Science.gov

Sample records for a-madman annotation-based microarray

  1. Transculturation of Madness: The Double Origin of Lu Xun's "Diary of a Madman".

    PubMed

    Ma, Xiaolu

    2015-01-01

    Over the years scholars have examined the allegorical features of the depiction of madness in Lu Xun's "Diary of a Madman," yet to date little research has taken into consideration the intercultural angle embedded in the narrative's intersection of three cultures, namely Russian, Japanese and Chinese. This paper traces the European-Japanese-Sino route of modern neologisms of madness to explore the introduction of such neologisms into the modern Chinese language and how it corresponds with changing patterns of knowledge and power. I use my study of transculturation on the macro scale to frame a reexamination of the lexicon in "Diary of a Madman." I focus especially on kuangren and pohaikuang, the two key words employed by Lu Xun, to see how they contribute to the ambiguity in his attitude towards the power struggle between the East and the West, the old and the new.

  2. 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…

  3. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

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

  4. SNAD: Sequence Name Annotation-based Designer.

    PubMed

    Sidorov, Igor A; Reshetov, Denis A; Gorbalenya, Alexander E

    2009-08-14

    A growing diversity of biological data is tagged with unique identifiers (UIDs) associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Here we introduce SNAD (Sequence Name Annotation-based Designer) that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list) into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. DNA Microarray Technology

    SciTech Connect

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

    Collaboration between Sandia National Laboratories and the University of New Mexico Biology Department resulted in the capability to train students in microarray techniques and the interpretation of data from microarray experiments. These studies provide for a better understanding of the role of stationary phase and the gene regulation involved in exit from stationary phase, which may eventually have important clinical implications. Importantly, this research trained numerous students and is the basis for three new Ph.D. projects.

  10. Functional GPCR microarrays.

    PubMed

    Hong, Yulong; Webb, Brian L; Su, Hui; Mozdy, Eric J; Fang, Ye; Wu, Qi; Liu, Li; Beck, Jonathan; Ferrie, Ann M; Raghavan, Srikanth; Mauro, John; Carre, Alain; Müeller, Dirk; Lai, Fang; Rasnow, Brian; Johnson, Michael; Min, Hosung; Salon, John; Lahiri, Joydeep

    2005-11-09

    This paper describes G-protein-coupled receptor (GPCR) microarrays on porous glass substrates and functional assays based on the binding of a europium-labeled GTP analogue. The porous glass slides were made by casting a glass frit on impermeable glass slides and then coating with gamma-aminopropyl silane (GAPS). The emitted fluorescence was captured on an imager with a time-gated intensified CCD detector. Microarrays of the neurotensin receptor 1, the cholinergic receptor muscarinic 2, the opioid receptor mu, and the cannabinoid receptor 1 were fabricated by pin printing. The selective agonism of each of the receptors was observed. The screening of potential antagonists was demonstrated using a cocktail of agonists. The amount of activation observed was sufficient to permit determinations of EC50 and IC50. Such microarrays could potentially streamline drug discovery by helping integrate primary screening with selectivity and safety screening without compromising the essential functional information obtainable from cellular assays.

  11. Nanotechnologies in protein microarrays.

    PubMed

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

    2015-01-01

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

  12. 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.

  13. 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…

  14. 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

  15. 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…

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

    USDA-ARS?s Scientific Manuscript database

    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...

  17. Biolog phenotype microarrays.

    PubMed

    Shea, April; Wolcott, Mark; Daefler, Simon; Rozak, David A

    2012-01-01

    Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

  18. 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.

  19. 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.

  20. 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.

  1. Ecotoxicogenomics: Microarray interlaboratory comparability.

    PubMed

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

    2016-02-01

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

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Reverse Phase Protein Microarrays.

    PubMed

    Baldelli, Elisa; Calvert, Valerie; Hodge, Alex; VanMeter, Amy; Petricoin, Emanuel F; Pierobon, Mariaelena

    2017-01-01

    While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive all cellular functions including proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool for understanding cellular functions.Alteration of the cellular homeostasis driven by elaborate intra- and extracellular interactions has become one of the most studied fields in the era of personalized medicine and targeted therapy. Increasing interest has been focused on developing and improving proteomic technologies that are suitable for analysis of clinical samples. In this context, reverse-phase protein microarrays (RPPA) is a sensitive, quantitative, high-throughput immunoassay for protein analyses of tissue samples, cells, and body fluids.RPPA is well suited for broad proteomic profiling and is capable of capturing protein activation as well as biochemical reactions such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations across hundreds of samples using a limited amount of biological material. For these reasons, RPPA represents a valid tool for protein analyses and generates data that help elucidate the functional signaling architecture through protein-protein interaction and protein activation mapping for the identification of critical nodes for individualized or combinatorial targeted therapy.

  8. 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

  9. 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.

  10. 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.

  11. DNA microarray integromics analysis platform.

    PubMed

    Waller, Tomasz; Gubała, Tomasz; Sarapata, Krzysztof; Piwowar, Monika; Jurkowski, Wiktor

    2015-01-01

    The study of interactions between molecules belonging to different biochemical families (such as lipids and nucleic acids) requires specialized data analysis methods. This article describes the DNA Microarray Integromics Analysis Platform, a unique web application that focuses on computational integration and analysis of "multi-omics" data. Our tool supports a range of complex analyses, including - among others - low- and high-level analyses of DNA microarray data, integrated analysis of transcriptomics and lipidomics data and the ability to infer miRNA-mRNA interactions. We demonstrate the characteristics and benefits of the DNA Microarray Integromics Analysis Platform using two different test cases. The first test case involves the analysis of the nutrimouse dataset, which contains measurements of the expression of genes involved in nutritional problems and the concentrations of hepatic fatty acids. The second test case involves the analysis of miRNA-mRNA interactions in polysaccharide-stimulated human dermal fibroblasts infected with porcine endogenous retroviruses. The DNA Microarray Integromics Analysis Platform is a web-based graphical user interface for "multi-omics" data management and analysis. Its intuitive nature and wide range of available workflows make it an effective tool for molecular biology research. The platform is hosted at https://lifescience.plgrid.pl/.

  12. Microfluidic microarray systems and methods thereof

    DOEpatents

    West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

    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.

  13. 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,…

  14. 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,…

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. Microarray Inspector: tissue cross contamination detection tool for microarray data.

    PubMed

    Stępniak, Piotr; Maycock, Matthew; Wojdan, Konrad; Markowska, Monika; Perun, Serhiy; Srivastava, Aashish; Wyrwicz, Lucjan S; Świrski, Konrad

    2013-01-01

    Microarray technology changed the landscape of contemporary life sciences by providing vast amounts of expression data. Researchers are building up repositories of experiment results with various conditions and samples which serve the scientific community as a precious resource. Ensuring that the sample is of high quality is of utmost importance to this effort. The task is complicated by the fact that in many cases datasets lack information concerning pre-experimental quality assessment. Transcription profiling of tissue samples may be invalidated by an error caused by heterogeneity of the material. The risk of tissue cross contamination is especially high in oncological studies, where it is often difficult to extract the sample. Therefore, there is a need of developing a method detecting tissue contamination in a post-experimental phase. We propose Microarray Inspector: customizable, user-friendly software that enables easy detection of samples containing mixed tissue types. The advantage of the tool is that it uses raw expression data files and analyses each array independently. In addition, the system allows the user to adjust the criteria of the analysis to conform to individual needs and research requirements. The final output of the program contains comfortable to read reports about tissue contamination assessment with detailed information about the test parameters and results. Microarray Inspector provides a list of contaminant biomarkers needed in the analysis of adipose tissue contamination. Using real data (datasets from public repositories) and our tool, we confirmed high specificity of the software in detecting contamination. The results indicated the presence of adipose tissue admixture in a range from approximately 4% to 13% in several tested surgical samples.

  2. 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.

  3. Spotting effect in microarray experiments

    PubMed Central

    Mary-Huard, Tristan; Daudin, Jean-Jacques; Robin, Stéphane; Bitton, Frédérique; Cabannes, Eric; Hilson, Pierre

    2004-01-01

    Background Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. Results Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. Conclusions The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis. PMID:15151695

  4. 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.

  5. 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.

  6. 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...

  7. 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...

  8. 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.

  9. 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

  10. "Harshlighting" small blemishes on microarrays

    PubMed Central

    Suárez-Fariñas, Mayte; Haider, Asifa; Wittkowski, Knut M

    2005-01-01

    Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs). Results We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Conclusion Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization. PMID:15784152

  11. "Harshlighting" small blemishes on microarrays.

    PubMed

    Suárez-Fariñas, Mayte; Haider, Asifa; Wittkowski, Knut M

    2005-03-22

    Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans show similar artefacts, which affect the analysis, particularly when one tries to detect subtle changes. However, most blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs). We present a method that harnesses the statistical power provided by having several HDONAs available, which are obtained under similar conditions except for the experimental factor. This method "harshlights" blemishes and renders them evident. We find empirically that about 25% of our chips are blemished, and we analyze the impact of masking them on screening for differentially expressed genes. Experiments attempting to assess subtle expression changes should be carefully screened for blemishes on the chips. The proposed method provides investigators with a novel robust approach to improve the sensitivity of microarray analyses. By utilizing topological information to identify and mask blemishes prior to model based analyses, the method prevents artefacts from confounding the process of background correction, normalization, and summarization.

  12. 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...

  13. 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...

  14. 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...

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

    PubMed Central

    2011-01-01

    Background Many plants have large and complex genomes with an abundance of repeated sequences. Many plants are also polyploid. Both of these attributes typify the genome architecture in the tribe Triticeae, whose members include economically important wheat, rye and barley. Large genome sizes, an abundance of repeated sequences, and polyploidy present challenges to genome-wide SNP discovery using next-generation sequencing (NGS) of total genomic DNA by making alignment and clustering of short reads generated by the NGS platforms difficult, particularly in the absence of a reference genome sequence. Results 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 from repetitive sequences and sequences shared by paralogous genes. Multiple genome equivalents of shotgun reads of another genotype generated with SOLiD or Solexa are then mapped to the annotated Roche 454 reads to identify putative SNPs. A pipeline program package, AGSNP, was developed and used for genome-wide SNP discovery in Aegilops tauschii-the diploid source of the wheat D genome, and with a genome size of 4.02 Gb, of which 90% is repetitive sequences. Genomic DNA of Ae. tauschii accession AL8/78 was sequenced with the Roche 454 NGS platform. Genomic DNA and cDNA of Ae. tauschii accession AS75 was sequenced primarily with SOLiD, although some Solexa and Roche 454 genomic sequences were also generated. A total of 195,631 putative SNPs were discovered in gene sequences, 155,580 putative SNPs were discovered in uncharacterized single-copy regions, and another 145,907 putative SNPs were discovered in repeat junctions. These SNPs were dispersed across the entire Ae. tauschii genome. To assess the false positive SNP discovery rate, DNA containing putative SNPs was

  16. 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…

  17. 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…

  18. Tissue Microarrays in Clinical Oncology

    PubMed Central

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

    2008-01-01

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

  19. 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.

  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. 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.

  3. 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

  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. 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

  6. Metric learning for DNA microarray data analysis

    NASA Astrophysics Data System (ADS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-12-01

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

  7. 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

  8. Demystified...tissue microarray technology.

    PubMed

    Packeisen, J; Korsching, E; Herbst, H; Boecker, W; Buerger, H

    2003-08-01

    Several "high throughput methods" have been introduced into research and routine laboratories during the past decade. Providing a new approach to the analysis of genomic alterations and RNA or protein expression patterns, these new techniques generate a plethora of new data in a relatively short time, and promise to deliver clues to the diagnosis and treatment of human cancer. Along with these revolutionary developments, new tools for the interpretation of these large sets of data became necessary and are now widely available. Tissue microarray (TMA) technology is one of these new tools. It is based on the idea of applying miniaturisation and a high throughput approach to the analysis of intact tissues. The potential and the scientific value of TMAs in modern research have been demonstrated in a logarithmically increasing number of studies. The spectrum for additional applications is widening rapidly, and comprises quality control in histotechnology, longterm tissue banking, and the continuing education of pathologists. This review covers the basic technical aspects of TMA production and discusses the current and potential future applications of TMA technology.

  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. 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

  11. [DNA microarrays in parasitology and medical sciences].

    PubMed

    Jaros, Sławomir

    2006-01-01

    The article presents the current knowledge on the microarray technique and its applications in medical sciences and parasitology. The first part of the article is focused on the technical aspects (microarray preparation, different microarray platforms, probes preparation, hybridization and signal detection). The article also describes possible ways of proceeding during laboratory work on organism of which the genome sequence is not known or has been only partially sequenced. The second part of the review describes how microarray technique have been, or possibly will be, used for better understanding parasite life cycles and development, host-parasite relationship, comparative genomics of virulent organisms, develpoment vaccines against the most virulent parasites and host responses to infection.

  12. 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

  13. 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.

  14. 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

  15. Evaluation of Surface Chemistries for Antibody Microarrays

    SciTech Connect

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

    2007-12-01

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

  16. 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

  17. 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…

  18. 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…

  19. 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

  20. Chromosomal microarray versus karyotyping for prenatal diagnosis.

    PubMed

    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

    2012-12-06

    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. 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. 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. 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.).

  1. Performing custom microRNA microarray experiments.

    PubMed

    Zhang, Xiaoxiao; Zeng, Yan

    2011-10-28

    microRNAs (miRNAs) are a large family of ˜ 22 nucleotides (nt) long RNA molecules that are widely expressed in eukaryotes (1). Complex genomes encode at least hundreds of miRNAs, which primarily inhibit the expression of a vast number of target genes post-transcriptionally (2, 3). miRNAs control a broad range of biological processes (1). In addition, altered miRNA expression has been associated with human diseases such as cancers, and miRNAs may serve as biomarkers for diseases and prognosis (4, 5). It is important, therefore, to understand the expression and functions of miRNAs under many different conditions. Three major approaches have been employed to profile miRNA expression: real-time PCR, microarray, and deep sequencing. The technique of miRNA microarray has the advantage of being high-throughput, generally less expensive, and most of the experimental and analysis steps can be carried out in a molecular biology laboratory at most universities, medical schools and associated hospitals. Here, we describe a method for performing custom miRNA microarray experiments. A miRNA probe set will be printed on glass slides to produce miRNA microarrays. RNA is isolated using a method or reagent that preserves small RNA species, and then labeled with a fluorescence dye. As a control, reference DNA oligonucleotides corresponding to a subset of miRNAs are also labeled with a different fluorescence dye. The reference DNA will serve to demonstrate the quality of the slide and hybridization and will also be used for data normalization. The RNA and DNA are mixed and hybridized to a microarray slide containing probes for most of the miRNAs in the database. After washing, the slide is scanned to obtain images, and intensities of the individual spots quantified. These raw signals will be further processed and analyzed as the expression data of the corresponding miRNAs. Microarray slides can be stripped and regenerated to reduce the cost of microarrays and to enhance the

  2. 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.

  3. Microarray Data Analysis and Mining Tools

    PubMed Central

    Selvaraj, Saravanakumar; Natarajan, Jeyakumar

    2011-01-01

    Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis. PMID:21584183

  4. Microarray data analysis and mining tools.

    PubMed

    Selvaraj, Saravanakumar; Natarajan, Jeyakumar

    2011-04-22

    Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis.

  5. 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.

  6. Designing microarray phantoms for hyperspectral imaging validation

    PubMed Central

    Clarke, Matthew L.; Lee, Ji Youn; Samarov, Daniel V.; Allen, David W.; Litorja, Maritoni; Nossal, Ralph; Hwang, Jeeseong

    2012-01-01

    The design and fabrication of custom-tailored microarrays for use as phantoms in the characterization of hyperspectral imaging systems is described. Corresponding analysis methods for biologically relevant samples are also discussed. An image-based phantom design was used to program a microarrayer robot to print prescribed mixtures of dyes onto microscope slides. The resulting arrays were imaged by a hyperspectral imaging microscope. The shape of the spots results in significant scattering signals, which can be used to test image analysis algorithms. Separation of the scattering signals allowed elucidation of individual dye spectra. In addition, spectral fitting of the absorbance spectra of complex dye mixtures was performed in order to determine local dye concentrations. Such microarray phantoms provide a robust testing platform for comparisons of hyperspectral imaging acquisition and analysis methods. PMID:22741076

  7. Microarray analysis of erythromycin resistance determinants.

    PubMed

    Volokhov, D; Chizhikov, V; Chumakov, K; Rasooly, A

    2003-01-01

    To develop a DNA microarray for analysis of genes encoding resistance determinants to erythromycin and the related macrolide, lincosamide and streptogramin B (MLS) compounds. We developed an oligonucleotide microarray containing seven oligonucleotide probes (oligoprobes) for each of the six genes (ermA, ermB, ermC, ereA, ereB and msrA/B) that account for more than 98% of MLS resistance in Staphylococcus aureus clinical isolates. The microarray was used to test reference and clinical S. aureus and Streptococcus pyrogenes strains. Target genes from clinical strains were amplified and fluorescently labelled using multiplex PCR target amplification. The microarray assay correctly identified the MLS resistance genes in the reference strains and clinical isolates of S. aureus, and the results were confirmed by direct DNA sequence analysis. Of 18 S. aureus clinical strains tested, 11 isolates carry MLS determinants. One gene (ermC) was found in all 11 clinical isolates tested, and two others, ermA and msrA/B, were found in five or more isolates. Indeed, eight (72%) of 11 clinical isolate strains contained two or three MLS resistance genes, in one of the three combinations (ermA with ermC, ermC with msrA/B, ermA with ermC and msrA/B). Oligonucleotide microarray can detect and identify the six MLS resistance determinants analysed in this study. Our results suggest that microarray-based detection of microbial antibiotic resistance genes might be a useful tool for identifying antibiotic resistance determinants in a wide range of bacterial strains, given the high homology among microbial MLS resistance genes.

