Identifying and prioritizing potential human-infecting viruses from their genome sequences

Efficient and accurate detection of viral sequences at single-cell resolution reveals putative novel viruses perturbing host gene expression

There are an estimated 300,000 mammalian viruses from which infectious diseases in humans may arise. They inhabit human tissues such as the lungs, blood, and brain and often remain undetected. Efficient and accurate detection of viral infection is vital to understanding its impact on human health and to make accurate predictions to limit adverse effects, such as future epidemics. The increasing use of high-throughput sequencing methods in research, agriculture, and healthcare provides an opportunity for the cost-effective surveillance of viral diversity and investigation of virus-disease correlation. However, existing methods for identifying viruses in sequencing data rely on and are limited to reference genomes or cannot retain single-cell resolution through cell barcode tracking. We introduce a method that accurately and rapidly detects viral sequences in bulk and single-cell transcriptomics data based on highly conserved amino acid domains, which enables the detection of RNA viruses covering up to 1012 virus species. The analysis of viral presence and host gene expression in parallel at single-cell resolution allows for the characterization of host viromes and the identification of viral tropism and host responses. We applied our method to identify putative novel viruses in rhesus macaque PBMC data that display cell type specificity and whose presence correlates with altered host gene expression.

Geographically widespread and novel hemotropic mycoplasmas and bartonellae in Mexican free-tailed bats and sympatric North American bat species

Bacterial pathogens remain poorly characterized in bats, especially in North America. We describe novel (and in some cases panmictic) hemoplasmas (12.9% positivity) and bartonellae (16.7% positivity) across three colonies of Mexican free-tailed bats (Tadarida brasiliensis), a partially migratory species that can seasonally travel hundreds of kilometers. Molecular analyses identified three novel Candidatus hemoplasma species most similar to another novel Candidatus species in Neotropical molossid bats. We also detected novel hemoplasmas in sympatric cave myotis (Myotis velifer) and pallid bats (Antrozous pallidus), with sequences in the latter 96.5% related to C. Mycoplasma haemohominis. We identified eight Bartonella genotypes, including those in cave myotis, with 96.7% similarity to C. Bartonella mayotimonensis. We also detected Bartonella rochalimae in migratory Tadarida brasiliensis, representing the first report of this human pathogen in bats. The seasonality and diversity of these bacteria observed here suggest that additional longitudinal, genomic, and immunological studies in bats are warranted.

Temporal Dynamics, Discovery, and Emergence of Human-Transmissible RNA Viruses

Transmissibility, the ability to spread within host populations, is a prerequisite for a pathogen to have epidemic or pandemic potential. Here, we estimate the phylogenies of human infectivity and transmissibility using 1,408 genome sequences from 743 distinct RNA virus species/types in 59 genera. By repeating this analysis using data sets censored by virus discovery date, we explore how temporal changes in the known diversity of RNA viruses-especially recent increases in recognized nonhuman viruses-have altered these phylogenies. Over time, we find significant increases in the proportion of RNA virus genera estimated to have a nonhuman-infective ancestral state, in the fraction of distinct human virus lineages that are purely human-transmissible or strictly zoonotic (compared to mixed lineages), and in the number of human viruses with nearest relatives known not to infect humans. Our results are consistent with viruses that are capable of spreading in human populations commonly emerging from a nonhuman reservoir. This is more likely in lineages that already contain human-transmissible viruses but is rare in lineages that contain only strictly zoonotic viruses.

