Automated Design of Diverse Stand-Alone Riboswitches

Deep generative design of RNA aptamers using structural predictions

RNAs represent a class of programmable biomolecules capable of performing diverse biological functions. Recent studies have developed accurate RNA three-dimensional structure prediction methods, which may enable new RNAs to be designed in a structure-guided manner. Here, we develop a structure-to-sequence deep learning platform for the de novo generative design of RNA aptamers. We show that our approach can design RNA aptamers that are predicted to be structurally similar, yet sequence dissimilar, to known light-up aptamers that fluoresce in the presence of small molecules. We experimentally validate several generated RNA aptamers to have fluorescent activity, show that these aptamers can be optimized for activity in silico, and find that they exhibit a mechanism of fluorescence similar to that of known light-up aptamers. Our results demonstrate how structural predictions can guide the targeted and resource-efficient design of new RNA sequences.

Engineering acyclovir-induced RNA nanodevices for reversible and tunable control of aptamer function

Small molecule-regulated RNA devices have the potential to modulate diverse aspects of cellular function, but the small molecules used to date have potential toxicities limiting their use in cells. Here we describe a method for creating drug-regulated RNA nanodevices (RNs) using acyclovir, a biologically compatible small molecule with minimal toxicity. Our modular approach involves a scaffold comprising a central F30 three-way junction, an integrated acyclovir aptamer on the input arm, and a variable effector-binding aptamer on the output arm. This design allows for the rapid engineering of acyclovir-regulated RNs, facilitating temporal, tunable, and reversible control of intracellular aptamers. We demonstrate the control of the Broccoli aptamer and the iron-responsive element (IRE) by acyclovir. Regulating the IRE with acyclovir enables precise control over iron-regulatory protein (IRP) sequestration, consequently promoting the inhibition of ferroptosis. Overall, the method described here provides a platform for transforming aptamers into acyclovir-controllable antagonists against physiologic target proteins.

Infrared: a declarative tree decomposition-powered framework for bioinformatics

MOTIVATION

Many bioinformatics problems can be approached as optimization or controlled sampling tasks, and solved exactly and efficiently using Dynamic Programming (DP). However, such exact methods are typically tailored towards specific settings, complex to develop, and hard to implement and adapt to problem variations.

METHODS

We introduce the Infrared framework to overcome such hindrances for a large class of problems. Its underlying paradigm is tailored toward problems that can be declaratively formalized as sparse feature networks, a generalization of constraint networks. Classic Boolean constraints specify a search space, consisting of putative solutions whose evaluation is performed through a combination of features. Problems are then solved using generic cluster tree elimination algorithms over a tree decomposition of the feature network. Their overall complexities are linear on the number of variables, and only exponential in the treewidth of the feature network. For sparse feature networks, associated with low to moderate treewidths, these algorithms allow to find optimal solutions, or generate controlled samples, with practical empirical efficiency.

RESULTS

Implementing these methods, the Infrared software allows Python programmers to rapidly develop exact optimization and sampling applications based on a tree decomposition-based efficient processing. Instead of directly coding specialized algorithms, problems are declaratively modeled as sets of variables over finite domains, whose dependencies are captured by constraints and functions. Such models are then automatically solved by generic DP algorithms. To illustrate the applicability of Infrared in bioinformatics and guide new users, we model and discuss variants of bioinformatics applications. We provide reimplementations and extensions of methods for RNA design, RNA sequence-structure alignment, parsimony-driven inference of ancestral traits in phylogenetic trees/networks, and design of coding sequences. Moreover, we demonstrate multidimensional Boltzmann sampling. These applications of the framework-together with our novel results-underline the practical relevance of Infrared. Remarkably, the achieved complexities are typically equivalent to the ones of specialized algorithms and implementations.

AVAILABILITY

Infrared is available at https://amibio.gitlabpages.inria.fr/Infrared with extensive documentation, including various usage examples and API reference; it can be installed using Conda or from source.

Compact RNA sensors for increasingly complex functions of multiple inputs

Designing single molecules that compute general functions of input molecular partners represents a major unsolved challenge in molecular design. Here, we demonstrate that high-throughput, iterative experimental testing of diverse RNA designs crowdsourced from Eterna yields sensors of increasingly complex functions of input oligonucleotide concentrations. After designing single-input RNA sensors with activation ratios beyond our detection limits, we created logic gates, including challenging XOR and XNOR gates, and sensors that respond to the ratio of two inputs. Finally, we describe the OpenTB challenge, which elicited 85-nucleotide sensors that compute a score for diagnosing active tuberculosis, based on the ratio of products of three gene segments. Building on OpenTB design strategies, we created an algorithm Nucleologic that produces similarly compact sensors for the three-gene score based on RNA and DNA. These results open new avenues for diverse applications of compact, single molecule sensors previously limited by design complexity.

