Virus Evolution最新文献

Endogenous viral elements (EVEs) are remnants of viral genetic material endogenized into the host genome. They have, in the last decades, attracted attention for their role as potential contributors to pathogenesis, drivers of selective advantage for the host, and genomic remnants of ancient viruses. EVEs have a nuanced and complex influence on both host health and evolution, and can offer insights on the deep evolutionary history of viruses. As an emerging field of research, several factors limit a comprehensive understanding of EVEs: they are currently underestimated and periodically overlooked in studies of the host genome, transcriptome, and virome. The absence of standardized guidelines for ensuring EVE-related data availability and accessibility following the FAIR ('findable, accessible, interoperable, and reusable') principles obstructs our ability to gather and connect information. Here, we discuss challenges to the availability and accessibility of EVE-related data and propose potential solutions. We identified the biological and research focus imbalance between different types of EVEs, and their overall biological complexity as genomic loci with viral ancestry, as potential challenges that can be addressed with the development of a user-oriented identification tool. In addition, reports of EVE identification are scattered between different subfields under different keywords, and EVE sequences and associated data are not properly gathered in databases. While developing an open and dedicated database might be ideal, targeted improvements of generalist databases might provide a pragmatic solution to EVE data and metadata accessibility. The implementation of these solutions, as well as the collective effort by the EVE scientific community in discussing and setting guidelines, is now drastically needed to lead the development of EVE research and offer insights into host-virus interactions and their evolutionary history.

Influenza A and B viruses represent significant global health threats, contributing substantially to morbidity and mortality rates. However, a comprehensive understanding of the molecular epidemiology of these viruses in Brazil, a continental-size country and a crucial hub for the entry, circulation, and dissemination of influenza viruses within South America, still needs to be improved. This study addresses this gap by consolidating data and samples across all Brazilian macroregions, as part of the Center for Viral Surveillance and Serological Assessment project, together with an extensive number of other Brazilian sequences provided by a public database during the epidemic seasons spanning 2021-23. Phylogenetic analysis of the hemagglutinin segment of influenza A/H1N1pdm09, A/H3N2, and influenza B/Victoria-lineage viruses revealed that in 2021 and in the first semester of 2022, the A/H3N2 2a.3 strain was the predominant circulating strain. Subsequently, the A/H3N2 2b became the prevalent strain until October, when it was substituted by A/H1N1pdm09 5a.2a and 5a.2a.1 lineages. This scenario was maintained during the year of 2023. B/Victoria emerged and circulated at low levels between December 2021 and September 2022 and then became coprevalent with A/H1N1pdm09 5a.2a and 5a.2a.1 lineages. The comparison between the vaccine strain A/Darwin/9/2021 and circulating viruses revealed shared mutations to aspartic acid at residues 186 and 225 across all A/H3N2 lineages from 2021 to 2023, altering the charge in the receptor-binding domain. For A/H1N1pdm09, the 2022 consensus of 5a.2a.1 and the vaccine strain A/Victoria/2570/2019 showed 14 amino acid substitutions. Key residues H180, D187, K219, R223, E224, and T133 are involved in hydrogen interactions with sialic acids, while N130, K142, and D222 may contribute to distance interactions based on docking analyses. Importantly, distinct influenza A lineage frequency patterns were observed across Brazil's macroregions, underscoring the regional variations in virus circulation. This study characterizes influenza A and B viruses circulating in Brazil, providing insights into their circulation patterns and dynamics across Brazilian macroregions. These findings hold significant implications for public health interventions, informing strategies to mitigate transmission risks, optimize vaccination efforts, and enhance outbreak control measures.

The widespread use of antivirals in immunocompromised individuals has led to frequent occurrences of drug-resistant herpes simplex virus 1 (HSV-1) infections. Current antivirals target the viral DNA polymerase (DP), resulting in cross-resistance patterns that emphasize the need for novel treatment strategies. In this study, we assessed whether combining antivirals with different targets affects drug resistance emergence by passaging wild-type HSV-1 under increasing concentrations of acyclovir (ACV), foscarnet (phosphonoformic acid, PFA), or the helicase-primase inhibitor pritelivir (PTV), individually or in combination (ACV + PTV or PFA + PTV). The resistance selection procedure was initiated from two different drug concentrations for each condition. Deep sequencing and subsequent phenotyping showed the rapid acquisition of resistance mutations under monotherapy pressure, whereas combination therapy resulted in either no mutations or mutations conferring ACV and/or PFA resistance. Notably, mutations associated with PTV resistance were not detected after five passages under combination pressure. Strains resistant to both ACV and PTV were eventually obtained upon further passaging under ACV + PTV pressure initiated from lower drug concentrations. PFA + PTV dual treatment induced PFA resistance mutations in the DP, but PTV resistance mutations were not acquired, even after 15 passages. Our data suggest that combining the helicase-primase inhibitor PTV with a DP inhibitor may be an effective strategy to prevent drug resistance evolution in HSV-1.

