Influenza B virus has global ordered RNA structure in (+) and (-) strands but relatively less stable predicted RNA folding free energy than allowed by the encoded protein sequence

In silico analysis of local RNA secondary structure in influenza virus A, B and C finds evidence of widespread ordered stability but little evidence of significant covariation

Influenza virus is a persistent threat to human health; indeed, the deadliest modern pandemic was in 1918 when an H1N1 virus killed an estimated 50 million people globally. The intent of this work is to better understand influenza from an RNA-centric perspective to provide local, structural motifs with likely significance to the influenza infectious cycle for therapeutic targeting. To accomplish this, we analyzed over four hundred thousand RNA sequences spanning three major clades: influenza A, B and C. We scanned influenza segments for local secondary structure, identified/modeled motifs of likely functionality, and coupled the results to an analysis of evolutionary conservation. We discovered 185 significant regions of predicted ordered stability, yet evidence of sequence covariation was limited to 7 motifs, where 3-found in influenza C-had higher than expected amounts of sequence covariation.

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.

An in silico map of the SARS-CoV-2 RNA Structurome

SARS-CoV-2 is a positive-sense single-stranded RNA virus that has exploded throughout the global human population. This pandemic coronavirus strain has taken scientists and public health researchers by surprise and knowledge of its basic biology (e.g. structure/function relationships in its genomic, messenger and template RNAs) and modes for therapeutic intervention lag behind that of other human pathogens. In this report we used a recently-developed bioinformatics approach, ScanFold, to deduce the RNA structural landscape of the SARS-CoV-2 transcriptome. We recapitulate known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that the SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a huge reservoir of potential drug targets for RNA-binding small molecules. Our results also predict regions that are accessible for intermolecular interactions, which can aid in the design of antisense therapeutics. All results are made available via a public database (the RNAStructuromeDB) where they may hopefully drive drug discovery efforts to inhibit SARS-CoV-2 pathogenesis.

Structural and Functional Motifs in Influenza Virus RNAs

Influenza A viruses (IAV) are responsible for recurrent influenza epidemics and occasional devastating pandemics in humans and animals. They belong to the Orthomyxoviridae family and their genome consists of eight (-) sense viral RNA (vRNA) segments of different lengths coding for at least 11 viral proteins. A heterotrimeric polymerase complex is bound to the promoter consisting of the 13 5′-terminal and 12 3′-terminal nucleotides of each vRNA, while internal parts of the vRNAs are associated with multiple copies of the viral nucleoprotein (NP), thus forming ribonucleoproteins (vRNP). Transcription and replication of vRNAs result in viral mRNAs (vmRNAs) and complementary RNAs (cRNAs), respectively. Complementary RNAs are the exact positive copies of vRNAs; they also form ribonucleoproteins (cRNPs) and are intermediate templates in the vRNA amplification process. On the contrary, vmRNAs have a 5′ cap snatched from cellular mRNAs and a 3′ polyA tail, both gained by the viral polymerase complex. Hence, unlike vRNAs and cRNAs, vmRNAs do not have a terminal promoter able to recruit the viral polymerase. Furthermore, synthesis of at least two viral proteins requires vmRNA splicing. Except for extensive analysis of the viral promoter structure and function and a few, mostly bioinformatics, studies addressing the vRNA and vmRNA structure, structural studies of the influenza A vRNAs, cRNAs, and vmRNAs are still in their infancy. The recent crystal structures of the influenza polymerase heterotrimeric complex drastically improved our understanding of the replication and transcription processes. The vRNA structure has been mainly studied in vitro using RNA probing, but its structure has been very recently studied within native vRNPs using crosslinking and RNA probing coupled to next generation RNA sequencing. Concerning vmRNAs, most studies focused on the segment M and NS splice sites and several structures initially predicted by bioinformatics analysis have now been validated experimentally and their role in the viral life cycle demonstrated. This review aims to compile the structural motifs found in the different RNA classes (vRNA, cRNA, and vmRNA) of influenza viruses and their function in the viral replication cycle.

Mycophenolic acid, an immunomodulator, has potent and broad-spectrum in vitro antiviral activity against pandemic, seasonal and avian influenza viruses affecting humans

Immunomodulators have been shown to improve the outcome of severe pneumonia. We have previously shown that mycophenolic acid (MPA), an immunomodulator, has antiviral activity against influenza A/WSN/1933(H1N1) using a high-throughput chemical screening assay. This study further investigated the antiviral activity and mechanism of action of MPA against contemporary clinical isolates of influenza A and B viruses. The 50 % cellular cytotoxicity (CC50) of MPA in Madin Darby canine kidney cell line was over 50 µM. MPA prevented influenza virus-induced cell death in the cell-protection assay, with significantly lower IC50 for influenza B virus B/411 than that of influenza A(H1N1)pdm09 virus H1/415 (0.208 vs 1.510 µM, P=0.0001). For H1/415, MPA interfered with the early stage of viral replication before protein synthesis. For B/411, MPA may also act at a later stage since MPA was active against B/411 even when added 12 h post-infection. Virus-yield reduction assay showed that the replication of B/411 was completely inhibited by MPA at concentrations ≥0.78 µM, while there was a dose-dependent reduction of viral titer for H1/415. The antiviral effect of MPA was completely reverted by guanosine supplementation. Plaque reduction assay showed that MPA had antiviral activity against eight different clinical isolates of A(H1N1), A(H3N2), A(H7N9) and influenza B viruses (IC50 <1 µM). In summary, MPA has broad-spectrum antiviral activity against human and avian-origin influenza viruses, in addition to its immunomodulatory activity. Together with a high chemotherapeutic index, the use of MPA as an antiviral agent should be further investigated in vivo.

In silico discovery and modeling of non-coding RNA structure in viruses

This review covers several computational methods for discovering structured non-coding RNAs in viruses and modeling their putative secondary structures. Here we will use examples from two target viruses to highlight these approaches: influenza A virus-a relatively small, segmented RNA virus; and Epstein-Barr virus-a relatively large DNA virus with a complex transcriptome. Each system has unique challenges to overcome and unique characteristics to exploit. From these particular cases, generically useful approaches can be derived for the study of additional viral targets.