Microarray Image Analysis and Management
DNA Microarray technology has emerged as a powerful tool for genome scale expression studies, disease gene identification, genotyping and diagnostics. DNA microarray or gene chip is a miniature device wherein complementary DNA (probes) for each of the thousands of genes are spotted or in situ synthesized on a solid support (like a small microscopic glass slide). The expression levels of corresponding genes are then measured by capturing labeled RNAs or cDNAs prepared from a particular tissue sample.

Measurement of Gene Activity
In order to measure a gene's activity, scientists collect the messenger RNA (mRNA), which carries information from the gene in the nucleus to the cytoplasm, where it is usually translated into a protein product. When the RNA from a cell population or tissue is collected, this preparation is typically converted into copy DNA (cDNA) and then amplified with the polymerase chain reaction (PCR). A sample of the amplified cDNA product can be labeled with fluorescent tags to allow that population to be identified.

Typically, the researcher uses two populations of cells: one representing the control and one representing the experimental treatment. As an example, a cultured cell line's response to insulin can be measured by preparing two cell populations: one treated with insulin and one mock treated. The RNA from the insulin-treated cells can be labeled with Fluor 1 (green color) and the RNA from the control cells can be labeled with Fluor 2 (red color). These probes can then be used to interrogate a microarray of immobilized DNA targets on a glass surface, where each (x,y) coordinate represents a known DNA sequence. When the green and red probes are hybridized to the array, the composite color is a measure of the gene activity ratio. A green color would indicate a gene that is on with insulin treatment and off when insulin is absent. A red color would indicate a gene that is on when insulin is absent and off with insulin treatment. A yellow color would indicate a gene that does not change significantly with insulin treatment.

At the most basic level, all fluorescence imaging systems must include certain subsystems: sample positioning, fluorescent excitation, emitted light collection, and electronics to convert emitted photons into a digital signal. The ultimate performance of any system is determined not only by the quality or power of each individual component, but by the efficiency with which they all work together. No single component is solely responsible for detection limits, image quality, or any other performance factor. For example, an extremely high-power laser may not improve detection limits if the other components of the excitation and emission paths are of poor quality or are misaligned.

Image analysis software performs three fundamental processes of image analysis: gridding, segmentation and information extraction. Gridding is a process to locate each spot on the slide. Segmentation is a process to differentiate the pixels within a spot-containing region into foreground (true signal) and background. Information extraction includes two parts, the spot intensity extraction and background intensity extraction. Spot intensity extraction refers to the calculation of fluorescence signal from the foreground from segmentation process, while background intensity extraction utilizes different algorithms to estimate the background signal due to the non-specific hybridization on the glass.

Chitraka© image analysis and management product will allow researchers and scientists in the biotechnology industry as well as university research laboratories to acquire and analyze complex microarray image data and infer trends in gene expression. It facilitates insights into how the biological processes in the body function. Chitraka© consists of a core engine comprised of proprietary as well as public image analysis algorithms for multilevel gridding & spot identification, is portable across many acquisition platforms and consists of a bench scientist friendly graphical user interface.Results of validation against public stanford microarray data (yeast cell cycle), show that accurate spot boundary tracing presents a factor of 2 or greater improvements in detected feature intensities.

Chitraka© has an intuitive wizard like user interface (GUI) and various steps in microarray image processing can be easily executed with only a few mouse clicks.