Scanning microarray slides.

PubMed

Ares, Manuel

2014-02-01

Here we describe some practical concerns surrounding the scanning of microarray slides that have been hybridized with fluorescent dyes. We use a laser scanner that has two lasers, each set to excite a different fluor, and separate detectors to capture emission from each fluor. The laser passes over an address (position on the scanned surface) and the detectors capture photons emitted from each address. Two superimposed image files are written that carry intensities for each channel for each pixel of the image scan. These are the raw data. Image analysis software is used to identify and summarize the intensities of the pixels that make up each spot. After comparison to background pixels, the processed intensity levels representing the gene expression measurements are associated with the identity of each spot.

Bioinformatic tools for inferring functional information from plant microarray data: tools for the first steps.

PubMed

Page, Grier P; Coulibaly, Issa

2008-01-01

Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).

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

PubMed

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

2004-08-01

We have developed programs to facilitate analysis of microarray data in Escherichia coli. They fall into two categories: manipulation of microarray images and identification of known biological relationships among lists of genes. A program in the first category arranges spots from glass-slide DNA microarrays according to their position in the E. coli genome and displays them compactly in genome order. The resulting genome image is presented in a web browser with an image map that allows the user to identify genes in the reordered image. Another program in the first category aligns genome images from two or more experiments. These images assist in visualizing regions of the genome with common transcriptional control. Such regions include multigene operons and clusters of operons, which are easily identified as strings of adjacent, similarly colored spots. The images are also useful for assessing the overall quality of experiments. The second category of programs includes a database and a number of tools for displaying biological information about many E. coli genes simultaneously rather than one gene at a time, which facilitates identifying relationships among them. These programs have accelerated and enhanced our interpretation of results from E. coli DNA microarray experiments. Examples are given. Copyright 2004 Genetics Society of America

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

PubMed

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

2009-06-01

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

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

PubMed

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

2009-10-27

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

On-Chip Synthesis of Protein Microarrays from DNA Microarrays Via Coupled In Vitro Transcription and Translation for Surface Plasmon Resonance Imaging Biosensor Applications

PubMed Central

Seefeld, Ting H.; Halpern, Aaron R.; Corn, Robert M.

2012-01-01

Protein microarrays are fabricated from double-stranded DNA (dsDNA) microarrays by a one-step, multiplexed enzymatic synthesis in an on-chip microfluidic format and then employed for antibody biosensing measurements with surface plasmon resonance imaging (SPRI). A microarray of dsDNA elements (denoted as generator elements) that encode either a His-tagged green fluorescent protein (GFP) or a His-tagged luciferase protein is utilized to create multiple copies of messenger RNA (mRNA) in a surface RNA polymerase reaction; the mRNA transcripts are then translated into proteins by cell-free protein synthesis in a microfluidic format. The His-tagged proteins diffuse to adjacent Cu(II)-NTA microarray elements (denoted as detector elements) and are specifically adsorbed. The net result is the on-chip, cell-free synthesis of a protein microarray that can be used immediately for SPRI protein biosensing. The dual element format greatly reduces any interference from the nonspecific adsorption of enzyme or proteins. SPRI measurements for the detection of the antibodies anti-GFP and anti-luciferase were used to verify the formation of the protein microarray. This convenient on-chip protein microarray fabrication method can be implemented for multiplexed SPRI biosensing measurements in both clinical and research applications. PMID:22793370

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

PubMed

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

2015-01-01

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

Mixed Membership Distributions with Applications to Modeling Multiple Strategy Usage

ERIC Educational Resources Information Center

Galyardt, April

2012-01-01

This dissertation examines two related questions. "How do mixed membership models work?" and "Can mixed membership be used to model how students use multiple strategies to solve problems?". Mixed membership models have been used in thousands of applications from text and image processing to genetic microarray analysis. Yet…

GP3: GENEPIX POST-PROCESSING SCRIPT FOR THE AUTOMATED ANALYSIS OF RAW MICROARRAY IMAGE OUTPUT FILES. (R827402)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

MicroGen: a MIAME compliant web system for microarray experiment information and workflow management.

PubMed

Burgarella, Sarah; Cattaneo, Dario; Pinciroli, Francesco; Masseroli, Marco

2005-12-01

Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results. We developed MicroGen, a web system for managing information and workflow in the production pipeline of spotted microarray experiments. It is constituted of a core multi-database system able to store all data completely characterizing different spotted microarray experiments according to the Minimum Information About Microarray Experiments (MIAME) standard, and of an intuitive and user-friendly web interface able to support the collaborative work required among multidisciplinary actors and roles involved in spotted microarray experiment production. MicroGen supports six types of user roles: the researcher who designs and requests the experiment, the spotting operator, the hybridisation operator, the image processing operator, the system administrator, and the generic public user who can access the unrestricted part of the system to get information about MicroGen services. MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production.

A new functional membrane protein microarray based on tethered phospholipid bilayers.

PubMed

Chadli, Meriem; Maniti, Ofelia; Marquette, Christophe; Tillier, Bruno; Cortès, Sandra; Girard-Egrot, Agnès

2018-04-30

A new prototype of a membrane protein biochip is presented in this article. This biochip was created by the combination of novel technologies of peptide-tethered bilayer lipid membrane (pep-tBLM) formation and solid support micropatterning. Pep-tBLMs integrating a membrane protein were obtained in the form of microarrays on a gold chip. The formation of the microspots was visualized in real-time by surface plasmon resonance imaging (SPRi) and the functionality of a GPCR (CXCR4), reinserted locally into microwells, was assessed by ligand binding studies. In brief, to achieve micropatterning, P19-4H, a 4 histidine-possessing peptide spacer, was spotted inside microwells obtained on polystyrene-coated gold, and Ni-chelating proteoliposomes were injected into the reaction chamber. Proteoliposome binding to the peptide was based on metal-chelate interaction. The peptide-tethered lipid bilayer was finally obtained by addition of a fusogenic peptide (AH peptide) to promote proteoliposome fusion. The CXCR4 pep-tBLM microarray was characterized by surface plasmon resonance imaging (SPRi) throughout the building-up process. This new generation of membrane protein biochip represents a promising method of developing a screening tool for drug discovery.

Deep learning for tissue microarray image-based outcome prediction in patients with colorectal cancer

NASA Astrophysics Data System (ADS)

Bychkov, Dmitrii; Turkki, Riku; Haglund, Caj; Linder, Nina; Lundin, Johan

2016-03-01

Recent advances in computer vision enable increasingly accurate automated pattern classification. In the current study we evaluate whether a convolutional neural network (CNN) can be trained to predict disease outcome in patients with colorectal cancer based on images of tumor tissue microarray samples. We compare the prognostic accuracy of CNN features extracted from the whole, unsegmented tissue microarray spot image, with that of CNN features extracted from the epithelial and non-epithelial compartments, respectively. The prognostic accuracy of visually assessed histologic grade is used as a reference. The image data set consists of digitized hematoxylin-eosin (H and E) stained tissue microarray samples obtained from 180 patients with colorectal cancer. The patient samples represent a variety of histological grades, have data available on a series of clinicopathological variables including long-term outcome and ground truth annotations performed by experts. The CNN features extracted from images of the epithelial tissue compartment significantly predicted outcome (hazard ratio (HR) 2.08; CI95% 1.04-4.16; area under the curve (AUC) 0.66) in a test set of 60 patients, as compared to the CNN features extracted from unsegmented images (HR 1.67; CI95% 0.84-3.31, AUC 0.57) and visually assessed histologic grade (HR 1.96; CI95% 0.99-3.88, AUC 0.61). As a conclusion, a deep-learning classifier can be trained to predict outcome of colorectal cancer based on images of H and E stained tissue microarray samples and the CNN features extracted from the epithelial compartment only resulted in a prognostic discrimination comparable to that of visually determined histologic grade.

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

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.

Automatic image analysis and spot classification for detection of pathogenic Escherichia coli on glass slide DNA microarrays

USDA-ARS?s Scientific Manuscript database

A computer algorithm was created to inspect scanned images from DNA microarray slides developed to rapidly detect and genotype E. Coli O157 virulent strains. The algorithm computes centroid locations for signal and background pixels in RGB space and defines a plane perpendicular to the line connect...

Reverse phase protein microarrays: fluorometric and colorimetric detection.

PubMed

Gallagher, Rosa I; Silvestri, Alessandra; Petricoin, Emanuel F; Liotta, Lance A; Espina, Virginia

2011-01-01

The Reverse Phase Protein Microarray (RPMA) is an array platform used to quantitate proteins and their posttranslationally modified forms. RPMAs are applicable for profiling key cellular signaling pathways and protein networks, allowing direct comparison of the activation state of proteins from multiple samples within the same array. The RPMA format consists of proteins immobilized directly on a nitrocellulose substratum. The analyte is subsequently probed with a primary antibody and a series of reagents for signal amplification and detection. Due to the diversity, low concentration, and large dynamic range of protein analytes, RPMAs require stringent signal amplification methods, high quality image acquisition, and software capable of precisely analyzing spot intensities on an array. Microarray detection strategies can be either fluorescent or colorimetric. The choice of a detection system depends on (a) the expected analyte concentration, (b) type of microarray imaging system, and (c) type of sample. The focus of this chapter is to describe RPMA detection and imaging using fluorescent and colorimetric (diaminobenzidine (DAB)) methods.

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

PubMed

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

2015-10-06

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

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

Microscopy Images as Interactive Tools in Cell Modeling and Cell Biology Education

ERIC Educational Resources Information Center

Araujo-Jorge, Tania C.; Cardona, Tania S.; Mendes, Claudia L. S.; Henriques-Pons, Andrea; Meirelles, Rosane M. S.; Coutinho, Claudia M. L. M.; Aguiar, Luiz Edmundo V.; Meirelles, Maria de Nazareth L.; de Castro, Solange L.; Barbosa, Helene S.; Luz, Mauricio R. M. P.

2004-01-01

The advent of genomics, proteomics, and microarray technology has brought much excitement to science, both in teaching and in learning. The public is eager to know about the processes of life. In the present context of the explosive growth of scientific information, a major challenge of modern cell biology is to popularize basic concepts of…

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

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

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

Surface plasmon resonance imaging system with Mach-Zehnder phase-shift interferometry for DNA micro-array hybridization

NASA Astrophysics Data System (ADS)

Hsiu, Feng-Ming; Chen, Shean-Jen; Tsai, Chien-Hung; Tsou, Chia-Yuan; Su, Y.-D.; Lin, G.-Y.; Huang, K.-T.; Chyou, Jin-Jung; Ku, Wei-Chih; Chiu, S.-K.; Tzeng, C.-M.

2002-09-01

Surface plasmon resonance (SPR) imaging system is presented as a novel technique based on modified Mach-Zehnder phase-shifting interferometry (PSI) for biomolecular interaction analysis (BIA), which measures the spatial phase variation of a resonantly reflected light in biomolecular interaction. In this technique, the micro-array SPR biosensors with over a thousand probe NDA spots can be detected simultaneously. Owing to the feasible and swift measurements, the micro-array SPR biosensors can be extensively applied to the nonspecific adsorption of protein, the membrane/protein interactions, and DNA hybridization. The detection sensitivity of the SPR PSI imaging system is improved to about 1 pg/mm2 for each spot over the conventional SPR imaging systems. The SPR PSI imaging system and its SPR sensors have been successfully used to observe slightly index change in consequence of argon gas flow through the nitrogen in real time, with high sensitivity, and at high-throughout screening rates.

Rapid Microarray Detection of DNA and Proteins in Microliter Volumes with SPR Imaging Measurements

PubMed Central

Seefeld, Ting Hu; Zhou, Wen-Juan; Corn, Robert M.

2011-01-01

A four chamber microfluidic biochip is fabricated for the rapid detection of multiple proteins and nucleic acids from microliter volume samples with the technique of surface plasmon resonance imaging (SPRI). The 18 mm × 18 mm biochip consists of four 3 μL microfluidic chambers attached to an SF10 glass substrate, each of which contains three individually addressable SPRI gold thin film microarray elements. The twelve element (4 × 3) SPRI microarray consists of gold thin film spots (1 mm2 area; 45 nm thickness) each in individually addressable 0.5 μL volume microchannels. Microarrays of single-stranded DNA and RNA (ssDNA and ssRNA respectively) are fabricated by either chemical and/or enzymatic attachment reactions in these microchannels; the SPRI microarrays are then used to detect femtomole amounts (nanomolar concentrations) of DNA and proteins (single stranded DNA binding protein and thrombin via aptamer-protein bioaffinity interactions). Microarrays of ssRNA microarray elements were also used for the ultrasensitive detection of zeptomole amounts (femtomolar concentrations) of DNA via the technique of RNase H-amplified SPRI. Enzymatic removal of ssRNA from the surface due to the hybridization adsorption of target ssDNA is detected as a reflectivity decrease in the SPR imaging measurements. The observed reflectivity loss was proportional to the log of the target ssDNA concentration with a detection limit of 10 fM or 30 zeptomoles (18,000 molecules). This enzymatic amplified ssDNA detection method is not limited by diffusion of ssDNA to the interface, and thus is extremely fast, requiring only 200 seconds in the microliter volume format. PMID:21488682

A hybrid approach to device integration on a genetic analysis platform

NASA Astrophysics Data System (ADS)

Brennan, Des; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Justice, John; Aherne, Margaret; Macek, Milan; Galvin, Paul

2012-10-01

Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization.

Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.

Calibration and assessment of channel-specific biases in microarray data with extended dynamical range.

PubMed

Bengtsson, Henrik; Jönsson, Göran; Vallon-Christersson, Johan

2004-11-12

Non-linearities in observed log-ratios of gene expressions, also known as intensity dependent log-ratios, can often be accounted for by global biases in the two channels being compared. Any step in a microarray process may introduce such offsets and in this article we study the biases introduced by the microarray scanner and the image analysis software. By scanning the same spotted oligonucleotide microarray at different photomultiplier tube (PMT) gains, we have identified a channel-specific bias present in two-channel microarray data. For the scanners analyzed it was in the range of 15-25 (out of 65,535). The observed bias was very stable between subsequent scans of the same array although the PMT gain was greatly adjusted. This indicates that the bias does not originate from a step preceding the scanner detector parts. The bias varies slightly between arrays. When comparing estimates based on data from the same array, but from different scanners, we have found that different scanners introduce different amounts of bias. So do various image analysis methods. We propose a scanning protocol and a constrained affine model that allows us to identify and estimate the bias in each channel. Backward transformation removes the bias and brings the channels to the same scale. The result is that systematic effects such as intensity dependent log-ratios are removed, but also that signal densities become much more similar. The average scan, which has a larger dynamical range and greater signal-to-noise ratio than individual scans, can then be obtained. The study shows that microarray scanners may introduce a significant bias in each channel. Such biases have to be calibrated for, otherwise systematic effects such as intensity dependent log-ratios will be observed. The proposed scanning protocol and calibration method is simple to use and is useful for evaluating scanner biases or for obtaining calibrated measurements with extended dynamical range and better precision. The cross-platform R package aroma, which implements all described methods, is available for free from http://www.maths.lth.se/bioinformatics/.

The tissue microarray data exchange specification: Extending TMA DES to provide flexible scoring and incorporate virtual slides

PubMed Central

Wright, Alexander; Lyttleton, Oliver; Lewis, Paul; Quirke, Philip; Treanor, Darren

2011-01-01

Background: Tissue MicroArrays (TMAs) are a high throughput technology for rapid analysis of protein expression across hundreds of patient samples. Often, data relating to TMAs is specific to the clinical trial or experiment it is being used for, and not interoperable. The Tissue Microarray Data Exchange Specification (TMA DES) is a set of eXtensible Markup Language (XML)-based protocols for storing and sharing digitized Tissue Microarray data. XML data are enclosed by named tags which serve as identifiers. These tag names can be Common Data Elements (CDEs), which have a predefined meaning or semantics. By using this specification in a laboratory setting with increasing demands for digital pathology integration, we found that the data structure lacked the ability to cope with digital slide imaging in respect to web-enabled digital pathology systems and advanced scoring techniques. Materials and Methods: By employing user centric design, and observing behavior in relation to TMA scoring and associated data, the TMA DES format was extended to accommodate the current limitations. This was done with specific focus on developing a generic tool for handling any given scoring system, and utilizing data for multiple observations and observers. Results: DTDs were created to validate the extensions of the TMA DES protocol, and a test set of data containing scores for 6,708 TMA core images was generated. The XML was then read into an image processing algorithm to utilize the digital pathology data extensions, and scoring results were easily stored alongside the existing multiple pathologist scores. Conclusions: By extending the TMA DES format to include digital pathology data and customizable scoring systems for TMAs, the new system facilitates the collaboration between pathologists and organizations, and can be used in automatic or manual data analysis. This allows complying systems to effectively communicate complex and varied scoring data. PMID:21572508

ATMAD: robust image analysis for Automatic Tissue MicroArray De-arraying.

PubMed

Nguyen, Hoai Nam; Paveau, Vincent; Cauchois, Cyril; Kervrann, Charles

2018-04-19

Over the last two decades, an innovative technology called Tissue Microarray (TMA), which combines multi-tissue and DNA microarray concepts, has been widely used in the field of histology. It consists of a collection of several (up to 1000 or more) tissue samples that are assembled onto a single support - typically a glass slide - according to a design grid (array) layout, in order to allow multiplex analysis by treating numerous samples under identical and standardized conditions. However, during the TMA manufacturing process, the sample positions can be highly distorted from the design grid due to the imprecision when assembling tissue samples and the deformation of the embedding waxes. Consequently, these distortions may lead to severe errors of (histological) assay results when the sample identities are mismatched between the design and its manufactured output. The development of a robust method for de-arraying TMA, which localizes and matches TMA samples with their design grid, is therefore crucial to overcome the bottleneck of this prominent technology. In this paper, we propose an Automatic, fast and robust TMA De-arraying (ATMAD) approach dedicated to images acquired with brightfield and fluorescence microscopes (or scanners). First, tissue samples are localized in the large image by applying a locally adaptive thresholding on the isotropic wavelet transform of the input TMA image. To reduce false detections, a parametric shape model is considered for segmenting ellipse-shaped objects at each detected position. Segmented objects that do not meet the size and the roundness criteria are discarded from the list of tissue samples before being matched with the design grid. Sample matching is performed by estimating the TMA grid deformation under the thin-plate model. Finally, thanks to the estimated deformation, the true tissue samples that were preliminary rejected in the early image processing step are recognized by running a second segmentation step. We developed a novel de-arraying approach for TMA analysis. By combining wavelet-based detection, active contour segmentation, and thin-plate spline interpolation, our approach is able to handle TMA images with high dynamic, poor signal-to-noise ratio, complex background and non-linear deformation of TMA grid. In addition, the deformation estimation produces quantitative information to asset the manufacturing quality of TMAs.

Development of a Digital Microarray with Interferometric Reflectance Imaging

NASA Astrophysics Data System (ADS)

Sevenler, Derin

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

An improved K-means clustering method for cDNA microarray image segmentation.

PubMed

Wang, T N; Li, T J; Shao, G F; Wu, S X

2015-07-14

Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

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

PubMed

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

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

The Glycan Microarray Story from Construction to Applications.

PubMed

Hyun, Ji Young; Pai, Jaeyoung; Shin, Injae

2017-04-18

Not only are glycan-mediated binding processes in cells and organisms essential for a wide range of physiological processes, but they are also implicated in various pathological processes. As a result, elucidation of glycan-associated biomolecular interactions and their consequences is of great importance in basic biological research and biomedical applications. In 2002, we and others were the first to utilize glycan microarrays in efforts aimed at the rapid analysis of glycan-associated recognition events. Because they contain a number of glycans immobilized in a dense and orderly manner on a solid surface, glycan microarrays enable multiple parallel analyses of glycan-protein binding events while utilizing only small amounts of glycan samples. Therefore, this microarray technology has become a leading edge tool in studies aimed at elucidating roles played by glycans and glycan binding proteins in biological systems. In this Account, we summarize our efforts on the construction of glycan microarrays and their applications in studies of glycan-associated interactions. Immobilization strategies of functionalized and unmodified glycans on derivatized glass surfaces are described. Although others have developed immobilization techniques, our efforts have focused on improving the efficiencies and operational simplicity of microarray construction. The microarray-based technology has been most extensively used for rapid analysis of the glycan binding properties of proteins. In addition, glycan microarrays have been employed to determine glycan-protein interactions quantitatively, detect pathogens, and rapidly assess substrate specificities of carbohydrate-processing enzymes. More recently, the microarrays have been employed to identify functional glycans that elicit cell surface lectin-mediated cellular responses. Owing to these efforts, it is now possible to use glycan microarrays to expand the understanding of roles played by glycans and glycan binding proteins in biological systems.

Standardization efforts of digital pathology in Europe.

PubMed

Rojo, Marcial García; Daniel, Christel; Schrader, Thomas

2012-01-01

EURO-TELEPATH is a European COST Action IC0604. It started in 2007 and will end in November 2011. Its main objectives are evaluating and validating the common technological framework and communication standards required to access, transmit, and manage digital medical records by pathologists and other medical specialties in a networked environment. Working Group 1, "Business Modelling in Pathology," has designed main pathology processes - Frozen Study, Formalin Fixed Specimen Study, Telepathology, Cytology, and Autopsy - using Business Process Modelling Notation (BPMN). Working Group 2 has been dedicated to promoting the application of informatics standards in pathology, collaborating with Integrating Healthcare Enterprise (IHE), Digital Imaging and Communications in Medicine (DICOM), Health Level Seven (HL7), and other standardization bodies. Health terminology standardization research has become a topic of great interest. Future research work should focus on standardizing automatic image analysis and tissue microarrays imaging.

Probing the effects of surface hydrophobicity and tether orientation on antibody-antigen binding

NASA Astrophysics Data System (ADS)

Bush, Derek B.; Knotts, Thomas A.

2017-04-01

Antibody microarrays have the potential to revolutionize molecular detection for many applications, but their current use is limited by poor reliability, and efforts to change this have not yielded fruitful results. One difficulty which limits the rational engineering of next-generation devices is that little is known, at the molecular level, about the antibody-antigen binding process near solid surfaces. Atomic-level structural information is scant because typical experimental techniques (X-ray crystallography and NMR) cannot be used to image proteins bound to surfaces. To overcome this limitation, this study uses molecular simulation and an advanced, experimentally validated, coarse-grain, protein-surface model to compare fab-lysozyme binding in bulk solution and when the fab is tethered to hydrophobic and hydrophilic surfaces. The results show that the tether site in the fab, as well as the surface hydrophobicity, significantly impacts the binding process and suggests that the optimal design involves tethering fabs upright on a hydrophilic surface. The results offer an unprecedented, molecular-level picture of the binding process and give hope that the rational design of protein-microarrays is possible.

Evaluating concentration estimation errors in ELISA microarray experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Don S.; White, Amanda M.; Varnum, Susan M.

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less

High-density fiber-optic DNA random microsphere array.

PubMed

Ferguson, J A; Steemers, F J; Walt, D R

2000-11-15

A high-density fiber-optic DNA microarray sensor was developed to monitor multiple DNA sequences in parallel. Microarrays were prepared by randomly distributing DNA probe-functionalized 3.1-microm-diameter microspheres in an array of wells etched in a 500-microm-diameter optical imaging fiber. Registration of the microspheres was performed using an optical encoding scheme and a custom-built imaging system. Hybridization was visualized using fluorescent-labeled DNA targets with a detection limit of 10 fM. Hybridization times of seconds are required for nanomolar target concentrations, and analysis is performed in minutes.

Rapid Spoligotyping of Mycobacterium tuberculosis Complex Bacteria by Use of a Microarray System with Automatic Data Processing and Assignment

PubMed Central

Ruettger, Anke; Nieter, Johanna; Skrypnyk, Artem; Engelmann, Ines; Ziegler, Albrecht; Moser, Irmgard; Monecke, Stefan; Ehricht, Ralf

2012-01-01

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability. PMID:22553239

Rapid spoligotyping of Mycobacterium tuberculosis complex bacteria by use of a microarray system with automatic data processing and assignment.

PubMed

Ruettger, Anke; Nieter, Johanna; Skrypnyk, Artem; Engelmann, Ines; Ziegler, Albrecht; Moser, Irmgard; Monecke, Stefan; Ehricht, Ralf; Sachse, Konrad

2012-07-01

Membrane-based spoligotyping has been converted to DNA microarray format to qualify it for high-throughput testing. We have shown the assay's validity and suitability for direct typing from tissue and detecting new spoligotypes. Advantages of the microarray methodology include rapidity, ease of operation, automatic data processing, and affordability.

Knowledge-based image processing for on-off type DNA microarray

NASA Astrophysics Data System (ADS)

Kim, Jong D.; Kim, Seo K.; Cho, Jeong S.; Kim, Jongwon

2002-06-01

This paper addresses the image processing technique for discriminating whether the probes are hybrized with target DNA in the Human Papilloma Virus (HPV) DNA Chip designed for genotyping HPV. In addition to the probes, the HPV DNA chip has markers that always react with the sample DNA. The positions of probe-dots in the final scanned image are fixed relative to the marker-dot locations with a small variation according to the accuracy of the dotter and the scanner. The probes are duplicated 4 times for the diagnostic stability. The prior knowledges such as the maker relative distance and the duplication information of probes is integrated into the template matching technique with the normalized correlation measure. Results show that the employment of both of the prior knowledges is to simply average the template matching measures over the positions of the markers and probes. The eventual proposed scheme yields stable marker locating and probe classification.

Practical considerations of image analysis and quantification of signal transduction IHC staining.

PubMed

Grunkin, Michael; Raundahl, Jakob; Foged, Niels T

2011-01-01

The dramatic increase in computer processing power in combination with the availability of high-quality digital cameras during the last 10 years has fertilized the grounds for quantitative microscopy based on digital image analysis. With the present introduction of robust scanners for whole slide imaging in both research and routine, the benefits of automation and objectivity in the analysis of tissue sections will be even more obvious. For in situ studies of signal transduction, the combination of tissue microarrays, immunohistochemistry, digital imaging, and quantitative image analysis will be central operations. However, immunohistochemistry is a multistep procedure including a lot of technical pitfalls leading to intra- and interlaboratory variability of its outcome. The resulting variations in staining intensity and disruption of original morphology are an extra challenge for the image analysis software, which therefore preferably should be dedicated to the detection and quantification of histomorphometrical end points.

ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.

ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

Analysis of High-Throughput ELISA Microarray Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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).

The impact of "omic" and imaging technologies on assessing the host immune response to biodefence agents.

PubMed

Tree, Julia A; Flick-Smith, Helen; Elmore, Michael J; Rowland, Caroline A

2014-01-01

Understanding the interactions between host and pathogen is important for the development and assessment of medical countermeasures to infectious agents, including potential biodefence pathogens such as Bacillus anthracis, Ebola virus, and Francisella tularensis. This review focuses on technological advances which allow this interaction to be studied in much greater detail. Namely, the use of "omic" technologies (next generation sequencing, DNA, and protein microarrays) for dissecting the underlying host response to infection at the molecular level; optical imaging techniques (flow cytometry and fluorescence microscopy) for assessing cellular responses to infection; and biophotonic imaging for visualising the infectious disease process. All of these technologies hold great promise for important breakthroughs in the rational development of vaccines and therapeutics for biodefence agents.

PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

EPA Science Inventory

Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

Tissue microarrays and digital image analysis.

PubMed

Ryan, Denise; Mulrane, Laoighse; Rexhepaj, Elton; Gallagher, William M

2011-01-01

Tissue microarrays (TMAs) have recently emerged as very valuable tools for high-throughput pathological assessment, especially in the cancer research arena. This important technology, however, has yet to fully penetrate into the area of toxicology. Here, we describe the creation of TMAs representative of samples produced from conventional toxicology studies within a large-scale, multi-institutional pan-European project, PredTox. PredTox, short for Predictive Toxicology, formed part of an EU FP6 Integrated Project, Innovative Medicines for Europe (InnoMed), and aimed to study pre-clinically 16 compounds of known liver and/or kidney toxicity. In more detail, TMAs were constructed from materials corresponding to the full face sections of liver and kidney from rats treated with different drug candidates by members of the consortium. We also describe the process of digital slide scanning of kidney and liver sections, in the context of creating an online resource of histopathological data.

AGScan: a pluggable microarray image quantification software based on the ImageJ library.

PubMed

Cathelin, R; Lopez, F; Klopp, Ch

2007-01-15

Many different programs are available to analyze microarray images. Most programs are commercial packages, some are free. In the latter group only few propose automatic grid alignment and batch mode. More often than not a program implements only one quantification algorithm. AGScan is an open source program that works on all major platforms. It is based on the ImageJ library [Rasband (1997-2006)] and offers a plug-in extension system to add new functions to manipulate images, align grid and quantify spots. It is appropriate for daily laboratory use and also as a framework for new algorithms. The program is freely distributed under X11 Licence. The install instructions can be found in the user manual. The software can be downloaded from http://mulcyber.toulouse.inra.fr/projects/agscan/. The questions and plug-ins can be sent to the contact listed below.

Manufacturing of microarrays.

PubMed

Petersen, David W; Kawasaki, Ernest S

2007-01-01

DNA microarray technology has become a powerful tool in the arsenal of the molecular biologist. Capitalizing on high precision robotics and the wealth of DNA sequences annotated from the genomes of a large number of organisms, the manufacture of microarrays is now possible for the average academic laboratory with the funds and motivation. Microarray production requires attention to both biological and physical resources, including DNA libraries, robotics, and qualified personnel. While the fabrication of microarrays is a very labor-intensive process, production of quality microarrays individually tailored on a project-by-project basis will help researchers shed light on future scientific questions.

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tholouli, Eleni; MacDermott, Sarah; Hoyland, Judith

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection inmore » archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.« less

Robust Segmentation of Overlapping Cells in Histopathology Specimens Using Parallel Seed Detection and Repulsive Level Set

PubMed Central

Qi, Xin; Xing, Fuyong; Foran, David J.; Yang, Lin

2013-01-01

Automated image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of breast cancer. Automated segmentation of the cells comprising imaged tissue microarrays (TMA) is a prerequisite for any subsequent quantitative analysis. Unfortunately, crowding and overlapping of cells present significant challenges for most traditional segmentation algorithms. In this paper, we propose a novel algorithm which can reliably separate touching cells in hematoxylin stained breast TMA specimens which have been acquired using a standard RGB camera. The algorithm is composed of two steps. It begins with a fast, reliable object center localization approach which utilizes single-path voting followed by mean-shift clustering. Next, the contour of each cell is obtained using a level set algorithm based on an interactive model. We compared the experimental results with those reported in the most current literature. Finally, performance was evaluated by comparing the pixel-wise accuracy provided by human experts with that produced by the new automated segmentation algorithm. The method was systematically tested on 234 image patches exhibiting dense overlap and containing more than 2200 cells. It was also tested on whole slide images including blood smears and tissue microarrays containing thousands of cells. Since the voting step of the seed detection algorithm is well suited for parallelization, a parallel version of the algorithm was implemented using graphic processing units (GPU) which resulted in significant speed-up over the C/C++ implementation. PMID:22167559

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference.

PubMed

Yang, Yunfeng; Zhu, Mengxia; Wu, Liyou; Zhou, Jizhong

2008-09-16

Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality. Microarray experiments were performed in a gamma-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses. These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.

A Universal Protocol for Photochemical Covalent Immobilization of Intact Carbohydrates for the Preparation of Carbohydrate Microarrays

PubMed Central

Wang, Huibin; Zhang, Yiming; Yuan, Xun; Chen, Yi; Yan, Mingdi

2010-01-01

A universal photochemical method has been established for the immobilization of intact carbohydrates and their analogues, and for the fabrication of carbohydrate microarrays. The method features the use of perfluorophenyl azide (PFPA)-modified substrates and the photochemical reaction of surface azido groups with printed carbohydrates. Various aldoses, ketoses, non-reducing sugars such as alditols and their derivatives can be directly arrayed on the PFPA-modified chips. The lectin-recognition ability of arrayed mannose, glucose and their oligo- and polysaccharides were confirmed using surface plasmon resonance imaging and laser-induced fluorescence imaging. PMID:21138274

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.

A universal protocol for photochemical covalent immobilization of intact carbohydrates for the preparation of carbohydrate microarrays.

PubMed

Wang, Huibin; Zhang, Yiming; Yuan, Xun; Chen, Yi; Yan, Mingdi

2011-01-19

A universal photochemical method has been established for the immobilization of intact carbohydrates and their analogues, and for the fabrication of carbohydrate microarrays. The method features the use of perfluorophenyl azide (PFPA)-modified substrates and the photochemical reaction of surface azido groups with printed carbohydrates. Various aldoses, ketoses, nonreducing sugars such as alditols, and their derivatives can be directly arrayed on the PFPA-modified chips. The lectin-recognition ability of arrayed mannose, glucose, and their oligo- and polysaccharides were confirmed using surface plasmon resonance imaging and laser-induced fluorescence imaging.

Image processing in digital pathology: an opportunity to solve inter-batch variability of immunohistochemical staining

NASA Astrophysics Data System (ADS)

van Eycke, Yves-Rémi; Allard, Justine; Salmon, Isabelle; Debeir, Olivier; Decaestecker, Christine

2017-02-01

Immunohistochemistry (IHC) is a widely used technique in pathology to evidence protein expression in tissue samples. However, this staining technique is known for presenting inter-batch variations. Whole slide imaging in digital pathology offers a possibility to overcome this problem by means of image normalisation techniques. In the present paper we propose a methodology to objectively evaluate the need of image normalisation and to identify the best way to perform it. This methodology uses tissue microarray (TMA) materials and statistical analyses to evidence the possible variations occurring at colour and intensity levels as well as to evaluate the efficiency of image normalisation methods in correcting them. We applied our methodology to test different methods of image normalisation based on blind colour deconvolution that we adapted for IHC staining. These tests were carried out for different IHC experiments on different tissue types and targeting different proteins with different subcellular localisations. Our methodology enabled us to establish and to validate inter-batch normalization transforms which correct the non-relevant IHC staining variations. The normalised image series were then processed to extract coherent quantitative features characterising the IHC staining patterns.

Image processing in digital pathology: an opportunity to solve inter-batch variability of immunohistochemical staining

PubMed Central

Van Eycke, Yves-Rémi; Allard, Justine; Salmon, Isabelle; Debeir, Olivier; Decaestecker, Christine

2017-01-01

Immunohistochemistry (IHC) is a widely used technique in pathology to evidence protein expression in tissue samples. However, this staining technique is known for presenting inter-batch variations. Whole slide imaging in digital pathology offers a possibility to overcome this problem by means of image normalisation techniques. In the present paper we propose a methodology to objectively evaluate the need of image normalisation and to identify the best way to perform it. This methodology uses tissue microarray (TMA) materials and statistical analyses to evidence the possible variations occurring at colour and intensity levels as well as to evaluate the efficiency of image normalisation methods in correcting them. We applied our methodology to test different methods of image normalisation based on blind colour deconvolution that we adapted for IHC staining. These tests were carried out for different IHC experiments on different tissue types and targeting different proteins with different subcellular localisations. Our methodology enabled us to establish and to validate inter-batch normalization transforms which correct the non-relevant IHC staining variations. The normalised image series were then processed to extract coherent quantitative features characterising the IHC staining patterns. PMID:28220842

CMOS Imaging of Temperature Effects on Pin-Printed Xerogel Sensor Microarrays.

PubMed

Lei Yao; Ka Yi Yung; Chodavarapu, Vamsy P; Bright, Frank V

2011-04-01

In this paper, we study the effect of temperature on the operation and performance of a xerogel-based sensor microarrays coupled to a complementary metal-oxide semiconductor (CMOS) imager integrated circuit (IC) that images the photoluminescence response from the sensor microarray. The CMOS imager uses a 32 × 32 (1024 elements) array of active pixel sensors and each pixel includes a high-gain phototransistor to convert the detected optical signals into electrical currents. A correlated double sampling circuit and pixel address/digital control/signal integration circuit are also implemented on-chip. The CMOS imager data are read out as a serial coded signal. The sensor system uses a light-emitting diode to excite target analyte responsive organometallic luminophores doped within discrete xerogel-based sensor elements. As a proto type, we developed a 3 × 3 (9 elements) array of oxygen (O2) sensors. Each group of three sensor elements in the array (arranged in a column) is designed to provide a different and specific sensitivity to the target gaseous O2 concentration. This property of multiple sensitivities is achieved by using a mix of two O2 sensitive luminophores in each pin-printed xerogel sensor element. The CMOS imager is designed to be low noise and consumes a static power of 320.4 μW and an average dynamic power of 624.6 μW when operating at 100-Hz sampling frequency and 1.8-V dc power supply.

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

Controllable Photovoltaic Effect of Microarray Derived from Epitaxial Tetragonal BiFeO3 Films.

PubMed

Lu, Zengxing; Li, Peilian; Wan, Jian-Guo; Huang, Zhifeng; Tian, Guo; Pan, Danfeng; Fan, Zhen; Gao, Xingsen; Liu, Jun-Ming

2017-08-16

Recently, the ferroelectric photovoltaic (FePV) effect has attracted great interest due to its potential in developing optoelectronic devices such as solar cell and electric-optical sensors. It is important for actual applications to realize a controllable photovoltaic process in ferroelectric-based materials. In this work, we prepared well-ordered microarrays based on epitaxially tetragonal BiFeO 3 (T-BFO) films by the pulsed laser deposition technique. The polarization-dependent photocurrent image was directly observed by a conductive atomic force microscope under ultraviolet illumination. By choosing a suitable buffer electrode layer and controlling the ferroelectric polarization in the T-BFO layer, we realized the manipulation of the photovoltaic process. Moreover, based on the analysis of the band structure, we revealed the mechanism of manipulating the photovoltaic process and attributed it to the competition between two key factors, i.e., the internal electric field caused by energy band alignments at interfaces and the depolarization field induced by the ferroelectric polarization in T-BFO. This work is very meaningful for deeply understanding the photovoltaic process of BiFeO 3 -based devices at the microscale and provides us a feasible avenue for developing data storage or logic switching microdevices based on the FePV effect.

Image microarrays (IMA): Digital pathology's missing tool

PubMed Central

Hipp, Jason; Cheng, Jerome; Pantanowitz, Liron; Hewitt, Stephen; Yagi, Yukako; Monaco, James; Madabhushi, Anant; Rodriguez-canales, Jaime; Hanson, Jeffrey; Roy-Chowdhuri, Sinchita; Filie, Armando C.; Feldman, Michael D.; Tomaszewski, John E.; Shih, Natalie NC.; Brodsky, Victor; Giaccone, Giuseppe; Emmert-Buck, Michael R.; Balis, Ulysses J.

2011-01-01

Introduction: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. Methods: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. Results: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. Conclusion: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. PMID:22200030

Microarrays in brain research: the good, the bad and the ugly.

PubMed

Mirnics, K

2001-06-01

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results. PMID:27499890

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

Bacterial identification and subtyping using DNA microarray and DNA sequencing.

PubMed

Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

2012-01-01

The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

An Advanced Approach to Simultaneous Monitoring of Multiple Bacteria in Space

NASA Technical Reports Server (NTRS)

Eggers, M.

1998-01-01

The utility of a novel microarray-based microbial analyzer was demonstrated by the rapid detection, imaging, and identification of a mixture of microorganisms found in a waste water sample from the Lunar-Mars Life Support Test Project through the synergistic combination of: (1) judicious RNA probe selection via algorithms developed by University of Houston scientists; (2) tuned surface chemistries developed by Baylor College of Medicine scientists to facilitate hybridization of rRNA targets to DNA probes under very low salt conditions, thereby minimizing secondary structure; and (3) integration of the microarray printing and detection/imaging instrumentation by Genometrix to complete the quantitative analysis of microorganism mixtures.

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

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" 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. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

Plant-pathogen interactions: what microarray tells about it?

PubMed

Lodha, T D; Basak, J

2012-01-01

Plant defense responses are mediated by elementary regulatory proteins that affect expression of thousands of genes. Over the last decade, microarray technology has played a key role in deciphering the underlying networks of gene regulation in plants that lead to a wide variety of defence responses. Microarray is an important tool to quantify and profile the expression of thousands of genes simultaneously, with two main aims: (1) gene discovery and (2) global expression profiling. Several microarray technologies are currently in use; most include a glass slide platform with spotted cDNA or oligonucleotides. Till date, microarray technology has been used in the identification of regulatory genes, end-point defence genes, to understand the signal transduction processes underlying disease resistance and its intimate links to other physiological pathways. Microarray technology can be used for in-depth, simultaneous profiling of host/pathogen genes as the disease progresses from infection to resistance/susceptibility at different developmental stages of the host, which can be done in different environments, for clearer understanding of the processes involved. A thorough knowledge of plant disease resistance using successful combination of microarray and other high throughput techniques, as well as biochemical, genetic, and cell biological experiments is needed for practical application to secure and stabilize yield of many crop plants. This review starts with a brief introduction to microarray technology, followed by the basics of plant-pathogen interaction, the use of DNA microarrays over the last decade to unravel the mysteries of plant-pathogen interaction, and ends with the future prospects of this technology.

Quantitative multiplex immunohistochemistry reveals myeloid-inflamed tumor-immune complexity associated with poor prognosis

PubMed Central

Tsujikawa, Takahiro; Kumar, Sushil; Borkar, Rohan N.; Azimi, Vahid; Thibault, Guillaume; Chang, Young Hwan; Balter, Ariel; Kawashima, Rie; Choe, Gina; Sauer, David; El Rassi, Edward; Clayburgh, Daniel R.; Kulesz-Martin, Molly F.; Lutz, Eric R.; Zheng, Lei; Jaffee, Elizabeth M.; Leyshock, Patrick; Margolin, Adam A.; Mori, Motomi; Gray, Joe W.; Flint, Paul W.; Coussens, Lisa M.

2017-01-01

SUMMARY Here we describe a multiplexed immunohistochemical platform, with computational image processing workflows including image cytometry, enabling simultaneous evaluation of 12 biomarkers in one formalin-fixed paraffin-embedded tissue section. To validate this platform, we used tissue microarrays containing 38 archival head and neck squamous cell carcinomas, and revealed differential immune profiles based on lymphoid and myeloid cell densities, correlating with human papilloma virus status and prognosis. Based on these results, we investigated 24 pancreatic ductal adenocarcinomas from patients who received neoadjuvant GVAX vaccination, and revealed that response to therapy correlated with degree of mono-myelocytic cell density, and percentages of CD8+ T cells expressing T cell exhaustion markers. These data highlight the utility of in situ immune monitoring for patient stratification, and provide digital image processing pipelines (https://github.com/multiplexIHC/cppipe) to the community for examining immune complexity in precious tissue sections, where phenotype and tissue architecture are preserved to thus improve biomarker discovery and assessment. PMID:28380359

Molecular imaging and the unification of multilevel mechanisms and data in medical physics.

PubMed

Nikiforidis, George C; Sakellaropoulos, George C; Kagadis, George C

2008-08-01

Molecular imaging (MI) constitutes a recently developed approach of imaging, where modalities and agents have been reinvented and used in novel combinations in order to expose and measure biologic processes occurring at molecular and cellular levels. It is an approach that bridges the gap between modalities acquiring data from high (e.g., computed tomography, magnetic resonance imaging, and positron-emitting isotopes) and low (e.g., PCR, microarrays) levels of a biological organization. While data integration methodologies will lead to improved diagnostic and prognostic performance, interdisciplinary collaboration, triggered by MI, will result in a better perception of the underlying biological mechanisms. Toward the development of a unifying theory describing these mechanisms, medical physicists can formulate new hypotheses, provide the physical constraints bounding them, and consequently design appropriate experiments. Their new scientific and working environment calls for interventions in their syllabi to educate scientists with enhanced capabilities for holistic views and synthesis.

High-density, microsphere-based fiber optic DNA microarrays.

PubMed

Epstein, Jason R; Leung, Amy P K; Lee, Kyong Hoon; Walt, David R

2003-05-01

A high-density fiber optic DNA microarray has been developed consisting of oligonucleotide-functionalized, 3.1-microm-diameter microspheres randomly distributed on the etched face of an imaging fiber bundle. The fiber bundles are comprised of 6000-50000 fused optical fibers and each fiber terminates with an etched well. The microwell array is capable of housing complementary-sized microspheres, each containing thousands of copies of a unique oligonucleotide probe sequence. The array fabrication process results in random microsphere placement. Determining the position of microspheres in the random array requires an optical encoding scheme. This array platform provides many advantages over other array formats. The microsphere-stock suspension concentration added to the etched fiber can be controlled to provide inherent sensor redundancy. Examining identical microspheres has a beneficial effect on the signal-to-noise ratio. As other sequences of interest are discovered, new microsphere sensing elements can be added to existing microsphere pools and new arrays can be fabricated incorporating the new sequences without altering the existing detection capabilities. These microarrays contain the smallest feature sizes (3 microm) of any DNA array, allowing interrogation of extremely small sample volumes. Reducing the feature size results in higher local target molecule concentrations, creating rapid and highly sensitive assays. The microsphere array platform is also flexible in its applications; research has included DNA-protein interaction profiles, microbial strain differentiation, and non-labeled target interrogation with molecular beacons. Fiber optic microsphere-based DNA microarrays have a simple fabrication protocol enabling their expansion into other applications, such as single cell-based assays.

Sandwich ELISA Microarrays: Generating Reliable and Reproducible Assays for High-Throughput Screens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gonzalez, Rachel M.; Varnum, Susan M.; Zangar, Richard C.

The sandwich ELISA microarray is a powerful screening tool in biomarker discovery and validation due to its ability to simultaneously probe for multiple proteins in a miniaturized assay. The technical challenges of generating and processing the arrays are numerous. However, careful attention to possible pitfalls in the development of your antibody microarray assay can overcome these challenges. In this chapter, we describe in detail the steps that are involved in generating a reliable and reproducible sandwich ELISA microarray assay.

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton

PubMed Central

Muller, Jean; Mehlen, André; Vetter, Guillaume; Yatskou, Mikalai; Muller, Arnaud; Chalmel, Frédéric; Poch, Olivier; Friederich, Evelyne; Vallar, Laurent

2007-01-01

Background The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton. Results Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not. Conclusion Our data demonstrate that Actichip is a powerful alternative to commercial high density microarrays for cytoskeleton gene profiling in normal or pathological samples. Actichip is available upon request. PMID:17727702

Tissue microarrays and quantitative tissue-based image analysis as a tool for oncology biomarker and diagnostic development.

PubMed

Dolled-Filhart, Marisa P; Gustavson, Mark D

2012-11-01

Translational oncology has been improved by using tissue microarrays (TMAs), which facilitate biomarker analysis of large cohorts on a single slide. This has allowed for rapid analysis and validation of potential biomarkers for prognostic and predictive value, as well as for evaluation of biomarker prevalence. Coupled with quantitative analysis of immunohistochemical (IHC) staining, objective and standardized biomarker data from tumor samples can further advance companion diagnostic approaches for the identification of drug-responsive or resistant patient subpopulations. This review covers the advantages, disadvantages and applications of TMAs for biomarker research. Research literature and reviews of TMAs and quantitative image analysis methodology have been surveyed for this review (with an AQUA® analysis focus). Applications such as multi-marker diagnostic development and pathway-based biomarker subpopulation analyses are described. Tissue microarrays are a useful tool for biomarker analyses including prevalence surveys, disease progression assessment and addressing potential prognostic or predictive value. By combining quantitative image analysis with TMAs, analyses will be more objective and reproducible, allowing for more robust IHC-based diagnostic test development. Quantitative multi-biomarker IHC diagnostic tests that can predict drug response will allow for greater success of clinical trials for targeted therapies and provide more personalized clinical decision making.

Development and characterization of a disposable plastic microarray printhead.

PubMed

Griessner, Matthias; Hartig, Dave; Christmann, Alexander; Pohl, Carsten; Schellhase, Michaela; Ehrentreich-Förster, Eva

2011-06-01

During the last decade microarrays have become a powerful analytical tool. Commonly microarrays are produced in a non-contact manner using silicone printheads. However, silicone printheads are expensive and not able to be used as a disposable. Here, we show the development and functional characterization of 8-channel plastic microarray printheads that overcome both disadvantages of their conventional silicone counterparts. A combination of injection-molding and laser processing allows us to produce a high quantity of cheap, customizable and disposable microarray printheads. The use of plastics (e.g., polystyrene) minimizes the need for surface modifications required previously for proper printing results. Time-consuming regeneration processes, cleaning procedures and contaminations caused by residual samples are avoided. The utilization of plastic printheads for viscous liquids, such as cell suspensions or whole blood, is possible. Furthermore, functional parts within the plastic printhead (e.g., particle filters) can be included. Our printhead is compatible with commercially available TopSpot devices but provides additional economic and technical benefits as compared to conventional TopSpot printheads, while fulfilling all requirements demanded on the latter. All in all, this work describes how the field of traditional microarray spotting can be extended significantly by low cost plastic printheads.

Digital Microarrays: Single-Molecule Readout with Interferometric Detection of Plasmonic Nanorod Labels.

PubMed

Sevenler, Derin; Daaboul, George G; Ekiz Kanik, Fulya; Ünlü, Neşe Lortlar; Ünlü, M Selim

2018-05-21

DNA and protein microarrays are a high-throughput technology that allow the simultaneous quantification of tens of thousands of different biomolecular species. The mediocre sensitivity and limited dynamic range of traditional fluorescence microarrays compared to other detection techniques have been the technology's Achilles' heel and prevented their adoption for many biomedical and clinical diagnostic applications. Previous work to enhance the sensitivity of microarray readout to the single-molecule ("digital") regime have either required signal amplifying chemistry or sacrificed throughput, nixing the platform's primary advantages. Here, we report the development of a digital microarray which extends both the sensitivity and dynamic range of microarrays by about 3 orders of magnitude. This technique uses functionalized gold nanorods as single-molecule labels and an interferometric scanner which can rapidly enumerate individual nanorods by imaging them with a 10× objective lens. This approach does not require any chemical signal enhancement such as silver deposition and scans arrays with a throughput similar to commercial fluorescence scanners. By combining single-nanoparticle enumeration and ensemble measurements of spots when the particles are very dense, this system achieves a dynamic range of about 6 orders of magnitude directly from a single scan. As a proof-of-concept digital protein microarray assay, we demonstrated detection of hepatitis B virus surface antigen in buffer with a limit of detection of 3.2 pg/mL. More broadly, the technique's simplicity and high-throughput nature make digital microarrays a flexible platform technology with a wide range of potential applications in biomedical research and clinical diagnostics.

