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Sample records for antibody microarray analysis

  1. 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

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

    PubMed Central

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

    2015-01-01

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

  3. 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

  4. 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.

  5. Microarray platform for omics analysis

    NASA Astrophysics Data System (ADS)

    Mecklenburg, Michael; Xie, Bin

    2001-09-01

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

  6. Microarray Analysis in Glioblastomas.

    PubMed

    Bhawe, Kaumudi M; Aghi, Manish K

    2016-01-01

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

  7. A computational framework for the analysis of peptide microarray antibody binding data with application to HIV vaccine profiling.

    PubMed

    Imholte, Greg C; Sauteraud, Renan; Korber, Bette; Bailer, Robert T; Turk, Ellen T; Shen, Xiaoying; Tomaras, Georgia D; Mascola, John R; Koup, Richard A; Montefiori, David C; Gottardo, Raphael

    2013-09-30

    We present an integrated analytical method for analyzing peptide microarray antibody binding data, from normalization through subject-specific positivity calls and data integration and visualization. Current techniques for the normalization of such data sets do not account for non-specific binding activity. A novel normalization technique based on peptide sequence information quickly and effectively reduced systematic biases. We also employed a sliding mean window technique that borrows strength from peptides sharing similar sequences, resulting in reduced signal variability. A smoothed signal aided in the detection of weak antibody binding hotspots. A new principled FDR method of setting positivity thresholds struck a balance between sensitivity and specificity. In addition, we demonstrate the utility and importance of using baseline control measurements when making subject-specific positivity calls. Data sets from two human clinical trials of candidate HIV-1 vaccines were used to validate the effectiveness of our overall computational framework. PMID:23770318

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

    PubMed

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

    2016-09-25

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

  9. Serial Analysis of 38 Proteins during the Progression of Human Breast Tumor in Mice Using an Antibody Colocalization Microarray*

    PubMed Central

    Li, Huiyan; Bergeron, Sébastien; Annis, Matthew G.; Siegel, Peter M.; Juncker, David

    2015-01-01

    Proteins in serum or plasma hold great potential for use in disease diagnosis and monitoring. However, the correlation between tumor burden and protein biomarker concentration has not been established. Here, using an antibody colocalization microarray, the protein concentration in serum was measured and compared with the size of mammary xenograft tumors in 11 individual mice from the time of injection; seven blood samples were collected from each tumor-bearing mouse as well as control mice on a weekly basis. The profiles of 38 proteins detected in sera from these animals were analyzed by clustering, and we identified 10 proteins with the greatest relative increase in serum concentration that correlated with growth of the primary mammary tumor. To evaluate the diagnosis of cancer based on these proteins using either an absolute threshold (i.e. a concentration cutoff) or self-referenced differential threshold based on the increase in concentration before cell injection, receiver operating characteristic curves were produced for 10 proteins with increased concentration, and the area under curve was calculated for each time point based on a single protein or on a panel of proteins, in each case showing a rapid increase of the area under curve. Next, the sensitivity and specificity of individual and optimal protein panels were calculated, showing high accuracy as early as week 2. These results provide a foundation for studies of tumor growth through measuring serial changes of protein concentration in animal models. PMID:25680959

  10. Serial analysis of 38 proteins during the progression of human breast tumor in mice using an antibody colocalization microarray.

    PubMed

    Li, Huiyan; Bergeron, Sébastien; Annis, Matthew G; Siegel, Peter M; Juncker, David

    2015-04-01

    Proteins in serum or plasma hold great potential for use in disease diagnosis and monitoring. However, the correlation between tumor burden and protein biomarker concentration has not been established. Here, using an antibody colocalization microarray, the protein concentration in serum was measured and compared with the size of mammary xenograft tumors in 11 individual mice from the time of injection; seven blood samples were collected from each tumor-bearing mouse as well as control mice on a weekly basis. The profiles of 38 proteins detected in sera from these animals were analyzed by clustering, and we identified 10 proteins with the greatest relative increase in serum concentration that correlated with growth of the primary mammary tumor. To evaluate the diagnosis of cancer based on these proteins using either an absolute threshold (i.e. a concentration cutoff) or self-referenced differential threshold based on the increase in concentration before cell injection, receiver operating characteristic curves were produced for 10 proteins with increased concentration, and the area under curve was calculated for each time point based on a single protein or on a panel of proteins, in each case showing a rapid increase of the area under curve. Next, the sensitivity and specificity of individual and optimal protein panels were calculated, showing high accuracy as early as week 2. These results provide a foundation for studies of tumor growth through measuring serial changes of protein concentration in animal models. PMID:25680959

  11. Tiling Microarray Analysis Tools

    SciTech Connect

    Nix, Davis Austin

    2005-05-04

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

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

    PubMed

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

    2016-05-01

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

  13. Tiling Microarray Analysis Tools

    Energy Science and Technology Software Center (ESTSC)

    2005-05-04

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

  14. 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. PMID:26709003

  15. 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

  16. Microarray Analysis of Microbial Weathering

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

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

    PubMed

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

    2016-01-01

    With the increasing need for understanding antibody specificity in antibody and vaccine research, pepscan assays provide a rapid method for mapping and profiling antibody responses to continuous epitopes. We have developed a relatively low-cost method to generate peptide microarray slides for studying antibody binding. Using a setup of an IntavisAG MultiPep RS peptide synthesizer, a Digilab MicroGrid II 600 microarray printer robot, and an InnoScan 1100 AL scanner, the method allows the interrogation of up to 1536 overlapping, alanine-scanning, and mutant peptides derived from the target antigens. Each peptide is tagged with a polyethylene glycol aminooxy terminus to improve peptide solubility, orientation, and conjugation efficiency to the slide surface. PMID:26490468

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Novel Microarrays for Simultaneous Serodiagnosis of Multiple Antiviral Antibodies

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed

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

    2003-01-01

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

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

    PubMed

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

    2015-07-01

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

  3. Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: Systematic variation between sample types and calibration of mass spectrometry data

    SciTech Connect

    Haab, Brian B.; Geierstanger, Bernhard H.; Michailidis, George; Vitzthum, Frank; Forrester, Sara; Okon, Ryan; Saviranta, Petri; Brinker, Achim; Sorette, Martin; Perlee, Lorah; Suresh, Shubha; Drwal, Garry; Adkins, Joshua N.; Omenn, Gilbert S.

    2005-08-01

    Four different immunoassay and antibody microarray methods performed at four different sites were used to measure the levels of a broad range of proteins (N = 323 assays; 39, 88, 168, and 28 assays at the respective sites; 237 unique analytes) in the human serum and plasma reference specimens distributed by the Plasma Proteome Project (PPP) of the HUPO. The methods provided a means to (1) assess the level of systematic variation in protein abundances associated with blood preparation methods (serum, citrate-anticoagulated-plasma, EDTA-anticoagulated-plasma, or heparin-anticoagulated-plasma) and (2) evaluate the dependence on concentration of MS-based protein identifications from data sets using the HUPO specimens. Some proteins, particularly cytokines, had highly variable concentrations between the different sample preparations, suggesting specific effects of certain anticoagulants on the stability or availability of these proteins. The linkage of antibody-based measurements from 66 different analytes with the combined MS/MS data from 18 different laboratories showed that protein detection and the quality of MS data increased with analyte concentration. The conclusions from these initial analyses are that the optimal blood preparation method is variable between analytes and that the discovery of blood proteins by MS can be extended to concentrations below the ng/mL range under certain circumstances. Continued developments in antibody-based methods will further advance the scientific goals of the PPP.

  4. A multivariate approach for high throughput pectin profiling by combining glycan microarrays with monoclonal antibodies.

    PubMed

    Sousa, António G; Ahl, Louise I; Pedersen, Henriette L; Fangel, Jonatan U; Sørensen, Susanne O; Willats, William G T

    2015-05-29

    Pectin-one of the most complex biomacromolecules in nature has been extensively studied using various techniques. This has been done so in an attempt to understand the chemical composition and conformation of pectin, whilst discovering and optimising new industrial applications of the polymer. For the last decade the emergence of glycan microarray technology has led to a growing capacity of acquiring simultaneous measurements related to various carbohydrate characteristics while generating large collections of data. Here we used a multivariate analysis approach in order to analyse a set of 359 pectin samples probed with 14 different monoclonal antibodies (mAbs). Principal component analysis (PCA) and partial least squares (PLS) regression were utilised to obtain the most optimal qualitative and quantitative information from the spotted microarrays. The potential use of microarray technology combined with chemometrics for the accurate determination of degree of methyl-esterification (DM) and degree of blockiness (DB) was assessed. PMID:25950120

  5. Immobilization strategies for single-chain antibody microarrays

    SciTech Connect

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

    2008-06-01

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

  6. 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

  7. 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

  8. 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

  9. Microarray analysis: Uses and Limitations

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

    Ramirez, Lisa S; Wang, Jun

    2016-01-01

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

  11. Microarray analysis in pulmonary hypertension.

    PubMed

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

    2016-07-01

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

  12. 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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2015-04-01

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

  15. 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

  16. 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

  17. 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

  18. Pineal function: impact of microarray analysis.

    PubMed

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

    2010-01-27

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

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

    PubMed

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

    2016-01-01

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

  20. 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

  1. 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...

  2. Data Analysis Strategies for Protein Microarrays

    PubMed Central

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

    2012-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  4. Microarray analysis at single molecule resolution

    PubMed Central

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

    2010-01-01

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

  5. Differential Anti-Glycan Antibody Responses in Schistosoma mansoni-Infected Children and Adults Studied by Shotgun Glycan Microarray

    PubMed Central

    van Diepen, Angela; Smit, Cornelis H.; van Egmond, Loes; Kabatereine, Narcis B.; Pinot de Moira, Angela; Dunne, David W.; Hokke, Cornelis H.

    2012-01-01

    Background Schistosomiasis (bilharzia) is a chronic and potentially deadly parasitic disease that affects millions of people in (sub)tropical areas. An important partial immunity to Schistosoma infections does develop in disease endemic areas, but this takes many years of exposure and maturation of the immune system. Therefore, children are far more susceptible to re-infection after treatment than older children and adults. This age-dependent immunity or susceptibility to re-infection has been shown to be associated with specific antibody and T cell responses. Many antibodies generated during Schistosoma infection are directed against the numerous glycans expressed by Schistosoma. The nature of glycan epitopes recognized by antibodies in natural schistosomiasis infection serum is largely unknown. Methodology/Principal Findings The binding of serum antibodies to glycans can be analyzed efficiently and quantitatively using glycan microarray approaches. Very small amounts of a large number of glycans are presented on a solid surface allowing binding properties of various glycan binding proteins to be tested. We have generated a so-called shotgun glycan microarray containing natural N-glycan and lipid-glycan fractions derived from 4 different life stages of S. mansoni and applied this array to the analysis of IgG and IgM antibodies in sera from children and adults living in an endemic area. This resulted in the identification of differential glycan recognition profiles characteristic for the two different age groups, possibly reflecting differences in age or differences in length of exposure or infection. Conclusions/Significance Using the shotgun glycan microarray approach to study antibody response profiles against schistosome-derived glycan elements, we have defined groups of infected individuals as well as glycan element clusters to which antibody responses are directed in S. mansoni infections. These findings are significant for further exploration of Schistosoma

  6. 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

  7. 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).

  8. 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…

  9. RNAi microarray analysis in cultured mammalian cells.

    PubMed

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

    2003-10-01

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

  10. Erratum: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing.

    PubMed

    2015-01-01

    The author's email has been corrected in the publication of Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing. There was an error with the author, Jerry Zhou's, email. The author's email has been updated to: j.zhou@uws.edu.au from: jzho7551@mail.usyd.edu.au. PMID:26167960

  11. 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

  12. 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.

  13. 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

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

    PubMed

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

    2015-01-01

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

  15. Meta-analysis of incomplete microarray studies.

    PubMed

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

    2015-10-01

    Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information-providing only a ranked list of genes, for example-it is common to reduce all studies to ranked lists prior to combining them. Since this entails a loss of information, we consider a hierarchical Bayes approach to meta-analysis using different types of information from different studies: the full data matrix, summary statistics, or ranks. The model uses an informative prior for the parameter of interest to aid the detection of differentially expressed genes. Simulations show that the new approach can give substantial power gains compared with classical meta-analysis and list aggregation methods. A meta-analysis of 11 published studies with different data types identifies genes known to be involved in ovarian cancer and shows significant enrichment. PMID:25987649

  16. 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. PMID:26345442

  17. Assessing Antibody Microarray for Space Missions: Effect of Long-term Storage, Gamma radiation and High Energy proton radiation

    NASA Astrophysics Data System (ADS)

    de Diego-Castilla, G.; Parro, V.

