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Sample records for affymetrix microarrays results

  1. 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

  2. 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...

  3. 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

  4. A comparison of statistical tests for detecting differential expression using Affymetrix oligonucleotide microarrays.

    PubMed

    Vardhanabhuti, Saran; Blakemore, Steven J; Clark, Steven M; Ghosh, Sujoy; Stephens, Richard J; Rajagopalan, Dilip

    2006-01-01

    Signal quantification and detection of differential expression are critical steps in the analysis of Affymetrix microarray data. Many methods have been proposed in the literature for each of these steps. The goal of this paper is to evaluate several signal quantification methods (GCRMA, RSVD, VSN, MAS5, and Resolver) and statistical methods for differential expression (t test, Cyber-T, SAM, LPE, RankProducts, Resolver RatioBuild). Our particular focus is on the ability to detect differential expression via statistical tests. We have used two different datasets for our evaluation. First, we have used the HG-U133 Latin Square spike in dataset developed by Affymetrix. Second, we have used data from an in-house rat liver transcriptomics study following 30 different drug treatments generated using the Affymetrix RAE230A chip. Our overall recommendation based on this study is to use GCRMA for signal quantification. For detection of differential expression, GCRMA coupled with Cyber-T or SAM is the best approach, as measured by area under the receiver operating characteristic (ROC) curve. The integrated pipeline in Resolver RatioBuild combining signal quantification and detection of differential expression is an equally good alternative for detecting differentially expressed genes. For most of the differential expression algorithms we considered, the performance using MAS5 signal quantification was inferior to that of the other methods we evaluated. PMID:17233564

  5. A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays

    PubMed Central

    2012-01-01

    Background DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. Results For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. Conclusions To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These

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

    PubMed Central

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

    2016-01-01

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

  7. Qualitative assessment of gene expression in affymetrix genechip arrays

    NASA Astrophysics Data System (ADS)

    Nagarajan, Radhakrishnan; Upreti, Meenakshi

    2007-01-01

    Affymetrix Genechip microarrays are used widely to determine the simultaneous expression of genes in a given biological paradigm. Probes on the Genechip array are atomic entities which by definition are randomly distributed across the array and in turn govern the gene expression. In the present study, we make several interesting observations. We show that there is considerable correlation between the probe intensities across the array which defy the independence assumption. While the mechanism behind such correlations is unclear, we show that scaling behavior and the profiles of perfect match (PM) as well as mismatch (MM) probes are similar and immune-to-background subtraction. We believe that the observed correlations are possibly an outcome of inherent non-stationarities or patchiness in the array devoid of biological significance. This is demonstrated by inspecting their scaling behavior and profiles of the PM and MM probe intensities obtained from publicly available Genechip arrays from three eukaryotic genomes, namely: Drosophila melanogaster (fruit fly), Homo sapiens (humans) and Mus musculus (house mouse) across distinct biological paradigms and across laboratories, with and without background subtraction. The fluctuation functions were estimated using detrended fluctuation analysis (DFA) with fourth-order polynomial detrending. The results presented in this study provide new insights into correlation signatures of PM and MM probe intensities and suggests the choice of DFA as a tool for qualitative assessment of Affymetrix Genechip microarrays prior to their analysis. A more detailed investigation is necessary in order to understand the source of these correlations.

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

    PubMed Central

    Chrominski, Kornel; Tkacz, Magdalena

    2015-01-01

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

  9. Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements

    PubMed Central

    Mecham, Brigham H.; Klus, Gregory T.; Strovel, Jeffrey; Augustus, Meena; Byrne, David; Bozso, Peter; Wetmore, Daniel Z.; Mariani, Thomas J.; Kohane, Isaac S.; Szallasi, Zoltan

    2004-01-01

    Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms. PMID:15161944

  10. Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements.

    PubMed

    Mecham, Brigham H; Klus, Gregory T; Strovel, Jeffrey; Augustus, Meena; Byrne, David; Bozso, Peter; Wetmore, Daniel Z; Mariani, Thomas J; Kohane, Isaac S; Szallasi, Zoltan

    2004-01-01

    Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms. PMID:15161944

  11. 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…

  12. 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.

  13. 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

  14. High Fidelity Copy Number Analysis of Formalin-Fixed and Paraffin-Embedded Tissues Using Affymetrix Cytoscan HD Chip

    PubMed Central

    Yu, Yan P.; Michalopoulos, Amantha; Ding, Ying; Tseng, George; Luo, Jian-Hua

    2014-01-01

    Detection of human genome copy number variation (CNV) is one of the most important analyses in diagnosing human malignancies. Genome CNV detection in formalin-fixed and paraffin-embedded (FFPE) tissues remains challenging due to suboptimal DNA quality and failure to use appropriate baseline controls for such tissues. Here, we report a modified method in analyzing CNV in FFPE tissues using microarray with Affymetrix Cytoscan HD chips. Gel purification was applied to select DNA with good quality and data of fresh frozen and FFPE tissues from healthy individuals were included as baseline controls in our data analysis. Our analysis showed a 91% overlap between CNV detection by microarray with FFPE tissues and chromosomal abnormality detection by karyotyping with fresh tissues on 8 cases of lymphoma samples. The CNV overlap between matched frozen and FFPE tissues reached 93.8%. When the analyses were restricted to regions containing genes, 87.1% concordance between FFPE and fresh frozen tissues was found. The analysis was further validated by Fluorescence In Situ Hybridization on these samples using probes specific for BRAF and CITED2. The results suggested that the modified method using Affymetrix Cytoscan HD chip gave rise to a significant improvement over most of the previous methods in terms of accuracy in detecting CNV in FFPE tissues. This FFPE microarray methodology may hold promise for broad application of CNV analysis on clinical samples. PMID:24699316

  15. 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.

  16. 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.

  17. CEL_INTERROGATOR: A FREE AND OPEN SOURCE PACKAGE FOR AFFYMETRIX CEL FILE PARSING

    Technology Transfer Automated Retrieval System (TEKTRAN)

    CEL_Interrogator Package is a suite of programs designed to extract the average probe intensity and other information for each probe sequence from an Affymetrix GeneChip CEL file and unite them with their human-readable Affymetrix consensus sequence names. The resulting text file is suitable for di...

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

    PubMed Central

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

    2007-01-01

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

  19. 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...

  20. 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)

  1. 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 ...

  2. 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

  3. Exon array data analysis using Affymetrix power tools and R statistical software

    PubMed Central

    2011-01-01

    The use of microarray technology to measure gene expression on a genome-wide scale has been well established for more than a decade. Methods to process and analyse the vast quantity of expression data generated by a typical microarray experiment are similarly well-established. The Affymetrix Exon 1.0 ST array is a relatively new type of array, which has the capability to assess expression at the individual exon level. This allows a more comprehensive analysis of the transcriptome, and in particular enables the study of alternative splicing, a gene regulation mechanism important in both normal conditions and in diseases. Some aspects of exon array data analysis are shared with those for standard gene expression data but others present new challenges that have required development of novel tools. Here, I will introduce the exon array and present a detailed example tutorial for analysis of data generated using this platform. PMID:21498550

  4. Tiling Microarray Analysis Tools

    2005-05-04

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

  5. 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

  6. Allergenius, an expert system for the interpretation of allergen microarray results

    PubMed Central

    2014-01-01

    Background An in vitro procedure based on a microarray containing many different allergen components has recently been introduced for use in allergy diagnosis. Recombinant and highly purified allergens belonging to different allergenic sources (inhalants, food, latex and hymenoptera) are present in the array. These components can either be genuine or cross-reactive, resistant or susceptible to heat and low pH, and innocuous or potentially dangerous. A large number of complex and heterogeneous relationships among these components has emerged, such that sometimes these interactions cannot be effectively managed by the allergist. In the 1960s, specialized languages and environments were developed to support the replacement of human experts with dedicated decision-making information systems. Currently, expert systems (ES) are advanced informatics tools that are widely used in medicine, engineering, finance and trading. Methods We developed an ES, named Allergenius ®, to support the interpretation of allergy tests based on microarray technology (ImmunoCAP ISAC ®). The ES was implemented using Flex, a LPA Win-Prolog shell. Rules representing the knowledge base (KB) were derived from the literature and specialized databases. The input data included the patient’s ID and disease(s), the results of either a skin prick test or specific IgE assays and ISAC results. The output was a medical report. Results The ES was first validated using artificial and real life cases and passed all in silico validations. Then, the opinions of allergists with experience in molecular diagnostics were compared with the ES reports. The Allergenius reports included all of the allergists’ opinions and considerations, as well as any additional information. Conclusions Allergenius is a trustable ES dedicated to molecular tests for allergy. In the present version, it provides a powerful method to understand ISAC results and to obtain a comprehensive interpretation of the patient’s Ig

  7. 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

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

    PubMed Central

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

    2015-01-01

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

  9. Development and Evaluation of an Affymetrix array for Aspergillus flavus

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A multi-species Affymetrix GeneChip array was developed to study development, metabolism and pathogenicity of A. flavus. This chip based on the whole genome sequence of A. flavus, contains 13,000 A. flavus genes, 8,000 maize genes and 25 human and mouse innate immune response genes, as well as the ...

  10. Detection of transcriptional difference of porcine imprinted genes using different microarray platforms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Presently, multiple options exist for conducting gene expression profiling studies in swine. In order to determine the performance of some of the existing platforms, Affymetrix Porcine, Affymetrix Human U133+2.0, and the U.S. Pig Genome Coordination Program spotted glass oligonucleotide microarray p...

  11. Software comparison for evaluating genomic copy number variation for Affymetrix 6.0 SNP array platform

    PubMed Central

    2011-01-01

    Background Copy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments. Results APT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce. Conclusions If the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package

  12. 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

  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. Motif effects in Affymetrix GeneChips seriously affect probe intensities

    PubMed Central

    Upton, Graham J. G.; Harrison, Andrew P.

    2012-01-01

    An Affymetrix GeneChip consists of an array of hundreds of thousands of probes (each a sequence of 25 bases) with the probe values being used to infer the extent to which genes are expressed in the biological material under investigation. In this article, we demonstrate that these probe values are also strongly influenced by their precise base sequence. We use data from >28 000 CEL files relating to 10 different Affymetrix GeneChip platforms and involving nearly 1000 experiments. Our results confirm known effects (those due to the T7-primer and the formation of G-quadruplexes) but reveal other effects. We show that there can be huge variations from one experiment to another, and that there may also be sizeable disparities between batches within an experiment and between CEL files within a batch. PMID:22904084

  16. VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

    NASA Technical Reports Server (NTRS)

    Moseyko, Nick; Feldman, Lewis J.

    2002-01-01

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

  17. 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

  18. 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

  19. 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

  20. Alternations in genes expression of pathway signaling in esophageal tissue with atresia: results of expression microarray profiling.

    PubMed

    Smigiel, R; Lebioda, A; Blaszczyński, M; Korecka, K; Czauderna, P; Korlacki, W; Jakubiak, A; Bednarczyk, D; Maciejewski, H; Wizinska, P; Sasiadek, M M; Patkowski, D

    2015-04-01

    Esophageal atresia (EA) is a congenital defect of the esophagus involving the interruption of the esophagus with or without connection to the trachea (tracheoesophageal fistula [TEF]). EA/TEF may occur as an isolated anomaly, may be part of a complex of congenital defects (syndromic), or may develop within the context of a known syndrome or association. The molecular mechanisms underlying the development of EA are poorly understood. It is supposed that a combination of multigenic factors and epigenetic modification of genes play a role in its etiology. The aim of our work was to assess the human gene expression microarray study in esophageal tissue samples. Total RNA was extracted from 26 lower pouches of esophageal tissue collected during thoracoscopic EA repair in neonates with the isolated (IEA) and the syndromic form (SEA). We identified 787 downregulated and 841 upregulated transcripts between SEA and controls, and about 817 downregulated and 765 upregulated probes between IEA and controls. Fifty percent of these genes showed differential expression specific for either IEA or SEA. Functional pathway analysis revealed substantial enrichment for Wnt and Sonic hedgehog, as well as cytokine and chemokine signaling pathways. Moreover, we performed reverse transcription polymerase chain reaction study in a group of SHH and Wnt pathways genes with differential expression in microarray profiling to confirm the microarray expression results. We verified the altered expression in SFRP2 gene from the Wnt pathway as well as SHH, GLI1, GLI2, and GLI3 from the Sonic hedgehog pathway. The results suggest an important role of these pathways and genes for EA/TEF etiology. PMID:24460849

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

    PubMed Central

    2012-01-01

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

  2. Comparison of feature selection methods for cross-laboratory microarray analysis.

    PubMed

    Liu, Hsi-Che; Peng, Pei-Chen; Hsieh, Tzung-Chien; Yeh, Ting-Chi; Lin, Chih-Jen; Chen, Chien-Yu; Hou, Jen-Yin; Shih, Lee-Yung; Liang, Der-Cherng

    2013-01-01

    The amount of gene expression data of microarray has grown exponentially. To apply them for extensive studies, integrated analysis of cross-laboratory (cross-lab) data becomes a trend, and thus, choosing an appropriate feature selection method is an essential issue. This paper focuses on feature selection for Affymetrix (Affy) microarray studies across different labs. We investigate four feature selection methods: $(t)$-test, significance analysis of microarrays (SAM), rank products (RP), and random forest (RF). The four methods are applied to acute lymphoblastic leukemia, acute myeloid leukemia, breast cancer, and lung cancer Affy data which consist of three cross-lab data sets each. We utilize a rank-based normalization method to reduce the bias from cross-lab data sets. Training on one data set or two combined data sets to test the remaining data set(s) are both considered. Balanced accuracy is used for prediction evaluation. This study provides comprehensive comparisons of the four feature selection methods in cross-lab microarray analysis. Results show that SAM has the best classification performance. RF also gets high classification accuracy, but it is not as stable as SAM. The most naive method is $(t)$-test, but its performance is the worst among the four methods. In this study, we further discuss the influence from the number of training samples, the number of selected genes, and the issue of unbalanced data sets. PMID:24091394

  3. Quality Control Usage in High-Density Microarrays Reveals Differential Gene Expression Profiles in Ovarian Cancer.

    PubMed

    Villegas-Ruiz, Vanessa; Moreno, Jose; Jacome-Lopez, Karina; Zentella-Dehesa, Alejandro; Juarez-Mendez, Sergio

    2016-01-01

    There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile. PMID:27268623

  4. Molecular characterization of Neisseria meningitidis isolates using a resequencing DNA microarray.

    PubMed

    Corless, Caroline E; Kaczmarski, Edward; Borrow, Ray; Guiver, Malcolm

    2008-05-01

    Neisseria meningitidis is a major cause of both meningitis and septicemia. Typically, isolates are characterized by using a combination of immunological phenotyping, using monoclonal and polyclonal antisera, and Sanger nucleotide sequencing of epitope-encoding variable regions, although these methods can be both time-consuming and limited by reagent availability. Herein, we describe and evaluate a novel microarray to define the porB and porA serotypes of N. meningitidis by the resequencing of variable regions in a single hybridization reaction. PCR products for each gene were amplified, pooled in equimolar concentrations, hybridized to the microarray, and analyzed using Affymetrix GeneChip DNA Analysis Software. Resequencing of the microarray data was then validated by comparison with sequencing data. Molecular profiles were generated for 50 isolates that were combinations of phenotypically typeable (ie, PorA and PorB) and non-typeable (PorB only) isolates. Microarray-generated profiles from isolates with a PorB phenotype were concordant with predicted profiles compared with a previously described typing scheme. In addition, 42% (8 of 19) of previously non-typeable samples were assigned a PorB type when tested using the microarray. The remaining isolates were novel types for which no typing antisera are currently available. The porA data were 97% concordant with Sanger nucleotide sequencing. These results suggest that that microarray resequencing may be a useful tool for the characterization of meningococci, particularly for those isolates that cannot be phenotyped, offering an alternative to conventional sequencing methods. PMID:18372424

  5. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed Central

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

    2015-01-01

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

  8. Q-GDEMAR: a general method for the identification of differentially expressed genes in microarrays with unbalanced groups.

    PubMed

    Guebel, Daniel V; Perera-Alberto, Montserrat; Torres, Néstor V

    2016-01-01

    Microarray analysis is a powerful tool to simultaneously determine the pattern of transcription of large amounts of genes. For data post-processing distinct computational methods are currently used that, however, lead to different results regarding the genes expressed differentially. Herein, a new methodology for microarray data analysis named Q-GDEMAR is presented. It combines the quantile characterization of the entire distribution together with the Gaussian deconvolution of the central region of the microarray data distribution. Three discriminant variable variants are proposed that allow us to summarize data and compare groups even when their size is strongly unbalanced. In addition, a simple procedure to compute the false discovery rate (FDR) is also presented. The performance of the method is compared with that observed when using LIMMA (Linear Models Microarray) software as reference. In 58 out of 68 cases, Q-GDEMAR showed a higher sensitivity than LIMMA to detect differentially expressed genes (p = 1 × 10(-10)). The proposed method does not produce biased information, detecting genes with high sensitivity equally well at both tails of the distribution (p = 0.7428). Moreover, all detected genes were associated with very low levels of FDR (median value = 0.67%, interquartile range = 0.87%). Q-GDEMAR can be used as a general method for microarray analysis, but is particularly indicated when the conditions to be compared are unbalanced. The superior performance of Q-GEDEMAR is the consequence of its higher discriminative power and, the fact that it yields a univocal correspondence between the p-values and the values of the discriminating variable. Q-GDEMAR was tested only using Affymetrix microarrays. However, given that it operates after the step of data standardization, it can be used with the same quality features on any of the available mono- or dual-channel microarray platforms. PMID:26563436

  9. The Sterolgene v0 cDNA microarray: a systemic approach to studies of cholesterol homeostasis and drug metabolism

    PubMed Central

    Režen, Tadeja; Juvan, Peter; Fon Tacer, Klementina; Kuzman, Drago; Roth, Adrian; Pompon, Denis; Aggerbeck, Lawrence P; Meyer, Urs A; Rozman, Damjana

    2008-01-01

    Background Cholesterol homeostasis and xenobiotic metabolism are complex biological processes, which are difficult to study with traditional methods. Deciphering complex regulation and response of these two processes to different factors is crucial also for understanding of disease development. Systems biology tools as are microarrays can importantly contribute to this knowledge and can also discover novel interactions between the two processes. Results We have developed a low density Sterolgene v0 cDNA microarray dedicated to studies of cholesterol homeostasis and drug metabolism in the mouse. To illustrate its performance, we have analyzed mouse liver samples from studies focused on regulation of cholesterol homeostasis and drug metabolism by diet, drugs and inflammation. We observed down-regulation of cholesterol biosynthesis during fasting and high-cholesterol diet and subsequent up-regulation by inflammation. Drug metabolism was down-regulated by fasting and inflammation, but up-regulated by phenobarbital treatment and high-cholesterol diet. Additionally, the performance of the Sterolgene v0 was compared to the two commercial high density microarray platforms: the Agilent cDNA (G4104A) and the Affymetrix MOE430A GeneChip. We hybridized identical RNA samples to the commercial microarrays and showed that the performance of Sterolgene is comparable to commercial arrays in terms of detection of changes in cholesterol homeostasis and drug metabolism. Conclusion Using the Sterolgene v0 microarray we were able to detect important changes in cholesterol homeostasis and drug metabolism caused by diet, drugs and inflammation. Together with its next generations the Sterolgene microarrays represent original and dedicated tools enabling focused and cost effective studies of cholesterol homeostasis and drug metabolism. These microarrays have the potential of being further developed into screening or diagnostic tools. PMID:18261244

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

    PubMed Central

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

    2009-01-01

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

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

    EPA Science Inventory

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

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

    PubMed Central

    2010-01-01

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

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

    PubMed Central

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

    2009-01-01

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

  14. SFP Genotyping from Affymetrix Arrays is Robust but Largely Detects Cis-acting Expression Regulators

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The recent development of Affymetrix chips designed from assembled EST sequences has spawned considerable interest in identifying single-feature polymorphisms (SFPs) from transcriptome data. SFPs are valuable genetic markers that potentially offer a physical link to the structural genes themselves....

  15. Discovery and mapping of single feature polymorphisms in wheat using affymetrix arrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Single feature polymorphisms (SFPs) can be a rich source of markers for gene mapping and function studies. To explore the feasibility of using the Affymetrix GeneChip to discover and map SFPs in the large hexaploid wheat genome, six wheat varieties of diverse origins were analyzed for significant pr...

  16. caCORRECT2: Improving the accuracy and reliability of microarray data in the presence of artifacts

    PubMed Central

    2011-01-01

    Background In previous work, we reported the development of caCORRECT, a novel microarray quality control system built to identify and correct spatial artifacts commonly found on Affymetrix arrays. We have made recent improvements to caCORRECT, including the development of a model-based data-replacement strategy and integration with typical microarray workflows via caCORRECT's web portal and caBIG grid services. In this report, we demonstrate that caCORRECT improves the reproducibility and reliability of experimental results across several common Affymetrix microarray platforms. caCORRECT represents an advance over state-of-art quality control methods such as Harshlighting, and acts to improve gene expression calculation techniques such as PLIER, RMA and MAS5.0, because it incorporates spatial information into outlier detection as well as outlier information into probe normalization. The ability of caCORRECT to recover accurate gene expressions from low quality probe intensity data is assessed using a combination of real and synthetic artifacts with PCR follow-up confirmation and the affycomp spike in data. The caCORRECT tool can be accessed at the website: http://cacorrect.bme.gatech.edu. Results We demonstrate that (1) caCORRECT's artifact-aware normalization avoids the undesirable global data warping that happens when any damaged chips are processed without caCORRECT; (2) When used upstream of RMA, PLIER, or MAS5.0, the data imputation of caCORRECT generally improves the accuracy of microarray gene expression in the presence of artifacts more than using Harshlighting or not using any quality control; (3) Biomarkers selected from artifactual microarray data which have undergone the quality control procedures of caCORRECT are more likely to be reliable, as shown by both spike in and PCR validation experiments. Finally, we present a case study of the use of caCORRECT to reliably identify biomarkers for renal cell carcinoma, yielding two diagnostic biomarkers with

  17. 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

  18. EMMA 2 – A MAGE-compliant system for the collaborative analysis and integration of microarray data

    PubMed Central

    Dondrup, Michael; Albaum, Stefan P; Griebel, Thasso; Henckel, Kolja; Jünemann, Sebastian; Kahlke, Tim; Kleindt, Christiane K; Küster, Helge; Linke, Burkhard; Mertens, Dominik; Mittard-Runte, Virginie; Neuweger, Heiko; Runte, Kai J; Tauch, Andreas; Tille, Felix; Pühler, Alfred; Goesmann, Alexander

    2009-01-01

    Background Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays. PMID:19200358

  19. 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.

  20. Gene expression in bovine mammary gland in response to increased milking frequency as determined by microarray and SAGE

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Transcript profiling was performed by Affymetrix microarray analysis and SAGE to characterize changes in gene expression in the bovine mammary gland in response to 4× versus 2× daily milking during the first week of lactation. These changes in gene expression may contribute to the increased milk pro...

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

    EPA Science Inventory

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

  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. 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.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2013-07-01

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

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

    PubMed Central

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

    2010-01-01

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

  9. 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.

