Viral CpG Deficiency Provides No Evidence That Dogs Were Intermediate Hosts for SARS-CoV-2

SARS-CoV-2 infection in animals: Patterns, transmission routes, and drivers

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is more widespread in animals than previously thought, and it may be able to infect a wider range of domestic and wild species. To effectively control the spread of the virus and protect animal health, it is crucial to understand the cross-species transmission mechanisms and risk factors of SARS-CoV-2. This article collects published literature on SARS-CoV-2 in animals and examines the distribution, transmission routes, biophysical, and anthropogenic drivers of infected animals. The reported cases of infection in animals are mainly concentrated in South America, North America, and Europe, and species affected include lions, white-tailed deer, pangolins, minks, and cats. Biophysical factors influencing infection of animals with SARS-CoV-2 include environmental determinants, high-risk landscapes, air quality, and susceptibility of different animal species, while anthropogenic factors comprise human behavior, intensive livestock farming, animal markets, and land management. Due to current research gaps and surveillance capacity shortcomings, future mitigation strategies need to be designed from a One Health perspective, with research focused on key regions with significant data gaps in Asia and Africa to understand the drivers, pathways, and spatiotemporal dynamics of interspecies transmission.

Genomic representation predicts an asymptotic host adaptation of bat coronaviruses using deep learning

Introduction

Coronaviruses (CoVs) are naturally found in bats and can occasionally cause infection and transmission in humans and other mammals. Our study aimed to build a deep learning (DL) method to predict the adaptation of bat CoVs to other mammals.

Methods

The CoV genome was represented with a method of dinucleotide composition representation (DCR) for the two main viral genes, ORF1ab and Spike. DCR features were first analyzed for their distribution among adaptive hosts and then trained with a DL classifier of convolutional neural networks (CNN) to predict the adaptation of bat CoVs.

Results and discussion

The results demonstrated inter-host separation and intra-host clustering of DCR-represented CoVs for six host types: Artiodactyla, Carnivora, Chiroptera, Primates, Rodentia/Lagomorpha, and Suiformes. The DCR-based CNN with five host labels (without Chiroptera) predicted a dominant adaptation of bat CoVs to Artiodactyla hosts, then to Carnivora and Rodentia/Lagomorpha mammals, and later to primates. Moreover, a linear asymptotic adaptation of all CoVs (except Suiformes) from Artiodactyla to Carnivora and Rodentia/Lagomorpha and then to Primates indicates an asymptotic bats-other mammals-human adaptation.

Conclusion

Genomic dinucleotides represented as DCR indicate a host-specific separation, and clustering predicts a linear asymptotic adaptation shift of bat CoVs from other mammals to humans via deep learning.

Contrasting patterns in the early stage of SARS-CoV-2 evolution between humans and minks

One of the unique features of SARS-CoV-2 is its apparent neutral evolution during the early pandemic (before February 2020). This contrasts with the preceding SARS-CoV epidemics, where viruses evolved adaptively. SARS-CoV-2 may exhibit a unique or adaptive feature which deviates from other coronaviruses. Alternatively, the virus may have been cryptically circulating in humans for a sufficient time to have acquired adaptive changes before the onset of the current pandemic. To test the scenarios above, we analyzed the SARS-CoV-2 sequences from minks (Neovision vision) and parental humans. In the early phase of the mink epidemic (April to May 2020), nonsynonymous to synonymous mutation ratio per site in the spike protein is 2.93, indicating a selection process favoring adaptive amino acid changes. Mutations in the spike protein were concentrated within its receptor binding domain and receptor binding motif. An excess of high frequency derived variants produced by genetic hitchhiking was found during the middle (June to July 2020) and late phase I (August to September 2020) of the mink epidemic. In contrast, the site frequency spectra of early SARS-CoV-2 in humans only show an excess of low frequency mutations, consistent with the recent outbreak of the virus. Strong positive selection in the mink SARS-CoV-2 implies the virus may not be pre-adapted to a wide range of hosts and illustrates how a virus evolves to establish a continuous infection in a new host. Therefore, the lack of positive selection signal during the early pandemic in humans deserves further investigation.

