Evaluating riboswitch optimality

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.

The ribosome as a small-molecule sensor

Sensing small molecules is crucial for microorganisms to adapt their genetic programs to changes in their environment. Arrest peptides encoded by short regulatory open reading frames program the ribosomes that translate them to undergo translational arrest in response to specific metabolites. Ribosome stalling in turn controls the expression of downstream genes on the same messenger RNA by translational or transcriptional means. In this review, we present our current understanding of the mechanisms by which ribosomes translating arrest peptides sense different metabolites, such as antibiotics or amino acids, to control gene expression.

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.

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.

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.

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.

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.