First detection and characterization of hepatitis E virus (Rocahepevirus ratti) from urban Norway rats (Rattus norvegicus) in the Republic of Korea

Hepatitis E virus (HEV), an emerging zoonotic pathogen, poses a significant public health concern worldwide. Recently, rat HEV (Rocahepevirus ratti genotype C1; HEV-C1) has been reported to cause zoonotic infections and hepatitis in humans. Human infections with HEV-C1 are considered to be underestimated worldwide due to limited knowledge of transmission routes, genome epidemiology, and the risk assessment of zoonosis associated with these viruses. A total of 186 wild Norway rats (Rattus norvegicus) were collected from the Republic of Korea (ROK) between 2011 and 2021. The prevalence of HEV-C1 RNA was 8 of 180 (4.4%) by reverse-transcription polymerase chain reaction. We first reported three nearly whole-genome sequences of HEV-C1 newly acquired from urban rats in the ROK. Phylogenetic analysis demonstrated that Korea-indigenous HEV-C1 formed an independent genetic group with those derived from R. norvegicus rats in other countries, indicating geographical and genetic diversity. Our findings provide critical insights into the molecular prevalence, genome epidemiology, and zoonotic potential of Rocahepevirus. This report raises awareness of the presence of Rocahepevirus-related hepatitis E among physicians in the ROK.

Characterisation of putative novel tick viruses and zoonotic risk prediction

Tick-associated viruses remain a substantial zoonotic risk worldwide, so knowledge of the diversity of tick viruses has potential health consequences. Despite their importance, large amounts of sequences in public data sets from tick meta-genomic and -transcriptomic projects remain unannotated, sequence data that could contain undocumented viruses. Through data mining and bioinformatic analysis of more than 37,800 public meta-genomic and -transcriptomic data sets, we found 83 unannotated contigs exhibiting high identity with known tick viruses. These putative viral contigs were classified into three RNA viral families (Alphatetraviridae, Orthomyxoviridae and Chuviridae) and one DNA viral family (Asfarviridae). After manual checking of quality and dissimilarity towards other sequences in the data set, these 83 contigs were reduced to five contigs in the Alphatetraviridae from four putative viruses, four in the Orthomyxoviridae from two putative viruses and one in the Chuviridae which clustered with known tick-associated viruses, forming a separate clade within the viral families. We further attempted to assess which previously known tick viruses likely represent zoonotic risks and thus deserve further investigation. We ranked the human infection potential of 133 known tick-associated viruses using a genome composition-based machine learning model. We found five high-risk tick-associated viruses (Langat virus, Lonestar tick chuvirus 1, Grotenhout virus, Taggert virus and Johnston Atoll virus) that have not been known to infect human and two viral families (Nairoviridae and Phenuiviridae) that contain a large proportion of potential zoonotic tick-associated viruses. This adds to the knowledge of tick virus diversity and highlights the importance of surveillance of newly emerging tick-associated diseases.

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick-borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high-risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work.

Bastroviruses (Astroviridae): genetic diversity and potential impact on human and animal health

INTRODUCTION

Bastroviruses were discovered in the Netherlands in 2016 in human stool samples and show partial genetic similarities to astroviruses and hepatitis E viruses. Their association with disease onset has not yet been established.

MATERIALS AND METHODS

Metagenomic sequencing of fecal samples of Nyctalus noctula bats collected in the Russian Federation in 2023 was performed. Two almost complete genomes of bastroviruses were assembled. The zoonotic potential of these viruses was assessed using machine learning methods, their recombination was studied, and phylogenetic trees were constructed.

RESULTS

A nearly complete bastrovirus genome was de novo assembled in one of the samples, and it was used to assemble another genome in another sample. The zoonotic potential of the virus from one of these samples was estimated as high. The existence of recombination between structural and non-structural polyproteins was demonstrated.

CONCLUSION

Two bastrovirus genomes were assembled, phylogenetic and recombination analyses were performed, and the zoonotic potential was evaluated.

