Virus Evolution最新文献

The 2022 panzootic of highly pathogenic avian influenza (HPAI) A(H5) viruses has led to unprecedented transmission to multiple mammalian species. Avian influenza A viruses of the H5 subtype circulate globally among birds and are classified into distinct clades based on their haemagglutinin (HA) genetic sequences. Thus, the ability to accurately and rapidly assign clades to newly sequenced isolates is key to surveillance and outbreak response. Cocirculation of endemic, low-pathogenicity avian influenza (LPAI) A(H5) lineages in North American and European wild birds necessitates the ability to rapidly and accurately distinguish between infections arising from these lineages and epizootic HPAI A(H5) viruses. However, currently available clade assignment tools are limited and often require command-line expertise, hindering their utility for public health surveillance labs. To address this gap, we have developed datasets to enable A(H5) clade assignments with Nextclade, a drag-and-drop tool originally developed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic clade classification. Using annotated reference datasets for all historical A(H5) clades, clade 2.3.2.1 descendants, and clade 2.3.4.4 descendants provided by the Food and Agriculture Organization/World Health Organization/World Organisation for Animal Health H5 Working Group, we identified clade-defining mutations for every established clade to enable tree-based clade assignment. We then created three Nextclade datasets which can be used to assign clades to A(H5) HA sequences and call mutations relative to reference strains through a drag-and-drop interface. Nextclade assignments were benchmarked with 19 834 unique sequences not in the reference set using a prereleased version of LABEL, a well-validated and widely used command-line software. Prospective assignment of new sequences with Nextclade and LABEL produced very well-matched assignments (match rates of 97.8% and 99.1% for the 2.3.2.1 and 2.3.4.4 datasets, respectively). The all-clades dataset also performed well (94.8% match rate) and correctly distinguished between all HPAI and LPAI strains. This tool additionally allows for the identification of polybasic cleavage site sequences and potential N-linked glycosylation sites. These datasets therefore provide an alternative, rapid method to accurately assign clades to new A(H5) HA sequences, with the benefit of an easy-to-use browser interface.

Gammacoronavirus (γ-CoV) primarily infects poultry, wild birds, and marine mammals. The widespread distribution and circulation of γ-CoV in the ecological environment may lead to sustained transmission and economic loss. To better understand the diversity of γ-CoV in wild birds, we collected 482 wild-bird faecal samples from Yunnan, encompassing 14 bird species. We detected 12 γ-CoV-positive samples in five bird species, characterized five complete genomes-HNU5-1, HNU5-2, HNU5-3, HNU6-1, and HNU6-2-and proposed that these genomes represent two viral species. The HNU5 strains were derived from black-headed gull (Chroicocephalus ridibundus), while the HNU6 strains came from mallard (Anas platyrhynchos), and both of those were recombinant. The HNU5 strain exhibited the highest sequence identity (~95%) with a γ-CoV strain isolated from Numenius phaeopus (GenBank accession: PP845452). Similarly, the HNU6 strain showed 95% nucleotide identity with a γ-CoV strain (GenBank accession: PP845437) derived from A. platyrhynchos. Taxonomic analysis confirmed that HNU6s belong to the Gammacoronavirus anatis species, while HNU5s are attributed to a new species. Cross-species analysis revealed active host-switching events among γ-CoVs, indicating potential transmission of γ-CoVs from marine mammals to wild bird and from wild bird to poultry, and inter-wild bird and interpoultry transmission. In summary, we report five new γ-CoV strains in wild birds and outline the cross-species transmission of γ-CoVs. Our findings link γ-CoV hosts across different natural environments and provide new insights for exploring γ-CoVs.

As crucial regulators of insect populations in nature, baculoviruses are promising biopesticides. However, due to the scarcity of individuals with overt disease and the sporadic nature of the epidemic, our knowledge of baculovirus ecology is very limited, which impacts the effective utilization of these viruses in biocontrol. Cnaphalocrocis medinalis granulovirus (CnmeGV) specifically infects the rice leaffolder, which is the main pest of rice. In this study, we identified a population of CnmeGV that can cause a persistent epizootic in Dahuai town, Enping County, Guangdong Province, China. We sequenced the whole genomes of 138 CnmeGV isolates collected from Dahuai town for four years, reporting for the first time the genetic structure of a natural population of baculovirus. The results indicated that a long-term endemic population of CnmeGV displayed substantial genetic variation. The discriminant analysis of principal components revealed that the genetic structure of CnmeGV is clearly differentiated annually and seasonally (by the rice-growing season). CnmeGV epidemics typically occur in three waves (W1, W2, and W3) during each rice-growing season. Although the genetic structures of the CnmeGV isolates within the same rice-growing season were closely related, nucleotide diversity analysis revealed that the CnmeGV genomes exhibit higher heterozygosity levels in the initial epidemic wave compared to subsequent waves. We also found that host behaviour, virus distribution, plant structure, and weather are important factors in the recurrence of CnmeGV epizootics. Leveraging these ecological insights, we revealed the potential transmission route of CnmeGV, named 'From W1 in sheath to W2+ in fold', during continuous epidemics in natural environments. This study provides important insights into the ecology and evolution of host-pathogen interactions and the route helps develop more effective biocontrol strategies.

