CBP-IDRs regulate acetylation and gene expression

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Gelder , View ORCID Profile Nicola A. Carruthers , View ORCID Profile Grace Gilbert , View ORCID Profile Laura J. Harrison , View ORCID Profile Brychan V. Evans , Thomas I. Evans , View ORCID Profile Sophie S. Ball , View ORCID Profile Mark Dunning , View ORCID Profile Timothy D. Craggs , View ORCID Profile Alison E. Twelvetrees , View ORCID Profile Daniel A. Bose doi: https://doi.org/10.1101/2024.06.04.597392 Katie L. Gelder 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. 5 Nucleic Acids Institute, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Katie L. Gelder Nicola A. Carruthers 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Nicola A. Carruthers Grace Gilbert 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. 6 Neuroscience Institute, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Grace Gilbert Laura J. Harrison 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Laura J. Harrison Brychan V. Evans 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. 5 Nucleic Acids Institute, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Brychan V. Evans Thomas I. Evans 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sophie S. Ball 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sophie S. Ball Mark Dunning 7 Sheffield Bioinformatics Core, Faculty of Health, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Mark Dunning Timothy D. Craggs 3 Department of Chemistry, School of Mathematical and Physical Sciences, Faculty of Science, The University of Sheffield , Dainton Building, Brook Hill, S3 7HF, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. 5 Nucleic Acids Institute, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Timothy D. Craggs Alison E. Twelvetrees 2 Division of Neuroscience, The School of Medicine and Population Health, Faculty of Health, The University of Sheffield , Glossop Road, Sheffield, S10 2HQ, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. 6 Neuroscience Institute, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Alison E. Twelvetrees Daniel A. Bose 1 Molecular and Cellular Biology, School of Biosciences, Faculty of Science, The University of Sheffield , Firth Court, Western Bank, Sheffield S10 2TN, UK 4 Centre for Single Molecule Biology (SM@SH), The University of Sheffield. 5 Nucleic Acids Institute, The University of Sheffield. Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Daniel A. Bose For correspondence: d.bose{at}sheffield.ac.uk Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Intrinsically disordered regions (IDRs) have emerged as crucial regulators of protein function, allowing proteins to sense and respond to their environment. Creb binding protein (CBP) and EP300 (p300) are transcription coactivators that regulate gene expression in multicellular organisms, following their recruitment to cis -regulatory elements. CBP and p300 contain large IDRs, however little is known about how these different IDRs work together to regulate CBP function. Here, we show that CBP-IDRs cooperate to control different aspects of CBP behaviour in the nucleus, by regulating the properties of fluid-like condensates formed by endogenous CBP. We show how IDRs with different sequence properties make unique contributions to CBP behaviour by establishing a balance between positive and negative regulation of CBP condensates. These conflicting interactions are functionally important, shaping CBPs response to factors such as lysine acetylation, that influence condensate formation. When disrupted, regulatory CBP-IDRs change how CBP interacts with chromatin, alter patterns of CBP-dependent histone acetylation and change gene expression. Together, our work highlights how IDRs with different sequences, spatially segregated in the same protein, can cooperate to shape protein function. Introduction Intrinsically Disordered Regions (IDRs) are amino acid sequences that regulate many biological functions despite lacking stable secondary and tertiary structures(van der Lee et al. 2014; Holehouse and Kragelund 2023). IDRs mediate specific and non-specific interactions between biomolecules and control the formation and behaviour of biomolecular condensates. Functionally important regions in IDRs can be defined by patterns of amino acid properties or compositional biases 1 , 2 . Their ability to adopt multiple conformations means that IDRs are responsive to their interactions and environmental context 3 , 4 . Despite an increasing understanding of the rules which govern these processes, how the different properties of IDRs are combined in the same protein to generate specific functions is still poorly understood. Creb binding protein (CBP) and its paralog EP300 (p300) are histone acetyltransferases (HATs) essential for shaping gene expression from cis -regulatory elements (CREs). By combining a structured catalytic HAT domain with large IDRs, CBP and p300 integrate HAT activity with the conformational plasticity needed to interact with diverse transcription factors (TFs) at CREs. CBP and p300 finely balance gene transcription by acting in several key ways. They control the strength of transcription by mediating lysine acetylation on histones (e.g., H3K27ac, H3K18ac, H3K122ac) 5 – 8 and transcription factors (TFs) 9 . Additionally, they contribute to RNA Polymerase II (PolII) recruitment to maintain promoter-proximal pausing 10 – 12 and form biomolecular condensates to regulate transcriptional bursting 11 , 13 , 14 . Intrinsically Disordered Regions (IDRs) and condensates are central to many of these processes. Firstly, binding to TFs is mediated by a combination of structured binding domains and IDRs, many of which undergo ‘coupled folding and binding’ with TFs 15 – 20 . Secondly, HAT activity is regulated by the autoregulatory loop (CBP AL ), an IDR insertion in the HAT domain that regulates enzymatic activity by blocking substrate binding to the active site 21 . CBP AL undergoes autoacetylation and binds to non-coding enhancer RNAs (eRNAs), both of which displace it from the active site to stimulate activity 21 – 25 21 , 22 , 26 . p300 HAT activity is decreased by crowding reagents and when condensate formation is triggered in vitro 27 , 28 . Conversely, formation of CBP and p300 condensates driven by the disordered transactivation domains of TFs in cells increased acetylation across the genome 11 , while TF binding to regions outside the HAT domain in CBP have been shown to stimulate or inhibit its HAT activity 29 . In combination, this suggests that CBP functions are highly dependent on interactions with its environment, and underlines the importance of IDRs for this process. Understanding how multiple IDRs with different sequence properties regulate functions when combined in the same protein remains a significant challenge. This is particularly relevant for CBP and p300, where multiple IDRs mediate diverse biological processes 11 , 19 , 30 . To address this question, we examined how distinct IDRs within CBP (CBP-IDRs) work together to regulate CBP behaviour, by systematically characterising the impact of these IDRs on CBP’s function within cells. We found that different IDRs play very different roles. Two adjacent C-terminal IDRs with different amino acid compositions and sequence patterning together allow CBP to respond to other factors that regulate condensates, such as acetylation. When disrupted, these IDRs caused changes in the behaviour of CBP condensates, including changing how they respond to lysine acetylation, and altered CBP’s chromatin localisation, histone acetylation and gene expression. Our results uncover new and unexpected functional roles for CBP-IDRs with different sequence properties, and highlight how intramolecular cooperation between IDRs can shape protein behaviour. Results CBP forms fluid-like condensates in the nucleus To validate the formation of CBP condensates, we imaged endogenous CBP by immunofluorescence (IF) in HEK293T cells, revealing distinct nuclear puncta consistent with previous observations 31 – 34 ( Figure 1A ). To uncover the behaviour of these puncta, we introduced an in-frame HaloTag to the C-terminus of endogenous CBP (CBP-Halo). PCR from genomic DNA confirmed heterozygous insertion (Figure S1A-B) and we confirmed near-endogenous expression levels by RT-qPCR (Figure S1C) and western blotting ( Figure 1B ). To confirm that CBP-Halo can also form endogenous puncta, we carried out live-cell imaging using the fluorescent ligand TMR to label the HaloTag (CBP-Halo TMR ). CBP-Halo TMR puncta were only observable in CBP-Halo HEK293T cells upon addition of TMR ( Figure 1C ). Download figure Open in new tab Figure 1: CBP forms fluid-like puncta in the nucleus. A) Immunofluorescence of CBP in HEK293T cells; Scale bars: 10 μm. B) Western blot for CBP and HaloTag in HEK293T cells