Evaluating the zoonotic potential of RNA viromes of rodents provides new insight into rodent-borne zoonotic pathogens in Guangdong, China

Emerging and re-emerging infectious diseases have been on the rise, with a significant proportion being zoonotic. Rodents, as the natural reservoirs of numerous diverse zoonotic viruses, pose a substantial threat to human health. To investigate the diversity of known and unknown viruses harbored by rodents in Guangdong (southern province of China), we conducted a comprehensive analysis of viral genomes through metagenomic sequencing of organs from 194 rodents. Our analysis yielded 2163 viral contigs that were assigned to 25 families known to infect a wide range of hosts, including vertebrates, invertebrates, amoebas, and plants. The viral compositions vary considerably among different organs, but not in rodent species. We also assessed and prioritized zoonotic potential of those detected viruses. Ninety-two viral species that are either known to infect vertebrates and invertebrates or only vertebrates were identified, among which 21 are considered high-risk to humans. The high-risk viruses included members of the Hantavirus, Picobirnaviruses, Astroviruses and Pestivirus. The phylogenetic trees of four zoonotic viruses revealed features of novel viral genomes that seem to fit evolutionarily into a zone of viruses that potentially pose a risk of transmission to humans. Recognizing that zoonotic diseases are a One Health issue, we approached the problem of identifying the zoonotic risk from rodent-transmitted disease in the Guangdong province by performing next-generation sequencing to look for potentially zoonotic viruses in these animals.

Evidence for an ancient aquatic origin of the RNA viral order Articulavirales

The emergence of previously unknown disease-causing viruses in mammals is in part the result of a long-term evolutionary process. Reconstructing the deep phylogenetic histories of viruses helps identify major evolutionary transitions and contextualizes the emergence of viruses in new hosts. We used a combination of total RNA sequencing and transcriptome data mining to extend the diversity and evolutionary history of the RNA virus order Articulavirales, which includes the influenza viruses. We identified instances of Articulavirales in the invertebrate phylum Cnidaria (including corals), constituting a novel and divergent family that we provisionally named the "Cnidenomoviridae." We further extended the evolutionary history of the influenza virus lineage by identifying four divergent, fish-associated influenza-like viruses, thereby supporting the hypothesis that fish were among the first hosts of influenza viruses. In addition, we substantially expanded the phylogenetic diversity of quaranjaviruses and proposed that this genus be reclassified as a family-the "Quaranjaviridae." Within this putative family, we identified a novel arachnid-infecting genus, provisionally named "Cheliceravirus." Notably, we observed a close phylogenetic relationship between the Crustacea- and Chelicerata-infecting "Quaranjaviridae" that is inconsistent with virus-host codivergence. Together, these data suggest that the Articulavirales has evolved over at least 600 million years, first emerging in aquatic animals. Importantly, the evolution of the Articulavirales was likely shaped by multiple aquatic-terrestrial transitions and substantial host jumps, some of which are still observable today.

Viral genomic features predict orthopoxvirus reservoir hosts

Orthopoxviruses (OPVs), including the causative agents of smallpox and mpox have led to devastating outbreaks in human populations worldwide. However, the discontinuation of smallpox vaccination, which also provides cross-protection against related OPVs, has diminished global immunity to OPVs more broadly. We apply machine learning models incorporating both host ecological and viral genomic features to predict likely reservoirs of OPVs. We demonstrate that incorporating viral genomic features in addition to host ecological traits enhanced the accuracy of potential OPV host predictions, highlighting the importance of host-virus molecular interactions in predicting potential host species. We identify hotspots for geographic regions rich with potential OPV hosts in parts of southeast Asia, equatorial Africa, and the Amazon, revealing high overlap between regions predicted to have a high number of potential OPV host species and those with the lowest smallpox vaccination coverage, indicating a heightened risk for the emergence or establishment of zoonotic OPVs. Our findings can be used to target wildlife surveillance, particularly related to concerns about mpox establishment beyond its historical range.

The International Virus Bioinformatics Meeting 2023

The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24-26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.

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.

