Identifying Suspect Bat Reservoirs of Emerging Infections

Robust evidence for bats as reservoir hosts is lacking in most African virus studies: a review and call to optimize sampling and conserve bats

Africa experiences frequent emerging disease outbreaks among humans, with bats often proposed as zoonotic pathogen hosts. We comprehensively reviewed virus-bat findings from papers published between 1978 and 2020 to evaluate the evidence that African bats are reservoir and/or bridging hosts for viruses that cause human disease. We present data from 162 papers (of 1322) with original findings on (1) numbers and species of bats sampled across bat families and the continent, (2) how bats were selected for study inclusion, (3) if bats were terminally sampled, (4) what types of ecological data, if any, were recorded and (5) which viruses were detected and with what methodology. We propose a scheme for evaluating presumed virus-host relationships by evidence type and quality, using the contrasting available evidence for Orthoebolavirus versus Orthomarburgvirus as an example. We review the wording in abstracts and discussions of all 162 papers, identifying key framing terms, how these refer to findings, and how they might contribute to people's beliefs about bats. We discuss the impact of scientific research communication on public perception and emphasize the need for strategies that minimize human-bat conflict and support bat conservation. Finally, we make recommendations for best practices that will improve virological study metadata.

Antiviral responses in a Jamaican fruit bat intestinal organoid model of SARS-CoV-2 infection

Bats are natural reservoirs for several zoonotic viruses, potentially due to an enhanced capacity to control viral infection. However, the mechanisms of antiviral responses in bats are poorly defined. Here we established a Jamaican fruit bat (JFB, Artibeus jamaicensis) intestinal organoid model of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Upon infection with SARS-CoV-2, increased viral RNA and subgenomic RNA was detected, but no infectious virus was released, indicating that JFB organoids support only limited viral replication but not viral reproduction. SARS-CoV-2 replication was associated with significantly increased gene expression of type I interferons and inflammatory cytokines. Interestingly, SARS-CoV-2 also caused enhanced formation and growth of JFB organoids. Proteomics revealed an increase in inflammatory signaling, cell turnover, cell repair, and SARS-CoV-2 infection pathways. Collectively, our findings suggest that primary JFB intestinal epithelial cells mount successful antiviral interferon responses and that SARS-CoV-2 infection in JFB cells induces protective regenerative pathways.

Coronavirus sampling and surveillance in bats from 1996-2019: a systematic review and meta-analysis

The emergence of SARS-CoV-2 highlights a need for evidence-based strategies to monitor bat viruses. We performed a systematic review of coronavirus sampling (testing for RNA positivity) in bats globally. We identified 110 studies published between 2005 and 2020 that collectively reported positivity from 89,752 bat samples. We compiled 2,274 records of infection prevalence at the finest methodological, spatiotemporal and phylogenetic level of detail possible from public records into an open, static database named datacov, together with metadata on sampling and diagnostic methods. We found substantial heterogeneity in viral prevalence across studies, reflecting spatiotemporal variation in viral dynamics and methodological differences. Meta-analysis identified sample type and sampling design as the best predictors of prevalence, with virus detection maximized in rectal and faecal samples and by repeat sampling of the same site. Fewer than one in five studies collected and reported longitudinal data, and euthanasia did not improve virus detection. We show that bat sampling before the SARS-CoV-2 pandemic was concentrated in China, with research gaps in South Asia, the Americas and sub-Saharan Africa, and in subfamilies of phyllostomid bats. We propose that surveillance strategies should address these gaps to improve global health security and enable the origins of zoonotic coronaviruses to be identified.

Optimising predictive models to prioritise viral discovery in zoonotic reservoirs

Despite the global investment in One Health disease surveillance, it remains difficult and costly to identify and monitor the wildlife reservoirs of novel zoonotic viruses. Statistical models can guide sampling target prioritisation, but the predictions from any given model might be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use the bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of probable reservoir hosts. In early 2020, we generated an ensemble of eight statistical models that predicted host-virus associations and developed priority sampling recommendations for potential bat reservoirs of betacoronaviruses and bridge hosts for SARS-CoV-2. During a time frame of more than a year, we tracked the discovery of 47 new bat hosts of betacoronaviruses, validated the initial predictions, and dynamically updated our analytical pipeline. We found that ecological trait-based models performed well at predicting these novel hosts, whereas network methods consistently performed approximately as well or worse than expected at random. These findings illustrate the importance of ensemble modelling as a buffer against mixed-model quality and highlight the value of including host ecology in predictive models. Our revised models showed an improved performance compared with the initial ensemble, and predicted more than 400 bat species globally that could be undetected betacoronavirus hosts. We show, through systematic validation, that machine learning models can help to optimise wildlife sampling for undiscovered viruses and illustrates how such approaches are best implemented through a dynamic process of prediction, data collection, validation, and updating.

