Kinetic Control of Nucleic Acid Strand Displacement Reactions

Nucleic acids are information-dense, programmable polymers that can be engineered into primers, probes, molecular motors, and signal amplification circuits for computation, diagnostic, and therapeutic purposes. Signal amplification circuits increase the signal-to-noise ratio of target nucleic acids in the absence of enzymes and thermal cycling. Amplification is made possible via toehold mediated strand displacement – a process where one nucleic acid strand binds to a nucleation site on a complementary helix, which then displaces one of the two strands in a nucleic acid complex. When compared to polymerase chain reactions (PCR), the sensitivity and stability of toehold-mediated strand displacement reactions suffer from circuit leakage – reactions of the system in the absence of an initiator. Presented here, from a materials science and engineering perspective, defect engineering has improved the leakage performance of model strand displacement systems made from DNA. Engineered defects used in this study included mismatched base pairs and alternative nucleic acids – both of which are known to impact the stability of hybridization. To identify sources of leakage in a model signal amplification circuit, availability was defined as the probability that a DNA base (A.T.C.G) was unpaired at equilibrium. This design metric was calculated using NUPACK, a thermodynamic modeling tool. To further understand the relationship between leakage rates and secondary structures, mutual availability was defined as the sum of all pairwise products of the availabilities of the corresponding bases in solution. This thermodynamic analysis yielded rational design principles for how to minimize leakage by as much as 4-fold by site-specifically introducing mismatched base pairs into DNA duplex regions. To further reduce leakage, chemically modified locked nucleic acids (LNAs) were site-specifically introduced into a model DNA strand displacement system. Briefly described, LNAs are geometrically restricted RNA analogues with enhanced thermo-mechanical stability towards their complement base. When compared to a DNA control with identical sequences, the leakage exhibited by a hybrid DNA/LNA system was reduced from 1.48 M-1s-1 (for the DNA system) to 0.03 M-1s-1. In addition, the signal-to-noise ratio increased ~50-fold for a similar hybrid system. This research provides insight into the sources of leakage in DNA strand-displacement systems, as well as how to maximize strand-displacement performance via the selective introduction of hybridization defects. Rational design of future nucleic acid signal amplification circuits will lead to broader applications in a variety of fields that range from DNA computation to point-of-care diagnostics and therapeutics

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

Computing Properties of Thermodynamic Binding Networks: An Integer Programming Approach

The thermodynamic binding networks (TBN) model was recently developed as a tool for studying engineered molecular systems. The TBN model allows one to reason about their behavior through a simplified abstraction that ignores details about molecular composition, focusing on two key determinants of a system's energetics common to any chemical substrate: how many molecular bonds are formed, and how many separate complexes exist in the system. We formulate as an integer program the NP-hard problem of computing stable configurations of a TBN (a.k.a., minimum energy: those that maximize the number of bonds and complexes). We provide open-source software that solves these formulations, and give empirical evidence that this approach enables dramatically faster computation of TBN stable configurations than previous approaches based on SAT solvers. Our setup can also reason about TBNs in which some molecules have unbounded counts. These improvements in turn allow us to efficiently automate verification of desired properties of practical TBNs. Finally, we show that the TBN's Graver basis (a kind of certificate of optimality in integer programming) has a natural interpretation as the "fundamental components" out of which locally minimal energy configurations are composed. This characterization helps verify correctness of not only stable configurations, but entire "kinetic pathways" in a TBN

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

Improving the Selectivity and Reducing the Leakage of DNA Strand Displacement Systems

