A cross-border comparison reveals expanded microbial diversity and zoonotic risk in Rhipicephalus microplus ticks of Yunnan, China

Abstract Background Rhipicephalus microplus is a critical vector for numerous agents of livestock and human diseases. Border regions are potential hotspots for pathogen exchange and emerging tick-borne diseases, yet comprehensive surveys of the total pathogen community (virome and microbiome) in ticks from these areas are limited. This study aimed to characterize the microbial diversity within R. microplus across different geographical locations (local vs. imported) and tissue types in Yunnan, China, to understand ecological drivers and assess associated zoonotic risks. Methods We performed meta-transcriptomic sequencing to profile the RNA virome and 16S rRNA gene sequencing to analyze the bacterial microbiome of R. microplus samples. Ticks were dissected into three key tissues: midgut, salivary glands, and ovaries. Bioinformatic and statistical analyses included taxonomic assignment, diversity metrics (alpha and beta diversity), co-occurrence network analysis, and tests for assessing the impact of geographic origin and tissue type on community structure. Results Our analysis revealed a highly diverse community of virome and bacterial microbiome. The virome comprised 63 viral families, including 28 with known animal hosts, such as the clinically significant families Flaviviridae, Phenuiviridae, and Peribunyaviridae. The bacterial microbiome included 167 bacterial genera, dominated by known pathogenic genera ( Coxiella , Rickettsia , Anaplasma , Ehrlichia ). We identified three novel viruses. Viral diversity was significantly richer in cross-border than in local samples, and the midgut exhibited the highest viral diversity among tissues. Network analysis indicated potential interactions between specific viral (e.g., Chuviridae ) and bacterial taxa. Conclusions This study reveals that R. microplus in border areas harbors a high diversity of pathogens with zoonotic potential. The composition of this pathogen community is fundamentally shaped by both geographic origin and vector tissue tropism. The elevated diversity at cross-border sites identifies them as key surveillance targets. These findings provide crucial data for informing surveillance strategies and early warning systems against tick-borne diseases in high-risk border regions.