Deep learning based on biologically interpretable genome representation predicts two types of human adaptation of SARS-CoV-2 variants

Explosively emerging SARS-CoV-2 variants challenge current nomenclature schemes based on genetic diversity and biological significance. Genomic composition-based machine learning methods have recently performed well in identifying phenotype–genotype relationships. We introduced a framework involving dinucleotide (DNT) composition representation (DCR) to parse the general human adaptation of RNA viruses and applied a three-dimensional convolutional neural network (3D CNN) analysis to learn the human adaptation of other existing coronaviruses (CoVs) and predict the adaptation of SARS-CoV-2 variants of concern (VOCs). A markedly separable, linear DCR distribution was observed in two major genes—receptor-binding glycoprotein and RNA-dependent RNA polymerase (RdRp)—of six families of single-stranded (ssRNA) viruses. Additionally, there was a general host-specific distribution of both the spike proteins and RdRps of CoVs. The 3D CNN based on spike DCR predicted a dominant type II adaptation of most Beta, Delta and Omicron VOCs, with high transmissibility and low pathogenicity. Type I adaptation with opposite transmissibility and pathogenicity was predicted for SARS-CoV-2 Alpha VOCs (77%) and Kappa variants of interest (58%). The identified adaptive determinants included D1118H and A570D mutations and local DNTs. Thus, the 3D CNN model based on DCR features predicts SARS-CoV-2, a major type II human adaptation and is qualified to predict variant adaptation in real time, facilitating the risk-assessment of emerging SARS-CoV-2 variants and COVID-19 control.

The low abundance of CpG in the SARS-CoV-2 genome is not an evolutionarily signature of ZAP

The zinc finger antiviral protein (ZAP) is known to restrict viral replication by binding to the CpG rich regions of viral RNA, and subsequently inducing viral RNA degradation. This enzyme has recently been shown to be capable of restricting SARS-CoV-2. These data have led to the hypothesis that the low abundance of CpG in the SARS-CoV-2 genome is due to an evolutionary pressure exerted by the host ZAP. To investigate this hypothesis, we performed a detailed analysis of many coronavirus sequences and ZAP RNA binding preference data. Our analyses showed neither evidence for an evolutionary pressure acting specifically on CpG dinucleotides, nor a link between the activity of ZAP and the low CpG abundance of the SARS-CoV-2 genome.

The slowing rate of CpG depletion in SARS-CoV-2 genomes is consistent with adaptations to the human host

Depletion of CpG dinucleotides in SARS-CoV-2 genomes has been linked to virus evolution, host-switching, virus replication, and innate immune responses. Temporal variations, if any, in the rate of CpG depletion during virus evolution in the host remain poorly understood. Here, we analysed the CpG content of over 1.4 million full-length SARS-CoV-2 genomes representing over 170 million documented infections during the first 17 months of the pandemic. Our findings suggest that the extent of CpG depletion in SARS-CoV-2 genomes is modest. Interestingly, the rate of CpG depletion is highest during early evolution in humans and it gradually tapers off almost reaching an equilibrium; this is consistent with adaptations to the human host. Furthermore, within the coding regions, CpG depletion occurs predominantly at codon positions 2-3 and 3-1. Loss of ZAP-binding motifs in SARS-CoV-2 genomes is primarily driven by the loss of the terminal CpG in the motifs. Nonetheless, majority of the CpG depletion in SARS-CoV-2 genomes occurs outside ZAP-binding motifs. SARS-CoV-2 genomes selectively lose CpGs-motifs from a U-rich context; this may help avoid immune recognition by TLR7. SARS-CoV-2 alpha-, beta- and delta-variants of concern have reduced CpG content compared to sequences from the beginning of the pandemic. In sum, we provide evidence that the rate of CpG depletion in virus genomes is not uniform and it greatly varies over time and during adaptations to the host. This work highlights how temporal variations in selection pressures during virus adaption may impact the rate and the extent of CpG depletion in virus genomes.