Permafrost viremia and immune tweening

The immune system, an exquisitely regulated physiological system, utilizes a wide spectrum of soluble factors and multiple cell populations and subpopulations at diverse states of maturation to monitor and protect the organism against foreign organisms. Immune surveillance is ensured by distinguishing self-antigens from self-associated with non-self (e.g., viral) peptides presented by major histocompatibility complexes (MHC). Pathology is often identified as unregulated inflammatory responses (e.g., cytokine storm), or recognizing self as a non-self entity (i.e., auto-immunity). Artificial intelligence (AI), and in particular specific machine learning (ML) paradigms (e.g., Deep Learning [DL]) proffer powerful algorithms to better understand and more accurately predict immune responses, immune regulation and homeostasis, and immune reactivity to challenges (i.e., immune allostasis) by their intrinsic ability to interpret immune parameters, pathways and events by analyzing large amounts of complex data and drawing predictive inferences (i.e., immune tweening). We propose here that DL models play an increasingly significant role in better defining and characterizing immunological surveillance to ancient and novel virus species released by thawing permafrost.

Higher convergence of human-great ape enteric eukaryotic viromes in central African forest than in a European zoo: a One Health analysis

Human-animal pathogenic transmissions threaten both human and animal health, and the processes catalyzing zoonotic spillover and spillback are complex. Prior field studies offer partial insight into these processes but overlook animal ecologies and human perceptions and practices facilitating human-animal contact. Conducted in Cameroon and a European zoo, this integrative study elucidates these processes, incorporating metagenomic, historical, anthropological and great ape ecological analyses, and real-time evaluation of human-great ape contact types and frequencies. We find more enteric eukaryotic virome sharing between Cameroonian humans and great apes than in the zoo, virome convergence between Cameroonian humans and gorillas, and adenovirus and enterovirus taxa as most frequently shared between Cameroonian humans and great apes. Together with physical contact from hunting, meat handling and fecal exposure, overlapping human cultivation and gorilla pillaging in forest gardens help explain these findings. Our multidisciplinary study identifies environmental co-use as a complementary mechanism for viral sharing.

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.

The host phylogeny determines viral infectivity and replication across Staphylococcus host species

Virus host shifts, where a virus transmits to and infects a novel host species, are a major source of emerging infectious disease. Genetic similarity between eukaryotic host species has been shown to be an important determinant of the outcome of virus host shifts, but it is unclear if this is the case for prokaryotes where anti-virus defences can be transmitted by horizontal gene transfer and evolve rapidly. Here, we measure the susceptibility of 64 strains of Staphylococcaceae bacteria (48 strains of Staphylococcus aureus and 16 non-S. aureus species spanning 2 genera) to the bacteriophage ISP, which is currently under investigation for use in phage therapy. Using three methods-plaque assays, optical density (OD) assays, and quantitative (q)PCR-we find that the host phylogeny explains a large proportion of the variation in susceptibility to ISP across the host panel. These patterns were consistent in models of only S. aureus strains and models with a single representative from each Staphylococcaceae species, suggesting that these phylogenetic effects are conserved both within and among host species. We find positive correlations between susceptibility assessed using OD and qPCR and variable correlations between plaque assays and either OD or qPCR, suggesting that plaque assays alone may be inadequate to assess host range. Furthermore, we demonstrate that the phylogenetic relationships between bacterial hosts can generally be used to predict the susceptibility of bacterial strains to phage infection when the susceptibility of closely related hosts is known, although this approach produced large prediction errors in multiple strains where phylogeny was uninformative. Together, our results demonstrate the ability of bacterial host evolutionary relatedness to explain differences in susceptibility to phage infection, with implications for the development of ISP both as a phage therapy treatment and as an experimental system for the study of virus host shifts.

