Biology subjects

Albery, G. F.

Publications and source records attributed to Albery, G. F..

34 records · Page 2Linked to original sources

bioRxiv2021

Host phylogeny and ecological associations best explain Wolbachia host shifts in scale insects

Wolbachia are among the most prevalent and widespread endosymbiotic bacteria on earth. Wolbachia s success in infecting an enormous number of arthropod species is attributed to two features: the range of phenotypes they induce in their hosts, and their ability to switch to new host species. Whilst much progress has been made in elucidating the phenotypes induced by Wolbachia, our understanding of Wolbachia host shifting is still very limited: we lack answers to even fundamental questions concerning Wolbachias routes of transfer and the importance of factors influencing host shifts. Here, we investigate the diversity and host-shift patterns of Wolbachia in scale insects, a group of arthropods with intimate associations with other insects that make them well-suited to studying host shifts. Using Illumina pooled amplicon sequencing of Wolbachia-infected scale insects and their direct associates we determined the identity of all Wolbachia strains, revealing that 32% of samples were multiply infected (with up to five distinct strains per species). We then fitted a Generalised Additive Mixed Model (GAMM) to our data to estimate the influence of factors such as the host phylogeny and the geographic distribution of each species on Wolbachia strain sharing among scale insect species. The model predicts no significant contribution of host geography but strong effects of host phylogeny, with high rates of Wolbachia sharing among closely related species and a sudden drop-off in sharing with increasing phylogenetic distance. We also detected the same Wolbachia strain in scale insects and several intimately associated species (ants, wasps, beetles, and flies). This indicates putative host shifts and potential routes of transfers via these associates and highlights the importance of ecological connectivity in Wolbachia host-shifting.

evolutionary biology↗

bioRxiv2021

Mammal virus diversity estimates are unstable due to accelerating discovery effort

Host-virus association data form the backbone of research into eco-evolutionary drivers of viral diversity and host-level zoonotic risk. However, 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 6,571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are still either constant or accelerating, with little evidence of declines towards viral richness asymptotes in even 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 show 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 our findings suggest that an analysis conducted today could feasibly draw quite different conclusions than one conducted only a decade ago.

ecology↗

bioRxiv2021

The Global Virome in One Network (VIRION): an atlas of vertebrate-virus associations

Data cataloguing viral diversity on Earth have been fragmented across sources, disciplines, formats, and various degrees of open collation, 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 datasets 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 tenth 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.

microbiology↗

bioRxiv2021

Ageing red deer alter their spatial behaviour and become less social

Social relationships are important to many aspects of animals lives, and an individuals connections may change over the course of their lifespan. Currently, it is unclear whether social connectedness declines within individuals as they age, and what the underlying mechanisms might be, so the role of age in structuring animal social systems remains unresolved, particularly in non-primates. Here, we describe senescent declines in social connectedness using 43 years of data in a wild, individually monitored population of a long-lived mammal (European red deer, Cervus elaphus). Applying a series of spatial and social network analyses, we demonstrate that these declines occur due to within-individual changes in social behaviour, with correlated changes in spatial behaviour (smaller home ranges and movements to lower-density, lower-quality areas). These findings demonstrate that within-individual socio-spatial behavioural changes can lead older animals in fission-fusion societies to become less socially connected, shedding light on the ecological and evolutionary processes structuring wild animal populations.

ecology↗

bioRxiv2021

Data proliferation, reconciliation, and synthesis in viral ecology

The fields of viral ecology and evolution have rapidly expanded in the last two decades, driven by technological improvements, and motivated by efforts to discover potentially zoonotic wildlife viruses under the rubric of pandemic prevention. One consequence has been a massive proliferation of host-virus association data, which comprise the backbone of research in viral macroecology and zoonotic risk prediction. These data remain fragmented across numerous data portals and projects, each with their own scope, structure, and reporting standards. Here, we propose that synthesis of host-virus association data is a central challenge to improve our understanding of the global virome and develop foundational theory in viral ecology. To illustrate this, we build an open reconciled mammal-virus database from four key published datasets, applying a standardized taxonomy and metadata. We show that reconciling these datasets provides a substantially richer view of the mammal virome than that offered by any one individual database. We argue for a shift in best practice towards the incremental development and use of synthetic datasets in viral ecology research, both to improve comparability and replicability across studies, and to facilitate future efforts to use machine learning to predict the structure and dynamics of the global virome.