    2012-09-01

    Fluorescent antibody microarray has been proposed for Molecular biomarker detector in planetary exploration [1]. A number of different environmental stresses may affect the antibody performance, such as temperatures variations, highly penetrating radiation and high energy particles. Here we have tested the effect of gamma radiation, proton radiation and longterm storage on the microarray immunoassay and fluorocromes. Although different antibodies might have different susceptibilities we conclude that there was not significant reduction in the functionality of antibodies printed on the microarray and the fluorescent tracers antibodies, even in a extreme case of receiving a radiation dose 3000-fold than a biochip would receive in a trip mission to Mars. In summary, antibodies are suitable for use in planetary exploration purposes.

  18. High-performance low-cost antibody microarrays using enzyme-mediated silver amplification.

    PubMed

    Zhou, Gina; Bergeron, Sebastien; Juncker, David

    2015-04-01

    Antibody microarrays can detect multiple proteins simultaneously, but the need for bulky and expensive fluorescence scanners limits their adaptation in clinical settings. Here we introduce a 15-plex enzyme-mediated silver enhanced sandwich immunoassay (SENSIA) on a microarray as an economic alternative to conventional fluorescence microarray assays. We compared several gold and silver amplification schemes, optimized HRP-mediated silver amplification, and evaluated the use of flatbed scanners for microarray quantification. Using the optimized assay condition, we established binding curves for 15 proteins using both SENSIA and conventional fluorescence microarray assays and compared their limits of detection (LODs) and dynamic ranges (DRs). We found that the LODs for all proteins are in the pg/mL range, with LODs for 12 proteins below 10 pg/mL. All but two proteins (ENDO and IL4) have similar LODs (less than 10-fold difference) and all but two proteins (IL1b and MCP1) are similar in DR (less than 1.5-log difference). Furthermore, we spiked six proteins in diluted serum and measured them by both silver enhancement and fluorescence detection and found a good agreement (R(2) > 0.9) between the two methods, suggesting that a complex matrix such as serum has a minimal effect on the measurement. By combining enzyme-mediated silver enhancement and consumer electronics for optical detection, SENSIA presents a new opportunity for low-cost high-sensitivity multiplex immunoassays for clinical applications. PMID:25668573

  19. Chapter 9 - Methylation Analysis by Microarray

    PubMed Central

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

    2010-01-01

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

  20. Microarrays with varying carbohydrate density reveal distinct subpopulations of serum antibodies.

    PubMed

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

    2009-07-01

    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

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

    PubMed

    Gehring, Andrew G; Brewster, Jeffrey D; He, Yiping; Irwin, Peter L; Paoli, George C; Simons, Tawana; Tu, Shu-I; Uknalis, Joseph

    2015-01-01

    Antibody microarray is a powerful analytical technique because of its inherent ability to simultaneously discriminate and measure numerous analytes, therefore making the technique conducive to both the multiplexed detection and identification of bacterial analytes (i.e., whole cells, as well as associated metabolites and/or toxins). We developed a sandwich fluorescent immunoassay combined with a high-throughput, multiwell plate microarray detection format. Inexpensive polystyrene plates were employed containing passively adsorbed, array-printed capture antibodies. During sample reaction, centrifugation was the only strategy found to significantly improve capture, and hence detection, of bacteria (pathogenic Escherichia coli O157:H7) to planar capture surfaces containing printed antibodies. Whereas several other sample incubation techniques (e.g., static vs. agitation) had minimal effect. Immobilized bacteria were labeled with a red-orange-fluorescent dye (Alexa Fluor 555) conjugated antibody to allow for quantitative detection of the captured bacteria with a laser scanner. Shiga toxin 1 (Stx1) could be simultaneously detected along with the cells, but none of the agitation techniques employed during incubation improved detection of the relatively small biomolecule. Under optimal conditions, the assay had demonstrated limits of detection of ~5.8 × 10⁵ cells/mL and 110 ng/mL for E. coli O157:H7 and Stx1, respectively, in a ~75 min total assay time. PMID:26690151

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

    PubMed Central

    Gehring, Andrew G.; Brewster, Jeffrey D.; He, Yiping; Irwin, Peter L.; Paoli, George C.; Simons, Tawana; Tu, Shu-I; Uknalis, Joseph

    2015-01-01

    Antibody microarray is a powerful analytical technique because of its inherent ability to simultaneously discriminate and measure numerous analytes, therefore making the technique conducive to both the multiplexed detection and identification of bacterial analytes (i.e., whole cells, as well as associated metabolites and/or toxins). We developed a sandwich fluorescent immunoassay combined with a high-throughput, multiwell plate microarray detection format. Inexpensive polystyrene plates were employed containing passively adsorbed, array-printed capture antibodies. During sample reaction, centrifugation was the only strategy found to significantly improve capture, and hence detection, of bacteria (pathogenic Escherichia coli O157:H7) to planar capture surfaces containing printed antibodies. Whereas several other sample incubation techniques (e.g., static vs. agitation) had minimal effect. Immobilized bacteria were labeled with a red-orange-fluorescent dye (Alexa Fluor 555) conjugated antibody to allow for quantitative detection of the captured bacteria with a laser scanner. Shiga toxin 1 (Stx1) could be simultaneously detected along with the cells, but none of the agitation techniques employed during incubation improved detection of the relatively small biomolecule. Under optimal conditions, the assay had demonstrated limits of detection of ~5.8 × 105 cells/mL and 110 ng/mL for E. coli O157:H7 and Stx1, respectively, in a ~75 min total assay time. PMID:26690151

  3. Ontology-Based Analysis of Microarray Data.

    PubMed

    Giuseppe, Agapito; Milano, Marianna

    2016-01-01

    The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress. PMID:25971913

  4. Genomic-Wide Analysis with Microarrays in Human Oncology

    PubMed Central

    Inaoka, Kenichi; Inokawa, Yoshikuni; Nomoto, Shuji

    2015-01-01

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

  5. Discovery and validation of an INflammatory PROtein-driven GAstric cancer Signature (INPROGAS) using antibody microarray-based oncoproteomics

    PubMed Central

    Puig-Costa, Manuel; Codina-Cazador, Antonio; Cortés-Pastoret, Elisabet; Oliveras-Ferraros, Cristina; Cufí, Sílvia; Flaquer, Sílvia; Llopis-Puigmarti, Francesca; Pujol-Amado, Eulalia; Corominas-Faja, Bruna; Cuyàs, Elisabet; Ortiz, Rosa; Lopez-Bonet, Eugeni; Queralt, Bernardo; Guardeño, Raquel; Martin-Castillo, Begoña; Roig, Josep; Joven, Jorge; Menendez, Javier A.

    2014-01-01

    This study aimed to improve gastric cancer (GC) diagnosis by identifying and validating an INflammatory PROtein-driven GAstric cancer Signature (hereafter INPROGAS) using low-cost affinity proteomics. The detection of 120 cytokines, 43 angiogenic factors, 41 growth factors, 40 inflammatory factors and 10 metalloproteinases was performed using commercially available human antibody microarray-based arrays. We identified 21 inflammation-related proteins (INPROGAS) with significant differences in expression between GC tissues and normal gastric mucosa in a discovery cohort of matched pairs (n=10) of tumor/normal gastric tissues. Ingenuity pathway analysis confirmed the “inflammatory response”, “cellular movement” and “immune cell trafficking” as the most overrepresented biofunctions within INPROGAS. Using an expanded independent validation cohort (n = 22), INPROGAS classified gastric samples as “GC” or “non-GC” with a sensitivity of 82% (95% CI 59-94) and a specificity of 73% (95% CI 49-89). The positive predictive value and negative predictive value in this validation cohort were 75% (95% CI 53-90) and 80% (95% CI 56-94), respectively. The positive predictive value and negative predictive value in this validation cohort were 75% (95% CI 53-90) and 80% (95% CI 56-94), respectively. Antibody microarray analyses of the GC-associated inflammatory proteome identified a 21-protein INPROGAS that accurately discriminated GC from noncancerous gastric mucosa. PMID:24722433

  6. Application of Protein Microarrays for Multiplexed Detection of Antibodies to Tumor Antigens in Breast Cancer

    PubMed Central

    Anderson, Karen S.; Ramachandran, Niroshan; Wong, Jessica; Raphael, Jacob V.; Hainsworth, Eugenie; Demirkan, Gokhan; Cramer, Daniel; Aronzon, Diana; Hodi, F. Stephen; Harris, Lyndsay; Logvinenko, Tanya; LaBaer, Joshua

    2012-01-01

    There is strong preclinical evidence that cancer, including breast cancer, undergoes immune surveillance. This continual monitoring, by both the innate and the adaptive immune systems, recognizes changes in protein expression, mutation, folding, glycosylation, and degradation. Local immune responses to tumor antigens are amplified in draining lymph nodes, and then enter the systemic circulation. The antibody response to tumor antigens, such as p53 protein, are robust, stable, and easily detected in serum, may exist in greater concentrations than their cognate antigens, and are potential highly specific biomarkers for cancer. However, antibodies have limited sensitivities as single analytes, and differences in protein purification and assay characteristics have limited their clinical application. For example, p53 autoantibodies in the sera are highly specific for cancer patients, but are only detected in the sera of 10-20% of patients with breast cancer. Detection of p53 autoantibodies is dependent on tumor burden, p53 mutation, rapidly decreases with effective therapy, but is relatively independent of breast cancer subtype. Although antibodies to hundreds of other tumor antigens have been identified in the sera of breast cancer patients, very little is known about the specificity and clinical impact of the antibody immune repertoire to breast cancer. Recent advances in proteomic technologies have the potential for rapid identification of immune response signatures for breast cancer diagnosis and monitoring. We have adapted programmable protein microarrays for the specific detection of autoantibodies in breast cancer. Here, we present the first demonstration of the application of programmable protein microarray ELISAs for the rapid identification of breast cancer autoantibodies. PMID:18311903

  7. Two-color, rolling-circle amplification on antibody microarrays for sensitive, multiplexed serum-protein measurements.

    PubMed

    Zhou, Heping; Bouwman, Kerri; Schotanus, Mark; Verweij, Cornelius; Marrero, Jorge A; Dillon, Deborah; Costa, Jose; Lizardi, Paul; Haab, Brian B

    2004-01-01

    The ability to conveniently and rapidly profile a diverse set of proteins has valuable applications. In a step toward further enabling such a capability, we developed the use of rolling-circle amplification (RCA) to measure the relative levels of proteins from two serum samples, labeled with biotin and digoxigenin, respectively, that have been captured on antibody microarrays. Two-color RCA produced fluorescence up to 30-fold higher than direct-labeling and indirect-detection methods using antibody microarrays prepared on both polyacrylamide-based hydrogels and nitrocellulose. Replicate RCA measurements of multiple proteins from sets of 24 serum samples were highly reproducible and accurate. In addition, RCA enabled reproducible measurements of distinct expression profiles from lower-abundance proteins that were not measurable using the other detection methods. Two-color RCA on antibody microarrays should allow the convenient acquisition of expression profiles from a great diversity of proteins for a variety of applications. PMID:15059261

  8. 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. PMID:22007740

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  10. ProMAT Calibrator: A Tool for Reducing Experimental Bias in Antibody Microarrays

    SciTech Connect

    Zangar, Richard C.; Daly, Don S.; White, A.; Servoss, Shannon; Tan, Ruimin; Collett, James R.

    2009-08-01

    Our research group has been developing enzyme-linked immunosorbent assays (ELISA) microarray technology for the rapid and quantitative evaluation of biomarker panels. Studies using antibody microarrays are susceptible to systematic bias from the various steps in the experimental process, and these biases can mask biologically significant differences. For this reason, we have developed a calibration system that can identify and reduce systematic bias due to processing factors. Specifically, we developed a sandwich ELISA for green fluorescent protein (GFP) that is included on each chip. The GFP antigen is spiked into each biological sample or standard mixture and the resulting signal is used for calibration across chips. We developed ProMAT Calibrator, an open-source bioinformatics tool, for the rapid visualization and interpretation of the calibrator data and, if desired, data normalization. We demonstrate that data normalization using this system markedly reduces bias from processing factors. Equally useful, this calibrator system can help reveal the source of the bias, thereby facilitating the elimination of the underlying problem.

  11. 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.

  12. 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

  13. 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.

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

    DOE PAGESBeta

    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 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

  15. Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

    PubMed Central

    Zhou, Jerry; Belov, Larissa; Solomon, Michael J.; Chan, Charles; Clarke, Stephen J.; Christopherson, Richard I.

