A multiplexed, automated evolution pipeline enables scalable discovery and characterization of biosensors

Direct testing of natural twister ribozymes from over a thousand organisms reveals a broad tolerance for structural imperfections

Twister ribozymes are an extensively studied class of nucleolytic RNAs. Thousands of natural twisters have been proposed using sequence homology and structural descriptors. Yet, most of these candidates have not been validated experimentally. To address this gap, we developed CHiTA (Cleavage High-Throughput Assay), a high-throughput pipeline utilizing massively parallel oligonucleotide synthesis and next-generation sequencing to test putative ribozymes en masse in a scarless fashion. As proof of principle, we applied CHiTA to a small set of known active and mutant ribozymes. We then used CHiTA to test two large sets of naturally occurring twister ribozymes: over 1, 600 previously reported putative twisters and ∼1, 000 new candidate twisters. The new candidates were identified computationally in ∼1, 000 organisms, representing a massive increase in the number of ribozyme-harboring organisms. Approximately 94% of the twisters we tested were active and cleaved site-specifically. Analysis of their structural features revealed that many substitutions and helical imperfections can be tolerated. We repeated our computational search with structural descriptors updated from this analysis, whereupon we identified and confirmed the first intrinsically active twister ribozyme in mammals. CHiTA broadly expands the number of active twister ribozymes found in nature and provides a powerful method for functional analyses of other RNAs.

GRAPHICAL ABSTRACT

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

Nuclease-assisted selection of slow-off rate aptamers

Conventional directed evolution methods offer the ability to select bioreceptors with high binding affinity for a specific target in terms of thermodynamic properties. However, there is a lack of analogous approaches for kinetic selection, which could yield affinity reagents that exhibit slow off-rates and thus remain tightly bound to targets for extended periods. Here, we describe an in vitro directed evolution methodology that uses the nuclease flap endonuclease 1 to achieve the efficient discovery of aptamers that have slow dissociation rates. Our nuclease-assisted selection strategy can yield specific aptamers for both small molecules and proteins with off-rates that are an order of magnitude slower relative to those obtained with conventional selection methods while still retaining excellent overall target affinity in terms of thermodynamics. This new methodology provides a generalizable approach for generating slow off-rate aptamers for diverse targets, which could, in turn, prove valuable for applications including molecular devices, bioimaging, and therapy.

In-vitro Clinical Diagnostics using RNA-Cleaving DNAzymes

Over the last three decades, significant advancements have been made in the development of biosensors and bioassays that use RNA-cleaving DNAzymes (RCDs) as molecular recognition elements. While early examples of RCDs were primarily responsive to metal ions, the past decade has seen numerous RCDs reported for more clinically relevant targets such as bacteria, cancer cells, small metabolites, and protein biomarkers. Over the past 5 years several RCD-based biosensors have also been evaluated using either spiked biological matrixes or patient samples, including blood, serum, saliva, nasal mucus, sputum, urine, and faeces, which is a critical step toward regulatory approval and commercialization of such sensors. In this review, an overview of the methods used to generate RCDs and the properties of key RCDs that have been utilized for in vitro testing is first provided. Examples of RCD-based assays and sensors that have been used to test either spiked biological samples or patient samples are then presented, highlighting assay performance in different biological matrixes. A summary of current prospects and challenges for development of in vitro diagnostic tests incorporating RCDs and an overview of future directions of the field is also provided.

Non-invasive single cell aptasensing in live cells and animals

We report a genetically encoded aptamer biosensor platform for non-invasive measurement of drug distribution in cells and animals. We combined the high specificity of aptamer molecular recognition with the easy-to-detect properties of fluorescent proteins. We generated six encoded aptasensors, showcasing the platform versatility. The biosensors display high sensitivity and specificity for detecting their specific drug target over related analogs. We show dose dependent response of biosensor performance reaching saturating drug uptake levels in individual live cells. We designed our platform for integration into animal genomes; thus, we incorporated aptamer biosensors into zebrafish, an important model vertebrate. The biosensors enabled non-invasive drug biodistribution imaging in whole animals across different timepoints. To our knowledge, this is the first example of an aptamer biosensor-expressing transgenic vertebrate that is carried through generations. As such, our encoded platform addresses the need for non-invasive whole animal biosensing ideal for pharmacokinetic-pharmacodynamic analyses that can be expanded to other organisms and to detect diverse molecules of interest.

