In this application note, a study is presented that details a stepwise approach towards the intracellular staining and assessment of various immune cell types in a mouse model of obesity.
Obesity can create an inflammatory environment that may lead to the production of exhausted T cell phenotypes. The loss of T cell effector function associated with this phenotype may result in patients becoming vulnerable to many disorders like infectious diseases and cancer. An analysis of immune cells and the effect of obesity on their function is, therefore, necessary to understand the phenomena of T cell exhaustion and obtain research insights that can potentially be useful for therapy development.
In this study, the authors have characterised immune cell types across different tissues and assessed T cell response in a mouse model to understand immune cell phenotypes and their relationship with obesity. They used two populations of C57BL/6 mice that were fed a control diet (CD) and a high-fat diet (HFD) respectively for a period of 4 to 16 weeks. Whole blood, spleen, and fat tissue cells from both populations were treated and stained with a broad, 21-colour immunophenotyping panel for the detection of surface and intracellular targets. The authors also used a separate 12-colour panel to study obesity-related T cell dysfunction. The analysis was carried out on a BD FACSymphony™ A5 cell analyser.
In blood and spleen, the authors detected three populations of CD11b+ myeloid cells based on the expression of CD11c and Ly-6G and used the BD Horizon™ Red 718 dye conjugated with anti-mouse CD107a or lysosome-associated protein 1 (LAMP1), to study its expression. CD107a is expressed widely and resides primarily across lysosomal membranes. The data generated by the authors reveals that the CD11b+ myeloid cells in the fat expressed the highest amounts of CD107a. CD11b+ CD11c+ and CD11b+ CD11b– cells in blood expressed intermediate and high levels of CD107a while neutrophils and lymphocyte populations expressed less.
Alterations in T cell distribution in the fat tissue
Following further analyses of CD45+ cells and dimensionality reduction using FlowJo™, the authors could obtain a general classification of clusters into B cells, T cells, NK cells and myeloid cell populations. Following the analysis of the T cell subpopulations, the authors propose that TCRγδ cells were increased in HFD mice compared to normal (CD) mice. Also, CD8 T cells showed a different clustering pattern compared to the other tissues. The use of the PhenoGraph algorithm (FlowJo™), confirmed the heterogeneity within the T cell population. Three major CD8 T cell clusters (PG-6, PG-11 and PG-26) were identified in both CD and HFD mice while a fourth cluster (PG-15) was only seen in HFD mice after 16 weeks. The proportion of the effector and memory cells were also higher in HFD mice.
Assessing cell de-granulation in the fat tissue
The authors assessed cell-degranulation using the surface expression of CD107a. In the CD mice, the CD8 T cells showed a robust increase in size and underwent at least three rounds of cell division upon stimulation. These cells also showed sustained expression of CD69 and PD-1 and externalised CD107a as a sign of activation-induced cell degranulation. In contrast, the HFD mice showed smaller cell size and increased cell debris. Though the cells upregulated CD69, PD-1 and surface CD107a, they proliferated at a lower rate.
Conclusion
To conclude, the authors propose that this study has revealed differences in cell composition across different tissues in HFD and CD mice. Intracellular measurement of CD107a expression showed distinct cell phenotypes, particularly in myeloid cells. Fat tissue in HFD mice had more effector/memory CD8 T cells and TCRγδ cells compared to CD mice. Surface expression of CD107a showed that CD8 T cells from HFD mice proliferated less in vitro. Thus, the experiments, including the analysis of both intracellular and surface CD107a expression resolved using the BD Horizon™ Red 718 dye, have revealed more information on the effect of obesity on immune cells.
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This application note has not been peer-reviewed.
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