TNFα signalling primes chromatin for NF-κB binding and induces rapid and widespread nucleosome repositioning
© Diermeier et al.; licensee BioMed Central Ltd. 2014
Received: 22 July 2014
Accepted: 7 November 2014
Published: 3 December 2014
The rearrangement of nucleosomes along the DNA fiber profoundly affects gene expression, but little is known about how signalling reshapes the chromatin landscape, in three-dimensional space and over time, to allow establishment of new transcriptional programs.
Using micrococcal nuclease treatment and high-throughput sequencing, we map genome-wide changes in nucleosome positioning in primary human endothelial cells stimulated with tumour necrosis factor alpha (TNFα) - a proinflammatory cytokine that signals through nuclear factor kappa-B (NF-κB). Within 10 min, nucleosomes reposition at regions both proximal and distal to NF-κB binding sites, before the transcription factor quantitatively binds thereon. Similarly, in long TNFα-responsive genes, repositioning precedes transcription by pioneering elongating polymerases and appears to nucleate from intragenic enhancer clusters resembling super-enhancers. By 30 min, widespread repositioning throughout megabase pair-long chromosomal segments, with consequential effects on three-dimensional structure (detected using chromosome conformation capture), is seen.
Whilst nucleosome repositioning is viewed as a local phenomenon, our results point to effects occurring over multiple scales. Here, we present data in support of a TNFα-induced priming mechanism, mostly independent of NF-κB binding and/or elongating RNA polymerases, leading to a plastic network of interactions that affects DNA accessibility over large domains.
The arrangement of nucleosomes along the chromatin fibre profoundly affects genome function ,. For example, silenced genomic segments and constitutive heterochromatin contain nucleosomes positioned in high-density arrays ,,, whereas active and regulatory regions appear more disorganized and ‘open’ ,,. Although some data exist on the reorganization of the nucleosomal landscape following extra-cellular signalling , and differentiation ,, the temporally resolved dynamics of chromatin architecture remain poorly characterized.
Nucleosome positioning can be mapped genome-wide at single-nucleosome resolution using micrococcal nuclease digestion followed by sequencing (MNase-seq) ,. We applied this technique to primary human umbilical vein endothelial cells (HUVECs) stimulated with tumour necrosis factor alpha (TNFα). This potent cytokine drives the inflammatory response by signalling through the transcription factor nuclear factor kappa-B (NF-κB) ,; on phosphorylation, NF-κB translocates into nuclei, where it regulates hundreds of genes ,. Therefore, we correlated nucleosomal repositioning with genome-wide NF-κB binding (assessed by chromatin immunoprecipitation coupled to high-throughput sequencing; ChIP-seq) and gene expression (assessed by sequencing of total RNA; RNA-seq).
TNFα induces immediate widespread changes in nucleosome positioning
HUVECs grown to confluence were serum-starved (to promote synchrony), stimulated with TNFα for 0, 10 or 30 min, and treated with MNase to release mononucleosomes. The purified DNA (Additional file 1A) was deep-sequenced to obtain approximately 180 million read-pairs per time point (Figure 1A). When mapped to the reference genome (hg19), reads from two 0- and 30-min biological replicates gave comparable profiles (Additional file 1B).
Genome Ontology analysis of nucleosome-unmasked regions
10 versus 0 min TNFα stimulation
30 versus 0 min TNFα stimulation
log P -value
log P -value
TNFα induces repositioning in differentially regulated gene subsets
We next examined genes differentially regulated following a 30-min TNFα pulse. They were selected using data obtained after deep sequencing total rRNA-depleted RNA (RNA-seq; approximately 120 million read pairs per time point) and were required to change by at least ±0.6 log2-fold (that is, ±1.5-fold at 30 min relative to 0 min); constitutively expressed genes (±0.01 log2-fold) provided controls (Additional file 2A and Additional file 3). We also monitored NF-κB binding using ChIP-seq data (by targeting its p65 subunit) at 10 and 30 min post-stimulation. At 10 min, marginal binding was observed, in agreement with data showing that NF-κB translocation into the nucleus and binding to cognate sites is not quantitatively detected before 15 or 30 min, respectively (examples in Figure 1B and Additional file 1E). At 30 min, more than 80% of up-regulated genes were associated with at least one p65 peak, compared to just 10% of down-regulated ones (compared to 6% and 7% for the 10-min data; Additional file 2B).
