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      The future of zoonotic risk prediction

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      1 , 2 , , 3 , 4 , 5 , 6 , 7 , 1 , 8 , 1 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 8 , 19 , 1 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 25 , 29 , 30 , 31 , 1 , 2 , 32 , 33 , 34
      Philosophical Transactions of the Royal Society B: Biological Sciences
      The Royal Society
      zoonotic risk, epidemic risk, access and benefit sharing, machine learning, global health, viral ecology

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          Abstract

          In the light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programmes will identify hundreds of novel viruses that might someday pose a threat to humans. To support the extensive task of laboratory characterization, scientists may increasingly rely on data-driven rubrics or machine learning models that learn from known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions. What are the prerequisites, in terms of open data, equity and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges?

          This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.

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          The proximal origin of SARS-CoV-2

          To the Editor — Since the first reports of novel pneumonia (COVID-19) in Wuhan, Hubei province, China 1,2 , there has been considerable discussion on the origin of the causative virus, SARS-CoV-2 3 (also referred to as HCoV-19) 4 . Infections with SARS-CoV-2 are now widespread, and as of 11 March 2020, 121,564 cases have been confirmed in more than 110 countries, with 4,373 deaths 5 . SARS-CoV-2 is the seventh coronavirus known to infect humans; SARS-CoV, MERS-CoV and SARS-CoV-2 can cause severe disease, whereas HKU1, NL63, OC43 and 229E are associated with mild symptoms 6 . Here we review what can be deduced about the origin of SARS-CoV-2 from comparative analysis of genomic data. We offer a perspective on the notable features of the SARS-CoV-2 genome and discuss scenarios by which they could have arisen. Our analyses clearly show that SARS-CoV-2 is not a laboratory construct or a purposefully manipulated virus. Notable features of the SARS-CoV-2 genome Our comparison of alpha- and betacoronaviruses identifies two notable genomic features of SARS-CoV-2: (i) on the basis of structural studies 7–9 and biochemical experiments 1,9,10 , SARS-CoV-2 appears to be optimized for binding to the human receptor ACE2; and (ii) the spike protein of SARS-CoV-2 has a functional polybasic (furin) cleavage site at the S1–S2 boundary through the insertion of 12 nucleotides 8 , which additionally led to the predicted acquisition of three O-linked glycans around the site. 1. Mutations in the receptor-binding domain of SARS-CoV-2 The receptor-binding domain (RBD) in the spike protein is the most variable part of the coronavirus genome 1,2 . Six RBD amino acids have been shown to be critical for binding to ACE2 receptors and for determining the host range of SARS-CoV-like viruses 7 . With coordinates based on SARS-CoV, they are Y442, L472, N479, D480, T487 and Y4911, which correspond to L455, F486, Q493, S494, N501 and Y505 in SARS-CoV-2 7 . Five of these six residues differ between SARS-CoV-2 and SARS-CoV (Fig. 1a). On the basis of structural studies 7–9 and biochemical experiments 1,9,10 , SARS-CoV-2 seems to have an RBD that binds with high affinity to ACE2 from humans, ferrets, cats and other species with high receptor homology 7 . Fig. 1 Features of the spike protein in human SARS-CoV-2 and related coronaviruses. a, Mutations in contact residues of the SARS-CoV-2 spike protein. The spike protein of SARS-CoV-2 (red bar at top) was aligned against the most closely related SARS-CoV-like coronaviruses and SARS-CoV itself. Key residues in the spike protein that make contact to the ACE2 receptor are marked with blue boxes in both SARS-CoV-2 and related viruses, including SARS-CoV (Urbani strain). b, Acquisition of polybasic cleavage site and O-linked glycans. Both the polybasic cleavage site and the three adjacent predicted O-linked glycans are unique to SARS-CoV-2 and were not previously seen in lineage B betacoronaviruses. Sequences shown are from NCBI GenBank, accession codes MN908947, MN996532, AY278741, KY417146 and MK211376. The pangolin coronavirus sequences are a consensus generated from SRR10168377 and SRR10168378 (NCBI BioProject PRJNA573298) 29,30 . While the analyses above suggest that SARS-CoV-2 may bind human ACE2 with high affinity, computational analyses predict that the interaction is not ideal 7 and that the RBD sequence is different from those shown in SARS-CoV to be optimal for receptor binding 7,11 . Thus, the high-affinity binding of the SARS-CoV-2 spike protein to human ACE2 is most likely the result of natural selection on a human or human-like ACE2 that permits another optimal binding solution to arise. This is strong evidence that SARS-CoV-2 is not the product of purposeful manipulation. 