and CBP-Halo HEK293T cells. C) Confocal microscopy in fixed HEK293T and CBP-Halo HEK293T cells using the fluorescent Halo ligand TMR (CBP-Halo TMR ); Scale bars: 10 μm. D) Lattice light sheet microcopy of endogenous CBP-Halo TMR condensates; Single plane images of endogenous CBP-Halo including merged image of Z plane, X/Z and Y/Z planes. Scale bar: 5 µm. E) Still images from Supplementary Movie 1 showing the dynamic behaviour of CBP-Halo condensates. Boxes indicate regions enlarged in the lower panel; arrows highlight representative dynamic condensates; Scale bars: 10 μm. F-G) FRAP of CBP-Halo condensates. F) Still images of live cell confocal microscopy showing FRAP of endogenous CBP-Halo JF549 . Scale bars: 10 μm; G) FRAP curves for endogenous CBP-Halo JF549 . Data was collected for 32 individual nuclei, and FRAP curves were calculated for 7 condensates where the bleached area did not diffuse away from the focal plane during the recovery period. Grey shading highlights imaging pre-bleach; Green line denotes bleaching. Still images from Supplementary Movie 2 H) Domain map and predicted intrinsic disorder of full length CBP wt using: DISOPRED3 93 (Top); PONDR 37 , (bottom). Positions of CBP-IDRs (CBP IDR1-7 , CBP AL and CBP CFID ) with their domain boundaries predicted using PONDR, and structured CBP domains are highlighted. IDRs that were predicted but not tested are indicated in grey. I) Live-cell confocal microscopy images showing the different behaviours of CBP IDR6 and CBP IDR7 in the OptoDroplet assay. Cells were imaged for 200s following exposure to blue light. Dashed box highlights the enlarged region. Scale bars: 10 μm J) Fold change in the calculated SD of the grey values for defined individual nuclei following blue light stimulation. Diffuse signal should have a low SD, while strong changes in intensity due to condensate formation should have a high SD. Grey shading highlights the 30 second window used to calculate the initial rate of change. Bars represent mean ± s.e.m, n=3. K) Initial rate of change over the first 30 seconds following blue light exposure. AL, Autoregulatory Loop; –ve, Opto-NLS negative control. Bars represent mean ± s.e.m; significant p values are reported (ns, not significant), n=3. Next, we used lattice light sheet microscopy to visualise the spatial organisation of CBP puncta ( Figure 1D ). CBP-Halo formed an average of 27.9 condensates/nucleus and we observed a variation in the size and integrated intensity density (IID) of observable puncta, with a mean volume of 33 ± 14.6 µm 3 and an IID of 835.6 ± 132.8. Importantly, CBP-Halo TMR condensates demonstrated hallmarks of fluid-like behaviour, as they were able to fuse and disperse over the 2s imaging period in live-cell confocal microscopy ( Figure 1E & Supplementary Movie 1). We next carried out Fluorescence Recovery After Photobleaching (FRAP) on endogenous CBP using Janelia Fluor Ⓡ 549 Halo ligand (CBP-Halo JF549 ), which showed that fluorescent signal recovered to ∼50% its pre-bleach levels after 30s, and to ∼90% over a 60s timeframe following photobleaching ( Figure 1F-G & Supplementary Movie 2). Together, these data clearly establish that endogenous CBP condensates have fluid-like behaviour in their native nuclear environment. IDRs in CBP have distinct abilities to form condensates Full length CBP wt is predicted to be ∼65% disordered ( Figure 1H ) 19 . AlphaFold2 predictions of CBP wt show structured domains interspersed with large disordered regions (Figure S1D) 35 . To test how these regions regulate CBP’s function, we identified nine IDRs for further analysis, using a threshold of 50 consecutive amino acids with a predicted disorder >50% (CBP IDR1-IDR7 , Figure 1H ) 36 in PONDR 37 to define IDR boundaries. We also tested the CBP:FUS interaction domain (CBP CFID ), a region previously shown to bind to Fused-in-sarcoma (FUS) 11 , 38 – 41 which comprises two identified IDRs (CBP IDR6 and CBP IDR7 ) and the Nuclear coactivator binding domain (CBP NCBD ), which binds to TFs 15 , 17 . Finally, we included CBP AL , an IDR in the HAT domain important for regulating CBP activity via acetylation and RNA binding ( Figure 1H ) 21 , 22 , 28 , 42 . The behaviour of IDRs is governed by non-random amino acid compositions and non-random patterning of amino acids. To uncover compositional and sequence biases in CBP-IDRs, we used NARDINI+, which compares the enrichment and depletion of sequence features of known importance for IDR behaviour, to the distribution of that feature in all human IDR-containing proteins 43 , 44 . Analysis with NARDINI+ revealed a number of sequence features that were enriched or depleted in specific CBP-IDRs (Figure S1E). For example, CBP IDR7 was enriched for glutamine residues and glutamine patches, reflecting the 18-residue polyQ region (residues 2199-2216) and depleted for hydrophobic residue pairs, while CBP AL was enriched for asparagine, lysine patches and positive/negative residue pairs. In contrast, CBP IDR4 and CBP IDR6 had an elevated ratio of Arginine and Lysine residues, as well as a higher fraction of proline residues and an increased propensity to adopt polyproline II conformations 45 , consistent with previous NMR studies 46 . As these factors affect biomolecular condensates 47 , we tested the ability of each CBP-IDR to form condensates in HEK293T cells using the OptoDroplet system, which drives condensate formation through homotypic interactions mediated primarily by self-associating IDRs 36 , 39 . Candidate IDRs and controls were fused to the photoactivatable Photolyase homology region of Cry2 (Cry2PHR) and an SV40 nuclear localization sequence (NLS) to control phase transitions in the nucleus (Figure S1F). Following exposure to blue light, CBP-IDRs with strong condensate forming properties (e.g CBP IDR7 ) formed defined puncta, while IDRs unable to form condensates (e.g CBP IDR6 ) failed to form puncta ( Figure 1I & S1G). To quantify differences between CBP-IDRs, we measured the standard deviation (SD) of intensities within treated nuclei: as condensate formation causes strong intensity changes, we expected the variance in grey values for a defined nucleus to increase, resulting in a high SD. Notably, most tested CBP-IDRs behaved similarly to the negative control, with the exception of CBP IDR7 and CBP CFID which both demonstrated a rapid increase in SD following photoactivation ( Figure 1J & S1H). We then calculated the initial rate of droplet formation over the first 30 seconds following photoactivation; again, only CBP IDR7 and CBP CFID showed a greater ability to form condensates than the negative control Opto-NLS ( Figure 1K & S1I). The results suggest that different CBP-IDRs undergo distinct phase transitions in the nucleus, and highlight strong condensate forming properties in the disordered C-terminal domain of CBP (CBP IDR7 and CBP CFID ). CBP-IDRs regulate the number of CBP condensates We next tested how CBP-IDRs contribute to formation of full-length CBP (CBP wt ) condensates. We deleted CBP-IDRs in CBP wt fused to an in-frame C-terminal GFP-tag (CBP wt -GFP, Figure 2A ). To generate CBP ΔAL -GFP, we replaced the IDR with a flexible 12-residue linker to maintain correct folding of the HAT domain ( Figure 2A ) 23 . Western blots show that HEK293T cells expressing CBP-GFP constructs have similar CBP-GFP expression at a population level (Figure S2A), although we cannot rule out the possibility of variable cell-to-cell transfection within each population. Cells were then fixed and imaged by confocal microscopy for quantification of nuclear puncta ( Figure 2B ). Download figure Open in new tab Figure 2: CBP-IDRs affect the behaviour of full length CBP wt A) Schematic of CBP ΔIDR -GFP constructs. Deleted regions are highlighted with dashed lines. For CBP ΔAL -GFP, the AL is replaced with a flexible 12 residue linker (blue text). B) Confocal microscopy in fixed transfected HEK293T cells showing the behaviour of CBP-GFP condensates. Data shows a maximum projection over the entire Z-stack. Scale bars: 10 μm. C) Percentage of nuclei displaying diffuse or punctate signal. Images were initially selected for successful transfection based on the presence or absence of GFP signal then the data was blinded and scored on whether GFP signal was punctate or diffuse. D) Standard deviation in grey values for nuclei transfected with CBP-GFP. p values were calculated using a Kruskal-Wallis test. E) Number of condensates per nuclei following filtering. Dashed line represents a threshold value of 6 puncta per nuclei. Data points highlight individual nuclei from 3 biological replicates. F) Integrated intensity density (IID) of condensates formed by CBP ΔIDR -GFP constructs. p values were calculated using a Kruskal-Wallis test. G) FRAP analysis of individual CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔAL -GFP puncta. F) Confocal microscopy images