A Bayesian approach to infer recombination patterns in coronaviruses

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed less than a decade prior to their emergence in humans. Phylogeographic analyses show bat sarbecoviruses traveled at rates approximating their horseshoe bat hosts and circulated in Asia for millennia. We find that the direct ancestors of SARS-CoV and SARS-CoV-2 are unlikely to have reached their respective sites of emergence via dispersal in the bat reservoir alone, supporting interactions with intermediate hosts through wildlife trade playing a role in zoonotic spillover. These results can guide future sampling efforts and demonstrate that viral genomic regions extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

Phylodynamics and phylogeography of watermelon mosaic virus: Multiple local invasion routes in southern France and recombination-driven limits to global analysis

Watermelon mosaic virus (WMV) is a major plant pathogen, infecting over 170 plant species, including cucurbits and legumes. Though mostly propagated locally by aphids in a non-persistent manner, long-range dispersal can occur through human-induced plant or vector movements. Understanding patterns of local and global spread of WMV is crucial to help formulate adequate control strategies. We used phylodynamic methods based on partial and whole-genome sequences collected in France between 2000 and 2017 to reconstruct the introduction of new lineages in the past 30 years and their subsequent diffusion in the country. We identified at least 11 different introduction events, hailing from different parts of the global diversity of WMV, highlighting the critical role international exchanges play in the spread of plant pathogens. For three of these lineages, we estimated the time and location of their introduction in the mid-1990s in the south of France and the speed at which they spread in this specific landscape. We also showed that the highly recombinogenic nature of WMV, as with most potyviruses, makes the use of whole genomes necessary to classify these viruses on a global scale and must be taken into consideration to reconstruct viral evolutionary history. Our results demonstrate how genomic sequencing of plant viruses can help reconstruct specific viral outbreaks and understand global circulation patterns of plant pathogens.

SARS-CoV-2: The Interplay Between Evolution and Host Immunity

The persistence of SARS-CoV-2 infections at a global level reflects the repeated emergence of variant strains encoding unique constellations of mutations. These variants have been generated principally because of a dynamic host immune landscape, the countermeasures deployed to combat disease, and selection for enhanced infection of the upper airway and respiratory transmission. The resulting viral diversity creates a challenge for vaccination efforts to maintain efficacy, especially regarding humoral aspects of protection. Here, we review our understanding of how SARS-CoV-2 has evolved during the pandemic, the immune mechanisms that confer protection, and the impact viral evolution has had on transmissibility and adaptive immunity elicited by natural infection and/or vaccination. Evidence suggests that SARS-CoV-2 evolution initially selected variants with increased transmissibility but currently is driven by immune escape. The virus likely will continue to drift to maintain fitness until countermeasures capable of disrupting transmission cycles become widely available.

Leveraging graphical model techniques to study evolution on phylogenetic networks

The evolution of molecular and phenotypic traits is commonly modelled using Markov processes along a phylogeny. This phylogeny can be a tree, or a network if it includes reticulations, representing events such as hybridization or admixture. Computing the likelihood of data observed at the leaves is costly as the size and complexity of the phylogeny grows. Efficient algorithms exist for trees, but cannot be applied to networks. We show that a vast array of models for trait evolution along phylogenetic networks can be reformulated as graphical models, for which efficient belief propagation algorithms exist. We provide a brief review of belief propagation on general graphical models, then focus on linear Gaussian models for continuous traits. We show how belief propagation techniques can be applied for exact or approximate (but more scalable) likelihood and gradient calculations, and prove novel results for efficient parameter inference of some models. We highlight the possible fruitful interactions between graphical models and phylogenetic methods. For example, approximate likelihood approaches have the potential to greatly reduce computational costs for phylogenies with reticulations.This article is part of the theme issue '"A mathematical theory of evolution": phylogenetic models dating back 100 years'.

Phylogeographic Characterizations of Recent (2015-2023) Senecavirus A Isolates from Canada

Senecavirus A (SVA) continues to cause vesicular lesions in swine in Canada and many regions worldwide. Since the vesicular lesions caused by SVA are similar to those caused by foot and mouth disease virus, swine vesicular disease virus and vesicular stomatitis virus, a foreign animal disease investigation must be initiated to rule out these diseases. SVA isolates from pigs displaying vesicular lesions in Canada from 2015 to 2023 were sequenced, and phylogeographic analysis was performed using the complete genome sequences. The results infer that SVA has spread between the United States and Canada several times. In addition, the results suggest that SVA spreads from different regions. SVA spread was inferred from Canada into Thailand, India and Mexico and inferred from the United States to Brazil, Columbia, Chile and China with ten separate introductions. Furthermore, recombination was observed in SVA genomes from Canada, the United States and China.

Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2

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.

Discordant phylodynamic and spatiotemporal transmission patterns driving the long-term persistence and evolution of human coronaviruses

Four distinct species of human coronaviruses (HCoVs) circulate in humans. Despite the recent attention due to SARS-CoV-2, a comprehensive understanding of the molecular epidemiology and genomic evolution of HCoVs remains unclear. Here, we employed primary differentiated human nasal epithelial cells for the successful isolation and genome sequencing of HCoVs derived from two retrospective cohorts in Singapore and Tanzania. Phylodynamic inference shows that HCoV-229E and HCoV-OC43 were subject to stronger genetic drift and reduced purifying selection from the early 2000s onwards, primarily targeting spike Domain A and B. This resulted in increased lineage diversification, coinciding with a higher effective reproductive number (Re>1.0). However, HCoV-NL63 and HCoV-HKU1 experienced weaker genetic drift and selective pressure with prolonged regional persistence. Our findings suggest that HCoV-229E and HCoV-OC43 viruses are adept at generating new variants and achieving widespread intercontinental dissemination driven by continuous genetic drift, recombination, and complex migration patterns.

The evolutionary and transmission dynamics of HIV-1 CRF08_BC

HIV-1 CRF08_BC is a significant subtype in China, though its origin and spread remain incompletely understood. Previous studies using partial genomic data have provided insights but lack comprehensive analysis. Here, we investigate the early evolutionary and spatiotemporal dynamics of HIV-1 CRF08_BC in China and Myanmar using near-complete genome sequences. We analyzed 28 near-complete HIV-1 CRF08_BC genomes from China and Myanmar (1997-2013). Phylogenetic, molecular clock, and Bayesian discrete trait analyses were performed to infer the virus's origin, spread, and associated risk groups. Based on Bayesian time-scaled inference with the best-fitting combination of models determined by marginal likelihood estimation (MLE), we inferred the time to the most recent common ancestor (TMRCA) and evolutionary rate of HIV-1 CRF08_BC to be at 3 October 1991 (95% HPD: 22 February1989-27 November 1993) and 2.30 × 10-3 substitutions per site per year (95% HPD: 1.96 × 10-3-2.63 × 10-3), respectively. Our analysis suggests that HIV-1 CRF08_BC originated in Yunnan Province, China, among injecting drug users, and subsequently spread to other regions. This study provides valuable insights into the early dynamics of HIV-1 CRF08_BC through combined genomic and epidemiological data, which may inform effective prevention and mitigation efforts. However, the limited genomic data influenced the extent of our findings, and challenges in collecting accurate risk group information during surveillance were evident.

Dimensionality reduction distills complex evolutionary relationships in seasonal influenza and SARS-CoV-2

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 (PCA), multidimensional scaling (MDS), t-distributed stochastic neighbor embedding (t-SNE), and uniform manifold approximation and projection (UMAP) 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.

Whole-genome demography of COVID-19 virus during its pandemic period and on "panvalent" vaccine design

With over 16 million submitted genomic sequences, the SARS-CoV-2 (SC2) virus, the cause of the most recent worldwide COVID-19 pandemic, has become the most sequenced genome of all known viruses, revealing, for example, a vast number of expanding viral lineages. Since the pandemic phase appears to be over, we performed a retrospective re-examination of the demographic grouping pattern and their genomic characteristics during the entire pandemic period up to the peak of the last pandemic wave. For our study, we extracted from the NCBI only unique viral sequences and converted each sequence data to a relational vector, indicating the presence/absence of each variational event compared to a "reference" sequence. Our study revealed several genomic features that are unexpected or different from those of previous studies. For example, approximately 44,000 variants with unique sequences emerged during the pandemic period; they group into only four major viral-genomic groups and each has a set of mostly unique highly-conserved variant-genotypes (HCVGs); and a small set from the first ("ancestral") group was inherited by the three ("descendant") groups, suggesting that HCVGs in the next group may be predictable from the current group(s). Such a concept may be potentially important in designing "panvalent" vaccines against the current and future waves of viral infections.

