Science.gov

Sample records for antibody microarray analysis

  1. Surface chemistries for antibody microarrays

    SciTech Connect

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

    2007-05-01

    Enzyme-linked immunosorbent assay (ELISA) microarrays promise to be a powerful tool for the detection of disease biomarkers. The original technology for printing ELISA microarray chips and capturing antibodies on slides was derived from the DNA microarray field. However, due to the need to maintain antibody structure and function when immobilized, surface chemistries used for DNA microarrays are not always appropriate for ELISA microarrays. In order to identify better surface chemistries for antibody capture, a number of commercial companies and academic research groups have developed new slide types that could improve antibody function in microarray applications. In this review we compare and contrast the commercially available slide chemistries, as well as highlight some promising recent advances in the field.

  2. Antibody Colocalization Microarray: A Scalable Technology for Multiplex Protein Analysis in Complex Samples*

    PubMed Central

    Pla-Roca, M.; Leulmi, R. F.; Tourekhanova, S.; Bergeron, S.; Laforte, V.; Moreau, E.; Gosline, S. J. C.; Bertos, N.; Hallett, M.; Park, M.; Juncker, D.

    2012-01-01

    DNA microarrays were rapidly scaled up from 256 to 6.5 million targets, and although antibody microarrays were proposed earlier, sensitive multiplex sandwich assays have only been scaled up to a few tens of targets. Cross-reactivity, arising because detection antibodies are mixed, is a known weakness of multiplex sandwich assays that is mitigated by lengthy optimization. Here, we introduce (1) vulnerability as a metric for assays. The vulnerability of multiplex sandwich assays to cross-reactivity increases quadratically with the number of targets, and together with experimental results, substantiates that scaling up of multiplex sandwich assays is unfeasible. We propose (2) a novel concept for multiplexing without mixing named antibody colocalization microarray (ACM). In ACMs, both capture and detection antibodies are physically colocalized by spotting to the same two-dimensional coordinate. Following spotting of the capture antibodies, the chip is removed from the arrayer, incubated with the sample, placed back onto the arrayer and then spotted with the detection antibodies. ACMs with up to 50 targets were produced, along with a binding curve for each protein. The ACM was validated by comparing it to ELISA and to a small-scale, conventional multiplex sandwich assay (MSA). Using ACMs, proteins in the serum of breast cancer patients and healthy controls were quantified, and six candidate biomarkers identified. Our results indicate that ACMs are sensitive, robust, and scalable. PMID:22171321

  3. Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

    PubMed Central

    Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

    2014-01-01

    The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

  4. Extensive Antibody Cross-reactivity among Infectious Gram-negative Bacteria Revealed by Proteome Microarray Analysis *

    PubMed Central

    Keasey, Sarah L.; Schmid, Kara E.; Lee, Michael S.; Meegan, James; Tomas, Patricio; Minto, Michael; Tikhonov, Alexander P.; Schweitzer, Barry; Ulrich, Robert G.

    2009-01-01

    Antibodies provide a sensitive indicator of proteins displayed by bacteria during sepsis. Because signals produced by infection are naturally amplified during the antibody response, host immunity can be used to identify biomarkers for proteins that are present at levels currently below detectable limits. We developed a microarray comprising ∼70% of the 4066 proteins contained within the Yersinia pestis proteome to identify antibody biomarkers distinguishing plague from infections caused by other bacterial pathogens that may initially present similar clinical symptoms. We first examined rabbit antibodies produced against proteomes extracted from Y. pestis, Burkholderia mallei, Burkholderia cepecia, Burkholderia pseudomallei, Pseudomonas aeruginosa, Salmonella typhimurium, Shigella flexneri, and Escherichia coli, all pathogenic Gram-negative bacteria. These antibodies enabled detection of shared cross-reactive proteins, fingerprint proteins common for two or more bacteria, and signature proteins specific to each pathogen. Recognition by rabbit and non-human primate antibodies involved less than 100 of the thousands of proteins present within the Y. pestis proteome. Further antigen binding patterns were revealed that could distinguish plague from anthrax, caused by the Gram-positive bacterium Bacillus anthracis, using sera from acutely infected or convalescent primates. Thus, our results demonstrate potential biomarkers that are either specific to one strain or common to several species of pathogenic bacteria. PMID:19112181

  5. High-Resolution Analysis of Antibodies to Post-Translational Modifications Using Peptide Nanosensor Microarrays.

    PubMed

    Lee, Jung-Rok; Haddon, D James; Gupta, Nidhi; Price, Jordan V; Credo, Grace M; Diep, Vivian K; Kim, Kyunglok; Hall, Drew A; Baechler, Emily C; Petri, Michelle; Varma, Madoo; Utz, Paul J; Wang, Shan X

    2016-12-27

    Autoantibodies are a hallmark of autoimmune diseases such as lupus and have the potential to be used as biomarkers for diverse diseases, including immunodeficiency, infectious disease, and cancer. More precise detection of antibodies to specific targets is needed to improve diagnosis of such diseases. Here, we report the development of reusable peptide microarrays, based on giant magnetoresistive (GMR) nanosensors optimized for sensitively detecting magnetic nanoparticle labels, for the detection of antibodies with a resolution of a single post-translationally modified amino acid. We have also developed a chemical regeneration scheme to perform multiplex assays with a high level of reproducibility, resulting in greatly reduced experimental costs. In addition, we show that peptides synthesized directly on the nanosensors are approximately two times more sensitive than directly spotted peptides. Reusable peptide nanosensor microarrays enable precise detection of autoantibodies with high resolution and sensitivity and show promise for investigating antibody-mediated immune responses to autoantigens, vaccines, and pathogen-derived antigens as well as other fundamental peptide-protein interactions.

  6. Microarray Analysis of Antibodies Induced with Synthetic Antitumor Vaccines: Specificity against Diverse Mucin Core Structures.

    PubMed

    Pett, Christian; Cai, Hui; Liu, Jia; Palitzsch, Björn; Schorlemer, Manuel; Hartmann, Sebastian; Stergiou, Natascha; Lu, Mengji; Kunz, Horst; Schmitt, Edgar; Westerlind, Ulrika

    2017-03-17

    Glycoprotein research is pivotal for vaccine development and biomarker discovery. Many successful methodologies for reliably increasing the antigenicity toward tumor-associated glycopeptide structures have been reported. Deeper insights into the quality and specificity of the raised polyclonal, humoral reactions are often not addressed, despite the fact that an immunological memory, which produces antibodies with cross-reactivity to epitopes exposed on healthy cells, may cause autoimmune diseases. In the current work, three MUC1 antitumor vaccine candidates conjugated with different immune stimulants are evaluated immunologically. For assessment of the influence of the immune stimulant on antibody recognition, a comprehensive library of mucin 1 glycopeptides (>100 entries) is synthesized and employed in antibody microarray profiling; these range from small tumor-associated glycans (TN , STN , and T-antigen structures) to heavily extended O-glycan core structures (type-1 and type-2 elongated core 1-3 tri-, tetra-, and hexasaccharides) glycosylated in variable density at the five different sites of the MUC1 tandem repeat. This is one of the most extensive glycopeptide libraries ever made through total synthesis. On tumor cells, the core 2 β-1,6-N-acetylglucosaminyltransferase-1 (C2GlcNAcT-1) is down-regulated, resulting in lower amounts of the branched core 2 structures, which favor formation of linear core 1 or core 3 structures, and in particular, truncated tumor-associated antigen structures. The core 2 structures are commonly found on healthy cells and the elucidation of antibody cross-reactivity to such epitopes may predict the tumor-selectivity and safety of synthetic vaccines. With the extended mucin core structures in hand, antibody cross-reactivity toward the branched core 2 glycopeptide epitopes is explored. It is observed that the induced antibodies recognize MUC1 peptides with very high glycosylation site specificity. The nature of the

  7. Distinct antibody responses of patients with mild and severe leptospirosis determined by whole proteome microarray analysis

    PubMed Central

    Lessa-Aquino, Carolina; Lindow, Janet C.; Randall, Arlo; Wunder, Elsio; Pablo, Jozelyn; Nakajima, Rie; Jasinskas, Algis; Cruz, Jaqueline S.; Damião, Alcineia O.; Nery, Nívison; Ribeiro, Guilherme S.; Costa, Federico; Hagan, José E.; Reis, Mitermayer Galvão; Ko, Albert I.; Medeiros, Marco Alberto; Felgner, Philip L.

    2017-01-01

    Background Leptospirosis is an important zoonotic disease worldwide. Humans usually present a mild non-specific febrile illness, but a proportion of them develop more severe outcomes, such as multi-organ failure, lung hemorrhage and death. Such complications are thought to depend on several factors, including the host immunity. Protective immunity is associated with humoral immune response, but little is known about the immune response mounted during naturally-acquired Leptospira infection. Methods and principal findings Here, we used protein microarray chip to profile the antibody responses of patients with severe and mild leptospirosis against the complete Leptospira interrogans serovar Copenhageni predicted ORFeome. We discovered a limited number of immunodominant antigens, with 36 antigens specific to patients, of which 11 were potential serodiagnostic antigens, identified at acute phase, and 33 were potential subunit vaccine targets, detected after recovery. Moreover, we found distinct antibody profiles in patients with different clinical outcomes: in the severe group, overall IgM responses do not change and IgG responses increase over time, while both IgM and IgG responses remain stable in the mild patient group. Analyses of individual patients’ responses showed that >74% of patients in the severe group had significant IgG increases over time compared to 29% of patients in the mild group. Additionally, 90% of IgM responses did not change over time in the mild group, compared to ~51% in the severe group. Conclusions In the present study, we detected antibody profiles associated with disease severity and speculate that patients with mild disease were protected from severe outcomes due to pre-existing antibodies, while patients with severe leptospirosis demonstrated an antibody profile typical of first exposure. Our findings represent a significant advance in the understanding of the humoral immune response to Leptospira infection, and we have identified new

  8. Distinct antibody responses of patients with mild and severe leptospirosis determined by whole proteome microarray analysis.

    PubMed

    Lessa-Aquino, Carolina; Lindow, Janet C; Randall, Arlo; Wunder, Elsio; Pablo, Jozelyn; Nakajima, Rie; Jasinskas, Algis; Cruz, Jaqueline S; Damião, Alcineia O; Nery, Nívison; Ribeiro, Guilherme S; Costa, Federico; Hagan, José E; Reis, Mitermayer Galvão; Ko, Albert I; Medeiros, Marco Alberto; Felgner, Philip L

    2017-01-01

    Leptospirosis is an important zoonotic disease worldwide. Humans usually present a mild non-specific febrile illness, but a proportion of them develop more severe outcomes, such as multi-organ failure, lung hemorrhage and death. Such complications are thought to depend on several factors, including the host immunity. Protective immunity is associated with humoral immune response, but little is known about the immune response mounted during naturally-acquired Leptospira infection. Here, we used protein microarray chip to profile the antibody responses of patients with severe and mild leptospirosis against the complete Leptospira interrogans serovar Copenhageni predicted ORFeome. We discovered a limited number of immunodominant antigens, with 36 antigens specific to patients, of which 11 were potential serodiagnostic antigens, identified at acute phase, and 33 were potential subunit vaccine targets, detected after recovery. Moreover, we found distinct antibody profiles in patients with different clinical outcomes: in the severe group, overall IgM responses do not change and IgG responses increase over time, while both IgM and IgG responses remain stable in the mild patient group. Analyses of individual patients' responses showed that >74% of patients in the severe group had significant IgG increases over time compared to 29% of patients in the mild group. Additionally, 90% of IgM responses did not change over time in the mild group, compared to ~51% in the severe group. In the present study, we detected antibody profiles associated with disease severity and speculate that patients with mild disease were protected from severe outcomes due to pre-existing antibodies, while patients with severe leptospirosis demonstrated an antibody profile typical of first exposure. Our findings represent a significant advance in the understanding of the humoral immune response to Leptospira infection, and we have identified new targets for the development of subunit vaccines and

  9. ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

    PubMed Central

    Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren

    2017-01-01

    Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope. PMID:28095436

  10. Microarray analysis of the human antibody response to synthetic Cryptosporidium glycopeptides.

    PubMed

    Heimburg-Molinaro, Jamie; Priest, Jeffrey W; Live, David; Boons, Geert-Jan; Song, Xuezheng; Cummings, Richard D; Mead, Jan R

    2013-10-01

    Glycoproteins expressed by Cryptosporidium parvum are immunogenic in infected individuals but the nature of the epitopes recognised in C. parvum glycoproteins is poorly understood. Since a known immunodominant antigen of Cryptosporidium, the 17kDa glycoprotein, has previously been shown to bind to lectins that recognise the Tn antigen (GalNAcα1-Ser/Thr-R), a large number of glycopeptides with different Tn valency and presentation were prepared. In addition, glycopeptides were synthesised based on a 40kDa cryptosporidial antigen, a polymorphic surface glycoprotein with varying numbers of serine residues, to determine the reactivity with sera from C. parvum-infected humans. These glycopeptides and non-glycosylated peptides were used to generate a glycopeptide microarray to allow screening of sera from C. parvum-infected individuals for the presence of IgM and IgG antibodies. IgG but not IgM in sera from C. parvum-infected individuals bound to multivalent Tn antigen epitopes presented on glycopeptides, suggesting that glycoproteins from C. parvum that contain the Tn antigen induce immune responses upon infection. In addition, molecular differences in glycosylated peptides (e.g. substituting Ser for Thr) as well as the site of glycosylation had a pronounced effect on reactivity. Lastly, pooled sera from individuals infected with either Toxoplasma or Plasmodium were also tested against the modified Cryptosporidium peptides and some sera showed specific binding to glycopeptide epitopes. These studies reveal that specific anti-glycopeptide antibodies that recognise the Tn antigen may be useful diagnostically and in defining the roles of parasite glycoconjugates in infections.

  11. Analysis of liquid bead microarray antibody assay data for epidemiologic studies of pathogen-cancer associations.

    PubMed

    Colombara, Danny V; Hughes, James P; Burnett-Hartman, Andrea N; Hawes, Stephen E; Galloway, Denise A; Schwartz, Stephen M; Bostick, Roberd M; Potter, John D; Manhart, Lisa E

    2015-10-01

    Liquid bead microarray antibody (LBMA) assays are used to assess pathogen-cancer associations. However, studies analyze LBMA data differently, limiting comparability. We generated 10,000 Monte Carlo-type simulations of log-normal antibody distributions (exposure) with 200 cases and 200 controls (outcome). We estimated type I error rates, statistical power, and bias associated with t-tests, logistic regression with a linear exposure and with the exposure dichotomized at 200 units, 400 units, the mean among controls plus two standard deviations, and the value corresponding to the optimal sensitivity and specificity. We also applied these models, and data visualizations (kernel density plots, receiver operating characteristic (ROC) curves, predicted probability plots, and Q-Q plots), to two empirical datasets to assess the consistency of the exposure-outcome relationship. All strategies had acceptable type I error rates (0.03 ≤ P ≤ 0.048), except for the dichotomization according to optimal sensitivity and specificity, which had a type I error rate of 0.27. Among the remaining methods, logistic regression with a linear predictor (Power=1.00) and t-tests (Power=1.00) had the highest power to detect a mean difference of 1.0 MFI (median fluorescence intensity) on the log scale and were unbiased. Dichotomization methods upwardly biased the risk estimates. These results indicate that logistic regression with linear predictors and unpaired t-tests are superior to logistic regression with dichotomized predictors for assessing disease associations with LBMA data. Logistic regression with continuous linear predictors and t-tests are preferable to commonly used LBMA dichotomization methods. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Evaluation of Surface Chemistries for Antibody Microarrays

    SciTech Connect

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

    2007-12-01

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

  13. Antibody microarrays for native toxin detection.

    PubMed

    Rucker, Victor C; Havenstrite, Karen L; Herr, Amy E

    2005-04-15

    We have developed antibody-based microarray techniques for the multiplexed detection of cholera toxin beta-subunit, diphtheria toxin, anthrax lethal factor and protective antigen, Staphylococcus aureus enterotoxin B, and tetanus toxin C fragment in spiked samples. Two detection schemes were investigated: (i) a direct assay in which fluorescently labeled toxins were captured directly by the antibody array and (ii) a competition assay that employed unlabeled toxins as reporters for the quantification of native toxin in solution. In the direct assay, fluorescence measured at each array element is correlated with labeled toxin concentration to yield baseline binding information (Langmuir isotherms and affinity constants). Extending from the direct assay, the competition assay yields information on the presence, identity, and concentration of toxins. A significant advantage of the competition assay over reported profiling assays is the minimal sample preparation required prior to analysis because the competition assay obviates the need to fluorescently label native proteins in the sample of interest. Sigmoidal calibration curves and detection limits were established for both assay formats. Although the sensitivity of the direct assay is superior to that of the competition assay, detection limits for unmodified toxins in the competition assay are comparable to values reported previously for sandwich-format immunoassays of antibodies arrayed on planar substrates. As a demonstration of the potential of the competition assay for unlabeled toxin detection, we conclude with a straightforward multiplexed assay for the differentiation and identification of both native S. aureus enterotoxin B and tetanus toxin C fragment in spiked dilute serum samples.

  14. Discrimination of Influenza Infection (A/2009 H1N1) from Prior Exposure by Antibody Protein Microarray Analysis

    PubMed Central

    te Beest, Dennis; de Bruin, Erwin; Imholz, Sandra; Wallinga, Jacco; Teunis, Peter; Koopmans, Marion; van Boven, Michiel

    2014-01-01

    Reliable discrimination of recent influenza A infection from previous exposure using hemagglutination inhibition (HI) or virus neutralization tests is currently not feasible. This is due to low sensitivity of the tests and the interference of antibody responses generated by previous infections. Here we investigate the diagnostic characteristics of a newly developed antibody (HA1) protein microarray using data from cross-sectional serological studies carried out before and after the pandemic of 2009. The data are analysed by mixture models, providing a probabilistic classification of sera (susceptible, prior-exposed, recently infected). Estimated sensitivity and specificity for identifying A/2009 infections are low using HI (66% and 51%), and high when using A/2009 microarray data alone or together with A/1918 microarray data (96% and 95%). As a heuristic, a high A/2009 to A/1918 antibody ratio (>1.05) is indicative of recent infection, while a low ratio is indicative of a pre-existing response, even if the A/2009 titer is high. We conclude that highly sensitive and specific classification of individual sera is possible using the protein microarray, thereby enabling precise estimation of age-specific infection attack rates in the population even if sample sizes are small. PMID:25405997

  15. A multi-parametric microarray for protein profiling: simultaneous analysis of 8 different cytochromes via differentially element tagged antibodies and laser ablation ICP-MS.

    PubMed

    Waentig, Larissa; Techritz, Sandra; Jakubowski, Norbert; Roos, Peter H

    2013-11-07

    The paper presents a new multi-parametric protein microarray embracing the multi-analyte capabilities of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). The combination of high throughput reverse phase protein microarrays with element tagged antibodies and LA-ICP-MS makes it possible to detect and quantify many proteins or biomarkers in multiple samples simultaneously. A proof of concept experiment is performed for the analysis of cytochromes particularly of cytochrome P450 enzymes, which play an important role in the metabolism of xenobiotics such as toxicants and drugs. With the aid of the LA-ICP-MS based multi-parametric reverse phase protein microarray it was possible to analyse 8 cytochromes in 14 different proteomes in one run. The methodology shows excellent detection limits in the lower amol range and a very good linearity of R(2) ≥ 0.9996 which is a prerequisite for the development of further quantification strategies.

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

    PubMed

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

    2012-02-01

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

  17. Comparison of hydroxylated print additives on antibody microarray performance

    PubMed Central

    Wu, Peng; Grainger, David W.

    2008-01-01

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

  18. Direct labeling of serum proteins by fluorescent dye for antibody microarray.

    PubMed

    Klimushina, M V; Gumanova, N G; Metelskaya, V A

    2017-05-06

    Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2016-09-25

    Many diagnostic and therapeutic concepts require antibodies of high specificity. Recombinant binder libraries and related selection approaches allow the efficient isolation of antibodies against almost every target of interest. Nevertheless, it cannot be guaranteed that selected antibodies perform well and interact specifically enough with analytes unless an elaborate characterisation is performed. Here, we present an approach to shorten this process by combining the selection of suitable antibodies with the identification of informative target molecules by means of antibody microarrays, thereby reducing the effort of antibody characterisation by concentrating on relevant molecules. In a pilot scheme, a library of 456 single-chain variable fragment (scFv) binders to 134 antigens was used. They were arranged in a microarray format and incubated with the protein content of clinical tissue samples isolated from pancreatic ductal adenocarcinoma and healthy pancreas, as well as recurrent and non-recurrent bladder tumours. We observed significant variation in the expression of the E3 ubiquitin-protein ligase (CHFR) as well as the glutamate receptor interacting protein 2 (GRIP2), for example, always with more than one of the scFvs binding to these targets. Only the relevant antibodies were then characterised further on antigen microarrays and by surface plasmon resonance experiments so as to select the most specific and highest affinity antibodies. These binders were in turn used to confirm a microarray result by immunohistochemistry analysis. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  20. The SOLID (Signs Of LIfe Detector) instruments, antibody microarray based biosensors for in situ analysis: environmental immuno-profiles as biosignatures

    NASA Astrophysics Data System (ADS)

    Parro, Víctor

    Up to now most of the techniques used for organics or life detection in space missions are based on the detection of volatiles compounds by gas chromatography mass spectrometry (GC-MS). This was the case for the Viking's and Cassini/Huygens missions, or for the proposed SAM instrument for MSL. Even the Urey instrument, proposed for ESA's ExoMars mission, which focus on the analysis of the fluorescent-tagged volatiles by capillary electrophoresis. Sandwich antibody microarray immnunoassay is an excellent technique for the detection of complex and non volatile biological polymers (Parro et al., Space Sci. Rev, 2007. DOI 10.1007/s11214- 007-9276-1). A positive result in a sandwich immunoassay indicates that the sample contains a relatively complex molecular structure with at least two antigenic determinants, otherwise sandwich could not be detected. We have reported (Rivas et al., submitted) a shotgun approach for antibody production for biomarker detection in astrobiology and environmental monitoring, the production and testing of 155 new polyclonal antibodies against different bacteria and natural samples (water, sediments, soil, biofilms, etc) from Mars analog environments, as well as the construction and validation of a Life Detector Chip (LDCHIP200) with more than 200 antibodies for monitoring the presence of such bacteria or some of their remains. Some of the antibodies produced against iron-sulfur rich Rio Tinto environment (SW Spain) reacted against biological polymers from samples taken around the world (Antarctica, Yellowstone, 4 km depth mine in South Africa or Iceland). A redundancy in the number of antibodies against different target biomarkers apart of revealing the presence of certain biomolecules, it renders a sample-specific immuno-profile, an immnuno-fingerprint, which may constitute by itself an indirect biosignature. We will present a case study of immunoprofiling different iron-sulfur as well as phylosilicates rich samples along the Rio Tinto

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-04-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

  4. DNA microarray integromics analysis platform.

    PubMed

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

    2015-01-01

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

  5. Analysis of Clonal Type-Specific Antibody Reactions in Toxoplasma gondii Seropositive Humans from Germany by Peptide-Microarray

    PubMed Central

    Maksimov, Pavlo; Zerweck, Johannes; Maksimov, Aline; Hotop, Andrea; Groß, Uwe; Spekker, Katrin; Däubener, Walter; Werdermann, Sandra; Niederstrasser, Olaf; Petri, Eckhardt; Mertens, Marc; Ulrich, Rainer G.; Conraths, Franz J.; Schares, Gereon

    2012-01-01

    Background Different clonal types of Toxoplasma gondii are thought to be associated with distinct clinical manifestations of infections. Serotyping is a novel technique which may allow to determine the clonal type of T. gondii humans are infected with and to extend typing studies to larger populations which include infected but non-diseased individuals. Methodology A peptide-microarray test for T. gondii serotyping was established with 54 previously published synthetic peptides, which mimic clonal type-specific epitopes. The test was applied to human sera (n = 174) collected from individuals with an acute T. gondii infection (n = 21), a latent T. gondii infection (n = 53) and from T. gondii-seropositive forest workers (n = 100). Findings The majority (n = 124; 71%) of all T. gondii seropositive human sera showed reactions against synthetic peptides with sequences specific for clonal type II (type II peptides). Type I and type III peptides were recognized by 42% (n = 73) or 16% (n = 28) of the human sera, respectively, while type II–III, type I–III or type I–II peptides were recognized by 49% (n = 85), 36% (n = 62) or 14% (n = 25) of the sera, respectively. Highest reaction intensities were observed with synthetic peptides mimicking type II-specific epitopes. A proportion of the sera (n = 22; 13%) showed no reaction with type-specific peptides. Individuals with acute toxoplasmosis reacted with a statistically significantly higher number of peptides as compared to individuals with latent T. gondii infection or seropositive forest workers. Conclusions Type II-specific reactions were overrepresented and higher in intensity in the study population, which was in accord with genotyping studies on T. gondii oocysts previously conducted in the same area. There were also individuals with type I- or type III-specific reactions. Well-characterized reference sera and further specific peptide markers are needed to establish and

  6. Transfected Cell Microarrays for the Expression of Membrane-Displayed Single-Chain Antibodies

    DTIC Science & Technology

    2011-01-01

    Appli- cations of single-chain variable fragment antibodies in therapeutics and diagnostics. Biotechnology Adv 27, 502–520. 6. Denzin , L. K...4-20. J Biol Chem 266, 14095–14103. Transfected Cell Microarrays 137 7. Denzin , L. K., Gulliver, G. A., Voss, E. W., Jr. (1993) Mutational analysis of

  7. A 200-antibody microarray biochip for environmental monitoring: searching for universal microbial biomarkers through immunoprofiling.

    PubMed

    Rivas, Luis A; García-Villadangos, Miriam; Moreno-Paz, Mercedes; Cruz-Gil, Patricia; Gómez-Elvira, Javier; Parro, Víctor

    2008-11-01

    Environmental biomonitoring approaches require the measurement of either unequivocal biomarkers or specific biological profiles. Antibody microarrays constitute new tools for fast and reliable analysis of up to hundreds of biomarkers simultaneously. Herein we report 150 new polyclonal antibodies against microbial strains and environmental extracts, as well as the construction and validation of an antibody microarray (EMCHIP200, for "Environmental Monitoring Chip") containing 200 different antibodies. Each antibody was tested against its antigen for its specificity and cross-reactivity by a sandwich microarray immunoassay. The limit of detection was 0.2 ng mL (-1) for some proteins and 10 (4)-10 (5) cells mL (-1) for bacterial cells and spores. Partial biochemical characterization allowed identification of polymeric compounds (proteins and polysaccharides) as some of the targets recognized by the antibodies. We have successfully used the EMCHIP200 for the detection of biological polymers in samples from extreme environments around the world (e.g., a deep South African mine, Antarctica's dry valleys, Yellowstone National Park, Iceland, and Rio Tinto surface and subsurface). Clustering analysis permitted us to associate similar immunoprofiles or patterns to samples from apparently very different environments, indicating that they indeed share similar universal biomarkers. Our EMCHIP200 constitutes a new generation of immunosensors for biomarker detection and profiling, for either environmental, industrial, biotechnological, or astrobiological applications.

  8. Regeneration of recombinant antigen microarrays for the automated monitoring of antibodies against zoonotic pathogens in swine sera.

    PubMed

    Meyer, Verena K; Kober, Catharina; Niessner, Reinhard; Seidel, Michael

    2015-01-23

    The ability to regenerate immobilized proteins like recombinant antigens (rAgs) on surfaces is an unsolved problem for flow-based immunoassays on microarray analysis systems. The regeneration on microarray chip surfaces is achieved by changing the protein structures and desorption of antibodies. Afterwards, reactivation of immobilized protein antigens is necessary for reconstitution processes. Any backfolding should be managed in a way that antibodies are able to detect the protein antigens in the next measurement cycle. The regeneration of rAg microarrays was examined for the first time on the MCR3 flow-based chemiluminescence (CL) microarray analysis platform. The aim was to reuse rAg microarray chips in order to reduce the screening effort and costs. An antibody capturing format was used to detect antibodies against zoonotic pathogens in sera of slaughtered pigs. Different denaturation and reactivation buffers were tested. Acidic glycine-SDS buffer (pH 2.5) and 8 M guanidinium hydrochloride showed the best results in respect of denaturation efficiencies. The highest CL signals after regeneration were achieved with a carbonate buffer containing 10 mM DTT and 0.1% BSA for reactivation. Antibodies against Yersinia spp. and hepatitis E virus (HEV) were detected in swine sera on one immunochip over 4 days and 25 measurement cycles. Each cycle took 10 min for detection and regeneration. By using the rAg microarray chip, a fast and automated screening of antibodies against pathogens in sera of slaughtered pigs would be possible for zoonosis monitoring.

  9. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

    2005-09-01

    The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

  10. An Integrated Peptide-Antigen Microarray on Plasmonic Gold Films for Sensitive Human Antibody Profiling

    PubMed Central

    Price, Jordan V.; Tabakman, Scott M.; Li, Yanguang; Gong, Ming; Hong, Guosong; Feng, Ju; Utz, Paul J.; Dai, Hongjie

    2013-01-01

    High-throughput screening for interactions of peptides with a variety of antibody targets could greatly facilitate proteomic analysis for epitope mapping, enzyme profiling, drug discovery and biomarker identification. Peptide microarrays are suited for such undertaking because of their high-throughput capability. However, existing peptide microarrays lack the sensitivity needed for detecting low abundance proteins or low affinity peptide-protein interactions. This work presents a new peptide microarray platform constructed on nanostructured plasmonic gold substrates capable of metal enhanced NIR fluorescence enhancement (NIR-FE) by hundreds of folds for screening peptide-antibody interactions with ultrahigh sensitivity. Further, an integrated histone peptide and whole antigen array is developed on the same plasmonic gold chip for profiling human antibodies in the sera of systemic lupus erythematosus (SLE) patients, revealing that collectively a panel of biomarkers against unmodified and post-translationally modified histone peptides and several whole antigens allow more accurate differentiation of SLE patients from healthy individuals than profiling biomarkers against peptides or whole antigens alone. PMID:23923050

  11. Analysis of DNA microarray expression data.

    PubMed

    Simon, Richard

    2009-06-01

    DNA microarrays are powerful tools for studying biological mechanisms and for developing prognostic and predictive classifiers for identifying the patients who require treatment and are best candidates for specific treatments. Because microarrays produce so much data from each specimen, they offer great opportunities for discovery and great dangers or producing misleading claims. Microarray based studies require clear objectives for selecting cases and appropriate analysis methods. Effective analysis of microarray data, where the number of measured variables is orders of magnitude greater than the number of cases, requires specialized statistical methods which have recently been developed. Recent literature reviews indicate that serious problems of analysis exist a substantial proportion of publications. This manuscript attempts to provide a non-technical summary of the key principles of statistical design and analysis for studies that utilize microarray expression profiling.

  12. Mutational analysis using oligonucleotide microarrays

    PubMed Central

    Hacia, J.; Collins, F.

    1999-01-01

    The development of inexpensive high throughput methods to identify individual DNA sequence differences is important to the future growth of medical genetics. This has become increasingly apparent as epidemiologists, pathologists, and clinical geneticists focus more attention on the molecular basis of complex multifactorial diseases. Such undertakings will rely upon genetic maps based upon newly discovered, common, single nucleotide polymorphisms. Furthermore, candidate gene approaches used in identifying disease associated genes necessitate screening large sequence blocks for changes tracking with the disease state. Even after such genes are isolated, large scale mutational analyses will often be needed for risk assessment studies to define the likely medical consequences of carrying a mutated gene.
This review concentrates on the use of oligonucleotide arrays for hybridisation based comparative sequence analysis. Technological advances within the past decade have made it possible to apply this technology to many different aspects of medical genetics. These applications range from the detection and scoring of single nucleotide polymorphisms to mutational analysis of large genes. Although we discuss published scientific reports, unpublished work from the private sector12 could also significantly affect the future of this technology.


Keywords: mutational analysis; oligonucleotide microarrays; DNA chips PMID:10528850

  13. An antibody profile of systemic lupus erythematosus detected by antigen microarray

    PubMed Central

    Fattal, Ittai; Shental, Noam; Mevorach, Dror; Anaya, Juan-Manuel; Livneh, Avi; Langevitz, Pnina; Zandman-Goddard, Gisele; Pauzner, Rachel; Lerner, Miriam; Blank, Miri; Hincapie, Maria-Eugenia; Gafter, Uzi; Naparstek, Yaakov; Shoenfeld, Yehuda; Domany, Eytan; Cohen, Irun R

    2010-01-01

    Patients with systemic lupus erythematosus (SLE) produce antibodies to many different self-antigens. Here, we investigated antibodies in SLE sera using an antigen microarray containing many hundreds of antigens, mostly self-antigens. The aim was to detect sets of antibody reactivities characteristic of SLE patients in each of various clinical states – SLE patients with acute lupus nephritis, SLE patients in renal remission, and SLE patients who had never had renal involvement. The analysis produced two novel findings: (i) an SLE antibody profile persists independently of disease activity and despite long-term clinical remission, and (ii) this SLE antibody profile includes increases in four specific immunoglobulin G (IgG) reactivities to double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), Epstein–Barr virus (EBV) and hyaluronic acid; the profile also includes decreases in specific IgM reactivities to myeloperoxidase (MPO), CD99, collagen III, insulin-like growth factor binding protein 1 (IGFBP1) and cardiolipin. The reactivities together showed high sensitivity (> 93%) and high specificity for SLE (> 88%). A healthy control subject who had the SLE antibody profile was later found to develop clinical SLE. The present study did not detect antibody reactivities that differentiated among the various subgroups of SLE subjects with statistical significance. Thus, SLE is characterized by an enduring antibody profile irrespective of clinical state. The association of SLE with decreased IgM natural autoantibodies suggests that these autoantibodies might enhance resistance to SLE. PMID:20201986

  14. Blood cell capture on antibody microarrays and monitoring of the cell capture using surface plasmon resonance imaging.

    PubMed

    Roupioz, Yoann; Milgram, Sarah; Roget, André; Livache, Thierry

    2011-01-01

    Blood is a tremendous source of data for diagnostic purposes. Thanks to the qualitative and quantitative analysis of the different cell types carried into the blood stream. To that end, cell capture of several cell types at different locations on a microarray is an interesting alternative to classical techniques run 'in solution' as it allows simultaneous characterization of several cells on a single device. In this chapter, we have described a method based on the production of antibody microarrays specific to two different cell types: B and T lymphocytes. We have also described the real-time monitoring of the cell capture on the microarray using surface plasmon resonance imaging (SPRi).

  15. Optimizing scan parameters for antibody microarray experiments: accelerating robust systems diagnostics for life sciences.

    PubMed

    Gu, Qiang; Sivanandam, Thamil Mani

    2014-06-01

    Microarray experiments are a centerpiece of postgenomics life sciences and the current efforts to develop systems diagnostics for personalized medicine. The majority of antibody microarray experiments are fluorescence-based, which utilizes a scanner to convert target signals into image files for subsequent quantification. Certain scan parameters such as the laser power and photomultiplier tube gain (PMT) can influence the readout of fluorescent intensities and thus may affect data quantitation. To date, however, there is no consensus of how to determine the optimal settings of microarray scanners. Here we show that different settings of the laser power and PMT not only affect the signal intensities but also the accuracy of antibody microarray experiments. More importantly, we demonstrate an experimental approach using two fluorescent dyes to determine optimal settings of scan parameters for microarray experiments. These measures provide added quality control of microarray experiments, and thus help to improve the accuracy of quantitative outcome in microarray experiments in the above contexts.

  16. Regeneration of Recombinant Antigen Microarrays for the Automated Monitoring of Antibodies against Zoonotic Pathogens in Swine Sera

    PubMed Central

    Meyer, Verena K.; Kober, Catharina; Niessner, Reinhard; Seidel, Michael

    2015-01-01

    The ability to regenerate immobilized proteins like recombinant antigens (rAgs) on surfaces is an unsolved problem for flow-based immunoassays on microarray analysis systems. The regeneration on microarray chip surfaces is achieved by changing the protein structures and desorption of antibodies. Afterwards, reactivation of immobilized protein antigens is necessary for reconstitution processes. Any backfolding should be managed in a way that antibodies are able to detect the protein antigens in the next measurement cycle. The regeneration of rAg microarrays was examined for the first time on the MCR3 flow-based chemiluminescence (CL) microarray analysis platform. The aim was to reuse rAg microarray chips in order to reduce the screening effort and costs. An antibody capturing format was used to detect antibodies against zoonotic pathogens in sera of slaughtered pigs. Different denaturation and reactivation buffers were tested. Acidic glycine-SDS buffer (pH 2.5) and 8 M guanidinium hydrochloride showed the best results in respect of denaturation efficiencies. The highest CL signals after regeneration were achieved with a carbonate buffer containing 10 mM DTT and 0.1% BSA for reactivation. Antibodies against Yersinia spp. and hepatitis E virus (HEV) were detected in swine sera on one immunochip over 4 days and 25 measurement cycles. Each cycle took 10 min for detection and regeneration. By using the rAg microarray chip, a fast and automated screening of antibodies against pathogens in sera of slaughtered pigs would be possible for zoonosis monitoring. PMID:25625908

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

    PubMed Central

    Maurer, Michael; Molidor, Robert; Sturn, Alexander; Hartler, Juergen; Hackl, Hubert; Stocker, Gernot; Prokesch, Andreas; Scheideler, Marcel; Trajanoski, Zlatko

    2005-01-01

    Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System) provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS), a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at . PMID:15836795

  18. Profiling human serum antibodies with a carbohydrate antigen microarray

    PubMed Central

    Oyelaran, Oyindasola; McShane, Lisa M.; Dodd, Lori; Gildersleeve, Jeffrey C.

    2009-01-01

    Carbohydrate antigen arrays (glycan arrays) have been recently developed for the high-throughput analysis of carbohydrate macromolecule interactions. When profiling serum, information about experimental variability, inter-individual biological variability, and intra-individual temporal variability is critical. In this report, we describe the characterization of a carbohydrate antigen array and assay for profiling human serum. Through optimization of assay conditions and development of a normalization strategy, we obtain highly reproducible results with a within-experiment coefficient of variation (CV) of 10.8% and an overall CV (across multiple batches of slides and days) of 28.5%. We also report antibody profiles for 48 human subjects and evaluate for the first time the effects of age, race, sex, geographic location, and blood type on antibody profiles for a large set of carbohydrate antigens. We found significant dependence on age and blood type of antibody levels for a variety of carbohydrates. Finally, we conducted a longitudinal study with a separate group of 7 serum donors to evaluate the variation in anti-carbohydrate antibody levels within an individual over a period ranging from 3 to 13 weeks and found that, for nearly all antigens on our array, antibody levels are generally stable over this period. The results presented here provide the most comprehensive evaluation of experimental and biological variation reported to date for a glycan array and have significant implications for studies involving human serum profiling. PMID:19624168

  19. Lensfree holographic imaging of antibody microarrays for high-throughput detection of leukocyte numbers and function.

    PubMed

    Stybayeva, Gulnaz; Mudanyali, Onur; Seo, Sungkyu; Silangcruz, Jaime; Macal, Monica; Ramanculov, Erlan; Dandekar, Satya; Erlinger, Anthony; Ozcan, Aydogan; Revzin, Alexander

    2010-05-01

    Characterization of leukocytes is an integral part of blood analysis and blood-based diagnostics. In the present paper, we combine lensless holographic imaging with antibody microarrays for rapid and multiparametric analysis of leukocytes from human blood. Monoclonal antibodies (Abs) specific for leukocyte surface antigens (CD4 and CD8) and cytokines (TNF-alpha, IFN-gamma, IL-2) were printed in an array so as to juxtapose cell capture and cytokine detection antibody (Ab) spots. Integration of Ab microarrays into a microfluidic flow chamber (4 muL volume) followed by incubation with human blood resulted in capture of CD4 and CD8 T-cells on specific Ab spots. On-chip mitogenic activation of these cells induced release of cytokine molecules that were subsequently captured on neighboring anticytokine Ab spots. The binding of IL-2, TNF-alpha, and IFN-gamma molecules on their respective Ab spots was detected using horseradish peroxidase (HRP)-labeled anticytokine Abs and a visible color reagent. Lensfree holographic imaging was then used to rapidly ( approximately 4 s) enumerate CD4 and CD8 T-lymphocytes captured on Ab spots and to quantify the cytokine signal emanating from IL-2, TNF-alpha, and IFN-gamma spots on the same chip. To demonstrate the utility of our approach for infectious disease monitoring, blood samples of healthy volunteers and human immunodeficiency virus (HIV)-infected patients were analyzed to determine the CD4/CD8 ratio, an important HIV/AIDS diagnostic marker. The ratio obtained by lensfree on-chip imaging of CD4 and CD8 T-cells captured on Ab spots was in close agreement with conventional microscopy-based cell counting. The present paper, describing tandem use of Ab microarrays and lensfree holographic imaging, paves the way for future development of miniature cytometry devices for multiparametric blood analysis at the point of care or in a resource-limited setting.

  20. Metric learning for DNA microarray data analysis

    NASA Astrophysics Data System (ADS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-12-01

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

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

    PubMed

    Ramirez, Lisa S; Wang, Jun

    2016-01-06

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

  2. Microarray analysis in pulmonary hypertension.

    PubMed

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

    2016-07-01

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

  3. Microarray analysis in pulmonary hypertension

    PubMed Central

    Hoffmann, Julia; Wilhelm, Jochen; Olschewski, Andrea

    2016-01-01

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

  4. The Impact of Photobleaching on Microarray Analysis

    PubMed Central

    von der Haar, Marcel; Preuß, John-Alexander; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank

    2015-01-01

    DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results. PMID:26378589

  5. Microarray Data Analysis and Mining Tools

    PubMed Central

    Selvaraj, Saravanakumar; Natarajan, Jeyakumar

    2011-01-01

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

  6. Microarray data analysis and mining tools.

    PubMed

    Selvaraj, Saravanakumar; Natarajan, Jeyakumar

    2011-04-22

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

  7. Systematic analysis of the IgG antibody immune response against varicella zoster virus (VZV) using a self-assembled protein microarray.

    PubMed

    Ceroni, Alessandro; Sibani, Sahar; Baiker, Armin; Pothineni, Venkata Raveendra; Bailer, Susanne M; LaBaer, Joshua; Haas, Jürgen; Campbell, Colin J

    2010-09-01

    Varicella zoster virus (VZV) is a human herpesvirus encoding at least 69 distinct viral proteins which causes chickenpox after primary infection and shingles during reactivation and which is particularly important in pregnancy and immunocompromised patients. Current serodiagnostic tests are either based on whole cell lysates or glycoprotein preparations. In order to investigate the humoral immune response to VZV infection or vaccination in more detail, and to improve the currently available diagnostic assays, we developed a nucleic acid programmable protein array (NAPPA) containing all 69 VZV proteins and performed a detailed analysis of 68 sera from individuals with either no, a previous or an acute VZV infection. In addition to the known reactive glycoprotein antigens (ORF 5, ORF 14, ORF 31, ORF 37, ORF 68), we discovered IgG antibodies against a variety of other membrane (ORF 2, ORF 24), capsid (ORF 20, ORF 23, ORF 43) and tegument (ORF 53, ORF 9, ORF 11) proteins, as well as other proteins involved in virus replication and assembly (ORF 25, ORF 26, ORF 28) and the transactivator proteins ORF 12, ORF 62 and ORF 63. All of these antigens were only reactive in a subset of VZV-positive individuals. A subset of the newly identified VZV antigens was validated by western blot analysis. Using these seroreactive new VZV antigens, more sensitive assays and tests distinguishing between different clinical entities may be developed.

