Article

Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling

Department of Biomedical Engineering, University of Virginia, Health System, Charlottesville, VA 22908, USA.
Trends in Immunology (Impact Factor: 12.03). 01/2009; 29(12):589-99. DOI: 10.1016/j.it.2008.08.006
Source: PubMed

ABSTRACT The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

Download full-text

Full-text

Available from: Jason A Papin, Jul 07, 2015
0 Followers
 · 
154 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The dynamics of H5N1 influenza virus pathogenesis are multifaceted and can be seen as an emergent property that cannot be comprehended without looking at the system as a whole. In past years, most of the high-throughput studies on H5N1-host interactions have focused on the host transcriptomic response, at the cellular or the lung tissue level. These studies pointed out that the dynamics and magnitude of the innate immune response and immune cell infiltration is critical to H5N1 pathogenesis. However, viral-host interactions are multidimensional and advances in technologies are creating new possibilities to systematically measure additional levels of 'omic data (e.g. proteomic, metabolomic, and RNA profiling) at each temporal and spatial scale (from the single cell to the organism) of the host response. Natural host genetic variation represents another dimension of the host response that determines pathogenesis. Systems biology models of H5N1 disease aim at understanding and predicting pathogenesis through integration of these different dimensions by using intensive computational modeling. In this review, we describe the importance of 'omic studies for providing a more comprehensive view of infection and mathematical models that are being developed to integrate these data. This review provides a roadmap for what needs to be done in the future and what computational strategies should be used to build a global model of H5N1 pathogenesis. It is time for systems biology of H5N1 pathogenesis to take center stage as the field moves towards a more comprehensive view of virus-host interactions.
    Virus Research 03/2013; DOI:10.1016/j.virusres.2013.02.011 · 2.83 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Opportunistic human pathogenic fungi like the ubiquitous fungus Aspergillus fumigatus are a major threat to immunocompromised patients. An impaired immune system renders the body vulnerable to invasive mycoses that often lead to the death of the patient. While the number of immunocompromised patients is rising with medical progress, the process, and dynamics of defense against invaded and ready to germinate fungal conidia are still insufficiently understood. Besides macrophages, neutrophil granulocytes form an important line of defense in that they clear conidia. Live imaging shows the interaction of those phagocytes and conidia as a dynamic process of touching, dragging, and phagocytosis. To unravel strategies of phagocytes on the hunt for conidia an agent-based modeling approach is used, implemented in NetLogo. Different modes of movement of phagocytes are tested regarding their clearing efficiency: random walk, short-term persistence in their recent direction, chemotaxis of chemokines excreted by conidia, and communication between phagocytes. While the short-term persistence hunting strategy turned out to be superior to the simple random walk, following a gradient of chemokines released by conidial agents is even better. The advantage of communication between neutrophilic agents showed a strong dependency on the spatial scale of the focused area and the distribution of the pathogens.
    Frontiers in Microbiology 04/2012; 3:129. DOI:10.3389/fmicb.2012.00129 · 3.94 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Key points  After myocardial infarction, fibroblasts infiltrate the necrotic myocardium, deposit collagen, and remodel collagen, forming scar tissue.  Mechanical, structural, and chemical guidance cues have all been shown to regulate alignment of fibroblasts and collagen in vitro.  We developed a computational model of infarct healing with parameters closely tied to published data, ran simulations with different combinations of guidance cues, and successfully predicted measured collagen structures in rat infarct scars.  We determined that a mechanical guidance cue was the most important determinant of collagen alignment in healing myocardial infarcts.  Since anisotropy of infarct scar tissue is an important determinant of cardiac function, our model represents a potentially powerful tool for testing the effects of post-infarction therapies on scar anisotropy and designing new therapies that modulate infarct healing by controlling the mechanical stimuli acting on the infarct region or the response of fibroblasts to those stimuli.
    The Journal of Physiology 04/2012; 590(Pt 18):4585-602. DOI:10.1113/jphysiol.2012.229484 · 4.54 Impact Factor