Insights on cross-species transmission of SARS-CoV-2 from structural modeling

AI Promoted Virtual Screening, Structure-Based Hit Optimization, and Synthesis of Novel COVID-19 S-RBD Domain Inhibitors

Coronavirus disease 2019 (COVID-19) is caused by a new, highly pathogenic severe-acute-respiratory syndrome coronavirus 2 (SARS-CoV-2) that infects human cells through its transmembrane spike (S) glycoprotein. The receptor-binding domain (RBD) of the S protein interacts with the angiotensin-converting enzyme II (ACE2) receptor of the host cells. Therefore, pharmacological targeting of this interaction might prevent infection or spread of the virus. Here, we performed a virtual screening to identify small molecules that block S-ACE2 interaction. Large compound libraries were filtered for drug-like properties, promiscuity and protein-protein interaction-targeting ability based on their ADME-Tox descriptors and also to exclude pan-assay interfering compounds. A properly designed AI-based virtual screening pipeline was applied to the remaining compounds, comprising approximately 10% of the starting data sets, searching for molecules that could bind to the RBD of the S protein. All molecules were sorted according to their screening score, grouped based on their structure and postfiltered for possible interaction patterns with the ACE2 receptor, yielding 31 hits. These hit molecules were further tested for their inhibitory effect on Spike RBD/ACE2 (19-615) interaction. Six compounds inhibited the S-ACE2 interaction in a dose-dependent manner while two of them also prevented infection of human cells from a pseudotyped virus whose entry is mediated by the S protein of SARS-CoV-2. Of the two compounds, the benzimidazole derivative CKP-22 protected Vero E6 cells from infection with SARS-CoV-2, as well. Subsequent, hit-to-lead optimization of CKP-22 was effected through the synthesis of 29 new derivatives of which compound CKP-25 suppressed the Spike RBD/ACE2 (19-615) interaction, reduced the cytopathic effect of SARS-CoV-2 in Vero E6 cells (IC50 = 3.5 μM) and reduced the viral load in cell culture supernatants. Early in vitro ADME-Tox studies showed that CKP-25 does not possess biodegradation or liver metabolism issues, while isozyme-specific CYP450 experiments revealed that CKP-25 was a weak inhibitor of the CYP450 system. Moreover, CKP-25 does not elicit mutagenic effect on Escherichia coli WP2 uvrA strain. Thus, CKP-25 is considered a lead compound against COVID-19 infection.

Preventing future zoonosis: SARS-CoV-2 mutations enhance human-animal cross-transmission

The COVID-19 pandemic has driven substantial evolution of the SARS-CoV-2 virus, yielding subvariants that exhibit enhanced infectiousness in humans. However, this adaptive advantage may not universally extend to zoonotic transmission. In this work, we hypothesize that viral adaptations favoring animal hosts do not necessarily correlate with increased human infectivity. In addition, we consider the potential for gain-of-function mutations that could facilitate the virus's rapid evolution in humans following adaptation in animal hosts. Specifically, we identify the SARS-CoV-2 receptor-binding domain (RBD) mutations that enhance human-animal cross-transmission. To this end, we construct a multitask deep learning model, MT-TopLap trained on multiple deep mutational scanning datasets, to accurately predict the binding free energy changes upon mutation for the RBD to ACE2 of various species, including humans, cats, bats, deer, and hamsters. By analyzing these changes, we identified key RBD mutations such as Q498H in SARS-CoV-2 and R493K in the BA.2 variant that are likely to increase the potential for human-animal cross-transmission.

Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source

We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.

Benchmarking the accuracy of structure-based binding affinity predictors on Spike-ACE2 deep mutational interaction set

Since the start of COVID-19 pandemic, a huge effort has been devoted to understanding the Spike (SARS-CoV-2)-ACE2 recognition mechanism. To this end, two deep mutational scanning studies traced the impact of all possible mutations across receptor binding domain (RBD) of Spike and catalytic domain of human ACE2. By concentrating on the interface mutations of these experimental data, we benchmarked six commonly used structure-based binding affinity predictors (FoldX, EvoEF1, MutaBind2, SSIPe, HADDOCK, and UEP). These predictors were selected based on their user-friendliness, accessibility, and speed. As a result of our benchmarking efforts, we observed that none of the methods could generate a meaningful correlation with the experimental binding data. The best correlation is achieved by FoldX (R = -0.51). When we simplified the prediction problem to a binary classification, that is, whether a mutation is enriching or depleting the binding, we showed that the highest accuracy is achieved by FoldX with a 64% success rate. Surprisingly, on this set, simple energetic scoring functions performed significantly better than the ones using extra evolutionary-based terms, as in Mutabind and SSIPe. Furthermore, we demonstrated that recent AI approaches, mmCSM-PPI and TopNetTree, yielded comparable performances to the force field-based techniques. These observations suggest plenty of room to improve the binding affinity predictors in guessing the variant-induced binding profile changes of a host-pathogen system, such as Spike-ACE2. To aid such improvements we provide our benchmarking data at https://github.com/CSB-KaracaLab/RBD-ACE2-MutBench with the option to visualize our mutant models at https://rbd-ace2-mutbench.github.io/.

Competitive fitness and homologous recombination of SARS-CoV-2 variants of concern

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge and cocirculate in humans and wild animals. The factors driving the emergence and replacement of novel variants and recombinants remain incompletely understood. Herein, we comprehensively characterized the competitive fitness of SARS-CoV-2 wild type (WT) and three variants of concern (VOCs), Alpha, Beta and Delta, by coinfection and serial passaging assays in different susceptible cells. Deep sequencing analyses revealed cell-specific competitive fitness: the Beta variant showed enhanced replication fitness during serial passage in Caco-2 cells, whereas the WT and Alpha variant showed elevated fitness in Vero E6 cells. Interestingly, a high level of neutralizing antibody sped up competition and completely reshaped the fitness advantages of different variants. More importantly, single clone purification identified a significant proportion of homologous recombinants that emerged during the passage history, and immune pressure reduced the frequency of recombination. Interestingly, a recombination hot region located between nucleotide sites 22,995 and 28,866 of the viral genomes could be identified in most of the detected recombinants. Our study not only profiled the variable competitive fitness of SARS-CoV-2 under different conditions, but also provided direct experimental evidence of homologous recombination between SARS-CoV-2 viruses, as well as a model for investigating SARS-CoV-2 recombination.

