This readme.txt file was generated on 2025-06-17 by Benedict Khoo. Recommended citation for the data: Khoo, Benedict S; Oliver, Jonathan D; Fountain-Jones, Nick; Burton, Erin. (2023). 16S Microbiome fastq Sequences From Adult I. scapularis Ticks Collected Across Minnesota, Iowa and Wisconsin During The Summer in 2017-2019. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/efgb-9b37. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset: 16S Microbiome fastq Sequences From Adult I. scapularis Ticks Collected Across Minnesota, Iowa and Wisconsin During The Summer in 2017-2019 2. Author Information Author Contact: Benedict Khoo (khoo0011@umn.edu) Name: Benedict S Khoo Institution: University of Minnesota Email: khoo0011@umn.edu Name: Jonathan D Oliver Institution: University of Minnesota Email: joliver@umn.edu Name: Nick Fountain-Jones Institution: School of Natural Sciences, University of Tasmania, Hobart, Australia Email: nick.fountainjones@utas.edu.au ORCID: orcid.org/0000-0001-9248-8493 Name: Erin Burton Institution: University of Minnesota Email: cvm-asa@umn.edu 3. Date published or finalized for release: 2023-06-01 4. Date of data collection: 2017 to 2019 5. Geographic location of data collection (where was data collected?): U.S. Upper Midwest 6. Information about funding sources that supported the collection of the data: MN Futures program of the University of Minnesota and Australian Research Council Discovery Project Grant (DP190102020). 7. Overview of the data (abstract): Untangling how factors such as environment, host, associations among bacterial species and dispersal predict microbial composition is a fundamental challenge. In this study, we use complementary machine-learning approaches to quantify the relative role of these factors in shaping microbiome variation of the blacklegged tick Ixodes scapularis. I. scapularis is the most important vector for Borrelia burgdorferi (the causative agent for Lyme disease) in the U.S. as well as a range of other important zoonotic pathogens. Yet the relative role of the interactions between pathogens and symbionts compared to other ecological forces is unknown. We found that positive associations between microbes where the occurrence of one microbe increases the probability of observing another, including between both pathogens and symbionts, was by far the most important factor shaping the tick microbiome. Microclimate and host factors played an important role for a subset of the tick microbiome including Borrelia (Borreliella) and Ralstonia, but for the majority of microbes, environmental and host variables were poor predictors at a regional scale. This study provides new hypotheses on how pathogens and symbionts might interact within tick species, as well as valuable predictions for how some taxa may respond to changing climate. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC0 1.0 Universal (https://creativecommons.org/publicdomain/zero/1.0/) 2. Links to publications that cite or use the data: Fountain-Jones, Nicholas M., Khoo, Benedict S., Rau, Austin, Berman, Jesse D., Burton, Erin N. and Oliver, Jonathan D. (2023). Positive associations matter: Microbial relationships drive tick microbiome composition. Molecular Ecology, 32(14): 4078-4092. https://doi.org/10.1111/mec.16985 3. Was data derived from another source? No If yes, list source(s): 4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/policies/#drum-terms-of-use --------------------- DATA & FILE OVERVIEW --------------------- Filename: I scapularis 16s sequences.zip Short description: Fastq Sequences -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: See related open access publication at: https://doi.org/10.1111/mec.16985 ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: I scapularis 16s sequences.zip ----------------------------------------- This zip file contains all 16S raw paired end reads sequencing data that we used to characterize the Ixodes scapularis microbiome community across tick populations in the upper midwest. Samples are coded as follows (Site Code)(Year of sample collection)_#(Tick sex or Sample type) followed by non-necessary information on plate well and barcoding Note that each sample will have two sequences denoted by the R1 or R2 at the trailing end before 001. As Illumina miseq generates paired end reads. List of Site Codes and coordinates to the location of sampling sites are listed below Site Code Coordinates CNF 47.49541, -93.65031 IS 47.19567, -95.2576 CR 46.10728, -94.37419 CA 45.35073, -93.0312 KF 45.31014, -93.03169 SC 45.95399, -92.73269 WW 44.056946, -92.049376 RDWB 43.73793, -91.64205 YR 43.178278, -91.240302 C, CE 42.67699, -91.59584 T, B 45.94043, -91.80924 TSA 45.21141, -91.38059 TH, SG 43.16581, -90.04027 GMWM, GMW 45.37001, -93.11268 LC 47.04312, -91.70883 HI 47.9982, -96.28737 Years are all in 2000. Thus for samples coded with 17 for the year of sample collection, ticks were collected from that site in the summer of 2017 Tick Sex is either M for male or F for Female. S coded samples are soil samples Samples that do not follow the site code and year breakdown are either labeled BLANK or BRACHYSPIRA. Blank samples are blank wells used as negative controls and BRACHYSPIRA samples are splash control wells.