The role of CARD9 in the pathogenesis of various chronic fungal infections has been established; however, the precise mechanisms underlying the pathobiology of these infections remain unclear. We aimed to investigate the specific cellular mechanisms by which CARD9 deficiency contributes to the pathogenesis of chronic fungal infections. Using single-cell RNA sequencing (scRNA-seq), we analyzed the immune cell profiles in skin lesions from both murine and human samples. We focused on macrophage differentiation and signaling pathways influenced by CARD9 deficiency. We found that CARD9 deficiency promotes the differentiation of TREM2high macrophages following fungal stimulation, impairing their antifungal functions and inducing exhaustion-like T helper 1 (Th1) cells. Mechanistically, the NF-κB pathway activation was restricted in CARD9-deficient macrophages, leading to enhanced CREB activation, which in turn exerted a positive regulatory effect on Trem2 expression by activating C/EBPβ. Notably, targeting TREM2 enhanced the antifungal immune response in vivo and in vitro, thereby alleviating the severity of CARD9-deficient subcutaneous dematiaceous fungal infection. Our findings highlight the important role of CARD9 in regulating cutaneous antifungal immunity and identify potential targets for immunotherapy in chronic dematiaceous fungal infections.
Lu Zhang, Zhichun Tang, Yi Zhang, Wenjie Liu, Haitao Jiang, Li Yu, Kexin Lei, Yubo Ma, Yang-xin Fu, Ruoyu Li, Wenyan Wang, Fan Bai, Xiaowen Wang
Usage data is cumulative from December 2025 through January 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 952 | 0 |
| 520 | 0 | |
| Supplemental data | 153 | 0 |
| Citation downloads | 80 | 0 |
| Totals | 1,705 | 0 |
| Total Views | 1,705 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.