Colored Petri Net Model of Early Mycobacterial Infection
These pages are in support of:
Modelling Innate Immune Response to early Mycobacterium Infection.
Rafael V. Carvalho, Jetty Kleijn, Annemarie H. Meijer, Fons J. Verbeek,
Computational and Mathematical Methods in Medicine, Accepted November(2012)
We have modelled the role of the innate immune system in the early stages of a mycobacterial infection and dissemination using Colored Petri Net (CPN) as a model formalism. The environment of the model represents innate immune response based on the Mycobacterium marinum infection process on the zebrafish, although at this level, the CPN model can be used to describe the early immune response to any kind of mycobacterial infection process. The rules of the model represent the biological interactions as described in section 2.1 of the paper,i.e.:
- Signalling of intruding bacteria detected by healthy macrophages followed by phagocytosis
- Migration and intracellular bacterial replication within infected macrophages and their death
- Recruitment and migration of healthy macrophages in response to the dead macrophage signals
- The aggregation process and granuloma formation
- The bacterial spread in the aggregate macrophage and the infection dissemination
We have used the Snoopy software to implement and animate our net with two different operating systems (OS): Windows 7 (HP Intel core i7, 4 Gb RAM) and Mac OS 10.6 (MacBook Pro Intel core i7, 4 Gb RAM). The main difference between the two platforms is the additional features in the user-interface for the Windows implementation. The CPN model runs with the same accuracy on both OS-versions. This illustrates the platform independency of the Snoopy software framework.
The animation mode in Snoopy allows you to observe the token-flow that represents the behaviour of the model. It is possible to animate the token-flow manually by clicking on the transitions or using the animation steering panel, where you can play/pause the animation, step-wise forward and backward or sequentially as long as one transition can be enabled. You can also change further animation properties under options, like refreshment, duration and stepping where you can control the behave of the animation.
The following videos illustrate three different animation sequences based on the stepping options, in which you can verify the dynamic behaviour of our model:
Single stepping animation mode
On this mode it is possible to see the token-flow in which one enabled transition fires at each time sequentially
Intermediate stepping animation mode
On this mode it is possible to see the token-flow in which one or more enabled transition fires at the same time (not sequentially):
Maximum stepping animation mode
On this mode it is possible to see the token-flow in which the enabled transition fires at the same time (not sequentially):
Contact Rafael V. Carvalho or Fons Verbeek for information.