Workflows for microarray data processing in the Kepler environment.

PubMed

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

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

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

2013-10-10

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.

DNA microarrays and their use in dermatology.

PubMed

Mlakar, Vid; Glavac, Damjan

2007-03-01

Multiple different DNA microarray technologies are available on the market today. They can be used for studying either DNA or RNA with the purpose of identifying and explaining the role of genes involved in different processes. This paper reviews different DNA microarray platforms available for such studies and their usage in cases of malignant melanomas, psoriasis, and exposure of keratinocytes and melanocytes to UV illumination.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid

2007-10-18

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

PubMed Central

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid

2007-01-01

Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480

Estimating gene function with least squares nonnegative matrix factorization.

PubMed

Wang, Guoli; Ochs, Michael F

2007-01-01

Nonnegative matrix factorization is a machine learning algorithm that has extracted information from data in a number of fields, including imaging and spectral analysis, text mining, and microarray data analysis. One limitation with the method for linking genes through microarray data in order to estimate gene function is the high variance observed in transcription levels between different genes. Least squares nonnegative matrix factorization uses estimates of the uncertainties on the mRNA levels for each gene in each condition, to guide the algorithm to a local minimum in normalized chi2, rather than a Euclidean distance or divergence between the reconstructed data and the data itself. Herein, application of this method to microarray data is demonstrated in order to predict gene function.

A highly oriented hybrid microarray modified electrode fabricated by a template-free method for ultrasensitive electrochemical DNA recognition

NASA Astrophysics Data System (ADS)

Shi, Lei; Chu, Zhenyu; Dong, Xueliang; Jin, Wanqin; Dempsey, Eithne

2013-10-01

Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors.Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors. Electronic supplementary information (ESI) available: Four-probe method for determining the conductivity of the hybrid crystal (Fig. S1); stability comparisons of the hybrid films (Fig. S2); FESEM images of the hybrid microarray (Fig. S3); electrochemical characterizations of the hybrid films (Fig. S4); DFT simulations (Fig. S5); cross-sectional FESEM image of the hybrid microarray (Fig. S6); regeneration and stability tests of the DNA biosensor (Fig. S7). See DOI: 10.1039/c3nr03097k

New diagnostics for melanoma detection: from artificial intelligence to RNA microarrays.

PubMed

Ahlgrimm-Siess, Verena; Laimer, Martin; Arzberger, Edith; Hofmann-Wellenhof, Rainer

2012-07-01

Early detection of melanoma remains crucial to ensuring a favorable prognosis. Dermoscopy and total body photography are well-established noninvasive aids that increase the diagnostic accuracy of dermatologists in their daily routine, beyond that of a naked-eye examination. New noninvasive diagnostic techniques, such as reflectance confocal microscopy, multispectral digital imaging and RNA microarrays, are currently being investigated to determine their utility for melanoma detection. This review presents emerging technologies for noninvasive melanoma diagnosis, and discusses their advantages and limitations.

Micro-Analyzer: automatic preprocessing of Affymetrix microarray data.

PubMed

Guzzi, Pietro Hiram; Cannataro, Mario

2013-08-01

A current trend in genomics is the investigation of the cell mechanism using different technologies, in order to explain the relationship among genes, molecular processes and diseases. For instance, the combined use of gene-expression arrays and genomic arrays has been demonstrated as an effective instrument in clinical practice. Consequently, in a single experiment different kind of microarrays may be used, resulting in the production of different types of binary data (images and textual raw data). The analysis of microarray data requires an initial preprocessing phase, that makes raw data suitable for use on existing analysis platforms, such as the TIGR M4 (TM4) Suite. An additional challenge to be faced by emerging data analysis platforms is the ability to treat in a combined way those different microarray formats coupled with clinical data. In fact, resulting integrated data may include both numerical and symbolic data (e.g. gene expression and SNPs regarding molecular data), as well as temporal data (e.g. the response to a drug, time to progression and survival rate), regarding clinical data. Raw data preprocessing is a crucial step in analysis but is often performed in a manual and error prone way using different software tools. Thus novel, platform independent, and possibly open source tools enabling the semi-automatic preprocessing and annotation of different microarray data are needed. The paper presents Micro-Analyzer (Microarray Analyzer), a cross-platform tool for the automatic normalization, summarization and annotation of Affymetrix gene expression and SNP binary data. It represents the evolution of the μ-CS tool, extending the preprocessing to SNP arrays that were not allowed in μ-CS. The Micro-Analyzer is provided as a Java standalone tool and enables users to read, preprocess and analyse binary microarray data (gene expression and SNPs) by invoking TM4 platform. It avoids: (i) the manual invocation of external tools (e.g. the Affymetrix Power Tools), (ii) the manual loading of preprocessing libraries, and (iii) the management of intermediate files, such as results and metadata. Micro-Analyzer users can directly manage Affymetrix binary data without worrying about locating and invoking the proper preprocessing tools and chip-specific libraries. Moreover, users of the Micro-Analyzer tool can load the preprocessed data directly into the well-known TM4 platform, extending in such a way also the TM4 capabilities. Consequently, Micro Analyzer offers the following advantages: (i) it reduces possible errors in the preprocessing and further analysis phases, e.g. due to the incorrect choice of parameters or due to the use of old libraries, (ii) it enables the combined and centralized pre-processing of different arrays, (iii) it may enhance the quality of further analysis by storing the workflow, i.e. information about the preprocessing steps, and (iv) finally Micro-Analzyer is freely available as a standalone application at the project web site http://sourceforge.net/projects/microanalyzer/. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

cDNA Microarray Screening in Food Safety

PubMed Central

ROY, SASHWATI; SEN, CHANDAN K

2009-01-01

The cDNA microarray technology and related bioinformatics tools presents a wide range of novel application opportunities. The technology may be productively applied to address food safety. In this mini-review article, we present an update highlighting the late breaking discoveries that demonstrate the vitality of cDNA microarray technology as a tool to analyze food safety with reference to microbial pathogens and genetically modified foods. In order to bring the microarray technology to mainstream food safety, it is important to develop robust user-friendly tools that may be applied in a field setting. In addition, there needs to be a standardized process for regulatory agencies to interpret and act upon microarray-based data. The cDNA microarray approach is an emergent technology in diagnostics. Its values lie in being able to provide complimentary molecular insight when employed in addition to traditional tests for food safety, as part of a more comprehensive battery of tests. PMID:16466843

Fiber-optic microarray for simultaneous detection of multiple harmful algal bloom species.

PubMed

Ahn, Soohyoun; Kulis, David M; Erdner, Deana L; Anderson, Donald M; Walt, David R

2006-09-01

Harmful algal blooms (HABs) are a serious threat to coastal resources, causing a variety of impacts on public health, regional economies, and ecosystems. Plankton analysis is a valuable component of many HAB monitoring and research programs, but the diversity of plankton poses a problem in discriminating toxic from nontoxic species using conventional detection methods. Here we describe a sensitive and specific sandwich hybridization assay that combines fiber-optic microarrays with oligonucleotide probes to detect and enumerate the HAB species Alexandrium fundyense, Alexandrium ostenfeldii, and Pseudo-nitzschia australis. Microarrays were prepared by loading oligonucleotide probe-coupled microspheres (diameter, 3 mum) onto the distal ends of chemically etched imaging fiber bundles. Hybridization of target rRNA from HAB cells to immobilized probes on the microspheres was visualized using Cy3-labeled secondary probes in a sandwich-type assay format. We applied these microarrays to the detection and enumeration of HAB cells in both cultured and field samples. Our study demonstrated a detection limit of approximately 5 cells for all three target organisms within 45 min, without a separate amplification step, in both sample types. We also developed a multiplexed microarray to detect the three HAB species simultaneously, which successfully detected the target organisms, alone and in combination, without cross-reactivity. Our study suggests that fiber-optic microarrays can be used for rapid and sensitive detection and potential enumeration of HAB species in the environment.

Use of diagnostic accuracy as a metric for evaluating laboratory proficiency with microarray assays using mixed-tissue RNA reference samples.

PubMed

Pine, P S; Boedigheimer, M; Rosenzweig, B A; Turpaz, Y; He, Y D; Delenstarr, G; Ganter, B; Jarnagin, K; Jones, W D; Reid, L H; Thompson, K L

2008-11-01

Effective use of microarray technology in clinical and regulatory settings is contingent on the adoption of standard methods for assessing performance. The MicroArray Quality Control project evaluated the repeatability and comparability of microarray data on the major commercial platforms and laid the groundwork for the application of microarray technology to regulatory assessments. However, methods for assessing performance that are commonly applied to diagnostic assays used in laboratory medicine remain to be developed for microarray assays. A reference system for microarray performance evaluation and process improvement was developed that includes reference samples, metrics and reference datasets. The reference material is composed of two mixes of four different rat tissue RNAs that allow defined target ratios to be assayed using a set of tissue-selective analytes that are distributed along the dynamic range of measurement. The diagnostic accuracy of detected changes in expression ratios, measured as the area under the curve from receiver operating characteristic plots, provides a single commutable value for comparing assay specificity and sensitivity. The utility of this system for assessing overall performance was evaluated for relevant applications like multi-laboratory proficiency testing programs and single-laboratory process drift monitoring. The diagnostic accuracy of detection of a 1.5-fold change in signal level was found to be a sensitive metric for comparing overall performance. This test approaches the technical limit for reliable discrimination of differences between two samples using this technology. We describe a reference system that provides a mechanism for internal and external assessment of laboratory proficiency with microarray technology and is translatable to performance assessments on other whole-genome expression arrays used for basic and clinical research.

Novel instrumentation of multispectral imaging technology for detecting tissue abnormity

NASA Astrophysics Data System (ADS)

Yi, Dingrong; Kong, Linghua

2012-10-01

Multispectral imaging is becoming a powerful tool in a wide range of biological and clinical studies by adding spectral, spatial and temporal dimensions to visualize tissue abnormity and the underlying biological processes. A conventional spectral imaging system includes two physically separated major components: a band-passing selection device (such as liquid crystal tunable filter and diffraction grating) and a scientific-grade monochromatic camera, and is expensive and bulky. Recently micro-arrayed narrow-band optical mosaic filter was invented and successfully fabricated to reduce the size and cost of multispectral imaging devices in order to meet the clinical requirement for medical diagnostic imaging applications. However the challenging issue of how to integrate and place the micro filter mosaic chip to the targeting focal plane, i.e., the imaging sensor, of an off-shelf CMOS/CCD camera is not reported anywhere. This paper presents the methods and results of integrating such a miniaturized filter with off-shelf CMOS imaging sensors to produce handheld real-time multispectral imaging devices for the application of early stage pressure ulcer (ESPU) detection. Unlike conventional multispectral imaging devices which are bulky and expensive, the resulting handheld real-time multispectral ESPU detector can produce multiple images at different center wavelengths with a single shot, therefore eliminates the image registration procedure required by traditional multispectral imaging technologies.

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

A metadata-aware application for remote scoring and exchange of tissue microarray images

PubMed Central

2013-01-01

Background The use of tissue microarrays (TMA) and advances in digital scanning microscopy has enabled the collection of thousands of tissue images. There is a need for software tools to annotate, query and share this data amongst researchers in different physical locations. Results We have developed an open source web-based application for remote scoring of TMA images, which exploits the value of Microsoft Silverlight Deep Zoom to provide a intuitive interface for zooming and panning around digital images. We use and extend existing XML-based standards to ensure that the data collected can be archived and that our system is interoperable with other standards-compliant systems. Conclusion The application has been used for multi-centre scoring of TMA slides composed of tissues from several Phase III breast cancer trials and ten different studies participating in the International Breast Cancer Association Consortium (BCAC). The system has enabled researchers to simultaneously score large collections of TMA and export the standardised data to integrate with pathological and clinical outcome data, thereby facilitating biomarker discovery. PMID:23635078

A curated collection of tissue microarray images and clinical outcome data of prostate cancer patients

PubMed Central

Zhong, Qing; Guo, Tiannan; Rechsteiner, Markus; Rüschoff, Jan H.; Rupp, Niels; Fankhauser, Christian; Saba, Karim; Mortezavi, Ashkan; Poyet, Cédric; Hermanns, Thomas; Zhu, Yi; Moch, Holger; Aebersold, Ruedi; Wild, Peter J.

2017-01-01

Microscopy image data of human cancers provide detailed phenotypes of spatially and morphologically intact tissues at single-cell resolution, thus complementing large-scale molecular analyses, e.g., next generation sequencing or proteomic profiling. Here we describe a high-resolution tissue microarray (TMA) image dataset from a cohort of 71 prostate tissue samples, which was hybridized with bright-field dual colour chromogenic and silver in situ hybridization probes for the tumour suppressor gene PTEN. These tissue samples were digitized and supplemented with expert annotations, clinical information, statistical models of PTEN genetic status, and computer source codes. For validation, we constructed an additional TMA dataset for 424 prostate tissues, hybridized with FISH probes for PTEN, and performed survival analysis on a subset of 339 radical prostatectomy specimens with overall, disease-specific and recurrence-free survival (maximum 167 months). For application, we further produced 6,036 image patches derived from two whole slides. Our curated collection of prostate cancer data sets provides reuse potential for both biomedical and computational studies. PMID:28291248

Towards MRI microarrays.

PubMed

Hall, Andrew; Mundell, Victoria J; Blanco-Andujar, Cristina; Bencsik, Martin; McHale, Glen; Newton, Michael I; Cave, Gareth W V

2010-04-14

Superparamagnetic iron oxide nanometre scale particles have been utilised as contrast agents to image staked target binding oligonucleotide arrays using MRI to correlate the signal intensity and T(2)* relaxation times in different NMR fluids.

Probabilistic segmentation and intensity estimation for microarray images.

PubMed

Gottardo, Raphael; Besag, Julian; Stephens, Matthew; Murua, Alejandro

2006-01-01

We describe a probabilistic approach to simultaneous image segmentation and intensity estimation for complementary DNA microarray experiments. The approach overcomes several limitations of existing methods. In particular, it (a) uses a flexible Markov random field approach to segmentation that allows for a wider range of spot shapes than existing methods, including relatively common 'doughnut-shaped' spots; (b) models the image directly as background plus hybridization intensity, and estimates the two quantities simultaneously, avoiding the common logical error that estimates of foreground may be less than those of the corresponding background if the two are estimated separately; and (c) uses a probabilistic modeling approach to simultaneously perform segmentation and intensity estimation, and to compute spot quality measures. We describe two approaches to parameter estimation: a fast algorithm, based on the expectation-maximization and the iterated conditional modes algorithms, and a fully Bayesian framework. These approaches produce comparable results, and both appear to offer some advantages over other methods. We use an HIV experiment to compare our approach to two commercial software products: Spot and Arrayvision.

CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

PubMed

Arnold, Christian; Externbrink, Fabian; Hackermüller, Jörg; Reiche, Kristin

2014-11-10

Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de. Copyright © 2014 Elsevier B.V. All rights reserved.

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

The use of open source bioinformatics tools to dissect transcriptomic data.

PubMed

Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

2012-01-01

Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

High quality epoxysilane substrate for clinical multiplex serodiagnostic proteomic microarrays

NASA Astrophysics Data System (ADS)

Ewart, Tom; Carmichael, Stuart; Lea, Peter

2005-09-01

Polylysine and aminopropylsilane treated glass comprised the majority of substrates employed in first generation genetic microarray substrates. Second generation single stranded long oligo libraries with amino termini provided for controlled terminal specific attachment, and rationally designed unique sequence libraries with normalized melting temperatures. These libraries benefit from active covalent coupling surfaces such as Epoxysilane. The latter's oxime ring shows versatile reactivity with amino-, thiol- and hydroxyl- groups thus encompassing small molecule, oligo and proteomic microarray applications. Batch-to-batch production uniformity supports entry of the Epoxysilane process into clinical diagnostics. We carried out multiple print runs of 21 clinically relevant bacterial and viral antigens at optimized concentrations, plus human IgG and IgM standards in triplicate on multiple batches of Epoxysilane substrates. A set of 45 patient sera were assayed in a 35 minute protocol using 10 microliters per array in a capillary-fill format (15 minute serum incubation, wash, 15 minute incubation with Cy3-labeled anti-hIgG plus Dy647-labeled anti-hIgM, final wash). The LOD (3 SD above background) was better than 1 microgram/ml for IgG, and standard curves were regular and monotonically increasing over the range 0 to 1000 micrograms/ml. Ninety-five percent of the CVs for the standards were under 10%, and 90% percent of CVs for antigen responses were under 10% across all batches of Epoxysilane and print runs. In addition, where SDs are larger than expected, microarray images may be readily reviewed for quality control purposes and pin misprints quickly identified. In order to determine the influence of stirring on sensitivity and speed of the microarray assay, we printed 10 common ToRCH antigens (H. pylori, T. gondii, Rubella, Rubeola, C. trachomatis, Herpes 1 and 2, CMV, C. jejuni, and EBV) in Epoxysilane-activated slide-wells. Anti-IgG-Cy3 direct binding to printed IgG calibration spots could be detected (3 x LOD) above background at 100 pg/ml (0.13 femtomoles sample content) in a 10 minute incubation. The LOD for detection of serum anti-H. pylori antibody level was 9 ng/ml in the same incubation time.

Emergent FDA biodefense issues for microarray technology: process analytical technology.

PubMed

Weinberg, Sandy

2004-11-01

A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver.

Simplified Microarray Technique for Identifying mRNA in Rare Samples

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

Two simplified methods of identifying messenger ribonucleic acid (mRNA), and compact, low-power apparatuses to implement the methods, are at the proof-of-concept stage of development. These methods are related to traditional methods based on hybridization of nucleic acid, but whereas the traditional methods must be practiced in laboratory settings, these methods could be practiced in field settings. Hybridization of nucleic acid is a powerful technique for detection of specific complementary nucleic acid sequences, and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes. A traditional microarray study entails at least the following six steps: 1. Purification of cellular RNA, 2. Amplification of complementary deoxyribonucleic acid [cDNA] by polymerase chain reaction (PCR), 3. Labeling of cDNA with fluorophores of Cy3 (a green cyanine dye) and Cy5 (a red cyanine dye), 4. Hybridization to a microarray chip, 5. Fluorescence scanning the array(s) with dual excitation wavelengths, and 6. Analysis of the resulting images. This six-step procedure must be performed in a laboratory because it requires bulky equipment.

Minimum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE).

PubMed

Deutsch, Eric W; Ball, Catherine A; Berman, Jules J; Bova, G Steven; Brazma, Alvis; Bumgarner, Roger E; Campbell, David; Causton, Helen C; Christiansen, Jeffrey H; Daian, Fabrice; Dauga, Delphine; Davidson, Duncan R; Gimenez, Gregory; Goo, Young Ah; Grimmond, Sean; Henrich, Thorsten; Herrmann, Bernhard G; Johnson, Michael H; Korb, Martin; Mills, Jason C; Oudes, Asa J; Parkinson, Helen E; Pascal, Laura E; Pollet, Nicolas; Quackenbush, John; Ramialison, Mirana; Ringwald, Martin; Salgado, David; Sansone, Susanna-Assunta; Sherlock, Gavin; Stoeckert, Christian J; Swedlow, Jason; Taylor, Ronald C; Walashek, Laura; Warford, Anthony; Wilkinson, David G; Zhou, Yi; Zon, Leonard I; Liu, Alvin Y; True, Lawrence D

2008-03-01

One purpose of the biomedical literature is to report results in sufficient detail that the methods of data collection and analysis can be independently replicated and verified. Here we present reporting guidelines for gene expression localization experiments: the minimum information specification for in situ hybridization and immunohistochemistry experiments (MISFISHIE). MISFISHIE is modeled after the Minimum Information About a Microarray Experiment (MIAME) specification for microarray experiments. Both guidelines define what information should be reported without dictating a format for encoding that information. MISFISHIE describes six types of information to be provided for each experiment: experimental design, biomaterials and treatments, reporters, staining, imaging data and image characterizations. This specification has benefited the consortium within which it was developed and is expected to benefit the wider research community. We welcome feedback from the scientific community to help improve our proposal.

BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems.

PubMed

Mcclenny, Levi D; Imani, Mahdi; Braga-Neto, Ulisses M

2017-11-25

Gene regulatory networks govern the function of key cellular processes, such as control of the cell cycle, response to stress, DNA repair mechanisms, and more. Boolean networks have been used successfully in modeling gene regulatory networks. In the Boolean network model, the transcriptional state of each gene is represented by 0 (inactive) or 1 (active), and the relationship among genes is represented by logical gates updated at discrete time points. However, the Boolean gene states are never observed directly, but only indirectly and incompletely through noisy measurements based on expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays. The Partially-Observed Boolean Dynamical System (POBDS) signal model is distinct from other deterministic and stochastic Boolean network models in removing the requirement of a directly observable Boolean state vector and allowing uncertainty in the measurement process, addressing the scenario encountered in practice in transcriptomic analysis. BoolFilter is an R package that implements the POBDS model and associated algorithms for state and parameter estimation. It allows the user to estimate the Boolean states, network topology, and measurement parameters from time series of transcriptomic data using exact and approximated (particle) filters, as well as simulate the transcriptomic data for a given Boolean network model. Some of its infrastructure, such as the network interface, is the same as in the previously published R package for Boolean Networks BoolNet, which enhances compatibility and user accessibility to the new package. We introduce the R package BoolFilter for Partially-Observed Boolean Dynamical Systems (POBDS). The BoolFilter package provides a useful toolbox for the bioinformatics community, with state-of-the-art algorithms for simulation of time series transcriptomic data as well as the inverse process of system identification from data obtained with various expression technologies such as cDNA microarrays, RNA-Seq, and cell imaging-based assays.

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.

The COST Action IC0604 "Telepathology Network in Europe" (EURO-TELEPATH).

PubMed

García-Rojo, Marcial; Gonçalves, Luís; Blobel, Bernd

2012-01-01

The COST Action IC0604 "Telepathology Network in Europe" (EURO-TELEPATH) is a European COST Action that has been running from 2007 to 2011. COST Actions are funded by the COST (European Cooperation in the field of Scientific and Technical Research) Agency, supported by the Seventh Framework Programme for Research and Technological Development (FP7), of the European Union. EURO-TELEPATH's main objectives were evaluating and validating the common technological framework and communication standards required to access, transmit and manage digital medical records by pathologists and other medical professionals in a networked environment. The project was organized in four working groups. orking Group 1 "Business modeling in pathology" has designed main pathology processes - Frozen Study, Formalin Fixed Specimen Study, Telepathology, Cytology, and Autopsy -using Business Process Modeling Notation (BPMN). orking Group 2 "Informatics standards in pathology" has been dedicated to promoting the development and application of informatics standards in pathology, collaborating with Integrating the Healthcare Enterprise (IHE), Digital Imaging and Communications in Medicine (DICOM), Health Level Seven (HL7), and other standardization bodies. Working Group 3 "Images: Analysis, Processing, Retrieval and Management" worked on the use of virtual or digital slides that are fostering the use of image processing and analysis in pathology not only for research purposes, but also in daily practice. Working Group 4 "Technology and Automation in Pathology" was focused on studying the adequacy of current existing technical solutions, including, e.g., the quality of images obtained by slide scanners, or the efficiency of image analysis applications. Major outcome of this action are the collaboration with international health informatics standardization bodies to foster the development of standards for digital pathology, offering a new approach for workflow analysis, based in business process modeling. Health terminology standardization research has become a topic of high interest. Future research work should focus on standardization of automatic image analysis and tissue microarrays imaging.

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

PubMed Central

Rosenzweig, Barry A; Pine, P Scott; Domon, Olen E; Morris, Suzanne M; Chen, James J; Sistare, Frank D

2004-01-01

A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. PMID:15033598

Improvement in the amine glass platform by bubbling method for a DNA microarray

PubMed Central

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool. PMID:26468293

Improvement in the amine glass platform by bubbling method for a DNA microarray.

PubMed

Jee, Seung Hyun; Kim, Jong Won; Lee, Ji Hyeong; Yoon, Young Soo

2015-01-01

A glass platform with high sensitivity for sexually transmitted diseases microarray is described here. An amino-silane-based self-assembled monolayer was coated on the surface of a glass platform using a novel bubbling method. The optimized surface of the glass platform had highly uniform surface modifications using this method, as well as improved hybridization properties with capture probes in the DNA microarray. On the basis of these results, the improved glass platform serves as a highly reliable and optimal material for the DNA microarray. Moreover, in this study, we demonstrated that our glass platform, manufactured by utilizing the bubbling method, had higher uniformity, shorter processing time, lower background signal, and higher spot signal than the platforms manufactured by the general dipping method. The DNA microarray manufactured with a glass platform prepared using bubbling method can be used as a clinical diagnostic tool.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling.

PubMed

Yuan, Yinyin; Failmezger, Henrik; Rueda, Oscar M; Ali, H Raza; Gräf, Stefan; Chin, Suet-Feung; Schwarz, Roland F; Curtis, Christina; Dunning, Mark J; Bardwell, Helen; Johnson, Nicola; Doyle, Sarah; Turashvili, Gulisa; Provenzano, Elena; Aparicio, Sam; Caldas, Carlos; Markowetz, Florian

2012-10-24

Solid tumors are heterogeneous tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Furthermore, tissue architecture is generally not reflected in molecular assays, rendering this rich information underused. To address these challenges, we developed a computational approach based on standard hematoxylin and eosin-stained tissue sections and demonstrated its power in a discovery and validation cohort of 323 and 241 breast tumors, respectively. To deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy number profiles between samples. We next devised a predictor for survival in estrogen receptor-negative breast cancer that integrated both image-based and gene expression analyses and significantly outperformed classifiers that use single data types, such as microarray expression signatures. Image processing also allowed us to describe and validate an independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative, image-based method could benefit any large-scale cancer study by refining and complementing molecular assays of tumor samples.

Microarray analysis of gene expression profiles in ripening pineapple fruits.

PubMed

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

2012-12-18

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

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 molecular basis of pineapple fruit ripening and non-climacteric fruit ripening in general. PMID:23245313

Fabrication of Carbohydrate Microarrays by Boronate Formation.

PubMed

Adak, Avijit K; Lin, Ting-Wei; Li, Ben-Yuan; Lin, Chun-Cheng

2017-01-01

The interactions between soluble carbohydrates and/or surface displayed glycans and protein receptors are essential to many biological processes and cellular recognition events. Carbohydrate microarrays provide opportunities for high-throughput quantitative analysis of carbohydrate-protein interactions. Over the past decade, various techniques have been implemented for immobilizing glycans on solid surfaces in a microarray format. Herein, we describe a detailed protocol for fabricating carbohydrate microarrays that capitalizes on the intrinsic reactivity of boronic acid toward carbohydrates to form stable boronate diesters. A large variety of unprotected carbohydrates ranging in structure from simple disaccharides and trisaccharides to considerably more complex human milk and blood group (oligo)saccharides have been covalently immobilized in a single step on glass slides, which were derivatized with high-affinity boronic acid ligands. The immobilized ligands in these microarrays maintain the receptor-binding activities including those of lectins and antibodies according to the structures of their pendant carbohydrates for rapid analysis of a number of carbohydrate-recognition events within 30 h. This method facilitates the direct construction of otherwise difficult to obtain carbohydrate microarrays from underivatized glycans.

Decentralized Data Sharing of Tissue Microarrays for Investigative Research in Oncology

PubMed Central

Chen, Wenjin; Schmidt, Cristina; Parashar, Manish; Reiss, Michael; Foran, David J.

2007-01-01

Tissue microarray technology (TMA) is a relatively new approach for efficiently and economically assessing protein and gene expression across large ensembles of tissue specimens. Tissue microarray technology holds great potential for reducing the time and cost associated with conducting research in tissue banking, proteomics, and outcome studies. However, the sheer volume of images and other data generated from even limited studies involving tissue microarrays quickly approach the processing capacity and resources of a division or department. This challenge is compounded by the fact that large-scale projects in several areas of modern research rely upon multi-institutional efforts in which investigators and resources are spread out over multiple campuses, cities, and states. To address some of the data management issues several leading institutions have begun to develop their own “in-house” systems, independently, but such data will be only minimally useful if it isn’t accessible to others in the scientific community. Investigators at different institutions studying the same or related disorders might benefit from the synergy of sharing results. To facilitate sharing of TMA data across different database implementations, the Technical Standards Committee of the Association for Pathology Informatics organized workshops in efforts to establish a standardized TMA data exchange specification. The focus of our research does not relate to the establishment of standards for exchange, but rather builds on these efforts and concentrates on the design, development and deployment of a decentralized collaboratory for the unsupervised characterization, and seamless and secure discovery and sharing of TMA data. Specifically, we present a self-organizing, peer-to-peer indexing and discovery infrastructure for quantitatively assessing digitized TMA’s. The system utilizes a novel, optimized decentralized search engine that supports flexible querying, while guaranteeing that once information has been stored in the system, it will be found with bounded costs. PMID:19081778

A 256 pixel magnetoresistive biosensor microarray in 0.18μm CMOS

PubMed Central

Hall, Drew A.; Gaster, Richard S.; Makinwa, Kofi; Wang, Shan X.; Murmann, Boris

2014-01-01

Magnetic nanotechnologies have shown significant potential in several areas of nanomedicine such as imaging, therapeutics, and early disease detection. Giant magnetoresistive spin-valve (GMR SV) sensors coupled with magnetic nanotags (MNTs) possess great promise as ultra-sensitive biosensors for diagnostics. We report an integrated sensor interface for an array of 256 GMR SV biosensors designed in 0.18 μm CMOS. Arranged like an imager, each of the 16 column level readout channels contains an analog front- end and a compact ΣΔ modulator (0.054 mm2) with 84 dB of dynamic range and an input referred noise of 49 nT/√Hz. Performance is demonstrated through detection of an ovarian cancer biomarker, secretory leukocyte peptidase inhibitor (SLPI), spiked at concentrations as low as 10 fM. This system is designed as a replacement for optical protein microarrays while also providing real-time kinetics monitoring. PMID:24761029

Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE)

PubMed Central

Deutsch, Eric W; Ball, Catherine A; Berman, Jules J; Bova, G Steven; Brazma, Alvis; Bumgarner, Roger E; Campbell, David; Causton, Helen C; Christiansen, Jeffrey H; Daian, Fabrice; Dauga, Delphine; Davidson, Duncan R; Gimenez, Gregory; Goo, Young Ah; Grimmond, Sean; Henrich, Thorsten; Herrmann, Bernhard G; Johnson, Michael H; Korb, Martin; Mills, Jason C; Oudes, Asa J; Parkinson, Helen E; Pascal, Laura E; Pollet, Nicolas; Quackenbush, John; Ramialison, Mirana; Ringwald, Martin; Salgado, David; Sansone, Susanna-Assunta; Sherlock, Gavin; Stoeckert, Christian J; Swedlow, Jason; Taylor, Ronald C; Walashek, Laura; Warford, Anthony; Wilkinson, David G; Zhou, Yi; Zon, Leonard I; Liu, Alvin Y; True, Lawrence D

2015-01-01

One purpose of the biomedical literature is to report results in sufficient detail so that the methods of data collection and analysis can be independently replicated and verified. Here we present for consideration a minimum information specification for gene expression localization experiments, called the “Minimum Information Specification For In Situ Hybridization and Immunohistochemistry Experiments (MISFISHIE)”. It is modelled after the MIAME (Minimum Information About a Microarray Experiment) specification for microarray experiments. Data specifications like MIAME and MISFISHIE specify the information content without dictating a format for encoding that information. The MISFISHIE specification describes six types of information that should be provided for each experiment: Experimental Design, Biomaterials and Treatments, Reporters, Staining, Imaging Data, and Image Characterizations. This specification has benefited the consortium within which it was initially developed and is expected to benefit the wider research community. We welcome feedback from the scientific community to help improve our proposal. PMID:18327244

Design of an ultrasonic micro-array for near field sensing during retinal microsurgery.

PubMed

Clarke, Clyde; Etienne-Cummings, Ralph

2006-01-01

A method for obtaining the optimal and specific sensor parameters for a tool-tip mountable ultrasonic transducer micro-array is presented. The ultrasonic transducer array sensor parameters, such as frequency of operation, element size, inter-element spacing, number of elements and transducer geometry are obtained using a quadratic programming method to obtain a maximum directivity while being constrained to a total array size of 4 mm2 and the required resolution for retinal imaging. The technique is used to design a uniformly spaced NxN transducer array that is capable of resolving structures in the retina that are as small as 2 microm from a distance of 100 microm. The resultant 37x37 array of 16 microm transducers with 26 microm spacing will be realized as a Capacitive Micromachined Ultrasonic Transducer (CMUT) array and used for imaging and robotic guidance during retinal microsurgery.

Microarray analysis of gene expression patterns in the leaf during potato tuberization in the potato somatic hybrid Solanum tuberosum and Solanum etuberosum.

PubMed

Tiwari, Jagesh Kumar; Devi, Sapna; Sundaresha, S; Chandel, Poonam; Ali, Nilofer; Singh, Brajesh; Bhardwaj, Vinay; Singh, Bir Pal

2015-06-01

Genes involved in photoassimilate partitioning and changes in hormonal balance are important for potato tuberization. In the present study, we investigated gene expression patterns in the tuber-bearing potato somatic hybrid (E1-3) and control non-tuberous wild species Solanum etuberosum (Etb) by microarray. Plants were grown under controlled conditions and leaves were collected at eight tuber developmental stages for microarray analysis. A t-test analysis identified a total of 468 genes (94 up-regulated and 374 down-regulated) that were statistically significant (p ≤ 0.05) and differentially expressed in E1-3 and Etb. Gene Ontology (GO) characterization of the 468 genes revealed that 145 were annotated and 323 were of unknown function. Further, these 145 genes were grouped based on GO biological processes followed by molecular function and (or) PGSC description into 15 gene sets, namely (1) transport, (2) metabolic process, (3) biological process, (4) photosynthesis, (5) oxidation-reduction, (6) transcription, (7) translation, (8) binding, (9) protein phosphorylation, (10) protein folding, (11) ubiquitin-dependent protein catabolic process, (12) RNA processing, (13) negative regulation of protein, (14) methylation, and (15) mitosis. RT-PCR analysis of 10 selected highly significant genes (p ≤ 0.01) confirmed the microarray results. Overall, we show that candidate genes induced in leaves of E1-3 were implicated in tuberization processes such as transport, carbohydrate metabolism, phytohormones, and transcription/translation/binding functions. Hence, our results provide an insight into the candidate genes induced in leaf tissues during tuberization in E1-3.

Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion.

PubMed

Steger, Doris; Berry, David; Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.

Systematic Spatial Bias in DNA Microarray Hybridization Is Caused by Probe Spot Position-Dependent Variability in Lateral Diffusion

PubMed Central

Haider, Susanne; Horn, Matthias; Wagner, Michael; Stocker, Roman; Loy, Alexander

2011-01-01

Background The hybridization of nucleic acid targets with surface-immobilized probes is a widely used assay for the parallel detection of multiple targets in medical and biological research. Despite its widespread application, DNA microarray technology still suffers from several biases and lack of reproducibility, stemming in part from an incomplete understanding of the processes governing surface hybridization. In particular, non-random spatial variations within individual microarray hybridizations are often observed, but the mechanisms underpinning this positional bias remain incompletely explained. Methodology/Principal Findings This study identifies and rationalizes a systematic spatial bias in the intensity of surface hybridization, characterized by markedly increased signal intensity of spots located at the boundaries of the spotted areas of the microarray slide. Combining observations from a simplified single-probe block array format with predictions from a mathematical model, the mechanism responsible for this bias is found to be a position-dependent variation in lateral diffusion of target molecules. Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias. Conclusions Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization. PMID:21858215

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

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

permGPU: Using graphics processing units in RNA microarray association studies.

PubMed

Shterev, Ivo D; Jung, Sin-Ho; George, Stephen L; Owzar, Kouros

2010-06-16

Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Molecular characterization of Coriolus versicolor PSP-induced apoptosis in human promyelotic leukemic HL-60 cells using cDNA microarray.

PubMed

Zeng, Fanya; Hon, Chung-Chau; Sit, Wai-Hung; Chow, Ken Yan-Ching; Hui, Raymond Kin-Hi; Law, Ivy Ka-Man; Ng, Victor Wai-Lap; Yang, Xiao-Tong; Leung, Frederick Chi-Ching; Wan, Jennifer Man-Fan

2005-08-01

Proteins and peptide bound polysaccharides (PSP) extracted from Basidiomycetous fungi are widely used in cancer immunotherapy and recently demonstrated to induce apoptosis in cancer cells in vitro. In order to provide the molecular pharmacological mechanisms of PSP on human cancer cells, we investigated the gene expression profiles of PSP-treated apoptotic human promyelotic leukemic HL-60 cells using ResGen 40k IMAGE printed cDNA microarray. In total 378 and 111 transcripts were identified as differentially expressed in the apoptotic cells by at least a factor of 2 or 3, respectively. Our data show that PSP-induced apoptosis in HL-60 cells might be mediated by up-regulation of early transcription factors such as AP-1, EGR1, IER2 and IER5, and down-regulation of NF-kappaB transcription pathways. Other gene expression changes, including the increase of several apoptotic or anti-proliferation genes, such as GADD45A/B and TUSC2, and the decrease of a batch of phosphatase and kinase genes, may also provide further evidences in supporting the process of PSP induced apoptosis in cancer cells. Some of the well-characterized carcinogenesis-related gene transcripts such as SAT, DCT, Melan-A, uPA and cyclin E1 were also alternated by PSP in the HL-60 cells. These transcripts can be employed as markers for quality control of PSP products on functional levels. The present study provides new insight into the molecular mechanisms involved in PSP-induced apoptosis in leukemic HL-60 cells analyzed by cDNA microarray.

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

PubMed Central

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

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

Single molecule fluorescence microscopy for ultra-sensitive RNA expression profiling

NASA Astrophysics Data System (ADS)

Hesse, Jan; Jacak, Jaroslaw; Regl, Gerhard; Eichberger, Thomas; Aberger, Fritz; Schlapak, Robert; Howorka, Stefan; Muresan, Leila; Frischauf, Anna-Maria; Schütz, Gerhard J.

2007-02-01

We developed a microarray analysis platform for ultra-sensitive RNA expression profiling of minute samples. It utilizes a novel scanning system for single molecule fluorescence detection on cm2 size samples in combination with specialized biochips, optimized for low autofluorescence and weak unspecific adsorption. 20 μg total RNA was extracted from 10 6 cells of a human keratinocyte cell line (HaCaT) and reversely transcribed in the presence of Alexa647-aha-dUTP. 1% of the resulting labeled cDNA was used for complex hybridization to a custom-made oligonucleotide microarray representing a set of 125 different genes. For low abundant genes, individual cDNA molecules hybridized to the microarray spots could be resolved. Single cDNA molecules hybridized to the chip surface appeared as diffraction limited features in the fluorescence images. The à trous wavelet method was utilized for localization and counting of the separated cDNA signals. Subsequently, the degree of labeling of the localized cDNA molecules was determined by brightness analysis for the different genes. Variations by factors up to 6 were found, which in conventional microarray analysis would result in a misrepresentation of the relative abundance of mRNAs.

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

NASA Astrophysics Data System (ADS)

Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

Exploring the mechanisms of DNA hybridization on a surface

NASA Astrophysics Data System (ADS)

Schmitt, Terry J.; Rogers, J. Brandon; Knotts, Thomas A.

2013-01-01

DNA microarrays are a potentially disruptive technology in the medical field, but their use in such settings is limited by poor reliability. Microarrays work on the principle of hybridization and can only be as reliable as this process is robust, yet little is known at the molecular level about how the surface affects the hybridization process. This work uses advanced molecular simulation techniques and an experimentally parameterized coarse-grain model to determine the mechanism by which hybridization occurs on surfaces. The results show that hybridization proceeds through a mechanism where the untethered (target) strand often flips orientation. For evenly lengthed strands, the surface stabilizes hybridization (compared to the bulk system) by reducing the barriers involved in the flipping event. For unevenly lengthed strands, the surface destabilizes hybridization compared to the bulk, but the degree of destabilization is dependent on the location of the matching sequence. Taken as a whole, the results offer an unprecedented view into the hybridization process on surfaces and provide some insights as to the poor reproducibility exhibited by microarrays.

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

PubMed Central

2010-01-01

Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets. PMID:20128918

Arraycount, an algorithm for automatic cell counting in microwell arrays.

PubMed

Kachouie, Nezamoddin; Kang, Lifeng; Khademhosseini, Ali

2009-09-01

Microscale technologies have emerged as a powerful tool for studying and manipulating biological systems and miniaturizing experiments. However, the lack of software complementing these techniques has made it difficult to apply them for many high-throughput experiments. This work establishes Arraycount, an approach to automatically count cells in microwell arrays. The procedure consists of fluorescent microscope imaging of cells that are seeded in microwells of a microarray system and then analyzing images via computer to recognize the array and count cells inside each microwell. To start counting, green and red fluorescent images (representing live and dead cells, respectively) are extracted from the original image and processed separately. A template-matching algorithm is proposed in which pre-defined well and cell templates are matched against the red and green images to locate microwells and cells. Subsequently, local maxima in the correlation maps are determined and local maxima maps are thresholded. At the end, the software records the cell counts for each detected microwell on the original image in high-throughput. The automated counting was shown to be accurate compared with manual counting, with a difference of approximately 1-2 cells per microwell: based on cell concentration, the absolute difference between manual and automatic counting measurements was 2.5-13%.

A universal reference sample derived from clone vector for improved detection of differential gene expression

PubMed Central

Khan, Rishi L; Gonye, Gregory E; Gao, Guang; Schwaber, James S

2006-01-01

Background Using microarrays by co-hybridizing two samples labeled with different dyes enables differential gene expression measurements and comparisons across slides while controlling for within-slide variability. Typically one dye produces weaker signal intensities than the other often causing signals to be undetectable. In addition, undetectable spots represent a large problem for two-color microarray designs and most arrays contain at least 40% undetectable spots even when labeled with reference samples such as Stratagene's Universal Reference RNAs™. Results We introduce a novel universal reference sample that produces strong signal for all spots on the array, increasing the average fraction of detectable spots to 97%. Maximizing detectable spots on the reference image channel also decreases the variability of microarray data allowing for reliable detection of smaller differential gene expression changes. The reference sample is derived from sequence contained in the parental EST clone vector pT7T3D-Pac and is called vector RNA (vRNA). We show that vRNA can also be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This reference sample can be made inexpensively in large quantities as a renewable resource that is consistent across experiments. Conclusion Results of this study show that vRNA provides a useful universal reference that yields high signal for almost all spots on a microarray, reduces variation and allows for comparisons between experiments and laboratories. Further, it can be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This type of reference allows for detection of small changes in differential expression while reference designs in general allow for large-scale multivariate experimental designs. vRNA in combination with reference designs enable systems biology microarray experiments of small physiologically relevant changes. PMID:16677381

Detection of pathogenic Vibrio spp. in shellfish by using multiplex PCR and DNA microarrays.

PubMed

Panicker, Gitika; Call, Douglas R; Krug, Melissa J; Bej, Asim K

2004-12-01

This study describes the development of a gene-specific DNA microarray coupled with multiplex PCR for the comprehensive detection of pathogenic vibrios that are natural inhabitants of warm coastal waters and shellfish. Multiplex PCR with vvh and viuB for Vibrio vulnificus, with ompU, toxR, tcpI, and hlyA for V. cholerae, and with tlh, tdh, trh, and open reading frame 8 for V. parahaemolyticus helped to ensure that total and pathogenic strains, including subtypes of the three Vibrio spp., could be detected and discriminated. For DNA microarrays, oligonucleotide probes for these targeted genes were deposited onto epoxysilane-derivatized, 12-well, Teflon-masked slides by using a MicroGrid II arrayer. Amplified PCR products were hybridized to arrays at 50 degrees C and detected by using tyramide signal amplification with Alexa Fluor 546 fluorescent dye. Slides were imaged by using an arrayWoRx scanner. The detection sensitivity for pure cultures without enrichment was 10(2) to 10(3) CFU/ml, and the specificity was 100%. However, 5 h of sample enrichment followed by DNA extraction with Instagene matrix and multiplex PCR with microarray hybridization resulted in the detection of 1 CFU in 1 g of oyster tissue homogenate. Thus, enrichment of the bacterial pathogens permitted higher sensitivity in compliance with the Interstate Shellfish Sanitation Conference guideline. Application of the DNA microarray methodology to natural oysters revealed the presence of V. vulnificus (100%) and V. parahaemolyticus (83%). However, V. cholerae was not detected in natural oysters. An assay involving a combination of multiplex PCR and DNA microarray hybridization would help to ensure rapid and accurate detection of pathogenic vibrios in shellfish, thereby improving the microbiological safety of shellfish for consumers.

Detection of Pathogenic Vibrio spp. in Shellfish by Using Multiplex PCR and DNA Microarrays

PubMed Central

Panicker, Gitika; Call, Douglas R.; Krug, Melissa J.; Bej, Asim K.

2004-01-01

This study describes the development of a gene-specific DNA microarray coupled with multiplex PCR for the comprehensive detection of pathogenic vibrios that are natural inhabitants of warm coastal waters and shellfish. Multiplex PCR with vvh and viuB for Vibrio vulnificus, with ompU, toxR, tcpI, and hlyA for V. cholerae, and with tlh, tdh, trh, and open reading frame 8 for V. parahaemolyticus helped to ensure that total and pathogenic strains, including subtypes of the three Vibrio spp., could be detected and discriminated. For DNA microarrays, oligonucleotide probes for these targeted genes were deposited onto epoxysilane-derivatized, 12-well, Teflon-masked slides by using a MicroGrid II arrayer. Amplified PCR products were hybridized to arrays at 50°C and detected by using tyramide signal amplification with Alexa Fluor 546 fluorescent dye. Slides were imaged by using an arrayWoRx scanner. The detection sensitivity for pure cultures without enrichment was 102 to 103 CFU/ml, and the specificity was 100%. However, 5 h of sample enrichment followed by DNA extraction with Instagene matrix and multiplex PCR with microarray hybridization resulted in the detection of 1 CFU in 1 g of oyster tissue homogenate. Thus, enrichment of the bacterial pathogens permitted higher sensitivity in compliance with the Interstate Shellfish Sanitation Conference guideline. Application of the DNA microarray methodology to natural oysters revealed the presence of V. vulnificus (100%) and V. parahaemolyticus (83%). However, V. cholerae was not detected in natural oysters. An assay involving a combination of multiplex PCR and DNA microarray hybridization would help to ensure rapid and accurate detection of pathogenic vibrios in shellfish, thereby improving the microbiological safety of shellfish for consumers. PMID:15574946

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

PubMed

Sheng, Xiuzhen; Xu, Xiaoli; Zhan, Wenbin

2013-05-01

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

Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

PubMed

Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

2017-08-07

High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mutual information estimation reveals global associations between stimuli and biological processes

PubMed Central

Suzuki, Taiji; Sugiyama, Masashi; Kanamori, Takafumi; Sese, Jun

2009-01-01

Background Although microarray gene expression analysis has become popular, it remains difficult to interpret the biological changes caused by stimuli or variation of conditions. Clustering of genes and associating each group with biological functions are often used methods. However, such methods only detect partial changes within cell processes. Herein, we propose a method for discovering global changes within a cell by associating observed conditions of gene expression with gene functions. Results To elucidate the association, we introduce a novel feature selection method called Least-Squares Mutual Information (LSMI), which computes mutual information without density estimaion, and therefore LSMI can detect nonlinear associations within a cell. We demonstrate the effectiveness of LSMI through comparison with existing methods. The results of the application to yeast microarray datasets reveal that non-natural stimuli affect various biological processes, whereas others are no significant relation to specific cell processes. Furthermore, we discover that biological processes can be categorized into four types according to the responses of various stimuli: DNA/RNA metabolism, gene expression, protein metabolism, and protein localization. Conclusion We proposed a novel feature selection method called LSMI, and applied LSMI to mining the association between conditions of yeast and biological processes through microarray datasets. In fact, LSMI allows us to elucidate the global organization of cellular process control. PMID:19208155

Microarray-based analysis of gene expression in lycopersicon esculentum seedling roots in response to cadmium, chromium, mercury, and lead.

PubMed

Hou, Jing; Liu, Xinhui; Wang, Juan; Zhao, Shengnan; Cui, Baoshan

2015-02-03

The effects of heavy metals in agricultural soils have received special attention due to their potential for accumulation in crops, which can affect species at all trophic levels. Therefore, there is a critical need for reliable bioassays for assessing risk levels due to heavy metals in agricultural soil. In the present study, we used microarrays to investigate changes in gene expression of Lycopersicon esculentum in response to Cd-, Cr-, Hg-, or Pb-spiked soil. Exposure to (1)/10 median lethal concentrations (LC50) of Cd, Cr, Hg, or Pb for 7 days resulted in expression changes in 29 Cd-specific, 58 Cr-specific, 192 Hg-specific and 864 Pb-specific genes as determined by microarray analysis, whereas conventional morphological and physiological bioassays did not reveal any toxicant stresses. Hierarchical clustering analysis showed that the characteristic gene expression profiles induced by Cd, Cr, Hg, and Pb were distinct from not only the control but also one another. Furthermore, a total of three genes related to "ion transport" for Cd, 14 genes related to "external encapsulating structure organization", "reproductive developmental process", "lipid metabolic process" and "response to stimulus" for Cr, 11 genes related to "cellular metabolic process" and "cellular response to stimulus" for Hg, 78 genes related to 20 biological processes (e.g., DNA metabolic process, monosaccharide catabolic process, cell division) for Pb were identified and selected as their potential biomarkers. These findings demonstrated that microarray-based analysis of Lycopersicon esculentum was a sensitive tool for the early detection of potential toxicity of heavy metals in agricultural soil, as well as an effective tool for identifying the heavy metal-specific genes, which should be useful for assessing risk levels due to heavy metals in agricultural soil.

