A computational model of invasive aspergillosis in the lung and the role of iron
Authored by Matthew Oremland, Reinhard Laubenbacher, Kathryn R Michels, Alexandra M Bettina, Chris Lawrence, Borna Mehrad
Date Published: 2016
DOI: 10.1186/s12918-016-0275-2
Sponsors:
United States National Institutes of Health (NIH)
United States National Science Foundation (NSF)
Platforms:
NetLogo
Model Documentation:
Other Narrative
Model Code URLs:
Model code not found
Abstract
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.
Tags
Agent-based model
systems biology
tuberculosis
Immunity
Stem-cell transplantation
Pulmonary aspergillosis
Host-defense
Amphotericin-b
Fumigatus
Airway