due to partial STR profiles of degraded DNA and possibility of inbreeding within the population. Case Report 169 autosomal SNPs were typed on array with severely degraded DNA of two bone samples, and the kinship compared to genotypes in a reference database of their putative family members. Results Two bone samples remained unidentified through traditional STR typing with partial profiles of 10 or 14 of 16 alleles. Because these samples originated from a geographically isolated population, a cautious approach was required when analyzing and declaring true paternity only based on PI values. In a supplementary SNP typing, 106 and 78 SNPs were obtained, and the match candidates were found in each case with improved PI values than using only STRs and with no discrepant SNPs in comparison. Conclusion Our case showed that the utility of multiple SNPs on array is expected in practical forensic caseworks with an establishment of reference database. PMID:27994531

  7. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation

    PubMed Central

    Datar, Akshata; Joshi, Pranav; Lee, Moo-Yeal

    2015-01-01

    Conventional drug screening processes are a time-consuming and expensive endeavor, but highly rewarding when they are successful. To identify promising lead compounds, millions of compounds are traditionally screened against therapeutic targets on human cells grown on the surface of 96-wells. These two-dimensional (2D) cell monolayers are physiologically irrelevant, thus, often providing false-positive or false-negative results, when compared to cells grown in three-dimensional (3D) structures such as hydrogel droplets. However, 3D cell culture systems are not easily amenable to high-throughput screening (HTS), thus inherently low throughput, and requiring relatively large volume for cell-based assays. In addition, it is difficult to control cellular microenvironments and hard to obtain reliable cell images due to focus position and transparency issues. To overcome these problems, miniaturized 3D cell cultures in hydrogels were developed via cell printing techniques where cell spots in hydrogels can be arrayed on the surface of glass slides or plastic chips by microarray spotters and cultured in growth media to form cells encapsulated 3D droplets for various cell-based assays. These approaches can dramatically reduce assay volume, provide accurate control over cellular microenvironments, and allow us to obtain clear 3D cell images for high-content imaging (HCI). In this review, several hydrogels that are compatible to microarray printing robots are discussed for miniaturized 3D cell cultures. PMID:26516921

  8. Exon Microarray Analysis of Human Dorsolateral Prefrontal Cortex in Alcoholism

    PubMed Central

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

    2014-01-01

    Background Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Methods Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC, Brodmann area 9) of 7 adult Alcoholic (6 males, 1 female, mean age 48 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST Array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using qRT-PCR, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Results Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN) and signaling (e.g., RASGRP, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease, and development including cellular assembly and organization impacting on psychological disorders. Conclusions Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation and signaling that targets white matter of the brain. PMID:24890784

  9. Novel microarray design strategy to study complex bacterial communities.

    PubMed

    Huyghe, Antoine; Francois, Patrice; Charbonnier, Yvan; Tangomo-Bento, Manuela; Bonetti, Eve-Julie; Paster, Bruce J; Bolivar, Ignacio; Baratti-Mayer, Denise; Pittet, Didier; Schrenzel, Jacques

    2008-03-01

    Assessing bacterial flora composition appears to be of increasing importance to fields as diverse as physiology, development, medicine, epidemiology, the environment, and the food industry. We report here the development and validation of an original microarray strategy that allows analysis of the phylogenic composition of complex bacterial mixtures. The microarray contains approximately 9,500 feature elements targeting 16S rRNA gene-specific regions. Probe design was performed by selecting oligonucleotide sequences specific to each node of the seven levels of the bacterial phylogenetic tree (domain, phylum, class, order, family, genus, and species). This approach, based on sequence information, allows analysis of the bacterial contents of complex bacterial mixtures to detect both known and unknown microorganisms. The presence of unknown organisms can be suspected and mapped on the phylogenetic tree, indicating where to refine analysis. Initial proof-of-concept experiments were performed on oral bacterial communities. Our results show that this hierarchical approach can reveal minor changes (

  10. Massively parallel pathogen identification using high‐density microarrays

    PubMed Central

    Berthet, Nicolas; Dickinson, Philip; Filliol, Ingrid; Reinhardt, Anita K.; Batejat, Christophe; Vallaeys, Tatiana; Kong, Katherine A.; Davies, Christopher; Lee, Walter; Zhang, Shenglan; Turpaz, Yaron; Heym, Beate; Coralie, Gilberte; Dacheux, Laurent; Burguière, Ana Maria; Bourhy, Hervé; Old, Iain G.; Manuguerra, Jean‐Claude; Cole, Stewart T.; Kennedy, Giulia C.

    2008-01-01

    Summary Identification of microbial pathogens in clinical specimens is still performed by phenotypic methods that are often slow and cumbersome, despite the availability of more comprehensive genotyping technologies. We present an approach based on whole‐genome amplification and resequencing microarrays for unbiased pathogen detection. This 10 h process identifies a broad spectrum of bacterial and viral species and predicts antibiotic resistance and pathogenicity and virulence profiles. We successfully identify a variety of bacteria and viruses, both in isolation and in complex mixtures, and the high specificity of the microarray distinguishes between different pathogens that cause diseases with overlapping symptoms. The resequencing approach also allows identification of organisms whose sequences are not tiled on the array, greatly expanding the repertoire of identifiable organisms and their variants. We identify organisms by hybridization of their DNA in as little as 1–4 h. Using this method, we identified Monkeypox virus and drug‐resistant Staphylococcus aureus in a skin lesion taken from a child suspected of an orthopoxvirus infection, despite poor transport conditions of the sample, and a vast excess of human DNA. Our results suggest this technology could be applied in a clinical setting to test for numerous pathogens in a rapid, sensitive and unbiased manner. PMID:21261824

  11. Variance estimation in the analysis of microarray data.

    PubMed

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

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  12. A microarray for assessing transcription from pelagic marine microbial taxa

    PubMed Central

    Shilova, Irina N; Robidart, Julie C; James Tripp, H; Turk-Kubo, Kendra; Wawrik, Boris; Post, Anton F; Thompson, Anne W; Ward, Bess; Hollibaugh, James T; Millard, Andy; Ostrowski, Martin; J Scanlan, David; Paerl, Ryan W; Stuart, Rhona; Zehr, Jonathan P

    2014-01-01

    Metagenomic approaches have revealed unprecedented genetic diversity within microbial communities across vast expanses of the world's oceans. Linking this genetic diversity with key metabolic and cellular activities of microbial assemblages is a fundamental challenge. Here we report on a collaborative effort to design MicroTOOLs (Microbiological Targets for Ocean Observing Laboratories), a high-density oligonucleotide microarray that targets functional genes of diverse taxa in pelagic and coastal marine microbial communities. MicroTOOLs integrates nucleotide sequence information from disparate data types: genomes, PCR-amplicons, metagenomes, and metatranscriptomes. It targets 19 400 unique sequences over 145 different genes that are relevant to stress responses and microbial metabolism across the three domains of life and viruses. MicroTOOLs was used in a proof-of-concept experiment that compared the functional responses of microbial communities following Fe and P enrichments of surface water samples from the North Pacific Subtropical Gyre. We detected transcription of 68% of the gene targets across major taxonomic groups, and the pattern of transcription indicated relief from Fe limitation and transition to N limitation in some taxa. Prochlorococcus (eHLI), Synechococcus (sub-cluster 5.3) and Alphaproteobacteria SAR11 clade (HIMB59) showed the strongest responses to the Fe enrichment. In addition, members of uncharacterized lineages also responded. The MicroTOOLs microarray provides a robust tool for comprehensive characterization of major functional groups of microbes in the open ocean, and the design can be easily amended for specific environments and research questions. PMID:24477198

  13. Bacterial DNA microarrays for clinical microbiology: the early logarithmic phase.

    PubMed

    Cassone, Marco; Giordano, Antonio; Pozzi, Gianni

    2007-01-01

    In this era of coexistence of high-throughput sequencing technologies and serious difficulties in the management of both common and novel infectious syndromes, new techniques which improve the study of micro-organisms is timely. In bacteriology, the most important subjects are bacterial pathogenicity, discovery of the genomic complexity of bacteria, and the epidemiology of antimicrobial resistance traits. From the clinical point of view, genetic testing is flanking phenotypic testing for the assessment of new, difficult to test antibiotic resistance traits, and for correlations with the microbial behaviour in vivo. The demand for faster, comprehensive and highly parallel microbial diagnostics is also cogent even at the basic laboratory level, where the ultimate objective is saving lives. In this setting, DNA microarrays offer a pivotal contribution by allowing performance of hybridization experiments in highly parallel formats, with an increasing reliability. Not only they are useful in deciphering host and microbial pathophysiology, they can also make the difference in the management of prognostic and therapeutic aspects of many diseases. Here, we provide an overview of the current use and the potential of DNA microarrays in clinical bacteriology, and several applications and technical solutions are discussed.

  14. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation.

    PubMed

    Datar, Akshata; Joshi, Pranav; Lee, Moo-Yeal

    2015-10-26

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

  15. 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.

  16. Systematic interpretation of microarray data using experiment annotations

    PubMed Central

    Fellenberg, Kurt; Busold, Christian H; Witt, Olaf; Bauer, Andrea; Beckmann, Boris; Hauser, Nicole C; Frohme, Marcus; Winter, Stefan; Dippon, Jürgen; Hoheisel, Jörg D

    2006-01-01

    Background Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format. Results We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel) and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design. Conclusion Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details. PMID:17181856

  17. Gene expression profiling in peanut using high density oligonucleotide microarrays

    PubMed Central

    Payton, Paxton; Kottapalli, Kameswara Rao; Rowland, Diane; Faircloth, Wilson; Guo, Baozhu; Burow, Mark; Puppala, Naveen; Gallo, Maria

    2009-01-01

    Background Transcriptome expression analysis in peanut to date has been limited to a relatively small set of genes and only recently has a significant number of ESTs been released into the public domain. Utilization of these ESTs for oligonucleotide microarrays provides a means to investigate large-scale transcript responses to a variety of developmental and environmental signals, ultimately improving our understanding of plant biology. Results We have developed a high-density oligonucleotide microarray for peanut using 49,205 publicly available ESTs and tested the utility of this array for expression profiling in a variety of peanut tissues. To identify putatively tissue-specific genes and demonstrate the utility of this array for expression profiling in a variety of peanut tissues, we compared transcript levels in pod, peg, leaf, stem, and root tissues. Results from this experiment showed 108 putatively pod-specific/abundant genes, as well as transcripts whose expression was low or undetected in pod compared to peg, leaf, stem, or root. The transcripts significantly over-represented in pod include genes responsible for seed storage proteins and desiccation (e.g., late-embryogenesis abundant proteins, aquaporins, legumin B), oil production, and cellular defense. Additionally, almost half of the pod-abundant genes represent unknown genes allowing for the possibility of associating putative function to these previously uncharacterized genes. Conclusion The peanut oligonucleotide array represents the majority of publicly available peanut ESTs and can be used as a tool for expression profiling studies in diverse tissues. PMID:19523230

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

    PubMed Central

    Warnat, Patrick; Eils, Roland; Brors, Benedikt

    2005-01-01

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

  19. A salmonid EST genomic study: genes, duplications, phylogeny and microarrays

    PubMed Central

    Koop, Ben F; von Schalburg, Kristian R; Leong, Jong; Walker, Neil; Lieph, Ryan; Cooper, Glenn A; Robb, Adrienne; Beetz-Sargent, Marianne; Holt, Robert A; Moore, Richard; Brahmbhatt, Sonal; Rosner, Jamie; Rexroad, Caird E; McGowan, Colin R; Davidson, William S

    2008-01-01

    Background Salmonids are of interest because of their relatively recent genome duplication, and their extensive use in wild fisheries and aquaculture. A comprehensive gene list and a comparison of genes in some of the different species provide valuable genomic information for one of the most widely studied groups of fish. Results 298,304 expressed sequence tags (ESTs) from Atlantic salmon (69% of the total), 11,664 chinook, 10,813 sockeye, 10,051 brook trout, 10,975 grayling, 8,630 lake whitefish, and 3,624 northern pike ESTs were obtained in this study and have been deposited into the public databases. Contigs were built and putative full-length Atlantic salmon clones have been identified. A database containing ESTs, assemblies, consensus sequences, open reading frames, gene predictions and putative annotation is available. The overall similarity between Atlantic salmon ESTs and those of rainbow trout, chinook, sockeye, brook trout, grayling, lake whitefish, northern pike and rainbow smelt is 93.4, 94.2, 94.6, 94.4, 92.5, 91.7, 89.6, and 86.2% respectively. An analysis of 78 transcript sets show Salmo as a sister group to Oncorhynchus and Salvelinus within Salmoninae, and Thymallinae as a sister group to Salmoninae and Coregoninae within Salmonidae. Extensive gene duplication is consistent with a genome duplication in the common ancestor of salmonids. Using all of the available EST data, a new expanded salmonid cDNA microarray of 32,000 features was created. Cross-species hybridizations to this cDNA microarray indicate that this resource will be useful for studies of all 68 salmonid species. Conclusion An extensive collection and analysis of salmonid RNA putative transcripts indicate that Pacific salmon, Atlantic salmon and charr are 94–96% similar while the more distant whitefish, grayling, pike and smelt are 93, 92, 89 and 86% similar to salmon. The salmonid transcriptome reveals a complex history of gene duplication that is consistent with an ancestral

  20. DNA microarray technology in toxicogenomics of aquatic models: methods and applications.

    PubMed

    Ju, Zhenlin; Wells, Melissa C; Walter, Ronald B

    2007-02-01

    Toxicogenomics represents the merging of toxicology with genomics and bioinformatics to investigate biological functions of genome in response to environmental contaminants. Aquatic species have traditionally been used as models in toxicology to characterize the actions of environmental stresses. Recent completion of the DNA sequencing for several fish species has spurred the development of DNA microarrays allowing investigators access to toxicogenomic approaches. However, since microarray technology is thus far limited to only a few aquatic species and derivation of biological meaning from microarray data is highly dependent on statistical arguments, the full potential of microarray in aquatic species research has yet to be realized. Herein we review some of the issues related to construction, probe design, statistical and bioinformatical data analyses, and current applications of DNA microarrays. As a model a recently developed medaka (Oryzias latipes) oligonucleotide microarray was described to highlight some of the issues related to array technology and its application in aquatic species exposed to hypoxia. Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology. Microarray applications in aquatic toxicogenomics will range from the discovery of diagnostic biomarkers, to establishment of stress-specific signatures and molecular pathways hallmarking the adaptation to new environmental conditions.

  1. Characteristics of induced human pluripotent stem cells using DNA microarray technology.

    PubMed

    Medvedev, S P; Smetanina, M A; Shevchenko, A I; Zakharova, I S; Malakhova, A A; Grigor'eva, E V; Dementyeva, E V; Aleksandrova, M A; Poltavtseva, R A; Veriasov, V N; Filipenko, M L; Sukhikh, G T; Pokushalov, E A; Zakian, S M

    2013-05-01

    We performed transcriptome analysis of some human induced pluripotent stem cells, embryonic stem cells, and human somatic cells using DNA microarrays. PluriTest bioinformatic system was used for evaluation of cell pluripotency. Changes in the genome structure and status of X-chromosome gene expression was analyzed using microarray technology.

  2. The application of phenotypic microarray analysis to anti-fungal drug development.

    PubMed

    Greetham, Darren; Lappin, David F; Rajendran, Ranjith; O'Donnell, Lindsay; Sherry, Leighann; Ramage, Gordon; Nile, Christopher

    2017-03-01

    Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.

  3. Transcriptional analysis of the innate immune response using the avian innate immunity microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The avian innate immunity microarray (AIIM) is a genomics tool designed to study the transcriptional activity of the avian immune response (Cytogenet. Genome Res. 117:139-145, 2007). It is an avian cDNA microarray representing 4,959 avian genes spotted in triplicate. The AIIM contains 25 avian int...

  4. Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

    PubMed

    Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

    2015-01-01

    DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

  5. DNA Microarray Wet Lab Simulation Brings Genomics into the High School Curriculum

    ERIC Educational Resources Information Center

    Campbell, A. Malcolm; Zanta, Carolyn A.; Heyer, Laurie J.; Kittinger, Ben; Gabric, Kathleen M.; Adler, Leslie

    2006-01-01

    We have developed a wet lab DNA microarray simulation as part of a complete DNA microarray module for high school students. The wet lab simulation has been field tested with high school students in Illinois and Maryland as well as in workshops with high school teachers from across the nation. Instead of using DNA, our simulation is based on pH…

  6. Microarray analysis of gene expression in acaricide-exposed Rhipcephalus (Boophilus) microplus larvae.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Acaricide-inducible differential gene expression was studied in larvae of Rhipicephalus (Boophilus) microplus using a microarray-based approach. The acaricides used were: coumaphos, permethrin, ivermectin, and amitraz. The microarrays contained over 13,000 probes, having been derived from a previous...

  7. DEVELOPMENT AND VALIDATION OF A 2,000 GENE MICROARRAY FOR THE FATHEAD MINNOW, PIMEPHALES PROMELAS

    EPA Science Inventory

    The development of the gene microarray has provided the field of ecotoxicology a new tool to identify modes of action (MOA) of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000 gene oligonucleotide microarray for the fathead minnow (P...

  8. Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

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

    PubMed Central

    Pedersen, Henriette L.; Fangel, Jonatan U.; McCleary, Barry; Ruzanski, Christian; Rydahl, Maja G.; Ralet, Marie-Christine; Farkas, Vladimir; von Schantz, Laura; Marcus, Susan E.; Andersen, Mathias C. F.; Field, Rob; Ohlin, Mats; Knox, J. Paul; Clausen, Mads H.; Willats, William G. T.

    2012-01-01

    Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less established, and one reason for this is a lack of suitable glycans with which to populate arrays. Polysaccharide microarrays are relatively easy to produce because of the ease of immobilizing large polymers noncovalently onto a variety of microarray surfaces, but they lack analytical resolution because polysaccharides often contain multiple distinct carbohydrate substructures. Microarrays of defined oligosaccharides potentially overcome this problem but are harder to produce because oligosaccharides usually require coupling prior to immobilization. We have assembled a library of well characterized plant oligosaccharides produced either by partial hydrolysis from polysaccharides or by de novo chemical synthesis. Once coupled to protein, these neoglycoconjugates are versatile reagents that can be printed as microarrays onto a variety of slide types and membranes. We show that these microarrays are suitable for the high throughput characterization of the recognition capabilities of monoclonal antibodies, carbohydrate-binding modules, and other oligosaccharide-binding proteins of biological significance and also that they have potential for the characterization of carbohydrate-active enzymes. PMID:22988248

  10. Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm

    PubMed Central

    Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

    2015-01-01

    DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively. PMID:26284175

  11. Rapid large-scale oligonucleotide selection for microarrays.

    PubMed

    Rahmann, Sven

    2002-01-01

    We present the first algorithm that selects oligonucleotide probes (e.g. 25-mers) for microarray experiments on a large scale. For example, oligos for human genes can be found within 50 hours. This becomes possible by using the longest common substring as a specificity measure for candidate oligos. We present an algorithm based on a suffix array with additional information that is efficient both in terms of memory usage and running time to rank all candidate oligos according to their specificity. We also introduce the concept of master sequences to describe the sequences from which oligos are to be selected. Constraints such as oligo length, melting temperature, and self-complementarity are incorporated in the master sequence at a preprocessing stage and thus kept separate from the main selection problem. As a result, custom oligos can now be designed for any sequenced genome, just as the technology for on-site chip synthesis is becoming increasingly mature.

  12. Chromosomal Microarray Testing in NEC: A Case Report

    PubMed Central

    Burjonrappa, Sathyaprasad C; Schwartzberg, David

    2016-01-01

    Necrotizing enterocolitis (NEC) remains the most common reason for emergent surgery in the neonatal intensive care unit. The common pathophysiology in all NEC involves alteration in gut microflora, abnormal blood supply to the intestine, and uncontrolled cytokine release. We report a full-term neonate who developed NEC. The neonate had surgical resection of approximately 120cms of bowel. After an initial proximal jejunostomy she underwent a successful jejuno-ileal anastomosis with preservation of her ileocolic valve at 6 weeks of age. A little more than one year of age, she is being weaned off her parenteral nutrition (PN) as her bowel adaptation continues. A chromosomal microarray analysis (CMA) resulted in the identification of a 15q13.3 microdeletion. PMID:27433452

  13. 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.

  14. Recyclable hydrophilic-hydrophobic micropatterns on glass for microarray applications.

    PubMed

    Zhang, Hua; Lee, Yong Yeow; Leck, Kwong Joo; Kim, Namyong Y; Ying, Jackie Y

    2007-04-24

    A novel method for fabricating recyclable hydrophilic-hydrophobic micropatterns on glass chips is presented. TiOx patterns (100-2000 microm) were sputtered on glass chips via a through-hole mask. The patterned chips were then vapor-coated with fluoroalkylsilane, for example, (heptadecafluoro-1,1,2,2-tetrahydrodecyl)triethoxysilane (FTES) to form a hydrophobic coating layer. The fluoroalkyl chain of FTES film on TiOx patterns was photocleaved under UV irradiation, exposing the fresh hydrophilic TiOx patterns. The resulting chip could be used multiple times by repeating the coating and photocleaving processes with negligible deterioration of the hydrophobic FTES film coated on glass. If desired, bare glass patterns could also be generated by removing the TiOx patterns with KOH. The patterned glass chips have been successfully used for microarray fabrication.

  15. Non-volatile copolymer compositions for fabricating gel element microarrays

    PubMed Central

    Golova, Julia B.; Chernov, Boris K.; Perov, Alexander N.; Reynolds, Jennifer; Linger, Yvonne L.; Kukhtin, Alexander; Chandler, Darrell P.