  10. A Microarray-Based Gene Expression Analysis to Identify Diagnostic Biomarkers for Unknown Primary Cancer

    PubMed Central

    Kurahashi, Issei; Fujita, Yoshihiko; Arao, Tokuzo; Kurata, Takayasu; Koh, Yasuhiro; Sakai, Kazuko; Matsumoto, Koji; Tanioka, Maki; Takeda, Koji; Takiguchi, Yuichi; Yamamoto, Nobuyuki; Tsuya, Asuka; Matsubara, Nobuaki; Mukai, Hirofumi; Minami, Hironobu; Chayahara, Naoko; Yamanaka, Yasuhiro; Miwa, Keisuke; Takahashi, Shin; Takahashi, Shunji; Nakagawa, Kazuhiko; Nishio, Kazuto

    2013-01-01

    Background The biological basis for cancer of unknown primary (CUP) at the molecular level remains largely unknown, with no evidence of whether a common biological entity exists. Here, we assessed the possibility of identifying a common diagnostic biomarker for CUP using a microarray gene expression analysis. Methods Tumor mRNA samples from 60 patients with CUP were analyzed using the Affymetrix U133A Plus 2.0 GeneChip and were normalized by asinh (hyperbolic arc sine) transformation to construct a mean gene-expression profile specific to CUP. A gene-expression profile specific to non-CUP group was constructed using publicly available raw microarray datasets. The t-tests were performed to compare the CUP with non-CUP groups and the top 59 CUP specific genes with the highest fold change were selected (p-value<0.001). Results Among the 44 genes that were up-regulated in the CUP group, 6 genes for ribosomal proteins were identified. Two of these genes (RPS7 and RPL11) are known to be involved in the Mdm2–p53 pathway. We also identified several genes related to metastasis and apoptosis, suggesting a biological attribute of CUP. Conclusions The protein products of the up-regulated and down-regulated genes identified in this study may be clinically useful as unique biomarkers for CUP. PMID:23671674

  11. Microarray Analyses of Gene Expression during Chondrocyte Differentiation Identifies Novel Regulators of Hypertrophy

    PubMed Central

    James, Claudine G.; Appleton, C. Thomas G.; Ulici, Veronica; Underhill, T. Michael; Beier, Frank

    2005-01-01

    Ordered chondrocyte differentiation and maturation is required for normal skeletal development, but the intracellular pathways regulating this process remain largely unclear. We used Affymetrix microarrays to examine temporal gene expression patterns during chondrogenic differentiation in a mouse micromass culture system. Robust normalization of the data identified 3300 differentially expressed probe sets, which corresponds to 1772, 481, and 249 probe sets exhibiting minimum 2-, 5-, and 10-fold changes over the time period, respectively. GeneOntology annotations for molecular function show changes in the expression of molecules involved in transcriptional regulation and signal transduction among others. The expression of identified markers was confirmed by RT-PCR, and cluster analysis revealed groups of coexpressed transcripts. One gene that was up-regulated at later stages of chondrocyte differentiation was Rgs2. Overexpression of Rgs2 in the chondrogenic cell line ATDC5 resulted in accelerated hypertrophic differentiation, thus providing functional validation of microarray data. Collectively, these analyses provide novel information on the temporal expression of molecules regulating endochondral bone development. PMID:16135533

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

    PubMed Central

    2010-01-01

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

  13. Performance of the Affymetrix GeneChip HIV PRT 440 Platform for Antiretroviral Drug Resistance Genotyping of Human Immunodeficiency Virus Type 1 Clades and Viral Isolates with Length Polymorphisms

    PubMed Central

    Vahey, Maryanne; Nau, Martin E.; Barrick, Sandra; Cooley, John D.; Sawyer, Robert; Sleeker, Alex A.; Vickerman, Peter; Bloor, Stuart; Larder, Brendan; Michael, Nelson L.; Wegner, Scott A.

    1999-01-01

    The performance of a silica chip-based resequencing method, the Affymetrix HIV PRT 440 assay (hereafter referred to as the Affymetrix assay), was evaluated on a panel of well-characterized nonclade B viral isolates and on isolates exhibiting length polymorphisms. Sequencing of human immunodeficiency virus type 1 (HIV-1) pol cDNAs from clades A, C, D, E, and F resulted in clade-specific regions of base-calling ambiguities in regions not known to be associated with resistance polymorphisms, as well as a small number of spurious resistance polymorphisms. The Affymetrix assay failed to detect the presence of additional serine codons distal to reverse transcriptase (RT) codon 68 that are associated with multinucleoside RT inhibitor resistance. The increasing prevalence of non-clade B HIV-1 strains in the United States and Europe and the identification of clinically relevant pol gene length polymorphisms will impact the generalizability of the Affymetrix assay, emphasizing the need to accommodate this expanding pool of pol genotypes in future assay versions. PMID:10405396

  14. Microarray-Based Genetic Mapping Using Soybean Near-Isogenic Lines and Generation of SNP Markers in the Rag1 Aphid-Resistance Interval

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A strategy using near-isogenic lines (NILs) and Affymetrix Soybean GeneChip microarrays was employed to identify genetic markers closely linked to the soybean aphid [Aphis glycines Matsumura (Hemiptera: Aphididae)] resistance gene Rag1 in soybean [Glycine max (L.) Merr.]. Genomic DNA from the aphid ...

  15. CGO: utilizing and integrating gene expression microarray data in clinical research and data management.

    PubMed

    Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D

    2002-02-01

    Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics. PMID:11847084

  16. 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.

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

    PubMed Central

    Cebeci, Ozge; Budak, Hikmet

    2009-01-01

    Glyphosate has been shown to act as an inhibitor of an aromatic amino acid biosynthetic pathway, while other pathways that may be affected by glyphosate are not known. Cross species hybridizations can provide a tool for elucidating biological pathways conserved among organisms. Comparative genome analyses have indicated a high level of colinearity among grass species and Festuca, on which we focus here, and showed rearrangements common to the Pooideae family. Based on sequence conservation among grass species, we selected the Affymetrix GeneChip Wheat Genome Array as a tool for the analysis of expression profiles of three Festuca (fescue) species with distinctly different tolerances to varying levels of glyphosate. Differences in transcript expression were recorded upon foliar glyphosate application at 1.58 mM and 6.32 mM, representing 5% and 20%, respectively, of the recommended rate. Differences highlighted categories of general metabolic processes, such as photosynthesis, protein synthesis, stress responses, and a larger number of transcripts responded to 20% glyphosate application. Differential expression of genes encoding proteins involved in the shikimic acid pathway could not be identified by cross hybridization. Microarray data were confirmed by RT-PCR and qRT-PCR analyses. This is the first report to analyze the potential of cross species hybridization in Fescue species and the data and analyses will help extend our knowledge on the cellular processes affected by glyphosate. PMID:20182642

  18. Gene Expression in the Rat Brain during Sleep Deprivation and Recovery Sleep: An Affymetrix GeneChip® Study

    PubMed Central

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

    2016-01-01

    Previous studies have demonstrated that macromolecular synthesis in the brain is modulated in association with the occurrence of sleep and wakefulness. Similarly, the spectral composition of electroencephalographic activity that occurs during sleep is dependent on the duration of prior wakefulness. Since this homeostatic relationship between wake and sleep is highly conserved across mammalian species, genes that are truly involved in the electroencephalographic response to sleep deprivation (SD) might be expected to be conserved across mammalian species. Therefore, in the rat cerebral cortex, we have studied the effects of SD on the expression of immediate early gene (IEG) and heat shock protein (HSP) mRNAs previously shown to be upregulated in the mouse brain in SD and in recovery sleep (RS) after SD. We find that the molecular response to SD and RS in the brain is highly conserved between these two mammalian species, at least in terms of expression of IEG and HSP family members. Using Affymetrix Neurobiology U34 GeneChips®, we also screened the rat cerebral cortex, basal forebrain, and hypothalamus for other genes whose expression may be modulated by SD or RS. We find that the response of the basal forebrain to SD is more similar to that of the cerebral cortex than to the hypothalamus. Together, these results suggest that sleep-dependent changes in gene expression in the cerebral cortex are similar across rodent species and therefore may underlie sleep history-dependent changes in sleep electroencephalographic activity. PMID:16257491

  19. MMBGX: a method for estimating expression at the isoform level and detecting differential splicing using whole-transcript Affymetrix arrays

    PubMed Central

    Turro, Ernest; Lewin, Alex; Rose, Anna; Dallman, Margaret J.; Richardson, Sylvia

    2010-01-01

    Affymetrix has recently developed whole-transcript GeneChips—‘Gene’ and ‘Exon’ arrays—which interrogate exons along the length of each gene. Although each probe on these arrays is intended to hybridize perfectly to only one transcriptional target, many probes match multiple transcripts located in different parts of the genome or alternative isoforms of the same gene. Existing statistical methods for estimating expression do not take this into account and are thus prone to producing inflated estimates. We propose a method, Multi-Mapping Bayesian Gene eXpression (MMBGX), which disaggregates the signal at ‘multi-match’ probes. When applied to Gene arrays, MMBGX removes the upward bias of gene-level expression estimates. When applied to Exon arrays, it can further disaggregate the signal between alternative transcripts of the same gene, providing expression estimates of individual splice variants. We demonstrate the performance of MMBGX on simulated data and a tissue mixture data set. We then show that MMBGX can estimate the expression of alternative isoforms within one experimental condition, confirming our results by RT-PCR. Finally, we show that our method for detecting differential splicing has a lower error rate than standard exon-level approaches on a previously validated colon cancer data set. PMID:19854940

  20. 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.

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

    PubMed Central

    2013-01-01

    Background The most important challenge of performing insitu transcriptional profiling of the human ocular surface epithelial regions is obtaining samples in sufficient amounts, without contamination from adjacent tissue, as the region of interest is microscopic and closely apposed to other tissues regions. We have effectively collected ocular surface (OS) epithelial tissue samples from the Limbal Epithelial Crypt (LEC), limbus, cornea and conjunctiva of post-mortem cadaver eyes with laser microdissection (LMD) technique for gene expression studies with spotted oligonucleotide microarrays and Gene 1.0 ST arrays. Methods Human donor eyes (4 pairs for spotted oligonucleotide microarrays, 3 pairs for Gene 1.0 ST arrays) consented for research were included in this study with due ethical approval of the Nottingham Research Ethics Committee. Eye retrieval was performed within 36 hours of post-mortem period. The dissected corneoscleral buttons were immersed in OCT media and frozen in liquid nitrogen and stored at −80°C till further use. Microscopic tissue sections of interest were taken on PALM slides and stained with Toluidine Blue for laser microdissection with PALM microbeam systems. Optimisation of the laser microdissection technique was crucial for efficient and cost effective sample collection. Results The starting concentration of RNA as stipulated by the protocol of microarray platforms was taken as the cut-off concentration of RNA samples in our studies. The area of LMD tissue processed for spotted oligonucleotide microarray study ranged from 86,253 μm2 in LEC to 392,887 μm2 in LEC stroma. The RNA concentration of the LMD samples ranged from 22 to 92 pg/μl. The recommended starting concentration of the RNA samples used for Gene 1.0 ST arrays was 6 ng/5 μl. To achieve the desired RNA concentration the area of ocular surface epithelial tissue sample processed for the Gene 1.0 ST array experiments was approximately 100,0000 μm2 to 130,0000 μm2. RNA

  2. 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

  3. 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

  4. Preliminary study of the expression of genes connected with the orexigenic and anorexigenic system using microarray technique in anorexia nervosa.

    PubMed

    Janas-Kozik, Malgorzata; Stachowicz, Malgorzata; Mazurek, Urszula; Zajdel, Alicja; Wilczok, Adam; Krupka-Matuszczyk, Irena; Rybakowski, Janusz K

    2008-01-01

    The pathogenesis of anorexia nervosa (AN) is still poorly understood. The Diagnostic and Statistical Manual of Mental Disorders (4th edition) classification differentiates 2 AN types: the restricting type (AN-R) and the binge eating/purging type (AN-BP). We investigated 4 young women suffering from AN (2 with AN-R and 2 with AN-BP). Four women, age matched, with other psychiatric disorders (paranoid schizophrenia, adjustment disorder, mental retardation) served as the reference group. The oligonucleotide microarray method (HG-U133A, Affymetrix) was used to determine the expression profile of 13 genes connected with the orexigenic and anorexigenic system: leptin, leptin receptor-coding gene, hypocretin (orexin) receptor-coding gene, hypocretin (orexin) neuropeptide precursor-coding gene and growth hormone secretagogue receptor. A hierarchical analysis of the results showed that AN-BP and AN-R patients were grouped into different clusters. Also, expression levels of leptin receptor-coding gene showed significant differences between AN-BP and AN-R patients and between AN-R and control subjects. This preliminary study suggests that the microarray technique may contribute to elucidating molecular genetics of the pathogenesis of both types of AN. PMID:18552512

  5. 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

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

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

  8. 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

  9. 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

  10. 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

  11. 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

  12. Human enteroendocrine cell responses to infection with Chlamydia trachomatis: a microarray study

    PubMed Central

    2014-01-01

    Background Enteroendocrine cells (EEC) are highly specialized cells producing signalling molecules vital to the normal functions of the gut. Recently, we showed altered protein distribution in Chlamydia infected EEC in vitro. The aim of this study was to perform a microarray analysis of the response pattern of EEC from both large and small bowel to infection in vitro, using Chlamydia trachomatis infection as a model. Methods Two human EEC lines: LCC-18, derived from a neuroendocrine colonic tumour, and CNDT-2, derived from a small intestinal carcinoid, were infected using cultured C. trachomatis serovar LGV II strain 434 (ATCC VR-902B). Penicillin G was used to induce persistent infection. We used microarray analysis (Affymetrix GeneChip®) for studying changes in gene expression at different stages of infection. Results Twenty-four hours after active and persistent infection, 66 and 411 genes in LCC-18 and 68 and 170 genes in CNDT-2 cells, respectively showed mean expression ratios >2-fold compared to non-infected cells. These genes encoded factors regulating apoptosis, cell differentiation, transcription regulation, cytokine activity, amine biosynthesis and vesicular transport. We found significant differences in gene transcription levels between persistently infected and non-infected cells in 10 genes coding for different solute carrier transporters (SLC) and in 5 genes related to endocrine function (GABARAPL1, GRIP1, DRD2, SYT5 and SYT7). Conclusions Infected EEC cells exhibit cell-type specific patterns related to vesicular transport, secretion and neurotransmitters. EEC play a pivotal role in regulation of gut motility and an impairment of enteroendocrine function can contribute to motility disorders. PMID:24959205

  13. 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

  14. 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

  15. Heterologous oligonucleotide microarrays for transcriptomics in a non-model species; a proof-of-concept study of drought stress in Musa

    PubMed Central

    Davey, Mark W; Graham, Neil S; Vanholme, Bartel; Swennen, Rony; May, Sean T; Keulemans, Johan

    2009-01-01

    Background 'Systems-wide' approaches such as microarray RNA-profiling are ideally suited to the study of the complex overlapping responses of plants to biotic and abiotic stresses. However, commercial microarrays are only available for a limited number of plant species and development costs are so substantial as to be prohibitive for most research groups. Here we evaluate the use of cross-hybridisation to Affymetrix oligonucleotide GeneChip® microarrays to profile the response of the banana (Musa spp.) leaf transcriptome to drought stress using a genomic DNA (gDNA)-based probe-selection strategy to improve the efficiency of detection of differentially expressed Musa transcripts. Results Following cross-hybridisation of Musa gDNA to the Rice GeneChip® Genome Array, ~33,700 gene-specific probe-sets had a sufficiently high degree of homology to be retained for transcriptomic analyses. In a proof-of-concept approach, pooled RNA representing a single biological replicate of control and drought stressed leaves of the Musa cultivar 'Cachaco' were hybridised to the Affymetrix Rice Genome Array. A total of 2,910 Musa gene homologues with a >2-fold difference in expression levels were subsequently identified. These drought-responsive transcripts included many functional classes associated with plant biotic and abiotic stress responses, as well as a range of regulatory genes known to be involved in coordinating abiotic stress responses. This latter group included members of the ERF, DREB, MYB, bZIP and bHLH transcription factor families. Fifty-two of these drought-sensitive Musa transcripts were homologous to genes underlying QTLs for drought and cold tolerance in rice, including in 2 instances QTLs associated with a single underlying gene. The list of drought-responsive transcripts also included genes identified in publicly-available comparative transcriptomics experiments. Conclusion Our results demonstrate that despite the general paucity of nucleotide sequence data in

  16. Transformation of metabolism with age and lifestyle in Antarctic seals: a case study of systems biology approach to cross-species microarray experiment

    PubMed Central

    2010-01-01

    Background The metabolic transformation that changes Weddell seal pups born on land into aquatic animals is not only interesting for the study of general biology, but it also provides a model for the acquired and congenital muscle disorders which are associated with oxygen metabolism in skeletal muscle. However, the analysis of gene expression in seals is hampered by the lack of specific microarrays and the very limited annotation of known Weddell seal (Leptonychotes weddellii) genes. Results Muscle samples from newborn, juvenile, and adult Weddell seals were collected during an Antarctic expedition. Extracted RNA was hybridized on Affymetrix Human Expression chips. Preliminary studies showed a detectable signal from at least 7000 probe sets present in all samples and replicates. Relative expression levels for these genes was used for further analysis of the biological pathways implicated in the metabolism transformation which occurs in the transition from newborn, to juvenile, to adult seals. Cytoskeletal remodeling, WNT signaling, FAK signaling, hypoxia-induced HIF1 activation, and insulin regulation were identified as being among the most important biological pathways involved in transformation. Conclusion In spite of certain losses in specificity and sensitivity, the cross-species application of gene expression microarrays is capable of solving challenging puzzles in biology. A Systems Biology approach based on gene interaction patterns can compensate adequately for the lack of species-specific genomics information. PMID:20920245

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

    PubMed Central

    2014-01-01

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

  18. 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

  19. 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

  20. TagSmart: analysis and visualization for yeast mutant fitness data measured by tag microarrays

    PubMed Central

    Kim, Chulyun; Kim, Sangkyum; Dorer, Russell; Xie, Dan; Han, Jiawei; Zhong, Sheng

    2007-01-01

    Background A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames) of the yeast Saccharomyces cerevisiae has been systematically constructed. Tag microarrays are widely used to measure the fitness of each mutant in a mutant mixture. The tag array experiments can have a complex experimental design, such as time course measurements and drug treatment with multiple dosages. Results TagSmart is a web application for analysis and visualization of Saccharomyces cerevisiae mutant fitness data measured by tag microarrays. It implements a robust statistical approach to assess the concentration differences among S. cerevisiae mutant strains. It also provides an interactive environment for data analysis and visualization. TagSmart has the following advantages over previously described analysis procedures: 1) it is user-friendly software rather than merely a description of analytical procedure; 2) It can handle complicated experimental designs, such as multiple time points and treatment with multiple dosages; 3) it has higher sensitivity and specificity; 4) It allows users to mask out "bad" tags in the analysis. Two biological tests were performed to illustrate the performance of TagSmart. First, we generated titration mixtures of mutant strains, in which the relative concentration of each strain was controlled. We used tag microarrays to measure the numbers of tag copies in each titration mixture. The data was analyzed with TagSmart and the result showed high precision and recall. Second, TagSmart was applied to a dataset in which heterozygous deletion strain mixture pools were treated with a new drug, Cincreasin. TagSmart identified 53 mutant strains as sensitive to Cincreasin treatment. We individually tested each identified mutant, and found 52 out of the 53 predicted mutants were indeed sensitive to Cincreasin. Conclusion TagSmart is provided "as is" to analyze tag array data produced by Affymetrix and Agilent arrays. TagSmart web

  1. 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

  2. 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.

  3. 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…

  4. CARMAweb: comprehensive R- and bioconductor-based web service for microarray data analysis.

    PubMed

    Rainer, Johannes; Sanchez-Cabo, Fatima; Stocker, Gernot; Sturn, Alexander; Trajanoski, Zlatko

    2006-07-01

    CARMAweb (Comprehensive R-based Microarray Analysis web service) is a web application designed for the analysis of microarray data. CARMAweb performs data preprocessing (background correction, quality control and normalization), detection of differentially expressed genes, cluster analysis, dimension reduction and visualization, classification, and Gene Ontology-term analysis. This web application accepts raw data from a variety of imaging software tools for the most widely used microarray platforms: Affymetrix GeneChips, spotted two-color microarrays and Applied Biosystems (ABI) microarrays. R and packages from the Bioconductor project are used as an analytical engine in combination with the R function Sweave, which allows automatic generation of analysis reports. These report files contain all R commands used to perform the analysis and guarantee therefore a maximum transparency and reproducibility for each analysis. The web application is implemented in Java based on the latest J2EE (Java 2 Enterprise Edition) software technology. CARMAweb is freely available at https://carmaweb.genome.tugraz.at. PMID:16845058

  5. Modeling Oncogenic Signaling in Colon Tumors by Multidirectional Analyses of Microarray Data Directed for Maximization of Analytical Reliability

    PubMed Central

    Rubel, Tymon; Paziewska, Agnieszka; Mikula, Michal; Jarosz, Dorota; Pachlewski, Jacek; Oledzki, Janusz; Ostrowsk, Jerzy

    2010-01-01

    Background Clinical progression of colorectal cancers (CRC) may occur in parallel with distinctive signaling alterations. We designed multidirectional analyses integrating microarray-based data with biostatistics and bioinformatics to elucidate the signaling and metabolic alterations underlying CRC development in the adenoma-carcinoma sequence. Methodology/Principal Findings Studies were performed on normal mucosa, adenoma, and carcinoma samples obtained during surgery or colonoscopy. Collections of cryostat sections prepared from the tissue samples were evaluated by a pathologist to control the relative cell type content. The measurements were done using Affymetrix GeneChip HG-U133plus2, and probe set data was generated using two normalization algorithms: MAS5.0 and GCRMA with least-variant set (LVS). The data was evaluated using pair-wise comparisons and data decomposition into singular value decomposition (SVD) modes. The method selected for the functional analysis used the Kolmogorov-Smirnov test. Expressional profiles obtained in 105 samples of whole tissue sections were used to establish oncogenic signaling alterations in progression of CRC, while those representing 40 microdissected specimens were used to select differences in KEGG pathways between epithelium and mucosa. Based on a consensus of the results obtained by two normalization algorithms, and two probe set sorting criteria, we identified 14 and 17 KEGG signaling and metabolic pathways that are significantly altered between normal and tumor samples and between benign and malignant tumors, respectively. Several of them were also selected from the raw microarray data of 2 recently published studies (GSE4183 and GSE8671). Conclusion/Significance Although the proposed strategy is computationally complex and labor–intensive, it may reduce the number of false results. PMID:20957034

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

    SciTech Connect

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

    2006-02-13

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

  7. GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms

    PubMed Central

    2010-01-01

    Background An important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases. Results Here we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina. Conclusions GeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions

  8. 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

  9. 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

  10. Profiling Pre-MicroRNA and Mature MicroRNA Expressions Using a Single Microarray and Avoiding Separate Sample Preparation

    PubMed Central

    Gan, Lin; Denecke, Bernd

    2013-01-01

    Mature microRNA is a crucial component in the gene expression regulation network. At the same time, microRNA gene expression and procession is regulated in a precise and collaborated way. Pre-microRNAs mediate products during the microRNA transcription process, they can provide hints of microRNA gene expression regulation or can serve as alternative biomarkers. To date, little effort has been devoted to pre-microRNA expression profiling. In this study, three human and three mouse microRNA profile data sets, based on the Affymetrix miRNA 2.0 array, have been re-analyzed for both mature and pre-microRNA signals as a primary test of parallel mature/pre-microRNA expression profiling on a single platform. The results not only demonstrated a glimpse of pre-microRNA expression in human and mouse, but also the relationship of microRNA expressions between pre- and mature forms. The study also showed a possible application of currently available microRNA microarrays in profiling pre-microRNA expression in a time and cost effective manner.

  11. A genome-wide study of preferential amplification/hybridization in microarray-based pooled DNA experiments

    PubMed Central

    Yang, H.-C.; Liang, Y.-J.; Huang, M.-C.; Li, L.-H.; Lin, C.-H.; Wu, J.-Y.; Chen, Y.-T.; Fann, C.S.J.

