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Twenty microsatellite loci developed for the straw-colored fruit bat, Eidolon helvum, are described. These markers were used in multiplex PCRs to amplify genomic DNA from 142 individuals sampled from nine populations across Africa. Nineteen loci were polymorphic, with a mean number of alleles per locus of 16.2 (3–46). Observed and expected heterozy...
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Dispersal and migratory behaviours are often important determinants of gene flow in wild species, and we have studied their
role using ringing-recapture data in the Portuguese population of Miniopterus schreibersii, a cave-dwelling bat that forms large maternity colonies. Juvenile dispersal, usually a major agent of gene flow, appears
to be negligi...
Citations
... Molecular methods have been described previously 12,20 . Genomic DNA was extracted from E. helvum tissues (predominantly wing membrane biopsies, but also liver and muscle samples, all stored in ethanol) using DNeasy Blood and Tissue Kits (QIAGEN Ltd., Crawley, West Sussex, UK). ...
... [Data Citation 1]. Loci B has previously been identified as being X-linked 20 . ...
... As previously described 20 , microsatellite loci were tested for evidence of departure from Hardy-Weinberg equilibrium (HWE) and genotypic disequilibrium using FSTAT 2.9 (ref. 40 CHECKER 41 to test for null alleles, stuttering and large allelic dropout as a cause of departure from HWE. ...
Bats, including African straw-coloured fruit bats (Eidolon helvum), have been highlighted as reservoirs of many recently emerged zoonotic viruses. This common, widespread and ecologically important species was the focus of longitudinal and continent-wide studies of the epidemiological and ecology of Lagos bat virus, henipaviruses and Achimota viruses. Here we present a spatial, morphological, demographic, genetic and serological dataset encompassing 2827 bats from nine countries over an 8-year period. Genetic data comprises cytochrome b mitochondrial sequences (n=608) and microsatellite genotypes from 18 loci (n=544). Tooth-cementum analyses (n=316) allowed derivation of rare age-specific serologic data for a lyssavirus, a henipavirus and two rubulaviruses. This dataset contributes a substantial volume of data on the ecology of E. helvum and its viruses and will be valuable for a wide range of studies, including viral transmission dynamic modelling in age-structured populations, investigation of seasonal reproductive asynchrony in wide-ranging species, ecological niche modelling, inference of island colonisation history, exploration of relationships between island and body size, and various spatial analyses of demographic, morphometric or serological data.
... 'Populations' were initially defined arbitrarily based on national borders related to roost location. 48 , Loci E and Ae were discarded due to difficulty in scoring or high error rates and data were locus Ag were re-binned and re-scored, correcting earlier issues with allelic dropout. Positive and negative controls were included on each plate. ...
The straw-coloured fruit bat, Eidolon helvum, is Africa's most widely distributed and commonly hunted fruit bat, often living in close proximity to human populations. This species has been identified as a reservoir of potentially zoonotic viruses, but uncertainties remain regarding viral transmission dynamics and mechanisms of persistence. Here we combine genetic and serological analyses of populations across Africa, to determine the extent of epidemiological connectivity among E. helvum populations. Multiple markers reveal panmixia across the continental range, at a greater geographical scale than previously recorded for any other mammal, whereas populations on remote islands were genetically distinct. Multiple serological assays reveal antibodies to henipaviruses and Lagos bat virus in all locations, including small isolated island populations, indicating that factors other than population size and connectivity may be responsible for viral persistence. Our findings have potentially important public health implications, and highlight a need to avoid disturbances that may precipitate viral spillover.
... In São Tomé, bats were obtained in collaboration with local hunters, who hunted at roost sites during the day or at feeding sites at night. Elsewhere, bats were captured at the roost using mist nets as described previously (Peel et al., 2010). Under manual restraint, 1 ml blood samples were collected and processed, and morphometric and demographic details were recorded as described previously (Peel et al., 2010, 2012). ...
... Elsewhere, bats were captured at the roost using mist nets as described previously (Peel et al., 2010). Under manual restraint, 1 ml blood samples were collected and processed, and morphometric and demographic details were recorded as described previously (Peel et al., 2010, 2012). Age was assessed by morphological characteristics (body size and the degree of genital and nipple development) and all individuals were allocated into one of four age classes: neonate (<2 months), juvenile (J; 2-<6 months), sexually immature (SI; 6-<24 months) or adult (A; ≥24 months). ...
Reservoir hosts of novel pathogens are often identified or suspected as such on the basis of serological assay results, prior to the isolation of the pathogen itself. Serological assays might therefore be used outside of their original, validated scope in order to infer seroprevalences in reservoir host populations, until such time that specific diagnostic assays can be developed. This is particularly the case in wildlife disease research. The absence of positive and negative control samples and gold standard diagnostic assays presents challenges in determining an appropriate threshold, or 'cutoff', for the assay that enables differentiation between seronegative and seropositive individuals. Here, multiple methods were explored to determine an appropriate cutoff for a multiplexed microsphere assay that is used to detect henipavirus antibody binding in fruit bat plasma. These methods included calculating multiples of 'negative' control assay values, receiver operating characteristic curve analyses, and Bayesian mixture models to assess the distribution of assay outputs for classifying seropositive and seronegative individuals within different age classes. As for any diagnostic assay, the most appropriate cutoff determination method and value selected must be made according to the aims of the study. This study is presented as an example for others where reference samples, and assays that have been characterised previously, are absent.
