RNA-seq accuracy and reproducibility for the mapping and quantification of influenza defective viral genomes

Meta-analysis of genomic characteristics for antiviral influenza defective interfering particle prioritization

Defective interfering particles (DIPs) are viral deletion mutants that hamper virus replication and are, thus, potent novel antiviral agents. To evaluate possible antiviral treatments, we first need to get a deeper understanding of DIP characteristics. Thus, we performed a meta-analysis of 20 already published sequencing datasets of influenza A and B viruses (IAV and IBV) from in vivo and in vitro experiments. We analyzed each dataset for characteristics, such as deletion-containing viral genome (DelVG) length distributions, direct repeats, and nucleotide enrichment at the deletion site. Our analysis suggests differences in the length of the 3'- and 5'-end retained in IAV and IBV viral sequences upon deletion. Moreover, in vitro DelVGs tend to be shorter than those in vivo, which is a novel finding with potential implications for future DIP treatment design. Additionally, our analysis demonstrates the presence of DelVGs with longer than expected sequences, possibly related to an alternative mechanism of DelVG formation. Finally, a joint ranking of DelVGs originating from 7 A/Puerto Rico/8/1934 datasets revealed 11 highly abundant, yet unnoticed, candidates. Together, our study highlights the importance of meta-analyses to uncover yet unknown DelVG characteristics and to pre-select candidates for antiviral treatment design.

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.

Evaluating storage conditions and enhancement strategies on viral biomarker recovery for WBE applications

Wastewater-based epidemiology (WBE) is a valuable disease surveillance tool. However, little is known on how factors such as transportation, storage, and wastewater characteristics influence the accuracy of the quantification methods. Hence, this study investigated the impact of storage temperatures and physicochemical characteristics of wastewater on SARS-CoV-2 and influenza A stability using droplet digital PCR. Additionally, strategies to enhance viral recovery were explored. Municipal influent wastewater stored between ±25 and -80 °C was assessed for a period of 84 days to determine viral degradation. Degradation up to 94.1% of influenza A and SARS-CoV-2 was observed in all samples with the highest at ±25 °C. Viral degradation was correlated to the changes in wastewater physicochemical characteristics. The low degradation observed of SARS-CoV-2 in the spiked pellets were indicative of viral adhesion to wastewater solids, which correlated with changes in pH. Ultrasonication frequencies ranging from 4 to 16 kHz, increased SARS-CoV-2 concentrations in the supernatant between 3.30 and 35.65%, indicating viral RNA attachment to wastewater solids. These results highlight the importance of additional pretreatment methods for maximizing RNA recovery from wastewater samples. Based on these findings, it was deduced that wastewater preservation studies are essential, and pretreatment should be included in the WBE methodology.

Influenza A genomic diversity during human infections underscores the strength of genetic drift and the existence of tight transmission bottlenecks

Influenza infections result in considerable public health and economic impacts each year. One of the contributing factors to the high annual incidence of human influenza is the virus's ability to evade acquired immunity through continual antigenic evolution. Understanding the evolutionary forces that act within and between hosts is therefore critical to interpreting past trends in influenza virus evolution and in predicting future ones. Several studies have analyzed longitudinal patterns of influenza A virus genetic diversity in natural human infections to assess the relative contributions of selection and genetic drift on within-host evolution. However, in these natural infections, within-host viral populations harbor very few single-nucleotide variants, limiting our resolution in understanding the forces acting on these populations in vivo. Furthermore, low levels of within-host viral genetic diversity limit the ability to infer the extent of drift across transmission events. Here, we propose to use influenza virus genomic diversity as an alternative signal to better understand within- and between-host patterns of viral evolution. Specifically, we focus on the dynamics of defective viral genomes (DVGs), which harbor large internal deletions in one or more of influenza virus's eight gene segments. Our longitudinal analyses of DVGs show that influenza A virus populations are highly dynamic within hosts, corroborating previous findings based on viral genetic diversity that point toward the importance of genetic drift in driving within-host viral evolution. Furthermore, our analysis of DVG populations across transmission pairs indicates that DVGs rarely appeared to be shared, indicating the presence of tight transmission bottlenecks. Our analyses demonstrate that viral genomic diversity can be used to complement analyses based on viral genetic diversity to reveal processes that drive viral evolution within and between hosts.

5' copyback defective viral genomes are major component in clinical and non-clinical influenza samples

Clinical samples from people with influenza disease have been analyzed to assess the presence and abundance of Defective Viral Genomes (DVGs), but these have not been assessed using the same bioinformatic pipeline. The type of DVG most described for influenza infections (deletion DVGs) differs from the most commonly described DVGs from non-segmented negative stranded viruses (5' copyback). This could be attributed to either differences between viruses or the tools used to detect and characterize DVGs. Here we analyze several NGS datasets from people infected with different types of influenza virus using the same bioinformatic pipeline. We observe that 5' copyback DVGs are prevalent in all human clinical samples but not in the cultured samples. To address this discrepancy between clinical and laboratory cultures, we infected cell culture and ferrets with an H5N8 influenza A virus (FLUAV) and analyzed the DVG composition. The results demonstrate that the DVG population is skewed toward 5' copyback DVGs in the in vivo infections and deletion DVGs in the in vitro infections. This demonstrates that there are differences in vivo genome production and in vitro genome production, and this has implications for how the role of DVGs in clinical disease is studied. We also investigate the role the host cofactor ANP32B has in DVG production.

