- Poster presentation
- Open Access
The 4-D landscape of the inflammatory response
© Papantonis; licensee BioMed Central Ltd. 2013
- Published: 18 March 2013
- Human Endothelial Cell
- Inflammatory Cascade
- Enhancer Activity
- Chromosomal Domain
- Chromosome Conformation Capture
It is widely accepted that chromatin ‘responds’ to physiological cues via protein:DNA interactions and nucleosome rearrangement [1, 2], and that transcription plays a key role in its higher-order organization . What remains elusive is how the nuclear landscape reshapes, in 3-D space and time, to facilitate such responses to unfold.
We add tumour necrosis factor α (TNFα) to primary human endothelial cells and induce the inflammatory cascade; this is orchestrated by the transcription factor NF-κB . We monitor the response for 0-85 min post-induction using ChIP nucleosome-positioning studies, and chromosome conformation capture, all coupled to next-generation sequencing. We also apply a new approach, where the isolation of ‘transcription factories’  is followed by RNA-seq to uncover nascent transcriptomes.
First, we redefine early, intermediate, late, and oscillating TNFα-responsive genes, based on changing levels of nascent RNA. We then examine how these co-associate in specialized ‘factories’, some of which further specialize in transcribing responsive non-coding genes . Contacts are driven by NF-κB, and evolve as genes are differentially turned on and off over time. We also monitor nucleosome rearrangements genome-wide; these correlate with poised promoters before induction, and with nucleosome depletion as a result of transcriptional activation, NF-κB binding, enhancer activity in TNFα-stimulated chromosomal domains.
We provide evidence for a prompt, within <30 min, reshaping of the genome in response to inflammation. This entails de novo associations of co-regulated coding and non-coding sequences in specialized 3-D networks that evolve over time, as well as extensive nucleosome depletion. We expect all extracellular cues to signal through analogous specialized networks and reassess our parsimonious model  for transcriptional regulation accordingly.
This work is supported by the BBSRC via the ERASysBio+/FP7 initiative.
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