Biology subjects

Blagrove, M. S.

Publications and source records attributed to Blagrove, M. S..

6 recordsLinked to original sources

bioRxiv2025

Mosquito Viromes in England and Wales Reveal Hidden Arbovirus Signals and Limited Ecological Structuring

Outbreaks of mosquito-borne viruses are increasing in temperate regions, with West Nile and Usutu viruses now established in wide regions across Europe, and both detected in the UK. Current surveillance strategies focus on targeted approaches which are well suited for monitoring established threats but limited in their ability to detect recently described or neglected viruses. High throughput sequencing (HTS) provides an unbiased alternative, allowing simultaneous identification of well-recognised and overlooked arboviruses, alongside insect-specific viruses (ISVs) that may modulate vector competence of the insects transmitting these pathogens. This study presents the first comprehensive virome survey of Culex mosquitoes in the UK, analysing populations collected from 93 sites across England and Wales through HTS and a systematic virus discovery pipeline. Across these sites, 41 distinct viral taxa were identified, including 11 novel species. Most viruses were rare or confined to a few sites, with only three detected in more than one third of sites, suggesting the absence of a broad conserved virome across populations. Within this diversity, three arbovirus-related lineages were detected: Hedwig virus (Peribunyaviridae), Umatilla virus (Sedoreoviridae), and Atherstone virus (Peribunyaviridae), the former two representing the first detections in the UK. These putative arboviruses were embedded in viral communities that showed minimal structuring by coarse land type but a modest decline in richness with latitude across rural sites, consistent with diversity gradients observed in other microbial systems. Together, these findings provide the first national-scale baseline of Culex mosquito-associated viral diversity in the UK, and demonstrate the value of metagenomic approaches in arbovirus preparedness.

microbiology↗

bioRxiv2025

Lack of Vector Competence in UK Culex pipiens molestus for Oropouche Virus

Oropouche virus (OROV) is an orthobunyavirus (Peribunyaviridae) that has caused recurrent outbreaks in South America and has recently expanded into the Caribbean, with various biting midge and mosquito species considered vectors. Recent imported cases to Europe and North America have raised concerns about the potential for local transmission in non-endemic areas. To assess this risk in the United Kingdom, we investigated the vector competence of Culex pipiens molestus (Cx. molestus), a human-biting mosquito common in urban environments. Laboratory-reared adult females were fed a bloodmeal containing a Cuban 2024 OROV outbreak strain (240023) and maintained at 27{degrees}C. Of 64 individuals tested at 12-s14 days post-infection via plaque assay, none were positive for OROV in bodies, indicating no evidence of infection and subsequently limited or no vector competence potential. These results provide evidence that UK populations of Cx. molestus are unlikely to support OROV transmission, thereby refining assessments of OROV emergence risk in temperate settings. Further studies are needed to test other putative UK mosquito vectors, as well as Culicoides biting midge species to fully assess the potential for OROV transmission in this region.

microbiology↗

bioRxiv2025

Emergence Risks from Within? Metagenomic Analysis of Mosquito Viromes from Two Zoos Reveals Mosquito-associated Orthobunyaviruses in the UK

In regions naive to mosquito-borne threats, risk assessments often prioritise incursion events, particularly those driven by climate change and host movement. However, these same factors may also facilitate the emergence of viruses already circulating in local vector populations. The use of metagenomics to assess mosquito viromes has expanded in recent decades, enabling the detection of both arboviruses and insect-specific viruses (ISVs), and helping to fill gaps in our understanding of virus circulation. In particular, zoological collections are potential interfaces for virus transmission between mosquitoes, animals, and humans, making them valuable sentinel sites for surveillance. Although mosquito virome studies have been conducted globally, UK mosquito populations remain comparatively understudied. To address this gap, we investigated the viromes of two key mosquito species, Culex pipiens s.l. and Culiseta annulata, through metagenomic sequencing of specimens collected at two UK zoos between 2021 and 2022. A total of 4,042 mosquitoes underwent sequencing across 44 pools, leading to the identification of 26 viral genomes, including nine novel species spanning RNA and DNA virus families. Viral distribution patterns revealed viruses shared across all pools, supporting the possibility of a conserved virome between mosquito species. Notably, two novel Orthobunyavirus species (Family Peribunyaviridae), Atherstone and Deva viruses, were detected. These represent the first documented mosquito-associated orthobunyaviruses in the UK, a genus that includes several known pathogens. Classification using the machine-learning tool MosViR suggests Atherstone virus, present at both zoos, is a putative arbovirus warranting further investigation. Supporting this is the presence of a non-structural protein S (NSs), a known virulence factor in orthobunyaviruses. In contrast, Deva virus had no NSs ORF and was not predicted to be an arbovirus. These findings improve our understanding of UK mosquito viruses, indicate possible risks to people or animals from orthobunyaviruses, and highlight the role of metagenomic surveillance in detecting emerging viral threats.

