Nucleic acids for the rational design of reaction circuits

Molecular Computation for Molecular Classification

DNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal-processing capabilities. Whether influenced by the silicon world or inspired by natural computation, molecular programming has gained attention for diagnosis applications. Of particular interest for this review, molecular classifiers have shown promising results for disease pattern recognition and sample classification. Because both input integration and computation are performed in a single tube, at the molecular level, this low-cost approach may come as a complementary tool to molecular profiling strategies, where all biomarkers are quantified independently using high-tech instrumentation. After introducing the elementary components of molecular classifiers, some of their experimental implementations are discussed either using digital Boolean logic or analog neural network architectures.

Isothermal digital detection of microRNAs using background-free molecular circuit

MicroRNAs, a class of transcripts involved in the regulation of gene expression, are emerging as promising disease-specific biomarkers accessible from tissues or bodily fluids. However, their accurate quantification from biological samples remains challenging. We report a sensitive and quantitative microRNA detection method using an isothermal amplification chemistry adapted to a droplet digital readout. Building on molecular programming concepts, we design a DNA circuit that converts, thresholds, amplifies, and reports the presence of a specific microRNA, down to the femtomolar concentration. Using a leak absorption mechanism, we were able to suppress nonspecific amplification, classically encountered in other exponential amplification reactions. As a result, we demonstrate that this isothermal amplification scheme is adapted to digital counting of microRNAs: By partitioning the reaction mixture into water-in-oil droplets, resulting in single microRNA encapsulation and amplification, the method provides absolute target quantification. The modularity of our approach enables to repurpose the assay for various microRNA sequences.

rEXPAR: An Isothermal Amplification Scheme That Is Robust to Autocatalytic Parasites

In the absence of DNA, a solution containing the four deoxynucleotidetriphosphates (dNTPs), a DNA polymerase, and a nicking enzyme generates a self-replicating mixture of DNA species called parasite. Parasites are problematic in template-based isothermal amplification schemes such as EXPAR as well as in related molecular programming approaches, such as the PEN DNA toolbox. Here we show that using a nicking enzyme with only three letters (C, G, T) in the top strand of its recognition site, such as Nb.BssSI, allows us to change the sequence design of EXPAR templates in a way that prevents the formation of parasites when dATP is removed from the solution. This method allows us to make the EXPAR reaction robust to parasite contamination, a common feature in the laboratory, while keeping it compatible with PEN programs, which we demonstrate by engineering a parasite-proof bistable reaction network.

Renewable Time-Responsive DNA Circuits

DNA devices have been shown to be capable of evaluating Boolean logic. Several robust designs for DNA circuits have been demonstrated. Some prior DNA-based circuits are use-once circuits since the gate motifs of the DNA circuits get permanently destroyed as a side effect of the computation, and hence cannot respond correctly to subsequent changes in inputs. Other DNA-based circuits use a large reservoir of buffered gates to replace the working gates of the circuit and can be used to drive a finite number of computation cycles. In many applications of DNA circuits, the inputs are inherently asynchronous, and this necessitates that the DNA circuits be asynchronous: the output must always be correct regardless of differences in the arrival time of inputs. This paper demonstrates: 1) renewable DNA circuits, which can be manually reverted to their original state by addition of DNA strands, and 2) time-responsive DNA circuits, where if the inputs change over time, the DNA circuit can recompute the output correctly based on the new inputs, that are manually added after the system has been reset. The properties of renewable, asynchronous, and time-responsiveness appear to be central to molecular-scale systems; for example, self-regulation in cellular organisms.

Computer-aided biochemical programming of synthetic microreactors as diagnostic devices

Biological systems have evolved efficient sensing and decision-making mechanisms to maximize fitness in changing molecular environments. Synthetic biologists have exploited these capabilities to engineer control on information and energy processing in living cells. While engineered organisms pose important technological and ethical challenges, de novo assembly of non-living biomolecular devices could offer promising avenues toward various real-world applications. However, assembling biochemical parts into functional information processing systems has remained challenging due to extensive multidimensional parameter spaces that must be sampled comprehensively in order to identify robust, specification compliant molecular implementations. We introduce a systematic methodology based on automated computational design and microfluidics enabling the programming of synthetic cell-like microreactors embedding biochemical logic circuits, or protosensors, to perform accurate biosensing and biocomputing operations in vitro according to temporal logic specifications. We show that proof-of-concept protosensors integrating diagnostic algorithms detect specific patterns of biomarkers in human clinical samples. Protosensors may enable novel approaches to medicine and represent a step toward autonomous micromachines capable of precise interfacing of human physiology or other complex biological environments, ecosystems, or industrial bioprocesses.