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.

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.

Generation and Functional Analysis of Defective Viral Genomes during SARS-CoV-2 Infection

Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from transcriptome sequencing (RNA-seq) data sets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hot spots were identified for DVG recombination, and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single-cell RNA-seq analysis indicated the interferon (IFN) stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the next-generation sequencing (NGS) data set from a published cohort study and observed a significantly higher amount and frequency of DVG in symptomatic patients than those in asymptomatic patients. Finally, we observed exceptionally diverse DVG populations in one immunosuppressive patient up to 140 days after the first positive test of COVID-19, suggesting for the first time an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and into how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection. IMPORTANCE Defective viral genomes (DVGs) are generated ubiquitously in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide the potential for them to be used in novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex, and this recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hot spots for nonhomologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide evidence to harness the immunostimulatory potential of DVGs in the development of a vaccine and antivirals for SARS-CoV-2.

ViReMa: a virus recombination mapper of next-generation sequencing data characterizes diverse recombinant viral nucleic acids

BACKGROUND

Genetic recombination is a tremendous source of intrahost diversity in viruses and is critical for their ability to rapidly adapt to new environments or fitness challenges. While viruses are routinely characterized using high-throughput sequencing techniques, characterizing the genetic products of recombination in next-generation sequencing data remains a challenge. Viral recombination events can be highly diverse and variable in nature, including simple duplications and deletions, or more complex events such as copy/snap-back recombination, intervirus or intersegment recombination, and insertions of host nucleic acids. Due to the variable mechanisms driving virus recombination and the different selection pressures acting on the progeny, recombination junctions rarely adhere to simple canonical sites or sequences. Furthermore, numerous different events may be present simultaneously in a viral population, yielding a complex mutational landscape.

FINDINGS

We have previously developed an algorithm called ViReMa (Virus Recombination Mapper) that bootstraps the bowtie short-read aligner to capture and annotate a wide range of recombinant species found within virus populations. Here, we have updated ViReMa to provide an "error density" function designed to accurately detect recombination events in the longer reads now routinely generated by the Illumina platforms and provide output reports for multiple types of recombinant species using standardized formats. We demonstrate the utility and flexibility of ViReMa in different settings to report deletion events in simulated data from Flock House virus, copy-back RNA species in Sendai viruses, short duplication events in HIV, and virus-to-host recombination in an archaeal DNA virus.

Transient RNA structures cause aberrant influenza virus replication and innate immune activation

During infection, the influenza A virus RNA polymerase produces both full-length and aberrant RNA molecules, such as defective viral genomes (DVGs) and mini viral RNAs (mvRNAs). Subsequent innate immune activation involves the binding of host pathogen receptor retinoic acid-inducible gene I (RIG-I) to viral RNAs. However, it is not clear what factors determine which influenza A virus RNAs are RIG-I agonists. Here, we provide evidence that RNA structures, called template loops (t-loops), stall the viral RNA polymerase and contribute to innate immune activation by mvRNAs during influenza A virus infection. Impairment of replication by t-loops depends on the formation of an RNA duplex near the template entry and exit channels of the RNA polymerase, and this effect is enhanced by mutation of the template exit path from the RNA polymerase active site. Overall, these findings are suggestive of a mechanism involving polymerase stalling that links aberrant viral replication to the activation of the innate immune 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.

Influenza A Virus Defective Viral Genomes Are Inefficiently Packaged into Virions Relative to Wild-Type Genomic RNAs

Deletion-containing viral genomes (DelVGs) are commonly produced during influenza A virus infection and have been implicated in influencing clinical infection outcomes. Despite their ubiquity, the specific molecular mechanisms that govern DelVG formation and their packaging into defective interfering particles (DIPs) remain poorly understood. Here, we utilized next-generation sequencing to analyze DelVGs that form de novo early during infection, prior to packaging. Analysis of these early DelVGs revealed that deletion formation occurs in clearly defined hot spots and is significantly associated with both direct sequence repeats and enrichment of adenosine and uridine bases. By comparing intracellular DelVGs with those packaged into extracellular virions, we discovered that DelVGs face a significant bottleneck during genome packaging relative to wild-type genomic RNAs. Interestingly, packaged DelVGs exhibited signs of enrichment for larger DelVGs suggesting that size is an important determinant of packaging efficiency. Our data provide the first unbiased, high-resolution portrait of the diversity of DelVGs that are generated by the influenza A virus replication machinery and shed light on the mechanisms that underly DelVG formation and packaging. IMPORTANCE Defective interfering particles (DIPs) are commonly produced by RNA viruses and have been implicated in modulating clinical infection outcomes; hence, there is increasing interest in the potential of DIPs as antiviral therapeutics. For influenza viruses, DIPs are formed by the packaging of genomic RNAs harboring internal deletions. Despite decades of study, the mechanisms that drive the formation of these deletion-containing viral genomes (DelVGs) remain elusive. Here, we used a specialized sequencing pipeline to characterize the first wave of DelVGs that form during influenza virus infection. This data set provides an unbiased profile of the deletion-forming preferences of the influenza virus replicase. In addition, by comparing the early intracellular DelVGs to those that get packaged into extracellular virions, we described a significant segment-specific bottleneck that limits DelVG packaging relative to wild-type viral RNAs. Altogether, these findings reveal factors that govern the production of both DelVGs and DIPs during influenza virus infection.

