Global estimates of mammalian viral diversity accounting for host sharing

Genetic diversity and cross-species transmissibility of bat-associated picornaviruses from Spain

BACKGROUND

Emerging zoonotic diseases arise from cross-species transmission events between wild or domesticated animals and humans, with bats being one of the major reservoirs of zoonotic viruses. Viral metagenomics has led to the discovery of many viruses, but efforts have mainly been focused on some areas of the world and on certain viral families.

METHODS

We set out to describe full-length genomes of new picorna-like viruses by collecting feces from hundreds of bats captured in different regions of Spain. Viral sequences were obtained by high-throughput Illumina sequencing and analyzed phylogenetically to classify them in the context of known viruses. Linear discriminant analysis (LDA) was performed to infer likely hosts based on genome composition.

RESULTS

We found five complete or nearly complete genomes belonging to the family Picornaviridae, including a new species of the subfamily Ensavirinae. LDA suggested that these were true vertebrate viruses, rather than viruses from the bat diet. Some of these viruses were related to picornaviruses previously found in other bat species from distant geographical regions. We also found a calhevirus genome that most likely belongs to a proposed new family within the order Picornavirales, and for which genome composition analysis suggested a plant host.

CONCLUSIONS

Our findings describe new picorna-like viral species and variants circulating in the Iberian Peninsula, illustrate the wide geographical distribution and interspecies transmissibility of picornaviruses, and suggest new hosts for calheviruses.

Unveiling the microbial realm with VEBA 2.0: a modular bioinformatics suite for end-to-end genome-resolved prokaryotic, (micro)eukaryotic and viral multi-omics from either short- or long-read sequencing

The microbiome is a complex community of microorganisms, encompassing prokaryotic (bacterial and archaeal), eukaryotic, and viral entities. This microbial ensemble plays a pivotal role in influencing the health and productivity of diverse ecosystems while shaping the web of life. However, many software suites developed to study microbiomes analyze only the prokaryotic community and provide limited to no support for viruses and microeukaryotes. Previously, we introduced the Viral Eukaryotic Bacterial Archaeal (VEBA) open-source software suite to address this critical gap in microbiome research by extending genome-resolved analysis beyond prokaryotes to encompass the understudied realms of eukaryotes and viruses. Here we present VEBA 2.0 with key updates including a comprehensive clustered microeukaryotic protein database, rapid genome/protein-level clustering, bioprospecting, non-coding/organelle gene modeling, genome-resolved taxonomic/pathway profiling, long-read support, and containerization. We demonstrate VEBA's versatile application through the analysis of diverse case studies including marine water, Siberian permafrost, and white-tailed deer lung tissues with the latter showcasing how to identify integrated viruses. VEBA represents a crucial advancement in microbiome research, offering a powerful and accessible software suite that bridges the gap between genomics and biotechnological solutions.

Identifying life-history patterns along the fast-slow continuum of mammalian viral carriers

Life-history traits have been identified as major indicators of mammals' susceptibility and exposure to viruses due to evolutionary constraints that link life-history speed with species' ecology and immunity. Nonetheless, it is unclear where along the fast-slow continuum of mammalian life-history lies the greatest diversity of host species. Consequently, life-history patterns that govern host-virus associations remain largely unknown. Here we analyse the virome of 1350 wild mammals and detect the characteristics that drive species' compatibility with different groups of viruses. We highlight that mammals with larger body size and either very rapid or very slow life histories are more likely to carry different groups of viruses, particularly zoonotic ones. While some common life-history patterns emerge across carriers, eco-evolutionary characteristics of viral groups appear to determine association with certain carrier species. Our findings underline the importance of incorporating both mammals' life-history information and viruses' ecological diversity into surveillance strategies to identify potential zoonotic carriers in wildlife.

Rapid taxonomic categorization of short, abundant virus sequences for ecological analyses

Public health concerns about recent viral epidemics have motivated researchers to seek novel ways to understand pathogen infection in native, wildlife hosts. With its deep history of tools and perspectives for understanding the abundance and distribution of organisms, ecology can shed new light on viral infection dynamics. However, datasets allowing deep explorations of viral communities from an ecological perspective are lacking. We sampled 1086 bats from two, adjacent Puerto Rican caves and tested them for infection by herpesviruses, resulting in 3131 short, viral sequences. Using percent identity of nucleotides and a machine learning algorithm (affinity propagation), we categorized herpesviruses into 43 operational taxonomic units (OTUs) to be used in place of species in subsequent ecological analyses. Herpesvirus metacommunities demonstrated long-tailed rank frequency distributions at all analyzed levels of host organization (i.e., individual, population, and community). Although 13 herpesvirus OTUs were detected in more than one host species, OTUs generally exhibited host specificity by infecting a single core host species at a significantly higher prevalence than in all satellite species combined. We describe the natural history of herpesvirus metacommunities in Puerto Rican bats and suggest that viruses follow the general law that communities comprise few common and many rare species. To guide future efforts in the field of viral ecology, hypotheses are presented regarding mechanisms that contribute to these patterns.

How do host population dynamics impact Lyme disease risk dynamics in theoretical models?

