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Sample records for bacterial microarray experiments

  1. OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments

    Directory of Open Access Journals (Sweden)

    Arkin Adam P

    2006-01-01

    Full Text Available Abstract Background Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. Results OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. Conclusion Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at http://microbesonline.org/OpWise.

  2. OpWise: Operons aid the identification of differentially expressedgenes in bacterial microarray experiments

    Energy Technology Data Exchange (ETDEWEB)

    Price, Morgan N.; Arkin, Adam P.; Alm, Eric J.

    2005-11-23

    Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. Results-OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at http://microbesonline.org/OpWise.

  3. Innovative DNA microarray design for bacterial flora composition evaluation

    OpenAIRE

    Huyghe, Antoine

    2009-01-01

    During the past decade, the advent of new molecular techniques has led to enormous progress in biology, notably with the development of DNA microarray technology. This technology allows monitoring simultaneously the expression of thousands of genes from a given organism. DNA microarrays have been used in a variety of applications, including the characterization of bacteria in biological samples. In this thesis, two distinct DNA microarray approaches for the characterization of bacterial flora...

  4. Assessing Bacterial Interactions Using Carbohydrate-Based Microarrays

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    Andrea Flannery

    2015-12-01

    Full Text Available 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.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2003-05-01

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

  7. Broad spectrum microarray for fingerprint-based bacterial species identification

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    Frey Jürg E

    2010-02-01

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

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

    OpenAIRE

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

    2005-01-01

    In an effort towards adapting new and defensible methods for assessing and managing the risk posed by microbial pollution, we evaluated the utility of oligonucleotide microarrays for bacterial source tracking (BST) of environmental Enterococcus sp. isolates derived from various host sources. Current bacterial source tracking approaches rely on various phenotypic and genotypic methods to identify sources of bacterial contamination resulting from point or non-point pollution. For this study Ent...

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

    Directory of Open Access Journals (Sweden)

    John S. Furey

    2005-04-01

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

  10. Development and application of the active surveillance of pathogens microarray to monitor bacterial gene flux

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    Hinds Jason

    2008-10-01

    Full Text Available Abstract Background Human and animal health is constantly under threat by emerging pathogens that have recently acquired genetic determinants that enhance their survival, transmissibility and virulence. We describe the construction and development of an Active Surveillance of Pathogens (ASP oligonucleotide microarray, designed to 'actively survey' the genome of a given bacterial pathogen for virulence-associated genes. Results The microarray consists of 4958 reporters from 151 bacterial species and include genes for the identification of individual bacterial species as well as mobile genetic elements (transposons, plasmid and phage, virulence genes and antibiotic resistance genes. The ASP microarray was validated with nineteen bacterial pathogens species, including Francisella tularensis, Clostridium difficile, Staphylococcus aureus, Enterococcus faecium and Stenotrophomonas maltophilia. The ASP microarray identified these bacteria, and provided information on potential antibiotic resistance (eg sufamethoxazole resistance and sulfonamide resistance and virulence determinants including genes likely to be acquired by horizontal gene transfer (e.g. an alpha-haemolysin. Conclusion The ASP microarray has potential in the clinic as a diagnostic tool, as a research tool for both known and emerging pathogens, and as an early warning system for pathogenic bacteria that have been recently modified either naturally or deliberately.

  11. Microarray-based identification of clinically relevant vaginal bacteria in relation to bacterial vaginosis

    NARCIS (Netherlands)

    Dols, J.A.M.; Smit, P.W.; Kort, R.; Reid, G.; Schuren, F.H.J.; Tempelman, H.; Bontekoe, T.R.; Korporaal, H.; Boon, M.E.

    2011-01-01

    Objective: The objective was to examine the use of a tailor-made DNA microarray containing probes representing the vaginal microbiota to examine bacterial vaginosis. Study Design: One hundred one women attending a health center for HIV testing in South Africa were enrolled. Stained, liquid-based cyt

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

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    Vetter Guillaume

    2008-09-01

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

  13. A methodology for global validation of microarray experiments

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    Sladek Robert

    2006-07-01

    Full Text Available Abstract Background DNA microarrays are popular tools for measuring gene expression of biological samples. This ever increasing popularity is ensuring that a large number of microarray studies are conducted, many of which with data publicly available for mining by other investigators. Under most circumstances, validation of differential expression of genes is performed on a gene to gene basis. Thus, it is not possible to generalize validation results to the remaining majority of non-validated genes or to evaluate the overall quality of these studies. Results We present an approach for the global validation of DNA microarray experiments that will allow researchers to evaluate the general quality of their experiment and to extrapolate validation results of a subset of genes to the remaining non-validated genes. We illustrate why the popular strategy of selecting only the most differentially expressed genes for validation generally fails as a global validation strategy and propose random-stratified sampling as a better gene selection method. We also illustrate shortcomings of often-used validation indices such as overlap of significant effects and the correlation coefficient and recommend the concordance correlation coefficient (CCC as an alternative. Conclusion We provide recommendations that will enhance validity checks of microarray experiments while minimizing the need to run a large number of labour-intensive individual validation assays.

  14. Microarray Analysis to Monitor Bacterial Cell Wall Homeostasis.

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    Hong, Hee-Jeon; Hesketh, Andy

    2016-01-01

    Transcriptomics, the genome-wide analysis of gene transcription, has become an important tool for characterizing and understanding the signal transduction networks operating in bacteria. Here we describe a protocol for quantifying and interpreting changes in the transcriptome of Streptomyces coelicolor that take place in response to treatment with three antibiotics active against different stages of peptidoglycan biosynthesis. The results defined the transcriptional responses associated with cell envelope homeostasis including a generalized response to all three antibiotics involving activation of transcription of the cell envelope stress sigma factor σ(E), together with elements of the stringent response, and of the heat, osmotic, and oxidative stress regulons. Many antibiotic-specific transcriptional changes were identified, representing cellular processes potentially important for tolerance to each antibiotic. The principles behind the protocol are transferable to the study of cell envelope homeostatic mechanisms probed using alternative chemical/environmental insults or in other bacterial strains. PMID:27311662

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

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    Toome Kadri

    2011-02-01

    Full Text Available Abstract 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.

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

    LENUS (Irish Health Repository)

    Scheler, Ott

    2011-02-28

    Abstract 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.

  17. Using DNA Microarrays To Identify Library-Independent Markers for Bacterial Source Tracking

    OpenAIRE

    Soule, Marilyn; Kuhn, Edward; Loge, Frank; Gay, John; Call, Douglas R.

    2006-01-01

    Bacterial source tracking is used to apportion fecal pollution among putative sources. Within this context, library-independent markers are genetic or phenotypic traits that can be used to identify the host origin without a need for library-dependent classification functions. The objective of this project was to use mixed-genome Enterococcus microarrays to identify library-independent markers. Separate shotgun libraries were prepared for five host groups (cow, dog, elk/deer, human, and waterf...

  18. Visualization of Growth Curve Data from Phenotype MicroarrayExperiments

    Energy Technology Data Exchange (ETDEWEB)

    Jacobsen, Janet S.; Joyner, Dominique C.; Borglin, Sharon E.; Hazen, Terry C.; Arkin, Adam P.; Bethel, E. Wes

    2007-04-19

    Phenotype microarrays provide a technology to simultaneouslysurvey the response of an organism to nearly 2,000 substrates, includingcarbon, nitrogen and potassium sources; varying pH; varying saltconcentrations; and antibiotics. In order to more quickly and easily viewand compare the large number of growth curves produced by phenotypemicroarray experiments, we have developed software to produce and displaycolor images, each of which corresponds to a set of 96 growth curves.Using color images to represent growth curves data has proven to be avaluable way to assess experiment quality, compare replicates, facilitatecomparison of the responses of different organisms, and identifysignificant phenotypes. The color images are linked to traditional plotsof growth versus time, as well as to information about the experiment,organism, and substrate. In order to share and view information and dataproject-wide, all information, plots, and data are accessible using onlya Web browser.

  19. Systematic interpretation of microarray data using experiment annotations

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    Frohme Marcus

    2006-12-01

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

  20. Design issues in toxicogenomics using DNA microarray experiment

    International Nuclear Information System (INIS)

    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

  1. Background Adjustment for DNA Microarrays Using a Database of Microarray Experiments

    OpenAIRE

    Sui, Yunxia; Zhao, Xiaoyue; Speed, Terence P.; Wu, Zhijin

    2009-01-01

    DNA microarrays have become an indispensable technique in biomedical research. The raw measurements from microarrays undergo a number of preprocessing steps before the data are converted to the genomic level for further analysis. Background adjustment is an important step in preprocessing. Estimating background noise has been challenging because background levels vary a lot from probe to probe, yet there are limited observations on each probe. Most current methods have used the empirical Baye...

  2. Sample size for detecting differentially expressed genes in microarray experiments

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    Li Jiangning

    2004-11-01

    Full Text Available Abstract Background Microarray experiments are often performed with a small number of biological replicates, resulting in low statistical power for detecting differentially expressed genes and concomitant high false positive rates. While increasing sample size can increase statistical power and decrease error rates, with too many samples, valuable resources are not used efficiently. The issue of how many replicates are required in a typical experimental system needs to be addressed. Of particular interest is the difference in required sample sizes for similar experiments in inbred vs. outbred populations (e.g. mouse and rat vs. human. Results We hypothesize that if all other factors (assay protocol, microarray platform, data pre-processing were equal, fewer individuals would be needed for the same statistical power using inbred animals as opposed to unrelated human subjects, as genetic effects on gene expression will be removed in the inbred populations. We apply the same normalization algorithm and estimate the variance of gene expression for a variety of cDNA data sets (humans, inbred mice and rats comparing two conditions. Using one sample, paired sample or two independent sample t-tests, we calculate the sample sizes required to detect a 1.5-, 2-, and 4-fold changes in expression level as a function of false positive rate, power and percentage of genes that have a standard deviation below a given percentile. Conclusions Factors that affect power and sample size calculations include variability of the population, the desired detectable differences, the power to detect the differences, and an acceptable error rate. In addition, experimental design, technical variability and data pre-processing play a role in the power of the statistical tests in microarrays. We show that the number of samples required for detecting a 2-fold change with 90% probability and a p-value of 0.01 in humans is much larger than the number of samples commonly used in

  3. Identification of self-consistent modulons from bacterial microarray expression data with the help of structured regulon gene sets

    KAUST Repository

    Permina, Elizaveta A.

    2013-01-01

    Identification of bacterial modulons from series of gene expression measurements on microarrays is a principal problem, especially relevant for inadequately studied but practically important species. Usage of a priori information on regulatory interactions helps to evaluate parameters for regulatory subnetwork inference. We suggest a procedure for modulon construction where a seed regulon is iteratively updated with genes having expression patterns similar to those for regulon member genes. A set of genes essential for a regulon is used to control modulon updating. Essential genes for a regulon were selected as a subset of regulon genes highly related by different measures to each other. Using Escherichia coli as a model, we studied how modulon identification depends on the data, including the microarray experiments set, the adopted relevance measure and the regulon itself. We have found that results of modulon identification are highly dependent on all parameters studied and thus the resulting modulon varies substantially depending on the identification procedure. Yet, modulons that were identified correctly displayed higher stability during iterations, which allows developing a procedure for reliable modulon identification in the case of less studied species where the known regulatory interactions are sparse. Copyright © 2013 Taylor & Francis.

  4. Microarray Analysis of the Transcriptome for Bacterial Wilt Resistance in Pepper (Capsicum annuum L.

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    Jihyun HWANG

    2011-11-01

    Full Text Available Ralstonia solanacearum causes one of the most common soil-borne vascular diseases of diverse plant species, including many solanaceous crops such as tomato and pepper. The resulting disease, bacterial wilt (BW, is devastating and difficult to control using conventional approaches. The aim of this study was to investigate the differentially expressed genes in pepper root systems in response to infection by R. solanacearum. DNA microarray (Capsicum annuum 135K Microarray v3.0 Gene Expression platform analyses were performed using a susceptible genotype, ‘Chilbok’, and a resistant genotype, ‘KC350’, at 3 time points (1, 3, and 6 days post inoculation. It has been identified 115 resistance-specific genes (R-response genes and 109 susceptibility-specific genes (S-response gene, which were up-regulated in 1 genotype, but down-regulated in the other genotype. Gene Ontology (GO analysis for functional categorization indicated that many R-response genes were related to genes that function in xyloglucan biosynthesis and cell wall organization, while S-response genes were involved in the response to stress and cell death. The expression of genes encoding xyloglucan endotransglycosylase/hydrolase (XTH and β-galactosidase were verified by real-time RT-PCR at an early time point of R. solanacearum infection. The results supported the idea that rapidly induced XTH expression in ‘KC350’ may play an important role in the restructuring and reinforcement of the cell wall and restrict bacterial movement in xylem vessels. In addition, induced expression of β-galactosidase in R. solanacearum-infected ‘Chilbok’ implied that degradation of the cell wall structure in vascular tissues by β-galactosidase might be an important factor facilitating R. solanacearum invasion of and movement in susceptible host plants.

  5. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA

    NARCIS (Netherlands)

    Nueda, M.J.; Conesa, A.; Westerhuis, J.A.; Hoefsloot, H.C.J.; Smilde, A.K.; Talón, M.; Ferrer, A.

    2007-01-01

    Motivation: Designed microarray experiments are used to investigate the effects that controlled experimental factors have on gene expression and learn about the transcriptional responses associated with external variables. In these datasets, signals of interest coexist with varying sources of unwant

  6. poolMC: Smart pooling of mRNA samples in microarray experiments

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    Schiefelbein John

    2010-06-01

    Full Text Available Abstract Background Typically, pooling of mRNA samples in microarray experiments implies mixing mRNA from several biological-replicate samples before hybridization onto a microarray chip. Here we describe an alternative smart pooling strategy in which different samples, not necessarily biological replicates, are pooled in an information theoretic efficient way. Further, each sample is tested on multiple chips, but always in pools made up of different samples. The end goal is to exploit the compressibility of microarray data to reduce the number of chips used and increase the robustness to noise in measurements. Results A theoretical framework to perform smart pooling of mRNA samples in microarray experiments was established and the software implementation of the pooling and decoding algorithms was developed in MATLAB. A proof-of-concept smart pooled experiment was performed using validated biological samples on commercially available gene chips. Differential-expression analysis of the smart pooled data was performed and compared against the unpooled control experiment. Conclusions The theoretical developments and experimental demonstration in this paper provide a useful starting point to investigate smart pooling of mRNA samples in microarray experiments. Although the smart pooled experiment did not compare favorably with the control, the experiment highlighted important conditions for the successful implementation of smart pooling - linearity of measurements, sparsity in data, and large experiment size.

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

    Science.gov (United States)

    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

  8. Minimum Information About a Microarray Experiment (MIAME – Successes, Failures, Challenges

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    Alvis Brazma

    2009-01-01

    Full Text Available The Minimum Information About a Microarray Experiment (known as MIAME guidelines describe information that needs to be provided to enable the interpretation of the results of a microarray-based experiment unambiguously. The MIAME guidelines were developed by the Microarray Gene Expression Data (MGED Society. Since the MIAME position paper was published in 2001, it has been cited in the scientific literature well over a thousand times. MIAME has been replicated for many other technologies, the major data repositories are supporting MIAME, and most scientific journals have adopted MIAME guidelines as a requirement for publishing. With the advent of new-generation sequencing technology, MIAME faces new challenges. To address this, the MGED Society has proposed new guidelines, i.e., Minimum Information about a high-throughput SeQuencing Experiment (MINSEQE. Here we present analysis of the reasons for the success of MIAME, as well as discuss where it has failed, and the challenges it faces.

  9. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA.

    NARCIS (Netherlands)

    M.J. Nueda; A. Conessa; J.A. Westerhuis; H.C.J. Hoefsloot; A.K. Smilde; M. Talon; A. Ferrer

    2007-01-01

    In this work, we develop the application of the Analysis of variance-simultaneous component analysis (ANOVA-SCA) Smilde et al. Bioinformatics, (2005) to the analysis of multiple series time course microarray data as an example of multifactorial gene expression profiling experiments. We denoted this

  10. Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial) Pathogens.

    Science.gov (United States)

    Kostić, Tanja; Sessitsch, Angela

    2011-10-14

    Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples.

  11. Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial Pathogens

    Directory of Open Access Journals (Sweden)

    Tanja Kostić

    2011-10-01

    Full Text Available Reliable and sensitive pathogen detection in clinical and environmental (including food and water samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i specificity; (ii sensitivity; (iii multiplexing potential; (iv robustness; (v speed; (vi automation potential; and (vii low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples.

  12. The construction and use of bacterial DNA microarrays based on an optimized two-stage PCR strategy

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    Pesta David

    2003-06-01

    Full Text Available Abstract Background DNA microarrays are a powerful tool with important applications such as global gene expression profiling. Construction of bacterial DNA microarrays from genomic sequence data using a two-stage PCR amplification approach for the production of arrayed DNA is attractive because it allows, in principal, the continued re-amplification of DNA fragments and facilitates further utilization of the DNA fragments for additional uses (e.g. over-expression of protein. We describe the successful construction and use of DNA microarrays by the two-stage amplification approach and discuss the technical challenges that were met and resolved during the project. Results Chimeric primers that contained both gene-specific and shared, universal sequence allowed the two-stage amplification of the 3,168 genes identified on the genome of Synechocystis sp. PCC6803, an important prokaryotic model organism for the study of oxygenic photosynthesis. The gene-specific component of the primer was of variable length to maintain uniform annealing temperatures during the 1st round of PCR synthesis, and situated to preserve full-length ORFs. Genes were truncated at 2 kb for efficient amplification, so that about 92% of the PCR fragments were full-length genes. The two-stage amplification had the additional advantage of normalizing the yield of PCR products and this improved the uniformity of DNA features robotically deposited onto the microarray surface. We also describe the techniques utilized to optimize hybridization conditions and signal-to-noise ratio of the transcription profile. The inter-lab transportability was demonstrated by the virtual error-free amplification of the entire genome complement of 3,168 genes using the universal primers in partner labs. The printed slides have been successfully used to identify differentially expressed genes in response to a number of environmental conditions, including salt stress. Conclusions The technique detailed

  13. DNA microarray analysis of Staphylococcus aureus causing bloodstream infection: bacterial genes associated with mortality?

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    Blomfeldt, A; Aamot, H V; Eskesen, A N; Monecke, S; White, R A; Leegaard, T M; Bjørnholt, J V

    2016-08-01

    Providing evidence for microbial genetic determinants' impact on outcome in Staphylococcus aureus bloodstream infections (SABSI) is challenging due to the complex and dynamic microbe-host interaction. Our recent population-based prospective study reported an association between the S. aureus clonal complex (CC) 30 genotype and mortality in SABSI patients. This follow-up investigation aimed to examine the genetic profiles of the SABSI isolates and test the hypothesis that specific genetic characteristics in S. aureus are associated with mortality. SABSI isolates (n = 305) and S. aureus CC30 isolates from asymptomatic nasal carriers (n = 38) were characterised by DNA microarray analysis and spa typing. Fisher's exact test, least absolute shrinkage and selection operator (LASSO) and elastic net regressions were performed to discern within four groups defined by patient outcome and characteristics. No specific S. aureus genetic determinants were found to be associated with mortality in SABSI patients. By applying LASSO and elastic net regressions, we found evidence suggesting that agrIII and cna were positively and setC (=selX) and seh were negatively associated with S. aureus CC30 versus non-CC30 isolates. The genes chp and sak, encoding immune evasion molecules, were found in higher frequencies in CC30 SABSI isolates compared to CC30 carrier isolates, indicating a higher virulence potential. In conclusion, no specific S. aureus genes were found to be associated with mortality by DNA microarray analysis and state-of-the-art statistical analyses. The next natural step is to test the hypothesis in larger samples with higher resolution methods, like whole genome sequencing. PMID:27177754

  14. A nested parallel experiment demonstrates differences in intensity-dependence between RNA-seq and microarrays.

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    Robinson, David G; Wang, Jean Y; Storey, John D

    2015-11-16

    Understanding the differences between microarray and RNA-Seq technologies for measuring gene expression is necessary for informed design of experiments and choice of data analysis methods. Previous comparisons have come to sometimes contradictory conclusions, which we suggest result from a lack of attention to the intensity-dependent nature of variation generated by the technologies. To examine this trend, we carried out a parallel nested experiment performed simultaneously on the two technologies that systematically split variation into four stages (treatment, biological variation, library preparation and chip/lane noise), allowing a separation and comparison of the sources of variation in a well-controlled cellular system, Saccharomyces cerevisiae. With this novel dataset, we demonstrate that power and accuracy are more dependent on per-gene read depth in RNA-Seq than they are on fluorescence intensity in microarrays. However, we carried out quantitative PCR validations which indicate that microarrays may demonstrate greater systematic bias in low-intensity genes than in RNA-seq. PMID:26130709

  15. Methods for interpreting lists of affected genes obtained in a DNA microarray experiment

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    Hedegaard Jakob

    2009-07-01

    Full Text Available Abstract Background The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. Results Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. Conclusion It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experiment.

  16. Parents' Experience with Pediatric Microarray: Transferrable Lessons in the Era of Genomic Counseling.

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    Hayeems, R Z; Babul-Hirji, R; Hoang, N; Weksberg, R; Shuman, C

    2016-04-01

    Advances in genome-based microarray and sequencing technologies hold tremendous promise for understanding, better-managing and/or preventing disease and disease-related risk. Chromosome microarray technology (array based comparative genomic hybridization [aCGH]) is widely utilized in pediatric care to inform diagnostic etiology and medical management. Less clear is how parents experience and perceive the value of this technology. This study explored parents' experiences with aCGH in the pediatric setting, focusing on how they make meaning of various types of test results. We conducted in-person or telephone-based semi-structured interviews with parents of 21 children who underwent aCGH testing in 2010. Transcripts were coded and analyzed thematically according to the principles of interpretive description. We learned that parents expect genomic tests to be of personal use; their experiences with aCGH results characterize this use as intrinsic in the test's ability to provide a much sought-after answer for their child's condition, and instrumental in its ability to guide care, access to services, and family planning. In addition, parents experience uncertainty regardless of whether aCGH results are of pathogenic, uncertain, or benign significance; this triggers frustration, fear, and hope. Findings reported herein better characterize the notion of personal utility and highlight the pervasive nature of uncertainty in the context of genomic testing. Empiric research that links pre-test counseling content and psychosocial outcomes is warranted to optimize patient care. PMID:26259530

  17. Microarray Analysis of Human Vascular Smooth Muscle Cell Responses to Bacterial Lipopolysaccharide

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    Joe Minta

    2007-01-01

    Full Text Available Accumulating evidence suggest a causal role of bacterial and viral infections in atherogenesis. Bacterial lipopolysaccharide (LPS has been shown to stimulate resting vascular smooth muscle cells (SMC with the production of inflammatory cytokines and modulation of quiescent cells to the proliferative and synthetic phenotype. To comprehensively identify biologically important genes associated with LPS-induced SMC phenotype modulation, we compared the transcriptomes of quiescent human coronary artery SMC and cells treated with LPS for 4 and 22 h. The SMCs responded robustly to LPS treatment by the differential regulation of several genes involved in chromatin remodeling, transcription regulation, translation, signal transduction, metabolism, host defense, cell proliferation, apoptosis, matrix formation, adhesion and motility and suggest that the induction of clusters of genes involved in cell proliferation, migration and ECM production may be the main force that drives the LPS-induced phenotypic modulation of SMC rather than the differential expression of a single gene or a few genes. An interesting observation was the early and dramatic induction of four tightly clustered interferon-induced genes with tetratricopeptide repeats (IFIT1, 2, 4, 5. siRNA knock-down of IFIT1 in SMC was found to be associated with a remarkable up-regulation of TP53, CDKN1A and FOS, suggesting that IFIT1 may play a role in cell proliferation. Our data provide a comprehensive list of genes involved in LPS biology and underscore the important role of LPS in SMC activation and phenotype modulation which is a pivotal event in the onset of atherogenesis.

  18. HAMSTER: visualizing microarray experiments as a set of minimum spanning trees

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    Harada Hajime

    2009-11-01

    Full Text Available Abstract Background Visualization tools allow researchers to obtain a global view of the interrelationships between the probes or experiments of a gene expression (e.g. microarray data set. Some existing methods include hierarchical clustering and k-means. In recent years, others have proposed applying minimum spanning trees (MST for microarray clustering. Although MST-based clustering is formally equivalent to the dendrograms produced by hierarchical clustering under certain conditions; visually they can be quite different. Methods HAMSTER (Helpful Abstraction using Minimum Spanning Trees for Expression Relations is an open source system for generating a set of MSTs from the experiments of a microarray data set. While previous works have generated a single MST from a data set for data clustering, we recursively merge experiments and repeat this process to obtain a set of MSTs for data visualization. Depending on the parameters chosen, each tree is analogous to a snapshot of one step of the hierarchical clustering process. We scored and ranked these trees using one of three proposed schemes. HAMSTER is implemented in C++ and makes use of Graphviz for laying out each MST. Results We report on the running time of HAMSTER and demonstrate using data sets from the NCBI Gene Expression Omnibus (GEO that the images created by HAMSTER offer insights that differ from the dendrograms of hierarchical clustering. In addition to the C++ program which is available as open source, we also provided a web-based version (HAMSTER+ which allows users to apply our system through a web browser without any computer programming knowledge. Conclusion Researchers may find it helpful to include HAMSTER in their microarray analysis workflow as it can offer insights that differ from hierarchical clustering. We believe that HAMSTER would be useful for certain types of gradient data sets (e.g time-series data and data that indicate relationships between cells/tissues. Both

  19. A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments

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    Chinnaiyan Arul M

    2007-09-01

    Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.

  20. Multi-TGDR: a regularization method for multi-class classification in microarray experiments.

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    Suyan Tian

    Full Text Available BACKGROUND: As microarray technology has become mature and popular, the selection and use of a small number of relevant genes for accurate classification of samples has arisen as a hot topic in the circles of biostatistics and bioinformatics. However, most of the developed algorithms lack the ability to handle multiple classes, arguably a common application. Here, we propose an extension to an existing regularization algorithm, called Threshold Gradient Descent Regularization (TGDR, to specifically tackle multi-class classification of microarray data. When there are several microarray experiments addressing the same/similar objectives, one option is to use a meta-analysis version of TGDR (Meta-TGDR, which considers the classification task as a combination of classifiers with the same structure/model while allowing the parameters to vary across studies. However, the original Meta-TGDR extension did not offer a solution to the prediction on independent samples. Here, we propose an explicit method to estimate the overall coefficients of the biomarkers selected by Meta-TGDR. This extension permits broader applicability and allows a comparison between the predictive performance of Meta-TGDR and TGDR using an independent testing set. RESULTS: Using real-world applications, we demonstrated the proposed multi-TGDR framework works well and the number of selected genes is less than the sum of all individualized binary TGDRs. Additionally, Meta-TGDR and TGDR on the batch-effect adjusted pooled data approximately provided same results. By adding Bagging procedure in each application, the stability and good predictive performance are warranted. CONCLUSIONS: Compared with Meta-TGDR, TGDR is less computing time intensive, and requires no samples of all classes in each study. On the adjusted data, it has approximate same predictive performance with Meta-TGDR. Thus, it is highly recommended.

  1. Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

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    Farztdinov Vadim

    2012-11-01

    Full Text Available Abstract Background Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. Results A new method of finding differentially expressed genes, called distributional fold change (DFC test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets

  2. EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

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    Craven Mark

    2009-09-01

    Full Text Available Abstract Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web

  3. Identification of non-random sequence properties in groups of signature peptides obtained in random sequence peptide microarray experiments.

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    Kuznetsov, Igor B

    2016-05-01

    Immunosignaturing is an emerging experimental technique that uses random sequence peptide microarrays to detect antibodies produced by the immune system in response to a particular disease. Two important questions regarding immunosignaturing are "Do microarray peptides that exhibit a strong affinity to a given type of antibodies share common sequence properties?" and "If so, what are those properties?" In this work, three statistical tests designed to detect non-random patterns in the amino acid makeup of a group of microarray peptides are presented. One test detects patterns of significantly biased amino acid usage, whereas the other two detect patterns of significant bias in the biochemical properties. These tests do not require a large number of peptides per group. The tests were applied to analyze 19 groups of peptides identified in immunosignaturing experiments as being specific for antibodies produced in response to various types of cancer and other diseases. The positional distribution of the biochemical properties of the amino acids in these 19 peptide groups was also studied. Remarkably, despite the random nature of the sequence libraries used to design the microarrays, a unique group-specific non-random pattern was identified in the majority of the peptide groups studied. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 318-329, 2016. PMID:27037995

  4. Information criterion-based clustering with order-restricted candidate profiles in short time-course microarray experiments

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    Zhang Baoxue

    2009-05-01

    Full Text Available Abstract Background Time-course microarray experiments produce vector gene expression profiles across a series of time points. Clustering genes based on these profiles is important in discovering functional related and co-regulated genes. Early developed clustering algorithms do not take advantage of the ordering in a time-course study, explicit use of which should allow more sensitive detection of genes that display a consistent pattern over time. Peddada et al. 1 proposed a clustering algorithm that can incorporate the temporal ordering using order-restricted statistical inference. This algorithm is, however, very time-consuming and hence inapplicable to most microarray experiments that contain a large number of genes. Its computational burden also imposes difficulty to assess the clustering reliability, which is a very important measure when clustering noisy microarray data. Results We propose a computationally efficient information criterion-based clustering algorithm, called ORICC, that also takes account of the ordering in time-course microarray experiments by embedding the order-restricted inference into a model selection framework. Genes are assigned to the profile which they best match determined by a newly proposed information criterion for order-restricted inference. In addition, we also developed a bootstrap procedure to assess ORICC's clustering reliability for every gene. Simulation studies show that the ORICC method is robust, always gives better clustering accuracy than Peddada's method and saves hundreds of times computational time. Under some scenarios, its accuracy is also better than some other existing clustering methods for short time-course microarray data, such as STEM 2 and Wang et al. 3. It is also computationally much faster than Wang et al. 3. Conclusion Our ORICC algorithm, which takes advantage of the temporal ordering in time-course microarray experiments, provides good clustering accuracy and is meanwhile much

  5. Chromosomal microarray analysis as a first-tier clinical diagnostic test: Estonian experience.

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    Zilina, Olga; Teek, Rita; Tammur, Pille; Kuuse, Kati; Yakoreva, Maria; Vaidla, Eve; Mölter-Väär, Triin; Reimand, Tiia; Kurg, Ants; Ounap, Katrin

    2014-03-01

    Chromosomal microarray analysis (CMA) is now established as the first-tier cytogenetic diagnostic test for fast and accurate detection of chromosomal abnormalities in patients with developmental delay/intellectual disability (DD/ID), multiple congenital anomalies (MCA), and autism spectrum disorders (ASD). We present our experience with using CMA for postnatal and prenatal diagnosis in Estonian patients during 2009-2012. Since 2011, CMA is on the official service list of the Estonian Health Insurance Fund and is performed as the first-tier cytogenetic test for patients with DD/ID, MCA or ASD. A total of 1191 patients were analyzed, including postnatal (1072 [90%] patients and 59 [5%] family members) and prenatal referrals (60 [5%] fetuses). Abnormal results were reported in 298 (25%) patients, with a total of 351 findings (1-3 per individual): 147 (42%) deletions, 106 (30%) duplications, 89 (25%) long contiguous stretches of homozygosity (LCSH) events (>5 Mb), and nine (3%) aneuploidies. Of all findings, 143 (41%) were defined as pathogenic or likely pathogenic; for another 143 findings (41%), most of which were LCSH, the clinical significance remained unknown, while 61 (18%) reported findings can now be reclassified as benign or likely benign. Clinically relevant findings were detected in 126 (11%) patients. However, the proportion of variants of unknown clinical significance was quite high (41% of all findings). It seems that our ability to detect chromosomal abnormalities has far outpaced our ability to understand their role in disease. Thus, the interpretation of CMA findings remains a rather difficult task requiring a close collaboration between clinicians and cytogeneticists.

  6. An improved procedure for gene selection from microarray experiments using false discovery rate criterion

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    Yang Mark CK

    2006-01-01

    Full Text Available Abstract Background A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are often used to quantify the significance of these differences. The genes with small p-values are then picked as the genes responsible for the differences in the tissue RNA expressions. One key question is what should be the threshold to consider the p-values small. There is always a trade off between this threshold and the rate of false claims. Recent statistical literature shows that the false discovery rate (FDR criterion is a powerful and reasonable criterion to pick those genes with differential expression. Moreover, the power of detection can be increased by knowing the number of non-differential expression genes. While this number is unknown in practice, there are methods to estimate it from data. The purpose of this paper is to present a new method of estimating this number and use it for the FDR procedure construction. Results A combination of test functions is used to estimate the number of differentially expressed genes. Simulation study shows that the proposed method has a higher power to detect these genes than other existing methods, while still keeping the FDR under control. The improvement can be substantial if the proportion of true differentially expressed genes is large. This procedure has also been tested with good results using a real dataset. Conclusion For a given expected FDR, the method proposed in this paper has better power to pick genes that show differentiation in their expression than two other well known methods.

  7. The tissue micro-array data exchange specification: a web based experience browsing imported data

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    Ayers Leona W

    2005-08-01

    Full Text Available Abstract Background The AIDS and Cancer Specimen Resource (ACSR is an HIV/AIDS tissue bank consortium sponsored by the National Cancer Institute (NCI Division of Cancer Treatment and Diagnosis (DCTD. The ACSR offers to approved researchers HIV infected biologic samples and uninfected control tissues including tissue cores in micro-arrays (TMA accompanied by de-identified clinical data. Researchers interested in the type and quality of TMA tissue cores and the associated clinical data need an efficient method for viewing available TMA materials. Because each of the tissue samples within a TMA has separate data including a core tissue digital image and clinical data, an organized, standard approach to producing, navigating and publishing such data is necessary. The Association for Pathology Informatics (API extensible mark-up language (XML TMA data exchange specification (TMA DES proposed in April 2003 provides a common format for TMA data. Exporting TMA data into the proposed format offers an opportunity to implement the API TMA DES. Using our public BrowseTMA tool, we created a web site that organizes and cross references TMA lists, digital "virtual slide" images, TMA DES export data, linked legends and clinical details for researchers. Microsoft Excel® and Microsoft Word® are used to convert tabular clinical data and produce an XML file in the TMA DES format. The BrowseTMA tool contains Extensible Stylesheet Language Transformation (XSLT scripts that convert XML data into Hyper-Text Mark-up Language (HTML web pages with hyperlinks automatically added to allow rapid navigation. Results Block lists, virtual slide images, legends, clinical details and exports have been placed on the ACSR web site for 14 blocks with 1623 cores of 2.0, 1.0 and 0.6 mm sizes. Our virtual microscope can be used to view and annotate these TMA images. Researchers can readily navigate from TMA block lists to TMA legends and to clinical details for a selected tissue core

  8. Tests for differential gene expression using weights in oligonucleotide microarray experiments

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    Beyene Joseph

    2006-02-01

    Full Text Available Abstract Background Microarray data analysts commonly filter out genes based on a number of ad hoc criteria prior to any high-level statistical analysis. Such ad hoc approaches could lead to conflicting conclusions with no clear guidance as to which method is most likely to be reproducible. Furthermore, the number of tests performed with concomitant inflation in type I error also plagues the statistical analysis of microarray data, since the number of tested quantities in a study significantly affects the family-wise error rate. It would, therefore, be very useful to develop and adopt strategies that allow quantification of the quality of each probeset, to filter out or give little credence to low-quality or unexpressed probesets, and to incorporate these strategies into gene selection within a multiple testing framework. Results We have proposed a unified scheme for filtering and gene selection. For Affymetrix gene expression microarrays, we developed new methods for measuring the reliability of a particular probeset in a single array, and we used these to develop measures for a set of arrays. These measures are then used as weights in standard t-statistic calculations, and are incorporated into the multiple testing procedures. We demonstrated the advantages of our methods using simulated data, publicly available spiked-in data as well as data comparing normal muscle to muscle from patients with Duchenne muscular dystrophy (DMD, in which a set of truly differentially expressed genes is known. Conclusion Our quality measures provide convenient ways to search for individual genes of high quality. The quality weighting strategies we proposed for testing differential gene expression have demonstrable improvement on the traditional filtering methods, the standard t-statistic and a regularized t-statistic in Affymetrix data analysis.

  9. Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

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    Jason H. Moore

    2007-01-01

    Full Text Available The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a fl exible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occurring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profi les of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specifi c gene expression patterns having both statistical and biological signifi cance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the fl exibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org.

  10. Technical variability is greater than biological variability in a microarray experiment but both are outweighed by changes induced by stimulation.

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    Penelope A Bryant

    Full Text Available INTRODUCTION: A central issue in the design of microarray-based analysis of global gene expression is that variability resulting from experimental processes may obscure changes resulting from the effect being investigated. This study quantified the variability in gene expression at each level of a typical in vitro stimulation experiment using human peripheral blood mononuclear cells (PBMC. The primary objective was to determine the magnitude of biological and technical variability relative to the effect being investigated, namely gene expression changes resulting from stimulation with lipopolysaccharide (LPS. METHODS AND RESULTS: Human PBMC were stimulated in vitro with LPS, with replication at 5 levels: 5 subjects each on 2 separate days with technical replication of LPS stimulation, amplification and hybridisation. RNA from samples stimulated with LPS and unstimulated samples were hybridised against common reference RNA on oligonucleotide microarrays. There was a closer correlation in gene expression between replicate hybridisations (0.86-0.93 than between different subjects (0.66-0.78. Deconstruction of the variability at each level of the experimental process showed that technical variability (standard deviation (SD 0.16 was greater than biological variability (SD 0.06, although both were low (SD<0.1 for all individual components. There was variability in gene expression both at baseline and after stimulation with LPS and proportion of cell subsets in PBMC was likely partly responsible for this. However, gene expression changes after stimulation with LPS were much greater than the variability from any source, either individually or combined. CONCLUSIONS: Variability in gene expression was very low and likely to improve further as technical advances are made. The finding that stimulation with LPS has a markedly greater effect on gene expression than the degree of variability provides confidence that microarray-based studies can be used to

  11. Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

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    Tözeren Aydin

    2007-03-01

    Full Text Available Abstract Background Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. Methods This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B, percentage occupied by stroma-like regions (P, and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Results Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. Conclusion These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists as hundreds of tumors that are used to develop an array have typically been evaluated

  12. Magnesium isotope fractionation in bacterial mediated carbonate precipitation experiments

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    Parkinson, I. J.; Pearce, C. R.; Polacskek, T.; Cockell, C.; Hammond, S. J.

    2012-12-01

    Magnesium is an essential component of life, with pivotal roles in the generation of cellular energy as well as in plant chlorophyll [1]. The bio-geochemical cycling of Mg is associated with mass dependant fractionation (MDF) of the three stable Mg isotopes [1]. The largest MDF of Mg isotopes has been recorded in carbonates, with foraminiferal tests having δ26Mg compositions up to 5 ‰ lighter than modern seawater [2]. Magnesium isotopes may also be fractionated during bacterially mediated carbonate precipitation and such carbonates are known to have formed in both modern and ancient Earth surface environments [3, 4], with cyanobacteria having a dominant role in carbonate formation during the Archean. In this study, we aim to better constrain the extent to which Mg isotope fractionation occurs during cellular processes, and to identify when, and how, this signal is transferred to carbonates. To this end we have undertaken biologically-mediated carbonate precipitation experiments that were performed in artificial seawater, but with the molar Mg/Ca ratio set to 0.6 and with the solution spiked with 0.4% yeast extract. The bacterial strain used was marine isolate Halomonas sp. (gram-negative). Experiments were run in the dark at 21 degree C for two to three months and produced carbonate spheres of various sizes up to 300 μm in diameter, but with the majority have diameters of ~100 μm. Control experiments run in sterile controls (`empty` medium without bacteria) yielded no precipitates, indicating a bacterial control on the precipitation. The carbonate spheres are produced are amenable to SEM, EMP and Mg isotopic analysis by MC-ICP-MS. Our new data will shed light on tracing bacterial signals in carbonates from the geological record. [1] Young & Galy (2004). Rev. Min. Geochem. 55, p197-230. [2] Pogge von Strandmann (2008). Geochem. Geophys. Geosys. 9 DOI:10.1029/2008GC002209. [3] Castanier, et al. (1999). Sed. Geol. 126, 9-23. [4] Cacchio, et al. (2003

  13. Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments

    Directory of Open Access Journals (Sweden)

    Kitchen Robert R

    2011-12-01

    Full Text Available Abstract Background Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR and individual or pooled breast-tumour RNA. Results A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependant upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content. Conclusions The magnitude of systematic

  14. PCR amplfication on a microarray of gel-immobilized oligonucleotides : detection of bacterial toxin- and drug-resistent genes and their mutations.

    Energy Technology Data Exchange (ETDEWEB)

    Strizhkov, B. N.; Drobyshev, A. L.; Mikhailovich, V. M.; Mirzabekov, A. D.; Biochip Technology Center; Engelhardt Inst. of Molecular Biology

    2000-10-01

    PCR amplification on a microarray of gel-immobilized primers (microchip) has been developed. One of a pair of PCR primers was immobilized inside a separate microchip polyacrylamide porous gel pad of 0.1 x 0.1 x 0.02 (or 0.04) micron in size and 0.2 (or 0.4) nL in volume. The amplification was carried out simultaneously both in solution covering the microchip array and inside gel pads. Each gel pad contained the immobilized forward primers, while the fluorescently labeled reverse primers, as well as all components of the amplification reaction, diffused into the gel pads from the solution. To increase the amplification efficiency, the forward primers were also added into the solution. The kinetics of amplification was measured in real time in parallel for all gel pads with a fluorescent microscope equipped with a charge-coupled device (CCD) camera. The accuracy of the amplification was assessed by using the melting curves obtained for the duplexes formed by the labeled amplification product and the gel-immobilized primers during the amplification process; alternatively, the duplexes were produced by hybridization of the extended immobilized primers with labeled oligonucleotide probes. The on-chip amplification was applied to detect the anthrax toxin genes and the plasmid-borne beta-lactamase gene responsible for bacterial ampicillin resistance. The allele-specific type of PCR amplification was used to identify the Shiga toxin gene and discriminate it from the Shiga-like one. The genomic mutations responsible for rifampicin resistance of the Mycobacterium tuberculosis strains were detected by the same type of PCR amplification of the rpoB gene fragment isolated from sputum of tuberculosis patients. The on-chip PCR amplification has been shown to be a rapid, inexpensive and powerful tool to test genes responsible for bacterial toxin production and drug resistance, as well as to reveal point nucleotide mutations.

  15. A novel approach combining the Calgary Biofilm Device and Phenotype MicroArray for the characterization of the chemical sensitivity of bacterial biofilms.

    Science.gov (United States)

    Santopolo, L; Marchi, E; Frediani, L; Decorosi, F; Viti, C; Giovannetti, L

    2012-01-01

    A rapid method for screening the metabolic susceptibility of biofilms to toxic compounds was developed by combining the Calgary Biofilm Device (MBEC device) and Phenotype MicroArray (PM) technology. The method was developed using Pseudomonas alcaliphila 34, a Cr(VI)-hyper-resistant bacterium, as the test organism. P. alcaliphila produced a robust biofilm after incubation for 16 h, reaching the maximum value after incubation for 24 h (9.4 × 10(6) ± 3.3 × 10(6) CFU peg(-1)). In order to detect the metabolic activity of cells in the biofilm, dye E (5×) and menadione sodium bisulphate (100 μM) were selected for redox detection chemistry, because they produced a high colorimetric yield in response to bacterial metabolism (340.4 ± 6.9 Omnilog Arbitrary Units). This combined approach, which avoids the limitations of traditional plate counts, was validated by testing the susceptibility of P. alcaliphila biofilm to 22 toxic compounds. For each compound the concentration level that significantly lowered the metabolic activity of the biofilm was identified. Chemical sensitivity analysis of the planktonic culture was also performed, allowing comparison of the metabolic susceptibility patterns of biofilm and planktonic cultures.

  16. DNA Microarrays

    Science.gov (United States)

    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.

  17. Not proper ROC curves as new tool for the analysis of differentially expressed genes in microarray experiments

    Directory of Open Access Journals (Sweden)

    Pistoia Vito

    2008-10-01

    Full Text Available Abstract Background Most microarray experiments are carried out with the purpose of identifying genes whose expression varies in relation with specific conditions or in response to environmental stimuli. In such studies, genes showing similar mean expression values between two or more groups are considered as not differentially expressed, even if hidden subclasses with different expression values may exist. In this paper we propose a new method for identifying differentially expressed genes, based on the area between the ROC curve and the rising diagonal (ABCR. ABCR represents a more general approach than the standard area under the ROC curve (AUC, because it can identify both proper (i.e., concave and not proper ROC curves (NPRC. In particular, NPRC may correspond to those genes that tend to escape standard selection methods. Results We assessed the performance of our method using data from a publicly available database of 4026 genes, including 14 normal B cell samples (NBC and 20 heterogeneous lymphomas (namely: 9 follicular lymphomas and 11 chronic lymphocytic leukemias. Moreover, NBC also included two sub-classes, i.e., 6 heavily stimulated and 8 slightly or not stimulated samples. We identified 1607 differentially expressed genes with an estimated False Discovery Rate of 15%. Among them, 16 corresponded to NPRC and all escaped standard selection procedures based on AUC and t statistics. Moreover, a simple inspection to the shape of such plots allowed to identify the two subclasses in either one class in 13 cases (81%. Conclusion NPRC represent a new useful tool for the analysis of microarray data.

