Population dynamics of defective viral genomes of tomato black ring virus during host-to-host transmission.

Defective viral genomes (DVGs) emerge during error-prone replication of viral genomes and contain deletions, insertions, genomic rearrangements, and hypermutations. These large-effect mutations result in the inability of DVGs to complete an infectious cycle in the absence of a helper wild-type virus. It has been shown that in vitro DVGs usually accumulate in viral populations when a virus is serially passaged in the same host at a high multiplicity of infection. To investigate the impact of host-to-host transmission on DVG formation and population dynamics in vivo, we conducted evolution experiments with tomato black ring virus (TBRV). TBRV was sequentially passaged through a combination of four distinct host species: quinoa, tobacco, lettuce, and spinach. The host was changed every fifth passage. The diversity and population dynamics of DVGs were analyzed based on the RNA-Seq data obtained through sequencing of viral RNA after 20 passages. Our findings indicate the possibility of TBRV DVGs generation when the virus was passaged through different host species. The level of DVG abundance varied across host plant combinations, with a weak indication that the host species past sequence may play a role in DVGs generation. Most abundant DVGs in the TBRV evolved populations were derived from RNA1. Deletions were the most prevalent class of DVGs, followed by insertions. The deletion DVG subpopulation exhibited substantial diversity in species composition and the richness of the deletions species was correlated with their abundance. Longer DVGs characterized by small deletions were predominant, whereas those shorter than 1,000 nucleotides constituted less than 2%. IMPORTANCE: Defective viral genomes (DVGs) have been identified in vivo and in vitro for different virus species infecting humans, animals, and plants. The ability to form DVGs during the passaging of virus in one host has been demonstrated, i.e., for tomato black ring virus (TBRV). In our research, RNA-Seq data obtained after TBRV passaging through a combination of four distinct host species were analyzed. Our results indicate that the level of DVG abundance varied across host plant combinations. Deletions were the most prevalent class of DVGs, with the domination of longer species. Additionally, the conserved junction sites in the TBRV genome were identified, resulting in the generation of identical deletions in independently evolved viral lineages. In summary, our findings provide significant insights into the origin and structure of DVGs of plant viruses. The obtained results will help in understanding viral evolution and host-virus interactions.

Quantifying defective and wild-type viruses from high-throughput RNA sequencing.

MOTIVATION: Defective viral genomes (DVGs) are variants of the wild-type (wt) virus that lack the ability to complete autonomously an infectious cycle. However, in the presence of their parental (helper) wt virus, DVGs can interfere with the replication, encapsidation and spread of functional genomes, acting as a significant selective force in viral evolution. DVGs also affect the host's immune responses and are linked to chronic infections and milder symptoms. Thus, identifying and characterizing DVGs is crucial for understanding infection prognosis. Quantifying DVGs is challenging due to their inability to sustain themselves, which makes it difficult to distinguish them from the helper virus, especially using high-throughput RNA sequencing (RNA-seq). An accurate quantification is essential for understanding their very dynamical interactions with the helper virus. RESULTS: We present a method to simultaneously estimate the abundances of DVGs and wt genomes within a sample by identifying genomic regions with significant deviations from the expected sequencing depth. Our approach involves reconstructing the depth profile through a linear system of equations, which provides an estimate of the number of wt and DVG genomes of each type. Until now, in silico methods have only estimated the DVG-to-wt ratio for localized genomic regions. This is the first method that simultaneously estimates the proportions of wt and DVGs genome wide from short-reads RNA sequencing. AVAILABILITY AND IMPLEMENTATION: The MATLAB code and the synthetic datasets are freely available at https://github.com/jmusan/wtDVGquantific.

Transcriptomic insights into the epigenetic modulation of turnip mosaic virus evolution in Arabidopsis thaliana.

