Four Novel Mycoviruses from the Hypovirulent Botrytis cinerea SZ-2-3y Isolate from Paris polyphylla: Molecular Characterisation and Mitoviral Sequence Transboundary Entry into Plants

A hypovirulent SZ-2-3y strain isolated from diseased Paris polyphylla was identified as Botrytis cinerea. Interestingly, SZ-2-3y was coinfected with a mitovirus, two botouliviruses, and a 3074 nt fusarivirus, designated Botrytis cinerea fusarivirus 8 (BcFV8); it shares an 87.2% sequence identity with the previously identified Botrytis cinerea fusarivirus 6 (BcFV6). The full-length 2945 nt genome sequence of the mitovirus, termed Botrytis cinerea mitovirus 10 (BcMV10), shares a 54% sequence identity with Fusarium boothii mitovirus 1 (FbMV1), and clusters with fungus mitoviruses, plant mitoviruses and plant mitochondria; hence BcMV10 is a new Mitoviridae member. The full-length 2759 nt and 2812 nt genome sequences of the other two botouliviruses, named Botrytis cinerea botoulivirus 18 and 19 (BcBoV18 and 19), share a 40% amino acid sequence identity with RNA-dependent RNA polymerase protein (RdRp), and these are new members of the Botoulivirus genus of Botourmiaviridae. Horizontal transmission analysis showed that BcBoV18, BcBoV19 and BcFV8 are not related to hypovirulence, suggesting that BcMV10 may induce hypovirulence. Intriguingly, a partial BcMV10 sequence was detected in cucumber plants inoculated with SZ-2-3y mycelium or pXT1/BcMV10 agrobacterium. In conclusion, we identified a hypovirulent SZ-2-3y fungal strain from P. polyphylla, coinfected with four novel mycoviruses that could serve as potential biocontrol agents. Our findings provide evidence of cross-kingdom mycoviral sequence transmission.

Venezuelan Equine Encephalitis Virus V3526 Vaccine RNA-Dependent RNA Polymerase Mutants Increase Vaccine Safety Through Restricted Tissue Tropism in a Mouse Model

Background: Venezuelan equine encephalitis virus (VEEV) is an arbovirus endemic to the Americas, for which no vaccines or antiviral agents have been approved. TC-83 and V3526 are the best-characterized vaccine candidates for VEEV. Both are live-attenuated vaccines and have been associated with safety concerns, although fewer concerns exist for V3526. A previous attempt to improve the TC-83 vaccine focused on further attenuating the vaccine by adding mutations that alter the error-incorporation rate of the RNA-dependent RNA polymerase (RdRp). Methods: The research herein examined the effects of these RdRp mutations in V3526 by cloning the 3X and 4X strains, assessing vaccine efficacy against challenge in adult female CD-1 mice, examining neutralizing-antibody titers, investigating vaccine tissue tropism, and testing the stability of the mutant strains. Results: The V3526 RdRp mutants exhibited less tissue tropism in the spleen and kidney than the wild-type V3526, while maintaining vaccine efficacy. Illumina sequencing indicated that the RdRp mutations reverted to wild-type V3526 after five passages in murine pup brains. Conclusions: The observed genotypic reversion is likely to be of limited concern, because wild-type V3526 remains an effective vaccine capable of providing protection. Our results indicate that the V3526 RdRp mutants may be a safer vaccine design than the original V3526.

Virtual Combinatorial Library Screening of Quinadoline B Derivatives against SARS-CoV-2 RNA-Dependent RNA Polymerase

The unprecedented global health threat of SARS-CoV-2 has sparked a continued interest in discovering novel anti-COVID-19 agents. To this end, we present here a computer-based protocol for identifying potential compounds targeting RNA-dependent RNA polymerase (RdRp). Starting from our previous study wherein, using a virtual screening campaign, we identified a fumiquinazolinone alkaloid quinadoline B (Q3), an antiviral fungal metabolite with significant activity against SARS-CoV-2 RdRp, we applied in silico combinatorial methodologies for generating and screening a library of anti-SARS-CoV-2 candidates with strong in silico affinity for RdRp. For this study, the quinadoline pharmacophore was subjected to structural iteration, obtaining a Q3-focused library of over 900,000 unique structures. This chemical library was explored to identify binders of RdRp with greater affinity with respect to the starting compound Q3. Coupling this approach with the evaluation of physchem profile, we found 26 compounds with significant affinities for the RdRp binding site. Moreover, top-ranked compounds were submitted to molecular dynamics to evaluate the stability of the systems during a selected time, and to deeply investigate the binding mode of the most promising derivatives. Among the generated structures, five compounds, obtained by inserting nucleotide-like scaffolds (1, 2, and 5), heterocyclic thiazolyl benzamide moiety (compound 3), and a peptide residue (compound 4), exhibited enhanced binding affinity for SARS-CoV-2 RdRp, deserving further investigation as possible antiviral agents. Remarkably, the presented in silico procedure provides a useful computational procedure for hit-to-lead optimization, having implications in anti-SARS-CoV-2 drug discovery and in general in the drug optimization process.