    2011-01-01

    The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority of CRC cases, cell dysfunction is the result of numerous mutations that modify protein expression and post-translational modification1. A number of cell surface antigens, including cluster of differentiation (CD) antigens, have been identified as potential prognostic or metastatic biomarkers in CRC. These antigens make ideal biomarkers as their expression often changes with tumour progression or interactions with other cell types, such as tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs). The use of immunohistochemistry (IHC) for cancer sub-classification and prognostication is well established for some tumour types2,3. However, no single ‘marker’ has shown prognostic significance greater than clinico-pathological staging or gained wide acceptance for use in routine pathology reporting of all CRC cases. A more recent approach to prognostic stratification of disease phenotypes relies on surface protein profiles using multiple 'markers'. While expression profiling of tumours using proteomic techniques such as iTRAQ is a powerful tool for the discovery of biomarkers4, it is not optimal for routine use in diagnostic laboratories and cannot distinguish different cell types in a mixed population. In addition, large amounts of tumour tissue are required for the profiling of purified plasma membrane glycoproteins by these methods. In this video we described a simple method for surface proteome profiling of viable cells from disaggregated CRC samples using a DotScan CRC antibody microarray. The 122-antibody microarray consists of a standard 82-antibody region recognizing a range of lineage-specific leukocyte markers, adhesion molecules, receptors and markers of inflammation and immune response5, together with a satellite region for detection of 40 potentially prognostic markers for CRC

  16. 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.

  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. PMID:22157075

  18. MICROARRAY SYSTEM FOR CONTAMINATED WATER ANALYSIS

    EPA Science Inventory

    We used the optimum slide treatment as determined by the previous study*: water plasma cleaning, photo-hydrolytic weathering, and silane treatment using 3-aminopropyl triethoxysilane (APS). Anti-E.coli antibodies were printed onto Corning 2947 (soda-lime-silicate) ...

  19. 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. PMID:21294639

  20. 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.

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

    PubMed Central

    Herold, Keith E.

    2008-01-01

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

  2. Bulk segregant analysis using single nucleotide polymorphism microarrays

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. 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

  4. 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. PMID:27293753

  5. Analysis of porcine MHC using microarrays.

    PubMed

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

    2012-07-15

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

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

    PubMed

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

    2015-01-01

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

  7. Examination of Oral Cancer Biomarkers by Tissue Microarray Analysis

    PubMed Central

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

    2008-01-01

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

  8. Analysis of microarray experiments of gene expression profiling

    PubMed Central

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

    2008-01-01

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

  9. Chemically-blocked Antibody Microarray for Multiplexed High-throughput Profiling of Specific Protein Glycosylation in Complex Samples

    PubMed Central

    Lu, Chen; Wonsidler, Joshua L.; Li, Jianwei; Du, Yanming; Block, Timothy; Haab, Brian; Chen, Songming

    2012-01-01

    In this study, we describe an effective protocol for use in a multiplexed high-throughput antibody microarray with glycan binding protein detection that allows for the glycosylation profiling of specific proteins. Glycosylation of proteins is the most prevalent post-translational modification found on proteins, and leads diversified modifications of the physical, chemical, and biological properties of proteins. Because the glycosylation machinery is particularly susceptible to disease progression and malignant transformation, aberrant glycosylation has been recognized as early detection biomarkers for cancer and other diseases. However, current methods to study protein glycosylation typically are too complicated or expensive for use in most normal laboratory or clinical settings and a more practical method to study protein glycosylation is needed. The new protocol described in this study makes use of a chemically blocked antibody microarray with glycan-binding protein (GBP) detection and significantly reduces the time, cost, and lab equipment requirements needed to study protein glycosylation. In this method, multiple immobilized glycoprotein-specific antibodies are printed directly onto the microarray slides and the N-glycans on the antibodies are blocked. The blocked, immobilized glycoprotein-specific antibodies are able to capture and isolate glycoproteins from a complex sample that is applied directly onto the microarray slides. Glycan detection then can be performed by the application of biotinylated lectins and other GBPs to the microarray slide, while binding levels can be determined using Dylight 549-Streptavidin. Through the use of an antibody panel and probing with multiple biotinylated lectins, this method allows for an effective glycosylation profile of the different proteins found in a given human or animal sample to be developed. Introduction Glycosylation of protein, which is the most ubiquitous post-translational modification on proteins, modifies

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

    PubMed

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

    2004-06-01

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

  11. Bioinformatics and Microarray Data Analysis on the Cloud.

    PubMed

    Calabrese, Barbara; Cannataro, Mario

    2016-01-01

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

  12. 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. PMID:26707204

  13. Development of Fluorescent Polymerization-based Signal Amplification for Sensitive and Non-enzymatic Biodetection in Antibody Microarrays

    PubMed Central

    Avens, Heather J.; Bowman, Christopher N.

    2009-01-01

    Antibody microarrays are a critical tool for proteomics, requiring broad, highly sensitive detection of numerous low abundance biomarkers. Fluorescent polymerization-based amplification (FPBA) is presented as a novel, non-enzymatic signal amplification method that takes advantage of the chain-reaction nature of radical polymerization to achieve a highly amplified fluorescent response. A streptavidin-eosin conjugate localizes eosin photoinitiators for polymerization on the chip where biotinylated target protein is bound. The chip is contacted with acrylamide as a monomer, N-methyldiethanolamine as a coinitiator and yellow/green fluorescent nanoparticles (NPs) which, upon initiation, combine to form a macroscopically visible and highly fluorescent film. The rapid polymerization kinetics and the presence of cross-linker favor entrapment of the fluorescent NPs in the polymer, enabling highly sensitive fluorescent biodetection. This method is demonstrated as being appropriate for antibody microarrays and is compared to detection approaches which utilize streptavidin-FITC (SA-FITC) and streptavidin-labeled yellow/green NPs (SA-NPs). It is found that FPBA is able to detect 0.16 (+/− 0.01) biotin-antibody/µm2 (or 40 zeptomole surface-bound target molecules), while SA-FITC has a limit of detection of 31 (+/− 1) biotin-antibody/µm2 and SA-NPs fail to achieve any significant signal under the conditions evaluated here. Further, FPBA in conjunction with fluorescent stereomicroscopy yields equal or better sensitivity compared to fluorescent detection of SA-eosin using a much more costly microarray scanner. By facilitating highly sensitive detection, FPBA is expected to enable detection of low abundance antigens and also make possible a transition towards less expensive fluorescence detection instrumentation. PMID:19508906

  14. Development of fluorescent polymerization-based signal amplification for sensitive and non-enzymatic biodetection in antibody microarrays.

    PubMed

    Avens, Heather J; Bowman, Christopher N

    2010-01-01

    Antibody microarrays are a critical tool for proteomics, requiring broad, highly sensitive detection of numerous low abundance biomarkers. Fluorescent polymerization-based amplification (FPBA) is presented as a novel, non-enzymatic signal amplification method that takes advantage of the chain-reaction nature of radical polymerization to achieve a highly amplified fluorescent response. A streptavidin-eosin conjugate localizes eosin photoinitiators for polymerization on the chip where biotinylated target protein is bound. The chip is contacted with acrylamide as a monomer, N-methyldiethanolamine as a coinitiator and yellow/green fluorescent nanoparticles (NPs) which, upon initiation, combine to form a macroscopically visible and highly fluorescent film. The rapid polymerization kinetics and the presence of cross-linker favor entrapment of the fluorescent NPs in the polymer, enabling highly sensitive fluorescent biodetection. This method is demonstrated as being appropriate for antibody microarrays and is compared to detection approaches which utilize streptavidin-fluorescein isothiocyanate (SA-FITC) and streptavidin-labeled yellow/green NPs (SA-NPs). It is found that FPBA is able to detect 0.16 + or - 0.01 biotin-antibody microm(-2) (or 40 zmol surface-bound target molecules), while SA-FITC has a limit of detection of 31 + or - 1 biotin-antibody microm(-2) and SA-NPs fail to achieve any significant signal under the conditions evaluated here. Further, FPBA in conjunction with fluorescent stereomicroscopy yields equal or better sensitivity compared to fluorescent detection of SA-eosin using a much more costly microarray scanner. By facilitating highly sensitive detection, FPBA is expected to enable detection of low abundance antigens and also make possible a transition towards less expensive fluorescence detection instrumentation. PMID:19508906

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

    PubMed

    Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

    2007-07-01

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

  16. 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. PMID:16939792

  17. 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

  18. 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

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed

    Ishihara, Takeaki; Sato, Yukiyo; Takahashi, Hideki

    2015-01-01

    The complex process for host-plant resistance to viruses is precisely regulated by a number of genes and signaling compounds. Thus, global gene expression analysis can provide a powerful tool to grasp the complex molecular network for resistance to viruses. The procedures for comparative global gene expression profiling of virus-resistant and control plants by microarray analysis include RNA extraction, cDNA synthesis, cRNA labeling, hybridization, array scanning, and data mining steps. There are several platforms for the microarray analysis. Commercial services for the steps from cDNA synthesis to array scanning are now widely available; however, the data manipulation step is highly dependent on the experimental design and research focus. The protocols presented here are optimized for analyzing global gene expression during the R gene-conferred defense response using commercial oligonucleotide-based arrays. We also demonstrate a technique to screen for differentially expressed genes using Excel software and a simple Internet tool-based data mining approach for characterizing the identified genes. PMID:25287505

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

    PubMed

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

    2014-10-01

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

  2. 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

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

    PubMed Central

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

    2010-01-01

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

  4. 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.

  5. 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

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

    PubMed

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

    2014-01-25

    Gene set analysis (GSA) incorporates biological information into statistical knowledge to identify gene sets differently expressed between two or more phenotypes. It allows us to gain an insight into the functional working mechanism of cells beyond the detection of differently expressed gene sets. In order to evaluate the competence of GSA approaches, three self-contained GSA approaches with different statistical methods were chosen; Category, Globaltest and Hotelling's T(2) together with their assayed power to identify the differences expressed via simulation and real microarray data. The Category does not take care of the correlation structure, while the other two deal with correlations. In order to perform these methods, R and Bioconductor were used. Furthermore, venous thromboembolism and acute lymphoblastic leukemia microarray data were applied. The results of three GSAs showed that the competence of these methods depends on the distribution of gene expression in a dataset. It is very important to assay the distribution of gene expression data before choosing the GSA method to identify gene sets differently expressed between phenotypes. On the other hand, assessment of common genes among significant gene sets indicated that there was a significant agreement between the result of GSA and the findings of biologists. PMID:24012817

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

    PubMed

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

    2001-02-01

    We have developed a three-component system for microbial identification that consists of (i) a universal syringe-operated silica minicolumn for successive DNA and RNA isolation, fractionation, fragmentation, fluorescent labeling, and removal of excess free label and short oligonucleotides; (ii) microarrays of immobilized oligonucleotide probes for 16S rRNA identification; and (iii) a portable battery-powered device for imaging the hybridization of fluorescently labeled RNA fragments with the arrays. The minicolumn combines a guanidine thiocyanate method of nucleic acid isolation with a newly developed hydroxyl radical-based technique for DNA and RNA labeling and fragmentation. DNA and RNA can also be fractionated through differential binding of double- and single-stranded forms of nucleic acids to the silica. The procedure involves sequential washing of the column with different solutions. No vacuum filtration steps, phenol extraction, or centrifugation is required. After hybridization, the overall fluorescence pattern is captured as a digital image or as a Polaroid photo. This three-component system was used to discriminate Escherichia coli, Bacillus subtilis, Bacillus thuringiensis, and human HL60 cells. The procedure is rapid: beginning with whole cells, it takes approximately 25 min to obtain labeled DNA and RNA samples and an additional 25 min to hybridize and acquire the microarray image using a stationary image analysis system or the portable imager. PMID:11157263

  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. 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

  10. 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

    2015-10-01

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

  11. Using Kepler for Tool Integration in Microarray Analysis Workflows

    PubMed Central

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

    2015-01-01

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

  12. Fast epitope mapping for the anti-MUC1 monoclonal antibody by combining a one-bead-one-glycopeptide library and a microarray platform.

    PubMed

    Garcia-Martin, Fayna; Matsushita, Takahiko; Hinou, Hiroshi; Nishimura, Shin-Ichiro

    2014-11-24

    Anti-MUC1 monoclonal antibodies (mAbs) are powerful tools that can be used to recognize cancer-related MUC1 molecules, the O-glycosylation status of which is believed to affect binding affinity. We demonstrate the feasibility of using a rapid screening methodology to elucidate those effects. The approach involves i) "one-bead-one-compound"-based preparation of bilayer resins carrying glycopeptides on the shell and mass-tag tripeptides coding O-glycan patterns in the core, ii) on-resin screening with an anti-MUC1 mAb, iii) separating positive resins by utilizing secondary antibody conjugation with magnetic beads, and (iv) decoding the mass-tag that is detached from the positive resins pool by using mass spectrometric analysis. We tested a small library consisting of 27 MUC1 glycopeptides with different O-glycosylations against anti-MUC1 mAb clone VU-3C6. Qualitative mass-tag analysis showed that increasing the number of glycans leads to an increase in the binding affinity. Six glycopeptides selected from the library were validated by using a microarray-based assay. Our screening provides valuable information on O-glycosylations of epitopes leading to high affinity with mAb. PMID:25303614

  13. 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…

  14. 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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  16. 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.

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

    PubMed Central

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

    2012-01-01

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

  18. TAMEE: data management and analysis for tissue microarrays

    PubMed Central

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

    2007-01-01

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

  19. 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

  20. 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.

