Sequence Design for a Test Tube of Interacting Nucleic Acid Strands

RNA-Based Sensor Systems for Affordable Diagnostics in the Age of Pandemics

In the era of the COVID-19 pandemic, the significance of point-of-care (POC) diagnostic tools has become increasingly vital, driven by the need for quick and precise virus identification. RNA-based sensors, particularly toehold sensors, have emerged as promising candidates for POC detection systems due to their selectivity and sensitivity. Toehold sensors operate by employing an RNA switch that changes the conformation when it binds to a target RNA molecule, resulting in a detectable signal. This review focuses on the development and deployment of RNA-based sensors for POC viral RNA detection with a particular emphasis on toehold sensors. The benefits and limits of toehold sensors are explored, and obstacles and future directions for improving their performance within POC detection systems are presented. The use of RNA-based sensors as a technology for rapid and sensitive detection of viral RNA holds great potential for effectively managing (dealing/coping) with present and future pandemics in resource-constrained settings.

DNA Crosslinked Mucin Hydrogels Allow for On-Demand Gel Disintegration and Triggered Particle Release

Whereas hydrogels created from synthetic polymers offer a high level of control over their stability and mechanical properties, their biomedical activity is typically limited. In contrast, biopolymers have evolved over billions of years to integrate a broad range of functionalities into a single design. Thus, biopolymeric hydrogels can show remarkable capabilities such as regulatory behavior, selective barrier properties, or antimicrobial effects. Still, despite their widespread use in numerous biomedical applications, achieving a meticulous control over the physical properties of macroscopic biopolymeric networks remains a challenge. Here, a macroscopic, DNA-crosslinked mucin hydrogel with tunable viscoelastic properties that responds to two types of triggers: temperature alterations and DNA displacement strands, is presented. As confirmed with bulk rheology and single particle tracking, the hybridized base pairs governing the stability of the hydrogel can be opened, thus allowing for a precise control over the hydrogel stiffness and even enabling a full gel-to-sol transition. As those DNA-crosslinked mucin hydrogels possess tunable mechanical properties and can be disintegrated on demand, they can not only be considered for controlled cargo release but may also serve as a role model for the development of smart biomedical materials in applications such as tissue engineering and wound healing.

Estimating RNA Secondary Structure Folding Free Energy Changes with efn2

A number of analyses require estimates of the folding free energy changes of specific RNA secondary structures. These predictions are often based on a set of nearest neighbor parameters that models the folding stability of a RNA secondary structure as the sum of folding stabilities of the structural elements that comprise the secondary structure. In the software suite RNAstructure, the free energy change calculation is implemented in the program efn2. The efn2 program estimates the folding free energy change and the experimental uncertainty in the folding free energy change. It can be run through the graphical user interface for RNAstructure, from the command line, or a web server. This chapter provides detailed protocols for using efn2.

Modified Nucleotides and RNA Structure Prediction

Nucleotide modifications are occurrent in all types of RNA and play an important role in RNA structure formation and stability. Modified bases not only possess the ability to shift the RNA structure ensemble towards desired functional confirmations. By changes in the base pairing partner preference, they may even enlarge or reduce the conformational space, i.e., the number and types of structures the RNA molecule can adopt. However, most methods to predict RNA secondary structure do not provide the means to include the effect of modifications on the result. With the help of a heavily modified transfer RNA (tRNA) molecule, this chapter demonstrates how to include the effect of different base modifications into secondary structure prediction using the ViennaRNA Package. The constructive approach demonstrated here allows for the calculation of minimum free energy structure and suboptimal structures at different levels of modified base support. In particular we, show how to incorporate the isomerization of uridine to pseudouridine ( Ψ ) and the reduction of uridine to dihydrouridine (D).

A highly specific and flexible detection assay using collaborated actions of DNA-processing enzymes for identifying multiple gene expression signatures in breast cancer

Most nucleic acid biosensors employ nucleic acid-processing enzymes to bind, degrade, splice, synthesize, and modify nucleic acids. Utilizing their unique substrate preference, binding mode, and catalytic activity is of great importance in designing nucleic acid biosensors. Combination with DNA-processing enzymes enables them to transform into a new generation of molecular diagnostics tools with enhanced selectivity and sensitivity and reduced reaction time. Here, we report an isothermal amplification strategy by coemploying a structure-specific endonuclease (flap endonuclease 1, FEN1) and a strand-displacing DNA polymerase (Bst DNA polymerase) to detect long RNA targets. This approach couples the FEN1-driven invasive cleavage reaction with toehold-mediated rolling circle amplification (iFEN-tRCA), enabling the highly selective and rapid detection of long RNA targets and offering a detection limit below 10 pM within 1 h. We used two targets, such as human epidermal growth factor receptor 2 (HER2, encoded by ERBB2) and dopamine- and cyclic AMP-regulated phosphoprotein (DARPP, encoded by PPP1R1B), associated with prognosis or response to anticancer therapy. We demonstrated the feasibility and quantitative capability of the iFEN-tRCA assay by assessing the expression of two RNA transcripts (ERBB2 and PPP1R1B) with total RNA extracts purified from human breast cancer cells. Therefore, we envision that the developed assay will provide a suitable prognostic and diagnostic tool for identifying appropriate patients for HER2-targeted therapy and predicting the clinical outcome and occurrence of metastasis relapse in breast cancer.