Lyme disease is the most common wildlife-to-human transmitted disease reported in North America. The study of this disease requires an understanding of the ecology of the complex communities of ticks and host species involved in harboring and transmitting this disease. Much of the ecology of this system is well understood, such as the life cycle of ticks, and how hosts are able to support tick populations and serve as disease reservoirs, but there is much to be explored about how the population dynamics of different host species and communities impact disease risk to humans. In this study, we construct a stage-structured, empirically-informed model with host dynamics to investigate how host population dynamics can affect disease risk to humans. The model describes a tick population and a simplified community of three host species, where primary nymph host populations are made to fluctuate on an annual basis, as commonly observed in host populations. We tested the model under different environmental conditions to examine the effect of environment on the interactions of host dynamics and disease risk. Results show that allowing for host dynamics in the model reduces mean nymphal infection prevalence and increases the maximum annual prevalence of nymphal infection and the density of infected nymphs. Effects of host dynamics on disease measures of nymphal infection prevalence were nonlinear and patterns in the effect of dynamics on amplitude in nymphal infection prevalence varied across environmental conditions. These results highlight the importance of further study of the effect of community dynamics on disease risk. This will involve the construction of further theoretical models and collection of robust field data to inform these models. With a more complete understanding of disease dynamics we can begin to better determine how to predict and manage disease risk using these models.

A global-scale dataset of bat viral detection suggests that pregnancy reduces viral shedding

Understanding viral infection dynamics in wildlife hosts can help forecast zoonotic pathogen spillover and human disease risk. Bats are particularly important reservoirs of zoonotic viruses, including some of major public health concern such as Nipah virus, Hendra virus, and SARS-related coronaviruses. Previous work has suggested that metapopulation dynamics, seasonal reproductive patterns, and other bat life history characteristics might explain temporal variation in spillover of bat-associated viruses into people. Here, we analyze viral dynamics in free-ranging bat hosts, leveraging a multi-year, global-scale viral detection dataset that spans eight viral families and 96 bat species from 14 countries. We fit hierarchical Bayesian models that explicitly control for important sources of variation, including geographic region, specimen type, and testing protocols, while estimating the influence of reproductive status on viral detection in female bats. Our models revealed that late pregnancy had a negative effect on viral shedding across multiple data subsets, while lactation had a weaker influence that was inconsistent across data subsets. These results are unusual for mammalian hosts, but given recent findings that bats may have high individual viral loads and population-level prevalence due to dampening of antiviral immunity, we propose that it would be evolutionarily advantageous for pregnancy to either not further reduce immunity or actually increase the immune response, reducing viral load, shedding, and risk of fetal infection. This novel hypothesis would be valuable to test given its potential to help monitor, predict, and manage viral spillover risk from bats.

Cellular receptors for mammalian viruses

The interaction of viral surface components with cellular receptors and other entry factors determines key features of viral infection such as host range, tropism and virulence. Despite intensive research, our understanding of these interactions remains limited. Here, we report a systematic analysis of published work on mammalian virus receptors and attachment factors. We build a dataset twice the size of those available to date and specify the role of each factor in virus entry. We identify cellular proteins that are preferentially used as virus receptors, which tend to be plasma membrane proteins with a high propensity to interact with other proteins. Using machine learning, we assign cell surface proteins a score that predicts their ability to function as virus receptors. Our results also reveal common patterns of receptor usage among viruses and suggest that enveloped viruses tend to use a broader repertoire of alternative receptors than non-enveloped viruses, a feature that might confer them with higher interspecies transmissibility.

Fifty Years of the National Rabies Control Program in Brazil under the One Health Perspective

In 1973, the National Rabies Program was created in Brazil through an agreement between the Ministry of Health and Agriculture. Since its beginning, it developed integrated action through access to free post-exposure prophylaxis (PEP) for people at risk, dog vaccination campaigns, a joint surveillance system, and awareness. This study aims to describe human rabies in Brazil under the One Health perspective in recent decades, including achievements in the control of dog-mediated cases and challenges in human cases transmitted by wild animals. This paper also explores possible drivers of human rabies in the Northeast Region with half of the cases. The first part of this study was descriptive, presenting data and examples by periods. Statistical analysis was performed in the last period (2010-2022) to explore possible drivers. Dog-mediated human cases decreased from 147 to 0, and dog cases decreased from 4500 to 7. A major challenge is now human cases transmitted by wild animals (bats, non-human primates, and wild canids). Most current human cases occur in municipalities with a tropical and subtropical moist broadleaf forest biome and a Gini index higher than 0.5. In the multivariable analysis, an association with temperature was estimated (OR = 1.739; CI95% = 1.181-2.744), and primary healthcare coverage (OR = 0.947; CI95% = 0.915-0.987) was identified as a protector. It is possible to significantly reduce the number of dog-mediated human rabies cases through the efforts presented. However, Brazil has wildlife variants of the rabies virus circulating. The association of human cases with higher temperatures in the Northeast is a concern with climate change. To reduce human cases transmitted by wild animals, it is important to continue distributing free PEP, especially in remote at-risk areas in the Amazon Region, and to increase awareness.

Effect of epidemic diseases on wild animal conservation

Under the background of global species extinction, the impact of epidemic diseases on wild animal protection is increasingly prominent. Here, we review and synthesize the literature on this topic, and discuss the relationship between diseases and biodiversity. Diseases usually reduce species diversity by decreasing or extinction of species populations, but also accelerate species evolution and promote species diversity. At the same time, species diversity can regulate disease outbreaks through dilution or amplification effects. The synergistic effect of human activities and global change is emphasized, which further aggravates the complex relationship between biodiversity and diseases. Finally, we emphasize the importance of active surveillance of wild animal diseases, which can protect wild animals from potential diseases, maintain population size and genetic variation, and reduce the damage of diseases to the balance of the whole ecosystem and human health. Therefore, we suggest that a background survey of wild animal populations and their pathogens should be carried out to assess the impact of potential outbreaks on the population or species level. The mechanism of dilution and amplification effect between species diversity and diseases of wild animals should be further studied to provide a theoretical basis and technical support for human intervention measures to change biodiversity. Most importantly, we should closely combine the protection of wild animals with the establishment of an active surveillance, prevention, and control system for wild animal epidemics, in an effort to achieve a win-win situation between wild animal protection and disease control.