showing photobleaching and recovery of CBP-GFP signal. Arrow indicates the bleached puncta. Scale bars: 10 μm. H) Relative fluorescence recovery normalised to pre-bleached intensity for a 90s time period following bleaching. Grey shading highlights imaging pre-bleach; Green line denotes bleaching. Still images from Supplementary Movies 6-8. I) Effect of 1,6 Hexanediol on CBP-GFP puncta. HEK293T cells were transfected with CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔAL -GFP. Images were taken at fixed time points following application of 5% w/v (final concentration) 1,6 Hexanediol. Scale bars: 10 μm. Still images from Supplementary Movies 3-5. J-K) RNAse treatment disrupts CBP condensates. Live cell images of transfected HEK293T cells with CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP. Cells were treated with 100 ug/ml RNase A for 20 minutes, images were taken pre– and post-treatment. Scale bars: 5 μm L) Lattice light sheet microscopy showing dominant phase separation phenotype on endogenous CBP condensates (JF-646) when HEK293T cells were transfected with CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP. Single plane images of endogenous CBP-Halo, and transfected protein including merged image of Z plane, X/Z and Y/Z planes. Scale bar: 5 µm. M-O) Properties of endogenous CBP puncta following transfection of CBP-GFP: CBP-Halo HEK293T cells were transfected with CBP wt -GFP, CBP ΔIDR6 -GFP or CBP ΔIDR7 -GFP for 24h. Endogenous CBP-Halo was labelled with Janelia Fluor Ⓡ 646 Halo ligand (CBP-Halo JF646 ). M) Number of condensates per nuclei, dashed line represents a threshold value of 6 puncta per nuclei; N) Integrated intensity density (IID) of condensates; O) Condensate volume in µM 3 . Data points highlight individual nuclei from 3 biological replicates, p values were calculated using a Kruskal-Wallis test. Data were initially selected for successful transfection based on the presence or absence of GFP signal, then the data was blinded and scored for punctate or diffuse nuclear signal ( Figure 2C & S2B). Following expression of CBP wt -GFP, CBP ΔIDR1 -GFP or CBP ΔIDR6 -GFP, 100% of scored nuclei demonstrated a punctate GFP signal. Indeed, expression of the majority of CBP-GFP constructs resulted in a punctate GFP signal, as CBP ΔIDR2-5 -GFP, and CBP ΔAL -GFP were all >91% punctate. CBP ΔIDR7 -GFP and CBP CFID -GFP were exceptions, with only 52.9% and 40.0% of nuclei showing a punctate signal. To provide a more unbiased measure of the proportion of nuclei that formed condensates, we measured the SD of intensities within treated nuclei. Using this approach, CBP ΔIDR1-5 -GFP failed to show any significant change in the formation of punctate nuclei compared to CBP wt -GFP ( Figure 2D & S2G). However, CBP ΔIDR6 -GFP nuclei were significantly enriched for condensates, while CBP ΔAL -GFP, CBP ΔIDR7 -GFP and CBP ΔCFID -GFP were significantly depleted for condensates ( Figure 2D ). Although informative, this coarse-grained approach was insufficient to describe the full spectrum of condensate-forming CBP ΔIDR -GFP behaviour. To better understand how CBP-IDRs affect both the number and the size and intensity of condensates, we first applied an unbiased filter to remove oversaturated nuclei, noise and overlapping puncta (Figure S2C-E) and calculated the mean number of condensates per nucleus for each CBP-GFP construct ( Figure 2E & S2H). CBP wt -GFP and the majority of CBP-IDR deletions formed well defined condensates, as >80% of nuclei displayed a punctate signal and nuclei that passed the filter formed >6 condensates per nucleus ( Figure 2B,E & S2F,H). CBP ΔIDR1 -GFP and CBP ΔIDR3 -GFP behaved similarly to CBP wt -GFP, while CBP ΔIDR4 -GFP and CBP ΔAL -GFP showed a ∼50% decrease in the average number of condensates compared to CBP wt -GFP ( Figure 2E ). There was a high degree of variability in the number of condensates per nucleus (Figure S2F). For CBP wt -GFP, the SD in the number of condensates was 0.86 of the mean, and most CBP-IDR deletions displayed a similarly high ratio, ranging from 1.37 for CBP ΔIDR1 -GFP to 0.75 for CBP ΔIDR7 -GFP. In contrast to condensate-forming mutants, 60% of CBP ΔCFID -GFP and 47% of CBP ΔIDR7 -GFP nuclei displayed a diffuse GFP signal ( Figure 2C ), alongside a large decrease in the SD of the intensities within each nuclei ( Figure 2D ) and a ∼75% decrease in quantifiable condensates per nucleus compared to CBP wt -GFP ( Figure 2E & S2F). Visual inspection of CBP ΔCFID -GFP and CBP ΔIDR7 -GFP nuclei showed that unlike other CBP-GFP constructs, any residual condensates which passed our filter were poorly defined puncta ( Figure 2B ). We were therefore confident that both CBP ΔCFID -GFP and CBP ΔIDR7 -GFP prevented condensate formation. Together with the OptoDroplet results ( Figure 1 I-K ), this emphasised the importance of C-terminal IDRs (CBP CFID and CBP IDR7 ) for promoting CBP wt condensates. Intriguingly, in contrast to other CBP-IDRs, CBP ΔIDR6 -GFP displayed a significantly greater SD in intensity values within each nucleus and formed ∼30% more condensates than CBP wt -GFP ( Figure 2D & S2F). The variability in the number of condensates for CBP ΔIDR6 -GFP was significantly lower (SD was 0.49 of the mean). This result indicates a much more uniform number of condensates compared to CBP wt -GFP and other CBP-IDR deletions, and suggests that the CBP IDR6 may actively promote variability in CBP condensate numbers. The results for CBP ΔIDR6 -GFP were surprising. Although CBP IDR6 (along with CBP IDR7 ) forms a large part of CBP CFID – which blocked condensation when deleted – the findings suggest that C-terminal IDRs of CBP contain opposing abilities to both promote and inhibit condensate formation. CBP-IDRs regulate the size and intensity of CBP condensates Deletion of CBP-IDRs clearly altered the size and intensity of CBP condensates ( Figure 2B ). To quantify this behaviour, we calculated the Integrated Intensity Density (IID) of CBP condensates. We excluded CBP ΔCFID -GFP and CBP ΔIDR7 -GFP which formed too few puncta. CBP wt -GFP condensates had relatively uniform size and intensity (mean IID = 870 ± 72 s.e.m.), and most CBP ΔIDR -GFP constructs again behaved similarly to CBP wt -GFP ( Figure 2F & S2I). The two exceptions were CBP ΔAL -GFP, which demonstrated a 1.5-fold increase and CBP ΔIDR6 -GFP which demonstrated a 3-fold increase compared to CBP wt -GFP ( Figure 2F ). The results suggest that when intact, CBP IDR6 and CBP AL may restrict the size and intensity of CBP wt condensates. To confirm that larger CBP-GFP condensates retained fluid-like properties, we carried out FRAP on individual CBP wt -GFP, CBP ΔAL -GFP and CBP ΔIDR6 -GFP puncta ( Figure 2G-H ). Following bleaching, all condensates recovered rapidly (Recovery rate: CBP wt -GFP = 0.11 s - 1 , CBP ΔAL -GFP = 0.12 s - 1 , CBP ΔIDR6 -GFP = 0.13 s - 1 , Figure 2H , S2J), demonstrating fluid-like behaviour rather than solid or gel-like properties, and only subtle differences in nuclear mobility. We also treated cells transfected with CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔAL -GFP with 5% 1,6-hexanediol (1,6-HD), an aliphatic alcohol that disrupts weak hydrophobic interactions 48 . Condensates formed by all three constructs dissolved in <20s following application of 5% 1,6-HD ( Figure 2I ), suggesting that hydrophobic interactions are important for maintaining CBP condensates. Diverse RNAs are important for shaping condensate properties. As CBP binds to RNA in vitro and in cells, we therefore tested how it affects CBP condensates ( Figure 2I ). Treating cells with 0.5uM RNAse A decreased the proportion of punctate nuclei for CBP wt -GFP and CBP ΔIDR6 -GFP but not CBP ΔIDR7 -GFP (Figure S2K). Notably, the size and intensity of CBP wt -GFP and CBP ΔIDR6 -GFP condensates was decreased following addition of RNase A, but residual CBP ΔIDR7 -GFP condensates were unchanged. RNase A also caused an increase in the number of condensates formed for all tested constructs (Figure S2L), potentially reflecting a dispersal of condensates following RNA degradation. The results highlight the ability of undefined RNAs to maintain properties of CBP condensates. Taken together, these results highlight clear differences between condensate behaviour regulated by CBP-IDRs. Notably, CBP condensates are strongly promoted by CBP IDR7 and inhibited by CBP IDR6 , but when deleted in combination as part of CBP ΔCFID , the phenotype of CBP ΔIDR7 appears dominant. CBP AL and CBP IDR6 play a more complex regulatory role, restricting the size and intensity of condensates, with CBP IDR6 in particular affecting variability in the number of condensates formed. Large CBP condensates have fluid-like properties and are sensitive to disruption of hydrophobic contacts, and RNAs can help to promote CBP condensate formation. CBP IDRs regulate endogenous CBP condensates