Host barriers to SARS-CoV-2 demonstrated by ferrets in a high-exposure domestic setting.
04 May 2021-Proceedings of the National Academy of Sciences of the United States of America (National Academy of Sciences)-Vol. 118, Iss: 18
TL;DR: In this paper, the authors compared SARS-CoV-2 sequences from natural and experimental mustelid infections and identified two surface glycoprotein Spike (S) mutations associated with mustelids.
Abstract: Ferrets (Mustela putorius furo) are mustelids of special relevance to laboratory studies of respiratory viruses and have been shown to be susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and onward transmission. Here, we report the results of a natural experiment where 29 ferrets in one home had prolonged, direct contact and constant environmental exposure to two humans with symptomatic disease, one of whom was confirmed positive for SARS-CoV-2. We observed no evidence of SARS-CoV-2 transmission from humans to ferrets based on viral and antibody assays. To better understand this discrepancy in experimental and natural infection in ferrets, we compared SARS-CoV-2 sequences from natural and experimental mustelid infections and identified two surface glycoprotein Spike (S) mutations associated with mustelids. While we found evidence that angiotensin-converting enzyme II provides a weak host barrier, one mutation only seen in ferrets is located in the novel S1/S2 cleavage site and is computationally predicted to decrease furin cleavage efficiency. These data support the idea that host factors interacting with the novel S1/S2 cleavage site may be a barrier in ferret SARS-CoV-2 susceptibility and that domestic ferrets are at low risk of natural infection from currently circulating SARS-CoV-2. We propose two mechanistically grounded hypotheses for mustelid host adaptation of SARS-CoV-2, with possible effects that require additional investigation.
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TL;DR: In this paper, the authors determined the structures of two human monoclonal antibodies-AZD8895 and AZD1061-which form the basis of the investigational antibody cocktail AZD7442, in complex with the receptor-binding domain (RBD) of SARS-CoV-2 to define the genetic and structural basis of neutralization.
Abstract: Understanding the molecular basis for immune recognition of SARS-CoV-2 spike glycoprotein antigenic sites will inform the development of improved therapeutics. We determined the structures of two human monoclonal antibodies-AZD8895 and AZD1061-which form the basis of the investigational antibody cocktail AZD7442, in complex with the receptor-binding domain (RBD) of SARS-CoV-2 to define the genetic and structural basis of neutralization. AZD8895 forms an 'aromatic cage' at the heavy/light chain interface using germ line-encoded residues in complementarity-determining regions (CDRs) 2 and 3 of the heavy chain and CDRs 1 and 3 of the light chain. These structural features explain why highly similar antibodies (public clonotypes) have been isolated from multiple individuals. AZD1061 has an unusually long LCDR1; the HCDR3 makes interactions with the opposite face of the RBD from that of AZD8895. Using deep mutational scanning and neutralization escape selection experiments, we comprehensively mapped the crucial binding residues of both antibodies and identified positions of concern with regards to virus escape from antibody-mediated neutralization. Both AZD8895 and AZD1061 have strong neutralizing activity against SARS-CoV-2 and variants of concern with antigenic substitutions in the RBD. We conclude that germ line-encoded antibody features enable recognition of the SARS-CoV-2 spike RBD and demonstrate the utility of the cocktail AZD7442 in neutralizing emerging variant viruses.
176 citations
TL;DR: In this paper, the authors sequenced full genomes of Vero cell-expanded SARS-CoV-2 inoculum and viruses recovered from cats (n = 6), dogs, cats, and hamsters within 1-to-3-d postexposure.
Abstract: SARS-CoV-2 spillback from humans into domestic and wild animals has been well documented, and an accumulating number of studies illustrate that human-to-animal transmission is widespread in cats, mink, deer, and other species. Experimental inoculations of cats, mink, and ferrets have perpetuated transmission cycles. We sequenced full genomes of Vero cell-expanded SARS-CoV-2 inoculum and viruses recovered from cats (n = 6), dogs (n = 3), hamsters (n = 3), and a ferret (n = 1) following experimental exposure. Five nonsynonymous changes relative to the USA-WA1/2020 prototype strain were near fixation in the stock used for inoculation but had reverted to wild-type sequences at these sites in dogs, cats, and hamsters within 1- to 3-d postexposure. A total of 14 emergent variants (six in nonstructural genes, six in spike, and one each in orf8 and nucleocapsid) were detected in viruses recovered from animals. This included substitutions in spike residues H69, N501, and D614, which also vary in human lineages of concern. Even though a live virus was not cultured from dogs, substitutions in replicase genes were detected in amplified sequences. The rapid selection of SARS-CoV-2 variants in vitro and in vivo reveals residues with functional significance during host switching. These observations also illustrate the potential for spillback from animal hosts to accelerate the evolution of new viral lineages, findings of particular concern for dogs and cats living in households with COVID-19 patients. More generally, this glimpse into viral host switching reveals the unrealized rapidity and plasticity of viral evolution in experimental animal model systems.