Comparison of MNase-seq (raw) read profiles along a typical immediate-early up-regulated gene, NFKBIA, showed nucleosomes already repositioned by 10 min, and changes in nucleosome occupancy became more pronounced at 30 min, when density decreased throughout the locus as NF-κB binding increased (Figure 1B, left). By contrast, profiles on a typical down-regulated gene, LIN37, became heightened and more defined (Figure 1B, right). This held true for other up- or down-regulated genes, whilst those of constitutively expressed loci varied little (Additional file 2C).
Global changes in genic nucleosome occupancy were assessed using ‘metagene’ analyses, by aggregating profiles from all up- or down-regulated genes. In up-regulated genes, the first few nucleosomes downstream of the promoter became more precisely positioned (most likely as transcription start site (TSS)-proximal nucleosomes form well-positioned arrays ), and occupancy decreased incrementally towards the 3′ end (as nucleosome-rich exons tend to be found more 3′ ,). In down-regulated genes, occupancy increased throughout; again, little change was observed in constitutively expressed loci (Figure 1C).
Nucleosome repositioning precedes transcriptional elongation in long genes
To simplify analysis, we initially applied the PeakPredictor algorithm  to our MNase-seq data and ‘called’ single-nucleosome positions along three such long genes. As expected, TSS-proximal regions appeared progressively more depleted of nucleosome peaks (for example, in the first 10 kbp downstream of the TSS of 318-kbp EXT1, 41, 38 and 24 peaks were called at 0, 10 and 30 min, respectively; Additional file 4B). Unexpectedly, peak depletion of the same scale spread over hundreds of kilobase pairs from TSS to transcription termination site (TTS) (for example, the number of peaks throughout EXT1 fell by 12% after 30 min; Additional file 4B), and ‘MNase-on-ChIP’ verified this effect (Additional file 4C).
Of course the above effect does not accurately describe the phenomenon, as there exist no such long nucleosome-devoid stretches of DNA. Thus, we analysed MNase-seq data throughout each long gene via a custom bioinformatics pipeline to examine whether nucleosome repositioning follows RNAP elongation (as might be expected). Genes were divided into 5-kbp non-overlapping windows, and changes in each window scored relative to (background) levels of nucleosome repositioning occurring in transcriptionally inert genomic segments (see Methods). This revealed a decrease in nucleosome occupancy (hereafter termed depletion), which was evident throughout 186-kbp ALCAM and 221-kbp SAMD4A (Figure 2), as well as in 116-kbp NFKB1 and 458-kbp ZFPM2 (Additional file 5A), at both 10 and 30 min, when pioneer RNAPs had advanced for <30 and <100 kbp, respectively. This effect was reproducible between biological replicates (Additional file 5B), and profiles of down-regulated and constitutively expressed genes served as controls (Figure 2 and Additional file 5A).
NF-κΒ binding is associated with repositioning over great distances
As p65 binds both close to and in the body of many up-regulated genes (Additional file 2B), we speculated that the TNFα-driven repositioning seen throughout such genes (Figure 1C) might be nucleated from p65 bound at intragenic sites (Figure 3C illustrates one locus). Thus, of all up-regulated genes examined, 72% encompassed ≥1 p65 peak; by contrast, <10% of down-regulated genes contained a p65 peak (Additional file 7A). The physical separation between such intragenic peaks in up-regulated genes is an order of magnitude greater than those between intergenic ones (despite the small fraction of the genome occupied by protein-coding genes); thus, this group of peaks covers a substantial portion of the respective gene bodies (Additional file 7A). These results point to a focused binding of NF-κΒ, in clusters of ‘primed’ sites, within genes (even though the transcription factor might be bound at low titres), followed by nucleosome repositioning over several tens of kilobase pairs (Additional file 6B and Additional file 7B).
