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Sample records for bacterial microarray experiments

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

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    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. Rapid Diagnosis of Bacterial Meningitis Using a Microarray

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    Ren-Jy Ben

    2008-06-01

    Conclusion: The microarray method provides a more accurate and rapid diagnostic tool for bacterial meningitis compared to traditional culture methods. Clinical application of this new technique may reduce the potential risk of delay in treatment.

  3. 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.

  4. 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.

  5. Normalization for triple-target microarray experiments

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    Magniette Frederic

    2008-04-01

    Full Text Available Abstract Background Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data. Results We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2. Conclusion The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

  6. Weighted analysis of general microarray experiments

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    Kristiansson Erik

    2007-10-01

    Full Text Available Abstract Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods.

  7. Microarray time course experiments: finding profiles.

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    Irigoien, Itziar; Vives, Sergi; Arenas, Concepción

    2011-01-01

    Time course studies with microarray techniques and experimental replicates are very useful in biomedical research. We present, in replicate experiments, an alternative approach to select and cluster genes according to a new measure for association between genes. First, the procedure normalizes and standardizes the expression profile of each gene, and then, identifies scaling parameters that will further minimize the distance between replicates of the same gene. Then, the procedure filters out genes with a flat profile, detects differences between replicates, and separates genes without significant differences from the rest. For this last group of genes, we define a mean profile for each gene and use it to compute the distance between two genes. Next, a hierarchical clustering procedure is proposed, a statistic is computed for each cluster to determine its compactness, and the total number of classes is determined. For the rest of the genes, those with significant differences between replicates, the procedure detects where the differences between replicates lie, and assigns each gene to the best fitting previously identified profile or defines a new profile. We illustrate this new procedure using simulated data and a representative data set arising from a microarray experiment with replication, and report interesting results.

  8. Universal Reference RNA as a standard for microarray experiments

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    Fero Michael

    2004-03-01

    Full Text Available Abstract Background Obtaining reliable and reproducible two-color microarray gene expression data is critically important for understanding the biological significance of perturbations made on a cellular system. Microarray design, RNA preparation and labeling, hybridization conditions and data acquisition and analysis are variables difficult to simultaneously control. A useful tool for monitoring and controlling intra- and inter-experimental variation is Universal Reference RNA (URR, developed with the goal of providing hybridization signal at each microarray probe location (spot. Measuring signal at each spot as the ratio of experimental RNA to reference RNA targets, rather than relying on absolute signal intensity, decreases variability by normalizing signal output in any two-color hybridization experiment. Results Human, mouse and rat URR (UHRR, UMRR and URRR, respectively were prepared from pools of RNA derived from individual cell lines representing different tissues. A variety of microarrays were used to determine percentage of spots hybridizing with URR and producing signal above a user defined threshold (microarray coverage. Microarray coverage was consistently greater than 80% for all arrays tested. We confirmed that individual cell lines contribute their own unique set of genes to URR, arguing for a pool of RNA from several cell lines as a better configuration for URR as opposed to a single cell line source for URR. Microarray coverage comparing two separately prepared batches each of UHRR, UMRR and URRR were highly correlated (Pearson's correlation coefficients of 0.97. Conclusion Results of this study demonstrate that large quantities of pooled RNA from individual cell lines are reproducibly prepared and possess diverse gene representation. This type of reference provides a standard for reducing variation in microarray experiments and allows more reliable comparison of gene expression data within and between experiments and

  9. Statistical implications of pooling RNA samples for microarray experiments

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    Landfield Philip W

    2003-06-01

    Full Text Available Abstract Background Microarray technology has become a very important tool for studying gene expression profiles under various conditions. Biologists often pool RNA samples extracted from different subjects onto a single microarray chip to help defray the cost of microarray experiments as well as to correct for the technical difficulty in getting sufficient RNA from a single subject. However, the statistical, technical and financial implications of pooling have not been explicitly investigated. Results Modeling the resulting gene expression from sample pooling as a mixture of individual responses, we derived expressions for the experimental error and provided both upper and lower bounds for its value in terms of the variability among individuals and the number of RNA samples pooled. Using "virtual" pooling of data from real experiments and computer simulations, we investigated the statistical properties of RNA sample pooling. Our study reveals that pooling biological samples appropriately is statistically valid and efficient for microarray experiments. Furthermore, optimal pooling design(s can be found to meet statistical requirements while minimizing total cost. Conclusions Appropriate RNA pooling can provide equivalent power and improve efficiency and cost-effectiveness for microarray experiments with a modest increase in total number of subjects. Pooling schemes in terms of replicates of subjects and arrays can be compared before experiments are conducted.

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

    NARCIS (Netherlands)

    Dols, Joke A M; Smit, Pieter W; Kort, Remco; Reid, Gregor; Schuren, Frank H J; Tempelman, Hugo; Bontekoe, Tj Romke; Korporaal, Hans; Boon, Mathilde E

    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

  11. 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.

  12. Bacterial Surface Glycans: Microarray and QCM Strategies for Glycophenotyping and Exploration of Recognition by Host Receptors.

    Science.gov (United States)

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

    2018-01-01

    Bacterial surfaces are decorated with a diversity of carbohydrate structures that play important roles in the bacteria-host relationships. They may offer protection against host defense mechanisms, elicit strong antigenic responses, or serve as ligands for host receptors, including lectins of the innate immune system. Binding by these lectins may trigger defense responses or, alternatively, promote attachment, thereby enhancing infection. The outcome will depend on the particular bacterial surface landscape, which may substantially differ among species and strains. In this chapter, we describe two novel methods for exploring interactions directly on the bacterial surface, based on the generation of bacterial microarrays and quartz crystal microbalance (QCM) sensor chips. Bacterial microarrays enable profiling of accessible carbohydrate structures and screening of their recognition by host receptors, also providing information on binding avidity, while the QCM approach allows determination of binding affinity and kinetics. In both cases, the chief element is the use of entire bacterial cells, so that recognition of the bacterial glycan epitopes is explored in their natural environment. © 2018 Elsevier Inc. All rights reserved.

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

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

    2011-02-28

    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. 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. The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics.

  14. 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.

  15. 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.

  16. Rapid identification of bacterial pathogens using a PCR- and microarray-based assay

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    Aittakorpi Anne

    2009-08-01

    Full Text Available Abstract Background During the course of a bacterial infection, the rapid identification of the causative agent(s is necessary for the determination of effective treatment options. We have developed a method based on a modified broad-range PCR and an oligonucleotide microarray for the simultaneous detection and identification of 12 bacterial pathogens at the species level. The broad-range PCR primer mixture was designed using conserved regions of the bacterial topoisomerase genes gyrB and parE. The primer design allowed the use of a novel DNA amplification method, which produced labeled, single-stranded DNA suitable for microarray hybridization. The probes on the microarray were designed from the alignments of species- or genus-specific variable regions of the gyrB and parE genes flanked by the primers. We included mecA-specific primers and probes in the same assay to indicate the presence of methicillin resistance in the bacterial species. The feasibility of this assay in routine diagnostic testing was evaluated using 146 blood culture positive and 40 blood culture negative samples. Results Comparison of our results with those of a conventional culture-based method revealed a sensitivity of 96% (initial sensitivity of 82% and specificity of 98%. Furthermore, only one cross-reaction was observed upon investigating 102 culture isolates from 70 untargeted bacteria. The total assay time was only three hours, including the time required for the DNA extraction, PCR and microarray steps in sequence. Conclusion The assay rapidly provides reliable data, which can guide optimal antimicrobial treatment decisions in a timely manner.

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

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    Jung Klaus

    2011-04-01

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

  18. 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.

  19. Confidence levels for the comparison of microarray experiments.

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    Shedden, Kerby

    2004-01-01

    A common experimental strategy utilizing microarrays is to develop a signature of genes responding to some treatment in a model system, and then ask whether the same genes respond in an analogous way in a more natural and uncontrolled environment. In statistical terms, the question posed is whether genes score similarly on some statistical test in two independent data sets. Approaches to this problem ignoring gene/gene correlations common to all microarray data sets are known to give overstated statistical confidence levels. Permutation approaches have been proposed to give more accurate confidence levels, but can not be applied when sample sizes are small. Here we argue that the product moment correlation between test statistics in the two experiments is an ideal measure for summarizing concordance between the experiments, as confidence levels accounting for intergene correlations depend only on a single number - the average squared correlation between gene pairs in the data set. The resulting null standard deviation is shown to vary by less than a factor of two over six distinct experimental data sets, suggesting that a universal constant may be used for this quantity. We show how a hidden assumption of the permutation approach may lead to incorrect p-values, while the analytic approach presented here is shown to be resistant to this assumption.

  20. Bacterial species determination from DNA-DNA hybridization by using genome fragments and DNA microarrays.

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    Cho, J C; Tiedje, J M

    2001-08-01

    Whole genomic DNA-DNA hybridization has been a cornerstone of bacterial species determination but is not widely used because it is not easily implemented. We have developed a method based on random genome fragments and DNA microarray technology that overcomes the disadvantages of whole-genome DNA-DNA hybridization. Reference genomes of four fluorescent Pseudomonas species were fragmented, and 60 to 96 genome fragments of approximately 1 kb from each strain were spotted on microarrays. Genomes from 12 well-characterized fluorescent Pseudomonas strains were labeled with Cy dyes and hybridized to the arrays. Cluster analysis of the hybridization profiles revealed taxonomic relationships between bacterial strains tested at species to strain level resolution, suggesting that this approach is useful for the identification of bacteria as well as determining the genetic distance among bacteria. Since arrays can contain thousands of DNA spots, a single array has the potential for broad identification capacity. In addition, the method does not require laborious cross-hybridizations and can provide an open database of hybridization profiles, avoiding the limitations of traditional DNA-DNA hybridization.

  1. 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

  2. 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.

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

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    Lee, Dae-Young [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada)], E-mail: daeyoung.lee@ec.gc.ca; Lauder, Heather; Cruwys, Heather; Falletta, Patricia [National Water Research Institute, Environment Canada, 867 Lakeshore Road, Burlington, Ontario, L7R 4A6 (Canada); Beaudette, Lee A. [Environmental Science and Technology Centre, Environment Canada, 335 River Road South, Ottawa, Ontario, K1A 0H3 (Canada)], E-mail: lee.beaudette@ec.gc.ca

    2008-07-15

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

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

    International Nuclear Information System (INIS)

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

    2008-01-01

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

  5. Use of phenotype microarrays to study the effect of acquisition of resistance to antimicrobials in bacterial physiology.

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    Reales-Calderon, Jose A; Blanco, Paula; Alcalde-Rico, Manuel; Corona, Fernando; Lira, Felipe; Hernando-Amado, Sara; Bernardini, Alejandra; Sánchez, María B; Martínez, José L

    It is widely accepted that the acquisition of resistance to antimicrobials confers a fitness cost. Different works have shown that the effect of acquiring resistance in bacterial physiology may be more specific than previously thought. Study of these specific changes may help to predict the outcome of resistant organisms in different ecosystems. In addition to changing bacterial physiology, acquisition of resistance either increases or reduces susceptibility to other antimicrobials. In the current article, we review recent information on the effect of acquiring resistance upon bacterial physiology, with a specific focus on studies using phenotype microarray technology. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  6. Functional profiling of microarray experiments using text-mining derived bioentities.

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    Minguez, Pablo; Al-Shahrour, Fátima; Montaner, David; Dopazo, Joaquín

    2007-11-15

    The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.

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

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    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.

  8. Microarray analysis of gene expression in disk abalone Haliotis discus discus after bacterial challenge.

    Science.gov (United States)

    De Zoysa, Mahanama; Nikapitiya, Chamilani; Oh, Chulhong; Lee, Youngdeuk; Whang, Ilson; Lee, Jae-Seong; Choi, Cheol Young; Lee, Jehee

    2011-02-01

    In this study, we investigated the gene expression profiling of disk abalone, Haliotis discus discus challenged by a mixture of three pathogenic bacteria Vibrio alginolyticus, Vibrio parahemolyticus, and Listeria monocytogenes using a cDNA microarray. Upon bacteria challenge, 68 (1.6%) and 112 (2.7%) gene transcripts changed their expression levels ≥2 or ≤2 -fold in gills and digestive tract, respectively. There were 46 tissue-specific transcripts that up-regulated specifically in the digestive tract. In contrast, only 13 transcripts showed gill-specific up-regulation. Quantitative real-time PCR was performed to verify microarray data and results revealed that candidate genes namely Krüppell-like factor (KLF), lachesin, muscle lim protein, thioredoxin-2 (TRx-2), nuclear factor interleukin 3 (NFIL-3) and abalone protein 38 were up-regulated. Also, our results further indicated that bacteria challenge may activate the transcription factors or their activators (Krüppell-like factor, inhibitor of NF-κB or Ik-B), inflammatory cytokines (IL-3 regulated protein, allograft inflammatory factor), other cytokines (IFN-44-like protein, SOCS-2), antioxidant enzymes (glutathione-S-transferase, thioredoxin-2 and thioredoxin peroxidase), and apoptosis-related proteins (TNF-α, archeron) in abalone. The identification of immune and stress response genes and their expression profiles in this microarray will permit detailed investigation of the stress and immune responses of abalone genes. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. 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

  10. Analysis of apple (Malus) responses to bacterial pathogens using an oligo microarray

    Science.gov (United States)

    Fire blight is a devastating disease of apple (Malus x domestica) caused by the bacterial pathogen Erwinia amylovora (Ea). When infiltrated into host leaves, Ea induces reactions similar to a hypersensitive response (HR). Type III (T3SS) associated effectors, especially DspA/E, are suspected to ha...

  11. Sample size calculation for microarray experiments with blocked one-way design

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    Jung Sin-Ho

    2009-05-01

    Full Text Available Abstract Background One of the main objectives of microarray analysis is to identify differentially expressed genes for different types of cells or treatments. Many statistical methods have been proposed to assess the treatment effects in microarray experiments. Results In this paper, we consider discovery of the genes that are differentially expressed among K (> 2 treatments when each set of K arrays consists of a block. In this case, the array data among K treatments tend to be correlated because of block effect. We propose to use the blocked one-way ANOVA F-statistic to test if each gene is differentially expressed among K treatments. The marginal p-values are calculated using a permutation method accounting for the block effect, adjusting for the multiplicity of the testing procedure by controlling the false discovery rate (FDR. We propose a sample size calculation method for microarray experiments with a blocked one-way design. With FDR level and effect sizes of genes specified, our formula provides a sample size for a given number of true discoveries. Conclusion The calculated sample size is shown via simulations to provide an accurate number of true discoveries while controlling the FDR at the desired level.

  12. 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.

  13. A unified framework for finding differentially expressed genes from microarray experiments

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    Yeasin Mohammed

    2007-09-01

    -sample microarray experiments. Two different ranking methods used in module 1 bring diversity in the selection of genes. The conversion of ranks to p-values, the fusion of p-values and FDR analysis aid in the identification of significant genes which cannot be judged based on gene ranking alone. The 3 fold validation, namely, robustness in selection of genes using FDR analysis, clustering, and visualization demonstrate the relevance of the DEGs. Empirical analyses on 50 artificial datasets and 6 real microarray datasets illustrate the efficacy of the proposed approach. The analyses on 3 cancer datasets demonstrate the utility of the proposed approach on microarray datasets with two classes of samples. The scalability of the proposed unified approach to multi-sample (more than two sample classes microarray datasets is addressed using three sets of Parkinson's Data. Empirical analyses show that the unified framework outperformed other gene selection methods in selecting differentially expressed genes from microarray data.

  14. Evaluation of the gene-specific dye bias in cDNA microarray experiments.

    Science.gov (United States)

    Martin-Magniette, Marie-Laure; Aubert, Julie; Cabannes, Eric; Daudin, Jean-Jacques

    2005-05-01

    In cDNA microarray experiments all samples are labeled with either Cy3 or Cy5. Systematic and gene-specific dye bias effects have been observed in dual-color experiments. In contrast to systematic effects which can be corrected by a normalization method, the gene-specific dye bias is not completely suppressed and may alter the conclusions about the differentially expressed genes. The gene-specific dye bias is taken into account using an analysis of variance model. We propose an index, named label bias index, to measure the gene-specific dye bias. It requires at least two self-self hybridization cDNA microarrays. After lowess normalization we have found that the gene-specific dye bias is the major source of experimental variability between replicates. The ratio (R/G) may exceed 2. As a consequence false positive genes may be found in direct comparison without dye-swap. The stability of this artifact and its consequences on gene variance and on direct or indirect comparisons are addressed. http://www.inapg.inra.fr/ens_rech/mathinfo/recherche/mathematique

  15. 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/.

  16. A permutation-based multiple testing method for time-course microarray experiments

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    George Stephen L

    2009-10-01

    Full Text Available Abstract Background Time-course microarray experiments are widely used to study the temporal profiles of gene expression. Storey et al. (2005 developed a method for analyzing time-course microarray studies that can be applied to discovering genes whose expression trajectories change over time within a single biological group, or those that follow different time trajectories among multiple groups. They estimated the expression trajectories of each gene using natural cubic splines under the null (no time-course and alternative (time-course hypotheses, and used a goodness of fit test statistic to quantify the discrepancy. The null distribution of the statistic was approximated through a bootstrap method. Gene expression levels in microarray data are often complicatedly correlated. An accurate type I error control adjusting for multiple testing requires the joint null distribution of test statistics for a large number of genes. For this purpose, permutation methods have been widely used because of computational ease and their intuitive interpretation. Results In this paper, we propose a permutation-based multiple testing procedure based on the test statistic used by Storey et al. (2005. We also propose an efficient computation algorithm. Extensive simulations are conducted to investigate the performance of the permutation-based multiple testing procedure. The application of the proposed method is illustrated using the Caenorhabditis elegans dauer developmental data. Conclusion Our method is computationally efficient and applicable for identifying genes whose expression levels are time-dependent in a single biological group and for identifying the genes for which the time-profile depends on the group in a multi-group setting.

  17. GeneRank: Using search engine technology for the analysis of microarray experiments

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    Breitling Rainer

    2005-09-01

    Full Text Available Abstract Background Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method – based on the PageRank algorithm employed by the popular search engine Google – that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. Results GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Conclusion Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  18. GeneRank: using search engine technology for the analysis of microarray experiments.

    Science.gov (United States)

    Morrison, Julie L; Breitling, Rainer; Higham, Desmond J; Gilbert, David R

    2005-09-21

    Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information. GeneRank is an intuitive modification of PageRank that maintains many of its mathematical properties. It combines gene expression information with a network structure derived from gene annotations (gene ontologies) or expression profile correlations. Using both simulated and real data we find that the algorithm offers an improved ranking of genes compared to pure expression change rankings. Our modification of the PageRank algorithm provides an alternative method of evaluating microarray experimental results which combines prior knowledge about the underlying network. GeneRank offers an improvement compared to assessing the importance of a gene based on its experimentally observed fold-change alone and may be used as a basis for further analytical developments.

  19. Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broad range of gram-negative bacterial pathogens.

    Science.gov (United States)

    Card, Roderick; Zhang, Jiancheng; Das, Priya; Cook, Charlotte; Woodford, Neil; Anjum, Muna F

    2013-01-01

    A microarray capable of detecting genes for resistance to 75 clinically relevant antibiotics encompassing 19 different antimicrobial classes was tested on 132 Gram-negative bacteria. Microarray-positive results correlated >91% with antimicrobial resistance phenotypes, assessed using British Society for Antimicrobial Chemotherapy clinical breakpoints; the overall test specificity was >83%. Microarray-positive results without a corresponding resistance phenotype matched 94% with PCR results, indicating accurate detection of genes present in the respective bacteria by microarray when expression was low or absent and, hence, undetectable by susceptibility testing. The low sensitivity and negative predictive values of the microarray results for identifying resistance to some antimicrobial resistance classes are likely due to the limited number of resistance genes present on the current microarray for those antimicrobial agents or to mutation-based resistance mechanisms. With regular updates, this microarray can be used for clinical diagnostics to help accurate therapeutic options to be taken following infection with multiple-antibiotic-resistant Gram-negative bacteria and prevent treatment failure.

  20. 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

  1. Improving the power to detect differentially expressed genes in comparative microarray experiments by including information from self-self hybridizations

    NARCIS (Netherlands)

    Gusnanto, Arief; Tom, Brian; Burns, Philippa; Macaulay, Iain; Thijssen-Timmer, Daphne C.; Tijssen, Marloes R.; Langford, Cordelia; Watkins, Nicholas; Ouwehand, Willem; Berzuini, Carlo; Dudbridge, Frank

    2007-01-01

    Our ability to detect differentially expressed genes in a microarray experiment can be hampered when the number of biological samples of interest is limited. In this situation, we propose the use of information from self-self hybridizations to acuminate our inference of differential expression. A

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

    Science.gov (United States)

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

  3. Comparing bacterial community composition between healthy and white plague-like disease states in Orbicella annularis using PhyloChip™ G3 microarrays.

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    Christina A Kellogg

    Full Text Available Coral disease is a global problem. Diseases are typically named or described based on macroscopic changes, but broad signs of coral distress such as tissue loss or discoloration are unlikely to be specific to a particular pathogen. For example, there appear to be multiple diseases that manifest the rapid tissue loss that characterizes 'white plague.' PhyloChip™ G3 microarrays were used to compare the bacterial community composition of both healthy and white plague-like diseased corals. Samples of lobed star coral (Orbicella annularis, formerly of the genus Montastraea[1] were collected from two geographically distinct areas, Dry Tortugas National Park and Virgin Islands National Park, to determine if there were biogeographic differences between the diseases. In fact, all diseased samples clustered together, however there was no consistent link to Aurantimonas coralicida, which has been described as the causative agent of white plague type II. The microarrays revealed a large amount of bacterial heterogeneity within the healthy corals and less diversity in the diseased corals. Gram-positive bacterial groups (Actinobacteria, Firmicutes comprised a greater proportion of the operational taxonomic units (OTUs unique to healthy samples. Diseased samples were enriched in OTUs from the families Corynebacteriaceae, Lachnospiraceae, Rhodobacteraceae, and Streptococcaceae. Much previous coral disease work has used clone libraries, which seem to be methodologically biased toward recovery of Gram-negative bacterial sequences and may therefore have missed the importance of Gram-positive groups. The PhyloChip™data presented here provide a broader characterization of the bacterial community changes that occur within Orbicella annularis during the shift from a healthy to diseased state.

  4. Optimal control and analysis of two-color genomotyping experiments using bacterial multistrain arrays

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    Ramirez Mário

    2008-05-01

    Full Text Available Abstract Background Microarray comparative genomic hybridization (aCGH evaluates the distribution of genes of sequenced bacterial strains among unsequenced strains of the same or related species. As genomic sequences from multiple strains of the same species become available, multistrain microarrays are designed, containing spots for every unique gene in all sequenced strains. To perform two-color aCGH experiments with multistrain microarrays, the choice of control sample can be the genomic DNA of one strain or a mixture of all the strains used in the array design. This important problem has no universally accepted solution. Results We performed a comparative study of the two control sample options with a Streptococcus pneumoniae microarray designed with three fully sequenced strains. We separately hybridized two of these strains (R6 and G54 as test samples using the third strain alone (TIGR4 or a mixture of the three strains as control. We show that for both types of control it is advantageous to analyze spots in separate sets according to their expected control channel signal (5–15% AUC increase. Following this analysis, the use of a mix control leads to higher accuracies (5% increase. This enhanced performance is due to gains in sensitivity (21% increase, p = 0.001 that compensate minor losses in specificity (5% decrease, p = 0.014. Conclusion The use of a single strain control increases the error rate in genes that are part of the accessory genome, where more variation across unsequenced strains is expected, further justifying the use of the mix control.

  5. Determination of the differentially expressed genes in microarray experiments using local FDR

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    Daudin J-J

    2004-09-01

    Full Text Available Abstract Background Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR, has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5% is arbitrary and a specific measure associated with each gene would be worthwhile. Results Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. Conclusions The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene or genes pertaining to the same regulation network or the same chromosomic region.

  6. Determination of the differentially expressed genes in microarray experiments using local FDR.

    Science.gov (United States)

    Aubert, J; Bar-Hen, A; Daudin, J J; Robin, S

    2004-09-06

    Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile. Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene) or genes pertaining to the same regulation network or the same chromosomic region.

  7. Performance assessment of copy number microarray platforms using a spike-in experiment

    Science.gov (United States)

    Halper-Stromberg, Eitan; Frelin, Laurence; Ruczinski, Ingo; Scharpf, Robert; Jie, Chunfa; Carvalho, Benilton; Hao, Haiping; Hetrick, Kurt; Jedlicka, Anne; Dziedzic, Amanda; Doheny, Kim; Scott, Alan F.; Baylin, Steve; Pevsner, Jonathan; Spencer, Forrest; Irizarry, Rafael A.

    2011-01-01

    Motivation: Changes in the copy number of chromosomal DNA segments [copy number variants (CNVs)] have been implicated in human variation, heritable diseases and cancers. Microarray-based platforms are the current established technology of choice for studies reporting these discoveries and constitute the benchmark against which emergent sequence-based approaches will be evaluated. Research that depends on CNV analysis is rapidly increasing, and systematic platform assessments that distinguish strengths and weaknesses are needed to guide informed choice. Results: We evaluated the sensitivity and specificity of six platforms, provided by four leading vendors, using a spike-in experiment. NimbleGen and Agilent platforms outperformed Illumina and Affymetrix in accuracy and precision of copy number dosage estimates. However, Illumina and Affymetrix algorithms that leverage single nucleotide polymorphism (SNP) information make up for this disadvantage and perform well at variant detection. Overall, the NimbleGen 2.1M platform outperformed others, but only with the use of an alternative data analysis pipeline to the one offered by the manufacturer. Availability: The data is available from http://rafalab.jhsph.edu/cnvcomp/. Contact: pevsner@jhmi.edu; fspencer@jhmi.edu; rafa@jhu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21478196

  8. Methods for interpreting lists of affected genes obstained in a DNA microarray experiment

    OpenAIRE

    Hedegaard, J.; Arce, A.M.G.; Bicciato, S.; Bonnet, A.; Buitenhuis, B.; Collado, M.C.; Conley, L.N.; San Cristobal, M.; Ferrari, F.; Garrido, J.J.; Groenen, M.A.M.; Hornshoj, H.; Hulsegge, B.; Jiang, L.; Jimenez-Marin, A.

    2009-01-01

    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 eac...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. "It wasn't a disaster or anything": Parents' experiences of their child's uncertain chromosomal microarray result.

    Science.gov (United States)

    Wilkins, Ella J; Archibald, Alison D; Sahhar, Margaret A; White, Susan M

    2016-11-01

    Chromosomal microarray is an increasingly utilized diagnostic test, particularly in the pediatric setting. However, the clinical significance of copy number variants detected by this technology is not always understood, creating uncertainties in interpreting and communicating results. The aim of this study was to explore parents' experiences of an uncertain microarray result for their child. This research utilized a qualitative approach with a phenomenological methodology. Semi-structured interviews were conducted with nine parents of eight children who received an uncertain microarray result for their child, either a 16p11.2 microdeletion or 15q13.3 microdeletion. Interviews were transcribed verbatim and thematic analysis was used to identify themes within the data. Participants were unprepared for the abnormal test result. They had a complex perception of the extent of their child's condition and a mixed understanding of the clinical relevance of the result, but were accepting of the limitations of medical knowledge, and appeared to have adapted to the result. The test result was empowering for parents in terms of access to medical and educational services; however, they articulated significant unmet support needs. Participants expressed hope for the future, in particular that more information would become available over time. This research has demonstrated that parents of children who have an uncertain microarray result appeared to adapt to uncertainty and limited availability of information and valued honesty and empathic ongoing support from health professionals. Genetic health professionals are well positioned to provide such support and aid patients' and families' adaptation to their situation as well as promote empowerment. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  12. 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.

  13. Carbohydrate microarrays

    DEFF Research Database (Denmark)

    Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola

    2012-01-01

    In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray-based technol......In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray......-based technology has been widely employed for rapid analysis of the glycan binding properties of lectins and antibodies, the quantitative measurements of glycan-protein interactions, detection of cells and pathogens, identification of disease-related anti-glycan antibodies for diagnosis, and fast assessment...

  14. Bacterial disease management: challenges, experience, innovation and future prospects: Challenges in Bacterial Molecular Plant Pathology.

    Science.gov (United States)

    Sundin, George W; Castiblanco, Luisa F; Yuan, Xiaochen; Zeng, Quan; Yang, Ching-Hong

    2016-12-01

    Plant diseases caused by bacterial pathogens place major constraints on crop production and cause significant annual losses on a global scale. The attainment of consistent effective management of these diseases can be extremely difficult, and management potential is often affected by grower reliance on highly disease-susceptible cultivars because of consumer preferences, and by environmental conditions favouring pathogen development. New and emerging bacterial disease problems (e.g. zebra chip of potato) and established problems in new geographical regions (e.g. bacterial canker of kiwifruit in New Zealand) grab the headlines, but the list of bacterial disease problems with few effective management options is long. The ever-increasing global human population requires the continued stable production of a safe food supply with greater yields because of the shrinking areas of arable land. One major facet in the maintenance of the sustainability of crop production systems with predictable yields involves the identification and deployment of sustainable disease management solutions for bacterial diseases. In addition, the identification of novel management tactics has also come to the fore because of the increasing evolution of resistance to existing bactericides. A number of central research foci, involving basic research to identify critical pathogen targets for control, novel methodologies and methods of delivery, are emerging that will provide a strong basis for bacterial disease management into the future. Near-term solutions are desperately needed. Are there replacement materials for existing bactericides that can provide effective disease management under field conditions? Experience should inform the future. With prior knowledge of bactericide resistance issues evolving in pathogens, how will this affect the deployment of newer compounds and biological controls? Knowledge is critical. A comprehensive understanding of bacterial pathosystems is required to not

  15. 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.

  16. A wavelet-based Markov random field segmentation model in segmenting microarray experiments.

    Science.gov (United States)

    Athanasiadis, Emmanouil; Cavouras, Dionisis; Kostopoulos, Spyros; Glotsos, Dimitris; Kalatzis, Ioannis; Nikiforidis, George

    2011-12-01

    In the present study, an adaptation of the Markov Random Field (MRF) segmentation model, by means of the stationary wavelet transform (SWT), applied to complementary DNA (cDNA) microarray images is proposed (WMRF). A 3-level decomposition scheme of the initial microarray image was performed, followed by a soft thresholding filtering technique. With the inverse process, a Denoised image was created. In addition, by using the Amplitudes of the filtered wavelet Horizontal and Vertical images at each level, three different Magnitudes were formed. These images were combined with the Denoised one to create the proposed SMRF segmentation model. For numerical evaluation of the segmentation accuracy, the segmentation matching factor (SMF), the Coefficient of Determination (r(2)), and the concordance correlation (p(c)) were calculated on the simulated images. In addition, the SMRF performance was contrasted to the Fuzzy C Means (FCM), Gaussian Mixture Models (GMM), Fuzzy GMM (FGMM), and the conventional MRF techniques. Indirect accuracy performances were also tested on the experimental images by means of the Mean Absolute Error (MAE) and the Coefficient of Variation (CV). In the latter case, SPOT and SCANALYZE software results were also tested. In the former case, SMRF attained the best SMF, r(2), and p(c) (92.66%, 0.923, and 0.88, respectively) scores, whereas, in the latter case scored MAE and CV, 497 and 0.88, respectively. The results and support the performance superiority of the SMRF algorithm in segmenting cDNA images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  17. 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

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

    Science.gov (United States)

    Kitchen, Robert R; Sabine, Vicky S; Simen, Arthur A; Dixon, J Michael; Bartlett, John M S; Sims, Andrew H

    2011-12-01

    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. 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 dependent 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. The magnitude of systematic processing noise in a microarray experiment is variable

  19. Design and validation of a DNA-microarray for phylogenetic analysis of bacterial communities in different oral samples and dental implants.

    Science.gov (United States)

    Parolin, Carola; Giordani, Barbara; Ñahui Palomino, Rogers Alberto; Biagi, Elena; Severgnini, Marco; Consolandi, Clarissa; Caredda, Giada; Storelli, Stefano; Strohmenger, Laura; Vitali, Beatrice

    2017-07-24

    The quali-quantitative characterization of the oral microbiota is crucial for an exhaustive knowledge of the oral ecology and the modifications of the microbial composition that occur during periodontal pathologies. In this study, we designed and validated a new phylogenetic DNA-microarray (OralArray) to quickly and reliably characterize the most representative bacterial groups that colonize the oral cavity. The OralArray is based on the Ligation Detection Reaction technology associated to Universal Arrays (LDR-UA), and includes 22 probe sets targeted to bacteria belonging to the phyla Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, and Spirochaete. The tool is characterized by high specificity, sensitivity and reproducibility. The OralArray was successfully tested and validated on different oral samples (saliva, lingual plaque, supragingival plaque, and healing cap) collected from 10 healthy subjects. For each specimen, a microbial signature was obtained, and our results established the presence of an oral microbial profile specific for each subject. Moreover, the tool was applied to evaluate the efficacy of a disinfectant treatment on the healing caps before their usage. The OralArray is, thus, suitable to study the microbiota associated with various oral sites and to monitor changes arising from therapeutic treatments.

  20. DNA Microarray Technology; TOPICAL

    International Nuclear Information System (INIS)

    WERNER-WASHBURNE, MARGARET; DAVIDSON, GEORGE S.

    2002-01-01

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

  1. 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.

