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Although most mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome are expected to be either deleterious and swiftly purged or relatively neutral, a small proportion will affect functional properties and may alter infectivity, disease severity or interactions with host immunity. The emergence of SARS-CoV-2 in late 2019 was followed by a period of relative evolutionary stasis lasting about 11 months. Since late 2020, however, SARS-CoV-2 evolution has been characterized by the emergence of sets of mutations, in the context of ‘variants of concern’, that impact virus characteristics, including transmissibility and antigenicity, probably in response to the changing immune profile of the human population. There is emerging evidence of reduced neutralization of some SARS-CoV-2 variants by postvaccination serum; however, a greater understanding of correlates of protection is required to evaluate how this may impact vaccine effectiveness. Nonetheless, manufacturers are preparing platforms for a possible update of vaccine sequences, and it is crucial that surveillance of genetic and antigenic changes in the global virus population is done alongside experiments to elucidate the phenotypic impacts of mutations. In this Review, we summarize the literature on mutations of the SARS-CoV-2 spike protein, the primary antigen, focusing on their impacts on antigenicity and contextualizing them in the protein structure, and discuss them in the context of observed mutation frequencies in global sequence datasets.The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been characterized by the emergence of mutations and so-called variants of concern that impact virus characteristics, including transmissibility and antigenicity. In this Review, members of the COVID-19 Genomics UK (COG-UK) Consortium and colleagues summarize mutations of the SARS-CoV-2 spike protein, focusing on their impacts on antigenicity and contextualizing them in the protein structure, and discuss them in the context of observed mutation frequencies in global sequence datasets.

The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host. Current machine learning approaches to predicting virus host interactions have a tendency to focus on nucleotide features, ignoring other representations of genomic information. Here we investigate the predictive potential of features generated from four different 'levels' of viral genome representation: nucleotide, amino acid, amino acid properties and protein domains. This more fully exploits the biological information present in the virus genomes. Over a hundred and eighty binary datasets for infecting versus non-infecting viruses at all taxonomic ranks of both eukaryote and prokaryote hosts were compiled. The viral genomes were converted into the four different levels of genome representation and twenty feature sets were generated by extracting k-mer compositions and predicted protein domains. We trained and tested Support Vector Machine, SVM, classifiers to compare the predictive capacity of each of these feature sets for each dataset. Our results show that all levels of genome representation are consistently predictive of host taxonomy and that prediction k-mer composition improves with increasing k-mer length for all k-mer based features. Using a phylogenetically aware holdout method, we demonstrate that the predictive feature sets contain signals reflecting both the evolutionary relationship between the viruses infecting related hosts, and host-mimicry. Our results demonstrate that incorporating a range of complementary features, generated purely from virus genome sequences, leads to improved accuracy for a range of virus host prediction tasks enabling computational assignment of host taxonomic information.

Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses . In contrast, our analysis detects evidence for significant positive episodic diversifying selection acting at the base of the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. While an undiscovered “facilitating” intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human–human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus.

Monoclonal antibodies (mAbs) offer a treatment option for individuals with severe COVID-19 and are especially important in high-risk individuals where vaccination is not an option. Given the importance of understanding the evolution of resistance to mAbs by SARS-CoV-2, we reviewed the available in vitro neutralization data for mAbs against live variants and viral constructs containing spike mutations of interest. Unfortunately, evasion of mAb-induced protection is being reported with new SARS-CoV-2 variants. The magnitude of neutralization reduction varied greatly among mAb–variant pairs. For example, sotrovimab retained its neutralization capacity against Omicron BA.1 but showed reduced efficacy against BA.2, BA.4 and BA.5, and BA.2.12.1. At present, only bebtelovimab has been reported to retain its efficacy against all SARS-CoV-2 variants considered here. Resistance to mAb neutralization was dominated by the action of epitope single amino acid substitutions in the spike protein. Although not all observed epitope mutations result in increased mAb evasion, amino acid substitutions at non-epitope positions and combinations of mutations also contribute to evasion of neutralization. This Review highlights the implications for the rational design of viral genomic surveillance and factors to consider for the development of novel mAb therapies.In this Review, Carabelli, Robertson and colleagues explore data on the neutralization of globally circulating variants of concern by monoclonal antibodies (mAbs) and discuss how knowledge of the dynamics of viral evasion of mAbs can contribute to viral surveillance and the development of novel mAb treatments, as well as inform predictions of resistance that may arise in the future.