Natural Transmission and Experimental Models of SARS CoV-2 Infection in Animals

Since the World Health Organization declared COVID-19 a pandemic in March 2020, millions of people have contracted SARS-CoV-2 and died from the infection. Several domestic and wild species have contracted the disease as well. From the beginning, scientists have been working to develop vaccines and establish therapies that can prevent disease development and improve the clinical outcome in infected people. To understand various aspects of viral pathogenesis and infection dynamics and to support preclinical evaluation of vaccines and therapeutics, a diverse number of animal species have been evaluated for use as models of the disease and infection in humans. Here, we discuss natural SARS-CoV-2 infection of domestic and captive wild animals, as well as the susceptibility of several species to experimental infection with this virus.

The Functional Consequences of the Novel Ribosomal Pausing Site in SARS-CoV-2 Spike Glycoprotein RNA

The SARS-CoV-2 Spike glycoprotein (S protein) acquired a unique new 4 amino acid -PRRA- insertion sequence at amino acid residues (aa) 681-684 that forms a new furin cleavage site in S protein as well as several new glycosylation sites. We studied various statistical properties of the -PRRA- insertion at the RNA level (CCUCGGCGGGCA). The nucleotide composition and codon usage of this sequence are different from the rest of the SARS-CoV-2 genome. One of such features is two tandem CGG codons, although the CGG codon is the rarest codon in the SARS-CoV-2 genome. This suggests that the insertion sequence could cause ribosome pausing as the result of these rare codons. Due to population variants, the Nextstrain divergence measure of the CCU codon is extremely large. We cannot exclude that this divergence might affect host immune responses/effectiveness of SARS-CoV-2 vaccines, possibilities awaiting further investigation. Our experimental studies show that the expression level of original RNA sequence "wildtype" spike protein is much lower than for codon-optimized spike protein in all studied cell lines. Interestingly, the original spike sequence produces a higher titer of pseudoviral particles and a higher level of infection. Further mutagenesis experiments suggest that this dual-effect insert, comprised of a combination of overlapping translation pausing and furin sites, has allowed SARS-CoV-2 to infect its new host (human) more readily. This underlines the importance of ribosome pausing to allow efficient regulation of protein expression and also of cotranslational subdomain folding.

Predicting the animal hosts of coronaviruses from compositional biases of spike protein and whole genome sequences through machine learning

The COVID-19 pandemic has demonstrated the serious potential for novel zoonotic coronaviruses to emerge and cause major outbreaks. The immediate animal origin of the causative virus, SARS-CoV-2, remains unknown, a notoriously challenging task for emerging disease investigations. Coevolution with hosts leads to specific evolutionary signatures within viral genomes that can inform likely animal origins. We obtained a set of 650 spike protein and 511 whole genome nucleotide sequences from 222 and 185 viruses belonging to the family Coronaviridae, respectively. We then trained random forest models independently on genome composition biases of spike protein and whole genome sequences, including dinucleotide and codon usage biases in order to predict animal host (of nine possible categories, including human). In hold-one-out cross-validation, predictive accuracy on unseen coronaviruses consistently reached ~73%, indicating evolutionary signal in spike proteins to be just as informative as whole genome sequences. However, different composition biases were informative in each case. Applying optimised random forest models to classify human sequences of MERS-CoV and SARS-CoV revealed evolutionary signatures consistent with their recognised intermediate hosts (camelids, carnivores), while human sequences of SARS-CoV-2 were predicted as having bat hosts (suborder Yinpterochiroptera), supporting bats as the suspected origins of the current pandemic. In addition to phylogeny, variation in genome composition can act as an informative approach to predict emerging virus traits as soon as sequences are available. More widely, this work demonstrates the potential in combining genetic resources with machine learning algorithms to address long-standing challenges in emerging infectious diseases.

Urgent Need for Field Surveys of Coronaviruses in Southeast Asia to Understand the SARS-CoV-2 Phylogeny and Risk Assessment for Future Outbreaks

Phylogenetic analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is focused on a single isolate of bat coronaviruses (bat CoVs) which does not adequately represent genetically related coronaviruses (CoVs) [...].

Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen

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.