  18. Gene Expression Analysis: Teaching Students to Do 30,000 Experiments at Once with Microarray

    Science.gov (United States)

    Carvalho, Felicia I.; Johns, Christopher; Gillespie, Marc E.

    2012-01-01

    Genome scale experiments routinely produce large data sets that require computational analysis, yet there are few student-based labs that illustrate the design and execution of these experiments. In order for students to understand and participate in the genomic world, teaching labs must be available where students generate and analyze large data…

  19. A newly designed 45 to 60 mer oligonucleotide Agilent platform microarray for global gene expression studies of Synechocystis PCC6803: example salt stress experiment

    NARCIS (Netherlands)

    E. Aguirre von Wobeser; J. Huisman; B. Ibelings; H.C.P. Matthijs

    2005-01-01

    A newly designed 45 to 60 mer oligonucleotide Agilent platform microarray for global gene expression studies of Synechocystis PCC6803: example salt stress experiment Eneas Aguirre-von-Wobeser 1, Jef Huisman1, Bas Ibelings2 and Hans C.P. Matthijs1 1 Universiteit van Amsterdam, Amsterdam, The Netherla

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

    OpenAIRE

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

    2014-01-01

    Background Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray u...

  1. Missing channels in two-colour microarray experiments: Combining single-channel and two-channel data

    Directory of Open Access Journals (Sweden)

    Burtt Glyn J

    2007-01-01

    Full Text Available Abstract Background There are mechanisms, notably ozone degradation, that can damage a single channel of two-channel microarray experiments. Resulting analyses therefore often choose between the unacceptable inclusion of poor quality data or the unpalatable exclusion of some (possibly a lot of good quality data along with the bad. Two such approaches would be a single channel analysis using some of the data from all of the arrays, and an analysis of all of the data, but only from unaffected arrays. In this paper we examine a 'combined' approach to the analysis of such affected experiments that uses all of the unaffected data. Results A simulation experiment shows that while a single channel analysis performs relatively well when the majority of arrays are affected, and excluding affected arrays performs relatively well when few arrays are affected (as would be expected in both cases, the combined approach out-performs both. There are benefits to actively estimating the key-parameter of the approach, but whether these compensate for the increased computational cost and complexity over just setting that parameter to take a fixed value is not clear. Inclusion of ozone-affected data results in poor performance, with a clear spatial effect in the damage being apparent. Conclusion There is no need to exclude unaffected data in order to remove those which are damaged. The combined approach discussed here is shown to out-perform more usual approaches, although it seems that if the damage is limited to very few arrays, or extends to very nearly all, then the benefits will be limited. In other circumstances though, large improvements in performance can be achieved by adopting such an approach.

  2. The continuity of bacterial and physicochemical evolution: theory and experiments.

    Science.gov (United States)

    Spitzer, Jan

    2014-01-01

    The continuity of chemical and biological evolution, incorporating life's emergence, can be explored experimentally by energizing 'dead' bacterial biomacromolecules with nutrients under cycling physicochemical gradients. This approach arises from three evolutionary principles rooted in physical chemistry: (i) broken bacterial cells cannot spontaneously self-assemble into a living state without the supply of external energy - 2nd law of thermodynamics, (ii) the energy delivery must be cycling - the primary mechanism of chemical evolution at rotating planetary surfaces under solar irradiation, (iii) the cycling energy must act on chemical mixtures of high molecular diversity and crowding - provided by dead bacterial populations.

  3. Heterologous microarray experiments allow the identification of the early events associated with potato tuber cold sweetening

    Directory of Open Access Journals (Sweden)

    Vitulli Federico

    2008-04-01

    Full Text Available Abstract Background Since its discovery more than 100 years ago, potato (Solanum tuberosum tuber cold-induced sweetening (CIS has been extensively investigated. Several carbohydrate-associated genes would seem to be involved in the process. However, many uncertainties still exist, as the relative contribution of each gene to the process is often unclear, possibly as the consequence of the heterogeneity of experimental systems. Some enzymes associated with CIS, such as β-amylases and invertases, have still to be identified at a sequence level. In addition, little is known about the early events that trigger CIS and on the involvement/association with CIS of genes different from carbohydrate-associated genes. Many of these uncertainties could be resolved by profiling experiments, but no GeneChip is available for the potato, and the production of the potato cDNA spotted array (TIGR has recently been discontinued. In order to obtain an overall picture of early transcriptional events associated with CIS, we investigated whether the commercially-available tomato Affymetrix GeneChip could be used to identify which potato cold-responsive gene family members should be further studied in detail by Real-Time (RT-PCR (qPCR. Results A tomato-potato Global Match File was generated for the interpretation of various aspects of the heterologous dataset, including the retrieval of best matching potato counterparts and annotation, and the establishment of a core set of highly homologous genes. Several cold-responsive genes were identified, and their expression pattern was studied in detail by qPCR over 26 days. We detected biphasic behaviour of mRNA accumulation for carbohydrate-associated genes and our combined GeneChip-qPCR data identified, at a sequence level, enzymatic activities such as β-amylases and invertases previously reported as being involved in CIS. The GeneChip data also unveiled important processes accompanying CIS, such as the induction of redox

  4. Chromosome Microarray.

    Science.gov (United States)

    Anderson, Sharon

    2016-01-01

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

  5. The intraclass correlation coefficient applied for evaluation of data correction, labeling methods and rectal biopsy sampling in DNA microarray experiments

    NARCIS (Netherlands)

    Pellis, E.P.M.; Franssen-Hal, van N.L.W.; Burema, J.; Keijer, J.

    2003-01-01

    We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from a

  6. Direct calibration of PICKY-designed microarrays

    Directory of Open Access Journals (Sweden)

    Ronald Pamela C

    2009-10-01

    Full Text Available Abstract Background Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples. Results Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website http://www.complex.iastate.edu under the PICKY Download area. Conclusion PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

  7. The Design of Simple Bacterial Microarrays: Development towards Immobilizing Single Living Bacteria on Predefined Micro-Sized Spots on Patterned Surfaces.

    Directory of Open Access Journals (Sweden)

    Nina Bjørk Arnfinnsdottir

    Full Text Available In this paper we demonstrate a procedure for preparing bacterial arrays that is fast, easy, and applicable in a standard molecular biology laboratory. Microcontact printing is used to deposit chemicals promoting bacterial adherence in predefined positions on glass surfaces coated with polymers known for their resistance to bacterial adhesion. Highly ordered arrays of immobilized bacteria were obtained using microcontact printed islands of polydopamine (PD on glass surfaces coated with the antiadhesive polymer polyethylene glycol (PEG. On such PEG-coated glass surfaces, bacteria were attached to 97 to 100% of the PD islands, 21 to 62% of which were occupied by a single bacterium. A viability test revealed that 99% of the bacteria were alive following immobilization onto patterned surfaces. Time series imaging of bacteria on such arrays revealed that the attached bacteria both divided and expressed green fluorescent protein, both of which indicates that this method of patterning of bacteria is a suitable method for single-cell analysis.

  8. Aptamer Microarrays

    Energy Technology Data Exchange (ETDEWEB)

    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.

  9. Genome-wide copy number profiling on high-density bacterial artificial chromosomes, single-nucleotide polymorphisms, and oligonucleotide microarrays: a platform comparison based on statistical power analysis.

    NARCIS (Netherlands)

    Hehir-Kwa, J.Y.; Egmont-Peterson, M.; Janssen, I.M.; Smeets, D.F.C.M.; Geurts van Kessel, A.H.M.; Veltman, J.A.

    2007-01-01

    Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a high

  10. The burden of bacterial vaginosis: women's experience of the physical, emotional, sexual and social impact of living with recurrent bacterial vaginosis.

    Directory of Open Access Journals (Sweden)

    Jade E Bilardi

    Full Text Available BACKGROUND: Bacterial vaginosis is a common vaginal infection, causing an abnormal vaginal discharge and/or odour in up to 50% of sufferers. Recurrence is common following recommended treatment. There are limited data on women's experience of bacterial vaginosis, and the impact on their self-esteem, sexual relationships and quality of life. The aim of this study was to explore the experiences and impact of recurrent bacterial vaginosis on women. METHODS: A social constructionist approach was chosen as the framework for the study. Thirty five women with male and/or female partners participated in semi-structured interviews face-to-face or by telephone about their experience of recurrent bacterial vaginosis. RESULTS: Recurrent bacterial vaginosis impacted on women to varying degrees, with some women reporting it had little impact on their lives but most reporting it had a moderate to severe impact. The degree to which it impacted on women physically, emotionally, sexually and socially often depended on the frequency of episodes and severity of symptoms. Women commonly reported that symptoms of bacterial vaginosis made them feel embarrassed, ashamed, 'dirty' and very concerned others may detect their malodour and abnormal discharge. The biggest impact of recurrent bacterial vaginosis was on women's self-esteem and sex lives, with women regularly avoiding sexual activity, in particular oral sex, as they were too embarrassed and self-conscious of their symptoms to engage in these activities. Women often felt confused about why they were experiencing recurrent bacterial vaginosis and frustrated at their lack of control over recurrence. CONCLUSION: Women's experience of recurrent bacterial vaginosis varied broadly and significantly in this study. Some women reported little impact on their lives but most reported a moderate to severe impact, mainly on their self-esteem and sex life. Further support and acknowledgement of these impacts are required when

  11. Differential expression of 114 oxidative stressrelated genes in peripheral blood mononuclear cells of acute cerebral infarction patients A gene microarray experiment

    Institute of Scientific and Technical Information of China (English)

    Jing Yang; Fei Zhong; Mingshan Ren; Jiangming Zhao

    2010-01-01

    Previous studies have focused on the analysis of single or several function-related genes in oxidative stress;however,little information is available regarding altered expression of oxidative stress-related genes in the process of ischemia-reperfusion injury from microarray experiments.The aim of the present study was to investigate the changes in cell oxidative stress-and toxicity-related gene expression utilizing microarray screening in patients with acute cerebral infarction during cerebral ischemia-reperfusion injury.Of the included 114 genes,expression was significantly upregulated in eight genes,including three heat shock protein-related genes,one oxidative and metabolic stress-related gene,one cell growth arrest/senescence related gene,two apoptosis signal-related genes,and one DNA damage and repair related gene.Expression was significantly downregulated in four genes,including one cell proliferation/cancer related gene,two oxidative and metabolic stress-related genes and one DNA damage and repair related gene.The results demonstrated that cerebral ischemia-reperfusion injury in patients with acute cerebral infarction was affected by many genes including oxidative stress-,heat shock-,DNA damage and repair-,and apoptosis signal-related genes.Therefore,it could be suggested that cerebral ischemia-reperfusion injury may be subjected to complex genetic regulation mechanisms.

  12. Bacterial Production of Poly(3-hydroxybutyrate): An Undergraduate Student Laboratory Experiment

    Science.gov (United States)

    Burns, Kristi L.; Oldham, Charlie D.; May, Sheldon W.

    2009-01-01

    As part of a multidisciplinary course that is cross-listed between five departments, we developed an undergraduate student laboratory experiment for culturing, isolating, and purifying the biopolymer, poly(3-hydroxybutyrate), PHB. This biopolyester accumulates in the cytoplasm of bacterial cells under specific growth conditions, and it has…

  13. Comprehensive comparison of six microarray technologies

    OpenAIRE

    Yauk, Carole L.; Berndt, M. Lynn; Williams, Andrew; Douglas, George R

    2004-01-01

    Microarray technology is extensively used in biological research. The applied technologies vary greatly between laboratories, and outstanding questions remain regarding the degree of correlation among approaches. Recently, there has been a drive toward ensuring high-quality microarray data by the implementation of MIAME (Minimal Information About a Microarray Experiment) guidelines and an emphasis on ensuring public-availability to all datasets. However, despite its current widespread use and...

  14. Novel R pipeline for analyzing biolog phenotypic microarray data.

    OpenAIRE

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

    2015-01-01

    Data produced by Biolog Phenotype MicroArrays are longitudinal measurements of cells' respiration on distinct substrates. We introduce a three-step pipeline to analyze phenotypic microarray data with novel procedures for grouping, normalization and effect identification. Grouping and normalization are standard problems in the analysis of phenotype microarrays defined as categorizing bacterial responses into active and non-active, and removing systematic errors from the experimental data, resp...

  15. Heterotrophic bacterial production and metabolic balance during the VAHINE mesocosm experiment in the New Caledonia lagoon

    Science.gov (United States)

    Van Wambeke, F.; Pfreundt, U.; Barani, A.; Berthelot, H.; Moutin, T.; Rodier, M.; Hess, W. R.; Bonnet, S.

    2015-12-01

    N2 fixation fuels ~ 50 % of new primary production in the oligotrophic South Pacific Ocean. The VAHINE mesocosm experiment designed to track the fate of diazotroph derived nitrogen (DDN) in the New Caledonia lagoon. Here, we examined the temporal dynamics of heterotrophic bacterial production during this experiment. Three replicate large-volume (~ 50 m3) mesocosms were deployed and were intentionally fertilized with dissolved inorganic phosphorus (DIP) to stimulate N2 fixation. We specifically examined relationships between N2 fixation rates and primary production, determined bacterial growth efficiency and established carbon budgets of the system from the DIP fertilization to the end of the experiment (days 5-23). Heterotrophic bacterioplankton production (BP) and alkaline phosphatase activity (APA) were statistically higher during the second phase of the experiment (P2: days 15-23), when chlorophyll biomass started to increase compared to the first phase (P1: days 5-14). Among autotrophs, Synechococcus abundances increased during P2, possibly related to its capacity to assimilate leucine and to produce alkaline phosphatase. Bacterial growth efficiency based on the carbon budget was notably higher than generally cited for oligotrophic environments (27-43 %), possibly due to a high representation of proteorhodopsin-containing organisms within the picoplanctonic community. The carbon budget showed that the main fate of gross primary production (particulate + dissolved) was respiration (67 %), and export through sedimentation (17 %). BP was highly correlated with particulate primary production and chlorophyll biomass during both phases of the experiment but slightly correlated, and only during P2 phase, with N2 fixation rates. Our results suggest that most of the DDN reached the heterotrophic bacterial community through indirect processes, like mortality, lysis and grazing.

  16. Microarrays, Integrated Analytical Systems

    Science.gov (United States)

    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. Nonlinearity in bacterial population dynamics: Proposal for experiments for the observation of abrupt transitions in patches

    OpenAIRE

    Kenkre, V. M.; Kumar, Niraj

    2008-01-01

    An explicit proposal for experiments leading to abrupt transitions in spatially extended bacterial populations in a Petri dish is presented on the basis of an exact formula obtained through an analytic theory. The theory provides accurately the transition expressions in spite of the fact that the actual solutions, which involve strong nonlinearity, are inaccessible to it. The analytic expressions are verified through numerical solutions of the relevant nonlinear equation. The experimental set...

  18. Heterotrophic bacterial production and metabolic balance during the VAHINE mesocosm experiment in the New Caledonia lagoon

    Science.gov (United States)

    Van Wambeke, France; Pfreundt, Ulrike; Barani, Aude; Berthelot, Hugo; Moutin, Thierry; Rodier, Martine; Hess, Wolfgang R.; Bonnet, Sophie

    2016-06-01

    Studies investigating the fate of diazotrophs through the microbial food web are lacking, although N2 fixation can fuel up to 50 % of new production in some oligotrophic oceans. In particular, the role played by heterotrophic prokaryotes in this transfer is largely unknown. In the frame of the VAHINE (VAriability of vertical and tropHIc transfer of diazotroph derived N in the south wEst Pacific) experiment, three replicate large-volume (˜ 50 m3) mesocosms were deployed for 23 days in the new Caledonia lagoon and were intentionally fertilized on day 4 with dissolved inorganic phosphorus (DIP) to stimulate N2 fixation. We specifically examined relationships between heterotrophic bacterial production (BP) and N2 fixation or primary production, determined bacterial growth efficiency and established carbon budgets. BP was statistically higher during the second phase of the experiment (P2: days 15-23), when chlorophyll biomass started to increase compared to the first phase (P1: days 5-14). Phosphatase alkaline activity increased drastically during the second phase of the experiment, showing adaptations of microbial populations after utilization of the added DIP. Notably, among autotrophs, Synechococcus abundances increased during P2, possibly related to its capacity to assimilate leucine and to produce alkaline phosphatase. Bacterial growth efficiency based on the carbon budget (27-43 %), was notably higher than generally cited for oligotrophic environments and discussed in links with the presence of abundant species of bacteria expressing proteorhodopsin. The main fates of gross primary production (particulate + dissolved) were respiration (67 %) and export through sedimentation (17 %). BP was highly correlated with particulate primary production and chlorophyll biomass during both phases of the experiment but was slightly correlated, and only during P2 phase, with N2 fixation rates. Heterotrophic bacterial production was strongly stimulated after mineral N enrichment

  19. Compressive Sensing DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Richard G. Baraniuk

    2009-01-01

    Full Text Available 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.

  20. The EADGENE Microarray Data Analysis Workshop

    DEFF Research Database (Denmark)

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø;

    2007-01-01

    Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from...... 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays...... statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful...

  1. Coexisting protist-bacterial community accelerates protein transformation in microcosm experiments

    Directory of Open Access Journals (Sweden)

    Ngo Vy Thao

    2014-12-01

    Full Text Available Proteins constitute the major portion of labile substances in the marine environment and are an important source of organic matter supporting marine ecosystems. However, previous studies have revealed that specific bacterial membrane proteins are refractory in the oceans. We here show by kinetic analyses of protease degradation activity using inactivated Pseudomonas aeruginosa (Pa cells as a proteinaceous substrate that bacterial proteases are insufficient to completely hydrolyze proteins, which may partially cause the protein accumulation in seawater. Protease activity was monitored simultaneously in 8 microcosms subjected to differing conditions. Some Pa proteins were retained for 30 days in the presence of bacteria without protists, whereas the Pa proteins were completely disappeared in the presence of both, indicating that these proteins were substantially incorporated into protist biomass. Our result suggests that protists play an important role in the transformation of bacterial proteins in seawater. Our experiments also imply that the functional/taxonomic diversity should be taken into account when considering decomposition activity in marine environments.

  2. DNA Microarray Technique

    Directory of Open Access Journals (Sweden)

    Thakare SP

    2012-11-01

    Full Text Available DNA Microarray is the emerging technique in Biotechnology. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. It also includes screening and diagnostic applications. The DNA microarray hybridization applications include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs, and short tandem repeats (STRs. In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes.

  3. Soil Respiration and Bacterial Structure and Function after 17 Years of a Reciprocal Soil Transplant Experiment.

    Science.gov (United States)

    Bond-Lamberty, Ben; Bolton, Harvey; Fansler, Sarah; Heredia-Langner, Alejandro; Liu, Chongxuan; McCue, Lee Ann; Smith, Jeffrey; Bailey, Vanessa

    2016-01-01

    The effects of climate change on soil organic matter-its structure, microbial community, carbon storage, and respiration response-remain uncertain and widely debated. In addition, the effects of climate changes on ecosystem structure and function are often modulated or delayed, meaning that short-term experiments are not sufficient to characterize ecosystem responses. This study capitalized on a long-term reciprocal soil transplant experiment to examine the response of dryland soils to climate change. The two transplant sites were separated by 500 m of elevation on the same mountain slope in eastern Washington state, USA, and had similar plant species and soil types. We resampled the original 1994 soil transplants and controls, measuring CO2 production, temperature response, enzyme activity, and bacterial community structure after 17 years. Over a laboratory incubation of 100 days, reciprocally transplanted soils respired roughly equal cumulative amounts of carbon as non-transplanted controls from the same site. Soils transplanted from the hot, dry, lower site to the cooler and wetter (difference of -5°C monthly maximum air temperature, +50 mm yr-1 precipitation) upper site exhibited almost no respiratory response to temperature (Q10 of 1.1), but soils originally from the upper, cooler site had generally higher respiration rates. The bacterial community structure of transplants did not differ significantly from that of untransplanted controls, however. Slight differences in local climate between the upper and lower Rattlesnake locations, simulated with environmental control chambers during the incubation, thus prompted significant differences in microbial activity, with no observed change to bacterial structure. These results support the idea that environmental shifts can influence soil C through metabolic changes, and suggest that microbial populations responsible for soil heterotrophic respiration may be constrained in surprising ways, even as shorter- and

  4. Soil respiration and bacterial structure and function after 17 years of a reciprocal soil transplant experiment

    Energy Technology Data Exchange (ETDEWEB)

    Bond-Lamberty, Benjamin; Bolton, Harvey; Fansler, Sarah J.; Heredia-Langner, Alejandro; Liu, Chongxuan; McCue, Lee Ann; Smith, Jeff L.; Bailey, Vanessa L.

    2016-03-02

    The effects of climate change on soil organic matter—its structure, microbial community, carbon storage, and respiration response—remain uncertain and widely debated. In addition, the effects of climate changes on ecosystem structure and function are often modulated or delayed, meaning that short-term experiments are not sufficient to characterize ecosystem responses. This study capitalized on a long-term reciprocal soil transplant experiment to examine the response of dryland soils to climate change. The two transplant sites were separated by 500 m of elevation on the same mountain slope in eastern Washington state, USA, and had similar plant species and soil types. We resampled the original 1994 soil transplants and controls, measuring CO2 production, temperature response, enzyme activity, and bacterial community structure after 17 years. Over a laboratory incubation of 100 days, reciprocally transplanted soils respired roughly equal cumulative amounts of carbon as non-transplanted controls from the same site. Soils transplanted from the hot, dry, lower site to the cooler and wetter (difference of -5 °C monthly maximum air temperature, +50 mm yr-1 precipitation) upper site exhibited almost no respiratory response to temperature (Q10 of 1.1), but soils originally from the upper, cooler site had generally higher respiration rates. The bacterial community structure of transplants did not differ significantly from that of untransplanted controls, however. Slight differences in local climate between the upper and lower Rattlesnake locations, simulated with environmental control chambers during the incubation, thus prompted significant differences in microbial activity, with no observed change to bacterial structure. These results support the idea that environmental shifts can influence soil C through metabolic changes, and suggest that microbial populations responsible for soil heterotrophic respiration may be constrained in surprising ways, even as shorter- and

  5. Design of a Comprehensive Biochemistry and Molecular Biology Experiment: Phase Variation Caused by Recombinational Regulation of Bacterial Gene Expression

    Science.gov (United States)

    Sheng, Xiumei; Xu, Shungao; Lu, Renyun; Isaac, Dadzie; Zhang, Xueyi; Zhang, Haifang; Wang, Huifang; Qiao, Zheng; Huang, Xinxiang

    2014-01-01

    Scientific experiments are indispensable parts of Biochemistry and Molecular Biology. In this study, a comprehensive Biochemistry and Molecular Biology experiment about "Salmonella enterica" serovar Typhi Flagellar phase variation has been designed. It consisted of three parts, namely, inducement of bacterial Flagellar phase variation,…

  6. Microarray Analysis in Glioblastomas

    Science.gov (United States)

    Bhawe, Kaumudi M.; Aghi, Manish K.

    2016-01-01

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

  7. The Impact of Photobleaching on Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Marcel von der Haar

    2015-09-01

    Full Text Available 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.

  8. A response to information criterion-based clustering with order-restricted candidate profiles in short time-course microarray experiments

    Directory of Open Access Journals (Sweden)

    Umbach David M

    2009-12-01

    Full Text Available Abstract Background For gene expression data obtained from a time-course microarray experiment, Liu et al. 1 developed a new algorithm for clustering genes with similar expression profiles over time. Performance of their proposal was compared with three other methods including the order-restricted inference based methodology of Peddada et al. 23. In this note we point out several inaccuracies in Liu et al. 1 and conclude that the order-restricted inference based methodology of Peddada et al. (programmed in the software ORIOGEN indeed operates at the desired nominal Type 1 error level, an important feature of a statistical decision rule, while being computationally substantially faster than indicated by Liu et al. 1. Results Application of ORIOGEN to the well-known breast cancer cell line data of Lobenhofer et al. 4 revealed that ORIOGEN software took only 21 minutes to run (using 100,000 bootstraps with p = 0.0025, substantially faster than the 72 hours found by Liu et al. 1 using Matlab. Also, based on a data simulated according to the model and parameters of simulation 1 (σ2 = 1, M = 5 in 1 we found that ORIOGEN took less than 30 seconds to run in stark contrast to Liu et al. who reported that their implementation of the same algorithm in R took 2979.29 seconds. Furthermore, for the simulation studies reported in 1, unlike the claims made by Liu et al. 1, ORIOGEN always maintained the desired false positive rate. According to Figure three in Liu et al. 1 their algorithm had a false positive rate ranging approximately from 0.20 to 0.70 for the scenarios that they simulated. Conclusions Our comparisons of run times indicate that the implementations of ORIOGEN's algorithm in Matlab and R by Liu et al. 1 is inefficient compared to the publicly available JAVA implementation. Our results on the false positive rate of ORIOGEN suggest some error in Figure three of Liu et al. 1, perhaps due to a programming error.

  9. rapmad: Robust analysis of peptide microarray data

    Directory of Open Access Journals (Sweden)

    Rothermel Andrée

    2011-08-01

    Full Text Available Abstract Background Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data, a novel computational tool implemented in R. Results We evaluated rapmad in antibody reactivity experiments for several thousand peptide spots and compared it to two existing algorithms for the analysis of peptide microarrays. rapmad displays competitive and superior behavior to existing software solutions. Particularly, it shows substantially improved sensitivity for low intensity settings without sacrificing specificity. It thereby contributes to increasing the effectiveness of high throughput screening experiments. Conclusions rapmad allows the robust and sensitive, automated analysis of high-throughput peptide array data. The rapmad R-package as well as the data sets are available from http://www.tron-mz.de/compmed.

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

    Directory of Open Access Journals (Sweden)

    Noriko Goji

    2012-01-01

    Full Text Available 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.

  11. Women's Management of Recurrent Bacterial Vaginosis and Experiences of Clinical Care: A Qualitative Study.

    Directory of Open Access Journals (Sweden)

    Jade Bilardi

    Full Text Available Few data are available on how women manage recurring bacterial vaginosis (BV and their experiences of the clinical care of this condition. This study aimed to explore women's recurrent BV management approaches and clinical care experiences, with a view to informing and improving the clinical management of BV.A descriptive, social constructionist approach was chosen as the framework for the study. Thirty-five women of varying sexual orientation who had experienced recurrent BV in the past 5 years took part in semi-structured interviews.The majority of women reported frustration and dissatisfaction with current treatment regimens and low levels of satisfaction with the clinical management of BV. Overall, women disliked taking antibiotics regularly, commonly experienced adverse side effects from treatment and felt frustrated at having symptoms recur quite quickly after treatment. Issues in clinical care included inconsistency in advice, misdiagnosis and inappropriate diagnostic approaches and insensitive or dismissive attitudes. Women were more inclined to report positive clinical experiences with sexual health physicians than primary care providers. Women's frustrations led most to try their own self-help remedies and lifestyle modifications in an attempt to treat symptoms and prevent recurrences, including well-known risk practices such as douching.In the face of considerable uncertainty about the cause of BV, high rates of recurrence, unacceptable treatment options and often insensitive and inconsistent clinical management, women are trying their own self-help remedies and lifestyle modifications to prevent recurrences, often with little effect. Clinical management of BV could be improved through the use of standardised diagnostic approaches, increased sensitivity and understanding of the impact of BV, and the provision of evidence based advice about known BV related risk factors.

  12. Physical and bacterial controls on inorganic nutrients and dissolved organic carbon during a sea ice growth and decay experiment

    DEFF Research Database (Denmark)

    Zhou, J.; Delille, B.; Kaartokallio, H.;

    2014-01-01

    We investigated how physical incorporation, brine dynamics and bacterial activity regulate the distribution of inorganic nutrients and dissolved organic carbon (DOC) in artificial sea ice during a 19-day experiment that included periods of both ice growth and decay. The experiment was performed...... regulating the distribution of the dissolved compounds within sea ice are clearly a complex interaction of brine dynamics, biological activity and in the case of dissolved organic matter, the physico-chemical properties of the dissolved constituents themselves....

  13. Viral control of bacterial biodiversity - Evidence from a nutrient enriched mesocosm experiment

    DEFF Research Database (Denmark)

    Sandaa, R.-A.; Gómez-Consarnau, L.; Pinhassi, J.;

    2009-01-01

    -host pairs. We investigated these relationships in nutrient-manipulated systems, under simulated in situ conditions. There was a strong correlation in the clustering of the viral and bacterial community data supporting the existence of an important link between the bacterial and viral communities...

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

    Directory of Open Access Journals (Sweden)

    Schlater Amber

    2010-09-01

    Full Text Available Abstract 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.

  15. Combining Affymetrix microarray results

    Directory of Open Access Journals (Sweden)

    Doerge RW

    2005-03-01

    Full Text Available Abstract Background As the use of microarray technology becomes more prevalent it is not unusual to find several laboratories employing the same microarray technology to identify genes related to the same condition in the same species. Although the experimental specifics are similar, typically a different list of statistically significant genes result from each data analysis. Results We propose a statistically-based meta-analytic approach to microarray analysis for the purpose of systematically combining results from the different laboratories. This approach provides a more precise view of genes that are significantly related to the condition of interest while simultaneously allowing for differences between laboratories. Of particular interest is the widely used Affymetrix oligonucleotide array, the results of which are naturally suited to a meta-analysis. A simulation model based on the Affymetrix platform is developed to examine the adaptive nature of the meta-analytic approach and to illustrate the usefulness of such an approach in combining microarray results across laboratories. The approach is then applied to real data involving a mouse model for multiple sclerosis. Conclusion The quantitative estimates from the meta-analysis model tend to be closer to the "true" degree of differential expression than any single lab. Meta-analytic methods can systematically combine Affymetrix results from different laboratories to gain a clearer understanding of genes' relationships to specific conditions of interest.

  16. Protein microarrays for systems biology

    Institute of Scientific and Technical Information of China (English)

    Lina Yang; Shujuan Guo; Yang Li; Shumin Zhou; Shengce Tao

    2011-01-01

    Systems biology holds the key for understanding biological systems on a system level. It eventually holds the key for the treatment and cure of complex diseases such as cancer,diabetes, obesity, mental disorders, and many others. The '-omics' technologies, such as genomics, transcriptomics,proteomics, and metabonomics, are among the major driving forces of systems biology. Featured as highthroughput, miniaturized, and capable of parallel analysis,protein microarrays have already become an important technology platform for systems biology, In this review, we will focus on the system level or global analysis of biological systems using protein microarrays. Four major types of protein microarrays will be discussed: proteome microarrays, antibody microarrays, reverse-phase protein arrays,and lectin microarrays. We will also discuss the challenges and future directions of protein microarray technologies and their applications for systems biology. We strongly believe that protein microarrays will soon become an indispensable and invaluable tool for systems biology.

  17. Microarray technology and its applications

    CERN Document Server

    Müller, UR

    2006-01-01

    It presents detailed overviews of the different techniques of fabricating microarrays, of the chemistries and preparative steps involved, of the different types of microarrays, and of the instrumentation and optical issues involved.

  18. Prominent feature selection of microarray data

    Institute of Scientific and Technical Information of China (English)

    Yihui Liu

    2009-01-01

    For wavelet transform, a set of orthogonal wavelet basis aims to detect the localized changing features contained in microarray data. In this research, we investigate the performance of the selected wavelet features based on wavelet detail coefficients at the second level and the third level. The genetic algorithm is performed to optimize wavelet detail coefficients to select the best discriminant features. Exper-iments are carried out on four microarray datasets to evaluate the performance of classification. Experimental results prove that wavelet features optimized from detail coefficients efficiently characterize the differences between normal tissues and cancer tissues.

  19. Leaching of Zinc Sulfide by Thiobacillus ferrooxidans: Experiments with a Controlled Redox Potential Indicate No Direct Bacterial Mechanism

    OpenAIRE

    Fowler, T. A.; Crundwell, F. K.

    1998-01-01

    The role of Thiobacillus ferrooxidans in bacterial leaching of mineral sulfides is controversial. Much of the controversy is due to the fact that the solution conditions, especially the concentrations of ferric and ferrous ions, change during experiments. The role of the bacteria would be more easily discernible if the concentrations of ferric and ferrous ions were maintained at set values throughout the experimental period. In this paper we report results obtained by using the constant redox...

  20. "Harshlighting" small blemishes on microarrays

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-03-01

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

  1. Navigating public microarray databases.

    Science.gov (United States)

    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

  2. AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data

    OpenAIRE

    Xia Yuannan; Nguyen The V; Lu Guoqing; Fromm Michael

    2006-01-01

    Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quanti...

  3. Bacterial monitoring with adhesive sheet in the international space station-"Kibo", the Japanese experiment module.

    Science.gov (United States)

    Ichijo, Tomoaki; Hieda, Hatsuki; Ishihara, Rie; Yamaguchi, Nobuyasu; Nasu, Masao

    2013-01-01

    Microbiological monitoring is important to assure microbiological safety, especially in long-duration space habitation. We have been continuously monitoring the abundance and diversity of bacteria in the International Space Station (ISS)-"Kibo" module to accumulate knowledge on microbes in the ISS. In this study, we used a new sampling device, a microbe-collecting adhesive sheet developed in our laboratory. This adhesive sheet has high operability, needs no water for sampling, and is easy to transport and store. We first validated the adhesive sheet as a sampling device to be used in a space habitat with regard to the stability of the bacterial number on the sheet during prolonged storage of up to 12 months. Bacterial abundance on the surfaces in Kibo was then determined and was lower than on the surfaces in our laboratory (10(5) cells [cm(2)](-1)), except for the return air grill, and the bacteria detected in Kibo were human skin microflora. From these aspects of microbial abundance and their phylogenetic affiliation, we concluded that Kibo has been microbiologically well maintained; however, microbial abundance may increase with the prolonged stay of astronauts. To ensure crew safety and understand bacterial dynamics in space habitation environments, continuous bacterial monitoring in Kibo is required.

  4. Small intestine bacterial overgrowth and irritable bowel syndrome-related symptoms: Experience with Rifaximin

    OpenAIRE

    Peralta, Sergio; Cottone, Claudia; Doveri, Tiziana; Almasio,Piero Luigi; Craxi, Antonio

    2009-01-01

    AIM: To estimate the prevalence of small intestinal bacterial overgrowth (SIBO) in our geographical area (Western Sicily, Italy) by means of an observational study, and to gather information on the use of locally active, non-absorbable antibiotics for treatment of SIBO.

  5. BayGO: Bayesian analysis of ontology term enrichment in microarray data

    Directory of Open Access Journals (Sweden)

    Gomes Suely L

    2006-02-01

    Full Text Available Abstract Background The search for enriched (aka over-represented or enhanced ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

  6. A new custom microarray for sRNA profiling in Escherichia coli.

    Science.gov (United States)

    Ruiz-Larrabeiti, Olatz; Plágaro, Ander Hernández; Gracia, Celine; Sevillano, Elena; Gallego, Lucía; Hajnsdorf, Eliane; Kaberdin, Vladimir R

    2016-07-01

    Bacterial small RNAs (sRNAs) play essential roles in the post-transcriptional control of gene expression. To improve their detection by conventional microarrays, we designed a custom microarray containing a group of probes targeting known and some putative Escherichia coli sRNAs. To assess its potential in detection of sRNAs, RNA profiling experiments were performed with total RNA extracted from E. coli MG1655 cells exponentially grown in rich (Luria-Bertani) and minimal (M9/glucose) media. We found that many sRNAs could yield reasonably strong and statistically significant signals corresponding to nearly all sRNAs annotated in the EcoCyc database. Besides differential expression of two sRNAs (GcvB and RydB), expression of other sRNAs was less affected by the composition of the growth media. Other examples of the differentially expressed sRNAs were revealed by comparing gene expression of the wild-type strain and its isogenic mutant lacking functional poly(A) polymerase I (pcnB). Further, northern blot analysis was employed to validate these data and to assess the existence of new putative sRNAs. Our results suggest that the use of custom microarrays with improved capacities for detection of sRNAs can offer an attractive opportunity for efficient gene expression profiling of sRNAs and their target mRNAs at the whole transcriptome level. PMID:27190161

  7. Seasonal fluctuations of bacterial community diversity in agricultural soil and experimental validation by laboratory disturbance experiments.

    Science.gov (United States)

    Meier, Christoph; Wehrli, Bernhard; van der Meer, Jan Roelof

    2008-08-01

    Natural fluctuations in soil microbial communities are poorly documented because of the inherent difficulty to perform a simultaneous analysis of the relative abundances of multiple populations over a long time period. Yet, it is important to understand the magnitudes of community composition variability as a function of natural influences (e.g., temperature, plant growth, or rainfall) because this forms the reference or baseline against which external disturbances (e.g., anthropogenic emissions) can be judged. Second, definition of baseline fluctuations in complex microbial communities may help to understand at which point the systems become unbalanced and cannot return to their original composition. In this paper, we examined the seasonal fluctuations in the bacterial community of an agricultural soil used for regular plant crop production by using terminal restriction fragment length polymorphism profiling (T-RFLP) of the amplified 16S ribosomal ribonucleic acid (rRNA) gene diversity. Cluster and statistical analysis of T-RFLP data showed that soil bacterial communities fluctuated very little during the seasons (similarity indices between 0.835 and 0.997) with insignificant variations in 16S rRNA gene richness and diversity indices. Despite overall insignificant fluctuations, between 8 and 30% of all terminal restriction fragments changed their relative intensity in a significant manner among consecutive time samples. To determine the magnitude of community variations induced by external factors, soil samples were subjected to either inoculation with a pure bacterial culture, addition of the herbicide mecoprop, or addition of nutrients. All treatments resulted in statistically measurable changes of T-RFLP profiles of the communities. Addition of nutrients or bacteria plus mecoprop resulted in bacteria composition, which did not return to the original profile within 14 days. We propose that at less than 70% similarity in T-RFLP, the bacterial communities risk to

  8. Identifying Fishes through DNA Barcodes and Microarrays

    Science.gov (United States)

    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

  9. Identifying Fishes through DNA Barcodes and Microarrays.

    Directory of Open Access Journals (Sweden)

    Marc Kochzius

    Full Text Available 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.

  10. A perspective on microarrays: current applications, pitfalls, and potential uses

    Directory of Open Access Journals (Sweden)

    Betenbaugh Michael

    2007-01-01

    Full Text Available Abstract With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold.

  11. COLOMBOS: access port for cross-platform bacterial expression compendia.

    Directory of Open Access Journals (Sweden)

    Kristof Engelen

    Full Text Available BACKGROUND: Microarrays are the main technology for large-scale transcriptional gene expression profiling, but the large bodies of data available in public databases are not useful due to the large heterogeneity. There are several initiatives that attempt to bundle these data into expression compendia, but such resources for bacterial organisms are scarce and limited to integration of experiments from the same platform or to indirect integration of per experiment analysis results. METHODOLOGY/PRINCIPAL FINDINGS: We have constructed comprehensive organism-specific cross-platform expression compendia for three bacterial model organisms (Escherichia coli, Bacillus subtilis, and Salmonella enterica serovar Typhimurium together with an access portal, dubbed COLOMBOS, that not only provides easy access to the compendia, but also includes a suite of tools for exploring, analyzing, and visualizing the data within these compendia. It is freely available at http://bioi.biw.kuleuven.be/colombos. The compendia are unique in directly combining expression information from different microarray platforms and experiments, and we illustrate the potential benefits of this direct integration with a case study: extending the known regulon of the Fur transcription factor of E. coli. The compendia also incorporate extensive annotations for both genes and experimental conditions; these heterogeneous data are functionally integrated in the COLOMBOS analysis tools to interactively browse and query the compendia not only for specific genes or experiments, but also metabolic pathways, transcriptional regulation mechanisms, experimental conditions, biological processes, etc. CONCLUSIONS/SIGNIFICANCE: We have created cross-platform expression compendia for several bacterial organisms and developed a complementary access port COLOMBOS, that also serves as a convenient expression analysis tool to extract useful biological information. This work is relevant to a large community

  12. DNA Microarray-Based Diagnostics.

    Science.gov (United States)

    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

  13. DNA Microarray-Based Diagnostics.

    Science.gov (United States)

    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.

  14. Emerging Use of Gene Expression Microarrays in Plant Physiology

    OpenAIRE

    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 e...

  15. Cluster stability scores for microarray data in cancer studies

    OpenAIRE

    Ghosh Debashis; Smolkin Mark

    2003-01-01

    Abstract Background A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, t...

  16. Bacteria repelling poly(methylmethacrylate-co-dimethylacrylamide) coatings for biomedical devices† †Electronic supplementary information (ESI) available: Polymer microarray screening, including analysis of bacterial adhesion by fluorescence microscopy and SEM, and chemical composition of bacteria repelling polymers identified in the screen; polymer synthesis and characterisation; preparation of catheter pieces and solvent studies, and details for confocal imaging/analysis. See DOI: 10.1039/c4tb01129e Click here for additional data file.

    Science.gov (United States)

    Venkateswaran, Seshasailam; Wu, Mei; Gwynne, Peter J.; Hardman, Ailsa; Lilienkampf, Annamaria; Pernagallo, Salvatore; Blakely, Garry; Swann, David G.

    2014-01-01

    Nosocomial infections due to bacteria have serious implications on the health and recovery of patients in a variety of medical scenarios. Since bacterial contamination on medical devices contributes to the majority of nosocomical infections, there is a need for redesigning the surfaces of medical devices, such as catheters and tracheal tubes, to resist the binding of bacteria. In this work, polyurethanes and polyacrylates/acrylamides, which resist binding by the major bacterial pathogens underpinning implant-associated infections, were identified using high-throughput polymer microarrays. Subsequently, two ‘hit’ polymers, PA13 (poly(methylmethacrylate-co-dimethylacrylamide)) and PA515 (poly(methoxyethylmethacrylate-co-diethylaminoethylacrylate-co-methylmethacrylate)), were used to coat catheters and substantially shown to decrease binding of a variety of bacteria (including isolates from infected endotracheal tubes and heart valves from intensive care unit patients). Catheters coated with polymer PA13 showed up to 96% reduction in bacteria binding in comparison to uncoated catheters. PMID:25580245

  17. Evaluation of toxicity of the mycotoxin citrinin using yeast ORF DNA microarray and Oligo DNA microarray

    Directory of Open Access Journals (Sweden)

    Nobumasa Hitoshi

    2007-04-01

    Full Text Available Abstract Background Mycotoxins are fungal secondary metabolites commonly present in feed and food, and are widely regarded as hazardous contaminants. Citrinin, one of the very well known mycotoxins that was first isolated from Penicillium citrinum, is produced by more than 10 kinds of fungi, and is possibly spread all over the world. However, the information on the action mechanism of the toxin is limited. Thus, we investigated the citrinin-induced genomic response for evaluating its toxicity. Results Citrinin inhibited growth of yeast cells at a concentration higher than 100 ppm. We monitored the citrinin-induced mRNA expression profiles in yeast using the ORF DNA microarray and Oligo DNA microarray, and the expression profiles were compared with those of the other stress-inducing agents. Results obtained from both microarray experiments clustered together, but were different from those of the mycotoxin patulin. The oxidative stress response genes – AADs, FLR1, OYE3, GRE2, and MET17 – were significantly induced. In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated. In the category of "metabolism", genes involved in the glutathione synthesis pathway were activated, and in the category of "cell rescue, defense and virulence", the ABC transporter genes were induced. To alleviate the induced stress, these cells might pump out the citrinin after modification with glutathione. While, the citrinin treatment did not induce the genes involved in the DNA repair. Conclusion Results from both microarray studies suggest that citrinin treatment induced oxidative stress in yeast cells. The genotoxicity was less severe than the patulin, suggesting that citrinin is less toxic than patulin. The reproducibility of the expression profiles was much better with the Oligo DNA microarray. However, the Oligo DNA microarray did not completely overcome cross

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

    Science.gov (United States)

    Delehanty, James B.; Ligler, Frances S.

    2002-01-01

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

  19. Bacterial Transformation and the Origins of Epidemics in the Interwar Period: The Epidemiological Significance of Fred Griffith's "Transforming Experiment".

    Science.gov (United States)

    Méthot, Pierre-Olivier

    2016-04-01

    Frederick Griffith (1879-1941) was an English bacteriologist at the Pathological Laboratory of the Ministry of Health in London who believed that progress in the epidemiology and control of infectious diseases would come only with more precise knowledge of the identity of the causative microorganisms. Over the years, Griffith developed and expanded a serological technique for identifying pathogenic microorganisms, which allowed the tracing of the sources of infectious disease outbreaks: slide agglutination. Yet Griffith is not remembered for his contributions to the biology and epidemiology of infectious diseases so much as for discovering the phenomenon known as 'transformation'. Griffith's discovery, for many, was a pure case of serendipity whose biological relevance had also largely escaped him. In this paper, I argue that the key to understanding the significance of bacterial transformation - and the scientific legacy of Fred Griffith - rests not only on it initiating a cascade of events leading to molecular genetics but also on its implications for epidemiology based on the biology of host-parasite interactions. Looking at Griffith's entire career, instead of focusing only on the transformation study, we can better appreciate the place of the latter within Griffith's overall contributions. Presented in this way, Griffith's experiment on bacterial transformation also ceases to appear as an anomaly, which in turn leads us to rethink some of the most prevalent historical conceptions about his work.