ecology↗

bioRxiv2021

Urban-adapted mammal species have more known pathogens

The world is rapidly urbanising, inviting mounting concern that urban environments will experience increased zoonotic disease risk. Urban animals could have more frequent contact with humans, and therefore may transmit more zoonotic parasites; however, these animals have a specific set of underlying traits that may determine their parasite burdens while predisposing them to urban living, and they may be subject to more intense research effort, both of which could complicate our ability to reliably identify the role of urbanisation in driving zoonotic risk. Here, we test whether urban mammal species host more known zoonotic parasites, investigating the potential underlying drivers while accounting for a correlated suite of phenotypic, taxonomic, and geographic predictors. We found that urban-adapted mammals have more documented parasites, and more zoonotic parasites specifically: despite comprising only 157 of the 2792 investigated species (6%), urban mammals provided 39% of known host-parasite combinations and showed consistently higher viral discovery rates throughout the last century. However, contrary to predictions, much of the observed effect was attributable to research effort rather than to urban adaptation status itself, and urban-adapted species in fact hosted fewer zoonoses than expected given their total observed parasite richness. We conclude that extended historical contact with humans has had a limited impact on the number of observed zoonotic parasites in urban-adapted mammals; instead, their greater observed zoonotic richness likely reflects sampling bias arising from proximity to humans, which supports a near-universal underlying pattern of conflation between zoonotic risk, research effort, and synanthropy. These findings underscore the need to resolve the ecological mechanisms underlying links between anthropogenic change, sampling bias, and observed wildlife disease dynamics.

ecology↗

bioRxiv2020

The discovery, distribution and diversity of DNA viruses associated with Drosophila melanogaster in Europe

Drosophila melanogaster is an important model for antiviral immunity in arthropods, but very few DNA viruses have been described from the family Drosophilidae. This deficiency limits our opportunity to use natural host-pathogen combinations in experimental studies, and may bias our understanding of the Drosophila virome. Here we report fourteen DNA viruses detected in a metagenomic analysis of approximately 6500 pool-sequenced Drosophila, sampled from 47 European locations between 2014 and 2016. These include three new Nudiviruses, a new and divergent Entomopox virus, a virus related to Leptopilina boulardi filamentous virus, and a virus related to Musca domestica salivary gland hypertrophy virus. We also find an endogenous genomic copy of Galbut virus, a dsRNA Partitivirus, segregating at very low frequency. Remarkably, we find that Drosophila Vesanto virus, a small DNA virus previously described as a Bidnavirus, may be composed of up to 12 segments and represent a new lineage of segmented DNA viruses. Two of the DNA viruses, Drosophila Kallithea nudivirus and Drosophila Vesanto virus are relatively common, found in 2% or more of wild flies. The others are rare, with many likely to be represented by a single infected fly. We find that virus prevalence in Europe reflects the prevalence seen in publicly-available datasets, with Drosophila Kallithea nudivirus and Drosophila Vesanto virus the only ones commonly detectable in public data from wild-caught flies and large population cages, and the other viruses being rare or absent. These analyses suggest that DNA viruses are at lower prevalence than RNA viruses in D. melanogaster, and may be less likely to persist in laboratory cultures. Our findings go some way to redressing an earlier bias toward RNA virus studies in Drosophila, and lay the foundation needed to harness the power of Drosophila as a model system for the study of DNA viruses.

