Effects of flanking regions on HDV cotranscriptional folding kinetics

Design Approaches to Expand the Toolkit for Building Cotranscriptionally Encoded RNA Strand Displacement Circuits

Cotranscriptionally encoded RNA strand displacement (ctRSD) circuits are an emerging tool for programmable molecular computation, with potential applications spanning in vitro diagnostics to continuous computation inside living cells. In ctRSD circuits, RNA strand displacement components are continuously produced together via transcription. These RNA components can be rationally programmed through base pairing interactions to execute logic and signaling cascades. However, the small number of ctRSD components characterized to date limits circuit size and capabilities. Here, we characterize over 200 ctRSD gate sequences, exploring different input, output, and toehold sequences and changes to other design parameters, including domain lengths, ribozyme sequences, and the order in which gate strands are transcribed. This characterization provides a library of sequence domains for engineering ctRSD components, i.e., a toolkit, enabling circuits with up to 4-fold more inputs than previously possible. We also identify specific failure modes and systematically develop design approaches that reduce the likelihood of failure across different gate sequences. Lastly, we show the ctRSD gate design is robust to changes in transcriptional encoding, opening a broad design space for applications in more complex environments. Together, these results deliver an expanded toolkit and design approaches for building ctRSD circuits that will dramatically extend capabilities and potential applications.

Landscape Zooming toward the Prediction of RNA Cotranscriptional Folding

RNA molecules fold as they are transcribed. Cotranscriptional folding of RNA plays a critical role in RNA functions in vivo. Present computational strategies focus on simulations where large structural changes may not be completely sampled. Here, we describe an alternative approach to predicting cotranscriptional RNA folding by zooming in and out of the RNA folding energy landscape. By classifying the RNA structural ensemble into "partitions" based on long, stable helices, we zoom out of the landscape and predict the overall slow folding kinetics from the interpartition kinetic network, and for each interpartition transition, we zoom in on the landscape to simulate the kinetics. Applications of the model to the 117-nucleotide E. coli SRP RNA and the 59-nucleotide HIV-1 TAR RNA show agreements with the experimental data and new structural and kinetic insights into biologically significant conformational switches and pathways for these important systems. This approach, by zooming in/out of an RNA folding landscape at different resolutions, might allow us to treat large RNAs in vivo with transcriptional pause, transcription speed, and other in vivo effects.

Regulation of the ThiM riboswitch is facilitated by the trapped structure formed during transcription of the wild-type sequence

The ThiM riboswitch from Escherichia coli is a typical mRNA device that modulates downstream gene expression by sensing TPP. The helix-based RNA folding theory is used to investigate its detailed regulatory behaviors in cells. This RNA molecule is transcriptionally trapped in a state with the unstructured SD sequence in the absence of TPP, which induces downstream gene expression. As a key step to turn on gene expression, formation of this trapped state (the genetic ON state) highly depends on the co-transcriptional folding of its wild-type sequence. Instead of stabilities of the genetic ON and OFF states, the transcription rate, pause, and ligand levels are combined to affect the ThiM riboswitch-mediated gene regulation, which is consistent with a kinetic control model.

A Cas12a-based gene editing system for Phytophthora infestans reveals monoallelic expression of an elicitor

Phytophthora infestans is a destructive pathogen of potato and a model for investigations of oomycete biology. The successful application of a CRISPR gene editing system to P. infestans is so far unreported. We discovered that it is difficult to express CRISPR/Cas9 but not a catalytically inactive form in transformants, suggesting that the active nuclease is toxic. We were able to achieve editing with CRISPR/Cas12a using vectors in which the nuclease and its guide RNA were expressed from a single transcript. Using the elicitor gene Inf1 as a target, we observed editing of one or both alleles in up to 13% of transformants. Editing was more efficient when guide RNA processing relied on the Cas12a direct repeat instead of ribozyme sequences. INF1 protein was not made when both alleles were edited in the same transformant, but surprisingly also when only one allele was altered. We discovered that the isolate used for editing, 1306, exhibited monoallelic expression of Inf1 due to insertion of a copia-like element in the promoter of one allele. The element exhibits features of active retrotransposons, including a target site duplication, long terminal repeats, and an intact polyprotein reading frame. Editing occurred more often on the transcribed allele, presumably due to differences in chromatin structure. The Cas12a system not only provides a tool for modifying genes in P. infestans, but also for other members of the genus by expanding the number of editable sites. Our work also highlights a natural mechanism that remodels oomycete genomes.

Salt-Dependent RNA Pseudoknot Stability: Effect of Spatial Confinement

Macromolecules, such as RNAs, reside in crowded cell environments, which could strongly affect the folded structures and stability of RNAs. The emergence of RNA-driven phase separation in biology further stresses the potential functional roles of molecular crowding. In this work, we employed the coarse-grained model that was previously developed by us to predict 3D structures and stability of the mouse mammary tumor virus (MMTV) pseudoknot under different spatial confinements over a wide range of salt concentrations. The results show that spatial confinements can not only enhance the compactness and stability of MMTV pseudoknot structures but also weaken the dependence of the RNA structure compactness and stability on salt concentration. Based on our microscopic analyses, we found that the effect of spatial confinement on the salt-dependent RNA pseudoknot stability mainly comes through the spatial suppression of extended conformations, which are prevalent in the partially/fully unfolded states, especially at low ion concentrations. Furthermore, our comprehensive analyses revealed that the thermally unfolding pathway of the pseudoknot can be significantly modulated by spatial confinements, since the intermediate states with more extended conformations would loss favor when spatial confinements are introduced.

