Exploring the microbiome of Otobius megnini in Mexico

Introduction Ticks harbor complex microbial communities that influence both their biology and their capacity for pathogen transmission. Although the microbiota of hard ticks has been extensively investigated, that of soft ticks, such as Otobius megnini , remains comparatively understudied. Methods In this exploratory study, we compared two independently generated 16S rRNA datasets from O. megnini collected in Querétaro and Comarca Lagunera and generated predicted MetaCyc pathway profiles with PICRUSt2. The taxonomic composition, alpha and beta diversity, exploratory co-occurrence network topology, and predicted functional profiles were compared descriptively. Differences in tissue type, 16S region, host replication, life stage, feeding status, and laboratory processing prevented causal attribution to geography. Results Both datasets showed recurrent bacterial taxa, including Staphylococcus , Corynebacterium , and Coxiella -like organisms. Pielou’s evenness was higher and observed feature richness was lower in Comarca Lagunera than in Querétaro (Kruskal–Wallis: both p = 0.0001), whereas Shannon diversity did not differ ( p = 0.888). The Bray–Curtis permutational multivariate analysis of variance (PERMANOVA) was significant ( p = 0.0001), but multivariate dispersion also differed (betadisper ANOVA: F = 10.61, p = 0.0001). Therefore, the PERMANOVA result cannot be interpreted as an unambiguous difference in group centroids. The inferred networks differed descriptively in topology, and PICRUSt2 predicted pathways shared across the datasets, including those related to central carbon metabolism, amino acid biosynthesis, and cofactor metabolism. Conclusions These results provide a descriptive baseline for two independently generated O. megnini microbiome datasets. Because dataset identity was confounded with tissue type, 16S region, host replication, life stage, feeding status, and laboratory processing, the observed differences cannot be attributed to geography. The network and PICRUSt2 results are hypothesis-generating and do not establish microbiome stability, robustness, functional conservation, redundancy, or metabolic activity.