  8. 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

  9. Protein Microarrays for the Detection of Biothreats

    NASA Astrophysics Data System (ADS)

    Herr, Amy E.

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

  10. 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

  11. MicroRNA expression profiling using microarrays.

    PubMed

    Love, Cassandra; Dave, Sandeep

    2013-01-01

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

  12. 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.

  13. 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).

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

    PubMed Central

    Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

    2008-01-01

    Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

  15. 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.

  16. 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.

  17. 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

  18. 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…

  19. High confidence rule mining for microarray analysis.

    PubMed

    McIntosh, Tara; Chawla, Sanjay

    2007-01-01

    We present an association rule mining method for mining high confidence rules, which describe interesting gene relationships from microarray datasets. Microarray datasets typically contain an order of magnitude more genes than experiments, rendering many data mining methods impractical as they are optimised for sparse datasets. A new family of row-enumeration rule mining algorithms have emerged to facilitate mining in dense datasets. These algorithms rely on pruning infrequent relationships to reduce the search space by using the support measure. This major shortcoming results in the pruning of many potentially interesting rules with low support but high confidence. We propose a new row-enumeration rule mining method, MaxConf, to mine high confidence rules from microarray data. MaxConf is a support-free algorithm which directly uses the confidence measure to effectively prune the search space. Experiments on three microarray datasets show that MaxConf outperforms support-based rule mining with respect to scalability and rule extraction. Furthermore, detailed biological analyses demonstrate the effectiveness of our approach -- the rules discovered by MaxConf are substantially more interesting and meaningful compared with support-based methods.

  20. 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...

  1. 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.

  2. 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...

  3. 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…

  4. 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.

  5. Microarray technology: a promising tool in nutrigenomics.

    PubMed

    Masotti, Andrea; Da Sacco, Letizia; Bottazzo, Gian Franco; Alisi, Anna

    2010-08-01

    Microarray technology is a powerful tool for the global evaluation of gene expression profiles in tissues and for understanding many of the factors controlling the regulation of gene transcription. This technique not only provides a considerable amount of information on markers and predictive factors that may potentially characterize a specific clinical picture, but also promises new applications for therapy. One of the most recent applications of microarrays concerns nutritional genomics. Nutritional genomics, known as nutrigenomics, aims to identify and understand mechanisms of molecular interaction between nutrients and/or other dietary bioactive compounds and the genome. Actually, many nutrigenomic studies utilize new approaches such as microarrays, genomics, and bioinformatics to understand how nutrients influence gene expression. The coupling of these new technologies with nutrigenomics promises to lead to improvements in diet and health. In fact, it may provide new information which can be used to ameliorate dietary regimens and to discover novel natural agents for the treatment of important diseases such as diabetes and cancer. This critical review gives an overview of the clinical relevance of a nutritional approach to several important diseases, and proposes the use of microarray for nutrigenomic studies.

  6. 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...

  7. 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...

  8. 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.

  9. Strategy for the design of custom cDNA microarrays.

    PubMed

    Lorenz, Matthias G O; Cortes, Lizette M; Lorenz, Juergen J; Liu, Edison T

    2003-06-01

    DNA microarrays are valuable but expensive tools for expression profiling of cells, tissues, and organs. The design of custom microarrays leads to cost reduction without necessarily compromising their biological value. Here we present a strategy for designing custom cDNA microarrays and constructed a microarray for mouse immunology research (ImmunoChip). The strategy used interrogates expressed sequence tag databases available in the public domain but overcomes many of the problems encountered. Immunologically relevant clusters were selected based on the expression of expressed sequence tags in relevant libraries. Selected clusters were organized in modules, and the best representative clones were identified. When tested, this microarray was found to have minimal clone identity errors or phage contamination and identified molecular signatures of lymphoid cell lines. Our proposed design of custom microarrays avoids probe redundancy, allows the organization of the chip to optimize chip production, and reduces microarray production costs. The strategy described is also useful for the design of oligonucleotide microarrays.

  10. 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...

  11. 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

  12. 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...

  13. 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.

  14. 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

  15. 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.

  16. Methods in molecular cardiology: microarray technology

    PubMed Central

    van den Bosch, B.; Doevendans, P.A.; Lips, D.; Smeets, H.J.M.

    2003-01-01

    It has become more and more evident that changes in expression levels of genes can play an important role in cardiovascular diseases. Specific gene expression profiles may explain, for example, the pathophysiology of myocardial hypertrophy and pump failure and may provide clues for therapeutic interventions. Knowledge of gene expression patterns can also be applied for diagnostic and prognostic purposes, in which differences in gene activity can be used for classification. DNA microarray technology has become the method of choice to simultaneously study the expression of many different genes in a single assay. Each microarray contains many thousands of different DNA sequences attached to a glass slide. The amount of messenger RNA, which is a measure of gene activity, is compared for each gene on the microarray by labelling the mRNA with different fluorescently labelled nucleotides (Cy3 or Cy5) for the test and reference samples. After hybridisation to the microarray the relative amounts of a particular gene transcript in the two samples can be determined by measuring the signal intensities for the fluorescent groups (Cy3 and Cy5) and calculating signal ratios. This paper describes the development of in-house microarray technology, using commercially available cDNA collections. Several technical approaches will be compared and an overview of the pitfalls and possibilities will be presented. The technology will be explained in the context of our project to determine gene expression differences between normal, hypertrophic and failing heart. ImagesFigure 1Figure 2Figure 3Figure 4Figure 5Figure 6Figure 7Figure 9 PMID:25696214

  17. Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

    PubMed

    Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

    2014-08-04

    Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. DNA microarrays: an introduction to the technology.

    PubMed

    Bilitewski, Ursula

    2009-01-01

    DNA microarrays allow the comprehensive genetic analysis of an organism or a sample. They are based on probes, which are immobilized in an ordered two-dimensional pattern on substrates, such as nylon membranes or glass slides. Probes are either spotted cDNAs or oligonucleotides and are designed to be specific for an organism, a gene, a genetic variant (mutation or polymorphism), or intergenic regions. Thus, they can be used for example for genotyping, expression analysis, or studies of protein-DNA interactions, and in the biomedical field they allow the detection of pathogens, antibiotic resistances, gene mutations and polymorphisms, and pathogenic states and can guide therapy. Microarrays, which cover the whole genome of an organism, are as well available as those which are focussed on genes related to a certain diagnostic application.

  4. 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.

  5. 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

  6. Respiratory Tularemia: Francisella Tularensis and Microarray Probe Designing.

    PubMed

    Ranjbar, Reza; Behzadi, Payam; Mammina, Caterina

    2016-01-01

    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. The main goal of this original article was to design suitable long oligo microarray probes for detection and identification of F. tularensis. 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. 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. 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.

  7. 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

  8. 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.

  9. An Affymetrix Microarray Design for Microbial Genotyping

    DTIC Science & Technology

    2009-10-01

    Pagotto, F. 2004. Selective discrimination of Listeria monocytogenes epidemic strains by a mixed-genome DNA microarray compared to discrimination by...Legionella pneumophila Paris 399 Legionella pneumophila pneumophila 5 Listeria innocua Clip 11262 105 Listeria ivanoviiI ATCC 19119 5 Listeria ...monocytogenes monocytogenes 10 Listeria monocytogenes APRT EGD-e 5 Listeria monocytogenes HPT 4b 2365 10 Listeria monocytogenes HPT EGD-e 5 Listeria

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Integrated microfluidic biochips for DNA microarray analysis.

    PubMed

    Liu, Robin Hui; Dill, Kilian; Fuji, H Sho; McShea, Andy

    2006-03-01

    A fully integrated and self-contained microfluidic biochip device has been developed to automate the fluidic handling steps required to perform a gene expression study of the human leukemia cell line (K-562). The device consists of a DNA microarray semiconductor chip with 12,000 features and a microfluidic cartridge that consists of microfluidic pumps, mixers, valves, fluid channels and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. A single-color transcriptional analysis of K-562 cells with a series of calibration controls (spiked-in controls) was performed to characterize this new platform with regard to sensitivity, specificity and dynamic range. The device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than 3 orders of magnitude. Experiments also demonstrated that chip-to-chip variability was low, indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis.

  15. Development and Applications of the Lectin Microarray.

    PubMed

    Hirabayashi, Jun; Kuno, Atsushi; Tateno, Hiroaki

    2015-01-01

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

  16. 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.

  17. Metadata Management and Semantics in Microarray Repositories

    PubMed Central

    Kocabaş, F; Can, T; Baykal, N

    2011-01-01

    The number of microarray and other high-throughput experiments on primary repositories keeps increasing as do the size and complexity of the results in response to biomedical investigations. Initiatives have been started on standardization of content, object model, exchange format and ontology. However, there are backlogs and inability to exchange data between microarray repositories, which indicate that there is a great need for a standard format and data management. We have introduced a metadata framework that includes a metadata card and semantic nets that make experimental results visible, understandable and usable. These are encoded in syntax encoding schemes and represented in RDF (Resource Description Frame-word), can be integrated with other metadata cards and semantic nets, and can be exchanged, shared and queried. We demonstrated the performance and potential benefits through a case study on a selected microarray repository. We concluded that the backlogs can be reduced and that exchange of information and asking of knowledge discovery questions can become possible with the use of this metadata framework. PMID:24052712

  18. 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

  19. 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

  20. 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.

  1. Thermodynamically optimal whole-genome tiling microarray design and validation.

    PubMed

    Cho, Hyejin; Chou, Hui-Hsien

    2016-06-13

    Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

  2. The microarray technology: facts and controversies.

    PubMed

    Lévêque, N; Renois, F; Andréoletti, L

    2013-01-01

    Molecular diagnostic techniques for viral testing have undergone rapid development in recent years. They are becoming more widely used than the classical virological assays in the majority of clinical virology laboratories, and now represent a new method for the diagnosis of human viral infections. Recently, new techniques based on multiplex RT-PCR amplification followed by microarray analysis have been developed and evaluated. On the basis of amplification of viral genome-specific fragments by multiplex RT-PCR and their subsequent detection via hybridization with microorganism-specific binding probes on solid surfaces, they allow simultaneous detection and identification of multiple viruses in a single clinical sample. The management of viral central nervous system and respiratory tract infections currently represents the two main applications of the microarrays in routine virological practice. Microarrays have shown reliable results in comparison with those of referenced (RT)-PCR assays, and appear to be of major interest for the detection of a broad range of respiratory and neurotropic viruses, assessment of the pathogenicity of newly discovered or neglected viruses, and identification of multiple viral infections in clinical samples. Despite several limitations observed during the different studies performed, this new technology might improve the clinical management of patients by enlarging the range of the viruses detected, in particular in cases of severe infections leading to patient hospitalization in the intensive-care unit. They might also help in the prevention of nosocomial transmission in hospital departments by contributing to the development of new epidemiological surveillance systems for viral infections. © 2012 The Authors. Clinical Microbiology and Infection © 2012 European Society of Clinical Microbiology and Infectious Diseases.

  3. 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

  4. 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

  5. Optimization and clinical validation of a pathogen detection microarray

    PubMed Central

    Wong, Christopher W; Heng, Charlie Lee Wah; Wan Yee, Leong; Soh, Shirlena WL; Kartasasmita, Cissy B; Simoes, Eric AF; Hibberd, Martin L; Sung, Wing-Kin; Miller, Lance D

    2007-01-01

    DNA microarrays used as 'genomic sensors' have great potential in clinical diagnostics. Biases inherent in random PCR-amplification, cross-hybridization effects, and inadequate microarray analysis, however, limit detection sensitivity and specificity. Here, we have studied the relationships between viral amplification efficiency, hybridization signal, and target-probe annealing specificity using a customized microarray platform. Novel features of this platform include the development of a robust algorithm that accurately predicts PCR bias during DNA amplification and can be used to improve PCR primer design, as well as a powerful statistical concept for inferring pathogen identity from probe recognition signatures. Compared to real-time PCR, the microarray platform identified pathogens with 94% accuracy (76% sensitivity and 100% specificity) in a panel of 36 patient specimens. Our findings show that microarrays can be used for the robust and accurate diagnosis of pathogens, and further substantiate the use of microarray technology in clinical diagnostics. PMID:17531104

  6. 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.

  7. 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.:

  8. 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.

  9. 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.

  10. 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.

  11. Fabrication and application of G protein-coupled receptor microarrays.

    PubMed

    Fang, Ye; Webb, Brian; Hong, Yulong; Ferrie, Ann; Lai, Fang; Frutos, Anthony G; Lahiri, Joydeep

    2004-01-01

    The increased number of drug targets and compounds demands novel high-throughput screening technologies that could be used for parallel analysis of many genes and proteins. Protein microarrays are evolving promising technologies for the parallel analysis of many proteins with respect to their abundance, location, modifications, and interactions with other biological and chemical molecules. This chapter specifically describes the fabrication of G protein-coupled receptor (GPCR) microarrays, a unique subset of protein microarrays, using contact-pin printing technology. The bioassays and potential applications of GPCR microarrays for the determination of compound affinities and potencies are also included.

  12. 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.

  13. Autocorrelation analysis reveals widespread spatial biases in microarray experiments

    PubMed Central

    Koren, Amnon; Tirosh, Itay; Barkai, Naama

    2007-01-01

    Background DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes. Results In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures. Conclusions Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data. PMID:17565680

  14. Autocorrelation analysis reveals widespread spatial biases in microarray experiments.

    PubMed

    Koren, Amnon; Tirosh, Itay; Barkai, Naama

    2007-06-12

    DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes. In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures. Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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).

  1. 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.

  2. Modeling background intensity in DNA microarrays

    NASA Astrophysics Data System (ADS)

    Kroll, K. M.; Barkema, G. T.; Carlon, E.

    2008-06-01

    DNA microarrays are devices that are able, in principle, to detect and quantify the presence of specific nucleic acid sequences in complex biological mixtures. The measurement consists in detecting fluorescence signals from several spots on the microarray surface onto which different probe sequences are grafted. One of the problems of the data analysis is that the signal contains a noisy background component due to nonspecific binding. We present a physical model for background estimation in Affymetrix Genechips. It combines two different approaches. The first is based on the sequence composition, specifically its sequence-dependent hybridization affinity. The second is based on the strong correlation of intensities from locations which are the physical neighbors of a specific spot on the chip. Both effects are incorporated in a background estimator which contains 24 free parameters, fixed by minimization on a training data set. In all data analyzed the sequence-specific parameters, obtained by minimization, are found to strongly correlate with empirically determined stacking free energies for RNA-DNA hybridization in solution. Moreover, there is an overall agreement with experimental background data and we show that the physics-based model that we propose performs on average better than purely statistical approaches for background calculations. The model thus provides an interesting alternative method for background subtraction schemes in Affymetrix Genechips.

  3. 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

  4. MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

    PubMed

    Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

    2014-06-15

    The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

  5. Automatic Spot Identification for High Throughput Microarray Analysis

    PubMed Central

    Wu, Eunice; Su, Yan A.; Billings, Eric; Brooks, Bernard R.; Wu, Xiongwu

    2013-01-01

    High throughput microarray analysis has great potential in scientific research, disease diagnosis, and drug discovery. A major hurdle toward high throughput microarray analysis is the time and effort needed to accurately locate gene spots in microarray images. An automatic microarray image processor will allow accurate and efficient determination of spot locations and sizes so that gene expression information can be reliably extracted in a high throughput manner. Current microarray image processing tools require intensive manual operations in addition to the input of grid parameters to correctly and accurately identify gene spots. This work developed a method, herein called auto-spot, to automate the spot identification process. Through a series of correlation and convolution operations, as well as pixel manipulations, this method makes spot identification an automatic and accurate process. Testing with real microarray images has demonstrated that this method is capable of automatically extracting subgrids from microarray images and determining spot locations and sizes within each subgrid, regardless of variations in array patterns and background noises. With this method, we are one step closer to the goal of high throughput microarray analysis. PMID:24298393

  6. 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...

  7. 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...

  8. 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…

  9. 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

  10. Shared probe design and existing microarray reanalysis using PICKY.

    PubMed

    Chou, Hui-Hsien

    2010-04-20

    Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations. PICKY 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. PICKY 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, PICKY does not sacrifice the quality of shared probes when choosing them. The latest PICKY 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making PICKY 2.1 more versatile to microarray users. Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.

