Programmable patterns in a DNA-based reaction-diffusion system

Fueling DNA Self-Assembly via Gel-Released Regulators

The development of responsive, multicomponent molecular materials requires means to physically separate yet easily couple distinct processes. Here we demonstrate methods to use molecules and reactions loaded into microliter-sized polyacrylamide hydrogels (mini-gels) to control the dynamic self-assembly of DNA nanotubes. We first characterize the UV-mediated release of DNA molecules from mini-gels, changing diffusion rates and minimizing spontaneous leakage of DNA. We then demonstrate that mini-gels can be used as compartments for storage and release of DNA that mediates the assembly or disassembly of DNA nanotubes in a one-pot process and that the speed of DNA release is controlled by the mini-gel porosity. With this approach, we achieve control of assembly and disassembly of nanotubes with distinct kinetics, including a finite delay that is obtained by loading distinct DNA regulators into distinct mini-gels. We finally show that mini-gels can also host and localize enzymatic reactions, by transcribing RNA regulators from synthetic genes loaded in the mini-gels, with diffusion of RNA to the aqueous phase resulting in the activation of self-assembly. Our experimental data are recapitulated by a mathematical model that describes the diffusion of DNA molecules from the gel phase to the aqueous phase in which they control self-assembly of nanotubes. Looking forward, DNA-loaded mini-gels may be further miniaturized and patterned to build more sophisticated storage compartments for use within multicomponent, complex biomolecular materials relevant for biomedical applications and artificial life.

Steady-State Operation of a Cell-Free Genetic Band-Detection Circuit

Pattern formation processes play a decisive role during embryogenesis and involve the precise spatial and temporal orchestration of intricate gene regulatory processes. Synthetic gene circuits modeled after their biological counterparts can be used to investigate such processes under well-controlled conditions and may, in the future, be utilized for autonomous position determination in synthetic biological materials. Here, we investigated a three-node feed-forward gene regulatory circuit in vitro that generates three distinct fluorescent outputs in response to varying concentrations of a single externally supplied morphogen. The circuit acts as a band detector for the morphogen concentration and, in a spatial context, could serve as a stripe-forming gene circuit. We simulated the behavior of the genetic circuit in the presence of a morphogen gradient using a system of ordinary differential equations and determined optimal parameters for stripe-pattern formation using an evolutionary algorithm. To analyze the subcircuits of the system, we conducted cell-free characterization experiments and finally tested the whole genetic circuit in nanoliter-scale microfluidic flow reactors that provided a continuous supply of cell extract and metabolites and allowed removal of degradation products. To make use of the widely employed promoters P_LlacO-1 and P_LtetO-1 in our design, we removed LacI from our bacterial cell extract by genome engineering Escherichia coli using a pORTMAGE workflow. Our results show that the band-detector works as designed when operated out of equilibrium within the flow reactors. On the other hand, subcircuits of the system and the whole circuit fail to generate the desired gene expression response when operated in a closed reactor. Our work thus underlines the importance of out-of-equilibrium operation of complex gene circuits, which cannot settle to a steady-state expression pattern within the finite lifetime of a cell-free expression system.

Spatial programming of self-organizing chemical systems using sustained physicochemical gradients from reaction, diffusion and hydrodynamics

Living organisms employ chemical self-organization to build structures, and inspire new strategies to design synthetic systems that spontaneously take a particular form, via a combination of integrated chemical reactions, assembly pathways and physicochemical processes. However, spatial programmability that is required to direct such self-organization is a challenge to control. Thermodynamic equilibrium typically brings about a homogeneous solution, or equilibrium structures such as supramolecular complexes and crystals. This perspective addresses out-of-equilibrium gradients that can be driven by coupling chemical reaction, diffusion and hydrodynamics, and provide spatial differentiation in the self-organization of molecular, ionic or colloidal building blocks in solution. These physicochemical gradients are required to (1) direct the organization from the starting conditions (e.g. a homogeneous solution), and (2) sustain the organization, to prevent it from decaying towards thermodynamic equilibrium. We highlight four different concepts that can be used as a design principle to establish such self-organization, using chemical reactions as a driving force to sustain the gradient and, ultimately, program the characteristics of the gradient: (1) reaction-diffusion coupling; (2) reaction-convection; (3) the Marangoni effect and (4) diffusiophoresis. Furthermore, we outline their potential as attractive pathways to translate chemical reactions and molecular/colloidal assembly into organization of patterns in solution, (dynamic) self-assembled architectures and collectively moving swarms at the micro-, meso- and macroscale, exemplified by recent demonstrations in the literature.

