Spatial epidemiology and genetic diversity of SARS-CoV-2 and related coronaviruses in domestic and wild animals

Assessing the emergence time of SARS-CoV-2 zoonotic spillover

Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.

Suburban Population of Bobcats (Lynx rufus) in Connecticut, USA, Tested Negative for SARS-CoV-2, November 2021-February 2022

A SARS-CoV-2 genomic and serologic survey was performed in a population of bobcats (Lynx rufus) inhabiting the state of Connecticut, USA. Wild animal populations are becoming established in densely populated cities with increased likelihood of direct or indirect contact with humans, as well as with household cats and dogs. Wild-caught bobcats (n=38) tested negative for SARS-CoV-2 genomic RNA by reverse-transcription quantitative PCR and for virus-neutralizing antibodies by ELISA, suggesting that either the species is not susceptible to SARS-CoV-2 or that the surveyed population has not yet been exposed to a source of infectious virus. However, this limited survey cannot rule out that human-to-bobcat or unknown reservoir-to-bobcat transmission of the virus occurs in nature.

Co-Circulation of Multiple Coronavirus Genera and Subgenera during an Epizootic of Lethal Respiratory Disease in Newborn Alpacas (Vicugna pacos) in Peru: First Report of Bat-like Coronaviruses in Alpacas

Coronaviruses (CoVs) infect a wide range of hosts, including humans, domestic animals, and wildlife, typically causing mild-to-severe respiratory or enteric disease. The main objective of this study was to identify CoV genera and subgenera detected in Peruvian alpacas. Lung lavage specimens were collected from 32 animals aged 1 to 6 weeks. CoVs were identified by using RT-PCR to amplify a pan-CoV conserved region of the RNA-dependent RNA polymerase-encoding gene. A nested PCR was performed to identify β-CoVs. Then, β-CoV-positive samples were subjected to RT-PCR using specific primers to identify the Embecovirus subgenus. Out of 32 analyzed samples, 30 (93.8%) tested positive for at least one CoV genus. β-, α-, or unclassified CoVs were identified in 24 (80%), 1 (3.3%), and 1 (3.3%) of the positive samples, respectively. A CoV genus could not be identified in two (6.7%) samples. A mixture of different CoV genera was detected in two (6.7%) samples: one was co-infected with β- and α-CoVs, and the other contained a β- and an unclassified CoV. A sequence analysis of the amplicons generated by the PCR identified 17 β-CoV strains belonging to the subgenus Embecovirus and two α-CoV strains belonging to Decacovirus. A phylogenetic analysis of two strains revealed a relationship with an unclassified Megaderma BatCoV strain. A subgenus could not be identified in nine β-CoV samples. Our data show a high prevalence and a high genetic diversity of CoV genera and subgenera that infect alpacas, in which the β-CoV subgenus Embecovirus predominated. Our data also suggest a new role for bats in the dissemination and transmission of uncommon CoVs to alpacas raised in rural Peru.

High activity of an affinity-matured ACE2 decoy against Omicron SARS-CoV-2 and pre-emergent coronaviruses

The viral genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), particularly its cell-binding spike protein gene, has undergone rapid evolution during the coronavirus disease 2019 (COVID-19) pandemic. Variants including Omicron BA.1 and Omicron BA.2 now seriously threaten the efficacy of therapeutic monoclonal antibodies and vaccines that target the spike protein. Viral evolution over a much longer timescale has generated a wide range of genetically distinct sarbecoviruses in animal populations, including the pandemic viruses SARS-CoV-2 and SARS-CoV-1. The genetic diversity and widespread zoonotic potential of this group complicates current attempts to develop drugs in preparation for the next sarbecovirus pandemic. Receptor-based decoy inhibitors can target a wide range of viral strains with a common receptor and may have intrinsic resistance to escape mutant generation and antigenic drift. We previously generated an affinity-matured decoy inhibitor based on the receptor target of the SARS-CoV-2 spike protein, angiotensin-converting enzyme 2 (ACE2), and deployed it in a recombinant adeno-associated virus vector (rAAV) for intranasal delivery and passive prophylaxis against COVID-19. Here, we demonstrate the exceptional binding and neutralizing potency of this ACE2 decoy against SARS-CoV-2 variants including Omicron BA.1 and Omicron BA.2. Tight decoy binding tracks with human ACE2 binding of viral spike receptor-binding domains across diverse clades of coronaviruses. Furthermore, in a coronavirus that cannot bind human ACE2, a variant that acquired human ACE2 binding was bound by the decoy with nanomolar affinity. Considering these results, we discuss a strategy of decoy-based treatment and passive protection to mitigate the ongoing COVID-19 pandemic and future airway virus threats.

