De novo automated design of small RNA circuits for engineering synthetic riboregulation in living cells

START: A Versatile Platform for Bacterial Ligand Sensing with Programmable Performances

Recognition of signaling molecules for coordinated regulation of target genes is a fundamental process for biological systems. Cells often rely on transcription factors to accomplish these intricate tasks, yet the subtle conformational changes of protein structures, coupled with the complexity of intertwined protein interaction networks, pose challenges for repurposing these for bioengineering applications. This study introduces a novel platform for ligand-responsive gene regulation, termed START (Synthetic Trans-Acting Riboswitch with Triggering RNA). Inspired by the bacterial ligand sensing system, riboswitch, and the synthetic gene regulator, toehold switch, the START platform enables the implementation of synthetic biosensors for various ligands. Rational sequence design with targeted domain optimization yields high-performance STARTs with a dynamic range up to 67.29-fold and a tunable ligand sensitivity, providing a simple and intuitive strategy for sensor engineering. The START platform also exhibits modularity and composability to allow flexible genetic circuit construction, enabling seamless implementation of OR, AND, and NOT Boolean logic gates for multiple ligand inputs. The START design principle is capable of broadening the suite of synthetic biosensors for diverse chemical and protein ligands, providing a novel riboregulator chassis for synthetic biology and bioengineering applications.

Designing a Novel Temperature- and Noncanonical Amino Acid-Controlled Biological Logic Gate in Escherichia coli

Genetic code expansion (GCE) is a powerful strategy that expands the genetic code of an organism for incorporating noncanonical amino acids into proteins using engineered tRNAs and aminoacyl-tRNA synthetases (aaRSs). While GCE has opened up new possibilities for synthetic biology, little is known about the potential side effects of exogenous aaRS/tRNA pairs. In this study, we investigated the impact of exogenous aaRS and amber suppressor tRNA on gene expression in Escherichia coli. We discovered that in DH10β ΔcyaA, transformed with the F1RP/F2P two-hybrid system, the high consumption rate of cellular adenosine triphosphate by exogenous aaRS/tRNA at elevated temperatures induces temperature sensitivity in the expression of genes regulated by the cyclic AMP receptor protein (CRP). We harnessed this temperature sensitivity to create a novel biological AND gate in E. coli, responsive to both p-benzoylphenylalanine (BzF) and low temperature, using a BzF-dependent variant of E. coli chorismate mutase and split subunits of Bordetella pertussis adenylate cyclase. Our study provides new insights into the unexpected effects of exogenous aaRS/tRNA pairs and offers a new approach for constructing a biological logic gate.

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.

Simultaneous enhancement of multiple functional properties using evolution-informed protein design

A major challenge in protein design is to augment existing functional proteins with multiple property enhancements. Altering several properties likely necessitates numerous primary sequence changes, and novel methods are needed to accurately predict combinations of mutations that maintain or enhance function. Models of sequence co-variation (e.g., EVcouplings), which leverage extensive information about various protein properties and activities from homologous protein sequences, have proven effective for many applications including structure determination and mutation effect prediction. We apply EVcouplings to computationally design variants of the model protein TEM-1 β-lactamase. Nearly all the 14 experimentally characterized designs were functional, including one with 84 mutations from the nearest natural homolog. The designs also had large increases in thermostability, increased activity on multiple substrates, and nearly identical structure to the wild type enzyme. This study highlights the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications.

Regulatory RNAs in Bacillus subtilis: A review on regulatory mechanism and applications in synthetic biology

Bacteria exhibit a rich repertoire of RNA molecules that intricately regulate gene expression at multiple hierarchical levels, including small RNAs (sRNAs), riboswitches, and antisense RNAs. Notably, the majority of these regulatory RNAs lack or have limited protein-coding capacity but play pivotal roles in orchestrating gene expression by modulating transcription, post-transcription or translation processes. Leveraging and redesigning these regulatory RNA elements have emerged as pivotal strategies in the domains of metabolic engineering and synthetic biology. While previous investigations predominantly focused on delineating the roles of regulatory RNA in Gram-negative bacterial models such as Escherichia coli and Salmonella enterica, this review aims to summarize the mechanisms and functionalities of endogenous regulatory RNAs inherent to typical Gram-positive bacteria, notably Bacillus subtilis. Furthermore, we explore the engineering and practical applications of these regulatory RNA elements in the arena of synthetic biology, employing B. subtilis as a foundational chassis.