    2011-01-01

    By modifying polymer compositions and cross-linking reagents, we have developed a simple yet effective manufacturing strategy for copolymerized three-dimensional gel element arrays. A new gel-forming monomer (2-(hydroxyethyl) methacrylamide; HEMAA) was used that possesses low volatility and improves the stability of copolymerized gel element arrays to on-chip thermal cycling procedures relative to previously used monomers. Probe immobilization efficiency within the new polymer was 55%, equivalent to that obtained with acrylamide (AA) and methacrylamide (MA) monomers. Non-specific binding of single stranded targets was equivalent for all monomers. Increasing cross-linker chain length improved hybridization kinetics and end-point signal intensities relative to N,N-methylenebisacrylamide (Bis). The new copolymer formulation was successfully applied to a model orthopox array. Because HEMAA greatly simplifies gel element array manufacture, we expect it (in combination with new cross-linkers described herein) to find widespread application in microarray science. PMID:22033291

  16. Reverse transfected cell microarrays in infectious disease research.

    PubMed

    Konrad, Andreas; Jochmann, Ramona; Kuhn, Elisabeth; Naschberger, Elisabeth; Chudasama, Priya; Stürzl, Michael

    2011-01-01

    Several human pathogenic viruses encode large genomes with often more than 100 genes. Viral pathogenicity is determined by carefully orchestrated co-operative activities of several different viral genes which trigger the phenotypic functions of the infected cells. Systematic analyses of these complex interactions require high-throughput transfection technology. Here we have provided a laboratory manual for the reverse transfected cell microarray (RTCM; alternative name: cell chip) as a high-throughput transfection procedure, which has been successfully applied for the systematic analyses of single and combination effects of genes encoded by the human herpesvirus-8 on the NF-kappaB signal transduction pathway. In order to quantitatively determine the effects of viral genes in transfected cells, protocols for the use of GFP as an indicator gene and for indirect immunofluorescence staining of cellular target proteins have been included. RTCM provides a useful methodological approach to investigate systematically combination effects of viral genes on cellular functions.

  17. 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. PMID:27600221

  18. From microarrays to networks: mining expression time series.

    PubMed

    Dewey, T Gregory

    2002-10-15

    Over the past few years, powerful new methods have been devised that enable researchers to study the expression dynamics of many genes simultaneously (e.g. gene expression profiles using cDNA microarrays). In principle, this potentially vast quantity of data enables the dissection of the complex genetic networks that control the patterns and rhythms of gene expression in the cell. Finding the patterns in those data represents the next major phase in our understanding of the programming and functioning of the living cell. Simple dynamic models can be used to generate gene expression networks. These networks reveal the phenomenological link between the expression of different genes. This review discuss how these networks are generated and outlines several data-mining techniques for extracting relationships and hypotheses in gene expression. These emerging methods can be applied to a range of biological problems.

  19. 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

  20. Classification and immunohistochemical scoring of breast tissue microarray spots.

    PubMed

    Amaral, Telmo; McKenna, Stephen J; Robertson, Katherine; Thompson, Alastair

    2013-10-01

    Tissue microarrays (TMAs) facilitate the survey of very large numbers of tumors. However, the manual assessment of stained TMA sections constitutes a bottleneck in the pathologist's work flow. This paper presents a computational pipeline for automatically classifying and scoring breast cancer TMA spots that have been subjected to nuclear immunostaining. Spots are classified based on a bag of visual words approach. Immunohistochemical scoring is performed by computing spot features reflecting the proportion of epithelial nuclei that are stained and the strength of that staining. These are then mapped onto an ordinal scale used by pathologists. Multilayer perceptron classifiers are compared with latent topic models and support vector machines for spot classification, and with Gaussian process ordinal regression and linear models for scoring. Intraobserver variation is also reported. The use of posterior entropy to identify uncertain cases is demonstrated. Evaluation is performed using TMA images stained for progesterone receptor.

  1. Using Kepler for Tool Integration in Microarray Analysis Workflows.

    PubMed

    Gan, Zhuohui; Stowe, Jennifer C; Altintas, Ilkay; McCulloch, Andrew D; Zambon, Alexander C

    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.

  2. Genome-wide transcription analyses in rice using tiling microarrays.

    PubMed

    Li, Lei; Wang, Xiangfeng; Stolc, Viktor; Li, Xueyong; Zhang, Dongfen; Su, Ning; Tongprasit, Waraporn; Li, Songgang; Cheng, Zhukuan; Wang, Jun; Deng, Xing Wang

    2006-01-01

    Sequencing and computational annotation revealed several features, including high gene numbers, unusual composition of the predicted genes and a large number of genes lacking homology to known genes, that distinguish the rice (Oryza sativa) genome from that of other fully sequenced model species. We report here a full-genome transcription analysis of the indica rice subspecies using high-density oligonucleotide tiling microarrays. Our results provided expression data support for the existence of 35,970 (81.9%) annotated gene models and identified 5,464 unique transcribed intergenic regions that share similar compositional properties with the annotated exons and have significant homology to other plant proteins. Elucidating and mapping of all transcribed regions revealed an association between global transcription and cytological chromosome features, and an overall similarity of transcriptional activity between duplicated segments of the genome. Collectively, our results provide the first whole-genome transcription map useful for further understanding the rice genome.

  3. 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.

  4. Analysis of Mycobacterium leprae gene expression using DNA microarray.

    PubMed

    Akama, Takeshi; Tanigawa, Kazunari; Kawashima, Akira; Wu, Huhehasi; Ishii, Norihisa; Suzuki, Koichi

    2010-10-01

    Mycobacterium leprae, the causative agent of leprosy, does not grow under in vitro condition, making molecular analysis of this bacterium difficult. For this reason, bacteriological information regarding M. leprae gene function is limited compared with other mycobacterium species. In this study, we performed DNA microarray analysis to clarify the RNA expression profile of the Thai53 strain of M. leprae grown in footpads of hypertensive nude rats (SHR/NCrj-rnu). Of 1605 M. leprae genes, 315 showed signal intensity twofold higher than the median. These genes include Acyl-CoA metabolic enzymes and drug metabolic enzymes, which might be related to the virulence of M. leprae. In addition, consecutive RNA expression profile and in silico analyses enabled identification of possible operons within the M. leprae genome. The present results will shed light on M. leprae gene function and further our understanding of the pathogenesis of leprosy.

  5. A dynamic bead-based microarray for parallel DNA detection

    NASA Astrophysics Data System (ADS)

    Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

    2011-05-01

    A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

  6. Electronic hybridization detection in microarray format and DNA genotyping

    NASA Astrophysics Data System (ADS)

    Blin, Antoine; Cissé, Ismaïl; Bockelmann, Ulrich

    2014-02-01

    We describe an approach to substituting a fluorescence microarray with a surface made of an arrangement of electrolyte-gated field effect transistors. This was achieved using a dedicated blocking of non-specific interactions and comparing threshold voltage shifts of transistors exhibiting probe molecules of different base sequence. We apply the approach to detection of the 35delG mutation, which is related to non-syndromic deafness and is one of the most frequent mutations in humans. The process involves barcode sequences that are generated by Tas-PCR, a newly developed replication reaction using polymerase blocking. The barcodes are recognized by hybridization to surface attached probes and are directly detected by the semiconductor device.

  7. Parallel classification and feature selection in microarray data using SPRINT

    PubMed Central

    Mitchell, Lawrence; Sloan, Terence M.; Mewissen, Muriel; Ghazal, Peter; Forster, Thorsten; Piotrowski, Michal; Trew, Arthur

    2014-01-01

    SUMMARY The statistical language R is favoured by many biostatisticians for processing microarray data. In recent times, the quantity of data that can be obtained in experiments has risen significantly, making previously fast analyses time consuming or even not possible at all with the existing software infrastructure. High performance computing (HPC) systems offer a solution to these problems but at the expense of increased complexity for the end user. The Simple Parallel R Interface is a library for R that aims to reduce the complexity of using HPC systems by providing biostatisticians with drop-in parallelised replacements of existing R functions. In this paper we describe parallel implementations of two popular techniques: exploratory clustering analyses using the random forest classifier and feature selection through identification of differentially expressed genes using the rank product method. PMID:24883047

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

    SciTech Connect

    Gardner, S; Jaing, C

    2012-03-27

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

  9. A Versatile Microarray Immobilization Strategy Based on a Biorthogonal Reaction Between Tetrazine and Trans-Cyclooctene.

    PubMed

    Wang, Ping; Gao, Liqian; Lei, Haipeng; Lee, Su Seong; Yao, Shao Q; Sun, Hongyan

    2017-01-01

    Given its increasing importance in transforming biomedical research in recent years, microarray technology has become highly popular as a powerful screening platform in detecting biomolecule interactions, discovering new inhibitors, and identifying biomarkers as well as diagnosing disease. The success of microarray technology in various biological applications is highly dependent on the accessibility, the functionality, and the density of the surface bound biomolecules. Therefore, compound immobilization represents a critical step for the successful implementation of microarray screening. Herein we describe a fast and site-specific microarray immobilization approach by using trans-cyclooctene-tetrazine ligation. This approach not only ensures fast immobilization and uniform display of biomolecules, but also allows the optimum orientation of biomolecules after immobilization. All these excellent properties facilitate subsequent interactions of the biomolecules and their interacting partners during the screening process. We envision that the immobilization strategy described here can find useful applications in many other microarray related studies.

  10. Automation of cDNA microarray hybridization and washing yields improved data quality.

    PubMed

    Yauk, Carole; Berndt, Lynn; Williams, Andrew; Douglas, George R

    2005-07-29

    Microarray technology allows the analysis of whole-genome transcription within a single hybridization, and has become a standard research tool. It is extremely important to minimize variation in order to obtain high quality microarray data that can be compared among experiments and laboratories. The majority of facilities implement manual hybridization approaches for microarray studies. We developed an automated method for cDNA microarray hybridization that uses equivalent pre-hybridization, hybridization and washing conditions to the suggested manual protocol. The automated method significantly decreased variability across microarray slides compared to manual hybridization. Although normalized signal intensities for buffer-only spots across the chips were identical, significantly reduced variation and inter-quartile ranges were obtained using the automated workstation. This decreased variation led to improved correlation among technical replicates across slides in both the Cy3 and Cy5 channels.

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

    PubMed Central

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

    2017-01-01

    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

  12. CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

    PubMed

    Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

    2014-11-10

    Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de.

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

    SciTech Connect

    Devi, Sachin S.; Mehendale, Harihara M. . E-mail: mehendale@ulm.edu

    2006-04-01

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

  14. Novel and future applications of microarrays in toxicological research.

    PubMed

    Gant, Timothy W

    2007-08-01

    Microarray technologies have both fascinated and frustrated the toxicological community since their introduction around a decade ago. Fascination arose from the possibility offered by the technology to gain a profound insight into the cellular response to chemically mediated stress, and the potential that this genomic signature would be indicative of the biological mechanism by which that stress was induced. Frustrations have arisen primarily from technical factors such as data variance, the requirement for the application of advanced statistical and mathematical analysis, and difficulties associated with actually recognising signature gene expression patterns, and discerning mechanisms. Toxicogenomics was predicted to make toxicological assessment and extrapolation easier, faster and cheaper. The reality has been somewhat different; toxicogenomics is difficult. However, its potential when properly applied has been indicated by some well designed toxicogenomics studies, particularly in the differentiation of genotoxins from non-genotoxins. Technology waits though for no man. While the toxicological community has been working to apply transcriptomics (mRNA levels) in toxicology, the technology has moved beyond this application into new arenas. Some have application to toxicology and are reviewed here, except transcriptomics which has been extensively written about before. This review discusses the application of microarray technologies applied to the genome per se (amplifications, deletions, epigenetic change), mRNA translation and its control mechanisms through miRNA. Which of the new genomics technoï¿(1/2)logies will find most application in toxicology? In the opinion of the author there are three potentially major applications: i) arrayCGH in assessment and recognition of genotoxicity; ii) epigenetic assessment in developmental and transgenerational toxicology; and iii) miRNA assessment in all toxicology types, but particularly developmental toxicology.

  15. Electrosonic ejector microarray for drug and gene delivery.

    PubMed

    Zarnitsyn, Vladimir G; Meacham, J Mark; Varady, Mark J; Hao, Chunhai; Degertekin, F Levent; Fedorov, Andrei G

    2008-04-01

    We report on development and experimental characterization of a novel cell manipulation device-the electrosonic ejector microarray-which establishes a pathway for drug and/or gene delivery with control of biophysical action on the length scale of an individual cell. The device comprises a piezoelectric transducer for ultrasound wave generation, a reservoir for storing the sample mixture and a set of acoustic horn structures that form a nozzle array for focused application of mechanical energy. The nozzles are micromachined in silicon or plastic using simple and economical batch fabrication processes. When the device is driven at a particular resonant frequency of the acoustic horn structures, the sample mixture of cells and desired transfection agents/molecules suspended in culture medium is ejected from orifices located at the nozzle tips. During sample ejection, focused mechanical forces (pressure and shear) are generated on a microsecond time scale (dictated by nozzle size/geometry and ejection velocity) resulting in identical "active" microenvironments for each ejected cell. This process enables a number of cellular bioeffects, from uptake of small molecules and gene delivery/transfection to cell lysis. Specifically, we demonstrate successful calcein uptake and transfection of DNA plasmid encoding green fluorescent protein (GFP) into human malignant glioma cells (cell line LN443) using electrosonic microarrays with 36, 45 and 50 mum diameter nozzle orifices and operating at ultrasound frequencies between 0.91 and 0.98 MHz. Our results suggest that efficacy and the extent of bioeffects are mainly controlled by nozzle orifice size and the localized intensity of the applied acoustic field.

  16. The fecal bifidobacterial transcriptome of adults: a microarray approach.

    PubMed

    Klaassens, Eline S; Ben-Amor, Kaouther; Vriesema, Aldwin; Vaughan, Elaine E; de Vos, Willem

    2011-01-01

    Bifidobacteria are a predominant group present among adult human intestinal microbiota and are considered to be beneficial to host health. Both the dynamics and functional activity of bifidobacteria from the intestinal tract of four adults, following ingestion of a mix consisting of short chain galactooligosaccharides, long chain fructooligosaccharides and acidic oligosaccharides from pectin hydrolysate (GFP), was investigated. The percentage of total bifidobacteria, monitored by quantitative real time PCR, was not significantly altered but marked species-specific changes occurred in all individuals over time, indicating a dynamic bifidobacterial community. Insight into the functional activity of the bifidobacteria was acquired using a clone library-based microarray comprising the genomes of various bifidobacteria to reveal the bifidobacterial transcriptome within the fecal community. Total RNA from the fecal microbial community was hybridized to the microarray and 310 clones were selected for sequencing which revealed genes belonging to a wide range of functional groups demonstrating substantial metabolic activity. While the intake of GFP did not have a significant effect on the overall change in gene expression, 82 genes showed a significant change. Most of the predicted genes were involved in metabolism of carbohydrates of plant origin, house keeping functions such as DNA replication and transcription, followed by membrane transport of a wide variety of substrates including sugars and metals and amino acid metabolism. Other genes were involved in transport, nucleotide metabolism, amino acid metabolism, environmental information processing and cellular processes and signalling. A smaller number of genes were involved in general metabolism, glycan metabolism, energy metabolism, lipid metabolism and cell surface. These results support the notion that bifidobacteria utilize mainly indigestible polysaccharides as their main source of energy and biosynthesis of

  17. Microarray analysis of circular RNA expression patterns in polarized macrophages

    PubMed Central

    Zhang, Yingying; Zhang, Yao; Li, Xueqin; Zhang, Mengying; Lv, Kun

    2017-01-01

    Circular RNAs (circRNAs) are generated from diverse genomic locations and are a new player in the regulation of post-transcriptional gene expression. Recent studies have revealed that circRNAs play a crucial role in fine-tuning the level of microRNA (miRNA)-mediated regulation of gene expression by sequestering miRNAs. The interaction of circRNAs with disease-associated miRNAs suggests that circRNAs are important in the pathology of disease. However, the effects and roles of circRNAs in macrophage polarization have yet to be explored. In the present study, we performed a circRNA microarray to compare the circRNA expression profiles of bone marrow-derived macrophages (BMDMs) under two distinct polarizing conditions (M1 macrophages induced by interferon-γ and LPS stimulation, and M2 macrophages induced by interleukin-4 stimulation). Our results showed that a total of 189 circRNAs were differentially expressed between M1 and M2 macrophages. Differentially expressed circRNAs with a high fold-change were selected for validation by RT-qPCR: circRNA-003780, circRNA-010056, and circRNA-010231 were upregulated and circRNA-003424, circRNA-013630, circRNA-001489 and circRNA-018127 were downregulated (fold-change >4, P<0.05) in M1 compared to M2, which was found to correlate with the microarray data. Furthermore, the most differentially expressed circRNAs within all the comparisons were annotated in detail with circRNA/miRNA interaction information using miRNA target prediction software. In conclusion, the present study provides novel insight into the role of circRNAs in macrophage differentiation and polarization. PMID:28075448

  18. Simplified microarray system for simultaneously detecting rifampin, isoniazid, ethambutol, and streptomycin resistance markers in Mycobacterium tuberculosis.

    PubMed

    Linger, Yvonne; Kukhtin, Alexander; Golova, Julia; Perov, Alexander; Lambarqui, Amine; Bryant, Lexi; Rudy, George B; Dionne, Kim; Fisher, Stefanie L; Parrish, Nicole; Chandler, Darrell P

    2014-06-01

    We developed a simplified microarray test for detecting and identifying mutations in rpoB, katG, inhA, embB, and rpsL and compared the analytical performance of the test to that of phenotypic drug susceptibility testing (DST). The analytical sensitivity was estimated to be at least 110 genome copies per amplification reaction. The microarray test correctly detected 95.2% of mutations for which there was a sequence-specific probe on the microarray and 100% of 96 wild-type sequences. In a blinded analysis of 153 clinical isolates, microarray sensitivity for first-line drugs relative to phenotypic DST (true resistance) was 100% for rifampin (RIF) (14/14), 90.0% for isoniazid (INH) (36/40), 70% for ethambutol (EMB) (7/10), and 89.1% (57/64) combined. Microarray specificity (true susceptibility) for first-line agents was 95.0% for RIF (132/139), 98.2% for INH (111/113), and 98.6% for EMB (141/143). Overall microarray specificity for RIF, INH, and EMB combined was 97.2% (384/395). The overall positive and negative predictive values for RIF, INH, and EMB combined were 84.9% and 98.3%, respectively. For the second-line drug streptomycin (STR), overall concordance between the agar proportion method and microarray analysis was 89.5% (137/153). Sensitivity was 34.8% (8/23) because of limited microarray coverage for STR-conferring mutations, and specificity was 99.2% (129/130). All false-susceptible discrepant results were a consequence of DNA mutations that are not represented by a specific microarray probe. There were zero invalid results from 220 total tests. The simplified microarray system is suitable for detecting resistance-conferring mutations in clinical M. tuberculosis isolates and can now be used for prospective trials or integrated into an all-in-one, closed-amplicon consumable.

  19. A genome-wide 20 K citrus microarray for gene expression analysis

    PubMed Central

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to

  20. 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

  1. 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...

  2. The Clinical Utility of a Single-Nucleotide Polymorphism Microarray in Patients With Epilepsy at a Tertiary Medical Center.

    PubMed

    Hrabik, Sarah A; Standridge, Shannon M; Greiner, Hansel M; Neilson, Derek E; Pilipenko, Valentina V; Zimmerman, Sarah L; Connor, Jessica A; Spaeth, Christine G

    2015-11-01

    Microarray testing has revolutionized clinical cytogenetics, as it provides a significantly higher resolution and greater clinical yield than karyotype analysis. This study assessed the clinical utility of single-nucleotide polymorphism microarray in patients with epilepsy. Study subjects were patients between the ages of birth to 23 years who were diagnosed with epilepsy and had a microarray performed at Cincinnati Children's Hospital Medical Center. Statistical analysis explored the association of microarray results and brain magnetic resonance imaging (MRI), seizure type, and structural malformations. Approximately 17.7% (26/147) of participants had an abnormal microarray as defined by laboratory guidelines. There were no differences in frequency of abnormal brain MRI or seizure type between the abnormal and normal microarray groups. There was a higher prevalence of musculoskeletal malformations (P < .0035) and cardiovascular malformations (P < .0081) in subjects with abnormal microarrays. Clinicians should consider microarray analysis in individuals who have epilepsy, especially in combination with musculoskeletal malformation or cardiovascular malformation.

  3. 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, ...

  4. 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...

  5. The microarray explorer tool for data mining of cDNA microarrays: application for the mammary gland.

    PubMed

    Lemkin, P F; Thornwall, G C; Walton, K D; Hennighausen, L

    2000-11-15

    The Microarray Explorer (MAExplorer) is a versatile Java-based data mining bioinformatic tool for analyzing quantitative cDNA expression profiles across multiple microarray platforms and DNA labeling systems. It may be run as either a stand-alone application or as a Web browser applet over the Internet. With this program it is possible to (i) analyze the expression of individual genes, (ii) analyze the expression of gene families and clusters, (iii) compare expression patterns and (iv) directly access other genomic databases for clones of interest. Data may be downloaded as required from a Web server or in the case of the stand-alone version, reside on the user's computer. Analyses are performed in real-time and may be viewed and directly manipulated in images, reports, scatter plots, histograms, expression profile plots and cluster analyses plots. A key feature is the clone data filter for constraining a working set of clones to those passing a variety of user-specified logical and statistical tests. Reports may be generated with hypertext Web access to UniGene, GenBank and other Internet databases for sets of clones found to be of interest. Users may save their explorations on the Web server or local computer and later recall or share them with other scientists in this groupware Web environment. The emphasis on direct manipulation of clones and sets of clones in graphics and tables provides a high level of interaction with the data, making it easier for investigators to test ideas when looking for patterns. We have used the MAExplorer to profile gene expression patterns of 1500 duplicated genes isolated from mouse mammary tissue. We have identified genes that are preferentially expressed during pregnancy and during lactation. One gene we identified, carbonic anhydrase III, is highly expressed in mammary tissue from virgin and pregnant mice and in gene knock-out mice with underdeveloped mammary epithelium. Other genes, which include those encoding milk proteins

  6. A Web-Based Multi-Database System Supporting Distributed Collaborative Management and Sharing of Microarray Experiment Information

    PubMed Central

    Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

    2006-01-01

    We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments. PMID:17238488

  7. A Web-based multi-database system supporting distributed collaborative management and sharing of microarray experiment information.

    PubMed

    Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

    2006-01-01

    We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments.

  8. Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France

    PubMed Central

    Kegel, Jessica U.; Del Amo, Yolanda; Costes, Laurence; Medlin, Linda K.

