Speaker
Description
Tristetraprolin (TTP) is a messenger RNA (mRNA)-binding protein that targets pro-inflammatory mRNAs and recruits protein complexes that promote their degradation, making it a key regulator of inflammation resolution. TTP phosphorylation and activity are regulated by the mitogen-activated protein kinase (MAPK) p38 pathway, a cascade of phosphorylation events that also promotes the expression of pro-inflammatory mRNAs. This pathway is complex, involving multiple protein interactions and feedback loops, and is therefore difficult to understand intuitively.
Biological evidence highlights the therapeutic potential of TTP: in a mouse knock-in model (TTPaa), in which TTP is constitutively active, mice are highly resistant to inflammation. However, clinical trials targeting this pathway have been unsuccessful. This disconnect between compelling biological evidence and poor clinical translation indicates gaps in mechanistic understanding that must be addressed to harness the potential of TTP.
To address this, mathematical modelling and experimental biology are combined in an iterative framework. A system of ordinary differential equations is used to generate experimentally testable predictions that highlight discrepancies between theoretical and biological results, thereby deepening understanding of the pathway. In this way, the model informs experimental design, and experimental results refine the model to help identify new therapeutic strategies for chronic inflammatory disease.