Multi-scale nucleosome repositioning impacts on higher-order structure
We next used the long arm of chromosome 14 as a model to study how changes in nucleosome density might affect structure at increasingly larger scales (as loci on this chromosome have been extensively studied before –). The chromosome was divided into non-overlapping windows of 25, 50 and 100 kbp, and nucleosome occupancy examined. By 10 min, alternating enriched and depleted domains were seen at all window sizes; by 30 min most of these further evolved (Additional file 8A) and depleted profiles predominated (also reproducible between replicates; Additional file 8B). In other words, a gradual spreading of nucleosome-depleted domains was observed, and this appeared to be nucleated by the hotspots seen at 10 min (many also engulfing DNase-hypersensitive sites, especially by 30 min post-stimulation; Additional file 8C).
By contrast, the EDN1 TSS formed fewer new contacts upon stimulation (of the 496 most frequent 30-min contacts 42% were also see at 0 min; Figure 4B, top). Moreover, significantly more shared contacts correlated with nucleosome-depleted windows (compared to 0- or 30-min specific ones; Figure 4B). Closer inspection of the two loci shows that contacts (in accord with obtained chromatin interaction analysis by paired-end tag sequencing data ) do not form randomly between ‘nucleosome-free’ regions, but rather share particular features (that is, NF-κB binding, H3K4me1 enrichment and transcriptional activity; Additional file 9).
We addressed the question: how does TNFα stimulation reshape the chromatin landscape as it establishes the immediate-early proinflammatory transcriptional programme? The cytokine signals through NF-κB , and one might envisage that the factor first binds in the vicinity of regulatory elements to induce repositioning of nucleosomes locally. This would then facilitate transcriptional initiation by RNA polymerase, and would in turn open up the bodies of TNFα-responsive genes as polymerases elongate through them ,. However, changes observed here cannot be reconciled with this scenario.
First, we saw hotspots of nucleosome depletion 10 min post-stimulation (Additional file 8Α), before detectable NF-κB binding to cognate sites (Additional file 6Α). Although there were approximately 1,300 NF-κB binding peaks in nucleosome-depleted windows after 30 min, most bound NF-κB was not embedded in kilobase pair-long depleted regions (Figure 3A). This also fits with the distribution of typical NF-κB motifs (5′-GGRRNNYYCC-3′): out of >550,000 sites found genome-wide, only 60,000 and 250,000 were embedded in windows depleted of nucleosomes after 10 and 30 min, respectively (with 28,000 being shared and very few being occupied; Figure 3A). It follows that NF-κB binding is highly selective; the first transcription factor complexes to enter nuclei (between 10 and 15 min) must preferentially bind to a small subset of primed domains depleted of nucleosomes, harbouring the highest affinity sites - probably within the critical enhancers that regulate the ensuing cascade and/or on particular Alu repeats . This is reminiscent of a subset of NF-κB dimers in macrophages selectively binding to already-accessible chromatin segments where partner regulators constitutively bind  - which raises the question of what the endothelial-specific NF-κB partners might be.