microbiology↗

bioRxiv2020

Fine-scale spatial patterns of wildlife disease are common and understudied

O_LIAll parasites are heterogeneous in space, yet little is known about the prevalence and scale of this spatial variation, particularly in wild animal systems. To address this question, we sought to identify and examine spatial dependence of wildlife disease across a wide range of systems. C_LIO_LIConducting a broad literature search, we collated 31 such datasets featuring 89 replicates and 71 unique host-parasite combinations, only 51% of which had previously been used to test spatial hypotheses. We analysed these datasets for spatial dependence within a standardised modelling framework using Bayesian linear models, and we then meta-analysed the results to identify generalised determinants of the scale and magnitude of spatial autocorrelation. C_LIO_LIWe detected spatial autocorrelation in 48/89 model replicates (54%) across 21/31 datasets (68%), spread across parasites of all groups. Even some very small study areas (under 0.01km2) exhibited substantial spatial variation. C_LIO_LIDespite the common manifestation of spatial variation, our meta-analysis was unable to identify host-, parasite-, or sampling-level determinants of this heterogeneity across systems. Parasites of all transmission modes had easily detectable spatial patterns, implying that structured contact networks and susceptibility effects are potentially as important in spatially structuring disease as are environmental drivers of transmission efficiency. C_LIO_LIOur findings demonstrate that fine-scale spatial patterns of infection manifest frequently and across a range of wild animal systems, and many studies are able to investigate them whether or not the original aim of the study was to examine spatially varying processes. Given the widespread nature of these findings, studies should more frequently record and analyse spatial data, facilitating development and testing of spatial hypotheses in disease ecology. Ultimately, this may pave the way for an a priori predictive framework for spatial variation in novel host-parasite systems. C_LI

ecology↗

bioRxiv2020

Negative density-dependent parasitism in a group-living carnivore

Animals living at high population densities commonly experience greater exposure to disease, leading to increased parasite burdens. However, social animals can benefit immunologically and hygienically from cooperation, and individuals may alter their socio-spatial behaviour in response to infection, both of which could counteract density-related increases in exposure. Consequently, the costs and benefits of sociality for disease are often uncertain. Here, we use a long-term study of a wild European badger population (Meles meles) to investigate how within-population variation in host density determines infection with multiple parasites. Four out of five parasite taxa exhibited consistent spatial hotspots of infection, which peaked among badgers living in areas of low local population density. Combined movement, survival, spatial, and social network analyses revealed that parasite avoidance was the likely cause of this negative density dependence, with possible roles for localised mortality, encounter-dilution effects, and micronutrient-enhanced immunity. These findings demonstrate that animals can organise their societies in space to minimise parasite infection, with important implications for badger behavioural ecology and for the control of badger-associated diseases.

ecology↗

bioRxiv2020

Spatial point locations explain a range of social network positions in a wild ungulate

The structure of wild animal social systems depends on a complex combination of intrinsic and extrinsic drivers. Population structuring and spatial behaviour are key determinants of individuals observed social behaviour, but quantifying these spatial components alongside multiple other drivers remains difficult due to data scarcity and analytical complexity. We used a 43-year dataset detailing a wild red deer population to investigate how individuals spatial behaviours drive social network positioning, while simultaneously assessing other potential contributing factors. Using Integrated Nested Laplace Approximation (INLA) multi-matrix animal models, we demonstrate that social network positions are shaped by two-dimensional landscape locations, pairwise space sharing, individual range size, and spatial and temporal variation in population density, alongside smaller but detectable impacts of a selection of individual-level phenotypic traits. These results indicate strong, multifaceted spatiotemporal structuring in this society, emphasising the importance of considering multiple spatial components when investigating the causes and consequences of sociality. Authorship StatementGFA conceived the study, analysed the data, and wrote the manuscript, advised by JAF. AM and SM collected the data. JAF, JMP, THCB, and DN commented on the manuscript. Data Accessibility StatementThe code used here is available at https://github.com/gfalbery/Spocial_Deer. On acceptance, the data will be uploaded to the same repo, which will be archived on Zenodo.

ecology↗

bioRxiv2020

Predicting wildlife hosts of betacoronaviruses for SARS-CoV-2 sampling prioritization

