RNA synthetic biology

Building RNA-Mediated Artificial Signaling Pathways between Endogenous Genes

ConspectusSophisticated genetic networks play a pivotal role in orchestrating cellular responses through intricate signaling pathways across diverse environmental conditions. Beyond the inherent complexity of natural cellular signaling networks, the construction of artificial signaling pathways (ASPs) introduces a vast array of possibilities for reshaping cellular responses, enabling programmable control of living organisms. ASPs can be integrated with existing cellular networks and redirect output responses as desired, allowing seamless communication and coordination with other cellular processes, thereby achieving designable transduction within cells. Among diversified ASPs, establishing connections between originally independent endogenous genes is of particular significance in modifying the genetic networks, so that cells can be endowed with new capabilities to sense and deal with abnormal factors related to differentiated gene expression (i.e., solve the issues of the aberrant gene expression induced by either external or internal stimuli). In a typical scenario, the two genes X and Y in the cell are originally expressed independently. After the introduction of an ASP, changes in the expression of gene X may exert a designed impact on gene Y, subsequently inducing the cellular response related to gene Y. If X represents a disease signal and Y serves as a therapeutic module, the introduction of the ASP empowers cells with a new spontaneous defense system to handle potential risks, which holds great potential for both fundamental and translational studies.In this Account, we primarily review our endeavors in the construction of RNA-mediated ASPs between endogenous genes that can respond to differentiated RNA expression. In contrast to other molecules that may be restricted to specific pathways, synthetic RNA circuits can be easily utilized and expanded as a general platform for constructing ASPs with a high degree of programmability and tunability for diversified functionalities through predictable Watson-Crick base pairing. We first provide an overview of recent advancements in RNA-based genetic circuits, encompassing but not limited to utilization of RNA toehold switches, siRNA and CRISPR systems. Despite notable progress, most reported RNA circuits have to contain at least one exogenous RNA X as input or one engineered RNA Y as a target, which is not suitable for establishing endogenous gene connections. While exogenous RNAs can be engineered and controlled as desired, constructing a general and efficient platform for manipulation of naturally occurring RNAs poses a formidable challenge, especially for the mammalian system. With a focus on this goal, we are devoted to developing efficient strategies to manipulate cell responses by establishing RNA-mediated ASPs between endogenous genes, particularly in mammalian cells. Our step-by-step progress in engineering customized cell signaling circuits, from bacterial cells to mammalian cells, from gene expression regulation to phenotype control, and from small RNA to long mRNA of low abundance and more complex secondary structures, is systematically described. Finally, future perspectives and potential applications of these RNA-mediated ASPs between endogenous genes are also discussed.

Circular single-stranded DNA as a programmable vector for gene regulation in cell-free protein expression systems

Cell-free protein expression (CFE) systems have emerged as a critical platform for synthetic biology research. The vectors for protein expression in CFE systems mainly rely on double-stranded DNA and single-stranded RNA for transcription and translation processing. Here, we introduce a programmable vector - circular single-stranded DNA (CssDNA), which is shown to be processed by DNA and RNA polymerases for gene expression in a yeast-based CFE system. CssDNA is already widely employed in DNA nanotechnology due to its addressability and programmability. To apply above methods in the context of synthetic biology, CssDNA can not only be engineered for gene regulation via the different pathways of sense CssDNA and antisense CssDNA, but also be constructed into several gene regulatory logic gates in CFE systems. Our findings advance the understanding of how CssDNA can be utilized in gene expression and gene regulation, and thus enrich the synthetic biology toolbox.

RNA Control via Redox-Responsive Acylation

Incorporating stimuli-responsive components into RNA constructs provides precise spatiotemporal control over RNA structures and functions. Despite considerable advancements, the utilization of redox-responsive stimuli for the activation of caged RNAs remains scarce. In this context, we present a novel strategy that leverages post-synthetic acylation coupled with redox-responsive chemistry to exert control over RNA. To achieve this, we design and synthesize a series of acylating reagents specifically tailored for introducing disulfide-containing acyl adducts into the 2'-OH groups of RNA ("cloaking"). Our data reveal that these acyl moieties can be readily appended, effectively blocking RNA catalytic activity and folding. We also demonstrate the traceless release and reactivation of caged RNAs ("uncloaking") through reducing stimuli. By employing this strategy, RNA exhibits rapid cellular uptake, effective distribution and activation in the cytosol without lysosomal entrapment. We anticipate that our methodology will be accessible to laboratories engaged in RNA biology and holds promise as a versatile platform for RNA-based applications.

Investigating the Effect of RNA Scaffolds on the Multicolor Fluorogenic Aptamer Pepper in Different Bacterial Species

RNA synthetic biology tools have primarily been applied in E. coli; however, many other bacteria are of industrial and clinical significance. Thus, the multicolor fluorogenic aptamer Pepper was evaluated in both Gram-positive and Gram-negative bacteria. Suitable HBC-Pepper dye pairs were identified that give blue, green, or red fluorescence signals in the E. coli, Bacillus subtilis, and Salmonella enterica serovar Typhimurium (S. Typhimurium). Furthermore, we found that different RNA scaffolds have a drastic effect on in vivo fluorescence, which did not correlate with the in vitro folding efficiency. One such scaffold termed DF30-tRNA displays 199-fold greater fluorescence than the Pepper aptamer alone and permits simultaneous dual color imaging in live cells.

dCas12a:Pre-crRNA: A New Tool to Induce mRNA Degradation in Saccharomyces cerevisiae Synthetic Gene Circuits

We describe a new way to trigger mRNA degradation in Saccharomyces cerevisiae synthetic gene circuits. Our method demands to modify either the 5'- or the 3'-UTR that flanks a target gene with elements from the pre-crRNA of type V Cas12a proteins and expresses a DNase-deficient Cas12a (dCas12a). dCas12a recognizes and cleaves the pre-crRNA motifs on mRNA sequences. Our tool does not require complex engineering operations and permits an efficient control of protein expression via mRNA degradation.