There are outstanding evolutionary questions on the recent emergence of human coronavirus SARS-CoV-2 including the role of reservoir species, the role of recombination and its time of divergence from animal viruses. We find that the sarbecoviruses—the viral subgenus containing SARS-CoV and SARS-CoV-2—undergo frequent recombination and exhibit spatially structured genetic diversity on a regional scale in China. SARS-CoV-2 itself is not a recombinant of any sarbecoviruses detected to date, and its receptor-binding motif, important for specificity to human ACE2 receptors, appears to be an ancestral trait shared with bat viruses and not one acquired recently via recombination. To employ phylogenetic dating methods, recombinant regions of a 68-genome sarbecovirus alignment were removed with three independent methods. Bayesian evolutionary rate and divergence date estimates were shown to be consistent for these three approaches and for two different prior specifications of evolutionary rates based on HCoV-OC43 and MERS-CoV. Divergence dates between SARS-CoV-2 and the bat sarbecovirus reservoir were estimated as 1948 (95% highest posterior density (HPD): 1879–1999), 1969 (95% HPD: 1930–2000) and 1982 (95% HPD: 1948–2009), indicating that the lineage giving rise to SARS-CoV-2 has been circulating unnoticed in bats for decades. In this manuscript, the authors address evolutionary questions on the emergence of SARS-CoV-2. They find that SARS-CoV-2 is not a recombinant of any sarbecoviruses detected to date, and that the bat and pangolin sequences most closely related to SARS-CoV-2 probably diverged several decades ago or possibly earlier from human SARS-CoV-2 samples.

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., “arboviruses”), infecting a certain type of host (e.g., “mycoviruses,” “bacteriophages”) or displaying specific pathogenicity (e.g., “human immunodeficiency viruses”), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep learning method that predicts the host species for viruses from viral sequences only. It also identifies important viral proteins that significantly contribute to host prediction. The method combines a pre-trained large protein language model (ESM) and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than sequence composition features, including amino acids, physiochemical properties, and DNA k-mers. In multi-host prediction tasks, EvoMIL achieves median F1 score improvements of 10.8%, 16.2%, and 4.9% in prokaryotic hosts, and 1.7%, 6.6% and 11.5% in eukaryotic hosts. EvoMIL binary classifiers achieve impressive AUC over 0.95 for all prokaryotic hosts and range from roughly 0.8 to 0.9 for eukaryotic hosts. Furthermore, EvoMIL identifies important proteins in the prediction task, capturing key functions involved in virus-host specificity.

The interleukin-1 (IL-1) receptor and ligand families are components of the immune system. Knowledge of their evolutionary history is essential to understand their function. Using chromosomal anatomy and sequence similarity, we show that IL-1 receptor family members are related and nine members are likely formed from duplication and modification of a proto-IL-1R1 receptor. The IL-1 ligands have a different evolutionary history. The first proto-IL-1β gene coincided with proto-IL-1R1 and duplication events resulted in the majority of IL-1 ligand family members. However, large evolutionary distances are observed for IL-1α, IL-18 and IL-33 proteins. Further analysis show that IL-33 and IL-18 have poor sequence similarity and no chromosomal evidence of common ancestry with the IL-1β cluster and therefore should not be included in the IL-1 ligand ancestral family. IL-1α formed from the duplication of IL-1β, and moonlighting functions of pro-IL-1α acted as divergent selection pressures for the observed sequence dissimilarity. The IL-1 evolutionary history is essential in our understanding of function and development. Here the authors use molecular phylogenetic analysis to probe the IL-1 family in a range of species, suggesting disparate phylogenetic association of IL-18 and IL-33 proteins within the IL-1 family.

This article reports changes to virus taxonomy and taxon nomenclature that were approved and ratified by the International Committee on Taxonomy of Viruses (ICTV) in April 2023. The entire ICTV membership was invited to vote on 174 taxonomic proposals that had been approved by the ICTV Executive Committee in July 2022, as well as a proposed revision of the ICTV Statutes. All proposals and the revised ICTV Statutes were approved by a majority of the voting membership. Of note, the ICTV continued the process of renaming existing species in accordance with the recently mandated binomial format and included gene transfer agents (GTAs) in the classification framework by classifying them as viriforms. In total, one class, seven orders, 31 families, 214 genera, and 858 species were created.