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Comparative Study
. 2012 Mar 16:6:19.
doi: 10.1186/1752-0509-6-19.

Network motif comparison rationalizes Sec1/Munc18-SNARE regulation mechanism in exocytosis

Tian Xia  1 , Jiansong Tong, Shailendra S Rathore, Xun Gu, Julie A Dickerson
Affiliations
Comparative Study

Network motif comparison rationalizes Sec1/Munc18-SNARE regulation mechanism in exocytosis

Tian Xia et al. BMC Syst Biol. .

Abstract

Background: Network motifs, recurring subnetwork patterns, provide significant insight into the biological networks which are believed to govern cellular processes.

Methods: We present a comparative network motif experimental approach, which helps to explain complex biological phenomena and increases the understanding of biological functions at the molecular level by exploring evolutionary design principles of network motifs.

Results: Using this framework to analyze the SM (Sec1/Munc18)-SNARE (N-ethylmaleimide-sensitive factor activating protein receptor) system in exocytic membrane fusion in yeast and neurons, we find that the SM-SNARE network motifs of yeast and neurons show distinct dynamical behaviors. We identify the closed binding mode of neuronal SM (Munc18-1) and SNARE (syntaxin-1) as the key factor leading to mechanistic divergence of membrane fusion systems in yeast and neurons. We also predict that it underlies the conflicting observations in SM overexpression experiments. Furthermore, hypothesis-driven lipid mixing assays validated the prediction.

Conclusion: Therefore this study provides a new method to solve the discrepancies and to generalize the functional role of SM proteins.

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Figures

Figure 1
Figure 1
Experimental Diagram of Comparative Network Motif Design Modeling.
Figure 2
Figure 2
SM-SNARE Network motif design. (a) Formulated diagram of the yeast SSNM in exocytosis. ySyx: yS25, ySyb and ySM describe Sso1p(yeast syntaxin), Sec9p(yeast SNAP25), Snc1/2p(yeast synaptobrevin) and Sec1p(SM), respectively. The logic network diagram on the left shows the cascade-like yeast SSNM. (b) Formulated diagram of neuronal network in synaptic exocytosis, nSyx, nS25, nSyb and nSM describe syntaxin-1, SNAP25, VAMP(neuronal synaptobrevin) and Munc18-1(neuronal SM), respectively. The logic network diagram on the left shows the feedback structure with modulation in the neuronal synaptic system. (c) Formulated diagram of mutant neuronal network in synaptic exocytosis, nSyx, nS25, nSyb and nSM describe syntaxin-1, SNAP25, VAMP (neuronal synaptobrevin) and Munc18-1(neuronal SM), respectively. The logic network diagram on the left shows that the feedback structure is blocked due to mutant nSyx. These network motifs are designed by CytoModeler based on the Cytoscape platform.
Figure 3
Figure 3
Comparative in silico experiments and analyses of yeast and neuronal SM-SNARE network motifs. (a) Fusion curves of five in silico experiments for different initial concentrations of the ySM protein using the network from Figure 2a. (b) Final fusion levels of the yeast SSNM at steady state with respect to concentration of the ySM protein. (c) Fusion curves of five in silico experiments for different initial concentrations of the nSM protein using the network from Figure 2b. (d) Final fusion levels of the neuronal SSNM at steady state with respect to the concentration of the nSM protein.
Figure 4
Figure 4
In silico mutant experiments and analysis of neuronal SM-SNARE network motif. (a) Fusion curves of five in silico experiments with different initial concentrations of the nSM protein in the mutant neuronal SSNM system which eliminates the nSM(Munc18-1) binding to closed nSyx(syntaxin-1) (Figure 2c). (b) A comparison of fusion levels between the yeast SSNM, neuronal SSNM and mutant SSNM at steady state with respect to the SM protein concentration.
Figure 5
Figure 5
Prediction-driven in vitro experiments and analysis of neuronal SM-SNARE network motif. (a) and (b) lipid mixing assay of wildtype neuronal SM-SNARE system with different initial concentration configurations of Munc18-1. The result confirms the bifurcation behavior predicted by simulation experiments (shown in Figure 3) that when the concentration of Munc18-1 is equal to the concentration of Syntaxin-1 the fusion effect reaches maximum (purple line). (c) and (d) Mutant lipid mixing assay of neuronal SM-SNARE system with separately expressed SNAP2 and mutant syntaxin-1. The result of b and c confirmed that the complicated bifurcation behavior is introduced by the unique binding mode between Munc18-1 and Syntaxin-1 because the mutant system which deletes the binding mode shows a similar behavior to the yeast system without bifurcation phenomenon.
Figure 6
Figure 6
Explaining conflictions in SM overexpression experiments. (a) shows a scenario where the overexpression of SM may cause increased fusion. (b) shows a scenario where the overexpression of SM may cause decreased fusion. The bifurcation behavior of the neuronal SM-SNARE network motif provides an explanation for conflicting observations in SM protein overexpression experiments.
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References

    1. Hartwell LH, Hopfield JJ, Leibler S, Murray AW. From molecular to modular cell biology. Nature. 1999;402:C47–C52. doi: 10.1038/35011540. - DOI - PubMed
    1. Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U. Network motifs: simple building blocks of complex networks. Science. 2002;298:824–827. doi: 10.1126/science.298.5594.824. - DOI - PubMed
    1. Barabasi AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nat Rev Genet. 2004;5:101–113. doi: 10.1038/nrg1272. - DOI - PubMed
    1. Song C, Havlin S, Makse HA. Self-similarity of complex networks. Nature. 2005;433:392–395. doi: 10.1038/nature03248. - DOI - PubMed
    1. Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature. 2004;430:88–93. doi: 10.1038/nature02555. - DOI - PubMed

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