Spillovers of viruses from animals to humans occur more frequently under warmer conditions, particularly arboviruses. The invasive tick species Haemaphysalis longicornis, the Asian longhorned tick, poses a significant public health threat due to its global expansion and its potential to carry a wide range of pathogens. We analyzed meta-transcriptomic data from 3595 adult H. longicornis ticks collected between 2016 and 2019 in 22 provinces across China encompassing diverse ecological conditions. Generalized additive modeling revealed that climate factors exerted a stronger influence on the virome of H. longicornis than other ecological factors, such as ecotypes, distance to coastline, animal host, tick gender, and antiviral immunity. To understand how climate changes drive the tick virome, we performed a mechanistic investigation using causality inference with emphasis on the significance of this process for public health. Our findings demonstrated that higher temperatures and lower relative humidity/precipitation contribute to variations in animal host diversity, leading to increased diversity of the tick virome, particularly the evenness of vertebrate-associated viruses. These findings may explain the evolution of tick-borne viruses into generalists across multiple hosts, thereby increasing the probability of spillover events involving tick-borne pathogens. Deep learning projections have indicated that the diversity of the H. longicornis virome is expected to increase in 81.9% of regions under the SSP8.5 scenario from 2019 to 2030. Extension of surveillance should be implemented to avert the spread of tick-borne diseases.
Keywords: climate changes; deep learning network; ecological modeling; meta-transcriptomics; tick virome; tick-borne viruses.
© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.