T7 phage-assisted evolution of riboswitches using error-prone replication and dual selection

Leveraging riboswitches, non-coding mRNA fragments pivotal to gene regulation, poses a challenge in effectively selecting and enriching these functional genetic sensors, which can toggle between ON and OFF states in response to their cognate inducers. Here, we show our engineered phage T7, enabling the evolution of a theophylline riboswitch. We have replaced T7's DNA polymerase with a transcription factor controlled by a theophylline riboswitch and have created two types of host environments to propagate the engineered phage. Both types host an error-prone T7 DNA polymerase regulated by a T7 promoter along with another critical gene-either cmk or pifA, depending on the host type. The cmk gene is necessary for T7 replication and is used in the first host type for selection in the riboswitch's ON state. Conversely, the second host type incorporates the pifA gene, leading to abortive T7 infections and used for selection in the riboswitch's OFF state. This dual-selection system, termed T7AE, was then applied to a library of 65,536 engineered T7 phages, each carrying randomized riboswitch variants. Through successive passage in both host types with and without theophylline, we observed an enrichment of phages encoding functional riboswitches that conferred a fitness advantage to the phage in both hosts. The T7AE technique thereby opens new pathways for the evolution and advancement of gene switches, including non-coding RNA-based switches, setting the stage for significant strides in synthetic biology.

"Toehold Switches; a foothold for Synthetic Biology"

Toehold switches are de novo designed riboregulators that contain two RNA components interacting through linear-linear RNA interactions, regulating the gene expression. These are highly versatile, exhibit excellent orthogonality, wide dynamic range, and are highly programmable, so can be used for various applications in synthetic biology. In this review, we summarized and discussed the design characteristics and benefits of toehold switch riboregulators over conventional riboregulators. We also discussed applications and recent advancements of toehold switch riboregulators in various fields like gene editing, DNA nanotechnology, translational repression, and diagnostics (detection of microRNAs and some pathogens). Toehold switches, therefore, furnished advancement in synthetic biology applications in various fields with their prominent features.

Programmable regulation of translation by harnessing the CRISPR-Cas13 system

The ability to control protein expression at both the transcriptional and post-transcriptional levels is instrumental for the cell to integrate multiple molecular signals and then reach high operational sophistication. Although challenging, fully artificial regulations at different levels are required for boosting systems and synthetic biology. Here, we report the development of a novel framework to regulate translation by repurposing the CRISPR-Cas13 immune system, which uses an RNA-guided ribonuclease. By exploiting a cell-free expression system for prototyping gene regulatory structures, our results demonstrate that CRISPR-dCas13a ribonucleoproteins (d means catalytically dead) can be programmed to repress or activate translation initiation. The performance assessment of the engineered systems also revealed guide RNA design principles. Moreover, we show that the system can work in vivo. This development complements the ability to regulate transcription with other CRISPR-Cas systems and offers potential applications.

Hydrogel on a Smart Nanomaterial Interface to Carry Therapeutics for Digitalized Glioma Treatment

Glioma is considered the primary brain tumor to cause brain illnesses, and it is difficult to treat and shows resistance to various routine therapeutics. The most common treatments to cure glioma are the surgical removal of tumors followed by adjuvant chemotherapy and radiation therapy. The latest biocompatible interfaces have been incorporated into therapeutic modalities such as the targeted delivery of drugs using hydrogels to treat and manage brain glioma. This review illustrates the applications of the multimodal hydrogel as the carrier of therapeutics, gene therapy, therapeutic tactics, and glioma devices. The scientific articles were retrieved from 2019 to 2022 on Google Scholar and the Scopus database and screened to determine whether they were suitable for review. The 20 articles that fit the study are summarized in this review. These studies indicated that the sizes of the hydrogel range from 28 nm to 500 nm. There are 16 out of 20 articles that also explain the post-surgical application of hydrogels, and 13 out of 20 articles are employed in 3D culture and other structural manifestations of hydrogels. The pros of the hydrogel include the quick formulation for a sufficient filling of irregular damage sites, solubilizing hydrophobic drugs, continuously slowing drug release, provision of a 3D cell growth environment, improving efficacy, targetability of soluble biomolecules, increasing patient compliance, and decreased side effects. The cons of the hydrogel include difficult real-time monitoring, genetic manipulations, the cumbersome synchronized release of components, and lack of safety data. The prospects of the hydrogel may include the development of electronic hydrogel sensors that can be used to enhance guidance for the precise targeting patterns using patient-specific pathological idiosyncrasies. This technology has the potential to revolutionize the precision medicine approaches that would aid in the early detection and management of solid brain tumors.

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.

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.

