Constrained Multistate Sequence Design for Nucleic Acid Reaction Pathway Engineering

Design and analysis of self-priming extension DNA hairpin probe for miRNA detection based on a unified dynamic programming framework

MicroRNAs (miRNAs) are potential biomarkers for cancer diagnosis and prognosis, methods for detecting miRNAs with high sensitivity, selectivity, and stability are urgently needed. Various nucleic acid probes that have traditionally been for this purpose suffer several drawbacks, including inefficient signal-to-noise ratios and intensities, high cost, and time-consuming method establishment. Computing tools used for investigating the thermodynamics of DNA hybridization reactions can accurately predict the secondary structure of DNA and the interactions between DNA molecules. Herein, NUPACK was used to design a series of nucleic acid probes and develop a phosphorothioated-terminal hairpin formation and self-priming extension (PS-THSP) signal amplification strategy, which enabled the ultrasensitive detection of miR-200a in serum samples. The free and binding energies of the DNA detection probes calculated using NUPACK, as well as the biological experimental results, were considered synthetically to select the best sequence and experimental conditions. A unified dynamic programming framework, NUPACK analysis and the experimental data, were complementary and improved the designed model in all respects. Our study demonstrates the feasibility of using computer technology such as NUPACK to simplify the experimental process and provide intuitive results.

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.

An approach for state differentiation in nucleic acid circuits: Application to diagnostic DNA computing

BACKGROUND

Differentiating between different states in nucleic acid circuits is crucial for various biological applications. One approach, there is a requirement for complicated sequential summation, which can be excessive for practical purposes. By selectively labeling biologically significant states, this study tackles the issue and presents a more cost-effective and streamlined solution. The challenge is to efficiently distinguish between different states in a nucleic acid circuit.

RESULTS

An innovative method is introduced in this study to distinguish between states in a nucleic acid circuit, emphasizing the biologically relevant ones. The circuit comprises four DNA logic gates and two detection modules, one for determining fetal gender and the other for diagnosing X-linked genetic disorders. The primary module generates a G-quadruplex DNAzyme when activated by specific biomarkers, which leads to a distinct colorimetric signal. The secondary module responds to hemophilia and choroideremia biomarkers, generating one or two DNAzymes. The absence of female fetus indicators results in no DNAzyme or color change. The circuit can differentiate various fetal states by producing one to four active DNAzymes in response to male fetus biomarkers. A single-color solution for state differentiation is provided by this approach, which promises significant advancements in DNA computing and diagnostic applications.

SIGNIFICANCE

The innovative approach used in this study to distinguish states in nucleic acid circuits holds great significance. By selectively labeling biologically relevant states, circuit design is simplified and complexity is reduced. This advancement enables cost-effective and efficient diagnostic applications and contributes to DNA computing, providing a valuable solution to a fundamental problem.

Multiplex, Quantitative, High-Resolution Imaging of Protein:Protein Complexes via Hybridization Chain Reaction

Signal amplification based on the mechanism of hybridization chain reaction (HCR) facilitates spatial exploration of gene regulatory networks by enabling multiplex, quantitative, high-resolution imaging of RNA and protein targets. Here, we extend these capabilities to the imaging of protein:protein complexes, using proximity-dependent cooperative probes to conditionally generate a single amplified signal if and only if two target proteins are colocalized within the sample. HCR probes and amplifiers combine to provide automatic background suppression throughout the protocol, ensuring that even if reagents bind nonspecifically in the sample, they will not generate amplified background. We demonstrate protein:protein imaging with a high signal-to-background ratio in human cells, mouse proT cells, and highly autofluorescent formalin-fixed paraffin-embedded (FFPE) human breast tissue sections. Further, we demonstrate multiplex imaging of three different protein:protein complexes simultaneously and validate that HCR enables accurate and precise relative quantitation of protein:protein complexes with subcellular resolution in an anatomical context. Moreover, we establish a unified framework for simultaneous multiplex, quantitative, high-resolution imaging of RNA, protein, and protein:protein targets, with one-step, isothermal, enzyme-free HCR signal amplification performed for all target classes simultaneously.