Spatiotemporal control of DNA-based chemical reaction network via electrochemical activation in microfluidics

In recent years, DNA computing frameworks have been developed to create dynamical systems which can be used for information processing. These emerging synthetic biochemistry tools can be leveraged to gain a better understanding of fundamental biology but can also be implemented in biosensors and unconventional computing. Most of the efforts so far have focused on changing the topologies of DNA molecular networks or scaling them up. Several issues have thus received little attention and remain to be solved to turn them into real life technologies. In particular, the ability to easily interact in real-time with them is a key requirement. The previous attempts to achieve this aim have used microfluidic approaches, such as valves, which are cumbersome. We show that electrochemical triggering using DNA-grafted micro-fabricated gold electrodes can be used to give instructions to these molecular systems. We demonstrate how this approach can be used to release at specific times and locations DNA- based instructions. In particular, we trigger reaction-diffusion autocatalytic fronts in microfluidic channels. While limited by the stability of the Au-S bond, this easy to implement, versatile and scalable technique can be used in any biology laboratory to provide new ways to interact with any DNA-based computing framework.

Biomimetic Molecular Signaling using DNA Walkers on Microparticles

We report the release of catalytic DNA walkers from hydrogel microparticles and the detection of those walkers by substrate-coated microparticles. This might be considered a synthetic biology analog of molecular signal release and reception. One type of particles was coated with components of a DNA one-step strand displacement (OSD) reaction to release the walker. A second type of particle was coated with substrate (or "track") for the molecular walker. We distinguish these particle types using fluorescence barcoding: we synthesized and distinguished multiple particle types with multicolor fluorescence microscopy and automated image analysis software. This represents a step toward amplified, multiplex, and microscopically localized detection based on DNA nanotechnology.

Microscopic agents programmed by DNA circuits

Information stored in synthetic nucleic acids sequences can be used in vitro to create complex reaction networks with precisely programmed chemical dynamics. Here, we scale up this approach to program networks of microscopic particles (agents) dispersed in an enzymatic solution. Agents may possess multiple stable states, thus maintaining a memory and communicate by emitting various orthogonal chemical signals, while also sensing the behaviour of neighbouring agents. Using this approach, we can produce collective behaviours involving thousands of agents, for example retrieving information over long distances or creating spatial patterns. Our systems recapitulate some fundamental mechanisms of distributed decision making and morphogenesis among living organisms and could find applications in cases where many individual clues need to be combined to reach a decision, for example in molecular diagnostics.

Self-Assembling Molecular Logic Gates Based on DNA Crossover Tiles

DNA-based computational hardware has attracted ever-growing attention due to its potential to be useful in the analysis of complex mixtures of biological markers. Here we report the design of self-assembling logic gates that recognize DNA inputs and assemble into crossover tiles when the output signal is high; the crossover structures disassemble to form separate DNA stands when the output is low. The output signal can be conveniently detected by fluorescence using a molecular beacon probe as a reporter. AND, NOT, and OR logic gates were designed. We demonstrate that the gates can connect to each other to produce other logic functions.

Antibody-controlled actuation of DNA-based molecular circuits

DNA-based molecular circuits allow autonomous signal processing, but their actuation has relied mostly on RNA/DNA-based inputs, limiting their application in synthetic biology, biomedicine and molecular diagnostics. Here we introduce a generic method to translate the presence of an antibody into a unique DNA strand, enabling the use of antibodies as specific inputs for DNA-based molecular computing. Our approach, antibody-templated strand exchange (ATSE), uses the characteristic bivalent architecture of antibodies to promote DNA-strand exchange reactions both thermodynamically and kinetically. Detailed characterization of the ATSE reaction allowed the establishment of a comprehensive model that describes the kinetics and thermodynamics of ATSE as a function of toehold length, antibody-epitope affinity and concentration. ATSE enables the introduction of complex signal processing in antibody-based diagnostics, as demonstrated here by constructing molecular circuits for multiplex antibody detection, integration of multiple antibody inputs using logic gates and actuation of enzymes and DNAzymes for signal amplification.

