bioRxivImmunologyPreprint
Host Metabolic Reprogramming Defines Macrophage Antifungal Activity Against Cryptococcus neoformans
Abstract
Innate immune cells, including macrophages and DCs, are critical for controlling infection by Cryptococcus neoformans. Although C. neoformans is phagocytosed equally by each pulmonary phagocyte subset, CD11b+ DCs support fungal growth, whereas Ly6c- monocyte-like macrophages are antifungal. The metabolic programs underlying these contrasting responses remain incompletely understood, but our previous work points to increased glycolysis in antifungal cells. Therefore, we hypothesized that metabolic reprogramming in phagocytes following cryptococcal exposure leads to different outcomes. We examined ten metabolic pathways using flow cytometry, metabolic inhibition, antifungal assays, and pulmonary infection. Cryptococcal exposure increased GLUT-1, HK, HIF-1, and lactate production in J774A.1 macrophages, consistent with enhanced glycolytic metabolism in antifungal cells. In contrast, ATP5a and IDH2 were reduced, suggesting diminished mitochondrial metabolism. Cryptococcus also decreased G6PD, ACAC, ASS1, and PRDX2, indicating alterations in PPP activity, fatty acid synthesis, arginine metabolism, and antioxidant defense. Pharmacologic inhibition of PPP further reduced G6PD expression and significantly decreased intracellular cryptococcal burden, supporting a role for glucose-derived metabolic pathways in regulating fungal survival. In vivo, infection increased GLUT-1 and HK expression in antifungal female Ly6c- monocyte-like macrophages but not in permissive CD11b+ DCs, whereas other metabolic markers showed limited or subset-specific changes. Collectively, these findings demonstrate that antifungal cells use a predominantly glycolytic program accompanied by reduced mitochondrial, anabolic, and antioxidant-associated protein expression following interaction with C. neoformans. This phagocyte subset-dependent metabolic response during pulmonary infection may influence antifungal activity and identify metabolic pathways that could be targeted to strengthen host defense.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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