An autocatalytic multicomponent DNAzyme nanomachine for tumor-specific photothermal therapy sensitization in pancreatic cancer

Multicomponent deoxyribozymes (MNAzymes) have great potential in gene therapy, but their ability to recognize disease tissue and further achieve synergistic gene regulation has rarely been studied. Herein, Arginylglycylaspartic acid (RGD)-modified Distearyl acylphosphatidyl ethanolamine (DSPE)-polyethylene glycol (PEG) (DSPE-PEG-RGD) micelle is prepared with a DSPE hydrophobic core to load the photothermal therapy (PTT) dye IR780 and the calcium efflux pump inhibitor curcumin. Then, the MNAzyme is distributed into the hydrophilic PEG layer and sealed with calcium phosphate through biomineralization. Moreover, RGD is attached to the outer tail of PEG for tumor targeting. The constructed nanomachine can release MNAzyme and the cofactor Ca2+ under acidic conditions and self-assemble into an active mode to cleave heat shock protein (HSP) mRNA by consuming the oncogene miRNA-21. Silencing miRNA-21 enhances the expression of the tumor suppressor gene PTEN, leading to PTT sensitization. Meanwhile, curcumin maintains high intracellular Ca2+ to further suppress HSP-chaperone ATP by disrupting mitochondrial Ca2+ homeostasis. Therefore, pancreatic cancer is triple-sensitized to IR780-mediated PTT. The in vitro and in vivo results show that the MNAzyme-based nanomachine can strongly regulate HSP and PTEN expression and lead to significant pancreatic tumor inhibition under laser irradiation.

Temporal logic circuits implementation using a dual cross-inhibition mechanism based on DNA strand displacement

Molecular circuits crafted from DNA molecules harness the inherent programmability and biocompatibility of DNA to intelligently steer molecular machines in the execution of microscopic tasks. In comparison to combinational circuits, DNA-based temporal circuits boast supplementary capabilities, allowing them to proficiently handle the omnipresent temporal information within biochemical systems and life sciences. However, the lack of temporal mechanisms and components proficient in comprehending and processing temporal information presents challenges in advancing DNA circuits that excel in complex tasks requiring temporal control and time perception. In this study, we engineered temporal logic circuits through the design and implementation of a dual cross-inhibition mechanism, which enables the acceptance and processing of temporal information, serving as a fundamental building block for constructing temporal circuits. By incorporating the dual cross-inhibition mechanism, the temporal logic gates are endowed with cascading capabilities, significantly enhancing the inhibitory effect compared to a cross-inhibitor. Furthermore, we have introduced the annihilation mechanism into the circuit to further augment the inhibition effect. As a result, the circuit demonstrates sensitive time response characteristics, leading to a fundamental improvement in circuit performance. This architecture provides a means to efficiently process temporal signals in DNA strand displacement circuits. We anticipate that our findings will contribute to the design of complex temporal logic circuits and the advancement of molecular programming.

Rapid Signal Amplification Based on Planetary Cross-Catalytic Hairpin Assembly Reactions

Non-enzymatic nucleic acid catalytic systems based on branch migration have been developed, with applications ranging from biological sensing to molecular computation. A scalable planetary cross-catalytic (PCC) system is built up in this work by cross-cascading three planetary catalytic hairpin assembly (CHA) reactions with a central three-arm-branched CHA reaction. With the bottom-up hierarchy strategy, we designed four levels of catalytic reactions, simple CHA reactions, two-layered linear cascades, conventional one-planetary PCC reactions, and two- and three-planetary PCC reactions, and examined the reaction products and intermediates in each level via native polyacrylamide gel electrophoresis. The gel shift assay optimized the designs of hairpin strands to keep the leaking reactions at a manageable level and protect against signal attenuation during serial signal transduction in nucleic acid circuits. The reaction kinetics, measured via fluorescence, are strongly dependent on the number of planetary reactions. As a result, the three-planetary PCC system achieved an exponential amplification factor of about 3^k, while the conventional one-planetary cross-catalytic system has an amplification factor of 2^k (k represents the cycling number). Finally, we demonstrated the rapid detection of a cancer biomarker, microRNA141, used as the catalyst in a two-planetary PCC system. We envision that the PCC systems could be applied in biological signal transduction, biocomputing, rapid detection of single- and multi-target nucleic acid probes, etc.

A hairpin probe-mediated exponential amplification reaction for highly sensitive and specific detection of microRNAs

In this work, we propose a hairpin probe-mediated exponential amplification reaction (HEAR) strategy that combines DNA strand displacement with a "who triggers, who gets generated" mode, providing excellent single-base discrimination and a reduced background signal. The detection limit is 19 aM, which is reduced by 3 orders of magnitude compared to traditional exponential amplification approaches. This one-pot strategy also exhibits a wide dynamic range, high specificity and short detection time. It is expected to become a powerful tool for clinical diagnosis.