    2013-01-01

    Harmful algal blooms (HABs) occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae)—an FP7-funded EU project—used rRNA genes (SSU and LSU) as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR) and compared with an enzyme-linked immunosorbent assay (ELISA). In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3) and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts. PMID:27605178

  9. Reusable conductimetric array of interdigitated microelectrodes for the readout of low-density microarrays.

    PubMed

    Mallén, Maria; Díaz-González, María; Bonilla, Diana; Salvador, Juan P; Marco, María P; Baldi, Antoni; Fernández-Sánchez, César

    2014-06-17

    Low-density protein microarrays are emerging tools in diagnostics whose deployment could be primarily limited by the cost of fluorescence detection schemes. This paper describes an electrical readout system of microarrays comprising an array of gold interdigitated microelectrodes and an array of polydimethylsiloxane microwells, which enabled multiplexed detection of up to thirty six biological events on the same substrate. Similarly to fluorescent readout counterparts, the microarray can be developed on disposable glass slide substrates. However, unlike them, the presented approach is compact and requires a simple and inexpensive instrumentation. The system makes use of urease labeled affinity reagents for developing the microarrays and is based on detection of conductivity changes taking place when ionic species are generated in solution due to the catalytic hydrolysis of urea. The use of a polydimethylsiloxane microwell array facilitates the positioning of the measurement solution on every spot of the microarray. Also, it ensures the liquid tightness and isolation from the surrounding ones during the microarray readout process, thereby avoiding evaporation and chemical cross-talk effects that were shown to affect the sensitivity and reliability of the system. The performance of the system is demonstrated by carrying out the readout of a microarray for boldenone anabolic androgenic steroid hormone. Analytical results are comparable to those obtained by fluorescent scanner detection approaches. The estimated detection limit is 4.0 ng mL(-1), this being below the threshold value set by the World Anti-Doping Agency and the European Community.

  10. 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.

  11. 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

  12. Testing a Microarray to Detect and Monitor Toxic Microalgae in Arcachon Bay in France.

    PubMed

    Kegel, Jessica U; Del Amo, Yolanda; Costes, Laurence; Medlin, Linda K

    2013-03-05

    Harmful algal blooms (HABs) occur worldwide, causing health problems and economic damages to fisheries and tourism. Monitoring agencies are therefore essential, yet monitoring is based only on time-consuming light microscopy, a level at which a correct identification can be limited by insufficient morphological characters. The project MIDTAL (Microarray Detection of Toxic Algae)-an FP7-funded EU project-used rRNA genes (SSU and LSU) as a target on microarrays to identify toxic species. Furthermore, toxins were detected with a newly developed multiplex optical Surface Plasmon Resonance biosensor (Multi SPR) and compared with an enzyme-linked immunosorbent assay (ELISA). In this study, we demonstrate the latest generation of MIDTAL microarrays (version 3) and show the correlation between cell counts, detected toxin and microarray signals from field samples taken in Arcachon Bay in France in 2011. The MIDTAL microarray always detected more potentially toxic species than those detected by microscopic counts. The toxin detection was even more sensitive than both methods. Because of the universal nature of both toxin and species microarrays, they can be used to detect invasive species. Nevertheless, the MIDTAL microarray is not completely universal: first, because not all toxic species are on the chip, and second, because invasive species, such as Ostreopsis, already influence European coasts.

  13. Semiconductor quantum dots for multiplexed bio-detection on solid-state microarrays.

    PubMed

    Rousserie, Gilles; Sukhanova, Alyona; Even-Desrumeaux, Klervi; Fleury, Fabrice; Chames, Patrick; Baty, Daniel; Oleinikov, Vladimir; Pluot, Michel; Cohen, Jacques H M; Nabiev, Igor

    2010-04-01

    Understanding cellular systems requires identification and analysis of their multiple components and determination of how they act together and are regulated. Microarray technology is one of the few tools that is able to solve such problems. It is based on high-throughput recognition of a target to the probe and has the potential to simultaneously measure the presence of numerous molecules in multiplexed tests, all contained in a small drop of test fluid. Microarrays allow the parallel analysis of genomic or proteomic content in healthy versus disease-affected or altered tissues or cells. The signal read-out from the microarrays is done with organic dyes which often suffer of photobleaching, low brightness and background fluorescence. Recent data show that the use of fluorescent nanocrystals named "quantum dots" (QDs) allows to push these limits away. QDs are sufficiently bright to be detected as individual particles, extremely resistant against photobleaching and provide unique possibilities for multiplexing, thus supplying the microarray technology with a novel read-out option enabling the sensitivity of detection to reach the single-molecule level. This paper reviews QDs applications to microarray-based detection and demonstrates how the combination of microarray and QDs technologies may increase sensitivity and highly parallel capacities of multiplexed microarrays. Such a combination should provide the breakthrough results in drug discovery, cancer diagnosis and establish new therapeutic approaches through the identification of binding target molecules and better understanding of cell signalling pathways.

  14. A Guided Materials Screening Approach for Developing Quantitative Sol-gel Derived Protein Microarrays

    PubMed Central

    Helka, Blake-Joseph; Brennan, John D.

    2013-01-01

    Microarrays have found use in the development of high-throughput assays for new materials and discovery of small-molecule drug leads. Herein we describe a guided material screening approach to identify sol-gel based materials that are suitable for producing three-dimensional protein microarrays. The approach first identifies materials that can be printed as microarrays, narrows down the number of materials by identifying those that are compatible with a given enzyme assay, and then hones in on optimal materials based on retention of maximum enzyme activity. This approach is applied to develop microarrays suitable for two different enzyme assays, one using acetylcholinesterase and the other using a set of four key kinases involved in cancer. In each case, it was possible to produce microarrays that could be used for quantitative small-molecule screening assays and production of dose-dependent inhibitor response curves. Importantly, the ability to screen many materials produced information on the types of materials that best suited both microarray production and retention of enzyme activity. The materials data provide insight into basic material requirements necessary for tailoring optimal, high-density sol-gel derived microarrays. PMID:24022739

  15. 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.

  16. 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

  17. Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

    PubMed

    Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

    2013-01-01

    Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially

  18. Striptease on glass: validation of an improved stripping procedure for in situ microarrays.

    PubMed

    Hahnke, Karin; Jacobsen, Marc; Gruetzkau, Andreas; Gruen, Joachim R; Koch, Markus; Emoto, Masashi; Meyer, Thomas F; Walduck, Anna; Kaufmann, Stefan H E; Mollenkopf, Hans-Joachim

    2007-01-30

    Microarrays have rapidly become an indispensable tool for gene analysis. Microarray experiments can be cost prohibitive, however, largely due to the price of the arrays themselves. Whilst different methods for stripping filter arrays on membranes have been established, only very few protocols are published for thermal and chemical stripping of microarrays on glass. Most of these protocols for stripping microarrays on glass were developed in combination with specific surface chemistry and different coatings for covalently immobilizing presynthesized DNA in a deposition process. We have developed a method for stripping commercial in situ microarrays using a multi-step procedure. We present a method that uses mild chemical degradation complemented by enzymatic treatment. We took advantage of the differences in biochemical properties of covalently linked DNA oligonucleotides on in situ synthesized microarrays and the antisense cRNA hybridization probes. The success of stripping protocols for microarrays on glass was critically dependent on the type of arrays, the nature of sample used for hybridization, as well as hybridization and washing conditions. The protocol employs alkali hydrolysis of the cRNA, several enzymatic degradation steps using RNAses and Proteinase K, combined with appropriate washing steps. Stripped arrays were rehybridized using the same protocols as for new microarrays. The stripping method was validated with microarrays from different suppliers and rehybridization of stripped in situ arrays yielded comparable results to hybridizations done on unused, new arrays with no significant loss in precision or accuracy. We show that stripping of commercial in situ arrays is feasible and that reuse of stripped arrays gave similar results compared to unused ones. This was true even for biological samples that show only slight differences in their expression profiles. Our analyses indicate that the stripping procedure does not significantly influence data

  19. On the Statics for Micro-Array Data Analysis

    NASA Astrophysics Data System (ADS)

    Urushibara, Tomoko; Akasaka, Shizu; Ito, Makiko; Suzuki, Tomonori; Miyazaki, Satoru

    2010-01-01

    data, we might get a different result because the distinct definition for micro array data has not been set yet. It means that from the same data we will get different results depending on researchers. We are afraid that this problem will have a big effect on developing new medicines and to progress the next step, like a 2nd screening. So, we suggest that we should have certain guidelines to analyze Micro-Array data validly with statistic method and it will surely be helpful for Micro-Array analysis for medical studies in the future.

  20. Microarray Technology for Major Chemical Contaminants Analysis in Food: Current Status and Prospects

    PubMed Central

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

    2012-01-01

    Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed. PMID:23012541

  1. From single gene to integrative molecular concept MAPS: pitfalls and potentials of microarray technology.

    PubMed

    Chiorino, G; Mello Grand, M; Scatolini, M; Ostano, P

    2008-01-01

    Microarray experiments have a large variety of applications and several important achievements have been obtained by means of this technology, especially within the field of whole genome expression profiling, which undoubtedly is the most diffused world-wide. Nevertheless, care must be taken in unconditionally applying such high-throughput techniques and in extracting/interpreting their results. Both the validity and the reproducibility of microarray-based clinical research have recently been challenged. Pitfalls and potentials of the microarray technology for gene expression profiling are critically reviewed in this paper.

  2. 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.

  3. The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

    PubMed Central

    Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

    2003-01-01

    Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

  4. Phenotype microarray profiling of Zymomonas mobilis ZM4.

    PubMed

    Bochner, Barry; Gomez, Vanessa; Ziman, Michael; Yang, Shihui; Brown, Steven D

    2010-05-01

    In this study, we developed a Phenotype MicroArray (PM) protocol to profile cellular phenotypes in Zymomonas mobilis, which included a standard set of nearly 2,000 assays for carbon, nitrogen, phosphorus and sulfur source utilization, nutrient stimulation, pH and osmotic stresses, and chemical sensitivities with 240 inhibitory chemicals. We observed two positive assays for C-source utilization (fructose and glucose) using the PM screen, which uses redox chemistry and cell respiration as a universal reporter to profile growth phenotypes in a high-throughput 96-well plate-based format. For nitrogen metabolism, the bacterium showed a positive test results for ammonia, aspartate, asparagine, glutamate, glutamine, and peptides. Z. mobilis appeared to use a diverse array of P-sources with two exceptions being pyrophosphate and tripolyphosphate. The assays suggested that Z. mobilis uses both inorganic and organic compounds as S-sources. No stimulation by nutrients was detected; however, there was evidence of partial inhibition by purines and pyrimidines, NAD, and deferoxamine. Z. mobilis was relatively resistant to acid pH, tolerating a pH down to about 4.0. It also tolerated phosphate, sulfate, and nitrate, but was rather sensitive to chloride and nitrite. Z. mobilis showed resistance to a large number of diverse chemicals that inhibit most bacteria. The information from PM analysis provides an overview of Z. mobilis physiology and a foundation for future comparisons of other wild-type and mutant Z. mobilis strains.

  5. New insights about host response to smallpox using microarray data

    PubMed Central

    Esteves, Gustavo H; Simoes, Ana CQ; Souza, Estevao; Dias, Rodrigo A; Ospina, Raydonal; Venancio, Thiago M

    2007-01-01

    Background Smallpox is a lethal disease that was endemic in many parts of the world until eradicated by massive immunization. Due to its lethality, there are serious concerns about its use as a bioweapon. Here we analyze publicly available microarray data to further understand survival of smallpox infected macaques, using systems biology approaches. Our goal is to improve the knowledge about the progression of this disease. Results We used KEGG pathways annotations to define groups of genes (or modules), and subsequently compared them to macaque survival times. This technique provided additional insights about the host response to this disease, such as increased expression of the cytokines and ECM receptors in the individuals with higher survival times. These results could indicate that these gene groups could influence an effective response from the host to smallpox. Conclusion Macaques with higher survival times clearly express some specific pathways previously unidentified using regular gene-by-gene approaches. Our work also shows how third party analysis of public datasets can be important to support new hypotheses to relevant biological problems. PMID:17718913

  6. Linear model for fast background subtraction in oligonucleotide microarrays

    PubMed Central

    2009-01-01

    Background One important preprocessing step in the analysis of microarray data is background subtraction. In high-density oligonucleotide arrays this is recognized as a crucial step for the global performance of the data analysis from raw intensities to expression values. Results We propose here an algorithm for background estimation based on a model in which the cost function is quadratic in a set of fitting parameters such that minimization can be performed through linear algebra. The model incorporates two effects: 1) Correlated intensities between neighboring features in the chip and 2) sequence-dependent affinities for non-specific hybridization fitted by an extended nearest-neighbor model. Conclusion The algorithm has been tested on 360 GeneChips from publicly available data of recent expression experiments. The algorithm is fast and accurate. Strong correlations between the fitted values for different experiments as well as between the free-energy parameters and their counterparts in aqueous solution indicate that the model captures a significant part of the underlying physical chemistry. PMID:19917117

  7. 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.

  8. Discovering Pair-wise Synergies in Microarray Data

    PubMed Central

    Chen, Yuan; Cao, Dan; Gao, Jun; Yuan, Zheming

    2016-01-01

    Informative gene selection can have important implications for the improvement of cancer diagnosis and the identification of new drug targets. Individual-gene-ranking methods ignore interactions between genes. Furthermore, popular pair-wise gene evaluation methods, e.g. TSP and TSG, are helpless for discovering pair-wise interactions. Several efforts to discover pair-wise synergy have been made based on the information approach, such as EMBP and FeatKNN. However, the methods which are employed to estimate mutual information, e.g. binarization, histogram-based and KNN estimators, depend on known data or domain characteristics. Recently, Reshef et al. proposed a novel maximal information coefficient (MIC) measure to capture a wide range of associations between two variables that has the property of generality. An extension from MIC(X; Y) to MIC(X1; X2; Y) is therefore desired. We developed an approximation algorithm for estimating MIC(X1; X2; Y) where Y is a discrete variable. MIC(X1; X2; Y) is employed to detect pair-wise synergy in simulation and cancer microarray data. The results indicate that MIC(X1; X2; Y) also has the property of generality. It can discover synergic genes that are undetectable by reference feature selection methods such as MIC(X; Y) and TSG. Synergic genes can distinguish different phenotypes. Finally, the biological relevance of these synergic genes is validated with GO annotation and OUgene database. PMID:27470995

  9. Image quantification of high-throughput tissue microarray

    NASA Astrophysics Data System (ADS)

    Wu, Jiahua; Dong, Junyu; Zhou, Huiyu

    2006-03-01

    Tissue microarray (TMA) technology allows rapid visualization of molecular targets in thousands of tissue specimens at a time and provides valuable information on expression of proteins within tissues at a cellular and sub-cellular level. TMA technology overcomes the bottleneck of traditional tissue analysis and allows it to catch up with the rapid advances in lead discovery. Studies using TMA on immunohistochemistry (IHC) can produce a large amount of images for interpretation within a very short time. Manual interpretation does not allow accurate quantitative analysis of staining to be undertaken. Automatic image capture and analysis has been shown to be superior to manual interpretation. The aims of this work is to develop a truly high-throughput and fully automated image capture and analysis system. We develop a robust colour segmentation algorithm using hue-saturation-intensity (HSI) colour space to provide quantification of signal intensity and partitioning of staining on high-throughput TMA. Initial segmentation results and quantification data have been achieved on 16,000 TMA colour images over 23 different tissue types.

  10. Improved covariance matrix estimators for weighted analysis of microarray data.

    PubMed

    Astrand, Magnus; Mostad, Petter; Rudemo, Mats

    2007-12-01

    Empirical Bayes models have been shown to be powerful tools for identifying differentially expressed genes from gene expression microarray data. An example is the WAME model, where a global covariance matrix accounts for array-to-array correlations as well as differing variances between arrays. However, the existing method for estimating the covariance matrix is very computationally intensive and the estimator is biased when data contains many regulated genes. In this paper, two new methods for estimating the covariance matrix are proposed. The first method is a direct application of the EM algorithm for fitting the multivariate t-distribution of the WAME model. In the second method, a prior distribution for the log fold-change is added to the WAME model, and a discrete approximation is used for this prior. Both methods are evaluated using simulated and real data. The first method shows equal performance compared to the existing method in terms of bias and variability, but is superior in terms of computer time. For large data sets (>15 arrays), the second method also shows superior computer run time. Moreover, for simulated data with regulated genes the second method greatly reduces the bias. With the proposed methods it is possible to apply the WAME model to large data sets with reasonable computer run times. The second method shows a small bias for simulated data, but appears to have a larger bias for real data with many regulated genes.

  11. Screening and characterization of plant cell walls using carbohydrate microarrays.

    PubMed

    Sørensen, Iben; Willats, William G T

    2011-01-01

    Plant cells are surrounded by cell walls built largely from complex carbohydrates. The primary walls of growing plant cells consist of interdependent networks of three polysaccharide classes: cellulose, cross-linking glycans (also known as hemicelluloses), and pectins. Cellulose microfibrils are tethered together by cross-linking glycans, and this assembly forms the major load-bearing component of primary walls, which is infiltrated with pectic polymers. In the secondary walls of woody tissues, pectins are much reduced and walls are reinforced with the phenolic polymer lignin. Plant cell walls are essential for plant life and also have numerous industrial applications, ranging from wood to nutraceuticals. Enhancing our knowledge of cell wall biology and the effective use of cell wall materials is dependent to a large extent on being able to analyse their fine structures. We have developed a suite of techniques based on microarrays probed with monoclonal antibodies with specificity for cell wall components, and here we present practical protocols for this type of analysis.

  12. Microarray Analysis of the Microflora of Root Caries in Elderly

    PubMed Central

    Preza, Dorita; Olsen, Ingar; Willumsen, Tiril; Boches, Susan K.; Cotton, Sean L.; Grinde, Bjørn; Paster, Bruce J.

    2009-01-01

    Purpose The present study used a new 16S rRNA-based microarray with probes for over 300 bacterial species better define the bacterial profiles of healthy root surfaces and root caries (RC) in the elderly. Materials Supragingival plaque was collected from 20 healthy subjects (Controls) and from healthy and carious roots and carious dentin from 21 RC subjects (Patients). Results Collectively, 179 bacterial species and species groups were detected. A higher bacterial diversity was observed in the Controls as compared to Patients. Lactobacillus casei/paracasei/rhamnosus and Pseudoramibacter alactolyticus were notably associated with most root caries samples. Streptococcus mutans was detected more frequently in the infected dentin than in the other samples, but the difference was not significant. Actinomyces were found more frequently in Controls. Conclusion Actinomyces and S. mutans may play a limited role as pathogens of RC. The results from this study were in agreement with those of our previous study based on 16S rRNA gene sequencing with 72% of the species being detected with both methods. PMID:19039610

  13. TMAinspiration: Decode Interdependencies in Multifactorial Tissue Microarray Data

    PubMed Central

    Boecker, Florian; Buerger, Horst; Mallela, Nikhil V.; Korsching, Eberhard

    2016-01-01

    There are no satisfying tools in tissue microarray (TMA) data analysis up to now to analyze the cooperative behavior of all measured markers in a multifactorial TMA approach. The developed tool TMAinspiration is not only offering an analysis option to close this gap but also offering an ecosystem consisting of quality control concepts and supporting scripts to make this approach a platform for informed practice and further research. The TMAinspiration method is specifically focusing on the demands of the TMA analysis by controlling errors and noise by a generalized regression scheme while at the same time avoiding to introduce a priori too many constraints into the analysis of the data. So, we are testing partitions of a proximity table to find an optimal support for a ranking scheme of molecular dependencies. The idea of combining several partitions to one ensemble, which is balancing the optimization process, is based on the main assumption that all these perspectives on the cellular network need to be self-consistent. Several application examples in breast cancer and one in squamous cell carcinoma demonstrate that this procedure is nicely confirming a priori knowledge on the expression characteristics of protein markers, while also integrating many new results discovered in the treasury of a bigger TMA experiment. The code and software are now freely available at: http://complex-systems.uni-muenster.de/tma_inspiration.html. PMID:27398021

  14. Protein microarray characterization of the S-nitrosoproteome.

    PubMed

    Lee, Yun-Il; Giovinazzo, Daniel; Kang, Ho Chul; Lee, Yunjong; Jeong, Jun Seop; Doulias, Paschalis-Thomas; Xie, Zhi; Hu, Jianfei; Ghasemi, Mehdi; Ischiropoulos, Harry; Qian, Jiang; Zhu, Heng; Blackshaw, Seth; Dawson, Valina L; Dawson, Ted M

    2014-01-01

    Nitric oxide (NO) mediates a substantial part of its physiologic functions via S-nitrosylation, however the cellular substrates for NO-mediated S-nitrosylation are largely unknown. Here we describe the S-nitrosoproteome using a high-density protein microarray chip containing 16,368 unique human proteins. We identified 834 potentially S-nitrosylated human proteins. Using a unique and highly specific labeling and affinity capture of S-nitrosylated proteins, 138 cysteine residues on 131 peptides in 95 proteins were determined, defining critical sites of NO's actions. Of these cysteine residues 113 are novel sites of S-nitrosylation. A consensus sequence motif from these 834 proteins for S-nitrosylation was identified, suggesting that the residues flanking the S-nitrosylated cysteine are likely to be the critical determinant of whether the cysteine is S-nitrosylated. We identify eight ubiquitin E3 ligases, RNF10, RNF11, RNF41, RNF141, RNF181, RNF208, WWP2, and UBE3A, whose activities are modulated by S-nitrosylation, providing a unique regulatory mechanism of the ubiquitin proteasome system. These results define a new and extensive set of proteins that are susceptible to NO regulation via S-nitrosylation. Similar approaches could be used to identify other post-translational modification proteomes.

  15. Linear RNA amplification for the production of microarray hybridization probes.

    PubMed

    Klebes, Ansgar; Kornberg, Thomas B

    2008-01-01

    To understand Drosophila development and other genetically controlled processes, it is often desirable to identify differences in gene expression levels. An experimental approach to investigate these processes is to catalog the transcriptome by hybridization of mRNA to DNA microbar-rays. In these experiments mRNA-derived hybridization probes are produced and hybridized to an array of DNA spots on a solid support. The labeled cDNAs of the complex hybridization probe will bind to their complementary sequences and provide quantification of the relative concentration of the corresponding transcript in the starting material. However, such approaches are often limited by the scarcity of the experimental sample because standard methods of probe preparation require microgram quantities of mRNA template. Linear RNA amplification can alleviate such limitations to support the generation of microarray hybridization probes from a few 100 pg of mRNA. These smaller quantities can be isolated from a few 100 cells. Here, we present a linear amplification protocol designed to preserve both the relative abundance of transcripts as well as their sequence complexity.

