Biomedical applications of RNA-based devices

RNA-Based Sensor Systems for Affordable Diagnostics in the Age of Pandemics

In the era of the COVID-19 pandemic, the significance of point-of-care (POC) diagnostic tools has become increasingly vital, driven by the need for quick and precise virus identification. RNA-based sensors, particularly toehold sensors, have emerged as promising candidates for POC detection systems due to their selectivity and sensitivity. Toehold sensors operate by employing an RNA switch that changes the conformation when it binds to a target RNA molecule, resulting in a detectable signal. This review focuses on the development and deployment of RNA-based sensors for POC viral RNA detection with a particular emphasis on toehold sensors. The benefits and limits of toehold sensors are explored, and obstacles and future directions for improving their performance within POC detection systems are presented. The use of RNA-based sensors as a technology for rapid and sensitive detection of viral RNA holds great potential for effectively managing (dealing/coping) with present and future pandemics in resource-constrained settings.

Targeting Lipoprotein(a): Can RNA Therapeutics Provide the Next Step in the Prevention of Cardiovascular Disease?

Numerous genetic and epidemiologic studies have demonstrated an association between elevated levels of lipoprotein(a) (Lp[a]) and cardiovascular disease. As a result, lowering Lp(a) levels is widely recognized as a promising strategy for reducing the risk of new-onset coronary heart disease, stroke, and heart failure. Lp(a) consists of a low-density lipoprotein-like particle with covalently linked apolipoprotein A (apo[a]) and apolipoprotein B-100, which explains its pro-thrombotic, pro-inflammatory, and pro-atherogenic properties. Lp(a) serum concentrations are genetically determined by the apo(a) isoform, with shorter isoforms having a higher rate of particle synthesis. To date, there are no approved pharmacological therapies that effectively reduce Lp(a) levels. Promising treatment approaches targeting apo(a) expression include RNA-based drugs such as pelacarsen, olpasiran, SLN360, and lepodisiran, which are currently in clinical trials. In this comprehensive review, we provide a detailed overview of RNA-based therapeutic approaches and discuss the recent advances and challenges of RNA therapeutics specifically designed to reduce Lp(a) levels and thus the risk of cardiovascular disease.

Deep generative design of RNA family sequences

RNA engineering has immense potential to drive innovation in biotechnology and medicine. Despite its importance, a versatile platform for the automated design of functional RNA is still lacking. Here, we propose RNA family sequence generator (RfamGen), a deep generative model that designs RNA family sequences in a data-efficient manner by explicitly incorporating alignment and consensus secondary structure information. RfamGen can generate novel and functional RNA family sequences by sampling points from a semantically rich and continuous representation. We have experimentally demonstrated the versatility of RfamGen using diverse RNA families. Furthermore, we confirmed the high success rate of RfamGen in designing functional ribozymes through a quantitative massively parallel assay. Notably, RfamGen successfully generates artificial sequences with higher activity than natural sequences. Overall, RfamGen significantly improves our ability to design functional RNA and opens up new potential for generative RNA engineering in synthetic biology.

Systematic Mutation and Unnatural Base Pair Incorporation Improves Riboswitch-Based Biosensor Response Time

Engineered RNAs have applications in diverse fields from biomedical to environmental. In many cases, the folding of the RNA is critical to its function. Here we describe a strategy to improve the response time of a riboswitch-based fluorescent biosensor. Systematic mutagenesis was performed to either make transpose or transition base pair mutants or introduce orthogonal base pairs. Both natural and unnatural base pair mutants were found to improve the biosensor response time without compromising fold turn-on or ligand affinity. These strategies can be transferred to improve the performance of other RNA-based tools.

Harnessing synthetic biology for advancing RNA therapeutics and vaccine design

Recent global events have drawn into focus the diversity of options for combatting disease across a spectrum of prophylactic and therapeutic approaches. The recent success of the mRNA-based COVID-19 vaccines has paved the way for RNA-based treatments to revolutionize the pharmaceutical industry. However, historical treatment options are continuously updated and reimagined in the context of novel technical developments, such as those facilitated through the application of synthetic biology. When it comes to the development of genetic forms of therapies and vaccines, synthetic biology offers diverse tools and approaches to influence the content, dosage, and breadth of treatment with the prospect of economic advantage provided in time and cost benefits. This can be achieved by utilizing the broad tools within this discipline to enhance the functionality and efficacy of pharmaceutical agent sequences. This review will describe how synthetic biology principles can augment RNA-based treatments through optimizing not only the vaccine antigen, therapeutic construct, therapeutic activity, and delivery vector. The enhancement of RNA vaccine technology through implementing synthetic biology has the potential to shape the next generation of vaccines and therapeutics.