Simultaneous identification of viruses and viral variants with programmable DNA nanobait

Respiratory infections are the major cause of death from infectious disease worldwide. Multiplexed diagnostic approaches are essential as many respiratory viruses have indistinguishable symptoms. We created self-assembled DNA nanobait that can simultaneously identify multiple short RNA targets. The nanobait approach relies on specific target selection via toehold-mediated strand displacement and rapid readout via nanopore sensing. Here we show that this platform can concurrently identify several common respiratory viruses, detecting a panel of short targets of viral nucleic acids from multiple viruses. Our nanobait can be easily reprogrammed to discriminate viral variants with single-nucleotide resolution, as we demonstrated for several key SARS-CoV-2 variants. Last, we show that the nanobait discriminates between samples extracted from oropharyngeal swabs from negative- and positive-SARS-CoV-2 patients without preamplification. Our system allows for the multiplexed identification of native RNA molecules, providing a new scalable approach for the diagnostics of multiple respiratory viruses in a single assay.

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.

Toehold-Mediated Strand Displacement in Random Sequence Pools

Toehold-mediated strand displacement (TMSD) has been used extensively for molecular sensing and computing in DNA-based molecular circuits. As these circuits grow in complexity, sequence similarity between components can lead to cross-talk, causing leak, altered kinetics, or even circuit failure. For small non-biological circuits, such unwanted interactions can be designed against. In environments containing a huge number of sequences, taking all possible interactions into account becomes infeasible. Therefore, a general understanding of the impact of sequence backgrounds on TMSD reactions is of great interest. Here, we investigate the impact of random DNA sequences on TMSD circuits. We begin by studying individual interfering strands and use the obtained data to build machine learning models that estimate kinetics. We then investigate the influence of pools of random strands and find that the kinetics are determined by only a small subpopulation of strongly interacting strands. Consequently, their behavior can be mimicked by a small collection of such strands. The equilibration of the circuit with the background sequences strongly influences this behavior, leading to up to 1 order of magnitude difference in reaction speed. Finally, we compare two established and one novel technique that speed up TMSD reactions in random sequence pools: a three-letter alphabet, protection of toeholds by intramolecular secondary structure, or by an additional blocking strand. While all of these techniques were useful, only the latter can be used without sequence constraints. We expect that our insights will be useful for the construction of TMSD circuits that are robust to molecular noise.

Tunable and Modular miRNA Classifier through Indirect Associative Toehold Strand Displacement

The programmability of nucleic acids allows detection devices with complex behaviors to be designed de novo. While highly specific, these high-order circuits are usually sequence constrained, making their adaptability toward biological targets challenging. Here, we devise a new strategy called indirect associative strand displacement to decouple sequence constraints between miRNA inputs and de novo strand displacement circuits. By splitting circuit inputs into their toehold and branch migration regions and controlling their association through a docking strand, we demonstrate how any miRNA sequence can be interfaced with synthetic DNA circuits, including catalytic hairpin assembly and a four-input classifier.

Conditionally designed luminescent DNA crystals doped by Ln3+(Eu3+/Tb3+) complexes or fluorescent proteins with smart drug sensing property

In this work, a designed porous DNA crystal with high intrinsic biocompatibility was used as the scaffold material to load fluorescent guest molecules to detect anti-cancer drugs. It is shown here that the synthesized crystals have the characteristics consistent with the designed large solvent channels, and can therefore accommodate guest molecules such as fluorescent proteins that cannot be accommodated by less porous crystals. Eu(TTA)₃phen and Tb(acac)₃phen lanthanide complexes were individually noncovalently loaded into the porous crystals, resulting in hybrid luminescent DNA crystals. Emodin, an anti-cancer, anti-tumor, anti-inflammatory drug, was found to quench lanthanide complexes in solution or in crystals. Notably, emodin is the active ingredient of Lianhua Qingwen Capsule, an anti-COVID-19 drug candidate. Therefore, the porous DNA crystals reported here have potential applications as a biocompatible and theranostic delivery biomaterial for functional macromolecules.

Pairing statistics and melting of random DNA oligomers: Finding your partner in superdiverse environments

Understanding of the pairing statistics in solutions populated by a large number of distinct solute species with mutual interactions is a challenging topic, relevant in modeling the complexity of real biological systems. Here we describe, both experimentally and theoretically, the formation of duplexes in a solution of random-sequence DNA (rsDNA) oligomers of length L = 8, 12, 20 nucleotides. rsDNA solutions are formed by 4^L distinct molecular species, leading to a variety of pairing motifs that depend on sequence complementarity and range from strongly bound, fully paired defectless helices to weakly interacting mismatched duplexes. Experiments and theory coherently combine revealing a hybridization statistics characterized by a prevalence of partially defected duplexes, with a distribution of type and number of pairing errors that depends on temperature. We find that despite the enormous multitude of inter-strand interactions, defectless duplexes are formed, involving a fraction up to 15% of the rsDNA chains at the lowest temperatures. Experiments and theory are limited here to equilibrium conditions.