  2. 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…

  3. The Stanford Microarray Database

    Science.gov (United States)

    Sherlock, Gavin; Hernandez-Boussard, Tina; Kasarskis, Andrew; Binkley, Gail; Matese, John C.; Dwight, Selina S.; Kaloper, Miroslava; Weng, Shuai; Jin, Heng; Ball, Catherine A.; Eisen, Michael B.; Spellman, Paul T.; Brown, Patrick O.; Botstein, David; Cherry, J. Michael

    2001-01-01

    The Stanford Microarray Database (SMD) stores raw and normalized data from microarray experiments, and provides web interfaces for researchers to retrieve, analyze and visualize their data. The two immediate goals for SMD are to serve as a storage site for microarray data from ongoing research at Stanford University, and to facilitate the public dissemination of that data once published, or released by the researcher. Of paramount importance is the connection of microarray data with the biological data that pertains to the DNA deposited on the microarray (genes, clones etc.). SMD makes use of many public resources to connect expression information to the relevant biology, including SGD [Ball,C.A., Dolinski,K., Dwight,S.S., Harris,M.A., Issel-Tarver,L., Kasarskis,A., Scafe,C.R., Sherlock,G., Binkley,G., Jin,H. et al. (2000) Nucleic Acids Res., 28, 77–80], YPD and WormPD [Costanzo,M.C., Hogan,J.D., Cusick,M.E., Davis,B.P., Fancher,A.M., Hodges,P.E., Kondu,P., Lengieza,C., Lew-Smith,J.E., Lingner,C. et al. (2000) Nucleic Acids Res., 28, 73–76], Unigene [Wheeler,D.L., Chappey,C., Lash,A.E., Leipe,D.D., Madden,T.L., Schuler,G.D., Tatusova,T.A. and Rapp,B.A. (2000) Nucleic Acids Res., 28, 10–14], dbEST [Boguski,M.S., Lowe,T.M. and Tolstoshev,C.M. (1993) Nature Genet., 4, 332–333] and SWISS-PROT [Bairoch,A. and Apweiler,R. (2000) Nucleic Acids Res., 28, 45–48] and can be accessed at http://genome-www.stanford.edu/microarray. PMID:11125075

  4. [Non-bacterial chronic osteomyelitis: Experience in a tertiary hospital].

    Science.gov (United States)

    Barral Mena, Estefanía; Freire Gómez, Xabier; Enríquez Merayo, Eugenia; Casado Picón, Rocío; Bello Gutierrez, Pablo; de Inocencio Arocena, Jaime

    2016-07-01

    Non-bacterial chronic osteomyelitis (NBCO) is an autoinflammatory disease that presents with recurrent bouts of bone inflammation in the absence of microbiological isolation. It is a diagnosis of exclusion. Its treatment was classically based on the use of non-steroidal anti-inflammatory drugs (NSAIDs) and corticosteroids, although nowadays bisphosphonates or anti-tumour necrosis factor-α (anti-TNF) drugs are frequently used with good results. The objective of the study is to describe our experience in the diagnosis and treatment of patients with NBCO. Retrospective chart review of patients with NBCO followed up in a tertiary centre between 2008 and 2015. A total of 7 patients with NBCO were recorded. Four were female and the median age was 10 years (IQR 2). The most common complaint was pain that interfered with sleep in 5 of the patients. Six patients had multifocal lesions at diagnosis. Bone biopsy demonstrated neutrophilic or lymphocytic infiltration and sclerosis in 6 patients. Four patients received antibiotics and NSAIDs without clinical response. Five received a short course of prednisone with an adequate control of symptoms, but only one of them maintained remission after corticosteroid suspension. Five patients received bisphosphonates with disease remission in 3 of them. The other 2 showed an inadequate response to pamidronate and were started on anti-TNF therapy (etanercept, infliximab or adalimumab), remaining asymptomatic at present. Our series, although limited, confirms the effectiveness and safety of bisphosphonate and anti-TNF therapy for children with NBCO. Copyright © 2015 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

  5. 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.

  6. A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

    Directory of Open Access Journals (Sweden)

    Vassal Aurélien

    2008-01-01

    Full Text Available Abstract Background The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix® technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM patients. Results After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM. Conclusion This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with

  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. 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...... from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using...

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

    Science.gov (United States)

    Bilardi, Jade E; Walker, Sandra; Temple-Smith, Meredith; McNair, Ruth; Mooney-Somers, Julie; Bellhouse, Clare; Fairley, Christopher K; Chen, Marcus Y; Bradshaw, Catriona

    2013-01-01

    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. 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. 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. 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 managing women with recurrent bacterial vaginosis.

  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. Identification of Common Bacterial Antigenic Markers From Bovine Digital Dermatitis Lesions Using Meta-Transcriptomics in Combination With High-Density Peptide-Microarrays

    DEFF Research Database (Denmark)

    Nielsen, Martin W.; Marcatili, Paoli; Sicheritz-Ponten, Thomas

    of collagenous and connective tissues. Multiple Treponema species, many of which are not-yet-cultivable, are strongly implicated in disease progression. Despite the economic and welfare importance of this disease, no effective vaccine is available; and there is presently very little knowledge concerning...... efficacious immunoprophylactic antigens against DD. It is highly likely that DD-associated treponemes possess considerable antigenic variation, as cows exhibit a variable humoral response against different isolates of Treponema. Hence, combinations of antigens from multiple Treponema species should be used...... response directed at the site of infection. By metatranscriptomics we measured the in situ genome-wide transcriptome of the bacterial population in DD-affected skin lesions from 21 dairy cows. From the transcriptome data, we identified a panel of Treponema genes that were highly expressed in multiple...

  12. miRNAs in lung cancer - Studying complex fingerprints in patient's blood cells by microarray experiments

    International Nuclear Information System (INIS)

    Keller, Andreas; Leidinger, Petra; Borries, Anne; Wendschlag, Anke; Wucherpfennig, Frank; Scheffler, Matthias; Huwer, Hanno; Lenhof, Hans-Peter; Meese, Eckart

    2009-01-01

    Deregulated miRNAs are found in cancer cells and recently in blood cells of cancer patients. Due to their inherent stability miRNAs may offer themselves for blood based tumor diagnosis. Here we addressed the question whether there is a sufficient number of miRNAs deregulated in blood cells of cancer patients to be able to distinguish between cancer patients and controls. We synthesized 866 human miRNAs and miRNA star sequences as annotated in the Sanger miRBase onto a microarray designed by febit biomed gmbh. Using the fully automated Geniom Real Time Analyzer platform, we analyzed the miRNA expression in 17 blood cell samples of patients with non-small cell lung carcinomas (NSCLC) and in 19 blood samples of healthy controls. Using t-test, we detected 27 miRNAs significantly deregulated in blood cells of lung cancer patients as compared to the controls. Some of these miRNAs were validated using qRT-PCR. To estimate the value of each deregulated miRNA, we grouped all miRNAs according to their diagnostic information that was measured by Mutual Information. Using a subset of 24 miRNAs, a radial basis function Support Vector Machine allowed for discriminating between blood cellsamples of tumor patients and controls with an accuracy of 95.4% [94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a sensitivity of 92.5% [91.8%-92.5%]. Our findings support the idea that neoplasia may lead to a deregulation of miRNA expression in blood cells of cancer patients compared to blood cells of healthy individuals. Furthermore, we provide evidence that miRNA patterns can be used to detect human cancers from blood cells

  13. Nitrogen fertilization decreases forest soil fungal and bacterial biomass in three long-term experiments

    Science.gov (United States)

    Matthew D. Wallenstein; Steven McNulty; Ivan J. Fernandez; Johnny Boggs; William H. Schlesinger

    2006-01-01

    We examined the effects of N fertilization on forest soil fungal and bacterial biomass at three long-term experiments in New England (Harvard Forest, MA; Mt. Ascutney, VT; Bear Brook, ME). At Harvard Forest, chronic N fertilization has decreased organic soil microbial biomass C (MBC) by an average of 54% and substrate induced respiration (SIR) was decreased by an...

  14. Compressive Sensing DNA Microarrays

    Directory of Open Access Journals (Sweden)

    Sheikh Mona A

    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.

  15. Annotating breast cancer microarray samples using ontologies

    Science.gov (United States)

    Liu, Hongfang; Li, Xin; Yoon, Victoria; Clarke, Robert

    2008-01-01

    As the most common cancer among women, breast cancer results from the accumulation of mutations in essential genes. Recent advance in high-throughput gene expression microarray technology has inspired researchers to use the technology to assist breast cancer diagnosis, prognosis, and treatment prediction. However, the high dimensionality of microarray experiments and public access of data from many experiments have caused inconsistencies which initiated the development of controlled terminologies and ontologies for annotating microarray experiments, such as the standard microarray Gene Expression Data (MGED) ontology (MO). In this paper, we developed BCM-CO, an ontology tailored specifically for indexing clinical annotations of breast cancer microarray samples from the NCI Thesaurus. Our research showed that the coverage of NCI Thesaurus is very limited with respect to i) terms used by researchers to describe breast cancer histology (covering 22 out of 48 histology terms); ii) breast cancer cell lines (covering one out of 12 cell lines); and iii) classes corresponding to the breast cancer grading and staging. By incorporating a wider range of those terms into BCM-CO, we were able to indexed breast cancer microarray samples from GEO using BCM-CO and MGED ontology and developed a prototype system with web interface that allows the retrieval of microarray data based on the ontology annotations. PMID:18999108

  16. A method of microarray data storage using array data type.

    Science.gov (United States)

    Tsoi, Lam C; Zheng, W Jim

    2007-04-01

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

  17. 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

  18. DNA Microarray Technology

    Science.gov (United States)

    ... this page. En Español: Tecnología de micromatriz de ADN DNA Microarray Technology What is a DNA microarray? ... this page. En Español: Tecnología de micromatriz de ADN Get Email Updates Privacy Copyright Contact Accessibility Plug- ...

  19. 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.

  20. 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

  1. 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,…

  2. porewater chemistry experiment at Mont Terri rock laboratory. Reactive transport modelling including bacterial activity

    International Nuclear Information System (INIS)

    Tournassat, Christophe; Gaucher, Eric C.; Leupin, Olivier X.; Wersin, Paul

    2010-01-01

    Document available in extended abstract form only. An in-situ test in the Opalinus Clay formation, termed pore water Chemistry (PC) experiment, was run for a period of five years. It was based on the concept of diffusive equilibration whereby traced water with a composition close to that expected in the formation was continuously circulated and monitored in a packed off borehole. The main original focus was to obtain reliable data on the pH/pCO 2 of the pore water, but because of unexpected microbially- induced redox reactions, the objective was then changed to elucidate the biogeochemical processes happening in the borehole and to understand their impact on pH/pCO 2 and pH in the low permeability clay formation. The biologically perturbed chemical evolution of the PC experiment was simulated with reactive transport models. The aim of this modelling exercise was to develop a 'minimal-' model able to reproduce the chemical evolution of the PC experiment, i.e. the chemical evolution of solute inorganic and organic compounds (organic carbon, dissolved inorganic carbon etc...) that are coupled with each other through the simultaneous occurrence of biological transformation of solute or solid compounds, in-diffusion and out-diffusion of solute species and precipitation/dissolution of minerals (in the borehole and in the formation). An accurate description of the initial chemical conditions in the surrounding formation together with simplified kinetics rule mimicking the different phases of bacterial activities allowed reproducing the evolution of all main measured parameters (e.g. pH, TOC). Analyses from the overcoring and these simulations evidence the high buffer capacity of Opalinus clay regarding chemical perturbations due to bacterial activity. This pH buffering capacity is mainly attributed to the carbonate system as well as to the clay surfaces reactivity. Glycerol leaching from the pH-electrode might be the primary organic source responsible for

  3. Nanotechnologies in protein microarrays.

    Science.gov (United States)

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

    2015-01-01

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

  4. Clustering in community structure across replicate ecosystems following a long-term bacterial evolution experiment.

    Science.gov (United States)

    Celiker, Hasan; Gore, Jeff

    2014-08-08

    Experiments to date probing adaptive evolution have predominantly focused on studying a single species or a pair of species in isolation. In nature, on the other hand, species evolve within complex communities, interacting and competing with many other species. It is unclear how reproducible or predictable adaptive evolution is within the context of a multispecies ecosystem. To explore this problem, we let 96 replicates of a multispecies laboratory bacterial ecosystem evolve in parallel for hundreds of generations. Here we find that relative abundances of individual species vary greatly across the evolved ecosystems and that the final profile of species frequencies within replicates clusters into several distinct types, as opposed to being randomly dispersed across the frequency space or converging fully. Our results suggest that community structure evolution has a tendency to follow one of only a few distinct paths.

  5. Development of a Digital Microarray with Interferometric Reflectance Imaging

    Science.gov (United States)

    Sevenler, Derin

    This dissertation describes a new type of molecular assay for nucleic acids and proteins. We call this technique a digital microarray since it is conceptually similar to conventional fluorescence microarrays, yet it performs enumerative ('digital') counting of the number captured molecules. Digital microarrays are approximately 10,000-fold more sensitive than fluorescence microarrays, yet maintain all of the strengths of the platform including low cost and high multiplexing (i.e., many different tests on the same sample simultaneously). Digital microarrays use gold nanorods to label the captured target molecules. Each gold nanorod on the array is individually detected based on its light scattering, with an interferometric microscopy technique called SP-IRIS. Our optimized high-throughput version of SP-IRIS is able to scan a typical array of 500 spots in less than 10 minutes. Digital DNA microarrays may have utility in applications where sequencing is prohibitively expensive or slow. As an example, we describe a digital microarray assay for gene expression markers of bacterial drug resistance.

  6. Characterization of probiotic Escherichia coli isolates with a novel pan-genome microarray

    DEFF Research Database (Denmark)

    Willenbrock, Hanni; Hallin, Peter Fischer; Wassenaar, Trudy

    2007-01-01

    Background: Microarrays have recently emerged as a novel procedure to evaluate the genetic content of bacterial species. So far, microarrays have mostly covered single or few strains from the same species. However, with cheaper high-throughput sequencing techniques emerging, multiple strains of t...

  7. "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.

  8. Robust Microarray Image Processing

    OpenAIRE

    Novikov, Eugene; Barillot, Emmanuel

    2007-01-01

    In this work we have presented a complete solution for robust, high-throughput, two-color microarray image processing comprising procedures for automatic spot localization, spot quantification and spot quality control. The spot localization algorithm is fully automatic and robust with respect to deviations from perfect spot alignment and contamination. As an input, it requires only the common array design parameters: number of blocks and number of spots in the x and y directions of the array....

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

    Science.gov (United States)

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

    2014-08-04

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

  10. Polysaccharide Microarray Technology for the Detection of Burkholderia Pseudomallei and Burkholderia Mallei Antibodies

    National Research Council Canada - National Science Library

    Parthasarathy, Narayanan; DeShazer, David; England, Marilyn; Waag, David M

    2006-01-01

    .... This polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray technology over the current serodiagnosis of the above bacterial infections were discussed.

  11. Computational biology of genome expression and regulation--a review of microarray bioinformatics.

    Science.gov (United States)

    Wang, Junbai

    2008-01-01

    Microarray technology is being used widely in various biomedical research areas; the corresponding microarray data analysis is an essential step toward the best utilizing of array technologies. Here we review two components of the microarray data analysis: a low level of microarray data analysis that emphasizes the designing, the quality control, and the preprocessing of microarray experiments, then a high level of microarray data analysis that focuses on the domain-specific microarray applications such as tumor classification, biomarker prediction, analyzing array CGH experiments, and reverse engineering of gene expression networks. Additionally, we will review the recent development of building a predictive model in genome expression and regulation studies. This review may help biologists grasp a basic knowledge of microarray bioinformatics as well as its potential impact on the future evolvement of biomedical research fields.

  12. A coexisting fungal-bacterial community stabilizes soil decomposition activity in a microcosm experiment.

    Directory of Open Access Journals (Sweden)

    Masayuki Ushio

    Full Text Available How diversity influences the stability of a community function is a major question in ecology. However, only limited empirical investigations of the diversity-stability relationship in soil microbial communities have been undertaken, despite the fundamental role of microbial communities in driving carbon and nutrient cycling in terrestrial ecosystems. In this study, we conducted a microcosm experiment to investigate the relationship between microbial diversity and stability of soil decomposition activities against changes in decomposition substrate quality by manipulating microbial community using selective biocides. We found that soil respiration rates and degradation enzyme activities by a coexisting fungal and bacterial community (a taxonomically diverse community are more stable against changes in substrate quality (plant leaf materials than those of a fungi-dominated or a bacteria-dominated community (less diverse community. Flexible changes in the microbial community composition and/or physiological state in the coexisting community against changes in substrate quality, as inferred by the soil lipid profile, may be the mechanism underlying this positive diversity-stability relationship. Our experiment demonstrated that the previously found positive diversity-stability relationship could also be valid in the soil microbial community. Our results also imply that the functional/taxonomic diversity and community ecology of soil microbes should be incorporated into the context of climate-ecosystem feedbacks. Changes in substrate quality, which could be induced by climate change, have impacts on decomposition process and carbon dioxide emission from soils, but such impacts may be attenuated by the functional diversity of soil microbial communities.

  13. 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, antibody agglutination test, and PCR analysis. Phase variation was observed by baterial motility assay and identified by antibody agglutination test and PCR analysis. This comprehensive experiment can be performed to help students improve their ability to use the knowledge acquired in Biochemistry and Molecular Biology. Copyright © 2014 by The International Union of Biochemistry and Molecular Biology.

  14. MicroarrayDesigner: an online search tool and repository for near-optimal microarray experimental designs.

    Science.gov (United States)

    Sacan, Ahmet; Ferhatosmanoglu, Nilgun; Ferhatosmanoglu, Hakan

    2009-09-22

    Dual-channel microarray experiments are commonly employed for inference of differential gene expressions across varying organisms and experimental conditions. The design of dual-channel microarray experiments that can help minimize the errors in the resulting inferences has recently received increasing attention. However, a general and scalable search tool and a corresponding database of optimal designs were still missing. An efficient and scalable search method for finding near-optimal dual-channel microarray designs, based on a greedy hill-climbing optimization strategy, has been developed. It is empirically shown that this method can successfully and efficiently find near-optimal designs. Additionally, an improved interwoven loop design construction algorithm has been developed to provide an easily computable general class of near-optimal designs. Finally, in order to make the best results readily available to biologists, a continuously evolving catalog of near-optimal designs is provided. A new search algorithm and database for near-optimal microarray designs have been developed. The search tool and the database are accessible via the World Wide Web at http://db.cse.ohio-state.edu/MicroarrayDesigner. Source code and binary distributions are available for academic use upon request.

  15. MicroarrayDesigner: an online search tool and repository for near-optimal microarray experimental designs

    Directory of Open Access Journals (Sweden)

    Ferhatosmanoglu Nilgun

    2009-09-01

    Full Text Available Abstract Background Dual-channel microarray experiments are commonly employed for inference of differential gene expressions across varying organisms and experimental conditions. The design of dual-channel microarray experiments that can help minimize the errors in the resulting inferences has recently received increasing attention. However, a general and scalable search tool and a corresponding database of optimal designs were still missing. Description An efficient and scalable search method for finding near-optimal dual-channel microarray designs, based on a greedy hill-climbing optimization strategy, has been developed. It is empirically shown that this method can successfully and efficiently find near-optimal designs. Additionally, an improved interwoven loop design construction algorithm has been developed to provide an easily computable general class of near-optimal designs. Finally, in order to make the best results readily available to biologists, a continuously evolving catalog of near-optimal designs is provided. Conclusion A new search algorithm and database for near-optimal microarray designs have been developed. The search tool and the database are accessible via the World Wide Web at http://db.cse.ohio-state.edu/MicroarrayDesigner. Source code and binary distributions are available for academic use upon request.

  16. Epidemiology and outcomes of bacterial meningitis in Mexican children: 10-year experience (1993-2003).

    Science.gov (United States)

    Franco-Paredes, Carlos; Lammoglia, Lorena; Hernández, Isabel; Santos-Preciado, José Ignacio

    2008-07-01

    Acute bacterial meningitis remains an important cause of morbidity, neurologic sequelae, and mortality in children in Latin America. We retrospectively reviewed the hospital-based medical records of children diagnosed with acute bacterial meningitis, aged 1 month to 18 years, at a large inner city referral Hospital in Mexico City, for a 10-year period (1993-2003). To characterize the epidemiology, clinical features, and outcomes of acute bacterial meningitis, we subdivided our study into two time periods: the period prior to the routine use of Haemophilus influenzae type b (Hib) vaccine (1993-1998) and the period after the vaccine became available (1999-2003). A total of 218 cases of acute bacterial meningitis were identified during the study period. The most frequently affected age group was that of children aged between 1 and 6 months. Hib was the most commonly isolated pathogen, found in 50% of cases. However, its incidence declined significantly after the introduction of the combined diphtheria, tetanus, pertussis, hepatitis B, and conjugated Hib (DTP-HB/Hib) pentavalent vaccine into the universal vaccination schedule for children in 1998. Streptococcus pneumoniae followed as the second most commonly isolated bacterial pathogen. Neisseria meningitidis was isolated in only a few cases, confirming the historically low incidence of this pathogen in Mexico. Identified risk factors for death were found to include the presence of septic shock and intracranial hypertension, but were not attributable to any particular bacterial pathogen. In our hospital, acute bacterial meningitis remains a severe disease with important sequelae and mortality. The incidence of Hib meningitis cases has declined since the introduction of the Hib vaccine. However, S. pneumoniae persists as an important cause of bacterial meningitis, highlighting the need for the implementation of vaccination policies against this pathogen.

  17. Microfluidic Methods for Protein Microarrays

    OpenAIRE

    Hartmann, Michael

    2010-01-01

    Protein microarray technology has an enormous potential for in vitro diagnostics (IVD)1. Miniaturized and parallelized immunoassays are powerful tools to measure dozens of parameters from minute amounts of sample, whilst only requiring small amounts of reagent. Protein microarrays have become well-established research tools in basic and applied research and the first diagnostic products are already released on the market. However, in order for protein microarrays to become broadly accepted to...

  18. 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

    2010-09-07

    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. 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. 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.

  19. 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.

  20. Challenges of bacterial meningitis case management in low income settings: an experience from Ethiopia.

    Science.gov (United States)

    Gudina, Esayas Kebede; Tesfaye, Markos; Adane, Aynishet; Lemma, Kinfe; Shibiru, Tamiru; Pfister, Hans-Walter; Klein, Matthias

    2016-07-01

    To investigate the current diagnostic and therapeutic strategies used in the care of patients with suspected bacterial meningitis at teaching hospitals in Ethiopia. This was a hospital-based retrospective study conducted at four teaching hospitals in different regions of Ethiopia. Participants were patients aged 14 years and older treated for suspected bacterial meningitis. Presenting complaints, diagnostic strategies used and treatments given were obtained from clinical records. A total of 425 patients were included in the study; 52.7% were men and 83.8% were younger than 50 years. Fever, headache, neck stiffness and impaired consciousness were the most common clinical presentations; 55.5% underwent lumbar puncture. Overall, only 96 (22.6%) patients had cerebrospinal fluid abnormalities compatible with bacterial meningitis. A causative bacterium was identified in only 14 cases. Ceftriaxone was used as the empiric treatment of choice, either alone or in combination with other antibiotics; 17.6% of patients were also given vancomycin. Adjunctive dexamethasone was given to 50.4%. Most patients treated as bacterial meningitis did not receive a proper diagnostic workup. The choice of antibiotic was not tailored to the specific clinical condition of the patient. Such an approach may result in poor treatment outcomes and lead to antibiotic resistance. Management of patients with suspected bacterial meningitis should be supported by analysis of cerebrospinal fluid, and treatment should be tailored to local evidence and current evidence-based recommendations. © 2016 John Wiley & Sons Ltd.

  1. 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.

  2. 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.

  3. DNA microarrays : a molecular cloning manual

    National Research Council Canada - National Science Library

    Sambrook, Joseph; Bowtell, David

    2002-01-01

    .... DNA Microarrays provides authoritative, detailed instruction on the design, construction, and applications of microarrays, as well as comprehensive descriptions of the software tools and strategies...

  4. 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

    . As predicted, the total number of viral populations was the same in all treatments, while the composition of the viral community varied. Our results support the theoretical prediction that there is one control mechanism for the number of niches for coexisting virus-host pairs (top-down control), and another......We demonstrate here results showing that bottom-up and top-down control mechanisms can operate simultaneously and in concert in marine microbial food webs, controlling prokaryote diversity by a combination of viral lysis and substrate limitation. Models in microbial ecology predict that a shift...... in the type of bacterial growth rate limitation is expected to have a major effect on species composition within the community of bacterial hosts, with a subsequent shift in the composition of the viral community. Only moderate effects would, however, be expected in the absolute number of coexisting virus...

  5. Microarray platform for omics analysis

    Science.gov (United States)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

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

  6. 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

  7. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

    Science.gov (United States)

    Li, Xuehua; Shu, Lan

    2008-01-01

    Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE) is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE's KNN algorithm. In addition, kernel method based support vector machine (SVM) will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method. PMID:27879930

  8. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray.

    Science.gov (United States)

    Li, Xuehua; Shu, Lan

    2008-07-15

    Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE) is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE's KNN algorithm. In addition, kernel method based support vector machine (SVM) will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

  9. Laser direct writing of biomolecule microarrays

    Science.gov (United States)

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

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

  10. Initial Therapy of Bacterial Meningitis with Cefuroxime: Experience in 167 Children

    Directory of Open Access Journals (Sweden)

    Lissette Navas

    1992-01-01

    Full Text Available The morbidity and mortality of patients with bacterial meningitis treated initially with cefuroxime were studied and compared with the results of a previous prospective study of patients treated initially with ampicillin plus chloramphenicol in the same institution from 1979 to 1983. A retrospective chart review was completed in all cases of microbiologically confirmed bacterial meningitis admitted to the Hospital for Sick Children in Toronto, Ontario between January 1, 1984 and August 1, 1988. During this period all patients were treated initially with intravenous cefuroxime. The 167 children reviewed ranged in age from six weeks to 17.1 years (median 11.6 months. The case fatality rate was 7.8% and the rate of hearing deficit 13%. There were no statistically significant differences in abnormal neurological outcome (20 versus 20%, respectively, hearing loss (12.9 versus 13%, respectively, and case fatality rate (6.4 versus 7.8%, respectively between the cohort of 1979–83 and the present study. The rate of hearing loss following meningitis caused by Haemophilus influenzae type b increased from 7.3 to 11.7% (P=0.26.

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

    Science.gov (United States)

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

    2013-01-01

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

  12. Analyzing microarray data using quantitative association rules.

    Science.gov (United States)

    Georgii, Elisabeth; Richter, Lothar; Rückert, Ulrich; Kramer, Stefan

    2005-09-01

    We tackle the problem of finding regularities in microarray data. Various data mining tools, such as clustering, classification, Bayesian networks and association rules, have been applied so far to gain insight into gene-expression data. Association rule mining techniques used so far work on discretizations of the data and cannot account for cumulative effects. In this paper, we investigate the use of quantitative association rules that can operate directly on numeric data and represent cumulative effects of variables. Technically speaking, this type of quantitative association rules based on half-spaces can find non-axis-parallel regularities. We performed a variety of experiments testing the utility of quantitative association rules for microarray data. First of all, the results should be statistically significant and robust against fluctuations in the data. Next, the approach should be scalable in the number of variables, which is important for such high-dimensional data. Finally, the rules should make sense biologically and be sufficiently different from rules found in regular association rule mining working with discretizations. In all of these dimensions, the proposed approach performed satisfactorily. Therefore, quantitative association rules based on half-spaces should be considered as a tool for the analysis of microarray gene-expression data. The code is available from the authors on request.

  13. Metadata management and semantics in microarray repositories.

    Science.gov (United States)

    Kocabaş, F; Can, T; Baykal, N

    2011-12-01

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

  14. [DNA microarrays and their application in detecting and identifying intestinal pathogens].

    Science.gov (United States)

    Jin, Da-Zhi; Wen, Si-Yuan; Wang, Sheng-Qi

    2006-06-01

    DNA microarrays offer many advantages of high throughout, automation, rapid detection, and so on. Therefore, this technology had been used in many fields such as molecular epidemiology of bacteria, microbial gene identification, disease mechanism, gene mutation, gene expression identification, DNA sequencing and medicine screening etc. The assays for identifying pathogens using DNA microarrays reported aboard recently are introduced. The application of DNA microarrays in detecting and identifying intestinal pathogens mainly includes three aspects: the identification of toxin and characteristic genes of pathogens, the identification of bacterial DNA or RNA directly, the simultaneous detection of a large number of intestinal pathogens with the target - gene of ribosomal RNA. Because of its high efficiency, DNA microarrays is superior to other biological method. Obviously DNA microarrays technology may be useful in identifying intestinal pathogens and have a wide prospect.

  15. Relationship of nutrient dynamics and bacterial community structure at the water-sediment interface using a benthic chamber experiment.

    Science.gov (United States)

    Ki, Bo-Min; Huh, In Ae; Choi, Jung-Hyun; Cho, Kyung-Suk

    2018-01-05

    The relationships between nutrient dynamics and the bacterial community at the water-sediment interface were investigated using the results of nutrient release fluxes, bacterial communities examined by 16S rRNA pyrosequencing and canonical correlation analysis (CCA) accompanied by lab-scale benthic chamber experiment. The nutrient release fluxes from the sediments into the water were as follows: -3.832 to 12.157 mg m -2 d -1 for total phosphorus, 0.049 to 9.993 mg m -2 d -1 for PO 4 -P, -2.011 to 41.699 mg m -2 d -1 for total nitrogen, -7.915 to -0.074 mg m -2 d -1 for NH 3 -N, and -17.940 to 1.209 mg m -2 d -1 for NO 3 -N. To evaluate the relationship between the bacterial communities and environmental variables, CCA was conducted in three representative conditions: in the overlying water, in the sediment at a depth of 0-5 cm, and in the sediment at a depth of 5-15 cm. CCA results showed that environmental variables such as nutrient release fluxes (TN, NH 4 , NO 3 , TP, and PO 4 ) and water chemical parameters (pH, DO, COD, and temperature) were highly correlated with the bacterial communities. From the results of the nutrient release fluxes and the bacterial community, this study proposed the hypothesis for bacteria involved in the nutrient dynamics at the interface between water and sediment. In the sediment, sulfate-reducing bacteria (SRB) such as Desulfatibacillum, Desulfobacterium, Desulfomicrobium, and Desulfosalsimonas are expected to contribute to the decomposition of organic matter, and release of ammonia (NH 4 + ) and phosphate (PO 4 3- ). The PO 4 3- released into the water layer was observed by the positive fluxes of PO 4 3- . The NH 4 + released from the sediment was rapidly oxidized by the methane-oxidizing bacteria (MOB). This study observed in the water layer dominantly abundant MOB of Methylobacillus, Methylobacter, Methylocaldum, and Methylophilus. The nitrate (NO 3 - ) accumulation caused by the oxidation environment of the water layer

  16. 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.

  17. Emerging use of gene expression microarrays in plant physiology.

    Science.gov (United States)

    Wullschleger, Stan D; Difazio, Stephen P

    2003-01-01

    Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

  18. 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.

  19. Melody pulmonary valve bacterial endocarditis: experience in four pediatric patients and a review of the literature.

    Science.gov (United States)

    Villafañe, Juan; Baker, George Hamilton; Austin, Erle H; Miller, Stephen; Peng, Lynn; Beekman, Robert

    2014-08-01

    The objectives of this manuscript are two-fold: (a) to describe the clinical characteristics and management of four pediatric patients with bacterial endocarditis (BE) after Melody pulmonary valve implantation (MPVI); and (b) to review the literature regarding Melody pulmonary valve endocarditis. There are several reports of BE following MPVI. The clinical course, BE management and outcome remain poorly defined. This is a multi-center report of four pediatric patients with repaired tetralogy of Fallot (TOF) and BE after MPVI. Clinical presentation, echocardiogram findings, infecting organism, BE management, and follow-up assessment are described. We review available literature on Melody pulmonary valve endocarditis and discuss the prognosis and challenges in the management of these patients. Of our four BE patients, two had documented vegetations and three showed worsening pulmonary stenosis. All patients remain asymptomatic after medical treatment (4) and surgical prosthesis replacement (3) at follow-up of 17 to 40 months. Analysis of published data shows that over half of patients undergo bioprosthesis explantation and that there is a 13% overall mortality. The most common BE pathogens are the Staphylococcus and Streptococcus species. Our case series of four pediatric patients with repaired TOF confirms a risk for BE after MPVI. A high index of suspicion for BE should be observed after MPVI. All patients should be advised to follow lifelong BE prophylaxis after MPVI. In case of BE, surgery should be considered for valve dysfunction or no clinical improvement in spite of medical treatment. © 2014 Wiley Periodicals, Inc.

  20. Ceftaroline fosamil and treatment of acute bacterial skin and skin structure infections: CAPTURE study experience.

    Science.gov (United States)

    Santos, Paul D; Davis, Amanda; Jandourek, Alena; Smith, Alexander; David Friedland, H

    2013-12-01

    The Clinical Assessment Program and TEFLARO Utilization Registry (CAPTURE) is a multicentre retrospective cohort study in the USA describing treatment of acute bacterial skin and skin structure infection (ABSSSI) with ceftaroline fosamil (CPT-F). Charts for review were chosen by random selection. Among 647 evaluable patients, 52% were obese, 46% had diabetes mellitus (DM), and 19% had peripheral vascular disease (PVD). Methicillin-resistant Staphylococcus aureus (MRSA) was recovered in 28% and methicillin-susceptible S. aureus (MSSA), 11%. Antibiotics were administered prior to CPT-F treatment in 80%, and concurrently in 39%. Clinical success overall was 85%; in patients with DM, 83%; with PVD, 76%; and in obese patients, 88%. Clinical success was ≥ 79% across all infection types; 81% for MRSA and 83% for MSSA; and 86% for ceftaroline monotherapy and 84% for concurrent therapy. These high clinical success rates support CPT-F as an effective treatment option for ABSSSI, including infections due to MRSA and patients with significant co-morbidities.

  1. Small intestine bacterial overgrowth and irritable bowel syndrome-related symptoms: experience with Rifaximin.

    Science.gov (United States)

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

    2009-06-07

    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. Our survey included 115 patients fulfilling the Rome II criteria for diagnosis of irritable bowel syndrome (IBS); a total of 97 patients accepted to perform a breath test with lactulose (BTLact), and those who had a positive test, received Rifaximin (Normix, Alfa Wassermann) 1200 mg/d for 7 d; 3 wk after the end of treatment, the BTLact was repeated. Based on the BTLact results, SIBO was present in about 56% of IBS patients, and it was responsible for some IBS-related symptoms, such as abdominal bloating and discomfort, and diarrhoea. 1-wk treatment with Rifaximin turned the BTLact to negative in about 50% of patients and significantly reduced the symptoms, especially in those patients with an alternated constipation/diarrhoea-variant IBS. SIBO should be always suspected in patients with IBS, and a differential diagnosis is done by means of a "breath test". Rifaximin may represent a valid approach to the treatment of SIBO.