  16. Protein Microarray Characterization of the S-Nitrosoproteome*

    PubMed Central

    Lee, Yun-Il; Giovinazzo, Daniel; Kang, Ho Chul; Lee, Yunjong; Jeong, Jun Seop; Doulias, Paschalis-Thomas; Xie, Zhi; Hu, Jianfei; Ghasemi, Mehdi; Ischiropoulos, Harry; Qian, Jiang; Zhu, Heng; Blackshaw, Seth; Dawson, Valina L.; Dawson, Ted M.

    2014-01-01

    Nitric oxide (NO) mediates a substantial part of its physiologic functions via S-nitrosylation, however the cellular substrates for NO-mediated S-nitrosylation are largely unknown. Here we describe the S-nitrosoproteome using a high-density protein microarray chip containing 16,368 unique human proteins. We identified 834 potentially S-nitrosylated human proteins. Using a unique and highly specific labeling and affinity capture of S-nitrosylated proteins, 138 cysteine residues on 131 peptides in 95 proteins were determined, defining critical sites of NO's actions. Of these cysteine residues 113 are novel sites of S-nitrosylation. A consensus sequence motif from these 834 proteins for S-nitrosylation was identified, suggesting that the residues flanking the S-nitrosylated cysteine are likely to be the critical determinant of whether the cysteine is S-nitrosylated. We identify eight ubiquitin E3 ligases, RNF10, RNF11, RNF41, RNF141, RNF181, RNF208, WWP2, and UBE3A, whose activities are modulated by S-nitrosylation, providing a unique regulatory mechanism of the ubiquitin proteasome system. These results define a new and extensive set of proteins that are susceptible to NO regulation via S-nitrosylation. Similar approaches could be used to identify other post-translational modification proteomes. PMID:24105792

  17. Unscaled Bayes factors for multiple hypothesis testing in microarray experiments.

    PubMed

    Bertolino, Francesco; Cabras, Stefano; Castellanos, Maria Eugenia; Racugno, Walter

    2015-12-01

    Multiple hypothesis testing collects a series of techniques usually based on p-values as a summary of the available evidence from many statistical tests. In hypothesis testing, under a Bayesian perspective, the evidence for a specified hypothesis against an alternative, conditionally on data, is given by the Bayes factor. In this study, we approach multiple hypothesis testing based on both Bayes factors and p-values, regarding multiple hypothesis testing as a multiple model selection problem. To obtain the Bayes factors we assume default priors that are typically improper. In this case, the Bayes factor is usually undetermined due to the ratio of prior pseudo-constants. We show that ignoring prior pseudo-constants leads to unscaled Bayes factor which do not invalidate the inferential procedure in multiple hypothesis testing, because they are used within a comparative scheme. In fact, using partial information from the p-values, we are able to approximate the sampling null distribution of the unscaled Bayes factor and use it within Efron's multiple testing procedure. The simulation study suggests that under normal sampling model and even with small sample sizes, our approach provides false positive and false negative proportions that are less than other common multiple hypothesis testing approaches based only on p-values. The proposed procedure is illustrated in two simulation studies, and the advantages of its use are showed in the analysis of two microarray experiments.

  18. 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.

  19. A protein microarray-based analysis of S-nitrosylation

    PubMed Central

    Foster, Matthew W.; Forrester, Michael T.; Stamler, Jonathan S.

    2009-01-01

    The ubiquitous cellular influence of nitric oxide (NO) is exerted substantially through protein S-nitrosylation. Whereas NO is highly promiscuous, physiological S-nitrosylation is typically restricted to one or very few Cys residue(s) in target proteins. The molecular basis for this specificity may derive from properties of the target protein, the S-nitrosylating species, or both. Here, we describe a protein microarray-based approach to investigate determinants of S-nitrosylation by biologically relevant low-mass S-nitrosothiols (SNOs). We identify large sets of yeast and human target proteins, among which those with active-site Cys thiols residing at N termini of α-helices or within catalytic loops were particularly prominent. However, S-nitrosylation varied substantially even within these families of proteins (e.g., papain-related Cys-dependent hydrolases and rhodanese/Cdc25 phosphatases), suggesting that neither secondary structure nor intrinsic nucleophilicity of Cys thiols was sufficient to explain specificity. Further analyses revealed a substantial influence of NO-donor stereochemistry and structure on efficiency of S-nitrosylation as well as an unanticipated and important role for allosteric effectors. Thus, high-throughput screening and unbiased proteome coverage reveal multifactorial determinants of S-nitrosylation (which may be overlooked in alternative proteomic analyses), and support the idea that target specificity can be achieved through rational design of S-nitrosothiols. PMID:19864628

  20. Microarray analysis of Xenopus endoderm expressing Ptf1a

    PubMed Central

    Bilogan, Cassandra K.; Horb, Marko E.

    2012-01-01

    Pancreas specific transcription factor 1a (Ptf1a), a bHLH transcription factor, has two temporally distinct functions during pancreas development; initially it is required for early specification of the entire pancreas, while later it is required for proper differentiation and maintenance of only acinar cells. The importance of Ptf1a function was revealed by the fact that loss of Ptf1a leads to pancreas agenesis in humans. While Ptf1a is one of the most important pancreatic transcription factors, little is known about the differences between the regulatory networks it controls during initial specification of the pancreas as opposed to acinar cell development, and to date no comprehensive analysis of its downstream targets has been published. In this paper, we use Xenopus embryos to identify putative downstream targets of Ptf1a. We isolated anterior endoderm tissue overexpressing Ptf1a at two early stages, NF32 and NF36, and compared their gene expression profiles using microarrays. Our results revealed that Ptf1a regulates genes with a wide variety of functions, providing insight into the complexity of the regulatory network required for pancreas specification. PMID:22815262

  1. A protein microarray-based analysis of S-nitrosylation.

    PubMed

    Foster, Matthew W; Forrester, Michael T; Stamler, Jonathan S

    2009-11-10

    The ubiquitous cellular influence of nitric oxide (NO) is exerted substantially through protein S-nitrosylation. Whereas NO is highly promiscuous, physiological S-nitrosylation is typically restricted to one or very few Cys residue(s) in target proteins. The molecular basis for this specificity may derive from properties of the target protein, the S-nitrosylating species, or both. Here, we describe a protein microarray-based approach to investigate determinants of S-nitrosylation by biologically relevant low-mass S-nitrosothiols (SNOs). We identify large sets of yeast and human target proteins, among which those with active-site Cys thiols residing at N termini of alpha-helices or within catalytic loops were particularly prominent. However, S-nitrosylation varied substantially even within these families of proteins (e.g., papain-related Cys-dependent hydrolases and rhodanese/Cdc25 phosphatases), suggesting that neither secondary structure nor intrinsic nucleophilicity of Cys thiols was sufficient to explain specificity. Further analyses revealed a substantial influence of NO-donor stereochemistry and structure on efficiency of S-nitrosylation as well as an unanticipated and important role for allosteric effectors. Thus, high-throughput screening and unbiased proteome coverage reveal multifactorial determinants of S-nitrosylation (which may be overlooked in alternative proteomic analyses), and support the idea that target specificity can be achieved through rational design of S-nitrosothiols.

  2. Microarray Analysis of Microbiota of Gingival Lesions in Noma Patients

    PubMed Central

    Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques

    2013-01-01

    Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma. PMID:24086784

  3. Identification of bacterial and fungal pathogens from positive blood culture bottles: a microarray-based approach.

    PubMed

    Raich, Teresa; Powell, Scott

    2015-01-01

    Rapid identification and characterization of bacterial and fungal pathogens present in the bloodstream are essential for optimal patient management and are associated with improved patient outcomes, improved antimicrobial stewardship, improved infection control, and reduced healthcare costs. Microarrays serve as reliable platforms for the identification of these bloodstream pathogens and their associated antimicrobial resistance genes, if present. Nanosphere's (Nanosphere, Inc., Northbrook, IL, USA) Verigene Gram-Positive Blood Culture Nucleic-Acid Test (BC-GP) is one such microarray-based approach for the detection of bacteria that cause bloodstream infection. Here, we describe the design of the microarray-based Verigene BC-GP Test, the steps necessary for performing the test, and the different components of the test including nucleic acid extraction and hybridization of target nucleic acid to a microarray.

  4. Improvement in the amine glass platform by bubbling method for a DNA microarray.

    PubMed

    Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

    2015-01-01

    A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

  5. Assessing the reliability of amplified RNA used in microarrays: a DUMB table approach.

    PubMed

    Bearden, Edward D; Simpson, Pippa M; Peterson, Charlotte A; Beggs, Marjorie L

    2006-01-01

    A certain minimal amount of RNA from biological samples is necessary to perform a microarray experiment with suitable replication. In some cases, the amount of RNA available is insufficient, necessitating RNA amplification prior to target synthesis. However, there is some uncertainty about the reliability of targets that have been generated from amplified RNA, because of nonlinearity and preferential amplification. This current work develops a straightforward strategy to assess the reliability of microarray data obtained from amplified RNA. The tabular method we developed, which utilises a Down-Up-Missing-Below (DUMB) classification scheme, shows that microarrays generated with amplified RNA targets are reliable within constraints. There was an increase in false negatives because of the need for increased filtering. Furthermore, this analysis method is generic and can be broadly applied to evaluate all microarray data. A copy of the Microsoft Excel spreadsheet is available upon request from Edward Bearden.

  6. Microarray analysis of p-anisaldehyde-induced transcriptome of Saccharomyces cerevisiae.

    PubMed

    Yu, Lu; Guo, Na; Yang, Yi; Wu, Xiuping; Meng, Rizeng; Fan, Junwen; Ge, Fa; Wang, Xuelin; Liu, Jingbo; Deng, Xuming

    2010-03-01

    p-Anisaldehyde (4-methoxybenzaldehyde), an extract from Pimpinella anisum L. seeds, is a potential novel preservative. To reveal the possible action mechanism of p-anisaldehyde against microorganisms, yeast-based commercial oligonucleotide microarrays were used to analyze the genome-wide transcriptional changes in response to p-anisaldehyde. Quantitative real-time RT-PCR was performed for selected genes to verify the microarray results. We interpreted our microarray data with the clustering tool, T-profiler. Analysis of microarray data revealed that p-anisaldehyde induced the expression of genes related to sulphur assimilation, aromatic aldehydes metabolism, and secondary metabolism, which demonstrated that the addition of p-anisaldehyde may influence the normal metabolism of aromatic aldehydes. This genome-wide transcriptomics approach revealed first insights into the response of Saccharomyces cerevisiae (S. cerevisiae) to p-anisaldehyde challenge.

  7. 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...

  8. Reconfiguration-based implementation of SVM classifier on FPGA for Classifying Microarray data.

    PubMed

    Hussain, Hanaa M; Benkrid, Khaled; Seker, Huseyin

    2013-01-01

    Classifying Microarray data, which are of high dimensional nature, requires high computational power. Support Vector Machines-based classifier (SVM) is among the most common and successful classifiers used in the analysis of Microarray data but also requires high computational power due to its complex mathematical architecture. Implementing SVM on hardware exploits the parallelism available within the algorithm kernels to accelerate the classification of Microarray data. In this work, a flexible, dynamically and partially reconfigurable implementation of the SVM classifier on Field Programmable Gate Array (FPGA) is presented. The SVM architecture achieved up to 85× speed-up over equivalent general purpose processor (GPP) showing the capability of FPGAs in enhancing the performance of SVM-based analysis of Microarray data as well as future bioinformatics applications.

  9. FPGA based system for automatic cDNA microarray image processing.

    PubMed

    Belean, Bogdan; Borda, Monica; Le Gal, Bertrand; Terebes, Romulus

    2012-07-01

    Automation is an open subject in DNA microarray image processing, aiming reliable gene expression estimation. The paper presents a novel shock filter based approach for automatic microarray grid alignment. The proposed method brings up significantly reduced computational complexity compared to state of the art approaches, while similar results in terms of accuracy are achieved. Based on this approach, we also propose an FPGA based system for microarray image analysis that eliminates the shortcomings of existing software platforms: user intervention, increased computational time and cost. Our system includes application-specific architectures which involve algorithm parallelization, aiming fast and automated cDNA microarray image processing. The proposed automated image processing chain is implemented both on a general purpose processor and using the developed hardware architectures as co-processors in a FPGA based system. The comparative results included in the last section show that an important gain in terms of computational time is obtained using hardware based implementations.

  10. [DNA microarrays--perspective of application for drug effectivity and safety evaluation].

    PubMed

    Roman, Iza

    2008-01-01

    Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). Microarray has been successfully applied to the high throughput simultaneous expression of many thousands of genes in a single experiment. One important application of DNA microarray technology, within the context of drugs effectiveness and safety evaluation studies, is its use as a screening tool for the identification of biochemical pathways, potential targets for novel molecular therapeutics, for the identification of molecular mechanisms of toxicity and to understand and predict individual drug sensitivity and resistance. The purpose of this review is presentation of the utility of DNA microarray technology in all phases of the drug discovery process.

  11. 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.

  12. THE MAQC (MICROARRAY QUALITY CONTROL) PROJECT: CALIBRATED RNA SAMPLES, REFERENCE DATASETS, AND QC METRICS AND THRESHOLDS

    EPA Science Inventory

    FDAs Critical Path Initiative identifies pharmacogenomics and toxicogenomics as key opportunities in advancing medical product development and personalized medicine, and the Guidance for Industry: Pharmacogenomic Data Submissions has been released. Microarrays represent a co...

  13. SPERM RNA AMPLIFICATION FOR GENE EXPRESSION PROFILING BY DNA MICROARRAY TECHNOLOGY

    EPA Science Inventory

    Sperm RNA Amplification for Gene Expression Profiling by DNA Microarray Technology
    Hongzu Ren, Kary E. Thompson, Judith E. Schmid and David J. Dix, Reproductive Toxicology Division, NHEERL, Office of Research and Development, US Environmental Protection Agency, Research Triang...

  14. Ultrasensitive microarray bioassays using cyanine5 dye-doped silica nanoparticles

    NASA Astrophysics Data System (ADS)

    Flynn, S. P.; Kelleher, S. M.; Acorn, J. N.; Kurzbuch, D.; Daniels, S.; McDonagh, C.; Clancy, E.; Smith, T. J.; Nooney, R.

    2016-11-01

    Herein we report the use of high brightness Cyanine5-doped silica nanoparticles (NPs) for the detection of antibodies or DNA in microarray bioassays. NP labels showed negligible non-specific binding, greater sensitivity and lower limits of detection when compared to free dye-labelled biomolecules. Moreover, the spotted microarrays used in this study required low NP and antibody concentrations to generate large data sets with improved statistical accuracy. These NPs have significant potential for use in biosensing for disease detection.

  15. A Protein Microarray ELISA for the Detection of Botulinum neurotoxin A

    SciTech Connect

    Varnum, Susan M.

    2007-06-01

    An enzyme-linked immunosorbent assay (ELISA) microarray was developed for the specific and sensitive detection of botulinum neurotoxin A (BoNT/A), using high-affinity recombinant monoclonal antibodies against the receptor binding domain of the heavy chain of BoNT/A. The ELISA microarray assay, because of its sensitivity, offers a screening test with detection limits comparable to the mouse bioassay, with results available in hours instead of days.

  16. 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

  17. POSaM: a fast, flexible, open-source, inkjet oligonucleotide synthesizer and microarrayer

    PubMed Central

    Lausted, Christopher; Dahl, Timothy; Warren, Charles; King, Kimberly; Smith, Kimberly; Johnson, Michael; Saleem, Ramsey; Aitchison, John; Hood, Lee; Lasky, Stephen R

    2004-01-01

    DNA arrays are valuable tools in molecular biology laboratories. Their rapid acceptance was aided by the release of plans for a pin-spotting microarrayer by researchers at Stanford. Inkjet microarraying is a flexible, complementary technique that allows the synthesis of arrays of any oligonucleotide sequences de novo. We describe here an open-source inkjet arrayer capable of rapidly producing sets of unique 9,800-feature arrays. PMID:15287980

  18. 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."

  19. 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.

  20. The use of chromosomal microarray for prenatal diagnosis.

    PubMed

    Dugoff, Lorraine; Norton, Mary E; Kuller, Jeffrey A

    2016-10-01

    Chromosomal microarray analysis is a high-resolution, whole-genome technique used to identify chromosomal abnormalities, including those detected by conventional cytogenetic techniques, as well as small submicroscopic deletions and duplications referred to as copy number variants. Because chromosomal microarray analysis has a greater resolution than conventional karyotyping, it can detect deletions and duplications down to a 50- to 100-kb level. The purpose of this document is to discuss the technique, advantages, and disadvantages of chromosomal microarray analysis and its indications and limitations. We recommend the following: (1) that chromosomal microarray analysis be offered when genetic analysis is performed in cases with fetal structural anomalies and/or stillbirth and replaces the need for fetal karyotype in these cases (GRADE 1A); (2) that providers discuss the benefits and limitations of chromosomal microarray analysis and conventional karyotype with patients who are considering amniocentesis and chorionic villus sampling (CVS), and that both options should be available to women who choose to undergo diagnostic testing (GRADE 1B); (3) that pre- and posttest counseling should be performed by trained genetic counselors, geneticists, or other providers with expertise in the complexities of interpreting chromosomal microarray analysis results (Best Practice); (4) that patients be informed that chromosomal microarray analysis does not detect every genetic disease or syndrome and specifically does not detect autosomal-recessive disorders associated with single gene point mutations, as well as that chromosomal microarray analysis can detect consanguinity and nonpaternity in some cases (Best Practice); (5) that patients in whom a fetal variant of uncertain significance is detected by prenatal diagnosis receive counseling from experts who have access to databases that provide updated information concerning genotype-phenotype correlations (Best Practice).

  1. High-Throughput Nano-Biofilm Microarray for Antifungal Drug Discovery

    DTIC Science & Technology

    2013-06-25

    antifungal drugs against the highly protective structured popula- tion of C. albicans. We have fabricated a cellular microarray sys- tem consisting of...is a robust and effi- cient tool for accelerating the drug discovery process: (i) combinatorial screening against a collection of 28 antifungal com... against the NCI challenge set small-molecule library identified three heretofore-unknown hits. This cell-based microarray platform allows for

  2. DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii

    DTIC Science & Technology

    2004-11-15

    DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii Chien-Chung Chao Rickettsiae Diseases...TITLE AND SUBTITLE DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii 5a. CONTRACT NUMBER 5b...ANSI Std Z39-18 Rickettsiae • Gram negative coccobacillary bacteria • Obligate intracellular organisms • Arthropod-borne • Cause febrile diseases (mild

  3. DNA nanostructure-based universal microarray platform for high-efficiency multiplex bioanalysis in biofluids.

    PubMed

    Li, Zhenhua; Zhao, Bin; Wang, Dongfang; Wen, Yanli; Liu, Gang; Dong, Haoqing; Song, Shiping; Fan, Chunhai

    2014-10-22

    Microarrays of biomolecules have greatly promoted the development of the fields of genomics, proteomics, and clinical assays because of their remarkably parallel and high-throughput assay capability. Immobilization strategies for biomolecules on a solid support surface play a crucial role in the fabrication of high-performance biological microarrays. In this study, rationally designed DNA tetrahedra carrying three amino groups and one single-stranded DNA extension were synthesized by the self-assembly of four oligonucleotides, followed by high-performance liquid chromatography purification. We fabricated DNA tetrahedron-based microarrays by covalently coupling the DNA tetrahedron onto glass substrates. After their biorecognition capability was evaluated, DNA tetrahedron microarrays were utilized for the analysis of different types of bioactive molecules. The gap hybridization strategy, the sandwich configuration, and the engineering aptamer strategy were employed for the assay of miRNA biomarkers, protein cancer biomarkers, and small molecules, respectively. The arrays showed good capability to anchor capture biomolecules for improving biorecognition. Addressable and high-throughput analysis with improved sensitivity and specificity had been achieved. The limit of detection for let-7a miRNA, prostate specific antigen, and cocaine were 10 fM, 40 pg/mL, and 100 nM, respectively. More importantly, we demonstrated that the microarray platform worked well with clinical serum samples and showed good relativity with conventional chemical luminescent immunoassay. We have developed a novel approach for the fabrication of DNA tetrahedron-based microarrays and a universal DNA tetrahedron-based microarray platform for the detection of different types of bioactive molecules. The microarray platform shows great potential for clinical diagnosis.

  4. 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.

  5. 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

  6. Development and validation of protein microarray technology for simultaneous inflammatory mediator detection in human sera.

    PubMed

    Selvarajah, Senthooran; 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.

  7. The detection and differentiation of canine respiratory pathogens using oligonucleotide microarrays.

    PubMed

    Wang, Lih-Chiann; Kuo, Ya-Ting; Chueh, Ling-Ling; Huang, Dean; Lin, Jiunn-Horng

    2017-05-01

    Canine respiratory diseases are commonly seen in dogs along with co-infections with multiple respiratory pathogens, including viruses and bacteria. Virus infections in even vaccinated dogs were also reported. The clinical signs caused by different respiratory etiological agents are similar, which makes differential diagnosis imperative. An oligonucleotide microarray system was developed in this study. The wild type and vaccine strains of canine distemper virus (CDV), influenza virus, canine herpesvirus (CHV), Bordetella bronchiseptica and Mycoplasma cynos were detected and differentiated simultaneously on a microarray chip. The detection limit is 10, 10, 100, 50 and 50 copy numbers for CDV, influenza virus, CHV, B. bronchiseptica and M. cynos, respectively. The clinical test results of nasal swab samples showed that the microarray had remarkably better efficacy than the multiplex PCR-agarose gel method. The positive detection rate of microarray and agarose gel was 59.0% (n=33) and 41.1% (n=23) among the 56 samples, respectively. CDV vaccine strain and pathogen co-infections were further demonstrated by the microarray but not by the multiplex PCR-agarose gel. The oligonucleotide microarray provides a highly efficient diagnosis alternative that could be applied to clinical usage, greatly assisting in disease therapy and control.