Several biological processes require that specific partner molecules succeed in binding after negotiating their way through a huge number of interactions with other molecules. How such molecular recognition emerges among millions distinct molecular species is an open problem. We have studied, both experimentally and theoretically, such process of “molecular recognition” in pools of highly diverse random DNA oligomers, which binds preferentially, but not exclusively, to its perfect complementary sequence. We find a complex behavior, in which some perfect pairing takes place with a non-trivial temperature dependence that we understand thorough statistical mechanics modelling. The pairing pattern of short random DNA is relevant in the context of the origin of life since the so-called “RNA World” was most probably based on the mutual recognition of random chains.

Self-assembly of DNA Nanogels with Endogenous MicroRNA Toehold Self-regulating Switches for Targeted Gene Regulation Therapy

Herein, a smart nanohydrogel with endogenous microRNA-21 toehold is developed to encapsulate gemcitabine-loaded mesoporous silica nanoparticles for targeted pancreatic cancer therapy. This toehold mediated strand displacement method can simultaneously achieve...

RNA Structure Prediction, Analysis, and Design: An Introduction to Web-Based Tools

Understanding RNA structure has become critical in the study of RNA in their roles as mediators of biological processes. To aid in these studies, computational algorithms that utilize thermodynamics have been developed to predict RNA secondary structure. Due to the importance of intermolecular interactions, the algorithms have been expanded to determine and predict RNA-RNA hybridization. This chapter discusses popular webservers with the tools for RNA secondary structure prediction, RNA-RNA hybridization, and design. We address key features that distinguish common-functioning programs and their purposes for the interests of the user. Ultimately, we hope this review elucidates web-based tools researchers may take advantage of in their investigations of RNA structure and function.

Computational Design of Small Transcription Activating RNAs (STARs)

A major goal of synthetic biology has been to develop libraries of versatile genetic regulators that enable the precise control of gene expression. In recent years, the creation of novel RNA design motifs has allowed for the bottom-up, computational design of large libraries of high-performing and orthogonal RNA regulator systems. One example of this is Small Transcription Activating RNAs (STARs), which function through the conditional formation of terminator hairpins to activate the transcription of targeted genes. STARs have found broad utility for creating synthetic gene circuits, engineering metabolic pathways, and creating new types of diagnostics. Here we describe the method to computationally design, build, and characterize STAR regulators.

RNA self-splicing by engineered hairpin ribozyme variants

Small RNAs capable of self-cleavage and ligation might have been the precursors for the much more complex self-splicing group I and II introns in an early RNA world. Here, we demonstrate the activity of engineered hairpin ribozyme variants, which as self-splicing introns are removed from their parent RNA. In the process, two cleavage reactions are supported at the two intron-exon junctions, followed by ligation of the two generated exon fragments. As a result, the hairpin ribozyme, here acting as the self-splicing intron, is cut out. Two self-splicing hairpin ribozyme variants were investigated, one designed by hand, the other by a computer-aided approach. Both variants perform self-splicing, generating a cut-out intron and ligated exons.

Controlling Gene Expression in Mammalian Cells Using Multiplexed Conditional Guide RNAs for Cas12a*

Spatiotemporal control of the activity of CRISPR-associated (Cas) proteins is of considerable interest for basic research and therapeutics. Here, we show that conditional guide RNAs (gRNAs) for Cas12a can be transcribed in mammalian cells by RNA polymerase II, followed by activation via input-dependent processing of the 3' tail of the gRNA transcript. We demonstrate processing using an RNA strand displacement mechanism, as well as microRNA-dependent processing, and cleavage by a guanine-responsive ribozyme. We further demonstrate that Cas12a along with several independently switchable gRNAs can be compactly integrated on a single transcript using stabilizing RNA triplexes, providing a route towards Cas12a-based gene regulation constructs with multi-input switching capabilities. The principle is shown to work in HEK and mouse fibroblast cells using luminescence, fluorescence, and is also demonstrated for the conditional upregulation of an endogenous gene.