  2. Linking probe thermodynamics to microarray quantification

    International Nuclear Information System (INIS)

    Li, Shuzhao; Pozhitkov, Alexander; Brouwer, Marius

    2010-01-01

    Understanding the difference in probe properties holds the key to absolute quantification of DNA microarrays. So far, Langmuir-like models have failed to link sequence-specific properties to hybridization signals in the presence of a complex hybridization background. Data from washing experiments indicate that the post-hybridization washing has no major effect on the specifically bound targets, which give the final signals. Thus, the amount of specific targets bound to probes is likely determined before washing, by the competition against nonspecific binding. Our competitive hybridization model is a viable alternative to Langmuir-like models. (comment)

  3. Identification of Listeria species by microarray-based assay.

    Science.gov (United States)

    Volokhov, Dmitriy; Rasooly, Avraham; Chumakov, Konstantin; Chizhikov, Vladimir

    2002-12-01

    We have developed a rapid microarray-based assay for the reliable detection and discrimination of six species of the Listeria genus: L. monocytogenes, L. ivanovii, L. innocua, L. welshimeri, L. seeligeri, and L. grayi. The approach used in this study involves one-tube multiplex PCR amplification of six target bacterial virulence factor genes (iap, hly, inlB, plcA, plcB, and clpE), synthesis of fluorescently labeled single-stranded DNA, and hybridization to the multiple individual oligonucleotide probes specific for each Listeria species and immobilized on a glass surface. Results of the microarray analysis of 53 reference and clinical isolates of Listeria spp. demonstrated that this method allowed unambiguous identification of all six Listeria species based on sequence differences in the iap gene. Another virulence factor gene, hly, was used for detection and genotyping all L. monocytogenes, all L. ivanovii, and 8 of 11 L. seeligeri isolates. Other members of the genus Listeria and three L. seeligeri isolates did not contain the hly gene. There was complete agreement between the results of genotyping based on the hly and iap gene sequences. All L. monocytogenes isolates were found to be positive for the inlB, plcA, plcB, and clpE virulence genes specific only to this species. Our data on Listeria species analysis demonstrated that this microarray technique is a simple, rapid, and robust genotyping method that is also a potentially valuable tool for identification and characterization of bacterial pathogens in general.

  4. Microarray Developed on Plastic Substrates.

    Science.gov (United States)

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

    2016-01-01

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

  5. Lipid Microarray Biosensor for Biotoxin Detection.

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-05-01

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

  6. 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...

  7. DNA Microarray for Rapid Detection and Identification of Food and Water Borne Bacteria: From Dry to Wet Lab.

    Science.gov (United States)

    Ranjbar, Reza; Behzadi, Payam; Najafi, Ali; Roudi, Raheleh

    2017-01-01

    A rapid, accurate, flexible and reliable diagnostic method may significantly decrease the costs of diagnosis and treatment. Designing an appropriate microarray chip reduces noises and probable biases in the final result. The aim of this study was to design and construct a DNA Microarray Chip for a rapid detection and identification of 10 important bacterial agents. In the present survey, 10 unique genomic regions relating to 10 pathogenic bacterial agents including Escherichia coli (E.coli), Shigella boydii, Sh.dysenteriae, Sh.flexneri, Sh.sonnei, Salmonella typhi, S.typhimurium, Brucella sp., Legionella pneumophila, and Vibrio cholera were selected for designing specific long oligo microarray probes. For this reason, the in-silico operations including utilization of the NCBI RefSeq database, Servers of PanSeq and Gview, AlleleID 7.7 and Oligo Analyzer 3.1 was done. On the other hand, the in-vitro part of the study comprised stages of robotic microarray chip probe spotting, bacterial DNAs extraction and DNA labeling, hybridization and microarray chip scanning. In wet lab section, different tools and apparatus such as Nexterion® Slide E, Qarray mini spotter, NimbleGen kit, TrayMix TM S4, and Innoscan 710 were used. A DNA microarray chip including 10 long oligo microarray probes was designed and constructed for detection and identification of 10 pathogenic bacteria. The DNA microarray chip was capable to identify all 10 bacterial agents tested simultaneously. The presence of a professional bioinformatician as a probe designer is needed to design appropriate multifunctional microarray probes to increase the accuracy of the outcomes.

  8. 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.

  9. Approximate sample size calculations with microarray data: an illustration

    NARCIS (Netherlands)

    Ferreira, José A.; Zwinderman, Aeilko

    2006-01-01

    We outline a method of sample size calculation in microarray experiments on the basis of pilot data and illustrate its practical application with both simulated and real data. The method was shown to be consistent (as the number of 'probed genes' tends to infinity) under general conditions in an

  10. Evaluating melanocytic lesions with single nucleotide polymorphism (SNP) chromosomal microarray.

    Science.gov (United States)

    Hedayat, Amin A; Linos, Konstantinos; Jung, Hou-Sung; Tafe, Laura J; Yan, Shaofeng; LeBlanc, Robert E; Lefferts, Joel A

    2017-12-01

    Histopathology is the gold standard for diagnosing melanocytic lesions; however, distinguishing benign versus malignant is not always clear histologically. Single nucleotide polymorphism (SNP) microarray analysis may help in making a definitive diagnosis. Here, we share our experience with the Oncoscan FFPE Assay and demonstrate its diagnostic utility in the context of ambiguous melanocytic lesions. Eleven archival melanocytic lesions, including three benign nevi, four melanomas, three BAP1-deficient Spitzoid nevi and one nevoid melanoma were selected for validation. SNP-array was performed according to the manufacturer's protocol, using the recommended 80ng of DNA; however, as little as 15ng was used if the extraction yield was lower. Concordance was assessed with H&E and various combinations of BAP1 and p16 immunohistochemical stains (IHC) and external reference laboratory chromosomal microarray results. After validation, the SNP array was utilized to make definitive diagnoses in four challenging cases. Oncoscan SNP array findings were in concordance with H&E, IHC, and reference laboratory chromosomal microarray testing. The SNP-based microarray can accurately detect copy number changes and aid in making a more definitive diagnosis of challenging melanocytic lesions. This can be accomplished using significantly less DNA than is required by other microarray technologies. Copyright © 2017. Published by Elsevier Inc.

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

    Directory of Open Access Journals (Sweden)

    Häsler Robert

    2005-02-01

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

  12. A Xenopus tropicalis oligonucleotide microarray works across species using RNA from Xenopus laevis.

    Science.gov (United States)

    Chalmers, Andrew D; Goldstone, Kim; Smith, James C; Gilchrist, Mike; Amaya, Enrique; Papalopulu, Nancy

    2005-03-01

    Microarrays have great potential for the study of developmental biology. As a model system Xenopus is well suited for making the most of this potential. However, Xenopus laevis has undergone a genome wide duplication meaning that most genes are represented by two paralogues. This causes a number of problems. Most importantly the presence of duplicated genes mean that a X. laevis microarray will have less or even half the coverage of a similar sized microarray from the closely related but diploid frog Xenopus tropicalis. However, to date, X. laevis is the most commonly used amphibian system for experimental embryology. Therefore, we have tested if a microarray based on sequences from X. tropicalis will work across species using RNA from X. laevis. We produced a pilot oligonucleotide microarray based on sequences from X. tropicalis. The microarray was used to identify genes whose expression levels changed during early X. tropicalis development. The same assay was then carried out using RNA from X. laevis. The cross species experiments gave similar results to those using X. tropicalis RNA. This was true at the whole microarray level and for individual genes, with most genes giving similar results using RNA from X. laevis and X. tropicalis. Furthermore, the overlap in genes identified between a X. laevis and a X. tropicalis set of experiments was only 12% less than the overlap between two sets of X. tropicalis experiments. Therefore researchers can work with X. laevis and still make use of the advantages offered by X. tropicalis microarrays.

  13. DNA microarray data and contextual analysis of correlation graphs

    Directory of Open Access Journals (Sweden)

    Hingamp Pascal

    2003-04-01

    Full Text Available Abstract Background DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation. Results We study networks of co-expressed genes obtained from DNA microarray experiments. The mathematical concept of curvature on graphs is used to group genes or samples into clusters to which relevant gene or sample annotations are automatically assigned. Application to publicly available yeast and human lymphoma data demonstrates the reliability of the method in spite of its simplicity, especially with respect to the small number of parameters involved. Conclusions We provide a method for automatically determining relevant gene clusters among the many genes monitored with microarrays. The automatic annotations and the graphical interface improve the readability of the data. A C++ implementation, called Trixy, is available from http://tagc.univ-mrs.fr/bioinformatics/trixy.html.

  14. Tumor classification ranking from microarray data

    Directory of Open Access Journals (Sweden)

    Kijsanayothin Phongphun

    2008-09-01

    Full Text Available Abstract Background Gene expression profiles based on microarray data are recognized as potential diagnostic indices of cancer. Molecular tumor classifications resulted from these data and learning algorithms have advanced our understanding of genetic changes associated with cancer etiology and development. However, classifications are not always perfect and in such cases the classification rankings (likelihoods of correct class predictions can be useful for directing further research (e.g., by deriving inferences about predictive indicators or prioritizing future experiments. Classification ranking is a challenging problem, particularly for microarray data, where there is a huge number of possible regulated genes with no known rating function. This study investigates the possibility of making tumor classification more informative by using a method for classification ranking that requires no additional ranking analysis and maintains relatively good classification accuracy. Results Microarray data of 11 different types and subtypes of cancer were analyzed using MDR (Multi-Dimensional Ranker, a recently developed boosting-based ranking algorithm. The number of predictor genes in all of the resulting classification models was at most nine, a huge reduction from the more than 12 thousands genes in the majority of the expression samples. Compared to several other learning algorithms, MDR gives the greatest AUC (area under the ROC curve for the classifications of prostate cancer, acute lymphoblastic leukemia (ALL and four ALL subtypes: BCR-ABL, E2A-PBX1, MALL and TALL. SVM (Support Vector Machine gives the highest AUC for the classifications of lung, lymphoma, and breast cancers, and two ALL subtypes: Hyperdiploid > 50 and TEL-AML1. MDR gives highly competitive results, producing the highest average AUC, 91.01%, and an average overall accuracy of 90.01% for cancer expression analysis. Conclusion Using the classification rankings from MDR is a simple

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

    Science.gov (United States)

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

    2009-07-01

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

  16. 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.

  17. Integrated olfactory receptor and microarray gene expression databases

    Directory of Open Access Journals (Sweden)

    Crasto Chiquito J

    2007-06-01

    Full Text Available Abstract Background Gene expression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit gene expression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the gene expression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray gene expression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of gene expression in the olfactory system. In conjunction with ORDB, ORMD integrates gene expression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

  18. 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.

  19. High-resolution genomic microarrays for X-linked mental retardation.

    NARCIS (Netherlands)

    Lugtenberg, D.; Veltman, J.A.; Bokhoven, J.H.L.M. van

    2007-01-01

    Developments in genomic microarray technology have revolutionized the study of human genomic copy number variation. This has significantly affected many areas in human genetics, including the field of X-linked mental retardation (XLMR). Chromosome X-specific bacterial artificial chromosomes

  20. Direct detection of Staphylococcus aureus mRNA using a flow through microarray

    NARCIS (Netherlands)

    Anthony, R. M.; Schuitema, A. R. J.; Oskam, L.; Klatser, P. R.

    2005-01-01

    The direct detection of mRNAs from bacterial cultures on a DNA array without amplification and labelling would greatly extend the range of applications suitable for microarray analysis. Here we describe the direct detection of 23S rRNA and seven mRNA species from total Staphylococcus aureus RNA

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

    Science.gov (United States)

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

    2015-01-01

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

  2. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    Bacterial adhesion is often mediated by complex polymeric surface structures referred to as fimbriae. Type I fimbriae of Escherichia coli represent the archetypical and best characterised fimbrial system. These adhesive organelles mediate binding to D-mannose and are directly associated...... we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  3. Identification of Listeria Species by Microarray-Based Assay

    OpenAIRE

    Volokhov, Dmitriy; Rasooly, Avraham; Chumakov, Konstantin; Chizhikov, Vladimir

    2002-01-01

    We have developed a rapid microarray-based assay for the reliable detection and discrimination of six species of the Listeria genus: L. monocytogenes, L. ivanovii, L. innocua, L. welshimeri, L. seeligeri, and L. grayi. The approach used in this study involves one-tube multiplex PCR amplification of six target bacterial virulence factor genes (iap, hly, inlB, plcA, plcB, and clpE), synthesis of fluorescently labeled single-stranded DNA, and hybridization to the multiple individual oligonucleot...

  4. Prediction of qualitative outcome of oligonucleotide microarray hybridization by measurement of RNA integrity using the 2100 Bioanalyzer capillary electrophoresis system.

    Science.gov (United States)

    Kiewe, Philipp; Gueller, Saskia; Komor, Martina; Stroux, Andrea; Thiel, Eckhard; Hofmann, Wolf-Karsten

    2009-12-01

    RNA quality is critical to achieve valid results in microarray experiments and to save resources. The RNA integrity number (RIN) can be measured with minimal sample consumption by microfluidics-based capillary electrophoresis. To determine whether RIN can predict the qualitative outcome of microarray hybridization, we measured RIN in total RNA samples from 484 different experiments by the 2100 Bioanalyzer system and correlated with the percentage of present calls (%pc) of downstream oligonucleotide microarrays. The correlation coefficient for RNA and %pc in all 408 samples for which the bioanalyzer algorithm was able to produce an RIN was 0.475 (p RNA sample is appropriate for successful microarray hybridization.

  5. Improving missing value estimation in microarray data with gene ontology.

    Science.gov (United States)

    Tuikkala, Johannes; Elo, Laura; Nevalainen, Olli S; Aittokallio, Tero

    2006-03-01

    Gene expression microarray experiments produce datasets with frequent missing expression values. Accurate estimation of missing values is an important prerequisite for efficient data analysis as many statistical and machine learning techniques either require a complete dataset or their results are significantly dependent on the quality of such estimates. A limitation of the existing estimation methods for microarray data is that they use no external information but the estimation is based solely on the expression data. We hypothesized that utilizing a priori information on functional similarities available from public databases facilitates the missing value estimation. We investigated whether semantic similarity originating from gene ontology (GO) annotations could improve the selection of relevant genes for missing value estimation. The relative contribution of each information source was automatically estimated from the data using an adaptive weight selection procedure. Our experimental results in yeast cDNA microarray datasets indicated that by considering GO information in the k-nearest neighbor algorithm we can enhance its performance considerably, especially when the number of experimental conditions is small and the percentage of missing values is high. The increase of performance was less evident with a more sophisticated estimation method. We conclude that even a small proportion of annotated genes can provide improvements in data quality significant for the eventual interpretation of the microarray experiments. Java and Matlab codes are available on request from the authors. Available online at http://users.utu.fi/jotatu/GOImpute.html.

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

    Science.gov (United States)

    Bilardi, Jade; Walker, Sandra; Mooney-Somers, Julie; Temple-Smith, Meredith; McNair, Ruth; Bellhouse, Clare; Fairley, Christopher; Chen, Marcus; Bradshaw, Catriona

    2016-01-01

    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.

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

    Science.gov (United States)

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

    2012-01-01

    Oligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (psunflower 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.

  8. The EADGENE Microarray Data Analysis Workshop

    OpenAIRE

    de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø; Watson, Michael; Channing, Caroline; Hulsegge, Ina; Pool, Marco; Buitenhuis, Bart; Hedegaard, Jakob; Hornshøj, Henrik; Jiang, Li; Sørensen, Peter; Marot, Guillemette; Delmas, Céline; Lê Cao, Kim-Anh

    2007-01-01

    Abstract 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 microarra...

  9. Bacterial Keratitis

    Science.gov (United States)

    ... Español Eye Health / Eye Health A-Z Bacterial Keratitis Sections What Is Bacterial Keratitis? Bacterial Keratitis Symptoms ... Lens Care Bacterial Keratitis Treatment What Is Bacterial Keratitis? Leer en Español: ¿Qué Es la Queratitis Bacteriana? ...

  10. Capturing Early Changes in the Marine Bacterial Community as a Result of Crude Oil Pollution in a Mesocosm Experiment

    Science.gov (United States)

    Krolicka, Adriana; Boccadoro, Catherine; Nilsen, Mari Mæland; Baussant, Thierry

    2017-01-01

    The results of marine bacterial community succession from a short-term study of seawater incubations at 4°C to North Sea crude oil are presented herein. Oil was used alone (O) or in combination with a dispersant (OD). Marine bacterial communities resulting from these incubations were characterized by a fingerprinting analysis and pyrosequencing of the 16S rRNA gene with the aim of 1) revealing differences in bacterial communities between the control, O treatment, and OD treatment and 2) identifying the operational taxonomic units (OTUs) of early responders in order to define the bacterial gene markers of oil pollution for in situ monitoring. After an incubation for 1 d, the distribution of the individual ribotypes of bacterial communities in control and oil-treated (O and OD) tanks differed. Differences related to the structures of bacterial communities were observed at later stages of the incubation. Among the early responders identified (Pseudoalteromonas, Sulfitobacter, Vibrio, Pseudomonas, Glaciecola, Neptunomonas, Methylophaga, and Pseudofulvibacter), genera that utilize a disintegrated biomass or hydrocarbons as well as biosurfactant producers were detected. None of these genera included obligate hydrocarbonoclastic bacteria (OHCB). After an incubation for 1 d, the abundances of Glaciecola and Pseudofulvibacter were approximately 30-fold higher in the OD and O tanks than in the control tank. OTUs assigned to the Glaciecola genus were represented more in the OD tank, while those of Pseudofulvibacter were represented more in the O tank. We also found that 2 to 3% of the structural community shift originated from the bacterial community in the oil itself, with Polaribacter being a dominant bacterium. PMID:29187706

  11. Capturing Early Changes in the Marine Bacterial Community as a Result of Crude Oil Pollution in a Mesocosm Experiment.

    Science.gov (United States)

    Krolicka, Adriana; Boccadoro, Catherine; Nilsen, Mari Mæland; Baussant, Thierry

    2017-12-27

    The results of marine bacterial community succession from a short-term study of seawater incubations at 4°C to North Sea crude oil are presented herein. Oil was used alone (O) or in combination with a dispersant (OD). Marine bacterial communities resulting from these incubations were characterized by a fingerprinting analysis and pyrosequencing of the 16S rRNA gene with the aim of 1) revealing differences in bacterial communities between the control, O treatment, and OD treatment and 2) identifying the operational taxonomic units (OTUs) of early responders in order to define the bacterial gene markers of oil pollution for in situ monitoring.After an incubation for 1 d, the distribution of the individual ribotypes of bacterial communities in control and oil-treated (O and OD) tanks differed. Differences related to the structures of bacterial communities were observed at later stages of the incubation. Among the early responders identified (Pseudoalteromonas, Sulfitobacter, Vibrio, Pseudomonas, Glaciecola, Neptunomonas, Methylophaga, and Pseudofulvibacter), genera that utilize a disintegrated biomass or hydrocarbons as well as biosurfactant producers were detected. None of these genera included obligate hydrocarbonoclastic bacteria (OHCB). After an incubation for 1 d, the abundances of Glaciecola and Pseudofulvibacter were approximately 30-fold higher in the OD and O tanks than in the control tank. OTUs assigned to the Glaciecola genus were represented more in the OD tank, while those of Pseudofulvibacter were represented more in the O tank. We also found that 2 to 3% of the structural community shift originated from the bacterial community in the oil itself, with Polaribacter being a dominant bacterium.

  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. Washing scaling of GeneChip microarray expression

    Directory of Open Access Journals (Sweden)

    Krohn Knut

    2010-05-01

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

  14. Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray

    Directory of Open Access Journals (Sweden)

    Lan Shu

    2008-07-01

    Full Text Available Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples. However, a simple microarray experiment often leads to very high-dimensional data and a huge amount of information, the vast amount of data challenges researchers into extracting the important features and reducing the high dimensionality. In this paper, a nonlinear dimensionality reduction kernel method based locally linear embedding(LLE is proposed, and fuzzy K-nearest neighbors algorithm which denoises datasets will be introduced as a replacement to the classical LLE’s KNN algorithm. In addition, kernel method based support vector machine (SVM will be used to classify genomic microarray data sets in this paper. We demonstrate the application of the techniques to two published DNA microarray data sets. The experimental results confirm the superiority and high success rates of the presented method.

  15. Integrating Biological Perspectives:. a Quantum Leap for Microarray Expression Analysis

    Science.gov (United States)

    Wanke, Dierk; Kilian, Joachim; Bloss, Ulrich; Mangelsen, Elke; Supper, Jochen; Harter, Klaus; Berendzen, Kenneth W.

    2009-02-01

    Biologists and bioinformatic scientists cope with the analysis of transcript abundance and the extraction of meaningful information from microarray expression data. By exploiting biological information accessible in public databases, we try to extend our current knowledge over the plant model organism Arabidopsis thaliana. Here, we give two examples of increasing the quality of information gained from large scale expression experiments by the integration of microarray-unrelated biological information: First, we utilize Arabidopsis microarray data to demonstrate that expression profiles are usually conserved between orthologous genes of different organisms. In an initial step of the analysis, orthology has to be inferred unambiguously, which then allows comparison of expression profiles between orthologs. We make use of the publicly available microarray expression data of Arabidopsis and barley, Hordeum vulgare. We found a generally positive correlation in expression trajectories between true orthologs although both organisms are only distantly related in evolutionary time scale. Second, extracting clusters of co-regulated genes implies similarities in transcriptional regulation via similar cis-regulatory elements (CREs). Vice versa approaches, where co-regulated gene clusters are found by investigating on CREs were not successful in general. Nonetheless, in some cases the presence of CREs in a defined position, orientation or CRE-combinations is positively correlated with co-regulated gene clusters. Here, we make use of genes involved in the phenylpropanoid biosynthetic pathway, to give one positive example for this approach.

  16. Microarray expression profiling of human dental pulp from single subject.

    Science.gov (United States)

    Tete, Stefano; Mastrangelo, Filiberto; Scioletti, Anna Paola; Tranasi, Michelangelo; Raicu, Florina; Paolantonio, Michele; Stuppia, Liborio; Vinci, Raffaele; Gherlone, Enrico; Ciampoli, Cristian; Sberna, Maria Teresa; Conti, Pio

    2008-01-01

    Microarray is a recently developed simultaneous analysis of expression patterns of thousand of genes. The aim of this research was to evaluate the expression profile of human healthy dental pulp in order to find the presence of genes activated and encoding for proteins involved in the physiological process of human dental pulp. We report data obtained by analyzing expression profiles of human tooth pulp from single subjects, using an approach based on the amplification of the total RNA. Experiments were performed on a high-density array able to analyse about 21,000 oligonucleotide sequences of about 70 bases in duplicate, using an approach based on the amplification of the total RNA from the pulp of a single tooth. Obtained data were analyzed using the S.A.M. system (Significance Analysis of Microarray) and genes were merged according to their molecular functions and biological process by the Onto-Express software. The microarray analysis revealed 362 genes with specific pulp expression. Genes showing significant high expression were classified in genes involved in tooth development, protoncogenes, genes of collagen, DNAse, Metallopeptidases and Growth factors. We report a microarray analysis, carried out by extraction of total RNA from specimens of healthy human dental pulp tissue. This approach represents a powerful tool in the study of human normal and pathological pulp, allowing minimization of the genetic variability due to the pooling of samples from different individuals.

  17. 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

    . The major findings are: (1) the incorporation of dissolved compounds (nitrate, nitrite, ammonium, phosphate, silicate, and DOC) into the sea ice was not conservative (relative to salinity) during ice growth. Brine convection clearly influenced the incorporation of the dissolved compounds, since the non......-conservative behavior of the dissolved compounds was particularly pronounced in the absence of brine convection. (2) Bacterial activity further regulated nutrient availability in the ice: ammonium and nitrite accumulated as a result of remineralization processes, although bacterial production was too low to induce...

  18. 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.

  19. LNA-modified isothermal oligonucleotide microarray for ...

    Indian Academy of Sciences (India)

    2014-10-20

    Oct 20, 2014 ... To achieve high detection specificity, we fabricated an isothermal microarray ... diagnosis, drug screening, food inspection, agricultural prod- uct monitoring ..... printed with probes B1, B2 and B3 for Bacillus licheniformis (image 1), and microarray analysis of Bacillus licheniformis PCR products amplified ...

  20. Diagnostic and analytical applications of protein microarrays

    DEFF Research Database (Denmark)

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

    2005-01-01

    years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria...

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

    Science.gov (United States)

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

    2014-08-18

    Bacterial pathogens are mostly responsible for food-borne diseases, and there is still substantial room for improvement in the effective detection of these organisms. In the present study, we explored a new method to detect target pathogens easily and rapidly with high sensitivity and specificity. This method uses an oligonucleotide microarray combined with quantum dots as fluorescent labels. Oligonucleotide probes targeting the 16SrRNA gene were synthesized to create an oligonucleotide microarray. The PCR products labeled with biotin were subsequently hybridized using an oligonucleotide microarray. Following incubation with CdSe/ZnS quantum dots coated with streptavidin, fluorescent signals were detected with a PerkinElmer Gx Microarray Scanner. The results clearly showed specific hybridization profiles corresponding to the bacterial species assessed. Two hundred and sixteen strains of food-borne bacterial pathogens, including standard strains and isolated strains from food samples, were used to test the specificity, stability, and sensitivity of the microarray system. We found that the oligonucleotide microarray combined with quantum dots used as fluorescent labels can successfully discriminate the bacterial organisms at the genera or species level, with high specificity and stability as well as a sensitivity of 10 colony forming units (CFU)/mL of pure culture. We further tested 105 mock-contaminated food samples and achieved consistent results as those obtained from traditional biochemical methods. Together, these results indicate that the quantum dot-based oligonucleotide microarray has the potential to be a powerful tool in the detection and identification of pathogenic bacteria in foods. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Translating microarray data for diagnostic testing in childhood leukaemia

    International Nuclear Information System (INIS)

    Hoffmann, Katrin; Firth, Martin J; Beesley, Alex H; Klerk, Nicholas H de; Kees, Ursula R

    2006-01-01

    and with microarray experiments being performed by a different research team

  3. Workflows for microarray data processing in the Kepler environment

    Science.gov (United States)

    2012-01-01

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

  4. Workflows for microarray data processing in the Kepler environment

    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

  5. Microarray-based genotyping of Salmonella: Inter-laboratory evaluation of reproducibility and standardization potential

    DEFF Research Database (Denmark)

    Grønlund, Hugo Ahlm; Riber, Leise; Vigre, Håkan

    2011-01-01

    Bacterial food-borne infections in humans caused by Salmonella spp. are considered a crucial food safety issue. Therefore, it is important for the risk assessments of Salmonella to consider the genomic variationamong different isolates in order to control pathogen-induced infections. Microarray...... critical methodology parameters that differed between the two labs were identified. These related to printing facilities, choice of hybridization buffer,wash buffers used following the hybridization and choice of procedure for purifying genomic DNA. Critical parameters were randomized in a four......DNA and different wash buffers. However, less agreement (Kappa=0.2–0.6) between microarray results were observed when using different hybridization buffers, indicating this parameter as being highly criticalwhen transferring a standard microarray assay between laboratories. In conclusion, this study indicates...

  6. Implementation of mutual information and bayes theorem for classification microarray data

    Science.gov (United States)

    Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

    2018-03-01

    Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

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

    Science.gov (United States)

    Jahandeh, Nadia; Ranjbar, Reza; Behzadi, Payam; Behzadi, Elham

    2015-01-01

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

  8. Contributions of the EMERALD project to assessing and improving microarray data quality.

    Science.gov (United States)

    Beisvåg, Vidar; Kauffmann, Audrey; Malone, James; Foy, Carole; Salit, Marc; Schimmel, Heinz; Bongcam-Rudloff, Erik; Landegren, Ulf; Parkinson, Helen; Huber, Wolfgang; Brazma, Alvis; Sandvik, Arne K; Kuiper, Martin

    2011-01-01

    While minimum information about a microarray experiment (MIAME) standards have helped to increase the value of the microarray data deposited into public databases like ArrayExpress and Gene Expression Omnibus (GEO), limited means have been available to assess the quality of this data or to identify the procedures used to normalize and transform raw data. The EMERALD FP6 Coordination Action was designed to deliver approaches to assess and enhance the overall quality of microarray data and to disseminate these approaches to the microarray community through an extensive series of workshops, tutorials, and symposia. Tools were developed for assessing data quality and used to demonstrate how the removal of poor-quality data could improve the power of statistical analyses and facilitate analysis of multiple joint microarray data sets. These quality metrics tools have been disseminated through publications and through the software package arrayQualityMetrics. Within the framework provided by the Ontology of Biomedical Investigations, ontology was developed to describe data transformations, and software ontology was developed for gene expression analysis software. In addition, the consortium has advocated for the development and use of external reference standards in microarray hybridizations and created the Molecular Methods (MolMeth) database, which provides a central source for methods and protocols focusing on microarray-based technologies.

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

    Science.gov (United States)

    Morris, Brandon E. L.

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

  10. Microarray-integrated optoelectrofluidic immunoassay system.

    Science.gov (United States)

    Han, Dongsik; Park, Je-Kyun

    2016-05-01

    A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection.

  11. 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.

  12. Applications of heparin and heparan sulfate microarrays.

    Science.gov (United States)

    Yin, Jian; Seeberger, Peter H

    2010-01-01

    Carbohydrate microarrays have become crucial tools for revealing the biological interactions and functions of glycans, primarily because the microarray format enables the investigation of large numbers of carbohydrates at a time. Heparan sulfate (HS) and heparin are the most structurally complex glycosaminoglycans (GAGs). In this chapter, we describe the preparation of a small library of HS/heparin oligosaccharides, and the fabrication of HS/heparin microarrays that have been used to establish HS/heparin-binding profiles. Fibroblast growth factors (FGFs), natural cytotoxicity receptors (NCRs), and chemokines were screened to illuminate the very important biological functions of these glycans. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  13. Fuzzy clustering analysis of microarray data.

    Science.gov (United States)

    Han, Lixin; Zeng, Xiaoqin; Yan, Hong

    2008-10-01

    Fuzzy clustering is a useful tool for identifying relevant subsets of microarray data. This paper proposes a fuzzy clustering method for microarray data analysis. An advantage of the method is that it used a combination of the fuzzy c-means and the principal component analysis to identify the groups of genes that show similar expression patterns. It allows a gene to belong to more than a gene expression pattern with different membership grades. The method is suitable for the analysis of large amounts of noisy microarray data.

  14. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

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

  15. Pineal function: impact of microarray analysis

    DEFF Research Database (Denmark)

    Klein, David C; Bailey, Michael J; Carter, David A

    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-h schedule. This effort has highlighted surprising similarity to the re......Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity...... foundation that microarray analysis has provided will broadly support future research on pineal function....

  16. Using pre-existing microarray datasets to increase experimental power: application to insulin resistance.

    Directory of Open Access Journals (Sweden)

    Bernie J Daigle

    2010-03-01

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

  17. Simultaneous Detection of Escherichia coli, Salmonella enterica, Listeria monocytegenes and Bacillus cereus by Oligonucleotide Microarray

    Directory of Open Access Journals (Sweden)

    Meysam Sarshar

    2015-11-01

    Full Text Available Background: Traditional laboratory methods to detect pathogenic bacteria are time consuming and laborious. Therefore, it is essential to use powerful and reliable molecular methods for quick and simultaneous detection of microbial pathogens. Objectives: The current study aimed to evaluate the capability and efficiency of 23S rDNA sequence for rapid and simultaneous detection of four important food-borne pathogens by an oligonucleotide microarray technique. Materials and Methods: The 23S rDNA sequences of Escherichia coli, Salmonella enterica, Listeria monocytogenes and Bacillus cereus were obtained from GenBank databases and used to design the oligonucleotide probes and primers by Vector NTI software. Oligonucleotide probes were placed on a nylon membrane and hybridization was performed between probes and 23S rDNA digoxigenin-labeled polymerase chain reaction (PCR products. Hybridization signals were visualized by NBT/BCIP color development. Results: Positive hybridization color was produced for Escherichia coli, Salmonella enterica, Listeria monocytogenes and Bacillus cereus. The oligonucleotide microarray detected all bacterial strains in a single reaction in less than five hours. The sensitivity of the performed microarray assay was 103 cfu/mL for each species of pathogen. No cross reaction was found between the tested bacterial species. Conclusions: The obtained results indicated that amplification of 23S rDNA gene followed by oligonucleotide microarray hybridization is a rapid and reliable method to identify and discriminate foodborne pathogens tested under the study.

  18. Magnetic Scanometric DNA Microarray Detection of Methyl Tertiary Butyl Ether Degrading Bacteria for Environmental Monitoring

    Science.gov (United States)

    Chan, Mei-Lin; Jaramillo, Gerardo; Hristova, Krassimira R.; Horsley, David A.

    2010-01-01

    A magnetoresistive biosensing platform based on a single magnetic tunnel junction (MTJ) scanning probe and DNA microarrays labeled with magnetic particles has been developed to provide an inexpensive, sensitive and reliable detection of DNA. The biosensing platform was demonstrated on a DNA microarray assay for quantifying bacteria capable of degrading methyl tertiary-butyl ether (MTBE), where concentrations as low as 10 pM were detectable. Synthetic probe bacterial DNA was immobilized on a microarray glass slide surface, hybridized with the 48 base pair long biotinylated target DNA and subsequently incubated with streptavidin-coated 2.8 μm diameter magnetic particles. The biosensing platform then makes use of a micron-sized MTJ sensor that was raster scanned across a 3 mm by 5 mm glass slide area to capture the stray magnetic field from the tagged DNA and extract two dimensional magnetic field images of the microarray. The magnetic field output is then averaged over each 100 μm diameter DNA array spot to extract the magnetic spot intensity, analogous to the fluorescence spot intensity used in conventional optical scanners. The magnetic scanning result is compared with results from a commercial laser scanner and particle coverage optical counting to demonstrate the dynamic range and linear sensitivity of the biosensing platform as a potentially inexpensive, sensitive and portable alternative for DNA microarray detection for field applications. PMID:20889328

  19. 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.