Botswana, like the rest of the world, has been significantly impacted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In December 2022, we detected a monophyletic cluster of genomes comprising a sublineage of the Omicron variant of concern (VOC) designated as B.1.1.529.5.3.1.1.1.1.1.1.74.1 (alias FN.1, clade 22E). These genomes were sourced from both epidemiologically linked and unlinked samples collected in three close locations within the district of Greater Gaborone. In this study, we assessed the worldwide prevalence of the FN.1 lineage, evaluated its mutational profile, and conducted a phylogeographic analysis to reveal its global dispersal dynamics. Among approximately 16 million publicly available SARS-CoV-2 sequences generated by 30 September 2023, only 87 were of the FN.1 lineage, including 22 from Botswana, 6 from South Africa, and 59 from the UK. The estimated time to the most recent common ancestor of the 87 FN.1 sequences was 22 October 2022 [95% highest posterior density: 2 September 2022-24 November 2022], with the earliest of the 22 Botswana sequences having been sampled on 7 December 2022. Discrete trait reconstruction of FN.1 identified Botswana as the most probable place of origin. The FN.1 lineage is derived from the BQ.1.1 lineage and carries two missense variants in the spike protein, S:K182E in NTD and S:T478R in RDB. Among the over 90 SARS-CoV-2 lineages circulating in Botswana between September 2020 and July 2023, FN.1 was most closely related to BQ.1.1.74 based on maximum likelihood phylogenetic inference, differing only by the S:K182E mutation found in FN.1. Given the early detection of numerous novel variants from Botswana and its neighbouring countries, our study underscores the necessity of continuous surveillance to monitor the emergence of potential VOCs, integrating molecular and spatial data to identify dissemination patterns enhancing preparedness efforts.

The International Committee for the Taxonomy of Viruses (ICTV) regulates assignment and names of virus species and higher taxa through its taxonomy proposal and ratification process. Despite using similar taxonomic ranks to those used elsewhere in biology, the ICTV has maintained the principle that species and other taxa are strictly categories with a formal nomenclature, whereas the viruses as objects are referenced through a parallel inventory of community-assigned virus names. This is strikingly different from common and scientific name synonyms for species used elsewhere in biology. The recent introduction of binomial names for virus species resembling biological scientific names has intensified this confusion in terms within the virology community and beyond. The ICTV taxonomy furthermore does not engage with or regulate classification below species and consequently lacks taxonomic terms or descriptions for important viral pathogens such as polioviruses, severe acute respiratory syndrome coronavirus type 2, HIV-1, and avian influenza as examples. The consequent reliance on community-adopted virus names, genotypes, and other categories often lacks clarity for clinical, biocontainment, and other regulatory purposes. This article proposes a revision of rules and procedures for species and below-species level classification. It recasts virus and virus species names as 'common' and 'scientific' names that are used in other biology nomenclature codes, each with expanded reference to both object and taxon. It further advocates the creation of a formal below-species taxonomic rank to define a new inventory of approved taxa and specified nomenclature below species. Adoption of the proposed changes will realign virus taxonomy with other biological nomenclatural codes and provide greater transparency and clarity in virology, medical, and regulatory fields.

Interest in phage therapy-the use of bacterial viruses to treat infections-has increased recently because of the rise of infections with antibiotic-resistant bacteria and the failure to develop new antibiotics to treat those infections. Phages have shown therapeutic promise in recent work, and successful treatment minimally requires giving the patient a phage that will grow on their infecting bacterium. Although nature offers a bountiful and diverse supply of phages, there have been a surprising number of patient infections that could not be treated with phages because no suitable phage was found to kill the patient's bacterium. Here, we develop computational models to analyze an alternative approach to obtaining phages with new host ranges-directed evolution via laboratory propagation of phages to select mutants that can grow on a new host. The models separately explore alternative directed evolution protocols for phage variants that overcome three types of bacterial blocks to phage growth: a block in adsorption, temperate phage immunity to superinfection, and abortive infection. Protocols assume serial transfer to amplify pre-existing, small-effect mutants that are initially rare. Best protocols are sensitive to the nature of the block, and the models provide several insights for enhancing success specific to each case. A common result is that low dilution rates between transfers are beneficial in reducing the mutant growth rate needed to ascend. Selection to overcome an adsorption block is insensitive to many protocol variations but benefits from long selection times between transfers. A temperate phage selected to grow on its lysogens can evolve in any of three phenotypes, but a common protocol favors the desired changes in all three. Abortive infection appears to be the least amenable to evolving phage growth because it is prone to select phages that avoid infection.