COVID-19 in Farm Animals: Host Susceptibility and Prevention Strategies

COVID-19 is caused by the virus SARS-CoV-2 that belongings to the family of Coronaviridae, which has affected multiple species and demonstrated zoonotic potential. The COVID-19 infections have been reported on farm animals (e.g., minks) and pets, which were discussed and summarized in this study. Although the damage of COVID-19 has not been reported as serious as highly pathogenic avian influenza (HPAI) for poultry and African Swine Fever (ASF) for pigs on commercial farms so far, the transmission mechanism of COVID-19 among group animals/farms and its long-term impacts are still not clear. Prior to the marketing of efficient vaccines for livestock and animals, on-farm biosecurity measures (e.g., conventional disinfection strategies and innovated technologies) need to be considered or innovated in preventing the direct contact spread or the airborne transmission of COVID-19.

The Long-Term Evolutionary History of Gradual Reduction of CpG Dinucleotides in the SARS-CoV-2 Lineage

Simple Summary

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the coronavirus disease 2019 (COVID-19), a pandemic that infected over 81 million people worldwide. This has led the scientific community to characterize the genome of this virus, including its nucleotide composition. Investigation of the dinucleotide frequency revealed that the proportion of CG dinucleotides (CpG) is highly reduced in the viral genomes. Since CpG dinucleotides is the target site for the host antiviral zinc finger protein, it has been suggested that the reduction in the proportion of CpG is the viral response to escape from the host defense machinery. In the present study, we investigated the time of origin of reduction in the CpG content. Whole genome analyses based on all representative viral genomes of the group Betacoronavirus revealed that the CpG content in the lineage of SARS-CoV-2 has been progressively declining over the past 1213 years. The depletion of CpG was found to occur at neutral—as well as selectively constrained—positions of the viral genomes.

Abstract

Recent studies suggested that the fraction of CG dinucleotides (CpG) is severely reduced in the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The CpG deficiency was predicted to be the adaptive response of the virus to evade degradation of the viral RNA by the antiviral zinc finger protein that specifically binds to CpG nucleotides. By comparing all representative genomes belonging to the genus Betacoronavirus, this study examined the potential time of origin of CpG depletion. The results of this investigation revealed a highly significant correlation between the proportions of CpG nucleotide (CpG content) of the betacoronavirus species and their times of divergence from SARS-CoV-2. Species that are distantly related to SARS-CoV-2 had much higher CpG contents than that of SARS-CoV-2. Conversely, closely related species had low CpG contents that are similar to or slightly higher than that of SARS-CoV-2. These results suggest a systematic and continuous reduction in the CpG content in the SARS-CoV-2 lineage that might have started since the Sarbecovirus + Hibecovirus clade separated from Nobecovirus, which was estimated to be 1213 years ago. This depletion was not found to be mediated by the GC contents of the genomes. Our results also showed that the depletion of CpG occurred at neutral positions of the genome as well as those under selection. The latter is evident from the progressive reduction in the proportion of arginine amino acid (coded by CpG dinucleotides) in the SARS-CoV-2 lineage over time. The results of this study suggest that shedding CpG nucleotides from their genome is a continuing process in this viral lineage, potentially to escape from their host defense mechanisms.

Where Did SARS-CoV-2 Come From?

Identifying the origin of SARS-CoV-2, the etiological agent of the current COVID-19 pandemic, may help us to avoid future epidemics of coronavirus and other zoonoses. Several theories about the zoonotic origin of SARS-CoV-2 have recently been proposed. While Betacoronavirus found in Rhinolophus bats from China have been broadly implicated, their genetic dissimilarity to SARS-CoV-2 is so high that they are highly unlikely to be its direct ancestors. Thus, an intermediary host is suspected to link bat to human coronaviruses. Based on genomic CpG dinucleotide patterns in different coronaviruses from different hosts, it was suggested that SARS-CoV-2 might have evolved in a canid gastro-intestinal tract prior to transmission to humans. However, similar CpG patterns are now reported in coronaviruses from other hosts, including bats themselves and pangolins. Therefore, reduced genomic CpG alone is not a highly predictive biomarker, suggesting a need for additional biomarkers to reveal intermediate hosts or tissues. The hunt for the zoonotic origin of SARS-CoV-2 continues.