Detection of Labeling Markers on Synthetic DNA molecules Nathan P. Brouwer Advisor: Richard A. Messner The Synthetic Vision and Pattern Analysis Laboratory Background Introduction Approach (MATLAB) Deoxyribonucleic acid (DNA) is the “code of life” that provides the recipe of genetic traits to all living organisms. DNA is a sequence of nucleotide base pairs that identify the correct order of amino acids that make up the proteins and end up defining all physical characteristics. A major road block in the effort to study and understand DNA has been sequencing the base pairs. Current sequencing techniques are costly and time intensive ZSGenetics has developed a patented technique to bind larger “heavy” labeling atoms to certain base pairs of DNA. DNA contains relatively “light” atoms (low atomic number). These labeling atoms provide enough contrast to be viewed when imaged using a scanning transmission electron microscope (STEM). With the fundamental development of this labeling technique, finding these markers means finding the particular base pair it was attached to, thus sequencing the DNA by visual means. The inherent problem with high resolution STEM images is the high level of back ground noise corruption. Improving the signal to noise ratio to an adequate level is one of the major challenges of this project. ZSGenetics has synthetically created a DNA molecule with every third base pair labeled. This means labels should occur between 1.3nm to 1.75nm apart. After preprocessing in ImageJ, the following can be performed using MATLAB: Cropped Image Imported into MATLAB Manually Cropped about the DNA Chain Zoomed in and added Pseudo Color One Possible String of Marker Atoms Approach (ImageJ) Conclusion The following steps describe the methodology of the approach in ImageJ : It is clear that there is DNA information in the images to be extracted. The labeling markers are providing enough contrast to be detected, but it seems there is still significant noise corruption embedded in the useful information. Extraction algorithms coupled with thresholding and pseudocoloring were used to create the final image useful for human interpretation. It is clear that individual base pairs can be labeled and viewed by these image processing techniques. Future work may make it possible to sequence an entire strand of DNA solely based on its digital image. Example Raw Image and Manual Identification of DNA (Annular Dark Field Imaging-Raster Scanned) Research To get up to speed, background research was necessary to gather fundamental principles from literature and scientific articles in: DNA Concepts Electron Microscopy Image Processing Techniques Software: ImageJ and MATLAB 3D View of DNA Sequence Implications This research is ground work for the automatic detection and sequencing of human and other genomes. By taking an image of specially prepared DNA samples and using intelligently prepared image processing algorithms, we can drastically cut time and money required to sequence long DNA chains. If successful, it will undoubtedly cause an explosion of research into genetic traits and variations. The implications in the medical field are profound. Future scientists and researchers could work towards understanding and curing genetic defects and diseases. Extracted DNA Strand STEM Basics Accelerates an ionized beam of concentrated electrons onto the sample Electrons travelling through the sample are deflected due to the positive charge of the nuclei of the atoms in the sample A Sensitive Detection Mechanism detects the received energy and a pixel is produced for each point in a 2D image lattice Apply Threshold and Ceiling Project Continuation I plan to continue this project by attempting higher level image processing algorithms and approaches as a master’s thesis while attending graduate school at UNH. ZSGenetics is working on a new ultra thin graphine substrate that shows promise to further reduce noise by increasing contrast. With improved images and additional processing (higher level filters and transforms), it seems very possible to move forward towards automatic detection , identifying periodicity, and directly sequencing the DNA via an imaging process Acknowledgements: ECE Department Hamel Center for Undergraduate Research Professor Richard A. Messner William Glover, ZSGenetics Nathan P. Brouwer nps5@unh.edu Department of Electrical Engineering University of New Hampshire Durham, NH 03824 College of Engineering and Physical Sciences University of New Hampshire