  8. Power of deep sequencing and agilent microarray for gene expression profiling study.

    PubMed

    Feng, Lin; Liu, Hang; Liu, Yu; Lu, Zhike; Guo, Guangwu; Guo, Suping; Zheng, Hongwei; Gao, Yanning; Cheng, Shujun; Wang, Jian; Zhang, Kaitai; Zhang, Yong

    2010-06-01

    Next-generation sequencing-based Digital Gene Expression tag profiling (DGE) has been used to study the changes in gene expression profiling. To compare the quality of the data generated by microarray and DGE, we examined the gene expression profiles of an in vitro cell model with these platforms. In this study, 17,362 and 15,938 genes were detected by microarray and DGE, respectively, with 13,221 overlapping genes. The correlation coefficients between the technical replicates were >0.99 and the detection variance was <9% for both platforms. The dynamic range of microarray was fixed with four orders of magnitude, whereas that of DGE was extendable. The consistency of the two platforms was high, especially for those abundant genes. It was more difficult for the microarray to distinguish the expression variation of less abundant genes. Although microarrays might be eventually replaced by DGE or transcriptome sequencing (RNA-seq) in the near future, microarrays are still stable, practical, and feasible, which may be useful for most biological researchers.

  9. In situ synthesis of DNA microarray on functionalized cyclic olefin copolymer substrate.

    PubMed

    Saaem, Ishtiaq; Ma, Kuo-Sheng; Marchi, Alexandria N; LaBean, Thomas H; Tian, Jingdong

    2010-02-01

    Thermoplastic materials such as cyclic-olefin copolymers (COC) provide a versatile and cost-effective alternative to the traditional glass or silicon substrate for rapid prototyping and industrial scale fabrication of microdevices. To extend the utility of COC as an effective microarray substrate, we developed a new method that enabled for the first time in situ synthesis of DNA oligonucleotide microarrays on the COC substrate. To achieve high-quality DNA synthesis, a SiO(2) thin film array was prepatterned on the inert and hydrophobic COC surface using RF sputtering technique. The subsequent in situ DNA synthesis was confined to the surface of the prepatterned hydrophilic SiO(2) thin film features by precision delivery of the phosphoramidite chemistry using an inkjet DNA synthesizer. The in situ SiO(2)-COC DNA microarray demonstrated superior quality and stability in hybridization assays and thermal cycling reactions. Furthermore, we demonstrate that pools of high-quality mixed-oligos could be cleaved off the SiO(2)-COC microarrays and used directly for construction of DNA origami nanostructures. It is believed that this method will not only enable synthesis of high-quality and low-cost COC DNA microarrays but also provide a basis for further development of integrated microfluidics microarrays for a broad range of bioanalytical and biofabrication applications.

  10. Development of a DNA-based microarray for the detection of zoonotic pathogens in rodent species.

    PubMed

    Giles, Timothy; Yon, Lisa; Hannant, Duncan; Barrow, Paul; Abu-Median, Abu-Bakr

    2015-12-01

    The demand for diagnostic tools that allow simultaneous screening of samples for multiple pathogens is increasing because they overcome the limitations of other methods, which can only screen for a single or a few pathogens at a time. Microarrays offer the advantages of being capable to test a large number of samples simultaneously, screening for multiple pathogen types per sample and having comparable sensitivity to existing methods such as PCR. Array design is often considered the most important process in any microarray experiment and can be the deciding factor in the success of a study. There are currently no microarrays for simultaneous detection of rodent-borne pathogens. The aim of this report is to explicate the design, development and evaluation of a microarray platform for use as a screening tool that combines ease of use and rapid identification of a number of rodent-borne pathogens of zoonotic importance. Nucleic acid was amplified by multiplex biotinylation PCR prior to hybridisation onto microarrays. The array sensitivity was comparable to standard PCR, though less sensitive than real-time PCR. The array presented here is a prototype microarray identification system for zoonotic pathogens that can infect rodent species.

  11. Application of a New Genetic Deafness Microarray for Detecting Mutations in the Deaf in China

    PubMed Central

    Wu, Hong; Feng, Yong; Jiang, Lu; Pan, Qian; Liu, Yalan; Liu, Chang; He, Chufeng; Chen, Hongsheng; Liu, Xueming; Hu, Chang; Hu, Yiqiao; Mei, Lingyun

    2016-01-01

    Objective The aim of this study was to evaluate the GoldenGate microarray as a diagnostic tool and to elucidate the contribution of the genes on this array to the development of both nonsyndromic and syndromic sensorineural hearing loss in China. Methods We developed a microarray to detect 240 mutations underlying syndromic and nonsyndromic sensorineural hearing loss. The microarray was then used for analysis of 382 patients with nonsyndromic sensorineural hearing loss (including 15 patients with enlarged vestibular aqueduct syndrome), 21 patients with Waardenburg syndrome, and 60 unrelated controls. Subsequently, we analyzed the sensitivity, specificity, and reproducibility of this new approach after Sanger sequencing-based verification, and also determined the contribution of the genes on this array to the development of distinct hearing disorders. Results The sensitivity and specificity of the microarray chip were 98.73% and 98.34%, respectively. Genetic defects were identified in 61.26% of the patients with nonsyndromic sensorineural hearing loss, and 9 causative genes were identified. The molecular etiology was confirmed in 19.05% and 46.67% of the patients with Waardenburg syndrome and enlarged vestibular aqueduct syndrome, respectively. Conclusion Our new mutation-based microarray comprises an accurate and comprehensive genetic tool for the detection of sensorineural hearing loss. This microarray-based detection method could serve as a first-pass screening (before next-generation-sequencing screening) for deafness-causing mutations in China. PMID:27018795

  12. Application of oligonucleotide microarrays for bacterial source tracking of environmental Enterococcus sp. isolates.

    PubMed

    Indest, Karl J; Betts, Kelley; Furey, John S

    2005-04-01

    In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST) of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Enterococcus sp. isolates originating from deer, bovine, gull, and human sources were examined using microarrays. Isolates were subjected to Box PCR amplification and the resulting amplification products labeled with Cy5. Fluorescent-labeled templates were hybridized to in-house constructed nonamer oligonucleotide microarrays consisting of 198 probes. Microarray hybridization profiles were obtained using the ArrayPro image analysis software. Principal Components Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were compared for their ability to visually cluster microarray hybridization profiles based on the environmental source from which the Enterococcus sp. isolates originated. The PCA was visually superior at separating origin-specific clusters, even for as few as 3 factors. A Soft Independent Modeling (SIM) classification confirmed the PCA, resulting in zero misclassifications using 5 factors for each class. The implication of these results for the application of random oligonucleotide microarrays for BST is that, given the reproducibility issues, factor-based variable selection such as in PCA and SIM greatly outperforms dendrogram-based similarity measures such as in HCA and K-Nearest Neighbor KNN.

  13. Application of Oligonucleotide Microarrays for Bacterial Source Tracking of Environmental Enterococcus sp. Isolates

    PubMed Central

    Indest, Karl J.; Betts, Kelley; Furey, John S.

    2005-01-01

    In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST) of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Enterococcus sp. isolates originating from deer, bovine, gull, and human sources were examined using microarrays. Isolates were subjected to Box PCR amplification and the resulting amplification products labeled with Cy5. Fluorescent-labeled templates were hybridized to in-house constructed nonamer oligonucleotide microarrays consisting of 198 probes. Microarray hybridization profiles were obtained using the ArrayPro image analysis software. Principal Components Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were compared for their ability to visually cluster microarray hybridization profiles based on the environmental source from which the Enterococcus sp. isolates originated. The PCA was visually superior at separating origin-specific clusters, even for as few as 3 factors. A Soft Independent Modeling (SIM) classification confirmed the PCA, resulting in zero misclassifications using 5 factors for each class. The implication of these results for the application of random oligonucleotide microarrays for BST is that, given the reproducibility issues, factor-based variable selection such as in PCA and SIM greatly outperforms dendrogram-based similarity measures such as in HCA and K-Nearest Neighbor KNN. PMID:16705816

  14. 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.

  15. 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.

  16. A microfluidic device for the automated electrical readout of low-density glass-slide microarrays.

    PubMed

    Díaz-González, María; Salvador, J Pablo; Bonilla, Diana; Marco, M Pilar; Fernández-Sánchez, César; Baldi, Antoni

    2015-12-15

    Microarrays are a powerful platform for rapid and multiplexed analysis in a wide range of research fields. Electrical readout systems have emerged as an alternative to conventional optical methods for microarray analysis thanks to its potential advantages like low-cost, low-power and easy miniaturization of the required instrumentation. In this work an automated electrical readout system for low-cost glass-slide microarrays is described. The system enables the simultaneous conductimetric detection of up to 36 biorecognition events by incorporating an array of interdigitated electrode transducers. A polydimethylsiloxane microfluidic structure has been designed that creates microwells over the transducers and incorporates the microfluidic channels required for filling and draining them with readout and cleaning solutions, thus making the readout process fully automated. Since the capture biomolecules are not immobilized on the transducer surface this readout system is reusable, in contrast to previously reported electrochemical microarrays. A low-density microarray based on a competitive enzymatic immunoassay for atrazine detection was used to test the performance of the readout system. The electrical assay shows a detection limit of 0.22±0.03 μg L(-1) similar to that obtained with fluorescent detection and allows the direct determination of the pesticide in polluted water samples. These results proved that an electrical readout system such as the one presented in this work is a reliable and cost-effective alternative to fluorescence scanners for the analysis of low-density microarrays.

  17. Which Members of the Microbial Communities Are Active? Microarrays

    NASA Astrophysics Data System (ADS)

    Morris, Brandon E. L.

    Here, we introduce the concept of microarrays, discuss the advantages of several different types of arrays and present a case study that illustrates a targeted-profiling approach to bioremediation of a hydrocarbon-contaminated site in an Arctic environment. The majority of microorganisms in the terrestrial subsurface, particularly those involved in 'heavy oil' formation, reservoir souring or biofouling remain largely uncharacterised (Handelsman, 2004). There is evidence though that these processes are biologically catalysed, including stable isotopic composition of hydrocarbons in oil formations (Pallasser, 2000; Sun et al., 2005), the absence of biodegraded oil from reservoirs warmer than 80°C (Head et al., 2003) or negligible biofouling in the absence of biofilms (Dobretsov et al., 2009; Lewandowski and Beyenal, 2008), and all clearly suggest an important role for microorganisms in the deep biosphere in general and oilfield systems in particular. While the presence of sulphate-reducing bacteria in oilfields was first observed in the early twentieth century (Bastin, 1926), it was only through careful experiments with isolates from oil systems or contaminated environments that unequivocal evidence for hydrocarbon biodegradation under anaerobic conditions was provided (for a review, see Widdel et al., 2006). Work with pure cultures and microbial enrichments also led to the elucidation of the biochemistry of anaerobic aliphatic and aromatic hydrocarbon degradation and the identification of central metabolites and genes involved in the process, e.g. (Callaghan et al., 2008; Griebler et al., 2003; Kropp et al., 2000). This information could then be extrapolated to the environment to monitor degradation processes and determine if in situ microbial populations possessed the potential for contaminant bioremediation, e.g. Parisi et al. (2009). While other methods have also been developed to monitor natural attenuation of hydrocarbons (Meckenstock et al., 2004), we are

  18. DNA Microarray-Based Typing of Streptococcus agalactiae Isolates

    PubMed Central

    Nitschke, Heike; Slickers, Peter; Müller, Elke; Ehricht, Ralf

    2014-01-01

    Streptococcus agalactiae frequently colonizes the urogenital tract, and it is a major cause of bacterial septicemia, meningitis, and pneumonia in newborns. For typing purposes, a microarray targeting group B streptococcus (GBS) virulence-associated markers and resistance genes was designed and validated with reference strains, as well as clinical and veterinary isolates. Selected isolates were also subjected to multilocus sequence typing. It was observed that putative typing markers, such as alleles of the alpha-like protein or capsule types, vary independently of each other, and they also vary independently from the affiliation to their multilocus sequence typing (MLST)-defined sequence types. Thus, it is not possible to assign isolates to sequence types based on the identification of a single distinct marker, such as a capsule type or alp allele. This suggests the occurrence of frequent genomic recombination. For array-based typing, a set of 11 markers (bac, alp, pil1 locus, pepS8, fbsB, capsule locus, hylB, abiG-I/-II plus Q8DZ34, pil2 locus, nss plus srr plus rogB2, and rgfC/A/D/B) was defined that provides a framework for splitting the tested 448 S. agalactiae isolates into 76 strains that clustered mainly according to MLST-defined clonal complexes. There was evidence for region- and host-specific differences in the population structure of S. agalactiae, as well as an overrepresentation of strains related to sequence type 17 among the invasive isolates. The arrays and typing scheme described here proved to be a convenient tool for genotyping large numbers of clinical/veterinary isolates and thus might help obtain insight into the epidemiology of S. agalactiae. PMID:25165085

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

    PubMed Central

    Tintle, Nathan L; Best, Aaron A; DeJongh, Matthew; Van Bruggen, Dirk; Heffron, Fred; Porwollik, Steffen; Taylor, Ronald C

    2008-01-01

    Background Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use biologically defined sets of genes in interpretation, instead of examining results gene-by-gene. Despite a serious limitation, a method based on Fisher's exact test remains one of the few plausible options for gene set analysis when an experiment has few replicates, as is typically the case for prokaryotes. Results We extend five methods of gene set analysis from use on experiments with multiple replicates, for use on experiments with few replicates. We then use simulated and real data to compare these methods with each other and with the Fisher's exact test (FET) method. As a result of the simulation we find that a method named MAXMEAN-NR, maintains the nominal rate of false positive findings (type I error rate) while offering good statistical power and robustness to a variety of gene set distributions for set sizes of at least 10. Other methods (ABSSUM-NR or SUM-NR) are shown to be powerful for set sizes less than 10. Analysis of three sets of experimental data shows similar results. Furthermore, the MAXMEAN-NR method is shown to be able to detect biologically relevant sets as significant, when other methods (including FET) cannot. We also find that the popular GSEA-NR method performs poorly when compared to MAXMEAN-NR. Conclusion MAXMEAN-NR is a method of gene set analysis for experiments with few replicates, as is common for prokaryotes. Results of simulation and real data analysis suggest that the MAXMEAN-NR method offers increased robustness and biological relevance of findings as compared to FET and other methods, while maintaining the nominal type I error rate. PMID:18986519

  20. Impact of Microarray Preprocessing Techniques in Unraveling Biological Pathways.

    PubMed

    Deandrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Saligan, Leorey N; Sonis, Stephen T

    2016-12-01

    To better understand the impact of microarray preprocessing normalization techniques on the analysis of biological pathways in the prediction of chronic fatigue (CF) following radiation therapy, this study has compared the list of predictive genes found using the Robust Multiarray Averaging (RMA) and the Affymetrix MAS5 method, with the list that is obtained working with raw data (without any preprocessing). First, we modeled the spiked-in data set where differentially expressed genes were known and spiked-in at different known concentrations, showing that the precisions established by different gene ranking methods were higher than working with raw data. The results obtained from the spiked-in experiment were extrapolated to the CF data set to run learning and blind validation. RMA and MAS5 provided different sets of discriminatory genes that have a higher predictive accuracy in the learning phase, but lower predictive accuracy during the blind validation phase, suggesting that the genetic signatures generated using both preprocessing techniques cannot be generalizable. The pathways found using the raw data set better described what is a priori known for the CF disease. Besides, RMA produced more reliable pathways than MAS5. Understanding the strengths of these two preprocessing techniques in phenotype prediction is critical for precision medicine. Particularly, this article concludes that biological pathways might be better unraveled working with raw expression data. Moreover, the interpretation of the predictive gene profiles generated by RMA and MAS5 should be done with caution. This is an important conclusion with a high translational impact that should be confirmed in other disease data sets.

  1. Microarray-based mutation detection in the dystrophin gene

    PubMed Central

    Hegde, Madhuri R.; Chin, Ephrem L.H.; Mulle, Jennifer G.; Okou, David T.; Warren, Stephen T.; Zwick, Michael E.

    2008-01-01

    Duchenne and Becker muscular dystrophies (DMD and BMD) are X-linked recessive neuromuscular disorders caused by mutations in the dystrophin gene affecting approximately 1 in 3,500 males. The human dystrophin gene spans > 2,200 kb, or roughly 0.1% of the genome, and is composed of 79 exons. The mutational spectrum of disease-causing alleles, including exonic copy number variations (CNVs), is complex. Deletions account for approximately 65% of DMD mutations and 85% of BMD mutations. Duplications occur in approximately 6–10% of males with either DMD or BMD. The remaining 30–35% of mutations consist of small deletions, insertions, point mutations, or splicing mutations, most of which introduce a premature stop codon. Laboratory analysis of dystrophin can be used to confirm a clinical diagnosis of DMD, characterize the type of dystrophin mutation, and perform prenatal testing and carrier testing for females. Current dystrophin diagnostic assays involve a variety of methodologies, including multiplex PCR, Southern blot analysis, MLPA, DOVAM-S, and SCAIP; however, these methods are time-consuming, laborious, and do not accurately detect duplication mutations in the dystrophin gene. Furthermore, carrier testing in females is often difficult when a related affected male is unavailable. Here we describe the development, design, validation, and implementation of a high-resolution CGH microarray-based approach capable of accurately detecting both deletions and duplications in the dystrophin gene. This assay can be readily adopted by clinical molecular testing laboratories and represents a rapid, cost-effective approach for screening a large gene, such as dystrophin. PMID:18663755

  2. Microarray-based mutation detection in the dystrophin gene.

    PubMed

    Hegde, Madhuri R; Chin, Ephrem L H; Mulle, Jennifer G; Okou, David T; Warren, Stephen T; Zwick, Michael E

    2008-09-01

    Duchenne and Becker muscular dystrophies (DMD and BMD) are X-linked recessive neuromuscular disorders caused by mutations in the dystrophin gene affecting approximately 1 in 3,500 males. The human dystrophin gene spans>2,200 kb, or roughly 0.1% of the genome, and is composed of 79 exons. The mutational spectrum of disease-causing alleles, including exonic copy number variations (CNVs), is complex. Deletions account for approximately 65% of DMD mutations and 85% of BMD mutations. Duplications occur in approximately 6 to 10% of males with either DMD or BMD. The remaining 30 to 35% of mutations consist of small deletions, insertions, point mutations, or splicing mutations, most of which introduce a premature stop codon. Laboratory analysis of dystrophin can be used to confirm a clinical diagnosis of DMD, characterize the type of dystrophin mutation, and perform prenatal testing and carrier testing for females. Current dystrophin diagnostic assays involve a variety of methodologies, including multiplex PCR, Southern blot analysis, multiplex ligation-dependent probe amplification (MLPA), detection of virtually all mutations-SSCP (DOVAM-S), and single condition amplification/internal primer sequencing (SCAIP); however, these methods are time-consuming, laborious, and do not accurately detect duplication mutations in the dystrophin gene. Furthermore, carrier testing in females is often difficult when a related affected male is unavailable. Here we describe the development, design, validation, and implementation of a high-resolution comparative genomic hybridization (CGH) microarray-based approach capable of accurately detecting both deletions and duplications in the dystrophin gene. This assay can be readily adopted by clinical molecular testing laboratories and represents a rapid, cost-effective approach for screening a large gene, such as dystrophin.