  8. Lensfree Holographic Imaging of Antibody Microarrays for High-Throughput Detection of Leukocyte Numbers and Function

    PubMed Central

    Stybayeva, Gulnaz; Mudanyali, Onur; Seo, Sungkyu; Silangcruz, Jaime; Macal, Monica; Ramanculov, Erlan; Dandekar, Satya; Erlinger, Anthony; Ozcan, Aydogan; Revzin, Alexander

    2010-01-01

    Characterization of leukocytes is an integral part of blood analysis and blood-based diagnostics. In the present paper we combine lensless holographic imaging with antibody microarrays for rapid and multiparametric analysis of leukocytes from human blood. Monoclonal antibodies (Abs) specific for leukocyte surface antigens (CD4 and CD8) and cytokines (TNF-α, IFN-γ, IL-2) were printed in an array so as to juxtapose cell capture and cytokine detection Ab spots. Integration of Ab microarrays into a microfluidic flow chamber (4 μl volume) followed by incubation with human blood resulted in capture of CD4 and CD8 T-cells on specific Ab spots. On-chip mitogenic activation of these cells induced release of cytokine molecules that were subsequently captured on neighboring anti-cytokine Ab spots. The binding of IL-2, TNF-α and IFN-γ molecules on their respective Ab spots was detected using HRP-labeled anti-cytokine Abs and a visible color reagent. Lensfree holographic imaging was then used to rapidly (∼4 sec) enumerate CD4 and CD8 T-lymphocytes captured on Ab spots and to quantify the cytokine signal emanating from IL-2, TNF-α, and IFN-γ spots on the same chip. To demonstrate the utility of our approach for infectious disease monitoring, blood samples of healthy volunteers and human immunodeficiency virus (HIV)-infected patients were analyzed to determine CD4/CD8 ratio – an important HIV/AIDS diagnostic marker. The ratio obtained by lensfree on-chip imaging of CD4 and CD8 T-cells captured on Ab spots was in close agreement with conventional microscopy-based cell counting. The present paper, describing tandem use of Ab microarrays and lensfree holographic imaging, paves the way for future development of miniature cytometry devices for multiparametric blood analysis at the point of care or in a resource-limited setting. PMID:20359168

  9. Interfacing antibody-based microarrays and digital holography enables label-free detection for loss of cell volume

    PubMed Central

    El-Schich, Zahra; Nilsson, Emmy; Gerdtsson, Anna S; Wingren, Christer; Wingren, Anette Gjörloff

    2015-01-01

    Background: We introduce the combination of digital holographic microscopy (DHM) and antibody microarrays as a powerful tool to measure morphological changes in specifically antibody-captured cells. The aim of the study was to develop DHM for analysis of cell death of etoposide-treated suspension cells. Results/methodology: We demonstrate that the cell number, mean area, thickness and volume were noninvasively measured by using DHM. The cell number was stable over time, but the two cell lines showed changes of cell area and cell irregularity after treatment. The cell volume in etoposide-treated cells was decreased, whereas untreated cells showed stable volume. Conclusion: Our results provide proof of concept for using DHM combined with antibody-based microarray technology for detecting morphological changes in captured cells. PMID:28031876

  10. Development and application of antibody microarray for lymphocystis disease virus detection in fish.

    PubMed

    Sheng, Xiuzhen; Xu, Xiaoli; Zhan, Wenbin

    2013-05-01

    Lymphocystis disease virus (LCDV) is the causative agent of lymphocystis disease affecting marine and freshwater fish worldwide. Here an antibody microarray was developed and employed to detect LCDV in fish. Rabbit anti-LCDV serum was arrayed on agarose gel-modified slides as capture antibody, and Cy3-conjugated anti-LCDV monoclonal antibody (MAbs) was added as detection antibody. The signals were imaged with a laser chip scanner and analyzed by corresponding software. To improve the sensitivity, different substrate binders (poly-L-lysine, MPTS, aldehyde, APES and agarose gel modified slides, and commercially available amino-modified slides), markers (fluorescein isothiocyanate, Cy3, horseradish peroxidase, biotin or colloidal gold) conjugated to anti-LCDV Mabs, and storage time of the antibody were assessed. The results showed that the antibody microarrays based on agarose gel-modified slides gave a lower detection limit of 0.55μg/ml of LCDV when Cy3 and HRP conjugated anti-LCDV MAbs were used as detection antibody; and the lowest detectable LCDV protein concentration was 0.0686 μg/ml when streptavidin-biotin conjugated to anti-LCDV MAbs served as detection antibody. The developed antibody microarray proved to have a high specificity for LCDV detection and a shelf-life of more than 8 months at -20°C. Furthermore, the LCDV detection results of the microarray in fish gills or fins (n=50) presented a concordance rate of 100% with enzyme-linked immunosorbent assay (ELISA) and 98% with immunofluorescence assay technique (IFAT). These results revealed that the developed antibody microarray could serve as an effective tool for diagnostic and epidemiological studies of LCDV in fish. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Dual-color Proteomic Profiling of Complex Samples with a Microarray of 810 Cancer-related Antibodies*

    PubMed Central

    Schröder, Christoph; Jacob, Anette; Tonack, Sarah; Radon, Tomasz P.; Sill, Martin; Zucknick, Manuela; Rüffer, Sven; Costello, Eithne; Neoptolemos, John P.; Crnogorac-Jurcevic, Tatjana; Bauer, Andrea; Fellenberg, Kurt; Hoheisel, Jörg D.

    2010-01-01

    Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses. PMID:20164060

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

    PubMed Central

    Stieber, Bettina; Monecke, Stefan; Müller, Elke; Büchler, Joseph; Ehricht, Ralf

    2015-01-01

    Background S. aureus is a pathogen in humans and animals that harbors a wide variety of virulence factors and resistance genes. This bacterium can cause a wide range of mild to life-threatening diseases. In the latter case, fast diagnostic procedures are important. In routine diagnostic laboratories, several genotypic and phenotypic methods are available to identify S. aureus strains and determine their resistances. However, there is a demand for multiplex routine diagnostic tests to directly detect staphylococcal toxins and proteins. Methods In this study, an antibody microarray based assay was established and validated for the rapid detection of staphylococcal markers and exotoxins. The following targets were included: staphylococcal protein A, penicillin binding protein 2a, alpha- and beta-hemolysins, Panton Valentine leukocidin, toxic shock syndrome toxin, enterotoxins A and B as well as staphylokinase. All were detected simultaneously within a single experiment, starting from a clonal culture on standard media. The detection of bound proteins was performed using a new fluorescence reading device for microarrays. Results 110 reference strains and clinical isolates were analyzed using this assay, with a DNA microarray for genotypic characterization performed in parallel. The results showed a general high concordance of genotypic and phenotypic data. However, genotypic analysis found the hla gene present in all S. aureus isolates but its expression under given conditions depended on the clonal complex affiliation of the actual isolate. Conclusions The multiplex antibody assay described herein allowed a rapid and reliable detection of clinically relevant staphylococcal toxins as well as resistance- and species-specific markers. PMID:26624622

  13. Microarray analysis of erythromycin resistance determinants.

    PubMed

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

    2003-01-01

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

  14. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

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

  15. MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

    EPA Science Inventory

    Microarray Data Analysis Using Multiple Statistical Models

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

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

    PubMed

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

    2016-06-08

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2013-06-01

    We aim to develop a protein microarray platform capable of presenting both natural and denatured forms of proteins for antibody biomarker discovery. We will further optimize plasma screening protocols to improve detection. We developed a new covalent capture protein microarray chemistry using HaloTag fusion proteins and ligand. To enhance protein yield, we used HeLa cell lysate as an in vitro transcription translation (IVTT) system. Escherichia coli lysates were added to the plasma blocking buffer to reduce nonspecific background. These protein microarrays were probed with plasma samples and autoantibody responses were quantified and compared with or without denaturing buffer treatment. We demonstrated that protein microarrays using the covalent attachment chemistry endured denaturing conditions. Blocking with E. coli lysates greatly reduced the background signals and expression with IVTT based on HeLa cell lysates significantly improved the antibody signals on protein microarrays probed with plasma samples. Plasma samples probed on denatured protein arrays produced autoantibody profiles distinct from those probed on natively displayed proteins. This versatile protein microarray platform allows the display of both natural and denatured proteins, offers a new dimension to search for disease-specific antibodies, broadens the repertoire of potential biomarkers, and will potentially yield clinical diagnostics with greater performance. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

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

  20. Microarrays

    ERIC Educational Resources Information Center

    Plomin, Robert; Schalkwyk, Leonard C.

    2007-01-01

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

  1. Analysis of High-Throughput ELISA Microarray Data

    SciTech Connect

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

    2011-02-23

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

  2. Technical Advances of the Recombinant Antibody Microarray Technology Platform for Clinical Immunoproteomics.

    PubMed

    Delfani, Payam; Dexlin Mellby, Linda; Nordström, Malin; Holmér, Andreas; Ohlsson, Mattias; Borrebaeck, Carl A K; Wingren, Christer

    2016-01-01

    In the quest for deciphering disease-associated biomarkers, high-performing tools for multiplexed protein expression profiling of crude clinical samples will be crucial. Affinity proteomics, mainly represented by antibody-based microarrays, have during recent years been established as a proteomic tool providing unique opportunities for parallelized protein expression profiling. But despite the progress, several main technical features and assay procedures remains to be (fully) resolved. Among these issues, the handling of protein microarray data, i.e. the biostatistics parts, is one of the key features to solve. In this study, we have therefore further optimized, validated, and standardized our in-house designed recombinant antibody microarray technology platform. To this end, we addressed the main remaining technical issues (e.g. antibody quality, array production, sample labelling, and selected assay conditions) and most importantly key biostatistics subjects (e.g. array data pre-processing and biomarker panel condensation). This represents one of the first antibody array studies in which these key biostatistics subjects have been studied in detail. Here, we thus present the next generation of the recombinant antibody microarray technology platform designed for clinical immunoproteomics.

  3. Technical Advances of the Recombinant Antibody Microarray Technology Platform for Clinical Immunoproteomics

    PubMed Central

    Delfani, Payam; Dexlin Mellby, Linda; Nordström, Malin; Holmér, Andreas; Ohlsson, Mattias; Borrebaeck, Carl A. K.; Wingren, Christer

    2016-01-01

    In the quest for deciphering disease-associated biomarkers, high-performing tools for multiplexed protein expression profiling of crude clinical samples will be crucial. Affinity proteomics, mainly represented by antibody-based microarrays, have during recent years been established as a proteomic tool providing unique opportunities for parallelized protein expression profiling. But despite the progress, several main technical features and assay procedures remains to be (fully) resolved. Among these issues, the handling of protein microarray data, i.e. the biostatistics parts, is one of the key features to solve. In this study, we have therefore further optimized, validated, and standardized our in-house designed recombinant antibody microarray technology platform. To this end, we addressed the main remaining technical issues (e.g. antibody quality, array production, sample labelling, and selected assay conditions) and most importantly key biostatistics subjects (e.g. array data pre-processing and biomarker panel condensation). This represents one of the first antibody array studies in which these key biostatistics subjects have been studied in detail. Here, we thus present the next generation of the recombinant antibody microarray technology platform designed for clinical immunoproteomics. PMID:27414037

  4. Bioinformatics/biostatistics: microarray analysis.

    PubMed

    Eichler, Gabriel S

    2012-01-01

    The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

  5. Integrated analysis of microarray data and gene function information.

    PubMed

    Cui, Yan; Zhou, Mi; Wong, Wing Hung

    2004-01-01

    Microarray data should be interpreted in the context of existing biological knowledge. Here we present integrated analysis of microarray data and gene function classification data using homogeneity analysis. Homogeneity analysis is a graphical multivariate statistical method for analyzing categorical data. It converts categorical data into graphical display. By simultaneously quantifying the microarray-derived gene groups and gene function categories, it captures the complex relations between biological information derived from microarray data and the existing knowledge about the gene function. Thus, homogeneity analysis provides a mathematical framework for integrating the analysis of microarray data and the existing biological knowledge.

  6. Integrated microfluidic biochips for DNA microarray analysis.

    PubMed

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

    2006-03-01

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

  7. Seeing better through a MIST: evaluation of monoclonal recombinant antibody fragments on microarrays.

    PubMed

    Angenendt, Philipp; Wilde, Jeannine; Kijanka, Gregor; Baars, Sabine; Cahill, Dolores J; Kreutzberger, Jürgen; Lehrach, Hans; Konthur, Zoltán; Glökler, Jörn

    2004-05-15

    Automation is the key approach for genomewide and proteomewide screening of function and interaction. Especially for proteomics, antibody microarrays are a useful tool for massive parallel profiling of complex samples. To meet the requirements of antibody microarrays and to obtain a great variety of antibodies, new technologies such as phage display have partly replaced the classical hybridoma method. While the selection process for phage-displayed antibody fragments itself has been automated, the bottleneck was shifted further downstream to the identification of monoclonal binders obtained from the selections. Here, we present a new approach to reduce time, material, and waste to extend automation beyond the selection process by application of conventional microarray machinery. We were able to express recombinant antibody fragments in a single inoculation and expression step and subjected them without purification directly to an automated high-throughput screening procedure based on the multiple spotting technique (MIST). While obtaining comparable sensitivities to enzyme-linked immunosorbent assays, we minimized manual interaction steps and streamlined the technique to be accessible within the automated selection procedure.

  8. Digital microarray analysis for digital artifact genomics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger; Handley, James; Williams, Deborah

    2013-06-01

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

  9. The SOLID (Signs Of LIfe Detector) instrument concept: an antibody microarray-based biosensor for life detection in astrobiology

    NASA Astrophysics Data System (ADS)

    Parro, V.; Rivas, L. A.; Rodríguez-Manfredi, J. A.; Blanco, Y.; de Diego-Castilla, G.; Cruz-Gil, P.; Moreno-Paz, M.; García-Villadangos, M.; Compostizo, C.; Herrero, P. L.

    2009-04-01

    Immunosensors have been extensively used since many years for environmental monitoring. Different technological platforms allow new biosensor designs and implementations. We have reported (Rivas et al., 2008) a shotgun approach for antibody production for biomarker detection in astrobiology and environmental monitoring, the production of 150 new polyclonal antibodies against microbial strains and environmental extracts, and the construction and validation of an antibody microarray (LDCHIP200, for "Life Detector Chip") containing 200 different antibodies. We have successfully used the LDCHIP200 for the detection of biological polymers in extreme environments in different parts of the world (e.g., a deep South African mine, Antarctica's Dry valleys, Yellowstone, Iceland, and Rio Tinto). Clustering analysis associated similar immunopatterns to samples from apparently very different environments, indicating that they indeed share similar universal biomarkers. A redundancy in the number of antibodies against different target biomarkers apart of revealing the presence of certain biomolecules, it renders a sample-specific immuno-profile, an "immnuno-fingerprint", which may constitute by itself an indirect biosignature. We will present a case study of immunoprofiling different iron-sulfur as well as phylosilicates rich samples along the Rio Tinto river banks. Based on protein microarray technology, we designed and built the concept instrument called SOLID (for "Signs Of LIfe Detector"; Parro et al., 2005; 2008a, b; http://cab.inta.es/solid) for automatic in situ analysis of soil samples and molecular biomarkers detection. A field prototype, SOLID2, was successfully tested for the analysis of grinded core samples during the 2005 "MARTE" campaign of a Mars drilling simulation experiment by a sandwich microarray immunoassay (Parro et al., 2008b). We will show the new version of the instrument (SOLID3) which is able to perform both sandwich and competitive immunoassays. SOLID3

  10. Cluster of differentiation antibody microarrays on plasma immersion ion implanted polycarbonate.

    PubMed

    Kosobrodova, E; Mohamed, A; Su, Y; Kondyurin, A; dos Remedios, C G; McKenzie, D R; Bilek, M M M

    2014-02-01

    Plasma immersion ion implantation (PIII) modifies the surface properties of polymers, enabling them to covalently immobilize proteins without using linker chemistry. We describe the use of PIII treated polycarbonate (PC) slides as a novel platform for producing microarrays of cluster of differentiation (CD) antibodies. We compare their performance to identical antibody microarrays printed on nitrocellulose-coated glass slides that are currently the industry standard. Populations of leukocytes are applied to the CD microarrays and unbound cells are removed revealing patterns of differentially immobilized cells that are detected in a simple label-free approach by scanning the slides with visible light. Intra-slide and inter-slide reproducibility, densities of bound cells, and limits of detection were determined. Compared to the nitrocellulose-coated glass slides, PIII treated PC slides have a lower background noise, better sensitivity, and comparable or better reproducibility. They require three-fold lower antibody concentrations to yield equivalent signal strength, resulting in significant reductions in production cost. The improved transparency of PIII treated PC in the near-UV and visible wavelengths combined with superior immobilization of biomolecules makes them an attractive platform for a wide range of microarray applications.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-07-27

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

  13. Monoclonal antibody selection for interleukin-4 quantification using suspension arrays and forward-phase protein microarrays.

    PubMed

    Wang, L; Cole, K D; Peterson, A; He, Hua-Jun; Gaigalas, A K; Zong, Y

    2007-12-01

    A recombinant mouse interleukin-4 (IL-4) and three different purified rat antimouse IL-4 monoclonal antibodies (Mab) with different clonalities were employed as a model system. This system was used to examine monoclonal antibody effectiveness using both conventional and high-throughput measurement techniques to select antibodies for attaining the most sensitive detection of the recombinant IL-4 through the "sandwich-type" immunoassays. Surface plasmon resonance (SPR) measurements and two high-throughput methods, suspension arrays (also called multiplexed bead arrays) and forward-phase protein microarrays, predicted the same capture (BVD4-1D11) and detection (BVD6-24G2) antibody pair for the most sensitive detection of the recombinant cytokine. By using this antibody pair, we were able to detect as low as 2 pg/mL of IL-4 in buffer solution and 13.5 pg/mL of IL-4 spiked in 100% normal mouse serum with the multiplexed bead arrays. Due to the large amount of material required for SPR measurements, the study suggests that the multiplexed bead arrays and protein microarrays are both suited for the selection of numerous antibodies against the same analyte of interest to meet the need in the areas of systems biology and reproducible clinical diagnostics for better patient care.

  14. Meta-analysis of incomplete microarray studies.

    PubMed

    Zollinger, Alix; Davison, Anthony C; Goldstein, Darlene R

    2015-10-01

    Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information-providing only a ranked list of genes, for example-it is common to reduce all studies to ranked lists prior to combining them. Since this entails a loss of information, we consider a hierarchical Bayes approach to meta-analysis using different types of information from different studies: the full data matrix, summary statistics, or ranks. The model uses an informative prior for the parameter of interest to aid the detection of differentially expressed genes. Simulations show that the new approach can give substantial power gains compared with classical meta-analysis and list aggregation methods. A meta-analysis of 11 published studies with different data types identifies genes known to be involved in ovarian cancer and shows significant enrichment.

  15. An application of protein microarray in the screening of monoclonal antibodies against the oyster mushroom spherical virus.

    PubMed

    Kim, Sang-Woo; Kim, Min-Gon; Jung, Hyo-Am; Lee, Kyung-Hee; Lee, Hyun-Sook; Ro, Hyeon-Su

    2008-03-15

    The oyster mushroom spherical virus (OMSV) is a causative agent of dieback disease in the oyster mushroom, Pleurotus ostreatus. Outbreaks of this virus occasionally result in serious disease that is associated with hefty economic losses. Thus, the detection and removal of OMSV-infected spawn is considered to be a crucial step for the stable production of P. ostreatus. For the detection of OMSV, we attempted to generate monoclonal antibodies (mAbs) against an RNA polymerase domain (RPD) of an OMSV protein. In an effort to simplify the laborious multistep mAb screening process, we developed a protein microarray on a slide glass that is chemically modified with the RPD protein. The culture supernatants of 87 hybridoma cells, which were prepared from the fusion of RPD-immunized mouse spleen cells with myeloma cells, were spotted onto the RPD-coated microarray. The binding of mAb to RPD was detected via Alexa 488 dye-labeled anti-mouse immunoglobulin G (IgG) as a secondary antibody. Of 87 samples, 13 evidenced a significant level of fluorescence signal intensity. Subsequent immunoblot analysis revealed that the specificity of each mAb against RPD coincided with the corresponding fluorescence signal intensity, thereby indicating the effectiveness of the protein microarray in mAb screening.

  16. Software and tools for microarray data analysis.

    PubMed

    Mehta, Jai Prakash; Rani, Sweta

    2011-01-01

    A typical microarray experiment results in series of images, depending on the experimental design and number of samples. Software analyses the images to obtain the intensity at each spot and quantify the expression for each transcript. This is followed by normalization, and then various data analysis techniques are applied on the data. The whole analysis pipeline requires a large number of software to accurately handle the massive amount of data. Fortunately, there are large number of freely available and commercial software to churn the massive amount of data to manageable sets of differentially expressed genes, functions, and pathways. This chapter describes the software and tools which can be used to analyze the gene expression data right from the image analysis to gene list, ontology, and pathways.

  17. Evaluating mixtures of 14 hygroscopic additives to improve antibody microarray performance.

    PubMed

    Bergeron, Sébastien; Laforte, Veronique; Lo, Pik-Shan; Li, Huiyan; Juncker, David

    2015-11-01

    Microarrays allow the miniaturization and multiplexing of biological assays while only requiring minute amounts of samples. As a consequence of the small volumes used for spotting and the assays, evaporation often deteriorates the quality, reproducibility of spots, and the overall assay performance. Glycerol is commonly added to antibody microarray printing buffers to decrease evaporation; however, it often decreases the binding of antibodies to the surface, thereby negatively affecting assay sensitivity. Here, combinations of 14 hygroscopic chemicals were used as additives to printing buffers for contact-printed antibody microarrays on four different surface chemistries. The ability of the additives to suppress evaporation was quantified by measuring the residual buffer volume in open quill pins over time. The seven best additives were then printed either individually or as a 1:1 mixture of two additives, and the homogeneity, intensity, and reproducibility of both the spotted protein and of a fluorescently labeled analyte in an assay were quantified. Among the 28 combinations on the four slides, many were found to outperform glycerol, and the best additive mixtures were further evaluated by changing the ratio of the two additives. We observed that the optimal additive mixture was dependent on the slide chemistry, and that it was possible to increase the binding of antibodies to the surface threefold compared to 50 % glycerol, while decreasing whole-slide coefficient of variation to 5.9 %. For the two best slides, improvements were made for both the limit of detection (1.6× and 5.9×, respectively) and the quantification range (1.2× and 2.1×, respectively). The additive mixtures identified here thus help improve assay reproducibility and performance, and might be beneficial to all types of microarrays that suffer from evaporation of the printing buffers.

  18. Surface Antigen Profiling of Helicobacter pylori-Infected and -Uninfected Gastric Cancer Cells Using Antibody Microarray.

    PubMed

    Sukri, Asif; Hanafiah, Alfizah; Kosai, Nik Ritza; Mohamed Taher, Mustafa; Mohamed Rose, Isa

    2016-10-01

    Comprehensive immunophenotyping cluster of differentiation (CD) antigens in gastric adenocarcinoma, specifically between Helicobacter pylori-infected and -uninfected gastric cancer patients by using DotScan(™) antibody microarray has not been conducted. Current immunophenotyping techniques include flow cytometry and immunohistochemistry are limited to the use of few antibodies for parallel examination. We used DotScan(™) antibody microarray consisting 144 CD antibodies to determine the distribution of CD antigens in gastric adenocarcinoma cells and to elucidate the effect of H. pylori infection toward CD antigen expression in gastric cancer. Mixed leukocytes population derived from gastric adenocarcinoma patients were immunophenotyped using DotScan(™) antibody microarray. AGS cells were infected with H. pylori strains and cells were captured on DotScan(™) slides. Cluster of differentiation antigens involved in perpetuating the tolerance of immune cells to tumor cells was upregulated in gastric adenocarcinoma cells compared to normal cells. CD279 which is essential in T cells apoptosis was found to be upregulated in normal cells. Remarkably, H. pylori-infected gastric cancer patients exhibited upregulated expression of CD27 that important in maintenance of T cells. Infection of cagA+ H. pylori with AGS cells increased CD antigens expression which involved in cancer stem cell while cagA- H. pylori polarized AGS cells to express immune-regulatory CD antigens. Increased CD antigens expression in AGS cells infected with cagA+ H. pylori were also detected in H. pylori-infected gastric cancer patients. This study suggests the tolerance of immune system toward tumor cells in gastric cancer and distinct mechanisms of immune responses exploited by different H. pylori strains. © 2016 John Wiley & Sons Ltd.

  19. Protein microarrays for highly parallel detection and quantitation of specific proteins and antibodies in complex solutions

    PubMed Central

    Haab, Brian B; Dunham, Maitreya J; Brown, Patrick O

    2001-01-01

    Background: We have developed and tested a method for printing protein microarrays and using these microarrays in a comparative fluorescence assay to measure the abundance of many specific proteins in complex solutions. A robotic device was used to print hundreds of specific antibody or antigen solutions in an array on the surface of derivatized microscope slides. Two complex protein samples, one serving as a standard for comparative quantitation, the other representing an experimental sample in which the protein quantities were to be measured, were labeled by covalent attachment of spectrally resolvable fluorescent dyes. Results: Specific antibody-antigen interactions localized specific components of the complex mixtures to defined cognate spots in the array, where the relative intensity of the fluorescent signal representing the experimental sample and the reference standard provided a measure of each protein's abundance in the experimental sample. To test the specificity, sensitivity and accuracy of this assay, we analyzed the performance of 115 antibody/antigen pairs. 50% of the arrayed antigens and 20% of the arrayed antibodies provided specific and accurate measurements of their cognate ligands at or below concentrations of 0.34 μg/ml and 1.6 μg/ml, respectively. Some of the antibody/antigen pairs allowed detection of the cognate ligands at absolute concentrations below 1 ng/ml, and partial concentrations of 1 part in 106, sensitivities sufficient for measurement of many clinically important proteins in patient blood samples. Conclusions: These results suggest that protein microarrays can provide a practical means to characterize patterns of variation in hundreds of thousands of different proteins in clinical or research applications. PMID:11182887

  20. Performance of a multiplexed serological microarray for the detection of antibodies against central nervous system pathogens.

    PubMed

    Jääskeläinen, Anne J; Viitala, Sari M; Kurkela, Satu; Hepojoki, Satu; Sillanpää, Heidi; Kallio-Kokko, Hannimari; Bergström, Tomas; Suni, Jukka; Närvänen, Ale; Vapalahti, Olli; Vaheri, Antti

    2014-05-01

    Central nervous system (CNS) infections have multiple potential causative agents for which simultaneous pathogen screening can provide a useful tool. This study evaluated a multiplexed microarray for the simultaneous detection of antibodies against CNS pathogens. The performance of selected microarray antigens for the detection of IgG antibodies against herpes simplex virus 1 and 2 (HSV-1 and HSV-2), varicella-zoster virus (VZV), adenovirus, Mycoplasma pneumoniae and Borrelia burgdorferi sensu lato, was evaluated using serum sample panels tested with reference assays used in a routine diagnostic laboratory. The microarray sensitivity for HSV-1, HSV-2, VZV, adenovirus and M. pneumonia ranged from 77% to 100%, and the specificity ranged from 74% to 97%. Very variable sensitivities and specificities were found for borrelial antigens of three different VlsE protein IR(6) peptide variants (IR6p1, IR6p2, IR6p4) and three recombinant decorin binding proteins A (DbpA; DbpAIa, DbpA91, DbpAG40). For single antigens, good specificity was shown for antigens of IR6p4 and DbpAIa (96%), while DbpA91, IR6p1 and IR6p2 were moderately specific (88-92%). The analytical sensitivity of the microarray was dependent on the borrelial IgG concentration of the specimen. The overall performance and technical features of the platform showed that the platform supports both recombinant proteins, whole viruses and peptides as antigens. This study showed diagnostic potential for all six CNS pathogens, including Borrelia burgdorferi sensu lato, using glutaraldehyde based microarray, and further highlighted the importance of careful antigen selection and the requirement for the use of multiple borrelial antigens in order to increase specificity without a major lack of sensitivity. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. Genome-Scale Protein Microarray Comparison of Human Antibody Responses in Plasmodium vivax Relapse and Reinfection

    PubMed Central

    Chuquiyauri, Raul; Molina, Douglas M.; Moss, Eli L.; Wang, Ruobing; Gardner, Malcolm J.; Brouwer, Kimberly C.; Torres, Sonia; Gilman, Robert H.; Llanos-Cuentas, Alejandro; Neafsey, Daniel E.; Felgner, Philip; Liang, Xiaowu; Vinetz, Joseph M.

    2015-01-01

    Large scale antibody responses in Plasmodium vivax malaria remains unexplored in the endemic setting. Protein microarray analysis of asexual-stage P. vivax was used to identify antigens recognized in sera from residents of hypoendemic Peruvian Amazon. Over 24 months, of 106 participants, 91 had two symptomatic P. vivax malaria episodes, 11 had three episodes, 3 had four episodes, and 1 had five episodes. Plasmodium vivax relapse was distinguished from reinfection by a merozoite surface protein-3α restriction fragment length polymorphism polymerase chain reaction (MSP3α PCR-RFLP) assay. Notably, P. vivax reinfection subjects did not have higher reactivity to the entire set of recognized P. vivax blood-stage antigens than relapse subjects, regardless of the number of malaria episodes. The most highly recognized P. vivax proteins were MSP 4, 7, 8, and 10 (PVX_003775, PVX_082650, PVX_097625, and PVX_114145); sexual-stage antigen s16 (PVX_000930); early transcribed membrane protein (PVX_090230); tryptophan-rich antigen (Pv-fam-a) (PVX_092995); apical merozoite antigen 1 (PVX_092275); and proteins of unknown function (PVX_081830, PVX_117680, PVX_118705, PVX_121935, PVX_097730, PVX_110935, PVX_115450, and PVX_082475). Genes encoding reactive proteins exhibited a significant enrichment of non-synonymous nucleotide variation, an observation suggesting immune selection. These data identify candidates for seroepidemiological tools to support malaria elimination efforts in P. vivax-endemic regions. PMID:26149860

  2. Protein Profiling Gastric Cancer and Neighboring Control Tissues Using High-Content Antibody Microarrays

    PubMed Central

    Sill, Martin; Schröder, Christoph; Shen, Ying; Marzoq, Aseel; Komel, Radovan; Hoheisel, Jörg D.; Nienhüser, Henrik; Schmidt, Thomas; Kastelic, Damjana

    2016-01-01

    In this study, protein profiling was performed on gastric cancer tissue samples in order to identify proteins that could be utilized for an effective diagnosis of this highly heterogeneous disease and as targets for therapeutic approaches. To this end, 16 pairs of postoperative gastric adenocarcinomas and adjacent non-cancerous control tissues were analyzed on microarrays that contain 813 antibodies targeting 724 proteins. Only 17 proteins were found to be differentially regulated, with much fewer molecules than the numbers usually identified in studies comparing tumor to healthy control tissues. Insulin-like growth factor-binding protein 7 (IGFBP7), S100 calcium binding protein A9 (S100A9), interleukin-10 (IL‐10) and mucin 6 (MUC6) exhibited the most profound variations. For an evaluation of the proteins’ capacity for discriminating gastric cancer, a Receiver Operating Characteristic curve analysis was performed, yielding an accuracy (area under the curve) value of 89.2% for distinguishing tumor from non-tumorous tissue. For confirmation, immunohistological analyses were done on tissue slices prepared from another cohort of patients with gastric cancer. The utility of the 17 marker proteins, and particularly the four molecules with the highest specificity for gastric adenocarcinoma, is discussed for them to act as candidates for diagnosis, even in serum, and targets for therapeutic approaches. PMID:27600085

  3. Development and standardization of multiplexed antibody microarrays for use in quantitative proteomics

    PubMed Central

    Perlee, LT; Christiansen, J; Dondero, R; Grimwade, B; Lejnine, S; Mullenix, M; Shao, W; Sorette, M; Tchernev, VT; Patel, DD; Kingsmore, SF

    2004-01-01

    Background Quantitative proteomics is an emerging field that encompasses multiplexed measurement of many known proteins in groups of experimental samples in order to identify differences between groups. Antibody arrays are a novel technology that is increasingly being used for quantitative proteomics studies due to highly multiplexed content, scalability, matrix flexibility and economy of sample consumption. Key applications of antibody arrays in quantitative proteomics studies are identification of novel diagnostic assays, biomarker discovery in trials of new drugs, and validation of qualitative proteomics discoveries. These applications require performance benchmarking, standardization and specification. Results Six dual-antibody, sandwich immunoassay arrays that measure 170 serum or plasma proteins were developed and experimental procedures refined in more than thirty quantitative proteomics studies. This report provides detailed information and specification for manufacture, qualification, assay automation, performance, assay validation and data processing for antibody arrays in large scale quantitative proteomics studies. Conclusion The present report describes development of first generation standards for antibody arrays in quantitative proteomics. Specifically, it describes the requirements of a comprehensive validation program to identify and minimize antibody cross reaction under highly multiplexed conditions; provides the rationale for the application of standardized statistical approaches to manage the data output of highly replicated assays; defines design requirements for controls to normalize sample replicate measurements; emphasizes the importance of stringent quality control testing of reagents and antibody microarrays; recommends the use of real-time monitors to evaluate sensitivity, dynamic range and platform precision; and presents survey procedures to reveal the significance of biomarker findings. PMID:15598355

  4. Microarrays with Varying Carbohydrate Density Reveal Distinct Subpopulations of Serum Antibodies

    PubMed Central

    Oyelaran, Oyindasola; Li, Qian; Farnsworth, David; Gildersleeve, Jeffrey C.

    2009-01-01

    Antigen arrays have become important tools for profiling complex mixtures of proteins such as serum antibodies. These arrays can be used to better understand immune responses, discover new biomarkers, and guide the development of vaccines. Nevertheless, they are not perfect and improved array designs would enhance the information derived from this technology. In this study, we describe and evaluate a strategy for varying antigen density on an array and then use the array to study binding of lectins, monoclonal antibodies, and serum antibodies. To vary density, neoglycoproteins containing differing amounts of carbohydrate were synthesized and used to make a carbohydrate microarray with variations in both structure and density. We demonstrate that this method provides variations in density on the array surface within a range that is relevant for biological recognition events. The array was used to evaluate density dependent binding properties of three lectins (Vicia villosa lectin B4, Helix pomatia agglutinin, and soybean agglutinin) and three monoclonal antibodies (HBTn-1, B1.1, and Bric111) that bind the tumor-associated Tn antigen. In addition, serum antibodies were profiled from 30 healthy donors. The results show that variations in antigen density are required to detect the full spectrum of antibodies that bind a particular antigen and can be used to reveal differences in antibody populations between individuals that are not detectable using a single antigen density. PMID:19366269

  5. CYANOCHIP: an antibody microarray for high-taxonomical-resolution cyanobacterial monitoring.

    PubMed

    Blanco, Yolanda; Quesada, Antonio; Gallardo-Carreño, Ignacio; Aguirre, Jacobo; Parro, Victor

    2015-02-03

    Cyanobacteria are Gram-negative photosynthetic prokaryotes that are widespread on Earth. Eutrophication and global warming make some aquatic ecosystems behave as bioreactors that trigger rapid and massive cyanobacterial growth with remarkable economic and health consequences. Rapid and efficient early warning systems are required to support decisions by water body authorities. We have produced 17 specific antibodies to the most frequent cyanobacterial strains blooming in freshwater ecosystems, some of which are toxin producers. A sandwich-type antibody microarray immunoassay (CYANOCHIP) was developed for the simultaneous testing of any of the 17 strains, or other closely related strains, in field samples from different habitats (water, rocks, and sediments). We titrated and tested all of the antibodies in succession using a fluorescent sandwich microarray immunoassay. Although most showed high specificity, we applied a deconvolution method based on graph theory to disentangle the few existing cross-reactions. The CYANOCHIP sensitivity ranged from 10(2) to 10(4) cells mL(-1), with most antibodies detecting approximately 10(2) cells mL(-1). We validated the system by testing multiple isolates and crude natural samples from freshwater reservoirs and rocks, both in the laboratory and by in situ testing in the field. The results demonstrated that CYANOCHIP is a valuable tool for the sensitive and reliable detection of cyanobacteria for early warning and research purposes.

  6. Ontology-Based Analysis of Microarray Data.

    PubMed

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

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

  7. Tissue Microarray Analysis Applied to Bone Diagenesis

    PubMed Central

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

    2017-01-01

    Taphonomic processes affecting bone post mortem are important in forensic, archaeological and palaeontological investigations. In this study, the application of tissue microarray (TMA) analysis to a sample of femoral bone specimens from 20 exhumed individuals of known period of burial and age at death is described. TMA allows multiplexing of subsamples, permitting standardized comparative analysis of adjacent sections in 3-D and of representative cross-sections of a large number of specimens. Standard hematoxylin and eosin, periodic acid-Schiff and silver methenamine, and picrosirius red staining, and CD31 and CD34 immunohistochemistry were applied to TMA sections. Osteocyte and osteocyte lacuna counts, percent bone matrix loss, and fungal spheroid element counts could be measured and collagen fibre bundles observed in all specimens. Decalcification with 7% nitric acid proceeded more rapidly than with 0.5 M EDTA and may offer better preservation of histological and cellular structure. No endothelial cells could be detected using CD31 and CD34 immunohistochemistry. Correlation between osteocytes per lacuna and age at death may reflect reported age-related responses to microdamage. Methodological limitations and caveats, and results of the TMA analysis of post mortem diagenesis in bone are discussed, and implications for DNA survival and recovery considered. PMID:28051148

  8. Transcriptome Analysis of Zebrafish Embryogenesis Using Microarrays

    PubMed Central

    Mathavan, Sinnakaruppan; Lee, Serene G. P; Mak, Alicia; Miller, Lance D; Murthy, Karuturi Radha Krishna; Govindarajan, Kunde R; Tong, Yan; Wu, Yi Lian; Lam, Siew Hong; Yang, Henry; Ruan, Yijun; Korzh, Vladimir; Gong, Zhiyuan; Liu, Edison T; Lufkin, Thomas

    2005-01-01

    Zebrafish (Danio rerio) is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula) revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html). PMID:16132083

  9. Autocorrelation analysis reveals widespread spatial biases in microarray experiments

    PubMed Central

    Koren, Amnon; Tirosh, Itay; Barkai, Naama

    2007-01-01

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

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

    PubMed

    Koren, Amnon; Tirosh, Itay; Barkai, Naama

    2007-06-12

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

  11. Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip.

    PubMed

    Blanco, Yolanda; Moreno-Paz, Mercedes; Parro, Victor

    2017-02-07

    Global warming and eutrophication make some aquatic ecosystems behave as true bioreactors that trigger rapid and massive cyanobacterial growth; this has relevant health and economic consequences. Many cyanobacterial strains are toxin producers, and only a few cells are necessary to induce irreparable damage to the environment. Therefore, water-body authorities and administrations require rapid and efficient early-warning systems providing reliable data to support their preventive or curative decisions. This manuscript reports an experimental protocol for the in-field detection of toxin-producing cyanobacterial strains by using an antibody microarray chip with 17 antibodies (Abs) with taxonomic resolution (CYANOCHIP). Here, a multiplex fluorescent sandwich microarray immunoassay (FSMI) for the simultaneous monitoring of 17 cyanobacterial strains frequently found blooming in freshwater ecosystems, some of them toxin producers, is described. A microarray with multiple identical replicates (up to 24) of the CYANOCHIP was printed onto a single microscope slide to simultaneously test a similar number of samples. Liquid samples can be tested either by direct incubation with the antibodies (Abs) or after cell concentration by filtration through a 1- to 3-μm filter. Solid samples, such as sediments and ground rocks, are first homogenized and dispersed by a hand-held ultrasonicator in an incubation buffer. They are then filtered (5 - 20 μm) to remove the coarse material, and the filtrate is incubated with Abs. Immunoreactions are revealed by a final incubation with a mixture of the 17 fluorescence-labeled Abs and are read by a portable fluorescence detector. The whole process takes around 3 h, most of it corresponding to two 1-h periods of incubation. The output is an image, where bright spots correspond to the positive detection of cyanobacterial markers.

  12. Automatic Spot Identification for High Throughput Microarray Analysis

    PubMed Central

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

    2013-01-01

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

  13. Polypyrrole-peptide microarray for biomolecular interaction analysis by SPR imaging

    PubMed Central

    Villiers, Marie-Bernadette; Cortès, Sandra; Brakha, Carine; Marche, Patrice; Roget, André; Livache, Thierry

    2009-01-01

    Nowadays, high-throughput analysis of biological events is a great challenge which could take benefit of the recent development of microarray devices. The great potential of such technology is related to the availability of a chip bearing a large set of probes, stable and easy to obtain, and suitable for ligand binding detection. Here, we described a new method based on polypyrrole chemistry and allowing the covalent immobilization of peptides in a microarray format and on a gold surface compatible with the use of Surface Plasmon Resonance. This technique is then illustrated by the detection and characterization of antibodies induced by hepatitis C virus and present in patients’serums. PMID:19649603

  14. Improved porous silicon microarray based prostate specific antigen immunoassay by optimized surface density of the capture antibody.

    PubMed

    Lee, SangWook; Kim, Soyoun; Malm, Johan; Jeong, Ok Chan; Lilja, Hans; Laurell, Thomas

    2013-09-24

    Enriching the surface density of immobilized capture antibodies enhances the detection signal of antibody sandwich microarrays. In this study, we improved the detection sensitivity of our previously developed P-Si (porous silicon) antibody microarray by optimizing concentrations of the capturing antibody. We investigated immunoassays using a P-Si microarray at three different capture antibody (PSA - prostate specific antigen) concentrations, analyzing the influence of the antibody density on the assay detection sensitivity. The LOD (limit of detection) for PSA was 2.5 ng mL(-1), 80 pg mL(-1), and 800 fg mL(-1) when arraying the PSA antibody, H117 at the concentration 15 μg mL(-1), 35 μg mL(-1), and 154 μg mL(-1), respectively. We further investigated PSA spiked into human female serum in the range of 800 fg mL(-1) to 500 ng mL(-1). The microarray showed a LOD of 800 fg mL(-1) and a dynamic range of 800 fg mL(-1) to 80 ng mL(-1) in serum spiked samples. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Visualization of high-throughput and label-free antibody-polypeptide binding for drug screening based on microarrays and surface plasmon resonance imaging

    NASA Astrophysics Data System (ADS)

    Chen, Shengyi; Deng, Tao; Wang, Tongzhou; Wang, Jia; Li, Xin; Li, Qiang; Huang, Guoliang

    2012-01-01

    This work presents a visualization method for the high-throughput monitoring of antibody-polypeptide binding by integrating a microarray chip with surface plasmon resonance imaging (SPRi). A prism-coupled SPRi system with smart images processing software and a 5×5 polypeptide microarray was developed. The modeling analysis was performed to optimize the system and the materials of prism and chip, looking for the optimal incident wavelength and angle of incidence for dynamic SPRi detection in solution. The system can dynamically monitor 25 tunnels of biomolecule interactions in solution without secondary tag reactants. In addition, this system can determine the specific profile of antibody-polypeptide binding in each tunnel and yield a visual three-dimensional histogram of dynamic combinations in all microarray tunnels. Furthermore, the detection limit of the label-free antibody-polypeptide binding reached 1 pg/μL in a one-step binding test, and an ultrasensitive detection of 10 fg/μL was obtained using three-step cascade binding. Using the peptide microarray, the amount of sample and reagents used was reduced to 80 nL per tunnel, and 20×20 tunnels of biomolecule interactions could be analyzed in parallel in a 7 mm×7 mm microreaction cells. This device and method offer a potential platform for high-throughput and label-free dynamic monitoring multiple biomolecule interactions for drug discovery and basic biomedical research.

