Improved Molecular Barcodes by Lifetime Discrimination

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DESCRIPTION (provided by applicant): DNA microarrays have advanced our understanding of cellular biology by their ability to simultaneously measure mRNA levels for thousands of genes. However, these microarrays are expensive to produce and quality control is a problem due to technical issues involved in reliably delivering microscopic droplets to the surface of the slide. Also, the kinetics of the binding reaction on the glass slides is slow do due mixing limitations. In order to overcome these limitations of DNA microarrays, it has been proposed to perform these assays with a large collection of tiny plastic beads, each of which is identified with a unique molecular barcode in a flow cytometer. Current barcode strategy is based upon impregnating the plastic beads with fluorescent dyes with different wavelengths and different loading intensities. Theoretically, the use of 4 different dyes with 10 different intensities would result in 10,000 barcodes. However, the emission wavelengths of neighboring dyes cannot be too close together, or light from the emission shoulders will interfere with accurate intensity measurements. In practice, Luminox, Inc. offers a set of 100 beads made with ten loading intensities at two wavelengths. RMD proposes using a similar concept, but instead basing the molecular barcode on differences in fluorescent lifetime rather than intensity. Discrimination based on fluorescent lifetimes is not nearly as sensitive to interfering signal from neighboring dyes. The major component of radiative decay can easily be deconvoluted from minor, interfering components. This will allow dyes with emission maximums close togetherto be used resulting in a higher number of barcodes. In addition, because our approach is not susceptible to the errors inherent with absolute intensity measurements, less calibration will be required and possibly more than 10 variations at each wavelength will be distinguishable. If developed, this approach will have applications in disease research. For example, large population samples could studied for responses to therapeutic treatment as correlated with genetic variations.