    2006-01-01

    Microarray-based pooled DNA methods overcome the cost bottleneck of simultaneously genotyping more than 100 000 markers for numerous study individuals. The success of such methods relies on the proper adjustment of preferential amplification/hybridization to ensure accurate and reliable allele frequency estimation. We performed a hybridization-based genome-wide single nucleotide polymorphisms (SNPs) genotyping analysis to dissect preferential amplification/hybridization. The majority of SNPs had less than 2-fold signal amplification or suppression, and the lognormal distributions adequately modeled preferential amplification/hybridization across the human genome. Comparative analyses suggested that the distributions of preferential amplification/hybridization differed among genotypes and the GC content. Patterns among different ethnic populations were similar; nevertheless, there were striking differences for a small proportion of SNPs, and a slight ethnic heterogeneity was observed. To fulfill appropriate and gratuitous adjustments, databases of preferential amplification/hybridization for African Americans, Caucasians and Asians were constructed based on the Affymetrix GeneChip Human Mapping 100 K Set. The robustness of allele frequency estimation using this database was validated by a pooled DNA experiment. This study provides a genome-wide investigation of preferential amplification/hybridization and suggests guidance for the reliable use of the database. Our results constitute an objective foundation for theoretical development of preferential amplification/hybridization and provide important information for future pooled DNA analyses. PMID:16931491

  12. Construction and Validation of the Rhodobacter sphaeroides 2.4.1 DNA Microarray: Transcriptome Flexibility at Diverse Growth Modes

    SciTech Connect

    Pappas, Christopher T.; Sram, Jakub; Moskvin, Oleg V.; Ivanov, Pavel S.; Mackenzie, Christopher; Choudhary, Madhusudan; Land, Miriam L; Larimer, Frank W; Kaplan, Samuel; Gomelsky, Mark

    2004-07-01

    A high-density oligonucleotide DNA microarray, a genechip, representing the 4.6-Mb genome of the facultative phototrophic proteobacterium, Rhodobacter sphaeroides 2.4.1, was custom-designed and manufactured by Affymetrix, Santa Clara, Calif. The genechip contains probe sets for 4,292 open reading frames (ORFs), 47 rRNA and tRNA genes, and 394 intergenic regions. The probe set sequences were derived from the genome annotation generated by Oak Ridge National Laboratory after extensive revision, which was based primarily upon codon usage characteristic of this GC-rich bacterium. As a result of the revision, numerous missing ORFs were uncovered, nonexistent ORFs were deleted, and misidentified start codons were corrected. To evaluate R. sphaeroides transcriptome flexibility, expression profiles for three diverse growth modes-aerobic respiration, anaerobic respiration in the dark, and anaerobic photosynthesis-were generated. Expression levels of one-fifth to one-third of the R. sphaeroides ORFs were significantly different in cells under any two growth modes. Pathways involved in energy generation and redox balance maintenance under three growth modes were reconstructed. Expression patterns of genes involved in these pathways mirrored known functional changes, suggesting that massive changes in gene expression are the major means used by R. sphaeroides in adaptation to diverse conditions. Differential expression was observed for genes encoding putative new participants in these pathways (additional photosystem genes, duplicate NADH dehydrogenase, ATP synthases), whose functionality has yet to be investigated. The DNA microarray data correlated well with data derived from quantitative reverse transcription-PCR, as well as with data from the literature, thus validating the R. sphaeroides genechip as a powerful and reliable tool for studying unprecedented metabolic versatility of this bacterium.

  13. Evaluating the Influence of Quality Control Decisions and Software Algorithms on SNP Calling for the Affymetrix 6.0 SNP Array Platform

    PubMed Central

    de Andrade, Mariza; Atkinson, Elizabeth J.; Bamlet, William R.; Matsumoto, Martha E.; Maharjan, Sooraj; Slager, Susan L.; Vachon, Celine M.; Cunningham, Julie M.; Kardia, Sharon L.R.

    2011-01-01

    Objective Our goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0. Methods Various QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets. Results For Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed. Conclusions Using our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h). PMID:21734406

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. GTI: A Novel Algorithm for Identifying Outlier Gene Expression Profiles from Integrated Microarray Datasets

    PubMed Central

    Mpindi, John Patrick; Sara, Henri; Haapa-Paananen, Saija; Kilpinen, Sami; Pisto, Tommi; Bucher, Elmar; Ojala, Kalle; Iljin, Kristiina; Vainio, Paula; Björkman, Mari; Gupta, Santosh; Kohonen, Pekka; Nees, Matthias; Kallioniemi, Olli

    2011-01-01

    Background Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. We developed and validated a new bioinformatic method for the identification of genes upregulated in subsets of samples of a given tumour type (‘outlier genes’), a hallmark of potential oncogenes. Methodology A new statistical method (the gene tissue index, GTI) was developed by modifying and adapting algorithms originally developed for statistical problems in economics. We compared the potential of the GTI to detect outlier genes in meta-datasets with four previously defined statistical methods, COPA, the OS statistic, the t-test and ORT, using simulated data. We demonstrated that the GTI performed equally well to existing methods in a single study simulation. Next, we evaluated the performance of the GTI in the analysis of combined Affymetrix gene expression data from several published studies covering 392 normal samples of tissue from the central nervous system, 74 astrocytomas, and 353 glioblastomas. According to the results, the GTI was better able than most of the previous methods to identify known oncogenic outlier genes. In addition, the GTI identified 29 novel outlier genes in glioblastomas, including TYMS and CDKN2A. The over-expression of these genes was validated in vivo by immunohistochemical staining data from clinical glioblastoma samples. Immunohistochemical data were available for 65% (19 of 29) of these genes, and 17 of these 19 genes (90%) showed a typical outlier staining pattern. Furthermore, raltitrexed, a specific inhibitor of TYMS used in the therapy of tumour types other than glioblastoma, also effectively blocked cell proliferation in glioblastoma cell lines, thus highlighting this outlier gene candidate as a potential therapeutic target. Conclusions/Significance Taken together, these results support the GTI as a novel approach to identify potential oncogene outliers and drug targets. The algorithm is implemented in

  3. 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

  4. Microarray Analysis of Port Wine Stains Before and After Pulsed Dye Laser Treatment

    PubMed Central

    Laquer, Vivian T.; Hevezi, Peter A.; Albrecht, Huguette; Chen, Tina S.; Zlotnik, Albert; Kelly, Kristen M.

    2014-01-01

    Background and Objectives Neither the pathogenesis of port wine stain (PWS) birthmarks nor tissue effects of pulsed dye laser (PDL) treatment of these lesions is fully understood. There are few published reports utilizing gene expression analysis in human PWS skin. We aim to compare gene expression in PWS before and after PDL, using DNA microarrays that represent most, if not all, human genes to obtain comprehensive molecular profiles of PWS lesions and PDL-associated tissue effects. Materials and Methods Five human subjects had PDL treatment of their PWS. One week later, three biopsies were taken from each subject: normal skin (N); untreated PWS (PWS); PWS post-PDL (PWS + PDL). Samples included two lower extremity lesions, two facial lesions, and one facial nodule. High-quality total RNA isolated from skin biopsies was processed and applied to Affymetrix Human gene 1.0ST microarrays for gene expression analysis. We performed a 16 pair-wise comparison identifying either up- or down-regulated genes between N versus PWS and PWS versus PWS + PDL for four of the donor samples. The PWS nodule (nPWS) was analyzed separately. Results There was significant variation in gene expression profiles between individuals. By doing pair-wise comparisons between samples taken from the same donor, we were able to identify genes that may participate in the formation of PWS lesions and PDL tissue effects. Genes associated with immune, epidermal, and lipid metabolism were up-regulated in PWS skin. The nPWS exhibited more profound differences in gene expression than the rest of the samples, with significant differential expression of genes associated with angiogenesis, tumorigenesis, and inflammation. Conclusion In summary, gene expression profiles from N, PWS, and PWS + PDL demonstrated significant variation within samples from the same donor and between donors. By doing pair-wise comparisons between samples taken from the same donor and comparing these results between donors, we were

  5. KARMA: a web server application for comparing and annotating heterogeneous microarray platforms.

    PubMed

    Cheung, Kei-Hoi; Hager, Janet; Pan, Deyun; Srivastava, Ranjana; Mane, Shrikant; Li, Yuli; Miller, Perry; Williams, Kenneth R

    2004-07-01

    We have developed a universal web server application (KARMA) that allows comparison and annotation of user-defined pairs of microarray platforms based on diverse types of genome annotation data (across different species) collected from multiple sources. The application is an effective tool for diverse microarray platforms, including arrays that are provided by (i) the Keck Microarray Resource at Yale, (ii) commercially available Affymetrix GeneChips and spotted arrays and (iii) custom arrays made by individual academics. The tool provides a web interface that allows users to input pairs of test files that represent diverse array platforms for either single or multiple species. The program dynamically identifies analogous DNA fragments spotted or synthesized on multiple microarray platforms based on the following types of information: (i) NCBI-Unigene identifiers, if the platforms being compared are within the same species or (ii) NCBI-Homologene data, if they are cross-species. The single-species comparison is implemented based on set operations: intersection, union and difference. Other forms of retrievable annotation data, including LocusLink, SwissProt and Gene Ontology (GO), are collected from multiple remote sites and stored in an integrated fashion using an Oracle database. The KARMA database, which is updated periodically, is available on line at the following URL: http://ymd.med.yale.edu/karma/cgi-bin/karma.pl. PMID:15215426

  6. Splicy: a web-based tool for the prediction of possible alternative splicing events from Affymetrix probeset data

    PubMed Central

    Rambaldi, Davide; Felice, Barbara; Praz, Viviane; Bucher, Philip; Cittaro, Davide; Guffanti, Alessandro

    2007-01-01

    Background The Affymetrix™ technology is nowadays a well-established method for the analysis of gene expression profiles in cancer research studies. However, changes in gene expression levels are not the only way to link genes and disease. The existence of gene isoforms specifically linked with cancer or apoptosis is increasingly found in literature. Hence it is of great interest to associate the results of a gene expression study with updated evidences on the transcript structure and its possible variants. Results We present here a web-based software tool, Splicy, whose primary task is to retrieve data on the mapping of Affymetrix™ probes to single exons of gene transcripts and displaying graphically this information projected on the gene physical structure. Starting from a list of Affymetrix™ probesets the program produces a series of graphical displays, each relative to a transcript associated with the gene targeted by a given probe. The information on the transcript-by-transcript and exon-by-exon mapping of probe pairs can be retrieved both graphically and in the form of tab-separated files. The mapping of single probes to NCBI RefSeq or EMBL cDNAs is handled by the ISREC mapping tables used in the CleanEx Expression Reference Database Project. We currently maintain these mappings for most popular human and mouse Affymetrix™ chips, and Splicy can be queried for matches with human and mouse NCBI RefSeq or EMBL cDNAs. Conclusion Splicy generates probeset annotations and images describing the relation between the single probes and intron/exon structure of the target transcript in all its known variants. We think that Splicy will be useful for giving to the researcher a clearer picture of the possible transcript variants linked with a given gene and an additional view on the interpretation of microarray experiment data. Splicy is publicly available and has been realized in the framework of a bioinformatics grant from the Italian Cancer Research Association

  7. A Robust Plant RNA Isolation Method for Affymetrix Genechip® Analysis and Quantitative Real-Time RT-PCR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Microarray analysis and quantitative real-time RT-PCR are the major high-throughput techniques that are used to study transcript profiles. One of the major limitations in these technologies is the isolation maximum yield of highly-pure RNA from plant tissues rich in complex polysaccharides, polyphen...

  8. 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

  9. Microarray analysis of microRNA expression in mouse fetus at 13.5 and 14.5 days post-coitum in ear and back skin tissues.

    PubMed

    Torres, Leda; Juárez, Ulises; García, Laura; Miranda-Ríos, Juan; Frias, Sara

    2016-09-01

    There is no information regarding the role of microRNAs in the development of the external ear in mammals. The purpose of this study was to determine the stage-specific expression of microRNA during external ear development in mice under normal conditions. GeneChip miRNA 3.0 arrays by Affymetrix were used to obtain miRNA expression profiles from mice fetal pinnae and back skin tissues at 13.5 days-post-coitum (dpc) and 14.5 dpc. Biological triplicates for each tissue were analyzed; one litter represents one biological replica, each litter had 16 fetuses on average. The results were analyzed with Affymetrix's Transcriptome Analysis Console software to identify differentially expressed miRNAs. The inquiry showed significant differential expression of 25 miRNAs at 13.5 dpc and 31 at 14.5 dpc, some of these miRNAs were predicted to target genes implicated in external ear development. One example is mmu-miR-10a whose low expression in pinnae is known to impact ear development by modulating Hoxa1 mRNA levels Garzon et al. (2006), Gavalas et al. (1998) [1], [2]. Other findings like the upregulation of mmu-miR-200c and mmu-miR-205 in the pinnae tissues of healthy mice are in agreement with what has been reported in human patients with microtia, in which down regulation of both miRNAs has been found Li et al. (2013) [3]. This study uncovered a spatiotemporal pattern of miRNA expression in the external ear, which results from continuous transcriptional changes during normal development of body structures. All microarray data are available at the Gene Expression Omnibus (GEO) at NCBI under accession number GSE64945. PMID:27408816

  10. Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray

    PubMed Central

    Linger, Yvonne; Kukhtin, Alexander; Golova, Julia; Perov, Alexander; Qu, Peter; Knickerbocker, Christopher; Cooney, Christopher G.; Chandler, Darrell P.

    2014-01-01

    Simplifying microarray workflow is a necessary first step for creating MDR-TB microarray-based diagnostics that can be routinely used in lower-resource environments. An amplification microarray combines asymmetric PCR amplification, target size selection, target labeling, and microarray hybridization within a single solution and into a single microfluidic chamber. A batch processing method is demonstrated with a 9-plex asymmetric master mix and low-density gel element microarray for genotyping multi-drug resistant Mycobacterium tuberculosis (MDR-TB). The protocol described here can be completed in 6 hr and provide correct genotyping with at least 1,000 cell equivalents of genomic DNA. Incorporating on-chip wash steps is feasible, which will result in an entirely closed amplicon method and system. The extent of multiplexing with an amplification microarray is ultimately constrained by the number of primer pairs that can be combined into a single master mix and still achieve desired sensitivity and specificity performance metrics, rather than the number of probes that are immobilized on the array. Likewise, the total analysis time can be shortened or lengthened depending on the specific intended use, research question, and desired limits of detection. Nevertheless, the general approach significantly streamlines microarray workflow for the end user by reducing the number of manually intensive and time-consuming processing steps, and provides a simplified biochemical and microfluidic path for translating microarray-based diagnostics into routine clinical practice. PMID:24796567

  11. 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.

  12. 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.

  13. Gene expression profiling of flag leaves at the booting stage in the japonica hybrid rice Huayou14 and its parental lines by microarray.

    PubMed

    Huangwei, Chu; Fuan, Niu; Can, Cheng; Jihua, Zhou; Xinqi, Wang; Xiaojin, Luo; Qin, Yuan; Liming, Cao

    2015-09-01

    Gene expression profiling using microarray has contributed significantly to heterosis studies. Using the Affymetrix rice genome array, we investigated gene expression profiles in the flag leaves of the japonica hybrid rice Huayou14 and its parental cultivars Shen9A and Fan14 at the booting stage. A total of 2057 genes differentially expressed (fold change ≥2 or ≤0.5) between Huayou14 and its parents were identified. Functional classification of the differentially expressed genes by Gene Ontology (GO) analysis indicated the differentially expressed genes were significantly enriched in photosynthesis-related cellular component categories (e.g. photosystem Ⅰ, chloroplast membrane and chloroplast envelope), and biological process categories (e.g. chlorophyll catabolic, chlorophyll biosynthetic and carotenoid biosynthetic processes). These results suggest that the changes in the photosynthetic ability of the japonica hybrid rice Huayou14 may be related to heterosis. Metabolic pathway analysis indicated that differentially expressed genes were significantly enriched in photosynthesis-antenna proteins and starch and sucrose metabolic pathways, instead of photosynthesis and carbon fixation pathways as reported previously. These results suggest that different genes or metabolic pathways might contribute to the heterosis of different hybrid combinations. PMID:26399533

  14. Consensus by Democracy. Using Meta-Analyses of Microarray and Genomic Data to Model the Cold Acclimation Signaling Pathway in Arabidopsis1[W

    PubMed Central

    Benedict, Catherine; Geisler, Matt; Trygg, Johan; Huner, Norman; Hurry, Vaughan

    2006-01-01

    The whole-genome response of Arabidopsis (Arabidopsis thaliana) exposed to different types and durations of abiotic stress has now been described by a wealth of publicly available microarray data. When combined with studies of how gene expression is affected in mutant and transgenic Arabidopsis with altered ability to transduce the low temperature signal, these data can be used to test the interactions between various low temperature-associated transcription factors and their regulons. We quantized a collection of Affymetrix microarray data so that each gene in a particular regulon could vote on whether a cis-element found in its promoter conferred induction (+1), repression (−1), or no transcriptional change (0) during cold stress. By statistically comparing these election results with the voting behavior of all genes on the same gene chip, we verified the bioactivity of novel cis-elements and defined whether they were inductive or repressive. Using in silico mutagenesis we identified functional binding consensus variants for the transcription factors studied. Our results suggest that the previously identified ICEr1 (induction of CBF expression region 1) consensus does not correlate with cold gene induction, while the ICEr3/ICEr4 consensuses identified using our algorithms are present in regulons of genes that were induced coordinate with observed ICE1 transcript accumulation and temporally preceding genes containing the dehydration response element. Statistical analysis of overlap and cis-element enrichment in the ICE1, CBF2, ZAT12, HOS9, and PHYA regulons enabled us to construct a regulatory network supported by multiple lines of evidence that can be used for future hypothesis testing. PMID:16896234

  15. Consensus by democracy. Using meta-analyses of microarray and genomic data to model the cold acclimation signaling pathway in Arabidopsis.

    PubMed

    Benedict, Catherine; Geisler, Matt; Trygg, Johan; Huner, Norman; Hurry, Vaughan

    2006-08-01

    The whole-genome response of Arabidopsis (Arabidopsis thaliana) exposed to different types and durations of abiotic stress has now been described by a wealth of publicly available microarray data. When combined with studies of how gene expression is affected in mutant and transgenic Arabidopsis with altered ability to transduce the low temperature signal, these data can be used to test the interactions between various low temperature-associated transcription factors and their regulons. We quantized a collection of Affymetrix microarray data so that each gene in a particular regulon could vote on whether a cis-element found in its promoter conferred induction (+1), repression (-1), or no transcriptional change (0) during cold stress. By statistically comparing these election results with the voting behavior of all genes on the same gene chip, we verified the bioactivity of novel cis-elements and defined whether they were inductive or repressive. Using in silico mutagenesis we identified functional binding consensus variants for the transcription factors studied. Our results suggest that the previously identified ICEr1 (induction of CBF expression region 1) consensus does not correlate with cold gene induction, while the ICEr3/ICEr4 consensuses identified using our algorithms are present in regulons of genes that were induced coordinate with observed ICE1 transcript accumulation and temporally preceding genes containing the dehydration response element. Statistical analysis of overlap and cis-element enrichment in the ICE1, CBF2, ZAT12, HOS9, and PHYA regulons enabled us to construct a regulatory network supported by multiple lines of evidence that can be used for future hypothesis testing. PMID:16896234

  16. 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.

  17. 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

  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. 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.

  20. Genomic response to Wnt signalling is highly context-dependent - Evidence from DNA microarray and chromatin immunoprecipitation screens of Wnt/TCF targets

    SciTech Connect

    Railo, Antti; Pajunen, Antti; Itaeranta, Petri; Naillat, Florence; Vuoristo, Jussi; Kilpelaeinen, Pekka; Vainio, Seppo

    2009-10-01

    Wnt proteins are important regulators of embryonic development, and dysregulated Wnt signalling is involved in the oncogenesis of several human cancers. Our knowledge of the downstream target genes is limited, however. We used a chromatin immunoprecipitation-based assay to isolate and characterize the actual gene segments through which Wnt-activatable transcription factors, TCFs, regulate transcription and an Affymetrix microarray analysis to study the global transcriptional response to the Wnt3a ligand. The anti-{beta}-catenin immunoprecipitation of DNA-protein complexes from mouse NIH3T3 fibroblasts expressing a fusion protein of {beta}-catenin and TCF7 resulted in the identification of 92 genes as putative TCF targets. GeneChip assays of gene expression performed on NIH3T3 cells and the rat pheochromocytoma cell line PC12 revealed 355 genes in NIH3T3 and 129 genes in the PC12 cells with marked changes in expression after Wnt3a stimulus. Only 2 Wnt-regulated genes were shared by both cell lines. Surprisingly, Disabled-2 was the only gene identified by the chromatin immunoprecipitation approach that displayed a marked change in expression in the GeneChip assay. Taken together, our approaches give an insight into the complex context-dependent nature of Wnt pathway transcriptional responses and identify Disabled-2 as a potential new direct target for Wnt signalling.

  1. 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

  2. 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

  3. 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

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

    PubMed

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

    2016-03-01

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

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

    PubMed Central

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

    2016-01-01

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

  6. The efficacy of detecting variants with small effects on the Affymetrix 6.0 platform using pooled DNA

    PubMed Central

    Chiang, Charleston W. K.; Gajdos, Zofia K. Z.; Butler, Johannah L.; Hackett, Rachel; Guiducci, Candace; Nguyen, Thutrang T.; Wilks, Rainford; Forrester, Terrence; Henderson, Katherine D.; Le Marchand, Loic; Henderson, Brian E.; Haiman, Christopher A.; Cooper, Richard S.; Lyon, Helen N.; Zhu, Xiaofeng; McKenzie, Colin A.; Palmer, Mark R.; Hirschhorn, Joel N.

    2012-01-01

    Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for

  7. 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

  8. Microarray analysis of immune challenged Drosophila hemocytes.

    PubMed

    Johansson, Karin C; Metzendorf, Christoph; Söderhäll, Kenneth

    2005-04-15

    Insect hemocytes play multiple roles in immunity and carry out cellular responses like phagocytosis, encapsulation and melanization as well as producing humoral effector proteins in the first line of defense after injury and invasion of microorganisms. In this work, we used the Drosophila melanogaster hemocyte-like cell line mbn-2 and Affymetrix Drosophila GeneChips to investigate the transcriptome of a single type of immune competent tissue exposed to Gram-negative cell wall components (crude LPS) or high dose infection with live Escherichia coli. We found that gene expression profiles of both treatments overlap but show important differences in expression levels of several genes involved in immunity. In addition, cell morphology during infection was monitored and revealed distinct alterations in cell shape and adhesion. Presence of large numbers of bacteria also increased the number of cells taking on crystal cell fate. Taken together, our results indicate that hemocytes sense and respond differently to purified bacterial surface molecules and infection with live and actively growing bacteria both at the level of gene expression and in cell behavior. PMID:15777795

  9. Microarray-based detection and expression analysis of extracellular matrix proteins in drug‑resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Ruciński, Marcin; Zabel, Maciej

    2014-11-01

    Ovarian cancer is the most lethal gynecological malignancy. Multiple drug resistance (MDR) development leads to resistance of cancer cells to chemotherapy. Microarray methods can provide information regarding new candidate genes that can play a role in resistance to cytostatic drugs. Extracellular matrix (ECM) can influence drug resistance by inhibiting the penetration of the drug into cancer tissue as well as increased apoptosis resistance. In the present study, we report changes in the ECM and related gene expression pattern in methotrexate-, cisplatin-, doxorubicin-, vincristine-, topotecan- and paclitaxel-resistant variants of the W1 ovarian cancer cell line. The resistant variants of the W1 cell line were generated by stepwise selection of cells with an increasing concentration of the indicated drugs. Affymetrix GeneChip® Human Genome U219 Array Strips were used for hybridizations. Independent t-tests were used to determinate the statistical significance of results. Genes whose expression levels were higher than the assumed threshold (upregulated, >5-fold and downregulated, <5-fold) were visualized using the scatter plot method, selected and listed in the tables. Among the investigated genes, expression of 24 genes increased, expression of 14 genes decreased and expression of three genes increased or decreased depending on the cell line. Among the increased genes, expression of 10 increased very significantly, >20-fold. These genes were: ITGB1BP3, COL3A1, COL5A2, COL15A1, TGFBI, DCN, LUM, MATN2, POSTN and EGFL6. The expression of seven genes decreased very significantly: ITGA1, COL1A2, LAMA2, GPC3, KRT23, VIT and HMCN1. The expression pattern of ECM and related genes provided the preliminary view into the role of ECM components in cytostatic drug resistance of cancer cells. The exact role of the investigated genes in drug resistance requires further investigation. PMID:25199881

  10. Microarray-based detection and expression analysis of ABC and SLC transporters in drug-resistant ovarian cancer cell lines.