Reaction–Diffusion Patterning of DNA-Based Artificial Cells

Biological cells display complex internal architectures with distinct micro environments that establish the chemical heterogeneity needed to sustain cellular functions. The continued efforts to create advanced cell mimics, namely, artificial cells, demands strategies for constructing similarly heterogeneous structures with localized functionalities. Here, we introduce a platform for constructing membraneless artificial cells from the self-assembly of synthetic DNA nanostructures in which internal domains can be established thanks to prescribed reaction–diffusion waves. The method, rationalized through numerical modeling, enables the formation of up to five distinct concentric environments in which functional moieties can be localized. As a proof-of-concept, we apply this platform to build DNA-based artificial cells in which a prototypical nucleus synthesizes fluorescent RNA aptamers that then accumulate in a surrounding storage shell, thus demonstrating the spatial segregation of functionalities reminiscent of that observed in biological cells.

Chemical Reaction Networks’ Programming for Solving Equations

The computational ability of the chemical reaction networks (CRNs) using DNA as the substrate has been verified previously. To solve more complex computational problems and perform the computational steps as expected, the practical design of the basic modules of calculation and the steps in the reactions have become the basic requirements for biomolecular computing. This paper presents a method for solving nonlinear equations in the CRNs with DNA as the substrate. We used the basic calculation module of the CRNs with a gateless structure to design discrete and analog algorithms and realized the nonlinear equations that could not be solved in the previous work, such as exponential, logarithmic, and simple triangle equations. The solution of the equation uses the transformation method, Taylor expansion, and Newton iteration method, and the simulation verified this through examples. We used and improved the basic calculation module of the CRN++ programming language, optimized the error in the basic module, and analyzed the error’s variation over time.

Synthetic cell-based materials extract positional information from morphogen gradients

Biomaterials composed of synthetic cells have the potential to adapt and differentiate guided by physicochemical environmental cues. Inspired by biological systems in development, which extract positional information (PI) from morphogen gradients in the presence of uncertainties, we here investigate how well synthetic cells can determine their position within a multicellular structure. To calculate PI, we created and analyzed a large number of synthetic cellular assemblies composed of emulsion droplets connected via lipid bilayer membranes. These droplets contained cell-free feedback gene circuits that responded to gradients of a genetic inducer acting as a morphogen. PI is found to be limited by gene expression noise and affected by the temporal evolution of the morphogen gradient and the cell-free expression system itself. The generation of PI can be rationalized by computational modeling of the system. We scale our approach using three-dimensional printing and demonstrate morphogen-based differentiation in larger tissue-like assemblies.

Molecular communication relays for dynamic cross-regulation of self-sorting fibrillar self-assemblies

Structures in living systems cross-regulate via exchange of molecular information to assemble or disassemble on demand and in a coordinated, signal-triggered fashion. DNA strand displacement (DSD) reaction networks allow rational design of signaling and feedback loops, but combining DSD with structural nanotechnology to achieve self-reconfiguring hierarchical system states is still in its infancy. We introduce modular DSD networks with increasing amounts of regulatory functions, such as negative feedback, signal amplification, and signal thresholding, to cross-regulate the transient polymerization/depolymerization of two self-sorting DNA origami nanofibrils and nanotubes. This is achieved by concatenation of the DSD network with molecular information relays embedded on the origami tips. The two origamis exchange information and display programmable transient states observable by TEM and fluorescence spectroscopy. The programmability on the DSD and the origami level is a viable starting point toward more complex lifelike behavior of colloidal multicomponent systems featuring advanced signal processing functions.

