The influence of bat ecology on viral diversity and reservoir status

Bats host a diversity of viruses, some zoonotic. Repeated emergence of diseases that jump into humans from bat reservoirs highlights a need for predictive approaches to pre-emptively identify virus-carrying species. We use a machine learning approach to examine drivers of viral diversity in bats, and differences in those drivers between RNA and DNA viruses. We find bat species with longer lifespans, broad geographic distributions in the eastern hemisphere, and large group sizes carry more viruses. Lifespan was a stronger predictor of DNA viral diversity, while group size and family were more important for RNA viruses, patterns that may reflect broad differences in infection duration. Finally, we identify 55 bat species not currently considered reservoirs that are most likely to carry viruses. Mapping these predictions highlights global regions that could be targeted for disease surveillance, including those with few bat species but a large proportion of predicted carriers.蝙蝠携带着多样的病毒，其中部分为人畜共患病病毒。从蝙蝠病毒储存宿主跨物种传播至人类的疾病反复暴发，凸显了开发预测方法以提前识别携毒蝙蝠物种的迫切需求。本研究采用机器学习方法，探究蝙蝠病毒多样性的驱动因素，并对比RNA病毒与DNA病毒的驱动因素差异。研究发现，寿命更长、在东半球拥有更广地理分布、种群规模更大的蝙蝠物种携带的病毒数量更多。寿命是DNA病毒多样性的更强预测因子，而种群规模与蝙蝠分类科则对RNA病毒的影响更为显著，这一模式或可反映两类病毒感染持续时长的广泛差异。最后，本研究鉴定出55种目前未被视为病毒储存宿主的蝙蝠物种，它们极有可能携带病毒。对这些预测结果进行可视化制图后，可明确全球范围内需要优先开展疾病监测的区域，其中包括蝙蝠物种数量较少但预测携毒物种占比偏高的地区。