Natural SARS-CoV-2 Infection in a Free-Ranging Black-Tailed Marmoset (Mico melanurus) from an Urban Area in Mid-West Brazil

Pereira, Asheley HB.; Vasconcelos, Anna L.; Silva, Victoria LB.; Nogueira, Beatriz S.; Silva, Anna CP.; Pacheco, Richard C.; Souza, Marcos A.; Colodel, Edson M.; Ubiali, Daniel G.; Biondo, Alexander Welker; Nakazato, Luciano; Dutra, Valéria

doi:10.1016/j.jcpa.2022.03.005

Cited by 28 publications

(21 citation statements)

References 17 publications

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“…Affected animals include lions and tigers, 24 snow leopards, otters, non‐human primates, gorillas, a binturong, a fishing cat, a coatimundi, hyenas, hippopotamuses, and manatees. 25 , 26 SARS‐CoV‐2 infection has also been identified in other wildlife, including white‐tailed deer, 27 a mule deer, 28 a black‐tailed marmoset, 29 a giant anteater, 30 wild otters, 31 wild mink, 32 fruit bats, 33 and racoon dogs, 34 which in the last two cases was experimentally confirmed. Tree shrews have been shown to develop subclinical infection after experimental infection, 35 and bank voles could be experimentally infected with SARS‐CoV‐2 but there was no transmission to contact controls.…”

Section: Animals In Which Natural or Experimental Sars‐cov‐2 Infectio...mentioning

confidence: 97%

SARS‐CoV‐2 does not infect pigs, but this has to be verified regularly

Opriessnig

Huang

2022

Xenotransplantation

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For successful xenotransplantation, freedom of the xenocraft donor from certain viral infections that may harm the organ recipient is important. A novel human coronavirus (CoV) with a respiratory tropism, designated as SARS-CoV-2, was first identified in January 2020 in China, but likely has been circulating unnoticed for some time before.Since then, this virus has reached most inhabited areas, resulting in a major global pandemic which is still ongoing. Due to a high number of subclinical infections, reinfections, geographic differences in diagnostic tests used, and differences in result reporting programs, the percentage of the population infected with SARS-CoV-2 at least once has been challenging to estimate. With continuous ongoing infections in people and an overall high viral load, it makes sense to look into possible viral spillover events in pets and farm animals, who are often in close contact with humans. The pig is currently the main species considered for xenotransplantation and hence there is interest to know if pigs can become infected with SARS-CoV-2 and if so what the infection dynamics may look like. This review article summarizes the latest research findings on this topic. It would appear that pigs can currently be considered a low risk species, and hence do not pose an immediate risk to the human population or xenotransplantation recipients per se. Monitoring the ever-changing SARS-CoV-2 variants appears important to recognize immediately should this change in the future.

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Section: Animals In Which Natural or Experimental Sars‐cov‐2 Infectio...mentioning

confidence: 97%

SARS‐CoV‐2 does not infect pigs, but this has to be verified regularly

Opriessnig

Huang

2022

Xenotransplantation

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“…Our results show host phylogeny as a viable alternative, which performs comparably to the best ACE2-based models. Anecdotally, this accuracy extends to species only recognised as susceptible after data collection for this study had ended, with 11 of 12 species more recently reported as naturally infected accurately predicted by the phylogeny-based model ( Supplementary file 2 ; Allender et al, 2022 ; Kuchipudi et al, 2022 ; Padilla-Blanco et al, 2022 ; Pereira et al, 2022 ; United States Department of Agriculture, 2022 ; United States Department of Agriculture, 2021a ; United States Department of Agriculture, 2021b ; United States Department of Agriculture, 2021c ; Wang et al, 2022 ). However, beyond data availability, the wide host range of sarbecoviruses represents a more significant practical hurdle, since the scope of surveillance suggested by these models is massive.…”

Section: Discussionmentioning

confidence: 63%

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

Mollentze

Keen

Munkhbayar

et al. 2022

eLife

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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.

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“…Our results show host phylogeny as a viable alternative, which performs comparably to the best ACE2-based models. Anecdotally, this accuracy extends to species only recognized as susceptible after data collection for this study had ended, with 11 of 12 species more recently reported as naturally-infected accurately predicted by the phylogeny-based model (Supplementary file 2) (Allender et al, 2022; Kuchipudi et al, 2022; Padilla-Blanco et al, 2022; Pereira et al, 2022; United States Department of Agriculture, 2022, 2021a, 2021b, 2021c; Wang et al, 2022). However, beyond data availability, the wide host range of sarbecoviruses represents a more significant practical hurdle, since the scope of surveillance suggested by these models is massive.…”

Section: Discussionmentioning

confidence: 65%

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

Mollentze

Keen

Munkhbayar

et al. 2022

Preprint

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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 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.

show abstract

Natural SARS-CoV-2 Infection in a Free-Ranging Black-Tailed Marmoset (Mico melanurus) from an Urban Area in Mid-West Brazil

Cited by 28 publications

References 17 publications

SARS‐CoV‐2 does not infect pigs, but this has to be verified regularly

SARS‐CoV‐2 does not infect pigs, but this has to be verified regularly

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

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

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