  20. Microarray data visualization and analysis with the Longhorn Array Database (LAD).

    Science.gov (United States)

    Killion, Patrick J; Iyer, Vishwanath R

    2004-12-01

    The wide availability and use of DNA microarrays has brought the power of whole-genome functional characterization to a large variety of research environments. Microarrays, however, also introduce significant infrastructural and analytical concerns with respect to the long-term warehousing, annotation, and visualization of immense data sets. The Longhorn Array Database (LAD) is a MIAME-compliant microarray database that operates on PostgreSQL and Linux. It is a free and completely open-source software solution, and provides a systematic and proven environment in which vast experiment sets can be safely archived, securely accessed, biologically annotated, quantitatively analyzed, and visually explored. This unit provides the complete set of information needed to successfully deploy, configure, and use LAD for the purposes of two-color DNA microarray analysis and visualization.

  1. A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB

    Directory of Open Access Journals (Sweden)

    White Joseph

    2006-11-01

    Full Text Available Abstract Background Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support. Results We propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion. Conclusion MAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.

  2. 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...

  3. Bacterial meningitis

    NARCIS (Netherlands)

    Roos, Karen L.; van de Beek, Diederik

    2010-01-01

    Bacterial meningitis is a neurological emergency. Empiric antimicrobial and adjunctive therapy should be initiated as soon as a single set of blood cultures has been obtained. Clinical signs suggestive of bacterial meningitis include fever, headache, meningismus, vomiting, photophobia, and an

  4. Goober: A fully integrated and user-friendly microarray data management and analysis solution for core labs and bench biologists

    Directory of Open Access Journals (Sweden)

    Luo Wen

    2009-03-01

    Full Text Available Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.

  5. PATMA: parser of archival tissue microarray

    Directory of Open Access Journals (Sweden)

    Lukasz Roszkowiak

    2016-12-01

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

  6. Diagnostic and analytical applications of protein microarrays.

    Science.gov (United States)

    Dufva, Martin; Christensen, Claus 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 past 5 years. A genome-scale protein microarray has been demonstrated for identifying protein-protein interactions as well as for rapid identification of protein binding to a particular drug. Furthermore, protein microarrays have been shown as an efficient tool in cancer profiling, detection of bacteria and toxins, identification of allergen reactivity and autoantibodies. They have also demonstrated the ability to measure the absolute concentration of small molecules. Besides their capacity for parallel diagnostics, microarrays can be more sensitive than traditional methods such as enzyme-linked immunosorbent assay, mass spectrometry or high-performance liquid chromatography-based assays. However, for protein and antibody arrays to be successfully introduced into diagnostics, the biochemistry of immunomicroarrays must be better characterized and simplified, they must be validated in a clinical setting and be amenable to automation or integrated into easy-to-use systems, such as micrototal analysis systems or point-of-care devices.

  7. Contributions to Statistical Problems Related to Microarray Data

    Science.gov (United States)

    Hong, Feng

    2009-01-01

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

  8. 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

  9. 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.

  10. Microarray image segmentation using additional dye--an experimental study.

    Science.gov (United States)

    Gupta, Rashi; Ruosaari, Salla; Kulathinal, Sangita; Hollmén, Jaakko; Auvinen, Petri

    2007-01-01

    The DNA microarray technique allows monitoring the expression levels of thousands of genes simultaneously. A single DNA microarray experiment involves a number of error-prone manual and automated processes, which influence the results and have an impact on the subsequent stages of analysis. Typical problems of arrays are pinning errors while probe printing and the corruption of spots by noise patches. These errors should be detected at the time of image analysis in order to prevent the erroneous intensities from ending up in the analysis and inference stages. In this paper we introduce the concept (referred to as SybrSpot) of utilizing information provided by an additional dye, SYBR green RNA II, for segmentation of gene expression microarrays. Owing to the effective binding of the SYBR green RNA II to the array probes, an image with high signal-to-noise ratio is obtained. This image is used to learn about the spot quality and to flag spots which are not reliably hybridized and corrupted by noise. Further, we compare SybrSpot with GenePix and demonstrate that SybrSpot performs better than GenePix when flagging spots with no probes or weak probes. The code is available upon request to authors.

  11. Sequence-dependent fluorescence of cyanine dyes on microarrays.

    Directory of Open Access Journals (Sweden)

    Christy Agbavwe

    Full Text Available Cy3 and Cy5 are among the most commonly used oligonucleotide labeling molecules. Studies of nucleic acid structure and dynamics use these dyes, and they are ubiquitous in microarray experiments. They are sensitive to their environment and have higher quantum yield when bound to DNA. The fluorescent intensity of terminal cyanine dyes is also known to be significantly dependent on the base sequence of the oligonucleotide. We have developed a very precise and high-throughput method to evaluate the sequence dependence of oligonucleotide labeling dyes using microarrays and have applied the method to Cy3 and Cy5. We used light-directed in-situ synthesis of terminally-labeled microarrays to determine the fluorescence intensity of each dye on all 1024 possible 5'-labeled 5-mers. Their intensity is sensitive to all five bases. Their fluorescence is higher with 5' guanines, and adenines in subsequent positions. Cytosine suppresses fluorescence. Intensity falls by half over the range of all 5-mers for Cy3, and two-thirds for Cy5. Labeling with 5'-biotin-streptavidin-Cy3/-Cy5 gives a completely different sequence dependence and greatly reduces fluorescence compared with direct terminal labeling.

  12. Application of phylogenetic microarray analysis to discriminate sources of fecal pollution.

    Science.gov (United States)

    Dubinsky, Eric A; Esmaili, Laleh; Hulls, John R; Cao, Yiping; Griffith, John F; Andersen, Gary L

    2012-04-17

    Conventional methods for fecal source tracking typically use single biomarkers to systematically identify or exclude sources. High-throughput DNA sequence analysis can potentially identify all sources of microbial contaminants in a single test by measuring the total diversity of fecal microbial communities. In this study, we used phylogenetic microarray analysis to determine the comprehensive suite of bacteria that define major sources of fecal contamination in coastal California. Fecal wastes were collected from 42 different populations of humans, birds, cows, horses, elk, and pinnipeds. We characterized bacterial community composition using a DNA microarray that probes for 16S rRNA genes of 59,316 different bacterial taxa. Cluster analysis revealed strong differences in community composition among fecal wastes from human, birds, pinnipeds, and grazers. Actinobacteria, Bacilli, and many Gammaproteobacteria taxa discriminated birds from mammalian sources. Diverse families within the Clostridia and Bacteroidetes taxa discriminated human wastes, grazers, and pinnipeds from each other. We found 1058 different bacterial taxa that were unique to either human, grazing mammal, or bird fecal wastes. These OTUs can serve as specific identifier taxa for these sources in environmental waters. Two field tests in marine waters demonstrate the capacity of phylogenetic microarray analysis to track multiple sources with one test.

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

    Science.gov (United States)

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

    2012-02-01

    A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Fish 'n' chips: the use of microarrays for aquatic toxicology.

    Science.gov (United States)

    Denslow, Nancy D; Garcia-Reyero, Natàlia; Barber, David S

    2007-03-01

    Gene expression analysis is changing the way that we look at toxicity, allowing toxicologists to perform parallel analyses of entire transcriptomes. While this technology is not as advanced in aquatic toxicology as it is for mammalian models, it has shown promise for determining modes of action, identifying biomarkers and developing "signatures" of chemicals that can be used for field and mixture studies. A major hurdle for the use of microarrays in aquatic toxicology is the lack of sequence information for non-model species. Custom arrays based on gene libraries enriched for genes that are expressed in response to specific contaminants have been used with excellent success for some non-model species, suggesting that this approach will work well for ecotoxicology and spurring on the sequencing of cDNA libraries for species of interest. New sequencing technology and development of repositories for gene expression data will accelerate the use of microarrays in aquatic toxicology. Notwithstanding the preliminary successes that have been achieved even with partial cDNA libraries printed on arrays, ecological samples present elevated challenges for this technology due to the high degree of variation of the samples. Furthermore, recent studies that show nonlinear toxic responses for ecological species underscore the necessity of establishing time and dose dependence of effects on gene expression and comparing these results with traditional markers of toxicity. To realize the full potential of microarrays, researchers must do the experiments required to bridge the gap between the 'omics' technologies and traditional toxicology to demonstrate that microarrays have predictive value in ecotoxicology.

  15. Contemporary use of ceftaroline fosamil for the treatment of community-acquired bacterial pneumonia: CAPTURE study experience.

    Science.gov (United States)

    Ramani, Ananthakrishnan; Udeani, George; Evans, John; Jandourek, Alena; Cole, Phillip; Smith, Alexander; David Friedland, H

    2014-08-01

    The Clinical Assessment Program and Teflaro(®) Utilization Registry (CAPTURE) is a multicenter cohort study designed to collect information on the contemporary use of ceftaroline fosamil in the US. Data collected from 398 evaluable patients with community-acquired bacterial pneumonia (CABP) (mean age 64 years) during the first 18 months of the study are presented. Most patients had co-morbidities (76%; primarily structural lung disease), and ≧2 signs and symptoms of CABP (76%). Overall clinical success was 79% which varied little with ceftaroline fosamil usage (monotherapy vs concurrent therapy; first-line vs second-line therapy). Most patients were discharged home (60%) or to another healthcare facility (35%). These data suggest that ceftaroline, in contemporary clinical use, is an effective antibiotic for the treatment of patients with CABP, including those with significant co-morbidities or who required a change of their prior antibiotic therapy.

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

    Science.gov (United States)

    Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

    2009-10-12

    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. 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. 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.

  17. 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.

  18. Aspiration in head and neck cancer patients: a single centre experience of clinical profile, bacterial isolates and antibiotic sensitivity pattern.

    Science.gov (United States)

    Lakshmaiah, K C; Sirsath, Nagesh T; Subramanyam, Jayshree R; Govind, Babu K; Lokanatha, D; Shenoy, Ashok M

    2013-07-01

    Most patients with head and neck cancer have dysphagia and are at increased risk of having aspiration and subsequent pneumonia. It can cause prolonged hospitalization, treatment delay and/or interruption and mortality in cancer patients. The treatment of these infections often relies on empirical antibiotics based on local microbiology and antibiotic sensitivity patterns. The aim of present study is to analyse respiratory tract pathogens isolated by sputum culture in head and neck cancer patients undergoing treatment at a tertiary cancer centre in South India who presented with features of aspiration. The study is carried out to establish empirical antibiotic policy for head and neck cancer patients who present with features of aspiration. This was a retrospective study. The study included sputum samples sent for culture and sensitivity from January 2011 to December 2012. Analysis of microbiologic species isolated in sputum specimen and the antibiotic sensitivity pattern of the bacterial isolates was performed. A detailed study of case files of all patients was done to find out which is the most common site prone for producing aspiration. There were 47 (31.54 %) gram positive isolates and 102 (68.45 %) gram negative isolates. The most common bacterial isolates were Klebsiella pneumoniae (25.50 %), Pseudomonas aeruginosa (16.77 %) and Haemophilus influenzae (15.43 %). Levofloxacin was the most effective antibiotic with excellent activity against both gram positive and gram negative isolates. Most patients with aspiration had laryngeal cancer (34.89 %). Aspiration pneumonia was present in 14 (9.39 %) patients. Gram negative bacteria are common etiologic agents in head and neck cancer patients presenting with features of aspiration. Levofloxacin should be started as empirical antibiotic in these patients while awaiting sputum culture sensitivity report. As aspiration in head and neck cancer is an underreported event such institutional antibiotic sensitivity

  19. 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.

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

    Science.gov (United States)

    Ewart, Tom; Carmichael, Stuart; Lea, Peter

    2005-09-01

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

  1. The Effects of Cropping Regimes on Fungal and Bacterial Communities of Wheat and Faba Bean in a Greenhouse Pot Experiment Differ between Plant Species and Compartment

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    Sandra Granzow

    2017-05-01

    Full Text Available Many bacteria and fungi in the plant rhizosphere and endosphere are beneficial to plant nutrient acquisition, health, and growth. Although playing essential roles in ecosystem functioning, our knowledge about the effects of multiple cropping regimes on the plant microbiome and their interactions is still limited. Here, we designed a pot experiment simulating different cropping regimes. For this purpose, wheat and faba bean plants were grown under controlled greenhouse conditions in monocultures and in two intercropping regimes: row and mixed intercropping. Bacterial and fungal communities in bulk and rhizosphere soils as well as in the roots and aerial plant parts were analyzed using large-scale metabarcoding. We detected differences in microbial richness and diversity between the cropping regimes. Generally, observed effects were attributed to differences between mixed and row intercropping or mixed intercropping and monoculture. Bacterial and fungal diversity were significantly higher in bulk soil samples of wheat and faba bean grown in mixed compared to row intercropping. Moreover, microbial communities varied between crop species and plant compartments resulting in different responses of these communities toward cropping regimes. Leaf endophytes were not affected by cropping regime but bacterial and fungal community structures in bulk and rhizosphere soil as well as fungal community structures in roots. We further recorded highly complex changes in microbial interactions. The number of negative inter-domain correlations between fungi and bacteria decreased in bulk and rhizosphere soil in intercropping regimes compared to monocultures due to beneficial effects. In addition, we observed plant species-dependent differences indicating that intra- and interspecific competition between plants had different effects on the plant species and thus on their associated microbial communities. To our knowledge, this is the first study investigating

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

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

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

  3. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets.

    Science.gov (United States)

    Yang, Jianji; Cohen, Aaron; Hersh, William

    2009-02-05

    Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS) is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html.

  4. mRNA expression in rabbit experimental aneurysms: a study using gene chip microarrays.

    Science.gov (United States)

    Mangrum, W I; Farassati, F; Kadirvel, R; Kolbert, C P; Raghavakaimal, S; Dai, D; Ding, Y H; Grill, D; Khurana, V G; Kallmes, D F

    2007-05-01

    The molecular characteristics of intracranial aneurysms are still poorly documented. A rabbit elastase aneurysm model has been helpful in the evaluation of devices and strategies involved in endovascular treatment of aneurysms. The goal of this project was to document the molecular changes, assessed by gene chip microarrays, associated with the creation of aneurysms in this model compared with the contralateral carotid artery. A microarray of rabbit genes of interest was constructed using rabbit nucleotide sequences from GenBank. Elastase-induced saccular aneurysms were created at the origin of the right common carotid artery in 4 rabbits. Twelve weeks after aneurysm creation, RNA was isolated from the aneurysm as well as the contralateral common carotid artery and used for microarray experiments. Reverse transcription-polymerase chain reaction (RT-PCR) was performed on 1 animal as a confirmatory test. Ninety-six (46%) of 209 genes in the microarray were differentially expressed in the rabbit aneurysm compared with the contralateral common carotid artery. In general, differential gene expression followed specific molecular pathways. Similarities were found between rabbit aneurysms and human intracranial aneurysms, including increased metalloproteinase activity and decreased production of the extracellular matrix. RT-PCR results confirmed the differential expression found by the gene chip microarray. The molecular characteristics of the rabbit elastase-induced saccular aneurysm are described. The rabbit aneurysm model shares some molecular features with human intracranial aneurysms. Future studies can use the rabbit model and the new rabbit gene chip microarray to study the molecular aspects of saccular aneurysms.

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

    Science.gov (United States)

    Uziela, Karolis; Honkela, Antti

    2015-01-01

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

  6. 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.

  7. The development of a DNA microarray-based assay for the characterization of commercially formulated microbial products.

    Science.gov (United States)

    Dubois, J W; Hill, S; England, L S; Edge, T; Masson, L; Trevors, J T; Brousseau, R

    2004-08-01

    Commercially formulated bioproducts containing a complex consortia of bacteria as an active ingredient pose a significant challenge for regulatory agencies and companies seeking to assess the safety and efficacy of these bioproducts. The main challenge stems from how to characterize the bacterial composition of these products, for which there is presently a lack of suitable methods. A prototype DNA microarray composed of oligonucleotide probes for functional genes, virulence factors, and taxonomic genes for a number of bacterial species was developed to examine the utility of microarray technology as a molecular tool for characterizing consortia bioproducts. The genomic DNA from four different products was extracted by two methods and examined with the microarray prototype and by denaturing gradient gel electrophoresis (DGGE). Although the identity of the consortial species remains unknown, the microarray assay provided unique and reproducible hybridization patterns for all four products, and agreed with the fingerprints generated by DGGE. The ability to differentiate between a variety of consortia products demonstrates that DNA microarrays have the potential to be a powerful tool in monitoring complex microbial communities.

  8. Advancing microarray assembly with acoustic dispensing technology.

    Science.gov (United States)

    Wong, E Y; Diamond, S L

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Wang Jelai

    2006-02-01

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

  10. Handling gene redundancy in microarray data using Grey Relational Analysis.

    Science.gov (United States)

    Zhang, Li-Juan; Li, Zhou-Jun; Chen, Huo-Wang

    2008-01-01

    Gene selection is one of the important and frequently used techniques for microarray data classification. In this paper, we introduce a new metric to measure gene-class relevance and gene-gene redundancy. The new metric is based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), and never used in gene selection before. Based on the GRG, we develop a new gene selection method, which uses GRG to group similar genes to clusters, and then select informative genes from each cluster to avoid redundancy. Experiments on public data sets demonstrate the effectiveness of the proposed method.

  11. GenePublisher: automated analysis of DNA microarray data

    DEFF Research Database (Denmark)

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

    2003-01-01

    , 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.......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...

  12. Bacterial Proteasomes.

    Science.gov (United States)

    Jastrab, Jordan B; Darwin, K Heran

    2015-01-01

    Interest in bacterial proteasomes was sparked by the discovery that proteasomal degradation is required for the pathogenesis of Mycobacterium tuberculosis, one of the world's deadliest pathogens. Although bacterial proteasomes are structurally similar to their eukaryotic and archaeal homologs, there are key differences in their mechanisms of assembly, activation, and substrate targeting for degradation. In this article, we compare and contrast bacterial proteasomes with their archaeal and eukaryotic counterparts, and we discuss recent advances in our understanding of how bacterial proteasomes function to influence microbial physiology.

  13. 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

  14. Hybridization and Selective Release of DNA Microarrays

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-11-29

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

  15. 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

  16. Detecting Outlier Microarray Arrays by Correlation and Percentage of Outliers Spots

    Directory of Open Access Journals (Sweden)

    Song Yang

    2006-01-01

    Full Text Available We developed a quality assurance (QA tool, namely microarray outlier filter (MOF, and have applied it to our microarray datasets for the identification of problematic arrays. Our approach is based on the comparison of the arrays using the correlation coefficient and the number of outlier spots generated on each array to reveal outlier arrays. For a human universal reference (HUR dataset, which is used as a technical control in our standard hybridization procedure, 3 outlier arrays were identified out of 35 experiments. For a human blood dataset, 12 outlier arrays were identified from 185 experiments. In general, arrays from human blood samples displayed greater variation in their gene expression profiles than arrays from HUR samples. As a result, MOF identified two distinct patterns in the occurrence of outlier arrays. These results demonstrate that this methodology is a valuable QA practice to identify questionable microarray data prior to downstream analysis.

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

    Science.gov (United States)

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

    2009-05-15

    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. 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. 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. 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.

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

    Directory of Open Access Journals (Sweden)

    King-Jung Lin

    2012-02-01

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

  20. 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.

  1. Bacterial adhesion

    NARCIS (Netherlands)

    Loosdrecht, van M.C.M.

    1988-01-01

    As mentioned in the introduction of this thesis bacterial adhesion has been studied from a variety of (mostly practice oriented) starting points. This has resulted in a range of widely divergent approaches. In order to elucidate general principles in bacterial adhesion phenomena, we felt it

  2. Biological microarray interpretation : The rules of engagement

    NARCIS (Netherlands)

    Breitling, Rainer

    2006-01-01

    Gene expression microarrays are now established as a standard tool in biological and biochemical laboratories. Interpreting the masses of data generated by this technology poses a number of unusual new challenges. Over the past few years a consensus has begun to emerge concerning the most important

  3. 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.

  4. Microarray technology: a promising tool in nutrigenomics.

    Science.gov (United States)

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

    2010-08-01

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

  5. Comparing transformation methods for DNA microarray data

    NARCIS (Netherlands)

    Thygesen, Helene H.; Zwinderman, Aeilko H.

    2004-01-01

    Background: When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include

  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. Evaluating different methods of microarray data normalization

    Directory of Open Access Journals (Sweden)

    Ferreira Carlos

    2006-10-01

    Full Text Available Abstract Background With the development of DNA hybridization microarray technologies, nowadays it is possible to simultaneously assess the expression levels of thousands to tens of thousands of genes. Quantitative comparison of microarrays uncovers distinct patterns of gene expression, which define different cellular phenotypes or cellular responses to drugs. Due to technical biases, normalization of the intensity levels is a pre-requisite to performing further statistical analyses. Therefore, choosing a suitable approach for normalization can be critical, deserving judicious consideration. Results Here, we considered three commonly used normalization approaches, namely: Loess, Splines and Wavelets, and two non-parametric regression methods, which have yet to be used for normalization, namely, the Kernel smoothing and Support Vector Regression. The results obtained were compared using artificial microarray data and benchmark studies. The results indicate that the Support Vector Regression is the most robust to outliers and that Kernel is the worst normalization technique, while no practical differences were observed between Loess, Splines and Wavelets. Conclusion In face of our results, the Support Vector Regression is favored for microarray normalization due to its superiority when compared to the other methods for its robustness in estimating the normalization curve.

  8. Ecologically relevant stress resistance: from microarrays and ...

    Indian Academy of Sciences (India)

    2004-10-15

    Oct 15, 2004 ... Home; Journals; Journal of Biosciences; Volume 29; Issue 4. Ecologically relevant stress resistance: from microarrays and quantitative trait loci to candidate genes – A research plan and preliminary results using Drosophila as a model organism and climatic and genetic stress as model stresses.

  9. Design of a covalently bonded glycosphingolipid microarray

    DEFF Research Database (Denmark)

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

    2012-01-01

    Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform for in vi......Glycosphingolipids (GSLs) are well known ubiquitous constituents of all eukaryotic cell membranes, yet their normal biological functions are not fully understood. As with other glycoconjugates and saccharides, solid phase display on microarrays potentially provides an effective platform......, 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......-mercaptoethylamine, was also tested. Underivatized or linker-derivatized lyso-GSL were then immobilized on N-hydroxysuccinimide- or epoxide-activated glass microarray slides and probed with carbohydrate binding proteins of known or partially known specificities (i.e., cholera toxin B-chain; peanut agglutinin...

  10. 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...

  11. Microarray Analysis of Space-flown Murine Thymus Tissue

    Data.gov (United States)

    National Aeronautics and Space Administration — Microarray Analysis of Space-flown Murine Thymus Tissue Reveals Changes in Gene Expression Regulating Stress and Glucocorticoid Receptors. We used microarrays to...

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

    Science.gov (United States)

    Chakraborty, Debasis; Maulik, Ujjwal

    2014-01-01

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

  14. Microarray analysis of defined Mycobacterium tuberculosis populations using RNA amplification strategies

    Directory of Open Access Journals (Sweden)

    Butcher Philip D

    2008-02-01

    Full Text Available Abstract Background The amplification of bacterial RNA is required if complex host-pathogen interactions are to be studied where the recovery of bacterial RNA is limited. Here, using a whole genome Mycobacterium tuberculosis microarray to measure cross-genome representation of amplified mRNA populations, we have investigated two approaches to RNA amplification using different priming strategies. The first using oligo-dT primers after polyadenylation of the bacterial RNA, the second using a set of mycobacterial amplification-directed primers both linked to T7 polymerase in vitro run off transcription. Results The reproducibility, sensitivity, and the representational bias introduced by these amplification systems were examined by contrasting expression profiles of the amplified products from inputs of 500, 50 and 5 ng total M. tuberculosis RNA with unamplified RNA from the same source. In addition, as a direct measure of the effectiveness of bacterial amplification for identifying biologically relevant changes in gene expression, a model M. tuberculosis system of microaerophilic growth and non-replicating persistence was used to assess the capability of amplified RNA microarray comparisons. Mycobacterial RNA was reproducibly amplified using both methods from as little as 5 ng total RNA (~equivalent to 2 × 105 bacilli. Differential gene expression patterns observed with unamplified RNA in the switch from aerobic to microaerophilic growth were also reflected in the amplified expression profiles using both methods. Conclusion Here we describe two reproducible methods of bacterial RNA amplification that will allow previously intractable host-pathogen interactions during bacterial infection to be explored at the whole genome level by RNA profiling.

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

    Directory of Open Access Journals (Sweden)

    Daniel Belstrøm

    2015-04-01

    Full Text Available 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.

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

    Science.gov (United States)

    Belstrøm, Daniel; Fiehn, Nils-Erik; Nielsen, Claus H.; Klepac-Ceraj, Vanja; Paster, Bruce J.; Twetman, Svante; Holmstrup, Palle

    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. PMID:25854857

  17. 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....

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

    DEFF Research Database (Denmark)

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

    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...... are exponentially growing, the text corpora are sparse and inconsistent in spite of attempts to standardize the format. Ordinary keyword search may in some cases be insucient to nd rele- vant information and the potential benet of using a semantic approach in this context has only been investigated to a limited...

  19. Bacterial Vaginosis

    Science.gov (United States)

    ... Archive STDs Home Page Bacterial Vaginosis (BV) Chlamydia Gonorrhea Genital Herpes Hepatitis HIV/AIDS & STDs Human Papillomavirus ( ... of getting other STDs, such as chlamydia and gonorrhea . These bacteria can sometimes cause pelvic inflammatory disease ( ...

  20. Evaluation criteria of rat hepatocytes transcriptome analysis under the influence of interferon alpha by DNA microarray

    Directory of Open Access Journals (Sweden)

    Kuklin A. V.

    2013-10-01

    Full Text Available The changes induced in transcriptome of rat hepatocytes treated with interferon alpha (IFN during three and six hours were analyzed by DNA microarray. Aim. To conduct a stepwise analysis of the results of microarray experiment and to determine whether they meet/fail to the conventional requirements. Methods. The files obtained after scanning microarrays were subjected to the analysis in statistical environment R by Bioconductor’s packages «affy», «simpleaffy», «affyPLM» and BRB Array Tools software for paired T-test. Results. All microarrays had quality metrics lying within recommended ranges, passed quality control, were normalized and are comparable with each other. The T-test revealed 28 and 124 differentially expressed genes after three and six hours of cells cultivation with IFNα , respectively. Conclusions. The obtained data meet the conventional criteria of quality and are applicable for further evaluation of their biological significance. The R-codes used in this study can be used for the analysis of the microarrays data.

  1. Cross-platform comparison of microarray-based multiple-class prediction.

    Directory of Open Access Journals (Sweden)

    Xiaohui Fan

    Full Text Available High-throughput microarray technology has been widely applied in biological and medical decision-making research during the past decade. However, the diversity of platforms has made it a challenge to re-use and/or integrate datasets generated in different experiments or labs for constructing array-based diagnostic models. Using large toxicogenomics datasets generated using both Affymetrix and Agilent microarray platforms, we carried out a benchmark evaluation of cross-platform consistency in multiple-class prediction using three widely-used machine learning algorithms. After an initial assessment of model performance on different platforms, we evaluated whether predictive signature features selected in one platform could be directly used to train a model in the other platform and whether predictive models trained using data from one platform could predict datasets profiled using the other platform with comparable performance. Our results established that it is possible to successfully apply multiple-class prediction models across different commercial microarray platforms, offering a number of important benefits such as accelerating the possible translation of biomarkers identified with microarrays to clinically-validated assays. However, this investigation focuses on a technical platform comparison and is actually only the beginning of exploring cross-platform consistency. Further studies are needed to confirm the feasibility of microarray-based cross-platform prediction, especially using independent datasets.

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

    DEFF Research Database (Denmark)

    Podolska, Agnieszka; Kaczkowski, Bogumil; Litman, Thomas

    2011-01-01

    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......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 microRNA...... 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....

  3. Bacterial community dynamics and activity in relation to dissolved organic matter availability during sea-ice formation in a mesocosm experiment.

    Science.gov (United States)

    Eronen-Rasimus, Eeva; Kaartokallio, Hermanni; Lyra, Christina; Autio, Riitta; Kuosa, Harri; Dieckmann, Gerhard S; Thomas, David N

    2014-02-01

    The structure of sea-ice bacterial communities is frequently different from that in seawater. Bacterial entrainment in sea ice has been studied with traditional microbiological, bacterial abundance, and bacterial production methods. However, the dynamics of the changes in bacterial communities during the transition from open water to frozen sea ice is largely unknown. Given previous evidence that the nutritional status of the parent water may affect bacterial communities during ice formation, bacterial succession was studied in under ice water and sea ice in two series of mesocosms: the first containing seawater from the North Sea and the second containing seawater enriched with algal-derived dissolved organic matter (DOM). The composition and dynamics of bacterial communities were investigated with terminal restriction fragment length polymorphism (T-RFLP), and cloning alongside bacterial production (thymidine and leucine uptake) and abundance measurements (measured by flow cytometry). Enriched and active sea-ice bacterial communities developed in ice formed in both unenriched and DOM-enriched seawater (0-6 days). γ-Proteobacteria dominated in the DOM-enriched samples, indicative of their capability for opportunistic growth in sea ice. The bacterial communities in the unenriched waters and ice consisted of the classes Flavobacteria, α- and γ-Proteobacteria, which are frequently found in natural sea ice in polar regions. Furthermore, the results indicate that seawater bacterial communities are able to adapt rapidly to sudden environmental changes when facing considerable physicochemical stress such as the changes in temperature, salinity, nutrient status, and organic matter supply during ice formation. © 2014 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

  4. 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

  5. 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.

  6. 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.

  7. Facilitating RNA structure prediction with microarrays.

    Science.gov (United States)

    Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

    2006-01-17

    Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

  8. Characterization, validation and application of a DNA microarray for the detection of mandatory and other waterborne pathogens.

    Science.gov (United States)

    Gomes, Maria; Vieira, Helena; Vale, Filipa F

    2015-11-01

    Culture methods for the detection of indicator bacteria are currently used for detection of waterborne bacteria. The need for an increased range of analyzed bacteria coupled with the obtainment of rapid and early results justify the development of a DNA microarray for the identification of waterborne pathogens. This DNA microarray has 16 implanted probes with a median size of 147 bases, targeting 12 different parameters, including all mandatory indicator microorganisms, such as Escherichia coli, Clostridium perfringens, Pseudomonas aeruginosa, Staphylococcus aureus, total and fecal coliforms and enterococci. The validation performed with DNA extracted from pure microbial cultures showed the suitability of the probes for detection of the target microorganism. To overcome the high dilution of water samples it was included either a prior culture step of bacterial contaminants retained after filtering 100 ml of water, or a 10-fold increase in the volume of filtered water, that resulted in the increase of the detected bacteria. The analysis of complex environmental water samples using culture methods and the DNA microarray revealed that the latter detected the same parameters plus other bacteria tested only in the DNA microarray. The results show that this DNA microarray may be a useful tool for water microbiological surveillance. © The Authors 2015. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

  9. 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.

  10. Respiratory Tularemia:Francisella Tularensisand Microarray Probe Designing.

    Science.gov (United States)

    Ranjbar, Reza; Behzadi, Payam; Mammina, Caterina

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-27

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

  12. Tissue Microarray Analysis Applied to Bone Diagenesis

    OpenAIRE

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

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens....

  13. A New Distribution Family for Microarray Data

    Directory of Open Access Journals (Sweden)

    Diana Mabel Kelmansky

    2017-02-01

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

  14. DNA Microarray for Detection of Gastrointestinal Viruses

    Science.gov (United States)

    Martínez, Miguel A.; Soto-del Río, María de los Dolores; Gutiérrez, Rosa María; Chiu, Charles Y.; Greninger, Alexander L.; Contreras, Juan Francisco; López, Susana; Arias, Carlos F.

    2014-01-01

    Gastroenteritis is a clinical illness of humans and other animals that is characterized by vomiting and diarrhea and caused by a variety of pathogens, including viruses. An increasing number of viral species have been associated with gastroenteritis or have been found in stool samples as new molecular tools have been developed. In this work, a DNA microarray capable in theory of parallel detection of more than 100 viral species was developed and tested. Initial validation was done with 10 different virus species, and an additional 5 species were validated using clinical samples. Detection limits of 1 × 103 virus particles of Human adenovirus C (HAdV), Human astrovirus (HAstV), and group A Rotavirus (RV-A) were established. Furthermore, when exogenous RNA was added, the limit for RV-A detection decreased by one log. In a small group of clinical samples from children with gastroenteritis (n = 76), the microarray detected at least one viral species in 92% of the samples. Single infection was identified in 63 samples (83%), and coinfection with more than one virus was identified in 7 samples (9%). The most abundant virus species were RV-A (58%), followed by Anellovirus (15.8%), HAstV (6.6%), HAdV (5.3%), Norwalk virus (6.6%), Human enterovirus (HEV) (9.2%), Human parechovirus (1.3%), Sapporo virus (1.3%), and Human bocavirus (1.3%). To further test the specificity and sensitivity of the microarray, the results were verified by reverse transcription-PCR (RT-PCR) detection of 5 gastrointestinal viruses. The RT-PCR assay detected a virus in 59 samples (78%). The microarray showed good performance for detection of RV-A, HAstV, and calicivirus, while the sensitivity for HAdV and HEV was low. Furthermore, some discrepancies in detection of mixed infections were observed and were addressed by reverse transcription-quantitative PCR (RT-qPCR) of the viruses involved. It was observed that differences in the amount of genetic material favored the detection of the most abundant

  15. Classification across gene expression microarray studies

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    Kuner Ruprecht

    2009-12-01

    Full Text Available Abstract Background The increasing number of gene expression microarray studies represents an important resource in biomedical research. As a result, gene expression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

  16. Discussion on research methods of bacterial resistant mutation mechanisms under selective culture--uncertainty analysis of data from the Luria-Delbrück fluctuation experiment.

