Cell Reports (Feb 2020)

Dissecting the Regulatory Strategies of NF-κB RelA Target Genes in the Inflammatory Response Reveals Differential Transactivation Logics

  • Kim A. Ngo,
  • Kensei Kishimoto,
  • Jeremy Davis-Turak,
  • Aditya Pimplaskar,
  • Zhang Cheng,
  • Roberto Spreafico,
  • Emily Y. Chen,
  • Amy Tam,
  • Gourisankar Ghosh,
  • Simon Mitchell,
  • Alexander Hoffmann

Journal volume & issue
Vol. 30, no. 8
pp. 2758 – 2775.e6

Abstract

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Summary: Nuclear factor κB (NF-κB) RelA is the potent transcriptional activator of inflammatory response genes. We stringently defined a list of direct RelA target genes by integrating physical (chromatin immunoprecipitation sequencing [ChIP-seq]) and functional (RNA sequencing [RNA-seq] in knockouts) datasets. We then dissected each gene’s regulatory strategy by testing RelA variants in a primary-cell genetic-complementation assay. All endogenous target genes require RelA to make DNA-base-specific contacts, and none are activatable by the DNA binding domain alone. However, endogenous target genes differ widely in how they employ the two transactivation domains. Through model-aided analysis of the dynamic time-course data, we reveal the gene-specific synergy and redundancy of TA1 and TA2. Given that post-translational modifications control TA1 activity and intrinsic affinity for coactivators determines TA2 activity, the differential TA logics suggests context-dependent versus context-independent control of endogenous RelA-target genes. Although some inflammatory initiators appear to require co-stimulatory TA1 activation, inflammatory resolvers are a part of the NF-κB RelA core response. : Ngo et al. developed a genetic complementation system for NF-κB RelA that reveals that NF-κB target-gene selection requires high-affinity RelA binding and transcriptional activation domains for gene induction. The synergistic and redundant functions of two transactivation domains define pro-inflammatory and inflammation-response genes. Keywords: NF-κB, NF-kappaB, inflammatory response, immune response, transcriptional activation, gene regulatory strategies, transcriptional synergy, mathematical modeling, systems biology, structure-function analysis