  11. 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…

  12. 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.

  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. 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.

  15. 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

  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. 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.

  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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  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. 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

  1. Polymer microarray technology for stem cell engineering.

    PubMed

    Coyle, Robert; Jia, Jia; Mei, Ying

    2016-04-01

    Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. During the past decade, significant progress has been made in developing soluble factors (e.g., small molecules and growth factors) to direct stem cells into a desired phenotype. However, the current lack of suitable synthetic materials to regulate stem cell activity has limited the realization of the enormous potential of stem cells. This can be attributed to a large number of materials properties (e.g., chemical structures and physical properties of materials) that can affect stem cell fate. This makes it challenging to design biomaterials to direct stem cell behavior. To address this, polymer microarray technology has been developed to rapidly identify materials for a variety of stem cell applications. In this article, we summarize recent developments in polymer array technology and their applications in stem cell engineering. Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. In the last decade, significant progress has been made in developing chemically defined media to direct stem cells into a desired phenotype. However, the current lack of the suitable synthetic materials to regulate stem cell activities has been limiting the realization of the potential of stem cells. This can be attributed to the number of variables in material properties (e.g., chemical structures and physical properties) that can affect stem cells. Polymer microarray technology has shown to be a powerful tool to rapidly identify materials for a variety of stem cell applications. Here we summarize recent developments in polymer array technology and their applications in stem cell engineering. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  2. Transformation and normalization of oligonucleotide microarray data.

    PubMed

    Geller, Sue C; Gregg, Jeff P; Hagerman, Paul; Rocke, David M

    2003-09-22

    Most methods of analyzing microarray data or doing power calculations have an underlying assumption of constant variance across all levels of gene expression. The most common transformation, the logarithm, results in data that have constant variance at high levels but not at low levels. Rocke and Durbin showed that data from spotted arrays fit a two-component model and Durbin, Hardin, Hawkins, and Rocke, Huber et al. and Munson provided a transformation that stabilizes the variance as well as symmetrizes and normalizes the error structure. We wish to evaluate the applicability of this transformation to the error structure of GeneChip microarrays. We demonstrate in an example study a simple way to use the two-component model of Rocke and Durbin and the data transformation of Durbin, Hardin, Hawkins and Rocke, Huber et al. and Munson on Affymetrix GeneChip data. In addition we provide a method for normalization of Affymetrix GeneChips simultaneous with the determination of the transformation, producing a data set without chip or slide effects but with constant variance and with symmetric errors. This transformation/normalization process can be thought of as a machine calibration in that it requires a few biologically constant replicates of one sample to determine the constant needed to specify the transformation and normalize. It is hypothesized that this constant needs to be found only once for a given technology in a lab, perhaps with periodic updates. It does not require extensive replication in each study. Furthermore, the variance of the transformed pilot data can be used to do power calculations using standard power analysis programs. SPLUS code for the transformation/normalization for four replicates is available from the first author upon request. A program written in C is available from the last author.

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

    PubMed

    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

    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. 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. 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. 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.

  4. 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

  5. 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.

  6. Functional assessment of time course microarray data

    PubMed Central

    Nueda, María José; Sebastián, Patricia; Tarazona, Sonia; García-García, Francisco; Dopazo, Joaquín; Ferrer, Alberto; Conesa, Ana

    2009-01-01

    Motivation Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated. Methods We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies. Results Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study. PMID:19534758

  7. Functional assessment of time course microarray data.

    PubMed

    Nueda, María José; Sebastián, Patricia; Tarazona, Sonia; García-García, Francisco; Dopazo, Joaquín; Ferrer, Alberto; Conesa, Ana

    2009-06-16

    Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated. We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies. Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study.

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

    PubMed

    Biyani, Manish; Ichiki, Takanori

    2015-07-14

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

  9. A Human Lectin Microarray for Sperm Surface Glycosylation Analysis.

    PubMed

    Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-Ce

    2016-09-01

    Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  10. Protein microarray-mediated detection of antienterovirus antibodies in serum.

    PubMed

    Zhang, Aiying; Xiu, Bingshui; Zhang, Heqiu; Li, Ning

    2016-04-01

    To utilize prokaryotic gene expression and protein microarray to develop and evaluate a sensitive, accurate protein microarray assay for detecting antienterovirus antibodies in serum samples from patients with hand, foot and mouth disease (HFMD). Enterovirus 71 (EV71) and coxsackievirus A16 (CA16), two common causative agents for HFMD, were used for assay development. Serum was collected from patients with HFMD and healthy controls. EV71 and CA16 VP1 and VP3 genes were expressed in transfected Escherichia coli; the resultant VP1 and 3 proteins were used in a microarray assay for human serum EV71 and CA16 immunoglobulin (Ig) M and IgG. To validate the microarray assay, serum samples were tested for EV71 IgM using enzyme-linked immunosorbent assay (ELISA). Out of 50 patients with HFMD, EV71 IgM and CA16 IgM was detected in 80% and 44% of serum samples, respectively, using protein microarray, and EV71 IgM was detected in 78% of samples using ELISA. Protein microarray and ELISA showed 100% specificity for EV71-IgM detection. The protein microarray assay developed in the present study shows potential as a sensitive technique for detecting EV71 IgM in serum samples from patients with HFMD. © The Author(s) 2016.

  11. 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. Copyright © 2016. Published by Elsevier Inc.

  12. A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

    PubMed Central

    Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

    2016-01-01

    Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

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

    PubMed Central

    Biyani, Manish; Ichiki, Takanori

    2015-01-01

    Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

  14. 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

  15. 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.

  16. 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.

  17. 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

  18. Ontology-Based Analysis of Microarray Data.

    PubMed

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

    The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress.

  19. Recessed Gold Nanoring-Ring Microarray Electrodes.

    PubMed

    Atighilorestani, Mahdieh; Brolo, Alexandre G

    2017-08-31

    A 6 × 6 recessed Au nanoring-ring electrodes microarray was fabricated over a glass substrate using focused ion beam milling. The electrochemical responses of this device to a reversible redox pair were examined. In redox-cycling mode, the lower ring acts as a generator and the upper ring as a collector. High collection efficiencies (close to 100%) and amplification factors (∼3.5) were achieved with this configuration. The redox-cycling behavior of this device was modeled using COMSOL Multiphysics. The effects of scaling the geometric parameters of the electrodes (ring height and radius), potential sweep rates, and inter-electrode gap distance were evaluated through simulations. The computational models showed that the attainable limiting current depends strongly on the ring radius, while it is almost independent of the ring height variations (for a particular inter-electrode gap). The effects of the scan rate and inter-electrode gap distance on the electrochemical characteristics of the device are also discussed. This study provides insights on the influence of the geometry on the performance of these arrays, which should guide the development of future applications.

  20. Tissue microarray profiling in human heart failure.

    PubMed

    Lal, Sean; Nguyen, Lisa; Tezone, Rhenan; Ponten, Fredrik; Odeberg, Jacob; Li, Amy; Dos Remedios, Cristobal

    2016-09-01

    Tissue MicroArrays (TMAs) are a versatile tool for high-throughput protein screening, allowing qualitative analysis of a large number of samples on a single slide. We have developed a customizable TMA system that uniquely utilizes cryopreserved human cardiac samples from both heart failure and donor patients to produce formalin-fixed paraffin-embedded sections. Confirmatory upstream or downstream molecular studies can then be performed on the same (biobanked) cryopreserved tissue. In a pilot study, we applied our TMAs to screen for the expression of four-and-a-half LIM-domain 2 (FHL2), a member of the four-and-a-half LIM family. This protein has been implicated in the pathogenesis of heart failure in a variety of animal models. While FHL2 is abundant in the heart, not much is known about its expression in human heart failure. For this purpose, we generated an affinity-purified rabbit polyclonal anti-human FHL2 antibody. Our TMAs allowed high-throughput profiling of FHL2 protein using qualitative and semiquantitative immunohistochemistry that proved complementary to Western blot analysis. We demonstrated a significant relative reduction in FHL2 protein expression across different forms of human heart failure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Digitized tissue microarray classification using sparse reconstruction

    NASA Astrophysics Data System (ADS)

    Xing, Fuyong; Liu, Baiyang; Qi, Xin; Foran, David J.; Yang, Lin

    2012-02-01

    In this paper, we propose a novel image classification method based on sparse reconstruction errors to discriminate cancerous breast tissue microarray (TMA) discs from benign ones. Sparse representation is employed to reconstruct the samples and separate the benign and cancer discs. The method consists of several steps including mask generation, dictionary learning, and data classification. Mask generation is performed using multiple scale texton histogram, integral histogram and AdaBoost. Two separate cancer and benign TMA dictionaries are learned using K-SVD. Sparse coefficients are calculated using orthogonal matching pursuit (OMP), and the reconstructive error of each testing sample is recorded. The testing image will be divided into many small patches. Each small patch will be assigned to the category which produced the smallest reconstruction error. The final classification of each testing sample is achieved by calculating the total reconstruction errors. Using standard RGB images, and tested on a dataset with 547 images, we achieved much better results than previous literature. The binary classification accuracy, sensitivity, and specificity are 88.0%, 90.6%, and 70.5%, respectively.

  2. Multi-platform microarray integration research

    NASA Astrophysics Data System (ADS)

    Wu, Ronghui; Lu, Lei

    2017-08-01

    There are more and more tumor data from different laboratories and different technology platforms. Data from independent laboratory is often difficult to explain and unreliable. So there comes a challenging task which is to develop robust integration algorithms to integrate microarray data from various experiments and platforms. We studied the traditional integration algorithm, and found that it was effective to use Combat to integrate the data. Combat is characterized not only in the integration of small samples, but also in the case of large samples. It is comparable with other integration algorithms and performs well on various evaluation indicators. But we find that Combat is a combination of mean and merging variance for several batches, and integrate directly without fully considering the information from sample data, which we believe will ignore a single Batch characteristics and parameters are estimated to be biased. So an improved algorithm is proposed to find the mean and variance for a single batch, and when integrating, consider the first principal component of a single batch and segment the sample using the first principal component, and then integrated. In the experimental part, we first evaluate our algorithm with the commonly used evaluation index.

  3. 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.

  4. 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.

  5. 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).

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Emerging technology of in situ cell free expression protein microarrays.

    PubMed

    Nand, Amita; Gautam, Anju; Pérez, Javier Batista; Merino, Alejandro; Zhu, Jinsong

    2012-02-01

    Recently, in situ protein microarrays have been developed for large scale analysis and high throughput studies of proteins. In situ protein microarrays produce proteins directly on the solid surface from pre-arrayed DNA or RNA. The advances in in situ protein microarrays are exemplified by the ease of cDNA cloning and cell free protein expression. These technologies can evaluate, validate and monitor protein in a cost effective manner and address the issue of a high quality protein supply to use in the array. Here we review the importance of recently employed methods: PISA (protein in situ array), DAPA (DNA array to protein array), NAPPA (nucleic acid programmable protein array) and TUSTER microarrays and the role of these methods in proteomics.

  11. DNA microarray technology for the microbiologist: an overview.

    PubMed

    Ehrenreich, Armin

    2006-11-01

    DNA microarrays have found widespread use as a flexible tool to investigate bacterial metabolism. Their main advantage is the comprehensive data they produce on the transcriptional response of the whole genome to an environmental or genetic stimulus. This allows the microbiologist to monitor metabolism and to define stimulons and regulons. Other fields of application are the identification of microorganisms or the comparison of genomes. The importance of this technology increases with the number of sequenced genomes and the falling prices for equipment and oligonucleotides. Knowledge of DNA microarrays is of rising relevance for many areas in microbiological research. Much literature has been published on various specific aspects of this technique that can be daunting to the casual user and beginner. This article offers a comprehensive outline of microarray technology for transcription analysis in microbiology. It shortly discusses the types of DNA microarrays available, the printing of custom arrays, common labeling strategies for targets, hybridization, scanning, normalization, and clustering of expression data.

  12. IgE Epitope Mapping Using Peptide Microarray Immunoassay.

    PubMed

    Lin, Jing; Sampson, Hugh A

    2017-01-01

    IgE epitope mapping has the potential to become an additional tool for food allergy diagnosis/prognosis and to lead to a better understanding of the pathogenesis and tolerance induction of food allergy. Due to its ability to screen thousands of targets in parallel using small volumes of sample, peptide microarray has greatly facilitated large-scale IgE epitope mapping. In the past 10 years, we have developed and optimized a reliable and sensitive peptide microarray immunoassay, which has been successfully applied for IgE epitope mapping of many food allergens in our lab. Here, we describe the method of performing the peptide microarray immunoassay for IgE epitope mapping. In addition, we have upgraded the microarray platform to measure antibody affinity by adding one additional competition step, which is also described in this chapter.

  13. The ultimate chip shot: can microarray technology deliver for neuroscience?

    PubMed

    Nisenbaum, L K

    2002-01-01

    The use of cDNA and oligonucleotide microarrays, or 'chips', is emerging as a powerful, new technology in the field of neuroscience for examining gene expression in a high-throughput fashion. The application of microarray technology to the study of brain and behavior has lagged behind other areas of biology such as cancer and yeast genetics due to the challenges presented by the heterogeneous and complex organization of the nervous system. This review provides a brief overview of available microarray technology as well as a description of experimental considerations in planning and implementing a neuroscience-based array study. Successful implementation of microarray technology within the field of neuroscience will provide a molecular approach to studying systems neurobiology, leading to insights into areas ranging from fundamental questions of developmental neurobiology to neurological and psychiatric disorders.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  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. Where statistics and molecular microarray experiments biology meet.

    PubMed

    Kelmansky, Diana M

    2013-01-01

    This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.

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

    PubMed Central

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

    2013-01-01

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

  1. Challenges for MicroRNA Microarray Data Analysis

    PubMed Central

    Wang, Bin; Xi, Yaguang

    2013-01-01

    Microarray is a high throughput discovery tool that has been broadly used for genomic research. Probe-target hybridization is the central concept of this technology to determine the relative abundance of nucleic acid sequences through fluorescence-based detection. In microarray experiments, variations of expression measurements can be attributed to many different sources that influence the stability and reproducibility of microarray platforms. Normalization is an essential step to reduce non-biological errors and to convert raw image data from multiple arrays (channels) to quality data for further analysis. In general, for the traditional microarray analysis, most established normalization methods are based on two assumptions: (1) the total number of target genes is large enough (>10,000); and (2) the expression level of the majority of genes is kept constant. However, microRNA (miRNA) arrays are usually spotted in low density, due to the fact that the total number of miRNAs is less than 2,000 and the majority of miRNAs are weakly or not expressed. As a result, normalization methods based on the above two assumptions are not applicable to miRNA profiling studies. In this review, we discuss a few representative microarray platforms on the market for miRNA profiling and compare the traditional methods with a few novel strategies specific for miRNA microarrays. PMID:24163754

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. DNA microarray technology for target identification and validation.

    PubMed

    Jayapal, Manikandan; Melendez, Alirio J

    2006-01-01

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

  7. 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

  8. 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.

  9. [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.

  10. 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.

  11. 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.

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

    PubMed

    Lemetre, Christophe; Zhang, Zhengdong D

    2013-01-01

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

  13. 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

  14. 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

  15. Characterizing dye bias in microarray experiments.

    PubMed

    Dobbin, K K; Kawasaki, E S; Petersen, D W; Simon, R M

    2005-05-15

    Spot intensity serves as a proxy for gene expression in dual-label microarray experiments. Dye bias is defined as an intensity difference between samples labeled with different dyes attributable to the dyes instead of the gene expression in the samples. Dye bias that is not removed by array normalization can introduce bias into comparisons between samples of interest. But if the bias is consistent across samples for the same gene, it can be corrected by proper experimental design and analysis. If the dye bias is not consistent across samples for the same gene, but is different for different samples, then removing the bias becomes more problematic, perhaps indicating a technical limitation to the ability of fluorescent signals to accurately represent gene expression. Thus, it is important to characterize dye bias to determine: (1) whether it will be removed for all genes by array normalization, (2) whether it will not be removed by normalization but can be removed by proper experimental design and analysis and (3) whether dye bias correction is more problematic than either of these and is not easily removable. We analyzed two large (each >27 arrays) tissue culture experiments with extensive dye swap arrays to better characterize dye bias. Indirect, amino-allyl labeling was used in both experiments. We found that post-normalization dye bias that is consistent across samples does appear to exist for many genes, and that controlling and correcting for this type of dye bias in design and analysis is advisable. The extent of this type of dye bias remained unchanged under a wide range of normalization methods (median-centering, various loess normalizations) and statistical analysis techniques (parametric, rank based, permutation based, etc.). We also found dye bias related to the individual samples for a much smaller subset of genes. But these sample-specific dye biases appeared to have minimal impact on estimated gene-expression differences between the cell lines.

  16. 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.