Universal ligation-detection-reaction microarray applied for compost microbes

PubMed Central

Hultman, Jenni; Ritari, Jarmo; Romantschuk, Martin; Paulin, Lars; Auvinen, Petri

2008-01-01

Background Composting is one of the methods utilised in recycling organic communal waste. The composting process is dependent on aerobic microbial activity and proceeds through a succession of different phases each dominated by certain microorganisms. In this study, a ligation-detection-reaction (LDR) based microarray method was adapted for species-level detection of compost microbes characteristic of each stage of the composting process. LDR utilises the specificity of the ligase enzyme to covalently join two adjacently hybridised probes. A zip-oligo is attached to the 3'-end of one probe and fluorescent label to the 5'-end of the other probe. Upon ligation, the probes are combined in the same molecule and can be detected in a specific location on a universal microarray with complementary zip-oligos enabling equivalent hybridisation conditions for all probes. The method was applied to samples from Nordic composting facilities after testing and optimisation with fungal pure cultures and environmental clones. Results Probes targeted for fungi were able to detect 0.1 fmol of target ribosomal PCR product in an artificial reaction mixture containing 100 ng competing fungal ribosomal internal transcribed spacer (ITS) area or herring sperm DNA. The detection level was therefore approximately 0.04% of total DNA. Clone libraries were constructed from eight compost samples. The LDR microarray results were in concordance with the clone library sequencing results. In addition a control probe was used to monitor the per-spot hybridisation efficiency on the array. Conclusion This study demonstrates that the LDR microarray method is capable of sensitive and accurate species-level detection from a complex microbial community. The method can detect key species from compost samples, making it a basis for a tool for compost process monitoring in industrial facilities. PMID:19116002

Reusable conductimetric array of interdigitated microelectrodes for the readout of low-density microarrays.

PubMed

Mallén, Maria; Díaz-González, María; Bonilla, Diana; Salvador, Juan P; Marco, María P; Baldi, Antoni; Fernández-Sánchez, César

2014-06-17

Low-density protein microarrays are emerging tools in diagnostics whose deployment could be primarily limited by the cost of fluorescence detection schemes. This paper describes an electrical readout system of microarrays comprising an array of gold interdigitated microelectrodes and an array of polydimethylsiloxane microwells, which enabled multiplexed detection of up to thirty six biological events on the same substrate. Similarly to fluorescent readout counterparts, the microarray can be developed on disposable glass slide substrates. However, unlike them, the presented approach is compact and requires a simple and inexpensive instrumentation. The system makes use of urease labeled affinity reagents for developing the microarrays and is based on detection of conductivity changes taking place when ionic species are generated in solution due to the catalytic hydrolysis of urea. The use of a polydimethylsiloxane microwell array facilitates the positioning of the measurement solution on every spot of the microarray. Also, it ensures the liquid tightness and isolation from the surrounding ones during the microarray readout process, thereby avoiding evaporation and chemical cross-talk effects that were shown to affect the sensitivity and reliability of the system. The performance of the system is demonstrated by carrying out the readout of a microarray for boldenone anabolic androgenic steroid hormone. Analytical results are comparable to those obtained by fluorescent scanner detection approaches. The estimated detection limit is 4.0 ng mL(-1), this being below the threshold value set by the World Anti-Doping Agency and the European Community. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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

2010-04-01

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

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

PubMed

Harvey, Benjamin; Soo-Yeon Ji

2014-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring inference though analysis of DNA/mRNA sequence data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological inference by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale classification analysis of microarray data using Wavelet thresholding in a Cloud environment to identify significantly expressed features. This paper proposes a novel methodology that uses Wavelet based Denoising to initialize a threshold for determination of significantly expressed genes for classification. Additionally, this research was implemented and encompassed within cloud-based distributed processing environment. The utilization of Cloud computing and Wavelet thresholding was used for the classification 14 tumor classes from the Global Cancer Map (GCM). The results proved to be more accurate than using a predefined p-value for differential expression classification. This novel methodology analyzed Wavelet based threshold features of gene expression in a Cloud environment, furthermore classifying the expression of samples by analyzing gene patterns, which inform us of biological processes. Moreover, enabling researchers to face the present and forthcoming challenges that may arise in the analysis of data in functional genomics of large microarray datasets.

Immunological Targeting of Tumor Initiating Prostate Cancer Cells

DTIC Science & Technology

2014-10-01

clinically using well-accepted immuno-competent animal models. 2) Keywords: Prostate Cancer, Lymphocyte, Vaccine, Antibody 3) Overall Project Summary...castrate animals . Task 1: Identify and verify antigenic targets from CAstrate Resistant Luminal Epithelial Cells (CRLEC) (months 1-16... animals per group will be processed to derive sufficient RNA for microarray analysis; the experiment will be repeated x 3. Microarray analysis will

PhylArray: phylogenetic probe design algorithm for microarray.

PubMed

Militon, Cécile; Rimour, Sébastien; Missaoui, Mohieddine; Biderre, Corinne; Barra, Vincent; Hill, David; Moné, Anne; Gagne, Geneviève; Meier, Harald; Peyretaillade, Eric; Peyret, Pierre

2007-10-01

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality. We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

An automated microfluidic platform for C. elegans embryo arraying, phenotyping, and long-term live imaging

NASA Astrophysics Data System (ADS)

Cornaglia, Matteo; Mouchiroud, Laurent; Marette, Alexis; Narasimhan, Shreya; Lehnert, Thomas; Jovaisaite, Virginija; Auwerx, Johan; Gijs, Martin A. M.

2015-05-01

Studies of the real-time dynamics of embryonic development require a gentle embryo handling method, the possibility of long-term live imaging during the complete embryogenesis, as well as of parallelization providing a population’s statistics, while keeping single embryo resolution. We describe an automated approach that fully accomplishes these requirements for embryos of Caenorhabditis elegans, one of the most employed model organisms in biomedical research. We developed a microfluidic platform which makes use of pure passive hydrodynamics to run on-chip worm cultures, from which we obtain synchronized embryo populations, and to immobilize these embryos in incubator microarrays for long-term high-resolution optical imaging. We successfully employ our platform to investigate morphogenesis and mitochondrial biogenesis during the full embryonic development and elucidate the role of the mitochondrial unfolded protein response (UPRmt) within C. elegans embryogenesis. Our method can be generally used for protein expression and developmental studies at the embryonic level, but can also provide clues to understand the aging process and age-related diseases in particular.

Effect of energy restriction and physical exercise intervention on phenotypic flexibility as examined by transcriptomics analyses of mRNA from adipose tissue and whole body magnetic resonance imaging.

PubMed

Lee, Sindre; Norheim, Frode; Langleite, Torgrim M; Noreng, Hans J; Storås, Trygve H; Afman, Lydia A; Frost, Gary; Bell, Jimmy D; Thomas, E Louise; Kolnes, Kristoffer J; Tangen, Daniel S; Stadheim, Hans K; Gilfillan, Gregor D; Gulseth, Hanne L; Birkeland, Kåre I; Jensen, Jørgen; Drevon, Christian A; Holen, Torgeir

2016-11-01

Overweight and obesity lead to changes in adipose tissue such as inflammation and reduced insulin sensitivity. The aim of this study was to assess how altered energy balance by reduced food intake or enhanced physical activity affect these processes. We studied sedentary subjects with overweight/obesity in two intervention studies, each lasting 12 weeks affecting energy balance either by energy restriction (~20% reduced intake of energy from food) in one group, or by enhanced energy expenditure due to physical exercise (combined endurance- and strength-training) in the other group. We monitored mRNA expression by microarray and mRNA sequencing from adipose tissue biopsies. We also measured several plasma parameters as well as fat distribution with magnetic resonance imaging and spectroscopy. Comparison of microarray and mRNA sequencing showed strong correlations, which were also confirmed using RT-PCR In the energy restricted subjects (body weight reduced by 5% during a 12 weeks intervention), there were clear signs of enhanced lipolysis as monitored by mRNA in adipose tissue as well as plasma concentration of free-fatty acids. This increase was strongly related to increased expression of markers for M1-like macrophages in adipose tissue. In the exercising subjects (glucose infusion rate increased by 29% during a 12-week intervention), there was a marked reduction in the expression of markers of M2-like macrophages and T cells, suggesting that physical exercise was especially important for reducing inflammation in adipose tissue with insignificant reduction in total body weight. Our data indicate that energy restriction and physical exercise affect energy-related pathways as well as inflammatory processes in different ways, probably related to macrophages in adipose tissue. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

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 through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume. PMID:19032776

Mining the Salivary Proteome with Grating-Coupled Surface Plasmon Resonance Imaging and Surface Plasmon Coupled Emission Microarrays

PubMed Central

Molony, Ryan D.; Rice, James M.; Yuk, Jongseol; Shetty, Vivek; Dey, Dipak; Lawrence, David A.; Lynes, Michael A.

2012-01-01

Biological indicators have numerous and widespread utility in personalized medicine, but the measurement of these indicators also pose many technological and practical challenges. Blood/plasma has typically been used as the sample source with which to measure these indicators, but the invasiveness associated with procurement of samples has led to increased interest in saliva as an attractive alternative. However, there are unique issues associated with the measurement of saliva biomarkers. These issues are compounded by the imperfect correlation between saliva and plasma with respect to biomarker profiles. In this manuscript, we address the technical challenges associated with saliva biomarker quantification describe a high-content microarray assay that employs both grating-coupled surface plasmon resonance imaging surface plasmon coupled emission modalities in a highly sensitive assay that has a large dynamic range. This powerful approach provides the tools to map the proteome of saliva, which in turn should greatly enhance the utility of salivary biomarker profiles in personalized medicine. PMID:22896008

Microarray platform affords improved product analysis in mammalian cell growth studies

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2008-01-01

Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers (Semantic Agents) such as Google to further enhance data discovery. Conclusions Microarray data and meta information in ArrayWiki are distributed and visualized using a novel and compact data storage format, BioPNG. Also, they are open to the research community for curation, modification, and contribution. By making a small investment of time to learn the syntax and structure common to all sites running MediaWiki software, domain scientists and practioners can all contribute to make better use of microarray technologies in research and medical practices. ArrayWiki is available at . PMID:18541053

High-throughput microarray mapping of cell wall polymers in roots and tubers during the viscosity-reducing process.

PubMed

Huang, Yuhong; Willats, William G; Lange, Lene; Jin, Yanling; Fang, Yang; Salmeán, Armando A; Pedersen, Henriette L; Busk, Peter Kamp; Zhao, Hai

2016-01-01

Viscosity reduction has a great impact on the efficiency of ethanol production when using roots and tubers as feedstock. Plant cell wall-degrading enzymes have been successfully applied to overcome the challenges posed by high viscosity. However, the changes in cell wall polymers during the viscosity-reducing process are poorly characterized. Comprehensive microarray polymer profiling, which is a high-throughput microarray, was used for the first time to map changes in the cell wall polymers of sweet potato (Ipomoea batatas), cassava (Manihot esculenta), and Canna edulis Ker. over the entire viscosity-reducing process. The results indicated that the composition of cell wall polymers among these three roots and tubers was markedly different. The gel-like matrix and glycoprotein network in the C. edulis Ker. cell wall caused difficulty in viscosity reduction. The obvious viscosity reduction of the sweet potato and the cassava was attributed to the degradation of homogalacturonan and the released 1,4-β-d-galactan and 1,5-α-l-arabinan. © 2015 International Union of Biochemistry and Molecular Biology, Inc.

Transcriptional Landscape of the Prenatal Human Brain

PubMed Central

Miller, Jeremy A.; Ding, Song-Lin; Sunkin, Susan M.; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L.; Aiona, Kaylynn; Arnold, James M.; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A.; Dee, Nick; Dolbeare, Tim A.; Facer, Benjamin A. C.; Feng, David; Fliss, Tim P.; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W.; Gu, Guangyu; Howard, Robert E.; Jochim, Jayson M.; Kuan, Chihchau L.; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A.; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick F.; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D.; Parry, Sheana E.; Player, Allison Stevens; Pletikos, Mihovil; Reding, Melissa; Royall, Joshua J.; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V.; Shen, Elaine H.; Sjoquist, Nathan; Slaughterbeck, Clifford R.; Smith, Michael; Sodt, Andy J.; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B.; Geschwind, Daniel H.; Glass, Ian A.; Hawrylycz, Michael J.; Hevner, Robert F.; Huang, Hao; Jones, Allan R.; Knowles, James A.; Levitt, Pat; Phillips, John W.; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G.; Lein, Ed S.

2014-01-01

Summary The anatomical and functional architecture of the human brain is largely determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and postmitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and human-expanded outer subventricular zones. Both germinal and postmitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in frontal lobe. Finally, many neurodevelopmental disorder and human evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development. PMID:24695229

Hierarchical nanoparticle assemblies formed by decorating breath figures.

PubMed

Böker, Alexander; Lin, Yao; Chiapperini, Kristen; Horowitz, Reina; Thompson, Mike; Carreon, Vincent; Xu, Ting; Abetz, Clarissa; Skaff, Habib; Dinsmore, A D; Emrick, Todd; Russell, Thomas P

2004-05-01

The combination of two self-assembly processes on different length scales leads to the formation of hierarchically structured nanoparticle arrays. Here, the formation of spherical cavities, or 'breath figures'-made by the condensation of micrometre-sized water droplets on the surface of a polymer solution-that self-assemble into a well-ordered hexagonal array, is combined with the self-assembly of CdSe nanoparticles at the polymer solution-water droplet interface. Complete evaporation of the solvent and water confines the particle assembly to an array of spherical cavities and allows for ex situ investigation. Fluorescence confocal, transmission electron and scanning electron microscope images show the preferential segregation of the CdSe nanoparticles to the polymer solution-water interface where they form a 5-7-nm-thick layer, thus functionalizing the walls of the holes. This process opens a new route to fabricating highly functionalized ordered microarrays of nanoparticles, potentially useful in sensory, separation membrane or catalytic applications.

76 FR 4921 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-27

... chemical imaging (IRCI) to detect nanostructure-based DNA microarrays, which can be utilized in the life science research arena to examine gene expression and single nucleotide polymorphisms (SNPs), as well as... can be applied to the areas of environmental sciences, agriculture research, bio-defense, diagnostics...

A prototype for unsupervised analysis of tissue microarrays for cancer research and diagnostics.

PubMed

Chen, Wenjin; Reiss, Michael; Foran, David J

2004-06-01

The tissue microarray (TMA) technique enables researchers to extract small cylinders of tissue from histological sections and arrange them in a matrix configuration on a recipient paraffin block such that hundreds can be analyzed simultaneously. TMA offers several advantages over traditional specimen preparation by maximizing limited tissue resources and providing a highly efficient means for visualizing molecular targets. By enabling researchers to reliably determine the protein expression profile for specific types of cancer, it may be possible to elucidate the mechanism by which healthy tissues are transformed into malignancies. Currently, the primary methods used to evaluate arrays involve the interactive review of TMA samples while they are viewed under a microscope, subjectively evaluated, and scored by a technician. This process is extremely slow, tedious, and prone to error. In order to facilitate large-scale, multi-institutional studies, a more automated and reliable means for analyzing TMAs is needed. We report here a web-based prototype which features automated imaging, registration, and distributed archiving of TMAs in multiuser network environments. The system utilizes a principal color decomposition approach to identify and characterize the predominant staining signatures of specimens in color space. This strategy was shown to be reliable for detecting and quantifying the immunohistochemical expression levels for TMAs.

Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone

PubMed Central

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

2015-01-01

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

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

PubMed

Ahmed, Zeeshan; Dandekar, Thomas

2015-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.

Practical protocols for fast histopathology by Fourier transform infrared spectroscopic imaging

NASA Astrophysics Data System (ADS)

Keith, Frances N.; Reddy, Rohith K.; Bhargava, Rohit

2008-02-01

Fourier transform infrared (FT-IR) spectroscopic imaging is an emerging technique that combines the molecular selectivity of spectroscopy with the spatial specificity of optical microscopy. We demonstrate a new concept in obtaining high fidelity data using commercial array detectors coupled to a microscope and Michelson interferometer. Next, we apply the developed technique to rapidly provide automated histopathologic information for breast cancer. Traditionally, disease diagnoses are based on optical examinations of stained tissue and involve a skilled recognition of morphological patterns of specific cell types (histopathology). Consequently, histopathologic determinations are a time consuming, subjective process with innate intra- and inter-operator variability. Utilizing endogenous molecular contrast inherent in vibrational spectra, specially designed tissue microarrays and pattern recognition of specific biochemical features, we report an integrated algorithm for automated classifications. The developed protocol is objective, statistically significant and, being compatible with current tissue processing procedures, holds potential for routine clinical diagnoses. We first demonstrate that the classification of tissue type (histology) can be accomplished in a manner that is robust and rigorous. Since data quality and classifier performance are linked, we quantify the relationship through our analysis model. Last, we demonstrate the application of the minimum noise fraction (MNF) transform to improve tissue segmentation.

MADGE: scalable distributed data management software for cDNA microarrays.

PubMed

McIndoe, Richard A; Lanzen, Aaron; Hurtz, Kimberly

2003-01-01

The human genome project and the development of new high-throughput technologies have created unparalleled opportunities to study the mechanism of diseases, monitor the disease progression and evaluate effective therapies. Gene expression profiling is a critical tool to accomplish these goals. The use of nucleic acid microarrays to assess the gene expression of thousands of genes simultaneously has seen phenomenal growth over the past five years. Although commercial sources of microarrays exist, investigators wanting more flexibility in the genes represented on the array will turn to in-house production. The creation and use of cDNA microarrays is a complicated process that generates an enormous amount of information. Effective data management of this information is essential to efficiently access, analyze, troubleshoot and evaluate the microarray experiments. We have developed a distributable software package designed to track and store the various pieces of data generated by a cDNA microarray facility. This includes the clone collection storage data, annotation data, workflow queues, microarray data, data repositories, sample submission information, and project/investigator information. This application was designed using a 3-tier client server model. The data access layer (1st tier) contains the relational database system tuned to support a large number of transactions. The data services layer (2nd tier) is a distributed COM server with full database transaction support. The application layer (3rd tier) is an internet based user interface that contains both client and server side code for dynamic interactions with the user. This software is freely available to academic institutions and non-profit organizations at http://www.genomics.mcg.edu/niddkbtc.

High-density fiber optic biosensor arrays

NASA Astrophysics Data System (ADS)

Epstein, Jason R.; Walt, David R.

2002-02-01

Novel approaches are required to coordinate the immense amounts of information derived from diverse genomes. This concept has influenced the expanded role of high-throughput DNA detection and analysis in the biological sciences. A high-density fiber optic DNA biosensor was developed consisting of oligonucleotide-functionalized, 3.1 mm diameter microspheres deposited into the etched wells on the distal face of a 500 micrometers imaging fiber bundle. Imaging fiber bundles containing thousands of optical fibers, each associated with a unique oligonucleotide probe sequence, were the foundation for an optically connected, individually addressable DNA detection platform. Different oligonucleotide-functionalized microspheres were combined in a stock solution, and randomly dispersed into the etched wells. Microsphere positions were registered from optical dyes incorporated onto the microspheres. The distribution process provided an inherent redundancy that increases the signal-to-noise ratio as the square root of the number of sensors examined. The representative amount of each probe-type in the array was dependent on their initial stock solution concentration, and as other sequences of interest arise, new microsphere elements can be added to arrays without altering the existing detection capabilities. The oligonucleotide probe sequences hybridize to fluorescently-labeled, complementary DNA target solutions. Fiber optic DNA microarray research has included DNA-protein interaction profiles, microbial strain differentiation, non-labeled target interrogation with molecular beacons, and single cell-based assays. This biosensor array is proficient in DNA detection linked to specific disease states, single nucleotide polymorphism (SNP's) discrimination, and gene expression analysis. This array platform permits multiple detection formats, provides smaller feature sizes, and enables sensor design flexibility. High-density fiber optic microarray biosensors provide a fast, reversible format with the detection limit of a few hundred molecules.

Fluorescent labeling of NASBA amplified tmRNA molecules for microarray applications

PubMed Central

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

2009-01-01

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

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

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

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.

Identifying pathogenic processes by integrating microarray data with prior knowledge

PubMed Central

2014-01-01

Background It is of great importance to identify molecular processes and pathways that are involved in disease etiology. Although there has been an extensive use of various high-throughput methods for this task, pathogenic pathways are still not completely understood. Often the set of genes or proteins identified as altered in genome-wide screens show a poor overlap with canonical disease pathways. These findings are difficult to interpret, yet crucial in order to improve the understanding of the molecular processes underlying the disease progression. We present a novel method for identifying groups of connected molecules from a set of differentially expressed genes. These groups represent functional modules sharing common cellular function and involve signaling and regulatory events. Specifically, our method makes use of Bayesian statistics to identify groups of co-regulated genes based on the microarray data, where external information about molecular interactions and connections are used as priors in the group assignments. Markov chain Monte Carlo sampling is used to search for the most reliable grouping. Results Simulation results showed that the method improved the ability of identifying correct groups compared to traditional clustering, especially for small sample sizes. Applied to a microarray heart failure dataset the method found one large cluster with several genes important for the structure of the extracellular matrix and a smaller group with many genes involved in carbohydrate metabolism. The method was also applied to a microarray dataset on melanoma cancer patients with or without metastasis, where the main cluster was dominated by genes related to keratinocyte differentiation. Conclusion Our method found clusters overlapping with known pathogenic processes, but also pointed to new connections extending beyond the classical pathways. PMID:24758699

Comparison of Chemical Sensitivity of Fresh and Long-Stored Heat Resistant Neosartorya fischeri Environmental Isolates Using BIOLOG Phenotype MicroArray System

PubMed Central

Panek, Jacek; Frąc, Magdalena; Bilińska-Wielgus, Nina

2016-01-01

Spoilage of heat processed food and beverage by heat resistant fungi (HRF) is a major problem for food industry in many countries. Neosartorya fischeri is the leading source of spoilage in thermally processed products. Its resistance to heat processing and toxigenicity makes studies about Neosartorya fischeri metabolism and chemical sensitivity essential. In this study chemical sensitivity of two environmental Neosartorya fischeri isolates were compared. One was isolated from canned apples in 1923 (DSM3700), the other from thermal processed strawberry product in 2012 (KC179765), used as long-stored and fresh isolate, respectively. The study was conducted using Biolog Phenotype MicroArray platforms of chemical sensitivity panel and traditional hole-plate method. The study allowed for obtaining data about Neosartorya fischeri growth inhibitors. The fresh isolate appeared to be much more resistant to chemical agents than the long-stored isolate. Based on phenotype microarray assay nitrogen compounds, toxic cations and membrane function compounds were the most effective in growth inhibition of N. fischeri isolates. According to the study zaragozic acid A, thallium(I) acetate and sodium selenate were potent and promising N. fischeri oriented fungicides which was confirmed by both chemical sensitivity microplates panel and traditional hole-plate methods. PMID:26815302

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform.

PubMed

Salehi, Reza; Tsoi, Stephen C M; Colazo, Marcos G; Ambrose, Divakar J; Robert, Claude; Dyck, Michael K

2017-01-30

Early embryonic loss is a large contributor to infertility in cattle. Moreover, bovine becomes an interesting model to study human preimplantation embryo development due to their similar developmental process. Although genetic factors are known to affect early embryonic development, the discovery of such factors has been a serious challenge. Microarray technology allows quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. One of the main decisions that have to be made when planning a microarray experiment is whether to use a one- or two-color approach. Two-color design increases technical replication, minimizes variability, improves sensitivity and accuracy as well as allows having loop designs, defining the common reference samples. Although microarray is a powerful biological tool, there are potential pitfalls that can attenuate its power. Hence, in this technical paper we demonstrate an optimized protocol for RNA extraction, amplification, labeling, hybridization of the labeled amplified RNA to the array, array scanning and data analysis using the two-color analysis strategy.

Data-adaptive test statistics for microarray data.

PubMed

Mukherjee, Sach; Roberts, Stephen J; van der Laan, Mark J

2005-09-01

An important task in microarray data analysis is the selection of genes that are differentially expressed between different tissue samples, such as healthy and diseased. However, microarray data contain an enormous number of dimensions (genes) and very few samples (arrays), a mismatch which poses fundamental statistical problems for the selection process that have defied easy resolution. In this paper, we present a novel approach to the selection of differentially expressed genes in which test statistics are learned from data using a simple notion of reproducibility in selection results as the learning criterion. Reproducibility, as we define it, can be computed without any knowledge of the 'ground-truth', but takes advantage of certain properties of microarray data to provide an asymptotically valid guide to expected loss under the true data-generating distribution. We are therefore able to indirectly minimize expected loss, and obtain results substantially more robust than conventional methods. We apply our method to simulated and oligonucleotide array data. By request to the corresponding author.

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

PubMed

Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

2009-12-21

Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment.

Microarray expression technology: from start to finish.

PubMed

Elvidge, Gareth

2006-01-01

The recent introduction of new microarray expression technologies and the further development of established platforms ensure that the researcher is presented with a range of options for performing an experiment. Whilst this has opened up the possibilities for future applications, such as exon-specific arrays, increased sample throughput and 'chromatin immunoprecipitation (ChIP) on chip' experiments, the initial decision processes and experiment planning are made more difficult. This review will give an overview of the various technologies that are available to perform a microarray expression experiment, from the initial planning stages through to the final data analysis. Both practical aspects and data analysis options will be considered. The relative advantages and disadvantages will be discussed with insights provided for future directions of the technology.

Printing Proteins as Microarrays for High-Throughput Function Determination

NASA Astrophysics Data System (ADS)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

Rational design of DNA sequences for nanotechnology, microarrays and molecular computers using Eulerian graphs.

PubMed

Pancoska, Petr; Moravek, Zdenek; Moll, Ute M

2004-01-01

Nucleic acids are molecules of choice for both established and emerging nanoscale technologies. These technologies benefit from large functional densities of 'DNA processing elements' that can be readily manufactured. To achieve the desired functionality, polynucleotide sequences are currently designed by a process that involves tedious and laborious filtering of potential candidates against a series of requirements and parameters. Here, we present a complete novel methodology for the rapid rational design of large sets of DNA sequences. This method allows for the direct implementation of very complex and detailed requirements for the generated sequences, thus avoiding 'brute force' filtering. At the same time, these sequences have narrow distributions of melting temperatures. The molecular part of the design process can be done without computer assistance, using an efficient 'human engineering' approach by drawing a single blueprint graph that represents all generated sequences. Moreover, the method eliminates the necessity for extensive thermodynamic calculations. Melting temperature can be calculated only once (or not at all). In addition, the isostability of the sequences is independent of the selection of a particular set of thermodynamic parameters. Applications are presented for DNA sequence designs for microarrays, universal microarray zip sequences and electron transfer experiments.

Development and Use of Integrated Microarray-Based Genomic Technologies for Assessing Microbial Community Composition and Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, J.; Wu, L.; Gentry, T.

2006-04-05

To effectively monitor microbial populations involved in various important processes, a 50-mer-based oligonucleotide microarray was developed based on known genes and pathways involved in: biodegradation, metal resistance and reduction, denitrification, nitrification, nitrogen fixation, methane oxidation, methanogenesis, carbon polymer decomposition, and sulfate reduction. This array contains approximately 2000 unique and group-specific probes with <85% similarity to their non-target sequences. Based on artificial probes, our results showed that at hybridization conditions of 50 C and 50% formamide, the 50-mer microarray hybridization can differentiate sequences having <88% similarity. Specificity tests with representative pure cultures indicated that the designed probes on the arrays appearedmore » to be specific to their corresponding target genes. Detection limits were about 5-10ng genomic DNA in the absence of background DNA, and 50-100ng ({approx}1.3{sup o} 10{sup 7} cells) in the presence background DNA. Strong linear relationships between signal intensity and target DNA and RNA concentration were observed (r{sup 2} = 0.95-0.99). Application of this microarray to naphthalene-amended enrichments and soil microcosms demonstrated that composition of the microflora varied depending on incubation conditions. While the naphthalene-degrading genes from Rhodococcus-type microorganisms were dominant in enrichments, the genes involved in naphthalene degradation from Gram-negative microorganisms such as Ralstonia, Comamonas, and Burkholderia were most abundant in the soil microcosms (as well as those for polyaromatic hydrocarbon and nitrotoluene degradation). Although naphthalene degradation is widely known and studied in Pseudomonas, Pseudomonas genes were not detected in either system. Real-time PCR analysis of 4 representative genes was consistent with microarray-based quantification (r{sup 2} = 0.95). Currently, we are also applying this microarray to the study of several different microbial communities and processes at the NABIR-FRC in Oak Ridge, TN. One project involves the monitoring of the development and dynamics of the microbial community of a fluidized bed reactor (FBR) used for reducing nitrate and the other project monitors microbial community responses to stimulation of uranium reducing populations via ethanol donor additions in situ and in a model system. Additionally, we are developing novel strategies for increasing microarray hybridization sensitivity. Finally, great improvements to our methods of probe design were made by the development of a new computer program, CommOligo. CommOligo designs unique and group-specific oligo probes for whole-genomes, metagenomes, and groups of environmental sequences and uses a new global alignment algorithm to design single or multiple probes for each gene or group. We are now using this program to design a more comprehensive functional gene array for environmental studies. Overall, our results indicate that the 50mer-based microarray technology has potential as a specific and quantitative tool to reveal the composition of microbial communities and their dynamics important to processes within contaminated environments.« less

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

Sunkin, Susan M.; Ng, Lydia; Lau, Chris; Dolbeare, Tim; Gilbert, Terri L.; Thompson, Carol L.; Hawrylycz, Michael; Dang, Chinh

2013-01-01

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal. PMID:23193282

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

PubMed

Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J

2013-01-01

Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

Laser capture microdissection of embryonic cells and preparation of RNA for microarray assays.

PubMed

Redmond, Latasha C; Pang, Christopher J; Dumur, Catherine; Haar, Jack L; Lloyd, Joyce A

2014-01-01

In order to compare the global gene expression profiles of different embryonic cell types, it is first necessary to isolate the specific cells of interest. The purpose of this chapter is to provide a step-by-step protocol to perform laser capture microdissection (LCM) on embryo samples and obtain sufficient amounts of high-quality RNA for microarray hybridizations. Using the LCM/microarray strategy on mouse embryo samples has some challenges, because the cells of interest are available in limited quantities. The first step in the protocol is to obtain embryonic tissue, and immediately cryoprotect and freeze it in a cryomold containing Optimal Cutting Temperature freezing media (Sakura Finetek), using a dry ice-isopentane bath. The tissue is then cryosectioned, and the microscope slides are processed to fix, stain, and dehydrate the cells. LCM is employed to isolate specific cell types from the slides, identified under the microscope by virtue of their morphology. Detailed protocols are provided for using the currently available ArcturusXT LCM instrument and CapSure(®) LCM Caps, to which the selected cells adhere upon laser capture. To maintain RNA integrity, upon removing a slide from the final processing step, or attaching the first cells on the LCM cap, LCM is completed within 20 min. The cells are then immediately recovered from the LCM cap using a denaturing solution that stabilizes RNA integrity. RNA is prepared using standard methods, modified for working with small samples. To ensure the validity of the microarray data, the quality of the RNA is assessed using the Agilent bioanalyzer. Only RNA that is of sufficient integrity and quantity is used to perform microarray assays. This chapter provides guidance regarding troubleshooting and optimization to obtain high-quality RNA from cells of limited availability, obtained from embryo samples by LCM.

Laser Capture Microdissection of Embryonic Cells and Preparation of RNA for Microarray Assays

PubMed Central

Redmond, Latasha C.; Pang, Christopher J.; Dumur, Catherine; Haar, Jack L.; Lloyd, Joyce A.

2014-01-01

In order to compare the global gene expression profiles of different embryonic cell types, it is first necessary to isolate the specific cells of interest. The purpose of this chapter is to provide a step-by-step protocol to perform laser capture microdissection (LCM) on embryo samples and obtain sufficient amounts of high-quality RNA for microarray hybridizations. Using the LCM/microarray strategy on mouse embryo samples has some challenges, because the cells of interest are available in limited quantities. The first step in the protocol is to obtain embryonic tissue, and immediately cryoprotect and freeze it in a cryomold containing Optimal Cutting Temperature freezing media (Sakura Finetek), using a dry ice–isopentane bath. The tissue is then cryosectioned, and the microscope slides are processed to fix, stain, and dehydrate the cells. LCM is employed to isolate specific cell types from the slides, identified under the microscope by virtue of their morphology. Detailed protocols are provided for using the currently available ArcturusXT LCM instrument and CapSure® LCM Caps, to which the selected cells adhere upon laser capture. To maintain RNA integrity, upon removing a slide from the final processing step, or attaching the first cells on the LCM cap, LCM is completed within 20 min. The cells are then immediately recovered from the LCM cap using a denaturing solution that stabilizes RNA integrity. RNA is prepared using standard methods, modified for working with small samples. To ensure the validity of the microarray data, the quality of the RNA is assessed using the Agilent bioanalyzer. Only RNA that is of sufficient integrity and quantity is used to perform microarray assays. This chapter provides guidance regarding troubleshooting and optimization to obtain high-quality RNA from cells of limited availability, obtained from embryo samples by LCM. PMID:24318813

An automated microfluidic DNA microarray platform for genetic variant detection in inherited arrhythmic diseases.

PubMed

Huang, Shu-Hong; Chang, Yu-Shin; Juang, Jyh-Ming Jimmy; Chang, Kai-Wei; Tsai, Mong-Hsun; Lu, Tzu-Pin; Lai, Liang-Chuan; Chuang, Eric Y; Huang, Nien-Tsu

2018-03-12

In this study, we developed an automated microfluidic DNA microarray (AMDM) platform for point mutation detection of genetic variants in inherited arrhythmic diseases. The platform allows for automated and programmable reagent sequencing under precise conditions of hybridization flow and temperature control. It is composed of a commercial microfluidic control system, a microfluidic microarray device, and a temperature control unit. The automated and rapid hybridization process can be performed in the AMDM platform using Cy3 labeled oligonucleotide exons of SCN5A genetic DNA, which produces proteins associated with sodium channels abundant in the heart (cardiac) muscle cells. We then introduce a graphene oxide (GO)-assisted DNA microarray hybridization protocol to enable point mutation detection. In this protocol, a GO solution is added after the staining step to quench dyes bound to single-stranded DNA or non-perfectly matched DNA, which can improve point mutation specificity. As proof-of-concept we extracted the wild-type and mutant of exon 12 and exon 17 of SCN5A genetic DNA from patients with long QT syndrome or Brugada syndrome by touchdown PCR and performed a successful point mutation discrimination in the AMDM platform. Overall, the AMDM platform can greatly reduce laborious and time-consuming hybridization steps and prevent potential contamination. Furthermore, by introducing the reciprocating flow into the microchannel during the hybridization process, the total assay time can be reduced to 3 hours, which is 6 times faster than the conventional DNA microarray. Given the automatic assay operation, shorter assay time, and high point mutation discrimination, we believe that the AMDM platform has potential for low-cost, rapid and sensitive genetic testing in a simple and user-friendly manner, which may benefit gene screening in medical practice.

Computational synchronization of microarray data with application to Plasmodium falciparum.

PubMed

Zhao, Wei; Dauwels, Justin; Niles, Jacquin C; Cao, Jianshu

2012-06-21

Microarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data. We develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC. By analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions. This study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.

Quantum-enhanced feature selection with forward selection and backward elimination

NASA Astrophysics Data System (ADS)

He, Zhimin; Li, Lvzhou; Huang, Zhiming; Situ, Haozhen

2018-07-01

Feature selection is a well-known preprocessing technique in machine learning, which can remove irrelevant features to improve the generalization capability of a classifier and reduce training and inference time. However, feature selection is time-consuming, particularly for the applications those have thousands of features, such as image retrieval, text mining and microarray data analysis. It is crucial to accelerate the feature selection process. We propose a quantum version of wrapper-based feature selection, which converts a classical feature selection to its quantum counterpart. It is valuable for machine learning on quantum computer. In this paper, we focus on two popular kinds of feature selection methods, i.e., wrapper-based forward selection and backward elimination. The proposed feature selection algorithm can quadratically accelerate the classical one.

Recent Developments in Synthetic Carbohydrate-Based Diagnostics, Vaccines, and Therapeutics.

PubMed

Fernández-Tejada, Alberto; Cañada, F Javier; Jiménez-Barbero, Jesús

2015-07-20

Glycans are everywhere in biological systems, being involved in many cellular events with important implications for medical purposes. Building upon a detailed understanding of the functional roles of carbohydrates in molecular recognition processes and disease states, glycans are increasingly being considered as key players in pharmacological research. On the basis of the important progress recently made in glycochemistry, glycobiology, and glycomedicine, we provide a complete overview of successful applications and future perspectives of carbohydrates in the biopharmaceutical and medical fields. This review highlights the development of carbohydrate-based diagnostics, exemplified by glycan imaging techniques and microarray platforms, synthetic oligosaccharide vaccines against infectious diseases (e.g., HIV) and cancer, and finally carbohydrate-derived therapeutics, including glycomimetic drugs and glycoproteins. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Genome-Wide Association Study of a Validated Case Definition of Gulf War Illness in a Population-Representative Sample

DTIC Science & Technology

2013-09-01

sequence dataset. All procedures were performed by personnel in the IIMT UT Southwestern Genomics and Microarray Core using standard protocols. More... sequencing run, samples were demultiplexed using standard algorithms in the Genomics and Microarray Core and processed into individual sample Illumina single... Sequencing (RNA-Seq), using Illumina’s multiplexing mRNA-Seq to generate full sequence libraries from the poly-A tailed RNA to a read depth of 30

Microarray labeling extension values: laboratory signatures for Affymetrix GeneChips

PubMed Central

Lee, Yun-Shien; Chen, Chun-Houh; Tsai, Chi-Neu; Tsai, Chia-Lung; Chao, Angel; Wang, Tzu-Hao

2009-01-01

Interlaboratory comparison of microarray data, even when using the same platform, imposes several challenges to scientists. RNA quality, RNA labeling efficiency, hybridization procedures and data-mining tools can all contribute variations in each laboratory. In Affymetrix GeneChips, about 11–20 different 25-mer oligonucleotides are used to measure the level of each transcript. Here, we report that ‘labeling extension values (LEVs)’, which are correlation coefficients between probe intensities and probe positions, are highly correlated with the gene expression levels (GEVs) on eukayotic Affymetrix microarray data. By analyzing LEVs and GEVs in the publicly available 2414 cel files of 20 Affymetrix microarray types covering 13 species, we found that correlations between LEVs and GEVs only exist in eukaryotic RNAs, but not in prokaryotic ones. Surprisingly, Affymetrix results of the same specimens that were analyzed in different laboratories could be clearly differentiated only by LEVs, leading to the identification of ‘laboratory signatures’. In the examined dataset, GSE10797, filtering out high-LEV genes did not compromise the discovery of biological processes that are constructed by differentially expressed genes. In conclusion, LEVs provide a new filtering parameter for microarray analysis of gene expression and it may improve the inter- and intralaboratory comparability of Affymetrix GeneChips data. PMID:19295132

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

PubMed Central

Hu, Guohong; Wang, Hui-Yun; Greenawalt, Danielle M.; Azaro, Marco A.; Luo, Minjie; Tereshchenko, Irina V.; Cui, Xiangfeng; Yang, Qifeng; Gao, Richeng; Shen, Li; Li, Honghua

2006-01-01

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from . PMID:16982644

A microarray immunoassay for simultaneous detection of proteins and bacteria

NASA Technical Reports Server (NTRS)

Delehanty, James B.; Ligler, Frances S.

2002-01-01

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

An interferometric imaging biosensor using weighted spectrum analysis to confirm DNA monolayer films with attogram sensitivity.

PubMed

Fu, Rongxin; Li, Qi; Wang, Ruliang; Xue, Ning; Lin, Xue; Su, Ya; Jiang, Kai; Jin, Xiangyu; Lin, Rongzan; Gan, Wupeng; Lu, Ying; Huang, Guoliang

2018-05-01

Interferometric imaging biosensors are powerful and convenient tools for confirming the existence of DNA monolayer films on silicon microarray platforms. However, their accuracy and sensitivity need further improvement because DNA molecules contribute to an inconspicuous interferometric signal both in thickness and size. Such weaknesses result in poor performance of these biosensors for low DNA content analyses and point mutation tests. In this paper, an interferometric imaging biosensor with weighted spectrum analysis is presented to confirm DNA monolayer films. The interferometric signal of DNA molecules can be extracted and then quantitative detection results for DNA microarrays can be reconstructed. With the proposed strategy, the relative error of thickness detection was reduced from 88.94% to merely 4.15%. The mass sensitivity per unit area of the proposed biosensor reached 20 attograms (ag). Therefore, the sample consumption per unit area of the target DNA content was only 62.5 zeptomoles (zm), with the volume of 0.25 picolitres (pL). Compared with the fluorescence resonance energy transfer (FRET), the measurement veracity of the interferometric imaging biosensor with weighted spectrum analysis is free to the changes in spotting concentration and DNA length. The detection range was more than 1µm. Moreover, single nucleotide mismatch could be pointed out combined with specific DNA ligation. A mutation experiment for lung cancer detection proved the high selectivity and accurate analysis capability of the presented biosensor. Copyright © 2017 Elsevier B.V. All rights reserved.

Mining meiosis and gametogenesis with DNA microarrays.

PubMed

Schlecht, Ulrich; Primig, Michael

2003-04-01

Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

PubMed Central

Ahmed, Zeeshan; Dandekar, Thomas

2018-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool ‘Mining Scientific Literature (MSL)’, which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system’s output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format. PMID:29721305

Waveguide-excited fluorescence microarray

NASA Astrophysics Data System (ADS)

Sagarzazu, Gabriel; Bedu, Mélanie; Martinelli, Lucio; Ha, Khoi-Nguyen; Pelletier, Nicolas; Safarov, Viatcheslav I.; Weisbuch, Claude; Gacoin, Thierry; Benisty, Henri

2008-04-01

Signal-to-noise ratio is a crucial issue in microarray fluorescence read-out. Several strategies are proposed for its improvement. First, light collection in conventional microarrays scanners is quite limited. It was recently shown that almost full collection can be achieved in an integrated lens-free biosensor, with labelled species hybridizing practically on the surface of a sensitive silicon detector [L. Martinelli et al. Appl. Phys. Lett. 91, 083901 (2007)]. However, even with such an improvement, the ultimate goal of real-time measurements during hybridization is challenging: the detector is dazzled by the large fluorescence of labelled species in the solution. In the present paper we show that this unwanted signal can effectively be reduced if the excitation light is confined in a waveguide. Moreover, the concentration of excitation light in a waveguide results in a huge signal gain. In our experiment we realized a structure consisting of a high index sol-gel waveguide deposited on a low-index substrate. The fluorescent molecules deposited on the surface of the waveguide were excited by the evanescent part of a wave travelling in the guide. The comparison with free-space excitation schemes confirms a huge gain (by several orders of magnitude) in favour of waveguide-based excitation. An optical guide deposited onto an integrated biosensor thus combines both advantages of ideal light collection and enhanced surface localized excitation without compromising the imaging properties. Modelling predicts a negligible penalty from spatial cross-talk in practical applications. We believe that such a system would bring microarrays to hitherto unattained sensitivities.

Using phylogenetic probes for quantification of stable isotope labeling and microbial community analysis

DOEpatents

Brodie, Eoin L; DeSantis, Todd Z; Karaoz, Ulas; Andersen, Gary L

2014-12-09

Herein is described methods for a high-sensitivity means to measure the incorporation of stable isotope labeled substrates into RNA following stable isotope probing experiments (SIP). RNA is hybridized to a set of probes such as phylogenetic microarrays and isotope incorporation is quantified such as by secondary ion mass spectrometer imaging (NanoSIMS).

Molecular analysis of meso- and thermophilic microbiota associated with anaerobic biowaste degradation

PubMed Central

2012-01-01

Background Microbial anaerobic digestion (AD) is used as a waste treatment process to degrade complex organic compounds into methane. The archaeal and bacterial taxa involved in AD are well known, whereas composition of the fungal community in the process has been less studied. The present study aimed to reveal the composition of archaeal, bacterial and fungal communities in response to increasing organic loading in mesophilic and thermophilic AD processes by applying 454 amplicon sequencing technology. Furthermore, a DNA microarray method was evaluated in order to develop a tool for monitoring the microbiological status of AD. Results The 454 sequencing showed that the diversity and number of bacterial taxa decreased with increasing organic load, while archaeal i.e. methanogenic taxa remained more constant. The number and diversity of fungal taxa increased during the process and varied less in composition with process temperature than bacterial and archaeal taxa, even though the fungal diversity increased with temperature as well. Evaluation of the microarray using AD sample DNA showed correlation of signal intensities with sequence read numbers of corresponding target groups. The sensitivity of the test was found to be about 1%. Conclusions The fungal community survives in anoxic conditions and grows with increasing organic loading, suggesting that Fungi may contribute to the digestion by metabolising organic nutrients for bacterial and methanogenic groups. The microarray proof of principle tests suggest that the method has the potential for semiquantitative detection of target microbial groups given that comprehensive sequence data is available for probe design. PMID:22727142

Retinal cell responses to elevated intraocular pressure: a gene array comparison between the whole retina and retinal ganglion cell layer.

PubMed

Guo, Ying; Cepurna, William O; Dyck, Jennifer A; Doser, Tom A; Johnson, Elaine C; Morrison, John C

2010-06-01

To determine and compare gene expression patterns in the whole retina and retinal ganglion cell layer (RGCL) in a rodent glaucoma model. IOP was unilaterally elevated in Brown Norway rats (N = 26) by injection of hypertonic saline and monitored for 5 weeks. A cDNA microarray was used on whole retinas from one group of eyes with extensive optic nerve injury and on RGCL isolated by laser capture microdissection (LCM) from another group with comparable injury, to determine the significantly up- or downregulated genes and gene categories in both groups. Expression changes of selected genes were examined by quantitative reverse transcription-PCR (qPCR) to verify microarray results. Microarray analysis of the whole retina identified 632 genes with significantly changed expression (335 up, 297 down), associated with 9 upregulated and 3 downregulated biological processes. In contrast, the RGCL microarray yielded 3726 genes with significantly changed expression (2003 up, 1723 down), including 60% of those found in whole retina. Thirteen distinct upregulated biological processes were identified in the RGCL, dominated by protein synthesis. Among 11 downregulated processes, axon extension and dendrite morphogenesis and generation of precursor metabolism and energy were uniquely identified in the RGCL. qPCR confirmed significant changes in 6 selected messages in whole retina and 11 in RGCL. Increased Atf3, the most upregulated gene in the RGCL, was confirmed by immunohistochemistry of RGCs. Isolation of RGCL by LCM allows a more refined detection of gene response to elevated pressure and improves the potential of determining cellular mechanisms in RGCs and their supporting cells that could be targets for enhancing RGC survival.

MASQOT: a method for cDNA microarray spot quality control

PubMed Central

Bylesjö, Max; Eriksson, Daniel; Sjödin, Andreas; Sjöström, Michael; Jansson, Stefan; Antti, Henrik; Trygg, Johan

2005-01-01

Background cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more. Results A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies. Conclusion The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process. PMID:16223442

Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

PubMed Central

Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

2012-01-01

Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Don S.; Anderson, Kevin K.; White, Amanda M.

Background: A microarray of enzyme-linked immunosorbent assays, or ELISA microarray, predicts simultaneously the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Making sound biological inferences as well as improving the ELISA microarray process require require both concentration predictions and creditable estimates of their errors. Methods: We present a statistical method based on monotonic spline statistical models, penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict concentrations and estimate prediction errors in ELISA microarray. PCLS restrains the flexible spline to a fit of assay intensitymore » that is a monotone function of protein concentration. With MC, both modeling and measurement errors are combined to estimate prediction error. The spline/PCLS/MC method is compared to a common method using simulated and real ELISA microarray data sets. Results: In contrast to the rigid logistic model, the flexible spline model gave credible fits in almost all test cases including troublesome cases with left and/or right censoring, or other asymmetries. For the real data sets, 61% of the spline predictions were more accurate than their comparable logistic predictions; especially the spline predictions at the extremes of the prediction curve. The relative errors of 50% of comparable spline and logistic predictions differed by less than 20%. Monte Carlo simulation rendered acceptable asymmetric prediction intervals for both spline and logistic models while propagation of error produced symmetric intervals that diverged unrealistically as the standard curves approached horizontal asymptotes. Conclusions: The spline/PCLS/MC method is a flexible, robust alternative to a logistic/NLS/propagation-of-error method to reliably predict protein concentrations and estimate their errors. The spline method simplifies model selection and fitting, and reliably estimates believable prediction errors. For the 50% of the real data sets fit well by both methods, spline and logistic predictions are practically indistinguishable, varying in accuracy by less than 15%. The spline method may be useful when automated prediction across simultaneous assays of numerous proteins must be applied routinely with minimal user intervention.« less

Transcriptional landscape of the prenatal human brain.

PubMed

Miller, Jeremy A; Ding, Song-Lin; Sunkin, Susan M; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L; Royall, Joshua J; Aiona, Kaylynn; Arnold, James M; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A; Dee, Nick; Dolbeare, Tim A; Facer, Benjamin A C; Feng, David; Fliss, Tim P; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W; Gu, Guangyu; Howard, Robert E; Jochim, Jayson M; Kuan, Chihchau L; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D; Parry, Sheana E; Stevens, Allison; Pletikos, Mihovil; Reding, Melissa; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V; Shen, Elaine H; Sjoquist, Nathan; Slaughterbeck, Clifford R; Smith, Michael; Sodt, Andy J; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B; Geschwind, Daniel H; Glass, Ian A; Hawrylycz, Michael J; Hevner, Robert F; Huang, Hao; Jones, Allan R; Knowles, James A; Levitt, Pat; Phillips, John W; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G; Lein, Ed S

2014-04-10

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

PubMed Central

2014-01-01

Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

A Versatile Method for Functionalizing Surfaces with Bioactive Glycans

PubMed Central

Cheng, Fang; Shang, Jing; Ratner, Daniel M.

