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Sample records for a-madman annotation-based microarray

  1. A-MADMAN: Annotation-based microarray data meta-analysis tool

    PubMed Central

    Bisognin, Andrea; Coppe, Alessandro; Ferrari, Francesco; Risso, Davide; Romualdi, Chiara; Bicciato, Silvio; Bortoluzzi, Stefania

    2009-01-01

    Background Publicly available datasets of microarray gene expression signals represent an unprecedented opportunity for extracting genomic relevant information and validating biological hypotheses. However, the exploitation of this exceptionally rich mine of information is still hampered by the lack of appropriate computational tools, able to overcome the critical issues raised by meta-analysis. Results This work presents A-MADMAN, an open source web application which allows the retrieval, annotation, organization and meta-analysis of gene expression datasets obtained from Gene Expression Omnibus. A-MADMAN addresses and resolves several open issues in the meta-analysis of gene expression data. Conclusion A-MADMAN allows i) the batch retrieval from Gene Expression Omnibus and the local organization of raw data files and of any related meta-information, ii) the re-annotation of samples to fix incomplete, or otherwise inadequate, metadata and to create user-defined batches of data, iii) the integrative analysis of data obtained from different Affymetrix platforms through custom chip definition files and meta-normalization. Software and documentation are available on-line at . PMID:19563634

  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. Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ricard-Blum, S.

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

  4. Chromosome Microarray.

    PubMed

    Anderson, Sharon

    2016-01-01

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

  5. DNA Microarrays

    NASA Astrophysics Data System (ADS)

    Nguyen, C.; Gidrol, X.

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

  6. 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. PMID:18430991

  7. Aptamer Microarrays

    SciTech Connect

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

    2009-01-02

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

  8. Microarrays, Integrated Analytical Systems

    NASA Astrophysics Data System (ADS)

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

  9. Microarrays in hematology.

    PubMed

    Walker, Josef; Flower, Darren; Rigley, Kevin

    2002-01-01

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

  10. Microarrays: an overview.

    PubMed

    Lee, Norman H; Saeed, Alexander I

    2007-01-01

    Gene expression microarrays are being used widely to address a myriad of complex biological questions. To gather meaningful expression data, it is crucial to have a firm understanding of the steps involved in the application of microarrays. The available microarray platforms are discussed along with their advantages and disadvantages. Additional considerations include study design, quality control and systematic assessment of microarray performance, RNA-labeling strategies, sample allocation, signal amplification schemes, defining the number of appropriate biological replicates, data normalization, statistical approaches to identify differentially regulated genes, and clustering algorithms for data visualization. In this chapter, the underlying principles regarding microarrays are reviewed, to serve as a guide when navigating through this powerful technology. PMID:17332646

  11. Microarrays--status and prospects.

    PubMed

    Venkatasubbarao, Srivatsa

    2004-12-01

    Microarrays have become an extremely important research tool for life science researchers and are also beginning to be used in diagnostic, treatment and monitoring applications. This article provides a detailed description of microarrays prepared by in situ synthesis, deposition using microspotting methods, nonplanar bead arrays, flow-through microarrays, optical fiber bundle arrays and nanobarcodes. The problems and challenges in the development of microarrays, development of standards and diagnostic microarrays are described. Tables summarizing the vendor list of various derivatized microarray surfaces, commercially sold premade microarrays, bead arrays and unique microarray products in development are also included. PMID:15542153

  12. Microarray Analysis in Glioblastomas.

    PubMed

    Bhawe, Kaumudi M; Aghi, Manish K

    2016-01-01

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

  13. Nanotechnologies in protein microarrays.

    PubMed

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

    2015-01-01

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

  14. 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…

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Microarrays under the microscope.

    PubMed

    Wildsmith, S E; Elcock, F J

    2001-02-01

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

  17. Navigating Public Microarray Databases

    PubMed Central

    Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  18. Navigating public microarray databases.

    PubMed

    Penkett, Christopher J; Bähler, Jürg

    2004-01-01

    With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources. PMID:18629145

  19. Tiling Microarray Analysis Tools

    SciTech Connect

    Nix, Davis Austin

    2005-05-04

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

  20. Compressive Sensing DNA Microarrays

    PubMed Central

    2009-01-01

    Compressive sensing microarrays (CSMs) are DNA-based sensors that operate using group testing and compressive sensing (CS) principles. In contrast to conventional DNA microarrays, in which each genetic sensor is designed to respond to a single target, in a CSM, each sensor responds to a set of targets. We study the problem of designing CSMs that simultaneously account for both the constraints from CS theory and the biochemistry of probe-target DNA hybridization. An appropriate cross-hybridization model is proposed for CSMs, and several methods are developed for probe design and CS signal recovery based on the new model. Lab experiments suggest that in order to achieve accurate hybridization profiling, consensus probe sequences are required to have sequence homology of at least 80% with all targets to be detected. Furthermore, out-of-equilibrium datasets are usually as accurate as those obtained from equilibrium conditions. Consequently, one can use CSMs in applications in which only short hybridization times are allowed. PMID:19158952

  1. 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

  2. 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. PMID:26614075

  3. Living-Cell Microarrays

    PubMed Central

    Yarmush, Martin L.; King, Kevin R.

    2011-01-01

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

  4. Tiling Microarray Analysis Tools

    Energy Science and Technology Software Center (ESTSC)

    2005-05-04

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

  5. Microarray platform for omics analysis

    NASA Astrophysics Data System (ADS)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

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

  6. 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

  7. Microarray Analysis of Microbial Weathering

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  8. The Stanford Tissue Microarray Database.

    PubMed

    Marinelli, Robert J; Montgomery, Kelli; Liu, Chih Long; Shah, Nigam H; Prapong, Wijan; Nitzberg, Michael; Zachariah, Zachariah K; Sherlock, Gavin J; Natkunam, Yasodha; West, Robert B; van de Rijn, Matt; Brown, Patrick O; Ball, Catherine A

    2008-01-01

    The Stanford Tissue Microarray Database (TMAD; http://tma.stanford.edu) is a public resource for disseminating annotated tissue images and associated expression data. Stanford University pathologists, researchers and their collaborators worldwide use TMAD for designing, viewing, scoring and analyzing their tissue microarrays. The use of tissue microarrays allows hundreds of human tissue cores to be simultaneously probed by antibodies to detect protein abundance (Immunohistochemistry; IHC), or by labeled nucleic acids (in situ hybridization; ISH) to detect transcript abundance. TMAD archives multi-wavelength fluorescence and bright-field images of tissue microarrays for scoring and analysis. As of July 2007, TMAD contained 205 161 images archiving 349 distinct probes on 1488 tissue microarray slides. Of these, 31 306 images for 68 probes on 125 slides have been released to the public. To date, 12 publications have been based on these raw public data. TMAD incorporates the NCI Thesaurus ontology for searching tissues in the cancer domain. Image processing researchers can extract images and scores for training and testing classification algorithms. The production server uses the Apache HTTP Server, Oracle Database and Perl application code. Source code is available to interested researchers under a no-cost license. PMID:17989087

  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. Characteristic attributes in cancer microarrays.

    PubMed

    Sarkar, I N; Planet, P J; Bael, T E; Stanley, S E; Siddall, M; DeSalle, R; Figurski, D H

    2002-04-01

    Rapid advances in genome sequencing and gene expression microarray technologies are providing unprecedented opportunities to identify specific genes involved in complex biological processes, such as development, signal transduction, and disease. The vast amount of data generated by these technologies has presented new challenges in bioinformatics. To help organize and interpret microarray data, new and efficient computational methods are needed to: (1) distinguish accurately between different biological or clinical categories (e.g., malignant vs. benign), and (2) identify specific genes that play a role in determining those categories. Here we present a novel and simple method that exhaustively scans microarray data for unambiguous gene expression patterns. Such patterns of data can be used as the basis for classification into biological or clinical categories. The method, termed the Characteristic Attribute Organization System (CAOS), is derived from fundamental precepts in systematic biology. In CAOS we define two types of characteristic attributes ('pure' and 'private') that may exist in gene expression microarray data. We also consider additional attributes ('compound') that are composed of expression states of more than one gene that are not characteristic on their own. CAOS was tested on three well-known cancer DNA microarray data sets for its ability to classify new microarray samples. We found CAOS to be a highly accurate and robust class prediction technique. In addition, CAOS identified specific genes, not emphasized in other analyses, that may be crucial to the biology of certain types of cancer. The success of CAOS in this study has significant implications for basic research and the future development of reliable methods for clinical diagnostic tools. PMID:12474425

  11. Microarrayed Materials for Stem Cells

    PubMed Central

    Mei, Ying

    2013-01-01

    Stem cells hold remarkable promise for applications in disease modeling, cancer therapy and regenerative medicine. Despite the significant progress made during the last decade, designing materials to control stem cell fate remains challenging. As an alternative, materials microarray technology has received great attention because it allows for high throughput materials synthesis and screening at a reasonable cost. Here, we discuss recent developments in materials microarray technology and their applications in stem cell engineering. Future opportunities in the field will also be reviewed. PMID:24311967

  12. Immunoprofiling Using NAPPA Protein Microarrays

    PubMed Central

    Sibani, Sahar; LaBaer, Joshua

    2012-01-01

    Protein microarrays provide an efficient method to immunoprofile patients in an effort to rapidly identify disease immunosignatures. The validity of using autoantibodies in diagnosis has been demonstrated in type 1 diabetes, rheumatoid arthritis, and systemic lupus, and is now being strongly considered in cancer. Several types of protein microarrays exist including antibody and antigen arrays. In this chapter, we describe the immunoprofiling application for one type of antigen array called NAPPA (nucleic acids programmable protein array). We provide a guideline for setting up the screening study and designing protein arrays to maximize the likelihood of obtaining quality data. PMID:21370064

  13. Microfluidic microarray systems and methods thereof

    DOEpatents

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

    2009-04-28

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

  14. Microarray analysis: Uses and Limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The use of microarray technology has exploded in resent years. All areas of biological research have found application for this powerful platform. From human disease studies to microbial detection systems, a plethora of uses for this technology are currently in place with new uses being developed ...

  15. Microarray Developed on Plastic Substrates.

    PubMed

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

    2016-01-01

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

  16. 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,…

  17. Biclustering of time series microarray data.

    PubMed

    Meng, Jia; Huang, Yufei

    2012-01-01

    Clustering is a popular data exploration technique widely used in microarray data analysis. In this chapter, we review ideas and algorithms of bicluster and its applications in time series microarray analysis. We introduce first the concept and importance of biclustering and its different variations. We then focus our discussion on the popular iterative signature algorithm (ISA) for searching biclusters in microarray dataset. Next, we discuss in detail the enrichment constraint time-dependent ISA (ECTDISA) for identifying biologically meaningful temporal transcription modules from time series microarray dataset. In the end, we provide an example of ECTDISA application to time series microarray data of Kaposi's Sarcoma-associated Herpesvirus (KSHV) infection. PMID:22130875

  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. Tissue microarrays: applications in genomic research.

    PubMed

    Watanabe, Aprill; Cornelison, Robert; Hostetter, Galen

    2005-03-01

    The widespread application of tissue microarrays in cancer research and the clinical pathology laboratory demonstrates a versatile and portable technology. The rapid integration of tissue microarrays into biomarker discovery and validation processes reflects the forward thinking of researchers who have pioneered the high-density tissue microarray. The precise arrangement of hundreds of archival clinical tissue samples into a composite tissue microarray block is now a proven method for the efficient and standardized analysis of molecular markers. With applications in cancer research, tissue microarrays are a valuable tool in validating candidate markers discovered in highly sensitive genome-wide microarray experiments. With applications in clinical pathology, tissue microarrays are used widely in immunohistochemistry quality control and quality assurance. The timeline of a biomarker implicated in prostate neoplasia, which was identified by complementary DNA expression profiling, validated by tissue microarrays and is now used as a prognostic immunohistochemistry marker, is reviewed. The tissue microarray format provides opportunities for digital imaging acquisition, image processing and database integration. Advances in digital imaging help to alleviate previous bottlenecks in the research pipeline, permit computer image scoring and convey telepathology opportunities for remote image analysis. The tissue microarray industry now includes public and private sectors with varying degrees of research utility and offers a range of potential tissue microarray applications in basic research, prognostic oncology and drug discovery. PMID:15833047

  1. 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

  2. Phenotypic MicroRNA Microarrays

    PubMed Central

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

    2013-01-01

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

  3. Microarray analysis in pulmonary hypertension.

    PubMed

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

    2016-07-01

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

  4. Self-Assembling Protein Microarrays

    NASA Astrophysics Data System (ADS)

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

    2004-07-01

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

  5. Optimisation algorithms for microarray biclustering.

    PubMed

    Perrin, Dimitri; Duhamel, Christophe

    2013-01-01

    In providing simultaneous information on expression profiles for thousands of genes, microarray technologies have, in recent years, been largely used to investigate mechanisms of gene expression. Clustering and classification of such data can, indeed, highlight patterns and provide insight on biological processes. A common approach is to consider genes and samples of microarray datasets as nodes in a bipartite graphs, where edges are weighted e.g. based on the expression levels. In this paper, using a previously-evaluated weighting scheme, we focus on search algorithms and evaluate, in the context of biclustering, several variations of Genetic Algorithms. We also introduce a new heuristic "Propagate", which consists in recursively evaluating neighbour solutions with one more or one less active conditions. The results obtained on three well-known datasets show that, for a given weighting scheme, optimal or near-optimal solutions can be identified. PMID:24109756

  6. Integrated Amplification Microarrays for Infectious Disease Diagnostics

    PubMed Central

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

    2012-01-01

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

  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. Living Cell Microarrays: An Overview of Concepts.

    PubMed

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

    2016-01-01

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

  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. 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.

  11. Protein microarrays as tools for functional proteomics.

    PubMed

    LaBaer, Joshua; Ramachandran, Niroshan

    2005-02-01

    Protein microarrays present an innovative and versatile approach to study protein abundance and function at an unprecedented scale. Given the chemical and structural complexity of the proteome, the development of protein microarrays has been challenging. Despite these challenges there has been a marked increase in the use of protein microarrays to map interactions of proteins with various other molecules, and to identify potential disease biomarkers, especially in the area of cancer biology. In this review, we discuss some of the promising advances made in the development and use of protein microarrays. PMID:15701447

  12. Photoelectrochemical synthesis of DNA microarrays

    PubMed Central

    Chow, Brian Y.; Emig, Christopher J.; Jacobson, Joseph M.

    2009-01-01

    Optical addressing of semiconductor electrodes represents a powerful technology that enables the independent and parallel control of a very large number of electrical phenomena at the solid-electrolyte interface. To date, it has been used in a wide range of applications including electrophoretic manipulation, biomolecule sensing, and stimulating networks of neurons. Here, we have adapted this approach for the parallel addressing of redox reactions, and report the construction of a DNA microarray synthesis platform based on semiconductor photoelectrochemistry (PEC). An amorphous silicon photoconductor is activated by an optical projection system to create virtual electrodes capable of electrochemically generating protons; these PEC-generated protons then cleave the acid-labile dimethoxytrityl protecting groups of DNA phosphoramidite synthesis reagents with the requisite spatial selectivity to generate DNA microarrays. Furthermore, a thin-film porous glass dramatically increases the amount of DNA synthesized per chip by over an order of magnitude versus uncoated glass. This platform demonstrates that PEC can be used toward combinatorial bio-polymer and small molecule synthesis. PMID:19706433

  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. 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...

  15. 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…

  16. Protein-Based Microarray for the Detection of Pathogenic Bacteria

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays have been used for gene expression and protein interaction studies, but recently, multianalyte diagnostic assays have employed the microarray platform. We developed a microarray immunoassay for bacteria, with biotinylated capture antibodies on streptavidin slides. To complete the fluor...

  17. 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

  18. DNA Microarrays for Identifying Fishes

    PubMed Central

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

    2008-01-01

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

  19. 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

  20. 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. PMID:27190571

  1. DNA Microarrays in Herbal Drug Research

    PubMed Central

    Chavan, Preeti; Joshi, Kalpana; Patwardhan, Bhushan

    2006-01-01

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

  2. 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

  3. AMIC@: All MIcroarray Clusterings @ once

    PubMed Central

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

    2008-01-01

    The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica. PMID:18477631

  4. AMIC@: All MIcroarray Clusterings @ once.

    PubMed

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

    2008-07-01

    The AMIC@ Web Server offers a light-weight multi-method clustering engine for microarray gene-expression data. AMIC@ is a highly interactive tool that stresses user-friendliness and robustness by adopting AJAX technology, thus allowing an effective interleaved execution of different clustering algorithms and inspection of results. Among the salient features AMIC@ offers, there are: (i) automatic file format detection, (ii) suggestions on the number of clusters using a variant of the stability-based method of Tibshirani et al. (iii) intuitive visual inspection of the data via heatmaps and (iv) measurements of the clustering quality using cluster homogeneity. Large data sets can be processed efficiently by selecting algorithms (such as FPF-SB and k-Boost), specifically designed for this purpose. In case of very large data sets, the user can opt for a batch-mode use of the system by means of the Clustering wizard that runs all algorithms at once and delivers the results via email. AMIC@ is freely available and open to all users with no login requirement at the following URL http://bioalgo.iit.cnr.it/amica. PMID:18477631

  5. 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. PMID:26134183

  6. DNA microarrays in prostate cancer.

    PubMed

    Ho, Shuk-Mei; Lau, Kin-Mang

    2002-02-01

    DNA microarray technology provides a means to examine large numbers of molecular changes related to a biological process in a high throughput manner. This review discusses plausible utilities of this technology in prostate cancer research, including definition of prostate cancer predisposition, global profiling of gene expression patterns associated with cancer initiation and progression, identification of new diagnostic and prognostic markers, and discovery of novel patient classification schemes. The technology, at present, has only been explored in a limited fashion in prostate cancer research. Some hurdles to be overcome are the high cost of the technology, insufficient sample size and repeated experiments, and the inadequate use of bioinformatics. With the completion of the Human Genome Project and the advance of several highly complementary technologies, such as laser capture microdissection, unbiased RNA amplification, customized functional arrays (eg, single-nucleotide polymorphism chips), and amenable bioinformatics software, this technology will become widely used by investigators in the field. The large amount of novel, unbiased hypotheses and insights generated by this technology is expected to have a significant impact on the diagnosis, treatment, and prevention of prostate cancer. Finally, this review emphasizes existing, but currently underutilized, data-mining tools, such as multivariate statistical analyses, neural networking, and machine learning techniques, to stimulate wider usage. PMID:12084220

  7. Quality Visualization of Microarray Datasets Using Circos

    PubMed Central

    Koch, Martin; Wiese, Michael

    2012-01-01

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

  8. Microarray: an approach for current drug targets.

    PubMed

    Gomase, Virendra S; Tagore, Somnath; Kale, Karbhari V

    2008-03-01

    Microarrays are a powerful tool has multiple applications both in clinical and cellular and molecular biology arenas. Early assessment of the probable biological importance of drug targets, pharmacogenomics, toxicogenomics and single nucleotide polymorphisms (SNPs). A list of new drug candidates along with proposed targets for intervention is described. Recent advances in the knowledge of microarrays analysis of organisms and the availability of the genomics sequences provide a wide range of novel targets for drug design. This review gives different process of microarray technologies; methods for comparative gene expression study, applications of microarrays in medicine and pharmacogenomics and current drug targets in research, which are relevant to common diseases as they relate to clinical and future perspectives. PMID:18336225

  9. Contributions to Statistical Problems Related to Microarray Data

    ERIC Educational Resources Information Center

    Hong, Feng

    2009-01-01

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

  10. Evaluation of Surface Chemistries for Antibody Microarrays

    SciTech Connect

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

    2007-12-01

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

  11. 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

  12. 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

  13. Quantifying the Antibody Binding on Protein Microarrays using Microarray Nonlinear Calibration

    PubMed Central

    Yu, Xiaobo; Wallstrom, Garrick; Magee, Dewey Mitchell; Qiu, Ji; Mendoza, D. Eliseo A.; Wang, Jie; Bian, Xiaofang; Graves, Morgan; LaBaer, Joshua

    2015-01-01

    To address the issue of quantification for antibody assays with protein microarrays, we firstly developed a Microarray Nonlinear Calibration (MiNC) method that applies in the quantification of antibody binding to the surface of microarray spots. We found that MiNC significantly increased the linear dynamic range and reduced assay variations. A serological analysis of guinea pig Mycobacterium tuberculosis models showed that a larger number of putative antigen targets were identified with MiNC, which is consistent with the improved assay performance of protein microarrays. We expect that our cumulative results will provide scientists with a new appreciation of antibody assays with protein microarrays. Our MiNC method has the potential to be employed in biomedical research with multiplex antibody assays which need quantitation, including the discovery of antibody biomarkers, clinical diagnostics with multi-antibody signatures and construction of immune mathematical models. PMID:23662896

  14. PERFORMANCE CHARACTERISTICS OF 65-MER OLIGONUCLEOTIDE MICROARRAYS

    PubMed Central

    Lee, Myoyong; Xiang, Charlie C.; Trent, Jeffrey M.; Bittner, Michael L.

    2009-01-01

    Microarray fabrication using pre-synthesized long oligonucleotide is becoming increasingly important, but a study of large-scale array productions is not published yet. We addressed the issue of fabricating oligonucleotide microarrays by spotting commercial, pre-synthesized 65-mers with 5′ amines representing 7500 murine genes. Amine-modified oligonucleotides were immobilized on glass slides having aldehyde groups via transient Schiff base formation followed by reduction to produce a covalent conjugate. When RNA derived from the same source was used for Cy3 and Cy5 labeling and hybridized to the same array, signal intensities spanning three orders of magnitude were observed, and the coefficient of variation between the two channels for all spots was 8–10%. To ascertain the reproducibility of ratio determination of these arrays, two triplicate hybridizations (with fluorochrome reversal) comparing RNAs from a fibroblast (NIH3T3) and a breast cancer (JC) cell line were carried out. The 95% confidence interval for all spots in the six hybridizations was 0.60 – 1.66. This level of reproducibility allows use of the full range of pattern finding and discriminant analysis typically applied to cDNA microarrays. Further comparative testing was carried out with oligonucleotide microarrays, cDNA microarrays and RT-PCR assays to examine the comparability of results across these different methodologies. PMID:17617369

  15. Advancing microarray assembly with acoustic dispensing technology.

    PubMed

    Wong, E Y; Diamond, S L

    2009-01-01

    In the assembly of microarrays and microarray-based chemical assays and enzymatic bioassays, most approaches use pins for contact spotting. Acoustic dispensing is a technology capable of nanoliter transfers by using acoustic energy to eject liquid sample from an open source well. Although typically used for well plate transfers, when applied to microarraying, it avoids the drawbacks of undesired physical contact with the sample; difficulty in assembling multicomponent reactions on a chip by readdressing, a rigid mode of printing that lacks patterning capabilities; and time-consuming wash steps. We demonstrated the utility of acoustic dispensing by delivering human cathepsin L in a drop-on-drop fashion into individual 50-nanoliter, prespotted reaction volumes to activate enzyme reactions at targeted positions on a microarray. We generated variable-sized spots ranging from 200 to 750 microm (and higher) and handled the transfer of fluorescent bead suspensions with increasing source well concentrations of 0.1 to 10 x 10(8) beads/mL in a linear fashion. There are no tips that can clog, and liquid dispensing CVs are generally below 5%. This platform expands the toolbox for generating analytical arrays and meets needs associated with spatially addressed assembly of multicomponent microarrays on the nanoliter scale. PMID:19035650

  16. A Synthetic Kinome Microarray Data Generator

    PubMed Central

    Maleki, Farhad; Kusalik, Anthony

    2015-01-01

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

  17. Long synthetic oligonucleotides for microarray expression measurement

    NASA Astrophysics Data System (ADS)

    Li, Jiong; Wang, Hong; Liu, Heping; Zhang, M.; Zhang, Chunxiu; Lu, Zu-Hong; Gao, Xiang; Kong, Dong

    2001-09-01

    There are generally two kinds of DNA microarray used for genomic-scale gene expression profiling of mRNA: cDNA and DNA chip, but both of them suffer from some drawbacks. To meet more requirements, another oligonucleotide microarray with long was produced. This type of microarray had the advantages of low cost, minimal Cross-hybridization, flexible and easy to make, which is most fit for small laboratories with special purposes. In this paper, we devised different probes with different probe lengths, GC contents and gene positions to optimization the probe design. Experiments showed 70 mer probes are suitable for both sufficient sensitivity and reasonable costs. Higher G-C content produces stronger signal intensity thus better sensitivity and probes designed at 3 untranslated region of gene within the range of 300 pb should be best for both sensitivity and specificity.

  18. Protein microarrays for parasite antigen discovery.

    PubMed

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

    2015-01-01

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

  19. Applications of protein microarrays for biomarker discovery

    PubMed Central

    Ramachandran, Niroshan; Srivastava, Sanjeeva; LaBaer, Joshua

    2011-01-01

    The search for new biomarkers for diagnosis, prognosis and therapeutic monitoring of diseases continues in earnest despite dwindling success at finding novel reliable markers. Some of the current markers in clinical use do not provide optimal sensitivity and specificity, with the prostate cancer antigen (PSA) being one of many such examples. The emergence of proteomic techniques and systems approaches to study disease pathophysiology has rekindled the quest for new biomarkers. In particular the use of protein microarrays has surged as a powerful tool for large scale testing of biological samples. Approximately half the reports on protein microarrays have been published in the last two years especially in the area of biomarker discovery. In this review, we will discuss the application of protein microarray technologies that offer unique opportunities to find novel biomarkers. PMID:21136793

  20. 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

  1. 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).

  2. 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. PMID:23288464

  3. 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

  4. Pineal function: impact of microarray analysis.

    PubMed

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

    2010-01-27

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

  5. MicroRNA expression profiling using microarrays.

    PubMed

    Love, Cassandra; Dave, Sandeep

    2013-01-01

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

  6. 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.

  7. Transcriptome sequencing and microarray design for functional genomics in the extremophile Arabidopsis relative Thellungiella salsuginea (Eutrema salsugineum)

    PubMed Central

    2013-01-01

    Background Most molecular studies of plant stress tolerance have been performed with Arabidopsis thaliana, although it is not particularly stress tolerant and may lack protective mechanisms required to survive extreme environmental conditions. Thellungiella salsuginea has attracted interest as an alternative plant model species with high tolerance of various abiotic stresses. While the T. salsuginea genome has recently been sequenced, its annotation is still incomplete and transcriptomic information is scarce. In addition, functional genomics investigations in this species are severely hampered by a lack of affordable tools for genome-wide gene expression studies. Results Here, we report the results of Thellungiella de novo transcriptome assembly and annotation based on 454 pyrosequencing and development and validation of a T. salsuginea microarray. ESTs were generated from a non-normalized and a normalized library synthesized from RNA pooled from samples covering different tissues and abiotic stress conditions. Both libraries yielded partially unique sequences, indicating their necessity to obtain comprehensive transcriptome coverage. More than 1 million sequence reads were assembled into 42,810 unigenes, approximately 50% of which could be functionally annotated. These unigenes were compared to all available Thellungiella genome sequence information. In addition, the groups of Late Embryogenesis Abundant (LEA) proteins, Mitogen Activated Protein (MAP) kinases and protein phosphatases were annotated in detail. We also predicted the target genes for 384 putative miRNAs. From the sequence information, we constructed a 44 k Agilent oligonucleotide microarray. Comparison of same-species and cross-species hybridization results showed superior performance of the newly designed array for T. salsuginea samples. The developed microarrays were used to investigate transcriptional responses of T. salsuginea and Arabidopsis during cold acclimation using the MapMan software

  8. 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...

  9. 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...

  10. Microarrays (DNA Chips) for the Classroom Laboratory

    ERIC Educational Resources Information Center

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

    2006-01-01

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

  11. 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...

  12. Microarray data classified by artificial neural networks.

    PubMed

    Linder, Roland; Richards, Tereza; Wagner, Mathias

    2007-01-01

    Systems biology has enjoyed explosive growth in both the number of people participating in this area of research and the number of publications on the topic. The field of systems biology encompasses the in silico analysis of high-throughput data as provided by DNA or protein microarrays. Along with the increasing availability of microarray data, attention is focused on methods of analyzing the expression rates. One important type of analysis is the classification task, for example, distinguishing different types of cell functions or tumors. Recently, interest has been awakened toward artificial neural networks (ANN), which have many appealing characteristics such as an exceptional degree of accuracy. Nonlinear relationships or independence from certain assumptions regarding the data distribution are also considered. The current work reviews advantages as well as disadvantages of neural networks in the context of microarray analysis. Comparisons are drawn to alternative methods. Selected solutions are discussed, and finally algorithms for the effective combination of multiple ANNs are presented. The development of approaches to use ANN-processed microarray data applicable to run cell and tissue simulations may be slated for future investigation. PMID:18220242

  13. Data Analysis Strategies for Protein Microarrays

    PubMed Central

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

    2012-01-01

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

  14. 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.

  15. 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.

  16. Raman-based microarray readout: a review.

    PubMed

    Haisch, Christoph

    2016-07-01

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

  17. 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.

  18. Microarray analysis at single molecule resolution

    PubMed Central

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

    2010-01-01

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

  19. Facilitating functional annotation of chicken microarray data

    PubMed Central

    2009-01-01

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

  20. 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

  1. 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

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

    PubMed

    Yu, Xiaobo; Petritis, Brianne; LaBaer, Joshua

    2016-04-01

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

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

    PubMed Central

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

    2016-01-01

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

  4. 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. Immobilization Techniques for Microarray: Challenges and Applications

    PubMed Central

    Nimse, Satish Balasaheb; Song, Keumsoo; Sonawane, Mukesh Digambar; Sayyed, Danishmalik Rafiq; Kim, Taisun

    2014-01-01

    The highly programmable positioning of molecules (biomolecules, nanoparticles, nanobeads, nanocomposites materials) on surfaces has potential applications in the fields of biosensors, biomolecular electronics, and nanodevices. However, the conventional techniques including self-assembled monolayers fail to position the molecules on the nanometer scale to produce highly organized monolayers on the surface. The present article elaborates different techniques for the immobilization of the biomolecules on the surface to produce microarrays and their diagnostic applications. The advantages and the drawbacks of various methods are compared. This article also sheds light on the applications of the different technologies for the detection and discrimination of viral/bacterial genotypes and the detection of the biomarkers. A brief survey with 115 references covering the last 10 years on the biological applications of microarrays in various fields is also provided. PMID:25429408

  6. Use of microarray technologies in toxicology research.

    PubMed

    Vrana, Kent E; Freeman, Willard M; Aschner, Michael

    2003-06-01

    Microarray technology provides a unique tool for the determination of gene expression at the level of messenger RNA (mRNA). The simultaneous measurement of the entire human genome (thousands of genes) will facilitate the uncovering of specific gene expression patterns that are associated with disease. One important application of microarray technology, within the context of neurotoxicological studies, is its use as a screening tool for the identification of molecular mechanisms of toxicity. Such approaches enable researchers to identify those genes and their products (either single or whole pathways) that are involved in conferring resistance or sensitivity to toxic substances. This review addresses: (1) the potential uses of array data; (2) the various array platforms, highlighting both their advantages and disadvantages; (3) insights into data analysis and presentation strategies; and (4) concrete examples of DNA array studies in neurotoxicological research. PMID:12782098

  7. A Flexible Microarray Data Simulation Model

    PubMed Central

    Dembélé, Doulaye

    2013-01-01

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

  8. Microarrays: how many do you need?

    PubMed

    Zien, Alexander; Fluck, Juliane; Zimmer, Ralf; Lengauer, Thomas

    2003-01-01

    We estimate the number of microarrays that is required in order to gain reliable results from a common type of study: the pairwise comparison of different classes of samples. We show that current knowledge allows for the construction of models that look realistic with respect to searches for individual differentially expressed genes and derive prototypical parameters from real data sets. Such models allow investigation of the dependence of the required number of samples on the relevant parameters: the biological variability of the samples within each class, the fold changes in expression that are desired to be detected, the detection sensitivity of the microarrays, and the acceptable error rates of the results. We supply experimentalists with general conclusions as well as a freely accessible Java applet at www.scai.fhg.de/special/bio/howmanyarrays/ for fine tuning simulations to their particular settings. PMID:12935350

  9. Glycan microarrays for decoding the glycome

    PubMed Central

    Rillahan, Cory D.; Paulson, James C.