Putative host-derived insertions in the genome of circulating SARS-CoV-2 variants

Insertions in the SARS-CoV-2 genome have the potential to drive viral evolution, but the source of the insertions is often unknown. Recent proposals have suggested that human RNAs could be a source of some insertions, but the small size of many insertions makes this difficult to confirm. Through an analysis of available direct RNA sequencing data from SARS-CoV-2 infected cells, we show that viral-host chimeric RNAs are formed through what are likely stochastic RNA-dependent RNA polymerase template switching events. Through an analysis of the publicly available GISAID SARS-CoV-2 genome collection, we then identified two genomic insertions in circulating SARS-CoV-2 variants that are identical to regions of the human 18S and 28S rRNAs. These results provide direct evidence of the formation of viral-host chimeric sequences and the integration of host genetic material into the SARS-CoV-2 genome, highlighting the potential importance of host-derived insertions in viral evolution.

Unveiling of Pyrimidindinones as Potential Anti-Norovirus Agents—A Pharmacoinformatic-Based Approach

The RNA-dependent RNA polymerase (RdRp) receptor is an attractive target for treating human norovirus (HNV). A computer-aided approach like e-pharmacophore, molecular docking, and single point energy calculations were performed on the compounds retrieved from the Development Therapeutics Program (DTP) AIDS Antiviral Screen Database to identify the antiviral agent that could target the HNV RdRp receptor. Induced-fit docking (IFD) results showed that compounds ZINC1617939, ZINC1642549, ZINC6425208, ZINC5887658 and ZINC32068149 bind with the residues in the active site-B of HNV RdRp receptor via hydrogen bonds, salt bridge, and electrostatic interactions. During the molecular dynamic simulations, compounds ZINC6425208, ZINC5887658 and ZINC32068149 displayed an unbalanced backbone conformation with HNV RdRp protein, while ZINC1617939 and ZINC1642549 maintained stability with the protein backbone when interacting with the residues. Hence, the two new concluding compounds discovered by the computational approach can be used as a chemotype to design promising antiviral agents aimed at HNV RdRp.

Synthesis of Nucleoside-like Molecules from a Pyrolysis Product of Cellulose and Their Computational Prediction as Potential SARS-CoV-2 RNA-Dependent RNA Polymerase Inhibitors

(1R,5S)-1-Hydroxy-3,6-dioxa-bicyclo[3.2.1]octan-2-one, available by an efficient catalytic pyrolysis of cellulose, has been applied as a chiral building block in the synthesis of seven new nucleoside analogues, with structural modifications on the nucleobase moiety and on the carboxyl- derived unit. The inverted configuration by Mitsunobu reaction used in their synthesis was verified by 2D-NOESY correlations, supported by the optimized structure employing the DFT methods. An in silico screening of these compounds as inhibitors of SARS-CoV-2 RNA-dependent RNA polymerase has been carried out in comparison with both remdesivir, a mono-phosphoramidate prodrug recently approved for COVID-19 treatment, and its ribonucleoside metabolite GS-441524. Drug-likeness prediction and data by docking calculation indicated compound 6 [=(3S,5S)-methyl 5-(hydroxymethyl)-3-(6-(4-methylpiperazin-1-yl)-9H-purin-9-yl)tetrahydrofuran-3-carboxylate] as the best candidate. Furthermore, molecular dynamics simulation showed a stable interaction of structure 6 in RNA-dependent RNA polymerase (RdRp) complex and a lower average atomic fluctuation than GS-441524, suggesting a well accommodation in the RdRp binding pocket.

NeoRdRp: A comprehensive dataset for identifying RNA-dependent RNA polymerase of various RNA viruses from metatranscriptomic data

RNA viruses are distributed in various environments, and most RNA viruses have been recently identified by metatranscriptome sequencing. However, due to the high nucleotide diversity of RNA viruses, it is still challenging to identify their sequences. Therefore, this study generated a dataset of RNA-dependent RNA polymerase (RdRp) domains essential for all RNA viruses belonging to Orthornavirae. Also, the collected genes with RdRp domains from various RNA viruses were clustered by amino acid sequence similarity. For each cluster, a multiple sequence alignment was generated, and a hidden Markov model (HMM) profile was created if the number of sequences was greater than five. Using the 1,467 HMM profiles, we detected RdRp domains in the RefSeq RNA virus sequences, combined the hit sequences with the RdRp domains, and reconstructed the HMM profiles. As a result, 2,234 HMM profiles were generated from 12,316 RdRp domain sequences, and the dataset was named NeoRdRp. Additionally, using the UniProt dataset, we confirmed that almost all NeoRdRp HMM profiles could specifically detect RdRps in Orthornavirae. Furthermore, we compared the NeoRdRp dataset with two previously reported RNA virus detection methods to detect RNA virus sequences from metatranscriptome sequencing data. Our methods can identify most of the RNA viruses in the datasets; however, some RNA viruses were not detected, similar to the other two methods. The NeoRdRp can be improved by repeatedly adding new RdRp sequences and can be expected to be widely applied as a system for detecting various RNA viruses from metatranscriptome data.