Cellular Computational Logic Using Toehold Switches

The development of computational logic that carries programmable and predictable features is one of the key requirements for next-generation synthetic biological devices. Despite considerable progress, the construction of synthetic biological arithmetic logic units presents numerous challenges. In this paper, utilizing the unique advantages of RNA molecules in building complex logic circuits in the cellular environment, we demonstrate the RNA-only bitwise logical operation of XOR gates and basic arithmetic operations, including a half adder, a half subtractor, and a Feynman gate, in Escherichia coli. Specifically, de-novo-designed riboregulators, known as toehold switches, were concatenated to enhance the functionality of an OR gate, and a previously utilized antisense RNA strategy was further optimized to construct orthogonal NIMPLY gates. These optimized synthetic logic gates were able to be seamlessly integrated to achieve final arithmetic operations on small molecule inputs in cells. Toehold-switch-based ribocomputing devices may provide a fundamental basis for synthetic RNA-based arithmetic logic units or higher-order systems in cells.

Detection of pks Island mRNAs Using Toehold Sensors in Escherichia coli

Synthetic biologists have applied biomolecular engineering approaches toward the goal of novel biological devices and have shown progress in diverse areas of medicine and biotechnology. Especially promising is the application of synthetic biological devices towards a novel class of molecular diagnostics. As an example, a de-novo-designed riboregulator called toehold switch, with its programmability and compatibility with field-deployable devices showed promising in vitro applications for viral RNA detection such as Zika and Corona viruses. However, the in vivo application of high-performance RNA sensors remains challenging due to the secondary structure of long mRNA species. Here, we introduced ‘Helper RNAs’ that can enhance the functionality of toehold switch sensors by mitigating the effect of secondary structures around a target site. By employing the helper RNAs, previously reported mCherry mRNA sensor showed improved fold-changes in vivo. To further generalize the Helper RNA approaches, we employed automatic design pipeline for toehold sensors that target the essential genes within the pks island, an important target of biomedical research in connection with colorectal cancer. The toehold switch sensors showed fold-changes upon the expression of full-length mRNAs that apparently depended sensitively on the identity of the gene as well as the predicted local structure within the target region of the mRNA. Still, the helper RNAs could improve the performance of toehold switch sensors in many instances, with up to 10-fold improvement over no helper cases. These results suggest that the helper RNA approaches can further assist the design of functional RNA devices in vivo with the aid of the streamlined automatic design software developed here. Further, our solutions for screening and stabilizing single-stranded region of mRNA may find use in other in vivo mRNA-sensing applications such as cas13 crRNA design, transcriptome engineering, and trans-cleaving ribozymes.

High-Performance Allosteric Conditional Guide RNAs for Mammalian Cell-Selective Regulation of CRISPR/Cas

The activity of a conditional guide RNA (cgRNA) is dependent on the presence or absence of an RNA trigger, enabling cell-selective regulation of CRISPR/Cas function. cgRNAs are programmable at two levels, with the target-binding sequence controlling the target of Cas activity (edit, silence, or induce a gene of choice) and the trigger-binding sequence controlling the scope of Cas activity (subset of cells expressing the trigger RNA). Allosteric cgRNA mechanisms enable independent design of the target and trigger sequences, providing the flexibility to select the regulatory target and scope independently. Building on prior advances in dynamic RNA nanotechnology that demonstrated the cgRNA concept, here we set the goal of engineering high-performance allosteric cgRNA mechanisms for the mammalian setting, pursuing both ON → OFF logic (conditional inactivation by an RNA trigger) and OFF → ON logic (conditional activation by an RNA trigger). For each mechanism, libraries of orthogonal cgRNA/trigger pairs were designed using NUPACK. In HEK 293T cells expressing cgRNAs, triggers, and inducing dCas9: (1) a library of four ON → OFF "terminator switch" cgRNAs exhibit a median fold-change of ≈50×, a median fractional dynamic range of ≈20%, and a median crosstalk modulus of ≈9%; (2) a library of three OFF → ON "split-terminator switch" cgRNAs exhibit a median fold-change of ≈150×, a median fractional dynamic range of ≈50%, and a median crosstalk modulus of ≈4%. Further, we demonstrate that xrRNA elements that protect viral RNAs from degradation by exoribonucleases can dramatically enhance the performance of RNA synthetic biology. The high-performance allosteric cgRNAs demonstrated here for ON → OFF and OFF → ON logic in mammalian cells provide a foundation for pursuing applications of programmable cell-selective regulation.

A Unified Dynamic Programming Framework for the Analysis of Interacting Nucleic Acid Strands: Enhanced Models, Scalability, and Speed

Dynamic programming algorithms within the NUPACK software suite enable analysis of nucleic acid sequences over complex and test tube ensembles containing arbitrary numbers of interacting strand species, serving the needs of researchers in molecular programming, nucleic acid nanotechnology, synthetic biology, and across the life sciences. Here, to enhance the underlying physical model, ensure scalability for large calculations, and achieve dramatic speedups when calculating diverse physical quantities over complex and test tube ensembles, we introduce a unified dynamic programming framework that combines three ingredients: (1) recursions that specify the dependencies between subproblems and incorporate the details of the structural ensemble and the free energy model, (2) evaluation algebras that define the mathematical form of each subproblem, (3) operation orders that specify the computational trajectory through the dependency graph of subproblems. The physical model is enhanced using new recursions that operate over the complex ensemble including coaxial and dangle stacking subensembles. The recursions are coded generically and then compiled with a quantity-specific evaluation algebra and operation order to generate an executable for each physical quantity: partition function, equilibrium base-pairing probabilities, MFE energy and proxy structure, suboptimal proxy structures, and Boltzmann sampled structures. For large complexes (e.g., 30 000 nt), scalability is achieved for partition function calculations using an overflow-safe evaluation algebra, and for equilibrium base-pairing probabilities using a backtrack-free operation order. A new blockwise operation order that treats subcomplex blocks for the complex species in a test tube ensemble enables dramatic speedups (e.g., 20-120× ) using vectorization and caching. With these performance enhancements, equilibrium analysis of substantial test tube ensembles can be performed in ≤ 1 min on a single computational core (e.g., partition function and equilibrium concentration for all complex species of up to six strands formed from two strand species of 300 nt each, or for all complex species of up to two strands formed from 80 strand species of 100 nt each). A new sampling algorithm simultaneously samples multiple structures from the complex ensemble to yield speedups of an order of magnitude or more as the number of structures increases above ≈10³. These advances are available within the NUPACK 4.0 code base (www.nupack.org) which can be flexibly scripted using the all-new NUPACK Python module.