    2011-01-01

    In the last decade glycan microarrays have revolutionized the analysis of the specificity of glycan binding proteins, providing information that simultaneously illuminates the biology mediated by them and decodes the information content of the glycome. Numerous methods have emerged for arraying glycans in a ‘chip’ format, and glycan libraries have been assembled that address the diversity of the human glycome. Such arrays have been successfully used for analysis of glycan binding proteins that mediate mammalian biology, host-pathogen interactions, immune recognition of glycans relevant to vaccine production and cancer antigens. This review covers the development of glycan microarrays and applications that have provided insights into the roles of mammalian and microbial glycan binding proteins. PMID:21469953

  10. 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

  11. 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. PMID:25821171

  12. RNAi microarray analysis in cultured mammalian cells.

    PubMed

    Mousses, Spyro; Caplen, Natasha J; Cornelison, Robert; Weaver, Don; Basik, Mark; Hautaniemi, Sampsa; Elkahloun, Abdel G; Lotufo, Roberto A; Choudary, Ashish; Dougherty, Edward R; Suh, Ed; Kallioniemi, Olli

    2003-10-01

    RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) is a powerful new tool for analyzing gene knockdown phenotypes in living mammalian cells. To facilitate large-scale, high-throughput functional genomics studies using RNAi, we have developed a microarray-based technology for highly parallel analysis. Specifically, siRNAs in a transfection matrix were first arrayed on glass slides, overlaid with a monolayer of adherent cells, incubated to allow reverse transfection, and assessed for the effects of gene silencing by digital image analysis at a single cell level. Validation experiments with HeLa cells stably expressing GFP showed spatially confined, sequence-specific, time- and dose-dependent inhibition of green fluorescence for those cells growing directly on microspots containing siRNA targeting the GFP sequence. Microarray-based siRNA transfections analyzed with a custom-made quantitative image analysis system produced results that were identical to those from traditional well-based transfection, quantified by flow cytometry. Finally, to integrate experimental details, image analysis, data display, and data archiving, we developed a prototype information management system for high-throughput cell-based analyses. In summary, this RNAi microarray platform, together with ongoing efforts to develop large-scale human siRNA libraries, should facilitate genomic-scale cell-based analyses of gene function. PMID:14525932

  13. Integrating data from heterogeneous DNA microarray platforms.

    PubMed

    Valente, Eduardo; Rocha, Miguel

    2015-01-01

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

  14. An imputation approach for oligonucleotide microarrays.

    PubMed

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

    2013-01-01

    Oligonucleotide microarrays are commonly adopted for detecting and qualifying the abundance of molecules in biological samples. Analysis of microarray data starts with recording and interpreting hybridization signals from CEL images. However, many CEL images may be blemished by noises from various sources, observed as "bright spots", "dark clouds", and "shadowy circles", etc. It is crucial that these image defects are correctly identified and properly processed. Existing approaches mainly focus on detecting defect areas and removing affected intensities. In this article, we propose to use a mixed effect model for imputing the affected intensities. The proposed imputation procedure is a single-array-based approach which does not require any biological replicate or between-array normalization. We further examine its performance by using Affymetrix high-density SNP arrays. The results show that this imputation procedure significantly reduces genotyping error rates. We also discuss the necessary adjustments for its potential extension to other oligonucleotide microarrays, such as gene expression profiling. The R source code for the implementation of approach is freely available upon request. PMID:23505547

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

    PubMed

    Spalvieri, Mónica P; Rotenberg, Rosa G

    2004-01-01

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

  16. 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.

  17. The diary of a madman, seventeenth-century style: Goodwin Wharton, MP and communer with the fairy world.

    PubMed

    Porter, R

    1986-08-01

    Goodwin Wharton (1653-1704) was a nobleman's son and a Whig MP who played no small part in English public life. His manuscript journal shows, however, that he also lived a bizarre secret life of the mind of a kind which, in later generations, would have led to his confinement as suffering from mental illness. Above all, through the offices of his medium and lover, Mary Parish, he entered into elaborate relations both with the fairy world and with God and His Angels. This paper examines our records of Wharton's consciousness. PMID:3532157

  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. Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays

    PubMed Central

    Hayden, Douglas; Lazar, Peter; Schoenfeld, David

    2009-01-01

    We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations. For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis. The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data. An R software package, permtest, implementing the method is freely available from the Comprehensive R Archive Network at http://cran.r-project.org. PMID:19529777

  20. Identification of significant features in DNA microarray data

    PubMed Central

    Bair, Eric

    2013-01-01

    DNA microarrays are a relatively new technology that can simultaneously measure the expression level of thousands of genes. They have become an important tool for a wide variety of biological experiments. One of the most common goals of DNA microarray experiments is to identify genes associated with biological processes of interest. Conventional statistical tests often produce poor results when applied to microarray data owing to small sample sizes, noisy data, and correlation among the expression levels of the genes. Thus, novel statistical methods are needed to identify significant genes in DNA microarray experiments. This article discusses the challenges inherent in DNA microarray analysis and describes a series of statistical techniques that can be used to overcome these challenges. The problem of multiple hypothesis testing and its relation to microarray studies are also considered, along with several possible solutions. PMID:24244802

  1. High-throughput allogeneic antibody detection using protein microarrays.

    PubMed

    Paul, Jed; Sahaf, Bita; Perloff, Spenser; Schoenrock, Kelsi; Wu, Fang; Nakasone, Hideki; Coller, John; Miklos, David

    2016-05-01

    Enzyme-linked immunosorbent assays (ELISAs) have traditionally been used to detect alloantibodies in patient plasma samples post hematopoietic cell transplantation (HCT); however, protein microarrays have the potential to be multiplexed, more sensitive, and higher throughput than ELISAs. Here, we describe the development of a novel and sensitive microarray method for detection of allogeneic antibodies against minor histocompatibility antigens encoded on the Y chromosome, called HY antigens. Six microarray surfaces were tested for their ability to bind recombinant protein and peptide HY antigens. Significant allogeneic immune responses were determined in male patients with female donors by considering normal male donor responses as baseline. HY microarray results were also compared with our previous ELISA results. Our overall goal was to maximize antibody detection for both recombinant protein and peptide epitopes. For detection of HY antigens, the Epoxy (Schott) protein microarray surface was both most sensitive and reliable and has become the standard surface in our microarray platform. PMID:26902899

  2. Prenatal chromosomal microarray for the Catholic physician

    PubMed Central

    Bringman, Jay J.

    2014-01-01

    Prenatal chromosomal microarray (CMA) is a test that is used to diagnose certain genetic problems in the fetus. While the test has been used in the pediatric setting for several years, it is now being introduced for use in the prenatal setting. The test offers great hope for detection of certain genetic defects in the fetus so that early intervention can be performed to improve the outcome for that individual. As with many biotechnical advances, CMA comes with certain bioethical issues that need to be addressed prior to its implementation. This paper is intended to provide guidance to all those that provide counseling regarding genetic testing options during pregnancy. PMID:24899750

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Inferring genetic networks from microarray data.

    SciTech Connect

    May, Elebeoba Eni; Davidson, George S.; Martin, Shawn Bryan; Werner-Washburne, Margaret C.; Faulon, Jean-Loup Michel

    2004-06-01

    In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three major challenges are: (1) inferring the network; (2) estimating the stability of the inferred network; and (3) making the network visually accessible to the user. Here we describe a method, tested on publicly available time series microarray data, which addresses these concerns. The inference of genetic networks from genome-wide experimental data is an important biological problem which has received much attention. Approaches to this problem have typically included application of clustering algorithms [6]; the use of Boolean networks [12, 1, 10]; the use of Bayesian networks [8, 11]; and the use of continuous models [21, 14, 19]. Overviews of the problem and general approaches to network inference can be found in [4, 3]. Our approach to network inference is similar to earlier methods in that we use both clustering and Boolean network inference. However, we have attempted to extend the process to better serve the end-user, the biologist. In particular, we have incorporated a system to assess the reliability of our network, and we have developed tools which allow interactive visualization of the proposed network.

  8. Enzyme Microarrays Assembled by Acoustic Dispensing Technology

    PubMed Central

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

    2008-01-01

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

  9. Laser direct writing of biomolecule microarrays

    NASA Astrophysics Data System (ADS)

    Serra, P.; Fernández-Pradas, J. M.; Berthet, F. X.; Colina, M.; Elvira, J.; Morenza, J. L.

    Protein-based biosensors are highly efficient tools for protein detection and identification. The production of these devices requires the manipulation of tiny amounts of protein solutions in conditions preserving their biological properties. In this work, laser induced forward transfer (LIFT) was used for spotting an array of a purified bacterial antigen in order to check the viability of this technique for the production of protein microarrays. A pulsed Nd:YAG laser beam (355 nm wavelength, 10 ns pulse duration) was used to transfer droplets of a solution containing the Treponema pallidum 17 kDa protein antigen on a glass slide. Optical microscopy showed that a regular array of micrometric droplets could be precisely and uniformly spotted onto a solid substrate. Subsequently, it was proved that LIFT deposition of a T. pallidum 17 kDa antigen onto nylon-coated glass slides preserves its antigenic reactivity and diagnostic properties. These results support that LIFT is suitable for the production of protein microarrays and pave the way for future diagnostics applications.

  10. Segmentation of prostate cancer tissue microarray images

    NASA Astrophysics Data System (ADS)

    Cline, Harvey E.; Can, Ali; Padfield, Dirk

    2006-02-01

    Prostate cancer is diagnosed by histopathology interpretation of hematoxylin and eosin (H and E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade. The morphological features vary with the advance of cancer where the epithelial regions grow into the stroma. An efficient pathology slide image analysis method involved using a tissue microarray with known disease stages. Digital 24-bit RGB images were acquired for each tissue element on the slide with both 10X and 40X objectives. Initial segmentation at low magnification was accomplished using prior spectral characteristics from a training tissue set composed of four tissue clusters; namely, glands, epithelia, stroma and nuclei. The segmentation method was automated by using the training RGB values as an initial guess and iterating the averaging process 10 times to find the four cluster centers. Labels were assigned to the nearest cluster center in red-blue spectral feature space. An automatic threshold algorithm separated the glands from the tissue. A visual pseudo color representation of 60 segmented tissue microarray image was generated where white, pink, red, blue colors represent glands, epithelia, stroma and nuclei, respectively. The higher magnification images provided refined nuclei morphology. The nuclei were detected with a RGB color space principle component analysis that resulted in a grey scale image. The shape metrics such as compactness, elongation, minimum and maximum diameters were calculated based on the eigenvalues of the best-fitting ellipses to the nuclei.

  11. Mining microarray expression data by literature profiling

    PubMed Central

    Chaussabel, Damien; Sher, Alan

    2002-01-01

    Background The rapidly expanding fields of genomics and proteomics have prompted the development of computational methods for managing, analyzing and visualizing expression data derived from microarray screening. Nevertheless, the lack of efficient techniques for assessing the biological implications of gene-expression data remains an important obstacle in exploiting this information. Results To address this need, we have developed a mining technique based on the analysis of literature profiles generated by extracting the frequencies of certain terms from thousands of abstracts stored in the Medline literature database. Terms are then filtered on the basis of both repetitive occurrence and co-occurrence among multiple gene entries. Finally, clustering analysis is performed on the retained frequency values, shaping a coherent picture of the functional relationship among large and heterogeneous lists of genes. Such data treatment also provides information on the nature and pertinence of the associations that were formed. Conclusions The analysis of patterns of term occurrence in abstracts constitutes a means of exploring the biological significance of large and heterogeneous lists of genes. This approach should contribute to optimizing the exploitation of microarray technologies by providing investigators with an interface between complex expression data and large literature resources. PMID:12372143

  12. Enzyme microarrays assembled by acoustic dispensing technology.

    PubMed

    Wong, E Y; Diamond, S L

    2008-10-01

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

  13. Label-free detection repeatability of protein microarrays by oblique-incidence reflectivity difference method

    NASA Astrophysics Data System (ADS)

    Dai, Jun; Li, Lin; Wang, JingYi; He, LiPing; Lu, HuiBin; Ruan, KangCheng; Jin, KuiJuan; Yang, GuoZhen

    2012-12-01

    We examine the repeatabilities of oblique-incidence reflectivity difference (OIRD) method for label-free detecting biological molecular interaction using protein microarrays. The experimental results show that the repeatabilities are the same in a given microarray or microarray-microarray and are consistent, indicating that OIRD is a promising label-free detection technique for biological microarrays.

  14. 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...

  15. 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…

  16. Removal of hybridization and scanning noise from microarrays.

    PubMed

    Gopalappa, Chaitra; Das, Tapas K; Enkemann, Steven; Eschrich, Steven

    2009-09-01

    Microarray technology for measuring gene expression values has created significant opportunities for advances in disease diagnosis and individualized treatment planning. However, the random noise introduced by the sample preparation, hybridization, and scanning stages of microarray processing creates significant inaccuracies in the gene expression levels, and hence presents a major barrier in realizing the anticipated advances. Literature presents several methodologies for noise reduction, which can be broadly categorized as: 1) model based approaches for estimation and removal of hybridization noise; 2) approaches using commonly available image denoising tools; and 3) approaches involving the need for control sample(s). In this paper, we present a novel methodology for identifying and removing hybridization and scanning noise from microarray images, using a dual-tree-complex-wavelet-transform-based multiresolution analysis coupled with bivariate shrinkage thresholding. The key features of our methodology include consideration of inherent features and type of noise specific to microarray images, and the ability to work with a single microarray without needing a control. Our methodology is first benchmarked on a fabricated dataset that mimics a real microarray probe dataset. Thereafter, our methodology is tested on datasets obtained from a number of Affymetrix GeneChip human genome HG-U133 Plus 2.0 arrays, processed on HCT-116 cell line at the Microarray Core Facility of Moffitt Cancer Center and Research Institute. The results indicate an appreciable improvement in the quality of the microarray data. PMID:20051337

  17. Applications of microarray technology in breast cancer research

    PubMed Central

    Cooper, Colin S

    2001-01-01

    Microarrays provide a versatile platform for utilizing information from the Human Genome Project to benefit human health. This article reviews the ways in which microarray technology may be used in breast cancer research. Its diverse applications include monitoring chromosome gains and losses, tumour classification, drug discovery and development, DNA resequencing, mutation detection and investigating the mechanism of tumour development. PMID:11305951

  18. 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

  19. Application of Microarray Technology to Investigate Salmonella and Antimicrobial Resistance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays have been developed for the study of various aspects of Salmonella, which is a model system for investigating pathogenesis. Microarrays were used to analyze the gene expression of Salmonella in various environments that mimic the host environment and these studies have helped to elucidat...

  20. A Comparative Study of Normalization Methods Used in Statistical Analysis of Oligonucleotide Microarray Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Normalization methods used in the statistical analysis of oligonucleotide microarray data were evaluated. The oligonucleotide microarray is considered an efficient analytical tool for analyzing thousands of genes simultaneously in a single experiment. However, systematic variation in microarray, ori...

  1. Genomic-Wide Analysis with Microarrays in Human Oncology

    PubMed Central

    Inaoka, Kenichi; Inokawa, Yoshikuni; Nomoto, Shuji

    2015-01-01

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

  2. An ultralow background substrate for protein microarray technology.

    PubMed

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

    2015-08-21

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

  3. Chapter 9 - Methylation Analysis by Microarray

    PubMed Central

    Deatherage, Daniel E.; Potter, Dustin; Yan, Pearlly S.; Huang, Tim H.-M.; Lin, Shili

    2010-01-01

    Differential Methylation Hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good read-outs for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. The step-by-step laboratory DMH protocol is described. In addition, we provide descriptions regarding DMH data analysis, including image quantification, background correction, and statistical procedures for both exploratory analysis and more formal inferences. Issues regarding quality control are addressed as well. PMID:19488875

  4. 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.

  5. 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. PMID:25987649

  6. DNA microarrays on a mesospaced surface

    NASA Astrophysics Data System (ADS)

    Hong, Bong Jin; Park, Joon Won

    2004-12-01

    A dendron having nine carboxylic acid groups at the end of the branches and a protected amine at the apex was allowed to form a molecular layer on the aminosilylated surface through multipoint ionic attraction. It was found that a compact and smooth monolayer was obtained at appropriate condition. The film quality was maintained successfully after deprotecting CBZ group with trimethylsilyl iodide. The surface density of the primary amine after the deprotection was measured with fluorometry, and 0.1-0.2 amine group per 1 nm2 was observed. This implies that the spacing between the amine functional groups is 24-34 Å in hexagonal close packing (hcp) model. In addition, DNA microarrays were fabricated successfully on the dendron-modified surface.

  7. Digital microarray analysis for digital artifact genomics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

    We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.

  8. 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

  9. 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

  10. Lipid Microarray Biosensor for Biotoxin Detection.

    SciTech Connect

    Singh, Anup K.; Throckmorton, Daniel J.; Moran-Mirabal, Jose C.; Edel, Joshua B.; Meyer, Grant D.; Craighead, Harold G.

    2006-05-01

    We present the use of micron-sized lipid domains, patterned onto planar substrates and within microfluidic channels, to assay the binding of bacterial toxins via total internal reflection fluorescence microscopy (TIRFM). The lipid domains were patterned using a polymer lift-off technique and consisted of ganglioside-populated DSPC:cholesterol supported lipid bilayers (SLBs). Lipid patterns were formed on the substrates by vesicle fusion followed by polymer lift-off, which revealed micron-sized SLBs containing either ganglioside GT1b or GM1. The ganglioside-populated SLB arrays were then exposed to either Cholera toxin subunit B (CTB) or Tetanus toxin fragment C (TTC). Binding was assayed on planar substrates by TIRFM down to 1 nM concentration for CTB and 100 nM for TTC. Apparent binding constants extracted from three different models applied to the binding curves suggest that binding of a protein to a lipid-based receptor is strongly affected by the lipid composition of the SLB and by the substrate on which the bilayer is formed. Patterning of SLBs inside microfluidic channels also allowed the preparation of lipid domains with different compositions on a single device. Arrays within microfluidic channels were used to achieve segregation and selective binding from a binary mixture of the toxin fragments in one device. The binding and segregation within the microfluidic channels was assayed with epifluorescence as proof of concept. We propose that the method used for patterning the lipid microarrays on planar substrates and within microfluidic channels can be easily adapted to proteins or nucleic acids and can be used for biosensor applications and cell stimulation assays under different flow conditions. KEYWORDS. Microarray, ganglioside, polymer lift-off, cholera toxin, tetanus toxin, TIRFM, binding constant.4

  11. 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

  12. Prediction in Annotation Based Guideline Encoding

    PubMed Central

    Hagerty, C. Greg; Pickens, David S.; Chang, Jaime; Kulikowski, Casimir A.; Sonnenberg, Frank A.

    2006-01-01

    The encoding of clinical practice guidelines into machine operable representations poses numerous challenges and will require considerable human intervention for the foreseeable future. To assist and potentially speed up this process, we have developed an incremental approach to guideline encoding which begins with the annotation of the original guideline text using markup techniques. A modular and flexible sequence of subtasks results in increasingly inter-operable representations while maintaining the connections to all prior source representations and supporting knowledge. To reduce the encoding bottleneck we also employ a number of machine-assisted learning and prediction techniques within a knowledge-based software environment. Promising results with a straightforward incremental learning algorithm illustrate the feasibility of such an approach. PMID:17238354

  13. Novel Microarrays for Simultaneous Serodiagnosis of Multiple Antiviral Antibodies

    PubMed Central

    Sivakumar, Ponnurengam Malliappan; Moritsugu, Nozomi; Obuse, Sei; Isoshima, Takashi; Tashiro, Hideo; Ito, Yoshihiro

    2013-01-01

    We developed an automated diagnostic system for the detection of virus-specific immunoglobulin Gs (IgGs) that was based on a microarray platform. We compared efficacies of our automated system with conventional enzyme immunoassays (EIAs). Viruses were immobilized to microarrays using a radical cross-linking reaction that was induced by photo-irradiation. A new photoreactive polymer containing perfluorophenyl azide (PFPA) and poly(ethylene glycol) methacrylate was prepared and coated on plates. Inactivated measles, rubella, mumps, Varicella-Zoster and recombinant Epstein-Barr viruse antigen were added to coated plates, and irradiated with ultraviolet light to facilitate immobilization. Virus-specific IgGs in healthy human sera were assayed using these prepared microarrays and the results obtained compared with those from conventional EIAs. We observed high correlation (0.79–0.96) in the results between the automated microarray technique and EIAs. The microarray-based assay was more rapid, involved less reagents and sample, and was easier to conduct compared with conventional EIA techniques. The automated microarray system was further improved by introducing reagent storage reservoirs inside the chamber, thereby conserving the use of expensive reagents and antibodies. We considered the microarray format to be suitable for rapid and multiple serological diagnoses of viral diseases that could be developed further for clinical applications. PMID:24367491

  14. Novel microarrays for simultaneous serodiagnosis of multiple antiviral antibodies.

    PubMed

    Sivakumar, Ponnurengam Malliappan; Moritsugu, Nozomi; Obuse, Sei; Isoshima, Takashi; Tashiro, Hideo; Ito, Yoshihiro

    2013-01-01

    We developed an automated diagnostic system for the detection of virus-specific immunoglobulin Gs (IgGs) that was based on a microarray platform. We compared efficacies of our automated system with conventional enzyme immunoassays (EIAs). Viruses were immobilized to microarrays using a radical cross-linking reaction that was induced by photo-irradiation. A new photoreactive polymer containing perfluorophenyl azide (PFPA) and poly(ethylene glycol) methacrylate was prepared and coated on plates. Inactivated measles, rubella, mumps, Varicella-Zoster and recombinant Epstein-Barr viruse antigen were added to coated plates, and irradiated with ultraviolet light to facilitate immobilization. Virus-specific IgGs in healthy human sera were assayed using these prepared microarrays and the results obtained compared with those from conventional EIAs. We observed high correlation (0.79-0.96) in the results between the automated microarray technique and EIAs. The microarray-based assay was more rapid, involved less reagents and sample, and was easier to conduct compared with conventional EIA techniques. The automated microarray system was further improved by introducing reagent storage reservoirs inside the chamber, thereby conserving the use of expensive reagents and antibodies. We considered the microarray format to be suitable for rapid and multiple serological diagnoses of viral diseases that could be developed further for clinical applications. PMID:24367491

  15. 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.

  16. 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.

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

    PubMed Central

    Pollack, Jonathan R.

    2007-01-01

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

  18. Deciphering the glycosaminoglycan code with the help of microarrays.

    PubMed

    de Paz, Jose L; Seeberger, Peter H

    2008-07-01

    Carbohydrate microarrays have become a powerful tool to elucidate the biological role of complex sugars. Microarrays are particularly useful for the study of glycosaminoglycans (GAGs), a key class of carbohydrates. The high-throughput chip format enables rapid screening of large numbers of potential GAG sequences produced via a complex biosynthesis while consuming very little sample. Here, we briefly highlight the most recent advances involving GAG microarrays built with synthetic or naturally derived oligosaccharides. These chips are powerful tools for characterizing GAG-protein interactions and determining structure-activity relationships for specific sequences. Thereby, they contribute to decoding the information contained in specific GAG sequences. PMID:18563243

  19. 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

  20. New technologies for fabricating biological microarrays

    NASA Astrophysics Data System (ADS)

    Larson, Bradley James

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

  1. 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. PMID:25971913

  2. Development and Optimization of a Thrombin Sandwich Aptamer Microarray

    PubMed Central

    Meneghello, Anna; Sosic, Alice; Antognoli, Agnese; Cretaio, Erica; Gatto, Barbara

    2012-01-01

    A sandwich microarray employing two distinct aptamers for human thrombin has been optimized for the detection of subnanomolar concentrations of the protein. The aptamer microarray demonstrates high specificity for thrombin, proving that a two-site binding assay with the TBA1 aptamer as capture layer and the TBA2 aptamer as detection layer can ensure great specificity at times and conditions compatible with standard routine analysis of biological samples. Aptamer microarray sensitivity was evaluated directly by fluorescent analysis employing Cy5-labeled TBA2 and indirectly by the use of TBA2-biotin followed by detection with fluorescent streptavidin. Sub-nanomolar LODs were reached in all cases and in the presence of serum, demonstrating that the optimized aptamer microarray can identify thrombin by a low-cost, sensitive and specific method.

  3. 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.

  4. 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. PMID:26077916

  5. Applications in high-content functional protein microarrays.

    PubMed

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

    2016-02-01

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

  6. Improving Microarray Sample Size Using Bootstrap Data Combination

    PubMed Central

    Phan, John H.; Moffitt, Richard A.; Barrett, Andrea B.; Wang, May D.

    2016-01-01

    Microarray technology has enabled us to simultaneously measure the expression of thousands of genes. Using this high-throughput technology, we can examine subtle genetic changes between biological samples and build predictive models for clinical applications. Although microarrays have dramatically increased the rate of data collection, sample size is still a major issue when selecting features. Previous methods show that combining multiple microarray datasets improves feature selection using simple methods such as fold change. We propose a wrapper-based gene selection technique that combines bootstrap estimated classification errors for individual genes across multiple datasets and reduces the contribution of datasets with high variance. We use the bootstrap because it is an unbiased estimator of classification error that is also effective for small sample data. Coupled with data combination across multiple datasets, we show that our meta-analytic approach improves the biological relevance of gene selection using prostate and renal cancer microarray data. PMID:19164001

  7. Emerging Use of Gene Expression Microarrays in Plant Physiology

    DOE PAGESBeta

    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

  8. 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

  9. Plant protein kinase substrates identification using protein microarrays.

    PubMed

    Ma, Shisong; Dinesh-Kumar, Savithramma P

    2015-01-01

    Protein kinases regulate signaling pathways by phosphorylating their targets. They play critical roles in plant signaling networks. Although many important protein kinases have been identified in plants, their substrates are largely unknown. We have developed and produced plant protein microarrays with more than 15,000 purified plant proteins. Here, we describe a detailed protocol to use these microarrays to identify plant protein kinase substrates via in vitro phosphorylation assays on these arrays. PMID:25930701

  10. 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. PMID:23385529

  11. 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.

  12. 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

  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. The Perils of SNP Microarray Testing: Uncovering Unexpected Consanguinity

    PubMed Central

    Tarini, Beth A.; Konczal, Laura; Goldenberg, Aaron J.; Goldman, Edward B.; McCandless, Shawn E.

    2013-01-01

    Background While single nucleotide polymorphism (SNP) chromosomal microarrays identify areas of small genetic deletions/duplications, they can also reveal regions of homozygosity indicative of consanguinity. As more non-geneticists order SNP microarrays, they must prepare for the potential ethical, legal and social issues that result from revelation of unanticipated consanguinity. Patient An infant with multiple congenital anomalies underwent SNP microarray testing. Results The results of the SNP microarray revealed several large regions of homozygosity that indicated identity by descent most consistent with a second or third degree relative mating (e.g., uncle/ niece, half brother/sister, first cousins). Mother was not aware of the test's potential to reveal consanguinity. When informed of the test results, she reluctantly admitted to being raped by her half-brother around the time of conception. Conclusions During the pre-testing consent process, providers should inform parents that SNP microarray testing could reveal consanguinity. Providers must also understand the psychological implications, as well as the legal and moral obligations, that accompany SNP microarray results that indicate consanguinity. PMID:23827427

  15. 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.

