In both the SARS-CoV and MERS-CoV epidemics, the viruses have likely originated from bats and then jumped into another amplification mammalian host [the Himalayan palm civet (Paguma larvata) for SARS-CoV and the dromedary camel (Camelus dromedarius) for MERS-CoV] before crossing species barriers to infect humans (Chan Em Micr Inf 2020, see below). Bonilla-Aldana (manuscript on Preprints: https://www.preprints.org/manuscript/202003.0103/v2) performed a systematic literature review with meta-analysis, using three databases to assess MERS-CoV and SARS-CoV infection in animals and its diagnosis by serological and molecular tests to calculate pooled prevalence. From 34 studies (n=20,896 animals), the pool prevalence by RT-PCR for MERS-CoV was 7.2% (95%CI 5.6-8.7%), with 97.3%
occurring in camels with a prevalence of 10.3% (95%CI 8.3-12.3). From 5 studies and 2,618 animals, for SARS-CoV, the RT-PCR pool prevalence was 2.3% (95%CI 1.3-3.3). Of those, 38.35% were reported on bats, in which the pool prevalence was 14.1% (95%CI0.0-44.6%). In this meta-analysis, camels and bats were found to be positive by RT-PCR in over 10% of the cases for both; thus, suggesting their relevance in the maintenance of wild zoonotic transmission.
While phylogenetic analysis indicates a bat origin of SARS-CoV-2, the virus also potentially recognizes the ACE2 receptor from a diversity of animal species (except mice and rats), implicating these animal species as possible intermediate hosts or animal models for SARS-CoV-2 infections (Wan, Shang, Granham et al. J Virol 2020, see below).
As explained by Andersen (Nature Med 2020, see below), detailed understanding of how an animal virus jumped species boundaries to infect humans so productively will help in the prevention of future zoonotic events. If SARS-CoV-2 pre-adapted in another animal species, then there is the risk of future re-emergence events. In contrast, if the adaptive process occurred in humans, then even if repeated zoonotic transfers occur, they are unlikely to take off without the same series of mutations. Building on these gaps, the Wildlife Disease Surveillance Focus Group recommends the creation of a central, publicly accessible database for recording the characteristics of animal viruses to help monitor the risk of any crossover into people. This would allow scientists to see how the pathogens and their prevalence are evolving worldwide, helping them identify any potential vaccine targets or antiviral treatments before a major outbreak occurs (Gray Vet Record 2020, see below).
Observations from genetic studies
A study by MacLean (bioRxiv 2020, see below) revealed a low frequency of viral mutations among 15 537 SARS-CoV-2 genome sequences circulating in humans, suggesting that significant SARS-CoV-2 evolution occurred prior to spillover in humans. The authors warned that the high diversity of sarbecoviruses and their generalist nature make future emergence of divergent viral strains from bats to humans likely.
Ji (J Med Virol. 2020, see below) suggested that snake is the most probable wildlife animal reservoir for SARS-CoV-2 based on its relative synonymous codon usage bias resembling snake compared to other animals. However, this hypothesis was received with skepticism (https://www.nature.com/articles/d41586-020-00180-8). It was not supported by the bioinformatics protein structure and sequence analyses by Zhang (manuscript on Arxiv:
https://arxiv.org/abs/2002.03173). Lam (manuscript on bioRxiv :
https://www.biorxiv.org/content/10.1101/2020.05.01.072371v6) modelled S-protein:ACE2 complexes from 215 vertebrate species, calculated their relative energies, correlated these energies to COVID-19 infection data, and analysed structural interactions. They predicted that known mutations are more detrimental in ACE2 than TMPRSS2, demonstrate phylogenetically that human 2 strains originated from animal, and suggested that SARS-CoV-2 can infect a broad range of mammals, but not fish, birds or reptiles.
Chinese researchers of the South China Agricultural University in Guangzhou found 99% sequence similarity in the S RBD region between SARS-CoV-2 isolated from infected human subjects and coronaviruses taken from pangolins (Manis javanica) (https://www.nature.com/articles/d41586-020-00364-2). Researchers had noted previously that coronaviruses are a possible cause of death in pangolins, and that SARS-CoV-2 and coronaviruses from pangolins use receptors with similar molecular structures to infect cells. Lam (Nature 2020, see below) also reported the identification of SARS-CoV-2-related coronaviruses in pangolins seized in anti-smuggling operations in southern China.
Metagenomic sequencing identified pangolin-associated CoVs that belong to two sub-lineages of SARS-CoV-2-related coronaviruses, including one very closely related to SARS-CoV-2 in the RBD. Cyranoski (Nature 2020, see below) subsequently summarized the investigations pertaining to the animal source of SARS-CoV-2. He noted that the previously communicated 99% homology between SARS-CoV-2 and a pangolin virus only applied to the S RBD region.
The homology with pangolin viruses when considering the whole genome did not exceed 92.4%. A subsequent report by Zhang (Current Biology 2020, see below) reached similar conclusions. By contrast, SARS-CoV shared 99.8% of its genome with a civet coronavirus.