Exploiting the fundamentals of biological organization for the advancement of biofabrication

The field of biofabrication continues to progress, offering higher levels of spatial control, reproducibility, and functionality. However, we remain far from recapitulating what nature has achieved. Biological systems such as tissues and organs are assembled from the bottom-up through coordinated supramolecular and cellular processes that result in their remarkable structures and functionalities. In this perspective, we propose that incorporating such biological assembling mechanisms within fabrication techniques, offers an opportunity to push the boundaries of biofabrication. We dissect these mechanisms into distinct biological organization principles (BOPs) including self-assembly, compartmentalization, diffusion-reaction, disorder-to-order transitions, and out-of-equilibrium processes. We highlight recent work demonstrating the viability and potential of these approaches to enhance scalability, reproducibility, vascularization, and biomimicry; as well as current challenges to overcome.

Cascaded pattern formation in hydrogel medium using the polymerisation approach

Reaction-diffusion systems are one of the models of the formation process with various patterns found in nature. Inspired by natural pattern formation, several methods for designing artificial chemical reaction-diffusion systems have been proposed. DNA is a suitable building block to build such artificial systems owing to its programmability. Previously, we reported a line pattern formed due to the reaction and diffusion of synthetic DNA; however, the width of the line was too wide to be used for further applications such as parallel and multi-stage pattern formations. Here, we propose a novel method to programme a reaction-diffusion system in a hydrogel medium to realise a sharp line capable of forming superimposed and cascaded patterns. The mechanism of this system utilises a two-segment polymerisation of DNA caused by hybridisation. To superimpose the system, we designed orthogonal DNA sequences that formed two lines in different locations on the hydrogel. Additionally, we designed a reaction to release DNA and form a cascade pattern, in which the third line appears between the two lines. To explain the mechanism of our system, we modelled the system as partial differential equations, whose simulation results agreed well with the experimental data. Our method to fabricate cascaded patterns may inspire combinations of DNA-based technologies and expand the applications of artificial reaction-diffusion systems.

One-Component DNA Mechanoprobes for Facile Mechanosensing in Photopolymerized Hydrogels and Elastomers

DNA mechanosensors offer unique properties for mechano-adaptive and self-reporting materials, such as programmable bond strength and geometrical strain response, tunable fluorescent strain sensing, interfacing to biological systems, and the ability to store mechanical information. However, the facile incorporation of advanced DNA motifs into polymer networks and achieving robustness in application settings remain difficult. Herein, we introduce one-component DNA mechanoprobes that can be easily polymerized into polymer hydrogels and even elastomers to allow strain-induced fluorescence sensing. The all-in-one mechanoprobe contains a DNA hairpin for programmable force sensing, an internal fluorophore-quencher pair as a reporter, and methacrylamide groups on both ends for rapid and facile photopolymerization into networks based on the nontoxic water-soluble monomer methoxy triethylene glycol acrylate (mTEGA). In addition to mechanosensing hydrogels, we utilize the low T_g of p(mTEGA) to develop the first bulk elastomer materials with DNA force sensors, which show high elasticity and stronger mechanofluorescence. The system makes decisive steps forward for DNA-based mechanoprobes by overcoming the classical multicomponent design of such probes, allowing photopolymerization useful for the design of complex objects or even 3D printing and demonstrating that such motifs may even be useful in dry bulk materials.

Accelerating the Finite-Element Method for Reaction-Diffusion Simulations on GPUs with CUDA

DNA nanotechnology offers a fine control over biochemistry by programming chemical reactions in DNA templates. Coupled to microfluidics, it has enabled DNA-based reaction-diffusion microsystems with advanced spatio-temporal dynamics such as traveling waves. The Finite Element Method (FEM) is a standard tool to simulate the physics of such systems where boundary conditions play a crucial role. However, a fine discretization in time and space is required for complex geometries (like sharp corners) and highly nonlinear chemistry. Graphical Processing Units (GPUs) are increasingly used to speed up scientific computing, but their application to accelerate simulations of reaction-diffusion in DNA nanotechnology has been little investigated. Here we study reaction-diffusion equations (a DNA-based predator-prey system) in a tortuous geometry (a maze), which was shown experimentally to generate subtle geometric effects. We solve the partial differential equations on a GPU, demonstrating a speedup of ∼100 over the same resolution on a 20 cores CPU.