Design, mutate, screen: Multiplexed creation and arrayed screening of synchronized genetic clocks

A major goal in synthetic biology is coordinating cellular behavior using cell-cell interactions; however, designing and testing complex genetic circuits that function only in large populations remains challenging. Although directed evolution has commonly supplemented rational design methods for synthetic gene circuits, this method relies on the efficient screening of mutant libraries for desired phenotypes. Recently, multiple techniques have been developed for identifying dynamic phenotypes from large, pooled libraries. These technologies have advanced library screening for single-cell, time-varying phenotypes but are currently incompatible with population-level phenotypes dependent on cell-cell communication. Here, we utilize directed mutagenesis and multiplexed microfluidics to develop an arrayed-screening workflow for dynamic, population-level genetic circuits. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and discover variants with different period-amplitude characteristics. Lastly, we utilize our screening workflow to construct a transcriptionally regulated synchronized oscillator that functions over long timescales. A record of this paper's transparent peer review process is included in the supplemental information.

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.

Building Endogenous Gene Connections through RNA Self-Assembly Controlled CRISPR/Cas9 Function

Construction of synthetic circuits that can artificially establish endogenous gene connections is essential to introduce new phenotypes for cellular behaviors. Given the diversity of endogenous genes, it lacks a general and easy-to-design toolbox to manipulate the genetic network. Here we present a type of self-assembly-induced RNA circuit that can directly build regulatory connections between endogenous genes. Inspired from the natural assembling process of guide RNA in the CRISPR/Cas9 complex, this design employs an independent trigger RNA strand to induce the formation of a ternary guide RNA assembly for functional control of CRISPR/Cas9. With this general principle, expressional regulations of endogenous genes can be controlled by totally independent endogenous small RNAs and mRNAs in E. coli via activatable CRISPR/Cas9 function. Moreover, the cellular phenotype of E. coli is successfully programmed with introduction of new gene connections. In addition, the functionality of this design is also verified in the mammalian system. This self-assembly-based RNA circuit exhibits a great flexibility and simplicity of design and provides a unique approach to build endogenous gene connections, which paves a broad way toward manipulation of cellular genetic networks.

Design and Evaluation of Synthetic RNA-Based Incoherent Feed-Forward Loop Circuits

RNA-based regulators are promising tools for building synthetic biological systems that provide a powerful platform for achieving a complex regulation of transcription and translation. Recently, de novo-designed synthetic RNA regulators, such as the small transcriptional activating RNA (STAR), toehold switch (THS), and three-way junction (3WJ) repressor, have been utilized to construct RNA-based synthetic gene circuits in living cells. In this work, we utilized these regulators to construct type 1 incoherent feed-forward loop (IFFL) circuits in vivo and explored their dynamic behaviors. A combination of a STAR and 3WJ repressor was used to construct an RNA-only IFFL circuit. However, due to the fast kinetics of RNA–RNA interactions, there was no significant timescale difference between the direct activation and the indirect inhibition, that no pulse was observed in the experiments. These findings were confirmed with mechanistic modeling and simulation results for a wider range of conditions. To increase delay in the inhibition pathway, we introduced a protein synthesis process to the circuit and designed an RNA–protein hybrid IFFL circuit using THS and TetR protein. Simulation results indicated that pulse generation could be achieved with this RNA–protein hybrid model, and this was further verified with experimental realization in E. coli. Our findings demonstrate that while RNA-based regulators excel in speed as compared to protein-based regulators, the fast reaction kinetics of RNA-based regulators could also undermine the functionality of a circuit (e.g., lack of significant timescale difference). The agreement between experiments and simulations suggests that the mechanistic modeling can help debug issues and validate the hypothesis in designing a new circuit. Moreover, the applicability of the kinetic parameters extracted from the RNA-only circuit to the RNA–protein hybrid circuit also indicates the modularity of RNA-based regulators when used in a different context. We anticipate the findings of this work to guide the future design of gene circuits that rely heavily on the dynamics of RNA-based regulators, in terms of both modeling and experimental realization.

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.

A guide to the design of synthetic gene networks in mammalian cells

Synthetic biology aims to harness natural and synthetic biological parts and engineering them in new combinations and systems, producing novel therapies, diagnostics, bioproduction systems, and providing information on the mechanism of function of biological systems. Engineering cell function requires the rewiring or de novo construction of cell information processing networks. Using natural and synthetic signal processing elements, researchers have demonstrated a wide array of signal sensing, processing and propagation modules, using transcription, translation, or post-translational modification to program new function. The toolbox for synthetic network design is ever-advancing and has still ample room to grow. Here, we review the diversity of synthetic gene networks, types of building modules, techniques of regulation, and their applications.

