A Virus Is a Community: Diversity within Negative-Sense RNA Virus Populations

Selection of nonstandard viral genomes during the evolution of RNA viruses: A virus survival strategy or a pesky inconvenience?

RNA viruses are some of the most successful biological entities due their ability to adapt and evolve. Despite their small genome and parasitic nature, RNA viruses have evolved many mechanisms to ensure their survival and maintenance in the host population. We propose that one of these mechanisms of survival is the generation of nonstandard viral genomes (nsVGs) that accumulate during viral replication. NsVGs are often considered to be accidental defective byproducts of the RNA virus replication, but their ubiquity and the plethora of roles they have during infection indicate that they are an integral part of the virus life cycle. Here we review the different types of nsVGs and discuss how their multiple roles during infection could be beneficial for RNA viruses to be maintained in nature. By shifting our perspectives on what makes a virus successful, we posit that nsVG generation is a conserved phenomenon that arose during RNA virus evolution as an essential component of a healthy virus community.

Bioinformatic analysis of defective viral genomes in SARS-CoV-2 and its impact on population infection characteristics

DVGs (Defective Viral Genomes) are prevalent in RNA virus infections. In this investigation, we conducted an analysis of high-throughput sequencing data and observed widespread presence of DVGs in SARS-CoV-2. Comparative analysis between SARS-CoV-2 and diverse DNA viruses revealed heightened susceptibility to damage and increased sequencing sample heterogeneity within the SARS-CoV-2 genome. Whole-genome sequencing depth variability analysis exhibited a higher coefficient of variation for SARS-CoV-2, while DVG analysis indicated a significant proportion of recombination sites, signifying notable genome heterogeneity and suggesting that a large proportion of assembled virus particles contain incomplete RNA sequences. Moreover, our investigation explored the sequencing depth and DVG content differences among various strains. Our findings revealed that as the virus evolves, there is a notable increase in the proportion of intact genomes within virus particles, as evidenced by third-generation sequencing data. Specifically, the proportion of intact genome in the Omicron strain surpassed that of the Delta and Alpha strains. This observation effectively elucidates the heightened infectiousness of the Omicron strain compared to the Delta and Alpha strains. We also postulate that this improvement in completeness stems from enhanced virus assembly capacity, as the Omicron strain can promptly facilitate the binding of RNA and capsid protein, thereby reducing the exposure time of vulnerable virus RNA in the host environment and significantly mitigating its degradation. Finally, employing mathematical modeling, we simulated the impact of DVG effects under varying environmental factors on infection characteristics and population evolution. Our findings provide an explanation for the close association between symptom severity and the extent of virus invasion, as well as the substantial disparity in population infection characteristics caused by the same strain under distinct environmental conditions. This study presents a novel approach for future virus research and vaccine development.

VODKA2: a fast and accurate method to detect non-standard viral genomes from large RNA-seq data sets

During viral replication, viruses carrying an RNA genome produce non-standard viral genomes (nsVGs), including copy-back viral genomes (cbVGs) and deletion viral genomes (delVGs), that play a crucial role in regulating viral replication and pathogenesis. Because of their critical roles in determining the outcome of RNA virus infections, the study of nsVGs has flourished in recent years, exposing a need for bioinformatic tools that can accurately identify them within next-generation sequencing data obtained from infected samples. Here, we present our data analysis pipeline, Viral Opensource DVG Key Algorithm 2 (VODKA2), that is optimized to run on a parallel computing environment for fast and accurate detection of nsVGs from large data sets.

Copy-back viral genomes induce a cellular stress response that interferes with viral protein expression without affecting antiviral immunity

Antiviral responses are often accompanied by translation inhibition and formation of stress granules (SGs) in infected cells. However, the triggers for these processes and their role during infection remain subjects of active investigation. Copy-back viral genomes (cbVGs) are the primary inducers of the mitochondrial antiviral signaling (MAVS) pathway and antiviral immunity during Sendai virus (SeV) and respiratory syncytial virus (RSV) infections. The relationship between cbVGs and cellular stress during viral infections is unknown. Here, we show that SGs form during infections containing high levels of cbVGs, and not during infections with low levels of cbVGs. Moreover, using RNA fluorescent in situ hybridization to differentiate accumulation of standard viral genomes from cbVGs at a single-cell level during infection, we show that SGs form exclusively in cells that accumulate high levels of cbVGs. Protein kinase R (PKR) activation is increased during high cbVG infections and, as expected, is necessary for virus-induced SGs. However, SGs form independent of MAVS signaling, demonstrating that cbVGs induce antiviral immunity and SG formation through 2 independent mechanisms. Furthermore, we show that translation inhibition and SG formation do not affect the overall expression of interferon and interferon stimulated genes during infection, making the stress response dispensable for global antiviral immunity. Using live-cell imaging, we show that SG formation is highly dynamic and correlates with a drastic reduction of viral protein expression even in cells infected for several days. Through analysis of active protein translation at a single-cell level, we show that infected cells that form SGs show inhibition of protein translation. Together, our data reveal a new cbVG-driven mechanism of viral interference where cbVGs induce PKR-mediated translation inhibition and SG formation, leading to a reduction in viral protein expression without altering overall antiviral immunity.

