Heterogeneity in viral populations increases the rate of deleterious mutation accumulation

A qPCR Assay for the Quantification of Selected Genotypic Variants of Spodoptera frugiperda Multiple Nucleopolyhedrovirus (Baculoviridae)

Alphabaculoviruses are lethal dsDNA viruses of Lepidoptera that have high genetic diversity and are transmitted in aggregates within proteinaceous occlusion bodies. This mode of transmission has implications for their efficacy as biological insecticides. A Nicaraguan isolate of Spodoptera frugiperda multiple nucleopolyhedrovirus (SfMNPV-NIC) comprising nine genotypic variants has been the subject of considerable study due to the influence of variant interactions on the insecticidal properties of mixed-variant occlusion bodies. As part of a systematic study on the replication and transmission of variant mixtures, a tool for the accurate quantification of a selection of genotypic variants was developed based on the quantitative PCR technique (qPCR). First, primer pairs were designed around a region of high variability in four variants named SfNic-A, SfNic-B, SfNic-C and SfNic-E to produce amplicons of 103-150 bp. Then, using cloned purified amplicons as standards, amplification was demonstrated over a dynamic range of 108-101 copies of each target. The assay was efficient (mean ± SD: 98.5 ± 0.8%), reproducible, as shown by low inter- and intra-assay coefficients of variation (<5%), and specific to the target variants (99.7-100% specificity across variants). The quantification method was validated on mixtures of genotype-specific amplicons and demonstrated accurate quantification. Finally, mixtures of the four variants were quantified based on mixtures of budded virions and mixtures of DNA extracted from occlusion-derived virions. In both cases, mixed-variant preparations compared favorably to total viral genome numbers by quantification of the polyhedrin (polh) gene that is present in all variants. This technique should prove invaluable in elucidating the influence of variant diversity on the transmission and insecticidal characteristics of this pathogen.

Incorporating Intracellular Processes in Virus Dynamics Models

In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.

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.

SARS-CoV-2 genomics and impact on clinical care for COVID-19

The emergence and worldwide spread of SARS-CoV-2 during the COVID-19 pandemic necessitated the adaptation and rapid deployment of viral WGS and analysis techniques that had been previously applied on a more limited basis to other viral pathogens, such as HIV and influenza viruses. The need for WGS was driven in part by the low mutation rate of SARS-CoV-2, which necessitated measuring variation along the entire genome sequence to effectively differentiate lineages and characterize viral evolution. Several WGS approaches designed to maximize throughput and accuracy were quickly adopted by surveillance labs around the world. These broad-based SARS-CoV-2 genomic sequencing efforts revealed ongoing evolution of the virus, highlighted by the successive emergence of new viral variants throughout the course of the pandemic. These genomic insights were instrumental in characterizing the effects of viral mutations on transmissibility, immune escape and viral tropism, which in turn helped guide public health policy, the use of monoclonal antibody therapeutics and vaccine development strategies. As the use of direct-acting antivirals for the treatment of COVID-19 became more widespread, the potential for emergence of antiviral resistance has driven ongoing efforts to delineate resistance mutations and to monitor global sequence databases for their emergence. Given the critical role of viral genomics in the international effort to combat the COVID-19 pandemic, coordinated efforts should be made to expand global genomic surveillance capacity and infrastructure towards the anticipation and prevention of future pandemics.