Rational design of aptamer switches with programmable pH response

Aptamer switches that respond sensitively to pH could enhance control over molecular devices, improving their diagnostic and therapeutic efficacy. Previous designs have inserted pH-sensitive DNA motifs into aptamer sequences. Unfortunately, their performance was limited by the motifs' intrinsic pH-responses and could not be tuned to operate across arbitrary pH ranges. Here, we present a methodology for converting virtually any aptamer into a molecular switch with pH-selective binding properties - in acidic, neutral, or alkaline conditions. Our design inserts two orthogonal motifs that can be manipulated in parallel to tune pH-sensitivity without altering the aptamer sequence itself. From a single ATP aptamer, we engineer pH-controlled target binding under diverse conditions, achieving pH-induced selectivity in affinity of up to 1,000-fold. Importantly, we demonstrate the design of tightly regulated aptamers with strong target affinity over only a narrow pH range. Our approach offers a highly generalizable strategy for integrating pH-responsiveness into molecular devices.

A domain-level DNA strand displacement reaction enumerator allowing arbitrary non-pseudoknotted secondary structures

Information technologies enable programmers and engineers to design and synthesize systems of startling complexity that nonetheless behave as intended. This mastery of complexity is made possible by a hierarchy of formal abstractions that span from high-level programming languages down to low-level implementation specifications, with rigorous connections between the levels. DNA nanotechnology presents us with a new molecular information technology whose potential has not yet been fully unlocked in this way. Developing an effective hierarchy of abstractions may be critical for increasing the complexity of programmable DNA systems. Here, we build on prior practice to provide a new formalization of 'domain-level' representations of DNA strand displacement systems that has a natural connection to nucleic acid biophysics while still being suitable for formal analysis. Enumeration of unimolecular and bimolecular reactions provides a semantics for programmable molecular interactions, with kinetics given by an approximate biophysical model. Reaction condensation provides a tractable simplification of the detailed reactions that respects overall kinetic properties. The applicability and accuracy of the model is evaluated across a wide range of engineered DNA strand displacement systems. Thus, our work can serve as an interface between lower-level DNA models that operate at the nucleotide sequence level, and high-level chemical reaction network models that operate at the level of interactions between abstract species.

An Artificial Intelligent Signal Amplification System for in vivo Detection of miRNA

MicroRNAs (miRNA) have been identified as oncogenic drivers and tumor suppressors in every major cancer type. In this work, we design an artificial intelligent signal amplification (AISA) system including double-stranded SQ (S, signal strand; Q, quencher strand) and FP (F, fuel strand; P, protect strand) according to thermodynamics principle for sensitive detection of miRNA in vitro and in vivo. In this AISA system for miRNA detection, strand S carries a quenched imaging marker inside the SQ. Target miRNA is constantly replaced by a reaction intermediate and circulatively participates in the reaction, similar to enzyme. Therefore, abundant fluorescent substances from S and SP are dissociated from excessive SQ for in vitro and in vivo visualization. The versatility and feasibility for disease diagnosis using this system were demonstrated by constructing two types of AISA system to detect Hsa-miR-484 and Hsa-miR-100, respectively. The minimum target concentration detected by the system in vitro (10 min after mixing) was 1/10th that of the control group. The precancerous lesions of liver cancer were diagnosed, and the detection accuracy were larger than 94% both in terms of location and concentration. The ability to establish this design framework for AISA system with high specificity provides a new way to monitor tumor progression and to assess therapeutic responses.

Aptamers as Modular Components of Therapeutic Nucleic Acid Nanotechnology

Nucleic acids play a central role in all domains of life, either as genetic blueprints or as regulators of various biochemical pathways. The chemical makeup of ribonucleic acid (RNA) or deoxyribonucleic acid (DNA), generally represented by a sequence of four monomers, also provides precise instructions for folding and higher-order assembly of these biopolymers that, in turn, dictate biological functions. The sequence-based specific 3D structures of nucleic acids led to the development of the directed evolution of oligonucleotides, SELEX (systematic evolution of ligands by exponential enrichment), against a chosen target molecule. Among the variety of functions, selected oligonucleotides named aptamers also allow targeting of cell-specific receptors with antibody-like precision and can deliver functional RNAs without a transfection agent. The advancements in the field of customizable nucleic acid nanoparticles (NANPs) opened avenues for the design of nanoassemblies utilizing aptamers for triggering or blocking cell signaling pathways or using aptamer-receptor combinations to activate therapeutic functionalities. A recent selection of fluorescent aptamers enables real-time tracking of NANP formation and interactions. The aptamers are anticipated to contribute to the future development of technologies, enabling an efficient assembly of functional NANPs in mammalian cells or in vivo. These research topics are of top importance for the field of therapeutic nucleic acid nanotechnology with the promises to scale up mass production of NANPs suitable for biomedical applications, to control the intracellular organization of biological materials to enhance the efficiency of biochemical pathways, and to enhance the therapeutic potential of NANP-based therapeutics while minimizing undesired side effects and toxicities.

