Virus Evolution最新文献

[This corrects the article DOI: 10.1093/ve/veac022.].

While intra-host evolution of arboviruses in mosquitoes has been documented, studies of insect-specific viruses (ISVs) remain limited. This study examines evolutionary patterns [i.e. evolutionary process, mutational types (synonymous/nonsynonymous)] of the cell-fusing agent virus (CFAV), an ISV that infects adult Aedes aegypti, over a period of 21 days post-infection (dpi), with a focus on the relationship between viral population dynamics and genetic diversity. High-throughput sequencing of amplification products covering the entire viral genome revealed a significant positive correlation of CFAV genetic diversity with viral population size and natural selection ([Formula: see text]/[Formula: see text]). Notably, diversity for both synonymous and nonsynonymous single nucleotide variant (SNV) sites displayed a positive correlation with population size and natural selection suggesting that genetic drift and purifying selection contribute to the overall outcome of genetic diversity. Additionally, we confirmed that smaller viral population sizes lead to greater temporal changes in genetic structure, particularly evident between Day 1 dpi and Day 3 dpi when genetic drift was most pronounced. We found that non-structural (NS) genes accumulated a higher frequency of synonymous SNV sites than structural genes, likely due to reduced selection pressure acting on NS genes. In contrast, structural genes, particularly the E gene, are likely to exhibit strong selective pressure, as indicated by a significant frequency of nonsynonymous SNV sites. Overall, this study elucidated the evolutionary patterns of CFAV, highlighting the roles of reduced genetic drift as influenced by population size and purifying selection in shaping the overall genetic diversity-and possibly adaptive evolution within structural genes, such as the E gene.

To comprehend the time of emergence and extent of cryptic circulation for Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) in Thailand, plasma specimens collected from patients at Siriraj Hospital, Bangkok, Thailand presenting with acute undifferentiated febrile illness (AUFI) were characterized by next-generation sequencing (NGS). Molecular and serological diagnostics were developed to screen for viral RNA and antibodies. Phylogenetic and phylogeographic analyses were performed using sequences generated from this study, publicly available genomes, and unsampled taxa to enhance temporal and geographic resolution. NGS detected SFTSV in 7 individuals with a median age of 73 years. Clinical manifestations ranged from low-grade fever and altered consciousness to multi-organ failure and death. RT-qPCR revealed three additional RNA positives, and antibody screening identified 38 IgG-positives for an incidence and prevalence of 0.4% and 2.7%, respectively. While SFTSV is reported as having been introduced into Thailand in 2019, evidence of infections dates back to 2012. Phylogenetic analyses revealed multiple introductions of Lineage 2 into Thailand around 2011-12, and phylogeographic reconstructions identified Thailand as a source for SFTSV spread to China and neighbouring countries. SFTSV has circulated cryptically in Thailand since 2012, diversifying locally and establishing endemicity. Genomic surveillance through improved diagnostics will be necessary to curb its spread through Asia and beyond.

Newcastle disease (ND), caused by virulent strains of avian paramyxovirus type-1 (APMV-1), is one of the most important poultry diseases globally due to its economic impact and endemicity in lower- and middle-income countries. A variant of APMV-1 is endemic in Columbiformes (pigeons and doves) worldwide and is commonly termed pigeon paramyxovirus-1 (PPMV-1). Since its initial detection in the 1980s, PPMV-1 has caused numerous ND outbreaks in poultry, including in high-income countries, and was the causative agent for the last ND outbreak in the British Isles in 2006. Here, we have undertaken sequencing of PPMV-1 isolates between 1983 and 2023 and define three distinct genotypes of PPMV-1 being present in the British Isles. Analysis of the contemporary VI.2.1.1.2.2 genotype, demonstrated likely incursion from mainland Europe, whilst this genotype has subsequently spread across China, with detections also occurring in Australia. The presence of a virulent fusion-gene cleavage site in sequences highlights the continued risk to poultry from PPMV-1 genotypes, which were detected in pigeons and doves across the British Isles.

Since late 2020, the emergence of variants of concern (VOCs) of SARS-CoV-2 has been of concern to public health, researchers and policymakers. Mutations in the SARS-CoV-2 genome-for which clear evidence is available indicating a significant impact on transmissibility, severity and/or immunity-illustrate the importance of genomic surveillance and monitoring the evolution and geographic spread of novel lineages. Lineage B.1.619 was first detected in Switzerland in January 2021, in international travellers returning from Cameroon. This lineage was subsequently also detected in Rwanda, Belgium, Cameroon, France, and many other countries and is characterised by spike protein amino acid mutations N440K and E484K in the receptor binding domain, which are associated with immune escape and higher infectiousness. In this study, we perform a phylogeographic analysis to track the geographic origin and subsequent dispersal of SARS-CoV-2 lineage B.1.619. We employ a recently developed travel history-aware phylogeographic model, enabling us to incorporate genomic sequences with associated travel information. We estimate that B.1.619 most likely originated in Cameroon, in November 2020. We estimate the influence of the number of air-traffic passengers on the dispersal of B.1.619 but find no significant effect, illustrative of the complex dispersal patterns of SARS-CoV-2 lineages. Finally, we examine the metadata associated with infected Belgian patients and report a wide range of symptoms and medical interventions.