  3. Exploring Lactobacillus plantarum Genome Diversity by Using Microarrays

    PubMed Central

    Molenaar, Douwe; Bringel, Françoise; Schuren, Frank H.; de Vos, Willem M.; Siezen, Roland J.; Kleerebezem, Michiel

    2005-01-01

    Lactobacillus plantarum is a versatile and flexible species that is encountered in a variety of niches and can utilize a broad range of fermentable carbon sources. To assess if this versatility is linked to a variable gene pool, microarrays containing a subset of small genomic fragments of L. plantarum strain WCFS1 were used to perform stringent genotyping of 20 strains of L. plantarum from various sources. The gene categories with the most genes conserved in all strains were those involved in biosynthesis or degradation of structural compounds like proteins, lipids, and DNA. Conversely, genes involved in sugar transport and catabolism were highly variable between strains. Moreover, besides the obvious regions of variance, like prophages, other regions varied between the strains, including regions encoding plantaricin biosynthesis, nonribosomal peptide biosynthesis, and exopolysaccharide biosynthesis. In many cases, these variable regions colocalized with regions of unusual base composition. Two large regions of flexibility were identified between 2.70 and 2.85 and 3.10 and 3.29 Mb of the WCFS1 chromosome, the latter being close to the origin of replication. The majority of genes encoded in these variable regions are involved in sugar metabolism. This functional overrepresentation and the unusual base composition of these regions led to the hypothesis that they represented lifestyle adaptation regions in L. plantarum. The present study consolidates this hypothesis by showing that there is a high degree of gene content variation among L. plantarum strains in genes located in these regions of the WCFS1 genome. Interestingly, based on our genotyping data L. plantarum strains clustered into two clearly distinguishable groups, which coincided with an earlier proposed subdivision of this species based on conventional methods. PMID:16109953

  4. Multilabel Image Annotation Based on Double-Layer PLSA Model

    PubMed Central

    Zhang, Jing; Li, Da; Hu, Weiwei; Chen, Zhihua; Yuan, Yubo

    2014-01-01

    Due to the semantic gap between visual features and semantic concepts, automatic image annotation has become a difficult issue in computer vision recently. We propose a new image multilabel annotation method based on double-layer probabilistic latent semantic analysis (PLSA) in this paper. The new double-layer PLSA model is constructed to bridge the low-level visual features and high-level semantic concepts of images for effective image understanding. The low-level features of images are represented as visual words by Bag-of-Words model; latent semantic topics are obtained by the first layer PLSA from two aspects of visual and texture, respectively. Furthermore, we adopt the second layer PLSA to fuse the visual and texture latent semantic topics and achieve a top-layer latent semantic topic. By the double-layer PLSA, the relationships between visual features and semantic concepts of images are established, and we can predict the labels of new images by their low-level features. Experimental results demonstrate that our automatic image annotation model based on double-layer PLSA can achieve promising performance for labeling and outperform previous methods on standard Corel dataset. PMID:24999490

  5. Annotation-Based Learner's Personality Modeling in Distance Learning Context

    ERIC Educational Resources Information Center

    Omheni, Nizar; Kalboussi, Anis; Mazhoud, Omar; Kacem, Ahmed Hadj

    2016-01-01

    Researchers in distance education are interested in observing and modeling learners' personality profiles, and adapting their learning experiences accordingly. When learners read and interact with their reading materials, they do unselfconscious activities like annotation which may be key feature of their personalities. Annotation activity…

  6. Identification of key genes associated with cervical cancer by comprehensive analysis of transcriptome microarray and methylation microarray

    PubMed Central

    LIU, MING-YAN; ZHANG, HONG; HU, YUAN-JING; CHEN, YU-WEI; ZHAO, XIAO-NAN

    2016-01-01

    Cervical cancer is the second most commonly diagnosed type of cancer and the third leading cause of cancer-associated mortality in women. The current study aimed to determine the genes associated with cervical cancer development. Microarray data (GSE55940 and GSE46306) were downloaded from Gene Expression Omnibus. Overlapping genes between the differentially expressed genes (DEGs) in GSE55940 (identified by Limma package) and the differentially methylated genes were screened. Gene Ontology (GO) enrichment analysis was subsequently performed for these genes using the ToppGene database. In GSE55940, 91 downregulated and 151 upregulated DEGs were identified. In GSE46306, 561 overlapping differentially methylated genes were obtained through the differential methylation analysis at the CpG site level, CpG island level and gene level. A total of 5 overlapping genes [dipeptidyl peptidase 4 (DPP4); endothelin 3 (EDN3); fibroblast growth factor 14 (FGF14); tachykinin, precursor 1 (TAC1); and wingless-type MMTV integration site family, member 16 (WNT16)] between the 561 overlapping differentially methylated genes and the 242 DEGs were identified, which were downregulated and hypermethylated simultaneously in cervical cancer samples. Enriched GO terms were receptor binding (involving DPP4, EDN3, FGF14, TAC1 and WNT16), ameboidal-type cell migration (DPP4, EDN3 and TAC1), mitogen-activated protein kinase cascade (FGF14, EDN3 and WNT16) and cell proliferation (EDN3, WNT16, DPP4 and TAC1). These results indicate that DPP4, EDN3, FGF14, TAC1 and WNT16 may be involved in the pathogenesis of cervical cancer. PMID:27347167

  7. Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning

    PubMed Central

    Maulik, Ujjwal

    2014-01-01

    Microarrays have now gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to novel algorithms for analyzing changes in expression profiles. In a micro-RNA (miRNA) or gene-expression profiling experiment, the expression levels of thousands of genes/miRNAs are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages on their expressions. Microarray-based gene expression profiling can be used to identify genes, whose expressions are changed in response to pathogens or other organisms by comparing gene expression in infected to that in uninfected cells or tissues. Recent studies have revealed that patterns of altered microarray expression profiles in cancer can serve as molecular biomarkers for tumor diagnosis, prognosis of disease-specific outcomes, and prediction of therapeutic responses. Microarray data sets containing expression profiles of a number of miRNAs or genes are used to identify biomarkers, which have dysregulation in normal and malignant tissues. However, small sample size remains a bottleneck to design successful classification methods. On the other hand, adequate number of microarray data that do not have clinical knowledge can be employed as additional source of information. In this paper, a combination of kernelized fuzzy rough set (KFRS) and semisupervised support vector machine (S3VM) is proposed for predicting cancer biomarkers from one miRNA and three gene expression data sets. Biomarkers are discovered employing three feature selection methods, including KFRS. The effectiveness of the proposed KFRS and S3VM combination on the microarray data sets is demonstrated, and the cancer biomarkers identified from miRNA data are reported. Furthermore, biological significance tests are conducted for miRNA cancer biomarkers. PMID:27170887

  8. Identifying Cancer Biomarkers From Microarray Data Using Feature Selection and Semisupervised Learning.

    PubMed

    Chakraborty, Debasis; Maulik, Ujjwal

    2014-01-01

    Microarrays have now gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from simple visual assessments of results to novel algorithms for analyzing changes in expression profiles. In a micro-RNA (miRNA) or gene-expression profiling experiment, the expression levels of thousands of genes/miRNAs are simultaneously monitored to study the effects of certain treatments, diseases, and developmental stages on their expressions. Microarray-based gene expression profiling can be used to identify genes, whose expressions are changed in response to pathogens or other organisms by comparing gene expression in infected to that in uninfected cells or tissues. Recent studies have revealed that patterns of altered microarray expression profiles in cancer can serve as molecular biomarkers for tumor diagnosis, prognosis of disease-specific outcomes, and prediction of therapeutic responses. Microarray data sets containing expression profiles of a number of miRNAs or genes are used to identify biomarkers, which have dysregulation in normal and malignant tissues. However, small sample size remains a bottleneck to design successful classification methods. On the other hand, adequate number of microarray data that do not have clinical knowledge can be employed as additional source of information. In this paper, a combination of kernelized fuzzy rough set (KFRS) and semisupervised support vector machine (S(3)VM) is proposed for predicting cancer biomarkers from one miRNA and three gene expression data sets. Biomarkers are discovered employing three feature selection methods, including KFRS. The effectiveness of the proposed KFRS and S(3)VM combination on the microarray data sets is demonstrated, and the cancer biomarkers identified from miRNA data are reported. Furthermore, biological significance tests are conducted for miRNA cancer biomarkers.

  9. 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

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

    PubMed Central

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

    2008-01-01

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

  11. THEME: a web tool for loop-design microarray data analysis.

    PubMed

    Chen, Chaang-Ray; Shu, Wun-Yi; Tsai, Min-Lung; Cheng, Wei-Chung; Hsu, Ian C

    2012-02-01

    A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/.

  12. Identifying genes relevant to specific biological conditions in time course microarray experiments.

    PubMed

    Singh, Nitesh Kumar; Repsilber, Dirk; Liebscher, Volkmar; Taher, Leila; Fuellen, Georg

    2013-01-01

    Microarrays have been useful in understanding various biological processes by allowing the simultaneous study of the expression of thousands of genes. However, the analysis of microarray data is a challenging task. One of the key problems in microarray analysis is the classification of unknown expression profiles. Specifically, the often large number of non-informative genes on the microarray adversely affects the performance and efficiency of classification algorithms. Furthermore, the skewed ratio of sample to variable poses a risk of overfitting. Thus, in this context, feature selection methods become crucial to select relevant genes and, hence, improve classification accuracy. In this study, we investigated feature selection methods based on gene expression profiles and protein interactions. We found that in our setup, the addition of protein interaction information did not contribute to any significant improvement of the classification results. Furthermore, we developed a novel feature selection method that relies exclusively on observed gene expression changes in microarray experiments, which we call "relative Signal-to-Noise ratio" (rSNR). More precisely, the rSNR ranks genes based on their specificity to an experimental condition, by comparing intrinsic variation, i.e. variation in gene expression within an experimental condition, with extrinsic variation, i.e. variation in gene expression across experimental conditions. Genes with low variation within an experimental condition of interest and high variation across experimental conditions are ranked higher, and help in improving classification accuracy. We compared different feature selection methods on two time-series microarray datasets and one static microarray dataset. We found that the rSNR performed generally better than the other methods.

  13. The implications of microarray technology for animal use in scientific research.

    PubMed

    Jenkins, Elizabeth S; Broadhead, Caren; Combes, Robert D

    2002-01-01

    Microarray technology has the potential to affect the number of laboratory animals used, the severity of animal experiments, and the development of non-animal alternatives in several areas scientific research. Microarrays can contain hundreds or thousands of microscopic spots of DNA, immobilised on a solid support, and their use enables global patterns of gene expression to be determined in a single experiment. This technology is being used to improve our understanding of the operation of biological systems during health and disease, and their responses to chemical insults. Although it is impossible to predict with certainty any future trends regarding animal use, microarray technology might not initially reduce animal use, as is often claimed to be the case. The accelerated pace of research as a result of the use of microarrays could increase overall animal use in basic and applied biological research, by increasing the numbers of interesting genes identified for further analysis, and the number of potential targets for drug development. Each new lead will require further evaluation i n studies that could involve animals. In toxicity testing, microarray studies could lead to increases in animal studies, if further confirmatory and other studies are performed. However, before such technology can be used more extensively, several technical problems need to be overcome, and the relevance of the data to biological processes needs to be assessed. Were microarray technology to be used in the manner envisaged by its protagonists, there need to be efforts to increase the likelihood that its application will create new opportunities for reducing, refining and replacing animal use. This comment is a critical assessment of the possible implications of the application of microarray technology on animal experimentation in various research areas, and makes some recommendations for maximising the application of the Three Rs.

  14. Stable feature selection and classification algorithms for multiclass microarray data

    PubMed Central

    2012-01-01

    Background Recent studies suggest that gene expression profiles are a promising alternative for clinical cancer classification. One major problem in applying DNA microarrays for classification is the dimension of obtained data sets. In this paper we propose a multiclass gene selection method based on Partial Least Squares (PLS) for selecting genes for classification. The new idea is to solve multiclass selection problem with the PLS method and decomposition to a set of two-class sub-problems: one versus rest (OvR) and one versus one (OvO). We use OvR and OvO two-class decomposition for other recently published gene selection method. Ranked gene lists are highly unstable in the sense that a small change of the data set often leads to big changes in the obtained ordered lists. In this paper, we take a look at the assessment of stability of the proposed methods. We use the linear support vector machines (SVM) technique in different variants: one versus one, one versus rest, multiclass SVM (MSVM) and the linear discriminant analysis (LDA) as a classifier. We use balanced bootstrap to estimate the prediction error and to test the variability of the obtained ordered lists. Results This paper focuses on effective identification of informative genes. As a result, a new strategy to find a small subset of significant genes is designed. Our results on real multiclass cancer data show that our method has a very high accuracy rate for different combinations of classification methods, giving concurrently very stable feature rankings. Conclusions This paper shows that the proposed strategies can improve the performance of selected gene sets substantially. OvR and OvO techniques applied to existing gene selection methods improve results as well. The presented method allows to obtain a more reliable classifier with less classifier error. In the same time the method generates more stable ordered feature lists in comparison with existing methods. Reviewers This article was reviewed

  15. Microarray profiling of circular RNAs in human papillary thyroid carcinoma

    PubMed Central

    Peng, Nianchun; Shi, Lixin; Zhang, Qiao; Hu, Ying; Wang, Nanpeng; Ye, Hui

    2017-01-01

    Background Non-coding circular RNAs (circRNAs) have displayed dysregulated expression in several human cancers. Here, we profiled the circRNA expression of papillary thyroid carcinoma (PTC) tumors to improve our understanding of PTC pathogenesis. Methods Microarray profiling was performed on 18 thyroid samples, consisting of six PTC tumors, six matching contralateral normal samples, and six benign thyroid lesions. After low-intensity filtering, hierarchical clustering revealed the circRNA expression patterns. Statistical analysis followed by qRT-PCR validation identified the differential circRNAs. MicroRNA (miRNA) target prediction software identified putative miRNA response elements (MREs), which were used to construct a network map of circRNA-miRNA interactions for the differential circRNAs. Bioinformatics platforms predicted cancer-related circRNA-miRNA associations and putative downstream target genes, respectively. Results A total of 88 circRNAs and 10 circRNAs were significantly upregulated and downregulated, respectively, in PTC tumors relative to normal thyroid tissue, while 129 circRNAs and 226 circRNAs were significantly upregulated and downregulated, respectively, in PTC tumors relative to benign thyroid lesions. A total of 12 upregulated and four downregulated circRNAs were overlapping between the foregoing comparisons. One downregulated circRNA (hsa_circRNA_100395) showed interactive potential with two cancer-related miRNAs (miR-141-3p and miR-200a-3p). From this analysis, we identified several promising cancer-related genes that may be targets of the dysregulated hsa_circRNA_100395/miR-141-3p/miR-200a-3p axis in PTC tumors. Conclusions circRNA dysregulation may play a role in PTC pathogenesis, and several key circRNAs show promise as candidate biomarkers for PTC. The hsa_circRNA_100395/miR-141-3p/ miR-200a-3p axis may be involved in the pathogenesis of PTC. PMID:28288173

  16. Microgel Tethering For Microarray-Based Nucleic Acid Diagnostics

    NASA Astrophysics Data System (ADS)

    Dai, Xiaoguang

    Molecular diagnostics (MDx) have radically changed the process of clinical microbial identification based on identifying genetic information, MDx approaches are both specific and fast. They can identify microbes to the species and strain level over a time scale that can be as short as one hour. With such information clinicians can administer the most effective and appropriate antimicrobial treatment at an early time point with substantial implications both for patient well-being and for easing the burden on the health-care system. Among the different MDx approaches, such as fluorescence in-situ hybridization, microarrays, next-generation sequencing, and mass spectrometry, point-of-care MDx platforms are drawing particular interest due to their low cost, robustness, and wide application. This dissertation develops a novel MDx technology platform capable of high target amplification and detection performance. For nucleic acid target detection, we fabricate an array of electron-beam-patterned microgels on a standard glass microscope slide. The microgels can be as small as a few hundred nanometers. The unique way of energy deposition during electron-beam lithography provides the microgels with a very diffuse water -gel interface that enables them to not only serve as substrates to immobilize DNA probes but do so while preserving them in a highly hydrated environment that optimizes their performance. Benefiting from the high spatial resolution provided by such techniques as position-sensitive microspotting and dip-pen nanolithography, multiple oligonucleotide probes known as molecular beacons (MBs) can be patterned on microgels. Furthermore, nucleic acid target amplification can be conducted in direct contact with the microgel-tethered detection array. Specifically, we use an isothermal RNA amplification reaction - nucleic acid sequence-based amplification (NASBA). ssRNA amplicons of from the NASBA reaction can directly hybridize with microgel-tethered MBs, and the

  17. A label-free, fluorescence based assay for microarray

    NASA Astrophysics Data System (ADS)

    Niu, Sanjun

    DNA chip technology has drawn tremendous attention since it emerged in the mid 90's as a method that expedites gene sequencing by over 100-fold. DNA chip, also called DNA microarray, is a combinatorial technology in which different single-stranded DNA (ssDNA) molecules of known sequences are immobilized at specific spots. The immobilized ssDNA strands are called probes. In application, the chip is exposed to a solution containing ssDNA of unknown sequence, called targets, which are labeled with fluorescent dyes. Due to specific molecular recognition among the base pairs in the DNA, the binding or hybridization occurs only when the probe and target sequences are complementary. The nucleotide sequence of the target is determined by imaging the fluorescence from the spots. The uncertainty of background in signal detection and statistical error in data analysis, primarily due to the error in the DNA amplification process and statistical distribution of the tags in the target DNA, have become the fundamental barriers in bringing the technology into application for clinical diagnostics. Furthermore, the dye and tagging process are expensive, making the cost of DNA chips inhibitive for clinical testing. These limitations and challenges make it difficult to implement DNA chip methods as a diagnostic tool in a pathology laboratory. The objective of this dissertation research is to provide an alternative approach that will address the above challenges. In this research, a label-free assay is designed and studied. Polystyrene (PS), a commonly used polymeric material, serves as the fluorescence agent. Probe ssDNA is covalently immobilized on polystyrene thin film that is supported by a reflecting substrate. When this chip is exposed to excitation light, fluorescence light intensity from PS is detected as the signal. Since the optical constants and conformations of ssDNA and dsDNA (double stranded DNA) are different, the measured fluorescence from PS changes for the same

  18. Characterization of Influenza Vaccine Immunogenicity Using Influenza Antigen Microarrays

    PubMed Central

    Kattah, Nicole H.; Newell, Evan; Dekker, Cornelia L.; Davis, Mark M.; Utz, Paul J.

    2013-01-01

    Background Existing methods to measure influenza vaccine immunogenicity prohibit detailed analysis of epitope determinants recognized by immunoglobulins. The development of highly multiplex proteomics platforms capable of capturing a high level of antibody binding information will enable researchers and clinicians to generate rapid and meaningful readouts of influenza-specific antibody reactivity. Methods We developed influenza hemagglutinin (HA) whole-protein and peptide microarrays and validated that the arrays allow detection of specific antibody reactivity across a broad dynamic range using commercially available antibodies targeted to linear and conformational HA epitopes. We derived serum from blood draws taken from 76 young and elderly subjects immediately before and 28±7 days post-vaccination with the 2008/2009 trivalent influenza vaccine and determined the antibody reactivity of these sera to influenza array antigens. Results Using linear regression and correcting for multiple hypothesis testing by the Benjamini and Hochberg method of permutations over 1000 resamplings, we identified antibody reactivity to influenza whole-protein and peptide array features that correlated significantly with age, H1N1, and B-strain post-vaccine titer as assessed through a standard microneutralization assay (p<0.05, q <0.2). Notably, we identified several peptide epitopes that were inversely correlated with regard to age and seasonal H1N1 and B-strain neutralization titer (p<0.05, q <0.2), implicating reactivity to these epitopes in age-related defects in response to H1N1 influenza. We also employed multivariate linear regression with cross-validation to build models based on age and pre-vaccine peptide reactivity that predicted vaccine-induced neutralization of seasonal H1N1 and H3N2 influenza strains with a high level of accuracy (84.7% and 74.0%, respectively). Conclusion Our methods provide powerful tools for rapid and accurate measurement of broad antibody-based immune

  19. Toward 'smart' DNA microarrays: algorithms for improving data quality and statistical inference

    NASA Astrophysics Data System (ADS)

    Bakewell, David J. G.; Wit, Ernst

    2007-12-01

    DNA microarrays are a laboratory tool for understanding biological processes at the molecular scale and future applications of this technology include healthcare, agriculture, and environment. Despite their usefulness, however, the information microarrays make available to the end-user is not used optimally, and the data is often noisy and of variable quality. This paper describes the use of hierarchical Maximum Likelihood Estimation (MLE) for generating algorithms that improve the quality of microarray data and enhance statistical inference about gene behavior. The paper describes examples of recent work that improves microarray performance, demonstrated using data from both Monte Carlo simulations and published experiments. One example looks at the variable quality of cDNA spots on a typical microarray surface. It is shown how algorithms, derived using MLE, are used to "weight" these spots according to their morphological quality, and subsequently lead to improved detection of gene activity. Another example, briefly discussed, addresses the "noisy data about too many genes" issue confronting many analysts who are also interested in the collective action of a group of genes, often organized as a pathway or complex. Preliminary work is described where MLE is used to "share" variance information across a pre-assigned group of genes of interest, leading to improved detection of gene activity.

  20. An event-specific DNA microarray to identify genetically modified organisms in processed foods.

    PubMed

    Kim, Jae-Hwan; Kim, Su-Youn; Lee, Hyungjae; Kim, Young-Rok; Kim, Hae-Yeong

    2010-05-26

    We developed an event-specific DNA microarray system to identify 19 genetically modified organisms (GMOs), including two GM soybeans (GTS-40-3-2 and A2704-12), thirteen GM maizes (Bt176, Bt11, MON810, MON863, NK603, GA21, T25, TC1507, Bt10, DAS59122-7, TC6275, MIR604, and LY038), three GM canolas (GT73, MS8xRF3, and T45), and one GM cotton (LLcotton25). The microarray included 27 oligonucleotide probes optimized to identify endogenous reference targets, event-specific targets, screening targets (35S promoter and nos terminator), and an internal target (18S rRNA gene). Thirty-seven maize-containing food products purchased from South Korean and US markets were tested for the presence of GM maize using this microarray system. Thirteen GM maize events were simultaneously detected using multiplex PCR coupled with microarray on a single chip, at a limit of detection of approximately 0.5%. Using the system described here, we detected GM maize in 11 of the 37 food samples tested. These results suggest that an event-specific DNA microarray system can reliably detect GMOs in processed foods.

  1. Hybridization chain reaction amplification for highly sensitive fluorescence detection of DNA with dextran coated microarrays.

    PubMed

    Chao, Jie; Li, Zhenhua; Li, Jing; Peng, Hongzhen; Su, Shao; Li, Qian; Zhu, Changfeng; Zuo, Xiaolei; Song, Shiping; Wang, Lianhui; Wang, Lihua

    2016-07-15

    Microarrays of biomolecules hold great promise in the fields of genomics, proteomics, and clinical assays on account of their remarkably parallel and high-throughput assay capability. However, the fluorescence detection used in most conventional DNA microarrays is still limited by sensitivity. In this study, we have demonstrated a novel universal and highly sensitive platform for fluorescent detection of sequence specific DNA at the femtomolar level by combining dextran-coated microarrays with hybridization chain reaction (HCR) signal amplification. Three-dimensional dextran matrix was covalently coated on glass surface as the scaffold to immobilize DNA recognition probes to increase the surface binding capacity and accessibility. DNA nanowire tentacles were formed on the matrix surface for efficient signal amplification by capturing multiple fluorescent molecules in a highly ordered way. By quantifying microscopic fluorescent signals, the synergetic effects of dextran and HCR greatly improved sensitivity of DNA microarrays, with a detection limit of 10fM (1×10(5) molecules). This detection assay could recognize one-base mismatch with fluorescence signals dropped down to ~20%. This cost-effective microarray platform also worked well with samples in serum and thus shows great potential for clinical diagnosis.

  2. A molecular beacon microarray based on a quantum dot label for detecting single nucleotide polymorphisms.

    PubMed

    Guo, Qingsheng; Bai, Zhixiong; Liu, Yuqian; Sun, Qingjiang

    2016-03-15

    In this work, we report the application of streptavidin-coated quantum dot (strAV-QD) in molecular beacon (MB) microarray assays by using the strAV-QD to label the immobilized MB, avoiding target labeling and meanwhile obviating the use of amplification. The MBs are stem-loop structured oligodeoxynucleotides, modified with a thiol and a biotin at two terminals of the stem. With the strAV-QD labeling an "opened" MB rather than a "closed" MB via streptavidin-biotin reaction, a sensitive and specific detection of label-free target DNA sequence is demonstrated by the MB microarray, with a signal-to-background ratio of 8. The immobilized MBs can be perfectly regenerated, allowing the reuse of the microarray. The MB microarray also is able to detect single nucleotide polymorphisms, exhibiting genotype-dependent fluorescence signals. It is demonstrated that the MB microarray can perform as a 4-to-2 encoder, compressing the genotype information into two outputs.