Conditional Guide RNAs: Programmable Conditional Regulation of CRISPR/Cas Function in Bacterial and Mammalian Cells via Dynamic RNA Nanotechnology

A guide RNA (gRNA) directs the function of a CRISPR protein effector to a target gene of choice, providing a versatile programmable platform for engineering diverse modes of synthetic regulation (edit, silence, induce, bind). However, the fact that gRNAs are constitutively active places limitations on the ability to confine gRNA activity to a desired location and time. To achieve programmable control over the scope of gRNA activity, here we apply principles from dynamic RNA nanotechnology to engineer conditional guide RNAs (cgRNAs) whose activity is dependent on the presence or absence of an RNA trigger. These cgRNAs are programmable at two levels, with the trigger-binding sequence controlling the scope of the effector activity and the target-binding sequence determining the subject of the effector activity. We demonstrate molecular mechanisms for both constitutively active cgRNAs that are conditionally inactivated by an RNA trigger (ON → OFF logic) and constitutively inactive cgRNAs that are conditionally activated by an RNA trigger (OFF → ON logic). For each mechanism, automated sequence design is performed using the reaction pathway designer within NUPACK to design an orthogonal library of three cgRNAs that respond to different RNA triggers. In E. coli expressing cgRNAs, triggers, and silencing dCas9 as the protein effector, we observe a median conditional response of ≈4-fold for an ON → OFF "terminator switch" mechanism, ≈15-fold for an ON → OFF "splinted switch" mechanism, and ≈3-fold for an OFF → ON "toehold switch" mechanism; the median crosstalk within each cgRNA/trigger library is <2%, ≈2%, and ≈20% for the three mechanisms. To test the portability of cgRNA mechanisms prototyped in bacteria to mammalian cells, as well as to test generalizability to different effector functions, we implemented the terminator switch in HEK 293T cells expressing inducing dCas9 as the protein effector, observing a median ON → OFF conditional response of ≈4-fold with median crosstalk of ≈30% for three orthogonal cgRNA/trigger pairs. By providing programmable control over both the scope and target of protein effector function, cgRNA regulators offer a promising platform for synthetic biology.

Switching the activity of Cas12a using guide RNA strand displacement circuits

The CRISPR effector protein Cas12a has been used for a wide variety of applications such as in vivo gene editing and regulation or in vitro DNA sensing. Here, we add programmability to Cas12a-based DNA processing by combining it with strand displacement-based reaction circuits. We first establish a viable strategy for augmenting Cas12a guide RNAs (gRNAs) at their 5' end and then use such 5' extensions to construct strand displacement gRNAs (SD gRNAs) that can be activated by single-stranded RNA trigger molecules. These SD gRNAs are further engineered to exhibit a digital and orthogonal response to different trigger RNA inputs-including full length mRNAs-and to function as multi-input logic gates. We also demonstrate that SD gRNAs can be designed to work inside bacterial cells. Using such in vivo SD gRNAs and a DNase inactive version of Cas12a (dCas12a), we demonstrate logic gated transcriptional control of gene expression in E. coli.

Evolving methods for rational de novo design of functional RNA molecules

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.

Label-Free and Enzyme-Free Colorimetric Detection of Pb2+ Based on RNA Cleavage and Annealing-Accelerated Hybridization Chain Reaction

A label-free and enzyme-free colorimetric sensor for rapid detection of Pb²⁺ is reported, which is based on the strategy of DNAzyme-mediated RNA cleavage combined with an annealing-accelerated DNA hybridization chain reaction (HCR). As a trigger DNA, the substrate strand (S_TM) of DNAzyme can initiate HCR effectively. However, when it is cleaved by DNAzyme in the presence of Pb²⁺, the separation of DNA functional domains leads to a serious decrease in HCR efficiency. As a result, the difference in Pb²⁺ concentration converts into the difference of DNA assembly, which eventually leads to the color change of colloidal gold nanoparticles (AuNPs). In this work, a DNA strand (cGR5) completely complementary to the catalytic strand (GR5) of DNAzyme is used to improve the dissociation of S_TM to enhance the HCR efficiency. In addition, the simple operation of DNA annealing is first used to accelerate the HCR process, enabling the Pb²⁺ detection to be completed in about 30 min. As advantages of high sensitivity, good selectivity, strong anti-interference ability, and good practical performance are achieved, it is anticipated that the cheap and simple colorimetric sensor will be helpful for on-site detection of environmental and food samples.

Principles and Applications of Nucleic Acid Strand Displacement Reactions

Dynamic DNA nanotechnology, a subfield of DNA nanotechnology, is concerned with the study and application of nucleic acid strand-displacement reactions. Strand-displacement reactions generally proceed by three-way or four-way branch migration and initially were investigated for their relevance to genetic recombination. Through the use of toeholds, which are single-stranded segments of DNA to which an invader strand can bind to initiate branch migration, the rate with which strand displacement reactions proceed can be varied by more than 6 orders of magnitude. In addition, the use of toeholds enables the construction of enzyme-free DNA reaction networks exhibiting complex dynamical behavior. A demonstration of this was provided in the year 2000, in which strand displacement reactions were employed to drive a DNA-based nanomachine (Yurke, B.; et al. Nature 2000, 406, 605-608). Since then, toehold-mediated strand displacement reactions have been used with ever increasing sophistication and the field of dynamic DNA nanotechnology has grown exponentially. Besides molecular machines, the field has produced enzyme-free catalytic systems, all DNA chemical oscillators and the most complex molecular computers yet devised. Enzyme-free catalytic systems can function as chemical amplifiers and as such have received considerable attention for sensing and detection applications in chemistry and medical diagnostics. Strand-displacement reactions have been combined with other enzymatically driven processes and have also been employed within living cells (Groves, B.; et al. Nat. Nanotechnol. 2015, 11, 287-294). Strand-displacement principles have also been applied in synthetic biology to enable artificial gene regulation and computation in bacteria. Given the enormous progress of dynamic DNA nanotechnology over the past years, the field now seems poised for practical application.