  20. Design, construction, characterization, and application of a hyperspectral microarray scanner.

    Science.gov (United States)

    Sinclair, Michael B; Timlin, Jerilyn A; Haaland, David M; Werner-Washburne, Margaret

    2004-04-01

    We describe the design, construction, and operation of a hyperspectral microarray scanner for functional genomic research. The hyperspectral instrument operates with spatial resolutions ranging from 3 to 30 microm and records the emission spectrum between 490 and 900 nm with a spectral resolution of 3 nm for each pixel of the microarray. This spectral information, when coupled with multivariate data analysis techniques, allows for identification and elimination of unwanted artifacts and greatly improves the accuracy of microarray experiments. Microarray results presented in this study clearly demonstrate the separation of fluorescent label emission from the spectrally overlapping emission due to the underlying glass substrate. We also demonstrate separation of the emission due to green fluorescent protein expressed by yeast cells from the spectrally overlapping autofluorescence of the yeast cells and the growth media.

  1. A measurement error model for microarray data analysis

    Institute of Scientific and Technical Information of China (English)

    ZHOU Yiming; CHENG Jing

    2005-01-01

    Microarray technology has been widely used to analyze the gene expression levels by detecting fluorescence intensity in a high throughput fashion. However, since the measurement error produced from various sources in microarray experiments is heterogeneous and too large to be ignored, we propose here a measurement error model for microarray data processing, by which the standard deviation of the measurement error is demonstrated to be linearly increased with fluorescence intensity. A robust algorithm, which estimates the parameters of the measurement error model from a single microarray without replicated spots, is provided. The model and algorithm for estimating of the parameters from a given data set are tested on both the real data set and the simulated data set, and the result has been proven satisfactory. And, combining the measurement error model with traditional Z-test method, a full statistical model has been developed. It can significantly improve the statistical inference for identifying differentially expressed genes.

  2. DNA Microarray-Based Typing of Streptococcus agalactiae Isolates

    OpenAIRE

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

    2014-01-01

    Streptococcus agalactiae frequently colonizes the urogenital tract, and it is a major cause of bacterial septicemia, meningitis, and pneumonia in newborns. For typing purposes, a microarray targeting group B streptococcus (GBS) virulence-associated markers and resistance genes was designed and validated with reference strains, as well as clinical and veterinary isolates. Selected isolates were also subjected to multilocus sequence typing. It was observed that putative typing markers, such as ...

  3. Inferring gene regulatory networks from asynchronous microarray data with AIRnet

    Directory of Open Access Journals (Sweden)

    Lai Chun Wan J

    2010-11-01

    Full Text Available Abstract Background Modern approaches to treating genetic disorders, cancers and even epidemics rely on a detailed understanding of the underlying gene signaling network. Previous work has used time series microarray data to infer gene signaling networks given a large number of accurate time series samples. Microarray data available for many biological experiments is limited to a small number of arrays with little or no time series guarantees. When several samples are averaged to examine differences in mean value between a diseased and normal state, information from individual samples that could indicate a gene relationship can be lost. Results Asynchronous Inference of Regulatory Networks (AIRnet provides gene signaling network inference using more practical assumptions about the microarray data. By learning correlation patterns for the changes in microarray values from all pairs of samples, accurate network reconstructions can be performed with data that is normally available in microarray experiments. Conclusions By focussing on the changes between microarray samples, instead of absolute values, increased information can be gleaned from expression data.

  4. Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens.

    Directory of Open Access Journals (Sweden)

    Leighton Pritchard

    2009-08-01

    Full Text Available Microarray comparative genomic hybridisation (aCGH provides an estimate of the relative abundance of genomic DNA (gDNA taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043 and Dickeya dadantii 3937 (Dda3937; and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.

  5. Microarray Scanner for Fluorescence Detection

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    A novel pseudo confocal microarray scanner is introduced, in which one dimension scanning is performed by a galvanometer optical scanner and a telecentric objective, another dimension scanning is performed by a stepping motor.

  6. Recent advances of protein microarrays

    OpenAIRE

    Hultschig, Claus; Kreutzberger, Jürgen; Seitz, Harald; Konthur, Zoltán; Büssow, Konrad; Lehrach, Hans

    2006-01-01

    Technological innovations and novel applications have greatly advanced the field of protein microarrays. Over the past two years, different types of protein microarrays have been used for serum profiling, protein abundance determinations, and identification of proteins that bind DNA or small compounds. However, considerable development is still required to ensure common quality standards and to establish large content repertoires. Here, we summarize applications available to date and discuss ...

  7. Are Gene Expression Microarray Analyses Reliable? A Review of Studies of Retinoic Acid Responsive Genes

    Institute of Scientific and Technical Information of China (English)

    Peter J. van der Spek; Andreas Kremer; Lynn Murry; Michael G. Walker

    2003-01-01

    Microarray analyses of gene expression are widely used, but reports of the same analyses by different groups give widely divergent results, and raise questions regarding reproducibility and reliability. We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes. These reports show substantial differences in their results. In this article, we review the methodology, results, and potential causes of differences in these applications of microarrays. Finally, we suggest practices to improve the reliability and reproducibility of microarray experiments.

  8. Are Gene Expression Microarray Analyses Reliable? A Review of Studies of Retinoic Acid Responsive Genes

    Institute of Scientific and Technical Information of China (English)

    PeterJ.vanderSpek; AndreasKremer; LynnMurry; MichaelG.Walker

    2003-01-01

    Microarray analyses of gene expression are widely used,but reports of the same analyses by different groups give widely divergent results,and raise questions regarding reproducibility and reliability.We take as an example recent published reports on microarray experiments that were designed to identify retinoic acid responsive genes.These reports show substantial differences in their results.In this article,we review the methodology,results,and potential causes of differences in these applications of microarrays.Finally,we suggest practices to improve the reliability and reproducibility of microarray experiments.

  9. Metadata Management and Semantics in Microarray Repositories

    Science.gov (United States)

    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

  10. Linking microarray reporters with protein functions

    Directory of Open Access Journals (Sweden)

    Gaj Stan

    2007-09-01

    Full Text Available Abstract Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/.

  11. AN INTELLIGENT SEGMENTATION ALGORITHM FOR MICROARRAY IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    P.Rajkumar

    2013-06-01

    Full Text Available Microarray technology consists of an array of thousands of microscopic spots of DNA oligonucleotides attached to a solid surface. It is a very powerful technique for analyzing gene expressions as well as to explore the underlying genetic causes of many human diseases. There are numerous applications of this technology, including environmental health research, drug design and discovery, clinical diagnosis and treatment and in cancer detection. The spots, which represent genes in microarray experiment contains the quantitative information that needs to be extracted accurately. For this process, preprocessing of microarray plays an essential role and it is also influential in future steps of the analysis. The three microarray preprocessing steps include gridding, segmentation and quantification. The first step is gridding, refers to the identification of the centre coordinates of each spot. The second step is segmentation, refers to the process of separating foreground and background fluorescence intensities. Segmentation is very important step as it directly affects the accuracy of gene expression analysis in the data mining process that follows. Accurate segmentation is one of the vital steps in microarray image processing. A novel method for segmentation of microarray image is proposed which accurately segment the spots from background when compared with adaptive threshold, combined global and local thresholdand fuzzy c-means clustering methods. Experimental results show that our proposed method provides better segmentation and improved intensity values than the above existing methods.

  12. Bacterial carbonatogenesis

    International Nuclear Information System (INIS)

    Several series of experiments in the laboratory as well as in natural conditions teach that the production of carbonate particles by heterotrophic bacteria follows different ways. The 'passive' carbonatogenesis is generated by modifications of the medium that lead to the accumulation of carbonate and bicarbonate ions and to the precipitation of solid particles. The 'active' carbonatogenesis is independent of the metabolic pathways. The carbonate particles are produced by ionic exchanges through the cell membrane following still poorly known mechanisms. Carbonatogenesis appears to be the response of heterotrophic bacterial communities to an enrichment of the milieu in organic matter. The active carbonatogenesis seems to start first. It is followed by the passive one which induces the growth of initially produced particles. The yield of heterotrophic bacterial carbonatogenesis and the amounts of solid carbonates production by bacteria are potentially very high as compared to autotrophic or chemical sedimentation from marine, paralic or continental waters. Furthermore, the bacterial processes are environmentally very ubiquitous; they just require organic matter enrichment. Thus, apart from purely evaporite and autotrophic ones, all Ca and/or Mg carbonates must be considered as from heterotrophic bacterial origin. By the way, the carbon of carbonates comes from primary organic matter. Such considerations ask questions about some interpretations from isotopic data on carbonates. Finally, bacterial heterotrophic carbonatogenesis appears as a fundamental phase in the relationships between atmosphere and lithosphere and in the geo-biological evolution of Earth. (author)

  13. The Stanford Tissue Microarray Database.

    Science.gov (United States)

    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

  14. Imaging combined autoimmune and infectious disease microarrays

    Science.gov (United States)

    Ewart, Tom; Raha, Sandeep; Kus, Dorothy; Tarnopolsky, Mark

    2006-09-01

    Bacterial and viral pathogens are implicated in many severe autoimmune diseases, acting through such mechanisms as molecular mimicry, and superantigen activation of T-cells. For example, Helicobacter pylori, well known cause of stomach ulcers and cancers, is also identified in ischaemic heart disease (mimicry of heat shock protein 65), autoimmune pancreatitis, systemic sclerosis, autoimmune thyroiditis (HLA DRB1*0301 allele susceptibility), and Crohn's disease. Successful antibiotic eradication of H.pylori often accompanies their remission. Yet current diagnostic devices, and test-limiting cost containment, impede recognition of the linkage, delaying both diagnosis and therapeutic intervention until the chronic debilitating stage. We designed a 15 minute low cost 39 antigen microarray assay, combining autoimmune, viral and bacterial antigens1. This enables point-of-care serodiagnosis and cost-effective narrowly targeted concurrent antibiotic and monoclonal anti-T-cell and anti-cytokine immunotherapy. Arrays of 26 pathogen and 13 autoimmune antigens with IgG and IgM dilution series were printed in triplicate on epoxysilane covalent binding slides with Teflon well masks. Sera diluted 1:20 were incubated 10 minutes, washed off, anti-IgG-Cy3 (green) and anti-IgM-Dy647 (red) were incubated for 5 minutes, washed off and the slide was read in an ArrayWoRx(e) scanning CCD imager (Applied Precision, Issaquah, WA). As a preliminary model for the combined infectious disease-autoimmune diagnostic microarray we surveyed 98 unidentified, outdated sera that were discarded after Hepatitis B antibody testing. In these, significant IgG or IgM autoantibody levels were found: dsDNA 5, ssDNA 11, Ro 2, RNP 7, SSB 4, gliadin 2, thyroglobulin 13 cases. Since control sera showed no autoantibodies, the high frequency of anti-DNA and anti-thyroglobulin antibodies found in infected sera lend increased support for linkage of infection to subsequent autoimmune disease. Expansion of the antigen

  15. Robust protein microarray image segmentation using improved seeded region growing algorithm

    Institute of Scientific and Technical Information of China (English)

    Liqiang Wang(王立强); Xuxiang Ni(倪旭翔); Zukang Lu(陆祖康)

    2003-01-01

    Protein microarray technology has recently emerged as a powerful tool for biomedical research. Before automatic analysis the protein microarray images, protein spots in the images must be determined appropriately by spot segmentation algorithm. In this paper, an improved seeded region growing (ISRG)algorithm for protein microarray segmentation is presented, the seeds are obtained by finding the positions of the printed spots, and the protein spot regions are grown through these seeds. The experiment results show that the presented algorithm is accurate for adaptive shape segmentation and robust for protein microarray images contaminated by noise.

  16. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

    Dufva, Hans Martin; Christensen, C.B.V.

    2005-01-01

    DNA microarrays have changed the field of biomedical sciences over the past 10 years. For several reasons, antibody and other protein microarrays have not developed at the same rate. However, protein and antibody arrays have emerged as a powerful tool to complement DNA microarrays during the post...

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

    Energy Technology Data Exchange (ETDEWEB)

    Gregory Stephanopoulos

    2004-07-31

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

  18. Women's Views and Experiences of the Triggers for Onset of Bacterial Vaginosis and Exacerbating Factors Associated with Recurrence.

    Directory of Open Access Journals (Sweden)

    Jade Bilardi

    Full Text Available Bacterial vaginosis (BV is the most common vaginal infection affecting women of childbearing age. While the aetiology and transmissibility of BV remain unclear, there is strong evidence to suggest an association between BV and sexual activity. This study explored women's views and experiences of the triggers for BV onset and factors associated with recurrence.A descriptive, social constructionist approach was chosen as the framework for the study. Thirty five women of varying sexual orientation who had experienced recurrent BV in the past five years took part in semi-structured interviews.The majority of women predominantly reported sexual contact triggered the onset of BV and sexual and non-sexual factors precipitated recurrence. Recurrence was most commonly referred to in terms of a 'flare-up' of symptoms. The majority of women did not think BV was a sexually transmitted infection however many reported being informed this by their clinician. Single women who attributed BV onset to sex with casual partners were most likely to display self-blame tendencies and to consider changing their future sexual behaviour. Women who have sex with women (WSW were more inclined to believe their partner was responsible for the transmission of or reinfection with BV and seek partner treatment or change their sexual practices.Findings from this study strongly suggest women believe that BV onset is associated with sexual activity, concurring with epidemiological data which increasingly suggest BV may be sexually transmitted. Exacerbating factors associated with recurrence were largely heterogeneous and may reflect the fact it is difficult to determine whether recurrence is due to persistent BV or a new infection in women. There was however evidence to suggest possible transmission and reinfection among WSW, reinforcing the need for new approaches to treatment and management strategies including male and female partner treatment trials.

  19. AMDA: an R package for the automated microarray data analysis

    Directory of Open Access Journals (Sweden)

    Foti Maria

    2006-07-01

    Full Text Available Abstract Background Microarrays are routinely used to assess mRNA transcript levels on a genome-wide scale. Large amount of microarray datasets are now available in several databases, and new experiments are constantly being performed. In spite of this fact, few and limited tools exist for quickly and easily analyzing the results. Microarray analysis can be challenging for researchers without the necessary training and it can be time-consuming for service providers with many users. Results To address these problems we have developed an automated microarray data analysis (AMDA software, which provides scientists with an easy and integrated system for the analysis of Affymetrix microarray experiments. AMDA is free and it is available as an R package. It is based on the Bioconductor project that provides a number of powerful bioinformatics and microarray analysis tools. This automated pipeline integrates different functions available in the R and Bioconductor projects with newly developed functions. AMDA covers all of the steps, performing a full data analysis, including image analysis, quality controls, normalization, selection of differentially expressed genes, clustering, correspondence analysis and functional evaluation. Finally a LaTEX document is dynamically generated depending on the performed analysis steps. The generated report contains comments and analysis results as well as the references to several files for a deeper investigation. Conclusion AMDA is freely available as an R package under the GPL license. The package as well as an example analysis report can be downloaded in the Services/Bioinformatics section of the Genopolis http://www.genopolis.it/

  20. D-MaPs - DNA-microarray projects: web-based software for multi-platform microarray analysis

    Directory of Open Access Journals (Sweden)

    Marcelo F. Carazzolle

    2009-01-01

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

  1. High quality protein microarray using in situ protein purification

    Directory of Open Access Journals (Sweden)

    Fleischmann Robert D

    2009-08-01

    protein solubility and denaturation problems caused by buffer exchange steps and freeze-thaw cycles, which are associated with resin-based purification, intermittent protein storage and deposition on microarrays. Conclusion An optimized platform for in situ protein purification on microarray slides using His-tagged recombinant proteins is a desirable tool for the screening of novel protein functions and protein-protein interactions. In the context of immunoproteomics, such protein microarrays are complimentary to approaches using non-recombinant methods to discover and characterize bacterial antigens.

  2. Intensity-based segmentation of microarray images.

    Science.gov (United States)

    Nagarajan, Radhakrishnan

    2003-07-01

    The underlying principle in microarray image analysis is that the spot intensity is a measure of the gene expression. This implicitly assumes the gene expression of a spot to be governed entirely by the distribution of the pixel intensities. Thus, a segmentation technique based on the distribution of the pixel intensities is appropriate for the current problem. In this paper, clustering-based segmentation is described to extract the target intensity of the spots. The approximate boundaries of the spots in the microarray are determined by manual adjustment of rectilinear grids. The distribution of the pixel intensity in a grid containing a spot is assumed to be the superposition of the foreground and the local background. The k-means clustering technique and the partitioning around medoids (PAM) were used to generate a binary partition of the pixel intensity distribution. The median (k-means) and the medoid (PAM) of the cluster members are chosen as the cluster representatives. The effectiveness of the clustering-based segmentation techniques was tested on publicly available arrays generated in a lipid metabolism experiment (Callow et al., 2000). The results are compared against those obtained using the region-growing approach (SPOT) (Yang et al., 2001). The effect of additive white Gaussian noise is also investigated. PMID:12906242

  3. Stata统计软件在细菌耐药性实验中的应用%Application of Stata on the Experiment of Bacterial Resistance

    Institute of Scientific and Technical Information of China (English)

    张少俊; 莫传伟; 彭拓华; 钟世顺; 杨彤

    2012-01-01

    Objective This article introduce a new method to carry on the experiment of bacterial resistance design with the statistical software-stata. Methods Using the command group and the command replace achieve both equal and unequal probability allocations of the experiment of bacterial resistance. Using the swor command could ensure all samplings without repetitions. Results It's convenient to design the experiment of bacterial resistance with the help of Stata. Conclusion Compared with manual and excel allocations, Stata is a statistical software that is easy to learn, simple to operate and has high repeatability.%目的 应用Stata统计软件细菌耐药性辅助实验设计.方法 应用Stata统计软件中的group、replace对细菌耐药性实验进行等概率与不等概率的分组,应用swor命令实现无重复抽样.结果 Stata统计软件能够方便的辅助细菌耐药性实验设计.结论 对比手工分组与excel分组,Stata统计软件好学易用,操作简单,可重复性高.

  4. Microarray results: how accurate are they?

    Directory of Open Access Journals (Sweden)

    Mane Shrikant

    2002-08-01

    Full Text Available Abstract Background DNA microarray technology is a powerful technique that was recently developed in order to analyze thousands of genes in a short time. Presently, microarrays, or chips, of the cDNA type and oligonucleotide type are available from several sources. The number of publications in this area is increasing exponentially. Results In this study, microarray data obtained from two different commercially available systems were critically evaluated. Our analysis revealed several inconsistencies in the data obtained from the two different microarrays. Problems encountered included inconsistent sequence fidelity of the spotted microarrays, variability of differential expression, low specificity of cDNA microarray probes, discrepancy in fold-change calculation and lack of probe specificity for different isoforms of a gene. Conclusions In view of these pitfalls, data from microarray analysis need to be interpreted cautiously.

  5. Optimisation algorithms for microarray biclustering.

    Science.gov (United States)

    Perrin, Dimitri; Duhamel, Christophe

    2013-01-01

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

  6. How Can Microarrays Unlock Asthma?

    Directory of Open Access Journals (Sweden)

    Alen Faiz

    2012-01-01

    Full Text Available Asthma is a complex disease regulated by the interplay of a large number of underlying mechanisms which contribute to the overall pathology. Despite various breakthroughs identifying genes related to asthma, our understanding of the importance of the genetic background remains limited. Although current therapies for asthma are relatively effective, subpopulations of asthmatics do not respond to these regimens. By unlocking the role of these underlying mechanisms, a source of novel and more effective treatments may be identified. In the new age of high-throughput technologies, gene-expression microarrays provide a quick and effective method of identifying novel genes and pathways, which would be impossible to discover using an individual gene screening approach. In this review we follow the history of expression microarray technologies and describe their contributions to advancing our current knowledge and understanding of asthma pathology.

  7. Microarray analysis in pulmonary hypertension.

    Science.gov (United States)

    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

  8. A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information

    Directory of Open Access Journals (Sweden)

    M. A. Smits

    2008-12-01

    Full Text Available Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1 Add synonyms of gene names by searching the Gene Ontology (GO database. (2 Search the Kyoto Encyclopaedia of Genes and Genomes (KEGG database for pathway information using this GO-enriched gene list. (3 Combine the pathway data with the microarray data and visualize the results using color codes indicating regulation. To demonstrate the power of the method, we used a previously reported chicken microarray experiment investigating line-specific reactions to Salmonella infection as an example.

  9. Bacterial discrimination by means of a universal array approach mediated by LDR (ligase detection reaction

    Directory of Open Access Journals (Sweden)

    Consolandi Clarissa

    2002-09-01

    Full Text Available Abstract Background PCR amplification of bacterial 16S rRNA genes provides the most comprehensive and flexible means of sampling bacterial communities. Sequence analysis of these cloned fragments can provide a qualitative and quantitative insight of the microbial population under scrutiny although this approach is not suited to large-scale screenings. Other methods, such as denaturing gradient gel electrophoresis, heteroduplex or terminal restriction fragment analysis are rapid and therefore amenable to field-scale experiments. A very recent addition to these analytical tools is represented by microarray technology. Results Here we present our results using a Universal DNA Microarray approach as an analytical tool for bacterial discrimination. The proposed procedure is based on the properties of the DNA ligation reaction and requires the design of two probes specific for each target sequence. One oligo carries a fluorescent label and the other a unique sequence (cZipCode or complementary ZipCode which identifies a ligation product. Ligated fragments, obtained in presence of a proper template (a PCR amplified fragment of the 16s rRNA gene contain either the fluorescent label or the unique sequence and therefore are addressed to the location on the microarray where the ZipCode sequence has been spotted. Such an array is therefore "Universal" being unrelated to a specific molecular analysis. Here we present the design of probes specific for some groups of bacteria and their application to bacterial diagnostics. Conclusions The combined use of selective probes, ligation reaction and the Universal Array approach yielded an analytical procedure with a good power of discrimination among bacteria.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  11. Construction of metastatic spinal cancer tissue microarrays

    Institute of Scientific and Technical Information of China (English)

    Yang Xinghai; Chen Huajiang; Xiao Jianru; Yuan Wen; Jia Lianshun

    2009-01-01

    Objective: To explore the construction of metastatic spinal cancer (MSC) tissue microarrays and validate its value in immunohistochemical study of MSC. Methods: Paraffin-embedded specimens from 71 MSC cases and 6 primary tumor cases were selected as donor blocks and prepared into MSC tissue microarrays by tissue array arrangement, the steps of which included location, punching, sampling, sample seeding, and re-diagnosis by hematoxylin-eosin (HE) as well as MMP-9 and MMP-14 immunohistochemical staining. Results: The MSC tissue microarrays thus constructed were intact and crackless, containing 154 complete and well arranged microarray points. None of the sectioned tissue microarrays was lost, and the results of HE staining was consistent with the primary pathologic diagnoses. Immunohistochemical staining was also good without non-specific or marginal effect. Conclusion: The MSC tissue microarrays have a high value in the immunohistochemical study of MSC.

  12. Microarray analysis reveals the actual specificity of enrichment media used for food safety assessment.

    Science.gov (United States)

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

    2011-06-01

    Microbial diagnostic microarrays are tools for simultaneous detection and identification of microorganisms in food, clinical, and environmental samples. In comparison to classic methods, microarray-based systems have the potential for high throughput, parallelism, and miniaturization. High specificity and high sensitivity of detection have been demonstrated. A microbial diagnostic microarray for the detection of the most relevant bacterial food- and waterborne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labeling of oligonucleotides and the phylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus and/or species level) and sensitive (0.1% relative and 10(4) CFU absolute sensitivity) detection of the target pathogens. In initial challenge studies of the applicability of microarray-based food analysis, we obtained results demonstrating the questionable specificity of standardized culture-dependent microbiological detection methods. Taking into consideration the importance of reliable food safety assessment methods, comprehensive performance assessment is essential. Results demonstrate the potential of this new pathogen diagnostic microarray to evaluate culture-based standard methods in microbiological food analysis.

  13. MICROARRAYS AND THEIR POTENTIAL IN MEDICINE

    Institute of Scientific and Technical Information of China (English)

    Erick Ling; Jie Xu

    2003-01-01

    Advancement in microarray technology can revolutionize many aspects of medicine. Microarrays have applications in gene expression profiling, genotyping, mutation analysis, gene identification, and pharmacology. This paper provides a brief review on the use of microarrays in studies of cancer, infectious diseases, chromosome disorders, neurological/mental disorders, and drugs, along with a prospect on its great potential in diagnosis, prognosis and the treatment of human diseases.

  14. [Experience of using bacteriophages and bitsillin-5 to reduce the incidence of respiratory diseases of bacterial ethiology in military personnel].

    Science.gov (United States)

    Akimkin, V G; Kalmykov, A A; Aminev, R M; Polyakov, V S; Artebyakin, S V

    2016-02-01

    The authors defined epidemiological efficacy and safety of the use of bacteriophages(streptococcal, staphylococcal, piobakferiophage multipartial) and bitsillin-5 to reduce tonsillitis morbidityand other respiratory diseases with bacterial etiology in groups of servicemen during their formationagainst increase of seasonal morbidity. The results of the use of these preventive agents were evaluatedby a comparative analysis of this disease in experimental and control groups. In total 510 healthy conscriptswere involved into the study. The effectiveness of prophylactic use of bacteriophages and bitsillin-5, whichprovided a reduction in the incidence of respiratory infections of bacterial ethiology, tonsillitis, and otherrespiratory diseases is showed. Recommendations on the choice of drugsfor the prevention of these infections,methods and organization of their application in organized groups are given.

  15. Fungal and bacterial growth responses to N fertilization and pH in the 150-year 'Park Grass' UK grassland experiment.

    Science.gov (United States)

    Rousk, Johannes; Brookes, Philip C; Bååth, Erland

    2011-04-01

    The effects of nitrogen (N) fertilization (0-150 kg N ha⁻¹ year⁻¹ since 1865) and pH (3.3-7.4) on fungal and bacterial growth, biomass and phospholipid fatty acid (PLFA) composition were investigated in grassland soils from the 'Park Grass Experiment', Rothamsted Research, UK. Bacterial growth decreased and fungal growth increased with lower pH, resulting in a 50-fold increase in the relative importance of fungi between pH 7.4 and 3.3. The PLFA-based fungal:bacterial biomass ratio was unchanged between pH 4.5 and 7.4, and decreased only below pH 4.5. Respiration and substrate-induced respiration biomass both decreased three- to fourfold with lower pH, but biomass concentrations estimated using PLFAs were unaffected by pH. N fertilization did not affect bacterial growth and marginally affected fungal growth while PLFA biomass marker concentrations were all reduced by higher N additions. Respiration decreased with higher N application, suggesting a reduced quality of the soil organic carbon. The PLFA composition was strongly affected by both pH and N. A comparison with a pH gradient in arable soil allowed us to generalize the pH effect between systems. There are 30-50-fold increases in the relative importance of fungi between high (7.4-8.3) and low (3.3-4.5) pH with concomitant reductions of respiration by 30-70%.

  16. Ontology-based retrieval of bio-medical information based on microarray text corpora

    DEFF Research Database (Denmark)

    Hansen, Kim Allan; Zambach, Sine; Have, Christian Theil

    degree. We explore the possibilities of retrieving biomedical information from microarrays in Gene Expression Omnibus (GEO), of which we have indexed a sample semantically, as a rst step towards ontology based searches. Through an example we argue that it is possible to improve the retrieval......Microarray technology is often used in gene expression exper- iments. Information retrieval in the context of microarrays has mainly been concerned with the analysis of the numeric data produced; how- ever, the experiments are often annotated with textual metadata. Al- though biomedical resources...

  17. Extraction of Bacterial RNA from Soil: Challenges and Solutions

    OpenAIRE

    Wang, Yong; Hayatsu, Masahito; Fujii, Takeshi

    2012-01-01

    Detection of bacterial gene expression in soil emerged in the early 1990s and provided information on bacterial responses in their original soil environments. As a key procedure in the detection, extraction of bacterial RNA from soil has attracted much interest, and many methods of soil RNA extraction have been reported in the past 20 years. In addition to various RT-PCR-based technologies, new technologies for gene expression analysis, such as microarrays and high-throughput sequencing techn...

  18. Multiscale study of bacterial growth: Experiments and model to understand the impact of gas exchange on global growth

    Science.gov (United States)

    Lalanne-Aulet, David; Piacentini, Adalberto; Guillot, Pierre; Marchal, Philippe; Moreau, Gilles; Colin, Annie

    2015-11-01

    Using a millifluidics and macroscale setup, we study quantitatively the impact of gas exchange on bacterial growth. In millifluidic environments, the permeability of the incubator materials allows an unlimited oxygen supply by diffusion. Moreover, the efficiency of diffusion at small scales makes the supply instantaneous in comparison with the cell division time. In hermetic closed vials, the amount of available oxygen is low. The growth curve has the same trend but is quantitatively different from the millifluidic situation. The analysis of all the data allows us to write a quantitative modeling enabling us to capture the entire growth process.

  19. Application of microarray technology in pulmonary diseases

    OpenAIRE

    Patlakas George; Tzouvelekis Argyris; Bouros Demosthenes

    2004-01-01

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

  20. Workflows for microarray data processing in the Kepler environment

    Directory of Open Access Journals (Sweden)

    Stropp Thomas

    2012-05-01

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

  1. Carbohydrate Microarrays in Plant Science

    DEFF Research Database (Denmark)

    Fangel, Jonatan Ulrik; Pedersen, H.L.; Vidal-Melgosa, S.;

    2012-01-01

    Almost all plant cells are surrounded by glycan-rich cell walls, which form much of the plant body and collectively are the largest source of biomass on earth. Plants use polysaccharides for support, defense, signaling, cell adhesion, and as energy storage, and many plant glycans are also important...... industrially and nutritionally. Understanding the biological roles of plant glycans and the effective exploitation of their useful properties requires a detailed understanding of their structures, occurrence, and molecular interactions. Microarray technology has revolutionized the massively high...... for plant research and can be used to map glycan populations across large numbers of samples to screen antibodies, carbohydrate binding proteins, and carbohydrate binding modules and to investigate enzyme activities....

  2. DNA Microarrays for Identifying Fishes

    Science.gov (United States)

    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

  3. Microarray analysis of Escherichia coli0157:H7

    Institute of Scientific and Technical Information of China (English)

    Hui-Ying Jin; Kai-Hua Tao; Yue-Xi Li; Fa-Qing Li; Su-Qin Li

    2005-01-01

    AIM: To establish the rapid, specific, and sensitive method for detecting O157:H7 with DNA microchips.METHODS: Specific oligonucleotide probes (26-28 nt) of bacterial antigenic and virulent genes of E. coli O157:H7 and other related pathogen genes were pre-synthesized and immobilized on a solid support to make microchips. The four genes encoding O157 somatic antigen (rfbE), H7 fiagellar antigen (fliC) and toxins (SLT1, SLT2) were monitored by multiplex PCR with four pairs of specific primers. Fluorescence-Cy3 labeled samples for hybridization were generated by PCR with Cy3-labeled single prime. Hybridization was performed for 60 min at 45 ℃. Microchip images were taken using a confocal fluorescent scanner.RESULTS: Twelve different bacterial strains were detected with various combinations of four virulent genes. All the O157:H7 strains yielded positive results by multiplex PCR.The size of the PCR products generated with these primers varied from 210 to 678 bp. All the rfbE/fliC/SLT1/SLT2 probes specifically recognized Cy3-labeled fluorescent samples from O157:H7 strains, or strains containing O157 and H7 genes. No cross hybridization of O157:H7 fluorescent samples occurred in other probes. Non-O157:H7 pathogens failed to yield any signal under comparable conditions. If the Cy3-labeled fluorescent product of O157 single PCR was diluted 50-fold, no signal was found in agarose gel electrophoresis, but a positive signal was found in microarray hybridization.CONCLUSION: Microarray analysis of O157:H7 is a rapid,specific, and efficient method for identification and detection of bacterial pathogens.

  4. FiRe and microarrays: a fast answer to burning questions

    OpenAIRE

    Garcion, Christophe; ApplimathFRI; Métraux, Jean-Pierre

    2006-01-01

    FiRe is a user-friendly Excel® macro designed to survey microarray data rapidly. This software interactively assembles data from different experiments and produces lists of candidate genes according to patterns of gene expression. Furthermore, macros bundled with FiRe can compare lists of genes, merge information from different spreadsheets, link candidates to information available from web-based databases, and produce heat-maps for easy visualization of microarray data. FiRe is freely availa...

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

    Science.gov (United States)

    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

  6. Bacterial profile and patterns of antimicrobial drug resistance in intra-abdominal infections: Current experience in a teaching hospital

    Directory of Open Access Journals (Sweden)

    Neetu Shree

    2013-01-01

    Full Text Available Context: Bacterial isolates from intra-abdominal infections, in particular, peritonitis and their unpredictable antimicrobial resistance patterns, continue to be a matter of concern not only globally but regionally too. Aim: An attempt in the present study was made to study the patterns of drug resistance in bacterial isolates, especially gram negative bacilli in intra-abdominal infections (IAI in our hospital. Materials and Methods: From 100 cases of peritonitis, identification of isolates was done as per recommended methods. Antimicrobial susceptibility and extended-spectrum beta-lactamase (ESBL testing were performed following the CLSI guidelines. Results: A total of 133 clinical isolates were obtained, of which 108 were aerobes and 22 anaerobes. Fungal isolates were recovered in only three cases. Escherichia coli (47/108 emerged as the most predominant pathogen followed by Klebsiella spp. (27/108, while Bacteroides fragilis emerged as the predominant anaerobe (12/22. Among coliforms, 61.7% E. coli and 74.1% Klebsiella spp. were ESBL positive. A high level of resistance was observed for beta lactams, ciprofloxacin, amikacin, and ertapenem. Ertapenem resistance (30-41% seen in coliforms, appears as an important issue. Imipenem, tigecycline, and colistin were the most consistently active agents tested against ESBL producers. Conclusion: Drug resistance continues to be a major concern in isolates from intra-abdominal infections. Treatment with appropriate antibiotics preceded by antimicrobial resistance testing aided by early diagnosis, adequate surgical management, and knowledge of antibiotic - resistant organisms appears effective in reducing morbidity and mortality in IAI cases.

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

    Directory of Open Access Journals (Sweden)

    Scheideler Marcel

    2005-04-01

    Full Text Available Abstract 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 http://genome.tugraz.at.

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

    Science.gov (United States)

    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

  9. Iterative normalization of cDNA microarray data.

    Science.gov (United States)

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

    2002-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Nelson Colleen C

    2005-09-01

    Full Text Available Abstract 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.

  11. DNA Microarrays in Herbal Drug Research

    Directory of Open Access Journals (Sweden)

    Preeti Chavan

    2006-01-01

    Full Text Available 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.

  12. Combined Bacteria Microarray and Quartz Crystal Microbalance Approach for Exploring Glycosignatures of Nontypeable Haemophilus influenzae and Recognition by Host Lectins.

    Science.gov (United States)

    Kalograiaki, Ioanna; Euba, Begoña; Proverbio, Davide; Campanero-Rhodes, María A; Aastrup, Teodor; Garmendia, Junkal; Solís, Dolores

    2016-06-01

    Recognition of bacterial surface epitopes by host receptors plays an important role in the infectious process and is intimately associated with bacterial virulence. Delineation of bacteria-host interactions commonly relies on the detection of binding events between purified bacteria- and host-target molecules. In this work, we describe a combined microarray and quartz crystal microbalance (QCM) approach for the analysis of carbohydrate-mediated interactions directly on the bacterial surface, thus preserving the native environment of the bacterial targets. Nontypeable Haemophilus influenzae (NTHi) was selected as a model pathogenic species not displaying a polysaccharide capsule or O-antigen-containing lipopolysaccharide, a trait commonly found in several important respiratory pathogens. Here, we demonstrate the usefulness of NTHi microarrays for exploring the presence of carbohydrate structures on the bacterial surface. Furthermore, the microarray approach is shown to be efficient for detecting strain-selective binding of three innate immune lectins, namely, surfactant protein D, human galectin-8, and Siglec-14, to different NTHi clinical isolates. In parallel, QCM bacteria-chips were developed for the analysis of lectin-binding kinetics and affinity. This novel QCM approach involves capture of NTHi on lectin-derivatized chips followed by formaldehyde fixation, rendering the bacteria an integrated part of the sensor chip, and subsequent binding assays with label-free lectins. The binding parameters obtained for selected NTHi-lectin pairs provide further insights into the interactions occurring at the bacterial surface.

  13. A two-genome microarray for the rice pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola and its use in the discovery of a difference in their regulation of hrp genes

    Directory of Open Access Journals (Sweden)

    Lin Ye

    2008-06-01

    Full Text Available Abstract Background Xanthomonas oryzae pv. oryzae (Xoo and X. oryzae pv. oryzicola (Xoc are bacterial pathogens of the worldwide staple and grass model, rice. Xoo and Xoc are closely related but Xoo invades rice vascular tissue to cause bacterial leaf blight, a serious disease of rice in many parts of the world, and Xoc colonizes the mesophyll parenchyma to cause bacterial leaf streak, a disease of emerging importance. Both pathogens depend on hrp genes for type III secretion to infect their host. We constructed a 50–70 mer oligonucleotide microarray based on available genome data for Xoo and Xoc and compared gene expression in Xoo strains PXO99A and Xoc strain BLS256 grown in the rich medium PSB vs. XOM2, a minimal medium previously reported to induce hrp genes in Xoo strain T7174. Results Three biological replicates of the microarray experiment to compare global gene expression in representative strains of Xoo and Xoc grown in PSB vs. XOM2 were carried out. The non-specific error rate and the correlation coefficients across biological replicates and among duplicate spots revealed that the microarray data were robust. 247 genes of Xoo and 39 genes of Xoc were differentially expressed in the two media with a false discovery rate of 5% and with a minimum fold-change of 1.75. Semi-quantitative-RT-PCR assays confirmed differential expression of each of 16 genes each for Xoo and Xoc selected for validation. The differentially expressed genes represent 17 functional categories. Conclusion We describe here the construction and validation of a two-genome microarray for the two pathovars of X. oryzae. Microarray analysis revealed that using representative strains, a greater number of Xoo genes than Xoc genes are differentially expressed in XOM2 relative to PSB, and that these include hrp genes and other genes important in interactions with rice. An exception was the rax genes, which are required for production of the host resistance elicitor AvrXa21

  14. Phenotype microarray profiling of the antibacterial activity of red cabbage

    Directory of Open Access Journals (Sweden)

    Hafidh RR

    2012-06-01

    Full Text Available Background: Functional food can be a potent source of wide array of biocomonents with antimicrobial activity. We investigated the antibacterial activity of red cabbage (RC extract on Gram negative and positive ATCC strains. Most intersting, we, for the first time, explored and analysed the complete phenotypic profile of RC-treated bacteria using Omnilog Phenotype Microarray. Results: This study revealed that the phenotype microarray (PM screen was a valuable tool in the search for compounds and their antibacterial mechanisms that can inhibit bacterial growth by affecting certain metabolic pathways. It was shown that RC exerted remarkable antibacterial effect on S. aureus and E. coli bacteria, and PM showed a wide range phenotypic profile of the exerted RC antibacterial activity. RC targeted the peptide, carbon, nutriontional assembly, and sulfur metbolic pathways altogether. The peptidoglycan synthesis pathway was inferred to be targeted by RC extract at a metabolic point different from other available cell wall-targeting drugs; these could be hot targets for the discovery of new therapy for many problematic microbes.Conclusions: Taken together, the phenotype microarray for functional food and medicinal plants can be a very useful tool for profiling their antimicrobial activity. Moreover, extracts of functional food can exert antibacterial activity by hitting a wide range of metabolic pathways, at the same time leading to very difficult condition for bacteria to rapidly develop resistance. Therefore, using functional foods or medicinal plants as such, or as extracts, can be superior on mono-targeting antibiotics if the optimal concentrations and conditions of these functional foods were sought.

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

    Science.gov (United States)

    Polen, Tino; Wendisch, Volker F

    2004-01-01

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

  16. Relationship between gene co-expression and probe localization on microarray slides

    Directory of Open Access Journals (Sweden)

    Qian Jiang

    2003-12-01

    Full Text Available Abstract Background Microarray technology allows simultaneous measurement of thousands of genes in a single experiment. This is a potentially useful tool for evaluating co-expression of genes and extraction of useful functional and chromosomal structural information about genes. Results In this work we studied the association between the co-expression of genes, their location on the chromosome and their location on the microarray slides by analyzing a number of eukaryotic expression datasets, derived from the S. cerevisiae, C. elegans, and D. melanogaster. We find that in several different yeast microarray experiments the distribution of the number of gene pairs with correlated expression profiles as a function of chromosomal spacing is peaked at short separations and has two superimposed periodicities. The longer periodicity has a spacing of 22 genes (~42 Kb, and the shorter periodicity is 2 genes (~4 Kb. Conclusion The relative positioning of DNA probes on microarray slides and source plates introduces subtle but significant correlations between pairs of genes. Careful consideration of this spatial artifact is important for analysis of microarray expression data. It is particularly relevant to recent microarray analyses that suggest that co-expressed genes cluster along chromosomes or are spaced by multiples of a fixed number of genes along the chromosome.

  17. 3D Biomaterial Microarrays for Regenerative Medicine

    DEFF Research Database (Denmark)

    Gaharwar, Akhilesh K.; Arpanaei, Ayyoob; Andresen, Thomas Lars;

    2015-01-01

    Three dimensional (3D) biomaterial microarrays hold enormous promise for regenerative medicine because of their ability to accelerate the design and fabrication of biomimetic materials. Such tissue-like biomaterials can provide an appropriate microenvironment for stimulating and controlling stem...

  18. SLIMarray: Lightweight software for microarray facility management

    Directory of Open Access Journals (Sweden)

    Marzolf Bruz

    2006-10-01

    Full Text Available Abstract Background Microarray core facilities are commonplace in biological research organizations, and need systems for accurately tracking various logistical aspects of their operation. Although these different needs could be handled separately, an integrated management system provides benefits in organization, automation and reduction in errors. Results We present SLIMarray (System for Lab Information Management of Microarrays, an open source, modular database web application capable of managing microarray inventories, sample processing and usage charges. The software allows modular configuration and is well suited for further development, providing users the flexibility to adapt it to their needs. SLIMarray Lite, a version of the software that is especially easy to install and run, is also available. Conclusion SLIMarray addresses the previously unmet need for free and open source software for managing the logistics of a microarray core facility.

  19. SAMMD: Staphylococcus aureus Microarray Meta-Database

    Directory of Open Access Journals (Sweden)

    Elasri Mohamed O

    2007-10-01

    Full Text Available Abstract Background Staphylococcus aureus is an important human pathogen, causing a wide variety of diseases ranging from superficial skin infections to severe life threatening infections. S. aureus is one of the leading causes of nosocomial infections. Its ability to resist multiple antibiotics poses a growing public health problem. In order to understand the mechanism of pathogenesis of S. aureus, several global expression profiles have been developed. These transcriptional profiles included regulatory mutants of S. aureus and growth of wild type under different growth conditions. The abundance of these profiles has generated a large amount of data without a uniform annotation system to comprehensively examine them. We report the development of the Staphylococcus aureus Microarray meta-database (SAMMD which includes data from all the published transcriptional profiles. SAMMD is a web-accessible database that helps users to perform a variety of analysis against and within the existing transcriptional profiles. Description SAMMD is a relational database that uses MySQL as the back end and PHP/JavaScript/DHTML as the front end. The database is normalized and consists of five tables, which holds information about gene annotations, regulated gene lists, experimental details, references, and other details. SAMMD data is collected from the peer-reviewed published articles. Data extraction and conversion was done using perl scripts while data entry was done through phpMyAdmin tool. The database is accessible via a web interface that contains several features such as a simple search by ORF ID, gene name, gene product name, advanced search using gene lists, comparing among datasets, browsing, downloading, statistics, and help. The database is licensed under General Public License (GPL. Conclusion SAMMD is hosted and available at http://www.bioinformatics.org/sammd/. Currently there are over 9500 entries for regulated genes, from 67 microarray

  20. Polymer microarrays for cell based applications

    OpenAIRE

    Hansen, Anne Klara Brigitte

    2012-01-01

    The development and identification of new biomaterials that can replace specific tissues and organs is desirable. In the presented PhD thesis polymer microarrays were applied for the screening of polyacrylates and polyurethanes and evaluation for material discovery for applications in the life sciences. In the first part of the thesis, the largest polymer microarray ever made with more than 7000 features was fabricated and subsequently used for the screening of polyacrylates...

  1. Text Mining Perspectives in Microarray Data Mining

    OpenAIRE

    Natarajan, Jeyakumar

    2013-01-01

    Current microarray data mining methods such as clustering, classification, and association analysis heavily rely on statistical and machine learning algorithms for analysis of large sets of gene expression data. In recent years, there has been a growing interest in methods that attempt to discover patterns based on multiple but related data sources. Gene expression data and the corresponding literature data are one such example. This paper suggests a new approach to microarray data mining as ...

