BII-Design: Exploring the ecology and evolution of the global virome with big data and machine learning

这项设计活动将产生一项建议，即创建一个生物整合研究所，该研究所将综合野生动物病毒学的最新进展，并寻求对全球病毒体的生态和进化的新见解。SARS-CoV-2大流行的出现只是野生动物产生危险病毒加速趋势的最新发展。全球旅行、城市化和人与野生动物接触的增加都使这些病毒更容易出现。未来，气候变化和土地利用变化将进一步重新组装全球病毒体，迫使哺乳动物跨越大陆，在新的生态系统中相遇，并以数千倍的速度交换病毒，可能会对全球健康造成更多威胁。在这些哺乳动物病毒中，至少有1万种可能感染人类，但全球大多数病毒群仍未被描述：只有约1%的哺乳动物病毒已被发现，在其他脊椎动物中的比例要小得多。由于数据如此之少，很难预测哪些病毒将构成未来的威胁，或者它们可能在哪里、何时以及如何出现。预测下一次大流行威胁将需要跨越生物尺度的新数据，从单基因到深度进化时间，以及来自计算机科学和数学前沿的新统计方法。此外，该项目将为实习生举办夏季实习，并开发将生物学与动手计算机科学实验室相结合的新课程。该项目汇集了一群病毒学家、计算机科学家、统计学家和生态学家，以探索关于方法学、推理和影响的尖端科学问题。该项目有三个目标：(1)合成关于所有脊椎动物分支的宿主-病毒关联的现有数据；(2)开发新的方法来预测宿主-病毒相互作用网络，使用新的数据流，如以基因组为特征的病毒株多样性，或来自免疫学研究的受体数据；以及(3)开发可操作的科学框架，将病毒生态学用于全球健康科学和安全。这些目标将通过协作讲习班实现。在这样做的过程中，它将为发展新兴病毒研究所的全面实施提案奠定基础。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Design activity will result in a proposal to create a Biology Integration Institute that will synthesize recent advances in wildlife virology and pursue new insights about the ecology and evolution of the global virome. The pandemic emergence of SARS-CoV-2 is only the latest development in an accelerating trend of dangerous viruses emerging from wildlife. Global travel, urbanization, and increasing human-wildlife contact have all made it easier for these viruses to emerge. In the future, climate change and land use change will reassemble the global virome even further, forcing mammals to cross continents, meet in new ecosystems, and exchange viruses thousands of times more, potentially unleashing even more threats to global health. At least 10,000 of these mammal viruses might have the potential to infect humans, but most of the global virome is still undescribed: only about 1% of mammal viruses have been discovered, and a much smaller fraction in other vertebrates. With so little data, it is difficult to predict which viruses will pose a future threat, or where, when, and how they could emerge. Predicting the next pandemic threat will require new data spanning biological scales, from single genes up to deep evolutionary time, and new statistical methods from the cutting edge of computer science and mathematics. In addition, the project will host summer residencies for trainees and develope new coursework that combines biology with hands-on computer science labs.The project assembles a group of virologists, computer scientists, statisticians, and ecologists to explore cutting edge scientific questions about methodology, inference, and impact. The project has three aims: (1) synthesizing existing data about host-virus associations for all vertebrate clades; (2) developing novel approaches to predict host-virus interaction networks, using novel data streams like viral strain diversity characterized from genomes, or receptor data from immunological studies; and (3) developing frameworks for actionable science that will put viral ecology to use for global health science and security. These aims will be accomplished through collaborative workshops. In doing so it will establish a foundation for a full Implementation proposal to develop an Emerging Virus Institute.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.