Selective, broad-spectrum antiviral photodynamic disinfection with dicationic imidazolyl chlorin photosensitizers

The COVID-19 pandemic exposes our vulnerability to viruses that acquire the ability to infect our cells. Classical disinfection methods are limited by toxicity. Existing medicines performed poorly against SARS-CoV-2 because of their specificity to targets in different organisms. We address the challenge of mitigating known and prospective viral infections with a new photosensitizer for antimicrobial photodynamic therapy (aPDT). Photodynamic inactivation is based on local oxidative stress, which is particularly damaging to enveloped viruses. We synthesized a cationic imidazolyl chlorin that reduced by > 99.999% of the percentage inhibition of amplification of SARS-CoV-2 collected from patients at 0.2 µM concentration and 4 J cm-2. Similar results were obtained in the prevention of infection of human ACE2-expressing HEK293T cells by a pseudotyped lentiviral vector exhibiting the S protein of SARS-CoV-2 at its surface. No toxicity to human epidermal keratinocytes (HaCaT) cells was found under similar conditions. aPDT with this chlorin offers fast and safe broad-spectrum photodisinfection and can be repeated with low risk of resistance.

Predicting zoonotic potential of viruses: where are we?

The prospect of identifying high-risk viruses and designing interventions to pre-empt their emergence into human populations is enticing, but controversial, particularly when used to justify large-scale virus discovery initiatives. We review the current state of these efforts, identifying three broad classes of predictive models that have differences in data inputs that define their potential utility for triaging newly discovered viruses for further investigation. Prospects for model predictions of public health risk to guide preparedness depend not only on computational improvements to algorithms, but also on more efficient data generation in laboratory, field and clinical settings. Beyond public health applications, efforts to predict zoonoses provide unique research value by creating generalisable understanding of the ecological and evolutionary factors that promote viral emergence.

Network embedding unveils the hidden interactions in the mammalian virome

Predicting host-virus interactions is fundamentally a network science problem. We develop a method for bipartite network prediction that combines a recommender system (linear filtering) with an imputation algorithm based on low-rank graph embedding. We test this method by applying it to a global database of mammal-virus interactions and thus show that it makes biologically plausible predictions that are robust to data biases. We find that the mammalian virome is under-characterized anywhere in the world. We suggest that future virus discovery efforts could prioritize the Amazon Basin (for its unique coevolutionary assemblages) and sub-Saharan Africa (for its poorly characterized zoonotic reservoirs). Graph embedding of the imputed network improves predictions of human infection from viral genome features, providing a shortlist of priorities for laboratory studies and surveillance. Overall, our study indicates that the global structure of the mammal-virus network contains a large amount of information that is recoverable, and this provides new insights into fundamental biology and disease emergence.

Abundant dsRNA picobirnaviruses show little geographic or host association in terrestrial systems

Picobirnaviruses are double-stranded RNA viruses known from a wide range of host species and locations but with unknown pathogenicity and host relationships. Here, we examined the diversity of picobirnaviruses from cattle and gorillas within and around Bwindi Impenetrable Forest National Park (BIFNP), Uganda, where wild and domesticated animals and humans live in relatively close contact. We use metagenomic sequencing with bioinformatic analyses to examine genetic diversity. We compared our findings to global Picobirnavirus diversity using clustering-based analyses. Picobirnavirus diversity at Bwindi was high, with 14 near-complete RdRp and 15 capsid protein sequences, and 497 new partial viral sequences recovered from 44 gorilla samples and 664 from 16 cattle samples. Sequences were distributed throughout a phylogenetic tree of globally derived picobirnaviruses. The relationship with Picobirnavirus diversity and host taxonomy follows a similar pattern to the global dataset, generally lacking pattern with either host or geography.

Discovery and characterization of novel paramyxoviruses from bat samples in China

Many paramyxoviruses are responsible for a variety of mild to severe human and animal diseases. Based on the novel discoveries over the past several decades, the family Paramyxoviridae infecting various hosts across the world includes 4 subfamilies, 17 classified genera and 78 species now. However, no systematic surveys of bat paramyxoviruses are available from the Chinese mainland. In this study, 13,064 samples from 54 bat species were collected and a comprehensive paramyxovirus survey was conducted. We obtained 94 new genome sequences distributed across paramyxoviruses from 22 bat species in seven provinces. Bayesian phylodynamic and phylogenetic analyses showed that there were four different lineages in the Jeilongvirus genus. Based on available data, results of host and region switches showed that the bat colony was partial to interior, whereas the rodent colony was exported, and the felines and hedgehogs were most likely the intermediate hosts from Scotophilus spp. rather than rodents. Based on the evolutionary trend, genus Jeilongvirus may have originated from Mus spp. in Australia, then transmitted to bats and rodents in Africa, Asia and Europe, and finally to bats and rodents in America.

Predicting primate-parasite associations using exponential random graph models

Ecological associations between hosts and parasites are influenced by host exposure and susceptibility to parasites, and by parasite traits, such as transmission mode. Advances in network analysis allow us to answer questions about the causes and consequences of traits in ecological networks in ways that could not be addressed in the past. We used a network-based framework (exponential random graph models or ERGMs) to investigate the biogeographic, phylogenetic and ecological characteristics of hosts and parasites that affect the probability of interactions among nonhuman primates and their parasites. Parasites included arthropods, bacteria, fungi, protozoa, viruses and helminths. We investigated existing hypotheses, along with new predictors and an expanded host-parasite database that included 213 primate nodes, 763 parasite nodes and 2319 edges among them. Analyses also investigated phylogenetic relatedness, sampling effort and spatial overlap among hosts. In addition to supporting some previous findings, our ERGM approach demonstrated that more threatened hosts had fewer parasites, and notably, that this effect was independent of hosts also having a smaller geographic range. Despite having fewer parasites, threatened host species shared more parasites with other hosts, consistent with loss of specialist parasites and threat arising from generalist parasites that can be maintained in other, non-threatened hosts. Viruses, protozoa and helminths had broader host ranges than bacteria, or fungi, and parasites that infect non-primates had a higher probability of infecting more primate species. The value of the ERGM approach for investigating the processes structing host-parasite networks provided a more complete view on the biogeographic, phylogenetic and ecological traits that influence parasite species richness and parasite sharing among hosts. The results supported some previous analyses and revealed new associations that warrant future research, thus revealing how hosts and parasites interact to form ecological networks.