  2. Subtype Identification of Avian Influenza Virus on DNA Microarray

    Institute of Scientific and Technical Information of China (English)

    WANG Xiu-rong; YU Kang-zhen; DENG Guo-hua; SHI Rui; LIU Li-ling; QIAO Chuan-ling; BAO Hong-mei; KONG Xian-gang; CHEN Hua-lan

    2005-01-01

    We have developed a rapid microarray-based assay for the reliable detection of H5, H7 and H9 subtypes of avian influenza virus (AIV). The strains used in the experiment were A/Goose/Guangdong/1/96 (H5N1), A/African starling/983/79 (H7N1) and A/Turkey/Wiscosin/1/66 (H9N2). The capture DNAs clones which encoding approximate 500-bp avian influenza virus gene fragments obtained by RT-PCR, were spotted on a slide-bound microarray. Cy5-1abeled fluorescent cDNAs,which generated from virus RNA during reverse transcription were hybridized to these capture DNAs. These capture DNAs contained multiple fragments of the hemagglutinin and matrix protein genes of AIV respectively, for subtyping and typing AIV. The arrays were scanned to determine the probe binding sites. The hybridization pattern agreed approximately with the known grid location of each target. The results show that DNA microarray technology provides a useful diagnostic method for AIV.

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

    Energy Technology Data Exchange (ETDEWEB)

    Hinman, R.; Thrall, B.; Wong, K,

    2002-01-01

    A cDNA microarray allows biologists to examine the expression of thousands of genes simultaneously. Researchers may analyze the complete transcriptional program of an organism in response to specific physiological or developmental conditions. By design, a cDNA microarray is an experiment with many variables and few controls. One question that inevitably arises when working with a cDNA microarray is data reproducibility. How easy is it to confirm mRNA expression patterns? In this paper, a case study involving the treatment of a murine macrophage RAW 264.7 cell line with tumor necrosis factor alpha (TNF) was used to obtain a rough estimate of data reproducibility. Two trials were examined and a list of genes displaying either a > 2-fold or > 4-fold increase in gene expression was compiled. Variations in signal mean ratios between the two slides were observed. We can assume that erring in reproducibility may be compensated by greater inductive levels of similar genes. Steps taken to obtain results included serum starvation of cells before treatment, tests of mRNA for quality/consistency, and data normalization.

  4. BASE - 2nd generation software for microarray data management and analysis

    Directory of Open Access Journals (Sweden)

    Nordborg Nicklas

    2009-10-01

    Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

  5. Resistance of Bacterial Endospores to Outer Space for Planetary Protection Purposes—Experiment PROTECT of the EXPOSE-E Mission

    OpenAIRE

    Horneck, Gerda; Moeller, Ralf; Cadet, Jean; Douki, Thierry; Mancinelli, Rocco L.; Nicholson, Wayne L.; Panitz, Corinna; Rabbow, Elke; Rettberg, Petra; Spry, Andrew; Stackebrandt, Erko; Vaishampayan, Parag; Kasthuri J Venkateswaran

    2012-01-01

    Spore-forming bacteria are of particular concern in the context of planetary protection because their tough endospores may withstand certain sterilization procedures as well as the harsh environments of outer space or planetary surfaces. To test their hardiness on a hypothetical mission to Mars, spores of Bacillus subtilis 168 and Bacillus pumilus SAFR-032 were exposed for 1.5 years to selected parameters of space in the experiment PROTECT during the EXPOSE-E mission on board the Internationa...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-01-01

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp. PMID:27657141

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

    Directory of Open Access Journals (Sweden)

    Paula Fernandez

    Full Text Available 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.

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

    Directory of Open Access Journals (Sweden)

    Bashar Yafouz

    2014-04-01

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

  11. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

    Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.;

    2003-01-01

    GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization......, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user....

  12. An experience on the purification of bacterially infested I.T.U. TRIGA Mark-II reactor water

    International Nuclear Information System (INIS)

    Because of the failure of conductivity meter at the makeup water purification system, highconductivity water was added into the tank water. For this reason, the conductivity of the tank water rose to 12.5 μS/cm and the tank water became turbid. Bacteriological analysis showed that the tank water became infested with bacteria. A suitable method for the sterilization of the tank water by means of the irradiation and the chemical materials was searched. Hydrogen-Peroxide (H2P2) was chosen as the most suitable material for the chemical sterilization. However, it was not used since it was not experienced in any reactor previously and the tank water was cleaned from the bacteria by means of the irradiation and the purification system. The makeup water purification system was modified permanently for this purpose. As a result, conductivity of the tank water was decreased to 0.2 μS/cm by using this modified system. Some new experiences about the purification and protection of tank water from the bacteria were gained during these operations. (orig.)

  13. Analysis of porcine MHC using microarrays.

    Science.gov (United States)

    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

  14. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

    data. For this, the DNA microarray technology has gained enormous popularity due to its ability to measure the presence or the activity of thousands of genes simultaneously. Microarrays for high throughput data analyses are not limited to a few organisms but may be applied to everything from bacteria...... at identifying the exact breakpoints where DNA has been gained or lost. In this thesis, three popular methods are compared and a realistic simulation model is presented for generating artificial data with known breakpoints and known DNA copy number. By using simulated data, we obtain a realistic evaluation...... of various strains of the bacteria, e.g. Escherichia coli, with regard to genes involved in pathogenesis. Finally, this thesis present results demonstrating that the gene expression level is sequence dependent, that is, it depends on both DNA structure and codon usage bias. Here, microarray data was used...

  15. Finding consistent disease subnetworks across microarray datasets

    Directory of Open Access Journals (Sweden)

    Soh Donny

    2011-11-01

    Full Text Available Abstract Background While contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet. SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as “subnetworks”. Results We tested SNet on independent datasets of several diseases, including childhood ALL, DMD and lung cancer. For each of these diseases, we obtained two independent microarray datasets produced by distinct labs on distinct platforms. In each case, our technique consistently produced almost the same list of significant nontrivial subnetworks from two independent sets of microarray data. The gene-level agreement of these significant subnetworks was between 51.18% to 93.01%. In contrast, when the same pairs of microarray datasets were analysed using GSEA, t-test and SAM, this percentage fell between 2.38% to 28.90% for GSEA, 49.60% tp 73.01% for t-test, and 49.96% to 81.25% for SAM. Furthermore, the genes selected using these existing methods did not form subnetworks of substantial size. Thus it is more probable that the subnetworks selected by our technique can provide the researcher with more descriptive information on the portions of the pathway actually affected by the disease. Conclusions These results clearly demonstrate that our technique generates significant subnetworks and genes that are more consistent and reproducible across datasets compared to the other popular methods available (GSEA, t-test and SAM. The large size of subnetworks which we generate indicates that they are generally more biologically significant (less likely to be spurious. In addition, we have chosen two sample subnetworks and validated them with

  16. Discovering biological progression underlying microarray samples.

    Directory of Open Access Journals (Sweden)

    Peng Qiu

    2011-04-01

    Full Text Available In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD, to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression, and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the

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

    Directory of Open Access Journals (Sweden)

    Kaplinski Lauris

    2009-05-01

    Full Text Available Abstract 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.

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

    Science.gov (United States)

    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

  19. Differentiation of salivary bacterial profiles of subjects with periodontitis and dental caries

    DEFF Research Database (Denmark)

    Belstrøm, Daniel; Fiehn, Nils-Erik; Nielsen, Claus H;

    2015-01-01

    Bacterial profiles of saliva in subjects with periodontitis and dental caries have been demonstrated to differ from that of oral health. The aim of this comparative analysis of existing data generated by the Human Oral Microbe Identification Microarray (HOMIM) from 293 stimulated saliva samples...... was to compare bacterial profiles of saliva in subjects with periodontitis and dental caries....

  20. Bacterial Vaginosis

    Science.gov (United States)

    ... 586. Related Content STDs during Pregnancy Fact Sheet Pregnancy and HIV, Viral Hepatitis, and STD Prevention Pelvic Inflammatory Disease ( ... Bacterial Vaginosis (BV) Chlamydia Gonorrhea Genital Herpes Hepatitis HIV/AIDS & STDs Human Papillomavirus ... STDs See Also Pregnancy Reproductive ...

  1. Bacterial Meningitis

    Science.gov (United States)

    ... Schedules Preteen & Teen Vaccines Meningococcal Disease Sepsis Bacterial Meningitis Recommend on Facebook Tweet Share Compartir On this ... serious disease. Laboratory Methods for the Diagnosis of Meningitis This manual summarizes laboratory methods used to isolate, ...

  2. Design of a covalently bonded glycosphingolipid microarray

    DEFF Research Database (Denmark)

    Arigi, Emma; Blixt, Klas Ola; Buschard, Karsten;

    2012-01-01

    , a monoclonal antibody to sulfatide, Sulph 1; and a polyclonal antiserum reactive to asialo-G(M2)). Preliminary evaluation of the method indicated successful immobilization of the GSLs, and selective binding of test probes. The potential utility of this methodology for designing covalent microarrays......, the major classes of plant and fungal GSLs. In this work, a prototype "universal" GSL-based covalent microarray has been designed, and preliminary evaluation of its potential utility in assaying protein-GSL binding interactions investigated. An essential step in development involved the enzymatic release...

  3. The use of microarrays in microbial ecology

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, G.L.; He, Z.; DeSantis, T.Z.; Brodie, E.L.; Zhou, J.

    2009-09-15

    Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogenetic microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer

  4. Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results

    Directory of Open Access Journals (Sweden)

    Dai Yilin

    2012-06-01

    Full Text Available Abstract Background Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. Findings We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Conclusion Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

  5. Microarray data mining with visual programming

    OpenAIRE

    Xu, Qikai; Curk, Tomaž; Shaulsky, Gad; Petrovič, Uroš; Bratko, Ivan; Zupan, Blaž; Demšar, Janez; Leban, Gregor

    2005-01-01

    Visual programming offers an intuitive means of combining known analysis and visualization methods into powerful applications. The system presented here enables users who are not programmers to manage microarray and genomic data flow and to customize their analyses by combining common data analysis tools to fit their needs.

  6. Shrinkage covariance matrix approach for microarray data

    Science.gov (United States)

    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 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.

  7. Diagnostic Oligonucleotide Microarray Fingerprinting of Bacillus Isolates

    OpenAIRE

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

    2006-01-01

    A genome-independent microarray and new statistical techniques were used to genotype Bacillus strains and quantitatively compare DNA fingerprints with the known taxonomy of the genus. A synthetic DNA standard was used to understand process level variability and lead to recommended standard operating procedures for microbial forensics and clinical diagnostics.

  8. Single-species microarrays and comparative transcriptomics.

    Directory of Open Access Journals (Sweden)

    Frédéric J J Chain

    Full Text Available BACKGROUND: Prefabricated expression microarrays are currently available for only a few species but methods have been proposed to extend their application to comparisons between divergent genomes. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate that the hybridization intensity of genomic DNA is a poor basis on which to select unbiased probes on Affymetrix expression arrays for studies of comparative transcriptomics, and that doing so produces spurious results. We used the Affymetrix Xenopus laevis microarray to evaluate expression divergence between X. laevis, X. borealis, and their F1 hybrids. When data are analyzed with probes that interrogate only sequences with confirmed identity in both species, we recover results that differ substantially analyses that use genomic DNA hybridizations to select probes. CONCLUSIONS/SIGNIFICANCE: Our findings have implications for the experimental design of comparative expression studies that use single-species microarrays, and for our understanding of divergent expression in hybrid clawed frogs. These findings also highlight important limitations of single-species microarrays for studies of comparative transcriptomics of polyploid species.

  9. Role of Permutations in Significance Analysis of Microarray and Clustering of Significant Microarray Gene list

    Directory of Open Access Journals (Sweden)

    Tejashree Damle

    2012-03-01

    Full Text Available Microarray is the gene expression data that represent gene in different biological states. Methods are needed to determine the significance of these changes while accounting for the enormous number of genes. Significance analysis of microarrays (SAM is a statistical technique for determining whether changes in gene expression are statistically significant. During the SAM procedure permutation of microarray data is considered to observe the changes in the overall expression level of data. With increasing number of permutations false discovery rate for gene set varies. In our work we took microarray data of Normal Glucose Tolerance (NGT, and Diabetes Mellitus (DM Type II. In this paper we proposed the result of permutations during execution of SAM algorithm. The hierarchical clustering is applied for observing expression levels of significant data and visualize it with heat map.

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

    Directory of Open Access Journals (Sweden)

    Hyunseok P Kang

    2010-01-01

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

  11. A comparative analysis of DNA barcode microarray feature size

    OpenAIRE

    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 platfor...

  12. Facilitating functional annotation of chicken microarray data

    Directory of Open Access Journals (Sweden)

    Gresham Cathy R

    2009-10-01

    Full Text Available Abstract 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

  13. Microarray-based detection of Salmonella enterica serovar Typhimurium transposon mutants that cannot survive in macrophages and mice.

    Science.gov (United States)

    Chan, Kaman; Kim, Charles C; Falkow, Stanley

    2005-09-01

    DNA microarrays provide an opportunity to combine the principles of signature-tagged mutagenesis (STM) with microarray technology to identify potentially important bacterial virulence genes. The scope of DNA microarrays allows for less laborious screening on a much larger scale than possible by STM alone. We have adapted a microarray-based transposon tracking strategy for use with a Salmonella enterica serovar Typhimurium cDNA microarray in order to identify genes important for survival and replication in RAW 264.7 mouse macrophage-like cells or in the spleens of BALB/cJ mice. A 50,000-CFU transposon library of S. enterica serovar Typhimurium strain SL1344 was serially passaged in cultured macrophages or intraperitoneally inoculated into BALB/cJ mice. The bacterial genomic DNA was isolated and processed for analysis on the microarray. The novel application of this approach to identify mutants unable to survive in cultured cells resulted in the identification of components of Salmonella pathogenicity island 2 (SPI2), which is known to be critical for intracellular survival and replication. In addition, array results indicated that a number of SPI1-associated genes, currently not associated with intracellular survival, are negatively selected. However, of the SPI1-associated mutants individually tested for intracellular survival, only a sirA mutant exhibited reduced numbers relative to those of wild-type bacteria. Of the mutants unable to survive in mice, significant proportions are either components of the SPI2 pathogenicity island or involved in lipopolysaccharide synthesis. This observation is in agreement with results obtained in the original S. enterica serovar Typhimurium STM screen, illustrating the utility of this approach for the high-throughput identification of virulence factors important for survival in the host.

  14. EXPANDER – an integrative program suite for microarray data analysis

    Directory of Open Access Journals (Sweden)

    Shiloh Yosef

    2005-09-01

    Full Text Available Abstract Background Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis. Results Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms. Conclusion EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander

  15. Comparison of three microarray probe annotation pipelines: differences in strategies and their effect on downstream analysis

    NARCIS (Netherlands)

    Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.

    2009-01-01

    Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/

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

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    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.

  17. A proposed metric for assessing the measurement quality of individual microarrays

    Directory of Open Access Journals (Sweden)

    Scheirer Katherine E

    2006-01-01

    Full Text Available Abstract Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements.

  18. Application of Microarray Technology and Softcomputing in Cancer Biology : A Review

    Directory of Open Access Journals (Sweden)

    P.K.Vaishali & Dr. A.vinayababu

    2011-10-01

    Full Text Available DNA microarray technology has emerged as a boon to the scientific community in understanding thegrowth and development of life as well as in widening their knowledge in exploring the geneticcauses of anomalies occurring in the working of the human body. microarray technology makesbiologists be capable of monitoring expression of thousands of genes in a single experiment on asmall chip. Extracting useful knowledge and info from these microarray has attracted the attention ofmany biologists and computer scientists. Knowledge engineering has revolutionalized the way inwhich the medical data is being looked at. Soft computing is a branch of computer science capable ofanalyzing complex medical data. Advances in the area of microarray –based expression analysishave led to the promise of cancer diagnosis using new molecular based approaches. Many studiesand methodologies have come up which analyszes the gene espression data by using thetechniques in data mining such as feature selection, classification, clustering etc. emboiding the softcomputing methods for more accuracy. This review is an attempt to look at the recent advances incancer research with DNA microarray technology , data mining and soft computing techniques.

  19. Signal oscillation is another reason for variability in microarray-based gene expression quantification.

    Directory of Open Access Journals (Sweden)

    Raghvendra Singh

    Full Text Available Microarrays have been widely used for various biological applications, such as, gene expression profiling, determination of SNPs, and disease profiling. However, quantification and analysis of microarray data have been a challenge. Previously, by taking into account translational and rotational diffusion of the target DNA, we have shown that the rate of hybridization depends on its size. Here, by mathematical modeling of surface diffusion of transcript, we show that the dynamics of hybridization on DNA microarray surface is inherently oscillatory and the amplitude of oscillation depends on fluid velocity. We found that high fluid velocity enhances the signal without affecting the background, and reduces the oscillation, thereby reducing likelihood of inter- and intra-experiment variability. We further show that a strong probe reduces dependence of signal-to-noise ratio on probe strength, decreasing inter-microarray variability. On the other hand, weaker probes are required for SNP detection. Therefore, we recommend high fluid velocity and strong probes for all microarray applications except determination of SNPs. For SNP detection, we recommend high fluid velocity with weak probe on the spot. We also recommend a surface with high adsorption and desorption rates of transcripts.

  20. Identification of listeria species isolated in Tunisia by Microarray based assay : results of a preliminary study

    International Nuclear Information System (INIS)

    Microarray-based assay is a new molecular approach for genetic screening and identification of microorganisms. We have developed a rapid microarray-based assay for the reliable detection and discrimination of Listeria spp. in food and clinical isolates from Tunisia. The method used in the present study is based on the PCR amplification of a virulence factor gene (iap gene). the PCR mixture contained cyanine Cy5labeled dCTP. Therefore, The PCR products were fluorescently labeled. The presence of multiple species-specific sequences within the iap gene enabled us to design different oligoprobes per species. The species-specific sequences of the iap gene used in this study were obtained from genBank and then aligned for phylogenetic analysis in order to identify and retrieve the sequences of homologues of the amplified iap gene analysed. 20 probes were used for detection and identification of 22 food isolates and clinical isolates of Listeria spp (L. monocytogenes, L. ivanovi), L. welshimeri, L. seeligeri, and L. grayi). Each bacterial gene was identified by hybridization to oligoprobes specific for each Listeria species and immobilized on a glass surface. The microarray analysis showed that 5 clinical isolates and 2 food isolates were identified listeria monocytogenes. Concerning the remaining 15 food isolates; 13 were identified listeria innocua and 2 isolates could not be identified by microarray based assay. Further phylogenetic and molecular analysis are required to design more species-specific probes for the identification of Listeria spp. Microarray-based assay is a simple and rapid method used for Listeria species discrimination

  1. Genomic Imbalances in Neonates With Birth Defects: High Detection Rates by Using Chromosomal Microarray Analysis

    Science.gov (United States)

    Lu, Xin-Yan; Phung, Mai T.; Shaw, Chad A.; Pham, Kim; Neil, Sarah E.; Patel, Ankita; Sahoo, Trilochan; Bacino, Carlos A.; Stankiewicz, Pawel; Lee Kang, Sung-Hae; Lalani, Seema; Chinault, A. Craig; Lupski, James R.; Cheung, Sau W.; Beaudet, Arthur L.

    2009-01-01

    OBJECTIVES Our aim was to determine the frequency of genomic imbalances in neonates with birth defects by using targeted array-based comparative genomic hybridization, also known as chromosomal microarray analysis. METHODS Between March 2006 and September 2007, 638 neonates with various birth defects were referred for chromosomal microarray analysis. Three consecutive chromosomal microarray analysis versions were used: bacterial artificial chromosome-based versions V5 and V6 and bacterial artificial chromosome emulated oligonucleotide-based version V6 Oligo. Each version had targeted but increasingly extensive genomic coverage and interrogated >150 disease loci with enhanced coverage in genomic rearrangement-prone pericentromeric and subtelomeric regions. RESULTS Overall, 109 (17.1%) patients were identified with clinically significant abnormalities with detection rates of 13.7%, 16.6%, and 19.9% on V5, V6, and V6 Oligo, respectively. The majority of these abnormalities would not be defined by using karyotype analysis. The clinically significant detection rates by use of chromosomal microarray analysis for various clinical indications were 66.7% for “possible chromosomal abnormality” ± “others” (other clinical indications), 33.3% for ambiguous genitalia ± others, 27.1% for dysmorphic features + multiple congenital anomalies ± others, 24.6% for dysmorphic features ± others, 21.8% for congenital heart disease ± others, 17.9% for multiple congenital anomalies ± others, and 9.5% for the patients referred for others that were different from the groups defined. In all, 16 (2.5%) patients had chromosomal aneuploidies, and 81 (12.7%) patients had segmental aneusomies including common microdeletion or microduplication syndromes and other genomic disorders. Chromosomal mosaicism was found in 12 (1.9%) neonates. CONCLUSIONS Chromosomal microarray analysis is a valuable clinical diagnostic tool that allows precise and rapid identification of genomic imbalances

  2. A Hybrid Reduction Approach for Enhancing Cancer Classification of Microarray Data

    Directory of Open Access Journals (Sweden)

    Abeer M. Mahmoud

    2014-10-01

    Full Text Available This paper presents a novel hybrid machine learning (MLreduction approach to enhance cancer classification accuracy of microarray data based on two ML gene ranking techniques (T-test and Class Separability (CS. The proposed approach is integrated with two ML classifiers; K-nearest neighbor (KNN and support vector machine (SVM; for mining microarray gene expression profiles. Four public cancer microarray databases are used for evaluating the proposed approach and successfully accomplish the mining process. These are Lymphoma, Leukemia SRBCT, and Lung Cancer. The strategy to select genes only from the training samples and totally excluding the testing samples from the classifier building process is utilized for more accurate and validated results. Also, the computational experiments are illustrated in details and comprehensively presented with literature related results. The results showed that the proposed reduction approach reached promising results of the number of genes supplemented to the classifiers as well as the classification accuracy.

  3. How the RNA isolation method can affect microRNA microarray results

    DEFF Research Database (Denmark)

    Podolska, Agnieszka; Kaczkowski, Bogumil; Litman, Thomas;

    2011-01-01

    RNA microarray analysis on porcine brain tissue. One method is a phenol-guanidine isothiocyanate-based procedure that permits isolation of total RNA. The second method, miRVana™ microRNA isolation, is column based and recovers the small RNA fraction alone. We found that microarray analyses give different results...... that depend on the RNA fraction used, in particular because some microRNAs appear very sensitive to the RNA isolation method. We conclude that precautions need to be taken when comparing microarray studies based on RNA isolated with different methods.......The quality of RNA is crucial in gene expression experiments. RNA degradation interferes in the measurement of gene expression, and in this context, microRNA quantification can lead to an incorrect estimation. In the present study, two different RNA isolation methods were used to perform micro...

  4. Improved statistical analysis of budding yeast TAG microarrays revealed by defined spike-in pools.

    Science.gov (United States)

    Peyser, Brian D; Irizarry, Rafael A; Tiffany, Carol W; Chen, Ou; Yuan, Daniel S; Boeke, Jef D; Spencer, Forrest A

    2005-09-15

    Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide 'TAG' sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.

  5. Rapid and sensitive detection of fluoroquinolone-resistant Escherichia coli from urine samples using a genotyping DNA microarray.

    Science.gov (United States)

    Yu, Xiaolei; Susa, Milorad; Weile, Jan; Knabbe, Cornelius; Schmid, Rolf D; Bachmann, Till T

    2007-10-01

    Urinary tract infections (UTI) are among the most common bacterial infections in humans, with Escherichia coli being the major cause of infection. Fluoroquinolone resistance of uropathogenic E. coli has increased significantly over the last decade. In this study a microarray-based assay was developed and applied, which provides a rapid, sensitive and specific detection of fluoroquinolone-resistant E. coli in urine. The capture probes were designed against previously identified and described hotspots for quinolone resistance (codons 83 and 87 of gyrA). The key goals of this development were to reduce assay time while increasing the sensitivity and specificity as compared with a pilot version of a gyrA genotyping DNA microarray. The performance of the assay was demonstrated with pure cultures of 30 E. coli isolates as well as with urine samples spiked with 6 E. coli isolates. The microarray results were confirmed by standard DNA sequencing and were in full agreement with the phenotypic antimicrobial susceptibility testing using standard methods. The DNA microarray test displayed an assay time of 3.5h, a sensitivity of 100CFU/ml, and the ability to detect fluoroquinolone-resistant E. coli in the presence of a 10-fold excess of fluoroquinolone-susceptible E. coli cells. As a consequence, we believe that this microarray-based determination of antibiotics resistance has a true potential for the application in clinical routine laboratories in the future.

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  9. Comparison of Alexa Fluor and CyDye for practical DNA microarray use.

    Science.gov (United States)

    Ballard, Joanne L; Peeva, Violet K; deSilva, Christopher J S; Lynch, Jessica L; Swanson, Nigel R

    2007-07-01

    Microarrays are a powerful tool for comparison and understanding of gene expression levels in healthy and diseased states. The method relies upon the assumption that signals from microarray features are a reflection of relative gene expression levels of the cell types under investigation. It has previously been reported that the classical fluorescent dyes used for microarray technology, Cy3 and Cy5, are not ideal due to the decreased stability and fluorescence intensity of the Cy5 dye relative to the Cy3, such that dye bias is an accepted phenomena necessitating dye swap experimental protocols and analysis of differential dye affects. The incentive to find new fluorophores is based on alleviating the problem of dye bias through synonymous performance between counterpart dyes. Alexa Fluor 555 and Alexa Fluor 647 are increasingly promoted as replacements for CyDye in microarray experiments. Performance relates to the molecular and steric similarities, which will vary for each new pair of dyes as well as the spectral integrity for the specific application required. Comparative analysis of the performance of these two competitive dye pairs in practical microarray applications is warranted towards this end. The findings of our study showed that both dye pairs were comparable but that conventional CyDye resulted in significantly higher signal intensities (P 0.05). This translated to greater levels of differential gene expression with CyDye than with the Alexa Fluor counterparts. However, CyDye fluorophores and in particular Cy5, were found to be less photostable over time and following repeated scans in microarray experiments. These results suggest that precautions against potential dye affects will continue to be necessary and that no one dye pair negates this need.

  10. Bacterial Adhesion & Blocking Bacterial Adhesion

    DEFF Research Database (Denmark)

    Vejborg, Rebecca Munk

    2008-01-01

    tract to the microbial flocs in waste water treatment facilities. Microbial biofilms may however also cause a wide range of industrial and medical problems, and have been implicated in a wide range of persistent infectious diseases, including implantassociated microbial infections. Bacterial adhesion...... is the first committing step in biofilm formation, and has therefore been intensely scrutinized. Much however, still remains elusive. Bacterial adhesion is a highly complex process, which is influenced by a variety of factors. In this thesis, a range of physico-chemical, molecular and environmental parameters......, which influence the transition from a planktonic lifestyle to a sessile lifestyle, have been studied. Protein conditioning film formation was found to influence bacterial adhesion and subsequent biofilm formation considerable, and an aqueous extract of fish muscle tissue was shown to significantly...

  11. Bacterial lipases

    NARCIS (Netherlands)

    Jaeger, Karl-Erich; Ransac, Stéphane; Dijkstra, Bauke W.; Colson, Charles; Heuvel, Margreet van; Misset, Onno

    1994-01-01

    Many different bacterial species produce lipases which hydrolyze esters of glycerol with preferably long-chain fatty acids. They act at the interface generated by a hydrophobic lipid substrate in a hydrophilic aqueous medium. A characteristic property of lipases is called interfacial activation, mea

  12. Viral diagnosis in Indian livestock using customized microarray chips.

    Science.gov (United States)

    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.

  13. Feature extraction and signal processing for nylon DNA microarrays

    Directory of Open Access Journals (Sweden)

    Bertucci F

    2004-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Burow Mark

    2009-06-01

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

  15. Human genomics and microarrays: implications for the plastic surgeon.

    Science.gov (United States)

    Cole, Jana; Isik, Frank

    2002-09-01

    The Human Genome Project was launched in 1989 in an effort to sequence the entire span of human DNA. Although coding sequences are important in identifying mutations, the static order of DNA does not explain how a cell or organism may respond to normal and abnormal biological processes. By examining the mRNA content of a cell, researchers can determine which genes are being activated in response to a stimulus. Traditional methods in molecular biology generally work on a "one gene: one experiment" basis, which means that the throughput is very limited and the "whole picture" of gene function is hard to obtain. To study each of the 60,000 to 80,000 genes in the human genome under each biological circumstance is not practical. Recently, microarrays (also known as gene or DNA chips) have emerged; these allow for the simultaneous determination of expression for thousands of genes and analysis of genome-wide mRNA expression. The purpose of this article is twofold: first, to provide the clinical plastic surgeon with a working knowledge and understanding of the fields of genomics, microarrays, and bioinformatics and second, to present a case to illustrate how these technologies can be applied in the study of wound healing.

  16. Harshlight: a "corrective make-up" program for microarray chips

    Directory of Open Access Journals (Sweden)

    Wittkowski Knut M

    2005-12-01

    Full Text Available Abstract Background Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans do show similar artifacts, which might affect subsequent analysis. Although all but the starkest blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs, few tools are available to help with the detection of those defects. Results We develop a novel tool, Harshlight, for the automatic detection and masking of blemishes in HDONA microarray chips. Harshlight uses a combination of statistic and image processing methods to identify three different types of defects: localized blemishes affecting a few probes, diffuse defects affecting larger areas, and extended defects which may invalidate an entire chip. Conclusion We demonstrate the use of Harshlight can materially improve analysis of HDONA chips, especially for experiments with subtle changes between samples. For the widely used MAS5 algorithm, we show that compact blemishes cause an average of 8 gene expression values per chip to change by more than 50%, two of them by more than twofold; our masking algorithm restores about two thirds of this damage. Large-scale artifacts are successfully detected and eliminated.

  17. Cluster stability scores for microarray data in cancer studies

    Directory of Open Access Journals (Sweden)

    Ghosh Debashis

    2003-09-01

    Full Text Available Abstract Background A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, the question of stability of individual-level clusters has not been addressed. Results We address this problem by developing cluster stability scores using subsampling techniques. These scores exploit the redundancy in biologically discriminatory information on the chip. Our approach is generic and can be used with any clustering method. We propose procedures for calculating cluster stability scores for situations involving both known and unknown numbers of clusters. We also develop cluster-size adjusted stability scores. The method is illustrated by application to data three cancer studies; one involving childhood cancers, the second involving B-cell lymphoma, and the final is from a malignant melanoma study. Availability Code implementing the proposed analytic method can be obtained at the second author's website.

  18. Rapid and simultaneous detection of ricin, staphylococcal enterotoxin B and saxitoxin by chemiluminescence-based microarray immunoassay

    OpenAIRE

    Szkola, A.; Linares, E. M.; Worbs, Sylvia; Dorner, Brigitte; R. Dietrich; Märtlbauer, E.; Niessner, R.; Seidel, Michael

    2014-01-01

    Simultaneous detection of small and large molecules on microarray immunoassays is a challenge that limits some applications in multiplex analysis. This is the case for biosecurity, where fast, cheap and reliable simultaneous detection of proteotoxins and small toxins is needed. Two highly relevant proteotoxins, ricin (60 kDa) and bacterial toxin staphylococcal enterotoxin B (SEB, 30 kDa) and the small phycotoxin saxitoxin (STX, 0.3 kDa) are potential biological warfare agents and require an a...

  19. Undetected sex chromosome aneuploidy by chromosomal microarray.

    Science.gov (United States)

    Markus-Bustani, Keren; Yaron, Yuval; Goldstein, Myriam; Orr-Urtreger, Avi; Ben-Shachar, Shay

    2012-11-01

    We report on a case of a female fetus found to be mosaic for Turner syndrome (45,X) and trisomy X (47,XXX). Chromosomal microarray analysis (CMA) failed to detect the aneuploidy because of a normal average dosage of the X chromosome. This case represents an unusual instance in which CMA may not detect chromosomal aberrations. Such a possibility should be taken into consideration in similar cases where CMA is used in a clinical setting.

  20. A Gene Expression Barcode for Microarray Data

    OpenAIRE

    Zilliox, Michael J.; Irizarry, Rafael A.

    2007-01-01

    The ability to measure genome-wide expression holds great promise for characterizing cells and distinguishing diseased from normal tissues. Thus far, microarray technology has only been useful for measuring relative expression between two or more samples, which has handicapped its ability to classify tissue types. This paper presents the first method that can successfully predict tissue type based on data from a single hybridization. A preliminary web-tool is available at http://rafalab.jhsph...

  1. Pineal Function: Impact of Microarray Analysis

    OpenAIRE

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

    2009-01-01

    Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-hour schedule. This effort has highlighted surprising similarity to the retina and has provided reason to explore new avenues of study including intracellular signaling, signal transduction, transcriptional cascades, thyroid/retinoic acid hormone signaling, metal biology...

  2. Tissue Microarrays for Analysis of Expression Patterns

    OpenAIRE

    Lindskog Bergström, Cecilia

    2013-01-01

    Proteins are essential building blocks in every living cell, and since the complete human genome was sequenced in 2004, researchers have attempted to map the human proteome, which is the functional representation of the genome. One such initiative is the Human Protein Atlas programme (HPA), which generates monospecific antibodies towards all human proteins and uses these for high-throughput tissue profiling on tissue microarrays (TMAs). The results are publically available at the website www....

  3. Direct Mutagenesis of Thousands of Genomic Targets using Microarray-derived Oligonucleotides

    DEFF Research Database (Denmark)

    Bonde, Mads; Kosuri, Sriram; Genee, Hans Jasper;

    2015-01-01

    Multiplex Automated Genome Engineering (MAGE) allows simultaneous mutagenesis of multiple target sites in bacterial genomes using short oligonucleotides. However, large-scale mutagenesis requires hundreds to thousands of unique oligos, which are costly to synthesize and impossible to scale......-up by traditional phosphoramidite column-based approaches. Here, we describe a novel method to amplify oligos from microarray chips for direct use in MAGE to perturb thousands of genomic sites simultaneously. We demonstrated the feasibility of large-scale mutagenesis by inserting T7 promoters upstream of 2585...

  4. Monitoring Gene Expression in Mixed Microbial Communities by Using DNA Microarrays

    OpenAIRE

    Dennis, Philip; Edwards, Elizabeth A.; Liss, Steven N; Fulthorpe, Roberta

    2003-01-01

    A DNA microarray to monitor the expression of bacterial metabolic genes within mixed microbial communities was designed and tested. Total RNA was extracted from pure and mixed cultures containing the 2,4-dichlorophenoxyacetic acid (2,4-D)-degrading bacterium Ralstonia eutropha JMP134, and the inducing agent 2,4-D. Induction of the 2,4-D catabolic genes present in this organism was readily detected 4, 7, and 24 h after the addition of 2,4-D. This strain was diluted into a constructed mixed mic...

  5. Microarrays for rapid identification of plant viruses.

    Science.gov (United States)

    Boonham, Neil; Tomlinson, Jenny; Mumford, Rick

    2007-01-01

    Many factors affect the development and application of diagnostic techniques. Plant viruses are an inherently diverse group that, unlike cellular pathogens, possess no nucleotide sequence type (e.g., ribosomal RNA sequences) in common. Detection of plant viruses is becoming more challenging as globalization of trade, particularly in ornamentals, and the potential effects of climate change enhance the movement of viruses and their vectors, transforming the diagnostic landscape. Techniques for assessing seed, other propagation materials and field samples for the presence of specific viruses include biological indexing, electron microscopy, antibody-based detection, including enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and microarray detection. Of these, microarray detection provides the greatest capability for parallel yet specific testing, and can be used to detect individual, or combinations of viruses and, using current approaches, to do so with a sensitivity comparable to ELISA. Methods based on PCR provide the greatest sensitivity among the listed techniques but are limited in parallel detection capability even in "multiplexed" applications. Various aspects of microarray technology, including probe development, array fabrication, assay target preparation, hybridization, washing, scanning, and interpretation are presented and discussed, for both current and developing technology.

  6. Chicken sperm transcriptome profiling by microarray analysis.

    Science.gov (United States)

    Singh, R P; Shafeeque, C M; Sharma, S K; Singh, R; Mohan, J; Sastry, K V H; Saxena, V K; Azeez, P A

    2016-03-01

    It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21,639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.

  7. Integrating data from heterogeneous DNA microarray platforms.

    Science.gov (United States)

    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

  8. Microarray analyses of inflammation response of human dermal fibroblasts to different strains of Borrelia burgdorferi sensu stricto.

    Directory of Open Access Journals (Sweden)

    Frédéric Schramm

    Full Text Available In Lyme borreliosis, the skin is the key site of bacterial inoculation by the infected tick, and of cutaneous manifestations, erythema migrans and acrodermatitis chronica atrophicans. We explored the role of fibroblasts, the resident cells of the dermis, in the development of the disease. Using microarray experiments, we compared the inflammation of fibroblasts induced by three strains of Borrelia burgdorferi sensu stricto isolated from different environments and stages of Lyme disease: N40 (tick, Pbre (erythema migrans and 1408 (acrodermatitis chronica atrophicans. The three strains exhibited a similar profile of inflammation with strong induction of chemokines (CXCL1 and IL-8 and IL-6 cytokine mainly involved in the chemoattraction of immune cells. Molecules such as TNF-alpha and NF-κB factors, metalloproteinases (MMP-1, -3 and -12 and superoxide dismutase (SOD2, also described in inflammatory and cellular events, were up-regulated. In addition, we showed that tick salivary gland extracts induce a cytotoxic effect on fibroblasts and that OspC, essential in the transmission of Borrelia to the vertebrate host, was not responsible for the secretion of inflammatory molecules by fibroblasts. Tick saliva components could facilitate the early transmission of the disease to the site of injury creating a feeding pit. Later in the development of the disease, Borrelia would intensively multiply in the skin and further disseminate to distant organs.

  9. Microarray analysis of microbiota of gingival lesions in noma patients.

    Science.gov (United States)

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

    2013-01-01

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

  10. Microarray analysis of microbiota of gingival lesions in noma patients.

    Directory of Open Access Journals (Sweden)

    Antoine Huyghe

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

  11. Bacterial Ecology

    DEFF Research Database (Denmark)

    Fenchel, Tom

    2011-01-01

    Bacterial ecology is concerned with the interactions between bacteria and their biological and nonbiological environments and with the role of bacteria in biogeochemical element cycling. Many fundamental properties of bacteria are consequences of their small size. Thus, they can efficiently exploit...... biogeochemical processes are carried exclusively by bacteria. * Bacteria play an important role in all types of habitats including some that cannot support eukaryotic life....

  12. [Bacterial vaginosis].

    Science.gov (United States)

    Romero Herrero, Daniel; Andreu Domingo, Antonia

    2016-07-01

    Bacterial vaginosis (BV) is the main cause of vaginal dysbacteriosis in the women during the reproductive age. It is an entity in which many studies have focused for years and which is still open for discussion topics. This is due to the diversity of microorganisms that cause it and therefore, its difficult treatment. Bacterial vaginosis is probably the result of vaginal colonization by complex bacterial communities, many of them non-cultivable and with interdependent metabolism where anaerobic populations most likely play an important role in its pathogenesis. The main symptoms are an increase of vaginal discharge and the unpleasant smell of it. It can lead to serious consequences for women, such as an increased risk of contracting sexually transmitted infections including human immunodeficiency virus and upper genital tract and pregnancy complications. Gram stain is the gold standard for microbiological diagnosis of BV, but can also be diagnosed using the Amsel clinical criteria. It should not be considered a sexually transmitted disease but it is highly related to sex. Recurrence is the main problem of medical treatment. Apart from BV, there are other dysbacteriosis less characterized like aerobic vaginitis of which further studies are coming slowly but are achieving more attention and consensus among specialists. PMID:27474242

  13. Accurate detection of carcinoma cells by use of a cell microarray chip.

    Directory of Open Access Journals (Sweden)

    Shohei Yamamura

    Full Text Available BACKGROUND: Accurate detection and analysis of circulating tumor cells plays an important role in the diagnosis and treatment of metastatic cancer treatment. METHODS AND FINDINGS: A cell microarray chip was used to detect spiked carcinoma cells among leukocytes. The chip, with 20,944 microchambers (105 µm width and 50 µm depth, was made from polystyrene; and the formation of monolayers of leukocytes in the microchambers was observed. Cultured human T lymphoblastoid leukemia (CCRF-CEM cells were used to examine the potential of the cell microarray chip for the detection of spiked carcinoma cells. A T lymphoblastoid leukemia suspension was dispersed on the chip surface, followed by 15 min standing to allow the leukocytes to settle down into the microchambers. Approximately 29 leukocytes were found in each microchamber when about 600,000 leukocytes in total were dispersed onto a cell microarray chip. Similarly, when leukocytes isolated from human whole blood were used, approximately 89 leukocytes entered each microchamber when about 1,800,000 leukocytes in total were placed onto the cell microarray chip. After washing the chip surface, PE-labeled anti-cytokeratin monoclonal antibody and APC-labeled anti-CD326 (EpCAM monoclonal antibody solution were dispersed onto the chip surface and allowed to react for 15 min; and then a microarray scanner was employed to detect any fluorescence-positive cells within 20 min. In the experiments using spiked carcinoma cells (NCI-H1650, 0.01 to 0.0001%, accurate detection of carcinoma cells was achieved with PE-labeled anti-cytokeratin monoclonal antibody. Furthermore, verification of carcinoma cells in the microchambers was performed by double staining with the above monoclonal antibodies. CONCLUSION: The potential application of the cell microarray chip for the detection of CTCs was shown, thus demonstrating accurate detection by double staining for cytokeratin and EpCAM at the single carcinoma cell level.

  14. A non-parametric meta-analysis approach for combining independent microarray datasets: application using two microarray datasets pertaining to chronic allograft nephropathy

    Directory of Open Access Journals (Sweden)

    Archer Kellie J

    2008-02-01

    Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been

  15. Diamagnetic levitation enhances growth of liquid bacterial cultures by increasing oxygen availability.

    Science.gov (United States)

    Dijkstra, Camelia E; Larkin, Oliver J; Anthony, Paul; Davey, Michael R; Eaves, Laurence; Rees, Catherine E D; Hill, Richard J A

    2011-03-01

    Diamagnetic levitation is a technique that uses a strong, spatially varying magnetic field to reproduce aspects of weightlessness, on the Earth. We used a superconducting magnet to levitate growing bacterial cultures for up to 18 h, to determine the effect of diamagnetic levitation on all phases of the bacterial growth cycle. We find that diamagnetic levitation increases the rate of population growth in a liquid culture and reduces the sedimentation rate of the cells. Further experiments and microarray gene analysis show that the increase in growth rate is owing to enhanced oxygen availability. We also demonstrate that the magnetic field that levitates the cells also induces convective stirring in the liquid. We present a simple theoretical model, showing how the paramagnetic force on dissolved oxygen can cause convection during the aerobic phases of bacterial growth. We propose that this convection enhances oxygen availability by transporting oxygen around the liquid culture. Since this process results from the strong magnetic field, it is not present in other weightless environments, e.g. in Earth orbit. Hence, these results are of significance and timely to researchers considering the use of diamagnetic levitation to explore effects of weightlessness on living organisms and on physical phenomena. PMID:20667843

  16. Novel R pipeline for analyzing Biolog Phenotypic MicroArray data.

    Directory of Open Access Journals (Sweden)

    Minna Vehkala

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

  17. A novel microbial source tracking microarray for pathogen detection and fecal source identification in environmental systems.

    Science.gov (United States)

    Li, Xiang; Harwood, Valerie J; Nayak, Bina; Staley, Christopher; Sadowsky, Michael J; Weidhaas, Jennifer

    2015-06-16

    Pathogen detection and the identification of fecal contamination sources are challenging in environmental waters. Factors including pathogen diversity and ubiquity of fecal indicator bacteria hamper risk assessment and remediation of contamination sources. A custom microarray targeting pathogens (viruses, bacteria, protozoa), microbial source tracking (MST) markers, and antibiotic resistance genes was tested against DNA obtained from whole genome amplification (WGA) of RNA and DNA from sewage and animal (avian, cattle, poultry, and swine) feces. Perfect and mismatch probes established the specificity of the microarray in sewage, and fluorescence decrease of positive probes over a 1:10 dilution series demonstrated semiquantitative measurement. Pathogens, including norovirus, Campylobacter fetus, Helicobacter pylori, Salmonella enterica, and Giardia lamblia were detected in sewage, as well as MST markers and resistance genes to aminoglycosides, beta-lactams, and tetracycline. Sensitivity (percentage true positives) of MST results in sewage and animal waste samples (21-33%) was lower than specificity (83-90%, percentage of true negatives). Next generation DNA sequencing revealed two dominant bacterial families that were common to all sample types: Ruminococcaceae and Lachnospiraceae. Five dominant phyla and 15 dominant families comprised 97% and 74%, respectively, of sequences from all fecal sources. Phyla and families not represented on the microarray are possible candidates for inclusion in subsequent array designs. PMID:25970344

  18. Evaluation of chronic lymphocytic leukemia by BAC-based microarray analysis

    Directory of Open Access Journals (Sweden)

    McDaniel Lisa D

    2011-02-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.