Catalytic nucleic acids (DNAzymes) as functional units for logic gates and computing circuits: from basic principles to practical applications

This feature article addresses the implementation of catalytic nucleic acids as functional units for the construction of logic gates and computing circuits, and discusses the future applications of these systems. The assembly of computational modules composed of DNAzymes has led to the operation of a universal set of logic gates, to field programmable logic gates and computing circuits, to the development of multiplexers/demultiplexers, and to full-adder systems. Also, DNAzyme cascades operating as logic gates and computing circuits were demonstrated. DNAzyme logic systems find important practical applications. These include the use of DNAzyme-based systems for sensing and multiplexed analyses, for the development of controlled release and drug delivery systems, for regulating intracellular biosynthetic pathways, and for the programmed synthesis and operation of cascades.

Synthesizing Configurable Biochemical Implementation of Linear Systems from Their Transfer Function Specifications

The ability to engineer synthetic systems in the biochemical context is constantly being improved and has a profound societal impact. Linear system design is one of the most pervasive methods applied in control tasks, and its biochemical realization has been proposed by Oishi and Klavins and advanced further in recent years. However, several technical issues remain unsolved. Specifically, the design process is not fully automated from specification at the transfer function level, systems once designed often lack dynamic adaptivity to environmental changes, matching rate constants of reactions is not always possible, and implementation may be approximative and greatly deviate from the specifications. Building upon the work of Oishi and Klavins, this paper overcomes these issues by introducing a design flow that transforms a transfer-function specification of a linear system into a set of chemical reactions, whose input-output response precisely conforms to the specification. This system is implementable using the DNA strand displacement technique. The underlying configurability is embedded into primitive components and template modules, and thus the entire system is adaptive. Simulation of DNA strand displacement implementation confirmed the feasibility and superiority of the proposed synthesis flow.

Nuclease-containing media for resettable operation of DNA logic gates

We designed and tested a system that allows DNA logic gates to respond multiple times to the addition of oligonucleotide inputs. After producing an output signal, the system spontaneously resets to the background state. This system does not require any operator action to achieve reset of a DNA logic gate, and may become useful for construction of reusable DNA-based computational devices.

Single-Molecule Visualization of the Activity of a Zn(2+)-Dependent DNAzyme

We demonstrate the single-molecule imaging of the catalytic reaction of a Zn(2+)-dependent DNAzyme in a DNA origami nanostructure. The single-molecule catalytic activity of the DNAzyme was examined in the designed nanostructure, a DNA frame. The DNAzyme and a substrate strand attached to two supported dsDNA molecules were assembled in the DNA frame in two different configurations. The reaction was monitored by observing the configurational changes of the incorporated DNA strands in the DNA frame. This configurational changes were clearly observed in accordance with the progress of the reaction. The separation processes of the dsDNA molecules, as induced by the cleavage by the DNAzyme, were directly visualized by high-speed atomic force microscopy (AFM). This nanostructure-based AFM imaging technique is suitable for the monitoring of various chemical and biochemical catalytic reactions at the single-molecule level.

Automated design of programmable enzyme-driven DNA circuits

Molecular programming allows for the bottom-up engineering of biochemical reaction networks in a controlled in vitro setting. These engineered biochemical reaction networks yield important insight in the design principles of biological systems and can potentially enrich molecular diagnostic systems. The DNA polymerase-nickase-exonuclease (PEN) toolbox has recently been used to program oscillatory and bistable biochemical networks using a minimal number of components. Previous work has reported the automatic construction of in silico descriptions of biochemical networks derived from the PEN toolbox, paving the way for generating networks of arbitrary size and complexity in vitro. Here, we report an automated approach that further bridges the gap between an in silico description and in vitro realization. A biochemical network of arbitrary complexity can be globally screened for parameter values that display the desired function and combining this approach with robustness analysis further increases the chance of successful in vitro implementation. Moreover, we present an automated design procedure for generating optimal DNA sequences, exhibiting key characteristics deduced from the in silico analysis. Our in silico method has been tested on a previously reported network, the Oligator, and has also been applied to the design of a reaction network capable of displaying adaptation in one of its components. Finally, we experimentally characterize unproductive sequestration of the exonuclease to phosphorothioate protected ssDNA strands. The strong nonlinearities in the degradation of active components caused by this unintended cross-coupling are shown computationally to have a positive effect on adaptation quality.

Designing ordered nucleic acid self-assembly processes

A major goal of self-assembly research is the synthesis of biomolecular structures with diverse, intricate features across multiple length scales. Designing self-assembly processes becomes more difficult as the number of species or target structure size increases. Just as the ordered assembly of a machine or device makes complex manufacturing possible, ordered (or 'algorithmic') biomolecular self-assembly processes could enable the self-assembly of more complex structures. We discuss the design of ordered assembly processes with particular attention to DNA and RNA. The assembly of complexes can be ordered using selective, multivalent interactions or active components that change shape after assembly. The self-assembly of spatial gradients driven by reaction-diffusion can also be ordered. We conclude by considering topics for future research.

