Biology subjects

Woolhouse, M. E. J.

Publications and source records attributed to Woolhouse, M. E. J..

4 recordsLinked to original sources

bioRxiv2022

West Nile Virus spread in Europe - phylogeographic pattern analysis and key drivers

Spread and emergence of West Nile virus (WNV) in Europe have been very different from those observed in North America. Here, we describe key drivers by combining viral genome sequences with epidemiological data and possible factors of spread into phylodynamic models. WNV in Europe has greater lineage diversity than other regions of the world, suggesting repeated introductions and local amplification. Among the six lineages found in Europe, WNV-2a is predominant, has spread to at least 14 countries and evolved into two major co-circulating clusters (A and B). Both of these seem to originate from regions of Central Europe. Viruses of Cluster A emerged earlier and have spread towards the west of Europe with higher genetic diversity. Amongst multiple drivers, high agriculture activities were associated with both spread direction and velocity. Our study suggests future surveillance activities should be strengthened in Central Europe and Southeast European countries, and enhanced monitoring should be targeted to areas with high agriculture activities.

evolutionary biology↗

bioRxiv2021

Secreted SARS-CoV-2 ORF8 modulates the cytokine expression profile of human macrophages

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still adapting to its new human host. Attention has focussed on the viral spike protein, but substantial variation has been seen in the ORF8 gene. Here, we show that SARS-CoV-2 ORF8 protein undergoes signal peptide-mediated processing through the endoplasmic reticulum and is secreted as a glycosylated, disulphide-linked dimer. The secreted protein from the prototype SARS-CoV-2 virus had no major effect on viability of a variety of cell types, or on IFN or NF-{kappa}B signalling. However, it modulated cytokine expression from primary CSF1-derived human macrophages, most notably by decreasing IL-6 and IL-8 secretion. Furthermore, a sequence polymorphism L84S that appeared early in the pandemic associated with the Clade S lineage of virus, showed a markedly different effect, of increasing IL-6 production. We conclude that ORF8 sequence polymorphisms can potentially affect SARS-CoV-2 virulence and should therefore be monitored in sequencing-based surveillance.

microbiology↗

bioRxiv2019

Evolutionary origins of epidemic potential among human RNA viruses

To have epidemic potential, a pathogen must be able to spread in human populations, but of human-infective RNA viruses only a minority can do so. We investigated the evolution of human transmissibility through parallel analyses of 1755 virus genome sequences from 39 RNA virus genera. We identified 57 lineages containing human-transmissible species and estimated that at least 74% of these lineages have evolved directly from non-human viruses in other mammals or birds, a public health threat recently designated \"Disease X\". Human-transmissible viruses rarely evolve from virus lineages that can infect but not transmit between humans. This result cautions against focussing surveillance and mitigation efforts narrowly on currently known human-infective virus lineages and supports calls for a better understanding of RNA virus diversity in non-human hosts.

evolutionary biology↗

bioRxiv2019

Tissue Tropism and Transmission Ecology Predict Virulence of Human RNA Viruses

Novel infectious diseases continue to emerge within human populations. Predictive studies have begun to identify pathogen traits associated with emergence. However, emerging pathogens vary widely in virulence, a key determinant of their ultimate risk to public health. Here, we use structured literature searches to review the virulence of each of the 214 known human-infective RNA virus species. We then use a machine learning framework to determine whether viral virulence can be predicted by ecological traits including human-to-human transmissibility, transmission routes, tissue tropisms and host range. Using severity of clinical disease as a measurement of virulence, we identified potential risk factors using predictive classification tree and random forest ensemble models. The random forest model predicted literature-assigned disease severity of test data with 90.3% accuracy, compared to a null accuracy of 74.2%. In addition to viral taxonomy, the ability to cause systemic infection, having renal and/or neural tropism, direct contact or respiratory transmission, and limited (0 < R0 [≤] 1) human-to-human transmissibility were the strongest predictors of severe disease. We present a novel, comparative perspective on the virulence of all currently known human RNA virus species. The risk factors identified may provide novel perspectives in understanding the evolution of virulence and elucidating molecular virulence mechanisms. These risk factors could also improve planning and preparedness in public health strategies as part of a predictive framework for novel human infections.\n\nAuthor SummaryNewly emerging infectious diseases present potentially serious threats to global health. Although studies have begun to identify pathogen traits associated with the emergence of new human diseases, these do not address why emerging infections vary in the severity of disease they cause, often termed virulence. We test whether ecological traits of human viruses can act as predictors of virulence, as suggested by theoretical studies. We conduct the first systematic review of virulence across all currently known human RNA virus species. We adopt a machine learning approach by constructing a random forest, a model that aims to optimally predict an outcome using a specific structure of predictors. Predictions matched literature-assigned ratings for 28 of 31 test set viruses. Our predictive model suggests that higher virulence is associated with infection of multiple organ systems, nervous systems or the renal systems. Higher virulence was also associated with contact-based or airborne transmission, and limited capability to transmit between humans. These risk factors may provide novel starting points for questioning why virulence should evolve and identifying causative mechanisms of virulence. In addition, our work could suggest priority targets for infectious disease surveillance and future public health risk strategies.\n\nBlurbComparative analysis using machine learning shows specificity of tissue tropism and transmission biology can act as predictive risk factors for virulence of human RNA viruses.

epidemiology↗