The RNA-binding protein RC3H1 (also known as ROQUIN) promotes TNFα mRNA decay via a 3′UTR constitutive decay element (CDE). Here we applied PAR-CLIP to human RC3H1 to identify ∼3,800 mRNA targets with >16,000 binding sites. A large number of sites are distinct from the consensus CDE and revealed a structure-sequence motif with U-rich sequences embedded in hairpins. RC3H1 binds preferentially short-lived and DNA damage-induced mRNAs, indicating a role of this RNA-binding protein in the post-transcriptional regulation of the DNA damage response. Intriguingly, RC3H1 affects expression of the NF-κB pathway regulators such as IκBα and A20. RC3H1 uses ROQ and Zn-finger domains to contact a binding site in the A20 3′UTR, demonstrating a not yet recognized mode of RC3H1 binding. Knockdown of RC3H1 resulted in increased A20 protein expression, thereby interfering with IκB kinase and NF-κB activities, demonstrating that RC3H1 can modulate the activity of the IKK/NF-κB pathway.

The transcription factor NF-κB (p65/p50) plays a central role in the coordination of cellular responses by activating the transcription of numerous target genes. The precise role of the dynamics of NF-κB signalling in regulating gene expression is still an open question. Here, we show that besides external stimulation intracellular parameters can influence the dynamics of NF-κB. By applying mathematical modelling and bifurcation analyses, we show that NF-κB is capable of exhibiting different types of dynamics in response to the same stimulus. We identified the total NF-κB concentration and the IκBα transcription rate constant as two critical parameters that modulate the dynamics and the fold change of NF-κB. Both parameters might vary as a result of cell-to-cell variability. The regulation of the IκBα transcription rate constant, e.g. by co-factors, provides the possibility of regulating the NF-κB dynamics by crosstalk.

Comparing A20-feedbacks by Modular Modeling by different, equally reasonable mathematical representations in computational models. We here focus on the NF-κB signaling pathway and develop a modular modeling approach to investigate how different implementations of a negative feedback regulation impact the dynamical behavior of a computational model. Our analysis shows similarities of the models with different implementations but also reveals implementation-specific differences. The identified differences are used to design and perform informative experiments that elucidate unknown details of the regulatory feedback mechanism.

24Signaling pathways involve complex molecular interactions and are controlled by non-25 linear regulatory mechanisms. If details of regulatory mechanisms are not fully 26 elucidated, they can be implemented by different, equally reasonable mathematical 27 representations in computational models. The study presented here focusses on NF-28 κB signaling, which is regulated by negative feedbacks via IκBα and A20. A20 inhibits 29 NF-κB activation indirectly through interference with proteins that transduce the signal 30 from the TNF receptor complex to activate the IκB kinase (IKK) complex. We focus on 31 the question how different implementations of the A20 feedback impact the dynamics 32 of NF-κB. To this end, we develop a modular modeling approach that allows combining 33 previously published A20 modules with a common pathway core module. The resulting 34 models are based on a comprehensive experimental data set and therefore show 35 quantitatively comparable NF-κB dynamics. Based on defined measures for the initial 36 and long-term behavior we analyze the effects of a wide range of changes in the A20 37 feedback strength, the IκBα feedback strength and the TNFα stimulation strength on 38 NF-κB dynamics. This shows similarities between the models but also model-specific 39 differences. In particular, the A20 feedback strength and the TNFα stimulation strength 40 affect initial and long-term NF-κB concentrations differently in the analyzed models. 41 We validated our model predictions experimentally by varying TNFα concentrations 42 applied to HeLa cells. These time course data indicate that only one of the A20 43 feedback models appropriately describes the impact of A20 on the NF-κB dynamics. 44 Author summary 45 Models are abstractions of reality and simplify a complex biological process to its 46 essential components and regulations while preserving its particular spatial-temporal 3 48 implement the necessary simplifications but also to cope with missing knowledge and 49 experimental information. In consequence, biological processes have been 50 implemented by different, equally reasonable mathematical representations in 51 computational models. We here focus on the NF-κB signaling pathway and develop a 52 modular modeling approach to investigate how different implementations of a negative 53 feedback regulation impact the dynamical behavior of a computational model. Our 54 analysis shows similarities of the models with different implementations but also 55 reveals implementation-specific differences. The identified differences are used to 56 design and perform informative experiments that elucidate unknown details of the 57 regulatory feedback mechanism. 58 65 complex is activated. The IKK complex phosphorylates IκBα, marking it for 66 proteasomal degradation. Released NF-κB translocates into the nucleus and activates 67 the transcription of a number of target genes (3). Two of these are NFKBIA, encoding 68 IκBα, and TNFAIP3, encoding A20. Both proteins exhibit negative feedbacks on NF-κB 69 activation. IκBα bi...