An RNA Motif That Enables Optozyme Control and Light-Dependent Gene Expression in Bacteria and Mammalian Cells

The regulation of gene expression by light enables the versatile, spatiotemporal manipulation of biological function in bacterial and mammalian cells. Optoribogenetics extends this principle by molecular RNA devices acting on the RNA level whose functions are controlled by the photoinduced interaction of a light-oxygen-voltage photoreceptor with cognate RNA aptamers. Here light-responsive ribozymes, denoted optozymes, which undergo light-dependent self-cleavage and thereby control gene expression are described. This approach transcends existing aptamer-ribozyme chimera strategies that predominantly rely on aptamers binding to small molecules. The optozyme method thus stands to enable the graded, non-invasive, and spatiotemporally resolved control of gene expression. Optozymes are found efficient in bacteria and mammalian cells and usher in hitherto inaccessible optoribogenetic modalities with broad applicability in synthetic and systems biology.

Aptamers in neuro-oncology: An emerging therapeutic modality

Despite recent advances in the understanding of brain tumor pathophysiology, challenges associated with tumor location and characteristics have prevented significant improvement in neuro-oncology therapies. Aptamers are short, single-stranded DNA or RNA oligonucleotides that fold into sequence-specific, 3-dimensional shapes that, like protein antibodies, interact with targeted ligands with high affinity and specificity. Aptamer technology has recently been applied to neuro-oncology as a potential approach to innovative therapy. Preclinical research has demonstrated the ability of aptamers to overcome some obstacles that have traditionally rendered neuro-oncology therapies ineffective. Potential aptamer advantages include their small size, ability in some cases to penetrate the blood-brain barrier, inherent lack of immunogenicity, and applicability for discovering novel biomarkers. Herein, we review recent reports of aptamer applications in neuro-oncology including aptamers found by cell- and in vivo- Systematic Evolution of Ligands by Exponential Enrichment approaches, aptamer-targeted therapeutic delivery modalities, and aptamers in diagnostics and imaging. We further identify crucial future directions for the field that will be important to advance aptamer-based drugs or tools to clinical application in neuro-oncology.

Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Engineering U1-Based Tetracycline-Inducible Riboswitches to Control Gene Expression in Mammals

Synthetic riboswitches are promising regulatory devices due to their small size, lack of immunogenicity, and ability to fine-tune gene expression in the absence of exogenous trans-acting factors. Based on a gene inhibitory system developed at our lab, termed U1snRNP interference (U1i), we developed tetracycline (TC)-inducible riboswitches that modulate mRNA polyadenylation through selective U1 snRNP recruitment. First, we engineered different TC-U1i riboswitches, which repress gene expression unless TC is added, leading to inductions of gene expression of 3-to-4-fold. Second, we developed a technique called Systematic Evolution of Riboswitches by Exponential Enrichment (SEREX), to isolate riboswitches with enhanced U1 snRNP binding capacity and activity, achieving inducibilities of up to 8-fold. Interestingly, by multiplexing riboswitches we increased inductions up to 37-fold. Finally, we demonstrated that U1i-based riboswitches are dose-dependent and reversible and can regulate the expression of reporter and endogenous genes in culture cells and mouse models, resulting in attractive systems for gene therapy applications. Our work probes SEREX as a much-needed technology for the in vitro identification of riboswitches capable of regulating gene expression in vivo.

Design of synthetic bacterial biosensors

Novel whole-cell bacterial biosensor designs require an emphasis on moving toward field deployment. Many current sensors are characterized under specified laboratory conditions, which frequently do not represent actual deployment conditions. To this end, recent developments such as toolkits for probing new host chassis that are more robust to environments of interest, have paved the way for improved designs. Strategies for rational tuning of genetic components or tools such as genetic amplifiers or designs that allow post hoc tuning are essential in optimizing existing biosensors for practical application. Furthermore, recent work has seen a rise in directed evolution techniques, which can be immensely valuable in both tuning existing sensors and developing sensors for new analytes that lack characterized sensors. Combined with advancements in bioinformatics and capabilities in rewiring two-component systems, many new sensors can be established, broadening biosensor use cases. Last, recent work in CRISPR-based dynamic regulation and memory mechanisms, as well as kill-switches for biosafety and innovative output integration concepts, represents promising steps toward designing bacterial biosensors for deployment in dynamic and heterogeneous conditions.