2011-01-01

Microarrays and biosensors owe their functionality to our ability to display surface-bound biomolecules with retained biological function. Versatile, stable, and facile methods for the immobilization of bioactive compounds on surfaces have expanded the application of high-throughput ‘omics’-scale screening of molecular interactions by non-expert laboratories. Herein, we demonstrate the potential of simplified chemistries to fabricate a glycan microarray, utilizing divinyl sulfone (DVS)-modified surfaces for the covalent immobilization of natural and chemically derived carbohydrates, as well as glycoproteins. The bioactivity of the captured glycans was quantitatively examined by surface plasmon resonance imaging (SPRi). Composition and spectroscopic evidence of carbohydrate species on the DVS-modified surface were obtained by X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), respectively. The site-selective immobilization of glycans based on relative nucleophilicity (reducing sugar vs. amine- and sulfhydryl-derived saccharides) and anomeric configuration was also examined. Our results demonstrate straightforward and reproducible conjugation of a variety of functional biomolecules onto a vinyl sulfone-modified biosensor surface. The simplicity of this method will have a significant impact on glycomics research, as it expands the ability of non-synthetic laboratories to rapidly construct functional glycan microarrays and quantitative biosensors. PMID:21142056

Switching benchmarks in cancer of unknown primary: from autopsy to microarray.

PubMed

Pentheroudakis, George; Golfinopoulos, Vassilios; Pavlidis, Nicholas

2007-09-01

Cancer of unknown primary (CUP) is associated with unknown biology and dismal prognosis. Information on the primary site of origin is scant and has never been analysed. We systematically reviewed all published evidence on the CUP primary site identified by two different approaches, either autopsy or microarray gene expression profiling. Published reports on identification of CUP primary site by autopsy or microarray-based multigene expression platforms were retrieved and analysed for year of publication, primary site, patient age, gender, histology, rate of primary identification, manifestations and metastatic deposits, microarray chip technology, training and validation sets, mathematical modelling, classification accuracy and number of classifying genes. From 1944 to 2000, a total of 884 CUP patients (66% males) underwent autopsy in 12 studies after presenting with metastatic or systemic symptoms and succumbing to their disease. A primary was identified in 644 (73%) of them, mostly in the lung (27%), pancreas (24%), hepatobiliary tree (8%), kidneys (8%), bowel, genital system and stomach, as a small focus of adenocarcinoma or poorly differentiated carcinoma. An unpredictable systemic dissemination was evident with high frequency of lung (46%), nodal (35%), bone (17%), brain (16%) and uncommon (18%) deposits. Between the 1944-1980 and the 1980-2000 series, female representation increased, 'undetermined neoplasm' diagnosis became rarer, pancreatic primaries were found less often while colonic ones were identified more frequently. Four studies using microarray technology profiled more than 500 CUP cases using classifier set of genes (ranging from 10 to 495) and reported strikingly dissimilar frequencies of assigned primary sites (lung 11.5%, pancreas 12.5%, bowel 12%, breast 15%, hepatobiliary tree 8%, kidneys 6%, genital system 9%, bladder 5%) in 75-90% of the cases. Evolution in medical imaging technology, diet and lifestyle habits probably account for changing epidemiology of CUP primaries in autopsies. Discrepant assignment of primary sites by microarrays may be due to the presence of 'sanctuary sites' in autopsies, molecular misclassification and the postulated presence of a pro-metastatic genetic signature. In view of the absence of patient therapeutic or prognostic benefit with primary identification, gene expression profiling should be re-orientated towards unraveling the complex pathophysiology of metastases.

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

PubMed Central

2009-01-01

Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a computational framework to reconstruct the genetic regulatory network from the microarray data using biological knowledge and constraint-based inferences. Our method is helpful in verifying possible interaction relations in gene regulatory networks and filtering out incorrect relations inferred by imperfect methods. We predicted not only individual gene related to cancer but also discovered significant gene regulation networks. Our method is also validated in several enriched published papers and databases and the significant gene regulatory networks perform critical biological functions and processes including cell adhesion molecules, androgen and estrogen metabolism, smooth muscle contraction, and GO-annotated processes. Those significant gene regulations and the critical concept of tumor progression are useful to understand cancer biology and disease treatment. PMID:20025723

Relevance of TNBS-Colitis in Rats: A Methodological Study with Endoscopic, Histologic and Transcriptomic Characterization and Correlation to IBD

PubMed Central

Brenna, Øystein; Furnes, Marianne W.; Drozdov, Ignat; van Beelen Granlund, Atle; Flatberg, Arnar; Sandvik, Arne K.; Zwiggelaar, Rosalie T. M.; Mårvik, Ronald; Nordrum, Ivar S.; Kidd, Mark; Gustafsson, Björn I.

2013-01-01

Background Rectal instillation of trinitrobenzene sulphonic acid (TNBS) in ethanol is an established model for inflammatory bowel disease (IBD). We aimed to 1) set up a TNBS-colitis protocol resulting in an endoscopic and histologic picture resembling IBD, 2) study the correlation between endoscopic, histologic and gene expression alterations at different time points after colitis induction, and 3) compare rat and human IBD mucosal transcriptomic data to evaluate whether TNBS-colitis is an appropriate model of IBD. Methodology/Principal Findings Five female Sprague Daley rats received TNBS diluted in 50% ethanol (18 mg/0.6 ml) rectally. The rats underwent colonoscopy with biopsy at different time points. RNA was extracted from rat biopsies and microarray was performed. PCR and in situ hybridization (ISH) were done for validation of microarray results. Rat microarray profiles were compared to human IBD expression profiles (25 ulcerative colitis Endoscopic score demonstrated mild to moderate colitis after three and seven days, but declined after twelve days. Histologic changes corresponded with the endoscopic appearance. Over-represented Gene Ontology Biological Processes included: Cell Adhesion, Immune Response, Lipid Metabolic Process, and Tissue Regeneration. IL-1α, IL-1β, TLR2, TLR4, PRNP were all significantly up-regulated, while PPARγ was significantly down-regulated. Among genes with highest fold change (FC) were SPINK4, LBP, ADA, RETNLB and IL-1α. The highest concordance in differential expression between TNBS and IBD transcriptomes was three days after colitis induction. ISH and PCR results corresponded with the microarray data. The most concordantly expressed biologically relevant pathways included TNF signaling, Cell junction organization, and Interleukin-1 processing. Conclusions/Significance Endoscopy with biopsies in TNBS-colitis is useful to follow temporal changes of inflammation visually and histologically, and to acquire tissue for gene expression analyses. TNBS-colitis is an appropriate model to study specific biological processes in IBD. PMID:23382912

Dynamic and label-free high-throughput detection of biomolecular interactions based on phase-shift interferometry

NASA Astrophysics Data System (ADS)

Li, Qiang; Huang, Guoliang; Gan, Wupeng; Chen, Shengyi

2009-08-01

Biomolecular interactions can be detected by many established technologies such as fluorescence imaging, surface plasmon resonance (SPR)[1-4], interferometry and radioactive labeling of the analyte. In this study, we have designed and constructed a label-free, real-time sensing platform and its operating imaging instrument that detects interactions using optical phase differences from the accumulation of biological material on solid substrates. This system allows us to monitor biomolecular interactions in real time and quantify concentration changes during micro-mixing processes by measuring the changes of the optical path length (OPD). This simple interferometric technology monitors the optical phase difference resulting from accumulated biomolecular mass. A label-free protein chip that forms a 4×4 probe array was designed and fabricated using a commercial microarray robot spotter on solid substrates. Two positive control probe lines of BSA (Bovine Serum Albumin) and two experimental human IgG and goat IgG was used. The binding of multiple protein targets was performed and continuously detected by using this label-free and real-time sensing platform.

A lymphocyte spatial distribution graph-based method for automated classification of recurrence risk on lung cancer images

NASA Astrophysics Data System (ADS)

Garciá-Arteaga, Juan D.; Corredor, Germán.; Wang, Xiangxue; Velcheti, Vamsidhar; Madabhushi, Anant; Romero, Eduardo

2017-11-01

Tumor-infiltrating lymphocytes occurs when various classes of white blood cells migrate from the blood stream towards the tumor, infiltrating it. The presence of TIL is predictive of the response of the patient to therapy. In this paper, we show how the automatic detection of lymphocytes in digital H and E histopathological images and the quantitative evaluation of the global lymphocyte configuration, evaluated through global features extracted from non-parametric graphs, constructed from the lymphocytes' detected positions, can be correlated to the patient's outcome in early-stage non-small cell lung cancer (NSCLC). The method was assessed on a tissue microarray cohort composed of 63 NSCLC cases. From the evaluated graphs, minimum spanning trees and K-nn showed the highest predictive ability, yielding F1 Scores of 0.75 and 0.72 and accuracies of 0.67 and 0.69, respectively. The predictive power of the proposed methodology indicates that graphs may be used to develop objective measures of the infiltration grade of tumors, which can, in turn, be used by pathologists to improve the decision making and treatment planning processes.

Microscopy Images as Interactive Tools in Cell Modeling and Cell Biology Education

PubMed Central

Araújo-Jorge, Tania C.; Cardona, Tania S.; Mendes, Cláudia L. S.; Henriques-Pons, Andrea; Meirelles, Rosane M. S.; Coutinho, Cláudia M. L. M.; Aguiar, Luiz Edmundo V.; Meirelles, Maria de Nazareth L.; de Castro, Solange L.; Barbosa, Helene S.; Luz, Mauricio R. M. P.

2004-01-01

The advent of genomics, proteomics, and microarray technology has brought much excitement to science, both in teaching and in learning. The public is eager to know about the processes of life. In the present context of the explosive growth of scientific information, a major challenge of modern cell biology is to popularize basic concepts of structures and functions of living cells, to introduce people to the scientific method, to stimulate inquiry, and to analyze and synthesize concepts and paradigms. In this essay we present our experience in mixing science and education in Brazil. For two decades we have developed activities for the science education of teachers and undergraduate students, using microscopy images generated by our work as cell biologists. We describe open-air outreach education activities, games, cell modeling, and other practical and innovative activities presented in public squares and favelas. Especially in developing countries, science education is important, since it may lead to an improvement in quality of life while advancing understanding of traditional scientific ideas. We show that teaching and research can be mutually beneficial rather than competing pursuits in advancing these goals. PMID:15257338

Cell and tissue microarray technologies for protein and nucleic acid expression profiling.

PubMed

Cardano, Marina; Diaferia, Giuseppe R; Falavigna, Maurizio; Spinelli, Chiara C; Sessa, Fausto; DeBlasio, Pasquale; Biunno, Ida

2013-02-01

Tissue microarray (TMA) and cell microarray (CMA) are two powerful techniques that allow for the immunophenotypical characterization of hundreds of samples simultaneously. In particular, the CMA approach is particularly useful for immunophenotyping new stem cell lines (e.g., cardiac, neural, mesenchymal) using conventional markers, as well as for testing the specificity and the efficacy of newly developed antibodies. We propose the use of a tissue arrayer not only to perform protein expression profiling by immunohistochemistry but also to carry out molecular genetics studies. In fact, starting with several tissues or cell lines, it is possible to obtain the complete signature of each sample, describing the protein, mRNA and microRNA expression, and DNA mutations, or eventually to analyze the epigenetic processes that control protein regulation. Here we show the results obtained using the Galileo CK4500 TMA platform.

Carbohydrate Cluster Microarrays Fabricated on 3-Dimensional Dendrimeric Platforms for Functional Glycomics Exploration

PubMed Central

Zhou, Xichun; Turchi, Craig; Wang, Denong

2009-01-01

We reported here a novel, ready-to-use bioarray platform and methodology for construction of sensitive carbohydrate cluster microarrays. This technology utilizes a 3-dimensional (3-D) poly(amidoamine) starburst dendrimer monolayer assembled on glass surface, which is functionalized with terminal aminooxy and hydrazide groups for site-specific coupling of carbohydrates. A wide range of saccharides, including monosaccharides, oligosaccharides and polysaccharides of diverse structures, are applicable for the 3-D bioarray platform without prior chemical derivatization. The process of carbohydrate coupling is effectively accelerated by microwave radiation energy. The carbohydrate concentration required for microarray fabrication is substantially reduced using this technology. Importantly, this bioarray platform presents sugar chains in defined orientation and cluster configurations. It is, thus, uniquely useful for exploration of the structural and conformational diversities of glyco-epitope and their functional properties. PMID:19791771

Peptides and Anti-peptide Antibodies for Small and Medium Scale Peptide and Anti-peptide Affinity Microarrays: Antigenic Peptide Selection, Immobilization, and Processing.

PubMed

Zhang, Fan; Briones, Andrea; Soloviev, Mikhail

2016-01-01

This chapter describes the principles of selection of antigenic peptides for the development of anti-peptide antibodies for use in microarray-based multiplex affinity assays and also with mass-spectrometry detection. The methods described here are mostly applicable to small to medium scale arrays. Although the same principles of peptide selection would be suitable for larger scale arrays (with 100+ features) the actual informatics software and printing methods may well be different. Because of the sheer number of proteins/peptides to be processed and analyzed dedicated software capable of processing all the proteins and an enterprise level array robotics may be necessary for larger scale efforts. This report aims to provide practical advice to those who develop or use arrays with up to ~100 different peptide or protein features.

Abnormal brain magnetic resonance imaging in two patients with Smith-Magenis syndrome.

PubMed

Maya, Idit; Vinkler, Chana; Konen, Osnat; Kornreich, Liora; Steinberg, Tamar; Yeshaya, Josepha; Latarowski, Victoria; Shohat, Mordechai; Lev, Dorit; Baris, Hagit N

2014-08-01

Smith-Magenis syndrome (SMS) is a clinically recognizable contiguous gene syndrome ascribed to an interstitial deletion in chromosome 17p11.2. Seventy percent of SMS patients have a common deletion interval spanning 3.5 megabases (Mb). Clinical features of SMS include characteristic mild dysmorphic features, ocular anomalies, short stature, brachydactyly, and hypotonia. SMS patients have a unique neurobehavioral phenotype that includes intellectual disability, self-injurious behavior and severe sleep disturbance. Little has been reported in the medical literature about anatomical brain anomalies in patients with SMS. Here we describe two patients with SMS caused by the common deletion in 17p11.2 diagnosed using chromosomal microarray (CMA). Both patients had a typical clinical presentation and abnormal brain magnetic resonance imaging (MRI) findings. One patient had subependymal periventricular gray matter heterotopia, and the second had a thin corpus callosum, a thin brain stem and hypoplasia of the cerebellar vermis. This report discusses the possible abnormal MRI images in SMS and reviews the literature on brain malformations in SMS. Finally, although structural brain malformations in SMS patients are not a common feature, we suggest baseline routine brain imaging in patients with SMS in particular, and in patients with chromosomal microdeletion/microduplication syndromes in general. Structural brain malformations in these patients may affect the decision-making process regarding their management. © 2014 Wiley Periodicals, Inc.

Image Analysis Algorithms for Immunohistochemical Assessment of Cell Death Events and Fibrosis in Tissue Sections

PubMed Central

Krajewska, Maryla; Smith, Layton H.; Rong, Juan; Huang, Xianshu; Hyer, Marc L.; Zeps, Nikolajs; Iacopetta, Barry; Linke, Steven P.; Olson, Allen H.; Reed, John C.; Krajewski, Stan

2009-01-01

Cell death is of broad physiological and pathological importance, making quantification of biochemical events associated with cell demise a high priority for experimental pathology. Fibrosis is a common consequence of tissue injury involving necrotic cell death. Using tissue specimens from experimental mouse models of traumatic brain injury, cardiac fibrosis, and cancer, as well as human tumor specimens assembled in tissue microarray (TMA) format, we undertook computer-assisted quantification of specific immunohistochemical and histological parameters that characterize processes associated with cell death. In this study, we demonstrated the utility of image analysis algorithms for color deconvolution, colocalization, and nuclear morphometry to characterize cell death events in tissue specimens: (a) subjected to immunostaining for detecting cleaved caspase-3, cleaved poly(ADP-ribose)-polymerase, cleaved lamin-A, phosphorylated histone H2AX, and Bcl-2; (b) analyzed by terminal deoxyribonucleotidyl transferase–mediated dUTP nick end labeling assay to detect DNA fragmentation; and (c) evaluated with Masson's trichrome staining. We developed novel algorithm-based scoring methods and validated them using TMAs as a high-throughput format. The proposed computer-assisted scoring methods for digital images by brightfield microscopy permit linear quantification of immunohistochemical and histochemical stainings. Examples are provided of digital image analysis performed in automated or semiautomated fashion for successful quantification of molecular events associated with cell death in tissue sections. (J Histochem Cytochem 57:649–663, 2009) PMID:19289554

Childhood chronic inflammatory demyelinating polyneuropathy: an overview of 10 cases in the modern era.

PubMed

Ware, Tyson L; Kornberg, Andrew J; Rodriguez-Casero, M Victoria; Ryan, Monique M

2014-01-01

Chronic inflammatory demyelinating polyneuropathy is a rare condition in children. In this article, we report our experience in the management of 10 cases of childhood chronic inflammatory demyelinating polyneuropathy in a single center, in the era of contrast-enhanced magnetic resonance imaging (MRI), genetic microarray, and chronic inflammatory demyelinating polyneuropathy disease activity status. Robust neurophysiologic abnormalities were present in all cases and both MRI and lumbar puncture were useful adjuncts in diagnosis. Genetic microarray is a simple technique useful in excluding the most common hereditary demyelinating neuropathy. Intravenous immunoglobulin was an effective first-line therapy in most cases, with refractory cases responding to corticosteroids and rituximab. We found the chronic inflammatory demyelinating polyneuropathy disease activity status useful for assessing outcome at final follow-up, whereas the modified Rankin score was better for assessing peak motor disability.

Deletion of the transcriptional coactivator PGC1α in skeletal muscles is associated with reduced expression of genes related to oxidative muscle function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hatazawa, Yukino; Research Fellow of Japan Society for the Promotion of Science, Tokyo; Minami, Kimiko

The expression of the transcriptional coactivator PGC1α is increased in skeletal muscles during exercise. Previously, we showed that increased PGC1α leads to prolonged exercise performance (the duration for which running can be continued) and, at the same time, increases the expression of branched-chain amino acid (BCAA) metabolism-related enzymes and genes that are involved in supplying substrates for the TCA cycle. We recently created mice with PGC1α knockout specifically in the skeletal muscles (PGC1α KO mice), which show decreased mitochondrial content. In this study, global gene expression (microarray) analysis was performed in the skeletal muscles of PGC1α KO mice compared withmore » that of wild-type control mice. As a result, decreased expression of genes involved in the TCA cycle, oxidative phosphorylation, and BCAA metabolism were observed. Compared with previously obtained microarray data on PGC1α-overexpressing transgenic mice, each gene showed the completely opposite direction of expression change. Bioinformatic analysis of the promoter region of genes with decreased expression in PGC1α KO mice predicted the involvement of several transcription factors, including a nuclear receptor, ERR, in their regulation. As PGC1α KO microarray data in this study show opposing findings to the PGC1α transgenic data, a loss-of-function experiment, as well as a gain-of-function experiment, revealed PGC1α’s function in the oxidative energy metabolism of skeletal muscles. - Highlights: • Microarray analysis was performed in the skeletal muscle of PGC1α KO mice. • Expression of genes in the oxidative energy metabolism was decreased. • Bioinformatic analysis of promoter region of the genes predicted involvement of ERR. • PGC1α KO microarray data in this study show the mirror image of transgenic data.« less

Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice.

PubMed

Bruno, D L; Ganesamoorthy, D; Schoumans, J; Bankier, A; Coman, D; Delatycki, M; Gardner, R J M; Hunter, M; James, P A; Kannu, P; McGillivray, G; Pachter, N; Peters, H; Rieubland, C; Savarirayan, R; Scheffer, I E; Sheffield, L; Tan, T; White, S M; Yeung, A; Bowman, Z; Ngo, C; Choy, K W; Cacheux, V; Wong, L; Amor, D J; Slater, H R

2009-02-01

Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.

Portable, stand-off spectral imaging camera for detection of effluents and residues

NASA Astrophysics Data System (ADS)

Goldstein, Neil; St. Peter, Benjamin; Grot, Jonathan; Kogan, Michael; Fox, Marsha; Vujkovic-Cvijin, Pajo; Penny, Ryan; Cline, Jason

2015-06-01

A new, compact and portable spectral imaging camera, employing a MEMs-based encoded imaging approach, has been built and demonstrated for detection of hazardous contaminants including gaseous effluents and solid-liquid residues on surfaces. The camera is called the Thermal infrared Reconfigurable Analysis Camera for Effluents and Residues (TRACER). TRACER operates in the long wave infrared and has the potential to detect a wide variety of materials with characteristic spectral signatures in that region. The 30 lb. camera is tripod mounted and battery powered. A touch screen control panel provides a simple user interface for most operations. The MEMS spatial light modulator is a Texas Instruments Digital Microarray Array with custom electronics and firmware control. Simultaneous 1D-spatial and 1Dspectral dimensions are collected, with the second spatial dimension obtained by scanning the internal spectrometer slit. The sensor can be configured to collect data in several modes including full hyperspectral imagery using Hadamard multiplexing, panchromatic thermal imagery, and chemical-specific contrast imagery, switched with simple user commands. Matched filters and other analog filters can be generated internally on-the-fly and applied in hardware, substantially reducing detection time and improving SNR over HSI software processing, while reducing storage requirements. Results of preliminary instrument evaluation and measurements of flame exhaust are presented.

Alternate Metabolic Programs Define Regional Variation of Relevant Biological Features in Renal Cell Carcinoma Progression.

PubMed

Brooks, Samira A; Khandani, Amir H; Fielding, Julia R; Lin, Weili; Sills, Tiffany; Lee, Yueh; Arreola, Alexandra; Milowsky, Mathew I; Wallen, Eric M; Woods, Michael E; Smith, Angie B; Nielsen, Mathew E; Parker, Joel S; Lalush, David S; Rathmell, W Kimryn

2016-06-15

Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans. ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis. Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA- and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype. Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease. Clin Cancer Res; 22(12); 2950-9. ©2016 AACR. ©2016 American Association for Cancer Research.

HPASubC: A suite of tools for user subclassification of human protein atlas tissue images.

PubMed

Cornish, Toby C; Chakravarti, Aravinda; Kapoor, Ashish; Halushka, Marc K

2015-01-01

The human protein atlas (HPA) is a powerful proteomic tool for visualizing the distribution of protein expression across most human tissues and many common malignancies. The HPA includes immunohistochemically-stained images from tissue microarrays (TMAs) that cover 48 tissue types and 20 common malignancies. The TMA data are used to provide expression information at the tissue, cellular, and occasionally, subcellular level. The HPA also provides subcellular data from confocal immunofluorescence data on three cell lines. Despite the availability of localization data, many unique patterns of cellular and subcellular expression are not documented. To get at this more granular data, we have developed a suite of Python scripts, HPASubC, to aid in subcellular, and cell-type specific classification of HPA images. This method allows the user to download and optimize specific HPA TMA images for review. Then, using a playstation-style video game controller, a trained observer can rapidly step through 10's of 1000's of images to identify patterns of interest. We have successfully used this method to identify 703 endothelial cell (EC) and/or smooth muscle cell (SMCs) specific proteins discovered within 49,200 heart TMA images. This list will assist us in subdividing cardiac gene or protein array data into expression by one of the predominant cell types of the myocardium: Myocytes, SMCs or ECs. The opportunity to further characterize unique staining patterns across a range of human tissues and malignancies will accelerate our understanding of disease processes and point to novel markers for tissue evaluation in surgical pathology.

HPASubC: A suite of tools for user subclassification of human protein atlas tissue images

PubMed Central

Cornish, Toby C.; Chakravarti, Aravinda; Kapoor, Ashish; Halushka, Marc K.

2015-01-01

Background: The human protein atlas (HPA) is a powerful proteomic tool for visualizing the distribution of protein expression across most human tissues and many common malignancies. The HPA includes immunohistochemically-stained images from tissue microarrays (TMAs) that cover 48 tissue types and 20 common malignancies. The TMA data are used to provide expression information at the tissue, cellular, and occasionally, subcellular level. The HPA also provides subcellular data from confocal immunofluorescence data on three cell lines. Despite the availability of localization data, many unique patterns of cellular and subcellular expression are not documented. Materials and Methods: To get at this more granular data, we have developed a suite of Python scripts, HPASubC, to aid in subcellular, and cell-type specific classification of HPA images. This method allows the user to download and optimize specific HPA TMA images for review. Then, using a playstation-style video game controller, a trained observer can rapidly step through 10's of 1000's of images to identify patterns of interest. Results: We have successfully used this method to identify 703 endothelial cell (EC) and/or smooth muscle cell (SMCs) specific proteins discovered within 49,200 heart TMA images. This list will assist us in subdividing cardiac gene or protein array data into expression by one of the predominant cell types of the myocardium: Myocytes, SMCs or ECs. Conclusions: The opportunity to further characterize unique staining patterns across a range of human tissues and malignancies will accelerate our understanding of disease processes and point to novel markers for tissue evaluation in surgical pathology. PMID:26167380

Transcriptional profiling of the parr–smolt transformation in Atlantic salmon

USGS Publications Warehouse

Robertson, Laura S.; McCormick, Stephen D.

2012-01-01

The parr–smolt transformation in Atlantic salmon (Salmo salar) is a complex developmental process that culminates in the ability to migrate to and live in seawater. We used GRASP 16K cDNA microarrays to identify genes that are differentially expressed in the liver, gill, hypothalamus, pituitary, and olfactory rosettes of smolts compared to parr. Smolts had higher levels of gill Na+/K+-ATPase activity, plasma cortisol and plasma thyroid hormones relative to parr. Across all five tissues, stringent microarray analyses identified 48 features that were differentially expressed in smolts compared to parr. Using a less stringent method we found 477 features that were differentially expressed at least 1.2-fold in smolts, including 172 features in the gill. Smolts had higher mRNA levels of genes involved in transcription, protein biosynthesis and folding, electron transport, oxygen transport, and sensory perception and lower mRNA levels for genes involved in proteolysis. Quantitative RT-PCR was used to confirm differential expression in select genes identified by microarray analyses and to quantify expression of other genes known to be involved in smolting. This study expands our understanding of the molecular processes that underlie smolting in Atlantic salmon and identifies genes for further investigation.

Microarray Detection of Duplex and Triplex DNA Binders with DNA-Modified Gold Nanoparticles

PubMed Central

Lytton-Jean, Abigail K. R.; Han, Min Su; Mirkin, Chad A.

2008-01-01

We have designed a chip-based assay, using microarray technology, for determining the relative binding affinities of duplex and triplex DNA binders. This assay combines the high discrimination capabilities afforded by DNA-modified Au nanoparticles with the high-throughput capabilities of DNA microarrays. The detection and screening of duplex DNA binders are important because these molecules, in many cases, are potential anticancer agents as well as toxins. Triplex DNA binders are also promising drug candidates. These molecules, in conjunction with triplex forming oligonucleotides, could potentially be used to achieve control of gene expression by interfering with transcription factors that bind to DNA. Therefore, the ability to screen for these molecules in a high-throughput fashion could dramatically improve the drug screening process. The assay reported here provides excellent discrimination between strong, intermediate, and weak duplex and triplex DNA binders in a high-throughput fashion. PMID:17614366

Cell and Tissue Microarray Technologies for Protein and Nucleic Acid Expression Profiling

PubMed Central

Cardano, Marina; Diaferia, Giuseppe R.; Falavigna, Maurizio; Spinelli, Chiara C.; Sessa, Fausto; DeBlasio, Pasquale

2013-01-01

Tissue microarray (TMA) and cell microarray (CMA) are two powerful techniques that allow for the immunophenotypical characterization of hundreds of samples simultaneously. In particular, the CMA approach is particularly useful for immunophenotyping new stem cell lines (e.g., cardiac, neural, mesenchymal) using conventional markers, as well as for testing the specificity and the efficacy of newly developed antibodies. We propose the use of a tissue arrayer not only to perform protein expression profiling by immunohistochemistry but also to carry out molecular genetics studies. In fact, starting with several tissues or cell lines, it is possible to obtain the complete signature of each sample, describing the protein, mRNA and microRNA expression, and DNA mutations, or eventually to analyze the epigenetic processes that control protein regulation. Here we show the results obtained using the Galileo CK4500 TMA platform. PMID:23172795

Rapid and Facile Microwave-Assisted Surface Chemistry for Functionalized Microarray Slides

PubMed Central

Lee, Jeong Heon; Hyun, Hoon; Cross, Conor J.; Henary, Maged; Nasr, Khaled A.; Oketokoun, Rafiou; Choi, Hak Soo; Frangioni, John V.

2011-01-01

We describe a rapid and facile method for surface functionalization and ligand patterning of glass slides based on microwave-assisted synthesis and a microarraying robot. Our optimized reaction enables surface modification 42-times faster than conventional techniques and includes a carboxylated self-assembled monolayer, polyethylene glycol linkers of varying length, and stable amide bonds to small molecule, peptide, or protein ligands to be screened for binding to living cells. We also describe customized slide racks that permit functionalization of 100 slides at a time to produce a cost-efficient, highly reproducible batch process. Ligand spots can be positioned on the glass slides precisely using a microarraying robot, and spot size adjusted for any desired application. Using this system, we demonstrate live cell binding to a variety of ligands and optimize PEG linker length. Taken together, the technology we describe should enable high-throughput screening of disease-specific ligands that bind to living cells. PMID:23467787

Fabrication of high quality cDNA microarray using a small amount of cDNA.

PubMed

Park, Chan Hee; Jeong, Ha Jin; Jung, Jae Jun; Lee, Gui Yeon; Kim, Sang-Chul; Kim, Tae Soo; Yang, Sang Hwa; Chung, Hyun Cheol; Rha, Sun Young

2004-05-01

DNA microarray technology has become an essential part of biological research. It enables the genome-scale analysis of gene expression in various types of model systems. Manufacturing high quality cDNA microarrays of microdeposition type depends on some key factors including a printing device, spotting pins, glass slides, spotting solution, and humidity during spotting. UsingEthe Microgrid II TAS model printing device, this study defined the optimal conditions for producing high density, high quality cDNA microarrays with the least amount of cDNA product. It was observed that aminosilane-modified slides were superior to other types of surface modified-slides. A humidity of 30+/-3% in a closed environment and the overnight drying of the spotted slides gave the best conditions for arraying. In addition, the cDNA dissolved in 30% DMSO gave the optimal conditions for spotting compared to the 1X ArrayIt, 3X SSC and 50% DMSO. Lastly, cDNA in the concentration range of 100-300 ng/ micro l was determined to be best for arraying and post-processing. Currently, the printing system in this study yields reproducible 9000 spots with a spot size 150 mm diameter, and a 200 nm spot spacing.

Customizing microarrays for neuroscience drug discovery.

PubMed

Girgenti, Matthew J; Newton, Samuel S

2007-08-01

Microarray-based gene profiling has become the centerpiece of gene expression studies in the biological sciences. The ability to now interrogate the entire genome using a single chip demonstrates the progress in technology and instrumentation that has been made over the last two decades. Although this unbiased approach provides researchers with an immense quantity of data, obtaining meaningful insight is not possible without intensive data analysis and processing. Custom developed arrays have emerged as a viable and attractive alternative that can take advantage of this robust technology and tailor it to suit the needs and requirements of individual investigations. The ability to simplify data analysis, reduce noise and carefully optimize experimental conditions makes it a suitable tool that can be effectively utilized in neuroscience drug discovery efforts. Furthermore, incorporating recent advancements in fine focusing gene profiling to include specific cellular phenotypes can help resolve the complex cellular heterogeneity of the brain. This review surveys the use of microarray technology in neuroscience paying special attention to customized arrays and their potential in drug discovery. Novel applications of microarrays and ancillary techniques, such as laser microdissection, FAC sorting and RNA amplification, have also been discussed. The notion that a hypothesis-driven approach can be integrated into drug development programs is highlighted.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions.

PubMed

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions

PubMed Central

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity. PMID:25191551

Tomato Expression Database (TED): a suite of data presentation and analysis tools

PubMed Central

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at . PMID:16381976

Tomato Expression Database (TED): a suite of data presentation and analysis tools.

PubMed

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150,000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at http://ted.bti.cornell.edu.

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

PubMed Central

2011-01-01

Background Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods. The recently introduced B-spline function based mutual information estimation method is competitive to the kernel based methods in terms of quality but at a lower computational complexity. Results We present a new approach to accelerate the B-spline function based mutual information estimation algorithm with commodity graphics hardware. To derive an efficient mapping onto this type of architecture, we have used the Compute Unified Device Architecture (CUDA) programming model to design and implement a new parallel algorithm. Our implementation, called CUDA-MI, can achieve speedups of up to 82 using double precision on a single GPU compared to a multi-threaded implementation on a quad-core CPU for large microarray datasets. We have used the results obtained by CUDA-MI to infer gene regulatory networks (GRNs) from microarray data. The comparisons to existing methods including ARACNE and TINGe show that CUDA-MI produces GRNs of higher quality in less time. Conclusions CUDA-MI is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant speedup over sequential multi-threaded implementation by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs. PMID:21672264

High-throughput investigation of endothelial-to-mesenchymal transformation (EndMT) with combinatorial cellular microarrays.

PubMed

Wang, Zongjie; Calpe, Blaise; Zerdani, Jalil; Lee, Youngsang; Oh, Jonghyun; Bae, Hojae; Khademhosseini, Ali; Kim, Keekyoung

2016-07-01

In the developing heart, a specific subset of endocardium undergoes an endothelial-to-mesenchymal transformation (EndMT) thus forming nascent valve leaflets. Extracellular matrix (ECM) proteins and growth factors (GFs) play important roles in regulating EndMT but the combinatorial effect of GFs with ECM proteins is less well understood. Here we use microscale engineering techniques to create single, binary, and tertiary component microenvironments to investigate the combinatorial effects of ECM proteins and GFs on the attachment and transformation of adult ovine mitral valve endothelial cells to a mesenchymal phenotype. With the combinatorial microenvironment microarrays, we utilized 60 different combinations of ECM proteins (Fibronectin, Collagen I, II, IV, Laminin) and GFs (TGF-β1, bFGF, VEGF) and were able to identify new microenvironmental conditions capable of modulating EndMT in MVECs. Experimental results indicated that TGF-β1 significantly upregulated the EndMT while either bFGF or VEGF downregulated EndMT process markedly. Also, ECM proteins could influence both the attachment of MVECs and the response of MVECs to GFs. In terms of attachment, fibronectin is significantly better for the adhesion of MVECs among the five tested proteins. Overall collagen IV and fibronectin appeared to play important roles in promoting EndMT process. Great consistency between macroscale and microarrayed experiments and present studies demonstrates that high-throughput cellular microarrays are a promising approach to study the regulation of EndMT in valvular endothelium. Biotechnol. Bioeng. 2016;113: 1403-1412. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Photo-Attachment of Biomolecules for Miniaturization on Wicking Si-Nanowire Platform

PubMed Central

Cheng, He; Zheng, Han; Wu, Jia Xin; Xu, Wei; Zhou, Lihan; Leong, Kam Chew; Fitzgerald, Eugene; Rajagopalan, Raj; Too, Heng Phon; Choi, Wee Kiong

2015-01-01

We demonstrated the surface functionalization of a highly three-dimensional, superhydrophilic wicking substrate using light to immobilize functional biomolecules for sensor or microarray applications. We showed here that the three-dimensional substrate was compatible with photo-attachment and the performance of functionalization was greatly improved due to both increased surface capacity and reduced substrate reflectivity. In addition, photo-attachment circumvents the problems induced by wicking effect that was typically encountered on superhydrophilic three-dimensional substrates, thus reducing the difficulty of producing miniaturized sites on such substrate. We have investigated various aspects of photo-attachment process on the nanowire substrate, including the role of different buffers, the effect of wavelength as well as how changing probe structure may affect the functionalization process. We demonstrated that substrate fabrication and functionalization can be achieved with processes compatible with microelectronics processes, hence reducing the cost of array fabrication. Such functionalization method coupled with the high capacity surface makes the substrate an ideal candidate for sensor or microarray for sensitive detection of target analytes. PMID:25689680

Importing MAGE-ML format microarray data into BioConductor.

PubMed

Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart

2004-12-12

The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.

Solving satisfiability problems using a novel microarray-based DNA computer.

PubMed

Lin, Che-Hsin; Cheng, Hsiao-Ping; Yang, Chang-Biau; Yang, Chia-Ning

2007-01-01

An algorithm based on a modified sticker model accompanied with an advanced MEMS-based microarray technology is demonstrated to solve SAT problem, which has long served as a benchmark in DNA computing. Unlike conventional DNA computing algorithms needing an initial data pool to cover correct and incorrect answers and further executing a series of separation procedures to destroy the unwanted ones, we built solutions in parts to satisfy one clause in one step, and eventually solve the entire Boolean formula through steps. No time-consuming sample preparation procedures and delicate sample applying equipment were required for the computing process. Moreover, experimental results show the bound DNA sequences can sustain the chemical solutions during computing processes such that the proposed method shall be useful in dealing with large-scale problems.

Probe classification of on-off type DNA microarray images with a nonlinear matching measure

NASA Astrophysics Data System (ADS)

Ryu, Munho; Kim, Jong Dae; Min, Byoung Goo; Kim, Jongwon; Kim, Y. Y.

2006-01-01

We propose a nonlinear matching measure, called counting measure, as a signal detection measure that is defined as the number of on pixels in the spot area. It is applied to classify probes for an on-off type DNA microarray, where each probe spot is classified as hybridized or not. The counting measure also incorporates the maximum response search method, where the expected signal is obtained by taking the maximum among the measured responses of the various positions and sizes of the spot template. The counting measure was compared to existing signal detection measures such as the normalized covariance and the median for 2390 patient samples tested on the human papillomavirus (HPV) DNA chip. The counting measure performed the best regardless of whether or not the maximum response search method was used. The experimental results showed that the counting measure combined with the positional search was the most preferable.

A genome-scale map of expression for a mouse brain section obtained using voxelation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, Mark H.; Geng, Alex B.; Khan, Arshad H.

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed 2- dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genesmore » with unexpected patterns were identified and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.« less

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

PubMed

Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

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

PubMed

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

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

Transcriptome analysis of the human T lymphocyte cell line Jurkat and human peripheral blood mononuclear cells exposed to deoxynivalenol (DON): New mechanistic insights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katika, Madhumohan R.; Department of Health Risk Analysis and Toxicology, Maastricht University; Netherlands Toxicogenomics Centre

Deoxynivalenol (DON) or vomitoxin is a commonly encountered type-B trichothecene mycotoxin, produced by Fusarium species predominantly found in cereals and grains. DON is known to exert toxic effects on the gastrointestinal, reproductive and neuroendocrine systems, and particularly on the immune system. Depending on dose and exposure time, it can either stimulate or suppress immune function. The main objective of this study was to obtain a deeper insight into DON-induced effects on lymphoid cells. For this, we exposed the human T-lymphocyte cell line Jurkat and human peripheral blood mononuclear cells (PBMCs) to various concentrations of DON for various times and examinedmore » gene expression changes by DNA microarray analysis. Jurkat cells were exposed to 0.25 and 0.5 μM DON for 3, 6 and 24 h. Biological interpretation of the microarray data indicated that DON affects various processes in these cells: It upregulates genes involved in ribosome structure and function, RNA/protein synthesis and processing, endoplasmic reticulum (ER) stress, calcium-mediated signaling, mitochondrial function, oxidative stress, the NFAT and NF-κB/TNF-α pathways, T cell activation and apoptosis. The effects of DON on the expression of genes involved in ER stress, NFAT activation and apoptosis were confirmed by qRT-PCR. Other biochemical experiments confirmed that DON activates calcium-dependent proteins such as calcineurin and M-calpain that are known to be involved in T cell activation and apoptosis. Induction of T cell activation was also confirmed by demonstrating that DON activates NFATC1 and induces its translocation from the cytoplasm to the nucleus. For the gene expression profiling of PBMCs, cells were exposed to 2 and 4 μM DON for 6 and 24 h. Comparison of the Jurkat microarray data with those obtained with PBMCs showed that most of the processes affected by DON in the Jurkat cell line were also affected in the PBMCs. -- Highlights: ► The human T cell line Jurkat and human PBMCs were exposed to DON. ► Whole-genome microarray experiments were performed. ► Microarray data indicates that DON affects ribosome and RNA/protein synthesis. ► DON treatment induces ER stress, calcium mediated signaling, NFAT and NF-κB. ► Exposure to DON induces T cell activation, oxidative stress and apoptosis.« less

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

PubMed Central

2010-01-01

Background Flax (Linum usitatissimum L.) has been cultivated for around 9,000 years and is therefore one of the oldest cultivated species. Today, flax is still grown for its oil (oil-flax or linseed cultivars) and its cellulose-rich fibres (fibre-flax cultivars) used for high-value linen garments and composite materials. Despite the wide industrial use of flax-derived products, and our actual understanding of the regulation of both wood fibre production and oil biosynthesis more information must be acquired in both domains. Recent advances in genomics are now providing opportunities to improve our fundamental knowledge of these complex processes. In this paper we report the development and validation of a high-density oligo microarray platform dedicated to gene expression analyses in flax. Results Nine different RNA samples obtained from flax inner- and outer-stems, seeds, leaves and roots were used to generate a collection of 1,066,481 ESTs by massive parallel pyrosequencing. Sequences were assembled into 59,626 unigenes and 48,021 sequences were selected for oligo design and high-density microarray (Nimblegen 385K) fabrication with eight, non-overlapping 25-mers oligos per unigene. 18 independent experiments were used to evaluate the hybridization quality, precision, specificity and accuracy and all results confirmed the high technical quality of our microarray platform. Cross-validation of microarray data was carried out using quantitative qRT-PCR. Nine target genes were selected on the basis of microarray results and reflected the whole range of fold change (both up-regulated and down-regulated genes in different samples). A statistically significant positive correlation was obtained comparing expression levels for each target gene across all biological replicates both in qRT-PCR and microarray results. Further experiments illustrated the capacity of our arrays to detect differential gene expression in a variety of flax tissues as well as between two contrasted flax varieties. Conclusion All results suggest that our high-density flax oligo-microarray platform can be used as a very sensitive tool for analyzing gene expression in a large variety of tissues as well as in different cultivars. Moreover, this highly reliable platform can also be used for the quantification of mRNA transcriptional profiling in different flax tissues. PMID:20964859

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

PubMed

Fenart, Stéphane; Ndong, Yves-Placide Assoumou; Duarte, Jorge; Rivière, Nathalie; Wilmer, Jeroen; van Wuytswinkel, Olivier; Lucau, Anca; Cariou, Emmanuelle; Neutelings, Godfrey; Gutierrez, Laurent; Chabbert, Brigitte; Guillot, Xavier; Tavernier, Reynald; Hawkins, Simon; Thomasset, Brigitte

2010-10-21

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

Microarray study of single nucleotide polymorphisms and expression of ATP-binding cassette genes in breast tumors

NASA Astrophysics Data System (ADS)

Tsyganov, M. M.; Ibragimova, M. K.; Karabut, I. V.; Freydin, M. B.; Choinzonov, E. L.; Litvyakov, N. V.

2015-11-01

Our previous research establishes that changes of expression of the ATP-binding cassette genes family is connected with the neoadjuvant chemotherapy effect. However, the mechanism of regulation of resistance gene expression remains unclear. As many researchers believe, single nucleotide polymorphisms can be involved in this process. Thereupon, microarray analysis is used to study polymorphisms in ATP-binding cassette genes. It is thus found that MDR gene expression is connected with 5 polymorphisms, i.e. rs241432, rs241429, rs241430, rs3784867, rs59409230, which participate in the regulation of expression of own genes.

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening.

PubMed

Costa, Fabrizio; Alba, Rob; Schouten, Henk; Soglio, Valeria; Gianfranceschi, Luca; Serra, Sara; Musacchi, Stefano; Sansavini, Silviero; Costa, Guglielmo; Fei, Zhangjun; Giovannoni, James

2010-10-25

Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-methylcyclopropene. To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated.The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species.

Differential Adipose Tissue Gene Expression Profiles in Abacavir Treated Patients That May Contribute to the Understanding of Cardiovascular Risk: A Microarray Study

PubMed Central

Shahmanesh, Mohsen; Phillips, Kenneth; Boothby, Meg; Tomlinson, Jeremy W.

2015-01-01

Objective To compare changes in gene expression by microarray from subcutaneous adipose tissue from HIV treatment naïve patients treated with efavirenz based regimens containing abacavir (ABC), tenofovir (TDF) or zidovidine (AZT). Design Subcutaneous fat biopsies were obtained before, at 6- and 18–24-months after treatment, and from HIV negative controls. Groups were age, ethnicity, weight, biochemical profile, and pre-treatment CD4 count matched. Microarray data was generated using the Agilent Whole Human Genome Microarray. Identification of differentially expressed genes and genomic response pathways was performed using limma and gene set enrichment analysis. Results There were significant divergences between ABC and the other two groups 6 months after treatment in genes controlling cell adhesion and environmental information processing, with some convergence at 18–24 months. Compared to controls the ABC group, but not AZT or TDF showed enrichment of genes controlling adherence junction, at 6 months and 18–24 months (adjusted p<0.05) and focal adhesions and tight junction at 6 months (p<0.5). Genes controlling leukocyte transendothelial migration (p<0.05) and ECM-receptor interactions (p = 0.04) were over-expressed in ABC compared to TDF and AZT at 6 months but not at 18–24 months. Enrichment of pathways and individual genes controlling cell adhesion and environmental information processing were specifically dysregulated in the ABC group in comparison with other treatments. There was little difference between AZT and TDF. Conclusion After initiating treatment, there is divergence in the expression of genes controlling cell adhesion and environmental information processing between ABC and both TDF and AZT in subcutaneous adipose tissue. If similar changes are also taking place in other tissues including the coronary vasculature they may contribute to the increased risk of cardiovascular events reported in patients recently started on abacavir-containing regimens. PMID:25617630

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

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

EPA Science Inventory

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

Modulation of Differentiation Processes in Murine Embryonic Stem Cells Exposed to Parabolic Flight-Induced Acute Hypergravity and Microgravity.

PubMed

Acharya, Aviseka; Brungs, Sonja; Henry, Margit; Rotshteyn, Tamara; Singh Yaduvanshi, Nirmala; Wegener, Lucia; Jentzsch, Simon; Hescheler, Jürgen; Hemmersbach, Ruth; Boeuf, Helene; Sachinidis, Agapios

2018-06-15

Embryonic developmental studies under microgravity conditions in space are very limited. To study the effects of short-term altered gravity on embryonic development processes, we exposed mouse embryonic stem cells (mESCs) to phases of hypergravity and microgravity and studied the differentiation potential of the cells using wide-genome microarray analysis. During the 64th European Space Agency's parabolic flight campaign, mESCs were exposed to 31 parabolas. Each parabola comprised phases lasting 22 s of hypergravity, microgravity, and a repeat of hypergravity. On different parabolas, RNA was isolated for microarray analysis. After exposure to 31 parabolas, mESCs (P31 mESCs) were further differentiated under normal gravity (1 g) conditions for 12 days, producing P31 12-day embryoid bodies (EBs). After analysis of the microarrays, the differentially expressed genes were analyzed using different bioinformatic tools to identify developmental and nondevelopmental biological processes affected by conditions on the parabolic flight experiment. Our results demonstrated that several genes belonging to GOs associated with cell cycle and proliferation were downregulated in undifferentiated mESCs exposed to gravity changes. However, several genes belonging to developmental processes, such as vasculature development, kidney development, skin development, and to the TGF-β signaling pathway, were upregulated. Interestingly, similar enriched and suppressed GOs were obtained in P31 12-day EBs compared with ground control 12-day EBs. Our results show that undifferentiated mESCs exposed to alternate hypergravity and microgravity phases expressed several genes associated with developmental/differentiation and cell cycle processes, suggesting a transition from the undifferentiated pluripotent to a more differentiated stage of mESCs.

Microarray gene-expression study in fibroblast and lymphoblastoid cell lines from antipsychotic-naïve first-episode schizophrenia patients.

PubMed

Gassó, Patricia; Mas, Sergi; Rodríguez, Natalia; Boloc, Daniel; García-Cerro, Susana; Bernardo, Miquel; Lafuente, Amalia; Parellada, Eduard

2017-12-01

Schizophrenia (SZ) is a chronic psychiatric disorder whose onset of symptoms occurs in late adolescence and early adulthood. The etiology is complex and involves important gene-environment interactions. Microarray gene-expression studies on SZ have identified alterations in several biological processes. The heterogeneity in the results can be attributed to the use of different sample types and other important confounding factors including age, illness chronicity and antipsychotic exposure. The aim of the present microarray study was to analyze, for the first time to our knowledge, differences in gene expression profiles in 18 fibroblast (FCLs) and 14 lymphoblastoid cell lines (LCLs) from antipsychotic-naïve first-episode schizophrenia (FES) patients and healthy controls. We used an analytical approach based on protein-protein interaction network construction and functional annotation analysis to identify the biological processes that are altered in SZ. Significant differences in the expression of 32 genes were found when LCLs were assessed. The network and gene set enrichment approach revealed the involvement of similar biological processes in FCLs and LCLs, including apoptosis and related biological terms such as cell cycle, autophagy, cytoskeleton organization and response to stress and stimulus. Metabolism and other processes, including signal transduction, kinase activity and phosphorylation, were also identified. These results were replicated in two independent cohorts using the same analytical approach. This provides more evidence for altered apoptotic processes in antipsychotic-naïve FES patients and other important biological functions such as cytoskeleton organization and metabolism. The convergent results obtained in both peripheral cell models support their usefulness for transcriptome studies on SZ. Copyright © 2017 Elsevier Ltd. All rights reserved.