Systematic analysis of cotranscriptional RNA folding using transcription elongation complex display

RNA can fold into structures that mediate diverse cellular functions. Understanding how RNA primary sequence directs the formation of functional structures requires methods that can comprehensively assess how changes in an RNA sequence affect its structure and function. Here we have developed a platform for performing high-throughput cotranscriptional RNA biochemical assays, called Transcription Elongation Complex display (TECdisplay). TECdisplay measures RNA function by fractionating a TEC library based on the activity of cotranscriptionally displayed nascent RNA. In this way, RNA function is measured as the distribution of template DNA molecules between fractions of the transcription reaction. This approach circumvents typical RNA sequencing library preparation steps that can cause technical bias. We used TECdisplay to characterize the transcription antitermination activity of 32,768 variants of the Clostridium beijerinckii pfl ZTP riboswitch designed to perturb steps within its cotranscriptional folding pathway. Our findings establish TECdisplay as an accessible platform for high-throughput RNA biochemical assays.

RNA and Single-Stranded DNA Phages: Unveiling the Promise from the Underexplored World of Viruses

RNA and single-stranded DNA (ssDNA) phages make up an understudied subset of bacteriophages that have been rapidly expanding in the last decade thanks to advancements in metaviromics. Since their discovery, applications of genetic engineering to ssDNA and RNA phages have revealed their immense potential for diverse applications in healthcare and biotechnology. In this review, we explore the past and present applications of this underexplored group of phages, particularly their current usage as therapeutic agents against multidrug-resistant bacteria. We also discuss engineering techniques such as recombinant expression, CRISPR/Cas-based genome editing, and synthetic rebooting of phage-like particles for their role in tailoring phages for disease treatment, imaging, biomaterial development, and delivery systems. Recent breakthroughs in RNA phage engineering techniques are especially highlighted. We conclude with a perspective on challenges and future prospects, emphasizing the untapped diversity of ssDNA and RNA phages and their potential to revolutionize biotechnology and medicine.

Riboswitches, from cognition to transformation

Riboswitches are functional RNA elements that regulate gene expression by directly detecting metabolites. Twenty years have passed since it was first discovered, researches on riboswitches are becoming increasingly standardized and refined, which could significantly promote people's cognition of RNA function as well. Here, we focus on some representative orphan riboswitches, enumerate the structural and functional transformation and artificial design of riboswitches including the coupling with ribozymes, hoping to attain a comprehensive understanding of riboswitch research.

Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system

Cell-free genetically encoded biosensors have been developed to detect small molecules and nucleic acids, but they have yet to be reliably engineered to detect proteins. Here we develop an automated platform to convert protein-binding RNA aptamers into riboswitch sensors that operate within low-cost cell-free assays. We demonstrate the platform by engineering 35 protein-sensing riboswitches for human monomeric C-reactive protein, human interleukin-32γ, and phage MS2 coat protein. The riboswitch sensors regulate output expression levels by up to 16-fold with input protein concentrations within the human serum range. We identify two distinct mechanisms governing riboswitch-mediated regulation of translation rates and leverage computational analysis to refine the protein-binding aptamer regions, improving design accuracy. Overall, we expand the cell-free sensor toolbox and demonstrate how computational design is used to develop protein-sensing riboswitches with future applications as low-cost medical diagnostics.