  3. Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

    PubMed

    Tra, Yolande V; Evans, Irene M

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

  4. Gene expression analysis of perennial ryegrass (Lolium perenne) using cDNA microarrays

    NASA Astrophysics Data System (ADS)

    Ong, Eng-Kok; Sawbridge, Tim; Webster, Tracie; Emmerling, Michael; Nguyen, Nga; Nunan, Katrina; O'Neill, Matthew; O'Toole, Fiona; Rhodes, Carolyn; Simmonds, Jason; Tian, Pei; Wearne, Katherine; Winkworth, Amanda; Spangenberg, German

    2003-07-01

    Perennial ryegrass (Lolium perenne) is a major forage grass of temperate pastures. A genomics program has been undertaken generating over 52,000 expressed sequence tags (ESTs). Cluster analysis of the ESTs identified approximately 14,600 ryegrass unigenes. In this report, we described the application of ryegrass unigene cDNAs to produce ryegrass 15K microarray. Fifteen microarray hybridisations were performed with labeled total RNA isolated from a variety of plant organs and developmental stages. In a proof of concept, gene expression profiling of ryegrass ESTs using the 15K unigene microarrays has been established using several known genes and two cluster analysis approaches (parallel coordinate planes plot and hierarchical clustering). The expression profile of the known genes (e.g. rubisco and invertase) corresponds well with published data. The microarray expression profile of a ryegrass putative root specific kinase gene was also verified with Northern blotting. This combination of DNA microarray hybridisations and cluster analysis can be applied as a tool for the identification of novel sequences of unknown function.

  5. Optimal Control of Shock Wave Turbulent Boundary Layer Interactions Using Micro-Array Actuation

    NASA Technical Reports Server (NTRS)

    Anderson, Bernhard H.; Tinapple, Jon; Surber, Lewis

    2006-01-01

    The intent of this study on micro-array flow control is to demonstrate the viability and economy of Response Surface Methodology (RSM) to determine optimal designs of micro-array actuation for controlling the shock wave turbulent boundary layer interactions within supersonic inlets and compare these concepts to conventional bleed performance. The term micro-array refers to micro-actuator arrays which have heights of 25 to 40 percent of the undisturbed supersonic boundary layer thickness. This study covers optimal control of shock wave turbulent boundary layer interactions using standard micro-vane, tapered micro-vane, and standard micro-ramp arrays at a free stream Mach number of 2.0. The effectiveness of the three micro-array devices was tested using a shock pressure rise induced by the 10 shock generator, which was sufficiently strong as to separate the turbulent supersonic boundary layer. The overall design purpose of the micro-arrays was to alter the properties of the supersonic boundary layer by introducing a cascade of counter-rotating micro-vortices in the near wall region. In this manner, the impact of the shock wave boundary layer (SWBL) interaction on the main flow field was minimized without boundary bleed.

  6. Probe-Level Analysis of Expression Microarrays Characterizes Isoform-Specific Degradation during Mouse Oocyte Maturation

    PubMed Central

    Salisbury, Jesse; Hutchison, Keith W.; Wigglesworth, Karen; Eppig, John J.; Graber, Joel H.

    2009-01-01

    Background Gene expression microarrays have provided many insights into changes in gene expression patterns between different tissue types, developmental stages, and disease states. Analyses of these data focused primarily measuring the relative abundance of transcripts of a gene, while treating most or all transcript isoforms as equivalent. Differences in the selection between transcript isoforms can, however, represent critical changes to either the protein product or the posttranscriptional regulation of the transcript. Novel analyses on existing microarray data provide fresh insights and new interpretations into transcriptome-wide changes in expression. Methodology A probe-level analysis of existing gene expression arrays revealed differences in mRNA processing, primarily affecting the 3′-untranslated region. Working with the example of microarrays drawn from a transcriptionally silent period of mouse oocyte development, probe-level analysis (implemented here as rmodel) identified genes whose transcript isoforms have differing stabilities. Comparison of micorarrays measuring cDNA generated from oligo-dT and random primers revealed further differences in the polyadenylation status of some transcripts. Additional analysis provided evidence for sequence-targeted cleavage, including putative targeting sequences, as one mechanism of degradation for several hundred transcripts in the maturing oocyte. Conclusions The capability of probe-level analysis to elicit novel findings from existing expression microarray data was demonstrated. The characterization of differences in stability between transcript isoforms in maturing mouse oocytes provided some mechanistic details of degradation. Similar analysis of existing archives of expression microarray data will likely provide similar discoveries. PMID:19834616

  7. 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.

  8. CrossNorm: a novel normalization strategy for microarray data in cancers

    PubMed Central

    Cheng, Lixin; Lo, Leung-Yau; Tang, Nelson L. S.; Wang, Dong; Leung, Kwong-Sak

    2016-01-01

    Normalization is essential to get rid of biases in microarray data for their accurate analysis. Existing normalization methods for microarray gene expression data commonly assume a similar global expression pattern among samples being studied. However, scenarios of global shifts in gene expressions are dominant in cancers, making the assumption invalid. To alleviate the problem, here we propose and develop a novel normalization strategy, Cross Normalization (CrossNorm), for microarray data with unbalanced transcript levels among samples. Conventional procedures, such as RMA and LOESS, arbitrarily flatten the difference between case and control groups leading to biased gene expression estimates. Noticeably, applying these methods under the strategy of CrossNorm, which makes use of the overall statistics of the original signals, the results showed significantly improved robustness and accuracy in estimating transcript level dynamics for a series of publicly available datasets, including titration experiment, simulated data, spike-in data and several real-life microarray datasets across various types of cancers. The results have important implications for the past and the future cancer studies based on microarray samples with non-negligible difference. Moreover, the strategy can also be applied to other sorts of high-throughput data as long as the experiments have global expression variations between conditions. PMID:26732145

  9. Universal protein binding microarrays for the comprehensive characterization of the DNA binding specificities of transcription factors

    PubMed Central

    Berger, Michael F.; Bulyk, Martha L.

    2010-01-01

    Protein binding microarray (PBM) technology provides a rapid, high-throughput means of characterizing the in vitro DNA binding specificities of transcription factors (TFs). Using high-density, custom-designed microarrays containing all 10-mer sequence variants, one can obtain comprehensive binding site measurements for any TF, regardless of its structural class or species of origin. Here, we present a protocol for the examination and analysis of TF binding specificities at high resolution using such ‘all 10-mer’ universal PBMs. This procedure involves double-stranding a commercially synthesized DNA oligonucleotide array, binding a TF directly to the double-stranded DNA microarray, and labeling the protein-bound microarray with a fluorophore-conjugated antibody. We describe how to computationally extract the relative binding preferences of the examined TF for all possible contiguous and gapped 8-mers over the full range of affinities, from highest affinity sites to nonspecific sites. Multiple proteins can be tested in parallel in separate chambers on a single microarray, enabling the processing of a dozen or more TFs in a single day. PMID:19265799

  10. Low-complexity PDE-based approach for automatic microarray image processing.

    PubMed

    Belean, Bogdan; Terebes, Romulus; Bot, Adrian

    2015-02-01

    Microarray image processing is known as a valuable tool for gene expression estimation, a crucial step in understanding biological processes within living organisms. Automation and reliability are open subjects in microarray image processing, where grid alignment and spot segmentation are essential processes that can influence the quality of gene expression information. The paper proposes a novel partial differential equation (PDE)-based approach for fully automatic grid alignment in case of microarray images. Our approach can handle image distortions and performs grid alignment using the vertical and horizontal luminance function profiles. These profiles are evolved using a hyperbolic shock filter PDE and then refined using the autocorrelation function. The results are compared with the ones delivered by state-of-the-art approaches for grid alignment in terms of accuracy and computational complexity. Using the same PDE formalism and curve fitting, automatic spot segmentation is achieved and visual results are presented. Considering microarray images with different spots layouts, reliable results in terms of accuracy and reduced computational complexity are achieved, compared with existing software platforms and state-of-the-art methods for microarray image processing.

  11. An oligonucleotide-based microarray for detection of plant RNA viruses.

    PubMed

    Nicolaisen, Mogens

    2011-04-01

    Currently, some of the methods used most widely for diagnosis and detection of plant viruses are ELISA, PCR, bioassays and electron microscopy. These methods only target one or a few species in each assay or they are time consuming and require expertise. Microarray-based approaches offer an alternative to these methods as microarrays with virus-specific probes could be capable of detecting an almost unlimited number of virus species in one assay. In the present study, the feasibility of this strategy was studied by constructing a microarray with 150 probes potentially capable of detecting 52 viruses from a broad range of genera. The array was printed in 16 subarrays to allow testing of several samples on each slide. Hybridizations with cDNA from plants infected with 52 different virus species showed that out of the 52 species tested, 49 were positive and identified correctly to species level. This array represents the largest published microarray for plant virus detection in terms of the number of targeted species and is thus an important milestone towards the construction of a generic microarray able to detect most, if not all, plant RNA viruses.

  12. 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.

  13. In Situ-Synthesized Novel Microarray Optimized for Mouse Stem Cell and Early Developmental Expression Profiling

    PubMed Central

    Carter, Mark G.; Hamatani, Toshio; Sharov, Alexei A.; Carmack, Condie E.; Qian, Yong; Aiba, Kazuhiro; Ko, Naomi T.; Dudekula, Dawood B.; Brzoska, Pius M.; Hwang, S. Stuart; Ko, Minoru S.H.

    2003-01-01

    Applications of microarray technologies to mouse embryology/genetics have been limited, due to the nonavailability of microarrays containing large numbers of embryonic genes and the gap between microgram quantities of RNA required by typical microarray methods and the miniscule amounts of tissue available to researchers. To overcome these problems, we have developed a microarray platform containing in situ-synthesized 60-mer oligonucleotide probes representing approximately 22,000 unique mouse transcripts, assembled primarily from sequences of stem cell and embryo cDNA libraries. We have optimized RNA labeling protocols and experimental designs to use as little as 2 ng total RNA reliably and reproducibly. At least 98% of the probes contained in the microarray correspond to clones in our publicly available collections, making cDNAs readily available for further experimentation on genes of interest. These characteristics, combined with the ability to profile very small samples, make this system a resource for stem cell and embryogenomics research. [Supplemental material is available online at www.genome.org and at the NIA Mouse cDNA Project Web site, http://lgsun.grc.nia.nih.gov/cDNA/cDNA.html.] PMID:12727912

  14. Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

    PubMed

    Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

    2015-01-01

    Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

  15. Multiplex RT-PCR and Automated Microarray for Detection of Eight Bovine Viruses.

    PubMed

    Lung, O; Furukawa-Stoffer, T; Burton Hughes, K; Pasick, J; King, D P; Hodko, D

    2016-11-23

    Microarrays can be a useful tool for pathogen detection as it allow for simultaneous interrogation of the presence of a large number of genetic sequences in a sample. However, conventional microarrays require extensive manual handling and multiple pieces of equipment for printing probes, hybridization, washing and signal detection. In this study, a reverse transcription (RT)-PCR with an accompanying novel automated microarray for simultaneous detection of eight viruses that affect cattle [vesicular stomatitis virus (VSV), bovine viral diarrhoea virus type 1 and type 2, bovine herpesvirus 1, bluetongue virus, malignant catarrhal fever virus, rinderpest virus (RPV) and parapox viruses] is described. The assay accurately identified a panel of 37 strains of the target viruses and identified a mixed infection. No non-specific reactions were observed with a panel of 23 non-target viruses associated with livestock. Vesicular stomatitis virus was detected as early as 2 days post-inoculation in oral swabs from experimentally infected animals. The limit of detection of the microarray assay was as low as 1 TCID50 /ml for RPV. The novel microarray platform automates the entire post-PCR steps of the assay and integrates electrophoretic-driven capture probe printing in a single user-friendly instrument that allows array layout and assay configuration to be user-customized on-site.

  16. ExpressYourself: a modular platform for processing and visualizing microarray data

    PubMed Central

    Luscombe, Nicholas M.; Royce, Thomas E.; Bertone, Paul; Echols, Nathaniel; Horak, Christine E.; Chang, Joseph T.; Snyder, Michael; Gerstein, Mark

    2003-01-01

    DNA microarrays are widely used in biological research; by analyzing differential hybridization on a single microarray slide, one can detect changes in mRNA expression levels, increases in DNA copy numbers and the location of transcription factor binding sites on a genomic scale. Having performed the experiments, the major challenge is to process large, noisy datasets in order to identify the specific array elements that are significantly differentially hybridized. This normally requires aggregating different, often incompatible programs into a multi-step pipeline. Here we present ExpressYourself, a fully integrated platform for processing microarray data. In completely automated fashion, it will correct the background array signal, normalize the Cy5 and Cy3 signals, score levels of differential hybridization, combine the results of replicate experiments, filter problematic regions of the array and assess the quality of individual and replicate experiments. ExpressYourself is designed with a highly modular architecture so various types of microarray analysis algorithms can readily be incorporated as they are developed; for example, the system currently implements several normalization methods, including those that simultaneously consider signal intensity and slide location. The processed data are presented using a web-based graphical interface to facilitate comparison with the original images of the array slides. In particular, Express Yourself is able to regenerate images of the original microarray after applying various steps of processing, which greatly facilities identification of position-specific artifacts. The program is freely available for use at http://bioinfo.mbb.yale.edu/expressyourself. PMID:12824348

  17. 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.

  18. MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.

    PubMed

    Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris

    2016-03-03

    cDNA microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images which often suffer from noise, artifacts, and uneven background. In this work, the MIGS-GPU (Microarray Image Gridding and Segmentation on GPU) software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the graphics processing unit (GPU) by means of the CUDA architecture in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a userfriendly interface that requires minimum input in order to run.

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

    PubMed

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

    2010-05-21

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

  20. Comprehensive Analysis of Prokaryotes in Environmental Water Using DNA Microarray Analysis and Whole Genome Amplification

    PubMed Central

    Akama, Takeshi; Kawashima, Akira; Tanigawa, Kazunari; Hayashi, Moyuru; Ishido, Yuko; Luo, Yuqian; Hata, Akihisa; Fujitani, Noboru; Ishii, Norihisa; Suzuki, Koichi

    2013-01-01

    The microflora in environmental water consists of a high density and diversity of bacterial species that form the foundation of the water ecosystem. Because the majority of these species cannot be cultured in vitro, a different approach is needed to identify prokaryotes in environmental water. A novel DNA microarray was developed as a simplified detection protocol. Multiple DNA probes were designed against each of the 97,927 sequences in the DNA Data Bank of Japan and mounted on a glass chip in duplicate. Evaluation of the microarray was performed using the DNA extracted from one liter of environmental water samples collected from seven sites in Japan. The extracted DNA was uniformly amplified using whole genome amplification (WGA), labeled with Cy3-conjugated 16S rRNA specific primers and hybridized to the microarray. The microarray successfully identified soil bacteria and environment-specific bacteria clusters. The DNA microarray described herein can be a useful tool in evaluating the diversity of prokaryotes and assessing environmental changes such as global warming. PMID:25437334

  1. Simultaneous discrimination between 15 fish pathogens by using 16S ribosomal DNA PCR and DNA microarrays.

    PubMed

    Warsen, Adelaide E; Krug, Melissa J; LaFrentz, Stacey; Stanek, Danielle R; Loge, Frank J; Call, Douglas R

    2004-07-01

    We developed a DNA microarray suitable for simultaneous detection and discrimination between multiple bacterial species based on 16S ribosomal DNA (rDNA) polymorphisms using glass slides. Microarray probes (22- to 31-mer oligonucleotides) were spotted onto Teflon-masked, epoxy-silane-derivatized glass slides using a robotic arrayer. PCR products (ca. 199 bp) were generated using biotinylated, universal primer sequences, and these products were hybridized overnight (55 degrees C) to the microarray. Targets that annealed to microarray probes were detected using a combination of Tyramide Signal Amplification and Alexa Fluor 546. This methodology permitted 100% specificity for detection of 18 microbes, 15 of which were fish pathogens. With universal 16S rDNA PCR (limited to 28 cycles), detection sensitivity for purified control DNA was equivalent to <150 genomes (675 fg), and this sensitivity was not adversely impacted either by the presence of competing bacterial DNA (1.1 x 10(6) genomes; 5 ng) or by the addition of up to 500 ng of fish DNA. Consequently, coupling 16S rDNA PCR with a microarray detector appears suitable for diagnostic detection and surveillance for commercially important fish pathogens.

  2. Generation of a non-small cell lung cancer transcriptome microarray

    PubMed Central

    Tanney, Austin; Oliver, Gavin R; Farztdinov, Vadim; Kennedy, Richard D; Mulligan, Jude M; Fulton, Ciaran E; Farragher, Susan M; Field, John K; Johnston, Patrick G; Harkin, D Paul; Proutski, Vitali; Mulligan, Karl A

    2008-01-01

    Background Non-small cell lung cancer (NSCLC) is the leading cause of cancer mortality worldwide. At present no reliable biomarkers are available to guide the management of this condition. Microarray technology may allow appropriate biomarkers to be identified but present platforms are lacking disease focus and are thus likely to miss potentially vital information contained in patient tissue samples. Methods A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterise the transcriptome of NSCLC and the data used to generate a disease-focused microarray – the Lung Cancer DSA research tool. Results Built on the Affymetrix GeneChip platform, the Lung Cancer DSA research tool allows for interrogation of ~60,000 transcripts relevant to Lung Cancer, tens of thousands of which are unavailable on leading commercial microarrays. Conclusion We have developed the first high-density disease specific transcriptome microarray. We present the array design process and the results of experiments carried out to demonstrate the array's utility. This approach serves as a template for the development of other disease transcriptome microarrays, including non-neoplastic diseases. PMID:18513400

  3. Peptide microarrays for the profiling of cytotoxic T-lymphocyte activity using minimum numbers of cells.

    PubMed

    Hoff, Antje; Bagû, Ana-Cristina; André, Thomas; Roth, Günter; Wiesmüller, Karl-Heinz; Gückel, Brigitte; Brock, Roland

    2010-09-01

    The identification of epitopes that elicit cytotoxic T-lymphocyte activity is a prerequisite for the development of cancer-specific immunotherapies. However, especially the parallel characterization of several epitopes is limited by the availability of T cells. Microarrays have enabled an unprecedented miniaturization and parallelization in biological assays. Here, we developed peptide microarrays for the detection of CTL activity. MHC class I-binding peptide epitopes were pipetted onto polymer-coated glass slides. Target cells, loaded with the cell-impermeant dye calcein, were incubated on these arrays, followed by incubation with antigen-expanded CTLs. Cytotoxic activity was detected by release of calcein and detachment of target cells. With only 200,000 cells per microarray, CTLs could be detected at a frequency of 0.5% corresponding to 1,000 antigen-specific T cells. Target cells and CTLs only settled on peptide spots enabling a clear separation of individual epitopes. Even though no physical boundaries were present between the individual spots, peptide loading only occurred locally and cytolytic activity was confined to the spots carrying the specific epitope. The peptide microarrays provide a robust platform that implements the whole process from antigen presentation to the detection of CTL activity in a miniaturized format. The method surpasses all established methods in the minimum numbers of cells required. With antigen uptake occurring on the microarray, further applications are foreseen in the testing of antigen precursors that require uptake and processing prior to presentation.

  4. Signal enhancement in antibody microarrays using quantum dots nanocrystals: application to potential Alzheimer's disease biomarker screening.

    PubMed

    Morales-Narváez, Eden; Montón, Helena; Fomicheva, Anna; Merkoçi, Arben

    2012-08-07

    The performance of cadmium-selenide/zinc-sulfide (CdSe@ZnS) quantum dots (QDs) and the fluorescent dye Alexa 647 as reporter in an assay designed to detect apolipoprotein E (ApoE) has been compared. The assay is a sandwich immunocomplex microarray that functions via excitation by visible light. ApoE was chosen for its potential as a biomarker for Alzheimer's disease. The two versions of the microarray (QD or Alexa 647) were assessed under the same experimental conditions and then compared to a conventional enzyme-linked immunosorbent assay (ELISA) targeting ApoE. The QDs proved to be highly effective reporters in the microarrays, although their performance strongly varied in function of the excitation wavelength. At 633 nm, the QD microarray gave a limit of detection (LOD) of ~247 pg mL(-1); however, at an excitation wavelength of 532 nm, it provided a LOD of ~62 pg mL(-1), five times more sensitive than that of the Alexa microarray (~307 pg mL(-1)) and seven times more than that of the ELISA (~470 pg mL(-1)). Finally, serial dilutions from a human serum sample were assayed with high sensitivity and acceptable precision and accuracy.

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

    PubMed Central

    Evans, Irene M.

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

  6. Profiling of differentially expressed genes in human gingival epithelial cells and fibroblasts by DNA microarray.

    PubMed

    Abiko, Yoshimitsu; Hiratsuka, Koichi; Kiyama-Kishikawa, Michiko; Tsushima, Katsumasa; Ohta, Mitsuhiro; Sasahara, Hiroshige

    2004-03-01

    Gingival epithelial cells and fibroblasts play important roles and have a harmonious relationship under normal and disease conditions, but the precise differences between theses cells remain unknown. To study the differences in gene expression between human gingival epithelial cells (HGE) and human gingival fibroblasts (HGF), mRNA was recovered from primary cultured cells and analyzed using cDNA microarray technology. The cDNA retro-transcribed from equal quantities of mRNA was labeled with the fluorescent dyes Cy5 and Cy3. The mixed probes were then hybridized with 7276 genes on the DNA microarray, after which fluorescence signals were scanned and further analyzed using GeneSpring software. Of the 7276 genes screened, 469 showed expression levels that were more than 2-fold greater in HGE than in HGF, while 293 showed expression levels that were more than 2-fold greater in HGF than in HGE. To confirm the reliability of the microarray results, keratin K5 and desmocolin, and vimentin and gp130, which showed higher mRNA levels in HGE and HGF, respectively, were selected and their mRNA levels were further analyzed by RT-PCR. The results of RT-PCR correlated well with those of microarray analysis. The present findings using a DNA microarray to detect differences in the gene expression profiles of HGE and HGF may be beneficial for genetic diagnosis of periodontal tissue metabolism and periodontal diseases.

  7. 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

  8. Improved microarray-based decision support with graph encoded interactome data.

    PubMed

    Daemen, Anneleen; Signoretto, Marco; Gevaert, Olivier; Suykens, Johan A K; De Moor, Bart

    2010-04-19

    In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG), protein-protein interactions (OPHID) and miRNA-gene targeting (microRNA.org) outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method.