genomics↗

bioRxiv2024

UK mosquitoes are competent to transmit Usutu virus at native temperatures

Usutu virus (USUV) is an emerging zoonotic virus transmitted primarily by Culex mosquitoes. Since its introduction into Europe from Africa during the late 20th century, it has caused mortality within populations of passerine birds and captive owls, and can on occasion lead to disease in humans. USUV was first detected in the UK in 2020 and has become endemic, having been detected in either birds and/or mosquitoes every subsequent year. Importantly, the vector competence of indigenous mosquitoes for the circulating UK (London) USUV strain at representative regional temperatures is still to be elucidated. This study assessed the vector competence of five field-caught mosquito species/biotypes, Culex pipiens biotype molestus, Culex pipiens biotype pipiens, Culex torrentium, Culiseta annulata and Aedes detritus for the London USUV strain, with infection rates (IR) and transmission rates (TR) evaluated between 7 to 28 days post-infection. Infection and transmission were observed in all species/biotypes aside from Ae. detritus and Cx. torrentium. For Cx. pipiens biotype molestus, transmission potential suggests these populations should be monitored further for their role in transmission to humans. Furthermore, both Cx. pipiens biotype pipiens and Cs. annulata were shown to be competent vectors at 19{degrees}C indicating the potential for geographical spread of the virus to other UK regions.

ecology↗

bioRxiv2023

Features that matter: evolutionary signatures that predict viral transmission routes

Routes of virus transmission between hosts are key to understanding viral epidemiology. Different routes have large effects on viral ecology, and likelihood and rate of transmission. For example, respiratory and vector-borne viruses together encompass the majority of high-consequence animal and plant outbreaks. However, the specific transmission route(s) can take months to years to determine, undermining the efficiency of mitigation efforts. Here, we identify the vial features and evolutionary signatures which are predictive of viral transmission routes, and use them to predict potential routes for fully-sequenced viruses - we perform this for both viruses with no observed routes, as well as viruses with missing routes. This was achieved by compiling a dataset of 24,953 virus-host associations with 81 defined transmission routes, constructing a hierarchy of virus transmission encompassing those routes and 42 higher-order modes, and engineering 446 predictive features from three complementary perspectives. We integrated those data and features, to train 98 independent ensembles of LightGBM classifiers, each incorporating five different class-balancing approaches. Using our trained ensembles, we demonstrated that all features contributed to the prediction for at least one of routes and/or modes of transmission, demonstrating the utility of our multi-perspective approach. Our approach achieved ROC-AUC=0.991, and F1-score=0.855 across all modelled transmission mechanisms; and was able to achieve high levels of predictive performance for high-consequence respiratory (ROC-AUC=0.990, and F1-score=0.864) and vector-borne transmission (ROC-AUC=0.997, and F1-score=0.921). Our framework ranks the viral features in order of their contribution to prediction, per transmission route, and hence identifies the genomic evolutionary signatures associated with each route. Together with the more matured field of viral host-range prediction, our predictive framework could: provide early insights into the potential for, and pattern of viral spread; facilitate rapid response with appropriate measures; and significantly triage the time-consuming investigations to confirm the likely routes of transmission. Moreover, the performance of our approach in high-consequence transmission routes showcases that our methodology has direct utility to pandemic preparedness. AUTHORS SUMMARYRoutes of virus transmission - the mechanism(s) by which a virus physically gets from an infected to an uninfected host, are crucial to understanding how viral diseases spread among animals and plants. Here, we uncover the evolutionary signatures which can predict the transmission routes a virus uses to move from one host to another, enabling us to identify any unobserved routes for known viruses and even predict potential routes of newly emerged viruses. We first compile a comprehensive dataset of virus-host associations. Leveraging this dataset, we employ a multi-perspective machine learning approach to achieve high predictive performance. Our framework ranks viral features by their significance in prediction, revealing genomic evolutionary signatures linked to each route. Our approach could provide early insights into viral spread patterns, facilitating prompt response efforts to new outbreaks and epidemics, and streamline laboratory investigations. Overall, our study represents a step forward in our ability to anticipate and mitigate the impact of emerging infectious diseases on human, animal, and plant health.

ecology↗

bioRxiv2020

Predicting mammalian hosts in which novel coronaviruses can be generated.

Novel pathogenic coronaviruses - including SARS-CoV and SARS-CoV-2 - arise by homologous recombination in a host cell1,2. This process requires a single host to be infected with more than one type of coronavirus, which recombine to form novel strains of virus with unique combinations of genetic material. Identifying possible sources of novel coronaviruses requires identifying hosts (termed recombination hosts) of more than one coronavirus type, in which recombination might occur. However, the majority of coronavirus-host interactions remain unknown, and therefore the vast majority of recombination hosts for coronaviruses cannot be identified. Here we show that there are 11.5-fold more coronavirus-host associations, and over 30-fold more potential SARS-CoV-2 recombination hosts, than have been observed to date. We show there are over 40-fold more host species with four or more different subgenera of coronaviruses. This underestimation of both number and novel coronavirus generation in wild and domesticated animals. Our results list specific high-risk hosts in which our model predicts homologous recombination could occur, our model identifies both wild and domesticated mammals including known important and understudied species. We recommend these species for coronavirus surveillance, as well as enforced separation in livestock markets and agriculture.

bioinformatics↗