    PubMed

    Januchowski, Radosław; Zawierucha, Piotr; Andrzejewska, Małgorzata; Ruciński, Marcin; Zabel, Maciej

    2013-04-01

    Multiple drug resistance of cancer cells is multifactorial. A microarray technique may provide information about new candidate genes playing a role in drug resistance. Drug membrane transporters from ABC and SLC families play a main role in this phenomenon. This study demonstrates alterations in ABC and SLC gene expression levels in methotrexate, cisplatin, doxorubicin, vincristine, topotecan and paclitaxel-resistant variant of W1 ovarian cancer cell line. Resistant W1 cell lines were derived by stepwise selection of cells in increasing concentration of drugs. Affymetrix GeneChip(®) Human Genome U219 Array Strip was used for hybridizations. Statistical significance was determined by independent sample t-test. The genes having altered expression levels in drug-resistant sublines were selected and filtered by scater plot. Genes up/downregulated more than threefolds were selected and listed. Among ABC genes, seven were upregulated and three were downregulated. Three genes: ABCB1, ABCB4 and ABCG2 were upregulated very significantly (over tenfold). One ABCA8 was significantly downregulated. Among 38 SLC genes, 18 were upregulated, 16 were downregulated and four were up- or downregulated dependent on the cell line. Expression of 10 SLC genes was changed very significantly (over tenfold). Four genes were significantly increased: SLC6A1, SLC9A2, SLC12A1, SLC16A6 and six genes were significantly decreased: SLC2A14, SLC7A3, SLC7A8, SLC7A11, SLC16A14, SLC38A9. Based on the expression profiles, our results provide a preliminary insight into the relationship between drug resistance and expression of membrane transporters involved in drug resistance. Correlation of specific drug transporter with drug resistance requires further analysis. PMID:23462296

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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

  19. 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, ...

  20. The LO-BaFL method and ALS microarray expression analysis

    PubMed Central

    2012-01-01

    Background Sporadic Amyotrophic Lateral Sclerosis (sALS) is a devastating, complex disease of unknown etiology. We studied this disease with microarray technology to capture as much biological complexity as possible. The Affymetrix-focused BaFL pipeline takes into account problems with probes that arise from physical and biological properties, so we adapted it to handle the long-oligonucleotide probes on our arrays (hence LO-BaFL). The revised method was tested against a validated array experiment and then used in a meta-analysis of peripheral white blood cells from healthy control samples in two experiments. We predicted differentially expressed (DE) genes in our sALS data, combining the results obtained using the TM4 suite of tools with those from the LO-BaFL method. Those predictions were tested using qRT-PCR assays. Results LO-BaFL filtering and DE testing accurately predicted previously validated DE genes in a published experiment on coronary artery disease (CAD). Filtering healthy control data from the sALS and CAD studies with LO-BaFL resulted in highly correlated expression levels across many genes. After bioinformatics analysis, twelve genes from the sALS DE gene list were selected for independent testing using qRT-PCR assays. High-quality RNA from six healthy Control and six sALS samples yielded the predicted differential expression for 7 genes: TARDBP, SKIV2L2, C12orf35, DYNLT1, ACTG1, B2M, and ILKAP. Four of the seven have been previously described in sALS studies, while ACTG1, B2M and ILKAP appear in the context of this disease for the first time. Supplementary material can be accessed at: http://webpages.uncc.edu/~cbaciu/LO-BaFL/supplementary_data.html. Conclusion LO-BaFL predicts DE results that are broadly similar to those of other methods. The small healthy control cohort in the sALS study is a reasonable foundation for predicting DE genes. Modifying the BaFL pipeline allowed us to remove noise and systematic errors, improving the power of this

  1. A Grid-based solution for management and analysis of microarrays in distributed experiments

    PubMed Central

    Porro, Ivan; Torterolo, Livia; Corradi, Luca; Fato, Marco; Papadimitropoulos, Adam; Scaglione, Silvia; Schenone, Andrea; Viti, Federica

    2007-01-01

    Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip® Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of

  2. 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

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

    SciTech Connect

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

    2009-03-01

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

  4. 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

  5. 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

  6. [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

  7. 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.

  8. Neuroprotective changes of striatal degeneration-related gene expression by acupuncture in an MPTP mouse model of Parkinsonism: microarray analysis.

    PubMed

    Choi, Yeong-Gon; Yeo, Sujung; Hong, Yeon-Mi; Lim, Sabina

    2011-04-01

    Acupuncture at acupoints GB34 and LR3 has been reported to inhibit nigrostriatal degeneration in Parkinsonism models, yet the genes related to this preventive effect of acupuncture on the nigrostriatal dopaminergic system remain elusive. This study investigated gene expression profile changes in the striatal region of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinsonism models after acupuncture at the acupoints GB34 and LR3 using a whole transcript genechip microarray (Affymetrix genechip mouse gene 1.0 ST array). It was confirmed that acupuncture at these acupoints could inhibit the decrease of tyrosine hydroxylase and dopamine transporter in the nigrostriatal region of the MPTP model while acupuncture at the non-acupoints could not counteract this decrease. Genechip gene array analysis (fold change cutoff 1.3 and P < 0.05) showed that 12 of the 69 probes up-regulated in MPTP when compared to the control were down-regulated by acupuncture at the acupoints. Of these 12 probes, 11 probes (nine annotated genes) were exclusively down-regulated by acupuncture only at the acupoints; the Gfral gene was excluded because it was commonly down-regulated by acupuncture at both the acupoints and the non-acupoints. In addition, 28 of the 189 probes down-regulated in MPTP when compared to the control were up-regulated by acupuncture at the acupoints. Of these 28 probes, 19 probes (seven annotated genes) were exclusively up-regulated by acupuncture only at the acupoints while nine probes were commonly up-regulated by acupuncture at both the acupoints and the non-acupoints. The regulation patterns of representative genes in real-time RT-PCR correlated with those of the genes in the microarray. These results suggest that the 30 probes (16 annotated genes), which are affected by MPTP and acupuncture only at the acupoints, are responsible for exerting in the striatal regions the inhibitory effect of acupuncture at the acupoints on MPTP-induced striatal

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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 ...

  18. 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

  19. 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

  20. A microarray analysis of retinal transcripts that are controlled by image contrast in mice

    PubMed Central

    Brand, Christine; Schaeffel, Frank

    2007-01-01

    Purpose The development of myopia is controlled by still largely unknown retinal signals. The aim of this study was to investigate the changes in retinal mRNA expression after different periods of visual deprivation in mice, while controlling for retinal illuminance. Methods Each group consisted of three male C57BL/6 mice. Treatment periods were 30 min, 4 h, and 6+6 h. High spatial frequencies were filtered from the retinal image by frosted diffusers over one eye while the fellow eyes were covered by clear neutral density (ND) filters that exhibited similar light attenuating properties (0.1 log units) as the diffusers. For the final 30 min of the respective treatment period mice were individually placed in a clear Perspex cylinder that was positioned in the center of a rotating (60 degrees) large drum. The inside of the drum was covered with a 0.1 cyc/degree vertical square wave grating. This visual environment was chosen to standardize illuminances and contrasts seen by the mice. Labeled cRNA was prepared and hybridized to Affymetrix GeneChip® Mouse Genome 430 2.0 arrays. Alterations in mRNA expression levels of candidate genes with potential biological relevance were confirmed by semi-quantitative real-time reverse transcription polymerase chain reaction (RT-PCR). Results In all groups, Egr-1 mRNA expression was reduced in diffuser-treated eyes. Furthermore, the degradation of the spatial frequency spectrum also changed the cFos mRNA level, with reduced expression after 4 h of diffuser treatment. Other interesting candidates were Akt2, which was up-regulated after 30 min of deprivation and Mapk8ip3, a neuron specific JNK binding and scaffolding protein that was temporally regulated in the diffuser-treated eyes only. Conclusions The microarray analysis demonstrated a pattern of differential transcriptional changes, even though differences in the retinal images were restricted to spatial features. The candidate genes may provide further insight into the

  1. The Microarray Revolution: Perspectives from Educators

    ERIC Educational Resources Information Center

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

    2004-01-01

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

  2. 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

  3. 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

  4. 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

  5. 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.

  6. Microarray analysis in pulmonary hypertension

    PubMed Central

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea

    2016-01-01

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

  7. 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.

  8. Microarray analysis in pulmonary hypertension.

    PubMed

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

    2016-07-01

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

  9. 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.

  10. 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

  11. 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

  12. 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

  13. Microarray Analysis of the Abscission-Related Transcriptome in the Tomato Flower Abscission Zone in Response to Auxin Depletion1[C][W][OA

    PubMed Central

    Meir, Shimon; Philosoph-Hadas, Sonia; Sundaresan, Srivignesh; Selvaraj, K.S. Vijay; Burd, Shaul; Ophir, Ron; Kochanek, Bettina; Reid, Michael S.; Jiang, Cai-Zhong; Lers, Amnon

    2010-01-01

    The abscission process is initiated by changes in the auxin gradient across the abscission zone (AZ) and is triggered by ethylene. Although changes in gene expression have been correlated with the ethylene-mediated execution of abscission, there is almost no information on the molecular and biochemical basis of the increased AZ sensitivity to ethylene. We examined transcriptome changes in the tomato (Solanum lycopersicum ‘Shiran 1335’) flower AZ during the rapid acquisition of ethylene sensitivity following flower removal, which depletes the AZ from auxin, with or without preexposure to 1-methylcyclopropene or application of indole-3-acetic acid after flower removal. Microarray analysis using the Affymetrix Tomato GeneChip revealed changes in expression, occurring prior to and during pedicel abscission, of many genes with possible regulatory functions. They included a range of auxin- and ethylene-related transcription factors, other transcription factors and regulatory genes that are transiently induced early, 2 h after flower removal, and a set of novel AZ-specific genes. All gene expressions initiated by flower removal and leading to pedicel abscission were inhibited by indole-3-acetic acid application, while 1-methylcyclopropene pretreatment inhibited only the ethylene-induced expressions, including those induced by wound-associated ethylene signals. These results confirm our hypothesis that acquisition of ethylene sensitivity in the AZ is associated with altered expression of auxin-regulated genes resulting from auxin depletion. Our results shed light on the regulatory control of abscission at the molecular level and further expand our knowledge of auxin-ethylene cross talk during the initial controlling stages of the process. PMID:20947671

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

    PubMed Central

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

    2014-01-01

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

  15. 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

  16. 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

  17. 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.

  18. 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

  19. [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

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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.

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

    EPA Science Inventory

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

  8. Clustering Short Time-Series Microarray

    NASA Astrophysics Data System (ADS)

    Ping, Loh Wei; Hasan, Yahya Abu

    2008-01-01

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

  9. 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

  10. 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

  11. 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...

  12. 2008 Microarray Research Group (MARG Survey): Sensing the State of Microarray Technology

    EPA Science Inventory

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

  13. [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

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

    PubMed

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

    2005-01-01

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

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

    PubMed Central

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

    2005-01-01

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

  16. Gene and noncoding RNA regulation underlying photoreceptor protection: microarray study of dietary antioxidant saffron and photobiomodulation in rat retina

    PubMed Central

    Zhu, Yuan; Valter, Krisztina; Bisti, Silvia; Eells, Janis; Stone, Jonathan

    2010-01-01

    Purpose To identify the genes and noncoding RNAs (ncRNAs) involved in the neuroprotective actions of a dietary antioxidant (saffron) and of photobiomodulation (PBM). Methods We used a previously published assay of photoreceptor damage, in which albino Sprague Dawley rats raised in dim cyclic illumination (12 h 5 lux, 12 h darkness) were challenged by 24 h exposure to bright (1,000 lux) light. Experimental groups were protected against light damage by pretreatment with dietary saffron (1 mg/kg/day for 21 days) or PBM (9 J/cm2 at the eye, daily for 5 days). RNA from one eye of four animals in each of the six experimental groups (control, light damage [LD], saffron, PBM, saffronLD, and PBMLD) was hybridized to Affymetrix rat genome ST arrays. Quantitative real-time PCR analysis of 14 selected genes was used to validate the microarray results. Results LD caused the regulation of 175 entities (genes and ncRNAs) beyond criterion levels (p<0.05 in comparison with controls, fold-change >2). PBM pretreatment reduced the expression of 126 of these 175 LD-regulated entities below criterion; saffron pretreatment reduced the expression of 53 entities (50 in common with PBM). In addition, PBM pretreatment regulated the expression of 67 entities not regulated by LD, while saffron pretreatment regulated 122 entities not regulated by LD (48 in common with PBM). PBM and saffron, given without LD, regulated genes and ncRNAs beyond criterion levels, but in lesser numbers than during their protective action. A high proportion of the entities regulated by LD (>90%) were known genes. By contrast, ncRNAs were prominent among the entities regulated by PBM and saffron in their neuroprotective roles (73% and 62%, respectively). Conclusions Given alone, saffron and (more prominently) PBM both regulated significant numbers of genes and ncRNAs. Given before retinal exposure to damaging light, thus while exerting their neuroprotective action, they regulated much larger numbers of entities

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

    ERIC Educational Resources Information Center

    Barnard, Betsy

    2006-01-01

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

  18. 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...

  19. 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

  20. 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

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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.

  6. Functional assessment of time course microarray data

    PubMed Central

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

    2009-01-01

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

  7. 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

  8. A Single-Array-Based Method for Detecting Copy Number Variants Using Affymetrix High Density SNP Arrays and its Application to Breast Cancer

    PubMed Central

    Li, Ming; Wen, Yalu; Fu, Wenjiang

    2014-01-01

    Cumulative evidence has shown that structural variations, due to insertions, deletions, and inversions of DNA, may contribute considerably to the development of complex human diseases, such as breast cancer. High-throughput genotyping technologies, such as Affymetrix high density single-nucleotide polymorphism (SNP) arrays, have produced large amounts of genetic data for genome-wide SNP genotype calling and copy number estimation. Meanwhile, there is a great need for accurate and efficient statistical methods to detect copy number variants. In this article, we introduce a hidden-Markov-model (HMM)-based method, referred to as the PICR-CNV, for copy number inference. The proposed method first estimates copy number abundance for each single SNP on a single array based on the raw fluorescence values, and then standardizes the estimated copy number abundance to achieve equal footing among multiple arrays. This method requires no between-array normalization, and thus, maintains data integrity and independence of samples among individual subjects. In addition to our efforts to apply new statistical technology to raw fluorescence values, the HMM has been applied to the standardized copy number abundance in order to reduce experimental noise. Through simulations, we show our refined method is able to infer copy number variants accurately. Application of the proposed method to a breast cancer dataset helps to identify genomic regions significantly associated with the disease. PMID:26279618

  9. 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

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

    PubMed

    Morais, Sergi; Puchades, Rosa; Maquieira, Ángel

    2016-07-01

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

  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. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. Gene Expression Profiling of Microdissected Pancreatic Ductal Carcinomas Using High-Density DNA Microarrays1,3

    PubMed Central

    Grützmann, Robert; Pilarsky, Christian; Ammerpohl, Ole; Lüttges, Jutta; Böhme, Armin; Sipos, Bence; Foerder, Melanie; Alldinger, Ingo; Jahnke, Beatrix; Schackert, Hans Konrad; Kalthoff, Holger; Kremer, Bernd; Klöppel, Günter; Saeger, Hans Detlev

    2004-01-01

    Abstract Pancreatic ductal adenocarcinoma (PDAC) remains an important cause of malignancy-related death and is the eighth most common cancer with the lowest overall 5-year relative survival rate. To identify new molecular markers and candidates for new therapeutic regimens, we investigated the gene expression profile of microdissected cells from 11 normal pancreatic ducts, 14 samples of PDAC, and 4 well-characterized pancreatic cancer cell lines using the Affymetrix U133 GeneChip set. RNA was extracted from microdissected samples and cell lines, amplified, and labeled using a repetitive in vitro transcription protocol. Differentially expressed genes were identified using the significance analysis of microarrays program. We found 616 differentially expressed genes. Within these, 140 were also identified in PDAC by others, such as Galectin-1, Galectin-3, and MT-SP2. We validated the differential expression of several genes (e.g., CENPF, MCM2, MCM7, RAMP, IRAK1, and PTTG1) in PDAC by immunohistochemistry and reverse transcription polymerase chain reaction. We present a whole genome expression study of microdissected tissues from PDAC, from microdissected normal ductal pancreatic cells and pancreatic cancer cell lines using highdensity microarrays. Within the panel of genes, we identified novel differentially expressed genes, which have not been associated with the pathogenesis of PDAC before. PMID:15548371

  19. Identification of candidate genes for congenital splay leg in piglets by alternative analysis of DNA microarray data

    PubMed Central

    Maak, Steffen; Boettcher, Diana; Tetens, Jens; Wensch-Dorendorf, Monika; Nürnberg, Gerd; Wimmers, Klaus; Swalve, Hermann H.; Thaller, Georg

    2009-01-01

    The congenital splay leg syndrome in piglets is characterized by a temporarily impaired functionality of the hind leg muscles immediately after birth. Etiology and pathogenetic mechanisms for the disease are still not well understood. We compared genome wide gene expression of three hind leg muscles (M. adductores, M. gracilis and M. sartorius) between affected piglets and their healthy littermates with the GeneChip® Porcine Genome Array (Affymetrix) in order to identify candidate genes for the disease. Data analysis with standard algorithms revealed no significant differences between both groups. By application of an alternative approach, we identified 63 transcripts with differences in two muscles and 5 genes differing between the groups in three muscles. The expression of six selected genes (SQSTM1, SSRP1, DDIT4, ENAH, MAF, and PDK4) was investigated with SYBRGreen RT - Real time PCR. The differences obtained with the microarray analysis could be confirmed and demonstrate the validity of the alternative approach to microarray data analysis. Four genes with different expression levels in at least two muscles (SQSTM1, SSRP1, DDIT4, and MAF) are assigned to transcriptional cascades related to cell death and may thus indicate pathways for further investigations on congenital splay leg in piglets. PMID:19421343

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

    PubMed

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

    2004-07-15

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

  1. DNA Microarrays in Herbal Drug Research

    PubMed Central

    Chavan, Preeti; Joshi, Kalpana; Patwardhan, Bhushan

    2006-01-01

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

  2. 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. 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

  4. Analyzing multiple-probe microarray: estimation and application of gene expression indexes

    PubMed Central

    Maadooliat, Mehdi; Huang, Jianhua Z.; Hu, Jianhua

    2014-01-01

    Summary Gene expression index estimation is an essential step in analyzing multiple probe microarray data. Various modeling methods have been proposed in this area. Amidst all, a popular method proposed in Li and Wong (2001) is based on a multiplicative model, which is similar to the additive model discussed in Irizarry et al. (2003a) at the logarithm scale. Along this line, Hu et al. (2006) proposed data transformation to improve expression index estimation based on an ad hoc entropy criteria and naive grid search approach. In this work, we re-examined this problem using a new profile likelihood-based transformation estimation approach that is more statistically elegant and computationally efficient. We demonstrate the applicability of the proposed method using a benchmark Affymetrix U95A spiked-in experiment. Moreover, We introduced a new multivariate expression index and used the empirical study to shows its promise in terms of improving model fitting and power of detecting differential expression over the commonly used univariate expression index. As the other important content of the work, we discussed two generally encountered practical issues in application of gene expression index: normalization and summary statistic used for detecting differential expression. Our empirical study shows somewhat different findings from the MAQC project (MAQC, 2006). PMID:22834966

  5. 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

  6. 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

  7. 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

  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. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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.

  18. 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

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

    PubMed Central

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

    2011-01-01

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

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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

  1. Hybridization and Selective Release of DNA Microarrays

    SciTech Connect

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

    2011-11-29

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

  2. Analysis of High-Throughput ELISA Microarray Data

    SciTech Connect

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

    2011-02-23

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

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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.

  19. Results.

    ERIC Educational Resources Information Center

    Zemsky, Robert; Shaman, Susan; Shapiro, Daniel B.

    2001-01-01

    Describes the Collegiate Results Instrument (CRI), which measures a range of collegiate outcomes for alumni 6 years after graduation. The CRI was designed to target alumni from institutions across market segments and assess their values, abilities, work skills, occupations, and pursuit of lifelong learning. (EV)

  20. 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

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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...

  10. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

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

  11. 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…

  12. 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...

  13. 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

  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. RNA Microarray Analysis of Macroscopically Normal Articular Cartilage from Knees Undergoing Partial Medial Meniscectomy: Potential Prediction of the Risk for Developing Osteoarthritis

    PubMed Central

    Sandell, Linda J.; Zhang, Bo; Wright, Rick W.; Brophy, Robert H.