2. Polybasic furin cleavage site and O-linked glycans The second notable feature of SARS-CoV-2 is a polybasic cleavage site (RRAR) at the junction of S1 and S2, the two subunits of the spike 8 (Fig. 1b). This allows effective cleavage by furin and other proteases and has a role in determining viral infectivity and host range 12 . In addition, a leading proline is also inserted at this site in SARS-CoV-2; thus, the inserted sequence is PRRA (Fig. 1b). The turn created by the proline is predicted to result in the addition of O-linked glycans to S673, T678 and S686, which flank the cleavage site and are unique to SARS-CoV-2 (Fig. 1b). Polybasic cleavage sites have not been observed in related ‘lineage B’ betacoronaviruses, although other human betacoronaviruses, including HKU1 (lineage A), have those sites and predicted O-linked glycans 13 . Given the level of genetic variation in the spike, it is likely that SARS-CoV-2-like viruses with partial or full polybasic cleavage sites will be discovered in other species. The functional consequence of the polybasic cleavage site in SARS-CoV-2 is unknown, and it will be important to determine its impact on transmissibility and pathogenesis in animal models. Experiments with SARS-CoV have shown that insertion of a furin cleavage site at the S1–S2 junction enhances cell–cell fusion without affecting viral entry 14 . In addition, efficient cleavage of the MERS-CoV spike enables MERS-like coronaviruses from bats to infect human cells 15 . In avian influenza viruses, rapid replication and transmission in highly dense chicken populations selects for the acquisition of polybasic cleavage sites in the hemagglutinin (HA) protein 16 , which serves a function similar to that of the coronavirus spike protein. Acquisition of polybasic cleavage sites in HA, by insertion or recombination, converts low-pathogenicity avian influenza viruses into highly pathogenic forms 16 . The acquisition of polybasic cleavage sites by HA has also been observed after repeated passage in cell culture or through animals 17 . The function of the predicted O-linked glycans is unclear, but they could create a ‘mucin-like domain’ that shields epitopes or key residues on the SARS-CoV-2 spike protein 18 . Several viruses utilize mucin-like domains as glycan shields involved immunoevasion 18 . Although prediction of O-linked glycosylation is robust, experimental studies are needed to determine if these sites are used in SARS-CoV-2. Theories of SARS-CoV-2 origins It is improbable that SARS-CoV-2 emerged through laboratory manipulation of a related SARS-CoV-like coronavirus. As noted above, the RBD of SARS-CoV-2 is optimized for binding to human ACE2 with an efficient solution different from those previously predicted 7,11 . Furthermore, if genetic manipulation had been performed, one of the several reverse-genetic systems available for betacoronaviruses would probably have been used 19 . However, the genetic data irrefutably show that SARS-CoV-2 is not derived from any previously used virus backbone 20 . Instead, we propose two scenarios that can plausibly explain the origin of SARS-CoV-2: (i) natural selection in an animal host before zoonotic transfer; and (ii) natural selection in humans following zoonotic transfer. We also discuss whether selection during passage could have given rise to SARS-CoV-2. 1. Natural selection in an animal host before zoonotic transfer As many early cases of COVID-19 were linked to the Huanan market in Wuhan 1,2 , it is possible that an animal source was present at this location. Given the similarity of SARS-CoV-2 to bat SARS-CoV-like coronaviruses 2 , it is likely that bats serve as reservoir hosts for its progenitor. Although RaTG13, sampled from a Rhinolophus affinis bat 1 , is ~96% identical overall to SARS-CoV-2, its spike diverges in the RBD, which suggests that it may not bind efficiently to human ACE2 7 (Fig. 1a). Malayan pangolins (Manis javanica) illegally imported into Guangdong province contain coronaviruses similar to SARS-CoV-2 21 . Although the RaTG13 bat virus remains the closest to SARS-CoV-2 across the genome 1 , some pangolin coronaviruses exhibit strong similarity to SARS-CoV-2 in the RBD, including all six key RBD residues 21 (Fig. 1). This clearly shows that the SARS-CoV-2 spike protein optimized for binding to human-like ACE2 is the result of natural selection. Neither the bat betacoronaviruses nor the pangolin betacoronaviruses sampled thus far have polybasic cleavage sites. Although no animal coronavirus has been identified that is sufficiently similar to have served as the direct progenitor of SARS-CoV-2, the diversity of coronaviruses in bats and other species is massively undersampled. Mutations, insertions and deletions can occur near the S1–S2 junction of coronaviruses 22 , which shows that the polybasic cleavage site can arise by a natural evolutionary process. For a precursor virus to acquire both the polybasic cleavage site and mutations in the spike protein suitable for binding to human ACE2, an animal host would probably have to have a high population density (to allow natural selection to proceed efficiently) and an ACE2-encoding gene that is similar to the human ortholog. 