MicroRNAs (miRNAs) are short, noncoding RNAs that play a critical role in post-transcriptional regulation of gene expression. Consequently, aberrant miRNA expression levels are associated with a wide range of human diseases, the most prominent of which is cancer. Cancer cells are often associated with the simultaneous up- and-down regulation of several miRNAs relative to normal cells of the same tissue, and these ?signatures? can reveal significant information about the underlying disease. Thus, nucleic acid analysis technologies aimed at profiling miRNA expression patterns in living cells and tissues hold great promise for early cancer detection and diagnosis. However, prevailing methods for detecting nucleic acids in living systems are generally limited to the detection of a single nucleic acid target, thereby precluding their use in more complex pattern- recognition applications. A promising solution to this problem is molecular circuitry, and specifically, DNA strand-displacement circuits that can be programmed to generate optical and/or chemical ?outputs? in response to specific combinations of nucleic acid ?inputs?. Unfortunately, exogenously delivered DNA has a cellular half- life on the order of minutes and is susceptible to unintended interactions with cellular macromolecules, all of which adversely affect the performance of the device. As a consequence, it remains enormously challenging to execute complex and useful tasks in living systems using DNA-based circuits. Herein, the PI provides an innovative solution to this problem: mirror image DNA. Mirror image DNA (referred to as L-DNA) has the same physical and chemical properties as its natural counterpart, D-DNA, yet as a reflection, it is completely invisible to the stereospecific environment of cells (i.e. L-DNA is resistant to both nuclease degradation and off-target interactions with cellular components). Consequently, DNA-based circuitry constructed from L-DNA is expected to operate free from cellular interference, thereby overcoming the primary barrier to engineering complex and reliable functionality. On this basis, the PI proposes to develop a series of autonomous L-DNA-based circuits capable of recognizing and reporting specific miRNA expression patterns in live human cells. The immediate goal of this work is to uncover fundamental relationships between circuit design and cellular delivery methods, which together represent a critical first step towards constructing more complex intracellular devices. As the project progresses, the complexity of the L-DNA circuitry will be gradually increased through the introduction of L-DNA-based logic gate motifs that will be arranged to compute the presence of specific combinations of up to four different miRNAs. If successful, this work will signify a major advance in the area of intracellular DNA computing and provide a strong foundation for future applications aimed at ?intelligent? disease diagnosis.
Cancer-associated microRNA signatures ? the simultaneous up-and-down regulation of several miRNAs ? can reveal significant information about the underlying disease, including tumor type, stage, and potential therapeutic response. Thus, nucleic acid analysis technologies aimed at profiling miRNA expression patterns in living cells and tissues hold great promise for early cancer detection and diagnosis. The proposed research addresses the current deficit of such technologies through the development of a robust, sensitive, and broadly applicable approach for intracellular profiling of microRNA expression.