  16. Shrinkage regression-based methods for microarray missing value imputation

    PubMed Central

    2013-01-01

    Background Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected. Inaccurate missing value estimation results in reducing the power of downstream microarray data analyses. Many types of methods have been developed to estimate missing values. Among them, the regression-based methods are very popular and have been shown to perform better than the other types of methods in many testing microarray datasets. Results To further improve the performances of the regression-based methods, we propose shrinkage regression-based methods. Our methods take the advantage of the correlation structure in the microarray data and select similar genes for the target gene by Pearson correlation coefficients. Besides, our methods incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the coefficients of the regression model, and then use the new coefficients to estimate missing values. Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression-based methods do. Conclusions Imputation of missing values is a very important aspect of microarray data analyses because most of the downstream analyses require a complete dataset. Therefore, exploring accurate and efficient methods for estimating missing values has become an essential issue. Since our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression-based methods. PMID:24565159

  17. 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

  18. Novel 3-Dimensional Dendrimer Platform for Glycolipid Microarray

    PubMed Central

    Zhang, Jian; Zhou, Xichun

    2011-01-01

    Glycolipids are important biological molecules that modulate cellular recognitions and pathogen adhesions. In this paper, we report a sensitive glycolipid microarray for non-covalently immobilizing glycolipids on a microarray substrate and we perform a set of immunoassays to explore glycolipid-protein interactions. This substrate utilizes a three-dimensional hydrazide-functionalized dendrimer monolayer attached onto a microscopic glass surface, which possesses the characteristics to adsorb glycoliplids non-covalently and facilitates multivalent attributes on the substrate surface. In the proof-of-concept experiments, gangliosides such as GM1, FucGM1, GM3, GD1b, GT1b, and GQ1b, and a lipoarabinomannan were tested on the substrate and interrogated with toxins and antibodies. The resulting glycolipid microarrays exhibited hypersensitivity and specificity for detection of glycolipid-protein interactions. In particular, a robust and specific binding of a pentameric cholera toxin B subunit to the GM1 glycolipid spotted on the array has demonstrated its superiority in sensitivity and specificity. In addition, this glycolipid microarray substrate was used to detect lipoarabinomannan in buffer within a limit-of-detection of 125 ng/mL. Furthermore, Mycobacterium tuberculosis (Mtb) Lipoarabinomannan was tested in human urine specimens on this platform, which can effectively identify urine samples either infected or not infected with Mtb. The results of this work suggest the possibility of using this glycolipid microarray platform to fabricate glycoconjugate microarrays, which includes free glycans and glycolipids and potential application in detection of pathogen and toxin. PMID:21820887

  19. Surface Enzyme Chemistries for Ultrasensitive Microarray Biosensing with SPR Imaging.

    PubMed

    Fasoli, Jennifer B; Corn, Robert M

    2015-09-01

    The sensitivity and selectivity of surface plasmon resonance imaging (SPRI) biosensing with nucleic acid microarrays can be greatly enhanced by exploiting various nucleic acid ligases, nucleases, and polymerases that manipulate the surface-bound DNA and RNA. We describe here various examples from each of these different classes of surface enzyme chemistries that have been incorporated into novel detection strategies that either drastically enhance the sensitivity of or create uniquely selective methods for the SPRI biosensing of proteins and nucleic acids. A dual-element generator-detector microarray approach that couples a bioaffinity adsorption event on one microarray element to nanoparticle-enhanced SPRI measurements of nucleic acid hybridization adsorption on a different microarray element is used to quantitatively detect DNA, RNA, and proteins at femtomolar concentrations. Additionally, this dual-element format can be combined with the transcription and translation of RNA from surface-bound double-stranded DNA (dsDNA) templates for the on-chip multiplexed biosynthesis of aptamer and protein microarrays in a microfluidic format; these microarrays can be immediately used for real-time SPRI bioaffinity sensing measurements. PMID:25641598

  20. 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

  1. Surface Enzyme Chemistries for Ultrasensitive Microarray Biosensing with SPR Imaging

    PubMed Central

    2015-01-01

    The sensitivity and selectivity of surface plasmon resonance imaging (SPRI) biosensing with nucleic acid microarrays can be greatly enhanced by exploiting various nucleic acid ligases, nucleases, and polymerases that manipulate the surface-bound DNA and RNA. We describe here various examples from each of these different classes of surface enzyme chemistries that have been incorporated into novel detection strategies that either drastically enhance the sensitivity of or create uniquely selective methods for the SPRI biosensing of proteins and nucleic acids. A dual-element generator–detector microarray approach that couples a bioaffinity adsorption event on one microarray element to nanoparticle-enhanced SPRI measurements of nucleic acid hybridization adsorption on a different microarray element is used to quantitatively detect DNA, RNA, and proteins at femtomolar concentrations. Additionally, this dual-element format can be combined with the transcription and translation of RNA from surface-bound double-stranded DNA (dsDNA) templates for the on-chip multiplexed biosynthesis of aptamer and protein microarrays in a microfluidic format; these microarrays can be immediately used for real-time SPRI bioaffinity sensing measurements. PMID:25641598

  2. 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.

  3. Nucleosome positioning from tiling microarray data

    PubMed Central

    Yassour, Moran; Kaplan, Tommy; Jaimovich, Ariel; Friedman, Nir

    2008-01-01

    Motivation: The packaging of DNA around nucleosomes in eukaryotic cells plays a crucial role in regulation of gene expression, and other DNA-related processes. To better understand the regulatory role of nucleosomes, it is important to pinpoint their position in a high (5–10 bp) resolution. Toward this end, several recent works used dense tiling arrays to map nucleosomes in a high-throughput manner. These data were then parsed and hand-curated, and the positions of nucleosomes were assessed. Results: In this manuscript, we present a fully automated algorithm to analyze such data and predict the exact location of nucleosomes. We introduce a method, based on a probabilistic graphical model, to increase the resolution of our predictions even beyond that of the microarray used. We show how to build such a model and how to compile it into a simple Hidden Markov Model, allowing for a fast and accurate inference of nucleosome positions. We applied our model to nucleosomal data from mid-log yeast cells reported by Yuan et al. and compared our predictions to those of the original paper; to a more recent method that uses five times denser tiling arrays as explained by Lee et al.; and to a curated set of literature-based nucleosome positions. Our results suggest that by applying our algorithm to the same data used by Yuan et al. our fully automated model traced 13% more nucleosomes, and increased the overall accuracy by about 20%. We believe that such an improvement opens the way for a better understanding of the regulatory mechanisms controlling gene expression, and how they are encoded in the DNA. Contact: nir@cs.huji.ac.il PMID:18586706

  4. Analysis of porcine MHC using microarrays.

    PubMed

    Gao, Yu; Wahlberg, Per; Marthey, Sylvain; Esquerré, Diane; Jaffrézic, Florence; Lecardonnel, Jérome; Hugot, Karine; Rogel-Gaillard, Claire

    2012-07-15

    The major histocompatibility complex (MHC) in Mammals is one of the most gene dense regions of the genome and contains the polymorphic histocompatibility gene families known to be involved in pathogen response and control of auto-immunity. The MHC is a complex genetic system that provides an interesting model system to study genome expression regulation and genetic diversity at the megabase scale. The pig MHC or SLA (Swine Leucocyte Antigen) complex spans 2.4 megabases and 151 loci have been annotated. We will review key results from previous RNA expression studies using microarrays containing probes specific to annotated loci within SLA and in addition present novel data obtained using high-density tiling arrays encompassing the whole SLA complex. We have focused on transcriptome modifications of porcine peripheral blood mononuclear cells stimulated with a mixture of phorbol myristate acetate and ionomycin known to activate B and T cell proliferation. Our results show that numerous loci mapping to the SLA complex are affected by the treatment. A general decreased level of expression for class I and II genes and an up-regulation of genes involved in peptide processing and transport were observed. Tiling array-based experiments contributed to refined gene annotations as presented for one SLA class I gene referred to as SLA-11. In conclusion, high-density tiling arrays can serve as an excellent tool to draw comprehensive transcription maps, and improve genome annotations for the SLA complex. We are currently studying their relevance to characterize SLA genetic diversity in combination with high throughput next generation sequencing. PMID:21561666

  5. Pipeline for macro- and microarray analyses.

    PubMed

    Vicentini, R; Menossi, M

    2007-05-01

    The pipeline for macro- and microarray analyses (PMmA) is a set of scripts with a web interface developed to analyze DNA array data generated by array image quantification software. PMmA is designed for use with single- or double-color array data and to work as a pipeline in five classes (data format, normalization, data analysis, clustering, and array maps). It can also be used as a plugin in the BioArray Software Environment, an open-source database for array analysis, or used in a local version of the web service. All scripts in PMmA were developed in the PERL programming language and statistical analysis functions were implemented in the R statistical language. Consequently, our package is a platform-independent software. Our algorithms can correctly select almost 90% of the differentially expressed genes, showing a superior performance compared to other methods of analysis. The pipeline software has been applied to 1536 expressed sequence tags macroarray public data of sugarcane exposed to cold for 3 to 48 h. PMmA identified thirty cold-responsive genes previously unidentified in this public dataset. Fourteen genes were up-regulated, two had a variable expression and the other fourteen were down-regulated in the treatments. These new findings certainly were a consequence of using a superior statistical analysis approach, since the original study did not take into account the dependence of data variability on the average signal intensity of each gene. The web interface, supplementary information, and the package source code are available, free, to non-commercial users at http://ipe.cbmeg.unicamp.br/pub/PMmA. PMID:17464422

  6. 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

  7. Protein microarray: sensitive and effective immunodetection for drug residues

    PubMed Central

    2010-01-01

    Background Veterinary drugs such as clenbuterol (CL) and sulfamethazine (SM2) are low molecular weight (<1000 Da) compounds, or haptens, that are difficult to develop immunoassays due to their low immunogenicity. In this study, we conjugated the drugs to ovalbumin to increase their immunogenicity for antiserum production in rabbits and developed a protein microarray immunoassay for detection of clenbuterol and sulfamethazine. The sensitivity of this approach was then compared to traditional ELISA technique. Results The artificial antigens were spotted on microarray slides. Standard concentrations of the compounds were added to compete with the spotted antigens for binding to the antisera to determine the IC50. Our microarray assay showed the IC50 were 39.6 ng/ml for CL and 48.8 ng/ml for SM2, while the traditional competitive indirect-ELISA (ci-ELISA) showed the IC50 were 190.7 ng/ml for CL and 156.7 ng/ml for SM2. We further validated the two methods with CL fortified chicken muscle tissues, and the protein microarray assay showed 90% recovery while the ci-ELISA had 76% recovery rate. When tested with CL-fed chicken muscle tissues, the protein microarray assay had higher sensitivity (0.9 ng/g) than the ci-ELISA (0.1 ng/g) for detection of CL residues. Conclusions The protein microarrays showed 4.5 and 3.5 times lower IC50 than the ci-ELISA detection for CL and SM2, respectively, suggesting that immunodetection of small molecules with protein microarray is a better approach than the traditional ELISA technique. PMID:20158905

  8. 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

  9. Evaluating concentration estimation errors in ELISA microarray experiments

    PubMed Central

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

    2005-01-01

    Background Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to estimate a protein's concentration in a sample. Deploying ELISA in a microarray format permits simultaneous estimation of the concentrations of numerous proteins in a small sample. These estimates, however, are uncertain due to processing error and biological variability. Evaluating estimation error is critical to interpreting biological significance and improving the ELISA microarray process. Estimation error evaluation must be automated to realize a reliable high-throughput ELISA microarray system. In this paper, we present a statistical method based on propagation of error to evaluate concentration estimation errors in the ELISA microarray process. Although propagation of error is central to this method and the focus of this paper, it is most 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 concentration estimation errors. Results We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of concentration estimation 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. We summarize the results with a simple, three-panel diagnostic visualization featuring a scatterplot of the standard data with logistic standard curve and 95% confidence intervals, an annotated histogram of sample measurements, and a plot of the 95% concentration coefficient of variation, or relative error, as a function of concentration. Conclusions This statistical method should be of value in the rapid evaluation and quality control of high-throughput ELISA microarray analyses

  10. Can Zipf's law be adapted to normalize microarrays?

    PubMed Central

    Lu, Tim; Costello, Christine M; Croucher, Peter JP; Häsler, Robert; Deuschl, Günther; Schreiber, Stefan

    2005-01-01

    Background Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented. Results Using pairwise comparisons using MA plots (log ratio vs. log intensity), we compared this novel method to previously published normalization techniques, namely global normalization to the mean, the quantile method, and a variation on the loess normalization method designed specifically for boutique microarrays. Results indicated that, for single channel microarrays, the quantile method was superior with regard to eliminating intensity-dependent effects (banana curves), but Zipf's law normalization does minimize this effect by rotating the data distribution such that the maximal number of data points lie on the zero of the log ratio axis. For two channel boutique microarrays, the Zipf's law normalizations performed as well as, or better than existing techniques. Conclusion Zipf's law normalization is a useful tool where the Quantile method cannot be applied, as is the case with microarrays containing functionally specific gene sets (boutique arrays). PMID:15727680

  11. Electronic microarray assays for avian influenza and Newcastle disease virus.

    PubMed

    Lung, Oliver; Beeston, Anne; Ohene-Adjei, Samuel; Pasick, John; Hodko, Dalibor; Hughes, Kimberley Burton; Furukawa-Stoffer, Tara; Fisher, Mathew; Deregt, Dirk

    2012-11-01

    Microarrays are suitable for multiplexed detection and typing of pathogens. Avian influenza virus (AIV) is currently classified into 16 H (hemagglutinin) and 9 N (neuraminidase) subtypes, whereas Newcastle disease virus (NDV) strains differ in virulence and are broadly classified into high and low pathogenicity types. In this study, three assays for detection and typing of poultry viruses were developed on an automated microarray platform: a multiplex assay for simultaneous detection of AIV and detection and pathotyping of NDV, and two separate assays for differentiating all AIV H and N subtypes. The AIV-NDV multiplex assay detected all strains in a 63 virus panel, and accurately typed all high pathogenicity NDV strains tested. A limit of detection of 10(1)-10(3) TCID(50)/mL and 200-400 EID(50)/mL was obtained for NDV and AIV, respectively. The AIV typing assays accurately typed all 41 AIV strains and a limit of detection of 4-200 EID(50)/mL was obtained. Assay validation showed that the microarray assays were generally comparable to real-time RT-PCR. However, the AIV typing microarray assays detected more positive clinical samples than the AIV matrix real-time RT-PCR, and also provided information regarding the subtype. The AIV-NDV multiplex and AIV H typing microarray assays detected mixed infections and could be useful for detection and typing of AIV and NDV. PMID:22796283

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

    PubMed Central

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

    2010-01-01

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

  13. Production of biomolecule microarrays through laser induced forward transfer

    NASA Astrophysics Data System (ADS)

    Fernandez-Pradas, Juan Marcos; Serra, Pere; Colina, Monica; Morenza, Jose-Luis

    2004-10-01

    Biomolecule microarrays are a kind of biosensors that consist in patterns of different biological molecules immobilized on a solid substrate and capable to bind specifically to their complementary targets. In particular, DNA and protein microarrays have been revealed to be very efficient devices for genen and protein identification, what has converted them in powerful tools for many applications, like clinical diagnose, drug discovery analysis, genomics and proteomics. The production of these devices requires the manipulation of tiny amounts of a liquid solution containing biomolecules without damaging them. In this work laser induced forward transfer (LIFT) has been used for spotting a biomolecule in order to check the viability of this technique for the production of microarrays. A pulsed Nd:YAG laser beam (355 nm wavelength) has been used to transfer droplets of a biomolecule containing solution onto a solid slide. Optical microscopy of the transferred material has been carried out to investigate the morphological characteristics of the droplets obtained under different irradiation conditions. Afterwards, a DNA microarray has been spotted. The viability of the transference has been tested by checking the biological activity of the biomolecule in front of its specific complementary target. This has revealed that, indeed, the LIFT technique is adequate for the production of DNA microarrays.

  14. 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. PMID:21901611

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

    PubMed

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

    2008-08-01

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

  16. 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. PMID:22157075

  17. 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.

  18. [Research progress of probe design software of oligonucleotide microarrays].

    PubMed

    Chen, Xi; Wu, Zaoquan; Liu, Zhengchun

    2014-02-01

    DNA microarray has become an essential medical genetic diagnostic tool for its high-throughput, miniaturization and automation. The design and selection of oligonucleotide probes are critical for preparing gene chips with high quality. Several sets of probe design software have been developed and are available to perform this work now. Every set of the software aims to different target sequences and shows different advantages and limitations. In this article, the research and development of these sets of software are reviewed in line with three main criteria, including specificity, sensitivity and melting temperature (Tm). In addition, based on the experimental results from literatures, these sets of software are classified according to their applications. This review will be helpful for users to choose an appropriate probe-design software. It will also reduce the costs of microarrays, improve the application efficiency of microarrays, and promote both the research and development (R&D) and commercialization of high-performance probe design software. PMID:24804514

  19. Fluorous-based Peptide Microarrays for Protease Screening

    PubMed Central

    Collet, Beatrice Y. M.; Nagashima, Tadamichi; Yu, Marvin S.; Pohl, Nicola L. B.

    2009-01-01

    As ever more protease sequences are uncovered through genome sequencing projects, efficient parallel methods to discover the potential substrates of these proteases becomes crucial. Herein we describe the first use of fluorous-based microarrays to probe peptide sequences and begin to define the scope and limitations of fluorous microarray technologies for the screening of proteases. Comparison of a series of serine proteases showed that their ability to cleave peptide substrates in solution was maintained upon immobilization of these substrates onto fluorous-coated glass slides. The fluorous surface did not serve to significantly inactivate the enzymes. However, addition of hydrophilic components to the peptide sequences could induce lower rates of substrate cleavage with enzymes such as chymotrypsin with affinities to hydrophobic moieties. This work represents the first step to creating robust protease screening platforms using noncovalent microarray interface that can easily incorporate a range of compounds on the same slide. PMID:20161483

  20. 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.

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

    PubMed

    Weinberg, Sandy

    2004-11-01

    A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver. PMID:15525220

  2. Salt concentration effects on equilibrium melting curves from DNA microarrays.

    PubMed

    Fuchs, J; Fiche, J-B; Buhot, A; Calemczuk, R; Livache, T

    2010-09-22

    DNA microarrays find applications in an increasing number of domains where more quantitative results are required. DNA being a charged polymer, the repulsive interactions between the surface of the microarray and the targets in solution are increasing upon hybridization. Such electrostatic penalty is generally reduced by increasing the salt concentration. In this article, we present equilibrium-melting curves obtained from dedicated physicochemical experiments on DNA microarrays in order to get a better understanding of the electrostatic penalty incurred during the hybridization reaction at the surface. Various salt concentrations have been considered and deviations from the commonly used Langmuir adsorption model are experimentally quantified for the first time in agreement with theoretical predictions. PMID:20858434

  3. An automated method for gridding in microarray images.

    PubMed

    Giannakeas, Nikolaos; Fotiadis, Dimitrios I; Politou, Anastasia S

    2006-01-01

    Microarray technology is a powerful tool for analyzing the expression of a large number of genes in parallel. A typical microarray image consists of a few thousands of spots which determine the level of gene expression in the sample. In this paper we propose a method which automatically addresses each spot area in the image. Initially, a preliminary segmentation of the image is produced using a template matching algorithm. Next, grid and spot finding are realized. The position of non-expressed spots is located and finally a Voronoi diagram is employed to fit the grid on the image. Our method has been evaluated in a set of five images consisting of 45960 spots, from the Stanford microarray database and the reported accuracy for spot detection was 93% PMID:17946343

  4. 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. PMID:20857358

  5. Chromosomal Microarrays for the Prenatal Detection of Microdeletions and Microduplications.

    PubMed

    Wou, Karen; Levy, Brynn; Wapner, Ronald J

    2016-06-01

    Chromosomal microarray analysis has replaced conventional G-banded karyotype in prenatal diagnosis as the first-tier test for the cytogenetic detection of copy number imbalances in fetuses with/without major structural abnormalities. This article reviews the basic technology of microarray; the value and clinical significance of the detection of microdeletions, microduplications, and other copy number variants; as well as the importance of genetic counseling for prenatal diagnosis. It also discusses the current status of noninvasive screening for some of these microdeletion and microduplication syndromes. PMID:27235911

  6. On the use of standards for microarray lossless image compression.

    PubMed

    Pinho, Armando J; Paiva, António R C; Neves, António J R

    2006-03-01

    The interest in methods that are able to efficiently compress microarray images is relatively new. This is not surprising, since the appearance and fast growth of the technology responsible for producing these images is also quite recent. In this paper, we present a set of compression results obtained with 49 publicly available images, using three image coding standards: lossless JPEG2000, JBIG, and JPEG-LS. We concluded that the compression technology behind JBIG seems to be the one that offers the best combination of compression efficiency and flexibility for microarray image compression. PMID:16532784

  7. 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.

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-02-01

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

  10. DNA microarrays: design principles for maximizing ergodic, chaotic mixing.

    PubMed

    Hertzsch, Jan-Martin; Sturman, Rob; Wiggins, Stephen

    2007-02-01

    In this article we show that models of flows in DNA microarrays generated by pulsed source-sink pairs can be studied as linked twist maps. The significance of this is that it enables us to relate the flow to mathematically precise notions of chaotic mixing that can be realized through specific design criteria. We apply these techniques to three different mixing protocols, two of which have been previously described in the literature, and we are able to isolate the features of each mixer that lead to "good" or "bad" mixing. Based on this, we propose a new design to generate a "well-mixed" flow in a DNA microarray. PMID:17262763

  11. 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.

  12. Consensus gene regulatory networks: combining multiple microarray gene expression datasets

    NASA Astrophysics Data System (ADS)

    Peeling, Emma; Tucker, Allan

    2007-09-01

    In this paper we present a method for modelling gene regulatory networks by forming a consensus Bayesian network model from multiple microarray gene expression datasets. Our method is based on combining Bayesian network graph topologies and does not require any special pre-processing of the datasets, such as re-normalisation. We evaluate our method on a synthetic regulatory network and part of the yeast heat-shock response regulatory network using publicly available yeast microarray datasets. Results are promising; the consensus networks formed provide a broader view of the potential underlying network, obtaining an increased true positive rate over networks constructed from a single data source.

  13. 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.

  14. Multiple criteria optimization joint analyses of microarray experiments in lung cancer: from existing microarray data to new knowledge.

    PubMed

    Camacho-Cáceres, Katia I; Acevedo-Díaz, Juan C; Pérez-Marty, Lynn M; Ortiz, Michael; Irizarry, Juan; Cabrera-Ríos, Mauricio; Isaza, Clara E

    2015-12-01

    Microarrays can provide large amounts of data for genetic relative expression in illnesses of interest such as cancer in short time. These data, however, are stored and often times abandoned when new experimental technologies arrive. This work reexamines lung cancer microarray data with a novel multiple criteria optimization-based strategy aiming to detect highly differentially expressed genes. This strategy does not require any adjustment of parameters by the user and is capable to handle multiple and incommensurate units across microarrays. In the analysis, groups of samples from patients with distinct smoking habits (never smoker, current smoker) and different gender are contrasted to elicit sets of highly differentially expressed genes, several of which are already associated to lung cancer and other types of cancer. The list of genes is provided with a discussion of their role in cancer, as well as the possible research directions for each of them. PMID:26471143

  15. Microarray platform for the detection of a range of plant viruses and viroids.

    PubMed

    Adams, Ian; Harrison, Catherine; Tomlinson, Jenny; Boonham, Neil

    2015-01-01

    Diagnostic microarrays are a useful tool for the simultaneous detection of multiple targets. In this chapter we describe the use of a simple tube-based microarray platform for the detection of plant infecting viruses and viroids. PMID:25981261

  16. 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...

  17. 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...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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, ...

  19. Using The Affymetrix Wheat Microarray As An Oat Expression Platform

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent advances in sequencing have resulted in the sequence of a large number of plant expressed sequence tags (ESTs) to entire plant genomes. Using these EST sequences, oligonucleotide microarray chips have been developed for several species including barley (Hordeum vulgare), maize (Zea mays), ric...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

    Morais, Sergi; Puchades, Rosa; Maquieira, Ángel

    2016-07-01

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

  2. Gene expression profiling in peanut using oligonucleotide microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

    von Götz, Franz

    2010-03-01

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

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

    PubMed

    Spielbauer, Bettina; Stahl, Frank

    2005-10-01

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

  5. 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).

  6. Application of Microarray Technology to Investigate Salmonella genomics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays were developed for the molecular study of various genes in Salmonella species, which may be important in causing illness in both humans and animals. There are over 2400 Salmonella serotypes each of which differs in their ability to cause disease in humans and animals, persist within the ...

  7. Detection of bacterial pathogens in environmental samples using DNA microarrays.

    PubMed

    Call, Douglas R; Borucki, Monica K; Loge, Frank J

    2003-05-01

    Polymerase chain reaction (PCR) is an important tool for pathogen detection, but historically, it has not been possible to accurately identify PCR products without sequencing, Southern blots, or dot-blots. Microarrays can be coupled with PCR where they serve as a set of parallel dot-blots to enhance product detection and identification. Microarrays are composed of many discretely located probes on a solid substrate such as glass. Each probe is composed of a sequence that is complimentary to a pathogen-specific gene sequence. PCR is used to amplify one or more genes and the products are then hybridized to the array to identify species-specific polymorphism within one or more genes. We illustrate this type of array using 16S rDNA probes suitable for distinguishing between several salmonid pathogens. We also describe the use of microarrays for direct detection of either RNA or DNA without the aid of PCR, although the sensitivity of these systems currently limits their application for pathogen detection. Finally, microarrays can also be used to "fingerprint" bacterial isolates and they can be used to identify diagnostic markers suitable for developing new PCR-based detection assays. We illustrate this type of array for subtyping an important food-borne pathogen, Listeria monocytogenes. PMID:12654494

  8. IDENTIFYING AND MONITORING ENVIRONMENTAL TOXICITY USING CERIODAPHNIA MICROARRAYS - PHASE I

    EPA Science Inventory

    The current U.S. Environmental Protection Agency (EPA) SBIR solicitation states that “technology is needed to better identify and monitor sources of pollution and protect water quality.” Microarrays may be particularly well suited to identifying environmental toxic...

  9. Improved microarray methods for profiling the yeast knockout strain collection

    PubMed Central

    Yuan, Daniel S.; Pan, Xuewen; Ooi, Siew Loon; Peyser, Brian D.; Spencer, Forrest A.; Irizarry, Rafael A.; Boeke, Jef D.

    2005-01-01

    A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens. PMID:15994458

  10. 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 ...

  11. 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.

  12. Assessing Agreement between miRNA Microarray Platforms

    PubMed Central

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

    2014-01-01

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

  13. 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.

  14. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Food Microbial Pathogen Detection and Analysis Using DNA Microarray Technologies

    PubMed Central

    Herold, Keith E.

    2008-01-01

    Abstract Culture-based methods used for microbial detection and identification are simple to use, relatively inexpensive, and sensitive. However, culture-based methods are too time-consuming for high-throughput testing and too tedious for analysis of samples with multiple organisms and provide little clinical information regarding the pathogen (e.g., antibiotic resistance genes, virulence factors, or strain subtype). DNA-based methods, such as polymerase chain reaction (PCR), overcome some these limitations since they are generally faster and can provide more information than culture-based methods. One limitation of traditional PCR-based methods is that they are normally limited to the analysis of a single pathogen, a small group of related pathogens, or a small number of relevant genes. Microarray technology enables a significant expansion of the capability of DNA-based methods in terms of the number of DNA sequences that can be analyzed simultaneously, enabling molecular identification and characterization of multiple pathogens and many genes in a single array assay. Microarray analysis of microbial pathogens has potential uses in research, food safety, medical, agricultural, regulatory, public health, and industrial settings. In this article, we describe the main technical elements of microarray technology and the application and potential use of DNA microarrays for food microbial analysis. PMID:18673074

  18. Microarrays/DNA Chips for the Detection of Waterborne Pathogens.

    PubMed

    Vale, Filipa F

    2016-01-01

    DNA microarrays are useful for the simultaneous detection of microorganisms in water samples. Specific probes targeting waterborne pathogens are selected with bioinformatics tools, synthesized and spotted onto a DNA array. Here, the construction of a DNA chip for waterborne pathogen detection is described, including the processes of probe in silico selection, synthesis, validation, and data analysis. PMID:27460375

  19. Bulk segregant analysis using single nucleotide polymorphism microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Bulk segregant analysis using microarrays, and extreme array mapping have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however require the identification of single feature polymorphisms between the cross parents for each ne...

  20. Analysis of microarray experiments of gene expression profiling

    PubMed Central

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

    2008-01-01

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

  1. 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...

  2. Single nucleotide polymorphism genotyping using BeadChip microarrays.

    PubMed

    Lambert, Gilliam; Tsinajinnie, Darwin; Duggan, David

    2013-07-01

    The genotyping of single nucleotide polymorphisms (SNPs) has successfully contributed to the study of complex diseases more than any other technology to date. Genome-wide association studies (GWAS) using 10,000s to >1,000,000 SNPs have identified 1000s of statistically significant SNPs pertaining to 17 different human disease and trait categories. Post-GWAS fine-mapping studies using 10,000s to 100,000s SNPs on a microarray have narrowed the region of interest for many of these GWAS findings; in addition, independent signals within the original GWAS region have been identified. Focused content, SNP-based microarrays such as the human exome, for example, have too been used successfully to identify novel disease associations. Success has come to studies where 100s to 10,000s (mostly) to >100,000 samples were genotyped. For the time being, SNP-based microarrays remain cost-effective especially when studying large numbers of samples compared to other "genotyping" technologies including next generation sequencing. In this unit, protocols for manual (LIMS-free), semi-manual, and automated processing of BeadChip microarrays are presented. Lower throughput studies will find value in the manual and semi-manual protocols, while all types of studies--low-, medium-, and high-throughput--will find value in the semi-manual and automated protocols. PMID:23853082

  3. Carboxymethyl cellulose film as a substrate for microarray fabrication.

    PubMed

    Shlyapnikov, Yuri M; Shlyapnikova, Elena A; Morozov, Victor N

    2014-02-18

    Magnetic beads (MB) are widely used for quick and highly sensitive signal detection in microarray-based assays. However, this technique imposes stringent requirements for smoothness and adhesive properties of the surface, which most common substrates do not satisfy. We report here a new type of substrate for microarrays with a low adhesion to MB-thermally cross-linked carboxymethyl cellulose (CMC) film. This substrate can be readily fabricated on a conventional glass slide. A highly cross-linked CMC film (∼1 cross-link per monomer unit) possesses a surface smooth on a nanometer scale and a low adhesion to protein-coated MB, which partly originates from electrostatic repulsion of MB from negatively charged CMC surface. The efficiency of the CMC substrate is demonstrated hereby in fabrication of microarrays for the detection of three bacterial toxins: cholera toxin, staphylococcal enterotoxin A, and toxic shock syndrome toxin. The assay employing a primary antibodies arrayed on a CMC surface and detection of the bound bacterial toxins with a biotinylated secondary antibodies and streptavidin-coated MB resulted in a limits of detection as low as 0.1 ng/mL. The CMC-based microarrays demonstrated very high storage stability; their activity did not change after one year storage at room temperature. PMID:24446727

  4. 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.

  5. USING MICROARRAY TECHNOLOGY TO OPTIMIZE ARTIFICIAL DIETS FOR BENEFICIAL INSECTS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An optimized artificial diet is key for the production of high quality beneficial insects at affordable cost. Using a Drosophila microarray chip with 7000 unigenes, several hundred dietary regulated genes were identified in Perillus bioculatus that fed on a suboptimal artificial diet. These dietary ...

  6. 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.