The panzootic potential of SARS-CoV-2

Each year, SARS-CoV-2 is infecting an increasingly unprecedented number of species. In the present article, we combine mammalian phylogeny with the genetic characteristics of isolates found in mammals to elaborate on the host-range potential of SARS-CoV-2. Infections in nonhuman mammals mirror those of contemporary viral strains circulating in humans, although, in certain species, extensive viral circulation has led to unique genetic signatures. As in other recent studies, we found that the conservation of the ACE2 receptor cannot be considered the sole major determinant of susceptibility. However, we are able to identify major clades and families as candidates for increased surveillance. On the basis of our findings, we argue that the use of the term panzootic could be a more appropriate term than pandemic to describe the ongoing scenario. This term better captures the magnitude of the SARS-CoV-2 host range and would hopefully inspire inclusive policy actions, including systematic screenings, that could better support the management of this worldwide event.

Interspecies transmission of SARS CoV-2 with special emphasis on viral mutations and ACE-2 receptor homology roles

COVID-19 outbreak was first reported in 2019, Wuhan, China. The spillover of the disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), to a wide range of pet, zoo, wild, and farm animals has emphasized potential zoonotic and reverse zoonotic viral transmission. Furthermore, it has evoked inquiries about susceptibility of different animal species to SARS-CoV-2 infection and role of these animals as viral reservoirs. Therefore, studying susceptible and non-susceptible hosts for SARS-CoV-2 infection could give a better understanding for the virus and will help in preventing further outbreaks. Here, we review structural aspects of SARS-CoV-2 spike protein, the effect of the different mutations observed in the spike protein, and the impact of ACE2 receptor variations in different animal hosts on inter-species transmission. Moreover, the SARS-CoV-2 spillover chain was reviewed. Combination of SARS-CoV-2 high mutation rate and homology of cellular ACE2 receptors enable the virus to transcend species barriers and facilitate its transmission between humans and animals.

Serological survey of SARS-CoV-2 in companion animals in China

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can be transmitted from human to companion animals. The national wide serological surveillance against SARS-CoV-2 was conducted among pet animals, mainly in cats and dogs, 1 year after the first outbreak of COVID-19 in China. All sera were tested for SARS-CoV-2 IgG antibodies using an indirect enzyme linked immunosorbent assay (ELISA) based on the receptor binding domain (RBD) of spike protein. This late survey takes advantage of the short duration of the serological response in these animals to track recent episode of transmission. A total of 20,592 blood samples were obtained from 25 provinces across 7 geographical regions. The overall seroprevalence of SARS-CoV-2 infections in cats was 0.015% (2/13397; 95% confidence intervals (CI): 0.0, 0.1). The virus infections in cats were only detected in Central (Hubei, 0.375%) and Eastern China (Zhejiang, 0.087%) with a seroprevalence estimated at 0.090 and 0.020%, respectively. In dogs, the seroprevalence of SARS-CoV-2 infections was 0.014% (1/7159; 95% CI: 0.0, 0.1) in the entire nation, seropositive samples were limited to Beijing (0.070%) of Northern China with a prevalence of 0.054%. No seropositive cases were discovered in other geographic regions, nor in other companion animals analyzed in this study. These data reveal the circulation of SARS-CoV-2 in companion animals, although transmission of the virus to domestic cats and dogs is low in China, continuous monitoring is helpful for the better understand of the virus transmission status and the effect on animals.

Variation in the ACE2 receptor has limited utility for SARS-CoV-2 host prediction

Transmission of SARS-CoV-2 from humans to other species threatens wildlife conservation and may create novel sources of viral diversity for future zoonotic transmission. A variety of computational heuristics have been developed to pre-emptively identify susceptible host species based on variation in the angiotensin-converting enzyme 2 (ACE2) receptor used for viral entry. However, the predictive performance of these heuristics remains unknown. Using a newly compiled database of 96 species, we show that, while variation in ACE2 can be used by machine learning models to accurately predict animal susceptibility to sarbecoviruses (accuracy = 80.2%, binomial confidence interval [CI]: 70.8-87.6%), the sites informing predictions have no known involvement in virus binding and instead recapitulate host phylogeny. Models trained on host phylogeny alone performed equally well (accuracy = 84.4%, CI: 75.5-91.0%) and at a level equivalent to retrospective assessments of accuracy for previously published models. These results suggest that the predictive power of ACE2-based models derives from strong correlations with host phylogeny rather than processes which can be mechanistically linked to infection biology. Further, biased availability of ACE2 sequences misleads projections of the number and geographic distribution of at-risk species. Models based on host phylogeny reduce this bias, but identify a very large number of susceptible species, implying that model predictions must be combined with local knowledge of exposure risk to practically guide surveillance. Identifying barriers to viral infection or onward transmission beyond receptor binding and incorporating data which are independent of host phylogeny will be necessary to manage the ongoing risk of establishment of novel animal reservoirs of SARS-CoV-2.

Variations in Cell Surface ACE2 Levels Alter Direct Binding of SARS-CoV-2 Spike Protein and Viral Infectivity: Implications for Measuring Spike Protein Interactions with Animal ACE2 Orthologs

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19), the most severe pandemic in a century. The virus gains access to host cells when the viral spike protein (S-protein) binds to the host cell surface receptor angiotensin-converting enzyme 2 (ACE2). Studies have attempted to understand SARS-CoV-2 S-protein interactions with vertebrate orthologs of ACE2 by expressing ACE2 orthologs in mammalian cells and measuring viral infection or S-protein binding. Often, these cells only transiently express ACE2 proteins, and the levels of ACE2 at the cell surface are not quantified. Here, we describe a cell-based assay that uses stably transfected cells expressing ACE2 proteins in a bicistronic vector with an easy-to-quantify reporter protein, Thy1.1. We found that both the binding of the S-protein receptor-binding domain (RBD) and infection with a SARS-CoV-2 pseudovirus are proportional to the amount of human ACE2 expressed at the cell surface, which can be inferred by quantifying the level of Thy1.1. We also compared different ACE2 orthologs, which were expressed in stably transfected cells expressing equivalent levels of Thy1.1. When ranked for either viral infectivity or RBD binding, mouse ACE2 had a weak to undetectable affinity for S-protein, while human ACE2 had the highest level detected, and feline ACE2 had an intermediate phenotype. The generation of stably transfected cells whose ACE2 level can be normalized for cross-ortholog comparisons allows us to create a reusable cellular library useful for measuring emerging SARS-CoV-2 variants' abilities to potentially infect different animals. IMPORTANCE SARS-CoV-2 is a zoonotic virus responsible for the worst global pandemic in a century. An understanding of how the virus can infect other vertebrate species is important for controlling viral spread and understanding the natural history of the virus. Here, we describe a method to generate cells stably expressing different orthologs of ACE2, the receptor for SARS-CoV-2, on the surface of a human cell line. We find that both the binding of the viral spike protein receptor-binding domain (RBD) and infection of cells with a SARS-CoV-2 pseudovirus are proportional to the ACE2 levels at the cell surface. This method will allow the creation of a library of stably transfected cells expressing similar levels of different vertebrate ACE2 orthologs, which can be used repeatedly for identifying vertebrate species that may be susceptible to infection with SARS-CoV-2 and its many variants.

