Discovery of the Role of Tick Salivary Glands in Enhancement of Virus Transmission-Beginning of an Exciting Story

The Vector Competence of Asian Longhorned Ticks in Langat Virus Transmission

Haemaphysalis longicornis (the longhorned tick), the predominant tick species in China, serves as a vector for a variety of pathogens, and is capable of transmitting the tick-borne encephalitis virus (TBEV), the causative agent of tick-borne encephalitis. However, it is unclear how these ticks transmit TBEV. Langat virus (LGTV), which has a reduced pathogenicity in humans, has been used as a surrogate for TBEV. In this study, we aimed to investigate the vector competence of H. longicornis to transmit LGTV and demonstrate the efficient acquisition and transmission of LGTV between this tick species and mice. LGTV localization was detected in several tick tissues, such as the midgut, salivary glands, and synganglion, using quantitative PCR and immunohistochemical staining with a polyclonal antibody targeting the LGTV envelope protein. We demonstrated the horizontal transmission of LGTV to different developmental stages within the same generation but did not see evidence of vertical transmission. It was interesting to note that we observed mice acting as a bridge, facilitating the transmission of LGTV to neighboring naïve ticks during blood feeding. In conclusion, the virus-vector-host model employed in this study provides valuable insights into the replication and transmission of LGTV throughout its life cycle.

Characterisation of putative novel tick viruses and zoonotic risk prediction

Tick-associated viruses remain a substantial zoonotic risk worldwide, so knowledge of the diversity of tick viruses has potential health consequences. Despite their importance, large amounts of sequences in public data sets from tick meta-genomic and -transcriptomic projects remain unannotated, sequence data that could contain undocumented viruses. Through data mining and bioinformatic analysis of more than 37,800 public meta-genomic and -transcriptomic data sets, we found 83 unannotated contigs exhibiting high identity with known tick viruses. These putative viral contigs were classified into three RNA viral families (Alphatetraviridae, Orthomyxoviridae and Chuviridae) and one DNA viral family (Asfarviridae). After manual checking of quality and dissimilarity towards other sequences in the data set, these 83 contigs were reduced to five contigs in the Alphatetraviridae from four putative viruses, four in the Orthomyxoviridae from two putative viruses and one in the Chuviridae which clustered with known tick-associated viruses, forming a separate clade within the viral families. We further attempted to assess which previously known tick viruses likely represent zoonotic risks and thus deserve further investigation. We ranked the human infection potential of 133 known tick-associated viruses using a genome composition-based machine learning model. We found five high-risk tick-associated viruses (Langat virus, Lonestar tick chuvirus 1, Grotenhout virus, Taggert virus and Johnston Atoll virus) that have not been known to infect human and two viral families (Nairoviridae and Phenuiviridae) that contain a large proportion of potential zoonotic tick-associated viruses. This adds to the knowledge of tick virus diversity and highlights the importance of surveillance of newly emerging tick-associated diseases.