  7. Examination of Oral Cancer Biomarkers by Tissue Microarray Analysis

    PubMed Central

    Choi, Peter; Jordan, C. Diana; Mendez, Eduardo; Houck, John; Yueh, Bevan; Farwell, D. Gregory; Futran, Neal; Chen, Chu

    2008-01-01

    Background Oral squamous cell carcinoma (OSCC) is a major healthcare problem worldwide. Efforts in our laboratory and others focusing on the molecular characterization of OSCC tumors with the use of DNA microarrays have yielded heterogeneous results. To validate the DNA microarray results on a subset of genes from these studies that could potentially serve as biomarkers of OSCC, we elected to examine their expression by an alternate quantitative method and by assessing their protein levels. Design Based on DNA microarray data from our lab and data reported in the literature, we identified six potential biomarkers of OSCC to investigate further. We employed quantitative, real-time polymerase chain reaction (qRT-PCR) to examine expression changes of CDH11, MMP3, SPARC, POSTN, TNC, TGM3 in OSCC and normal control tissues. We further examined validated markers on the protein level by immunohistochemistry (IHC) analysis of OSCC tissue microarray (TMA) sections. Results qRT-PCR analysis revealed up-regulation of CDH11, SPARC, POSTN, and TNC gene expression, and decreased TGM3 expression in OSCC compared to normal controls. MMP3 was not found to be differentially expressed. In TMA IHC analyses, SPARC, periostin, and tenascin C exhibited increased protein expression in cancer compared to normal tissues, and their expression was primarily localized within tumor-associated stroma rather than tumor epithelium. Conversely, transglutaminase-3 protein expression was found only within keratinocytes in normal controls, and was significantly down-regulated in cancer cells. Conclusions Of six potential gene markers of OSCC, initially identified by DNA microarray analyses, differential expression of CDH11, SPARC, POSTN, TNC, and TGM3 were validated by qRT-PCR. Differential expression and localization of proteins encoded by SPARC, POSTN, TNC, and TGM3 were clearly shown by TMA IHC. PMID:18490578

  8. 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

  9. Reordering based integrative expression profiling for microarray classification

    PubMed Central

    2012-01-01

    Background Current network-based microarray analysis uses the information of interactions among concerned genes/gene products, but still considers each gene expression individually. We propose an organized knowledge-supervised approach - Integrative eXpression Profiling (IXP), to improve microarray classification accuracy, and help discover groups of genes that have been too weak to detect individually by traditional ways. To implement IXP, ant colony optimization reordering (ACOR) algorithm is used to group functionally related genes in an ordered way. Results Using Alzheimer's disease (AD) as an example, we demonstrate how to apply ACOR-based IXP approach into microarray classifications. Using a microarray dataset - GSE1297 with 31 samples as training set, the result for the blinded classification on another microarray dataset - GSE5281 with 151 samples, shows that our approach can improve accuracy from 74.83% to 82.78%. A recently-published 1372-probe signature for AD can only achieve 61.59% accuracy in the same condition. The ACOR-based IXP approach also has better performance than the IXP approach based on classic network ranking, graph clustering, and random-ordering methods in an overall classification performance comparison. Conclusions The ACOR-based IXP approach can serve as a knowledge-supervised feature transformation approach to increase classification accuracy dramatically, by transforming each gene expression profile to an integrated expression files as features inputting into standard classifiers. The IXP approach integrates both gene expression information and organized knowledge - disease gene/protein network topology information, which is represented as both network node weights (local topological properties) and network node orders (global topological characteristics). PMID:22536860

  10. Advances in spotted microarray resources for expression profiling.

    PubMed

    Lyons, Paul

    2003-04-01

    The new millennium has ushered in a new era in human biology. The elucidation of the human genome sequence, together with those of model organisms, provides us with an unprecedented insight into the makeup of our genetic blueprint. The challenge now is to figure out how all the constituent pieces fit together to form the whole picture, and the consequences of what happens when the process goes awry. One experimental tool that has the potential to provide enormous insights into this complex process is expression profiling using microarrays. The past few years have seen a considerable growth in the availability and use of microarrays. Fuelled in part by the many genome projects currently underway, there has been a large increase in the number of organisms for which microarray reagents are available from both commercial and academic sources. In addition to the increasing number of genome-wide probe sets that are available, a significant amount of attention has been focussed on generating more targeted probe sets that focus in on specific pathways or biological processes. Finally, the microarray field is starting to see a shift away from the use of cDNAs or polymerase chain reaction (PCR) products as probes towards the use of 50-70mer oligonucleotide probes with all of the potential advantages that they offer. The aim of this review is to provide an overview of what is currently available in terms of spotted microarray reagents both with respect to pre-made arrays and to probe sets available for arraying. PMID:15239940

  11. 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

  12. Biclustering of microarray data with MOSPO based on crowding distance

    PubMed Central

    Liu, Junwan; Li, Zhoujun; Hu, Xiaohua; Chen, Yiming

    2009-01-01

    Background High-throughput microarray technologies have generated and accumulated massive amounts of gene expression datasets that contain expression levels of thousands of genes under hundreds of different experimental conditions. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. The analysis of such datasets can discover local structures composed by sets of genes that show coherent expression patterns under subsets of experimental conditions. It leads to the development of sophisticated algorithms capable of extracting novel and useful knowledge from a biomedical point of view. In the medical domain, these patterns are useful for understanding various diseases, and aid in more accurate diagnosis, prognosis, treatment planning, as well as drug discovery. Results In this work we present the CMOPSOB (Crowding distance based Multi-objective Particle Swarm Optimization Biclustering), a novel clustering approach for microarray datasets to cluster genes and conditions highly related in sub-portions of the microarray data. The objective of biclustering is to find sub-matrices, i.e. maximal subgroups of genes and subgroups of conditions where the genes exhibit highly correlated activities over a subset of conditions. Since these objectives are mutually conflicting, they become suitable candidates for multi-objective modelling. Our approach CMOPSOB is based on a heuristic search technique, multi-objective particle swarm optimization, which simulates the movements of a flock of birds which aim to find food. In the meantime, the nearest neighbour search strategies based on crowding distance and ϵ-dominance can rapidly converge to the Pareto front and guarantee diversity of solutions. We compare the potential of this methodology with other biclustering algorithms by analyzing two common and public datasets of gene expression profiles. In all cases our method can find localized structures

  13. Estimating RNA-quality using GeneChip microarrays

    PubMed Central

    2012-01-01

    Background Microarrays are a powerful tool for transcriptome analysis. Best results are obtained using high-quality RNA samples for preparation and hybridization. Issues with RNA integrity can lead to low data quality and failure of the microarray experiment. Results Microarray intensity data contains information to estimate the RNA quality of the sample. We here study the interplay of the characteristics of RNA surface hybridization with the effects of partly truncated transcripts on probe intensity. The 3′/5′ intensity gradient, the basis of microarray RNA quality measures, is shown to depend on the degree of competitive binding of specific and of non-specific targets to a particular probe, on the degree of saturation of the probes with bound transcripts and on the distance of the probe from the 3′-end of the transcript. Increasing degrees of non-specific hybridization or of saturation reduce the 3′/5′ intensity gradient and if not taken into account, this leads to biased results in common quality measures for GeneChip arrays such as affyslope or the control probe intensity ratio. We also found that short probe sets near the 3′-end of the transcripts are prone to non-specific hybridization presumable because of inaccurate positional assignment and the existence of transcript isoforms with variable 3′ UTRs. Poor RNA quality is associated with a decreased amount of RNA material hybridized on the array paralleled by a decreased total signal level. Additionally, it causes a gene-specific loss of signal due to the positional bias of transcript abundance which requires an individual, gene-specific correction. We propose a new RNA quality measure that considers the hybridization mode. Graphical characteristics are introduced allowing assessment of RNA quality of each single array (‘tongs plot’ and ‘degradation hook’). Furthermore, we suggest a method to correct for effects of RNA degradation on microarray intensities. Conclusions The presented RNA

  14. 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

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

    NASA Astrophysics Data System (ADS)

    Bajcsy, Peter

    2006-12-01

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

  16. 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.

  17. Optical detection of nanoparticle-enhanced human papillomavirus genotyping microarrays.

    PubMed

    Li, Xue Zhe; Kim, Sookyung; Cho, Wonhyung; Lee, Seung-Yop

    2013-02-01

    In this study, we propose a new detection method of nanoparticle-enhanced human papillomavirus genotyping microarrays using a DVD optical pick-up with a photodiode. The HPV genotyping DNA chip was labeled using Au/Ag core-shell nanoparticles, prepared on a treatment glass substrate. Then, the bio information of the HPV genotyping target DNA was detected by measuring the difference of the optical signals between the DNA spots and the background parts for cervical cancer diagnosis. Moreover the approximate linear relationship between the concentration of the HPV genotyping target DNA and the optical signal depending on the density of Au/Ag core-shell nanoparticles was obtained by performing a spot finding algorithm. It is shown that the nanoparticle-labeled HPV genotyping target DNA can be measured and quantified by collecting the low-cost photodiode signal on the treatment glass chip, replacing high-cost fluorescence microarray scanners using a photomultiplier tube. PMID:23413051

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

    PubMed

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

    2010-12-01

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

  19. Coexpression analysis of human genes across many microarray data sets.

    PubMed

    Lee, Homin K; Hsu, Amy K; Sajdak, Jon; Qin, Jie; Pavlidis, Paul

    2004-06-01

    We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function. PMID:15173114

  20. Iterative normalization of cDNA microarray data.

    PubMed

    Wang, Yue; Lu, Jianping; Lee, Richard; Gu, Zhiping; Clarke, Robert

    2002-03-01

    This paper describes a new approach to normalizing microarray expression data. The novel feature is to unify the tasks of estimating normalization coefficients and identifying control gene set. Unification is realized by constructing a window function over the scatter plot defining the subset of constantly expressed genes and by affecting optimization using an iterative procedure. The structure of window function gates contributions to the control gene set used to estimate normalization coefficients. This window measures the consistency of the matched neighborhoods in the scatter plot and provides a means of rejecting control gene outliers. The recovery of normalizational regression and control gene selection are interleaved and are realized by applying coupled operations to the mean square error function. In this way, the two processes bootstrap one another. We evaluate the technique on real microarray data from breast cancer cell lines and complement the experiment with a data cluster visualization study. PMID:11936594

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

    PubMed

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

    2010-01-01

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

  2. 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.

  3. Subpicomolar Iron Sensing Platform Based on Functional Lipid Monolayer Microarrays.

    PubMed

    Kenaan, Ahmad; Nguyen, Tuyen D; Dallaporta, Hervé; Raimundo, Jean-Manuel; Charrier, Anne M

    2016-04-01

    We report herein the fabrication of novel microarrays based on air-stable functional lipid monolayers over silicon using a combination of e-beam lithography and lift-off. We demonstrate these microarrays can be use as ultrasensitive platform for Kelvin probe force microscopy in sensing experiments. Specificity of the detection is given by the functional group grafted at the lipid headgroup. The arrays developed for the detection of ferric ions, Fe(3+), using a γ-pyrone derivative chelator, demonstrate subpicomolar limit of detection with high specificity. In addition, the technique takes advantage of the structure of the array with the silicon areas playing the role of reference for the measurement, and we determine critical pattern dimensions below which the probe size/shape impacts the measured results. PMID:26974586

  4. Application of Tissue Microarray Technology to Stem Cell Research

    PubMed Central

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

    2014-01-01

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

  5. Printing Proteins as Microarrays for High-Throughput Function Determination

    NASA Astrophysics Data System (ADS)

    MacBeath, Gavin; Schreiber, Stuart L.

    2000-09-01

    Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

  6. 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.

  7. Discovering cancer biomarkers from clinical samples by protein microarrays.

    PubMed

    Hu, Bin; Niu, Xin; Cheng, Li; Yang, Li-Na; Li, Qing; Wang, Yang; Tao, Sheng-Ce; Zhou, Shu-Min

    2015-02-01

    Cancer biomarkers are of potential use in early cancer diagnosis, anticancer therapy development, and monitoring the responses to treatments. Protein-based cancer biomarkers are major forms in use, as they are much easier to be monitored in body fluids or tissues. For cancer biomarker discovery, high-throughput techniques such as protein microarrays hold great promises, because they are capable of global unbiased monitoring but with a miniaturized format. In doing so, novel and cancer type specific biomarkers can be systematically discovered at an affordable cost. In this review, we give a relatively complete picture on protein microarrays applied to clinical samples for cancer biomarker discovery, and conclude this review with the future perspectives. PMID:25523829

  8. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

    High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data. PMID:25863787

  9. Aptamer Affinity Maturation by Resampling and Microarray Selection.

    PubMed

    Kinghorn, Andrew B; Dirkzwager, Roderick M; Liang, Shaolin; Cheung, Yee-Wai; Fraser, Lewis A; Shiu, Simon Chi-Chin; Tang, Marco S L; Tanner, Julian A

    2016-07-19

    Aptamers have significant potential as affinity reagents, but better approaches are critically needed to discover higher affinity nucleic acids to widen the scope for their diagnostic, therapeutic, and proteomic application. Here, we report aptamer affinity maturation, a novel aptamer enhancement technique, which combines bioinformatic resampling of aptamer sequence data and microarray selection to navigate the combinatorial chemistry binding landscape. Aptamer affinity maturation is shown to improve aptamer affinity by an order of magnitude in a single round. The novel aptamers exhibited significant adaptation, the complexity of which precludes discovery by other microarray based methods. Honing aptamer sequences using aptamer affinity maturation could help optimize a next generation of nucleic acid affinity reagents. PMID:27346322

  10. 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

  11. 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.

  12. 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. PMID:26490468

  13. Common errors in the implementation and interpretation of microarray studies.

    PubMed

    Reeve, Jeff; Halloran, Philip F; Kaplan, Bruce

    2015-03-01

    Microarray analysis is used to tackle transplant-related problems as diverse as diagnosing rejection, predicting graft loss, and determining who can safely be removed from immunosuppression. Highly accurate predictions seem to be the norm. Unfortunately, many of these studies are flawed, either through questionable experimental design or improper validation methods. In addition, results are often presented in a misleading manner which exaggerates their true worth. In this paper, we describe the most common and serious errors and misrepresentations. PMID:25695786

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

    PubMed Central

    2012-01-01

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

  15. Chromosome microarrays in diagnostic testing: interpreting the genomic data.

    PubMed

    Peters, Greg B; Pertile, Mark D

    2014-01-01

    DNA-based Chromosome MicroArrays (CMAs) are now well established as diagnostic tools in clinical genetics laboratories. Over the last decade, the primary application of CMAs has been the genome-wide detection of a particular class of mutation known as copy number variants (CNVs). Since 2010, CMA testing has been recommended as a first-tier test for detection of CNVs associated with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies…in the post-natal setting. CNVs are now regarded as pathogenic in 14-18 % of patients referred for these (and related) disorders.Through consideration of clinical examples, and several microarray platforms, we attempt to provide an appreciation of microarray diagnostics, from the initial inspection of the microarray data, to the composing of the patient report. In CMA data interpretation, a major challenge comes from the high frequency of clinically irrelevant CNVs observed within "patient" and "normal" populations. As might be predicted, the more common and clinically insignificant CNVs tend to be the smaller ones <100 kb in length, involving few or no known genes. However, this relationship is not at all straightforward: CNV length and gene content are only very imperfect indicators of CNV pathogenicity. Presently, there are no reliable means of separating, a priori, the benign from the pathological CNV classes.This chapter also considers sources of technical "noise" within CMA data sets. Some level of noise is inevitable in diagnostic genomics, given the very large number of data points generated in any one test. Noise further limits CMA resolution, and some miscalling of CNVs is unavoidable. In this, there is no ideal solution, but various strategies for handling noise are available. Even without solutions, consideration of these diagnostic problems per se is informative, as they afford critical insights into the biological and technical underpinnings of CNV discovery. These are indispensable

  16. 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.

  17. 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.

  18. 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. PMID:26822839

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

    PubMed

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

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

  20. 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. PMID:19463569

  1. Rapid bacterial identification using evanescent-waveguide oligonucleotide microarray classification.

    PubMed

    Francois, Patrice; Charbonnier, Yvan; Jacquet, Jean; Utinger, Dominic; Bento, Manuela; Lew, Daniel; Kresbach, Gerhard M; Ehrat, Markus; Schlegel, Werner; Schrenzel, Jacques

    2006-06-01

    Bacterial identification relies primarily on culture-based methodologies and requires 48-72 h to deliver results. We developed and used i) a bioinformatics strategy to select oligonucleotide signature probes, ii) a rapid procedure for RNA labelling and hybridization, iii) an evanescent-waveguide oligoarray with exquisite signal/noise performance, and iv) informatics methods for microarray data analysis. Unique 19-mer signature oligonucleotides were selected in the 5'-end of 16s rDNA genes of human pathogenic bacteria. Oligonucleotides spotted onto a Ta(2)O(5)-coated microarray surface were incubated with chemically labelled total bacterial RNA. Rapid hybridization and stringent washings were performed before scanning and analyzing the slide. In the present paper, the eight most abundant bacterial pathogens representing >54% of positive blood cultures were selected. Hierarchical clustering analysis of hybridization data revealed characteristic patterns, even for closely related species. We then evaluated artificial intelligence-based approaches that outperformed conventional threshold-based identification schemes on cognate probes. At this stage, the complete procedure applied to spiked blood cultures was completed in less than 6 h. In conclusion, when coupled to optimal signal detection strategy, microarrays provide bacterial identification within a few hours post-sampling, allowing targeted antimicrobial prescription. PMID:16216356

  2. 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.

  3. Autonomous system for Web-based microarray image analysis.

    PubMed

    Bozinov, Daniel

    2003-12-01

    Software-based feature extraction from DNA microarray images still requires human intervention on various levels. Manual adjustment of grid and metagrid parameters, precise alignment of superimposed grid templates and gene spots, or simply identification of large-scale artifacts have to be performed beforehand to reliably analyze DNA signals and correctly quantify their expression values. Ideally, a Web-based system with input solely confined to a single microarray image and a data table as output containing measurements for all gene spots would directly transform raw image data into abstracted gene expression tables. Sophisticated algorithms with advanced procedures for iterative correction function can overcome imminent challenges in image processing. Herein is introduced an integrated software system with a Java-based interface on the client side that allows for decentralized access and furthermore enables the scientist to instantly employ the most updated software version at any given time. This software tool is extended from PixClust as used in Extractiff incorporated with Java Web Start deployment technology. Ultimately, this setup is destined for high-throughput pipelines in genome-wide medical diagnostics labs or microarray core facilities aimed at providing fully automated service to its users. PMID:15376911

  4. Multiclass microarray data classification based on confidence evaluation.

    PubMed

    Yu, H L; Gao, S; Qin, B; Zhao, J

    2012-01-01

    Microarray technology is becoming a powerful tool for clinical diagnosis, as it has potential to discover gene expression patterns that are characteristic for a particular disease. To date, this possibility has received much attention in the context of cancer research, especially in tumor classification. However, most published articles have concentrated on the development of binary classification methods while neglected ubiquitous multiclass problems. Unfortunately, only a few multiclass classification approaches have had poor predictive accuracy. In an effort to improve classification accuracy, we developed a novel multiclass microarray data classification method. First, we applied a "one versus rest-support vector machine" to classify the samples. Then the classification confidence of each testing sample was evaluated according to its distribution in feature space and some with poor confidence were extracted. Next, a novel strategy, which we named as "class priority estimation method based on centroid distance", was used to make decisions about categories for those poor confidence samples. This approach was tested on seven benchmark multiclass microarray datasets, with encouraging results, demonstrating effectiveness and feasibility. PMID:22653582

  5. 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. PMID:22957961

  6. 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

  7. Laser-based patterning for transfected cell microarrays.

    PubMed

    Hook, Andrew L; Creasey, Rhiannon; Hayes, Jason P; Thissen, Helmut; Voelcker, Nicolas H

    2009-12-01

    The spatial control over biomolecule- and cell-surface interactions is of great interest to a broad range of biomedical applications, including sensors, implantable devices and cell microarrays. Microarrays in particular require precise spatial control and the formation of patterns with microscale features. Here, we have developed an approach specifically designed for transfected cell microarray (TCM) applications that allows microscale spatial control over the location of both DNA and cells on highly doped p-type silicon substrates. This was achieved by surface modification, involving plasma polymerization of allylamine, grafting of poly(ethylene glycol) and subsequent excimer laser ablation. DNA could be delivered in a spatially defined manner using ink-jet printing. In addition, electroporation was investigated as an approach to transfect attached cells with adsorbed DNA and good transfection efficiencies of approximately 20% were observed. The ability of the microstructured surfaces to spatially direct both DNA adsorption and cell attachment was demonstrated in a functional TCM, making this system an exciting platform for chip-based functional genomics. PMID:20811112

  8. Beyond microarrays: Finding key transcription factors controlling signal transduction pathways

    PubMed Central

    Kel, Alexdander; Voss, Nico; Jauregui, Ruy; Kel-Margoulis, Olga; Wingender, Edgar

    2006-01-01

    Background Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an "echo" of real molecular processes in the cells. Transcription factors constitute a class of the regulatory molecules that typically require posttranscriptional modifications or ligand binding in order to exert their function. Therefore, such important functional changes of transcription factors are not directly visible in the microarray experiments. Results We developed a novel approach to find key transcription factors that may explain concerted expression changes of specific components of the signal transduction network. The approach aims at revealing evidence of positive feedback loops in the signal transduction circuits through activation of pathway-specific transcription factors. We demonstrate that promoters of genes encoding components of many known signal transduction pathways are enriched by binding sites of those transcription factors that are endpoints of the considered pathways. Application of the approach to the microarray gene expression data on TNF-alpha stimulated primary human endothelial cells helped to reveal novel key transcription factors potentially involved in the regulation of the signal transduction pathways of the cells. Conclusion We developed a novel computational approach for revealing key transcription factors by knowledge-based analysis of gene expression data with the help of databases on gene regulatory networks (TRANSFAC® and TRANSPATH®). The corresponding software and databases are available at . PMID:17118134

  9. Retrieving relevant experiments: The case of microRNA microarrays.

    PubMed

    Açıcı, Koray; Terzi, Yunus Kasım; Oğul, Hasan

    2015-08-01

    Content-based retrieval of biological experiments in large public repositories is a recent challenge in computational biology and bioinformatics. The task is, in general, to search in a database using a query-by-example without any experimental meta-data annotation. Here, we consider a more specific problem that seeks a solution for retrieving relevant microRNA experiments from microarray repositories. A computational framework is proposed with this objective. The framework adapts a normal-uniform mixture model for identifying differentially expressed microRNAs in microarray profiling experiments. A rank-based thresholding scheme is offered to binarize real-valued experiment fingerprints based on differential expression. An effective similarity metric is introduced to compare categorical fingerprints, which in turn infers the relevance between two experiments. Two different views of experimental relevance are evaluated, one for disease association and another for embryonic germ layer, to discern the retrieval ability of the proposed model. To the best of our knowledge, the experiment retrieval task is investigated for the first time in the context of microRNA microarrays. PMID:26116091

  10. Genopal™: A Novel Hollow Fibre Array for Focused Microarray Analysis

    PubMed Central

    Okuzaki, Daisuke; Fukushima, Tatsunobu; Tougan, Takahiro; Ishii, Tomonori; Kobayashi, Shigeto; Yoshizaki, Kazuyuki; Akita, Takashi; Nojima, Hiroshi

    2010-01-01

    Expression profiling of target genes in patient blood is a powerful tool for RNA diagnosis. Here, we describe Genopal™, a novel platform ideal for efficient focused microarray analysis. Genopal™, which consists of gel-filled fibres, is advantageous for high-quality mass production via large-scale slicing of the Genopal™ block. We prepared two arrays, infectant and autoimmunity, that provided highly reliable data in terms of repetitive scanning of the same and/or distinct microarrays. Moreover, we demonstrated that Genopal™ had sensitivity sufficient to yield signals in short hybridization times (0.5 h). Application of the autoimmunity array to blood samples allowed us to identify an expression pattern specific to Takayasu arteritis based on the Spearman rank correlation by comparing the reference profile with those of several autoimmune diseases and healthy volunteers (HVs). The comparison of these data with those obtained by other methods revealed that they exhibited similar expression profiles of many target genes. Taken together, these data demonstrate that Genopal™ is an advantageous platform for focused microarrays with regard to its low cost, rapid results and reliable quality. PMID:21059707

  11. Integrated imaging instrument for self-calibrated fluorescence protein microarrays

    NASA Astrophysics Data System (ADS)

    Reddington, A. P.; Monroe, M. R.; Ünlü, M. S.

    2013-10-01

    Protein microarrays, or multiplexed and high-throughput assays, monitor multiple protein binding events to facilitate the understanding of disease progression and cell physiology. Fluorescence imaging is a popular method to detect proteins captured by immobilized probes with high sensitivity and specificity. Reliability of fluorescence assays depends on achieving minimal inter- and intra-assay probe immobilization variation, an ongoing challenge for protein microarrays. Therefore, it is desirable to establish a label-free method to quantify the probe density prior to target incubation to calibrate the fluorescence readout. Previously, a silicon oxide on silicon chip design was introduced to enhance the fluorescence signal and enable interferometric imaging to self-calibrate the signal with the immobilized probe density. In this paper, an integrated interferometric reflectance imaging sensor and wide-field fluorescence instrument is introduced for sensitive and calibrated microarray measurements. This platform is able to analyze a 2.5 mm × 3.4 mm area, or 200 spots (100 μm diameter with 200 μm pitch), in a single field-of-view.

  12. ArrayPipe: a flexible processing pipeline for microarray data.

    PubMed

    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

    2004-07-01

    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

  13. DNA microarray for tracing Salmonella in the feed chain.

    PubMed

    Koyuncu, Sevinc; Andersson, Gunnar; Vos, Pieter; Häggblom, Per

    2011-03-01

    In the present study we investigated if the microarray platforms Premi®Test Salmonella (PTS) and Salmonella array (SA) could be applied for the identification and typing of Salmonella in artificially contaminated animal feed materials. The results were compared to the culture-based MSRV method and serotyping according to Kauffman-White. The SA platform showed a specificity of 100% for the identification of Salmonella compared to 93% with the PTS platform and a sensitivity of 99% or 100%, respectively. Among all identified Salmonella serotypes, 56% with the SA platform and 81% with the PTS platform were correctly identified. The difference in probe signal intensity for each probe was higher between duplicates analyzed with the SA platform than with the PTS platform. Attempts to use the microarray platforms from BPW resulted in many false negative samples and incorrect typing results. The microarray platforms tested were simple to use and might have a potential in tracing studies for Salmonella in the feed chain particularly when rapid information about serotypes are important. PMID:20688409

  14. Classification of Microarray Data Using Kernel Fuzzy Inference System

    PubMed Central

    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.

  15. 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

  16. 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...

  17. Microarrays as a diagnostic tool in prenatal screening strategies: ethical reflection.

    PubMed

    de Jong, Antina; Dondorp, Wybo J; Macville, Merryn V E; de Die-Smulders, Christine E M; van Lith, Jan M M; de Wert, Guido M W R

    2014-02-01

    Genomic microarray analysis is increasingly being applied as a prenatal diagnostic tool. Microarrays enable searching the genome at a higher resolution and with higher sensitivity than conventional karyotyping for identifying clinically significant chromosomal abnormalities. As yet, no clear guidelines exist on whether microarrays should be applied prenatally for all indications or only in selected cases such as ultrasound abnormalities, whether a targeted or genome-wide array should be used, and what these should include exactly. In this paper, we present some ethical considerations on the prenatal use of microarrays. There is a strong consensus, at least in Western countries, that the aim of prenatal screening for foetal abnormalities should be understood as facilitating autonomous reproductive choice for prospective parents. The tests offered should be valid and useful to reach that purpose. Against this background, we address several ethical issues raised by the prenatal application of microarrays. First, we argue that the general distinction between a targeted and a genome-wide microarray needs to be scrutinised. Then we examine whether microarrays are 'suitable tests' to serve either a screening or a diagnostic purpose. Given the wide range of findings possibly generated by microarrays, the question arises whether microarrays actually promote or interfere with autonomous reproductive decision-making. Moreover, if variants of unknown clinical significance are identified, this adds to the burden and complexity of reproductive decision-making. We suggest a qualified use of microarrays in the prenatal context. PMID:24077959

  18. 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

  19. Design and development of a microarray processing station (MPS) for automated miniaturized immunoassays.

    PubMed

    Pla-Roca, Mateu; Altay, Gizem; Giralt, Xavier; Casals, Alícia; Samitier, Josep

    2016-08-01

    Here we describe the design and evaluation of a fluidic device for the automatic processing of microarrays, called microarray processing station or MPS. The microarray processing station once installed on a commercial microarrayer allows automating the washing, and drying steps, which are often performed manually. The substrate where the assay occurs remains on place during the microarray printing, incubation and processing steps, therefore the addressing of nL volumes of the distinct immunoassay reagents such as capture and detection antibodies and samples can be performed on the same coordinate of the substrate with a perfect alignment without requiring any additional mechanical or optical re-alignment methods. This allows the performance of independent immunoassays in a single microarray spot. PMID:27405464

  20. 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.

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

    PubMed

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

    2011-01-01

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

  2. 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.

  3. Quantitative dose-response curves from subcellular lipid multilayer microarrays.

    PubMed

    Kusi-Appiah, A E; Lowry, T W; Darrow, E M; Wilson, K A; Chadwick, B P; Davidson, M W; Lenhert, S

    2015-08-21

    The dose-dependent bioactivity of small molecules on cells is a crucial factor in drug discovery and personalized medicine. Although small-molecule microarrays are a promising platform for miniaturized screening, it has been a challenge to use them to obtain quantitative dose-response curves in vitro, especially for lipophilic compounds. Here we establish a small-molecule microarray assay capable of controlling the dosage of small lipophilic molecules delivered to cells by varying the sub-cellular volumes of surface supported lipid micro- and nanostructure arrays fabricated with nanointaglio. Features with sub-cellular lateral dimensions were found necessary to obtain normal cell adhesion with HeLa cells. The volumes of the lipophilic drug-containing nanostructures were determined using a fluorescence microscope calibrated by atomic-force microscopy. We used the surface supported lipid volume information to obtain EC-50 values for the response of HeLa cells to three FDA-approved lipophilic anticancer drugs, docetaxel, imiquimod and triethylenemelamine, which were found to be significantly different from neat lipid controls. No significant toxicity was observed on the control cells surrounding the drug/lipid patterns, indicating lack of interference or leakage from the arrays. Comparison of the microarray data to dose-response curves for the same drugs delivered liposomally from solution revealed quantitative differences in the efficacy values, which we explain in terms of cell-adhesion playing a more important role in the surface-based assay. The assay should be scalable to a density of at least 10,000 dose response curves on the area of a standard microtiter plate. PMID:26167949

  4. Quantitative Dose-Response Curves from Subcellular Lipid Multilayer Microarrays

    PubMed Central

    Kusi-Appiah, A. E.; Lowry, T. W.; Darrow, E. M.; Wilson, K.; Chadwick, B. P.; Davidson, M. W.; Lenhert, S.