Endogenous CBP-Halo ( Figure 1E-G ) and CBP-GFP ( Figure 2F-G ) both form fluid-like condensates. In cells, condensates form due to a combination of homotypic interactions between self-associating IDRs, and heterotypic multicomponent interactions, including with RNAs and other proteins 49 . We hypothesised that the observed changes in CBP condensate behaviour might be caused, at least partially, by alterations in homotypic interactions between its IDRs. To test whether this was the case, we next asked whether CBP-IDR deletions could regulate endogenous CBP condensates. We used lattice light sheet microscopy to image endogenous CBP-Halo labelled with fluorescent JF 646 ligand (CBP-Halo JF646 ) following expression of CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP ( Figure 2L ). Compared to control cells, CBP wt -GFP caused a slight decrease in the number of endogenous CBP-Halo condensates (27.9 ± 79.2 > 14.9 ± 28.9 s.e.m condensates/nucleus; Figure 2M ), coupled to an increase in the IID (835 ± 132 > 1759 ± 803 s.e.m; Figure 2N ) and average volume (32.9 ± 14.6 > 58.9 ± 40.0 s.e.m; Figure 2O ), probably reflecting the presence of extra CBP-GFP molecules due to transient expression. However, compared to cells expressing CBP wt -GFP, CBP ΔIDR6 -GFP increased the median IID (2223 ± 832 s.e.m; Figure 2N ) and the volume (101.7 ± 55.4 s.e.m; Figure 2O ) of endogenous CBP-Halo condensates, while CBP ΔIDR7 -GFP, had the opposite effect, decreasing both the IID (655 ± 411 s.e.m; Figure 2N ) and volume (45.2 ± 33.4 s.e.m; Figure 2O ). Similar results were seen with live cell confocal microscopy (Figure S2M) with no bleed through into other imaging channels (Figure S2N). Although we cannot rule out complexities arising from the mixed populations of endogenous wild type and co-expressed CBP-GFP, these results highlight the importance of homotypic interactions between CBP-IDRs, with CBP IDR6 and CBP IDR7 exerting a dominant positive/negatve influence respectively on endogenous CBP condensates. Although striking, the results don’t exclude the potential for heterotypic interactions, and indeed we believe this is highly likely, given evidence from p300 11 . The ability of CBP-IDRs to shape condensates through homotypic interactions could provide a pathway for modifications of CBP-IDRs, such as acetylation, or disease mutations in CBP-IDRs, to broadly affect CBP activity by affecting its condensate behaviour. Opposing properties of CBP-IDRs reflect their sequence characteristics To investigate whether the opposing behaviours of the C-terminal IDRs CBP IDR6 and CBP IDR7 are encoded by their amino acid sequence, we used localCIDER 50 to examine their sequence properties, alongside CBP CFID which contains both CBP IDR6 and CBP IDR7 ( Figure 3A ). Compared to CBP wt , CBP CFID is enriched for polar amino acids and proline, which promote expanded chain conformations 51 , but depleted for charged and aromatic residues. There is more variation between CBP IDR6 and CBP IDR7 individually: Polar amino acids are more enriched in CBP IDR7 (54%) than CBP IDR6 (41%), while CBP IDR6 is enriched for proline (21%) compared to CBP IDR7 (14%). The linear distribution of amino acids ( Figure 3B ) shows that amino acid properties in CBP IDR6 are evenly distributed, but less so in CBP IDR7 . This is especially true for polar amino acids, which in CBP IDR7 are concentrated around the 18-residue polyQ region (residues 2199-2216), and proline which is concentrated towards the C-terminus ( Figure 3B ). Download figure Open in new tab Figure 3: Sequence properties of CBP-IDRs. A) Sequence properties of CBP wt , CBP CFID , CBP IDR6 and CBP IDR7 . Amino acids are grouped by property: Polar (Q,N,S,T,G,H,C); Proline (P); Aliphatic (A,L,M,I,V); Charged (E,D,R,K); Aromatic (F,Y,W) based on localCIDER defaults 50 . Numbers indicate the fraction of amino acids in each domain with the grouped property. B) Linear amino acid composition of CBP CFID calculated using localCIDER 50 . The relative positions of CBP IDR6 (light blue) and CBP IDR7 (Grey) are highlighted, along a schematic of their positions in the context of CBP wt and CBP CFID ; The position of the 18 residue polyQ expansion is highlighted by the green bar and dashed lines. Amino acids are grouped by property: Charged (magenta); Polar (green); Aliphatic (blue); Aromatic (yellow); Proline (purple); Thin lines give the per-residue composition; Sliding window used to calculate local composition=50 residues; Stepsize between windows = 1 residue. C) Comparison of sequence composition and patterning of CBP IDR6 and CBP IDR7 with CBP IDR6-Shuffle and CBP IDR7-Shuffle using NARDINI+ 43 , 44 . Features represented by negative z-scores are depleted in the IDR (relative to all human IDR proteins), while features with positive z-scores are enriched; features where –1 ≤ z ≤ +1 are not considered to be enriched or depleted compared to representation in all human IDRs 43 , 44 . Features referred to in the main text are highlighted in bold. D-F) Effect of Shuffled IDRs on CBP condensates. D) Fixed cell confocal microscopy comparing CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP to their shuffled counterpart. Scale bars: 10 μm; E) Number of condensates per nuclei following filtering. Dashed line represents a threshold value of 6 puncta per nuclei. Data points highlight individual nuclei from 3 biological replicates; F) Integrated intensity density (IID) of condensates. p values were calculated using a Kruskal-Wallis test. G) PLAAC analysis 53 , 55 of CBP’s C-terminal domains (residues 1856-2441), showing CBP wt , CBP IDR6-shuffle and CBP IDR7-shuffle . The relative positions of CBP IDR6 and CBP IDR7 are highlighted. The composition and sequence patterning of amino acids can impart different behaviours to IDR-containing proteins, and create different properties in biomolecular condensates. To test the role of sequence patterning in CBP IDR6 and CBP IDR7 , we used GOOSE 52 to design CBP IDR6 and CBP IDR7 mutants where the overall composition of was retained, but their sequence was randomly shuffled (CBP IDR6-Shuffle and CBP IDR7-Shuffle Figure S3A-B). Analysis of wild-type and shuffled CBP-IDR sequences using NARDINI+ 43 , 44 highlighted expected similarities in composition, for example in the Fraction of glutamine residues, (FracQ) and Fraction of Charged Residues (FCR) ( Figure 3C , bold). It also highlighted differences in pairwise patterning in the shuffled sequences; for example, CBP IDR6 was enriched for leucine patches and pairs of hydrophobic-proline and proline-proline residue pairs, while CBP IDR6-shuffle was depleted for these features. Similarly, while CBP IDR7 was depleted for hydrophobic and polar-proline residue pairs, CBP IDR7-shuffle was enriched for these features ( Figure 3C , bold). Next, we tested whether these differences in sequence patterning were important for the formation of CBP condensates. We expressed CBP IDR6-Shuffle -GFP and CBP IDR7-Shuffle -GFP in HEK293T cells and imaged using confocal microscopy ( Figure 3D ). CBP IDR6-Shuffle -GFP formed large condensates, similar to those formed by CBP ΔIDR6 -GFP. Following filtering (Figure S3D), it was clear that shuffling the residues in CBP IDR6 increased the proportion of punctate nuclei (Figure S3E), the number of condensates per nuclei ( Figure 3E ) and the size and intensity of condensates compared to CBP wt -GFP ( Figure 3F ), while condensates became more uniform. The result suggests that the order and sequence patterning of amino acids in CBP IDR6 is important for its condensate forming behaviour, as disrupting the native sequence has the same effect on phenotype as deleting the IDR. In contrast, CBP IDR7-Shuffle -GFP continued to form condensates, unlike CBP ΔIDR7 -GFP. Indeed CBP IDR7-Shuffle -GFP behaved more similarly to CBP wt -GFP, with no difference in the proportion of punctate nuclei (Figure S3E), number of condensates per nuclei ( Figure 3D ) or the size and intensity of condensates ( Figure 3E ). The result suggests that the ability of CBP IDR7 to drive condensate formation is more likely to result from its overall composition – which includes enrichment of glutamine and the ratio of arginine and lysine residues ( Figure 3C , bold) – than specific pairwise patterning of amino acids. Our results show that CBP IDR7 strongly promotes CBP condensates while CBP IDR6 restricts condensate formation. CBP IDR6 and CBP IDR7 are enriched for polar residues and polyQ tracts ( Figure 3C ), which are associated with prion-forming domains 53 . Prion-like domains have been identified as strong drivers of condensate formation across diverse proteins 54 . To test whether CBP IDR6 and CBP IDR7 could be displaying prion-like behaviours, we used PLAAC analysis 53 , 55 to examine the sequence of the C-terminal CBP-IDRs for prion-like regions. Results from PLAAC predicted that CBP IDR7 