Evaluating DFHBI-Responsive RNA Light-Up Aptamers as Fluorescent Reporters for Gene Expression

Protein-based fluorescent reporters have been widely used to characterize and localize biological processes in living cells. However, these reporters may have certain drawbacks for some applications, such as transcription-based studies or biological interactions with fast dynamics. In this context, RNA nanotechnology has emerged as a promising alternative, suggesting the use of functional RNA molecules as transcriptional fluorescent reporters. RNA-based aptamers can bind to nonfluorescent small molecules to activate their fluorescence. However, their performance as reporters of gene expression in living cells has not been fully characterized, unlike protein-based reporters. Here, we investigate the performance of three RNA light-up aptamers─F30-2xdBroccoli, tRNA-Spinach, and Tornado Broccoli─as fluorescent reporters for gene expression in Escherichia coli and compare them to a protein reporter. We examine the activation range and effect on the cell growth of RNA light-up aptamers in time-course experiments and demonstrate that these aptamers are suitable transcriptional reporters over time. Using flow cytometry, we compare the variability at the single-cell level caused by the RNA fluorescent reporters and protein-based reporters. We found that the expression of RNA light-up aptamers produced higher variability in a population than that of their protein counterpart. Finally, we compare the dynamical behavior of these RNA light-up aptamers and protein-based reporters. We observed that RNA light-up aptamers might offer faster dynamics compared to a fluorescent protein in E. coli. The implementation of these transcriptional reporters may facilitate transcription-based studies, gain further insights into transcriptional processes, and expand the implementation of RNA-based circuits in bacterial cells.

Counting Distinguishable RNA Secondary Structures

RNA secondary structures are essential abstractions for understanding spacial folding behaviors of those macromolecules. Many secondary structure algorithms involve a common dynamic programming setup to exploit the property that secondary structures can be decomposed into substructures. Dirks et al. noted that this setup cannot directly address an issue of distinguishability among secondary structures, which arises for classes of sequences that admit nontrivial symmetry. Circular sequences are among these. We examine the problem of counting distinguishable secondary structures. Drawing from elementary results in group theory, we identify useful subsets of secondary structures. We then extend an algorithm due to Hofacker et al. for computing the sizes of these subsets. This yields a cubic-time algorithm to count distinguishable structures compatible with a given circular sequence. Furthermore, this general approach may be used to solve similar problems for which the RNA structures of interest involve symmetries.

Tumor targeting and therapeutic assessments of RNA nanoparticles carrying α9-nAChR aptamer and anti-miR-21 in triple-negative breast cancers

Triple-negative breast cancer (TNBC) is highly aggressive with a poor prognosis because of a lack of cell markers as drug targets. α9-Nicotinic acetylcholine receptor (nAChR) is expressed abundantly in TNBC; thus, it is a valuable biomarker for TNBC detection and treatment. In this study, we utilized thermodynamically stable three-way junction (3WJ) packaging RNA (pRNA) as the core to construct RNA nanoparticles with an α9-nAChR RNA aptamer as a targeting ligand and an anti-microRNA-21 (miR-21) as a therapeutic module. We compared the configuration of the two RNA nanoparticles and found that 3WJ-B-α9-nAChR-aptamer fluorescent RNA nanoparticles (3WJ-B-α9-apt-Alexa) exhibited better specificity for α9-nAChR in TNBC cells compared with 3WJ-C-α9-nAChR. Furthermore, 3WJ-B-α9-apt-Alexa bound more efficiently to TNBC patient-derived xenograft (PDX) tumors than 3WJ fluorescent RNA nanoparticles (3WJ-Alexa) with little or no accumulation in healthy organs after systemic injection in mice. Moreover, 3WJ-B-α9-nAChR-aptamer RNA nanoparticles carrying anti-miR-21 (3WJ-B-α9-apt-anti-miR-21) significantly suppressed TNBC-PDX tumor growth and induced cell apoptosis because of reduced miR-21 gene expression and upregulated the phosphatase and tensin homolog (PTEN) and programmed cell death 4 (PDCD4) proteins. In addition, no pathological changes were detected upon toxicity examination of treated mice. In conclusion, the 3WJ-B-α9-nAChR-aptamer RNA nanoparticles established in this study efficiently deliver therapeutic anti-miR-21, indicating their potential as a novel TNBC therapy.

Cryo-EM-guided engineering of T-box-tRNA modules with enhanced selectivity and sensitivity in translational regulation

Riboswitches are non-coding RNA elements that play vital roles in regulating gene expression. Their specific ligand-dependent structural reorganization facilitates their use as templates for design of engineered RNA switches for therapeutics, nanotechnology and synthetic biology. T-box riboswitches bind tRNAs to sense aminoacylation and control gene expression via transcription attenuation or translation inhibition. Here we determine the cryo-EM structure of the wild-type Mycobacterium smegmatis ileS T-box in complex with its cognate tRNA ^Ile . This structure shows a very flexible antisequestrator region that tolerates both 3'-OH and 2',3'-cyclic phosphate modification at the 3' end of tRNA ^Ile . Elongation of one helical turn (11-base pair) in both the tRNA acceptor arm and T-box Stem III maintains T-box-tRNA complex formation and increases the selectivity for tRNA 3' end modification. Moreover, elongation of Stem III results in ∼6-fold tighter binding to tRNA, which leads to increased sensitivity of downstream translational regulation indicated by precedent translation. Our results demonstrate that cryo-EM can guide RNA engineering to design improved riboswitch modules for translational regulation, and potentially a variety of additional functions.

