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Scalable DNA Data Storage Systems

Authors: 
Keung, A. J. - Presenter, North Carolina State University
DNA holds significant promise as a data storage medium due to its density, longevity, and resource and energy sustainability. These advantages arise from the inherent biomolecular structure of DNA as well as, perhaps unintuitively, the spatially disordered nature of DNA mixtures. For example, disordered pools of DNA strands confer extreme density, while arraying DNA strands on fixed substrates or within microwells would abrogate almost all of this density advantage. Furthermore, even just terabyte-sized databases would require mixtures of billions of distinct DNA strands, much larger than the sequence diversity of the human genome; thus, the unique molecular and disordered nature of DNA storage presents clear challenges arising simply from the fact that many diverse strands of DNA will be in crowded proximity with severe thermodynamically-driven limitations on file access specificity and accuracy. This prompts important discussions on how data should be organized, accessed, and manipulated. Here we argue that the novel architecture of DNA storage may actually confer novel functionalities beyond what is possible with conventional storage media, and that inspiration from natural biological processes and biochemistry can be leveraged to engineer novel and scalable functionalities into DNA databases. We will describe three examples of this approach. We will show how hierarchical file systems can be engineered to expand the number of possible unique DNA file addresses by five orders of magnitude and that individual KB sized files can be specifically accessed from large TB sized background databases. Next, we took inspiration from the processes of gene expression and strand displacements to engineer a dynamic and reusable DNA storage system that can rename, lock, and delete files while also improving encoding efficiency and information density over current random access methods. Finally, we describe how thermodynamics can be leveraged to tune biomolecular interactions and implement functions such as File Preview.