forms a large, contiguous prion-like domain ( Figure 3F ), which extended even further towards the C-terminus of CBP in CBP IDR7-Shuffle . This is consistent with the ability of CBP IDR7 to form condensates in OptoDroplet experiments ( Figure 1I-K ), and the inability of CBP ΔIDR7 -GFP to form condensates ( Figure 2B-E ). While CBP IDR6 was also predicted to contain prion-like regions, these were discontiguous and smaller than those encoded by CBP IDR7 . Finally, we also tested the role of residues 1951-1978 in CBP IDR6 (CBP IDR6-H2 ), which were shown to form transient α-helices by Nuclear Magnetic Resonance (NMR) 46 , and were predicted by Alphafold2 to interact with an α-helix formed by residues 2187-2216 in CBP IDR7 (Figure S3F, CBP IDR7-H1 ). Deletion of either predicted helix did not affect CBP condensates (Figure S3G-I). The different behaviours caused by CBP IDR6 and CBP IDR7 led us to ask whether their sequence properties were conserved in CBP’s paralog p300. Over their entire sequence, CBP and p300 are 60.8% identical (70.7% similarity). While this identity is as high as 87.3% (94.4% similarity) in the HAT domain, CBP IDR6 only has 48.1% identity (58.0% similarity) and CBP IDR7 has 56.1% identity (66.2% similarity) (Figure S3J). To compare the sequence properties of CBP IDR6 and CBP IDR7 to their counterparts in p300, we again used NARDINI+ 43 , 44 (Figure S3K). The results highlight different composition and patterning parameters between p300 IDR6 and p300 IDR7 as seen for CBP, however there were also notable divergences between the equivalent sequences in CBP and p300. For example, CBP IDR7 has higher enrichment of polar-polar and polar-glycine residue pairs, while p300 IDR7 has a higher ratio of arginine and lysine residues and is more depleted for polar-hydrophobic residue pairs (Figure S3K, bold). As CBP IDR6 and CBP IDR7 were predicted to contain prion-forming domains, we also subjected p300 to PLAAC analysis. Similar to CBP, p300 IDR7 was predicted to form a large, contiguous prion-like domain. However, where prion-like properties in CBP IDR6 were discontinuous, p300 IDR6 was predicted to also form a single prion-like domain. Taken together, results based solely on their amino acid sequences suggest that condensates formed by p300 may behave differently to those formed by CBP, but further work is needed to test the hypothesis experimentally. CBP-IDRs allow global lysine acetylation to shape CBP condensates Our results show that distinct sequence properties within CBP-IDRs lead to markedly different properties in the resulting CBP condensates. We hypothesised that this could influence how other environmental inputs, such as post-translational modifications (PTMs), control condensate behaviour and affect overall CBP function. To test this, we focused on lysine acetylation: CBP and p300 acetylate nearly one-third of nuclear proteins, including themselves 9 , and thus both are acetylated on multiple residues, including a hotspot located in CBP 9 , 21 , 28 . Acetylation therefore plays a complex role in regulating CBP/p300 function. Recently, acetylation has been shown to regulate p300 condensates in cells by providing nucleation sites for bromodomain proteins, 11 , 28 , 56 and in vitro where recombinant p300-HAT domain condensates are promoted by p300 AL ’s positive charge and negatively regulated by lysine acetylation 28 . However, it remains unknown how these regulatory events combine with CBP-IDR-mediated regulation of condensates. Firstly, to test how CBP-IDRs allow CBP to respond to global lysine acetylation, we used A-485, a potent inhibitor of CBP and p300 HAT activity 57 to deplete CBP and p300-dependent acetylation and asked how condensates formed by CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP behaved ( Figure 4A ). Treatment with 500nM A-485 for 36 hours 57 increased the proportion of punctate nuclei in CBP wt -GFP ( Figure 4B ), but had no effect on the number ( Figure 4C ) or intensity of condensates ( Figure 4D ). In contrast, A-485 caused a slight decrease in both the proportion of CBP ΔIDR6 -GFP cells forming condensates and the number of puncta per nuclei ( Figure 4B-C ), and a large decrease in the size and intensity of condensates ( Figure 4D ). For CBP ΔIDR7 -GFP, A-485 caused more cells to form puncta ( Figure 4B ), but when quantified the size and intensity of condensates was lower than control cells ( Figure 4D ). The results confirm that CBP and p300-dependent acetylation can regulate CBP condensates. The large decrease in the size and intensity of CBP ΔIDR6 -GFP condensates suggests that removal of CBP IDR6 increased their sensitivity to changes in global acetylation, while acetylation was unable to overcome the dramatic decrease in condensate formation caused by deletion of CBP IDR7 . Download figure Open in new tab Figure 4: CBP-IDRs affect response to acetylation A) Fixed cell confocal microscopy of CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP after 48h treatment with 0.5uM A-485, DMSO or no treatment. Scale bars: 5 μm. B-D) Effect of A-485 or Trichostatin A (TSA) on CBP condensate behaviour: B) Percentage of nuclei displaying diffuse or punctate signal; C) Number of condensates per nuclei following filtering. Dashed line represents a threshold value of 6 puncta per nuclei. Data points highlight individual nuclei from 3 biological replicates; D) Integrated intensity density (IID) of condensates formed by CBP ΔIDR -GFP constructs. Cells were treated with A-485 for 36 hours 57 and with TSA for 90 minutes 58 . E-G) A-485 concentrations affect CBP condensate behaviour: E) Fixed cell confocal microscopy of CBP wt -GFP and CBP ΔIDR6 -GFP after 60 minutes treatment with stated concentration of A-485 (0um = DMSO). Scale bars: 5 μm; F) Number of condensates per nuclei; G) Integrated intensity density (IID) of condensates. Scale: Pseudo-log base 10. H-L) CBP-IDRs affect CBP’s response to acetylation on the AL: H) Fixed cell confocal microscopy of CBP AL double mutant constructs. Scale bars: 10 μm; I) Percentage of nuclei displaying diffuse or punctate signal; J) Number of condensates per nucleus; K) Integrated intensity density (CBP wt -GFP background); L) Integrated intensity density (CBP ΔIDR6 -GFP background). M) Confocal microscopy showing inducible CBP-GFP expression. Stable inducible CBP-GFP HEK293T cells were treated with Doxycycline (Dox) for 48h. Dox concentrations: CBP wt -GFP, 25ngml-1; CBP ΔIDR6 -GFP, 5ngml-1; and CBP IDR7 -GFP, 25ngml-1; Scale bars: 10 μm. N) Western blot of CBP, K1535ac in the AL of CBP/p300 and H3K27ac and following the addition of Doxycycline ( Figure 4M & S4K) to induce expression of CBP-GFP. CBP was resolved using 3-8% Tris-Acetate PAGE (loading control: GAPDH, imaged using chemiluminescence) and H3K27ac was resolved using 12% Bis-Tris PAGE (loading control: Histone H4). O) Immunoprecipitation HAT assay using recombinant di-nucleosome substrate. CBP-GFP expression was induced at equivalent levels using Doxycycline as in ( Figure 4M & S4K) and CBP-GFP was immunoprecipitated using GFP-Trap® Magnetic beads. The reaction was resolved by 12% Bis-Tris PAGE and probed for H3K27ac and H4 by western blot. All p-values for IID were calculated using Kruskal-Wallis tests . We next carried out the opposite experiment, testing the response of condensates to hyperacetylation and chromatin de-compaction by treating cells with Trichostatin A (TSA), a general inhibitor of histone deacetylases (HDACs). Treatment with 500nM Trichostatin A (TSA) 58 for 90 minutes caused a slight increase in the proportion of punctate nuclei in CBP wt -GFP and CBP ΔIDR7 -GFP cells ( Figure 4B ), but had a negligible effect on the number and integrated density of condensates. However, following TSA treatment, CBP ΔIDR6 -GFP showed an increase in both the number of condensates per nuclei and the size and intensity of condensates ( Figure 4B-D ), suggesting that acetylation could positively regulate CBP ΔIDR6 -GFP condensates. Again this suggests that CBP has increased sensitivity to acetylation following removal of CBP IDR6 . We were surprised by the A-485 data for CBP wt -GFP, as A-485 was previously shown to cause a large increase in the number, but decrease the size of p300 wt -GFP puncta when used at a higher concentration 11 . We therefore tested how CBP condensates responded to different concentrations (including 10µM) of A-485 and shorter treatment times (0-120 minutes) 11 ( Figure 4E & S4C). Consistent with our initial data, increasing the concentration of A-485 for 60 and 120 minutes did not change the number of CBP wt -GFP puncta ( Figure 4F & S4D, orange), and slightly decreased their intensity, which only reached significance after treatment with 10uM A-485 for 120 minutes ( Figure 4G & S4E, orange). In contrast, increasing concentrations of A-485 caused a pronounced decrease in the number ( Figure 4E & S4D, blue) of CBP ΔIDR6 -GFP condensates, supporting an increased sensitivity to A-485. However, while 60 minutes treatment with 10µM A-485 caused a modest decrease in intensity ( Figure 4G , blue), we note that no changes in intensity were observed after 120 minutes treatment (Figure S4E, blue). Experiments with A-485 and TSA reveal the potential importance of CBP IDR6 for shaping how CBP condensates behave in response to global acetylation. Its removal appears to hyper-sensitize CBP condensates to changes in acetylation, as hypoacetylation caused a greater decrease, while hyperacetylation caused a greater increase in the number, size and intensity of condensates than CBP wt -GFP. However, A-485 and TSA both affect global levels of acetylation, which makes it challenging to separate changes in condensates due to direct acetylation of CBP from indirect disruption of heterotypic interactions. Regulation of condensates by acetylation of CBP AL relies on CBP-IDR integrity Next, to assess the role of direct CBP acetylation on condensate formation, we examined how changing acetylation of CBP AL regulates CBP condensates. In CBP ΔAL -GFP data, we observed a ∼50% reduction in the mean number of condensates ( Figure 2E ) but a slight increase in their size and intensity ( Figure 2F ) compared to CBP wt -GFP. This might be explained by a balance in CBP condensates: a positive effect from exposed lysines in CBP AL could be offset by negative regulation due to lysine acetylation, as seen previously for recombinant p300-HAT in vitro 28 . To test the role of acetylation on CBP AL , we generated two mutants, CBP ΔAL -GFP ( Figure 2A ) and CBP KTG -GFP, where all 13 lysine residues were mutated to glycine to prevent acetylation (Figure S4F). When expressed in HEK293T cells to visualise CBP condensates, CBP wt/ΔAL -GFP and CBP wt/KTG -GFP had similar effects, decreasing the overall proportion of punctate nuclei compared to CBP wt -GFP ( Figure 4H & 4I). Both CBP AL mutations also reduced the number of condensates per nucleus by 40-60% compared to CBP wt -GFP, but retained a high variability ( Figure 4J ) and caused a 40-50% increase in their size and intensity ( Figure 4K ). As CBP AL in CBP wt/KTG -GFP was intact, but incapable of being acetylated, this suggested that acetylation of lysine residues in CBP AL can help to maintain a larger number of smaller CBP condensates. To better understand the relative contributions of CBP-IDRs and lysine acetylation on the CBP AL , we next tested how CBP IDR6 and CBP IDR7 impacted condensate behaviour due to CBP AL acetylation. To do this, we made double mutants of CBP-GFP, where the two single CBP AL mutants (CBP ΔAL & CBP KTG ) were generated alongside CBP ΔIDR6 -GFP (CBP ΔIDR6/ΔAL -GFP & CBP ΔIDR6/KTG -GFP) and CBP ΔIDR7 -GFP (CBP ΔIDR7/ΔAL -GFP & CBP ΔIDR7/KTG -GFP). Due to their inability to form condensates, CBP ΔIDR7 -GFP and CBP ΔCFID -GFP were not affected by CBP AL mutations (Figure S4G-I). Notably, CBP AL mutations did not produce the same effects when combined with CBP ΔIDR6 -GFP as they did in CBP wt -GFP. When combined with CBP ΔIDR6 -GFP, neither CBP AL mutation affected the overall proportion ( Figure 4I ), the number ( Figure 4J ) or the size and intensity ( Figure 4L ) of condensates compared to CBP ΔIDR6 -GFP single mutants. The result suggests that CBP ΔIDR6 -GFP is essential for enabling these condensates to respond to acetylation, as mutations in CBP AL that alter CBP wt -GFP condensate behaviour lost their effect when CBP ΔIDR6 -GFP was deleted. Finally, to compare how direct acetylation of CBP AL works together with global acetylation, we treated cells expressing CBP wt/KTG -GFP or CBP ΔIDR6/KTG -GFP with A-485. Following treatment, there was a slight reduction in the size and intensity of CBP wt/KTG -GFP, and a larger decrease in CBP ΔIDR6/KTG -GFP condensates (Figure S4J) as observed following treatment of CBP wt -GFP and CBP ΔIDR6 -GFP with A-485. As neither mutant could be acetylated on CBP AL , the result underlines the importance of bulk acetylation as a driver of condensates, and again highlights how deletion of CBP IDR6 appears to hypersensitize condensates to changes in global acetylation levels. Together, these results highlight the complex roles of acetylation on CBP condensates. They suggest that changes to global acetylation exert relatively minor effects on CBP wt condensates, while direct acetylation of CBP AL could support formation of more and smaller condensates. The results clearly demonstrate the importance of CBP IDRs; in all cases deletion of CBP IDR7 severely reduced the ability of CBP to form condensates, while deletion of CBP IDR6 promoted the formation of more and larger condensates regardless of mutations that affect acetylation on CBP AL . This latter finding suggests that the integrity of CBP IDR6 could be crucial to ensure that modifications, such as acetylation on CBP AL , can effectively regulate condensates. However, observations made using CBP AL mutations must be interpreted cautiously before conclusively attributing results to lysine acetylation. Due to the importance of CBP AL for CBP function, these mutations could have multiple pleiotropic consequences, each capable of shaping CBP condensate behaviour. For example, deletion of CBP AL increases catalytic activity 21 which could lead to increased global histone acetylation and nucleation of condensates 56 . Similarly, lysine residues in CBP AL facilitate RNA binding 22 , potentially affecting condensates independent of acetylation 59 . IDRs regulate CBP-dependent acetylation Next, we asked whether CBP-IDRs could affect CBP-dependent histone acetylation. To better control expression of CBP-GFP, we made clonal HEK293T lines stably expressing doxycycline inducible CBP wt -GFP, CBP ΔIDR6 -GFP and CBP IDR7 -GFP. The cells showed a clear increase in GFP signal in response to increasing concentrations of doxycycline (Figure S4K-L). For all subsequent experiments we chose doxycycline concentrations that maintained overall CBP-GFP expression at near-endogenous levels (Figure S4L). Following induction, CBP wt -GFP and CBP ΔIDR6 -GFP formed visible condensates, while CBP ΔIDR7 -GFP displayed a more diffuse signal ( Figure 4M ). The overall proportion of punctate nuclei (Figure S4M) and the number of condensates per nuclei was lower for inducible CBP-GFP than when transiently expressed (Figure S4N). CBP ΔIDR6 -GFP condensates (mean IID = 126.0 ± 21.5 s.e.m.) were also larger and more intense than CBP wt -GFP condensates (mean IID = 80.6 ± 18.3 s.e.m.), while CBP ΔIDR7 -GFP failed to form quantifiable puncta (Figure S4O). Next, we tested how CBP-IDRs impacted histone acetylation. Induction of CBP wt -GFP slightly increased total levels of H3K27ac, while CBP ΔIDR7 -GFP slightly decreased global H3K27ac ( Figure 4N & S4P). However, induction of CBP ΔIDR6 -GFP caused >2-fold increase in total H3K27ac ( Figure 4N & S4P). The amount of activated CBP (K1535ac) remained similar relative to total CBP levels for CBP wt -GFP and CBP ΔIDR6 -GFP, but was depleted by CBP ΔIDR7 -GFP ( Figure 4N & S4Q). To test whether HAT activity was affected by CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP, we purified doxycycline inducible CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP and tested their ability to acetylate recombinant nucleosomes in vitro . We expected that dilution of CBP and disruption of chromatin during sample preparation would prevent formation of condensates in vitro. CBP wt -GFP had the highest HAT activity, while surprisingly, H3K27ac was reduced for CBP ΔIDR6 -GFP and further decreased for CBP ΔIDR7 -GFP ( Figure 4O & S4R). The disparity between the total level of H3K27ac in cells, which increased following induction of CBP ΔIDR6 -GFP, and the decreased activity of purified CBP ΔIDR6 -GFP suggests a complex regulatory mechanism. The total level of CBP (and p300)-dependent acetylation observed in cells is a function of both the acetyltransferase activity of CBP, and the recruitment of CBP to sites on chromatin. The discrepancy could therefore be explained by an increase in the contacts between CBP and chromatin as a result of the formation of larger condensates, or by a stimulation of CBP ΔIDR6 -GFP activity in cells that we are unable to detect in vitro . CBP IDRs shape how CBP binds to chromatin Our results suggest that CBP-IDRs outside the HAT domain can influence HAT activity, and highlight a discrepancy between CBP behaviour in vitro and levels of histone acetylation in cells. We reasoned that as well as controlling HAT activity, regulation of CBP condensates by CBP-IDRs could change CBP chromatin association, and thus control total levels of histone acetylation. We tested this in our inducible CBP-GFP cell lines using chromatin immunoprecipitation sequencing (ChIP-seq) and CUT&RUN. To confirm the GFP-tag does not adversely