Lyme disease, due to infection with the Ixodes tick-transmitted spirochete Borrelia burgdorferi (Bb) is the most common vector-borne disease in the United States, with over 300,000 new cases annually. Infection can result in asymptomatic IgG seroconversion or cause clinical disease manifesting as an isolated skin lesion erythema migrans (EM) or with systemic illness involving the skin, heart, nervous system and/or joints. The infection is most responsive to antibiotics when identified early, but those people with disseminated infection or in whom treatment is delayed can experience debilitating disease that can become unresponsive to antibiotics. The immune responses to Bb associated with asymptomatic IgG seroconversion and that give rise to specific organ system involvement are poorly understood. This proposal will profile the innate and adaptive immune responses that arise after Bb infection in well-characterized patients with a) asymptomatic IgG seroconversion; b) isolated EM; c) acute disseminated infection with multiple EM and/or neurologic disease; and d) the late manifestation of arthritis. We will use novel state-of-the-art technologies to deeply characterize the immune response to Bb over time, both phenotypically and functionally, and correlate these responses with clinical presentations and outcomes. State-of-the-art high-resolution technologies such as CyTOF will be conducted on whole blood and synovial fluid, and T cell library populations exhibiting different chemokine receptors defining cytokine secretion and tissue migration will be generated to evaluate antigen-specific responses. The transcriptomes of responding T cell subsets in blood and other cell populations of interest identified by CyTOF will be analyzed by single cell RNAseq. Novel nanowell technologies will be used when cell samples are limiting, as in the case of skin biopsies or CSF samples, to characterize responding cells at the single cell level phenotypically using MuSIC (MultiSpectral Imaging Cytometry). These same tissues will be interrogated for immune signatures found in blood vs those unique to these sites and will be further assessed by single cell RNAseq. Along with the immune responses, we will also profile the host metabolome to define metabolite signatures associated with divergent clinical outcomes. Enabling this understanding of the immune response will be a systems biology approach to data integration, including clinical status, host metabolites and in vitro cell responses, to support an in-depth analysis and modeling of the host metabolic and immune responses as they evolve in subjects with Lyme disease. The output of this functional systems immunology approach will be definitions of human metabolite and immune signatures following infection with an extracellular bacterial pathogen Bb that will be compared to other infectious pathogens, with the ultimate goal of defining future targets for intervention and predicting susceptibility or resistance to systemic disease.

Public Health Relevance

Infection with the Lyme disease spirochete Borrelia burgdorferi can be localized to the skin or cause a systemic illness involving the skin, heart, nervous system and/or the joints. The immune responses that dictate the divergent clinical presentations and outcomes from Lyme disease are not known. This proposal will take an unbiased approach using state-of-the-art high-resolution technologies to evaluate the metabolic signatures and immune responses in Lyme disease that give rise to divergent clinical presentations and outcomes from infection with this bacterial pathogen.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI089992-10
Application #
10079822
Study Section
Special Emphasis Panel (ZAI1)
Project Start
2010-07-12
Project End
2021-11-30
Budget Start
2020-12-01
Budget End
2021-11-30
Support Year
10
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Yale University
Department
Type
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
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