25Multiple factors modulate microbial community assembly in the gut, but the magnitude of 26 each can vary substantially across studies. This may be in part due to a heavy reliance on 27 captive animals, which can have very different gut microbiomes versus their wild counterparts. 28In order to better resolve the influence of evolution and diet on gut microbiome diversity, we 29 generated a large and highly diverse animal distal gut 16S rRNA microbiome dataset, which 30 comprises 80 % wild animals and includes members of Mammalia, Aves, Reptilia, Amphibia, 31 and Actinopterygii. We decoupled the effects of host evolutionary history and diet on gut 32 microbiome diversity and show that each factor explains different aspects of diversity. Moreover, 33we resolved particular microbial taxa associated with host phylogeny or diet, and we show that 34Mammalia have a stronger signal of cophylogeny versus non-mammalian hosts. Additionally, 35 our results from ecophylogenetics and co-occurrence analyses suggest that environmental 36 filtering and microbe-microbe interactions differ among host clades. These findings provide a 37 robust assessment of the processes driving microbial community assembly in the vertebrate 38 intestine. 39 40

Large-scale metagenome assemblies of human microbiomes have produced a vast catalogue of previously unseen microbial genomes; however, comparatively few microbial genomes derive from other vertebrates. Here, we generated 4374 metagenome assembled genomes (MAGs) from gut samples of 180 predominantly wild animal species representing 5 classes. Combined with existing datasets, we produced 5596 non-redundant, quality MAGs and 1522 species-level genome bins (SGBs). Most SGBs were novel at the species, genus, or family levels, and the majority were enriched in host versus environment metagenomes. Many traits distinguished SGBs enriched in host or environmental biomes, including the number of antimicrobial resistance genes. We identified 1986 diverse and largely novel biosynthetic gene clusters. Gene-based assembly revealed tremendous gene diversity, much of it host or environment specific. Our MAG and gene datasets greatly expand the microbial genome repertoire and provide a broad view of microbial adaptations to life within a living host.

51Outbreaks of emerging coronaviruses in the past two decades and the current pandemic 52 of a novel coronavirus (SARS-CoV-2) that emerged in China highlight the importance of this 53 viral family as a zoonotic public health threat. To gain a better understanding of coronavirus 54 presence and diversity in wildlife at wildlife-human interfaces in three southern provinces in Viet 55Nam 2013-2014, we used consensus Polymerase Chain Reactions to detect coronavirus 56 sequences. In comparison to previous studies, we observed high proportions of positive samples 57 among field rats (34.0%, 239/702) destined for human consumption and insectivorous bats in 58 guano farms (74.8%, 234/313) adjacent to human dwellings. Most notably among field rats, the 59 odds of coronavirus RNA detection significantly increased along the supply chain from field rats 60 sold by traders (reference group; 20.7% positivity, 39/188) by a factor of 2.2 for field rats sold in 61 large markets (32.0%, 116/363) and 10.0 for field rats sold and served in restaurants (55.6%, 62 84/151). Coronaviruses were detected in the majority of wildlife farms (60.7%, 17/28) and in the 63 Malayan porcupines (6.0%, 20/331) and bamboo rats (6.3%, 6/96) that are farmed. We identified 64 six known coronaviruses in bats and rodents, clustered in three Coronaviridae genera, including 65 the Alpha-, Beta-, and Gammacoronaviruses. Our analysis also suggested either mixing of 66 animal excreta in the environment or interspecies transmission of coronaviruses, as both bat and 67 avian coronaviruses were detected in rodent feces in the trade. The mixing of multiple 68 coronaviruses, and their apparent amplification along the wildlife supply chain into restaurants, 69 suggests maximal risk for end consumers and likely underpins the mechanisms of zoonotic 70 spillover to people. 71 72

Commonly used 16S rRNA gene primers do not detect the full range of archaeal diversity present in the vertebrate gut. As a result, several questions regarding the archaeal component of the gut microbiota remain, including which Archaea are host-associated, the specificities of such associations and the major factors influencing archaeal diversity. Using 16S rRNA gene amplicon sequencing with primers that specifically target Archaea, we obtained sufficient sequence data from 185 gastrointestinal samples collected from 110 vertebrate species that span five taxonomic classes (Mammalia, Aves, Reptilia, Amphibia and Actinopterygii), of which the majority were wild. We provide evidence for previously undescribed Archaea–host associations, including Bathyarchaeia and Methanothermobacter, the latter of which was prevalent among Aves and relatively abundant in species with higher body temperatures, although this association could not be decoupled from host phylogeny. Host phylogeny explained archaeal diversity more strongly than diet, while specific taxa were associated with both factors, and cophylogeny was significant and strongest for mammalian herbivores. Methanobacteria was the only class predicted to be present in the last common ancestors of mammals and all host species. Further analysis indicated that Archaea–Bacteria interactions have a limited effect on archaeal diversity. These findings expand our current understanding of Archaea–vertebrate associations.