2. Natural selection in humans following zoonotic transfer It is possible that a progenitor of SARS-CoV-2 jumped into humans, acquiring the genomic features described above through adaptation during undetected human-to-human transmission. Once acquired, these adaptations would enable the pandemic to take off and produce a sufficiently large cluster of cases to trigger the surveillance system that detected it 1,2 . All SARS-CoV-2 genomes sequenced so far have the genomic features described above and are thus derived from a common ancestor that had them too. The presence in pangolins of an RBD very similar to that of SARS-CoV-2 means that we can infer this was also probably in the virus that jumped to humans. This leaves the insertion of polybasic cleavage site to occur during human-to-human transmission. Estimates of the timing of the most recent common ancestor of SARS-CoV-2 made with current sequence data point to emergence of the virus in late November 2019 to early December 2019 23 , compatible with the earliest retrospectively confirmed cases 24 . Hence, this scenario presumes a period of unrecognized transmission in humans between the initial zoonotic event and the acquisition of the polybasic cleavage site. Sufficient opportunity could have arisen if there had been many prior zoonotic events that produced short chains of human-to-human transmission over an extended period. This is essentially the situation for MERS-CoV, for which all human cases are the result of repeated jumps of the virus from dromedary camels, producing single infections or short transmission chains that eventually resolve, with no adaptation to sustained transmission 25 . Studies of banked human samples could provide information on whether such cryptic spread has occurred. Retrospective serological studies could also be informative, and a few such studies have been conducted showing low-level exposures to SARS-CoV-like coronaviruses in certain areas of China 26 . Critically, however, these studies could not have distinguished whether exposures were due to prior infections with SARS-CoV, SARS-CoV-2 or other SARS-CoV-like coronaviruses. Further serological studies should be conducted to determine the extent of prior human exposure to SARS-CoV-2. 3. Selection during passage Basic research involving passage of bat SARS-CoV-like coronaviruses in cell culture and/or animal models has been ongoing for many years in biosafety level 2 laboratories across the world 27 , and there are documented instances of laboratory escapes of SARS-CoV 28 . We must therefore examine the possibility of an inadvertent laboratory release of SARS-CoV-2. In theory, it is possible that SARS-CoV-2 acquired RBD mutations (Fig. 1a) during adaptation to passage in cell culture, as has been observed in studies of SARS-CoV 11 . The finding of SARS-CoV-like coronaviruses from pangolins with nearly identical RBDs, however, provides a much stronger and more parsimonious explanation of how SARS-CoV-2 acquired these via recombination or mutation 19 . The acquisition of both the polybasic cleavage site and predicted O-linked glycans also argues against culture-based scenarios. New polybasic cleavage sites have been observed only after prolonged passage of low-pathogenicity avian influenza virus in vitro or in vivo 17 . Furthermore, a hypothetical generation of SARS-CoV-2 by cell culture or animal passage would have required prior isolation of a progenitor virus with very high genetic similarity, which has not been described. Subsequent generation of a polybasic cleavage site would have then required repeated passage in cell culture or animals with ACE2 receptors similar to those of humans, but such work has also not previously been described. Finally, the generation of the predicted O-linked glycans is also unlikely to have occurred due to cell-culture passage, as such features suggest the involvement of an immune system 18 . Conclusions In the midst of the global COVID-19 public-health emergency, it is reasonable to wonder why the origins of the pandemic matter. Detailed understanding of how an animal virus jumped species boundaries to infect humans so productively will help in the prevention of future zoonotic events. For example, 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. In addition, identifying the closest viral relatives of SARS-CoV-2 circulating in animals will greatly assist studies of viral function. Indeed, the availability of the RaTG13 bat sequence helped reveal key RBD mutations and the polybasic cleavage site. The genomic features described here may explain in part the infectiousness and transmissibility of SARS-CoV-2 in humans. Although the evidence shows that SARS-CoV-2 is not a purposefully manipulated virus, it is currently impossible to prove or disprove the other theories of its origin described here. However, since we observed all notable SARS-CoV-2 features, including the optimized RBD and polybasic cleavage site, in related coronaviruses in nature, we do not believe that any type of laboratory-based scenario is plausible. More scientific data could swing the balance of evidence to favor one hypothesis over another. Obtaining related viral sequences from animal sources would be the most definitive way of revealing viral origins. For example, a future observation of an intermediate or fully formed polybasic cleavage site in a SARS-CoV-2-like virus from animals would lend even further support to the natural-selection hypotheses. It would also be helpful to obtain more genetic and functional data about SARS-CoV-2, including animal studies. The identification of a potential intermediate host of SARS-CoV-2, as well as sequencing of the virus from very early cases, would similarly be highly informative. Irrespective of the exact mechanisms by which SARS-CoV-2 originated via natural selection, the ongoing surveillance of pneumonia in humans and other animals is clearly of utmost importance.
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            Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses

            Over the past 20 years, several coronaviruses have crossed the species barrier into humans, causing outbreaks of severe, and often fatal, respiratory illness. Since SARS-CoV was first identified in animal markets, global viromics projects have discovered thousands of coronavirus sequences in diverse animals and geographic regions. Unfortunately, there are few tools available to functionally test these viruses for their ability to infect humans, which has severely hampered efforts to predict the next zoonotic viral outbreak. Here, we developed an approach to rapidly screen lineage B betacoronaviruses, such as SARS-CoV and the recent SARS-CoV-2, for receptor usage and their ability to infect cell types from different species. We show that host protease processing during viral entry is a significant barrier for several lineage B viruses and that bypassing this barrier allows several lineage B viruses to enter human cells through an unknown receptor. We also demonstrate how different lineage B viruses can recombine to gain entry into human cells, and confirm that human ACE2 is the receptor for the recently emerging SARS-CoV-2.
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              Human organoids: model systems for human biology and medicine

              The historical reliance of biological research on the use of animal models has sometimes made it challenging to address questions that are specific to the understanding of human biology and disease. But with the advent of human organoids — which are stem cell-derived 3D culture systems — it is now possible to re-create the architecture and physiology of human organs in remarkable detail. Human organoids provide unique opportunities for the study of human disease and complement animal models. Human organoids have been used to study infectious diseases, genetic disorders and cancers through the genetic engineering of human stem cells, as well as directly when organoids are generated from patient biopsy samples. This Review discusses the applications, advantages and disadvantages of human organoids as models of development and disease and outlines the challenges that have to be overcome for organoids to be able to substantially reduce the need for animal experiments.
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                Author and article information

