The saprophytic mold Aspergillus fumigatus produces small (2-3 microm) airborne spores (conidia) that can reach the lung alveoli upon inhalation. There, they encounter the surfactant-rich environment of the alveolar epithelium and initiate swelling and germination. Primary alveolar macrophages are essential for the rapid clearance of conidia and maintenance of pulmonary homeostasis. However, A. fumigatus remains the leading cause of invasive pulmonary aspergillosis in immunocompromised patients, and the mechanisms governing fungal clearance versus invasion remain poorly understood. In this study, we adapted a previously established monocyte-derived alveolar-like macrophage (ALM) model to investigate early host-pathogen interactions upon A. fumigatus challenge. Given the requirement of GM-CSF for maintaining alveolar macrophage identity and function, we included GM-CSF differentiated macrophages (GM-M), as a widely used reference model. Primary alveolar macrophages (pAM), isolated from human lung biopsies were used to validate the physiological relevance of the ALM model. Combined phenotypic, functional and transcriptomic analyses demonstrated that ALMs closely resemble pAMs under both steady-state and infection conditions across multiple time points and fungal burdens. Notably, fungal dual RNA-sequencing revealed a significant upregulation of fungal virulence-associated factors during interaction with ALM, which was not observed in GM-M co-cultures. Collectively, these findings support the use of ALMs as a robust, experimentally accessible and physiologically relevant in vitro model for investigating early A. fumigatus infection, providing new insights into host-pathogen dynamics at the alveolar interface.
Disclosure in the era of generative artificial intelligence
Generative artificial intelligence (AI) has rapidly become embedded in academic writing, assisting with tasks ranging from language editing to drafting text and producing evidence. Despite