  17. Microintaglio Printing of In situ Synthesized Proteins Enables Rapid Printing of High-Density Protein Microarrays Directly from DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Biyani, Manish; Moriyasu, Junpei; Tanaka, Yoko; Sato, Shusuke; Ueno, Shingo; Ichiki, Takanori

    2013-08-01

    A simple and versatile approach to the simultaneous on-chip synthesis and printing of proteins has been studied for high-density protein microarray applications. The method used is based on the principle of intaglio printing using microengraved plates. Unlike conventional approaches that require multistep reactions for synthesizing proteins off the chip followed by printing using a robotic spotter, our approach demonstrates the following: (i) parallel and spotter-free printing of high-density protein microarrays directly from a type of DNA microarray and (ii) microcompartmentalization of cell-free coupled transcription/translation reaction and direct transferring of picoliter protein solution per spot to pattern microarrays of 25-100 µm features.

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

    PubMed

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

    2016-12-01

    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. 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%. Overall, the newly developed microarray platform provides a convenient, highly accurate, and reliable clinical assay for the determination of blood protozoan species.

  19. 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

  20. 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

  1. New oligonucleotide microarray for rapid diagnosis of avian viral diseases.

    PubMed

    Sultankulova, Kulyaisan T; Kozhabergenov, Nurlan S; Strochkov, Vitaliy M; Burashev, Yerbol D; Shorayeva, Kamshat A; Chervyakova, Olga V; Rametov, Nurkuisa M; Sandybayev, Nurlan T; Sansyzbay, Abylay R; Orynbayev, Mukhit B

    2017-04-05

    We developed a new oligonucleotide microarray comprising 16 identical subarrays for simultaneous rapid detection of avian viruses: avian influenza virus (AIV), Newcastle disease virus (NDV), infection bronchitis virus (IBV), and infectious bursal disease virus (IBDV) in single- and mixed-virus infections. The objective of the study was to develop an oligonucleotide microarray for rapid diagnosis of avian diseases that would be used in the course of mass analysis for routine epidemiological surveillance owing to its ability to test one specimen for several infections. The paper describes the technique for rapid and simultaneous diagnosis of avian diseases such as avian influenza, Newcastle disease, infectious bronchitis and infectious bursal disease with use of oligonucleotide microarray, conditions for hybridization of fluorescent-labelled viral cDNA on the microarray and its specificity tested with use of AIV, NDV, IBV, IBDV strains as well as biomaterials from poultry. Sensitivity and specificity of the developed microarray was evaluated with use of 122 specimens of biological material: 44 cloacal swabs from sick birds and 78 tissue specimens from dead wild and domestic birds, as well as with use of 15 AIV, NDV, IBV and IBDV strains, different in their origin, epidemiological and biological characteristics (RIBSP Microbial Collection). This microarray demonstrates high diagnostic sensitivity (99.16% within 95% CI limits 97.36-100%) and specificity (100%). Specificity of the developed technique was confirmed by direct sequencing of NP and M (AIV), VP2 (IBDV), S1 (IBV), NP (NDV) gene fragments. Diagnostic effectiveness of the developed DNA microarray is 99.18% and therefore it can be used in mass survey for specific detection of AIV, NDV, IBV and IBDV circulating in the region in the course of epidemiological surveillance. Rather simple method for rapid diagnosis of avian viral diseases that several times shortens duration of assay versus classical diagnostic

  2. 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

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

    PubMed Central

    Yatskou, Mikalai; Novikov, Eugene; Vetter, Guillaume; Muller, Arnaud; Barillot, Emmanuel; Vallar, Laurent; Friederich, Evelyne

    2008-01-01

    Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP) using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5%) than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions. PMID:18798985

  4. Construction and validation of a Bovine Innate Immune Microarray

    PubMed Central

    Donaldson, Laurelea; Vuocolo, Tony; Gray, Christian; Strandberg, Ylva; Reverter, Antonio; McWilliam, Sean; Wang, YongHong; Byrne, Keren; Tellam, Ross

    2005-01-01

    Background Microarray transcript profiling has the potential to illuminate the molecular processes that are involved in the responses of cattle to disease challenges. This knowledge may allow the development of strategies that exploit these genes to enhance resistance to disease in an individual or animal population. Results The Bovine Innate Immune Microarray developed in this study consists of 1480 characterised genes identified by literature searches, 31 positive and negative control elements and 5376 cDNAs derived from subtracted and normalised libraries. The cDNA libraries were produced from 'challenged' bovine epithelial and leukocyte cells. The microarray was found to have a limit of detection of 1 pg/μg of total RNA and a mean slide-to-slide correlation co-efficient of 0.88. The profiles of differentially expressed genes from Concanavalin A (ConA) stimulated bovine peripheral blood lymphocytes were determined. Three distinct profiles highlighted 19 genes that were rapidly up-regulated within 30 minutes and returned to basal levels by 24 h; 76 genes that were up-regulated between 2–8 hours and sustained high levels of expression until 24 h and 10 genes that were down-regulated. Quantitative real-time RT-PCR on selected genes was used to confirm the results from the microarray analysis. The results indicate that there is a dynamic process involving gene activation and regulatory mechanisms re-establishing homeostasis in the ConA activated lymphocytes. The Bovine Innate Immune Microarray was also used to determine the cross-species hybridisation capabilities of an ovine PBL sample. Conclusion The Bovine Innate Immune Microarray has been developed which contains a set of well-characterised genes and anonymous cDNAs from a number of different bovine cell types. The microarray can be used to determine the gene expression profiles underlying innate immune responses in cattle and sheep. PMID:16176586

  5. 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

  6. 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

  7. 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.

  8. 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).

  9. 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.

  10. 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

  11. Inkjet printing for the production of protein microarrays.

    PubMed

    McWilliam, Iain; Chong Kwan, Marisa; Hall, Duncan

    2011-01-01

    A significant proportion of protein microarray researchers would like the arrays they develop to become widely used research, screening, validation or diagnostic devices. For this to be achievable the arrays must be compatible with high-throughput techniques that allow manufacturing scale production. In order to simplify the transition from laboratory bench to market, Arrayjet have developed a range of inkjet microarray printers, which, at one end of the scale, are suitable for R&D and, at the other end, are capable of true high-throughput array output. To maintain scalability, all Arrayjet microarray printers utilise identical core technology comprising a JetSpyder™ liquid handling adaptor, which enables automated loading of an industry standard inkjet printhead compatible with non-contact on-the-fly printing. This chapter contains a detailed explanation of Arrayjet technology followed by a historical look at the development of inkjet technologies for protein microarray production. The method described subsequently is a simple example of an antibody array printed onto nitrocellulose-coated slides with specific detection with fluorescently labelled IgG. The method is linked to a notes section with advice on best practice and sources of useful information for protein microarray production using inkjet technology.

  12. Women's experiences receiving abnormal prenatal chromosomal microarray testing results.

    PubMed

    Bernhardt, Barbara A; Soucier, Danielle; Hanson, Karen; Savage, Melissa S; Jackson, Laird; Wapner, Ronald J

    2013-02-01

    Genomic microarrays can detect copy-number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy-number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Participants were a subset of women participating in a multicenter prospective study "Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis." Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. As prenatal microarray testing is increasingly used, uncertain findings will be common, resulting in greater need for careful pre- and posttest counseling, and more education of and resources for providers so they can adequately support the women who are undergoing testing.

  13. Experiments using microarray technology: limitations and standard operating procedures.

    PubMed

    Forster, T; Roy, D; Ghazal, P

    2003-08-01

    Microarrays are a powerful method for the global analysis of gene or protein content and expression, opening up new horizons in molecular and physiological systems. This review focuses on the critical aspects of acquiring meaningful data for analysis following fluorescence-based target hybridisation to arrays. Although microarray technology is adaptable to the analysis of a range of biomolecules (DNA, RNA, protein, carbohydrates and lipids), the scheme presented here is applicable primarily to customised DNA arrays fabricated using long oligomer or cDNA probes. Rather than provide a comprehensive review of microarray technology and analysis techniques, both of which are large and complex areas, the aim of this paper is to provide a restricted overview, highlighting salient features to provide initial guidance in terms of pitfalls in planning and executing array projects. We outline standard operating procedures, which help streamline the analysis of microarray data resulting from a diversity of array formats and biological systems. We hope that this overview will provide practical initial guidance for those embarking on microarray studies.

  14. 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

  15. 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

  16. 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.

  17. Gene expression profiles in varicose veins using complementary DNA microarray.

    PubMed

    Lee, Seokjong; Lee, Wonchae; Choe, Yoonseok; Kim, Dowon; Na, Gunyeon; Im, Sanguk; Kim, Jinoh; Kim, Moonkyu; Kim, Jungchul; Cho, Joonyong

    2005-04-01

    There has been little information reported about the genetic event concerning the pathophysiology of varicose vein (VV). The purpose of this study was to examine the differentiation of gene expression in the wall of VV using complementary deoxyribonucleic acid (cDNA) microarrays. The study was performed with four pairs of VVs and control veins (CVs). cDNA specimens of VVs were prepared from the ribonucleic acid-isolated VVs of patients who underwent venous obliteration, using radiofrequency, as well as from CVs of those who underwent aortocoronary bypass grafting. Each set of VVs and CVs was hybridized with high-density microarray containing 3,063 human cDNAs. The finding of microarray hybridization were scanned, analyzed, and classified with the cluster program. Among 3,063 cDNA clones, 82 genes were up-regulated in VVs, and some of the up-regulated genes, which were detected by cDNA microarray, including transforming growth factor 3-induced gene (BIGH3), tubulin, lumican, actinin, collagen type I, versican, actin, and tropomyosin, belonged to extracelluar matrix molecules, cytoskeletal proteins, or myofibroblasts. Many up-regulated genes were found in Ws by applying cDNA microarray. These gene profiles suggested a pathway associated with fibrosis and that wound healing might be related to the pathophysiology of VVs.

  18. Development and characterization of a disposable plastic microarray printhead.

    PubMed

    Griessner, Matthias; Hartig, Dave; Christmann, Alexander; Pohl, Carsten; Schellhase, Michaela; Ehrentreich-Förster, Eva

    2011-06-01

    During the last decade microarrays have become a powerful analytical tool. Commonly microarrays are produced in a non-contact manner using silicone printheads. However, silicone printheads are expensive and not able to be used as a disposable. Here, we show the development and functional characterization of 8-channel plastic microarray printheads that overcome both disadvantages of their conventional silicone counterparts. A combination of injection-molding and laser processing allows us to produce a high quantity of cheap, customizable and disposable microarray printheads. The use of plastics (e.g., polystyrene) minimizes the need for surface modifications required previously for proper printing results. Time-consuming regeneration processes, cleaning procedures and contaminations caused by residual samples are avoided. The utilization of plastic printheads for viscous liquids, such as cell suspensions or whole blood, is possible. Furthermore, functional parts within the plastic printhead (e.g., particle filters) can be included. Our printhead is compatible with commercially available TopSpot devices but provides additional economic and technical benefits as compared to conventional TopSpot printheads, while fulfilling all requirements demanded on the latter. All in all, this work describes how the field of traditional microarray spotting can be extended significantly by low cost plastic printheads.

  19. Statistical approaches for the analysis of DNA methylation microarray data.

    PubMed

    Siegmund, Kimberly D

    2011-06-01

    Following the rapid development and adoption in DNA methylation microarray assays, we are now experiencing a growth in the number of statistical tools to analyze the resulting large-scale data sets. As is the case for other microarray applications, biases caused by technical issues are of concern. Some of these issues are old (e.g., two-color dye bias and probe- and array-specific effects), while others are new (e.g., fragment length bias and bisulfite conversion efficiency). Here, I highlight characteristics of DNA methylation that suggest standard statistical tools developed for other data types may not be directly suitable. I then describe the microarray technologies most commonly in use, along with the methods used for preprocessing and obtaining a summary measure. I finish with a section describing downstream analyses of the data, focusing on methods that model percentage DNA methylation as the outcome, and methods for integrating DNA methylation with gene expression or genotype data.

  20. Protein Microarrays with Novel Microfluidic Methods: Current Advances

    PubMed Central

    Dixit, Chandra K.; Aguirre, Gerson R.

    2014-01-01

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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. H5 avian influenza virus pathotyping using oligonucleotide microarray.

    PubMed

    Wang, Lih-Chiann; Huang, Dean; Cheng, Ming-Chu; Lee, Shu-Hwae; Wang, Ching-Ho

    2015-08-01

    The H5 avian influenza virus subtype has huge impact on the poultry industry. Rapid diagnosis and accurate identification of the highly pathogenic avian influenza virus and low-pathogenicity avian influenza virus is essential, especially during H5 outbreaks and surveillance. To this end, a novel and rapid strategy for H5 virus molecular pathotyping is presented. The specific hemagglutinin gene of the H5 virus and the basic amino acid number of the motif at the hemagglutinin precursor protein cleavage site were detected using oligonucleotide microarray. Highly pathogenic and low-pathogenicity avian influenza viruses in Taiwan were differentiated using 13 microarray probes with the naked eye. The detection limit reached 3.4 viral RNA copies, 1000 times more sensitive than reverse transcription polymerase chain reaction. Thus, the oligonucleotide microarray would provide an alternative H5 pathogenicity determination using the naked eye for laboratories lacking facilities. Copyright © 2015 Elsevier B.V. All rights reserved.

  6. Medical applications of microarray technologies: a regulatory science perspective.

    PubMed

    Petricoin, Emanuel F; Hackett, Joseph L; Lesko, Lawrence J; Puri, Raj K; Gutman, Steven I; Chumakov, Konstantin; Woodcock, Janet; Feigal, David W; Zoon, Kathryn C; Sistare, Frank D

    2002-12-01

    The potential medical applications of microarrays have generated much excitement, and some skepticism, within the biomedical community. Some researchers have suggested that within the decade microarrays will be routinely used in the selection, assessment, and quality control of the best drugs for pharmaceutical development, as well as for disease diagnosis and for monitoring desired and adverse outcomes of therapeutic interventions. Realizing this potential will be a challenge for the whole scientific community, as breakthroughs that show great promise at the bench often fail to meet the requirements of clinicians and regulatory scientists. The development of a cooperative framework among regulators, product sponsors, and technology experts will be essential for realizing the revolutionary promise that microarrays hold for drug development, regulatory science, medical practice and public health.

  7. 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

  8. Performance comparison of SLFN training algorithms for DNA microarray classification.

    PubMed

    Huynh, Hieu Trung; Kim, Jung-Ja; Won, Yonggwan

    2011-01-01

    The classification of biological samples measured by DNA microarrays has been a major topic of interest in the last decade, and several approaches to this topic have been investigated. However, till now, classifying the high-dimensional data of microarrays still presents a challenge to researchers. In this chapter, we focus on evaluating the performance of the training algorithms of the single hidden layer feedforward neural networks (SLFNs) to classify DNA microarrays. The training algorithms consist of backpropagation (BP), extreme learning machine (ELM) and regularized least squares ELM (RLS-ELM), and an effective algorithm called neural-SVD has recently been proposed. We also compare the performance of the neural network approaches with popular classifiers such as support vector machine (SVM), principle component analysis (PCA) and fisher discriminant analysis (FDA).

  9. D-MaPs - DNA-microarray projects: Web-based software for multi-platform microarray analysis

    PubMed Central

    2009-01-01

    The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix). Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus) submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner). In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core. PMID:21637530

  10. D-MaPs - DNA-microarray projects: Web-based software for multi-platform microarray analysis.

    PubMed

    Carazzolle, Marcelo F; Herig, Taís S; Deckmann, Ana C; Pereira, Gonçalo A G

    2009-07-01

    The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix). Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus) submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner). In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.

  11. Microarray analysis of papillary thyroid cancers in Korean.

    PubMed

    Kim, Hyun Sook; Kim, Do Hyung; Kim, Ji Yeon; Jeoung, Nam Ho; Lee, In Kyu; Bong, Jin Gu; Jung, Eui Dal

    2010-12-01

    Papillary thyroid cancer (PTC) is the most common malignancy of the thyroid gland. It involves several molecular mechanisms. The BRAF V600E mutation has been identified as the most common genetic abnormality in PTC. Moreover, it is known to be more prevalent in Korean PTC patients than in patients from other countries. We investigated distinct genetic profiles in Korean PTC through cDNA microarray analysis. Transcriptional profiles of five PTC samples and five paired normal thyroid tissue samples were generated using cDNA microarrays. The tumors were genotyped for BRAF mutations. The results of the cDNA microarray gene expression analysis were confirmed by real-time PCR and immunohistochemistry analysis of 35 PTC patients. Four of the five patients whose PTC tissues were subjected to microarray analysis were found to carry the BRAF V600E mutation. Microarrays analysis of the five PTC tissue samples showed the expression of 96 genes to be increased and that of 16 genes decreased. Real-time reverse transcription-polymerase chain reaction (RT-PCR) confirmed increased expression of SLC34A2, TM7SF4, COMP, KLK7, and KCNJ2 and decreased expression of FOXA2, SLC4A4, LYVE-1, and TFCP2L1 in PTC compared with normal tissue. Of these genes, TFCP2L1, LYVE-1, and KLK7 were previously unidentified in PTC microarray analysis. Notably, Foxa2 activity in PTC was reduced, as shown by its cytoplasmic localization, in immunohistochemical analyses. These findings demonstrate both similarities and differences between our results and previous reports. In Korean cases of PTC, Foxa2 activity was reduced with its cytoplasmic accumulation. Further studies are needed to confirm the relationship between FOXA2 and BRAF mutations in Korean cases of PTC.

