A map of the SARS-CoV-2 RNA structurome.

SARS-CoV-2 has exploded throughout the human population. To facilitate efforts to gain insights into SARS-CoV-2 biology and to target the virus therapeutically, it is essential to have a roadmap of likely functional regions embedded in its RNA genome. In this report, we used a bioinformatics approach, ScanFold, to deduce the local RNA structural landscape of the SARS-CoV-2 genome with the highest likelihood of being functional. We recapitulate previously-known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a large reservoir of potential drug targets for RNA-binding small molecules. Results are enhanced via the re-analyses of publicly-available genome-wide biochemical structure probing datasets that are broadly in agreement with our models. Additionally, ScanFold was updated to incorporate experimental data as constraints in the analysis to facilitate comparisons between ScanFold and other RNA modelling approaches. Ultimately, ScanFold was able to identify eight highly structured/conserved motifs in SARS-CoV-2 that agree with experimental data, without explicitly using these data. All results are made available via a public database (the RNAStructuromeDB: https://structurome.bb.iastate.edu/sars-cov-2) and model comparisons are readily viewable at https://structurome.bb.iastate.edu/sars-cov-2-global-model-comparisons.

In vivo secondary structural analysis of Influenza A virus genomic RNA.

Influenza A virus (IAV) is a respiratory virus that causes epidemics and pandemics. Knowledge of IAV RNA secondary structure in vivo is crucial for a better understanding of virus biology. Moreover, it is a fundament for the development of new RNA-targeting antivirals. Chemical RNA mapping using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) coupled with Mutational Profiling (MaP) allows for the thorough examination of secondary structures in low-abundance RNAs in their biological context. So far, the method has been used for analyzing the RNA secondary structures of several viruses including SARS-CoV-2 in virio and in cellulo. Here, we used SHAPE-MaP and dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) for genome-wide secondary structure analysis of viral RNA (vRNA) of the pandemic influenza A/California/04/2009 (H1N1) strain in both in virio and in cellulo environments. Experimental data allowed the prediction of the secondary structures of all eight vRNA segments in virio and, for the first time, the structures of vRNA5, 7, and 8 in cellulo. We conducted a comprehensive structural analysis of the proposed vRNA structures to reveal the motifs predicted with the highest accuracy. We also performed a base-pairs conservation analysis of the predicted vRNA structures and revealed many highly conserved vRNA motifs among the IAVs. The structural motifs presented herein are potential candidates for new IAV antiviral strategies.

ScanFold 2.0: a rapid approach for identifying potential structured RNA targets in genomes and transcriptomes.

A major limiting factor in target discovery for both basic research and therapeutic intervention is the identification of structural and/or functional RNA elements in genomes and transcriptomes. This was the impetus for the original ScanFold algorithm, which provides maps of local RNA structural stability, evidence of sequence-ordered (potentially evolved) structure, and unique model structures comprised of recurring base pairs with the greatest structural bias. A key step in quantifying this propensity for ordered structure is the prediction of secondary structural stability for randomized sequences which, in the original implementation of ScanFold, is explicitly evaluated. This slow process has limited the rapid identification of ordered structures in large genomes/transcriptomes, which we seek to overcome in this current work introducing ScanFold 2.0. In this revised version of ScanFold, we no longer explicitly evaluate randomized sequence folding energy, but rather estimate it using a machine learning approach. For high randomization numbers, this can increase prediction speeds over 100-fold compared to ScanFold 1.0, allowing for the analysis of large sequences, as well as the use of additional folding algorithms that may be computationally expensive. In the testing of ScanFold 2.0, we re-evaluate the Zika, HIV, and SARS-CoV-2 genomes and compare both the consistency of results and the time of each run to ScanFold 1.0. We also re-evaluate the SARS-CoV-2 genome to assess the quality of ScanFold 2.0 predictions vs several biochemical structure probing datasets and compare the results to those of the original ScanFold program.

Secondary Structure of Influenza A Virus Genomic Segment 8 RNA Folded in a Cellular Environment.

Influenza A virus (IAV) is a member of the single-stranded RNA (ssRNA) family of viruses. The most recent global pandemic caused by the SARS-CoV-2 virus has shown the major threat that RNA viruses can pose to humanity. In comparison, influenza has an even higher pandemic potential as a result of its high rate of mutations within its relatively short (<13 kbp) genome, as well as its capability to undergo genetic reassortment. In light of this threat, and the fact that RNA structure is connected to a broad range of known biological functions, deeper investigation of viral RNA (vRNA) structures is of high interest. Here, for the first time, we propose a secondary structure for segment 8 vRNA (vRNA8) of A/California/04/2009 (H1N1) formed in the presence of cellular and viral components. This structure shows similarities with prior in vitro experiments. Additionally, we determined the location of several well-defined, conserved structural motifs of vRNA8 within IAV strains with possible functionality. These RNA motifs appear to fold independently of regional nucleoprotein (NP)-binding affinity, but a low or uneven distribution of NP in each motif region is noted. This research also highlights several accessible sites for oligonucleotide tools and small molecules in vRNA8 in a cellular environment that might be a target for influenza A virus inhibition on the RNA level.