Xiao (Nature 2020, see below) reported the isolation of a coronavirus from a Malayan pangolin, which showed 100%, 98.6%, 97.8% and 90.7% amino acid identity with SARS-CoV-2 in the E, M, N and S genes, respectively. In particular, the receptor-binding domain within the S protein of the Pangolin-CoV is virtually identical to that of SARS-CoV-2, with one noncritical amino acid difference. Results of comparative genomic analysis suggested that SARS-CoV-2 might have
originated from the recombination of a Pangolin-CoV-like virus with a Bat-CoV-RaTG13-like virus. The Pangolin-CoV was detected in 17 of 25 Malayan pangolins analyzed. Infected pangolins showed clinical signs and histological changes, and circulating antibodies against Pangolin-CoV reacted with the S protein of SARS-CoV-2. The data suggest that pangolins have the potential to act as the intermediate host of SARS-CoV-2. Noteworthy is the evidence of Malayan pangolin SARS-CoV-2-related coronavirus (SARSr-CoV-2) is closely related to SARS-CoV-2 infecting multiple organs in pangolins, with the lungs being the major target, with ACE2 and TMPRSS2 co-expression with viral RNA. Importantly, viral RNA and protein were detected in 3 foetuses providing evidence for vertical virus transmission in pangolins (Li, preprint on bioRxiv: https://doi.org/10.1101/2020.06.22.164442).
Another prediction of the interaction between the RBD of the S protein and the ACE2 receptor surprisingly suggested that not only pangolins, but also turtles (C. picta bellii, C. mydas, and P. sinensis) might act as potential intermediate hosts transmitting SARS-CoV-2 to human (Liu, Xiao et al. J Med Vir 2020, see below).
ACE2 contains at least five key amino acids critical for binding S protein of SARS-CoV-2. Based on these five amino acids, Luan (Biochem Biophys Res Commun 2020, see below) analysed the corresponding amino acids of different mammals to determine which mammalian ACE2 could interact with the SARS-CoV-2 S protein. The authors found that the ACE2 of Camelus dromedarius, Procyon lotor, Rhinolophus ferrumequinum, Rattus norvegicus, Mus musculus, Ornithorhynchus anatinus, Loxodonta africana, Erinaceus europaeus, Nyctereutes procyonoides, Suricata suricatta, Dipodomys ordii, and Cavia porcellus are not able to associate with S protein. The authors indicated cat/dog ACE2 may bind to S protein of SARS-CoV-2. The ACE2 proteins from Circetidae, incl. Mesocricetus auratus (golden hamster) and Cricetulus griseus (Chinese hamster). Similarly, a study by Luan (J Med Vir 2020, see below) also suggested that ACE2 proteins from Cricetidae were able to associate with SARS-CoV-2 RBD. The authors found a similar result for Bovidae.
Rodrigues (manuscript on bioRxiv: https://doi.org/10.1101/2020.06.05.136861) investigated the structural properties of several ACE2 orthologs bound to the SARS-CoV-2 S protein and found that species not susceptible to SARS-CoV-2 infection have non-conservative mutations in several ACE2 amino acid residues which disrupt key polar and charged contacts with the viral spike protein. Their models predict affinity-enhancing mutations that could be used to design ACE2 variants for therapeutic purposes.
Robins (manuscript on bioRxiv: https://doi.org/10.1101/2020.06.05.136887) examined the protein covariance-based on the conserved CoV proteins called 1a/1b, S, 3a, E, M, and N from a set of 850 viral genome networks of SARS coronaviruses revealing interactions important to their emergence as human pathogens. They state that recombination with other viruses in combination with new adaptive mutations important for entry into human cells is the likely evolutionary scenario that converted a bat virus into human pathogen. Analysing ± 9,000 SARS-CoV-2 genomes from Africa, America, Asia, Europe, and Oceania, Jones (manuscript on bioRxiv:
https://doi.org/10.1101/2020.06.05.135954) showed that the virus is a complex of slightly different genetic variants that are unevenly distributed on Earth, demonstrated that SARS-CoV-2 phylogeny is spatially structured and hypothesized this could be the result of founder effects occurring as a consequence of, and local evolution occurring after, long-distance dispersal.
Of note, while controversies about the source of the virus and its intermediate host remain, Li (Infect Genet Evol 2020, see below) evaluated coronaviruses derived from five wild animals, including Paguma larvata, Paradoxurus hermaphroditus, Civet, Aselliscus stoliczkanus and Rhinolophus sinicus (Chinese rufous horseshoe bat). Genome and ORF1a homology analyses showed that SARS-CoV-2 is not the same coronavirus as the coronavirus derived from these five animals, whereas the authors confirmed the highest homology with Bat coronavirus isolate RaTG13. Latinne (Nature Comm 2020, see below) next studied bat-CoVs (including 630 novel CoV sequences) macroevolution, cross-species transmission, and dispersal in China. Adopting a Bayesian approach the authors found inter-family and -genus switching is most common in Rhinolophidae bats and the genus Rhinolophus and present a phylogenetic analysis suggesting a likely origin for SARS-CoV-2 in Rhinolophus spp. bats. They further identify the host taxa and geographic
regions that define hotspots of CoV evolutionary diversity in China that could help target bat-CoV discovery for proactive zoonotic disease surveillance. Further bayesian evolutionary rate and divergence dates estimates were used to understand the role of reservoir species, the role of recombination and the time of SARS-CoV-2 divergence. As presented above (see Origin of the virus), Boni (Nature 2020, see below) showed 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. Boni and co-authors estimated that divergence time between SARS-CoV-2 and bat sarbecovirus reservoir were in 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.
