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Lost in presumption: stochastic reactions in spatial models

Nature Methods volume 9, pages 1163–1166 (2012)Cite this article

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Physical modeling is increasingly important for generating insights into intracellular processes. We describe situations in which combined spatial and stochastic aspects of chemical reactions are needed to capture the relevant dynamics of biochemical systems.

Consider a situation in which intracellular spatial oscillations are observed for a protein of interest. Some of the protein's biochemical interactions and their parameters have been characterized, so it is straightforward to draw a cartoon showing how the components may interact. However, on the basis of the cartoon alone, it is very hard to discern whether the components and their interactions are sufficient and necessary to explain the observed oscillation phenomenon. The reason is that the intracellular reactions are nonlinear, noisy, out of equilibrium and dependent on local concentrations, which can make the outcome of intracellular interactions highly nonintuitive. One way to resolve this problem is to make a quantitative description—that is, a mathematical model—of the cartoon. A well-formulated model makes it possible to identify whether the reactions in the cartoon are sufficient to give rise to the observed phenotype and, if so, under which conditions. Building such a mathematical model is not straightforward, however, especially because it is rarely obvious a priori which level of physical detail is required to capture the biochemical behavior of the cellular process.

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Figure 1: Different levels of quantitative modeling frameworks for intracellular chemistry.
Figure 2: Examples of combined spatial and stochastic effects in three simple systems.

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Acknowledgements

This work was supported by the Swedish Research Council (VR), Knut and Alice Wallenberg Foundation (KAW) and European Research Council (ERC). We are grateful for comments on the text from I. Barkefors.

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Authors and Affiliations

  1. Otto G. Berg and Johan Elf are in the Department of Cell and Molecular Biology, Anel Mahmutovic, David Fange, Science for Life Laboratory, Uppsala University, Sweden.,

    Anel Mahmutovic, David Fange, Otto G Berg & Johan Elf

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  1. Anel Mahmutovic
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  2. David Fange
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  3. Otto G Berg
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Correspondence to Johan Elf.

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Mahmutovic, A., Fange, D., Berg, O. et al. Lost in presumption: stochastic reactions in spatial models. Nat Methods 9, 1163–1166 (2012). https://doi.org/10.1038/nmeth.2253

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