Seasonal human coronaviruses OC43, 229E, and NL63 induce cell surface modulation of entry receptors and display host cell-specific viral replication kinetics

The emergence of the COVID-19 pandemic prompted an increased interest in seasonal human coronaviruses. OC43, 229E, NL63, and HKU1 are endemic seasonal coronaviruses that cause the common cold and are associated with generally mild respiratory symptoms. In this study, we identified cell lines that exhibited cytopathic effects (CPE) upon infection by three of these coronaviruses and characterized their viral replication kinetics and the effect of infection on host surface receptor expression. We found that NL63 produced CPE in LLC-MK2 cells, while OC43 produced CPE in MRC-5, HCT-8, and WI-38 cell lines, while 229E produced CPE in MRC-5 and WI-38 by day 3 post-infection. We observed a sharp increase in nucleocapsid and spike viral RNA (vRNA) from day 3 to day 5 post-infection for all viruses; however, the abundance and the proportion of vRNA copies measured in the supernatants and cell lysates of infected cells varied considerably depending on the virus-host cell pair. Importantly, we observed modulation of coronavirus entry and attachment receptors upon infection. Infection with 229E and OC43 led to a downregulation of CD13 and GD3, respectively. In contrast, infection with NL63 and OC43 leads to an increase in ACE2 expression. Attempts to block entry of NL63 using either soluble ACE2 or anti-ACE2 monoclonal antibodies demonstrated the potential of these strategies to greatly reduce infection. Overall, our results enable a better understanding of seasonal coronaviruses infection kinetics in permissive cell lines and reveal entry receptor modulation that may have implications in facilitating co-infections with multiple coronaviruses in humans.IMPORTANCESeasonal human coronavirus is an important cause of the common cold associated with generally mild upper respiratory tract infections that can result in respiratory complications for some individuals. There are no vaccines available for these viruses, with only limited antiviral therapeutic options to treat the most severe cases. A better understanding of how these viruses interact with host cells is essential to identify new strategies to prevent infection-related complications. By analyzing viral replication kinetics in different permissive cell lines, we find that cell-dependent host factors influence how viral genes are expressed and virus particles released. We also analyzed entry receptor expression on infected cells and found that these can be up- or down-modulated depending on the infecting coronavirus. Our findings raise concerns over the possibility of infection enhancement upon co-infection by some coronaviruses, which may facilitate genetic recombination and the emergence of new variants and strains.

Data-driven recombination detection in viral genomes

Recombination is a key molecular mechanism for the evolution and adaptation of viruses. The first recombinant SARS-CoV-2 genomes were recognized in 2021; as of today, more than ninety SARS-CoV-2 lineages are designated as recombinant. In the wake of the COVID-19 pandemic, several methods for detecting recombination in SARS-CoV-2 have been proposed; however, none could faithfully confirm manual analyses by experts in the field. We hereby present RecombinHunt, an original data-driven method for the identification of recombinant genomes, capable of recognizing recombinant SARS-CoV-2 genomes (or lineages) with one or two breakpoints with high accuracy and within reduced turn-around times. ReconbinHunt shows high specificity and sensitivity, compares favorably with other state-of-the-art methods, and faithfully confirms manual analyses by experts. RecombinHunt identifies recombinant viral genomes from the recent monkeypox epidemic in high concordance with manually curated analyses by experts, suggesting that our approach is robust and can be applied to any epidemic/pandemic virus.

Assessing the emergence time of SARS-CoV-2 zoonotic spillover

Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.

SARS-CoV-2 biology and host interactions

The zoonotic emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the ensuing coronavirus disease 2019 (COVID-19) pandemic have profoundly affected our society. The rapid spread and continuous evolution of new SARS-CoV-2 variants continue to threaten global public health. Recent scientific advances have dissected many of the molecular and cellular mechanisms involved in coronavirus infections, and large-scale screens have uncovered novel host-cell factors that are vitally important for the virus life cycle. In this Review, we provide an updated summary of the SARS-CoV-2 life cycle, gene function and virus-host interactions, including recent landmark findings on general aspects of coronavirus biology and newly discovered host factors necessary for virus replication.