Metagenomic Detection of Divergent Insect- and Bat-Associated Viruses in Plasma from Two African Individuals Enrolled in Blood-Borne Surveillance

Metagenomic next-generation sequencing (mNGS) has enabled the high-throughput multiplexed identification of sequences from microbes of potential medical relevance. This approach has become indispensable for viral pathogen discovery and broad-based surveillance of emerging or re-emerging pathogens. From 2015 to 2019, plasma was collected from 9586 individuals in Cameroon and the Democratic Republic of the Congo enrolled in a combined hepatitis virus and retrovirus surveillance program. A subset (n = 726) of the patient specimens was analyzed by mNGS to identify viral co-infections. While co-infections from known blood-borne viruses were detected, divergent sequences from nine poorly characterized or previously uncharacterized viruses were also identified in two individuals. These were assigned to the following groups by genomic and phylogenetic analyses: densovirus, nodavirus, jingmenvirus, bastrovirus, dicistrovirus, picornavirus, and cyclovirus. Although of unclear pathogenicity, these viruses were found circulating at high enough concentrations in plasma for genomes to be assembled and were most closely related to those previously associated with bird or bat excrement. Phylogenetic analyses and in silico host predictions suggested that these are invertebrate viruses likely transmitted through feces containing consumed insects or through contaminated shellfish. This study highlights the power of metagenomics and in silico host prediction in characterizing novel viral infections in susceptible individuals, including those who are immunocompromised from hepatitis viruses and retroviruses, or potentially exposed to zoonotic viruses from animal reservoir species.

Through an ecological lens: An ecosystem-based approach to zoonotic risk assessment: An ecosystem-based approach to zoonotic risk assessment

Public health strategies to mitigate the emergence of novel pathogenic viruses should implement longitudinal metagenomic surveillance of ecosystems experiencing biodiversity changes to identify generalist viruses.

An Old Acquaintance: Could Adenoviruses Be Our Next Pandemic Threat?

Human adenoviruses (HAdV) are one of the most important pathogens detected in acute respiratory diseases in pediatrics and immunocompromised patients. In 1953, Wallace Rowe described it for the first time in oropharyngeal lymphatic tissue. To date, more than 110 types of HAdV have been described, with different cellular tropisms. They can cause respiratory and gastrointestinal symptoms, even urinary tract inflammation, although most infections are asymptomatic. However, there is a population at risk that can develop serious and even lethal conditions. These viruses have a double-stranded DNA genome, 25-48 kbp, 90 nm in diameter, without a mantle, are stable in the environment, and resistant to fat-soluble detergents. Currently the diagnosis is made with lateral flow immunochromatography or molecular biology through a polymerase chain reaction. This review aimed to highlight the HAdV variability and the pandemic potential that a HAdV3 and 7 recombinant could have considering the aggressive outbreaks produced in health facilities. Herein, we described the characteristics of HAdV, from the infection to treatment, vaccine development, and the evaluation of the social determinants of health associated with HAdV, suggesting the necessary measures for future sanitary control to prevent disasters such as the SARS-CoV-2 pandemic, with an emphasis on the use of recombinant AdV vaccines to control other potential pandemics.

Design of a pan-betacoronavirus vaccine candidate through a phylogenetically informed approach

Coronaviruses are a diverse family of viruses that crossed over into humans at least seven times, precipitating mild to catastrophic outcomes. The severe acute respiratory syndrome coronavirus 2 pandemic renewed efforts to identify strains with zoonotic potential and to develop pan-coronavirus vaccines. The analysis of 2181 coronavirus genomes (from 102 host species) confirmed the limited sequence conservation across genera (alpha-, beta-, delta-, and gammacoronavirus) and proteins. A phylogenetically informed pan-coronavirus vaccine was not feasible because of high genetic heterogeneity across genera. We focused on betacoronaviruses and identified nonhuman-infecting receptor binding domain (RBD) sequences that were more genetically similar to human coronaviruses than expected given their phylogenetic divergence. These human-like RBDs defined three phylogenetic clusters. A vaccine candidate based on a representative sequence for each cluster covers the diversity estimated to protect against existing and future human-infecting betacoronaviruses. Our findings emphasize the potential value of conceptualizing prophylaxis against zoonoses in terms of genetic, rather than species, diversity.

