IMAGE PROCESSING OF DNA NANOBARCODE

Abstract

Master of Engineering ThesisAn image processing software package was designed to assign clearly distinguishable colors to DNA nanobarcode probes labeled with varying ratios of red and green fluorescent dyes. The DNA nanobarcode probes were produced using novel tri-strand Y-shaped DNA secondary structures. These Y-shaped DNA structures are multivalent and anisotropic, allowing for specific and controlled hybridization to other Y-shaped DNA building blocks to create a dendrimer-like DNA structure (DL-DNA). Here, the image processing of fluorescence-intensity-encoded nanobarcodes was explored using the MATLAB software environment. DNA nanobarcodes were created with varying green:red intensity ratios: 4G1R (4 green : 1 red), 2G1R, 1G1R, 1G2R and 1G4R. Additionally, these nanobarcodes incorporated specific molecular probes to target the DNA of bacillus anthracis (anthrax), francisella tularensis (?rabbit fever?), Ebola virus, a positive control and corona virus (SARS) respectively. Fluorescence was amplified by attaching DL-DNA to polystyrene beads through biotin-avidin interactions. The nanobarcodes were visualized using a fluorescent microscope and pseudocolor images were obtained. These images were easy to distinguish for 4G1R (bright green) and 1G4R (bright red), but were difficult to distinguish for other ratios which showed up as different shades of yellow, green and orange. Using the image processing software, these nanobarcodes were assigned highly distinguishable colors based on their green:red intensity ratio, allowing for easy and fast visual identification of the pathogens targeted. With further development, this software package will be able to assign at least 25 different and visually distinguishable colors for two and three fluorescent dyes arranged in varying ratios to create high throughput visual screening of harmful pathogens.Cornell University, Molecular Bioengineering Laborator