Fig. 5: Distinct regulatory mechanisms of NFκB target genes depending on their response time.

Diagram of the distinct transcription regulatory mechanisms that characterizes each TNF-induced NFκB target gene cluster. Mean fold change in nuclear NFκB abundance of two biological replicates in Ctrl and siIκBα were interpolated to every second (same method used in mathematical modeling) and were max-normalized from 0 to 1 together, shown as line graphs in the top panel. The dots indicate the data from fixed-cell immunofluorescence experiments. The bottom panel shows the schematic curves of the expression patterns of ERGs, IRGs, and DRGs in subcluster 2. Despite the persistent pattern of nuclear NFκB abundance in siIκBα, post-induction repression was observed for the ERGs, and model v4 was the most effective model to recapitulate post-induction repression and reduced expression. For the IRGs, the 3-state cycle model was the most effective model, and for the DRGs, the simple model was the most effective model. The complexity of the transcription regulatory mechanisms increases as the response time of transcription decreases. Inflammation and cancer-related JUNB and KLF10, respectively, showed a transient fold change in expression, indicating that post-induction repression mechanism safeguards gene expression from overproduction, protecting from inflammatory diseases and tumor progression.