  1. 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

  2. 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

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2016-01-01

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

  5. Cytokines in cerebrospinal fluid of neurosyphilis patients: Identification of Urokinase plasminogen activator using antibody microarrays.

    PubMed

    Lu, Ping; Zheng, Dao-Cheng; Fang, Chang; Huang, Jin-Mei; Ke, Wu-Jian; Wang, Liu-Yuan; Zeng, Wei-Ying; Zheng, He-Ping; Yang, Bin

    2016-04-15

    Little is known regarding protein responses to syphilis infection in cerebrospinal fluid (CSF) of patients presenting with neurosyphilis. Protein and antibody arrays offer a new opportunity to gain insights into global protein expression profiles in these patients. Here we obtained CSF samples from 46 syphilis patients, 25 of which diagnosed as having central nervous system involvement based on clinical and laboratory findings. The CSF samples were then analyzed using a RayBioH L-Series 507 Antibody Array system designed to simultaneously analyze 507 specific cytokines. The results indicated that 41 molecules showed higher levels in patients with neurosyphilis in comparison with patients without neural involvement. For validation by single target ELISA, we selected five of them (MIP-1a, I-TAC/CXCL11, Urokinase plasminogen activator [uPA], and Oncostatin M) because they have previously been found to be involved in central nervous system (CNS) disorders. The ELISA tests confirmed that uPA levels were significantly higher in the CSF of neurosyphilis patients (109.1±7.88pg/ml) versus patients without CNS involvement (63.86±4.53pg/ml, p<0.0001). There was also a clear correlation between CSF uPA levels and CSF protein levels (p=0.0128) as well as CSF-VDRL titers (p=0.0074) used to diagnose neurosyphilis. No significant difference between the two groups of patients, however, was found in uPA levels in the serum, suggesting specific activation of the inflammatory system in the CNS but not the periphery in neurosyphilis patients. We conclude that measurements of uPA levels in CSF may be an additional parameter for diagnosing neurosyphilis. PMID:27049560

  6. 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.

  7. “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

  8. High-throughput screening of monoclonal antibodies against plant cell wall glycans by hierarchical clustering of their carbohydrate microarray binding profiles

    PubMed Central

    Moller, Isabel; Marcus, Susan E.; Haeger, Ash; Verhertbruggen, Yves; Verhoef, Rene; Schols, Henk; Ulvskov, Peter; Mikkelsen, Jørn Dalgaard; Knox, J. Paul

    2007-01-01

    Antibody-producing hybridoma cell lines were created following immunisation with a crude extract of cell wall polymers from the plant Arabidopsis thaliana. In order to rapidly screen the specificities of individual monoclonal antibodies (mAbs), their binding to microarrays containing 50 cell wall glycans immobilized on nitrocellulose was assessed. Hierarchical clustering of microarray binding profiles from newly produced mAbs, together with the profiles for mAbs with previously defined specificities allowed the rapid assignments of mAb binding to antigen classes. mAb specificities were further investigated using subsequent immunochemical and biochemical analyses and two novel mAbs are described in detail. mAb LM13 binds to an arabinanase-sensitive pectic epitope and mAb LM14, binds to an epitope occurring on arabinogalactan-proteins. Both mAbs display novel patterns of recognition of cell walls in plant materials. PMID:17629746

  9. Differential analysis for high density tiling microarray data

    PubMed Central

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

    2007-01-01

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

  10. 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

  11. 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

    2016-01-01

    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

  12. Multiplexed fluorescent microarray for human salivary protein analysis using polymer microspheres and fiber-optic bundles.

    PubMed

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

    2013-01-01

    Herein, we describe a protocol for simultaneously measuring six proteins in saliva using a fiber-optic microsphere-based antibody array. The immuno-array technology employed combines the advantages of microsphere-based suspension array fabrication with the use of fluorescence microscopy. As described in the video protocol, commercially available 4.5 μm polymer microspheres were encoded into seven different types, differentiated by the concentration of two fluorescent dyes physically trapped inside the microspheres. The encoded microspheres containing surface carboxyl groups were modified with monoclonal capture antibodies through EDC/NHS coupling chemistry. To assemble the protein microarray, the different types of encoded and functionalized microspheres were mixed and randomly deposited in 4.5 μm microwells, which were chemically etched at the proximal end of a fiber-optic bundle. The fiber-optic bundle was used as both a carrier and for imaging the microspheres. Once assembled, the microarray was used to capture proteins in the saliva supernatant collected from the clinic. The detection was based on a sandwich immunoassay using a mixture of biotinylated detection antibodies for different analytes with a streptavidin-conjugated fluorescent probe, R-phycoerythrin. The microarray was imaged by fluorescence microscopy in three different channels, two for microsphere registration and one for the assay signal. The fluorescence micrographs were then decoded and analyzed using a homemade algorithm in MATLAB. PMID:24145242

  13. 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

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

    PubMed

    Bozinov, Daniel

    2003-12-01

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

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

    PubMed

    Polen, Tino; Wendisch, Volker F

    2004-01-01

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

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

    PubMed

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

    2006-07-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-09-01

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

  19. 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.

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

    PubMed

    Valafar, Faramarz

    2002-12-01

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

  1. SpotWhatR: a user-friendly microarray data analysis system.

    PubMed

    Koide, Tie; Salem-Izacc, Silvia M; Gomes, Suely L; Vêncio, Ricardo Z N

    2006-01-01

    SpotWhatR is a user-friendly microarray data analysis tool that runs under a widely and freely available R statistical language (http://www.r-project.org) for Windows and Linux operational systems. The aim of SpotWhatR is to help the researcher to analyze microarray data by providing basic tools for data visualization, normalization, determination of differentially expressed genes, summarization by Gene Ontology terms, and clustering analysis. SpotWhatR allows researchers who are not familiar with computational programming to choose the most suitable analysis for their microarray dataset. Along with well-known procedures used in microarray data analysis, we have introduced a stand-alone implementation of the HTself method, especially designed to find differentially expressed genes in low-replication contexts. This approach is more compatible with our local reality than the usual statistical methods. We provide several examples derived from the Blastocladiella emersonii and Xylella fastidiosa Microarray Projects. SpotWhatR is freely available at http://blasto.iq.usp.br/~tkoide/SpotWhatR, in English and Portuguese versions. In addition, the user can choose between "single experiment" and "batch processing" versions. PMID:16755501

  2. 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

  3. 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

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

    PubMed Central

    2015-01-01

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

  5. 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.

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

    PubMed Central

    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. PMID:26722428

  7. 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.

  8. Microarray analysis of bacterial diversity and distribution in aggregates from a desert agricultural soil

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The microbial community structure of inner and outer layer fractions of microaggregates from a desert agricultural soil were examined using low and high resolution methods employing PCR-DGGE and microarray analysis of 16S rRNA genes. Analysis of microbial community structures with PCR-DGGE, which d...

  9. Innovative instrumentation for microarray scanning and analysis: application for characterization of oligonucleotide duplexes behavior.

    PubMed

    Khomyakova, E B; Dreval, E V; Tran-Dang, M; Potier, M C; Soussaline, F P

    2004-05-01

    Accuracy in microarray technology requires new approaches to microarray reader development. A microarray reader system (optical scanning array or OSA reader) based on automated microscopy with large field of view, high speed 3 axis scanning at multiple narrow-band spectra of excitation light has been developed. It allows fast capture of high-resolution, multi-fluorescence images and is characterized by a linear dynamic range and sensitivity comparable to commonly used photo-multiplier tube (PMT)-based laser scanner. Controlled by high performance software, the instrument can be used for scanning and quantitative analysis of any type of dry microarray. Studies implying temperature-controlled hybridization chamber containing a microarray can also be performed. This enables the registration of kinetics and melting curves. This feature is required in a wide range of on-chip chemical and enzymatic reactions including on-chip PCR amplification. We used the OSA reader for the characterization of hybridization and melting behaviour of oligonucleotide:oligonucleotide duplexes on three-dimensional Code Link slides. PMID:15209342

  10. 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. PMID:26539568

  11. 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

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

    PubMed

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

    2014-08-01

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

  13. 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

  14. Microarray analysis of a microbe-mineral interaction.

    PubMed

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

    2010-12-01

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

  15. 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

  16. 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.

  17. Quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging method optimized for analysis of multicolor microarrays.

    PubMed

    Liu, Zhiyi; Ma, Suihua; Ji, Yanhong; Liu, Le; Hu, Zhaoxu; Guo, Jihua; Ma, Hui; He, Yonghong

    2010-09-15

    The microarray technique, which can provide parallel detection with high throughput in biomedical research, has generated considerable interest since the end of the 20th century. A number of instruments have been reported for microarray detection. In this paper, we have developed a quasi-confocal, multichannel parallel scan hyperspectral fluorescence imaging system for multicolor microarray research. Hyperspectral imaging records the entire emission spectrum for every voxel within the imaged area in contrast to recording only fluorescence intensities of filter-based scanners. When coupled with data analysis, the recorded spectral information allows for quantitative identification of the contributions of multiple, spectrally overlapping fluorescent dyes and elimination of unwanted artifacts. This system is improved with a specifically designed, high performance spectrometer which can offer a spectral resolution of 0.2 nm and operates with spatial resolutions ranging from 2 to 30 μm. We demonstrate the application of the system by reading out arrays for identification of bacteria. PMID:20718427

  18. Human Thrombin Detection Through a Sandwich Aptamer Microarray: Interaction Analysis in Solution and in Solid Phase

    PubMed Central

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

    2011-01-01

    We have developed an aptamer-based microarray for human thrombin detection exploiting two non-overlapping DNA thrombin aptamers recognizing different exosites of the target protein. The 15-mer aptamer (TBA1) binds the fibrinogen-binding site, whereas the 29-mer aptamer (TBA2) binds the heparin binding domain. Extensive analysis on the complex formation between human thrombin and modified aptamers was performed by Electrophoresis Mobility Shift Assay (EMSA), in order to verify in solution whether the chemical modifications introduced would affect aptamers/protein recognition. The validated system was then applied to the aptamer microarray, using the solid phase system devised by the solution studies. Finally, the best procedure for Sandwich Aptamer Microarray (SAM) and the specificity of the sandwich formation for the developed aptasensor for human thrombin were optimized. PMID:22163703

  19. Protein Microarrays

    NASA Astrophysics Data System (ADS)

    Ricard-Blum, S.

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

  20. 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.

  1. Fluorescence, XPS, and TOF-SIMS surface chemical state image analysis of DNA microarrays.

    PubMed

    Lee, Chi-Ying; Harbers, Gregory M; Grainger, David W; Gamble, Lara J; Castner, David G

    2007-08-01

    Performance improvements in DNA-modified surfaces required for microarray and biosensor applications rely on improved capabilities to accurately characterize the chemistry and structure of immobilized DNA molecules on micropatterned surfaces. Recent innovations in imaging X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (TOF-SIMS) now permit more detailed studies of micropatterned surfaces. We have exploited the complementary information provided by imaging XPS and imaging TOF-SIMS to detail the chemical composition, spatial distribution, and hybridization efficiency of amine-terminated single-stranded DNA (ssDNA) bound to commercial polyacrylamide-based, amine-reactive microarray slides, immobilized in both macrospot and microarray diagnostic formats. Combinations of XPS imaging and small spot analysis were used to identify micropatterned DNA spots within printed DNA arrays on slide surfaces and quantify DNA elements within individual microarray spots for determination of probe immobilization and hybridization efficiencies. This represents the first report of imaging XPS of DNA immobilization and hybridization efficiencies for arrays fabricated on commercial microarray slides. Imaging TOF-SIMS provided distinct analytical data on the lateral distribution of DNA within single array microspots before and after target hybridization. Principal component analysis (PCA) applied to TOF-SIMS imaging datasets demonstrated that the combination of these two techniques provides information not readily observable in TOF-SIMS images alone, particularly in identifying species associated with array spot nonuniformities (e.g., "halo" or "donut" effects often observed in fluorescence images). Chemically specific spot images were compared to conventional fluorescence scanned images in microarrays to provide new information on spot-to-spot DNA variations that affect current diagnostic reliability, assay variance, and sensitivity. PMID:17625851

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

    PubMed

    Bremer, Martina; Himelblau, Edward; Madlung, Andreas

    2010-01-01

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

  3. 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…

  4. 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.