Second, results cannot be reconciled with the idea that transcription through nucleosomes by pioneering elongating RNAPs is solely responsible for changes in chromatin structure. Nucleosomes in long TNFα-responsive genes are repositioned throughout, well before elongating polymerases have transversed their full length (Figure 2). Then, what molecular mechanism might drive repositioning at sites many kilobase pairs away from a bound NF-κB or a pioneering polymerase? We can suggest some possibilities that might act singly, or in concert. For example, an effector other than NF-κB might be responsible for priming; then, NF-κB (and/or another effector) could induce chromatin remodelling enzymes to act throughout the surrounding locale - perhaps a chromatin loop or cluster of loops in a topological domain attached to a transcriptional hot spot . Alternatively, transcription could generate supercoiling that remodels one such loop (or cluster of loops) within a topological domain . Lastly, polymerases other than pioneers on responsive genes could drive repositioning - perhaps ones generating enhancer RNAs (like in Additional file 6B) . This is supported by the presence of NF-κB clusters bound within gene bodies at sites marked by histone marks and transcripts characteristic of enhancers; these overlap ‘super-enhancers’ previously mapped in HUVECs  that also show decreased nucleosome density post-stimulation (see examples in Figure 3C and Additional file 6B).
Third, nucleosome repositioning has traditionally been viewed as a local phenomenon, but we detect occupancy changes throughout megabase pair-long segments (see chromosomes 4 and 14 in Additional file 8). (Note that, using semi-quantitative Western blotting with antibodies targeting histones H3 and H4, we verified TNFα stimulation does not affect global histone levels; data not shown.) Using 3C-seq, we confirmed the intuition that changes in nucleosome positioning around two megabase pair-long chromosomal loci go hand-in-hand with the development of contacts in three-dimensional nuclear space. Interestingly, a subset of recorded 3C contacts - which predominantly form between regulatory cis-modules , marked by NF-κB and characteristic histone modifications (Additional file 9) - persist throughout the transition from the unstimulated to the TNFα-stimulated state (Figure 4). This is consistent with pre-looped chromatin facilitating responses to extra-cellular cues , and can now be explained also at the level of nucleosomal organization.
Collectively, our data point to TNFα triggering chromatin priming so that most nucleosomes are repositioned independently of NF-κB binding and/or polymerases elongating through responsive genes. This effect is a prelude to the ensuing proinflammatory programme, and it occurs both locally (at the gene level) as well as at considerable distances from, what have hitherto been considered, the major nucleating sites to affect large chromosomal segments. Finally, although ‘topological domains’ may constitute invariant building blocks within chromatin –, an underlying and plastic network of interactions within a domain must affect DNA accessibility to polymerases, ultimately allowing the rapid transitions that occur as different sets of genes become active and inactive and the inflammatory cascade unfolds ,. Of course, the molecular machines responsible for priming, their interplay with NF-κB, and the potential role of other factors (like histone H1 eviction or activity of topoisomerases) need be addressed in light of these findings.
HUVECs from pooled donors (Lonza, Cologne, Germany) were grown to 80% to 90% confluence in endothelial basal medium 2-MV with supplements (EBM; Lonza) and 5% foetal bovine serum (FBS); starved for 16 to 18 h in EBM +0.5% FBS; treated with TNFα (10 ng/ml; Peprotech, Hamburg, Germany); and harvested 0, 10 or 30 min post-stimulation.
Isolation of mononucleosomes, sequencing and mapping
Approximately 5 × 106 HUVECs stimulated with TNFα for 0, 10 or 30 min were digested (3 min at 37°C) with 750 units of micrococcal nuclease (MNase; Sigma-Aldrich, Seelze, Germany). Mononucleosomal DNA was isolated following separation on 1.3% agarose gels using glass beads (Qiagen, Hilden, Germany), and average fragment lengths determined using a 2100 Bioanalyzer (Agilent). Libraries were generated using the NEBNext DNA Library Prep Master Mix Kit (New England Biolabs, Ipswich, USA) and paired-end (2 × 50-bp) sequenced on a HiSeq2000 platform (Illumina, Essex, UK) to comparable depths (that is, 181, 185 and 187 million reads for 0, 10 and 30 min samples, respectively). Obtained reads were processed using the toolkits FastQC  and FASTX , mapped to hg19 using Bowtie .
