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

Background 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. 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. Conclusion MicroGen represents a MIAME compliant information system that enables managing workflow and supporting collaborative work in spotted microarray experiment production.


Biological Samples
The origin of the biological sample : human coronary arteries were obtained from patients at Stanford University Hospital undergoing orthotopic heart transplantation.
Characteristics of the biological sample : basic demographic information, clinical risk factors, and medication profiles were obtained from each patient. Refer to Table 1 in the paper for a detailed description of patient characteristics.
Manipulation of biological samples : major epicardial coronary arteries were dissected from explanted hearts. The vessels were dissected longitudinally to expose the endoluminal surface and lesions were identified and scored by inspection using a dissecting microscope. The arteries were then divided into 1.0-2.0 cm normal and diseased segments.
Protocol for preparing the hybridization extract : samples were homogenized (PRO250 Homogenizer, 10 mm X 105 mm generator, PRO Scientific Inc., Oxford, Connecticut) in TRIzol (Invitrogen Life Technologies, Carlsbad, California). After phenol/chloroform extraction, the aqueous phase was applied to an RNeasy Mini column (Qiagen, Valencia, California) following manufacturer's instructions. Purity and quantity of total RNA was assessed using the RNA 6000 Nano Chip and Bioanalyzer (Agilent Technologies, Palo Alto, California).
Labeling protocol : 10 µg of total RNA was primed with 2 µl of 100µM T 16 N 2 oligo d(T) DNA primer in a 50 ul reaction that was incubated at 70°C for 10 minutes. The RNA was reverse transcribed with Superscript II RT (Invitrogen Life Technologies, Carlsbad, California) to yield either cy3-or cy5-labelled double stranded cDNA. 50 µl of labelling mix and 50 µl of the oligo d(T) primed RNA were combined on ice and incubated at 42°C for 60 minutes. Final concentrations of labelling reagents were as follows: 10 mM DTT, 100 µM dNTP (without dCTP), 25 µM dCTP, 25 µM of cy3-or cy5-dCTP (NEN Life Science, Boston, Massachusetts), 1 µl RNase inhibitor per reaction, and 4U/µl SSII in 1x RT buffer. After labelling reaction, 2 µl of RNase A (0.05 mg/mL) was added to each 100 µl reaction and incubated for 30 minutes at room temperature to degrade residual RNA. Labelled cDNA targets were purified with a Qiaquick column (Qiagen, Valencia, California) following manufacturer's instructions. Purified targets were dried in a Speed Vac at 50°C until dry.

Array Design
Platform type : our cDNA microarrays were printed onto glass slides by Agilent Technologies using their proprietary SurePrint inkjet technology (Agilent Technologies, Inc., Palo Alto, CA).
Surface and coating specifications : surface and coating specifications were not provided by the manufacturer.
PCR amplification : the cDNAs spotted onto our arrays were chosen from cDNA libraries generated in our laboratory (see materials and methods section for details). Some cDNA clones were obtained commercially (Research Genetics, Carlsbad, California). All cDNA clones were amplified by PCR with primers specific for vector flanking sequences. PCR-amplified DNA was purified with automated column methodology (Qiagen, Valencia, California) and assessed by visualization on agarose gels.
Spotting protocol : spotting protocols were not provided by the manufacturer (Agilent Technologies, Inc., Palo Alto, CA).
Additional treatment : additional post-printing processing was not provided by the manufacturer (Agilent Technologies, Inc., Palo Alto, CA).
Hybridization, blocking and washing protocols : samples were quick spun and applied to our custom cDNA microarray (Agilent Technologies, Palo Alto, California), covered with a cover slip (Corning, Fountain Valley, California), placed in hybridization chambers (DieTech, San Jose, California) and incubated overnight (16-18 hours) at 65 °C. The arrays were washed with gentle stirring in 0.5X SSC/0.01% SDS for 5 minutes, then in 0.06X SSC for 10 minutes, 5 minutes, and 10 minutes (changing buffer after each wash). Arrays were spun dry at 1350 rpm at room temperature for 2 minutes.

Measurement Data and Specifications
Type of scanning hardware and software used : microarrays were scanned on an Agilent G2565AA Microarray Scanner System and raw images were quantified using Agilent Feature Extraction Software (Version A.6.1.1).
The quantitations based on the images : for further details about feature extracted data files, please use following link to Agilent's Feature Extraction Software PDF file: http://www.chem.agilent.com/scripts/cag_filexfer.asp?iWHID=CAG-05-099-00028703 .
The set of quantitations upon which conclusions are based : local background subtraction was performed and a LOWESS algorithm was used for data normalization. Dye normalization was performed to generate log ratios of sample signal/reference signal. This processed log ratio was then used for subsequent analysis with various statistical algorithms.
Description of measurements used in the analysis : the algorithm employs separate experiments to develop a measure of variance that is used to test whether observed differences in gene expression, in two sample type partitions, are likely to be real.
Notes on measurements (data selection and transformation procedures) : microarray data was also analyzed with the Threshold Number of Misclassifications (TNoM), a non-parametric score representing how well a gene separates two sample classes [Ben-Dor, 2001 #55;Ho, 2003 #115]. TNoM counts the minimal number of errors committed by using a threshold on the expression values for this separation.

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Available images of the arrays and available excel files of the processed images: Date of its creation: Wed Jan 12