Target-dependent RNA polymerase as universal platform for gene expression control in response to intracellular molecules

Controlling gene expression in response to specific molecules is an essential technique for regulating cellular functions. However, current platforms with transcription and translation regulators have a limited number of detectable molecules to induce gene expression. Here to address these issues, we present a Target-dependent RNA polymerase (TdRNAP) that can induce RNA transcription in response to the intracellular target specifically recognized by single antibody. By substituting the fused antibody, we demonstrate that TdRNAPs respond to a wide variety of molecules, including peptides, proteins, RNA, and small molecules, and produce desired transcripts in human cells. Furthermore, we show that multiple TdRNAPs can construct orthogonal and multilayer genetic circuits. Finally, we apply TdRNAP to achieve cell-specific genome editing that is autonomously triggered by detecting the target gene product. TdRNAP can expand the molecular variety for controlling gene expression and provide the genetic toolbox for bioengineering and future therapeutic applications.

In vitro selection of aptamers and their applications

The introduction of the in-vitro evolution method known as SELEX (Systematic Evolution of Ligands by Exponential enrichment) more than 30 years ago led to the conception of versatile synthetic receptors known as aptamers. Offering many benefits such as low cost, high stability and flexibility, aptamers have sparked innovation in molecular diagnostics, enabled advances in synthetic biology and have facilitated new therapeutic approaches. The SELEX method itself is inherently adaptable and offers near limitless possibilities in yielding functional nucleic acid ligands. This Primer serves to provide guidance on experimental design and highlight new growth areas for this impactful technology.

Generative and predictive neural networks for the design of functional RNA molecules

RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence and structural properties of an RNA molecule and its ability to perform specific functions often necessitates extensive experimental screening of candidate sequences. Here we present a generalized neural network architecture that utilizes the sequence and structure of RNA molecules (SANDSTORM) to inform functional predictions. We demonstrate that this approach achieves state-of-the-art performance across several distinct RNA prediction tasks, while learning interpretable abstractions of RNA secondary structure. We paired these predictive models with generative adversarial RNA design networks (GARDN), allowing the generative modelling of novel mRNA 5' untranslated regions and toehold switch riboregulators exhibiting a predetermined fitness. This approach enabled the design of novel toehold switches with a 43-fold increase in experimentally characterized dynamic range compared to those designed using classic thermodynamic algorithms. SANDSTORM and GARDN thus represent powerful new predictive and generative tools for the development of diagnostic and therapeutic RNA molecules with improved function.

Semi-automated and efficient parallel SELEX of aptamers for multiple targets

In this study, we constructed and optimized a semi-automatic instrument to perform aptamer SELEX targeting multiple proteins simultaneously. Our work provides a simple SELEX platform characterized by real-time feedback, which is time efficient and can reduce human intervention. A number of aptamers were rapidly screened by this method. Moreover, the binding affinities of these aptamers were verified by various methods, including SPR and flow cytometry, which supports the applicability and reliability of our newly established aptamer SELEX system.

Synthetic biology tools to promote the folding and function of RNA aptamers in mammalian cells

RNA aptamers are structured RNAs that can bind to diverse ligands, including proteins, metabolites, and other small molecules. RNA aptamers are widely used as in vitro affinity reagents. However, RNA aptamers have not been highly successful as bioactive intracellular molecules that can bind target molecules and influence cellular processes. We describe how poor RNA aptamer expression and especially poor RNA aptamer folding have limited the use of RNA aptamers in RNA synthetic biology applications. We discuss innovative new approaches that promote RNA aptamer folding in living cells and how these approaches have improved the function of aptamers in mammalian cells. These new approaches are making RNA aptamer-based synthetic biology and RNA aptamer therapeutic applications much more achievable.