SARS-CoV-2 Detection with De Novo-Designed Synthetic Riboregulators

SARS-CoV-2 is a human pathogen and the main cause of COVID-19 disease, announced as a global pandemic by the World Health Organization. COVID-19 is characterized by severe conditions, and early diagnosis can make dramatic changes for both personal and public health. Low-cost, easy-to-use diagnostic capabilities can have a very critical role in controlling the transmission of the disease. Here, we are reporting a state-of-the-art diagnostic tool developed with an in vitro synthetic biology approach by employing engineered de novo riboregulators. Our design coupled with a home-made point-of-care device can detect and report the presence of SARS-CoV-2-specific genes. The presence of SARS-CoV-2-related genes triggers the translation of sfGFP mRNAs, resulting in a green fluorescence output. The approach proposed here has the potential of being a game changer in SARS-CoV-2 diagnostics by providing an easy-to-run, low-cost diagnostic capability.

A CRISPR-based and post-amplification coupled SARS-CoV-2 detection with a portable evanescent wave biosensor

The continuing pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which causes coronavirus disease 2019 (COVID-19), has spread globally and its reliable diagnosis is one of the foremost priorities for protecting public health. Herein a rapid (<1 h), easy-to-implement, and accurate CRISPR-based evanescent wave fluorescence biosensing platform for detection of SARS-CoV-2 is reported. The collateral effect of Cas13a is combined with a universal autonomous enzyme-free hybridization chain reaction (HCR) by designing a cleavage hairpin reporter, which is cleaved upon target recognition, and hence releasing the initiator sequence to trigger the downstream HCR circuits. Detection of HCR assemblies is accomplished by first adsorbing to the desthiobiotin-modified optical fiber, followed by fluorescence emission induced by an evanescent field. Three Cas13a crRNAs targeting the genes of S, N and Orf1ab of SARS-CoV-2 are programmed to specifically target SARS-CoV-2 or broadly detect related coronavirus strains, such as MERS-CoV and SARS-CoV. The HCR amplification coupled Cas13a-based biosensing platform is capable of rapid detection of SARS-CoV-2 with attomolar sensitivity. This method is further validated by adding target RNA of SARS-CoV-2 in negative oropharyngeal swabs. The good discrimination capability of this technique demonstrates its promising potential for point-of-care diagnosis of COVID-19.

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.

Genetically encoded RNA nanodevices for cellular imaging and regulation

Nucleic acid-based nanodevices have been widely used in the fields of biosensing and nanomedicine. Traditionally, the majority of these nanodevices were first constructed in vitro using synthetic DNA or RNA oligonucleotides and then delivered into cells. Nowadays, the emergence of genetically encoded RNA nanodevices has provided a promising alternative approach for intracellular analysis and regulation. These genetically encoded RNA-based nanodevices can be directly transcribed and continuously produced inside living cells. A variety of highly precise and programmable nanodevices have been constructed in this way during the last decade. In this review, we will summarize the recent advances in the design and function of these artificial genetically encoded RNA nanodevices. In particular, we will focus on their applications in regulating cellular gene expression, imaging, logic operation, structural biology, and optogenetics. We believe these versatile RNA-based nanodevices will be broadly used in the near future to probe and program cells and other biological systems.

Boolean logic gate based on DNA strand displacement for biosensing: current and emerging strategies

DNA computers are considered one of the most prominent next-generation molecular computers that perform Boolean logic using DNA elements. DNA-based Boolean logic gates, especially DNA strand displacement-based logic gates (SDLGs), have shown tremendous potential in biosensing since they can perform the logic analysis of multi-targets simultaneously. Moreover, SDLG biosensors generate a unique output in the form of YES/NO, which is contrary to the quantitative measurement used in common biosensors. In this review, the recent achievements of SDLG biosensing strategies are summarized. Initially, the development and mechanisms of Boolean logic gates, strand-displacement reaction, and SDLGs are introduced. Afterwards, the diversified input and output of SDLG biosensors are elaborated. Then, the state-of-the-art SDLG biosensors are reviewed in the classification of different signal-amplification methods, such as rolling circle amplification, catalytic hairpin assembly, strand-displacement amplification, DNA molecular machines, and DNAzymes. Most importantly, limitations and future trends are discussed. The technology reviewed here is a promising tool for multi-input analysis and lays a foundation for intelligent diagnostics.

