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Viruses are generally considered tiny biological entities with small genomes; however, some dsDNA viruses, known as giant viruses, have large genomes that are comparable to those of small bacteria. These viruses may have evolved from a small ancestor. During their evolution, virus-to-virus horizontal gene transfer has substantially contributed to the expansion of the genomic repertoire of giant viruses. In this study, we identified a horizontal transfer of a large fraction of the genome between viruses in pandoraviruses, a group of giant viruses with the largest genome sizes reaching 2.5 Mbp. We isolated a pandoravirus that belongs to a known viral species. However, its genome size was 200 kbp larger than that of other strains in the same species. Comparative genomics identified a 180-kbp genomic fraction with 168 genes in the newly isolated virus, which may have been horizontally transferred from a distantly related pandoravirus. The gene composition in the 180-kbp region further indicates that this region was already large at the time of the horizontal transfer. Our findings suggest that pandoraviruses can horizontally exchange a large portion of their genomes. This event presumably represents one mechanism for accelerating genomic evolution and gigantism in giant viruses.IMPORTANCEGiant viruses are double-stranded DNA viruses belonging to the phylum Nucleocytoviricota, characterized by large particles and genomes. Previous studies have suggested that these viruses may have evolved from a small ancestor, but the underlying mechanisms are not fully understood. In this study, we isolated one of the largest giant viruses, pandoravirus, which belongs to a known viral species but has a genome 200 kbp larger than that of other strains in the same species. Comparative genomics identified a 180-kbp genomic fragment containing 168 genes in the newly isolated virus that is absent from other strains of the same species. Further comparative analysis indicated that this 180-kbp region has been horizontally transferred from a distantly related pandoravirus. Our findings suggest that giant viruses can exchange a massive number of genes by a horizontal transfer of a large genomic fraction, which may have contributed to their gigantism.
Tsaoko stripe mosaic virus (TkSMV) has been identified as the predominant viral pathogen of Amomum tsaoko in Yunnan province of China. This virus induced various foliar symptoms including chlorosis, stripe mosaic and necrosis, while some infected A. tsaoko plants remain asymptomatic. Comprehensive investigation​ of the population genetic structure and molecular detection protocols for TkSMV is crucial for elucidating its evolutionary dynamics, epidemiology, and disease control strategies. Phylogenetic analysis based on 15 full-length genomic sequences and 29 coat protein (CP) gene fragments revealed three distinct evolutionary lineages (S1, S2, S3) within the TkSMV population. Neutrality tests analysis indicates that the genetic polymorphism of the TkSMV population is consistent with a neutral evolution model (Tajima's D > 0, not significant). The comparative evolutionary analysis demonstrated significant selective pressures across viral proteins: codon usage bias analysis revealed strong purifying selection (dN/dS < 1) in nine structural/functional proteins, eliminating deleterious mutations. The 9K gene exhibited the highest nucleotide diversity (π= 0.13567), suggesting its role in adaptive evolution. NIa-Pro protease showed the lowest diversity (π= 0.09497), indicating functional constraint. Remarkably, the CP gene displayed polarized evolutionary patterns. N-terminal region (aa 1-100) acted as a hypervariable hotspot, C-terminal region (aa 151-240) maintained evolutionary conservation. Furthermore, multiplex RT-PCR assays for accurate discrimination TkSMV-S1/S2/S3 strains in mixed infections were developed. These advancements provide technical foundations for​ epidemiological surveillance​ through strain-specific monitoring, seed certification programs​ for A. tsaoko cultivation.