  16. Role of antibodies to human papillomavirus 16 in prostate cancer: A seroscreening by peptide microarray.

    PubMed

    Zhao, Xiaojun; Zhou, Zheng; Chen, Ye; Chen, Wen; Ma, Hongwei; Pu, Jinxian

    2017-06-01

    Evidence is accumulating in estimating the potential role of human papillomavirus infection in prostate carcinogenesis. However, the results remain inconclusive. We measured the serostatus of antibodies to one of the high-risk human papillomaviruses, human papillomavirus 16, with a newly developed peptide microarray. Serum samples were collected from 75 untreated prostate cancer patients, along with 80 control subjects. We identified 12 peptides with significant differences in prostate cancer samples from all 241 peptides derived from human papillomavirus 16. Our results showed human papillomavirus 16 infection in 64.0% of prostate cancer serum samples, which is significantly different compared with the controls ( p < 0.01) because only 17.5% of the control serum was considered seropositive. The area under the receiver operator characteristic curve was 0.793 (95% confidence interval 0.721-0.864), indicating that the new microarray technique may have diagnostic value. The results showed an association between serological evidence for human papillomavirus 16 infection and risk of prostate cancer. The different serostatus of antibodies in the two subgroups indicated that human papillomavirus 16 infection might occur and play a potential role of progression in a minority of prostate cancer.

  17. Microarray screening of Guillain-Barré syndrome sera for antibodies to glycolipid complexes

    PubMed Central

    Halstead, Susan K.; Kalna, Gabriela; Islam, Mohammad B.; Jahan, Israt; Mohammad, Quazi D.; Jacobs, Bart C.; Endtz, Hubert P.; Islam, Zhahirul

    2016-01-01

    Objective: To characterize the patterns of autoantibodies to glycolipid complexes in a large cohort of Guillain-Barré syndrome (GBS) and control samples collected in Bangladesh using a newly developed microarray technique. Methods: Twelve commonly studied glycolipids and lipids, plus their 66 possible heteromeric complexes, totaling 78 antigens, were applied to polyvinylidene fluoride–coated slides using a microarray printer. Arrays were probed with 266 GBS and 579 control sera (2 μL per serum, diluted 1/50) and bound immunoglobulin G detected with secondary antibody. Scanned arrays were subjected to statistical analyses. Results: Measuring antibodies to single targets was 9% less sensitive than to heteromeric complex targets (49.2% vs 58.3%) without significantly affecting specificity (83.9%–85.0%). The optimal screening protocol for GBS sera comprised a panel of 10 glycolipids (4 single glycolipids GM1, GA1, GD1a, GQ1b, and their 6 heteromeric complexes), resulting in an overall assay sensitivity of 64.3% and specificity of 77.1%. Notable heteromeric targets were GM1:GD1a, GM1:GQ1b, and GA1:GD1a, in which exclusive binding to the complex was observed. Conclusions: Rationalizing the screening protocol to capture the enormous diversity of glycolipid complexes can be achieved by miniaturizing the screening platform to a microarray platform, and applying simple bioinformatics to determine optimal sensitivity and specificity of the targets. Glycolipid complexes are an important category of glycolipid antigens in autoimmune neuropathy cases that require specific analytical and bioinformatics methods for optimal detection. PMID:27790627

  18. A flow-through microarray cell for the online SERS detection of antibody-captured E. coli bacteria.

    PubMed

    Knauer, Maria; Ivleva, Natalia P; Niessner, Reinhard; Haisch, Christoph

    2012-03-01

    We present an immunoassay microarray flow-through system for the surface-enhanced Raman scattering (SERS) analysis of bacteria. The system has been constructed to support and automatize the nondestructive in situ analysis of different microorganisms in aqueous environment. After the immobilization of the desired antibodies to an activated PEG-coated surface, the chip is placed into the flow cell which is then flushed with the contaminated sample. Finally, colloidal metal nanoparticles are added and the cells are detected label-free by SERS. Here, we introduce the successful imaging of single microorganisms in the flow cell as well as the quantification of microorganisms in water by SERS mapping with a linear range between 4.3 × 10(3) to 4.3 × 10(5) cells/mL. The method has potential for routine application, e.g. for drinking water control.

  19. High confidence rule mining for microarray analysis.

    PubMed

    McIntosh, Tara; Chawla, Sanjay

    2007-01-01

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

  20. Zeptosens' protein microarrays: a novel high performance microarray platform for low abundance protein analysis.

    PubMed

    Pawlak, Michael; Schick, Eginhard; Bopp, Martin A; Schneider, Michael J; Oroszlan, Peter; Ehrat, Markus

    2002-04-01

    Protein microarrays are considered an enabling technology, which will significantly expand the scope of current protein expression and protein interaction analysis. Current technologies, such as two-dimensional gel electrophoresis (2-DE) in combination with mass spectrometry, allowing the identification of biologically relevant proteins, have a high resolving power, but also considerable limitations. As was demonstrated by Gygi et al. (Proc. Nat. Acad. Sci. USA 2000,97, 9390-9395), most spots in 2-DE, observed from whole cell extracts, are from high abundance proteins, whereas low abundance proteins, such as signaling molecules or kinases, are only poorly represented. Protein microarrays are expected to significantly expedite the discovery of new markers and targets of pharmaceutical interest, and to have the potential for high-throughput applications. Key factors to reach this goal are: high read-out sensitivity for quantification also of low abundance proteins, functional analysis of proteins, short assay analysis times, ease of handling and the ability to integrate a variety of different targets and new assays. Zeptosens has developed a revolutionary new bioanalytical system based on the proprietary planar waveguide technology which allows us to perform multiplexed, quantitative biomolecular interaction analysis with highest sensitivity in a microarray format upon utilizing the specific advantages of the evanescent field fluorescence detection. The analytical system, comprising an ultrasensitive fluorescence reader and microarray chips with integrated microfluidics, enables the user to generate a multitude of high fidelity data in applications such as protein expression profiling or investigating protein-protein interactions. In this paper, the important factors for developing high performance protein microarray systems, especially for targeting low abundant messengers of relevant biological information, will be discussed and the performance of the system will

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

    PubMed

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

    2016-09-01

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

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

    PubMed Central

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

    2016-01-01

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

  3. Assessing antibody microarrays for space missions: effect of long-term storage, gamma radiation, and temperature shifts on printed and fluorescently labeled antibodies.

    PubMed

    de Diego-Castilla, Graciela; Cruz-Gil, Patricia; Mateo-Martí, Eva; Fernández-Calvo, Patricia; Rivas, Luis A; Parro, Víctor

    2011-10-01

    Antibody microarrays are becoming frequently used tools for analytical purposes. A key factor for optimal performance is the stability of the immobilized (capturing) antibodies as well as those that have been fluorescently labeled to achieve the immunological test (tracers). This is especially critical for long-distance transport, field testing, or planetary exploration. A number of different environmental stresses may affect the antibody integrity, such as dryness, sudden temperature shift cycles, or, as in the case of space science, exposure to large quantities of the highly penetrating gamma radiation. Here, we report on the effect of certain stabilizing solutions for long-term storage of printed antibody microarrays under different conditions. We tested the effect of gamma radiation on printed and freeze- or vacuum-dried fluorescent antibodies at working concentrations (tracer antibodies), as well as the effect of multiple cycles of sudden and prolonged temperature shifts on the stability of fluorescently labeled tracer antibody cocktails. Our results show that (i) antibody microarrays are stable at room temperature when printed on stabilizing spotting solutions for at least 6 months, (ii) lyophilized and vacuum-dried fluorescently labeled tracer antibodies are stable for more than 9 months of sudden temperature shift cycles (-20°C to 25°C and 50°C), and (iii) both printed and freeze- or vacuum-dried fluorescent tracer antibodies are stable after several-fold excess of the dose of gamma radiation expected during a mission to Mars. Although different antibodies may exhibit different susceptibilities, we conclude that, in general, antibodies are suitable for use in planetary exploration purposes if they are properly treated and stored with the use of stabilizing substances.

  4. Analysis of Microarray and RNA-seq Expression Profiling Data.

    PubMed

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Gene expression profiling refers to the simultaneous measurement of the expression levels of a large number of genes (often all genes in a genome), typically in multiple experiments spanning a variety of cell types, treatments, or environmental conditions. Expression profiling is accomplished by assaying mRNA levels with microarrays or next-generation sequencing technologies (RNA-seq). This introduction describes normalization and analysis of data generated from microarray or RNA-seq experiments.

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

    PubMed Central

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

    2008-01-01

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

  6. Challenges for MicroRNA Microarray Data Analysis

    PubMed Central

    Wang, Bin; Xi, Yaguang

    2013-01-01

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

  7. ProMAT: protein microarray analysis tool

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Varnum, Susan M.; Anderson, Kevin K.; Bollinger, Nikki; Zangar, Richard C.

    2006-04-04

    Summary: ProMAT is a software tool for statistically analyzing data from ELISA microarray experiments. The software estimates standard curves, sample protein concentrations and their uncertainties for multiple assays. ProMAT generates a set of comprehensive figures for assessing results and diagnosing process quality. The tool is available for Windows or Mac, and is distributed as open-source Java and R code. Availability: ProMAT is available at http://www.pnl.gov/statistics/ProMAT. ProMAT requires Java version 1.5.0 and R version 1.9.1 (or more recent versions) which are distributed with the tool.

  8. Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays.

    PubMed

    Khosravi, Farhad; Trainor, Patrick; Rai, Shesh N; Kloecker, Goetz; Wickstrom, Eric; Panchapakesan, Balaji

    2016-04-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in buffy coats using nanotube-antibody micro-arrays. Single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (EpCAM) antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester functionalization method. Following functionalization, plain buffy coat and MCF7 cell spiked buffy coats were adsorbed on to the nanotube device and electrical signatures were recorded for differences in interaction between samples. A statistical classifier for the 'liquid biopsy' was developed to create a predictive model based on dynamic time warping to classify device electrical signals that corresponded to plain (control) or spiked buffy coats (case). In training test, the device electrical signals originating from buffy versus spiked buffy samples were classified with ∼100% sensitivity, ∼91% specificity and ∼96% accuracy. In the blinded test, the signals were classified with ∼91% sensitivity, ∼82% specificity and ∼86% accuracy. A heatmap was generated to visually capture the relationship between electrical signatures and the sample condition. Confocal microscopic analysis of devices that were classified as spiked buffy coats based on their electrical signatures confirmed the presence of cancer cells, their attachment to the device and overexpression of EpCAM receptors. The cell numbers were counted to be ∼1-17 cells per 5 μl per device suggesting single cell sensitivity in spiked buffy coats that is scalable to higher volumes using the micro-arrays.

  9. Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

    PubMed Central

    Khosravi, Farhad; Trainor, Patrick; Rai, Shesh N; Kloecker, Goetz; Wickstrom, Eric; Panchapakesan, Balaji

    2016-01-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in buffy coats using nanotube-antibody micro-arrays. Single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (EpCAM) antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester functionalization method. Following functionalization, plain buffy coat and MCF7 cell spiked buffy coats were adsorbed on to the nanotube device and electrical signatures were recorded for differences in interaction between samples. A statistical classifier for the ‘liquid biopsy’ was developed to create a predictive model based on dynamic time warping to classify device electrical signals that corresponded to plain (control) or spiked buffy coats (case). In training test, the device electrical signals originating from buffy versus spiked buffy samples were classified with ~100% sensitivity, ~91% specificity and ~96% accuracy. In the blinded test, the signals were classified with ~91% sensitivity, ~82% specificity and ~86% accuracy. A heatmap was generated to visually capture the relationship between electrical signatures and the sample condition. Confocal microscopic analysis of devices that were classified as spiked buffy coats based on their electrical signatures confirmed the presence of cancer cells, their attachment to the device and overexpression of EpCAM receptors. The cell numbers were counted to be ~1—17 cells per 5 µl per device suggesting single cell sensitivity in spiked buffy coats that is scalable to higher volumes using the micro-arrays. PMID:26901310

  10. Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

    NASA Astrophysics Data System (ADS)

    Khosravi, Farhad; Trainor, Patrick; Rai, Shesh N.; Kloecker, Goetz; Wickstrom, Eric; Panchapakesan, Balaji

    2016-04-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in buffy coats using nanotube-antibody micro-arrays. Single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (EpCAM) antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester functionalization method. Following functionalization, plain buffy coat and MCF7 cell spiked buffy coats were adsorbed on to the nanotube device and electrical signatures were recorded for differences in interaction between samples. A statistical classifier for the ‘liquid biopsy’ was developed to create a predictive model based on dynamic time warping to classify device electrical signals that corresponded to plain (control) or spiked buffy coats (case). In training test, the device electrical signals originating from buffy versus spiked buffy samples were classified with ˜100% sensitivity, ˜91% specificity and ˜96% accuracy. In the blinded test, the signals were classified with ˜91% sensitivity, ˜82% specificity and ˜86% accuracy. A heatmap was generated to visually capture the relationship between electrical signatures and the sample condition. Confocal microscopic analysis of devices that were classified as spiked buffy coats based on their electrical signatures confirmed the presence of cancer cells, their attachment to the device and overexpression of EpCAM receptors. The cell numbers were counted to be ˜1-17 cells per 5 μl per device suggesting single cell sensitivity in spiked buffy coats that is scalable to higher volumes using the micro-arrays.

  11. Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

    DOE PAGES

    Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; ...

    2014-11-14

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth ofmore » IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.« less

  12. Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development

    SciTech Connect

    Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; Pawlowski, Nikolaus; Knaute, Tobias; Zerweck, Johannes; Korber, Bette T.; Barouch, Dan H.

    2014-11-14

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research.

  13. Quantification of the epitope diversity of HIV-1-specific binding antibodies by peptide microarrays for global HIV-1 vaccine development.

    PubMed

    Stephenson, Kathryn E; Neubauer, George H; Reimer, Ulf; Pawlowski, Nikolaus; Knaute, Tobias; Zerweck, Johannes; Korber, Bette T; Barouch, Dan H

    2015-01-01

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research. Copyright © 2014. Published by Elsevier B.V.

  14. Quantification of the Epitope Diversity of HIV-1-Specific Binding Antibodies by Peptide Microarrays for Global HIV-1 Vaccine Development

    PubMed Central

    Stephenson, Kathryn E.; Neubauer, George H.; Reimer, Ulf; Pawlowski, Nikolaus; Knaute, Tobias; Zerweck, Johannes; Korber, Bette T.; Barouch, Dan H.

    2014-01-01

    An effective vaccine against human immunodeficiency virus type 1 (HIV-1) will have to provide protection against a vast array of different HIV-1 strains. Current methods to measure HIV-1-specific binding antibodies following immunization typically focus on determining the magnitude of antibody responses, but the epitope diversity of antibody responses has remained largely unexplored. Here we describe the development of a global HIV-1 peptide microarray that contains 6,564 peptides from across the HIV-1 proteome and covers the majority of HIV-1 sequences in the Los Alamos National Laboratory global HIV-1 sequence database. Using this microarray, we quantified the magnitude, breadth, and depth of IgG binding to linear HIV-1 sequences in HIV-1-infected humans and HIV-1-vaccinated humans, rhesus monkeys and guinea pigs. The microarray measured potentially important differences in antibody epitope diversity, particularly regarding the depth of epitope variants recognized at each binding site. Our data suggest that the global HIV-1 peptide microarray may be a useful tool for both preclinical and clinical HIV-1 research. PMID:25445329

  15. WebArray: an online platform for microarray data analysis

    PubMed Central

    Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

    2005-01-01

    Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

  16. Microarray diagnosis of antibody-mediated rejection in kidney transplant biopsies: an international prospective study (INTERCOM).

    PubMed

    Halloran, P F; Pereira, A B; Chang, J; Matas, A; Picton, M; De Freitas, D; Bromberg, J; Serón, D; Sellarés, J; Einecke, G; Reeve, J

    2013-11-01

    In a reference set of 403 kidney transplant biopsies, we recently developed a microarray-based test that diagnoses antibody-mediated rejection (ABMR) by assigning an ABMR score. To validate the ABMR score and assess its potential impact on practice, we performed the present prospective INTERCOM study (clinicaltrials.gov NCT01299168) in 300 new biopsies (264 patients) from six centers: Baltimore, Barcelona, Edmonton, Hannover, Manchester and Minneapolis. We assigned ABMR scores using the classifier created in the reference set and compared it to conventional assessment as documented in the pathology reports. INTERCOM documented uncertainty in conventional assessment: In 41% of biopsies where ABMR features were noted, the recorded diagnoses did not mention ABMR. The ABMR score correlated with ABMR histologic lesions and donor-specific antibodies, but not with T cell-mediated rejection lesions. The agreement between ABMR scores and conventional assessment was identical to that in the reference set (accuracy 85%). The ABMR score was more strongly associated with failure than conventional assessment, and when the ABMR score and conventional assessment disagreed, only the ABMR score was associated with early progression to failure. INTERCOM confirms the need to reduce uncertainty in the diagnosis of ABMR, and demonstrates the potential of the ABMR score to impact practice.

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

    PubMed

    Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe

    2011-12-01

    Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.

  18. Short time-series microarray analysis: Methods and challenges

    PubMed Central

    Wang, Xuewei; Wu, Ming; Li, Zheng; Chan, Christina

    2008-01-01

    The detection and analysis of steady-state gene expression has become routine. Time-series microarrays are of growing interest to systems biologists for deciphering the dynamic nature and complex regulation of biosystems. Most temporal microarray data only contain a limited number of time points, giving rise to short-time-series data, which imposes challenges for traditional methods of extracting meaningful information. To obtain useful information from the wealth of short-time series data requires addressing the problems that arise due to limited sampling. Current efforts have shown promise in improving the analysis of short time-series microarray data, although challenges remain. This commentary addresses recent advances in methods for short-time series analysis including simplification-based approaches and the integration of multi-source information. Nevertheless, further studies and development of computational methods are needed to provide practical solutions to fully exploit the potential of this data. PMID:18605994

  19. Microarray analysis of papillary thyroid cancers in Korean.

    PubMed

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

    2010-12-01

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

  20. Optimized T7 amplification system for microarray analysis.

    PubMed

    Pabón, C; Modrusan, Z; Ruvolo, M V; Coleman, I M; Daniel, S; Yue, H; Arnold, L J

    2001-10-01

    Glass cDNA microarray technologies offer a highly parallel approach for profiling expressed gene sequences in disease-relevant tissues. However, standard hybridization and detection protocols are insufficient for milligram quantities of tissue, such as those derived from needle biopsies. Amplification systems utilizing T7 RNA polymerase can provide multiple cRNA copies from mRNA transcripts, permitting microarray studies with reduced sample inputs. Here, we describe an optimized T7-based amplification system for microarray analysis that yields between 200- and 700-fold amplification. This system was evaluated with both mRNA and total RNA samples and provided microarray sensitivity and precision that are comparable to our standard production process without amplification. The size distributions of amplified cRNA ranged from 200 bp to 4 kb and were similar to original mRNA profiles. These amplified cRNA samples were fluorescently labeled by reverse transcription and hybridized to microarrays comprising approximately 10,000 cDNA targets using a dual-channel format. Replicate hybridization experiments were conducted with the same and different tissues in each channel to assess the sensitivity and precision of differential expression ratios. Statistical analysis of differential expression ratios showed the lower limit of detection to be about 2-fold within and between amplified data sets, and about 3-fold when comparing amplified data to unamplified data (99.5% confidence).

  1. Microarray analysis of DNA replication timing.

    PubMed

    Karnani, Neerja; Taylor, Christopher M; Dutta, Anindya

    2009-01-01

    Although all of the DNA in an eukaryotic cell replicates during the S-phase of cell cycle, there is a significant difference in the actual time in S-phase when a given chromosomal segment replicates. Methods are described here for generation of high-resolution temporal maps of DNA replication in synchronized human cells. This method does not require amplification of DNA before microarray hybridization and so avoids errors introduced during PCR. A major advantage of using this procedure is that it facilitates finer dissection of replication time in S-phase. Also, it helps delineate chromosomal regions that undergo biallelic or asynchronous replication, which otherwise are difficult to detect at a genome-wide scale by existing methods. The continuous TR50 (time of completion of 50% replication) maps of replication across chromosomal segments identify regions that undergo acute transitions in replication timing. These transition zones can play a significant role in identifying insulators that separate chromosomal domains with different chromatin modifications.

  2. Determination of specific antibody responses to the six species of ebola and Marburg viruses by multiplexed protein microarrays.

    PubMed

    Kamata, Teddy; Natesan, Mohan; Warfield, Kelly; Aman, M Javad; Ulrich, Robert G

    2014-12-01

    Infectious hemorrhagic fevers caused by the Marburg and Ebola filoviruses result in human mortality rates of up to 90%, and there are no effective vaccines or therapeutics available for clinical use. The highly infectious and lethal nature of these viruses highlights the need for reliable and sensitive diagnostic methods. We assembled a protein microarray displaying nucleoprotein (NP), virion protein 40 (VP40), and glycoprotein (GP) antigens from isolates representing the six species of filoviruses for use as a surveillance and diagnostic platform. Using the microarrays, we examined serum antibody responses of rhesus macaques vaccinated with trivalent (GP, NP, and VP40) virus-like particles (VLP) prior to infection with the Marburg virus (MARV) (i.e., Marburg marburgvirus) or the Zaire virus (ZEBOV) (i.e., Zaire ebolavirus). The microarray-based assay detected a significant increase in antigen-specific IgG resulting from immunization, while a greater level of antibody responses resulted from challenge of the vaccinated animals with ZEBOV or MARV. Further, while antibody cross-reactivities were observed among NPs and VP40s of Ebola viruses, antibody recognition of GPs was very specific. The performance of mucin-like domain fragments of GP (GP mucin) expressed in Escherichia coli was compared to that of GP ectodomains produced in eukaryotic cells. Based on results with ZEBOV and MARV proteins, antibody recognition of GP mucins that were deficient in posttranslational modifications was comparable to that of the eukaryotic cell-expressed GP ectodomains in assay performance. We conclude that the described protein microarray may translate into a sensitive assay for diagnosis and serological surveillance of infections caused by multiple species of filoviruses.

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

    PubMed

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

    2007-10-24

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

  4. Microarray Analysis in the Archaeon Halobacterium salinarum Strain R1

    PubMed Central

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

    2007-01-01

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

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

    PubMed

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

    2016-12-01

    In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J

  6. SOLID3: A Multiplex Antibody Microarray-Based Optical Sensor Instrument for In Situ Life Detection in Planetary Exploration

    NASA Astrophysics Data System (ADS)

    Parro, Víctor; de Diego-Castilla, Graciela; Rodríguez-Manfredi, José A.; Rivas, Luis A.; Blanco-López, Yolanda; Sebastián, Eduardo; Romeral, Julio; Compostizo, Carlos; Herrero, Pedro L.; García-Marín, Adolfo; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Cruz-Gil, Patricia; Peinado, Verónica; Martín-Soler, Javier; Pérez-Mercader, Juan; Gómez-Elvira, Javier

    2011-01-01

    The search for unequivocal signs of life on other planetary bodies is one of the major challenges for astrobiology. The failure to detect organic molecules on the surface of Mars by measuring volatile compounds after sample heating, together with the new knowledge of martian soil chemistry, has prompted the astrobiological community to develop new methods and technologies. Based on protein microarray technology, we have designed and built a series of instruments called SOLID (for ``Signs Of LIfe Detector'') for automatic in situ detection and identification of substances or analytes from liquid and solid samples (soil, sediments, or powder). Here, we present the SOLID3 instrument, which is able to perform both sandwich and competitive immunoassays and consists of two separate functional units: a Sample Preparation Unit (SPU) for 10 different extractions by ultrasonication and a Sample Analysis Unit (SAU) for fluorescent immunoassays. The SAU consists of five different flow cells, with an antibody microarray in each one (2000 spots). It is also equipped with an exclusive optical package and a charge-coupled device (CCD) for fluorescent detection. We demonstrated the performance of SOLID3 in the detection of a broad range of molecular-sized compounds, which range from peptides and proteins to whole cells and spores, with sensitivities at 1-2ppb (ngmL-1) for biomolecules and 104 to 103 spores per milliliter. We report its application in the detection of acidophilic microorganisms in the Río Tinto Mars analogue and report the absence of substantial negative effects on the immunoassay in the presence of 50mM perchlorate (20 times higher than that found at the Phoenix landing site). Our SOLID instrument concept is an excellent option with which to detect biomolecules because it avoids the high-temperature treatments that may destroy organic matter in the presence of martian oxidants.

  7. SOLID3: a multiplex antibody microarray-based optical sensor instrument for in situ life detection in planetary exploration.

    PubMed

    Parro, Víctor; de Diego-Castilla, Graciela; Rodríguez-Manfredi, José A; Rivas, Luis A; Blanco-López, Yolanda; Sebastián, Eduardo; Romeral, Julio; Compostizo, Carlos; Herrero, Pedro L; García-Marín, Adolfo; Moreno-Paz, Mercedes; García-Villadangos, Miriam; Cruz-Gil, Patricia; Peinado, Verónica; Martín-Soler, Javier; Pérez-Mercader, Juan; Gómez-Elvira, Javier

    2011-01-01

    The search for unequivocal signs of life on other planetary bodies is one of the major challenges for astrobiology. The failure to detect organic molecules on the surface of Mars by measuring volatile compounds after sample heating, together with the new knowledge of martian soil chemistry, has prompted the astrobiological community to develop new methods and technologies. Based on protein microarray technology, we have designed and built a series of instruments called SOLID (for "Signs Of LIfe Detector") for automatic in situ detection and identification of substances or analytes from liquid and solid samples (soil, sediments, or powder). Here, we present the SOLID3 instrument, which is able to perform both sandwich and competitive immunoassays and consists of two separate functional units: a Sample Preparation Unit (SPU) for 10 different extractions by ultrasonication and a Sample Analysis Unit (SAU) for fluorescent immunoassays. The SAU consists of five different flow cells, with an antibody microarray in each one (2000 spots). It is also equipped with an exclusive optical package and a charge-coupled device (CCD) for fluorescent detection. We demonstrated the performance of SOLID3 in the detection of a broad range of molecular-sized compounds, which range from peptides and proteins to whole cells and spores, with sensitivities at 1-2 ppb (ng mL⁻¹) for biomolecules and 10⁴ to 10³ spores per milliliter. We report its application in the detection of acidophilic microorganisms in the Río Tinto Mars analogue and report the absence of substantial negative effects on the immunoassay in the presence of 50 mM perchlorate (20 times higher than that found at the Phoenix landing site). Our SOLID instrument concept is an excellent option with which to detect biomolecules because it avoids the high-temperature treatments that may destroy organic matter in the presence of martian oxidants.

  8. Development and application of an antibody-based protein microarray to assess physiological stress in grizzly bears (Ursus arctos).

    PubMed

    Carlson, Ruth I; Cattet, Marc R L; Sarauer, Bryan L; Nielsen, Scott E; Boulanger, John; Stenhouse, Gordon B; Janz, David M

    2016-01-01

    A novel antibody-based protein microarray was developed that simultaneously determines expression of 31 stress-associated proteins in skin samples collected from free-ranging grizzly bears (Ursus arctos) in Alberta, Canada. The microarray determines proteins belonging to four broad functional categories associated with stress physiology: hypothalamic-pituitary-adrenal axis proteins, apoptosis/cell cycle proteins, cellular stress/proteotoxicity proteins and oxidative stress/inflammation proteins. Small skin samples (50-100 mg) were collected from captured bears using biopsy punches. Proteins were isolated and labelled with fluorescent dyes, with labelled protein homogenates loaded onto microarrays to hybridize with antibodies. Relative protein expression was determined by comparison with a pooled standard skin sample. The assay was sensitive, requiring 80 µg of protein per sample to be run in triplicate on the microarray. Intra-array and inter-array coefficients of variation for individual proteins were generally <10 and <15%, respectively. With one exception, there were no significant differences in protein expression among skin samples collected from the neck, forelimb, hindlimb and ear in a subsample of n = 4 bears. This suggests that remotely delivered biopsy darts could be used in future sampling. Using generalized linear mixed models, certain proteins within each functional category demonstrated altered expression with respect to differences in year, season, geographical sampling location within Alberta and bear biological parameters, suggesting that these general variables may influence expression of specific proteins in the microarray. Our goal is to apply the protein microarray as a conservation physiology tool that can detect, evaluate and monitor physiological stress in grizzly bears and other species at risk over time in response to environmental change.

  9. Development and application of an antibody-based protein microarray to assess physiological stress in grizzly bears (Ursus arctos)

    PubMed Central

    Carlson, Ruth I.; Cattet, Marc R. L.; Sarauer, Bryan L.; Nielsen, Scott E.; Boulanger, John; Stenhouse, Gordon B.; Janz, David M.

    2016-01-01

    A novel antibody-based protein microarray was developed that simultaneously determines expression of 31 stress-associated proteins in skin samples collected from free-ranging grizzly bears (Ursus arctos) in Alberta, Canada. The microarray determines proteins belonging to four broad functional categories associated with stress physiology: hypothalamic–pituitary–adrenal axis proteins, apoptosis/cell cycle proteins, cellular stress/proteotoxicity proteins and oxidative stress/inflammation proteins. Small skin samples (50–100 mg) were collected from captured bears using biopsy punches. Proteins were isolated and labelled with fluorescent dyes, with labelled protein homogenates loaded onto microarrays to hybridize with antibodies. Relative protein expression was determined by comparison with a pooled standard skin sample. The assay was sensitive, requiring 80 µg of protein per sample to be run in triplicate on the microarray. Intra-array and inter-array coefficients of variation for individual proteins were generally <10 and <15%, respectively. With one exception, there were no significant differences in protein expression among skin samples collected from the neck, forelimb, hindlimb and ear in a subsample of n = 4 bears. This suggests that remotely delivered biopsy darts could be used in future sampling. Using generalized linear mixed models, certain proteins within each functional category demonstrated altered expression with respect to differences in year, season, geographical sampling location within Alberta and bear biological parameters, suggesting that these general variables may influence expression of specific proteins in the microarray. Our goal is to apply the protein microarray as a conservation physiology tool that can detect, evaluate and monitor physiological stress in grizzly bears and other species at risk over time in response to environmental change. PMID:27293753

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

    PubMed Central

    Kong, Wei; Mou, Xiaoyang; Liu, Qingzhong; Chen, Zhongxue; Vanderburg, Charles R; Rogers, Jack T; Huang, Xudong

    2009-01-01

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

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

    PubMed

    Ma, Shuangge; Huang, Jian

    2009-01-01

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

  12. Microarray data analysis for differential expression: a tutorial.

    PubMed

    Suárez, Erick; Burguete, Ana; Mclachlan, Geoffrey J

    2009-06-01

    DNA microarray is a technology that simultaneously evaluates quantitative measurements for the expression of thousands of genes. DNA microarrays have been used to assess gene expression between groups of cells of different organs or different populations. In order to understand the role and function of the genes, one needs the complete information about their mRNA transcripts and proteins. Unfortunately, exploring the protein functions is very difficult, due to their unique 3-dimentional complicated structure. To overcome this difficulty, one may concentrate on the mRNA molecules produced by the gene expression. In this paper, we describe some of the methods for preprocessing data for gene expression and for pairwise comparison from genomic experiments. Previous studies to assess the efficiency of different methods for pairwise comparisons have found little agreement in the lists of significant genes. Finally, we describe the procedures to control false discovery rates, sample size approach for these experiments, and available software for microarray data analysis. This paper is written for those professionals who are new in microarray data analysis for differential expression and want to have an overview of the specific steps or the different approaches for this sort of analysis.

  13. Comparison of orthogonal chromatographic and lectin-affinity microarray methods for glycan profiling of a therapeutic monoclonal antibody.

    PubMed

    Cook, Matthew C; Kaldas, Sherif J; Muradia, Gauri; Rosu-Myles, Michael; Kunkel, Jeremy P

    2015-08-01

    The N-linked glycosylation of four lots of a marketed human therapeutic monoclonal antibody (mAb) was assessed by three orthogonal chromatographic methods and a commercial lectin microarray. For chromatography, the N-glycans were removed enzymatically from the mAbs using PNGase F. Native glycans were determined by HPAEC-PAD using a panel of 21 N-glycan standards and a multi-stage linear gradient eluent profile for sequential analyses of typical neutral and sialylated glycans in one chromatographic run. The monosaccharide contents of these glycans following acid hydrolysis were confirmed by HPAEC-PAD with monosaccharide standards. Glycosylation analysis by HILIC-FD after stoichiometric labelling with two different fluorescent tags (2-AA and 2-AB) enabled direct quantitation. The 2-AA- and 2-AB-labelled versions of the same glycan standard panel yielded distinctive separation profiles suitable for orthogonal identification of mAb glycans. Glycan profiling with the lectin microarray required partial denaturation of the intact mAbs to expose the sequestered Fc N-glycans. Glycosylation fingerprints were obtained using a fluorescently labelled antibody directed against human IgG Fc. Fluorescence intensities from the fingerprints were deconvoluted with a proprietary algorithm to obtain semi-quantitative "glycan structural class" information. Glycosylation analyses of the four mAb lots by these four methods, which separate and detect oligosaccharides according to different principles, provided complementary and corroboratory qualitative and quantitative information. The predominant N-linked structures were core-fucosylated asialo diantennary structures with varying galactosylation. There were also trace amounts of afucosyl and bisected glycans, but no detectable sialylation by any of the four methods. The therapeutic mAb demonstrated a high degree of consistency in the types and amounts of N-linked glycans in the four lots (<6% CV), and between all four analysis methods

  14. Overview of Protein Microarrays

    PubMed Central

    Reymond Sutandy, FX; Qian, Jiang; Chen, Chien-Sheng; Zhu, Heng

    2013-01-01

    Protein microarray is an emerging technology that provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput way. Two major classes of protein microarrays are defined to describe their applications: analytical and functional protein microarrays. In addition, tissue or cell lysates can also be fractionated and spotted on a slide to form a reverse-phase protein microarray. While the fabrication technology is maturing, applications of protein microarrays, especially functional protein microarrays, have flourished during the past decade. Here, we will first review recent advances in the protein microarray technologies, and then present a series of examples to illustrate the applications of analytical and functional protein microarrays in both basic and clinical research. The research areas will include detection of various binding properties of proteins, study of protein posttranslational modifications, analysis of host-microbe interactions, profiling antibody specificity, and identification of biomarkers in autoimmune diseases. As a powerful technology platform, it would not be surprising if protein microarrays will become one of the leading technologies in proteomic and diagnostic fields in the next decade. PMID:23546620

  15. Targeted Deposition of Antibodies on a Multiplex CMOS Microarray and Optimization of a Sensitive Immunoassay Using Electrochemical Detection

    DTIC Science & Technology

    2010-03-19

    sandwich immunoassay used a capture Ab adsorbed to the Ppy and a reporter Ab labeled for fluorescence detection or ECD, and results from these methods of...Targeted Deposition of Antibodies on a Multiplex CMOS Microarray and Optimization of a Sensitive Immunoassay Using Electrochemical Detection John...Sensitive Immunoassay Using Electrochemical Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT

  16. Measuring affinity constants of 1450 monoclonal antibodies to peptide targets with a microarray-based label-free assay platform.

    PubMed

    Landry, J P; Ke, Yaohuang; Yu, Guo-Liang; Zhu, X D

    2015-02-01

    Monoclonal antibodies (mAbs) are major reagents for research and clinical diagnosis. For their inherently high specificities to intended antigen targets and thus low toxicity in general, they are pursued as one of the major classes of new drugs. Yet binding properties of most monoclonal antibodies are not well characterized in terms of affinity constants and how they vary with presentations and/or conformational isomers of antigens, buffer compositions, and temperature. We here report a microarray-based label-free assay platform for high-throughput measurements of monoclonal antibody affinity constants to antigens immobilized on solid surfaces. Using this platform we measured affinity constants of over 1410 rabbit monoclonal antibodies and 46 mouse monoclonal antibodies to peptide targets that are immobilized through a terminal cysteine residue to a glass surface. The experimentally measured affinity constants vary from 10 pM to 200 pM with the median value at 66 pM. We compare the results obtained from the microarray-based platform with those from a benchmarking surface-plasmon-resonance-based (SPR) sensor (Biacore 3000).

  17. Deciphering the prokaryotic community and metabolisms in South African deep-mine biofilms through antibody microarrays and graph theory.

    PubMed

    Blanco, Yolanda; Rivas, Luis A; García-Moyano, Antonio; Aguirre, Jacobo; Cruz-Gil, Patricia; Palacín, Arantxa; van Heerden, Esta; Parro, Víctor

    2014-01-01

    In the South African deep mines, a variety of biofilms growing in mine corridor walls as water seeps from intersections or from fractures represents excellent proxies for deep-subsurface environments. However, they may be greatly affected by the oxygen inputs through the galleries of mining activities. As a consequence, the interaction between the anaerobic water coming out from the walls with the oxygen inputs creates new conditions that support rich microbial communities. The inherent difficulties for sampling these delicate habitats, together with transport and storage conditions may alter the community features and composition. Therefore, the development of in situ monitoring methods would be desirable for quick evaluation of the microbial community. In this work, we report the usefulness of an antibody-microarray (EMChip66) immunoassay for a quick check of the microbial diversity of biofilms located at 1.3 km below surface within the Beatrix deep gold mine (South Africa). In addition, a deconvolution method, previously described and used for environmental monitoring, based on graph theory and applied on antibody cross-reactivity was used to interpret the immunoassay results. The results were corroborated and further expanded by 16S rRNA gene sequencing analysis. Both culture-independent techniques coincided in detecting features related to aerobic sulfur-oxidizers, aerobic chemoorganotrophic Alphaproteobacteria and metanotrophic Gammaproteobacteria. 16S rRNA gene sequencing detected phylotypes related to nitrate-reducers and anaerobic sulfur-oxidizers, whereas the EMChip66 detected immunological features from methanogens and sulfate-reducers. The results reveal a diverse microbial community with syntrophic metabolisms both anaerobic (fermentation, methanogenesis, sulphate and nitrate reduction) and aerobic (methanotrophy, sulphur oxidation). The presence of oxygen-scavenging microbes might indicate that the system is modified by the artificial oxygen inputs

  18. Deciphering the Prokaryotic Community and Metabolisms in South African Deep-Mine Biofilms through Antibody Microarrays and Graph Theory

    PubMed Central

    García-Moyano, Antonio; Aguirre, Jacobo; Cruz-Gil, Patricia; Palacín, Arantxa; van Heerden, Esta; Parro, Víctor

    2014-01-01

    In the South African deep mines, a variety of biofilms growing in mine corridor walls as water seeps from intersections or from fractures represents excellent proxies for deep-subsurface environments. However, they may be greatly affected by the oxygen inputs through the galleries of mining activities. As a consequence, the interaction between the anaerobic water coming out from the walls with the oxygen inputs creates new conditions that support rich microbial communities. The inherent difficulties for sampling these delicate habitats, together with transport and storage conditions may alter the community features and composition. Therefore, the development of in situ monitoring methods would be desirable for quick evaluation of the microbial community. In this work, we report the usefulness of an antibody-microarray (EMChip66) immunoassay for a quick check of the microbial diversity of biofilms located at 1.3 km below surface within the Beatrix deep gold mine (South Africa). In addition, a deconvolution method, previously described and used for environmental monitoring, based on graph theory and applied on antibody cross-reactivity was used to interpret the immunoassay results. The results were corroborated and further expanded by 16S rRNA gene sequencing analysis. Both culture-independent techniques coincided in detecting features related to aerobic sulfur-oxidizers, aerobic chemoorganotrophic Alphaproteobacteria and metanotrophic Gammaproteobacteria. 16S rRNA gene sequencing detected phylotypes related to nitrate-reducers and anaerobic sulfur-oxidizers, whereas the EMChip66 detected immunological features from methanogens and sulfate-reducers. The results reveal a diverse microbial community with syntrophic metabolisms both anaerobic (fermentation, methanogenesis, sulphate and nitrate reduction) and aerobic (methanotrophy, sulphur oxidation). The presence of oxygen-scavenging microbes might indicate that the system is modified by the artificial oxygen inputs

  19. Outcome Based Screening for Prognostic Phospho-RTK (Receptor Tyrosine Kinase) Antibodies Using Tissue Microarrays)

    DTIC Science & Technology

    2004-08-01

    urokinase - type plasminogen activator ; PAl. plasminogen activator bated overnight at 4°C, with the exception of antibodies to ERs, PRs, and Her2...Lee. S. L., Dickson, R. B .. and Lin, C. Y. Activation of hepatocyte growth factor andtcascade, PAl, i urokinase / plasminogen activator by matriptase, an...Genet., 16: 68 -73. 1997. J. A. Pooled analysis of prognostic impact of urokinase - type plasminogen activator 19. Lee. 1. H.. Han, S.

  20. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

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

  1. Microarray analysis of gene expression in medicinal plant research.

    PubMed

    Youns, M; Efferth, T; Hoheisel, J D

    2009-10-01

    Expression profiling analysis offers great opportunities for the identification of novel molecular targets, drug discovery, development, and validation. The beauty of microarray analysis of gene expression is that it can be used to screen the expression of tens of thousands of genes in parallel and to identify appropriate molecular targets for therapeutic intervention. Toward identifying novel therapeutic options, natural products, notably from medicinal plants used in traditional Chinese medicine (TCM), have been thoroughly investigated. Increased knowledge of the molecular mechanisms of TCM-derived drugs could be achieved through application of modern molecular technologies including transcript profiling. In the present review, we introduce a brief introduction to the field of microarray technology and disclose its role in target identification and validation. Moreover, we provide examples for applications regarding molecular target discovery in medicinal plants derived TCM. This could be an attractive strategy for the development of novel and improved therapeutics.

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

    PubMed

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

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

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

    PubMed Central

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-01-01

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

  4. Analysis of variance of microarray data.

    PubMed

    Ayroles, Julien F; Gibson, Greg

    2006-01-01

    Analysis of variance (ANOVA) is an approach used to identify differentially expressed genes in complex experimental designs. It is based on testing for the significance of the magnitude of effect of two or more treatments taking into account the variance within and between treatment classes. ANOVA is a highly flexible analytical approach that allows investigators to simultaneously assess the contributions of multiple factors to gene expression variation, including technical (dye, batch) effects and biological (sex, genotype, drug, time) ones, as well as interactions between factors. This chapter provides an overview of the theory of linear mixture modeling and the sequence of steps involved in fitting gene-specific models and discusses essential features of experimental design. Commercial and open-source software for performing ANOVA is widely available.