    2015-01-01

    The dose-dependent bioactivity of small molecules on cells is a crucial factor in drug discovery and personalized medicine. Although small-molecule microarrays are a promising platform for miniaturized screening, it has been a challenge to use them to obtain quantitative dose-response curves in vitro, especially for lipophilic compounds. Here we establish a small-molecule microarray assay capable of controlling the dosage of small lipophilic molecules delivered to cells by varying the sub-cellular volumes of surface supported lipid micro- and nanostructure arrays fabricated with nanointaglio. Features with sub-cellular lateral dimensions were found necessary to obtain normal cell adhesion with HeLa cells. The volumes of the lipophilic drug-containing nanostructures were determined using a fluorescence microscope calibrated by atomic-force microscopy. We used the surface supported lipid volume information to obtain EC-50 values for the response of HeLa cells to three FDA-approved lipophilic anticancer drugs, docetaxel, imiquimod and triethylenemelamine, which were found to be significantly different from neat lipid controls. No significant toxicity was observed on the control cells surrounding the drug/lipid patterns, indicating lack of interference or leakage from the arrays. Comparison of the microarray data to dose-response curves for the same drugs delivered liposomally from solution revealed quantitative differences in the efficacy values, which we explain in terms of cell-adhesion playing a more important role in the surface-based assay. The assay should be scalable to a density of at least 10,000 dose response curves on the area of a standard microtiter plate. PMID:26167949

  5. 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. PMID:19020556

  6. Immobilization strategies for single-chain antibody microarrays

    SciTech Connect

    Seurynck-Servoss, Shannon L.; Baird, Cheryl L.; Miller, Keith D.; Pefaur, Noah B.; Gonzalez, Rachel M.; Apiyo, David O.; Engelmann, Heather E.; Srinivastava, Sudhir; Kagan, Jacob; Rodland, Karin D.; Zangar, Richard C.

    2008-06-01

    Sandwich enzyme-linked immunosorbent assay (ELISA) microarrays have great potential for validating biomarkers of disease. ELISA relies on robust affinity reagents that retain activity when immobilized or when labeled for detection. Single-chain antibodies (scFv) are affinity reagents that have greater potential for high-throughput production than traditional immunoglobin G (IgG). Unfortunately, scFv are typically less stabile than IgG and not always suitable for use in sandwich ELISAs. We therefore investigated different immobilization strategies and scFv structural modifications to see if we could develop a more robust scFv reagent. Two promising strategies that emerged from these studies: 1) the precapture of epitope-tagged scFv using an anti-epitope antibody and 2) the direct printing of a thioredoxin/scFv fusion protein on glass slides. The use of either strategy improved the stability of immobilized scFv and increased the sensitivity of the scFv ELISA microarray assays, although the anti-epitope precapture method had a risk of reagent transfer. Using the direct printing method, we show that anti-PSA scFv are highly specific when tested against 21 different IgG-based assays. Finally, the scFv microarray PSA assay gave comparable results (R2 = 0.95) to a commercial 96-well ELISA when tested using serum samples. Overall, these results suggest that minor modifications of the scFv protein structure are sufficiently to produce reagents that are suitable for use in multiplex assay systems.

  7. A hybrid imputation approach for microarray missing value estimation

    PubMed Central

    2015-01-01

    Background Missing data is an inevitable phenomenon in gene expression microarray experiments due to instrument failure or human error. It has a negative impact on performance of downstream analysis. Technically, most existing approaches suffer from this prevalent problem. Imputation is one of the frequently used methods for processing missing data. Actually many developments have been achieved in the research on estimating missing values. The challenging task is how to improve imputation accuracy for data with a large missing rate. Methods In this paper, induced by the thought of collaborative training, we propose a novel hybrid imputation method, called Recursive Mutual Imputation (RMI). Specifically, RMI exploits global correlation information and local structure in the data, captured by two popular methods, Bayesian Principal Component Analysis (BPCA) and Local Least Squares (LLS), respectively. Mutual strategy is implemented by sharing the estimated data sequences at each recursive process. Meanwhile, we consider the imputation sequence based on the number of missing entries in the target gene. Furthermore, a weight based integrated method is utilized in the final assembling step. Results We evaluate RMI with three state-of-art algorithms (BPCA, LLS, Iterated Local Least Squares imputation (ItrLLS)) on four publicly available microarray datasets. Experimental results clearly demonstrate that RMI significantly outperforms comparative methods in terms of Normalized Root Mean Square Error (NRMSE), especially for datasets with large missing rates and less complete genes. Conclusions It is noted that our proposed hybrid imputation approach incorporates both global and local information of microarray genes, which achieves lower NRMSE values against to any single approach only. Besides, this study highlights the need for considering the imputing sequence of missing entries for imputation methods. PMID:26330180

  8. 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

  9. Profiling DNA Methylomes from Microarray to Genome-Scale Sequencing

    PubMed Central

    Huang, Yi-Wen; Huang, Tim H.-M.; Wang, Li-Shu

    2010-01-01

    DNA cytosine methylation is a central epigenetic modification which plays critical roles in cellular processes including genome regulation, development and disease. Here, we review current and emerging microarray and next-generation sequencing based technologies that enhance our knowledge of DNA methylation profiling. Each methodology has limitations and their unique applications, and combinations of several modalities may help build the entire methylome. With advances on next-generation sequencing technologies, it is now possible to globally map the DNA cytosine methylation at single-base resolution, providing new insights into the regulation and dynamics of DNA methylation in genomes. PMID:20218736

  10. Profiling DNA methylomes from microarray to genome-scale sequencing.

    PubMed

    Huang, Yi-Wei; Huang, Tim H-M; Wang, Li-Shu

    2010-04-01

    DNA cytosine methylation is a central epigenetic modification which plays critical roles in cellular processes including genome regulation, development and disease. Here, we review current and emerging microarray and next-generation sequencing based technologies that enhance our knowledge of DNA methylation profiling. Each methodology has limitations and their unique applications, and combinations of several modalities may help build the entire methylome. With advances on next-generation sequencing technologies, it is now possible to globally map the DNA cytosine methylation at single-base resolution, providing new insights into the regulation and dynamics of DNA methylation in genomes. PMID:20218736

  11. Glycan Profiling of Plant Cell Wall Polymers using Microarrays

    PubMed Central

    Moller, Isabel E.; Pettolino, Filomena A.; Hart, Charlie; Lampugnani, Edwin R.; Willats, William G.T.; Bacic, Antony

    2012-01-01

    to determine the relative abundance of glycans in a broad range of plant and tissue types simultaneously9,10,11. Here we present a microarray-based glycan screening method called Comprehensive Microarray Polymer Profiling (CoMPP) (Figures 1 & 2)10,11 that enables multiple samples (100 sec) to be screened using a miniaturised microarray platform with reduced reagent and sample volumes. The spot signals on the microarray can be formally quantified to give semi-quantitative data about glycan epitope occurrence. This approach is well suited to tracking glycan changes in complex biological systems12 and providing a global overview of cell wall composition particularly when prior knowledge of this is unavailable. PMID:23271573

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

    PubMed Central

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

    2015-01-01

    We have recently identified lymphatic endothelial cells (LECs) to form two morphologically different populations, exhibiting significantly different surface protein expression levels of podoplanin, a major surface marker for this cell type. In vitro shockwave treatment (IVSWT) of LECs resulted in enrichment of the podoplaninhigh cell population and was accompanied by markedly increased cell proliferation, as well as 2D and 3D migration. Gene expression profiles of these distinct populations were established using Affymetrix microarray analyses. Here we provide additional details about our dataset (NCBI GEO accession number GSE62510) and describe how we analyzed the data to identify differently expressed genes in these two LEC populations. PMID:26484194

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

    NASA Astrophysics Data System (ADS)

    Ewart, Tom; Carmichael, Stuart; Lea, Peter

    2005-09-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Bhatnagar, Parijat

    2007-07-01

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

  16. A cooperative polymer-DNA microarray approach to biomaterial investigation.

    PubMed

    Pernagallo, Salvatore; Diaz-Mochon, Juan Jose; Bradley, Mark

    2009-02-01

    In this study, polymer microarrays were used for the rapid identification of polymer substrates upon which a suspension cell line would both adhere and proliferate giving a detailed and rapid understanding of cell-biomaterial interactions. Analysis demonstrated that suspension K562 human erythroleukemic cells, which normally grow in suspension, adhered and proliferated on several different polymers. Phenotypic and transcriptomic analysis techniques allowed examination of the interaction between cells and polymers permitting the elucidation of putative links between phenotypic responses to cell-biomaterial interactions and global gene expression. PMID:19156288

  17. Technical considerations in using DNA microarrays to define regulons.

    PubMed

    Rhodius, Virgil A; Wade, Joseph T

    2009-01-01

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

  18. 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.

  19. L2L: a simple tool for discovering the hidden significance in microarray expression data

    PubMed Central

    Newman, John C; Weiner, Alan M

    2005-01-01

    L2L is a database consisting of lists of differentially expressed genes compiled from published mammalian microarray studies, along with an easy-to-use application for mining the database with the user's own microarray data. As illustrated by re-analysis of a recent study of diabetic nephropathy, L2L identifies novel biological patterns in microarray data, providing insights into the underlying nature of biological processes and disease. L2L is available online at the authors' website []. PMID:16168088

  20. A review of independent component analysis application to microarray gene expression data

    PubMed Central

    Kong, Wei; Vanderburg, Charles R.; Gunshin, Hiromi; Rogers, Jack T.; Huang, Xudong

    2010-01-01

    Independent component analysis (ICA) methods have received growing attention as effective data-mining tools for microarray gene expression data. As a technique of higher-order statistical analysis, ICA is capable of extracting biologically relevant gene expression features from microarray data. Herein we have reviewed the latest applications and the extended algorithms of ICA in gene clustering, classification, and identification. The theoretical frameworks of ICA have been described to further illustrate its feature extraction function in microarray data analysis. PMID:19007336

  1. Simulation and visualization of flow pattern in microarrays for liquid phase oligonucleotide and peptide synthesis.

    PubMed

    O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

    2007-01-01

    Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053

  2. SIMULATION AND VISUALIZATION OF FLOW PATTERN IN MICROARRAYS FOR LIQUID PHASE OLIGONUCLEOTIDE AND PEPTIDE SYNTHESIS

    PubMed Central

    O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

    2008-01-01

    Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053

  3. Exploration of high-density protein microarrays for antibody validation and autoimmunity profiling.

    PubMed

    Sjöberg, Ronald; Mattsson, Cecilia; Andersson, Eni; Hellström, Cecilia; Uhlen, Mathias; Schwenk, Jochen M; Ayoglu, Burcu; Nilsson, Peter

    2016-09-25

    High-density protein microarrays of recombinant human protein fragments, representing 12,412 unique Ensembl Gene IDs, have here been produced and explored. These protein microarrays were used to analyse antibody off-target interactions, as well as for profiling the human autoantibody repertoire in plasma against the antigens represented by the protein fragments. Affinity-purified polyclonal antibodies produced within the Human Protein Atlas (HPA) were analysed on microarrays of three different sizes, ranging from 384 antigens to 21,120 antigens, for evaluation of the antibody validation criteria in the HPA. Plasma samples from secondary progressive multiple sclerosis patients were also screened in order to explore the feasibility of these arrays for broad-scale profiling of autoantibody reactivity. Furthermore, analysis on these near proteome-wide microarrays was complemented with analysis on HuProt™ Human Proteome protein microarrays. The HPA recombinant protein microarray with 21,120 antigens and the HuProt™ Human Proteome protein microarray are currently the largest protein microarray platforms available to date. The results on these arrays show that the Human Protein Atlas antibodies have few off-target interactions if the antibody validation criteria are kept stringent and demonstrate that the HPA-produced high-density recombinant protein fragment microarrays allow for a high-throughput analysis of plasma for identification of possible autoantibody targets in the context of various autoimmune conditions. PMID:26417875

  4. Undulate microarray fabrication on polymer film using standing surface acoustic waves and ultraviolet polymerization

    NASA Astrophysics Data System (ADS)

    Mei, Deqing; Xue, Dai; Wang, Yancheng; Chen, Shaochen

    2016-06-01

    By exciting standing surface acoustic waves (SAWs), a monomer solution can be shaped into a wavy structure. By applying ultraviolet (UV) polymerization, a linear undulate microarray can be fabricated on the polymer material using one-dimensional standing SAWs. When two-dimensional standing SAWs are applied, a latticed microarray, which presents periodically distributed bumps and wells, can be fabricated. The periodicity of the undulate microarray is dependent on the SAW wavelength. Also, the undulating amplitude of the microarray is tunable when applying different input voltages to generate SAWs. The integrated standing SAWs and UV polymerization process provide a rapid method for creating periodic surface patterns.

  5. 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

  6. DNA microarrays for hybridization detection by surface plasmon resonance spectroscopy.

    PubMed

    Kick, Alfred; Bönsch, Martin; Katzschner, Beate; Voigt, Jan; Herr, Alexander; Brabetz, Werner; Jung, Martin; Sonntag, Frank; Klotzbach, Udo; Danz, Norbert; Howitz, Steffen; Mertig, Michael

    2010-12-15

    We report on the development of a new platform technology for the detection of genetic variations by means of surface plasmon resonance (SPR) spectroscopy. TOPAS chips with integrated optics were exploited in combination with microfluidics. Within minutes, the detection of hybridization kinetics was achieved simultaneously at all spots of the DNA microarray. A nanoliter dispenser is used to deposit thiol-modified single-stranded probe DNA on the gold surface of the chips. We investigated the influence of different parameters on hybridization using model polymerase chain reaction (PCR) products. These PCR products comprised a single-stranded tag sequence being complementary to an anti-tag sequence of probes immobilized on the gold surface. The signals increased with increasing length of PCR products (60, 100 or 300 base pairs) as well as with their concentration. We investigated hybridizations on DNA microarrays comprising 90 spots of probe DNA with three different sequences. Furthermore, we demonstrate that sequences with possible hairpin structures significantly lower the binding rate, and thus, the SPR signals during hybridization. PMID:20729067

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-01-01

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

  9. 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

  10. 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. PMID:24012817

  11. Microarrays of phospholipid bilayers generated by inkjet printing.

    PubMed

    Yamada, Misato; Imaishi, Hiromasa; Morigaki, Kenichi

    2013-05-28

    We report an efficient and reproducible method to generate a microarray of model biological membranes on a solid substrate by applying the inkjet printing technology. Although inkjet printing is currently widely used for industrial fabrication processes, including biological materials, printing lipid membranes remains technically challenging due to the hydrophobic nature of droplets and instability of the lipid bilayer structure against dehydration. In the present study, we printed lipids onto a glass substrate covered with a micropatterned membrane of a polymeric phospholipid bilayer. Polymeric bilayers were formed by the lithographic photopolymerization of a diacetylene-containing phospholipid, 1,2-bis(10,12-tricosadiynoyl)-sn-glycero-3-phosphocholine (DiynePC). After removal of nonpolymerized DiynePC with a detergent solution, natural lipid membranes were incorporated into the polymer-free regions (corrals) by using an electric-field-based inkjet printing device that can eject subfemtoliter volume droplets. To avoid rapid dehydration and destabilization, we preprinted an aqueous solution containing agarose and trehalose onto the corrals and subsequently printed lipid suspensions ("two-step-printing method"). After rinsing, stable lipid bilayer membranes were formed in the corrals. The bilayers were continuous and fluid as confirmed by fluorescence recovery after photobleaching. We could introduce multiple bilayer patches having different lipid compositions into the neighboring corrals. The present results demonstrate that the combination of a patterned polymeric bilayer and inkjet printing technology enables efficient, reliable, and scalable generation of the model membrane microarrays having varied compositions. PMID:23627772

  12. 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

  13. Genetic programming based ensemble system for microarray data classification.

    PubMed

    Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

    2015-01-01

    Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved. PMID:25810748

  14. 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. PMID:25287505

  15. Pattern recognition techniques in microarray data analysis: a survey.

    PubMed

    Valafar, Faramarz

    2002-12-01

    Recent development of technologies (e.g., microarray technology) that are capable of producing massive amounts of genetic data has highlighted the need for new pattern recognition techniques that can mine and discover biologically meaningful knowledge in large data sets. Many researchers have begun an endeavor in this direction to devise such data-mining techniques. As such, there is a need for survey articles that periodically review and summarize the work that has been done in the area. This article presents one such survey. The first portion of the paper is meant to provide the basic biology (mostly for non-biologists) that is required in such a project. This part is only meant to be a starting point for those experts in the technical fields who wish to embark on this new area of bioinformatics. The second portion of the paper is a survey of various data-mining techniques that have been used in mining microarray data for biological knowledge and information (such as sequence information). This survey is not meant to be treated as complete in any form, since the area is currently one of the most active, and the body of research is very large. Furthermore, the applications of the techniques mentioned here are not meant to be taken as the most significant applications of the techniques, but simply as examples among many. PMID:12594081

  16. Attachment of motile bacterial cells to prealigned holed microarrays.

    PubMed

    Rozhok, Sergey; Fan, Zhifang; Nyamjav, Dorjderem; Liu, Chang; Mirkin, Chad A; Holz, Richard C

    2006-12-19

    Construction of biomotors is an exciting area of scientific research that holds great promise for the development of new technologies with broad potential applications in areas such as the energy industry and medicine. Herein, we demonstrate the fabrication of prealigned microarrays of motile Escherichia coli bacterial cells on SiOx substrates. To prepare these arrays, holed surfaces with a gold layer on the bottom of the holes were utilized. The attachment of bacteria to the holes was achieved via nonspecific interactions using poly-l-lysine hydrobromide (PLL). Our data suggest that a single motile bacterial cell can be selectively attached to an individual hole on a surface and bacterial cell binding can be controlled by altering the pH, with the greatest occupancy occurring at pH 7.8. Cells attached to hole arrays remained motile for at least 4 h. These data indicate that holed surface structures provide a promising footprint for the attachment of motile bacterial cells to form high-density site-specific functional bacterial microarrays. PMID:17154612

  17. 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

  18. Rank-based algorithms for anlaysis of microarrays

    NASA Astrophysics Data System (ADS)

    Liu, Wei-min; Mei, Rui; Bartell, Daniel M.; Di, Xiaojun; Webster, Teresa A.; Ryder, Tom

    2001-06-01

    Analysis of microarray data often involves extracting information from raw intensities of spots of cells and making certain calls. Rank-based algorithms are powerful tools to provide probability values of hypothesis tests, especially when the distribution of the intensities is unknown. For our current gene expression arrays, a gene is detected by a set of probe pairs consisting of perfect match and mismatch cells. The one-sided upper-tail Wilcoxon's signed rank test is used in our algorithms for absolute calls (whether a gene is detected or not), as well as comparative calls (whether a gene is increasing or decreasing or no significant change in a sample compared with another sample). We also test the possibility to use only perfect match cells to make calls. This paper focuses on absolute calls. We have developed error analysis methods and software tools that allow us to compare the accuracy of the calls in the presence or absence of mismatch cells at different target concentrations. The usage of nonparametric rank-based tests is not limited to absolute and comparative calls of gene expression chips. They can also be applied to other oligonucleotide microarrays for genotyping and mutation detection, as well as spotted arrays.

  19. Polymer Microarrays for High Throughput Discovery of Biomaterials

    PubMed Central

    Hook, Andrew L.; Chang, Chien-Yi; Yang, Jing; Scurr, David J.; Langer, Robert; Anderson, Daniel G.; Atkinson, Steve; Williams, Paul; Davies, Martyn C.; Alexander, Morgan R.

    2012-01-01

    The discovery of novel biomaterials that are optimized for a specific biological application is readily achieved using polymer microarrays, which allows a combinatorial library of materials to be screened in a parallel, high throughput format1. Herein is described the formation and characterization of a polymer microarray using an on-chip photopolymerization technique 2. This involves mixing monomers at varied ratios to produce a library of monomer solutions, transferring the solution to a glass slide format using a robotic printing device and curing with UV irradiation. This format is readily amenable to many biological assays, including stem cell attachment and proliferation, cell sorting and low bacterial adhesion, allowing the ready identification of 'hit' materials that fulfill a specific biological criterion3-5. Furthermore, the use of high throughput surface characterization (HTSC) allows the biological performance to be correlated with physio-chemical properties, hence elucidating the biological-material interaction6. HTSC makes use of water contact angle (WCA) measurements, atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS). In particular, ToF-SIMS provides a chemically rich analysis of the sample that can be used to correlate the cell response with a molecular moiety. In some cases, the biological performance can be predicted from the ToF-SIMS spectra, demonstrating the chemical dependence of a biological-material interaction, and informing the development of hit materials5,3. PMID:22314927

  20. Multiplex component-based allergen microarray in recent clinical studies.

    PubMed

    Patelis, A; Borres, M P; Kober, A; Berthold, M

    2016-08-01

    During the last decades component-resolved diagnostics either as singleplex or multiplex measurements has been introduced into the field of clinical allergology, providing important information that cannot be obtained from extract-based tests. Here we review recent studies that demonstrate clinical applications of the multiplex microarray technique in the diagnosis and risk assessment of allergic patients, and its usefulness in studies of allergic diseases. The usefulness of ImmunoCAP ISAC has been validated in a wide spectrum of allergic diseases like asthma, allergic rhinoconjunctivitis, atopic dermatitis, eosinophilic esophagitis, food allergy and anaphylaxis. ISAC provides a broad picture of a patient's sensitization profile from a single test, and provides information on specific and cross-reactive sensitizations that facilitate diagnosis, risk assessment, and disease management. Furthermore, it can reveal unexpected sensitizations which may explain anaphylaxis previously categorized as idiopathic and also display for the moment clinically non-relevant sensitizations. ISAC can facilitate a better selection of relevant allergens for immunotherapy compared with extract testing. Microarray technique can visualize the allergic march and molecular spreading in the preclinical stages of allergic diseases, and may indicate that the likelihood of developing symptomatic allergy is associated with specific profiles of sensitization to allergen components. ISAC is shown to be a useful tool in routine allergy diagnostics due to its ability to improve risk assessment, to better select relevant allergens for immunotherapy as well as detecting unknown sensitization. Multiplex component testing is especially suitable for patients with complex symptomatology. PMID:27196983

  1. Biocompatible Hydrogels for Microarray Cell Printing and Encapsulation.

    PubMed

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

    2015-12-01

    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

  2. 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

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

    PubMed

    Bavykin, S G; Akowski, J P; Zakhariev, V M; Barsky, V E; Perov, A N; Mirzabekov, A D

    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. PMID:11157263

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

    SciTech Connect

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

    2001-02-01

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

  5. Validation of analytical breast cancer microarray analysis in medical laboratory.

    PubMed

    Darweesh, Amal Said; Louka, Manal Louis; Hana, Maha; Rashad, Shaymaa; El-Shinawi, Mohamed; Sharaf-Eldin, Ahmed; Kassim, Samar Kamal

    2014-10-01

    A previously reported microarray data analysis by RISS algorithm on breast cancer showed over-expression of the growth factor receptor (Grb7) and it also highlighted Tweety (TTYH1) gene to be under expressed in breast cancer for the first time. Our aim was to validate the results obtained from the microarray analysis with respect to these genes. Also, the relationship between their expression and the different prognostic indicators was addressed. RNA was extracted from the breast tissue of 30 patients with primary malignant breast cancer. Control samples from the same patients were harvested at a distance of ≥5 cm from the tumour. Semi-quantitative RT-PCR analysis was done on all samples. There was a significant difference between the malignant and control tissues as regards Grb7 expression. It was significantly related to the presence of lymph node metastasis, stage and histological grade of the malignant tumours. There was a significant inverse relation between expression of Grb7 and expression of both oestrogen and progesterone receptors. Grb7 was found to be significantly related to the biological classification of breast cancer. TTYH1 was not expressed in either the malignant or the control samples. The RISS by our group algorithm developed was laboratory validated for Grb7, but not for TTYH1. The newly developed software tool needs to be improved. PMID:25182704

  6. 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

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

    PubMed

    Palmer, Ella; Freeman, Tom

    2005-07-01

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

  8. Single-Round Patterned DNA Library Microarray Aptamer Lead Identification

    PubMed Central

    Martin, Jennifer A.; Mirau, Peter A.; Chushak, Yaroslav; Chávez, Jorge L.; Naik, Rajesh R.; Hagen, Joshua A.; Kelley-Loughnane, Nancy

    2015-01-01

    A method for identifying an aptamer in a single round was developed using custom DNA microarrays containing computationally derived patterned libraries incorporating no information on the sequences of previously reported thrombin binding aptamers. The DNA library was specifically designed to increase the probability of binding by enhancing structural complexity in a sequence-space confined environment, much like generating lead compounds in a combinatorial drug screening library. The sequence demonstrating the highest fluorescence intensity upon target addition was confirmed to bind the target molecule thrombin with specificity by surface plasmon resonance, and a novel imino proton NMR/2D NOESY combination was used to screen the structure for G-quartet formation. We propose that the lack of G-quartet structure in microarray-derived aptamers may highlight differences in binding mechanisms between surface-immobilized and solution based strategies. This proof-of-principle study highlights the use of a computational driven methodology to create a DNA library rather than a SELEX based approach. This work is beneficial to the biosensor field where aptamers selected by solution based evolution have proven challenging to retain binding function when immobilized on a surface. PMID:26075138

  9. 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.

  10. 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.

  11. Small molecule microarrays for drug residue detection in foodstuffs.

    PubMed

    Peng, Zuo; Bang-Ce, Ye

    2006-09-20

    Microarrays have been used as tools for analyzing biological compositions at different levels. In this study, we proposed a small molecule microarray (SMM) method for detection of three veterinary drug residues, chloramphenicol, clenbuterol, and tylosin, in foodstuffs simultaneously and quantitatively. The small drug molecules were immobilized on the surface of the modified glass slides. Then the mixture of drug corresponding antibodies and standards or samples was added to the reaction area. After incubation, the antigen-antibody binding was detected using cy5 labeled secondary antibody. The calibration curves of the residues were drawn, and they indicated the lowest detection limit the linearity range. The detectable concentrations of the three residues are lower than the maximum residue levels (MRLs). No cross reactivity was found among the three residues. The coefficient of variation of the spot intensities was below 5% in a subarray, and below 15% among subarrays. The spike sample test and the comparison of detection results by SMMs and ELISA demonstrated the accuracy of the proposed SMMs method. PMID:16968051

  12. Tracking Humoral Responses Using Self Assembling Protein Microarrays

    PubMed Central

    Ramachandran, Niroshan; Anderson, Karen S.; Raphael, Jacob v.; Hainsworth, Eugenie; Sibani, Sahar; Montor, Wagner R.; Pacek, Marcin; Wong, Jessica; Eljanne, Mariam; Sanda, Martin G.; Hu, Yanhui; Logvinenko, Tanya; LaBaer, Joshua

    2011-01-01

    The humoral immune response is a highly specific and adaptive sensor for changes in the body's protein milieu, which responds to novel structures of both foreign and self antigens. Although immunoglobulins represent a major component of human serum and are vital to survival, little is known about the response specificity and determinants that govern the human immunome. Historically, antigen-specific humoral immunity has been investigated using individually-produced and purified target proteins, a labor-intensive process that has limited the number of antigens that have been studied. Here, we present the development of methods for applying self-assembling protein microarrays and a related method for producing 96-well formatted macroarrays for monitoring the humoral response at the proteome scale. Using plasmids encoding full-length cDNAs for over 850 human proteins and 1700 pathogen proteins, we demonstrate that these microarrays are highly sensitive, specific, reproducible, and can simultaneously measure immunity to thousands of proteins without a priori protein purification. Using this approach, we demonstrate the detection of humoral immunity to known and novel self-antigens, cancer antigens, autoimmune antigens, as well as pathogen-derived antigens. This represents a powerful and versatile tool for monitoring the immunome in health and disease. PMID:21136799

  13. 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

  14. 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. PMID:16098712

  15. A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

    PubMed Central

    2010-01-01

    Background Microarrays are invaluable tools for genome interrogation, SNP detection, and expression analysis, among other applications. Such broad capabilities would be of value to many pathogen research communities, although the development and use of genome-scale microarrays is often a costly undertaking. Therefore, effective methods for reducing unnecessary probes while maintaining or expanding functionality would be relevant to many investigators. Results Taking advantage of available genome sequences and annotation for Toxoplasma gondii (a pathogenic parasite responsible for illness in immunocompromised individuals) and Plasmodium falciparum (a related parasite responsible for severe human malaria), we designed a single oligonucleotide microarray capable of supporting a wide range of applications at relatively low cost, including genome-wide expression profiling for Toxoplasma, and single-nucleotide polymorphism (SNP)-based genotyping of both T. gondii and P. falciparum. Expression profiling of the three clonotypic lineages dominating T. gondii populations in North America and Europe provides a first comprehensive view of the parasite transcriptome, revealing that ~49% of all annotated genes are expressed in parasite tachyzoites (the acutely lytic stage responsible for pathogenesis) and 26% of genes are differentially expressed among strains. A novel design utilizing few probes provided high confidence genotyping, used here to resolve recombination points in the clonal progeny of sexual crosses. Recent sequencing of additional T. gondii isolates identifies >620 K new SNPs, including ~11 K that intersect with expression profiling probes, yielding additional markers for genotyping studies, and further validating the utility of a combined expression profiling/genotyping array design. Additional applications facilitating SNP and transcript discovery, alternative statistical methods for quantifying gene expression, etc. are also pursued at pilot scale to inform

  16. DETECTION OF EMERGING MICROBIAL CONTAMINANTS IN SOURCE AND FINISHED DRINKING WATER WITH DNA MICROARRAYS

    EPA Science Inventory

    DNA microarrays represent a potentially significant technology and analytical technique for the simultaneous detection of multiple pathogens in a single water sample, with the ability to incorporate live/dead discrimination via mRNA analysis. However, microarrays have not been a...

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

    EPA Science Inventory

    New microarray technologies to determine gene expression in animals exposed to chemical stressors promise to revolutionize the science of toxicology. The work described in this abstract concerns development and validation of a gene microarray for the fathead minnow designed to ai...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. DNA Microarray Detection of Antimicrobial Resistance Genes in Bacteria Co-Cultured from Swine Feces

    Technology Transfer Automated Retrieval System (TEKTRAN)

    One factor leading to the spread of antimicrobial resistance (AR) in bacteria is the horizontal transfer of resistance genes. To study this, a DNA microarray was recently developed to detect these genes. To maximize the capability of this microarray, probes were designed and added to detect all AR g...

  1. 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

  2. Development and Validation of a 2,000 Gene Microarray in the Fathead Minnow, Pimephales promelas

    EPA Science Inventory

    The development of the gene microarray has given the field of ecotoxicology a new tool to understand the mechanisms of action (MOA) of various anthropogenic compounds. . .Overall, data from this analysis suggest that the microarrays can be broadly useful in ecotoxicology studies ...

  3. Enzyme family-specific and activity-based screening of chemical libraries using enzyme microarrays.

    PubMed

    Funeriu, Daniel P; Eppinger, Jörg; Denizot, Lucile; Miyake, Masato; Miyake, Jun

    2005-05-01

    The potential of protein microarrays in high-throughput screening (HTS) still remains largely unfulfilled, essentially because of the difficulty of extracting meaningful, quantitative data from such experiments. In the particular case of enzyme microarrays, low-molecular-weight fluorescent affinity labels (FALs) can function as ideally suited activity probes of the microarrayed enzymes. FALs form covalent bonds with enzymes in an activity-dependent manner and therefore can be used to characterize enzyme activity at each enzyme's address, as predetermined by the microarraying process. Relying on this principle, we introduce herein thematic enzyme microarrays (TEMA). In a kinetic setup we used TEMAs to determine the full set of kinetic constants and the reaction mechanism between the microarrayed enzymes (the theme of the microarray) and a family-wide FAL. Based on this kinetic understanding, in an HTS setup we established the practical and theoretical methodology for quantitative, multiplexed determination of the inhibition profile of compounds from a chemical library against each microarrayed enzyme. Finally, in a validation setup, K(i)(app) values and inhibitor profiles were confirmed and refined. PMID:15821728

  4. 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...