Dynamic RNA synthetic biology: new principles, practices and potential

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

De novo selected hACE2 mimics that integrate hotspot peptides with aptameric scaffolds for binding tolerance of SARS-CoV-2 variants

The frequent occurrence of viral variants is a critical problem in developing antiviral prophylaxis and therapy; along with stronger recognition of host cell receptors, the variants evade the immune system-based vaccines and neutralizing agents more easily. In this work, we focus on enhanced receptor binding of viral variants and demonstrate generation of receptor-mimicking synthetic reagents, capable of strongly interacting with viruses and their variants. The hotspot interaction of viruses with receptor-derived short peptides is maximized by aptamer-like scaffolds, the compact and stable architectures of which can be in vitro selected from a myriad of the hotspot peptide-coupled random nucleic acids. We successfully created the human angiotensin-converting enzyme 2 (hACE2) receptor-mimicking hybrid ligand that recruits the hACE2-derived receptor binding domain-interacting peptide to directly interact with a binding hotspot of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Experiencing affinity boosting by ~500% to Omicron, the de novo selected hACE2 mimic exhibited a great binding tolerance to all SARS-CoV-2 variants of concern.

Highly multiplexed selection of RNA aptamers against a small molecule library

Applications of synthetic biology spanning human health, industrial bioproduction, and ecosystem monitoring often require small molecule sensing capabilities, typically in the form of genetically encoded small molecule biosensors. Critical to the deployment of greater numbers of these systems are methods that support the rapid development of such biosensors against a broad range of small molecule targets. Here, we use a previously developed method for selection of RNA biosensors against unmodified small molecules (DRIVER) to perform a selection against a densely multiplexed mixture of small molecules, representative of those employed in high-throughput drug screening. Using a mixture of 5,120 target compounds randomly sampled from a large diversity drug screening library, we performed a 95-round selection and then analyzed the enriched RNA biosensor library using next generation sequencing (NGS). From our analysis, we identified RNA biosensors with at least 2-fold change in signal in the presence of at least 217 distinct target compounds with sensitivities down to 25 nM. Although many of these biosensors respond to multiple targets, clustering analysis indicated at least 150 different small-molecule sensing patterns. We also built a classifier that was able to predict whether the biosensors would respond to a new compound with an average precision of 0.82. Since the target compound library was designed to be representative of larger diversity compound libraries, we expect that the described approach can be used with similar compound libraries to identify aptamers against other small molecules with a similar success rate. The new RNA biosensors (or their component aptamers) described in this work can be further optimized and used in applications such as biosensing, gene control, or enzyme evolution. In addition, the data presented here provide an expanded compendium of new RNA aptamers compared to the 82 small molecule RNA aptamers published in the literature, allowing further bioinformatic analyses of the general classes of small molecules for which RNA aptamers can be found.

Future of Digital Assays to Resolve Clinical Heterogeneity of Single Extracellular Vesicles

Extracellular vesicles (EVs) are complex lipid membrane vehicles with variable expressions of molecular cargo, composed of diverse subpopulations that participate in the intercellular signaling of biological responses in disease. EV-based liquid biopsies demonstrate invaluable clinical potential for overhauling current practices of disease management. Yet, EV heterogeneity is a major needle-in-a-haystack challenge to translate their use into clinical practice. In this review, existing digital assays will be discussed to analyze EVs at a single vesicle resolution, and future opportunities to optimize the throughput, multiplexing, and sensitivity of current digital EV assays will be highlighted. Furthermore, this review will outline the challenges and opportunities that impact the clinical translation of single EV technologies for disease diagnostics and treatment monitoring.

Metabolic and cellular engineering for the production of natural products

Increased awareness of the environmental and health concerns of consuming chemically synthesized products has led to a rising demand for natural products that are greener and more sustainable. Despite their importance, however, industrial-scale production of natural products has been challenging due to the low yield and high cost of the bioprocesses. To cope with this problem, systems metabolic engineering has been employed to efficiently produce natural products from renewable biomass. Here, we review the recent systems metabolic engineering strategies employed for enhanced production of value-added natural products, together with accompanying examples. Particular focus is set on systems-level engineering and cell physiology engineering strategies. Future perspectives are also discussed.