A novel structure-based approach for identification of vertebrate susceptibility to SARS-CoV-2: Implications for future surveillance programmes

Understanding the origin of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a highly debatable and unresolved issue for scientific communities all over the world. Understanding the mechanism of virus entry to the host cells is crucial to deciphering the susceptibility profiles of animal species to SARS-CoV-2. The interaction of SARS-CoV-2 ligands (receptor-binding domain on spike protein) with its host cell receptor, angiotensin-converting enzyme 2 (ACE2), is a critical determinant of host range and cross-species transmission. In this study, we developed and implemented a rigorous computational approach for predicting binding affinity between 299 ACE2 orthologs from diverse vertebrate species and the SARS-CoV-2 spike protein. The findings show that the SARS-CoV-2 spike protein can bind to a wide range of vertebrate species carrying evolutionary divergent ACE2, implying a broad host range at the virus entry level, which may contribute to cross-species transmission and further viral evolution. Furthermore, the current study facilitated the identification of genetic determinants that may differentiate susceptible from resistant host species based on the conservation of ACE2-spike protein interacting residues in vertebrate host species known to facilitate SARS-CoV-2 infection; however, these genetic determinants warrant in vivo experimental confirmation. The molecular interactions associated with varied binding affinity of distinct ACE2 isoforms in a specific bat species were identified using protein structure analysis, implying the existence of diversified bat species' susceptibility to SARS-CoV-2. The current study's findings highlight the importance of intensive surveillance programmes aimed at identifying susceptible hosts, especially those with the potential to transmit zoonotic pathogens, in order to prevent future outbreaks.

Dynamics of Viral Infection and Evolution of SARS-CoV-2 Variants in the Calabria Area of Southern Italy

In this study, we report on the results of SARS-CoV-2 surveillance performed in an area of Southern Italy for 12 months (from March 2021 to February 2022). To this study, we have sequenced RNA from 609 isolates. We have identified circulating VOCs by Sanger sequencing of the S gene and defined their genotypes by whole-genome NGS sequencing of 157 representative isolates. Our results indicated that B.1 and Alpha were the only circulating lineages in Calabria in March 2021; while Alpha remained the most common variant between April 2021 and May 2021 (90 and 73%, respectively), we observed a concomitant decrease in B.1 cases and appearance of Gamma cases (6 and 21%, respectively); C.36.3 and Delta appeared in June 2021 (6 and 3%, respectively); Delta became dominant in July 2021 while Alpha continued to reduce (46 and 48%, respectively). In August 2021, Delta became the only circulating variant until the end of December 2021. As of January 2022, Omicron emerged and took over Delta (72 and 28%, respectively). No patient carrying Beta, Iota, Mu, or Eta variants was identified in this survey. Among the genomes identified in this study, some were distributed all over Europe (B1_S477N, Alpha_L5F, Delta_T95, Delta_G181V, and Delta_A222V), some were distributed in the majority of Italian regions (B1_S477N, B1_Q675H, Delta_T95I and Delta_A222V), and some were present mainly in Calabria (B1_S477N_T29I, B1_S477N_T29I_E484Q, Alpha_A67S, Alpha_A701S, and Alpha_T724I). Prediction analysis of the effects of mutations on the immune response (i.e., binding to class I MHC and/or recognition of T cells) indicated that T29I in B.1 variant; A701S in Alpha variant; and T19R in Delta variant were predicted to impair binding to class I MHC whereas the mutations A67S identified in Alpha; E484K identified in Gamma; and E156G and ΔF157/R158 identified in Delta were predicted to impair recognition by T cells. In conclusion, we report on the results of SARS-CoV-2 surveillance in Regione Calabria in the period between March 2021 and February 2022, identified variants that were enriched mainly in Calabria, and predicted the effects of identified mutations on host immune response.

An Electrostatically-steered Conformational Selection Mechanism Promotes SARS-CoV-2 Spike Protein Variation

After two years since the outbreak, the COVID-19 pandemic remains a global public health emergency. SARS-CoV-2 variants with substitutions on the spike (S) protein emerge increasing the risk of immune evasion and cross-species transmission. Here, we analyzed the evolution of the S protein as recorded in 276,712 samples collected before the start of vaccination efforts. Our analysis shows that most variants destabilize the S protein trimer, increase its conformational heterogeneity and improve the odds of the recognition by the host cell receptor. Most frequent substitutions promote overall hydrophobicity by replacing charged amino acids, reducing stabilizing local interactions in the unbound S protein trimer. Moreover, our results identify "forbidden" regions that rarely show any sequence variation, and which are related to conformational changes occurring upon fusion. These results are significant for understanding the structure and function of SARS-CoV-2 related proteins which is a critical step in vaccine development and epidemiological surveillance.

Characterization of SARS-CoV-2 Spike mutations important for infection of mice and escape from human immune sera

Due to differences in human and murine angiotensin converting enzyme 2 (ACE-2) receptor, initially available SARS-CoV-2 isolates could not infect mice. Here we show that serial passaging of USA-WA1/2020 strain in mouse lungs results in "mouse-adapted" SARS-CoV-2 (MA-SARS-CoV-2) with mutations in S, M, and N genes, and a twelve-nucleotide insertion in the S gene. MA-SARS-CoV-2 infection causes mild disease, with more pronounced morbidity depending on genetic background and in aged and obese mice. Two mutations in the S gene associated with mouse adaptation (N501Y, H655Y) are present in SARS-CoV-2 variants of concern (VoCs). N501Y in the receptor binding domain of viruses of the B.1.1.7, B.1.351, P.1 and B.1.1.529 lineages (Alpha, Beta, Gamma and Omicron variants) is associated with high transmissibility and allows VoCs to infect wild type mice. We further show that S protein mutations of MA-SARS-CoV-2 do not affect neutralization efficiency by human convalescent and post vaccination sera.