Despite global investment in One Health disease surveillance, it remains difficult--and often very costly--to identify and monitor the wildlife reservoirs of novel zoonotic viruses. Statistical models can be used to guide sampling prioritization, but predictions from any given model may be highly uncertain; moreover, systematic model validation is rare, and the drivers of model performance are consequently under-documented. Here, we use bat hosts of betacoronaviruses as a case study for the data-driven process of comparing and validating predictive models of likely reservoir hosts. In the first quarter of 2020, we generated an ensemble of eight statistical models that predict host-virus associations and developed priority sampling recommendations for potential bat reservoirs and potential bridge hosts for SARS-CoV-2. Over more than a year, we tracked the discovery of 40 new bat hosts of betacoronaviruses, validated initial predictions, and dynamically updated our analytic pipeline. We find that ecological trait-based models perform extremely well at predicting these novel hosts, whereas network methods consistently perform roughly as well or worse than expected at random. These findings illustrate the importance of ensembling as a buffer against variation in model quality and highlight the value of including host ecology in predictive models. Our revised models show improved performance and predict over 400 bat species globally that could be undetected hosts of betacoronaviruses. Although 20 species of horseshoe bats (Rhinolophus spp.) are known to be the primary reservoir of SARS-like viruses, we find at least three-fourths of plausible betacoronavirus reservoirs in this bat genus might still be undetected. Our study is the first to demonstrate through systematic validation that machine learning models can help optimize wildlife sampling for undiscovered viruses and illustrates how such approaches are best implemented through a dynamic process of prediction, data collection, validation, and updating.

ecology↗

bioRxiv2020

Spatiotemporal variation in drivers of parasitism in a wild wood mouse population

O_LIHost-parasite interactions in nature are driven by a range of factors across several ecological scales, so observed relationships are often context-dependent. Importantly, if these factors vary across space and time, practical sampling limitations can limit or bias inferences, and the relative importance of different drivers can be hard to discern. C_LIO_LIWe collected a replicated, longitudinal dataset of >1000 individual wood mice (Apodemus sylvaticus) encompassing 6 years of sampling across 5 different woodland sites to investigate how environmental, host and within-host factors determine infection intensity of a highly prevalent gastrointestinal nematode, Heligmosomoides polygyrus. C_LIO_LIWe used a Bayesian modelling approach to further quantify if and how each factor varied in space and time. Finally, we examined the extent to which a lack of spatially or temporally replication (i.e., within single years or single sites) and single (cross-sectional) versus repeated (longitudinal) sampling of individuals would affect which drivers were found to predict H. polygyrus infection. C_LIO_LISeason, host body condition, and sex were the three most important determinants of infection intensity; however, the strength and even direction of these effects varied in time, but not in space. Additionally, longitudinal datasets, in which we can control for within-individual variation through repeat observations, provided more robust estimates of the drivers of parasite intensity compared to cross-sectional data. C_LIO_LIThese results highlight the importance of accounting for spatiotemporal variation in drivers of disease dynamics and the need to incorporate spatiotemporal replication when designing sampling regimes. Furthermore, they suggest that embracing rather than simply controlling for spatiotemporal variation can reveal important insight into host-parasite relationships in the wild. C_LI

ecology↗

bioRxiv2020

Climate change will drive novel cross-species viral transmission

At least 10,000 species of mammal virus are estimated to have the potential to spread in human populations, but the vast majority are currently circulating in wildlife, largely undescribed and undetected by disease outbreak surveillance 1-3 . In addition, changing climate and land use are already driving geographic range shifts in wildlife, producing novel species assemblages and opportunities for viral sharing between previously isolated species 4, 5 . In some cases, this will inevitably facilitate spillover into humans 6, 7 --a possible mechanistic link between global environmental change and emerging zoonotic disease 8 . Here, we map potential hotspots of viral sharing, using a phylogeographic model of the mammal-virus network, and projections of potential geographic range shifts for 3,139 mammal species under climate change and land use scenarios for the year 2070. Range-shifting mammal species are predicted to aggregate at high elevations, in biodiversity hotspots, and in areas of high human population density in Asia and Africa, driving the novel cross-species transmission of their viruses an estimated 4,000 times. Counter to expectations, holding warming under 2{degrees}C within the century does not reduce new viral sharing, due to greater potential range expansions-- highlighting the need to invest in surveillance even in a low-warming future. Most projected viral sharing is driven by diverse hyperreservoirs (rodents and bats) and large-bodied predators (carnivores). Because of their unique dispersal capacity, bats account for the majority of novel viral sharing, and are likely to share viruses along evolutionary pathways that could facilitate future emergence in humans. Our findings highlight the urgent need to pair viral surveillance and discovery efforts with biodiversity surveys tracking species range shifts, especially in tropical countries that harbor the most emerging zoonoses.