Sensing intracellular signatures with synthetic mRNAs

The bottom-up assembly of biological components in synthetic biology has contributed to a better understanding of natural phenomena and the development of new technologies for practical applications. Over the past few decades, basic RNA research has unveiled the regulatory roles of RNAs underlying gene regulatory networks; while advances in RNA biology, in turn, have highlighted the potential of a wide variety of RNA elements as building blocks to construct artificial systems. In particular, synthetic mRNA-based translational regulators, which respond to signals in cells and regulate the production of encoded output proteins, are gaining attention with the recent rise of mRNA therapeutics. In this Review, we discuss recent progress in RNA synthetic biology, mainly focusing on emerging technologies for sensing intracellular protein and RNA molecules and controlling translation.

Dynamic RNA synthetic biology: new principles, practices and potential

An increased appreciation of the role of RNA dynamics in governing RNA function is ushering in a new wave of dynamic RNA synthetic biology. Here, we review recent advances in engineering dynamic RNA systems across the molecular, circuit and cellular scales for important societal-scale applications in environmental and human health, and bioproduction. For each scale, we introduce the core concepts of dynamic RNA folding and function at that scale, and then discuss technologies incorporating these concepts, covering new approaches to engineering riboswitches, ribozymes, RNA origami, RNA strand displacement circuits, biomaterials, biomolecular condensates, extracellular vesicles and synthetic cells. Considering the dynamic nature of RNA within the engineering design process promises to spark the next wave of innovation that will expand the scope and impact of RNA biotechnologies.

Oligonucleotide separation techniques for purification and analysis: What can we learn for today's tasks?

Nucleic acids are the blueprint of life. They are not only the construction plan of the single cell or higher associations of them, but also necessary for function, communication and regulation. Due to the pandemic, the attention shifted in particular to their therapeutic potential as a vaccine. As pharmaceutical oligonucleotides are unique in terms of their stability and application, special delivery systems were also considered. Oligonucleotide production systems can vary and depend on the feasibility, availability, price and intended application. To achieve good purity, reliable results and match the strict specifications in the pharmaceutical industry, the separation of oligonucleotides is always essential. Besides the separation required for production, additional and specifically different separation techniques are needed for analysis to determine if the product complies with the designated specifications. After a short introduction to ribonucleic acids (RNAs), messenger RNA vaccines, and their production and delivery systems, an overview regarding separation techniques will be provided. This not only emphasises electrophoretic separations but also includes spin columns, extractions, precipitations, magnetic nanoparticles and several chromatographic separation principles, such as ion exchange chromatography, ion-pair reversed-phase, size exclusion and affinity.

aRNAque: an evolutionary algorithm for inverse pseudoknotted RNA folding inspired by Lévy flights

BACKGROUND

We study in this work the inverse folding problem for RNA, which is the discovery of sequences that fold into given target secondary structures.

RESULTS

We implement a Lévy mutation scheme in an updated version of aRNAque an evolutionary inverse folding algorithm and apply it to the design of RNAs with and without pseudoknots. We find that the Lévy mutation scheme increases the diversity of designed RNA sequences and reduces the average number of evaluations of the evolutionary algorithm. Compared to antaRNA, aRNAque CPU time is higher but more successful in finding designed sequences that fold correctly into the target structures.

CONCLUSION

We propose that a Lévy flight offers a better standard mutation scheme for optimizing RNA design. Our new version of aRNAque is available on GitHub as a python script and the benchmark results show improved performance on both Pseudobase++ and the Eterna100 datasets, compared to existing inverse folding tools.

Model-Based Investigation of the Relationship between Regulation Level and Pulse Property of I1-FFL Gene Circuits

Mathematical models are powerful tools in guiding the construction of synthetic biological circuits, given their capability of accurately capturing and predicting circuit dynamics. Recent innovations in RNA technology have enabled the development of a variety of new tools for regulating gene expression at both the transcription and translation levels. However, the effects of different regulation levels on the circuit dynamics remain largely unexplored. In this study, we focus on the type 1 incoherent feed-forward loop (I1-FFL) gene circuit with four different variations (TX, TL, HY-1, HY-2), to investigate how regulation at the transcription and translation levels affect the circuit dynamics. We develop a mechanistic model for each of the four circuits and deploy sensitivity analysis to investigate the circuits' dynamics in terms of pulse generation. Based on the analysis, we observe that the repression regulation mechanism dominates the characteristics of the pulse as compared to the activation regulation mechanism and find that the I1-FFL with transcription repression has a higher chance of generating a pulse meeting the desired criteria. The experimental results in Escherichia coli also confirm our findings from the computational analysis. We expect our findings to facilitate future experimental construction of gene circuits with insights on the selection of appropriate transcription and translation regulation tools.

Premature translation termination mediated non-ER stress induced ATF6 activation by a ligand-dependent ribosomal frameshifting circuit

The −1 programmed ribosomal frameshifting (−1 PRF) has been explored as a gene regulatory circuit for synthetic biology applications. The −1 PRF usually uses an RNA pseudoknot structure as the frameshifting stimulator. Finding a ligand-responsive pseudoknot with efficient −1 PRF activity is time consuming and is becoming a bottleneck for its development. Inserting a guanine to guanine (GG)–mismatch pair in the 5′-stem of a small frameshifting pseudoknot could attenuate −1 PRF activity by reducing stem stability. Thus, a ligand-responsive frameshifting pseudoknot can be built using GG-mismatch–targeting small molecules to restore stem stability. Here, a pseudoknot requiring stem–loop tertiary interactions for potent frameshifting activity was used as the engineering template. This considerably amplified the effect of mismatch destabilization, and led to creation of a mammalian −1 PRF riboswitch module capable of mediating premature translation termination as a synthetic regulatory mode. Application of the synthetic circuit allowed ligand-dependent ATF6N mimic formation for the activation of protein folding–related genes involved in the unfolded protein response without an ER-stress inducing agent. With the availability of mismatch-targeting molecules, the tailored module thus paves the way for various mismatch plug-ins to streamline highly efficient orthogonal ligand-dependent −1 PRF stimulator development in the synthetic biology toolbox.

