Novel Techniques and Applications in Molecular Computing, Data Storage, Diagnostics, and Fabrication

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2021

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For the past several decades, the discoveries, development, and improvement of microscale and nanoscale techniques and tools have been a major momentum driving the rapid technological advances across many areas of modern sciences and engineering, especially in multidisciplinary fields such as nucleic acid research. Owing to the remarkable programmability, long-term stability, and excellent coding capacity, nucleic acids have received much attention as a promising substrate for constructing next-generation data storage and computing systems at the molecular scale. These emerging applications bridge the knowledge from multiple disciplines including computer science, materials science, and biological science. Advances in nucleic acid technologies have also made significant contributions to life sciences and healthcare, leading to innovations that continue to improve disease prevention, diagnosis, and treatment. For example, techniques such as nucleic acid isothermal amplification hold great promises to enable widespread low-cost molecular testing of pathogens and infectious diseases without expensive instrumentation. The rapidly advancing field of nucleic acid research have given rise to a broad range of practical applications, many of which rely on the development and innovations of supporting technologies such as microscale and nanoscale fabrication techniques, which continue to help pave the way for designing and prototyping better and useful tools such as microfluidics and microarrays. Collectively, this dissertation focuses on these several distinct yet interconnected areas of research around nucleic acid technologies and contributes several novel techniques with applications spanning molecular computing, DNA data storage, molecular diagnostics, and benchtop microfabrication.

This dissertation is organized as follows. Chapter 1 presents an overview of recent advances in nucleic-acid-based molecular data storage and computing systems. DNA outperforms most conventional storage media in terms of information retention time, physical density, and volumetric coding capacity. Advances in synthesis and sequencing technologies have enabled implementations of large synthetic DNA storage with impressive storage capacity and reliable data recovery. Several robust DNA storage architectures featuring random access, error correction, and content-rewritability have been constructed with the potential for scalability and cost reduction. This chapter surveys these recent achievements and discusses alternative routes for overcoming the hurdles of engineering practical DNA storage systems. This chapter also reviews recent exciting work on in vivo DNA memory including intracellular recorders constructed by programmable genome editing tools. Besides information storage, DNA could serve as a versatile molecular computing substrate. Several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks are introduced. These simple primitives have facilitated rational designs and implementations of in vitro DNA reaction networks that emulate digital/analog circuits, artificial neural networks, or nonlinear dynamic systems. This chapter also highlights in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. The chapter concludes with a discussion of applications and challenges of DNA-based data storage and computing and their far-reaching implications in biocomputing, security, and medicine.

Chapter 2 presents the design, modeling, and simulation of a novel molecular data storage architecture that enables highly efficient, scalable, multidimensional data organization and random access in large DNA storage systems. With impressive physical density and molecular-scale coding capacity, DNA is a promising substrate for building long-lasting data archival storage systems. To retrieve data from DNA storage, recent implementations typically rely on large libraries of meticulously designed orthogonal PCR primers, which fundamentally limit the capacity and scalability of practical DNA storage. This work combines nested and semi-nested PCR to enable multidimensional data organization and random access in large DNA storage. Our strategy effectively pushes the limit of DNA storage capacity and dramatically reduces the number of orthogonal primers needed for efficient PCR random access. Our design uses only k*n primers to uniquely address n^k data-encoding oligos. The architecture inherently supports various well-defined PCR random-access patterns that can be tailored to organize and preserve the underlying DNA-encoded data structures and relations in simple database-like formats such as rows, columns, tables, and blocks of data entries. We design in silico PCR experiments of a four-dimensional DNA storage to illustrate the mechanisms of sixteen different random-access patterns each requiring no more than two PCR reactions to selectively amplify a target dataset of various sizes. To better approximate the physical system, we formulate mathematical models based on empirical distributions to analyze the effect of pipetting, PCR bias, and PCR stochasticity on the performance of multidimensional data queries from large DNA storage.

