Identification of a nuclear factor kappa B-dependent gene network

Abstract

Nuclear factor-kappa B (NF-kappaB) is a highly inducible transcription factor that plays an important role in the hepatic acute-phase response, innate/adaptive immunity, and cellular survival through the induction of genetic networks. The major transcriptional-activating species Rel A-NF-kappaB is a cytoplasmic complex whose nuclear translocation is controlled by its association with a family of inhibitory proteins, termed IkappaBs. Activation of NF-kappaB results in the targeted proteolysis of IkappaB, releasing NF-kappaB to enter the nucleus and bind to specific sequences in target promoters. Because the genomic actions of NF-kappaB are influenced by the stimulus applied and the promoter context/chromatin structure in which it binds, the spectrum of NF-kappaB-regulated genes has not been elucidated. We have begun to address this question, exploiting a tightly regulated cellular system expressing a nondegradable IkappaBalpha mutant that completely inhibits NF-kappaB action. High-density oligonucleotide microarrays were used to identify genetic responses in response to complex biological stimuli (viral replication) in the presence and absence of NF-kappaB. Using statistical and informatics tools, we identified two groups of NF-kappaB-dependent genes with distinct expression profiles: 1) a group with high constitutive expression whose expression levels fall in response to viral exposure and constitutive mRNA expression increases from NF-kappaB blockade, and 2) a group where constitutive expression was very low (or undetectable) and, after stimulation, expression levels strongly increased. In this group, NF-kappaB blockade inhibited the viral induction of genes. This latter cluster includes chemokines, transcriptional regulators, intracellular proteins regulating translation and proteolysis, and secreted proteins (e.g., complement components, growth factor regulators). These data reveal complexity in the genetic response to NF-kappaB and serve as a foundation for further informatics analysis to identify genetic features common to up- and downregulated NF-kappaB-dependent promoters.