Different peak-calling algorithms were applied depending on the downstream application. For Additional file 4 the Peak Predictor/GeneTrack package  was used. For motif analyses, as well as Gene and Genome Ontology profiling (Additional file 1 and Table 1), the HOMER software package  and findPeaks 3.1  were applied (adjusting fragment size to that determined using the Bioanalyzer with the following settings: −style factor –size 147 –minDist 1 –F 0 –L 0 –C 0). When comparing two or more datasets, the getDifferentialPeaks or mergePeaks scripts were used. For visualization, tag directories of mapped reads were generated and .bedGraph files produced using the makeUCSCfile (for raw reads) or pos2bed.pl (for peaks and other BED-formatted files) scripts; tracks were then visualized with the UCSC Genome browser . Both known and de novo motif analyses were performed with findMotifsGenome.pl using standard settings and the repeat-masked hg19 genome build. All peak annotations, including histograms, were generated with annotatePeaks.pl, and graphs plotted in R  with a smoothing spline of 0.2.
Thus, the smaller p(||q i ||) is, the lower the probability that the ratio ||q i || is merely due to a stochastic fluctuation of read counts.
Chromosome conformation capture
Nuclei were harvested after 0 or 30 min of TNFα stimulation, cross-linked in 1% paraformaldehyde (PFA; Electron Microscopy Science, Munich, Germany), and processed as described  using ApoI as the primary restriction endonuclease. Following sequencing on a HiSeq2000 platform (Illumina; approximately 2 × 107 reads), data were analysed using the r3Cseq pipeline . The domainogram in Figure 4 was generated using the top 167 cis-contacts on chromosome 14 (on which the viewpoint lies) using publicly available software . In brief, 3C-seq reads are made binary and relative enrichments calculated using sliding windows compared to a randomized background made up of 3,000 fragment ends. Data permutation is then used to determine a threshold of <0.01 false discovery rate (FDR); windows exceeding this threshold are scored as interacting.
Chromatin immunoprecipitation and ChIP-seq analysis
Approximately 107 HUVECs were cross-linked (using 1% PFA for 10 min, preceded by 25 min in 10 mM ethyl-glycol-bis-succinimidylsuccinate at room temperature, as described previously ) 0, 10 or 30 min after TNFα stimulation; chromatin was fragmented by sonication (Bioruptor; Diagenode, Liège, Belgium); then immunoprecipitation was carried out using a rat monoclonal against phospho-Ser2 in the C-terminal domain of the largest subunit of RNA polymerase II (3E10 ; a gift from Dirk Eick, Helmholtz Institute, Munich, Germany) or a rabbit polyclonal against the full-length p65 subunit of NF-κB (39369, Active motif) on aliquots of approximately 25 μg chromatin. Immunoprecipitated complexes were washed and eluted using the ChIP-It-Express kit (Active motif, Rixensart, Belgium).
For qPCR analysis, a Rotor-Gene 3000 cycler (Qiagen) and Platinum SYBR Green qPCR SuperMix-UDG (Invitrogen, Darmstadt, Germany) were used. Following incubation at 50°C for 2 min to activate the qPCR mix, and 95°C for 5 min to denature templates, reactions were carried out for 40 cycles at 95°C for 15 s, and 60°C for 50 s. PCR primers were designed via Primer3Plus  using qPCR settings with an optimal length of 20 to 22 nucleotides, a Tm of 62°C, targeting 100 to 200 bp. The presence of single amplimers was confirmed by melting-curve analysis, and data were analysed to obtain enrichments relative to input. P values (two-tailed) from unpaired Student’s t-tests  were considered significant when <0.05.
For deep sequencing, previous (0- and 30-min ) and newly generated (10-min) p65 ChIP-seq data were aligned to hg18 and signal peaks detected using MACS . This allowed 68, 214 and 8,583 high-confidence p65-binding events to be detected for 0, 10 and 30 min respectively (FDR ≤0.01, peak height ≥20 reads/million). Peaks were correlated to publicly available ENCODE Hidden Markov chromatin models and HUVEC ChIP-seq data (H3K27ac: GSM733691; H3K4me1: GSM733690 ,) and annotated against RefSeq genomic features (TSS, exon, intron, intergenic region).
