Search

In the Anthropocene, in which we now live, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial 'unseen majority'. We must learn not just how microorganisms affect climate change (including production and consumption of greenhouse gases) but also how they will be affected by climate change and other human activities. This Consensus Statement documents the central role and global importance of microorganisms in climate change biology. It also puts humanity on notice that the impact of climate change will depend heavily on responses of microorganisms, which are essential for achieving an environmentally sustainable future.

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 rapid outbreaks and high-consequence animal and plant epidemics. However, determining the specific transmission route(s) can take months to years, delaying 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 in silico and rapidly, 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. We found that all features contributed to the prediction for at least one of the routes and/or modes of transmission, demonstrating the utility of our broad multi-perspective approach. Our framework achieved ROC-AUC = 0.991, and F1-score = 0.855 across all included transmission routes and modes, 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. Author summary: Routes 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. Using 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. [ABSTRACT FROM AUTHOR]

The emergence of Japanese encephalitis virus (JEV) in the Himalayan highlands is of significant veterinary and public health concern and may be related to climate warming and anthropogenic landscape change, or simply improved surveillance. To investigate this phenomenon, a One Health approach focusing on the phylogeography of JEV, the distribution and abundance of the mosquito vectors, and seroprevalence in humans and animal reservoirs would be useful to understand the epidemiology of Japanese encephalitis in highland areas.

The only tickborne flavivirus in the United Kingdom documented to cause disease in vertebrates is louping ill virus (LIV), a virus transmitted by the deer/sheep tick, Ixodes ricinus (1). This [...]

Background: Usutu virus (USUV), which is closely related to West Nile virus (WNV), sharing a similar ecology and transmission cycle, was first reported in the UK in the southeast of England in 2020. Both USUV and WNV are emerging zoonotic viruses hosted by wild birds. The 2020 finding of USUV in England raised awareness of this virus and highlighted the importance of understanding the seasonality of Culexpipiens sensu lato (Cx. pipiens s.l.), the main enzootic vector of these viruses. Zoos are prime locations for trapping mosquitoes because of their infrastructure, security, and range of vertebrate hosts and aquatic habitats. Methods: Three independent zoo-based case studies at four locations that cover the seasonality of Cx.pipiens s.l. in England were undertaken: (i) London Zoo (Zoological Society London [ZSL]) and surrounding areas, London; (ii) Chester Zoo (Cheshire); (ii) Twycross Zoo (Leicestershire); and (iv) Flamingo Land (zoo; North Yorkshire). Various adult mosquito traps were used to catch adult Cx.pipiens s.l. across seasons. Results: High yields of Cx.pipiens s.l./Culex torrentium were observed in Biogents-Mosquitaire and Center for Disease Control and Prevention Gravid traps in all studies where these traps were used. Mosquito counts varied between sites and between years. Observations of adult Cx.pipiens s.l./Cx. torrentium abundance and modelling studies demonstrated peak adult abundance between late July and early August, with active adult female Cx.pipiens s.l./Cx. torrentium populations between May and September. Conclusions: The information collated in this study illustrates the value of multiple mosquito monitoring approaches in zoos to describe the seasonality of this UK vector across multiple sites in England and provides a framework that can be used for ongoing and future surveillance programmes and disease risk management strategies. [ABSTRACT FROM AUTHOR]