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Pascall, D. J.

Publications and source records attributed to Pascall, D. J..

5 recordsLinked to original sources

Evaluation of the zoonotic potential of tick-borne viruses in public datasets

Tick-borne 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 datasets from tick meta-genomic and -transcriptomic projects remain unannotated, sequence data that could contain undocumented viruses. Through data mining and bioinformatic analyses of more than 37,800 public meta-genomic and -transcriptomic datasets, 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, Chuviridae) and one DNA viral family (Asfaviridae). After manual checking of quality and dissimilarity toward other sequences in the dataset, these 83 contigs were reduced to five putative novel Alphatetra-like viral contigs, four putative novel Orthomyxo-like viral contigs, and one Chu-like viral contig which clustered with known tick-borne 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 136 known tick-borne viruses using a genome composition-based machine learning model. We found five high-risk tick-borne 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-borne viruses. This adds to the knowledge of tick virus diversity and highlights the importance of surveillance of newly emerging tick-borne diseases. ImportanceTicks are important hosts of pathogens. Despite this, numerous tick-borne viruses are still unknown or poorly characterised. To overcome this, we re-examined currently known tick-borne viruses and identified putative novel viruses associated with ticks in public datasets. Using genome-based machine learning approach, we predicted five high-risk tick-borne viruses that have not yet been reported to cause human infections. Additionally, we highlighted two viral families, Nairoviridae and Phenuiviridae, which are potential public health threats. Our analysis also revealed 10 putative novel RNA viral contigs clustered with known tick-borne viruses. Our study highlights the importance of monitoring ticks and the viruses they carry in endemic areas to prevent and control zoonotic infectious disease outbreaks. To achieve this, we advocate for a multidisciplinary approach within a One Health and EcoHealth framework that considers the relationship between zoonotic disease outbreaks and their hosts, humans, and the environment.

microbiology↗

Predictors of virus prevalence and diversity across a wild bumblebee community

Viruses are key regulators of natural populations. Despite this, we have limited knowledge of the diversity and ecology of viruses that lack obvious fitness effects on their host. This is even the case in wild host populations that provide ecosystem services, where small fitness effects may have major ecological and financial impacts in aggregate. One such group of hosts are the bumblebees, which have a major role in the pollination of food crops and have suffered population declines and range contractions in recent decades. In this study, we used a multivariate generalised linear mixed model to investigate the ecological factors that determine the prevalence of four recently discovered bumblebee viruses (Mayfield virus 1, Mayfield virus 2, River Liunaeg virus and Loch Morlich virus), and two previously known viruses that infect both wild bumblebees and managed honeybees (Acute bee paralysis virus and Slow bee paralysis virus). We show that the recently discovered bumblebee viruses were more genetically diverse than the viruses shared with honeybees, potentially due to spillover dynamics of shared viruses. We found evidence for ecological drivers of prevalence in our samples, with relatively weak evidence for a positive effect of precipitation on the prevalence of River Luinaeg virus. Coinfection is potentially important in shaping prevalence: we found a strong positive association between River Liunaeg virus and Loch Morlich virus presence after controlling for host species, location and other relevant ecological variables. This study represents a first step in the description of predictors of bumblebee infection in the wild not driven by spillover from honeybees.

microbiology↗

The circulating SARS-CoV-2 spike variant N439K maintains fitness while evading antibody-mediated immunity

SARS-CoV-2 can mutate to evade immunity, with consequences for the efficacy of emerging vaccines and antibody therapeutics. Herein we demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is the most divergent region of S, and provide epidemiological, clinical, and molecular characterization of a prevalent RBM variant, N439K. We demonstrate that N439K S protein has enhanced binding affinity to the hACE2 receptor, and that N439K virus has similar clinical outcomes and in vitro replication fitness as compared to wild- type. We observed that the N439K mutation resulted in immune escape from a panel of neutralizing monoclonal antibodies, including one in clinical trials, as well as from polyclonal sera from a sizeable fraction of persons recovered from infection. Immune evasion mutations that maintain virulence and fitness such as N439K can emerge within SARS-CoV-2 S, highlighting the need for ongoing molecular surveillance to guide development and usage of vaccines and therapeutics.

microbiology↗

Evolutionary stasis of an RNA virus indicates arbovirus re-emergence triggered by accidental release

The mechanisms underlying virus emergence are rarely well understood, making the appearance of outbreaks largely unpredictable. Bluetongue virus serotype 8 (BTV-8), an insect-borne virus of ruminants, emerged in livestock in Northern Europe in 2006, spreading to most European countries by 2009 and causing losses of billions of Euros. Though the outbreak was successfully controlled through vaccination by early 2010, puzzlingly a closely-related BTV-8 strain re-emerged in France in 2015, triggering a second outbreak that is still ongoing. The origin of this virus and the mechanisms underlying its re-emergence are unknown. Here, we performed phylogenetic analyses of 164 whole BTV-8 genomes sampled throughout the two outbreaks. We demonstrate consistent clock-like virus evolution during both epizootics but found negligible evolutionary change between them. We estimate that the ancestor of the second outbreak dates from the height of the first outbreak in 2008. This implies that the virus had not been replicating for multiple years prior to its re-emergence in 2015. Given the absence of any known natural mechanism that could explain BTV-8 persistence over this period without replication, we conclude that the second outbreak was most likely initiated by accidental exposure of livestock to frozen material contaminated with virus from approximately 2008. Our work highlights new targets for pathogen surveillance programmes in livestock and illustrates the power of genomic epidemiology to identify pathways of infectious disease emergence.

evolutionary biology↗

Host evolutionary history predicts virus prevalence across bumblebee species

Why a pathogen associates with one host but not another is one of the most important questions in disease ecology. Here we use transcriptome sequencing of wild-caught bumblebees from 13 species to describe their natural viruses, and to quantify the impact of evolutionary history on the realised associations between viruses and their pollinator hosts. We present 37 novel virus sequences representing at least 30 different viruses associated with bumblebees. We verified 17 of them by PCR and estimate their prevalence across species in the wild. Through small RNA sequencing, we demonstrate that at least 10 of these viruses form active infections in wild individuals. Using a phylogenetic mixed model approach, we show that the evolutionary history of the host shapes the current distribution of virus/bumblebee associations. Specifically, we find that related hosts share viral assemblages, viruses differ in their prevalence averaged across hosts and the prevalence of infection in individual virus-host pairings depends on precise characteristics of that pairing. Authors SummaryDespite the importance of disease in the regulation of animal populations, our understanding of the distribution of pathogen burden across wild communities remains in its infancy. In this study, we investigated the distribution of viruses across natural populations of 13 different bumblebee species in Scotland. We first searched for viruses using a metatranscriptomic approach, finding at least 30 new viruses of bumblebees, and assayed a subset of them for their presence and absence in different host species. Then, in the first application of these methods to an animal-virus system, we used co-phylogenetic mixed models to investigate the factors that lead to species being having different prevalences for a subset of these viruses. While much of the variation in the prevalence of the viruses can be explained by the idiosyncrasies of individual bumblebee-virus pairings, there is a phylogenetic signal with related bumblebee species being infected at similar frequencies by the same sets of viruses. Consistent with previous work, our study indicates that, while in general the interaction between a host and a virus may be unpredictable, closely related species are more likely to exhibit similar patterns of infection.

evolutionary biology↗