Codon usage bias (CUB) reflects the combined effects of mutational pressure and natural selection and provides insight into viral evolution and host adaptation. Although previous studies have examined CUB in individual coronaviruses or at the whole-genome level, systematic comparative analyses focusing on the spike (S) gene-an important determinant of viral evolution and host adaptation-across all four coronavirus genera including Alphacoronavirus, Betacoronavirus, Gammacoronavirus, and Deltacoronavirus, remain limited. In this study, we analyzed CUB in coronavirus spike genes across multiple genera and host groups. Codon usage indices, including codon adaptation index (CAI), effective number of codons (ENC), and GC content at the third synonymous codon position (GC3s), were evaluated alongside multivariate and clustering approaches, including correspondence analysis, hierarchical clustering, heatmap visualization, and ENC-GC3s analysis. Significant differences in CAI and ENC were observed among coronavirus genera, whereas GC3s showed no significant variation, indicating that codon usage patterns are structured primarily by phylogenetic relationships rather than nucleotide composition alone. Multivariate and clustering analyses further supported genus-level organization of codon usage profiles. In contrast, host-based comparisons showed that CAI varied significantly across host groups, while ENC and GC3s remained relatively stable, suggesting that host-associated translational selection influences codon preference without substantially altering overall codon bias strength. Heatmap analysis revealed enrichment of A/U-ending codons and underrepresentation of C/G-ending codons across coronavirus genomes, with consistent suppression of (cytosine-guanine dinucleotides) CpG-containing codons. ENC-GC3s analysis indicated that most genomes deviate from the expected neutral curve, suggesting that factors beyond mutational bias contribute to codon usage patterns. These findings indicate that codon usage bias in coronavirus spike genes is shaped by a combination of virus-intrinsic constraints and host-associated selective pressures, providing a gene-centric, cross-genera framework for understanding coronavirus evolution and host adaptation.
Although viruses are often studied in relation to disease, they can also offer valuable insights into RNA functionality. Due to their vast range of hosts and high mutation rates, viruses can quickly adapt to changing environments. It is therefore likely that viruses exploit a broad range of RNA functionalities to develop strategies for host infection and propagation. Our aim is to discover RNA viruses with survival strategies that reveal unknown RNA characteristics and functionalities. Here, we report a new, unclassified negative-sense single-stranded RNA virus from the large brown seaweed Saccharina latissima that showed a unique genome characteristic. The novel virus, designated SalaUV-NL1, possesses a bipartite genome. The small segment (2120 nt) encodes a putative 328-aa protein and possibly an additional protein of ≥315 aa. The large segment (7065 nt) encodes a putative RNA-dependent RNA polymerase (RdRp) of 2296 amino acids on the anti-genomic strand, but strikingly contains a similarly sized and largely overlapping open reading frame (reverse ORF; rORF) on the genomic strand that encodes a putative protein of 2317 aa. This raises the possibility that SalaUV-NL1 represents an ambigrammatic virus. However, the RdRp ORF exhibits an extreme GC3 codon bias (98%), far exceeding the typical codon constraints of ambigrammatic viruses that mostly reflect the avoidance of stop codons on the reverse strand. Therefore, the rORF is likely incidental because it is the result of the GC3 codon bias on the RdRp-coding anti-genomic strand. We therefore designate SalaUV-NL1 as pseudoambigrammatic. Several other viruses with a similar pseudoambigrammatic signature, characterized by unusually high GC3 codon bias, were identified in GenBank, most of which lack a discernible rORF. The codon bias of SalaUV-NL1 surpasses even that of its host, S. latissima, although other hosts of pseudoambigrammatic viruses do not display elevated GC3 levels. Comparative analysis of multiple SalaUV-NL1 variants further revealed exceptionally high nucleotide substitution rates, particularly silent A/U → G/C transitions, reaching frequencies of up to 81%. This novel virus, therefore, exemplifies a previously unrecognized survival strategy among RNA viruses, the functional implications of which remain unclear.
High mutation rates erode viral sequence similarity, obscuring deep evolutionary history. While protein structure is far more conserved than sequence, its use in evolutionary studies has historically been bottlenecked by experimental determination. The recent revolution in artificial intelligence (AI) structure prediction has fundamentally changed this, enabling the rapid generation of millions of viral protein structures. This review examines the effect of AI-based protein structure prediction methods on our understanding of deep viral evolution. We describe the strengths and limitations of protein structure prediction and consider the questions it can be used to address: illuminating viral dark matter in metagenomic datasets, resolving high-level taxonomy for orphan lineages, and inferring function for divergent proteins. Furthermore, we assess the emerging field of structural phylogenetics, exploring the theoretical and practical challenges of integrating structure and sequence to reconstruct ancient evolutionary events. We conclude that despite remaining challenges, systematic structure prediction will extend our exploration of deep evolution across the virosphere.