Recombination plays a pivotal role in generating within-host diversity and enabling HIV's evolutionary success, particularly in evading the host immune response. Despite this, the variability in recombination rates across different settings and the underlying factors that drive these differences remain poorly understood. In this study, we analysed a large dataset encompassing hundreds of untreated, longitudinally sampled infections using both whole-genome long-read and short-read sequencing datasets. By quantifying recombination rates, we uncover substantial variation across subtypes, viral loads, and stages of infection. We also map recombination hot and cold spots across the genome using a sliding window approach, finding that previously reported inter-subtype regions of high or low recombination are replicated at the within-host level. Importantly, our findings reveal the significant influence of selection on recombination, showing that the presence and success of recombinant genomes is strongly interconnected with the fitness landscape. These results offer valuable insights into the contribution of recombination to evolutionary dynamics and demonstrate the enhanced resolution that long-read sequencing offers for studying viral evolution.

Despite extensive use of vaccination, porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2) continues to evolve, likely driven by escape from natural or vaccine-derived immunity. However, direct evidence of vaccine-induced evolutionary pressure remains limited. Here, we tracked the evolution of PRRSV-2 sublineage 1A strain IA/2014 (variant 1A-unclassified) genome from infection chains of sequentially infected pigs under different immune conditions. Weaned pigs were divided into three groups: a non-immunized control group and two groups vaccinated with different modified live virus (MLV) vaccines, namely Prevacent® PRRS MLV (variant 1D.2) and Ingelvac PRRS® MLV (variant 5A.1). Sixty-four days post-vaccination, the pigs were challenged with IA/2014 PRRSV-2. Virus infection chains (which used serum from pigs in batch n to infect batch n + 1) were maintained across six sequential batches of roughly seven pigs each, allowing for virus evolution to occur across the ~ 84 days of the infection chain. A total of 110 serum samples were successfully sequenced. Vaccinated groups exhibited over twice the genetic divergence from the original challenge virus (0.3%-0.4% mean nucleotide distance) compared to non-immunized group (0.15%). Variability was concentrated in ORF1a and ORF1b. Deep sequencing revealed more rapid shifts of viral quasispecies composition in vaccinated pigs, and more homogeneous viral populations over batches compared to non-immunized pigs. Selection pressure analyses indicated strong purifying selection in one vaccinated group, though without clear signals at known antigenic sites in all treatment groups. However, vaccinated pigs had significantly higher cycle threshold values (P<.001), indicating lower viral loads and suggesting potential fitness limitations for highly diverged viruses in immunized pigs. These findings demonstrate that MLV vaccination can exert substantial evolutionary pressure on PRRSV-2, driving genetic diversification and highlighting the need for continuous PRRS monitoring and adaptive control strategies.

Analyses of viral samples from prolonged SARS-CoV-2 infections as well as from prolonged infections with other respiratory viruses have indicated that there are several consistent patterns of evolution observed across these infections. These patterns include accelerated rates of nonsynonymous substitution, viral genetic diversification into distinct lineages, parallel substitutions across infected individuals, and heterogeneity in rates of antigenic evolution. Here, we use within-host model simulations to explore the drivers of these intrahost evolutionary patterns. Our simulations build on a tunably rugged fitness landscape model to first assess the role that mutations that impact only viral replicative fitness have in driving these patterns. We then further incorporate pleiotropic sites that jointly impact replicative fitness and antigenicity to assess the role that immune pressure has on these patterns. Through simulation, we find that the empirically observed patterns of viral evolution in prolonged infections cannot be robustly explained by viral populations evolving on replicative fitness landscapes alone. Instead, we find that immune pressure is needed to consistently reproduce the observed patterns. Moreover, our simulations show that the amount of antigenic change that occurs is higher when immune pressure is stronger and at intermediate immune breadth. While our simulation models were designed to shed light on drivers of viral evolution in prolonged infections with respiratory viruses that generally cause acute infection, their structure can be used to better understand viral evolution in other acutely infecting viruses such as noroviruses that can cause prolonged infection as well as viruses such as HIV that are known to chronically infect.

[This corrects the article DOI: 10.1093/ve/vead067.].