  5. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    SciTech Connect

    Gardner, S; Jaing, C

    2012-03-27

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

  10. [Application of screening microarray technology in genus level for detection of Pospiviroid].

    PubMed

    Zhang, Yongjiang; Xin, Yanyan; Zhu, Shuifang; Deng, Congliang

    2014-03-01

    The aim was to establish an effective screening microarray at genus level for Pospiviroid. We analyzed nucleotide sequences from Pospiviroid viroid and designed 19 probes with genus identification characteristics. The standards of these probes included the characters of (i) a GC content between 40 and 60%, (ii) less than 50% of single nucleotide, (iii) less than 4 continuous mononucleotides, and (iv) less than 6 nucleotides in the inner hairpin. We synthesized microarrays by using these probes on glass slides. The validation results of microarray probes show effective signals from chrysanthemum stunt viroid and tomato planta macho viroid standard samples hybridization. The sensitivity results show that the microarray detected 200 pg/microL of total RNA. The microarray can be used to screen Pospiviroid viroid. PMID:25009845

  11. Exploring the feasibility of next-generation sequencing and microarray data meta-analysis

    PubMed Central

    Wu, Po-Yen; Phan, John H.; Wang, May D.

    2016-01-01

    Emerging next-generation sequencing (NGS) technology potentially resolves many issues that prevent widespread clinical use of gene expression microarrays. However, the number of publicly available NGS datasets is still smaller than that of microarrays. This paper explores the possibilities for combining information from both microarray and NGS gene expression datasets for the discovery of differentially expressed genes (DEGs). We evaluate several existing methods in detecting DEGs using individual datasets as well as combined NGS and microarray datasets. Results indicate that analysis of combined NGS and microarray data is feasible, but successful detection of DEGs may depend on careful selection of algorithms as well as on data normalization and pre-processing. PMID:22256102

  12. Caryoscope: An Open Source Java application for viewing microarray data in a genomic context

    PubMed Central

    Awad, Ihab AB; Rees, Christian A; Hernandez-Boussard, Tina; Ball, Catherine A; Sherlock, Gavin

    2004-01-01

    Background Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. Results We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context. PMID:15488149

  13. An automated method for gridding and clustering-based segmentation of cDNA microarray images.

    PubMed

    Giannakeas, Nikolaos; Fotiadis, Dimitrios I

    2009-01-01

    Microarrays are widely used to quantify gene expression levels. Microarray image analysis is one of the tools, which are necessary when dealing with vast amounts of biological data. In this work we propose a new method for the automated analysis of microarray images. The proposed method consists of two stages: gridding and segmentation. Initially, the microarray images are preprocessed using template matching, and block and spot finding takes place. Then, the non-expressed spots are detected and a grid is fit on the image using a Voronoi diagram. In the segmentation stage, K-means and Fuzzy C means (FCM) clustering are employed. The proposed method was evaluated using images from the Stanford Microarray Database (SMD). The results that are presented in the segmentation stage show the efficiency of our Fuzzy C means-based work compared to the two already developed K-means-based methods. The proposed method can handle images with artefacts and it is fully automated. PMID:19046850

  14. The neoglycolipid (NGL)-based oligosaccharide microarray system poised to decipher the meta-glycome

    PubMed Central

    Palma, Angelina S.; Feizi, Ten; Childs, Robert A.; Chai, Wengang; Liu, Yan

    2014-01-01

    The neoglycolipid (NGL) technology is the basis of a state-of-the-art oligosaccharide microarray system. The NGL-based microarray system in the Glycosciences Laboratory Imperial College London (http://www3.imperial.ac.uk/glycosciences), is one of the two leading platforms for glycan microarrays, being offered for screening analyses to the broad biomedical community. Highlighted in this review are the sensitivity of the analysis system and, coupled with mass spectrometry, the provision for generating ‘designer’ microarrays from glycomes to identify novel ligands of biological relevance. Among recent applications are: assignments of ligands for apicomplexan parasites, pandemic 2009 influenza virus, polyoma and reoviruses, an innate immune receptor against fungal pathogens, Dectin-1, and a novel protein of the endoplasmic reticulum, malectin; also the characterization of an elusive cancer-associated antigen. Some other contemporary advances in glycolipid-containing arrays and microarrays are also discussed. PMID:24508828

  15. 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.

  16. 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

  17. Electronic hybridization detection in microarray format and DNA genotyping

    PubMed Central

    Blin, Antoine; Cissé, Ismaïl; Bockelmann, Ulrich

    2014-01-01

    We describe an approach to substituting a fluorescence microarray with a surface made of an arrangement of electrolyte-gated field effect transistors. This was achieved using a dedicated blocking of non-specific interactions and comparing threshold voltage shifts of transistors exhibiting probe molecules of different base sequence. We apply the approach to detection of the 35delG mutation, which is related to non-syndromic deafness and is one of the most frequent mutations in humans. The process involves barcode sequences that are generated by Tas-PCR, a newly developed replication reaction using polymerase blocking. The barcodes are recognized by hybridization to surface attached probes and are directly detected by the semiconductor device. PMID:24569823

  18. Probing small molecule microarrays with tagged proteins in cell lysates

    PubMed Central

    Pop, Marius S.; Wassaf, Dina; Koehler, Angela N.

    2014-01-01

    The technique of small-molecule microarray (SMM) screening is based on the ability of small molecules to bind to various soluble proteins. This type of interaction is easily detected by the presence of a fluorescence signal produced by labeled antibodies that specifically recognize a unique sequence (tag) present on the target protein. The fluorescent signal intensity values are determined based on signal-to-noise ratios (SNR). SMM screening is a high throughput, unbiased method that can rapidly identify novel direct ligands for various protein targets. This binding-based assay format is generally applicable to most proteins, but it is especially useful for protein targets that do not possess an enzymatic activity. SMMs enable screening a protein in a purified form or in the context of a cellular lysate, likely providing a more physiologically relevant screening environment. PMID:25445177

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

    PubMed Central

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

    2011-01-01

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

  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.

  1. 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.

  2. Electronic hybridization detection in microarray format and DNA genotyping

    NASA Astrophysics Data System (ADS)

    Blin, Antoine; Cissé, Ismaïl; Bockelmann, Ulrich

    2014-02-01

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

  3. Analyzing microarray data with transitive directed acyclic graphs.

    PubMed

    Phan, Vinhthuy; Olusegun George, E; Tran, Quynh T; Goodwin, Shirlean; Bodreddigari, Sridevi; Sutter, Thomas R

    2009-02-01

    Post hoc assignment of patterns determined by all pairwise comparisons in microarray experiments with multiple treatments has been proven to be useful in assessing treatment effects. We propose the usage of transitive directed acyclic graphs (tDAG) as the representation of these patterns and show that such representation can be useful in clustering treatment effects, annotating existing clustering methods, and analyzing sample sizes. Advantages of this approach include: (1) unique and descriptive meaning of each cluster in terms of how genes respond to all pairs of treatments; (2) insensitivity of the observed patterns to the number of genes analyzed; and (3) a combinatorial perspective to address the sample size problem by observing the rate of contractible tDAG as the number of replicates increases. The advantages and overall utility of the method in elaborating drug structure activity relationships are exemplified in a controlled study with real and simulated data. PMID:19226664

  4. Chromosomal Microarray Testing in NEC: A Case Report.

    PubMed

    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

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

    PubMed Central

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

    2014-01-01

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

  6. High throughput screening of starch structures using carbohydrate microarrays.

    PubMed

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Motawia, Mohammed Saddik; Shaik, Shahnoor Sultana; Mikkelsen, Maria Dalgaard; Krunic, Susanne Langgaard; Fangel, Jonatan Ulrik; Willats, William George Tycho; Blennow, Andreas

    2016-01-01

    In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated maltooligosaccharides, pure starch samples including a variety of different structures with variations in the amylopectin branching pattern, amylose content and phosphate content, enzymatically modified starches and glycogen were included. Using this technique, different important structures, including amylose content and branching degrees could be differentiated in a high throughput fashion. The screening method was validated using transgenic barley grain analysed during development and subjected to germination. Typically, extreme branching or linearity were detected less than normal starch structures. The method offers the potential for rapidly analysing resistant and slowly digested dietary starches. PMID:27468930

  7. Using Kepler for Tool Integration in Microarray Analysis Workflows

    PubMed Central

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

    2015-01-01

    Increasing numbers of genomic technologies are leading to massive amounts of genomic data, all of which requires complex analysis. More and more bioinformatics analysis tools are being developed by scientist to simplify these analyses. However, different pipelines have been developed using different software environments. This makes integrations of these diverse bioinformatics tools difficult. Kepler provides an open source environment to integrate these disparate packages. Using Kepler, we integrated several external tools including Bioconductor packages, AltAnalyze, a python-based open source tool, and R-based comparison tool to build an automated workflow to meta-analyze both online and local microarray data. The automated workflow connects the integrated tools seamlessly, delivers data flow between the tools smoothly, and hence improves efficiency and accuracy of complex data analyses. Our workflow exemplifies the usage of Kepler as a scientific workflow platform for bioinformatics pipelines. PMID:26605000

  8. Neuron-based microarray sensors for environmental sensing.

    PubMed

    Prasad, Shalini; Zhang, Xuan; Ozkan, Cengiz S; Ozkan, Mihrimah

    2004-11-01

    We present a novel sensing scheme for detecting the effects of unburned fossil fuels by integrating microarray technology and dielectrophoresis to develop single-neuron arrays. These arrays have the capability to sense and identify the two fuels, at parts per billion (ppb) concentrations, as well to determine the associated physiological changes at the single-cell level. Identification is achieved through frequency domain analysis of the measured changes to the extracellular electrical activity due to the effect of the fossil fuels. This yields unique electrical identifiers known as "signature patterns". Simultaneous optical visualization to the physiological changes is obtained by specific fluorescent staining. The correlation between the signature patterns and the cellular biological behavior establishes the veracity of this identification technique. PMID:15565684

  9. Glycan specificity of neuraminidases determined in microarray format.

    PubMed

    McCombs, Janet E; Diaz, Jason P; Luebke, Kevin J; Kohler, Jennifer J

    2016-06-16

    Neuraminidases hydrolytically remove sialic acids from glycoconjugates. Neuraminidases are produced by both humans and their pathogens, and function in normal physiology and in pathological events. Identification of neuraminidase substrates is needed to reveal their mechanism of action, but high-throughput methods to determine glycan specificity of neuraminidases are limited. Here we use two glycan labeling reactions to monitor neuraminidase activity toward glycan substrates. While both periodate oxidation and aniline-catalyzed oxime ligation (PAL) and galactose oxidase and aniline-catalyzed oxime ligation (GAL) can be used to monitor neuraminidase activity toward glycans in microtiter plates, only GAL accurately measured neuraminidase activity toward glycans displayed on a commercial glass slide microarray. Using GAL, we confirm known linkage specificities of three pneumococcal neuraminidases and obtain new information about underlying glycan specificity. PMID:27131125

  10. High throughput screening of starch structures using carbohydrate microarrays

    PubMed Central

    Tanackovic, Vanja; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Motawia, Mohammed Saddik; Shaik, Shahnoor Sultana; Mikkelsen, Maria Dalgaard; Krunic, Susanne Langgaard; Fangel, Jonatan Ulrik; Willats, William George Tycho; Blennow, Andreas

    2016-01-01

    In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using high throughput carbohydrate microarray technology. Defined linear, branched and phosphorylated maltooligosaccharides, pure starch samples including a variety of different structures with variations in the amylopectin branching pattern, amylose content and phosphate content, enzymatically modified starches and glycogen were included. Using this technique, different important structures, including amylose content and branching degrees could be differentiated in a high throughput fashion. The screening method was validated using transgenic barley grain analysed during development and subjected to germination. Typically, extreme branching or linearity were detected less than normal starch structures. The method offers the potential for rapidly analysing resistant and slowly digested dietary starches. PMID:27468930

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

    SciTech Connect

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

    2006-04-01

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

  12. Acute hepatotoxicity: a predictive model based on focused illumina microarrays.

    PubMed

    Zidek, Nadine; Hellmann, Juergen; Kramer, Peter-Juergen; Hewitt, Philip G

    2007-09-01

    Drug-induced hepatotoxicity is a major issue for drug development, and toxicogenomics has the potential to predict toxicity during early toxicity screening. A bead-based Illumina oligonucleotide microarray containing 550 liver specific genes has been developed. We have established a predictive screening system for acute hepatotoxicity by analyzing differential gene expression profiles of well-known hepatotoxic and nonhepatotoxic compounds. Low and high doses of tetracycline, carbon tetrachloride (CCL4), 1-naphthylisothiocyanate (ANIT), erythromycin estolate, acetaminophen (AAP), or chloroform as hepatotoxicants, clofibrate, theophylline, naloxone, estradiol, quinidine, or dexamethasone as nonhepatotoxic compounds, were administered as a single dose to male Sprague-Dawley rats. After 6, 24, and 72 h, livers were taken for histopathological evaluation and for analysis of gene expression alterations. All hepatotoxic compounds tested generated individual gene expression profiles. Based on leave-one-out cross-validation analysis, gene expression profiling allowed the accurate discrimination of all model compounds, 24 h after high dose treatment. Even during the regeneration phase, 72 h after treatment, CCL4, ANIT, and AAP were predicted to be hepatotoxic, and only these three compounds showed histopathological changes at this time. Furthermore, we identified 64 potential marker genes responsible for class prediction, which reflected typical hepatotoxicity responses. These genes and pathways, commonly deregulated by hepatotoxicants, may be indicative of the early characterization of hepatotoxicity and possibly predictive of later hepatotoxicity onset. Two unknown test compounds were used for prevalidating the screening test system, with both being correctly predicted. We conclude that focused gene microarrays are sufficient to classify compounds with respect to toxicity prediction. PMID:17522070

  13. Electrosonic ejector microarray for drug and gene delivery.

    PubMed

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

    2008-04-01

    We report on development and experimental characterization of a novel cell manipulation device-the electrosonic ejector microarray-which establishes a pathway for drug and/or gene delivery with control of biophysical action on the length scale of an individual cell. The device comprises a piezoelectric transducer for ultrasound wave generation, a reservoir for storing the sample mixture and a set of acoustic horn structures that form a nozzle array for focused application of mechanical energy. The nozzles are micromachined in silicon or plastic using simple and economical batch fabrication processes. When the device is driven at a particular resonant frequency of the acoustic horn structures, the sample mixture of cells and desired transfection agents/molecules suspended in culture medium is ejected from orifices located at the nozzle tips. During sample ejection, focused mechanical forces (pressure and shear) are generated on a microsecond time scale (dictated by nozzle size/geometry and ejection velocity) resulting in identical "active" microenvironments for each ejected cell. This process enables a number of cellular bioeffects, from uptake of small molecules and gene delivery/transfection to cell lysis. Specifically, we demonstrate successful calcein uptake and transfection of DNA plasmid encoding green fluorescent protein (GFP) into human malignant glioma cells (cell line LN443) using electrosonic microarrays with 36, 45 and 50 mum diameter nozzle orifices and operating at ultrasound frequencies between 0.91 and 0.98 MHz. Our results suggest that efficacy and the extent of bioeffects are mainly controlled by nozzle orifice size and the localized intensity of the applied acoustic field. PMID:17994280

  14. Protein Microarrays-Based Strategies for Life Detection in Astrobiology

    NASA Astrophysics Data System (ADS)

    Parro, Víctor; Rivas, Luis A.; Gómez-Elvira, Javier

    2008-03-01

    The detection of organic molecules of unambiguous biological origin is fundamental for the confirmation of present or past life. Planetary exploration requires the development of miniaturized apparatus for in situ life detection. Analytical techniques based on mass spectrometry have been traditionally used in space science. Following the Viking landers, gas chromatography-mass spectrometry (GC-MS) for organic detection has gained general acceptance and has been used successfully in the Cassini-Huygens mission to Titan. Microfluidics allows the development of miniaturized capillary electrophoresis devices for the detection of important molecules for life, like amino acids or nucleobases. Recently, a new approach is gaining acceptance in the space science community: the application of the well-known, highly specific, antibody-antigen affinity interaction for the detection and identification of organics and biochemical compounds. Antibodies can specifically bind a plethora of structurally different compounds of a broad range of molecular sizes, from amino acids level to whole cells. Antibody microarray technology allows us to look for the presence of thousands of different compounds in a single assay and in just one square centimeter. Herein, we discuss several important issues—most of which are common with other instruments dealing with life signature detection in the solar system—that must be addressed in order to use antibody microarrays for life detection and planetary exploration. These issues include (1) preservation of biomarkers, (2) the extraction techniques for biomarkers, (3) terrestrial analogues, (4) the antibody stability under space environments, (5) the selection of unequivocal biomarkers for the antibody production, or (6) the instrument design and implementation.

  15. Protein Microarrays-Based Strategies for Life Detection in Astrobiology

    NASA Astrophysics Data System (ADS)

    Parro, Víctor; Rivas, Luis A.; Gómez-Elvira, Javier

    The detection of organic molecules of unambiguous biological origin is fundamental for the confirmation of present or past life. Planetary exploration requires the development of miniaturized apparatus for in situ life detection. Analytical techniques based on mass spectrometry have been traditionally used in space science. Following the Viking landers, gas chromatography-mass spectrometry (GC-MS) for organic detection has gained general acceptance and has been used successfully in the Cassini-Huygens mission to Titan. Microfluidics allows the development of miniaturized capillary electrophoresis devices for the detection of important molecules for life, like amino acids or nucleobases. Recently, a new approach is gaining acceptance in the space science community: the application of the well-known, highly specific, antibody-antigen affinity interaction for the detection and identification of organics and biochemical compounds. Antibodies can specifically bind a plethora of structurally different compounds of a broad range of molecular sizes, from amino acids level to whole cells. Antibody microarray technology allows us to look for the presence of thousands of different compounds in a single assay and in just one square centimeter. Herein, we discuss several important issues—most of which are common with other instruments dealing with life signature detection in the solar system—that must be addressed in order to use antibody microarrays for life detection and planetary exploration. These issues include (1) preservation of biomarkers, (2) the extraction techniques for biomarkers, (3) terrestrial analogues, (4) the antibody stability under space environments, (5) the selection of unequivocal biomarkers for the antibody production, or (6) the instrument design and implementation.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

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

    PubMed

    Rogers, Susan; Cambrosio, Alberto

    2007-12-01

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

  20. Hyperspectral microarray scanning: impact on the accuracy and reliability of gene expression data

    PubMed Central

    Timlin, Jerilyn A; Haaland, David M; Sinclair, Michael B; Aragon, Anthony D; Martinez, M Juanita; Werner-Washburne, Margaret

    2005-01-01

    Background Commercial microarray scanners and software cannot distinguish between spectrally overlapping emission sources, and hence cannot accurately identify or correct for emissions not originating from the labeled cDNA. We employed our hyperspectral microarray scanner coupled with multivariate data analysis algorithms that independently identify and quantitate emissions from all sources to investigate three artifacts that reduce the accuracy and reliability of microarray data: skew toward the green channel, dye separation, and variable background emissions. Results Here we demonstrate that several common microarray artifacts resulted from the presence of emission sources other than the labeled cDNA that can dramatically alter the accuracy and reliability of the array data. The microarrays utilized in this study were representative of a wide cross-section of the microarrays currently employed in genomic research. These findings reinforce the need for careful attention to detail to recognize and subsequently eliminate or quantify the presence of extraneous emissions in microarray images. Conclusion Hyperspectral scanning together with multivariate analysis offers a unique and detailed understanding of the sources of microarray emissions after hybridization. This opportunity to simultaneously identify and quantitate contaminant and background emissions in microarrays markedly improves the reliability and accuracy of the data and permits a level of quality control of microarray emissions previously unachievable. Using these tools, we can not only quantify the extent and contribution of extraneous emission sources to the signal, but also determine the consequences of failing to account for them and gain the insight necessary to adjust preparation protocols to prevent such problems from occurring. PMID:15888208

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

    PubMed Central

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

    2006-01-01

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

  2. Clinical Utility of Microarrays: Current Status, Existing Challenges and Future Outlook

    PubMed Central

    Li, Xinmin; Quigg, Richard J; Zhou, Jian; Gu, Weikuan; Nagesh Rao, P; Reed, Elaine F

    2008-01-01

    Microarray-based clinical tests have become powerful tools in the diagnosis and treatment of diseases. In contrast to traditional DNA-based tests that largely focus on single genes associated with rare conditions, microarray-based tests are ideal for the study of diseases with underlying complex genetic causes. Several microarray based tests have been translated into clinical practice such as MammaPrint and AmpliChip CYP450. Additional cancer-related microarray-based tests are either in the process of FDA review or under active development, including Tissue of Tumor Origin and AmpliChip p53. All diagnostic microarray testing is ordered by physicians and tested by a Clinical Laboratories Improvement Amendment-certified (CLIA) reference laboratory. Recently, companies offering consumer based microarray testing have emerged. Individuals can order tests online and service providers deliver the results directly to the clients via a password-protected secure website. Navigenics, 23andMe and deCODE Genetics represent pioneering companies in this field. Although the progress of these microarray-based tests is extremely encouraging with the potential to revolutionize the recognition and treatment of common diseases, these tests are still in their infancy and face technical, clinical and marketing challenges. In this article, we review microarray-based tests which are currently approved or under review by the FDA, as well as the consumer-based testing. We also provide a summary of the challenges and strategic solutions in the development and clinical use of the microarray-based tests. Finally, we present a brief outlook for the future of microarray-based clinical applications. PMID:19506735

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

    PubMed Central

    Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

    2006-01-01

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

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

    PubMed

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

    2000-11-15

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

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

    PubMed

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

    2014-06-17

    Low-density protein microarrays are emerging tools in diagnostics whose deployment could be primarily limited by the cost of fluorescence detection schemes. This paper describes an electrical readout system of microarrays comprising an array of gold interdigitated microelectrodes and an array of polydimethylsiloxane microwells, which enabled multiplexed detection of up to thirty six biological events on the same substrate. Similarly to fluorescent readout counterparts, the microarray can be developed on disposable glass slide substrates. However, unlike them, the presented approach is compact and requires a simple and inexpensive instrumentation. The system makes use of urease labeled affinity reagents for developing the microarrays and is based on detection of conductivity changes taking place when ionic species are generated in solution due to the catalytic hydrolysis of urea. The use of a polydimethylsiloxane microwell array facilitates the positioning of the measurement solution on every spot of the microarray. Also, it ensures the liquid tightness and isolation from the surrounding ones during the microarray readout process, thereby avoiding evaporation and chemical cross-talk effects that were shown to affect the sensitivity and reliability of the system. The performance of the system is demonstrated by carrying out the readout of a microarray for boldenone anabolic androgenic steroid hormone. Analytical results are comparable to those obtained by fluorescent scanner detection approaches. The estimated detection limit is 4.0 ng mL(-1), this being below the threshold value set by the World Anti-Doping Agency and the European Community. PMID:24890693

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

    PubMed Central

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

    2003-01-01

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

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

    PubMed Central

    2012-01-01

    Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

  8. Detection of antibodies against avian influenza virus by protein microarray using nucleoprotein expressed in insect cells

    PubMed Central

    ZHAO, Yuhui; WANG, Xiurong; CHEN, Pucheng; ZENG, Xianying; BAO, Hongmei; WANG, Yunhe; XU, Xiaolong; JIANG, Yongping; CHEN, Hualan; LI, Guangxing

    2014-01-01

    Avian influenza (AI) is an infectious disease caused by avian influenza viruses (AIVs) which belong to the influenza virus A group. AI causes tremendous economic losses in poultry industry and pose great threatens to human health. Active serologic surveillance is necessary to prevent and control the spread of AI. In this study, a protein microarray using nucleoprotein (NP) of H5N1 AIV expressed in insect cells was developed to detect antibodies against AIV NP protein. The protein microarray was used to test Newcastle disease virus (NDV), infectious bursal disease virus (IBDV), AIV positive and negative sera. The results indicated that the protein microarray could hybridize specifically with antibodies against AIV with strong signals and without cross-hybridization. Moreover, 76 field serum samples were detected by microarray, enzyme-linked immunosorbent assay (ELISA) and hemagglutination inhibition test (HI). The positive rate was 92.1% (70/76), 93.4% (71/76) and 89.4% (68/76) by protein microarray, ELISA and HI test, respectively. Compared with ELISA, the microarray showed 100% (20/20) agreement ratio in chicken and 98.2% (55/56) in ornamental bird. In conclusion, this method provides an alternative serological diagnosis for influenza antibody screening and will provide a basis for the development of protein microarrays that can be used to respectively detect antibodies of different AIV subtypes and other pathogens. PMID:25650059

  9. A Hybrid BPSO-CGA Approach for Gene Selection and Classification of Microarray Data

    PubMed Central

    Chuang, Li-Yeh; Yang, Cheng-Huei; Li, Jung-Chike

    2012-01-01

    Abstract Microarray analysis promises to detect variations in gene expressions, and changes in the transcription rates of an entire genome in vivo. Microarray gene expression profiles indicate the relative abundance of mRNA corresponding to the genes. The selection of relevant genes from microarray data poses a formidable challenge to researchers due to the high-dimensionality of features, multiclass categories being involved, and the usually small sample size. A classification process is often employed which decreases the dimensionality of the microarray data. In order to correctly analyze microarray data, the goal is to find an optimal subset of features (genes) which adequately represents the original set of features. A hybrid method of binary particle swarm optimization (BPSO) and a combat genetic algorithm (CGA) is to perform the microarray data selection. The K-nearest neighbor (K-NN) method with leave-one-out cross-validation (LOOCV) served as a classifier. The proposed BPSO-CGA approach is compared to ten microarray data sets from the literature. The experimental results indicate that the proposed method not only effectively reduce the number of genes expression level, but also achieves a low classification error rate. PMID:21210743

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

    PubMed Central

    Helka, Blake-Joseph; Brennan, John D.

    2013-01-01

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

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

    PubMed Central

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Elham

    2015-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  13. Detection of antibodies against avian influenza virus by protein microarray using nucleoprotein expressed in insect cells.

    PubMed

    Zhao, Yuhui; Wang, Xiurong; Chen, Pucheng; Zeng, Xianying; Bao, Hongmei; Wang, Yunhe; Xu, Xiaolong; Jiang, Yongping; Chen, Hualan; Li, Guangxing

    2015-04-01

    Avian influenza (AI) is an infectious disease caused by avian influenza viruses (AIVs) which belong to the influenza virus A group. AI causes tremendous economic losses in poultry industry and pose great threatens to human health. Active serologic surveillance is necessary to prevent and control the spread of AI. In this study, a protein microarray using nucleoprotein (NP) of H5N1 AIV expressed in insect cells was developed to detect antibodies against AIV NP protein. The protein microarray was used to test Newcastle disease virus (NDV), infectious bursal disease virus (IBDV), AIV positive and negative sera. The results indicated that the protein microarray could hybridize specifically with antibodies against AIV with strong signals and without cross-hybridization. Moreover, 76 field serum samples were detected by microarray, enzyme-linked immunosorbent assay (ELISA) and hemagglutination inhibition test (HI). The positive rate was 92.1% (70/76), 93.4% (71/76) and 89.4% (68/76) by protein microarray, ELISA and HI test, respectively. Compared with ELISA, the microarray showed 100% (20/20) agreement ratio in chicken and 98.2% (55/56) in ornamental bird. In conclusion, this method provides an alternative serological diagnosis for influenza antibody screening and will provide a basis for the development of protein microarrays that can be used to respectively detect antibodies of different AIV subtypes and other pathogens. PMID:25650059

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

    PubMed

    Ramirez, Lisa S; Wang, Jun

    2016-01-01

    Antibody microarray as a well-developed technology is currently challenged by a few other established or emerging high-throughput technologies. In this report, we renovate the antibody microarray technology by using a novel approach for manufacturing and by introducing new features. The fabrication of our high-density antibody microarray is accomplished through perpendicularly oriented flow-patterning of single stranded DNAs and subsequent conversion mediated by DNA-antibody conjugates. This protocol outlines the critical steps in flow-patterning DNA, producing and purifying DNA-antibody conjugates, and assessing the quality of the fabricated microarray. The uniformity and sensitivity are comparable with conventional microarrays, while our microarray fabrication does not require the assistance of an array printer and can be performed in most research laboratories. The other major advantage is that the size of our microarray units is 10 times smaller than that of printed arrays, offering the unique capability of analyzing functional proteins from single cells when interfacing with generic microchip designs. This barcode technology can be widely employed in biomarker detection, cell signaling studies, tissue engineering, and a variety of clinical applications. PMID:26780370

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

    PubMed Central

    Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

    2012-01-01

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

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

    SciTech Connect

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

    2002-01-23

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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2015-11-01

    Microfluidic live-cell microarrays show much promise as screening tools for biomedical research because they could shed light on key biological processes such as cell signaling and cell-to-cell and cell-to-substrate dynamic responses. While miniaturization reduces the need for expensive clinical grade reagents, the integration of functional components including micropumps, biosensors, actuators, mixers and gradient generators results in improved assay reliability, reproducibility and well-defined cell culture conditions. The present review addresses recent technological advances in microfluidic live-cell microarray technology with a special focus on the applications of microfluidic single-cell, multi-cell and 3D cell microarrays. PMID:26133396

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  20. Multiplex Serum Cytokine Immunoassay Using Nanoplasmonic Biosensor Microarrays

    PubMed Central

    Chen, Pengyu; Chung, Meng Ting; McHugh, Walker; Nidetz, Robert; Li, Yuwei; Fu, Jianping; Cornell, Timothy T.; Shanley, Thomas P.; Kurabayashi, Katsuo

    2015-01-01

    Precise monitoring of the rapidly changing immune status during the course of a disease requires multiplex analysis of cytokines from frequently sampled human blood. However, the current lack of rapid, multiplex, and low volume assays makes immune monitoring for clinical decision-making (e.g., critically ill patients) impractical. Without such assays, immune monitoring is even virtually impossible for infants and neonates with infectious diseases and/or immune mediated disorders as access to their blood in large quantities is prohibited. Localized surface plasmon resonance (LSPR)-based microfluidic optical biosensing is a promising approach to fill this technical gap as it could potentially permit real-time refractometric detection of biomolecular binding on a metallic nanoparticle surface and sensor miniaturization, both leading to rapid and sample-sparing analyte analysis. Despite this promise, practical implementation of such a microfluidic assay for cytokine biomarker detection in serum samples has not been established primarily due to the limited sensitivity of LSPR biosensing. Here, we developed a high-throughput, label-free, multiarrayed LSPR optical biosensor device with 480 nanoplasmonic sensing spots in microfluidic channel arrays and demonstrated parallel multiplex immunoassays of six cytokines in a complex serum matrix on a single device chip while overcoming technical limitations. The device was fabricated using easy-to-implement, one-step microfluidic patterning and antibody conjugation of gold nanorods (AuNRs). When scanning the scattering light intensity across the microarrays of AuNR ensembles with dark-field imaging optics, our LSPR biosensing technique allowed for high-sensitivity quantitative cytokine measurements at concentrations down to 5–20 pg/mL from a 1 µL serum sample. Using the nanoplasmonic biosensor microarray device, we demonstrated the ability to monitor the inflammatory responses of infants following cardiopulmonary bypass (CPB

  1. Microarray analysis of a microbe-mineral interaction.

    PubMed

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

    2010-12-01

    The weathering of volcanic minerals makes a significant contribution to the global silicate weathering budget, influencing carbon dioxide drawdown and long-term climate control. Basalt rocks may account for over 30% of the global carbon dioxide drawdown in silicate weathering. Micro-organisms are known to play a role in rock weathering yet the genomics and genetics of biological rock weathering are unknown. We apply DNA microarray technology to determine putative genes involved in weathering using the heavy metal-resistant organism, Cupriavidus metallidurans CH34; in particular we investigate the sequestering of iron. The results show that the bacterium does not depend on siderophores. Instead, the up-regulation of porins and transporters which are employed concomitantly with genes associated with biofilm formation suggests that novel passive and active iron uptake systems are involved. We hypothesize that these mechanisms induce rock weathering by changes in chemical equilibrium at the microbe-mineral interface, reducing the saturation state of iron. We also demonstrate that low concentrations of metals in the basalt induce heavy metal-resistant genes. Some of the earliest environments on the Earth were volcanic. Therefore, these results not only elucidate the mechanisms by which micro-organisms might have sequestered nutrients on the early Earth but also provide an explanation for the evolution of multiple heavy metal resistance genes long before the creation of contaminated industrial biotopes by human activity. PMID:20718869

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

    PubMed Central

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

    2009-01-01

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

  3. Xylella fastidiosa gene expression analysis by DNA microarrays

    PubMed Central

    2009-01-01

    Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants. PMID:21637690

  4. An Efficient Ensemble Learning Method for Gene Microarray Classification

    PubMed Central

    Shadgar, Bita

    2013-01-01

    The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost. PMID:24024194

  5. Particle-Based Microarrays of Oligonucleotides and Oligopeptides

    PubMed Central

    Nesterov-Mueller, Alexander; Maerkle, Frieder; Hahn, Lothar; Foertsch, Tobias; Schillo, Sebastian; Bykovskaya, Valentina; Sedlmayr, Martyna; Weber, Laura K.; Ridder, Barbara; Soehindrijo, Miriam; Muenster, Bastian; Striffler, Jakob; Bischoff, F. Ralf; Breitling, Frank; Loeffler, Felix F.