Secondary Structure of Subgenomic RNA M of SARS-CoV-2.

SARS-CoV-2 belongs to the Coronavirinae family. Like other coronaviruses, SARS-CoV-2 is enveloped and possesses a positive-sense, single-stranded RNA genome of ~30 kb. Genomic RNA is used as the template for replication and transcription. During these processes, positive-sense genomic RNA (gRNA) and subgenomic RNAs (sgRNAs) are created. Several studies presented the importance of the genomic RNA secondary structure in SARS-CoV-2 replication. However, the structure of sgRNAs has remained largely unsolved so far. In this study, we probed the sgRNA M model of SARS-CoV-2 in vitro. The presented model molecule includes 5'UTR and a coding sequence of gene M. This is the first experimentally informed secondary structure model of sgRNA M, which presents features likely to be important in sgRNA M function. The knowledge of sgRNA M structure provides insights to better understand virus biology and could be used for designing new therapeutics.

Prediction and analysis of functional RNA structures within the integrative genomics viewer.

In recent years, interest in RNA secondary structure has exploded due to its implications in almost all biological functions and its newly appreciated capacity as a therapeutic agent/target. This surge of interest has driven the development and adaptation of many computational and biochemical methods to discover novel, functional structures across the genome/transcriptome. To further enhance efforts to study RNA secondary structure, we have integrated the functional secondary structure prediction tool ScanFold, into IGV. This allows users to directly perform structure predictions and visualize results-in conjunction with probing data and other annotations-in one program. We illustrate the utility of this new tool by mapping the secondary structural landscape of the human MYC precursor mRNA. We leverage the power of vast 'omics' resources by comparing individually predicted structures with published data including: biochemical structure probing, RNA binding proteins, microRNA binding sites, RNA modifications, single nucleotide polymorphisms, and others that allow functional inferences to be made and aid in the discovery of potential drug targets. This new tool offers the RNA community an easy to use tool to find, analyze, and characterize RNA secondary structures in the context of all available data, in order to find those worthy of further analyses.

SARS-CoV-2 expresses a microRNA-like small RNA able to selectively repress host genes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), continues to be a pressing health concern. In this study, we investigated the impact of SARS-CoV-2 infection on host microRNA (miRNA) populations in three human lung-derived cell lines, as well as in nasopharyngeal swabs from SARS-CoV-2-infected individuals. We did not detect any major and consistent differences in host miRNA levels after SARS-CoV-2 infection. However, we unexpectedly discovered a viral miRNA-like small RNA, named CoV2-miR-O7a (for SARS-CoV-2 miRNA-like ORF7a-derived small RNA). Its abundance ranges from low to moderate as compared to host miRNAs and it associates with Argonaute proteins-core components of the RNA interference pathway. We identify putative targets for CoV2-miR-O7a, including Basic Leucine Zipper ATF-Like Transcription Factor 2 (BATF2), which participates in interferon signaling. We demonstrate that CoV2-miR-O7a production relies on cellular machinery, yet is independent of Drosha protein, and is enhanced by the presence of a strong and evolutionarily conserved hairpin formed within the ORF7a sequence.

Targeting the SARS-CoV-2 RNA Genome with Small Molecule Binders and Ribonuclease Targeting Chimera (RIBOTAC) Degraders.

COVID-19 is a global pandemic, thus requiring multiple strategies to develop modalities against it. Herein, we designed multiple bioactive small molecules that target a functional structure within the SARS-CoV-2's RNA genome, the causative agent of COVID-19. An analysis to characterize the structure of the RNA genome provided a revised model of the SARS-CoV-2 frameshifting element, in particular its attenuator hairpin. By studying an RNA-focused small molecule collection, we identified a drug-like small molecule (C5) that avidly binds to the revised attenuator hairpin structure with a K d of 11 nM. The compound stabilizes the hairpin's folded state and impairs frameshifting in cells. The ligand was further elaborated into a ribonuclease targeting chimera (RIBOTAC) to recruit a cellular ribonuclease to destroy the viral genome (C5-RIBOTAC) and into a covalent molecule (C5-Chem-CLIP) that validated direct target engagement and demonstrated its specificity for the viral RNA, as compared to highly expressed host mRNAs. The RIBOTAC lead optimization strategy improved the bioactivity of the compound at least 10-fold. Collectively, these studies demonstrate that the SARS-CoV-2 RNA genome should be considered druggable.