Akt phosphorylates insulin receptor substrate to limit PI3K-mediated PIP3 synthesis.

The phosphoinositide 3-kinase (PI3K)-Akt network is tightly controlled by feedback mechanisms that regulate signal flow and ensure signal fidelity. A rapid overshoot in insulin-stimulated recruitment of Akt to the plasma membrane has previously been reported, which is indicative of negative feedback operating on acute timescales. Here, we show that Akt itself engages this negative feedback by phosphorylating insulin receptor substrate (IRS) 1 and 2 on a number of residues. Phosphorylation results in the depletion of plasma membrane-localised IRS1/2, reducing the pool available for interaction with the insulin receptor. Together these events limit plasma membrane-associated PI3K and phosphatidylinositol (3,4,5)-trisphosphate (PIP3) synthesis. We identified two Akt-dependent phosphorylation sites in IRS2 at S306 (S303 in mouse) and S577 (S573 in mouse) that are key drivers of this negative feedback. These findings establish a novel mechanism by which the kinase Akt acutely controls PIP3 abundance, through post-translational modification of the IRS scaffold

Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells

CITATION: Rateitschak, K., et al. 2012. Parameter identifiability and sensitivity analysis predict targets for enhancement of STAT1 activity in pancreatic cancer and stellate cells. PLoS Computational Biology, 8(12): 1-14, doi: 10.1371/journal.pcbi.1002815.The original publication is available at http://journals.plos.org/ploscompbiolThe present work exemplifies how parameter identifiability analysis can be used to gain insights into differences in experimental systems and how uncertainty in parameter estimates can be handled. The case study, presented here, investigates interferon-gamma (IFNc) induced STAT1 signalling in two cell types that play a key role in pancreatic cancer development: pancreatic stellate and cancer cells. IFNc inhibits the growth for both types of cells and may be prototypic of agents that simultaneously hit cancer and stroma cells. We combined time-course experiments with mathematical modelling to focus on the common situation in which variations between profiles of experimental time series, from different cell types, are observed. To understand how biochemical reactions are causing the observed variations, we performed a parameter identifiability analysis. We successfully identified reactions that differ in pancreatic stellate cells and cancer cells, by comparing confidence intervals of parameter value estimates and the variability of model trajectories. Our analysis shows that useful information can also be obtained from nonidentifiable parameters. For the prediction of potential therapeutic targets we studied the consequences of uncertainty in the values of identifiable and nonidentifiable parameters. Interestingly, the sensitivity of model variables is robust against parameter variations and against differences between IFNc induced STAT1 signalling in pancreatic stellate and cancer cells. This provides the basis for a prediction of therapeutic targets that are valid for both cell types.Financial support: Bundesministerium für Bildung und Forschung through the FORSYS partner program (grant number 0315255 to KR); Deutsche Forschunggemeinschaft (to RJ); Interdisciplinary Faculty of the University of Rostock: Grant to FW; Helmholtz Society: Support to OW.Publisher's versio

Mathematical Modelling of Inter- and Intracellular Signal Transduction: The Regulatory Role of Multisite Interactions

Signalling processes regulate various aspects of living cells via modulation of protein activity. The interactions between the signalling proteins can occur at single or multiple sites. Although single site protein interactions are relatively easy to understand, these rarely occur in living systems. It is therefore important to investigate multisite interactions. Despite the recent progress in experimental studies, the underlying molecular mechanisms and molecular functions of the multisite interactions are still not clear and therefore require systems approaches for deeper understanding, for example to understand how the system will react to perturbation of one of its components. The examples of the molecular functions that are studied in this thesis are: kinetics of multisite calcium binding to proteins such as calmodulin (CaM), multisite phosphorylation of interferon regulatory factor 5 (IRF-5) and signal transducers and activators of transcription (STATs). We also study the role of STATs in the overall immune response and in T cell phenotype switching as well as multisite phosphorylation of high osmolarity glycerol factor 1 (Hog1) in mitogen activated protein kinase (MAPK) cascade during the adaptation of Candida glabrata to osmotic stress. In this thesis, these examples are studied using the systems approach in the context of human diseases: cancer, candidiasis, immunity-related pathologies such as rheumatoid arthritis, inflammatory bowel disease and systemic lupus erythematosus. We discuss potential therapeutic implications of the proposed models in these diseases. The predictions of the models developed in this thesis are supported by the experimental data and propose possible mechanisms of the multisite interactions involved in the cellular regulation