Transmission of SARS-CoV-2 from humans to animals and potential host adaptation

SARS-CoV-2, the causative agent of the COVID-19 pandemic, can infect a wide range of mammals. Since its spread in humans, secondary host jumps of SARS-CoV-2 from humans to multiple domestic and wild populations of mammals have been documented. Understanding the extent of adaptation to these animal hosts is critical for assessing the threat that the spillback of animal-adapted SARS-CoV-2 into humans poses. We compare the genomic landscapes of SARS-CoV-2 isolated from animal species to that in humans, profiling the mutational biases indicative of potentially different selective pressures in animals. We focus on viral genomes isolated from mink (Neovison vison) and white-tailed deer (Odocoileus virginianus) for which multiple independent outbreaks driven by onward animal-to-animal transmission have been reported. We identify five candidate mutations for animal-specific adaptation in mink (NSP9_G37E, Spike_F486L, Spike_N501T, Spike_Y453F, ORF3a_L219V), and one in deer (NSP3a_L1035F), though they appear to confer a minimal advantage for human-to-human transmission. No considerable changes to the mutation rate or evolutionary trajectory of SARS-CoV-2 has resulted from circulation in mink and deer thus far. Our findings suggest that minimal adaptation was required for onward transmission in mink and deer following human-to-animal spillover, highlighting the 'generalist' nature of SARS-CoV-2 as a mammalian pathogen.

Insights into SARS-CoV-2's Mutations for Evading Human Antibodies: Sacrifice and Survival

The highly infectious SARS-CoV-2 variant B.1.351 that first emerged in South Africa with triple mutations (N501Y, K417N, and E484K) is globally worrisome. It is known that N501Y and E484K can enhance binding between the coronavirus receptor domain (RBD) and human ACE2. However, the K417N mutation appears to be unfavorable as it removes one interfacial salt bridge. Here, we show that despite the decrease in binding affinity (1.48 kcal/mol) between RBD and ACE2, the K417N mutation abolishes a buried interfacial salt bridge between the RBD and neutralizing antibody CB6. This substantially reduces their binding energy by 9.59 kcal/mol, thus facilitating the process by which the variant efficiently eludes CB6 (including many other antibodies). Our theoretical predictions agree with existing experimental findings. Harnessing the revealed molecular mechanisms makes it possible to redesign therapeutic antibodies, thus making them more efficacious.

Yeast surface display-based identification of ACE2 mutations that modulate SARS-CoV-2 spike binding across multiple mammalian species

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with different mammalian angiotensin-converting enzyme II (ACE2) cell entry receptors elucidates determinants of virus transmission and facilitates development of vaccines for humans and animals. Yeast display-based directed evolution identified conserved ACE2 mutations that increase spike binding across multiple species. Gln42Leu increased ACE2-spike binding for human and four of four other mammalian ACE2s; Leu79Ile had an effect for human and three of three mammalian ACE2s. These residues are highly represented, 83% for Gln42 and 56% for Leu79, among mammalian ACE2s. The above findings can be important in protecting humans and animals from existing and future SARS-CoV-2 variants.

ACE2 is the critical in vivo receptor for SARS-CoV-2 in a novel COVID-19 mouse model with TNF- and IFNγ-driven immunopathology

Despite tremendous progress in the understanding of COVID-19, mechanistic insight into immunological, disease-driving factors remains limited. We generated maVie16, a mouse-adapted SARS-CoV-2, by serial passaging of a human isolate. In silico modeling revealed how only three Spike mutations of maVie16 enhanced interaction with murine ACE2. maVie16 induced profound pathology in BALB/c and C57BL/6 mice, and the resulting mouse COVID-19 (mCOVID-19) replicated critical aspects of human disease, including early lymphopenia, pulmonary immune cell infiltration, pneumonia, and specific adaptive immunity. Inhibition of the proinflammatory cytokines IFNγ and TNF substantially reduced immunopathology. Importantly, genetic ACE2-deficiency completely prevented mCOVID-19 development. Finally, inhalation therapy with recombinant ACE2 fully protected mice from mCOVID-19, revealing a novel and efficient treatment. Thus, we here present maVie16 as a new tool to model COVID-19 for the discovery of new therapies and show that disease severity is determined by cytokine-driven immunopathology and critically dependent on ACE2 in vivo.

Yeast surface display-based identification of ACE2 mutations that modulate SARS-CoV-2 spike binding across multiple mammalian species

Understanding how SARS-CoV-2 interacts with different mammalian angiotensin-converting enzyme II (ACE2) cell entry receptors elucidates determinants of virus transmission and facilitates development of vaccines for humans and animals. Yeast display-based directed evolution identified conserved ACE2 mutations that increase spike binding across multiple species. Gln42Leu increased ACE2-spike binding for human and four of four other mammalian ACE2s; Leu79Ile had a effect for human and three of three mammalian ACE2s. These residues are highly represented, 83% for Gln42 and 56% for Leu79, among mammalian ACE2s. The above findings can be important in protecting humans and animals from existing and future SARS-CoV-2 variants.

Infection of wild-type mice by SARS-CoV-2 B.1.351 variant indicates a possible novel cross-species transmission route

COVID-19 is identified as a zoonotic disease caused by SARS-CoV-2, which also can cross-transmit to many animals but not mice. Genetic modifications of SARS-CoV-2 or mice enable the mice susceptible to viral infection. Although neither is the natural situation, they are currently utilized to establish mouse infection models. Here we report a direct contact transmission of SARS-CoV-2 variant B.1.351 in wild-type mice. The SARS-CoV-2 (B.1.351) replicated efficiently and induced significant pathological changes in lungs and tracheas, accompanied by elevated proinflammatory cytokines in the lungs and sera. Mechanistically, the receptor-binding domain (RBD) of SARS-CoV-2 (B.1.351) spike protein turned to a high binding affinity to mouse angiotensin-converting enzyme 2 (mACE2), allowing the mice highly susceptible to SARS-CoV-2 (B.1.351) infection. Our work suggests that SARS-CoV-2 (B.1.351) expands the host range and therefore increases its transmission route without adapted mutation. As the wild house mice live with human populations quite closely, this possible transmission route could be potentially risky. In addition, because SARS-CoV-2 (B.1.351) is one of the major epidemic strains and the mACE2 in laboratory-used mice is naturally expressed and regulated, the SARS-CoV-2 (B.1.351)/mice could be a much convenient animal model system to study COVID-19 pathogenesis and evaluate antiviral inhibitors and vaccines.