Insects are associated with a wide variety of diverse RNA viruses, including iflaviruses, a group of positive stranded RNA viruses that mainly infect arthropods. Whereas some iflaviruses cause severe diseases in insects, numerous iflaviruses detected in healthy populations of butterflies and moths (order: Lepidoptera) do not show apparent symptoms. Compared to other hosts, only few iflavirus genomes for lepidopteran hosts could be found in publicly available databases and we know little about the occurrence of iflaviruses in natural and laboratory lepidopteran populations. To expand the known diversity of iflaviruses in Lepidoptera, we developed a pipeline to automatically reconstruct virus genomes from public transcriptome data. We reconstructed 1548 virus genomes from 55 different lepidopteran species, which were identified as coding-complete based on their length. To include incompletely assembled genomes, we developed a reference-based patching approach, resulting in 240 patched genomes. By including publicly available genomes, we inferred a phylogeny consisting of 139 non-redundant iflavirus genomes. Of these, 65 represent novel complete genomes, of which 39 might even belong to novel virus species. Our analysis expanded virus host range, where highly similar viruses were found in the transcriptomes of different lepidopteran species, genera, or even families. Additionally, we find two groups of lepidopteran species depending on the diversity of viruses that infect them: some species were only infected by closely related viruses, whereas other species are infected by highly diverse viruses from different regions of the phylogeny. Finally, we show that the evolution of one virus species, Iflavirus betaspexiguae, is impacted by recombination within the species, which is also supported by the co-occurrence of multiple strains within the data sets. Our analysis demonstrates how data mining of publicly available sequencing data can be used at a large scale to reconstruct intra-family viral diversity which serves as a basis to study virus host range and evolution. Our results contain numerous novel viruses and novel virus-host associations, including viruses for relevant insect pests, highlighting the impact of iflaviruses in insect ecology and as potential biological control agents in the future.

Piscine orthoreovirus genotype-1 (PRV-1) is a double-stranded non-enveloped RNA virus that has two subtypes (PRV-1a and PRV-1b) with members of PRV-1b considered to be more virulent than members of PRV-1a. PRV-1 is commonly found in wild and farmed salmonids of the Northeast Pacific (PRV-1a only), North Atlantic and Chilean waters (PRV-1a and PRV-1b). We are interested in understanding the original source of PRV-1, the timing of its introduction, and the role that salmon farming has in the spread and maintenance of PRV-1 in the Northeast Pacific, as well as in other regions. To this end, we generated 179 concatenated coding genome sequences of PRV-1a from archived/historical, as well as contemporary clinical and environmental samples, collected primarily in the Northeast Pacific. These concatenated genomes, along with 152 concatenated genomes generated using sequences from GenBank, were used to generate Northeast Pacific (n = 302 genomes) and Global (n = 331 genomes) datasets. In both datasets, we found that evidence for a temporal signal is restricted to a single clade from the Northeast Pacific, so conducting divergence time estimations for the entire Northeast Pacific and Global datasets was not undertaken. However, partial PRV-1 sequences obtained from histology samples collected in 1977 show that PRV-1a has been in the Northeast Pacific for at least 47 years, and we propose based on the probability of detection, that it was likely widely distributed at that time. With the exception of a recently introduced genetic variant, WCAN_BC17_AS_2017, PRV-1a variants from the Northeast Pacific form 3 well-supported clades at the genome level. All clades contain sequences from farmed and wild salmon, although one PRV-1 clade was only detected in farmed/wild Pacific salmon and not in farmed Atlantic Salmon. This observation, along with the occurrence of identical PRV-1a genetic variants in wild and farmed fish, provides evidence for transfer between these groups in the Northeast Pacific. Our analysis of the Global dataset identified additional PRV-1 genetic structure in the North Atlantic and Chilean waters and the requirement for additional PRV-1 genomic sequencing from these areas to better understand these relationships. The high level of Global PRV-1 genetic homogeneity at the genome level and the prediction that both PRV-1a and PRV-1b are under strong negative/purifying selection, suggests that PRV-1 is at or near a fitness peak in most host populations. The majority of differences between PRV-1 genetic variants are synonymous mutations. Understanding the extent to which synonymous mutations determine the phenotypes of PRV-1 could help to explain why some genetically similar variants differ in their pathogenicity and virulence.

Cottontails (Sylvilagus spp.) and jackrabbits (Lepus spp.) within the Leporidae family are native to North America and are found in a wide range of habitats, including deserts, forests, and grasslands. Although there is a growing body of research describing the arrival of the highly virulent rabbit haemorrhagic disease virus 2 (RHDV2, GI.2) on this continent, and its impact on native lagomorphs, information about the natural virome and microbiome of healthy and deceased American lagomorphs is relatively limited. In this study, we used a meta-transcriptomics approach to conduct whole pathogen profiling on healthy and deceased animals in the USA. We analysed 48 matched liver and lung sample pools from apparently healthy cottontails and jackrabbits in Texas and an additional 48 liver samples from deceased animals from nine other US states. This approach enabled the discovery of three distinct new viruses and revealed additional new insights into the lung and liver microbiomes of North American lagomorphs. Of the three new viruses, a tetnovirus and a novel picorna-like virus were likely of insect origin and therefore considered environmental contaminants. Of particular interest was a new species of hepacivirus, with around 50% sequence identity to a known hepacivirus from a xeric four-striped grass rat (Rhabdomys pumilio). Phylogenetic analysis from 41 individual hepacivirus genomes recovered from our lagomorph samples revealed two distinct clades, corresponding with different cottontail species. No hepaciviruses were detected in any of the jackrabbit samples. This is the first description of a hepacivirus in lagomorphs. Our findings extend the Hepacivirus genus, provide new insights into its evolution, and describe the first baseline on microbial diversity in North American lagomorphs, an important step towards understanding the role of potential pathogens for population management and conservation.