Severe fever with thrombocytopenia syndrome (SFTS), caused by SFTS virus (SFTSV), is an emerging tick-borne disease in East Asia. SFTS monitoring has been carried out since 2010 in mainland China, but no confirmed human cases or infected vectors had been reported from the northern regions of Hebei Province. We intensified surveillance in this area by collecting serum samples from patients with fever of unknown origin (FUO) and ticks from local habitats. Subsequently, all collected samples were screened for SFTSV by qRT-PCR. SFTSV RNA was detected in two patient sera from Chengde (2.2%). In six, positive ticks were detected among the Haemaphysalis verticalis (8.6%) collected from Zhangjiakou; no positive ticks were detected among the ticks collected from Chengde. Complete viral genomes were recovered from positive tick samples via next-generation sequencing and subjected to a suite of bioinformatic analyses. Two complete genomes from Haemaphysalis verticalis formed a distinct clade with an Inner Mongolia strain across L/M/S (bootstrap = 1.0) and separate from genotypes A–F; pairwise p-distances to genotypes A–F were >0.11 across L/M/S, supporting designation of a distinct genotype. We designate this lineage as genotype G; no credible recombination was detected. Based on the L segment, molecular-clock analyses dated the genotype G lineage to the late 13th century, predating the crown age of genotypes A–F (~18th century) by more than 400 years. We provide the first evidence of SFTSV circulation in northern Hebei and identify a novel, deeply divergent lineage. This finding confirms the co-circulation of distinct viral lineages (G and F) within the province and provides critical new insights into the virus’s diversity and evolutionary history. These results expand the known range and genetic diversity of SFTSV, underscoring the need for enhanced surveillance and ecological investigation in emerging regions. It is necessary to strengthen public health education, improve the early diagnosis and treatment ability of medical workers, and provide a scientific basis for targeted public health interventions.

In recent years, there have been significant advancements in the research of Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV). However, several limitations and challenges still exist. For instance, researchers face constraints regarding experimental conditions and the feasibility of sample acquisition for studying SFTSV. To enhance the quality and comprehensiveness of SFTSV research, we opted to employ PMA-induced THP-1 cells as a model for SFTSV infection. Multiple time points of SFTSV infection were designed to capture the dynamic nature of the virus–host interaction. Through a comprehensive analysis utilizing various bioinformatics approaches, including diverse clustering methods, MUfzz analysis, and LASSO/Cox machine learning, we performed dynamic analysis and identified key genes associated with SFTSV infection at the host cell transcriptomic level. Notably, successful clustering was achieved for samples infected at different time points, leading to the identification of two important genes, PHGDH and NLRP12. And these findings may provide valuable insights into the pathogenesis of SFTSV and contribute to our understanding of host–virus interactions.

Ticks serve as primary vectors for a wide array of RNA viruses, yet the diversity and distribution of tick-associated RNA viruses remain incompletely characterized in Hebei province. To address this gap, we conducted a systematic metatranscriptomic investigation of 986 ticks representing six species, collected from the diverse ecological landscapes of Hebei Province in northern China. Our analysis recovered 25 complete or near-complete viral genomes spanning 12 families, including Phenuiviridae, Flaviviridae, and Nairoviridae. Of critical public health significance, we identified Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) in both Haemaphysalis longicornis and Dermacentor nuttalli. Phylogenetic reconstruction revealed marked geographic stratification where strains from the coastal plains clustered with the dominant Genotype F, while those from the mountainous north formed a characteristic and divergent lineage phylogenetically linked to isolates from Inner Mongolia. Furthermore, a novel viral agent provisionally named Zhangjiakou Hepacivirus was discovered in Haemaphysalis japonica. This virus shared less than 80% nucleotide identity with the rodent-associated Hepacivirus P, consistent with a rodent origin and possible cross-species transmission. Collectively, these findings reveal descriptive variation associated with vector identity, physiological status, and ecological context in shaping viral evolution and underscore the need for continuous metagenomic surveillance to mitigate emerging tick-borne disease risks within a One Health framework.

SNX11, a sorting nexin protein localized on the endosomal membrane, is an important protein closely related to protein sorting and endosomal trafficking. Previously, through a genome-wide CRISPR screening, we identified SNX11 as a critical protein for the entry of Dabie bandavirus. SNX11 deletion significantly inhibits the replication of Dabie bandavirus. We further discovered that the loss of SNX11 alters endosomal pH, potentially affecting the release process of Dabie bandavirus from endosomes to the cytoplasm. However, the mechanism by which SNX11 modulates endosomal pH and whether SNX11 deletion similarly inhibits other viruses remain to be elucidated. This study reveals that SNX11 can interact with the V1 subunit of the endosomal proton pump V-ATPase, affecting the expression level of this subunit on the endosomal membrane and thereby disrupting the assembly of V-ATPase. Additionally, we found that SNX11 deletion significantly inhibits the replication of dengue virus, hantavirus, and influenza virus. These findings suggest that SNX11 may be a key protein in the process of viral infection and could serve as a broad-spectrum antiviral target.

Severe Fever with thrombocytopenia syndrome (SFTS) is a highly fatal viral infectious disease that poses a significant threat to public health. Currently, the phase and pathogenesis of SFTS are not well understood, and there are no specific vaccines or effective treatment available. Therefore, it is crucial to identify biomarkers for diagnosing acute SFTS, which has a high mortality rate. In this study, we conducted differentially expressed genes (DEGs) analysis and WGCNA module analysis on the GSE144358 dataset, comparing the acute phase of SFTSV-infected patients with healthy individuals. Through the LASSO–Cox and random forest algorithms, a total of 2128 genes were analyzed, leading to the identification of four genes: ADIPOR1, CENPO, E2F2, and H2AC17. The GSEA analysis of these four genes demonstrated a significant correlation with immune cell function and cell cycle, aligning with the functional enrichment findings of DEGs. Furthermore, we also utilized CIBERSORT to analyze the immune cell infiltration and its correlation with characteristic genes. The results indicate that the combination of ADIPOR1, CENPO, E2F2, and H2AC17 genes has the potential as characteristic genes for diagnosing and studying the acute phase of SFTS virus (SFTSV) infection.