Mussel parasite richness and risk of extinction

Parasite conservation is important for the maintenance of ecosystem diversity and function. Conserving parasites relies first on understanding parasite biodiversity and second on estimating the extinction risk to that biodiversity. Although steps have been taken independently in both these areas, previous studies have overwhelmingly focused on helminths in vertebrate hosts over broad scales, providing low resolution and excluding a large proportion of possible host and parasite diversity. We estimated both total obligate parasite richness and parasite extinction risk in freshwater mussels (Unionidae and Margaritiferidae) from Europe and the United States to provide a case study for considering parasite conservation in a severely understudied system. We used currently reported host-parasite relationships to extrapolate parasite diversity to all possible mussel hosts and then used the threat levels of those hosts to estimate the extinction risk for both described and undescribed parasites. An estimated 67% of parasite richness in freshwater mussels is undescribed and over 80% of the most host-specific groups (digenean trematodes and ciliates) are undescribed. We estimated that 21% of this total parasite fauna is at immediate risk of extinction, corresponding to 60 unique species, many of which will likely go extinct before being described. Given the important roles parasites play in community structure and function and the strong ecosystem engineering capacities of freshwater mussels, such extinctions are likely to severely affect freshwater ecosystems. Our detailed study of mussel parasites provides compelling evidence for the hidden conservation threat to parasites through extinction cascades and shows parasites are deserving of immediate attention.

Wild Animal Migration As a Potential Threat of Introduction of New Viruses into Russia

The SARS-CoV-2 pandemic has shown how serious the problem of re-emerging zoonotic infections is for our existence. Migrations of animals, which are natural reservoirs of a particular virus, play a colossal role in the spread of pathogens to new territories. Examples are the migrations of both land animals (carnivores, rodents, and ungulates) and many marine mammals (pinnipeds and cetaceans). Yet the most interesting from the point of view of the speed and range of the spread of viral infections are migrations associated with flights. In nature, these can be migrations of insects, bats, and, of course, birds. Unfortunately, there are very few studies on the migration of these animals in Russia. Considering the problems related to climate change and other environmental factors, it is important to obtain up-to-date data on the changing animal migration routes and, as a consequence, to develop domestic equipment, particularly transmitters, to fix them.

Predicting the potential for zoonotic transmission and host associations for novel viruses

Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.

Climate change increases cross-species viral transmission risk

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals^1,2. However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife^3,4. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.

Climate change increases cross-species viral transmission risk

At least 10,000 virus species have the ability to infect humans but, at present, the vast majority are circulating silently in wild mammals^1,2. However, changes in climate and land use will lead to opportunities for viral sharing among previously geographically isolated species of wildlife^3,4. In some cases, this will facilitate zoonotic spillover-a mechanistic link between global environmental change and disease emergence. Here we simulate potential hotspots of future viral sharing, using a phylogeographical model of the mammal-virus network, and projections of geographical range shifts for 3,139 mammal species under climate-change and land-use scenarios for the year 2070. We predict that species will aggregate in new combinations at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, causing the cross-species transmission of their associated viruses an estimated 4,000 times. Owing to their unique dispersal ability, bats account for the majority of novel viral sharing and are likely to share viruses along evolutionary pathways that will facilitate future emergence in humans. Notably, we find that this ecological transition may already be underway, and holding warming under 2 °C within the twenty-first century will not reduce future viral sharing. Our findings highlight an urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking the range shifts of species, especially in tropical regions that contain the most zoonoses and are experiencing rapid warming.

The Ecology of Viral Emergence

The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on human health, economic well-being, and societal function. It is essential that we use this generational experience to better understand the processes that underpin the emergence of COVID-19 and other zoonotic diseases. Herein, I review the mechanisms that determine why and how viruses emerge in new hosts, as well as the barriers to this process. I show that traditional studies of virus emergence have an inherent anthropocentric bias, with disease in humans considered the inevitable outcome of virus emergence, when in reality viruses are integral components of a global ecosystem characterized by continual host jumping with humans also transmitting their viruses to other animals. I illustrate these points using coronaviruses, including severe acute respiratory syndrome coronavirus 2, as a case study. I also outline the potential steps that can be followed to help mitigate and prevent future pandemics, with combating climate change a central component. Expected final online publication date for the Annual Review of Virology, Volume 9 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Diversity and ecological footprint of Global Ocean RNA viruses

DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and "species"-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

Droplet Microfluidics for High-Resolution Virology

Microfluidics has enabled a new era of cellular and molecular assays due to the small length scales, parallelization, and the modularity of various analysis and actuation functions. Droplet microfluidics, in particular, has been instrumental in providing new tools for biology with its ability to quickly and reproducibly generate drops that act as individual reactors. A notable beneficiary of this technology has been single-cell RNA sequencing, which has revealed new heterogeneities and interactions for the fundamental unit of life. However, viruses far surpass the diversity of cellular life, affect the dynamics of all ecosystems, and are a chronic source of global health crises. Despite their impact on the world, high-throughput and high-resolution viral profiling has been difficult, with conventional methods being limited to population-level averaging, large sample volumes, and few cultivable hosts. Consequently, most viruses have not been identified and studied. Droplet microfluidics holds the potential to address many of these limitations and offers new levels of sensitivity and throughput for virology. This Feature highlights recent efforts that have applied droplet microfluidics to the detection and study of viruses, including for diagnostics, virus-host interactions, and cell-independent virus assays. In combination with traditional virology methods, droplet microfluidics should prove a potent tool toward achieving a better understanding of the most abundant biological species on Earth.