Understanding the prevalence of SARS-CoV-2 (COVID-19) exposure in companion, captive, wild, and farmed animals

Several animal species, including ferrets, hamsters, monkeys, and raccoon dogs, have been shown to be susceptible to experimental infection by the human severe acute respiratory syndrome coronaviruses, such as SARS-CoV and SARS-CoV-2, which were responsible for the 2003 SARS outbreak and the 2019 coronavirus disease (COVID-19) pandemic, respectively. Emerging studies have shown that SARS-CoV-2 natural infection of pet dogs and cats is also possible, but its prevalence is not fully understood. Experimentally, it has been demonstrated that SARS-CoV-2 replicates more efficiently in cats than in dogs and that cats can transmit the virus through aerosols. With approximately 470 million pet dogs and 370 million pet cats cohabitating with their human owners worldwide, the finding of natural SARS-CoV-2 infection in these household pets has important implications for potential zoonotic transmission events during the COVID-19 pandemic as well as future SARS-related outbreaks. Here, we describe some of the ongoing worldwide surveillance efforts to assess the prevalence of SARS-CoV-2 exposure in companion, captive, wild, and farmed animals, as well as provide some perspectives on these efforts including the intra- and inter-species coronavirus transmissions, evolution, and their implications on the human-animal interface along with public health. Some ongoing efforts to develop and implement a new COVID-19 vaccine for animals are also discussed. Surveillance initiatives to track SARS-CoV-2 exposures in animals are necessary to accurately determine their impact on veterinary and human health, as well as define potential reservoir sources of the virus and its evolutionary and transmission dynamics.

SARS-CoV-2 in animals: potential for unknown reservoir hosts and public health implications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) is suspected of having originated in 2019 in China from a coronavirus infected bat of the genus Rhinolophus. Following the initial emergence, possibly facilitated by a mammalian bridge host, SARS-CoV-2 is currently transmitted across the globe via efficient human-to-human transmission. Results obtained from experimental studies indicate that animal species such as cats, ferrets, raccoon dogs, cynomolgus macaques, rhesus macaques, white-tailed deer, rabbits, Egyptian fruit bats, and Syrian hamsters are susceptible to SARS-CoV-2 infection, and that cat-to-cat and ferret-to-ferret transmission can take place via contact and air. However, natural infections of SARS-CoV-2 have been reported only in pet dogs and cats, tigers, lions, snow leopards, pumas, and gorillas at zoos, and farmed mink and ferrets. Even though human-to-animal spillover has been reported at several instances, SARS-CoV-2 transmission from animals-to-humans has only been reported from mink-to-humans in mink farms. Following the rapid transmission of SARS-CoV-2 within the mink population, a new mink-associated SARS-CoV-2 variant emerged that was identified in both humans and mink. The increasing reports of SARS-CoV-2 in carnivores indicate the higher susceptibility of animal species belonging to this order. The sporadic reports of SARS-CoV-2 infection in domestic and wild animal species require further investigation to determine if SARS-CoV-2 or related Betacoronaviruses can get established in kept, feral or wild animal populations, which may eventually act as viral reservoirs. This review analyzes the current evidence of SARS-CoV-2 natural infection in domestic and wild animal species and their possible implications on public health.

Evidence for a mouse origin of the SARS-CoV-2 Omicron variant

The rapid accumulation of mutations in the SARS-CoV-2 Omicron variant that enabled its outbreak raises questions as to whether its proximal origin occurred in humans or another mammalian host. Here, we identified 45 point mutations that Omicron acquired since divergence from the B.1.1 lineage. We found that the Omicron spike protein sequence was subjected to stronger positive selection than that of any reported SARS-CoV-2 variants known to evolve persistently in human hosts, suggesting a possibility of host-jumping. The molecular spectrum of mutations (i.e., the relative frequency of the 12 types of base substitutions) acquired by the progenitor of Omicron was significantly different from the spectrum for viruses that evolved in human patients but resembled the spectra associated with virus evolution in a mouse cellular environment. Furthermore, mutations in the Omicron spike protein significantly overlapped with SARS-CoV-2 mutations known to promote adaptation to mouse hosts, particularly through enhanced spike protein binding affinity for the mouse cell entry receptor. Collectively, our results suggest that the progenitor of Omicron jumped from humans to mice, rapidly accumulated mutations conducive to infecting that host, then jumped back into humans, indicating an inter-species evolutionary trajectory for the Omicron outbreak.

Predicting the zoonotic capacity of mammals to transmit SARS-CoV-2

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.

Evolutionary and Phenotypic Characterization of Two Spike Mutations in European Lineage 20E of SARS-CoV-2

We have detected two mutations in the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at amino acid positions 1163 and 1167 that appeared independently in multiple transmission clusters and different genetic backgrounds. Furthermore, both mutations appeared together in a cluster of 1,627 sequences belonging to clade 20E. This cluster is characterized by 12 additional single nucleotide polymorphisms but no deletions. The available structural information on the S protein in the pre- and postfusion conformations predicts that both mutations confer rigidity, which could potentially decrease viral fitness. Accordingly, we observed reduced infectivity of this spike genotype relative to the ancestral 20E sequence in vitro, and the levels of viral RNA in nasopharyngeal swabs were not significantly higher. Furthermore, the mutations did not impact thermal stability or antibody neutralization by sera from vaccinated individuals but moderately reduce neutralization by convalescent-phase sera from the early stages of the pandemic. Despite multiple successful appearances of the two spike mutations during the first year of SARS-CoV-2 evolution, the genotype with both mutations was displaced upon the expansion of the 20I (Alpha) variant. The midterm fate of the genotype investigated was consistent with the lack of advantage observed in the clinical and experimental data.