Bioinformatics analysis of differentially expressed gene profiles associated with systemic lupus erythematosus

PubMed Central

Wu, Chengjiang; Zhao, Yangjing; Lin, Yu; Yang, Xinxin; Yan, Meina; Min, Yujiao; Pan, Zihui; Xia, Sheng; Shao, Qixiang

2018-01-01

DNA microarray and high-throughput sequencing have been widely used to identify the differentially expressed genes (DEGs) in systemic lupus erythematosus (SLE). However, the big data from gene microarrays are also challenging to work with in terms of analysis and processing. The presents study combined data from the microarray expression profile (GSE65391) and bioinformatics analysis to identify the key genes and cellular pathways in SLE. Gene ontology (GO) and cellular pathway enrichment analyses of DEGs were performed to investigate significantly enriched pathways. A protein-protein interaction network was constructed to determine the key genes in the occurrence and development of SLE. A total of 310 DEGs were identified in SLE, including 193 upregulated genes and 117 downregulated genes. GO analysis revealed that the most significant biological process of DEGs was immune system process. Kyoto Encyclopedia of Genes and Genome pathway analysis showed that these DEGs were enriched in signaling pathways associated with the immune system, including the RIG-I-like receptor signaling pathway, intestinal immune network for IgA production, antigen processing and presentation and the toll-like receptor signaling pathway. The current study screened the top 10 genes with higher degrees as hub genes, which included 2′-5′-oligoadenylate synthetase 1, MX dynamin like GTPase 2, interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 7, interferon induced with helicase C domain 1, signal transducer and activator of transcription 1, ISG15 ubiquitin-like modifier, DExD/H-box helicase 58, interferon induced protein with tetratricopeptide repeats 3 and 2′-5′-oligoadenylate synthetase 2. Module analysis revealed that these hub genes were also involved in the RIG-I-like receptor signaling, cytosolic DNA-sensing, toll-like receptor signaling and ribosome biogenesis pathways. In addition, these hub genes, from different probe sets, exhibited significant co-expressed tendency in multi-experiment microarray datasets (P<0.01). In conclusion, these key genes and cellular pathways may improve the current understanding of the underlying mechanism of development of SLE. These key genes may be potential biomarkers of diagnosis, therapy and prognosis for SLE. PMID:29257335

Microarray analysis identifies candidate genes for key roles in coral development

PubMed Central

Grasso, Lauretta C; Maindonald, John; Rudd, Stephen; Hayward, David C; Saint, Robert; Miller, David J; Ball, Eldon E

2008-01-01

Background Anthozoan cnidarians are amongst the simplest animals at the tissue level of organization, but are surprisingly complex and vertebrate-like in terms of gene repertoire. As major components of tropical reef ecosystems, the stony corals are anthozoans of particular ecological significance. To better understand the molecular bases of both cnidarian development in general and coral-specific processes such as skeletogenesis and symbiont acquisition, microarray analysis was carried out through the period of early development – when skeletogenesis is initiated, and symbionts are first acquired. Results Of 5081 unique peptide coding genes, 1084 were differentially expressed (P ≤ 0.05) in comparisons between four different stages of coral development, spanning key developmental transitions. Genes of likely relevance to the processes of settlement, metamorphosis, calcification and interaction with symbionts were characterised further and their spatial expression patterns investigated using whole-mount in situ hybridization. Conclusion This study is the first large-scale investigation of developmental gene expression for any cnidarian, and has provided candidate genes for key roles in many aspects of coral biology, including calcification, metamorphosis and symbiont uptake. One surprising finding is that some of these genes have clear counterparts in higher animals but are not present in the closely-related sea anemone Nematostella. Secondly, coral-specific processes (i.e. traits which distinguish corals from their close relatives) may be analogous to similar processes in distantly related organisms. This first large-scale application of microarray analysis demonstrates the potential of this approach for investigating many aspects of coral biology, including the effects of stress and disease. PMID:19014561

Gene expression profile of blood cells for the prediction of delayed cerebral ischemia after intracranial aneurysm rupture: a pilot study in humans.

PubMed

Baumann, Antoine; Devaux, Yvan; Audibert, Gérard; Zhang, Lu; Bracard, Serge; Colnat-Coulbois, Sophie; Klein, Olivier; Zannad, Faiez; Charpentier, Claire; Longrois, Dan; Mertes, Paul-Michel

2013-01-01

Delayed cerebral ischemia (DCI) is a potentially devastating complication after intracranial aneurysm rupture and its mechanisms remain poorly elucidated. Early identification of the patients prone to developing DCI after rupture may represent a major breakthrough in its prevention and treatment. The single gene approach of DCI has demonstrated interest in humans. We hypothesized that whole genome expression profile of blood cells may be useful for better comprehension and prediction of aneurysmal DCI. Over a 35-month period, 218 patients with aneurysm rupture were included in this study. DCI was defined as the occurrence of a new delayed neurological deficit occurring within 2 weeks after aneurysm rupture with evidence of ischemia either on perfusion-diffusion MRI, CT angiography or CT perfusion imaging, or with cerebral angiography. DCI patients were matched against controls based on 4 out of 5 criteria (age, sex, Fisher grade, aneurysm location and smoking status). Genome-wide expression analysis of blood cells obtained at admission was performed by microarrays. Transcriptomic analysis was performed using long oligonucleotide microarrays representing 25,000 genes. Quantitative PCR: 1 µg of total RNA extracted was reverse-transcribed, and the resulting cDNA was diluted 10-fold before performing quantitative PCR. Microarray data were first analyzed by 'Significance Analysis of Microarrays' software which includes the Benjamini correction for multiple testing. In a second step, microarray data fold change was compared using a two-tailed, paired t test. Analysis of receiver-operating characteristic (ROC) curves and the area under the ROC curves were used for prediction analysis. Logistic regression models were used to investigate the additive value of multiple biomarkers. A total of 16 patients demonstrated DCI. Significance Analysis of Microarrays software failed to retrieve significant genes, most probably because of the heterogeneity of the patients included in the microarray experiments and the small size of the DCI population sample. Standard two-tailed paired t test and C-statistic revealed significant associations between gene expression and the occurrence of DCI: in particular, the expression of neuroregulin 1 was 1.6-fold upregulated in patients with DCI (p = 0.01) and predicted DCI with an area under the ROC curve of 0.96. Logistic regression analyses revealed a significant association between neuroregulin 1 and DCI (odds ratio 1.46, 95% confidence interval 1.02-2.09, p = 0.02). This pilot study suggests that blood cells may be a reservoir of prognostic biomarkers of DCI in patients with intracranial aneurysm rupture. Despite an evident lack of power, this study elicited neuroregulin 1, a vasoreactivity-, inflammation- and angiogenesis-related gene, as a possible candidate predictor of DCI. Larger cohort studies are needed but genome-wide microarray-based studies are promising research tools for the understanding of DCI after intracranial aneurysm rupture. © 2013 S. Karger AG, Basel.

Quantitative characterization of conformational-specific protein-DNA binding using a dual-spectral interferometric imaging biosensor.

PubMed

Zhang, Xirui; Daaboul, George G; Spuhler, Philipp S; Dröge, Peter; Ünlü, M Selim

2016-03-14

DNA-binding proteins play crucial roles in the maintenance and functions of the genome and yet, their specific binding mechanisms are not fully understood. Recently, it was discovered that DNA-binding proteins recognize specific binding sites to carry out their functions through an indirect readout mechanism by recognizing and capturing DNA conformational flexibility and deformation. High-throughput DNA microarray-based methods that provide large-scale protein-DNA binding information have shown effective and comprehensive analysis of protein-DNA binding affinities, but do not provide information of DNA conformational changes in specific protein-DNA complexes. Building on the high-throughput capability of DNA microarrays, we demonstrate a quantitative approach that simultaneously measures the amount of protein binding to DNA and nanometer-scale DNA conformational change induced by protein binding in a microarray format. Both measurements rely on spectral interferometry on a layered substrate using a single optical instrument in two distinct modalities. In the first modality, we quantitate the amount of binding of protein to surface-immobilized DNA in each DNA spot using a label-free spectral reflectivity technique that accurately measures the surface densities of protein and DNA accumulated on the substrate. In the second modality, for each DNA spot, we simultaneously measure DNA conformational change using a fluorescence vertical sectioning technique that determines average axial height of fluorophores tagged to specific nucleotides of the surface-immobilized DNA. The approach presented in this paper, when combined with current high-throughput DNA microarray-based technologies, has the potential to serve as a rapid and simple method for quantitative and large-scale characterization of conformational specific protein-DNA interactions.

THE ABRF-MARG MICROARRAY SURVEY 2004: TAKING THE PULSE OF THE MICROARRAY FIELD

EPA Science Inventory

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

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

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

On the relevance of glycolysis process on brain gliomas.

PubMed

Kounelakis, M G; Zervakis, M E; Giakos, G C; Postma, G J; Buydens, L M C; Kotsiakis, X

2013-01-01

The proposed analysis considers aspects of both statistical and biological validation of the glycolysis effect on brain gliomas, at both genomic and metabolic level. In particular, two independent datasets are analyzed in parallel, one engaging genomic (Microarray Expression) data and the other metabolomic (Magnetic Resonance Spectroscopy Imaging) data. The aim of this study is twofold. First to show that, apart from the already studied genes (markers), other genes such as those involved in the human cell glycolysis significantly contribute in gliomas discrimination. Second, to demonstrate how the glycolysis process can open new ways towards the design of patient-specific therapeutic protocols. The results of our analysis demonstrate that the combination of genes participating in the glycolytic process (ALDOA, ALDOC, ENO2, GAPDH, HK2, LDHA, LDHB, MDH1, PDHB, PFKM, PGI, PGK1, PGM1 and PKLR) with the already known tumor suppressors (PTEN, Rb, TP53), oncogenes (CDK4, EGFR, PDGF) and HIF-1, enhance the discrimination of low versus high-grade gliomas providing high prediction ability in a cross-validated framework. Following these results and supported by the biological effect of glycolytic genes on cancer cells, we address the study of glycolysis for the development of new treatment protocols.

Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

PubMed

Mirzal, Andri; Chaudhry, Shafique Ahmad

2016-01-01

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

Standards to support information systems integration in anatomic pathology.

PubMed

Daniel, Christel; García Rojo, Marcial; Bourquard, Karima; Henin, Dominique; Schrader, Thomas; Della Mea, Vincenzo; Gilbertson, John; Beckwith, Bruce A

2009-11-01

Integrating anatomic pathology information- text and images-into electronic health care records is a key challenge for enhancing clinical information exchange between anatomic pathologists and clinicians. The aim of the Integrating the Healthcare Enterprise (IHE) international initiative is precisely to ensure interoperability of clinical information systems by using existing widespread industry standards such as Digital Imaging and Communication in Medicine (DICOM) and Health Level Seven (HL7). To define standard-based informatics transactions to integrate anatomic pathology information to the Healthcare Enterprise. We used the methodology of the IHE initiative. Working groups from IHE, HL7, and DICOM, with special interest in anatomic pathology, defined consensual technical solutions to provide end-users with improved access to consistent information across multiple information systems. The IHE anatomic pathology technical framework describes a first integration profile, "Anatomic Pathology Workflow," dedicated to the diagnostic process including basic image acquisition and reporting solutions. This integration profile relies on 10 transactions based on HL7 or DICOM standards. A common specimen model was defined to consistently identify and describe specimens in both HL7 and DICOM transactions. The IHE anatomic pathology working group has defined standard-based informatics transactions to support the basic diagnostic workflow in anatomic pathology laboratories. In further stages, the technical framework will be completed to manage whole-slide images and semantically rich structured reports in the diagnostic workflow and to integrate systems used for patient care and those used for research activities (such as tissue bank databases or tissue microarrayers).

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

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

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

PubMed Central

Hu, Wenchao; Liu, Yuting; Yan, Jun

2014-01-01

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

In vitro study of the effects of ELF electric fields on gene expression in human epidermal cells.

PubMed

Collard, Jean-Francois; Mertens, Benjamin; Hinsenkamp, Maurice

2011-01-01

An acceleration of differentiation, at the expense of proliferation, is observed after exposure of various biological models to low frequency and low amplitude electric and electromagnetic fields. Following these results showing significant modifications, we try to identify the biological mechanism involved at the cell level through microarray screening. For this study, we use epidermis cultures harvested from human abdominoplasty. Two platinum electrodes are used to apply the electric signal. The gene expressions of 38,500 well-characterized human genes are analyzed using Affymetrix(®) microarray U133 Plus 2.0 chips. The protocol is repeated on three different patients. After three periods of exposure, a total of 24 chips have been processed. After the application of ELF electric fields, the microarray analysis confirms a modification of the gene expression of epidermis cells. Particularly, four up-regulated genes (DKK1, TXNRD1, ATF3, and MME) and one down-regulated gene (MACF1) are involved in the regulation of proliferation and differentiation. Expression of these five genes was also confirmed by real-time rtPCR in all samples used for microarray analysis. These results corroborate an acceleration of cell differentiation at the expense of cell proliferation. © 2010 Wiley-Liss, Inc.

Searching for links in the biotic characteristics and abiotic parameters of nine different biogas plants

PubMed Central

Walter, Andreas; Knapp, Brigitte A.; Farbmacher, Theresa; Ebner, Christian; Insam, Heribert; Franke‐Whittle, Ingrid H.

2012-01-01

Summary To find links between the biotic characteristics and abiotic process parameters in anaerobic digestion systems, the microbial communities of nine full‐scale biogas plants in South Tyrol (Italy) and Vorarlberg (Austria) were investigated using molecular techniques and the physical and chemical properties were monitored. DNA from sludge samples was subjected to microarray hybridization with the ANAEROCHIP microarray and results indicated that sludge samples grouped into two main clusters, dominated either by Methanosarcina or by Methanosaeta, both aceticlastic methanogens. Hydrogenotrophic methanogens were hardly detected or if detected, gave low hybridization signals. Results obtained using denaturing gradient gel electrophoresis (DGGE) supported the findings of microarray hybridization. Real‐time PCR targeting Methanosarcina and Methanosaeta was conducted to provide quantitative data on the dominating methanogens. Correlation analysis to determine any links between the microbial communities found by microarray analysis, and the physicochemical parameters investigated was conducted. It was shown that the sludge samples dominated by the genus Methanosarcina were positively correlated with higher concentrations of acetate, whereas sludge samples dominated by representatives of the genus Methanosaeta had lower acetate concentrations. No other correlations between biotic characteristics and abiotic parameters were found. Methanogenic communities in each reactor were highly stable and resilient over the whole year. PMID:22950603

BμG@Sbase—a microbial gene expression and comparative genomic database

PubMed Central

Witney, Adam A.; Waldron, Denise E.; Brooks, Lucy A.; Tyler, Richard H.; Withers, Michael; Stoker, Neil G.; Wren, Brendan W.; Butcher, Philip D.; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future. PMID:21948792

BμG@Sbase--a microbial gene expression and comparative genomic database.

PubMed

Witney, Adam A; Waldron, Denise E; Brooks, Lucy A; Tyler, Richard H; Withers, Michael; Stoker, Neil G; Wren, Brendan W; Butcher, Philip D; Hinds, Jason

2012-01-01

The reducing cost of high-throughput functional genomic technologies is creating a deluge of high volume, complex data, placing the burden on bioinformatics resources and tool development. The Bacterial Microarray Group at St George's (BμG@S) has been at the forefront of bacterial microarray design and analysis for over a decade and while serving as a hub of a global network of microbial research groups has developed BμG@Sbase, a microbial gene expression and comparative genomic database. BμG@Sbase (http://bugs.sgul.ac.uk/bugsbase/) is a web-browsable, expertly curated, MIAME-compliant database that stores comprehensive experimental annotation and multiple raw and analysed data formats. Consistent annotation is enabled through a structured set of web forms, which guide the user through the process following a set of best practices and controlled vocabulary. The database currently contains 86 expertly curated publicly available data sets (with a further 124 not yet published) and full annotation information for 59 bacterial microarray designs. The data can be browsed and queried using an explorer-like interface; integrating intuitive tree diagrams to present complex experimental details clearly and concisely. Furthermore the modular design of the database will provide a robust platform for integrating other data types beyond microarrays into a more Systems analysis based future.

Classification of Microarray Data Using Kernel Fuzzy Inference System

PubMed Central

Kumar Rath, Santanu

2014-01-01

The DNA microarray classification technique has gained more popularity in both research and practice. In real data analysis, such as microarray data, the dataset contains a huge number of insignificant and irrelevant features that tend to lose useful information. Classes with high relevance and feature sets with high significance are generally referred for the selected features, which determine the samples classification into their respective classes. In this paper, kernel fuzzy inference system (K-FIS) algorithm is applied to classify the microarray data (leukemia) using t-test as a feature selection method. Kernel functions are used to map original data points into a higher-dimensional (possibly infinite-dimensional) feature space defined by a (usually nonlinear) function ϕ through a mathematical process called the kernel trick. This paper also presents a comparative study for classification using K-FIS along with support vector machine (SVM) for different set of features (genes). Performance parameters available in the literature such as precision, recall, specificity, F-measure, ROC curve, and accuracy are considered to analyze the efficiency of the classification model. From the proposed approach, it is apparent that K-FIS model obtains similar results when compared with SVM model. This is an indication that the proposed approach relies on kernel function. PMID:27433543

eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Longiaru, Mathew

2009-05-01

DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

Bimodal imprint chips for peptide screening: integration of high-throughput sequencing by MS and affinity analyses by surface plasmon resonance imaging.

PubMed

Wang, Weizhi; Li, Menglin; Wei, Zewen; Wang, Zihua; Bu, Xiangli; Lai, Wenjia; Yang, Shu; Gong, He; Zheng, Hui; Wang, Yuqiao; Liu, Ying; Li, Qin; Fang, Qiaojun; Hu, Zhiyuan

2014-04-15

Peptide probes and drugs have widespread applications in disease diagnostics and therapy. The demand for peptides ligands with high affinity and high specificity toward various targets has surged in the biomedical field in recent years. The traditional peptide screening procedure involves selection, sequencing, and characterization steps, and each step is manual and tedious. Herein, we developed a bimodal imprint microarray system to embrace the whole peptide screening process. Silver-sputtered silicon chip fabricated with microwell array can trap and pattern the candidate peptide beads in a one-well-one-bead manner. Peptides on beads were photocleaved in situ. A portion of the peptide in each well was transferred to a gold-coated chip to print the peptide array for high-throughput affinity analyses by surface plasmon resonance imaging (SPRi), and the peptide left in the silver-sputtered chip was ready for in situ single bead sequencing by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Using the bimodal imprint chip system, affinity peptides toward AHA were efficiently screened out from the 7 × 10(4) peptide library. The method provides a solution for high efficiency peptide screening.

Identification of Novel Tissue-Specific Genes by Analysis of Microarray Databases: A Human and Mouse Model

PubMed Central

Suh, Yeunsu; Davis, Michael E.; Lee, Kichoon

2013-01-01

Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI′s Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved. PMID:23741331

DNA microarray analyses reveal a post-irradiation differential time-dependent gene expression profile in yeast cells exposed to X-rays and gamma-rays.

PubMed

Kimura, Shinzo; Ishidou, Emi; Kurita, Sakiko; Suzuki, Yoshiteru; Shibato, Junko; Rakwal, Randeep; Iwahashi, Hitoshi

2006-07-21

Ionizing radiation (IR) is the most enigmatic of genotoxic stress inducers in our environment that has been around from the eons of time. IR is generally considered harmful, and has been the subject of numerous studies, mostly looking at the DNA damaging effects in cells and the repair mechanisms therein. Moreover, few studies have focused on large-scale identification of cellular responses to IR, and to this end, we describe here an initial study on the transcriptional responses of the unicellular genome model, yeast (Saccharomyces cerevisiae strain S288C), by cDNA microarray. The effect of two different IR, X-rays, and gamma (gamma)-rays, was investigated by irradiating the yeast cells cultured in YPD medium with 50 Gy doses of X- and gamma-rays, followed by resuspension of the cells in YPD for time-course experiments. The samples were collected for microarray analysis at 20, 40, and 80 min after irradiation. Microarray analysis revealed a time-course transcriptional profile of changed gene expressions. Up-regulated genes belonged to the functional categories mainly related to cell cycle and DNA processing, cell rescue defense and virulence, protein and cell fate, and metabolism (X- and gamma-rays). Similarly, for X- and gamma-rays, the down-regulated genes belonged to mostly transcription and protein synthesis, cell cycle and DNA processing, control of cellular organization, cell fate, and C-compound and carbohydrate metabolism categories, respectively. This study provides for the first time a snapshot of the genome-wide mRNA expression profiles in X- and gamma-ray post-irradiated yeast cells and comparatively interprets/discusses the changed gene functional categories as effects of these two radiations vis-à-vis their energy levels.

cDNA microarrays as a tool for identification of biomineralization proteins in the coccolithophorid Emiliania huxleyi (Haptophyta).

PubMed

Quinn, Patrick; Bowers, Robert M; Zhang, Xiaoyu; Wahlund, Thomas M; Fanelli, Michael A; Olszova, Daniela; Read, Betsy A

2006-08-01

Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis.

cDNA Microarrays as a Tool for Identification of Biomineralization Proteins in the Coccolithophorid Emiliania huxleyi (Haptophyta)

PubMed Central

Quinn, Patrick; Bowers, Robert M.; Zhang, Xiaoyu; Wahlund, Thomas M.; Fanelli, Michael A.; Olszova, Daniela; Read, Betsy A.

2006-01-01

Marine unicellular coccolithophore algae produce species-specific calcite scales otherwise known as coccoliths. While the coccoliths and their elaborate architecture have attracted the attention of investigators from various scientific disciplines, our knowledge of the underpinnings of the process of biomineralization in this alga is still in its infancy. The processes of calcification and coccolithogenesis are highly regulated and likely to be complex, requiring coordinated expression of many genes and pathways. In this study, we have employed cDNA microarrays to investigate changes in gene expression associated with biomineralization in the most abundant coccolithophorid, Emiliania huxleyi. Expression profiling of cultures grown under calcifying and noncalcifying conditions has been carried out using cDNA microarrays corresponding to approximately 2,300 expressed sequence tags. A total of 127 significantly up- or down-regulated transcripts were identified using a P value of 0.01 and a change of >2.0-fold. Real-time reverse transcriptase PCR was used to test the overall validity of the microarray data, as well as the relevance of many of the proteins predicted to be associated with biomineralization, including a novel gamma-class carbonic anhydrase (A. R. Soto, H. Zheng, D. Shoemaker, J. Rodriguez, B. A. Read, and T. M. Wahlund, Appl. Environ. Microbiol. 72:5500-5511, 2006). Differentially regulated genes include those related to cellular metabolism, ion channels, transport proteins, vesicular trafficking, and cell signaling. The putative function of the vast majority of candidate transcripts could not be defined. Nonetheless, the data described herein represent profiles of the transcription changes associated with biomineralization-related pathways in E. huxleyi and have identified novel and potentially useful targets for more detailed analysis. PMID:16885305

Genomic analysis of Fusarium verticillioides.

PubMed

Brown, D W; Butchko, R A E; Proctor, R H

2008-09-01

Fusarium verticillioides (teleomorph Gibberella moniliformis) can be either an endophyte of maize, causing no visible disease, or a pathogen-causing disease of ears, stalks, roots and seedlings. At any stage, this fungus can synthesize fumonisins, a family of mycotoxins structurally similar to the sphingolipid sphinganine. Ingestion of fumonisin-contaminated maize has been associated with a number of animal diseases, including cancer in rodents, and exposure has been correlated with human oesophageal cancer in some regions of the world, and some evidence suggests that fumonisins are a risk factor for neural tube defects. A primary goal of the authors' laboratory is to eliminate fumonisin contamination of maize and maize products. Understanding how and why these toxins are made and the F. verticillioides-maize disease process will allow one to develop novel strategies to limit tissue destruction (rot) and fumonisin production. To meet this goal, genomic sequence data, expressed sequence tags (ESTs) and microarrays are being used to identify F. verticillioides genes involved in the biosynthesis of toxins and plant pathogenesis. This paper describes the current status of F. verticillioides genomic resources and three approaches being used to mine microarray data from a wild-type strain cultured in liquid fumonisin production medium for 12, 24, 48, 72, 96 and 120h. Taken together, these approaches demonstrate the power of microarray technology to provide information on different biological processes.

Leukemia and colon tumor detection based on microarray data classification using momentum backpropagation and genetic algorithm as a feature selection method

NASA Astrophysics Data System (ADS)

Wisesty, Untari N.; Warastri, Riris S.; Puspitasari, Shinta Y.

2018-03-01

Cancer is one of the major causes of mordibility and mortality problems in the worldwide. Therefore, the need of a system that can analyze and identify a person suffering from a cancer by using microarray data derived from the patient’s Deoxyribonucleic Acid (DNA). But on microarray data has thousands of attributes, thus making the challenges in data processing. This is often referred to as the curse of dimensionality. Therefore, in this study built a system capable of detecting a patient whether contracted cancer or not. The algorithm used is Genetic Algorithm as feature selection and Momentum Backpropagation Neural Network as a classification method, with data used from the Kent Ridge Bio-medical Dataset. Based on system testing that has been done, the system can detect Leukemia and Colon Tumor with best accuracy equal to 98.33% for colon tumor data and 100% for leukimia data. Genetic Algorithm as feature selection algorithm can improve system accuracy, which is from 64.52% to 98.33% for colon tumor data and 65.28% to 100% for leukemia data, and the use of momentum parameters can accelerate the convergence of the system in the training process of Neural Network.

Global monitoring of autumn gene expression within and among phenotypically divergent populations of Sitka spruce (Picea sitchensis).

PubMed

Holliday, Jason A; Ralph, Steven G; White, Richard; Bohlmann, Jörg; Aitken, Sally N

2008-01-01

Cold acclimation in conifers is a complex process, the timing and extent of which reflects local adaptation and varies widely along latitudinal gradients for many temperate and boreal tree species. Despite their ecological and economic importance, little is known about the global changes in gene expression that accompany autumn cold acclimation in conifers. Using three populations of Sitka spruce (Picea sitchensis) spanning the species range, and a Picea cDNA microarray with 21,840 unique elements, within- and among-population gene expression was monitored during the autumn. Microarray data were validated for selected genes using real-time PCR. Similar numbers of genes were significantly twofold upregulated (1257) and downregulated (967) between late summer and early winter. Among those upregulated were dehydrins, pathogenesis-related/antifreeze genes, carbohydrate and lipid metabolism genes, and genes involved in signal transduction and transcriptional regulation. Among-population microarray hybridizations at early and late autumn time points revealed substantial variation in the autumn transcriptome, some of which may reflect local adaptation. These results demonstrate the complexity of cold acclimation in conifers, highlight similarities and differences to cold tolerance in annual plants, and provide a solid foundation for functional and genetic studies of this important adaptive process.

Framework for Parallel Preprocessing of Microarray Data Using Hadoop

PubMed Central

2018-01-01

Nowadays, microarray technology has become one of the popular ways to study gene expression and diagnosis of disease. National Center for Biology Information (NCBI) hosts public databases containing large volumes of biological data required to be preprocessed, since they carry high levels of noise and bias. Robust Multiarray Average (RMA) is one of the standard and popular methods that is utilized to preprocess the data and remove the noises. Most of the preprocessing algorithms are time-consuming and not able to handle a large number of datasets with thousands of experiments. Parallel processing can be used to address the above-mentioned issues. Hadoop is a well-known and ideal distributed file system framework that provides a parallel environment to run the experiment. In this research, for the first time, the capability of Hadoop and statistical power of R have been leveraged to parallelize the available preprocessing algorithm called RMA to efficiently process microarray data. The experiment has been run on cluster containing 5 nodes, while each node has 16 cores and 16 GB memory. It compares efficiency and the performance of parallelized RMA using Hadoop with parallelized RMA using affyPara package as well as sequential RMA. The result shows the speed-up rate of the proposed approach outperforms the sequential approach and affyPara approach. PMID:29796018

Expression profiling of cardiovascular disease

PubMed Central

2004-01-01

Cardiovascular disease is the most important cause of morbidity and mortality in developed countries, causing twice as many deaths as cancer in the USA. The major cardiovascular diseases, including coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF) and common congenital heart disease (CHD), are caused by multiple genetic and environmental factors, as well as the interactions between them. The underlying molecular pathogenic mechanisms for these disorders are still largely unknown, but gene expression may play a central role in the development and progression of cardiovascular disease. Microarrays are high-throughput genomic tools that allow the comparison of global expression changes in thousands of genes between normal and diseased cells/tissues. Microarrays have recently been applied to CAD/MI, CHF and CHD to profile changes in gene expression patterns in diseased and non-diseased patients. This same technology has also been used to characterise endothelial cells, vascular smooth muscle cells and inflammatory cells, with or without various treatments that mimic disease processes involved in CAD/MI. These studies have led to the identification of unique subsets of genes associated with specific diseases and disease processes. Ongoing microarray studies in the field will provide insights into the molecular mechanism of cardiovascular disease and may generate new diagnostic and therapeutic markers. PMID:15588496

Dynamic, electronically switchable surfaces for membrane protein microarrays.

PubMed

Tang, C S; Dusseiller, M; Makohliso, S; Heuschkel, M; Sharma, S; Keller, B; Vörös, J

2006-02-01

Microarray technology is a powerful tool that provides a high throughput of bioanalytical information within a single experiment. These miniaturized and parallelized binding assays are highly sensitive and have found widespread popularity especially during the genomic era. However, as drug diagnostics studies are often targeted at membrane proteins, the current arraying technologies are ill-equipped to handle the fragile nature of the protein molecules. In addition, to understand the complex structure and functions of proteins, different strategies to immobilize the probe molecules selectively onto a platform for protein microarray are required. We propose a novel approach to create a (membrane) protein microarray by using an indium tin oxide (ITO) microelectrode array with an electronic multiplexing capability. A polycationic, protein- and vesicle-resistant copolymer, poly(l-lysine)-grafted-poly(ethylene glycol) (PLL-g-PEG), is exposed to and adsorbed uniformly onto the microelectrode array, as a passivating adlayer. An electronic stimulation is then applied onto the individual ITO microelectrodes resulting in the localized release of the polymer thus revealing a bare ITO surface. Different polymer and biological moieties are specifically immobilized onto the activated ITO microelectrodes while the other regions remain protein-resistant as they are unaffected by the induced electrical potential. The desorption process of the PLL-g-PEG is observed to be highly selective, rapid, and reversible without compromising on the integrity and performance of the conductive ITO microelectrodes. As such, we have successfully created a stable and heterogeneous microarray of biomolecules by using selective electronic addressing on ITO microelectrodes. Both pharmaceutical diagnostics and biomedical technology are expected to benefit directly from this unique method.

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna

2008-10-06

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.

Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline

PubMed Central

Rahmatallah, Yasir; Emmert-Streib, Frank

2016-01-01

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128

Transcriptome sequencing and microarray development for the woodrat (Neotoma spp.): custom genetic tools for exploring herbivore ecology.

PubMed

Malenke, J R; Milash, B; Miller, A W; Dearing, M D

2013-07-01

Massively parallel sequencing has enabled the creation of novel, in-depth genetic tools for nonmodel, ecologically important organisms. We present the de novo transcriptome sequencing, analysis and microarray development for a vertebrate herbivore, the woodrat (Neotoma spp.). This genus is of ecological and evolutionary interest, especially with respect to ingestion and hepatic metabolism of potentially toxic plant secondary compounds. We generated a liver transcriptome of the desert woodrat (Neotoma lepida) using the Roche 454 platform. The assembled contigs were well annotated using rodent references (99.7% annotation), and biotransformation function was reflected in the gene ontology. The transcriptome was used to develop a custom microarray (eArray, Agilent). We tested the microarray with three experiments: one across species with similar habitat (thus, dietary) niches, one across species with different habitat niches and one across populations within a species. The resulting one-colour arrays had high technical and biological quality. Probes designed from the woodrat transcriptome performed significantly better than functionally similar probes from the Norway rat (Rattus norvegicus). There were a multitude of expression differences across the woodrat treatments, many of which related to biotransformation processes and activities. The pattern and function of the differences indicate shared ecological pressures, and not merely phylogenetic distance, play an important role in shaping gene expression profiles of woodrat species and populations. The quality and functionality of the woodrat transcriptome and custom microarray suggest these tools will be valuable for expanding the scope of herbivore biology, as well as the exploration of conceptual topics in ecology. © 2013 John Wiley & Sons Ltd.

Unravelling Glucan Recognition Systems by Glycome Microarrays Using the Designer Approach and Mass Spectrometry*

PubMed Central

Palma, Angelina S.; Liu, Yan; Zhang, Hongtao; Zhang, Yibing; McCleary, Barry V.; Yu, Guangli; Huang, Qilin; Guidolin, Leticia S.; Ciocchini, Andres E.; Torosantucci, Antonella; Wang, Denong; Carvalho, Ana Luísa; Fontes, Carlos M. G. A.; Mulloy, Barbara; Childs, Robert A.; Feizi, Ten; Chai, Wengang

2015-01-01

Glucans are polymers of d-glucose with differing linkages in linear or branched sequences. They are constituents of microbial and plant cell-walls and involved in important bio-recognition processes, including immunomodulation, anticancer activities, pathogen virulence, and plant cell-wall biodegradation. Translational possibilities for these activities in medicine and biotechnology are considerable. High-throughput micro-methods are needed to screen proteins for recognition of specific glucan sequences as a lead to structure–function studies and their exploitation. We describe construction of a “glucome” microarray, the first sequence-defined glycome-scale microarray, using a “designer” approach from targeted ligand-bearing glucans in conjunction with a novel high-sensitivity mass spectrometric sequencing method, as a screening tool to assign glucan recognition motifs. The glucome microarray comprises 153 oligosaccharide probes with high purity, representing major sequences in glucans. Negative-ion electrospray tandem mass spectrometry with collision-induced dissociation was used for complete linkage analysis of gluco-oligosaccharides in linear “homo” and “hetero” and branched sequences. The system is validated using antibodies and carbohydrate-binding modules known to target α- or β-glucans in different biological contexts, extending knowledge on their specificities, and applied to reveal new information on glucan recognition by two signaling molecules of the immune system against pathogens: Dectin-1 and DC-SIGN. The sequencing of the glucan oligosaccharides by the MS method and their interrogation on the microarrays provides detailed information on linkage, sequence and chain length requirements of glucan-recognizing proteins, and are a sensitive means of revealing unsuspected sequences in the polysaccharides. PMID:25670804

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks

PubMed Central

2014-01-01

Background Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. Conclusions This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally. PMID:24739361

Linking microarray reporters with protein functions.

PubMed

Gaj, Stan; van Erk, Arie; van Haaften, Rachel I M; Evelo, Chris T A

2007-09-26

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

Visualization for genomics: the Microbial Genome Viewer.

PubMed

Kerkhoven, Robert; van Enckevort, Frank H J; Boekhorst, Jos; Molenaar, Douwe; Siezen, Roland J

2004-07-22

A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection. The Microbial Genome Viewer 1.0 is freely available at http://www.cmbi.kun.nl/MGV

mRNA-Seq and microarray development for the Grooved carpet shell clam, Ruditapes decussatus: a functional approach to unravel host -parasite interaction

PubMed Central

2013-01-01

Background The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. Results A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. Conclusions This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported. PMID:24168212

Identifying Fishes through DNA Barcodes and Microarrays.

PubMed

Kochzius, Marc; Seidel, Christian; Antoniou, Aglaia; Botla, Sandeep Kumar; Campo, Daniel; Cariani, Alessia; Vazquez, Eva Garcia; Hauschild, Janet; Hervet, Caroline; Hjörleifsdottir, Sigridur; Hreggvidsson, Gudmundur; Kappel, Kristina; Landi, Monica; Magoulas, Antonios; Marteinsson, Viggo; Nölte, Manfred; Planes, Serge; Tinti, Fausto; Turan, Cemal; Venugopal, Moleyur N; Weber, Hannes; Blohm, Dietmar

2010-09-07

International fish trade reached an import value of 62.8 billion Euro in 2006, of which 44.6% are covered by the European Union. Species identification is a key problem throughout the life cycle of fishes: from eggs and larvae to adults in fisheries research and control, as well as processed fish products in consumer protection. This study aims to evaluate the applicability of the three mitochondrial genes 16S rRNA (16S), cytochrome b (cyt b), and cytochrome oxidase subunit I (COI) for the identification of 50 European marine fish species by combining techniques of "DNA barcoding" and microarrays. In a DNA barcoding approach, neighbour Joining (NJ) phylogenetic trees of 369 16S, 212 cyt b, and 447 COI sequences indicated that cyt b and COI are suitable for unambiguous identification, whereas 16S failed to discriminate closely related flatfish and gurnard species. In course of probe design for DNA microarray development, each of the markers yielded a high number of potentially species-specific probes in silico, although many of them were rejected based on microarray hybridisation experiments. None of the markers provided probes to discriminate the sibling flatfish and gurnard species. However, since 16S-probes were less negatively influenced by the "position of label" effect and showed the lowest rejection rate and the highest mean signal intensity, 16S is more suitable for DNA microarray probe design than cty b and COI. The large portion of rejected COI-probes after hybridisation experiments (>90%) renders the DNA barcoding marker as rather unsuitable for this high-throughput technology. Based on these data, a DNA microarray containing 64 functional oligonucleotide probes for the identification of 30 out of the 50 fish species investigated was developed. It represents the next step towards an automated and easy-to-handle method to identify fish, ichthyoplankton, and fish products.

mRNA-Seq and microarray development for the Grooved Carpet shell clam, Ruditapes decussatus: a functional approach to unravel host-parasite interaction.

PubMed

Leite, Ricardo B; Milan, Massimo; Coppe, Alessandro; Bortoluzzi, Stefania; dos Anjos, António; Reinhardt, Richard; Saavedra, Carlos; Patarnello, Tomaso; Cancela, M Leonor; Bargelloni, Luca

2013-10-29

The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported.

Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method.

PubMed

Bengtsson, Henrik; Hössjer, Ola

2006-03-01

Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general. A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit ("lowess") normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are revisited in the light of the affine model and their strengths and weaknesses are investigated in this context. As a direct result from this study, we propose a robust non-parametric multi-dimensional affine normalization method, which can be applied to any number of microarrays with any number of channels either individually or all at once. A high-quality cDNA microarray data set with spike-in controls is used to demonstrate the power of the affine model and the proposed normalization method. We find that an affine model can explain non-linear intensity-dependent systematic effects in observed log-ratios. Affine normalization removes such artifacts for non-differentially expressed genes and assures that symmetry between negative and positive log-ratios is obtained, which is fundamental when identifying differentially expressed genes. In addition, affine normalization makes the empirical distributions in different channels more equal, which is the purpose of quantile normalization, and may also explain why dye-swap normalization works or fails. All methods are made available in the aroma package, which is a platform-independent package for R.

High-throughput identification of proteins with AMPylation using self-assembled human protein (NAPPA) microarrays.

PubMed

Yu, Xiaobo; LaBaer, Joshua

2015-05-01

AMPylation (adenylylation) has been recognized as an important post-translational modification that is used by pathogens to regulate host cellular proteins and their associated signaling pathways. AMPylation has potential functions in various cellular processes, and it is widely conserved across both prokaryotes and eukaryotes. However, despite the identification of many AMPylators, relatively few candidate substrates of AMPylation are known. This is changing with the recent development of a robust and reliable method for identifying new substrates using protein microarrays, which can markedly expand the list of potential substrates. Here we describe procedures for detecting AMPylated and auto-AMPylated proteins in a sensitive, high-throughput and nonradioactive manner. The approach uses high-density protein microarrays fabricated using nucleic acid programmable protein array (NAPPA) technology, which enables the highly successful display of fresh recombinant human proteins in situ. The modification of target proteins is determined via copper-catalyzed azide-alkyne cycloaddition (CuAAC). The assay can be accomplished within 11 h.

Genetic programming based ensemble system for microarray data classification.

PubMed

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved.

Genetic Programming Based Ensemble System for Microarray Data Classification

PubMed Central

Liu, Kun-Hong; Tong, Muchenxuan; Xie, Shu-Tong; Yee Ng, Vincent To

2015-01-01

Recently, more and more machine learning techniques have been applied to microarray data analysis. The aim of this study is to propose a genetic programming (GP) based new ensemble system (named GPES), which can be used to effectively classify different types of cancers. Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble system, and they become more and more accurate in the evolutionary process. The feature selection technique and balanced subsampling technique are applied to increase the diversity in each ensemble system. The final ensemble committee is selected by a forward search algorithm, which is shown to be capable of fitting data automatically. The performance of GPES is evaluated using five binary class and six multiclass microarray datasets, and results show that the algorithm can achieve better results in most cases compared with some other ensemble systems. By using elaborate base classifiers or applying other sampling techniques, the performance of GPES may be further improved. PMID:25810748

Derivation of an artificial gene to improve classification accuracy upon gene selection.

PubMed

Seo, Minseok; Oh, Sejong

2012-02-01

Classification analysis has been developed continuously since 1936. This research field has advanced as a result of development of classifiers such as KNN, ANN, and SVM, as well as through data preprocessing areas. Feature (gene) selection is required for very high dimensional data such as microarray before classification work. The goal of feature selection is to choose a subset of informative features that reduces processing time and provides higher classification accuracy. In this study, we devised a method of artificial gene making (AGM) for microarray data to improve classification accuracy. Our artificial gene was derived from a whole microarray dataset, and combined with a result of gene selection for classification analysis. We experimentally confirmed a clear improvement of classification accuracy after inserting artificial gene. Our artificial gene worked well for popular feature (gene) selection algorithms and classifiers. The proposed approach can be applied to any type of high dimensional dataset. Copyright © 2011 Elsevier Ltd. All rights reserved.

Suppression subtractive hybridization as a tool to identify anthocyanin metabolism-related genes in apple skin.

PubMed

Ban, Yusuke; Moriguchi, Takaya

2010-01-01

The pigmentation of anthocyanins is one of the important determinants for consumer preference and marketability in horticultural crops such as fruits and flowers. To elucidate the mechanisms underlying the physiological process leading to the pigmentation of anthocyanins, identification of the genes differentially expressed in response to anthocyanin accumulation is a useful strategy. Currently, microarrays have been widely used to isolate differentially expressed genes. However, the use of microarrays is limited by its high cost of special apparatus and materials. Therefore, availability of microarrays is limited and does not come into common use at present. Suppression subtractive hybridization (SSH) is an alternative tool that has been widely used to identify differentially expressed genes due to its easy handling and relatively low cost. This chapter describes the procedures for SSH, including RNA extraction from polysaccharides and polyphenol-rich samples, poly(A)+ RNA purification, evaluation of subtraction efficiency, and differential screening using reverse northern in apple skin.

Gene Expression Omnibus (GEO): Microarray data storage, submission, retrieval, and analysis

PubMed Central

Barrett, Tanya

2006-01-01

The Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) archives and freely distributes high-throughput molecular abundance data, predominantly gene expression data generated by DNA microarray technology. The database has a flexible design that can handle diverse styles of both unprocessed and processed data in a MIAME- (Minimum Information About a Microarray Experiment) supportive infrastructure that promotes fully annotated submissions. GEO currently stores about a billion individual gene expression measurements, derived from over 100 organisms, submitted by over 1,500 laboratories, addressing a wide range of biological phenomena. To maximize the utility of these data, several user-friendly Web-based interfaces and applications have been implemented that enable effective exploration, query, and visualization of these data, at the level of individual genes or entire studies. This chapter describes how the data are stored, submission procedures, and mechanisms for data retrieval and query. GEO is publicly accessible at http://www.ncbi.nlm.nih.gov/projects/geo/. PMID:16939800

Analysis of Temporal-spatial Co-variation within Gene Expression Microarray Data in an Organogenesis Model

NASA Astrophysics Data System (ADS)

Ehler, Martin; Rajapakse, Vinodh; Zeeberg, Barry; Brooks, Brian; Brown, Jacob; Czaja, Wojciech; Bonner, Robert F.

The gene networks underlying closure of the optic fissure during vertebrate eye development are poorly understood. We used a novel clustering method based on Laplacian Eigenmaps, a nonlinear dimension reduction method, to analyze microarray data from laser capture microdissected (LCM) cells at the site and developmental stages (days 10.5 to 12.5) of optic fissure closure. Our new method provided greater biological specificity than classical clustering algorithms in terms of identifying more biological processes and functions related to eye development as defined by Gene Ontology at lower false discovery rates. This new methodology builds on the advantages of LCM to isolate pure phenotypic populations within complex tissues and allows improved ability to identify critical gene products expressed at lower copy number. The combination of LCM of embryonic organs, gene expression microarrays, and extracting spatial and temporal co-variations appear to be a powerful approach to understanding the gene regulatory networks that specify mammalian organogenesis.

Oligonucleotide microarray chip for the quantification of MS2, ΦX174, and adenoviruses on the multiplex analysis platform MCR 3.

PubMed

Lengger, Sandra; Otto, Johannes; Elsässer, Dennis; Schneider, Oliver; Tiehm, Andreas; Fleischer, Jens; Niessner, Reinhard; Seidel, Michael

2014-05-01

Pathogenic viruses are emerging contaminants in water which should be analyzed for water safety to preserve public health. A strategy was developed to quantify RNA and DNA viruses in parallel on chemiluminescence flow-through oligonucleotide microarrays. In order to show the proof of principle, bacteriophage MS2, ΦX174, and the human pathogenic adenovirus type 2 (hAdV2) were analyzed in spiked tap water samples on the analysis platform MCR 3. The chemiluminescence microarray imaging unit was equipped with a Peltier heater for a controlled heating of the flow cell. The efficiency and selectivity of DNA hybridization could be increased resulting in higher signal intensities and lower cross-reactivities of polymerase chain reaction (PCR) products from other viruses. The total analysis time for DNA/RNA extraction, cDNA synthesis for RNA viruses, polymerase chain reaction, single-strand separation, and oligonucleotide microarray analysis was performed in 4-4.5 h. The parallel quantification was possible in a concentration range of 9.6 × 10(5)-1.4 × 10(10) genomic units (GU)/mL for bacteriophage MS2, 1.4 × 10(5)-3.7 × 10(8) GU/mL for bacteriophage ΦX174, and 6.5 × 10(3)-1.2 × 10(5) for hAdV2, respectively, by using a measuring temperature of 40 °C. Detection limits could be calculated to 6.6 × 10(5) GU/mL for MS2, 5.3 × 10(3) GU/mL for ΦX174, and 1.5 × 10(2) GU/mL for hAdV2, respectively. Real samples of surface water and treated wastewater were tested. Generally, found concentrations of hAdV2, bacteriophage MS2, and ΦX174 were at the detection limit. Nevertheless, bacteriophages could be identified with similar results by means of quantitative PCR and oligonucleotide microarray analysis on the MCR 3.

Physico-chemical foundations underpinning microarray and next-generation sequencing experiments

PubMed Central

Harrison, Andrew; Binder, Hans; Buhot, Arnaud; Burden, Conrad J.; Carlon, Enrico; Gibas, Cynthia; Gamble, Lara J.; Halperin, Avraham; Hooyberghs, Jef; Kreil, David P.; Levicky, Rastislav; Noble, Peter A.; Ott, Albrecht; Pettitt, B. Montgomery; Tautz, Diethard; Pozhitkov, Alexander E.

2013-01-01

Hybridization of nucleic acids on solid surfaces is a key process involved in high-throughput technologies such as microarrays and, in some cases, next-generation sequencing (NGS). A physical understanding of the hybridization process helps to determine the accuracy of these technologies. The goal of a widespread research program is to develop reliable transformations between the raw signals reported by the technologies and individual molecular concentrations from an ensemble of nucleic acids. This research has inputs from many areas, from bioinformatics and biostatistics, to theoretical and experimental biochemistry and biophysics, to computer simulations. A group of leading researchers met in Ploen Germany in 2011 to discuss present knowledge and limitations of our physico-chemical understanding of high-throughput nucleic acid technologies. This meeting inspired us to write this summary, which provides an overview of the state-of-the-art approaches based on physico-chemical foundation to modeling of the nucleic acids hybridization process on solid surfaces. In addition, practical application of current knowledge is emphasized. PMID:23307556

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Intra-Platform Repeatability and Inter-Platform Comparability of MicroRNA Microarray Technology

PubMed Central

Sato, Fumiaki; Tsuchiya, Soken; Terasawa, Kazuya; Tsujimoto, Gozoh

2009-01-01

Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems. PMID:19436744

Living Cell Microarrays: An Overview of Concepts

PubMed Central

Jonczyk, Rebecca; Kurth, Tracy; Lavrentieva, Antonina; Walter, Johanna-Gabriela; Scheper, Thomas; Stahl, Frank

2016-01-01

Living cell microarrays are a highly efficient cellular screening system. Due to the low number of cells required per spot, cell microarrays enable the use of primary and stem cells and provide resolution close to the single-cell level. Apart from a variety of conventional static designs, microfluidic microarray systems have also been established. An alternative format is a microarray consisting of three-dimensional cell constructs ranging from cell spheroids to cells encapsulated in hydrogel. These systems provide an in vivo-like microenvironment and are preferably used for the investigation of cellular physiology, cytotoxicity, and drug screening. Thus, many different high-tech microarray platforms are currently available. Disadvantages of many systems include their high cost, the requirement of specialized equipment for their manufacture, and the poor comparability of results between different platforms. In this article, we provide an overview of static, microfluidic, and 3D cell microarrays. In addition, we describe a simple method for the printing of living cell microarrays on modified microscope glass slides using standard DNA microarray equipment available in most laboratories. Applications in research and diagnostics are discussed, e.g., the selective and sensitive detection of biomarkers. Finally, we highlight current limitations and the future prospects of living cell microarrays. PMID:27600077

An overview of the Progenika ID CORE XT: an automated genotyping platform based on a fluidic microarray system.

PubMed

Goldman, Mindy; Núria, Núria; Castilho, Lilian M

2015-01-01

Automated testing platforms facilitate the introduction of red cell genotyping of patients and blood donors. Fluidic microarray systems, such as Luminex XMAP (Austin, TX), are used in many clinical applications, including HLA and HPA typing. The Progenika ID CORE XT (Progenika Biopharma-Grifols, Bizkaia, Spain) uses this platform to analyze 29 polymorphisms determining 37 antigens in 10 blood group systems. Once DNA has been extracted, processing time is approximately 4 hours. The system is highly automated and includes integrated analysis software that produces a file and a report with genotype and predicted phenotype results.

MRI phenotypes with high neurodegeneration are associated with peripheral blood B-cell changes.