  12. 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.

  13. Karyotype versus microarray testing for genetic abnormalities after stillbirth.

    PubMed

    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

    2012-12-06

    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. 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. 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. 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 and Human Development.).

  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. 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.

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

    SciTech Connect

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

    2007-03-08

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

  17. 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

  18. 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.

  19. Comparison of hydroxylated print additives on antibody microarray performance

    PubMed Central

    Wu, Peng; Grainger, David W.

    2008-01-01

    Various hydroxylated additives were added to antibody print buffers at different concentrations to stabilize printed antibodies during normal array spot desiccation on commercial polymer-coated microarray slides. Polyvinyl alcohol addition to print buffers produced the most regular spot morphologies, homogenous intra-spot antibody distribution, uniform fluorescence intensity, and improved analyte capture activity, maintained up to 1 month at 4°C for capturing model analytes, anti-human IL-1β, IL-4 and TNFα, on these microarraying slides. PMID:17081047

  20. 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.

  1. 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.

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

    PubMed

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

    2010-07-13

    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. 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. We present examples of files utilizing the schema and conversion of XML data (similar to the TMA DES) to OWL. 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.

  3. 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

  4. 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.

  5. 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

  6. 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

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

    USDA-ARS?s Scientific Manuscript database

    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 (...

  8. 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.

  9. Genomic and microarray approaches to coral reef conservation biology

    NASA Astrophysics Data System (ADS)

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

    2007-09-01

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

  10. 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...

  11. 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

  12. 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.

  13. 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.

  14. 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).

  15. 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.

  16. Large scale patterning of hydrogel microarrays using capillary pinning.

    PubMed

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

    2015-02-07

    Capillary barriers provide a simple and elegant means for autonomous fluid-flow control in microfluidic systems. In this work, we report on the fabrication of periodic hydrogel microarrays in closed microfluidic systems using non-fluorescent capillary barriers. This design strategy enables the fabrication of picoliter-volume patterns of photopolymerized and thermo-gelling hydrogels without any defects and distortions.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  18. 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

  19. 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).

  20. 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.

  1. Antibody microarrays for label-free cell-based applications.

    PubMed

    Milgram, Sarah; Bombera, Radoslaw; Livache, Thierry; Roupioz, Yoann

    2012-02-01

    The recent advances in microtechnologies have shown the interest of developing microarrays dedicated to cell analysis. In this way, miniaturized cell analyzing platforms use several detection techniques requiring specific solid supports for microarray read-out (colorimetric, fluorescent, electrochemical, acoustic, optical…). Real-time and label-free techniques, such as Surface Plasmon Resonance imaging (SPRi), arouse increasing interest for applications in miniaturized formats. Thus, we focused our study on chemical methods for antibody-based microarray fabrication dedicated to the SPRi analysis of cells or cellular activity. Three different approaches were designed and developed for specific applications. In the first case, a polypyrrole-based chemistry was used to array antibody-microarray for specific capture of whole living cells. In the second case, the polypyrrole-based chemistry was complexified in a three molecular level assembly using DNA and antibody conjugates to allow the specific release of cells after their capture. Finally, in the third case, a thiol-based chemistry was developed for long incubation times of biological samples of high complexity. This last approach was focused on the simultaneous study of both cell type characterization and secretory activity (detection of proteins secreted by cells). This paper describes three original methods allowing a rapid and efficient analysis of cellular sample on-chip using immunoaffinity-based assays. Copyright © 2011 Elsevier Inc. All rights reserved.

  2. 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. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. 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...

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

    PubMed

    von Götz, Franz

    2010-03-01

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

  5. Regularized gene selection in cancer microarray meta-analysis.

    PubMed

    Ma, Shuangge; Huang, Jian

    2009-01-01

    In cancer studies, it is common that multiple microarray experiments are conducted to measure the same clinical outcome and expressions of the same set of genes. An important goal of such experiments is to identify a subset of genes that can potentially serve as predictive markers for cancer development and progression. Analyses of individual experiments may lead to unreliable gene selection results because of the small sample sizes. Meta analysis can be used to pool multiple experiments, increase statistical power, and achieve more reliable gene selection. The meta analysis of cancer microarray data is challenging because of the high dimensionality of gene expressions and the differences in experimental settings amongst different experiments. We propose a Meta Threshold Gradient Descent Regularization (MTGDR) approach for gene selection in the meta analysis of cancer microarray data. The MTGDR has many advantages over existing approaches. It allows different experiments to have different experimental settings. It can account for the joint effects of multiple genes on cancer, and it can select the same set of cancer-associated genes across multiple experiments. Simulation studies and analyses of multiple pancreatic and liver cancer experiments demonstrate the superior performance of the MTGDR. The MTGDR provides an effective way of analyzing multiple cancer microarray studies and selecting reliable cancer-associated genes.

  6. 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

  7. 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.

  8. 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.

  9. Validation of the Swine Protein-Annotated Oligonucleotide Microarray

    USDA-ARS?s Scientific Manuscript database

    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. Native antigen fractionation protein microarrays for biomarker discovery.

    PubMed

    Caiazzo, Robert J; O'Rourke, Dennis J; Barder, Timothy J; Nelson, Bryce P; Liu, Brian C-S

    2011-01-01

    In this protocol, we used the T24 human bladder cancer cell line as a source of native antigens to construct fractionated lysate microarrays. Subsequently, these microarrays were used to compare the autoantibody responses of individuals with interstitial cystitis/painful bladder syndrome (IC/PBS) to those of normal female controls. To accomplish this, T24 cells were lysed under nondenaturing conditions to obtain native antigens. These native antigens were then fractionated in 2D using a PF-2D liquid chromatography; the first dimension separated the proteins by their isoelectric points, and the second separated them according to hydrophobicity. The resulting protein fractions were printed onto nitrocellulose-coated glass slides (PATH slides) to create a set of fractionated lysate microarrays. To compare the autoantibody responses of IC/PBS patients with normal controls, the fractionated lysate arrays were competitively hybridized with fluorescently labeled IgG samples purified from both IC/PBS and control sera. This protocol presents a detailed description of the creation and use of native antigen fractionated lysate microarrays for autoantibody profiling.

  11. 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.

  12. 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

  13. Mining pathway signatures from microarray data and relevant biological knowledge.

    PubMed

    Panteris, Eleftherios; Swift, Stephen; Payne, Annette; Liu, Xiaohui

    2007-12-01

    High-throughput technologies such as DNA microarray are in the process of revolutionizing the way modern biological research is being done. Bioinformatics tools are becoming increasingly important to assist biomedical scientists in their quest in understanding complex biological processes. Gene expression analysis has attracted a large amount of attention over the last few years mostly in the form of algorithms, exploring cluster and regulatory relationships among genes of interest, and programs that try to display the multidimensional microarray data in appropriate formats so that they make biological sense. To reduce the dimensionality of microarray data and make the corresponding analysis more biologically relevant, in this paper we propose a biologically-led approach to biochemical pathway analysis using microarray data and relevant biological knowledge. The method selects a subset of genes for each pathway that describes the behaviour of the pathway at a given experimental condition, and transforms them into pathway signatures. The metabolic pathways of Escherichia coli are used as a case study.

  14. 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.

  15. 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

  16. Gene expression profiling in peanut using oligonucleotide microarrays

    USDA-ARS?s Scientific Manuscript database

    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...

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

    USDA-ARS?s Scientific Manuscript database

    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. 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 ...

  19. 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).

  20. High quality protein microarray using in situ protein purification

    PubMed Central

    Kwon, Keehwan; Grose, Carissa; Pieper, Rembert; Pandya, Gagan A; Fleischmann, Robert D; Peterson, Scott N

    2009-01-01

    Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC). This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG) coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST) composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents protein solubility and

  1. 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

  2. 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

  3. Workflows for microarray data processing in the Kepler environment

    PubMed Central

    2012-01-01

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

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

    PubMed

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

    2012-05-17

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

  5. Challenges of microarray applications for microbial detection and gene expression profiling in food

    USDA-ARS?s Scientific Manuscript database

    Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

  6. 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...

  7. 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.

  8. 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...

  9. 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...

  10. 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.

  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. 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.

  14. 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

  15. Washing scaling of GeneChip microarray expression

    PubMed Central

    2010-01-01

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

  16. 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.

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

    PubMed

    Twellmeyer, Jens; Wende, Andy; Wolfertz, Jan; Pfeiffer, Friedhelm; Panhuysen, Markus; Zaigler, Alexander; Soppa, Jörg; Welzl, Gerhard; Oesterhelt, Dieter

    2007-10-24

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

  18. Microarray Analysis in the Archaeon Halobacterium salinarum Strain R1

    PubMed Central

    Twellmeyer, Jens; Wende, Andy; Wolfertz, Jan; Pfeiffer, Friedhelm; Panhuysen, Markus; Zaigler, Alexander; Soppa, Jörg; Welzl, Gerhard; Oesterhelt, Dieter

    2007-01-01

    Background Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. Methodology/Principal Findings We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. Conclusion/Significance This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis. PMID:17957248

  19. Combining results of microarray experiments: a rank aggregation approach.

    PubMed

    DeConde, Robert P; Hawley, Sarah; Falcon, Seth; Clegg, Nigel; Knudsen, Beatrice; Etzioni, Ruth

    2006-01-01

    As technology for microarray analysis becomes widespread, it is becoming increasingly important to be able to compare and combine the results of experiments that explore the same scientific question. In this article, we present a rank-aggregation approach for combining results from several microarray studies. The motivation for this approach is twofold; first, the final results of microarray studies are typically expressed as lists of genes, rank-ordered by a measure of the strength of evidence that they are functionally involved in the disease process, and second, using the information on this rank-ordered metric means that we do not have to concern ourselves with data on the actual expression levels, which may not be comparable across experiments. Our approach draws on methods for combining top-k lists from the computer science literature on meta-search. The meta-search problem shares several important features with that of combining microarray experiments, including the fact that there are typically few lists with many elements and the elements may not be common to all lists. We implement two meta-search algorithms, which use a Markov chain framework to convert pairwise preferences between list elements into a stationary distribution that represents an aggregate ranking (Dwork et al, 2001). We explore the behavior of the algorithms in hypothetical examples and a simulated dataset and compare their performance with that of an algorithm based on the order-statistics model of Thurstone (Thurstone, 1927). We apply all three algorithms to aggregate the results of five microarray studies of prostate cancer.

  20. 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»). Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

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

    PubMed

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

    2016-12-01

    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. 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. 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). 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 bone formation.Cite this article: J. J

  2. Diagnostic utility of microarray testing in pregnancy loss.

    PubMed

    Rosenfeld, J A; Tucker, M E; Escobar, L F; Neill, N J; Torchia, B S; McDaniel, L D; Schultz, R A; Chong, K; Chitayat, D

    2015-10-01

    To determine the frequency of clinically significant chromosomal abnormalities identified by chromosomal microarray in pregnancy losses at any gestational age and to compare microarray performance with that of traditional cytogenetic analysis when testing pregnancy losses. Among 535 fetal demise specimens of any gestational age, clinical microarray-based comparative genomic hybridization (aCGH) was performed successfully on 515, and a subset of 107 specimens underwent additional single nucleotide polymorphism (SNP) analysis. Overall, clinically significant abnormalities were identified in 12.8% (64/499) of specimens referred with normal or unknown karyotypes. Detection rates were significantly higher with earlier gestational age. In the subset with normal karyotype, clinically significant abnormalities were identified in 6.9% (20/288). This detection rate did not vary significantly with gestational age, suggesting that, unlike aneuploidy, the contribution of submicroscopic chromosomal abnormalities to fetal demise does not vary with gestational age. In the 107 specimens that underwent aCGH and SNP analysis, seven cases (6.5%) had abnormalities of potential clinical significance detected by the SNP component, including female triploidy. aCGH failed to yield fetal results in 8.3%, which is an improvement over traditional cytogenetic analysis of fetal demise specimens. Both the provision of results in cases in which karyotype fails and the detection of abnormalities in the presence of a normal karyotype demonstrate the increased diagnostic utility of microarray in pregnancy loss. Thus, chromosomal microarray testing is a preferable, robust method of analyzing cases of pregnancy loss to better delineate possible genetic etiologies, regardless of gestational age. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

  3. 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. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. High-Throughput Analysis of Serum Antigens Using Sandwich ELISAs on Microarrays

    SciTech Connect

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

    2009-05-11

    Enzyme-linked immunosorbent assay (ELISA) microarrays promise to be a powerful tool for the detection and validation of disease biomarkers. ELISA microarrays are capable of simultaneous detection of many proteins using a small sample volume. Although there are many potential pitfalls to the use of ELISA microarrays, these can be avoided by careful planning of experiments. In this chapter we describe a high-throughput protocol for processing ELISA microarrays that will result in reliable and reproducible data.

  5. 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

  6. 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.

  7. Incorporating Nonlinear Relationships in Microarray Missing Value Imputation.

    PubMed

    Yu, Tianwei; Peng, Hesen; Sun, Wei

    2011-01-01

    Microarray gene expression data often contain missing values. Accurate estimation of the missing values is important for downstream data analyses that require complete data. Nonlinear relationships between gene expression levels have not been well-utilized in missing value imputation. We propose an imputation scheme based on nonlinear dependencies between genes. By simulations based on real microarray data, we show that incorporating nonlinear relationships could improve the accuracy of missing value imputation, both in terms of normalized root-mean-squared error and in terms of the preservation of the list of significant genes in statistical testing. In addition, we studied the impact of artificial dependencies introduced by data normalization on the simulation results. Our results suggest that methods relying on global correlation structures may yield overly optimistic simulation results when the data have been subjected to row (gene)-wise mean removal.

  8. Incorporating nonlinear relationships in microarray missing value imputation

    PubMed Central

    Yu, Tianwei; Peng, Hesen; Sun, Wei

    2013-01-01

    Microarray gene expression data often contain missing values. Accurate estimation of the missing values is important for down-stream data analyses that require complete data. Nonlinear relationships between gene expression levels have not been well-utilized in missing value imputation. We propose an imputation scheme based on nonlinear dependencies between genes. By simulations based on real microarray data, we show that incorporating non-linear relationships could improve the accuracy of missing value imputation, both in terms of normalized root mean squared error and in terms of the preservation of the list of significant genes in statistical testing. In addition, we studied the impact of artificial dependencies introduced by data normalization on the simulation results. Our results suggest that methods relying on global correlation structures may yield overly optimistic simulation results when the data has been subjected to row (gene) – wise mean removal. PMID:20733236

  9. 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.

  10. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

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

  11. Picoliter-scale protein microarrays by laser direct write.

    PubMed

    Ringeisen, B R; Wu, P K; Kim, H; Piqué, A; Auyeung, R Y C; Young, H D; Chrisey, D B; Krizman, D B

    2002-01-01

    We demonstrate the accurate picoliter-scale dispensing of active proteins using a novel laser transfer technique. Droplets of protein solution are dispensed onto functionalized glass slides and into plastic microwells, activating as small as 50-microm diameter areas on these surfaces. Protein microarrays fabricated by laser transfer were assayed using standard fluorescent labeling techniques to demonstrate successful protein and antigen binding. These results indicate that laser transfer does not damage the active site of the dispensed protein and that this technique can be used to successfully fabricate a functioning protein microarray. Also, as a result of the efficient nature of the process, material usage is reduced by two to four orders of magnitude compared to conventional pin dispensing methods for protein spotting.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease

    PubMed Central

    Orihuela, Carlos J.; Radin, Jana N.; Sublett, Jack E.; Gao, Geli; Kaushal, Deepak; Tuomanen, Elaine I.

    2004-01-01

    Streptococcus pneumoniae is a leading cause of invasive bacterial disease. This is the first study to examine the expression of S. pneumoniae genes in vivo by using whole-genome microarrays available from The Institute for Genomic Research. Total RNA was collected from pneumococci isolated from infected blood, infected cerebrospinal fluid, and bacteria attached to a pharyngeal epithelial cell line in vitro. Microarray analysis of pneumococcal genes expressed in these models identified body site-specific patterns of expression for virulence factors, transporters, transcription factors, translation-associated proteins, metabolism, and genes with unknown function. Contributions to virulence predicted for several unknown genes with enhanced expression in vivo were confirmed by insertion duplication mutagenesis and challenge of mice with the mutants. Finally, we cross-referenced our results with previous studies that used signature-tagged mutagenesis and differential fluorescence induction to identify genes that are potentially required by a broad range of pneumococcal strains for invasive disease. PMID:15385455

  18. Matrix Factorization Methods Applied in Microarray Data Analysis

    PubMed Central

    Kossenkov, Andrew V.