  19. Whole-genome microarrays of fission yeast: characteristics, accuracy, reproducibility, and processing of array data

    Directory of Open Access Journals (Sweden)

    Chen Dongrong

    2003-07-01

    Full Text Available Abstract Background The genome of the fission yeast Schizosaccharomyces pombe has recently been sequenced, setting the stage for the post-genomic era of this increasingly popular model organism. We have built fission yeast microarrays, optimised protocols to improve array performance, and carried out experiments to assess various characteristics of microarrays. Results We designed PCR primers to amplify specific probes (180–500 bp for all known and predicted fission yeast genes, which are printed in duplicate onto separate regions of glass slides together with control elements (~13,000 spots/slide. Fluorescence signal intensities depended on the size and intragenic position of the array elements, whereas the signal ratios were largely independent of element properties. Only the coding strand is covalently linked to the slides, and our array elements can discriminate transcriptional direction. The microarrays can distinguish sequences with up to 70% identity, above which cross-hybridisation contributes to the signal intensity. We tested the accuracy of signal ratios and measured the reproducibility of array data caused by biological and technical factors. Because the technical variability is lower, it is best to use samples prepared from independent biological experiments to obtain repeated measurements with swapping of fluorochromes to prevent dye bias. We also developed a script that discards unreliable data and performs a normalization to correct spatial artefacts. Conclusions This paper provides data for several microarray properties that are rarely measured. The results define critical parameters for microarray design and experiments and provide a framework to optimise and interpret array data. Our arrays give reproducible and accurate expression ratios with high sensitivity. The scripts for primer design and initial data processing as well as primer sequences and detailed protocols are available from our website.

  20. Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

    DEFF Research Database (Denmark)

    Novak, Jaroslav P; Kim, Seon-Young; Xu, Jun;

    2006-01-01

    BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have...... technology give "true" representation of physical processes, involved in measurement of RNA abundance. REVIEWERS: This article was reviewed by Yoav Gilad (nominated by Doron Lancet), Sach Mukherjee (nominated by Sandrine Dudoit) and Amir Niknejad and Shmuel Friedland (nominated by Neil Smalheiser)....

  1. Graph-driven features extraction from microarray data

    CERN Document Server

    Vert, J P; Vert, Jean-Philippe; Kanehisa, Minoru

    2002-01-01

    Gene function prediction from microarray data is a first step toward better understanding the machinery of the cell from relatively cheap and easy-to-produce data. In this paper we investigate whether the knowledge of many metabolic pathways and their catalyzing enzymes accumulated over the years can help improve the performance of classifiers for this problem. The complex network of known biochemical reactions in the cell results in a representation where genes are nodes of a graph. Formulating the problem as a graph-driven features extraction problem, based on the simple idea that relevant features are likely to exhibit correlation with respect to the topology of the graph, we end up with an algorithm which involves encoding the network and the set of expression profiles into kernel functions, and performing a regularized form of canonical correlation analysis in the corresponding reproducible kernel Hilbert spaces. Function prediction experiments for the genes of the yeast S. Cerevisiae validate this appro...

  2. Viral and bacterial production in the North Water: in situ measurements, batch-culture experiments and characterization and distribution of a virus host system

    Science.gov (United States)

    Middelboe, Mathias; Nielsen, Torkel G.; Bjørnsen, Peter K.

    Growth and viral lysis of bacterioplankton at subzero temperatures were measured in the North Water polynya in July 1998. In situ measurements of bacterial carbon consumption in surface waters ranged from 15 to 63 μg C l -1 d -1 in the eastern and 6 to 7 μg C l -1 d -1 in the northern part of the polynya. Both bacterial abundance and activity appeared to increase in response to the decay of the phytoplankton bloom that developed in the North Water. Organic carbon was the limiting substrate for bacteria in the polynya since addition of glucose, but not inorganic nutrients, to batch cultures increased both the carrying capacity of the substrate and the growth rate of the bacteria. Bacterial growth rates ranged from 0.11 to 0.40 d -1, corresponding to bacterial generation times of 1.7-6.3 d. The in situ viral production rate was estimated both from the frequency of visibly infected cells and from the rate of viral production in batch cultures; it ranged from 0.04 to 0.52 d -1 and from 0.25 to 0.47 d -1, respectively. From 6% to 28% of bacterial production was found to be lost due to viral lysis. The average virus-bacteria ratio was 5.1±3.1, with the abundance of viruses being correlated positively with bacterial production. A Pseudoalteromonas sp. bacterial host and an infective virus were isolated from the polynya; characteristics and distribution of the virus-host system were examined. The Pseudoalteromonas sp. showed psychrotolerant growth and sustained significant production of viruses at 0°C. The virus-host system was found throughout the polynya. Overall the results suggested that a large amount of organic carbon released during the development and breakdown of the spring phytoplankton bloom was consumed by planktonic bacteria and that the microbial food web was an important and dynamic component of the planktonic food web in the North Water.

  3. Formation and characterization of DNA microarrays at silicon nitride substrates.

    Science.gov (United States)

    Manning, Mary; Redmond, Gareth

    2005-01-01

    A versatile method for direct, covalent attachment of DNA microarrays at silicon nitride layers, previously deposited by chemical vapor deposition at silicon wafer substrates, is reported. Each microarray fabrication process step, from silicon nitride substrate deposition, surface cleaning, amino-silanation, and attachment of a homobifunctional cross-linking molecule to covalent immobilization of probe oligonucleotides, is defined, characterized, and optimized to yield consistent probe microarray quality, homogeneity, and probe-target hybridization performance. The developed microarray fabrication methodology provides excellent (high signal-to-background ratio) and reproducible responsivity to target oligonucleotide hybridization with a rugged chemical stability that permits exposure of arrays to stringent pre- and posthybridization wash conditions through many sustained cycles of reuse. Overall, the achieved performance features compare very favorably with those of more mature glass based microarrays. It is proposed that this DNA microarray fabrication strategy has the potential to provide a viable route toward the successful realization of future integrated DNA biochips.

  4. Extended -Regular Sequence for Automated Analysis of Microarray Images

    Directory of Open Access Journals (Sweden)

    Jin Hee-Jeong

    2006-01-01

    Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.

  5. Gene Expression Analysis Using Agilent DNA Microarrays

    DEFF Research Database (Denmark)

    Stangegaard, Michael

    2009-01-01

    Hybridization of labeled cDNA to microarrays is an intuitively simple and a vastly underestimated process. If it is not performed, optimized, and standardized with the same attention to detail as e.g., RNA amplification, information may be overlooked or even lost. Careful balancing of the amount...... of labeled cDNA added to each slide reduces dye-bias and slide to slide variation. Efficient mixing of the hybridization solution throughout the hybridization reaction increases signals several fold. The amount of near perfect target-probe hybrids may be reduced by efficient stringency washes...

  6. Biocompatible polymer microarrays for cellular high-content screening

    OpenAIRE

    Pernagallo, Salvatore

    2010-01-01

    The global aim of this thesis was to study the use of microarray technology for the screening and identification of biocompatible polymers, to understand physiological phenomena, and the design of biomaterials, implant surfaces and tissue-engineering scaffolds. This work was based upon the polymer microarray platform developed by the Bradley group. Polymer microarrays were successfully applied to find the best polymer supports for: (i) mouse fibroblast cells and used to eval...

  7. DNA Microarray Assessment of Putative Borrelia burgdorferi Lipoprotein Genes

    OpenAIRE

    Liang, Fang Ting; Nelson, F. Kenneth; Fikrig, Erol

    2002-01-01

    A DNA microarray containing fragments of 137 Borrelia burgdorferi B31 putative lipoprotein genes was used to examine Lyme disease spirochetes. DNA from B. burgdorferi sensu stricto B31, 297, and N40; Borrelia garinii IP90; and Borrelia afzelii P/Gau was fluorescently labeled and hybridized to the microarray, demonstrating the degree to which the individual putative lipoprotein genes were conserved among the genospecies. These data show that a DNA microarray can globally examine the genes enco...

  8. Miniaturised Spotter-Compatible Multicapillary Stamping Tool for Microarray Printing

    CERN Document Server

    Drobyshev, A L; Zasedatelev, A S; Drobyshev, Alexei L; Verkhodanov, Nikolai N; Zasedatelev, Alexander S

    2007-01-01

    Novel microstamping tool for microarray printing is proposed. The tool is capable to spot up to 127 droplets of different solutions in single touch. It is easily compatible with commercially available microarray spotters. The tool is based on multichannel funnel with polypropylene capillaries inserted into its channels. Superior flexibility is achieved by ability to replace any printing capillary of the tool. As a practical implementation, hydrogel-based microarrays were stamped and successfully applied to identify the Mycobacterium tuberculosis drug resistance.

  9. A comparative analysis of DNA barcode microarray feature size

    OpenAIRE

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

    2009-01-01

    Abstract 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 microarra...

  10. Chemiluminescence microarrays in analytical chemistry: a critical review.

    Science.gov (United States)

    Seidel, Michael; Niessner, Reinhard

    2014-09-01

    Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

  11. Identification of upper respiratory tract pathogens using electrochemical detection on an oligonucleotide microarray.

    Directory of Open Access Journals (Sweden)

    Michael J Lodes

    Full Text Available Bacterial and viral upper respiratory infections (URI produce highly variable clinical symptoms that cannot be used to identify the etiologic agent. Proper treatment, however, depends on correct identification of the pathogen involved as antibiotics provide little or no benefit with viral infections. Here we describe a rapid and sensitive genotyping assay and microarray for URI identification using standard amplification and hybridization techniques, with electrochemical detection (ECD on a semiconductor-based oligonucleotide microarray. The assay was developed to detect four bacterial pathogens (Bordetella pertussis, Streptococcus pyogenes, Chlamydia pneumoniae and Mycoplasma pneumoniae and 9 viral pathogens (adenovirus 4, coronavirus OC43, 229E and HK, influenza A and B, parainfluenza types 1, 2, and 3 and respiratory syncytial virus. This new platform forms the basis for a fully automated diagnostics system that is very flexible and can be customized to suit different or additional pathogens. Multiple probes on a flexible platform allow one to test probes empirically and then select highly reactive probes for further iterative evaluation. Because ECD uses an enzymatic reaction to create electrical signals that can be read directly from the array, there is no need for image analysis or for expensive and delicate optical scanning equipment. We show assay sensitivity and specificity that are excellent for a multiplexed format.

  12. A robust measure of correlation between two genes on a microarray

    Directory of Open Access Journals (Sweden)

    Hicks Leanne

    2007-06-01

    Full Text Available Abstract Background The underlying goal of microarray experiments is to identify gene expression patterns across different experimental conditions. Genes that are contained in a particular pathway or that respond similarly to experimental conditions could be co-expressed and show similar patterns of expression on a microarray. Using any of a variety of clustering methods or gene network analyses we can partition genes of interest into groups, clusters, or modules based on measures of similarity. Typically, Pearson correlation is used to measure distance (or similarity before implementing a clustering algorithm. Pearson correlation is quite susceptible to outliers, however, an unfortunate characteristic when dealing with microarray data (well known to be typically quite noisy. Results We propose a resistant similarity metric based on Tukey's biweight estimate of multivariate scale and location. The resistant metric is simply the correlation obtained from a resistant covariance matrix of scale. We give results which demonstrate that our correlation metric is much more resistant than the Pearson correlation while being more efficient than other nonparametric measures of correlation (e.g., Spearman correlation. Additionally, our method gives a systematic gene flagging procedure which is useful when dealing with large amounts of noisy data. Conclusion When dealing with microarray data, which are known to be quite noisy, robust methods should be used. Specifically, robust distances, including the biweight correlation, should be used in clustering and gene network analysis.

  13. Ontology-based, Tissue MicroArray oriented, image centered tissue bank

    Directory of Open Access Journals (Sweden)

    Viti Federica

    2008-04-01

    Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

  14. Chromosomal microarrays testing in children with developmental disabilities and congenital anomalies

    Directory of Open Access Journals (Sweden)

    Guillermo Lay-Son

    2015-04-01

    Full Text Available OBJECTIVES: Clinical use of microarray-based techniques for the analysis of many developmental disorders has emerged during the last decade. Thus, chromosomal microarray has been positioned as a first-tier test. This study reports the first experience in a Chilean cohort. METHODS: Chilean patients with developmental disabilities and congenital anomalies were studied with a high-density microarray (CytoScan(tm HD Array, Affymetrix, Inc., Santa Clara, CA, USA. Patients had previous cytogenetic studies with either a normal result or a poorly characterized anomaly. RESULTS: This study tested 40 patients selected by two or more criteria, including: major congenital anomalies, facial dysmorphism, developmental delay, and intellectual disability. Copy number variants (CNVs were found in 72.5% of patients, while a pathogenic CNV was found in 25% of patients and a CNV of uncertain clinical significance was found in 2.5% of patients. CONCLUSION: Chromosomal microarray analysis is a useful and powerful tool for diagnosis of developmental diseases, by allowing accurate diagnosis, improving the diagnosis rate, and discovering new etiologies. The higher cost is a limitation for widespread use in this setting.

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

    Directory of Open Access Journals (Sweden)

    Gutierrez Laurent

    2010-10-01

    Full Text Available Abstract 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

  16. Microarray analysis of the developing cortex.

    Science.gov (United States)

    Semeralul, Mawahib O; Boutros, Paul C; Likhodi, Olga; Okey, Allan B; Van Tol, Hubert H M; Wong, Albert H C

    2006-12-01

    Abnormal development of the prefrontal cortex (PFC) is associated with a number of neuropsychiatric disorders that have an onset in childhood or adolescence. Although the basic laminar structure of the PFC is established in utero, extensive remodeling continues into adolescence. To map the overall pattern of changes in cortical gene transcripts during postnatal development, we made serial measurements of mRNA levels in mouse PFC using oligonucleotide microarrays. We observed changes in mRNA transcripts consistent with known postnatal morphological and biochemical events. Overall, most transcripts that changed significantly showed a progressive decrease in abundance after birth, with the majority of change between postnatal weeks 2 and 4. Genes with cell proliferative, cytoskeletal, extracellular matrix, plasma membrane lipid/transport, protein folding, and regulatory functions had decreases in mRNA levels. Quantitative PCR verified the microarray results for six selected genes: DNA methyltransferase 3A (Dnmt3a), procollagen, type III, alpha 1 (Col3a1), solute carrier family 16 (monocarboxylic acid transporters), member 1 (Slc16a1), MARCKS-like 1 (Marcksl1), nidogen 1 (Nid1) and 3-hydroxybutyrate dehydrogenase (heart, mitochondrial) (Bdh).

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

    International Nuclear Information System (INIS)

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

  18. Bacterial Hydrodynamics

    Science.gov (United States)

    Lauga, Eric

    2016-01-01

    Bacteria predate plants and animals by billions of years. Today, they are the world's smallest cells, yet they represent the bulk of the world's biomass and the main reservoir of nutrients for higher organisms. Most bacteria can move on their own, and the majority of motile bacteria are able to swim in viscous fluids using slender helical appendages called flagella. Low-Reynolds number hydrodynamics is at the heart of the ability of flagella to generate propulsion at the micrometer scale. In fact, fluid dynamic forces impact many aspects of bacteriology, ranging from the ability of cells to reorient and search their surroundings to their interactions within mechanically and chemically complex environments. Using hydrodynamics as an organizing framework, I review the biomechanics of bacterial motility and look ahead to future challenges.

  19. Bacterial hydrodynamics

    CERN Document Server

    Lauga, Eric

    2015-01-01

    Bacteria predate plants and animals by billions of years. Today, they are the world's smallest cells yet they represent the bulk of the world's biomass, and the main reservoir of nutrients for higher organisms. Most bacteria can move on their own, and the majority of motile bacteria are able to swim in viscous fluids using slender helical appendages called flagella. Low-Reynolds-number hydrodynamics is at the heart of the ability of flagella to generate propulsion at the micron scale. In fact, fluid dynamic forces impact many aspects of bacteriology, ranging from the ability of cells to reorient and search their surroundings to their interactions within mechanically and chemically-complex environments. Using hydrodynamics as an organizing framework, we review the biomechanics of bacterial motility and look ahead to future challenges.

  20. Exploring host-pathogen interactions through genome wide protein microarray analysis.

    Science.gov (United States)

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-06-15

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis.

  1. Exploring host-pathogen interactions through genome wide protein microarray analysis

    Science.gov (United States)

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F.; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J.; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-01-01

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis. PMID:27302108

  2. Exploring host-pathogen interactions through genome wide protein microarray analysis.

    Science.gov (United States)

    Scietti, Luigi; Sampieri, Katia; Pinzuti, Irene; Bartolini, Erika; Benucci, Barbara; Liguori, Alessia; Haag, Andreas F; Lo Surdo, Paola; Pansegrau, Werner; Nardi-Dei, Vincenzo; Santini, Laura; Arora, Seguinde; Leber, Xavier; Rindi, Simonetta; Savino, Silvana; Costantino, Paolo; Maione, Domenico; Merola, Marcello; Speziale, Pietro; Bottomley, Matthew J; Bagnoli, Fabio; Masignani, Vega; Pizza, Mariagrazia; Scharenberg, Meike; Schlaeppi, Jean-Marc; Nissum, Mikkel; Liberatori, Sabrina

    2016-01-01

    During bacterial pathogenesis extensive contacts between the human and the bacterial extracellular proteomes take place. The identification of novel host-pathogen interactions by standard methods using a case-by-case approach is laborious and time consuming. To overcome this limitation, we took advantage of large libraries of human and bacterial recombinant proteins. We applied a large-scale protein microarray-based screening on two important human pathogens using two different approaches: (I) 75 human extracellular proteins were tested on 159 spotted Staphylococcus aureus recombinant proteins and (II) Neisseria meningitidis adhesin (NadA), an important vaccine component against serogroup B meningococcus, was screened against ≈2300 spotted human recombinant proteins. The approach presented here allowed the identification of the interaction between the S. aureus immune evasion protein FLIPr (formyl-peptide receptor like-1 inhibitory protein) and the human complement component C1q, key players of the offense-defense fighting; and of the interaction between meningococcal NadA and human LOX-1 (low-density oxidized lipoprotein receptor), an endothelial receptor. The novel interactions between bacterial and human extracellular proteins here presented might provide a better understanding of the molecular events underlying S. aureus and N. meningitidis pathogenesis. PMID:27302108

  3. Bulk segregant analysis using single nucleotide polymorphism microarrays.

    Directory of Open Access Journals (Sweden)

    Anthony Becker

    Full Text Available Bulk segregant analysis (BSA using microarrays, and extreme array mapping (XAM have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.

  4. Bacterial Communities: Interactions to Scale

    Science.gov (United States)

    Stubbendieck, Reed M.; Vargas-Bautista, Carol; Straight, Paul D.

    2016-01-01

    In the environment, bacteria live in complex multispecies communities. These communities span in scale from small, multicellular aggregates to billions or trillions of cells within the gastrointestinal tract of animals. The dynamics of bacterial communities are determined by pairwise interactions that occur between different species in the community. Though interactions occur between a few cells at a time, the outcomes of these interchanges have ramifications that ripple through many orders of magnitude, and ultimately affect the macroscopic world including the health of host organisms. In this review we cover how bacterial competition influences the structures of bacterial communities. We also emphasize methods and insights garnered from culture-dependent pairwise interaction studies, metagenomic analyses, and modeling experiments. Finally, we argue that the integration of multiple approaches will be instrumental to future understanding of the underlying dynamics of bacterial communities. PMID:27551280

  5. Bacterial Communities: Interactions to Scale

    Directory of Open Access Journals (Sweden)

    Reed M. Stubbendieck

    2016-08-01

    Full Text Available In the environment, bacteria live in complex multispecies communities. These communities span in scale from small, multicellular aggregates to billions or trillions of cells within the gastrointestinal tract of animals. The dynamics of bacterial communities are determined by pairwise interactions that occur between different species in the community. Though interactions occur between a few cells at a time, the outcomes of these interchanges have ramifications that ripple through many orders of magnitude, and ultimately affect the macroscopic world including the health of host organisms. In this review we cover how bacterial competition influences the structures of bacterial communities. We also emphasize methods and insights garnered from culture-dependent pairwise interaction studies, metagenomic analyses, and modeling experiments. Finally, we argue that the integration of multiple approaches will be instrumental to future understanding of the underlying dynamics of bacterial communities.

  6. Analysis of factorial time-course microarrays with application to a clinical study of burn injury

    OpenAIRE

    Zhou, Baiyu; Xu, Weihong; Herndon, David; Tompkins, Ronald; Davis, Ronald; Xiao, Wenzhong; Wong, Wing Hung; Toner, Mehmet; Warren, H. Shaw; Schoenfeld, David A.; Rahme, Laurence; McDonald-Smith, Grace P.; Hayden, Douglas; Mason, Philip; Fagan, Shawn

    2010-01-01

    Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple tes...

  7. An Archived Multi Objective Simulated Annealing Method to Discover Biclusters in Microarray Data

    OpenAIRE

    Mohsen Lashkargir; Mohammad Sadegh Tabatabaeifar; Sadegh Taghizadeh

    2011-01-01

    With the advent of microarray technology it has been possible to measure thousands of expression values of genes in a single experiment. Analysis of large scale geonomics data, notably gene expression, has initially focused on clustering methods. Recently, biclustering techniques were proposed for revealing submatrices showing unique patterns. Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression d...

  8. Mining microarray datasets aided by knowledge stored in literature

    NARCIS (Netherlands)

    R. Jelier (Rob); G.W. Jenster (Guido); L.C.J. Dorssers (Lambert); E.M. van Mulligen (Erik); B. Mons (Barend); J.A. Kors (Jan)

    2003-01-01

    textabstractDNA microarray technology produces large amounts of data. For data mining of these datasets, background information on genes can be helpful. Unfortunately most information is stored in free text. Here, we present an approach to use this information for DNA microarray da

  9. Shared probe design and existing microarray reanalysis using PICKY

    Directory of Open Access Journals (Sweden)

    Chou Hui-Hsien

    2010-04-01

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

  10. Near-optimal designs for dual channel microarray studies

    NARCIS (Netherlands)

    Wit, Ernst; Nobile, Agostino; Khanin, Raya

    2005-01-01

    Much biological and medical research employs microarray studies to monitor gene expression levels across a wide range of organisms and under many experimental conditions. Dual channel microarrays are a common platform and allow two samples to be measured simultaneously. A frequently used design uses

  11. Defining best practice for microarray analyses in nutrigenomic studies

    NARCIS (Netherlands)

    Garosi, P.; Filippo, C. de; Erk, M. van; Rocca-Serra, P.; Sansone, S.A.; Elliott, R.

    2005-01-01

    Microarrays represent a powerful tool for studies of diet-gene interactions. Their use is, however, associated with a number of technical challenges and potential pitfalls. The cost of microarrays continues to drop but is still comparatively high. This, coupled with the complex logistical issues ass

  12. Design of an Enterobacteriaceae Pan-genome Microarray Chip

    DEFF Research Database (Denmark)

    Lukjancenko, Oksana; Ussery, David

    2010-01-01

    -density microarray chip has been designed, using 116 Enterobacteriaceae genome sequences, taking into account the enteric pan-genome. Probes for the microarray were checked in silico and performance of the chip, based on experimental strains from four different genera, demonstrate a relatively high ability...

  13. Mathematical design of prokaryotic clone-based microarrays

    NARCIS (Netherlands)

    Pieterse, B.; Quirijns, E.J.; Schuren, F.H.J.; Werf, M.J. van der

    2005-01-01

    Background: Clone-based microarrays, on which each spot represents a random genomic fragment, are a good alternative to open reading frame-based microarrays, especially for microorganisms for which the complete genome sequence is not available. Since the generation of a genomic DNA library is a rand

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

    International Nuclear Information System (INIS)

    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

  15. cDNA microarray screening in food safety

    International Nuclear Information System (INIS)

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

  16. DNA microarray-based mutation discovery and genotyping.

    Science.gov (United States)

    Gresham, David

    2011-01-01

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

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

    DEFF Research Database (Denmark)

    Pedersen, Henriette Lodberg; Fangel, Jonatan Ulrik; McCleary, Barry;

    2012-01-01

    Microarrays are powerful tools for high throughput analysis, and hundreds or thousands of molecular interactions can be assessed simultaneously using very small amounts of analytes. Nucleotide microarrays are well established in plant research, but carbohydrate microarrays are much less establish...

  18. GEPAS, a web-based tool for microarray data analysis and interpretation

    Science.gov (United States)

    Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín

    2008-01-01

    Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806

  19. Uses of Dendrimers for DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Jean-Pierre Majoral

    2006-08-01

    Full Text Available Biosensors such as DNA microarrays and microchips are gaining an increasingimportance in medicinal, forensic, and environmental analyses. Such devices are based onthe detection of supramolecular interactions called hybridizations that occur betweencomplementary oligonucleotides, one linked to a solid surface (the probe, and the other oneto be analyzed (the target. This paper focuses on the improvements that hyperbranched andperfectly defined nanomolecules called dendrimers can provide to this methodology. Twomain uses of dendrimers for such purpose have been described up to now; either thedendrimer is used as linker between the solid surface and the probe oligonucleotide, or thedendrimer is used as a multilabeled entity linked to the target oligonucleotide. In the firstcase 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 smallquantities of biological entities.

  20. Digital microarray analysis for digital artifact genomics

    Science.gov (United States)

    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.

  1. Differential splicing using whole-transcript microarrays

    Directory of Open Access Journals (Sweden)

    Robinson Mark D

    2009-05-01

    Full Text Available Abstract Background The latest generation of Affymetrix microarrays are designed to interrogate expression over the entire length of every locus, thus giving the opportunity to study alternative splicing genome-wide. The Exon 1.0 ST (sense target platform, with versions for Human, Mouse and Rat, is designed primarily to probe every known or predicted exon. The smaller Gene 1.0 ST array is designed as an expression microarray but still interrogates expression with probes along the full length of each well-characterized transcript. We explore the possibility of using the Gene 1.0 ST platform to identify differential splicing events. Results We propose a strategy to score differential splicing by using the auxiliary information from fitting the statistical model, RMA (robust multichip analysis. RMA partitions the probe-level data into probe effects and expression levels, operating robustly so that if a small number of probes behave differently than the rest, they are downweighted in the fitting step. We argue that adjacent poorly fitting probes for a given sample can be evidence of differential splicing and have designed a statistic to search for this behaviour. Using a public tissue panel dataset, we show many examples of tissue-specific alternative splicing. Furthermore, we show that evidence for putative alternative splicing has a strong correspondence between the Gene 1.0 ST and Exon 1.0 ST platforms. Conclusion We propose a new approach, FIRMAGene, to search for differentially spliced genes using the Gene 1.0 ST platform. Such an analysis complements the search for differential expression. We validate the method by illustrating several known examples and we note some of the challenges in interpreting the probe-level data. Software implementing our methods is freely available as an R package.

  2. Drag Reduction of Bacterial Cellulose Suspensions

    OpenAIRE

    Ogata, Satoshi; Numakawa, Tetsuya; Kubo, Takuya

    2010-01-01

    Drag reduction due to bacterial cellulose suspensions with small environmental loading was investigated. Experiments were carried out by measuring the pressure drop in pipe flow. It was found that bacterial cellulose suspensions give rise to drag reduction in the turbulent flow range. We observed a maximum drag reduction ratio of 11% and found that it increased with the concentration of the bacterial cellulose suspension. However, the drag reduction effect decreased in the presence of mechani...

  3. Drag Reduction of Bacterial Cellulose Suspensions

    OpenAIRE

    Satoshi Ogata; Tetsuya Numakawa; Takuya Kubo

    2011-01-01

    Drag reduction due to bacterial cellulose suspensions with small environmental loading was investigated. Experiments were carried out by measuring the pressure drop in pipe flow. It was found that bacterial cellulose suspensions give rise to drag reduction in the turbulent flow range. We observed a maximum drag reduction ratio of 11% and found that it increased with the concentration of the bacterial cellulose suspension. However, the drag reduction effect decreased in the presence of mechani...

  4. A cell spot microarray method for production of high density siRNA transfection microarrays

    Directory of Open Access Journals (Sweden)

    Mpindi John-Patrick

    2011-03-01

    Full Text Available Abstract Background High-throughput RNAi screening is widely applied in biological research, but remains expensive, infrastructure-intensive and conversion of many assays to HTS applications in microplate format is not feasible. Results Here, we describe the optimization of a miniaturized cell spot microarray (CSMA method, which facilitates utilization of the transfection microarray technique for disparate RNAi analyses. To promote rapid adaptation of the method, the concept has been tested with a panel of 92 adherent cell types, including primary human cells. We demonstrate the method in the systematic screening of 492 GPCR coding genes for impact on growth and survival of cultured human prostate cancer cells. Conclusions The CSMA method facilitates reproducible preparation of highly parallel cell microarrays for large-scale gene knockdown analyses. This will be critical towards expanding the cell based functional genetic screens to include more RNAi constructs, allow combinatorial RNAi analyses, multi-parametric phenotypic readouts or comparative analysis of many different cell types.

  5. Development of a rapid microarray-based DNA subtyping assay for the alleles of Shiga toxins 1 and 2 of Escherichia coli.

    Science.gov (United States)

    Geue, Lutz; Stieber, Bettina; Monecke, Stefan; Engelmann, Ines; Gunzer, Florian; Slickers, Peter; Braun, Sascha D; Ehricht, Ralf

    2014-08-01

    In this study, we developed a new rapid, economic, and automated microarray-based genotyping test for the standardized subtyping of Shiga toxins 1 and 2 of Escherichia coli. The microarrays from Alere Technologies can be used in two different formats, the ArrayTube and the ArrayStrip (which enables high-throughput testing in a 96-well format). One microarray chip harbors all the gene sequences necessary to distinguish between all Stx subtypes, facilitating the identification of single and multiple subtypes within a single isolate in one experiment. Specific software was developed to automatically analyze all data obtained from the microarray. The assay was validated with 21 Shiga toxin-producing E. coli (STEC) reference strains that were previously tested by the complete set of conventional subtyping PCRs. The microarray results showed 100% concordance with the PCR results. Essentially identical results were detected when the standard DNA extraction method was replaced by a time-saving heat lysis protocol. For further validation of the microarray, we identified the Stx subtypes or combinations of the subtypes in 446 STEC field isolates of human and animal origin. In summary, this oligonucleotide array represents an excellent diagnostic tool that provides some advantages over standard PCR-based subtyping. The number of the spotted probes on the microarrays can be increased by additional probes, such as for novel alleles, species markers, or resistance genes, should the need arise. PMID:24899022

  6. Characterization of ovine hepatic gene expression profiles in response to Escherichia coli lipopolysaccharide using a bovine cDNA microarray

    Directory of Open Access Journals (Sweden)

    Boermans Herman J

    2006-11-01

    Full Text Available Abstract Background During systemic gram-negative bacterial infections, lipopolysaccharide (LPS ligation to the hepatic Toll-like receptor-4 complex induces the production of hepatic acute phase proteins that are involved in the host response to infection and limit the associated inflammatory process. Identifying the genes that regulate this hepatic response to LPS in ruminants may provide insight into the pathogenesis of bacterial diseases and eventually facilitate breeding of more disease resistant animals. The objective of this research was to profile the expression of ovine hepatic genes in response to Escherichia coli LPS challenge (0, 200, 400 ng/kg using a bovine cDNA microarray and quantitative real-time PCR (qRT-PCR. Results Twelve yearling ewes were challenged iv with E. coli LPS (0, 200, 400 ng/kg and liver biopsies were collected 4–5 hours post-challenge to assess hepatic gene expression profiles by bovine cDNA microarray and qRT-PCR analyses. The expression of CD14, C3, IL12R, NRAMP1, SOD and IGFBP3 genes was down regulated, whereas the expression of ACTHR, IFNαR, CD1, MCP-1 and GH was increased during LPS challenge. With the exception of C3, qRT-PCR analysis of 7 of these genes confirmed the microarray results and demonstrated that GAPDH is not a suitable housekeeping gene in LPS challenged sheep. Conclusion We have identified several potentially important genes by bovine cDNA microarray and qRT-PCR analyses that are differentially expressed during the ovine hepatic response to systemic LPS challenge. Their potential role in regulating the inflammatory response to LPS warrants further investigation.

  7. Clinical Experience of Bacterial Meningitis Treated by Latamoxef Sodium%拉氧头孢钠治疗细菌性脑膜炎的临床体会

    Institute of Scientific and Technical Information of China (English)

    谷祥富

    2011-01-01

    Objective: To observe the clinical efficacy and safety of bacterial meningitis treated by latamoxef sodium.Methods: Retrospective investigation to the bacterial mengitis cases in our hospital in the past 5 years was taken.Forty cases were randomly selected and divided into the latamoxef sodium 50 mg/kg treatment group(group A) and the cefepime 50 mg/kg control group(group B),each with 20 cases.Then the clinical efficacy,bacteriological changes and adverse reactions were compared between the two groups.Results: The clinical efficacy of group A and B was 95.00% and 90.00% respectively,without significant difference(P0.05).Conclusion: Latamoxef sodium treating bacterial meningitis,which had higher efficacy,safety and less adverse reaction,could reach a win-win situation for both the medical institutions and the patients under the system of new rural cooperative medicare scheme and urban health insurance.It is wealthy of clinical application.%目的:观察拉氧头孢钠治疗细菌性脑膜炎的临床疗效和安全性。方法:回顾性调查分析近5年我院治疗细菌性脑膜炎的病历,随即抽取拉氧头孢钠50mg/kg治疗组20例(A组)和头孢吡肟50 mg/kg对照组20例(B组),1次/12 h,疗程均为5~14 d。比较两组临床疗效、细菌学改变及不良反应情况。结果:A、B两组的临床痊愈率分别为90.00%、85.00%,A、B两组的临床有效率分别为95.00%、90.00%,二者比较差异无统计学意义(P〉0.05)。结论:拉氧头孢钠治疗细菌性脑膜炎的疗效满意,不良反应少,药物安全性高,在新农合和城镇医保范围,可对医疗机构及患者取得双赢,值得在临床推广应用。

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

    Directory of Open Access Journals (Sweden)

    Manish Biyani

    2015-07-01

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

  9. Hybrid microarray based on double biomolecular markers of DNA and carbohydrate for simultaneous genotypic and phenotypic detection of cholera toxin-producing Vibrio cholerae.

    Science.gov (United States)

    Shin, Hwa Hui; Seo, Jeong Hyun; Kim, Chang Sup; Hwang, Byeong Hee; Cha, Hyung Joon

    2016-05-15

    Life-threatening diarrheal cholera is usually caused by water or food contaminated with cholera toxin-producing Vibrio cholerae. For the prevention and surveillance of cholera, it is crucial to rapidly and precisely detect and identify the etiological causes, such as V. cholerae and/or its toxin. In the present work, we propose the use of a hybrid double biomolecular marker (DBM) microarray containing 16S rRNA-based DNA capture probe to genotypically identify V. cholerae and GM1 pentasaccharide capture probe to phenotypically detect cholera toxin. We employed a simple sample preparation method to directly obtain genomic DNA and secreted cholera toxin as target materials from bacterial cells. By utilizing the constructed DBM microarray and prepared samples, V. cholerae and cholera toxin were detected successfully, selectively, and simultaneously; the DBM microarray was able to analyze the pathogenicity of the identified V. cholerae regardless of whether the bacteria produces toxin. Therefore, our proposed DBM microarray is a new effective platform for identifying bacteria and analyzing bacterial pathogenicity simultaneously. PMID:26735874

  10. Bacteria repelling poly(methylmethacrylate-co-dimethylacrylamide) coatings for biomedical devices† †Electronic supplementary information (ESI) available: Polymer microarray screening, including analysis of bacterial adhesion by fluorescence microscopy and SEM, and chemical composition of bacteria repelling polymers identified in the screen; polymer synthesis and characterisation; preparation of catheter pieces and solvent studies, and details for confocal imaging/analysis. See DOI: 10.1039/c4tb01129e Click here for additional data file.

    OpenAIRE

    Venkateswaran, Seshasailam; Wu, Mei; Gwynne, Peter J.; Hardman, Ailsa; Lilienkampf, Annamaria; Pernagallo, Salvatore; Blakely, Garry; Swann, David G; Gallagher, Maurice P.; Bradley, Mark

    2014-01-01

    Nosocomial infections due to bacteria have serious implications on the health and recovery of patients in a variety of medical scenarios. Since bacterial contamination on medical devices contributes to the majority of nosocomical infections, there is a need for redesigning the surfaces of medical devices, such as catheters and tracheal tubes, to resist the binding of bacteria. In this work, polyurethanes and polyacrylates/acrylamides, which resist binding by the major bacterial pathogens unde...

  11. An Archived Multi Objective Simulated Annealing Method to Discover Biclusters in Microarray Data

    Directory of Open Access Journals (Sweden)

    Mohsen Lashkargir

    2011-01-01

    Full Text Available With the advent of microarray technology it has been possible to measure thousands of expression values of genes in a single experiment. Analysis of large scale geonomics data, notably gene expression, has initially focused on clustering methods. Recently, biclustering techniques were proposed for revealing submatrices showing unique patterns. Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression data in information retrieval, knowledge discovery, and data mining. In biclustering of microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A multi objective model is very suitable for solving this problem. Our method proposes a algorithm which is based on multi objective Simulated Annealing for discovering biclusters in gene expression data. Experimental result in bench mark data base present a significant improvement in overlap among biclusters and coverage of elements in gene expression and quality of biclusters.

  12. Global pathway analysis using DNA microarrays in skeletal muscle of women with polycystic ovary syndrome

    DEFF Research Database (Denmark)

    Skov, Vibe

    2007-01-01

    . The spots were well separated on the chips and had satisfactory spot morphology. The linear range was three orders of magnitude. In a series of self-hybridization experiments, we demonstrated a low coefficient of variation (CV) and high precision and accuracy of the chips. Conclusions These data indicate...... that impaired expression of genes representing OXPHOS pathways may play a role for insulin resistance in skeletal muscle of women with PCOS. Upregulation of OXPHOS pathways seems to be one of the mechanisms whereby pioglitazone improves insulin sensitivity. Our in-house spotted microarray chip performed...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....

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

    Science.gov (United States)

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

    2016-04-01

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

  14. AFM 4.0: a toolbox for DNA microarray analysis

    OpenAIRE

    Breitkreutz, Bobby-Joe; Jorgensen, Paul; Breitkreutz, Ashton; Tyers, Mike

    2001-01-01

    We have developed a series of programs, collectively packaged as Array File Maker 4.0 (AFM), that manipulate and manage DNA microarray data. AFM 4.0 is simple to use, applicable to any organism or microarray, and operates within the familiar confines of Microsoft Excel. Given a database of expression ratios, AFM 4.0 generates input files for clustering, helps prepare colored figures and Venn diagrams, and can uncover aneuploidy in yeast microarray data. AFM 4.0 should be especially useful to ...

  15. Towards standardization of microarray-based genotyping of Salmonella

    DEFF Research Database (Denmark)

    Löfström, Charlotta; Grønlund, Hugo Ahlm; Riber, Leise;

    2010-01-01

    Genotyping is becoming an increasingly important tool to improve risk assessments of Salmonella. DNA microarray technology is a promising diagnostic tool that can provide high resolution genomic profile of many genes simultaneously. However, standardization of DNA microarray analysis is needed...... of Salmonella at two different laboratories. The low-density array contained 281 of 57-60-mer oligonucleotide probes for detecting a wide range of specific genomic markers associated with antibiotic resistance, cell envelope structures, mobile genetic elements and pathogenicity. Several test parameters...... for a decentralized and simple-to-implement DNA microarray as part of a pan-European source-attribution model for risk assessment of Salmonella....

  16. Consistent Differential Expression Pattern (CDEP on microarray to identify genes related to metastatic behavior

    Directory of Open Access Journals (Sweden)

    Tsoi Lam C

    2011-11-01

    Full Text Available Abstract Background To utilize the large volume of gene expression information generated from different microarray experiments, several meta-analysis techniques have been developed. Despite these efforts, there remain significant challenges to effectively increasing the statistical power and decreasing the Type I error rate while pooling the heterogeneous datasets from public resources. The objective of this study is to develop a novel meta-analysis approach, Consistent Differential Expression Pattern (CDEP, to identify genes with common differential expression patterns across different datasets. Results We combined False Discovery Rate (FDR estimation and the non-parametric RankProd approach to estimate the Type I error rate in each microarray dataset of the meta-analysis. These Type I error rates from all datasets were then used to identify genes with common differential expression patterns. Our simulation study showed that CDEP achieved higher statistical power and maintained low Type I error rate when compared with two recently proposed meta-analysis approaches. We applied CDEP to analyze microarray data from different laboratories that compared transcription profiles between metastatic and primary cancer of different types. Many genes identified as differentially expressed consistently across different cancer types are in pathways related to metastatic behavior, such as ECM-receptor interaction, focal adhesion, and blood vessel development. We also identified novel genes such as AMIGO2, Gem, and CXCL11 that have not been shown to associate with, but may play roles in, metastasis. Conclusions CDEP is a flexible approach that borrows information from each dataset in a meta-analysis in order to identify genes being differentially expressed consistently. We have shown that CDEP can gain higher statistical power than other existing approaches under a variety of settings considered in the simulation study, suggesting its robustness and

  17. Production of DNA microarray and expression analysis of genes from Xylella fastidiosa in different culture media

    Directory of Open Access Journals (Sweden)

    Regiane de Fátima Travensolo

    2009-06-01

    Full Text Available DNA Microarray was developed to monitor the expression of many genes from Xylella fastidiosa, allowing the side by-side comparison of two situations in a single experiment. The experiments were performed using X. fastidiosa cells grown in two culture media: BCYE and XDM2. The primers were synthesized, spotted onto glass slides and the array was hybridized against fluorescently labeled cDNAs. The emitted signals were quantified, normalized and the data were statistically analyzed to verify the differentially expressed genes. According to the data, 104 genes were differentially expressed in XDM2 and 30 genes in BCYE media. The present study showed that DNA microarray technique efficiently differentiate the expressed genes under different conditions.DNA Microarray foi desenvolvida para monitorar a expressão de muitos genes de Xylella fastidiosa, permitindo a comparação de duas situações distintas em um único experimento. Os experimentos foram feitos utilizando células de X. fastidiosa cultivada em dois meios de cultura: BCYE e XDM2. Pares de oligonucleotídeos iniciadores foram sintetizados, depositados em lâminas de vidro e o arranjo foi hibridizado contra cDNAs marcados fluorescentemente. Os sinais emitidos foram quantificados, normalizados e os dados foram estatisticamente analisados para verificar os genes diferencialmente expressos. De acordo com nossos dados, 104 genes foram diferencialmente expressos para o meio de cultura XDM2 e 30 genes para o BCYE. No presente estudo, nós demonstramos que a técnica de DNA microarrays eficientemente diferencia genes expressos sob diferentes condições de cultivo.

  18. An analysis of the use of genomic DNA as a universal reference in two channel DNA microarrays

    Directory of Open Access Journals (Sweden)

    Kapur Vivek

    2005-05-01

    Full Text Available Abstract Background DNA microarray is an invaluable tool for gene expression explorations. In the two-dye microarray, fluorescence intensities of two samples, each labeled with a different dye, are compared after hybridization. To compare a large number of samples, the 'reference design' is widely used, in which all RNA samples are hybridized to a common reference. Genomic DNA is an attractive candidate for use as a universal reference, especially for bacterial systems with a low percentage of non-coding sequences. However, genomic DNA, comprising of both the sense and anti-sense strands, is unlike the single stranded cDNA usually used in microarray hybridizations. The presence of the antisense strand in the 'reference' leads to reactions between complementary labeled strands in solution and may cause the assay result to deviate from true values. Results We have developed a mathematical model to predict the validity of using genomic DNA as a reference in the microarray assay. The model predicts that the assay can accurately estimate relative concentrations for a wide range of initial cDNA concentrations. Experimental results of DNA microarray assay using genomic DNA as a reference correlated well to those obtained by a direct hybridization between two cDNA samples. The model predicts that the initial concentrations of labeled genomic DNA strands and immobilized strands, and the hybridization time do not significantly affect the assay performance. At low values of the rate constant for hybridization between immobilized and mobile strands, the assay performance varies with the hybridization time and initial cDNA concentrations. For the case where a microarray with immobilized single strands is used, results from hybridizations using genomic DNA as a reference will correspond to true ratios under all conditions. Conclusion Simulation using the mathematical model, and the experimental study presented here show the potential utility of microarray

  19. Seasonal changes in bacterial and archaeal gene expression patterns across salinity gradients in the Columbia River coastal margin.

    Directory of Open Access Journals (Sweden)

    Maria W Smith

    Full Text Available Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM. A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April and late summer (August. Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition

  20. Ontology-Based Analysis of Microarray Data.

    Science.gov (United States)

    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.

  1. Transcriptome analysis of zebrafish embryogenesis using microarrays.

    Directory of Open Access Journals (Sweden)

    Sinnakaruppan Mathavan

    2005-08-01

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

  2. Robust Model Selection for Classification of Microarrays

    Directory of Open Access Journals (Sweden)

    Ikumi Suzuki

    2009-01-01

    Full Text Available Recently, microarray-based cancer diagnosis systems have been increasingly investigated. However, cost reduction and reliability assurance of such diagnosis systems are still remaining problems in real clinical scenes. To reduce the cost, we need a supervised classifier involving the smallest number of genes, as long as the classifier is sufficiently reliable. To achieve a reliable classifier, we should assess candidate classifiers and select the best one. In the selection process of the best classifier, however, the assessment criterion must involve large variance because of limited number of samples and non-negligible observation noise. Therefore, even if a classifier with a very small number of genes exhibited the smallest leave-one-out cross-validation (LOO error rate, it would not necessarily be reliable because classifiers based on a small number of genes tend to show large variance. We propose a robust model selection criterion, the min-max criterion, based on a resampling bootstrap simulation to assess the variance of estimation of classification error rates. We applied our assessment framework to four published real gene expression datasets and one synthetic dataset. We found that a state- of-the-art procedure, weighted voting classifiers with LOO criterion, had a non-negligible risk of selecting extremely poor classifiers and, on the other hand, that the new min-max criterion could eliminate that risk. These finding suggests that our criterion presents a safer procedure to design a practical cancer diagnosis system.