Hepatitis A virus (HAV) remains a significant public health concern despite the availability of effective vaccines, particularly in regions experiencing epidemiological transitions. Recent HAV cases in Japan have increasingly occurred among defined risk groups rather than through large food-borne outbreaks. This study analyzed the phylodynamic patterns and molecular evolution of capsid protein sequences of HAV circulating in Japan between 1957 and 2021. Phylogenetic analysis showed that genotype IA predominates in Japan forming five well-supported clusters, including two lineages that persisted for more than two decades, indicating long-term endemic co-circulation. Bayesian evolutionary analysis suggested that genotype IA diversification in Japan began in the early 20th century, and Bayesian Skygrid plot demonstrated substantial temporal fluctuations in effective viral population size, with notable peaks corresponding to documented outbreaks around 2010 and 2017, the latter associated with internationally transmitted men who have sex with men-related strains. Selection pressure analyses indicated strong purifying selection with limited evidence of adaptive evolution. HAV transmission dynamics in Japan are shaped by both endemic multi-lineage persistence and episodic introductions of international strains rather than viral genetic adaptation. Continuous genomic surveillance integrated with epidemiological data is essential for anticipating future outbreaks in low-endemicity area.
Respiratory syncytial virus (RSV) is an important respiratory pathogen in infants, young children and older adults. Based on global RSV genomic surveillance data, this review systematically summarizes the geographic distribution, seasonal epidemic patterns, and long-term evolutionary trends of RSV, with particular emphasis on the sustained circulation and evolutionary mechanisms of dominant genotypes such as ON1 in RSV-A and BA9 in RSV-B. Current evidence indicates that RSV transmission dynamics are tightly coupled with viral evolution. The G gene evolves relatively rapidly and contains multiple positively selected sites, suggesting an important role in immune escape and population adaptation. In recent years, changes in social behavior patterns and population immunity have further disrupted the seasonal rhythm of RSV and may have influenced the spread of dominant genotypes. Under routine respiratory infectious disease surveillance, strengthened genomic monitoring and integration of multi-source data are needed to improve early warning of abnormal RSV epidemics and variant-associated risks, thereby providing prospective evidence for protecting high-risk populations and informing public health decision-making. 呼吸道合胞病毒（RSV）是婴幼儿和老年人重要的呼吸道病原。本文基于全球RSV基因组监测数据，系统综述了该病毒的地理分布特征、季节性流行规律和长期进化趋势，重点解析了ON1（RSV-A）和BA9（RSV-B）等优势基因型的持续流行及其进化机制。现有证据表明，RSV的传播动力学与病毒进化高度耦合，其G基因进化速率较快且存在多处正向选择位点，在免疫逃逸和人群适应中发挥关键作用。近年来的社会行为模式变迁及人群免疫背景变化进一步扰动了RSV的季节性节律，并在一定程度上影响了优势基因型的扩散效应。建议今后在常态化呼吸道传染病监测背景下，通过加强基因组监测与多源数据整合，提升RSV异常流行和变异风险的早期预警能力，从而为高风险人群防护及公共卫生决策提供前瞻性的科学依据。.
Lassa fever is a viral haemorrhagic fever that poses a persistent public health threat in several West African countries, particularly Nigeria. The scarcity of Lassa virus (LASV) sequences isolated from small mammal reservoirs limits our knowledge and understanding of LASV genomic diversity and transmission dynamics. To address this knowledge gap, we sampled 1189 small mammals, including mice, rats, and shrews, from two LASV-endemic states in southern Nigeria (Ondo and Ebonyi States) and tested them for the presence of LASV RNA using reverse transcription-quantitative polymerase chain reaction. Selected quantitative polymerase chain reaction-positive samples were subjected to whole genome sequencing and small mammal speciation through next-generation sequencing outputs. We recorded an overall polymerase chain reaction positivity rate of 61.6%, with rat species demonstrating the highest LASV prevalence. We also conducted a serosurvey of 269 small rodents using indirect Enzyme-Linked Immunosorbent Assay (ELISA) and obtained an overall anti-LASV seroprevalence of 45%. Using the Nextera XT metagenomic sequencing protocol, we produced 55 LASV partial (n = 28) and full-length genomes (n = 27) from small mammals sampled, all of which clustered within sublineage 2g. LASV sequences generated from this study suggest that LASV variation is mostly driven by location, as isolates from this study tend to cluster more closely with other isolates collected from within the same region, rather than by collection date or host. However, samples collected from Ebonyi State were more closely related to isolates collected in Ondo State than to isolates from Edo, despite a larger physical distance. Overall, the data from this study suggest free movement of the virus across states in Nigeria, among humans and various non-human taxa. The finding of LASV in additional small mammal hosts suggests that the virus reservoir is vast and may include many small mammals not well-characterized.