The future of zoonotic risk prediction

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'.

Variations in cell-surface ACE2 levels alter direct binding of SARS-CoV-2 Spike protein and viral infectivity: Implications for measuring Spike protein interactions with animal ACE2 orthologs

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19, the most severe pandemic in a century. The virus gains access to host cells when the viral Spike protein (S-protein) binds to the host cell-surface receptor angiotensin-converting enzyme 2 (ACE2). Studies have attempted to understand SARS-CoV-2 S-protein interaction with vertebrate orthologs of ACE2 by expressing ACE2 orthologs in mammalian cells and measuring viral infection or S-protein binding. Often these cells only transiently express ACE2 proteins and levels of ACE2 at the cell surface are not quantified. Here, we describe a cell-based assay that uses stably transfected cells expressing ACE2 proteins in a bi-cistronic vector with an easy to quantify reporter protein to normalize ACE2 expression. We found that both binding of the S-protein receptor-binding domain (RBD) and infection with a SARS-CoV-2 pseudovirus is proportional to the amount of human ACE2 expressed at the cell surface, which can be inferred by quantifying the level of reporter protein, Thy1.1. We also compared different ACE2 orthologs which were expressed in stably transfected cells expressing equivalent levels of Thy1.1. When ranked for either viral infectivity or RBD binding, mouse ACE2 had a weak to undetectable affinity for S-protein while human ACE2 was the highest level detected and feline ACE2 had an intermediate phenotype. The generation of stably transfected cells whose ACE2 level can be normalized for cross-ortholog comparisons allows us to create a reusable cellular library useful for measuring emerging SARS-CoV-2 variant's ability to potentially infect different animals.

IMPORTANCE

SARS-CoV-2 is a zoonotic virus responsible for the worst global pandemic in a century. An understanding of how the virus can infect other vertebrate species is important for controlling viral spread and understanding the natural history of the virus. Here we describe a method to generate cells stably expressing equivalent levels of different ACE2 orthologs, the receptor for SARS-CoV-2, on the surface of a human cell line. We find that both binding of the viral Spike protein receptor binding domain (RBD) and infection of cells with a SARS-CoV-2 pseudovirus are proportional to ACE2 levels at the cell surface. Adaptation of this method will allow for the creation of a library of stable transfected cells expressing equivalent levels of different vertebrate ACE2 orthologs which can be repeatedly used for identifying vertebrate species which may be susceptible to infection with SARS-CoV-2 and its many variants.

Orchestrating an Optimized Next-Generation Sequencing-Based Cloud Workflow for Robust Viral Identification during Pandemics

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a novel pandemic event following the swine flu that occurred in 2009, which was caused by the influenza A virus (H1N1 subtype). The accurate identification of the huge number of samples during a pandemic still remains a challenge. In this study, we integrate two technologies, next-generation sequencing and cloud computing, into an optimized workflow version that uses a specific identification algorithm on the designated cloud platform. We use 182 samples (92 for COVID-19 and 90 for swine flu) with short-read sequencing data from two open-access datasets to represent each pandemic and evaluate our workflow performance based on an index specifically created for SARS-CoV-2 or H1N1. Results show that our workflow could differentiate cases between the two pandemics with a higher accuracy depending on the index used, especially when the index that exclusively represented each dataset was used. Our workflow substantially outperforms the original complete identification workflow available on the same platform in terms of time and cost by preserving essential tools internally. Our workflow can serve as a powerful tool for the robust identification of cases and, thus, aid in controlling the current and future pandemics.

Cell entry by SARS-CoV-2

Severe acute respiratory syndrome virus 2 (SARS-CoV-2) invades host cells by interacting with receptors/coreceptors, as well as with other cofactors, via its spike (S) protein that further mediates fusion between viral and cellular membranes. The host membrane protein, angiotensin-converting enzyme 2 (ACE2), is the major receptor for SARS-CoV-2 and is a crucial determinant for cross-species transmission. In addition, some auxiliary receptors and cofactors are also involved that expand the host/tissue tropism of SARS-CoV-2. After receptor engagement, specific proteases are required that cleave the S protein and trigger its fusogenic activity. Here we discuss the recent advances in understanding the molecular events during SARS-CoV-2 entry which will contribute to developing vaccines and therapeutics.

Temperature-Dependent Conformational Evolution of SARS CoV-2 RNA Genome Using Network Analysis

Understanding the dynamics of the SARS CoV-2 RNA genome and its dependence on temperature is necessary to fight the current COVID-19 crisis. Computationally, the handling of large data is a major challenge in the elucidation of the structures of RNA. This work presents network analysis as an important tool to see the conformational evolution and the most dominant structures of the RNA genome at six different temperatures. It effectively distinguished different communities of RNA having structural variation. It is found that at higher temperatures (348 K and above), 80% of the RNA structure is destroyed in both the SPC/E and mTIP3P water models. The thermal denaturation free energy change ΔΔG value calculated for the long-lived structure at higher temperatures of 348 and 363 K ranges from 2.58 to 2.78 kcal/mol for the SPC/E water model, which agrees well with the experimentally reported thermal denaturation free energy range of 2.874 kcal/mol of SARS CoV-NP at normal pH. At higher temperatures, the stability of RNA conformation is found to be due to the existence of non-native base pairs in the SPC/E water model.

ACE2-Variants Indicate Potential SARS-CoV-2-Susceptibility in Animals: A Molecular Dynamics Study

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to be a global threat, causing millions of deaths worldwide. SARS-CoV-2 is an enveloped virus with spike (S) glycoproteins conferring binding to the host cell's angiotensin-converting enzyme 2 (ACE2), which is critical for cellular entry. The host range of the virus extends well beyond humans and non-human primates. Natural and experimental infections have confirmed the high susceptibility of cats, ferrets, and Syrian hamsters, whereas dogs, mice, rats, pigs, and chickens are refractory to SARS-CoV-2 infection. To investigate the underlying reason for the variable susceptibility observed in different species, we have developed molecular descriptors to efficiently analyse dynamic simulation models of complexes between SARS-CoV-2 S and ACE2. Our extensive analyses represent the first systematic structure-based approach that allows predictions of species susceptibility to SARS-CoV-2 infection.

