Hairpin-DNA memory using molecular addressing

Encoding, Decoding, and Rendering Information in DNA Nanoswitch Libraries

DNA-based construction allows the creation of molecular devices that are useful in information storage and processing. Here, we combine the programmability of DNA nanoswitches and stimuli-responsive conformational changes to demonstrate information encoding and graphical readout using gel electrophoresis. We encoded information as 5-bit binary codes for alphanumeric characters using a combination of DNA and RNA inputs that can be decoded using molecular stimuli such as a ribonuclease. We also show that a similar strategy can be used for graphical visual readout of alphabets on an agarose gel, information that is encoded by nucleic acids and decoded by a ribonuclease. Our method of information encoding and processing could be combined with DNA actuation for molecular computation and diagnostics that require a nonarbitrary visual readout.

Emerging Approaches to DNA Data Storage: Challenges and Prospects

With the total amount of worldwide data skyrocketing, the global data storage demand is predicted to grow to 1.75 × 10¹⁴ GB by 2025. Traditional storage methods have difficulties keeping pace given that current storage media have a maximum density of 10³ GB/mm³. As such, data production will far exceed the capacity of currently available storage methods. The costs of maintaining and transferring data, as well as the limited lifespans and significant data losses associated with current technologies also demand advanced solutions for information storage. Nature offers a powerful alternative through the storage of information that defines living organisms in unique orders of four bases (A, T, C, G) located in molecules called deoxyribonucleic acid (DNA). DNA molecules as information carriers have many advantages over traditional storage media. Their high storage density, potentially low maintenance cost, ease of synthesis, and chemical modification make them an ideal alternative for information storage. To this end, rapid progress has been made over the past decade by exploiting user-defined DNA materials to encode information. In this review, we discuss the most recent advances of DNA-based data storage with a major focus on the challenges that remain in this promising field, including the current intrinsic low speed in data writing and reading and the high cost per byte stored. Alternatively, data storage relying on DNA nanostructures (as opposed to DNA sequence) as well as on other combinations of nanomaterials and biomolecules are proposed with promising technological and economic advantages. In summarizing the advances that have been made and underlining the challenges that remain, we provide a roadmap for the ongoing research in this rapidly growing field, which will enable the development of technological solutions to the global demand for superior storage methodologies.

Structure and Dynamics of dsDNA in Cell-like Environments

Deoxyribonucleic acid (DNA) is a fundamental biomolecule for correct cellular functioning and regulation of biological processes. DNA's structure is dynamic and has the ability to adopt a variety of structural conformations in addition to its most widely known double-stranded DNA (dsDNA) helix structure. Stability and structural dynamics of dsDNA play an important role in molecular biology. In vivo, DNA molecules are folded in a tightly confined space, such as a cell chamber or a channel, and are highly dense in solution; their conformational properties are restricted, which affects their thermodynamics and mechanical properties. There are also many technical medical purposes for which DNA is placed in a confined space, such as gene therapy, DNA encapsulation, DNA mapping, etc. Physiological conditions and the nature of confined spaces have a significant influence on the opening or denaturation of DNA base pairs. In this review, we summarize the progress of research on the stability and dynamics of dsDNA in cell-like environments and discuss current challenges and future directions. We include studies on various thermal and mechanical properties of dsDNA in ionic solutions, molecular crowded environments, and confined spaces. By providing a better understanding of melting and unzipping of dsDNA in different environments, this review provides valuable guidelines for predicting DNA thermodynamic quantities and for designing DNA/RNA nanostructures.

A last-in first-out stack data structure implemented in DNA

DNA-based memory systems are being reported with increasing frequency. However, dynamic DNA data structures able to store and recall information in an ordered way, and able to be interfaced with external nucleic acid computing circuits, have so far received little attention. Here we present an in vitro implementation of a stack data structure using DNA polymers. The stack is able to record combinations of two different DNA signals, release the signals into solution in reverse order, and then re-record. We explore the accuracy limits of the stack data structure through a stochastic rule-based model of the underlying polymerisation chemistry. We derive how the performance of the stack increases with the efficiency of washing steps between successive reaction stages, and report how stack performance depends on the history of stack operations under inefficient washing. Finally, we discuss refinements to improve molecular synchronisation and future open problems in implementing an autonomous chemical data structure.

