Substrate complex competition is a regulatory motif that allows NFκB RelA to license but not amplify NFκB RelB

Abstract

Signaling pathways often share molecular components, tying the activity of one pathway to the functioning of another. In the NFκB signaling system, distinct kinases mediate inflammatory and developmental signaling via RelA and RelB, respectively. Although the substrates of the developmental, so-called noncanonical, pathway are induced by inflammatory/canonical signaling, crosstalk is limited. Through dynamical systems modeling, we identified the underlying regulatory mechanism. We found that as the substrate of the noncanonical kinase NIK, the nfkb2 gene product p100, transitions from a monomer to a multimeric complex, it may compete with and inhibit p100 processing to the active p52. Although multimeric complexes of p100 (IκBδ) are known to inhibit preexisting RelA:p50 through sequestration, here we report that p100 complexes can inhibit the enzymatic formation of RelB:p52. We show that the dose-response systems properties of this complex substrate competition motif are poorly accounted for by standard Michaelis-Menten kinetics, but require more detailed mass action formulations. In sum, although tonic inflammatory signaling is required for adequate expression of the noncanonical pathway precursors, the substrate complex competition motif identified here can prevent amplification of the active RelB:p52 dimer in elevated inflammatory conditions to ensure reliable RelB-dependent developmental signaling independent of inflammatory context.NFκB canonical pathway | NFκB noncanonical pathway | inflammation | crosstalk | immune development

The NF-κB multidimer system model: A knowledge base to explore diverse biological contexts

“…Furthermore, due to the abundance of IκBδ in MYD88 L265P mutant simulations, RelB:p52 is slightly reduced due to "substrate complex competition" (40). Together, these simulations predict that Myd88 L265P may unlock crosstalk from noncanonical pathway activation to canonical cReland RelA-containing NF-κB dimers.…”

“…These studies suggest that whereas RelB activation is regulated by basal RelA activity, p100 synthesis induced by RelA activation is a critical determinant of activation of the noncanonical pathway (6). Despite this substantial potential for crosstalk, competition between the roles of NIK in p52 processing and p100 release limits the effect of canonical signaling on the noncanonical NF-κB pathway in inflammatory environments (40). Pathway insulation may also be mediated by other, receptor-proximal mechanisms (13).…”

NF-kB and the CLL microenvironment

“…Genes that encode non-canonical pathway components p100 and RelB are induced by canonical pathway activity ( 18 ), unprocessed p100 can inhibit canonical NF-κB dimers rendering them responsive to non-canonical pathway activity ( 19 ), and NF-κB proteins from both pathways compete to form dimers ( 20 ). The prevailing direction of crosstalk in non-malignant B cells is non-canonical activity inducing canonical dimers, as canonical pathway activity does not induce RelB:p52 ( 19 , 21 ). The magnitude and functional significance of this crosstalk in CLL is not known and likely dependent on the microenvironmental context.…”

Diverse cell stimulation kinetics identify predictive signal transduction models

“…Signaling pathways are common in all eukaryotes and play key roles in cellular responses and function under a diverse range of different stimulations (Hatzivassiliou et al, 2010). However, mutations in these pathways can alter signaling dynamics and can contribute to many human diseases (Cildir et al, 2016;Hanahan and Weinberg, 2000;Logan and Nusse, 2004;Mitchell and Hoffmann, 2019;Suarez-Lopez et al, 2018). Therefore, understanding and predicting signal transduction network behavior will be a critical step to identify hidden regulatory mechanisms, distinguish between proteins and reaction rates that are sensitive to kinetic stimulations, and to detect and treat abnormal regulation that occurs in a large number of human diseases (Cildir et al, 2016;Hanahan and Weinberg, 2000;Logan and Nusse, 2004;Mitchell and Hoffmann, 2019;Suarez-Lopez et al, 2018).…”

“…A key obstacle that prevents predictive cell signaling models is the gross mismatch between the preponderance of biological complexity and the sparsity of quantitative experimental data (Oltvai and Barabási, 2002). Specifically, cell signal transduction networks are notoriously complicated (Campbell et al, 1998;Hanahan and Weinberg, 2000), yet experimental analyses of their dynamics often capture only a few signaling proteins at only a few time points during cellular responses (Kingsmore, 2006;Mitchell and Hoffmann, 2019;Sorre et al, 2014). As a result, most current mechanistic models of signal transduction pathways are too complex and poorly constrained to provide predictive power, while current data-driven models are often too simple to extend beyond the most basic aspects of biological reality (Csete and Doyle, 2002;Klipp et al, 2005;Schoeberl et al, 2002).…”