    2016-01-01

    Objectives (i) To provide baseline knowledge of gene expression in macroscopically normal articular cartilage, (ii) to test the hypothesis that age, body-mass-index (BMI), and sex are associated with cartilage RNA transcriptome, and (iii) to predict individuals at potential risk for developing “pre-osteoarthritis” (OA) based on screening of genetic risk-alleles associated with OA and gene transcripts differentially expressed between normal and OA cartilage. Design Healthy-appearing cartilage was obtained from the medial femoral notch of 12 knees with a meniscus tear undergoing arthroscopic partial meniscectomy. Cartilage had no radiographic, magnetic-resonance-imaging or arthroscopic evidence for degeneration. RNA was subjected to Affymetrix microarrays followed by validation of selected transcripts by microfluidic digital polymerase-chain-reaction. The underlying biological processes were explored computationally. Transcriptome-wide gene expression was probed for association with known OA genetic risk-alleles assembled from published literature and for comparison with gene transcripts differentially expressed between healthy and OA cartilage from other studies. Results We generated a list of 27,641 gene transcripts in healthy cartilage. Several gene transcripts representing numerous biological processes were correlated with age and BMI and differentially expressed by sex. Based on disease-specific Ingenuity Pathways Analysis, gene transcripts associated with aging were enriched for bone/cartilage disease while the gene expression profile associated with BMI was enriched for growth-plate calcification and OA. When segregated by genetic risk-alleles, two clusters of study patients emerged, one cluster containing transcripts predicted by risk studies. When segregated by OA-associated gene transcripts, three clusters of study patients emerged, one of which is remarkably similar to gene expression pattern in OA. Conclusions Our study provides a list of gene

  16. Microarray analysis at single molecule resolution

    PubMed Central

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

    2010-01-01

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

  17. 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

  18. 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

  19. Changing interpretation of chromosomal microarray over time in a community cohort with intellectual disability.

    PubMed

    Palmer, Emma; Speirs, Helen; Taylor, Peter J; Mullan, Glenda; Turner, Gill; Einfeld, Stewart; Tonge, Bruce; Mowat, David

    2014-02-01

    Chromosomal microarray (CMA) is the first-line diagnostic test for individuals with intellectual disability, autism, or multiple congenital anomalies, with a 10-20% diagnostic yield. An ongoing challenge for the clinician and laboratory scientist is the interpretation of variants of uncertain significance (VOUS)-usually rare, unreported genetic variants. Laboratories differ in their threshold for reporting VOUS, and clinical practice varies in how this information is conveyed to the family and what follow-up is arranged. Workflows, websites, and databases are constantly being updated to aid the interpretation of VOUS. There is a growing literature reporting new microdeletion and duplication syndromes, susceptibility, and modifier copy number variants (CNVs). Diagnostic methods are also evolving with new array platforms and genome builds. In 2010, high-resolution arrays (Affymetrix 2.7 M Oligo and SNP, 50 kB resolution) were performed on a community cohort of 67 individuals with intellectual disability of unknown aetiology. Three hundred and one CNVs were detected and analyzed using contemporary resources and a simple scoring system. Thirteen (19%) of the arrays were assessed as potentially pathogenic, 4 (6%) as benign and 50 (75%) of uncertain clinical significance. The CNV data were re-analyzed in 2012 using the contemporary interpretative resources. There was a statistically significant difference in the assessment of individual CNVs (P < 0.0001). An additional eight patients were reassessed as having a potentially pathogenic array (n = 21, 31%) and several additional susceptibility or modifier CNVs were identified. This study highlights the complexity involved in the interpretation of CMA and uniquely demonstrates how, even on the same array platform, it can be subject to change over time. PMID:24311194

  20. Gene network and canonical pathway analysis in canine myxomatous mitral valve disease: a microarray study.

    PubMed

    Lu, C-C; Liu, M-M; Culshaw, G; Clinton, M; Argyle, D J; Corcoran, B M

    2015-04-01

    Myxomatous mitral valve disease (MMVD) is the single most common acquired heart disease of the dog and is particularly common in small pedigree breed dogs such as the Cavalier King Charles spaniel (CKCS). There are limited data on the mitral valve transcriptome and the aim of this study was to use the microarray technology in conjunction with bioinformatics platforms to analyse transcript changes in MMVD in CKCS compared to normal dogs (non-CKCS). Differentially expressed genes (n = 5397) were identified using cut-off settings of fold change, false discovery rate (FDR) and P <0.05. In total, 4002 genes were annotated to a specific transcript in the Affymetrix canine database, and after further filtering, 591 annotated canine genes were identified: 322 (55%) were up-regulated and 269 (45%) were down-regulated. Canine microRNAs (cfa-miR; n = 59) were also identified. Gene ontology and network analysis platforms identified between six and 10 significantly different biological function clusters from which the following were selected as relevant to MMVD: inflammation, cell movement, cardiovascular development, extracellular matrix organisation and epithelial-to-mesenchymal (EMT) transition. Ingenuity Pathway Analysis identified three canonical pathways relevant to MMVD: caveolar-mediated endocytosis, remodelling of epithelial adherens junctions, and endothelin-1 signalling. Considering the biological relevance to MMVD, the gene families of importance with significant difference between groups included collagens, ADAMTS peptidases, proteoglycans, matrix metalloproteinases (MMPs) and their inhibitors, basement membrane components, cathepsin S, integrins, tight junction cell adhesion proteins, cadherins, other matrix-associated proteins, and members of the serotonin (5-HT)/transforming growth factor -β signalling pathway. PMID:25841900

  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. 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

  4. 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

  5. Construction and evaluation of a whole genome microarray of Chlamydomonas reinhardtii

    PubMed Central

    2011-01-01

    Background Chlamydomonas reinhardtii is widely accepted as a model organism regarding photosynthesis, circadian rhythm, cell mobility, phototaxis, and biotechnology. The complete annotation of the genome allows transcriptomic studies, however a new microarray platform was needed. Based on the completed annotation of Chlamydomonas reinhardtii a new microarray on an Agilent platform was designed using an extended JGI 3.1 genome data set which included 15000 transcript models. Results In total 44000 probes were determined (3 independent probes per transcript model) covering 93% of the transcriptome. Alignment studies with the recently published AUGUSTUS 10.2 annotation confirmed 11000 transcript models resulting in a very good coverage of 70% of the transcriptome (17000). Following the estimation of 10000 predicted genes in Chlamydomonas reinhardtii our new microarray, nevertheless, covers the expected genome by 90-95%. Conclusions To demonstrate the capabilities of the new microarray, we analyzed transcript levels for cultures grown under nitrogen as well as sulfate limitation, and compared the results with recently published microarray and RNA-seq data. We could thereby confirm previous results derived from data on nutrient-starvation induced gene expression of a group of genes related to protein transport and adaptation of the metabolism as well as genes related to efficient light harvesting, light energy distribution and photosynthetic electron transport. PMID:22118351

  6. Pigeons: A Novel GUI Software for Analysing and Parsing High Density Heterologous Oligonucleotide Microarray Probe Level Data

    PubMed Central

    Lai, Hung-Ming; May, Sean T.; Mayes, Sean

    2014-01-01

    Genomic DNA-based probe selection by using high density oligonucleotide arrays has recently been applied to heterologous species (Xspecies). With the advent of this new approach, researchers are able to study the genome and transcriptome of a non-model or an underutilised crop species through current state-of-the-art microarray platforms. However, a software package with a graphical user interface (GUI) to analyse and parse the oligonucleotide probe pair level data is still lacking when an experiment is designed on the basis of this cross species approach. A novel computer program called Pigeons has been developed for customised array data analysis to allow the user to import and analyse Affymetrix GeneChip® probe level data through XSpecies. One can determine empirical boundaries for removing poor probes based on genomic hybridisation of the test species to the Xspecies array, followed by making a species-specific Chip Description File (CDF) file for transcriptomics in the heterologous species, or Pigeons can be used to examine an experimental design to identify potential Single-Feature Polymorphisms (SFPs) at the DNA or RNA level. Pigeons is also focused around visualization and interactive analysis of the datasets. The software with its manual (the current release number version 1.2.1) is freely available at the website of the Nottingham Arabidopsis Stock Centre (NASC).

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

    PubMed Central

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

    2016-01-01

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

  8. 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

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

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

    PubMed Central

    Behzadi, Payam; Najafi, Ali; Behzadi, Elham

    2016-01-01

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

  18. 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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  1. Global Analysis of Human Nonreceptor Tyrosine Kinase Specificity Using High-Density Peptide Microarrays

    PubMed Central

    2015-01-01

    Protein kinases phosphorylate substrates in the context of specific phosphorylation site sequence motifs. The knowledge of the specific sequences that are recognized by kinases is useful for mapping sites of phosphorylation in protein substrates and facilitates the generation of model substrates to monitor kinase activity. Here, we have adapted a positional scanning peptide library method to a microarray format that is suitable for the rapid determination of phosphorylation site motifs for tyrosine kinases. Peptide mixtures were immobilized on glass slides through a layer of a tyrosine-free Y33F mutant avidin to facilitate the analysis of phosphorylation by radiolabel assay. A microarray analysis provided qualitatively similar results in comparison with the solution phase peptide library “macroarray” method. However, much smaller quantities of kinases were required to phosphorylate peptides on the microarrays, which thus enabled a proteome scale analysis of kinase specificity. We illustrated this capability by microarray profiling more than 80% of the human nonreceptor tyrosine kinases (NRTKs). Microarray results were used to generate a universal NRTK substrate set of 11 consensus peptides for in vitro kinase assays. Several substrates were highly specific for their cognate kinases, which should facilitate their incorporation into kinase-selective biosensors. PMID:25164267

  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. 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

  4. Label-Free and High-Throughput Detection of Protein Microarrays by Oblique-Incidence Reflectivity Difference Method

    NASA Astrophysics Data System (ADS)

    Wang, Xu; Lu, Heng; Wen, Juan; Yuan, Kun; LÜ, Hui-Bin; Jin, Kui-Juan; Zhou, Yue-Liang; Yang, Guo-Zhen

    2010-10-01

    We label-free detected the biological process of preparing a microarray that includes 400 spots of mouse immunoglobulin G (IgG) as well as the specific hybridization between mouse IgG and goat anti-mouse IgG by an oblique-incidence reflectivity difference (OI-RD) method. The detection results after each process including printing, washing, blocking, and hybridization, demonstrate that the OI-RD method can trace the preparation process of a microarray and detect the specific hybridization between antigens and antibodies. OI-RD is a promising method for label-free and high-throughput detection of biological microarrays.

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

    PubMed Central

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

    2015-01-01

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

  6. The PowerAtlas: a power and sample size atlas for microarray experimental design and research

    PubMed Central

    Page, Grier P; Edwards, Jode W; Gadbury, Gary L; Yelisetti, Prashanth; Wang, Jelai; Trivedi, Prinal; Allison, David B

    2006-01-01

    Background Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies. Results To address this challenge, we have developed a Microrarray PowerAtlas [1]. The atlas enables estimation of statistical power by allowing investigators to appropriately plan studies by building upon previous studies that have similar experimental characteristics. Currently, there are sample sizes and power estimates based on 632 experiments from Gene Expression Omnibus (GEO). The PowerAtlas also permits investigators to upload their own pilot data and derive power and sample size estimates from these data. This resource will be updated regularly with new datasets from GEO and other databases such as The Nottingham Arabidopsis Stock Center (NASC). Conclusion This resource provides a valuable tool for investigators who are planning efficient microarray studies and estimating required sample sizes. PMID:16504070

  7. Detection of NASBA amplified bacterial tmRNA molecules on SLICSel designed microarray probes

    PubMed Central

    2011-01-01

    Background We present a comprehensive technological solution for bacterial diagnostics using tmRNA as a marker molecule. A robust probe design algorithm for microbial detection microarray is implemented. The probes were evaluated for specificity and, combined with NASBA (Nucleic Acid Sequence Based Amplification) amplification, for sensitivity. Results We developed a new web-based program SLICSel for the design of hybridization probes, based on nearest-neighbor thermodynamic modeling. A SLICSel minimum binding energy difference criterion of 4 kcal/mol was sufficient to design of Streptococcus pneumoniae tmRNA specific microarray probes. With lower binding energy difference criteria, additional hybridization specificity tests on the microarray were needed to eliminate non-specific probes. Using SLICSel designed microarray probes and NASBA we were able to detect S. pneumoniae tmRNA from a series of total RNA dilutions equivalent to the RNA content of 0.1-10 CFU. Conclusions The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics. PMID:21356118

  8. Fish and chips: Various methodologies demonstrate utility of a 16,006-gene salmonid microarray

    PubMed Central

    von Schalburg, Kristian R; Rise, Matthew L; Cooper, Glenn A; Brown, Gordon D; Gibbs, A Ross; Nelson, Colleen C; Davidson, William S; Koop, Ben F

    2005-01-01

    Background We have developed and fabricated a salmonid microarray containing cDNAs representing 16,006 genes. The genes spotted on the array have been stringently selected from Atlantic salmon and rainbow trout expressed sequence tag (EST) databases. The EST databases presently contain over 300,000 sequences from over 175 salmonid cDNA libraries derived from a wide variety of tissues and different developmental stages. In order to evaluate the utility of the microarray, a number of hybridization techniques and screening methods have been developed and tested. Results We have analyzed and evaluated the utility of a microarray containing 16,006 (16K) salmonid cDNAs in a variety of potential experimental settings. We quantified the amount of transcriptome binding that occurred in cross-species, organ complexity and intraspecific variation hybridization studies. We also developed a methodology to rapidly identify and confirm the contents of a bacterial artificial chromosome (BAC) library containing Atlantic salmon genomic DNA. Conclusion We validate and demonstrate the usefulness of the 16K microarray over a wide range of teleosts, even for transcriptome targets from species distantly related to salmonids. We show the potential of the use of the microarray in a variety of experimental settings through hybridization studies that examine the binding of targets derived from different organs and tissues. Intraspecific variation in transcriptome expression is evaluated and discussed. Finally, BAC hybridizations are demonstrated as a rapid and accurate means to identify gene content. PMID:16164747

  9. Construction and Evaluation of a Clostridium thermocellum ATCC 27405 Whole-Genome Oligonucleotide Microarray

    NASA Astrophysics Data System (ADS)

    Brown, Steven D.; Raman, Babu; McKeown, Catherine K.; Kale, Shubha P.; He, Zhili; Mielenz, Jonathan R.

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

  10. Development of highly fluorescent silica nanoparticles chemically doped with organic dye for sensitive DNA microarray detection.

    PubMed

    Liu, Aihua; Wu, Liyou; He, Zhili; Zhou, Jizhong

    2011-10-01

    Increasing the sensitivity in DNA microarray hybridization can significantly enhance the capability of microarray technology for a wide range of research and clinical diagnostic applications, especially for those with limited sample biomass. To address this issue, using reverse microemulsion method and surface chemistry, a novel class of homogenous, photostable, highly fluorescent streptavidin-functionalized silica nanoparticles was developed, in which Alexa Fluor 647 (AF647) molecules were covalently embedded. The coating of bovine serum albumin on the resultant fluorescent particles can greatly eliminate nonspecific background signal interference. The thus-synthesized fluorescent nanoparticles can specifically recognize biotin-labeled target DNA hybridized to the microarray via streptavidin-biotin interaction. The response of this DNA microarray technology exhibited a linear range within 0.2 to 10 pM complementary DNA and limit of detection of 0.1 pM, enhancing microarray hybridization sensitivity over tenfold. This promising technology may be potentially applied to other binding events such as specific interactions between proteins. PMID:21822973

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  12. An efficient algorithm for the stochastic simulation of the hybridization of DNA to microarrays

    PubMed Central

    2009-01-01

    Background Although oligonucleotide microarray technology is ubiquitous in genomic research, reproducibility and standardization of expression measurements still concern many researchers. Cross-hybridization between microarray probes and non-target ssDNA has been implicated as a primary factor in sensitivity and selectivity loss. Since hybridization is a chemical process, it may be modeled at a population-level using a combination of material balance equations and thermodynamics. However, the hybridization reaction network may be exceptionally large for commercial arrays, which often possess at least one reporter per transcript. Quantification of the kinetics and equilibrium of exceptionally large chemical systems of this type is numerically infeasible with customary approaches. Results In this paper, we present a robust and computationally efficient algorithm for the simulation of hybridization processes underlying microarray assays. Our method may be utilized to identify the extent to which nucleic acid targets (e.g. cDNA) will cross-hybridize with probes, and by extension, characterize probe robustnessusing the information specified by MAGE-TAB. Using this algorithm, we characterize cross-hybridization in a modified commercial microarray assay. Conclusions By integrating stochastic simulation with thermodynamic prediction tools for DNA hybridization, one may robustly and rapidly characterize of the selectivity of a proposed microarray design at the probe and "system" levels. Our code is available at http://www.laurenzi.net. PMID:20003312

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

    SciTech Connect

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

    2007-04-01

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

  14. 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

  15. 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

  16. 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

  17. 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

  18. Microarray testing for the presence of toxic algae monitoring programme in Galicia (NW Spain).

    PubMed

    Dittami, Simon M; Pazos, Yolanda; Laspra, Melchor; Medlin, Linda K

    2013-10-01

    Rapid and reliable detection of harmful algae in coastal areas and shellfish farms is an important requirement of monitoring programmes. Monitoring of toxic algae by means of traditional methods, i.e., light microscopy, can be time consuming when many samples have to be routinely analysed. Reliable species identification requires expensive equipment and trained personnel to carry out the analyses. However, all techniques for the monitoring of harmful algae usually require transportation of samples to specialised laboratories. In many monitoring laboratories, results are usually obtained within five working days after receiving the sample and therefore preventative measures are not always possible. Molecular technologies are rapidly improving the detection of phytoplankton and their toxins and the speed at which the results can be obtained. Assays are based on the discrimination of the genetic differences of the different species and species-specific probes can be designed. Such probes have been adapted to a microarray or phylochip format and assessed in several EU monitoring sites. Microarray results are presented for 1 year of field samples validated with cell counts from concentrated samples taken during toxic events from the weekly sampling of the Galician Monitoring Programme done by INTECMAR. The Galician monitoring laboratory does their own counting and their results are posted on their web site within 24 h. There was good correlation between cells present and microarray signals. In the few cases of false negatives, these can be attributed to poor RNA extraction of the target species, viz. Prorocentrum or Dinophysis. Where potential false positives were encountered, the smaller volume taken for cell counts as compared to the upto 300 times more volume taken for RNA extraction for the microarray is likely the cause for these differences, making the microarray more sensitive. The microarray was able to provide better species resolution in Alexandrium and Pseudo

  19. A Review of Feature Selection and Feature Extraction Methods Applied on Microarray Data

    PubMed Central

    Hira, Zena M.; Gillies, Duncan F.

    2015-01-01

    We summarise various ways of performing dimensionality reduction on high-dimensional microarray data. Many different feature selection and feature extraction methods exist and they are being widely used. All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. A popular source of data is microarrays, a biological platform for gathering gene expressions. Analysing microarrays can be difficult due to the size of the data they provide. In addition the complicated relations among the different genes make analysis more difficult and removing excess features can improve the quality of the results. We present some of the most popular methods for selecting significant features and provide a comparison between them. Their advantages and disadvantages are outlined in order to provide a clearer idea of when to use each one of them for saving computational time and resources. PMID:26170834

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

    PubMed Central

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

    2014-01-01

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

  1. An inexpensive method of small paraffin tissue microarrays using mechanical pencil tips

    PubMed Central

    2011-01-01

    Background Tissue microarray technology has provided a high throughput means of evaluating potential biomarkers in archival pathological specimens. This study was carried out in order to produce tissue microarray blocks using mechanical pencil tips without high cost. Method Conventional mechanical pencil tips (Rotring Tikky II Mechanical Pencil 1.0 mm) were used to cut out 1 mm wax cylinders from the recipient block, creating from 36 to 72 holes. Three cores of tumor areas were punched out manually by using the mechanical pencil tips from donor paraffin embedded tissue blocks and transferred to the holes of the paraffin tissue microarrays. Results This technique was easy and caused little damage to the donor blocks. We successfully performed H&E slides and immunodetection without substantial tissue cylinder loss. Conclusion Our mechanical pencil tip technique is the most inexpensive easy technique among the literature. It also takes a reasonable amount of time and reduces antibody consumption during immunohistochemistry PMID:22132713

  2. Identifying protein interactions with metal-modified DNA using microarray technology.

    PubMed

    Stansfield, Hope E; Kulczewski, Bethany P; Lybrand, Kyle E; Jamieson, Elizabeth R

    2009-02-01

    Protein microarrays have been used extensively to identify protein-protein interactions; however, this technology has not been widely applied to protein-DNA interactions. In particular, this work demonstrates the utility of this technique for rapidly identifying interactions of proteins with metal-modified DNA. Protein macroarray experiments were carried out with high mobility group protein 1 (HMG-1) and cisplatin- and chromium-modified 50-mer oligonucleotides to demonstrate "proof of principle." Commercially available protein microarrays containing many different classes of human proteins were then employed to search for additional interactions with cisplatin-modified DNA. The results of the microarray experiments confirmed some known interactions and, more importantly, identified many novel protein interactions, demonstrating the utility of this method as a rapid, high-throughput technique to discover proteins that interact with metal-modified DNA. PMID:18936984

  3. 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

  4. 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.

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. Protein microarrays based on polymer brushes prepared via surface-initiated atom transfer radical polymerization.

    PubMed

    Barbey, Raphael; Kauffmann, Ekkehard; Ehrat, Markus; Klok, Harm-Anton

    2010-12-13

    Polymer brushes represent an interesting platform for the development of high-capacity protein binding surfaces. Whereas the protein binding properties of polymer brushes have been investigated before, this manuscript evaluates the feasibility of poly(glycidyl methacrylate) (PGMA) and PGMA-co-poly(2-(diethylamino)ethyl methacrylate) (PGMA-co-PDEAEMA) (co)polymer brushes grown via surface-initiated atom transfer radical polymerization (SI-ATRP) as protein reactive substrates in a commercially available microarray system using tantalum-pentoxide-coated optical waveguide-based chips. The performance of the polymer-brush-based protein microarray chips is assessed using commercially available dodecylphosphate (DDP)-modified chips as the benchmark. In contrast to the 2D planar, DDP-coated chips, the polymer-brush-covered chips represent a 3D sampling volume. This was reflected in the results of protein immobilization studies, which indicated that the polymer-brush-based coatings had a higher protein binding capacity as compared to the reference substrates. The protein binding capacity of the polymer-brush-based coatings was found to increase with increasing brush thickness and could also be enhanced by copolymerization of 2-(diethylamino)ethyl methacrylate (DEAEMA), which catalyzes epoxide ring-opening of the glycidyl methacrylate (GMA) units. The performance of the polymer-brush-based microarray chips was evaluated in two proof-of-concept microarray experiments, which involved the detection of biotin-streptavidin binding as well as a model TNFα reverse assay. These experiments revealed that the use of polymer-brush-modified microarray chips resulted not only in the highest absolute fluorescence readouts, reflecting the 3D nature and enhanced sampling volume provided by the brush coating, but also in significantly enhanced signal-to-noise ratios. These characteristics make the proposed polymer brushes an attractive alternative to commercially available, 2D microarray

  15. Introduction to the statistical analysis of two-color microarray data.

    PubMed

    Bremer, Martina; Himelblau, Edward; Madlung, Andreas

    2010-01-01

    Microarray experiments have become routine in the past few years in many fields of biology. Analysis of array hybridizations is often performed with the help of commercial software programs, which produce gene lists, graphs, and sometimes provide values for the statistical significance of the results. Exactly what is computed by many of the available programs is often not easy to reconstruct or may even be impossible to know for the end user. It is therefore not surprising that many biology students and some researchers using microarray data do not fully understand the nature of the underlying statistics used to arrive at the results.We have developed a module that we have used successfully in undergraduate biology and statistics education that allows students to get a better understanding of both the basic biological and statistical theory needed to comprehend primary microarray data. The module is intended for the undergraduate level but may be useful to anyone who is new to the field of microarray biology. Additional course material that was developed for classroom use can be found at http://www.polyploidy.org/ .In our undergraduate classrooms we encourage students to manipulate microarray data using Microsoft Excel to reinforce some of the concepts they learn. We have included instructions for some of these manipulations throughout this chapter (see the "Do this..." boxes). However, it should be noted that while Excel can effectively analyze our small sample data set, more specialized software would typically be used to analyze full microarray data sets. Nevertheless, we believe that manipulating a small data set with Excel can provide insights into the workings of more advanced analysis software. PMID:20652509

  16. 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.

  17. Evolution of the MIDTAL microarray: the adaption and testing of oligonucleotide 18S and 28S rDNA probes and evaluation of subsequent microarray generations with Prymnesium spp. cultures and field samples.

    PubMed

    McCoy, Gary R; Touzet, Nicolas; Fleming, Gerard T A; Raine, Robin

    2015-07-01

    The toxic microalgal species Prymnesium parvum and Prymnesium polylepis are responsible for numerous fish kills causing economic stress on the aquaculture industry and, through the consumption of contaminated shellfish, can potentially impact on human health. Monitoring of toxic phytoplankton is traditionally carried out by light microscopy. However, molecular methods of identification and quantification are becoming more common place. This study documents the optimisation of the novel Microarrays for the Detection of Toxic Algae (MIDTAL) microarray from its initial stages to the final commercial version now available from Microbia Environnement (France). Existing oligonucleotide probes used in whole-cell fluorescent in situ hybridisation (FISH) for Prymnesium species from higher group probes to species-level probes were adapted and tested on the first-generation microarray. The combination and interaction of numerous other probes specific for a whole range of phytoplankton taxa also spotted on the chip surface caused high cross reactivity, resulting in false-positive results on the microarray. The probe sequences were extended for the subsequent second-generation microarray, and further adaptations of the hybridisation protocol and incubation temperatures significantly reduced false-positive readings from the first to the second-generation chip, thereby increasing the specificity of the MIDTAL microarray. Additional refinement of the subsequent third-generation microarray protocols with the addition of a poly-T amino linker to the 5' end of each probe further enhanced the microarray performance but also highlighted the importance of optimising RNA labelling efficiency when testing with natural seawater samples from Killary Harbour, Ireland. PMID:25631743

  18. 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.

