Ticks are globally distributed arthropods and a public health concern due to the many human pathogens they carry and transmit, including the causative agent of Lyme disease, Borrelia burgdorferi. As tick species’ ranges increase, so do the number of reported tick related illnesses. The microbiome is a critical part of understanding arthropod biology, and the microbiome of pathogen vectors may provide critical insight into disease transmission and management. Yet we lack a comprehensive understanding of the microbiome of wild ticks, including what effect the presence of multiple tick-borne pathogens (TBPs) has on the microbiome. In this study we chose samples based on life stage (adult or nymph) and which TBPs were present. We used DNA from previously extracted Ixodes scapularis ticks that tested positive for zero, one, two or three common TBPs (B. burgdorferi, B. miyamotoi, Anaplasma phagocytophilum, Babesia microti). We produced 16S rRNA amplicon data for the whole tick microbiome and compared samples across TBPs status, single vs multiple coinfections, and life stages. Focusing on samples with a single TBP, we found no significant differences in microbiome diversity in ticks that were infected with B. burgdorferi and ticks with no TBPs. When comparing multiple TBPs, we found no significant difference in both alpha and beta diversity between ticks with a single TBP and ticks with multiple TBPs. Removal of TBPs from the microbiome did not alter alpha or beta diversity results. Life stage significantly correlated to variation in beta diversity and nymphs had higher alpha diversity than adult ticks. Rickettsia, a common tick endosymbiont, was the most abundant genus. This study confirms that the wild tick microbiome is highly influenced by life stage and much less by the presence of human pathogenic bacteria.

The taxonomic composition of a microbiome is predominately identified using amplicon sequencing of 16S rRNA genes, but as a single marker, it cannot identify functions (genes). Metagenome and metatranscriptome sequencing can determine microbiome function but can be cost prohibitive.

The gut microbiota has many positive effects on the host, but how the microbiota is shaped and influenced can vary greatly. These factors affect the composition, diversity, and function of host-associated microbiota; however, these factors vary greatly from organism to organism and clade to clade. The avian microbiota often correlates more with the sampling locations rather than host-associated co-factors. These correlations between location and microbiota often only include a few sampling locations within the species' range. To better understand the connection between geographic distance and the microbiota, were collected from non-migratory Canada geese across the United States. We expected host-associated factors to have minimal effect on the microbiota and geese microbiota will be strongly correlated to geography. We hypothesized more proximal geese will be exposed to more similar environmental microbes and will have more similar microbiota. Canada geese microbiota are largely similar across the entire sampling range. Several bacterial taxa were shared by more than half of the geese. Four phyla were found in the majority of the samples: Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. Three genera were also present in the majority of the samples: Helicobacter, Subdoligranulum, and Faecalibacterium. There were minimal differences in alpha diversity with respect to age, sex, and flyway. There were significant correlations between geography and beta diversity. Supervised machine learning models were able to predict the location of a fecal sample based on taxonomic data alone. Distance decay analysis show a positive relationship between geographic distance and beta diversity. Our work provides novel insights into the microbiota of the ubiquitous Canada goose and further supports the claim that the avian microbiota is largely dominated by the host's environment. This work also suggests that there is a minimum distance that must be reached before significant differences in the microbiota between two individuals can be observed.