A Review of Mammarenaviruses and Rodent Reservoirs in the Americas

In the Americas, infectious viral diseases caused by viruses of the genus Mammarenavirus have been reported since the 1960s. Such diseases have commonly been associated with land use changes, which favor abundance of generalist rodent species. In the Americas-where the rates of land use change are among the highest worldwide-at least 1326 of all 2277 known rodent species have been reported. We conducted a literature review of studies between 1960 and 2020, to establish the current and historical knowledge about genotypes of mammarenaviruses and their rodent reservoirs in the Americas. Our overall goal was to show the importance of focusing research efforts on the American continent, since the conditions exist for future viral hemorrhagic fever (VHF) outbreaks caused by rodent-borne viruses, in turn, carried by widely distributed rodents. We found 47 species identified down to the species level, and one species identified only down to the genus level (Oryzomys sp.), reported in the Americas as reservoirs of mammarenaviruses, most these are ecological generalists. These species associate with 29 genotypes of Mammarenavirus, seven of which have been linked to VHFs in humans. We also highlight the need to monitor these species, in order to prevent viral disease outbreaks in the region.

The Global Virome in One Network (VIRION): an Atlas of Vertebrate-Virus Associations

Data that catalogue viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open sharing, posing challenges for research on macroecology, evolution, and public health. Here, we solve this problem by establishing a dynamically maintained database of vertebrate-virus associations, called The Global Virome in One Network (VIRION). The VIRION database has been assembled through both reconciliation of static data sets and integration of dynamically updated databases. These data sources are all harmonized against one taxonomic backbone, including metadata on host and virus taxonomic validity and higher classification; additional metadata on sampling methodology and evidence strength are also available in a harmonized format. In total, the VIRION database is the largest open-source, open-access database of its kind, with roughly half a million unique records that include 9,521 resolved virus “species” (of which 1,661 are ICTV ratified), 3,692 resolved vertebrate host species, and 23,147 unique interactions between taxonomically valid organisms. Together, these data cover roughly a quarter of mammal diversity, a 10th of bird diversity, and ∼6% of the estimated total diversity of vertebrates, and a much larger proportion of their virome than any previous database. We show how these data can be used to test hypotheses about microbiology, ecology, and evolution and make suggestions for best practices that address the unique mix of evidence that coexists in these data.

Primate malarias as a model for cross-species parasite transmission

Parasites regularly switch into new host species, representing a disease burden and conservation risk to the hosts. The distribution of these parasites also gives insight into characteristics of ecological networks and genetic mechanisms of host-parasite interactions. Some parasites are shared across many species, whereas others tend to be restricted to hosts from a single species. Understanding the mechanisms producing this distribution of host specificity can enable more effective interventions and potentially identify genetic targets for vaccines or therapies. As ecological connections between human and local animal populations increase, the risk to human and wildlife health from novel parasites also increases. Which of these parasites will fizzle out and which have the potential to become widespread in humans? We consider the case of primate malarias, caused by Plasmodium parasites, to investigate the interacting ecological and evolutionary mechanisms that put human and nonhuman primates at risk for infection. Plasmodium host switching from nonhuman primates to humans led to ancient introductions of the most common malaria-causing agents in humans today, and new parasite switching is a growing threat, especially in Asia and South America. Based on a wild host-Plasmodium occurrence database, we highlight geographic areas of concern and potential areas to target further sampling. We also discuss methodological developments that will facilitate clinical and field-based interventions to improve human and wildlife health based on this eco-evolutionary perspective.

Diversity and evolution of the animal virome

The COVID-19 pandemic has given the study of virus evolution and ecology new relevance. Although viruses were first identified more than a century ago, we likely know less about their diversity than that of any other biological entity. Most documented animal viruses have been sampled from just two phyla - the Chordata and the Arthropoda - with a strong bias towards viruses that infect humans or animals of economic and social importance, often in association with strong disease phenotypes. Fortunately, the recent development of unbiased metagenomic next-generation sequencing is providing a richer view of the animal virome and shedding new light on virus evolution. In this Review, we explore our changing understanding of the diversity, composition and evolution of the animal virome. We outline the factors that determine the phylogenetic diversity and genomic structure of animal viruses on evolutionary timescales and show how this impacts assessment of the risk of disease emergence in the short term. We also describe the ongoing challenges in metagenomic analysis and outline key themes for future research. A central question is how major events in the evolutionary history of animals, such as the origin of the vertebrates and periodic mass extinction events, have shaped the diversity and evolution of the viruses they carry.

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data underpin research into the distribution and eco-evolutionary correlates of viral diversity and zoonotic risk across host species. However, current knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are either constant or accelerating, with little evidence of declines towards viral richness asymptotes, even in highly sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species' ranked viral richness. Our results illustrate that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since it is feasible that an analysis conducted today could draw quite different conclusions than one conducted only a decade ago.

The science of the host-virus network

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.