Genetic characterization and pathogenicity in a mouse model of newly isolated bat-originated mammalian orthoreovirus in South Korea

Mammalian orthoreoviruses (MRVs) infect a wide range of hosts, including humans, livestock, and wildlife. In the present study, we isolated a novel Mammalian orthoreovirus from the intestine of a microbat (Myotis aurascens) and investigated its biological and pathological characteristics. Phylogenetic analysis indicated that the new isolate was serotype 2, sharing the segments with those from different hosts. Our results showed that it can infect a wide range of cell lines from different mammalian species, including human, swine, and non-human primate cell lines. Additionally, media containing trypsin, yeast extract, and tryptose phosphate broth promoted virus propagation in primate cell lines and most human cell lines, but not in A549 and porcine cell lines. Mice infected with this strain via the intranasal route, but not via the oral route, exhibited weight loss and respiratory distress. The virus is distributed in a broad range of organs and causes lung damage. In vitro and in vivo experiments also suggested that the new virus could be a neurotropic infectious strain that can infect a neuroblastoma cell line and replicate in the brains of infected mice. Additionally, it caused a delayed immune response, as indicated by the high expression levels of cytokines and chemokines only at 14 days post-infection (dpi). These data provide an important understanding of the genetics and pathogenicity of mammalian orthoreoviruses in bats at risk of spillover infections.IMPORTANCEMammalian orthoreoviruses (MRVs) have a broad range of hosts and can cause serious respiratory and gastroenteritis diseases in humans and livestock. Some strains infect the central nervous system, causing severe encephalitis. In this study, we identified BatMRV2/SNU1/Korea/2021, a reassortment of MRV serotype 2, isolated from bats with broad tissue tropism, including the neurological system. In addition, it has been shown to cause respiratory syndrome in mouse models. The given data will provide more evidence of the risk of mammalian orthoreovirus transmission from wildlife to various animal species and the sources of spillover infections.

Espalier: Efficient Tree Reconciliation and Ancestral Recombination Graphs Reconstruction Using Maximum Agreement Forests

In the presence of recombination individuals may inherit different regions of their genome from different ancestors, resulting in a mosaic of phylogenetic histories across their genome. Ancestral recombination graphs (ARGs) can capture how phylogenetic relationships vary across the genome due to recombination, but reconstructing ARGs from genomic sequence data is notoriously difficult. Here, we present a method for reconciling discordant phylogenetic trees and reconstructing ARGs using maximum agreement forests (MAFs). Given two discordant trees, a MAF identifies the smallest possible set of topologically concordant subtrees present in both trees. We show how discordant trees can be reconciled through their MAF in a way that retains discordances strongly supported by sequence data while eliminating conflicts likely attributable to phylogenetic noise. We further show how MAFs and our reconciliation approach can be combined to select a path of local trees across the genome that maximizes the likelihood of the genomic sequence data, minimizes discordance between neighboring local trees, and identifies the recombination events necessary to explain remaining discordances to obtain a fully connected ARG. While heuristic, our ARG reconstruction approach is often as accurate as more exact methods while being much more computationally efficient. Moreover, important demographic parameters such as recombination rates can be accurately estimated from reconstructed ARGs. Finally, we apply our approach to plant infecting RNA viruses in the genus Potyvirus to demonstrate how true recombination events can be disentangled from phylogenetic noise using our ARG reconstruction methods.

The effects of amino acid substitution of spike protein and genomic recombination on the evolution of SARS-CoV-2

Over three years' pandemic of 2019 novel coronavirus disease (COVID-19), multiple variants and novel subvariants have emerged successively, outcompeted earlier variants and become predominant. The sequential emergence of variants reflects the evolutionary process of mutation-selection-adaption of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Amino acid substitution/insertion/deletion in the spike protein causes altered viral antigenicity, transmissibility, and pathogenicity of SARS-CoV-2. Early in the pandemic, D614G mutation conferred virus with advantages over previous variants and increased transmissibility, and it also laid a conservative background for subsequent substantial mutations. The role of genomic recombination in the evolution of SARS-CoV-2 raised increasing concern with the occurrence of novel recombinants such as Deltacron, XBB.1.5, XBB.1.9.1, and XBB.1.16 in the late phase of pandemic. Co-circulation of different variants and co-infection in immunocompromised patients accelerate the emergence of recombinants. Surveillance for SARS-CoV-2 genomic variations, particularly spike protein mutation and recombination, is essential to identify ongoing changes in the viral genome and antigenic epitopes and thus leads to the development of new vaccine strategies and interventions.

