Galectin-9 Expression Defines a Subpopulation of NK Cells with Impaired Cytotoxic Effector Molecules but Enhanced IFN-γ Production, Dichotomous to TIGIT, in HIV-1 Infection
NK cell functions are tightly regulated by the balance between the inhibitory and stimulatory surface receptors. We investigated the surface expression of galectin-9 (Gal-9) and its function in NK cells from HIV-infected individuals on antiretroviral therapy, long-term nonprogressors, and progressors compared with healthy controls. We also measured the expression of TIGIT and TIM-3 on different NK cell subpopulations and compared their functionality to Gal-9 + NK cells. Our data demonstrated significant upregulation of Gal-9 on NK cells in HIV-infected groups versus healthy controls. Gal-9 expression was associated with impaired expression of cytotoxic effector molecules granzyme B, perforin, and granulysin. In contrast, Gal-9 expression significantly enhanced IFN-γ expression in NK cells of HIV-1-infected individuals. We also found an expansion of TIGIT + NK cells in HIV-infected individuals; however, dichotomous to Gal-9 + NK cells, TIGIT + NK cells expressed significantly higher amounts of cytotoxic molecules but lower IFN-γ. Moreover, lower expression of cytotoxic effector molecules in Gal-9+ NK cells was associated with higher CD107a expression, which suggests indiscriminate degranulation. Importantly, a positive correlation between the plasma viral load and Gal-9+ NK cells was observed in progressors. Finally, we found that a cytokine mixture (IL-12, IL-15, and IL-18) can improve effector functions of Gal-9+ NK cells in HIV-infected individuals, although, such an effect was observed for Gal-9- NK cells, as well. Overall, our data highlight the important role of Gal-9 in dysfunctional NK cells and, more importantly, a dichotomy for the role of Gal-9 versus TIGIT and suggest a potential new avenue for the development of therapeutic approaches.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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