Combined small molecule and loss-of-function screen uncovers estrogen receptor alpha and CAD as host factors for HDV infection and antiviral targets

OBJECTIVE

Hepatitis D virus (HDV) is a circular RNA virus coinfecting hepatocytes with hepatitis B virus. Chronic hepatitis D results in severe liver disease and an increased risk of liver cancer. Efficient therapeutic approaches against HDV are absent.

DESIGN

Here, we combined an RNAi loss-of-function and small molecule screen to uncover host-dependency factors for HDV infection.

RESULTS

Functional screening unravelled the hypoxia-inducible factor (HIF)-signalling and insulin-resistance pathways, RNA polymerase II, glycosaminoglycan biosynthesis and the pyrimidine metabolism as virus-hepatocyte dependency networks. Validation studies in primary human hepatocytes identified the carbamoyl-phosphatesynthetase 2, aspartate transcarbamylase and dihydroorotase (CAD) enzyme and estrogen receptor alpha (encoded by ESR1) as key host factors for HDV life cycle. Mechanistic studies revealed that the two host factors are required for viral replication. Inhibition studies using N-(phosphonoacetyl)-L-aspartic acid and fulvestrant, specific CAD and ESR1 inhibitors, respectively, uncovered their impact as antiviral targets.

CONCLUSION

The discovery of HDV host-dependency factors elucidates the pathogenesis of viral disease biology and opens therapeutic strategies for HDV cure.

Regulation of the thiamine pyrophosphate (TPP)-sensing riboswitch in NMT1 mRNA from Neurospora crassa

The expression of Neurospora crassa NMT1 involved in thiamine pyrophosphate (TPP) metabolism is regulated at the level of mRNA splicing by a TPP-sensing riboswitch within the precursor NMT1 mRNA. Here, using the systematic helix-based computational method, we investigated the regulation of this riboswitch. We find that the function of the riboswitch does not depend on the transcription process. Whether TPP is present or not, the riboswitch predominately folds into the ON state, while the OFF state aptamer structure does not appear during transcription. Since the transition from the ON state to the aptamer structure is extremely slow, TPP may interact with the RNA before full formation of the aptamer structure, promoting the switch flipping. The potential to fully form helix P0 of the ON state is necessary to restore ligand-dependent gene control by the riboswitch.

Structure folding of RNA kissing complexes in salt solutions: predicting 3D structure, stability, and folding pathway

RNA kissing complexes are essential for genomic RNA dimerization and regulation of gene expression, and their structures and stability are critical to their biological functions. In this work, we used our previously developed coarse-grained model with an implicit structure-based electrostatic potential to predict three-dimensional (3D) structures and stability of RNA kissing complexes in salt solutions. For extensive RNA kissing complexes, our model shows great reliability in predicting 3D structures from their sequences, and our additional predictions indicate that the model can capture the dependence of 3D structures of RNA kissing complexes on monovalent/divalent ion concentrations. Moreover, the comparisons with extensive experimental data show that the model can make reliable predictions on the stability for various RNA kissing complexes over wide ranges of monovalent/divalent ion concentrations. Notably, for RNA kissing complexes, our further analyses show the important contribution of coaxial stacking to the 3D structures and stronger stability than the corresponding kissing-interface duplexes at high salts. Furthermore, our comprehensive analyses for RNA kissing complexes reveal that the thermally folding pathway for a complex sequence is mainly determined by the relative stability of two possible folded states of kissing complex and extended duplex, which can be significantly modulated by its sequence.

What is the best reference state for building statistical potentials in RNA 3D structure evaluation?

Knowledge-based statistical potentials have been shown to be efficient in protein structure evaluation/prediction, and the core difference between various statistical potentials is attributed to the choice of reference states. However, for RNA 3D structure evaluation, a comprehensive examination on reference states is still lacking. In this work, we built six statistical potentials based on six reference states widely used in protein structure evaluation, including averaging, quasi-chemical approximation, atom-shuffled, finite-ideal-gas, spherical-noninteracting, and random-walk-chain reference states, and we examined the six reference states against three RNA test sets including six subsets. Our extensive examinations show that, overall, for identifying native structures and ranking decoy structures, the finite-ideal-gas and random-walk-chain reference states are slightly superior to others, while for identifying near-native structures, there is only a slight difference between these reference states. Our further analyses show that the performance of a statistical potential is apparently dependent on the quality of the training set. Furthermore, we found that the performance of a statistical potential is closely related to the origin of test sets, and for the three realistic test subsets, the six statistical potentials have overall unsatisfactory performance. This work presents a comprehensive examination on the existing reference states and statistical potentials for RNA 3D structure evaluation.