Pneumologie 2013; 67 - P304
DOI: 10.1055/s-0033-1334618

The role of microRNA regulation in the early inflammatory response: miR-146a and NF-κB signaling in lung inflammation

X Lai 1, C Schulz 2, F Seifert 2, B Dolniak 3, O Wolkenhauer 1, J Vera 1, B Schmeck 2, A Sittka 2
  • 1Department of Systems Biology and Bioinformatics, University of Rostock
  • 2Department of Molecular Pulmonology/Ilung, Ugmlc, Dzl, Philipps-University Marburg; Department of Infectious Diseases and Pulmonary Medicine, Charité – University Medicine Berlin
  • 3Department of Infectious Diseases and Pulmonary Medicine, Charité – University Medicine Berlin

Inflammatory lung diseases encompass a range of conditions which can be divided into acute and chronic diseases. In some extreme cases such as pneumonia, chronic bronchitis, and lung cancer, inflammation leads to high mortality. Recent studies suggest that microRNA (miRNA) regulation plays an important role in the lung inflammatory response. Here, we investigate the role of miR-146a in the early regulation of NF-κB signaling after infection with Legionella pneumophila, a pathogen that causes severe pneumonia.

We constructed a mathematical model based on quantitative experimental data, describing the early inflammatory response after Legionella infection. Our model accounts for: i) flagellin mediated activation of the membrane Toll like receptor-5 (TLR5); ii) a number of intermediate events triggered by TLR5, which involve the signaling proteins IRAK1, TRAF6, IRAK4, and TAK1; and iii) the subsequent activation of the IKK/IκB/NF-κB and Raf1/MEK/ERK signaling pathways. Furthermore, we included equations accounting for NF-κB mediated activation of inflammatory genes like IL-8, but also the NF-κB and ERK mediated synthesis of miR-146a, a miRNA that regulates the system by translational repression of some of the protein mediators, including IRAK1, via a feedback loop. The model consists of 14 ordinary differenzial equations, with 14 state variables and 34 parameters and is validated through iterative cycles of quantitative experimentation, model calibration, and refinement.

The model can correctly capture the dynamics of experimental data. By analyzing the model, some key processes are identified that control the intensity and duration of the immune response, e.g., the negative regulation formed between miR-146a and its target is suggested to be a crucial process in the overall signaling pathway. Furthermore, the model also helps to better understand the mechanism by which miR-146a is activated by its upstream proteins.