Rare inventory of trematode diversity in a protected natural reserve

In the face of ongoing habitat degradation and the biodiversity crisis, natural reserves are important refuges for wildlife. Since most free-living organisms serve as hosts to parasites, the diverse communities in protected areas can be expected to provide suitable habitats for a species-rich parasite fauna. However, to date, assessments of parasite diversity in protected nature reserves are rare. To expand our knowledge of parasite communities in natural habitats, we examined 1994 molluscs belonging to 15 species for trematode infections in a central European natural reserve. The parasitological examination revealed an overall prevalence of 17.3% and a total species richness of 40 trematode species. However, the parasite diversity and prevalence did not differ markedly from trematode communities in non-protected environments, which might be partly explained by a dilution effect caused by a high number of non-host organisms in our study system. The proportion of complex and long life cycles of parasites in the present study is high, indicating complex biotic interactions. We conclude that life cycle complexity, in addition to parasite diversity and trematode species richness, can provide valuable information on ecosystem health and should therefore be considered in future studies.

Predictions of primate-parasite coextinction

Future biodiversity loss threatens the integrity of complex ecological associations, including among hosts and parasites. Almost half of primate species are threatened with extinction, and the loss of threatened hosts could negatively impact parasite associations and ecosystem functions. If endangered hosts are highly connected in host-parasite networks, then future host extinctions will also drive parasite extinctions, destabilizing ecological networks. If threatened hosts are not highly connected, however, then network structure should not be greatly affected by the loss of threatened hosts. Networks with high connectance, modularity, nestedness and robustness are more resilient to perturbations such as the loss of interactions than sparse, nonmodular and non-nested networks. We analysed the interaction network involving 213 primates and 763 parasites and removed threatened primates (114 species) to simulate the effects of extinction. Our analyses revealed that connections to 23% of primate parasites (176 species) may be lost if threatened primates go extinct. In addition, measures of network structure were affected, but in varying ways because threatened hosts have fewer parasite interactions than non-threatened hosts. These results reveal that host extinctions will perturb the host-parasite network and potentially lead to secondary extinctions of parasites. The ecological consequences of these extinctions remain unclear. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

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'.

Challenges in modeling the emergence of novel pathogens

The emergence of infectious agents with pandemic potential present scientific challenges from detection to data interpretation to understanding determinants of risk and forecasts. Mathematical models could play an essential role in how we prepare for future emergent pathogens. Here, we describe core directions for expansion of the existing tools and knowledge base, including: using mathematical models to identify critical directions and paths for strengthening data collection to detect and respond to outbreaks of novel pathogens; expanding basic theory to identify infectious agents and contexts that present the greatest risks, over both the short and longer term; by strengthening estimation tools that make the most use of the likely range and uncertainties in existing data; and by ensuring modelling applications are carefully communicated and developed within diverse and equitable collaborations for increased public health benefit.

Genomic signatures for predicting the zoonotic potential of novel viruses

Powered by metagenomics, viral discovery is outpacing our capacity for the downstream characterization needed to fully assess zoonotic potential. A study published in PLOS Biology uses machine learning to prioritize novel viruses based only on genomic signatures.

Zoonotic and reverse zoonotic transmission of viruses between humans and pigs

Humans and pigs share a close contact relationship, similar biological traits, and one of the highest estimated number of viruses compared to other mammalian species. The contribution and directionality of viral exchange between humans and pigs remain unclear for some of these viruses, but their transmission routes are important to characterize in order to prevent outbreaks of disease in both host species. This review collects and assesses the evidence to determine the likely transmission route of 27 viruses between humans and pigs.

Synzootics

Ecologists increasingly recognise coinfection as an important component of emergent epidemiological patterns, connecting aspects of ecoimmunology, behaviour, ecosystem function and even extinction risk. Building on syndemic theory in medical anthropology, we propose the term 'synzootics' to describe co-occurring enzootic or epizootic processes that produce worse health outcomes in wild animals. Using framing from syndemic theory, we describe how the synzootic concept offers new insights into the ecology and evolution of infectious diseases. We then recommend a set of empirical criteria and lines of evidence that can be used to identify synzootics in nature. We conclude by exploring how synzootics could indirectly drive the emergence of novel pathogens in human populations.

Ancient viral integrations in marsupials: a potential antiviral defence

Marsupial viruses are understudied compared to their eutherian mammal counterparts, although they may pose severe threats to vulnerable marsupial populations. Genomic viral integrations, termed 'endogenous viral elements' (EVEs), could protect the host from infection. It is widely known past viral infections and EVEs play an active role in antiviral defence in invertebrates and plants. This study aimed to characterise actively transcribed EVEs in Australian marsupial species, because they may play an integral role in cellular defence against viruses. This study screened publicly available RNA sequencing data sets (n = 35) and characterised 200 viral transcripts from thirteen Australian marsupial species. Of the 200 transcripts, 188 originated from either Bornaviridae, Filoviridae, or Parvoviridae EVEs. The other twelve transcripts were from putative active infections from members of the Herpesviridae and Anelloviridae, and Hepadnaviridae. EVE transcripts (n = 188) were mapped to marsupial genomes (where available, n = 5/13) to identify the genomic insertion sites. Of the 188 transcripts, 117 mapped to 39 EVEs within the koala, bare-nosed wombat, tammar wallaby, brushtail possum, and Tasmanian devil genomes. The remaining eight animals had no available genome (transcripts n = 71). Every marsupial has Bornaviridae, Filoviridae, and Parvoviridae EVEs, a trend widely observed in eutherian mammals. Whilst eutherian bornavirus EVEs are predominantly nucleoprotein-derived, marsupial bornavirus EVEs demonstrate a surprising replicase gene bias. We predicted these widely distributed EVEs were conserved within marsupials from ancient germline integrations, as many were over 65 million years old. One bornavirus replicase EVE, present in six marsupial genomes, was estimated to be 160 million years old, predating the American-Australian marsupial split. We considered transcription of these EVEs through small non-coding RNA as an ancient viral defence. Consistent with this, in koala small RNA sequence data sets, we detected Bornaviridae replicase and Filoviridae nucleoprotein produced small RNA. These were enriched in testis tissue, suggesting they could protect marsupials from vertically transmitted viral integrations.

