Scalable, Time-Responsive, Digital, Energy-Efficient Molecular Circuits using DNA Strand Displacement

We propose a novel theoretical biomolecular design to implement any Boolean circuit using the mechanism of DNA strand displacement. The design is scalable: all species of DNA strands can in principle be mixed and prepared in a single test tube, rather than requiring separate purification of each species, which is a barrier to large-scale synthesis. The design is time-responsive: the concentration of output species changes in response to the concentration of input species, so that time-varying inputs may be continuously processed. The design is digital: Boolean values of wires in the circuit are represented as high or low concentrations of certain species, and we show how to construct a single-input, single-output signal restoration gate that amplifies the difference between high and low, which can be distributed to each wire in the circuit to overcome signal degradation. This means we can achieve a digital abstraction of the analog values of concentrations. Finally, the design is energy-efficient: if input species are specified ideally (meaning absolutely 0 concentration of unwanted species), then output species converge to their ideal concentrations at steady-state, and the system at steady-state is in (dynamic) equilibrium, meaning that no energy is consumed by irreversible reactions until the input again changes. Drawbacks of our design include the following. If input is provided non-ideally (small positive concentration of unwanted species), then energy must be continually expended to maintain correct output concentrations even at steady-state. In addition, our fuel species - those species that are permanently consumed in irreversible reactions - are not "generic"; each gate in the circuit is powered by its own specific type of fuel species. Hence different circuits must be powered by different types of fuel. Finally, we require input to be given according to the dual-rail convention, so that an input of 0 is specified not only by the absence of a certain species, but by the presence of another. That is, we do not construct a "true NOT gate" that sets its output to high concentration if and only if its input's concentration is low. It remains an open problem to design scalable, time-responsive, digital, energy-efficient molecular circuits that additionally solve one of these problems, or to prove that some subset of their resolutions are mutually incompatible.Comment: version 2: the paper itself is unchanged from version 1, but the arXiv software stripped some asterisk characters out of the abstract whose purpose was to highlight words. These characters have been replaced with underscores in version 2. The arXiv software also removed the second paragraph of the abstract, which has been (attempted to be) re-inserted. Also, although the secondary subject is "Soft Condensed Matter", this classification was chosen by the arXiv moderators after submission, not chosen by the authors. The authors consider this submission to be a theoretical computer science paper

Selection platforms for directed evolution in synthetic biology

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules – gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function – be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code

Antimicrobial Nanoplexes meet Model Bacterial Membranes: the key role of Cardiolipin

Antimicrobial resistance to traditional antibiotics is a crucial challenge of medical research. Oligonucleotide therapeutics, such as antisense or Transcription Factor Decoys (TFDs), have the potential to circumvent current resistance mechanisms by acting on novel targets. However, their full translation into clinical application requires efficient delivery strategies and fundamental comprehension of their interaction with target bacterial cells. To address these points, we employed a novel cationic bolaamphiphile that binds TFDs with high affinity to form self-assembled complexes (nanoplexes). Confocal microscopy revealed that nanoplexes efficiently transfect bacterial cells, consistently with biological efficacy on animal models. To understand the factors affecting the delivery process, liposomes with varying compositions, taken as model synthetic bilayers, were challenged with nanoplexes and investigated with Scattering and Fluorescence techniques. Thanks to the combination of results on bacteria and synthetic membrane models we demonstrate for the first time that the prokaryotic-enriched anionic lipid Cardiolipin (CL) plays a key-role in the TFDs delivery to bacteria. Moreover, we can hypothesize an overall TFD delivery mechanism, where bacterial membrane reorganization with permeability increase and release of the TFD from the nanoplexes are the main factors. These results will be of great benefit to boost the development of oligonucleotides-based antimicrobials of superior efficacy

DNA for nano-bio scale computation of chemical formalisms using Higher Order Logic (HOL) and analysis using an interdisciplinary approach

Bio-molecular computing, 'computations performed by bio-molecules', is already challenging traditional approaches to computation both theoretically and technologically. Often placed within the wider context of ´bio-inspired' or 'natural' or even 'unconventional' computing, the study of natural and artificial molecular computations is adding to our understanding of biology, physical sciences and computer science well beyond the framework of existing design and implementation paradigms. In this introduction, We wish to outline the current scope of the field and assemble some basic arguments that, bio-molecular computation is of central importance to computer science, physical sciences and biology using HOL - Higher Order Logic. HOL is used as the computational tool in our R&D work. DNA was analyzed as a chemical computing engine, in our effort to develop novel formalisms to understand the molecular scale bio-chemical computing behavior using HOL. In our view, our focus is one of the pioneering efforts in this promising domain of nano-bio scale chemical information processing dynamics.Universidade Estadual Paulista Júlio de Mesquita Filho Laboratório de Plasmas TecnológicosUniversidade Estadual Paulista Júlio de Mesquita Filho Laboratório de Plasmas Tecnológico

Controlling the rate of organic reactions: rational design of allosteric Diels-Alderase ribozymes

Allosteric mechanisms are widely used in nature to control the rates of enzymatic reactions, but little is known about RNA catalysts controlled by these principles. The only natural allosteric ribozyme reported to date catalyzes an RNA cleavage reaction, and so do almost all artificial systems. RNA has, however, been shown to accelerate a much wider range of chemical reactions. Here we report that RNA catalysts for organic reactions can be put under the stringent control of effector molecules by straight-forward rational design. This approach uses known RNA sequences with catalytic and ligand-binding properties, and exploits weakly conserved sequence elements and available structural information to induce the formation of alternative, catalytically inactive structures. The potential and general applicability is demonstrated by the design of three different systems in which the rate of a catalytic carbon–carbon bond forming reaction is positively regulated up to 2100-fold by theophylline, tobramycin and a specific mRNA sequence, respectively. Although smaller in size than a tRNA, all three ribozymes show typical features of allosteric metabolic enzymes, namely high rate acceleration and tight allosteric regulation. Not only do these findings demonstrate RNA's power as a catalyst, but also highlight on RNA's capabilities as signaling components in regulatory networks