Protease-based synthetic sensing and signal amplification

The bottom-up design of protein-based signaling networks is a key goal of synthetic biology; yet, it remains elusive due to our inability to tailor-make signal transducers and receptors that can be readily compiled into defined signaling networks. Here, we report a generic approach for the construction of protein-based molecular switches based on artficially autoinhibited proteases. Using structure-guided design and directed protein evolution, we created signal transducers based on artificially autoinhibited proteases that can be activated following site-specific proteolysis and also demonstrate the modular design of an allosterically regulated protease receptor following recombination with an affinity clamp peptide receptor. Notably, the receptor's mode of action can be varied from >5-fold switch-OFF to >30-fold switch-ON solely by changing the length of the connecting linkers, demonstrating a high functional plasticity not previously observed in naturally occurring receptor systems. We also create an integrated signaling circuit based on two orthogonal autoinhibited protease units that can propagate and amplify molecular queues generated by the protease receptor. Finally, we present a generic two-component receptor architecture based on proximity-based activation of two autoinhibited proteases. Overall, the approach allows the design of protease-based signaling networks that, in principle, can be connected to any biological process.

Computational design of nucleic acid feedback control circuits

The design of synthetic circuits for controlling molecular-scale processes is an important goal of synthetic biology, with potential applications in future in vitro and in vivo biotechnology. In this paper, we present a computational approach for designing feedback control circuits constructed from nucleic acids. Our approach relies on an existing methodology for expressing signal processing and control circuits as biomolecular reactions. We first extend the methodology so that circuits can be expressed using just two classes of reactions: catalysis and annihilation. We then propose implementations of these reactions in three distinct classes of nucleic acid circuits, which rely on DNA strand displacement, DNA enzyme and RNA enzyme mechanisms, respectively. We use these implementations to design a Proportional Integral controller, capable of regulating the output of a system according to a given reference signal, and discuss the trade-offs between the different approaches. As a proof of principle, we implement our methodology as an extension to a DNA strand displacement software tool, thus allowing a broad range of nucleic acid circuits to be designed and analyzed within a common modeling framework.

The emerging age of cell-free synthetic biology

The engineering of and mastery over biological parts has catalyzed the emergence of synthetic biology. This field has grown exponentially in the past decade. As increasingly more applications of synthetic biology are pursued, more challenges are encountered, such as delivering genetic material into cells and optimizing genetic circuits in vivo. An in vitro or cell-free approach to synthetic biology simplifies and avoids many of the pitfalls of in vivo synthetic biology. In this review, we describe some of the innate features that make cell-free systems compelling platforms for synthetic biology and discuss emerging improvements of cell-free technologies. We also select and highlight recent and emerging applications of cell-free synthetic biology.

Synthetic circuit for exact adaptation and fold-change detection

Biological organisms use their sensory systems to detect changes in their environment. The ability of sensory systems to adapt to static inputs allows wide dynamic range as well as sensitivity to input changes including fold-change detection, a response that depends only on fold changes in input, and not on absolute changes. This input scale invariance underlies an important strategy for search that depends solely on the spatial profile of the input. Synthetic efforts to reproduce the architecture and response of cellular circuits provide an important step to foster understanding at the molecular level. We report the bottom-up assembly of biochemical systems that show exact adaptation and fold-change detection. Using a malachite green aptamer as the output, a synthetic transcriptional circuit with the connectivity of an incoherent feed-forward loop motif exhibits pulse generation and exact adaptation. A simple mathematical model was used to assess the amplitude and duration of pulse response as well as the parameter regimes required for fold-change detection. Upon parameter tuning, this synthetic circuit exhibits fold-change detection for four successive rounds of two-fold input changes. The experimental realization of fold-change detection circuit highlights the programmability of transcriptional switches and the ability to obtain predictive dynamical systems in a cell-free environment for technological applications.

Photocleavage control of nucleated DNA nanosystems--the influence of surface strand sterics

We use sterically inaccessible 'seed' strands, released from a surface into solution by photocleavage to initiate a nucleated DNA polymerization reaction. We demonstrate control of the quantity of 'seed' release and that hairpin steric protection of the 'seed' leads to less 'leaky' surfaces. This polymerization is a model system for surface-photocleavage initiation of sub-stoichiometric reaction cascades; these cascades should find use as a component of labs-on-chips capable of bioanalytical and DNA-computing tasks.