Rational design of hairpin RNA excited states reveals multi-step transitions

RNA excited states represent a class of high-energy-level and thus low-populated conformational states of RNAs that are sequestered within the free energy landscape until being activated by cellular cues. In recent years, there has been growing interest in structural and functional studies of these transient states, but the rational design of excited states remains unexplored. Here we developed a method to design small hairpin RNAs with predefined excited states that exchange with ground states through base pair reshuffling, and verified these transient states by combining NMR relaxation dispersion technique and imino chemical shift prediction. Using van’t Hoff analysis and accelerated molecular dynamics simulations, a mechanism of multi-step sequential transition has been revealed. The efforts made in this study will expand the scope of RNA rational design, and also contribute towards improved predictions of RNA secondary structure.

RNA molecules exhibit conformational fluctuations between ground states and excited states. Here the authors designed and verified small hairpin RNAs with predefined secondary structure reshufflings. In light of Van’t Hoff analysis and accelerated molecular dynamics simulation, a mechanism of multistep sequential transition has been revealed.

Lipid membranes modulate the activity of RNA through sequence-dependent interactions

RNA is a ubiquitous biomolecule that can serve as both catalyst and information carrier. Understanding how RNA bioactivity is controlled is crucial for elucidating its physiological roles and potential applications in synthetic biology. Here, we show that lipid membranes can act as RNA organization platforms, introducing a mechanism for riboregulation. The activity of R3C ribozyme can be modified by the presence of lipid membranes, with direct RNA-lipid interactions dependent on RNA nucleotide content, base pairing, and length. In particular, the presence of guanine in short RNAs is crucial for RNA-lipid interactions, and G-quadruplex formation further promotes lipid binding. Lastly, by artificially modifying the R3C substrate sequence to enhance membrane binding, we generated a lipid-sensitive ribozyme reaction with riboswitch-like behavior. These findings introduce RNA-lipid interactions as a tool for developing synthetic riboswitches and RNA-based lipid biosensors and bear significant implications for RNA world scenarios for the origin of life.

Control of RNA with quinone methide reversible acylating reagents

Caging RNA by polyacylation (cloaking) has been developed recently as a simple and rapid method to control the function of RNAs. Previous approaches for chemical reversal of acylation (uncloaking) made use of azide reduction followed by amine cyclization, requiring ∼2-4 h for the completion of cyclization. In new studies aimed at improving reversal rates and yields, we have designed novel acylating reagents that utilize quinone methide (QM) elimination for reversal. The QM de-acylation reactions were tested with two bioorthogonally cleavable motifs, azide and vinyl ether, and their acylation and reversal efficiencies were assessed with NMR and mass spectrometry on model small-molecule substrates as well as on RNAs. Successful reversal both with phosphines and strained alkenes was documented. Among the compounds tested, the azido-QM compound A-3 displayed excellent de-acylation efficiency, with t1/2 for de-acylation of less than an hour using a phosphine trigger. To test its function in RNA caging, A-3 was successfully applied to control EGFP mRNA translation in vitro and in HeLa cells. We expect that this molecular caging strategy can serve as a valuable tool for biological investigation and control of RNAs both in vitro and in cells.

An overview and future prospects of recombinant protein production in Bacillus subtilis

Bacillus subtilis is a well-characterized Gram-positive bacterium and a valuable host for recombinant protein production because of its efficient secretion ability, high yield, and non-toxicity. Here, we comprehensively review the recent studies on recombinant protein production in B. subtilis to update and supplement other previous reviews. We have focused on several aspects, including optimization of B. subtilis strains, enhancement and regulation of expression, improvement of secretion level, surface display of proteins, and fermentation optimization. Among them, optimization of B. subtilis strains mainly involves undirected chemical/physical mutagenesis and selection and genetic manipulation; enhancement and regulation of expression comprises autonomous plasmid and integrated expression, promoter regulation and engineering, and fine-tuning gene expression based on proteases and molecular chaperones; improvement of secretion level predominantly involves secretion pathway and signal peptide screening and optimization; surface display of proteins includes surface display of proteins on spores or vegetative cells; and fermentation optimization incorporates medium optimization, process condition optimization, and feeding strategy optimization. Furthermore, we propose some novel methods and future challenges for recombinant protein production in B. subtilis.Key points• A comprehensive review on recombinant protein production in Bacillus subtilis.• Novel techniques facilitate recombinant protein expression and secretion.• Surface display of proteins has significant potential for different applications.

Post-Transcriptional Control in the Regulation of Polyhydroxyalkanoates Synthesis

The large production of non-degradable petrol-based plastics has become a major global issue due to its environmental pollution. Biopolymers produced by microorganisms such as polyhydroxyalkanoates (PHAs) are gaining potential as a sustainable alternative, but the high cost associated with their industrial production has been a limiting factor. Post-transcriptional regulation is a key step to control gene expression in changing environments and has been reported to play a major role in numerous cellular processes. However, limited reports are available concerning the regulation of PHA accumulation in bacteria, and many essential regulatory factors still need to be identified. Here, we review studies where the synthesis of PHA has been reported to be regulated at the post-transcriptional level, and we analyze the RNA-mediated networks involved. Finally, we discuss the forthcoming research on riboregulation, synthetic, and metabolic engineering which could lead to improved strategies for PHAs synthesis in industrial production, thereby reducing the costs currently associated with this procedure.