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just ~1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

A fast and scalable method for inferring phylogenetic networks from trees by aligning lineage taxon strings

The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the minimum phylogenetic network problem, in which phylogenetic trees are first inferred, and then the smallest phylogenetic network that displays all the trees is computed. The approach takes advantage of the fact that the theory of phylogenetic trees is mature, and there are excellent tools available for inferring phylogenetic trees from a large number of biomolecular sequences. A tree-child network is a phylogenetic network satisfying the condition that every nonleaf node has at least one child that is of indegree one. Here, we develop a new method that infers the minimum tree-child network by aligning lineage taxon strings in the phylogenetic trees. This algorithmic innovation enables us to get around the limitations of the existing programs for phylogenetic network inference. Our new program, named ALTS, is fast enough to infer a tree-child network with a large number of reticulations for a set of up to 50 phylogenetic trees with 50 taxa that have only trivial common clusters in about a quarter of an hour on average.

A comprehensive survey of bat sarbecoviruses across China in relation to the origins of SARS-CoV and SARS-CoV-2

SARS-CoV and SARS-CoV-2 have been thought to originate from bats. In this study, we screened pharyngeal and anal swabs from 13 064 bats collected between 2016 and 2021 at 703 locations across China for sarbecoviruses, covering almost all known southern hotspots, and found 146 new bat sarbecoviruses. Phylogenetic analyses of all available sarbecoviruses show that there are three different lineages-L1 as SARS-CoV-related CoVs (SARSr-CoVs), L2 as SARS-CoV-2-related CoVs (SC2r-CoVs) and novel L-R (recombinants of L1 and L2)-present in Rhinolophus pusillus bats, in the mainland of China. Among the 146 sequences, only four are L-Rs. Importantly, none belong in the L2 lineage, indicating that circulation of SC2r-CoVs in China might be very limited. All remaining 142 sequences belong in the L1 lineage, of which YN2020B-G shares the highest overall sequence identity with SARS-CoV (95.8%). The observation suggests endemic circulations of SARSr-CoVs, but not SC2r-CoVs, in bats in China. Geographic analysis of the collection sites in this study, together with all published reports, indicates that SC2r-CoVs may be mainly present in bats of Southeast Asia, including the southern border of Yunnan province, but absent in all other regions within China. In contrast, SARSr-CoVs appear to have broader geographic distribution, with the highest genetic diversity and sequence identity to human sarbecoviruses along the southwest border of China. Our data provide the rationale for further extensive surveys in broader geographical regions within, and beyond, Southeast Asia in order to find the most recent ancestors of human sarbecoviruses.

PF-D-Trimer, a protective SARS-CoV-2 subunit vaccine: immunogenicity and application

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has had and continues to have a significant impact on global public health. One of the characteristics of SARS-CoV-2 is a surface homotrimeric spike protein, which is primarily responsible for the host immune response upon infection. Here we present the preclinical studies of a broadly protective SARS-CoV-2 subunit vaccine developed from our trimer domain platform using the Delta spike protein, from antigen design through purification, vaccine evaluation and manufacturability. The pre-fusion trimerized Delta spike protein, PF-D-Trimer, was highly expressed in Chinese hamster ovary (CHO) cells, purified by a rapid one-step anti-Trimer Domain monoclonal antibody immunoaffinity process and prepared as a vaccine formulation with an adjuvant. Immunogenicity studies have shown that this vaccine candidate induces robust immune responses in mouse, rat and Syrian hamster models. It also protects K18-hACE2 transgenic mice in a homologous viral challenge. Neutralizing antibodies induced by this vaccine show cross-reactivity against the ancestral WA1, Delta and several Omicrons, including BA.5.2. The formulated PF-D Trimer is stable for up to six months without refrigeration. The Trimer Domain platform was proven to be a key technology in the rapid production of PF-D-Trimer vaccine and may be crucial to accelerate the development and accessibility of updated versions of SARS-CoV-2 vaccines.

Using Haplotype-Based Artificial Intelligence to Evaluate SARS-CoV-2 Novel Variants and Mutations

Importance

Earlier detection of emerging novel SARS-COV-2 variants is important for public health surveillance of potential viral threats and for earlier prevention research. Artificial intelligence may facilitate early detection of SARS-CoV2 emerging novel variants based on variant-specific mutation haplotypes and, in turn, be associated with enhanced implementation of risk-stratified public health prevention strategies.

Objective

To develop a haplotype-based artificial intelligence (HAI) model for identifying novel variants, including mixture variants (MVs) of known variants and new variants with novel mutations.

Design, Setting, and Participants

This cross-sectional study used serially observed viral genomic sequences globally (prior to March 14, 2022) to train and validate the HAI model and used it to identify variants arising from a prospective set of viruses from March 15 to May 18, 2022.