  9. The role of DNA microarrays in the evaluation of fetal death.

    PubMed

    Reddy, Uma M; Page, Grier P; Saade, George R

    2012-04-01

    Fetal death occurs in 15% of clinically recognized pregnancies. Cytogenetic abnormalities are present in 50% of spontaneous abortions (fetal deaths < 20 weeks) whereas the rate is 6% to 13% for stillbirths (fetal deaths ≥ 20 weeks). Microarray has been demonstrated to increase the diagnosis of genetic abnormalities by providing coverage of the entire genome at a higher density, detecting as small as 50 to 100 kb deletions or duplications, known as copy number changes. Microarray is particularly suited for evaluation of fetal death because DNA can still be analyzed in macerated fetuses and nonviable tissue, two situations where culturing and karyotyping is known to have low yield. Microarray has already proven successful in providing additional genetic information beyond karyotype in spontaneous abortion. The few studies on the use of microarray in stillbirth evaluation have been promising, demonstrating an increase in the diagnosis of clinically relevant genetic abnormalities when compared with karyotype. As the cost and technology improve, microarray may ultimately become the first line screen for genetic abnormalities in stillbirth. The accurate diagnosis of a genetic abnormality as the cause for fetal death may provide closure for families, prevent unnecessary treatments, and enable clinicians to more accurately counsel and manage subsequent pregnancies.

  10. 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

  11. The use of lectin microarray for assessing glycosylation of therapeutic proteins

    PubMed Central

    Zhang, Lei; Luo, Shen; Zhang, Baolin

    2016-01-01

    ABSTRACT Glycans or carbohydrates attached to therapeutic glycoproteins can directly affect product quality, safety and efficacy, and therefore must be adequately analyzed and controlled throughout product life cycles. However, the complexity of protein glycosylation poses a daunting analytical challenge. In this study, we evaluated the utility of a lectin microarray for assessing protein glycans. Using commercial lectin chips, which contain 45 lectins toward distinct glycan structures, we were able to determine the lectin binding patterns of a panel of 15 therapeutic proteins, including 8 monoclonal antibodies. Lectin binding signals were analyzed to generate glycan profiles that were generally consistent with the known glycan patterns for these glycoproteins. In particular, the lectin-based microarray was found to be highly sensitive to variations in the terminal carbohydrate structures such as galactose versus sialic acid epitopes. These data suggest that lectin microarray could be used for screening glycan patterns of therapeutic glycoproteins. PMID:26918373

  12. 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.

  13. Multiplex giant magnetoresistive biosensor microarrays identify interferon-associated autoantibodies in systemic lupus erythematosus

    NASA Astrophysics Data System (ADS)

    Lee, Jung-Rok; Haddon, D. James; Wand, Hannah E.; Price, Jordan V.; Diep, Vivian K.; Hall, Drew A.; Petri, Michelle; Baechler, Emily C.; Balboni, Imelda M.; Utz, Paul J.; Wang, Shan X.

    2016-06-01

    High titer, class-switched autoantibodies are a hallmark of systemic lupus erythematosus (SLE). Dysregulation of the interferon (IFN) pathway is observed in individuals with active SLE, although the association of specific autoantibodies with chemokine score, a combined measurement of three IFN-regulated chemokines, is not known. To identify autoantibodies associated with chemokine score, we developed giant magnetoresistive (GMR) biosensor microarrays, which allow the parallel measurement of multiple serum antibodies to autoantigens and peptides. We used the microarrays to analyze serum samples from SLE patients and found individuals with high chemokine scores had significantly greater reactivity to 13 autoantigens than individuals with low chemokine scores. Our findings demonstrate that multiple autoantibodies, including antibodies to U1-70K and modified histone H2B tails, are associated with IFN dysregulation in SLE. Further, they show the microarrays are capable of identifying autoantibodies associated with relevant clinical manifestations of SLE, with potential for use as biomarkers in clinical practice.

  14. Construction of citrus gene coexpression networks from microarray data using random matrix theory.

    PubMed

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.

  15. Pattern recognition of genomic features with microarrays: site typing of Mycobacterium tuberculosis strains

    PubMed Central

    Raychaudhuri, Soumya; Stuart, Joshua M.; Liu, Xuemin; Small, Peter M.; Altman, Russ B.

    2009-01-01

    Mycobacterium tuberculosis (M. tb.) strains differ in the number and locations of a transposon-like insertion sequence known as IS6110. Accurate detection of this sequence can be used as a fingerprint for individual strains, but can be difficult because of noisy data. In this paper, we propose a non-parametric discriminant analysis method for predicting the locations of the IS6110 sequence from microarray data. Polymerase chain reaction extension products generated from primers specific for the insertion sequence are hybridized to a microarray containing targets corresponding to each open reading frame in M. tb. To test for insertion sites, we use microarray intensity values extracted from small windows of contiguous open reading frames. Rank-transformation of spot intensities and first-order differences in local windows provide enough information to reliably determine the presence of an insertion sequence. The non-parametric approach outperforms all other methods tested in this study. PMID:10977090

  16. Applications of nanotechnology, next generation sequencing and microarrays in biomedical research.

    PubMed

    Elingaramil, Sauli; Li, Xiaolong; He, Nongyue

    2013-07-01

    Next-generation sequencing technologies, microarrays and advances in bio nanotechnology have had an enormous impact on research within a short time frame. This impact appears certain to increase further as many biomedical institutions are now acquiring these prevailing new technologies. Beyond conventional sampling of genome content, wide-ranging applications are rapidly evolving for next-generation sequencing, microarrays and nanotechnology. To date, these technologies have been applied in a variety of contexts, including whole-genome sequencing, targeted re sequencing and discovery of transcription factor binding sites, noncoding RNA expression profiling and molecular diagnostics. This paper thus discusses current applications of nanotechnology, next-generation sequencing technologies and microarrays in biomedical research and highlights the transforming potential these technologies offer.

  17. Continuous scaling 3d micro flow printing for improved spot morphology in protein microarrays - biomed 2013.

    PubMed

    Romanov, Valentin; Gale, Bruce; Eckman, Josh; Miles, Adam; Brooks, Benjamin

    2013-01-01

    The protein microarray platform while innovative still poses a number of challenges which can only be met through creative and sophisticated system design. Pin printing while allowing for flexibility as to the type of medium printed does not offer the kind of spot reproducibility that a very sensitive application may require. The Continuous Flow Microspotter (CFM) was designed to not only allow for flexibility and reproducibility but to also achieve solution stability through flow scaling. This study uses the emerging CFM for printing protein and antibodies three dimensionally for general protein microarray applications. Consistent spot morphology, a continual and persistent problem in traditional pin printed microarrays, was compared under variable printed flow rates. The final assessment was performed using a rudimentary shear model. Force effects discussion and statistical data was used to demonstrate the versatility of the system.

  18. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    PubMed Central

    Walsh, Christopher J.; Hu, Pingzhao; Batt, Jane; Dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers. PMID:27600230

  19. Protein-Protein Interaction Inhibitors of BRCA1 Discovered Using Small Molecule Microarrays.

    PubMed

    Na, Zhenkun; Pan, Sijun; Uttamchandani, Mahesh; Yao, Shao Q

    2017-01-01

    Microarray screening technology has transformed the life sciences arena over the last decade. The platform is widely used in the area of mapping interaction networks, to molecular fingerprinting and small molecular inhibitor discovery. The technique has significantly impacted both basic and applied research. The microarray platform can likewise enable high-throughput screening and discovery of protein-protein interaction (PPI) inhibitors. Herein we demonstrate the application of microarray-guided PPI inhibitor discovery, using human BRCA1 as an example. Mutations in BRCA1 have been implicated in ~50 % of hereditary breast cancers. By targeting the (BRCT)2 domain, we showed compound 15a and its prodrug 15b inhibited BRCA1 activities in tumor cells. Unlike previously reported peptide-based PPI inhibitors of BRCA1, the compounds identified could be directly administered to tumor cells, thus making them useful in targeting BRCA1/PARP-related pathways involved in DNA damage and repair response, for cancer therapy.

  20. 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

    2014-04-25

    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.

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

    PubMed

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

    2015-01-01

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

  2. ADIBO-based "click" chemistry for diagnostic peptide micro-array fabrication: physicochemical and assay characteristics.

    PubMed

    Prim, Denis; Rebeaud, Fabien; Cosandey, Vincent; Marti, Roger; Passeraub, Philippe; Pfeifer, Marc E

    2013-08-16

    Several azide-derivatized and fluorescently-labeled peptides were immobilized on azadibenzocyclooctyne (ADIBO)-activated slide surfaces via a strain-promoted alkyne-azide cycloaddition (SPAAC) reaction revealing excellent immobilization kinetics, good spot homogeneities and reproducible fluorescence signal intensities. A myc-peptide micro-array immunoassay showed an antibody limit-of-detection (LOD) superior to a microtiter plate-based ELISA. Bovine serum albumin (BSA) and dextran covalently attached via "click" chemistry more efficiently reduced non-specific binding (NSB) of fluorescently-labeled IgG to the microarray surface in comparison to immobilized hexanoic acid and various types of polyethylene glycol (PEG) derivatives. Confirmation of these findings via further studies with other proteins and serum components could open up new possibilities for human sample and microarray platform-based molecular diagnostic tests.

  3. A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data

    PubMed Central

    Hira, Zena M.; Gillies, Duncan F.

    2015-01-01

    We summarise various ways of performing dimensionality reduction on high-dimensional microarray data. Many different feature selection and feature extraction methods exist and they are being widely used. All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. A popular source of data is microarrays, a biological platform for gathering gene expressions. Analysing microarrays can be difficult due to the size of the data they provide. In addition the complicated relations among the different genes make analysis more difficult and removing excess features can improve the quality of the results. We present some of the most popular methods for selecting significant features and provide a comparison between them. Their advantages and disadvantages are outlined in order to provide a clearer idea of when to use each one of them for saving computational time and resources. PMID:26170834

  4. SNP microarray abnormalities in a cohort of 28 infants with congenital diaphragmatic hernia.

    PubMed

    Stark, Zornitza; Behrsin, Joanna; Burgess, Trent; Ritchie, Anna; Yeung, Alison; Tan, Tiong Y; Brown, Natasha J; Savarirayan, Ravi; Patel, Neil

    2015-10-01

    Chromosomal abnormalities are an important factor in the pathogenesis of congenital diaphragmatic hernia (CDH), a relatively common congenital defect associated with high morbidity and mortality. The adoption of array-based platforms for chromosome analysis has resulted in the identification of numerous copy number variants (CNVs) in infants with CDH, highlighting the potential pathogenic role of many novel genes. We identified a retrospective cohort of 28 infants treated for CDH at a single institution who had microarray testing to determine the proportion of microarray abnormalities and whether these were contributory to CDH pathogenesis. Eight patients (29%) had microarray abnormality. Seven (25%) were considered likely contributory to CDH pathogenesis, including two mosaic trisomy 9s, a 9q22.31q22.32 microduplication, two atypical 22q11.21 microdeletions, a 2q35q36.1 microdeletion, and a 15q11.2 microdeletion, offering insights into the genetic mechanisms underlying CDH development.

  5. Multiplex giant magnetoresistive biosensor microarrays identify interferon-associated autoantibodies in systemic lupus erythematosus

    PubMed Central

    Lee, Jung-Rok; Haddon, D. James; Wand, Hannah E.; Price, Jordan V.; Diep, Vivian K.; Hall, Drew A.; Petri, Michelle; Baechler, Emily C.; Balboni, Imelda M.; Utz, Paul J.; Wang, Shan X.

    2016-01-01

    High titer, class-switched autoantibodies are a hallmark of systemic lupus erythematosus (SLE). Dysregulation of the interferon (IFN) pathway is observed in individuals with active SLE, although the association of specific autoantibodies with chemokine score, a combined measurement of three IFN-regulated chemokines, is not known. To identify autoantibodies associated with chemokine score, we developed giant magnetoresistive (GMR) biosensor microarrays, which allow the parallel measurement of multiple serum antibodies to autoantigens and peptides. We used the microarrays to analyze serum samples from SLE patients and found individuals with high chemokine scores had significantly greater reactivity to 13 autoantigens than individuals with low chemokine scores. Our findings demonstrate that multiple autoantibodies, including antibodies to U1-70K and modified histone H2B tails, are associated with IFN dysregulation in SLE. Further, they show the microarrays are capable of identifying autoantibodies associated with relevant clinical manifestations of SLE, with potential for use as biomarkers in clinical practice. PMID:27279139

  6. Construction of citrus gene coexpression networks from microarray data using random matrix theory

    PubMed Central

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G.

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus. PMID:26504573

  7. Microarray analysis for a comprehensive immunological-status evaluation during cancer vaccine immune monitoring.

    PubMed

    Monsurrò, Vladia; Marincola, Francesco M

    2011-01-01

    Anticancer immune responses can be enhanced by immune intervention that promotes complex biological mechanisms involving several cellular populations. The classical immune monitoring for biological-based cancer clinical trials is often based on single-cell analysis. However, the overall effect could be lost by such a reductionist approach explaining the lack of correlation among clinical and immunological endpoints often reported. Microarray technology could give the possibility of studying in a multiparametric setting the immune therapy effects. The application of microarray is leading to an improved understanding of the immune responses to tumor immunotherapy. In fact, analysis of cancer vaccine-induced host responses using microarrays is proposed as valuable alternative to the standard cell-based methods. This paper shows successful examples of how high-throughput gene expression profiling contributed to the understanding of anticancer immune responses during biological therapy, introducing as well the integrative platforms that allow the network analysis in molecular biology studies.

  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. On-chip synthesis of RNA aptamer microarrays for multiplexed protein biosensing with SPR imaging measurements.

    PubMed

    Chen, Yulin; Nakamoto, Kohei; Niwa, Osamu; Corn, Robert M

    2012-06-05

    Microarrays of RNA aptamers are fabricated in a one-step, multiplexed enzymatic synthesis on gold thin films in a microfluidic format and then employed in the detection of protein biomarkers with surface plasmon resonance imaging (SPRI) measurements. Single-stranded RNA (ssRNA) oligonucleotides are transcribed on-chip from double-stranded DNA (dsDNA) templates attached to microarray elements (denoted as generator elements) by the surface transcription reaction of T7 RNA polymerase. As they are synthesized, the ssRNA oligonucleotides diffuse in the microfluidic channel and are quickly captured by hybridization adsorption onto adjacent single-stranded DNA (ssDNA) microarray elements (denoted as detector elements) that contain a sequence complementary to 5'-end of the ssRNA. The RNA aptamers attached to these detector elements are subsequently used in SPRI measurements for the bioaffinity detection of protein biomarkers. The microfluidic generator-detector element format permits the simultaneous fabrication of multiple ssRNA oligonucleotides with different capture sequences that can hybridize simultaneously to distinct detector elements and thus create a multiplexed aptamer microarray. In an initial set of demonstration experiments, SPRI measurements are used to monitor the bioaffinity adsorption of human thrombin (hTh) and vascular endothelial growth factor (VEGF) proteins onto RNA aptamer microarrays fabricated in situ with this on-chip RNA polymerase synthesis methodology. Additional SPRI measurements of the hydrolysis and desorption of the surface-bound ssRNA aptamers with a surface RNase H are used to verify the capture of ssRNA with RNA-DNA surface hybridization onto the detector elements. The on-chip RNA synthesis described here is an elegant, one-step multiplexed methodology for the rapid and contamination-free fabrication of RNA aptamer microarrays for protein biosensing with SPRI.

  10. 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.

  11. Oligonucleotide Microarray for the Study of Functional Gene Diversity in the Nitrogen Cycle in the Environment

    PubMed Central

    Taroncher-Oldenburg, Gaspar; Griner, Erin M.; Francis, Chris A.; Ward, Bess B.

    2003-01-01

    The analysis of functional diversity and its dynamics in the environment is essential for understanding the microbial ecology and biogeochemistry of aquatic systems. Here we describe the development and optimization of a DNA microarray method for the detection and quantification of functional genes in the environment and report on their preliminary application to the study of the denitrification gene nirS in the Choptank River-Chesapeake Bay system. Intergenic and intragenic resolution constraints were determined by an oligonucleotide (70-mer) microarray approach. Complete signal separation was achieved when comparing unrelated genes within the nitrogen cycle (amoA, nifH, nirK, and nirS) and detecting different variants of the same gene, nirK, corresponding to organisms with two different physiological modes, ammonia oxidizers and denitrifying halobenzoate degraders. The limits of intragenic resolution were investigated with a microarray containing 64 nirS sequences comprising 14 cultured organisms and 50 clones obtained from the Choptank River in Maryland. The nirS oligonucleotides covered a range of sequence identities from approximately 40 to 100%. The threshold values for specificity were determined to be 87% sequence identity and a target-to-probe perfect match-to-mismatch binding free-energy ratio of 0.56. The lower detection limit was 10 pg of DNA (equivalent to approximately 107 copies) per target per microarray. Hybridization patterns on the microarray differed between sediment samples from two stations in the Choptank River, implying important differences in the composition of the denitirifer community along an environmental gradient of salinity, inorganic nitrogen, and dissolved organic carbon. This work establishes a useful set of design constraints (independent of the target gene) for the implementation of functional gene microarrays for environmental applications. PMID:12571043

  12. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates.

    PubMed

    Boopathi, Pon Arunachalam; Subudhi, Amit Kumar; Middha, Sheetal; Acharya, Jyoti; Mugasimangalam, Raja Chinnadurai; Kochar, Sanjay Kumar; Kochar, Dhanpat Kumar; Das, Ashis

    2016-12-01

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n=14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n=85) present in the arrays showed perfect correlation (r(2)=0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r≥0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates.

  13. 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

  14. Efficient monitoring of protein ubiquitylation levels using TUBEs-based microarrays.

    PubMed

    Serna, Sonia; Xolalpa, Wendy; Lang, Valérie; Aillet, Fabienne; England, Patrick; Reichardt, Niels; Rodriguez, Manuel S

    2016-08-01

    Analyzing protein ubiquitylation changes during physiological or pathological processes is challenging due to its high reversibility and dynamic turnover of modified targets. We have developed a protein microarray to assess endogenous ubiquitylation levels from cell cultures, employing tandem ubiquitin-binding entities (TUBEs) with three or four ubiquitin-associated (UBA) domains as capture probes. Adriamycin (ADR)-stimulated MCF7 cells were used to differentiate protein ubiquitylation levels between cells that are sensitive or resistant to ADR treatment. We show that TUBEs-based microarrays can be used for the analysis of cellular processes regulated by ubiquitylation and for the detection of pathologies with aberrant ubiquitylation levels.

  15. High-throughput cellular microarray platforms: applications in drug discovery, toxicology and stem cell research

    PubMed Central

    Fernandes, Tiago G.; Diogo, Maria Margarida; Clark, Douglas S.; Dordick, Jonathan S.; Cabral, Joaquim M.S.

    2017-01-01

    Cellular microarrays are powerful experimental tools for high-throughput screening of large numbers of test samples. Miniaturization increases assay throughput while reducing reagent consumption and the number of cells required, making these systems attractive for a wide range of assays in drug discovery, toxicology, stem cell research and potentially therapy. Here, we provide an overview of the emerging technologies that can be used to generate cellular microarrays, and we highlight recent significant advances in the field. This emerging and multidisciplinary approach offers new opportunities for the design and control of stem cells in tissue engineering and cellular therapies and promises to expedite drug discovery in the biotechnology and pharmaceutical industries. PMID:19398140

  16. Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization

    PubMed Central

    2010-01-01

    Background In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points. Results Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control. Conclusion Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene

  17. CGO: utilizing and integrating gene expression microarray data in clinical research and data management.

    PubMed

    Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D

    2002-02-01

    Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.

  18. Construction of a peptide microarray for auto-anti- body detection.

    PubMed

    Cosandey, Vincent; Debrot, Fabien; Kaeser, Jérémy; Marti, Roger; Passeraub, Philippe; Pétremand, Jannick; Prim, Denis; Pfeifer, Marc E

    2012-01-01

    Peptide and protein microarrays provide a multiplex approach to identification and quantification of protein-protein interactions (PPI), useful to study for instance antigen-antibody properties. Multivariate serology assays detecting multiple tumor auto-antibodies (TAA) is an emerging class of blood tests for cancer detection. Here we describe the efficient coupling of peptide baits derived from the BRCA1-associated RING domain protein 1 (BARD1) to a solid surface and detection of a commercially available anti-BARD1 antibody with this newly designed peptide microarray. Analytical sensitivity and specificity were shown to be comparable to a microtiter plate based enzyme-linked immunosorbent assay (ELISA).

  19. Fluorescent glycosylamides produced by microscale derivatization of free glycans for natural glycan microarrays.

    PubMed

    Song, Xuezheng; Lasanajak, Yi; Xia, Baoyun; Smith, David F; Cummings, Richard D

    2009-09-18

    A novel strategy for creating naturally derived glycan microarrays has been developed. Glycosylamines are prepared from free reducing glycans and stabilized by reaction with acryloyl chloride to generate a glycosylamide in which the reducing monosaccharide has a closed-ring structure. Ozonolysis of the protected glycan yields an active aldehyde, to which a bifunctional fluorescent linker is coupled by reductive amination. The fluorescent derivatives are easily coupled through a residual primary alkylamine to generate glycan microarrays. This strategy preserves structural features of glycans required for antibody recognition and allows development of natural arrays of fluorescent glycans in which the cyclic pyranose structure of the reducing-end sugar residue is retained.

  20. Fluorescent Glycosylamides Produced by Microscale Derivatization of Free Glycans for Natural Glycan Microarrays

    PubMed Central

    Song, Xuezheng; Lasanajak, Yi; Xia, Baoyun; Smith, David F.; Cummings, Richard D.

    2009-01-01

    A novel strategy for creating naturally-derived glycan microarrays has been developed. Glycosylamines are prepared from free reducing glycans and stabilized by reaction with acryloyl chloride to generate a glycosylamide in which the reducing monosaccharide has a closed ring structure. Ozonolysis of the protected glycan yields an active aldehyde, to which a bifunctional fluorescent linker is coupled by reductive amination. The fluorescent derivatives are easily coupled through a residual primary alkylamine to generate glycan microarrays. This strategy preserves structural features of glycans required for antibody recognition, and allows development of natural arrays of fluorescent glycans in which the cyclic pyranose structure of the reducing-end sugar residue is retained. PMID:19618966