[New England
      Complex Systems Institute]
[Home] [Research] [Education] [Current Section: Activities & Events] [Community] [News] [The Complex World] [About Complex Systems] [About NECSI]
International Conference on Complex Systems (ICCS2006)

An agent-based model for Leishmania infection

Garrett Dancik
Program in Bioinformatics and Computational Biology, Iowa St

Karin Dorman
Department of Statistics, Genetics, Development and Cell Biology, Iowa State University

Doug Jones
Department of Veterinary Pathology, Iowa State University

     Full text: PDF
     Last modified: May 27, 2006

Abstract
An agent-based model for Leishmania major infection

Leishmania are protozoan parasites, endemic in 88 countries, that are transmitted through the bites of infected sandflies. Over twenty species of Leishmania cause disease, which can be either cutaneous, where skin ulcers and permanent scarring occur on exposed surfaces of the body; or visceral, with a mortality rate of almost 100% if left untreated. C3HeB/FeJ mice are resistant to L. major infection, but develop chronic cutaneous lesions when infected with L. amazonensis. The mechanism of resistance in these mice is well understood: secretion of IL-12 by dendritic cells promotes a Th1 response, CD4+ Th1 cells activate macrophages through IFN-gamma; production, and activated macropohages clear the parasite. The in vivo factors that are necessary for host susceptibility to L. amazonensis, however, remain ambiguous. Although susceptibility is traditionally attributed to a weakened Th1 response, it is possible that other factors significantly contribute to disease. Through computer simulation, biologists can gain insight into the factors that favor parasite survival. Here we describe an agent-based model for L. major infection in C3HeB/FeJ mice. This model consists of macrophages, CD4+ Th1 cells, the Leishmania parasite, and chemokine, which influences the movement of cells. A replicated Latin hypercube sampling method was used to assess the sensitivity of various model output measures to the values of model parameters. These results indicate that the strength of the Th1 response, resting macrophage speed, and the transfer threshold of infected macrophages (which determines when infected macrophages transfer parasite to additional cells) have a large impact on the time it takes for the infection to be resolved. Parasite load at the peak of infection depends primarily on the timing of the Th1 response and on the transfer threshold of infected macrophages. These results reveal that the exploration of other factors, such as the transfer threshold of infected macrophages, in addition to the strength of the Th1 response, will be important for understanding L. amazonensis disease.


Appendices
      Agent-based model parameters




Conference Home   |   Conference Topics   |   Application to Attend
Submit Abstract/Paper   |   Accommodation and Travel   |   Information for Participants


Maintained by NECSI Webmaster    Copyright © 2000-2005 New England Complex Systems Institute. All rights reserved.