Signal Transduction in Human Cell Lysate via Dynamic RNA Nanotechnology

Dynamic RNA nanotechnology with small conditional RNAs (scRNAs) offers a promising conceptual approach to introducing synthetic regulatory links into endogenous biological circuits. Here, we use human cell lysate containing functional Dicer and RNases as a testbed for engineering scRNAs for conditional RNA interference (RNAi). scRNAs perform signal transduction via conditional shape change: detection of a subsequence of mRNA input X triggers formation of a Dicer substrate that is processed to yield small interfering RNA (siRNA) output anti-Y targeting independent mRNA Y for destruction. Automated sequence design is performed using the reaction pathway designer within NUPACK to encode this conditional hybridization cascade into the scRNA sequence subject to the sequence constraints imposed by X and Y. Because it is difficult for secondary structure models to predict which subsequences of mRNA input X will be accessible for detection, here we develop the RNAhyb method to experimentally determine accessible windows within the mRNA that are provided to the designer as sequence constraints. We demonstrate the programmability of scRNA regulators by engineering scRNAs for transducing in both directions between two full-length mRNAs X and Y, corresponding to either the forward molecular logic “if X then not Y” (X  Y) or the reverse molecular logic “if Y then not X” (Y  X). In human cell lysate, we observe a strong OFF/ON conditional response with low crosstalk, corresponding to a ≈20-fold increase in production of the siRNA output in response to the cognate versus noncognate full-length mRNA input. 2′OMe-RNA chemical modifications protect signal transduction reactants and intermediates against RNase degradation while enabling Dicer processing of signal transduction products. Because diverse biological pathways interact with RNA, scRNAs that transduce between detection of endogenous RNA inputs and production of biologically active RNA outputs hold great promise as a synthetic regulatory paradigm.

Label-free optical biosensor for target detection based on simulation-assisted catalyzed hairpin assembly

The development of efficient and convenient strategy without involving enzyme or complex nanomaterial for the micro molecules detection has profound meaning in the diagnosis of diseases. Herein, taking the advantages of the strong affinity of aptamer and catalyzed hairpin assembly, we develop a new non-label optical amplified strategy for thrombin detection in this work. To support both biological inquiry and technological innovation, thermodynamic models are introduced to predict the minimum energy secondary structure of interacting nucleic acid strands and calculate the partition function and equilibrium concentration for complexes in our system. Then, the thermodynamics properties of interacting DNA strands and the reactions of toehold strand displacement-driven assembly have been simulated, validating the feasibility of the theory and optimizing the follow-up lab tests. Following that, our strategy for thrombin detection is proved to be feasible and effective in biological experiment. Taken together, such a biosensor has a good potential in bioactive molecules detection and disease diagnosis for future biological research.

AptaBlocks: Designing RNA complexes and accelerating RNA-based drug delivery systems

RNA-based therapeutics, i.e. the utilization of synthetic RNA molecules to alter cellular functions, have the potential to address targets which are currently out of scope for traditional drug design pipelines. This potential however hinges on the ability to selectively deliver and internalize therapeutic RNAs into cells of interest. Cell internalizing RNA aptamers selected against surface receptors and discriminatively expressed on target cells hold particular promise as suitable candidates for such delivery agents. Specifically, these aptamers can be combined with a therapeutic cargo and facilitate internalization of the cargo into the cell of interest. A recently proposed method to obtain such aptamer-cargo constructs employs a double-stranded "sticky bridge" where the complementary strands constituting the bridge are conjugated with the aptamer and the cargo respectively. The design of appropriate sticky bridge sequences however has proven highly challenging given the structural and functional constraints imposed on them during synthesis and administration. These include, but are not limited to, guaranteed formation and stability of the complex, non-interference with the aptamer or the cargo, as well as the prevention of spurious aggregation of the molecules during incubation. In order to address these issues, we have developed AptaBlocks - a computational method to design RNA complexes that hybridize via sticky bridges. The effectiveness of our approach has been verified computationally, and experimentally in the context of drug delivery to pancreatic cancer cells. Importantly, AptaBlocks is a general method for the assembly of nucleic acid systems that, in addition to designing of RNA-based drug delivery systems, can be used in other applications of RNA nanotechnology. AptaBlocks is available at https://github.com/wyjhxq/AptaBlocks.

Sequential super-resolution imaging using DNA strand displacement

Sequential labeling and imaging in fluorescence microscopy allows the imaging of multiple structures in the same cell using a single fluorophore species. In super-resolution applications, the optimal dye suited to the method can be chosen, the optical setup can be simpler and there are no chromatic aberrations between images of different structures. We describe a method based on DNA strand displacement that can be used to quickly and easily perform the labeling and removal of the fluorophores during each sequence. Site-specific tags are conjugated with unique and orthogonal single stranded DNA. Labeling for a particular structure is achieved by hybridization of antibody-bound DNA with a complimentary dye-labeled strand. After imaging, the dye is removed using toehold-mediated strand displacement, in which an invader strand competes off the dye-labeled strand than can be subsequently washed away. Labeling and removal of each DNA-species requires only a few minutes. We demonstrate the concept using sequential dSTORM super-resolution for multiplex imaging of subcellular structures.