BACKGROUND: Plant-virus interaction models propose that a virus's ability to infect a host genotype depends on the compatibility between virulence and resistance genes. Recently, we conducted an evolution experiment in which lineages of turnip mosaic virus (TuMV) were passaged in Arabidopsis thaliana genotypes carrying mutations in components of the DNA methylation and the histone demethylation epigenetic pathways. All evolved lineages increased infectivity, virulence and viral load in a host genotype-dependent manner. RESULTS: To better understand the underlying reasons for these evolved relationships, we delved into the transcriptomic responses of mutant and WT plant genotypes in mock conditions and infected with either the ancestral or evolved viruses. Such a comparison allowed us to classify every gene into nine basic expression profiles. Regarding the targets of viral adaptation, our analyses allowed the identification of common viral targets as well as host genotype-specific genes and categories of biological processes. As expected, immune response-related genes were found to be altered upon infection. However, we also noticed the pervasive over-representation of other functional groups, suggesting that viral adaptation was not solely driven by the level of expression of plant resistance genes. In addition, a significant association between the presence of transposable elements within or upstream the differentially expressed genes was observed. Finally, integration of transcriptomic data into a virus-host protein-protein interaction network highlighted the most impactful interactions. CONCLUSIONS: These findings shed extra light on the complex dynamics between plants and viruses, indicating that viral infectivity depends on various factors beyond just the plant's resistance genes.

Phenotypic and genomic changes during Turnip mosaic virus adaptation to Arabidopsis thaliana mutants lacking epigenetic regulatory factors.

In this study, we investigated how an emerging RNA virus evolves, interacts, and adapts to populations of a novel host species with defects in epigenetically controlled plant defense mechanisms. Mutations in epigenetic regulatory pathways would exert different effects on defense-response genes but also induce large-scale alterations in cellular physiology and homeostasis. To test whether these effects condition the emergence and subsequent adaptation of a viral pathogen, we have evolved five independent lineages of a naive turnip mosaic virus (TuMV) strain in a set of Arabidopsis thaliana genotypes carrying mutations that influence important elements of two main epigenetic pathways and compare the results with those obtained for viral lineages evolved in wild-type plants. All evolved lineages showed adaptation to the lack of epigenetically regulated responses through significant increases in infectivity, virulence, and viral load although the magnitude of the improvements strongly depended on the plant genotype. In early passages, these traits evolved more rapidly, but the rate of evolution flattened out in later ones. Viral load was positively correlated with different measures of virulence, though the strength of the associations changed from the ancestral to the evolved viruses. High-throughput sequencing was used to evaluate the viral diversity of each lineage, as well as characterizing the nature of fixed mutations, evolutionary convergences, and potential targets of TuMV adaptation. Within each lineage, we observed a net increase in genome-wide genetic diversity, with some instances where nonsynonymous alleles experienced a transient rise in abundance before being displaced by the ancestral allele. In agreement with previous studies, viral VPg protein has been shown as a key player in the adaptation process, even though no obvious association between fixed alleles and host genotype was found.

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.

Experimental evolution of an RNA virus in Caenorhabditis elegans.

The discovery of Orsay virus (OrV), the first virus infecting wild populations of Caenorhabditis elegans, has boosted studies of viral immunity pathways in this nematode. Considering the many advantages that C. elegans offers for fundamental research in host-pathogen interactions, this pathosystem has high potential to become a model system for experimental virus evolution studies. However, the evolutionary constraints - i.e, the balance between genetic variation, selection, drift and historical contingency- operating in this pathosystem have barely been explored. Here we describe for the first time an evolution experiment of two different OrV strains in C. elegans. Comparison of the two ancestral strains showed differences in infectivity and sequence, and highlighted the importance of consistently normalize viral inocula for meaningful comparisons among strains. After 10 serial passages of evolution, we report slight changes in infectivity and non-synonymous mutations fixed in the evolved viral populations. In addition, we observed numerous minor variants emerging in the viral population. These minor variants were not randomly distributed along the genome but concentrated in polymorphic genomic regions. Overall, our work established the grounds for future experimental virus evolution studies using Caenorhabditis nematodes.

Story of an infection: Viral dynamics and host responses in the Caenorhabditis elegans-Orsay virus pathosystem.

Orsay virus (OrV) is the only known natural virus affecting Caenorhabditis elegans, with minimal impact on the animal's fitness due to its robust innate immune response. This study aimed to understand the interactions between C. elegans and OrV by tracking the infection's progression during larval development. Four distinct stages of infection were identified on the basis of viral load, with a peak in capsid-encoding RNA2 coinciding with the first signs of viral egression. Transcriptomic analysis revealed temporal changes in gene expression and functions induced by the infection. A specific set of up-regulated genes remained active throughout the infection, and genes correlated and anticorrelated with virus accumulation were identified. Responses to OrV mirrored reactions to other biotic stressors, distinguishing between virus-specific responses and broader immune responses. Moreover, mutants of early response genes and defense-related processes showed altered viral load progression, uncovering additional players in the antiviral defense response.

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.