Concurrent infection of humans by multiple distinct viruses is a common biological phenomenon with important consequences for virus-host interactions. While coinfection refers to the simultaneous infection of an individual or cell with two or more viruses, superinfection denotes the establishment of a secondary infection following a primary one, in which the initial infection influences the susceptibility, replication, or outcome of the secondary infection. Virus-virus interactions can be antagonistic, facilitative, dependent/assisted, or neutral. Antagonistic interactions include superinfection exclusion, whereby a primary virus prevents or restricts secondary infection of the same cell, securing access to host resources and stabilizing replication while limiting genetic and viral diversity. In contrast, facilitative viral interactions arise when one virus disrupts tissue barriers, suppresses immune responses, or remodels cellular pathways, thereby increasing susceptibility to additional viral infections. These interactions intersect with fundamental viral strategies, including the generation of genetically diverse RNA virus quasispecies that promote rapid adaptation and the deployment of DNA virus immunoevasins that interfere with antigen presentation and host immune recognition. While each of these processes has been extensively studied individually, their combined impact during coinfection remains poorly defined. In this review, we synthesize current knowledge on virus-virus interactions, viral diversity, and immune evasion in the context of multi-viral infections. We focus on how interactions at cellular and tissue levels shape infection outcomes, influence viral evolution, and contribute to virus-host coevolution. Finally, we also highlight key gaps in our understanding of viral interference and cooperation and discuss emerging approaches needed to define the spatiotemporal dynamics of coinfection in vivo.
Surveillance of tick-associated viruses may contribute to our understanding of viral diversity and evolution. Here, we identified a novel victorivirus in a sample derived from a human-biting tick, Amblyomma testudinarium, in Japan. The viral sequence was identified by metatranscriptomic sequencing of total RNA extracted from Vero cells treated with tick homogenate. The viral sequence was 4621 bp in length and contained two major open reading frames predicted to encode a putative coat protein (CP) and a putative RNA-dependent RNA polymerase (RdRp), respectively. The two open reading frames overlapped at the tetranucleotide sequence AUGA. The C-terminal region of putative CP was enriched in alanine, glycine, and proline residues. All these features are similar to those commonly observed in victoriviruses. Phylogenetic analyses based on the amino acid sequences of the putative CP and RdRp showed that the virus belongs to the genus Victorivirus of the family Pseudototiviridae. We therefore designated this putative virus as Amblyomma testudinarium-associated victorivirus 1 (ATaVV1). These findings expand our current knowledge of hidden viral diversity in tick-associated samples.
Matryoshka RNA virus 1 (MaRNAV-1) is a bi-segmented and single-stranded RNA virus associated with Plasmodium vivax, a cause of human malaria. Little has been uncovered about the epidemiology and ecology of this virus since its discovery in 2019. To address this, we used a combination of primary and publicly available metatranscriptomic data to map the geographic distribution and host associations of MaRNAV-1. We detected this virus throughout Southeast Asia, in parts of South America, and, for the first time, in Oceania. Despite its broad distribution, MaRNAV-1 was found exclusively in metatranscriptomes containing P. vivax, suggesting that there is a specific virus-host relationship that has shaped the evolutionary history of this virus. We were unable to estimate the emergence date of the MaRNAV-1 lineage; however, phylogeographic mapping analysis suggested that MaRNAV-1 is widely dispersed throughout Southeast Asia. Our findings have both evolutionary and public health implications and can serve as the basis for future investigations in these fields.