A Non-Label and Enzyme-Free Sensitive Detection Method for Thrombin Based on Simulation-Assisted DNA Assembly

Taking advantage of the high selectivity of aptamers and enzyme-free catalyzed hairpin assembly (CHA) amplification strategy, we herein describe a label-free and enzyme-free sensitive fluorescent and colorimetric strategy for thrombin detection in this paper. In the presence of target, the corresponding aptamer of the partial dsDNA probes will bind to the target and liberate the initiation strand, which is artfully designed as the “on” switch for hairpin assembly. Moreover, the displaced initiation strand partakes in a multi-cycle process and produces numerous G-quadruplexes, which have a remarkable enhancement in fluorescent/colorimetric signal from NMM (N-methyl-mesoporphyrin IX) and TMB (3,3′,5,5′-tetramethylbenzidine), respectively. The proposed amplification strategy for thrombin detection is of high sensitivity, down to 2.4 pM, and also achieves colorimetric signals that are able to be distinguished by naked eye. More importantly, the thermodynamics of interacting DNA strands used in our work, and the process of toehold strand displacement-driven assembly are simulated before biological testing, verifying the feasibility theoretically, and simplifying the subsequent actual experiments. Therefore, our approach and simulation have a certain potential application in biomarker detection and quantitatively monitor for disease diagnosis.

RNAblueprint: flexible multiple target nucleic acid sequence design

Motivation

Realizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility.

Results

We developed a C ++  library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages.

Availability and implementation

RNAblueprint, Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA.

Supplementary information

Supplementary data are available at Bioinformatics online.

Detection of Sub-fM DNA with Target Recycling and Self-Assembly Amplification on Graphene Field-Effect Biosensors

All-electronic DNA biosensors based on graphene field-effect transistors (GFETs) offer the prospect of simple and cost-effective diagnostics. For GFET sensors based on complementary probe DNA, the sensitivity is limited by the binding affinity of the target oligonucleotide, in the nM range for 20 mer targets. We report a ∼20 000× improvement in sensitivity through the use of engineered hairpin probe DNA that allows for target recycling and hybridization chain reaction. This enables detection of 21 mer target DNA at sub-fM concentration and provides superior specificity against single-base mismatched oligomers. The work is based on a scalable fabrication process for biosensor arrays that is suitable for multiplexed detection. This approach overcomes the binding-affinity-dependent sensitivity of nucleic acid biosensors and offers a pathway toward multiplexed and label-free nucleic acid testing with high accuracy and selectivity.

Programmable and Multifunctional DNA-Based Materials for Biomedical Applications

DNA encodes the genetic information; recently, it has also become a key player in material science. Given the specific Watson-Crick base-pairing interactions between only four types of nucleotides, well-designed DNA self-assembly can be programmable and predictable. Stem-loops, sticky ends, Holliday junctions, DNA tiles, and lattices are typical motifs for forming DNA-based structures. The oligonucleotides experience thermal annealing in a near-neutral buffer containing a divalent cation (usually Mg²⁺ ) to produce a variety of DNA nanostructures. These structures not only show beautiful landscape, but can also be endowed with multifaceted functionalities. This Review begins with the fundamental characterization and evolutionary trajectory of DNA-based artificial structures, but concentrates on their biomedical applications. The coverage spans from controlled drug delivery to high therapeutic profile and accurate diagnosis. A variety of DNA-based materials, including aptamers, hydrogels, origamis, and tetrahedrons, are widely utilized in different biomedical fields. In addition, to achieve better performance and functionality, material hybridization is widely witnessed, and DNA nanostructure modification is also discussed. Although there are impressive advances and high expectations, the development of DNA-based structures/technologies is still hindered by several commonly recognized challenges, such as nuclease instability, lack of pharmacokinetics data, and relatively high synthesis cost.

Thermodynamics of the pseudo-knot in helix 18 of 16S ribosomal RNA

A fragment of E. coli 16S rRNA formed by nucleotides 500 to 545 is termed helix 18. Nucleotides 505-507 and 524-526 form a pseudo-knot and its distortion affects ribosome function. Helix 18 isolated from the ribosome context is thus an interesting fragment to investigate the structural properties and folding of RNA with pseudo-knots. With all-atom molecular dynamics simulations, spectroscopic and gel electrophoresis experiments, we investigated thermodynamics of helix 18, with a focus on its pseudo-knot. In solution studies at ambient conditions we observed dimerization of helix 18. We proposed that the loop, containing nucleotides forming the pseudo-knot, interacts with another monomer of helix 18. The native dimer is difficult to break but introducing mutations in the pseudo-knot indeed assured a monomeric form of helix 18. Molecular dynamics simulations at 310 K confirmed the stability of the pseudo-knot but at elevated temperatures this pseudo-knot was the first part of helix 18 to lose the hydrogen bond pattern. To further determine helix 18 stability, we analyzed the interactions of helix 18 with short oligomers complementary to a nucleotide stretch containing the pseudo-knot. The formation of higher-order structures by helix 18 impacts hybridization efficiency of peptide nucleic acid and 2'-O methyl RNA oligomers.

Hybridization Chain Reaction Design and Biosensor Implementation

DNA biosensors could overcome some of the common drawbacks of lab-based techniques for nucleic acids detection for diagnostics purposes. One of the main impediments for such applications of DNA biosensors is their lack of sensitivity: this can prevent their full exploitation in the diagnostic analytical field. DNA nanotechnology could enhance DNA biosensors and let them perform at the required high sensitivity. Well-designed, programmable self-assembly reactions can be triggered by a specific nucleic acid target. The Hybridization Chain Reaction (HCR) is a self-assembly strategy in which the target nucleic acid sequence triggers the formation of long nicked double-stranded DNA nanostructures. This can be performed in solution or on a surface, and the process can be coupled to different signal transduction schemes. We here describe the methods to design and test HCR reactions for the detection of different nucleic acid targets in solution and the procedures to exploit this strategy on surfaces with an electrochemical biosensing platform.