Conditional guide RNA through two intermediate hairpins for programmable CRISPR/Cas9 function: building regulatory connections between endogenous RNA expressions

A variety of nanodevices developed for nucleic acid computation provide great opportunities to construct versatile synthetic circuits for manipulation of gene expressions. In our study, by employing a two-hairpin mediated nucleic acid strand displacement as a processing joint for conditional guide RNA, we aim to build artificial connections between naturally occurring RNA expressions through programmable CRISPR/Cas9 function. This two-hairpin joint possesses a sequence-switching machinery, in which a random trigger strand can be processed to release an unconstrained sequence-independent strand and consequently activate the self-inhibitory guide RNA for conditional gene regulation. This intermediate processor was characterized by the fluorescence reporter system and applied for regulation of the CRISPR/Cas9 binding activity. Using plasmids to generate this sequence-switching machinery in situ, we achieved the autonomous genetic regulation of endogenous RNA expressions controlled by other unrelated endogenous RNAs in both E. coli and human cells. Unlike previously reported strand-displacement genetic circuits, this advanced nucleic acid nanomachine provides a novel approach that can establish regulatory connections between naturally occurring endogenous RNAs. In addition to CRISPR systems, we anticipate this two-hairpin machine can serve as a general processing joint for wide applications in the development of other RNA-based genetic circuits.

Sequence-to-function deep learning frameworks for engineered riboregulators

While synthetic biology has revolutionized our approaches to medicine, agriculture, and energy, the design of completely novel biological circuit components beyond naturally-derived templates remains challenging due to poorly understood design rules. Toehold switches, which are programmable nucleic acid sensors, face an analogous design bottleneck; our limited understanding of how sequence impacts functionality often necessitates expensive, time-consuming screens to identify effective switches. Here, we introduce Sequence-based Toehold Optimization and Redesign Model (STORM) and Nucleic-Acid Speech (NuSpeak), two orthogonal and synergistic deep learning architectures to characterize and optimize toeholds. Applying techniques from computer vision and natural language processing, we 'un-box' our models using convolutional filters, attention maps, and in silico mutagenesis. Through transfer-learning, we redesign sub-optimal toehold sensors, even with sparse training data, experimentally validating their improved performance. This work provides sequence-to-function deep learning frameworks for toehold selection and design, augmenting our ability to construct potent biological circuit components and precision diagnostics.

Engineered RNA-Interacting CRISPR Guide RNAs for Genetic Sensing and Diagnostics

CRISPR guide RNAs (gRNAs) can be programmed with relative ease to allow the genetic editing of nearly any DNA or RNA sequence. Here, we propose novel molecular architectures to achieve RNA-dependent modulation of CRISPR activity in response to specific RNA molecules. We designed and tested, in both living Escherichia coli cells and cell-free assays for rapid prototyping, cis-repressed RNA-interacting guide RNA (igRNA) that switch to their active state only upon interaction with small RNA fragments or long RNA transcripts, including pathogen-derived mRNAs of medical relevance such as the human immunodeficiency virus infectivity factor. The proposed CRISPR-igRNAs are fully customizable and easily adaptable to the majority if not all the available CRISPR-Cas variants to modulate a variety of genetic functions in response to specific cellular conditions, providing orthogonal activation and increased specificity. We thereby foresee a large scope of application for therapeutic, diagnostic, and biotech applications in both prokaryotic and eukaryotic systems.

Enzyme-Assisted Nucleic Acid Detection for Infectious Disease Diagnostics: Moving toward the Point-of-Care

Driven by complex and interconnected factors, including population growth, climate change, and geopolitics, infectious diseases represent one of the greatest healthcare challenges of the 21st century. Diagnostic technologies are the first line of defense in the fight against infectious disease, providing critical information to inform epidemiological models, track diseases, decide treatment choices, and ultimately prevent epidemics. The diagnosis of infectious disease at the genomic level using nucleic acid disease biomarkers has proven to be the most effective approach to date. Such methods rely heavily on enzymes to specifically amplify or detect nucleic acids in complex samples, and significant effort has been exerted to harness the power of enzymes for in vitro nucleic acid diagnostics. Unfortunately, significant challenges limit the potential of enzyme-assisted nucleic acid diagnostics, particularly when translating diagnostic technologies from the lab toward the point-of-use or point-of-care. Herein, we discuss the current state of the field and highlight cross-disciplinary efforts to solve the challenges associated with the successful deployment of this important class of diagnostics at or near the point-of-care.

