Analysing the Role of UVB-Induced Translational Inhibition and PP2Ac Deactivation in NF-κB Signalling Using a Minimal Mathematical Model

Abstract

Activation of nuclear factor κB (NF-κB) by interleukin-1β (IL-1) usually results in an anti-apoptotic activity that is rapidly terminated by a negative feedback loop involving NF-κB dependent resynthesis of its own inhibitor IκBα. However, apoptosis induced by ultraviolet B radiation (UVB) is not attenuated, but significantly enhanced by co-stimulation with IL-1 in human epithelial cells. Under these conditions NF-κB remains constitutively active and turns into a pro-apoptotic factor by selectively repressing anti-apoptotic genes. Two different mechanisms have been separately proposed to explain UV-induced lack of IκBα recurrence: global translational inhibition as well as deactivation of the Ser/Thr phosphatase PP2Ac. Using mathematical modelling, we show that the systems behaviour requires a combination of both mechanisms, and we quantify their contribution in different settings. A mathematical model including both mechanisms is developed and fitted to various experimental data sets. A comparison of the model results and predictions with model variants lacking one of the mechanisms shows that both mechanisms are present in our experimental setting. The model is successfully validated by the prediction of independent data. Weak constitutive IKKβ phosphorylation is shown to be a decisive process in IκBα degradation induced by UVB stimulation alone, but irrelevant for (co-)stimulations with IL-1. In silico knockout experiments show that translational inhibition is predominantly responsible for lack of IκBα recurrence following IL-1+UVB stimulation. In case of UVB stimulation alone, cooperation of both processes causes the observed decrease of IκBα. This shows that the processes leading to activation of transcription factor NF-κB upon stimulation with ultraviolet B radiation with and without interleukin-1 costimulation are more complex than previously thought, involving both a cross talk of UVB induced translational inhibition and PP2Ac deactivation. The importance of each of the mechanisms depends on the specific cellular setting.

Identification of New IκBα Complexes by an Iterative Experimental and Mathematical Modeling Approach

“…Based on our previous NFκB signaling model [15] we generated an extended mathematical model (variant M-1, Fig. 4A ).…”

“…Successful parameter fitting was performed based on a huge variety of experimental data comprising multiple stimulations: OVA−, ActD−, ActD+OVA, CHX+OVA-stimulation ( Fig. 1 – 3 ), IL-1 + OVA-stimulation [18] , as well as data describing IκBα depletion upon IL-1−, UVB−, IL-1+UVB−, CHX−, IL-1+UVB+MG132-stimulation collected before [15] , [19] . All experimental data could be fitted well ( Fig.…”

“…Using a systems biological approach we could show that not only PP2A inactivation but also global translational inhibition appeared to be involved in preventing IκBα recurrence. Above this, translational inhibition was shown to induce IκBα depletion in cells irradiated with UVB alone, indicating both mechanisms to individually mediate UVB-dependent responses [15] , [19] .…”

“…Since dysregulation of NFκB plays a major role in the development of various diseases, a number of mathematical models have been implemented to analyze the non-linear dynamical behavior of this regulatory network [7] , [8] . These models contributed to the analysis of the role of negative feedback loops [9] – [11] , the description of the overall input-output behavior of the pathways [12] – [14] , the understanding of the integration from multiple input signals [14] , [15] , as well as to the identification of sensitive parameters [16] . However, the pattern of NFκB-induced gene expression may significantly change depending on the cell type, the intracellular protein-protein interaction and the physiological context.…”

Evaluating Strategies to Normalise Biological Replicates of Western Blot Data

“…Thus the biological variability of the reference condition influences the variability of the normalised data. The second normalisation category we consider is normalisation by sum ( Figure 1B ), where the data on a blot is divided by the sum of the data on the same blot [14] , or equivalently the data is scaled such that the average is the same across blots [15] , [16] . It should be noted that in contrast with the analogous normalisation used in microarrays (scaling methods), in this case the sum is not assumed to be a constant.…”