Why are there so few (or so many) circulating coronaviruses?

Despite vast diversity in non-human hosts and conspicuous recent spillover events, only a small number of coronaviruses have been observed to persist in human populations. This puzzling mismatch suggests substantial barriers to establishment. We detail hypotheses that might contribute to explain the low numbers of endemic coronaviruses, despite their considerable evolutionary and emergence potential. We assess possible explanations ranging from issues of ascertainment, historically lower opportunities for spillover, aspects of human demographic changes, and features of pathogen biology and pre-existing adaptive immunity to related viruses. We describe how successful emergent viral species must triangulate transmission, virulence, and host immunity to maintain circulation. Characterizing the factors that might shape the limits of viral persistence can delineate promising research directions to better understand the combinations of pathogens and contexts that are most likely to lead to spillover.

Hidden Viral Sequences in Public Sequencing Data and Warning for Future Emerging Diseases

RNA viruses cause numerous emerging diseases, mostly due to transmission from mammalian and avian reservoirs. Large-scale surveillance of RNA viral infections in these animals is a fundamental step for controlling viral infectious diseases. Metagenomic analysis is a powerful method for virus identification with low bias and has contributed substantially to the discovery of novel viruses. Deep-sequencing data have been collected from diverse animals and accumulated in public databases, which can be valuable resources for identifying unknown viral sequences. Here, we screened for infections of 33 RNA viral families in publicly available mammalian and avian sequencing data and found approximately 900 hidden viral infections. We also discovered six nearly complete viral genomes in livestock, wild, and experimental animals: hepatovirus in a goat, hepeviruses in blind mole-rats and a galago, astrovirus in macaque monkeys, parechovirus in a cow, and pegivirus in tree shrews. Some of these viruses were phylogenetically close to human-pathogenic viruses, suggesting the potential risk of causing disease in humans upon infection. Furthermore, infections of five novel viruses were identified in several different individuals, indicating that their infections may have already spread in the natural host population. Our findings demonstrate the reusability of public sequencing data for surveying viral infections and identifying novel viral sequences, presenting a warning about a new threat of viral infectious disease to public health. IMPORTANCE Monitoring the spread of viral infections and identifying novel viruses capable of infecting humans through animal reservoirs are necessary to control emerging viral diseases. Massive amounts of sequencing data collected from various animals are publicly available, and these data may contain sequences originating from a wide variety of viruses. Here, we analyzed more than 46,000 public sequencing data and identified approximately 900 hidden RNA viral infections in mammalian and avian samples. Some viruses discovered in this study were genetically similar to pathogens that cause hepatitis, diarrhea, or encephalitis in humans, suggesting the presence of new threats to public health. Our study demonstrates the effectiveness of reusing public sequencing data to identify known and unknown viral infections, indicating that future continuous monitoring of public sequencing data by metagenomic analyses would help prepare and mitigate future viral pandemics.

Data Proliferation, Reconciliation, and Synthesis in Viral Ecology

The fields of viral ecology and evolution are rapidly expanding, motivated in part by concerns around emerging zoonoses. One consequence is the proliferation of host–virus association data, which underpin viral macroecology and zoonotic risk prediction but remain fragmented across numerous data portals. In the present article, we propose that synthesis of host–virus data is a central challenge to characterize the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open database of mammal host–virus associations that reconciles four published data sets. We show that this offers a substantially richer view of the known virome than any individual source data set but also that databases such as these risk becoming out of date as viral discovery accelerates. We argue for a shift in practice toward the development, incremental updating, and use of synthetic data sets in viral ecology, to improve replicability and facilitate work to predict the structure and dynamics of the global virome.

Setting the Terms for Zoonotic Diseases: Effective Communication for Research, Conservation, and Public Policy

Many of the world's most pressing issues, such as the emergence of zoonotic diseases, can only be addressed through interdisciplinary research. However, the findings of interdisciplinary research are susceptible to miscommunication among both professional and non-professional audiences due to differences in training, language, experience, and understanding. Such miscommunication contributes to the misunderstanding of key concepts or processes and hinders the development of effective research agendas and public policy. These misunderstandings can also provoke unnecessary fear in the public and have devastating effects for wildlife conservation. For example, inaccurate communication and subsequent misunderstanding of the potential associations between certain bats and zoonoses has led to persecution of diverse bats worldwide and even government calls to cull them. Here, we identify four types of miscommunication driven by the use of terminology regarding bats and the emergence of zoonotic diseases that we have categorized based on their root causes: (1) incorrect or overly broad use of terms; (2) terms that have unstable usage within a discipline, or different usages among disciplines; (3) terms that are used correctly but spark incorrect inferences about biological processes or significance in the audience; (4) incorrect inference drawn from the evidence presented. We illustrate each type of miscommunication with commonly misused or misinterpreted terms, providing a definition, caveats and common misconceptions, and suggest alternatives as appropriate. While we focus on terms specific to bats and disease ecology, we present a more general framework for addressing miscommunication that can be applied to other topics and disciplines to facilitate more effective research, problem-solving, and public policy.