Engineering a Circular Riboregulator in Escherichia coli

RNAs of different shapes and sizes, natural or synthetic, can regulate gene expression in prokaryotes and eukaryotes. Circular RNAs have recently appeared to be more widespread than previously thought, but their role in prokaryotes remains elusive. Here, by inserting a riboregulatory sequence within a group I permuted intron-exon ribozyme, we created a small noncoding RNA that self-splices to produce a circular riboregulator in Escherichia coli. We showed that the resulting riboregulator can trans-activate gene expression by interacting with a cis-repressed messenger RNA. We characterized the system with a fluorescent reporter and with an antibiotic resistance marker, and we modeled this novel posttranscriptional mechanism. This first reported example of a circular RNA regulating gene expression in E. coli adds to an increasing repertoire of RNA synthetic biology parts, and it highlights that topological molecules can play a role in the case of prokaryotic regulation.

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.

Probing the operability regime of an engineered ribocomputing unit in terms of dynamic range maintenance with extracellular changes and time

Synthetic biology aims at engineering gene regulatory circuits to end with cells (re)programmed on purpose to implement novel functions or discover natural behaviors. However, one overlooked question is whether the resulting circuits perform as intended in variety of environments or with time. Here, we considered a recently engineered genetic system that allows programming the cell to work as a minimal computer (arithmetic logic unit) in order to analyze its operability regime. This system involves transcriptional and post-transcriptional regulations. In particular, we studied the analog behavior of the system, the effect of physicochemical changes in the environment, the impact on cell growth rate of the heterologous expression, and the ability to maintain the arithmetic functioning over time. Conclusively, our results suggest 1) that there are wide input concentration ranges that the system can correctly process, the resulting outputs being predictable with a simple mathematical model, 2) that the engineered circuitry is quite sensitive to temperature effects, 3) that the expression of heterologous small RNAs is costly for the cell, not only of heterologous proteins, and 4) that a proper genetic reorganization of the system to reduce the amount of heterologous DNA in the cell can improve its evolutionary stability.

Designing RNA Secondary Structures Is Hard

A ribonucleic acid (RNA) sequence is a word over an alphabet on four elements [Formula: see text] called bases. RNA sequences fold into secondary structures where some bases pair with one another, while others remain unpaired. The two fundamental problems in RNA algorithmic are to predict how sequences fold within some models of energy and to design sequences of bases that will fold into targeted secondary structures. Predicting how a given RNA sequence folds into a pseudoknot-free secondary structure is known to be solvable in cubic time since the eighties and in truly subcubic time by a recent result of Bringmann et al. (FOCS, 2016), whereas Lyngsø has shown it is computationally hard if pseudoknots are allowed (ICALP, 2004). As a stark contrast, it is unknown whether or not designing a given RNA secondary structure is a tractable task; this has been raised as a challenging open question by Condon (ICALP, 2003). Because of its crucial importance in a number of fields such as pharmaceutical research and biochemistry, there are dozens of heuristics and software libraries dedicated to the RNA secondary structure design. It is therefore rather surprising that the computational complexity of this central problem in bioinformatics has been unsettled for decades. In this article, we show that in the simplest model of energy, which is the Watson-Crick model, the design of secondary structures is computationally hard if one adds natural constraints of the form: index i of the sequence has to be labeled by base b. This negative result suggests that the same lower bound holds for more realistic models of energy. It is noteworthy that the additional constraints are by no means artificial: they are provided by all the RNA design pieces of software and they do correspond to the actual practice (e.g., the instances of the EteRNA project).

Precise and Programmable Detection of Mutations Using Ultraspecific Riboregulators

The ability to identify single-nucleotide mutations is critical for probing cell biology and for precise detection of disease. However, the small differences in hybridization energy provided by single-base changes makes identification of these mutations challenging in living cells and complex reaction environments. Here, we report a class of de novo-designed prokaryotic riboregulators that provide ultraspecific RNA detection capabilities in vivo and in cell-free transcription-translation reactions. These single-nucleotide-specific programmable riboregulators (SNIPRs) provide over 100-fold differences in gene expression in response to target RNAs differing by a single nucleotide in E. coli and resolve single epitranscriptomic marks in vitro. By exploiting the programmable SNIPR design, we implement an automated design algorithm to develop riboregulators for a range of mutations associated with cancer, drug resistance, and genetic disorders. Integrating SNIPRs with portable paper-based cell-free reactions enables convenient isothermal detection of cancer-associated mutations from clinical samples and identification of Zika strains through unambiguous colorimetric reactions.

Timing effciency in small-RNA-regulated post-transcriptional processes

Gene regulation in a cellular environment is a stochastic phenomenon leading to a large variability in mRNAs and protein numbers that are often produced in bursts. The regulation leading to varied protein dynamics can be ascribed to transcriptional or post-transcriptional mechanisms. In transcriptional regulation, the gene dynamically switches between an active and an inactive state, while in the post-transcriptional regulation small RNAs tune the activity of mRNAs. In either scenario, it is possible to calculate the time-dependent probability distribution of proteins and address the interesting question pertaining to their first passage time statistics. The coefficient of variation of first passage time can be considered to be an indicator of efficiency in controlling regulatory pathways and we show that post-transcriptional regulation performs better than simple transcriptional regulation for comparable protein yields.

