Compiler-aided systematic construction of large-scale DNA strand displacement circuits using unpurified components

Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits

Enzyme-Free Nucleic Acid Dynamical Systems

An important goal of synthetic biology is to create biochemical control systems with the desired characteristics from scratch. Srinivas et al. describe the creation of a biochemical oscillator that requires no enzymes or evolved components, but rather is implemented through DNA molecules designed to function in strand displacement cascades. Furthermore, they created a compiler that could translate a formal chemical reaction network into the necessary DNA sequences that could function together to provide a specified dynamic behavior

On the biophysics and kinetics of toehold-mediated DNA strand displacement

Dynamic DNA nanotechnology often uses toehold-mediated strand displacement for controlling reaction kinetics. Although the dependence of strand displacement kinetics on toehold length has been experimentally characterized and phenomenologically modeled, detailed biophysical understanding has remained elusive. Here, we study strand displacement at multiple levels of detail, using an intuitive model of a random walk on a 1D energy landscape, a secondary structure kinetics model with single base-pair steps and a coarse-grained molecular model that incorporates 3D geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Two factors explain the dependence of strand displacement kinetics on toehold length: (i) the physical process by which a single step of branch migration occurs is significantly slower than the fraying of a single base pair and (ii) initiating branch migration incurs a thermodynamic penalty, not captured by state-of-the-art nearest neighbor models of DNA, due to the additional overhang it engenders at the junction. Our findings are consistent with previously measured or inferred rates for hybridization, fraying and branch migration, and they provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems

Compiler-aided systematic construction of large-scale DNA strand displacement circuits using unpurified components

Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits

Verifying chemical reaction network implementations: A pathway decomposition approach

The emerging fields of genetic engineering, synthetic biology, DNA computing, DNA nanotechnology, and molecular programming herald the birth of a new information technology that acquires information by directly sensing molecules within a chemical environment, stores information in molecules such as DNA, RNA, and proteins, processes that information by means of chemical and biochemical transformations, and uses that information to direct the manipulation of matter at the nanometer scale. To scale up beyond current proof-of-principle demonstrations, new methods for managing the complexity of designed molecular systems will need to be developed. Here we focus on the challenge of verifying the correctness of molecular implementations of abstract chemical reaction networks, where operation in a well-mixed “soup” of molecules is stochastic, asynchronous, concurrent, and often involves multiple intermediate steps in the implementation, parallel pathways, and side reactions. This problem relates to the verification of Petri nets, but existing approaches are not sufficient for providing a single guarantee covering an infinite set of possible initial states (molecule counts) and an infinite state space potentially explored by the system given any initial state. We address these issues by formulating a new theory of pathway decomposition that provides an elegant formal basis for comparing chemical reaction network implementations, and we present an algorithm that computes this basis. Our theory naturally handles certain situations that commonly arise in molecular implementations, such as what we call “delayed choice,” that are not easily accommodated by other approaches. We further show how pathway decomposition can be combined with weak bisimulation to handle a wider class that includes most currently known enzyme-free DNA implementation techniques. We anticipate that our notion of logical equivalence between chemical reaction network implementations will be valuable for other molecular implementations such as biochemical enzyme systems, and perhaps even more broadly in concurrency theory

Stochastic Simulation of the Kinetics of Multiple Interacting Nucleic Acid Strands

DNA nanotechnology is an emerging field which utilizes the unique structural properties of nucleic acids in order to build nanoscale devices, such as logic gates, motors, walkers, and algorithmic structures. Predicting the structure and interactions of a DNA device requires good modeling of both the thermodynamics and the kinetics of the DNA strands within the system. The kinetics of a set of DNA strands can be modeled as a continuous time Markov process through the state space of all secondary structures. The primary means of exploring the kinetics of a DNA system is by simulating trajectories through the state space and aggregating data over many such trajectories. We expand on previous work by extending the thermodynamics and kinetics models to handle multiple strands in a fixed volume, and show that the new models are consistent with previous models. We developed data structures and algorithms that allow us to take advantage of local properties of secondary structure, improving the efficiency of the simulator so that we can handle larger systems. The new kinetic parameters in our model were calibrated by analyzing simulator results on experimental systems that measure basic kinetic rates of various processes. Finally, we apply the new simulator to explore a case study on toehold-mediated four-way branch migration.</p

Verifying chemical reaction network implementations: A pathway decomposition approach

The emerging fields of genetic engineering, synthetic biology, DNA computing, DNA nanotechnology, and molecular programming herald the birth of a new information technology that acquires information by directly sensing molecules within a chemical environment, stores information in molecules such as DNA, RNA, and proteins, processes that information by means of chemical and biochemical transformations, and uses that information to direct the manipulation of matter at the nanometer scale. To scale up beyond current proof-of-principle demonstrations, new methods for managing the complexity of designed molecular systems will need to be developed. Here we focus on the challenge of verifying the correctness of molecular implementations of abstract chemical reaction networks, where operation in a well-mixed “soup” of molecules is stochastic, asynchronous, concurrent, and often involves multiple intermediate steps in the implementation, parallel pathways, and side reactions. This problem relates to the verification of Petri nets, but existing approaches are not sufficient for providing a single guarantee covering an infinite set of possible initial states (molecule counts) and an infinite state space potentially explored by the system given any initial state. We address these issues by formulating a new theory of pathway decomposition that provides an elegant formal basis for comparing chemical reaction network implementations, and we present an algorithm that computes this basis. Our theory naturally handles certain situations that commonly arise in molecular implementations, such as what we call “delayed choice,” that are not easily accommodated by other approaches. We further show how pathway decomposition can be combined with weak bisimulation to handle a wider class that includes most currently known enzyme-free DNA implementation techniques. We anticipate that our notion of logical equivalence between chemical reaction network implementations will be valuable for other molecular implementations such as biochemical enzyme systems, and perhaps even more broadly in concurrency theory