Massively Parallel Profiling of RNA-targeting CRISPR-Cas13d

Type VI CRISPR enzymes cleave target RNAs and are widely used for gene regulation, RNA tracking, and diagnostics. However, a systematic understanding of their RNA binding specificity and cleavage activation is lacking. Here, we describe RNA chip-hybridized association-mapping platform (RNA-CHAMP), a massively parallel platform that repurposes next-generation DNA sequencing chips to measure the binding affinity for over 10,000 RNA targets containing structural perturbations, mismatches, insertions, and deletions relative to the CRISPR RNA (crRNA). Deep profiling of Cas13d, a compact and widely used RNA nuclease, reveals that it does not require a protospacer flanking sequence (PFS) but is exquisitely sensitive to secondary structure within the target RNA. Cas13d binding is strongly penalized by mismatches, insertions, and deletions in the distal crRNA-target RNA regions, while alterations in the proximal region inhibit nuclease activity without affecting binding. A biophysical model built from these data reveals that target recognition begins at the distal end of unstructured target RNAs and proceeds to the proximal end. Using this model, we designed a series of partially mismatched guide RNAs that modulate nuclease activity to detect single nucleotide polymorphisms (SNPs) in circulating SARS-CoV-2 variants. This work describes the key determinants of RNA targeting by a type VI CRISPR enzyme to improve CRISPR diagnostics and in vivo RNA editing. More broadly, RNA-CHAMP provides a quantitative platform for systematically measuring protein-RNA interactions.

High-throughput biochemistry in RNA sequence space: predicting structure and function

RNAs are central to fundamental biological processes in all known organisms. The set of possible intramolecular interactions of RNA nucleotides defines the range of alternative structural conformations of a specific RNA that can coexist, and these structures enable functional catalytic properties of RNAs and/or their productive intermolecular interactions with other RNAs or proteins. However, the immense combinatorial space of potential RNA sequences has precluded predictive mapping between RNA sequence and molecular structure and function. Recent advances in high-throughput approaches in vitro have enabled quantitative thermodynamic and kinetic measurements of RNA-RNA and RNA-protein interactions, across hundreds of thousands of sequence variations. In this Review, we explore these techniques, how they can be used to understand RNA function and how they might form the foundations of an accurate model to predict the structure and function of an RNA directly from its nucleotide sequence. The experimental techniques and modelling frameworks discussed here are also highly relevant for the sampling of sequence-structure-function space of DNAs and proteins.

RNA secondary structure packages evaluated and improved by high-throughput experiments

Despite the popularity of computer-aided study and design of RNA molecules, little is known about the accuracy of commonly used structure modeling packages in tasks sensitive to ensemble properties of RNA. Here, we demonstrate that the EternaBench dataset, a set of more than 20,000 synthetic RNA constructs designed on the RNA design platform Eterna, provides incisive discriminative power in evaluating current packages in ensemble-oriented structure prediction tasks. We find that CONTRAfold and RNAsoft, packages with parameters derived through statistical learning, achieve consistently higher accuracy than more widely used packages in their standard settings, which derive parameters primarily from thermodynamic experiments. We hypothesized that training a multitask model with the varied data types in EternaBench might improve inference on ensemble-based prediction tasks. Indeed, the resulting model, named EternaFold, demonstrated improved performance that generalizes to diverse external datasets including complete messenger RNAs, viral genomes probed in human cells and synthetic designs modeling mRNA vaccines.

Exploring molecular biology in sequence space: The road to next-generation single-molecule biophysics

Next-generation sequencing techniques have led to a new quantitative dimension in the biological sciences. In particular, integrating sequencing techniques with biophysical tools allows sequence-dependent mechanistic studies. Using the millions of DNA clusters that are generated during sequencing to perform high-throughput binding affinity and kinetics measurements enabled the construction of energy landscapes in sequence space, uncovering relationships between sequence, structure, and function. Here, we review the approaches to perform ensemble fluorescence experiments on next-generation sequencing chips for variations of DNA, RNA, and protein sequences. As the next step, we anticipate that these fluorescence experiments will be pushed to the single-molecule level, which can directly uncover kinetics and molecular heterogeneity in an unprecedented high-throughput fashion. Molecular biophysics in sequence space, both at the ensemble and single-molecule level, leads to new mechanistic insights. The wide spectrum of applications in biology and medicine ranges from the fundamental understanding of evolutionary pathways to the development of new therapeutics.

Crowdsourced RNA design discovers diverse, reversible, efficient, self-contained molecular switches

Internet-based scientific communities promise a means to apply distributed, diverse human intelligence toward previously intractable scientific problems. However, current implementations have not allowed communities to propose experiments to test all emerging hypotheses at scale or to modify hypotheses in response to experiments. We report high-throughput methods for molecular characterization of nucleic acids that enable the large-scale video game–based crowdsourcing of RNA sensor design, followed by high-throughput functional characterization. Iterative design testing of thousands of crowdsourced RNA sensor designs produced near–thermodynamically optimal and reversible RNA switches that act as self-contained molecular sensors and couple five distinct small molecule inputs to three distinct protein binding and fluorogenic outputs. This work suggests a paradigm for widely distributed experimental bioscience.

Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology

We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).