Large-scale investigation of zoonotic viruses in the era of high-throughput sequencing

Zoonotic diseases considerably impact public health and socioeconomics. RNA viruses reportedly caused approximately 94% of zoonotic diseases documented from 1990 to 2010, emphasizing the importance of investigating RNA viruses in animals. Furthermore, it has been estimated that hundreds of thousands of animal viruses capable of infecting humans are yet to be discovered, warning against the inadequacy of our understanding of viral diversity. High-throughput sequencing (HTS) has enabled the identification of viral infections with relatively little bias. Viral searches using both symptomatic and asymptomatic animal samples by HTS have revealed hidden viral infections. This review introduces the history of viral searches using HTS, current analytical limitations, and future potentials. We primarily summarize recent research on large-scale investigations on viral infections reusing HTS data from public databases. Furthermore, considering the accumulation of uncultivated viruses, we discuss current studies and challenges for connecting viral sequences to their phenotypes using various approaches: performing data analysis, developing predictive modeling, or implementing high-throughput platforms of virological experiments. We believe that this article provides a future direction in large-scale investigations of potential zoonotic viruses using the HTS technology.

Glycosylation and the global virome

The sugars that coat the outsides of viruses and host cells are key to successful disease transmission, but they remain understudied compared to other molecular features. Understanding the comparative zoology of glycosylation - and harnessing it for predictive science - could help close the molecular gap in zoonotic risk assessment.

Bioinformatics approaches for unveiling virus-host interactions

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus-host interactions through host range prediction and protein-protein interaction prediction. Although many algorithms have been developed to predict virus-host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus-host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus-host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

Enveloped viruses show increased propensity to cross-species transmission and zoonosis

The transmission of viruses between different host species is a major source of emerging diseases and is of particular concern in the case of zoonotic transmission from mammals to humans. Several zoonosis risk factors have been identified, but it is currently unclear which viral traits primarily determine this process as previous work has focused on a few hundred viruses that are not representative of actual viral diversity. Here, we investigate fundamental virological traits that influence cross-species transmissibility and zoonotic propensity by interrogating a database of over 12,000 mammalian virus-host associations. Our analysis reveals that enveloped viruses tend to infect more host species and are more likely to be zoonotic than nonenveloped viruses, while other viral traits such as genome composition, structure, size, or the viral replication compartment play a less obvious role. This contrasts with the previous notion that viral envelopes did not significantly impact or even reduce zoonotic risk and should help better prioritize outbreak prevention efforts. We suggest several mechanisms by which viral envelopes could promote cross-species transmissibility, including structural flexibility of receptor-binding proteins and evasion of viral entry barriers.

Disease-causing human viruses: novelty and legacy

About 270 viruses are known to infect humans. Some of these viruses have been known for centuries, whereas others have recently emerged. During their evolutionary history, humans have moved out of Africa to populate the world. In historical times, human migrations resulted in the displacement of large numbers of people. All these events determined the movement and dispersal of human-infecting viruses. Technological advances have resulted in the characterization of the genetic variability of human viruses, both in extant and in archaeological samples. Field studies investigated the diversity of viruses hosted by other animals. In turn, these advances provided insight into the evolutionary history of human viruses back in time and defined the key events through which they originated and spread.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens.

International law reform for One Health notifications

Epidemic risk assessment and response relies on rapid information sharing. Using examples from the past decade, we discuss the limitations of the present system for outbreak notifications, which suffers from ambiguous obligations, fragile incentives, and an overly narrow focus on human outbreaks. We examine existing international legal frameworks, and provide clarity on what a successful One Health approach to proposed international law reforms-including a pandemic treaty and amendments to the International Health Regulations-would require. In particular, we focus on how a treaty would provide opportunities to simultaneously expand reporting obligations, accelerate the sharing of scientific discoveries, and strengthen existing legal frameworks, all while addressing the most complex issues that global health governance currently faces.

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.

An atlas of human viruses provides new insights into diversity and tissue tropism of human viruses

MOTIVATION

Viruses continue to threaten human health. Yet, the complete viral species carried by humans and their infection characteristics have not been fully revealed.

