Dermacentor silvarum is an obligate blood sucking arthropod and transmits various pathogens to humans and domestic animals. Recently several new viruses were detected in D. silvarum as an emerging disease threat. In this study, we aimed to analyze its geographical distribution and associated pathogens. Data were collected from multiple sources, including a field survey, reference book, and literature review. We searched various electronic databases with the terms “Dermacentor silvarum” OR “D. silvarum” for studies published since 1963 and the positive rates for Dermacentor silvarum-associated pathogens were estimated by meta-analysis. D. silvarum was found only in four countries in Eurasia, ranging from 22° N to 57° N latitude. At least 20 human pathogens were associated with D. silvarum, including five species of spotted fever group rickettsiae, three species in the family of Anaplasmataceae, three genospecies in the complex Borrelia burgdorferi sensu lato, Francisella tularensis, Babesia venatorum, Coxiella buenetii, Borrelia miyamotoi, and five species of virus. Among them, Rickettsia raoultii was widely detected in D. silvarum, showing the highest pooled positive rate (25.15%; 95% CI 13.31–39.27). Our work presents the most comprehensive data and analysis (to our knowledge) for the geographical distribution of D. silvarum and associated pathogens, revealing an emerging threat to public health and stocking farming. Continued surveillance and further investigations should be enhanced.

Dermacentor nuttalli, a member of family Ixodidae and genus Dermacentor, is predominantly found in North Asia. It transmits various pathogens of human and animal diseases, such as Lymphocytic choriomeningitis mammarenavirus and Brucella ovis, leading to severe symptoms in patients and posing serious hazards to livestock husbandry. To profile pathogen abundances of wild D. nuttalli, metagenomic sequencing was performed of four field-collected tick samples, revealing that Rickettsia, Streptomyces, and Pseudomonas were the most abundant bacterial genera in D. nuttalli. Specifically, four nearly complete Rickettsia genomes were assembled, closely relative to Rickettsia conorii subsp. raoultii. Then, a comprehensive meta-analysis was performed to evaluate its potential threats based on detected pathogens and geographical distribution positions reported in literature, reference books, related websites, and field surveys. At least 48 pathogens were identified, including 20 species of bacteria, seven species of eukaryota, and 21 species of virus. Notably, Rickettsia conorii subsp. raoultii, Coxiella burnetii, and Brucella ovis displayed remarkably high positivity rates, which were known to cause infectious diseases in both humans and livestock. Currently, the primary distribution of D. nuttalli spans China, Mongolia, and Russia. However, an additional 14 countries in Asia and America that may also be affected by D. nuttalli were identified in our niche model, despite no previous reports of its presence in these areas. This study provides comprehensive data and analysis on the pathogens carried by D. nuttalli, along with documented and potential distribution, suggesting an emerging threat to public health and animal husbandry. Therefore, there is a need for heightened surveillance and thorough investigation of D. nuttalli.

Soft ticks (Ixodida: Argasidae) are ectoparasites of terrestrial vertebrates with worldwide distributions. As one representative group of Argasidae, the genus Argas has an important vectorial role in transmitting zoonotic diseases. However, our knowledge of the subgenus Argas in China is still limited, as most literature only lists occurrence records or describes specific case reports without providing detailed morphological characteristics and further molecular data. This study aims to characterize Argas vulgaris through complete mitochondrial sequencing and morphological diagnostic techniques based on a batch of adult specimens collected from Ningxia Hui Autonomous Regions (NXHAR), North China. The morphology and microstructures of Ar. vulgaris and other lectotypes of argasid ticks in the subgenus Argas were also observed using a stereomicroscope. Following DNA extraction and sequencing, a complete mitochondrial sequence of Ar. vulgaris was assembled and analyzed within a phylogenetic context. The 14,479 bp mitogenome of Ar. vulgaris consists of 37 genes, including 13 genes for protein coding, two for ribosomal RNA, 22 for transfer RNA, and one for control region (D-loops). Phylogenetic analysis of Ar. vulgaris showed 98.27%-100% nucleotide identity with Ar. japonicus, indicating a close relationship between the two tick species. The morphological diagnostic features to differentiate Ar. vulgaris from other ticks within the subgenus Argas included the location of the anus and setae on the anterior lip of the female genital aperture. This study provided high-resolution scanning electron microscope images of female Ar. vulgaris and corresponding molecular data, representing valuable resources for future accurate species identification.

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.