Molecular identification of Eimeria species in Spanish bats

This is the first study reporting the detection and molecular characterization of Eimeria in bats in Spain, specifically in 12 of 32 chiropteran species described in the Iberian Peninsula. A total of 76 faecal samples were collected from different bat roosting sites across Spanish territory. The DNA was extracted from the samples and sequenced by targeting the Eimeria SSU-rRNA gene. Two Eimeria species were detected in 29 of the 76 faecal samples (38%), and the bat-specific Eimeria rioarribaensis and rodent-specific Eimeria jerfinica were detected in 4 (5%) and 25 (33%) of the samples, respectively. This is the first report of E. rioarribaensis in the bats Rhinolophus euryale, Myotis myotis and Nyctalus lasiopterus, extending the host and geographical ranges for this bat coccidian parasite. The identification of the rodent-specific parasite species E. jerfinica in bats indicates the occurrence of this species in Spain, although its presence has not previously been reported in wild rodents in this country. Considering that most of the Eimeria spp. reported in bats were described only on the basis of morphometric data, molecular studies are required to determined which Eimeria species occur in bats, to complete the identification of these species and to clarify the phylogeny.

Virus isolation data improve host predictions for New World rodent orthohantaviruses

Identifying reservoir host species is crucial for understanding the ecology of multi-host pathogens and predicting risks of pathogen spillover from wildlife to people. Predictive models are increasingly used for identifying ecological traits and prioritizing surveillance of likely zoonotic reservoirs, but these often employ different types of evidence for establishing host associations. Comparisons between models with different infection evidence are necessary to guide inferences about the trait profiles of likely hosts and identify which hosts and geographical regions are likely sources of spillover. Here, we use New World rodent-orthohantavirus associations to explore differences in the performance and predictions of models trained on two types of evidence for infection and onward transmission: RT-PCR and live virus isolation data, representing active infections versus host competence, respectively. Orthohantaviruses are primarily carried by muroid rodents and cause the diseases haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) in humans. We show that although boosted regression tree (BRT) models trained on RT-PCR and live virus isolation data both performed well and capture generally similar trait profiles, rodent phylogeny influenced previously collected RT-PCR data, and BRTs using virus isolation data displayed a narrower list of predicted reservoirs than those using RT-PCR data. BRT models trained on RT-PCR data identified 138 undiscovered hosts and virus isolation models identified 92 undiscovered hosts, with 27 undiscovered hosts identified by both models. Distributions of predicted hosts were concentrated in several different regions for each model, with large discrepancies between evidence types. As a form of validation, virus isolation models independently predicted several orthohantavirus-rodent host associations that had been previously identified through empirical research using RT-PCR. Our model predictions provide a priority list of species and locations for future orthohantavirus sampling. More broadly, these results demonstrate the value of multiple data types for predicting zoonotic pathogen hosts. These methods can be applied across a range of systems to improve our understanding of pathogen maintenance and increase efficiency of pathogen surveillance.

Morphological and quantitative analysis of leukocytes in free-living Australian black flying foxes (Pteropus alecto)

The black flying fox (Pteropus alecto) is a natural reservoir for Hendra virus, a paramyxovirus that causes fatal infections in humans and horses in Australia. Increased excretion of Hendra virus by flying foxes has been hypothesized to be associated with physiological or energetic stress in the reservoir hosts. The objective of this study was to explore the leukocyte profiles of wild-caught P. alecto, with a focus on describing the morphology of each cell type to facilitate identification for clinical purposes and future virus spillover research. To this end, we have created an atlas of images displaying the commonly observed morphological variations across each cell type. We provide quantitative and morphological information regarding the leukocyte profiles in bats captured at two roost sites located in Redcliffe and Toowoomba, Queensland, Australia, over the course of two years. We examined the morphology of leukocytes, platelets, and erythrocytes of P. alecto using cytochemical staining and characterization of blood films through light microscopy. Leukocyte profiles were broadly consistent with previous studies of P. alecto and other Pteropus species. A small proportion of individual samples presented evidence of hemoparasitic infection or leukocyte morphological traits that are relevant for future research on bat health, including unique large granular lymphocytes. Considering hematology is done by visual inspection of blood smears, examples of the varied cell morphologies are included as a visual guide. To the best of our knowledge, this study provides the first qualitative assessment of P. alecto leukocytes, as well as the first set of published hematology reference images for this species.

Natural History of Aerosol-Induced Ebola Virus Disease in Rhesus Macaques

Ebola virus disease (EVD) is a serious global health concern because case fatality rates are approximately 50% due to recent widespread outbreaks in Africa. Well-defined nonhuman primate (NHP) models for different routes of Ebola virus exposure are needed to test the efficacy of candidate countermeasures. In this natural history study, four rhesus macaques were challenged via aerosol with a target titer of 1000 plaque-forming units per milliliter of Ebola virus. The course of disease was split into the following stages for descriptive purposes: subclinical, clinical, and decompensated. During the subclinical stage, high levels of venous partial pressure of carbon dioxide led to respiratory acidemia in three of four of the NHPs, and all developed lymphopenia. During the clinical stage, all animals had fever, viremia, and respiratory alkalosis. The decompensatory stage involved coagulopathy, cytokine storm, and liver and renal injury. These events were followed by hypotension, elevated lactate, metabolic acidemia, shock and mortality similar to historic intramuscular challenge studies. Viral loads in the lungs of aerosol-exposed animals were not distinctly different compared to previous intramuscularly challenged studies. Differences in the aerosol model, compared to intramuscular model, include an extended subclinical stage, shortened clinical stage, and general decompensated stage. Therefore, the shortened timeframe for clinical detection of the aerosol-induced disease can impair timely therapeutic administration. In summary, this nonhuman primate model of aerosol-induced EVD characterizes early disease markers and additional details to enable countermeasure development.