An sRNA Screen for Reversal of Quinolone Resistance in Escherichia coli

In light of the rising prevalence of antimicrobial resistance (AMR) and the slow pace of new antimicrobial development, there has been increasing interest in the development of adjuvants that improve or restore the effectiveness of existing drugs. Here, we use a novel small RNA (sRNA) screening approach to identify genes whose knockdown increases ciprofloxacin (CIP) sensitivity in a resistant strain of Escherichia coli 5000 sRNA constructs were initially screened on a gyrA S83L background, ultimately leading to 30 validated genes whose disruption reduces CIP resistance. This set includes genes involved in DNA replication, repair, recombination, efflux, and other regulatory systems. Our findings increase understanding of the functional interactions of DNA Gyrase, and may aid in the development of new therapeutic approaches for combating AMR.

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.

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.

Automated Design of Diverse Stand-Alone Riboswitches

Riboswitches that couple binding of ligands to conformational changes offer sensors and control elements for RNA synthetic biology and medical biotechnology. However, design of these riboswitches has required expert intuition or software specialized to transcription or translation outputs; design has been particularly challenging for applications in which the riboswitch output cannot be amplified by other molecular machinery. We present a fully automated design method called RiboLogic for such “stand-alone” riboswitches and test it via high-throughput experiments on 2875 molecules using RNA-MaP (RNA on a massively parallel array) technology. These molecules consistently modulate their affinity to the MS2 bacteriophage coat protein upon binding of flavin mononucleotide, tryptophan, theophylline, and microRNA miR-208a, achieving activation ratios of up to 20 and significantly better performance than control designs. By encompassing a wide diversity of stand-alone switches and highly quantitative data, the resulting ribologic-solves experimental data set provides a rich resource for further improvement of riboswitch models and design methods.

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.

Advances in engineered trans-acting regulatory RNAs and their application in bacterial genome engineering

Small noncoding RNAs, a large class of ancient posttranscriptional regulators, are increasingly recognized and utilized as key modulators of gene expression in a broad range of microorganisms. Owing to their small molecular size and the central role of Watson-Crick base pairing in defining their interactions, structure and function, numerous diverse types of trans-acting RNA regulators that are functional at the DNA, mRNA and protein levels have been experimentally characterized. It has become increasingly clear that most small RNAs play critical regulatory roles in many processes and are, therefore, considered to be powerful tools for genetic engineering and synthetic biology. The trans-acting regulatory RNAs accelerate this ability to establish potential framework for genetic engineering and genome-scale engineering, which allows RNA structure characterization, easier to design and model compared to DNA or protein-based systems. In this review, we summarize recent advances in engineered trans-acting regulatory RNAs that are used in bacterial genome-scale engineering and in novel cellular capabilities as well as their implementation in wide range of biotechnological, biological and medical applications.

Engineering CRISPR guide RNA riboswitches for in vivo applications

CRISPR-based genome editing provides a simple and scalable toolbox for a variety of therapeutic and biotechnology applications. Whilst the fundamental properties of CRISPR proved easily transferable from the native prokaryotic hosts to eukaryotic and multicellular organisms, the tight control of the CRISPR-editing activity remains a major challenge. Here we summarise recent developments of CRISPR and riboswitch technologies and recommend novel functionalised synthetic-gRNA (sgRNA) designs to achieve inducible and spatiotemporal regulation of CRISPR-based genetic editors in response to cellular or extracellular stimuli. We believe that future advances of these tools will have major implications for both basic and applied research, spanning from fundamental genetic studies and synthetic biology to genetic editing and gene therapy.