  3. Development of a novel ozone- and photo-stable HyPer5 red fluorescent dye for array CGH and microarray gene expression analysis with consistent performance irrespective of environmental conditions

    Directory of Open Access Journals (Sweden)

    Kille Peter

    2008-11-01

    Full Text Available Abstract Background Array-based comparative genomic hybridization (CGH and gene expression profiling have become vital techniques for identifying molecular defects underlying genetic diseases. Regardless of the microarray platform, cyanine dyes (Cy3 and Cy5 are one of the most widely used fluorescent dye pairs for microarray analysis owing to their brightness and ease of incorporation, enabling high level of assay sensitivity. However, combining both dyes on arrays can become problematic during summer months when ozone levels rise to near 25 parts per billion (ppb. Under such conditions, Cy5 is known to rapidly degrade leading to loss of signal from either "homebrew" or commercial arrays. Cy5 can also suffer disproportionately from dye photobleaching resulting in distortion of (Cy5/Cy3 ratios used in copy number analysis. Our laboratory has been active in fluorescent dye research to find a suitable alternative to Cy5 that is stable to ozone and resistant to photo-bleaching. Here, we report on the development of such a dye, called HyPer5, and describe its' exceptional ozone and photostable properties on microarrays. Results Our results show HyPer5 signal to be stable to high ozone levels. Repeated exposure of mouse arrays hybridized with HyPer5-labeled cDNA to 300 ppb ozone at 5, 10 and 15 minute intervals resulted in no signal loss from the dye. In comparison, Cy5 arrays showed a dramatic 80% decrease in total signal during the same interval. Photobleaching experiments show HyPer5 to be resistant to light induced damage with 3- fold improvement in dye stability over Cy5. In high resolution array CGH experiments, HyPer5 is demonstrated to detect chromosomal aberrations at loci 2p21-16.3 and 15q26.3-26.2 from three patient sample using bacterial artificial chromosome (BAC arrays. The photostability of HyPer5 is further documented by repeat array scanning without loss of detection. Additionally, HyPer5 arrays are shown to preserve sensitivity and

  4. Microarray of DNA probes on carboxylate functional beads surface

    Institute of Scientific and Technical Information of China (English)

    黄承志; 李原芳; 黄新华; 范美坤

    2000-01-01

    The microarray of DNA probes with 5’ -NH2 and 5’ -Tex/3’ -NH2 modified terminus on 10 um carboxylate functional beads surface in the presence of 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) is characterized in the preseni paper. it was found that the microarray capacity of DNA probes on the beads surface depends on the pH of the aqueous solution, the concentra-tion of DNA probe and the total surface area of the beads. On optimal conditions, the minimum distance of 20 mer single-stranded DNA probe microarrayed on beads surface is about 14 nm, while that of 20 mer double-stranded DNA probes is about 27 nm. If the probe length increases from 20 mer to 35 mer, its microarray density decreases correspondingly. Mechanism study shows that the binding mode of DNA probes on the beads surface is nearly parallel to the beads surface.

  5. Cell-Based Microarrays for In Vitro Toxicology

    Science.gov (United States)

    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.

  6. Resequencing Pathogen Microarray (RPM) for prospective detection and identification of emergent pathogen strains and variants

    Science.gov (United States)

    Tibbetts, Clark; Lichanska, Agnieszka M.; Borsuk, Lisa A.; Weslowski, Brian; Morris, Leah M.; Lorence, Matthew C.; Schafer, Klaus O.; Campos, Joseph; Sene, Mohamadou; Myers, Christopher A.; Faix, Dennis; Blair, Patrick J.; Brown, Jason; Metzgar, David

    2010-04-01

    High-density resequencing microarrays support simultaneous detection and identification of multiple viral and bacterial pathogens. Because detection and identification using RPM is based upon multiple specimen-specific target pathogen gene sequences generated in the individual test, the test results enable both a differential diagnostic analysis and epidemiological tracking of detected pathogen strains and variants from one specimen to the next. The RPM assay enables detection and identification of pathogen sequences that share as little as 80% sequence similarity to prototype target gene sequences represented as detector tiles on the array. This capability enables the RPM to detect and identify previously unknown strains and variants of a detected pathogen, as in sentinel cases associated with an infectious disease outbreak. We illustrate this capability using assay results from testing influenza A virus vaccines configured with strains that were first defined years after the design of the RPM microarray. Results are also presented from RPM-Flu testing of three specimens independently confirmed to the positive for the 2009 Novel H1N1 outbreak strain of influenza virus.

  7. Antibody Microarray for E. coli O157:H7 and Shiga Toxin in Microtiter Plates

    Directory of Open Access Journals (Sweden)

    Andrew G. Gehring

    2015-12-01

    Full Text Available Antibody microarray is a powerful analytical technique because of its inherent ability to simultaneously discriminate and measure numerous analytes, therefore making the technique conducive to both the multiplexed detection and identification of bacterial analytes (i.e., whole cells, as well as associated metabolites and/or toxins. We developed a sandwich fluorescent immunoassay combined with a high-throughput, multiwell plate microarray detection format. Inexpensive polystyrene plates were employed containing passively adsorbed, array-printed capture antibodies. During sample reaction, centrifugation was the only strategy found to significantly improve capture, and hence detection, of bacteria (pathogenic Escherichia coli O157:H7 to planar capture surfaces containing printed antibodies. Whereas several other sample incubation techniques (e.g., static vs. agitation had minimal effect. Immobilized bacteria were labeled with a red-orange-fluorescent dye (Alexa Fluor 555 conjugated antibody to allow for quantitative detection of the captured bacteria with a laser scanner. Shiga toxin 1 (Stx1 could be simultaneously detected along with the cells, but none of the agitation techniques employed during incubation improved detection of the relatively small biomolecule. Under optimal conditions, the assay had demonstrated limits of detection of ~5.8 × 105 cells/mL and 110 ng/mL for E. coli O157:H7 and Stx1, respectively, in a ~75 min total assay time.

  8. Development of a high-throughput microfluidic integrated microarray for the detection of chimeric bioweapons.

    Energy Technology Data Exchange (ETDEWEB)

    Sheppod, Timothy; Satterfield, Brent; Hukari, Kyle W.; West, Jason A. A.; Hux, Gary A.

    2006-10-01

    The advancement of DNA cloning has significantly augmented the potential threat of a focused bioweapon assault, such as a terrorist attack. With current DNA cloning techniques, toxin genes from the most dangerous (but environmentally labile) bacterial or viral organism can now be selected and inserted into robust organism to produce an infinite number of deadly chimeric bioweapons. In order to neutralize such a threat, accurate detection of the expressed toxin genes, rather than classification on strain or genealogical decent of these organisms, is critical. The development of a high-throughput microarray approach will enable the detection of unknowns chimeric bioweapons. The development of a high-throughput microarray approach will enable the detection of unknown bioweapons. We have developed a unique microfluidic approach to capture and concentrate these threat genes (mRNA's) upto a 30 fold concentration. These captured oligonucleotides can then be used to synthesize in situ oligonucleotide copies (cDNA probes) of the captured genes. An integrated microfluidic architecture will enable us to control flows of reagents, perform clean-up steps and finally elute nanoliter volumes of synthesized oligonucleotides probes. The integrated approach has enabled a process where chimeric or conventional bioweapons can rapidly be identified based on their toxic function, rather than being restricted to information that may not identify the critical nature of the threat.

  9. ADVANTAGES AND APPLICATIONS OF TISSUE MICROARRAY TECHNOLOGY ON CANCER RESEARCH

    Institute of Scientific and Technical Information of China (English)

    张喜平; 苏丹; 程琪辉

    2003-01-01

    S To provide evidences for exploiting tissue microarray (TMA) technology, we reviewed advantages and applications of TMA on tumor research. TMA has many advantages, including (1) section from TMA blocks can be utilized for the simultaneous analysis of up to 1,000 different tumors at DNA, RNA or protein level; (2) TMA is highly representative of their donor tissues; (3) TMA can improve conservation of tissue resources and experimental reagents, improve internal experimental control, and increase sample numbers per experiment, and can be used for large-scale, massively parallel in situ analysis; (4) TMA facilitates rapid translation of molecular discoveries to clinical applications. TMA has been applied to tumor research, such as glioma, breast tumor, lung cancer and so on. The development of novel biochip technologies has opened up new possibilities for the high-throughput molecular profiling of human tumors. Novel molecular markers emerging from high-throughput expression surveys could be analyzed on tumor TMA. It is anticipated that TMA, a new member of biochip, will soon become a widely used tool for all types of tissue-based research. TMA will lead to a significant acceleration of the transition of basic research findings into clinical applications.

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

    Science.gov (United States)

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

    2016-01-01

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

  11. Application of Phenotype Microarray technology to soil microbiology

    Science.gov (United States)

    Mocali, Stefano

    2016-04-01

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

  12. Professor WANG Changhong's Experience in Treatment of Bacterial Liver Abscess%王长洪教授治疗细菌性肝脓肿经验

    Institute of Scientific and Technical Information of China (English)

    高文艳; 王长洪

    2013-01-01

    Professor WANG Changhong thinks that the external cause of bacterial liver abscess is the accumulation of heat and toxin,clearing away heat and toxic materia is the fundamental treatment,the herb's dosage should be heavy.The internal cause is deficiency of healthy Qi,benefiting vital energy should through the treatment,the Mongolian Milkvetch Root should be used most frequently ; Qi-stagnation and blood stasis is the critical pathogenesis,activating blood circulation to dissipate blood stasis can promote abscess to dissipate.Treating by stages has the better manipuility.%王长洪教授认为细菌性肝脓肿热毒内蕴是外因,清热解毒是根本大法,用药宜重剂;正气虚损是内因,益气扶正宜贯穿治疗始终,应用黄芪最为常;气阻血瘀是关键病机,活血化瘀促消散.临证之时,分期论治更具可操作性.

  13. The peroxidase-mediated biodegradation of petroleum hydrocarbons in a H2O2-induced SBR using in-situ production of peroxidase: Biodegradation experiments and bacterial identification.

    Science.gov (United States)

    Shekoohiyan, Sakine; Moussavi, Gholamreza; Naddafi, Kazem

    2016-08-01

    A bacterial peroxidase-mediated oxidizing process was developed for biodegrading total petroleum hydrocarbons (TPH) in a sequencing batch reactor (SBR). Almost complete biodegradation (>99%) of high TPH concentrations (4g/L) was attained in the bioreactor with a low amount (0.6mM) of H2O2 at a reaction time of 22h. A specific TPH biodegradation rate as high as 44.3mgTPH/gbiomass×h was obtained with this process. The reaction times required for complete biodegradation of TPH concentrations of 1, 2, 3, and 4g/L were 21, 22, 28, and 30h, respectively. The catalytic activity of hydrocarbon catalyzing peroxidase was determined to be 1.48U/mL biomass. The biodegradation of TPH in seawater was similar to that in fresh media (no salt). A mixture of bacteria capable of peroxidase synthesis and hydrocarbon biodegradation including Pseudomonas spp. and Bacillus spp. were identified in the bioreactor. The GC/MS analysis of the effluent indicated that all classes of hydrocarbons could be well-degraded in the H2O2-induced SBR. Accordingly, the peroxidase-mediated process is a promising method for efficiently biodegrading concentrated TPH-laden saline wastewater. PMID:27060866

  14. Feature extraction and signal processing for nylon DNA microarrays

    OpenAIRE

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

    2004-01-01

    Abstract Background High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels. Results We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introdu...

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

    OpenAIRE

    Tewfik Ahmed H; Tchagang Alain B

    2006-01-01

    Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, w...

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

    OpenAIRE

    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 unde...

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

    Science.gov (United States)

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

    2006-01-01

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

  18. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

    Full Text Available Abstract 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.

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

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    Zer Cindy

    2010-02-01

    Full Text Available Abstract Background Veterinary drugs such as clenbuterol (CL and sulfamethazine (SM2 are low molecular weight ( 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.

  20. Granulometric Analysis of Spots in DNA Microarray Images

    Institute of Scientific and Technical Information of China (English)

    Behara Latha; Balasubramanian Venkatesh

    2004-01-01

    As the topological properties of each spot in DNA microarray images may vary from one another, we employed granulometries to understand the shape-size con tent contributed due to a significant intensity value within a spot. Analysis was performed on the microarray image that consisted of 240 spots by using concepts from mathematical morphology. In order to find out indices for each spot and to further classify them, we adopted morphological multiscale openings, which provided microarrays at multiple scales. Successive opened microarrays were subtracted to identify the protrusions that were smaller than the size of structuring element. Spot-wise details, in terms of probability of these observed protrusions,were computed by placing a regularly spaced grid on microarray such that each spot was centered in each grid. Based on the probability of size distribution functions of these protrusions isolated at each level, we estimated the mean size and texture index for each spot. With these characteristics, we classified the spots in a microarray image into bright and dull categories through pattern spectrum and shape-size complexity measures. These segregated spots can be compared with those of hybridization levels.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  2. Microarray and real-time PCR analyses of the responses of high-arctic soil bacteria to hydrocarbon pollution and bioremediation treatments.

    Science.gov (United States)

    Yergeau, Etienne; Arbour, Mélanie; Brousseau, Roland; Juck, David; Lawrence, John R; Masson, Luke; Whyte, Lyle G; Greer, Charles W

    2009-10-01

    High-Arctic soils have low nutrient availability, low moisture content, and very low temperatures and, as such, they pose a particular problem in terms of hydrocarbon bioremediation. An in-depth knowledge of the microbiology involved in this process is likely to be crucial to understand and optimize the factors most influencing bioremediation. Here, we compared two distinct large-scale field bioremediation experiments, located at the Canadian high-Arctic stations of Alert (ex situ approach) and Eureka (in situ approach). Bacterial community structure and function were assessed using microarrays targeting the 16S rRNA genes of bacteria found in cold environments and hydrocarbon degradation genes as well as quantitative reverse transcriptase PCR targeting key functional genes. The results indicated a large difference between sampling sites in terms of both soil microbiology and decontamination rates. A rapid reorganization of the bacterial community structure and functional potential as well as rapid increases in the expression of alkane monooxygenases and polyaromatic hydrocarbon-ring-hydroxylating dioxygenases were observed 1 month after the bioremediation treatment commenced in the Alert soils. In contrast, no clear changes in community structure were observed in Eureka soils, while key gene expression increased after a relatively long lag period (1 year). Such discrepancies are likely caused by differences in bioremediation treatments (i.e., ex situ versus in situ), weathering of the hydrocarbons, indigenous microbial communities, and environmental factors such as soil humidity and temperature. In addition, this study demonstrates the value of molecular tools for the monitoring of polar bacteria and their associated functions during bioremediation. PMID:19684169

  3. ONCOMINE: A Cancer Microarray Database and Integrated Data-Mining Platform

    Directory of Open Access Journals (Sweden)

    Daniel R. Rhodes

    2004-01-01

    Full Text Available DNA microarray technology has led to an explosion of oncogenomic analyses, generating a wealth of data and uncovering the complex gene expression patterns of cancer. Unfortunately, due to the lack of a unifying bioinformatic resource, the majority of these data sit stagnant and disjointed following publication, massively underutilized by the cancer research community. Here, we present ONCOMINE, a cancer microarray database and web-based data-mining platform aimed at facilitating discovery from genome-wide expression analyses. To date, ONCOMINE contains 65 gene expression datasets comprising nearly 48 million gene expression measurements form over 4700 microarray experiments. Differential expression analyses comparing most major types of cancer with respective normal tissues as well as a variety of cancer subtypes and clinical-based and pathology-based analyses are available for exploration. Data can be queried and visualized for a selected gene across all analyses or for multiple genes in a selected analysis. Furthermore, gene sets can be limited to clinically important annotations including secreted, kinase, membrane, and known gene-drug target pairs to facilitate the discovery of novel biomarkers and therapeutic targets.

  4. Parallelization of multicategory support vector machines (PMC-SVM for classifying microarray data

    Directory of Open Access Journals (Sweden)

    Deng Youping

    2006-12-01

    Full Text Available Abstract Background Multicategory Support Vector Machines (MC-SVM are powerful classification systems with excellent performance in a variety of data classification problems. Since the process of generating models in traditional multicategory support vector machines for large datasets is very computationally intensive, there is a need to improve the performance using high performance computing techniques. Results In this paper, Parallel Multicategory Support Vector Machines (PMC-SVM have been developed based on the sequential minimum optimization-type decomposition method for support vector machines (SMO-SVM. It was implemented in parallel using MPI and C++ libraries and executed on both shared memory supercomputer and Linux cluster for multicategory classification of microarray data. PMC-SVM has been analyzed and evaluated using four microarray datasets with multiple diagnostic categories, such as different cancer types and normal tissue types. Conclusion The experiments show that the PMC-SVM can significantly improve the performance of classification of microarray data without loss of accuracy, compared with previous work.

  5. The tissue microarray data exchange specification: A community-based, open source tool for sharing tissue microarray data

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    Edgerton Mary E

    2003-05-01

    Full Text Available Abstract Background Tissue Microarrays (TMAs allow researchers to examine hundreds of small tissue samples on a single glass slide. The information held in a single TMA slide may easily involve Gigabytes of data. To benefit from TMA technology, the scientific community needs an open source TMA data exchange specification that will convey all of the data in a TMA experiment in a format that is understandable to both humans and computers. A data exchange specification for TMAs allows researchers to submit their data to journals and to public data repositories and to share or merge data from different laboratories. In May 2001, the Association of Pathology Informatics (API hosted the first in a series of four workshops, co-sponsored by the National Cancer Institute, to develop an open, community-supported TMA data exchange specification. Methods A draft tissue microarray data exchange specification was developed through workshop meetings. The first workshop confirmed community support for the effort and urged the creation of an open XML-based specification. This was to evolve in steps with approval for each step coming from the stakeholders in the user community during open workshops. By the fourth workshop, held October, 2002, a set of Common Data Elements (CDEs was established as well as a basic strategy for organizing TMA data in self-describing XML documents. Results The TMA data exchange specification is a well-formed XML document with four required sections: 1 Header, containing the specification Dublin Core identifiers, 2 Block, describing the paraffin-embedded array of tissues, 3Slide, describing the glass slides produced from the Block, and 4 Core, containing all data related to the individual tissue samples contained in the array. Eighty CDEs, conforming to the ISO-11179 specification for data elements constitute XML tags used in the TMA data exchange specification. A set of six simple semantic rules describe the complete data exchange

  6. Swarm Intelligence Approach Based on Adaptive ELM Classifier with ICGA Selection for Microarray Gene Expression and Cancer Classification

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    T. Karthikeyan

    2014-05-01

    Full Text Available The aim of this research study is based on efficient gene selection and classification of microarray data analysis using hybrid machine learning algorithms. The beginning of microarray technology has enabled the researchers to quickly measure the position of thousands of genes expressed in an organic/biological tissue samples in a solitary experiment. One of the important applications of this microarray technology is to classify the tissue samples using their gene expression representation, identify numerous type of cancer. Cancer is a group of diseases in which a set of cells shows uncontrolled growth, instance that interrupts upon and destroys nearby tissues and spreading to other locations in the body via lymph or blood. Cancer has becomes a one of the major important disease in current scenario. DNA microarrays turn out to be an effectual tool utilized in molecular biology and cancer diagnosis. Microarrays can be measured to establish the relative quantity of mRNAs in two or additional organic/biological tissue samples for thousands/several thousands of genes at the same time. As the superiority of this technique become exactly analysis/identifying the suitable assessment of microarray data in various open issues. In the field of medical sciences multi-category cancer classification play a major important role to classify the cancer types according to the gene expression. The need of the cancer classification has been become indispensible, because the numbers of cancer victims are increasing steadily identified by recent years. To perform this proposed a combination of Integer-Coded Genetic Algorithm (ICGA and Artificial Bee Colony algorithm (ABC, coupled with an Adaptive Extreme Learning Machine (AELM, is used for gene selection and cancer classification. ICGA is used with ABC based AELM classifier to chose an optimal set of genes which results in an efficient hybrid algorithm that can handle sparse data and sample imbalance. The

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

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    Malyj Wasyl

    2005-08-01

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

  8. Photopatterning of Hydrogel Microarrays in Closed Microchips.

    Science.gov (United States)

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

    2015-12-14

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

  9. Pipeline for macro- and microarray analyses

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    R. Vicentini

    2007-05-01

    Full Text Available 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.

  10. Pipeline for macro- and microarray analyses.

    Science.gov (United States)

    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

  11. Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone.

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    Susann K J Ludwig

    Full Text Available Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1. Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this 'protein microarray on a smartphone'-concept for on-site testing, e.g., in food safety, environment and health monitoring.

  12. Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone.

    Science.gov (United States)

    Ludwig, Susann K J; Tokarski, Christian; Lang, Stefan N; van Ginkel, Leendert A; Zhu, Hongying; Ozcan, Aydogan; Nielen, Michel W F

    2015-01-01

    Here we present the concept of a protein microarray-based fluorescence immunoassay for multiple biomarker detection in milk extracts by an ordinary smartphone. A multiplex immunoassay was designed on a microarray chip, having built-in positive and negative quality controls. After the immunoassay procedure, the 48 microspots were labelled with Quantum Dots (QD) depending on the protein biomarker levels in the sample. QD-fluorescence was subsequently detected by the smartphone camera under UV light excitation from LEDs embedded in a simple 3D-printed opto-mechanical smartphone attachment. The somewhat aberrant images obtained under such conditions, were corrected by newly developed Android-based software on the same smartphone, and protein biomarker profiles were calculated. The indirect detection of recombinant bovine somatotropin (rbST) in milk extracts based on altered biomarker profile of anti-rbST antibodies was selected as a real-life challenge. RbST-treated and untreated cows clearly showed reproducible treatment-dependent biomarker profiles in milk, in excellent agreement with results from a flow cytometer reference method. In a pilot experiment, anti-rbST antibody detection was multiplexed with the detection of another rbST-dependent biomarker, insulin-like growth factor 1 (IGF-1). Milk extract IGF-1 levels were found to be increased after rbST treatment and correlated with the results obtained from the reference method. These data clearly demonstrate the potential of the portable protein microarray concept towards simultaneous detection of multiple biomarkers. We envisage broad application of this 'protein microarray on a smartphone'-concept for on-site testing, e.g., in food safety, environment and health monitoring. PMID:26308444

  13. Development and validation of a microarray for the investigation of the CAZymes encoded by the human gut microbiome.

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    Abdessamad El Kaoutari

    Full Text Available Distal gut bacteria play a pivotal role in the digestion of dietary polysaccharides by producing a large number of carbohydrate-active enzymes (CAZymes that the host otherwise does not produce. We report here the design of a custom microarray that we used to spot non-redundant DNA probes for more than 6,500 genes encoding glycoside hydrolases and lyases selected from 174 reference genomes from distal gut bacteria. The custom microarray was tested and validated by the hybridization of bacterial DNA extracted from the stool samples of lean, obese and anorexic individuals. Our results suggest that a microarray-based study can detect genes from low-abundance bacteria better than metagenomic-based studies. A striking example was the finding that a gene encoding a GH6-family cellulase was present in all subjects examined, whereas metagenomic studies have consistently failed to detect this gene in both human and animal gut microbiomes. In addition, an examination of eight stool samples allowed the identification of a corresponding CAZome core containing 46 families of glycoside hydrolases and polysaccharide lyases, which suggests the functional stability of the gut microbiota despite large taxonomical variations between individuals.

  14. Development of a novel multiplex DNA microarray for Fusarium graminearum and analysis of azole fungicide responses

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    Deising Holger B

    2011-01-01

    . Comparative analyses with published microarray experiments obtained from two different nutritional stress conditions identified subsets of genes responding to different types of stress. Some of the genes that responded only to tebuconazole treatment appeared to be unique to the F. graminearum genome. Conclusions The novel F. graminearum 8 × 15 k microarray is a reliable and efficient high-throughput tool for genome-wide expression profiling experiments in fungicide research, and beyond, as shown by our data obtained for azole responses. The array data contribute to understanding mechanisms of fungicide resistance and allow identifying fungicide targets.

  15. CGHScan: finding variable regions using high-density microarray comparative genomic hybridization data

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    Rajashekara Gireesh

    2006-04-01

    Full Text Available Abstract Background Comparative genomic hybridization can rapidly identify chromosomal regions that vary between organisms and tissues. This technique has been applied to detecting differences between normal and cancerous tissues in eukaryotes as well as genomic variability in microbial strains and species. The density of oligonucleotide probes available on current microarray platforms is particularly well-suited for comparisons of organisms with smaller genomes like bacteria and yeast where an entire genome can be assayed on a single microarray with high resolution. Available methods for analyzing these experiments typically confine analyses to data from pre-defined annotated genome features, such as entire genes. Many of these methods are ill suited for datasets with the number of measurements typical of high-density microarrays. Results We present an algorithm for analyzing microarray hybridization data to aid identification of regions that vary between an unsequenced genome and a sequenced reference genome. The program, CGHScan, uses an iterative random walk approach integrating multi-layered significance testing to detect these regions from comparative genomic hybridization data. The algorithm tolerates a high level of noise in measurements of individual probe intensities and is relatively insensitive to the choice of method for normalizing probe intensity values and identifying probes that differ between samples. When applied to comparative genomic hybridization data from a published experiment, CGHScan identified eight of nine known deletions in a Brucella ovis strain as compared to Brucella melitensis. The same result was obtained using two different normalization methods and two different scores to classify data for individual probes as representing conserved or variable genomic regions. The undetected region is a small (58 base pair deletion that is below the resolution of CGHScan given the array design employed in the study

  16. Prevention of bacterial adhesion

    DEFF Research Database (Denmark)

    Klemm, Per; Vejborg, Rebecca Munk; Hancock, Viktoria

    2010-01-01

    Management of bacterial infections is becoming increasingly difficult due to the emergence and increasing prevalence of bacterial pathogens that are resistant to available antibiotics. Conventional antibiotics generally kill bacteria by interfering with vital cellular functions, an approach that ...

  17. Significance analysis of lexical bias in microarray data

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    Falkow Stanley

    2003-04-01

    Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.

  18. AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

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    V.G. Biju

    2015-11-01

    Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

  19. A novel method for preparation of tissue microarray

    Institute of Scientific and Technical Information of China (English)

    Han-Lei Dan; Yan-Qing Ding; Chun-Hai Guo; Dian-Yuan Zhou; Ya-Li Zhang; Yan Zhang; Ya-Dong Wang; Zuo-Sheng Lai; Yu-Jie Yang; Hai-Hong Cui; Yan-Ting Jian; Jian Geng

    2004-01-01

    AIM: To improve the technique of tissue microarray (tissue chip).METHODS: A new tissue microarraying method was invented with a common microscope installed with a special holing needle, a sampling needle, and a special box fixing paraffin blocks on the microscope slide carrier. With the movement of microscope tube and objective stage on vertical and cross dimensions respectively, the holing procedure on the recipient paraffin blocks and sampling procedure of core tissue biopsies taken from the donor blocks were performed with the refitted microscope on the same platform. The precise observation and localization of representative regions in the donor blocks were also performed with the microscope equipped with a stereoscope.RESULTS: Highly-qualified tissue chips of colorectal tumors were produced by a new method, which simplified the conventional microarraying procedure, and was more convenient and accurate than that employing the existing tissue microarraying instruments.CONCLUSION: Using the refitted common microscope to produce tissue microarray is a simple, reliable, cost-effective and well-applicable technique.

  20. Advanced Data Mining of Leukemia Cells Micro-Arrays

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    Ryan M. Pierce

    2009-12-01

    Full Text Available This paper provides continuation and extensions of previous research by Segall and Pierce (2009a that discussed data mining for micro-array databases of Leukemia cells for primarily self-organized maps (SOM. As Segall and Pierce (2009a and Segall and Pierce (2009b the results of applying data mining are shown and discussed for the data categories of microarray databases of HL60, Jurkat, NB4 and U937 Leukemia cells that are also described in this article. First, a background section is provided on the work of others pertaining to the applications of data mining to micro-array databases of Leukemia cells and micro-array databases in general. As noted in predecessor article by Segall and Pierce (2009a, micro-array databases are one of the most popular functional genomics tools in use today. This research in this paper is intended to use advanced data mining technologies for better interpretations and knowledge discovery as generated by the patterns of gene expressions of HL60, Jurkat, NB4 and U937 Leukemia cells. The advanced data mining performed entailed using other data mining tools such as cubic clustering criterion, variable importance rankings, decision trees, and more detailed examinations of data mining statistics and study of other self-organized maps (SOM clustering regions of workspace as generated by SAS Enterprise Miner version 4. Conclusions and future directions of the research are also presented.

  1. Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells

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    Kim Han

    2012-07-01

    Full Text Available Abstract Background In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. Results Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1 was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2. Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. Conclusions Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that

  2. Bacterial survival in Martian conditions

    CERN Document Server

    D'Alessandro, Giuseppe Galletta; Giulio Bertoloni; Maurizio

    2010-01-01

    We shortly discuss the observable consequences of the two hypotheses about the origin of life on Earth and Mars: the Lithopanspermia (Mars to Earth or viceversa) and the origin from a unique progenitor, that for Earth is called LUCA (the LUCA hypothesis). To test the possibility that some lifeforms similar to the terrestrial ones may survive on Mars, we designed and built two simulators of Martian environments where to perform experiments with different bacterial strains: LISA and mini-LISA. Our LISA environmental chambers can reproduce the conditions of many Martian locations near the surface trough changes of temperature, pressure, UV fluence and atmospheric composition. Both simulators are open to collaboration with other laboratories interested in performing experiments on many kind of samples (biological, minerals, electronic) in situations similar to that of the red planet. Inside LISA we have studied the survival of several bacterial strains and endospores. We verified that the UV light is the major re...

  3. Reproducibility of oligonucleotide microarray transcriptome analyses - An interlaboratory comparison using chemostat cultures of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Piper, M.D.W.; Daran-Lapujade, P.; Bro, Christoffer;

    2002-01-01

    -microarray analysis in functional genomics and metabolic engineering, we designed a set of experiments to specifically address this issue. Saccharomyces cerevisiae CEN.PK113-7D was grown under defined,conditions in, glucose-limited chemostats, followed by transcriptome analysis with Affymetrix Gene-Chip arrays. In...... each of the laboratories, three independent replicate cultures were grown aerobically as well as anaerobically. Although variations introduced by in vitro handling steps were small and unbiased, greater variation from replicate cultures underscored that, to obtain reliable information, experimental...

  4. Silicon biochips for dual label-free and fluorescence detection: Application to protein microarray development

    OpenAIRE

    Cretich M.; Reddington A.; Monroe M.; Bagnati M.; Damin F.; Sola L.; Unlu M.S.; Chiari M.

    2011-01-01

    A new silicon chip for protein microarray development, fabrication and validation is proposed. The chip is made of two areas with oxide layers of different thicknesses: an area with a 500 nm SiO2 layer dedicated to interferometric label-free detection and quantification of proteins and an area with 100 nm SiO2 providing enhanced fluorescence. The chip allows, within a single experiment performed on the same surface, label-free imaging of arrayed protein probes coupled with high sensitivity fl...

  5. Prevention of bacterial adhesion

    DEFF Research Database (Denmark)

    Klemm, Per; Vejborg, Rebecca Munk; Hancock, Viktoria

    2010-01-01

    that imposes selection pressure for resistant bacteria. New approaches are urgently needed. Targeting bacterial virulence functions directly is an attractive alternative. An obvious target is bacterial adhesion. Bacterial adhesion to surfaces is the first step in colonization, invasion, and biofilm formation....... As such, adhesion represents the Achilles heel of crucial pathogenic functions. It follows that interference with adhesion can reduce bacterial virulence. Here, we illustrate this important topic with examples of techniques being developed that can inhibit bacterial adhesion. Some of these will become...

  6. Utilisation of antibody microarrays for the selection of specific and informative antibodies from recombinant library binders of unknown quality.

    Science.gov (United States)

    Kibat, Janek; Schirrmann, Thomas; Knape, Matthias J; Helmsing, Saskia; Meier, Doris; Hust, Michael; Schröder, Christoph; Bertinetti, Daniela; Winter, Gerhard; Pardes, Khalid; Funk, Mia; Vala, Andrea; Giese, Nathalia; Herberg, Friedrich W; Dübel, Stefan; Hoheisel, Jörg D

    2016-09-25

    Many diagnostic and therapeutic concepts require antibodies of high specificity. Recombinant binder libraries and related selection approaches allow the efficient isolation of antibodies against almost every target of interest. Nevertheless, it cannot be guaranteed that selected antibodies perform well and interact specifically enough with analytes unless an elaborate characterisation is performed. Here, we present an approach to shorten this process by combining the selection of suitable antibodies with the identification of informative target molecules by means of antibody microarrays, thereby reducing the effort of antibody characterisation by concentrating on relevant molecules. In a pilot scheme, a library of 456 single-chain variable fragment (scFv) binders to 134 antigens was used. They were arranged in a microarray format and incubated with the protein content of clinical tissue samples isolated from pancreatic ductal adenocarcinoma and healthy pancreas, as well as recurrent and non-recurrent bladder tumours. We observed significant variation in the expression of the E3 ubiquitin-protein ligase (CHFR) as well as the glutamate receptor interacting protein 2 (GRIP2), for example, always with more than one of the scFvs binding to these targets. Only the relevant antibodies were then characterised further on antigen microarrays and by surface plasmon resonance experiments so as to select the most specific and highest affinity antibodies. These binders were in turn used to confirm a microarray result by immunohistochemistry analysis. PMID:26709003

  7. Systematic identification of cell cycle regulated transcription factors from microarray time series data

    Directory of Open Access Journals (Sweden)

    Li Lei M

    2008-03-01

    Full Text Available Abstract Background The cell cycle has long been an important model to study the genome-wide transcriptional regulation. Although several methods have been introduced to identify cell cycle regulated genes from microarray data, they can not be directly used to investigate cell cycle regulated transcription factors (CCRTFs, because for many transcription factors (TFs it is their activities instead of expressions that are periodically regulated across the cell cycle. To overcome this problem, it is useful to infer TF activities across the cell cycle by integrating microarray expression data with ChIP-chip data, and then examine the periodicity of the inferred activities. For most species, however, large-scale ChIP-chip data are still not available. Results We propose a two-step method to identify the CCRTFs by integrating microarray cell cycle data with ChIP-chip data or motif discovery data. In S. cerevisiae, we identify 42 CCRTFs, among which 23 have been verified experimentally. The cell cycle related behaviors (e.g. at which cell cycle phase a TF achieves the highest activity predicted by our method are consistent with the well established knowledge about them. We also find that the periodical activity fluctuation of some TFs can be perturbed by the cell synchronization treatment. Moreover, by integrating expression data with in-silico motif discovery data, we identify 8 cell cycle associated regulatory motifs, among which 7 are binding sites for well-known cell cycle related TFs. Conclusion Our method is effective to identify CCRTFs by integrating microarray cell cycle data with TF-gene binding information. In S. cerevisiae, the TF-gene binding information is provided by the systematic ChIP-chip experiments. In other species where systematic ChIP-chip data is not available, in-silico motif discovery and analysis provide us with an alternative method. Therefore, our method is ready to be implemented to the microarray cell cycle data sets from

  8. Microarray-based sketches of the HERV transcriptome landscape.

    Science.gov (United States)

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

    2012-01-01

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

  9. Microarray-based sketches of the HERV transcriptome landscape.

    Directory of Open Access Journals (Sweden)

    Philippe Pérot

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

  10. Bacterial survival in Martian conditions

    OpenAIRE

    Galletta, Giuseppe; Bertoloni, Giulio; D'Alessandro, Maurizio

    2010-01-01

    We shortly discuss the observable consequences of the two hypotheses about the origin of life on Earth and Mars: the Lithopanspermia (Mars to Earth or viceversa) and the origin from a unique progenitor, that for Earth is called LUCA (the LUCA hypothesis). To test the possibility that some lifeforms similar to the terrestrial ones may survive on Mars, we designed and built two simulators of Martian environments where to perform experiments with different bacterial strains: LISA and mini-LISA. ...

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

    Science.gov (United States)

    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.

  12. A Protein Microarray ELISA for Screening Biological Fluids

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-02-01

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

  13. Effect of heavy metals on bacterial transport

    Science.gov (United States)

    Zhang, H.; Olson, M. S.

    2010-12-01

    Adsorption of metals onto bacteria and soil takes place as stormwater runoff infiltrates into the subsurface. Changes in both bacterial surfaces and soil elemental content have been observed, and may alter the attachment of bacteria to soil surfaces. In this study, scanning electron microscopy (SEM) and Energy Dispersive X-ray Spectrometry (EDS) analyses were performed on soil samples equilibrated with synthetic stormwater amended with copper, lead and zinc. The results demonstrate the presence of copper and zinc on soil surfaces. To investigate bacterial attachment behavior, sets of batch sorption experiments were conducted on Escherichia Coli (E. coli) under different chemical conditions by varying solution compositions (nutrient solution vs synthetic stormwater). The adsorption data is best described using theoretical linear isotherms. The equilibrium coefficient (Kd) of E. coli is higher in synthetic stormwater than in nutrient solution without heavy metals. The adsorption of heavy metals onto bacterial surfaces significantly decreases their negative surface charge as determined via zeta potential measurements (-17.0±5.96mv for E. coli equilibrated with synthetic stormwater vs -21.6±5.45mv for E. coli equilibrated with nutrient solution), indicating that bacterial attachment may increase due to the attachment of metals onto bacterial surfaces and their subsequent change in surface charge. The attachment efficiency (α) of bacteria was also calculated and compared for both solution chemistries. Bacterial attachment efficiency (α) in synthetic stormwater is 0.997, which is twice as high as that in nutrient solution(α 0.465). The ratio of bacterial diameter : collector diameter suggests minimal soil straining during bacterial transport. Results suggest that the presence of metals in synthetic stormwater leads to an increase in bacterial attachment to soil surfaces. In terms of designing stormwater infiltration basins, the presence of heavy metals seems to

  14. arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays

    Directory of Open Access Journals (Sweden)

    Moreau Yves

    2005-05-01

    Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.

  15. On-Chip Isothermal Nucleic Acid Amplification on Flow-Based Chemiluminescence Microarray Analysis Platform for the Detection of Viruses and Bacteria.

    Science.gov (United States)

    Kunze, A; Dilcher, M; Abd El Wahed, A; Hufert, F; Niessner, R; Seidel, M

    2016-01-01

    This work presents an on-chip isothermal nucleic acid amplification test (iNAAT) for the multiplex amplification and detection of viral and bacterial DNA by a flow-based chemiluminescence microarray. In a principle study, on-chip recombinase polymerase amplification (RPA) on defined spots of a DNA microarray was used to spatially separate the amplification reaction of DNA from two viruses (Human adenovirus 41, Phi X 174) and the bacterium Enterococcus faecalis, which are relevant for water hygiene. By establishing the developed assay on the microarray analysis platform MCR 3, the automation of isothermal multiplex-amplification (39 °C, 40 min) and subsequent detection by chemiluminescence imaging was realized. Within 48 min, the microbes could be identified by the spot position on the microarray while the generated chemiluminescence signal correlated with the amount of applied microbe DNA. The limit of detection (LOD) determined for HAdV 41, Phi X 174, and E. faecalis was 35 GU/μL, 1 GU/μL, and 5 × 10(3) GU/μL (genomic units), which is comparable to the sensitivity reported for qPCR analysis, respectively. Moreover the simultaneous amplification and detection of DNA from all three microbes was possible. The presented assay shows that complex enzymatic reactions like an isothermal amplification can be performed in an easy-to-use experimental setup. Furthermore, iNAATs can be potent candidates for multipathogen detection in clinical, food, or environmental samples in routine or field monitoring approaches.

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

    Science.gov (United States)

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

    2002-01-01

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

  17. Bacterial profiles of saliva in relation to diet, lifestyle factors, and socioeconomic status

    DEFF Research Database (Denmark)

    Belstrøm, Daniel; Holmstrup, Palle; Nielsen, Claus H;

    2014-01-01

    BACKGROUND AND OBJECTIVE: The bacterial profile of saliva is composed of bacteria from different oral surfaces. The objective of this study was to determine whether different diet intake, lifestyle, or socioeconomic status is associated with characteristic bacterial saliva profiles. DESIGN......: Stimulated saliva samples from 292 participants with low levels of dental caries and periodontitis, enrolled in the Danish Health Examination Survey (DANHES), were analyzed for the presence of approximately 300 bacterial species by means of the Human Oral Microbe Identification Microarray (HOMIM). Using...... presence and levels (mean HOMIM-value) of bacterial probes as endpoints, the influence of diet intake, lifestyle, and socioeconomic status on the bacterial saliva profile was analyzed by Mann-Whitney tests with Benjamini-Hochberg's correction for multiple comparisons and principal component analysis...

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

    Directory of Open Access Journals (Sweden)

    Amir Syahir

    2015-04-01

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

  19. Probe Selection for DNA Microarrays using OligoWiz

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Juncker, Agnieszka; Nielsen, Henrik Bjørn

    2007-01-01

    Nucleotide abundance measurements using DNA microarray technology are possible only if appropriate probes complementary to the target nucleotides can be identified. Here we present a protocol for selecting DNA probes for microarrays using the OligoWiz application. OligoWiz is a client......-server application that offers a detailed graphical interface and real-time user interaction on the client side, and massive computer power and a large collection of species databases (400, summer 2007) on the server side. Probes are selected according to five weighted scores: cross-hybridization, deltaT(m), folding...

  20. Compressió de microarrays d'ADN

    OpenAIRE

    Pueyo Navarro, Iván

    2015-01-01

    La tecnologia relacionada amb la creació d'imatges de microarray d'ADN és una eina de gran importància en el descobriment de l'estructura i funcionament de la nostra informació genètica. Dins d'aquest camp, la detecció del comportament de determinats gens sota condicions especifiques adquireix una gran rellevància. La grandària de les imatges de microarray sol ser de mitjana elevada, a causa de la gran quantitat de gens que s'analitzen i al fet que s'intenta mantenir en les imatges el major c...

  1. Fluorescence Lifetime Imaging of Quantum Dot Labeled DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Jonathan G. Terry

    2009-04-01

    Full Text Available Quantum dot (QD labeling combined with fluorescence lifetime imaging microscopy is proposed as a powerful transduction technique for the detection of DNA hybridization events. Fluorescence lifetime analysis of DNA microarray spots of hybridized QD labeled target indicated a characteristic lifetime value of 18.8 ns, compared to 13.3 ns obtained for spots of free QD solution, revealing that QD labels are sensitive to the spot microenvironment. Additionally, time gated detection was shown to improve the microarray image contrast ratio by 1.8, achieving femtomolar target sensitivity. Finally, lifetime multiplexing based on Qdot525 and Alexa430 was demonstrated using a single excitation-detection readout channel.

  2. Bacterial Evolution and Bak-Sneppen Model

    OpenAIRE

    Bose, Indrani; Chaudhuri, Indranath

    2002-01-01

    Recently, Lenski et al [Elena,Lenski,Travisano] have carried out several experiments on bacterial evolution. Their findings support the theory of punctuated equilibrium in biological evolution. They have further quantified the relative contributions of adaptation, chance and history to bacterial evolution. In this paper, we show that a modified $M$-trait Bak-Sneppen model can explain many of the experimental results in a qualitative manner.

  3. BR 07-1 DEVELOPMENT OF THE CELL MICROARRAY FOR HIGH-THROUGHPUT ANALYSIS OF GUT MICROBIOTA.

    Science.gov (United States)

    Hong, Seong-Tshool

    2016-09-01

    cell microarray contains all of the known individual microbial organisms constituting gut microbiota. We proved by using Rheumatoid arthritis (RA) cases that the cell microarray is much more accurately and faster than the current metagenomic sequencing approaches in analyzing gut microbiota. The cell microarray was hybridized with the serums of healthy people and RA patients. Based on the binding affinity of serum immunoglobin with the spots of bacterial cultures on the cell microarray, our results clearly indicated that the serum of RA patients have significantly less response to gut bacterial species than those of healthy control. It was also able to detect the microbial species playing a causative role for RA and the microbial species playing a protective role to RA. This result suggests that, the cell microarray developed here is an effective, less expensive, and rapid identification method for analyzing gut microbiota. We believe that the cell microarray can be used to various clinical blood samples, including hypertension, to elucidate the etiological microbial species of gut microbiota which play causative roles for complex diseases or protective roles to the complex disease. PMID:27643284

  4. Sensitivity and fidelity of DNA microarray improved with integration of Amplified Differential Gene Expression (ADGE

    Directory of Open Access Journals (Sweden)

    Ile Kristina E

    2003-07-01

    Full Text Available Abstract Background The ADGE technique is a method designed to magnify the ratios of gene expression before detection. It improves the detection sensitivity to small change of gene expression and requires small amount of starting material. However, the throughput of ADGE is low. We integrated ADGE with DNA microarray (ADGE microarray and compared it with regular microarray. Results When ADGE was integrated with DNA microarray, a quantitative relationship of a power function between detected and input ratios was found. Because of ratio magnification, ADGE microarray was better able to detect small changes in gene expression in a drug resistant model cell line system. The PCR amplification of templates and efficient labeling reduced the requirement of starting material to as little as 125 ng of total RNA for one slide hybridization and enhanced the signal intensity. Integration of ratio magnification, template amplification and efficient labeling in ADGE microarray reduced artifacts in microarray data and improved detection fidelity. The results of ADGE microarray were less variable and more reproducible than those of regular microarray. A gene expression profile generated with ADGE microarray characterized the drug resistant phenotype, particularly with reference to glutathione, proliferation and kinase pathways. Conclusion ADGE microarray magnified the ratios of differential gene expression in a power function, improved the detection sensitivity and fidelity and reduced the requirement for starting material while maintaining high throughput. ADGE microarray generated a more informative expression pattern than regular microarray.