    2010-01-01

    Numerous methods have been applied to microarray data to group genes into clusters that show similar expression patterns. These methods assign each gene to a single group, which does not reflect the widely held view among biologists that most, if not all, genes in eukaryotes are involved in multiple biological processes and therefore will be multiply regulated. Here, we review several methods that have been developed that are capable of identifying patterns of behavior in transcriptional response and assigning genes to multiple patterns. Broadly speaking, these methods define a series of mathematical approaches to matrix factorization with different approaches to the fitting of the model to the data. We focus on these methods in contrast to traditional clustering methods applied to microarray data, which assign one gene to one cluster. PMID:20376923

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

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

    PubMed

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

    2012-12-18

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

  5. Universal ligation-detection-reaction microarray applied for compost microbes

    PubMed Central

    Hultman, Jenni; Ritari, Jarmo; Romantschuk, Martin; Paulin, Lars; Auvinen, Petri

    2008-01-01

    Background Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR) based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones. Results Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS) area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array. Conclusion This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities. PMID:19116002

  6. 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

  7. Deoxyoligonucleotide microarrays for gene expression profiling in murine tooth germs.

    PubMed

    Osmundsen, Harald; Jevnaker, Anne-Marthe; Landin, Maria A

    2012-01-01

    The use of deoxyoligonucleotide microarrays facilitates rapid expression profiling of gene expression using samples of about 1 μg of total RNA. Here are described practical aspects of the procedures involved, including essential reagents. Analysis of results is discussed from a practical, experimental, point of view together with software required to carry out the required statistical analysis to isolate populations of differentially expressed genes.

  8. Application of click chemistry to the production of DNA microarrays.

    PubMed

    Uszczyńska, Barbara; Ratajczak, Tomasz; Frydrych, Emilia; Maciejewski, Hieronim; Figlerowicz, Marek; Markiewicz, Wojciech T; Chmielewski, Marcin K

    2012-03-21

    The copper-catalyzed alkyne-azide cycloaddition (CuAAC) reaction was applied as the novel method of DNA immobilization on a modified solid support. The CuAAC click reaction enables the covalent binding of DNA modified with pentynyl groups at its 5'-end to azide-loaded slides. Click microarrays were produced using this approach and successfully employed in biological/model experiments.

  9. A diagnostic oligonucleotide microarray for simultaneous detection of grapevine viruses.

    PubMed

    Engel, Esteban A; Escobar, Paula F; Rojas, Luis A; Rivera, Paulina A; Fiore, Nicola; Valenzuela, Pablo D T

    2010-02-01

    At least 58 viruses have been reported to infect grapevines causing economic damage globally. Conventional detection strategies based on serological assays, biological indexing and RT-PCR targeting one or few viruses in each assay are widely used. Grapevines are prone to contain mixed infections of several viruses, making the use of these techniques time-consuming. A 70-mer oligonucleotide microarray able to detect simultaneously a broad spectrum of known viruses as well as new viruses by cross-hybridization to highly conserved probes is reported in the present study. The array contains 570 unique probes designed against highly conserved and species-specific regions of 44 plant viral genomes. In addition probes designed against plant housekeeping genes are also included. By using a random primed RT-PCR amplification strategy of grapevine double stranded RNA-enriched samples, viral agents were detected in single and mixed infections. The microarray accuracy to detect 10 grapevine viruses was compared with RT-PCR yielding consistent results. For this purpose, grapevine samples containing single or mixed infections of Grapevine leafroll-associated virus-1, -2, -3, -4, -7, -9, Grapevine fanleaf virus, Grapevine rupestris stem pitting-associated virus, Grapevine virus A, and Grapevine virus B were used. Genomic libraries containing complete viral genomes were also used as part of the validation process. The specific probe hybridization pattern obtained from each virus makes this approach a powerful tool for high throughput plant certification purposes and also for virus discovery if the new viral genomic sequences have partial similarity with the microarray probes. Three Closteroviridae members (Grapevine leafroll-associated virus -4, -7 and -9) were detected for the first time in Chilean grapevines using the microarray. 2009 Elsevier B.V. All rights reserved.

  10. Chromatin immunoprecipitation and microarray-based analysis of protein location

    PubMed Central

    Lee, Tong Ihn; Johnstone, Sarah E; Young, Richard A

    2010-01-01

    Genome-wide location analysis, also known as ChIP-Chip, combines chromatin immunoprecipitation and DNA microarray analysis to identify protein-DNA interactions that occur in living cells. Protein-DNA interactions are captured in vivo by chemical crosslinking. Cell lysis, DNA fragmentation and immunoaffinity purification of the desired protein will co-purify DNA fragments that are associated with that protein. The enriched DNA population is then labeled, combined with a differentially labeled reference sample and applied to DNA microarrays to detect enriched signals. Various computational and bioinformatic approaches are then applied to normalize the enriched and reference channels, to connect signals to the portions of the genome that are represented on the DNA microarrays, to provide confidence metrics and to generate maps of protein-genome occupancy. Here, we describe the experimental protocols that we use from crosslinking of cells to hybridization of labeled material, together with insights into the aspects of these protocols that influence the results. These protocols require approximately 1 week to complete once sufficient numbers of cells have been obtained, and have been used to produce robust, high-quality ChIP-chip results in many different cell and tissue types. PMID:17406303

  11. High-Throughput Variation Detection and Genotyping Using Microarrays

    PubMed Central

    Cutler, David J.; Zwick, Michael E.; Carrasquillo, Minerva M.; Yohn, Christopher T.; Tobin, Katherine P.; Kashuk, Carl; Mathews, Debra J.; Shah, Nila A.; Eichler, Evan E.; Warrington, Janet A.; Chakravarti, Aravinda

    2001-01-01

    The genetic dissection of complex traits may ultimately require a large number of SNPs to be genotyped in multiple individuals who exhibit phenotypic variation in a trait of interest. Microarray technology can enable rapid genotyping of variation specific to study samples. To facilitate their use, we have developed an automated statistical method (ABACUS) to analyze microarray hybridization data and applied this method to Affymetrix Variation Detection Arrays (VDAs). ABACUS provides a quality score to individual genotypes, allowing investigators to focus their attention on sites that give accurate information. We have applied ABACUS to an experiment encompassing 32 autosomal and eight X-linked genomic regions, each consisting of ∼50 kb of unique sequence spanning a 100-kb region, in 40 humans. At sufficiently high-quality scores, we are able to read ∼80% of all sites. To assess the accuracy of SNP detection, 108 of 108 SNPs have been experimentally confirmed; an additional 371 SNPs have been confirmed electronically. To access the accuracy of diploid genotypes at segregating autosomal sites, we confirmed 1515 of 1515 homozygous calls, and 420 of 423 (99.29%) heterozygotes. In replicate experiments, consisting of independent amplification of identical samples followed by hybridization to distinct microarrays of the same design, genotyping is highly repeatable. In an autosomal replicate experiment, 813,295 of 813,295 genotypes are called identically (including 351 heterozygotes); at an X-linked locus in males (haploid), 841,236 of 841,236 sites are called identically. PMID:11691856

  12. Oligonucleotide microarray for the identification of potential mycotoxigenic fungi

    PubMed Central

    2010-01-01

    Background Mycotoxins are secondary metabolites which are produced by numerous fungi and pose a continuous challenge to the safety and quality of food commodities in South Africa. These toxins have toxicologically relevant effects on humans and animals that eat contaminated foods. In this study, a diagnostic DNA microarray was developed for the identification of the most common food-borne fungi, as well as the genes leading to toxin production. Results A total of 40 potentially mycotoxigenic fungi isolated from different food commodities, as well as the genes that are involved in the mycotoxin synthetic pathways, were analyzed. For fungal identification, oligonucleotide probes were designed by exploiting the sequence variations of the elongation factor 1-alpha (EF-1 α) coding regions and the internal transcribed spacer (ITS) regions of the rRNA gene cassette. For the detection of fungi able to produce mycotoxins, oligonucleotide probes directed towards genes leading to toxin production from different fungal strains were identified in data available in the public domain. The probes selected for fungal identification and the probes specific for toxin producing genes were spotted onto microarray slides. Conclusions The diagnostic microarray developed can be used to identify single pure strains or cultures of potentially mycotoxigenic fungi as well as genes leading to toxin production in both laboratory samples and maize-derived foods offering an interesting potential for microbiological laboratories. PMID:20307326

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. ArrayPipe: a flexible processing pipeline for microarray data

    PubMed Central

    Hokamp, Karsten; Roche, Fiona M.; Acab, Michael; Rousseau, Marc-Etienne; Kuo, Byron; Goode, David; Aeschliman, Dana; Bryan, Jenny; Babiuk, Lorne A.; Hancock, Robert E. W.; Brinkman, Fiona S. L.

    2004-01-01

    A number of microarray analysis software packages exist already; however, none combines the user-friendly features of a web-based interface with potential ability to analyse multiple arrays at once using flexible analysis steps. The ArrayPipe web server (freely available at www.pathogenomics.ca/arraypipe) allows the automated application of complex analyses to microarray data which can range from single slides to large data sets including replicates and dye-swaps. It handles output from most commonly used quantification software packages for dual-labelled arrays. Application features range from quality assessment of slides through various data visualizations to multi-step analyses including normalization, detection of differentially expressed genes, andcomparison and highlighting of gene lists. A highly customizable action set-up facilitates unrestricted arrangement of functions, which can be stored as action profiles. A unique combination of web-based and command-line functionality enables comfortable configuration of processes that can be repeatedly applied to large data sets in high throughput. The output consists of reports formatted as standard web pages and tab-delimited lists of calculated values that can be inserted into other analysis programs. Additional features, such as web-based spreadsheet functionality, auto-parallelization and password protection make this a powerful tool in microarray research for individuals and large groups alike. PMID:15215429

  18. A glance at DNA microarray technology and applications.

    PubMed

    Saei, Amir Ata; Omidi, Yadollah

    2011-01-01

    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. To pursue such aim, recently published papers and microarray softwares were reviewed. 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. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Novel R Pipeline for Analyzing Biolog Phenotypic Microarray Data

    PubMed Central

    Vehkala, Minna; Shubin, Mikhail; Connor, Thomas R; Thomson, Nicholas R; Corander, Jukka

    2015-01-01

    Data produced by Biolog Phenotype MicroArrays are longitudinal measurements of cells’ respiration on distinct substrates. We introduce a three-step pipeline to analyze phenotypic microarray data with novel procedures for grouping, normalization and effect identification. Grouping and normalization are standard problems in the analysis of phenotype microarrays defined as categorizing bacterial responses into active and non-active, and removing systematic errors from the experimental data, respectively. We expand existing solutions by introducing an important assumption that active and non-active bacteria manifest completely different metabolism and thus should be treated separately. Effect identification, in turn, provides new insights into detecting differing respiration patterns between experimental conditions, e.g. between different combinations of strains and temperatures, as not only the main effects but also their interactions can be evaluated. In the effect identification, the multilevel data are effectively processed by a hierarchical model in the Bayesian framework. The pipeline is tested on a data set of 12 phenotypic plates with bacterium Yersinia enterocolitica. Our pipeline is implemented in R language on the top of opm R package and is freely available for research purposes. PMID:25786143

  8. Multiple hybridization-extension sequencing (MHES) on microarray.

    PubMed

    Pan, Zhiqiang; Li, Yanqiang; Xiao, Pengfeng; Lu, Zuhong

    2007-11-01

    Sequencing-by-synthesis (SBS) by fluorescein-labelled nucleotide incorporating into a target DNA template has been greatly concerned on microarray. The extended fluorophore-base must be required to be quenched prior to sequencing the next one. However, the low quenching efficiency has been an obstacle in length-read. Here, we present a new sequencing strategy, multiple hybridization-extension sequencing (MHES), to resolve the above problem. First, the sequencing primers hybridize to the ssDNA template immobilized on microarray. The first 3-5 bases next to the primer's end are sequenced by SBS of Cy5-dNTP. The extended primers are rapidly removed by lambda DNA exonuclease. Then, the same primers hybridize to the same ssDNA templates again. The sequenced bases are polished by natural dNTP. The other 3-5 bases next to the polished primer's end are sequenced. According to this principle, the unknown sequences of a target DNA could be sequenced after primers' hybridization-extension multiple times. Although the fluorescein-labelled nucleotides are also needed, it is unnecessary to quench the fluorophore-bases in the process of sequencing. It has been successfully demonstrated that 10 bp fragment from synthetic template and 10 bp fragment from DTBNP1 gene were accurately sequenced. The new method has a great potential in read-length and high-throughput sequencing on microarray.

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

    PubMed Central

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-01-01

    The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch. PMID:17517778

  10. 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.

  11. 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.

  12. 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.

  13. LTR: Linear Cross-Platform Integration of Microarray Data

    PubMed Central

    Boutros, Paul C.

    2010-01-01

    The size and scope of microarray experiments continue to increase. However, datasets generated on different platforms or at different centres contain biases. Improved techniques are needed to remove platform- and batch-specific biases. One experimental control is the replicate hybridization of a subset of samples at each site or on each platform to learn the relationship between the two platforms. To date, no algorithm exists to specifically use this type of control. LTR is a linear-modelling-based algorithm that learns the relationship between different microarray batches from replicate hybridizations. LTR was tested on a new benchmark dataset of 20 samples hybridized to different Affymetrix microarray platforms. Before LTR, the two platforms were significantly different; application of LTR removed this bias. LTR was tested with six separate data pre-processing algorithms, and its effectiveness was independent of the pre-processing algorithm. Sample-size experiments indicate that just three replicate hybridizations can significantly reduce bias. An R library implementing LTR is available. PMID:20838609

  14. Statistical designs for two-color spotted microarray experiments.

    PubMed

    Chai, Feng-Shun; Liao, Chen-Tuo; Tsai, Shin-Fu

    2007-04-01

    Two-color cDNA or oligonucleotide-based spotted microarrays have been commonly used in measuring the expression levels of thousands of genes simultaneously. To realize the immense potential of this powerful new technology, budgeted within limited resources or other constraints, practical designs with high efficiencies are in demand. In this study, we address the design issue concerning the arrangement of the mRNA samples labeled with fluorescent dyes and hybridized on the slides. A normalization model is proposed to characterize major sources of systematic variation in a two-color microarray experiment. This normalization model establishes a connection between designs for two-color microarray experiments with a particular class of classical row-column designs. A heuristic algorithm for constructing A-optimal or highly efficient designs is provided. Statistical optimality results are found for some of the designs generated from the algorithm. It is believed that the constructed designs are the best or very close to the best possible for estimating the relative gene expression levels among the mRNA samples of interest.

  15. Detection and Identification of Mycobacterium Species Isolates by DNA Microarray

    PubMed Central

    Fukushima, Masao; Kakinuma, Kenichi; Hayashi, Hiroshi; Nagai, Hiroko; Ito, Kunihiko; Kawaguchi, Ryuji

    2003-01-01

    Rapid identification of Mycobacterium species isolates is necessary for the effective management of tuberculosis. Recently, analysis of DNA gyrase B subunit (gyrB) genes has been identified as a suitable means for the identification of bacterial species. We describe a microarray assay based on gyrB gene sequences that can be used for the identification of Mycobacteria species. Primers specific for a gyrB gene region common to all mycobacteria were synthesized and used for PCR amplification of DNA purified from clinical samples. A set of oligonucleotide probes for specific gyrB gene regions was developed for the identification of 14 Mycobacterium species. Each probe was spotted onto a silylated glass slide with an arrayer and used for hybridization with fluorescently labeled RNA derived from amplified sample DNA to yield a pattern of positive spots. This microarray produced unique hybridization patterns for each species of mycobacteria and could differentiate closely related bacterial species. Moreover, the results corresponded well with those obtained by the conventional culture method for the detection of mycobacteria. We conclude that a gyrB-based microarray can rapidly detect and identify closely related mycobacterial species and may be useful in the diagnosis and effective management of tuberculosis. PMID:12791887

  16. 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.

  17. DNA microarrays: translation of the genome from laboratory to clinic.

    PubMed

    Geschwind, Daniel H

    2003-05-01

    As the complete sequences of human and other mammalian genomes become available we are faced with the challenge of understanding how variation in sequence and gene expression contributes to neurological and psychiatric disorders. DNA microarrays, or DNA chips, provide the means to measure simultaneously where and when thousands of genes are expressed. Microarrays are changing the way that researchers approach work at the bench and have already yielded new insights into brain tumours, multiple sclerosis, acute neurological insults such as stroke and seizures, and schizophrenia. The study of disease-related changes in gene expression is the first step in the long process in translation of genome research to the clinic. Eventually, the changes observed in microarray studies will need to be independently confirmed and we wil need to understand how gene expression changes translate into functional effects at the cellular level in the nervous system. Progress in these studies will translate into array-based disease classification schemes and help optimise therapy for individual patients based on gene expression patterns or their genetic background.

