DNA Hydrogels with Programmable Condensation, Expansion, and Degradation for Molecular Carriers.

Molecular carriers are necessary for the controlled release of drugs and genes to achieve the desired therapeutic outcomes. DNA hydrogels can be a promising candidate in this application with their distinctive sequence-dependent programmability, which allows precise encapsulation of specific cargo molecules and stimuli-responsive release of them at the target. However, DNA hydrogels are inherently susceptible to the degradation of nucleases, making them vulnerable in a physiological environment. To be an effective molecular carrier, DNA hydrogels should be able to protect encapsulated cargo molecules until they reach the target and release them once they are reached. Here, we develop a simple way of controlling the enzyme resistance of DNA hydrogels for cargo protection and release by using cation-mediated condensation and expansion. We found that DNA hydrogels condensed by spermine are highly resistant to enzymatic degradation. They become degradable again if expanded back to their original, uncondensed state by sodium ions interfering with the interaction between spermine and DNA. These controllable condensation, expansion, and degradation of DNA hydrogels pave the way for the development of DNA hydrogels as an effective molecular carrier.

Prediction of DNA origami shape using graph neural network.

Unlike proteins, which have a wealth of validated structural data, experimentally or computationally validated DNA origami datasets are limited. Here we present a graph neural network that can predict the three-dimensional conformation of DNA origami assemblies both rapidly and accurately. We develop a hybrid data-driven and physics-informed approach for model training, designed to minimize not only the data-driven loss but also the physics-informed loss. By employing an ensemble strategy, the model can successfully infer the shape of monomeric DNA origami structures almost in real time. Further refinement of the model in an unsupervised manner enables the analysis of supramolecular assemblies consisting of tens to hundreds of DNA blocks. The proposed model enables an automated inverse design of DNA origami structures for given target shapes. Our approach facilitates the real-time virtual prototyping of DNA origami, broadening its design space.

Controlling Chiroptical Responses via Chemo-Mechanical Deformation of DNA Origami Structures.

DNA origami-based templates have been widely used to fabricate chiral plasmonic metamaterials due to their precise control of the placement of nanoparticles (NPs) in a desired configuration. However, achieving various chiroptical responses inevitably requires a change in the structure of DNA origami-based templates or binding sites on them, leading to the use of significantly different sets of DNA strands. Here, we propose an approach to controlling various chiroptical responses with a single DNA origami design using its chemo-mechanical deformation induced by DNA intercalators. The chiroptical response could be finely tuned by altering the concentration of intercalators only. The silver (Ag) enhancement was used to amplify the chiroptical signal by enlarging NPs and to maintain it by stiffening the template DNA structure. Furthermore, the sensitivity in the chiroptical signal change to the concentration of intercalators could be modulated by the type of intercalator, the mixture of two intercalators, and the stiffness of DNA origami structures. This approach would be useful in a variety of optical applications that require programmed spatial modification of chiroptical responses.

Precise and selective macroscopic assembly of a dual lock-and-key structured hydrogel.

Macroscopic assembly offers immense potential for constructing complex systems due to the high design flexibility of the building blocks. In such assembly systems, hydrogels are promising candidates for building blocks due to their versatile chemical compositions and ease of property tuning. However, two major challenges must be addressed to facilitate application in a broader context: the precision of assembly and the quantity of orthogonally matching pairs must both be increased. Although previous studies have attempted to address these challenges, none have successfully dealt with both simultaneously. Here, we propose topology-based design criteria for the selective assembly of hydrogel building blocks. By introducing the dual lock-and-key structures, we demonstrate highly precise assembly exclusively between the matching pairs. We establish principles for selecting multiple orthogonally matching pairs and achieve selective assembly involving simple one-to-one matching and complex assemblies with multiple orthogonal matching points. Moreover, by harnessing hydrogel tunability and the abundance of matching pairs, we synthesize complementary single-stranded structures for programmable assembly and successfully assemble them in the correct order. Finally, we demonstrate a hydrogel-based self-assembled logic gate system, including a YES gate, an OR gate, and an AND gate. The output is generated only when the corresponding inputs are provided according to each logic.

A computational model for structural dynamics and reconfiguration of DNA assemblies.

Recent advances in constructing a structured DNA assembly whose configuration can be dynamically changed in response to external stimuli have demanded the development of an efficient computational modeling approach to expedite its design process. Here, we present a computational framework capable of analyzing both equilibrium and non-equilibrium dynamics of structured DNA assemblies at the molecular level. The framework employs Langevin dynamics with structural and hydrodynamic finite element models that describe mechanical, electrostatic, base stacking, and hydrodynamic interactions. Equilibrium dynamic analysis for various problems confirms the solution accuracy at a near-atomic resolution, comparable to molecular dynamics simulations and experimental measurements. Furthermore, our model successfully simulates a long-time-scale close-to-open-to-close dynamic reconfiguration of the switch structure in response to changes in ion concentration. We expect that the proposed model will offer a versatile way of designing responsive and reconfigurable DNA machines.

