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    • Albert Einstein College of Medicine: Doctoral Dissertations
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    • Albert Einstein College of Medicine (AECOM)
    • Albert Einstein College of Medicine: Doctoral Dissertations
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    Targeting effector CD4 T cell developmental plasticity for improving vaccine design

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    Date
    2013
    Author
    Goldberg, Michael F.
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    Abstract
    Naive CD4 T cells have remarkable developmental plasticity and can differentiate into TH1, TH2, TH17, inducible regulatory T cells (iTreg), and T follicular helper cells (TfH) subsets, each capable of orchestrating a unique functional outcome. We have used mouse models of mycobacterial infection to further elaborate the roles of various CD4 T cell subsets in protecting against tuberculosis. Our analyses following vaccination with BCG and IKEPLUS, a novel vaccine based on M. smegmatis, strong associations were seen between the level of protection and the quality of CD4 responses. Vaccination with IKEPLUS expanded a larger pool of multifunctional TH1 cells that correlated with enhanced bactericidal immunity. In related studies, we found that varying the medium used to grow BCG in culture had a major impact on the frequency of TH17 cells following BCG vaccination, correlating with changes in the protective efficacy of the vaccine. We hypothesized that by manipulating the adjuvant component of a vaccine we could skew antigen-specific CD4 T cell differentiation toward a specific subset. Adjuvants mediate immunogenicity by triggering pattern recognition receptors (PRRs) on antigen presenting cells, stimulating cytokine production and the engagement of antigen-processing and presentation systems. Unfortunately, a lack of robust discovery platforms for testing PRR agonists has limited the discovery of more effective and safe candidate adjuvants. To address this limitation, we developed a novel high-throughput flow cytometry-based in vitro CD4 priming assay. With this system, we are able to identify and quantify populations of TH1, TH2, TH17, iTreg, and TfH cells. This platform has enabled us to rapidly screen a large panel of PRR agonists with predicted adjuvant properties individually and in complex combinations. We have also developed a computational framework that scores each adjuvant combination based on the strength and quality of CD4 priming. Initial screening has revealed adjuvant synergy in every parameter interrogated with several unexpected candidates resulting from the screening process. These compounds have been tested in an in vivo vaccination model and have demonstrated a high degree of reproducibility. In summary, this platform has the potential to lay the foundation for the rational design of prophylactic and therapeutic vaccine adjuvants.
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    https://ezproxy.yu.edu/login?url=http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:3536144
    https://hdl.handle.net/20.500.12202/1367
    Citation
    Source: Dissertation Abstracts International, Volume: 74-06(E), Section: B.;Advisors: Steven A. Porcelli.
    *This is constructed from limited available data and may be imprecise.
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