PubMed

Comabella, Manuel; Cantó, Ester; Nurtdinov, Ramil; Río, Jordi; Villar, Luisa M; Picón, Carmen; Castilló, Joaquín; Fissolo, Nicolás; Aymerich, Xavier; Auger, Cristina; Rovira, Alex; Montalban, Xavier

2016-01-15

Little is known about the mechanisms leading to neurodegeneration in multiple sclerosis (MS) and the role of peripheral blood cells in this neurodegenerative component. We aimed to correlate brain radiological phenotypes defined by high and low neurodegeneration with gene expression profiling of peripheral blood mononuclear cells (PBMC) from MS patients. Magnetic resonance imaging (MRI) scans from 64 patients with relapsing-remitting MS (RRMS) were classified into radiological phenotypes characterized by low (N = 27) and high (N = 37) neurodegeneration according to the number of contrast-enhancing lesions, the relative volume of non-enhancing black holes on T1-weighted images, and the brain parenchymal fraction. Gene expression profiling was determined in PBMC using microarrays, and validation of selected genes was performed by polymerase chain reaction (PCR). B-cell immunophenotyping was conducted by flow cytometry. Microarray analysis revealed the B-cell specific genes FCRL1, FCRL2, FCRL5 (Fc receptor-like 1, 2 and 5 respectively), and CD22 as the top differentially expressed genes between patients with high and low neurodegeneration. Levels for these genes were significantly down-regulated in PBMC from patients with MRI phenotypes characterized by high neurodegeneration and microarray findings were validated by PCR. In patients with high neurodegeneration, immunophenotyping showed a significant increase in the expression of the B-cell activation markers CD80 in naïve B cells (CD45+/CD19+/CD27-/IgD+), unswitched memory B cells (CD45+/CD19+/CD27+/IgD+), and switched memory B cells (CD45+/CD19+/CD27+/IgD-), and CD86 in naïve and switched memory B cells. These results suggest that RRMS patients with radiological phenotypes showing high neurodegeneration have changes in B cells characterized by down-regulation of B-cell-specific genes and increased activation status. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Micropatterned comet assay enables high throughput and sensitive DNA damage quantification

PubMed Central

Ge, Jing; Chow, Danielle N.; Fessler, Jessica L.; Weingeist, David M.; Wood, David K.; Engelward, Bevin P.

2015-01-01

The single cell gel electrophoresis assay, also known as the comet assay, is a versatile method for measuring many classes of DNA damage, including base damage, abasic sites, single strand breaks and double strand breaks. However, limited throughput and difficulties with reproducibility have limited its utility, particularly for clinical and epidemiological studies. To address these limitations, we created a microarray comet assay. The use of a micrometer scale array of cells increases the number of analysable comets per square centimetre and enables automated imaging and analysis. In addition, the platform is compatible with standard 24- and 96-well plate formats. Here, we have assessed the consistency and sensitivity of the microarray comet assay. We showed that the linear detection range for H2O2-induced DNA damage in human lymphoblastoid cells is between 30 and 100 μM, and that within this range, inter-sample coefficient of variance was between 5 and 10%. Importantly, only 20 comets were required to detect a statistically significant induction of DNA damage for doses within the linear range. We also evaluated sample-to-sample and experiment-to-experiment variation and found that for both conditions, the coefficient of variation was lower than what has been reported for the traditional comet assay. Finally, we also show that the assay can be performed using a 4× objective (rather than the standard 10× objective for the traditional assay). This adjustment combined with the microarray format makes it possible to capture more than 50 analysable comets in a single image, which can then be automatically analysed using in-house software. Overall, throughput is increased more than 100-fold compared to the traditional assay. Together, the results presented here demonstrate key advances in comet assay technology that improve the throughput, sensitivity, and robustness, thus enabling larger scale clinical and epidemiological studies. PMID:25527723

Micropatterned comet assay enables high throughput and sensitive DNA damage quantification.

PubMed

Ge, Jing; Chow, Danielle N; Fessler, Jessica L; Weingeist, David M; Wood, David K; Engelward, Bevin P

2015-01-01

The single cell gel electrophoresis assay, also known as the comet assay, is a versatile method for measuring many classes of DNA damage, including base damage, abasic sites, single strand breaks and double strand breaks. However, limited throughput and difficulties with reproducibility have limited its utility, particularly for clinical and epidemiological studies. To address these limitations, we created a microarray comet assay. The use of a micrometer scale array of cells increases the number of analysable comets per square centimetre and enables automated imaging and analysis. In addition, the platform is compatible with standard 24- and 96-well plate formats. Here, we have assessed the consistency and sensitivity of the microarray comet assay. We showed that the linear detection range for H2O2-induced DNA damage in human lymphoblastoid cells is between 30 and 100 μM, and that within this range, inter-sample coefficient of variance was between 5 and 10%. Importantly, only 20 comets were required to detect a statistically significant induction of DNA damage for doses within the linear range. We also evaluated sample-to-sample and experiment-to-experiment variation and found that for both conditions, the coefficient of variation was lower than what has been reported for the traditional comet assay. Finally, we also show that the assay can be performed using a 4× objective (rather than the standard 10× objective for the traditional assay). This adjustment combined with the microarray format makes it possible to capture more than 50 analysable comets in a single image, which can then be automatically analysed using in-house software. Overall, throughput is increased more than 100-fold compared to the traditional assay. Together, the results presented here demonstrate key advances in comet assay technology that improve the throughput, sensitivity, and robustness, thus enabling larger scale clinical and epidemiological studies. © The Author 2014. Published by Oxford University Press on behalf of the Mutagenesis Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Imaging combined autoimmune and infectious disease microarrays

NASA Astrophysics Data System (ADS)

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

2006-09-01

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

Internet-based profiler system as integrative framework to support translational research

PubMed Central

Kim, Robert; Demichelis, Francesca; Tang, Jeffery; Riva, Alberto; Shen, Ronglai; Gibbs, Doug F; Mahavishno, Vasudeva; Chinnaiyan, Arul M; Rubin, Mark A

2005-01-01

Background Translational research requires taking basic science observations and developing them into clinically useful tests and therapeutics. We have developed a process to develop molecular biomarkers for diagnosis and prognosis by integrating tissue microarray (TMA) technology and an internet-database tool, Profiler. TMA technology allows investigators to study hundreds of patient samples on a single glass slide resulting in the conservation of tissue and the reduction in inter-experimental variability. The Profiler system allows investigator to reliably track, store, and evaluate TMA experiments. Here within we describe the process that has evolved through an empirical basis over the past 5 years at two academic institutions. Results The generic design of this system makes it compatible with multiple organ system (e.g., prostate, breast, lung, renal, and hematopoietic system,). Studies and folders are restricted to authorized users as required. Over the past 5 years, investigators at 2 academic institutions have scanned 656 TMA experiments and collected 63,311 digital images of these tissue samples. 68 pathologists from 12 major user groups have accessed the system. Two groups directly link clinical data from over 500 patients for immediate access and the remaining groups choose to maintain clinical and pathology data on separate systems. Profiler currently has 170 K data points such as staining intensity, tumor grade, and nuclear size. Due to the relational database structure, analysis can be easily performed on single or multiple TMA experimental results. The TMA module of Profiler can maintain images acquired from multiple systems. Conclusion We have developed a robust process to develop molecular biomarkers using TMA technology and an internet-based database system to track all steps of this process. This system is extendable to other types of molecular data as separate modules and is freely available to academic institutions for licensing. PMID:16364175

Internet-based Profiler system as integrative framework to support translational research.

PubMed

Kim, Robert; Demichelis, Francesca; Tang, Jeffery; Riva, Alberto; Shen, Ronglai; Gibbs, Doug F; Mahavishno, Vasudeva; Chinnaiyan, Arul M; Rubin, Mark A

2005-12-19

Translational research requires taking basic science observations and developing them into clinically useful tests and therapeutics. We have developed a process to develop molecular biomarkers for diagnosis and prognosis by integrating tissue microarray (TMA) technology and an internet-database tool, Profiler. TMA technology allows investigators to study hundreds of patient samples on a single glass slide resulting in the conservation of tissue and the reduction in inter-experimental variability. The Profiler system allows investigator to reliably track, store, and evaluate TMA experiments. Here within we describe the process that has evolved through an empirical basis over the past 5 years at two academic institutions. The generic design of this system makes it compatible with multiple organ system (e.g., prostate, breast, lung, renal, and hematopoietic system,). Studies and folders are restricted to authorized users as required. Over the past 5 years, investigators at 2 academic institutions have scanned 656 TMA experiments and collected 63,311 digital images of these tissue samples. 68 pathologists from 12 major user groups have accessed the system. Two groups directly link clinical data from over 500 patients for immediate access and the remaining groups choose to maintain clinical and pathology data on separate systems. Profiler currently has 170 K data points such as staining intensity, tumor grade, and nuclear size. Due to the relational database structure, analysis can be easily performed on single or multiple TMA experimental results. The TMA module of Profiler can maintain images acquired from multiple systems. We have developed a robust process to develop molecular biomarkers using TMA technology and an internet-based database system to track all steps of this process. This system is extendable to other types of molecular data as separate modules and is freely available to academic institutions for licensing.

Spectral Analysis of Breast Cancer on Tissue Microarrays: Seeing Beyond Morphology

DTIC Science & Technology

2005-04-01

Harvey N., Szymanski J.J., Bloch J.J., Mitchell M. investigation of image feature extraction by a genetic algorithm. Proc. SPIE 1999;3812:24-31. 11...automated feature extraction using multiple data sources. Proc. SPIE 2003;5099:190-200. 15 4 Spectral-Spatial Analysis of Urine Cytology Angeletti et al...Appendix Contents: 1. Harvey, N.R., Levenson, R.M., Rimm, D.L. (2003) Investigation of Automated Feature Extraction Techniques for Applications in

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

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

PubMed Central

2013-01-01

Background The most important challenge of performing insitu transcriptional profiling of the human ocular surface epithelial regions is obtaining samples in sufficient amounts, without contamination from adjacent tissue, as the region of interest is microscopic and closely apposed to other tissues regions. We have effectively collected ocular surface (OS) epithelial tissue samples from the Limbal Epithelial Crypt (LEC), limbus, cornea and conjunctiva of post-mortem cadaver eyes with laser microdissection (LMD) technique for gene expression studies with spotted oligonucleotide microarrays and Gene 1.0 ST arrays. Methods Human donor eyes (4 pairs for spotted oligonucleotide microarrays, 3 pairs for Gene 1.0 ST arrays) consented for research were included in this study with due ethical approval of the Nottingham Research Ethics Committee. Eye retrieval was performed within 36 hours of post-mortem period. The dissected corneoscleral buttons were immersed in OCT media and frozen in liquid nitrogen and stored at −80°C till further use. Microscopic tissue sections of interest were taken on PALM slides and stained with Toluidine Blue for laser microdissection with PALM microbeam systems. Optimisation of the laser microdissection technique was crucial for efficient and cost effective sample collection. Results The starting concentration of RNA as stipulated by the protocol of microarray platforms was taken as the cut-off concentration of RNA samples in our studies. The area of LMD tissue processed for spotted oligonucleotide microarray study ranged from 86,253 μm2 in LEC to 392,887 μm2 in LEC stroma. The RNA concentration of the LMD samples ranged from 22 to 92 pg/μl. The recommended starting concentration of the RNA samples used for Gene 1.0 ST arrays was 6 ng/5 μl. To achieve the desired RNA concentration the area of ocular surface epithelial tissue sample processed for the Gene 1.0 ST array experiments was approximately 100,0000 μm2 to 130,0000 μm2. RNA concentration of these samples ranged from 10.88 ng/12 μl to 25.8 ng/12 μl, with the RNA integrity numbers (RIN) for these samples from 3.3 to 7.9. RNA samples with RIN values below 2, that had failed to amplify satisfactorily were discarded. Conclusions The optimised protocol for sample collection and laser microdissection improved the RNA yield of the insitu ocular surface epithelial regions for effective microarray studies on spotted oligonucleotide and affymetrix platforms. PMID:24160452

A biomolecule friendly photolithographic process for fabrication of protein microarrays on polymeric films coated on silicon chips.

PubMed

Petrou, Panagiota S; Chatzichristidi, Margarita; Douvas, Antonios M; Argitis, Panagiotis; Misiakos, Konstantinos; Kakabakos, Sotirios E

2007-04-15

The last years, there is a steadily growing demand for methods and materials appropriate to create patterns of biomolecules for bioanalytical applications. Here, a photolithographic method for patterning biomolecules onto a silicon surface coated with a polymeric layer of high protein binding capacity is presented. The patterning process does not affect the polymeric film and the activity of the immobilized onto the surface biomolecules. Therefore, it permits sequential immobilization of different biomolecules on spatially distinct areas on the same solid support. The polymeric layer is based on a commercially available photoresist (AZ5214) that is cured at high temperature in order to provide a stable substrate for creation of protein microarrays by the developed photolithographic process. The photolithographic material consists of a (meth)acrylate copolymer and a sulfonium salt as a photoacid generator, and it is lithographically processed by thermal treatment at temperatures

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

NASA Astrophysics Data System (ADS)

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2006-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions.

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

PubMed Central

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2008-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions. PMID:19081771

Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays

PubMed Central

Chaudhery, Vikram; Huang, Cheng-Sheng; Pokhriyal, Anusha; Polans, James; Cunningham, Brian T.

2011-01-01

By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer. PMID:22109210

Spatially selective photonic crystal enhanced fluorescence and application to background reduction for biomolecule detection assays.

PubMed

Chaudhery, Vikram; Huang, Cheng-Sheng; Pokhriyal, Anusha; Polans, James; Cunningham, Brian T

2011-11-07

By combining photonic crystal label-free biosensor imaging with photonic crystal enhanced fluorescence, it is possible to selectively enhance the fluorescence emission from regions of the PC surface based upon the density of immobilized capture molecules. A label-free image of the capture molecules enables determination of optimal coupling conditions of the laser used for fluorescence imaging of the photonic crystal surface on a pixel-by-pixel basis, allowing maximization of fluorescence enhancement factor from regions incorporating a biomolecule capture spot and minimization of background autofluorescence from areas between capture spots. This capability significantly improves the contrast of enhanced fluorescent images, and when applied to an antibody protein microarray, provides a substantial advantage over conventional fluorescence microscopy. Using the new approach, we demonstrate detection limits as low as 0.97 pg/ml for a representative protein biomarker in buffer.

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

PubMed Central

Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

2003-01-01

Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

Strand-specific transcriptome profiling with directly labeled RNA on genomic tiling microarrays

PubMed Central

2011-01-01

Background With lower manufacturing cost, high spot density, and flexible probe design, genomic tiling microarrays are ideal for comprehensive transcriptome studies. Typically, transcriptome profiling using microarrays involves reverse transcription, which converts RNA to cDNA. The cDNA is then labeled and hybridized to the probes on the arrays, thus the RNA signals are detected indirectly. Reverse transcription is known to generate artifactual cDNA, in particular the synthesis of second-strand cDNA, leading to false discovery of antisense RNA. To address this issue, we have developed an effective method using RNA that is directly labeled, thus by-passing the cDNA generation. This paper describes this method and its application to the mapping of transcriptome profiles. Results RNA extracted from laboratory cultures of Porphyromonas gingivalis was fluorescently labeled with an alkylation reagent and hybridized directly to probes on genomic tiling microarrays specifically designed for this periodontal pathogen. The generated transcriptome profile was strand-specific and produced signals close to background level in most antisense regions of the genome. In contrast, high levels of signal were detected in the antisense regions when the hybridization was done with cDNA. Five antisense areas were tested with independent strand-specific RT-PCR and none to negligible amplification was detected, indicating that the strong antisense cDNA signals were experimental artifacts. Conclusions An efficient method was developed for mapping transcriptome profiles specific to both coding strands of a bacterial genome. This method chemically labels and uses extracted RNA directly in microarray hybridization. The generated transcriptome profile was free of cDNA artifactual signals. In addition, this method requires fewer processing steps and is potentially more sensitive in detecting small amount of RNA compared to conventional end-labeling methods due to the incorporation of more fluorescent molecules per RNA fragment. PMID:21235785

Microarray analysis of the rat lacrimal gland following the loss of parasympathetic control of secretion

PubMed Central

Nguyen, Doan H.; Toshida, Hiroshi; Schurr, Jill; Beuerman, Roger W.

2010-01-01

Previous studies showed that loss of muscarinic parasympathetic input to the lacrimal gland (LG) leads to a dramatic reduction in tear secretion and profound changes to LG structure. In this study, we used DNA microarrays to examine the regulation of the gene expression of the genes for secretory function and organization of the LG. Long-Evans rats anesthetized with a mixture of ketamine/xylazine (80:10 mg/kg) underwent unilateral sectioning of the greater superficial petrosal nerve, the input to the pterygopalatine ganglion. After 7 days, tear secretion was measured, the animals were killed, and structural changes in the LG were examined by light microscopy. Total RNA from control and experimental LGs (n = 5) was used for DNA microarray analysis employing the U34A GeneChip. Three statistical algorithms (detection, change call, and signal log ratio) were used to determine differential gene expression using the Microarray Suite (5.0) and Data Mining Tools (3.0). Tear secretion was significantly reduced and corneal ulcers developed in all experimental eyes. Light microscopy showed breakdown of the acinar structure of the LG. DNA microarray analysis showed downregulation of genes associated with the endoplasmic reticulum and Golgi, including genes involved in protein folding and processing. Conversely, transcripts for cytoskeleton and extracellular matrix components, inflammation, and apoptosis were upregulated. The number of significantly upregulated genes (116) was substantially greater than the number of downregulated genes (49). Removal of the main secretory input to the rat LG resulted in clinical symptoms associated with severe dry eye. Components of the secretory pathway were negatively affected, and the increase in cell proliferation and inflammation may lead to loss of organization in the parasympathectomized lacrimal gland. PMID:15084711

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Linking microarray reporters with protein functions

PubMed Central

Gaj, Stan; van Erk, Arie; van Haaften, Rachel IM; Evelo, Chris TA

2007-01-01

Background The analysis of microarray experiments requires accurate and up-to-date functional annotation of the microarray reporters to optimize the interpretation of the biological processes involved. Pathway visualization tools are used to connect gene expression data with existing biological pathways by using specific database identifiers that link reporters with elements in the pathways. Results This paper proposes a novel method that aims to improve microarray reporter annotation by BLASTing the original reporter sequences against a species-specific EMBL subset, that was derived from and crosslinked back to the highly curated UniProt database. The resulting alignments were filtered using high quality alignment criteria and further compared with the outcome of a more traditional approach, where reporter sequences were BLASTed against EnsEMBL followed by locating the corresponding protein (UniProt) entry for the high quality hits. Combining the results of both methods resulted in successful annotation of > 58% of all reporter sequences with UniProt IDs on two commercial array platforms, increasing the amount of Incyte reporters that could be coupled to Gene Ontology terms from 32.7% to 58.3% and to a local GenMAPP pathway from 9.6% to 16.7%. For Agilent, 35.3% of the total reporters are now linked towards GO nodes and 7.1% on local pathways. Conclusion Our methods increased the annotation quality of microarray reporter sequences and allowed us to visualize more reporters using pathway visualization tools. Even in cases where the original reporter annotation showed the correct description the new identifiers often allowed improved pathway and Gene Ontology linking. These methods are freely available at http://www.bigcat.unimaas.nl/public/publications/Gaj_Annotation/. PMID:17897448

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

PubMed Central

Zhu, Yuerong; Zhu, Yuelin; Xu, Wei

2008-01-01

Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

PubMed

Bühnemann, Claudia; Li, Simon; Yu, Haiyue; Branford White, Harriet; Schäfer, Karl L; Llombart-Bosch, Antonio; Machado, Isidro; Picci, Piero; Hogendoorn, Pancras C W; Athanasou, Nicholas A; Noble, J Alison; Hassan, A Bassim

2014-01-01

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. Such an automated and integrated methodology has potential application in the identification of prognostic classifiers based on tumour cell heterogeneity.

Mass-transport limitations in spot-based microarrays.

PubMed

Zhao, Ming; Wang, Xuefeng; Nolte, David

2010-09-20

Mass transport of analyte to surface-immobilized affinity reagents is the fundamental bottleneck for sensitive detection in solid-support microarrays and biosensors. Analyte depletion in the volume adjacent to the sensor causes deviation from ideal association, significantly slows down reaction kinetics, and causes inhomogeneous binding across the sensor surface. In this paper we use high-resolution molecular interferometric imaging (MI2), a label-free optical interferometry technique for direct detection of molecular films, to study the inhomogeneous distribution of intra-spot binding across 100 micron-diameter protein spots. By measuring intra-spot binding inhomogeneity, reaction kinetics can be determined accurately when combined with a numerical three-dimensional finite element model. To ensure homogeneous binding across a spot, a critical flow rate is identified in terms of the association rate k(a) and the spot diameter. The binding inhomogeneity across a spot can be used to distinguish high-affinity low-concentration specific reactions from low-affinity high-concentration non-specific binding of background proteins.

Evaluation of the efficacy of constitutional array-based comparative genomic hybridization in the diagnosis of aneuploidy using genomic and amplified DNA.

PubMed

Tan, Niap H; Palmer, Rodger; Wang, Rubin

2010-02-01

Array-based comparative genomic hybridization (array CGH) is a new molecular technique that has the potential to revolutionize cytogenetics. However, use of high resolution array CGH in the clinical setting is plagued by the problem of widespread copy number variations (CNV) in the human genome. Constitutional microarray, containing only clones that interrogate regions of known constitutional syndromes, may circumvent the dilemma of detecting CNV of unknown clinical significance. The present study investigated the efficacy of constitutional microarray in the diagnosis of trisomy. Test samples included genomic DNA from trisomic cell lines, amplification products of 50 ng of genomic DNA and whole genome amplification products of single cells. DNA amplification was achieved by means of multiple displacement amplification (MDA) over 16 h. The trisomic and sex chromosomes copy number imbalances in the genomic DNA were correctly identified by the constitutional microarrays. However, there was a failure to detect the trisomy in the amplification products of 50 ng of genomic DNA and whole genome amplification products of single cells. Using carefully selected clones, Spectral Genomics constitutional microarray was able to detect the chromosomal copy number imbalances in genomic DNA without the confounding effects of CNV. The diagnostic failure in amplified DNA samples could be attributed to the amplification process. The MDA duration of 16 h generated excessive amount of biases and shortening the duration might minimize the problem.

Model-based variance-stabilizing transformation for Illumina microarray data.

PubMed

Lin, Simon M; Du, Pan; Huber, Wolfgang; Kibbe, Warren A

2008-02-01

Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

Automated Immunomagnetic Separation and Microarray Detection of E. coli O157:H7 from Poultry Carcass Rinse

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandler, Darrell P.; Brown, Jeremy D.; Call, Douglas R.

2001-09-01

We describe the development and application of a novel electromagnetic flow cell and fluidics system for automated immunomagnetic separation of E. coli directly from unprocessed poultry carcass rinse, and the biochemical coupling of automated sample preparation with nucleic acid microarrays without cell growth. Highly porous nickel foam was used as a magnetic flux conductor. Up to 32% recovery efficiency of 'total' E. coli was achieved within the automated system with 6 sec contact times and 15 minute protocol (from sample injection through elution), statistically similar to cell recovery efficiencies in > 1 hour 'batch' captures. The electromagnet flow cell allowedmore » complete recovery of 2.8 mm particles directly from unprocessed poultry carcass rinse whereas the batch system did not. O157:H7 cells were reproducibly isolated directly from unprocessed poultry rinse with 39% recovery efficiency at 103 cells ml-1 inoculum. Direct plating of washed beads showed positive recovery of O 157:H7 directly from carcass rinse at an inoculum of 10 cells ml-1. Recovered beads were used for direct PCR amplification and microarray detection, with a process-level detection limit (automated cell concentration through microarray detection) of < 103 cells ml-1 carcass rinse. The fluidic system and analytical approach described here are generally applicable to most microbial detection problems and applications.« less

High-throughput quantum cascade laser (QCL) spectral histopathology: a practical approach towards clinical translation.

PubMed

Pilling, Michael J; Henderson, Alex; Bird, Benjamin; Brown, Mick D; Clarke, Noel W; Gardner, Peter

2016-06-23

Infrared microscopy has become one of the key techniques in the biomedical research field for interrogating tissue. In partnership with multivariate analysis and machine learning techniques, it has become widely accepted as a method that can distinguish between normal and cancerous tissue with both high sensitivity and high specificity. While spectral histopathology (SHP) is highly promising for improved clinical diagnosis, several practical barriers currently exist, which need to be addressed before successful implementation in the clinic. Sample throughput and speed of acquisition are key barriers and have been driven by the high volume of samples awaiting histopathological examination. FTIR chemical imaging utilising FPA technology is currently state-of-the-art for infrared chemical imaging, and recent advances in its technology have dramatically reduced acquisition times. Despite this, infrared microscopy measurements on a tissue microarray (TMA), often encompassing several million spectra, takes several hours to acquire. The problem lies with the vast quantities of data that FTIR collects; each pixel in a chemical image is derived from a full infrared spectrum, itself composed of thousands of individual data points. Furthermore, data management is quickly becoming a barrier to clinical translation and poses the question of how to store these incessantly growing data sets. Recently, doubts have been raised as to whether the full spectral range is actually required for accurate disease diagnosis using SHP. These studies suggest that once spectral biomarkers have been predetermined it may be possible to diagnose disease based on a limited number of discrete spectral features. In this current study, we explore the possibility of utilising discrete frequency chemical imaging for acquiring high-throughput, high-resolution chemical images. Utilising a quantum cascade laser imaging microscope with discrete frequency collection at key diagnostic wavelengths, we demonstrate that we can diagnose prostate cancer with high sensitivity and specificity. Finally we extend the study to a large patient dataset utilising tissue microarrays, and show that high sensitivity and specificity can be achieved using high-throughput, rapid data collection, thereby paving the way for practical implementation in the clinic.

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

EPA Science Inventory

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

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Protein microarray with horseradish peroxidase chemiluminescence for quantification of serum α-fetoprotein.

PubMed

Zhao, Yuanshun; Zhang, Yonghong; Lin, Dongdong; Li, Kang; Yin, Chengzeng; Liu, Xiuhong; Jin, Boxun; Sun, Libo; Liu, Jinhua; Zhang, Aiying; Li, Ning

2015-10-01

To develop and evaluate a protein microarray assay with horseradish peroxidase (HRP) chemiluminescence for quantification of α-fetoprotein (AFP) in serum from patients with hepatocellular carcinoma (HCC). A protein microarray assay for AFP was developed. Serum was collected from patients with HCC and healthy control subjects. AFP was quantified using protein microarray and enzyme-linked immunosorbent assay (ELISA). Serum AFP concentrations determined via protein microarray were positively correlated (r = 0.973) with those determined via ELISA in patients with HCC (n = 60) and healthy control subjects (n = 30). Protein microarray showed 80% sensitivity and 100% specificity for HCC diagnosis. ELISA had 83.3% sensitivity and 100% specificity. Protein microarray effectively distinguished between patients with HCC and healthy control subjects (area under ROC curve 0.974; 95% CI 0.000, 1.000). Protein microarray is a rapid, simple and low-cost alternative to ELISA for detecting AFP in human serum. © The Author(s) 2015.

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

PubMed Central

2011-01-01

Background In previous work, we reported the development of caCORRECT, a novel microarray quality control system built to identify and correct spatial artifacts commonly found on Affymetrix arrays. We have made recent improvements to caCORRECT, including the development of a model-based data-replacement strategy and integration with typical microarray workflows via caCORRECT's web portal and caBIG grid services. In this report, we demonstrate that caCORRECT improves the reproducibility and reliability of experimental results across several common Affymetrix microarray platforms. caCORRECT represents an advance over state-of-art quality control methods such as Harshlighting, and acts to improve gene expression calculation techniques such as PLIER, RMA and MAS5.0, because it incorporates spatial information into outlier detection as well as outlier information into probe normalization. The ability of caCORRECT to recover accurate gene expressions from low quality probe intensity data is assessed using a combination of real and synthetic artifacts with PCR follow-up confirmation and the affycomp spike in data. The caCORRECT tool can be accessed at the website: http://cacorrect.bme.gatech.edu. Results We demonstrate that (1) caCORRECT's artifact-aware normalization avoids the undesirable global data warping that happens when any damaged chips are processed without caCORRECT; (2) When used upstream of RMA, PLIER, or MAS5.0, the data imputation of caCORRECT generally improves the accuracy of microarray gene expression in the presence of artifacts more than using Harshlighting or not using any quality control; (3) Biomarkers selected from artifactual microarray data which have undergone the quality control procedures of caCORRECT are more likely to be reliable, as shown by both spike in and PCR validation experiments. Finally, we present a case study of the use of caCORRECT to reliably identify biomarkers for renal cell carcinoma, yielding two diagnostic biomarkers with potential clinical utility, PRKAB1 and NNMT. Conclusions caCORRECT is shown to improve the accuracy of gene expression, and the reproducibility of experimental results in clinical application. This study suggests that caCORRECT will be useful to clean up possible artifacts in new as well as archived microarray data. PMID:21957981

Genomics of the Effect of Spinal Cord Stimulation on an Animal Model of Neuropathic Pain.

PubMed

Vallejo, Ricardo; Tilley, Dana M; Cedeño, David L; Kelley, Courtney A; DeMaegd, Margaret; Benyamin, Ramsin

2016-08-01

Few studies have evaluated single-gene changes modulated by spinal cord stimulation (SCS), providing a narrow understanding of molecular changes. Genomics allows for a robust analysis of holistic gene changes in response to stimulation. Rats were randomized into six groups to determine the effect of continuous SCS in uninjured and spared-nerve injury (SNI) animals. After behavioral assessment, tissues from the dorsal quadrant of the spinal cord (SC) and dorsal root ganglion (DRG) underwent full-genome microarray analyses. Weighted Gene Correlation Network Analysis (WGCNA), and Gene Ontology (GO) analysis identified similar expression patterns, molecular functions and biological processes for significant genes. Microarray analyses reported 20,985 gene probes in SC and 19,104 in DRG. WGCNA sorted 7449 SC and 4275 DRG gene probes into 29 and 9 modules, respectively. WGCNA provided significant modules from paired comparisons of experimental groups. GO analyses reported significant biological processes influenced by injury, as well as the presence of an electric field. The genes Tlr2, Cxcl16, and Cd68 were used to further validate the microarray based on significant response to SCS in SNI animals. They were up-regulated in the SC while both Tlr2 and Cd68 were up-regulated in the DRG. The process described provides highly significant interconnected genes and pathways responsive to injury and/or electric field in the SC and DRG. Genes in the SC respond significantly to the SCS in both injured and uninjured animals, while those in the DRG significantly responded to injury, and SCS in injured animals. © 2016 International Neuromodulation Society.

Gene expression profiling of Listeria monocytogenes strain F2365 during growth in ultrahigh-temperature-processed skim milk.

PubMed

Liu, Yanhong; Ream, Amy

2008-11-01

To study how Listeria monocytogenes survives and grows in ultrahigh-temperature-processed (UHT) skim milk, microarray technology was used to monitor the gene expression profiles of strain F2365 in UHT skim milk. Total RNA was isolated from strain F2365 in UHT skim milk after 24 h of growth at 4 degrees C, labeled with fluorescent dyes, and hybridized to "custom-made" commercial oligonucleotide (35-mers) microarray chips containing the whole genome of L. monocytogenes strain F2365. Compared to L. monocytogenes grown in brain heart infusion (BHI) broth for 24 h at 4 degrees C, 26 genes were upregulated (more-than-twofold increase) in UHT skim milk, whereas 14 genes were downregulated (less-than-twofold decrease). The upregulated genes included genes encoding transport and binding proteins, transcriptional regulators, proteins in amino acid biosynthesis and energy metabolism, protein synthesis, cell division, and hypothetical proteins. The downregulated genes included genes that encode transport and binding proteins, protein synthesis, cellular processes, cell envelope, energy metabolism, a transcriptional regulator, and an unknown protein. The gene expression changes determined by microarray assays were confirmed by real-time reverse transcriptase PCR analyses. Furthermore, cells grown in UHT skim milk displayed the same sensitivity to hydrogen peroxide as cells grown in BHI, demonstrating that the elevated levels of expression of genes encoding manganese transporter complexes in UHT skim milk did not result in changes in the oxidative stress sensitivity. To our knowledge, this report represents a novel study of global transcriptional gene expression profiling of L. monocytogenes in a liquid food.

Development of a high-throughput Candida albicans biofilm chip.

PubMed

Srinivasan, Anand; Uppuluri, Priya; Lopez-Ribot, Jose; Ramasubramanian, Anand K

2011-04-22

We have developed a high-density microarray platform consisting of nano-biofilms of Candida albicans. A robotic microarrayer was used to print yeast cells of C. albicans encapsulated in a collagen matrix at a volume as low as 50 nL onto surface-modified microscope slides. Upon incubation, the cells grow into fully formed "nano-biofilms". The morphological and architectural complexity of these biofilms were evaluated by scanning electron and confocal scanning laser microscopy. The extent of biofilm formation was determined using a microarray scanner from changes in fluorescence intensities due to FUN 1 metabolic processing. This staining technique was also adapted for antifungal susceptibility testing, which demonstrated that, similar to regular biofilms, cells within the on-chip biofilms displayed elevated levels of resistance against antifungal agents (fluconazole and amphotericin B). Thus, results from structural analyses and antifungal susceptibility testing indicated that despite miniaturization, these biofilms display the typical phenotypic properties associated with the biofilm mode of growth. In its final format, the C. albicans biofilm chip (CaBChip) is composed of 768 equivalent and spatially distinct nano-biofilms on a single slide; multiple chips can be printed and processed simultaneously. Compared to current methods for the formation of microbial biofilms, namely the 96-well microtiter plate model, this fungal biofilm chip has advantages in terms of miniaturization and automation, which combine to cut reagent use and analysis time, minimize labor intensive steps, and dramatically reduce assay costs. Such a chip should accelerate the antifungal drug discovery process by enabling rapid, convenient and inexpensive screening of hundreds-to-thousands of compounds simultaneously.

Systematic gene microarray analysis of the lncRNA expression profiles in human uterine cervix carcinoma.

PubMed

Chen, Jie; Fu, Ziyi; Ji, Chenbo; Gu, Pingqing; Xu, Pengfei; Yu, Ningzhu; Kan, Yansheng; Wu, Xiaowei; Shen, Rong; Shen, Yan

2015-05-01

The human uterine cervix carcinoma is one of the most well-known malignancy reproductive system cancers, which threatens women health globally. However, the mechanisms of the oncogenesis and development process of cervix carcinoma are not yet fully understood. Long non-coding RNAs (lncRNAs) have been proved to play key roles in various biological processes, especially development of cancer. The function and mechanism of lncRNAs on cervix carcinoma is still rarely reported. We selected 3 cervix cancer and normal cervix tissues separately, then performed lncRNA microarray to detect the differentially expressed lncRNAs. Subsequently, we explored the potential function of these dysregulated lncRNAs through online bioinformatics databases. Finally, quantity real-time PCR was carried out to confirm the expression levels of these dysregulated lncRNAs in cervix cancer and normal tissues. We uncovered the profiles of differentially expressed lncRNAs between normal and cervix carcinoma tissues by using the microarray techniques, and found 1622 upregulated and 3026 downregulated lncRNAs (fold-change>2.0) in cervix carcinoma compared to the normal cervical tissue. Furthermore, we found HOXA11-AS might participate in cervix carcinogenesis by regulating HOXA11, which is involved in regulating biological processes of cervix cancer. This study afforded expression profiles of lncRNAs between cervix carcinoma tissue and normal cervical tissue, which could provide database for further research about the function and mechanism of key-lncRNAs in cervix carcinoma, and might be helpful to explore potential diagnosis factors and therapeutic targets for cervix carcinoma. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Global transcriptional responses of Bacillus subtilis to xenocoumacin 1.

PubMed

Zhou, T; Zeng, H; Qiu, D; Yang, X; Wang, B; Chen, M; Guo, L; Wang, S

2011-09-01

To determine the global transcriptional response of Bacillus subtilis to an antimicrobial agent, xenocoumacin 1 (Xcn1). Subinhibitory concentration of Xcn1 applied to B. subtilis was measured according to Hutter's method for determining optimal concentrations. cDNA microarray technology was used to study the global transcriptional response of B. subtilis to Xcn1. Real-time RT-PCR was employed to verify alterations in the transcript levels of six genes. The subinhibitory concentration was determined to be 1 μg ml(-1). The microarray data demonstrated that Xcn1 treatment of B. subtilis led to more than a 2.0-fold up-regulation of 480 genes and more than a 2.0-fold down-regulation of 479 genes (q ≤ 0.05). The transcriptional responses of B. subtilis to Xcn1 were determined, and several processes were affected by Xcn1. Additionally, cluster analysis of gene expression profiles after treatment with Xcn1 or 37 previously studied antibiotics indicated that Xcn1 has similar mechanisms of action to protein synthesis inhibitors. These microarray data showed alterations of gene expression in B. subtilis after exposure to Xcn1. From the results, we identified various processes affected by Xcn1. This study provides a whole-genome perspective to elucidate the action of Xcn1 as a potential antimicrobial agent. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Transcriptome Analysis of Early Responsive Genes in Rice during Magnaporthe oryzae Infection.

PubMed

Wang, Yiming; Kwon, Soon Jae; Wu, Jingni; Choi, Jaeyoung; Lee, Yong-Hwan; Agrawal, Ganesh Kumar; Tamogami, Shigeru; Rakwal, Randeep; Park, Sang-Ryeol; Kim, Beom-Gi; Jung, Ki-Hong; Kang, Kyu Young; Kim, Sang Gon; Kim, Sun Tae

2014-12-01

Rice blast disease caused by Magnaporthe oryzae is one of the most serious diseases of cultivated rice (Oryza sativa L.) in most rice-growing regions of the world. In order to investigate early response genes in rice, we utilized the transcriptome analysis approach using a 300 K tilling microarray to rice leaves infected with compatible and incompatible M. oryzae strains. Prior to the microarray experiment, total RNA was validated by measuring the differential expression of rice defense-related marker genes (chitinase 2, barwin, PBZ1, and PR-10) by RT-PCR, and phytoalexins (sakuranetin and momilactone A) with HPLC. Microarray analysis revealed that 231 genes were up-regulated (>2 fold change, p < 0.05) in the incompatible interaction compared to the compatible one. Highly expressed genes were functionally characterized into metabolic processes and oxidation-reduction categories. The oxidative stress response was induced in both early and later infection stages. Biotic stress overview from MapMan analysis revealed that the phytohormone ethylene as well as signaling molecules jasmonic acid and salicylic acid is important for defense gene regulation. WRKY and Myb transcription factors were also involved in signal transduction processes. Additionally, receptor-like kinases were more likely associated with the defense response, and their expression patterns were validated by RT-PCR. Our results suggest that candidate genes, including receptor-like protein kinases, may play a key role in disease resistance against M. oryzae attack.

hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

PubMed

Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

2016-01-01

Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

Microarray Analysis of Gene Expression Alteration in Human Middle Ear Epithelial Cells Induced by Asian Sand Dust.

PubMed

Go, Yoon Young; Park, Moo Kyun; Kwon, Jee Young; Seo, Young Rok; Chae, Sung-Won; Song, Jae-Jun

2015-12-01

The primary aim of this study is to evaluate the gene expression profile of Asian sand dust (ASD)-treated human middle ear epithelial cell (HMEEC) using microarray analysis. The HMEEC was treated with ASD (400 µg/mL) and total RNA was extracted for microarray analysis. Molecular pathways among differentially expressed genes were further analyzed. For selected genes, the changes in gene expression were confirmed by real-time polymerase chain reaction. A total of 1,274 genes were differentially expressed by ASD. Among them, 1,138 genes were 2 folds up-regulated, whereas 136 genes were 2 folds down-regulated. Up-regulated genes were mainly involved in cellular processes, including apoptosis, cell differentiation, and cell proliferation. Down-regulated genes affected cellular processes, including apoptosis, cell cycle, cell differentiation, and cell proliferation. The 10 genes including ADM, CCL5, EDN1, EGR1, FOS, GHRL, JUN, SOCS3, TNF, and TNFSF10 were identified as main modulators in up-regulated genes. A total of 11 genes including CSF3, DKK1, FOSL1, FST, TERT, MMP13, PTHLH, SPRY2, TGFBR2, THBS1, and TIMP1 acted as main components of pathway associated with 2-fold down regulated genes. We identified the differentially expressed genes in ASD-treated HMEEC. Our work indicates that air pollutant like ASD, may play an important role in the pathogenesis of otitis media.

Use of homologous and heterologous gene expression profiling tools to characterize transcription dynamics during apple fruit maturation and ripening

PubMed Central

2010-01-01

Background Fruit development, maturation and ripening consists of a complex series of biochemical and physiological changes that in climacteric fruits, including apple and tomato, are coordinated by the gaseous hormone ethylene. These changes lead to final fruit quality and understanding of the functional machinery underlying these processes is of both biological and practical importance. To date many reports have been made on the analysis of gene expression in apple. In this study we focused our investigation on the role of ethylene during apple maturation, specifically comparing transcriptomics of normal ripening with changes resulting from application of the hormone receptor competitor 1-Methylcyclopropene. Results To gain insight into the molecular process regulating ripening in apple, and to compare to tomato (model species for ripening studies), we utilized both homologous and heterologous (tomato) microarray to profile transcriptome dynamics of genes involved in fruit development and ripening, emphasizing those which are ethylene regulated. The use of both types of microarrays facilitated transcriptome comparison between apple and tomato (for the later using data previously published and available at the TED: tomato expression database) and highlighted genes conserved during ripening of both species, which in turn represent a foundation for further comparative genomic studies. The cross-species analysis had the secondary aim of examining the efficiency of heterologous (specifically tomato) microarray hybridization for candidate gene identification as related to the ripening process. The resulting transcriptomics data revealed coordinated gene expression during fruit ripening of a subset of ripening-related and ethylene responsive genes, further facilitating the analysis of ethylene response during fruit maturation and ripening. Conclusion Our combined strategy based on microarray hybridization enabled transcriptome characterization during normal climacteric apple ripening, as well as definition of ethylene-dependent transcriptome changes. Comparison with tomato fruit maturation and ethylene responsive transcriptome activity facilitated identification of putative conserved orthologous ripening-related genes, which serve as an initial set of candidates for assessing conservation of gene activity across genomes of fruit bearing plant species. PMID:20973957

Screening unlabeled DNA targets with randomly ordered fiber-optic gene arrays.

PubMed

Steemers, F J; Ferguson, J A; Walt, D R

2000-01-01

We have developed a randomly ordered fiber-optic gene array for rapid, parallel detection of unlabeled DNA targets with surface immobilized molecular beacons (MB) that undergo a conformational change accompanied by a fluorescence change in the presence of a complementary DNA target. Microarrays are prepared by randomly distributing MB-functionalized 3-microm diameter microspheres in an array of wells etched in a 500-microm diameter optical imaging fiber. Using several MBs, each designed to recognize a different target, we demonstrate the selective detection of genomic cystic fibrosis related targets. Positional registration and fluorescence response monitoring of the microspheres was performed using an optical encoding scheme and an imaging fluorescence microscope system.

The Microarray Revolution: Perspectives from Educators

ERIC Educational Resources Information Center

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

2004-01-01

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

Electronic hybridization detection in microarray format and DNA genotyping

NASA Astrophysics Data System (ADS)

Blin, Antoine; Cissé, Ismaïl; Bockelmann, Ulrich

2014-02-01

We describe an approach to substituting a fluorescence microarray with a surface made of an arrangement of electrolyte-gated field effect transistors. This was achieved using a dedicated blocking of non-specific interactions and comparing threshold voltage shifts of transistors exhibiting probe molecules of different base sequence. We apply the approach to detection of the 35delG mutation, which is related to non-syndromic deafness and is one of the most frequent mutations in humans. The process involves barcode sequences that are generated by Tas-PCR, a newly developed replication reaction using polymerase blocking. The barcodes are recognized by hybridization to surface attached probes and are directly detected by the semiconductor device.

Electronic hybridization detection in microarray format and DNA genotyping

PubMed Central

Blin, Antoine; Cissé, Ismaïl; Bockelmann, Ulrich

2014-01-01

We describe an approach to substituting a fluorescence microarray with a surface made of an arrangement of electrolyte-gated field effect transistors. This was achieved using a dedicated blocking of non-specific interactions and comparing threshold voltage shifts of transistors exhibiting probe molecules of different base sequence. We apply the approach to detection of the 35delG mutation, which is related to non-syndromic deafness and is one of the most frequent mutations in humans. The process involves barcode sequences that are generated by Tas-PCR, a newly developed replication reaction using polymerase blocking. The barcodes are recognized by hybridization to surface attached probes and are directly detected by the semiconductor device. PMID:24569823

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

PubMed Central

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto

2017-01-01

Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367

Discovery of Possible Gene Relationships through the Application of Self-Organizing Maps to DNA Microarray Databases

PubMed Central

Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres

2014-01-01

DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques –an unsupervised artificial neural network called a Self-Organizing Map (SOM)–which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms. PMID:24699245

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

Recent progress in making protein microarray through BioLP

NASA Astrophysics Data System (ADS)

Yang, Rusong; Wei, Lian; Feng, Ying; Li, Xiujian; Zhou, Quan

2017-02-01

Biological laser printing (BioLP) is a promising biomaterial printing technique. It has the advantage of high resolution, high bioactivity, high printing frequency and small transported liquid amount. In this paper, a set of BioLP device is design and made, and protein microarrays are printed by this device. It's found that both laser intensity and fluid layer thickness have an influence on the microarrays acquired. Besides, two kinds of the fluid layer coating methods are compared, and the results show that blade coating method is better than well-coating method in BioLP. A microarray of 0.76pL protein microarray and a "NUDT" patterned microarray are printed to testify the printing ability of BioLP.

Circular RNA Expression Profile of Pancreatic Ductal Adenocarcinoma Revealed by Microarray.

PubMed

Li, Haimin; Hao, Xiaokun; Wang, Huimin; Liu, Zhengcai; He, Yong; Pu, Meng; Zhang, Hongtao; Yu, Hengchao; Duan, Juanli; Qu, Shibin

2016-01-01

Circular RNAs (circRNAs) are a special novel type of a stable, diverse and conserved noncoding RNA in mammalian cells. Particularly in cancer, circRNAs have been reported to be widely involved in the physiological/pathological process of life. However, it is unclear whether circRNAs are specifically involved in pancreatic ductal adenocarcinoma (PDAC). We investigated the expression profile of circRNAs in six PDAC cancer samples and paired adjacent normal tissues using microarray. A high-throughput circRNA microarray was used to identify dysregulated circular RNAs in six PDAC patients. Bioinformatic analyses were applied to study these differentially expressed circRNAs. Furthermore, quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to confirm these results. We revealed and confirmed that a number of circRNAs were dysregulated, which suggests a potential role in pancreatic cancer. this study demonstrates that clusters of circRNAs are aberrantly expressed in PDAC compared with normal samples and provides new potential targets for the future treatment of PDAC and novel insights into PDAC biology. © 2016 The Author(s) Published by S. Karger AG, Basel.

Noncoding RNAs in human intervertebral disc degeneration: An integrated microarray study.

PubMed

Liu, Xu; Che, Lu; Xie, Yan-Ke; Hu, Qing-Jie; Ma, Chi-Jiao; Pei, Yan-Jun; Wu, Zhi-Gang; Liu, Zhi-Heng; Fan, Li-Ying; Wang, Hai-Qiang

2015-09-01

Accumulating evidence indicates that noncoding RNAs play important roles in a multitude of biological processes. The striking findings of miRNAs (microRNAs) and lncRNAs (long noncoding RNAs) as members of noncoding RNAs open up an exciting era in the studies of gene regulation. More recently, the reports of circRNAs (circular RNAs) add fuel to the noncoding RNAs research. Human intervertebral disc degeneration (IDD) is a main cause of low back pain as a disabling spinal disease. We have addressed the expression profiles if miRNAs, lncRNAs and mRNAs in IDD (Wang et al., J Pathology, 2011 and Wan et al., Arthritis Res Ther, 2014). Furthermore, we thoroughly analysed noncoding RNAs, including miRNAs, lncRNAs and circRNAs in IDD using the very same samples. Here we delineate in detail the contents of the aforementioned microarray analyses. Microarray and sample annotation data were deposited in GEO under accession number GSE67567 as SuperSeries. The integrated analyses of these noncoding RNAs will shed a novel light on coding-noncoding regulatory machinery.

Characterization of regulatory pathways in Xylella fastidiosa: genes and phenotypes controlled by algU.

PubMed

Shi, Xiang Yang; Dumenyo, C Korsi; Hernandez-Martinez, Rufina; Azad, Hamid; Cooksey, Donald A

2007-11-01

Many virulence genes in plant bacterial pathogens are coordinately regulated by "global" regulatory genes. Conducting DNA microarray analysis of bacterial mutants of such genes, compared with the wild type, can help to refine the list of genes that may contribute to virulence in bacterial pathogens. The regulatory gene algU, with roles in stress response and regulation of the biosynthesis of the exopolysaccharide alginate in Pseudomonas aeruginosa and many other bacteria, has been extensively studied. The role of algU in Xylella fastidiosa, the cause of Pierce's disease of grapevines, was analyzed by mutation and whole-genome microarray analysis to define its involvement in aggregation, biofilm formation, and virulence. In this study, an algU::nptII mutant had reduced cell-cell aggregation, attachment, and biofilm formation and lower virulence in grapevines. Microarray analysis showed that 42 genes had significantly lower expression in the algU::nptII mutant than in the wild type. Among these are several genes that could contribute to cell aggregation and biofilm formation, as well as other physiological processes such as virulence, competition, and survival.

Identification of rat lung-specific microRNAs by micoRNA microarray: valuable discoveries for the facilitation of lung research.

PubMed

Wang, Yang; Weng, Tingting; Gou, Deming; Chen, Zhongming; Chintagari, Narendranath Reddy; Liu, Lin

2007-01-24

An important mechanism for gene regulation utilizes small non-coding RNAs called microRNAs (miRNAs). These small RNAs play important roles in tissue development, cell differentiation and proliferation, lipid and fat metabolism, stem cells, exocytosis, diseases and cancers. To date, relatively little is known about functions of miRNAs in the lung except lung cancer. In this study, we utilized a rat miRNA microarray containing 216 miRNA probes, printed in-house, to detect the expression of miRNAs in the rat lung compared to the rat heart, brain, liver, kidney and spleen. Statistical analysis using Significant Analysis of Microarray (SAM) and Tukey Honestly Significant Difference (HSD) revealed 2 miRNAs (miR-195 and miR-200c) expressed specifically in the lung and 9 miRNAs co-expressed in the lung and another organ. 12 selected miRNAs were verified by Northern blot analysis. The identified lung-specific miRNAs from this work will facilitate functional studies of miRNAs during normal physiological and pathophysiological processes of the lung.