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

    PubMed Central

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

    2015-01-01

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

  6. Microarray-based MALDI-TOF mass spectrometry enables monitoring of monoclonal antibody production in batch and perfusion cell cultures.

    PubMed

    Steinhoff, Robert F; Karst, Daniel J; Steinebach, Fabian; Kopp, Marie R G; Schmidt, Gregor W; Stettler, Alexander; Krismer, Jasmin; Soos, Miroslav; Pabst, Martin; Hierlemann, Andreas; Morbidelli, Massimo; Zenobi, Renato

    2016-07-15

    Cell culture process monitoring in monoclonal antibody (mAb) production is essential for efficient process development and process optimization. Currently employed online, at line and offline methods for monitoring productivity as well as process reproducibility have their individual strengths and limitations. Here, we describe a matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS)-based on a microarray for mass spectrometry (MAMS) technology to rapidly monitor a broad panel of analytes, including metabolites and proteins directly from the unpurified cell supernatant or from host cell culture lysates. The antibody titer is determined from the intact antibody mass spectra signal intensity relative to an internal protein standard spiked into the supernatant. The method allows a semi-quantitative determination of light and heavy chains. Intracellular mass profiles for metabolites and proteins can be used to track cellular growth and cell productivity. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    PubMed Central

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

    2016-01-01

    Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and

  8. Microarray Analysis of Pneumococcal Gene Expression during Invasive Disease

    PubMed Central

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

    2004-01-01

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

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

    PubMed Central

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

    2010-01-01

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

  10. Automated target preparation for microarray-based gene expression analysis.

    PubMed

    Raymond, Frédéric; Metairon, Sylviane; Borner, Roland; Hofmann, Markus; Kussmann, Martin

    2006-09-15

    DNA microarrays have rapidly evolved toward a platform for massively paralleled gene expression analysis. Despite its widespread use, the technology has been criticized to be vulnerable to technical variability. Addressing this issue, recent comparative, interplatform, and interlaboratory studies have revealed that, given defined procedures for "wet lab" experiments and data processing, a satisfactory reproducibility and little experimental variability can be achieved. In view of these advances in standardization, the requirement for uniform sample preparation becomes evident, especially if a microarray platform is used as a facility, i.e., by different users working in the laboratory. While one option to reduce technical variability is to dedicate one laboratory technician to all microarray studies, we have decided to automate the entire RNA sample preparation implementing a liquid handling system coupled to a thermocycler and a microtiter plate reader. Indeed, automated RNA sample preparation prior to chip analysis enables (1) the reduction of experimentally caused result variability, (2) the separation of (important) biological variability from (undesired) experimental variation, and (3) interstudy comparison of gene expression results. Our robotic platform can process up to 24 samples in parallel, using an automated sample preparation method that produces high-quality biotin-labeled cRNA ready to be hybridized on Affymetrix GeneChips. The results show that the technical interexperiment variation is less pronounced than with manually prepared samples. Moreover, experiments using the same starting material showed that the automated process yields a good reproducibility between samples.

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

    PubMed

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

    2012-12-18

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

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

    PubMed Central

    2012-01-01

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

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

    PubMed Central

    2009-01-01

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

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

    PubMed

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

    2009-07-01

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

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

    PubMed

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

    2011-04-01

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

  16. Signal enhancement in antibody microarrays using quantum dots nanocrystals: application to potential Alzheimer's disease biomarker screening.

    PubMed

    Morales-Narváez, Eden; Montón, Helena; Fomicheva, Anna; Merkoçi, Arben

    2012-08-07

    The performance of cadmium-selenide/zinc-sulfide (CdSe@ZnS) quantum dots (QDs) and the fluorescent dye Alexa 647 as reporter in an assay designed to detect apolipoprotein E (ApoE) has been compared. The assay is a sandwich immunocomplex microarray that functions via excitation by visible light. ApoE was chosen for its potential as a biomarker for Alzheimer's disease. The two versions of the microarray (QD or Alexa 647) were assessed under the same experimental conditions and then compared to a conventional enzyme-linked immunosorbent assay (ELISA) targeting ApoE. The QDs proved to be highly effective reporters in the microarrays, although their performance strongly varied in function of the excitation wavelength. At 633 nm, the QD microarray gave a limit of detection (LOD) of ~247 pg mL(-1); however, at an excitation wavelength of 532 nm, it provided a LOD of ~62 pg mL(-1), five times more sensitive than that of the Alexa microarray (~307 pg mL(-1)) and seven times more than that of the ELISA (~470 pg mL(-1)). Finally, serial dilutions from a human serum sample were assayed with high sensitivity and acceptable precision and accuracy.

  17. Improved porous silicon (P-Si) microarray based PSA (prostate specific antigen) immunoassay by optimized surface density of the capture antibody

    PubMed Central

    Lee, SangWook; Kim, Soyoun; Malm, Johan; Jeong, Ok Chan; Lilja, Hans; Laurell, Thomas

    2014-01-01

    Enriching the surface density of immobilized capture antibodies enhances the detection signal of antibody sandwich microarrays. In this study, we improved the detection sensitivity of our previously developed P-Si (porous silicon) antibody microarray by optimizing concentrations of the capturing antibody. We investigated immunoassays using a P-Si microarray at three different capture antibody (PSA - prostate specific antigen) concentrations, analyzing the influence of the antibody density on the assay detection sensitivity. The LOD (limit of detection) for PSA was 2.5ngmL−1, 80pgmL−1, and 800fgmL−1 when arraying the PSA antibody, H117 at the concentration 15µgmL−1, 35µgmL−1 and 154µgmL−1, respectively. We further investigated PSA spiked into human female serum in the range of 800fgmL−1 to 500ngmL−1. The microarray showed a LOD of 800fgmL−1 and a dynamic range of 800 fgmL−1 to 80ngmL−1 in serum spiked samples. PMID:24016590

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

    PubMed

    Ishihara, Takeaki; Sato, Yukiyo; Takahashi, Hideki

    2015-01-01

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

  19. Diagnostic challenges for multiplexed protein microarrays.

    PubMed

    Master, Stephen R; Bierl, Charlene; Kricka, Larry J

    2006-11-01

    Multiplexed protein analysis using planar microarrays or microbeads is growing in popularity for simultaneous assays of antibodies, cytokines, allergens, drugs and hormones. However, this new assay format presents several new operational issues for the clinical laboratory, such as the quality control of protein-microarray-based assays, the release of unrequested test data and the use of diagnostic algorithms to transform microarray data into diagnostic results.

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

    DTIC Science & Technology

    2006-04-27

    SRM117, 1026b, and 576 (micromoles of rhamnose equivalents per milliliter) were 3.6, 16.0, 3.6, and 3.5, respectively. We also used inulin (Sigma...the rabbit antiserum did not react with inulin , the polysaccharide used as a negative control. Furthermore, using this microarray, we are able to

  1. Supervised group Lasso with applications to microarray data analysis

    PubMed Central

    Ma, Shuangge; Song, Xiao; Huang, Jian

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Tchagang, Alain B.; Tewfik, Ahmed H.

    2006-12-01

    Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

  3. Using antibodies against ATPase and microarray immunoassays for the search for potential extraterrestrial life in saline environments on Mars.

    NASA Astrophysics Data System (ADS)

    Weigl, Andreas; Gruber, Claudia; Blanco-López, Yolanda; Rivas, Luis A.; Parro, Victor; Stan-Lotter, Helga

    2010-05-01

    membrane fraction and whole cell preparation of Halobacterium salinarum NRC-1, Escherichia coli LE392 as well as the whole cell fraction of Halorubrum saccharovorum and Bacillus megaterium. Further experiments with antibodies against ATPase are proposed to be done with procedures that are more adjusted to the search for extraterrestrial life. Therefore tests with a microarray system (Rivas et al., 2008) were done at the Centro de Astrobiología in Madrid. Cellular extracts of environmental samples from a sea salt from Piranske (Slovenia) and a rock salt from Himalaya (Pakistan) were tested with a "supermix" of 300 antibodies, additionally including an antibody against the subunit A of the A-ATPase from Halorubrum sacharovorum. Positive immuno reactions with antibodies against halophile cells as well as antibodies against exopolysaccharides could be shown. (1)Gruber C, Stan-Lotter H (1997) Western blot of stained proteins from dried polyacrylamide gels. Anal Biochem 253, 125-127. (2)Rivas LA, Garcia-Villadangos M, Moreno-Paz M, Cruz-Gil P, Gómez-Elvira J, Parro V (2008) A 200-antibody microarray biochip for environmental monitoring: searching for universal microbial biomarkers through immunoprofiling. Anal Chem 80, 7970-7979

  4. Microarray analysis of mRNAs: experimental design and data analysis fundamentals.

    PubMed

    Mehta, Jai Prakash

    2011-01-01

    Microarray technology has made it possible to quantify gene expression of thousands of genes in a single experiment. With the technological advancement, it is now possible to quantify expression of all known genes using a single microarray chip. With this volume of data and the possibility of improper quantification of expression beyond our control, the challenge lies in appropriate experimental design and the data analysis.This chapter describes the different types of experimental design for experiments involving microarray analysis (with their specific advantages and disadvantages). It considers the optimum number of replicates for a particular type of experiment. Additionally, this chapter describes the fundamentals of data analysis and the data analysis pipeline to be followed in most common types of microarray experiment.

  5. Comparison of microarray and sage techniques in gene expression analysis of human glioblastoma.

    PubMed

    Kavsan, V M; Dmitrenko, V V; Shostak, K O; Bukreieva, T V; Vitak, N Y; Simirenko, O E; Malisheva, T A; Shamayev, M I; Rozumenko, V D; Zozulya, Y A

    2007-01-01

    To enhance glioblastoma (GB) marker discovery we compared gene expression in GB with human normal brain (NB) by accessing SAGE Genie web site and compared obtained results with published data. Nine GB and five NB SAGE-libraries were analyzed using the Digital Gene Expression Displayer (DGED), the results of DGED were tested by Northern blot analysis and RT-PCR of arbitrary selected genes. Review of available data from the articles on gene expression profiling by microarray-based hybridization showed as few as 35 overlapped genes with increased expression in GB. Some of them were identified in four articles, but most genes in three or even in two investigations. There was found also some differences between SAGE results of GB analysis. Digital Gene Expression Displayer approach revealed 676 genes differentially expressed in GB vs. NB with cut-off ratio: twofold change and P < or = 0.05. Differential expression of selectedgenes obtained by DGED was confirmed by Northern analysis and RT-PCR. Altogether, only 105 of 955 genes presented in published investigations were among the genes obtained by DGED. Comparison of the results obtained by microarrays and SAGE is very complicated because authors present only the most prominent differentially expressed genes. However, even available data give quite poor overlapping of genes revealed by microarrays. Some differences between results obtained by SAGE in different investigations can be explained by high dependence on the statistical methods used. As for now, the best solution to search for molecular tumor markers is to compare all available results and to select only those genes, which significant expression in tumor combined with very low expression in normal tissues was reproduced in several articles. 105 differentially expressed genes, common to both methods, can be included in the list of candidates for the molecular typing of GBs. Some genes, encoded cell surface or extra-cellular proteins may be useful for targeting

  6. Structural analysis of hepatitis C RNA genome using DNA microarrays

    PubMed Central

    Martell, María; Briones, Carlos; de Vicente, Aránzazu; Piron, María; Esteban, Juan I.; Esteban, Rafael; Guardia, Jaime; Gómez, Jordi

    2004-01-01

    Many studies have tried to identify specific nucleotide sequences in the quasispecies of hepatitis C virus (HCV) that determine resistance or sensitivity to interferon (IFN) therapy, unfortunately without conclusive results. Although viral proteins represent the most evident phenotype of the virus, genomic RNA sequences determine secondary and tertiary structures which are also part of the viral phenotype and can be involved in important biological roles. In this work, a method of RNA structure analysis has been developed based on the hybridization of labelled HCV transcripts to microarrays of complementary DNA oligonucleotides. Hybridizations were carried out at non-denaturing conditions, using appropriate temperature and buffer composition to allow binding to the immobilized probes of the RNA transcript without disturbing its secondary/tertiary structural motifs. Oligonucleotides printed onto the microarray covered the entire 5′ non-coding region (5′NCR), the first three-quarters of the core region, the E2–NS2 junction and the first 400 nt of the NS3 region. We document the use of this methodology to analyse the structural degree of a large region of HCV genomic RNA in two genotypes associated with different responses to IFN treatment. The results reported here show different structural degree along the genome regions analysed, and differential hybridization patterns for distinct genotypes in NS2 and NS3 HCV regions. PMID:15247323

  7. Exon Microarray Analysis of Human Dorsolateral Prefrontal Cortex in Alcoholism

    PubMed Central

    Manzardo, Ann M.; Gunewardena, Sumedha; Wang, Kun; Butler, Merlin G.

    2014-01-01

    Background Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Methods Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC, Brodmann area 9) of 7 adult Alcoholic (6 males, 1 female, mean age 48 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST Array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using qRT-PCR, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Results Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN) and signaling (e.g., RASGRP, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease, and development including cellular assembly and organization impacting on psychological disorders. Conclusions Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation and signaling that targets white matter of the brain. PMID:24890784

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

    SciTech Connect

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

    2001-02-01

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

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

    PubMed

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

    2014-01-25

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

  10. Analysis of recursive gene selection approaches from microarray data.

    PubMed

    Li, Fan; Yang, Yiming

    2005-10-01

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

  11. Using Kepler for Tool Integration in Microarray Analysis Workflows.

    PubMed

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

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

  12. Analysis of Mycobacterium leprae gene expression using DNA microarray.

    PubMed

    Akama, Takeshi; Tanigawa, Kazunari; Kawashima, Akira; Wu, Huhehasi; Ishii, Norihisa; Suzuki, Koichi

    2010-10-01

    Mycobacterium leprae, the causative agent of leprosy, does not grow under in vitro condition, making molecular analysis of this bacterium difficult. For this reason, bacteriological information regarding M. leprae gene function is limited compared with other mycobacterium species. In this study, we performed DNA microarray analysis to clarify the RNA expression profile of the Thai53 strain of M. leprae grown in footpads of hypertensive nude rats (SHR/NCrj-rnu). Of 1605 M. leprae genes, 315 showed signal intensity twofold higher than the median. These genes include Acyl-CoA metabolic enzymes and drug metabolic enzymes, which might be related to the virulence of M. leprae. In addition, consecutive RNA expression profile and in silico analyses enabled identification of possible operons within the M. leprae genome. The present results will shed light on M. leprae gene function and further our understanding of the pathogenesis of leprosy.

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

    PubMed

    Wu, Bin; Wang, Jianguo; Wang, Miqu

    2007-12-01

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

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

    PubMed

    Zhang, Zhe; Fenstermacher, David

    2005-01-01

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

  15. Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

    PubMed

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

    2015-10-06

    Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

  16. Segment and Fit Thresholding: A New Method for Image Analysis Applied to Microarray and Immunofluorescence Data

    PubMed Central

    Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M.; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E.; Allen, Peter J.; Sempere, Lorenzo F.; Haab, Brian B.

    2016-01-01

    Certain experiments involve the high-throughput quantification of image data, thus requiring algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multi-color, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu’s method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

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

    PubMed

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

    2016-11-30

    The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.

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

    PubMed Central

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

    2016-01-01

    The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs. PMID:27916881

  19. Immune recognition surface construction of Mycobacterium tuberculosis epitope-specific antibody responses in tuberculosis patients identified by peptide microarrays.

    PubMed

    Valentini, Davide; Rao, Martin; Ferrara, Giovanni; Perkins, Marc; Dodoo, Ernest; Zumla, Alimuddin; Maeurer, Markus

    2017-03-01

    Understanding of humoral immune responses in tuberculosis (TB) is gaining interest, since B-cells and antibodies may be important in diagnosis as well as protective immune responses. High-content peptide microarrays (HCPM) are highly precise and reliable for gauging specific antibody responses to pathogens, as well as autoantigens. An HCPM comprising epitopes spanning 154 proteins of Mycobacterium tuberculosis was used to gauge specific IgG antibody responses in sera of TB patients from Africa and South America. Open source software for general access to this method is provided. The IgG response pattern of TB patients differs from that of healthy individuals, with the molecular complexity of the antigens influencing the strength of recognition. South American individuals with or without TB exhibited a generally stronger serum IgG response to the tested M. tuberculosis antigens compared to their African counterparts. Individual M. tuberculosis peptide targets were defined, segregating patients with TB from Africa versus those from South America. These data reveal the heterogeneity of epitope-dependent humoral immune responses in TB patients, partly due to geographical setting. These findings expose a new avenue for mining clinically meaningful vaccine targets, diagnostic tools, and the development of immunotherapeutics in TB disease management or prevention. Copyright © 2017. Published by Elsevier Ltd.

  20. Targeted Deposition of Antibodies on a Multiplex CMOS Microarray and Optimization of a Sensitive Immunoassay Using Electrochemical Detection

    PubMed Central

    Cooper, John; Yazvenko, Nina; Peyvan, Kia; Maurer, Karl; Taitt, Chris R.; Lyon, Wanda; Danley, David L.

    2010-01-01

    Background The CombiMatrix ElectraSense® microarray is a highly multiplex, complementary metal oxide semiconductor with 12,544 electrodes that are individually addressable. This platform is commercially available as a custom DNA microarray; and, in this configuration, it has also been used to tether antibodies (Abs) specifically on electrodes using complementary DNA sequences conjugated to the Abs. Methodology/Principal Findings An empirical method is described for developing and optimizing immunoassays on the CombiMatrix ElectraSense® microarray based upon targeted deposition of polypyrrole (Ppy) and capture Ab. This process was automated using instrumentation that can selectively apply a potential or current to individual electrodes and also measure current generated at the electrodes by an enzyme-enhanced electrochemical (ECD) reaction. By designating groups of electrodes on the array for different Ppy deposition conditions, we determined that the sensitivity and specificity of a sandwich immunoassay for staphylococcal enterotoxin B (SEB) is influenced by the application of different voltages or currents and the application time. The sandwich immunoassay used a capture Ab adsorbed to the Ppy and a reporter Ab labeled for fluorescence detection or ECD, and results from these methods of detection were different. Conclusions/Significance Using Ppy deposition conditions for optimum results, the lower limit of detection for SEB using the ECD assay was between 0.003 and 0.01 pg/ml, which represents an order of magnitude improvement over a conventional enzyme-linked immunosorbant assay. In the absence of understanding the variables and complexities that affect assay performance, this highly multiplexed electrode array provided a rapid, high throughput, and empirical approach for developing a sensitive immunoassay. PMID:20333309

  1. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    PubMed Central

    Warnat, Patrick; Eils, Roland; Brors, Benedikt

    2005-01-01

    Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85%) were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and microarray technologies

  2. The application of phenotypic microarray analysis to anti-fungal drug development.

    PubMed

    Greetham, Darren; Lappin, David F; Rajendran, Ranjith; O'Donnell, Lindsay; Sherry, Leighann; Ramage, Gordon; Nile, Christopher

    2017-03-01

    Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.

  3. Experimental Approaches to Microarray Analysis of Tumor Samples

    ERIC Educational Resources Information Center

    Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

    2008-01-01

    Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

  4. Experimental Approaches to Microarray Analysis of Tumor Samples

    ERIC Educational Resources Information Center

    Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

    2008-01-01

    Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

  5. Exon microarray analysis of human dorsolateral prefrontal cortex in alcoholism.

    PubMed

    Manzardo, Ann M; Gunewardena, Sumedha; Wang, Kun; Butler, Merlin G

    2014-06-01

    Alcohol abuse is associated with cellular and biochemical disturbances that impact upon protein and nucleic acid synthesis, brain development, function, and behavioral responses. To further characterize the genetic influences in alcoholism and the effects of alcohol consumption on gene expression, we used a highly sensitive exon microarray to examine mRNA expression in human frontal cortex of alcoholics and control males. Messenger RNA was isolated from the dorsolateral prefrontal cortex (dlPFC; Brodmann area 9) of 7 adult alcoholic (6 males, 1 female, mean age 49 years) and 7 matched controls. Affymetrix Human Exon 1.0 ST array was performed according to standard procedures and the results analyzed at the gene level. Microarray findings were validated using quantitative reverse transcription polymerase chain reaction, and the ontology of disturbed genes characterized using Ingenuity Pathway Analysis (IPA). Decreased mRNA expression was observed for genes involved in cellular adhesion (e.g., CTNNA3, ITGA2), transport (e.g., TF, ABCA8), nervous system development (e.g., LRP2, UGT8, GLDN), and signaling (e.g., RASGRP3, LGR5) with influence over lipid and myelin synthesis (e.g., ASPA, ENPP2, KLK6). IPA identified disturbances in network functions associated with neurological disease and development including cellular assembly and organization impacting on psychological disorders. Our data in alcoholism support a reduction in expression of dlPFC mRNA for genes involved with neuronal growth, differentiation, and signaling that targets white matter of the brain. Copyright © 2014 by the Research Society on Alcoholism.

  6. On the Statics for Micro-Array Data Analysis

    NASA Astrophysics Data System (ADS)

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

    2010-01-01

    data, we might get a different result because the distinct definition for micro array data has not been set yet. It means that from the same data we will get different results depending on researchers. We are afraid that this problem will have a big effect on developing new medicines and to progress the next step, like a 2nd screening. So, we suggest that we should have certain guidelines to analyze Micro-Array data validly with statistic method and it will surely be helpful for Micro-Array analysis for medical studies in the future.

  7. Inferring epitopes of a polymorphic antigen amidst broadly cross-reactive antibodies using protein microarrays: a study of OspC proteins of Borrelia burgdorferi.

    PubMed

    Baum, Elisabeth; Randall, Arlo Z; Zeller, Michael; Barbour, Alan G

    2013-01-01

    Epitope mapping studies aim to identify the binding sites of antibody-antigen interactions to enhance the development of vaccines, diagnostics and immunotherapeutic compounds. However, mapping is a laborious process employing time- and resource-consuming 'wet bench' techniques or epitope prediction software that are still in their infancy. For polymorphic antigens, another challenge is characterizing cross-reactivity between epitopes, teasing out distinctions between broadly cross-reactive responses, limited cross-reactions among variants and the truly type-specific responses. A refined understanding of cross-reactive antibody binding could guide the selection of the most informative subsets of variants for diagnostics and multivalent subunit vaccines. We explored the antibody binding reactivity of sera from human patients and Peromyscus leucopus rodents infected with Borrelia burgdorferi to the polymorphic outer surface protein C (OspC), an attractive candidate antigen for vaccine and improved diagnostics for Lyme disease. We constructed a protein microarray displaying 23 natural variants of OspC and quantified the degree of cross-reactive antibody binding between all pairs of variants, using Pearson correlation calculated on the reactivity values using three independent transforms of the raw data: (1) logarithmic, (2) rank, and (3) binary indicators. We observed that the global amino acid sequence identity between OspC pairs was a poor predictor of cross-reactive antibody binding. Then we asked if specific regions of the protein would better explain the observed cross-reactive binding and performed in silico screening of the linear sequence and 3-dimensional structure of OspC. This analysis pointed to residues 179 through 188 the fifth C-terminal helix of the structure as a major determinant of type-specific cross-reactive antibody binding. We developed bioinformatics methods to systematically analyze the relationship between local sequence/structure variation

  8. An antibody microarray, in multiwell plate format, for multiplex screening of foodborne pathogenic bacteria and biomolecules

    USDA-ARS?s Scientific Manuscript database

    Intoxication and infection caused by foodborne pathogens are important problems in the United States, and screening tests for multiple pathogen detection have been developed because food producers are known reservoirs of multiple pathogens. We developed a 96-well microplate, multiplex antibody micr...

  9. Application of microarray analysis on computer cluster and cloud platforms.

    PubMed

    Bernau, C; Boulesteix, A-L; Knaus, J

    2013-01-01

    Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

  10. Rapid and Sensitive Multiplex Detection of Burkholderia pseudomallei-Specific Antibodies in Melioidosis Patients Based on a Protein Microarray Approach

    PubMed Central

    Kohler, Christian; Dunachie, Susanna J.; Müller, Elke; Kohler, Anne; Jenjaroen, Kemajittra; Teparrukkul, Prapit; Baier, Vico; Ehricht, Ralf; Steinmetz, Ivo

    2016-01-01

    Background The environmental bacterium Burkholderia pseudomallei causes the infectious disease melioidosis with a high case-fatality rate in tropical and subtropical regions. Direct pathogen detection can be difficult, and therefore an indirect serological test which might aid early diagnosis is desirable. However, current tests for antibodies against B. pseudomallei, including the reference indirect haemagglutination assay (IHA), lack sensitivity, specificity and standardization. Consequently, serological tests currently do not play a role in the diagnosis of melioidosis in endemic areas. Recently, a number of promising diagnostic antigens have been identified, but a standardized, easy-to-perform clinical laboratory test for sensitive multiplex detection of antibodies against B. pseudomallei is still lacking. Methods and Principal Findings In this study, we developed and validated a protein microarray which can be used in a standard 96-well format. Our array contains 20 recombinant and purified B. pseudomallei proteins, previously identified as serodiagnostic candidates in melioidosis. In total, we analyzed 196 sera and plasmas from melioidosis patients from northeast Thailand and 210 negative controls from melioidosis-endemic and non-endemic regions. Our protein array clearly discriminated between sera from melioidosis patients and controls with a specificity of 97%. Importantly, the array showed a higher sensitivity than did the IHA in melioidosis patients upon admission (cut-off IHA titer ≥1:160: IHA 57.3%, protein array: 86.7%; p = 0.0001). Testing of sera from single patients at 0, 12 and 52 weeks post-admission revealed that protein antigens induce either a short- or long-term antibody response. Conclusions Our protein array provides a standardized, rapid, easy-to-perform test for the detection of B. pseudomallei-specific antibody patterns. Thus, this system has the potential to improve the serodiagnosis of melioidosis in clinical settings. Moreover, our

  11. GENEVESTIGATOR. Arabidopsis Microarray Database and Analysis Toolbox1[w

    PubMed Central

    Zimmermann, Philip; Hirsch-Hoffmann, Matthias; Hennig, Lars; Gruissem, Wilhelm

    2004-01-01

    High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch. PMID:15375207

  12. Fabrication of Homogeneous High-Density Antibody Microarrays for Cytokine Detection

    PubMed Central

    Hospach, Ingeborg; Joseph, Yvonne; Mai, Michaela Kathrin; Krasteva, Nadejda; Nelles, Gabriele

    2014-01-01

    Cytokine proteins are known as biomarker molecules, characteristic of a disease or specific body condition. Monitoring of the cytokine pattern in body fluids can contribute to the diagnosis of diseases. Here we report on the development of an array comprised of different anti-cytokine antibodies on an activated solid support coupled with a fluorescence readout mechanism. Optimization of the array preparation was done in regard of spot homogeneity and spot size. The proinflammatory cytokines Tumor Necrosis Factor alpha (TNFα) and Interleukin 6 (IL-6) were chosen as the first targets of interest. First, the solid support for covalent antibody immobilization and an adequate fluorescent label were selected. Three differently functionalized glass substrates for spotting were compared: amine and epoxy, both having a two-dimensional structure, and the NHS functionalized hydrogel (NHS-3D). The NHS-hydrogel functionalization of the substrate was best suited to antibody immobilization. Then, the optimization of plotting parameters and geometry as well as buffer media were investigated, considering the ambient analyte theory of Roger Ekins. As a first step towards real sample studies, a proof of principle of cytokine detection has been established. PMID:27600349

  13. A comparative analysis of DNA barcode microarray feature size

    PubMed Central

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

    2009-01-01

    Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density), but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO) collection used for screens of pooled yeast (Saccharomyces cerevisiae) deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density. PMID:19825181

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

    SciTech Connect

    Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong

    2008-08-15

    Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.

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

    PubMed Central

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

    2012-01-01

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

  16. Microarray platform affords improved product analysis in mammalian cell growth studies

    PubMed Central

    Li, Lingyun; Migliore, Nicole; Schaefer, Eugene; Sharfstein, Susan T.; Dordick, Jonathan S.; Linhardt, Robert J.

    2014-01-01

    High throughput (HT) platforms serve as cost-efficient and rapid screening method for evaluating the effect of cell culture conditions and screening of chemicals. The aim of the current study was to develop a high-throughput cell-based microarray platform to assess the effect of culture conditions on Chinese hamster ovary (CHO) cells. Specifically, growth, transgene expression and metabolism of a GS/MSX CHO cell line, which produces a therapeutic monoclonal antibody, was examined using microarray system in conjunction with conventional shake flask platform in a non-proprietary medium. The microarray system consists of 60 nl spots of cells encapsulated in alginate and separated in groups via an 8-well chamber system attached to the chip. Results show the non-proprietary medium developed allows cell growth, production and normal glycosylation of recombinant antibody and metabolism of the recombinant CHO cells in both the microarray and shake flask platforms. In addition, 10.3 mM glutamate addition to the defined base media results in lactate metabolism shift in the recombinant GS/MSX CHO cells in the shake flask platform. Ultimately, the results demonstrate that the high-throughput microarray platform has the potential to be utilized for evaluating the impact of media additives on cellular processes, such as, cell growth, metabolism and productivity. PMID:24227746

  17. ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments

    PubMed Central

    Dickson, B.M.; Cornett, E.M.; Ramjan, Z.; Rothbart, S.B.

    2017-01-01

    Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. PMID:27423857

  18. Microarray analysis of Xenopus endoderm expressing Ptf1a

    PubMed Central

    Bilogan, Cassandra K.; Horb, Marko E.

    2012-01-01

    Pancreas specific transcription factor 1a (Ptf1a), a bHLH transcription factor, has two temporally distinct functions during pancreas development; initially it is required for early specification of the entire pancreas, while later it is required for proper differentiation and maintenance of only acinar cells. The importance of Ptf1a function was revealed by the fact that loss of Ptf1a leads to pancreas agenesis in humans. While Ptf1a is one of the most important pancreatic transcription factors, little is known about the differences between the regulatory networks it controls during initial specification of the pancreas as opposed to acinar cell development, and to date no comprehensive analysis of its downstream targets has been published. In this paper, we use Xenopus embryos to identify putative downstream targets of Ptf1a. We isolated anterior endoderm tissue overexpressing Ptf1a at two early stages, NF32 and NF36, and compared their gene expression profiles using microarrays. Our results revealed that Ptf1a regulates genes with a wide variety of functions, providing insight into the complexity of the regulatory network required for pancreas specification. PMID:22815262

  19. Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

    PubMed Central

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

    2015-01-01

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

  20. Glycan microarray analysis of Candida glabrata adhesin ligand specificity.

    PubMed

    Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P

    2008-05-01

    The Candida glabrata genome encodes at least 23 members of the EPA (epithelial adhesin) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate-binding specificities. Using Saccharomyces cerevisiae strains surface-expressing the N-terminal ligand-binding domain of the Epa proteins, we found that the three Epa family members functionally identified as adhesins in Candida glabrata (Epa1, Epa6 and Epa7) bind to ligands containing a terminal galactose residue. However, the specificity of the three proteins for glycans within this class varies, with Epa6 having a broader specificity range than Epa1 or Epa7. This result is intriguing given the close homology between Epa6 and Epa7, which are 92% identical at the amino acid level. We have mapped a five-amino-acid region within the N-terminal ligand-binding domain that accounts for the difference in specificity of Epa6 and Epa7 and show that these residues contribute to adherence to both epithelial and endothelial cell lines in vitro.

  1. Xylella fastidiosa gene expression analysis by DNA microarrays

    PubMed Central

    2009-01-01

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

  2. Microarray analysis of human epithelial cell responses to bacterial interaction.

    PubMed

    Mans, Jeffrey J; Lamont, Richard J; Handfield, Martin

    2006-09-01

    Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has--until recently--held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.

  3. Tissue MicroArray (TMA) analysis of normal and persistent Chlamydophila pneumoniae infection.

    PubMed

    Borel, Nicole; Mukhopadhyay, Sanghamitra; Kaiser, Carmen; Sullivan, Erin D; Miller, Richard D; Timms, Peter; Summersgill, James T; Ramirez, Julio A; Pospischil, Andreas

    2006-10-19

    Chlamydophila pneumoniae infection has been implicated as a potential risk factor for atherosclerosis, however the mechanism leading to persistent infection and its role in the disease process remains to be elucidated. We validated the use of tissue microarray (TMA) technology, in combination with immunohistochemistry (IHC), to test antibodies (GroEL, GroES, GspD, Ndk and Pyk) raised against differentially expressed proteins under an interferon-gamma (IFN-gamma) induced model of chlamydial persistence. In the cell pellet array, we were able to identify differences in protein expression patterns between untreated and IFN-gamma treated samples. Typical, large chlamydial inclusions could be observed in the untreated samples with all antibodies, whereas the number of inclusions were decreased and were smaller and atypical in shape in the IFN-gamma treated samples. The staining results obtained with the TMA method were generally similar to the changes observed between normal and IFN-gamma persistence using proteomic analysis. Subsequently, it was shown in a second TMA including archival atheromatous heart tissues from 12 patients undergoing heart transplantation, that GroEL, GroES, GspD and Pyk were expressed in atheromatous heart tissue specimens as well, and were detectable morphologically within lesions by IHC. TMA technology proved useful in documenting functional proteomics data with the morphologic distribution of GroEL, GroES, GspD, Ndk and Pyk within formalin-fixed, paraffin-embedded cell pellets and tissues from patients with severe coronary atherosclerosis. The antibodies GroEL and GroES, which were upregulated under persistence in proteomic analysis, displayed positive reaction in atheromatous heart tissue from 10 out of 12 patients. These may be useful markers for the detection of persistent infection in vitro and in vivo.

  4. A genome-wide 20 K citrus microarray for gene expression analysis

    PubMed Central

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-01-01

    Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to

  5. A genome-wide 20 K citrus microarray for gene expression analysis.

    PubMed

    Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

    2008-07-03

    Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in

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

    PubMed

    Siegmund, Kimberly D

    2011-06-01

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

  7. Multiplexed Salivary Protein Profiling for Patients with Respiratory Diseases using Fiber-Optic Bundles and Fluorescent Antibody-Based Microarrays

    PubMed Central

    Nie, Shuai; Benito-Peña, Elena; Zhang, Huaibin; Wu, Yue; Walt, David R.

    2013-01-01

    Over the past 40 years, the incidence and prevalence of respiratory diseases have increased significantly throughout the world, damaging economic productivity and challenging health care systems. Current diagnoses of different respiratory diseases generally involve invasive sampling methods such as induced sputum or bronchoalveolar lavage that are uncomfortable, or even painful, for the patient. In this paper, we present a platform incorporating fiber-optic bundles and antibody based microarrays to perform multiplexed protein profiling of a panel of six salivary biomarkers for asthma and cystic fibrosis (CF) diagnosis. The platform utilizes an optical fiber bundle containing approximately 50,000 individual 4.5 μm diameter fibers that are chemically etched to create microwells in which modified microspheres decorated with monoclonal capture antibodies can be deposited. Based on a sandwich immunoassay format, the array quantifies human vascular endothelial growth factor (VEGF), interferon gamma-induced protein 10 (IP-10), interleukin 8 (IL-8), epidermal growth factor (EGF), matrix metalloproteinase 9 (MMP-9), and interleukin 1 beta (IL-1β) salivary biomarkers in the sub-picomolar range. Saliva supernatants collected from 291 individuals (164 asthmatics, 71 CF patients, and 56 healthy controls (HC)) were analyzed on the platform to profile each group of patients using this six-analyte suite. It was found that four of the six proteins were observed to be significantly elevated (p<0.01) in asthma and CF patients compared with HC. These results demonstrate the potential to use the multiplexed protein array platform for respiratory disease diagnosis. PMID:23972398

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  10. Microarray gene expression analysis of uterosacral ligaments in uterine prolapse.

    PubMed

    Ak, Handan; Zeybek, Burak; Atay, Sevcan; Askar, Niyazi; Akdemir, Ali; Aydin, Hikmet Hakan

    2016-11-01

    Pelvic organ prolapse (POP) is a major health problem that impairs the quality of life with a wide clinical spectrum. Since the uterosacral ligaments provide primary support for the uterus and the upper vagina, we hypothesize that the disruption of these ligaments may lead to a loss of support and eventually contribute to POP. In this study, we therefore investigated whether there are any differences in the transcription profile of uterosacral ligaments in patients with POP when compared to those of the control samples. Seventeen women with POP and 8 non-POP controls undergoing hysterectomy for benign conditions were included in the study. Affymetrix® Gene Chip microarrays (Human Hu 133 plus 2.0) were used for whole genome gene expression profiling analysis. There was 1 significantly down-regulated gene, NKX2-3 in patients with POP compared to the controls (p=4.28464e-013). KIF11 gene was found to be significantly down-regulated in patients with ≥3 deliveries compared to patients with <3 deliveries (p=0.0156237). UGT1A1 (p=2.43388e-005), SCARB1 (p=1.19001e-006) and NKX2-3 (p=2.17966e-013) genes were found to be significantly down-regulated in the premenopausal patients compared to the premenopausal controls. UGT1A1 gene was also found to be significantly down-regulated in the post menopausal patients compared to the postmenopausal controls (p=0.0005). This study provides evidence for a significant down-regulation of the genes that take role in cell cycle, proliferation and embryonic development along with cell adhesion process on the development of POP for the first time. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  11. Differential analysis for high density tiling microarray data.

    PubMed

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

    2007-09-24

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

  12. “On silico” peptide microarrays for high-resolution mapping of antibody epitopes and diverse protein-protein interactions

    PubMed Central

    Price, Jordan V; Tangsombatvisit, Stephanie; Xu, Guangyu; Levy, Dan; Baechler, Emily C.; Gozani, Or; Varma, Madoo; Liu, Chih Long

    2011-01-01

    We have developed a novel, silicon-based peptide array for broad biological applications, including potential for development as a real-time point-of-care platform. We employed photolithography on silicon wafers to synthesize microarrays (Intel arrays), containing every possible overlapping peptide within a linear protein sequence covering the N-terminal tail of human histone H2B. Arrays also included peptides with acetylated and methylated lysine residues reflecting post-translational modifications of H2B. We defined minimum binding epitopes for commercial antibodies recognizing modified and unmodified H2B peptides. We further demonstrated that this platform is suitable for highly sensitive methyltransferase and kinase substrate characterization. Intel arrays also revealed specific H2B epitopes recognized by autoantibodies in individuals with systemic lupus erythematosus (SLE) that have increased disease severity. By combining emerging nonfluorescence-based detection methods with an underlying integrated circuit, we are now poised to create a truly transformative proteomics platform with applications in bioscience, drug development, and clinical diagnostics. PMID:22902875

  13. Speeding up the Consensus Clustering methodology for microarray data analysis

    PubMed Central

    2011-01-01

    Background The inference of the number of clusters in a dataset, a fundamental problem in Statistics, Data Analysis and Classification, is usually addressed via internal validation measures. The stated problem is quite difficult, in particular for microarrays, since the inferred prediction must be sensible enough to capture the inherent biological structure in a dataset, e.g., functionally related genes. Despite the rich literature present in that area, the identification of an internal validation measure that is both fast and precise has proved to be elusive. In order to partially fill this gap, we propose a speed-up of Consensus (Consensus Clustering), a methodology whose purpose is the provision of a prediction of the number of clusters in a dataset, together with a dissimilarity matrix (the consensus matrix) that can be used by clustering algorithms. As detailed in the remainder of the paper, Consensus is a natural candidate for a speed-up. Results Since the time-precision performance of Consensus depends on two parameters, our first task is to show that a simple adjustment of the parameters is not enough to obtain a good precision-time trade-off. Our second task is to provide a fast approximation algorithm for Consensus. That is, the closely related algorithm FC (Fast Consensus) that would have the same precision as Consensus with a substantially better time performance. The performance of FC has been assessed via extensive experiments on twelve benchmark datasets that summarize key features of microarray applications, such as cancer studies, gene expression with up and down patterns, and a full spectrum of dimensionality up to over a thousand. Based on their outcome, compared with previous benchmarking results available in the literature, FC turns out to be among the fastest internal validation methods, while retaining the same outstanding precision of Consensus. Moreover, it also provides a consensus matrix that can be used as a dissimilarity matrix

  14. DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii

    DTIC Science & Technology

    2004-11-15

    DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii Chien-Chung Chao Rickettsiae Diseases...TITLE AND SUBTITLE DNA Microarray Analysis of Human Monocytes Early Response Genes upon Infection with Rickettsia rickettsii 5a. CONTRACT NUMBER 5b...ANSI Std Z39-18 Rickettsiae • Gram negative coccobacillary bacteria • Obligate intracellular organisms • Arthropod-borne • Cause febrile diseases (mild

  15. Measuring Affinity Constants of 1,450 Monoclonal Antibodies to Peptide Targets with a Microarray-based Label-Free Assay Platform

    PubMed Central

    Landry, J. P.; Ke, Yaohuang; Yu, Guo-Liang; Zhu, X. D.

