Catalyzed relaxation of a metastable DNA fuel

Practically all of life's molecular processes, from chemical synthesis to replication, involve enzymes that carry out their functions through the catalytic transformation of metastable fuels into waste products. Catalytic control of reaction rates will prove to be as useful and ubiquitous in nucleic-acid-based engineering as it is in biology. Here we report a metastable DNA "fuel" and a corresponding DNA "catalyst" that improve upon the original hybridization-based catalyst system (Turberfield et al. Phys. Rev. Lett. 90, 118102-1118102-4) by more than 2 orders of magnitude. This is achieved by identifying and purifying a fuel with a kinetically trapped metastable configuration consisting of a "kissing loop" stabilized by flanking helical domains; the catalyst strand acts by opening a helical domain and allowing the complex to relax to its ground state by a multistep pathway. The improved fuel/catalyst system shows a roughly 5000-fold acceleration of the uncatalyzed reaction, with each catalyst molecule capable of turning over in excess of 40 substrates. With k_(cat)/K_M ≈ 10^7/M/min, comparable to many protein enzymes and ribozymes, this fuel system becomes a viable component enabling future DNA-based synthetic molecular machines and logic circuits. As an example, we designed and characterized a signal amplifier based on the fuel-catalyst system. The amplifier uses a single strand of DNA as input and releases a second strand with unrelated sequence as output. A single input strand can catalytically trigger the release of more than 10 output strands

Robustness and modularity properties of a non-covalent DNA catalytic reaction

The biophysics of nucleic acid hybridization and strand displacement have been used for the rational design of a number of nanoscale structures and functions. Recently, molecular amplification methods have been developed in the form of non-covalent DNA catalytic reactions, in which single-stranded DNA (ssDNA) molecules catalyze the release of ssDNA product molecules from multi-stranded complexes. Here, we characterize the robustness and specificity of one such strand displacement-based catalytic reaction. We show that the designed reaction is simultaneously sensitive to sequence mutations in the catalyst and robust to a variety of impurities and molecular noise. These properties facilitate the incorporation of strand displacement-based DNA components in synthetic chemical and biological reaction networks

Probabilistic switching circuits in DNA

A natural feature of molecular systems is their inherent stochastic behavior. A fundamental challenge related to the programming of molecular information processing systems is to develop a circuit architecture that controls the stochastic states of individual molecular events. Here we present a systematic implementation of probabilistic switching circuits, using DNA strand displacement reactions. Exploiting the intrinsic stochasticity of molecular interactions, we developed a simple, unbiased DNA switch: An input signal strand binds to the switch and releases an output signal strand with probability one-half. Using this unbiased switch as a molecular building block, we designed DNA circuits that convert an input signal to an output signal with any desired probability. Further, this probability can be switched between 2^n different values by simply varying the presence or absence of n distinct DNA molecules. We demonstrated several DNA circuits that have multiple layers and feedback, including a circuit that converts an input strand to an output strand with eight different probabilities, controlled by the combination of three DNA molecules. These circuits combine the advantages of digital and analog computation: They allow a small number of distinct input molecules to control a diverse signal range of output molecules, while keeping the inputs robust to noise and the outputs at precise values. Moreover, arbitrarily complex circuit behaviors can be implemented with just a single type of molecular building block

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro

Non-natural protein-protein communication mediated by a DNA-based, antibody-responsive device

We report here the rational design and optimization of an antibody responsive, DNA-based device that enables communication between pairs of otherwise non-interacting proteins. The device is designed to recognize and bind a specific antibody and, in response, undergo a conformational change that leads to the release of a DNA strand, termed the “translator,” that regulates the activity of a downstream target protein. As proof of principle, we demonstrate antibody-induced control of the proteins thrombin and Taq DNA polymerase. The resulting strategy is versatile and, in principle, can be easily adapted to control artificial protein-protein communication in artificial regulatory networks