Related Experiment Video
Updated: Jun 9, 2025

07:21
Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
12.8K
Comparative ecological analysis and predictive modeling of tick-borne pathogens.
William Manley1, Tam Tran1, Melissa Prusinski2
1Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
Journal of Medical Entomology
|October 23, 2024
Summary
Black-legged ticks spread Lyme disease, babesiosis, and anaplasmosis. This study models environmental factors impacting pathogen prevalence in New York, revealing distinct ecological patterns for Babesia microti and Anaplasma phagocytophilium.
Area of Science:
- Veterinary Entomology
- Epidemiology
- Disease Ecology
Background:
- Tick-borne diseases are a major North American health concern.
- Black-legged tick populations and associated diseases like Lyme disease are expanding.
- Limited research exists on environmental factors influencing Babesia microti and Anaplasma phagocytophilium.
Purpose of the Study:
- To model the impact of environmental features on tick-borne pathogen infection prevalence in New York State.
- To investigate the ecological determinants of Babesia microti and Anaplasma phagocytophilium distribution.
- To forecast future infection prevalence using validated biogeographic models.
Main Methods:
- Utilized over a decade of surveillance data (2009-2019) from New York State.
- Developed biogeographic models incorporating over 250 environmental variables.
- Modeled infection prevalence of Borrelia burgdorferi, Babesia microti, and Anaplasma phagocytophilium in Ixodes scapularis.
Main Results:
- Observed consistent northward and westward expansion of Babesia microti across New York.
- Documented fine-scale spatial variation in Anaplasma phagocytophilium range.
- Identified divergent environmental influences on pathogen distribution, suggesting unique ecological dynamics.
Conclusions:
- Environmental factors significantly shape the prevalence and distribution of tick-borne pathogens.
- Biogeographic models can accurately forecast pathogen prevalence.
- Findings support targeted disease prevention strategies by highlighting ecological differences between pathogens.