Eukaryotic cell encystation and cancer cell dormancy: is a greater devil veiled in the details of a lesser evil?

PubMed

Baig, Abdul Mannan; Khan, Naveed Ahmed; Abbas, Farhat

2015-03-01

Cancer cell dormancy is the main cause of cancer recurrence and failure of therapy as dormant cells evade not only the anticancer drugs but also the host immune system. These dormant cells veil themselves from detection by imaging and/or using biomarkers, which imposes an additional problem in targeting such cells. A similar form of hibernation process known as encystation is studied in detail for pathogenic unicellular eukaryotic microorganisms. By examination using microarray gene expression profiles, immunocytochemistry tools, and siRNAs during the process of encystation, understanding the covert features of cancer cell dormancy as proposed could be possible. This knowledge can be extended to dormant cancer cells to uncover the mechanisms that underlie this ghost, yet dangerous state of human cancers. We propose a strategy to induce dormancy and exit this state by application of knowledge gained from the encystation induction and retrieval processes in pathogenic eukaryotic microorganisms. Given that early detection and characterization of dormant malignant tumor cells is important as a general strategy to monitor and prevent the development of overt metastatic disease, this homology may enable the design of therapies that could either awake the dormant cell from dormancy to make it available for therapies or prolong such a phase to make cancer appear as a chronic disease.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

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

PubMed Central

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

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.

Mode of action from dose-response microarray data: case study using 10 environmental chemicals

EPA Science Inventory

Ligand-activated nuclear receptors regulate many biological processes through complex interactions with biological macromolecules. Certain xenobiotics alter nuclear receptor signaling through direct or indirect interactions. Defining the mode of action of such xenobiotics is di...

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma.

PubMed

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong; Li, Ning

2016-12-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC ( n = 65) and healthy control subjects ( n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC.

Development and application of a fluorescence protein microarray for detecting serum alpha-fetoprotein in patients with hepatocellular carcinoma

PubMed Central

Zhang, Aiying; Yin, Chengzeng; Wang, Zhenshun; Zhang, Yonghong; Zhao, Yuanshun; Li, Ang; Sun, Huanqin; Lin, Dongdong

2016-01-01

Objective To develop a simple, effective, time-saving and low-cost fluorescence protein microarray method for detecting serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC). Method Non-contact piezoelectric print techniques were applied to fluorescence protein microarray to reduce the cost of prey antibody. Serum samples from patients with HCC and healthy control subjects were collected and evaluated for the presence of AFP using a novel fluorescence protein microarray. To validate the fluorescence protein microarray, serum samples were tested for AFP using an enzyme-linked immunosorbent assay (ELISA). Results A total of 110 serum samples from patients with HCC (n = 65) and healthy control subjects (n = 45) were analysed. When the AFP cut-off value was set at 20 ng/ml, the fluorescence protein microarray had a sensitivity of 91.67% and a specificity of 93.24% for detecting serum AFP. Serum AFP quantified via fluorescence protein microarray had a similar diagnostic performance compared with ELISA in distinguishing patients with HCC from healthy control subjects (area under receiver operating characteristic curve: 0.906 for fluorescence protein microarray; 0.880 for ELISA). Conclusion A fluorescence protein microarray method was developed for detecting serum AFP in patients with HCC. PMID:27885040

Genotyping microarray: Mutation screening in Spanish families with autosomal dominant retinitis pigmentosa

PubMed Central

García-Hoyos, María; Cortón, Marta; Ávila-Fernández, Almudena; Riveiro-Álvarez, Rosa; Giménez, Ascensión; Hernan, Inma; Carballo, Miguel; Ayuso, Carmen

2012-01-01

Purpose Presently, 22 genes have been described in association with autosomal dominant retinitis pigmentosa (adRP); however, they explain only 50% of all cases, making genetic diagnosis of this disease difficult and costly. The aim of this study was to evaluate a specific genotyping microarray for its application to the molecular diagnosis of adRP in Spanish patients. Methods We analyzed 139 unrelated Spanish families with adRP. Samples were studied by using a genotyping microarray (adRP). All mutations found were further confirmed with automatic sequencing. Rhodopsin (RHO) sequencing was performed in all negative samples for the genotyping microarray. Results The adRP genotyping microarray detected the mutation associated with the disease in 20 of the 139 families with adRP. As in other populations, RHO was found to be the most frequently mutated gene in these families (7.9% of the microarray genotyped families). The rate of false positives (microarray results not confirmed with sequencing) and false negatives (mutations in RHO detected with sequencing but not with the genotyping microarray) were established, and high levels of analytical sensitivity (95%) and specificity (100%) were found. Diagnostic accuracy was 15.1%. Conclusions The adRP genotyping microarray is a quick, cost-efficient first step in the molecular diagnosis of Spanish patients with adRP. PMID:22736939

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies.

PubMed

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-09-20

High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option.GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike.

MicroArray Facility: a laboratory information management system with extended support for Nylon based technologies

PubMed Central

Honoré, Paul; Granjeaud, Samuel; Tagett, Rebecca; Deraco, Stéphane; Beaudoing, Emmanuel; Rougemont, Jacques; Debono, Stéphane; Hingamp, Pascal

2006-01-01

Background High throughput gene expression profiling (GEP) is becoming a routine technique in life science laboratories. With experimental designs that repeatedly span thousands of genes and hundreds of samples, relying on a dedicated database infrastructure is no longer an option. GEP technology is a fast moving target, with new approaches constantly broadening the field diversity. This technology heterogeneity, compounded by the informatics complexity of GEP databases, means that software developments have so far focused on mainstream techniques, leaving less typical yet established techniques such as Nylon microarrays at best partially supported. Results MAF (MicroArray Facility) is the laboratory database system we have developed for managing the design, production and hybridization of spotted microarrays. Although it can support the widely used glass microarrays and oligo-chips, MAF was designed with the specific idiosyncrasies of Nylon based microarrays in mind. Notably single channel radioactive probes, microarray stripping and reuse, vector control hybridizations and spike-in controls are all natively supported by the software suite. MicroArray Facility is MIAME supportive and dynamically provides feedback on missing annotations to help users estimate effective MIAME compliance. Genomic data such as clone identifiers and gene symbols are also directly annotated by MAF software using standard public resources. The MAGE-ML data format is implemented for full data export. Journalized database operations (audit tracking), data anonymization, material traceability and user/project level confidentiality policies are also managed by MAF. Conclusion MicroArray Facility is a complete data management system for microarray producers and end-users. Particular care has been devoted to adequately model Nylon based microarrays. The MAF system, developed and implemented in both private and academic environments, has proved a robust solution for shared facilities and industry service providers alike. PMID:16987406

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

STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

PubMed Central

Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

2009-01-01

Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039

An introduction to MATLAB.

PubMed

Sobie, Eric A

2011-09-13

This two-part lecture introduces students to the scientific computing language MATLAB. Prior computer programming experience is not required. The lectures present basic concepts of computer programming logic that tend to cause difficulties for beginners in addition to concepts that relate specifically to the MATLAB language syntax. The lectures begin with a discussion of vectors, matrices, and arrays. Because many types of biological data, such as fluorescence images and DNA microarrays, are stored as two-dimensional objects, processing these data is a form of array manipulation, and MATLAB is especially adept at handling such array objects. The students are introduced to basic commands in MATLAB, as well as built-in functions that provide useful shortcuts. The second lecture focuses on the differences between MATLAB scripts and MATLAB functions and describes when one method of programming organization might be preferable to the other. The principles are illustrated through the analysis of experimental data, specifically measurements of intracellular calcium concentration in live cells obtained using confocal microscopy.

An Introduction to MATLAB

PubMed Central

Sobie, Eric A.

2014-01-01

This two-part lecture introduces students to the scientific computing language MATLAB. Prior computer programming experience is not required. The lectures present basic concepts of computer programming logic that tend to cause difficulties for beginners in addition to concepts that relate specifically to the MATLAB language syntax. The lectures begin with a discussion of vectors, matrices, and arrays. Because many types of biological data, such as fluorescence images and DNA microarrays, are stored as two-dimensional objects, processing these data is a form of array manipulation, and MATLAB is especially adept at handling such array objects. The students are introduced to basic commands in MATLAB, as well as built-in functions that provide useful shortcuts. The second lecture focuses on the differences between MATLAB scripts and MATLAB functions and describes when one method of programming organization might be preferable to the other. The principles are illustrated through the analysis of experimental data, specifically measurements of intracellular calcium concentration in live cells obtained using confocal microscopy. PMID:21934110

The Effect of Substrate Topography on Direct Reprogramming of Fibroblasts to Induced Neurons

PubMed Central

Kulangara, Karina; Adler, Andrew F.; Wang, Hong; Chellappan, Malathi; Hammett, Ellen; Yasuda, Ryohei; Leong, Kam W.

2014-01-01

Cellular reprogramming holds tremendous potential for cell therapy and regenerative medicine. Recently, fibroblasts have been directly converted into induced neurons (iNs) by overexpression of the neuronal transcription factors Ascl1, Brn2 and Myt1L. Hypothesizing that cell-topography interactions could influence the fibroblast-to-neuron reprogramming process, we investigated the effects of various topographies on iNs produced by direct reprogramming. Final iN purity and conversion efficiency were increased on micrograting substrates. Neurite branching was increased on microposts and decreased on microgratings, with a simplified dendritic arbor characterized by the reduction of MAP2+ neurites. Neurite outgrowth increased significantly on various topographies. DNA microarray analysis detected 20 differentially expressed genes in iNs reprogrammed on smooth versus microgratings, and quantitative PCR (qPCR) confirmed the upregulation of Vip and downregulation of Thy1 and Bmp5 on microgratings. Electrophysiology and calcium imaging verified the functionality of these iNs. This study demonstrates the potential of applying topographical cues to optimize cellular reprogramming. PMID:24709523

Plug-and-actuate on demand: multimodal individual addressability of microarray plates using modular hybrid acoustic wave technology.

PubMed

Rezk, Amgad R; Ramesan, Shwathy; Yeo, Leslie Y

2018-01-30

The microarray titre plate remains a fundamental workhorse in genomic, proteomic and cellomic analyses that underpin the drug discovery process. Nevertheless, liquid handling technologies for sample dispensing, processing and transfer have not progressed significantly beyond conventional robotic micropipetting techniques, which are not only at their fundamental sample size limit, but are also prone to mechanical failure and contamination. This is because alternative technologies to date suffer from a number of constraints, mainly their limitation to carry out only a single liquid operation such as dispensing or mixing at a given time, and their inability to address individual wells, particularly at high throughput. Here, we demonstrate the possibility for true sequential or simultaneous single- and multi-well addressability in a 96-well plate using a reconfigurable modular platform from which MHz-order hybrid surface and bulk acoustic waves can be coupled to drive a variety of microfluidic modes including mixing, sample preconcentration and droplet jetting/ejection in individual or multiple wells on demand, thus constituting a highly versatile yet simple setup capable of improving the functionality of existing laboratory protocols and processes.

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

PubMed Central

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-01-01

Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1α and EF-2. Conclusion Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination. PMID:19114004

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni.

PubMed

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-12-29

Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1alpha and EF-2. Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination.

Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays

PubMed Central

Lawson, Jonathan; Robinson-Vyas, Rupesh J; McQuillan, Janette P; Paterson, Andy; Christie, Sarah; Kidza-Griffiths, Matthew; McDuffus, Leigh-Anne; Moutasim, Karwan A; Shaw, Emily C; Kiltie, Anne E; Howat, William J; Hanby, Andrew M; Thomas, Gareth J; Smittenaar, Peter

2017-01-01

Background: Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing – enlisting help from the public – is a sufficiently accurate method to score such samples. Methods: We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers – bladder/ki67, lung/EGFR, and oesophageal/CD8 – to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples. Results: We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively). Conclusions: These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains. PMID:27959886

Cell-surface marker discovery for lung cancer

PubMed Central

Cohen, Allison S.; Khalil, Farah K.; Welsh, Eric A.; Schabath, Matthew B.; Enkemann, Steven A.; Davis, Andrea; Zhou, Jun-Min; Boulware, David C.; Kim, Jongphil; Haura, Eric B.; Morse, David L.

2017-01-01

Lung cancer is the leading cause of cancer deaths in the United States. Novel lung cancer targeted therapeutic and molecular imaging agents are needed to improve outcomes and enable personalized care. Since these agents typically cannot cross the plasma membrane while carrying cytotoxic payload or imaging contrast, discovery of cell-surface targets is a necessary initial step. Herein, we report the discovery and characterization of lung cancer cell-surface markers for use in development of targeted agents. To identify putative cell-surface markers, existing microarray gene expression data from patient specimens were analyzed to select markers with differential expression in lung cancer compared to normal lung. Greater than 200 putative cell-surface markers were identified as being overexpressed in lung cancers. Ten cell-surface markers (CA9, CA12, CXorf61, DSG3, FAT2, GPR87, KISS1R, LYPD3, SLC7A11 and TMPRSS4) were selected based on differential mRNA expression in lung tumors vs. non-neoplastic lung samples and other normal tissues, and other considerations involving known biology and targeting moieties. Protein expression was confirmed by immunohistochemistry (IHC) staining and scoring of patient tumor and normal tissue samples. As further validation, marker expression was determined in lung cancer cell lines using microarray data and Kaplan–Meier survival analyses were performed for each of the markers using patient clinical data. High expression for six of the markers (CA9, CA12, CXorf61, GPR87, LYPD3, and SLC7A11) was significantly associated with worse survival. These markers should be useful for the development of novel targeted imaging probes or therapeutics for use in personalized care of lung cancer patients. PMID:29371917

De novo transcriptome sequencing and customized abscission zone-specific microarray as a new molecular tool for analysis of tomato organ abscission

USDA-ARS?s Scientific Manuscript database

Abscission, which is the process of organ separation, is a highly regulated process occurring as a final stage of organ development. In the tomato (Solanum lycopersicum) system, flower and leaf abscission was induced by flower removal or leaf deblading, leading to auxin depletion which results in in...

A Next-generation Tissue Microarray (ngTMA) Protocol for Biomarker Studies

PubMed Central

Zlobec, Inti; Suter, Guido; Perren, Aurel; Lugli, Alessandro

2014-01-01

Biomarker research relies on tissue microarrays (TMA). TMAs are produced by repeated transfer of small tissue cores from a ‘donor’ block into a ‘recipient’ block and then used for a variety of biomarker applications. The construction of conventional TMAs is labor intensive, imprecise, and time-consuming. Here, a protocol using next-generation Tissue Microarrays (ngTMA) is outlined. ngTMA is based on TMA planning and design, digital pathology, and automated tissue microarraying. The protocol is illustrated using an example of 134 metastatic colorectal cancer patients. Histological, statistical and logistical aspects are considered, such as the tissue type, specific histological regions, and cell types for inclusion in the TMA, the number of tissue spots, sample size, statistical analysis, and number of TMA copies. Histological slides for each patient are scanned and uploaded onto a web-based digital platform. There, they are viewed and annotated (marked) using a 0.6-2.0 mm diameter tool, multiple times using various colors to distinguish tissue areas. Donor blocks and 12 ‘recipient’ blocks are loaded into the instrument. Digital slides are retrieved and matched to donor block images. Repeated arraying of annotated regions is automatically performed resulting in an ngTMA. In this example, six ngTMAs are planned containing six different tissue types/histological zones. Two copies of the ngTMAs are desired. Three to four slides for each patient are scanned; 3 scan runs are necessary and performed overnight. All slides are annotated; different colors are used to represent the different tissues/zones, namely tumor center, invasion front, tumor/stroma, lymph node metastases, liver metastases, and normal tissue. 17 annotations/case are made; time for annotation is 2-3 min/case. 12 ngTMAs are produced containing 4,556 spots. Arraying time is 15-20 hr. Due to its precision, flexibility and speed, ngTMA is a powerful tool to further improve the quality of TMAs used in clinical and translational research. PMID:25285857

Multiple epitope presentation and surface density control enabled by chemoselective immobilization lead to enhanced performance in IgE-binding fingerprinting on peptide microarrays.

PubMed

Gori, Alessandro; Cretich, Marina; Vanna, Renzo; Sola, Laura; Gagni, Paola; Bruni, Giulia; Liprino, Marta; Gramatica, Furio; Burastero, Samuele; Chiari, Marcella

2017-08-29

Multiple ligand presentation is a powerful strategy to enhance the affinity of a probe for its corresponding target. A promising application of this concept lies in the analytical field, where surface immobilized probes interact with their corresponding targets in the context of complex biological samples. Here we investigate the effect of multiple epitope presentation (MEP) in the challenging context of IgE-detection in serum samples using peptide microarrays, and evaluate the influence of probes surface density on the assay results. Using the milk allergen alpha-lactalbumin as a model, we have synthesized three immunoreactive epitope sequences in a linear, branched and tandem form and exploited a chemoselective click strategy (CuAAC) for their immobilization on the surface of two biosensors, a microarray and an SPR chip both modified with the same clickable polymeric coating. We first demonstrated that a fine tuning of the surface peptide density plays a crucial role to fully exploit the potential of oriented and multiple peptide display. We then compared the three multiple epitope presentations in a microarray assay using sera samples from milk allergic patients, confirming that a multiple presentation, in particular that of the tandem construct, allows for a more efficient characterization of IgE-binding fingerprints at a statistically significant level. To gain insights on the binding parameters that characterize antibody/epitopes affinity, we selected the most reactive epitope of the series (LAC1) and performed a Surface Plasmon Resonance Imaging (SPRi) analysis comparing different epitope architectures (linear versus branched versus tandem). We demonstrated that the tandem peptide provides an approximately twofold increased binding capacity with respect to the linear and branched peptides, that could be attributed to a lower rate of dissociation (K d ). Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements.

PubMed

Devonshire, Alison S; Elaswarapu, Ramnath; Foy, Carole A

2010-11-24

Gene expression profiling is an important approach for detecting diagnostic and prognostic biomarkers, and predicting drug safety. The development of a wide range of technologies and platforms for measuring mRNA expression makes the evaluation and standardization of transcriptomic data problematic due to differences in protocols, data processing and analysis methods. Thus, universal RNA standards, such as those developed by the External RNA Controls Consortium (ERCC), are proposed to aid validation of research findings from diverse platforms such as microarrays and RT-qPCR, and play a role in quality control (QC) processes as transcriptomic profiling becomes more commonplace in the clinical setting. Panels of ERCC RNA standards were constructed in order to test the utility of these reference materials (RMs) for performance characterization of two selected gene expression platforms, and for discrimination of biomarker profiles between groups. The linear range, limits of detection and reproducibility of microarray and RT-qPCR measurements were evaluated using panels of RNA standards. Transcripts of low abundance (≤ 10 copies/ng total RNA) showed more than double the technical variability compared to higher copy number transcripts on both platforms. Microarray profiling of two simulated 'normal' and 'disease' panels, each consisting of eight different RNA standards, yielded robust discrimination between the panels and between standards with varying fold change ratios, showing no systematic effects due to different labelling and hybridization runs. Also, comparison of microarray and RT-qPCR data for fold changes showed agreement for the two platforms. ERCC RNA standards provide a generic means of evaluating different aspects of platform performance, and can provide information on the technical variation associated with quantification of biomarkers expressed at different levels of physiological abundance. Distinct panels of standards serve as an ideal quality control tool kit for determining the accuracy of fold change cut-off threshold and the impact of experimentally-derived noise on the discrimination of normal and disease profiles.

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

PubMed Central

2013-01-01

Background Drop drying is a key factor in a wide range of technical applications, including spotted microarrays. The applied nL liquid volume provides specific reaction conditions for the immobilization of probe molecules to a chemically modified surface. Results We investigated the influence of nL and μL liquid drop volumes on the process of probe immobilization and compare the results obtained to the situation in liquid solution. In our data, we observe a strong relationship between drop drying effects on immobilization and surface chemistry. In this work, we present results on the immobilization of dye labeled 20mer oligonucleotides with and without an activating 5′-aminoheptyl linker onto a 2D epoxysilane and a 3D NHS activated hydrogel surface. Conclusions Our experiments identified two basic processes determining immobilization. First, the rate of drop drying that depends on the drop volume and the ambient relative humidity. Oligonucleotides in a dried spot react unspecifically with the surface and long reaction times are needed. 3D hydrogel surfaces allow for immobilization in a liquid environment under diffusive conditions. Here, oligonucleotide immobilization is much faster and a specific reaction with the reactive linker group is observed. Second, the effect of increasing probe concentration as a result of drop drying. On a 3D hydrogel, the increasing concentration of probe molecules in nL spotting volumes accelerates immobilization dramatically. In case of μL volumes, immobilization depends on whether the drop is allowed to dry completely. At non-drying conditions, very limited immobilization is observed due to the low oligonucleotide concentration used in microarray spotting solutions. The results of our study provide a general guideline for microarray assay development. They allow for the initial definition and further optimization of reaction conditions for the immobilization of oligonucleotides and other probe molecule classes to different surfaces in dependence of the applied spotting and reaction volume. PMID:23758982

Quantification of protein interaction kinetics in a micro droplet

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, L. L.; College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044; Wang, S. P., E-mail: shaopeng.wang@asu.edu, E-mail: njtao@asu.edu

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the averagemore » SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.« less

Quantification of protein interaction kinetics in a micro droplet

NASA Astrophysics Data System (ADS)

Yin, L. L.; Wang, S. P.; Shan, X. N.; Zhang, S. T.; Tao, N. J.

2015-11-01

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.

Systems microscopy: an emerging strategy for the life sciences.

PubMed

Lock, John G; Strömblad, Staffan

2010-05-01

Dynamic cellular processes occurring in time and space are fundamental to all physiology and disease. To understand complex and dynamic cellular processes therefore demands the capacity to record and integrate quantitative multiparametric data from the four spatiotemporal dimensions within which living cells self-organize, and to subsequently use these data for the mathematical modeling of cellular systems. To this end, a raft of complementary developments in automated fluorescence microscopy, cell microarray platforms, quantitative image analysis and data mining, combined with multivariate statistics and computational modeling, now coalesce to produce a new research strategy, "systems microscopy", which facilitates systems biology analyses of living cells. Systems microscopy provides the crucial capacities to simultaneously extract and interrogate multiparametric quantitative data at resolution levels ranging from the molecular to the cellular, thereby elucidating a more comprehensive and richly integrated understanding of complex and dynamic cellular systems. The unique capacities of systems microscopy suggest that it will become a vital cornerstone of systems biology, and here we describe the current status and future prospects of this emerging field, as well as outlining some of the key challenges that remain to be overcome. Copyright 2010 Elsevier Inc. All rights reserved.

Protein-diazonium adduct direct electrografting onto SPRi-biochip.

PubMed

Corgier, Benjamin P; Bellon, Sophie; Anger-Leroy, Marielle; Blum, Loïc J; Marquette, Christophe A

2009-08-18

A direct protein immobilization method for surface plasmon resonance imaging (SPRi) gold chip arraying is exposed. The biomolecule electroaddressing strategy, previously demonstrated by our team on carbon surfaces, is here valuably involved and adapted to create a straightforward and efficient protein immobilization process onto SPRi-biochips. The proteins, modified with an aryl-diazonium adduct, are addressed to the SPRi chip surface through the electroreduction of the aryl-diazonium. The biomolecule deposition was followed through SPRi live measurements during the electrografting process. A specially designed setup enabled us to directly observe the mass increasing at the sensor surface while the proteins were electrografted. A pin electrospotting method, allowing the achievement of distinct sensing layers on gold SPRi-biochips, was used to generate microarray biochips. The integrity of the immobilized proteins and the specificity of the detection, based on antigen/antibody interactions, were demonstrated for the detection of specific antibodies and ovalbumin. The SPRi detection limit of ovalbumin using the electroaddressing of anti-ovalbumin IgG was compared with two other immobilization procedures, cystamine-glutaraldehyde self-assembled monolayer and pyrrole, and was found to be a decade lower than these ones (100 ng/mL, i.e., 2 nM).

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Investigating the biochemical progression of liver disease through fibrosis, cirrhosis, dysplasia, and hepatocellular carcinoma using Fourier transform infrared spectroscopic imaging

NASA Astrophysics Data System (ADS)

Sreedhar, Hari; Pant, Mamta; Ronquillo, Nemencio R.; Davidson, Bennett; Nguyen, Peter; Chennuri, Rohini; Choi, Jacqueline; Herrera, Joaquin A.; Hinojosa, Ana C.; Jin, Ming; Kajdacsy-Balla, Andre; Guzman, Grace; Walsh, Michael J.

2014-03-01

Hepatocellular carcinoma (HCC) is the most common form of primary hepatic carcinoma. HCC ranks the fourth most prevalent malignant tumor and the third leading cause of cancer related death in the world. Hepatocellular carcinoma develops in the context of chronic liver disease and its evolution is characterized by progression through intermediate stages to advanced disease and possibly even death. The primary sequence of hepatocarcinogenesis includes the development of cirrhosis, followed by dysplasia, and hepatocellular carcinoma.1 We addressed the utility of Fourier Transform Infrared (FT-IR) spectroscopic imaging, both as a diagnostic tool of the different stages of the disease and to gain insight into the biochemical process associated with disease progression. Tissue microarrays were obtained from the University of Illinois at Chicago tissue bank consisting of liver explants from 12 transplant patients. Tissue core biopsies were obtained from each explant targeting regions of normal, liver cell dysplasia including large cell change and small cell change, and hepatocellular carcinoma. We obtained FT-IR images of these tissues using a modified FT-IR system with high definition capabilities. Firstly, a supervised spectral classifier was built to discriminate between normal and cancerous hepatocytes. Secondly, an expanded classifier was built to discriminate small cell and large cell changes in liver disease. With the emerging advances in FT-IR instrumentation and computation there is a strong drive to develop this technology as a powerful adjunct to current histopathology approaches to improve disease diagnosis and prognosis.

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

PubMed

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

2017-01-01

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

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

PubMed

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

2014-08-04

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

Microarray analysis of differentially expressed genes engaged in fruit development between Prunus mume and Prunus armeniaca.

PubMed

Li, Xiaoying; Korir, Nicholas Kibet; Liu, Lili; Shangguan, Lingfei; Wang, Yuzhu; Han, Jian; Chen, Ming; Fang, Jinggui

2012-11-15

Microarray analysis is a technique that can be employed to provide expression profiles of single genes and new insights to elucidate the biological mechanisms responsible for fruit development. To evaluate expression of genes mostly engaged in fruit development between Prunus mume and Prunus armeniaca, we first identified differentially expressed transcripts along the entire fruit life cycle by using microarrays spotted with 10,641 ESTs collected from P. mume and other Prunus EST sequences. A total of 1418 ESTs were selected after quality control of microarray spots and analysis for differential gene expression patterns during fruit development of P. mume and P. Armeniaca. From these, 707 up-regulated and 711 down-regulated genes showing more than two-fold differences in expression level were annotated by GO based on biological processes, molecular functions and cellular components. These differentially expressed genes were found to be involved in several important pathways of carbohydrate, galactose, and starch and sucrose metabolism as well as in biosynthesis of other secondary metabolites via KEGG. This could provide detailed information on the fruit quality differences during development and ripening of these two species. With the results obtained, we provide a practical database for comprehensive understanding of molecular events during fruit development and also lay a theoretical foundation for the cloning of genes regulating in a series of important rate-limiting enzymes involved in vital metabolic pathways during fruit development. Copyright © 2012 Elsevier GmbH. All rights reserved.

Microarray expression profiling in adhesion and normal peritoneal tissues.

PubMed

Ambler, Dana R; Golden, Alicia M; Gell, Jennifer S; Saed, Ghassan M; Carey, David J; Diamond, Michael P

2012-05-01

To identify molecular markers associated with adhesion and normal peritoneal tissue using microarray expression profiling. Comparative study. University hospital. Five premenopausal women. Adhesion and normal peritoneal tissue samples were obtained from premenopausal women. Ribonucleic acid was extracted using standard protocols and processed for hybridization to Affymetrix Whole Transcript Human Gene Expression Chips. Microarray data were obtained from five different patients, each with adhesion tissue and normal peritoneal samples. Real-time polymerase chain reaction was performed for confirmation using standard protocols. Gene expression in postoperative adhesion and normal peritoneal tissues. A total of 1,263 genes were differentially expressed between adhesion and normal tissues. One hundred seventy-three genes were found to be up-regulated and 56 genes were down-regulated in the adhesion tissues compared with normal peritoneal tissues. The genes were sorted into functional categories according to Gene Ontology annotations. Twenty-six up-regulated genes and 11 down-regulated genes were identified with functions potentially relevant to the pathophysiology of postoperative adhesions. We evaluated and confirmed expression of 12 of these specific genes via polymerase chain reaction. The pathogenesis, natural history, and optimal treatment of postoperative adhesive disease remains unanswered. Microarray analysis of adhesions identified specific genes with increased and decreased expression when compared with normal peritoneum. Knowledge of these genes and ontologic pathways with altered expression provide targets for new therapies to treat patients who have or are at risk for postoperative adhesions. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

2011-09-22

Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

geneCommittee: a web-based tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification.

PubMed

Reboiro-Jato, Miguel; Arrais, Joel P; Oliveira, José Luis; Fdez-Riverola, Florentino

2014-01-30

The diagnosis and prognosis of several diseases can be shortened through the use of different large-scale genome experiments. In this context, microarrays can generate expression data for a huge set of genes. However, to obtain solid statistical evidence from the resulting data, it is necessary to train and to validate many classification techniques in order to find the best discriminative method. This is a time-consuming process that normally depends on intricate statistical tools. geneCommittee is a web-based interactive tool for routinely evaluating the discriminative classification power of custom hypothesis in the form of biologically relevant gene sets. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. Provided with a straightforward and intuitive interface, geneCommittee is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research. geneCommittee allows the enrichment of microarrays raw data with gene functional annotations, producing integrated datasets that simplify the construction of better discriminative hypothesis, and allows the creation of a set of complementary classifiers. The trained committees can then be used for clinical research and diagnosis. Full documentation including common use cases and guided analysis workflows is freely available at http://sing.ei.uvigo.es/GC/.

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Plastic Polymers for Efficient DNA Microarray Hybridization: Application to Microbiological Diagnostics▿

PubMed Central

Zhao, Zhengshan; Peytavi, Régis; Diaz-Quijada, Gerardo A.; Picard, Francois J.; Huletsky, Ann; Leblanc, Éric; Frenette, Johanne; Boivin, Guy; Veres, Teodor; Dumoulin, Michel M.; Bergeron, Michel G.

2008-01-01

Fabrication of microarray devices using traditional glass slides is not easily adaptable to integration into microfluidic systems. There is thus a need for the development of polymeric materials showing a high hybridization signal-to-background ratio, enabling sensitive detection of microbial pathogens. We have developed such plastic supports suitable for highly sensitive DNA microarray hybridizations. The proof of concept of this microarray technology was done through the detection of four human respiratory viruses that were amplified and labeled with a fluorescent dye via a sensitive reverse transcriptase PCR (RT-PCR) assay. The performance of the microarray hybridization with plastic supports made of PMMA [poly(methylmethacrylate)]-VSUVT or Zeonor 1060R was compared to that with high-quality glass slide microarrays by using both passive and microfluidic hybridization systems. Specific hybridization signal-to-background ratios comparable to that obtained with high-quality commercial glass slides were achieved with both polymeric substrates. Microarray hybridizations demonstrated an analytical sensitivity equivalent to approximately 100 viral genome copies per RT-PCR, which is at least 100-fold higher than the sensitivities of previously reported DNA hybridizations on plastic supports. Testing of these plastic polymers using a microfluidic microarray hybridization platform also showed results that were comparable to those with glass supports. In conclusion, PMMA-VSUVT and Zeonor 1060R are both suitable for highly sensitive microarray hybridizations. PMID:18784318

A Web-Based Multi-Database System Supporting Distributed Collaborative Management and Sharing of Microarray Experiment Information

PubMed Central

Burgarella, Sarah; Cattaneo, Dario; Masseroli, Marco

2006-01-01

We developed MicroGen, a multi-database Web based system for managing all the information characterizing spotted microarray experiments. It supports information gathering and storing according to the Minimum Information About Microarray Experiments (MIAME) standard. It also allows easy sharing of information and data among all multidisciplinary actors involved in spotted microarray experiments. PMID:17238488

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

DTIC Science & Technology

2006-04-27

polysaccharide microarray platform was prepared by immobilizing Burkholderia pseudomallei and Burkholderia mallei polysaccharides . This... polysaccharide array was tested with success for detecting B. pseudomallei and B. mallei serum (human and animal) antibodies. The advantages of this microarray... Polysaccharide microarrays; Burkholderia pseudomallei; Burkholderia mallei; Glanders; Melioidosis1. Introduction There has been a great deal of emphasis on the

Microarray-integrated optoelectrofluidic immunoassay system

PubMed Central

Han, Dongsik

2016-01-01

A microarray-based analytical platform has been utilized as a powerful tool in biological assay fields. However, an analyte depletion problem due to the slow mass transport based on molecular diffusion causes low reaction efficiency, resulting in a limitation for practical applications. This paper presents a novel method to improve the efficiency of microarray-based immunoassay via an optically induced electrokinetic phenomenon by integrating an optoelectrofluidic device with a conventional glass slide-based microarray format. A sample droplet was loaded between the microarray slide and the optoelectrofluidic device on which a photoconductive layer was deposited. Under the application of an AC voltage, optically induced AC electroosmotic flows caused by a microarray-patterned light actively enhanced the mass transport of target molecules at the multiple assay spots of the microarray simultaneously, which reduced tedious reaction time from more than 30 min to 10 min. Based on this enhancing effect, a heterogeneous immunoassay with a tiny volume of sample (5 μl) was successfully performed in the microarray-integrated optoelectrofluidic system using immunoglobulin G (IgG) and anti-IgG, resulting in improved efficiency compared to the static environment. Furthermore, the application of multiplex assays was also demonstrated by multiple protein detection. PMID:27190571

Microarray-integrated optoelectrofluidic immunoassay system.

PubMed

Han, Dongsik; Park, Je-Kyun

2016-05-01

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

Advances in cell-free protein array methods.

PubMed

Yu, Xiaobo; Petritis, Brianne; Duan, Hu; Xu, Danke; LaBaer, Joshua

2018-01-01

Cell-free protein microarrays represent a special form of protein microarray which display proteins made fresh at the time of the experiment, avoiding storage and denaturation. They have been used increasingly in basic and translational research over the past decade to study protein-protein interactions, the pathogen-host relationship, post-translational modifications, and antibody biomarkers of different human diseases. Their role in the first blood-based diagnostic test for early stage breast cancer highlights their value in managing human health. Cell-free protein microarrays will continue to evolve to become widespread tools for research and clinical management. Areas covered: We review the advantages and disadvantages of different cell-free protein arrays, with an emphasis on the methods that have been studied in the last five years. We also discuss the applications of each microarray method. Expert commentary: Given the growing roles and impact of cell-free protein microarrays in research and medicine, we discuss: 1) the current technical and practical limitations of cell-free protein microarrays; 2) the biomarker discovery and verification pipeline using protein microarrays; and 3) how cell-free protein microarrays will advance over the next five years, both in their technology and applications.

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

PubMed

Baek, Jangsun; Son, Young Sook; McLachlan, Geoffrey J

2007-02-15

We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data; (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods; (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions; (4) the use of the bivariate t distribution for the foreground intensity provides a model that is less sensitive to extreme observations; (5) as a consequence of the aforementioned properties, it allows segmentation to be undertaken for a wide range of spot shapes, including doughnut, sickle shape and artifacts. We apply our method for gridding, segmentation and estimation to cDNA microarray real images and artificial data. Our method provides better segmentation results in spot shapes as well as intensity estimation than Spot and spotSegmentation R language softwares. It detected blank spots as well as bright artifact for the real data, and estimated spot intensities with high-accuracy for the synthetic data. The algorithms were implemented in Matlab. The Matlab codes implementing both the gridding and segmentation/estimation are available upon request. Supplementary material is available at Bioinformatics online.

Carbohydrate Microarray Technology Applied to High-Throughput Mapping of Plant Cell Wall Glycans Using Comprehensive Microarray Polymer Profiling (CoMPP).

PubMed

Kračun, Stjepan Krešimir; Fangel, Jonatan Ulrik; Rydahl, Maja Gro; Pedersen, Henriette Lodberg; Vidal-Melgosa, Silvia; Willats, William George Tycho

2017-01-01

Cell walls are an important feature of plant cells and a major component of the plant glycome. They have both structural and physiological functions and are critical for plant growth and development. The diversity and complexity of these structures demand advanced high-throughput techniques to answer questions about their structure, functions and roles in both fundamental and applied scientific fields. Microarray technology provides both the high-throughput and the feasibility aspects required to meet that demand. In this chapter, some of the most recent microarray-based techniques relating to plant cell walls are described together with an overview of related contemporary techniques applied to carbohydrate microarrays and their general potential in glycoscience. A detailed experimental procedure for high-throughput mapping of plant cell wall glycans using the comprehensive microarray polymer profiling (CoMPP) technique is included in the chapter and provides a good example of both the robust and high-throughput nature of microarrays as well as their applicability to plant glycomics.

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Identification of the TFII-I family target genes in the vertebrate genome.

PubMed

Chimge, Nyam-Osor; Makeyev, Aleksandr V; Ruddle, Frank H; Bayarsaihan, Dashzeveg

2008-07-01

GTF2I and GTF2IRD1 encode members of the TFII-I transcription factor family and are prime candidates in the Williams syndrome, a complex neurodevelopmental disorder. Our previous expression microarray studies implicated TFII-I proteins in the regulation of a number of genes critical in various aspects of cell physiology. Here, we combined bioinformatics and microarray results to identify TFII-I downstream targets in the vertebrate genome. These results were validated by chromatin immunoprecipitation and siRNA analysis. The collected evidence revealed the complexity of TFII-I-mediated processes that involve distinct regulatory networks. Altogether, these results lead to a better understanding of specific molecular events, some of which may be responsible for the Williams syndrome phenotype.

Designing microarray and RNA-Seq experiments for greater systems biology discovery in modern plant genomics.

PubMed

Yang, Chuanping; Wei, Hairong

2015-02-01

Microarray and RNA-seq experiments have become an important part of modern genomics and systems biology. Obtaining meaningful biological data from these experiments is an arduous task that demands close attention to many details. Negligence at any step can lead to gene expression data containing inadequate or composite information that is recalcitrant for pattern extraction. Therefore, it is imperative to carefully consider experimental design before launching a time-consuming and costly experiment. Contemporarily, most genomics experiments have two objectives: (1) to generate two or more groups of comparable data for identifying differentially expressed genes, gene families, biological processes, or metabolic pathways under experimental conditions; (2) to build local gene regulatory networks and identify hierarchically important regulators governing biological processes and pathways of interest. Since the first objective aims to identify the active molecular identities and the second provides a basis for understanding the underlying molecular mechanisms through inferring causality relationships mediated by treatment, an optimal experiment is to produce biologically relevant and extractable data to meet both objectives without substantially increasing the cost. This review discusses the major issues that researchers commonly face when embarking on microarray or RNA-seq experiments and summarizes important aspects of experimental design, which aim to help researchers deliberate how to generate gene expression profiles with low background noise but with more interaction to facilitate novel biological discoveries in modern plant genomics. Copyright © 2015 The Author. Published by Elsevier Inc. All rights reserved.

Transcriptome analysis of a tau overexpression model in rats implicates an early pro-inflammatory response

PubMed Central

Wang, David B.; Dayton, Robert D.; Zweig, Richard M.; Klein, Ronald L.

2010-01-01

Neurofibrillary tangles comprised of the microtubule-associated protein tau are pathological features of Alzheimer's disease and several other neurodegenerative diseases, such as progressive supranuclear palsy. We previously overexpressed tau in the substantia nigra of rats and mimicked some of the neurodegenerative sequelae that occur in humans such as tangle formation, loss of dopamine neurons, and microgliosis. To study molecular changes involved in the tau-induced disease state, we used DNA microarrays at an early stage of the disease process. A range of adeno-associated virus (AAV9) vector doses for tau were injected in groups of rats with a survival interval of two weeks. Specific decreases in messages for dopamine related genes validated the technique with respect to the dopaminergic cell loss observed. Of the mRNAs upregulated, there was a dose-dependent effect on multiple genes involved in immune response such as chemokines, interferon-inducible genes and leukocyte markers, only in the tau vector groups and not in dose-matched controls of either transgene-less empty vector or control green fluorescent protein vector. Histological staining for dopamine neurons and microglia matched the loss of dopaminergic markers and upregulation of immune response mRNAs in the microarray data, respectively. RT-PCR for selected markers confirmed the microarray results, with similar changes found by either technique. The mRNA data correlate well with previous findings, and underscore microgliosis and immune response in the degenerative process following tau overexpression. PMID:20346943

Methods for processing microarray data.

PubMed

Ares, Manuel

2014-02-01

Quality control must be maintained at every step of a microarray experiment, from RNA isolation through statistical evaluation. Here we provide suggestions for analyzing microarray data. Because the utility of the results depends directly on the design of the experiment, the first critical step is to ensure that the experiment can be properly analyzed and interpreted. What is the biological question? What is the best way to perform the experiment? How many replicates will be required to obtain the desired statistical resolution? Next, the samples must be prepared, pass quality controls for integrity and representation, and be hybridized and scanned. Also, slides with defects, missing data, high background, or weak signal must be rejected. Data from individual slides must be normalized and combined so that the data are as free of systematic bias as possible. The third phase is to apply statistical filters and tests to the data to determine genes (1) expressed above background, (2) whose expression level changes in different samples, and (3) whose RNA-processing patterns or protein associations change. Next, a subset of the data should be validated by an alternative method, such as reverse transcription-polymerase chain reaction (RT-PCR). Provided that this endorses the general conclusions of the array analysis, gene sets whose expression, splicing, polyadenylation, protein binding, etc. change in different samples can be classified with respect to function, sequence motif properties, as well as other categories to extract hypotheses for their biological roles and regulatory logic.

Profiling Ethylene-Responsive Genes Expressed in the Latex of the Mature Virgin Rubber Trees Using cDNA Microarray

PubMed Central

Nie, Zhiyi; Kang, Guijuan; Duan, Cuifang; Li, Yu; Dai, Longjun; Zeng, Rizhong

2016-01-01

Ethylene is commonly used as a latex stimulant of Hevea brasiliensis by application of ethephon (chloro-2-ethylphosphonic acid); however, the molecular mechanism by which ethylene increases latex production is not clear. To better understand the effects of ethylene stimulation on the laticiferous cells of rubber trees, a latex expressed sequence tag (EST)-based complementary DNA microarray containing 2,973 unique genes (probes) was first developed and used to analyze the gene expression changes in the latex of the mature virgin rubber trees after ethephon treatment at three different time-points: 8, 24 and 48 h. Transcript levels of 163 genes were significantly altered with fold-change values ≥ 2 or ≤ –2 (q-value < 0.05) in ethephon-treated rubber trees compared with control trees. Of the 163 genes, 92 were up-regulated and 71 down-regulated. The microarray results were further confirmed using real-time quantitative reverse transcript-PCR for 20 selected genes. The 163 ethylene-responsive genes were involved in several biological processes including organic substance metabolism, cellular metabolism, primary metabolism, biosynthetic process, cellular response to stimulus and stress. The presented data suggest that the laticifer water circulation, production and scavenging of reactive oxygen species, sugar metabolism, and assembly and depolymerization of the latex actin cytoskeleton might play important roles in ethylene-induced increase of latex production. The results may provide useful insights into understanding the molecular mechanism underlying the effect of ethylene on latex metabolism of H. brasiliensis. PMID:26985821

A common-path phase-shift interferometry surface plasmon imaging system

NASA Astrophysics Data System (ADS)

Su, Y.-T.; Chen, Shean-Jen; Yeh, T.-L.

2005-03-01

A biosensing imaging system is proposed based on the integration of surface plasmon resonance (SPR) and common-path phase-shift interferometry (PSI) techniques to measure the two-dimensional spatial phase variation caused by biomolecular interactions upon a sensing chip. The SPR phase imaging system can offer high resolution and high-throughout screening capabilities to analyze microarray biomolecular interaction without the need for additional labeling. With the long-term stability advantage of the common-path PSI technique even with external disturbances such as mechanical vibration, buffer flow noise, and laser unstable issue, the system can match the demand of real-time kinetic study for biomolecular interaction analysis (BIA). The SPR-PSI imaging system has achieved a detection limit of 2×10-7 refraction index change, a long-term phase stability of 2.5x10-4π rms over four hours, and a spatial phase resolution of 10-3 π with a lateral resolution of 100μm.

How Can We Use Bioinformatics to Predict Which Agents Will Cause Birth Defects?

EPA Science Inventory

The availability of genomic sequences from a growing number of human and model organisms has provided an explosion of data, information, and knowledge regarding biological systems and disease processes. High-throughput technologies such as DNA and protein microarray biochips are ...

Fast gene ontology based clustering for microarray experiments.

PubMed

Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Spotting optimization for oligo microarrays on aldehyde-glass.

PubMed

Dawson, Erica D; Reppert, Amy E; Rowlen, Kathy L; Kuck, Laura R

2005-06-15

Low-density microarrays that utilize short oligos (<100 nt) for capture are highly attractive for use in diagnostic applications, yet these experiments require strict quality control and meticulous reproducibility. However, a survey of current literature indicates vast inconsistencies in the spotting and processing procedures. In this study, spotting and processing protocols were optimized for aldehyde-functionalized glass substrates. Figures of merit were developed for quantitative comparison of spot quality and reproducibility. Experimental variables examined included oligo concentration in the spotting buffer, composition of the spotting buffer, postspotting "curing" conditions, and postspotting wash conditions. Optimized conditions included the use of 3-4 microM oligo in a 3x standard saline citrate/0.05% sodium dodecyl sulfate/0.001% (3-[(3-cholamidopropyl) dimethylammonia]-1-propane sulfonate) spotting buffer, 24-h postspotting reaction at 100% relative humidity, and a four-step wash procedure. Evaluation of six types of aldehyde-functionalized glass substrates indicated that those manufactured by CEL Associates, Inc. yield the highest oligo coverage.

Microarray evaluation of gene expression profiles in inflamed and healthy human dental pulp: the role of IL1beta and CD40 in pulp inflammation.

PubMed

Gatta, V; Zizzari, V L; Dd ' Amico, V; Salini, L; D' Aurora, M; Franchi, S; Antonucci, I; Sberna, M T; Gherlone, E; Stuppia, L; Tetè, S

2012-01-01

Dental pulp undergoes a number of changes passing from healthy status to inflammation due to deep decay. These changes are regulated by several genes resulting differently expressed in inflamed and healthy dental pulp, and the knowledge of the processes underlying this differential expression is of great relevance in the identification of the pathogenesis of the disease. In this study, the gene expression profile of inflamed and healthy dental pulps were compared by microarray analysis, and data obtained were analyzed by Ingenuity Pathway Analysis (IPA) software. This analysis allows to focus on a variety of genes, typically expressed in inflamed tissues. The comparison analysis showed an increased expression of several genes in inflamed pulp, among which IL1β and CD40 resulted of particular interest. These results indicate that gene expression profile of human dental pulp in different physiological and pathological conditions may become an useful tool for improving our knowledge about processes regulating pulp inflammation.

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

[Web-ring of sites for pathologists in the internet: a computer-mediated communication environment].

PubMed

Khramtsov, A I; Isianov, N N; Khorzhevskiĭ, V A

2009-01-01

The recently developed Web-ring of pathology-related Web-sites has transformed computer-mediated communications for Russian-speaking pathologists. Though the pathologists may be geographically dispersed, the network provides a complex of asynchronous and synchronous conferences for the purposes of diagnosis, consultations, education, communication, and collaboration in the field of pathology. This paper describes approaches to be used by participants of the pathology-related Web-ring. The approaches are analogous to the tools employed in telepathology and digital microscopy. One of the novel methodologies is the use of Web-based conferencing systems, in which the whole slide digital images of tissue microarrays were jointly reviewed online by pathologists at distant locations. By using ImageScope (Aperio Technologies) and WebEx connect desktop management technology, they shared presentations and images and communicated in realtime. In this manner, the Web-based forums and conferences will be a powerful addition to a telepathology.

The effect of column purification on cDNA indirect labelling for microarrays

PubMed Central

Molas, M Lia; Kiss, John Z

2007-01-01

Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays. PMID:17597522

The effect of column purification on cDNA indirect labelling for microarrays.

PubMed

Molas, M Lia; Kiss, John Z

2007-06-27

The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays.

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

PubMed

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

2015-07-01

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

Two-Dimensional VO2 Mesoporous Microarrays for High-Performance Supercapacitor

NASA Astrophysics Data System (ADS)

Fan, Yuqi; Ouyang, Delong; Li, Bao-Wen; Dang, Feng; Ren, Zongming

2018-05-01

Two-dimensional (2D) mesoporous VO2 microarrays have been prepared using an organic-inorganic liquid interface. The units of microarrays consist of needle-like VO2 particles with a mesoporous structure, in which crack-like pores with a pore size of about 2 nm and depth of 20-100 nm are distributed on the particle surface. The liquid interface acts as a template for the formation of the 2D microarrays, as identified from the kinetic observation. Due to the mesoporous structure of the units and high conductivity of the microarray, such 2D VO2 microarrays exhibit a high specific capacitance of 265 F/g at 1 A/g and excellent rate capability (182 F/g at 10 A/g) and cycling stability, suggesting the effect of unique microstructure for improving the electrochemical performance.

TAMEE: data management and analysis for tissue microarrays.

PubMed

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

2007-03-07

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. 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. 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 http://genome.tugraz.at/Software/TAMEE.

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

PubMed Central

Jaluria, Pratik; Konstantopoulos, Konstantinos; Betenbaugh, Michael; Shiloach, Joseph

2007-01-01

With advances in robotics, computational capabilities, and the fabrication of high quality glass slides coinciding with increased genomic information being available on public databases, microarray technology is increasingly being used in laboratories around the world. In fact, fields as varied as: toxicology, evolutionary biology, drug development and production, disease characterization, diagnostics development, cellular physiology and stress responses, and forensics have benefiting from its use. However, for many researchers not familiar with microarrays, current articles and reviews often address neither the fundamental principles behind the technology nor the proper designing of experiments. Although, microarray technology is relatively simple, conceptually, its practice does require careful planning and detailed understanding of the limitations inherently present. Without these considerations, it can be exceedingly difficult to ascertain valuable information from microarray data. Therefore, this text aims to outline key features in microarray technology, paying particular attention to current applications as outlined in recent publications, experimental design, statistical methods, and potential uses. Furthermore, this review is not meant to be comprehensive, but rather substantive; highlighting important concepts and detailing steps necessary to conduct and interpret microarray experiments. Collectively, the information included in this text will highlight the versatility of microarray technology and provide a glimpse of what the future may hold. PMID:17254338

A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach.