Main Outcomes and Measures

Viral sequences, collection dates, and locations were subjected to statistical learning analysis to estimate variant-specific core mutations and haplotype frequencies, which were then used to construct an HAI model to identify novel variants.

Results

Through training on more than 5 million viral sequences, an HAI model was built, and its identification performance was validated on an independent validation set of more than 5 million viruses. Its identification performance was assessed on a prospective set of 344 901 viruses. In addition to achieving an accuracy of 92.8% (95% CI within 0.1%), the HAI model identified 4 Omicron MVs (Omicron-Alpha, Omicron-Delta, Omicron-Epsilon, and Omicron-Zeta), 2 Delta MVs (Delta-Kappa and Delta-Zeta), and 1 Alpha-Epsilon MV, among which Omicron-Epsilon MVs were most frequent (609/657 MVs [92.7%]). Furthermore, the HAI model found that 1699 Omicron viruses had unidentifiable variants given that these variants acquired novel mutations. Lastly, 524 variant-unassigned and variant-unidentifiable viruses carried 16 novel mutations, 8 of which were increasing in prevalence percentages as of May 2022.

Conclusions and Relevance

In this cross-sectional study, an HAI model found SARS-COV-2 viruses with MV or novel mutations in the global population, which may require closer examination and monitoring. These results suggest that HAI may complement phylogenic variant assignment, providing additional insights into emerging novel variants in the population.

Correlated substitutions reveal SARS-like coronaviruses recombine frequently with a diverse set of structured gene pools

Quantifying SARS-like coronavirus (SL-CoV) evolution is critical to understanding the origins of SARS-CoV-2 and the molecular processes that could underlie future epidemic viruses. While genomic analyses suggest recombination was a factor in the emergence of SARS-CoV-2, few studies have quantified recombination rates among SL-CoVs. Here, we infer recombination rates of SL-CoVs from correlated substitutions in sequencing data using a coalescent model with recombination. Our computationally-efficient, non-phylogenetic method infers recombination parameters of both sampled sequences and the unsampled gene pools with which they recombine. We apply this approach to infer recombination parameters for a range of positive-sense RNA viruses. We then analyze a set of 191 SL-CoV sequences (including SARS-CoV-2) and find that ORF1ab and S genes frequently undergo recombination. We identify which SL-CoV sequence clusters have recombined with shared gene pools, and show that these pools have distinct structures and high recombination rates, with multiple recombination events occurring per synonymous substitution. We find that individual genes have recombined with different viral reservoirs. By decoupling contributions from mutation and recombination, we recover the phylogeny of non-recombined portions for many of these SL-CoVs, including the position of SARS-CoV-2 in this clonal phylogeny. Lastly, by analyzing >400,000 SARS-CoV-2 whole genome sequences, we show current diversity levels are insufficient to infer the within-population recombination rate of the virus since the pandemic began. Our work offers new methods for inferring recombination rates in RNA viruses with implications for understanding recombination in SARS-CoV-2 evolution and the structure of clonal relationships and gene pools shaping its origins.

VirusRecom: an information-theory-based method for recombination detection of viral lineages and its application on SARS-CoV-2

Genomic recombination is an important driving force for viral evolution, and recombination events have been reported for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the Coronavirus Disease 2019 pandemic, which significantly alter viral infectivity and transmissibility. However, it is difficult to identify viral recombination, especially for low-divergence viruses such as SARS-CoV-2, since it is hard to distinguish recombination from in situ mutation. Herein, we applied information theory to viral recombination analysis and developed VirusRecom, a program for efficiently screening recombination events on viral genome. In principle, we considered a recombination event as a transmission process of ``information'' and introduced weighted information content (WIC) to quantify the contribution of recombination to a certain region on viral genome; then, we identified the recombination regions by comparing WICs of different regions. In the benchmark using simulated data, VirusRecom showed a good balance between precision and recall compared to two competing tools, RDP5 and 3SEQ. In the detection of SARS-CoV-2 XE, XD and XF recombinants, VirusRecom providing more accurate positions of recombination regions than RDP5 and 3SEQ. In addition, we encapsulated the VirusRecom program into a command-line-interface software for convenient operation by users. In summary, we developed a novel approach based on information theory to identify viral recombination within highly similar sequences, providing a useful tool for monitoring viral evolution and epidemic control.