Enzyme-free nucleic acid dynamical systems

Chemistries exhibiting complex dynamics—from inorganic oscillators to gene regulatory networks—have been long known but either cannot be reprogrammed at will or rely on the sophisticated enzyme chemistry underlying the central dogma. Can simpler molecular mechanisms, designed from scratch, exhibit the same range of behaviors? Abstract chemical reaction networks have been proposed as a programming language for complex dynamics, along with their systematic implementation using short synthetic DNA molecules. We developed this technology for dynamical systems by identifying critical design principles and codifying them into a compiler automating the design process. Using this approach, we built an oscillator containing only DNA components, establishing that Watson-Crick base-pairing interactions alone suffice for complex chemical dynamics and that autonomous molecular systems can be designed via molecular programming languages.

Programmable autonomous synthesis of single-stranded DNA

DNA performs diverse functional roles in biology, nanotechnology and biotechnology, but current methods for autonomously synthesizing arbitrary single-stranded DNA are limited. Here, we introduce the concept of primer exchange reaction (PER) cascades, which grow nascent single-stranded DNA with user-specified sequences following prescribed reaction pathways. PER synthesis happens in a programmable, autonomous, in situ and environmentally responsive fashion, providing a platform for engineering molecular circuits and devices with a wide range of sensing, monitoring, recording, signal-processing and actuation capabilities. We experimentally demonstrate a nanodevice that transduces the detection of a trigger RNA into the production of a DNAzyme that degrades an independent RNA substrate, a signal amplifier that conditionally synthesizes long fluorescent strands only in the presence of a particular RNA signal, molecular computing circuits that evaluate logic (AND, OR, NOT) combinations of RNA inputs, and a temporal molecular event recorder that records in the PER transcript the order in which distinct RNA inputs are sequentially detected.

Programmable Nucleic Acid Based Polygons with Controlled Neuroimmunomodulatory Properties for Predictive QSAR Modeling

In the past few years, the study of therapeutic RNA nanotechnology has expanded tremendously to encompass a large group of interdisciplinary sciences. It is now evident that rationally designed programmable RNA nanostructures offer unique advantages in addressing contemporary therapeutic challenges such as distinguishing target cell types and ameliorating disease. However, to maximize the therapeutic benefit of these nanostructures, it is essential to understand the immunostimulatory aptitude of such tools and identify potential complications. This paper presents a set of 16 nanoparticle platforms that are highly configurable. These novel nucleic acid based polygonal platforms are programmed for controllable self-assembly from RNA and/or DNA strands via canonical Watson-Crick interactions. It is demonstrated that the immunostimulatory properties of these particular designs can be tuned to elicit the desired immune response or lack thereof. To advance the current understanding of the nanoparticle properties that contribute to the observed immunomodulatory activity and establish corresponding designing principles, quantitative structure-activity relationship modeling is conducted. The results demonstrate that molecular weight, together with melting temperature and half-life, strongly predicts the observed immunomodulatory activity. This framework provides the fundamental guidelines necessary for the development of a new library of nanoparticles with predictable immunomodulatory activity.

Model-based design of RNA hybridization networks implemented in living cells

Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations.

CAGE: Chromatin Analogous Gene Expression

Self-assembled nucleic acids perform biological, chemical, and mechanical work at the nanoscale. DNA-based molecular machines have been designed here to perform work by reacting with cancer-specific miRNA mimics and then regulating gene expression in vitro by tuning RNA polymerase activity. Because RNA production is topologically restrained, the machines demonstrate chromatin analogous gene expression (CAGE). With modular and tunable design features, CAGE has potential for molecular biology, synthetic biology, and personalized medicine applications.

Single-Molecule Counting of Point Mutations by Transient DNA Binding

High-confidence detection of point mutations is important for disease diagnosis and clinical practice. Hybridization probes are extensively used, but are hindered by their poor single-nucleotide selectivity. Shortening the length of DNA hybridization probes weakens the stability of the probe-target duplex, leading to transient binding between complementary sequences. The kinetics of probe-target binding events are highly dependent on the number of complementary base pairs. Here, we present a single-molecule assay for point mutation detection based on transient DNA binding and use of total internal reflection fluorescence microscopy. Statistical analysis of single-molecule kinetics enabled us to effectively discriminate between wild type DNA sequences and single-nucleotide variants at the single-molecule level. A higher single-nucleotide discrimination is achieved than in our previous work by optimizing the assay conditions, which is guided by statistical modeling of kinetics with a gamma distribution. The KRAS c.34 A mutation can be clearly differentiated from the wild type sequence (KRAS c.34 G) at a relative abundance as low as 0.01% mutant to WT. To demonstrate the feasibility of this method for analysis of clinically relevant biological samples, we used this technology to detect mutations in single-stranded DNA generated from asymmetric RT-PCR of mRNA from two cancer cell lines.

Construction and In Vivo Testing of Prokaryotic Riboregulators

RNAs that are transcribed and self-assemble within living cells are valuable tools for regulating and organizing cellular activities. Riboregulators, in particular, have been widely used for modulating translation and transcription in response to cognate transactivating or trigger RNAs, enabling cells to evaluate logic operations and to respond to environmental cues. Herein we detail a set of methods for the rapid construction and testing of prokaryotic riboregulators in Escherichia coli. These methods enable construction of dozens of riboregulator plasmids at the same time without the use of restriction enzymes. Furthermore, they facilitate rapid screening of devices and can be applied to a variety of other self-assembling in vivo RNA systems.