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.

Bacterial two-component systems as sensors for synthetic biology applications

Two-component systems (TCSs) are a ubiquitous family of signal transduction pathways that enable bacteria to sense and respond to diverse physical, chemical, and biological stimuli outside and inside the cell. Synthetic biologists have begun to repurpose TCSs for applications in optogenetics, materials science, gut microbiome engineering, and soil nutrient biosensing, among others. New engineering methods including genetic refactoring, DNA-binding domain swapping, detection threshold tuning, and phosphorylation cross-talk insulation are being used to increase the reliability of TCS sensor performance and tailor TCS signaling properties to the requirements of specific applications. There is now potential to combine these methods with large-scale gene synthesis and laboratory screening to discover the inputs sensed by many uncharacterized TCSs and develop a large new family of genetically-encoded sensors that respond to an unrivaled breadth of stimuli.

RNA Engineering for Public Health: Innovations in RNA-Based Diagnostics and Therapeutics

RNA is essential for cellular function: From sensing intra- and extracellular signals to controlling gene expression, RNA mediates a diverse and expansive list of molecular processes. A long-standing goal of synthetic biology has been to develop RNA engineering principles that can be used to harness and reprogram these RNA-mediated processes to engineer biological systems to solve pressing global challenges. Recent advances in the field of RNA engineering are bringing this to fruition, enabling the creation of RNA-based tools to combat some of the most urgent public health crises. Specifically, new diagnostics using engineered RNAs are able to detect both pathogens and chemicals while generating an easily detectable fluorescent signal as an indicator. New classes of vaccines and therapeutics are also using engineered RNAs to target a wide range of genetic and pathogenic diseases. Here, we discuss the recent breakthroughs in RNA engineering enabling these innovations and examine how advances in RNA design promise to accelerate the impact of engineered RNA systems.

RNA-based fluorescent biosensors for live cell detection of bacterial sRNA

Bacteria contain a diverse set of RNAs to provide tight regulation of gene expression in response to environmental stimuli. Bacterial small RNAs (sRNAs) work in conjunction with protein cofactors to bind complementary mRNA sequences in the cell, leading to up- or downregulation of protein synthesis. In vivo imaging of sRNAs can aid in understanding their spatiotemporal dynamics in real time, which inspires new ways to manipulate these systems for a variety of applications including synthetic biology and therapeutics. Current methods for sRNA imaging are quite limited in vivo and do not provide real-time information about fluctuations in sRNA levels. Herein, we describe our efforts toward the development of an RNA-based fluorescent biosensor for bacterial sRNA both in vitro and in vivo. We validated these sensors for three different bacterial sRNAs in Escherichia coli and demonstrated that the designs provide a bright, sequence-specific signal output in response to exogenous and endogenous RNA targets.

Enhancing single-cell hyaluronic acid biosynthesis by microbial morphology engineering

Microbial morphology engineering is a novel approach for cell factory to improve the titer of target product in bio-manufacture. Hyaluronic acid (HA), a valuable glycosaminoglycan polymerized by HA synthase (HAS), a membrane protein, is particularly selected as the model product to improve its single-cell HA-producing capacity via morphology engineering. DivIVA and FtsZ, the cell-elongation and cell division related protein, respectively, were both down/up dual regulated in C. glutamicum via weak promoter substitution or plasmid overexpression. Different from the natural short-rod shape, varied morphologies of engineered cells, i.e. small-ellipsoid-like (DivIVA-reduced), bulb-like (DivIVA-enhanced), long-rod (FtsZ-reduced) and dumbbell-like (FtsZ-enhanced), were observed. Applying these morphology-changed cells as hosts for HA production, the reduced expression of both DivIVA and FtsZ seriously inhibited normal cell growth; meanwhile, overexpression of DivIVA didn't show morphology changes, but overexpression of FtsZ surprisingly change the cell-shape into long and thick rod with remarkably enlarged single-cell surface area (more than 5.2-fold-increase). And finally, the single-cell HA-producing capacity of the FtsZ-overexpressed C. glutamicum was immensely improved by 13.5-folds. Flow cytometry analyses verified that the single-cell HAS amount on membrane was enhanced by 2.1 folds. This work is pretty valuable for high titer synthesis of diverse metabolic products with microbial cell factory.

Nucleic acid therapeutics: a focus on the development of aptamers

INTRODUCTION

Aptamers provide exciting opportunities for the development of specific and targeted therapeutic approaches.