  5. Single nucleotide polymorphism-based microarray analysis for the diagnosis of hydatidiform moles.

    PubMed

    Xie, Yingjun; Pei, Xiaojuan; Dong, Yu; Wu, Huiqun; Wu, Jianzhu; Shi, Huijuan; Zhuang, Xuying; Sun, Xiaofang; He, Jialing

    2016-07-01

    In clinical diagnostics, single nucleotide polymorphism (SNP)-based microarray analysis enables the detection of copy number variations (CNVs), as well as copy number neutral regions, that are absent of heterozygosity throughout the genome. The aim of the present study was to evaluate the effectiveness and sensitivity of SNP‑based microarray analysis in the diagnosis of hydatidiform mole (HM). By using whole‑genome SNP microarray analysis, villous genotypes were detected, and the ploidy of villous tissue was determined to identify HMs. A total of 66 villous tissues and two twin tissues were assessed in the present study. Among these samples, 11 were triploid, one was tetraploid, 23 were abnormal aneuploidy, three were complete genome homozygosity, and the remaining ones were normal ploidy. The most noteworthy finding of the present study was the identification of six partial HMs and three complete HMs from those samples that were not identified as being HMs on the basis of the initial diagnosis of experienced obstetricians. This study has demonstrated that the application of an SNP‑based microarray analysis was able to increase the sensitivity of diagnosis for HMs with partial and complete HMs, which makes the identification of these diseases at an early gestational age possible. PMID:27151252

  6. 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…

  7. Single nucleotide polymorphism-based microarray analysis for the diagnosis of hydatidiform moles

    PubMed Central

    XIE, YINGJUN; PEI, XIAOJUAN; DONG, YU; WU, HUIQUN; WU, JIANZHU; SHI, HUIJUAN; ZHUANG, XUYING; SUN, XIAOFANG; HE, JIALING

    2016-01-01

    In clinical diagnostics, single nucleotide polymorphism (SNP)-based microarray analysis enables the detection of copy number variations (CNVs), as well as copy number neutral regions, that are absent of heterozygosity throughout the genome. The aim of the present study was to evaluate the effectiveness and sensitivity of SNP-based microarray analysis in the diagnosis of hydatidiform mole (HM). By using whole-genome SNP microarray analysis, villous genotypes were detected, and the ploidy of villous tissue was determined to identify HMs. A total of 66 villous tissues and two twin tissues were assessed in the present study. Among these samples, 11 were triploid, one was tetraploid, 23 were abnormal aneuploidy, three were complete genome homozygosity, and the remaining ones were normal ploidy. The most noteworthy finding of the present study was the identification of six partial HMs and three complete HMs from those samples that were not identified as being HMs on the basis of the initial diagnosis of experienced obstetricians. This study has demonstrated that the application of an SNP-based microarray analysis was able to increase the sensitivity of diagnosis for HMs with partial and complete HMs, which makes the identification of these diseases at an early gestational age possible. PMID:27151252

  8. 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...

  9. 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…

  10. 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…

  11. 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

  12. The Stanford Tissue Microarray Database.

    PubMed

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

    2008-01-01

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

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

    PubMed

    Dittami, Simon M; Edvardsen, Bente

    2013-10-01

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

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

    PubMed

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

    2013-01-01

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

  15. 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.

  16. 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

  17. 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

  18. A Bayesian Approach to Pathway Analysis by Integrating Gene–Gene Functional Directions and Microarray Data

    PubMed Central

    Zhao, Yifang; Chen, Ming-Hui; Pei, Baikang; Rowe, David; Shin, Dong-Guk; Xie, Wangang; Yu, Fang; Kuo, Lynn

    2012-01-01

    Many statistical methods have been developed to screen for differentially expressed genes associated with specific phenotypes in the microarray data. However, it remains a major challenge to synthesize the observed expression patterns with abundant biological knowledge for more complete understanding of the biological functions among genes. Various methods including clustering analysis on genes, neural network, Bayesian network and pathway analysis have been developed toward this goal. In most of these procedures, the activation and inhibition relationships among genes have hardly been utilized in the modeling steps. We propose two novel Bayesian models to integrate the microarray data with the putative pathway structures obtained from the KEGG database and the directional gene–gene interactions in the medical literature. We define the symmetric Kullback–Leibler divergence of a pathway, and use it to identify the pathway(s) most supported by the microarray data. Monte Carlo Markov Chain sampling algorithm is given for posterior computation in the hierarchical model. The proposed method is shown to select the most supported pathway in an illustrative example. Finally, we apply the methodology to a real microarray data set to understand the gene expression profile of osteoblast lineage at defined stages of differentiation. We observe that our method correctly identifies the pathways that are reported to play essential roles in modulating bone mass. PMID:23482678

  19. 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

  20. Fine specificity of the antibody response to Epstein-Barr nuclear antigen-2 and other Epstein-Barr virus proteins in patients with clinically isolated syndrome: A peptide microarray-based case-control study.

    PubMed

    Schlemm, Ludwig; Giess, René Markus; Rasche, Ludwig; Pfuhl, Catherina; Wakonig, Katharina; Behrens, Janina Ruth; Scheibenbogen, Carmen; Bellmann-Strobl, Judith; Paul, Friedemann; Reimer, Ulf; Ruprecht, Klemens

    2016-08-15

    We analyzed the fine specificity of antibodies to Epstein-Barr nuclear antigen-2 (EBNA-2) and other Epstein-Barr virus (EBV) proteins in 29 patients with clinically isolated syndrome (CIS, the first clinical manifestation of multiple sclerosis [MS]) and 29 controls with a peptide microarray containing 117 overlapping peptides representing the full-length EBNA-2 protein and 71 peptides from 8 further EBV proteins. While EBV peptide antibodies were elevated in CIS, suggesting that EBV contributes to MS early during disease development, they discriminated groups only slightly better than EBNA-1 antibodies. Thus, the additional value of EBV peptide antibodies as diagnostic biomarkers for CIS appears moderate. PMID:27397076

  1. 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. PMID:23748756

  2. 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

  3. Genome-wide analysis of mRNA polysomal profiles with spotted DNA microarrays.

    PubMed

    Melamed, Daniel; Arava, Yoav

    2007-01-01

    The sedimentation of an mRNA in sucrose gradients is highly affected by its ribosomal association. Sedimentation analysis has therefore become routine for studying changes in ribosomal association of mRNAs of interest. DNA microarray technology has been combined with sedimentation analysis to characterize changes in ribosomal association for thousands of mRNAs in parallel. Such analyses revealed mRNAs that are translationally regulated and have provided new insights into the translation process. In this chapter, we describe possible experimental designs for analyzing genome-wide changes in ribosomal association, and discuss some of their advantages and disadvantages. We then provide a detailed protocol for analysis of polysomal fractions using spotted DNA microarrays. PMID:17923236

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed Central

    Chrominski, Kornel; Tkacz, Magdalena

    2015-01-01

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

  7. 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

  8. Clinical Presentation and Microarray Analysis of Peruvian Children with Atypical Development and/or Aberrant Behavior

    PubMed Central

    Butler, Merlin G.; Usrey, Kelly; Roberts, Jennifer L.; Schroeder, Stephen R.

    2014-01-01

    We report our experience with high resolution microarray analysis in infants and young children with developmental disability and/or aberrant behavior enrolled at the Centro Ann Sullivan del Peru in Lima, Peru, a low income country. Buccal cells were collected with cotton swabs from 233 participants for later DNA isolation and identification of copy number variation (deletions/duplications) and regions of homozygosity (ROH) for estimating consanguinity status in 15 infants and young children (12 males, 3 females; mean age ± SD = 28.1 m ±  7.9 m; age range 14 m–41 m) randomly selected for microarray analysis. An adequate DNA yield was found in about one-half of the enrolled participants. Ten participants showed deletions or duplications containing candidate genes reported to impact behavior or cognitive development. Five children had ROHs which could have harbored recessive gene alleles contributing to their clinical presentation. The coefficient of inbreeding was calculated and three participants showed first-second cousin relationships, indicating consanguinity. Our preliminary study showed that DNA isolated from buccal cells using cotton swabs was suboptimal, but yet in a subset of participants the yield was adequate for high resolution microarray analysis and several genes were found that impact development and behavior and ROHs identified to determine consanguinity status. PMID:25400949

  9. Comprehensive DNA Microarray Analysis of Bacillus subtilis Two-Component Regulatory Systems

    PubMed Central

    Kobayashi, Kazuo; Ogura, Mitsuo; Yamaguchi, Hirotake; Yoshida, Ken-Ichi; Ogasawara, Naotake; Tanaka, Teruo; Fujita, Yasutaro

    2001-01-01

    It has recently been shown through DNA microarray analysis of Bacillus subtilis two-component regulatory systems (DegS-DegU, ComP-ComA, and PhoR-PhoP) that overproduction of a response regulator of the two-component systems in the background of a deficiency of its cognate sensor kinase affects the regulation of genes, including its target ones. The genome-wide effect on gene expression caused by the overproduction was revealed by DNA microarray analysis. In the present work, we newly analyzed 24 two-component systems by means of this strategy, leaving out 8 systems to which it was unlikely to be applicable. This analysis revealed various target gene candidates for these two-component systems. It is especially notable that interesting interactions appeared to take place between several two-component systems. Moreover, the probable functions of some unknown two-component systems were deduced from the list of their target gene candidates. This work is heuristic but provides valuable information for further study toward a comprehensive understanding of the B. subtilis two-component regulatory systems. The DNA microarray data obtained in this work are available at the KEGG Expression Database website (http://www.genome.ad.jp/kegg/expression). PMID:11717295

  10. 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.

  11. Microarray Analysis to Monitor Bacterial Cell Wall Homeostasis.

    PubMed

    Hong, Hee-Jeon; Hesketh, Andy

    2016-01-01

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

  12. 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

  13. Parallel human genome analysis: Microarray-based expression monitoring of 1000 genes

    SciTech Connect

    Schena, M.; Heller, R.; Chai, A.; Davis, R.W.

    1996-10-01

    Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm{sup 2} DNA {open_quotes}chips{close_quotes} were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. 33 refs., 3 figs., 2 tabs.

  14. Inferring genetic networks from DNA microarray data by multiple regression analysis.

    PubMed

    Kato, M; Tsunoda, T; Takagi, T

    2000-01-01

    Inferring gene regulatory networks by differential equations from the time series data of a DNA microarray is one of the most challenging tasks in the post-genomic era. However, there have been no studies actually inferring gene regulatory networks by differential equations from genome-level data. The reason for this is that the number of parameters in the equations exceeds the number of measured time points. We here succeeded in executing the inference, not by directly determining parameters but by applying multiple regression analysis to our equations. We derived our differential equations and steady state equations from the rate equations of transcriptional reactions in an organism. Verification with a number of genes related to respiration indicated the validity and effectiveness of our method. Moreover, the steady state equations were more appropriate than the differential equations for the microarray data used. PMID:11700593

  15. Microarray analysis of neural stem cell differentiation in the striatum of the fetal rat.

    PubMed

    Wen, Tieqiao; Gu, Ping; Minning, Todd A; Wu, Qi; Liu, Min; Chen, Fuxue; Liu, Hao; Huang, Haihua

    2002-08-01

    1. Gene expression profiles in neural stem cell differentiation in vitro were determined by cDNA microarray analysis. 2. Total RNA was extracted and reverse transcripted into cDNA from differentiated and undifferentiated neural stem cells. The 33P labeled cDNA was hybridized with a cDNA microarray consisting of 14,000 human genes. 3. The results showed that a total of 1406 genes were differentially expressed, of which 148 genes exhibited more than twofold differences. Some genes were obviously activated while others were strongly repressed. These changes in gene expression suggest that differentiation is regulated by different genes at different expressional levels. By biological classification, the differentially expressed genes were divided into four functional categories: molecular function, biological process, cellular component, and new functional genes or ESTs. 4. These findings will be a valuable contribution for gene expression profiling and elucidation of neural stem cell differentiation mechanisms. PMID:12507390

  16. 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. PMID:26407868

  17. Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets.

    PubMed

    Yin, Lanlan; Coelho, Sergio G; Valencia, Julio C; Ebsen, Dominik; Mahns, Andre; Smuda, Christoph; Miller, Sharon A; Beer, Janusz Z; Kolbe, Ludger; Hearing, Vincent J

    2015-10-01

    More than 375 genes have been identified that are involved in regulating skin pigmentation and these act during development, survival, differentiation, and/or responses of melanocytes to the environment. Many of these genes have been cloned, and disruptions of their functions are associated with various pigmentary diseases; however, many remain to be identified. We have performed a series of microarray analyses of hyperpigmented compared with less pigmented skin to identify genes responsible for these differences. The rationale and goal for this study was to perform a meta-analysis on these microarray databases to identify genes that may be significantly involved in regulating skin phenotype either directly or indirectly that might not have been identified due to subtle differences by any of these individual studies alone. The meta-analysis demonstrates that 1,271 probes representing 921 genes are differentially expressed at significant levels in the 5 microarray data sets compared, providing new insights into the variety of genes involved in determining skin phenotype. Immunohistochemistry was used to validate two of these markers at the protein level (TRIM63 and QPCT), and we discuss the possible functions of these genes in regulating skin physiology. PMID:25950827

  18. 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. PMID:24253858

  19. Gene expression profile analysis in astaxanthin-induced Haematococcus pluvialis using a cDNA microarray.

    PubMed

    Eom, Hyunsuk; Lee, Choul-Gyun; Jin, EonSeon

    2006-05-01

    The unicellular green alga Haematococcus pluvialis (Volvocales) is known for the ketocarotenoid astaxanthin (3, 3'-dihydroxy-beta, beta-carotene-4, 4'-dione) accumulation, which is induced under unfavorable culture conditions. In this work, we used cDNA microarray analysis to screen differentially expressed genes in H. pluvialis under astaxanthin-inductive culture conditions, such as combination of cell exposure to high irradiance and nutrient deprivation. Among the 965 genes in the cDNA array, there are 144 genes exhibiting differential expression (twofold changes) under these conditions. A significant decrease in the expression of photosynthesis-related genes was shown in astaxanthin-accumulating cells (red cells). Defense- or stress-related genes and signal transduction genes were also induced in the red cells. A comparison of microarray and real-time PCR analysis showed good correlation between the differentially expressed genes by the two methods. Our results indicate that the cDNA microarray approach, as employed in this work, can be relied upon and used to monitor gene expression profiles in H. pluvialis. In addition, the genes that were differentially expressed during astaxanthin induction are suitable candidates for further study and can be used as tools for dissecting the molecular mechanism of this unique pigment accumulation process in the green alga H. pluvialis. PMID:16320067

  20. Identification of Genes Expressed in Hyperpigmented Skin using Meta-Analysis of Microarray Datasets

    PubMed Central

    Yin, Lanlan; Coelho, Sergio G.; Valencia, Julio C.; Ebsen, Dominik; Mahns, Andre; Smuda, Christoph; Miller, Sharon A.; Beer, Janusz Z.; Kolbe, Ludger; Hearing, Vincent J.