ACE2-lentiviral transduction enables mouse SARS-CoV-2 infection and mapping of receptor interactions

SARS-CoV-2 uses the human ACE2 (hACE2) receptor for cell attachment and entry, with mouse ACE2 (mACE2) unable to support infection. Herein we describe an ACE2-lentivirus system and illustrate its utility for in vitro and in vivo SARS-CoV-2 infection models. Transduction of non-permissive cell lines with hACE2 imparted replication competence, and transduction with mACE2 containing N30D, N31K, F83Y and H353K substitutions, to match hACE2, rescued SARS-CoV-2 replication. Intrapulmonary hACE2-lentivirus transduction of C57BL/6J mice permitted significant virus replication in lung epithelium. RNA-Seq and histological analyses illustrated that this model involved an acute inflammatory disease followed by resolution and tissue repair, with a transcriptomic profile similar to that seen in COVID-19 patients. hACE2-lentivirus transduction of IFNAR-/- and IL-28RA-/- mouse lungs was used to illustrate that loss of type I or III interferon responses have no significant effect on virus replication. However, their importance in driving inflammatory responses was illustrated by RNA-Seq analyses. We also demonstrate the utility of the hACE2-lentivirus transduction system for vaccine evaluation in C57BL/6J mice. The ACE2-lentivirus system thus has broad application in SARS-CoV-2 research, providing a tool for both mutagenesis studies and mouse model development.

Predicting the zoonotic capacity of mammals to transmit SARS-CoV-2

Back and forth transmission of SARS-CoV-2 between humans and animals may lead to wild reservoirs of virus that can endanger efforts toward long-term control of COVID-19 in people, and protecting vulnerable animal populations that are particularly susceptible to lethal disease. Predicting high risk host species is key to targeting field surveillance and lab experiments that validate host zoonotic potential. A major bottleneck to predicting animal hosts is the small number of species with available molecular information about the structure of ACE2, a key cellular receptor required for viral cell entry. We overcome this bottleneck by combining species' ecological and biological traits with 3D modeling of virus and host cell protein interactions using machine learning methods. This approach enables predictions about the zoonotic capacity of SARS-CoV-2 for over 5,000 mammals - an order of magnitude more species than previously possible. The high accuracy predictions achieved by this approach are strongly corroborated by in vivo empirical studies. We identify numerous common mammal species whose predicted zoonotic capacity and close proximity to humans may further enhance the risk of spillover and spillback transmission of SARS-CoV-2. Our results reveal high priority areas of geographic overlap between global COVID-19 hotspots and potential new mammal hosts of SARS-CoV-2. With molecular sequence data available for only a small fraction of potential host species, predictive modeling integrating data across multiple biological scales offers a conceptual advance that may expand our predictive capacity for zoonotic viruses with similarly unknown and potentially broad host ranges.

In silico comparison of SARS-CoV-2 spike protein-ACE2 binding affinities across species and implications for virus origin

The devastating impact of the COVID-19 pandemic caused by SARS-coronavirus 2 (SARS-CoV-2) has raised important questions about its origins and the mechanism of its transfer to humans. A further question was whether companion or commercial animals could act as SARS-CoV-2 vectors, with early data suggesting susceptibility is species specific. To better understand SARS-CoV-2 species susceptibility, we undertook an in silico structural homology modelling, protein-protein docking, and molecular dynamics simulation study of SARS-CoV-2 spike protein's ability to bind angiotensin converting enzyme 2 (ACE2) from relevant species. Spike protein exhibited the highest binding to human (h)ACE2 of all the species tested, forming the highest number of hydrogen bonds with hACE2. Interestingly, pangolin ACE2 showed the next highest binding affinity despite having a relatively low sequence homology, whereas the affinity of monkey ACE2 was much lower despite its high sequence similarity to hACE2. These differences highlight the power of a structural versus a sequence-based approach to cross-species analyses. ACE2 species in the upper half of the predicted affinity range (monkey, hamster, dog, ferret, cat) have been shown to be permissive to SARS-CoV-2 infection, supporting a correlation between binding affinity and infection susceptibility. These findings show that the earliest known SARS-CoV-2 isolates were surprisingly well adapted to bind strongly to human ACE2, helping explain its efficient human to human respiratory transmission. This study highlights how in silico structural modelling methods can be used to rapidly generate information on novel viruses to help predict their behaviour and aid in countermeasure development.

A Comparative Analysis of Coronavirus Nucleocapsid (N) Proteins Reveals the SADS-CoV N Protein Antagonizes IFN-β Production by Inducing Ubiquitination of RIG-I

Coronaviruses (CoVs) are a known global threat, and most recently the ongoing COVID-19 pandemic has claimed more than 2 million human lives. Delays and interference with IFN responses are closely associated with the severity of disease caused by CoV infection. As the most abundant viral protein in infected cells just after the entry step, the CoV nucleocapsid (N) protein likely plays a key role in IFN interruption. We have conducted a comprehensive comparative analysis and report herein that the N proteins of representative human and animal CoVs from four different genera [swine acute diarrhea syndrome CoV (SADS-CoV), porcine epidemic diarrhea virus (PEDV), severe acute respiratory syndrome CoV (SARS-CoV), SARS-CoV-2, Middle East respiratory syndrome CoV (MERS-CoV), infectious bronchitis virus (IBV) and porcine deltacoronavirus (PDCoV)] suppress IFN responses by multiple strategies. In particular, we found that the N protein of SADS-CoV interacted with RIG-I independent of its RNA binding activity, mediating K27-, K48- and K63-linked ubiquitination of RIG-I and its subsequent proteasome-dependent degradation, thus inhibiting the host IFN response. These data provide insight into the interaction between CoVs and host, and offer new clues for the development of therapies against these important viruses.

Zoonotic and Reverse Zoonotic Transmissibility of SARS-CoV-2

The Coronavirus Disease 2019 (COVID-19) is the first known pandemic caused by a coronavirus. Its causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), appears to be capable of infecting different mammalian species. Recent detections of this virus in pet, zoo, wild, and farm animals have compelled inquiry regarding the zoonotic (animal-to-human) and reverse zoonotic (human-to-animal) transmissibility of SARS-CoV-2 with the potential of COVID-19 pandemic evolving into a panzootic.