  19. 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

  20. 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

  1. Evaluation of a novel automated allergy microarray platform compared with three other allergy test methods.

    PubMed

    Williams, P; Önell, A; Baldracchini, F; Hui, V; Jolles, S; El-Shanawany, T

    2016-04-01

    Microarray platforms, enabling simultaneous measurement of many allergens with a small serum sample, are potentially powerful tools in allergy diagnostics. We report here the first study comparing a fully automated microarray system, the Microtest allergy system, with a manual microarray platform, Immuno-Solid phase Allergen Chip (ISAC), and two well-established singleplex allergy tests, skin prick test (SPT) and ImmunoCAP, all tested on the same patients. One hundred and three adult allergic patients attending the allergy clinic were included into the study. All patients were tested with four allergy test methods (SPT, ImmunoCAP, Microtest and ISAC 112) and a total of 3485 pairwise test results were analysed and compared. The four methods showed comparable results with a positive/negative agreement of 81-88% for any pair of test methods compared, which is in line with data in the literature. The most prevalent allergens (cat, dog, mite, timothy, birch and peanut) and their individual allergen components revealed an agreement between methods with correlation coefficients between 0·73 and 0·95. All four methods revealed deviating individual patient results for a minority of patients. These results indicate that microarray platforms are efficient and useful tools to characterize the specific immunoglobulin (Ig)E profile of allergic patients using a small volume of serum sample. The results produced by the Microtest system were in agreement with diagnostic tests in current use. Further data collection and evaluation are needed for other populations, geographical regions and allergens. PMID:26437695

  2. ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

    PubMed Central

    Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D

    2008-01-01

    Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers

  3. Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization

    PubMed Central

    2010-01-01

    Background In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points. Results Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control. Conclusion Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene

  4. Detection of protein microarrays by oblique-incidence reflectivity difference technique

    NASA Astrophysics Data System (ADS)

    Wen, Juan; Lu, Heng; Wang, Xu; Yuan, Kun; Lü, Huibin; Zhou, Yueliang; Yin, Kuijuan; Yang, Guozhen; Li, Wei; Ruan, Kangcheng

    2010-02-01

    Biological microarrays with different proteins and different protein concentrations are detected without external labeling by an oblique-incidence reflectivity difference (OIRD) technique. The initial experiment results reveal that the intensities of OIRD signals can distinguish the different proteins and concentrations of protein. The OIRD technique promises feasible applications to life sciences for label-free and high-throughput detection.

  5. Parents' Perceptions of the Usefulness of Chromosomal Microarray Analysis for Children with Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Reiff, Marian; Giarelli, Ellen; Bernhardt, Barbara A.; Easley, Ebony; Spinner, Nancy B.; Sankar, Pamela L.; Mulchandani, Surabhi

    2015-01-01

    Clinical guidelines recommend chromosomal microarray analysis (CMA) for all children with autism spectrum disorders (ASDs). We explored the test's perceived usefulness among parents of children with ASD who had undergone CMA, and received a result categorized as pathogenic, variant of uncertain significance, or negative. Fifty-seven parents…

  6. Informatics Enhanced SNP Microarray Analysis of 30 Miscarriage Samples Compared to Routine Cytogenetics

    PubMed Central

    Lathi, Ruth B.; Loring, Megan; Massie, Jamie A. M.; Demko, Zachary P.; Johnson, David; Sigurjonsson, Styrmir; Gemelos, George; Rabinowitz, Matthew

    2012-01-01

    Purpose The metaphase karyotype is often used as a diagnostic tool in the setting of early miscarriage; however this technique has several limitations. We evaluate a new technique for karyotyping that uses single nucleotide polymorphism microarrays (SNP). This technique was compared in a blinded, prospective fashion, to the traditional metaphase karyotype. Methods Patients undergoing dilation and curettage for first trimester miscarriage between February and August 2010 were enrolled. Samples of chorionic villi were equally divided and sent for microarray testing in parallel with routine cytogenetic testing. Results Thirty samples were analyzed, with only four discordant results. Discordant results occurred when the entire genome was duplicated or when a balanced rearrangement was present. Cytogenetic karyotyping took an average of 29 days while microarray-based karytoyping took an average of 12 days. Conclusions Molecular karyotyping of POC after missed abortion using SNP microarray analysis allows for the ability to detect maternal cell contamination and provides rapid results with good concordance to standard cytogenetic analysis. PMID:22403611

  7. Microarray analysis of E9.5 reduced folate carrier (RFC1; Slc19a1) knockout embryos reveals altered expression of genes in the cubilin-megalin multiligand endocytic receptor complex

    PubMed Central

    Gelineau-van Waes, Janee; Maddox, Joyce R; Smith, Lynette M; van Waes, Michael; Wilberding, Justin; Eudy, James D; Bauer, Linda K; Finnell, Richard H

    2008-01-01

    Background The reduced folate carrier (RFC1) is an integral membrane protein and facilitative anion exchanger that mediates delivery of 5-methyltetrahydrofolate into mammalian cells. Adequate maternal-fetal transport of folate is necessary for normal embryogenesis. Targeted inactivation of the murine RFC1 gene results in post-implantation embryolethality, but daily folic acid supplementation of pregnant dams prolongs survival of homozygous embryos until mid-gestation. At E10.5 RFC1-/- embryos are developmentally delayed relative to wildtype littermates, have multiple malformations, including neural tube defects, and die due to failure of chorioallantoic fusion. The mesoderm is sparse and disorganized, and there is a marked absence of erythrocytes in yolk sac blood islands. The identification of alterations in gene expression and signaling pathways involved in the observed dysmorphology following inactivation of RFC1-mediated folate transport are the focus of this investigation. Results Affymetrix microarray analysis of the relative gene expression profiles in whole E9.5 RFC1-/- vs. RFC1+/+ embryos identified 200 known genes that were differentially expressed. Major ontology groups included transcription factors (13.04%), and genes involved in transport functions (ion, lipid, carbohydrate) (11.37%). Genes that code for receptors, ligands and interacting proteins in the cubilin-megalin multiligand endocytic receptor complex accounted for 9.36% of the total, followed closely by several genes involved in hematopoiesis (8.03%). The most highly significant gene network identified by Ingenuity™ Pathway analysis included 12 genes in the cubilin-megalin multiligand endocytic receptor complex. Altered expression of these genes was validated by quantitative RT-PCR, and immunohistochemical analysis demonstrated that megalin protein expression disappeared from the visceral yolk sac of RFC1-/- embryos, while cubilin protein was widely misexpressed. Conclusion Inactivation of

  8. Gene expression profiling in mitochondrial disease: assessment of microarray accuracy by high-throughput Q-PCR.

    PubMed

    Beckman, Kenneth B; Lee, Kathleen Y; Golden, Tamara; Melov, Simon

    2004-09-01

    Mitochondrial diseases are a heterogeneous array of disorders with a complex etiology. Use of microarrays as a tool to investigate complex human disease is increasingly common, however, a principle drawback of microarrays is their limited dynamic range, due to the poor quantification of weak signals. Although it is generally understood that low-intensity microarray 'spots' may be unreliable, there exists little documentation of their accuracy. Quantitative PCR (Q-PCR) is frequently used to validate microarray data, yet few Q-PCR validation studies have focused on the accuracy of low-intensity microarray signals. Hence, we have used Q-PCR to systematically assess microarray accuracy as a function of signal strength in a mouse model of mitochondrial disease, the superoxide dismutase 2 (SOD2) nullizygous mouse. We have focused on a unique category of data--spots with only one weak signal in a two-dye comparative hybridization--and show that such 'high-low' signal intensities are common for differentially expressed genes. This category of differential expression may be more important in mitochondrial disease in which there are often mosaic expression patterns due to the idiosyncratic distribution of mutant mtDNA in heteroplasmic individuals. Using RNA from the SOD2 mouse, we found that when spotted cDNA microarray data are filtered for quality (low variance between many technical replicates) and spot intensity (above a negative control threshold in both channels), there is an excellent quantitative concordance with Q-PCR (R2 = 0.94). The accuracy of gene expression ratios from low-intensity spots (R2 = 0.27) and 'high-low' spots (R2 = 0.32) is considerably lower. Our results should serve as guidelines for microarray interpretation and the selection of genes for validation in mitochondrial disorders. PMID:16120406

  9. 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...

  10. 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…

  11. 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

  12. 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...

  13. Simultaneous Detection of Multiple Fish Pathogens Using a Naked-Eye Readable DNA Microarray

    PubMed Central

    Chang, Chin-I; Hung, Pei-Hsin; Wu, Chia-Che; Cheng, Ta Chih; Tsai, Jyh-Ming; Lin, King-Jung; Lin, Chung-Yen

    2012-01-01

    We coupled 16S rDNA PCR and DNA hybridization technology to construct a microarray for simultaneous detection and discrimination of eight fish pathogens (Aeromonas hydrophila, Edwardsiella tarda, Flavobacterium columnare, Lactococcus garvieae, Photobacterium damselae, Pseudomonas anguilliseptica, Streptococcus iniae and Vibrio anguillarum) commonly encountered in aquaculture. The array comprised short oligonucleotide probes (30 mer) complementary to the polymorphic regions of 16S rRNA genes for the target pathogens. Targets annealed to the microarray probes were reacted with streptavidin-conjugated alkaline phosphatase and nitro blue tetrazolium/5-bromo-4-chloro-3′-indolylphosphate, p-toluidine salt (NBT/BCIP), resulting in blue spots that are easily visualized by the naked eye. Testing was performed against a total of 168 bacterial strains, i.e., 26 representative collection strains, 81 isolates of target fish pathogens, and 61 ecologically or phylogenetically related strains. The results showed that each probe consistently identified its corresponding target strain with 100% specificity. The detection limit of the microarray was estimated to be in the range of 1 pg for genomic DNA and 103 CFU/mL for pure pathogen cultures. These high specificity and sensitivity results demonstrate the feasibility of using DNA microarrays in the diagnostic detection of fish pathogens. PMID:22736973

  14. Simultaneous detection of multiple fish pathogens using a naked-eye readable DNA microarray.

    PubMed

    Chang, Chin-I; Hung, Pei-Hsin; Wu, Chia-Che; Cheng, Ta Chih; Tsai, Jyh-Ming; Lin, King-Jung; Lin, Chung-Yen

    2012-01-01

    We coupled 16S rDNA PCR and DNA hybridization technology to construct a microarray for simultaneous detection and discrimination of eight fish pathogens (Aeromonas hydrophila, Edwardsiella tarda, Flavobacterium columnare, Lactococcus garvieae, Photobacterium damselae, Pseudomonas anguilliseptica, Streptococcus iniae and Vibrio anguillarum) commonly encountered in aquaculture. The array comprised short oligonucleotide probes (30 mer) complementary to the polymorphic regions of 16S rRNA genes for the target pathogens. Targets annealed to the microarray probes were reacted with streptavidin-conjugated alkaline phosphatase and nitro blue tetrazolium/5-bromo-4-chloro-3'-indolylphosphate, p-toluidine salt (NBT/BCIP), resulting in blue spots that are easily visualized by the naked eye. Testing was performed against a total of 168 bacterial strains, i.e., 26 representative collection strains, 81 isolates of target fish pathogens, and 61 ecologically or phylogenetically related strains. The results showed that each probe consistently identified its corresponding target strain with 100% specificity. The detection limit of the microarray was estimated to be in the range of 1 pg for genomic DNA and 10(3) CFU/mL for pure pathogen cultures. These high specificity and sensitivity results demonstrate the feasibility of using DNA microarrays in the diagnostic detection of fish pathogens. PMID:22736973

  15. Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

    PubMed

    Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

    2016-04-01

    Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. PMID:26975600

  16. Simultaneous Light-Directed Synthesis of Mirror-Image Microarrays in a Photochemical Reaction Cell with Flare Suppression

    PubMed Central

    2013-01-01

    The use of photolabile protecting groups is a versatile and well-established means of synthesizing high complexity microarrays of biopolymers, such as nucleic acids and peptides, for high-throughput analysis. The synthesis takes place in a photochemical reaction cell which positions the microarray substrate at the focus of the optical system delivering the light and which can be connected to a fluidics system which delivers appropriate reagents to the surface in synchrony with the light exposure. Here we describe a novel photochemical reaction cell which allows for the simultaneous synthesis of microarrays on two substrates. The reaction cell positions both substrates within the limited depth-of-focus of the optical system while maintaining the necessary reagent flow conditions. The resulting microarrays are mirror images of each other but otherwise essentially identical. The new reaction cell doubles the throughput of microarray synthesis without increasing the consumption of reagents. In addition, a secondary flow chamber behind the reaction cell can be filled with an absorbent and index-matching fluid to eliminate reflections from light exiting the reaction cell assembly, greatly reducing unintended light exposure that reduces the sequence fidelity of the microarray probes. PMID:23968455

  17. Development and application of an oligonucleotide microarray and real-time quantitative PCR for detection of wastewater bacterial pathogens.

    PubMed

    Lee, Dae-Young; Lauder, Heather; Cruwys, Heather; Falletta, Patricia; Beaudette, Lee A

    2008-07-15

    Conventional microbial water quality test methods are well known for their technical limitations, such as lack of direct pathogen detection capacity and low throughput capability. The microarray assay has recently emerged as a promising alternative for environmental pathogen monitoring. In this study, bacterial pathogens were detected in municipal wastewater using a microarray equipped with short oligonucleotide probes targeting 16S rRNA sequences. To date, 62 probes have been designed against 38 species, 4 genera, and 1 family of pathogens. The detection sensitivity of the microarray for a waterborne pathogen Aeromonas hydrophila was determined to be approximately 1.0% of the total DNA, or approximately 10(3)A. hydrophila cells per sample. The efficacy of the DNA microarray was verified in a parallel study where pathogen genes and E. coli cells were enumerated using real-time quantitative PCR (qPCR) and standard membrane filter techniques, respectively. The microarray and qPCR successfully detected multiple wastewater pathogen species at different stages of the disinfection process (i.e. secondary effluents vs. disinfected final effluents) and at two treatment plants employing different disinfection methods (i.e. chlorination vs. UV irradiation). This result demonstrates the effectiveness of the DNA microarray as a semi-quantitative, high throughput pathogen monitoring tool for municipal wastewater. PMID:18423816

  18. 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...

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. Development and validation of a flax (Linum usitatissimum L.) gene expression oligo microarray

    PubMed Central

    2010-01-01

    Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted

  7. 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

  8. 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

  9. 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.

  10. 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

  11. Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

    PubMed Central

    Scheler, Ott; Glynn, Barry; Parkel, Sven; Palta, Priit; Toome, Kadri; Kaplinski, Lauris; Remm, Maido; Maher, Majella; Kurg, Ants

    2009-01-01

    Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology. PMID:19445684

  12. Antibody microarray profiling of osteosarcoma cell serum for identifying potential biomarkers.

    PubMed

    Zhu, Zi-Qiang; Tang, Jin-Shan; Gang, Duan; Wang, Ming-Xing; Wang, Jian-Qiang; Lei, Zhou; Feng, Zhou; Fang, Ming-Liang; Yan, Lin

    2015-07-01

    The aim of the present study was to identify biomarkers in osteosarcoma (OS) cell serum by antibody microarray profiling, which may be used for OS diagnosis and therapy. An antibody microarray was used to detect the expression levels of cytokines in serum samples from 20 patients with OS and 20 healthy individuals. Significantly expressed cytokines in OS serum were selected when P<0.05 and fold change >2. An enzyme-linked immunosorbent assay (ELISA) was used to validate the antibody microarray results. Finally, classification accuracy was calculated by cluster analysis. Twenty one cytokines were significantly upregulated in OS cell serum samples compared with control samples. Expression of interleukin-6, monocyte chemoattractant protein-1, tumor growth factor-β, growth-related oncogene, hepatocyte growth factor, chemokine ligand 16, Endoglin, matrix metalloproteinase-9 and platelet-derived growth factor-AA was validated by ELISAs. OS serum samples and control samples were distinguished by significantly expressed cytokines with an accuracy of 95%. The results demonstrated that expressed cytokines identified by antibody microarray may be used as biomarkers for OS diagnosis and therapy. PMID:25815525

  13. Application of Equilibrium Models of Solution Hybridization to Microarray Design and Analysis

    PubMed Central

    Gharaibeh, Raad Z.; Newton, Joshua M.; Weller, Jennifer W.; Gibas, Cynthia J.

    2010-01-01

    Background The probe percent bound value, calculated using multi-state equilibrium models of solution hybridization, is shown to be useful in understanding the hybridization behavior of microarray probes having 50 nucleotides, with and without mismatches. These longer oligonucleotides are in widespread use on microarrays, but there are few controlled studies of their interactions with mismatched targets compared to 25-mer based platforms. Principal Findings 50-mer oligonucleotides with centrally placed single, double and triple mismatches were spotted on an array. Over a range of target concentrations it was possible to discriminate binding to perfect matches and mismatches, and the type of mismatch could be predicted accurately in the concentration midrange (100 pM to 200 pM) using solution hybridization modeling methods. These results have implications for microarray design, optimization and analysis methods. Conclusions Our results highlight the importance of incorporating biophysical factors in both the design and the analysis of microarrays. Use of the probe “percent bound” value predicted by equilibrium models of hybridization is confirmed to be important for predicting and interpreting the behavior of long oligonucleotide arrays, as has been shown for short oligonucleotide arrays. PMID:20548788

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

    PubMed Central

    2010-01-01

    Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

  15. Baculovirus display for discovery of low-affinity extracellular receptor-ligand interactions using protein microarrays.

    PubMed

    Tom, Irene; Estevez, Alberto; Bowman, Krista; Gonzalez, Lino C

    2015-06-15

    When used in conjunction with multivalent protein probes, protein microarrays offer a robust technology for discovery of low-affinity extracellular protein-protein interactions. Probes for receptor-matching screens generally consist of purified extracellular domains fused to affinity tags. Given that approximately two-thirds of extracellular proteins are transmembrane domain-containing proteins, it would be desirable to develop a system to express and display probe receptors in a native-like membrane environment. Toward this end, we evaluated baculovirus display as a platform for generating multivalent probes for protein microarray screens. Virion particles were generated displaying single-transmembrane domain receptors BTLA, CD200, and EFNB2, representing a range of affinities for their interacting partners. Virions directly labeled with Cy5 fluorophore were screened against a microarray containing more than 600 extracellular proteins, and the results were compared with data derived from soluble Fc protein or probe-coated protein A microbeads. An optimized protocol employing a blocking step with a nonrelated probe-expressing control baculovirus allowed identification of the expected interactions with a signal-to-noise ratio similar to or higher than those obtained with the other formats. Our results demonstrate that baculovirus display is suitable for detection of high- and low-affinity extracellular protein-protein interactions on protein microarrays. This platform eliminates the need for protein purification and provides a native-like lipid environment for membrane-associated receptors. PMID:25797350

  16. Microarray and KOG analysis of Acanthamoeba healyi genes up-regulated by mouse-brain passage.

    PubMed

    Moon, Eun-Kyung; Xuan, Ying-Hua; Kong, Hyun-Hee

    2014-08-01

    Long-term cultivation in a laboratory could reduce the virulence of Acanthamoeba. To identify virulence factors of Acanthamoeba, the authors compared the transcription profiles of long-term cultivated Acanthamoeba healyi (OLD) and three times mouse-brain passaged A. healyi (MBP) using microarray analysis and eukaryotic orthologous group (KOG) assignments. Microarray analysis revealed that 601 genes were up-regulated by mouse-brain passage. The results of real-time PCR of 8 randomly selected genes up-regulated in the MBP strain confirmed microarray analysis findings. KOG assignments showed relatively higher percentages of the MBP strain up-regulated genes in T article (signal transduction mechanism), O article (posttranslational modification, protein turnover, chaperones), C article (energy production and conversion), and J article (translation, ribosomal structure and biogenesis). In particular, the MBP strain showed higher expressions of cysteine protease and metalloprotease. A comparison of KOG assignments by microarray analysis and previous EST (expressed sequence tags) analysis showed similar populations of up-regulated genes. These results provide important information regarding the identification of virulence factors of pathogenic Acanthamoeba. PMID:24859526

  17. Genome image programs: visualization and interpretation of Escherichia coli microarray experiments.

    PubMed Central

    Zimmer, Daniel P; Paliy, Oleg; Thomas, Brian; Gyaneshwar, Prasad; Kustu, Sydney

    2004-01-01

    We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. PMID:15342544

  18. 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

  19. 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

  20. Effect of data normalization on fuzzy clustering of DNA microarray data

    PubMed Central

    Kim, Seo Young; Lee, Jae Won; Bae, Jong Sung

    2006-01-01

    Background Microarray technology has made it possible to simultaneously measure the expression levels of large numbers of genes in a short time. Gene expression data is information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. Clustering is an important tool for finding groups of genes with similar expression patterns in microarray data analysis. However, hard clustering methods, which assign each gene exactly to one cluster, are poorly suited to the analysis of microarray datasets because in such datasets the clusters of genes frequently overlap. Results In this study we applied the fuzzy partitional clustering method known as Fuzzy C-Means (FCM) to overcome the limitations of hard clustering. To identify the effect of data normalization, we used three normalization methods, the two common scale and location transformations and Lowess normalization methods, to normalize three microarray datasets and three simulated datasets. First we determined the optimal parameters for FCM clustering. We found that the optimal fuzzification parameter in the FCM analysis of a microarray dataset depended on the normalization method applied to the dataset during preprocessing. We additionally evaluated the effect of normalization of noisy datasets on the results obtained when hard clustering or FCM clustering was applied to those datasets. The effects of normalization were evaluated using both simulated datasets and microarray datasets. A comparative analysis showed that the clustering results depended on the normalization method used and the noisiness of the data. In particular, the selection of the fuzzification parameter value for the FCM method was sensitive to the normalization method used for datasets with large variations across samples. Conclusion Lowess normalization is more robust for clustering of genes from general microarray data than the two common scale and location adjustment methods

  1. QA/QC issues to aid regulatory acceptance of microarray gene expression data.

    PubMed

    Fuscoe, James C; Tong, Weida; Shi, Leming

    2007-06-01

    The U.S. Food and Drug Administration is responsible for (1) promoting and protecting public health by assuring the safety and effectiveness of medicines and medical devices and (2) advancing public health by helping to speed innovations that make medicines and foods safer, more effective, and more affordable. The genomics revolution has dramatically increased our knowledge of basic biology but this has not resulted in the expected acceleration of new medical product development. The Agency's Critical Path to New Medical Products stresses that new tools are needed to address this pipeline problem. Microarray technology is one of these promising tools although questions have risen about the reproducibility of measurements. The Microarray Quality Control (MAQC) Project was initiated by FDA scientists to address this issue. This large project, which evaluated reference RNA samples on seven microarray platforms, found good intralaboratory repeatability and interlaboratory reproducibility. In addition, there was high cross-platform consistency. All data are available free of cost and the reference RNA samples are available for proficiency testing. Thus, current microarray technology appears to provide both reliability and consistency for regulatory submissions. PMID:17567852

  2. Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

    PubMed Central

    Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

    2015-01-01

    This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

  3. Measuring information flow in cellular networks by the systems biology method through microarray data

    PubMed Central

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells. PMID:26082788

  4. Electrospinning of poly(dimethylsiloxane)/poly(methyl methacrylate) nanofibrous membrane: fabrication and application in protein microarrays.

    PubMed

    Yang, Dayong; Liu, Xing; Jin, Yu; Zhu, Ying; Zeng, Dongdong; Jiang, Xingyu; Ma, Hongwei

    2009-12-14

    Fabrication of poly(dimethylsiloxane) (PDMS)/poly(methyl methacrylate) (PMMA) nanofibers is critical to harness the advantage of nanostructured membrane applied in protein microarrays. Electrospinning (ES) of PDMS nanofibers is challenging because of the relatively low molecular weight of PDMS prepolymer. We report a strategy to fabricate PDMS/PMMA nanofibers via ES by introducing carrier polymer PMMA into PDMS solutions to supplement the deficiency of chain entanglements in the PDMS prepolymer. The prepared PDMS/PMMA nanofibrous membrane (PDMS/PMMA NFM) was successfully used as substrates for protein microarrays. The results of immunoassays showed the superior performance of PDMS/PMMA NFM as 3D substrate for protein microarrays; the limit-of-detection (LOD) on PDMS/PMMA NFM was 32 times lower than that on nitrocellulose membrane. The realization of ES PDMS extends the scope of ES materials from thermoplastic polymers to thermosetting materials. Given the simplicity, low cost, and high efficiency of ES technology, we believe that PDMS/PMMA NFM is a promising 3D substrate for protein microarrays. PMID:19924999

  5. Profiling Humoral Immune Responses to Clostridium difficile-Specific Antigens by Protein Microarray Analysis.

    PubMed

    Negm, Ola H; Hamed, Mohamed R; Dilnot, Elizabeth M; Shone, Clifford C; Marszalowska, Izabela; Lynch, Mark; Loscher, Christine E; Edwards, Laura J; Tighe, Patrick J; Wilcox, Mark H; Monaghan, Tanya M

    2015-09-01

    Clostridium difficile is an anaerobic, Gram-positive, and spore-forming bacterium that is the leading worldwide infective cause of hospital-acquired and antibiotic-associated diarrhea. Several studies have reported associations between humoral immunity and the clinical course of C. difficile infection (CDI). Host humoral immune responses are determined using conventional enzyme-linked immunosorbent assay (ELISA) techniques. Herein, we report the first use of a novel protein microarray assay to determine systemic IgG antibody responses against a panel of highly purified C. difficile-specific antigens, including native toxins A and B (TcdA and TcdB, respectively), recombinant fragments of toxins A and B (TxA4 and TxB4, respectively), ribotype-specific surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). Microarrays were probed with sera from a total of 327 individuals with CDI, cystic fibrosis without diarrhea, and healthy controls. For all antigens, precision profiles demonstrated <10% coefficient of variation (CV). Significant correlation was observed between microarray and ELISA in the quantification of antitoxin A and antitoxin B IgG. These results indicate that microarray is a suitable assay for defining humoral immune responses to C. difficile protein antigens and may have potential advantages in throughput, convenience, and cost. PMID:26178385

  6. Drug-eluting microarrays to identify effective chemotherapeutic combinations targeting patient-derived cancer stem cells

    PubMed Central

    Carstens, Matthew R.; Fisher, Robert C.; Acharya, Abhinav P.; Butterworth, Elizabeth A.; Scott, Edward; Huang, Emina H.; Keselowsky, Benjamin G.