General Strategy for the Design of DNA Coding Sequences Applied to Nanoparticle Assembly

The DNA-directed assembly of nano-objects has been the subject of many recent studies as a means to construct advanced nanomaterial architectures. Although much experimental in silico work has been presented and discussed, there has been no in-depth consideration of the proper design of single-strand sticky termination of DNA sequences, noted as ssST, which is important in avoiding self-folding within one DNA strand, unwanted strand-to-strand interaction, and mismatching. In this work, a new comprehensive and computationally efficient optimization algorithm is presented for the construction of all possible DNA sequences that specifically prevents these issues. This optimization procedure is also effective when a spacer section is used, typically repeated sequences of thymine or adenine placed between the ssST and the nano-object, to address the most conventional experimental protocols. We systematically discuss the fundamental statistics of DNA sequences considering complementarities limited to two (or three) adjacent pairs to avoid self-folding and hybridization of identical strands due to unwanted complements and mismatching. The optimized DNA sequences can reach maximum lengths of 9 to 34 bases depending on the level of applied constraints. The thermodynamic properties of the allowed sequences are used to develop a ranking for each design. For instance, we show that the maximum melting temperature saturates with 14 bases under typical solvation and concentration conditions. Thus, DNA ssST with optimized sequences are developed for segments ranging from 4 to 40 bases, providing a very useful guide for all technological protocols. An experimental test is presented and discussed using the aggregation of Al and CuO nanoparticles and is shown to validate and illustrate the importance of the proposed DNA coding sequence optimization.

An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures

Computational design of RNA sequences that fold into targeted secondary structures has many applications in biomedicine, nanotechnology and synthetic biology. An RNA molecule is made of different types of secondary structure elements and an important RNA element named pseudoknot plays a key role in stabilizing the functional form of the molecule. However, due to the computational complexities associated with characterizing pseudoknotted RNA structures, most of the existing RNA sequence designer algorithms generally ignore this important structural element and therefore limit their applications. In this paper we present a new algorithm to design RNA sequences for pseudoknotted secondary structures. We use NUPACK as the folding algorithm to compute the equilibrium characteristics of the pseudoknotted RNAs, and describe a new adaptive defect weighted sampling algorithm named Enzymer to design low ensemble defect RNA sequences for targeted secondary structures including pseudoknots. We used a biological data set of 201 pseudoknotted structures from the Pseudobase library to benchmark the performance of our algorithm. We compared the quality characteristics of the RNA sequences we designed by Enzymer with the results obtained from the state of the art MODENA and antaRNA. Our results show our method succeeds more frequently than MODENA and antaRNA do, and generates sequences that have lower ensemble defect, lower probability defect and higher thermostability. Finally by using Enzymer and by constraining the design to a naturally occurring and highly conserved Hammerhead motif, we designed 8 sequences for a pseudoknotted cis-acting Hammerhead ribozyme. Enzymer is available for download at https://bitbucket.org/casraz/enzymer.

Computational Design of a Circular RNA with Prionlike Behavior

RNA molecules engineered to fold into predefined conformations have enabled the design of a multitude of functional RNA devices in the field of synthetic biology and nanotechnology. More complex designs require efficient computational methods, which need to consider not only equilibrium thermodynamics but also the kinetics of structure formation. Here we present a novel type of RNA design that mimics the behavior of prions, that is, sequences capable of interaction-triggered autocatalytic replication of conformations. Our design was computed with the ViennaRNA package and is based on circular RNA that embeds domains amenable to intermolecular kissing interactions.

Computational Approaches to Nucleic Acid Origami

Recent advances in experimental DNA origami have dramatically expanded the horizon of DNA nanotechnology. Complex 3D suprastructures have been designed and developed using DNA origami with applications in biomaterial science, nanomedicine, nanorobotics, and molecular computation. Ribonucleic acid (RNA) origami has recently been realized as a new approach. Similar to DNA, RNA molecules can be designed to form complex 3D structures through complementary base pairings. RNA origami structures are, however, more compact and more thermodynamically stable due to RNA's non-canonical base pairing and tertiary interactions. With all these advantages, the development of RNA origami lags behind DNA origami by a large gap. Furthermore, although computational methods have proven to be effective in designing DNA and RNA origami structures and in their evaluation, advances in computational nucleic acid origami is even more limited. In this paper, we review major milestones in experimental and computational DNA and RNA origami and present current challenges in these fields. We believe collaboration between experimental nanotechnologists and computer scientists are critical for advancing these new research paradigms.

DyNAMiC Workbench: an integrated development environment for dynamic DNA nanotechnology

Dynamic DNA nanotechnology provides a promising avenue for implementing sophisticated assembly processes, mechanical behaviours, sensing and computation at the nanoscale. However, design of these systems is complex and error-prone, because the need to control the kinetic pathway of a system greatly increases the number of design constraints and possible failure modes for the system. Previous tools have automated some parts of the design workflow, but an integrated solution is lacking. Here, we present software implementing a three 'tier' design process: a high-level visual programming language is used to describe systems, a molecular compiler builds a DNA implementation and nucleotide sequences are generated and optimized. Additionally, our software includes tools for analysing and 'debugging' the designs in silico, and for importing/exporting designs to other commonly used software systems. The software we present is built on many existing pieces of software, but is integrated into a single package—accessible using a Web-based interface at http://molecular-systems.net/workbench. We hope that the deep integration between tools and the flexibility of this design process will lead to better experimental results, fewer experimental design iterations and the development of more complex DNA nanosystems.