    2015-01-01

    More than 375 genes have been identified that are involved in regulating skin pigmentation, and those act during development, survival, differentiation and/or responses of melanocytes to the environment. Many of those genes have been cloned and disruptions of their functions are associated with various pigmentary diseases, however many remain to be identified. We have performed a series of microarray analyses of hyperpigmented compared to less pigmented skin to identify genes responsible for those differences. The rationale and goal for this study was to perform a meta-analysis on those microarray databases to identify genes that may be significantly involved in regulating skin phenotype either directly or indirectly that might not have been identified due to subtle differences by any of those individual studies alone. The meta-analysis demonstrates that 1,271 probes representing 921 genes are differentially expressed at significant levels in the 5 microarray datasets compared, which provides new insights into the variety of genes involved in determining skin phenotype. Immunohistochemistry was used to validate 2 of those markers at the protein level (TRIM63 and QPCT) and we discuss the possible functions of those genes in regulating skin physiology. PMID:25950827

  1. Transcriptional analysis of highly syntenic regions between Medicago truncatula and Glycine max using tiling microarrays

    PubMed Central

    Li, Lei; He, Hang; Zhang, Juan; Wang, Xiangfeng; Bai, Sulan; Stolc, Viktor; Tongprasit, Waraporn; Young, Nevin D; Yu, Oliver; Deng, Xing-Wang

    2008-01-01

    Background Legumes are the third largest family of flowering plants and are unique among crop species in their ability to fix atmospheric nitrogen. As a result of recent genome sequencing efforts, legumes are now one of a few plant families with extensive genomic and transcriptomic data available in multiple species. The unprecedented complexity and impending completeness of these data create opportunities for new approaches to discovery. Results We report here a transcriptional analysis in six different organ types of syntenic regions totaling approximately 1 Mb between the legume plants barrel medic (Medicago truncatula) and soybean (Glycine max) using oligonucleotide tiling microarrays. This analysis detected transcription of over 80% of the predicted genes in both species. We also identified 499 and 660 transcriptionally active regions from barrel medic and soybean, respectively, over half of which locate outside of the predicted exons. We used the tiling array data to detect differential gene expression in the six examined organ types and found several genes that are preferentially expressed in the nodule. Further investigation revealed that some collinear genes exhibit different expression patterns between the two species. Conclusion These results demonstrate the utility of genome tiling microarrays in generating transcriptomic data to complement computational annotation of the newly available legume genome sequences. The tiling microarray data was further used to quantify gene expression levels in multiple organ types of two related legume species. Further development of this method should provide a new approach to comparative genomics aimed at elucidating genome organization and transcriptional regulation. PMID:18348734

  2. 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

  3. 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. PMID:26562156

  4. Outcome-Driven Cluster Analysis with Application to Microarray Data

    PubMed Central

    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. PMID:26562156

  5. A Simple Method for Optimization of Reference Gene Identification and Normalization in DNA Microarray Analysis

    PubMed Central

    Casares, Federico M.

    2016-01-01

    Background Comparative DNA microarray analyses typically yield very large gene expression data sets that reflect complex patterns of change. Despite the wealth of information that is obtained, the identification of stable reference genes is required for normalization of disease- or drug-induced changes across tested groups. This is a prerequisite in quantitative real-time reverse transcription-PCR (qRT-PCR) and relative RT-PCR but rare in gene microarray analysis. The goal of the present study was to outline a simple method for identification of reliable reference genes derived from DNA microarray data sets by comparative statistical analysis of software-generated and manually calculated candidate genes. Material/Methods DNA microarray data sets derived from whole-blood samples obtained from 14 Zucker diabetic fatty (ZDF) rats (7 lean and 7 diabetic obese) were used for the method development. This involved the use of software-generated filtering parameters to accomplish the desired signal-to-noise ratios, 75th percentile signal manual normalizations, and the selection of reference genes as endogenous controls for target gene expression normalization. Results The combination of software-generated and manual normalization methods yielded a group of 5 stably expressed, suitable endogenous control genes which can be used in further target gene expression determinations in whole blood of ZDF rats. Conclusions This method can be used to correct for potentially false results and aid in the selection of suitable endogenous control genes. It is especially useful when aimed to aid the software in cases of borderline results, where the expression and/or the fold change values are just beyond the pre-established set of acceptable parameters. PMID:27122237

  6. Rapid O serogroup identification of the six clinically relevant Shiga toxin-producing Escherichia coli by antibody microarray

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Prognostic Significance of CREB-Binding Protein and CD81 Expression in Primary High Grade Non-Muscle Invasive Bladder Cancer: Identification of Novel Biomarkers for Bladder Cancer Using Antibody Microarray.

    PubMed

    Lee, Myung-Shin; Kim, Joo Heon; Lee, Ji-Su; Yun, Seok Joong; Kim, Wun-Jae; Ahn, Hanjong; Park, Jinsung

    2015-01-01

    High-grade (HG) bladder cancers (BCs) are genetically unstable and have an unpredictable course. The identification of prognostic factors in HG non-muscle invasive BC (NMIBC) is crucial for improving patients' quality of life and preventing BC-specific mortality. Here, we used an antibody microarray (AbM) to identify novel candidate biomarkers in primary HG NMIBC and validated the prognostic significance of the candidate biomarkers. Three pairs of tissue samples from primary HG NMIBC and normal urothelium were analyzed using an AbM kit containing 656 antibodies, and differentially expressed proteins were identified. Among the 42 upregulated and 14 downregulated proteins with statistical significance in BC tissues, CREB-binding protein and CD81 were selected as representative upregulated and downregulated candidate biomarkers, respectively. We then validated the expression of these candidate biomarkers in primary human urothelial cells and BC cell lines by western blotting and immunofluorescence assays, and the results were consistent with the AbM expression profiles. Additionally, Kaplan-Meier survival using immunohistochemical data from an independent primary HG NMIBC cohort comprising 113 patients showed that expression of the 2 biomarkers was significantly associated with recurrence-free and progression-free survival. In multivariate analysis, the 2 biomarkers remained significant predictors for recurrence-free survival. Taken together, our findings suggest that expression of CREB-binding protein and CD81 in BC tissue specimens may have prognostic value in patients with primary HG NMIBC. PMID:25915404

  8. The antibody mining toolbox: an open source tool for the rapid analysis of antibody repertoires.

    PubMed

    D'Angelo, Sara; Glanville, Jacob; Ferrara, Fortunato; Naranjo, Leslie; Gleasner, Cheryl D; Shen, Xiaohong; Bradbury, Andrew R M; Kiss, Csaba

    2014-01-01

    In vitro selection has been an essential tool in the development of recombinant antibodies against various antigen targets. Deep sequencing has recently been gaining ground as an alternative and valuable method to analyze such antibody selections. The analysis provides a novel and extremely detailed view of selected antibody populations, and allows the identification of specific antibodies using only sequencing data, potentially eliminating the need for expensive and laborious low-throughput screening methods such as enzyme-linked immunosorbant assay. The high cost and the need for bioinformatics experts and powerful computer clusters, however, have limited the general use of deep sequencing in antibody selections. Here, we describe the AbMining ToolBox, an open source software package for the straightforward analysis of antibody libraries sequenced by the three main next generation sequencing platforms (454, Ion Torrent, MiSeq). The ToolBox is able to identify heavy chain CDR3s as effectively as more computationally intense software, and can be easily adapted to analyze other portions of antibody variable genes, as well as the selection outputs of libraries based on different scaffolds. The software runs on all common operating systems (Microsoft Windows, Mac OS X, Linux), on standard personal computers, and sequence analysis of 1-2 million reads can be accomplished in 10-15 min, a fraction of the time of competing software. Use of the ToolBox will allow the average researcher to incorporate deep sequence analysis into routine selections from antibody display libraries. PMID:24423623

  9. ZODET: Software for the Identification, Analysis and Visualisation of Outlier Genes in Microarray Expression Data

    PubMed Central

    Roden, Daniel L.; Sewell, Gavin W.; Lobley, Anna; Levine, Adam P.; Smith, Andrew M.; Segal, Anthony W.

    2014-01-01

    Summary Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET)) that enables identification and visualisation of gross abnormalities in gene expression (outliers) in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI), using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java. Availability The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis. PMID:24416128

  10. Stability of gene contributions and identification of outliers in multivariate analysis of microarray data

    PubMed Central

    Baty, Florent; Jaeger, Daniel; Preiswerk, Frank; Schumacher, Martin M; Brutsche, Martin H

    2008-01-01

    Background Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. Results In this study, we developed a computationally efficient algorithm for: i) the assessment of the significance of gene contributions and ii) the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples. Conclusion The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data. PMID:18570644

  11. Krylov subspace algorithms for computing GeneRank for the analysis of microarray data mining.

    PubMed

    Wu, Gang; Zhang, Ying; Wei, Yimin

    2010-04-01

    GeneRank is a new engine technology for the analysis of microarray experiments. It combines gene expression information with a network structure derived from gene notations or expression profile correlations. Using matrix decomposition techniques, we first give a matrix analysis of the GeneRank model. We reformulate the GeneRank vector as a linear combination of three parts in the general case when the matrix in question is non-diagonalizable. We then propose two Krylov subspace methods for computing GeneRank. Numerical experiments show that, when the GeneRank problem is very large, the new algorithms are appropriate choices. PMID:20426695

  12. PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.

    PubMed

    Trost, Brett; Kindrachuk, Jason; Määttänen, Pekka; Napper, Scott; Kusalik, Anthony

    2013-01-01

    Kinome microarrays are comprised of peptides that act as phosphorylation targets for protein kinases. This platform is growing in popularity due to its ability to measure phosphorylation-mediated cellular signaling in a high-throughput manner. While software for analyzing data from DNA microarrays has also been used for kinome arrays, differences between the two technologies and associated biologies previously led us to develop Platform for Intelligent, Integrated Kinome Analysis (PIIKA), a software tool customized for the analysis of data from kinome arrays. Here, we report the development of PIIKA 2, a significantly improved version with new features and improvements in the areas of clustering, statistical analysis, and data visualization. Among other additions to the original PIIKA, PIIKA 2 now allows the user to: evaluate statistically how well groups of samples cluster together; identify sets of peptides that have consistent phosphorylation patterns among groups of samples; perform hierarchical clustering analysis with bootstrapping; view false negative probabilities and positive and negative predictive values for t-tests between pairs of samples; easily assess experimental reproducibility; and visualize the data using volcano plots, scatterplots, and interactive three-dimensional principal component analyses. Also new in PIIKA 2 is a web-based interface, which allows users unfamiliar with command-line tools to easily provide input and download the results. Collectively, the additions and improvements described here enhance both the breadth and depth of analyses available, simplify the user interface, and make the software an even more valuable tool for the analysis of kinome microarray data. Both the web-based and stand-alone versions of PIIKA 2 can be accessed via http://saphire.usask.ca. PMID:24312246

  13. 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

  14. 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

  15. Comprehensive literature review and statistical considerations for microarray meta-analysis

    PubMed Central

    Tseng, George C.; Ghosh, Debashis; Feingold, Eleanor

    2012-01-01

    With the rapid advances of various high-throughput technologies, generation of ‘-omics’ data is commonplace in almost every biomedical field. Effective data management and analytical approaches are essential to fully decipher the biological knowledge contained in the tremendous amount of experimental data. Meta-analysis, a set of statistical tools for combining multiple studies of a related hypothesis, has become popular in genomic research. Here, we perform a systematic search from PubMed and manual collection to obtain 620 genomic meta-analysis papers, of which 333 microarray meta-analysis papers are summarized as the basis of this paper and the other 249 GWAS meta-analysis papers are discussed in the next companion paper. The review in the present paper focuses on various biological purposes of microarray meta-analysis, databases and software and related statistical procedures. Statistical considerations of such an analysis are further scrutinized and illustrated by a case study. Finally, several open questions are listed and discussed. PMID:22262733

  16. Microarrays in hematology.

    PubMed

    Walker, Josef; Flower, Darren; Rigley, Kevin

    2002-01-01

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

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

    PubMed

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

    2016-04-01

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

  18. 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.