An analysis of simple computational strategies to facilitate the design of functional molecular information processors

BACKGROUND: Biological macromolecules (DNA, RNA and proteins) are capable of processing physical or chemical inputs to generate outputs that parallel conventional Boolean logical operators. However, the design of functional modules that will enable these macromolecules to operate as synthetic molecular computing devices is challenging. RESULTS: Using three simple heuristics, we designed RNA sensors that can mimic the function of a seven-segment display (SSD). Ten independent and orthogonal sensors representing the numerals 0 to 9 are designed and constructed. Each sensor has its own unique oligonucleotide binding site region that is activated uniquely by a specific input. Each operator was subjected to a stringent in silico filtering. Random sensors were selected and functionally validated via ribozyme self cleavage assays that were visualized via electrophoresis. CONCLUSIONS: By utilising simple permutation and randomisation in the sequence design phase, we have developed functional RNA sensors thus demonstrating that even the simplest of computational methods can greatly aid the design phase for constructing functional molecular devices. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1297-x) contains supplementary material, which is available to authorized users

Logic integration of mRNA signals by an RNAi-based molecular computer

Synthetic in vivo molecular ‘computers’ could rewire biological processes by establishing programmable, non-native pathways between molecular signals and biological responses. Multiple molecular computer prototypes have been shown to work in simple buffered solutions. Many of those prototypes were made of DNA strands and performed computations using cycles of annealing-digestion or strand displacement. We have previously introduced RNA interference (RNAi)-based computing as a way of implementing complex molecular logic in vivo. Because it also relies on nucleic acids for its operation, RNAi computing could benefit from the tools developed for DNA systems. However, these tools must be harnessed to produce bioactive components and be adapted for harsh operating environments that reflect in vivo conditions. In a step toward this goal, we report the construction and implementation of biosensors that ‘transduce’ mRNA levels into bioactive, small interfering RNA molecules via RNA strand exchange in a cell-free Drosophila embryo lysate, a step beyond simple buffered environments. We further integrate the sensors with our RNAi ‘computational’ module to evaluate two-input logic functions on mRNA concentrations. Our results show how RNA strand exchange can expand the utility of RNAi computing and point toward the possibility of using strand exchange in a native biological setting

A Modern Mode of Activation for Nucleic Acid Enzymes

Through evolution, enzymes have developed subtle modes of activation in order to ensure the sufficiently high substrate specificity required by modern cellular metabolism. One of these modes is the use of a target-dependent module (i.e. a docking domain) such as those found in signalling kinases. Upon the binding of the target to a docking domain, the substrate is positioned within the catalytic site. The prodomain acts as a target-dependent module switching the kinase from an off state to an on state. As compared to the allosteric mode of activation, there is no need for the presence of a third partner. None of the ribozymes discovered to date have such a mode of activation, nor does any other known RNA. Starting from a specific on/off adaptor for the hepatitis delta virus ribozyme, that differs but has a mechanism reminiscent of this signalling kinase, we have adapted this mode of activation, using the techniques of molecular engineering, to both catalytic RNAs and DNAs exhibiting various activities. Specifically, we adapted three cleaving ribozymes (hepatitis delta virus, hammerhead and hairpin ribozymes), a cleaving 10-23 deoxyribozyme, a ligating hairpin ribozyme and an artificially selected capping ribozyme. In each case, there was a significant gain in terms of substrate specificity. Even if this mode of control is unreported for natural catalytic nucleic acids, its use needs not be limited to proteinous enzymes. We suggest that the complexity of the modern cellular metabolism might have been an important selective pressure in this evolutionary process

A thermodynamic approach to designing structure-free combinatorial DNA word sets

An algorithm is presented for the generation of sets of non-interacting DNA sequences, employing existing thermodynamic models for the prediction of duplex stabilities and secondary structures. A DNA ‘word’ structure is employed in which individual DNA ‘words’ of a given length (e.g. 12mer and 16mer) may be concatenated into longer sequences (e.g. four tandem words and six tandem words). This approach, where multiple word variants are used at each tandem word position, allows very large sets of non-interacting DNA strands to be assembled from combinations of the individual words. Word sets were generated and their figures of merit are compared to sets as described previously in the literature (e.g. 4, 8, 12, 15 and 16mer). The predicted hybridization behavior was experimentally verified on selected members of the sets using standard UV hyperchromism measurements of duplex melting temperatures (T(m)s). Additional experimental validation was obtained by using the sequences in formulating and solving a small example of a DNA computing problem

DNA nanomachines.

We are learning to build synthetic molecular machinery from DNA. This research is inspired by biological systems in which individual molecules act, singly and in concert, as specialized machines: our ambition is to create new technologies to perform tasks that are currently beyond our reach. DNA nanomachines are made by self-assembly, using techniques that rely on the sequence-specific interactions that bind complementary oligonucleotides together in a double helix. They can be activated by interactions with specific signalling molecules or by changes in their environment. Devices that change state in response to an external trigger might be used for molecular sensing, intelligent drug delivery or programmable chemical synthesis. Biological molecular motors that carry cargoes within cells have inspired the construction of rudimentary DNA walkers that run along self-assembled tracks. It has even proved possible to create DNA motors that move autonomously, obtaining energy by catalysing the reaction of DNA or RNA fuels