RESULTS

This study curated an atlas of human viruses from public databases and literature, and built the Human Virus Database (HVD). The HVD contains 1,131 virus species of 54 viral families which were more than twice the number of the human-infecting virus species reported in previous studies. These viruses were identified in human samples including 68 human tissues, the excreta and body fluid. The viral diversity in humans was age-dependent with a peak in the infant and a valley in the teenager. The tissue tropism of viruses was found to be associated with several factors including the viral group (DNA, RNA or reverse-transcribing viruses), enveloped or not, viral genome length and GC content, viral receptors and the virus-interacting proteins. Finally, the tissue tropism of DNA viruses was predicted using a random-forest algorithm with a middle performance. Overall, the study not only provides a valuable resource for further studies of human viruses, but also deepens our understanding towards the diversity and tissue tropism of human viruses.

AVAILABILITY

The HVD is available at http://computationalbiology.cn/humanVirusBase/#/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SARS-CoV-2 host prediction based on virus-host genetic features

The genetic diversity of the Coronaviruses gives them different biological abilities, such as infect different cells and/or organisms, a wide spectrum of clinical manifestations, their different routes of dispersion, and viral transmission in a specific host. In recent decades, different Coronaviruses have emerged that are highly adapted for humans and causing serious diseases, leaving their host of unknown origin. The viral genome information is particularly important to enable the recognition of patterns linked to their biological characteristics, such as the specificity in the host-parasite relationship. Here, based on a previously computational tool, the Seq2Hosts, we developed a novel approach which uses new variables obtained from the frequency of spike-Coronaviruses codons, the Relative Synonymous Codon Usage (RSCU) to shed new light on the molecular mechanisms involved in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) host specificity. By using the RSCU obtained from nucleotide sequences before the SARS-CoV-2 pandemic, we assessed the possibility of know the hosts capable to be infected by these new emerging species, which was first identified infecting humans during 2019 in Wuhan, China. According to the model trained and validated using sequences available before the pandemic, bats are the most likely the natural host to the SARS-CoV-2 infection, as previously suggested in other studies that searched for the host viral origin.

RNA Virus Diversity in Birds and Small Mammals From Qinghai–Tibet Plateau of China

Most emerging and re-emerging viruses causing infectious diseases in humans and domestic animals have originated from wildlife. However, current knowledge of the spectrum of RNA viruses in the Qinghai-Tibet Plateau in China is still limited. Here, we performed metatranscriptomic sequencing on fecal samples from 56 birds and 91 small mammals in Tibet and Qinghai Provinces, China, to delineate their viromes and focused on vertebrate RNA viruses. A total of 184 nearly complete genome RNA viruses belonging to 28 families were identified. Among these, 173 new viruses shared <90% amino acid identity with previously known viral sequences. Several of these viruses, such as those belonging to genera Orthonairovirus and Hepatovirus, could be zoonotic viruses. In addition, host taxonomy and geographical location of these viruses showed new hosts and distribution of several previously discovered viruses. Moreover, 12 invertebrate RNA viruses were identified with <40% amino acid identity to known viruses, indicating that they belong to potentially new taxa. The detection and characterization of RNA viruses from wildlife will broaden our knowledge of virus biodiversity and possible viral diseases in the Qinghai–Tibet Plateau.

The costs and benefits of primary prevention of zoonotic pandemics

The lives lost and economic costs of viral zoonotic pandemics have steadily increased over the past century. Prominent policymakers have promoted plans that argue the best ways to address future pandemic catastrophes should entail, "detecting and containing emerging zoonotic threats." In other words, we should take actions only after humans get sick. We sharply disagree. Humans have extensive contact with wildlife known to harbor vast numbers of viruses, many of which have not yet spilled into humans. We compute the annualized damages from emerging viral zoonoses. We explore three practical actions to minimize the impact of future pandemics: better surveillance of pathogen spillover and development of global databases of virus genomics and serology, better management of wildlife trade, and substantial reduction of deforestation. We find that these primary pandemic prevention actions cost less than 1/20th the value of lives lost each year to emerging viral zoonoses and have substantial cobenefits.