  18. 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

  19. Microbial diagnostic microarray for food‐ and water‐borne pathogens

    PubMed Central

    Kostić, Tanja; Stessl, Beatrix; Wagner, Martin; Sessitsch, Angela; Bodrossy, Levente

    2010-01-01

    Summary A microbial diagnostic microarray for the detection of the most relevant bacterial food‐ and water‐borne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence‐specific end labelling of oligonucleotides and the pyhylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus/species level) and sensitive (0.1% relative and 104 cfu absolute detection sensitivity) detection of the target pathogens. Validation was performed using a set of reference strains and a set of spiked environmental samples. Reliability of the obtained data was additionally verified by independent analysis of the samples via fluorescence in situ hybridization (FISH) and conventional microbiological reference methods. The applicability of this diagnostic system for food analysis was demonstrated through extensive validation using artificially and naturally contaminated spiked food samples. The microarray‐based pathogen detection was compared with the corresponding microbiological reference methods (performed according to the ISO norm). Microarray results revealed high consistency with the reference microbiological data. PMID:21255342

  20. 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

  1. 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

  2. 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...

  3. 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...

  4. Peptide microarray patterning for controlling and monitoring cell growth.

    PubMed

    Lin, Edith; Sikand, Adhirath; Wickware, Jessica; Hao, Yubin; Derda, Ratmir

    2016-04-01

    The fate of cells is influenced by their microenvironment and many cell types undergo differentiation when stimulated by extracellular cues, such as soluble growth factors and the insoluble extracellular matrix (ECM). Stimulating differentiation by insoluble or "immobilized" cues is a particularly attractive method because it allows for the induction of differentiation in a spatially-defined cohort of cells within a larger subpopulation. To improve the design of de novo screening of such insoluble factors, we describe a methodology for producing high-density peptide microarrays suitable for extended cell culture and fluorescence microscopy. As a model, we used a murine mammary gland cell line (NMuMG) that undergoes epithelial to mesenchymal transition (EMT) in response to soluble transforming growth factor beta (TGF-β) and surface-immobilized peptides that target TGF-β receptors (TGFβRI/II). We repurposed a well-established DNA microarray printing technique to produce arrays of micropatterned surfaces that displayed TGFβRI/II-binding peptides and integrin binding peptides. Upon long-term culture on these arrays, only NMuMG cells residing on EMT-stimulating areas exhibited growth arrest and decreased E-cadherin expression. We believe that the methodology created in this report will aid the development of peptide-decorated surfaces that can locally stimulate defined cell surface receptors and control EMT and other well-characterized differentiation events. Scope of work: This manuscript aims to accelerate the development of instructive biomaterials decorated with specific ligands that target cell-surface receptors and induce specific differentiation of cells upon contact. These materials can be used for practical applications, such as fabricating synthetic materials for large scale, stem cell culture, or investigating differentiation and asymmetric division in stem cells. Specifically, in this manuscript, we repurposed a DNA microarray printer to produce

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Development of a genotyping microarray for Usher syndrome

    PubMed Central

    Cremers, Frans P M; Kimberling, William J; Külm, Maigi; de Brouwer, Arjan P; van Wijk, Erwin; te Brinke, Heleen; Cremers, Cor W R J; Hoefsloot, Lies H; Banfi, Sandro; Simonelli, Francesca; Fleischhauer, Johannes C; Berger, Wolfgang; Kelley, Phil M; Haralambous, Elene; Bitner‐Glindzicz, Maria; Webster, Andrew R; Saihan, Zubin; De Baere, Elfride; Leroy, Bart P; Silvestri, Giuliana; McKay, Gareth J; Koenekoop, Robert K; Millan, Jose M; Rosenberg, Thomas; Joensuu, Tarja; Sankila, Eeva‐Marja; Weil, Dominique; Weston, Mike D; Wissinger, Bernd; Kremer, Hannie

    2007-01-01

    Background Usher syndrome, a combination of retinitis pigmentosa (RP) and sensorineural hearing loss with or without vestibular dysfunction, displays a high degree of clinical and genetic heterogeneity. Three clinical subtypes can be distinguished, based on the age of onset and severity of the hearing impairment, and the presence or absence of vestibular abnormalities. Thus far, eight genes have been implicated in the syndrome, together comprising 347 protein‐coding exons. Methods: To improve DNA diagnostics for patients with Usher syndrome, we developed a genotyping microarray based on the arrayed primer extension (APEX) method. Allele‐specific oligonucleotides corresponding to all 298 Usher syndrome‐associated sequence variants known to date, 76 of which are novel, were arrayed. Results Approximately half of these variants were validated using original patient DNAs, which yielded an accuracy of >98%. The efficiency of the Usher genotyping microarray was tested using DNAs from 370 unrelated European and American patients with Usher syndrome. Sequence variants were identified in 64/140 (46%) patients with Usher syndrome type I, 45/189 (24%) patients with Usher syndrome type II, 6/21 (29%) patients with Usher syndrome type III and 6/20 (30%) patients with atypical Usher syndrome. The chip also identified two novel sequence variants, c.400C>T (p.R134X) in PCDH15 and c.1606T>C (p.C536S) in USH2A. Conclusion The Usher genotyping microarray is a versatile and affordable screening tool for Usher syndrome. Its efficiency will improve with the addition of novel sequence variants with minimal extra costs, making it a very useful first‐pass screening tool. PMID:16963483

  13. Microarray expression profiling in adhesion and normal peritoneal tissues.

    PubMed

    Ambler, Dana R; Golden, Alicia M; Gell, Jennifer S; Saed, Ghassan M; Carey, David J; Diamond, Michael P

    2012-05-01

    To identify molecular markers associated with adhesion and normal peritoneal tissue using microarray expression profiling. Comparative study. University hospital. Five premenopausal women. Adhesion and normal peritoneal tissue samples were obtained from premenopausal women. Ribonucleic acid was extracted using standard protocols and processed for hybridization to Affymetrix Whole Transcript Human Gene Expression Chips. Microarray data were obtained from five different patients, each with adhesion tissue and normal peritoneal samples. Real-time polymerase chain reaction was performed for confirmation using standard protocols. Gene expression in postoperative adhesion and normal peritoneal tissues. A total of 1,263 genes were differentially expressed between adhesion and normal tissues. One hundred seventy-three genes were found to be up-regulated and 56 genes were down-regulated in the adhesion tissues compared with normal peritoneal tissues. The genes were sorted into functional categories according to Gene Ontology annotations. Twenty-six up-regulated genes and 11 down-regulated genes were identified with functions potentially relevant to the pathophysiology of postoperative adhesions. We evaluated and confirmed expression of 12 of these specific genes via polymerase chain reaction. The pathogenesis, natural history, and optimal treatment of postoperative adhesive disease remains unanswered. Microarray analysis of adhesions identified specific genes with increased and decreased expression when compared with normal peritoneum. Knowledge of these genes and ontologic pathways with altered expression provide targets for new therapies to treat patients who have or are at risk for postoperative adhesions. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  14. 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.

  15. Supervised group Lasso with applications to microarray data analysis

    PubMed Central

    Ma, Shuangge; Song, Xiao; Huang, Jian

    2007-01-01

    Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

  16. 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.

  17. 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

  18. 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.

  19. 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.

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

    PubMed

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

    2016-11-30

    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.

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. Dimension reduction for classification with gene expression microarray data.

    PubMed

    Dai, Jian J; Lieu, Linh; Rocke, David

    2006-01-01

    An important application of gene expression microarray data is classification of biological samples or prediction of clinical and other outcomes. One necessary part of multivariate statistical analysis in such applications is dimension reduction. This paper provides a comparison study of three dimension reduction techniques, namely partial least squares (PLS), sliced inverse regression (SIR) and principal component analysis (PCA), and evaluates the relative performance of classification procedures incorporating those methods. A five-step assessment procedure is designed for the purpose. Predictive accuracy and computational efficiency of the methods are examined. Two gene expression data sets for tumor classification are used in the study.

  8. Recent discoveries and applications involving small-molecule microarrays.

    PubMed

    Hong, Jiyoung A; Neel, Dylan V; Wassaf, Dina; Caballero, Francisco; Koehler, Angela N

    2014-02-01

    High-throughput and unbiased binding assays have proven useful in probe discovery for a myriad of biomolecules, including targets of unknown structure or function and historically challenging target classes. Over the past decade, a number of novel formats for executing large-scale binding assays have been developed and used successfully in probe discovery campaigns. Here we review the use of one such format, the small-molecule microarray (SMM), as a tool for discovering protein-small molecule interactions. This review will briefly highlight selected recent probe discoveries using SMMs as well as novel uses of SMMs in profiling applications. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Sequential interim analyses of survival data in DNA microarray experiments

    PubMed Central

    2011-01-01

    Background Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Frequently, microarray studies are performed to identify genes of which the expression levels in pretherapeutic tissue samples are correlated to survival times of patients. Typically, such a study can take several years until the full planned sample size is available. Therefore, interim analyses are desirable, offering the possibility of stopping the study earlier, or of performing additional laboratory experiments to validate the role of the detected genes. While many methods correcting the multiple testing bias introduced by interim analyses have been proposed for studies of one single feature, there are still open questions about interim analyses of multiple features, particularly of high-dimensional microarray data, where the number of features clearly exceeds the number of samples. Therefore, we examine false discovery rates and power rates in microarray experiments performed during interim analyses of survival studies. In addition, the early stopping based on interim results of such studies is evaluated. As stop criterion we employ the achieved average power rate, i.e. the proportion of detected true positives, for which a new estimator is derived and compared to existing estimators. Results In a simulation study, pre-specified levels of the false discovery rate are maintained in each interim analysis, where reduced levels as used in classical group sequential designs of one single feature are not necessary. Average power rates increase with each interim analysis, and many studies can be stopped prior to their planned end when a certain pre-specified power rate is achieved. The new estimator for the power rate slightly deviates from the true power rate but is comparable to other estimators. Conclusions Interim analyses of microarray experiments can provide evidence for early stopping of

  10. 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.

  11. 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

  12. [Software development in data analysis and mining for cDNA microarray].

    PubMed

    Wu, Bin; Wang, Jianguo; Wang, Miqu

    2007-12-01

    Data analysis and mining is a key issue to microarray technology and is usually implemented through software development. This paper summarizes the state-of-art software development in cDNA microarray data analysis and mining. The updated software developments are discussed in three stages: data inquisition from cDNA microarray tests, statistical treatment of cDNA data and data mining from gene network.

  13. 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.

  14. 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.

  15. Model selection and efficiency testing for normalization of cDNA microarray data

    PubMed Central

    Futschik, Matthias; Crompton, Toni

    2004-01-01

    In this study we present two novel normalization schemes for cDNA microarrays. They are based on iterative local regression and optimization of model parameters by generalized cross-validation. Permutation tests assessing the efficiency of normalization demonstrated that the proposed schemes have an improved ability to remove systematic errors and to reduce variability in microarray data. The analysis also reveals that without parameter optimization local regression is frequently insufficient to remove systematic errors in microarray data. PMID:15287982

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

    PubMed

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

    2008-08-04

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

  17. 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.

  18. 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.

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

    PubMed

    Zhang, Zhe; Fenstermacher, David

    2005-01-01

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

  20. Feature extraction and signal processing for nylon DNA microarrays

    PubMed Central

    Lopez, F; Rougemont, J; Loriod, B; Bourgeois, A; Loï, L; Bertucci, F; Hingamp, P; Houlgatte, R; Granjeaud, S

    2004-01-01

    Background High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. Results We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis). Conclusions Our novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper. PMID:15222896

  1. 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

  2. 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

  3. 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

  4. Microarray analysis of R-gene-mediated resistance to viruses.

    PubMed

    Ishihara, Takeaki; Sato, Yukiyo; Takahashi, Hideki

    2015-01-01

    The complex process for host-plant resistance to viruses is precisely regulated by a number of genes and signaling compounds. Thus, global gene expression analysis can provide a powerful tool to grasp the complex molecular network for resistance to viruses. The procedures for comparative global gene expression profiling of virus-resistant and control plants by microarray analysis include RNA extraction, cDNA synthesis, cRNA labeling, hybridization, array scanning, and data mining steps. There are several platforms for the microarray analysis. Commercial services for the steps from cDNA synthesis to array scanning are now widely available; however, the data manipulation step is highly dependent on the experimental design and research focus. The protocols presented here are optimized for analyzing global gene expression during the R gene-conferred defense response using commercial oligonucleotide-based arrays. We also demonstrate a technique to screen for differentially expressed genes using Excel software and a simple Internet tool-based data mining approach for characterizing the identified genes.

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

    PubMed Central

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

    2014-01-01

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

  6. 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.

  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. 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

  9. 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

  10. 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 (

  11. Quantum Dots-based Reverse Phase Protein Microarray

    SciTech Connect

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

    2005-07-15

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

  12. 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. 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.

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

    PubMed

    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; Scanlan, David J; Paerl, Ryan W; Stuart, Rhona; Zehr, Jonathan P

    2014-07-01

    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.

  15. 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

  16. 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.

  17. ArrayD: A general purpose software for Microarray design

    PubMed Central

    Sharma, Anu; Srivastava, Gyan Prakash; Sharma, Vineet K; Ramachandran, Srinivasan

    2004-01-01

    Background Microarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted. Results We have developed a software called 'ArrayD' that offers various alternative design solutions for an array given a set of user requirements. The user feeds the following inputs: type of source plates to be used, number of gene probes to be printed, number of replicates and number of pins to be used for printing. The solutions are stored in a text file. The choice of a design solution to be used will be governed by the spotting chemistry to be used and the accuracy of the robot. Conclusions ArrayD is a software for standard cartesian robots. The software aids users in preparing a judicious and elegant design. ArrayD is universally applicable and is available at . PMID:15461789

  18. Kinship Testing Based on SNPs Using Microarray System.

    PubMed

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

    2016-11-01

    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. 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. 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. Our case showed that the utility of multiple SNPs on array is expected in practical forensic caseworks with an establishment of reference database.

  19. 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.

  20. 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.

  1. Protein microarrays using liquid phase fractionation of cell lysates.

    PubMed

    Yan, Fang; Sreekumar, Arun; Laxman, Bharathi; Chinnaiyan, Arul M; Lubman, David M; Barder, Timothy J

    2003-07-01

    We describe an approach in which protein microarrays are produced using a two-dimensional (2-D) liquid phase fractionation of cell lysates. The method involves a pI-based fractionation using chromatofocusing in the first dimension followed by nonporous reversed-phase high-performance liquid chromatography (HPLC) of each pI fraction in the second dimension. This allows fractionation of cellular proteins in the liquid phase that could then be arrayed on nitrocellulose slides and used to study humoral response in cancer. Protein microarrays have been used to identify potential serum biomarkers for prostate cancer. It is shown that specific fractions are immunoreactive against prostate cancer serum but not against serum from healthy individuals. These proteins could serve as sero-diagnostic markers for prostate cancer. Importantly, this method allows for use of post-translationally modified proteins as baits for detection of humoral response. Proteins eliciting an immune response are identified using the molecular mass and peptide sequence data obtained using mass spectrometric analysis of the liquid fractions. The fractionation of proteins in the liquid phase make this method amenable to automation.

  2. Differentiation of the seven major lyssavirus species by oligonucleotide microarray.

    PubMed

    Xi, Jin; Guo, Huancheng; Feng, Ye; Xu, Yunbin; Shao, Mingfu; Su, Nan; Wan, Jiayu; Li, Jiping; Tu, Changchun

    2012-03-01

    An oligonucleotide microarray, LyssaChip, has been developed and verified as a highly specific diagnostic tool for differentiation of the 7 major lyssavirus species. As with conventional typing microarray methods, the LyssaChip relies on sequence differences in the 371-nucleotide region coding for the nucleoprotein. This region was amplified using nested reverse transcription-PCR primers that bind to the 7 major lyssaviruses. The LyssaChip includes 57 pairs of species typing and corresponding control oligonucleotide probes (oligoprobes) immobilized on glass slides, and it can analyze 12 samples on a single slide within 8 h. Analysis of 111 clinical brain specimens (65 from animals with suspected rabies submitted to the laboratory and 46 of butchered dog brain tissues collected from restaurants) showed that the chip method was 100% sensitive and highly consistent with the "gold standard," a fluorescent antibody test (FAT). The chip method could detect rabies virus in highly decayed brain tissues, whereas the FAT did not, and therefore the chip test may be more applicable to highly decayed brain tissues than the FAT. LyssaChip may provide a convenient and inexpensive alternative for diagnosis and differentiation of rabies and rabies-related diseases.

  3. 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.

  4. Assessment of gene set analysis methods based on microarray data.

    PubMed

    Alavi-Majd, Hamid; Khodakarim, Soheila; Zayeri, Farid; Rezaei-Tavirani, Mostafa; Tabatabaei, Seyyed Mohammad; Heydarpour-Meymeh, Maryam

    2014-01-25

    Gene set analysis (GSA) incorporates biological information into statistical knowledge to identify gene sets differently expressed between two or more phenotypes. It allows us to gain an insight into the functional working mechanism of cells beyond the detection of differently expressed gene sets. In order to evaluate the competence of GSA approaches, three self-contained GSA approaches with different statistical methods were chosen; Category, Globaltest and Hotelling's T(2) together with their assayed power to identify the differences expressed via simulation and real microarray data. The Category does not take care of the correlation structure, while the other two deal with correlations. In order to perform these methods, R and Bioconductor were used. Furthermore, venous thromboembolism and acute lymphoblastic leukemia microarray data were applied. The results of three GSAs showed that the competence of these methods depends on the distribution of gene expression in a dataset. It is very important to assay the distribution of gene expression data before choosing the GSA method to identify gene sets differently expressed between phenotypes. On the other hand, assessment of common genes among significant gene sets indicated that there was a significant agreement between the result of GSA and the findings of biologists. © 2013 Elsevier B.V. All rights reserved.