Synthetic RNA-based post-transcriptional expression control methods and genetic circuits

RNA-based synthetic genetic circuits provide an alternative for traditional transcription-based circuits in applications where genomic integration is to be avoided. Incorporating various post-transcriptional control methods into such circuits allows for controlling the behaviour of the circuit through the detection of certain biomolecular inputs or reconstituting defined circuit behaviours, thus manipulating cellular functions. In this review, recent developments of various types of post-transcriptional control methods in mammalian cells are discussed as well as auxiliary components that allow for the creation and development of mRNA-based switches. How such post-transcriptional switches are combined into synthetic circuits as well as their applications in biomedical and preclinical settings are also described. Finally, we examine the challenges that need to be surmounted before RNA-based synthetic circuits can be reliably deployed into clinical settings.

Engineering synthetic RNA devices for cell control

The versatility of RNA in sensing and interacting with small molecules, proteins and other nucleic acids while encoding genetic instructions for protein translation makes it a powerful substrate for engineering biological systems. RNA devices integrate cellular information sensing, processing and actuation of specific signals into defined functions and have yielded programmable biological systems and novel therapeutics of increasing sophistication. However, challenges centred on expanding the range of analytes that can be sensed and adding new mechanisms of action have hindered the full realization of the field's promise. Here, we describe recent advances that address these limitations and point to a significant maturation of synthetic RNA-based devices.

Dynamic RNA fitness landscapes of a group I ribozyme during changes to the experimental environment

Fitness landscapes of protein and RNA molecules can be studied experimentally using high-throughput techniques to measure the functional effects of numerous combinations of mutations. The rugged topography of these molecular fitness landscapes is important for understanding and predicting natural and experimental evolution. Mutational effects are also dependent upon environmental conditions, but the effects of environmental changes on fitness landscapes remains poorly understood. Here, we investigate the changes to the fitness landscape of a catalytic RNA molecule while changing a single environmental variable that is critical for RNA structure and function. Using high-throughput sequencing of in vitro selections, we mapped a fitness landscape of the Azoarcus group I ribozyme under eight different concentrations of magnesium ions (1–48 mM MgCl₂). The data revealed the magnesium dependence of 16,384 mutational neighbors, and from this, we investigated the magnesium induced changes to the topography of the fitness landscape. The results showed that increasing magnesium concentration improved the relative fitness of sequences at higher mutational distances while also reducing the ruggedness of the mutational trajectories on the landscape. As a result, as magnesium concentration was increased, simulated populations evolved toward higher fitness faster. Curve-fitting of the magnesium dependence of individual ribozymes demonstrated that deep sequencing of in vitro reactions can be used to evaluate the structural stability of thousands of sequences in parallel. Overall, the results highlight how environmental changes that stabilize structures can also alter the ruggedness of fitness landscapes and alter evolutionary processes.

Sweet sensation: Developing a single-cell fluorescent reporter of glycolytic heterogeneity

Conversion of in vitro selected aptamers into functional metabolic sensors is hampered by reduced in vivo aptamer binding and limited tunability of cellular metabolite levels. In this issue of Cell Chemical Biology, Ortega et al. (2021) construct RNA sensors of fructose-6-bisphosphate (FBP) that report on metabolite levels within single yeast cells.

Riboswitches for Controlled Expression of Therapeutic Transgenes Delivered by Adeno-Associated Viral Vectors

Vectors developed from adeno-associated virus (AAV) are powerful tools for in vivo transgene delivery in both humans and animal models, and several AAV-delivered gene therapies are currently approved for clinical use. However, AAV-mediated gene therapy still faces several challenges, including limited vector packaging capacity and the need for a safe, effective method for controlling transgene expression during and after delivery. Riboswitches, RNA elements which control gene expression in response to ligand binding, are attractive candidates for regulating expression of AAV-delivered transgene therapeutics because of their small genomic footprints and non-immunogenicity compared to protein-based expression control systems. In addition, the ligand-sensing aptamer domains of many riboswitches can be exchanged in a modular fashion to allow regulation by a variety of small molecules, proteins, and oligonucleotides. Riboswitches have been used to regulate AAV-delivered transgene therapeutics in animal models, and recently developed screening and selection methods allow rapid isolation of riboswitches with novel ligands and improved performance in mammalian cells. This review discusses the advantages of riboswitches in the context of AAV-delivered gene therapy, the subsets of riboswitch mechanisms which have been shown to function in human cells and animal models, recent progress in riboswitch isolation and optimization, and several examples of AAV-delivered therapeutic systems which might be improved by riboswitch regulation.