    2014-01-01

    Monoclonal antibodies (mAbs) are major reagents for research and clinical diagnosis. For their inherently high specificities to intended antigen targets and thus low toxicity in general, they are pursued as one of the major classes of new drugs. Yet binding properties of most monoclonal antibodies are not well characterized in terms of affinity constants and how they vary with presentations and/or conformational isomers of antigens, buffer compositions, and temperature. We here report a microarray-based label-free assay platform for high-throughput measurements of monoclonal antibody affinity constants to antigens immobilized on solid surfaces. Using this platform we measured affinity constants of over 1,410 rabbit monoclonal antibodies and 46 mouse monoclonal antibodies to peptide targets that are immobilized through a terminal cysteine residue to a glass surface. The experimentally measured affinity constants vary from 10 pM to 200 pM with the median value at 66 pM. We compare results of the microarray-based platform with those of a benchmarking surface-plasmon-resonance-based (SPR) sensor (Biacore 3000). PMID:25536073

  16. Transcriptomic profiling of long non-coding RNAs in dermatomyositis by microarray analysis

    PubMed Central

    Peng, Qing-Lin; Zhang, Ya-Mei; Yang, Han-Bo; Shu, Xiao-Ming; Lu, Xin; Wang, Guo-Chun

    2016-01-01

    Long non-coding RNAs (lncRNAs) are prevalently transcribed in the genome and have been found to be of functional importance. However, the potential roles of lncRNAs in dermatomyositis (DM) remain unknown. In this study, a lncRNA + mRNA microarray analysis was performed to profile lncRNAs and mRNAs from 15 treatment-naive DM patients and 5 healthy controls. We revealed a total of 1198 lncRNAs (322 up-regulated and 876 down-regulated) and 1213 mRNAs (665 up-regulated and 548 down-regulated) were significantly differentially expressed in DM patients compared with the healthy controls (fold change>2, P < 0.05). Subgrouping DM patients according to the presence of interstitial lung disease and anti-Jo-1 antibody revealed different expression patterns of the lncRNAs. Pathway and gene ontology analysis for the differentially expressed mRNAs confirmed that type 1 interferon signaling was the most significantly dysregulated pathway in all DM subgroups. In addition, distinct pathways that uniquely associated with DM subgroup were also identified. Bioinformatics prediction suggested that linc-DGCR6-1 may be a lncRNA that regulates type 1 interferon-inducible gene USP18, which was found highly expressed in the perifascicular areas of the muscle fibers of DM patients. Our findings provide an overview of aberrantly expressed lncRNAs in DM muscle and further broaden the understanding of DM pathogenesis. PMID:27605457

  17. Transcriptomic profiling of long non-coding RNAs in dermatomyositis by microarray analysis.

    PubMed

    Peng, Qing-Lin; Zhang, Ya-Mei; Yang, Han-Bo; Shu, Xiao-Ming; Lu, Xin; Wang, Guo-Chun

    2016-09-08

    Long non-coding RNAs (lncRNAs) are prevalently transcribed in the genome and have been found to be of functional importance. However, the potential roles of lncRNAs in dermatomyositis (DM) remain unknown. In this study, a lncRNA + mRNA microarray analysis was performed to profile lncRNAs and mRNAs from 15 treatment-naive DM patients and 5 healthy controls. We revealed a total of 1198 lncRNAs (322 up-regulated and 876 down-regulated) and 1213 mRNAs (665 up-regulated and 548 down-regulated) were significantly differentially expressed in DM patients compared with the healthy controls (fold change>2, P < 0.05). Subgrouping DM patients according to the presence of interstitial lung disease and anti-Jo-1 antibody revealed different expression patterns of the lncRNAs. Pathway and gene ontology analysis for the differentially expressed mRNAs confirmed that type 1 interferon signaling was the most significantly dysregulated pathway in all DM subgroups. In addition, distinct pathways that uniquely associated with DM subgroup were also identified. Bioinformatics prediction suggested that linc-DGCR6-1 may be a lncRNA that regulates type 1 interferon-inducible gene USP18, which was found highly expressed in the perifascicular areas of the muscle fibers of DM patients. Our findings provide an overview of aberrantly expressed lncRNAs in DM muscle and further broaden the understanding of DM pathogenesis.

  18. Matrix Factorization Methods Applied in Microarray Data Analysis

    PubMed Central

    Kossenkov, Andrew V.

    2010-01-01

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

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

    PubMed Central

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

    2008-01-01

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

  20. Copasetic analysis: a framework for the blind analysis of microarray imagery.

    PubMed

    Fraser, K; O'Neill, P; Wang, Z; Liu, X

    2004-06-01

    From its conception, bioinformatics has been a multidisciplinary field which blends domain expert knowledge with new and existing processing techniques, all of which are focused on a common goal. Typically, these techniques have focused on the direct analysis of raw microarray image data. Unfortunately, this fails to utilise the image's full potential and in practice, this results in the lab technician having to guide the analysis algorithms. This paper presents a dynamic framework that aims to automate the process of microarray image analysis using a variety of techniques. An overview of the entire framework process is presented, the robustness of which is challenged throughout with a selection of real examples containing varying degrees of noise. The results show the potential of the proposed framework in its ability to determine slide layout accurately and perform analysis without prior structural knowledge. The algorithm achieves approximately, a 1 to 3 dB improved peak signal-to-noise ratio compared to conventional processing techniques like those implemented in GenePix when used by a trained operator. As far as the authors are aware, this is the first time such a comprehensive framework concept has been directly applied to the area of microarray image analysis.

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

    PubMed

    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.

  2. Analysis of Protein Glycosylation and Phosphorylation Using Liquid Phase Separation, Protein Microarray Technology, and Mass Spectrometry

    PubMed Central

    Zhao, Jia; Patwa, Tasneem H.; Pal, Manoj; Qiu, Weilian; Lubman, David M.

    2010-01-01

    Summary Protein glycosylation and phosphorylation are very common posttranslational modifications. The alteration of these modifications in cancer cells is closely related to the onset and progression of cancer and other disease states. In this protocol, strategies for monitoring the changes in protein glycosylation and phosphorylation in serum or tissue cells on a global scale and specifically characterizing these alterations are included. The technique is based on lectin affinity enrichment for glycoproteins, all liquid-phase two-dimensional fractionation, protein microarray, and mass spectrometry technology. Proteins are separated based on pI in the first dimension using chromatofocusing (CF) or liquid isoelectric focusing (IEF) followed by the second-dimension separation using nonporous silica RP-HPLC. Five lectins with different binding specificities to glycan structures are used for screening glycosylation patterns in human serum through a biotin–streptavidin system. Fluorescent phosphodyes and phosphospecific antibodies are employed to detect specific phosphorylated proteins in cell lines or human tissues. The purified proteins of interest are identified by peptide sequencing. Their modifications including glycosylation and phosphorylation could be further characterized by mass-spectrometry-based approaches. These strategies can be used in biological samples for large-scale glycoproteome/phosphoproteome screening as well as for individual protein modification analysis. PMID:19241043

  3. Analysis of protein glycosylation and phosphorylation using liquid phase separation, protein microarray technology, and mass spectrometry.

    PubMed

    Zhao, Jia; Patwa, Tasneem H; Pal, Manoj; Qiu, Weilian; Lubman, David M

    2009-01-01

    Protein glycosylation and phosphorylation are very common posttranslational modifications. The alteration of these modifications in cancer cells is closely related to the onset and progression of cancer and other disease states. In this protocol, strategies for monitoring the changes in protein glycosylation and phosphorylation in serum or tissue cells on a global scale and specifically characterizing these alterations are included. The technique is based on lectin affinity enrichment for glycoproteins, all liquid-phase two-dimensional fractionation, protein microarray, and mass spectrometry technology. Proteins are separated based on pI in the first dimension using chromatofocusing (CF) or liquid isoelectric focusing (IEF) followed by the second-dimension separation using nonporous silica RP-HPLC. Five lectins with different binding specificities to glycan structures are used for screening glycosylation patterns in human serum through a biotin streptavidin system. Fluorescent phosphodyes and phosphospecific antibodies are employed to detect specific phosphorylated proteins in cell lines or human tissues. The purified proteins of interest are identified by peptide sequencing. Their modifications including glycosylation and phosphorylation could be further characterized by mass-spectrometry-based approaches. These strategies can be used in biological samples for large-scale glycoproteome/phosphoproteome screening as well as for individual protein modification analysis.

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

    PubMed

    Polen, Tino; Wendisch, Volker F

    2004-01-01

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

  5. Microarray analysis of p-anisaldehyde-induced transcriptome of Saccharomyces cerevisiae.

    PubMed

    Yu, Lu; Guo, Na; Yang, Yi; Wu, Xiuping; Meng, Rizeng; Fan, Junwen; Ge, Fa; Wang, Xuelin; Liu, Jingbo; Deng, Xuming

    2010-03-01

    p-Anisaldehyde (4-methoxybenzaldehyde), an extract from Pimpinella anisum L. seeds, is a potential novel preservative. To reveal the possible action mechanism of p-anisaldehyde against microorganisms, yeast-based commercial oligonucleotide microarrays were used to analyze the genome-wide transcriptional changes in response to p-anisaldehyde. Quantitative real-time RT-PCR was performed for selected genes to verify the microarray results. We interpreted our microarray data with the clustering tool, T-profiler. Analysis of microarray data revealed that p-anisaldehyde induced the expression of genes related to sulphur assimilation, aromatic aldehydes metabolism, and secondary metabolism, which demonstrated that the addition of p-anisaldehyde may influence the normal metabolism of aromatic aldehydes. This genome-wide transcriptomics approach revealed first insights into the response of Saccharomyces cerevisiae (S. cerevisiae) to p-anisaldehyde challenge.

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

    PubMed

    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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2006-03-01

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

  9. Probe-Level Analysis of Expression Microarrays Characterizes Isoform-Specific Degradation during Mouse Oocyte Maturation

    PubMed Central

    Salisbury, Jesse; Hutchison, Keith W.; Wigglesworth, Karen; Eppig, John J.; Graber, Joel H.

    2009-01-01

    Background Gene expression microarrays have provided many insights into changes in gene expression patterns between different tissue types, developmental stages, and disease states. Analyses of these data focused primarily measuring the relative abundance of transcripts of a gene, while treating most or all transcript isoforms as equivalent. Differences in the selection between transcript isoforms can, however, represent critical changes to either the protein product or the posttranscriptional regulation of the transcript. Novel analyses on existing microarray data provide fresh insights and new interpretations into transcriptome-wide changes in expression. Methodology A probe-level analysis of existing gene expression arrays revealed differences in mRNA processing, primarily affecting the 3′-untranslated region. Working with the example of microarrays drawn from a transcriptionally silent period of mouse oocyte development, probe-level analysis (implemented here as rmodel) identified genes whose transcript isoforms have differing stabilities. Comparison of micorarrays measuring cDNA generated from oligo-dT and random primers revealed further differences in the polyadenylation status of some transcripts. Additional analysis provided evidence for sequence-targeted cleavage, including putative targeting sequences, as one mechanism of degradation for several hundred transcripts in the maturing oocyte. Conclusions The capability of probe-level analysis to elicit novel findings from existing expression microarray data was demonstrated. The characterization of differences in stability between transcript isoforms in maturing mouse oocytes provided some mechanistic details of degradation. Similar analysis of existing archives of expression microarray data will likely provide similar discoveries. PMID:19834616

  10. Variance estimation in the analysis of microarray data.

    PubMed

    Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

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

    PubMed

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

    2015-09-01

    Clostridium difficile is an anaerobic, Gram-positive, and spore-forming bacterium that is the leading worldwide infective cause of hospital-acquired and antibiotic-associated diarrhea. Several studies have reported associations between humoral immunity and the clinical course of C. difficile infection (CDI). Host humoral immune responses are determined using conventional enzyme-linked immunosorbent assay (ELISA) techniques. Herein, we report the first use of a novel protein microarray assay to determine systemic IgG antibody responses against a panel of highly purified C. difficile-specific antigens, including native toxins A and B (TcdA and TcdB, respectively), recombinant fragments of toxins A and B (TxA4 and TxB4, respectively), ribotype-specific surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). Microarrays were probed with sera from a total of 327 individuals with CDI, cystic fibrosis without diarrhea, and healthy controls. For all antigens, precision profiles demonstrated <10% coefficient of variation (CV). Significant correlation was observed between microarray and ELISA in the quantification of antitoxin A and antitoxin B IgG. These results indicate that microarray is a suitable assay for defining humoral immune responses to C. difficile protein antigens and may have potential advantages in throughput, convenience, and cost. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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

    PubMed Central

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

    2015-01-01

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

  13. GeneXplorer: an interactive web application for microarray data visualization and analysis.

    PubMed

    Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

    2004-10-01

    When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

  14. ArrayQuest: a web resource for the analysis of DNA microarray data

    PubMed Central

    Argraves, Gary L; Jani, Saurin; Barth, Jeremy L; Argraves, W Scott

    2005-01-01

    Background Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Results Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1) it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2) new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3) input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC) DNA Microarray Database or Gene Expression Omnibus (GEO)) or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4) analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. Conclusion ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at . PMID:16321157

  15. ArrayQuest: a web resource for the analysis of DNA microarray data.

    PubMed

    Argraves, Gary L; Jani, Saurin; Barth, Jeremy L; Argraves, W Scott

    2005-12-01

    Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1) it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2) new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3) input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC) DNA Microarray Database or Gene Expression Omnibus (GEO)) or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4) analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.

  16. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    PubMed Central

    Evans, Irene M.

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

  17. Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

    PubMed

    Tra, Yolande V; Evans, Irene M

    2010-01-01

    BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

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

    PubMed

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

    2008-06-18

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

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

    PubMed Central

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

    2008-01-01

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

  20. [Preparation of recombinant serpins B3 and B4 and investigation of their specific interactions with antibodies using hydrogel-based microarrays].

    PubMed

    Butvilovskaya, V I; Tsybulskaya, M V; Tikhonov, A A; Talibov, V O; Belousov, P V; Sazykin, A Yu; Schwartz, A M; Putlyaeva, L V; Surzhikov, S A; Stomakhin, A A; Solopova, O N; Rubina, A Yu

    2015-01-01

    The objective of this work was to obtain preparations of recombinant squamous-cell carcinoma antigens (serpins B3 and B4) and to investigate their interactions with different monoclonal antibodies using hydrogel-based microarrays (biochips). Two genetic constructs encoding full-length serpin B3 and serpin B4 molecules were created to produce recombinant SPB3 and SPB4 proteins carrying a N-terminal His6-tag. Monoclonal antibodies against serpin B3 (H3, C5, H5, H81, and G9) were also obtained. An experimental gel-based biological microchip was designed to contain gel elements that carry immobilized antibodies against SPB3, immobilized commercial monoclonal SCC107 and SCC140 antibodies against squamous-cell carcinoma antigen (SCCA), and gel elements with immobilized SPB3 or SPB4. Judging by the specificity of recombinant SPB3 and SPB4, which bind to monoclonal antibodies against SCCA and, according to the manufacturer's data, can recognize conformational epitopes of both SPB3 and SPB4, it was concluded that the obtained recombinant serpins had the correct tertiary structure. A biochip-based direct immunoassay showed that SPB4 could bind effectively only to SCC107 and SCC140 antibodies, while SPB3 interacted specifically not only with these antibodies, but also with H3 and C5 monoclonal antibodies. Using biochip-based sandwich immunoassay, a pair of monoclonal antibodies SCC107/C5 that interacted specifically with serpin B3 but did not interact with serpin B4 was identified. Thus, it has been demonstrated that serpin B3 can be selectively determined in the presence of highly homologous serpin B4 using a biochip-based assay.

  1. Microarray analysis for a comprehensive immunological-status evaluation during cancer vaccine immune monitoring.

    PubMed

    Monsurrò, Vladia; Marincola, Francesco M

    2011-01-01

    Anticancer immune responses can be enhanced by immune intervention that promotes complex biological mechanisms involving several cellular populations. The classical immune monitoring for biological-based cancer clinical trials is often based on single-cell analysis. However, the overall effect could be lost by such a reductionist approach explaining the lack of correlation among clinical and immunological endpoints often reported. Microarray technology could give the possibility of studying in a multiparametric setting the immune therapy effects. The application of microarray is leading to an improved understanding of the immune responses to tumor immunotherapy. In fact, analysis of cancer vaccine-induced host responses using microarrays is proposed as valuable alternative to the standard cell-based methods. This paper shows successful examples of how high-throughput gene expression profiling contributed to the understanding of anticancer immune responses during biological therapy, introducing as well the integrative platforms that allow the network analysis in molecular biology studies.

  2. Gene expression analysis of perennial ryegrass (Lolium perenne) using cDNA microarrays

    NASA Astrophysics Data System (ADS)

    Ong, Eng-Kok; Sawbridge, Tim; Webster, Tracie; Emmerling, Michael; Nguyen, Nga; Nunan, Katrina; O'Neill, Matthew; O'Toole, Fiona; Rhodes, Carolyn; Simmonds, Jason; Tian, Pei; Wearne, Katherine; Winkworth, Amanda; Spangenberg, German

    2003-07-01

    Perennial ryegrass (Lolium perenne) is a major forage grass of temperate pastures. A genomics program has been undertaken generating over 52,000 expressed sequence tags (ESTs). Cluster analysis of the ESTs identified approximately 14,600 ryegrass unigenes. In this report, we described the application of ryegrass unigene cDNAs to produce ryegrass 15K microarray. Fifteen microarray hybridisations were performed with labeled total RNA isolated from a variety of plant organs and developmental stages. In a proof of concept, gene expression profiling of ryegrass ESTs using the 15K unigene microarrays has been established using several known genes and two cluster analysis approaches (parallel coordinate planes plot and hierarchical clustering). The expression profile of the known genes (e.g. rubisco and invertase) corresponds well with published data. The microarray expression profile of a ryegrass putative root specific kinase gene was also verified with Northern blotting. This combination of DNA microarray hybridisations and cluster analysis can be applied as a tool for the identification of novel sequences of unknown function.

  3. Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

    PubMed

    Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

    2015-01-01

    Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

  4. Automating dChip: toward reproducible sharing of microarray data analysis.

    PubMed

    Li, Cheng

    2008-05-08

    During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users. We report here implementation and application of the dChip automation module. Through this module, dChip automation files can be created to include menu steps, parameters, and data viewpoints to run automatically. A data-packaging function allows convenient transfer from one user to another of the dChip software, microarray data, and analysis procedures, so that the second user can reproduce the entire analysis session of the first user. An analysis report file can also be generated during an automated run, including analysis logs, user comments, and viewpoint screenshots. The dChip automation module is a step toward reproducible research, and it can prompt a more convenient and reproducible mechanism for sharing microarray software, data, and analysis procedures and results. Automation data packages can also be used as publication supplements. Similar automation mechanisms could be valuable to the research community if implemented in other genomics and bioinformatics software packages.

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

    SciTech Connect

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

    2006-04-01

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

  6. Microarray analysis of circular RNA expression patterns in polarized macrophages

    PubMed Central

    Zhang, Yingying; Zhang, Yao; Li, Xueqin; Zhang, Mengying; Lv, Kun

    2017-01-01

    Circular RNAs (circRNAs) are generated from diverse genomic locations and are a new player in the regulation of post-transcriptional gene expression. Recent studies have revealed that circRNAs play a crucial role in fine-tuning the level of microRNA (miRNA)-mediated regulation of gene expression by sequestering miRNAs. The interaction of circRNAs with disease-associated miRNAs suggests that circRNAs are important in the pathology of disease. However, the effects and roles of circRNAs in macrophage polarization have yet to be explored. In the present study, we performed a circRNA microarray to compare the circRNA expression profiles of bone marrow-derived macrophages (BMDMs) under two distinct polarizing conditions (M1 macrophages induced by interferon-γ and LPS stimulation, and M2 macrophages induced by interleukin-4 stimulation). Our results showed that a total of 189 circRNAs were differentially expressed between M1 and M2 macrophages. Differentially expressed circRNAs with a high fold-change were selected for validation by RT-qPCR: circRNA-003780, circRNA-010056, and circRNA-010231 were upregulated and circRNA-003424, circRNA-013630, circRNA-001489 and circRNA-018127 were downregulated (fold-change >4, P<0.05) in M1 compared to M2, which was found to correlate with the microarray data. Furthermore, the most differentially expressed circRNAs within all the comparisons were annotated in detail with circRNA/miRNA interaction information using miRNA target prediction software. In conclusion, the present study provides novel insight into the role of circRNAs in macrophage differentiation and polarization. PMID:28075448

  7. Automated ERCC1 immunochemistry on hybrid cytology/tissue microarray of malignant effusions: evaluation of antibodies 8F1 and D-10.

    PubMed

    Soltermann, Alex; Kilgus-Hawelski, Sandra; Behnke, Silvia; Storz, Martina; Moch, Holger; Bode, Beata

    2011-09-30

    The excision repair cross-complementation group 1 (ERCC1) protein is the key enzyme of the nucleotide excision repair (NER) pathway. Loss of protein expression on immunohistochemistry is predictive for platinum-based chemotherapy response. Frequently, the diagnosis of malignancy is made on cytologic effusion samples. Therefore, we evaluated the staining quality of monoclonal anti-ERCC1 antibodies 8F1 and D-10 on microarrays of malignant pleural and peritoneal effusions by automated immunochemistry. Cores from effusion cell blocks of 117 patients with > 40 malignant cell clusters per whole section (pleural n = 75, peritoneal n = 42) were assembled together with 30 histologic control cores from large tissue blocks (lung, breast and ovarian carcinoma, each n = 10) on hybrid cytology-tissue microarrays (C/TMA). Four immunochemistry protocols (Mab 8F1 and D-10, CC1-mono Ventana and H2-60 Bond automat) were performed. Immunoreactivity was semi-quantitatively scored for intensity and intensity multiplied by percentage staining (H-score). Tumors were classified into female genital tract carcinoma (n = 39), lung adenocarcinoma (n = 23), mesothelioma (n = 15), unknown primary (n = 14), breast carcinoma (n = 10), gastro-intestinal carcinoma (n = 12) and other (n = 4). On both platforms, reproducible nuclear ERCC1 immunoreactivity was achieved with both antibodies, although D-10 was slightly weaker and presented more background staining as well as more variation in the low expression range. No significant differences were found between cytologic and histologic cores. Using the 8F1 CC1-mono protocol, lung and breast carcinomas had lower ERCC1 expression in comparison to the other entities (p-value < 0.05). Cytology microarrays (CMA) are suitable for investigation of clinical biomarkers and can be combined with conventional TMA's. Dichotomization of ERCC1 immunoreactivity scores is most suitable for patient stratification since definition of negativity is antibody-dependent.

  8. Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

    PubMed

    Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

    2017-06-06

    Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

  9. Characterizing Antibody Responses to Plasmodium vivax and Plasmodium falciparum Antigens in India Using Genome-Scale Protein Microarrays

    PubMed Central

    Awasthi, Vikky; Verma, Kalpana; Sutton, Patrick; Ali, Syed Zeeshan; Patel, Ankita; G., Sri Lakshmi Priya; Ravishankaran, Sangamithra; Desai, Nisha; Tandel, Nikunj; Choubey, Sandhya; Barla, Punam; Kanagaraj, Deena; Eapen, Alex; Pradhan, Khageswar; Singh, Ranvir; Jain, Aarti; Felgner, Philip L.; Davies, D. Huw; Das, Jyoti

    2017-01-01

    Understanding naturally acquired immune responses to Plasmodium in India is key to improving malaria surveillance and diagnostic tools. Here we describe serological profiling of immune responses at three sites in India by probing protein microarrays consisting of 515 Plasmodium vivax and 500 Plasmodium falciparum proteins with 353 plasma samples. A total of 236 malaria-positive (symptomatic and asymptomatic) plasma samples and 117 malaria-negative samples were collected at three field sites in Raurkela, Nadiad, and Chennai. Indian samples showed significant seroreactivity to 265 P. vivax and 373 P. falciparum antigens, but overall seroreactivity to P. vivax antigens was lower compared to P. falciparum antigens. We identified the most immunogenic antigens of both Plasmodium species that were recognized at all three sites in India, as well as P. falciparum antigens that were associated with asymptomatic malaria. This is the first genome-scale analysis of serological responses to the two major species of malaria parasite in India. The range of immune responses characterized in different endemic settings argues for targeted surveillance approaches tailored to the diverse epidemiology of malaria across the world. PMID:28118367

  10. Characterizing Antibody Responses to Plasmodium vivax and Plasmodium falciparum Antigens in India Using Genome-Scale Protein Microarrays.

    PubMed

    Uplekar, Swapna; Rao, Pavitra Nagesh; Ramanathapuram, Lalitha; Awasthi, Vikky; Verma, Kalpana; Sutton, Patrick; Ali, Syed Zeeshan; Patel, Ankita; G, Sri Lakshmi Priya; Ravishankaran, Sangamithra; Desai, Nisha; Tandel, Nikunj; Choubey, Sandhya; Barla, Punam; Kanagaraj, Deena; Eapen, Alex; Pradhan, Khageswar; Singh, Ranvir; Jain, Aarti; Felgner, Philip L; Davies, D Huw; Carlton, Jane M; Das, Jyoti

    2017-01-01

    Understanding naturally acquired immune responses to Plasmodium in India is key to improving malaria surveillance and diagnostic tools. Here we describe serological profiling of immune responses at three sites in India by probing protein microarrays consisting of 515 Plasmodium vivax and 500 Plasmodium falciparum proteins with 353 plasma samples. A total of 236 malaria-positive (symptomatic and asymptomatic) plasma samples and 117 malaria-negative samples were collected at three field sites in Raurkela, Nadiad, and Chennai. Indian samples showed significant seroreactivity to 265 P. vivax and 373 P. falciparum antigens, but overall seroreactivity to P. vivax antigens was lower compared to P. falciparum antigens. We identified the most immunogenic antigens of both Plasmodium species that were recognized at all three sites in India, as well as P. falciparum antigens that were associated with asymptomatic malaria. This is the first genome-scale analysis of serological responses to the two major species of malaria parasite in India. The range of immune responses characterized in different endemic settings argues for targeted surveillance approaches tailored to the diverse epidemiology of malaria across the world.

  11. A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

    PubMed Central

    Carter, Ben; Wu, Guanghui; Woodward, Martin J; Anjum, Muna F

    2008-01-01

    Background Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes. PMID:18230148

  12. EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data.

    PubMed

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

    2009-02-06

    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. 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. Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

  13. The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

    PubMed

    Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

    2015-01-01

    Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

  14. Immunohistochemistry - microarray analysis of patients with peritoneal metastases of appendiceal or colorectal origin.

    PubMed

    Green, Danielle E; Jayakrishnan, Thejus T; Hwang, Michael; Pappas, Sam G; Gamblin, T Clark; Turaga, Kiran K

    2014-01-01

    The value of immunohistochemistry (IHC)-microarray analysis of pathological specimens in the management of patients is controversial, although preliminary data suggest potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM) and the feasibility of this technique in this population. We retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular Intelligence(™) testing. IHC, microarray, FISH, and mutational analysis were included and stratified by Peritoneal Carcinomatosis Index (PCI) score, histology, and treatment characteristics. Statistical analysis was performed using non-parametric tests. Our study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65) years, with 11 (68%) female. The median PCI score of the patients was 17 (IQR 10-25). Hyperthermic intra-peritoneal chemoperfusion was performed in 4 (80%) patients with appendiceal primary tumors and 4 (36%) with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p = 0.06). IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n = 7) patients, which was not associated with previous use of chemotherapy (p > 0.20 for 5-FU/LV, Irinotecan and Oxaliplatin). In a small sample of patients with PM, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.

  15. A protein microarray-based analysis of S-nitrosylation

    PubMed Central

    Foster, Matthew W.; Forrester, Michael T.; Stamler, Jonathan S.

    2009-01-01

    The ubiquitous cellular influence of nitric oxide (NO) is exerted substantially through protein S-nitrosylation. Whereas NO is highly promiscuous, physiological S-nitrosylation is typically restricted to one or very few Cys residue(s) in target proteins. The molecular basis for this specificity may derive from properties of the target protein, the S-nitrosylating species, or both. Here, we describe a protein microarray-based approach to investigate determinants of S-nitrosylation by biologically relevant low-mass S-nitrosothiols (SNOs). We identify large sets of yeast and human target proteins, among which those with active-site Cys thiols residing at N termini of α-helices or within catalytic loops were particularly prominent. However, S-nitrosylation varied substantially even within these families of proteins (e.g., papain-related Cys-dependent hydrolases and rhodanese/Cdc25 phosphatases), suggesting that neither secondary structure nor intrinsic nucleophilicity of Cys thiols was sufficient to explain specificity. Further analyses revealed a substantial influence of NO-donor stereochemistry and structure on efficiency of S-nitrosylation as well as an unanticipated and important role for allosteric effectors. Thus, high-throughput screening and unbiased proteome coverage reveal multifactorial determinants of S-nitrosylation (which may be overlooked in alternative proteomic analyses), and support the idea that target specificity can be achieved through rational design of S-nitrosothiols. PMID:19864628

  16. DNA microarray analysis of genes differentially expressed in adipocyte differentiation.

    PubMed

    Yin, Chunyan; Xiao, Yanfeng; Zhang, Wei; Xu, Erdi; Liu, Weihua; Yi, Xiaoqing; Chang, Ming

    2014-06-01

    In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. 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 exhibited a greater than or equal to 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RTPCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR?2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.

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

    PubMed Central

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

    2009-01-01

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

  18. Microarray analysis reveals differential gene expression in hybrid sunflower species

    PubMed Central

    LAI, ZHAO; GROSS, BRIANA L.; YIZOU; ANDREWS, JUSTEN; RIESEBERG, LOREN H.

    2008-01-01

    This paper describes the creation of a cDNA microarray for annual sunflowers and its use to elucidate patterns of gene expression in Helianthus annuus, Helianthus petiolaris, and the homoploid hybrid species Helianthus deserticola. The array comprises 3743 ESTs (expressed sequence tags) representing approximately 2897 unique genes. It has an average clone/EST identity rate of 91%, is applicable across species boundaries within the annual sunflowers, and shows patterns of gene expression that are highly reproducible according to real-time RT–PCR (reverse transcription–polymerase chain reaction) results. Overall, 12.8% of genes on the array showed statistically significant differential expression across the three species. Helianthus deserticola displayed transgressive, or extreme, expression for 58 genes, with roughly equal numbers exhibiting up- or down-regulation relative to both parental species. Transport-related proteins were strongly over-represented among the transgressively expressed genes, which makes functional sense given the extreme desert floor habitat of H. deserticola. The potential adaptive value of differential gene expression was evaluated for five genes in two populations of early generation (BC2) hybrids between the parental species grown in the H. deserticola habitat. One gene (a G protein-coupled receptor) had a significant association with fitness and maps close to a QTL controlling traits that may be adaptive in the desert habitat. PMID:16626449

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

    PubMed Central

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

    2013-01-01

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

  20. A protein microarray-based analysis of S-nitrosylation.

    PubMed

    Foster, Matthew W; Forrester, Michael T; Stamler, Jonathan S

    2009-11-10

    The ubiquitous cellular influence of nitric oxide (NO) is exerted substantially through protein S-nitrosylation. Whereas NO is highly promiscuous, physiological S-nitrosylation is typically restricted to one or very few Cys residue(s) in target proteins. The molecular basis for this specificity may derive from properties of the target protein, the S-nitrosylating species, or both. Here, we describe a protein microarray-based approach to investigate determinants of S-nitrosylation by biologically relevant low-mass S-nitrosothiols (SNOs). We identify large sets of yeast and human target proteins, among which those with active-site Cys thiols residing at N termini of alpha-helices or within catalytic loops were particularly prominent. However, S-nitrosylation varied substantially even within these families of proteins (e.g., papain-related Cys-dependent hydrolases and rhodanese/Cdc25 phosphatases), suggesting that neither secondary structure nor intrinsic nucleophilicity of Cys thiols was sufficient to explain specificity. Further analyses revealed a substantial influence of NO-donor stereochemistry and structure on efficiency of S-nitrosylation as well as an unanticipated and important role for allosteric effectors. Thus, high-throughput screening and unbiased proteome coverage reveal multifactorial determinants of S-nitrosylation (which may be overlooked in alternative proteomic analyses), and support the idea that target specificity can be achieved through rational design of S-nitrosothiols.

  1. A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

    PubMed

    Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

    2010-05-21

    Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays.

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

    PubMed

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

    2009-10-27

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

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

    PubMed Central

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

    2009-01-01

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

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

    PubMed

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

    2014-08-01

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

  5. Grating coupled SPR microarray analysis of proteins and cells in blood from mice with breast cancer.

    PubMed

    Mendoza, A; Torrisi, D M; Sell, S; Cady, N C; Lawrence, D A

    2016-01-21

    Biomarker discovery for early disease diagnosis is highly important. Of late, much effort has been made to analyze complex biological fluids in an effort to develop new markers specific for different cancer types. Recent advancements in label-free technologies such as surface plasmon resonance (SPR)-based biosensors have shown promise as a diagnostic tool since there is no need for labeling or separation of cells. Furthermore, SPR can provide rapid, real-time detection of antigens from biological samples since SPR is highly sensitive to changes in surface-associated molecular and cellular interactions. Herein, we report a lab-on-a-chip microarray biosensor that utilizes grating-coupled surface plasmon resonance (GCSPR) and grating-coupled surface plasmon coupled fluorescence (GCSPCF) imaging to detect circulating tumor cells (CTCs) from a mouse model (FVB-MMTV-PyVT). GCSPR and GCSPCF analysis was accomplished by spotting antibodies to surface cell markers, cytokines and stress proteins on a nanofabricated GCSPR microchip and screening blood samples from FVB control mice or FVB-MMTV-PyVT mice with developing mammary carcinomas. A transgenic MMTV-PyVT mouse derived cancer cell line was also analyzed. The analyses indicated that CD24, CD44, CD326, CD133 and CD49b were expressed in both cell lines and in blood from MMTV-PyVT mice. Furthermore, cytokines such as IL-6, IL-10 and TNF-α, along with heat shock proteins HSP60, HSP27, HSc70(HSP73), HSP90 total, HSP70/HSc70, HSP90, HSP70, HSP90 alpha, phosphotyrosine and HSF-1 were overexpressed in MMTV-PyVT mice.

  6. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    PubMed Central

    Walsh, Christopher J.; Hu, Pingzhao; Batt, Jane; Dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers. PMID:27600230

  7. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery.

    PubMed

    Walsh, Christopher J; Hu, Pingzhao; Batt, Jane; Santos, Claudia C Dos

    2015-08-21

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.

  8. A renewed approach to the nonparametric analysis of replicated microarray experiments.

    PubMed

    Jung, Klaus; Quast, Karsten; Gannoun, Ali; Urfer, Wolfgang

    2006-04-01

    DNA-microarrays find broad employment in biochemical research. This technology allows the monitoring of the expression levels of thousands of genes at the same time. Often, the goal of a microarray study is to find differentially expressed genes in two different types of tissue, for example normal and cancerous. Multiple hypothesis testing is a useful statistical tool for such studies. One approach using multiple hypothesis testing is nonparametric analysis for replicated microarray experiments. In this paper we present an improved version of this method. We also show how p-values are calculated for all significant genes detected with this testing procedure. All algorithms were implemented in an R-package, and instructions on it's use are included. The package can be downloaded at http://www.statistik.unidortmund.de/de/content/einrichtungen/lehrstuehle/personen/jung.html

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

    PubMed Central

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

    2016-01-01

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

  10. Microarray analysis of radiation response genes in primary human fibroblasts

    SciTech Connect

    Kis, Enikoe; Szatmari, Tuende; Keszei, Marton; Farkas, Robert; Esik, Olga; Lumniczky, Katalin; Falus, Andras; Safrany, Geza . E-mail: safrany@hp.osski.hu

    2006-12-01

    Purpose: To identify radiation-induced early transcriptional responses in primary human fibroblasts and understand cellular pathways leading to damage correction. Methods and Materials: Primary human fibroblast cell lines were irradiated with 2 Gy {gamma}-radiation and RNA isolated 2 h later. Radiation-induced transcriptional alterations were investigated with microarrays covering the entire human genome. Time- and dose dependent radiation responses were studied by quantitative real-time polymerase chain reaction (RT-PCR). Results: About 200 genes responded to ionizing radiation on the transcriptional level in primary human fibroblasts. The expression profile depended on individual genetic backgrounds. Thirty genes (28 up- and 2 down-regulated) responded to radiation in identical manner in all investigated cells. Twenty of these consensus radiation response genes were functionally categorized: most of them belong to the DNA damage response (GADD45A, BTG2, PCNA, IER5), regulation of cell cycle and cell proliferation (CDKN1A, PPM1D, SERTAD1, PLK2, PLK3, CYR61), programmed cell death (BBC3, TP53INP1) and signaling (SH2D2A, SLIC1, GDF15, THSD1) pathways. Four genes (SEL10, FDXR, CYP26B1, OR11A1) were annotated to other functional groups. Many of the consensus radiation response genes are regulated by, or regulate p53. Time- and dose-dependent expression profiles of selected consensus genes (CDKN1A, GADD45A, IER5, PLK3, CYR61) were investigated by quantitative RT-PCR. Transcriptional alterations depended on the applied dose, and on the time after irradiation. Conclusions: The data presented here could help in the better understanding of early radiation responses and the development of biomarkers to identify radiation susceptible individuals.

  11. MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

    EPA Science Inventory


    MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

    Dichloroacetic acid (DCA) is a major by-product of water disinfection by chlorination. Several studies have demonstrated the hepatocarcinogenicity of DCA in rodents when administered in dri...

  12. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    ERIC Educational Resources Information Center

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  13. The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

    ERIC Educational Resources Information Center

    Beaudet, Arthur L.

    2013-01-01

    Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

  14. Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

    ERIC Educational Resources Information Center

    McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

    2012-01-01

    Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

  15. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    ERIC Educational Resources Information Center

    Tra, Yolande V.; Evans, Irene M.

    2010-01-01

    "BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

  16. The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

    ERIC Educational Resources Information Center

    Beaudet, Arthur L.

    2013-01-01

    Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  19. Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

    ERIC Educational Resources Information Center

    Tra, Yolande V.; Evans, Irene M.

    2010-01-01

    "BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

  20. Scanometric analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles.

    PubMed

    Cho, Hyunmin; Jung, Juyeon; Chung, Bong Hyun

    2012-08-07

    We introduce a scanometric detection method for the analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles that can be analyzed with the naked eye or with an optical scanner after the enhancement of the AuNPs. Moreover, we successfully detected a hemagglutinin-subtyping DNA array using this method.

  1. Multivariate curve resolution for hyperspectral image analysis :applications to microarray technology.

    SciTech Connect

    Van Benthem, Mark Hilary; Sinclair, Michael B.; Haaland, David Michael; Martinez, M. Juanita (University of New Mexico, Albuquerque, NM); Timlin, Jerilyn Ann; Werner-Washburne, Margaret C. (University of New Mexico, Albuquerque, NM); Aragon, Anthony D. (University of New Mexico, Albuquerque, NM)

    2003-01-01

    Multivariate curve resolution (MCR) using constrained alternating least squares algorithms represents a powerful analysis capability for a quantitative analysis of hyperspectral image data. We will demonstrate the application of MCR using data from a new hyperspectral fluorescence imaging microarray scanner for monitoring gene expression in cells from thousands of genes on the array. The new scanner collects the entire fluorescence spectrum from each pixel of the scanned microarray. Application of MCR with nonnegativity and equality constraints reveals several sources of undesired fluorescence that emit in the same wavelength range as the reporter fluorphores. MCR analysis of the hyperspectral images confirms that one of the sources of fluorescence is due to contaminant fluorescence under the printed DNA spots that is spot localized. Thus, traditional background subtraction methods used with data collected from the current commercial microarray scanners will lead to errors in determining the relative expression of low-expressed genes. With the new scanner and MCR analysis, we generate relative concentration maps of the background, impurity, and fluorescent labels over the entire image. Since the concentration maps of the fluorescent labels are relatively unaffected by the presence of background and impurity emissions, the accuracy and useful dynamic range of the gene expression data are both greatly improved over those obtained by commercial microarray scanners.

  2. MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

    EPA Science Inventory


    MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

    Dichloroacetic acid (DCA) is a major by-product of water disinfection by chlorination. Several studies have demonstrated the hepatocarcinogenicity of DCA in rodents when administered in dri...

  3. Simultaneous and sensitive detection of six serotypes of botulinum neurotoxin using enzyme-linked immunosorbent assay-based protein antibody microarrays

    PubMed Central

    Zhang, Yanfeng; Lou, Jianlong; Jenko, Kathy L.; Marks, James D.; Varnum, Susan M.

    2012-01-01

    Botulinum neurotoxins (BoNTs), produced by Clostridium botulinum, are a group of seven (A–G) immunologically distinct proteins and cause the paralytic disease botulism. These toxins are the most poisonous substances known to humans and are potential bioweapon agents. Therefore, it is necessary to develop highly sensitive assays for the detection of BoNTs in both clinical and environmental samples. In the current study, we have developed an enzyme-linked immunosorbent assay (ELISA)-based protein antibody microarray for the sensitive and simultaneous detection of BoNT serotypes A, B, C, D, E, and F. With engineered high-affinity antibodies, the BoNT assays have sensitivities in buffer ranging from 1.3 fM (0.2 pg/ml) to 14.7 fM (2.2 pg/ml). Using clinical and food matrices (serum and milk), the microarray is capable of detecting BoNT serotypes A to F to similar levels as in standard buffer. Cross-reactivity between assays for individual serotype was also analyzed. These simultaneous, rapid, and sensitive assays have the potential to measure botulinum toxins in a high-throughput manner in complex clinical, food, and environmental samples. PMID:22935296

  4. Simultaneous and sensitive detection of six serotypes of botulinum neurotoxin using enzyme-linked immunosorbent assay-based protein antibody microarrays

    SciTech Connect

    Zhang, Yanfeng; Lou, Jianlong; Jenko, Kathryn L.; Marks, James D.; Varnum, Susan M.

    2012-11-15

    Botulinum neurotoxins (BoNTs), produced by Clostridium botulinum, are a group of seven (A-G) immunologically distinct proteins and cause the paralytic disease botulism. These toxins are the most poisonous substances known to humans and are potential bioweapon agents. Therefore, it is necessary to develop highly sensitive assays for the detection of BoNTs in both clinical and environmental samples. In the present study, we have developed an ELISA-based protein antibody microarray for the sensitive and simultaneous detection of BoNT serotype A, B, C, D, E and F. With engineered high-affinity antibodies, the assays have sensitivities in buffer of 8 fM (1.2 pg/mL) for serotypes A and B, and 32 fM (4.9 pg/mL) for serotypes C, D, E, and F. Using clinical and environmental samples (serum and milk), the microarray is capable of detecting BoNT/A-F to the same levels as in standard buffer. Cross reactivity between assays for individual serotype was also analyzed. These simultaneous, rapid, and sensitive assays have the potential to measure botulinum toxins in a high-throughput manner in complex clinical or environmental samples.

  5. Candidate genes for the progression of malignant gliomas identified by microarray analysis.

    PubMed

    Bozinov, Oliver; Köhler, Sylvia; Samans, Birgit; Benes, Ludwig; Miller, Dorothea; Ritter, Markus; Sure, Ulrich; Bertalanffy, Helmut

    2008-01-01

    Malignant astrocytomas of World Health Organization (WHO) grade III or IV have a reduced median survival time, and possible pathways have been described for the progression of anaplastic astrocytomas and glioblastomas, but the molecular basis of malignant astrocytoma progression is still poorly understood. Microarray analysis provides the chance to accelerate studies by comparison of the expression of thousands of genes in these tumours and consequently identify targeting genes. We compared the transcriptional profile of 4,608 genes in tumours of 15 patients including 6 anaplastic astrocytomas (WHO grade III) and 9 glioblastomas (WHO grade IV) using microarray analysis. The microarray data were corroborated by real-time reverse transcription-polymerase chain reaction analysis of two selected genes. We identified 166 gene alterations with a fold change of 2 and higher whose mRNA levels differed (absolute value of the t statistic of 1.96) between the two malignant glioma groups. Further analyses confirmed same transcription directions for Olig2 and IL-13Ralpha2 in anaplastic astrocytomas as compared to glioblastomas. Microarray analyses with a close binary question reveal numerous interesting candidate genes, which need further histochemical testing after selection for confirmation. IL-13Ralpha2 and Olig2 have been identified and confirmed to be interesting candidate genes whose differential expression likely plays a role in malignant progression of astrocytomas.

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

    SciTech Connect

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

    2006-02-13

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

  7. Robust gene selection methods using weighting schemes for microarray data analysis.

    PubMed

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  8. Gene microarray data analysis using parallel point-symmetry-based clustering.