Varicella-zoster virus (VZV), a highly contagious α-herpesvirus, causes chickenpox and shingles. Although vaccines have been widely deployed, breakthrough infections still occur occasionally. Therefore, genomic surveillance of VZV remains essential. This study collected samples from 28 VZV-infected patients in Beijing, generating 25 complete viral genome sequences. These strains exhibited high genomic similarity and all belonged to Clade 2, which we further subdivided into five subclades with distinct characteristic variants. Most newly sequenced strains carried the A20795T (gC: Ser107Thr) mutation and were classified as Clade 2b.4. Recombination analysis identified 32 putative recombination events, including both inter- and intra-clade types. Genes with diverse functions are under differential selective pressures, with 3-20 positively selected sites detected in ORF17, ORF33, ORF33.5, and ORF14 (gC). These findings on new subclades, frequent recombination, and rapidly changing genes crucial for viral adaptation are important for controlling future outbreaks and improving vaccine effectiveness. The research provided critical resources for investigating VZV genomic evolution in Beijing and to offer new insights into viral evolution and transmission patterns for public health initiatives.

Foot-and-mouth disease (FMD), a highly contagious viral infection affecting cloven-hoofed animals, has significant implications for global livestock production and trade. In this study, we aimed to characterize and describe dispersal patterns and factors affecting pool 4 serotypes of FMD viruses (FMDVs) in the East and Horn of Africa. The study area included 12 countries, i.e. Sudan, South Sudan, Eritrea, Djibouti, Ethiopia, Somalia (Horn of Africa) and Kenya, Uganda, Tanzania, Rwanda, Burundi, and Malawi (East Africa); 1423 VP1 sequence data were used (224 serotype A, 593 serotype O, 310 SAT1, and 296 SAT2), obtained from the National Center for Biotechnology Information (NCBI) GenBank database. Using continuous and discrete space phylogeographic models in BEAST, we assessed viral dispersal, population dynamics, direction, and velocity modelled against environmental, human, and livestock demographic and trade data as raster files. We observed a rise in accessible sequences in the last decade, signifying enhanced surveillance and research endeavours but emphasizing the need for rigorous analyses to address biases, ensuring comprehensive data collection for precise phylogeographic inference, and highlighting the importance of genomic surveillance given the geographical imbalance pre-1970. Higher precipitation correlated with increased dispersal velocity for certain serotypes, while elevation influenced the direction of viral spread. Proximity to human and livestock populations, i.e. urbanization and agricultural activities, also influenced spatial transmission dynamics. We identified distinct viral clusters with Kenya and Sudan as major sources for intercountry spread in the East and Northern regions, respectively. Regional collaboration, data sharing, and targeted surveillance, informed by genomic data and environmental factors, can aid in early outbreak detection and management.

Acute viral infections pose significant public health challenges. Since viral evolution, immune escape, and infection severity are influenced by how viruses spread between hosts, understanding transmission bottlenecks is crucial for predicting disease dynamics and developing effective control strategies. Transmission bottlenecks reduce viral population size and genetic diversity as the virus spreads to new hosts. Bottleneck size, defined as the number of viral individuals successfully establishing infection in a new host, varies across transmission events and can influence disease emergence and virus evolution. In this study, we introduce ViralBottleneck, an R package integrating six established methods for estimating transmission bottleneck size: the presence-absence method, Kullback-Leibler (KL) method, binomial method, two versions of the beta-binomial method, and the Wright-Fisher method. We demonstrate the package's functionality using simulated datasets generated with SANTA-Sim under different scenarios with known bottleneck sizes. Our results reveal considerable variation in estimates across methods, highlighting the impact of methodological choice on bottleneck size estimation. The code and associated tutorial are available at https://github.com/BowenArchaman/ViralBottleneck.

Influenza A viruses remain a persistent public health concern due to their extensive genomic diversity and seasonality. Among the mechanisms driving their evolution, reassortment plays a pivotal role by facilitating the exchange of gene segments between co-infecting viruses, leading to novel viral genotypes. This mechanism contributes to pandemic strains, such as the 2009 H1N1 pandemic (H1N1pdm), and affects seasonal influenza by introducing genetic changes with potential impacts on viral traits and clinical outcomes. Comprehensive reassortment analysis is therefore critical for better understanding the mechanisms underlying influenza virus evolution and their potential impact on public health. A new visualization tool, Crossing lines Annotating with Tanglegrams on Trees (CatTrees), was designed to enhance the presentation of reassortment events in multiple phylogenetic trees. To facilitate this workflow, we developed the Virus Data Analysis Toolkit (VIDA), a modular Python toolkit that automates and standardizes viral sequence preprocessing and downstream analyses. This integrated approach was successfully applied to whole genomes of influenza A(H1N1)pdm from 2019 to 2023. Notably, a novel group named reassortment 6B.1A.5a.1 (in short, re6B.1A.5a.1 or re5a.1) emerged during the 2020-21 season and became dominant in the Netherlands, France, Togo, South Africa, and Kenya in 2021-22, eventually replacing the original clade 6B.1A.5a.1 in the 2022-23 season. Three reassortment patterns were observed, in which clade 6B.1A.5a.1 reassorted with clades 6B.1A.5a and 6B.1A.5a.2. These patterns shed light on the ongoing evolution of influenza viruses.

Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007-2008 Swedish HIV-1 outbreak and the broader 1998-2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at https://github.com/MolEvolEpid/SEEPS.