  19. 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 ...

  20. 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.

  1. Analysis of hypertrophic and normal scar gene expression with cDNA microarrays.

    PubMed

    Tsou, R; Cole, J K; Nathens, A B; Isik, F F; Heimbach, D M; Engrav, L H; Gibran, N S

    2000-01-01

    Hypertrophic scar is one form of abnormal wound healing. Previous studies have suggested that hypertrophic scar formation results from altered gene expression of extracellular matrix molecules. A broadscale evaluation of gene expression in hypertrophic scars has not been reported. To better understand abnormalities in hypertrophic scar gene expression, we compared messenger RNA expression in hypertrophic scars, normal scars, and uninjured skin with the use of complementary (c)DNA microarrays. Total RNA was extracted from freshly excised human hypertrophic scars, normal scars, or uninjured skin and reverse transcribed into cDNA with the incorporation of [33P] deoxycytidine triphosphate. The resulting radioactive cDNA probes were hybridized onto cDNA microarrays of 4000 genes. Hybridization signals were normalized and analyzed. In the comparison of tissue samples, mean intensities were calculated for each gene within each group (hypertrophic scars, normal scars, and uninjured skin). Ratios of the mean intensities of hypertrophic scars to normal scars, hypertrophic scars to uninjured skin, and normal scars to uninjured skin were generated. A ratio that was greater than 1 indicated upregulation of any particular gene and a ratio that was less than 1 indicated downregulation of any particular gene. Our data indicated that 142 genes were overexpressed and 50 genes were underexpressed in normal scars compared with uninjured skin, 107 genes were overexpressed and 71 were underexpressed in hypertrophic scars compared with uninjured skin, and 44 genes were overexpressed and 124 were underexpressed in hypertrophic scars compared with normal scars. Our analysis of collagen, growth factor, and metalloproteinase gene expression confirmed that our molecular data were consistent with published biochemical and clinical observations of normal scars and hypertrophic scars. cDNA microarray analysis provides a powerful tool for the investigation of differential gene expression in

  2. Comprehensive Analysis of Prokaryotes in Environmental Water Using DNA Microarray Analysis and Whole Genome Amplification

    PubMed Central

    Akama, Takeshi; Kawashima, Akira; Tanigawa, Kazunari; Hayashi, Moyuru; Ishido, Yuko; Luo, Yuqian; Hata, Akihisa; Fujitani, Noboru; Ishii, Norihisa; Suzuki, Koichi

    2013-01-01

    The microflora in environmental water consists of a high density and diversity of bacterial species that form the foundation of the water ecosystem. Because the majority of these species cannot be cultured in vitro, a different approach is needed to identify prokaryotes in environmental water. A novel DNA microarray was developed as a simplified detection protocol. Multiple DNA probes were designed against each of the 97,927 sequences in the DNA Data Bank of Japan and mounted on a glass chip in duplicate. Evaluation of the microarray was performed using the DNA extracted from one liter of environmental water samples collected from seven sites in Japan. The extracted DNA was uniformly amplified using whole genome amplification (WGA), labeled with Cy3-conjugated 16S rRNA specific primers and hybridized to the microarray. The microarray successfully identified soil bacteria and environment-specific bacteria clusters. The DNA microarray described herein can be a useful tool in evaluating the diversity of prokaryotes and assessing environmental changes such as global warming. PMID:25437334

  3. 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

  4. A new 12-gene diagnostic biomarker signature of melanoma revealed by integrated microarray analysis

    PubMed Central

    Liu, Wanting

    2013-01-01

    Genome-wide microarray technology has facilitated the systematic discovery of diagnostic biomarkers of cancers and other pathologies. However, meta-analyses of published arrays often uncover significant inconsistencies that hinder advances in clinical practice. Here we present an integrated microarray analysis framework, based on a genome-wide relative significance (GWRS) and genome-wide global significance (GWGS) model. When applied to five microarray datasets on melanoma published between 2000 and 2011, this method revealed a new signature of 200 genes. When these were linked to so-called ‘melanoma driver’ genes involved in MAPK, Ca2+, and WNT signaling pathways we were able to produce a new 12-gene diagnostic biomarker signature for melanoma (i.e., EGFR, FGFR2, FGFR3, IL8, PTPRF, TNC, CXCL13, COL11A1, CHP2, SHC4, PPP2R2C, and WNT4). We have begun to experimentally validate a subset of these genes involved in MAPK signaling at the protein level, including CXCL13, COL11A1, PTPRF and SHC4 and found these to be over-expressed in metastatic and primary melanoma cells in vitro and in situ compared to melanocytes cultured from healthy skin epidermis and normal healthy human skin. While SHC4 has been reported previously to be associated to melanoma, this is the first time CXCL13, COL11A1, and PTPRF have been associated with melanoma on experimental validation. Our computational evaluation indicates that this 12-gene biomarker signature achieves excellent diagnostic power in distinguishing metastatic melanoma from normal skin and benign nevus. Further experimental validation of the role of these 12 genes in a new signaling network may provide new insights into the underlying biological mechanisms driving the progression of melanoma. PMID:23638386

  5. Microarray analysis of differential gene expression in sensitive and resistant pig to Escherichia coli F18.

    PubMed

    Bao, W B; Ye, L; Pan, Z Y; Zhu, J; Du, Z D; Zhu, G Q; Huang, X G; Wu, S L

    2012-10-01

    In this study, Agilent two-colour microarray-based gene expression profiling was used to detect differential gene expression in duodenal tissues collected from eight full-sib pairs of Sutai pigs differing in adhesion phenotype (sensitivity and resistance to Escherichia coli F18). Using a two-fold change minimum threshold, we found 18 genes that were differentially expressed (10 up-regulated and eight down-regulated) between the sensitive and resistant animal groups. Our gene ontology analysis revealed that these differentially expressed genes are involved in a variety of biological processes, including immune responses, extracellular modification (e.g. glycosylation), cell adhesion and signal transduction, all of which are related to the anabolic metabolism of glycolipids, as well as to inflammation- and immune-related pathways. Based on the genes identified in the screen and the pathway analysis results, real-time PCR was used to test the involvement of ST3GAL1 and A genes (of glycolipid-related pathways), SLA-1 and SLA-3 genes (of inflammation- and immune-related pathways), as well as the differential genes FUT1, TAP1 and SLA-DQA. Subsequently, real-time PCR was performed to validate seven differentially expressed genes screened out by the microarray approach, and sufficient consistency was observed between the two methods. The results support the conclusion that these genes are related to the E. coli F18 receptor and susceptibility to E. coli F18. PMID:22497274

  6. 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

  7. 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.

  8. Phylogenetic microarray analysis of a microbial community performing reductive dechlorination at a TCE-contaminated site.

    PubMed

    Lee, Patrick K H; Warnecke, F; Brodie, Eoin L; Macbeth, Tamzen W; Conrad, Mark E; Andersen, Gary L; Alvarez-Cohen, Lisa

    2012-01-17

    A high-density phylogenetic microarray (PhyloChip) was applied to track bacterial and archaeal populations through different phases of remediation at Ft. Lewis, WA, a trichloroethene (TCE)-contaminated groundwater site. Biostimulation with whey, and bioaugmentation with a Dehalococcoides-containing enrichment culture were strategies implemented to enhance dechlorination. As a measure of species richness, over 1300 operational taxonomic units (OTUs) were detected in DNA from groundwater samples extracted during different stages of treatment and in the bioaugmentation culture. In order to determine active members within the community, 16S rRNA from samples were analyzed by microarray and ∼600 OTUs identified. A cDNA clone library of the expressed 16S rRNA corroborated the observed diversity and activity of some of the phyla. Principle component analysis of the treatment plot samples revealed that the microbial populations were constantly changing during the course of the study. Dynamic analysis of the archaeal population showed significant increases in methanogens at the later stages of treatment that correlated with increases in methane concentrations of over 2 orders of magnitude. Overall, the PhyloChip analyses in this study have provided insights into the microbial ecology and population dynamics at the TCE-contaminated field site useful for understanding the in situ reductive dechlorination processes. PMID:22091783

  9. Phylogenetic Microarray Analysis of a Microbial Community Performing Reductive Dechlorination at a TCE-contaminated Site

    PubMed Central

    Lee, Patrick K. H.; Warnecke, F.; Brodie, Eoin L.; Macbeth, Tamzen W.; Conrad, Mark E.; Andersen, Gary L.; Alvarez-Cohen, Lisa

    2012-01-01

    A high-density phylogenetic microarray (PhyloChip) was applied to track bacterial and archaeal populations through different phases of remediation at Ft. Lewis, WA, a trichloroethene (TCE)-contaminated groundwater site. Biostimulation with whey, and bioaugmentation with a Dehalococcoides-containing enrichment culture were strategies implemented to enhance dechlorination. As a measure of species richness, over 1300 operational taxonomic units (OTUs) were detected in DNA from groundwater samples extracted during different stages of treatment and in the bioaugmentation culture. In order to determine active members within the community, 16S rRNA from samples were analyzed by microarray and ~600 OTUs identified. A cDNA clone library of the expressed 16S rRNA corroborated the observed diversity and activity of some of the phyla. Principle component analysis of the treatment plot samples revealed that the microbial populations were constantly changing during the course of the study. Dynamic analysis of the archaeal population showed significant increases in methanogens at the later stages of treatment that correlated with increases in methane concentrations of over two orders of magnitude. Overall, the PhyloChip analyses in this study have provided insights into the microbial ecology and population dynamics at the TCE-contaminated field site useful for understanding the in situ reductive dechlorination processes. PMID:22091783

  10. [Advances of microarray analysis on plant gene expression under environmental stresses].

    PubMed

    Lin, Hai-Jian; Zhang, Zhi-Ming; Shen, Ya-Ou; Gao, Shi-Bin; Pan, Guang-Tang

    2009-12-01

    Different stressed conditions impair plant growth and further, cause great loss of crop yield and even lead to lose production completely. Increasing resistance/tolerance of crops under stressed conditions is a major goal of numerous plant breeders, and many elegant works are focusing on this area to uncover these complicated mechanisms underlying it. However, the traditional strategies including physiological and biochemical methods, as well as studies on a few genes, can not well understand the overall biological mechanism. Microarray analysis opens a door to uncover these cryptic mechanisms, and has the ability of detecting gene transcription and regulation at genomic level in different plant tissues. And works in association with related methods of proteomics and metabolomics. Therefore, it is possible to locate genes in certain key metabolism pathways. Through these procedures, it is also possible to look for critical genes in the pathway and to well understand the molecular mechanism of resistance/tolerance. These results can be as a guidance for increasing the resistance/tolerance of stressed conditions using biotechnology methods in future. This paper mainly focused on and discussed the advances of microarray analysis of stressed conditions-related genes in plants. PMID:20042386

  11. [Differential gene expression analysis by DNA microarrays technology and its application in molecular oncology].