                Contributors
                Journal
                Philos Trans R Soc Lond B Biol Sci
                Philos Trans R Soc Lond B Biol Sci
                RSTB
                royptb
                Philosophical Transactions of the Royal Society B: Biological Sciences
                The Royal Society
                0962-8436
                1471-2970
                November 8, 2021
                September 20, 2021
                September 20, 2021
                : 376
                : 1837 , Theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’ edited by Patrick R. Stephens, Shan Huang and Maxwell Farrell
                : 20200358
                Affiliations
                [ 1 ] Center for Global Health Science and Security, Georgetown University Medical Center, , Washington, DC 20007, USA
                [ 2 ] Department of Microbiology and Immunology, Georgetown University Medical Center, , Washington, DC 20007, USA
                [ 3 ] Department of Ecology and Evolutionary Biology, University of Toronto, , Toronto, Ontario, Canada
                [ 4 ] Public Health Scotland, , Glasgow G2 6QE, UK
                [ 5 ] Cary Institute of Ecosystem Studies, , Millbrook, NY 12545, USA
                [ 6 ] Medical Research Council, University of Glasgow Centre for Virus Research, , Glasgow G61 1QH, UK
                [ 7 ] Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, , Glasgow G12 8QQ, UK
                [ 8 ] O'Neill Institute for National and Global Health Law, Georgetown University Law Center, , Washington, DC 20001, USA
                [ 9 ] Department of Biology, Georgetown University, , Washington, DC 20007, USA
                [ 10 ] Animal and Human Health Program, International Livestock Research Institute, , PO Box 30709-00100, Nairobi, Kenya
                [ 11 ] Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, , Omaha, NE, USA
                [ 12 ] Icahn School of Medicine at Mount Sinai, , New York, NY, USA
                [ 13 ] Department of Biological Sciences, Louisiana State University, , Baton Rouge, LA 70806, USA
                [ 14 ] Department of Biology, Pacific Lutheran University, , Tacoma, WA, USA
                [ 15 ] Department of Microbiology, Immunology, and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, , Fort Collins, CO, USA
                [ 16 ] Department of Biological Sciences, University of Arkansas, , Fayetteville, AR 72701, USA
                [ 17 ] Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, , London, UK
                [ 18 ] Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, , London, UK
                [ 19 ] Centre for the Study of Existential Risk, University of Cambridge, , Cambridge, UK
                [ 20 ] Department of Medical Microbiology and Infectious Diseases, University of Manitoba, , Winnipeg, Manitoba, Canada, R3E 0J9
                [ 21 ] Molecular Epidemiology and Public Health Laboratory, Hopkirk Research Institute, Massey University, , Palmerston North, New Zealand
                [ 22 ] Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, , North Grafton, MA 01536, USA
                [ 23 ] Department of Public Health and Community Medicine, School of Medicine, Tufts University, , Boston, MA 02111, USA
                [ 24 ] University of Nairobi, , Nairobi, Kenya
                [ 25 ] EcoHealth Alliance, , New York, NY 10018, USA
                [ 26 ] Law Futures Centre, Griffith Law School, Griffith University, , Nathan, Queensland 4111, Australia
                [ 27 ] Department of Geography and Emerging Pathogens Institute, University of Florida, , Gainesville, FL, USA
                [ 28 ] School of Life Sciences, University of KwaZulu-Natal, , Durban, South Africa
                [ 29 ] Paul G. Allen School for Global Health, Washington State University, , Pullman, WA, USA
                [ 30 ] Department of Virology, University of Helsinki, , Helsinki, Finland
                [ 31 ] Department of Veterinary Biosciences, University of Helsinki, , Helsinki, Finland
                [ 32 ] Department of Chemical Engineering, Carnegie Mellon University, , Pittsburgh, PA 15213, USA
                [ 33 ] Zoonotic Arbo and Respiratory Virus Program, Centre for Viral Zoonoses, Department of Medical Virology, University of Pretoria, , Pretoria, South Africa
                [ 34 ] Department of Forestry and Wildlife Management, Maasai Mara University, , Narok 20500, Kenya
                Author notes
                Author information
                http://orcid.org/0000-0001-6960-8434
                http://orcid.org/0000-0003-0452-6993
                http://orcid.org/0000-0002-9948-3078
                http://orcid.org/0000-0002-7583-8495
                http://orcid.org/0000-0003-3328-9958
                http://orcid.org/0000-0002-1153-5356
                http://orcid.org/0000-0002-0969-5078
                http://orcid.org/0000-0002-2112-2707
                http://orcid.org/0000-0002-0965-1649
                http://orcid.org/0000-0002-8288-0288
                http://orcid.org/0000-0002-4308-6321
                Article
                rstb20200358
                10.1098/rstb.2020.0358
                8450624
                34538140
                4d9e322d-9e86-4cfd-9841-2fa5a20dacde
                © 2021 The Authors.

                Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

                History
                : July 15, 2021
                Funding
                Funded by: Wellcome Trust, http://dx.doi.org/10.13039/100004440;
                Award ID: 217221/Z/19/Z
                Funded by: Directorate for Biological Sciences, http://dx.doi.org/10.13039/100000076;
                Award ID: BII 2021909
                Funded by: University of Toronto, http://dx.doi.org/10.13039/501100003579;
                Award ID: EEB Fellowship
                Categories
                1001
                87
                Part III: Zoonotic Disease Risk and Impacts
                Opinion Piece
                Custom metadata
                November 8, 2021

                Philosophy of science
                zoonotic risk,epidemic risk,access and benefit sharing,machine learning,global health,viral ecology

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