It is important to monitor the global spread of disease and to assess the significance of genomic changes to support prevention and control efforts during a pandemic. An understanding of the SARS-CoV-2 epidemiology provides opportunities to prevent the risk of repeated re-infection of humans and requires a robust One Health-based investigation. This review paper describes the known properties and the existing gaps in scientific knowledge about the zoonotic and reverse zoonotic transmissibility of the novel virus SARS-CoV-2 and the COVID-19 disease it causes.

UnityMol prototype for FAIR sharing of molecular-visualization experiences: from pictures in the cloud to collaborative virtual reality exploration in immersive 3D environments

Motivated by the current COVID-19 pandemic, which has spurred a substantial flow of structural data, the use of molecular-visualization experiences to make these data sets accessible to a broad audience is described. Using a variety of technology vectors related to the cloud, 3D and virtual reality gear, how to share curated visualizations of structural biology, modeling and/or bioinformatics data sets for interactive and collaborative exploration is examined. FAIR is discussed as an overarching principle for sharing such visualizations. Four initial example scenes related to recent COVID-19 structural data are provided, together with a ready-to-use (and share) implementation in the UnityMol software.

Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: Lessons from the pandemic and preparing for future health crises

There is an urgent need to identify new therapies that prevent SARS-CoV-2 infection and improve the outcome of COVID-19 patients. This pandemic has thus spurred intensive research in most scientific areas and in a short period of time, several vaccines have been developed. But, while the race to find vaccines for COVID-19 has dominated the headlines, other types of therapeutic agents are being developed. In this mini-review, we report several databases and online tools that could assist the discovery of anti-SARS-CoV-2 small chemical compounds and peptides. We then give examples of studies that combined in silico and in vitro screening, either for drug repositioning purposes or to search for novel bioactive compounds. Finally, we question the overall lack of discussion and plan observed in academic research in many countries during this crisis and suggest that there is room for improvement.

Vasculitis and Neutrophil Extracellular Traps in Lungs of Golden Syrian Hamsters With SARS-CoV-2

Neutrophil extracellular traps (NETs) have been identified as one pathogenetic trigger in severe COVID-19 cases and therefore well-described animal models to understand the influence of NETs in COVID-19 pathogenesis are needed. SARS-CoV-2 infection causes infection and interstitial pneumonia of varying severity in humans and COVID-19 models. Pulmonary as well as peripheral vascular lesions represent a severe, sometimes fatal, disease complication of unknown pathogenesis in COVID-19 patients. Furthermore, neutrophil extracellular traps (NETs), which are known to contribute to vessel inflammation or endothelial damage, have also been shown as potential driver of COVID-19 in humans. Though most studies in animal models describe the pulmonary lesions characterized by interstitial inflammation, type II pneumocyte hyperplasia, edema, fibrin formation and infiltration of macrophages and neutrophils, detailed pathological description of vascular lesions or NETs in COVID-19 animal models are lacking so far. Here we report different types of pulmonary vascular lesions in the golden Syrian hamster model of COVID-19. Vascular lesions included endothelialitis and vasculitis at 3 and 6 days post infection (dpi), and were almost nearly resolved at 14 dpi. Importantly, virus antigen was present in pulmonary lesions, but lacking in vascular alterations. In good correlation to these data, NETs were detected in the lungs of infected animals at 3 and 6 dpi. Hence, the Syrian hamster seems to represent a useful model to further investigate the role of vascular lesions and NETs in COVID-19 pathogenesis.

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

The N501Y mutation in SARS-CoV-2 spike leads to morbidity in obese and aged mice and is neutralized by convalescent and post-vaccination human sera

The current COVID-19 (coronavirus disease 19) pandemic, caused by SARS-CoV-2, disproportionally affects the elderly and people with comorbidities like obesity and associated type 2 diabetes mellitus. Small animal models are crucial for the successful development and validation of antiviral vaccines, therapies and to study the role that comorbidities have on the outcome of viral infections. The initially available SARS-CoV-2 isolates require adaptation in order to use the mouse angiotensin converting enzyme 2 (mACE-2) entry receptor and to productively infect the cells of the murine respiratory tract. We have "mouse-adapted" SARS-CoV-2 by serial passaging a clinical virus isolate in the lungs of mice. We then used low doses of this virus in mouse models for advanced age, diabetes and obesity. Similar to SARS-CoV-2 infection in humans, the outcome of infection with mouse-adapted SARS-CoV-2 resulted in enhanced morbidity in aged and diabetic obese mice. Mutations associated with mouse adaptation occurred in the S, M, N and ORF8 genes. Interestingly, one mutation in the receptor binding domain of the S protein results in the change of an asparagine to tyrosine residue at position 501 (N501Y). This mutation is also present in the newly emerging SARS-CoV-2 variant viruses reported in the U.K. (20B/501Y.V1, B1.1.7 lineage) that is epidemiologically associated with high human to human transmission. We show that human convalescent and post vaccination sera can neutralize the newly emerging N501Y virus variant with similar efficiency as that of the reference USA-WA1/2020 virus, suggesting that current SARS-CoV-2 vaccines will protect against the 20B/501Y.V1 strain.

Predicting susceptibility to SARS-CoV-2 infection based on structural differences in ACE2 across species

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the global pandemic of coronavirus disease-2019 (COVID-19). SARS-CoV-2 is a zoonotic disease, but little is known about variations in species susceptibility that could identify potential reservoir species, animal models, and the risk to pets, wildlife, and livestock. Certain species, such as domestic cats and tigers, are susceptible to SARS-CoV-2 infection, while other species such as mice and chickens are not. Most animal species, including those in close contact with humans, have unknown susceptibility. Hence, methods to predict the infection risk of animal species are urgently needed. SARS-CoV-2 spike protein binding to angiotensin-converting enzyme 2 (ACE2) is critical for viral cell entry and infection. Here we integrate species differences in susceptibility with multiple in-depth structural analyses to identify key ACE2 amino acid positions including 30, 83, 90, 322, and 354 that distinguish susceptible from resistant species. Using differences in these residues across species, we developed a susceptibility score that predicts an elevated risk of SARS-CoV-2 infection for multiple species including horses and camels. We also demonstrate that SARS-CoV-2 is nearly optimal for binding ACE2 of humans compared to other animals, which may underlie the highly contagious transmissibility of this virus among humans. Taken together, our findings define potential ACE2 and SARS-CoV-2 residues for therapeutic targeting and identification of animal species on which to focus research and protection measures for environmental and public health.