    2014-01-01

    In this review, we describe different methods of microarray fabrication based on the use of micro-particles/-beads and point out future tendencies in the development of particle-based arrays. First, we consider oligonucleotide bead arrays, where each bead is a carrier of one specific sequence of oligonucleotides. This bead-based array approach, appearing in the late 1990s, enabled high-throughput oligonucleotide analysis and had a large impact on genome research. Furthermore, we consider particle-based peptide array fabrication using combinatorial chemistry. In this approach, particles can directly participate in both the synthesis and the transfer of synthesized combinatorial molecules to a substrate. Subsequently, we describe in more detail the synthesis of peptide arrays with amino acid polymer particles, which imbed the amino acids inside their polymer matrix. By heating these particles, the polymer matrix is transformed into a highly viscous gel, and thereby, imbedded monomers are allowed to participate in the coupling reaction. Finally, we focus on combinatorial laser fusing of particles for the synthesis of high-density peptide arrays. This method combines the advantages of particles and combinatorial lithographic approaches.

  6. Multiplex planar microarrays for disease prognosis, diagnosis and theranosis

    PubMed Central

    Lea, Peter

    2015-01-01

    Advanced diagnostic methods and algorithms for immune disorders provide qualitative and quantitative multiplex measurement for pre-clinical prognostic and clinical diagnostic biomarkers specific for diseases. Choice of therapy is confirmed by modulating diagnostic efficacy of companion, theranotic drug concentrations. Assay methods identify, monitor and manage autoimmune diseases, or risk thereof, in subjects who have, or who are related to individuals with autoimmune disease. These same diagnostic protocols also integrate qualitative and quantitative assay test protocol designs for responder patient assessment, risk analysis and management of disease when integrating multiplex planar microarray diagnostic tests, patient theranostic companion diagnostic methods and test panels for simultaneous assessment and management of dysimmune and inflammatory disorders, autoimmunity, allergy and cancer. Proprietary assay methods are provided to identify, monitor and manage dysimmune conditions, or risk thereof, in subjects with pathological alterations in the immune system, or who are related to individuals with these conditions. The protocols can be used for confirmatory testing of subjects who exhibit symptoms of dysimmunity, as well as subjects who are apparently healthy and do not exhibit symptoms of altered immune function. The protocols also provide for methods of determining whether a subject has, is at risk for, or is a candidate for disease therapy, guided by companion diagnosis and immunosuppressive therapy, as well as therapeutic drug monitoring and theranostic testing of disease biomarkers in response to immuno-absorption therapy. The multiplex test panels provide the components that are integral for performing the methods to recognized clinical standards. PMID:26309820

  7. A large field CCD system for quantitative imaging of microarrays

    PubMed Central

    Hamilton, G.; Brown, N.; Oseroff, V.; Huey, B.; Segraves, R.; Sudar, D.; Kumler, J.; Albertson, D.; Pinkel, D.

    2006-01-01

    We describe a charge-coupled device (CCD) imaging system for microarrays capable of acquiring quantitative, high dynamic range images of very large fields. Illumination is supplied by an arc lamp, and filters are used to define excitation and emission bands. The system is linear down to fluorochrome densities ≪1 molecule/µm2. The ratios of the illumination intensity distributions for all excitation wavelengths have a maximum deviation ∼±4% over the object field, so that images can be analyzed without computational corrections for the illumination pattern unless higher accuracy is desired. Custom designed detection optics produce achromatic images of the spectral region from ∼ 450 to ∼750 nm. Acquisition of a series of images of multiple fluorochromes from multiple arrays occurs under computer control. The version of the system described in detail provides images of 20 mm square areas using a 27 mm square, 2K × 2K pixel, cooled CCD chip with a well depth of ∼105 electrons, and provides ratio measurements accurate to a few percent over a dynamic range in intensity >1000. Resolution referred to the sample is 10 µm, sufficient for obtaining quantitative multicolor images from >30 000 array elements in an 18 mm × 18 mm square. PMID:16670425

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

    PubMed

    Klebes, Ansgar; Kornberg, Thomas B

    2008-01-01

    To understand Drosophila development and other genetically controlled processes, it is often desirable to identify differences in gene expression levels. An experimental approach to investigate these processes is to catalog the transcriptome by hybridization of mRNA to DNA microbar-rays. In these experiments mRNA-derived hybridization probes are produced and hybridized to an array of DNA spots on a solid support. The labeled cDNAs of the complex hybridization probe will bind to their complementary sequences and provide quantification of the relative concentration of the corresponding transcript in the starting material. However, such approaches are often limited by the scarcity of the experimental sample because standard methods of probe preparation require microgram quantities of mRNA template. Linear RNA amplification can alleviate such limitations to support the generation of microarray hybridization probes from a few 100 pg of mRNA. These smaller quantities can be isolated from a few 100 cells. Here, we present a linear amplification protocol designed to preserve both the relative abundance of transcripts as well as their sequence complexity. PMID:18641956

  9. TMAinspiration: Decode Interdependencies in Multifactorial Tissue Microarray Data

    PubMed Central

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

    2016-01-01

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

  10. Compressed sensing methods for DNA microarrays, RNA interference, and metagenomics.

    PubMed

    Rao, Aditya; P, Deepthi; Renumadhavi, C H; Chandra, M Girish; Srinivasan, Rajgopal

    2015-02-01

    Compressed sensing (CS) is a sparse signal sampling methodology for efficiently acquiring and reconstructing a signal from relatively few measurements. Recent work shows that CS is well-suited to be applied to problems in genomics, including probe design in microarrays, RNA interference (RNAi), and taxonomic assignment in metagenomics. The principle of using different CS recovery methods in these applications has thus been established, but a comprehensive study of using a wide range of CS methods has not been done. For each of these applications, we apply three hitherto unused CS methods, namely, l1-magic, CoSaMP, and l1-homotopy, in conjunction with CS measurement matrices such as randomly generated CS m matrix, Hamming matrix, and projective geometry-based matrix. We find that, in RNAi, the l1-magic (the standard package for l1 minimization) and l1-homotopy methods show significant reduction in reconstruction error compared to the baseline. In metagenomics, we find that l1-homotopy as well as CoSaMP estimate concentration with significantly reduced time when compared to the GPSR and WGSQuikr methods. PMID:25629590

  11. Fibrin-mediated lentivirus gene transfer: implications for lentivirus microarrays

    PubMed Central

    Raut, Shruti; Lei, Pedro; Padmashali, Roshan; Andreadis, Stelios T.

    2010-01-01

    We employed fibrin hydrogel as bioactive matrix for lentivirus mediated gene transfer. Fibrin-mediated gene transfer was highly efficient and exhibited strong dependence on fibrinogen concentration. Efficient gene transfer was achieved with fibrinogen concentration between 3.75 – 7.5 mg/mL. Lower fibrinogen concentrations resulted in diffusion of virus out of the gel while higher concentrations led to ineffective fibrin degradation by target cells. Addition of fibrinolytic inhibitors decreased gene transfer in a dose-dependent manner suggesting that fibrin degradation by target cells may be necessary for successful gene delivery. Under these conditions transduction may be limited only to cells interacting with the matrix thereby providing a method for spatially localized gene delivery. Indeed, when lentivirus-containing fibrin microgels were spotted in an array format gene transfer was confined to virus-containing fibrin spots with minimal cross-contamination between neighboring sites. Collectively, our data suggest that fibrin may provide an effective matrix for spatially-localized gene delivery with potential applications in high-throughput lentiviral microarrays and in regenerative medicine. PMID:20153386

  12. Benchmarking a memetic algorithm for ordering microarray data.

    PubMed

    Moscato, P; Mendes, A; Berretta, R

    2007-03-01

    This work introduces a new algorithm for "gene ordering". Given a matrix of gene expression data values, the task is to find a permutation of the gene names list such that genes with similar expression patterns should be relatively close in the permutation. The algorithm is based on a combined approach that integrates a constructive heuristic with evolutionary and Tabu Search techniques in a single methodology. To evaluate the benefits of this method, we compared our results with the current outputs provided by several widely used algorithms in functional genomics. We also compared the results with our own hierarchical clustering method when used in isolation. We show that the use of images, corrupted with known levels of noise, helps to illustrate some aspects of the performance of the algorithms and provide a complementary benchmark for the analysis. The use of these images, with known high-quality solutions, facilitates in some cases the assessment of the methods and helps the software development, validation and reproducibility of results. We also propose two quantitative measures of performance for gene ordering. Using these measures, we make a comparison with probably the most used algorithm (due to Eisen and collaborators, PNAS 1998) using a microarray dataset available on the public domain (the complete yeast cell cycle dataset). PMID:16870322

  13. Application of Phenotype Microarray technology to soil microbiology

    NASA Astrophysics Data System (ADS)

    Mocali, Stefano

    2016-04-01

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

  14. Discovering Pair-wise Synergies in Microarray Data

    PubMed Central

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

    2016-01-01

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

  15. Discovering Pair-wise Synergies in Microarray Data.

    PubMed

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

    2016-01-01

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

  16. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    PubMed Central

    Wang, Xi; Ning, Yujie; Zhang, Feng; Yu, Fangfang; Tan, Wuhong; Lei, Yanxia; Wu, Cuiyan; Zheng, Jingjing; Wang, Sen; Yu, Hanjie; Li, Zheng; Lammi, Mikko J.; Guo, Xiong

    2015-01-01

    Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs) from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR) algorithm and support vector machine (SVM) algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD. PMID:25997002

  17. Application of Broad-Spectrum Resequencing Microarray for Genotyping Rhabdoviruses▿

    PubMed Central

    Dacheux, Laurent; Berthet, Nicolas; Dissard, Gabriel; Holmes, Edward C.; Delmas, Olivier; Larrous, Florence; Guigon, Ghislaine; Dickinson, Philip; Faye, Ousmane; Sall, Amadou A.; Old, Iain G.; Kong, Katherine; Kennedy, Giulia C.; Manuguerra, Jean-Claude; Cole, Stewart T.; Caro, Valérie; Gessain, Antoine; Bourhy, Hervé

    2010-01-01

    The rapid and accurate identification of pathogens is critical in the control of infectious disease. To this end, we analyzed the capacity for viral detection and identification of a newly described high-density resequencing microarray (RMA), termed PathogenID, which was designed for multiple pathogen detection using database similarity searching. We focused on one of the largest and most diverse viral families described to date, the family Rhabdoviridae. We demonstrate that this approach has the potential to identify both known and related viruses for which precise sequence information is unavailable. In particular, we demonstrate that a strategy based on consensus sequence determination for analysis of RMA output data enabled successful detection of viruses exhibiting up to 26% nucleotide divergence with the closest sequence tiled on the array. Using clinical specimens obtained from rabid patients and animals, this method also shows a high species level concordance with standard reference assays, indicating that it is amenable for the development of diagnostic assays. Finally, 12 animal rhabdoviruses which were currently unclassified, unassigned, or assigned as tentative species within the family Rhabdoviridae were successfully detected. These new data allowed an unprecedented phylogenetic analysis of 106 rhabdoviruses and further suggest that the principles and methodology developed here may be used for the broad-spectrum surveillance and the broader-scale investigation of biodiversity in the viral world. PMID:20610710

  18. Protein microarrays imaging using oblique-incidence reflectivity difference method

    NASA Astrophysics Data System (ADS)

    Lu, Heng; Zhang, Hongyan; Li, Wei; Zhou, Yueliang; Lu, Huibin; Jin, Kuijuan; Yang, Guozhen; Ruan, Kangcheng

    2007-11-01

    In this study Oblique-Incidence Reflectivity Difference (OIRD) technique, a recent developed label-free detection, is applied to image biomolecular microarrays. Compared to the currently widely used fluorescence-dependent optical microscopy, OIRD technique not only images the morphology of protein bio-arrays in the absence of extrinsic labeling molecules but also monitors the changes in the optical properties of biochips in high-throughput fashion. Additionally, such a technique complements other label-free detections including Surface Plasmon Resonance (SPR) and Mass Spectrometry (MS) by offering the opportunity to detect biochemical activities without the special requirements on the substrate or the specific matrix medium. It is shown in this article that the surface topography can be reflected by OIRD method. Besides, the differences among printing concentrations and various proteins are able to be identified as well. Incidentally, the OIRD images appear to be useful aids to distinguish the variations resulting from antibody-antigen capture. Both the imaginary and real parts of OIRD images we presented provide more information than the single imaginary one especially. On the basis of the scattering mechanism, the absorptive properties of protein molecules are analyzed through the real part of OIRD signal. Accordingly, OIRD technique shows its unique potential in detection of biochemical processes.

  19. Using Semantic Web Technologies to Annotate and Align Microarray Designs

    PubMed Central

    Szpakowski, Sebastian; McCusker, James; Krauthammer, Michael

    2009-01-01

    In this paper, we annotate and align two different gene expression microarray designs using the Genomic ELement Ontology (GELO). GELO is a new ontology that leverages an existing community resource, Sequence Ontology (SO), to create views of genomically-aligned data in a semantic web environment. We start the process by mapping array probes to genomic coordinates. The coordinates represent an implicit link between the probes and multiple genomic elements, such as genes, transcripts, miRNA, and repetitive elements, which are represented using concepts in SO. We then use the RDF Query Language (SPARQL) to create explicit links between the probes and the elements. We show how the approach allows us to easily determine the element coverage and genomic overlap of the two array designs. We believe that the method will ultimately be useful for integration of cancer data across multiple omic studies. The ontology and other materials described in this paper are available at http://krauthammerlab.med.yale.edu/wiki/Gelo. PMID:24904201

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

    PubMed Central

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

    2013-01-01

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

  1. Spot addressing for microarray images structured in hexagonal grids.

    PubMed

    Giannakeas, Nikolaos; Kalatzis, Fanis; Tsipouras, Markos G; Fotiadis, Dimitrios I

    2012-04-01

    In this work, an efficient method for spot addressing in images, which are generated by the scanning of hexagonal structured microarrays, is proposed. Initially, the blocks of the image are separated using the projections of the image. Next, all the blocks of the image are processed separately for the detection of each spot. The spot addressing procedure begins with the detection of the high intensity objects, which are probably the spots of the image. Next, the Growing Concentric Hexagon algorithm, which uses the properties of the hexagonal grid, is introduced for the detection of the non-hybridized spots. Finally, the Voronoi diagram is applied to the centers of the detected spots for the gridding of the image. The method is evaluated using spots generated from the scanning of the Beadchip of Illumina, which is used for the detection of Single Nucleotide Polymorphisms in the human genome, and uses hexagonal structure for the location of the spots. For the evaluation, the detected centers for each of the spot in the image are compared to the centers of the annotation, obtaining up to 98% accuracy for the spot addressing procedure. PMID:21924515

  2. Human protein atlas and the use of microarray technologies.

    PubMed

    Hober, S; Uhlén, M

    2008-02-01

    Currently one of the most challenging tasks in biological and medical research is to explore and understand the function of all proteins encoded by the genome of an organism. A systematic approach based on the genome sequences is feasible because the full genome of many organisms presently is available and many more are underway. For the production of expression atlases different strategies are used. Early attempts to acquire information about protein expression levels have focused on the analysis of mRNA levels within different tissues and cell types. Recently, novel strategies to focus directly on protein levels have been developed. To assess global protein expression in a systematic and high-throughput manner, methods based on design of specific affinity ligands to recognize the proteins have been presented. By subsequently using these affinity molecules for detection of the corresponding proteins in a wide range of platforms, important information can be gained. This article focuses on strategies to profile protein levels and in particular the human protein atlas initiative and the use of microarray technologies. PMID:18187316

  3. Dense microarrays for ambient noise tomography at Solfatara (Italy)

    NASA Astrophysics Data System (ADS)

    Pilz, Marco; Parolai, Stefano; Festa, Gaetano; Woith, Heiko

    2014-05-01

    Imaging shallow subsurface structures and monitoring related temporal variations are two of the main tasks for modern seismology. Although many observations have reported temporal velocity changes e.g. in volcanic areas and on landslides, new methods based on passive sources like ambient seismic noise can provide accurate information on the velocity structure and on velocity changes. The success of these passive applications is explained by the fact that these methods are based on surface waves which are always present in the ambient seismic noise wave field because they are excited preferentially by superficial sources. These waves can easily be extracted because they dominate the Green's function between receivers located at the surface. For imaging the shallow velocity structure of the Solfatara crater, one the forty volcanoes in the Campi Flegrei area characterized by an intense hydrothermal shallow activity due to the interaction of deep convection and meteoric water, we have installed a dense network of wireless seismological sensing units covering the whole surface area in the framework of the European project MED-SUV. On four consecutive days continuous recordings of the ambient seismic noise using different microarray configurations were performed. Based on a weighted inversion procedure for the passive imaging using ambient noise cross-correlations we will present a preliminary velocity model of the structure beneath Solfatara.

  4. TMAinspiration: Decode Interdependencies in Multifactorial Tissue Microarray Data.

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2007-01-01

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

  6. The Microarray Explorer tool for data mining of cDNA microarrays: application for the mammary gland

    PubMed Central

    Lemkin, Peter F.; Thornwall, Gregory C.; Walton, Katherine D.; Hennighausen, Lothar

    2000-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  8. MICROARRAY GENE EXPRESSION ANALYSIS OF GRAPE PLANTS IN RESPONSE TO XYLELLA FASTIDIOSA INFECTION

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Transcriptional profiling using a custom high-density microarray chip of 20,020 Vitis transcripts showed significant variations in responses between the susceptible and resistant genotypes to Xylella fastidiosa (Xf) infection. Differentially expressed transcripts reflecting spatial and temporal resp...

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

    EPA Science Inventory

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

  10. Review of the literature examining the correlation among DNA microarray technologies

    PubMed Central

    Yauk, Carole L; Berndt, M Lynn

    2007-01-01

    DNA microarray technologies are used in a variety of biological disciplines. The diversity of platforms and analytical methods employed has raised concerns over the reliability, reproducibility and correlation of data produced across the different approaches. Initial investigations (years 2000–2003) found discrepancies in the gene expression measures produced by different microarray technologies. Increasing knowledge and control of the factors that result in poor correlation among the technologies has led to much higher levels of correlation among more recent publications (years 2004 to present). Here, we review the studies examining the correlation among microarray technologies. We find that with improvements in the technology (optimization and standardization of methods, including data analysis) and annotation, analysis across platforms yields highly correlated and reproducible results. We suggest several key factors that should be controlled in comparing across technologies, and are good microarray practice in general. Environ. Mol. Mutagen. 48:380–394, 2007. © 2007 Wiley-Liss, Inc. PMID:17370338

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  13. Detection of mRNAs in soils using targeted microarrays for genes associated with lignin degradation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarrays have become established tools for describing microbial systems, however the direct assessment of expression profiles for uncharacterized environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relat...

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

    PubMed Central

    Wang, Denong

    2015-01-01

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

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

    PubMed

    Polen, Tino; Wendisch, Volker F

    2004-01-01

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

  16. Microarray-based technologies for the discovery of selective, RNA-binding molecules.

    PubMed

    Abulwerdi, Fardokht A; Schneekloth, John S

    2016-07-01

    The identification of small molecules that bind specifically to RNA is a challenge. However, the recent explosion in knowledge about the role RNA plays in a number of physiological processes apart from coding for protein sequences makes it a highly interesting target for chemical probes and therapeutics. One technology that has played an important role in the discovery of RNA-binding molecules is microarrays. Microarrays have been broadly employed to screen, profile, and quantify RNA interactions, and will likely play an important role in the discovery of new classes of ligands going forward. Here, we discuss the development of microarray technologies, including aminoglycoside, peptide, peptoid, and small molecule microarrays, and their use in studying RNA-interacting molecules. PMID:27109057

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

    PubMed

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

    2016-04-01

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

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

    PubMed Central

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

    2016-01-01

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

  19. Utility of a Panviral Microarray for Detection of Swine Respiratory Viruses in Clinical Samples

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Several factors have recently converged elevating the need for highly parallel diagnostic platforms that have the ability to detect many known, novel, and emerging pathogenic agents simultaneously. Panviral DNA microarrays represent the most robust approach for massively parallel viral surveillance ...

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

    PubMed Central

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

    2015-01-01

    A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. PMID:26468293

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

    PubMed Central

    Zirlinger, Mariela; Kreiman, Gabriel; Anderson, David J.

    2001-01-01

    Microarray technology represents a potentially powerful method for identifying cell type- and regionally restricted genes expressed in the brain. Here we have combined a microarray analysis of differential gene expression among five selected brain regions, including the amygdala, cerebellum, hippocampus, olfactory bulb, and periaqueductal gray, with in situ hybridization. On average, 0.3% of the 34,000 genes interrogated were highly enriched in each of the five regions, relative to the others. In situ hybridization performed on a subset of amygdala-enriched genes confirmed in most cases the overall region-specificity predicted by the microarray data and identified additional sites of brain expression not examined on the microarrays. Strikingly, the majority of these genes exhibited boundaries of expression within the amygdala corresponding to cytoarchitectonically defined subnuclei. These results define a unique set of molecular markers for amygdaloid subnuclei and provide tools to genetically dissect their functional roles in different emotional behaviors. PMID:11320257

  2. Comparing bioinformatic gene expression profiling methods: microarray and RNA-Seq.

    PubMed

    Mantione, Kirk J; Kream, Richard M; Kuzelova, Hana; Ptacek, Radek; Raboch, Jiri; Samuel, Joshua M; Stefano, George B

    2014-01-01

    Understanding the control of gene expression is critical for our understanding of the relationship between genotype and phenotype. The need for reliable assessment of transcript abundance in biological samples has driven scientists to develop novel technologies such as DNA microarray and RNA-Seq to meet this demand. This review focuses on comparing the two most useful methods for whole transcriptome gene expression profiling. Microarrays are reliable and more cost effective than RNA-Seq for gene expression profiling in model organisms. RNA-Seq will eventually be used more routinely than microarray, but right now the techniques can be complementary to each other. Microarrays will not become obsolete but might be relegated to only a few uses. RNA-Seq clearly has a bright future in bioinformatic data collection. PMID:25149683

  3. The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

    PubMed Central

    van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.

    2015-01-01

    Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674

  4. Using Pre-existing Microarray Datasets to Increase Experimental Power: Application to Insulin Resistance

    PubMed Central

    Daigle, Bernie J.; Deng, Alicia; McLaughlin, Tracey; Cushman, Samuel W.; Cam, Margaret C.; Reaven, Gerald; Tsao, Philip S.; Altman, Russ B.

    2010-01-01

    Although they have become a widely used experimental technique for identifying differentially expressed (DE) genes, DNA microarrays are notorious for generating noisy data. A common strategy for mitigating the effects of noise is to perform many experimental replicates. This approach is often costly and sometimes impossible given limited resources; thus, analytical methods are needed which increase accuracy at no additional cost. One inexpensive source of microarray replicates comes from prior work: to date, data from hundreds of thousands of microarray experiments are in the public domain. Although these data assay a wide range of conditions, they cannot be used directly to inform any particular experiment and are thus ignored by most DE gene methods. We present the SVD Augmented Gene expression Analysis Tool (SAGAT), a mathematically principled, data-driven approach for identifying DE genes. SAGAT increases the power of a microarray experiment by using observed coexpression relationships from publicly available microarray datasets to reduce uncertainty in individual genes' expression measurements. We tested the method on three well-replicated human microarray datasets and demonstrate that use of SAGAT increased effective sample sizes by as many as 2.72 arrays. We applied SAGAT to unpublished data from a microarray study investigating transcriptional responses to insulin resistance, resulting in a 50% increase in the number of significant genes detected. We evaluated 11 (58%) of these genes experimentally using qPCR, confirming the directions of expression change for all 11 and statistical significance for three. Use of SAGAT revealed coherent biological changes in three pathways: inflammation, differentiation, and fatty acid synthesis, furthering our molecular understanding of a type 2 diabetes risk factor. We envision SAGAT as a means to maximize the potential for biological discovery from subtle transcriptional responses, and we provide it as a freely available

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

    PubMed Central

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement. PMID:23110046

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

    PubMed Central

    Uziela, Karolis; Honkela, Antti

    2015-01-01

    Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. Although RNA-sequencing (RNA-seq) is attracting the most attention, at present, the rate of new microarray studies submitted to public databases far exceeds the rate of new RNA-seq studies. There is clearly a need for methods that make it easier to combine data from different technologies. In this paper, we propose a new method for processing RNA-seq data that yields gene expression estimates that are much more similar to corresponding estimates from microarray data, hence greatly improving cross-platform comparability. The method we call PREBS is based on estimating the expression from RNA-seq reads overlapping the microarray probe regions, and processing these estimates with standard microarray summarisation algorithms. Using paired microarray and RNA-seq samples from TCGA LAML data set we show that PREBS expression estimates derived from RNA-seq are more similar to microarray-based expression estimates than those from other RNA-seq processing methods. In an experiment to retrieve paired microarray samples from a database using an RNA-seq query sample, gene signatures defined based on PREBS expression estimates were found to be much more accurate than those from other methods. PREBS also allows new ways of using RNA-seq data, such as expression estimation for microarray probe sets. An implementation of the proposed method is available in the Bioconductor package “prebs.” PMID:25966034

  7. Normalization of Affymetrix miRNA Microarrays for the Analysis of Cancer Samples.

    PubMed

    Wu, Di; Gantier, Michael P

    2016-01-01

    microRNA (miRNA) microarray normalization is a critical step for the identification of truly differentially expressed miRNAs. This is particularly important when dealing with cancer samples that have a global miRNA decrease. In this chapter, we provide a simple step-by-step procedure that can be used to normalize Affymetrix miRNA microarrays, relying on robust normal-exponential background correction with cyclic loess normalization. PMID:25971910

  8. Development of low-density oligonucleotide microarrays for detecting mutations causing Wilson's disease

    PubMed Central

    Mathur, Manjula; Singh, Ekta; Poduval, T.B.; Rao, Akkipeddi V.S.S.N.