Over a decade since its discovery, piscine myocarditis virus (PMCV) remains a significant pathogen in Atlantic salmon aquaculture. Despite this significant impact, the genomic landscape, evolutionary dynamics, and virulence factors of PMCV are poorly understood. This study enhances the existing PMCV sequence dataset by adding 34 genome sequences and 202 new ORF3 sequences from clinical cardiomyopathy syndrome (CMS) cases in Norwegian aquaculture. Phylogenetic analyses, also including sequences from the Faroe Islands and Ireland revealed that PMCV sequences are highly conserved with distinct clustering by country of origin. Still, single CMS outbreaks display multiple PMCV variants, and although some clustering was seen by case origin, occasional grouping of sequences from different cases was also apparent. Temporal data from selected cases indicated increased sequence diversity in the population. We hypothesize that multiple bottlenecks and changing infection dynamics in the host population, with transfer to naïve individuals over time, represent a continuous selection pressure on the virus populations. No clear relation was found between PMCV variants and the severity of heart pathology. However, specific non-synonymous and synonymous mutations that might impact protein function and gene expression efficiency were identified. An additional factor that may impact PMCV replication is the presence of defective viral genomes, a novel finding for viruses of the order Ghabrivirales. This study provides new insights into PMCV genomic characteristics and evolutionary dynamics, highlighting the complex interplay of genetic diversity, virulence markers, and host-pathogen interactions, underscoring the epidemiological complexity of the virus. Keywords: piscine myocarditis virus; evolutionary dynamics; diversity; phylogeny; genomic sequencing; defective viral genomes.

Viruses in the Secoviridae include monopartite and bipartite genomes, suggesting the possibility to study members of this family to experimentally address evolutionary transitions resulting in multipartitism. Torradoviruses are bipartite members of the family Secoviridae characterized by a genus-specific 5' open reading frame, named P21, encoded by RNA2. Here, in a study originally intended to verify if P21 can function in trans, we attempted to provide P21 from a third P21-expressing construct under control of the 35S promoter and containing the 5'- and 3'-untranslated regions (UTRs) of wild-type (WT) RNA2. When this construct was combined with an RNA2 with a complete deletion of the P21 coding region we verified that the P21 provided in trans cannot immediately complement the mutant, but occasional systemic infections in a limited number of the inoculated plants display the presence of a tripartite virus with an actively replicating P21-expressing RNA3. Furthermore, in all the systemically infected plants investigated in six distinct experiments, this replicating RNA3 accumulates deletions in a small region inside the original 3'-UTR provided by the cDNA clone. Such tripartite virus, which we obtained through deconstructing the coding potential of the RNA2 in two distinct RNAs, can be transmitted mechanically and by whiteflies, is competent for virion formation, and its RNA3 is encapsidated. It can be mechanically transferred for 11 serial passages without losing its infectivity or showing major genomic rearrangements. Furthermore, mixing equal amounts of WT and tripartite virus inocula in the same leaf resulted in plants systemically infected only with the WT virus, showing that the tripartite virus has lower fitness than the WT. To our knowledge, this is the first example of an engineered tripartite viral genome becoming stable through artificial evolution in vivo, in plants. This tripartite system was also used to derive a stable viral vector to express green fluorescence protein (GFP) systemically in the context of viral infection.

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

Public health researchers and practitioners commonly infer phylogenies from viral genome sequences to understand transmission dynamics and identify clusters of genetically-related samples. However, viruses that reassort or recombine violate phylogenetic assumptions and require more sophisticated methods. Even when phylogenies are appropriate, they can be unnecessary or difficult to interpret without specialty knowledge. For example, pairwise distances between sequences can be enough to identify clusters of related samples or assign new samples to existing phylogenetic clusters. In this work, we tested whether dimensionality reduction methods could capture known genetic groups within two human pathogenic viruses that cause substantial human morbidity and mortality and frequently reassort or recombine, respectively: seasonal influenza A/H3N2 and SARS-CoV-2. We applied principal component analysis, multidimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection to sequences with well-defined phylogenetic clades and either reassortment (H3N2) or recombination (SARS-CoV-2). For each low-dimensional embedding of sequences, we calculated the correlation between pairwise genetic and Euclidean distances in the embedding and applied a hierarchical clustering method to identify clusters in the embedding. We measured the accuracy of clusters compared to previously defined phylogenetic clades, reassortment clusters, or recombinant lineages. We found that MDS embeddings accurately represented pairwise genetic distances including the intermediate placement of recombinant SARS-CoV-2 lineages between parental lineages. Clusters from t-SNE embeddings accurately recapitulated known phylogenetic clades, H3N2 reassortment groups, and SARS-CoV-2 recombinant lineages. We show that simple statistical methods without a biological model can accurately represent known genetic relationships for relevant human pathogenic viruses. Our open source implementation of these methods for analysis of viral genome sequences can be easily applied when phylogenetic methods are either unnecessary or inappropriate.