Harnessing a paper-folding mechanism for reconfigurable DNA origami.

The paper-folding mechanism has been widely adopted in building of reconfigurable macroscale systems because of its unique capabilities and advantages in programming variable shapes and stiffness into a structure1-5. However, it has barely been exploited in the construction of molecular-level systems owing to the lack of a suitable design principle, even though various dynamic structures based on DNA self-assembly6-9 have been developed10-23. Here we propose a method to harness the paper-folding mechanism to create reconfigurable DNA origami structures. The main idea is to build a reference, planar wireframe structure24 whose edges follow a crease pattern in paper folding so that it can be folded into various target shapes. We realized several paper-like folding and unfolding patterns using DNA strand displacement25 with high yield. Orthogonal folding, repeatable folding and unfolding, folding-based microRNA detection and fluorescence signal control were demonstrated. Stimuli-responsive folding and unfolding triggered by pH or light-source change were also possible. Moreover, by employing hierarchical assembly26 we could expand the design space and complexity of the paper-folding mechanism in a highly programmable manner. Because of its high programmability and scalability, we expect that the proposed paper-folding-based reconfiguration method will advance the development of complex molecular systems.

A hybrid framework to predict ski jumping forces by combining data-driven pose estimation and model-based force calculation.

The aim of this paper is to propose a hybrid framework that combines a data-driven pose estimation with model-based force calculation in order to predict the ski jumping force from a recorded motion video. A skeletal model consisting of five joints (ear, hip, knee, ankle, and toe) and four rigid segments (head/arm/trunk or HAT, thigh, shank, and foot) connecting each joint is developed. The joint forces are calculated from the dynamic equilibrium equations, which requires the time history of joint coordinates. They are estimated from a recorded motion video using a deep neural network for pose estimation trained with human motion data. Joint coordinates can be obtained by the proposed deep neural network directly from images of jumping motion without using any markers. The validity and usefulness of the proposed method are confirmed in lab experiments. Further, our method is practically applicable to the study in a real competition environment because it is not required to attach any sensor or marker to athletes.Highlights A method to predict the ski jumping force from a recorded motion video is proposed.It combines a data-driven pose estimation with a model-based force calculation.The proposed method does not require any markers and sensors to be attached to athletes.In a laboratory environment, the relative error in the maximum jumping force is less than 7%.The method can be easily applied to a field study in a real competition environment.

Engineering DNA-based synthetic condensates with programmable material properties, compositions, and functionalities.

Biomolecular condensates participate in diverse cellular processes, ranging from gene regulation to stress survival. Bottom-up engineering of synthetic condensates advances our understanding of the organizing principle of condensates. It also enables the synthesis of artificial systems with novel functions. However, building synthetic condensates with a predictable organization and function remains challenging. Here, we use DNA as a building block to create synthetic condensates that are assembled through phase separation. The programmability of intermolecular interactions between DNA molecules enables the control over various condensate properties including assembly, composition, and function. Similar to the way intracellular condensates are organized, DNA clients are selectively partitioned into cognate condensates. We demonstrate that the synthetic condensates can accelerate DNA strand displacement reactions and logic gate operation by concentrating specific reaction components. We envision that the DNA-based condensates could help the realization of the high-order functions required to build more life-like artificial systems.

Peptide-DNA origami as a cryoprotectant for cell preservation.

Cryopreservation of cells is essential for the conservation and cold chain of bioproducts and cell-based medicines. Here, we demonstrate that self-assembled DNA origami nanostructures have a substantial ability to protect cells undergoing freeze-thaw cycles; thereby, they can be used as cryoprotectant agents, because their nanoscale morphology and ice-philicity are tailored. In particular, a single-layered DNA origami nanopatch functionalized with antifreezing threonine peptides enabled the viability of HSC-3 cells to reach 56% after 1 month of cryopreservation, surpassing dimethyl sulfoxide, which produced 38% viability. It also exhibited minimal dependence on the cryopreservation period and freezing conditions. We attribute this outcome to the fact that the peptide-functionalized DNA nanopatches exert multisite actions for the retardation of ice growth in both intra- and extracellular regions and the protection of cell membranes during cryopreservation. This discovery is expected to deepen our fundamental understanding of cell survival under freezing environment and affect current cryopreservation technologies.

Direct visualization of floppy two-dimensional DNA origami using cryogenic electron microscopy.