    PubMed

    Frolov, A E; Godwin, A K; Favorova, O O

    2003-01-01

    Accumulation of genetic and epigenetic aberrations leads to malignant transformation of normal cells. Functional studies of cancer using genomic and proteomic tools will help to reveal the true complexity of the processes leading to cancer development in humans. Until recently, diagnosis and prognosis of cancer was based on conventional pathologic criteria and epidemiological evidence. Certain tumors were divided only into relatively broad histological and morphological subcategories. Rapidly developing methods of differential gene expression analysis promote the search for clinically relevant genes changing their expression levels during malignant transformation. DNA microarrays offer a unique possibility to rapidly assess the global expression picture of thousands genes in any given time point and compare the detailed combinatory analysis results of global expression profiles for normal and malignant cells at various functional stages or separate experimental conditions. Acquisition of such "genetic portraits" allows searching for regularity and difference in expression patterns of certain genes, understanding their function and pathological importance, and ultimately developing the "molecular nosology" of cancer. This review describes the basis of DNA microarray technology and methodology, and focuses on their applications in molecular classification of tumors, drug sensitivity and resistance studies, and identification of biological markers of cancer. PMID:12942629

  12. Development of antibody arrays for monoclonal antibody Higher Order Structure analysis

    PubMed Central

    Wang, Xing; Li, Qing; Davies, Michael

    2013-01-01

    Antibody arrays were developed to probe a monoclonal antibody's three-dimensional structure (3-D structure). Peptides with overlapping regions were designed to cover the whole mAb light chain and heavy chain, respectively, and used to generate polyclonal antibodies after the conjugation of the peptides to a carrier protein, KLH. It was shown that good peptide specificity was achieved from the antibodies generated. Using more than 30 different polyclonal antibodies to measure the surface epitope distribution, it was shown that the mAb antibody array can detect epitope exposure as low as 0.1% of defined mAb populations. This ELISA-based analysis of mAb epitope exposure can be considered as a measurement of “conformational impurity” in biologics development, similar to the analysis of other product-related impurities such as different forms of glycosylation, deamidation, and oxidation. This analysis of “conformational impurity” could provide valuable information on the mAb conformational comparability for biosimilar mAbs as well as novel mAbs, especially in the area of protein immunogenicity. Furthermore, stability studies indicated that there are several conformational “hot spots” in many mAbs tested, especially in the hinge region. This antibody array technology can be used for novel mAb Higher Order Structure (HOS) analysis during process and formulation development. Another important area of application is for biosimilar mAb development where the innovator molecule and biosimilar molecule could be compared based on their systemic “fingerprint” from the 30 plus antibodies. PMID:23970865

  13. 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

  14. Microarray data analysis of neuroblastoma: Expression of SOX2 downregulates the expression of MYCN.

    PubMed

    Bao, Juntao; Qin, Luying; Cui, Lingling; Wang, Xiaohui; Meng, Qinglei; Zhu, Linchao; Zhang, Shufeng

    2015-11-01

    The present study aimed to identify the genes directly or indirectly correlated with the amplification of MYCN in neuroblastoma (NB). Microarray data (GSE53371) were downloaded from Gene Expression Omnibus, and included 10 NB cell lines with MYCN amplification and 10 NB cell lines with normal MYCN copy numbers. Differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Data package, and a false discovery rate of <0.05 and |log2FC (fold change)|>1 were selected as cut‑off criteria. Hierarchical clustering analysis and Gene Ontology analysis were respectively performed for the DEGs using the Pheatmap package in R language and The Database for Annotation, Visualization and Integrated Discovery. A protein‑protein interaction network (PPI) was constructed for the DEGs using the Search Tool for the Retrieval of Interacting Genes database. Pathway analysis was performed for the DEGs in the PPI network using the WEB‑based GEne SeT AnaLysis Toolkit. The correlation between MYCN and the key gene associated with MYCN was determined using Pearson's correlation coefficient. In total, 137 downregulated and 35 upregulated DEGs were identified. Functional enrichment analysis indicated that KCNMB4 was involved in the regulation of action potential in neuron term, and the FOS, GLI3 and GLI1 genes were involved in the extracellular matrix‑receptor interaction pathway. The PPI network and correlation analysis revealed that the expression of SOX2 was directly correlated with the expression of MYCN, and the correlation coefficient of SOX2 and MYCN was ‑0.83. Therefore, SOX2, KCNMB4, FOS, GLI3 and GLI1 may be involved in the pathogenesis of NB, with the expression of SOX2 downregulating the expression of MYCN. PMID:26398570

  15. Deep sequencing and human antibody repertoire analysis.

    PubMed

    Boyd, Scott D; Crowe, James E

    2016-06-01

    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

  16. Microarray-Based Comparative Genomic and Transcriptome Analysis of Borrelia burgdorferi.

    PubMed

    Iyer, Radha; Schwartz, Ira

    2016-01-01

    Borrelia burgdorferi, the spirochetal agent of Lyme disease, is maintained in nature in a cycle involving a tick vector and a mammalian host. Adaptation to the diverse conditions of temperature, pH, oxygen tension and nutrient availability in these two environments requires the precise orchestration of gene expression. Over 25 microarray analyses relating to B. burgdorferi genomics and transcriptomics have been published. The majority of these studies has explored the global transcriptome under a variety of conditions and has contributed substantially to the current understanding of B. burgdorferi transcriptional regulation. In this review, we present a summary of these studies with particular focus on those that helped define the roles of transcriptional regulators in modulating gene expression in the tick and mammalian milieus. By performing comparative analysis of results derived from the published microarray expression profiling studies, we identified composite gene lists comprising differentially expressed genes in these two environments. Further, we explored the overlap between the regulatory circuits that function during the tick and mammalian phases of the enzootic cycle. Taken together, the data indicate that there is interplay among the distinct signaling pathways that function in feeding ticks and during adaptation to growth in the mammal. PMID:27600075

  17. Testing for mean and correlation changes in microarray experiments: an application for pathway analysis

    PubMed Central

    2010-01-01

    Background Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the response of genes within specific pathways. Pathways are comprised of genes that interact to carry out a particular biological function. Existing methods for analyzing pathways focus on detecting changes in the mean or over-representation of the number of differentially expressed genes relative to the total of genes within the pathway. The issue of how to incorporate the influence of correlation among the genes is not generally addressed. Results In this paper, we propose a non-parametric rank test for analyzing pathways that takes into account the correlation among the genes and compared two existing methods, Global and Gene Set Enrichment Analysis (GSEA), using two publicly available data sets. A simulation study was conducted to demonstrate the advantage of the rank test method. Conclusions The data indicate the advantages of the rank test. The method can distinguish significant changes in pathways due to either correlations or changes in the mean or both. From the simulation study the rank test out performed Global and GSEA. The greatest gain in performance was for the sample size case which makes the application of the rank test ideal for microarray experiments. PMID:20109181

  18. Microarray Analysis Identifies COMP as the Most Differentially Regulated Transcript Throughout In Vitro Follicle Growth

    PubMed Central

    Skory, Robin M.; Bernabé, Beatriz Peñalver; Galdones, Eugene; Broadbelt, Linda J.; Shea, Lonnie D.; Woodruff, Teresa K.

    2013-01-01

    Summary In vitro follicle growth has emerged as a technology that can provide new information about folliculogenesis and serve as part of a suite of methods currently under development to assist women whose fertility is threatened by cancer treatments. Though it has been shown that in vitro-grown follicles secrete peptide and steroid hormones, much of the follicular transcriptome remains unknown. Thus, microarray analysis was performed to characterize the transcriptome and secretome of in vitro-grown follicles. One prominently regulated gene product was cartilage oligomeric matrix protein (Comp): its mRNA was upregulated during the final 4 days of culture (P < 0.05) and COMP protein could be detected in medium from individual follicles. COMP expression localized to mural granulosa cells of large antral follicles both in vitro and in vivo, with maximal expression immediately preceding ovulation in cycling and chorionic gonadotropin-primed female mice. COMP was co-expressed with two known markers of follicle maturation, inhibin βA and gremlin, and was expressed only in TUNEL-negative follicles. In addition to other gene products identified in the microarray, COMP has potential utility as a marker of follicle maturation. PMID:23242557

  19. 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

  20. Microarray and Co-expression Network Analysis of Genes Associated with Acute Doxorubicin Cardiomyopathy in Mice.

    PubMed

    Wei, Sheng-Nan; Zhao, Wen-Jie; Zeng, Xiang-Jun; Kang, Yu-Ming; Du, Jie; Li, Hui-Hua

    2015-10-01

    Clinical use of doxorubicin (DOX) in cancer therapy is limited by its dose-dependent cardiotoxicity. But molecular mechanisms underlying this phenomenon have not been well defined. This study was to investigate the effect of DOX on the changes of global genomics in hearts. Acute cardiotoxicity was induced by giving C57BL/6J mice a single intraperitoneal injection of DOX (15 mg/kg). Cardiac function and apoptosis were monitored using echocardiography and TUNEL assay at days 1, 3 and 5. Myocardial glucose and ATP levels were measured. Microarray assays were used to screen gene expression profiles in the hearts at day 5, and the results were confirmed with qPCR analysis. DOX administration caused decreased cardiac function, increased cardiomyocyte apoptosis and decreased glucose and ATP levels. Microarrays showed 747 up-regulated genes and 438 down-regulated genes involved in seven main functional categories. Among them, metabolic pathway was the most affected by DOX. Several key genes, including 2,3-bisphosphoglycerate mutase (Bpgm), hexokinase 2, pyruvate dehydrogenase kinase, isoenzyme 4 and fructose-2,6-bisphosphate 2-phosphatase, are closely related to glucose metabolism. Gene co-expression networks suggested the core role of Bpgm in DOX cardiomyopathy. These results obtained in mice were further confirmed in cultured cardiomyocytes. In conclusion, genes involved in glucose metabolism, especially Bpgm, may play a central role in the pathogenesis of DOX-induced cardiotoxicity. PMID:25575753

  1. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis.

    PubMed

    Wei, Hengxi; Liu, Xiangjie; Yuan, Jihong; Li, Li; Zhang, Dongdong; Guo, Xinzheng; Liu, Lin; Zhang, Shouquan

    2015-01-01

    The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated) and 84 (downregulated) genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates. PMID:26421297

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

    PubMed Central

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

    2013-01-01

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

  3. Age-Specific Gene Expression Profiles of Rhesus Monkey Ovaries Detected by Microarray Analysis

    PubMed Central

    Wei, Hengxi; Liu, Xiangjie; Yuan, Jihong; Li, Li; Zhang, Dongdong; Guo, Xinzheng; Liu, Lin; Zhang, Shouquan

    2015-01-01

    The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated) and 84 (downregulated) genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates. PMID:26421297

  4. High-throughput isotopic analysis of RNA microarrays to quantify microbial resource use

    PubMed Central

    Mayali, Xavier; Weber, Peter K; Brodie, Eoin L; Mabery, Shalini; Hoeprich, Paul D; Pett-Ridge, Jennifer

    2012-01-01

    Most microorganisms remain uncultivated, and typically their ecological roles must be inferred from diversity and genomic studies. To directly measure functional roles of uncultivated microbes, we developed Chip-stable isotope probing (SIP), a high-sensitivity, high-throughput SIP method performed on a phylogenetic microarray (chip). This approach consists of microbial community incubations with isotopically labeled substrates, hybridization of the extracted community rRNA to a microarray and measurement of isotope incorporation—and therefore substrate use—by secondary ion mass spectrometer imaging (NanoSIMS). Laboratory experiments demonstrated that Chip-SIP can detect isotopic enrichment of 0.5 atom % 13C and 0.1 atom % 15N, thus permitting experiments with short incubation times and low substrate concentrations. We applied Chip-SIP analysis to a natural estuarine community and quantified amino acid, nucleic acid or fatty acid incorporation by 81 distinct microbial taxa, thus demonstrating that resource partitioning occurs with relatively simple organic substrates. The Chip-SIP approach expands the repertoire of stable isotope-enabled methods available to microbial ecologists and provides a means to test genomics-generated hypotheses about biogeochemical function in any natural environment. PMID:22158395

  5. 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.

  6. Glycosylation and post-translational modification gene expression analysis by DNA microarrays for cultured mammalian cells

    PubMed Central

    Brodsky, Arthur Nathan; Caldwell, Mary; Harcum, Sarah W.

    2011-01-01

    DNA microarray analysis of gene expression has become a valuable tool for bioprocessing research aimed at improving therapeutic protein yields. The highly parallel nature of DNA microarray technology allows researchers to assess hundreds of gene simultaneously, essentially enabling genome-wide snapshots. The quality and amount of therapeutic proteins produced by cultured mammalian cells rely heavily on the culture environment. In order to implement beneficial changes to the culture environment, a better understanding of the relationship between the product quality and culture environment must be developed. By analyzing gene expression levels under various environmental conditions, light can be shed on the underlying mechanisms. This paper describes a method for evaluating gene expression changes for cultured NS0 cells, a mouse-derived myeloma cell line, under culture environment conditions, such as ammonia buildup, known to affect product quality. These procedures can be easily adapted to other environmental conditions and any mammalian cell lines cultured in suspension, so long as a sufficient number of gene sequences are publicly available. PMID:22033470

  7. Microarray-Based Comparative Genomic and Transcriptome Analysis of Borrelia burgdorferi

    PubMed Central

    Iyer, Radha; Schwartz, Ira

    2016-01-01

    Borrelia burgdorferi, the spirochetal agent of Lyme disease, is maintained in nature in a cycle involving a tick vector and a mammalian host. Adaptation to the diverse conditions of temperature, pH, oxygen tension and nutrient availability in these two environments requires the precise orchestration of gene expression. Over 25 microarray analyses relating to B. burgdorferi genomics and transcriptomics have been published. The majority of these studies has explored the global transcriptome under a variety of conditions and has contributed substantially to the current understanding of B. burgdorferi transcriptional regulation. In this review, we present a summary of these studies with particular focus on those that helped define the roles of transcriptional regulators in modulating gene expression in the tick and mammalian milieus. By performing comparative analysis of results derived from the published microarray expression profiling studies, we identified composite gene lists comprising differentially expressed genes in these two environments. Further, we explored the overlap between the regulatory circuits that function during the tick and mammalian phases of the enzootic cycle. Taken together, the data indicate that there is interplay among the distinct signaling pathways that function in feeding ticks and during adaptation to growth in the mammal. PMID:27600075

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

    PubMed

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

    2015-01-01

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

  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