Cross-Regulation between Bacteria and Phages at a Posttranscriptional Level

The study of bacteriophages (phages) and prophages has provided key insights into almost every cellular process as well as led to the discovery of unexpected new mechanisms and the development of valuable tools. This is exemplified for RNA-based regulation. For instance, the characterization and exploitation of the antiphage CRISPR (clustered regularly interspaced short palindromic repeat) systems is revolutionizing molecular biology. Phage-encoded proteins such as the RNA-binding MS2 protein, which is broadly used to isolate tagged RNAs, also have been developed as valuable tools. Hfq, the RNA chaperone protein central to the function of many base-pairing small RNAs (sRNAs), was first characterized as a bacterial host factor required for Qβ phage replication. The ongoing studies of RNAs are continuing to reveal regulatory connections between infecting phages, prophages, and bacteria and to provide novel insights. There are bacterial and prophage sRNAs that regulate prophage genes, which impact bacterial virulence as well as bacterial cell killing. Conversely, phage- and prophage-encoded sRNAs modulate the expression of bacterial genes modifying metabolism. An interesting subcategory of the prophage-encoded sRNAs are sponge RNAs that inhibit the activities of bacterial-encoded sRNAs. Phages also affect posttranscriptional regulation in bacteria through proteins that inhibit or alter the activities of key bacterial proteins involved in posttranscriptional regulation. However, what is most exciting about phage and prophage research, given the millions of phage-encoded genes that have not yet been characterized, is the vast potential for discovering new RNA regulators and novel mechanisms and for gaining insight into the evolution of regulatory RNAs.

Establishing a Multivariate Model for Predictable Antisense RNA-Mediated Repression

Recent advances in our understanding of RNA folding and functions have facilitated the use of regulatory RNAs such as synthetic antisense RNAs (asRNAs) to modulate gene expression. However, despite the simple and universal complementarity rule, predictable asRNA-mediated repression is still challenging due to the intrinsic complexity of native asRNA-mediated gene regulation. To address this issue, we present a multivariate model, based on the change in free energy of complex formation (Δ G_CF) and percent mismatch of the target binding region, which can predict synthetic asRNA-mediated repression efficiency in diverse contexts. First, 69 asRNAs that bind to multiple target mRNAs were designed and tested to create the predictive model. Second, we showed that the same model is effective predicting repression of target genes in both plasmids and chromosomes. Third, using our model, we designed asRNAs that simultaneously modulated expression of a toxin and its antitoxin to demonstrate tunable control of cell growth. Fourth, we tested and validated the same model in two different biotechnologically important organisms: Escherichia coli Nissle 1917 and Bacillus subtilis 168. Last, multiple parameters, including target locations, the presence of an Hfq binding site, GC contents, and gene expression levels, were revisited to define the conditions under which the multivariate model should be used for accurate prediction. Together, 434 different strain-asRNA combinations were tested, validating the predictive model in a variety of contexts, including multiple target genes and organisms. The result presented in this study is an important step toward achieving predictable tunability of asRNA-mediated repression.

Rationally designing antisense therapy to keep up with evolving bacterial resistance

Antisense molecules used as antibiotics offer the potential to keep up with acquired resistance, by redesigning the sequence of an antisense. Once bacteria acquire resistance by mutating the targeted sequence, new antisense can readily be designed by using sequence information of a target gene. However, antisense molecules require additional delivery vehicles to get into bacteria and be protected from degradation. Based on progress in the last few years it appears that, while redesigning or finding new delivery vehicle will be more difficult than redesigning the antisense cargo, it will perhaps be less difficult than finding new conventional small molecule antibiotics. In this study we propose a protocol that maximizes the combined advantages of engineered delivery vehicle and antisense cargo by decreasing the immediate growth advantage to the pathogen of mutating the entry mechanisms and increasing the advantage to the pathogen of antisense target mutations. Using this protocol, we show by computer simulation an appropriately designed antisense therapy can potentially be effective many times longer than conventional antibiotics before succumbing to resistance. While the simulations describe an in-vitro situation, based on comparison with other in-vitro studies on acquired resistance we believe the advantages of the combination antisense strategy have the potential to provide much more sustainability in vivo than conventional antibiotic therapy.

Advancement of Metabolic Engineering Assisted by Synthetic Biology

Synthetic biology has undergone dramatic advancements for over a decade, during which it has expanded our understanding on the systems of life and opened new avenues for microbial engineering. Many biotechnological and computational methods have been developed for the construction of synthetic systems. Achievements in synthetic biology have been widely adopted in metabolic engineering, a field aimed at engineering micro-organisms to produce substances of interest. However, the engineering of metabolic systems requires dynamic redistribution of cellular resources, the creation of novel metabolic pathways, and optimal regulation of the pathways to achieve higher production titers. Thus, the design principles and tools developed in synthetic biology have been employed to create novel and flexible metabolic pathways and to optimize metabolic fluxes to increase the cells’ capability to act as production factories. In this review, we introduce synthetic biology tools and their applications to microbial cell factory constructions.

