Cellular signaling processes depend on spatiotemporal distributions of molecular components. Multicolor, high-resolution microscopy permits detailed assessment of such distributions, providing input for fine-grained computational models that explore mechanisms governing dynamic assembly of multimolecular complexes and their role in shaping cellular behavior. However, it is challenging to incorporate into such models both complex molecular reaction cascades and the spatial localization of signaling components in dynamic cellular morphologies. Here we introduce an approach to address these challenges by automatically generating computational representations of complex reaction networks based on simple bimolecular interaction rules embedded into detailed, adaptive models of cellular morphology. Using examples of receptor-mediated cellular adhesion and signal-induced localized mitogen-activated protein kinase (MAPK) activation in yeast, we illustrate the capacity of this simulation technique to provide insights into cell biological processes. The modeling algorithms, implemented in a new version of the Simmune toolset, are accessible through intuitive graphical interfaces and programming libraries.
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We thank R. Schwartz, R. Varma, A. Nita-Lazar, I. Fraser, J. Tsang and D. Cioffi for helpful comments, members of the Laboratory for Systems Biology at the US National Institute of Allergy and Infectious Diseases for insightful discussions, G. Mack for advice during the early stages of Simmune development and A. Meier-Schellersheim for creating Figure 2 and Supplementary Figure 1. This work was supported by the Intramural Research Program of the US National Institute of Allergy and Infectious Diseases of the National Institutes of Health.
The authors declare no competing financial interests.
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Angermann, B., Klauschen, F., Garcia, A. et al. Computational modeling of cellular signaling processes embedded into dynamic spatial contexts. Nat Methods 9, 283–289 (2012). https://doi.org/10.1038/nmeth.1861
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