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Published on: July 9, 2014
Computational Modeling of Macrophage Iron Sequestration during Host Defense against Aspergillus
Bandita Adhikari1,2, Yogesh Scindia3, Luis Sordo Vieira3
1University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Abstract:
Iron is essential to the virulence of Aspergillus species, and restricting iron availability is a critical mechanism of antimicrobial host defense. Macrophages recruited to the site of infection are at the crux of this process, employing multiple intersecting mechanisms to orchestrate iron sequestration from pathogens. To gain an integrated understanding of how this is achieved in aspergillosis, we generated a transcriptomic time series of the response of human monocyte-derived macrophages to Aspergillus and used this and the available literature to construct a mechanistic computational model of iron handling of macrophages during this infection. We found an overwhelming macrophage response beginning 2 to 4 h after exposure to the fungus, which included upregulated transcription of iron import proteins transferrin receptor-1, divalent metal transporter-1, and ZIP family transporters, and downregulated transcription of the iron exporter ferroportin. The computational model, based on a discrete dynamical systems framework, consisted of 21 3-state nodes, and was validated with additional experimental data that were not used in model generation. The model accurately captures the steady state and the trajectories of most of the quantitatively measured nodes. In the experimental data, we surprisingly found that transferrin receptor-1 upregulation preceded the induction of inflammatory cytokines, a feature that deviated from model predictions. Model simulations suggested that direct induction of transferrin receptor-1 (TfR1) after fungal recognition, independent of the iron regulatory protein-labile iron pool (IRP-LIP) system, explains this finding. We anticipate that this model will contribute to a quantitative understanding of iron regulation as a fundamental host defense mechanism during aspergillosis. IMPORTANCE Invasive pulmonary aspergillosis is a major cause of death among immunosuppressed individuals despite the best available therapy. Depriving the pathogen of iron is an essential component of host defense in this infection, but the mechanisms by which the host achieves this are complex. To understand how recruited macrophages mediate iron deprivation during the infection, we developed and validated a mechanistic computational model that integrates the available information in the field. The insights provided by this approach can help in designing iron modulation therapies as anti-fungal treatments.
Insights
Macrophages restrict essential iron during Aspergillus infection. A computational model revealed transferrin receptor-1 upregulation precedes cytokine induction, suggesting direct fungal recognition triggers iron import.
Area of Science:
- Immunology
- Computational Biology
- Mycology
Background:
- Iron is crucial for Aspergillus virulence.
- Macrophages are key in host defense by sequestering iron.
- Understanding macrophage iron handling in aspergillosis is vital.
Purpose of the Study:
- To develop a mechanistic computational model of macrophage iron handling during Aspergillus infection.
- To integrate transcriptomic data and literature for a comprehensive understanding.
- To elucidate the dynamics of iron regulation in aspergillosis.
Main Methods:
- Generated a transcriptomic time series of human macrophages responding to Aspergillus.
- Constructed a discrete dynamical systems computational model.
- Validated the model with independent experimental data.
Main Results:
- Macrophage iron import proteins (TfR1, DMT1, ZIP) upregulated; iron exporter ferroportin downregulated.
- Model accurately predicted steady states and trajectories.
- Transferrin receptor-1 upregulation unexpectedly preceded inflammatory cytokine induction.
Conclusions:
- Direct induction of transferrin receptor-1 upon fungal recognition, independent of IRP-LIP, explains early TfR1 upregulation.
- The model provides a quantitative framework for understanding iron regulation in aspergillosis.
- Insights may inform the development of iron modulation therapies against fungal infections.