affect CBP recruitment to chromatin, we first verified that induced CBP-GFP binds to the same genomic locations as endogenous CBP. We compared ChIP-seq profiles for endogenous CBP wt in maternal HEK293T Tet3G cells (ɑ-CBP; CBP wt-Tet3G ) and for CBP-GFP (ɑ-GFP; following addition of Doxycycline to inducible cell lines ( Figure 4L ). Read densities for CBP ChIP-seq (CBP wt-Tet3G ) and GFP ChIP-seq were well correlated across the genome (Figure S5A&B), confirming that reads aligned to similar locations. We then used MACS2 60 to highlight CBP-bound sites in pooled replicates ( Figure 5A ), identifying 14,913 binding sites for endogenous CBP wt-Tet3G using CBP ChIP-seq, but only 7,661 sites for CBP wt -GFP in GFP ChIP-seq ( Figure 5A ). We attribute this disparity to reduced precipitation in the GFP ChIP-seq data, likely stemming from differences in antibody efficiency and from the mixed population of endogenous CBP and CBP-GFP proteins. Accordingly, while endogenous CBP wt-Tet3G binding sites were still enriched for CBP wt -GFP read densities in GFP ChIP-seq data, the enrichment was lower than that observed with endogenous CBP wt-Tet3G read densities from CBP ChIP-seq data (Figure S5C-D); endogenous CBP wt-Tet3G sites (median width = 416bp) were therefore broader than those of CBP wt -GFP (median width = 340bp, Figure 5B ), again indicative of differences in ChIP efficiency. Despite differences in the number of binding sites, CBP wt -GFP and CBP wt-Tet3G bound to similar regions in the genome; most binding sites were found at promoters (51.5% CBP wt -GFP; 52.1% CBP wt-Tet3G ), then introns (14.4% CBP wt -GFP; 18.6% CBP wt-Tet3G ) and intergenic sites (13.5% CBP wt -GFP; 15.0% CBP wt-Tet3G ); 20.5% of CBP wt -GFP binding sites and 14.3% of CBP wt-Tet3G binding sites mapped to exons ( Figure 5C ). CBP wt-Tet3G and CBP-GFP binding sites were closer than expected by chance 61 (Figure S5E-F), demonstrating spatial correlation between CBP-GFP and CBP wt ; all CBP-GFP binding sites showed statistically-significant overlap with CBP wt-Tet3G ( Figure 5A & S5F). Taken together, the data show that CBP-GFP and endogenous CBP wt-Tet3G bind to similar sites in the genome. Download figure Open in new tab Figure 5: CBP-IDRs regulate nuclear chromatin association and H3K27ac. A) Overlap between CBP binding sites identified from CBP and GFP ChIP-seq. CBP wt-Tet3G (purple), CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) and CBP IDR7 -GFP (dark blue). Magenta bar highlights consensus peaks found in every CBP-GFP dataset. B) Peak widths of CBP binding sites. Violin plots show CBP peak widths in HEK293T Tet3G cells (purple), and GFP ChIP-seq reads in CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) and CBP IDR7 -GFP (dark blue). p values from Mann-Whitney U-test. C) Distribution of CBP binding sites by genome region. D) Genome browser views of CBP and GFP ChIP-seq (top) and H3K27ac CUT&RUN (bottom) at the TSC22D3 gene. CBP wt-Tet3G (Purple), CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) CBP IDR7 -GFP (dark blue) and H3K27ac (red). Solid bars show binding sites identified using MACS2. E) Peak widths of enriched H3K27ac domains. Violin plots show H3K27ac peak widths following induction of CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) and CBP IDR7 -GFP (dark blue). p values from Mann-Whitney U-test. F-G) Read density enrichment at H3K27ac domains. E) H3K27ac; F) CBP-GFP. H3K27ac peaks were randomly downsampled to match the size of the smallest dataset (CBP wt -GFP, 9213); p values from Mann-Whitney U test. H-I) Read density enrichment at 4,657 CBP peaks common in all datasets. E) H3K27ac; F) CBP-GFP; p values from Mann-Whitney U test. J) Distribution of consensus and non-consensus CBP binding sites by genome region. K-L) Heatmaps of sites unique to each CBP-IDR mutation. K) CBP-GFP ChIP-seq signal; L) H3K27ac CUT&RUN signal. Heatmaps show ±2.5 Kb window from centre of peaks; CBP wt -GFP (3,049 sites, orange), CBP ΔIDR6 -GFP (13,776 sites, light blue) CBP IDR7 -GFP (12,605 sites, dark blue). M-N) Enrichment of M) CBP-GFP and N) H3K27ac read densities at 2,348,854 GRCh38 cCREs from ENCODE v4 62 . p-values from Mann-Whitney U test. Given the differences in ChIP efficiency between endogenous CBP and CBP-GFP ChIP-seq datasets, we focused on CBP-GFP ChIP-seq data to uncover how CBP-IDRs affected chromatin localisation. Notably, we observed more binding sites for both CBP ΔIDR6 -GFP (18,357 sites) and CBP ΔIDR7 -GFP (17,237 sites) than for CBP wt -GFP (7,661 sites) in GFP ChIP-seq ( Figure 5A ) and the location of binding sites shifted towards introns and intergenic regions for CBP ΔIDR6 -GFP (22.6 % introns, 19.9 % intergenic) and CBP ΔIDR7 -GFP (27.2 % introns, 21.8% intergenic), ( Figure 5C ). CBP wt -GFP sites overlapped 77% of CBP ΔIDR6 -GFP and 69% of CBP ΔIDR7 -GFP. However, only 43% of CBP ΔIDR7 -GFP bound-sites overlapped CBP ΔIDR6 -GFP ( Figure 5A & S5F). We next asked how CBP-IDRs affected the profiles of CBP-GFP chromatin binding. Compared to CBP wt -GFP at endogenous CBP binding sites, CBP ΔIDR6 -GFP read densities were enriched, while CBP ΔIDR7 -GFP was depleted (Figure S5C&D). Increased CBP enrichment was reflected in the size of peaks; across all CBP-GFP binding sites, the median peak width for CBP ΔIDR6 -GFP (394bp) was greater than for CBP wt -GFP (340bp), and the peak width for CBP ΔIDR7 -GFP (283bp) was lower than for CBP wt -GFP ( Figure 5B ). The behaviour of CBP-GFP constructs when bound to chromatin thus mirrors their behaviour in imaging data: CBP ΔIDR6 -GFP bound to more locations with a larger average peak size, while CBP ΔIDR7 -GFP bound to more locations but with a smaller average peak size. The results suggest that larger condensates formed by CBP ΔIDR6 -GFP increased its enrichment on chromatin, while dispersion of CBP ΔIDR7 -GFP condensates led to lower levels of CBP binding, but at a larger number of locations. CBP IDRs shape histone acetylation Our results show that CBP-IDRs regulate total levels of CBP-dependent H3K27ac ( Figure 4N ) and CBP activity ( Figure 4O ). To examine how changes in chromatin localisation affected histone acetylation across the genome, we used spike-in normalised CUT&RUN to quantify H3K27ac levels. Genome browser views of CBP-bound regions and corresponding H3K27ac enrichment, such as at the TSC22D3 gene and a candidate CRE (cCRE) ( Figure 5D ), highlight binding of CBP-GFP to similar locations as CBP wt and corresponding enrichment for H3K27ac. We used MACS3 60 to identify enriched H3K27ac domains in our CUT&RUN data, highlighting 37,117 loci with a median peak width of 381bp following CBP wt -GFP expression ( Figure 5E ). Deleting CBP-IDRs had a striking effect on H3K27ac enrichment; compared to CBP wt -GFP, expression of CBP ΔIDR6 -GFP caused an increase in the number (46,576 enriched loci) and the size (median width = 421bp) of enriched H3K27ac domains, while expression of CBP ΔIDR7 -GFP caused a large decrease in their number (9,213 loci) but not their size (median width = 420bp) ( Figure 5E ). This corresponded to an increase in both H3K27ac ( Figure 5F ) and CBP-GFP enrichment compared to CBP wt -GFP ( Figure 5G ) in CBP ΔIDR6 -GFP cells, and a decrease in CBP ΔIDR7 -GFP cells. The pattern of H3K27ac and CBP-GFP enrichment was replicated when sampling all CBP-GFP bound sites in CBP-GFP ChIP-seq data (Figure S5G-H). We noted that CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP were recruited to more than twice as many loci as CBP wt -GFP ( Figure 5A ). To directly compare how CBP-IDRs affect H3K27ac levels, and avoid complexities from sampling a mixture of CBP-bound and CBP-unbound locations, we focussed on a subset of 4,765 binding sites found in common between all CBP-GFP datasets ( Figure 5A , magenta). Again, these common sites were enriched for H3K27ac read densities in CBP ΔIDR6 -GFP cells, but depleted in CBP ΔIDR7 -GFP cells compared to CBP wt -GFP ( Figure 5H & S5I). Compared to CBP wt -GFP (mean signal = 0.17), CBP-GFP read densities were enriched at common sites in both CBP ΔIDR6 -GFP cells (mean signal = 0.21) and CBP ΔIDR7 -GFP cells (mean signal = 0.18) ( Figure 5I & S5I). Although CBP-GFP data was not normalised to spike-in controls, the result suggests that H3K27ac broadly reflects CBP recruitment for CBP wt -GFP and CBP ΔIDR6 -GFP, but suggests a discrepancy between CBP ΔIDR7 -GFP recruitment and H3K27ac. We next mapped the genomic distribution of the unique binding sites identified for each CBP-GFP mutant. Common binding sites predominantly overlapped promoters (58%) and exons (22%), while introns (11%) and intergenic regions (9%) were less common ( Figure 5J ). This balance shifted considerably for unique sites, with unique sites for CBP wt -GFP (21% introns, 20% intergenic), CBP ΔIDR6 -GFP (27% introns, 23% intergenic) and CBP ΔIDR7 -GFP (33% intron, 27% intergenic) for