    Science.gov (United States)

    Jin, Jianling; Wei, Gang; Yang, Weiqiang; Zhang, Huaiqiang; Gao, Peiji

    2012-11-01

    Whether bacterial drug-resistance is drug-induced or results from rapid propagation of random spontaneous mutations in the flora prior to exposure, remains a long-term key issue concerned and debated in both genetics and medicinal fields. In a pioneering study, Luria and Delbrück exposed E. coli to T1 phage, to investigate whether the number of resistant colonies followed the Poisson distribution. They deduced that the development of resistant colonies is independent of phage presence. Similar results have since been obtained on solid medium containing antibacterial agents. Luria and Delbrück's conclusions were long considered a gold standard for analyzing drug resistance mutations. More recently, the concept of adaptive mutation has triggered controversy over this approach. Microbiological observation shows that, following exposure to drugs of various concentrations, drug-resistant cells emerge and multiply depending on the time course, and show a process function, inconsistent with the definition of Poisson distribution (which assumes not only that resistance is independent of drug quantity but follows no specific time course). At the same time, since cells tend to aggregate after division rather than separating, colonies growing on drug plates arise from the multiplication of resistant bacteria cells of various initial population sizes. Thus, statistical analysis based on equivalence of initial populations will yield erroneous results. In this paper, 310 data from the Luria-Delbrück fluctuation experiment were reanalyzed from this perspective. In most cases, a high-end abnormal value, resulting from the non-synchronous variation of the two above-mentioned time variables, was observed. Therefore, the mean value cannot be regarded as an unbiased expectation estimate. The ratio between mean value and variance was similarly incomparable, because two different sampling methods were used. In fact, the Luria-Delbrück data appear to follow an aggregated, rather than

  17. 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...... operons in E. coli using this method, which we call Microarray-Oligonucleotide (MO)-MAGE. The resulting mutant library was characterized by high-throughput sequencing to show that all attempted insertions were estimated to have occurred at an average frequency of 0.02 % per loci with 0.4 average...

  18. Serious limitations of the QTL/Microarray approach for QTL gene discovery

    Directory of Open Access Journals (Sweden)

    Warden Craig H

    2010-07-01

    Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes

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

    Science.gov (United States)

    Stokes, Todd H; Torrance, J T; Li, Henry; Wang, May D

    2008-05-28

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

  20. BACTERIAL CONSORTIUM

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    Payel Sarkar

    2013-01-01

    Full Text Available Petroleum aromatic hydrocarbons like benzen e, toluene, ethyl benzene and xylene, together known as BTEX, has almost the same chemical structure. These aromatic hydrocarbons are released as pollutants in th e environment. This work was taken up to develop a solvent tolerant bacterial cons ortium that could degrade BTEX compounds as they all share a common chemical structure. We have isolated almost 60 different types of bacterial strains from different petroleum contaminated sites. Of these 60 bacterial strains almost 20 microorganisms were screene d on the basis of capability to tolerate high concentration of BTEX. Ten differe nt consortia were prepared and the compatibility of the bacterial strains within the consortia was checked by gram staining and BTEX tolerance level. Four successful mi crobial consortia were selected in which all the bacterial strains concomitantly grew in presence of high concentration of BTEX (10% of toluene, 10% of benzene 5% ethyl benzene and 1% xylene. Consortium #2 showed the highest growth rate in pr esence of BTEX. Degradation of BTEX by consortium #2 was monitored for 5 days by gradual decrease in the volume of the solvents. The maximum reduction observed wa s 85% in 5 days. Gas chromatography results also reveal that could completely degrade benzene and ethyl benzene within 48 hours. Almost 90% degradation of toluene and xylene in 48 hours was exhibited by consortium #2. It could also tolerate and degrade many industrial solvents such as chloroform, DMSO, acetonitrile having a wide range of log P values (0.03–3.1. Degradation of aromatic hydrocarbon like BTEX by a solvent tolerant bacterial consortium is greatly significant as it could degrade high concentration of pollutants compared to a bacterium and also reduces the time span of degradation.

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

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    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.

  2. 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.

  3. Accurate Detection of Carcinoma Cells by Use of a Cell Microarray Chip

    Science.gov (United States)

    Yamamura, Shohei; Yatsushiro, Shouki; Yamaguchi, Yuka; Abe, Kaori; Shinohara, Yasuo; Tamiya, Eiichi; Baba, Yoshinobu; Kataoka, Masatoshi

    2012-01-01

    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. PMID:22396762

  4. Design, construction and validation of a Plasmodium vivax microarray for the transcriptome profiling of clinical isolates

    KAUST Repository

    Boopathi, Pon Arunachalam

    2016-10-09

    High density oligonucleotide microarrays have been used on Plasmodium vivax field isolates to estimate whole genome expression. However, no microarray platform has been experimentally optimized for studying the transcriptome of field isolates. In the present study, we adopted both bioinformatics and experimental testing approaches to select best optimized probes suitable for detecting parasite transcripts from field samples and included them in designing a custom 15K P. vivax microarray. This microarray has long oligonucleotide probes (60 mer) that were in-situ synthesized onto glass slides using Agilent SurePrint technology and has been developed into an 8X15K format (8 identical arrays on a single slide). Probes in this array were experimentally validated and represents 4180 P. vivax genes in sense orientation, of which 1219 genes have also probes in antisense orientation. Validation of the 15K array by using field samples (n =14) has shown 99% of parasite transcript detection from any of the samples. Correlation analysis between duplicate probes (n = 85) present in the arrays showed perfect correlation (r(2) = 0.98) indicating the reproducibility. Multiple probes representing the same gene exhibited similar kind of expression pattern across the samples (positive correlation, r >= 0.6). Comparison of hybridization data with the previous studies and quantitative real-time PCR experiments were performed to highlight the microarray validation procedure. This array is unique in its design, and results indicate that the array is sensitive and reproducible. Hence, this microarray could be a valuable functional genomics tool to generate reliable expression data from P. vivax field isolates. (C) 2016 Published by Elsevier B.V.

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

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    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.

  6. Exploring the use of internal and externalcontrols for assessing microarray technical performance

    Directory of Open Access Journals (Sweden)

    Game Laurence

    2010-12-01

    Full Text Available Abstract Background The maturing of gene expression microarray technology and interest in the use of microarray-based applications for clinical and diagnostic applications calls for quantitative measures of quality. This manuscript presents a retrospective study characterizing several approaches to assess technical performance of microarray data measured on the Affymetrix GeneChip platform, including whole-array metrics and information from a standard mixture of external spike-in and endogenous internal controls. Spike-in controls were found to carry the same information about technical performance as whole-array metrics and endogenous "housekeeping" genes. These results support the use of spike-in controls as general tools for performance assessment across time, experimenters and array batches, suggesting that they have potential for comparison of microarray data generated across species using different technologies. Results A layered PCA modeling methodology that uses data from a number of classes of controls (spike-in hybridization, spike-in polyA+, internal RNA degradation, endogenous or "housekeeping genes" was used for the assessment of microarray data quality. The controls provide information on multiple stages of the experimental protocol (e.g., hybridization, RNA amplification. External spike-in, hybridization and RNA labeling controls provide information related to both assay and hybridization performance whereas internal endogenous controls provide quality information on the biological sample. We find that the variance of the data generated from the external and internal controls carries critical information about technical performance; the PCA dissection of this variance is consistent with whole-array quality assessment based on a number of quality assurance/quality control (QA/QC metrics. Conclusions These results provide support for the use of both external and internal RNA control data to assess the technical quality of microarray

  7. Evaluation of a gene information summarization system by users during the analysis process of microarray datasets

    Directory of Open Access Journals (Sweden)

    Cohen Aaron

    2009-02-01

    Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html

  8. Hybridisation mix synthesis in a spiral lab-on-chip device for fast-track microarray genotyping of human pathogens

    Science.gov (United States)

    Peham, Johannes R.; Recnik, Lisa-Maria; Grienauer, Walter; Vellekoop, Michael J.; Nöhammer, Christa; Wiesinger-Mayr, Herbert

    2011-05-01

    DNA microarrays can provide bacterial identification, which is crucial for targeted therapy. However they lack rapidness, because of multiple analysis steps. Therefore a fast one-step method for synthesising a hybridisation-ready reagent out of initial bacterial DNA is required. This work presents the combination and acceleration of PCR and fluorescent labelling within a disposable microfluidic chip, fabricated by injection moulding. The utilised geometry consists of a spiral meander with 40 turns, representing a cyclic-flow PCR system. The used reaction chemistry includes Cy3-conjugated primers and a high-yield polymerase leading to a one-step process accelerated by cyclic-flow PCR. Three different bacterial samples (Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa) were processed and the bacterial DNA was successfully amplified and labelled with detection limits down to 102 cells per reaction. The specificity of species identification was comparable to the approach of separate PCR and labelling. Furthermore the overall processing time was decreased from 6 hours to 1.5 hours. We showed that a disposable polycarbonate chip, fabricated by injection moulding is suitable for the significant acceleration of DNA microarray assays. The reaction output lead to high-sensitivity bacterial identification in a short time, which is crucial for an early and targeted therapy against infectious diseases.

  9. 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...

  10. Bacterial meningitis

    NARCIS (Netherlands)

    Heckenberg, Sebastiaan G. B.; Brouwer, Matthijs C.; van de Beek, Diederik

    2014-01-01

    Bacterial meningitis is a neurologic emergency. Vaccination against common pathogens has decreased the burden of disease. Early diagnosis and rapid initiation of empiric antimicrobial and adjunctive therapy are vital. Therapy should be initiated as soon as blood cultures have been obtained,

  11. Bacterial lipases

    NARCIS (Netherlands)

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

    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,

  12. Bacterial Ecology

    DEFF Research Database (Denmark)

    Fenchel, Tom

    2011-01-01

    , the production and oxidation of methane, nitrate reduction and fixation of atmospheric nitrogen are exclusively carried out by different groups of bacteria. Some bacterial species – ‘extremophiles’ – thrive in extreme environments in which no eukaryotic organisms can survive with respect to temperature, salinity...

  13. Bacterial Vaginosis

    Science.gov (United States)

    ... that coats the walls of the vagina Vaginal discharge with an unpleasant or fishlike odor Vaginal pain or itching Burning during urination Doctors are unsure of the incubation period for bacterial vaginosis. How Is the Diagnosis Made? Your child’s pediatrician can make the diagnosis ...

  14. Bacterial stress

    Indian Academy of Sciences (India)

    First page Back Continue Last page Graphics. Bacterial stress. Physicochemical and chemical parameters: temperature, pressure, pH, salt concentration, oxygen, irradiation. Nutritional depravation: nutrient starvation, water shortage. Toxic compounds: Antibiotics, heavy metals, toxins, mutagens. Interactions with other cells: ...

  15. Bacterial Adhesion & Blocking Bacterial Adhesion

    DEFF Research Database (Denmark)

    Vejborg, Rebecca Munk

    2008-01-01

    reduce or delay bacterial biofilm formation of a range of urinary tract infectious E.coli and Klebsiella isolates. Several other proteinaceous coatings were also found to display anti-adhesive properties, possibly providing a measure for controlling the colonization of implant materials. Several other...... components. These substances may both mediate and stabilize the bacterial biofilm. Finally, several adhesive structures were examined, and a novel physiological biofilm phenotype in E.coli biofilms was characterized, namely cell chain formation. The autotransporter protein, antigen 43, was implicated...

  16. 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.

  17. Performance of a 70-mer oligonucleotide microarray for genotyping of Campylobacter jejuni

    Directory of Open Access Journals (Sweden)

    Ljungström Marianne

    2008-05-01

    Full Text Available Abstract Background Campylobacter jejuni is widespread in the environment and is the major cause of bacterial gastroenteritis in humans. In the present study we use microarray-based comparative genomic hybridizations (CGH, pulsed-field gel electrophoresis (PFGE and multilocus sequence typing (MLST to analyze closely related C. jejuni isolates from chicken and human infection. Results With the exception of one isolate, the microarray data clusters the isolates according to the five groups determined by PFGE. In contrast, MLST defines only three genotypes among the isolates, indicating a lower resolution. All methods show that there is no inherit difference between isolates infecting humans and chicken, suggesting a common underlying population of C. jejuni. We further identify regions that frequently differ between isolates, including both previously described and novel regions. Finally, we show that genes that belong to certain functional groups differ between isolates more often than expected by chance. Conclusion In this study we demonstrated the utility of 70-mer oligonucleotide microarrays for genotyping of Campylobacter jejuni isolates, with resolution outperforming MLST.

  18. 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.

  19. Antigen microarrays: descriptive chemistry or functional immunomics?

    Science.gov (United States)

    Prechl, József; Papp, Krisztián; Erdei, Anna

    2010-04-01

    Advances in protein microarray technology allow the generation of high content, reliable information about complex, multilevel protein interaction networks. Yet antigen arrays are used mostly only as devices for parallel immune assays describing multitudes of individual binding events. We propose here that the huge amount of immunological information hidden in the plasma of an individual could be better revealed by combining the characterization of antibody binding to target epitopes with improved estimation of effector functions triggered by these binding events. Furthermore, we could generate functional immune profiles characterizing general immune responsiveness of the individual by designing arrays incorporating epitope collections from diverse subsets of antibody targets. Copyright 2010 Elsevier Ltd. All rights reserved.

  20. Microarray technology applied to the complex disorder of preeclampsia.

    Science.gov (United States)

    Founds, Sandra A; Dorman, Janice S; Conley, Yvette P

    2008-01-01

    Preeclampsia is a life-threatening perinatal complication with unknown etiology. Microarray technology has characterized global gene expression in complex disorders such as preeclampsia. Nursing research and future practice may incorporate findings from microarray analyses to identify susceptibility to and prevent disease, to diagnose early, and to design and monitor personalized therapies. This overview of microarray technology, with emphasis on how it can inform genomics of preeclampsia, may provide concepts to improve future maternal-neonatal nursing care.

  1. 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.

  2. Bacterial lipases

    OpenAIRE

    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, meaning a sharp increase in lipase activity observed when the substrate starts to form an emulsion, thereby presenting to the enzyme an interfacial area. As a consequence, the kinetics of a lipase rea...

  3. Enzyme microarrays assembled by acoustic dispensing technology.

    Science.gov (United States)

    Wong, E Y; Diamond, S L

    2008-10-01

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

  4. Additive risk survival model with microarray data

    Directory of Open Access Journals (Sweden)

    Huang Jian

    2007-06-01

    Full Text Available Abstract Background Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with survival risks for diseases such as lymphoma and construct predictive models using those selected genes. In this article, we investigate simultaneous estimation and gene selection with right censored survival data and high dimensional gene expression measurements. Results We model the survival time using the additive risk model, which provides a useful alternative to the proportional hazards model and is adopted when the absolute effects, instead of the relative effects, of multiple predictors on the hazard function are of interest. A Lasso (least absolute shrinkage and selection operator type estimate is proposed for simultaneous estimation and gene selection. Tuning parameter is selected using the V-fold cross validation. We propose Leave-One-Out cross validation based methods for evaluating the relative stability of individual genes and overall prediction significance. Conclusion We analyze the MCL and DLBCL data using the proposed approach. A small number of probes represented on the microarrays are identified, most of which have sound biological implications in lymphoma development. The selected probes are relatively stable and the proposed approach has overall satisfactory prediction power.

  5. An algorithm for finding biologically significant features in microarray data based on a priori manifold learning.

    Directory of Open Access Journals (Sweden)

    Zena M Hira

    Full Text Available Microarray databases are a large source of genetic data, which, upon proper analysis, could enhance our understanding of biology and medicine. Many microarray experiments have been designed to investigate the genetic mechanisms of cancer, and analytical approaches have been applied in order to classify different types of cancer or distinguish between cancerous and non-cancerous tissue. However, microarrays are high-dimensional datasets with high levels of noise and this causes problems when using machine learning methods. A popular approach to this problem is to search for a set of features that will simplify the structure and to some degree remove the noise from the data. The most widely used approach to feature extraction is principal component analysis (PCA which assumes a multivariate Gaussian model of the data. More recently, non-linear methods have been investigated. Among these, manifold learning algorithms, for example Isomap, aim to project the data from a higher dimensional space onto a lower dimension one. We have proposed a priori manifold learning for finding a manifold in which a representative set of microarray data is fused with relevant data taken from the KEGG pathway database. Once the manifold has been constructed the raw microarray data is projected onto it and clustering and classification can take place. In contrast to earlier fusion based methods, the prior knowledge from the KEGG databases is not used in, and does not bias the classification process--it merely acts as an aid to find the best space in which to search the data. In our experiments we have found that using our new manifold method gives better classification results than using either PCA or conventional Isomap.

  6. 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.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Gravelat Fabrice

    2010-09-01

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

  9. Considerations when using the significance analysis of microarrays (SAM algorithm

    Directory of Open Access Journals (Sweden)

    Timmons James A

    2005-05-01

    Full Text Available Abstract Background Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments. One of the most frequently utilised methods for gene expression data analysis is SAM (significance analysis of microarrays. The impact of selection thresholds, on the output from SAM, may critically alter the conclusion of a study, yet this consideration has not been systematically evaluated in any publication. Results We have examined the effect of discrete data selection criteria (qualification criteria for inclusion and response thresholds (out-put filtering on the number of significant genes reported by SAM. The use of a reduced data set by applying arbitrary restrictions vis-à-vis abundance calls (e.g. from D-chip or application of the fold change (FC option within SAM (named the FC hurdle hereafter, can substantially alter the significant gene list when running SAM in Microsoft Excel. We determined that for a given final FC criteria (e.g. 1.5 fold change the FC hurdle applied within Microsoft Excel SAM alters the number of reported genes above the final FC criteria. The reason is that the FC hurdle changes the composition of the control data set, such that a different significance level (q-value is obtained for any given gene. This effect can be so large that it changes subsequent post hoc analysis interpretation, such as ontology overrepresentation analysis. Conclusion Our results argue for caution when using SAM. All data sets analysed with SAM could be reanalysed taking into account the potential impact of the use of arbitrary thresholds to trim data sets before significance testing.

  10. Altered Bacterial Profiles in Saliva from Adults with Caries Lesions

    DEFF Research Database (Denmark)

    Belstrøm, D; Fiehn, N-E; Nielsen, C H

    2014-01-01

    The aim of this study was to learn whether presence of caries in an adult population was associated with a salivary bacterial profile different from that of individuals without untreated caries. Stimulated saliva samples from 621 participants of the Danish Health Examination Survey were analyzed ...... of commensal microbial communities are involved in the shift from oral health to tooth decay. © 2014 S. Karger AG, Basel....... using the Human Oral Microbe Identification Microarray technology. Samples from 174 individuals with dental caries and 447 from a control cohort were compared using frequency and levels of identified bacterial taxa/clusters as endpoints. Differences at taxon/cluster level were analyzed using Mann......-Whitney's test with Benjamini-Hochberg correction for multiple comparisons. Principal component analysis was used to visualize bacterial community profiles. A reduced bacterial diversity was observed in samples from subjects with dental caries. Five bacterial taxa (Veillonella parvula, Veillonella atypica...

  11. Bulk segregant analysis using single nucleotide polymorphism microarrays.

    Directory of Open Access Journals (Sweden)

    Anthony Becker

    2011-01-01

    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.

  12. Development of a gold nanoparticle-based universal oligonucleotide microarray for multiplex and low-cost detection of foodborne pathogens.

    Science.gov (United States)

    Wang, Xiaoqiang; Ying, Sisi; Wei, Xiaoguang; Yuan, Jun

    2017-07-17

    Bacterial foodborne diseases remain major threats to food safety and public health, especially in developing countries. In this study a novel assay, combining gold nanoparticle (GNP)-based multiplex oligonucleotide ligation-PCR and universal oligonucleotide microarray technology, was developed for inexpensive, specific, sensitive, and multiplex detection of eight common foodborne pathogens, including Shigella spp., Campylobacter jejuni, Bacillus cereus, Escherichia coli O157:H7, Listeria monocytogenes, Salmonella enterica, Staphylococcus aureus, and Vibrio parahaemolyticus. The target fragments of the eight pathogens were enriched by multiplex PCR and subjected to multiplex ligase detection reaction. Ligation products were enriched and labeled with GNPs by universal asymmetric PCR, using excess GNP-conjugated primers. The labeled single-stranded amplicons containing complementary tag sequences were captured by the corresponding tag sequences immobilized on microarrays, followed by silver staining for signal enhancement. Black images of microarray spots were visualized by naked eyes or scanned on a simple flatbed scanner, and quantified. The results indicated that this assay could unambiguously discriminate all eight pathogens in single and multiple infections, with detection sensitivity of 3.3-85CFU/mL for pure cultures. Microarray results of ninety-five artificially contaminated and retail food samples were consistent with traditional culture, biochemical and real-time PCR findings. Therefore, the novel assay has the potential to be used for routine detection due to rapidity, low cost, and high specificity and sensitivity. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. 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

  14. 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...

  15. Microarray-based Detection of Antibiotic Resisteance Genes in Salmonella

    NARCIS (Netherlands)

    Hoek, van A.H.A.M.; Aarts, H.J.M.

    2008-01-01

    In the presented study, 143 Salmonella isolates belonging to 26 different serovars were screened for the presence of antibiotic resistance genes by microarray analysis. The microarray contained a total of 223 oligonucleotides representing genes encoding for resistance to the following antibiotic

  16. A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

    NARCIS (Netherlands)

    Sontrop, H.M.J.

    2015-01-01

    Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

  17. 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.

  18. Bacterial mitosis

    DEFF Research Database (Denmark)

    Møller-Jensen, Jakob; Borch, Jonas; Dam, Mette

    2003-01-01

    Bacterial DNA segregation takes place in an active and ordered fashion. In the case of Escherichia coli plasmid R1, the partitioning system (par) separates paired plasmid copies and moves them to opposite cell poles. Here we address the mechanism by which the three components of the R1 par system...... movement is powered by insertional polymerization of ParM. Consistently, we find that segregating plasmids are positioned at the ends of extending ParM filaments. Thus, the process of R1 plasmid segregation in E. coli appears to be mechanistically analogous to the actin-based motility operating...

  19. Microarray Assisted Gene Discovery in Ulcerative Colitis

    DEFF Research Database (Denmark)

    Brusgaard, Klaus

    ), and microarray based expression studies. In IBD the increased production of chemo attractants from the inflamed microenvironment results in recruitment of activated CD4+ T lymphocytes which results in tissue damage. Where Th1 cell-derived cytokines has been reported to be essential mediators in CD with high (IFN...... on the activation of different downstream pathways. Thus it seems that different genetic backgrounds can lead to similar clinical manifestations, and as well determines the susceptibility to IBD. In the previous micro array based expression studies on UC the main target has been to point to new candidate genes...... based on analysis of the main up or down regulated genes in the dataset. The majority of the studies are hampered by a relatively shortcoming of the numbers of genes analysed on the particular array. In this study the main target has been to point to clusters of genes involved in biochemical pathways...

  20. 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.

  1. Bystander effect: Biological endpoints and microarray analysis

    Energy Technology Data Exchange (ETDEWEB)

    Chaudhry, M. Ahmad [Department of Medical Laboratory and Radiation Sciences, College of Nursing and Health Sciences, University of Vermont, 302 Rowell Building, Burlington, VT 05405 (United States) and DNA Microarray Facility, University of Vermont, Burlington, VT 05405 (United States)]. E-mail: mchaudhr@uvm.edu

    2006-05-11

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  2. Bystander effect: Biological endpoints and microarray analysis

    International Nuclear Information System (INIS)

    Chaudhry, M. Ahmad

    2006-01-01

    In cell populations exposed to ionizing radiation, the biological effects occur in a much larger proportion of cells than are estimated to be traversed by radiation. It has been suggested that irradiated cells are capable of providing signals to the neighboring unirradiated cells resulting in damage to these cells. This phenomenon is termed the bystander effect. The bystander effect induces persistent, long-term, transmissible changes that result in delayed death and neoplastic transformation. Because the bystander effect is relevant to carcinogenesis, it could have significant implications for risk estimation for radiation exposure. The nature of the bystander effect signal and how it impacts the unirradiated cells remains to be elucidated. Examination of the changes in gene expression could provide clues to understanding the bystander effect and could define the signaling pathways involved in sustaining damage to these cells. The microarray technology serves as a tool to gain insight into the molecular pathways leading to bystander effect. Using medium from irradiated normal human diploid lung fibroblasts as a model system we examined gene expression alterations in bystander cells. The microarray data revealed that the radiation-induced gene expression profile in irradiated cells is different from unirradiated bystander cells suggesting that the pathways leading to biological effects in the bystander cells are different from the directly irradiated cells. The genes known to be responsive to ionizing radiation were observed in irradiated cells. Several genes were upregulated in cells receiving media from irradiated cells. Surprisingly no genes were found to be downregulated in these cells. A number of genes belonging to extracellular signaling, growth factors and several receptors were identified in bystander cells. Interestingly 15 genes involved in the cell communication processes were found to be upregulated. The induction of receptors and the cell

  3. 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

  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. Deciphering cellular morphology and biocompatibility using polymer microarrays

    International Nuclear Information System (INIS)

    Pernagallo, Salvatore; Unciti-Broceta, Asier; DIaz-Mochon, Juan Jose; Bradley, Mark

    2008-01-01

    A quantitative and qualitative analysis of cellular adhesion, morphology and viability is essential in understanding and designing biomaterials such as those involved in implant surfaces or as tissue-engineering scaffolds. As a means to simultaneously perform these studies in a high-throughput (HT) manner, we report a normalized protocol which allows the rapid analysis of a large number of potential cell binding substrates using polymer microarrays and high-content fluorescence microscopy. The method was successfully applied to the discovery of optimal polymer substrates from a 214-member polyurethane library with mouse fibroblast cells (L929), as well as simultaneous evaluation of cell viability and cellular morphology. Analysis demonstrated high biocompatibility of the binding polymers and permitted the identification of several different cellular morphologies, showing that specific polymer interactions may provoke changes in cell shape. In addition, SAR studies showed a clear correspondence between cellular adhesion and polymer structure. The approach can be utilized to perform multiple experiments (up to 1024 single experiments per slide) in a highly reproducible manner, leading to the generation of vast amounts of data in a short time period (48-72 h) while reducing dramatically the quantities of polymers, reagents and cells used

  6. The tissue microarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource

    Directory of Open Access Journals (Sweden)

    Dhir Rajiv

    2004-02-01

    Full Text Available Abstract Background Tissue Microarrays (TMAs have emerged as a powerful tool for examining the distribution of marker molecules in hundreds of different tissues displayed on a single slide. TMAs have been used successfully to validate candidate molecules discovered in gene array experiments. Like gene expression studies, TMA experiments are data intensive, requiring substantial information to interpret, replicate or validate. Recently, an open access Tissue Microarray Data Exchange Specification has been released that allows TMA data to be organized in a self-describing XML document annotated with well-defined common data elements. While this specification provides sufficient information for the reproduction of the experiment by outside research groups, its initial description did not contain instructions or examples of actual implementations, and no implementation studies have been published. The purpose of this paper is to demonstrate how the TMA Data Exchange Specification is implemented in a prostate cancer TMA. Results The Cooperative Prostate Cancer Tissue Resource (CPCTR is funded by the National Cancer Institute to provide researchers with samples of prostate cancer annotated with demographic and clinical data. The CPCTR now offers prostate cancer TMAs and has implemented a TMA database conforming to the new open access Tissue Microarray Data Exchange Specification. The bulk of the TMA database consists of clinical and demographic data elements for 299 patient samples. These data elements were extracted from an Excel database using a transformative Perl script. The Perl script and the TMA database are open access documents distributed with this manuscript. Conclusions TMA databases conforming to the Tissue Microarray Data Exchange Specification can be merged with other TMA files, expanded through the addition of data elements, or linked to data contained in external biological databases. This article describes an open access

  7. The tissue microarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource.

    Science.gov (United States)

    Berman, Jules J; Datta, Milton; Kajdacsy-Balla, Andre; Melamed, Jonathan; Orenstein, Jan; Dobbin, Kevin; Patel, Ashok; Dhir, Rajiv; Becich, Michael J

    2004-02-27

    Tissue Microarrays (TMAs) have emerged as a powerful tool for examining the distribution of marker molecules in hundreds of different tissues displayed on a single slide. TMAs have been used successfully to validate candidate molecules discovered in gene array experiments. Like gene expression studies, TMA experiments are data intensive, requiring substantial information to interpret, replicate or validate. Recently, an open access Tissue Microarray Data Exchange Specification has been released that allows TMA data to be organized in a self-describing XML document annotated with well-defined common data elements. While this specification provides sufficient information for the reproduction of the experiment by outside research groups, its initial description did not contain instructions or examples of actual implementations, and no implementation studies have been published. The purpose of this paper is to demonstrate how the TMA Data Exchange Specification is implemented in a prostate cancer TMA. The Cooperative Prostate Cancer Tissue Resource (CPCTR) is funded by the National Cancer Institute to provide researchers with samples of prostate cancer annotated with demographic and clinical data. The CPCTR now offers prostate cancer TMAs and has implemented a TMA database conforming to the new open access Tissue Microarray Data Exchange Specification. The bulk of the TMA database consists of clinical and demographic data elements for 299 patient samples. These data elements were extracted from an Excel database using a transformative Perl script. The Perl script and the TMA database are open access documents distributed with this manuscript. TMA databases conforming to the Tissue Microarray Data Exchange Specification can be merged with other TMA files, expanded through the addition of data elements, or linked to data contained in external biological databases. This article describes an open access implementation of the TMA Data Exchange Specification and provides

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  10. Analysis of a simulated microarray dataset: Comparison of methods for data normalisation and detection of differntial expression

    NARCIS (Netherlands)

    Watson, M.; Perez-Alegre, M.; Denis Baron, M.; Delmas, C.; Dovc, P.; Duval, M.; Foulley, J.L.; Garrido-Pavon, J.J.; Hulsegge, B.; Jafrezic, F.; Jiménez-Marín, A.; Lavric, M.; Lê Cao, K.A.; Marot, G.; Mouzaki, D.; Pool, M.H.; Robert-Granié, C.; San Cristobal, M.; Tosser-Klop, G.; Waddington, D.; Koning, de D.J.

    2007-01-01

    Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised

  11. 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.

  12. Optimal designs for one- and two-color microarrays using mixed models: a comparative evaluation of their efficiencies.

    Science.gov (United States)

    Lima Passos, Valéria; Tan, Frans E S; Winkens, Bjorn; Berger, Martijn P F

    2009-01-01

    Comparative studies between the one- and two-color microarrays provide supportive evidence for similarities of results on differential gene expression. So far, no design comparisons between the two platforms have been undertaken. With the objective of comparing optimal designs of one- and two-color microarrays in their statistical efficiencies, techniques of design optimization were applied within a mixed model framework. A- and D-optimal designs for the one- and two-color platforms were sought for a 3 x 3 factorial experiment. The results suggest that the choice of the platform will not affect the "subjects to groups" allocation, being concordant in the two designs. However, under financial constraints, the two-color arrays are expected to have a slight upper hand in terms of efficiency of model parameters estimates, once the price of arrays is more expensive than that of subjects. This statement is especially valid for microarray studies envisaging class comparisons.

  13. Meta-analysis of gene expression microarrays with missing replicates

    Directory of Open Access Journals (Sweden)

    Leckie Christopher

    2011-03-01

    Full Text Available Abstract Background Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as incomplete genes, may also be informative and useful. Results We propose a meta-analysis framework, called "Incomplete Gene Meta-analysis", which can include incomplete genes by imputing the significance of missing replicates, and computing a meta-score for every gene across all datasets. We demonstrate that the incomplete genes are worthy of being included and our method is able to appropriately estimate their significance in two groups of experiments. We first apply the Incomplete Gene Meta-analysis and several comparable methods to five breast cancer datasets with an identical set of probes. We simulate incomplete genes by randomly removing a subset of probes from each dataset and demonstrate that our method consistently outperforms two other methods in terms of their false discovery rate. We also apply the methods to three gastric cancer datasets for the purpose of discriminating diffuse and intestinal subtypes. Conclusions Meta-analysis is an effective approach that identifies more robust sets of differentially expressed genes from multiple studies. The incomplete genes that mainly arise from the use of different platforms may also have statistical and biological importance but are ignored or are not appropriately involved by previous studies. Our Incomplete Gene Meta-analysis is able to incorporate the incomplete genes by estimating their significance. The results on both breast and gastric cancer datasets suggest that the highly ranked genes and associated GO

  14. 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....

  15. AFM 4.0: a toolbox for DNA microarray analysis.

    Science.gov (United States)

    Breitkreutz, B J; Jorgensen, P; Breitkreutz, A; Tyers, M

    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 laboratories that do not have access to specialized commercial or in-house software.

  16. Gene expression profile analysis in human hepatocellular carcinoma by cDNA microarray.

    Science.gov (United States)

    Chung, Eun Jung; Sung, Young Kwan; Farooq, Mohammad; Kim, Younghee; Im, Sanguk; Tak, Won Young; Hwang, Yoon Jin; Kim, Yang Il; Han, Hyung Soo; Kim, Jung-Chul; Kim, Moon Kyu

    2002-12-31

    We performed gene expression profiling of normal and hepatocellular carcinoma (HCC) liver tissues using a high-density microarray that contained 3,063 human cDNA. The results of a microarray hybridization experiment from eight different HCC tissues were analyzed and classified by the Cluster program. Among these differentially-expressed genes, the galectin-3, serine/threonine kinase SGK, translation factor eIF-4A, -4B, -3, fibroblast growth factor receptor, and ribosomal protein L35A were up-regulated; the mRNAs of Nip3, decorin, and the insulin-like growth factor binding protein-3 were down-regulated in HCC. The differential expression of these genes was further confirmed by an RT-PCR analysis. In addition, our data suggest that the gene expression profile of HCC varies according to the histological types.

  17. Long-Term Warming Shifts the Composition of Bacterial Communities in the Phyllosphere ofGalium albumin a Permanent Grassland Field-Experiment.