... Additionally, bats are second only to rodents in their species diversity among mammals, resulting in a vast and diverse pool of pathogens to supply potential zoonotic candidates (Wong et al., 2007). The migratory nature of some bat species might also contribute to pathogen mixing across large geographical areas and populations (Peel et al., 2010). The single, synchronised birth pulse of many bat colonies can facilitate persistence of endemic pathogens in bat populations by regularly introducing a large group of susceptible individuals (George et al., 2011). ...
... Its range stretches across nearly the whole of sub-Saharan Africa, though its habitat is largely thought to be tropical forest. A recent genetic study suggests that E. helvum forms one, panmictic population across this range (Peel et al., 2010); however, non-migratory populations located on islands in the Gulf of Guinea may have diverged enough from this mainland population to be considered a subspecies (Juste et al., 2000). E. helvum migrates seasonally, but the full details of the migrational drivers and directions are unclear. ...
... There is also significant evidence of active and endemic henipavirus infections within the Ghanaian fruit bat populations (Hayman et al., 2008). As the populations across this area are panmictic (Peel et al., 2010), it is possible they share a common pool of pathogens as well as genes. While ...
Despite major advances in vaccines, antibiotics and antiviral treatments, infectious diseases still kill 15 million people around the world each year - one quarter of global deaths (Fauci and Morens, 2012). Emerging diseases, caused by new or newly expanding pathogens, form a rapidly changing and intensely challenging front of this international battle. Pathogens that can jump from animals into humans, known as zoonoses, cause over 65% of emerging diseases; three quarters of zoonoses originate in wildlife (Jones et al., 2008). One of the most common sources of human-wildlife contact is through hunting wild animals for food. Researchers have estimated that western and central Africans alone harvest five million tons of bushmeat annually (Fa et al., 2002; Ntiamoa-Baidu, 1998). This massive industry raises concerns across disciplines: not only do epidemiologists fear for the transmission of zoonotic diseases (Daszak, 2000), but conservationists fear for the depletion of threatened and endangered species (Milner-Gulland and Bennett, 2003) and development practitioners worry for the welfare of the communities and people that depend on wild meat for protein and income (Davies, 2002). Of the many animals hunted for bushmeat, bats pose a number of unanswered questions. Hosting almost sixty viruses that can or do infect humans (Wong et al., 2007), bats globally also are suffering severe population declines due to overhunting (Streubig et al., 2007; Harrison et al., 2011). Yet their roles as reservoirs of human disease, as sources of valuable products, and in human culture are all understudied and largely unexplained. The newly identified presence of henipavirus antibodies and $\textit{Bartonella}$ bacteria in $\textit{Eidolon helvum}$ fruit bats in Ghana, as well as the potential for commercial hunting of fruit bats, led me to this project in Ghana, West Africa. I set out to: (1) delineate ways in which bats and their pathogens may come into contact with humans; (2) understand how, where and how many bats are hunted, prepared and sold as bushmeat; (3) identify and characterise potentially at-risk populations for bat-borne zoonoses; and (4) determine whether transmission of selected bat-borne pathogens is already occurring within the identified populations. The urban nature of $\textit{E. helvum}$, the high prevalence of raw palm sap drinking and the large bat bushmeat market all serve as modes of contact between humans and bats. Through 551 interviews with Ghanaians as well as more in depth work with 26 vendors and hunters, I identified demographics as well as perceptions of people involved in bat bushmeat trade. Bat hunting, selling and consumption are widely distributed across region and tribal lines, with hotspots in certain locales; butchering is concentrated in females and active hunters. Interviewees held little belief of disease risk from bats, saw no ecological value of fruit bats outside their economic worth and thought that consumption related to specific tribes. Serological and culture evidence for humans in close contact with bats (by living or working around large $\textit{E. helvum}$ colonies; or through hunting or butchering bats) strongly suggests there is no current spillover of bat-borne $\textit{Bartonella}$ infections. However, a low prevalence of positive human sera samples for henipavirus antibodies using a Luminex testing platform suggests that there may be human exposure to a henipa-like virus.
Exogenous markers to track migrations in wildlife are limited because of their cost and low recapture rates, given this; the use of isotopic markers on ecology has greatly increased. We used isotopic and spatial data from flying foxes (Family Pteropodidae) to determine the migratory origins of E. helvum, species related to a wide range of ecosystem services in Central Africa. We analysed the isotopic ratios (δ) of 2H, 13C and 15N from museum samples and validated the sedentary status of six out of seven species sampled as sedentary. We observed a weak correlation between δ2H from fur samples and δ2H from localities of capture using species as random intercept and slope. However using a triple isotopic approach we were able to discriminate between different locations of capture for two sedentary species with 84% of correct assignations. Finally we implemented a gamma distribution using data from sedentary species to relate δ2H from fur and precipitation, to create probability origin maps for the migratory species. We obtained that 32.9% of E. helvum specimens had a different origin than their locality of capture, with a mean minimum distance of 414 km. For E. gambianus we found a maximum migratory distance about 3,000 km for 7 specimens, and 72.7% of individuals with a migratory behaviour. Even if our results for E. helvum gave us a good representation about their migrations in Central Africa, the results obtained for E. gambianus are contradictory with the literature and previous morphometric studies.