Because of the elegance of Watson-Crick base pairing and the programmability of toehold-mediated strand displacement, DNA is a model material for designing, building, and testing molecular assemblies. DNA assemblies are categorized as structural when they are at thermodynamic equilibrium and dynamic when they are not. Through programmed perturbations, metastable assemblies perform physical, chemical, and computational work. When integrated into a diagnostic package, disease-specific nucleic acid sequences can be identified, amplified, and analyzed via standard DNA nanotechnology rules. In order for these rules to make an impact, two critical challenges in the field have been undertaken in this dissertation. First, the selectivity to distinguish an on-target sequence from off-target sequences, with a resolution of a single-nucleotide mutation, has been explored by site-specifically integrating locked nucleic acids into DNA sequences. Locked nucleic acids are RNA analogues that have higher thermal and hence mechanical stability than RNA and DNA. Second, the initiation of metastable chemical reaction networks, in the absence of on-target sequences, has been explored to suppress network leakage; which is the single greatest problem in dynamic DNA nanotechnology. To address this challenge, original catalytic substrates were designed, built, and tested to increase the energy barrier of the leakage reactions without sacrificing the performance of the favorable catalytic reactions. The experimental results showed that site-specific integration of LNA into DNA sequences improved the sequence selectivity by over 2 orders of magnitude. They also showed that network leakage could be suppressed by 2 orders of magnitude by decoupling the leakage pathway from the catalytic pathway in the original catalytic substrates. When combined, these results constitute a substantial contribution to the field of dynamic DNA nanotechnology and represent important steps towards the creation of low-cost, early-stage diagnostic tools for difficult to detect diseases such as lung, breast, and pancreatic cancers

Functional nucleic acids as substrate for information processing

Information processing applications driven by self-assembly and conformation dynamics of nucleic acids are possible. These underlying paradigms (self-assembly and conformation dynamics) are essential for natural information processors as illustrated by proteins. A key advantage in utilising nucleic acids as information processors is the availability of computational tools to support the design process. This provides us with a platform to develop an integrated environment in which an orchestration of molecular building blocks can be realised. Strict arbitrary control over the design of these computational nucleic acids is not feasible. The microphysical behaviour of these molecular materials must be taken into consideration during the design phase. This thesis investigated, to what extent the construction of molecular building blocks for a particular purpose is possible with the support of a software environment. In this work we developed a computational protocol that functions on a multi-molecular level, which enable us to directly incorporate the dynamic characteristics of nucleic acids molecules. To allow the implementation of this computational protocol, we developed a designer that able to solve the nucleic acids inverse prediction problem, not only in the multi-stable states level, but also include the interactions among molecules that occur in each meta-stable state. The realisation of our computational protocol are evaluated by generating computational nucleic acids units that resembles synthetic RNA devices that have been successfully implemented in the laboratory. Furthermore, we demonstrated the feasibility of the protocol to design various types of computational units. The accuracy and diversity of the generated candidates are significantly better than the best candidates produced by conventional designers. With the computational protocol, the design of nucleic acid information processor using a network of interconnecting nucleic acids is now feasible

Dynamic DNA Nanotechnology for Probing Single Nucleotide Variants and DNA Modifications

In the last decades, various DNA hybridization probes have been developed that attempt to conquer the challenge of single-nucleotide-variants (SNVs) detection. Even though a powerful toolbox including the toehold-exchange reaction, the dynamic ‘sink’ design, and the polymerase chain reaction (PCR) has been built, it still faces practical problems. For example, the natural DNA is usually in double-stranded form whereas most hybridization probes aim for single-stranded targets; the concentration of extracted DNA samples is totally unknown thus may lay outside the optimal design of probes/primers. To achieve ultra-high sensitivity and specificity, expensive and sophisticated machines such as digital droplet PCR and next-generation-sequencing may be inapplicable in rural areas. Therefore, the quantitative PCR method is still the gold standard for clinical tests. Thus motivated, my PhD career was mainly focused on the fundamental understanding of the challenges in SNVs discrimination and developing robust, versatile, and user-friendly probes/strategies. In this thesis, Chapter 1 provides a general introduction of dynamic DNA nanotechnology and its representative applications in discriminating SNVs. Chapter 2 to 4 describe three completed projects that aim to understand the thermodynamic and kinetic properties of strand displacement reactions and to circumvent the challenges of discriminating SNVs through finely tuned probes/assays