  5. Impact of surface chemistry and blocking strategies on DNA microarrays.

    PubMed

    Taylor, Scott; Smith, Stephanie; Windle, Brad; Guiseppi-Elie, Anthony

    2003-08-15

    The surfaces and immobilization chemistries of DNA microarrays are the foundation for high quality gene expression data. Four surface modification chemistries, poly-L-lysine (PLL), 3-glycidoxypropyltrimethoxysilane (GPS), DAB-AM-poly(propyleminime hexadecaamine) dendrimer (DAB) and 3-aminopropyltrimethoxysilane (APS), were evaluated using cDNA and oligonucleotide sub-arrays. Two un-silanized glass surfaces, RCA-cleaned and immersed in Tris-EDTA buffer were also studied. DNA on amine-modified surfaces was fixed by UV (90 mJ/cm(2)), while DNA on GPS-modified surfaces was immobilized by covalent coupling. Arrays were blocked with either succinic anhydride (SA), bovine serum albumin (BSA) or left unblocked prior to hybridization with labeled PCR product. Quality factors evaluated were surface affinity for cDNA versus oligonucleotides, spot and background intensity, spotting concentration and blocking chemistry. Contact angle measurements and atomic force microscopy were preformed to characterize surface wettability and morphology. The GPS surface exhibited the lowest background intensity regardless of blocking method. Blocking the arrays did not affect raw spot intensity, but affected background intensity on amine surfaces, BSA blocking being the lowest. Oligonucleotides and cDNA on unblocked GPS-modified slides gave the best signal (spot-to-background intensity ratio). Under the conditions evaluated, the unblocked GPS surface along with amine covalent coupling was the most appropriate for both cDNA and oligonucleotide microarrays.

  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. Analysis of recursive gene selection approaches from microarray data.

    PubMed

    Li, Fan; Yang, Yiming

    2005-10-01

    Finding a small subset of most predictive genes from microarray for disease prediction is a challenging problem. Support vector machines (SVMs) have been found to be successful with a recursive procedure in selecting important genes for cancer prediction. However, it is not well understood how much of the success depends on the choice of the specific classifier and how much on the recursive procedure. We answer this question by examining multiple classifers [SVM, ridge regression (RR) and Rocchio] with feature selection in recursive and non-recursive settings on three DNA microarray datasets (ALL-AML Leukemia data, Breast Cancer data and GCM data). We found recursive RR most effective. On the AML-ALL dataset, it achieved zero error rate on the test set using only three genes (selected from over 7000), which is more encouraging than the best published result (zero error rate using 8 genes by recursive SVM). On the Breast Cancer dataset and the two largest categories of the GCM dataset, the results achieved by recursive RR are also very encouraging. A further analysis of the experimental results shows that different classifiers penalize redundant features to different extent and this property plays an important role in the recursive feature selection process. RR classifier tends to penalize redundant features to a much larger extent than the SVM does. This may be the reason why recursive RR has a better performance in selecting genes.

  8. Bayesian decomposition: analyzing microarray data within a biological context.

    PubMed

    Ochs, Michael F; Moloshok, Thomas D; Bidaut, Ghislain; Toby, Garabet

    2004-05-01

    The detection and correct identification of cancer, especially at an early stage, are vitally important for patient survival and quality of life. Since signaling pathways play critical roles in cancer development and metastasis, methods that reliably assess the activity of these pathways are critical to understand cancer and the response to therapy. Bayesian Decomposition (BD) identifies signatures of expression that can be linked directly to signaling pathway activity, allowing the changes in mRNA levels to be used as downstream indicators of pathway activity. Here, we demonstrate this ability by identifying the downstream expression signal associated with the mating response in Saccharomyces cerevisiae and showing that this signal disappears in deletion mutants of genes critical to the MAPK signaling cascade used to trigger the response. We also show the use of BD in the context of supervised learning, by analyzing the Mus musculus tissue-specific data set provided by Project Normal. The algorithm correctly removes routine metabolic processes, allowing tissue-specific signatures of expression to be identified. Gene ontology is used to interpret these signatures. Since a number of modern therapeutics specifically target signaling proteins, it is important to be able to identify changes in signaling pathways in order to use microarray data to interpret cancer response. By removing routine metabolic signatures and linking specific signatures to signaling pathway activity, BD makes it possible to link changes in microarray results to signaling pathways.

  9. Development of an oligonucleotide microarray method for Salmonella serotyping

    PubMed Central

    Tankouo‐Sandjong, B.; Sessitsch, A.; Stralis‐Pavese, N.; Liebana, E.; Kornschober, C.; Allerberger, F.; Hächler, H.; Bodrossy, L.

    2008-01-01

    Summary Adequate identification of Salmonella enterica serovars is a prerequisite for any epidemiological investigation. This is traditionally obtained via a combination of biochemical and serological typing. However, primary strain isolation and traditional serotyping is time‐consuming and faster methods would be desirable. A microarray, based on two housekeeping and two virulence marker genes (atpD, gyrB, fliC and fljB), has been developed for the detection and identification of the two species of Salmonella (S. enterica and S. bongori), the five subspecies of S. enterica (II, IIIa, IIIb, IV, VI) and 43 S. enterica ssp. enterica serovars (covering the most prevalent ones in Austria and the UK). A comprehensive set of probes (n = 240), forming 119 probe units, was developed based on the corresponding sequences of 148 Salmonella strains, successfully validated with 57 Salmonella strains and subsequently evaluated with 35 blind samples including isolated serotypes and mixtures of different serotypes. Results demonstrated a strong discriminatory ability of the microarray among Salmonella serovars. Threshold for detection was 1 colony forming unit per 25 g of food sample following overnight (14 h) enrichment. PMID:21261872

  10. [Design and realization of a microarray data analysis platform].

    PubMed

    Sun, Xian-He; Guo, Yun-Bo; Liu, Na; Ma, Li; Deng, Qin-Kai

    2011-04-01

    To design a platform for microarray data analysis and processing in the browser/server mode running in Linux operating system. Based on the Apache HTTP server, the platform, programmed with Perl language, integrated R language and Bioconductor packages for processing and analysis of the input data of oligonucleotide arrays and two-color spotted arrays. Users were allowed to submit data and parameter configurations to the platform via the web page, and the results of analysis were also returned via the web page. With an easy operation and high performance, the platform fulfilled the functions of processing, quality assessment, biological annotation and statistical analysis of the data from oligonucleotide arrays and two-color spotted arrays. Using the platform, we analyzed the gene expression profiles in Mtb-stimulated macrophages of three clinical phenotypes, namely latent TB (LTB), pulmonary (PTB) and meningeal (TBM), and obtained valuable clues for identifying tuberculosis susceptibility genes. We also analyzed the effect of INH treatment on Mycobacterium tuberculosis gene expression in various dormancy models, such as hypoxia and KatG mutant, and found that a set of genes responded to INH treatment during exponential growth but not in dormancy, and that the overall number of differentially regulated genes was reduced in the cells in low metabolic state. The platform we have constructed integrates comprehensive resources, and with a user-friendly interface, allows direct result visualization to facilitate microarray data analysis.

  11. Blood Signature of Pre-Heart Failure: A Microarrays Study

    PubMed Central

    Smih, Fatima; Desmoulin, Franck; Berry, Matthieu; Turkieh, Annie; Harmancey, Romain; Iacovoni, Jason; Trouillet, Charlotte; Delmas, Clement; Pathak, Atul; Lairez, Olivier; Koukoui, François; Massabuau, Pierre; Ferrieres, Jean; Galinier, Michel; Rouet, Philippe

    2011-01-01

    Background The preclinical stage of systolic heart failure (HF), known as asymptomatic left ventricular dysfunction (ALVD), is diagnosed only by echocardiography, frequent in the general population and leads to a high risk of developing severe HF. Large scale screening for ALVD is a difficult task and represents a major unmet clinical challenge that requires the determination of ALVD biomarkers. Methodology/Principal Findings 294 individuals were screened by echocardiography. We identified 9 ALVD cases out of 128 subjects with cardiovascular risk factors. White blood cell gene expression profiling was performed using pangenomic microarrays. Data were analyzed using principal component analysis (PCA) and Significant Analysis of Microarrays (SAM). To build an ALVD classifier model, we used the nearest centroid classification method (NCCM) with the ClaNC software package. Classification performance was determined using the leave-one-out cross-validation method. Blood transcriptome analysis provided a specific molecular signature for ALVD which defined a model based on 7 genes capable of discriminating ALVD cases. Analysis of an ALVD patients validation group demonstrated that these genes are accurate diagnostic predictors for ALVD with 87% accuracy and 100% precision. Furthermore, Receiver Operating Characteristic curves of expression levels confirmed that 6 out of 7 genes discriminate for left ventricular dysfunction classification. Conclusions/Significance These targets could serve to enhance the ability to efficiently detect ALVD by general care practitioners to facilitate preemptive initiation of medical treatment preventing the development of HF. PMID:21731613

  12. Identifying new human oocyte marker genes: a microarray approach

    PubMed Central

    Gasca, Stephan; Pellestor, Franck; Assou, Said; Loup, Vanessa; Anahory, Tal; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2007-01-01

    Efficiency in classical IVF (cIVF) techniques is still impaired by poor implantation and pregnancy rates after embryo transfer. This is mostly due to a lack of reliable criteria for the selection of embryos with sufficient development potential. Several studies have provided evidence that some genes’ expression levels could be used as objective markers of oocytes and embryos competence and of their capacity to sustain a successful pregnancy. These analyses usually used reverse transcription-polymerase chain reaction to look at small sets of pre-selected genes. However, microarray approaches permit to identify a wider range of cellular marker genes. Thus they allow the identification of additional and perhaps more suited genes that could serve as embryo selection markers. Microarray screenings of circa 30 000 genes on U133P Affymetrix™ gene chips made it possible to establish the expression profile of these genes as well as other related genes in human oocytes and cumulus cells. In this study, we identified new potential regulators and marker genes such as BARD1, RBL2, RBBP7, BUB3 or BUB1B, which are involved in oocyte maturation. PMID:17298719

  13. Identifying new human oocyte marker genes: a microarray approach.

    PubMed

    Gasca, Stéphan; Pellestor, Franck; Assou, Saïd; Loup, Vanessa; Anahory, Tal; Dechaud, Hervé; De Vos, John; Hamamah, Samir

    2007-02-01

    The efficacy of classical IVF techniques is still impaired by poor implantation and pregnancy rates after embryo transfer. This is mainly due to a lack of reliable criteria for the selection of embryos with sufficient development potential. Several studies have provided evidence that some gene expression levels could be used as objective markers of oocyte and embryo competence and capacity to sustain a successful pregnancy. These analyses usually use reverse transcription-polymerase chain reaction to look at small sets of pre-selected genes. However, microarray approaches allow the identification of a wider range of cellular marker genes which could include additional and perhaps more suitable genes that could serve as embryo selection markers. Microarray screenings of around 30,000 genes on U133P Affymetrix gene chips made it possible to establish the expression profile of these genes as well as other related genes in human oocytes and cumulus cells. This study identifies new potential regulators and marker genes such as BARD1, RBL2, RBBP7, BUB3 or BUB1B, which are involved in oocyte maturation.

  14. 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

  15. 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

  16. Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses.

    PubMed

    Griffith, Obi L; Pleasance, Erin D; Fulton, Debra L; Oveisi, Mehrdad; Ester, Martin; Siddiqui, Asim S; Jones, Steven J M

    2005-10-01

    Large amounts of gene expression data from several different technologies are becoming available to the scientific community. A common practice is to use these data to calculate global gene coexpression for validation or integration of other "omic" data. To assess the utility of publicly available datasets for this purpose we have analyzed Homo sapiens data from 1202 cDNA microarray experiments, 242 SAGE libraries, and 667 Affymetrix oligonucleotide microarray experiments. The three datasets compared demonstrate significant but low levels of global concordance (rc<0.11). Assessment against Gene Ontology (GO) revealed that all three platforms identify more coexpressed gene pairs with common biological processes than expected by chance. As the Pearson correlation for a gene pair increased it was more likely to be confirmed by GO. The Affymetrix dataset performed best individually with gene pairs of correlation 0.9-1.0 confirmed by GO in 74% of cases. However, in all cases, gene pairs confirmed by multiple platforms were more likely to be confirmed by GO. We show that combining results from different expression platforms increases reliability of coexpression. A comparison with other recently published coexpression studies found similar results in terms of performance against GO but with each method producing distinctly different gene pair lists.

  17. 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

  18. 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…

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

    USDA-ARS?s Scientific Manuscript database

    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...

  20. 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.

  1. Protein microarrays identify disease-specific anti-cytokine autoantibody profiles in the landscape of immunodeficiency

    PubMed Central

    Rosenberg, Jacob M.; Price, Jordan V.; Barcenas-Morales, Gabriela; Ceron-Gutierrez, Lourdes; Davies, Sophie; Kumararatne, Dinakantha S.; Döffinger, Rainer; Utz, Paul J.

    2015-01-01

    Background Anti-cytokine autoantibodies (ACAAs) are pathogenic in a handful of rare immunodeficiencies. However, the prevalence and significance of other ACAAs across immunodeficiencies have not yet been described. Objective We sought to profile ACAAs in a diverse cohort of serum samples from patients with immunodeficiency and assess the sensitivity and specificity of protein microarrays for ACAA identification and discovery. Methods Highly multiplexed protein microarrays were designed and fabricated. Blinded serum samples from a cohort of 58 patients with immunodeficiency and healthy control subjects were used to probe microarrays. Unsupervised hierarchical clustering was used to identify clusters of reactivity, and after unblinding, significance analysis of microarrays was used to identify disease-specific autoantibodies. A bead-based assay was used to validate protein microarray results. Blocking activity of serum containing ACAAs was measured in vitro. Results Protein microarrays were highly sensitive and specific for the detection of ACAAs in patients with autoimmune polyendocrine syndrome type I and pulmonary alveolar proteinosis, detecting ACAA levels consistent with those in the published literature. Protein microarray results were validated by using an independent bead-based assay. To confirm the functional significance of these ACAAs, we tested and confirmed the blocking activity of select ACAAs in vitro. Conclusion Protein microarrays are a powerful tool for ACAA detection and discovery, and they hold promise as a diagnostic for the evaluation and monitoring of clinical immunodeficiency. PMID:26365387

  2. 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…

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

    USDA-ARS?s Scientific Manuscript database

    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...

  4. 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.

  5. 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...

  6. Microarray analysis of acaricide inducible gene expression in the southern cattle tick, Rhipicephalus (Boophilus) microplus

    USDA-ARS?s Scientific Manuscript database

    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. PASE: a web-based platform for peptide/protein microarray experiments.

    PubMed

    Pamelard, Fabien; Even, Gael; Apostol, Costin; Preda, Cristian; Dhaenens, Clarisse; Fafeur, Vronique; Desmet, Rémi; Melnyk, Oleg

    2009-01-01

    Peptide microarray technology requires bioinformatics and statistical tools to manage, store, and analyze the large amount of data produced. To address these needs, we developed a system called protein array software environment (PASE) that provides an integrated framework to manage and analyze microarray information from polypeptide chip technologies.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  10. Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

    PubMed Central

    García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

    2012-01-01

    Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

  11. Assessing the utility of confirmatory studies following identification of large-scale genomic imbalances by microarray.

    PubMed

    Sanmann, Jennifer N; Pickering, Diane L; Golden, Denae M; Stevens, Jadd M; Hempel, Thomas E; Althof, Pamela A; Wiggins, Michele L; Starr, Lois J; Davé, Bhavana J; Sanger, Warren G

    2015-11-01

    The identification of clinically relevant genomic dosage anomalies assists in accurate diagnosis, prognosis, and medical management of affected individuals. Technological advancements within the field, such as the advent of microarray, have markedly increased the resolution of detection; however, clinical laboratories have maintained conventional techniques for confirmation of genomic imbalances identified by microarray to ensure diagnostic accuracy. In recent years the utility of this confirmatory testing of large-scale aberrations has been questioned but has not been scientifically addressed. We retrospectively reviewed 519 laboratory cases with genomic imbalances meeting reportable criteria by microarray and subsequently confirmed with a second technology, primarily fluorescence in situ hybridization. All genomic imbalances meeting reportable criteria detected by microarray were confirmed with a second technology. Microarray analysis generated no false-positive results. Confirmatory testing of large-scale genomic imbalances (deletion of ≥150 kb, duplication of ≥500 kb) solely for the purpose of microarray verification may be unwarranted. In some cases, however, adjunct testing is necessary to overcome limitations inherent to microarray. A recommended clinical strategy for adjunct testing following identified genomic imbalances using microarray is detailed.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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.