Transmission Dynamics and Genomic Epidemiology of Emerging Variants of SARS-CoV-2 in Bangladesh

With the progression of the global SARS-CoV-2 pandemic, the new variants have become more infectious and continue spreading at a higher rate than pre-existing ones. Thus, we conducted a study to explore the epidemiology of emerging variants of SARS-CoV-2 that circulated in Bangladesh from December 2020 to September 2021, representing the 2nd and 3rd waves. We collected new cases and deaths per million daily data with the reproduction rate. We retrieved 928 SARS-CoV-2 sequences from GISAID and performed phylogenetic tree construction and mutation analysis. Case counts were lower initially at the end of 2020, during January-February and April-May 2021, whereas the death toll reached the highest value of 1.587 per million on the first week of August and then started to decline. All the variants (α, β, δ, η) were prevalent in the capital city, Dhaka, with dispersion to large cities, such as Sylhet and Chattogram. The B.1.1.25 lineage was prevalent during December 2020, but the B.1.617.2/δ variant was later followed by the B.1.351/β variant. The phylogeny revealed that the various strains found in Bangladesh could be from numerous countries. The intra-cluster and inter-cluster communication began in Bangladesh soon after the virus arrived. The prominent amino acid substitution was D614G from December 2020 to July 2021 (93.5 to 100%). From February-April, one of the VOC's important mutations, N501Y substitution, was also estimated at 51.8%, 76.1%, and 65.1% for the α, β and γ variants, respectively. The γ variant's unique mutation K417T was detected only at 1.8% in February. Another frequent mutation was P681R, a salient feature of the δ variant, detected in June (88.2%) and July (100%). Furthermore, only one γ variant was detected during the entire second and third wave, whereas no η variant was observed in this period. This rapid growth in the number of variants identified across Bangladesh shows virus adaptation and a lack of strict quarantine, prompting periodic genomic surveillance to foresee the spread of new variants, if any, and to take preventive measures as soon as possible.

Current Methods for Recombination Detection in Bacteria

The role of genetic exchanges, i.e., homologous recombination (HR) and horizontal gene transfer (HGT), in bacteria cannot be overestimated for it is a pivotal mechanism leading to their evolution and adaptation, thus, tracking the signs of recombination and HGT events is importance both for fundamental and applied science. To date, dozens of bioinformatics tools for revealing recombination signals are available, however, their pros and cons as well as the spectra of solvable tasks have not yet been systematically reviewed. Moreover, there are two major groups of software. One aims to infer evidence of HR, while the other only deals with horizontal gene transfer (HGT). However, despite seemingly different goals, all the methods use similar algorithmic approaches, and the processes are interconnected in terms of genomic evolution influencing each other. In this review, we propose a classification of novel instruments for both HR and HGT detection based on the genomic consequences of recombination. In this context, we summarize available methodologies paying particular attention to the type of traceable events for which a certain program has been designed.

Forming and updating vaccination beliefs: does the continued effect of misinformation depend on what we think we know?

People may cling to false facts even in the face of updated and correct information. The present study confronted misconceptions about the measles, mumps and rubella vaccine and a novel, fictitious Zika vaccine. Two experiments are reported, examining misconceptions as motivated by a poor risk understanding (Experiment 1, N = 130) or the exposure to conspiracy theories (Experiment 2, N = 130). Each experiment featured a Misinformation condition, wherein participants were presented with fictitious stories containing some misinformation (Experiment 1) and rumours focused on conspiracy theories (Experiment 2) that were later retracted by public health experts and a No misinformation condition, containing no reference to misinformation and rumours. Across experiments, participants were more hesitant towards vaccines when exposed to stories including vaccine misinformation. Notwithstanding, our results suggest a positive impact of a trusted source communicating the scientific consensus about vaccines. Zika virus represents a particular case showing how missing information can easily evolve into misinformation. Implications for effective dissemination of information are discussed.