An in silico model of the effects of Vitamin D3 on mycobacterium infected macrophage

Maya Gough, Elebeoba May

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Mycobacterium tuberculosis is a global health concern, causing over one million deaths a year. Alveolar macrophages, as the primary host cell of this intracellular bacterium, play an important role in the course of disease. Vitamin D3 is known to have a potent effect on macrophage behavior during infection, modulating the production of pro- and anti-inflammatory cytokines and immune effector molecules. In a vitamin D3 deficient host, the immune systems response to infection is greatly impaired. We used a quantitative systems biology approach to model the intracellular effects of vitamin D3 and compared our simulation output to our in vitro model of mycobacterium infection of macrophages in the presence and absence of Vitamin D3. Our in silico model results agreed with the in vitro assay results of interleukin-10, an anti-inflammatory protein whose production is known to be influenced by vitamin D3. This model will provide a platform for further investigation of the effects of vitamin D3 deficiency on host immune response to infection.

Original languageEnglish (US)
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1443-1446
Number of pages4
Volume2016-October
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Other

Other38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Country/TerritoryUnited States
CityOrlando
Period8/16/168/20/16

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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