    Science.gov (United States)

    Aydogan, Ebru L; Moser, Gerald; Müller, Christoph; Kämpfer, Peter; Glaeser, Stefanie P

    2018-01-01

    Global warming is currently a much discussed topic with as yet largely unexplored consequences for agro-ecosystems. Little is known about the warming effect on the bacterial microbiota inhabiting the plant surface (phyllosphere), which can have a strong impact on plant growth and health, as well as on plant diseases and colonization by human pathogens. The aim of this study was to investigate the effect of moderate surface warming on the diversity and composition of the bacterial leaf microbiota of the herbaceous plant Galium album . Leaves were collected from four control and four surface warmed (+2°C) plots located at the field site of the Environmental Monitoring and Climate Impact Research Station Linden in Germany over a 6-year period. Warming had no effect on the concentration of total number of cells attached to the leaf surface as counted by Sybr Green I staining after detachment, but changes in the diversity and phylogenetic composition of the bacterial leaf microbiota analyzed by bacterial 16S rRNA gene Illumina amplicon sequencing were observed. The bacterial phyllosphere microbiota were dominated by Proteobacteria , Bacteroidetes , and Actinobacteria . Warming caused a significant higher relative abundance of members of the Gammaproteobacteria , Actinobacteria , and Firmicutes , and a lower relative abundance of members of the Alphaproteobacteria and Bacteroidetes . Plant beneficial bacteria like Sphingomonas spp. and Rhizobium spp. occurred in significantly lower relative abundance in leaf samples of warmed plots. In contrast, several members of the Enterobacteriaceae , especially Enterobacter and Erwinia , and other potential plant or human pathogenic genera such as Acinetobacter and insect-associated Buchnera and Wolbachia spp. occurred in higher relative abundances in the phyllosphere samples from warmed plots. This study showed for the first time the long-term impact of moderate (+2°C) surface warming on the phyllosphere microbiota on plants. A

  18. 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.

  19. Tissue Microarray Analysis Applied to Bone Diagenesis.

    Science.gov (United States)

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

    2017-01-04

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

  20. Tissue microarray profiling in human heart failure.

    Science.gov (United States)

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

    2016-09-01

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

  1. 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. 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.

  3. BACTERIAL PLASMIDS

    Directory of Open Access Journals (Sweden)

    Marina Dinic

    2007-12-01

    Full Text Available Plasmids, extrachromosomal DNA, were identified in bacteria pertaining to family of Enterobacteriacae for the very first time. After that, they were discovered in almost every single observed strain. The structure of plasmids is made of circular double chain DNA molecules which are replicated autonomously in a host cell. Their length may vary from few up to several hundred kilobase (kb. Among the bacteria, plasmids are mostly transferred horizontally by conjugation process. Plasmid replication process can be divided into three stages: initiation, elongation, and termination. The process involves DNA helicase I, DNA gyrase, DNA polymerase III, endonuclease, and ligase.Plasmids contain genes essential for plasmid function and their preservation in a host cell (the beginning and the control of replication. Some of them possess genes whichcontrol plasmid stability. There is a common opinion that plasmids are unnecessary fora growth of bacterial population and their vital functions; thus, in many cases they can be taken up or kicked out with no lethal effects to a plasmid host cell. However,there are numerous biological functions of bacteria related to plasmids. Plasmids identification and classification are based upon their genetic features which are presented permanently in all of them, and these are: abilities to preserve themselves in a host cell and to control a replication process. In this way, plasmids classification among incompatibility groups is performed. The method of replicon typing, which is based on genotype and not on phenotype characteristics, has the same results as in compatibility grouping.

  4. House dust mites as potential carriers for IgE sensitization to bacterial antigens.

    Science.gov (United States)

    Dzoro, S; Mittermann, I; Resch-Marat, Y; Vrtala, S; Nehr, M; Hirschl, A M; Wikberg, G; Lundeberg, L; Johansson, C; Scheynius, A; Valenta, R

    2018-01-01

    IgE reactivity to antigens from Gram-positive and Gram-negative bacteria is common in patients suffering from respiratory and skin manifestations of allergy, but the routes and mechanisms of sensitization are not fully understood. The analysis of the genome, transcriptome and microbiome of house dust mites (HDM) has shown that Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) species are abundant bacteria within the HDM microbiome. Therefore, our aim was to investigate whether HDM are carriers of bacterial antigens leading to IgE sensitization in patients suffering from atopic dermatitis. Plasma samples from patients with AD (n = 179) were analysed for IgE reactivity to a comprehensive panel of microarrayed HDM allergen molecules and to S. aureus and E. coli by IgE immunoblotting. Antibodies specific for S. aureus and E. coli antigens were tested for reactivity to nitrocellulose-blotted extract from purified HDM bodies, and the IgE-reactive antigens were detected by IgE immunoblot inhibition experiments. IgE antibodies directed to bacterial antigens in HDM were quantified by IgE ImmunoCAP™ inhibition experiments. IgE reactivity to bacterial antigens was significantly more frequent in patients with AD sensitized to HDM than in AD patients without HDM sensitization. S. aureus and E. coli antigens were detected in immune-blotted HDM extract, and the presence of IgE-reactive antigens in HDM was demonstrated by qualitative and quantitative IgE inhibition experiments. House dust mites (HDM) may serve as carriers of bacteria responsible for the induction of IgE sensitization to microbial antigens. © 2017 The Authors. Allergy Published by John Wiley & Sons Ltd.

  5. Identification of mycotoxigenic fungi using an oligonucleotide microarray

    CSIR Research Space (South Africa)

    Barros, E

    2013-01-01

    Full Text Available the development of an oligonucleotide microarray specific for eleven mycotoxigenic fungi isolated from different food commodities in South Africa. This array is suitable for the detection and identification of cultures of potential mycotoxigenic fungi in both...

  6. Novel Protein Microarray Technology to Examine Men with Prostate Cancer

    National Research Council Canada - National Science Library

    Lilja, Hans

    2005-01-01

    The authors developed a novel macro and nanoporous silicon surface for protein microarrays to facilitate high-throughput biomarker discovery, and high-density protein-chip array analyses of complex biological samples...

  7. Graph-based iterative Group Analysis enhances microarray interpretation

    Directory of Open Access Journals (Sweden)

    Amtmann Anna

    2004-07-01

    Full Text Available Abstract Background One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically important associations between the differentially expressed genes. A large part of the relevant functional evidence can be represented in the form of graphs, e.g. metabolic and signaling pathways, protein interaction maps, shared GeneOntology annotations, or literature co-citation relations. Such graphs are easily constructed from available genome annotation data. The problem of biological interpretation can then be described as identifying the subgraphs showing the most significant patterns of gene expression. We applied a graph-based extension of our iterative Group Analysis (iGA approach to obtain a statistically rigorous identification of the subgraphs of interest in any evidence graph. Results We validated the Graph-based iterative Group Analysis (GiGA by applying it to the classic yeast diauxic shift experiment of DeRisi et al., using GeneOntology and metabolic network information. GiGA reliably identified and summarized all the biological processes discussed in the original publication. Visualization of the detected subgraphs allowed the convenient exploration of the results. The method also identified several processes that were not presented in the original paper but are of obvious relevance to the yeast starvation response. Conclusions GiGA provides a fast and flexible delimitation of the most interesting areas in a microarray experiment, and leads to a considerable speed-up and improvement of the interpretation process.

  8. Expression profiling using a hexamer-based universal microarray.

    Science.gov (United States)

    Roth, Matthew E; Feng, Li; McConnell, Kevin J; Schaffer, Paul J; Guerra, Cesar E; Affourtit, Jason P; Piper, Kevin R; Guccione, Lorri; Hariharan, Jayashree; Ford, Maura J; Powell, Stephen W; Krishnaswamy, Harish; Lane, Jennifer; Guccione, Lisa; Intrieri, Gino; Merkel, Jane S; Perbost, Clotilde; Valerio, Anthony; Zolla, Brenda; Graham, Carol D; Hnath, Jonathan; Michaelson, Chris; Wang, Rixin; Ying, Baoge; Halling, Conrad; Parman, Craig E; Raha, Debasish; Orr, Brent; Jedrzkiewicz, Barbara; Liao, Ji; Tevelev, Anton; Mattessich, Martin J; Kranz, David M; Lacey, Michelle; Kaufman, Joseph C; Kim, Junhyong; Latimer, Darin R; Lizardi, Paul M

    2004-04-01

    We describe a transcriptional analysis platform consisting of a universal micro-array system (UMAS) combined with an enzymatic manipulation step that is capable of generating expression profiles from any organism without requiring a priori species-specific knowledge of transcript sequences. The transcriptome is converted to cDNA and processed with restriction endonucleases to generate low-complexity pools (approximately 80-120) of equal length DNA fragments. The resulting material is amplified and detected with the UMAS system, comprising all possible 4,096 (4(6)) DNA hexamers. Ligation to the arrays yields thousands of 14-mer sequence tags. The compendium of signals from all pools in the array-of-universal arrays comprises a full-transcriptome expression profile. The technology was validated by analysis of the galactose response of Saccharomyces cerevisiae, and the resulting profiles showed excellent agreement with the literature and real-time PCR assays. The technology was also used to demonstrate expression profiling from a hybrid organism in a proof-of-concept experiment where a T-cell receptor gene was expressed in yeast.

  9. Application of four dyes in gene expression analyses by microarrays

    Directory of Open Access Journals (Sweden)

    van Schooten Frederik J

    2005-07-01

    Full Text Available Abstract Background DNA microarrays are widely used in gene expression analyses. To increase throughput and minimize costs without reducing gene expression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for gene expression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressed genes with comparable effects on gene expression.

  10. 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.

  11. Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery.

    Science.gov (United States)

    Sadhu, Arnab; Bhattacharyya, Balaram

    2017-10-11

    Molecular biomarkers can be potential facilitators for detection of cancer at early stage which is otherwise difficult through conventional biomarkers. Gene expression data from microarray experiments on both normal and diseased cell samples provide enormous scope to explore genetic relations of disease using computational techniques. Varied patterns of expressions of thousands of genes at different cell conditions along with inherent experimental error make the task of isolating disease related genes challenging. In this paper, we present a data mining method, common subcluster mining (CSM), to discover highly perturbed genes under diseased condition from differential expression patterns. The method builds heap through superposing near centroid clusters from gene expression data of normal samples and extracts its core part. It, thus, isolates genes exhibiting the most stable state across normal samples and constitute a reference set for each centroid. It performs the same operation on datasets from corresponding diseased samples and isolates the genes showing drastic changes in their expression patterns. The method thus finds the disease-sensitive genesets when applied to datasets of lung cancer, prostrate cancer, pancreatic cancer, breast cancer, leukemia and pulmonary arterial hypertension. In majority of the cases, few new genes are found over and above some previously reported ones. Genes with distinct deviations in diseased samples are prospective candidates for molecular biomarkers of the respective disease.

  12. On the Statics for Micro-Array Data Analysis

    Science.gov (United States)

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

    2010-01-01

    Recently after human genome sequence has been determined almost perfectly, more and more researchers have been studying genes in detail. Therefore, we are sure that accumulated gene information for human will be getting more important in the near future to develop customized medicine and to make gene interactions clear. Among plenty of information, micro array might be one of the most important analysis method for genes because it is the technique that can get big amount of the gene expressions data from one time experiment and also can be used for DNA isolation. To get the novel knowledge from micro array data, we need to enrich statistical tools for its data analysis. So far, many mathematical theories and definition have been proposing. However, many of those proposals are tested with strict conditions or customized to data for specific species. In this paper, we reviewed existing typical statistical methods for micro array analysis and discussed the repeatability of the analysis, construction the guideline with more general procedure. First we analyzed the micro array data for TG rats, with statistical methods of family-wise error rate (FWER) control approach and False Discovery Rate (FDR) control approach. As existing report, no significantly different gene could be detected with FWER control approach. On the other hand, we could find several genes significantly with FDR control approach even q=0.5. To find out the reliability of FDR control approach with micro array conditions, we have analyzed 2 more pieces of data from Gene Expression Omnibus (GEO) public database on the web site with SAM in addition to FWER and FDR control approaches. We could find a certain number of significantly different genes with BH method and SAM in the case of q=0.05. However, we have to note that the number and kinds of detected genes are different when we compare our result with the one from the published paper. Even if the same approach is used to analyze the same micro array

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

    Science.gov (United States)

    Chrominski, Kornel; Tkacz, Magdalena

    2015-01-01

    When we were asked for help with high-level microarray data analysis (on Affymetrix HGU-133A microarray), we faced the problem of selecting an appropriate method. We wanted to select a method that would yield "the best result" (detected as many "really" differentially expressed genes (DEGs) as possible, without false positives and false negatives). However, life scientists could not help us--they use their "favorite" method without special argumentation. We also did not find any norm or recommendation. Therefore, we decided to examine it for our own purpose. We considered whether the results obtained using different methods of high-level microarray data analyses--Significant Analysis of Microarrays, Rank Products, Bland-Altman, Mann-Whitney test, T test and the Linear Models for Microarray Data--would be in agreement. Initially, we conducted a comparative analysis of the results on eight real data sets from microarray experiments (from the Array Express database). The results were surprising. On the same array set, the set of DEGs by different methods were significantly different. We also applied the methods to artificial data sets and determined some measures that allow the preparation of the overall scoring of tested methods for future recommendation. We found a very low level concordance of results from tested methods on real array sets. The number of common DEGs (detected by all six methods on fixed array sets, checked on eight array sets) ranged from 6 to 433 (22,283 total array readings). Results on artificial data sets were better than those on the real data. However, they were not fully satisfying. We scored tested methods on accuracy, recall, precision, f-measure and Matthews correlation coefficient. Based on the overall scoring, the best methods were SAM and LIMMA. We also found TT to be acceptable. The worst scoring was MW. Based on our study, we recommend: 1. Carefully taking into account the need for study when choosing a method, 2. Making high

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

    Directory of Open Access Journals (Sweden)

    Guifang Shao

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

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

    Science.gov (United States)

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

    2015-01-01

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

  16. Microarray analysis of gene expression during bacteriophage T4 infection.

    Science.gov (United States)

    Luke, Kimberly; Radek, Agnes; Liu, XiuPing; Campbell, John; Uzan, Marc; Haselkorn, Robert; Kogan, Yakov

    2002-08-01

    Genomic microarrays were used to examine the complex temporal program of gene expression exhibited by bacteriophage T4 during the course of development. The microarray data confirm the existence of distinct early, middle, and late transcriptional classes during the bacteriophage replicative cycle. This approach allows assignment of previously uncharacterized genes to specific temporal classes. The genomic expression data verify many promoter assignments and predict the existence of previously unidentified promoters.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  2. 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

  3. A study of inter-lab and inter-platform agreement of DNA microarray data

    Directory of Open Access Journals (Sweden)

    Wilson Carole

    2005-05-01

    Full Text Available Abstract As gene expression profile data from DNA microarrays accumulate rapidly, there is a natural need to compare data across labs and platforms. Comparisons of microarray data can be quite challenging due to data complexity and variability. Different labs may adopt different technology platforms. One may ask about the degree of agreement we can expect from different labs and different platforms. To address this question, we conducted a study of inter-lab and inter-platform agreement of microarray data across three platforms and three labs. The statistical measures of consistency and agreement used in this paper are the Pearson correlation, intraclass correlation, kappa coefficients, and a measure of intra-transcript correlation. The three platforms used in the present paper were Affymetrix GeneChip, custom cDNA arrays, and custom oligo arrays. Using the within-platform variability as a benchmark, we found that these technology platforms exhibited an acceptable level of agreement, but the agreement between two technologies within the same lab was greater than that between two labs using the same technology. The consistency of replicates in each experiment varies from lab to lab. When there is high consistency among replicates, different technologies show good agreement within and across labs using the same RNA samples. On the other hand, the lab effect, especially when confounded with the RNA sample effect, plays a bigger role than the platform effect on data agreement.

  4. Microarray Meta-Analysis of RNA-Binding Protein Functions in Alternative Polyadenylation

    Science.gov (United States)

    Hu, Wenchao; Liu, Yuting; Yan, Jun

    2014-01-01

    Alternative polyadenylation (APA) is a post-transcriptional mechanism to generate diverse mRNA transcripts with different 3′UTRs from the same gene. In this study, we systematically searched for the APA events with differential expression in public mouse microarray data. Hundreds of genes with over-represented differential APA events and the corresponding experiments were identified. We further revealed that global APA differential expression occurred prevalently in tissues such as brain comparing to peripheral tissues, and biological processes such as development, differentiation and immune responses. Interestingly, we also observed widespread differential APA events in RNA-binding protein (RBP) genes such as Rbm3, Eif4e2 and Elavl1. Given the fact that RBPs are considered as the main regulators of differential APA expression, we constructed a co-expression network between APAs and RBPs using the microarray data. Further incorporation of CLIP-seq data of selected RBPs showed that Nova2 represses and Mbnl1 promotes the polyadenylation of closest poly(A) sites respectively. Altogether, our study is the first microarray meta-analysis in a mammal on the regulation of APA by RBPs that integrated massive mRNA expression data under a wide-range of biological conditions. Finally, we present our results as a comprehensive resource in an online website for the research community. PMID:24622240

  5. A novel method using edge detection for signal extraction from cDNA microarray image analysis.

    Science.gov (United States)

    Kim, J H; Kim, H Y; Lee, Y S

    2001-06-30

    Gene expression analyses by probes of hybridization from mRNA to cDNA targets arrayed on membranes or activated glass surfaces have revolutionized the way of profiling mega level gene expression. The main remaining problems however are sensitivity of detection, reproducibility and data processing. During processing of microarray images, especially irregularities of spot position and shape could generate significant errors: small regions of signal spots can be mis-included into background area and vice versa. Here we report a novel method to eliminate such obstacles by sensing their edges. Application of edge detection technology on separating spots from the background decreases the probability of the errors and gives more accurate information about the states of spots such as the pixel number, degree of fragmentation, width and height of spot, and circumference of spot. Such information can be used for the quality control of cDNA microarray experiments and filtering of low quality spots. We analyzed the cDNA microarray image that contains 10,368 genes using edge detection and compared the result with that of conventional method which draws circle around the spot.

  6. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Directory of Open Access Journals (Sweden)

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Mertens Dominik

    2009-02-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Fish ‘n’ chips: the use of microarrays for aquatic toxicology

    Science.gov (United States)

    Denslow, Nancy D.; Garcia-Reyero, Natàlia; Barber, David S.

    2007-01-01

    Gene expression analysis is changing the way that we look at toxicity, allowing toxicologists to perform parallel analyses of entire transcriptomes. While this technology is not as advanced in aquatic toxicology as it is for mammalian models, it has shown promise for determining modes of action, identifying biomarkers and developing ‘‘signatures’’ of chemicals that can be used for field and mixture studies. A major hurdle for the use of microarrays in aquatic toxicology is the lack of sequence information for non-model species. Custom arrays based on gene libraries enriched for genes that are expressed in response to specific contaminants have been used with excellent success for some non-model species, suggesting that this approach will work well for ecotoxicology and spurring on the sequencing of cDNA libraries for species of interest. New sequencing technology and development of repositories for gene expression data will accelerate the use of microarrays in aquatic toxicology. Notwithstanding the preliminary successes that have been achieved even with partial cDNA libraries printed on arrays, ecological samples present elevated challenges for this technology due to the high degree of variation of the samples. Furthermore, recent studies that show nonlinear toxic responses for ecological species underscore the necessity of establishing time and dose dependence of effects on gene expression and comparing these results with traditional markers of toxicity. To realize the full potential of microarrays, researchers must do the experiments required to bridge the gap between the ‘omics’ technologies and traditional toxicology to demonstrate that microarrays have predictive value in ecotoxicology. PMID:17308663

  12. Identification of molecular mechanisms of radiation-induced vascular damage in normal tissues using microarray analyses

    International Nuclear Information System (INIS)

    Kruse, J.J.C.M.; Te Poele, J.A.M.; Russell, N.S.; Boersma, L.J.; Stewart, F.A.

    2003-01-01

    Radiation-induced telangiectasia, characterized by thin-walled dilated blood vessels, can be a serious late complication in patients that have been previously treated for cancer. It might cause cosmetic problems when occurring in the skin, and excessive bleeding requiring surgery when occurring in rectal mucosa. The mechanisms underlying the development of radiation-induced telangiectasia are unclear. The aim of the present study is to determine whether microarrays are useful for studying mechanisms of radiation-induced telangiectasia. The second aim is to test the hypotheses that telangiectasia is characterized by a final common pathway in different tissues. Microarray experiments were performed using amplified RNA from (sham)irradiated mouse tissues (kidney, rectum) at different intervals (1-30 weeks) after irradiation. After normalization procedures, the differentially expressed genes were identified. Control/repeat experiments were done to confirm that the observations were not artifacts of the array procedure. The mouse kidney experiments showed significant upregulation of 31 and 42 genes and downregulation of 9 and 4 genes at 10 and 20 weeks after irradiation, respectively. Irradiated mouse rectum has 278 upregulated and 537 downregulated genes at 10 weeks and 86 upregulated and 29 downregulated genes at 20 weeks. During the development of telangiectasia, 19 upregulated genes and 5 downregulated genes were common to both tissues. Upregulation of Jagged-1, known to play a role in angiogenesis, is particularly interesting in the context of radiation-induced telangiectasia. Microarrays are affective discovery tools to identify novel genes of interest, which may be involved in radiation-induced normal tissue injury. Using information from control arrays (particularly straight color, color reverse and self-self experiments) allowed for a more accurate and reproducible identification of differentially expressed genes than the selection of an arbitrary 2-fold change

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

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

    2017-04-05

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

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

    Science.gov (United States)

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

    2016-12-01

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

  17. DNA Microarrays in Comparative Genomics and Transcriptomics

    DEFF Research Database (Denmark)

    Willenbrock, Hanni

    2007-01-01

    analysis, analysis of chromosomal aberrations and DNA sequence dependent gene expression. First, this thesis contains a description of how the gene expression profiles from children with acute lymphoblastic leukemia may be used to improve the diagnosis of these patients and potentially improve......During the past few years, innovations in the DNA sequencing technology has led to an explosion in available DNA sequence information. This has revolutionized biological research and promoted the development of high throughput analysis methods that can take advantage of the vast amount of sequence...... of each method’s ability to analyze DNA copy number data. Moreover, our study shows that analysis methods developed for cancer research may also successfully be applied to DNA copy number profiles from bacterial genomes. However, here the purpose is to characterize variations in the gene content...

  18. Development of an ordered microarray of electrochemiluminescent nanosensors

    Science.gov (United States)

    Chovin, Arnaud; Garrigue, Patrick; Pecastaings, Gilles; Saadaoui, Hassan; Sojic, Neso

    2006-05-01

    A microarray of electrochemiluminescent (ECL) nanosensors for remote detection is reported. Such nanosensor arrays were created on the distal face of coherent optical fibre bundles by adapting near-field optical probe and nanoelectrode methodologies. The fabrication process allows the production of high-density microarrays of nanosensors where each optical aperture is surrounded by a gold nanoring electrode. The initial architecture of the optical fibre bundle is retained and thus the microarray keeps its imaging properties. The electrochemical response of the array displays a steady-state current. This feature indicates that the nanoelectrodes forming the array can be considered as diffusively independent. In other words, each ring-shaped electrode of the array probes electrochemically a different micro-environment. We also show that this microdevice can be used as an ECL nanosensor microarray. Indeed, ECL light is initiated by the gold nanoring electrode in the presence of a co-reactant biospecies, NADH. A fraction of the isotropically electrochemically generated light is collected by the same aperture, transmitted by the corresponding fibre core and eventually imaged by a CCD camera. The gold coating therefore acts as an electrode material and also to confine the ECL light in each etched core. Such nanostructured microdevice integrates ECL-light generation, collection and imaging in a microarray format.

  19. Oligonucleotide microarrays: immobilization of phosphorylated oligonucleotides on epoxylated surface.

    Science.gov (United States)

    Mahajan, S; Kumar, P; Gupta, K C

    2006-01-01

    A facile and efficient method for direct immobilization of phosphorylated oligonucleotides on an epoxy-activated glass surface is described. The new immobilization strategy has been analyzed for its performance in DNA microarray under both microwave and thermal conditions. It reflects high immobilization efficiency ( approximately 23%), and signal-to-noise ratio ( approximately 98) and resulted in high hybridization efficiency ( approximately 36%) in comparison to those obtained with standard methods, viz., NTMTA ( approximately 9.76%) and epoxide-amine ( approximately 9.82%). The probes immobilized through the new strategy were found to be heat-stable, since the performance of microarray decreased by only approximately 7% after subjecting it to 20 PCR-like heat cycles, suggesting that the chemistry could be used in integrated PCR/microarray devices. The immobilization of probes following the proposed chemistry resulted in spots of superior quality in terms of spot morphology, spot homogeneity, and signal reproducibility. The constructed microarrays have been successfully used for the discrimination of nucleotide mismatches. In conclusion, these features make the new immobilization strategy ideal for facile, efficient, and cost-effective manufacturing of DNA microarrays.

  20. Automated multidimensional phenotypic profiling using large public microarray repositories

    Science.gov (United States)

    Xu, Min; Li, Wenyuan; James, Gareth M.; Mehan, Michael R.; Zhou, Xianghong Jasmine

    2009-01-01

    Phenotypes are complex, and difficult to quantify in a high-throughput fashion. The lack of comprehensive phenotype data can prevent or distort genotype–phenotype mapping. Here, we describe “PhenoProfiler,” a computational method that enables in silico phenotype profiling. Drawing on the principle that similar gene expression patterns are likely to be associated with similar phenotype patterns, PhenoProfiler supplements the missing quantitative phenotype information for a given microarray dataset based on other well-characterized microarray datasets. We applied our method to 587 human microarray datasets covering >14,000 samples, and confirmed that the predicted phenotype profiles are highly consistent with true phenotype descriptions. PhenoProfiler offers several unique capabilities: (i) automated, multidimensional phenotype profiling, facilitating the analysis and treatment design of complex diseases; (ii) the extrapolation of phenotype profiles beyond provided classes; and (iii) the detection of confounding phenotype factors that could otherwise bias biological inferences. Finally, because no direct comparisons are made between gene expression values from different datasets, the method can use the entire body of cross-platform microarray data. This work has produced a compendium of phenotype profiles for the National Center for Biotechnology Information GEO datasets, which can facilitate an unbiased understanding of the transcriptome-phenome mapping. The continued accumulation of microarray data will further increase the power of PhenoProfiler, by increasing the variety and the quality of phenotypes to be profiled. PMID:19590007

  1. Advanced Data Mining of Leukemia Cells Micro-Arrays

    Directory of Open Access Journals (Sweden)

    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.

  2. Tissue Microarray: A rapidly evolving diagnostic and research tool

    Science.gov (United States)

    Jawhar, Nazar M.T.

    2009-01-01

    Tissue microarray is a recent innovation in the field of pathology. A microarray contains many small representative tissue samples from hundreds of different cases assembled on a single histologic slide, and therefore allows high throughput analysis of multiple specimens at the same time. Tissue microarrays are paraffin blocks produced by extracting cylindrical tissue cores from different paraffin donor blocks and re-embedding these into a single recipient (microarray) block at defined array coordinates. Using this technique, up to 1000 or more tissue samples can be arrayed into a single paraffin block. It can permit simultaneous analysis of molecular targets at the DNA, mRNA, and protein levels under identical, standardized conditions on a single glass slide, and also provide maximal preservation and use of limited and irreplaceable archival tissue samples. This versatile technique, in which data analysis is automated facilitates retrospective and prospective human tissue studies. It is a practical and effective tool for high-throughput molecular analysis of tissues that is helping to identify new diagnostic and prognostic markers and targets in human cancers, and has a range of potential applications in basic research, prognostic oncology and drug discovery. This article summarizes the technical aspects of tissue microarray construction and sectioning, advantages, application, and limitations. PMID:19318744

  3. Significance analysis of lexical bias in microarray data

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. A Fisheye Viewer for microarray-based gene expression data.

    Science.gov (United States)

    Wu, Min; Thao, Cheng; Mu, Xiangming; Munson, Ethan V

    2006-10-13

    Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology. The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  6. A fisheye viewer for microarray-based gene expression data

    Directory of Open Access Journals (Sweden)

    Munson Ethan V

    2006-10-01

    Full Text Available Abstract Background Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface – an electronic table (E-table that uses fisheye distortion technology. Results The Fisheye Viewer for microarray-based gene expression data has been successfully developed to view MIAME data stored in the MAGE-ML format. The viewer can be downloaded from the project web site http://polaris.imt.uwm.edu:7777/fisheye/. The fisheye viewer was implemented in Java so that it could run on multiple platforms. We implemented the E-table by adapting JTable, a default table implementation in the Java Swing user interface library. Fisheye views use variable magnification to balance magnification for easy viewing and compression for maximizing the amount of data on the screen. Conclusion This Fisheye Viewer is a lightweight but useful tool for biologists to quickly overview the raw microarray-based gene expression data in an E-table.

  7. 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 appl......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...... computer skills and can be executed from any Internet-connected computer. The probe selection procedure for a standard microarray design targeting all yeast transcripts can be completed in 1 h....

  8. Development of a 9600-clone procedure for oligonucleotide fingerprinting of rRNA genes: utilization to identify soil bacterial rRNA genes that correlate in abundance with the development of avocado root rot.

    Science.gov (United States)

    Bent, Elizabeth; Yin, Bei; Figueroa, Andres; Ye, Jingxiao; Fu, Qi; Liu, Zheng; McDonald, Virginia; Jeske, Daniel; Jiang, Tao; Borneman, James

    2006-10-01

    Oligonucleotide fingerprinting of rRNA genes (OFRG) is an array-based method that generates microbial community profiles through analysis of rRNA gene clone libraries. The original OFRG method allowed 1536 clones to be analyzed per experiment. This report describes a procedure for analyzing 9600 clones per experiment, including a new probe set for bacterial analysis, and improved data processing and statistical analysis tools. The software tools are available at the OFRG website (). Use of the 9600-clone procedure was demonstrated by examining the bacterial rRNA gene compositions of soils subjected to various temperature treatments. These treatments produced a series of soils with a range of abilities to suppress avocado root rot, enabling the identification of bacterial rRNA genes that correlate in abundance with root rot suppressiveness. OFRG analysis of these soils produced 8876 bacterial rRNA gene fingerprints grouped into 5123 clusters, or operational taxonomic units (OTUs). Eleven OTUs exhibited a positive correlation between the number of clones and the percentage of healthy roots. An in silico analysis was performed to examine the relationship between the number of rRNA genes analyzed and the number of correlates (rRNA gene-avocado root rot symptoms) identified. As the number of clones decreased, fewer correlates were identified. To further increase the throughput of the OFRG method, use of a glass slide-fluorescent probe microarray format was also explored.

  9. A Semi-Quantitative Study of the Impact of Bacterial Pollutant Uptake Capability on Bioremediation in a Saturated Sand-Packed Two-Dimensional Microcosm: Experiments and Simulation

    Science.gov (United States)

    Zheng, S.; Ford, R.; Van den Berg, B.

    2016-12-01

    The transport of microorganisms through the saturated porous matrix of soil is critical to the success of bioremediation in polluted groundwater systems. Chemotaxis can direct the movement of microorganisms toward higher concentration of pollutants, which they chemically transform and use as carbon and energy sources, resulting in enhanced bioremediation efficiency. In addition to accessibility and degradation kinetics, bacterial uptake of the pollutants is a critical step in bioremediation. In order to study the impact of bacterial pollutant uptake capability on bioremediation, a two-dimensional microcosm packed with saturated sand was set up to mimic the natural groundwater system where mass transfer limitation poses a barrier (see the figure below). Toluene source was continuously injected into the microcosm from an injection port. Pseudomonas putida F1, either wild-type (WT) or genetic mutants (TodX knockout, TodX and CymD knockout) that exhibited impaired toluene uptake capability, were co-injected with a conservative tracer into the microcosm either above or below the toluene. After each run, samples were collected from a dozen effluent ports to determine the concentration profiles of the bacteria and tracers. Toluene serves as the only carbon source throughout the microcosm. So the percent recovery, which is the ratio of cells collected at the outlet over that at the inlet, can be used as the indicator for bioremediation efficiency. Comparisons were made between the WT and mutant strains, where PpF1 WT showed greater proliferation than the mutants. Comparisons for low and high toluene source concentrations showed that the PpF1 mutant strains exhibited a greater degree of growth inhibition than WT at higher toluene concentration. A mathematical model was applied to evaluate the impact of various parameters on toluene uptake illustrating that with reasonable parameter estimates, the bioremediation efficiency was more sensitive to proliferation than transport

  10. Bacterial evolution: Resistance is a numbers game

    OpenAIRE

    Hall, J.P.J.; Harrison, E.

    2016-01-01

    Plasmids are well known for spreading antibiotic-resistance genes between bacterial strains. Recent experiments show that they can also act as catalysts for evolutionary innovation, promoting rapid evolution of novel antibiotic resistance.

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

    Directory of Open Access Journals (Sweden)

    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

  12. A Genetic Algorithm Approach to DNA Microarrays Analysis of Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    MELITA, N. T.

    2008-06-01

    Full Text Available We address the problem of collecting and analyzing vast amount of information in medicine and biology, in the light of the revolutionary technological evolution during the last decades. Currently, the methods of achieving information challenge our capacity to sort and process that data. However, we use the methods of machine learning to sort and analyze this information. In this comprehensive review we describe an experiment of analyzing DNA microarrays using a Genetic Algorithm for feature selection. We study how we can establish a causal relationship between a pattern of genic expression and the evolution of pancreatic cancer using a Genetic Algorithm.

  13. EST and microarray analysis of horn development in Onthophagus beetles

    Directory of Open Access Journals (Sweden)

    Tang Zuojian

    2009-10-01

    Full Text Available Abstract Background The origin of novel traits and their subsequent diversification represent central themes in evo-devo and evolutionary ecology. Here we explore the genetic and genomic basis of a class of traits that is both novel and highly diverse, in a group of organisms that is ecologically complex and experimentally tractable: horned beetles. Results We developed two high quality, normalized cDNA libraries for larval and pupal Onthophagus taurus and sequenced 3,488 ESTs that assembled into 451 contigs and 2,330 singletons. We present the annotation and a comparative analysis of the conservation of the sequences. Microarrays developed from the combined libraries were then used to contrast the transcriptome of developing primordia of head horns, prothoracic horns, and legs. Our experiments identify a first comprehensive list of candidate genes for the evolution and diversification of beetle horns. We find that developing horns and legs show many similarities as well as important differences in their transcription profiles, suggesting that the origin of horns was mediated partly, but not entirely, by the recruitment of genes involved in the formation of more traditional appendages such as legs. Furthermore, we find that horns developing from the head and prothorax differ in their transcription profiles to a degree that suggests that head and prothoracic horns are not serial homologs, but instead may have evolved independently from each other. Conclusion We have laid the foundation for a systematic analysis of the genetic basis of horned beetle development and diversification with the potential to contribute significantly to several major frontiers in evolutionary developmental biology.