AI in Measurement Science

Measurement of biological systems containing biomolecules and bioparticles is a key task in the fields of analytical chemistry, biology, and medicine. Driven by the complex nature of biological systems and unprecedented amounts of measurement data, artificial intelligence (AI) in measurement science has rapidly advanced from the use of silicon-based machine learning (ML) for data mining to the development of molecular computing with improved sensitivity and accuracy. This review presents an overview of fundamental ML methodologies and discusses their applications in disease diagnostics, biomarker discovery, and imaging analysis. We next provide the working principles of molecular computing using logic gates and arithmetical devices, which can be employed for in situ detection, computation, and signal transduction for biological systems. This review concludes by summarizing the strengths and limitations of AI-involved biological measurement in fundamental and applied research.

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.

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.

In situ Generation of RNA Complexes for Synthetic Molecular Strand-Displacement Circuits in Autonomous Systems

Synthetic molecular circuits implementing DNA or RNA strand-displacement reactions can be used to build complex systems such as molecular computers and feedback control systems. Despite recent advances, application of nucleic acid-based circuits in vivo remains challenging due to a lack of efficient methods to produce their essential components, namely, multistranded complexes known as gates, in situ, i.e., in living cells or other autonomous systems. Here, we propose the use of naturally occurring self-cleaving ribozymes to cut a single-stranded RNA transcript into a gate complex of shorter strands, thereby opening new possibilities for the autonomous and continuous production of RNA strands in a stoichiometrically and structurally controlled way.

A deep learning approach to programmable RNA switches

Engineered RNA elements are programmable tools capable of detecting small molecules, proteins, and nucleic acids. Predicting the behavior of these synthetic biology components remains a challenge, a situation that could be addressed through enhanced pattern recognition from deep learning. Here, we investigate Deep Neural Networks (DNN) to predict toehold switch function as a canonical riboswitch model in synthetic biology. To facilitate DNN training, we synthesize and characterize in vivo a dataset of 91,534 toehold switches spanning 23 viral genomes and 906 human transcription factors. DNNs trained on nucleotide sequences outperform (R2 = 0.43-0.70) previous state-of-the-art thermodynamic and kinetic models (R2 = 0.04-0.15) and allow for human-understandable attention-visualizations (VIS4Map) to identify success and failure modes. This work shows that deep learning approaches can be used for functionality predictions and insight generation in RNA synthetic biology.

Developments of Riboswitches and Toehold Switches for Molecular Detection-Biosensing and Molecular Diagnostics

Riboswitches and toehold switches are considered to have potential for implementation in various fields, i.e., biosensing, metabolic engineering, and molecular diagnostics. The specific binding, programmability, and manipulability of these RNA-based molecules enable their intensive deployments in molecular detection as biosensors for regulating gene expressions, tracking metabolites, or detecting RNA sequences of pathogenic microorganisms. In this review, we will focus on the development of riboswitches and toehold switches in biosensing and molecular diagnostics. This review introduces the operating principles and the notable design features of riboswitches as well as toehold switches. Moreover, we will describe the advances and future directions of riboswitches and toehold switches in biosensing and molecular diagnostics.

Mathematical Models of Protease-Based Enzymatic Biosensors

An important goal of synthetic biology is to build biosensors and circuits with well-defined input-output relationships that operate at speeds found in natural biological systems. However, for molecular computation, most commonly used genetic circuit elements typically involve several steps from input detection to output signal production: transcription, translation, and post-translational modifications. These multiple steps together require up to several hours to respond to a single stimulus, and this limits the overall speed and complexity of genetic circuits. To address this gap, molecular frameworks that rely exclusively on post-translational steps to realize reaction networks that can process inputs at a time scale of seconds to minutes have been proposed. Here, we build mathematical models of fast biosensors capable of producing Boolean logic functionality. We employ protease-based chemical and light-induced switches, investigate their operation, and provide selection guidelines for their use as on-off switches. As a proof of concept, we implement a rapamycin-induced switch in vitro and demonstrate that its response qualitatively agrees with the predictions from our models. We then use these switches as elementary blocks, developing models for biosensors that can perform OR and XOR Boolean logic computation while using reaction conditions as tuning parameters. We use sensitivity analysis to determine the time-dependent sensitivity of the output to proteolytic and protein-protein binding reaction parameters. These fast protease-based biosensors can be used to implement complex molecular circuits with a capability of processing multiple inputs controllably and algorithmically. Our framework for evaluating and optimizing circuit performance can be applied to other molecular logic circuits.

Optogenetic control of mRNA localization and translation in live cells

Despite efforts to visualize the spatio-temporal dynamics of single messenger RNAs, the ability to precisely control their function has lagged. This study presents an optogenetic approach for manipulating the localization and translation of specific mRNAs by trapping them in clusters. This clustering greatly amplified reporter signals, enabling endogenous RNA-protein interactions to be clearly visualized in single cells. Functionally, this sequestration reduced the ability of mRNAs to access ribosomes, markedly attenuating protein synthesis. A spatio-temporally resolved analysis indicated that sequestration of endogenous β-actin mRNA attenuated cell motility through the regulation of focal-adhesion dynamics. These results suggest a mechanism highlighting the indispensable role of newly synthesized β-actin protein for efficient cell migration. This platform may be broadly applicable for use in investigating the spatio-temporal activities of specific mRNAs in various biological processes.

