TICK microbiome and pathobiome interactions with biotic factors to mitigate their SpreAd via wild VErtebrate hosts

Background

Tick-borne diseases are an increasing public health concern, with Ixodes ricinus serving as a primary vector in Europe. Environmental factors, land-use changes, and host availability significantly influence tick density, pathogen prevalence, and microbiome diversity. However, the interactions between these factors remain insufficiently understood. Previous studies have identified that disturbed habitats can impact pathogen transmission and microbial communities in ticks, yet detailed phylogeographic and microbiome analyses are lacking. This study aims to fill these gaps by integrating ecological, molecular, and bioinformatics approaches to understand tick-pathogen-microbiome interactions.

Goals

1. Investigate how land-use intensity and forest structure affect tick density and pathogen prevalence.
2. Examine relationships between host abundance, landscape variables, and tick density.
3. Compare microbial communities in ticks from disturbed (FOX plots) and undisturbed sites.
4. Assess correlations between the tick microbiome and pathogen prevalence.
5. Recover and analyze Borrelia genomes from I. ricinus ticks to explore phylogeographic variations.
6. Establish phylogeographic maps of tick populations and relate them to pathogen prevalence and Borrelia diversity.

Hypotheses

HYPOTHESIS 1 (H1): Disturbed experimental plots (FOX plots) will show a higher pathogen prevalence in I. ricinus ticks but a lower I. ricinus nymph density compared to undisturbed sites.

HYPOTHESIS 2 (H2): Ixodes ricinus nymph density is driven more by mammal communities (recorded by local management Max Müller, not included in this project) and local landscape variables (taken from BEXIS) inducing a livable microclimate then by large scaled landscape variables and broad climatic variables in a time span of 2 years and the BE setting.

HYPOTHESIS 3 (H3): As the land use intensity index increases, the tick microbiome diversity, structure and assembly will undergo changes, lowering diversity but increasing abundance of potential pathogenic taxa (pathobiome).

HYPOTHESIS 4 (H4): There will be a negative correlation between the abundance of tick-borne pathogens in ticks and the diversity of the tick microbiome, and specific bacterial community assemblies.

HYPOTHESIS 5 (H5): Borrelia genome diversity and tick phylogenic diversity vary geographically between all three BEs and higher genetic diversity will be obtained in mixed and broad leaf forests with an older forest stand compared to coniferous younger forests.

HYPOTHESIS 6 (H6): The tick microbiome diversity is reflected in the microbiome diversity of the surrounding soil.

Methods

Field Sampling: Questing ticks will be collected from experimental and FOX plots in three Biodiversity Exploratories (BEs) in Germany across all seasons (2026-2027). Tick density will be quantified in relation to forest structure and land-use practices.
Tick and Pathogen Analysis: Collected ticks will be taxonomically identified, and DNA will be extracted for further analysis. Borrelia prevalence and genospecies will be determined using qPCR and MLST sequencing.
Microbiome Analysis: The tick microbiome will be characterized using 16S rRNA sequencing, with comparisons between disturbed and undisturbed plots and correlation with pathogen presence.
Phylogenetic and Statistical Analysis: Genetic relationships among tick populations will be assessed using mitochondrial markers, and phylogenetic trees will be constructed. Statistical models (GLMM, PERMANOVA) will be applied to evaluate the influence of environmental and biotic factors on tick density, pathogen prevalence, and microbiome diversity.