Susceptibility of various animal species to SARS-CoV-2
Field studies and laboratory challenge data remain important to conduct for better understanding the zoonotic transmission of SARS-CoV-2. One of these studies was conducted by Deng (Transbound Em Dis 2020, see below), who after confirming the specificity, sensitivity and suitability of SARS-CoV-2 ELISA kit for different species of experimental animals, evaluated clinical serum samples from domestic livestock (pig, cow, sheep, horse), poultry (chicken, duck, goose), experimental animal (mice, rat, and rhesus monkey), companion animal (dog and cat), and wild animals (camel, fox, mink, alpaca, ferret, bamboo rat, peacock, eagle, tiger, rhinoceros, pangolin, leopard, cat, jackal, giant panda, masked civet, porcupine, bear, yellow-throated marten, weasel, red pandas, and wild boar). All serum samples had negative results, which made the authors conclude that the animal species above can be excluded as intermediate host of SARS-CoV-2. Of note, no SARS CoV-2 specific antibodies were detected in all dogs and cats, even for the street dogs and cats in Wuhan City and the pet dog raised by a COVID-19 patient.
Rabbit (Oryctolagus cuniculus) and livestock (cattle, Bos Taurus) susceptibility to SARS-CoV-2 have been experimentally tested in more recent studies. While the infection is asymptomatic in healthy New Zealand White rabbits, infectious virus with peak titers corresponding to ~103 TCID50 could be detected up to day seven post inoculation in the nose.
The minimum dose to establish productive infection was 105 TCID50, indicating that virus transmission between rabbits may be less efficient compared to ferrets and hamsters. The use of young, immunocompetent, and healthy rabbits however may not reflect virus shedding and disease in other rabbit breeds or rabbits at different ages. Thus, surveillance studies - including serological testing - may be needed to assess the presence of SARS-CoV-2 in farmed rabbits (Mykytyn preprint on bioRxiv : https://doi.org/10.1101/2020.08.27.263988). To examine the susceptibility of cattle for SARS-CoV-2 and to characterize the course of infection under experimental conditions, six 4-5 months old, male Holstein-Friesian dairy calves were intranasally inoculated with 1×105 tissue culture infectious dose 50% (TCID50) of SARS-CoV-2 strain “2019_nCoV Muc-IMB-1” (GISAID ID_EPI_ISL_406862, designation “hCoV-19/Germany/BavPat1/2020”) at 1ml per nostril ; 24 hours after inoculation three contact cattle, were introduced.
Ulrich (preprint on https://doi.org/10.1101/2020.08.25.254474) demonstrated that under selected experimental conditions cattle show low susceptibility to SARS-CoV-2, since two out of six animals appeared to be infected as demonstrated by SARS-CoV-2-genome detection in nasal swabs and specific seroconversion. The sample was small and - despite for controlling for bovine CoV cross-seroreactivity - results should be taken with caution.
SARS-CoV-2 emergence risk maps
A modelling study by Walsh (One Health 2020, see below) provided a first systematic, data-driven, quantitative geography investigation of high-impact spillover wildlife-livestock/poultry-human interfaces taking into account human health system performance and global connectivity via the network of air travel. It showed that many of the world’s most connected cities are adjacent to or within areas (50km radius) where wildlife share space with humans and their domesticated animals. Indeed, more than 40% of these cities were within or adjacent to landscapes of
extensive animal-human interface, while approximately 14%-20% were located in landscapes of both extensive interface and poor health system performance. The output is an alert-level map (yellow, orange, and red zones classified according to increased risk) which can be used as a tool to develop targeted surveillance systems and improving health infrastructure in vulnerable areas that may present conduits for future pandemics (Figure 12). As sensitive and SARS-Cov-2 specific tests (e.g. new ELISA) develop, and experimental evidence of transmission from infected animal hosts to naïve conspecifics and the nature and amount of viral shedding build up, new data should ultimately help refine the above-mentioned model and design more specific, data informed, SARS-CoV-2 emergence risk maps at fine scale human-animal interfaces.
Figure 12 Alert-level red zones depicting interfaces between mammalian richness, human population density, and livestock/ poultry densities based on the intersection of the top quartile of each feature’s distribution, extending the intersection of these interfaces with the
top quartile of infant mortality (from Walsh One Health 2020).
Cities of high network centrality (75th percentile) based on global air travel and within 50 km of red interfaces are overlaid. The proportion of highly connected transportation hubs (75th percentile of airport network centrality) within 50 km of each interface is presented with the
airplane icon. Cities mapped twice have two high centrality airports.