Ant colony optimization for predicting RNA folding pathways

RNA folding dynamics plays important roles in various functions of RNAs. To date, coarse-grained modeling has been successfully employed to simulate RNA folding dynamics on the energy landscape composed of secondary structures. In such a modeling, the energy barrier height between metastable structures is a key parameter that crucially affects the simulation results. Although a number of approaches ranging from the exact method to heuristic ones are available to predict the barrier heights, developing an efficient heuristic for this purpose is still an algorithmic challenge. We developed a novel RNA folding pathway prediction method, ACOfoldpath, based on Ant Colony Optimization (ACO). ACO is a widely used powerful combinatorial optimization algorithm inspired from the food-seeking behavior of ants. In ACOfoldpath, to accelerate the folding pathway prediction, we reduce the search space by utilizing originally devised structure generation rules. To evaluate the performance of the proposed method, we benchmarked ACOfoldpath on the known nineteen conformational RNA switches. As a result, ACOfoldpath successfully predicted folding pathways better than or comparable to the previous heuristics. The results of RNA folding dynamics simulations and pseudoknotted pathway predictions are also presented.

Reprogramming bacteria with RNA regulators

The revolution of genomics and growth of systems biology urged the creation of synthetic biology, an engineering discipline aiming at recreating and reprogramming cellular functions for industrial needs. There has been a huge effort in synthetic biology to develop versatile and programmable genetic regulators that would enable the precise control of gene expression. Synthetic RNA components have emerged as a solution, offering a diverse range of programmable functions, including signal sensing, gene regulation and the modulation of molecular interactions. Owing to their compactness, structure and way of action, several types of RNA devices that act on DNA, RNA and protein have been characterized and applied in synthetic biology. RNA-based approaches are more ‘economical' for the cell, since they are generally not translated. These RNA-based strategies act on a much shorter time scale than transcription-based ones and can be more efficient than protein-based mechanisms. In this review, we explore these RNA components as building blocks in the RNA synthetic biology field, first by explaining their natural mode of action and secondly discussing how these RNA components have been exploited to rewire bacterial regulatory circuitry.

Design of highly active double-pseudoknotted ribozymes: a combined computational and experimental study

Design of RNA sequences that adopt functional folds establishes principles of RNA folding and applications in biotechnology. Inverse folding for RNAs, which allows computational design of sequences that adopt specific structures, can be utilized for unveiling RNA functions and developing genetic tools in synthetic biology. Although many algorithms for inverse RNA folding have been developed, the pseudoknot, which plays a key role in folding of ribozymes and riboswitches, is not addressed in most algorithms. For the few algorithms that attempt to predict pseudoknot-containing ribozymes, self-cleavage activity has not been tested. Herein, we design double-pseudoknot HDV ribozymes using an inverse RNA folding algorithm and test their kinetic mechanisms experimentally. More than 90% of the positively designed ribozymes possess self-cleaving activity, whereas more than 70% of negative control ribozymes, which are predicted to fold to the necessary structure but with low fidelity, do not possess it. Kinetic and mutation analyses reveal that these RNAs cleave site-specifically and with the same mechanism as the WT ribozyme. Most ribozymes react just 50- to 80-fold slower than the WT ribozyme, and this rate can be improved to near WT by modification of a junction. Thus, fast-cleaving functional ribozymes with multiple pseudoknots can be designed computationally.

De novo design of bioactive protein switches

Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix 'cage' with a single interface that can interact either intramolecularly with a terminal 'latch' helix or intermolecularly with a peptide 'key'. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage-key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.

Synthetic 5' UTRs Can Either Up- or Downregulate Expression upon RNA-Binding Protein Binding

The construction of complex gene-regulatory networks requires both inhibitory and upregulatory modules. However, the vast majority of RNA-based regulatory "parts" are inhibitory. Using a synthetic biology approach combined with SHAPE-seq, we explored the regulatory effect of RNA-binding protein (RBP)-RNA interactions in bacterial 5' UTRs. By positioning a library of RNA hairpins upstream of a reporter gene and co-expressing them with the matching RBP, we observed a set of regulatory responses, including translational stimulation, translational repression, and cooperative behavior. Our combined approach revealed three distinct states in vivo: in the absence of RBPs, the RNA molecules can be found in either a molten state that is amenable to translation or a structured phase that inhibits translation. In the presence of RBPs, the RNA molecules are in a semi-structured phase with partial translational capacity. Our work provides new insight into RBP-based regulation and a blueprint for designing complete gene-regulatory circuits at the post-transcriptional level.

An emergent understanding of strand displacement in RNA biology

DNA and RNA are generally regarded as central molecules in molecular biology. Recent advancements in the field of DNA/RNA nanotechnology successfully used DNA/RNA as programmable molecules to construct molecular machines and nanostructures with predefined shapes and functions. The key mechanism for dynamic control of the conformations of these DNA/RNA nanodevices is a reaction called strand displacement, in which one strand in a formed duplex is replaced by a third invading strand. While DNA/RNA strand displacement has mainly been used to de novo design molecular devices, we argue in this review that this reaction is also likely to play a key role in multiple cellular events such as gene recombination, CRISPR-based genome editing, and RNA cotranscriptional folding. We introduce the general mechanism of strand displacement reaction, give examples of its use in the construction of molecular machines, and finally review natural processes having characteristic which suggest that strand displacement is occurring.