    2015-01-01

    A new paradigm in oncology establishes a spectrum of tumorigenic potential across the heterogeneous phenotypes within a tumor. The cancer stem cell hypothesis postulates that a minute fraction of cells within a tumor, termed cancer stem cells (CSCs), have a tumor-initiating capacity that propels tumor growth. An application of this discovery is to target this critical cell population using chemotherapy; however, the process of isolating these cells is arduous, and the rarity of CSCs makes it difficult to test potential drug candidates in a robust fashion, particularly for individual patients. To address the challenge of screening drug libraries on patient-derived populations of rare cells, such as CSCs, we have developed a drug-eluting microarray, a miniaturized platform onto which a minimal quantity of cells can adhere and be exposed to unique treatment conditions. Hundreds of drug-loaded polymer islands acting as drug depots colocalized with adherent cells are surrounded by a nonfouling background, creating isolated culture environments on a solid substrate. Significant results can be obtained by testing <6% of the cells required for a typical 96-well plate. Reliability was demonstrated by an average coefficient of variation of 14% between all of the microarrays and 13% between identical conditions within a single microarray. Using the drug-eluting array, colorectal CSCs isolated from two patients exhibited unique responses to drug combinations when cultured on the drug-eluting microarray, highlighting the potential as a prognostic tool to identify personalized chemotherapeutic regimens targeting CSCs. PMID:26124098

  7. Detection of Alicyclobacillus species in fruit juice using a random genomic DNA microarray chip.

    PubMed

    Jang, Jun Hyeong; Kim, Sun-Joong; Yoon, Bo Hyun; Ryu, Jee-Hoon; Gu, Man Bock; Chang, Hyo-Ihl

    2011-06-01

    This study describes a method using a DNA microarray chip to rapidly and simultaneously detect Alicyclobacillus species in orange juice based on the hybridization of genomic DNA with random probes. Three food spoilage bacteria were used in this study: Alicyclobacillus acidocaldarius, Alicyclobacillus acidoterrestris, and Alicyclobacillus cycloheptanicus. The three Alicyclobacillus species were adjusted to 2 × 10(3) CFU/ml and inoculated into pasteurized 100% pure orange juice. Cy5-dCTP labeling was used for reference signals, and Cy3-dCTP was labeled for target genomic DNA. The molar ratio of 1:1 of Cy3-dCTP and Cy5-dCTP was used. DNA microarray chips were fabricated using randomly fragmented DNA of Alicyclobacillus spp. and were hybridized with genomic DNA extracted from Bacillus spp. Genomic DNA extracted from Alicyclobacillus spp. showed a significantly higher hybridization rate compared with DNA of Bacillus spp., thereby distinguishing Alicyclobacillus spp. from Bacillus spp. The results showed that the microarray DNA chip containing randomly fragmented genomic DNA was specific and clearly identified specific food spoilage bacteria. This microarray system is a good tool for rapid and specific detection of thermophilic spoilage bacteria, mainly Alicyclobacillus spp., and is useful and applicable to the fruit juice industry. PMID:21669070

  8. An equipment-free polydimethylsiloxane microfluidic spotter for fabrication of microarrays

    PubMed Central

    Tang, Teng; Li, Gang; Jia, Chunping; Gao, Kunpeng; Zhao, Jianlong

    2014-01-01

    This paper presents a low-cost, power-free, and easy-to-use spotter system for fabrication of microarrays. The spotter system uses embedded dispensing microchannels combined with a polydimethylsiloxane (PDMS) membrane containing regular arrays of well-defined thru-holes to produce precise, uniform DNA or protein microarrays for disease diagnosis or drug screening. Powered by pre-evacuation of its PDMS substrate, the spotter system does not require any additional components or external equipment for its operation, which can potentially allow low-cost, high-quality microarray fabrication by minimally trained individuals. Polyvinylpyrrolidone was used to modify the PDMS surface to prevent protein adsorption by the microchannels. Experimental results indicate that the PDMS spotter shows excellent printing performance for immobilizing proteins. The measured coefficient of variation (CV) of the diameter of 48 spots was 2.63% and that of the intensity within one array was 2.87%. Concentration gradient experiments revealed the superiority of the immobilization density of the PDMS spotter over the conventional pin-printing method. Overall, this low-cost, power-free, and easy-to-use spotting system provides an attractive new method to fabricate microarrays. PMID:24803969

  9. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays

    PubMed Central

    Gerdtsson, Anna S.; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A. K.; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. PMID:27600082

  10. Dye-Doped Silica Nanoparticle Labels/Protein Microarray for Detection of Protein Biomarkers

    SciTech Connect

    Wu, Hong; Huo, Qisheng; Varnum, Susan M.; Liu, Guodong; Wang, Jun; Nie, Zimin; Liu, Jun; Lin, Yuehe

    2008-10-20

    Biomarkers serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Interleukin-6 (IL-6), a biomarker with its important biological and pathological functions, has been studied for decades. Conventional fluorescence immunoassay has been widely used for analysis of biomakers like IL-6. However, single fluorophore labeling shows its limitations of low intensity and poor stability. We report a dye-encapsulated silica nanoparticle as a label, with the advantages of high fluorescence intensity, photostability, and biocompatibility, in conjunction with microarray technology for sensitive immunoassay of IL-6 on a microarray format. The tris (2,2’-bipyridyl)ruthenium (II)chloride hexahydrate (Rubpy) dye incorporated into silica nanoparticles using a simple one-step microemulsion synthesis step. The nanoparticles are uniform in size with a diameter of 50 nm. The microarray fluorescent immunoassay approach based on dye-doped silica nanoparticle labels has high sensitivity for practical applications with a limit of detection for IL-6 down to 0.1 ng mL-1. The calibration curve is linear over the range from 0.1 ng mL-1 to 10 ng mL-1. Furthermore, results illustrated that the assay is highly specific for IL-6 in the presence of range of cytokines or proteins. The RuDS dye-labeled nanoparticles in connection with protein microarrays show the promise for clinical diagnosis of biomarkers.

  11. A Fully Automatic Method for Gridding Bright Field Images of Bead-Based Microarrays.

    PubMed

    Datta, Abhik; Wai-Kin Kong, Adams; Yow, Kin-Choong

    2016-07-01

    In this paper, a fully automatic method for gridding bright field images of bead-based microarrays is proposed. There have been numerous techniques developed for gridding fluorescence images of traditional spotted microarrays but to our best knowledge, no algorithm has yet been developed for gridding bright field images of bead-based microarrays. The proposed gridding method is designed for automatic quality control during fabrication and assembly of bead-based microarrays. The method begins by estimating the grid parameters using an evolutionary algorithm. This is followed by a grid-fitting step that rigidly aligns an ideal grid with the image. Finally, a grid refinement step deforms the ideal grid to better fit the image. The grid fitting and refinement are performed locally and the final grid is a nonlinear (piecewise affine) grid. To deal with extreme corruptions in the image, the initial grid parameter estimation and grid-fitting steps employ robust search techniques. The proposed method does not have any free parameters that need tuning. The method is capable of identifying the grid structure even in the presence of extreme amounts of artifacts and distortions. Evaluation results on a variety of images are presented. PMID:26011899

  12. Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

    PubMed

    Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

    2015-01-01

    This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

  13. Development of a sandwiched microarray platform for studying the interactions of antibiotics with Staphylococcus aureus.

    PubMed

    Liu, Xia; Lei, Zhen; Liu, Dianjun; Wang, Zhenxin

    2016-04-21

    It still confronts an outstanding challenge to screen efficient antibacterial drugs from millions of potential antibiotic candidates. In this regard, a sandwiched microarray platform has been developed to culture live bacteria and carry out high-throughput screening antibacterial drugs. The optimized lectin-hydrogel microarray can be used as an efficient bacterial capturing and culturing platform, which is beneficial to identify spots and collect data. At the same time, a matching drug-laden polyacrylamide microarray with Luria-Bertani (LB) culture medium can be generated automatically and accurately by using a standard non-contacting procedure. A large number of microscale culture chambers (more than 100 individual samples) between two microarrays can be formed by linking two aligned hydrogel spots using LB culture medium, where live bacteria can be co-cultured with drug candidates. Using Staphylococcus aureus (S. aureus) and four well-known antibiotics (amoxicillin, vancomycin, streptomycin and chloramphenicol) as model system, the MIC (minimum inhibitory concentration) values of the antibiotics can be determined by the drug induced change of bacterial growth, and the results demonstrate that the MIC values of amoxicillin, vancomycin and streptomycin are 1.7 μg mL(-1), 3.3 μg mL(-1) and 10.3 μg mL(-1), respectively. PMID:27026605

  14. Establishment and Application of a Visual DNA Microarray for the Detection of Food-borne Pathogens.

    PubMed

    Li, Yongjin

    2016-01-01

    The accurate detection and identification of food-borne pathogenic microorganisms is critical for food safety nowadays. In the present work, a visual DNA microarray was established and applied to detect pathogens commonly found in food, including Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in food samples. Multiplex PCR (mPCR) was employed to simultaneously amplify specific gene fragments, fimY for Salmonella, ipaH for Shigella, iap for L. monocytogenes and ECs2841 for E. coli O157:H7, respectively. Biotinylated PCR amplicons annealed to the microarray probes were then reacted with a streptavidin-alkaline phosphatase conjugate and nitro blue tetrazolium/5-bromo-4-chloro-3'-indolylphosphate, p-toluidine salt (NBT/BCIP); the positive results were easily visualized as blue dots formatted on the microarray surface. The performance of a DNA microarray was tested against 14 representative collection strains and mock-contamination food samples. The combination of mPCR and a visual micro-plate chip specifically and sensitively detected Salmonella enterica, Shigella flexneri, E. coli O157:H7 and Listeria monocytogenes in standard strains and food matrices with a sensitivity of ∼10(2) CFU/mL of bacterial culture. Thus, the developed method is advantageous because of its high throughput, cost-effectiveness and ease of use. PMID:26860568

  15. Evaluation of Solid Supports for Slide- and Well-Based Recombinant Antibody Microarrays.

    PubMed

    Gerdtsson, Anna S; Dexlin-Mellby, Linda; Delfani, Payam; Berglund, Erica; Borrebaeck, Carl A K; Wingren, Christer

    2016-01-01

    Antibody microarrays have emerged as an important tool within proteomics, enabling multiplexed protein expression profiling in both health and disease. The design and performance of antibody microarrays and how they are processed are dependent on several factors, of which the interplay between the antibodies and the solid surfaces plays a central role. In this study, we have taken on the first comprehensive view and evaluated the overall impact of solid surfaces on the recombinant antibody microarray design. The results clearly demonstrated the importance of the surface-antibody interaction and showed the effect of the solid supports on the printing process, the array format of planar arrays (slide- and well-based), the assay performance (spot features, reproducibility, specificity and sensitivity) and assay processing (degree of automation). In the end, two high-end recombinant antibody microarray technology platforms were designed, based on slide-based (black polymer) and well-based (clear polymer) arrays, paving the way for future large-scale protein expression profiling efforts. PMID:27600082

  16. Easy and fast detection and genotyping of high-risk human papillomavirus by dedicated DNA microarrays.

    PubMed

    Albrecht, Valérie; Chevallier, Anne; Magnone, Virginie; Barbry, Pascal; Vandenbos, Fanny; Bongain, André; Lefebvre, Jean-Claude; Giordanengo, Valérie

    2006-11-01

    Persistent cervical high-risk human papillomavirus (HPV) infection is correlated with an increased risk of developing a high-grade cervical intraepithelial lesion. A two-step method was developed for detection and genotyping of high-risk HPV. DNA was firstly amplified by asymmetrical PCR in the presence of Cy3-labelled primers and dUTP. Labelled DNA was then genotyped using DNA microarray hybridization. The current study evaluated the technical efficacy of laboratory-designed HPV DNA microarrays for high-risk HPV genotyping on 57 malignant and non-malignant cervical smears. The approach was evaluated for a broad range of cytological samples: high-grade squamous intraepithelial lesions (HSIL), low-grade squamous intraepithelial lesions (LSIL) and atypical squamous cells of high-grade (ASC-H). High-risk HPV was also detected in six atypical squamous cells of undetermined significance (ASC-US) samples; among them only one cervical specimen was found uninfected, associated with no histological lesion. The HPV oligonucleotide DNA microarray genotyping detected 36 infections with a single high-risk HPV type and 5 multiple infections with several high-risk types. Taken together, these results demonstrate the sensitivity and specificity of the HPV DNA microarray approach. This approach could improve clinical management of patients with cervical cytological abnormalities. PMID:16879879

  17. An evaluation of the applicability of microarrays for monitoring toxic algae in Irish coastal waters.

    PubMed

    McCoy, Gary R; Touzet, Nicolas; Fleming, Gerard Ta; Raine, Robin

    2013-10-01

    The applicability of microarrays to monitor harmful algae across a broad range of ecological niches and toxic species responsible for harmful algal events has been one of the key tasks in the EU Seventh Framework Programme (FP7)-funded Microarrays for the Detection of Toxic Algae project. The technique has a strong potential for improving speed and accuracy of the identification of harmful algae and their toxins to assist monitoring programmes. Water samples were collected from a number of coastal sites around Ireland, including several that are used in the Irish National Phytoplankton and Biotoxin Monitoring Programme. Ribosomal RNA was extracted from filtered field samples, labelled with a fluorescent dye, and hybridised to probes spotted in a microarray format on a glass slide. The fluorescent signal intensity of the hybridisation to >120 probes on the chip was analysed and compared with actual field counts. There was a general agreement between cell counts and microarray signal. Results are presented for field samples taken from a range of stations along the Irish coastline known for harmful algal events during the first field trial (July 2009-April 2010). PMID:23184126

  18. GPR-Analyzer: a simple tool for quantitative analysis of hierarchical multispecies microarrays.

    PubMed

    Dittami, Simon M; Edvardsen, Bente

    2013-10-01

    Monitoring of marine microalgae is important to predict and manage harmful algae blooms. It currently relies mainly on light-microscopic identification and enumeration of algal cells, yet several molecular tools are currently being developed to complement traditional methods. MIcroarray Detection of Toxic ALgae (MIDTAL) is an FP7-funded EU project aiming to establish a hierarchical multispecies microarray as one of these tools. Prototype arrays are currently being tested with field samples, yet the analysis of the large quantities of data generated by these arrays presents a challenge as suitable analysis tools or protocols are scarce. This paper proposes a two-part protocol for the analysis of the MIDTAL and other hierarchical multispecies arrays: Signal-to-noise ratios can be used to determine the presence or absence of signals and to identify potential false-positives considering parallel and hierarchical probes. In addition, normalized total signal intensities are recommended for comparisons between microarrays and in order to relate signals for specific probes to cell concentrations using external calibration curves. Hybridization- and probe-specific detection limits can be calculated to help evaluate negative results. The suggested analyses were implemented in "GPR-Analyzer", a platform-independent and graphical user interface-based application, enabling non-specialist users to quickly and quantitatively analyze hierarchical multispecies microarrays. It is available online at http://folk.uio.no/edvardse/gpranalyzer . PMID:22767354

  19. 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.

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

    PubMed

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

    2016-04-01

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

  1. High-throughput detection of food-borne pathogenic bacteria using oligonucleotide microarray with quantum dots as fluorescent labels.

    PubMed

    Huang, Aihua; Qiu, Zhigang; Jin, Min; Shen, Zhiqiang; Chen, Zhaoli; Wang, Xinwei; Li, Jun-Wen

    2014-08-18

    Bacterial pathogens are mostly responsible for food-borne diseases, and there is still substantial room for improvement in the effective detection of these organisms. In the present study, we explored a new method to detect target pathogens easily and rapidly with high sensitivity and specificity. This method uses an oligonucleotide microarray combined with quantum dots as fluorescent labels. Oligonucleotide probes targeting the 16SrRNA gene were synthesized to create an oligonucleotide microarray. The PCR products labeled with biotin were subsequently hybridized using an oligonucleotide microarray. Following incubation with CdSe/ZnS quantum dots coated with streptavidin, fluorescent signals were detected with a PerkinElmer Gx Microarray Scanner. The results clearly showed specific hybridization profiles corresponding to the bacterial species assessed. Two hundred and sixteen strains of food-borne bacterial pathogens, including standard strains and isolated strains from food samples, were used to test the specificity, stability, and sensitivity of the microarray system. We found that the oligonucleotide microarray combined with quantum dots used as fluorescent labels can successfully discriminate the bacterial organisms at the genera or species level, with high specificity and stability as well as a sensitivity of 10 colony forming units (CFU)/mL of pure culture. We further tested 105 mock-contaminated food samples and achieved consistent results as those obtained from traditional biochemical methods. Together, these results indicate that the quantum dot-based oligonucleotide microarray has the potential to be a powerful tool in the detection and identification of pathogenic bacteria in foods. PMID:24927399

  2. Microarray analysis of gene expression in vestibular schwannomas reveals SPP1/MET signaling pathway and androgen receptor deregulation

    PubMed Central

    TORRES-MARTIN, MIGUEL; LASSALETTA, LUIS; SAN-ROMAN-MONTERO, JESUS; DE CAMPOS, JOSE M.; ISLA, ALBERTO; GAVILAN, JAVIER; MELENDEZ, BARBARA; PINTO, GIOVANNY R.; BURBANO, ROMMEL R.; CASTRESANA, JAVIER S.; REY, JUAN A.

    2013-01-01

    Vestibular schwannomas are benign neoplasms that arise from the vestibular nerve. The hallmark of these tumors is the biallelic inactivation of neurofibromin 2 (NF2). Transcriptomic alterations, such as the neuregulin 1 (NRG1)/ErbB2 pathway, have been described in schwannomas. In this study, we performed a whole transcriptome analysis in 31 vestibular schwannomas and 9 control nerves in the Affymetrix Gene 1.0 ST platform, validated by quantitative real-time PCR (qRT-PCR) using TaqMan Low Density arrays. We performed a mutational analysis of NF2 by PCR/denaturing high-performance liquid chromatography (dHPLC) and multiplex ligation-dependent probe amplification (MLPA), as well as a microsatellite marker analysis of the loss of heterozygosity (LOH) of chromosome 22q. The microarray analysis demonstrated that 1,516 genes were deregulated and 48 of the genes were validated by qRT-PCR. At least 2 genetic hits (allelic loss and/or gene mutation) in NF2 were found in 16 tumors, seven cases showed 1 hit and 8 tumors showed no NF2 alteration. MET and associated genes, such as integrin, alpha 4 (ITGA4)/B6, PLEXNB3/SEMA5 and caveolin-1 (CAV1) showed a clear deregulation in vestibular schwannomas. In addition, androgen receptor (AR) downregulation may denote a hormonal effect or cause in this tumor. Furthermore, the osteopontin gene (SPP1), which is involved in merlin protein degradation, was upregulated, which suggests that this mechanism may also exert a pivotal role in schwannoma merlin depletion. Finally, no major differences were observed among tumors of different size, histological type or NF2 status, which suggests that, at the mRNA level, all schwannomas, regardless of their molecular and clinical characteristics, may share common features that can be used in their treatment. PMID:23354516

  3. A Microarray Analysis of the Temporal Response of Liver to Methylprednisolone: A Comparative Analysis of Two Dosing Regimens

    PubMed Central

    Almon, Richard R.; DuBois, Debra C.; Jusko, William J.

    2014-01-01

    Microarray analyses were performed on livers from adrenalectomized male Wistar rats chronically infused with methylprednisolone (MPL) (0.3 mg/kg·h) using Alzet mini-osmotic pumps for periods ranging from 6 h to 7 d. Four control and 40 drug-treated animals were killed at 10 different times during drug infusion. Total RNA preparations from the livers of these animals were hybridized to 44 individual Affymetrix REA230A gene chips, generating data for 15,967 different probe sets for each chip. A series of three filters were applied sequentially. These filters were designed to eliminate probe sets that were not expressed in the tissue, were not regulated by the drug, or did not meet defined quality control standards. These filters eliminated 13,978 probe sets (87.5%) leaving a remainder of 1989 probe sets for further consideration. We previously described a similar dataset obtained from animals after administration of a single dose of MPL (50 mg/kg given iv). That study involved 16 time points over a 72-h period. A similar filtering schema applied to the single-bolus-dose data-set identified 1519 probe sets as being regulated by MPL. A comparison of datasets from the two different dosing regimens identified 358 genes that were regulated by MPL in response to both dosing regimens. Regulated genes were grouped into 13 categories, mainly on gene product function. The temporal profiles of these common genes were subjected to detailed scrutiny. Examination of temporal profiles demonstrates that current perspectives on the mechanism of glucocorticoid action cannot entirely explain the temporal profiles of these regulated genes. PMID:17303664

  4. 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.

  5. 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

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

    PubMed

    de Paz, Jose L; Seeberger, Peter H

    2008-07-01

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

  7. 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

  8. Sex-related gene expression profiles in the adrenal cortex in the mature rat: Microarray analysis with emphasis on genes involved in steroidogenesis

    PubMed Central

    TREJTER, MARCIN; HOCHOL, ANNA; TYCZEWSKA, MARIANNA; ZIOLKOWSKA, AGNIESZKA; JOPEK, KAROL; SZYSZKA, MARTA; MALENDOWICZ, LUDWIK K; RUCINSKI, MARCIN

    2015-01-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix® Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

  9. Sex-related gene expression profiles in the adrenal cortex in the mature rat: microarray analysis with emphasis on genes involved in steroidogenesis.