Alphavirus-derived vector systems have been used for heterologous gene expression for nearly four decades, providing foundational insights into RNA virus replication, host interactions, and genome engineering. The recent success of conventional mRNA vaccines has intensified interest in leveraging the alphavirus replicase and its associated conserved sequence elements (CSEs) to develop self-amplifying mRNA (sa-mRNA) platforms characterized by more sustained antigen expression and dose-sparing. In this minireview, we summarize key advances that define the coordinated functions of the nonstructural proteins and CSEs in viral RNA synthesis and host modulation. We then contextualize the developmental milestones of alphavirus replicons that underpin modern sa-mRNA technologies. We further discuss emerging strategies to engineer replicase functions and RNA architecture in different sa-mRNA applications, while outlining critical gaps in alphavirus biology that currently constrain rational sa-mRNA design. Renewed investigation of nonstructural proteins and CSEs will accelerate optimization of next-generation sa-mRNA platforms and reinvigorate fundamental studies of alphavirus replication, evolution, and host adaptation.
In recent years, OROV has emerged as a significant public health threat beyond the Amazon region. Here we review current epidemiological, virological, clinical and ecological knowledge of OROV to inform health practitioners, public health authorities and the scientific community and to facilitate the development of effective control strategies for OROV. We describe the epidemiological, virological, ecological and clinical characteristics of OROV, focusing on lessons from the recent expansion, and highlighting needs for control and management of this emerging arbovirus. This review aims to inform health practitioners, public health authorities and the scientific community of the recent reemergence and expansion of OROV beyond the Amazon Basin. The ecology, epidemiology, virology of OROV and clinical presentations of OROV infection are discussed, and knowledge gaps are identified.
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Sudan virus (SUDV; species Orthoebolavirus sudanense) remains a major public health threat, yet research is limited by restricted access to biosafety level 4 (BSL-4) facilities. To address this, we developed a biologically contained SUDV lacking the essential VP30 gene, restricting replication to VP30-expressing cells. We demonstrate efficient virus rescue, strict functional and genetic containment, and replication kinetics comparable to wild-type SUDV in permissive cells. Using heterologous VP30-expressing cell lines, we observe strong cross-functionality among orthoebolaviruses, whereas Marburg virus VP30 shows minimal activity, highlighting genus-specific constraints. The system supports high-throughput antiviral screening and confirms robust activity of remdesivir. In addition, resistance profiling identified substitutions at residue F549 of viral polymerase L as key determinants for remdesivir resistance, with additional mutations at M675. Together, this biologically contained SUDV system enables safe study of viral replication, antiviral discovery, and resistance evolution under lower biosafety conditions.
Marek's disease (MD) is a highly contagious neoplastic disorder of poultry caused by MD virus (MDV; gallid alphaherpesvirus 2 [GaAHV2]). Infection results in profound immunosuppression, neurological dysfunction, and the development of malignant T-cell lymphomas. Continued viral evolution has produced increasingly virulent strains capable of partially or fully evading current vaccines, leaving few options for controlling emerging variants. This highlights the importance of identifying new antiviral targets, particularly those involved in the nuclear trafficking events essential for GaAHV2 replication. The UL36 large tegument protein of alphaherpesviruses contains N-terminal nuclear localization signals (NLSs) thought to guide capsid transport to the nuclear pore complex. However, the specific mechanism by which GaAHV2 UL36 engages the host nuclear import machinery remains unclear. In this work, we defined the NLS within the N-terminal region of GaAHV2 UL36 and characterized its interaction with importin proteins. Through high-resolution crystallography and quantitative binding assays, we pinpointed the residues and structural motifs within UL36 that mediate recognition by importin-α (IMPα) and compared their affinities across different IMPα isoforms. Our structural and biochemical data show that the predicted N-terminal NLS of GaAHV2 UL36 is essential for IMPα binding. These findings provide a detailed molecular framework for host-virus interactions during GaAHV2 nuclear entry and offer potential avenues for the development of targeted antiviral strategies.