Inverse RNA Folding Workflow to Design and Test Ribozymes that Include Pseudoknots

Ribozymes are RNAs that catalyze reactions. They occur in nature, and can also be evolved in vitro to catalyze novel reactions. This chapter provides detailed protocols for using inverse folding software to design a ribozyme sequence that will fold to a known ribozyme secondary structure and for testing the catalytic activity of the sequence experimentally. This protocol is able to design sequences that include pseudoknots, which is important as all naturally occurring full-length ribozymes have pseudoknots. The starting point is the known pseudoknot-containing secondary structure of the ribozyme and knowledge of any nucleotides whose identity is required for function. The output of the protocol is a set of sequences that have been tested for function. Using this protocol, we were previously successful at designing highly active double-pseudoknotted HDV ribozymes.

Sequence-independent RNA sensing and DNA targeting by a split domain CRISPR-Cas12a gRNA switch

CRISPR technologies increasingly require spatiotemporal and dosage control of nuclease activity. One promising strategy involves linking nuclease activity to a cell's transcriptional state by engineering guide RNAs (gRNAs) to function only after complexing with a ‘trigger’ RNA. However, standard gRNA switch designs do not allow independent selection of trigger and guide sequences, limiting gRNA switch application. Here, we demonstrate the modular design of Cas12a gRNA switches that decouples selection of these sequences. The 5′ end of the Cas12a gRNA is fused to two distinct and non-overlapping domains: one base pairs with the gRNA repeat, blocking formation of a hairpin required for Cas12a recognition; the other hybridizes to the RNA trigger, stimulating refolding of the gRNA repeat and subsequent gRNA-dependent Cas12a activity. Using a cell-free transcription-translation system and Escherichia coli, we show that designed gRNA switches can respond to different triggers and target different DNA sequences. Modulating the length and composition of the sensory domain altered gRNA switch performance. Finally, gRNA switches could be designed to sense endogenous RNAs expressed only under specific growth conditions, rendering Cas12a targeting activity dependent on cellular metabolism and stress. Our design framework thus further enables tethering of CRISPR activities to cellular states.

A Web Server for Designing Molecular Switches Composed of Two Interacting RNAs

The programmability of RNA–RNA interactions through intermolecular base-pairing has been successfully exploited to design a variety of RNA devices that artificially regulate gene expression. An in silico design for interacting structured RNA sequences that satisfies multiple design criteria becomes a complex multi-objective problem. Although multi-objective optimization is a powerful technique that explores a vast solution space without empirical weights between design objectives, to date, no web service for multi-objective design of RNA switches that utilizes RNA–RNA interaction has been proposed. We developed a web server, which is based on a multi-objective design algorithm called MODENA, to design two interacting RNAs that form a complex in silico. By predicting the secondary structures with RactIP during the design process, we can design RNAs that form a joint secondary structure with an external pseudoknot. The energy barrier upon the complex formation is modeled by an interaction seed that is optimized in the design algorithm. We benchmarked the RNA switch design approaches (MODENA+RactIP and MODENA+RNAcofold) for the target structures based on natural RNA-RNA interactions. As a result, MODENA+RactIP showed high design performance for the benchmark datasets.

Handhold-Mediated Strand Displacement: A Nucleic Acid Based Mechanism for Generating Far-from-Equilibrium Assemblies through Templated Reactions

The use of templates is a well-established method for the production of sequence-controlled assemblies, particularly long polymers. Templating is canonically envisioned as akin to a self-assembly process, wherein sequence-specific recognition interactions between a template and a pool of monomers favor the assembly of a particular polymer sequence at equilibrium. However, during the biogenesis of sequence-controlled polymers, template recognition interactions are transient; RNA and proteins detach spontaneously from their templates to perform their biological functions and allow template reuse. Breaking template recognition interactions puts the product sequence distribution far from equilibrium, since specific product formation can no longer rely on an equilibrium dominated by selective copy-template bonds. The rewards of engineering artificial polymer systems capable of spontaneously exhibiting nonequilibrium templating are large, but fields like DNA nanotechnology lack the requisite tools; the specificity and drive of conventional DNA reactions rely on product stability at equilibrium, sequestering any recognition interaction in products. The proposed alternative is handhold-mediated strand displacement (HMSD), a DNA-based reaction mechanism suited to producing out-of-equilibrium products. HMSD decouples the drive and specificity of the reaction by introducing a transient recognition interaction, the handhold. We measure the kinetics of 98 different HMSD systems to prove that handholds can accelerate displacement by 4 orders of magnitude without being sequestered in the final product. We then use HMSD to template the selective assembly of any one product DNA duplex from an ensemble of equally stable alternatives, generating a far-from-equilibrium output. HMSD thus brings DNA nanotechnology closer to the complexity of out-of-equilibrium biological systems.

