Where coronaviruses hide, where novel strains are generated, and how they get to us: Predicting reservoirs, recombination, and geographical hotspots

冠状病毒隐藏在哪里，新毒株在哪里产生，以及它们如何到达我们身边：预测储存库、重组和地理热点

• 批准号: NE/W002302/1
• 负责人: Marcus Blagrove
• 金额: $ 10.1万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FW002302%2F1
• 关键词: Where; coronaviruses; hide; where; novel

Novel pathogenic coronaviruses, including SARS-CoV and SARS-CoV-2, arise by genetic recombining of two different coronavirus strains co-infecting an animal host. These viruses circulate in reservoir animal populations before spillover to humans.Understanding, monitoring, and mitigating both recombination and spillover requires identifying hosts that are susceptible to each coronavirus and hosts susceptible to multiple coronavirus strains (termed recombination hosts).However, the majority of coronavirus-host associations, and therefore reservoirs and recombination hosts, remain unidentified. This has led to an underappreciation of the potential scale of novel coronavirus generation and spillover.Here, we aim to predict all host species which act as SARS-CoV-2 reservoirs and recombination hosts (WP1), by expanding our tried-and-tested machine-learning framework to include avian hosts. This will enable monitoring of SARS-CoV-2 reservoirs during the pandemic, and hosts in which SARS-CoV-2 could recombine to generate novel pathogenic viruses.Geographical overlap of host species is a key predictor of between-species viral sharing. By constructing a species-level ecological contact network and integrating it with our framework we will further refine our predictions. This will enable us to identify geographical hotspots of coronaviruses recombination (WP2), and therefore enable specific spatially-targeted surveillance and mitigation efforts.Many coronavirus hosts interact with humans, either naturally by e.g. geographic/habitat overlap, or are used by humans as e.g. pets/food. Using geographical data from WP2 and host species utilisation data from open-access sources, we will (WP3) estimate the in situ likelihood of spillover from hosts identified in WP1. This will inform policy makers of species and hotspots for spillover mitigation efforts.

新的致病性冠状病毒，包括SARS-CoV和SARS-CoV-2，是由两种不同的冠状病毒株共同感染动物宿主的基因重组产生的。这些病毒在传播给人类之前在宿主动物群体中传播。了解、监测和减轻重组和传播需要识别对每种冠状病毒易感的宿主和对多种冠状病毒株易感的宿主（称为重组宿主）。然而，大多数冠状病毒-宿主关系，因此宿主和重组宿主仍然是未知的。这导致了对新型冠状病毒产生和溢出的潜在规模的低估。在这里，我们的目标是预测所有作为SARS-CoV-2宿主和重组宿主（WP 1）的宿主物种，通过扩展我们久经考验的机器学习框架，包括鸟类宿主。这将使监测SARS-CoV-2在大流行期间的宿主，以及SARS-CoV-2可能重组产生新的致病病毒的宿主成为可能。宿主物种的地理重叠是物种间病毒共享的一个关键预测因素。通过构建一个物种级的生态接触网络，并将其与我们的框架相结合，我们将进一步完善我们的预测。这将使我们能够确定冠状病毒重组（WP 2）的地理热点，从而实现特定的空间目标监测和缓解工作。许多冠状病毒宿主与人类相互作用，例如通过地理/栖息地重叠自然发生，或被人类用作宠物/食物。利用WP 2的地理数据和开放获取来源的宿主物种利用数据，我们将（WP 3）估计WP 1中确定的宿主的原位溢出可能性。这将为政策制定者提供物种和热点的信息，以减轻溢出效应。

项目成果

Identifying life-history patterns along the fast-slow continuum of mammalian viral carriers

识别哺乳动物病毒携带者快慢连续体的生活史模式

• DOI: 10.21203/rs.3.rs-2722217/v1
• 发表时间: 2023
• 作者: Tonelli A

Monkeypox virus shows potential to infect a diverse range of native animal species across Europe, indicating high risk of becoming endemic in the region

猴痘病毒有可能感染欧洲各地的多种本土动物物种，表明该地区流行的风险很高

• DOI: 10.1101/2022.08.13.503846
• 发表时间: 2022
• 作者: Blagrove M

Features that matter: evolutionary signatures that predict viral transmission routes

重要的特征：预测病毒传播途径的进化特征

• DOI: 10.1101/2023.11.22.568327
• 发表时间: 2023
• 作者: Wardeh M

Predicting mammalian hosts in which novel coronaviruses can be generated.

• DOI: 10.1038/s41467-021-21034-5
• 发表时间: 2021-02-16
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Wardeh M;Baylis M;Blagrove MSC
• 通讯作者: Blagrove MSC

Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations.

• DOI: 10.1038/s41467-021-24085-w
• 发表时间: 2021-06-25
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Wardeh M;Blagrove MSC;Sharkey KJ;Baylis M
• 通讯作者: Baylis M