Two-dimensional (2D) DNA origami that is capable of self-assembling into complex 2D and 3D geometries pave the way for a bottom-up synthesis for various applications in nano/biotechnology. Here, we directly visualized the aqueous structure of 2D DNA origami cross-tiles and their assemblies using cryogenic electron microscopy. We uncovered flexible arms in cross-tile monomers and designated inter-tile folding. In addition, we observed the formation of clusters and stacks of DNA cross-tiles in solution, which could potentially affect the interaction and assembly of DNA origami. Finally, we quantitatively evaluated the flexibility of DNA origami in solution using finite element analysis. Our discovery has laid the foundation for investigating the dynamic structures of 2D DNA origami assemblies in solution, providing insights regarding the self-assembly and self-replication mechanisms of 2D DNA origami.

Formation of non-base-pairing DNA microgels using directed phase transition of amphiphilic monomers.

Programmability of DNA sequences enables the formation of synthetic DNA nanostructures and their macromolecular assemblies such as DNA hydrogels. The base pair-level interaction of DNA is a foundational and powerful mechanism to build DNA structures at the nanoscale; however, its temperature sensitivity and weak interaction force remain a barrier for the facile and scalable assembly of DNA structures toward higher-order structures. We conducted this study to provide an alternative, non-base-pairing approach to connect nanoscale DNA units to yield micrometer-sized gels based on the sequential phase transition of amphiphilic unit structures. Strong electrostatic interactions between DNA nanostructures and polyelectrolyte spermines led to the formation of giant phase-separated aggregates of monomer units. Gelation could be initiated by the addition of NaCl, which weakened the electrostatic DNA-spermine interaction while attractive interactions between cholesterols created stable networks by crosslinking DNA monomers. In contrast to the conventional DNA gelation techniques, our system used solid aggregates as a precursor for DNA microgels. Therefore, in situ gelation could be achieved by depositing aggregates on the desired substrate and subsequently initiating a phase transition. Our approach can expand the utility and functionality of DNA hydrogels by using more complex nucleic acid assemblies as unit structures and combining the technique with top-down microfabrication methods.

Predicting the Free-Form Shape of Structured DNA Assemblies from Their Lattice-Based Design Blueprint.

Structured DNA assemblies have been designed primarily on a three-dimensional lattice because it is easy to arrange and cross-link the helices there. However, when we design free-form structures including wireframes and topologically closed circular objects on a lattice, artificially stretched bonds connecting bases are inevitably and arbitrarily formed. They often lead to nonconvergence or convergence to a wrong configuration in computational analysis to predict the equilibrium shape of the structure when started from its lattice-based configuration, which hinders the design process of free-form structures. Here, we present a computational procedure enabling the shape prediction of free-form structures from their lattice-based design blueprint without any convergence issue. It automatically partitions the structure into substructures and relocates them into a new configuration. When the analysis for calculating the equilibrium shape begins from this configuration, no convergence issue occurs because substructures and stretched bonds connecting them do not overlap and intertwine each other during analysis. Using the proposed approach, we could obtain the free-form shape of a comprehensive set of wireframe and circular structures accurately and quickly. We further demonstrated that it also facilitated a design of wireframe structures with nonstraight edges.

Accelerating AFM Characterization via Deep-Learning-Based Image Super-Resolution.

Atomic force microscopy (AFM) is one of the most popular imaging and characterizing methods applicable to a wide range of nanoscale material systems. However, high-resolution imaging using AFM generally suffers from a low scanning yield due to its method of raster scanning. Here, a systematic method of data acquisition and preparation combined with a deep-learning-based image super-resolution, enabling rapid AFM characterization with accuracy, is proposed. Its application to measuring the geometrical and mechanical properties of structured DNA assemblies reveals that around a tenfold reduction in AFM imaging time can be achieved without significant loss of accuracy. Through a transfer learning strategy, it can be efficiently customized for a specific target sample on demand.

Characterizing and Harnessing the Mechanical Properties of Short Single-Stranded DNA in Structured Assemblies.

Precise engineering of DNA structures is of growing interest to solve challenging problems in biomolecular applications and beyond. The introduction of single-stranded DNA (ssDNA) into the DNA structure can play a pivotal role in providing high controllability of critical structural features. Herein, we present a computational model of ssDNA with structural applications to harness its characteristics. The nonlinear properties of nucleotide gaps are systematically characterized to construct a structural model of the ssDNA across length scales with the incorporation of a finite element framework. The proposed method shows the programmability of structural bending, twisting, and persistence length by implementing the ssDNA in various DNA structures with experimental validation. Our results have significant implications for DNA nanotechnology in expanding the boundary of design and analysis of structural shape and stiffness.

Modulating the chemo-mechanical response of structured DNA assemblies through binding molecules.