A CRISPR-Cas autocatalysis-driven feedback amplification network for supersensitive DNA diagnostics

Artificial nucleic acid circuits with precisely controllable dynamic and function have shown great promise in biosensing, but their utility in molecular diagnostics is still restrained by the inability to process genomic DNA directly and moderate sensitivity. To address this limitation, we present a CRISPR-Cas-powered catalytic nucleic acid circuit, namely, CRISPR-Cas-only amplification network (CONAN), for isothermally amplified detection of genomic DNA. By integrating the stringent target recognition, helicase activity, and trans-cleavage activity of Cas12a, a Cas12a autocatalysis-driven artificial reaction network is programmed to construct a positive feedback circuit with exponential dynamic in CONAN. Consequently, CONAN achieves one-enzyme, one-step, real-time detection of genomic DNA with attomolar sensitivity. Moreover, CONAN increases the intrinsic single-base specificity of Cas12a, and enables the effective detection of hepatitis B virus infection and human bladder cancer-associated single-nucleotide mutation in clinical samples, highlighting its potential as a powerful tool for disease diagnostics.

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.

A molecular device: A DNA molecular lock driven by the nicking enzymes

As people are placing more and more importance on information security, how to realize the protection of information has become a hotspot of current research. As a security device, DNA molecular locks have great potential to realize information protection at the molecular level. However, building a highly secure molecular lock is still a serious challenge. Therefore, taking advantage of the DNA strand displacement and enzyme control technology, we constructed a molecular lock with a self-destructive mechanism. This molecular lock is mainly composed of logic circuits and takes nicking enzymes as inputs. To build this molecular lock, we first constructed a series of cascade circuits, including a YES–YES cascade circuit and a YES–AND cascade circuit. Then, an Inhibit logic gate was constructed to explore the inhibitory properties between different combinations of two nicking enzymes. Finally, using the characteristics of mutual inhibition between several enzymes, a DNA molecular lock driven by three nicking enzymes was constructed. In this molecular device, only the correct sequence of nicking enzymes can be input to ensure the normal operation of the molecular lock. Once the wrong password is entered, the device will be destroyed and cannot be recovered, which effectively prevents intruders from cracking the lock through exhaustive methods. The molecular lock has the function of simulating an electronic keyboard, which can realize the protection of information at the molecular level, and provides a new implementation method for building more advanced and complex molecular devices.

Domain-Specific Programming Languages for Computational Nucleic Acid Systems

The construction of models of system behavior is of great importance throughout science and engineering. In bioengineering and bionanotechnology, these often take the form of dynamic models that specify the evolution of different species over time. To ensure that scientific observations and conclusions are consistent and that systems can be reliably engineered on the basis of model predictions, it is important that models of biomolecular systems can be constructed in a reliable, principled, and efficient manner. This review focuses on efforts to address this need by using domain-specific programming languages as the basis for custom design tools for researchers working on computational nucleic acid devices, where a domain-specific language is simply a programming language tailored to a particular application domain. The underlying thesis of our review is that there is a continuum of practical implementation strategies for computational nucleic acid systems, which can all benefit from appropriate domain-specific languages and software design tools. We emphasize the need for specialized yet flexible tools that can be realized using domain-specific languages that compile to more general-purpose representations.

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.

Improved Nucleic Acid Therapy with Advanced Nanoscale Biotechnology

Due to a series of systemic and intracellular obstacles in nucleic acid (NA) therapy, including fast degradation in blood, renal clearance, poor cellular uptake, and inefficient endosomal escape, NAs may need delivery methods to transport to the cell nucleus or cytosol to be effective. Advanced nanoscale biotechnology-associated strategies, such as controlling the particle size, charge, drug loading, response to environmental signals, or other physical/chemical properties of delivery carriers, have provided great help for the in vivo and in vitro delivery of NA therapeutics. In this review, we introduce the characteristics of different NA modalities and illustrate how advanced nanoscale biotechnology assists NA therapy. The specific features and challenges of various nanocarriers in clinical and preclinical studies are summarized and discussed. With the help of advanced nanoscale biotechnology, some of the major barriers to the development of NA therapy will eventually be overcome in the near future.

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.