Total RNA sequencing and analysis
Total RNA was isolated from 0.5 × 106 HUVECs stimulated with TNFα for 0, 10 or 30 min using TRIzol (Invitrogen), treated with RQ1 DNase (1 unit/μg RNA, 37°C, 45 min; Promega, Leiden, Netherlands), depleted of rRNA (RiboMinus; Epicentre, Madison, USA), chemically fragmented to approximately 350 nucleotides, and cDNA generated using random hexamers as primers (according to the True-seq protocol; Illumina). Adapters were then ligated to cDNA molecules, and libraries sequenced (Illumina HiSeq2000 platform; 100-bp paired-end reads; around 120 × 106 read-pairs per sample). Raw reads were then mapped to hg18 using TopHat  and reads aligning to RefSeq gene models were counted using the HTseq package . Statistical analysis of differentially expressed genes was performed with the DESeq Bioconductor package  (asking for >100 reads per gene, and for a >0.6, <−0.6, or ±0.01 log2 fold-change for up-regulated, down-regulated or constitutively expressed genes, respectively; Additional file 3).
HUVECs grown on coverslips etched with hydrofluoric acid were fixed with 4% PFA (Electron Microscopy Science) in phosphate-buffered saline (PBS; 20 min, 20°C), washed once in PBS (5 min, 20°C), permeabilized using 0.5% Triton X-100 in PBS (5 min, 20°C) and blocked with 1% bovine serum albumin (BSA) in PBS (Sigma-Aldrich; 45 min, 20°C). Phosphorylated (at Ser536) p65 was detected using a rabbit monoclonal antibody (1:500 dilution, 0.5% BSA in PBS; #04-1000, Millipore, Nottingham, UK) and Alexa488-conjugated donkey anti-rabbit AffinityPure F(ab’)2 Fragment (1.5 μg/ml; Jackson ImmunoResearch, Maine, USA). After DAPI counter-staining, images were collected on a Leica DMI6000 B widefield microscope and analysed using ImageJ ; nuclei were encircled, the mean intensity calculated per area, and nuclear fluorescence (arbitrary units) calculated by subtracting the background (measured as the minimum intensity in the image).
MNase-seq raw data are available at the GEO database under accession number [GEO: GSE53343], while 3C-seq, p65 ChIP-seq and total (ribo-depleted) RNA-seq data generated here can be accessed at the SRA archive under accession number [SRA: SRP044729].
chromosome conformation capture coupled to deep sequencing
bovine serum albumin
chromatin immunoprecipitation coupled to high-throughput sequencing
endothelial basal medium
foetal bovine serum
false discovery rate
micrococcal nuclease digestion followed by sequencing
nuclear factor kappa-B
sequencing of total RNA
tumour necrosis factor alpha
transcription start site
transcription termination site
We thank Karsten Rippe and Alvaro Rada-Iglesias for discussions; Vladimir Benes (EMBL, Heidelberg, Germany), Wilfred van Ijcken (Erasmus MC, Rotterdam, Netherlands) and Chris Greenman (TGAC, Norwich, UK) for sequencing the MNase-, ChIP-, 3C- and RNA-seq libraries, respectively; and Dirk Eick for the 3E10 antibody. This work was supported by the Epigensys consortium funded by the ERASysBio+/FP7 initiative via the BBSRC (PRC), the BMBF (SD, GL, GW) and the NWO (PK, FG, TAK); by a M.E.C. Booster grant from the Netherlands Genomics Institute (PK); by an SBF960 collaborative grant (GL); by CMMC intramural funding (TG, AP); and by Köln Fortune (AZ).
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