    PubMed

    Sarkar, Anasua; Maulik, Ujjwal

    2015-01-01

    Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed Central

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

    2010-01-01

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

  11. Analysis of gene expression on anodic porous alumina microarrays

    PubMed Central

    Nicolini, Claudio; Singh, Manjul; Spera, Rosanna; Felli, Lamberto

    2013-01-01

    This paper investigates the application of anodic porous alumina as an advancement on chip laboratory for gene expressions. The surface was prepared by a suitable electrolytic process to obtain a regular distribution of deep micrometric holes and printed bypen robot tips under standard conditions. The gene expression within the Nucleic Acid Programmable Protein Array (NAPPA) is realized in a confined environment of 16 spots, containing circular DNA plasmids expressed using rabbit reticulocyte lysate. Authors demonstrated the usefulness of APA in withholding the protein expression by detecting with a CCD microscope the photoluminescence signal emitted from the complex secondary antibody anchored to Cy3 and confined in the pores. Friction experiments proved the mechanical resistance under external stresses by the robot tip pens printing. So far, no attempts have been made to directly compare APA with any other surface/substrate; the rationale for pursuing APA as a potential surface coating is that it provides advantages over the simple functionalization of a glass slide, overcoming concerns about printing and its ability to generate viable arrays. PMID:23783000

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

    PubMed

    Seidel, Michael; Niessner, Reinhard

    2014-09-01

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

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

    PubMed

    Luo, Wen; Gudipati, Murali; Jung, Kevin; Chen, Mao; Marschke, Keith B

    2009-08-23

    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.

  14. Comparative analysis of gene expression by microarray analysis of male and female flowers of Asparagus officinalis.

    PubMed

    Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou

    2013-01-01

    To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.

  15. MiMiR – an integrated platform for microarray data sharing, mining and analysis

    PubMed Central

    Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

    2008-01-01

    Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and

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

    PubMed Central

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

    2009-01-01

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

  17. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability.

    PubMed

    Sontrop, Herman M J; Moerland, Perry D; van den Ham, René; Reinders, Marcel J T; Verhaegh, Wim F J

    2009-11-26

    Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight different datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Feature variability can have a strong impact on

  18. Electronic microarray analysis of 16S rDNA amplicons for bacterial detection.

    PubMed

    Barlaan, Edward A; Sugimori, Miho; Furukawa, Seiji; Takeuchi, Kazuhisa

    2005-01-12

    Electronic microarray technology is a potential alternative in bacterial detection and identification. However, conditions for bacterial detection by electronic microarray need optimization. Using the NanoChip electronic microarray, we investigated eight marine bacterial species. Based on the 16S rDNA sequences of these species, we constructed primers, reporter probes, and species-specific capture probes. We carried out two separate analyses for longer (533 bp) and shorter (350 and 200 bp) amplified products (amplicons). To detect simultaneously the hybridization signals for the 350- and 200-bp amplicons, we designed a common reporter probe from an overlapping sequence within both fragments. We developed methods to optimize detection of hybridization signals for processing the DNA chips. A matrix analysis was performed for different bacterial species and complementary capture probes on electronic microarrays. Results showed that, when using the longer amplicon, not all bacterial targets hybridized with the complementary capture probes, which was characterized by the presence of false-positive signals. However, with the shorter amplicons, all bacterial species were correctly and completely detected using the constructed complementary capture probes.

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

    PubMed Central

    2010-01-01

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

  20. Microarray analysis of gene expression during early development: a cautionary overview.

    PubMed

    Robert, Claude

    2010-12-01

    The rise of the 'omics' technologies started nearly a decade ago and, among them, transcriptomics has been used successfully to contrast gene expression in mammalian oocytes and early embryos. The scarcity of biological material that early developmental stages provide is the prime reason why the field of transcriptomics is becoming more and more popular with reproductive biologists. The potential to amplify scarce mRNA samples and generate the necessary amounts of starting material enables the relative measurement of RNA abundance of thousands of candidates simultaneously. So far, microarrays have been the most commonly used high-throughput method in this field. Microarray platforms can be found in a wide variety of formats, from cDNA collections to long or short oligo probe sets. These platforms generate large amounts of data that require the integration of comparative RNA abundance values in the physiological context of early development for their full benefit to be appreciated. Unfortunately, significant discrepancies between datasets suggest that direct comparison between studies is difficult and often not possible. We have investigated the sample-handling steps leading to the generation of microarray data produced from prehatching embryo samples and have identified key steps that significantly impact the downstream results. This review provides a discussion on the best methods for the preparation of samples from early embryos for microarray analysis and focuses on the challenges that impede dataset comparisons from different platforms and the reasons why methodological benchmarking performed using somatic cells may not apply to the atypical nature of prehatching development.

  1. Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

    PubMed Central

    2013-01-01

    Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N > 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies. PMID:23822712

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

    PubMed

    Kong, Xiangrong; Mas, Valeria; Archer, Kellie J

    2008-02-26

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

  3. VARAN: a web server for variability analysis of DNA microarray experiments.

    PubMed

    Golfier, G; Dang, M Tran; Dauphinot, L; Graison, E; Rossier, J; Potier, M-C

    2004-07-10

    Here, we describe a tool for VARiability Analysis of DNA microarrays experiments (VARAN), a freely available Web server that performs a signal intensity based analysis of the log2 expression ratio variability deduced from DNA microarray data (one or two channels). Two modules are proposed: VARAN generator to compute a sliding windows analysis of the experimental variability (mean and SD) and VARAN analyzer to compare experimental data with an asymptotic variability model previously built with the generator module from control experiments. Both modules provide normalized intensity signals with five possible methods, log ratio values and a list of genes showing significant variations between conditions. http://www.bionet.espci.fr/varan/ http://www.bionet.espci.fr/varan/help.html

  4. Improving gene set analysis of microarray data by SAM-GS

    PubMed Central

    Dinu, Irina; Potter, John D; Mueller, Thomas; Liu, Qi; Adewale, Adeniyi J; Jhangri, Gian S; Einecke, Gunilla; Famulski, Konrad S; Halloran, Philip; Yasui, Yutaka

    2007-01-01

    Background Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary phenotype, and is of great biologic interest in many DNA microarray studies. Gene Set Enrichment Analysis (GSEA) has been applied widely as a tool for gene-set analyses. We describe here some critical problems with GSEA and propose an alternative method by extending the individual-gene analysis method, Significance Analysis of Microarray (SAM), to gene-set analyses (SAM-GS). Results Using a mouse microarray dataset with simulated gene sets, we illustrate that GSEA gives statistical significance to gene sets that have no gene associated with the phenotype (null gene sets), and has very low power to detect gene sets in which half the genes are moderately or strongly associated with the phenotype (truly-associated gene sets). SAM-GS, on the other hand, performs very well. The two methods are also compared in the analyses of three real microarray datasets and relevant pathways, the diverging results of which clearly show advantages of SAM-GS over GSEA, both statistically and biologically. In a microarray study for identifying biological pathways whose gene expressions are associated with p53 mutation in cancer cell lines, we found biologically relevant performance differences between the two methods. Specifically, there are 31 additional pathways identified as significant by SAM-GS over GSEA, that are associated with the presence vs. absence of p53. Of the 31 gene sets, 11 actually involve p53 directly as a member. A further 6 gene sets directly involve the extrinsic and intrinsic apoptosis pathways, 3 involve the cell-cycle machinery, and 3 involve cytokines and/or JAK/STAT signaling. Each of these 12 gene sets, then, is in a direct, well-established relationship with aspects of p53 signaling. Of the remaining 8 gene sets, 6 have plausible, if less well established, links with p53. Conclusion We

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

    PubMed Central

    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

  6. Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays.

    PubMed

    Degletagne, Cyril; Keime, Céline; Rey, Benjamin; de Dinechin, Marc; Forcheron, Fabien; Chuchana, Paul; Jouventin, Pierre; Gautier, Christian; Duchamp, Claude

    2010-05-31

    Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.

  7. Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

    PubMed Central

    2010-01-01

    Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979

  8. A rapid automatic processing platform for bead label-assisted microarray analysis: application for genetic hearing-loss mutation detection.

    PubMed

    Zhu, Jiang; Song, Xiumei; Xiang, Guangxin; Feng, Zhengde; Guo, Hongju; Mei, Danyang; Zhang, Guohao; Wang, Dong; Mitchelson, Keith; Xing, Wanli; Cheng, Jing

    2014-04-01

    Molecular diagnostics using microarrays are increasingly being used in clinical diagnosis because of their high throughput, sensitivity, and accuracy. However, standard microarray processing takes several hours and involves manual steps during hybridization, slide clean up, and imaging. Here we describe the development of an integrated platform that automates these individual steps as well as significantly shortens the processing time and improves reproducibility. The platform integrates such key elements as a microfluidic chip, flow control system, temperature control system, imaging system, and automated analysis of clinical results. Bead labeling of microarray signals required a simple imaging system and allowed continuous monitoring of the microarray processing. To demonstrate utility, the automated platform was used to genotype hereditary hearing-loss gene mutations. Compared with conventional microarray processing procedures, the platform increases the efficiency and reproducibility of hybridization, speeding microarray processing through to result analysis. The platform also continuously monitors the microarray signals, which can be used to facilitate optimization of microarray processing conditions. In addition, the modular design of the platform lends itself to development of simultaneous processing of multiple microfluidic chips. We believe the novel features of the platform will benefit its use in clinical settings in which fast, low-complexity molecular genetic testing is required.

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

    PubMed

    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

  10. [Diagnosis of a case with Williams-Beuren syndrome with nephrocalcinosis using chromosome microarray analysis].

    PubMed

    Jin, S J; Liu, M; Long, W J; Luo, X P

    2016-12-02

    Objective: To explore the clinical phenotypes and the genetic cause for a boy with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders. Method: Routine G-banding and chromosome microarray analysis were applied to a child with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders treated in the Department of Pediatrics of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in September 2015 and his parents to conduct the chromosomal karyotype analysis and the whole genome scanning. Deleted genes were searched in the Decipher and NCBI databases, and their relationships with the clinical phenotypes were analyzed. Result: A six-month-old boy was refered to us because of unexplained growth retardation and feeding intolerance.The affected child presented with abnormal manifestation such as special face, umbilical hernia, growth retardation, hypothyroidism, congenital heart disease, right ear sensorineural deafness, hypercalcemia and nephrocalcinosis. The child's karyotype was 46, XY, 16qh(+) , and his parents' karyotypes were normal. Chromosome microarray analysis revealed a 1 436 kb deletion on the 7q11.23(72701098_74136633) region of the child. This region included 23 protein-coding genes, which were reported to be corresponding to Williams-Beuren syndrome and its certain clinical phenotypes. His parents' results of chromosome microarray analysis were normal. Conclusion: A boy with characteristic manifestation of Williams-Beuren syndrome and rare nephrocalcinosis was diagnosed using chromosome microarray analysis. The deletion on the 7q11.23 might be related to the clinical phenotypes of Williams-Beuren syndrome, yet further studies are needed.

  11. Systematic analysis of microarray datasets to identify Parkinson's disease-associated pathways and genes

    PubMed Central

    Feng, Yinling; Wang, Xuefeng

    2017-01-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co-expression networks and clinical information was adopted, using weighted gene co-expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co-pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution-based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD-associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis. PMID:28098893

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

    PubMed

    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. Gene expression analysis: teaching students to do 30,000 experiments at once with microarray.

    PubMed

    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 sets. We present a microarray-based gene expression analysis experiment that is tailored for undergraduate students. The methods in this article describe an expression analysis experiment that can also be applied to CGH and SNP experiments. Factors such as technical difficulty, duration, cost, and availability of materials and equipments are considered in the lab design. The microarray teaching lab is performed in two sessions. The first is an introductory wet bench exercise that allows students to master the basic technical skills. The second builds on the concepts and skills with students acquiring and analyzing the microarray data. This lab exercise familiarizes students with large-scale data experiments and introduces them to the initial analysis steps. Copyright © 2011 Wiley Periodicals, Inc.

  14. Microarray analysis of differentially expressed genes between cysts and trophozoites of Acanthamoeba castellanii.

    PubMed

    Moon, Eun-Kyung; Xuan, Ying-Hua; Chung, Dong-Il; Hong, Yeonchul; Kong, Hyun-Hee

    2011-12-01

    Acanthamoeba infection is difficult to treat because of the resistance property of Acanthamoeba cyst against the host immune system, diverse antibiotics, and therapeutic agents. To identify encystation mediating factors of Acanthamoeba, we compared the transcription profile between cysts and trophozoites using microarray analysis. The DNA chip was composed of 12,544 genes based on expressed sequence tag (EST) from an Acanthamoeba ESTs database (DB) constructed in our laboratory, genetic information of Acanthamoeba from TBest DB, and all of Acanthamoeba related genes registered in the NCBI. Microarray analysis indicated that 701 genes showed higher expression than 2 folds in cysts than in trophozoites, and 859 genes were less expressed in cysts than in trophozoites. The results of real-time PCR analysis of randomly selected 9 genes of which expression was increased during cyst formation were coincided well with the microarray results. Eukaryotic orthologous groups (KOG) analysis showed an increment in T article (signal transduction mechanisms) and O article (posttranslational modification, protein turnover, and chaperones) whereas significant decrement of C article (energy production and conversion) during cyst formation. Especially, cystein proteinases showed high expression changes (282 folds) with significant increases in real-time PCR, suggesting a pivotal role of this proteinase in the cyst formation of Acanthamoeba. The present study provides important clues for the identification and characterization of encystation mediating factors of Acanthamoeba.

  15. New molecular phenotypes in the dst mutants of Arabidopsis revealed by DNA microarray analysis.

    PubMed

    Pérez-Amador, M A; Lidder, P; Johnson, M A; Landgraf, J; Wisman, E; Green, P J

    2001-12-01

    In this study, DNA microarray analysis was used to expand our understanding of the dst1 mutant of Arabidopsis. The dst (downstream) mutants were isolated originally as specifically increasing the steady state level and the half-life of DST-containing transcripts. As such, txhey offer a unique opportunity to study rapid sequence-specific mRNA decay pathways in eukaryotes. These mutants show a threefold to fourfold increase in mRNA abundance for two transgenes and an endogenous gene, all containing DST elements, when examined by RNA gel blot analysis; however, they show no visible aberrant phenotype. Here, we use DNA microarrays to identify genes with altered expression levels in dst1 compared with the parental plants. In addition to verifying the increase in the transgene mRNA levels, which were used to isolate these mutants, we were able to identify new genes with altered mRNA abundance in dst1. RNA gel blot analysis confirmed the microarray data for all genes tested and also was used to catalog the first molecular differences in gene expression between the dst1 and dst2 mutants. These differences revealed previously unknown molecular phenotypes for the dst mutants that will be helpful in future analyses. Cluster analysis of genes altered in dst1 revealed new coexpression patterns that prompt new hypotheses regarding the nature of the dst1 mutation and a possible role of the DST-mediated mRNA decay pathway in plants.

  16. Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

    PubMed

    Feng, Yinling; Wang, Xuefeng

    2017-03-01

    In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

  17. Blind source separation and the analysis of microarray data.

    PubMed

    Chiappetta, P; Roubaud, M C; Torrésani, B

    2004-01-01

    We develop an approach for the exploratory analysis of gene expression data, based upon blind source separation techniques. This approach exploits higher-order statistics to identify a linear model for (logarithms of) expression profiles, described as linear combinations of "independent sources." As a result, it yields "elementary expression patterns" (the "sources"), which may be interpreted as potential regulation pathways. Further analysis of the so-obtained sources show that they are generally characterized by a small number of specific coexpressed or antiexpressed genes. In addition, the projections of the expression profiles onto the estimated sources often provides significant clustering of conditions. The algorithm relies on a large number of runs of "independent component analysis" with random initializations, followed by a search of "consensus sources." It then provides estimates for independent sources, together with an assessment of their robustness. The results obtained on two datasets (namely, breast cancer data and Bacillus subtilis sulfur metabolism data) show that some of the obtained gene families correspond to well known families of coregulated genes, which validates the proposed approach.

  18. Statistical analysis of efficient unbalanced factorial designs for two-color microarray experiments.

    PubMed

    Tempelman, Robert J

    2008-01-01

    Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures. That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors. This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability.

  19. Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments

    PubMed Central

    Tempelman, Robert J.

    2008-01-01

    Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures. That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors. This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability. PMID:18584033

  20. Integration of optical waveguides and microfluidics in a miniaturized antibody micro-array system for life detection in the NASA/ESA ExoMars mission

    NASA Astrophysics Data System (ADS)

    Prak, A.; Leeuwis, H.; Heideman, R. G.; Leinse, A.; Borst, G.

    2011-02-01

    Novel developments in antibody micro-array technology allow the development of very sensitive instrument that is capable of detecting a wide variety of different biomarkers from a sample liquid. An international consortium led by the UK is currently developing the Life Marker Chip as an analytical instrument for the ExoMars mission in 2018 based on the use of immunoassay technique. In this paper it will be discussed how micro/nano system hardware has been designed and the connected fabrication technology has been developed, compatible with the requirements of a Mars mission instrument and allowing a seamless integration in the instrument. A microfluidic fused silica chip integrates all the relevant components for the analysis/assay procedure (except the pumping, which is performed by a syringe-type bellows pump). The fluidic chip therefore contains an entries for intake of the pretreated sample, chambers for the solution of preloaded reagents and the hybridization reaction, liquid front sensors, inputs and output ports for the selector valve and a channel structure connecting these components. Moreover, the design has three parallel fluidic pathways in order to allow for three different classes of assays. The whole fluidic design is driven by the requirement that the dead volumes and the total liquid volume are as small as possible. It appeared that a miniaturized and integrated selector valve has far better properties than a system with numerous integrated and externally, often pneumatically actuated on-off valves. Next to this, the connected volume and mass of the whole fluid management system is lower. An optical array chip incorporates integrated waveguides, which allow for excitation of the fluorescent labels by the evanescent field of the guided light wave. The system had to be designed in such a way that the light of a single fibercoupled lightsource is distributed over all the spots (10 x 10) of the array. The LioniX proprietary waveguide technology Tri

  1. Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

    NASA Astrophysics Data System (ADS)

    Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

    Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed

  2. Peptide-MHC Cellular Microarray with Innovative Data Analysis System for Simultaneously Detecting Multiple CD4 T-Cell Responses

    PubMed Central

    Ge, Xinhui; Gebe, John A.; Bollyky, Paul L.; James, Eddie A.; Yang, Junbao; Stern, Lawrence J.; Kwok, William W.

    2010-01-01

    Background Peptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation. Methodology/Principal Findings We co-immobilized peptide:DR0401 complexes, anti-CD28, anti-CD11a and cytokine capture antibodies on the surface of chamber slides to generate a functional array that was able to detect rare Ag-specific T cell populations from previously primed in vitro T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells. Conclusions/Significance The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings. PMID:20634998

  3. Long non-coding RNA expression profiles in gallbladder carcinoma identified using microarray analysis

    PubMed Central

    Wang, Jiwen; Liu, Han; Shen, Xiaokun; Wang, Yueqi; Zhang, Dexiang; Shen, Sheng; Suo, Tao; Pan, Hongtao; Ming, Yue; Ding, Kan; Liu, Houbao

    2017-01-01

    Gallbladder carcinoma (GBC) is the most common biliary tract cancer and exhibits poor patient prognosis. Previous studies have identified that long non-coding RNAs (lncRNAs) serve important regulatory roles in cancer biology. Alterations in lncRNAs are associated with several types of cancer. However, the contribution of lncRNAs to GBC remains unclear. To investigate the lncRNAs that are potentially involved in GBC, lncRNA profiles were identified in three pairs of human GBC and corresponding peri-carcinomatous tissue samples using microarray analysis. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the microarray data. In order to elucidate potential functions, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and network analysis were used to determine relevant signaling pathways. Abundant RNA probes were used, and 1,758 lncRNAs and 1,254 mRNAs were detected to be differentially expressed by the microarray. Compared with para-carcinoma tissue, numerous lncRNAs were markedly upregulated or downregulated in GBC. The results demonstrated that the lncRNAs that were downregulated in GBC were more numerous compared with the lncRNAs that were upregulated. Among them, RP11-152P17.2-006 was the most upregulated, whereas CTA-941F9.9 was the most downregulated. The RT-qPCR results were consistent with the microarray data. Pathway analysis indicated that five pathways corresponded to the differentially expressed transcripts. It was demonstrated that lncRNA expression in GBC was markedly altered, and a series of novel lncRNAs associated with GBC were identified. The results of the present study suggest that the functions of lncRNAs are important in GBC development and progression. PMID:28529578

  4. DNA microarray analysis of the liver of mice treated with cobalt chloride.

    PubMed

    Matsumoto, Kanako; Fujishiro, Hitomi; Satoh, Masahiko; Himeno, Seiichiro

    2010-12-01

    To investigate the in vivo effects of cobalt chloride on gene expression at early time points, DNA microarray analysis was performed on the liver of mice injected subcutaneously with cobalt chloride. The liver tissue samples were taken 0.5, 1, and 3 hr after injection. Of the 14 genes up-regulated at 0.5 hr after injection, 7 are related to immunological responses, and 4 of the 7 were found to be involved in the activation of interferon.

  5. Long non-coding RNA expression profiles in gallbladder carcinoma identified using microarray analysis.

    PubMed

    Wang, Jiwen; Liu, Han; Shen, Xiaokun; Wang, Yueqi; Zhang, Dexiang; Shen, Sheng; Suo, Tao; Pan, Hongtao; Ming, Yue; Ding, Kan; Liu, Houbao

    2017-05-01

    Gallbladder carcinoma (GBC) is the most common biliary tract cancer and exhibits poor patient prognosis. Previous studies have identified that long non-coding RNAs (lncRNAs) serve important regulatory roles in cancer biology. Alterations in lncRNAs are associated with several types of cancer. However, the contribution of lncRNAs to GBC remains unclear. To investigate the lncRNAs that are potentially involved in GBC, lncRNA profiles were identified in three pairs of human GBC and corresponding peri-carcinomatous tissue samples using microarray analysis. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the microarray data. In order to elucidate potential functions, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analysis, and network analysis were used to determine relevant signaling pathways. Abundant RNA probes were used, and 1,758 lncRNAs and 1,254 mRNAs were detected to be differentially expressed by the microarray. Compared with para-carcinoma tissue, numerous lncRNAs were markedly upregulated or downregulated in GBC. The results demonstrated that the lncRNAs that were downregulated in GBC were more numerous compared with the lncRNAs that were upregulated. Among them, RP11-152P17.2-006 was the most upregulated, whereas CTA-941F9.9 was the most downregulated. The RT-qPCR results were consistent with the microarray data. Pathway analysis indicated that five pathways corresponded to the differentially expressed transcripts. It was demonstrated that lncRNA expression in GBC was markedly altered, and a series of novel lncRNAs associated with GBC were identified. The results of the present study suggest that the functions of lncRNAs are important in GBC development and progression.

  6. Microarray analysis reveals altered circulating microRNA expression in mice infected with Coxsackievirus B3

    PubMed Central

    Sun, Chaoyu; Tong, Lei; Zhao, Wenran; Wang, Yan; Meng, Yuan; Lin, Lexun; Liu, Bingchen; Zhai, Yujia; Zhong, Zhaohua; Li, Xueqi

    2016-01-01

    Coxsackievirus B3 (CVB3) is a common causative agent in the development of inflammatory cardiomyopathy. However, whether the expression of peripheral blood microRNAs (miRNAs) is altered in this process is unknown. The present study investigated changes to miRNA expression in the peripheral blood of CVB3-infected mice. Utilizing miRNA microarray technology, differential miRNA expression was examined between normal and CVB3-infected mice. The present results suggest that specific miRNAs were differentially expressed in the peripheral blood of mice infected with CVB3, varying with infection duration. Using miRNA microarray analysis, a total of 96 and 89 differentially expressed miRNAs were identified in the peripheral blood of mice infected with CVB3 for 3 and 6 days, respectively. Quantitative polymerase chain reaction was used to validate differentially expressed miRNAs, revealing a consistency of these results with the miRNA microarray analysis results. The biological functions of the differentially expressed miRNAs were then predicted by bioinformatics analysis. The potential biological roles of differentially expressed miRNAs included hypertrophic cardiomyopathy, dilated cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. These results may provide important insights into the mechanisms responsible for the progression of CVB3 infection. PMID:27698715

  7. Bayesian Survival Analysis of High-Dimensional Microarray Data for Mantle Cell Lymphoma Patients.

    PubMed

    Moslemi, Azam; Mahjub, Hossein; Saidijam, Massoud; Poorolajal, Jalal; Soltanian, Ali Reza

    2016-01-01

    Survival time of lymphoma patients can be estimated with the help of microarray technology. In this study, with the use of iterative Bayesian Model Averaging (BMA) method, survival time of Mantle Cell Lymphoma patients (MCL) was estimated and in reference to the findings, patients were divided into two high- risk and low-risk groups. In this study, gene expression data of MCL patients were used in order to select a subset of genes for survival analysis with microarray data, using the iterative BMA method. To evaluate the performance of the method, patients were divided into high-risk and low-risk based on their scores. Performance prediction was investigated using the log-rank test. The bioconductor package "iterativeBMAsurv" was applied with R statistical software for classification and survival analysis. In this study, 25 genes associated with survival for MCL patients were identified across 132 selected models. The maximum likelihood estimate coefficients of the selected genes and the posterior probabilities of the selected models were obtained from training data. Using this method, patients could be separated into high-risk and low-risk groups with high significance (p<0.001). The iterative BMA algorithm has high precision and ability for survival analysis. This method is capable of identifying a few predictive variables associated with survival, among many variables in a set of microarray data. Therefore, it can be used as a low-cost diagnostic tool in clinical research.

  8. System Level Meta-analysis of Microarray Datasets for Elucidation of Diabetes Mellitus Pathobiology.

    PubMed

    Saxena, Aditya; Sachin, Kumar; Bhatia, Ashok Kumar

    2017-06-01

    Type 2 diabetes (T2D) is a common multi-factorial disease that is primarily ac-counted to ineffective insulin action in lowering blood glucose level and later escalates to impaired insu-lin secretion by pancreatic β cells. Deregulation in insulin signaling to its target organs is attributed to this disease phenotype. Various genome-wide microarray studies from multiple insulin responsive tis-sues have been conducted in past but due to inherent noise in microarray data and heterogeneity in dis-ease etiology; reproduction of prioritized pathways/genes is very low across various studies. In this study, we aim to identify consensus signaling and metabolic pathways through system level meta-analysis of multiple expression-sets to elucidate T2D pathobiology. We used 'R', an open source statistical environment, which is routinely used for Microarray data analysis particularly using special sets of packages available at Bioconductor. We primarily focused on gene-set analysis methods to elucidate various aspects of T2D. Literature-based evidences have shown the success of our approach in exploring various known aspects of diabetes pathophysiology. Our study stressed the need to develop novel bioinformatics workflows to advance our understanding further in insulin signaling.

  9. GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data

    PubMed Central

    Vaquerizas, Juan M.; Conde, Lucía; Yankilevich, Patricio; Cabezón, Amaya; Minguez, Pablo; Díaz-Uriarte, Ramón; Al-Shahrour, Fátima; Herrero, Javier; Dopazo, Joaquín

    2005-01-01

    The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With >76 000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at . PMID:15980548

  10. Analysis and modelling of septic shock microarray data using Singular Value Decomposition.

    PubMed

    Allanki, Srinivas; Dixit, Madhulika; Thangaraj, Paul; Sinha, Nandan Kumar

    2017-06-01

    Being a high throughput technique, enormous amounts of microarray data has been generated and there arises a need for more efficient techniques of analysis, in terms of speed and accuracy. Finding the differentially expressed genes based on just fold change and p-value might not extract all the vital biological signals that occur at a lower gene expression level. Besides this, numerous mathematical models have been generated to predict the clinical outcome from microarray data, while very few, if not none, aim at predicting the vital genes that are important in a disease progression. Such models help a basic researcher narrow down and concentrate on a promising set of genes which leads to the discovery of gene-based therapies. In this article, as a first objective, we have used the lesser known and used Singular Value Decomposition (SVD) technique to build a microarray data analysis tool that works with gene expression patterns and intrinsic structure of the data in an unsupervised manner. We have re-analysed a microarray data over the clinical course of Septic shock from Cazalis et al. (2014) and have shown that our proposed analysis provides additional information compared to the conventional method. As a second objective, we developed a novel mathematical model that predicts a set of vital genes in the disease progression that works by generating samples in the continuum between health and disease, using a simple normal-distribution-based random number generator. We also verify that most of the predicted genes are indeed related to septic shock. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Biofunctionalization of surfaces by energetic ion implantation: Review of progress on applications in implantable biomedical devices and antibody microarrays

    NASA Astrophysics Data System (ADS)

    Bilek, Marcela M. M.

    2014-08-01

    Despite major research efforts in the field of biomaterials, rejection, severe immune responses, scar tissue and poor integration continue to seriously limit the performance of today's implantable biomedical devices. Implantable biomaterials that interact with their host via an interfacial layer of active biomolecules to direct a desired cellular response to the implant would represent a major and much sought after improvement. Another, perhaps equally revolutionary, development that is on the biomedical horizon is the introduction of cost-effective microarrays for fast, highly multiplexed screening for biomarkers on cell membranes and in a variety of analyte solutions. Both of these advances will rely on effective methods of functionalizing surfaces with bioactive molecules. After a brief introduction to other methods currently available, this review will describe recently developed approaches that use energetic ions extracted from plasma to facilitate simple, one-step covalent surface immobilization of bioactive molecules. A kinetic theory model of the immobilization process by reactions with long-lived, mobile, surface-embedded radicals will be presented. The roles of surface chemistry and microstructure of the ion treated layer will be discussed. Early progress on applications of this technology to create diagnostic microarrays and to engineer bioactive surfaces for implantable biomedical devices will be reviewed.

  12. Outcome-Driven Cluster Analysis with Application to Microarray Data.

    PubMed

    Hsu, Jessie J; Finkelstein, Dianne M; Schoenfeld, David A

    2015-01-01

    One goal of cluster analysis is to sort characteristics into groups (clusters) so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes) into groups of highly correlated genes that have the same effect on the outcome (recovery). We propose a random effects model where the genes within each group (cluster) equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.

  13. Chipster: user-friendly analysis software for microarray and other high-throughput data

    PubMed Central

    2011-01-01

    Background The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Results Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Conclusions Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available. PMID:21999641

  14. Nutrient control of gene expression in Drosophila: microarray analysis of starvation and sugar-dependent response

    PubMed Central

    Zinke, Ingo; Schütz, Christina S.; Katzenberger, Jörg D.; Bauer, Matthias; Pankratz, Michael J.

    2002-01-01

    We have identified genes regulated by starvation and sugar signals in Drosophila larvae using whole-genome microarrays. Based on expression profiles in the two nutrient conditions, they were organized into different categories that reflect distinct physiological pathways mediating sugar and fat metabolism, and cell growth. In the category of genes regulated in sugar-fed, but not in starved, animals, there is an upregulation of genes encoding key enzymes of the fat biosynthesis pathway and a downregulation of genes encoding lipases. The highest and earliest activated gene upon sugar ingestion is sugarbabe, a zinc finger protein that is induced in the gut and the fat body. Identification of potential targets using microarrays suggests that sugarbabe functions to repress genes involved in dietary fat breakdown and absorption. The current analysis provides a basis for studying the genetic mechanisms underlying nutrient signalling. PMID:12426388

  15. Membrane gene ontology bias in sequencing and microarray obtained by housekeeping-gene analysis.

    PubMed

    Zhang, Yijuan; Akintola, Oluwafemi S; Liu, Ken J A; Sun, Bingyun

    2016-01-10

    Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Nano rolling-circle amplification for enhanced SERS hot spots in protein microarray analysis.

    PubMed

    Yan, Juan; Su, Shao; He, Shijiang; He, Yao; Zhao, Bin; Wang, Dongfang; Zhang, Honglu; Huang, Qing; Song, Shiping; Fan, Chunhai

    2012-11-06

    Although "hot spots" have been proved to contribute to surface enhanced Raman scattering (SERS), less attention was paid to increase the number of the "hot spot" to directly enhance the Raman signals in bioanalytical systems. Here we report a new strategy based on nano rolling-circle amplification (nanoRCA) and nano hyperbranched rolling-circle amplification (nanoHRCA) to increase "hot spot" groups for protein microarrays. First, protein and ssDNA are coassembled on gold nanoparticles, making the assembled probe have both binding ability and hybridization ability. Second, the ssDNAs act as primers to initiate in situ RCA reaction to produced long ssDNAs. Third, a large number of SERS probes are loaded on the long ssDNA templetes, allowing thousands of SERS probes involved in each biomolecular recognition event. The strategy offered high-efficiency Raman enhancement and could detect less than 10 zeptomolar protein molecules in protein microarray analysis.

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

    PubMed

    Vêncio, Ricardo Z N; Koide, Tie; Gomes, Suely L; Pereira, Carlos A de B

    2006-02-23

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

  18. Microarray analysis of differentially expressed genes engaged in fruit development between Prunus mume and Prunus armeniaca.

    PubMed

    Li, Xiaoying; Korir, Nicholas Kibet; Liu, Lili; Shangguan, Lingfei; Wang, Yuzhu; Han, Jian; Chen, Ming; Fang, Jinggui

    2012-11-15

    Microarray analysis is a technique that can be employed to provide expression profiles of single genes and new insights to elucidate the biological mechanisms responsible for fruit development. To evaluate expression of genes mostly engaged in fruit development between Prunus mume and Prunus armeniaca, we first identified differentially expressed transcripts along the entire fruit life cycle by using microarrays spotted with 10,641 ESTs collected from P. mume and other Prunus EST sequences. A total of 1418 ESTs were selected after quality control of microarray spots and analysis for differential gene expression patterns during fruit development of P. mume and P. Armeniaca. From these, 707 up-regulated and 711 down-regulated genes showing more than two-fold differences in expression level were annotated by GO based on biological processes, molecular functions and cellular components. These differentially expressed genes were found to be involved in several important pathways of carbohydrate, galactose, and starch and sucrose metabolism as well as in biosynthesis of other secondary metabolites via KEGG. This could provide detailed information on the fruit quality differences during development and ripening of these two species. With the results obtained, we provide a practical database for comprehensive understanding of molecular events during fruit development and also lay a theoretical foundation for the cloning of genes regulating in a series of important rate-limiting enzymes involved in vital metabolic pathways during fruit development. Copyright © 2012 Elsevier GmbH. All rights reserved.

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

    PubMed Central

    Vêncio, Ricardo ZN; Koide, Tie; Gomes, Suely L; de B Pereira, Carlos A

    2006-01-01

    Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis. PMID:16504085

  20. Application of microarray analysis of foodborne Salmonella in poultry production: a review.

    PubMed

    Ricke, Steven C; Khatiwara, Anita; Kwon, Young Min

    2013-09-01

    Salmonellosis in the United States is one of the most costly foodborne diseases. Given that Salmonella can originate from a wide variety of environments, reduction of this organism at all stages of poultry production is critical. Salmonella species can encounter various environmental stress conditions that can dramatically influence their survival and virulence. Previous knowledge of Salmonella species genomic regulation of metabolism and physiology in relation to poultry is based on limited information of a few well-characterized genes. Consequently, although there is some information about environmental signals that control Salmonella growth and pathogenesis, much still remains unknown. Advancements in DNA sequencing technologies revolutionized the way bacteria were studied and molecular tools such as microarrays have subsequently been used for comprehensive transcriptomic analysis of Salmonella. With microarray analysis, the expression levels of each single gene in the Salmonella genome can be directly assessed and previously unknown genetic systems that are required for Salmonella growth and survival in the poultry production cycle can be elucidated. This represents an opportunity for development of novel approaches for limiting Salmonella establishment in all phases of poultry production. In this review, recent advances in transcriptome-microarray technologies that are facilitating a better understanding of Salmonella biology in poultry production and processing are discussed.

  1. Single exon-resolution targeted chromosomal microarray analysis of known and candidate intellectual disability genes

    PubMed Central

    Tucker, Tracy; Zahir, Farah R; Griffith, Malachi; Delaney, Allen; Chai, David; Tsang, Erica; Lemyre, Emmanuelle; Dobrzeniecka, Sylvia; Marra, Marco; Eydoux, Patrice; Langlois, Sylvie; Hamdan, Fadi F; Michaud, Jacques L; Friedman, Jan M

    2014-01-01

    Intellectual disability affects about 3% of individuals globally, with∼50% idiopathic. We designed an exonic-resolution array targeting all known submicroscopic chromosomal intellectual disability syndrome loci, causative genes for intellectual disability, and potential candidate genes, all genes encoding glutamate receptors and epigenetic regulators. Using this platform, we performed chromosomal microarray analysis on 165 intellectual disability trios (affected child and both normal parents). We identified and independently validated 36 de novo copy-number changes in 32 trios. In all, 67% of the validated events were intragenic, involving only exon 1 (which includes the promoter sequence according to our design), exon 1 and adjacent exons, or one or more exons excluding exon 1. Seventeen of the 36 copy-number variants involve genes known to cause intellectual disability. Eleven of these, including seven intragenic variants, are clearly pathogenic (involving STXBP1, SHANK3 (3 patients), IL1RAPL1, UBE2A, NRXN1, MEF2C, CHD7, 15q24 and 9p24 microdeletion), two are likely pathogenic (PI4KA, DCX), two are unlikely to be pathogenic (GRIK2, FREM2), and two are unclear (ARID1B, 15q22 microdeletion). Twelve individuals with genomic imbalances identified by our array were tested with a clinical microarray, and six had a normal result. We identified de novo copy-number variants within genes not previously implicated in intellectual disability and uncovered pathogenic variation of known intellectual disability genes below the detection limit of standard clinical diagnostic chromosomal microarray analysis. PMID:24253858

  2. Single exon-resolution targeted chromosomal microarray analysis of known and candidate intellectual disability genes.

    PubMed

    Tucker, Tracy; Zahir, Farah R; Griffith, Malachi; Delaney, Allen; Chai, David; Tsang, Erica; Lemyre, Emmanuelle; Dobrzeniecka, Sylvia; Marra, Marco; Eydoux, Patrice; Langlois, Sylvie; Hamdan, Fadi F; Michaud, Jacques L; Friedman, Jan M

    2014-06-01

    Intellectual disability affects about 3% of individuals globally, with∼50% idiopathic. We designed an exonic-resolution array targeting all known submicroscopic chromosomal intellectual disability syndrome loci, causative genes for intellectual disability, and potential candidate genes, all genes encoding glutamate receptors and epigenetic regulators. Using this platform, we performed chromosomal microarray analysis on 165 intellectual disability trios (affected child and both normal parents). We identified and independently validated 36 de novo copy-number changes in 32 trios. In all, 67% of the validated events were intragenic, involving only exon 1 (which includes the promoter sequence according to our design), exon 1 and adjacent exons, or one or more exons excluding exon 1. Seventeen of the 36 copy-number variants involve genes known to cause intellectual disability. Eleven of these, including seven intragenic variants, are clearly pathogenic (involving STXBP1, SHANK3 (3 patients), IL1RAPL1, UBE2A, NRXN1, MEF2C, CHD7, 15q24 and 9p24 microdeletion), two are likely pathogenic (PI4KA, DCX), two are unlikely to be pathogenic (GRIK2, FREM2), and two are unclear (ARID1B, 15q22 microdeletion). Twelve individuals with genomic imbalances identified by our array were tested with a clinical microarray, and six had a normal result. We identified de novo copy-number variants within genes not previously implicated in intellectual disability and uncovered pathogenic variation of known intellectual disability genes below the detection limit of standard clinical diagnostic chromosomal microarray analysis.

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

    PubMed

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

    2015-08-07

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

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

    PubMed Central

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

    2015-01-01

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

  5. Whole Genome Microarray Analysis of Gene Expression in Prader–Willi Syndrome

    PubMed Central

    Bittel, Douglas C.; Kibiryeva, Nataliya; Sell, Susan M.; Strong, Theresa V.; Butler, Merlin G.

    2017-01-01

    Prader–Willi syndrome (PWS) is caused by loss of function of paternally expressed genes in the 15q11-q13 region and a paucity of data exists on transcriptome variation. To further characterize genetic alterations in this classic obesity syndrome using whole genome microarrays to analyze gene expression, microarray and quantitative RT-PCR analysis were performed using RNA isolated from lymphoblastoid cells from PWS male subjects (four with 15q11-q13 deletion and three with UPD) and three age and cognition matched nonsyndromic comparison males. Of more than 47,000 probes examined in the microarray, 23,383 were detectable and 323 had significantly different expression in the PWS lymphoblastoid cells relative to comparison cells, 14 of which were related to neurodevelopment and function. As expected, there was no evidence of expression of paternally expressed genes from the 15q11-q13 region (e.g., SNRPN) in the PWS cells. Alterations in expression of serotonin receptor genes (e.g., HTR2B) and genes involved in eating behavior and obesity (ADIPOR2, MC2R, HCRT, OXTR) were noted. Other genes of interest with reduced expression in PWS subjects included STAR (a key regulator of steroid synthesis) and SAG (an arrestin family member which desensitizes G-protein-coupled receptors). Quantitative RT-PCR for SAG, OXTR, STAR, HCRT, and HTR2B using RNA isolated from their lymphoblastoid cells and available brain tissue (frontal cortex) from separate individuals with PWS and control subjects and normalized to GAPD gene expression levels validated our microarray gene expression data. Our analysis identified previously unappreciated changes in gene expression which may contribute to the clinical manifestations seen in PWS. PMID:17236194

  6. Predicting microRNA targets in time-series microarray experiments via functional data analysis.

    PubMed

    Parker, Brian J; Wen, Jiayu

    2009-01-30

    MicroRNA (miRNA) target prediction is an important component in understanding gene regulation. One approach is computational: searching nucleotide sequences for miRNA complementary base pairing. An alternative approach explored in this paper is the use of gene expression profiles from time-series microarray experiments to aid in miRNA target prediction. This requires distinguishing genuine targets from genes that are secondarily down-regulated as part of the same regulatory module. We use a functional data analytic (FDA) approach, FDA being a subfield of statistics that extends standard multivariate techniques to datasets with predictor and/or response variables that are functional. In a miR-124 transfection experiment spanning 120 hours, for genes with measurably down-regulated mRNA, exploratory functional data analysis showed differences in expression profiles over time between directly and indirectly down-regulated genes, such as response latency and biphasic response for direct miRNA targets. For prediction, an FDA approach was shown to effectively classify direct miR-124 targets from time-series microarray data (accuracy 88%; AUC 0.96), providing better performance than multivariate approaches. Exploratory FDA analysis can reveal interesting aspects of dynamic microarray miRNA studies. Predictive FDA models can be applied where computational miRNA target predictors fail or are unreliable, e.g. when there is a lack of evolutionary conservation, and can provide posterior probabilities to provide additional confirmatory evidence to validate candidate miRNA targets computationally predicted using sequence information. This approach would be applicable to the investigation of other miRNAs and suggests that dynamic microarray studies at a higher time resolution could reveal further details on miRNA regulation.