Recent advances in DNA nanotechnology led the fabrication and utilization of various DNA assemblies, but the development of a method to control their global shapes and mechanical flexibilities with high efficiency and repeatability is one of the remaining challenges for the realization of the molecular machines with on-demand functionalities. DNA-binding molecules with intercalation and groove binding modes are known to induce the perturbation on the geometrical and mechanical characteristics of DNA at the strand level, which might be effective in structured DNA assemblies as well. Here, we demonstrate that the chemo-mechanical response of DNA strands with binding ligands can change the global shape and stiffness of DNA origami nanostructures, thereby enabling the systematic modulation of them by selecting a proper ligand and its concentration. Multiple DNA-binding drugs and fluorophores were applied to straight and curved DNA origami bundles, which demonstrated a fast, recoverable, and controllable alteration of the bending persistence length and the radius of curvature of DNA nanostructures. This chemo-mechanical modulation of DNA nanostructures would provide a powerful tool for reconfigurable and dynamic actuation of DNA machineries.

The flexibility-based modulation of DNA nanostar phase separation.

Phase separation of biomolecules plays key roles in physiological compartmentalization as well as pathological aggregation. A deeper understanding of biomolecular phase separation requires dissection of a relation between intermolecular interactions and resulting phase behaviors. DNA nanostars, multivalent DNA assemblies of which sticky ends define attractive interactions, represent an ideal system to probe this fundamental relation governing phase separation processes. Here, we use DNA nanostars to systematically study how structural flexibility exhibited by interacting species impacts their phase behaviors. We design multiple nanostars with a varying degree of flexibility using single-stranded gaps of different lengths in the arm of each nanostar unit. We find that structural flexibility drastically alters the phase diagram of DNA nanostars in such a way that the phase separation of more flexible structures is strongly inhibited. This result is not due to self-inhibition from the loss of valency but rather ascribed to a generic flexibility-driven change in the thermodynamics of the system. Our work provides not only potential regulatory mechanisms cells may exploit to dynamically control intracellular phase separation but also a route to build synthetic systems of which assembly can be controlled in a signal dependent manner.

Programming ultrasensitive threshold response through chemomechanical instability.

The ultrasensitive threshold response is ubiquitous in biochemical systems. In contrast, achieving ultrasensitivity in synthetic molecular structures in a controllable way is challenging. Here, we propose a chemomechanical approach inspired by Michell's instability to realize it. A sudden reconfiguration of topologically constrained rings results when the torsional stress inside reaches a critical value. We use DNA origami to construct molecular rings and then DNA intercalators to induce torsional stress. Michell's instability is achieved successfully when the critical concentration of intercalators is applied. Both the critical point and sensitivity of this ultrasensitive threshold reconfiguration can be controlled by rationally designing the cross-sectional shape and mechanical properties of DNA rings.

Rapid Computational Analysis of DNA Origami Assemblies at Near-Atomic Resolution.

Structural DNA nanotechnology plays an ever-increasing role in advanced biomolecular applications. Here, we present a computational method to analyze structured DNA assemblies rapidly at near-atomic resolution. Both high computational efficiency and molecular-level accuracy are achieved by developing a multiscale analysis framework. The sequence-dependent relative geometry and mechanical properties of DNA motifs are characterized by the all-atom molecular dynamics simulation and incorporated into the structural finite element model successfully without significant loss of atomic information. The proposed method can predict the three-dimensional shape, equilibrium dynamic properties, and mechanical rigidities of monomeric to hierarchically assembled DNA structures at near-atomic resolution without adjusting any model parameters. The calculation takes less than only 15 min for most origami-scale DNA nanostructures consisting of 7000-8000 base-pairs. Hence, it is expected to be highly utilized in an iterative design-analysis-revision process for structured DNA assemblies.

Design Approaches and Computational Tools for DNA Nanostructures.

Designing a structure in nanoscale with desired shape and properties has been enabled by structural DNA nanotechnology. Design strategies in this research field have evolved to interpret various aspects of increasingly more complex nanoscale assembly and to realize molecular-level functionality by exploring static to dynamic characteristics of the target structure. Computational tools have naturally been of significant interest as they are essential to achieve a fine control over both shape and physicochemical properties of the structure. Here, we review the basic design principles of structural DNA nanotechnology together with its computational analysis and design tools.

Tailoring the Mechanical Stiffness of DNA Nanostructures Using Engineered Defects.

As scaffolded DNA origami enables the construction of diverse DNA nanostructures with predefined shapes, precise modulation of their mechanical stiffness remains challenging. We demonstrate a modular design method to widely and precisely control the mechanical flexibility of scaffolded DNA origami nanostructures while maintaining their overall structural integrity and geometric characteristics. Individually engineered defects that are short single-stranded DNA (ssDNA) gaps could reduce up to 70% of the bending stiffness of DNA origami constructs with different cross-sectional shapes. We further developed a computational analysis platform predicting the bending stiffness of a defect-engineered DNA nanostructure quickly during the design process, to offer an efficient way of designing various DNA constructs with required mechanical stiffness in a desired shape for a targeted function.