    PubMed

    Trejter, Marcin; Hochol, Anna; Tyczewska, Marianna; Ziolkowska, Agnieszka; Jopek, Karol; Szyszka, Marta; Malendowicz, Ludwik K; Rucinski, Marcin

    2015-03-01

    Notable sex-related differences exist in mammalian adrenal cortex structure and function. In adult rats, the adrenal weight and the average volume of zona fasciculata cells of females are larger and secrete greater amounts of corticosterone than those of males. The molecular bases of these sex-related differences are poorly understood. In this study, to explore the molecular background of these differences, we defined zone- and sex-specific transcripts in adult male and female (estrous cycle phase) rats. Twelve-week-old rats of both genders were used and samples were taken from the zona glomerulosa (ZG) and zona fasciculata/reticularis (ZF/R) zones. Transcriptome identification was carried out using the Affymetrix(®) Rat Gene 1.1 ST Array. The microarray data were compared by fold change with significance according to moderated t-statistics. Subsequently, we performed functional annotation clustering using the Gene Ontology (GO) and Database for Annotation, Visualization and Integrated Discovery (DAVID). In the first step, we explored differentially expressed transcripts in the adrenal ZG and ZF/R. The number of differentially expressed transcripts was notably higher in the female than in the male rats (702 vs. 571). The differentially expressed genes which were significantly enriched included genes involved in steroid hormone metabolism, and their expression levels in the ZF/R of adult female rats were significantly higher compared with those in the male rats. In the female ZF/R, when compared with that of the males, prevailing numbers of genes linked to cell fraction, oxidation/reduction processes, response to nutrients and to extracellular stimuli or steroid hormone stimuli were downregulated. The microarray data for key genes involved directly in steroidogenesis were confirmed by qPCR. Thus, when compared with that of the males, in the female ZF/R, higher expression levels of genes involved directly in steroid hormone synthesis were accompanied by lower

  10. Detecting variants with Metabolic Design, a new software tool to design probes for explorative functional DNA microarray development

    PubMed Central

    2010-01-01

    Background Microorganisms display vast diversity, and each one has its own set of genes, cell components and metabolic reactions. To assess their huge unexploited metabolic potential in different ecosystems, we need high throughput tools, such as functional microarrays, that allow the simultaneous analysis of thousands of genes. However, most classical functional microarrays use specific probes that monitor only known sequences, and so fail to cover the full microbial gene diversity present in complex environments. We have thus developed an algorithm, implemented in the user-friendly program Metabolic Design, to design efficient explorative probes. Results First we have validated our approach by studying eight enzymes involved in the degradation of polycyclic aromatic hydrocarbons from the model strain Sphingomonas paucimobilis sp. EPA505 using a designed microarray of 8,048 probes. As expected, microarray assays identified the targeted set of genes induced during biodegradation kinetics experiments with various pollutants. We have then confirmed the identity of these new genes by sequencing, and corroborated the quantitative discrimination of our microarray by quantitative real-time PCR. Finally, we have assessed metabolic capacities of microbial communities in soil contaminated with aromatic hydrocarbons. Results show that our probe design (sensitivity and explorative quality) can be used to study a complex environment efficiently. Conclusions We successfully use our microarray to detect gene expression encoding enzymes involved in polycyclic aromatic hydrocarbon degradation for the model strain. In addition, DNA microarray experiments performed on soil polluted by organic pollutants without prior sequence assumptions demonstrate high specificity and sensitivity for gene detection. Metabolic Design is thus a powerful, efficient tool that can be used to design explorative probes and monitor metabolic pathways in complex environments, and it may also be used to

  11. DNA methylation analysis using CpG microarrays is impaired in benzopyrene exposed cells

    SciTech Connect

    Sadikovic, Bekim; Andrews, Joseph; Rodenhiser, David I.

    2007-12-15

    Epigenetic alterations have emerged as a key mechanism involved in tumorigenesis. These disruptions are partly due to environmental factors that change normal DNA methylation patterns necessary for transcriptional regulation and chromatin compaction. Microarray technologies are allowing environmentally susceptible epigenetic patterns to be mapped and the precise targets of environmentally induced alterations to be identified. Previously, we observed BaP-induced epigenetic events and cell cycle disruptions in breast cancer cell lines that included time- and concentration-dependent loss of proliferation as well as sequence-specific hypo- and hypermethylation events. In this present report, we further characterized epigenetic changes in BaP-exposed MCF-7 cells. We analyzed DNA methylation on a CpG island microarray platform with over 5400 unique genomic regions. Depleted and enriched microarray targets, representative of putative DNA methylation changes, were identified across the genome; however, subsequent sodium bisulfite analyses revealed no changes in DNA methylation at a number of these loci. Instead, we found that the identification of DNA methylation changes using this restriction enzyme-based microarray approach corresponded with the regions of DNA bound by the BaP derived DNA adducts. This DNA adduct formation occurs at both methylated and unmethylated CpG dinucleotides and affects PCR amplification during sample preparation. Our data suggest that caution should be exercised when interpreting data from comparative microarray experiments that rely on enzymatic reactions. These results are relevant to genome screening approaches involving environmental exposures in which DNA adduct formation at specific nucleotide sites may bias target acquisition and compromise the correct identification of epigenetically responsive genes.

  12. Development of a microarray for two rice subspecies: characterization and validation of gene expression in rice tissues

    PubMed Central

    2014-01-01

    Background Rice is one of the major crop species in the world helping to sustain approximately half of the global population’s diet especially in Asia. However, due to the impact of extreme climate change and global warming, rice crop production and yields may be adversely affected resulting in a world food crisis. Researchers have been keen to understand the effects of drought, temperature and other environmental stress factors on rice plant growth and development. Gene expression microarray technology represents a key strategy for the identification of genes and their associated expression patterns in response to stress. Here, we report on the development of the rice OneArray® microarray platform which is suitable for two major rice subspecies, japonica and indica. Results The rice OneArray® 60-mer, oligonucleotide microarray consists of a total of 21,179 probes covering 20,806 genes of japonica and 13,683 genes of indica. Through a validation study, total RNA isolated from rice shoots and roots were used for comparison of gene expression profiles via microarray examination. The results were submitted to NCBI’s Gene Expression Omnibus (GEO). Data can be found under the GEO accession number GSE50844 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50844). A list of significantly differentially expressed genes was generated; 438 shoot-specific genes were identified among 3,138 up-regulated genes, and 463 root-specific genes were found among 3,845 down-regulated genes. GO enrichment analysis demonstrates these results are in agreement with the known physiological processes of the different organs/tissues. Furthermore, qRT-PCR validation was performed on 66 genes, and found to significantly correlate with the microarray results (R = 0.95, p < 0.001***). Conclusion The rice OneArray® 22 K microarray, the first rice microarray, covering both japonica and indica subspecies was designed and validated in a comprehensive study of gene expression in

  13. 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

  14. 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.

  15. Cell-Based Microarrays for In Vitro Toxicology

    NASA Astrophysics Data System (ADS)

    Wegener, Joachim

    2015-07-01

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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. Variation of RNA Quality and Quantity Are Major Sources of Batch Effects in Microarray Expression Data

    PubMed Central

    Fasold, Mario; Binder, Hans

    2014-01-01

    The great utility of microarrays for genome-scale expression analysis is challenged by the widespread presence of batch effects, which bias expression measurements in particular within large data sets. These unwanted technical artifacts can obscure biological variation and thus significantly reduce the reliability of the analysis results. It is largely unknown which are the predominant technical sources leading to batch effects. We here quantitatively assess the prevalence and impact of several known technical effects on microarray expression results. Particularly, we focus on important factors such as RNA degradation, RNA quantity, and sequence biases including multiple guanine effects. We find that the common variation of RNA quality and RNA quantity can not only yield low-quality expression results, but that both factors also correlate with batch effects and biological characteristics of the samples.

  2. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

    PubMed Central

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

    2015-01-01

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

  3. 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

  4. 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

  5. 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

  6. 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

  7. Anti-CD antibody microarray for human leukocyte morphology examination allows analyzing rare cell populations and suggesting preliminary diagnosis in leukemia

    PubMed Central

    Khvastunova, Alina N.; Kuznetsova, Sofya A.; Al-Radi, Liubov S.; Vylegzhanina, Alexandra V.; Zakirova, Anna O.; Fedyanina, Olga S.; Filatov, Alexander V.; Vorobjev, Ivan A.; Ataullakhanov, Fazly

    2015-01-01

    We describe a method for leukocyte sorting by a microarray of anti-cluster-of-differentiation (anti-CD) antibodies and for preparation of the bound cells for morphological or cytochemical examination. The procedure results in a “sorted” smear with cells positive for certain surface antigens localised in predefined areas. The morphology and cytochemistry of the microarray-captured normal and neoplastic peripheral blood mononuclear cells are identical to the same characteristics in a smear. The microarray permits to determine the proportions of cells positive for the CD antigens on the microarray panel with high correlation with flow cytometry. Using the anti-CD microarray we show that normal granular lymphocytes and lymphocytes with radial segmentation of the nuclei are positive for CD3, CD8, CD16 or CD56 but not for CD4 or CD19. We also show that the described technique permits to obtain a pure leukemic cell population or to separate two leukemic cell populations on different antibody spots and to study their morphology or cytochemistry directly on the microarray. In cases of leukemias/lymphomas when circulating neoplastic cells are morphologically distinct, preliminary diagnosis can be suggested from full analysis of cell morphology, cytochemistry and their binding pattern on the microarray. PMID:26212756

  8. Development and Assessment of Whole-Genome Oligonucleotide Microarrays to Analyze an Anaerobic Microbial Community and its Responses to Oxidative Stress

    SciTech Connect

    Scholten, Johannes C.; Culley, David E.; Nie, Lei; Munn, Kyle J.; Chow, Lely; Brockman, Fred J.; Zhang, Weiwen

    2007-06-29

    The application of DNA microarray technology to investigate multiple-species microbial community presents great challenges. In this study, we reported the design and quality assessment of four whole genome oligonucleotide microarrays for two syntroph bacteria, Desulfovibrio vulgaris and Syntrophobacter fumaroxidans, and two archaeal methanogens, Methanosarcina barkeri and Methanospirillum hungatei, and their application to analyze global gene expression of this four-species microbial community in response to oxidative stress. In order to minimize the possible cross-hybridization, cross-genome comparison was performed to assure all probes unique to each genome so that the microarrays could provide species-level resolution. Microarray quality was validated by the good reproducibility of experimental measurements of multiple biological and analytical replicates. Microarray analysis showed that S. fumaroxidans and M. hungatei responded to the stress with up-regulation of several genes known to be involved in ROS detoxification, such as catalase and rubrerythrin in S. fumaroxidans and thioredoxin and heat shock protein Hsp20 in M. hungatei. Consistent with previous study in pure culture, the microarray analysis showed that genes involved in methane production and energy metabolism were down-regulated by oxidative stress in M. barkeri. However, D. vulgaris seemed less sensitive to the oxidative stress when grown in a community, with almost no gene up-regulated. The study demonstrated the successful application of microarray technology to multiple-species microbial community, and our preliminary results indicated that the approach can provide novel insights on the metabolic and regulatory networks within microbial communities.

  9. Anti-CD antibody microarray for human leukocyte morphology examination allows analyzing rare cell populations and suggesting preliminary diagnosis in leukemia.

    PubMed

    Khvastunova, Alina N; Kuznetsova, Sofya A; Al-Radi, Liubov S; Vylegzhanina, Alexandra V; Zakirova, Anna O; Fedyanina, Olga S; Filatov, Alexander V; Vorobjev, Ivan A; Ataullakhanov, Fazly

    2015-01-01

    We describe a method for leukocyte sorting by a microarray of anti-cluster-of-differentiation (anti-CD) antibodies and for preparation of the bound cells for morphological or cytochemical examination. The procedure results in a "sorted" smear with cells positive for certain surface antigens localised in predefined areas. The morphology and cytochemistry of the microarray-captured normal and neoplastic peripheral blood mononuclear cells are identical to the same characteristics in a smear. The microarray permits to determine the proportions of cells positive for the CD antigens on the microarray panel with high correlation with flow cytometry. Using the anti-CD microarray we show that normal granular lymphocytes and lymphocytes with radial segmentation of the nuclei are positive for CD3, CD8, CD16 or CD56 but not for CD4 or CD19. We also show that the described technique permits to obtain a pure leukemic cell population or to separate two leukemic cell populations on different antibody spots and to study their morphology or cytochemistry directly on the microarray. In cases of leukemias/lymphomas when circulating neoplastic cells are morphologically distinct, preliminary diagnosis can be suggested from full analysis of cell morphology, cytochemistry and their binding pattern on the microarray. PMID:26212756

  10. 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.

  11. An extremely simple method for fabricating 3D protein microarrays with an anti-fouling background and high protein capacity.

    PubMed

    Lin, Zhifeng; Ma, Yuhong; Zhao, Changwen; Chen, Ruichao; Zhu, Xing; Zhang, Lihua; Yan, Xu; Yang, Wantai

    2014-07-21

    Protein microarrays have become vital tools for various applications in biomedicine and bio-analysis during the past decade. The intense requirements for a lower detection limit and industrialization in this area have resulted in a persistent pursuit to fabricate protein microarrays with a low background and high signal intensity via simple methods. Here, we report on an extremely simple strategy to create three-dimensional (3D) protein microarrays with an anti-fouling background and a high protein capacity by photo-induced surface sequential controlled/living graft polymerization developed in our lab. According to this strategy, "dormant" groups of isopropyl thioxanthone semipinacol (ITXSP) were first introduced to a polymeric substrate through ultraviolet (UV)-induced surface abstraction of hydrogen, followed by a coupling reaction. Under visible light irradiation, the ITXSP groups were photolyzed to initiate surface living graft polymerization of poly(ethylene glycol) methyl methacrylate (PEGMMA), thus introducing PEG brushes to the substrate to generate a full anti-fouling background. Due to the living nature of this graft polymerization, there were still ITXSP groups on the chain ends of the PEG brushes. Therefore, by in situ secondary living graft cross-linking copolymerization of glycidyl methacrylate (GMA) and polyethylene glycol diacrylate (PEGDA), we could finally plant height-controllable cylinder microarrays of a 3D PEG network containing reactive epoxy groups onto the PEG brushes. Through a commonly used reaction of amine and epoxy groups, the proteins could readily be covalently immobilized onto the microarrays. This delicate design aims to overcome two universal limitations in protein microarrays: a full anti-fouling background can effectively eliminate noise caused by non-specific absorption and a 3D reactive network provides a larger protein-loading capacity to improve signal intensity. The results of non-specific protein absorption tests

  12. 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

  13. Microarray characterization of gene expression changes in blood during acute ethanol exposure

    PubMed Central

    2013-01-01

    Background As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we performed a DNA microarray analysis of human whole blood samples from a five-time point study of subjects administered ethanol orally, followed by breathalyzer analysis, to monitor blood alcohol concentration (BAC) to discover significant gene expression changes in response to the ethanol exposure. Methods Subjects were administered either orange juice or orange juice with ethanol. Blood samples were taken based on BAC and total RNA was isolated from PaxGene™ blood tubes. The amplified cDNA was used in microarray and quantitative real-time polymerase chain reaction (RT-qPCR) analyses to evaluate differential gene expression. Microarray data was analyzed in a pipeline fashion to summarize and normalize and the results evaluated for relative expression across time points with multiple methods. Candidate genes showing distinctive expression patterns in response to ethanol were clustered by pattern and further analyzed for related function, pathway membership and common transcription factor binding within and across clusters. RT-qPCR was used with representative genes to confirm relative transcript levels across time to those detected in microarrays. Results Microarray analysis of samples representing 0%, 0.04%, 0.08%, return to 0.04%, and 0.02% wt/vol BAC showed that changes in gene expression could be detected across the time course. The expression changes were verified by qRT-PCR. The candidate genes of interest (GOI) identified from the microarray analysis and clustered by expression pattern across the five BAC points showed seven coordinately expressed groups. Analysis showed function-based networks, shared transcription factor binding sites and signaling pathways for members of the clusters. These include hematological functions, innate immunity and inflammation functions, metabolic functions expected of ethanol metabolism, and pancreatic

  14. A New Generation Microarray for the Simultaneous Detection and Identification of Yersinia pestis and Bacillus anthracis in Food

    PubMed Central

    Goji, Noriko; MacMillan, Trevor; Amoako, Kingsley Kwaku

    2012-01-01

    The use of microarrays as a multiple analytic system has generated increased interest and provided a powerful analytical tool for the simultaneous detection of pathogens in a single experiment. A wide array of applications for this technology has been reported. A low density oligonucleotide microarray was generated from the genetic sequences of Y. pestis and B. anthracis and used to fabricate a microarray chip. The new generation chip, consisting of 2,240 spots in 4 quadrants with the capability of stripping/rehybridization, was designated as “Y-PESTIS/B-ANTHRACIS 4x2K Array.” The chip was tested for specificity using DNA from a panel of bacteria that may be potentially present in food. In all, 37 unique Y. pestis-specific and 83 B. anthracis-specific probes were identified. The microarray assay distinguished Y. pestis and B. anthracis from the other bacterial species tested and correctly identified the Y. pestis-specific oligonucleotide probes using DNA extracted from experimentally inoculated milk samples. Using a whole genome amplification method, the assay was able to detect as low as 1 ng genomic DNA as the start sample. The results suggest that oligonucleotide microarray can specifically detect and identify Y. pestis and B. anthracis and may be a potentially useful diagnostic tool for detecting and confirming the organisms in food during a bioterrorism event. PMID:23125935

  15. Transfer printing of transfected cell microarrays from poly(ethylene glycol)-oleyl surfaces onto biological hydrogels.

    PubMed

    Yamaguchi, Satoshi; Komiya, Senori; Matsunuma, Erika; Yamahira, Shinya; Kihara, Takanori; Miyake, Jun; Nagamune, Teruyuki

    2013-12-01

    We have developed a novel technique for constructing microarrays of transfected mammalian cells on or in extracellular matrix (ECM) hydrogels by transfer printing from patterned poly(ethylene glycol) (PEG)-oleyl surfaces. A mixed solution of small interfering RNA (siRNA) and a transfection reagent was spotted on PEG-oleyl-coated glass slides using an ink-jet printer, and the cells were then transiently immobilized on the patterned transfection mixtures. After overlaying an ECM hydrogel sheet onto the immobilized cells, the cells sandwiched between the glass slide and the hydrogel sheet were incubated at 37°C for simultaneous transfection of siRNA into cells and adhesion of cells to the hydrogel sheet. Transfer of the adhered, transfected cells was completed by peeling off the hydrogel sheet. The knockdown of a model gene in the transferred cell microarray by the transfected siRNA was successfully confirmed. Transfected cell microarrays were also embedded within three-dimensional ECM hydrogels. In the three-dimensional hydrogel, the inhibition effect of siRNA on cancer cell invasion was evaluated by quantifying the size of cell clusters on the microarrays. These results indicate that transfection of cell microarrays on or in a biological matrix is a promising technique for high-throughput screening of disease-related genes by direct observation of cellular phenomena in a physiologically relevant environment. PMID:23893595

  16. Computerized system for recognition of autism on the basis of gene expression microarray data.

    PubMed

    Latkowski, Tomasz; Osowski, Stanislaw

    2015-01-01

    The aim of this paper is to provide a means to recognize a case of autism using gene expression microarrays. The crucial task is to discover the most important genes which are strictly associated with autism. The paper presents an application of different methods of gene selection, to select the most representative input attributes for an ensemble of classifiers. The set of classifiers is responsible for distinguishing autism data from the reference class. Simultaneous application of a few gene selection methods enables analysis of the ill-conditioned gene expression matrix from different points of view. The results of selection combined with a genetic algorithm and SVM classifier have shown increased accuracy of autism recognition. Early recognition of autism is extremely important for treatment of children and increases the probability of their recovery and return to normal social communication. The results of this research can find practical application in early recognition of autism on the basis of gene expression microarray analysis. PMID:25464350

  17. 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

  18. Estimation of Prognostic Marker Genes by Public Microarray Data in Patients with Ovarian Serous Cystadenocarcinoma

    PubMed Central

    Yang, San-Duk; Jang, Se-Song; Han, Jeong A.; Park, Hyun-Seok

    2016-01-01

    Purpose Lymphatic invasion (LI) is regarded as a predictor of the aggressiveness of ovarian cancer (OC). However, LI is not always the major determinant of long-term patient survival. To establish proper diagnosis and treatment for OC, we analyzed differentially expressed genes (DEGs) for patients with serous epithelial OC, with or without LI, who did or did not survive for 5 years. Materials and Methods Gene expression data from 63 patients with OC and LI, and 35 patients with OC but without LI, were investigated using an Affymetrix Human Genome U133 Array and analyzed using The Cancer Genome Atlas (TCGA) database. Among these 98 patients, 16 survived for 5 years or more. DEGs were identified using the Bioconductor R package, and their functions were analyzed using the DAVID web tool. Results We found 55 significant DEGs (p<0.01) from the patients with LI and 20 highly significant DEGs (p<0.001) from those without it. Pathway analysis showed that DEGs associated with carbohydrate metabolism or with renal cell carcinoma pathways were enriched in the patients with and without LI, respectively. Using the top five prognostic marker genes, we generated survival scores that could be used to predict the 5-year survival of patients with OC without LI. Conclusion The DEGs identified in this study could be used to elucidate the mechanism of tumor progression and to guide the prognosis and treatment of patients with serous OC but without LI. PMID:27189279

  19. A Combinational Clustering Based Method for cDNA Microarray Image Segmentation

    PubMed Central

    Shao, Guifang; Li, Tiejun; Zuo, Wangda; Wu, Shunxiang; Liu, Tundong

    2015-01-01

    Microarray technology plays an important role in drawing useful biological conclusions by analyzing thousands of gene expressions simultaneously. Especially, image analysis is a key step in microarray analysis and its accuracy strongly depends on segmentation. The pioneering works of clustering based segmentation have shown that k-means clustering algorithm and moving k-means clustering algorithm are two commonly used methods in microarray image processing. However, they usually face unsatisfactory results because the real microarray image contains noise, artifacts and spots that vary in size, shape and contrast. To improve the segmentation accuracy, in this article we present a combination clustering based segmentation approach that may be more reliable and able to segment spots automatically. First, this new method starts with a very simple but effective contrast enhancement operation to improve the image quality. Then, an automatic gridding based on the maximum between-class variance is applied to separate the spots into independent areas. Next, among each spot region, the moving k-means clustering is first conducted to separate the spot from background and then the k-means clustering algorithms are combined for those spots failing to obtain the entire boundary. Finally, a refinement step is used to replace the false segmentation and the inseparable ones of missing spots. In addition, quantitative comparisons between the improved method and the other four segmentation algorithms--edge detection, thresholding, k-means clustering and moving k-means clustering--are carried out on cDNA microarray images from six different data sets. Experiments on six different data sets, 1) Stanford Microarray Database (SMD), 2) Gene Expression Omnibus (GEO), 3) Baylor College of Medicine (BCM), 4) Swiss Institute of Bioinformatics (SIB), 5) Joe DeRisi’s individual tiff files (DeRisi), and 6) University of California, San Francisco (UCSF), indicate that the improved approach is

  20. A Combinational Clustering Based Method for cDNA Microarray Image Segmentation.

    PubMed

    Shao, Guifang; Li, Tiejun; Zuo, Wangda; Wu, Shunxiang; Liu, Tundong

    2015-01-01

    Microarray technology plays an important role in drawing useful biological conclusions by analyzing thousands of gene expressions simultaneously. Especially, image analysis is a key step in microarray analysis and its accuracy strongly depends on segmentation. The pioneering works of clustering based segmentation have shown that k-means clustering algorithm and moving k-means clustering algorithm are two commonly used methods in microarray image processing. However, they usually face unsatisfactory results because the real microarray image contains noise, artifacts and spots that vary in size, shape and contrast. To improve the segmentation accuracy, in this article we present a combination clustering based segmentation approach that may be more reliable and able to segment spots automatically. First, this new method starts with a very simple but effective contrast enhancement operation to improve the image quality. Then, an automatic gridding based on the maximum between-class variance is applied to separate the spots into independent areas. Next, among each spot region, the moving k-means clustering is first conducted to separate the spot from background and then the k-means clustering algorithms are combined for those spots failing to obtain the entire boundary. Finally, a refinement step is used to replace the false segmentation and the inseparable ones of missing spots. In addition, quantitative comparisons between the improved method and the other four segmentation algorithms--edge detection, thresholding, k-means clustering and moving k-means clustering--are carried out on cDNA microarray images from six different data sets. Experiments on six different data sets, 1) Stanford Microarray Database (SMD), 2) Gene Expression Omnibus (GEO), 3) Baylor College of Medicine (BCM), 4) Swiss Institute of Bioinformatics (SIB), 5) Joe DeRisi's individual tiff files (DeRisi), and 6) University of California, San Francisco (UCSF), indicate that the improved approach is

  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. 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

  4. Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures

    PubMed Central

    Tan, Meng P; Smith, Erin N; Broach, James R; Floudas, Christodoulos A

    2008-01-01

    Background DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting information on this genomic scale, and a first step towards the rapid and comprehensive interpretation of this data is gene clustering with respect to the expression patterns. Classifying genes into clusters can lead to interesting biological insights. In this study, we describe an iterative clustering approach to uncover biologically coherent structures from DNA microarray data based on a novel clustering algorithm EP_GOS_Clust. Results