  5. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Directory of Open Access Journals (Sweden)

    Daniel Vasiliu

    Full Text Available Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED. Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  6. A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size.

    Science.gov (United States)

    Vasiliu, Daniel; Clamons, Samuel; McDonough, Molly; Rabe, Brian; Saha, Margaret

    2015-01-01

    Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED). Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

  7. Microarrays for Universal Detection and Identification of Phytoplasmas

    DEFF Research Database (Denmark)

    Nicolaisen, Mogens; Nyskjold, Henriette; Bertaccini, Assunta

    2013-01-01

    Detection and identification of phytoplasmas is a laborious process often involving nested PCR followed by restriction enzyme analysis and fine-resolution gel electrophoresis. To improve throughput, other methods are needed. Microarray technology offers a generic assay that can potentially detect...

  8. Large scale multiplex PCR improves pathogen detection by DNA microarrays

    Directory of Open Access Journals (Sweden)

    Krönke Martin

    2009-01-01

    Full Text Available Abstract Background Medium density DNA microchips that carry a collection of probes for a broad spectrum of pathogens, have the potential to be powerful tools for simultaneous species identification, detection of virulence factors and antimicrobial resistance determinants. However, their widespread use in microbiological diagnostics is limited by the problem of low pathogen numbers in clinical specimens revealing relatively low amounts of pathogen DNA. Results To increase the detection power of a fluorescence-based prototype-microarray designed to identify pathogenic microorganisms involved in sepsis, we propose a large scale multiplex PCR (LSplex PCR for amplification of several dozens of gene-segments of 9 pathogenic species. This protocol employs a large set of primer pairs, potentially able to amplify 800 different gene segments that correspond to the capture probes spotted on the microarray. The LSplex protocol is shown to selectively amplify only the gene segments corresponding to the specific pathogen present in the analyte. Application of LSplex increases the microarray detection of target templates by a factor of 100 to 1000. Conclusion Our data provide a proof of principle for the improvement of detection of pathogen DNA by microarray hybridization by using LSplex PCR.

  9. Thermodynamics of competitive surface adsorption on DNA microarrays

    International Nuclear Information System (INIS)

    Gene microarrays provide a powerful functional genomics technology which permits the expression profiling of tens of thousands of genes in parallel. The basic idea of their functioning is based on the sequence specificity of probe-target interactions combined with fluorescence detection. In reality, this straightforward principle is opposed by the complexity of the experimental system due to imperfections of chip fabrication and RNA preparation, due to the non-linearity of the probe response and especially due to competitive interactions which are inherently connected with the high throughput character of the method. We theoretically analysed aspects of the hybridization of DNA oligonucleotide probes with a complex multicomponent mixture of RNA fragments, such as the effect of different interactions between nucleotide strands competing with the formation of specific duplexes, electrostatic and entropic blocking, the fragmentation of the RNA, the incomplete synthesis of the probes and 'zipping' effects in the oligonucleotide duplexes. The effective hybridization affinities of microarray probes are considerably smaller than those for bulk hybridization owing to the effects discussed, but they correlate well with the bulk data on a relative scale. In general, the hybridization isotherms of microarray probes are shown to deviate from a Langmuir-type behaviour. Nevertheless isotherms of the Langmuir or Sips type are predicted to provide a relatively simple description of the non-linear, probe-specific concentration dependence of the signal intensity of microarray probes

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

    Science.gov (United States)

    von Götz, Franz

    2010-03-01

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

  11. Storing, linking, and mining microarray databases using SRS.

    NARCIS (Netherlands)

    A. Veldhoven (Antoine); D. de Lange (Don); M. Smid (Marcel); V. de Jager (Victor); J.A. Kors (Jan); G.W. Jenster (Guido)

    2005-01-01

    textabstractBACKGROUND: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray

  12. Microarray-based RNA profiling of breast cancer

    DEFF Research Database (Denmark)

    Larsen, Martin J; Thomassen, Mads; Tan, Qihua;

    2014-01-01

    analyzed the same 234 breast cancers on two different microarray platforms. One dataset contained known batch-effects associated with the fabrication procedure used. The aim was to assess the significance of correcting for systematic batch-effects when integrating data from different platforms. We here...

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

    Science.gov (United States)

    Peters, Greg B; Pertile, Mark D

    2014-01-01

    DNA-based Chromosome MicroArrays (CMAs) are now well established as diagnostic tools in clinical genetics laboratories. Over the last decade, the primary application of CMAs has been the genome-wide detection of a particular class of mutation known as copy number variants (CNVs). Since 2010, CMA testing has been recommended as a first-tier test for detection of CNVs associated with intellectual disability, autism spectrum disorders, and/or multiple congenital anomalies…in the post-natal setting. CNVs are now regarded as pathogenic in 14-18 % of patients referred for these (and related) disorders.Through consideration of clinical examples, and several microarray platforms, we attempt to provide an appreciation of microarray diagnostics, from the initial inspection of the microarray data, to the composing of the patient report. In CMA data interpretation, a major challenge comes from the high frequency of clinically irrelevant CNVs observed within "patient" and "normal" populations. As might be predicted, the more common and clinically insignificant CNVs tend to be the smaller ones resolution, and some miscalling of CNVs is unavoidable. In this, there is no ideal solution, but various strategies for handling noise are available. Even without solutions, consideration of these diagnostic problems per se is informative, as they afford critical insights into the biological and technical underpinnings of CNV discovery. These are indispensable to any clinician or scientist practising within the field of genome diagnostics. PMID:24870134

  14. Protein Microarrays for Quantitative Detection of PAI-1 in Serum

    Institute of Scientific and Technical Information of China (English)

    Xu Ma; Qing-yun Zhang

    2012-01-01

    Objective:Plasminogen activator inhibitor-1 (PAl-1),one crucial component of the plasminogen activator system,is a major player in the pathogenesis of many vascular diseases as well as in cancer.High levels of PAI-1 in breast cancer tissue are associated with poor prognosis.The aim of this study is to evaluate rigorously the potential of serum PAl-1 concentration functioning as a general screening test in diagnostic or prognostic assays.Methods:A protein-microarray-based sandwich fluorescence immunoassay (FIA) was developed to detect PAl-1 in serum.Several conditions of this microarray-based FIA were optimized to establish an efficacious method.Serum specimens of 84 healthy women and 285 women with breast cancer were analyzed using the optimized FIA microarray.Results:The median serum PAl-1 level of breast cancer patients was higher than that of healthy women (109.7 ng/ml vs.63.4 ng/ml).Analysis of covariance revealed that PAl-1 levels of the two groups were significantly different (P<0.001) when controlling for an age effect on PAl-1 levels.However,PAl-1 values in TNM stage Ⅰ-Ⅳ patients respectively were not significantly different from each other.Conclusion:This microarray-based sandwich FIA holds potential for quantitative analysis of tumor markers such as PAl-1.

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

    Science.gov (United States)

    Vale, Filipa F

    2016-01-01

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

  16. Application of Microarray technology in research and diagnostics

    DEFF Research Database (Denmark)

    Helweg-Larsen, Rehannah Borup

    The overall purpose of this thesis is to evaluate the use of microarray analysis to investigate the transcriptome of human cancers and human follicular cells and define the correlation between expression of human genes and specific cancer types as well as the developmental competence of the oocyte...

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

    Science.gov (United States)

    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

  18. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    International Nuclear Information System (INIS)

    Protein microarray technology is becoming the method of choice for identifying protein interaction partners, detecting specific proteins, carbohydrates and lipids, or for characterizing protein interactions and serum antibodies in a massively parallel manner. Availability of the well-established instrumentation of DNA arrays and development of new fluorescent detection instruments promoted the spread of this technique. Fluorescent detection has the advantage of high sensitivity, specificity, simplicity and wide dynamic range required by most measurements. Fluorescence through specifically designed probes and an increasing variety of detection modes offers an excellent tool for such microarray platforms. Measuring for example the level of antibodies, their isotypes and/or antigen specificity simultaneously can offer more complex and comprehensive information about the investigated biological phenomenon, especially if we take into consideration that hundreds of samples can be measured in a single assay. Not only body fluids, but also cell lysates, extracted cellular components, and intact living cells can be analyzed on protein arrays for monitoring functional responses to printed samples on the surface. As a rapidly evolving area, protein microarray technology offers a great bulk of information and new depth of knowledge. These are the features that endow protein arrays with wide applicability and robust sample analyzing capability. On the whole, protein arrays are emerging new tools not just in proteomics, but glycomics, lipidomics, and are also important for immunological research. In this review we attempt to summarize the technical aspects of planar fluorescent microarray technology along with the description of its main immunological applications. (topical review)

  19. Electrostatic readout of DNA microarrays with charged microspheres

    Energy Technology Data Exchange (ETDEWEB)

    Clack, Nathan G. [Univ. of California, Berkeley, CA (United States). Biophysics Graduate Group; Salaita, Khalid [Univ. of California, Berkeley, CA (United States). Department of Chemistry; Groves, Jay T. [Univ. of California, Berkeley, CA (United States). Biophysics Graduate Group and Department of Chemistry

    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.

  20. Differentiating pancreatic lesions by Microarray and QPCR analysis of pancreatic juice RNAs

    NARCIS (Netherlands)

    C.D. Rogers; N. Fukushima; N. Sato; C. Shi; N. Prasad; S.R. Hustinx; H. Matsubayashi; M. Canto; J.R. Eshleman; R.H. Hruban; M. Goggins

    2006-01-01

    Background: The gene expression profile of pancreatic cancer is significantly different from that of normal pancreas. Differences in gene expression are detectable using microarrays, but microarrays have traditionally been applied to pancreatic cancer tissue obtained from surgical resection. We hypo

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

    Science.gov (United States)

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

  2. Collective Functionality through Bacterial Individuality

    Science.gov (United States)

    Ackermann, Martin

    According to the conventional view, the properties of an organism are a product of nature and nurture - of its genes and the environment it lives in. Recent experiments with unicellular organisms have challenged this view: several molecular mechanisms generate phenotypic variation independently of environmental signals, leading to variation in clonal groups. My presentation will focus on the causes and consequences of this microbial individuality. Using examples from bacterial genetic model systems, I will first discuss different molecular and cellular mechanisms that give rise to bacterial individuality. Then, I will discuss the consequences of individuality, and focus on how phenotypic variation in clonal populations of bacteria can promote interactions between individuals, lead to the division of labor, and allow clonal groups of bacteria to cope with environmental uncertainty. Variation between individuals thus provides clonal groups with collective functionality.

  3. Seeded Bayesian Networks: Constructing genetic networks from microarray data

    Directory of Open Access Journals (Sweden)

    Quackenbush John

    2008-07-01

    Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

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

    Directory of Open Access Journals (Sweden)

    Jens Twellmeyer

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

  5. Development of an oligonucleotide microarray for the detection and monitoring of marine dinoflagellates.

    Science.gov (United States)

    Galluzzi, Luca; Cegna, Alessandra; Casabianca, Silvia; Penna, Antonella; Saunders, Nick; Magnani, Mauro

    2011-02-01

    Harmful Algal Blooms (HABs), mainly caused by dinoflagellates and diatoms, have great economic and sanitary implications. An important contribution for the comprehension of HAB phenomena and for the identification of risks related to toxic algal species is given by the monitoring programs. In the microscopy-based monitoring methods, harmful species are distinguished through their morphological characteristics. This can be time consuming and requires great taxonomic expertise due to the existence of morphologically close-related species. The high throughput, automation possibility and specificity of microarray-based detection assay, makes this technology very promising for qualitative detection of HAB species. In this study, an oligonucleotide microarray targeted to the ITS1-5.8S-ITS2 rDNA region of nine toxic dinoflagellate species/clades was designed and evaluated. Two probes (45-47 nucleotides in length) were designed for each species/clade to reduce the potential for false positives. The specificity and sensitivity of the probes were evaluated with ITS1-5.8S-ITS2 PCR amplicons obtained from 20 dinoflagellates cultured strains. Cross hybridization experiments confirmed the probe specificity; moreover, the assay showed a good sensitivity, allowing the detection of up to 2 ng of labeled PCR product. The applicability of the assay with field samples was demonstrated using net concentrated seawater samples, un-spiked or spiked with known amounts of cultured cells. Despite the general application of microarray technology for harmful algae detection is not new, a peculiar group of target species/clades has been included in this new-format assay. Moreover, novelties regarding mainly the probes and the target rDNA region have allowed sensitivity improvements in comparison to previously published studies. PMID:21138747

  6. Investigating the effect of paralogs on microarray gene-set analysis

    LENUS (Irish Health Repository)

    Faure, Andre J

    2011-01-24

    Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.

  7. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. PMID:25880524

  8. High performance protein microarrays based on glycidyl methacrylate-modified polyethylene terephthalate plastic substrate.

    Science.gov (United States)

    Liu, Yingshuai; Li, Chang Ming; Hu, Weihua; Lu, Zhisong

    2009-01-15

    There is a great challenge to immobilize high density of probe molecules for high performance protein microarrays, and this is achieved in this work by using polyethylene terephthalate (PET) plastic substrate onto which glycidyl methacrylate (GMA) photopolymer is grafted under mild conditions to introduce high density of epoxy groups for covalent immobilization of proteins. The poly(GMA)-grafted PET (PGMA-PET) surface was characterized with atomic force microscope (AFM) and attenuated total reflectance Fourier transform infra-red (ATR-FTIR) spectroscopy. For high density of protein immobilization and good quality of microspots, experiments were conducted to optimize the printing buffer, and an optimal buffer was found out to be PBS with 10% glycerol+0.003% triton X-100. According to the studies of loading capacity and immobilization kinetics, the optimal protein probe concentration and incubation time for the efficient immobilization are 200 microg mL(-1) and 8h, respectively. The performance of the PGMA-PET-based protein microarrays is evaluated with sandwich immunoassay using rat IgG and anti-rat IgG as model proteins, demonstrating a limit of detection (LOD) of 10 pg mL(-1) and a dynamic range of five orders of magnitude which are better than or very comparable with the reported or commercially available immunoassays, while providing a high-throughput approach. The work renders a simple and economic method to manufacture high performance protein microarrays and is expected to have great potentials in broad applications related to clinic diagnosis, drug discovery and proteomic research. PMID:19064107

  9. Taguchi design-based optimization of sandwich immunoassay microarrays for detecting breast cancer biomarkers.

    Science.gov (United States)

    Luo, Wen; Pla-Roca, Mateu; Juncker, David

    2011-07-15

    Taguchi design, a statistics-based design of experiment method, is widely used for optimization of products and complex production processes in many different industries. However, its use for antibody microarray optimization has remained underappreciated. Here, we provide a brief explanation of Taguchi design and present its use for the optimization of antibody sandwich immunoassay microarray with five breast cancer biomarkers: CA15-3, CEA, HER2, MMP9, and uPA. Two successive optimization rounds with each 16 experimental trials were performed. We tested three factors (capture antibody, detection antibody, and analyte) at four different levels (concentrations) in the first round and seven factors (including buffer solution, streptavidin-Cy5 dye conjugate concentration, and incubation times for five assay steps) with two levels each in the second round; five two-factor interactions between selected pairs of factors were also tested. The optimal levels for each factor as measured by net assay signal increase were determined graphically, and the significance of each factor was analyzed statistically. The concentration of capture antibody, streptavidin-Cy5, and buffer composition were identified as the most significant factors for all assays; analyte incubation time and detection antibody concentration were significant only for MMP9 and CA15-3, respectively. Interactions between pairs of factors were identified, but were less influential compared with single factor effects. After Taguchi optimization, the assay sensitivity was improved between 7 and 68 times, depending on the analyte, reaching 640 fg/mL for uPA, and the maximal signal intensity increased between 1.8 and 3 times. These results suggest that Taguchi design is an efficient and useful approach for the rapid optimization of antibody microarrays.

  10. A flexible whole-genome microarray for transcriptomics in three-spine stickleback (Gasterosteus aculeatus

    Directory of Open Access Journals (Sweden)

    Primmer Craig R

    2009-09-01

    Full Text Available Abstract Background The use of microarray technology for describing changes in mRNA expression to address ecological and evolutionary questions is becoming increasingly popular. Since three-spine stickleback are an important ecological and evolutionary model-species as well as an emerging model for eco-toxicology, the ability to have a functional and flexible microarray platform for transcriptome studies will greatly enhance the research potential in these areas. Results We designed 43,392 unique oligonucleotide probes representing 19,274 genes (93% of the estimated total gene number, and tested the hybridization performance of both DNA and RNA from different populations to determine the efficacy of probe design for transcriptome analysis using the Agilent array platform. The majority of probes were functional as evidenced by the DNA hybridization success, and 30,946 probes (14,615 genes had a signal that was significantly above background for RNA isolated from liver tissue. Genes identified as being expressed in liver tissue were grouped into functional categories for each of the three Gene Ontology groups: biological process, molecular function, and cellular component. As expected, the highest proportions of functional categories belonged to those associated with metabolic functions: metabolic process, binding, catabolism, and organelles. Conclusion The probe and microarray design presented here provides an important step facilitating transcriptomics research for this important research organism by providing a set of over 43,000 probes whose hybridization success and specificity to liver expression has been demonstrated. Probes can easily be added or removed from the current design to tailor the array to specific experiments and additional flexibility lies in the ability to perform either one-color or two-color hybridizations.

  11. Improving PLS-RFE based gene selection for microarray data classification.

    Science.gov (United States)

    Wang, Aiguo; An, Ning; Chen, Guilin; Li, Lian; Alterovitz, Gil

    2015-07-01

    Gene selection plays a crucial role in constructing efficient classifiers for microarray data classification, since microarray data is characterized by high dimensionality and small sample sizes and contains irrelevant and redundant genes. In practical use, partial least squares-based gene selection approaches can obtain gene subsets of good qualities, but are considerably time-consuming. In this paper, we propose to integrate partial least squares based recursive feature elimination (PLS-RFE) with two feature elimination schemes: simulated annealing and square root, respectively, to speed up the feature selection process. Inspired from the strategy of annealing schedule, the two proposed approaches eliminate a number of features rather than one least informative feature during each iteration and the number of removed features decreases as the iteration proceeds. To verify the effectiveness and efficiency of the proposed approaches, we perform extensive experiments on six publicly available microarray data with three typical classifiers, including Naïve Bayes, K-Nearest-Neighbor and Support Vector Machine, and compare our approaches with ReliefF, PLS and PLS-RFE feature selectors in terms of classification accuracy and running time. Experimental results demonstrate that the two proposed approaches accelerate the feature selection process impressively without degrading the classification accuracy and obtain more compact feature subsets for both two-category and multi-category problems. Further experimental comparisons in feature subset consistency show that the proposed approach with simulated annealing scheme not only has better time performance, but also obtains slightly better feature subset consistency than the one with square root scheme. PMID:25912984

  12. Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures.

    Science.gov (United States)

    O'Donnell, Brian; Maurer, Alexander; Papandreou-Suppappola, Antonia; Stafford, Phillip

    2015-01-01

    One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the body's immune system to detect and amplify tumor-specific signals may enable detection of cancer using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides in a microarray format, we chose to synthesize only 330,000 peptides on a single immunosignature microarray. The 330,000 random-sequence peptides on the microarray represent 83% of all tetramers and 27% of all pentamers, creating an unbiased but substantial gap in the coverage of total sequence space. We therefore chose to examine many relatively short motifs from these random-sequence peptides. Time-variant analysis of recurrent subsequences provided a means to dissect amino acid sequences from the peptides while simultaneously retaining the antibody-peptide binding intensities. We first used a simple experiment in which monoclonal antibodies with known linear epitopes were exposed to these random-sequence peptides, and their binding intensities were used to create our algorithm. We then demonstrated the performance of the proposed algorithm by examining immunosignatures from patients with Glioblastoma multiformae (GBM), an aggressive form of brain cancer. Eight different frameshift targets were identified from the random-sequence peptides using this technique. If immune-reactive antigens can be identified using a relatively simple immune assay, it might enable a diagnostic test with sufficient sensitivity to detect tumors in a

  13. Direct, Specific and Rapid Detection of Staphylococcal Proteins and Exotoxins Using a Multiplex Antibody Microarray.

    Directory of Open Access Journals (Sweden)

    Bettina Stieber

    Full Text Available S. aureus is a pathogen in humans and animals that harbors a wide variety of virulence factors and resistance genes. This bacterium can cause a wide range of mild to life-threatening diseases. In the latter case, fast diagnostic procedures are important. In routine diagnostic laboratories, several genotypic and phenotypic methods are available to identify S. aureus strains and determine their resistances. However, there is a demand for multiplex routine diagnostic tests to directly detect staphylococcal toxins and proteins.In this study, an antibody microarray based assay was established and validated for the rapid detection of staphylococcal markers and exotoxins. The following targets were included: staphylococcal protein A, penicillin binding protein 2a, alpha- and beta-hemolysins, Panton Valentine leukocidin, toxic shock syndrome toxin, enterotoxins A and B as well as staphylokinase. All were detected simultaneously within a single experiment, starting from a clonal culture on standard media. The detection of bound proteins was performed using a new fluorescence reading device for microarrays.110 reference strains and clinical isolates were analyzed using this assay, with a DNA microarray for genotypic characterization performed in parallel. The results showed a general high concordance of genotypic and phenotypic data. However, genotypic analysis found the hla gene present in all S. aureus isolates but its expression under given conditions depended on the clonal complex affiliation of the actual isolate.The multiplex antibody assay described herein allowed a rapid and reliable detection of clinically relevant staphylococcal toxins as well as resistance- and species-specific markers.

  14. Vimentin in Bacterial Infections

    Directory of Open Access Journals (Sweden)

    Tim N. Mak

    2016-04-01

    Full Text Available Despite well-studied bacterial strategies to target actin to subvert the host cell cytoskeleton, thus promoting bacterial survival, replication, and dissemination, relatively little is known about the bacterial interaction with other components of the host cell cytoskeleton, including intermediate filaments (IFs. IFs have not only roles in maintaining the structural integrity of the cell, but they are also involved in many cellular processes including cell adhesion, immune signaling, and autophagy, processes that are important in the context of bacterial infections. Here, we summarize the knowledge about the role of IFs in bacterial infections, focusing on the type III IF protein vimentin. Recent studies have revealed the involvement of vimentin in host cell defenses, acting as ligand for several pattern recognition receptors of the innate immune system. Two main aspects of bacteria-vimentin interactions are presented in this review: the role of vimentin in pathogen-binding on the cell surface and subsequent bacterial invasion and the interaction of cytosolic vimentin and intracellular pathogens with regards to innate immune signaling. Mechanistic insight is presented involving distinct bacterial virulence factors that target vimentin to subvert its function in order to change the host cell fate in the course of a bacterial infection.

  15. Inter-Platform comparability of microarrays in acute lymphoblastic leukemia

    Directory of Open Access Journals (Sweden)

    Mintz Michelle

    2004-09-01

    for prognostic variables. We have also been able to validate the gene predictors with high accuracy using an independent dataset generated on cDNA arrays. Conclusion Interarray comparisons such as this one will further enhance the ability to integrate data from several generations of microarray experiments and will help to break down barriers to the assimilation of existing datasets into a comprehensive data pool.

  16. Bacterial profiles of saliva in relation to diet, lifestyle factors, and socioeconomic status

    Directory of Open Access Journals (Sweden)

    Daniel Belstrøm

    2014-04-01

    Full Text Available Background and objective: The bacterial profile of saliva is composed of bacteria from different oral surfaces. The objective of this study was to determine whether different diet intake, lifestyle, or socioeconomic status is associated with characteristic bacterial saliva profiles. Design: Stimulated saliva samples from 292 participants with low levels of dental caries and periodontitis, enrolled in the Danish Health Examination Survey (DANHES, were analyzed for the presence of approximately 300 bacterial species by means of the Human Oral Microbe Identification Microarray (HOMIM. Using presence and levels (mean HOMIM-value of bacterial probes as endpoints, the influence of diet intake, lifestyle, and socioeconomic status on the bacterial saliva profile was analyzed by Mann–Whitney tests with Benjamini–Hochberg's correction for multiple comparisons and principal component analysis. Results: Targets for 131 different probes were identified in 292 samples, with Streptococcus and Veillonella being the most predominant genera identified. Two bacterial taxa (Streptococcus sobrinus and Eubacterium [11][G-3] brachy were more associated with smokers than non-smokers (adjusted p-value<0.01. Stratification of the group based on extreme ends of the parameters age, gender, alcohol consumption, body mass index (BMI, and diet intake had no statistical influence on the composition of the bacterial profile of saliva. Conversely, differences in socioeconomic status were reflected by the bacterial profiles of saliva. Conclusions: The bacterial profile of saliva seems independent of diet intake, but influenced by smoking and maybe socioeconomic status.

  17. Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells

    Directory of Open Access Journals (Sweden)

    Ahmed Sharlin

    2004-07-01

    Full Text Available Abstract Background cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accurately due to "noise" from random and systematic errors. While experimental designs and statistical analysis methods have been proposed to reduce these errors, few studies have tested their accuracy and ability to identify small, but biologically important, changes. Here, we have compared two cDNA microarray experimental design methods with northern blot confirmation to reveal changes in gene expression that could contribute to the early antiproliferative effects of neuregulin on MCF10AT human breast epithelial cells. Results We performed parallel experiments on identical samples using a dye-swap design with ANOVA and an experimental design that excludes systematic biases by "correcting" experimental/control hybridization ratios with control/control hybridizations on a spot-by-spot basis. We refer to this approach as the "control correction method" (CCM. Using replicate arrays, we identified a decrease in proliferation genes and an increase in differentiation genes. Using an arbitrary cut-off of 1.7-fold and p values Conclusions We validated two experimental design paradigms for cDNA microarray experiments capable of detecting small (

  18. DNA Microarrays in the Undergraduate Microbiology Lab: Experimentation and Handling Large Datasets in as Few as Six Weeks

    Directory of Open Access Journals (Sweden)

    David B. Kushner

    2009-12-01

    Full Text Available DNA microarrays have significantly impacted the study of gene expression on a genome-wide level but also have forced a more global consideration of research questions. As such, it has become critical to introduce undergraduate students to genomics approaches to research. A challenge with performing a DNA microarray experiment in the teaching lab is determining the time required for the study and how to handle the voluminous data generated. At an unexpectedly low cost, a 6-week, project-based lab module has been developed that provides 3 weeks for wet lab (hands-on work with the DNA microarrays and 3 weeks for dry lab (analyzing data, using databases to help with data analysis, and considering the meaning of data within the large dataset. Options exist for extending the number of weeks dedicated to the project, but 6 weeks is sufficient for providing an introduction to both experimental genomics and data analysis. Students indicate that being able to both perform array experiments and thoroughly analyze data enriches their understanding of genomics and the complexity of biological systems.

  19. Firmicutes dominate the bacterial taxa within sugar-cane processing plants

    OpenAIRE

    Farhana Sharmin; Steve Wakelin; Flavia Huygens; Megan Hargreaves

    2013-01-01

    Sugar cane processing sites are characterised by high sugar/hemicellulose levels, available moisture and warm conditions, and are relatively unexplored unique microbial environments. The PhyloChip microarray was used to investigate bacterial diversity and community composition in three Australian sugar cane processing plants. These ecosystems were highly complex and dominated by four main Phyla, Firmicutes (the most dominant), followed by Proteobacteria, Bacteroidetes, and Chloroflexi. Signif...

  20. Key informants' perspectives of implementing chromosomal microarrays into clinical practice in Australia.

    Science.gov (United States)

    Turbitt, Erin; Halliday, Jane L; Metcalfe, Sylvia A

    2013-08-01

    High-resolution genomic tests have the potential to revolutionize healthcare by vastly improving mutation detection. The use of chromosomal microarray (CMA) represents one of the earliest examples of these new genomic tests being introduced and disseminated in the clinic. While CMA has clear advantages over traditional karyotyping in terms of mutation detection, little research has investigated the process by which CMA was implemented in clinical settings. Fifteen key informants, six clinicians, and nine laboratory scientists from four Australian states were interviewed about their experiences during and in the time since CMA was adopted for clinical use. Participants discussed challenges such as result interpretation and communication. Strengths were also highlighted, including the collaborative approaches of some centers. Clinical experiences and opinions can inform larger studies with a range of stakeholders, including patients. The historical perspectives from this retrospective study can be helpful in guiding the implementation of future genomic technologies such as whole exome/genome sequencing.

  1. Microarray applications to understand the impact of exposure to environmental contaminants in wild dolphins (Tursiops truncatus).

    Science.gov (United States)

    Mancia, Annalaura; Abelli, Luigi; Kucklick, John R; Rowles, Teresa K; Wells, Randall S; Balmer, Brian C; Hohn, Aleta A; Baatz, John E; Ryan, James C

    2015-02-01

    It is increasingly common to monitor the marine environment and establish geographic trends of environmental contamination by measuring contaminant levels in animals from higher trophic levels. The health of an ecosystem is largely reflected in the health of its inhabitants. As an apex predator, the common bottlenose dolphin (Tursiops truncatus) can reflect the health of near shore marine ecosystems, and reflect coastal threats that pose risk to human health, such as legacy contaminants or marine toxins, e.g. polychlorinated biphenyls (PCBs) and brevetoxins. Major advances in the understanding of dolphin biology and the unique adaptations of these animals in response to the marine environment are being made as a result of the development of cell-lines for use in in vitro experiments, the production of monoclonal antibodies to recognize dolphin proteins, the development of dolphin DNA microarrays to measure global gene expression and the sequencing of the dolphin genome. These advances may play a central role in understanding the complex and specialized biology of the dolphin with regard to how this species responds to an array of environmental insults. This work presents the creation, characterization and application of a new molecular tool to better understand the complex and unique biology of the common bottlenose dolphin and its response to environmental stress and infection. A dolphin oligo microarray representing 24,418 unigene sequences was developed and used to analyze blood samples collected from 69 dolphins during capture-release health assessments at five geographic locations (Beaufort, NC, Sarasota Bay, FL, Saint Joseph Bay, FL, Sapelo Island, GA and Brunswick, GA). The microarray was validated and tested for its ability to: 1) distinguish male from female dolphins; 2) differentiate dolphins inhabiting different geographic locations (Atlantic coasts vs the Gulf of Mexico); and 3) study in detail dolphins resident in one site, the Georgia coast, known to

  2. Microarray applications to understand the impact of exposure to environmental contaminants in wild dolphins (Tursiops truncatus).

    Science.gov (United States)

    Mancia, Annalaura; Abelli, Luigi; Kucklick, John R; Rowles, Teresa K; Wells, Randall S; Balmer, Brian C; Hohn, Aleta A; Baatz, John E; Ryan, James C

    2015-02-01

    It is increasingly common to monitor the marine environment and establish geographic trends of environmental contamination by measuring contaminant levels in animals from higher trophic levels. The health of an ecosystem is largely reflected in the health of its inhabitants. As an apex predator, the common bottlenose dolphin (Tursiops truncatus) can reflect the health of near shore marine ecosystems, and reflect coastal threats that pose risk to human health, such as legacy contaminants or marine toxins, e.g. polychlorinated biphenyls (PCBs) and brevetoxins. Major advances in the understanding of dolphin biology and the unique adaptations of these animals in response to the marine environment are being made as a result of the development of cell-lines for use in in vitro experiments, the production of monoclonal antibodies to recognize dolphin proteins, the development of dolphin DNA microarrays to measure global gene expression and the sequencing of the dolphin genome. These advances may play a central role in understanding the complex and specialized biology of the dolphin with regard to how this species responds to an array of environmental insults. This work presents the creation, characterization and application of a new molecular tool to better understand the complex and unique biology of the common bottlenose dolphin and its response to environmental stress and infection. A dolphin oligo microarray representing 24,418 unigene sequences was developed and used to analyze blood samples collected from 69 dolphins during capture-release health assessments at five geographic locations (Beaufort, NC, Sarasota Bay, FL, Saint Joseph Bay, FL, Sapelo Island, GA and Brunswick, GA). The microarray was validated and tested for its ability to: 1) distinguish male from female dolphins; 2) differentiate dolphins inhabiting different geographic locations (Atlantic coasts vs the Gulf of Mexico); and 3) study in detail dolphins resident in one site, the Georgia coast, known to

  3. Functional protein microarray as molecular decathlete: a versatile player in clinical proteomics.

    Science.gov (United States)

    Zhu, Heng; Cox, Eric; Qian, Jiang

    2012-12-01

    Functional protein microarrays were developed as a high-throughput tool to overcome the limitations of DNA microarrays and to provide a versatile platform for protein functional analyses. Recent years have witnessed tremendous growth in the use of protein microarrays, particularly functional protein microarrays, to address important questions in the field of clinical proteomics. In this review, we will summarize some of the most innovative and exciting recent applications of protein microarrays in clinical proteomics, including biomarker identification, pathogen-host interactions, and cancer biology. PMID:23027439

  4. Differences in bacterial saliva profile between periodontitis patients and a control cohort

    DEFF Research Database (Denmark)

    Belstrøm, Daniel; Fiehn, Nils-Erik; Nielsen, Claus H;

    2014-01-01

    the bacterial profile of saliva from subjects with chronic periodontitis with that of saliva from a control cohort. MATERIALS AND METHODS: Stimulated saliva samples from 139 chronic periodontitis patients and 447 samples from a control cohort were analysed using the Human Oral Microbe Identification Microarray...... in samples from periodontitis patients than in samples from the control cohort. These differences were independent of the individuals' smoking status. CONCLUSIONS: Periodontitis is associated with a characteristic bacterial profile of saliva different from that of a control cohort....

  5. MAID : An effect size based model for microarray data integration across laboratories and platforms

    Directory of Open Access Journals (Sweden)

    Edwards Aled M

    2008-07-01

    Full Text Available Abstract Background Gene expression profiling has the potential to unravel molecular mechanisms behind gene regulation and identify gene targets for therapeutic interventions. As microarray technology matures, the number of microarray studies has increased, resulting in many different datasets available for any given disease. The increase in sensitivity and reliability of measurements of gene expression changes can be improved through a systematic integration of different microarray datasets that address the same or similar biological questions. Results Traditional effect size models can not be used to integrate array data that directly compare treatment to control samples expressed as log ratios of gene expressions. Here we extend the traditional effect size model to integrate as many array datasets as possible. The extended effect size model (MAID can integrate any array datatype generated with either single or two channel arrays using either direct or indirect designs across different laboratories and platforms. The model uses two standardized indices, the standard effect size score for experiments with two groups of data, and a new standardized index that measures the difference in gene expression between treatment and control groups for one sample data with replicate arrays. The statistical significance of treatment effect across studies for each gene is determined by appropriate permutation methods depending on the type of data integrated. We apply our method to three different expression datasets from two different laboratories generated using three different array platforms and two different experimental designs. Our results indicate that the proposed integration model produces an increase in statistical power for identifying differentially expressed genes when integrating data across experiments and when compared to other integration models. We also show that genes found to be significant using our data integration method are of direct

  6. An alternative method to amplify RNA without loss of signal conservation for expression analysis with a proteinase DNA microarray in the ArrayTube® format

    Directory of Open Access Journals (Sweden)

    Wiederanders B

    2006-06-01

    RNA starts from as little as 100 ng total RNA, it presents an alternative method for detecting even low expressed genes by microarray experiments in a highly reproducible and sensitive manner. Preservation of signal integrity is demonstrated out by QRT-PCR measurements. The little amounts of total RNA necessary for the analyses make this method applicable for investigations with limited material as in clinical samples from, for example, organ or tumour biopsies. Those are arguments in favour of the high potential of our assay compared to established procedures for amplification within the field of diagnostic expression profiling. Nevertheless, the screening character of microarray data must be mentioned, and independent methods should verify the results.

  7. Analysis of factorial time-course microarrays with application to a clinical study of burn injury

    Science.gov (United States)

    Zhou, Baiyu; Xu, Weihong; Herndon, David; Tompkins, Ronald; Davis, Ronald; Xiao, Wenzhong; Wong, Wing Hung; Toner, Mehmet; Warren, H. Shaw; Schoenfeld, David A.; Rahme, Laurence; McDonald-Smith, Grace P.; Hayden, Douglas; Mason, Philip; Fagan, Shawn; Yu, Yong-Ming; Cobb, J. Perren; Remick, Daniel G.; Mannick, John A.; Lederer, James A.; Gamelli, Richard L.; Silver, Geoffrey M.; West, Michael A.; Shapiro, Michael B.; Smith, Richard; Camp, David G.; Qian, Weijun; Storey, John; Mindrinos, Michael; Tibshirani, Rob; Lowry, Stephen; Calvano, Steven; Chaudry, Irshad; West, Michael A.; Cohen, Mitchell; Moore, Ernest E.; Johnson, Jeffrey; Moldawer, Lyle L.; Baker, Henry V.; Efron, Philip A.; Balis, Ulysses G.J.; Billiar, Timothy R.; Ochoa, Juan B.; Sperry, Jason L.; Miller-Graziano, Carol L.; De, Asit K.; Bankey, Paul E.; Finnerty, Celeste C.; Jeschke, Marc G.; Minei, Joseph P.; Arnoldo, Brett D.; Hunt, John L.; Horton, Jureta; Cobb, J. Perren; Brownstein, Bernard; Freeman, Bradley; Maier, Ronald V.; Nathens, Avery B.; Cuschieri, Joseph; Gibran, Nicole; Klein, Matthew; O’Keefe, Grant

    2010-01-01

    Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body’s response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package “TANOVA” and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/. PMID:20479259

  8. Analysis of ripening-related gene expression in papaya using an Arabidopsis-based microarray

    Directory of Open Access Journals (Sweden)

    Fabi João Paulo

    2012-12-01

    Full Text Available Abstract Background Papaya (Carica papaya L. is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.

  9. Monitoring microarray-based gene expression profile changes in hepatocellular carcinoma

    Institute of Scientific and Technical Information of China (English)

    Hong-Ju Mao; Hong-Nian Li; Xiao-Mei Zhou; Jian-Long Zhao; Da-Fang Wan

    2005-01-01

    AIM: To find out key genes responsible for hepatocarc inogenesis and to further understand the underlying molecular mechanism through investigating the differential gene expression between human normal liver tissue and hepatocellular carcinoma (HCC).METHODS: DNA microarray was prepared by spotting PCR products of 1 000 human genes including 445 novel genes, 540 known genes as well as 12 positive (housekeeping) and 3 negative controls (plant gene) onto treated glass slides. cDNA probes were prepared by labeling normal liver tissue mRNA and cancer liver tissue mRNA with Cy3-dUTP and Cy5-dUTP separately through reverse transcription. The arrays were hybridized against the cDNA probe and the fluorescent signals were scanned. The dataobtained from repeated experiments were analyzed. RESULTS: Among the 20 couple samples investigated (from cancerous liver tissue and normal liver tissue), 38 genes including 21 novel genes and 17 known genes exhibited different expressions. CONCLUSION: cDNA microarray technique is powerful to identify candidate target genes that may play important roles in human carcinogenesis. Further analysis of the obtained genes is helpful to understand the molecular changes in HCC progression and ultimately may lead to the identification of new targets for HCC diagnosis and intervention.

  10. A universal assay for detection of oncogenic fusion transcripts by oligo microarray analysis

    Directory of Open Access Journals (Sweden)

    Ribeiro Franclim R

    2009-01-01

    Full Text Available Abstract Background The ability to detect neoplasia-specific fusion genes is important not only in cancer research, but also increasingly in clinical settings to ensure that correct diagnosis is made and the optimal treatment is chosen. However, the available methodologies to detect such fusions all have their distinct short-comings. Results We describe a novel oligonucleotide microarray strategy whereby one can screen for all known oncogenic fusion transcripts in a single experiment. To accomplish this, we combine measurements of chimeric transcript junctions with exon-wise measurements of individual fusion partners. To demonstrate the usefulness of the approach, we designed a DNA microarray containing 68,861 oligonucleotide probes that includes oligos covering all combinations of chimeric exon-exon junctions from 275 pairs of fusion genes, as well as sets of oligos internal to all the exons of the fusion partners. Using this array, proof of principle was demonstrated by detection of known fusion genes (such as TCF3:PBX1, ETV6:RUNX1, and TMPRSS2:ERG from all six positive controls consisting of leukemia cell lines and prostate cancer biopsies. Conclusion This new method bears promise of an important complement to currently used diagnostic and research tools for the detection of fusion genes in neoplastic diseases.

  11. Microdissection, mRNA amplification and microarray: a study of pleural mesothelial and malignant mesothelioma cells.

    Science.gov (United States)

    Mohr, Steve; Bottin, Marie-Claire; Lannes, Béatrice; Neuville, Agnès; Bellocq, Jean-Pierre; Keith, Gérard; Rihn, Bertrand Henri

    2004-01-01

    The studies of molecular alterations in tumor cells with microarrays are often hampered by inherent tissue heterogeneity. The emergence of Laser Capture Microdissection (LCM) allowed us to overcome this challenge since it gives selective access to cancer cells that are isolated from their native tissue environment. In this report, we microdissected mesothelial cells and malignant mesothelioma cells of ex vivo resected specimens using LCM. Amplified RNA from mesothelial and mesothelioma microdissected cells allowed us to measure global gene expression with 10 K-microarrays in four independent experiments. We screened 9850 annotated human genes, 1275 of which have satisfied our data analysis requirements. They included 302 overexpressed genes and 160 downregulated genes in mesothelioma microdissected cells as compared to mesothelial microdissected cells. Among them, the expression levels of eight genes, namely BF, FTL, IGFBP7, RARRES1, RARRES2, RBP1, SAT, and TXN according to HUGO nomenclature, were increased, whereas six: ALOX5AP, CLNS1A, EIF4A2, ELK3, REQ and SYPL, were found to be underexpressed in mesothelioma microdissected cells. The ferritin light polypeptide (FTL) gene overexpression was confirmed by real time quantitative PCR. Our approach allowed a comprehensive in situ examination of mesothelioma and provided an accurate way to find new marker genes that may be useful for diagnosis and treatment of malignant pleural mesothelioma. PMID:14987796

  12. The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2004-01-01

    Full Text Available An unsupervised data clustering method, called the local maximum clustering (LMC method, is proposed for identifying clusters in experiment data sets based on research interest. A magnitude property is defined according to research purposes, and data sets are clustered around each local maximum of the magnitude property. By properly defining a magnitude property, this method can overcome many difficulties in microarray data clustering such as reduced projection in similarities, noises, and arbitrary gene distribution. To critically evaluate the performance of this clustering method in comparison with other methods, we designed three model data sets with known cluster distributions and applied the LMC method as well as the hierarchic clustering method, the -mean clustering method, and the self-organized map method to these model data sets. The results show that the LMC method produces the most accurate clustering results. As an example of application, we applied the method to cluster the leukemia samples reported in the microarray study of Golub et al. (1999.

  13. Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

    Science.gov (United States)

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

    2015-10-01

    Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

  14. Intestinal microbiota in healthy U.S. young children and adults--a high throughput microarray analysis.

    Directory of Open Access Journals (Sweden)

    Tamar Ringel-Kulka

    Full Text Available It is generally believed that the infant's microbiota is established during the first 1-2 years of life. However, there is scarce data on its characterization and its comparison to the adult-like microbiota in consecutive years.To characterize and compare the intestinal microbiota in healthy young children (1-4 years and healthy adults from the North Carolina region in the U.S. using high-throughput bacterial phylogenetic microarray analysis.Detailed characterization and comparison of the intestinal microbiota of healthy children aged 1-4 years old (n = 28 and healthy adults of 21-60 years (n = 23 was carried out using the Human Intestinal Tract Chip (HITChip phylogenetic microarray targeting the V1 and V6 regions of 16S rRNA and quantitative PCR.The HITChip microarray data indicate that Actinobacteria, Bacilli, Clostridium cluster IV and Bacteroidetes are the predominant phylum-like groups that exhibit differences between young children and adults. The phylum-like group Clostridium cluster XIVa was equally predominant in young children and adults and is thus considered to be established at an early age. The genus-like level show significant 3.6 fold (higher or lower differences in the abundance of 26 genera between young children and adults. Young U.S. children have a significantly 3.5-fold higher abundance of Bifidobacterium species than the adults from the same location. However, the microbiota of young children is less diverse than that of adults.We show that the establishment of an adult-like intestinal microbiota occurs at a later age than previously reported. Characterizing the microbiota and its development in the early years of life may help identify 'windows of opportunity' for interventional strategies that may promote health and prevent or mitigate disease processes.

  15. Aptamer Affinity Maturation by Resampling and Microarray Selection.

    Science.gov (United States)

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

    2016-07-19

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

  16. Investigating amoebic pathogenesis using Entamoeba histolytica DNA microarrays

    Indian Academy of Sciences (India)

    Upinder Singh; Preetam Shah

    2002-11-01

    Entamoeba histolytica, a protozoan parasite, causes diarrhea and liver abscesses resulting in 50 million cases of infection worldwide annually. Elucidation of parasite virulence determinants has recently been investigated using genetic approaches. We have undertaken a genomics approach to identify novel virulence determinants in the parasite. A DNA microarray of E. histolytica is being developed based on sequenced genomic clones from the genome sequencing efforts of The Institute of Genomic Research (TIGR) and the Sanger Center. Hybridization of the slides with samples labelled differentially using fluorescent dyes allows the characterization of transcriptional profiles of genes under the biological conditions tested. Additionally, a genome-wide comparison of E. histolytica and E. dispar can be undertaken. The development of an E. histolytica microarray will be outlined and its uses in identifying novel virulence determinants and characterizing amoebic biology will be discussed.