Engineering DNA-Based Self-Assembly Systems to Produce Nanostructures and Chemical Patterns

While commonly known as a material that stores biological information essential for life, few realize that deoxyribonucleic acid (DNA) is also a wonderful building (i.e., physical structures) and computing material. The field of DNA nanotechnology aims to use DNA primarily to build and control matter on the nanoscale. In 2006, a technique known as DNA origami was developed, which allows for the formation of about any shape on the nanoscale. Such DNA origami have been used in many applications: nanodevices, nanotubes, nanoreactors. However, the small surface area of the origami often limits its usefulness. One promising method for building large (micron-sized) DNA origami structures is to self-assemble multiple origami components into well-defined structures. To date, however, such structures suffer low yields, long reaction times and require experimental optimization with no guiding principles. One primary reason is that a governing theory and experimental measurements behind such a self-assembly process are lacking. In this work, we develop coarse-grained computational simulations to describe and understand the self-assembly of finite-sized, multicomponent complexes (e.g., nine different DNA-origami components that form a square grid complex). To help inform the model, we experimentally investigate how various interface architectures between two self-assembling DNA origami components affect the reaction kinetics and thermodynamics. We further develop the accuracy of our simulations by incorporating these measurements and other thermodynamic measurements from our group and implement a computational algorithm that optimizes the interaction strengths between self-assembling components for reaction efficiency (i.e., speed and yield of the complex). With these experimentally-informed simulations, we suggest design improvements and provide yield predictions to an experimentally demonstrated tetrameric complex. Finally, with the overarching idea of using DNA-based components to self-assemble to produce ordered structures and patterns, we build a reaction-diffusion system whose reactions are programmed using DNA strand displacement and diffusion which occurs in a hydrogel, wherein patterns develop, and liquid reservoirs, which are used to supply the high energy components. With this reaction-diffusion system we create stable (i.e., unchanging in space and time) one and two-dimensional patterns of DNA molecules with millimeter-scale features

DESIGN AND APPLICATIONS OF DNA-BASED DEVICES FOR SELF-ASSEMBLY, MOLECULAR CIRCUITS, AND SOFT MATERIALS

Biologically inspired synthetic materials have led to novel technologies due of their ability to sense, influence, or adapt to their environment. One way to build these materials and devices is to utilize the high sequence specificity and innate biocompatibility of DNA. While once considered as a material useful for only storing genetic information, DNA-based devices are now being realized as molecular tools in fields such as therapeutics, diagnostics, regenerative medicine, and soft robotics. In this dissertation, we investigate the use of DNA to build programmable tools to control self-assembly, implement molecular computation, and direct material change processes. DNA origami nanostructures are useful tools for controlling the spatial patterns of proteins, nanoparticles, and fluorophores because they contain hundreds of independently functionalizable locations that can be engineered with nanoscale precision. However, the addressable surface area is currently limited by the size of single origami structures, and efficient, high-yield self-assembly of multiple origami into higher-order assemblies continues to be a challenge. To investigate the factors important for heterogeneous self-assembly of multiple origami, we experimentally measure the equilibrium distribution of four origami tiles in the monomer, intermediate, and final tetramer states as a function of temperature. We find that the thermodynamics of the self-assembly process is determined by the binding interface between origami. Simulations of the assembly kinetics suggest assembly occurs primarily via hierarchical pathways. Next, we engineer a DNA-based timer circuit that can be used in computational devices for molecular release or material control. The circuit releases target DNA sequences into solution at a programmable time with a tunable, constant rate. Multiple timer circuits can operate simultaneously, each releasing their target sequences at independent rates and times. We further develop the utility of the timer and similar DNA-based circuits as a means to control molecular events in biological environments, such as serum-supplemented cell media, where DNA-degrading nucleases can reduce the functional stability and lifetime of DNA-based devices. By implementing DNA circuit-protective design principles and by adding screening molecules to reduce nuclease activity, the functional lifetime of simple DNA circuits can be significantly increased. We develop a model by fitting parameters for reactions between nucleases and simple DNA circuits. Using the model, we can qualitatively predict the behavior of more complex circuits: multiple circuits in series and circuits containing competitive reactions. Finally, we investigate how DNA-based circuits can be used to trigger the high-degree swelling response of DNA-crosslinked metamorphic hydrogels. By coupling signal amplification to the triggering process, we demonstrate modular control over the timescale and degree of swelling. Further, we show control over the identity of the trigger molecule using molecular translators and computational controllers capable of converting complex chemical inputs into mechanical actuation