Transmission of SARS-CoV-2 virus and ambient temperature: a critical review

The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented public health, and social and economic challenges. It remains unclear whether seasonal changes in ambient temperature will alter spreading trajectory of the COVID-19 epidemic. The probable mechanism on this is still lacking. This review summarizes the most recent research data on the effect of ambient temperature on the COVID-19 epidemic characteristic. The available data suggest that (i) mesophilic traits of viruses are different due to their molecular composition; (ii) increasing ambient temperature decreases the persistence of some viruses in aquatic media; (iii) a 1°C increase in the average monthly minimum ambient temperatures (AMMAT) was related to a 0.72% fewer mammalian individuals that would be infected by coronavirus; (iv) proportion of zoonotic viruses of mammals including humans is probably related to their body temperature difference; (v) seasonal divergence between the northern and southern hemispheres may be a significant driver in determining a waved trajectory in the next 2 years. Further research is needed to understand its effects and mechanisms of global temperature change so that effective strategies can be adopted to curb its natural effects. This paper mainly explores possible scientific hypothesis and evidences that local communities and authorities should consider to find optimal solutions that can limit the transmission of SARS-CoV-2 virus.

Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations

Our knowledge of viral host ranges remains limited. Completing this picture by identifying unknown hosts of known viruses is an important research aim that can help identify and mitigate zoonotic and animal-disease risks, such as spill-over from animal reservoirs into human populations. To address this knowledge-gap we apply a divide-and-conquer approach which separates viral, mammalian and network features into three unique perspectives, each predicting associations independently to enhance predictive power. Our approach predicts over 20,000 unknown associations between known viruses and susceptible mammalian species, suggesting that current knowledge underestimates the number of associations in wild and semi-domesticated mammals by a factor of 4.3, and the average potential mammalian host-range of viruses by a factor of 3.2. In particular, our results highlight a significant knowledge gap in the wild reservoirs of important zoonotic and domesticated mammals' viruses: specifically, lyssaviruses, bornaviruses and rotaviruses.

How many human pathogens are there in Laos? An estimate of national human pathogen diversity and analysis of historical trends

Objective

The emergence of infectious diseases pose major global health threats. Estimates of total in-country human pathogen diversity, and insights as to how and when species were described through history, could be used to estimate the probability of new pathogen discoveries. Data from the Lao People’s Democratic Republic (Laos) were used in this proof-of-concept study to estimate national human pathogen diversity and to examine historical discovery rate drivers.

Methods

A systematic survey of the French and English scientific and grey literature of pathogen description in Laos between 1874 and 2017 was conducted. The first descriptions of each known human pathogen in Laos were coded according to the diagnostic evidence available. Cumulative frequency of discovery across time informed the rate of discovery. Four distinct periods of health systems development in Laos were identified prospectively and juxtaposed to the unmodelled rate of discovery. A model with a time-varying rate of discovery was fitted to these data using a Markov-Chain- Monte-Carlo technique.

Results

From 6456 pathogen descriptions, 245 discoveries of known human pathogens in Laos, including repeat discoveries using different grades of evidence, were identified. The models estimate that the Laos human pathogen species diversity in 2017 is between 169 and 206. During the last decade, there has been a 33-fold increase in the discovery rate coinciding with the strengthening of medical research and microbiology.

Conclusion

Discovery curves can be used to model and estimate country-level human pathogen diversity present in a territory. Combining this with historical assessment improves the understanding of the factors affecting local pathogen discovery.

PROSPERO registration number

A protocol of this work was registered on PROSPERO (ID:CRD42016046728).

Leveraging natural history biorepositories as a global, decentralized, pathogen surveillance network

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic reveals a major gap in global biosecurity infrastructure: a lack of publicly available biological samples representative across space, time, and taxonomic diversity. The shortfall, in this case for vertebrates, prevents accurate and rapid identification and monitoring of emerging pathogens and their reservoir host(s) and precludes extended investigation of ecological, evolutionary, and environmental associations that lead to human infection or spillover. Natural history museum biorepositories form the backbone of a critically needed, decentralized, global network for zoonotic pathogen surveillance, yet this infrastructure remains marginally developed, underutilized, underfunded, and disconnected from public health initiatives. Proactive detection and mitigation for emerging infectious diseases (EIDs) requires expanded biodiversity infrastructure and training (particularly in biodiverse and lower income countries) and new communication pipelines that connect biorepositories and biomedical communities. To this end, we highlight a novel adaptation of Project ECHO’s virtual community of practice model: Museums and Emerging Pathogens in the Americas (MEPA). MEPA is a virtual network aimed at fostering communication, coordination, and collaborative problem-solving among pathogen researchers, public health officials, and biorepositories in the Americas. MEPA now acts as a model of effective international, interdisciplinary collaboration that can and should be replicated in other biodiversity hotspots. We encourage deposition of wildlife specimens and associated data with public biorepositories, regardless of original collection purpose, and urge biorepositories to embrace new specimen sources, types, and uses to maximize strategic growth and utility for EID research. Taxonomically, geographically, and temporally deep biorepository archives serve as the foundation of a proactive and increasingly predictive approach to zoonotic spillover, risk assessment, and threat mitigation.

How accurately can we assess zoonotic risk?

Identifying the animal reservoirs from which zoonotic viruses will likely emerge is central to understanding the determinants of disease emergence. Accordingly, there has been an increase in studies attempting zoonotic “risk assessment.” Herein, we demonstrate that the virological data on which these analyses are conducted are incomplete, biased, and rapidly changing with ongoing virus discovery. Together, these shortcomings suggest that attempts to assess zoonotic risk using available virological data are likely to be inaccurate and largely only identify those host taxa that have been studied most extensively. We suggest that virus surveillance at the human–animal interface may be more productive.

Determining which organisms harbour viruses that could potentially infect humans is of great topical interest. This Essay demonstrates that the data on which such zoonotic risk assessments are conducted are incomplete, biased, and rapidly changing with ongoing virus discovery.