  7. Subunit mass analysis for monitoring antibody oxidation

    PubMed Central

    Sokolowska, Izabela; Mo, Jingjie; Dong, Jia; Lewis, Michael J.; Hu, Ping

    2017-01-01

    ABSTRACT Methionine oxidation is a common posttranslational modification (PTM) of monoclonal antibodies (mAbs). Oxidation can reduce the in-vivo half-life, efficacy and stability of the product. Peptide mapping is commonly used to monitor the levels of oxidation, but this is a relatively time-consuming method. A high-throughput, automated subunit mass analysis method was developed to monitor antibody methionine oxidation. In this method, samples were treated with IdeS, EndoS and dithiothreitol to generate three individual IgG subunits (light chain, Fd’ and single chain Fc). These subunits were analyzed by reversed phase-ultra performance liquid chromatography coupled with an online quadrupole time-of-flight mass spectrometer and the levels of oxidation on each subunit were quantitated based on the deconvoluted mass spectra using the UNIFI software. The oxidation results obtained by subunit mass analysis correlated well with the results obtained by peptide mapping. Method qualification demonstrated that this subunit method had excellent repeatability and intermediate precision. In addition, UNIFI software used in this application allows automated data acquisition and processing, which makes this method suitable for high-throughput process monitoring and product characterization. Finally, subunit mass analysis revealed the different patterns of Fc methionine oxidation induced by chemical and photo stress, which makes it attractive for investigating the root cause of oxidation. PMID:28106519

  8. Subunit mass analysis for monitoring antibody oxidation.

    PubMed

    Sokolowska, Izabela; Mo, Jingjie; Dong, Jia; Lewis, Michael J; Hu, Ping

    2017-04-01

    Methionine oxidation is a common posttranslational modification (PTM) of monoclonal antibodies (mAbs). Oxidation can reduce the in-vivo half-life, efficacy and stability of the product. Peptide mapping is commonly used to monitor the levels of oxidation, but this is a relatively time-consuming method. A high-throughput, automated subunit mass analysis method was developed to monitor antibody methionine oxidation. In this method, samples were treated with IdeS, EndoS and dithiothreitol to generate three individual IgG subunits (light chain, Fd' and single chain Fc). These subunits were analyzed by reversed phase-ultra performance liquid chromatography coupled with an online quadrupole time-of-flight mass spectrometer and the levels of oxidation on each subunit were quantitated based on the deconvoluted mass spectra using the UNIFI software. The oxidation results obtained by subunit mass analysis correlated well with the results obtained by peptide mapping. Method qualification demonstrated that this subunit method had excellent repeatability and intermediate precision. In addition, UNIFI software used in this application allows automated data acquisition and processing, which makes this method suitable for high-throughput process monitoring and product characterization. Finally, subunit mass analysis revealed the different patterns of Fc methionine oxidation induced by chemical and photo stress, which makes it attractive for investigating the root cause of oxidation.

  9. Rapid O serogroup identification of the six clinically relevant Shiga toxin-producing Escherichia coli by antibody microarray

    USDA-ARS?s Scientific Manuscript database

    Antibody array was developed for the detection of the top six non-O157 Shiga toxin-producing Escherichia coli O serogroups. Sensitivity of the array was 10**5 CFU, and the limit of detection of serogroups in ground beef was 1-10 CFU following 12 h of enrichment. The array utilized a minimal amount...

  10. Transcript-Specific Expression Profiles Derived from Sequence-Based Analysis of Standard Microarrays

    PubMed Central

    Moll, Anton G.; Lindenmeyer, Maja T.; Kretzler, Matthias; Nelson, Peter J.; Zimmer, Ralf; Cohen, Clemens D.

    2009-01-01

    Background Alternative mRNA processing mechanisms lead to multiple transcripts (i.e. splice isoforms) of a given gene which may have distinct biological functions. Microarrays like Affymetrix GeneChips measure mRNA expression of genes using sets of nucleotide probes. Until recently probe sets were not designed for transcript specificity. Nevertheless, the re-analysis of established microarray data using newly defined transcript-specific probe sets may provide information about expression levels of specific transcripts. Methodology/Principal Findings In the present study alignment of probe sequences of the Affymetrix microarray HG-U133A with Ensembl transcript sequences was performed to define transcript-specific probe sets. Out of a total of 247,965 perfect match probes, 95,008 were designated “transcript-specific”, i.e. showing complete sequence alignment, no cross-hybridization, and transcript-, not only gene-specificity. These probes were grouped into 7,941 transcript-specific probe sets and 15,619 gene-specific probe sets, respectively. The former were used to differentiate 445 alternative transcripts of 215 genes. For selected transcripts, predicted by this analysis to be differentially expressed in the human kidney, confirmatory real-time RT-PCR experiments were performed. First, the expression of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was determined by the transcript-specific array analysis and confirmed by real-time RT-PCR. Secondly, disease-specific differential expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and Q5VYS0_HUMAN) was computed from the available array data sets and confirmed by transcript-specific real-time RT-PCR. Conclusions Transcript-specific analysis of microarray experiments can be employed to study gene-regulation on the transcript level using conventional microarray data. In this study, predictions based on sufficient probe set size and

  11. Extreme value distribution based gene selection criteria for discriminant microarray data analysis using logistic regression.

    PubMed

    Li, Wentian; Sun, Fengzhu; Grosse, Ivo

    2004-01-01

    One important issue commonly encountered in the analysis of microarray data is to decide which and how many genes should be selected for further studies. For discriminant microarray data analyses based on statistical models, such as the logistic regression models, gene selection can be accomplished by a comparison of the maximum likelihood of the model given the real data, L(D|M), and the expected maximum likelihood of the model given an ensemble of surrogate data with randomly permuted label, L(D(0)|M). Typically, the computational burden for obtaining L(D(0)M) is immense, often exceeding the limits of available computing resources by orders of magnitude. Here, we propose an approach that circumvents such heavy computations by mapping the simulation problem to an extreme-value problem. We present the derivation of an asymptotic distribution of the extreme-value as well as its mean, median, and variance. Using this distribution, we propose two gene selection criteria, and we apply them to two microarray datasets and three classification tasks for illustration.

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

    PubMed Central

    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

  13. Array painting: a protocol for the rapid analysis of aberrant chromosomes using DNA microarrays

    PubMed Central

    Gribble, Susan M; Ng, Bee Ling; Prigmore, Elena; Fitzgerald, Tomas; Carter, Nigel P

    2012-01-01

    Aarray painting is a technique that uses microarray technology to rapidly map chromosome translocation breakpoints. previous methods to map translocation breakpoints have used fluorescence in situ hybridization (FIsH) and have consequently been labor-intensive, time-consuming and restricted to the low breakpoint resolution imposed by the use of metaphase chromosomes. array painting combines the isolation of derivative chromosomes (chromosomes with translocations) and high-resolution microarray analysis to refine the genomic location of translocation breakpoints in a single experiment. In this protocol, we describe array painting by isolation of derivative chromosomes using a MoFlo flow sorter, amplification of these derivatives using whole-genome amplification and hybridization onto commercially available oligonucleotide microarrays. although the sorting of derivative chromosomes is a specialized procedure requiring sophisticated equipment, the amplification, labeling and hybridization of Dna is straightforward, robust and can be completed within 1 week. the protocol described produces good quality data; however, array painting is equally achievable using any combination of the available alternative methodologies for chromosome isolation, amplification and hybridization. PMID:19893508

  14. Microarray gene expression profiling analysis combined with bioinformatics in multiple sclerosis.

    PubMed

    Liu, Mingyuan; Hou, Xiaojun; Zhang, Ping; Hao, Yong; Yang, Yiting; Wu, Xiongfeng; Zhu, Desheng; Guan, Yangtai

    2013-05-01

    Multiple sclerosis (MS) is the most prevalent demyelinating disease and the principal cause of neurological disability in young adults. Recent microarray gene expression profiling studies have identified several genetic variants contributing to the complex pathogenesis of MS, however, expressional and functional studies are still required to further understand its molecular mechanism. The present study aimed to analyze the molecular mechanism of MS using microarray analysis combined with bioinformatics techniques. We downloaded the gene expression profile of MS from Gene Expression Omnibus (GEO) and analysed the microarray data using the differentially coexpressed genes (DCGs) and links package in R and Database for Annotation, Visualization and Integrated Discovery. The regulatory impact factor (RIF) algorithm was used to measure the impact factor of transcription factor. A total of 1,297 DCGs between MS patients and healthy controls were identified. Functional annotation indicated that these DCGs were associated with immune and neurological functions. Furthermore, the RIF result suggested that IKZF1, BACH1, CEBPB, EGR1, FOS may play central regulatory roles in controlling gene expression in the pathogenesis of MS. Our findings confirm the presence of multiple molecular alterations in MS and indicate the possibility for identifying prognostic factors associated with MS pathogenesis.

  15. RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection.

    PubMed

    Venu, R C; Jia, Yulin; Gowda, Malali; Jia, Melissa H; Jantasuriyarat, Chatchawan; Stahlberg, Eric; Li, Huameng; Rhineheart, Andrew; Boddhireddy, Prashanth; Singh, Pratibha; Rutger, Neil; Kudrna, David; Wing, Rod; Nelson, James C; Wang, Guo-Liang

    2007-10-01

    Sheath blight caused by the fungal pathogen Rhizoctonia solani is an emerging problem in rice production worldwide. To elucidate the molecular basis of rice defense to the pathogen, RNA isolated from R. solani-infected leaves of Jasmine 85 was used for both RL-SAGE library construction and microarray hybridization. RL-SAGE sequence analysis identified 20,233 and 24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half of the significant tags (> or =2 copies) from both libraries matched TIGR annotated genes and KOME full-length cDNAs. Among them, 42% represented sense and 7% antisense transcripts, respectively. Interestingly, 60% of the library-specific (> or =10 copies) and differentially expressed (>4.0-fold change) tags were novel transcripts matching genomic sequence but not annotated genes. About 70% of the genes identified in the SAGE libraries showed similar expression patterns (up or down-regulated) in the microarray data obtained from three biological replications. Some candidate RL-SAGE tags and microarray genes were located in known sheath blight QTL regions. The expression of ten differentially expressed RL-SAGE tags was confirmed with RT-PCR. The defense genes associated with resistance to R. solani identified in this study are useful genomic materials for further elucidation of the molecular basis of the defense response to R. solani and fine mapping of target sheath blight QTLs.

  16. Neural network analysis of lymphoma microarray data: prognosis and diagnosis near-perfect

    PubMed Central

    O'Neill, Michael C; Song, Li

    2003-01-01

    Background Microarray chips are being rapidly deployed as a major tool in genomic research. To date most of the analysis of the enormous amount of information provided on these chips has relied on clustering techniques and other standard statistical procedures. These methods, particularly with regard to cancer patient prognosis, have generally been inadequate in providing the reduced gene subsets required for perfect classification. Results Networks trained on microarray data from DLBCL lymphoma patients have, for the first time, been able to predict the long-term survival of individual patients with 100% accuracy. Other networks were able to distinguish DLBCL lymphoma donors from other donors, including donors with other lymphomas, with 99% accuracy. Differentiating the trained network can narrow the gene profile to less than three dozen genes for each classification. Conclusions Here we show that artificial neural networks are a superior tool for digesting microarray data both with regard to making distinctions based on the data and with regard to providing very specific reference as to which genes were most important in making the correct distinction in each case. PMID:12697066

  17. Global gene expression analysis of two Streptococcus thermophilus bacteriophages using DNA microarray.

    PubMed

    Duplessis, Martin; Russell, W Michael; Romero, Dennis A; Moineau, Sylvain

    2005-09-30

    A custom microarray was developed to study the temporal gene expression of the two groups of phages infecting the Gram-positive lactic acid bacterium Streptococcus thermophilus. The complete genomic sequence of the virulent cos-type phage DT1 (34,815 bp) and the pac-type phage 2972 (34,704 bp) were used for the construction of the microarray. Gene expression was measured at nine time intervals (0, 2, 7, 12, 17, 22, 27, 32 and 37 min) during phage infection and an expression curve was determined for each gene. Each phage gene was then classified into one of the three traditional transcription classes and these data were used to generate the complete transcriptional map of DT1 and 2972. Phage DT1 possesses 18 early genes, 12 middle genes and 12 late-expressed genes whereas 2972 has 16 early, 11 middle and 14 late genes. The trends of the phage gene expression profiles were also confirmed by slot blot hybridizations. Significant differences were observed when comparing the transcriptional maps of DT1 and 2972 with those already available for the S. thermophilus phages Sfi19 and Sfi21. To our knowledge, this report presents the first complete transcription analysis of bacteriophages infecting Gram-positive bacteria using the DNA microarray technology.

  18. Differential modulation of Bordetella pertussis virulence genes as evidenced by DNA microarray analysis.

    PubMed

    Hot, D; Antoine, R; Renauld-Mongénie, G; Caro, V; Hennuy, B; Levillain, E; Huot, L; Wittmann, G; Poncet, D; Jacob-Dubuisson, F; Guyard, C; Rimlinger, F; Aujame, L; Godfroid, E; Guiso, N; Quentin-Millet, M-J; Lemoine, Y; Locht, C

    2003-07-01

    The production of most factors involved in Bordetella pertussis virulence is controlled by a two-component regulatory system termed BvgA/S. In the Bvg+ phase virulence-activated genes (vags) are expressed, and virulence-repressed genes (vrgs) are down-regulated. The expression of these genes can also be modulated by MgSO(4) or nicotinic acid. In this study we used microarrays to analyse the influence of BvgA/S or modulation on the expression of nearly 200 selected genes. With the exception of one vrg, all previously known vags and vrgs were correctly assigned as such, and the microarray analyses identified several new vags and vrgs, including genes coding for putative autotransporters, two-component systems, extracellular sigma factors, the adenylate cyclase accessory genes cyaBDE, and two genes coding for components of a type III secretion system. For most of the new vrgs and vags the results of the microarray analyses were confirmed by RT-PCR analysis and/or lacZfusions. The degree of regulation and modulation varied between genes, and showed a continuum from strongly BvgA/S-activated genes to strongly BvgA/S-repressed genes. The microarray analyses also led to the identification of a subset of vags and vrgs that are differentially regulated and modulated by MgSO(4) or nicotinic acid, indicating that these genes may be targets for multiple regulatory circuits. For example, the expression of bilA, a gene predicted to encode an intimin-like protein, was found to be activated by BvgA/S and up-modulated by nicotinic acid. Furthermore, surprisingly, in the strain analysed here, which produces only type 2 fimbriae, the fim3 gene was identified as a vrg, while fim2 was confirmed to be a vag.

  19. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis

    PubMed Central

    Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

    2016-01-01

    A high phosphorus (HP) diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus) or a HP diet (containing 1.2% phosphorus). Gene Ontology analysis of differentially expressed genes (DEGs) revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054) in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty acids

  20. A High Phosphorus Diet Affects Lipid Metabolism in Rat Liver: A DNA Microarray Analysis.

    PubMed

    Chun, Sunwoo; Bamba, Takeshi; Suyama, Tatsuya; Ishijima, Tomoko; Fukusaki, Eiichiro; Abe, Keiko; Nakai, Yuji

    2016-01-01

    A high phosphorus (HP) diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus) or a HP diet (containing 1.2% phosphorus). Gene Ontology analysis of differentially expressed genes (DEGs) revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054) in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty acids

  1. Detection of total and A1c-glycosylated hemoglobin in human whole blood using sandwich immunoassays on polydimethylsiloxane-based antibody microarrays.

    PubMed

    Chen, Huang-Han; Wu, Chih-Hsing; Tsai, Mei-Ling; Huang, Yi-Jing; Chen, Shu-Hui

    2012-10-16

    The percentage of glycosylated hemoglobin A1c (%GHbA1c) in human whole blood indicates the average plasma glucose concentration over a prolonged period of time and is used to diagnose diabetes. However, detecting GHbA1c in the whole blood using immunoassays has limited detection sensitivity due to its low percentage in total hemoglobin (tHb) and interference from various glycan moieties in the sample. We have developed a sandwich immunoassay using an antibody microarray on a polydimethylsiloxane (PDMS) substrate modified with fluorinated compounds to detect tHb and glycosylated hemoglobin A1c (GHbA1c) in human whole blood without sample pretreatment. A polyclonal antibody against hemoglobin (Hb) immobilized on PDMS is used as a common capture probe to enrich all forms of Hb followed by detection via monoclonal anti-Hb and specific monoclonal anti-GHbA1c antibodies for tHb and GHbA1c detection, respectively. This method prevents the use of glycan binding molecules and dramatically reduces the background interference, yielding a detection limit of 3.58 ng/mL for tHb and 0.20 ng/mL for GHbA1c. The fluorinated modification on PDMS is superior to the glass substrate and eliminates the need for the blocking step which is required in commercial enzyme linked immunosorbent assay (ELISA) kits. Moreover, the detection sensitivity for GHbA1c is 4-5 orders of magnitude higher, but the required sample amount is 25 times less than the commercial method. On the basis of patient sample data, a good linear correlation between %GHbA1c values determined by our method and the certified high performance liquid chromatography (HPLC) standard method is shown with R(2) > 0.98, indicating the great promise of the developed method for clinical applications.

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

    PubMed

    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.

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

    PubMed Central

    2010-01-01

    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. PMID:20509938

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

    PubMed Central

    2011-01-01

    Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024) groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide. Comparative analyses with

  5. High-content single-cell analysis on-chip using a laser microarray scanner.

    PubMed

    Zhou, Jing; Wu, Yu; Lee, Sang-Kwon; Fan, Rong

    2012-12-07

    High-content cellomic analysis is a powerful tool for rapid screening of cellular responses to extracellular cues and examination of intracellular signal transduction pathways at the single-cell level. In conjunction with microfluidics technology that provides unique advantages in sample processing and precise control of fluid delivery, it holds great potential to transform lab-on-a-chip systems for high-throughput cellular analysis. However, high-content imaging instruments are expensive, sophisticated, and not readily accessible. Herein, we report on a laser scanning cytometry approach that exploits a bench-top microarray scanner as an end-point reader to perform rapid and automated fluorescence imaging of cells cultured on a chip. Using high-content imaging analysis algorithms, we demonstrated multiplexed measurements of morphometric and proteomic parameters from all single cells. Our approach shows the improvement of both sensitivity and dynamic range by two orders of magnitude as compared to conventional epifluorescence microscopy. We applied this technology to high-throughput analysis of mesenchymal stem cells on an extracellular matrix protein array and characterization of heterotypic cell populations. This work demonstrates the feasibility of a laser microarray scanner for high-content cellomic analysis and opens up new opportunities to conduct informative cellular analysis and cell-based screening in the lab-on-a-chip systems.

  6. Extending the Interpretation of Gene Profiling Microarray Experiments to Pathway Analysis Through the Use of Gene Ontology Terms

    NASA Astrophysics Data System (ADS)

    Chatziioannou, Aristotelis; Moulos, Panagiotis

    Microarray technology allows the survey of gene expression at a global level by measuring mRNA abundance. However, the grand complexity characterizing a microarray experiment entails the development of computationally powerful tools apt for probing the biological problem studied. Here we propose a suite for flexible, adaptable to a wide range of possible needs of the biological end-user, data-driven interpretation of microarray experiments. The suite is implemented in MATLAB and is making use of two modules, able to perform all steps of typical microarray data analysis starting from data standardization and normalization up to statistical selection and pathway analysis utilizing Gene Ontology Term annotations for the species genomes interrogated, whereas due to its modular structure it is scalable thus enabling the incorporation or its seamless assembly with other existing tools.

  7. Development of a prostate cDNA microarray and statistical gene expression analysis package.

    PubMed

    Carlisle, A J; Prabhu, V V; Elkahloun, A; Hudson, J; Trent, J M; Linehan, W M; Williams, E D; Emmert-Buck, M R; Liotta, L A; Munson, P J; Krizman, D B

    2000-05-01

    A cDNA microarray comprising 5184 different cDNAs spotted onto nylon membrane filters was developed for prostate gene expression studies. The clones used for arraying were identified by cluster analysis of > 35 000 prostate cDNA library-derived expressed sequence tags (ESTs) present in the dbEST database maintained by the National Center for Biotechnology Information. Total RNA from two cell lines, prostate line 8.4 and melanoma line UACC903, was used to make radiolabeled probe for filter hybridizations. The absolute intensity of each individual cDNA spot was determined by phosphorimager scanning and evaluated by a bioinformatics package developed specifically for analysis of cDNA microarray experimentation. Results indicated 89% of the genes showed intensity levels above background in prostate cells compared with only 28% in melanoma cells. Replicate probe preparations yielded results with correlation values ranging from r = 0.90 to 0.93 and coefficient of variation ranging from 16 to 28%. Findings indicate that among others, the keratin 5 and vimentin genes were differentially expressed between these two divergent cell lines. Follow-up northern blot analysis verified these two expression changes, thereby demonstrating the reliability of this system. We report the development of a cDNA microarray system that is sensitive and reliable, demonstrates a low degree of variability, and is capable of determining verifiable gene expression differences between two distinct human cell lines. This system will prove useful for differential gene expression analysis in prostate-derived cells and tissue.

  8. Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review.

    PubMed

    Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

    2017-09-01

    High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

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

    PubMed Central

    Menten, Björn; Pattyn, Filip; De Preter, Katleen; Robbrecht, Piet; Michels, Evi; Buysse, Karen; Mortier, Geert; De Paepe, Anne; van Vooren, Steven; Vermeesch, Joris; Moreau, Yves; De Moor, Bart; Vermeulen, Stefan; Speleman, Frank; Vandesompele, Jo

    2005-01-01

    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 . PMID:15910681

  10. Development of an oligonucleotide-based DNA microarray for transcriptional analysis of Choristoneura fumiferana nucleopolyhedrovirus (CfMNPV) genes.

    PubMed

    Yang, Dan-Hui; Barari, Mehrnoosh; Arif, Basil M; Krell, Peter J

    2007-08-01

    A modified oligonucleotide-based two-channel DNA microarray was developed for characterization of temporal expression profiles of select Choristoneura fumiferana nucleopolyhedrovirus (CfMNPV) ORFs including its 7 unique ORFs. The microarray chip contained oligonucleotide probes for 23 CfMNPV ORFs and their complements as well as five host genes. Total RNA was isolated at different times post infection from Cf203 insect cells infected with CfMNPV. The cDNA was synthesized, fluorescent labelled with Cy3, and co-hybridized to the microarray chips along with Cy5-labelled viral genomic DNA, which served as equimolar reference standards for each probe. Transcription of the 7 CfMNPV unique ORFs was detected using DNA microarray analysis and their temporal expression profiles suggest that they are functional genes. The expression levels of three host genes varied throughout virus infection and therefore were unsuitable for normalization between microarrays. The DNA microarray results were compared to quantitative RT-PCR (qRT-PCR). Transcription of the non-coding (antisense) strands of some of the CfMNPV select genes including the polyhedrin gene, was also detected by array analysis and confirmed by qRT-PCR. The polyhedrin antisense transcript, based on long-range RT-PCR analysis, appeared to be a read-through product of an adjacent ORF in the same orientation as the antisense transcript.

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

    PubMed

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

    2016-04-01

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

  12. Microarray meta-analysis identifies evolutionarily conserved BMP signaling targets in developing long bones.

    PubMed

    Prashar, Paritosh; Yadav, Prem Swaroop; Samarjeet, Fnu; Bandyopadhyay, Amitabha

    2014-05-15

    In vertebrates, BMP signaling has been demonstrated to be sufficient for bone formation in several tissue contexts. This suggests that genes necessary for bone formation are expressed in a BMP signaling dependent manner. However, till date no gene has been reported to be expressed in a BMP signaling dependent manner in bone. Our aim was to identify such genes. On searching the literature we found that several microarray experiments have been conducted where the transcriptome of osteogenic cells in absence and presence of BMP signaling activation have been compared. However, till date, there is no evidence to suggest that any of the genes found to be upregulated in presence of BMP signaling in these microarray analyses is indeed a target of BMP signaling in bone. We wanted to utilize this publicly available information to identify candidate BMP signaling target genes in vivo. We performed a meta-analysis of six such comparable microarray datasets. This analysis and subsequent experiments led to the identification of five targets of BMP signaling in bone that are conserved both in mouse and chick. Of these Lox, Klf10 and Gpr97 are likely to be direct transcriptional targets of BMP signaling pathway. Dpysl3, is a novel BMP signaling target identified in our study. Our data demonstrate that Dpysl3 is important for osteogenic differentiation of mesenchymal cells and is involved in cell secretion. We have demonstrated that the expression of Dpysl3 is co-operatively regulated by BMP signaling and Runx2. Based on our experimental data, in silico analysis of the putative promoter-enhancer regions of Bmp target genes and existing literature, we hypothesize that BMP signaling collaborates with multiple signaling pathways to regulate the expression of a unique set of genes involved in endochondral ossification. Copyright © 2014. Published by Elsevier Inc.

  13. Aberrant Expression Profile of Long Noncoding RNA in Human Sinonasal Squamous Cell Carcinoma by Microarray Analysis

    PubMed Central

    Meng, Ling-zhao; Sun, Jing-wu; Yang, Fan

    2016-01-01

    Objectives. This study aimed to identify aberrantly expressed long noncoding RNAs (lncRNAs) profile of sinonasal squamous cell carcinoma (SSCC) and explore their potential functions. Methods. We investigated lncRNA and mRNA expression in SSCC and paired adjacent noncancerous tissues obtained from 6 patients with microarrays. Gene ontology (GO) analysis and pathway analysis were utilized to investigate the gene function. Gene signal-network and lncRNA-mRNA network were depicted. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to validate 5 lncRNAs in a second set of paired SSCC and adjacent noncancerous tissues obtained from 22 additional patients. Results. We identified significantly differentially expressed lncRNAs (n = 3146) and mRNAs (n = 2208) in SSCC relative to noncancerous tissues. The GO annotation indicated that there are some core gene products that may be attributed to the progress of SSCC. The pathway analysis identified many pathways associated with cancer. The results of lncRNA-mRNA network and gene signal-network implied some core lncRNAs/mRNAs might play important roles in SSCC pathogenesis. The results of qRT-PCR showed that all of the 5 lncRNAs were differentially expressed and consistent with the microarray results. Conclusion. Our study is the first screening and analysis of lncRNAs expression profile in SSCC and may offer new insights into pathogenesis of this disease. PMID:28044124

  14. From RNA isolation to microarray analysis: Comparison of methods in FFPE tissues.

    PubMed

    Belder, Nevin; Coskun, Öznur; Doganay Erdogan, Beyza; Ilk, Ozlem; Savas, Berna; Ensari, Arzu; Özdağ, Hilal

    2016-08-01

    Genome-wide gene expression profiling analysis of FFPE tissue samples is indispensable for cancer research and provides the opportunity to evaluate links between molecular and clinical information, however, working with FFPE samples is challenging due to extensive cross-linking, fragmentation and limited quantities of nucleic acid. Thus, processing of FFPE tissue samples from RNA extraction to microarray analysis still needs optimization. In this study, a modified deparaffinization protocol was conducted prior to RNA isolation. Trizol, Qiagen RNeasy FFPE and Arcturus PicoPure RNA Isolation kits were used in parallel to compare their impact on RNA isolation. We also evaluated the effect of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) on the percentage of present calls. Our optimization study shows that the Qiagen RNeasy FFPE kit with modified deparaffinization step gives better results (RNA quantity and quality) than the other two isolation kits. The Ribo-SPIA protocol gave a significantly higher percentage of present calls than the 3' IVT cDNA amplification and labeling system. However, no significant differences were found between the two array platforms. Our study paves the way for future high-throughput transcriptional analysis by optimizing FFPE tissue sample processing from RNA isolation to microarray analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

  15. Separate-channel analysis of two-channel microarrays: recovering inter-spot information

    PubMed Central

    2013-01-01

    Background Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. Results This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis

  16. Nonlinear matching measure for the analysis of on-off type DNA microarray images

    NASA Astrophysics Data System (ADS)

    Kim, Jong D.; Park, Misun; Kim, Jongwon

    2003-07-01

    In this paper, we propose a new nonlinear matching measure for automatic analysis of the on-off type DNA microarray images in which the hybridized spots are detected by the template matching method. The targeting spots of HPV DNA chips are designed for genotyping the human papilloma virus(HPV). The proposed measure is obtained by binarythresholding over the whole template region and taking the number of white pixels inside the spotted area. This measure is evaluated in terms of the accuracy of the estimated marker location to show better performance than the normalized covariance.

  17. Diagnostic biomarkers for renal cell carcinoma: selection using novel bioinformatics systems for microarray data analysis

    PubMed Central

    Osunkoya, Adeboye O; Yin-Goen, Qiqin; Phan, John H; Moffitt, Richard A; Stokes, Todd H; Wang, May D; Young, Andrew N

    2009-01-01

    Summary The differential diagnosis of clear cell, papillary and chromophobe renal cell carcinoma is clinically important, because these tumor subtypes are associated with different pathobiology and clinical behavior. For cases in which histopathology is equivocal, immunohistochemistry and quantitative RT-PCR can assist in the differential diagnosis by measuring expression of subtype-specific biomarkers. Several renal tumor biomarkers have been discovered in expression microarray studies. However, due to heterogeneity of gene and protein expression, additional biomarkers are needed for reliable diagnostic classification. We developed novel bioinformatics systems to identify candidate renal tumor biomarkers from the microarray profiles of 45 clear cell, 16 papillary and 10 chromophobe renal cell carcinoma; the microarray data was derived from two independent published studies. The ArrayWiki biocomputing system merged the microarray datasets into a single file, so gene expression could be analyzed from a larger number of tumors. The caCORRECT system removed non-random sources of error from the microarray data, and the omniBioMarker system analyzed data with several gene-ranking algorithms, in order to identify algorithms effective at recognizing previously described renal tumor biomarkers. We predicted these algorithms would also be effective at identifying unknown biomarkers that could be verified by independent methods. We selected six novel candidate biomakers from the omniBioMarker analysis, and verified their differential expression in formalin-fixed paraffin-embedded tissues by quantitative RT-PCR and immunohistochemistry. The candidate biomarkers were carbonic anhydrase IX, ceruloplasmin, schwannomin-interacting protein 1, E74-like factor 3, cytochrome c oxidase subunit 5a and acetyl-CoA acetyltransferase 1. Quantitative RT-PCR was performed on 17 clear cell, 13 papillary and 7 chromophobe renal cell carcinoma. Carbonic anhydrase IX and ceruloplasmin were

  18. Thermodynamics of antibody-antigen interaction revealed by mutation analysis of antibody variable regions.

    PubMed

    Akiba, Hiroki; Tsumoto, Kouhei

    2015-07-01

    Antibodies (immunoglobulins) bind specific molecules (i.e. antigens) with high affinity and specificity. In order to understand their mechanisms of recognition, interaction analysis based on thermodynamic and kinetic parameters, as well as structure determination is crucial. In this review, we focus on mutational analysis which gives information about the role of each amino acid residue in antibody-antigen interaction. Taking anti-hen egg lysozyme antibodies and several anti-small molecule antibodies, the energetic contribution of hot-spot and non-hot-spot residues is discussed in terms of thermodynamics. Here, thermodynamics of the contribution from aromatic, charged and hydrogen bond-forming amino acids are discussed, and their different characteristics have been elucidated. The information gives fundamental understanding of the antibody-antigen interaction. Furthermore, the consequences of antibody engineering are analysed from thermodynamic viewpoints: humanization to reduce immunogenicity and rational design to improve affinity. Amino acid residues outside hot-spots in the interface play important roles in these cases, and thus thermodynamic and kinetic parameters give much information about the antigen recognition. Thermodynamic analysis of mutant antibodies thus should lead to advanced strategies to design and select antibodies with high affinity. © The Authors 2015. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

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

    SciTech Connect

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

    2009-05-11

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

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

    PubMed Central

    2011-01-01

    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. PMID:21261946

  1. Nanopore-based kinetics analysis of individual antibody-channel and antibody-antigen interactions

    PubMed Central

    Winters-Hilt, Stephen; Morales, Eric; Amin, Iftekhar; Stoyanov, Alexander

    2007-01-01

    Background The UNO/RIC Nanopore Detector provides a new way to study the binding and conformational changes of individual antibodies. Many critical questions regarding antibody function are still unresolved, questions that can be approached in a new way with the nanopore detector. Results We present evidence that different forms of channel blockade can be associated with the same antibody, we associate these different blockades with different orientations of "capture" of an antibody in the detector's nanometer-scale channel. We directly detect the presence of antibodies via reductions in channel current. Changes to blockade patterns upon addition of antigen suggest indirect detection of antibody/antigen binding. Similarly, DNA-hairpin anchored antibodies have been studied, where the DNA linkage is to the carboxy-terminus at the base of the antibody's Fc region, with significantly fewer types of (lengthy) capture blockades than was observed for free (un-bound) IgG antibody. The introduction of chaotropic agents and its effects on protein-protein interactions have also been observed. Conclusion Nanopore-based approaches may eventually provide a direct analysis of the complex conformational "negotiations" that occur upon binding between proteins. PMID:18047720

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

    PubMed

    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).

  3. Microarray analysis of differentially expressed genes regulating lipid metabolism during melanoma progression.

    PubMed

    Sumantran, Venil N; Mishra, Pratik; Sudhakar, N

    2015-04-01

    A new hallmark of cancer involves acquisition of a lipogenic phenotype which promotes tumorigenesis. Little is known about lipid metabolism in melanomas. Therefore, we used BRB (Biometrics Research Branch) class comparison tool with multivariate analysis to identify differentially expressed genes in human cutaneous melanomas, compared with benign nevi and normal skin derived from the microarray dataset (GDS1375). The methods were validated by identifying known melanoma biomarkers (CITED1, FGFR2, PTPRF, LICAM, SPP1 and PHACTR1) in our results. Eighteen genes regulating metabolism of fatty acids, lipid second messengers and gangliosides were 2-9 fold upregulated in melanomas of GDS-1375. Out of the 18 genes, 13 were confirmed by KEGG pathway analysis and 10 were also significantly upregulated in human melanoma cell lines of NCI-60 Cell Miner database. Results showed that melanomas upregulated PPARGC1A transcription factor and its target genes regulating synthesis of fatty acids (SCD) and complex lipids (FABP3 and ACSL3). Melanoma also upregulated genes which prevented lipotoxicity (CPT2 and ACOT7) and regulated lipid second messengers, such as phosphatidic acid (AGPAT-4, PLD3) and inositol triphosphate (ITPKB, ITPR3). Genes for synthesis of pro-tumorigenic GM3 and GD3 gangliosides (UGCG, HEXA, ST3GAL5 and ST8SIA1) were also upregulated in melanoma. Overall, the microarray analysis of GDS-1375 dataset indicated that melanomas can become lipogenic by upregulating genes, leading to increase in fatty acid metabolism, metabolism of specific lipid second messengers, and ganglioside synthesis.

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

    NASA Astrophysics Data System (ADS)

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

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

  5. A microarray analysis of gene expression patterns during early phases of newt lens regeneration

    PubMed Central

    Sousounis, Konstantinos; Michel, Christian S.; Bruckskotten, Marc; Maki, Nobuyasu; Borchardt, Thilo; Braun, Thomas; Tsonis, Panagiotis A.

    2013-01-01

    Purpose Notophthalmus viridescens, the red-spotted newt, possesses tremendous regenerative capabilities. Among the tissues and organs newts can regenerate, the lens is regenerated via transdifferentiation of the pigment epithelial cells of the dorsal iris, following complete removal (lentectomy). Under normal conditions, the same cells from the ventral iris are not capable of regenerating. This study aims to further understand the initial signals of lens regeneration. Methods We performed microarray analysis using RNA from a dorsal or ventral iris isolated 1, 3, and 5 days after lentectomy and compared to RNA isolated from an intact iris. This analysis was supported with quantitative real-time polymerase chain reaction (qRT-PCR) of selected genes. Results Microarrays showed 804 spots were differentially regulated 1, 3, and 5 days post-lentectomy in the dorsal and ventral iris. Functional annotation using Gene Ontology revealed interesting terms. Among them, factors related to cell cycle and DNA repair were mostly upregulated, in the microarray, 3 and 5 days post-lentectomy. qRT-PCR for rad1 and vascular endothelial growth factor receptor 1 showed upregulation for the dorsal iris 3 and 5 days post- lentectomy and for the ventral iris 5 days post-lentectomy. Rad1 was also upregulated twofold more in the dorsal iris than in the ventral iris 5 days post-lentectomy (p<0.001). Factors related to redox homeostasis were mostly upregulated in the microarray in all time points and samples. qRT-PCR for glutathione peroxidase 1 also showed upregulation in all time points for the ventral and dorsal iris. For the most part, mitochondrial enzymes were downregulated with the notable exception of cytochrome c–related oxidases that were mostly upregulated at all time points. qRT-PCR for cytochrome c oxidase subunit 2 showed upregulation especially 3 days post-lentectomy for the dorsal and ventral iris (p<0.001). Factors related to extracellular matrix and tissue remodeling showed

  6. Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

    PubMed

    Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

    2012-01-01

    Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

  7. Loss of HITS (FAM107B) expression in cancers of multiple organs: tissue microarray analysis.

    PubMed

    Nakajima, Hideo; Koizumi, Keita; Tanaka, Takuji; Ishigaki, Yasuhito; Yoshitake, Yoshino; Yonekura, Hideto; Sakuma, Tsutomu; Fukushima, Toshihiro; Umehara, Hisanori; Ueno, Soichiro; Minamoto, Toshinari; Motoo, Yoshiharu

    2012-10-01

    Family with sequence similarity 107 (FAM107) proteins consist of two subtypes, FAM107A and FAM107B in mammals, possessing a conserved N-terminal domain of unknown function. Recently we found that FAM107B, an 18 kDa nuclear protein, is expressed in a broad range of tissues and is downregulated in gastrointestinal cancer. Because FAM107B expression is amplified by heat-shock stimulation, we designated it heat shock-inducible tumor small protein (HITS). Although data related to FAM107A as a candidate tumor suppressor have been accumulated, little biological information is available for HITS. In the present study, we examined HITS expression using immunohistochemistry with tissue microarrays and performed detailed statistical analyses. By screening a high-density multiple organ tumor and normal tissue microarray, HITS expression was decreased in tumor tissues of the breast, thyroid, testis and uterine cervix as well as the stomach and colon. Further analysis of tissue microarrays of individual organs showed that loss of HITS expression in cancer tissues was statistically significant and commonly observed in distinct organs in a histological type-specific manner. The HITS expression intensity was inversely correlated with the primary tumor size in breast and thyroid cancers. In addition, effects of tetracycline-inducible HITS expression on tumor growth were investigated in vivo. Forced expression of HITS inhibited tumor xenograft proliferation, compared with the mock-treated tumor xenograft model. These results show that loss of HITS expression is a common phenomenon observed in cancers of distinct organs and involved in tumor development and proliferation.

  8. Microarray and functional analysis of growth phase-dependent gene regulation in Bordetella bronchiseptica.

    PubMed

    Nicholson, Tracy L; Buboltz, Anne M; Harvill, Eric T; Brockmeier, Susan L

    2009-10-01

    Growth phase-dependent gene regulation has recently been demonstrated to occur in Bordetella pertussis, with many transcripts, including known virulence factors, significantly decreasing during the transition from logarithmic to stationary-phase growth. Given that B. pertussis is thought to have derived from a Bordetella bronchiseptica-like ancestor, we hypothesized that growth phase-dependent gene regulation would also occur in B. bronchiseptica. Microarray analysis revealed and quantitative real-time PCR (qRT-PCR) confirmed that growth phase-dependent gene regulation occurs in B. bronchiseptica, resulting in prominent temporal shifts in global gene expression. Two virulence phenotypes associated with these gene expression changes were tested. We found that growth-dependent increases in expression of some type III secretion system (TTSS) genes led to a growth phase-dependent increase in a TTSS-dependent function, cytotoxicity. Although the transcription of genes encoding adhesins previously shown to mediate adherence was decreased in late-log and stationary phases, we found that the adherence of B. bronchiseptica did not decrease in these later phases of growth. Microarray analysis revealed and qRT-PCR confirmed that growth phase-dependent gene regulation occurred in both Bvg(+) and Bvg(-) phase-locked mutants, indicating that growth phase-dependent gene regulation in B. bronchiseptica can function independently from the BvgAS regulatory system.

  9. Identification of Iron Homeostasis Genes Dysregulation Potentially Involved in Retinopathy of Prematurity Pathogenicity by Microarray Analysis

    PubMed Central

    Luo, Xian-qiong; Zhang, Chun-yi; Zhang, Jia-wen; Jiang, Jing-bo; Yin, Ai-hua; Guo, Li; Nie, Chuan; Lu, Xu-zai; Deng, Hua; Zhang, Liang

    2015-01-01

    Retinopathy of prematurity (ROP) is a serious disease of preterm neonates and there are limited systematic studies of the molecular mechanisms underlying ROP. Therefore, here we performed global gene expression profiling in human fetal retinal microvascular endothelial cells (RMECs) under hypoxic conditions in vitro. Aborted fetuses were enrolled and primary RMECs were isolated from eyeballs. Cultivated cells were treated with CoCl2 to induce hypoxia. The dual-color microarray approach was adopted to compare gene expression profiling between treated RMECs and the paired untreated control. The one-class algorithm in significance analysis of microarray (SAM) software was used to screen the differentially expressed genes (DEGs) and quantitative RT-PCR (qRT-PCR) was conducted to validate the results. Gene Ontology was employed for functional enrichment analysis. There were 326 DEGs between the hypoxia-induced group and untreated group. Of these genes, 198 were upregulated in hypoxic RMECs, while the other 128 hits were downregulated. In particular, genes in the iron ion homeostasis pathway were highly enriched under hypoxic conditions. Our study indicates that dysregulation of genes involved in iron homeostasis mediating oxidative damage may be responsible for the mechanisms underlying ROP. The “oxygen plus iron” hypothesis may improve our understanding of ROP pathogenesis. PMID:26557385

  10. Using microarray analysis to evaluate genetic polymorphisms involved in the metabolism of environmental chemicals.

    PubMed

    Ban, Susumu; Kondo, Tomoko; Ishizuka, Mayumi; Sasaki, Seiko; Konishi, Kanae; Washino, Noriaki; Fujita, Syoichi; Kishi, Reiko

    2007-05-01

    The field of molecular biology currently faces the need for a comprehensive method of evaluating individual differences derived from genetic variation in the form of single nucleotide polymorphisms (SNPs). SNPs in human genes are generally considered to be very useful in determining inherited genetic disorders, susceptibility to certain diseases, and cancer predisposition. Quick and accurate discrimination of SNPs is the key characteristic of technology used in DNA diagnostics. For this study, we first developed a DNA microarray and then evaluated its efficacy by determining the detection ability and validity of this method. Using DNA obtained from 380 pregnant Japanese women, we examined 13 polymorphisms of 9 genes, which are associated with the metabolism of environmental chemical compounds found in high frequency among Japanese populations. The ability to detect CYP1A1 I462V, CYP1B1 L432V, GSTP1 I105V and AhR R554K gene polymorphisms was above 98%, and agreement rates when compared with real time PCR analysis methods (kappa values) showed high validity: 0.98 (0.96), 0.97 (0.93), 0.90 (0.81), 0.90 (0.91), respectively. While this DNA microarray analysis should prove important as a method for initial screening, it is still necessary that we find better methods for improving the detection of other gene polymorphisms not part of this study.

  11. Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

    PubMed Central

    Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.