Cell-Free Synthetic Biology Platform for Engineering Synthetic Biological Circuits and Systems

Synthetic biology brings engineering disciplines to create novel biological systems for biomedical and technological applications. The substantial growth of the synthetic biology field in the past decade is poised to transform biotechnology and medicine. To streamline design processes and facilitate debugging of complex synthetic circuits, cell-free synthetic biology approaches has reached broad research communities both in academia and industry. By recapitulating gene expression systems in vitro, cell-free expression systems offer flexibility to explore beyond the confines of living cells and allow networking of synthetic and natural systems. Here, we review the capabilities of the current cell-free platforms, focusing on nucleic acid-based molecular programs and circuit construction. We survey the recent developments including cell-free transcription-translation platforms, DNA nanostructures and circuits, and novel classes of riboregulators. The links to mathematical models and the prospects of cell-free synthetic biology platforms will also be discussed.

Programming Structured DNA Assemblies to Probe Biophysical Processes

Structural DNA nanotechnology is beginning to emerge as a widely accessible research tool to mechanistically study diverse biophysical processes. Enabled by scaffolded DNA origami in which a long single strand of DNA is weaved throughout an entire target nucleic acid assembly to ensure its proper folding, assemblies of nearly any geometric shape can now be programmed in a fully automatic manner to interface with biology on the 1-100-nm scale. Here, we review the major design and synthesis principles that have enabled the fabrication of a specific subclass of scaffolded DNA origami objects called wireframe assemblies. These objects offer unprecedented control over the nanoscale organization of biomolecules, including biomolecular copy numbers, presentation on convex or concave geometries, and internal versus external functionalization, in addition to stability in physiological buffer. To highlight the power and versatility of this synthetic structural biology approach to probing molecular and cellular biophysics, we feature its application to three leading areas of investigation: light harvesting and nanoscale energy transport, RNA structural biology, and immune receptor signaling, with an outlook toward unique mechanistic insight that may be gained in these areas in the coming decade.

DNA-based memory devices for recording cellular events

Measuring biological data across time and space is critical for understanding complex biological processes and for various biosurveillance applications. However, such data are often inaccessible or difficult to directly obtain. Less invasive, more robust and higher-throughput biological recording tools are needed to profile cells and their environments. DNA-based cellular recording is an emerging and powerful framework for tracking intracellular and extracellular biological events over time across living cells and populations. Here, we review and assess DNA recorders that utilize CRISPR nucleases, integrases and base-editing strategies, as well as recombinase and polymerase-based methods. Quantitative characterization, modelling and evaluation of these DNA-recording modalities can guide their design and implementation for specific application areas.

Design of RNAs: comparing programs for inverse RNA folding

Computational programs for predicting RNA sequences with desired folding properties have been extensively developed and expanded in the past several years. Given a secondary structure, these programs aim to predict sequences that fold into a target minimum free energy secondary structure, while considering various constraints. This procedure is called inverse RNA folding. Inverse RNA folding has been traditionally used to design optimized RNAs with favorable properties, an application that is expected to grow considerably in the future in light of advances in the expanding new fields of synthetic biology and RNA nanostructures. Moreover, it was recently demonstrated that inverse RNA folding can successfully be used as a valuable preprocessing step in computational detection of novel noncoding RNAs. This review describes the most popular freeware programs that have been developed for such purposes, starting from RNAinverse that was devised when formulating the inverse RNA folding problem. The most recently published ones that consider RNA secondary structure as input are antaRNA, RNAiFold and incaRNAfbinv, each having different features that could be beneficial to specific biological problems in practice. The various programs also use distinct approaches, ranging from ant colony optimization to constraint programming, in addition to adaptive walk, simulated annealing and Boltzmann sampling. This review compares between the various programs and provides a simple description of the various possibilities that would benefit practitioners in selecting the most suitable program. It is geared for specific tasks requiring RNA design based on input secondary structure, with an outlook toward the future of RNA design programs.

Engineering nucleic acid structures for programmable molecular circuitry and intracellular biocomputation

Nucleic acids have attracted widespread attention due to the simplicity with which they can be designed to form discrete structures and programmed to perform specific functions at the nanoscale. The advantages of DNA/RNA nanotechnology offer numerous opportunities for in-cell and in-vivo applications, and the technology holds great promise to advance the growing field of synthetic biology. Many elegant examples have revealed the potential in integrating nucleic acid nanostructures in cells and in vivo where they can perform important physiological functions. In this Review, we summarize the current abilities of DNA/RNA nanotechnology to realize applications in live cells and then discuss the key problems that must be solved to fully exploit the useful properties of nanostructures. Finally, we provide viewpoints on how to integrate the tools provided by DNA/RNA nanotechnology and related new technologies to construct nucleic acid nanostructure-based molecular circuitry for synthetic biology.

Design of nucleic acid strands with long low-barrier folding pathways

A major goal of natural computing is to design biomolecules, such as nucleic acid sequences, that can be used to perform computations. We design sequences of nucleic acids that are "guaranteed" to have long folding pathways relative to their length. This particular sequences with high probability follow low-barrier folding pathways that visit a large number of distinct structures. Long folding pathways are interesting, because they demonstrate that natural computing can potentially support long and complex computations. Formally, we provide the first scalable designs of molecules whose low-barrier folding pathways, with respect to a simple, stacked pair energy model, grow superlinearly with the molecule length, but for which all significantly shorter alternative folding pathways have an energy barrier that is [Formula: see text] times that of the low-barrier pathway for any [Formula: see text] and a sufficiently long sequence.

Engineering an inducible gene expression system for Bacillus subtilis from a strong constitutive promoter and a theophylline-activated synthetic riboswitch

Background

Synthetic riboswitches have been increasingly used to control and tune gene expression in diverse organisms. Although a set of theophylline-responsive riboswitches have been developed for bacteria, fully functional expression elements mediated by synthetic riboswitches in Bacillus subtilis are rarely used because of the host-dependent compatibility between the promoters and riboswitches.