S RNA Intergenic Deletions Drive Viral Interference during Arenavirus Infections

Arenaviruses, a family of negative-sense RNA viruses spread by rodents, are a leading cause of severe hemorrhagic fever in humans. Due to a paucity of antivirals and vaccines for arenaviruses, there is a need to identify new mechanisms for interfering with arenavirus replication. In several negative-sense RNA viruses, natural viral interference results from the production of non-standard viral genomes (nsVGs) that activate the innate immune system and/or compete for essential viral products. Although it is well established that arenaviruses produce strong interfering activities, it is unknown if they produce interfering nsVGs. Here we show that arenaviruses produce deletions within the intergenic region of their Small (S) RNA genome, which prevents the production of viral mRNA and protein. These deletions are more abundant when arenaviruses are grown in high-interfering conditions and are associated with inhibited viral replication. Overall, we found that arenaviruses produce internal deletions within the S RNA intergenic region that are produced by arenaviruses and can block viral replication. These natural arenavirus interfering molecules provide a new target for the generation of antivirals as well as an alternative strategy for producing attenuated arenaviruses for vaccines.

Copy-back viral genomes induce a cellular stress response that interferes with viral protein expression without affecting antiviral immunity

Antiviral responses are often accompanied by translation inhibition and formation of stress granules (SG) in infected cells. However, the triggers for these processes and their role during infection remain subjects of active investigation. Copy-back viral genomes (cbVGs) are the primary inducers of the Mitochondrial Antiviral Signaling (MAVS) pathway and antiviral immunity during Sendai Virus (SeV) and Respiratory Syncytial virus (RSV) infections. The relationship between cbVGs and cellular stress during viral infections is unknown. Here we show that SG form during infections containing high levels of cbVGs, and not during infections with low levels of cbVGs. Moreover, using RNA fluorescent in situ hybridization to differentiate accumulation of standard viral genomes from cbVGs at a single-cell level during infection, we show that SG form exclusively in cells that accumulate high levels of cbVGs. PKR activation is increased during high cbVG infections and, as expected, PKR is necessary to induce virus-induced SG. However, SG form independent of MAVS signaling, demonstrating that cbVGs induce antiviral immunity and SG formation through two independent mechanisms. Furthermore, we show that translation inhibition and SG formation do not affect the overall expression of interferon and interferon stimulated genes during infection, making the stress response dispensable for antiviral immunity. Using live-cell imaging, we show that SG formation is highly dynamic and correlates with a drastic reduction of viral protein expression even in cells infected for several days. Through analysis of active protein translation at a single cell level, we show that infected cells that form SG show inhibition of protein translation. Together, our data reveal a new cbVG-driven mechanism of viral interference where cbVGs induce PKR-mediated translation inhibition and SG formation leading to a reduction in viral protein expression without altering overall antiviral immunity.

VODKA2: A fast and accurate method to detect non-standard viral genomes from large RNA-seq datasets

During viral replication, viruses carrying an RNA genome produce non-standard viral genomes (nsVGs), including copy-back viral genomes (cbVGs) and deletion viral genomes (delVGs), that play a crucial role in regulating viral replication and pathogenesis. Because of their critical roles in determining the outcome of RNA virus infections, the study of nsVGs has flourished in recent years exposing a need for bioinformatic tools that can accurately identify them within Next-Generation Sequencing data obtained from infected samples. Here, we present our data analysis pipeline, Viral Opensource DVG Key Algorithm2 (VODKA2), that is optimized to run on a High Performance Computing (HPC) environment for fast and accurate detection of nsVGs from large data sets.

Collective fusion activity determines neurotropism of an en bloc transmitted enveloped virus

Measles virus (MeV), which is usually non-neurotropic, sometimes persists in the brain and causes subacute sclerosing panencephalitis (SSPE) several years after acute infection, serving as a model for persistent viral infections. The persisting MeVs have hyperfusogenic mutant fusion (F) proteins that likely enable cell-cell fusion at synapses and "en bloc transmission" between neurons. We here show that during persistence, F protein fusogenicity is generally enhanced by cumulative mutations, yet mutations paradoxically reducing the fusogenicity may be selected alongside the wild-type (non-neurotropic) MeV genome. A mutant F protein having SSPE-derived substitutions exhibits lower fusogenicity than the hyperfusogenic F protein containing some of those substitutions, but by the wild-type F protein coexpression, the fusogenicity of the former F protein is enhanced, while that of the latter is nearly abolished. These findings advance the understanding of the long-term process of MeV neuropathogenicity and provide critical insight into the genotype-phenotype relationships of en bloc transmitted viruses.