  14. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia adhesion

    Directory of Open Access Journals (Sweden)

    Faisal Mohamed

    2010-05-01

    Full Text Available Abstract Background The zebra mussel (Dreissena polymorpha has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. Results In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A, current velocity (Factor B, dissolved oxygen (Factor C, and byssogenesis status (Factor D. Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR. The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. Conclusions The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  15. Factorial microarray analysis of zebra mussel (Dreissena polymorpha: Dreissenidae, Bivalvia) adhesion.

    Science.gov (United States)

    Xu, Wei; Faisal, Mohamed

    2010-05-28

    The zebra mussel (Dreissena polymorpha) has been well known for its expertise in attaching to substances under the water. Studies in past decades on this underwater adhesion focused on the adhesive protein isolated from the byssogenesis apparatus of the zebra mussel. However, the mechanism of the initiation, maintenance, and determination of the attachment process remains largely unknown. In this study, we used a zebra mussel cDNA microarray previously developed in our lab and a factorial analysis to identify the genes that were involved in response to the changes of four factors: temperature (Factor A), current velocity (Factor B), dissolved oxygen (Factor C), and byssogenesis status (Factor D). Twenty probes in the microarray were found to be modified by one of the factors. The transcription products of four selected genes, DPFP-BG20_A01, EGP-BG97/192_B06, EGP-BG13_G05, and NH-BG17_C09 were unique to the zebra mussel foot based on the results of quantitative reverse transcription PCR (qRT-PCR). The expression profiles of these four genes under the attachment and non-attachment were also confirmed by qRT-PCR and the result is accordant to that from microarray assay. The in situ hybridization with the RNA probes of two identified genes DPFP-BG20_A01 and EGP-BG97/192_B06 indicated that both of them were expressed by a type of exocrine gland cell located in the middle part of the zebra mussel foot. The results of this study suggested that the changes of D. polymorpha byssogenesis status and the environmental factors can dramatically affect the expression profiles of the genes unique to the foot. It turns out that the factorial design and analysis of the microarray experiment is a reliable method to identify the influence of multiple factors on the expression profiles of the probesets in the microarray; therein it provides a powerful tool to reveal the mechanism of zebra mussel underwater attachment.

  16. DNA microarrays : a molecular cloning manual

    National Research Council Canada - National Science Library

    Sambrook, Joseph; Bowtell, David

    2002-01-01

    .... This manual, designed to extend and to complement the information in the best-selling Molecular Cloning, is a synthesis of the expertise and experience of more than 30 contributors all innovators in a fast moving field...

  17. MICROARRAY IMAGE GRIDDING USING GRID LINE REFINEMENT TECHNIQUE

    Directory of Open Access Journals (Sweden)

    V.G. Biju

    2015-05-01

    Full Text Available An important stage in microarray image analysis is gridding. Microarray image gridding is done to locate sub arrays in a microarray image and find co-ordinates of spots within each sub array. For accurate identification of spots, most of the proposed gridding methods require human intervention. In this paper a fully automatic gridding method which enhances spot intensity in the preprocessing step as per a histogram based threshold method is used. The gridding step finds co-ordinates of spots from horizontal and vertical profile of the image. To correct errors due to the grid line placement, a grid line refinement technique is proposed. The algorithm is applied on different image databases and results are compared based on spot detection accuracy and time. An average spot detection accuracy of 95.06% depicts the proposed method’s flexibility and accuracy in finding the spot co-ordinates for different database images.

  18. 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.

  19. Screening of cDNA libraries on glass slide microarrays.

    Science.gov (United States)

    Berger, Dave K; Crampton, Bridget G; Hein, Ingo; Vos, Wiesner

    2007-01-01

    A quantitative screening method was developed to evaluate the quality of cDNA libraries constructed by suppression subtraction hybridization (SSH) or other enrichment techniques. The SSH technique was adapted to facilitate screening of the resultant library on a small number of glass slide microarrays. A simple data analysis pipeline named SSHscreen using "linear models for microarray data" (limma) functions in the R computing environment was developed to identify clones in the cDNA libraries that are significantly differentially expressed, and to determine if they were rare or abundant in the original treated sample. This approach facilitates the choice of clones from the cDNA library for further analysis, such as DNA sequencing, Northern blotting, RT-PCR, or detailed expression profiling using a custom cDNA microarray. Furthermore, this strategy is particularly useful for studies of nonmodel organisms for which there is little genome sequence information.

  20. The human gut chip "HuGChip", an explorative phylogenetic microarray for determining gut microbiome diversity at family level.

    Science.gov (United States)

    Tottey, William; Denonfoux, Jeremie; Jaziri, Faouzi; Parisot, Nicolas; Missaoui, Mohiedine; Hill, David; Borrel, Guillaume; Peyretaillade, Eric; Alric, Monique; Harris, Hugh M B; Jeffery, Ian B; Claesson, Marcus J; O'Toole, Paul W; Peyret, Pierre; Brugère, Jean-François

    2013-01-01

    Evaluating the composition of the human gut microbiota greatly facilitates studies on its role in human pathophysiology, and is heavily reliant on culture-independent molecular methods. A microarray designated the Human Gut Chip (HuGChip) was developed to analyze and compare human gut microbiota samples. The PhylArray software was used to design specific and sensitive probes. The DNA chip was composed of 4,441 probes (2,442 specific and 1,919 explorative probes) targeting 66 bacterial families. A mock community composed of 16S rRNA gene sequences from intestinal species was used to define the threshold criteria to be used to analyze complex samples. This was then experimentally verified with three human faecal samples and results were compared (i) with pyrosequencing of the V4 hypervariable region of the 16S rRNA gene, (ii) metagenomic data, and (iii) qPCR analysis of three phyla. When compared at both the phylum and the family level, high Pearson's correlation coefficients were obtained between data from all methods. The HuGChip development and validation showed that it is not only able to assess the known human gut microbiota but could also detect unknown species with the explorative probes to reveal the large number of bacterial sequences not yet described in the human gut microbiota, overcoming the main inconvenience encountered when developing microarrays.

  1. Hand-held portable microarray reader for biodetection

    Science.gov (United States)

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

    2013-04-23

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

  2. Advanced Data Mining of Leukemia Cells Micro-Arrays

    OpenAIRE

    Richard S. Segall; Ryan M. Pierce

    2009-01-01

    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 pro...

  3. 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/.

  4. GeneX Va: VBC open source microarray database and analysis software.

    Science.gov (United States)

    Lee, Jae K; Laudeman, Tom; Kanter, Jodi; James, Teela; Siadaty, Mir S; Knaus, William A; Prorok, Alyson; Bao, Yongde; Freeman, Brad; Puiu, Daniela; Wen, Li Min; Buck, Gregory A; Schlauch, Karen; Weller, Jennifer; Fox, Jay W

    2004-04-01

    Developed by the Virginia Bioinformatics Consortium (VBC), GeneX Va is an open source, freeware database and bioinformatics analysis software for archiving and analyzing Affymetrix GeneChip data. It provides an integrated framework for management, documentation, and analysis of microarray experiments and data to support a range of users, from individual research laboratories to institutional microarray facilities. GeneX Va also provides web-based access to a PostgreSQL relational database system with a comprehensive security system. Data can be extracted from the database and delivered to interactive or scriptable statistical analysis protocols. The security system allows each investigator to manage their own array data and analysis output files and also provides custom access privileges for other users, groups, and internal/external collaborators. The analysis interface uses "Analysis Trees," an innovative user interface that allows researchers to interactively create a tree-structured flow chart of analysis routines. The latest GeneX Va software is available from and can be freely downloaded at the Sourceforge web site http://va-genex.sourceforge.net. To allow researchers to access the database and analysis capabilities of the GeneX Va system, microarray data from many VBC GeneChip experiments have been deposited into a public section of the GeneX Va system at the University of Virginia. The VBC GeneX Va sites, which include documentation, are at http://genes.med.virginia.edu/ of the University of Virginia and at http://genex.csbc.vcu.edu/ of the Virginia Commonwealth University.

  5. 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.

  6. Bacterial growth and DOC consumption in a tropical coastal lagoon

    OpenAIRE

    Farjalla,V. F.; Enrich-Prast,A.; Esteves,F. A.; Cimbleris,A. C. P.

    2006-01-01

    The aims of this research were to determine the main limiting nutrient to bacterial growth in Imboassica lagoon, southeastern Brazil, to estimate the percentage of dissolved organic carbon (DOC) available for bacterial growth, and to determine the bacterial growth efficiency (BGE) of natural assemblages. Bacterial growth and DOC consumption were determined in batch culture experiments, in which water samples were supplemented with nitrogen and phosphorus together or separately, or incubated w...

  7. 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.

  8. Analysis of a simulated microarray dataset : Comparison of methods for data normalisation and detection of differential expression

    OpenAIRE

    Watson, Michael; Pérez-Alegre, Monica; Baron, Michael Denis; Delmas, Celine; Dovc, Peter; Duval, Mylene; Foulley, Jean Louis; Garrido-Pavon, Juan José; Hulsegge, Ina; Jaffrézic, Florence; Jiménez-Marin, Angeles; Lavric, Miha; Lê Cao, Kim-Anh; Marot, Guillemette; Mouzaki, Daphné

    2007-01-01

    Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the ...

  9. 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.

  10. Identification of cytokinin-responsive genes using microarray meta-analysis and RNA-Seq in Arabidopsis.

    Science.gov (United States)

    Bhargava, Apurva; Clabaugh, Ivory; To, Jenn P; Maxwell, Bridey B; Chiang, Yi-Hsuan; Schaller, G Eric; Loraine, Ann; Kieber, Joseph J

    2013-05-01

    Cytokinins are N(6)-substituted adenine derivatives that play diverse roles in plant growth and development. We sought to define a robust set of genes regulated by cytokinin as well as to query the response of genes not represented on microarrays. To this end, we performed a meta-analysis of microarray data from a variety of cytokinin-treated samples and used RNA-seq to examine cytokinin-regulated gene expression in Arabidopsis (Arabidopsis thaliana). Microarray meta-analysis using 13 microarray experiments combined with empirically defined filtering criteria identified a set of 226 genes differentially regulated by cytokinin, a subset of which has previously been validated by other methods. RNA-seq validated about 73% of the up-regulated genes identified by this meta-analysis. In silico promoter analysis indicated an overrepresentation of type-B Arabidopsis response regulator binding elements, consistent with the role of type-B Arabidopsis response regulators as primary mediators of cytokinin-responsive gene expression. RNA-seq analysis identified 73 cytokinin-regulated genes that were not represented on the ATH1 microarray. Representative genes were verified using quantitative reverse transcription-polymerase chain reaction and NanoString analysis. Analysis of the genes identified reveals a substantial effect of cytokinin on genes encoding proteins involved in secondary metabolism, particularly those acting in flavonoid and phenylpropanoid biosynthesis, as well as in the regulation of redox state of the cell, particularly a set of glutaredoxin genes. Novel splicing events were found in members of some gene families that are known to play a role in cytokinin signaling or metabolism. The genes identified in this analysis represent a robust set of cytokinin-responsive genes that are useful in the analysis of cytokinin function in plants.

  11. Spotted cotton oligonucleotide microarrays for gene expression analysis

    Directory of Open Access Journals (Sweden)

    Nettleton Dan

    2007-03-01

    Full Text Available Abstract Background Microarrays offer a powerful tool for diverse applications plant biology and crop improvement. Recently, two comprehensive assemblies of cotton ESTs were constructed based on three Gossypium species. Using these assemblies as templates, we describe the design and creation and of a publicly available oligonucleotide array for cotton, useful for all four of the cultivated species. Results Synthetic oligonucleotide probes were generated from exemplar sequences of a global assembly of 211,397 cotton ESTs derived from >50 different cDNA libraries representing many different tissue types and tissue treatments. A total of 22,787 oligonucleotide probes are included on the arrays, optimized to target the diversity of the transcriptome and previously studied cotton genes, transcription factors, and genes with homology to Arabidopsis. A small portion of the oligonucleotides target unidentified protein coding sequences, thereby providing an element of gene discovery. Because many oligonucleotides were based on ESTs from fiber-specific cDNA libraries, the microarray has direct application for analysis of the fiber transcriptome. To illustrate the utility of the microarray, we hybridized labeled bud and leaf cDNAs from G. hirsutum and demonstrate technical consistency of results. Conclusion The cotton oligonucleotide microarray provides a reproducible platform for transcription profiling in cotton, and is made publicly available through http://cottonevolution.info.

  12. Microarray-based large scale detection of single feature ...

    Indian Academy of Sciences (India)

    2015-12-08

    Dec 8, 2015 ... Hybridization and data quality. The five genotypes such as JKC703, JKC725, JKC737,. JKC777 and JKC783 were used in the present study. To assess our microarray intensity data, the raw intensity data of only PM probes/features of cotton cultivars were log2 transformed and studied by density plots, and ...

  13. Gene ordering in partitive clustering using microarray expressions

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution. Ray S S, Bandyopadhyay S and Pal S K 2007 Gene ordering in partitive clustering using microarray expressions; J. Biosci.

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

    Science.gov (United States)

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

  15. Dimension reduction methods for microarray data: a review

    Directory of Open Access Journals (Sweden)

    Rabia Aziz

    2017-03-01

    Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.

  16. 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...

  17. DNA microarray analysis of fim mutations in Escherichia coli

    DEFF Research Database (Denmark)

    Schembri, Mark; Ussery, David; Workman, Christopher

    2002-01-01

    we have used DNA microarray analysis to examine the molecular events involved in response to fimbrial gene expression in E. coli K-12. Observed differential expression levels of the fim genes were in good agreement with our current knowledge of the stoichiometry of type I fimbriae. Changes in fim...

  18. Comparison of Comparative Genomic Hybridization Technologies across Microarray Platforms

    Science.gov (United States)

    In the 2007 Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) project, we analyzed HL-60 DNA with five platforms: Agilent, Affymetrix 500K, Affymetrix U133 Plus 2.0, Illumina, and RPCI 19K BAC arrays. Copy number variation (CNV) was analyzed ...

  19. The microarray detecting six fruit-tree viruses

    Czech Academy of Sciences Publication Activity Database

    Lenz, Ondřej; Petrzik, Karel; Špak, Josef

    2009-01-01

    Roč. 148, July (2009), s. 27 ISSN 1866-590X. [International Conference on Virus and other Graft Transmissible Diseases of Fruit Crops /21./. 05.07.2009-10.07.2009, Neustadt] R&D Projects: GA MŠk OC 853.001 Institutional research plan: CEZ:AV0Z50510513 Keywords : microarray * detection * virus Subject RIV: EE - Microbiology, Virology

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

    Science.gov (United States)

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

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

    Science.gov (United States)

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

  2. Towards a programmable magnetic bead microarray in a microfluidic channel

    DEFF Research Database (Denmark)

    Smistrup, Kristian; Bruus, Henrik; Hansen, Mikkel Fougt

    2007-01-01

    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....

  3. Microarrays: Molecular allergology and nanotechnology for personalised medicine (II).

    Science.gov (United States)

    Lucas, J M

    2010-01-01

    Progress in nanotechnology and DNA recombination techniques have produced tools for the diagnosis and investigation of allergy at molecular level. The most advanced examples of such progress are the microarray techniques, which have been expanded not only in research in the field of proteomics but also in application to the clinical setting. Microarrays of allergic components offer results relating to hundreds of allergenic components in a single test, and using a small amount of serum which can be obtained from capillary blood. The availability of new molecules will allow the development of panels including new allergenic components and sources, which will require evaluation for clinical use. Their application opens the door to component-based diagnosis, to the holistic perception of sensitisation as represented by molecular allergy, and to patient-centred medical practice by allowing great diagnostic accuracy and the definition of individualised immunotherapy for each patient. The present article reviews the application of allergenic component microarrays to allergology for diagnosis, management in the form of specific immunotherapy, and epidemiological studies. A review is also made of the use of protein and gene microarray techniques in basic research and in allergological diseases. Lastly, an evaluation is made of the challenges we face in introducing such techniques to clinical practice, and of the future perspectives of this new technology. Copyright 2010 SEICAP. Published by Elsevier Espana. All rights reserved.

  4. Review Article: Current Knowledge on Microarray Technology - An ...

    African Journals Online (AJOL)

    The completion of whole genome sequencing projects has led to a rapid increase in the availability of genetic information. In the field of transcriptomics, the emergence of microarray-based technologies and the design of DNA biochips allow high-throughput studies of RNA expression in cell and tissue at a given moment.

  5. Microarray analysis of adipose tissue gene expression profiles ...

    Indian Academy of Sciences (India)

    Excessive accumulation of lipids in the adipose tissue is one of the main problems faced by the broiler industry nowadays. In order to visualize the mechanisms involved in the gene expression and regulation of lipid metabolism in adipose tissue, cDNA microarray containing 9 024 cDNA was used to construct gene ...

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

    Science.gov (United States)

    Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

    2017-02-01

    Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. DNA microarray analysis of genes differentially expressed in ...

    Indian Academy of Sciences (India)

    These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes ...

  8. 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.

  9. 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...

  10. Exploiting fluorescence for multiplex immunoassays on protein microarrays

    Science.gov (United States)

    Herbáth, Melinda; Papp, Krisztián; Balogh, Andrea; Matkó, János; Prechl, József

    2014-09-01

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

  11. Microarray analysis of the gene expression profile in triethylene ...

    African Journals Online (AJOL)

    Microarray analysis of the gene expression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in gene expression levels and complex interactions with different signaling pathways.

  12. Evaluation of prognostic indicators using validated canine insulinoma tissue microarrays

    NARCIS (Netherlands)

    Buishand, Floryne O; Visser, Judith; Kik, Marja; Gröne, Andrea; Keesler, Rebekah I; Briaire-de Bruijn, Inge H; Kirpensteijn, Jolle

    Tissue microarray (TMA) technology allows analysis of multiple tumour samples simultaneously on a single slide. The aim of the present study was to develop and assess a TMA containing 32 primary canine insulinomas and 13 insulinoma metastases. The results of histopathological and immunohistochemical

  13. SNP typing on the NanoChip electronic microarray

    DEFF Research Database (Denmark)

    Børsting, Claus; Sanchez Sanchez, Juan Jose; Morling, Niels

    2005-01-01

    We describe a single nucleotide polymorphism (SNP) typing protocol developed for the NanoChip electronic microarray. The NanoChip array consists of 100 electrodes covered by a thin hydrogel layer containing streptavidin. An electric currency can be applied to one, several, or all electrodes...

  14. 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...

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

    Directory of Open Access Journals (Sweden)

    Vanderburg Charles R

    2009-01-01

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

  16. Extending Immunological Profiling in the Gilthead Sea Bream, Sparus aurata, by Enriched cDNA Library Analysis, Microarray Design and Initial Studies upon the Inflammatory Response to PAMPs

    Directory of Open Access Journals (Sweden)

    Sebastian Boltaña

    2017-02-01

    Full Text Available This study describes the development and validation of an enriched oligonucleotide-microarray platform for Sparus aurata (SAQ to provide a platform for transcriptomic studies in this species. A transcriptome database was constructed by assembly of gilthead sea bream sequences derived from public repositories of mRNA together with reads from a large collection of expressed sequence tags (EST from two extensive targeted cDNA libraries characterizing mRNA transcripts regulated by both bacterial and viral challenge. The developed microarray was further validated by analysing monocyte/macrophage activation profiles after challenge with two Gram-negative bacterial pathogen-associated molecular patterns (PAMPs; lipopolysaccharide (LPS and peptidoglycan (PGN. Of the approximately 10,000 EST sequenced, we obtained a total of 6837 EST longer than 100 nt, with 3778 and 3059 EST obtained from the bacterial-primed and from the viral-primed cDNA libraries, respectively. Functional classification of contigs from the bacterial- and viral-primed cDNA libraries by Gene Ontology (GO showed that the top five represented categories were equally represented in the two libraries: metabolism (approximately 24% of the total number of contigs, carrier proteins/membrane transport (approximately 15%, effectors/modulators and cell communication (approximately 11%, nucleoside, nucleotide and nucleic acid metabolism (approximately 7.5% and intracellular transducers/signal transduction (approximately 5%. Transcriptome analyses using this enriched oligonucleotide platform identified differential shifts in the response to PGN and LPS in macrophage-like cells, highlighting responsive gene-cassettes tightly related to PAMP host recognition. As observed in other fish species, PGN is a powerful activator of the inflammatory response in S. aurata macrophage-like cells. We have developed and validated an oligonucleotide microarray (SAQ that provides a platform enriched for the study

  17. CellMinerHCC: a microarray-based expression database for hepatocellular carcinoma cell lines.

    Science.gov (United States)

    Staib, Frank; Krupp, Markus; Maass, Thorsten; Itzel, Timo; Weinmann, Arndt; Lee, Ju-Seog; Schmidt, Bertil; Müller, Martina; Thorgeirsson, Snorri S; Galle, Peter R; Teufel, Andreas

    2014-04-01

    Therapeutic options for hepatocellular carcinoma (HCC) still remain limited. Development of gene targeted therapies is a promising option. A better understanding of the underlying molecular biology is gained in in vitro experiments. However, even with targeted manipulation of gene expression varying treatment responses were observed in diverse HCC cell lines. Therefore, information on gene expression profiles of various HCC cell lines may be crucial to experimental designs. To generate a publicly available database containing microarray expression profiles of diverse HCC cell lines. Microarray data were analyzed using an individually scripted R program package. Data were stored in a PostgreSQL database with a PHP written web interface. Evaluation and comparison of individual cell line expression profiles are supported via public web interface. This database allows evaluation of gene expression profiles of 18 HCC cell lines and comparison of differential gene expression between multiple cell lines. Analysis of commonly regulated genes for signaling pathway enrichment and interactions demonstrates a liver tumor phenotype with enrichment of major cancer related KEGG signatures like 'cancer' and 'inflammatory response'. Further molecular associations of strong scientific interest, e.g. 'lipid metabolism', were also identified. We have generated CellMinerHCC (http://www.medicalgenomics.org/cellminerhcc), a publicly available database containing gene expression data of 18 HCC cell lines. This database will aid in the design of in vitro experiments in HCC research, because the genetic specificities of various HCC cell lines will be considered. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  18. Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

    Directory of Open Access Journals (Sweden)

    E. V. Thomas

    2009-01-01

    Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

  19. Image Analysis and Data Normalization Procedures are Crucial for Microarray Analyses

    Directory of Open Access Journals (Sweden)

    Ali Kpatcha Kadanga

    2008-01-01

    Full Text Available This study was conducted with the aim of optimizing the experimental design of array experiments. We compared two image analysis and normalization procedures prior to data analysis using two experimental designs. For this, RNA samples from Charolais steers Longissimus thoracis muscle and subcutaneous adipose tissues were labeled and hybridized to a bovine 8,400 oligochip either in triplicate or in a dye-swap design. Image analysis and normalization were processed by either GenePix/MadScan or ImaGene/GeneSight. Statistical data analysis was then run using either the SAM method or a Student’s t-test using a multiple test correction run on R 2.1 software. Our results show that image analysis and normalization procedure had an impact whereas the statistical methods much less influenced the outcome of differentially expressed genes. Image analysis and data normalization are thus an important aspect of microarray experiments, having a potentially significant impact on downstream analyses such as the identification of differentially expressed genes. This study provides indications on the choice of raw data preprocessing in microarray technology.

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

    Science.gov (United States)

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

    2017-04-07

    Microarray technology, recently implemented in international prenatal diagnosis systems, has become one of the main techniques in this field in terms of detection rate and objectivity of the results. This guideline attempts to provide background information on this technology, including technical and diagnostic aspects to be considered. Specifically, this guideline defines: the different prenatal sample types to be used, as well as their characteristics (chorionic villi samples, amniotic fluid, fetal cord blood or miscarriage tissue material); variant reporting policies (including variants of uncertain significance) to be considered in informed consents and prenatal microarray reports; microarray limitations inherent to the technique and which must be taken into account when recommending microarray testing for diagnosis; a detailed clinical algorithm recommending the use of microarray testing and its introduction into routine clinical practice within the context of other genetic tests, including pregnancies in families with a genetic history or specific syndrome suspicion, first trimester increased nuchal translucency or second trimester heart malformation and ultrasound findings not related to a known or specific syndrome. This guideline has been coordinated by the Spanish Association for Prenatal Diagnosis (AEDP, «Asociación Española de Diagnóstico Prenatal»), the Spanish Human Genetics Association (AEGH, «Asociación Española de Genética Humana») and the Spanish Society of Clinical Genetics and Dysmorphology (SEGCyD, «Sociedad Española de Genética Clínica y Dismorfología»). Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

  1. Diagnostic utility of microarray testing in pregnancy loss.

    Science.gov (United States)

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

    2015-10-01

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

  2. 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.

  3. Diagnostic microarray for 14 water and foodborne pathogens using a flatbed scanner.

    Science.gov (United States)

    Srinivasan, Vidya; Stedtfeld, Robert D; Tourlousse, Dieter M; Baushke, Samuel W; Xin, Yu; Miller, Sarah M; Pham, Trinh; Rouillard, Jean-Marie; Gulari, Erdogan; Tiedje, James M; Hashsham, Syed A

    2017-08-01

    Parallel detection approaches are of interest to many researchers interested in identifying multiple water and foodborne pathogens simultaneously. Availability and cost-effectiveness are two key factors determining the usefulness of such approaches for laboratories with limited resources. In this study, we developed and validated a high-density microarray for simultaneous screening of 14 bacterial pathogens using an approach that employs gold labeling with silver enhancement (GLS) protocol. In total, 8887 probes (50-mer) were designed using an in-house database of virulence and marker genes (VMGs), and synthesized in quadruplicate on glass slides using an in-situ synthesis technology. Target VMG amplicons were obtained using multiplex polymerase chain reaction (PCR), labeled with biotin, and hybridized to the microarray. The signals generated after gold deposition and silver enhancement, were quantified using a flatbed scanner having 2-μm resolution. Data analysis indicated that reliable presence/absence calls could be made, if: i) over four probes were used per gene, ii) the signal-to-noise ratio (SNR) cutoff was greater than or equal to two, and iii) the positive fraction (PF), i.e., number of probes with SNR≥2 for a given VMG was greater than 0.75. Hybridization of the array with blind samples resulted in 100% correct calls, and no false positive. Because amplicons were obtained by multiplex PCR, sensitivity of this method is similar to PCR. This assay is an inexpensive and reliable technique for high throughput screening of multiple pathogens. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Optimization of diagnostic microarray for application in analysing landfill methanotroph communities under different plant covers.

    Science.gov (United States)

    Stralis-Pavese, Nancy; Sessitsch, Angela; Weilharter, Alexandra; Reichenauer, Thomas; Riesing, Johann; Csontos, József; Murrell, J Colin; Bodrossy, Levente

    2004-04-01

    Landfill sites are responsible for 6-12% of global methane emission. Methanotrophs play a very important role in decreasing landfill site methane emissions. We investigated the methane oxidation capacity and methanotroph diversity in lysimeters simulating landfill sites with different plant vegetations. Methane oxidation rates were 35 g methane m-2 day-1 or higher for planted lysimeters and 18 g methane m-2 day-1 or less for bare soil controls. Best methane oxidation, as displayed by gas depth profiles, was found under a vegetation of grass and alfalfa. Methanotroph communities were analysed at high throughput and resolution using a microbial diagnostic microarray targeting the particulate methane monooxygenase (pmoA) gene of methanotrophs and functionally related bacteria. Members of the genera Methylocystis and Methylocaldum were found to be the dominant members in landfill site simulating lysimeters. Soil bacterial communities in biogas free control lysimeters, which were less abundant in methanotrophs, were dominated by Methylocaldum. Type Ia methanotrophs were found only in the top layers of bare soil lysimeters with relatively high oxygen and low methane concentrations. A competetive advantage of type II methanotrophs over type Ia methanotrophs was indicated under all plant covers investigated. Analysis of average and individual results from parallel samples was used to identify general trends and variations in methanotroph community structures in relation to depth, methane supply and plant cover. The applicability of the technology for the detection of environmental perturbations was proven by an erroneous result, where an unexpected community composition detected with the microarray indicated a potential gas leakage in the lysimeter being investigated.

  5. 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 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. An integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection

    Science.gov (United States)

    Liu, Hai-Tao; Wen, Zhi-Yu; Xu, Yi; Shang, Zheng-Guo; Peng, Jin-Lan; Tian, Peng

    2017-09-01

    In this paper, an integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection was purposed based on microfluidic chips dielectrophoresis technique and electrochemical impedance detection principle. The microsystems include microfluidic chip, main control module, and drive and control module, and signal detection and processing modulet and result display unit. The main control module produce the work sequence of impedance detection system parts and achieve data communication functions, the drive and control circuit generate AC signal which amplitude and frequency adjustable, and it was applied on the foodborne pathogens impedance analysis microsystems to realize the capture enrichment and impedance detection. The signal detection and processing circuit translate the current signal into impendence of bacteria, and transfer to computer, the last detection result is displayed on the computer. The experiment sample was prepared by adding Escherichia coli standard sample into chicken sample solution, and the samples were tested on the dielectrophoresis chip capture enrichment and in-situ impedance detection microsystems with micro-array electrode microfluidic chips. The experiments show that the Escherichia coli detection limit of microsystems is 5 × 104 CFU/mL and the detection time is within 6 min in the optimization of voltage detection 10 V and detection frequency 500 KHz operating conditions. The integrated microfluidic analysis microsystems laid the solid foundation for rapid real-time in-situ detection of bacteria.

  7. 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

    AIM: Periodontitis is a multifactorial disease in which subgingival bacteria play an important role in the pathogenesis of the disease. The objective of this study was to determine if periodontitis is associated with a characteristic salivary bacterial profile. This was accomplished by comparing...... 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...... component analysis was used to visualize bacterial community profiles obtained by the HOMIM. RESULTS: Eight bacterial taxa, including putative periodontal pathogens as Parvimonas micra and Filifactor alocis, and four bacterial clusters were identified statistically more frequently and at higher levels...

  8. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Seoighe Cathal

    2011-01-01

    Full Text Available 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.

  10. Drop drying on surfaces determines chemical reactivity - the specific case of immobilization of oligonucleotides on microarrays

    Science.gov (United States)

    2013-01-01

    Background Drop drying is a key factor in a wide range of technical applications, including spotted microarrays. The applied nL liquid volume provides specific reaction conditions for the immobilization of probe molecules to a chemically modified surface. Results We investigated the influence of nL and μL liquid drop volumes on the process of probe immobilization and compare the results obtained to the situation in liquid solution. In our data, we observe a strong relationship between drop drying effects on immobilization and surface chemistry. In this work, we present results on the immobilization of dye labeled 20mer oligonucleotides with and without an activating 5′-aminoheptyl linker onto a 2D epoxysilane and a 3D NHS activated hydrogel surface. Conclusions Our experiments identified two basic processes determining immobilization. First, the rate of drop drying that depends on the drop volume and the ambient relative humidity. Oligonucleotides in a dried spot react unspecifically with the surface and long reaction times are needed. 3D hydrogel surfaces allow for immobilization in a liquid environment under diffusive conditions. Here, oligonucleotide immobilization is much faster and a specific reaction with the reactive linker group is observed. Second, the effect of increasing probe concentration as a result of drop drying. On a 3D hydrogel, the increasing concentration of probe molecules in nL spotting volumes accelerates immobilization dramatically. In case of μL volumes, immobilization depends on whether the drop is allowed to dry completely. At non-drying conditions, very limited immobilization is observed due to the low oligonucleotide concentration used in microarray spotting solutions. The results of our study provide a general guideline for microarray assay development. They allow for the initial definition and further optimization of reaction conditions for the immobilization of oligonucleotides and other probe molecule classes to different

  11. Cross-platform comparison of microarray data using order restricted inference

    Science.gov (United States)

    Klinglmueller, Florian; Tuechler, Thomas; Posch, Martin

    2013-01-01

    Motivation Titration experiments measuring the gene expression from two different tissues, along with total RNA mixtures of the pure samples, are frequently used for quality evaluation of microarray technologies. Such a design implies that the true mRNA expression of each gene, is either constant or follows a monotonic trend between the mixtures, applying itself to the use of order restricted inference procedures. Exploiting only the postulated monotonicity of titration designs, we propose three statistical analysis methods for the validation of high-throughput genetic data and corresponding preprocessing techniques. Results Our methods allow for inference of accuracy, repeatability and cross-platform agreement, with minimal required assumptions regarding the underlying data generating process. Therefore, they are readily applicable to all sorts of genetic high-throughput data independent of the degree of preprocessing. An application to the EMERALD dataset was used to demonstrate how our methods provide a rich spectrum of easily interpretable quality metrics and allow the comparison of different microarray technologies and normalization methods. The results are on par with previous work, but provide additional new insights that cast doubt on the utility of popular preprocessing techniques, specifically concerning the EMERALD projects dataset. Availability All datasets are available on EBI’s ArrayExpress web site (http://www.ebi.ac.uk/microarray-as/ae/) under accession numbers E-TABM-536, E-TABM-554 and E-TABM-555. Source code implemented in C and R is available at: http://statistics.msi.meduniwien.ac.at/float/cross_platform/. Methods for testing and variance decomposition have been made available in the R-package orQA, which can be downloaded and installed from CRAN http://cran.r-project.org. PMID:21317143

  12. Normalization and gene p-value estimation: issues in microarray data processing.

    Science.gov (United States)

    Fundel, Katrin; Küffner, Robert; Aigner, Thomas; Zimmer, Ralf

    2008-05-28

    Numerous methods exist for basic processing, e.g. normalization, of microarray gene expression data. These methods have an important effect on the final analysis outcome. Therefore, it is crucial to select methods appropriate for a given dataset in order to assure the validity and reliability of expression data analysis. Furthermore, biological interpretation requires expression values for genes, which are often represented by several spots or probe sets on a microarray. How to best integrate spot/probe set values into gene values has so far been a somewhat neglected problem. We present a case study comparing different between-array normalization methods with respect to the identification of differentially expressed genes. Our results show that it is feasible and necessary to use prior knowledge on gene expression measurements to select an adequate normalization method for the given data. Furthermore, we provide evidence that combining spot/probe set p-values into gene p-values for detecting differentially expressed genes has advantages compared to combining expression values for spots/probe sets into gene expression values. The comparison of different methods suggests to use Stouffer's method for this purpose. The study has been conducted on gene expression experiments investigating human joint cartilage samples of osteoarthritis related groups: a cDNA microarray (83 samples, four groups) and an Affymetrix (26 samples, two groups) data set. The apparently straight forward steps of gene expression data analysis, e.g. between-array normalization and detection of differentially regulated genes, can be accomplished by numerous different methods. We analyzed multiple methods and the possible effects and thereby demonstrate the importance of the single decisions taken during data processing. We give guidelines for evaluating normalization outcomes. An overview of these effects via appropriate measures and plots compared to prior knowledge is essential for the biological

  13. Normal uniform mixture differential gene expression detection for cDNA microarrays

    Directory of Open Access Journals (Sweden)

    Raftery Adrian E

    2005-07-01

    Full Text Available Abstract Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002 1. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM, and Empirical Bayes for microarrays (EBarrays with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at http://www.bioconductor.org.

