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    Guinea pigs are an ideal animal model for the study of several infectious diseases, including tuberculosis, legionellosis, brucellosis, and spotted fever rickettsiosis. In comparison to the murine model, clinical signs in guinea pigs are more representative of disease in humans, the guinea pig immune system is more similar to that of the human, and their large size offers logistic advantages for sample collection while following disease progression. Unfortunately, the advantage of using guinea pigs in biomedical research, particularly in understanding the immune response to infectious agents, is limited in large part by the paucity of available reagents and lack of genetically manipulated strains. Here, we expand the utility of guinea pigs in biomedical research by establishing an optimized five-color/seven-parameter polychromatic flow cytometric assay for immunophenotyping lymphocytes. This assay fills a need for immunophenotyping peripheral blood lymphocytes and is an improvement over current published flow cytometry assays for guinea pigs. We anticipate that our approach will be an important starting point for developing new assays to evaluate the cellular immune response to infectious diseases in the guinea pig model. Importantly, we are currently using this assay for evaluating immunity to spotted fever rickettsiosis in a guinea pig-tick-Rickettsia system, where CD8+ T cells are a critical contributor to the immune response. Developing resources to utilize the guinea pig more effectively will enhance our ability to understand infectious diseases where the guinea pig would otherwise be the ideal model. Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.

    Citation

    John V Stokes, Anna E Crawford, Claire E Cross, Anne-Marie L Ross, Jamie D Walker, Bridget V Willeford, Andrea S Varela-Stokes. An optimized five-color/seven-parameter flow cytometry panel for immunophenotyping guinea pig peripheral blood lymphocytes. Journal of immunological methods. 2020 Jan;476:112682

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    PMID: 31682796

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