A computational model of invasive aspergillosis in the lung and the role of iron

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dc.contributor.authorOremland, Matthewen
dc.contributor.authorMichels, Kathryn R.en
dc.contributor.authorBettina, Alexandra M.en
dc.contributor.authorLawrence, Chrisen
dc.contributor.authorMehrad, Bornaen
dc.contributor.authorLaubenbacher, Reinhard C.en
dc.contributor.departmentFish and Wildlife Conservationen
dc.date.accessioned2019-11-13T13:49:24Zen
dc.date.available2019-11-13T13:49:24Zen
dc.date.issued2016en
dc.description.abstractBackground: 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.en
dc.description.sponsorshipMO was supported in part by NSF Grant DMS-0931642 to the Mathematical Biosciences Institute. He was also supported partially by NSF Grant DMS-1062878 and US Department of Defense Grant Nr. W911NF0910538. KRM, AMB, and BM were supported in part by NIH Grants HL098526 and HL098329. RL was partially supported by NIH Grant Nr. 1R21AI101619-01. CL was supported by his affiliated institution.en
dc.format.extent14 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationOremland et al. BMC Systems Biology (2016) 10:34 DOI 10.1186/s12918-016-0275-2en
dc.identifier.doihttps://doi.org/10.1186/s12918-016-0275-2en
dc.identifier.urihttp://hdl.handle.net/10919/95519en
dc.identifier.volume10en
dc.language.isoenen
dc.publisherBMCen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectInvasive aspergillosisen
dc.subjectAgent-based modelen
dc.subjectLungen
dc.subjectIronen
dc.titleA computational model of invasive aspergillosis in the lung and the role of ironen
dc.title.serialBMC Systems Biologyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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