Single TNFα trimers mediating NF-κB activation: Stochastic robustness of NF-κB signaling

Tomasz Lipniacki, Krzysztof Puszynski, Pawel Paszek, Allan R. Brasier, Marek Kimmel

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Background: The NF-κB regulatory network controls innate immune response by transducing variety of pathogen-derived and cytokine stimuli into well defined single-cell gene regulatory events. Results: We analyze the network by means of the model combining a deterministic description for molecular species with large cellular concentrations with two classes of stochastic switches: cell-surface receptor activation by TNFα ligand, and IκBα and A20 genes activation by NF-κB molecules. Both stochastic switches are associated with amplification pathways capable of translating single molecular events into tens of thousands of synthesized or degraded proteins. Here, we show that at a low TNFα dose only a fraction of cells are activated, but in these activated cells the amplification mechanisms assure that the amplitude of NF-κB nuclear translocation remains above a threshold. Similarly, the lower nuclear NF-κB concentration only reduces the probability of gene activation, but does not reduce gene expression of those responding. Conclusion: These two effects provide a particular stochastic robustness in cell regulation, allowing cells to respond differently to the same stimuli, but causing their individual responses to be unequivocal. Both effects are likely to be crucial in the early immune response: Diversity in cell responses causes that the tissue defense is harder to overcome by relatively simple programs coded in viruses and other pathogens. The more focused single-cell responses help cells to choose their individual fates such as apoptosis or proliferation. The model supports the hypothesis that binding of single TNFα ligands is sufficient to induce massive NF-κB translocation and activation of NF-κB dependent genes. © 2007 Lipniacki et al; licensee BioMed Central Ltd.
    Original languageEnglish
    Article number376
    JournalBMC Bioinformatics
    Volume8
    DOIs
    Publication statusPublished - 9 Oct 2007

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