A computational model of invasive aspergillosis in the lung and the role of iron.
BACKGROUND
Invasive aspergillosis is a severe infection of immunocompromised hosts, caused by the inhalation of the spores of the ubiquitous environmental molds of the Aspergillus genus. The innate immune response in this infection entails a series of complex and inter-related interactions between multiple recruited and resident cell populations with each other and with the fungal cell; in particular, iron is critical for fungal growth.


RESULTS
A computational model of invasive aspergillosis is presented here; the model can be used as a rational hypothesis-generating tool to investigate host responses to this infection. Using a combination of laboratory data and published literature, an in silico model of a section of lung tissue was generated that includes an alveolar duct, adjacent capillaries, and surrounding lung parenchyma. The three-dimensional agent-based model integrates temporal events in fungal cells, epithelial cells, monocytes, and neutrophils after inhalation of spores with cellular dynamics at the tissue level, comprising part of the innate immune response. Iron levels in the blood and tissue play a key role in the fungus' ability to grow, and the model includes iron recruitment and consumption by the different types of cells included. Parameter sensitivity analysis suggests the model is robust with respect to unvalidated parameters, and thus is a viable tool for an in silico investigation of invasive aspergillosis.


CONCLUSIONS
Using laboratory data from a mouse model of invasive aspergillosis in the context of transient neutropenia as validation, the model predicted qualitatively similar time course changes in fungal burden, monocyte and neutrophil populations, and tissue iron levels. This model lays the groundwork for a multi-scale dynamic mathematical model of the immune response to Aspergillus species.
Mathematical Biosciences Institute, Ohio State University, 1735 Neil Ave, Columbus OH, USA. oremland.2@osu.edu.
Matthew
M
Oremland
University of Virginia, Pulmonary and Critical Care Medicine, Charlottesville VA, USA.
Kathryn R
KR
Michels
University of Virginia, Pulmonary and Critical Care Medicine, Charlottesville VA, USA.
Alexandra M
AM
Bettina
Virginia Bioinformatics Institute, Virginia Tech, 1015 Life Science Circle, Blacksburg VA, USA.
Chris
C
Lawrence
University of Virginia, Pulmonary and Critical Care Medicine, Charlottesville VA, USA.
Borna
B
Mehrad
Center for Quantitative Medicine, University of Connecticut Health Center, 236 Farmington Ave, Farmington CT, USA.|Jackson Laboratory for Genomic Medicine, 236 Farmington Ave, Farmington CT, USA.
Reinhard
R
Laubenbacher
D000818:Animals; D001228:Aspergillosis / Q000378:metabolism*; D003198:Computer Simulation; D005260:Female; D007501:Iron / Q000378:metabolism*; D008168:Lung / Q000378:metabolism* / Q000382:microbiology* / Q000473:pathology; D051379:Mice; D008954:Models, Biological
D007501:Iron
Agent-based model; Invasive aspergillosis; Iron; Lung