PubMed

Motakis, E S; Nason, G P; Fryzlewicz, P; Rutter, G A

2006-10-15

Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar-Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being 'distribution-free' in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data. DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results. The R package of the Data-Driven Haar-Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

Microintaglio Printing for Soft Lithography-Based in Situ Microarrays

PubMed Central

Biyani, Manish; Ichiki, Takanori

2015-01-01

Advances in lithographic approaches to fabricating bio-microarrays have been extensively explored over the last two decades. However, the need for pattern flexibility, a high density, a high resolution, affordability and on-demand fabrication is promoting the development of unconventional routes for microarray fabrication. This review highlights the development and uses of a new molecular lithography approach, called “microintaglio printing technology”, for large-scale bio-microarray fabrication using a microreactor array (µRA)-based chip consisting of uniformly-arranged, femtoliter-size µRA molds. In this method, a single-molecule-amplified DNA microarray pattern is self-assembled onto a µRA mold and subsequently converted into a messenger RNA or protein microarray pattern by simultaneously producing and transferring (immobilizing) a messenger RNA or a protein from a µRA mold to a glass surface. Microintaglio printing allows the self-assembly and patterning of in situ-synthesized biomolecules into high-density (kilo-giga-density), ordered arrays on a chip surface with µm-order precision. This holistic aim, which is difficult to achieve using conventional printing and microarray approaches, is expected to revolutionize and reshape proteomics. This review is not written comprehensively, but rather substantively, highlighting the versatility of microintaglio printing for developing a prerequisite platform for microarray technology for the postgenomic era. PMID:27600226

Development of an oligo DNA microarray for the European sea bass and its application to expression profiling of jaw deformity

PubMed Central

2010-01-01

Background The European sea bass (Dicentrarchus labrax) is a marine fish of great importance for fisheries and aquaculture. Functional genomics offers the possibility to discover the molecular mechanisms underlying productive traits in farmed fish, and a step towards the application of marker assisted selection methods in this species. To this end, we report here on the development of an oligo DNA microarray for D. labrax. Results A database consisting of 19,048 unique transcripts was constructed, of which 12,008 (63%) could be annotated by similarity and 4,692 received a GO functional annotation. Two non-overlapping 60mer probes were designed for each unique transcript and in-situ synthesized on glass slides using Agilent SurePrint™ technology. Probe design was positively completed for 19,035 target clusters; the oligo microarray was then applied to profile gene expression in mandibles and whole-heads of fish affected by prognathism, a skeletal malformation that strongly affects sea bass production. Statistical analysis identified 242 transcripts that are significantly down-regulated in deformed individuals compared to normal fish, with a significant enrichment in genes related to nervous system development and functioning. A set of genes spanning a wide dynamic range in gene expression level were selected for quantitative RT-PCR validation. Fold change correlation between microarray and qPCR data was always significant. Conclusions The microarray platform developed for the European sea bass has a high level of flexibility, reliability, and reproducibility. Despite the well known limitations in achieving a proper functional annotation in non-model species, sufficient information was obtained to identify biological processes that are significantly enriched among differentially expressed genes. New insights were obtained on putative mechanisms involved on mandibular prognathism, suggesting that bone/nervous system development might play a role in this phenomenon. PMID:20525278

Expression profiling and pathway analysis of Krüppel-like factor 4 in mouse embryonic fibroblasts

PubMed Central

Hagos, Engda G; Ghaleb, Amr M; Kumar, Amrita; Neish, Andrew S; Yang, Vincent W

2011-01-01

Background: Krüppel-like factor 4 (KLF4) is a zinc-finger transcription factor with diverse regulatory functions in proliferation, differentiation, and development. KLF4 also plays a role in inflammation, tumorigenesis, and reprogramming of somatic cells to induced pluripotent stem (iPS) cells. To gain insight into the mechanisms by which KLF4 regulates these processes, we conducted DNA microarray analyses to identify differentially expressed genes in mouse embryonic fibroblasts (MEFs) wild type and null for Klf4. Methods: Expression profiles of fibroblasts isolated from mouse embryos wild type or null for the Klf4 alleles were examined by DNA microarrays. Differentially expressed genes were subjected to the Database for Annotation, Visualization and Integrated Discovery (DAVID). The microarray data were also interrogated with the Ingenuity Pathway Analysis (IPA) and Gene Set Enrichment Analysis (GSEA) for pathway identification. Results obtained from the microarray analysis were confirmed by Western blotting for select genes with biological relevance to determine the correlation between mRNA and protein levels. Results: One hundred and sixty three up-regulated and 88 down-regulated genes were identified that demonstrated a fold-change of at least 1.5 and a P-value < 0.05 in Klf4-null MEFs compared to wild type MEFs. Many of the up-regulated genes in Klf4-null MEFs encode proto-oncogenes, growth factors, extracellular matrix, and cell cycle activators. In contrast, genes encoding tumor suppressors and those involved in JAK-STAT signaling pathways are down-regulated in Klf4-null MEFs. IPA and GSEA also identified various pathways that are regulated by KLF4. Lastly, Western blotting of select target genes confirmed the changes revealed by microarray data. Conclusions: These data are not only consistent with previous functional studies of KLF4's role in tumor suppression and somatic cell reprogramming, but also revealed novel target genes that mediate KLF4's functions. PMID:21892412

Use of lectin microarray to differentiate gastric cancer from gastric ulcer

PubMed Central

Huang, Wei-Li; Li, Yang-Guang; Lv, Yong-Chen; Guan, Xiao-Hui; Ji, Hui-Fan; Chi, Bao-Rong

2014-01-01

AIM: To investigate the feasibility of lectin microarray for differentiating gastric cancer from gastric ulcer. METHODS: Twenty cases of human gastric cancer tissue and 20 cases of human gastric ulcer tissue were collected and processed. Protein was extracted from the frozen tissues and stored. The lectins were dissolved in buffer, and the sugar-binding specificities of lectins and the layout of the lectin microarray were summarized. The median of the effective data points for each lectin was globally normalized to the sum of medians of all effective data points for each lectin in one block. Formalin-fixed paraffin-embedded gastric cancer tissues and their corresponding gastric ulcer tissues were subjected to Ag retrieval. Biotinylated lectin was used as the primary antibody and HRP-streptavidin as the secondary antibody. The glycopatterns of glycoprotein in gastric cancer and gastric ulcer specimens were determined by lectin microarray, and then validated by lectin histochemistry. Data are presented as mean ± SD for the indicated number of independent experiments. RESULTS: The glycosylation level of gastric cancer was significantly higher than that in ulcer. In gastric cancer, most of the lectin binders showed positive signals and the intensity of the signals was stronger, whereas the opposite was the case for ulcers. Significant differences in the pathological score of the two lectins were apparent between ulcer and gastric cancer tissues using the same lectin. For MPL and VVA, all types of gastric cancer detected showed stronger staining and a higher positive rate in comparison with ulcer, especially in the case of signet ring cell carcinoma and intra-mucosal carcinoma. GalNAc bound to MPL showed a significant increase. A statistically significant association between MPL and gastric cancer was observed. As with MPL, there were significant differences in VVA staining between gastric cancer and ulcer. CONCLUSION: Lectin microarray can differentiate the different glycopatterns in gastric cancer and gastric ulcer, and the lectins MPL and VVA can be used as biomarkers. PMID:24833877

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

PubMed

Zhang, Zhe; Fenstermacher, David

2005-01-01

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

Methods to study legionella transcriptome in vitro and in vivo.

PubMed

Faucher, Sebastien P; Shuman, Howard A

2013-01-01

The study of transcriptome responses can provide insight into the regulatory pathways and genetic factors that contribute to a specific phenotype. For bacterial pathogens, it can identify putative new virulence systems and shed light on the mechanisms underlying the regulation of virulence factors. Microarrays have been previously used to study gene regulation in Legionella pneumophila. In the past few years a sharp reduction of the costs associated with microarray experiments together with the availability of relatively inexpensive custom-designed commercial microarrays has made microarray technology an accessible tool for the majority of researchers. Here we describe the methodologies to conduct microarray experiments from in vitro and in vivo samples.

Near-infrared fluorescence imaging of cancer mediated by tumor hypoxia and HIF1α/OATPs signaling axis

PubMed Central

Wu, Jason Boyang; Shao, Chen; Li, Xiangyan; Shi, Changhong; Li, Qinlong; Hu, Peizhen; Chen, Yi-Ting; Dou, Xiaoliang; Sahu, Divya; Li, Wei; Harada, Hiroshi; Zhang, Yi; Wang, Ruoxiang; Zhau, Haiyen E.; Chung, Leland W.K.

2014-01-01

Near-infrared fluorescence (NIRF) imaging agents are promising tools for noninvasive cancer imaging. Here, we explored the mechanistic properties of a specific group of NIR heptamethine carbocyanines including MHI-148 dye we identified and synthesized, and demonstrated these dyes to achieve cancer-specific imaging and targeting via a hypoxia-mediated mechanism. We found that cancer cells and tumor xenografts exhibited hypoxia-dependent MHI-148 dye uptake in vitro and in vivo, which was directly mediated by hypoxia-inducible factor 1α (HIF1α). Microarray analysis and dye uptake assay further revealed a group of hypoxia-inducible organic anion-transporting polypeptides (OATPs) responsible for dye uptake, and the correlation between OATPs and HIF1α was manifested in progressive clinical cancer specimens. Finally, we demonstrated increased uptake of MHI-148 dye in situ in perfused clinical tumor samples with activated HIF1α/OATPs signaling. Our results establish these NIRF dyes as potential tumor hypoxia-dependent cancer-targeting agents and provide a mechanistic rationale for continued development of NIRF imaging agents for improved cancer detection, prognosis and therapy. PMID:24957295

Large scale infrared imaging of tissue micro arrays (TMAs) using a tunable Quantum Cascade Laser (QCL) based microscope.

PubMed

Bassan, Paul; Weida, Miles J; Rowlette, Jeremy; Gardner, Peter

2014-08-21

Chemical imaging in the field of vibrational spectroscopy is developing into a promising tool to complement digital histopathology. Applications include screening of biopsy tissue via automated recognition of tissue/cell type and disease state based on the chemical information from the spectrum. For integration into clinical practice, data acquisition needs to be speeded up to implement a rack based system where specimens are rapidly imaged to compete with current visible scanners where 100's of slides can be scanned overnight. Current Fourier transform infrared (FTIR) imaging with focal plane array (FPA) detectors are currently the state-of-the-art instrumentation for infrared absorption chemical imaging, however recent development in broadly tunable lasers in the mid-IR range is considered the most promising potential candidate for next generation microscopes. In this paper we test a prototype quantum cascade laser (QCL) based spectral imaging microscope with a focus on discrete frequency chemical imaging. We demonstrate how a protein chemical image of the amide I band (1655 cm(-1)) of a 2 × 2.4 cm(2) breast tissue microarray (TMA) containing over 200 cores can be measured in 9 min. This result indicates that applications requiring chemical images from a few key wavelengths would be ideally served by laser-based microscopes.

Multiplex infectious disease microarrays: STAT serology on a drop of blood

NASA Astrophysics Data System (ADS)

Ewart, Tom; Tarnopolsky, Mark; Baker, Steve; Raha, Sandeep; Wong, Yuen-Yee; Ciebiera, Kathy

2009-06-01

New and resurgent viral and antibiotic-resistant bacterial diseases are being encountered worldwide. The US CDC now ranks hospital acquired infections among the top 10 leading causes of death in the US, costing $20 billion annually. Such nosocomial infections presently affect 5% - 10% of hospitalized patients leading to 2 million cases and 99,000 deaths annually. Until now, assays available to mount comprehensive surveillance of infectious disease exposure by biosecurity agencies and hospital infection control units have been too slow and too costly. In earlier clinical studies we have reported proteomic microarrays combining 13 autoimmune and 26 viral and bacterial pathogens that revealed correlations between autoimmune diseases and antecedent infections. In this work we have expanded the array to 40 viruses and bacteria and investigated a suspected role of human endogenous retroviruses in autoimmune neuropathies. Using scanning laser imaging, and fluorescence color multiplexing, serum IgG and IgM responses are measured concurrently on the same array, for 14 arrays (patient samples) per microscope slide in 15 minutes. Other advantages include internal calibration, 10 μL sample size, increased laboratory efficiency, and potential factor of 100 cost reduction.

Multiplexed immunosensing and kinetics monitoring in nanofluidic devices with highly enhanced target capture efficiency

PubMed Central

Lin, Yii-Lih; Huang, Yen-Jun; Teerapanich, Pattamon; Leïchlé, Thierry

2016-01-01

Nanofluidic devices promise high reaction efficiency and fast kinetic responses due to the spatial constriction of transported biomolecules with confined molecular diffusion. However, parallel detection of multiple biomolecules, particularly proteins, in highly confined space remains challenging. This study integrates extended nanofluidics with embedded protein microarray to achieve multiplexed real-time biosensing and kinetics monitoring. Implementation of embedded standard-sized antibody microarray is attained by epoxy-silane surface modification and a room-temperature low-aspect-ratio bonding technique. An effective sample transport is achieved by electrokinetic pumping via electroosmotic flow. Through the nanoslit-based spatial confinement, the antigen-antibody binding reaction is enhanced with ∼100% efficiency and may be directly observed with fluorescence microscopy without the requirement of intermediate washing steps. The image-based data provide numerous spatially distributed reaction kinetic curves and are collectively modeled using a simple one-dimensional convection-reaction model. This study represents an integrated nanofluidic solution for real-time multiplexed immunosensing and kinetics monitoring, starting from device fabrication, protein immobilization, device bonding, sample transport, to data analysis at Péclet number less than 1. PMID:27375819

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

PubMed

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

2004-10-01

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

Fluorescence-based bioassays for the detection and evaluation of food materials.

PubMed

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-10-13

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials.

Fluorescence-Based Bioassays for the Detection and Evaluation of Food Materials

PubMed Central

Nishi, Kentaro; Isobe, Shin-Ichiro; Zhu, Yun; Kiyama, Ryoiti

2015-01-01

We summarize here the recent progress in fluorescence-based bioassays for the detection and evaluation of food materials by focusing on fluorescent dyes used in bioassays and applications of these assays for food safety, quality and efficacy. Fluorescent dyes have been used in various bioassays, such as biosensing, cell assay, energy transfer-based assay, probing, protein/immunological assay and microarray/biochip assay. Among the arrays used in microarray/biochip assay, fluorescence-based microarrays/biochips, such as antibody/protein microarrays, bead/suspension arrays, capillary/sensor arrays, DNA microarrays/polymerase chain reaction (PCR)-based arrays, glycan/lectin arrays, immunoassay/enzyme-linked immunosorbent assay (ELISA)-based arrays, microfluidic chips and tissue arrays, have been developed and used for the assessment of allergy/poisoning/toxicity, contamination and efficacy/mechanism, and quality control/safety. DNA microarray assays have been used widely for food safety and quality as well as searches for active components. DNA microarray-based gene expression profiling may be useful for such purposes due to its advantages in the evaluation of pathway-based intracellular signaling in response to food materials. PMID:26473869

Genomic approaches to identifying transcriptional regulators of osteoblast differentiation

NASA Technical Reports Server (NTRS)

Stains, Joseph P.; Civitelli, Roberto

2003-01-01

Recent microarray studies of mouse and human osteoblast differentiation in vitro have identified novel transcription factors that may be important in the establishment and maintenance of differentiation. These findings help unravel the pattern of gene-expression changes that underly the complex process of bone formation.

Transcriptome response to elevated CO2, water deficit, and thermal stress in peanut

USDA-ARS?s Scientific Manuscript database

Previously, our laboratories have performed gene expression studies using EST sequencing and spotted microarrays to investigate tissue-specific gene expression and response to abiotic stress. While these studies have provided valuable insight into these processes, they are constrained by sequencer t...

Microfluidic microarray systems and methods thereof

DOEpatents

West, Jay A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Hux, Gary A [Tracy, CA

2009-04-28

Disclosed are systems that include a manifold in fluid communication with a microfluidic chip having a microarray, an illuminator, and a detector in optical communication with the microarray. Methods for using these systems for biological detection are also disclosed.

Mining subspace clusters from DNA microarray data using large itemset techniques.

PubMed

Chang, Ye-In; Chen, Jiun-Rung; Tsai, Yueh-Chi

2009-05-01

Mining subspace clusters from the DNA microarrays could help researchers identify those genes which commonly contribute to a disease, where a subspace cluster indicates a subset of genes whose expression levels are similar under a subset of conditions. Since in a DNA microarray, the number of genes is far larger than the number of conditions, those previous proposed algorithms which compute the maximum dimension sets (MDSs) for any two genes will take a long time to mine subspace clusters. In this article, we propose the Large Itemset-Based Clustering (LISC) algorithm for mining subspace clusters. Instead of constructing MDSs for any two genes, we construct only MDSs for any two conditions. Then, we transform the task of finding the maximal possible gene sets into the problem of mining large itemsets from the condition-pair MDSs. Since we are only interested in those subspace clusters with gene sets as large as possible, it is desirable to pay attention to those gene sets which have reasonable large support values in the condition-pair MDSs. From our simulation results, we show that the proposed algorithm needs shorter processing time than those previous proposed algorithms which need to construct gene-pair MDSs.

Power enhancement via multivariate outlier testing with gene expression arrays.

PubMed

Asare, Adam L; Gao, Zhong; Carey, Vincent J; Wang, Richard; Seyfert-Margolis, Vicki

2009-01-01

As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing. We applied our approach to several data resources. First, as a negative control, we found that the Affymetrix and Illumina contributions to MAQC data were free from outliers at a nominal outlier flagging rate of alpha=0.01. Second, we created a tunable framework for artificially corrupting intensity data from the Affymetrix Latin Square spike-in experiment to allow investigation of sensitivity and specificity of quality assurance (QA) criteria. Third, we applied the procedure to 507 Affymetrix microarray GeneChips processed with RNA from human peripheral blood samples. We show that exclusion of arrays by this approach substantially increases inferential power, or the ability to detect differential expression, in large clinical studies. http://bioconductor.org/packages/2.3/bioc/html/arrayMvout.html and http://bioconductor.org/packages/2.3/bioc/html/affyContam.html affyContam (credentials: readonly/readonly)

Expert Knowledge Influences Decision-Making for Couples Receiving Positive Prenatal Chromosomal Microarray Testing Results.

PubMed

Rubel, M A; Werner-Lin, A; Barg, F K; Bernhardt, B A

2017-09-01

To assess how participants receiving abnormal prenatal genetic testing results seek information and understand the implications of results, 27 US female patients and 12 of their male partners receiving positive prenatal microarray testing results completed semi-structured phone interviews. These interviews documented participant experiences with chromosomal microarray testing, understanding of and emotional response to receiving results, factors affecting decision-making about testing and pregnancy termination, and psychosocial needs throughout the testing process. Interview data were analyzed using a modified grounded theory approach. In the absence of certainty about the implications of results, understanding of results is shaped by biomedical expert knowledge (BEK) and cultural expert knowledge (CEK). When there is a dearth of BEK, as in the case of receiving results of uncertain significance, participants rely on CEK, including religious/spiritual beliefs, "gut instinct," embodied knowledge, and social network informants. CEK is a powerful platform to guide understanding of prenatal genetic testing results. The utility of culturally situated expert knowledge during testing uncertainty emphasizes that decision-making occurs within discourses beyond the biomedical domain. These forms of "knowing" may be integrated into clinical consideration of efficacious patient assessment and counseling.

Variation of gene expression in Bacillus subtilis samples of fermentation replicates.

PubMed

Zhou, Ying; Yu, Wen-Bang; Ye, Bang-Ce

2011-06-01

The application of comprehensive gene expression profiling technologies to compare wild and mutated microorganism samples or to assess molecular differences between various treatments has been widely used. However, little is known about the normal variation of gene expression in microorganisms. In this study, an Agilent customized microarray representing 4,106 genes was used to quantify transcript levels of five-repeated flasks to assess normal variation in Bacillus subtilis gene expression. CV analysis and analysis of variance were employed to investigate the normal variance of genes and the components of variance, respectively. The results showed that above 80% of the total variation was caused by biological variance. For the 12 replicates, 451 of 4,106 genes exhibited variance with CV values over 10%. The functional category enrichment analysis demonstrated that these variable genes were mainly involved in cell type differentiation, cell type localization, cell cycle and DNA processing, and spore or cyst coat. Using power analysis, the minimal biological replicate number for a B. subtilis microarray experiment was determined to be six. The results contribute to the definition of the baseline level of variability in B. subtilis gene expression and emphasize the importance of replicate microarray experiments.

A multilevel Lab on chip platform for DNA analysis.

PubMed

Marasso, Simone Luigi; Giuri, Eros; Canavese, Giancarlo; Castagna, Riccardo; Quaglio, Marzia; Ferrante, Ivan; Perrone, Denis; Cocuzza, Matteo

2011-02-01

Lab-on-chips (LOCs) are critical systems that have been introduced to speed up and reduce the cost of traditional, laborious and extensive analyses in biological and biomedical fields. These ambitious and challenging issues ask for multi-disciplinary competences that range from engineering to biology. Starting from the aim to integrate microarray technology and microfluidic devices, a complex multilevel analysis platform has been designed, fabricated and tested (All rights reserved-IT Patent number TO2009A000915). This LOC successfully manages to interface microfluidic channels with standard DNA microarray glass slides, in order to implement a complete biological protocol. Typical Micro Electro Mechanical Systems (MEMS) materials and process technologies were employed. A silicon/glass microfluidic chip and a Polydimethylsiloxane (PDMS) reaction chamber were fabricated and interfaced with a standard microarray glass slide. In order to have a high disposable system all micro-elements were passive and an external apparatus provided fluidic driving and thermal control. The major microfluidic and handling problems were investigated and innovative solutions were found. Finally, an entirely automated DNA hybridization protocol was successfully tested with a significant reduction in analysis time and reagent consumption with respect to a conventional protocol.

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages.

PubMed

Taminau, Jonatan; Meganck, Stijn; Lazar, Cosmin; Steenhoff, David; Coletta, Alain; Molter, Colin; Duque, Robin; de Schaetzen, Virginie; Weiss Solís, David Y; Bersini, Hugues; Nowé, Ann

2012-12-24

With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].

Assessing the impact of Benzo[a]pyrene on Marine Mussels: Application of a novel targeted low density microarray complementing classical biomarker responses

PubMed Central

Sforzini, Susanna; Arlt, Volker M.; Barranger, Audrey; Dallas, Lorna J.; Oliveri, Caterina; Aminot, Yann; Pacchioni, Beniamina; Millino, Caterina; Lanfranchi, Gerolamo; Readman, James W.; Moore, Michael N.; Viarengo, Aldo; Jha, Awadhesh N.

2017-01-01

Despite the increasing use of mussels in environmental monitoring and ecotoxicological studies, their genomes and gene functions have not been thoroughly explored. Several cDNA microarrays were recently proposed for Mytilus spp., but putatively identified partial transcripts have rendered the generation of robust transcriptional responses difficult in terms of pathway identification. We developed a new low density oligonucleotide microarray with 465 probes covering the same number of genes. Target genes were selected to cover most of the well-known biological processes in the stress response documented over the last decade in bivalve species at the cellular and tissue levels. Our new ‘STressREsponse Microarray’ (STREM) platform consists of eight sub-arrays with three replicates for each target in each sub-array. To assess the potential use of the new array, we tested the effect of the ubiquitous environmental pollutant benzo[a]pyrene (B[a]P) at 5, 50, and 100 μg/L on two target tissues, the gills and digestive gland, of Mytilus galloprovincialis exposed invivo for three days. Bioaccumulation of B[a]P was also determined demonstrating exposure in both tissues. In addition to the well-known effects of B[a]P on DNA metabolism and oxidative stress, the new array data provided clues about the implication of other biological processes, such as cytoskeleton, immune response, adhesion to substrate, and mitochondrial activities. Transcriptional data were confirmed using qRT-PCR. We further investigated cellular functions and possible alterations related to biological processes highlighted by the microarray data using oxidative stress biomarkers (Lipofuscin content) and the assessment of genotoxicity. DNA damage, as measured by the alkaline comet assay, increased as a function of dose.DNA adducts measurements using 32P-postlabeling method also showed the presence of bulky DNA adducts (i.e. dG-N2-BPDE). Lipofiscin content increased significantly in B[a]P exposed mussels. Immunohistochemical analysis of tubulin and actin showed changes in cytoskeleton organisation. Our results adopting an integrated approach confirmed that the combination of newly developed transcriptomic approcah, classical biomarkers along with chemical analysis of water and tissue samples should be considered for environmental bioimonitoring and ecotoxicological studies to obtain holistic information to assess the impact of contaminants on the biota. PMID:28651000

Functional comparison of microarray data across multiple platforms using the method of percentage of overlapping functions.

PubMed

Li, Zhiguang; Kwekel, Joshua C; Chen, Tao

2012-01-01

Functional comparison across microarray platforms is used to assess the comparability or similarity of the biological relevance associated with the gene expression data generated by multiple microarray platforms. Comparisons at the functional level are very important considering that the ultimate purpose of microarray technology is to determine the biological meaning behind the gene expression changes under a specific condition, not just to generate a list of genes. Herein, we present a method named percentage of overlapping functions (POF) and illustrate how it is used to perform the functional comparison of microarray data generated across multiple platforms. This method facilitates the determination of functional differences or similarities in microarray data generated from multiple array platforms across all the functions that are presented on these platforms. This method can also be used to compare the functional differences or similarities between experiments, projects, or laboratories.

Profiling In Situ Microbial Community Structure with an Amplification Microarray

PubMed Central

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

2013-01-01

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

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

EPA Science Inventory

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

IMPROVING THE RELIABILITY OF MICROARRAYS FOR TOXICOLOGY RESEARCH: A COLLABORATIVE APPROACH

EPA Science Inventory

Microarray-based gene expression profiling is a critical tool to identify molecular biomarkers of specific chemical stressors. Although current microarray technologies have progressed from their infancy, biological and technical repeatability and reliability are often still limit...

Form-Deprivation Myopia in Chick Induces Limited Changes in Retinal Gene Expression

PubMed Central

McGlinn, Alice M.; Baldwin, Donald A.; Tobias, John W.; Budak, Murat T.; Khurana, Tejvir S.; Stone, Richard A.

2007-01-01

Purpose Evidence has implicated the retina as a principal controller of refractive development. In the present study, the retinal transcriptome was analyzed to identify alterations in gene expression and potential signaling pathways involved in form-deprivation myopia of the chick. Methods One-week-old white Leghorn chicks wore a unilateral image-degrading goggle for 6 hours or 3 days (n = 6 at each time). Total RNA from the retina/(retinal pigment epithelium) was used for expression profiling with chicken gene microarrays (Chicken GeneChips; Affymetrix, Santa Clara, CA). To identify gene expression level differences between goggled and contralateral nongoggled eyes, normalized microarray signal intensities were analyzed by the significance analysis of microarrays (SAM) approach. Differentially expressed genes were validated by real-time quantitative reverse transcription–polymerase chain reaction (qPCR) in independent biological replicates. Results Small changes were detected in differentially expressed genes in form-deprived eyes. In chickens that had 6 hours of goggle wear, downregulation of bone morphogenetic protein 2 and connective tissue growth factor was validated. In those with 3 days of goggle wear, downregulation of bone morphogenetic protein 2, vasoactive intestinal peptide, preopro-urotensin II–related peptide and mitogen-activated protein kinase phosphatase 2 was validated, and upregulation of endothelin receptor type B and interleukin-18 was validated. Conclusions Form-deprivation myopia, in its early stages, is associated with only minimal changes in retinal gene expression at the level of the transcriptome. While the list of validated genes is short, each merits further study for potential involvement in the signaling cascade mediating myopia development. PMID:17652709

Changes in the microbial communities during co-composting of digestates☆

PubMed Central

Franke-Whittle, Ingrid H.; Confalonieri, Alberto; Insam, Heribert; Schlegelmilch, Mirko; Körner, Ina

2014-01-01

Anaerobic digestion is a waste treatment method which is of increasing interest worldwide. At the end of the process, a digestate remains, which can gain added value by being composted. A study was conducted in order to investigate microbial community dynamics during the composting process of a mixture of anaerobic digestate (derived from the anaerobic digestion of municipal food waste), green wastes and a screened compost (green waste/kitchen waste compost), using the COMPOCHIP microarray. The composting process showed a typical temperature development, and the highest degradation rates occurred during the first 14 days of composting, as seen from the elevated CO2 content in the exhaust air. With an exception of elevated nitrite and nitrate levels in the day 34 samples, physical–chemical parameters for all compost samples collected during the 63 day process indicated typical composting conditions. The microbial communities changed over the 63 days of composting. According to principal component analysis of the COMPOCHIP microarray results, compost samples from the start of the experiment were found to cluster most closely with the digestate and screened compost samples. The green waste samples were found to group separately. All starting materials investigated were found to yield fewer and lower signals when compared to the samples collected during the composting experiment. PMID:24456768

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

PubMed Central

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

2013-01-01

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

A microarray of ubiquitylated proteins for profiling deubiquitylase activity reveals the critical roles of both chain and substrate.

PubMed

Loch, Christian M; Strickler, James E

2012-11-01

Substrate ubiquitylation is a reversible process critical to cellular homeostasis that is often dysregulated in many human pathologies including cancer and neurodegeneration. Elucidating the mechanistic details of this pathway could unlock a large store of information useful to the design of diagnostic and therapeutic interventions. Proteomic approaches to the questions at hand have generally utilized mass spectrometry (MS), which has been successful in identifying both ubiquitylation substrates and profiling pan-cellular chain linkages, but is generally unable to connect the two. Interacting partners of the deubiquitylating enzymes (DUBs) have also been reported by MS, although substrates of catalytically competent DUBs generally cannot be. Where they have been used towards the study of ubiquitylation, protein microarrays have usually functioned as platforms for the identification of substrates for specific E3 ubiquitin ligases. Here, we report on the first use of protein microarrays to identify substrates of DUBs, and in so doing demonstrate the first example of microarray proteomics involving multiple (i.e., distinct, sequential and opposing) enzymatic activities. This technique demonstrates the selectivity of DUBs for both substrate and type (mono- versus poly-) of ubiquitylation. This work shows that the vast majority of DUBs are monoubiquitylated in vitro, and are incapable of removing this modification from themselves. This work also underscores the critical role of utilizing both ubiquitin chains and substrates when attempting to characterize DUBs. This article is part of a Special Issue entitled: Ubiquitin Drug Discovery and Diagnostics. Copyright © 2012 Elsevier B.V. All rights reserved.

Informatic selection of a neural crest-melanocyte cDNA set for microarray analysis

PubMed Central

Loftus, S. K.; Chen, Y.; Gooden, G.; Ryan, J. F.; Birznieks, G.; Hilliard, M.; Baxevanis, A. D.; Bittner, M.; Meltzer, P.; Trent, J.; Pavan, W.

1999-01-01

With cDNA microarrays, it is now possible to compare the expression of many genes simultaneously. To maximize the likelihood of finding genes whose expression is altered under the experimental conditions, it would be advantageous to be able to select clones for tissue-appropriate cDNA sets. We have taken advantage of the extensive sequence information in the dbEST expressed sequence tag (EST) database to identify a neural crest-derived melanocyte cDNA set for microarray analysis. Analysis of characterized genes with dbEST identified one library that contained ESTs representing 21 neural crest-expressed genes (library 198). The distribution of the ESTs corresponding to these genes was biased toward being derived from library 198. This is in contrast to the EST distribution profile for a set of control genes, characterized to be more ubiquitously expressed in multiple tissues (P < 1 × 10−9). From library 198, a subset of 852 clustered ESTs were selected that have a library distribution profile similar to that of the 21 neural crest-expressed genes. Microarray analysis demonstrated the majority of the neural crest-selected 852 ESTs (Mel1 array) were differentially expressed in melanoma cell lines compared with a non-neural crest kidney epithelial cell line (P < 1 × 10−8). This was not observed with an array of 1,238 ESTs that was selected without library origin bias (P = 0.204). This study presents an approach for selecting tissue-appropriate cDNAs that can be used to examine the expression profiles of developmental processes and diseases. PMID:10430933

Immune and inflammatory gene signature in rat cerebrum in subarachnoid hemorrhage with microarray analysis.

PubMed

Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren

2012-01-01

Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

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

2016-01-01

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

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

2006-01-01

Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497

Biologically relevant effects of mRNA amplification on gene expression profiles.

PubMed

van Haaften, Rachel I M; Schroen, Blanche; Janssen, Ben J A; van Erk, Arie; Debets, Jacques J M; Smeets, Hubert J M; Smits, Jos F M; van den Wijngaard, Arthur; Pinto, Yigal M; Evelo, Chris T A

2006-04-11

Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results. In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other.Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range. Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P <0.001). Those reporters were also predicted to form significantly more (0.76+/-0.07 versus 0.38+/-0.1) and longer (9.4+/-0.3 versus 8.4+/-0.4) hairpins as compared to representative control reporters present before and after amplification. This study establishes that the gene expression profile obtained after amplification of mRNA of left ventricular biopsies is representative for the whole left ventricle of the rat heart. However, specific gene transcripts present in parental tissues were undetectable in the minute left ventricular biopsies. Transcripts that were lost due to the amplification process were not randomly distributed, but had higher GC-content and hairpins in the sequence and were mainly found in the lower intensity range which includes many transcription factors from specific signalling pathways.

Biologically relevant effects of mRNA amplification on gene expression profiles

PubMed Central

van Haaften, Rachel IM; Schroen, Blanche; Janssen, Ben JA; van Erk, Arie; Debets, Jacques JM; Smeets, Hubert JM; Smits, Jos FM; van den Wijngaard, Arthur; Pinto, Yigal M; Evelo, Chris TA

2006-01-01

Background Gene expression microarray technology permits the analysis of global gene expression profiles. The amount of sample needed limits the use of small excision biopsies and/or needle biopsies from human or animal tissues. Linear amplification techniques have been developed to increase the amount of sample derived cDNA. These amplified samples can be hybridised on microarrays. However, little information is available whether microarrays based on amplified and unamplified material yield comparable results. In the present study we compared microarray data obtained from amplified mRNA derived from biopsies of rat cardiac left ventricle and non-amplified mRNA derived from the same organ. Biopsies were linearly amplified to acquire enough material for a microarray experiment. Both amplified and unamplified samples were hybridized to the Rat Expression Set 230 Array of Affymetrix. Results Analysis of the microarray data showed that unamplified material of two different left ventricles had 99.6% identical gene expression. Gene expression patterns of two biopsies obtained from the same parental organ were 96.3% identical. Similarly, gene expression pattern of two biopsies from dissimilar organs were 92.8% identical to each other. Twenty-one percent of reporters called present in parental left ventricular tissue disappeared after amplification in the biopsies. Those reporters were predominantly seen in the low intensity range. Sequence analysis showed that reporters that disappeared after amplification had a GC-content of 53.7+/-4.0%, while reporters called present in biopsy- and whole LV-samples had an average GC content of 47.8+/-5.5% (P <0.001). Those reporters were also predicted to form significantly more (0.76+/-0.07 versus 0.38+/-0.1) and longer (9.4+/-0.3 versus 8.4+/-0.4) hairpins as compared to representative control reporters present before and after amplification. Conclusion This study establishes that the gene expression profile obtained after amplification of mRNA of left ventricular biopsies is representative for the whole left ventricle of the rat heart. However, specific gene transcripts present in parental tissues were undetectable in the minute left ventricular biopsies. Transcripts that were lost due to the amplification process were not randomly distributed, but had higher GC-content and hairpins in the sequence and were mainly found in the lower intensity range which includes many transcription factors from specific signalling pathways. PMID:16608515

MICROARRAY ANALYSIS OF PM-INDUCED GENEEXPRESSION IN HUMAN BRONCHIAL EPITHELIAL CELLS

EPA Science Inventory

Ambient air particles (PM) are generally classified into 3 sizes; coarse (2.5, 10m), fine (0.1, 2.5m), and ultrafine (<0.lpm). Each particle size is evolved from different sources and transformation processes (e.g., combustion vs. mechanical abrasion, and atmospheric conversion ...

Nanoelectrospray ion generation for high-throughput mass spectrometry using a micromachined ultrasonic ejector array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aderogba, S.; Meacham, J.M.; Degertekin, F.L.

2005-05-16

Ultrasonic electrospray ionization (ESI) for high-throughput mass spectrometry is demonstrated using a silicon micromachined microarray. The device uses a micromachined ultrasonic atomizer operating in the 900 kHz-2.5 MHz range for droplet generation and a metal electrode in the fluid cavity for ionization. Since the atomization and ionization processes are separated, the ultrasonic ESI source shows the potential for operation at low voltages with a wide range of solvents in contrast with conventional capillary ESI technology. This is demonstrated using the ultrasonic ESI microarray to obtain the mass spectrum of a 10 {mu}M reserpine sample on a time of flight massmore » spectrometer with 197:1 signal-to-noise ratio at an ionization potential of 200 V.« less

THE MAQC PROJECT: ESTABLISHING QC METRICS AND THRESHOLDS FOR MICROARRAY QUALITY CONTROL

EPA Science Inventory

Microarrays represent a core technology in pharmacogenomics and toxicogenomics; however, before this technology can successfully and reliably be applied in clinical practice and regulatory decision-making, standards and quality measures need to be developed. The Microarray Qualit...

Spatial resolution versus contrast trade-off enhancement in high-resolution surface plasmon resonance imaging (SPRI) by metal surface nanostructure design.

PubMed

Banville, Frederic A; Moreau, Julien; Sarkar, Mitradeep; Besbes, Mondher; Canva, Michael; Charette, Paul G

2018-04-16

Surface plasmon resonance imaging (SPRI) is an optical near-field method used for mapping the spatial distribution of chemical/physical perturbations above a metal surface without exogenous labeling. Currently, the majority of SPRI systems are used in microarray biosensing, requiring only modest spatial resolution. There is increasing interest in applying SPRI for label-free near-field imaging of biological cells to study cell/surface interactions. However, the required resolution (sub-µm) greatly exceeds what current systems can deliver. Indeed, the attenuation length of surface plasmon polaritons (SPP) severely limits resolution along one axis, typically to tens of µm. Strategies to date for improving spatial resolution result in a commensurate deterioration in other imaging parameters. Unlike the smooth metal surfaces used in SPRI that support purely propagating surface modes, nanostructured metal surfaces support "hybrid" SPP modes that share attributes from both propagating and localized modes. We show that these hybrid modes are especially well-suited to high-resolution imaging and demonstrate how the nanostructure geometry can be designed to achieve sub-µm resolution while mitigating the imaging parameter trade-off according to an application-specific optimum.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Development of a DNA microarray for species identification of quarantine aphids.

PubMed

Lee, Won Sun; Choi, Hwalran; Kang, Jinseok; Kim, Ji-Hoon; Lee, Si Hyeock; Lee, Seunghwan; Hwang, Seung Yong

2013-12-01

Aphid pests are being brought into Korea as a result of increased crop trading. Aphids exist on growth areas of plants, and thus plant growth is seriously affected by aphid pests. However, aphids are very small and have several sexual morphs and life stages, so it is difficult to identify species on the basis of morphological features. This problem was approached using DNA microarray technology. DNA targets of the cytochrome c oxidase subunit I gene were generated with a fluorescent dye-labelled primer and were hybridised onto a DNA microarray consisting of specific probes. After analysing the signal intensity of the specific probes, the unique patterns from the DNA microarray, consisting of 47 species-specific probes, were obtained to identify 23 aphid species. To confirm the accuracy of the developed DNA microarray, ten individual blind samples were used in blind trials, and the identifications were completely consistent with the sequencing data of all individual blind samples. A microarray has been developed to distinguish aphid species. DNA microarray technology provides a rapid, easy, cost-effective and accurate method for identifying aphid species for pest control management. © 2013 Society of Chemical Industry.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

SIMULATION AND VISUALIZATION OF FLOW PATTERN IN MICROARRAYS FOR LIQUID PHASE OLIGONUCLEOTIDE AND PEPTIDE SYNTHESIS

PubMed Central

O-Charoen, Sirimon; Srivannavit, Onnop; Gulari, Erdogan

2008-01-01

Microfluidic microarrays have been developed for economical and rapid parallel synthesis of oligonucleotide and peptide libraries. For a synthesis system to be reproducible and uniform, it is crucial to have a uniform reagent delivery throughout the system. Computational fluid dynamics (CFD) is used to model and simulate the microfluidic microarrays to study geometrical effects on flow patterns. By proper design geometry, flow uniformity could be obtained in every microreactor in the microarrays. PMID:17480053

The application of DNA microarrays in gene expression analysis.

PubMed

van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

2000-03-31

DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

Electrosonic ejector microarray for drug and gene delivery.

PubMed

Zarnitsyn, Vladimir G; Meacham, J Mark; Varady, Mark J; Hao, Chunhai; Degertekin, F Levent; Fedorov, Andrei G

2008-04-01

We report on development and experimental characterization of a novel cell manipulation device-the electrosonic ejector microarray-which establishes a pathway for drug and/or gene delivery with control of biophysical action on the length scale of an individual cell. The device comprises a piezoelectric transducer for ultrasound wave generation, a reservoir for storing the sample mixture and a set of acoustic horn structures that form a nozzle array for focused application of mechanical energy. The nozzles are micromachined in silicon or plastic using simple and economical batch fabrication processes. When the device is driven at a particular resonant frequency of the acoustic horn structures, the sample mixture of cells and desired transfection agents/molecules suspended in culture medium is ejected from orifices located at the nozzle tips. During sample ejection, focused mechanical forces (pressure and shear) are generated on a microsecond time scale (dictated by nozzle size/geometry and ejection velocity) resulting in identical "active" microenvironments for each ejected cell. This process enables a number of cellular bioeffects, from uptake of small molecules and gene delivery/transfection to cell lysis. Specifically, we demonstrate successful calcein uptake and transfection of DNA plasmid encoding green fluorescent protein (GFP) into human malignant glioma cells (cell line LN443) using electrosonic microarrays with 36, 45 and 50 mum diameter nozzle orifices and operating at ultrasound frequencies between 0.91 and 0.98 MHz. Our results suggest that efficacy and the extent of bioeffects are mainly controlled by nozzle orifice size and the localized intensity of the applied acoustic field.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

PubMed Central

van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.

2015-01-01

Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674

Best practices for hybridization design in two-colour microarray analysis.

PubMed

Knapen, Dries; Vergauwen, Lucia; Laukens, Kris; Blust, Ronny

2009-07-01

Two-colour microarrays are a popular platform of choice in gene expression studies. Because two different samples are hybridized on a single microarray, and several microarrays are usually needed in a given experiment, there are many possible ways to combine samples on different microarrays. The actual combination employed is commonly referred to as the 'hybridization design'. Different types of hybridization designs have been developed, all aimed at optimizing the experimental setup for the detection of differentially expressed genes while coping with technical noise. Here, we first provide an overview of the different classes of hybridization designs, discussing their advantages and limitations, and then we illustrate the current trends in the use of different hybridization design types in contemporary research.

Single-particle imaging for biosensor applications

NASA Astrophysics Data System (ADS)

Yorulmaz, Mustafa; Isil, Cagatay; Seymour, Elif; Yurdakul, Celalettin; Solmaz, Berkan; Koc, Aykut; Ünlü, M. Selim

2017-10-01

Current state-of-the-art technology for in-vitro diagnostics employ laboratory tests such as ELISA that consists of a multi-step test procedure and give results in analog format. Results of these tests are interpreted by the color change in a set of diluted samples in a multi-well plate. However, detection of the minute changes in the color poses challenges and can lead to false interpretations. Instead, a technique that allows individual counting of specific binding events would be useful to overcome such challenges. Digital imaging has been applied recently for diagnostics applications. SPR is one of the techniques allowing quantitative measurements. However, the limit of detection in this technique is on the order of nM. The current required detection limit, which is already achieved with the analog techniques, is around pM. Optical techniques that are simple to implement and can offer better sensitivities have great potential to be used in medical diagnostics. Interference Microscopy is one of the tools that have been investigated over years in optics field. More of the studies have been performed in confocal geometry and each individual nanoparticle was observed separately. Here, we achieve wide-field imaging of individual nanoparticles in a large field-of-view ( 166 μm × 250 μm) on a micro-array based sensor chip in fraction of a second. We tested the sensitivity of our technique on dielectric nanoparticles because they exhibit optical properties similar to viruses and cells. We can detect non-resonant dielectric polystyrene nanoparticles of 100 nm. Moreover, we perform post-processing applications to further enhance visibility.

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…

Challenges of microarray applications for microbial detection and gene expression profiling in food

USDA-ARS?s Scientific Manuscript database

Microarray technology represents one of the latest advances in molecular biology. The diverse types of microarrays have been applied to clinical and environmental microbiology, microbial ecology, and in human, veterinary, and plant diagnostics. Since multiple genes can be analyzed simultaneously, ...

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

PubMed Central

Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Caryoscope: An Open Source Java application for viewing microarray data in a genomic context

PubMed Central

Awad, Ihab AB; Rees, Christian A; Hernandez-Boussard, Tina; Ball, Catherine A; Sherlock, Gavin

2004-01-01

Background Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context. Results We have developed Caryoscope, which is an open source Java application for visualizing microarray data from array comparative genome hybridization experiments in a genomic context. Caryoscope can read General Feature Format files (GFF files), as well as comma- and tab-delimited files, that define the genomic positions of the microarray reporters for which data are obtained. The microarray data can be browsed using an interactive, zoomable interface, which helps users identify regions of chromosomal deletion or amplification. The graphical representation of the data can be exported in a number of graphic formats, including publication-quality formats such as PostScript. Conclusion Caryoscope is a useful tool that can aid in the visualization, exploration and interpretation of microarray data in a genomic context. PMID:15488149

Evaluation of a Field-Portable DNA Microarray Platform and Nucleic Acid Amplification Strategies for the Detection of Arboviruses, Arthropods, and Bloodmeals

PubMed Central

Grubaugh, Nathan D.; Petz, Lawrence N.; Melanson, Vanessa R.; McMenamy, Scott S.; Turell, Michael J.; Long, Lewis S.; Pisarcik, Sarah E.; Kengluecha, Ampornpan; Jaichapor, Boonsong; O'Guinn, Monica L.; Lee, John S.

2013-01-01

Highly multiplexed assays, such as microarrays, can benefit arbovirus surveillance by allowing researchers to screen for hundreds of targets at once. We evaluated amplification strategies and the practicality of a portable DNA microarray platform to analyze virus-infected mosquitoes. The prototype microarray design used here targeted the non-structural protein 5, ribosomal RNA, and cytochrome b genes for the detection of flaviviruses, mosquitoes, and bloodmeals, respectively. We identified 13 of 14 flaviviruses from virus inoculated mosquitoes and cultured cells. Additionally, we differentiated between four mosquito genera and eight whole blood samples. The microarray platform was field evaluated in Thailand and successfully identified flaviviruses (Culex flavivirus, dengue-3, and Japanese encephalitis viruses), differentiated between mosquito genera (Aedes, Armigeres, Culex, and Mansonia), and detected mammalian bloodmeals (human and dog). We showed that the microarray platform and amplification strategies described here can be used to discern specific information on a wide variety of viruses and their vectors. PMID:23249687

A molecular beacon microarray based on a quantum dot label for detecting single nucleotide polymorphisms.

PubMed

Guo, Qingsheng; Bai, Zhixiong; Liu, Yuqian; Sun, Qingjiang

2016-03-15

In this work, we report the application of streptavidin-coated quantum dot (strAV-QD) in molecular beacon (MB) microarray assays by using the strAV-QD to label the immobilized MB, avoiding target labeling and meanwhile obviating the use of amplification. The MBs are stem-loop structured oligodeoxynucleotides, modified with a thiol and a biotin at two terminals of the stem. With the strAV-QD labeling an "opened" MB rather than a "closed" MB via streptavidin-biotin reaction, a sensitive and specific detection of label-free target DNA sequence is demonstrated by the MB microarray, with a signal-to-background ratio of 8. The immobilized MBs can be perfectly regenerated, allowing the reuse of the microarray. The MB microarray also is able to detect single nucleotide polymorphisms, exhibiting genotype-dependent fluorescence signals. It is demonstrated that the MB microarray can perform as a 4-to-2 encoder, compressing the genotype information into two outputs. Copyright © 2015 Elsevier B.V. All rights reserved.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

PubMed Central

2012-01-01

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. PMID:16964229

Application of carbohydrate microarray technology for the detection of Burkholderia pseudomallei, Bacillus anthracis and Francisella tularensis antibodies.

PubMed

Parthasarathy, N; Saksena, R; Kováč, P; Deshazer, D; Peacock, S J; Wuthiekanun, V; Heine, H S; Friedlander, A M; Cote, C K; Welkos, S L; Adamovicz, J J; Bavari, S; Waag, D M

2008-11-03

We developed a microarray platform by immobilizing bacterial 'signature' carbohydrates onto epoxide modified glass slides. The carbohydrate microarray platform was probed with sera from non-melioidosis and melioidosis (Burkholderia pseudomallei) individuals. The platform was also probed with sera from rabbits vaccinated with Bacillus anthracis spores and Francisella tularensis bacteria. By employing this microarray platform, we were able to detect and differentiate B. pseudomallei, B. anthracis and F. tularensis antibodies in infected patients, and infected or vaccinated animals. These antibodies were absent in the sera of naïve test subjects. The advantages of the carbohydrate microarray technology over the traditional indirect hemagglutination and microagglutination tests for the serodiagnosis of melioidosis and tularemia are discussed. Furthermore, this array is a multiplex carbohydrate microarray for the detection of all three biothreat bacterial infections including melioidosis, anthrax and tularemia with one, multivalent device. The implication is that this technology could be expanded to include a wide array of infectious and biothreat agents.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.