Regulatory sRNAs in Cyanobacteria

As the transcriptional and post-transcriptional regulators of gene expression, small RNAs (sRNAs) play important roles in every domain of life in organisms. It has been discovered gradually that bacteria possess multiple means of gene regulation using RNAs. They have been continuously used as model organisms for photosynthesis, metabolism, biotechnology, evolution, and nitrogen fixation for many decades. Cyanobacteria, one of the most ancient life forms, constitute all kinds of photoautotrophic bacteria and exist in almost any environment on this planet. It is believed that a complex RNA-based regulatory mechanism functions in cyanobacteria to help them adapt to changes and stresses in diverse environments. Although lagging far behind other model microorganisms, such as yeast and Escherichia coli, more and more non-coding regulatory sRNAs have been recognized in cyanobacteria during the past decades. In this article, by focusing on cyanobacterial sRNAs, the approaches for detection and targeting of sRNAs will be summarized, four major mechanisms and regulatory functions will be generalized, eight types of cis-encoded sRNA and four types of trans-encoded sRNAs will be reviewed in detail, and their possible physiological functions will be further discussed.

Exploring of the feature space of de novo developed post-transcriptional riboregulators

Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.

To allow reliable forward engineering of microbial cell factories, various metabolic engineering efforts rely on RNA-based technology. As such, programmable riboregulators allow dynamic control over gene expression. However, no clear design principles exist for de novo developed repressing riboregulators, which limits their applicability. Here, various engineering principles are identified and computationally explored. Subsequently, various design criteria are used in an experimental design, which were explored in an in vivo study. This resulted in a regression model that enables a more reliable computational design of repression small RNAs.

Binary addition in a living cell based on riboregulation

Synthetic biology aims at (re-)programming living cells like computers to perform new functions for a variety of applications. Initial work rested on transcription factors, but regulatory RNAs have recently gained much attention due to their high programmability. However, functional circuits mainly implemented with regulatory RNAs are quite limited. Here, we report the engineering of a fundamental arithmetic logic unit based on de novo riboregulation to sum two bits of information encoded in molecular concentrations. Our designer circuit robustly performs the intended computation in a living cell encoding the result as fluorescence amplitudes. The whole system exploits post-transcriptional control to switch on tightly silenced genes with small RNAs, together with allosteric transcription factors to sense the molecular signals. This important result demonstrates that regulatory RNAs can be key players in synthetic biology, and it paves the way for engineering more complex RNA-based biocomputers using this designer circuit as a building block.

RNAblueprint: flexible multiple target nucleic acid sequence design

Motivation

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

Results

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

Availability and implementation

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

Supplementary information

Supplementary data are available at Bioinformatics online.

Post-transcriptional bursting in genes regulated by small RNA molecules

Gene expression programs in living cells are highly dynamic due to spatiotemporal molecular signaling and inherent biochemical stochasticity. Here we study a mechanism based on molecule-to-molecule variability at the RNA level for the generation of bursts of protein production, which can lead to heterogeneity in a cell population. We develop a mathematical framework to show numerically and analytically that genes regulated post transcriptionally by small RNA molecules can exhibit such bursts due to different states of translation activity (on or off), mostly revealed in a regime of few molecules. We exploit this framework to compare transcriptional and post-transcriptional bursting and also to illustrate how to tune the resulting protein distribution with additional post-transcriptional regulations. Moreover, because RNA-RNA interactions are predictable with an energy model, we define the kinetic constants of on-off switching as functions of the two characteristic free-energy differences of the system, activation and formation, with a nonequilibrium scheme. Overall, post-transcriptional bursting represents a distinctive principle linking gene regulation to gene expression noise, which highlights the importance of the RNA layer beyond the simple information transfer paradigm and significantly contributes to the understanding of the intracellular processes from a first-principles perspective.

Quantitative Characterization of Translational Riboregulators Using an in Vitro Transcription-Translation System

Riboregulators are short RNA sequences that, upon binding to a ligand, change their secondary structure and influence the expression rate of a downstream gene. They constitute an attractive alternative to transcription factors for building synthetic gene regulatory networks because they can be engineered de novo. However, riboregulators are generally designed in silico and tested in vivo, which provides little quantitative information about their performances, thus hindering the improvement of design algorithms. Here we show that a cell-free transcription-translation (TX-TL) system provides valuable information about the performances of in silico designed riboregulators. We first propose a simple model that provides a quantitative definition of the dynamic range of a riboregulator. We further characterize two types of translational riboregulators composed of a cis-repressed (cr) and a trans-activating (ta) strand. At the DNA level we demonstrate that high concentrations of taDNA poisoned the activator until total shut off, in agreement with our model, and that relative dynamic ranges of riboregulators determined in vitro are in agreement with published in vivo data. At the RNA level, we show that this approach provides a fast and simple way to measure dissociation constants of functional riboregulators, in contrast to standard mobility-shift assays. Our method opens the route for using cell-free TX-TL systems for the quantitative characterization of functional riboregulators in order to improve their design in silico.