Innate Intracellular Antiviral Responses Restrict the Amplification of Defective Virus Genomes of Parainfluenza Virus 5

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.

Accumulation Dynamics of Defective Genomes during Experimental Evolution of Two Betacoronaviruses

Virus-encoded replicases often generate aberrant RNA genomes, known as defective viral genomes (DVGs). When co-infected with a helper virus providing necessary proteins, DVGs can multiply and spread. While DVGs depend on the helper virus for propagation, they can in some cases disrupt infectious virus replication, impact immune responses, and affect viral persistence or evolution. Understanding the dynamics of DVGs alongside standard viral genomes during infection remains unclear. To address this, we conducted a long-term experimental evolution of two betacoronaviruses, the human coronavirus OC43 (HCoV-OC43) and the murine hepatitis virus (MHV), in cell culture at both high and low multiplicities of infection (MOI). We then performed RNA-seq at regular time intervals, reconstructed DVGs, and analyzed their accumulation dynamics. Our findings indicate that DVGs evolved to exhibit greater diversity and abundance, with deletions and insertions being the most common types. Notably, some high MOI deletions showed very limited temporary existence, while others became prevalent over time. We observed differences in DVG abundance between high and low MOI conditions in HCoV-OC43 samples. The size distribution of HCoV-OC43 genomes with deletions differed between high and low MOI passages. In low MOI lineages, short and long DVGs were the most common, with an additional cluster in high MOI lineages which became more prevalent along evolutionary time. MHV also showed variations in DVG size distribution at different MOI conditions, though they were less pronounced compared to HCoV-OC43, suggesting a more random distribution of DVG sizes. We identified hotspot regions for deletions that evolved at a high MOI, primarily within cistrons encoding structural and accessory proteins. In conclusion, our study illustrates the widespread formation of DVGs during betacoronavirus evolution, influenced by MOI and cell- and virus-specific factors.

Generation of Defective Interfering Particles of Morbilliviruses Using Reverse Genetics

RNA viruses generate defective genomes naturally during virus replication. Defective genomes that interfere with the infection dynamics either through resource competition or by interferon stimulation are known as defective interfering (DI) genomes. DI genomes can be successfully packaged into virus-like-particles referred to as defective interfering particles (DIPs). Such DIPs can sustainably coexist with the full-length virus particles and have been shown to negatively impact virus replication in vitro and in vivo. Here, we describe a method to generate a clonal DI genome population by reverse genetics. This method is applicable to other RNA viruses and will enable assessment of DIPs for their antiviral properties.

Molecular biology of canine parainfluenza virus V protein and its potential applications in tumor immunotherapy

Canine parainfluenza virus (CPIV) is a zoonotic virus that is widely distributed and is the main pathogen causing canine infectious respiratory disease (CIRD), also known as "kennel cough," in dogs. The CPIV-V protein is the only nonstructural protein of the virus and plays an important role in multiple stages of the virus life cycle by inhibiting apoptosis, altering the host cell cycle and interfering with the interferon response. In addition, studies have shown that the V protein has potential applications in the field of immunotherapy in oncolytic virus therapy or self-amplifying RNA vaccines. In this review, the biosynthesis, structural characteristics and functions of the CPIV-V protein are reviewed with an emphasis on how it facilitates viral immune escape and its potential applications in the field of immunotherapy. Therefore, this review provides a scientific basis for research into the CPIV-V protein and its potential applications.

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

Negative-sense RNA virus populations are composed of diverse viral components that interact to form a community and shape the outcome of virus infections. At the genomic level, RNA virus populations consist not only of a homogeneous population of standard viral genomes but also of an extremely large number of genome variants, termed viral quasispecies, and nonstandard viral genomes, which include copy-back viral genomes, deletion viral genomes, mini viral RNAs, and hypermutated RNAs. At the particle level, RNA virus populations are composed of pleomorphic particles, particles missing or having additional genomes, and single particles or particle aggregates. As we continue discovering more about the components of negative-sense RNA virus populations and their crucial functions during virus infection, it will become more important to study RNA virus populations as a whole rather than their individual parts. In this review, we will discuss what is known about the components of negative-sense RNA virus communities, speculate how the components of the virus community interact, and summarize what vaccines and antiviral therapies are being currently developed to target or harness these components.

DVGfinder: A Metasearch Tool for Identifying Defective Viral Genomes in RNA-Seq Data

The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential therapeutic and biotechnological applications. Identifying such DVGs in high-throughput sequencing (HTS) data has become an interesting computational problem. Several algorithms have been proposed to accomplish this goal, though all incur false positives, a problem of practical interest if such DVGs have to be synthetized and tested in the laboratory. We present a metasearch tool, DVGfinder, that wraps the two most commonly used DVG search algorithms in a single workflow for the identification of the DVGs in HTS data. DVGfinder processes the results of ViReMa-a and DI-tector and uses a gradient boosting classifier machine learning algorithm to reduce the number of false-positive events. The program also generates output files in user-friendly HTML format, which can help users to explore the DVGs identified in the sample. We evaluated the performance of DVGfinder compared to the two search algorithms used separately and found that it slightly improves sensitivities for low-coverage synthetic HTS data and DI-tector precision for high-coverage samples. The metasearch program also showed higher sensitivity on a real sample for which a set of copy-backs were previously validated.