  17. MatArray: a Matlab toolbox for microarray data.

    Science.gov (United States)

    Venet, David

    2003-03-22

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

  18. R/BHC: fast Bayesian hierarchical clustering for microarray data

    Directory of Open Access Journals (Sweden)

    Grant Murray

    2009-08-01

    Full Text Available Abstract Background Although the use of clustering methods has rapidly become one of the standard computational approaches in the literature of microarray gene expression data analysis, little attention has been paid to uncertainty in the results obtained. Results We present an R/Bioconductor port of a fast novel algorithm for Bayesian agglomerative hierarchical clustering and demonstrate its use in clustering gene expression microarray data. The method performs bottom-up hierarchical clustering, using a Dirichlet Process (infinite mixture to model uncertainty in the data and Bayesian model selection to decide at each step which clusters to merge. Conclusion Biologically plausible results are presented from a well studied data set: expression profiles of A. thaliana subjected to a variety of biotic and abiotic stresses. Our method avoids several limitations of traditional methods, for example how many clusters there should be and how to choose a principled distance metric.

  19. Nanomedicine, microarrays and their applications in clinical microbiology

    Directory of Open Access Journals (Sweden)

    Özcan Deveci

    2010-12-01

    Full Text Available Growing interest in the future medical applications of nanotechnology is leading to the emergence of a new scientific field that called as “nanomedicine”. Nanomedicine may be defined as the investigating, treating, reconstructing and controlling human biology and health at the molecular level, using engineered nanodevices and nanostructures. Microarray technology is a revolutionary tool for elucidating roles of genes in infectious diseases, shifting from traditional methods of research to integrated approaches. This technology has great potential to provide medical diagnosis, monitor treatment and help in the development of new tools for infectious disease prevention and/or management. The aim of this paper is to provide an overview of the current application of microarray platforms and nanomedicine in the study of experimental microbiology and the impact of this technology in clinical settings.

  20. Enhancing the quality metric of protein microarray image

    Institute of Scientific and Technical Information of China (English)

    王立强; 倪旭翔; 陆祖康; 郑旭峰; 李映笙

    2004-01-01

    The novel method of improving the quality metric of protein microarray image presented in this paper reduces impulse noise by using an adaptive median filter that employs the switching scheme based on local statistics characters; and achieves the impulse detection by using the difference between the standard deviation of the pixels within the filter window and the current pixel of concern. It also uses a top-hat filter to correct the background variation. In order to decrease time consumption, the top-hat filter core is cross structure. The experimental results showed that, for a protein microarray image contaminated by impulse noise and with slow background variation, the new method can significantly increase the signal-to-noise ratio, correct the trends in the background, and enhance the flatness of the background and the consistency of the signal intensity.

  1. Bioinformatics and Microarray Data Analysis on the Cloud.

    Science.gov (United States)

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

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

  2. Classification analysis of microarray data based on ontological engineering

    Institute of Scientific and Technical Information of China (English)

    LI Guo-qi; SHENG Huan-ye

    2007-01-01

    Background knowledge is important for data mining, especially in complicated situation. Ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. Microarray dataset is the output of DNA chip.With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.

  3. Bacterial adhesion to worn silicone hydrogel contact lenses

    OpenAIRE

    Santos, Lívia; Rodrigues, Diana Alexandra Ferreira; Lira, Madalena; Oliveira, M. Elisabete; Oliveira, Rosário; Yebra-Pimentel Vilar, Eva; Azeredo, Joana

    2008-01-01

    Purpose. The aim of this study was to, firstly, investigate whether silicone-hydrogel contact lenses (CL) are more or less susceptible to bacterial adhesion than conventional ones and, secondly, assess the influence of lens wear in the extent of bacterial adhesion. Four silicone-hydrogel CL (galyfilcon A, balafilcon A, lotrafilcon A, and lotrafilcon B) and one conventional hydrogel (etafilcon A) CL were tested. Methods. Bacterial adhesion experiments were performed on unworn and worn CL us...

  4. Interfering with bacterial gossip

    DEFF Research Database (Denmark)

    Bjarnsholt, Thomas; Tolker-Nielsen, Tim; Givskov, Michael

    2011-01-01

    defense. Antibiotics exhibit a rather limited effect on biofilms. Furthermore, antibiotics have an ‘inherent obsolescence’ because they select for development of resistance. Bacterial infections with origin in bacterial biofilms have become a serious threat in developed countries. Pseudomonas aeruginosa...... that appropriately target bacteria in their relevant habitat with the aim of mitigating their destructive impact on patients. In this review we describe molecular mechanisms involved in “bacterial gossip” (more scientifically referred to as quorum sensing (QS) and c-di-GMP signaling), virulence, biofilm formation...

  5. DNA-Microarray-based Genotyping of Clostridium difficile

    OpenAIRE

    Gawlik, Darius; Slickers, Peter; Engelmann, Ines; Müller, Elke; Lück, Christian; Friedrichs, Anette; Ehricht, Ralf; Monecke, Stefan

    2015-01-01

    Background Clostridium difficile can cause antibiotic-associated diarrhea and a possibility of outbreaks in hospital settings warrants molecular typing. A microarray was designed that included toxin genes (tcdA/B, cdtA/B), genes related to antimicrobial resistance, the slpA gene and additional variable genes. Results DNA of six reference strains and 234 clinical isolates from South-Western and Eastern Germany was subjected to linear amplification and labeling with dUTP-linked biotin. Amplicon...

  6. Assessing the Application of Tissue Microarray Technology to Kidney Research

    OpenAIRE

    Zhang, Ming-Zhi; Su, Yinghao; Yao, Bing; Zheng, Wei; deCaestecker, Mark; Harris, Raymond C.

    2010-01-01

    Tissue microarray (TMA) is a new high-throughput method that enables simultaneous analysis of the profiles of protein expression in multiple tissue samples. TMA technology has not previously been adapted for physiological and pathophysiological studies of rodent kidneys. We have evaluated the validity and reliability of using TMA to assess protein expression in mouse and rat kidneys. A representative TMA block that we have produced included: (1) mouse and rat kidney cortex, outer medulla, and...

  7. Portable System for Microbial Sample Preparation and Oligonucleotide Microarray Analysis

    OpenAIRE

    Bavykin, Sergei G.; Akowski, James P.; Zakhariev, Vladimir M.; Barsky, Viktor E.; Perov, Alexander N.; Mirzabekov, Andrei D.

    2001-01-01

    We have developed a three-component system for microbial identification that consists of (i) a universal syringe-operated silica minicolumn for successive DNA and RNA isolation, fractionation, fragmentation, fluorescent labeling, and removal of excess free label and short oligonucleotides; (ii) microarrays of immobilized oligonucleotide probes for 16S rRNA identification; and (iii) a portable battery-powered device for imaging the hybridization of fluorescently labeled RNA fragments with the ...

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

    Directory of Open Access Journals (Sweden)

    Koia Jonni H

    2012-12-01

    Full Text Available Abstract 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

  9. Pattern-driven neighborhood search for biclustering of microarray data

    OpenAIRE

    Ayadi, Wassim; Elloumi, Mourad; Hao, Jin-Kao

    2012-01-01

    Background Biclustering aims at finding subgroups of genes that show highly correlated behaviors across a subgroup of conditions. Biclustering is a very useful tool for mining microarray data and has various practical applications. From a computational point of view, biclustering is a highly combinatorial search problem and can be solved with optimization methods. Results We describe a stochastic pattern-driven neighborhood search algorithm for the biclustering problem. Starting from an initi...

  10. Nanomedicine, microarrays and their applications in clinical microbiology

    OpenAIRE

    Özcan Deveci; Erkan Yula

    2010-01-01

    Growing interest in the future medical applications of nanotechnology is leading to the emergence of a new scientific field that called as “nanomedicine”. Nanomedicine may be defined as the investigating, treating, reconstructing and controlling human biology and health at the molecular level, using engineered nanodevices and nanostructures. Microarray technology is a revolutionary tool for elucidating roles of genes in infectious diseases, shifting from traditional methods of research to int...

  11. Parsimonious selection of useful genes in microarray gene expression data

    OpenAIRE

    González Navarro, Félix Fernando; Belanche Muñoz, Luis Antonio

    2011-01-01

    Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification in microarray gene expression data. These tasks are characterized by a large number of features and a few observations, making the modeling a non-trivial undertaking. In this work we apply entropic filter methods for gene selection, in combination with several off-the-shelf classifiers. The introduction of bootstrap resampling techniques permits the achiev...

  12. Segmentation and intensity estimation for microarray images with saturated pixels

    Directory of Open Access Journals (Sweden)

    Yang Yan

    2011-11-01

    Full Text Available Abstract Background Microarray image analysis processes scanned digital images of hybridized arrays to produce the input spot-level data for downstream analysis, so it can have a potentially large impact on those and subsequent analysis. Signal saturation is an optical effect that occurs when some pixel values for highly expressed genes or peptides exceed the upper detection threshold of the scanner software (216 - 1 = 65, 535 for 16-bit images. In practice, spots with a sizable number of saturated pixels are often flagged and discarded. Alternatively, the saturated values are used without adjustments for estimating spot intensities. The resulting expression data tend to be biased downwards and can distort high-level analysis that relies on these data. Hence, it is crucial to effectively correct for signal saturation. Results We developed a flexible mixture model-based segmentation and spot intensity estimation procedure that accounts for saturated pixels by incorporating a censored component in the mixture model. As demonstrated with biological data and simulation, our method extends the dynamic range of expression data beyond the saturation threshold and is effective in correcting saturation-induced bias when the lost information is not tremendous. We further illustrate the impact of image processing on downstream classification, showing that the proposed method can increase diagnostic accuracy using data from a lymphoma cancer diagnosis study. Conclusions The presented method adjusts for signal saturation at the segmentation stage that identifies a pixel as part of the foreground, background or other. The cluster membership of a pixel can be altered versus treating saturated values as truly observed. Thus, the resulting spot intensity estimates may be more accurate than those obtained from existing methods that correct for saturation based on already segmented data. As a model-based segmentation method, our procedure is able to identify inner

  13. Tissue Microarray A New Tool for Cancer Research

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Shanghai Outdo Biotech Co.Ltd. (Outdo Biotech) is a leading company in human/animal Tissue Microarrays (TMA) and "Clinical-Type" Gene Chip (CTGC) in China. Our shareholders are Shanghai Biochip Co., Ltd. & National Engineering Center for Biochip at Shanghai, Shanghai Cancer institute and Eastern Liver and Bladder Hospital of Second Military Medical University. TMA is a mean of combining tens to hundreds of specimens of tissue, paraffin embedded or frozen, onto a single slide for analysis at once. Our constr...

  14. DNA microarray technique for detecting food-borne pathogens

    Directory of Open Access Journals (Sweden)

    Xing GAO

    2012-08-01

    Full Text Available Objective To study the application of DNA microarray technique for screening and identifying multiple food-borne pathogens. Methods The oligonucleotide probes were designed by Clustal X and Oligo 6.0 at the conserved regions of specific genes of multiple food-borne pathogens, and then were validated by bioinformatic analyses. The 5' end of each probe was modified by amino-group and 10 Poly-T, and the optimized probes were synthesized and spotted on aldehyde-coated slides. The bacteria DNA template incubated with Klenow enzyme was amplified by arbitrarily primed PCR, and PCR products incorporated into Aminoallyl-dUTP were coupled with fluorescent dye. After hybridization of the purified PCR products with DNA microarray, the hybridization image and fluorescence intensity analysis was acquired by ScanArray and GenePix Pro 5.1 software. A series of detection conditions such as arbitrarily primed PCR and microarray hybridization were optimized. The specificity of this approach was evaluated by 16 different bacteria DNA, and the sensitivity and reproducibility were verified by 4 food-borne pathogens DNA. The samples of multiple bacteria DNA and simulated water samples of Shigella dysenteriae were detected. Results Nine different food-borne bacteria were successfully discriminated under the same condition. The sensitivity of genomic DNA was 102 -103pg/ μl, and the coefficient of variation (CV of the reproducibility of assay was less than 15%. The corresponding specific hybridization maps of the multiple bacteria DNA samples were obtained, and the detection limit of simulated water sample of Shigella dysenteriae was 3.54×105cfu/ml. Conclusions The DNA microarray detection system based on arbitrarily primed PCR can be employed for effective detection of multiple food-borne pathogens, and this assay may offer a new method for high-throughput platform for detecting bacteria.

  15. Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Hu Xiaohua

    2011-07-01

    Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

  16. RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. M. Farouk

    2014-09-01

    Full Text Available The complementary DNA (cDNA sequence considered the magic biometric technique for personal identification. Microarray image processing used for the concurrent genes identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN. We have segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarray image resized and used as an input for the proposed artificial neural network. For matching and recognition, we have trained the artificial neural network. Recognition results are given for the galleries of cDNA sequences . The numerical results show that, the proposed matching technique is an effective in the cDNA sequences process. The experimental results of our matching approach using different databases shows that, the proposed technique is an effective matching performance.

  17. Coupled Two-Way Clustering Analysis of Gene Microarray Data

    CERN Document Server

    Getz, G; Domany, E

    2000-01-01

    We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.

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

    Science.gov (United States)

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

    2013-01-01

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

  19. A Glance at DNA Microarray Technology and Applications

    Directory of Open Access Journals (Sweden)

    Amir-Ata Saei

    2011-08-01

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

  20. Application of nanostructured biochips for efficient cell transfection microarrays

    Science.gov (United States)

    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.

  1. Sequencing ebola and marburg viruses genomes using microarrays.

    Science.gov (United States)

    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

  2. Genopal™: a novel hollow fibre array for focused microarray analysis.

    Science.gov (United States)

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

    2010-12-01

    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

  3. Microarray, SAGE and their applications to cardiovascular diseases

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The wealth of DNA data generated by the human genome project coupling with recently invented high-throughput gene expression profiling techniques has dramatically sped up the process for biomedical researchers on elucidating the role of genes in human diseases. One powerful method to reveal insight into gene functions is the systematic analysis of gene expression. Two popular high-throughput gene expression technologies, microarray and Serial Analysis of Gene Expression (SAGE) are capable of producing large amounts of gene expression data with the potential of providing novel insights into fundamental disease processes, especially complex syndromes such as cardiovascular disease, whose etiologies are due to multiple genetic factors and their interplay with the environment. Microarray and SAGE have already been used to examine gene expression patterns of cell-culture, animal and human tissues models of cardiovascular diseases. In this review, we will first give a brief introduction of microarray and SAGE technologies and point out their limitations. We will then discuss the major discoveries and the new biological insightsthat have emerged from their applications to cardiovascular diseases. Finally we will touch upon potential challenges and future developments in this area.

  4. Laser-based patterning for transfected cell microarrays

    Energy Technology Data Exchange (ETDEWEB)

    Hook, Andrew L; Creasey, Rhiannon; Voelcker, Nicolas H [Flinders University, GPO Box 2100, Bedford Park, SA 5042 (Australia); Hayes, Jason P [MiniFAB, 1 Dalmore Drive, Caribbean Park, Scoresby VIC 3179 (Australia); Thissen, Helmut, E-mail: Nico.Voelcker@flinders.edu.a [CSIRO Molecular and Health Technologies, Bayview Avenue, Clayton VIC 3168 (Australia)

    2009-12-15

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

  5. Mulcom: a multiple comparison statistical test for microarray data in Bioconductor

    Directory of Open Access Journals (Sweden)

    Renzulli Tommaso

    2011-09-01

    Full Text Available Abstract Background Many microarray experiments search for genes with differential expression between a common "reference" group and multiple "test" groups. In such cases currently employed statistical approaches based on t-tests or close derivatives have limited efficacy, mainly because estimation of the standard error is done on only two groups at a time. Alternative approaches based on ANOVA correctly capture within-group variance from all the groups, but then do not confront single test groups with the reference. Ideally, a t-test better suited for this type of data would compare each test group with the reference, but use within-group variance calculated from all the groups. Results We implemented an R-Bioconductor package named Mulcom, with a statistical test derived from the Dunnett's t-test, designed to compare multiple test groups individually against a common reference. Interestingly, the Dunnett's test uses for the denominator of each comparison a within-group standard error aggregated from all the experimental groups. In addition to the basic Dunnett's t value, the package includes an optional minimal fold-change threshold, m. Due to the automated, permutation-based estimation of False Discovery Rate (FDR, the package also permits fast optimization of the test, to obtain the maximum number of significant genes at a given FDR value. When applied to a time-course experiment profiled in parallel on two microarray platforms, and compared with two commonly used tests, Mulcom displayed better concordance of significant genes in the two array platforms (39% vs. 26% or 15%, and higher enrichment in functional annotation to categories related to the biology of the experiment (p value Conclusions The Mulcom package provides a powerful tool for the identification of differentially expressed genes when several experimental conditions are compared against a common reference. The results of the practical example presented here show that lists of

  6. Association of targeted multiplex PCR with resequencing microarray for the detection of multiple respiratory pathogens

    Directory of Open Access Journals (Sweden)

    Xuejun eMa

    2015-05-01

    Full Text Available A large number of viral and bacterial organisms are responsible for community-acquired pneumonia (CAP which contributes to substantial burden on health management. A new resequencing microarray (RPM-IVDC1 associated with targeted multiplex PCR was recently developed and validated for multiple respiratory viruses detection and discrimination. In this study, we evaluated the capability of RPM-IVDC1 for simultaneous identification of multiple viral and bacterial organisms. The nasopharyngeal aspirates (NPAs of 110 consecutive CAP patients, aged from 1 month to 96 years old, were collected from 5 distinct general hospitals in Beijing during 1-year period. The samples were subjected to the RPM-IVDC1 established protocol as compared to a real-time PCR (qRT-PCR, which was used as standard. The results of virus detection were consistent with those previously described. A total of 37 of Streptococcus pneumoniae, 14 of Haemophilus influenzae, 10 of Mycoplasma pneumoniae, 2 of Klebsiella pneumoniae and 1 of Moraxella catarrhalis were detected by RPM-IVDC1. The sensitivities and specificities were compared with those of qRT-PCR for S. pneumoniae (100%, 100%, respectively, H. influenzae (92.3%, 97.9%, respectively, M. pneumoniae (69.2%, 99.0%, respectively, K. pneumoniae (100%, 100%, respectively and M. catarrhalis (100%, 100%, respectively. Additional 22 of Streptococcus spp., 24 of Haemophilus spp. and 16 of Neisseria spp. were identified. In addition, methicillin-resistant and carbapenemases allele were also found in 9 of Staphylococcus spp. and 1 of K. pneumoniae, respectively. These results demonstrated the capability of RPM-IVDC1 for simultaneous detection of broad-spectrum respiratory pathogens in complex backgrounds and the advantage of accessing to the actual sequences, showing great potential use of epidemic outbreak investigation. The detection results should be carefully interpreted when introducing this technique in the clinical diagnostics.

  7. Carbon Nanotube Microarrays Grown on Nanoflake Substrates

    Science.gov (United States)

    Schmidt, Howard K.; Hauge, Robert H.; Pint, Cary; Pheasant, Sean

    2013-01-01

    coated on U.S. currency. After deposition, the growth is carried out in a hot-filament chemical vapor deposition apparatus. A tungsten hot filament placed in the flow of H2 at a temperature greater than 1,600 C creates atomic hydrogen, which serves to reduce the Fe catalyst into a metallic state. The catalyst can now precipitate SWNTs in the presence of growth gases. The gases used for the experiments reported are C2H2, H2O, and H2, at rates of 2, 2, and 400 standard cubic centimeters per minute (sccm), respectively. In order to retain the flakes, a cage is constructed by spot welding stainless steel or copper mesh to form an enclosed area, in which the flakes are placed prior to growth. This allows growth gases and atomic hydrogen to reach the flakes, but does not allow the flakes, which rapidly nucleate SWNTs, to escape from the cage.

  8. Bacterial Wound Culture

    Science.gov (United States)

    ... Home Visit Global Sites Search Help? Bacterial Wound Culture Share this page: Was this page helpful? Also known as: Aerobic Wound Culture; Anaerobic Wound Culture Formal name: Culture, wound Related ...

  9. Bacterial surface adaptation

    Science.gov (United States)

    Utada, Andrew

    2014-03-01

    Biofilms are structured multi-cellular communities that are fundamental to the biology and ecology of bacteria. Parasitic bacterial biofilms can cause lethal infections and biofouling, but commensal bacterial biofilms, such as those found in the gut, can break down otherwise indigestible plant polysaccharides and allow us to enjoy vegetables. The first step in biofilm formation, adaptation to life on a surface, requires a working knowledge of low Reynolds number fluid physics, and the coordination of biochemical signaling, polysaccharide production, and molecular motility motors. These crucial early stages of biofilm formation are at present poorly understood. By adapting methods from soft matter physics, we dissect bacterial social behavior at the single cell level for several prototypical bacterial species, including Pseudomonas aeruginosa and Vibrio cholerae.

  10. Bacterial intermediate filaments

    DEFF Research Database (Denmark)

    Charbon, Godefroid; Cabeen, M.; Jacobs-Wagner, C.

    2009-01-01

    Crescentin, which is the founding member of a rapidly growing family of bacterial cytoskeletal proteins, was previously proposed to resemble eukaryotic intermediate filament (IF) proteins based on structural prediction and in vitro polymerization properties. Here, we demonstrate that crescentin...

  11. Bacterial Meningitis in Infants

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2004-04-01

    Full Text Available A retrospective study of 80 infantile patients (ages 30-365 days; 47 male, 33 female with culture-proven bacterial meningitis seen over a 16 year period (1986-2001 is reported from Taiwan.

  12. Hazard characterization and identification of a former ammunition site using microarrays, bioassays, and chemical analysis.

    Science.gov (United States)

    Eisentraeger, Adolf; Reifferscheid, Georg; Dardenne, Freddy; Blust, Ronny; Schofer, Andrea

    2007-04-01

    More than 100,000 tons of 2,4,6-trinitrotoluene were produced at the former ammunition site Werk Tanne in Clausthal-Zellerfeld, Germany. The production of explosives and consequent detonation in approximately 1944 by the Allies caused great pollution in this area. Four soil samples and three water samples were taken from this site and characterized by applying chemical-analytical methods and several bioassays. Ecotoxicological test systems, such as the algal growth inhibition assay with Desmodesmus subspicatus, and genotoxicity tests, such as the umu and NM2009 tests, were performed. Also applied were the Ames test, according to International Organization for Standardization 16240, and an Ames fluctuation test. The toxic mode of action was examined using bacterial gene profiling assays with a battery of Escherichia coli strains and with the human liver cell line hepG2 using the PIQOR Toxicology cDNA microarray. Additionally, the molecular mechanism of 2,4,6-trinitrotoluene in hepG2 cells was analyzed. The present assessment indicates a danger of pollutant leaching for the soil-groundwater path. A possible impact for human health is discussed, because the groundwater in this area serves as drinking water. PMID:17447547

  13. Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis

    Directory of Open Access Journals (Sweden)

    Turnbull Arran K

    2012-08-01

    Full Text Available Abstract Background Affymetrix GeneChips and Illumina BeadArrays are the most widely used commercial single channel gene expression microarrays. Public data repositories are an extremely valuable resource, providing array-derived gene expression measurements from many thousands of experiments. Unfortunately many of these studies are underpowered and it is desirable to improve power by combining data from more than one study; we sought to determine whether platform-specific bias precludes direct integration of probe intensity signals for combined reanalysis. Results Using Affymetrix and Illumina data from the microarray quality control project, from our own clinical samples, and from additional publicly available datasets we evaluated several approaches to directly integrate intensity level expression data from the two platforms. After mapping probe sequences to Ensembl genes we demonstrate that, ComBat and cross platform normalisation (XPN, significantly outperform mean-centering and distance-weighted discrimination (DWD in terms of minimising inter-platform variance. In particular we observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets. Conclusion Normalised and batch-corrected intensity-level data from Affymetrix and Illumina microarrays can be directly combined to generate biologically meaningful results with improved statistical power for robust, integrated reanalysis.

  14. Factors influencing the statistical power of complex data analysis protocols for molecular signature development from microarray data.

    Directory of Open Access Journals (Sweden)

    Constantin F Aliferis

    Full Text Available BACKGROUND: Critical to the development of molecular signatures from microarray and other high-throughput data is testing the statistical significance of the produced signature in order to ensure its statistical reproducibility. While current best practices emphasize sufficiently powered univariate tests of differential expression, little is known about the factors that affect the statistical power of complex multivariate analysis protocols for high-dimensional molecular signature development. METHODOLOGY/PRINCIPAL FINDINGS: We show that choices of specific components of the analysis (i.e., error metric, classifier, error estimator and event balancing have large and compounding effects on statistical power. The effects are demonstrated empirically by an analysis of 7 of the largest microarray cancer outcome prediction datasets and supplementary simulations, and by contrasting them to prior analyses of the same data. CONCLUSIONS/SIGNIFICANCE: THE FINDINGS OF THE PRESENT STUDY HAVE TWO IMPORTANT PRACTICAL IMPLICATIONS: First, high-throughput studies by avoiding under-powered data analysis protocols, can achieve substantial economies in sample required to demonstrate statistical significance of predictive signal. Factors that affect power are identified and studied. Much less sample than previously thought may be sufficient for exploratory studies as long as these factors are taken into consideration when designing and executing the analysis. Second, previous highly-cited claims that microarray assays may not be able to predict disease outcomes better than chance are shown by our experiments to be due to under-powered data analysis combined with inappropriate statistical tests.

  15. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

    Directory of Open Access Journals (Sweden)

    Hala Alshamlan

    2015-01-01

    Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  16. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

  17. Chromosome microarray proficiency testing and analysis of quality metric data trends through an external quality assessment program for Australasian laboratories.

    Science.gov (United States)

    Wright, D C; Adayapalam, N; Bain, N; Bain, S M; Brown, A; Buzzacott, N; Carey, L; Cross, J; Dun, K; Joy, C; McCarthy, C; Moore, S; Murch, A R; O'Malley, F; Parker, E; Watt, J; Wilkin, H; Fagan, K; Pertile, M D; Peters, G B

    2016-10-01

    Chromosome microarrays are an essential tool for investigation of copy number changes in children with congenital anomalies and intellectual deficit. Attempts to standardise microarray testing have focused on establishing technical and clinical quality criteria, however external quality assessment programs are still needed. We report on a microarray proficiency testing program for Australasian laboratories. Quality metrics evaluated included analytical accuracy, result interpretation, report completeness, and laboratory performance data: sample numbers, success and abnormality rate and reporting times. Between 2009 and 2014 nine samples were dispatched with variable results for analytical accuracy (30-100%), correct interpretation (32-96%), and report completeness (30-92%). Laboratory performance data (2007-2014) showed an overall mean success rate of 99.2% and abnormality rate of 23.6%. Reporting times decreased from >90 days to 102 days to <35 days for abnormal results. Data trends showed a positive correlation with improvement for all these quality metrics, however only 'report completeness' and reporting times reached statistical significance. Whether the overall improvement in laboratory performance was due to participation in this program, or from accumulated laboratory experience over time, is not clear. Either way, the outcome is likely to assist referring clinicians and improve patient care.

  18. Chromosome microarray proficiency testing and analysis of quality metric data trends through an external quality assessment program for Australasian laboratories.

    Science.gov (United States)

    Wright, D C; Adayapalam, N; Bain, N; Bain, S M; Brown, A; Buzzacott, N; Carey, L; Cross, J; Dun, K; Joy, C; McCarthy, C; Moore, S; Murch, A R; O'Malley, F; Parker, E; Watt, J; Wilkin, H; Fagan, K; Pertile, M D; Peters, G B

    2016-10-01

    Chromosome microarrays are an essential tool for investigation of copy number changes in children with congenital anomalies and intellectual deficit. Attempts to standardise microarray testing have focused on establishing technical and clinical quality criteria, however external quality assessment programs are still needed. We report on a microarray proficiency testing program for Australasian laboratories. Quality metrics evaluated included analytical accuracy, result interpretation, report completeness, and laboratory performance data: sample numbers, success and abnormality rate and reporting times. Between 2009 and 2014 nine samples were dispatched with variable results for analytical accuracy (30-100%), correct interpretation (32-96%), and report completeness (30-92%). Laboratory performance data (2007-2014) showed an overall mean success rate of 99.2% and abnormality rate of 23.6%. Reporting times decreased from >90 days to 102 days to <35 days for abnormal results. Data trends showed a positive correlation with improvement for all these quality metrics, however only 'report completeness' and reporting times reached statistical significance. Whether the overall improvement in laboratory performance was due to participation in this program, or from accumulated laboratory experience over time, is not clear. Either way, the outcome is likely to assist referring clinicians and improve patient care. PMID:27575971

  19. Novel design and controls for focused DNA microarrays: applications in quality assurance/control and normalization for the Health Canada ToxArray™

    Directory of Open Access Journals (Sweden)

    Lambert Iain B

    2006-10-01

    Full Text Available Abstract Background Microarray normalizations typically apply methods that assume absence of global transcript shifts, or absence of changes in internal control features such as housekeeping genes. These normalization approaches are not appropriate for focused arrays with small sets of genes where a large portion may be expected to change. Furthermore, many microarrays lack control features that can be used for quality assurance (QA. Here, we describe a novel external control series integrated with a design feature that addresses the above issues. Results An EC dilution series that involves spike-in of a single concentration of the A. thaliana chlorophyll synthase gene to hybridize against spotted dilutions (0.000015 to 100 μM of a single complimentary oligonucleotide representing the gene was developed. The EC series is printed in duplicate within each subgrid of the microarray and covers the full range of signal intensities from background to saturation. The design and placement of the series allows for QA examination of frequently encountered problems in hybridization (e.g., uneven hybridizations and printing (e.g., cross-spot contamination. Additionally, we demonstrate that the series can be integrated with a LOWESS normalization to improve the detection of differential gene expression (improved sensitivity and predictivity over LOWESS normalization on its own. Conclusion The quality of microarray experiments and the normalization methods used affect the ability to measure accurate changes in gene expression. Novel methods are required for normalization of small focused microarrays, and for incorporating measures of performance and quality. We demonstrate that dilution of oligonucleotides on the microarray itself provides an innovative approach allowing the full dynamic range of the scanner to be covered with a single gene spike-in. The dilution series can be used in a composite normalization to improve detection of differential gene

  20. O-antigen and virulence profiling of Shiga toxin-producing Escherichia coli by a rapid and cost-effective DNA microarray colorimetric method

    Directory of Open Access Journals (Sweden)

    Beatriz eQuiñones

    2012-05-01

    Full Text Available Shiga toxin-producing Escherichia coli (STEC is a leading cause of foodborne illness worldwide. The present study developed the use of DNA microarrays with the ampliPHOX colorimetric method to rapidly detect and genotype STEC strains. A low-density 30-mer oligonucleotide DNA microarray was designed to target O-antigen gene clusters of eleven E. coli serogroups (O26, O45, O91, O103, O104, O111, O113, O121, O128, O145 and O157 that have been associated with the majority of STEC infections. In addition, the DNA microarray targeted eleven virulence genes, encoding adhesins, cytotoxins, proteases, and receptor proteins, which have been implicated in conferring increased ability to cause disease for STEC. Results from the validation experiments demonstrated that this microarray-based colorimetric method allowed for a rapid and accurate genotyping of STEC reference strains from environmental and clinical sources and from distinct geographical locations. Positive hybridization signals were detected only for probes targeting serotype and virulence genes known to be present in the STEC reference strains. Quantification analysis indicated that the mean pixel intensities of the signal for probes targeting O-antigen or virulence genes were at least three times higher when compared to the background. Furthermore, this microarray-based colorimetric method was then employed to genotype a group of E. coli isolates from watershed sediment and animal fecal samples that were collected from an important region for leafy-vegetable production in the central coast of California. The results indicated an accurate identification of O-type and virulence genes in the tested isolates and confirmed that the ampliPHOX colorimetric method with low density DNA microarrays enabled a fast assessment of the virulence potential of STEC using low-cost reagents and instrumentation.

  1. Jellyfish modulate bacterial dynamic and community structure.

    Directory of Open Access Journals (Sweden)

    Tinkara Tinta

    Full Text Available Jellyfish blooms have increased in coastal areas around the world and the outbreaks have become longer and more frequent over the past few decades. The Mediterranean Sea is among the heavily affected regions and the common bloom-forming taxa are scyphozoans Aurelia aurita s.l., Pelagia noctiluca, and Rhizostoma pulmo. Jellyfish have few natural predators, therefore their carcasses at the termination of a bloom represent an organic-rich substrate that supports rapid bacterial growth, and may have a large impact on the surrounding environment. The focus of this study was to explore whether jellyfish substrate have an impact on bacterial community phylotype selection. We conducted in situ jellyfish-enrichment experiment with three different jellyfish species. Bacterial dynamic together with nutrients were monitored to assess decaying jellyfish-bacteria dynamics. Our results show that jellyfish biomass is characterized by protein rich organic matter, which is highly bioavailable to 'jellyfish-associated' and 'free-living' bacteria, and triggers rapid shifts in bacterial population dynamics and composition. Based on 16S rRNA clone libraries and denaturing gradient gel electrophoresis (DGGE analysis, we observed a rapid shift in community composition from unculturable Alphaproteobacteria to culturable species of Gammaproteobacteria and Flavobacteria. The results of sequence analyses of bacterial isolates and of total bacterial community determined by culture independent genetic analysis showed the dominance of the Pseudoalteromonadaceae and the Vibrionaceae families. Elevated levels of dissolved proteins, dissolved organic and inorganic nutrient release, bacterial abundance and carbon production as well as ammonium concentrations characterized the degradation process. The biochemical composition of jellyfish species may influence changes in the amount of accumulated dissolved organic and inorganic nutrients. Our results can contribute insights into

  2. Ability to differentiate between cp and ncp BVDV by microarrays: towards an application in clinical veterinary medicine?

    Science.gov (United States)

    Werling, Dirk; Ruryk, Andriy; Heaney, Judith; Moeller, Eva; Brownlie, Joe

    2005-10-18

    Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a 'system' that is more than the sum of its parts. The vigilance of cells to environmental change, the alacrity of the transcriptional response, the short half-life of cellular mRNA and the genome-scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to infectious processes; the identification of co-ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of viral pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival of the virus in the host's cells. Here, we show data obtained using a tailored microarray system based on synthetic polynucleotides derived from human sequences (SIRS-Lab GmbH, Jena, Germany) to study the effect of cytopathogenic (cpe) and non-cytopathogenic (ncp) bovine viral diarrhoea virus (BVDV) infection of bovine macrophages, focusing on intracellular signalling molecules. Of the 575 genes present on the array, more than 70% showed a reaction with the oligonuleotides spotted on the array, and 26 genes were differentially expressed comparing cDNA derived from cpe and ncp infected cells. These data will help to further understand our knowledge regarding BVDV infection, and will

  3. Model for Mutation in Bacterial Populations

    Science.gov (United States)

    Donangelo, R.; Fort, H.

    2002-07-01

    We describe the evolution of E. coli populations through a Bak-Sneppen-type model which incorporates random mutations. We show that, for a value of the mutation level which coincides with the one estimated from experiments, this model reproduces the measures of mean fitness relative to that of a common ancestor, performed for over 10 000 bacterial generations.

  4. A model for mutation in bacterial populations

    OpenAIRE

    Donangelo, R.; Fort, H.

    2002-01-01

    We describe the evolution of $E.coli$ populations through a Bak-Sneppen type model which incorporates random mutations. We show that, for a value of the mutation level which coincides with the one estimated from experiments, this model reproduces the measures of mean fitness relative to that of a common ancestor, performed for over 10,000 bacterial generations.

  5. Punctuated equilibrium in an evolving bacterial population

    OpenAIRE

    Chaudhuri, Indranath; Bose, Indrani

    1999-01-01

    Recently, Lenski et al have carried out an experiment on bacterial evolution. Their findings support the theory of punctuated equilibrium in biological evolution. We show that the M=2 Bak-Sneppen model can explain some of the experimental results in a qualitative manner.

  6. Corticosteroids for acute adult bacterial meningitis

    NARCIS (Netherlands)

    D. van de Beek

    2009-01-01

    Bacterial meningitis in adults is a severe disease, with high fatality and morbidity rates. Experimental studies showed that the inflammatory response in the subarachnoid space is associated with unfavorable outcome. In these experiments, corticosteroids, and in particular dexamethasone, were able t

  7. Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

    Science.gov (United States)

    Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

    2006-07-01

    Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

  8. DNA microarray synthesis by using PDMS molecular stamps (Ⅲ)-- Optimization for the reaction conditions

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Optimization for the technological processes of fabricating oligonucleotide microarray by the molecular stamping method is studied in this note. Three factors that affect the pressing coupling reactions of the nucleosides are focused on: the stability of the chemical activities of the reaction solutions, the contamination of the remain of the reactive nucleotides among the different spots on the chip, and the influence of the capping reaction on the hybridization result. The experiments show that the acetonitrile solution of tetrazole and nucleoside monomer could maintain sufficient reactive activity for more than 10 h. An effective method has been used and proved to eliminate the residual reactive nucleosides on chip with small molecules containing hydroxyl group. Finally, the capping step-- a regular step in the conventional DNA chemical synthesis can be neglected in our on-chip DNA synthetic process, which would not affect its hybridization results.

  9. "Hook"-calibration of GeneChip-microarrays: Chip characteristics and expression measures

    Directory of Open Access Journals (Sweden)

    Krohn Knut

    2008-08-01

    Full Text Available Abstract Background Microarray experiments rely on several critical steps that may introduce biases and uncertainty in downstream analyses. These steps include mRNA sample extraction, amplification and labelling, hybridization, and scanning causing chip-specific systematic variations on the raw intensity level. Also the chosen array-type and the up-to-dateness of the genomic information probed on the chip affect the quality of the expression measures. In the accompanying publication we presented theory and algorithm of the so-called hook method which aims at correcting expression data for systematic biases using a series of new chip characteristics. Results In this publication we summarize the essential chip characteristics provided by this method, analyze special benchmark experiments to estimate transcript related expression measures and illustrate the potency of the method to detect and to quantify the quality of a particular hybridization. It is shown that our single-chip approach provides expression measures responding linearly on changes of the transcript concentration over three orders of magnitude. In addition, the method calculates a detection call judging the relation between the signal and the detection limit of the particular measurement. The performance of the method in the context of different chip generations and probe set assignments is illustrated. The hook method characterizes the RNA-quality in terms of the 3'/5'-amplification bias and the sample-specific calling rate. We show that the proper judgement of these effects requires the disentanglement of non-specific and specific hybridization which, otherwise, can lead to misinterpretations of expression changes. The consequences of modifying probe/target interactions by either changing the labelling protocol or by substituting RNA by DNA targets are demonstrated. Conclusion The single-chip based hook-method provides accurate expression estimates and chip-summary characteristics

  10. DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

    Institute of Scientific and Technical Information of China (English)

    Yuka; Kobayashi; Sofya; P; Kulikova; Junko; Shibato; Randeep; Rakwal; Hiroyuki; Satoh; Didier; Pinault; Yoshinori; Masuo

    2015-01-01

    AIM:To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS:Rats were treated with an intraperitoneal injection of MK-801 [0.08(low-dose) and 0.16(highdose) mg/kg] or NaC l(vehicle control). In a first series of experiment,the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments,the whole brain of each animal was rapidly removed at 40 min post-injection,and different regions were separated:amygdala,cerebral cortex,hippocampus,hypothalamus,midbrain and ventral striatum on ice followed by DNA microarray(4 × 44 K whole rat genome chip) analysis.RESULTS:Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency(30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number(up- and down- regulations) of gene expressions in the cerebral cortex(378),midbrain(376),hippocampus(375),ventral striatum(353),amygdala(301),and hypothalamus(201) under low-dose(0.08 mg/kg) of MK-801. Under high-dose(0.16 mg/kg),ventral striatum(811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region.CONCLUSION:Acute MK-801 treatment increases synchrony of baseline gamma oscillations,and causes very early changes in gene expressions in six individual rat brain regions,a first report.

  11. The bacterial lipocalins.

    Science.gov (United States)

    Bishop, R E

    2000-10-18

    The lipocalins were once regarded as a eukaryotic protein family, but new members have been recently discovered in bacteria. The first bacterial lipocalin (Blc) was identified in Escherichia coli as an outer membrane lipoprotein expressed under conditions of environmental stress. Blc is distinguished from most lipocalins by the absence of intramolecular disulfide bonds, but the presence of a membrane anchor is shared with two of its closest homologues, apolipoprotein D and lazarillo. Several common features of the membrane-anchored lipocalins suggest that each may play an important role in membrane biogenesis and repair. Additionally, Blc proteins are implicated in the dissemination of antibiotic resistance genes and in the activation of immunity. Recent genome sequencing efforts reveal the existence of at least 20 bacterial lipocalins. The lipocalins appear to have originated in Gram-negative bacteria and were probably transferred horizontally to eukaryotes from the endosymbiotic alpha-proteobacterial ancestor of the mitochondrion. The genome sequences also reveal that some bacterial lipocalins exhibit disulfide bonds and alternative modes of subcellular localization, which include targeting to the periplasmic space, the cytoplasmic membrane, and the cytosol. The relationships between bacterial lipocalin structure and function further illuminate the common biochemistry of bacterial and eukaryotic cells.

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

    Directory of Open Access Journals (Sweden)

    Sarah Schumacher

    2015-04-01

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

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

    Science.gov (United States)

    Schumacher, Sarah; Muekusch, Sandra; Seitz, Harald

    2015-04-23

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

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

    Science.gov (United States)

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

    2015-01-01

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

  15. Determination of strongly overlapping signaling activity from microarray data

    Directory of Open Access Journals (Sweden)

    Bidaut Ghislain

    2006-02-01

    Full Text Available Abstract Background As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of signaling pathways during disease development or therapeutic intervention would assist in drug development, design of therapy, and target identification. Microarrays provide a global measure of cellular response, however linking these responses to signaling pathways requires an analytic approach tuned to the underlying biology. An ongoing issue in pattern recognition in microarrays has been how to determine the number of patterns (or clusters to use for data interpretation, and this is a critical issue as measures of statistical significance in gene ontology or pathways rely on proper separation of genes into groups. Results Here we introduce a method relying on gene annotation coupled to decompositional analysis of global gene expression data that allows us to estimate specific activity on strongly coupled signaling pathways and, in some cases, activity of specific signaling proteins. We demonstrate the technique using the Rosetta yeast deletion mutant data set, decompositional analysis by Bayesian Decomposition, and annotation analysis using ClutrFree. We determined from measurements of gene persistence in patterns across multiple potential dimensionalities that 15 basis vectors provides the correct dimensionality for interpreting the data. Using gene ontology and data on gene regulation in the Saccharomyces Genome Database, we identified the transcriptional signatures of several cellular processes in yeast, including cell wall creation, ribosomal disruption, chemical blocking of protein synthesis, and, criticially, individual signatures of the strongly coupled mating and filamentation pathways. Conclusion This works demonstrates that microarray data can provide downstream indicators of pathway activity either through use of gene ontology or transcription

  16. Oligonucleotide microarray for subtyping of influenza A viruses

    Science.gov (United States)

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

    2012-02-01

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

  17. Producing reverse phase protein microarrays from formalin-fixed tissues.

    Science.gov (United States)

    Wolff, Claudia; Schott, Christina; Malinowsky, Katharina; Berg, Daniela; Becker, Karl-Friedrich

    2011-01-01

    In most hospitals around the world FFPE (formalin fixed, paraffin embedded) tissues have been used for diagnosis and have subsequently been archived since decades. This has lead to a sizeable pool of this kind of tissues. Till quite recently it was not possible to use this congeries of samples for protein analysis, but now several groups described successful protein extraction from FFPE tissues. In this chapter, we describe a protein extraction protocol established in our laboratory combined with the use of reverse phase protein microarray.

  18. Towards a programmable magnetic bead microarray in a microfluidic channel

    DEFF Research Database (Denmark)

    Smistrup, Kristian; Bruus, Henrik; Hansen, Mikkel Fougt

    2007-01-01

    A new hybrid magnetic bead separator that combines an external magnetic field with 175@mm thick current lines buried in the back side of a silicon wafer is presented. A microfluidic channel was etched into the front side of the wafer. The large cross-section of the current lines makes it possible...... to use larger currents and obtain forces of longer range than from thin current lines at a given power limit. Guiding of magnetic beads in the hybrid magnetic separator and the construction of a programmable microarray of magnetic beads in the microfluidic channel by hydrodynamic focusing is presented....

  19. Two heuristic approaches to describe periodicities in genomic microarrays

    Directory of Open Access Journals (Sweden)

    Jörg Aßmus

    2009-09-01

    Full Text Available In the first part we discuss the filtering of panels of time series based on singular value decomposition. The discussion is based on an approach where this filtering is used to normalize microarray data. We point out effects on the periodicity and phases for time series panels. In the second part we investigate time dependent periodic panels with different phases. We align the time series in the panel and discuss the periodogram of the aligned time series with the purpose of describing the periodic structure of the panel. The method is quite powerful assuming known phases in the model, but it deteriorates rapidly for noisy data.  

  20. Oligonucleotide microarray for subtyping of influenza A viruses

    International Nuclear Information System (INIS)

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