High virulence does not necessarily impede viral adaptation to a new host: a case study using a plant RNA virus

Analysis of SARS-CoV-2 genome evolutionary patterns

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

Viral cross-class transmission results in disease of a phytopathogenic fungus

Interspecies transmission of viruses is a well-known phenomenon in animals and plants whether via contacts or vectors. In fungi, interspecies transmission between distantly related fungi is often suspected but rarely experimentally documented and may have practical implications. A newly described double-strand RNA (dsRNA) virus found asymptomatic in the phytopathogenic fungus Leptosphaeria biglobosa of cruciferous crops was successfully transmitted to an evolutionarily distant, broad-host range pathogen Botrytis cinerea. Leptosphaeria biglobosa botybirnavirus 1 (LbBV1) was characterized in L. biglobosa strain GZJS-19. Its infection in L. biglobosa was asymptomatic, as no significant differences in radial mycelial growth and pathogenicity were observed between LbBV1-infected and LbBV1-free strains. However, cross-species transmission of LbBV1 from L. biglobosa to infection in B. cinerea resulted in the hypovirulence of the recipient B. cinerea strain t-459-V. The cross-species transmission was succeeded only by inoculation of mixed spores of L. biglobosa and B. cinerea on PDA or on stems of oilseed rape with the efficiency of 4.6% and 18.8%, respectively. To investigate viral cross-species transmission between L. biglobosa and B. cinerea in nature, RNA sequencing was carried out on L. biglobosa and B. cinerea isolates obtained from Brassica samples co-infected by these two pathogens and showed that at least two mycoviruses were detected in both fungal groups. These results indicate that cross-species transmission of mycoviruses may occur frequently in nature and result in the phenotypical changes of newly invaded phytopathogenic fungi. This study also provides new insights for using asymptomatic mycoviruses as biocontrol agent.

The phylogenomics of evolving virus virulence

How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study.

On the stability of sequences inserted into viral genomes

Viruses are widely used as vectors for heterologous gene expression in cultured cells or natural hosts, and therefore a large number of viruses with exogenous sequences inserted into their genomes have been engineered. Many of these engineered viruses are viable and express heterologous proteins at high levels, but the inserted sequences often prove to be unstable over time and are rapidly lost, limiting heterologous protein expression. Although virologists are aware that inserted sequences can be unstable, processes leading to insert instability are rarely considered from an evolutionary perspective. Here, we review experimental work on the stability of inserted sequences over a broad range of viruses, and we present some theoretical considerations concerning insert stability. Different virus genome organizations strongly impact insert stability, and factors such as the position of insertion can have a strong effect. In addition, we argue that insert stability not only depends on the characteristics of a particular genome, but that it will also depend on the host environment and the demography of a virus population. The interplay between all factors affecting stability is complex, which makes it challenging to develop a general model to predict the stability of genomic insertions. We highlight key questions and future directions, finding that insert stability is a surprisingly complex problem and that there is need for mechanism-based, predictive models. Combining theoretical models with experimental tests for stability under varying conditions can lead to improved engineering of viral modified genomes, which is a valuable tool for understanding genome evolution as well as for biotechnological applications, such as gene therapy.