AREAS COVERED

In this review, the authors discuss different therapeutic options available with nucleic acids, including aptamers, focussing on similarities and differences between them. The authors concentrate on case studies with specific aptamers, which exemplify their distinct advantages. The reasons for failure, wherever available, are deliberated upon. Attempts to accelerate the in vitro selection process have been discussed. Challenges with aptamers in terms of their specificity and targeted delivery and strategies to overcome these are described. Examples of precise regulation of systemic half-life of aptamers using antidotes are discussed.

EXPERT OPINION

Despite their nontoxic nature, a variety of reasons limit the therapeutic potential of aptamers in the clinic. The analysis of adverse effects observed with the pegnivacogin/anivamersen pair has highlighted the need to screen for preexisting PEG antibodies in any clinical trial involving pegylated molecules. Surprisingly, and promisingly, the ability of nucleic acid therapeutics to breach the blood brain barrier seems achievable. The recognition of specific motifs, e.g. G-quadruplex in thrombin-binding aptamers, or a 'nucleation' zone while designing aptamer-antidote pairs, is likely to accelerate the discovery of therapeutically efficacious molecules.

SPRINT: a Cas13a-based platform for detection of small molecules

Recent efforts in biological engineering have made detection of nucleic acids in samples more rapid, inexpensive and sensitive using CRISPR-based approaches. We expand one of these Cas13a-based methods to detect small molecules in a one-batch assay. Using SHERLOCK-based profiling of in vitrotranscription (SPRINT), in vitro transcribed RNA sequence-specifically triggers the RNase activity of Cas13a. This event activates its non-specific RNase activity, which enables cleavage of an RNA oligonucleotide labeled with a quencher/fluorophore pair and thereby de-quenches the fluorophore. This fluorogenic output can be measured to assess transcriptional output. The use of riboswitches or proteins to regulate transcription via specific effector molecules is leveraged as a coupled assay that transforms effector concentration into fluorescence intensity. In this way, we quantified eight different compounds, including cofactors, nucleotides, metabolites of amino acids, tetracycline and monatomic ions in samples. In this manner, hundreds of reactions can be easily quantified in a few hours. This increased throughput also enables detailed characterization of transcriptional regulators, synthetic compounds that inhibit transcription, or other coupled enzymatic reactions. These SPRINT reactions are easily adaptable to portable formats and could therefore be used for the detection of analytes in the field or at point-of-care situations.

Fundamental studies of functional nucleic acids: aptamers, riboswitches, ribozymes and DNAzymes

This review aims at juxtaposing common versus distinct structural and functional strategies that are applied by aptamers, riboswitches, and ribozymes/DNAzymes. Focusing on recently discovered systems, we begin our analysis with small-molecule binding aptamers, with emphasis on in vitro-selected fluorogenic RNA aptamers and their different modes of ligand binding and fluorescence activation. Fundamental insights are much needed to advance RNA imaging probes for detection of exo- and endogenous RNA and for RNA process tracking. Secondly, we discuss the latest gene expression-regulating mRNA riboswitches that respond to the alarmone ppGpp, to PRPP, to NAD⁺, to adenosine and cytidine diphosphates, and to precursors of thiamine biosynthesis (HMP-PP), and we outline new subclasses of SAM and tetrahydrofolate-binding RNA regulators. Many riboswitches bind protein enzyme cofactors that, in principle, can catalyse a chemical reaction. For RNA, however, only one system (glmS ribozyme) has been identified in Nature thus far that utilizes a small molecule - glucosamine-6-phosphate - to participate directly in reaction catalysis (phosphodiester cleavage). We wonder why that is the case and what is to be done to reveal such likely existing cellular activities that could be more diverse than currently imagined. Thirdly, this brings us to the four latest small nucleolytic ribozymes termed twister, twister-sister, pistol, and hatchet as well as to in vitro selected DNA and RNA enzymes that promote new chemistry, mainly by exploiting their ability for RNA labelling and nucleoside modification recognition. Enormous progress in understanding the strategies of nucleic acids catalysts has been made by providing thorough structural fundaments (e.g. first structure of a DNAzyme, structures of ribozyme transition state mimics) in combination with functional assays and atomic mutagenesis.

Application of combinatorial optimization strategies in synthetic biology

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

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.

