Deciphering the quantitative relationship between NRF2 and SRXN1 through semi-mechanistic computational modeling

Abstract

Nuclear factor erythroid 2-related factor 2 (NRF2) plays a vital role in the regulation of various antioxidant response element (ARE) genes, which control physiological processes such as oxidative stress, autophagy, proliferation and apoptosis to maintain cellular homeostasis. It is not understood in detail how the NRF2 program acquires its flexibility with respect to regulation of its downstream targets. Various NRF2 binding partners and cofactors specific to ARE genes are involved in this regulation, and are potentially condition-specific (e.g., type of stressor) and dependent on non-canonical signaling pathways (i.e., crosstalk). Here, we explored the quantitative relationship between NRF2 and sulfiredoxin 1 (SRXN1), a bona fide key NRF2 target gene. We developed a semi-mechanistic mathematical model based on time course experimental data of NRF2 and SRXN1 protein expression in HepG2 cells following single or repeated exposure to NRF2 activating soft electrophiles (sulforaphane, andrographolide, ethacrynic acid or CDDO-me) at a wide concentration range. We showed that a nonlinear mixed effect modeling approach with partially hierarchical parameters accurately captures the observed experimental dynamics. Our analysis highlights that NRF2 requires a cofactor or post-translational modification to regulate its activity as a transcription factor. Moreover, this modulation of the transcription factor activity of NRF2 is time-, compound- and exposure scenario specific. We conclude that a complete understanding of NRF2-mediated ARE genes activation requires detailed dynamic information on NRF2 binding partners and cofactors.