Developing futures for DNA-based computers and nanomachines

Bradley Harding

doi:10.25907/00481

Computational and mechanical constructs formed from DNA have promising potential for information processing and self-actuation in environments—such as those found within the human body—which would traditionally be considered hostile or non-viable for silicon-based systems. This project was centred around improving the fundamental capabilities of DNA-based computers and nanomachines, such that DNA-based computers and nanomachines might be more readily adoptable for use in biointegrative information processing systems and biodevices—such as smart biosensors and autonomous therapeutics. While there is a breadth of platforms that DNA-based computers encompass, this project focused specifically on phosphodiesterase deoxyribozymes (DNAzymes), which are short single-stranded DNA molecules that gain allosterically controllable phosphodiesterase activity in the presence of divalent metal ions. DNAzymes were chosen as the focus of this project for the overall potential they hold as a foundational platform of DNA-based computing, and for their enzymatic nature that offers the boon of innate signal amplification. Following a review of current DNA-based computing approaches for application within smart biosensors, several potential targets for improving the computational capacity of DNAzymes were identified. These were: 1) the development of an oligonucleotide-based system for controllably resetting DNAzymes for repeated reuse; 2) the preliminary expansion of targetable substrates, to increase the informational capacity of DNAzyme-based circuits; and 3) increasing biosensing capabilities through the rational incorporation of RNA aptamer-ligand interaction into DNAzyme control. The first aim of recyclability was demonstrated through an oligonucleotide-based system for the controlled resetting of DNAzymes. The designed system provided the first demonstrations of real-time control of both DNAzyme deactivation and reactivation—with DNAzymes returning to 90-125% of their original activity after reactivation—which was extended to include cyclical activity toggling. The designed system also provided the first demonstration of the removal and regeneration of the fluorescence associated with DNAzyme activity. The second aim—the preliminary increase of informational capacity for DNAzyme-based circuits—demonstrated the largest reported collection of substrate sequences for allosterically regulated 8-17 and E6 DNAzymes to date, providing the potential for a DNAzyme-based circuit that can yield up to a byte worth of data. This was achieved with the use of random sequence generators for the non-conserved regions of substrate sequences—based on four previously described substrates—with vetting by structure prediction and interaction modelling algorithms. The third aim of input type diversification provided the first demonstrations of DNAzymes complexing with RNA aptamers, such that the DNAzymes gain positive activity in the presence of the aptamer’s target ligand due to competitive binding. The bronchodilator theophylline—a methylxanthine compound known to not interact with DNA constructs—was used for this demonstration, and was not only positively detected by three DNAzyme-RNA aptamer complexes, but also semi-quantitated. The semi-quantitation of theophylline allowed concentrations which were either therapeutically ineffective, safe and effective, or toxic to be readily identified. The combined effects of this project’s outcomes were increased longevity and sensing capabilities, enhanced circuit complexity and bit-width, and the miniaturization of complex DNAzyme-based circuits. These outcomes should allow DNA-based computers and nanomachines to better utilise the unique capabilities of DNAzymes—enabling biodevices such as autonomous multiplexing biosensors and contextual drug release systems, and improved integration into gene-expression systems. This project successfully improved several of the fundamental capabilities of DNA-based computers and nanomachines, demonstrating the benefit of their continued development for adoption in biointegrative information processing systems and biodevices.

Developing futures for DNA-based computers and nanomachines

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