Dissociative Transition State in Hepatitis Delta Virus Ribozyme Catalysis

Ribonucleases and small nucleolytic ribozymes are both able to catalyze RNA strand cleavage through 2'-O-transphosphorylation, provoking the question of whether protein and RNA enzymes facilitate mechanisms that pass through the same or distinct transition states. Here, we report the primary and secondary 18O kinetic isotope effects for hepatitis delta virus ribozyme catalysis that reveal a dissociative, metaphosphate-like transition state in stark contrast to the late, associative transition states observed for reactions catalyzed by specific base, Zn2+ ions, or ribonuclease A. This new information provides evidence for a discrete ribozyme active site design that modulates the RNA cleavage pathway to pass through an altered transition state.

Modulating myoblast differentiation with RNA-based controllers

Tunable genetic controllers play a critical role in the engineering of biological systems that respond to environmental and cellular signals. RNA devices, a class of engineered RNA-based controllers, enable tunable gene expression control of target genes in response to molecular effectors. RNA devices have been demonstrated in a number of systems showing proof-of-concept of applying ligand-responsive control over therapeutic activities, including regulation of cell fate decisions such as T cell proliferation and apoptosis. Here, we describe the application of a theophylline-responsive RNA device in a muscle progenitor cell system to control myogenic differentiation. Ribozyme-based RNA switches responsive to theophylline control fluorescent reporter expression in C2C12 myoblasts in a ligand dependent manner. HRAS and JAK1, both anti-differentiation proteins, were incorporated into RNA devices. Finally, we demonstrate that the regulation of HRAS expression via theophylline-responsive RNA devices results in the modulation of myoblast differentiation in a theophylline-dependent manner. Our work highlights the potential for RNA devices to exert drug-responsive, tunable control over cell fate decisions with applications in stem cell therapy and basic stem cell biology research.

Who stole the proton? Suspect general base guanine found with a smoking gun in the pistol ribozyme

The pistol ribozyme (Psr) is one among the most recently discovered classes of small nucleolytic ribozymes that catalyze site-specific RNA self-cleavage through 2'-O-transphosphorylation. The Psr contains a conserved guanine (G40) that in crystal structures is in a position suggesting it plays the role of the general base to abstract a proton from the nucleophile to activate the reaction. Although some functional data is consistent with this mechanistic role, a notable exception is 2-aminopurine (2AP) substitution which has no effect on the rate, unlike similar substitutions across other so-called "G + M" and "G + A" ribozyme classes. Herein we postulate that an alternate conserved guanine, G42, is the primary general base, and provide evidence from molecular simulations that the active site of Psr can undergo local refolding into a structure that is consistent with the common "L-platform/L-scaffold" architecture identified in G + M and G + A ribozyme classes with Psr currently the notable exception. We summarize the key currently available experimental data and present new classical and combined quantum mechanical/molecular mechanical simulation results that collectively suggest a new hypothesis. We hypothesize that there are two available catalytic pathways supported by different conformational states connected by a local refolding of the active site: (1) a primary pathway with an active site architecture aligned with the L-platform/L-scaffold framework where G42 acts as a general base, and (2) a secondary pathway with the crystallographic active site architecture where G40 acts as a general base. We go on to make several experimentally testable predictions, and suggest specific experiments that would ultimately bring closure to the mystery as to "who stole the proton in the pistol ribozyme?".

Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions

We present a fast, accurate, and robust approach for determination of free energy profiles and kinetic isotope effects for RNA 2'-O-transphosphorylation reactions with inclusion of nuclear quantum effects. We apply a deep potential range correction (DPRc) for combined quantum mechanical/molecular mechanical (QM/MM) simulations of reactions in the condensed phase. The method uses the second-order density-functional tight-binding method (DFTB2) as a fast, approximate base QM model. The DPRc model modifies the DFTB2 QM interactions and applies short-range corrections to the QM/MM interactions to reproduce ab initio DFT (PBE0/6-31G*) QM/MM energies and forces. The DPRc thus enables both QM and QM/MM interactions to be tuned to high accuracy, and the QM/MM corrections are designed to smoothly vanish at a specified cutoff boundary (6 Å in the present work). The computational speed-up afforded by the QM/MM+DPRc model enables free energy profiles to be calculated that include rigorous long-range QM/MM interactions under periodic boundary conditions and nuclear quantum effects through a path integral approach using a new interface between the AMBER and i-PI software. The approach is demonstrated through the calculation of free energy profiles of a native RNA cleavage model reaction and reactions involving thio-substitutions, which are important experimental probes of the mechanism. The DFTB2+DPRc QM/MM free energy surfaces agree very closely with the PBE0/6-31G* QM/MM results, and it is vastly superior to the DFTB2 QM/MM surfaces with and without weighted thermodynamic perturbation corrections. ¹⁸O and ³⁴S primary kinetic isotope effects are compared, and the influence of nuclear quantum effects on the free energy profiles is examined.

diffBUM-HMM: a robust statistical modeling approach for detecting RNA flexibility changes in high-throughput structure probing data

Advancing RNA structural probing techniques with next-generation sequencing has generated demands for complementary computational tools to robustly extract RNA structural information amidst sampling noise and variability. We present diffBUM-HMM, a noise-aware model that enables accurate detection of RNA flexibility and conformational changes from high-throughput RNA structure-probing data. diffBUM-HMM is widely compatible, accounting for sampling variation and sequence coverage biases, and displays higher sensitivity than existing methods while robust against false positives. Our analyses of datasets generated with a variety of RNA probing chemistries demonstrate the value of diffBUM-HMM for quantitatively detecting RNA structural changes and RNA-binding protein binding sites.

Aptamers in Drug Design: An Emerging Weapon to Fight a Losing Battle

Implementation of novel and biocompatible polymers in drug design is an emerging and rapidly growing area of research. Even though we have a large number of polymer materials for various applications, the biocompatibility of these materials remains as a herculean task for researchers. Aptamers provide a vital and efficient solution to this problem. They are usually small (ranging from 20 to 60 nucleotides, single-stranded DNA or RNA oligonucleotides which are capable of binding to molecules possessing high affinity and other properties like specificity. This review focuses on different aspects of Aptamers in drug discovery, starting from its preparation methods and covering the recent scenario reported in the literature regarding their use in drug discovery. We address the limitations of Aptamers and provide valuable insights into their future potential in the areas regarding drug discovery research. Finally, we explained the major role of Aptamers like medical imaging techniques, application as synthetic antibodies, and the most recent application, which is in combination with nanomedicines.

Dynamical ensemble of the active state and transition state mimic for the RNA-cleaving 8-17 DNAzyme in solution

We perform molecular dynamics simulations, based on recent crystallographic data, on the 8-17 DNAzyme at four states along the reaction pathway to determine the dynamical ensemble for the active state and transition state mimic in solution. A striking finding is the diverse roles played by Na+ and Pb2+ ions in the electrostatically strained active site that impact all four fundamental catalytic strategies, and share commonality with some features recently inferred for naturally occurring hammerhead and pistol ribozymes. The active site Pb2+ ion helps to stabilize in-line nucleophilic attack, provides direct electrostatic transition state stabilization, and facilitates leaving group departure. A conserved guanine residue is positioned to act as the general base, and is assisted by a bridging Na+ ion that tunes the pKa and facilitates in-line fitness. The present work provides insight into how DNA molecules are able to solve the RNA-cleavage problem, and establishes functional relationships between the mechanism of these engineered DNA enzymes with their naturally evolved RNA counterparts. This adds valuable information to our growing body of knowledge on general mechanisms of phosphoryl transfer reactions catalyzed by RNA, proteins and DNA.

Linking RNA Sequence, Structure, and Function on Massively Parallel High-Throughput Sequencers

High-throughput sequencing methods have revolutionized our ability to catalog the diversity of RNAs and RNA-protein interactions that can exist in our cells. However, the relationship between RNA sequence, structure, and function is enormously complex, demonstrating the need for methods that can provide quantitative thermodynamic and kinetic measurements of macromolecular interaction with RNA, at a scale commensurate with the sequence diversity of RNA. Here, we discuss a class of methods that extend the core functionality of DNA sequencers to enable high-throughput measurements of RNA folding and RNA-protein interactions. Topics discussed include a description of the method and multiple applications to RNA-binding proteins, riboswitch design and engineering, and RNA tertiary structure energetics.

