Data from: Drivers and patterns of microbial community assembly in a Lyme disease vector
Couper, Lisa I.
Kwan, Jessica Y.
Published Jun 18, 2019 on Dryad.
Cite this dataset
Couper, Lisa I.; Kwan, Jessica Y.; Ma, Joyce; Swei, Andrea (2019). Data from: Drivers and patterns of microbial community assembly in a Lyme disease vector [Dataset]. Dryad. https://doi.org/10.5061/dryad.2nv32qh
Vector-borne diseases constitute a major global health burden and are increasing in geographic range and prevalence. Mounting evidence has demonstrated that the vector microbiome can impact pathogen dynamics, making the microbiome a focal point in vector-borne disease ecology. However, efforts to generalize preliminary findings across studies and systems and translate these findings into disease control strategies are hindered by a lack of fundamental understanding of the processes shaping the vector microbiome and the interactions therein. Here we use 16S rRNA sequencing and apply a community ecology framework to analyze microbiome community assembly and interactions in Ixodes pacificus, the Lyme disease vector in the western US. We find that vertical and environmental transmission routes drive population-level patterns in I. pacificus microbial diversity and composition, but not in microbial function and overall abundance. Further we find that the I. pacificus microbiome is not strongly structured based on competition but assembles non-randomly, likely due to vector-specific filtering processes which largely eliminate all but the dominant endosymbiont, Rickettsia. At the scale of the individual I. pacificus, we find support for a highly limited internal microbial community, and propose that the tick endosymbiont may be the most important component of the vector microbiome in influencing pathogen dynamics.
This table list percentage relative abundance for each OTU retained after the sequence quality filtering pipeline for each sample included in this study. The treatment group (both clutch and environmental exposure time) is also listed for each sample.