ecology↗

bioRxiv2019

Predicting the global mammalian viral sharing network using phylogeography

Understanding interspecific viral transmission is key to understanding viral ecology and evolution, disease spillover into humans, and the consequences of global change. Prior work has demonstrated that macroecological factors drive viral sharing in some mammalian groups, but analyses have never attempted to predict viral sharing in a pan-mammalian context. Here we show that host phylogenetic similarity and geographic range overlap are strong, nonlinear predictors of viral sharing among species across the entire mammal class. Using these traits, we predict global viral sharing patterns across 4196 mammal species and show that our simulated network successfully predicts viral sharing and reservoir host status using internal validation and an external dataset. We predict high rates of mammalian viral sharing in the tropics, particularly among rodents and bats, and that within- and between-order sharing differs geographically and taxonomically. Our results emphasize the importance of macroecological factors in shaping mammalian viral communities, and provide a robust, general model to predict viral host range and guide pathogen surveillance and conservation efforts.

ecology↗

bioRxiv2019

Fitness costs of parasites explain multiple life history tradeoffs in a wild mammal

Reproduction in wild animals can divert limited resources away from immune defence, resulting in increased parasite burdens. A longstanding prediction of life history theory states that these parasites can harm the reproductive individual, reducing its subsequent fitness and producing reproduction-fitness tradeoffs. Here, we examined associations among reproductive allocation, immunity, parasitism, and subsequent fitness in a wild population of individually identified red deer (Cervus elaphus). Using path analysis, we investigated whether costs of lactation for downstream survival and fecundity were mediated by changes in strongyle nematode count and mucosal antibody levels. Lactating females exhibited increased parasite counts, which were in turn associated with substantially decreased fitness in the following year in terms of overwinter survival, fecundity, subsequent calf weight, and parturition date. This study offers observational evidence for parasite regulation of multiple life history tradeoffs, supporting the role of parasites as an important mediating factor in wild mammal populations.

ecology↗

bioRxiv2018

The fine-scale landscape of immunity and parasitism in a wild ungulate population

Spatial heterogeneity in parasite susceptibility and exposure is a common source of confounding variation in disease ecology studies. However, it is not known whether spatial autocorrelation acts on immunity in particular at small scales, within wild animal populations, and whether this predicts spatial patterns in infection. Here we used a well-mixed wild population of individually recognised red deer (Cervus elaphus) inhabiting a heterogeneous landscape to investigate fine-scale spatial patterns of immunity and parasitism. We noninvasively collected 842 faecal samples from 141 females with known ranging behaviour over two years. We quantified total and helminth-specific mucosal antibodies and counted propagules of three gastrointestinal helminth taxa. These data were analysed with linear mixed models using the Integrated Nested Laplace Approximation (INLA), using a Stochastic Partial Differentiation Equation approach (SPDE) to control for and quantify spatial autocorrelation. We also investigated whether spatial patterns of immunity and parasitism changed seasonally. We discovered substantial spatial heterogeneity in general and helminth-specific antibody levels and parasitism with two helminth taxa, all of which exhibited contrasting seasonal variation in their spatial patterns. Notably, strongyle nematode intensity did not align with density hotspots, while Fasciola hepatica intensity appeared to be strongly influenced by the presence of wet grazing. In addition, antibody hotspots did not correlate with distributions of any parasites. Our results suggest spatial heterogeneity may be an important factor affecting immunity and parasitism in a wide range of study systems. We discuss these findings with regards to the design of sampling regimes and public health interventions, and suggest that disease ecology studies investigate spatial heterogeneity more regularly to enhance their results, even when examining small geographic areas.

ecology↗