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Tick microbiome and Borreliaceae pan-genome characterization: towards the development of a two-tiered diagnostic for Lyme borreliosis
Dissertation   Open access

Tick microbiome and Borreliaceae pan-genome characterization: towards the development of a two-tiered diagnostic for Lyme borreliosis

Kayla Merced Socarras
Doctor of Philosophy (Ph.D.), Drexel University
Nov 2022
DOI:
https://doi.org/10.17918/00001453
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Abstract

Borrelia Tick-borne diseases Ticks Borreliaceae Microbiome Pangenome Bioinformatics
Tick-borne diseases (TBD) have been a blight on human health worldwide despite numerous efforts to advance proper treatment and prevention for this group of maladies. The lack of improvement primarily stems from the paucity of available information on the vectors and TBD pathogens of interest. This extends beyond understanding the basic biology of these parasitic organisms and how to deal with them, it extends on how to identify their impact on the human body. In this dissertation several approaches were taken with the singular focus on how to address the impact and presence of TBD pathogens. First, it is imperative to understand the complete complement of microbes within TBD vectors. Current efforts in this field have been focused on the most wildly known tick species such as Dermacentor variabilis, Amblyomma americanum, and Ixodes scapularis. While these species are a detriment to human safety, so is a rising vector within western North America, Ixodes pacificus. Thus, the first section of this work is dedicated to understanding the bacterial composition of this arachnid ectoparasite. The second segment of this dissertation then focuses on the largest and increasingly prevalent group of obligate pathogens, Borreliaceae spirochetes. These works are the first to develop, construct, and mine the pangenome at the family-level. They are also the first in proposing tangible means of definitively characterizing the spirochetes. Lastly, the final segment of this dissertation is collection of works centered on developing several diagnostic platforms to detect TBD pathogens.

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