51 citations
TL;DR: In this paper, the authors summarized the current findings regarding the susceptibility of different domestic and wild animal species to experimental SARS-CoV-2 infection and provided detailed descriptions of the clinical disease and transmissibility in these animals.
Abstract: SARS-CoV-2 is the etiological agent responsible for the ongoing COVID-19 pandemic, which continues to spread with devastating effects on global health and socioeconomics. The susceptibility of domestic and wild animal species to infection is a critical facet of SARS-CoV-2 ecology, since reverse zoonotic spillover events resulting in SARS-CoV-2 outbreaks in animal populations could result in the establishment of new virus reservoirs. Adaptive mutations in the virus to new animal species could also complicate ongoing mitigation strategies to combat SARS-CoV-2. In addition, animal species susceptible to SARS-CoV-2 infection are essential as standardized preclinical models for the development and efficacy testing of vaccines and therapeutics. In this review, we summarize the current findings regarding the susceptibility of different domestic and wild animal species to experimental SARS-CoV-2 infection and provide detailed descriptions of the clinical disease and transmissibility in these animals. In addition, we outline the documented natural infections in animals that have occurred at the human-animal interface. A comprehensive understanding of animal susceptibility to SARS-CoV-2 is crucial to inform public health, veterinary, and agricultural systems, and to guide environmental policies.
44 citations
TL;DR: In this paper, the authors combine species' ecological and biological traits with three-dimensional modeling of host-virus protein-protein interactions using machine learning to predict the zoonotic capacity of SARS-CoV-2 for greater than 5000 mammals.
Abstract: Back and forth transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between humans and animals will establish wild reservoirs of virus that endanger long-term efforts to control COVID-19 in people and to protect vulnerable animal populations. Better targeting surveillance and laboratory experiments to validate zoonotic potential requires predicting high-risk host species. A major bottleneck to this effort is the few species with available sequences for angiotensin-converting enzyme 2 receptor, a key receptor required for viral cell entry. We overcome this bottleneck by combining species' ecological and biological traits with three-dimensional modelling of host-virus protein-protein interactions using machine learning. This approach enables predictions about the zoonotic capacity of SARS-CoV-2 for greater than 5000 mammals-an order of magnitude more species than previously possible. Our predictions are strongly corroborated by in vivo studies. The predicted zoonotic capacity and proximity to humans suggest enhanced transmission risk from several common mammals, and priority areas of geographic overlap between these species and global COVID-19 hotspots. With molecular data available for only a small fraction of potential animal hosts, linking data across biological scales offers a conceptual advance that may expand our predictive modelling capacity for zoonotic viruses with similarly unknown host ranges.
42 citations
TL;DR: In this article, the authors evaluated a model of experimental acute lung injury as a result of SARS-CoV-2 infection in Syrian golden hamsters and showed significant differences in hamster phospholipidome.
26 citations
References
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TL;DR: SAMtools as discussed by the authors implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Abstract: Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Availability: http://samtools.sourceforge.net
Contact: [email protected]
45,957 citations
TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
Abstract: Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals.
Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ~10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package.
Availability: http://maq.sourceforge.net
Contact: [email protected]
43,862 citations
TL;DR: This work presents some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees.
Abstract: Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting postanalyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU
23,838 citations
TL;DR: Identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China, and it is shown that this virus belongs to the species of SARSr-CoV, indicates that the virus is related to a bat coronav virus.
Abstract: Since the outbreak of severe acute respiratory syndrome (SARS) 18 years ago, a large number of SARS-related coronaviruses (SARSr-CoVs) have been discovered in their natural reservoir host, bats1–4. Previous studies have shown that some bat SARSr-CoVs have the potential to infect humans5–7. Here we report the identification and characterization of a new coronavirus (2019-nCoV), which caused an epidemic of acute respiratory syndrome in humans in Wuhan, China. The epidemic, which started on 12 December 2019, had caused 2,794 laboratory-confirmed infections including 80 deaths by 26 January 2020. Full-length genome sequences were obtained from five patients at an early stage of the outbreak. The sequences are almost identical and share 79.6% sequence identity to SARS-CoV. Furthermore, we show that 2019-nCoV is 96% identical at the whole-genome level to a bat coronavirus. Pairwise protein sequence analysis of seven conserved non-structural proteins domains show that this virus belongs to the species of SARSr-CoV. In addition, 2019-nCoV virus isolated from the bronchoalveolar lavage fluid of a critically ill patient could be neutralized by sera from several patients. Notably, we confirmed that 2019-nCoV uses the same cell entry receptor—angiotensin converting enzyme II (ACE2)—as SARS-CoV. Characterization of full-length genome sequences from patients infected with a new coronavirus (2019-nCoV) shows that the sequences are nearly identical and indicates that the virus is related to a bat coronavirus.
16,857 citations
TL;DR: The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences.
Abstract: Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
13,223 citations