    2013-01-01

    While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185

  12. Focused Microarray Analysis of Peripheral Mononuclear Blood Cells from Churg–Strauss Syndrome Patients

    PubMed Central

    Tougan, Takahiro; Onda, Hiroaki; Okuzaki, Daisuke; Kobayashi, Shigeto; Hashimoto, Hiroshi; Nojima, Hiroshi

    2008-01-01

    DNA diagnostics are useful but are hampered by difficult ethical issues. Moreover, it cannot provide enough information on the environmental factors that are important for pathogenesis of certain diseases. However, this is not a problem for RNA diagnostics, which evaluate the expression of the gene in question. We here report a novel RNA diagnostics tool that can be employed with peripheral blood mononuclear cells (PBMCs). To establish this tool, we identified 290 genes that are highly expressed in normal PBMCs but not in TIG-1, a normal human fibroblast cell. These genes were entitled PREP after predominantly expressed in PBMC and included 50 uncharacterized genes. We then conducted PREP gene-focused microarray analysis on PBMCs from seven cases of Churg–Strauss syndrome (CSS), which is a small-vessel necrotizing vasculitis. We found that PREP135 (coactosin-like protein), PREP77 (prosaposin), PREP191 (cathepsin D), PREP234 (c-fgr), and PREP136 (lysozyme) were very highly up-regulated in all seven CSS patients. Another 28 genes were also up-regulated, albeit more moderately, and three were down-regulated in all CSS patients. The nature of these up- and down-regulated genes suggest that the immune systems of the patients are activated in response to invading microorganisms. These observations indicate that focused microarray analysis of PBMCs may be a practical, useful, and low-cost bedside diagnostics tool. PMID:18263571

  13. Use of automated image analysis in evaluation of Mesothelioma Tissue Microarray (TMA) from National Mesothelioma Virtual Bank.

    PubMed

    Amin, Waqas; Srinivasan, Malini; Song, Sang Yong; Parwani, Anil V; Becich, Michael J

    2014-02-01

    The National Mesothelioma Virtual Bank (NMVB) was established to provide annotated biospecimens to the mesothelioma research community. The resource provides tissue microarrays (TMA) to evaluate the biomarkers along with a variety of other resected mesothelioma specimens. In this manuscript, we describe the immunohistochemical evaluation of the mesothelioma TMA with three key antibodies that are used in making the diagnosis of mesothelioma, and compared the immunohistochemical assessment between manual scoring and image analysis. The TMA was assessed for the immunohistochemical expression of calretinin (N=39), cytokeratin (CK) 5/6 (N=33), and D2-40 (N=37). Immunohistochemistry was evaluated by semi-quantitative (manual) scoring using light microscope (MS) and by automated image analysis (AS). Calretinin staining was seen in both cytoplasmic and nuclear locations. CK5/6 stain was localized to the cytoplasm. D2-40 stain showed only membranous expression in our cases. • Based on the pathologist’s scores, calretinin was positive in 31 of the 39 cases (80%), CK 5/6 in 15 of the 33 cases (46%) and D2-40 in 18 of the 37 cases (49%). • The percent-positive agreement between manual scores and image analysis was 90% (35/39), 94% (31/33), and 95% (35/37) for calretinin, CK 5/6, and D2-40, respectively. There was a substantial agree-ment between manual and automated scores for calretinin (kappa = 0.614) and an almost perfect agreement for CK5/6 (kappa = 0.879) and D2-40 (kappa = 0.892). Our study confirms that the immunohistochemical staining pattern of mesotheliomas in the NMVB UPMC TMA is similar to other studies. Our findings also show that automated image analysis provides similar results to manual scoring by pathologists, and provides a reproducible, objective, and accurate platform for immunohistochemical assessment of biomarker expression. Copyright © 2013 Elsevier GmbH. All rights reserved.

  14. Microarray proteomic analysis discriminates tumorigenic mouse ovarian surface epithelial cells of divergent aggressive potential.

    PubMed

    Urzúa, Ulises; Best, Lionel; Munroe, David J

    2010-12-01

    Cancer is an intrinsically heterogeneous disease. Tumors classified under the same etiology and histological type may display divergent growth and invasion properties, resulting in different progression rates and clinical outcomes. Here, we approached this subject in a syngeneic mouse model of ovarian cancer. Antibody microarrays were applied to obtain the proteomic profiles of IF5 and IG10, two spontaneously transformed mouse ovarian surface epithelial (MOSE) cell lines of cognate clonal origin but different tumorigenic behavior in vivo. Repeated dye-swap allowed filter out about 40% of inconsistent signals from a total of 224 arrayed antibodies. Two-class comparison tests resulted in 31 differentially expressed proteins (adjusted p < 0.05). Proteins of the ErbB and focal adhesion signaling pathways showed higher levels in IG10, the most aggressive cell. In contrast, the less aggressive IF5 cell was enriched in proteins related to nuclear chromatin organization and cell-cycle. Additionally, comparison between protein levels and mRNA levels of MOSE cells resulted in a positive rank correlation for 50-60% of protein-mRNA pairs (p < 1.7 × 10(-5)). Importantly, the protein profile of IG10 is linked to invasion and chemotherapy response in human ovarian tumors while the IF5 profile is associated to growth control. The minimal IG10 network contained the proteins Jun, Smad4, Myc, Atf2, and Pak1 as major nodes while Chek2, Mdm2 and Ccna2 were the predominant nodes of the IF5 network. The molecular basis accounting for a high aggressive potential not necessarily related to an increased tumor growth capacity is discussed on a pathway-network basis.

  15. Prediction of recurrence of non muscle-invasive bladder cancer by means of a protein signature identified by antibody microarray analyses.

    PubMed

    Srinivasan, Harish; Allory, Yves; Sill, Martin; Vordos, Dimitri; Alhamdani, Mohamed Saiel Saeed; Radvanyi, Francois; Hoheisel, Jörg D; Schröder, Christoph

    2014-06-01

    About 70% of newly diagnosed cases of bladder cancer are low-stage, low-grade, non muscle-invasive. Standard treatment is transurethral resection. About 60% of the tumors will recur, however, and in part progress to become invasive. Therefore, surveillance cystoscopy is performed after resection. However, in the USA and Europe alone, about 54 000 new patients per year undergo repeated cystoscopies over several years, who do not experience recurrence. Analysing in a pilot study resected tumors from patients with (n = 19) and without local recurrence (n = 6) after a period of 5 years by means of an antibody microarray that targeted 724 cancer-related proteins, we identified 255 proteins with significantly differential abundance. Most are involved in the regulation and execution of apoptosis and cell proliferation. A multivariate classifier was constructed based on 20 proteins. It facilitates the prediction of recurrence with a sensitivity of 80% and a specificity of 100%. As a measure of overall accuracy, the area under the curve value was found to be 91%. After validation in additional sample cohorts with a similarly long follow-up, such a signature could support decision making about the stringency of surveillance or even different treatment options.

  16. Antibody

    MedlinePlus

    An antibody is a protein produced by the body's immune system when it detects harmful substances, called antigens. Examples ... microorganisms (bacteria, fungi, parasites, and viruses) and chemicals. Antibodies may be produced when the immune system mistakenly ...

  17. Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts

    PubMed Central

    Trost, Brett; Moir, Catherine A.; Gillespie, Zoe E.; Kusalik, Anthony; Mitchell, Jennifer A.; Eskiw, Christopher H.

    2015-01-01

    DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibroblasts, we measured changes in transcript abundance as cells transitioned from proliferative growth to quiescence using both DNA microarrays and RNA-seq. The internal reproducibility of the RNA-seq data was greater than that of the microarray data. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarray values were moderate. The two technologies had good agreement when considering probes with the largest (both positive and negative) fold change (FC) values. An independent technique, quantitative reverse-transcription PCR (qRT-PCR), was used to measure the FC of 76 genes between proliferative and quiescent samples, and a higher correlation was observed between the qRT-PCR data and the RNA-seq data than between the qRT-PCR data and the microarray data. PMID:26473061

  18. Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments.

    PubMed

    Schneider, Jörg; Buness, Andreas; Huber, Wolfgang; Volz, Joachim; Kioschis, Petra; Hafner, Mathias; Poustka, Annemarie; Sültmann, Holger

    2004-04-30

    The requirement of a large amount of high-quality RNA is a major limiting factor for microarray experiments using biopsies. An average microarray experiment requires 10-100 microg of RNA. However, due to their small size, most biopsies do not yield this amount. Several different approaches for RNA amplification in vitro have been described and applied for microarray studies. In most of these, systematic analyses of the potential bias introduced by the enzymatic modifications are lacking. We examined the sources of error introduced by the T7 RNA polymerase based RNA amplification method through hybridisation studies on microarrays and performed statistical analysis of the parameters that need to be evaluated prior to routine laboratory use. The results demonstrate that amplification of the RNA has no systematic influence on the outcome of the microarray experiment. Although variations in differential expression between amplified and total RNA hybridisations can be observed, RNA amplification is reproducible, and there is no evidence that it introduces a large systematic bias. Our results underline the utility of the T7 based RNA amplification for use in microarray experiments provided that all samples under study are equally treated.

  19. Systematic analysis of T7 RNA polymerase based in vitro linear RNA amplification for use in microarray experiments

    PubMed Central

    Schneider, Jörg; Buneß, Andreas; Huber, Wolfgang; Volz, Joachim; Kioschis, Petra; Hafner, Mathias; Poustka, Annemarie; Sültmann, Holger

    2004-01-01

    Background The requirement of a large amount of high-quality RNA is a major limiting factor for microarray experiments using biopsies. An average microarray experiment requires 10–100 μg of RNA. However, due to their small size, most biopsies do not yield this amount. Several different approaches for RNA amplification in vitro have been described and applied for microarray studies. In most of these, systematic analyses of the potential bias introduced by the enzymatic modifications are lacking. Results We examined the sources of error introduced by the T7 RNA polymerase based RNA amplification method through hybridisation studies on microarrays and performed statistical analysis of the parameters that need to be evaluated prior to routine laboratory use. The results demonstrate that amplification of the RNA has no systematic influence on the outcome of the microarray experiment. Although variations in differential expression between amplified and total RNA hybridisations can be observed, RNA amplification is reproducible, and there is no evidence that it introduces a large systematic bias. Conclusions Our results underline the utility of the T7 based RNA amplification for use in microarray experiments provided that all samples under study are equally treated. PMID:15119961

  20. DATE analysis: A general theory of biological change applied to microarray data.

    PubMed

    Rasnick, David

    2009-01-01

    In contrast to conventional data mining, which searches for specific subsets of genes (extensive variables) to correlate with specific phenotypes, DATE analysis correlates intensive state variables calculated from the same datasets. At the heart of DATE analysis are two biological equations of state not dependent on genetic pathways. This result distinguishes DATE analysis from other bioinformatics approaches. The dimensionless state variable F quantifies the relative overall cellular activity of test cells compared to well-chosen reference cells. The variable pi(i) is the fold-change in the expression of the ith gene of test cells relative to reference. It is the fraction phi of the genome undergoing differential expression-not the magnitude pi-that controls biological change. The state variable phi is equivalent to the control strength of metabolic control analysis. For tractability, DATE analysis assumes a linear system of enzyme-connected networks and exploits the small average contribution of each cellular component. This approach was validated by reproducible values of the state variables F, RNA index, and phi calculated from random subsets of transcript microarray data. Using published microarray data, F, RNA index, and phi were correlated with: (1) the blood-feeding cycle of the malaria parasite, (2) embryonic development of the fruit fly, (3) temperature adaptation of Killifish, (4) exponential growth of cultured S. pneumoniae, and (5) human cancers. DATE analysis was applied to aCGH data from the great apes. A good example of the power of DATE analysis is its application to genomically unstable cancers, which have been refractory to data mining strategies.

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

    PubMed

    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 perform two different types of analysis: the first covers the traditional Fisher's Test used by Pathway Processor and topology-aware analyses, which take into account the propagation of changes over the whole structure of a pathway, and the second is a new pathway-based method to investigate differences between phenotypes of interest. Common problems and troubleshooting are also discussed.

  2. GEPAS: a web-based resource for microarray gene expression data analysis

    PubMed Central

    Herrero, Javier; Al-Shahrour, Fátima; Díaz-Uriarte, Ramón; Mateos, Álvaro; Vaquerizas, Juan M.; Santoyo, Javier; Dopazo, Joaquín

    2003-01-01

    We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es). PMID:12824345

  3. k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction.

    PubMed

    Parry, R M; Jones, W; Stokes, T H; Phan, J H; Moffitt, R A; Fang, H; Shi, L; Oberthuer, A; Fischer, M; Tong, W; Wang, M D

    2010-08-01

    In the clinical application of genomic data analysis and modeling, a number of factors contribute to the performance of disease classification and clinical outcome prediction. This study focuses on the k-nearest neighbor (KNN) modeling strategy and its clinical use. Although KNN is simple and clinically appealing, large performance variations were found among experienced data analysis teams in the MicroArray Quality Control Phase II (MAQC-II) project. For clinical end points and controls from breast cancer, neuroblastoma and multiple myeloma, we systematically generated 463,320 KNN models by varying feature ranking method, number of features, distance metric, number of neighbors, vote weighting and decision threshold. We identified factors that contribute to the MAQC-II project performance variation, and validated a KNN data analysis protocol using a newly generated clinical data set with 478 neuroblastoma patients. We interpreted the biological and practical significance of the derived KNN models, and compared their performance with existing clinical factors.

  4. Microarray Based Gene Expression Analysis of Murine Brown and Subcutaneous Adipose Tissue: Significance with Human

    PubMed Central

    Boparai, Ravneet K.; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Background Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. Methodology/Principle Findings The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Conclusion Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose

  5. Microarray based gene expression analysis of murine brown and subcutaneous adipose tissue: significance with human.

    PubMed

    Baboota, Ritesh K; Sarma, Siddhartha M; Boparai, Ravneet K; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra

    2015-01-01

    Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose tissue to another using murine model with focus on

  6. SegMine workflows for semantic microarray data analysis in Orange4WS

    PubMed Central

    2011-01-01

    Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment. PMID:22029475

  7. SegMine workflows for semantic microarray data analysis in Orange4WS.

    PubMed

    Podpečan, Vid; Lavrač, Nada; Mozetič, Igor; Novak, Petra Kralj; Trajkovski, Igor; Langohr, Laura; Kulovesi, Kimmo; Toivonen, Hannu; Petek, Marko; Motaln, Helena; Gruden, Kristina

    2011-10-26

    In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.

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

    DOE PAGES

    Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; ...

    2009-01-01

    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 partmore » 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.« less

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    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

  11. Analysing breast cancer microarrays from African Americans using shrinkage-based discriminant analysis.

    PubMed

    Pang, Herbert; Ebisu, Keita; Watanabe, Emi; Sue, Laura Y; Tong, Tiejun

    2010-10-01

    Breast cancer tumours among African Americans are usually more aggressive than those found in Caucasian populations. African-American patients with breast cancer also have higher mortality rates than Caucasian women. A better understanding of the disease aetiology of these breast cancers can help to improve and develop new methods for cancer prevention, diagnosis and treatment. The main goal of this project was to identify genes that help differentiate between oestrogen receptor-positive and -negative samples among a small group of African-American patients with breast cancer. Breast cancer microarrays from one of the largest genomic consortiums were analysed using 13 African-American and 201 Caucasian samples with oestrogen receptor status. We used a shrinkage-based classification method to identify genes that were informative in discriminating between oestrogen receptor-positive and -negative samples. Subset analysis and permutation were performed to obtain a set of genes unique to the African-American population. We identified a set of 156 probe sets, which gave a misclassification rate of 0.16 in distinguishing between oestrogen receptor-positive and -negative patients. The biological relevance of our findings was explored through literature-mining techniques and pathway mapping. An independent dataset was used to validate our findings and we found that the top ten genes mapped onto this dataset gave a misclassification rate of 0.15. The described method allows us best to utilise the information available from small sample size microarray data in the context of ethnic minorities.

  12. cDNA Microarray Analysis of Serially Sampled Cervical Cancer Specimens From Patients Treated With Thermochemoradiotherapy

    SciTech Connect

    Borkamo, Erling Dahl; Schem, Baard-Christian; Fluge, Oystein; Bruland, Ove; Dahl, Olav; Mella, Olav

    2009-12-01

    Purpose: To elucidate changes in gene expression after treatment with regional thermochemoradiotherapy in locally advanced squamous cell cervical cancer. Methods and Materials: Tru-Cut biopsy specimens were serially collected from 16 patients. Microarray gene expression levels before and 24 h after the first and second trimodality treatment sessions were compared. Pathway and network analyses were conducted by use of Ingenuity Pathways Analysis (IPA; Ingenuity Systems, Redwood City, CA). Single gene expressions were analyzed by quantitative real-time reverse transcription-polymerase chain reaction. Results: We detected 53 annotated genes that were differentially expressed after trimodality treatment. Central in the three top networks detected by IPA were interferon alfa, interferon beta, and interferon gamma receptor; nuclear factor kappaB; and tumor necrosis factor, respectively. These genes encode proteins that are important in regulation cell signaling, proliferation, gene expression, and immune stimulation. Biological processes over-represented among the 53 genes were fibrosis, tumorigenesis, and immune response. Conclusions: Microarrays showed minor changes in gene expression after thermochemoradiotherapy in locally advanced cervical cancer. We detected 53 differentially expressed genes, mainly involved in fibrosis, tumorigenesis, and immune response. A limitation with the use of serial biopsy specimens was low quality of ribonucleic acid from tumors that respond to highly effective therapy. Another 'key limitation' is timing of the post-treatment biopsy, because 24 h may be too late to adequately assess the impact of hyperthermia on gene expression.

  13. ParaSAM: a parallelized version of the significance analysis of microarrays algorithm

    PubMed Central

    Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A.

    2010-01-01

    Motivation: Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. Summary: We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. Availability:A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx Contact: rmcindoe@mail.mcg.edu Supplementary information: Supplementary Data is available at Bioinformatics online. PMID:20400455

  14. Comparative analysis of amplified and nonamplified RNA for hybridization in cDNA microarray.

    PubMed

    Gomes, Luciana I; Silva, Ricardo L A; Stolf, Beatriz S; Cristo, Elier B; Hirata, Roberto; Soares, Fernando A; Reis, Luiz F L; Neves, E Jordão; Carvalho, Alex F

    2003-10-15

    Limiting amounts of RNA is a major issue in cDNA microarray, especially when one is dealing with fresh tissue samples. Here we describe a protocol based on template switch and T7 amplification that led to efficient and linear amplification of 1300x. Using a glass-array containing 368 genes printed in three or six replicas covering a wide range of expression levels and ratios, we determined quality and reproducibility of the data obtained from one nonamplified and two independently amplified RNAs (aRNA) derived from normal and tumor samples using replicas with dye exchange (dye-swap measurements). Overall, signal-to-noise ratio improved when we used aRNA (1.45-fold for channel 1 and 2.02-fold for channel 2), increasing by 6% the number of spots with meaningful data. Measurements arising from independent aRNA samples showed strong correlation among themselves (r(2)=0.962) and with those from the nonamplified sample (r(2)=0.975), indicating the reproducibility and fidelity of the amplification procedure. Measurement differences, i.e, spots with poor correlation between amplified and nonamplified measurements, did not show association with gene sequence, expression intensity, or expression ratio and can, therefore, be compensated with replication. In conclusion, aRNA can be used routinely in cDNA microarray analysis, leading to improved quality of data with high fidelity and reproducibility.

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

    PubMed Central

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

    2010-01-01

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

  16. Hidden variable analysis of transcription factor cooperativity from microarray time courses.

    PubMed

    Cromer, D; Christophides, G K; Stark, J

    2010-03-01

    Gene expression is regulated by transcription factor activity, which can be extremely difficult to measure directly. Previous work has established a method to extract the 'hidden' transcription factor activity profile from microarray data and use it to effectively identify genes that are targets of a single transcription factor. However, most genes are regulated by two or more transcription factors, and so may not be recognised by this method. Here, the authors present a model-based analysis technique which is able to extract two separate 'hidden' transcription factor profiles using microarray data from wild-type and gene knock-down samples. The algorithm can predict targets of each of the transcription factors as well as the amount of cooperative regulation of genes which occurs because of the interaction between the two transcription factors. The authors evaluate this method using simulated data, and show that it is highly effective at classifying genes into categories based on their relative regulation by each of the transcription factors. The authors also show that our method can accurately measure the effectiveness of a gene knock-down when including of a reasonable amount of measurement error.

  17. Microarray analysis of differentially expressed genes in preeclamptic and normal placental tissues.

    PubMed

    Ma, K; Lian, Y; Zhou, S; Hu, R; Xiong, Y; Ting, P; Xiong, Y; Li, X; Wang, X

    2014-01-01

    To detect the candidate genes for preeclampsia (PE). The gene expression profiles in preeclamptic and normal placental tissues were analyzed using cDNA microarray approach and the altered expression of important genes were further confirmed by real-time RT-PCR (reverse transcription polymerase chain reaction) technique. Total RNA was extracted from placental tissues of three cases with severe PE and from three cases with normal pregnancy. After scanning, differentially expressed genes were detected by software. In two experiments (the fluorescent labels were exchanged), a total of 111 differentially expressed genes were detected. In placental tissue ofpreeclamptic pregnancy, 68 differentially expressed genes were up-regulated, and 44 differentially expressed genes were down-regulated. Of these genes, 16 highly differentially expressed genes were confirmed by real-time fluorescent quantitative RT-PCR, and the result showed that the ratio of gene expression differences was comparable to that detected by cDNA microarray. The results of bioinformatic analysis showed that encoding products of differentially expressed genes were correlated to infiltration of placenta trophoblastic cells, immunomodulatory factors, pregnancy-associated plasma protein, signal transduction pathway, and cell adhesion. Further studies on the biological function and regulating mechanism of these genes will provide new clues for better understanding of etiology and pathogenesis of PE.

  18. Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

    PubMed Central

    2011-01-01

    Background Epidermal Growth Factor (EGF) is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer. Results By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. Conclusions We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data. PMID:21699700

  19. ParaSAM: a parallelized version of the significance analysis of microarrays algorithm.

    PubMed

    Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A

    2010-06-01

    Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx.

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

    PubMed

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

    2010-06-01

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

  1. Functional analysis of differentially expressed genes associated with glaucoma from DNA microarray data.

    PubMed

    Wu, Y; Zang, W D; Jiang, W

    2014-11-11

    Microarray data of astrocytes extracted from the optic nerves of donors with and without glaucoma were analyzed to screen for differentially expressed genes (DEGs). Functional exploration with bioinformatic tools was then used to understand the roles of the identified DEGs in glaucoma. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database, which contains 13 astrocyte samples, 6 from healthy subjects and 7 from patients suffering from glaucoma. Data were pre-processed, and DEGs were screened out using R software packages. Interactions between DEGs were identified, and networks were built using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GENECODIS was utilized for the functional analysis of the DEGs, and GOTM was used for module division, for which functional annotation was conducted with the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A total of 371 DEGs were identified between glaucoma-associated samples and normal samples. Three modules included in the PPID database were generated with 11, 12, and 2 significant functional annotations, including immune system processes, inflammatory responses, and synaptic vesicle endocytosis, respectively. We found that the most significantly enriched functions for each module were associated with immune function. Several genes that play interesting roles in the development of glaucoma are described; these genes may be potential biomarkers for glaucoma diagnosis or treatment.

  2. DNA microarray analysis on gene candidates possibly related to tetrodotoxin accumulation in pufferfish.

    PubMed

    Feroudj, Holger; Matsumoto, Takuya; Kurosu, Yohei; Kaneko, Gen; Ushio, Hideki; Suzuki, Katsuaki; Kondo, Hidehiro; Hirono, Ikuo; Nagashima, Yuji; Akimoto, Seiji; Usui, Kazushige; Kinoshita, Shigeharu; Asakawa, Shuichi; Kodama, Masaaki; Watabe, Shugo

    2014-01-01

    Pufferfish accumulate tetrodotoxin (TTX) at high levels in liver and ovary through the food chain. However, the mechanisms underlying TTX toxification in pufferfish have been poorly understood. In order to search gene candidates involved in TTX accumulation in the torafugu pufferfish Takifugu rubripes, a custom 4x44k oligonucleotide microarray slide was designed by the Agilent eArray program using oligonucleotide probes of 60 bp in length referring to 42,724 predicted transcripts in the publicly available Fugu genome database. DNA microarray analysis was performed with total RNA samples from the livers of two toxic wild specimens in comparison with those from a nontoxic wild specimen and two nontoxic cultured specimens. The mRNA levels of 1108 transcripts were more than 2-fold higher in the toxic specimens than in the nontoxic specimens. The levels of 613 transcripts were remarkably high, and 16 transcripts encoded by 9 genes were up-regulated more than 10-fold. These genes included those encoding forming structural filaments (keratins) and those related to vitamin D metabolism and immunity. It was also noted that the levels of the transcripts encoding serpin peptidase inhibitor clade C member 1, coagulation factor X precursor, complement C2, C3, C5, C8 precursors, and interleukin-6 receptor were high in the toxic liver samples. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Increased power of microarray analysis by use of an algorithm based on a multivariate procedure.

    PubMed

    Krohn, K; Eszlinger, M; Paschke, R; Roeder, I; Schuster, E

    2005-09-01

    The power of microarray analyses to detect differential gene expression strongly depends on the statistical and bioinformatical approaches used for data analysis. Moreover, the simultaneous testing of tens of thousands of genes for differential expression raises the 'multiple testing problem', increasing the probability of obtaining false positive test results. To achieve more reliable results, it is, therefore, necessary to apply adjustment procedures to restrict the family-wise type I error rate (FWE) or the false discovery rate. However, for the biologist the statistical power of such procedures often remains abstract, unless validated by an alternative experimental approach. In the present study, we discuss a multiplicity adjustment procedure applied to classical univariate as well as to recently proposed multivariate gene-expression scores. All procedures strictly control the FWE. We demonstrate that the use of multivariate scores leads to a more efficient identification of differentially expressed genes than the widely used MAS5 approach provided by the Affymetrix software tools (Affymetrix Microarray Suite 5 or GeneChip Operating Software). The practical importance of this finding is successfully validated using real time quantitative PCR and data from spike-in experiments. The R-code of the statistical routines can be obtained from the corresponding author. Schuster@imise.uni-leipzig.de

  4. [Microarray analytic system for multiplex analysis by real-time polymerase chain reaction with reagents immobilized in microreactors].

    PubMed

    Navolotskiĭ, D V; Perchik, A V; Mark'ianov, I A; Ganeev, A A; Sliadnev, M N

    2011-01-01

    A microarray analytic system that uses a silicon chip with immobilized in microreactor test-system for multiplex analysis of DNA by real-time polymerase chain reaction (RT-PCR) was developed and optimized. We suggested the method of immobilization of PCR-components of a test-system, chose the stabilizer, and conducted the optimization of the composition of reaction mixture to achieve permanent stability of a microarray. We conducted optimization of preparation of samples using magnetic sorbent and indicated that, with 2.6 x 10(4) copies/ml, 60 min are necessary to obtain positive identification including time for preparation of model probes. The abilities of the created system were demonstrated on the example of microarray analysis of samples with different content of DNA, low absolute limits of identification (20 DNA copies in microreactor), and high reproducibility of the analysis.

  5. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

    PubMed Central

    Ho, Karen S.; Wassman, E. Robert; Baxter, Adrianne L.; Hensel, Charles H.; Martin, Megan M.; Prasad, Aparna; Twede, Hope; Vanzo, Rena J.; Butler, Merlin G.

    2016-01-01

    Copy number variants (CNVs) detected by chromosomal microarray analysis (CMA) significantly contribute to understanding the etiology of autism spectrum disorder (ASD) and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID) and/or multiple congenital anomalies (MCA). The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD. PMID:27941670

  6. Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders.

    PubMed

    Ho, Karen S; Wassman, E Robert; Baxter, Adrianne L; Hensel, Charles H; Martin, Megan M; Prasad, Aparna; Twede, Hope; Vanzo, Rena J; Butler, Merlin G

    2016-12-09

    Copy number variants (CNVs) detected by chromosomal microarray analysis (CMA) significantly contribute to understanding the etiology of autism spectrum disorder (ASD) and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID) and/or multiple congenital anomalies (MCA). The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.

  7. Phytoremediation potential of Arabidopsis with reference to acrylamide and microarray analysis of acrylamide-response genes.

    PubMed

    Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong

    2015-10-01

    Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Cyclin D1 and Ewing's sarcoma/PNET: A microarray analysis.

    PubMed

    Fagone, Paolo; Nicoletti, Ferdinando; Salvatorelli, Lucia; Musumeci, Giuseppe; Magro, Gaetano

    2015-10-01

    Recent immunohistochemical analyses have showed that cyclin D1 is expressed in soft tissue Ewing's sarcoma/peripheral neuroectodermal tumor (PNET) of childhood and adolescents, while it is undetectable in both embryonal and alveolar rhabdomyosarcoma. In the present paper, microarray analysis provided evidence of a significant upregulation of cyclin D1 in Ewing's sarcoma as compared to normal tissues. In addition, we confirmed our previous findings of a significant over-expression of cyclin D1 in Ewing sarcoma as compared to rhabdomyosarcoma. Bioinformatic analysis also allowed to identify some other genes, strongly correlated to cyclin D1, which, although not previously studied in pediatric tumors, could represent novel markers for the diagnosis and prognosis of Ewing's sarcoma/PNET. The data herein provided support not only the use of cyclin D1 as a diagnostic marker of Ewing sarcoma/PNET but also the possibility of using drugs targeting cyclin D1 as potential therapeutic strategies.

  9. Administered chrysanthemum flower oil attenuates hyperuricemia: mechanism of action as revealed by DNA microarray analysis.

    PubMed

    Honda, Shinichi; Kawamoto, Seiji; Tanaka, Hozumi; Kishida, Hideyuki; Kitagawa, Masayasu; Nakai, Yuji; Abe, Keiko; Hirata, Dai

    2014-01-01

    We applied Chrysanthemum flower oil (CFO) to a hyperuricemia model by feeding rats a hyperuricemia-inducing diet (HID) and investigated its effect on serum uric acid (SUA) levels and its mode of action. CFO is the oily fraction that contains polyphenols derived from chrysanthemum flowers. Oral administration of CFO to HID-fed rats significantly decreased their SUA levels. It also inhibited xanthine oxidase activities in the liver and increased urine uric acid levels. The effects of CFO on the renal gene expressions that accompanied the induction of hyperuricemia were comprehensively confirmed by DNA microarray analysis. The analysis showed up-regulation of those genes for uric acid excretion by CFO administration. These results suggest that CFO suppresses the increase in SUA levels via two mechanisms: suppression of uric acid production by inhibition of xanthine oxidase in the liver and acceleration of its excretion by up-regulation of uric acid transporter genes in the kidney.

  10. Microarray analysis of Neosartorya fischeri using different carbon sources, petroleum asphaltenes and glucose-peptone

    PubMed Central

    Hernández-López, Edna L.; Ramírez-Puebla, Shamayim T.; Vazquez-Duhalt, Rafael

    2015-01-01

    Asphaltenes are considered as the most recalcitrant petroleum fraction and represent a big problem for the recovery, separation and processing of heavy oils and bitumens. Neosartorya fischeri is a saprophytic fungus that is able to grow using asphaltenes as the sole carbon source [1]. We performed transcription profiling using a custom designed microarray with the complete genome from N. fischeri NRRL 181 in order to identify genes related to the transformation of asphaltenes [1]. Data analysis was performed using the genArise software. Results showed that 287 genes were up-regulated and 118 were down-regulated. Here we describe experimental procedures and methods about our dataset (NCBI GEO accession number GSE68146) and describe the data analysis to identify different expression levels in N. fischeri using this recalcitrant carbon source. PMID:26484261

  11. Adaptation of a Bioinformatics Microarray Analysis Workflow for a Toxicogenomic Study in Rainbow Trout

    PubMed Central

    Depiereux, Sophie; De Meulder, Bertrand; Bareke, Eric; Berger, Fabrice; Le Gac, Florence; Depiereux, Eric; Kestemont, Patrick

    2015-01-01

    Sex steroids play a key role in triggering sex differentiation in fish, the use of exogenous hormone treatment leading to partial or complete sex reversal. This phenomenon has attracted attention since the discovery that even low environmental doses of exogenous steroids can adversely affect gonad morphology (ovotestis development) and induce reproductive failure. Modern genomic-based technologies have enhanced opportunities to find out mechanisms of actions (MOA) and identify biomarkers related to the toxic action of a compound. However, high throughput data interpretation relies on statistical analysis, species genomic resources, and bioinformatics tools. The goals of this study are to improve the knowledge of feminisation in fish, by the analysis of molecular responses in the gonads of rainbow trout fry after chronic exposure to several doses (0.01, 0.1, 1 and 10 μg/L) of ethynylestradiol (EE2) and to offer target genes as potential biomarkers of ovotestis development. We successfully adapted a bioinformatics microarray analysis workflow elaborated on human data to a toxicogenomic study using rainbow trout, a fish species lacking accurate functional annotation and genomic resources. The workflow allowed to obtain lists of genes supposed to be enriched in true positive differentially expressed genes (DEGs), which were subjected to over-representation analysis methods (ORA). Several pathways and ontologies, mostly related to cell division and metabolism, sexual reproduction and steroid production, were found significantly enriched in our analyses. Moreover, two sets of potential ovotestis biomarkers were selected using several criteria. The first group displayed specific potential biomarkers belonging to pathways/ontologies highlighted in the experiment. Among them, the early ovarian differentiation gene foxl2a was overexpressed. The second group, which was highly sensitive but not specific, included the DEGs presenting the highest fold change and lowest p

  12. Deep sequencing and human antibody repertoire analysis

    PubMed Central

    Boyd, Scott D; Crowe, James E

    2016-01-01

    In the past decade, high-throughput DNA sequencing (HTS) methods and improved approaches for isolating antigen-specific B cells and their antibody genes have been applied in many areas of human immunology. This work has greatly increased our understanding of human antibody repertoires and the specific clones responsible for protective immunity or immune-mediated pathogenesis. Although the principles underlying selection of individual B cell clones in the intact immune system are still under investigation, the combination of more powerful genetic tracking of antibody lineage development and functional testing of the encoded proteins promises to transform therapeutic antibody discovery and optimization. Here, we highlight recent advances in this fast-moving field. PMID:27065089

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

    PubMed Central

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

    2009-01-01

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

  14. Use of expressed sequence tag analysis and cDNA microarrays of the filamentous fungus Aspergillus nidulans.

    PubMed

    Sims, Andrew H; Robson, Geoffrey D; Hoyle, David C; Oliver, Stephen G; Turner, Geoffrey; Prade, Rolf A; Russell, Hugh H; Dunn-Coleman, Nigel S; Gent, Manda E

    2004-02-01

    The use of microarrays in the analysis of gene expression is becoming widespread for many organisms, including yeast. However, although the genomes of a number of filamentous fungi have been fully or partially sequenced, microarray analysis is still in its infancy in these organisms. Here, we describe the construction and validation of microarrays for the fungus Aspergillus nidulans using PCR products from a 4092 EST conidial germination library. An experiment was designed to validate these arrays by monitoring the expression profiles of known genes following the addition of 1% (w/v) glucose to wild-type A. nidulans cultures grown to mid-exponential phase in Vogel's minimal medium with ethanol as the sole carbon source. The profiles of genes showing statistically significant differential expression following the glucose up-shift are presented and an assessment of the quality and reproducibility of the A. nidulans arrays discussed.

  15. Differential co-expression analysis of rheumatoid arthritis with microarray data.

    PubMed

    Wang, Kunpeng; Zhao, Liqiang; Liu, Xuefeng; Hao, Zhenyong; Zhou, Yong; Yang, Chuandong; Li, Hongqiang

    2014-11-01

    The aim of the present study was to investigate the underlying molecular mechanisms of rheumatoid arthritis (RA) using microarray expression profiles from osteoarthritis and RA patients, to improve diagnosis and treatment strategies for the condition. The gene expression profile of GSE27390 was downloaded from Gene Expression Omnibus, including 19 samples from patients with RA (n=9) or osteoarthritis (n=10). Firstly, the differentially expressed genes (DEGs) were obtained with the thresholds of |logFC|>1.0 and P<0.05, using the t‑test method in LIMMA package. Then, differentially co-expressed genes (DCGs) and differentially co-expressed links (DCLs) were screened with q<0.25 by the differential coexpression analysis and differential regulation analysis of gene expression microarray data package. Secondly, pathway enrichment analysis for DCGs was performed by the Database for Annotation, Visualization and Integrated Discovery and the DCLs associated with RA were selected by comparing the obtained DCLs with known transcription factor (TF)-targets in the TRANSFAC database. Finally, the obtained TFs were mapped to the known TF-targets to construct the network using cytoscape software. A total of 1755 DEGs, 457 DCGs and 101988 DCLs were achieved and there were 20 TFs in the obtained six TF-target relations (STAT3-TNF, PBX1‑PLAU, SOCS3-STAT3, GATA1-ETS2, ETS1-ICAM4 and CEBPE‑GATA1) and 457 DCGs. A number of TF-target relations in the constructed network were not within DCLs when the TF and target gene were DCGs. The identified TFs may have an important role in the pathogenesis of RA and have the potential to be used as biomarkers for the development of novel diagnostic and therapeutic strategies for RA.

  16. Expression profile of long non-coding RNAs in colorectal cancer: A microarray analysis.

    PubMed

    Luo, Jia; Xu, Luning; Jiang, Yigui; Zhuo, Dexiang; Zhang, Shengjun; Wu, Lianhui; Xu, Huadong; Huang, Yue

    2016-04-01

    Colorectal cancer (CRC) is one of the most prevalent malignant tumors and the second cause of cancer-related mortality worldwide. Due to increased morbidity and mortality rates, there is an urgent need to understand the pathogenesis of CRC, discover strategies that can improve diagnosis, and ultimately identify therapies targeting this disease. Over the past several years, research into tumor progression mechanisms has been devoted to identifying and understanding various coding and non-coding regions of the genome and how these genetic variants may affect tumorigenesis and progression. Recently, long non-coding RNAs (lncRNAs), which are non‑protein coding transcripts longer than 200 nucleotides, have emerged as a key aspect in tumor pathogenesis. In the present study, we examined the lncRNA and mRNA expression profiles in 4 patients with colon adenocarcinoma, with paired adjacent normal tissues as controls. Microarray data showed that a total of 3,523 lncRNAs and 2,515 mRNAs were consistently differentially expressed in the CRC tissues compared to adjacent normal tissues. Upon comparison of the differentially expressed transcripts between the groups, we identified 22 pathways which were related to the upregulated transcripts and 24 pathways that corresponded to the downregulated transcripts. Gene ontology analysis revealed that the upregulated transcripts were predominantly enriched in DNA metabolic processes, and the downregulated transcripts were predominantly enriched in organic hydroxyl compound metabolic processes. Coding-non-coding gene co-expression analysis showed that these differentially expressed lncRNAs were closely correlated with 'Wnt signaling pathway' components, whose aberrant activation plays a central role in CRC, indicating that a functional correlation exists between them. In conclusion, the results of the microarray and informatic analysis strongly suggest that lncRNA dysregulation is involved in the complicated process of CRC development

  17. The cut-off value for normal nuchal translucency evaluated by chromosomal microarray analysis.

    PubMed

    Maya, Idit; Yacobson, Shiri; Kahana, Sarit; Yeshaya, Josepha; Tenne, Tamar; Agmon-Fishman, Ifaat; Cohen-Vig, Lital; Shohat, Mordechai; Basel-Vanagaite, Lina; Sharony, Reuven

    2017-01-30

    An association between isolated, increased nuchal translucency thickness and pathogenic chromosomal microarray analysis (CMA) has been reported. A recent meta-analysis reported that most studies used a 3.5 mm cut-off value. Considering nuchal translucency distribution and the commonly accepted 5% false positive rate in maternal serum screening, nuchal translucency cut-off levels should be reconsidered. This study evaluated the unique contribution of CMA to the investigation of foetuses with mildly increased nuchal translucency (NT) thickness of 3.0-3.4 mm. This was a retrospective, multicenter study. A single laboratory performed all genetic analyses. Comparative Genomic Hybridization Microarray analysis or Single Nucleotide Polymorphism Array technology was used for CMA. NT was divided into three groups (≤2.9; 3.0-3.4; ≥3.5 mm) and the results were compared, focusing on pregnancies with NT as the only medical indication for CMA at the time of the invasive procedure. If combined first trimester screening (NT and biochemistry) indicated increased risk for common aneuploidies, the case was excluded. CMA results were recorded in 1,588 pregnancies, of which 770 foetuses had NT as a normal or an isolated abnormal finding. Of these, 462 had NT ≤2.9 mm, 170 had NT 3.0-3.4 mm and 138 had NT ≥3.5 mm. Pathogenic copy number variations were found in 1.7%, 7.1%, and 13.0%, respectively. The results suggest that CMA should be part of the investigation in foetuses with isolated, mildly increased NT (3.0-3.4 mm). This article is protected by copyright. All rights reserved.

  18. Detection of Herpesviridae in whole blood by multiplex PCR DNA-based microarray analysis after hematopoietic stem cell transplantation.

    PubMed

    Debaugnies, France; Busson, Laurent; Ferster, Alina; Lewalle, Philippe; Azzi, Nadira; Aoun, Mickael; Verhaegen, Godelieve; Mahadeb, Bhavna; de Marchin, Jérôme; Vandenberg, Olivier; Hallin, Marie

    2014-07-01

    Viral infections are important causes of morbidity and mortality in patients after hematopoietic stem cell transplantation. The monitoring by PCR of Herpesviridae loads in blood samples has become a critical part of posttransplant follow-up, representing mounting costs for the laboratory. In this study, we assessed the clinical performance of the multiplex PCR DNA microarray Clart Entherpex kit for detection of cytomegalovirus (CMV), Epstein-Barr virus (EBV), and human herpesvirus 6 (HHV-6) as a screening test for virological follow-up. Two hundred fifty-five blood samples from 16 transplanted patients, prospectively tested by routine PCR assays, were analyzed by microarray. Routine PCR detected single or multiple viruses in 42% and 10% of the samples, respectively. Microarray detected single or multiple viruses in 34% and 18% of the samples, respectively. Microarray results correlated well with CMV and EBV detections by routine PCR (kappa tests = 0.79 and 0.78, respectively), whereas a weak correlation was observed with HHV-6 (0.43). HHV-7 was also detected in 48 samples by microarray. In conclusion, the microarray is a reliable screening assay for a posttransplant virological follow-up to detect CMV and EBV infections in blood. However, positive samples must be subsequently confirmed and viral loads must be quantified by PCR assays. Limitations were identified regarding HHV-6 detection. Although it is promising, is easy to use as a first-line test, and allows a reduction in the cost of analysis without undue delay in the reporting of the final quantitative result to the clinician, some characteristics of this microarray should be improved, particularly regarding quality control and the targeted virus panel, such that it could then be used as a routine test. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

  19. Microarray-Based Analysis of Differential Gene Expression between Infective and Noninfective Larvae of Strongyloides stercoralis

    PubMed Central

    Ramanathan, Roshan; Varma, Sudhir; Ribeiro, José M. C.; Myers, Timothy G.; Nolan, Thomas J.; Abraham, David; Lok, James B.; Nutman, Thomas B.

    2011-01-01

    Background Differences between noninfective first-stage (L1) and infective third-stage (L3i) larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. Methods and Findings Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs) obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased) having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004), and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90). Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE) had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively fou