Chapter 3 presents the design, modeling, and simulation of a renewable DNA logic computing scheme. An important achievement in the field of DNA computing has been the development of experimental protocols for evaluation of Boolean logic circuits. These protocols for DNA circuits generally take as inputs single-stranded DNA molecules that encode Boolean values, and via a series of DNA hybridization reactions then release ssDNA strands to indicate Boolean output values. However, most of these DNA circuits protocols are use-once only, and there remains the major challenge of designing DNA circuits to be renewable for use with multiple sets of inputs. Prior proposed schemes to make DNA gates renewable suffered from multiple problems, including waste accumulation, signal restoration, noise tolerance, and limited scalable complexity. In this work, we propose a scalable design and in silico demonstration of photoregulated renewable DNA seesaw logic circuits, which after processing a given set of inputs, can be repeatedly reset to reliably process other distinct inputs. To achieve renewability, specific toeholds in the system are labeled with photoresponsive molecules such as azobenzene to modulate the effective rate constants of toehold-mediated strand displacement (TMSD) reactions. Our proposed design strategy of leveraging the collective effect of TMSD and azobenzene-mediated dehybridization provides new perspectives on achieving synchronized and localized control of DNA hybridizations in complex and scalable reaction networks efficiently and economically. Various devices such as molecular walkers and motors could potentially be engineered reusable, be simulated and subsequently implemented using our simplified design strategy.

Chapter 4 present the design and experimental validation of a rapid, inexpensive, high-performance molecular home test kit for self-administered diagnosis of COVID-19 and other infectious diseases without instrumentation or trained personnel. To curb and monitor the spread of SARS-CoV-2, simple, affordable, accurate home tests are urgently needed for global population-scale surveillance. We report a rapid, low-cost (~2 USD), simple-to-use molecular test kit for self-administered at-home testing with high sensitivity and specificity. A one-pot lyophilization protocol was developed and optimized to preserve all required biochemical reagents of the test in a single microtube, facilitating long-term storage, inexpensive distribution, and simple testing without specialized instrumentation or trained personnel. The entire sample-to-answer workflow takes <60 minutes, including noninvasive sample collection, one-step RNA isolation, reverse-transcription loop-mediated isothermal amplification (RT-LAMP) in a thermos, and finally a direct visual inspection of colorimetric test result. Our test kit remains stable for ≥30 days at typical home-refrigeration temperature (4 °C) and ≥10 days at room temperature (~20 to 22 °C), achieving ≥95% analytical sensitivity and >99% specificity with a reproducible limit of detection down to at least five copies of viral RNA per microliter under both storage conditions. Notably, the lyophilized RT-LAMP assay demonstrated reduced false positives and enhanced tolerance to a wider range of incubation temperatures compared to conventional solution-based RT-LAMP reactions. Validation tests conducted using simulated SARS-CoV-2 infected samples confirmed rapid detection of SARS-CoV-2 virus from both anterior nasal swabs and gingival swabs. Our test successfully detected multiple SARS-CoV-2 variants and can be easily adapted to enable inexpensive near-patient/at-home molecular testing solutions for other pathogens and infectious diseases.

Chapter 5 presents the invention of a rapid, low-cost, benchtop microfabrication method termed UV-micropatterned miniaturization. Shrink lithography is a promising top-down micro/nanofabrication technique capable of miniaturizing patterns/structures to scales much smaller than the initial mold, however, rapid inexpensive fabrication of high-fidelity shrinkable microfeatures remains challenging. This work reports the discovery and characterization of a simple, fast, low-cost method for replicating and miniaturizing intricate micropatterns/structures on commodity heat-shrinkable polymers. Large-area permanent micropatterning on polystyrene and polyolefin shrink film is attained in one step under ambient conditions through brief irradiation by a shortwave UV pencil lamp. After baking briefly in an oven, the film shrinks biaxially and the miniaturized micropatterns emerge with significantly reduced surface area (up to 95%) and enhanced depth profile. The entire UV-micropatterned miniaturization process is highly reproducible and achievable on benchtop under a few minutes without chemicals or sophisticated apparatus. A variety of microgrid patterns are replicated and miniaturized with high yield and resolution on both planar and curved surfaces. Sequential UV exposures enable easy and rapid engineering of sophisticated microtopography with miniaturized, multi-scale, multi-dimensional microstructures. UV-ozone micropatterned polystyrene surfaces are well-suited for lab-on-a-chip analytical applications owing to the inherent biocompatibility and enhanced surface hydrophilicity. Miniaturization of dense, periodic micropatterns may facilitate low-cost prototyping of functional devices/surfaces such as micro-optics/sensors and tunable metamaterials.

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Song, Xin (2021). Novel Techniques and Applications in Molecular Computing, Data Storage, Diagnostics, and Fabrication. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/24383.

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