Nanopore-Based Direct RNA-Sequencing Reveals a High-Resolution Transcriptional Landscape of Porcine Reproductive and Respiratory Syndrome Virus

The TRS-mediated discontinuous transcription process is a hallmark of Arteriviruses. Precise assessment of the intricate subgenomic RNA (sg mRNA) populations is required to understand the kinetics of viral transcription. It is difficult to reconstruct and comprehensively quantify splicing events using short-read sequencing, making the identification of transcription-regulatory sequences (TRS) particularly problematic. Here, we applied long-read direct RNA sequencing to characterize the recombined RNA molecules produced in porcine alveolar macrophages during early passage infection of porcine reproductive and respiratory syndrome virus (PRRSV). Based on sequencing two PRRSV isolates, namely XM-2020 and GD, we revealed a high-resolution and diverse transcriptional landscape in PRRSV. The data revealed intriguing differences in subgenomic recombination types between the two PRRSVs while also demonstrating TRS-independent heterogeneous subpopulation not previously observed in Arteriviruses. We find that TRS usage is a regulated process and share the common preferred TRS in both strains. This study also identified a substantial number of TRS-mediated transcript variants, including alternative-sg mRNAs encoding the same annotated ORF, as well as putative sg mRNAs encoded nested internal ORFs, implying that the genetic information encoded in PRRSV may be more intensively expressed. Epigenetic modifications have emerged as an essential regulatory layer in gene expression. Here, we gained a deeper understanding of m5C modification in poly(A) RNA, elucidating a potential link between methylation and transcriptional regulation. Collectively, our findings provided meaningful insights for redefining the transcriptome complexity of PRRSV. This will assist in filling the research gaps and developing strategies for better control of the PRRS.

Library-based analysis reveals segment and length dependent characteristics of defective influenza genomes

Found in a diverse set of viral populations, defective interfering particles are parasitic variants that are unable to replicate on their own yet rise to relatively high frequencies. Their presence is associated with a loss of population fitness, both through the depletion of key cellular resources and the stimulation of innate immunity. For influenza A virus, these particles contain large internal deletions in the genomic segments which encode components of the heterotrimeric polymerase. Using a library-based approach, we comprehensively profile the growth and replication of defective influenza species, demonstrating that they possess an advantage during genome replication, and that exclusion during population expansion reshapes population composition in a manner consistent with their final, observed, distribution in natural populations. We find that an innate immune response is not linked to the size of a deletion; however, replication of defective segments can enhance their immunostimulatory properties. Overall, our results address several key questions in defective influenza A virus biology, and the methods we have developed to answer those questions may be broadly applied to other defective viruses.

Influenza Virus RNA Synthesis and the Innate Immune Response

Infection with influenza A and B viruses results in a mild to severe respiratory tract infection. It is widely accepted that many factors affect the severity of influenza disease, including viral replication, host adaptation, innate immune signalling, pre-existing immunity, and secondary infections. In this review, we will focus on the interplay between influenza virus RNA synthesis and the detection of influenza virus RNA by our innate immune system. Specifically, we will discuss the generation of various RNA species, host pathogen receptors, and host shut-off. In addition, we will also address outstanding questions that currently limit our knowledge of influenza virus replication and host adaption. Understanding the molecular mechanisms underlying these factors is essential for assessing the pandemic potential of future influenza virus outbreaks.

The influenza virus RNA polymerase as an innate immune agonist and antagonist

Influenza A viruses cause a mild-to-severe respiratory disease that affects millions of people each year. One of the many determinants of disease outcome is the innate immune response to the viral infection. While antiviral responses are essential for viral clearance, excessive innate immune activation promotes lung damage and disease. The influenza A virus RNA polymerase is one of viral proteins that affect innate immune activation during infection, but the mechanisms behind this activity are not well understood. In this review, we discuss how the viral RNA polymerase can both activate and suppress innate immune responses by either producing immunostimulatory RNA species or directly targeting the components of the innate immune signalling pathway, respectively. Furthermore, we provide a comprehensive overview of the polymerase residues, and their mutations, associated with changes in innate immune activation, and discuss their putative effects on polymerase function based on recent advances in our understanding of the influenza A virus RNA polymerase structure.