Swine influenza A viruses (swIAVs) undergo frequent reassortment and evolution, posing significant threats to both animal and human health. In this study, we employed reverse genetics to generate five recombinant viruses and evaluated their potential as vaccine candidates. Through pathogenicity evaluation in mice, we identified two promising candidates: an inactivated vaccine (rPR8-JGL16+2) and a live-attenuated vaccine (rPR8-JGL15+3). Both vaccines induced robust hemagglutination inhibition (HI) antibody responses and specific IgG levels against homologous strains. Notably, the attenuated rPR8-JGL15+3 vaccine provided complete protection against both homologous (H1N1) and heterologous (H3N2) viral challenges, with no detectable viral loads in the lungs or nasal turbinate. Although the inactivated rPR8-JGL16+2 vaccine exhibited effective protective efficacy against influenza viruses, it did not fully inhibit the replication of heterologous viruses in mice. Histopathological assessment revealed that rPR8-JGL15+3 immunization prevented significant lung damage, contrasting with the mild pathology observed in rPR8-JGL16+2-vaccinated animals. These findings demonstrate the successful development of novel vaccine candidates against avian-like H1N1 swIAV, with the attenuated vaccine showing promise for broad protection against circulating strains.
Nipah virus (NiV) is a highly pathogenic henipavirus responsible for recurrent outbreaks of severe encephalitis. This study aimed to address gaps in historical genomic data by characterizing NiV genomes recovered from archived central nervous system (CNS) tissues from the 1998-1999 Malaysian outbreak and evaluating viral evolution and intra-host genetic variation. We analyzed 18 NiV genomes obtained from archived CNS tissues. Whole-genome sequencing was performed, followed by phylogenetic reconstruction, comparative genomic analysis, and intra-host single nucleotide variant (iSNV) profiling. Paired CNS tissue samples from the individual patients were included to assess regional viral heterogeneity across distinct CNS tissues. All Malaysian NiV sequences formed a highly conserved, monophyletic clade (NiV-MY), distinct from the Bangladesh-India lineage (NiV-BD). Overall genomic diversity was low, with high amino acid conservation across the genome. Although intra-host variation was limited, however, paired CNS tissue samples from two patients contained closely related but non-identical genomes, differing by a single nucleotide in the attachment glycoprotein (G) gene, indicating localized genetic variation across distinct CNS tissues. NiV from the Malaysian outbreak demonstrated remarkable genomic conservation consistent with a single dominant introduction or a highly restricted set of closely related introductions. Nevertheless, the presence of limited intra-host variation highlights ongoing micro-evolution within the CNS and underscores the importance of continued genomic surveillance to better understand NiV evolutionary dynamics.
Influenza virus remains a major global health challenge due to its genetic variability and frequent emergence of novel strains. Subtyping is determined by the diverse arrangements of hemagglutinin (HA) and neuraminidase (NA) glycoproteins, with HA frequently serving as the molecular target for diagnostic assays. Conventional detection methods, however, are labor-intensive, require specialized expertise, and often lack adaptability to rapidly evolving viral variants. Aptamer-based biosensing technologies have emerged as promising alternatives. Aptamers, synthetic single-stranded DNA or RNA oligonucleotides generated via the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) process, exhibit exceptional specificity and high binding affinity, enabling precise recognition of viral proteins. This systematic and critical review synthesizes recent advances in aptamer-integrated biosensing platforms, focusing on electrochemical and optical detection strategies for influenza virus. By comparing sensitivity, specificity, operational simplicity, and translational potential, this review highlights that electrochemical platforms are better suited for point-of-care use due to their speed and simpler instrumentation, while optical platforms offer superior sensitivity for reference laboratory settings. A key finding is that despite two decades of research and remarkable analytical sensitivity (reaching fg/mL levels), the vast majority of platforms have not been validated on authentic clinical specimens or compared with gold-standard molecular methods, explaining why none have entered routine diagnostic workflows. The analysis provides evidence-based insights into which biosensing strategies are most suitable for the development of rapid, reliable, and scalable diagnostic tools against influenza virus, thereby informing future research directions and clinical translation.