    2015-01-01

    Background & objectives: Wilson's disease (WD) is an autosomal recessive disorder caused by mutations in ATP7B, a copper transporter gene, leading to hepatic and neuropsychiatric manifestations due to copper accumulation. If diagnosed early, WD patients can be managed by medicines reducing morbidity and mortality. Diagnosis of this disease requires a combination of tests and at times is inconclusive due to overlap of the symptoms with other disorders. Genetic testing is the preferred alternative in such cases particularly for individuals with a family history. Use of DNA microarray for detecting mutations in ATP7B gene is gaining popularity because of the advantages it offers in terms of throughput and sensitivity. This study attempts to establish the quality analysis procedures for microarray based diagnosis of Wilson's disease. Methods: A home-made microarrayer was used to print oligonucleotide based low-density microarrays for addressing 62 mutations causing Wilson's disease reported from Indian population. Inter- and intra- array comparisons were used to study quality of the arrays. The arrays were validated by using mutant samples generated by site directed mutagenesis. Results: The hybridization reaction were found to be consistent across the surface of a given microarray. Our results have shown that 52 °C post-hybridization wash yields better reproducibility across experiments compared to 42 °C. Our arrays have shown > 80 per cent sensitivity in detecting these 62 mutations. Interpretation & conclusions: The present results demonstrate the design and evaluation of a low-density microarray for the detection of 62 mutations in ATP7B gene, and show that a microarray based approach can be cost-effective for detecting a large number of mutations simultaneously. This study also provides information on some of the important parameters required for microarray based diagnosis of genetic disorders. PMID:25900953

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

    PubMed Central

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

    2004-01-01

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

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

    PubMed

    Fernandez, Paula; Soria, Marcelo; Blesa, David; DiRienzo, Julio; Moschen, Sebastian; Rivarola, Maximo; Clavijo, Bernardo Jose; Gonzalez, Sergio; Peluffo, Lucila; Príncipi, Dario; Dosio, Guillermo; Aguirrezabal, Luis; García-García, Francisco; Conesa, Ana; Hopp, Esteban; Dopazo, Joaquín; Heinz, Ruth Amelia; Paniego, Norma

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement. PMID:23110046

  11. Seasonal dynamics of harmful algae in outer Oslofjorden monitored by microarray, qPCR, and microscopy.

    PubMed

    Dittami, Simon M; Hostyeva, Vladyslava; Egge, Elianne Sirnæs; Kegel, Jessica U; Eikrem, Wenche; Edvardsen, Bente

    2013-10-01

    Monitoring of marine microalgae is important to predict and manage harmful algal blooms. Microarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a multi-species microarray as a tool to aid monitoring agencies. We tested the suitability of different prototype versions of the MIDTAL microarray for the monthly monitoring of a sampling station in outer Oslofjorden during a 1-year period. Microarray data from two different versions of the MIDTAL chip were compared to results from cell counts (several species) and quantitative real-time PCR (qPCR; only Pseudochattonella spp.). While results from generation 2.5 microarrays exhibited a high number of false positive signals, generation 3.3 microarray data generally correlated with microscopy and qPCR data, with three important limitations: (1) Pseudo-nitzschia cells were not reliably detected, possibly because cells were not sufficiently retained during filtration or lysed during the extraction, and because of low sensitivity of the probes; (2) in the case of samples with high concentrations of non-target species, the sensitivity of the arrays was decreased; (3) one occurrence of Alexandrium pseudogonyaulax was not detected due to a 1-bp mismatch with the genus probe represented on the microarray. In spite of these shortcomings our data demonstrate the overall progress made and the potential of the MIDTAL array. The case of Pseudochattonella - where two morphologically similar species impossible to separate by light microscopy were distinguished - in particular, underlines the added value of molecular methods such as microarrays in routine phytoplankton monitoring. PMID:23325054

  12. Microarray dataset of Jurkat cells following miR-93 over-expression.

    PubMed

    Gioiosa, Silvia; Verduci, Lorena; Azzalin, Gianluca; Carissimi, Claudia; Fulci, Valerio; Macino, Giuseppe

    2016-09-01

    The dataset presented here represents a microarray experiment of Jurkat cell line over-expressing miR-93 after lentiviral transgenic construct transduction. Three biological replicates have been performed. We further provide normalized and processed data, log2 Fold Change based ranked list and GOterms resulting table. The raw microarray data are available in the ArrayExpress database (www.ebi.ac.uk/arrayexpress) under accession number ArrayExpress: E-MTAB-4588. PMID:27408928

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

    PubMed

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

    2015-12-15

    Microarrays are a powerful platform for rapid and multiplexed analysis in a wide range of research fields. Electrical readout systems have emerged as an alternative to conventional optical methods for microarray analysis thanks to its potential advantages like low-cost, low-power and easy miniaturization of the required instrumentation. In this work an automated electrical readout system for low-cost glass-slide microarrays is described. The system enables the simultaneous conductimetric detection of up to 36 biorecognition events by incorporating an array of interdigitated electrode transducers. A polydimethylsiloxane microfluidic structure has been designed that creates microwells over the transducers and incorporates the microfluidic channels required for filling and draining them with readout and cleaning solutions, thus making the readout process fully automated. Since the capture biomolecules are not immobilized on the transducer surface this readout system is reusable, in contrast to previously reported electrochemical microarrays. A low-density microarray based on a competitive enzymatic immunoassay for atrazine detection was used to test the performance of the readout system. The electrical assay shows a detection limit of 0.22±0.03 μg L(-1) similar to that obtained with fluorescent detection and allows the direct determination of the pesticide in polluted water samples. These results proved that an electrical readout system such as the one presented in this work is a reliable and cost-effective alternative to fluorescence scanners for the analysis of low-density microarrays. PMID:26210466

  14. Use of a bacterial antimicrobial resistance gene microarray for the identification of resistant Staphylococcus aureus.

    PubMed

    Garneau, P; Labrecque, O; Maynard, C; Messier, S; Masson, L; Archambault, M; Harel, J

    2010-11-01

    As diagnostic and surveillance activities are vital to determine measures needed to control antimicrobial resistance (AMR), new and rapid laboratory methods are necessary to facilitate this important effort. DNA microarray technology allows the detection of a large number of genes in a single reaction. This technology is simple, specific and high-throughput. We have developed a bacterial antimicrobial resistance gene DNA microarray that will allow rapid antimicrobial resistance gene screening for all Gram-positive and Gram-negative bacteria. A prototype microarray was designed using a 70-mer based oligonucleotide set targeting AMR genes of Gram-negative and Gram-positive bacteria. In the present version, the microarray consists of 182 oligonucleotides corresponding to 166 different acquired AMR gene targets, covering most of the resistance genes found in both Gram-negative and -positive bacteria. A test study was performed on a collection of Staphylococcus aureus isolates from milk samples from dairy farms in Québec, Canada. The reproducibility of the hybridizations was determined, and the microarray results were compared with those obtained by phenotypic resistance tests (either MIC or Kirby-Bauer). The microarray genotyping demonstrated a correlation between penicillin, tetracycline and erythromycin resistance phenotypes with the corresponding acquired resistance genes. The hybridizations showed that the 38 antimicrobial resistant S. aureus isolates possessed at least one AMR gene. PMID:21083822

  15. Prolonged durability of electroporation microarrays as a result of addition of saccharides to nucleic acids.

    PubMed

    Fujimoto, Hiroyuki; Kato, Koichi; Iwata, Hiroo

    2009-01-01

    The electroporation microarray is a useful tool for high-throughput analysis of gene functions. However, transfection efficiency is greatly impaired by storage of the microarrays, due to water evaporation from arrayed nucleotides. In this study, we aimed at evaluating the effect of saccharides and sugar alcohols, added to the solution of the plasmid DNA or small interfering RNA (siRNA). Microarrays loaded with plasmids and siRNAs were prepared with various polyols including sugars and sugar alcohols. After storage of these microarrays at different temperatures for various time periods, transfection efficiency was evaluated using human embryonic kidney cells. In the case of plasmid-loaded microarrays, addition of monosaccharides (glucose, fructose), disaccharides (trehalose, sucrose), and trisaccharide (raffinose) served to retain transfection efficiency at a reasonably high level after storage at -20 degrees C. The observed effects may be because moisture retention serves to maintain the solubility of DNA. In contrast, polysaccharide (dextran) and sugar alcohol (glycerol) had insignificant effects on retention of transfection efficiency. On the other hand, addition of saccharides and sugar alcohols had insignificant effects on the transfection of siRNA after storage of a microarray at 25 degrees C for 7 days, presumably due to the intrinsically-high solubility of siRNA which consists of short nucleotides. PMID:18989662

  16. Antibody microarray profiling of human prostate cancer sera: antibody screening and identification of potential biomarkers.

    PubMed

    Miller, Jeremy C; Zhou, Heping; Kwekel, Joshua; Cavallo, Robert; Burke, Jocelyn; Butler, E Brian; Teh, Bin S; Haab, Brian B

    2003-01-01

    We developed a practical strategy for serum protein profiling using antibody microarrays and applied the method to the identification of potential biomarkers in prostate cancer serum. Protein abundances from 33 prostate cancer and 20 control serum samples were compared to abundances from a common reference pool using a two-color fluorescence assay. Robotically spotted microarrays containing 184 unique antibodies were prepared on two different substrates: polyacrylamide based hydrogels on glass and poly-1-lysine coated glass with a photoreactive cross-linking layer. The hydrogel substrate yielded an average six-fold higher signal-to-noise ratio than the other substrate, and detection of protein binding was possible from a greater number of antibodies using the hydrogels. A statistical filter based on the correlation of data from "reverse-labeled" experiment sets accurately predicted the agreement between the microarray measurements and enzyme-linked immunosorbent assay measurements, showing that this parameter can serve to screen for antibodies that are functional on microarrays. Having defined a set of reliable microarray measurements, we identified five proteins (von Willebrand Factor, immunoglobulinM, Alpha1-antichymotrypsin, Villin and immunoglobulinG) that had significantly different levels between the prostate cancer samples and the controls. These developments enable the immediate use of high-density antibody and protein microarrays in biomarker discovery studies. PMID:12548634

  17. Comparative Evaluation of Effectiveness of IAVchip DNA Microarray in Influenza A Diagnosis

    PubMed Central

    Sultankulova, K. T.; Chervyakova, O. V.; Kozhabergenov, N. S.; Shorayeva, K. A.; Strochkov, V. M.; Orynbayev, M. B.; Sandybayev, N. T.; Sansyzbay, A. R.; Vasin, A. V.

    2014-01-01

    The paper describes comparative evaluation of IAVchip DNA microarray, reverse transcription PCR (RT-PCR), and real-time RT-PCR versus virus isolation in chicken embryos and shows their diagnostic effectiveness in detection and subtyping of influenza A virus. The tests were evaluated with use of 185 specimens from humans, animals, and birds. IAVchip DNA microarray demonstrates higher diagnostic effectiveness (99.45%) in early influenza A diagnosis as compared to the real-time PCR (98.38%) and RT-PCR (96.22%), thus showing its clear superiority. Diagnostic sensitivity of IAVchip DNA microarray (100%) exceeds the same of RT-PCR (95.95%) and real-time RT-PCR (97.96%) in the range of estimated confidence intervals. IAVchip DNA microarray and real-time RT-PCR displayed equal diagnostic specificity (98.85%), while diagnostic specificity of RT-PCR was 96.40%. IAVchip DNA microarray has an advantage over the other tests for influenza A diagnosis and virus identification as a more rapid method that allows performing simultaneous detection and subtyping of about tens of specimens within one experiment during 8–10 hours. The developed IAVchip DNA microarray is a general test tool that enables identifying simultaneously 16 hemagglutinin (HA) and 9 neuraminidase (NA) subtypes of influenza A virus and also to screen the influenza A viruses from humans, animals, and birds by M and NP genes. PMID:25548788

  18. Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images

    PubMed Central

    2015-01-01

    Biological assays formatted as microarrays have become a critical tool for the generation of the comprehensive data sets required for systems-level understanding of biological processes. Manual annotation of data extracted from images of microarrays, however, remains a significant bottleneck, particularly for protein microarrays due to the sensitivity of this technology to weak artifact signal. In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully automate microarray segmentation. Automated artifact removal is also accomplished by segregating structured pixels from the background noise using iterative clustering and pixel connectivity. Correlation of the location of structured pixels across image channels is used to identify and remove artifact pixels from the image prior to data extraction. This component improves the accuracy of data sets while reducing the requirement for time-consuming visual inspection of the data. Crossword enables a fully automated protocol that is robust to significant spatial and intensity aberrations. Overall, the average amount of user intervention is reduced by an order of magnitude and the data quality is increased through artifact removal and reduced user variability. The increase in throughput should aid the further implementation of microarray technologies in clinical studies. PMID:24417579

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2015-12-01

    The demand for diagnostic tools that allow simultaneous screening of samples for multiple pathogens is increasing because they overcome the limitations of other methods, which can only screen for a single or a few pathogens at a time. Microarrays offer the advantages of being capable to test a large number of samples simultaneously, screening for multiple pathogen types per sample and having comparable sensitivity to existing methods such as PCR. Array design is often considered the most important process in any microarray experiment and can be the deciding factor in the success of a study. There are currently no microarrays for simultaneous detection of rodent-borne pathogens. The aim of this report is to explicate the design, development and evaluation of a microarray platform for use as a screening tool that combines ease of use and rapid identification of a number of rodent-borne pathogens of zoonotic importance. Nucleic acid was amplified by multiplex biotinylation PCR prior to hybridisation onto microarrays. The array sensitivity was comparable to standard PCR, though less sensitive than real-time PCR. The array presented here is a prototype microarray identification system for zoonotic pathogens that can infect rodent species. PMID:26188129

  1. A microarray system for Y chromosomal and mitochondrial single nucleotide polymorphism analysis in chimpanzee populations.

    PubMed

    Andrés, Olga; Rönn, Ann-Charlotte; Bonhomme, Maxime; Kellermann, Thomas; Crouau-Roy, Brigitte; Doxiadis, Gaby; Verschoor, Ernst J; Goossens, Benoît; Domingo-Roura, Xavier; Bruford, Michael W; Bosch, Montserrat; Syvänen, Ann-Christine

    2008-05-01

    Chimpanzee populations are diminishing as a consequence of human activities, and as a result this species is now endangered. In the context of conservation programmes, genetic data can add vital information, for instance on the genetic diversity and structure of threatened populations. Single nucleotide polymorphisms (SNP) are biallelic markers that are widely used in human molecular studies and can be implemented in efficient microarray systems. This technology offers the potential of robust, multiplexed SNP genotyping at low reagent cost in other organisms than humans, but it is not commonly used yet in wild population studies. Here, we describe the characterization of new SNPs in Y-chromosomal intronic regions in chimpanzees and also identify SNPs from mitochondrial genes, with the aim of developing a microarray system that permits the simultaneous study of both paternal and maternal lineages. Our system consists of 42 SNPs for the Y chromosome and 45 SNPs for the mitochondrial genome. We demonstrate the applicability of this microarray in a captive population where genotypes accurately reflected its large pedigree. Two wild-living populations were also analysed and the results show that the microarray will be a useful tool alongside microsatellite markers, since it supplies complementary information about population structure and ecology. SNP genotyping using microarray technology, therefore, is a promising approach and may become an essential tool in conservation genetics to help in the management and study of captive and wild-living populations. Moreover, microarrays that combine SNPs from different genomic regions could replace microsatellite typing in the future. PMID:21585830

  2. Comparative evaluation of effectiveness of IAVchip DNA microarray in influenza A diagnosis.

    PubMed

    Sultankulova, K T; Chervyakova, O V; Kozhabergenov, N S; Shorayeva, K A; Strochkov, V M; Orynbayev, M B; Sandybayev, N T; Sansyzbay, A R; Vasin, A V

    2014-01-01

    The paper describes comparative evaluation of IAVchip DNA microarray, reverse transcription PCR (RT-PCR), and real-time RT-PCR versus virus isolation in chicken embryos and shows their diagnostic effectiveness in detection and subtyping of influenza A virus. The tests were evaluated with use of 185 specimens from humans, animals, and birds. IAVchip DNA microarray demonstrates higher diagnostic effectiveness (99.45%) in early influenza A diagnosis as compared to the real-time PCR (98.38%) and RT-PCR (96.22%), thus showing its clear superiority. Diagnostic sensitivity of IAVchip DNA microarray (100%) exceeds the same of RT-PCR (95.95%) and real-time RT-PCR (97.96%) in the range of estimated confidence intervals. IAVchip DNA microarray and real-time RT-PCR displayed equal diagnostic specificity (98.85%), while diagnostic specificity of RT-PCR was 96.40%. IAVchip DNA microarray has an advantage over the other tests for influenza A diagnosis and virus identification as a more rapid method that allows performing simultaneous detection and subtyping of about tens of specimens within one experiment during 8-10 hours. The developed IAVchip DNA microarray is a general test tool that enables identifying simultaneously 16 hemagglutinin (HA) and 9 neuraminidase (NA) subtypes of influenza A virus and also to screen the influenza A viruses from humans, animals, and birds by M and NP genes. PMID:25548788

  3. A versatile protein microarray platform enabling antibody profiling against denatured proteins

    PubMed Central

    Wang, Jie; Barker, Kristi; Steel, Jason; Park, Jin; Saul, Justin; Festa, Fernanda; Wallstrom, Garrick; Yu, Xiaobo; Bian, Xiaofang; Anderson, Karen S; Figueroa, Jonine D; LaBaer, Joshua; Qiu, Ji

    2014-01-01

    Purpose We aim to develop a protein microarray platform capable of presenting both natural and denatured forms of proteins for antibody biomarker discovery. We will further optimize plasma screening protocols to improve detection. Experimental design We developed a new covalent capture protein microarray chemistry using HaloTag fusion proteins and ligand. To enhance protein yield, we used HeLa cell lysate as an in vitro transcription translation system (IVTT). E. coli lysates were added to the plasma blocking buffer to reduce non-specific background. These protein microarrays were probed with plasma samples and autoantibody responses were quantified and compared with or without denaturing buffer treatment. Results We demonstrated that protein microarrays using the covalent attachment chemistry endured denaturing conditions. Blocking with E. coli lysates greatly reduced the background signals and expression with IVTT based on HeLa cell lysates significantly improved the antibody signals on protein microarrays probed with plasma samples. Plasma samples probed on denatured protein arrays produced autoantibody profiles distinct from those probed on natively displayed proteins. Conclusions and clinical relevance This versatile protein microarray platform allows the display of both natural and denatured proteins, offers a new dimension to search for disease-specific antibodies, broadens the repertoire of potential biomarkers, and will potentially yield clinical diagnostics with greater performance. PMID:23027520

  4. Development and validation of a 2,000-gene microarray for the fathead minnow (Pimephales promelas)

    SciTech Connect

    Larkin, Patrick; Villeneuve, Daniel L.; Knoebl, Iris; Miracle, Ann L.; Carter, Barbara J.; Liu, Li; Denslow, Nancy D.; Ankley, Gerald T.

    2007-07-01

    Gene microarrays provide the field of ecotoxicology new tools to identify mechanisms of action of chemicals and chemical mixtures. Herein we describe the development and application of a 2,000-gene oligonucleotide microarray for the fathead minnow Pimephales promelas, a species commonly used in ecological risk assessments in North America. The microarrays were developed from various cDNA and subtraction libraries that we constructed. Consistency and reproducibility of the microarrays were documented by examining multiple technical replicates. To test application of the fathead minnow microarrays, gene expression profiles of fish exposed to 17-estradiol, a well-characterized estrogen receptor (ER) agonist, were examined. For these experiments, adult male fathead minnows were exposed for 24 h to waterborne 17-estradiol (40 or 100 ng/L) in a flow-through system, and gene expression in liver samples was characterized. Seventy-one genes were identified as differentially regulated by estradiol exposure. Examination of the gene ontology designations of these genes revealed patterns consistent with estradiol’s expected mechanisms of action and also provided novel insights as to molecular effects of the estrogen. Our studies indicate the feasibility and utility of microarrays as a basis for understanding biological responses to chemical exposure in a model ecotoxicology test species.

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

    NASA Astrophysics Data System (ADS)

    Morris, Brandon E. L.

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

  6. Microarray-Based Sketches of the HERV Transcriptome Landscape

    PubMed Central

    Pérot, Philippe; Mugnier, Nathalie; Montgiraud, Cécile; Gimenez, Juliette; Jaillard, Magali; Bonnaud, Bertrand; Mallet, François

    2012-01-01

    Human endogenous retroviruses (HERVs) are spread throughout the genome and their long terminal repeats (LTRs) constitute a wide collection of putative regulatory sequences. Phylogenetic similarities and the profusion of integration sites, two inherent characteristics of transposable elements, make it difficult to study individual locus expression in a large-scale approach, and historically apart from some placental and testis-regulated elements, it was generally accepted that HERVs are silent due to epigenetic control. Herein, we have introduced a generic method aiming to optimally characterize individual loci associated with 25-mer probes by minimizing cross-hybridization risks. We therefore set up a microarray dedicated to a collection of 5,573 HERVs that can reasonably be assigned to a unique genomic position. We obtained a first view of the HERV transcriptome by using a composite panel of 40 normal and 39 tumor samples. The experiment showed that almost one third of the HERV repertoire is indeed transcribed. The HERV transcriptome follows tropism rules, is sensitive to the state of differentiation and, unexpectedly, seems not to correlate with the age of the HERV families. The probeset definition within the U3 and U5 regions was used to assign a function to some LTRs (i.e. promoter or polyA) and revealed that (i) autonomous active LTRs are broadly subjected to operational determinism (ii) the cellular gene density is substantially higher in the surrounding environment of active LTRs compared to silent LTRs and (iii) the configuration of neighboring cellular genes differs between active and silent LTRs, showing an approximately 8 kb zone upstream of promoter LTRs characterized by a drastic reduction in sense cellular genes. These gathered observations are discussed in terms of virus/host adaptive strategies, and together with the methods and tools developed for this purpose, this work paves the way for further HERV transcriptome projects. PMID:22761958

  7. Identification of genes associated with osteoarthritis by microarray analysis.

    PubMed

    Sun, Jianwei; Yan, Bingshan; Yin, Wangping; Zhang, Xinchao

    2015-10-01

    The aim of the present study was to investigate the mechanisms of osteoarthritis (OA). Raw microarray data (GSE51588) were downloaded from Gene Expression Omnibus, including samples from OA (n=20) and non‑OA (n=5) knee lateral and medial tibial plateaus. Differentially expressed genes (DEGs) were identified using Student's t‑test. Functional and pathway enrichment analyses were performed for the upregulated and downregulated DEGs. A protein‑protein interaction network (PPI) was constructed according to the Search Tool for the Retrieval of Interacting Genes/Proteins database, and module analysis of the PPI network was performed using CFinder. The protein domain enrichment analysis for genes in modules was performed using the INTERPRO database. A total of 869 upregulated and 508 downregulated DEGs were identified. The enriched pathways of downregulated and upregulated DEGs were predominantly associated with the cell cycle (BUB1, BUB1B, CCNA2, CCNB1 and CCNE1), and extracellular matrix (ECM)‑receptor interaction (CD36, COL11A2, COL1A1, COL2A1 and COL3A1). Functional enrichment analysis of the DEGs demonstrated that FGF19, KIF11 and KIF2C were involved in the response to stress and that ACAN, ADAMTS10 and BGN were associated with proteinaceous ECM. The top protein domain was IPR001752: Kinesin motor region involving three genes (KIF2C, KIF11 and KIF20A). The identified DEGs, including KIF2C, KIF11 and KIF20A, may be significant in the pathogenesis of OA. PMID:26151199

  8. DNA Microarray-Based Typing of Streptococcus agalactiae Isolates

    PubMed Central

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

    2014-01-01

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

  9. TAMEE: data management and analysis for tissue microarrays

    PubMed Central

    Thallinger, Gerhard G; Baumgartner, Kerstin; Pirklbauer, Martin; Uray, Martina; Pauritsch, Elke; Mehes, Gabor; Buck, Charles R; Zatloukal, Kurt; Trajanoski, Zlatko

    2007-01-01

    Background With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. Results TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. Conclusion We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from . PMID:17343750

  10. Differential analysis for high density tiling microarray data

    PubMed Central

    Ghosh, Srinka; Hirsch, Heather A; Sekinger, Edward A; Kapranov, Philipp; Struhl, Kevin; Gingeras, Thomas R

    2007-01-01

    Background High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. Results We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. Conclusion The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1]. PMID:17892592

  11. Inflammatory Pathways in Parkinson's Disease; A BNE Microarray Study

    PubMed Central

    Durrenberger, Pascal. F.; Grünblatt, Edna; Fernando, Francesca S.; Monoranu, Camelia Maria; Evans, Jordan; Riederer, Peter; Reynolds, Richard; Dexter, David T.

    2012-01-01

    The aetiology of Parkinson's disease (PD) is yet to be fully understood but it is becoming more and more evident that neuronal cell death may be multifactorial in essence. The main focus of PD research is to better understand substantia nigra homeostasis disruption, particularly in relation to the wide-spread deposition of the aberrant protein α-synuclein. Microarray technology contributed towards PD research with several studies to date and one gene, ALDH1A1 (Aldehyde dehydrogenase 1 family, member A1), consistently reappeared across studies including the present study, highlighting dopamine (DA) metabolism dysfunction resulting in oxidative stress and most probably leading to neuronal cell death. Neuronal cell death leads to increased inflammation through the activation of astrocytes and microglia. Using our dataset, we aimed to isolate some of these pathways so to offer potential novel neuroprotective therapeutic avenues. To that effect our study has focused on the upregulation of P2X7 (purinergic receptor P2X, ligand-gated ion channel, 7) receptor pathway (microglial activation) and on the NOS3 (nitric oxide synthase 3) pathway (angiogenesis). In summary, although the exact initiator of striatal DA neuronal cell death remains to be determined, based on our analysis, this event does not remain without consequence. Extracellular ATP and reactive astrocytes appear to be responsible for the activation of microglia which in turn release proinflammatory cytokines contributing further to the parkinsonian condition. In addition to tackling oxidative stress pathways we also suggest to reduce microglial and endothelial activation to support neuronal outgrowth. PMID:22548201

  12. EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

    PubMed Central

    Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

    2008-01-01

    Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks

  13. Simplified Microarray System for Simultaneously Detecting Rifampin, Isoniazid, Ethambutol, and Streptomycin Resistance Markers in Mycobacterium tuberculosis

    PubMed Central

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

    2014-01-01

    We developed a simplified microarray test for detecting and identifying mutations in rpoB, katG, inhA, embB, and rpsL and compared the analytical performance of the test to that of phenotypic drug susceptibility testing (DST). The analytical sensitivity was estimated to be at least 110 genome copies per amplification reaction. The microarray test correctly detected 95.2% of mutations for which there was a sequence-specific probe on the microarray and 100% of 96 wild-type sequences. In a blinded analysis of 153 clinical isolates, microarray sensitivity for first-line drugs relative to phenotypic DST (true resistance) was 100% for rifampin (RIF) (14/14), 90.0% for isoniazid (INH) (36/40), 70% for ethambutol (EMB) (7/10), and 89.1% (57/64) combined. Microarray specificity (true susceptibility) for first-line agents was 95.0% for RIF (132/139), 98.2% for INH (111/113), and 98.6% for EMB (141/143). Overall microarray specificity for RIF, INH, and EMB combined was 97.2% (384/395). The overall positive and negative predictive values for RIF, INH, and EMB combined were 84.9% and 98.3%, respectively. For the second-line drug streptomycin (STR), overall concordance between the agar proportion method and microarray analysis was 89.5% (137/153). Sensitivity was 34.8% (8/23) because of limited microarray coverage for STR-conferring mutations, and specificity was 99.2% (129/130). All false-susceptible discrepant results were a consequence of DNA mutations that are not represented by a specific microarray probe. There were zero invalid results from 220 total tests. The simplified microarray system is suitable for detecting resistance-conferring mutations in clinical M. tuberculosis isolates and can now be used for prospective trials or integrated into an all-in-one, closed-amplicon consumable. PMID:24719444

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

    PubMed Central

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

    2016-01-01

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

  15. M-BISON: Microarray-based integration of data sources using networks

    PubMed Central

    Daigle, Bernie J; Altman, Russ B

    2008-01-01

    Background The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variability of microarrays can be limiting. While a number of existing methods partially overcome these limitations by incorporating biological knowledge in the form of gene groups, these methods sacrifice gene-level resolution. This loss of precision can be inappropriate, especially if the desired output is a ranked list of individual genes. To address this shortcoming, we developed M-BISON (Microarray-Based Integration of data SOurces using Networks), a formal probabilistic model that integrates background biological knowledge with microarray data to predict individual DE genes. Results M-BISON improves signal detection on a range of simulated data, particularly when using very noisy microarray data. We also applied the method to the task of predicting heat shock-related differentially expressed genes in S. cerevisiae, using an hsf1 mutant microarray dataset and conserved yeast DNA sequence motifs. Our results demonstrate that M-BISON improves the analysis quality and makes predictions that are easy to interpret in concert with incorporated knowledge. Specifically, M-BISON increases the AUC of DE gene prediction from .541 to .623 when compared to a method using only microarray data, and M-BISON outperforms a related method, GeneRank. Furthermore, by analyzing M-BISON predictions in the context of the background knowledge, we identified YHR124W as a potentially novel player in the yeast heat shock response. Conclusion This work provides a solid foundation for the principled integration of imperfect biological knowledge with gene expression data and other high-throughput data sources. PMID:18439292

  16. Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells

    PubMed Central

    Zhao, Shanrong; Fung-Leung, Wai-Ping; Bittner, Anton; Ngo, Karen; Liu, Xuejun

    2014-01-01

    To demonstrate the benefits of RNA-Seq over microarray in transcriptome profiling, both RNA-Seq and microarray analyses were performed on RNA samples from a human T cell activation experiment. In contrast to other reports, our analyses focused on the difference, rather than similarity, between RNA-Seq and microarray technologies in transcriptome profiling. A comparison of data sets derived from RNA-Seq and Affymetrix platforms using the same set of samples showed a high correlation between gene expression profiles generated by the two platforms. However, it also demonstrated that RNA-Seq was superior in detecting low abundance transcripts, differentiating biologically critical isoforms, and allowing the identification of genetic variants. RNA-Seq also demonstrated a broader dynamic range than microarray, which allowed for the detection of more differentially expressed genes with higher fold-change. Analysis of the two datasets also showed the benefit derived from avoidance of technical issues inherent to microarray probe performance such as cross-hybridization, non-specific hybridization and limited detection range of individual probes. Because RNA-Seq does not rely on a pre-designed complement sequence detection probe, it is devoid of issues associated with probe redundancy and annotation, which simplified interpretation of the data. Despite the superior benefits of RNA-Seq, microarrays are still the more common choice of researchers when conducting transcriptional profiling experiments. This is likely because RNA-Seq sequencing technology is new to most researchers, more expensive than microarray, data storage is more challenging and analysis is more complex. We expect that once these barriers are overcome, the RNA-Seq platform will become the predominant tool for transcriptome analysis. PMID:24454679

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

    PubMed Central

    Maulik, Ujjwal

    2014-01-01

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

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

    PubMed Central

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

    2005-01-01

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

  19. Mouse strain specific gene expression differences for illumina microarray expression profiling in embryos

    PubMed Central

    2012-01-01

    Background In the field of mouse genetics the advent of technologies like microarray based expression profiling dramatically increased data availability and sensitivity, yet these advanced methods are often vulnerable to the unavoidable heterogeneity of in vivo material and might therefore reflect differentially expressed genes between mouse strains of no relevance to a targeted experiment. The aim of this study was not to elaborate on the usefulness of microarray analysis in general, but to expand our knowledge regarding this potential “background noise” for the widely used Illumina microarray platform surpassing existing data which focused primarily on the adult sensory and nervous system, by analyzing patterns of gene expression at different embryonic stages using wild type strains and modern transgenic models of often non-isogenic backgrounds. Results Wild type embryos of 11 mouse strains commonly used in transgenic and molecular genetic studies at three developmental time points were subjected to Illumina microarray expression profiling in a strain-by-strain comparison. Our data robustly reflects known gene expression patterns during mid-gestation development. Decreasing diversity of the input tissue and/or increasing strain diversity raised the sensitivity of the array towards the genetic background. Consistent strain sensitivity of some probes was attributed to genetic polymorphisms or probe design related artifacts. Conclusion Our study provides an extensive reference list of gene expression profiling background noise of value to anyone in the field of developmental biology and transgenic research performing microarray expression profiling with the widely used Illumina microarray platform. Probes identified as strain specific background noise further allow for microarray expression profiling on its own to be a valuable tool for establishing genealogies of mouse inbred strains. PMID:22583621

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

    PubMed Central

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

    2008-01-01

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