From Protein to Pandemic: The Transdisciplinary Approach Needed to Prevent Spillover and the Next Pandemic

Pandemics are a consequence of a series of processes that span scales from viral biology at 10-9 m to global transmission at 106 m. The pathogen passes from one host species to another through a sequence of events that starts with an infected reservoir host and entails interspecific contact, innate immune responses, receptor protein structure within the potential host, and the global spread of the novel pathogen through the naive host population. Each event presents a potential barrier to the onward passage of the virus and should be characterized with an integrated transdisciplinary approach. Epidemic control is based on the prevention of exposure, infection, and disease. However, the ultimate pandemic prevention is prevention of the spillover event itself. Here, we focus on the potential for preventing the spillover of henipaviruses, a group of viruses derived from bats that frequently cross species barriers, incur high human mortality, and are transmitted among humans via stuttering chains. We outline the transdisciplinary approach needed to prevent the spillover process and, therefore, future pandemics.

Taxonomic resolution affects host-parasite association model performance

Identifying the factors that structure host–parasite interactions is fundamental to understand the drivers of species distributions and to predict novel cross-species transmission events. More phylogenetically related host species tend to have more similar parasite associations, but parasite specificity may vary as a function of transmission mode, parasite taxonomy or life history. Accordingly, analyses that attempt to infer host−parasite associations using combined data on different parasite groups may perform quite differently relative to analyses on each parasite subset. In essence, are more data always better when predicting host−parasite associations, or does parasite taxonomic resolution matter? Here, we explore how taxonomic resolution affects predictive models of host−parasite associations using the London Natural History Museum's database of host–helminth interactions. Using boosted regression trees, we demonstrate that taxon-specific models (i.e. of Acanthocephalans, Nematodes and Platyhelminthes) consistently outperform full models in predicting mammal-helminth associations. At finer spatial resolutions, full and taxon-specific model performance does not vary, suggesting tradeoffs between phylogenetic and spatial scales of analysis. Although all models identify similar host and parasite covariates as important to such patterns, our results emphasize the importance of phylogenetic scale in the study of host–parasite interactions and suggest that using taxonomic subsets of data may improve predictions of parasite distributions and cross-species transmission. Predictive models of host–pathogen interactions should thus attempt to encompass the spatial resolution and phylogenetic scale desired for inference and prediction and potentially use model averaging or ensemble models to combine predictions from separately trained models.

Worldwide occurrence of haemoplasmas in wildlife: Insights into the patterns of infection, transmission, pathology and zoonotic potential

Haemotropic mycoplasmas (haemoplasmas) have increasingly attracted the attention of wildlife disease researchers due to a combination of wide host range, high prevalence and genetic diversity. A systematic review identified 75 articles that investigated haemoplasma infection in wildlife by molecular methods (chiefly targeting partial 16S rRNA gene sequences), which included 131 host genera across six orders. Studies were less common in the Eastern Hemisphere (especially Africa and Asia) and more frequent in the Artiodactyla and Carnivora. Meta-analysis showed that infection prevalence did not vary by geographic region nor host order, but wild hosts showed significantly higher prevalence than captive hosts. Using a taxonomically flexible machine learning algorithm, we also found vampire bats and cervids to have greater prevalence, whereas mink, a subclade of vesper bats, and true foxes all had lower prevalence compared to the remaining sampled mammal phylogeny. Haemoplasma genotype and nucleotide diversity varied little among wild mammals but were marginally lower in primates and bats. Coinfection with more than one haemoplasma species or genotype was always confirmed when assessed. Risk factors of infection identified were sociality, age, males and high trophic levels, and both prevalence and diversity were often higher in undisturbed environments. Haemoplasmas likely use different and concurrent transmission routes and typically display enzootic dynamics when wild populations are studied longitudinally. Haemoplasma pathology is poorly known in wildlife but appears subclinical. Candidatus Mycoplasma haematohominis, which causes disease in humans, probably has it natural host in bats. Haemoplasmas can serve as a model system in ecological and evolutionary studies, and future research on these pathogens in wildlife must focus on increasing the geographic range and taxa of studies and elucidating pathology, transmission and zoonotic potential. To facilitate such work, we recommend using universal PCR primers or NGS protocols to detect novel haemoplasmas and other genetic markers to differentiate among species and infer cross-species transmission.