DNA is becoming increasingly used as a medium to store non-genetic information. Here the authors present a dynamic stack data structure implemented as a DNA polymer chemistry able to record and retrieve signals in a last-in first-out order.

Nucleic Acid Databases and Molecular-Scale Computing

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 databases 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. We survey these recent achievements and discuss alternative routes for overcoming the hurdles of engineering practical DNA storage systems. We also review 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. We highlight several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks. We summarize how 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. We envision these modular primitives could be strategically adapted for sophisticated database operations and massively parallel computations on DNA databases. We also highlight in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. To conclude, we discuss various implications and challenges of DNA-based storage and computing, and we particularly encourage innovative work on bridging these two areas of research to further explore molecular parallelism and near-data processing. Such integrated molecular systems could lead to far-reaching applications in biocomputing, security, and medicine.

Improving the mesoscopic modeling of DNA denaturation dynamics

Although previously developed mesoscopic DNA models have successfully reproduced thermodynamic denaturation data, recent studies show that these overestimate the rate of denaturation by orders of magnitude. Using adapted Peyrard-Bishop-Dauxois (PBD) models, we have calculated the denaturation rates of several DNA hairpins and made comparison with experimental data. We show that the addition of a barrier at the onsite potential of the PBD model gives a more accurate description of the unzipping dynamics of short DNA sequences. The new models provide a refined theoretical insight on the dynamical mechanisms of unzipping which can have implications for the understanding of transcription and replication processes. Still, this class of adapted PBD models seems to have a fundamental limitation which implies that it is not possible to get agreement with available experimental results on the dynamics of long DNA sequences and at the same time maintain the good agreement regarding its thermodynamics. The reason for this is that the denaturation rate of long DNA chains is not dramatically lowered by the additional barrier-as the base-pairs that open are more likely to remain open, facilitating the opening of the full DNA molecule. Some care has to be taken, since experimental techniques suitable to the study of denaturation rates of long sequences seem not to agree with other experimental data on short DNA sequences. Further research, both theoretical and experimental, is therefore needed to resolve these inconsistencies-which will be a starting point for new minimalistic models that are able to describe both thermodynamics and dynamics at a predictive level.

Addressable configurations of DNA nanostructures for rewritable memory

DNA serves as nature's information storage molecule, and has been the primary focus of engineered systems for biological computing and data storage. Here we combine recent efforts in DNA self-assembly and toehold-mediated strand displacement to develop a rewritable multi-bit DNA memory system. The system operates by encoding information in distinct and reversible conformations of a DNA nanoswitch and decoding by gel electrophoresis. We demonstrate a 5-bit system capable of writing, erasing, and rewriting binary representations of alphanumeric symbols, as well as compatibility with 'OR' and 'AND' logic operations. Our strategy is simple to implement, requiring only a single mixing step at room temperature for each operation and standard gel electrophoresis to read the data. We envision such systems could find use in covert product labeling and barcoding, as well as secure messaging and authentication when combined with previously developed encryption strategies. Ultimately, this type of memory has exciting potential in biomedical sciences as data storage can be coupled to sensing of biological molecules.

Complex-shaped three-dimensional multi-compartmental microparticles generated by diffusional and Marangoni microflows in centrifugally discharged droplets

We report a versatile method for the generation of complex-shaped three-dimensional multi-compartmental (3D-MC) microparticles. Complex-shaped microparticles have recently received much attention for potential application in self-assemblies, micromachines, and biomedical and environmental engineering. Here, we have developed a method based on 3D nonequilibrium-induced microflows (Marangoni and diffusional flows) of microdroplets that are discharged from the tip of a thin capillary in a simple centrifugal microfluidic device. The microparticle shapes can be tuned by the partial dissolution of specific compartments and by the deformation of the precursor microdroplets by manipulating the 3D microflows. We believe that this method will have wide applications in nano- and microscience and technologies.

Droplet microfluidics for the study of artificial cells

In this review, we describe recent advances in droplet-based microfluidics technology that can be applied in studies of artificial cells. Artificial cells are simplified models of living cells and provide valuable model platforms designed to reveal the functions of biological systems. The study of artificial cells is promoted by microfluidics technologies, which provide control over tiny volumes of solutions during quantitative chemical experiments and other manipulations. Here, we focus on current and future trends in droplet microfluidics and their applications in studies of artificial cells.