The COVID-19 pandemic has re-focused attention on mechanisms that lead to zoonotic disease spillover and spread. Commercial wildlife trade, and associated markets, are recognized mechanisms for zoonotic disease emergence, resulting in a growing global conversation around reducing human disease risks from spillover associated with hunting, trade, and consumption of wild animals. These discussions are especially relevant to people who rely on harvesting wildlife to meet nutritional, and cultural needs, including those in Arctic and boreal regions. Global policies around wildlife use and trade can impact food sovereignty and security, especially of Indigenous Peoples. We reviewed known zoonotic pathogens and current risks of transmission from wildlife (including fish) to humans in North American Arctic and boreal biomes, and evaluated the epidemic and pandemic potential of these zoonoses. We discuss future concerns, and consider monitoring and mitigation measures in these changing socio-ecological systems. While multiple zoonotic pathogens circulate in these systems, risks to humans are mostly limited to individual illness or local community outbreaks. These regions are relatively remote, subject to very cold temperatures, have relatively low wildlife, domestic animal, and pathogen diversity, and in many cases low density, including of humans. Hence, favorable conditions for emergence of novel diseases or major amplification of a spillover event are currently not present. The greatest risk to northern communities from pathogens of pandemic potential is via introduction with humans visiting from other areas. However, Arctic and boreal ecosystems are undergoing rapid changes through climate warming, habitat encroachment, and development; all of which can change host and pathogen relationships, thereby affecting the probability of the emergence of new (and re-emergence of old) zoonoses. Indigenous leadership and engagement in disease monitoring, prevention and response, is vital from the outset, and would increase the success of such efforts, as well as ensure the protection of Indigenous rights as outlined in the United Nations Declaration on the Rights of Indigenous Peoples. Partnering with northern communities and including Indigenous Knowledge Systems would improve the timeliness, and likelihood, of detecting emerging zoonotic risks, and contextualize risk assessments to the unique human-wildlife relationships present in northern biomes.

The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 in animal hosts. We used two major health databases to extract unstructured data and generated a global dataset of SARS-CoV-2 events in animals. The dataset presents harmonized host names, integrates relevant epidemiological and clinical data on each event, and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapting monitoring strategies, preventing the formation of animal reservoirs, and tailoring future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborations, to develop it further and expand its use.

Despite the discovery of several closely related viruses in bats, the direct evolutionary progenitor of SARS-CoV-2 has not yet been identified. In this study, we investigated potential animal sources of SARS-related coronaviruses using archived specimens from Sunda pangolins (Manis javanica) and Chinese pangolins (Manis pentadactyla) confiscated from the illegal wildlife trade, and from common palm civets (Paradoxurus hermaphroditus) raised on wildlife farms in Viet Nam. A total of 696 pangolin and civet specimens were screened for the presence of viral RNA from five zoonotic viral families and from Sarbecoviruses using primers specifically designed for pangolin coronaviruses. We also performed a curated data collection of media reports of wildlife confiscation events involving pangolins in Viet Nam between January 2016 and December 2020, to illustrate the global pangolin supply chain in the context of Viet Nam where the trade confiscated pangolins were sampled for this study. All specimens from pangolins and civets sampled along the wildlife supply chains between February 2017 and July 2018, in Viet Nam and tested with conventional PCR assays designed to detect flavivirus, paramyxovirus, filovirus, coronavirus, and orthomyxovirus RNA were negative. Civet samples were also negative for Sarbecoviruses, but 12 specimens from seven live pangolins confiscated in Hung Yen province, northern Viet Nam, in 2018 were positive for Sarbecoviruses. Our phylogenetic trees based on two fragments of the RdRp gene revealed that the Sarbecoviruses identified in these pangolins were closely related to pangolin coronaviruses detected in pangolins confiscated from the illegal wildlife trade in Yunnan and Guangxi provinces, China. Our curated data collection of media reports of wildlife confiscation events involving pangolins in Viet Nam between January 2016 and December 2020, reflected what is known about pangolin trafficking globally. Pangolins confiscated in Viet Nam were largely in transit, moving toward downstream consumers in China. Confiscations included pangolin scales sourced originally from Africa (and African species of pangolins), or pangolin carcasses and live pangolins native to Southeast Asia (predominately the Sunda pangolin) sourced from neighboring range countries and moving through Viet Nam toward provinces bordering China.

The pathogens that cause most emerging infectious diseases in humans originate in animals, particularly wildlife, and then spill over into humans. The accelerating frequency with which humans and domestic animals encounter wildlife because of activities such as land-use change, animal husbandry, and markets and trade in live wildlife has created growing opportunities for pathogen spillover. The risk of pathogen spillover and early disease spread among domestic animals and humans, however, can be reduced by stopping the clearing and degradation of tropical and subtropical forests, improving health and economic security of communities living in emerging infectious disease hotspots, enhancing biosecurity in animal husbandry, shutting down or strictly regulating wildlife markets and trade, and expanding pathogen surveillance. We summarize expert opinions on how to implement these goals to prevent outbreaks, epidemics, and pandemics.