The next major emergent infectious disease: reflections on vaccine emergency development strategies

INTRODUCTION

Major emergent infectious diseases (MEID) pose the most serious threat to human health. The research proposes targeted response strategies for the prevention and control of potential MEID.

AREAS COVERED

Based on the analysis of infectious diseases, this research analyzes pandemics that have a high probability of occurrence and aims to synthesize the past experience and lessons learned of controlling infectious diseases such as coronavirus, influenza, Ebola, etc. In addition, by integrating major infectious disease response guidelines developed by WHO, the European Union, the United States, and the United Kingdom, we intend to bring forward national vaccine R&D development strategies for emergency use.

EXPERT OPINION

We advise to establish and improve existing laws, regulations, and also prevention and control systems for the emergent R&D and application of vaccines in response to potential infectious diseases. The strategies would not only help increase the various abilities in response to the research, development, evaluation, production, and supervision of emergency vaccines, but also establish surrogate endpoint of immunogenicity protection in early clinical studies to enable a rapid evaluation of the efficacy of emergency vaccines.

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.

One Health Approach: A Data-Driven Priority for Mitigating Outbreaks of Emerging and Re-Emerging Zoonotic Infectious Diseases

This paper discusses the contributions that One Health principles can make in improving global response to zoonotic infectious disease. We highlight some key benefits of taking a One Health approach to a range of complex infectious disease problems that have defied a more traditional sectoral approach, as well as public health policy and practice, where gaps in surveillance systems need to be addressed. The historical examples demonstrate the scope of One Health, partly from an Australian perspective, but also with an international flavour, and illustrate innovative approaches and outcomes with the types of collaborative partnerships that are required.

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.

Animal Models in Human Adenovirus Research

Simple Summary

Animal models are widely used to study various aspects of human diseases and disorders. Likewise, they are indispensable for preclinical testing of medicals and vaccines. Human adenovirus infections are usually self-limiting, and can cause mild respiratory symptoms with fever, eye infection or gastrointestinal symptoms, but occasional local outbreaks with severe disease courses have been reported. In addition, adenovirus infections pose a serious risk for children and patients with a weakened immune system. Human adenovirus research in animal models to study adenovirus-induced disease and tumor development started in the 1950s. Various animal species have been tested for their susceptibility to human adenovirus infection since then, and some have been shown to mimic key characteristics of the infection in humans, including persistent infection. Furthermore, some rodent species have been found to develop tumors upon human adenovirus infection. Our review summarizes the current knowledge on animal models in human adenovirus research, describing the pros and cons along with important findings and future perspectives.

Abstract

Human adenovirus (HAdV) infections cause a wide variety of clinical symptoms, ranging from mild upper respiratory tract disease to lethal outcomes, particularly in immunocompromised individuals. To date, neither widely available vaccines nor approved antiadenoviral compounds are available to efficiently deal with HAdV infections. Thus, there is a need to thoroughly understand HAdV-induced disease, and for the development and preclinical evaluation of HAdV therapeutics and/or vaccines, and consequently for suitable standardizable in vitro systems and animal models. Current animal models to study HAdV pathogenesis, persistence, and tumorigenesis include rodents such as Syrian hamsters, mice, and cotton rats, as well as rabbits. In addition, a few recent studies on other species, such as pigs and tree shrews, reported promising data. These models mimic (aspects of) HAdV-induced pathological changes in humans and, although they are relevant, an ideal HAdV animal model has yet to be developed. This review summarizes the available animal models of HAdV infection with comprehensive descriptions of virus-induced pathogenesis in different animal species. We also elaborate on rodent HAdV animal models and how they contributed to insights into adenovirus-induced cell transformation and cancer.

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.