Results

A novel genetic element composed of the promoter P43 and a theophylline-riboswitch was developed and characterized in B. subtilis. When combined with a P43 promoter (P43′-riboE1), the theophylline-riboswitch successfully switched the constitutive expression pattern of P43 to an induced pattern. The expression mediated by the novel element could be activated at the translational level by theophylline with a relatively high induction ratio. The induction ratios for P43′-riboE1 by 4-mM theophylline were elevated during the induction period. The level of induced expression was dependent on the theophylline dose. Correspondingly, the induction ratios gradually increased in parallel with the elevated dose of theophylline. Importantly, the induced expression level was higher than three other strong constitutive promoters including P_srfA, P_aprE, and the native P43. It was found that the distance between the SD sequence within the expression element and the start codon significantly influenced both the level of induced expression and the induction ratio. A 9-bp spacer was suitable for producing desirable expression level and induction ratio. Longer spacer reduced the activation efficiency. Importantly, the system successfully overexpressed β-glucuronidase at equal levels, and induction ratio was similar to that of GFP.

Conclusion

The constructed theophylline-inducible gene expression system has broad compatibility and robustness, which has great potential in over-production of pharmaceutical and industrial proteins and utilization in building more complex gene circuits.

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

BACKGROUND

Biological macromolecules (DNA, RNA and proteins) are capable of processing physical or chemical inputs to generate outputs that parallel conventional Boolean logical operators. However, the design of functional modules that will enable these macromolecules to operate as synthetic molecular computing devices is challenging.

RESULTS

Using three simple heuristics, we designed RNA sensors that can mimic the function of a seven-segment display (SSD). Ten independent and orthogonal sensors representing the numerals 0 to 9 are designed and constructed. Each sensor has its own unique oligonucleotide binding site region that is activated uniquely by a specific input. Each operator was subjected to a stringent in silico filtering. Random sensors were selected and functionally validated via ribozyme self cleavage assays that were visualized via electrophoresis.

CONCLUSIONS

By utilising simple permutation and randomisation in the sequence design phase, we have developed functional RNA sensors thus demonstrating that even the simplest of computational methods can greatly aid the design phase for constructing functional molecular devices.

A modular clamp-like mechanism to regulate the activity of nucleic-acid target-responsive nanoswitches with external activators

Here we demonstrate a general and modular approach to regulate the activity of target-responsive DNA-based nanoswitches. We do so by coupling together two DNA-based responsive elements: a triplex-forming clamp-like probe able to bind a specific DNA sequence and a split aptamer selected to bind a small molecule. In the presence of the specific target of one of the above responsive elements, the nanoswitch partially folds and its ability to bind the second target is restored. With this approach we can finely modulate the affinity of both DNA-recognition elements and aptamers using an external ligand. The modular nature of our strategy makes it easily generalizable to different DNA based recognition elements. As a demonstration of this we successfully designed five different DNA nanoswitches whose responsiveness can be regulated by different molecular effectors and targets. The convenience with which this mechanism is designed suggests that it may prove a useful tool by which sensors, genetic networks and other biotechnology devices employing nucleic-acid based receptors can be controlled with an external input.

Natural antisense RNAs as mRNA regulatory elements in bacteria: a review on function and applications

Naturally occurring antisense RNAs are small, diffusible, untranslated transcripts that pair to target RNAs at specific regions of complementarity to control their biological function by regulating gene expression at the post-transcriptional level. This review focuses on known cases of antisense RNA control in prokaryotes and provides an overview of some natural RNA-based mechanisms that bacteria use to modulate gene expression, such as mRNA sensors, riboswitches and antisense RNAs. We also highlight recent advances in RNA-based technology. The review shows that studies on both natural and synthetic systems are reciprocally beneficial.

Molecular Buffers Permit Sensitivity Tuning and Inversion of Riboswitch Signals

Predictable integration of foreign biological signals and parts remains a key challenge in the systematic engineering of synthetic cellular actuations, and general methods to improve signal transduction and sensitivity are needed. To address this problem we modeled and built a molecular signal buffer network in Saccharomyces cerevisiae inspired by chemical pH buffer systems. The molecular buffer system context-insulates a riboswitch enabling synthetic control of colony formation and modular signal manipulations. The riboswitch signal is relayed to a transcriptional activation domain of a split transcription factor, while interacting DNA-binding domains mediate the transduction of signal and form an interacting molecular buffer. The molecular buffer system enables modular signal inversion through integration with repressor modules. Further, tuning of input sensitivity was achieved through perturbation of the buffer pair ratio guided by a mathematical model. Such buffered signal tuning networks will be useful for domestication of RNA-based sensors enabling tunable outputs and library-wide selections for drug discovery and metabolic engineering.

Probabilistic Boolean Network Modelling and Analysis Framework for mRNA Translation

mRNA translation is a complex process involving the progression of ribosomes on the mRNA, resulting in the synthesis of proteins, and is subject to multiple layers of regulation. This process has been modelled using different formalisms, both stochastic and deterministic. Recently, we introduced a Probabilistic Boolean modelling framework for mRNA translation, which possesses the advantage of tools for numerically exact computation of steady state probability distribution, without requiring simulation. Here, we extend this model to incorporate both random sequential and parallel update rules, and demonstrate its effectiveness in various settings, including its flexibility in accommodating additional static and dynamic biological complexities and its role in parameter sensitivity analysis. In these applications, the results from the model analysis match those of TASEP model simulations. Importantly, the proposed modelling framework maintains the stochastic aspects of mRNA translation and provides a way to exactly calculate probability distributions, providing additional tools of analysis in this context. Finally, the proposed modelling methodology provides an alternative approach to the understanding of the mRNA translation process, by bridging the gap between existing approaches, providing new analysis tools, and contributing to a more robust platform for modelling and understanding translation.