Emerging tick-borne infections pose growing public health threats, causing global disease burdens and economic losses. In this study, tick-borne pathogens were detected in ticks collected from ruminants in 19 sites of Khyber Pakhtunkhwa Province, Pakistan, between 2023 and 2024. A total of 989 ticks, belonging to five species, i.e., Hyalomma marginatum, Rhipicephalus microplus, Rhipicephalus sanguineus, Rhipicephalus haemaphysaloides, and Haemaphysalis bispinosa, were tested by specific PCR followed by Sanger sequencing. In total, fourteen pathogens including two Anaplasma species, three Ehrlichia species, three Rickettsia species, one Babesia species, and five Theileria species were identified, with an overall infection rate of 20.2% (95% CI: 17.7–22.7%). Phylogenetic analyses revealed two undefined Ehrlichia species: Candidatus Ehrlichia hyalommae was exclusively detected in Hy. marginatum ticks, while Candidatus Ehrlichia rhipicephalis was only found in R. microplus. Additionally, an undefined Rickettsia, provisionally named Candidatus Rickettsia pakistanensis, was identified, which is phylogenetically close to R. sibirica in North Asia and R. africae in Africa, suggesting its potential pathogenicity to humans. Although coinfections of two pathogens were observed, the coinfection rates were quite low. The findings revealed a significant diversity of tick-borne pathogens in Pakistani ticks, which may pose risks to livestock and humans.

RNA viruses exhibit high mutation rates and strong host adaptive capacity, posing major public health challenges. Although meta-transcriptomic studies have uncovered vast numbers of novel RNA viral sequences, identifying those with spillover risks remains difficult. Current virus host-prediction methods can only predict a narrow set of host labels at coarse taxonomic levels (e.g., kingdom or order), which hampers precise evaluation of cross-species transmission risk and may overlook potential zoonotic hosts. To overcome these limitations, we developed UniVH, a unified virus–host association prediction framework trained on an exceptionally broad spectrum of 90 viral families and 240 host families, enabling robust prediction even for phylogenetically distant or data-scarce hosts. UniVH achieved a host prediction accuracy of 71.2% for novel viruses discovered after 2020, representing a 15.3% improvement over conventional BLASTp-based homology approaches. Feature interpretation revealed that viral structural genes and host immune- and metabolism-related genes contributed most significantly to predictive performance. Model predictions indicated widespread host-range expansion, with 20 mammalian virus families doubling their documented mammalian host ranges and several showing marked increases in viruses with human-infection potential. This unified, interpretable framework represents an important methodological advance for future RNA virus spillover-risk evaluation and emerging virus prioritization.

Ticks, which are globally distributed, transmit a wide range of human and animal pathogens. Soft and hard ticks are two major tick families exhibiting distinct vector capacities and blood-feeding abilities. However, understanding the genetic basis of these differences is hindered by the scarcity of high-quality tick genomes, particularly for soft ticks. Here, we present high-quality genomes of two soft and two hard tick species of both evolutionary and medical importance, and compare the genomic characteristics of the two tick families. Compared with soft ticks, hard ticks exhibited faster genome evolution, characterized by larger genome sizes, higher rates of gene gain and loss, and a greater number of positively selected genes. Both tick families exhibited frequent positive selection across metabolism and organismal systems, sharing a core set of adaptive genes but undergoing refinement at different sites. Gene families underpinning various vector capacities, including those involved in cuticle structure, heme biosynthesis, egg waxing, and immune pathways, were identified. Additionally, we assembled the genomes of two novel Rickettsia endosymbionts from soft ticks, revealing high genomic divergence and lineage-specific adaptations to their hosts. These genomic resources provide fundamental insights into the genetic basis of tick biology and vector capacity, highlighting the divergent evolutionary strategies of blood-feeding arthropods shaped by their ecological niches.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is a severe tick-borne viral disease characterized by dysregulated host immune responses. Although previous studies have suggested sex-related differences in immune responses in SFTS, the sex-specific magnitude of cytokine changes and their relationships with viral load and laboratory parameters have not been fully characterized. Methods: We investigated sex differences in cytokine profiles and their associations with viral load and disease severity in 100 confirmed SFTS patients and 60 healthy controls. Nineteen cytokines, viral load, and clinical and laboratory parameters were assessed in acute-phase sera. Correlation analyses were performed to assess the relationships of cytokine changes with viral load and clinical parameters. Multivariable regression analyses were used to evaluate the association between sex and cytokine changes after adjustment for potential confounders, and sex-stratified ROC analyses were conducted to assess the ability of cytokines to discriminate disease severity. Results: Cytokine levels were generally higher in SFTS patients than in controls and increased with disease severity. After normalization to sex-matched controls, females showed higher normalized cytokine ratios for CCL4, IL-17, IL-8, and FGF2, whereas males showed higher normalized ratios for IL-5 and PDGF-AB. Cytokine changes were associated with viral load in both sexes, but these associations did not differ significantly between males and females. After adjustment for potential confounders, FGF2 and IL-17 showed higher normalized cytokine ratios in females, whereas IL-5 and CXCL10 showed higher normalized ratios in males. Exploratory sex-stratified ROC analyses identified several cytokines with relatively high AUCs for discriminating concurrent mild and severe disease, including CXCL10 and CCL4. Conclusions: These findings provide preliminary indications of sex-related differences in cytokine responses during acute SFTS and suggest that the magnitude of cytokine changes may help better characterize sex-specific cytokine responses and their associations with disease severity.