Rickettsia and Francisella were negatively correlated in the ticks (Pearson’s product moment correlation; R = − 0.44, P < 0.01; Fig. 6). In order to assess whether the tick microbiomes were predictive of infection with spotted fever group Rickettsia (as determined by real-time PCR of the rompA gene and IGR sequences), a Random Forests supervised learning analysis using 1,000 trees and 10× cross validation was performed on the OTU dataset minus Rickettsiaceae and Rickettsia OTUs. The ratio of baseline error to the estimated generalization error was 8.8 (i.e., more than 8 times greater than random chance). The most predictive OTU was the FLE OTU 840032 and it accounted for 13% of the model. OTUs 866436 and 639277 each accounted for 3% of the model and the closest database matches to it were the Firmicutes Geobacillus and Aeribacillus (Geobacillus), respectively (Minana-Galbis et al., 2010). Non-Rickettsia, non-Francisella bacteria associated with Francisella to Rickettsia > 2 (range 2.4–119.0) were Planococcaceae and Geobacillus (Kruskal–Wallis test; H = 23.8, 14.2, Bonferroni P < 0.001 and P = 0.011, respectively). In addition, PERMANOVA with Bray-Curtis distances was used to test for the impact of tick sex, collection site and endosymbiotic infection status on the composition of microbial communities between samples (Anderson, 2001). These environmental differences showed a significant influence on the tick associated microbial communities. SFG (P = 0.001), tick sex (P = 0.021), location (P = 0.001), and Rickettsia to Francisella ratio (P = 0.008) all had significant effects on the bacterial communities.