Synthetic bionanotechnology: synthetic biology finds a toehold in nanotechnology

Enabled by its central role in the molecular networks that govern cell function, RNA has been widely used for constructing components used in biological circuits for synthetic biology. Nucleic acid nanotechnology, which exploits predictable nucleic acid interactions to implement programmable molecular systems, has seen remarkable advances in in vitro nanoscale self-assembly and molecular computation, enabling the production of complex nanostructures and DNA-based neural networks. Living cells genetically engineered to execute nucleic acid nanotechnology programs thus have outstanding potential to significantly extend the current limits of synthetic biology. This perspective discusses the recent developments and future challenges in the field of synthetic bionanotechnology. Thus far, researchers in this emerging area have implemented dozens of programmable RNA nanodevices that provide precise control over gene expression at the transcriptional and translational levels and through CRISPR/Cas effectors. Moreover, they have employed synthetic self-assembling RNA networks in engineered bacteria to carry out computations featuring up to a dozen inputs and to substantially enhance the rate of chemical synthesis. Continued advancement of the field will benefit from improved in vivo strategies for streamlining nucleic acid network synthesis and new approaches for enhancing network function. As the field matures and the complexity gap between in vitro and in vivo systems narrows, synthetic bionanotechnology promises to have diverse potential applications ranging from intracellular circuits that detect and treat disease to synthetic enzymatic pathways that efficiently produce novel drug molecules.

Multitag-Regulated Cascade Reaction: A Generalizable Ultrasensitive MicroRNA Biosensing Approach for Cancer Prognosis

Ultrasensitive PCR-free microRNA (miR) analysis based on biosensors with enzyme-free nucleic acid amplification and reusable surface has great clinical significance in cancer prognosis. However, building such a biosensing strategy has long been challenging due to uncontrollable miR-triggered cascade amplifiers and insufficient sensing surface regeneration capability. To meet the challenge, for the first time, a general approach, named enzyme-free multitag-regulated cascade reaction (MCR), is developed to fabricate reliable trace miR biosensors. As a proof of concept, miR let-7a is detected on an evanescent wave fluorescent optical-fiber biosensing platform. The size and morphology of well-formed MCR assemblies (∼1 μm in length) are characterized by atomic force microscopy. This MCR method achieves a 30 000-fold improved sensitivity (detection limit 0.8 fM) compared to the MCR-free system and can detect abnormal urinary miR levels in lung cancer patients. Moreover, the biosensor is robust enough to be reused for over 100 cycles, which greatly reduces the cost of single detection. In sum, MCR is developed as a generalizable ultrasensitive miR biosensing approach for cancer prognosis, which opens a broad field for facile enzyme-free biosensing applications by nucleic acid assembling regulation.

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.

A pipeline for computational design of novel RNA-like topologies

Designing novel RNA topologies is a challenge, with important therapeutic and industrial applications. We describe a computational pipeline for design of novel RNA topologies based on our coarse-grained RNA-As-Graphs (RAG) framework. RAG represents RNA structures as tree graphs and describes RNA secondary (2D) structure topologies (currently up to 13 vertices, ≈260 nucleotides). We have previously identified novel graph topologies that are RNA-like among these. Here we describe a systematic design pipeline and illustrate design for six broad design problems using recently developed tools for graph-partitioning and fragment assembly (F-RAG). Following partitioning of the target graph, corresponding atomic fragments from our RAG-3D database are combined using F-RAG, and the candidate atomic models are scored using a knowledge-based potential developed for 3D structure prediction. The sequences of the top scoring models are screened further using available tools for 2D structure prediction. The results indicate that our modular approach based on RNA-like topologies rather than specific 2D structures allows for greater flexibility in the design process, and generates a large number of candidate sequences quickly. Experimental structure probing using SHAPE-MaP for two sequences agree with our predictions and suggest that our combined tools yield excellent candidates for further sequence and experimental screening.

EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame

Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold into specific base-pairing patterns, but computational algorithms generally remain inadequate for these secondary structure design tasks. The Eterna project has crowdsourced RNA design to human video game players in the form of puzzles that reach extraordinary difficulty. Here, we demonstrate that Eterna participants' moves and strategies can be leveraged to improve automated computational RNA design. We present an eternamoves-large repository consisting of 1.8 million of player moves on 12 of the most-played Eterna puzzles as well as an eternamoves-select repository of 30,477 moves from the top 72 players on a select set of more advanced puzzles. On eternamoves-select, we present a multilayer convolutional neural network (CNN) EternaBrain that achieves test accuracies of 51% and 34% in base prediction and location prediction, respectively, suggesting that top players' moves are partially stereotyped. Pipelining this CNN's move predictions with single-action-playout (SAP) of six strategies compiled by human players solves 61 out of 100 independent puzzles in the Eterna100 benchmark. EternaBrain-SAP outperforms previously published RNA design algorithms and achieves similar or better performance than a newer generation of deep learning methods, while being largely orthogonal to these other methods. Our study provides useful lessons for future efforts to achieve human-competitive performance with automated RNA design algorithms.

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.