(388f) Single Lane Unlabelled DNA Sequencing – a Bench Top Genomics Unit

Label Free Intrinsic Imaging (LFII) combines UV absorption, photodiode array detection, automated fluidic handling and digital signal processing to map the space-time trajectories of bioanalytes and chemicals in capillaries. This direct absorption technique eliminates labels and dyes by using signal-to-noise enhancing image processing algorithms, and has been successfully applied to protein sizing, DNA fragment analysis, chemical detection and DNA sequencing. Imaging the molecule itself, rather than the label chemically attached to it, significantly improves resolution while controlling migration time. There are also advantages in the speed of analysis, health and safety issues, reagent costs and reduced sample size. By working with unlabeled molecules, LFII also allows real-time fraction collection in the system. This gives us the ability to actively manipulate analytes, for example by switching an identified protein for subsequent analysis and the potential to identify using advanced data-mining tools. LFII has been applied to the development of a bench top DNA sequencing machine for the rapid short template analysis. The unit is designed to exploit deltaDOT's proven expertise in signal processing by imaging all four DNA sequence reactions in a single microfluidic channel. The unit will be optimised for short template sequencing of up to 200 bases in diagnostic applications. These will include re-sequencing, the identification of specific variants in a target template compared with a known genomic sequence, Single Nucleotide Polymorphorism (SNP) validation and the sequence analysis of drug resistant pathogen strains. The unit will also free researchers from the service sequencing regime that while relatively cheap, can take up to 3 days to return data, allowing them to check DNA manipulations in a few hours or less. The unit is designed to be a component of a larger system incorporating both sample preparation and data processing. When linked to a GRID-computing based information dissemination and feedback network it will allow will allow researchers achieve real-time epidemiology, advising remote health care workers on optimal drug therapy and allowing targeted deliveries of appropriate drug regimes to areas afflicted, by a particular drug resistant strain of, for example Malaria.