  14. Cross-platform comparison of microarray data using order restricted inference.

    Science.gov (United States)

    Klinglmueller, Florian; Tuechler, Thomas; Posch, Martin

    2011-04-01

    Titration experiments measuring the gene expression from two different tissues, along with total RNA mixtures of the pure samples, are frequently used for quality evaluation of microarray technologies. Such a design implies that the true mRNA expression of each gene, is either constant or follows a monotonic trend between the mixtures, applying itself to the use of order restricted inference procedures. Exploiting only the postulated monotonicity of titration designs, we propose three statistical analysis methods for the validation of high-throughput genetic data and corresponding preprocessing techniques. Our methods allow for inference of accuracy, repeatability and cross-platform agreement, with minimal required assumptions regarding the underlying data generating process. Therefore, they are readily applicable to all sorts of genetic high-throughput data independent of the degree of preprocessing. An application to the EMERALD dataset was used to demonstrate how our methods provide a rich spectrum of easily interpretable quality metrics and allow the comparison of different microarray technologies and normalization methods. The results are on par with previous work, but provide additional new insights that cast doubt on the utility of popular preprocessing techniques, specifically concerning the EMERALD projects dataset. All datasets are available on EBI's ArrayExpress web site http://www.ebi.ac.uk/microarray-as/ae/) under accession numbers E-TABM-536, E-TABM-554 and E-TABM-555. Source code implemented in C and R is available at: http://statistics.msi.meduniwien.ac.at/float/cross_platform/. Methods for testing and variance decomposition have been made available in the R-package orQA, which can be downloaded and installed from CRAN http://cran.r-project.org.

  15. 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.

  16. 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.

  17. Microarray is an efficient tool for circRNA profiling.

    Science.gov (United States)

    Li, Shasha; Teng, Shuaishuai; Xu, Junquan; Su, Guannan; Zhang, Yu; Zhao, Jianqing; Zhang, Suwei; Wang, Haiyan; Qin, Wenyan; Lu, Zhi John; Guo, Yong; Zhu, Qianyong; Wang, Dong

    2018-02-03

    Circular RNAs (circRNAs) are emerging as a new class of endogenous and regulatory noncoding RNAs in latest years. With the widespread application of RNA sequencing (RNA-seq) technology and bioinformatics prediction, large numbers of circRNAs have been identified. However, at present, we lack a comprehensive characterization of all these circRNAs in interested samples. In this study, we integrated 87 935 circRNAs sequences that cover most of circRNAs identified till now represented in circBase to design microarray probes targeting back-splice site of each circRNA to profile expression of those circRNAs. By comparing the circRNA detection efficiency of RNA-seq with this circRNA microarray, we revealed that microarray is more efficient than RNA-seq for circRNA profiling. Then, we found ∼80 000 circRNAs were expressed in cervical tumors and matched normal tissues, and ∼25 000 of them were differently expressed. Notably, many of these circRNAs detected by this microarray can be validated by quantitative reverse transcription polymerase chain reaction (RT-qPCR) or RNA-seq. Strikingly, as many as ∼18 000 circRNAs could be robustly detected in cell-free plasma samples, and the expression of ∼2700 of them differed after surgery for tumor removal. Our findings provided a comprehensive and genome-wide characterization of circRNAs in paired normal tissues and tumors and plasma samples from multiple individuals. In addition, we also provide a rich resource with 41 microarray data sets and 10 RNA-seq data sets and strong evidences for circRNA expression in cervical cancer. In conclusion, circRNAs could be efficiently profiled by circRNA microarray to target their reported back-splice sites in interested samples. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

    DEFF Research Database (Denmark)

    Kibat, Janek; Schirrmann, Thomas; Knape, Matthias J

    2016-01-01

    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...

  19. 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

  20. Fuzzy C-means method with empirical mode decomposition for clustering microarray data.

    Science.gov (United States)

    Wang, Yan-Fei; Yu, Zu-Guo; Anh, Vo

    2013-01-01

    Microarray techniques have revolutionised genomic research by making it possible to monitor the expression of thousands of genes in parallel. The Fuzzy C-Means (FCM) method is an efficient clustering approach devised for microarray data analysis. However, microarray data contains noise, which would affect clustering results. In this paper, we propose to combine the FCM method with the Empirical Mode Decomposition (EMD) for clustering microarray data to reduce the effect of the noise. The results suggest the clustering structures of denoised microarray data are more reasonable and genes have tighter association with their clusters than those using FCM only.

  1. 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

  2. A microarray gene expressions with classification using extreme learning machine

    Directory of Open Access Journals (Sweden)

    Yasodha M.

    2015-01-01

    Full Text Available In the present scenario, one of the dangerous disease is cancer. It spreads through blood or lymph to other location of the body, it is a set of cells display uncontrolled growth, attack and destroy nearby tissues, and occasionally metastasis. In cancer diagnosis and molecular biology, a utilized effective tool is DNA microarrays. The dominance of this technique is recognized, so several open doubt arise regarding proper examination of microarray data. In the field of medical sciences, multicategory cancer classification plays very important role. The need for cancer classification has become essential because the number of cancer sufferers is increasing. In this research work, to overcome problems of multicategory cancer classification an improved Extreme Learning Machine (ELM classifier is used. It rectify problems faced by iterative learning methods such as local minima, improper learning rate and over fitting and the training completes with high speed.

  3. Analyses of Aloe polysaccharides using carbohydrate microarray profiling

    DEFF Research Database (Denmark)

    Isager Ahl, Louise; Grace, Olwen M; Pedersen, Henriette Lodberg

    2018-01-01

    As the popularity of Aloe vera extracts continues to rise, a desire to fully understand the individual polymer components of the leaf mesophyll, their relation to one another and the effects they have on the human body are increasing. Polysaccharides present in the leaf mesophyll have been...... identified as the components responsible for the biological activities of Aloe vera, and they have been widely studied in the past decades. However, the commonly used methods do not provide the desired platform to conduct large comparative studies of polysaccharide compositions as most of them require...... a complete or near-complete fractionation of the polymers. The objective for this study was to assess whether carbohydrate microarrays could be used for the high-throughput analysis of cell wall polysaccharides in Aloe leaf mesophyll. The method we chose is known as Comprehensive Microarray Polymer Profiling...

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

    Science.gov (United States)

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

    2016-01-01

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

  5. Studying bacterial multispecies biofilms

    DEFF Research Database (Denmark)

    Røder, Henriette Lyng; Sørensen, Søren Johannes; Burmølle, Mette

    2016-01-01

    , but the identity and significance of interspecies bacterial interactions is neglected in these analyses. There is therefore an urgent need for bridging the gap between metagenomic analysis and in vitro models suitable for studies of bacterial interactions.Bacterial interactions and coadaptation are important......The high prevalence and significance of multispecies biofilms have now been demonstrated in various bacterial habitats with medical, industrial, and ecological relevance. It is highly evident that several species of bacteria coexist and interact in biofilms, which highlights the need for evaluating...

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

    Science.gov (United States)

    2012-01-01

    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. PMID:23256600

  7. Microarray estimation of genomic inter-strain variability in the genus Ectocarpus (Phaeophyceae

    Directory of Open Access Journals (Sweden)

    Peters Akira F

    2011-01-01

    Full Text Available Background Brown algae of the genus Ectocarpus exhibit high levels of genetic diversity and variability in morphological and physiological characteristics. With the establishment of E. siliculosus as a model and the availability of a complete genome sequence, it is now of interest to analyze variability among different species, ecotypes, and strains of the genus Ectocarpus both at the genome and the transcriptome level. Results We used an E. siliculosus gene expression microarray based on EST sequences from the genome-sequenced strain (reference strain to carry out comparative genome hybridizations for five Ectocarpus strains: four E. siliculosus isolates (the male genome strain, a female strain used for outcrosses with the genome strain, a strain isolated from freshwater, and a highly copper-tolerant strain, as well as one strain of the sister species E. fasciculatus. Our results revealed significant genomic differences between ecotypes of the same species, and enable the selection of conserved probes for future microarray experiments with these strains. In the two closely related strains (a male and a female strain used for crosses, genomic differences were also detected, but concentrated in two smaller genomic regions, one of which corresponds to a viral insertion site. Conclusion The high variability between strains supports the concept of E. siliculosus as a complex of cryptic species. Moreover, our data suggest that several parts of the Ectocarpus genome may have evolved at different rates: high variability was detected particularly in transposable elements and fucoxanthin chlorophyll a/c binding proteins.

  8. BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.

    Science.gov (United States)

    Geeleher, Paul; Morris, Dermot; Hinde, John P; Golden, Aaron

    2009-06-01

    BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).

  9. Algorithm-driven artifacts in median polish summarization of microarray data.

    Science.gov (United States)

    Giorgi, Federico M; Bolger, Anthony M; Lohse, Marc; Usadel, Bjoern

    2010-11-11

    High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification. In the present paper we benchmark the three most used normalization procedures (MAS5, RMA and GCRMA) in the context of inter-array correlation analysis, confirming and extending the finding that RMA and GCRMA consistently overestimate sample similarity upon normalization. We determine that median polish summarization is responsible for generating a large proportion of these over-similarity artifacts. Furthermore, we show that most affected probesets show also internal signal disagreement, and tend to be composed by individual probes hitting different gene transcripts. We finally provide a correction to the RMA/GCRMA summarization procedure that massively reduces inter-array correlation artifacts, without affecting the detection of differentially expressed genes. We propose tRMA as a modification of RMA to normalize microarray experiments for correlation-based analysis.

  10. Density based pruning for identification of differentially expressed genes from microarray data

    Directory of Open Access Journals (Sweden)

    Xu Jia

    2010-11-01

    Full Text Available Abstract Motivation Identification of differentially expressed genes from microarray datasets is one of the most important analyses for microarray data mining. Popular algorithms such as statistical t-test rank genes based on a single statistics. The false positive rate of these methods can be improved by considering other features of differentially expressed genes. Results We proposed a pattern recognition strategy for identifying differentially expressed genes. Genes are mapped to a two dimension feature space composed of average difference of gene expression and average expression levels. A density based pruning algorithm (DB Pruning is developed to screen out potential differentially expressed genes usually located in the sparse boundary region. Biases of popular algorithms for identifying differentially expressed genes are visually characterized. Experiments on 17 datasets from Gene Omnibus Database (GEO with experimentally verified differentially expressed genes showed that DB pruning can significantly improve the prediction accuracy of popular identification algorithms such as t-test, rank product, and fold change. Conclusions Density based pruning of non-differentially expressed genes is an effective method for enhancing statistical testing based algorithms for identifying differentially expressed genes. It improves t-test, rank product, and fold change by 11% to 50% in the numbers of identified true differentially expressed genes. The source code of DB pruning is freely available on our website http://mleg.cse.sc.edu/degprune

  11. 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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Prospects for exploring the molecular-genomic foundations of therapeutic hypnosis with DNA microarrays.

    Science.gov (United States)

    Rossi, Ernest Lawrence

    A new perspective on how therapeutic hypnosis and neuroscience may be integrated on the molecular-genomic level is offered as a guide for basic research and clinical applications. An update of Watson and Crick's original formulation of molecular biology is proposed to illustrate how psychosocial experiences modulate gene expression, protein synthesis, and brain plasticity during memory trace reactivation for the reorganization of neural networks that encode fear, stress, and traumatic symptoms. Examples of the scientific literature on DNA microarrays are used to explore how this new technology could integrate therapeutic hypnosis, neuroscience, and psychosocial genomics as a new foundation for mind-body medicine. Researchers and clinicians in therapeutic hypnosis need to partner with colleagues in neuroscience and molecular biology that utilize DNA microarray technology. It is recommended that hypnotic susceptibility scales of the future incorporate gene expression data to include the concept of "embodied imagination" and the "ideo-plastic faculty" on a molecular-genomic level as well as the psychological and behavioral level of ideomotor and ideosensory responses that are currently assessed.

  13. 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.

  14. 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

  15. 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.

  16. Specific serology for emerging human coronaviruses by protein microarray

    NARCIS (Netherlands)

    Reusken, C.; Mou, H.; Godeke, G. J.; van der Hoek, L.; Meyer, B.; Müller, M. A.; Haagmans, B.; de Sousa, R.; Schuurman, N.; Dittmer, U.; Rottier, P.; Osterhaus, A.; Drosten, C.; Bosch, B. J.; Koopmans, M.

    2013-01-01

    We present a serological assay for the specific detection of IgM and IgG antibodies against the emerging human coronavirus hCoV-EMC and the SARS-CoV based on protein microarray technology. The assay uses the S1 receptor-binding subunit of the spike protein of hCoV-EMC and SARS-CoV as antigens. The

  17. Microarrays of near-field optical probes with adjustable dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Chovin, A. [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire, Universite Bordeaux I, ENSCPB, 16 avenue Pey-Berland, 33607 Pessac (France); Garrigue, P. [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire, Universite Bordeaux I, ENSCPB, 16 avenue Pey-Berland, 33607 Pessac (France); Pecastaings, G. [Centre de Recherche Paul Pascal-CNRS, 115 avenue du Dr Schweitzer, 33600 Pessac (France); Saadaoui, H. [Centre de Recherche Paul Pascal-CNRS, 115 avenue du Dr Schweitzer, 33600 Pessac (France); Manek-Hoenninger, I. [Centre Lasers Intenses et Applications, Universite Bordeaux I, 351 Cours de la Liberation, 33405 Talence (France)]. E-mail: manek@celia.u-bordeaux1.fr; Sojic, N. [Laboratoire d' Analyse Chimique par Reconnaissance Moleculaire, Universite Bordeaux I, ENSCPB, 16 avenue Pey-Berland, 33607 Pessac (France)]. E-mail: sojic@enscpb.fr

    2006-01-15

    We present the fabrication and the characterization of high-density microarrays comprising thousands of near-field optical probes. Two types of microarrays have been prepared by adapting the SNOM methodology: arrays of uncoated fiber nanotips (i.e. apertureless probes) and arrays of apertures with adjustable subwavelength dimensions. Such arrays were fabricated by retaining the coherent structure of monomode optical fiber bundles and therefore keeping their imaging properties. The size of the apertures in a microarray was tuned at the nanometer scale by modifying the fabrication parameters. Far-field characterization of these near-field probe arrays shows completely different behavior depending both on their architecture and on their characteristic size. The angular distribution of the far-field intensity transmitted through the aperture arrays is used to determine the optical size of such diffracting apertures. Aperture radii ranging from 95 to 250 nm were found in good agreement with SEM data. Furthermore, each nanoaperture of the array is optically independent in the far-field regime. Eventually, this study demonstrates potential applications of these imaging arrays as parallel near-field optical probes in both configurations (apertureless and with apertures)

  18. Microarrays of near-field optical probes with adjustable dimensions.

    Science.gov (United States)

    Chovin, A; Garrigue, P; Pecastaings, G; Saadaoui, H; Manek-Hönninger, I; Sojic, N

    2006-01-01

    We present the fabrication and the characterization of high-density microarrays comprising thousands of near-field optical probes. Two types of microarrays have been prepared by adapting the SNOM methodology: arrays of uncoated fiber nanotips (i.e. apertureless probes) and arrays of apertures with adjustable subwavelength dimensions. Such arrays were fabricated by retaining the coherent structure of monomode optical fiber bundles and therefore keeping their imaging properties. The size of the apertures in a microarray was tuned at the nanometer scale by modifying the fabrication parameters. Far-field characterization of these near-field probe arrays shows completely different behavior depending both on their architecture and on their characteristic size. The angular distribution of the far-field intensity transmitted through the aperture arrays is used to determine the optical size of such diffracting apertures. Aperture radii ranging from 95 to 250 nm were found in good agreement with SEM data. Furthermore, each nanoaperture of the array is optically independent in the far-field regime. Eventually, this study demonstrates potential applications of these imaging arrays as parallel near-field optical probes in both configurations (apertureless and with apertures).

  19. Intestinal microbiota in healthy U.S. young children and adults--a high throughput microarray analysis.

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    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.

  20. Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

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    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

  1. 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.

  2. Mulcom: a multiple comparison statistical test for microarray data in Bioconductor.

    Science.gov (United States)

    Isella, Claudio; Renzulli, Tommaso; Corà, Davide; Medico, Enzo

    2011-09-28

    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. 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 < 0.001 in 4 categories vs. 3). 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 differentially expressed

  3. 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

  4. Instance-based concept learning from multiclass DNA microarray data

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    Dubitzky Werner

    2006-02-01

    Full Text Available Abstract Background Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as nearest neighbor (NN approaches perform remarkably well in comparison to more complex models, and are currently experiencing a renaissance in the analysis of data sets from biology and biotechnology. While binary classification of microarray data has been extensively investigated, studies involving multiclass data are rare. The question remains open whether there exists a significant difference in performance between NN approaches and more complex multiclass methods. Comparative studies in this field commonly assess different models based on their classification accuracy only; however, this approach lacks the rigor needed to draw reliable conclusions and is inadequate for testing the null hypothesis of equal performance. Comparing novel classification models to existing approaches requires focusing on the significance of differences in performance. Results We investigated the performance of instance-based classifiers, including a NN classifier able to assign a degree of class membership to each sample. This model alleviates a major problem of conventional instance-based learners, namely the lack of confidence values for predictions. The model translates the distances to the nearest neighbors into 'confidence scores'; the higher the confidence score, the closer is the considered instance to a pre-defined class. We applied the models to three real gene expression data sets and compared them with state-of-the-art methods for classifying microarray data of multiple classes, assessing performance using a statistical significance test that took into account the data resampling strategy. Simple NN classifiers performed as well as, or significantly better than, their more intricate competitors. Conclusion Given its highly intuitive underlying principles – simplicity

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

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    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.

  6. Literature Lab: a method of automated literature interrogation to infer biology from microarray analysis

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    Stegmaier Kimberly

    2007-12-01

    Full Text Available Abstract Background The biomedical literature is a rich source of associative information but too vast for complete manual review. We have developed an automated method of literature interrogation called "Literature Lab" that identifies and ranks associations existing in the literature between gene sets, such as those derived from microarray experiments, and curated sets of key terms (i.e. pathway names, medical subject heading (MeSH terms, etc. Results Literature Lab was developed using differentially expressed gene sets from three previously published cancer experiments and tested on a fourth, novel gene set. When applied to the genesets from the published data including an in vitro experiment, an in vivo mouse experiment, and an experiment with human tumor samples, Literature Lab correctly identified known biological processes occurring within each experiment. When applied to a novel set of genes differentially expressed between locally invasive and metastatic prostate cancer, Literature Lab identified a strong association between the pathway term "FOSB" and genes with increased expression in metastatic prostate cancer. Immunohistochemistry subsequently confirmed increased nuclear FOSB staining in metastatic compared to locally invasive prostate cancers. Conclusion This work demonstrates that Literature Lab can discover key biological processes by identifying meritorious associations between experimentally derived gene sets and key terms within the biomedical literature.

  7. A mixed-species microarray for identification of food spoilage bacilli.

    Science.gov (United States)

    Caspers, Martien P M; Schuren, Frank H J; van Zuijlen, Andre C M; Brul, Stanley; Montijn, Roy C; Abee, Tjakko; Kort, Remco

    2011-04-01

    Failure of food preservation is frequently caused by thermostable spores of members of the Bacillaceae family, which show a wide spectrum of resistance to cleaning and preservation treatments. We constructed and validated a mixed-species genotyping array for 6 Bacillus species, including Bacillus subtilis, Bacillus licheniformis, Bacillus pumilus, Bacillus sporothermodurans, Bacillus cereus and Bacillus coagulans, and 4 Geobacillus species, including Geobacillus stearothermophilus, Geobacillus thermocatenulatus, Geobacillus toebii and Geobacillus sp., in order to track food spoilage isolates from ingredient to product. The discriminating power of the array was evaluated with sets of 42 reference and 20 test strains. Bacterial isolates contain a within-species-conserved core genome comprising 68-88% of the entire genome and a non-conserved accessory genome comprising 7-22%. The majority of the core genome markers do not hybridise between species, thus they allow for efficient discrimination at the species level. The accessory genome array markers provide high-resolution discrimination at the level of individual isolates from a single species. In conclusion, the reported mixed-species microarray contains discriminating markers that allow rapid and cost-effective typing of Bacillus food spoilage bacteria in a wide variety of food products. Copyright © 2010 Elsevier Ltd. All rights reserved.

  8. Microarray-based whole-genome hybridization as a tool for determining procaryotic species relatedness.

    Science.gov (United States)

    Wu, Liyou; Liu, Xueduan; Fields, Matthew W; Thompson, Dorothea K; Bagwell, Christopher E; Tiedje, James M; Hazen, Terry C; Zhou, Jizhong

    2008-06-01

    The definition and delineation of microbial species are of great importance and challenge due to the extent of evolution and diversity. Whole-genome DNA-DNA hybridization is the cornerstone for defining procaryotic species relatedness, but obtaining pairwise DNA-DNA reassociation values for a comprehensive phylogenetic analysis of procaryotes is tedious and time consuming. A previously described microarray format containing whole-genomic DNA (the community genome array or CGA) was rigorously evaluated as a high-throughput alternative to the traditional DNA-DNA reassociation approach for delineating procaryotic species relationships. DNA similarities for multiple bacterial strains obtained with the CGA-based hybridization were comparable to those obtained with various traditional whole-genome hybridization methods (r=0.87, Pspecies relationships in several representative genera, including Pseudomonas, Azoarcus and Shewanella, were largely congruent with previous classifications based on various conventional whole-genome DNA-DNA reassociation, SSU rRNA and/or gyrB analyses. These results suggest that CGA-based DNA-DNA hybridization could serve as a powerful, high-throughput format for determining species relatedness among microorganisms.

  9. 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.

  10. A novel synthetic peptide microarray assay detects Chlamydia species-specific antibodies in animal and human sera.

    Science.gov (United States)

    Sachse, Konrad; Rahman, Kh Shamsur; Schnee, Christiane; Müller, Elke; Peisker, Madlen; Schumacher, Thomas; Schubert, Evelyn; Ruettger, Anke; Kaltenboeck, Bernhard; Ehricht, Ralf

    2018-03-16

    Serological analysis of Chlamydia (C.) spp. infections is still mainly based on micro-immunofluorescence and ELISA. To overcome the limitations of conventional serology, we have designed a novel microarray carrying 52 synthetic peptides representing B-cell epitopes from immunodominant proteins of all 11 chlamydial species. The new assay has been validated using monospecific mouse hyperimmune sera. Subsequently, serum samples from cattle, sheep and humans with a known history of chlamydial infection were examined. For instance, the specific humoral response of sheep to treatment with a C. abortus vaccine has been visualized against a background of C. pecorum carriership. In samples from humans, dual infection with C. trachomatis and C. pneumoniae could be demonstrated. The experiments revealed that the peptide microarray assay was capable of simultaneously identifying specific antibodies to each Chlamydia spp. The actual assay represents an open platform test that can be complemented through future advances in Chlamydia proteome research. The concept of the highly parallel multi-antigen microarray proven in this study has the potential to enhance our understanding of antibody responses by defining not only a single quantitative response, but also the pattern of this response. The added value of using peptide antigens will consist in unprecedented serodiagnostic specificity.

  11. 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. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Sharmin, Farhana; Wakelin, Steve; Huygens, Flavia; Hargreaves, Megan

    2013-11-01

    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. Significant variation (p sugars present. This process may help displace other bacterial taxa, providing a competitive advantage for Firmicutes bacteria.

  13. 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

  14. "Bone Development" Is an Ontology Group Upregulated in Porcine Oocytes Before In Vitro Maturation: A Microarray Approach.

    Science.gov (United States)

    Budna, Joanna; Bryja, Artur; Celichowski, Piotr; Kranc, Wiesława; Ciesiółka, Sylwia; Borys, Sylwia; Rybska, Marta; Kolecka-Bednarczyk, Agata; Jeseta, Michal; Bukowska, Dorota; Antosik, Paweł; Brüssow, Klaus P; Bruska, Małgorzata; Nowicki, Michał; Zabel, Maciej; Kempisty, Bartosz

    2017-08-01

    Mammalian cumulus-oocyte complexes (COCs) reach full developmental capability during folliculogenesis and oogenesis. It is well recognized that only gametes achieving MII stage after in vivo or in vitro maturation (IVM) are successfully fertilized by a single spermatozoon. Although the process of oocyte nuclear and/or cytoplasmic maturation in pigs is well determined, there exist many differences that promote these processes in vivo and in vitro. Therefore, this study aimed to investigate the differences in RNA expression profiles between porcine oocytes before and after IVM using microarray and real-time quantitative polymerase chain reaction (RT-qPCR) assays. Experiments were performed on oocytes isolated from 55 pubertal crossbred Landrace gilts. The oocytes were analyzed both before and after IVM and only Brilliant Cresyl Blue (BCB)-positive gametes were used for subsequent microarray analysis (Affymetrix) and RT-qPCR analysis. The microarray assay, which measures expression of 12,258 transcripts, revealed 419 differentially expressed transcripts in porcine oocytes, from which 379 were downregulated and 40 were upregulated before IVM compared to those analyzed after IVM. After DAVID analysis, we found eight different transcripts, including IHH, BMP1, WWTR1, CHRDL1, KLF10, EIF2AK3, MMP14, and STC1. Their expression is related to the "bone development" ontology group and was further subjected to hierarchical clusterization. Using RT-qPCR analysis, we confirmed the results of the microarray assay, showing increased expression of the eight genes in oocytes before IVM compared to oocytes after maturation in vitro. It has been suggested that "bone development" belongs to one ontological group involving genes substantially upregulated in porcine oocytes before IVM. We suggest that the gamete mRNA expression profile before IVM may comprise stored transcripts, which are templates for protein biosynthesis following fertilization. We also hypothesize that these mRNAs may

  15. Changes in gene expression linked with adult reproductive diapause in a northern malt fly species: a candidate gene microarray study

    Directory of Open Access Journals (Sweden)

    Hoikkala Anneli

    2010-02-01

    Full Text Available Abstract Background Insect diapause is an important biological process which involves many life-history parameters important for survival and reproductive fitness at both individual and population level. Drosophila montana, a species of D. virilis group, has a profound photoperiodic reproductive diapause that enables the adult flies to survive through the harsh winter conditions of high latitudes and altitudes. We created a custom-made microarray for D. montana with 101 genes known to affect traits important in diapause, photoperiodism, reproductive behaviour, circadian clock and stress tolerance in model Drosophila species. This array gave us a chance to filter out genes showing expression changes during photoperiodic reproductive diapause in a species adapted to live in northern latitudes with high seasonal changes in environmental conditions. Results Comparisons among diapausing, reproducing and young D. montana females revealed expression changes in 24 genes on microarray; for example in comparison between diapausing and reproducing females one gene (Drosophila cold acclimation gene, Dca showed up-regulation and 15 genes showed down-regulation in diapausing females. Down-regulation of seven of these genes was specific to diapause state while in five genes the expression changes were linked with the age of the females rather than with their reproductive status. Also, qRT-PCR experiments confirmed couch potato (cpo gene to be involved in diapause of D. montana. Conclusions A candidate gene microarray proved to offer a practical and cost-effective way to trace genes that are likely to play an important role in photoperiodic reproductive diapause and further in adaptation to seasonally varying environmental conditions. The present study revealed two genes, Dca and cpo, whose role in photoperiodic diapause in D. montana is worth of studying in more details. Also, further studies using the candidate gene microarray with more specific experimental

  16. Chromosomal microarray analysis of consecutive individuals with autism spectrum disorders or learning disability presenting for genetic services.

    Science.gov (United States)

    Roberts, Jennifer L; Hovanes, Karine; Dasouki, Majed; Manzardo, Ann M; Butler, Merlin G

    2014-02-01

    Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105 K and 180K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009-2012). Of the 215 patients [140 males and 75 females (male/female ratio=1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n=20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n=8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group. © 2013 Elsevier B.V. All rights reserved.

  17. MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

    Science.gov (United States)

    Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

    2017-05-01

    Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

  18. Exploring bacterial infections: theoretical and experimental studies of the bacterial population dynamics and antibiotic treatment

    Science.gov (United States)

    Shao, Xinxian

    Bacterial infections are very common in human society. Thus extensive research has been conducted to reveal the molecular mechanisms of the pathogenesis and to evaluate the antibiotics' efficacy against bacteria. Little is known, however, about the population dynamics of bacterial populations and their interactions with the host's immune system. In this dissertation, a stochatic model is developed featuring stochastic phenotypic switching of bacterial individuals to explain the single-variant bottleneck discovered in multi strain bacterial infections. I explored early events in a bacterial infection establishment using classical experiments of Moxon and Murphy on neonatal rats. I showed that the minimal model and its simple variants do not work. I proposed modifications to the model that could explain the data quantitatively. The bacterial infections are also commonly established in physical structures, as biofilms or 3-d colonies. In contrast, most research on antibiotic treatment of bacterial infections has been conducted in well-mixed liquid cultures. I explored the efficacy of antibiotics to treat such bacterial colonies, a broadly applicable method is designed and evaluated where discrete bacterial colonies on 2-d surfaces were exposed to antibiotics. I discuss possible explanations and hypotheses for the experimental results. To verify these hypotheses, we investigated the dynamics of bacterial population as 3-d colonies. We showed that a minimal mathematical model of bacterial colony growth in 3-d was able to account for the experimentally observed presence of a diffusion-limited regime. The model further revealed highly loose packing of the cells in 3-d colonies and smaller cell sizes in colonies than plancktonic cells in corresponding liquid culture. Further experimental tests of the model predictions have revealed that the ratio of the cell size in liquid culture to that in colony cultures was consistent with the model prediction, that the dead cells

  19. [Spontaneous bacterial peritonitis].

    Science.gov (United States)

    Strauss, Edna; Caly, Wanda Regina

    2003-01-01

    Spontaneous bacterial peritonitis occurs in 30% of patients with ascites due to cirrhosis leading to high morbidity and mortality rates. The pathogenesis of spontaneous bacterial peritonitis is related to altered host defenses observed in end-stage liver disease, overgrowth of microorganisms, and bacterial translocation from the intestinal lumen to mesenteric lymph nodes. Clinical manifestations vary from severe to slight or absent, demanding analysis of the ascitic fluid. The diagnosis is confirmed by a number of neutrophils over 250/mm3 associated or not to bacterial growth in culture of an ascites sample. Enterobacteriae prevail and Escherichia coli has been the most frequent bacterium reported. Mortality rates decreased markedly in the last two decades due to early diagnosis and prompt antibiotic treatment. Third generation intravenous cephalosporins are effective in 70% to 95% of the cases. Recurrence of spontaneous bacterial peritonitis is common and can be prevented by the continuous use of oral norfloxacin. The development of bacterial resistance demands the search for new options in the prophylaxis of spontaneous bacterial peritonitis; probiotics are a promising new approach, but deserve further evaluation. Short-term antibiotic prophylaxis is recommended for patients with cirrhosis and ascites shortly after an acute episode of gastrointestinal bleeding.

  20. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Science.gov (United States)

    Choi, Woon Yong; Kim, Ji Seon; Park, Sung Jin; Ma, Choong Je; Lee, Hyeon Yong

    2014-01-01

    In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL). Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out. PMID:24717412

  1. Microarray-Based Gene Expression Profiling to Elucidate Effectiveness of Fermented Codonopsis lanceolata in Mice

    Directory of Open Access Journals (Sweden)

    Woon Yong Choi

    2014-04-01

    Full Text Available In this study, the effect of Codonopsis lanceolata fermented by lactic acid on controlling gene expression levels related to obesity was observed in an oligonucleotide chip microarray. Among 8170 genes, 393 genes were up regulated and 760 genes were down regulated in feeding the fermented C. lanceolata (FCL. Another 374 genes were up regulated and 527 genes down regulated without feeding the sample. The genes were not affected by the FCL sample. It was interesting that among those genes, Chytochrome P450, Dmbt1, LOC76487, and thyroid hormones, etc., were mostly up or down regulated. These genes are more related to lipid synthesis. We could conclude that the FCL possibly controlled the gene expression levels related to lipid synthesis, which resulted in reducing obesity. However, more detailed protein expression experiments should be carried out.

  2. Pathway-based analysis of microarray and RNAseq data using Pathway Processor 2.0.

    Science.gov (United States)

    Beltrame, Luca; Bianco, Luca; Fontana, Paolo; Cavalieri, Duccio

    2013-03-01

    The constant improvement of high-throughput technologies has led to a great increase in generated data per single experiment. Pathway analysis is a widespread method to understand experimental results at the system level. Pathway Processor 2.0 is an upgrade over the original Pathway Processor program developed in 2002, extended to support more species, analysis methods, and RNAseq data in addition to microarrays through a simple Web-based interface. The tool can p