The Theophylline Aptamer: 25 Years as an Important Tool in Cellular Engineering Research

The theophylline aptamer was isolated from an oligonucleotide library in 1994. Since that time, the aptamer has found wide utility, particularly in synthetic biology, cellular engineering, and diagnostic applications. The primary application of the theophylline aptamer is in the construction and characterization of synthetic riboswitches for regulation of gene expression. These riboswitches have been used to control cellular motility, regulate carbon metabolism, construct logic gates, screen for mutant enzymes, and control apoptosis. Other applications of the theophylline aptamer in cellular engineering include regulation of RNA interference and genome editing through CRISPR systems. Here we describe the uses of the theophylline aptamer for cellular engineering over the past 25 years. In so doing, we also highlight important synthetic biology applications to control gene expression in a ligand-dependent manner.

RNA-based fluorescent biosensors for live cell imaging of small molecules and RNAs

Genetically encodable fluorescent biosensors provide spatiotemporal information on their target analytes in a label-free manner, which has enabled the study of cell biology and signaling in living cells. Over the past three decades, fueled by the development of a wide palette of fluorescent proteins, protein-based fluorescent biosensors against a broad array of targets have been developed. Recently, with the development of fluorogenic RNA aptamer-dye pairs that function in live cells, RNA-based fluorescent (RBF) biosensors have emerged as a complementary class of biosensors. Here we review the current state-of-the-art for fluorogenic RNA aptamers and RBF biosensors for imaging small molecules and RNAs, and highlight some emerging opportunities.

Point-of-Use Detection of Environmental Fluoride via a Cell-Free Riboswitch-Based Biosensor

Advances in biosensor engineering have enabled the design of programmable molecular systems to detect a range of pathogens, nucleic acids, and chemicals. Here, we engineer and field-test a biosensor for fluoride, a major groundwater contaminant of global concern. The sensor consists of a cell-free system containing a DNA template that encodes a fluoride-responsive riboswitch regulating genes that produce a fluorescent or colorimetric output. Individual reactions can be lyophilized for long-term storage and detect fluoride at levels above 2 ppm, the Environmental Protection Agency's most stringent regulatory standard, in both laboratory and field conditions. Through onsite detection of fluoride in a real-world water source, this work provides a critical proof-of-principle for the future engineering of riboswitches and other biosensors to address challenges for global health and the environment.

Zinc-finger protein CNBP alters the 3-D structure of lncRNA Braveheart in solution

Long non-coding RNAs (lncRNAs) constitute a significant fraction of the transcriptome, playing important roles in development and disease. However, our understanding of structure-function relationships for this emerging class of RNAs has been limited to secondary structures. Here, we report the 3-D atomistic structural study of epigenetic lncRNA, Braveheart (Bvht), and its complex with CNBP (Cellular Nucleic acid Binding Protein). Using small angle X-ray scattering (SAXS), we elucidate the ensemble of Bvht RNA conformations in solution, revealing that Bvht lncRNA has a well-defined, albeit flexible 3-D structure that is remodeled upon CNBP binding. Our study suggests that CNBP binding requires multiple domains of Bvht and the RHT/AGIL RNA motif. We show that RHT/AGIL, previously shown to interact with CNBP, contains a highly flexible loop surrounded by more ordered helices. As one of the largest RNA-only 3-D studies, the work lays the foundation for future structural studies of lncRNA-protein complexes.

ssRNA Phages: Life Cycle, Structure and Applications

ssRNA phages belonging to the family Leviviridae are among the tiniest viruses, infecting various Gram-negative bacteria by adsorption to their pilus structures. Due to their simplicity, they have been intensively studied as models for understanding various problems in molecular biology and virology. Several of the studied ssRNA characteristics, such as coat protein–RNA interactions and the ability to readily form virus-like particles in recombinant expression systems, have fueled many practical applications such as RNA labeling and tracking systems and vaccine development. In this chapter, we review the life cycle, structure and applications of these small yet fascinating viruses.

Contemporary Tools for Regulating Gene Expression in Bacteria

Insights from novel mechanistic paradigms in gene expression control have led to the development of new gene expression systems for bioproduction, control, and sensing applications. Coupled with a greater understanding of synthetic burden and modern creative biodesign approaches, contemporary bacterial gene expression tools and systems are emerging that permit fine-tuning of expression, enabling greater predictability and maximisation of specific productivity, while minimising deleterious effects upon cell viability. These advances have been achieved by using a plethora of regulatory tools, operating at all levels of the so-called 'central dogma' of molecular biology. In this review, we discuss these gene regulation tools in the context of their design, prototyping, integration into expression systems, and biotechnological application.