Abstract Rationale Invasive pulmonary aspergillosis is a life-threatening infection in immunocompromised individuals. Neutrophils play a critical role in host defense against Aspergillus fumigatus, contributing both to direct fungal killing and immune modulation. Their response involves complex mechanisms including recognition via pathogen-recognition receptors or complement, followed by signaling cascades that lead to degranulation, oxidative burst, phagocytosis, NETosis, apoptosis, or necrosis. Mechanistic computational modeling is well-suited to capture this complexity, offering a virtual platform to explore key pathways and test hypotheses efficiently. Despite the importance of neutrophils in fungal defense, few mathematical models exist that describe their intracellular mechanisms, and none to our knowledge address their interaction with Aspergillus. We developed a computational model informed by published literature and our own experimental data to elucidate neutrophil responses following exposure to A. fumigatus. Materials and Methods Neutrophils were cultured alone or with Aspergillus, and samples were collected every two hours for RNA sequencing using an Illumina HiSeq 4000. Differential gene expression analysis was performed using DESeq2 in R, and gene set enrichment was conducted against KEGG and Reactome databases. Model construction integrated RNA-seq data with known signaling pathways from the literature. A stochastic Boolean network model of neutrophil intracellular signaling was built and simulated across 1,000 randomly selected parameter sets. Model predictions were validated in vitro using flow cytometry, live-cell fluorescent imaging, and ELISA. Results Gene expression and enrichment analyses revealed upregulation of key transcriptional markers and pathways, including NFκB, TLR, TNF, neutrophil degranulation, cytokine-mediated signaling, chemokine signaling, and IL-17 signaling. These pathways were incorporated into a Boolean framework to construct a computational model that predicts neutrophil outcomes—apoptosis, fungal killing, and NETosis—in response to varying levels of Aspergillus infection. The model was further used to simulate the effects of various inhibitors on neutrophil function and their impact on antifungal responses. Conclusions We present a novel intracellular model of neutrophil response to Aspergillus fumigatus, capable of predicting NETosis and apoptosis rates under different infection conditions. By integrating multiple signaling pathways, the model enables mechanistic investigation and identification of optimal control strategies to enhance neutrophil fungicidal activity while minimizing harmful NETosis. This model lays the groundwork for incorporation into broader systems-level models of immune response to invasive pulmonary aspergillosis. This abstract is funded by: NIH:R01AI135128, NIH:U01EB024501, NSF:DMS-2424635, Keck Foundation Medical Research Grant 994413, AAI Intersect Fellowship
Wheeler et al. (Fri,) studied this question.