Cleaning Up Mechanistic Debris Generated by Twister Ribozymes Using Computational RNA Enzymology

The catalytic properties of RNA have been a subject of fascination and intense research since their discovery over 30 years ago. Very recently, several classes of nucleolytic ribozymes have emerged and been characterized structurally. Among these, the twister ribozyme has been center-stage, and a topic of debate about its architecture and mechanism owing to conflicting interpretations of different crystal structures, and in some cases conflicting interpretations of the same functional data. In the present work, we attempt to clean up the mechanistic "debris" generated by twister ribozymes using a comprehensive computational RNA enzymology approach aimed to provide a unified interpretation of existing structural and functional data. Simulations in the crystalline environment and in solution provide insight into the origins of observed differences in crystal structures, and coalesce on a common active site architecture, and dynamical ensemble in solution. We use GPU-accelerated free energy methods with enhanced sampling to ascertain microscopic nucleobase pK a values of the implicated general acid and base, from which predicted activity-pH profiles can be compared directly with experiments. Next, ab initio quantum mechanical/molecular mechanical (QM/MM) simulations with full dynamic solvation under periodic boundary conditions are used to determine mechanistic pathways through multi-dimensional free energy landscapes for the reaction. We then characterize the rate-controlling transition state, and make predictions about kinetic isotope effects and linear free energy relations. Computational mutagenesis is performed to explain the origin of rate effects caused by chemical modifications and make experimentally testable predictions. Finally, we provide evidence that helps to resolve conflicting issues related to the role of metal ions in catalysis. Throughout each stage, we highlight how a conserved L-platform structural motif, to- gether with a key L-anchor residue, forms the characteristic active site scaffold enabling each of the catalytic strategies to come together not only for the twister ribozyme, but the majority of the known small nucleolytic ribozyme classes.

An Ontology for Facilitating Discussion of Catalytic Strategies of RNA-Cleaving Enzymes

A predictive understanding of the mechanisms of RNA cleavage is important for the design of emerging technology built from biological and synthetic molecules that have promise for new biochemical and medicinal applications. Over the past 15 years, RNA cleavage reactions involving 2'-O-transphosphorylation have been discussed using a simplified framework introduced by Breaker that consists of four fundamental catalytic strategies (designated α, β, γ, and δ) that contribute to rate enhancement. As more detailed mechanistic data emerge, there is need for the framework to evolve and keep pace. We develop an ontology for discussion of strategies of enzymes that catalyze RNA cleavage via 2'-O-transphosphorylation that stratifies Breaker's framework into primary (1°), secondary (2°), and tertiary (3°) contributions to enable more precise interpretation of mechanism in the context of structure and bonding. Further, we point out instances where atomic-level changes give rise to changes in more than one catalytic contribution, a phenomenon we refer to as "functional blurring". We hope that this ontology will help clarify our conversations and pave the path forward toward a consensus view of these fundamental and fascinating mechanisms. The insight gained will deepen our understanding of RNA cleavage reactions catalyzed by natural protein and RNA enzymes, as well as aid in the design of new engineered DNA and synthetic enzymes.

Programmable mutually exclusive alternative splicing for generating RNA and protein diversity

Alternative splicing performs a central role in expanding genomic coding capacity and proteomic diversity. However, programming of splicing patterns in engineered biological systems remains underused. Synthetic approaches thus far have predominantly focused on controlling expression of a single protein through alternative splicing. Here, we describe a modular and extensible platform for regulating four programmable exons that undergo a mutually exclusive alternative splicing event to generate multiple functionally-distinct proteins. We present an intron framework that enforces the mutual exclusivity of two internal exons and demonstrate a graded series of consensus sequence elements of varying strengths that set the ratio of two mutually exclusive isoforms. We apply this framework to program the DNA-binding domains of modular transcription factors to differentially control downstream gene activation. This splicing platform advances an approach for generating diverse isoforms and can ultimately be applied to program modular proteins and increase coding capacity of synthetic biological systems.