Hexamer oligonucleotide topology and assembly under solution phase NMR and theoretical modeling scrutiny

The entire family of noncomplementary hexamer oligodeoxyribonucleotides d(GCXYGC) (X and Y = A, G, C, or T) were assessed for topological indicators and equilibrium thermodynamics using a priori molecular modeling and solution phase NMR spectroscopy. Feasible modeled hairpin structures formed a basis from which solution structure and equilibria for each oligonucleotide were considered. ¹H and ³¹P variable temperature-dependent (VT) and concentration-dependent NMR data, NMR signal assignments, and diffusion parameters led to d(GCGAGC) and d(GCGGGC) being understood as exceptions within the family in terms of self-association and topological character. A mean diffusion coefficient D(298 K) = (2.0 ± 0.07) × 10⁻¹⁰ m² s⁻¹ was evaluated across all hexamers except for d(GCGAGC) (D(298 K) = 1.7 × 10⁻¹⁰ m² s⁻¹) and d(GCGGGC) (D(298 K) = 1.2 × 10⁻¹⁰ m² s⁻¹). Melting under VT analysis (T(m) = 323 K) combined with supporting NMR evidence confirmed d(GCGAGC) as the shortest tandem sheared GA mismatched duplex. Diffusion measurements were used to conclude that d(GCGGGC) preferentially exists as the shortest stable quadruplex structure. Thermodynamic analysis of all data led to the assertion that, with the exception of XY = GA and GG, the remaining noncomplementary oligonucleotides adopt equilibria between monomer and duplex, contributed largely by monomer random-coil forms. Contrastingly, d(GCGAGC) showed preference for tandem sheared GA mismatch duplex formation with an association constant K = 3.9 × 10⁵M⁻¹. No direct evidence was acquired for hairpin formation in any instance although its potential existence is considered possible for d(GCGAGC) on the basis of molecular modeling studies.

Quantitative design and experimental validation for a single-molecule DNA nanodevice transformable among three structural states

In this work, we report the development and experimental validation of a coupled statistical thermodynamic model allowing prediction of the structural transitions executed by a novel DNA nanodevice, for quantitative operational design. The efficiency of target structure formation by this nanodevice, implemented with a bistable DNA molecule designed to transform between three distinct structures, is modeled by coupling the isolated equilibrium models for the individual structures. A peculiar behavior is predicted for this nanodevice, which forms the target structure within a limited temperature range by sensing thermal variations. The predicted thermal response is then validated via fluorescence measurements to quantitatively assess whether the nanodevice performs as designed. Agreement between predictions and experiment was substantial, with a 0.95 correlation for overall curve shape over a wide temperature range, from 30 C to 90 C. The obtained accuracy, which is comparable to that of conventional melting behavior prediction for DNA duplexes in isolation, ensures the applicability of the coupled model for illustrating general DNA reaction systems involving competitive duplex formation. Finally, tuning of the nanodevice using the current model towards design of a thermal band pass filter to control chemical circuits, as a novel function of DNA nanodevices is proposed.

Retrieval efficiency of DNA-based databases of digital signals

Using DNA to store digital signals, or data in general, offers significant advantages when compared to other media. The DNA molecule, especially in its double-stranded form, is very stable, compact, and inexpensive. In the past, we have shown that DNA can be used to store and retrieve digital signals encoded and stored in DNA. We have also shown that DNA hybridization can be used as a similarity criterion for retrieving digital signals encoded and stored in a DNA database. Retrieval is achieved through hybridization of "query" and "data" DNA molecules. In this paper, we present a mathematical framework to simulate single-query and parallel-query scenarios, and to estimate hybridization efficiency. Our framework allows for exact numerical solutions as well as closed-form approximations under certain conditions. Similarly to the digital domain, we define a DNA SNR measure to assess the performance of the DNA-based retrieval scheme in terms of database size and source statistics. With approximations, we show that the SNR of any finite-sized DNA-based database is upper bounded by the SNR of an infinitely large DNA-based database that has the same source distribution. Computer simulations are presented to validate our results.