William T. Nash, Alyssa L. Gillespie, Michael G. Brown
Abstract
Dendritic cells (DC) are well-known modulators of immunity. This heterogeneous population is composed of defined subsets that exhibit functional specialization and are critical in initiating responses to pathogens. As such, many infectious agents employ strategies to disrupt DC functioning in attempts to evade the immune system. In some instances, this manifests as an outright loss of these cells. Previous work has suggested that, in the absence of an efficient natural killer (NK) cell response, murine cytomegalovirus (MCMV) induces large amounts of interferon (IFN)-I. This heightened IFN-I response is thought to contribute to conventional DC (cDC) loss and delayed development of T cell immunity. However, the precise role of IFN-I in such cDC loss remains unclear. We investigated the effects of licensed NK cells and IFN-I signaling on splenic cDC subsets during MCMV infection and found that a licensed NK cell response partially protects cDC numbers, but does not prevent increases in serum IFN-I. This suggested that high residual IFN-I could contribute to cDC loss. Therefore, we used multiple strategies to modulate IFN-I signaling during MCMV infection including plasmacytoid DC depletion, IFN-I receptor (IFNAR) blockade, and genetic ablation of IFNAR expression. Interestingly, restriction of IFN-I signals did not substantially preserve either CD8(+) or CD4(+) DC total numbers, but resulted in significant retention and/or accumulation of the splenic CD8(-) CD4(-) [double negative (DN)] subset. However, the DN DC effect manifested in a DC-extrinsic manner since IFNAR-deficient cells were not preferentially retained over their IFNAR wild-type counterparts in a mixed-chimera setting. Our results show that IFN-I signaling is not responsible for overt cDC toxicity in the setting of acute MCMV infection and emphasize that additional mechanisms contribute to DC loss and require exploration.
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 March 2017.
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