frequently found in introns and intergenic regions. This change in distribution suggests that both the larger condensates formed by CBP ΔIDR6 -GFP, and the dispersal of CBP ΔIDR7 -GFP condensates caused a relocation of CBP to introns and intergenic sites. CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP read densities were enriched at their unique binding sites compared to CBP wt -GFP ( Figure 5K & S5J) and levels of H3K27ac were elevated at unique CBP ΔIDR6 -GFP sites and depleted at unique CBP ΔIDR7 -GFP sites ( Figure 5L & S5K). Finally, as CBP was recruited to CREs across the genome, we examined how CBP-IDRs affected CBP recruitment and H3K27ac levels at candidate CREs (cCREs) defined by ENCODE 62 . Compared to CBP wt -GFP, binding of CBP ΔIDR6 -GFP was enriched and CBP ΔIDR7 -GFP were reduced at cCREs ( Figure 5M ). H3K27ac had a similar pattern, showing enrichment in CBP ΔIDR6 -GFP cells and depletion in CBP ΔIDR7 -GFP cells, compared to CBP wt -GFP ( Figure 5N ). Taken together, the data highlight how the effect of CBP-IDRs on HAT activity and chromatin localisation combine to determine patterns of histone acetylation at CBP binding sites on chromatin, and that this behaviour is also seen at cCREs across the genome. CBP-IDRs affect gene expression Our results show that CBP-IDRs regulate the properties of CBP condensates, and thus shape the localisation of CBP to chromatin and the pattern of histone acetylation at regulatory elements across the genome. As CBP binding to CREs and altered histone acetylation directly regulate gene expression, we therefore asked whether disrupting CBP-IDRs affected patterns of gene expression. We carried out RNAseq from two biological replicates each of CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP following addition of doxycycline to induce their expression ( Figure 4M ). Replicates from the same sample type were well correlated (Figure S6A), and replicates from each sample formed distinct clusters in principle components analysis (PCA) (Figure S6B). To identify gene expression changes specifically resulting from disruption of CBP-IDRs rather than induced expression of CBP-GFP, we compared gene expression profiles in CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP to CBP wt -GFP. Expression of CBP ΔIDR6 -GFP resulted in significant up regulation of 190 genes, and down regulation of 349 genes compared to CBP wt -GFP ( Figure 6A & S6C); expression of CBP ΔIDR7 -GFP caused upregulation of 182 genes and down regulation of 278 genes compared to CBP wt -GFP ( Figure 6B & S6D). Download figure Open in new tab Figure 6: CBP-IDRs regulate gene expression profiles A-B) Differentially expressed genes between A) CBP wt -GFP and CBP ΔIDR6 -GFP; and B) CBP wt -GFP and CBP ΔIDR7 -GFP. Genes showing significant changes in expression using more stringent significance parameters p 3 are highlighted (red points, gene names & Supplementary Table 4). HAND1 (bold) is upregulated in both CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP datasets. C) Genome browser views of GFP ChIP-seq (top) and H3K27ac CUT&RUN (bottom) at the HAND1 gene. CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) CBP IDR7 -GFP (dark blue) and H3K27ac (red). Solid bars show identified binding sites. Importantly, genes with altered expression displayed differences in CBP chromatin binding in GFP ChIP-seq data, and were characterised by changes to H3K27ac levels in spike-in normalised CUT&RUN data. For example HAND1 , which was upregulated in both CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP datasets, showed additional CBP-GFP binding at regulatory elements, including the promoter, and altered patterns of H3K27ac ( Figure 6C ). The results highlight how disruption of CBP-IDRs causes off-target accumulation of CBP and alterations to H3K27ac, leading to widespread deregulation of gene expression. Discussion Our results provide direct evidence for the importance of CBP-IDRs as regulators of CBP function. We show that different CBP-IDRs can regulate CBP activity in a sequence-dependent manner, by controlling the properties of CBP condensates, altering chromatin localisation and by shaping histone acetylation and gene expression profiles. Importantly, we uncover very different behaviours in different CBP-IDRs, and show how they regulate the response of CBP to lysine acetylation. The ability of condensates to regulate transcription requires balance: too much condensation downregulates transcription, suggesting that condensates must exist within a window of optimal properties to guarantee accurate transcriptional output 11 , 13 , 47 , 48 , 63 . Here, we highlight how different IDRs within CBP help maintain this balance. Primary drivers of CBP condensate formation are found in its C-terminal IDRs, where CBP IDR6 and CBP IDR7 make opposing positive and negative contributions to the formation of CBP condensates, that depend on their amino acid sequence patterning in the case of CBP IDR6 and overall composition in the case of CBP IDR7 . The inhibitory effect of CBP IDR6 on the condensates driven by CBP IDR7 ( Figure 7A ) is similar to regulatory interactions in those formed by Ataxin-2, where condensate forming IDRs – with prion-like properties similar to CBP IDR7 – could be quenched by neighbouring IDRs 64 . In CBP, the balance between CBP IDR6 and CBP IDR7 strongly influences how CBP interacts with chromatin. CBP and p300 are recruited to chromatin by the association of TFs with TF interacting domains in their C-terminal regions 65 . Here, we show that disruption of CBP IDR6 and CBP IDR7 can shape how CBP behaves once it has been recruited to chromatin, potentially by changing its interactions with TF-condensates 11 . This leads to two key changes: an increase in the number of CBP binding sites on chromatin, and altered profiles of CBP recruitment. Specifically, broader interactions occur when CBP IDR6 is deleted, while the size of CBP binding sites decreases following CBP IDR7 deletion, behaviour which directly mirrors that observed in CBP condensates when CBP IDR6 and CBP IDR7 are deleted. Download figure Open in new tab Figure 7: Summary of CBP-IDR functions A) Summary of how CBP-IDRs regulate condensates, chromatin localisation and histone acetylation. B) Summary of how CBP-IDRs work with lysine acetylation to control condensate behaviour. These alterations in chromatin binding also reshape histone acetylation patterns at regulatory elements, impacting gene expression. Since CBP functions as a crucial scaffolding factor, modifications to its condensate properties and chromatin binding could further disrupt the recruitment and retention of other vital regulatory factors at these sites 10 , 12 , 14 . We have shown that CBP-IDRs determine the sensitivity of CBP condensates to different forms of lysine acetylation. p300 condensates are regulated by global lysine acetylation, which nucleates condensate assembly by recruiting bromodomain proteins 11 , 56 , but also through direct acetylation of lysine resides in p300, which is inhibitory to p300 HAT domain condensates in vitro 28 . In contrast to p300, CBP condensates appear relatively insensitive to changes in global acetylation ( Figure 7B ). This buffering function is potentially mediated by CBP IDR6 , as its deletion seems to hyper-sensitize CBP condensates to changes in global acetylation. Like p300, acetylation of CBP AL appears to negatively regulate the number and size of CBP condensates, but again this function is dependent on the integrity of C-terminal CBP-IDRs; deletion of CBP IDR7 largely inhibits CBP condensates, while the larger condensates formed following removal of CBP IDR6 seem to be largely impervious to acetylation events on CBP AL ( Figure 7B ). Taken together, the results highlight the fundamental importance of CBP-IDRs to condensate behaviour, but also underline the complex nature of CBP condensates, which integrate diverse environmental factors including global and direct lysine acetylation on CBP. Surprisingly, as well as CBP’s response to acetylation, disrupting CBP-IDRs changed CBP’s catalytic activity. CBP-HAT activity was eliminated by deletion of CBP IDR7 and drastically reduced by deletion of CBP IDR6 ( Figure 4O ). Truncation of p300 in the p300 TAZ2 domain (N-terminal to CBP IDR6 and CBP IDR7 ) can increase histone acetylation in vitro by relieving p300 TAZ2 -dependent inhibition of HAT activity 66 . As CBP TAZ2 remained intact in both our CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP mutants, it’s possible that CBP IDR6 and CBP IDR7 may relieve inhibitory interactions between CBP TAZ2 and CBP-HAT, and that their removal causes inhibition of HAT activity by CBP TAZ2 . The regulation of HAT activity by C-terminal CBP-IDRs suggests that factors interacting with these regions, such as the CBP NCBD – which is located between CBP IDR6 and CBP IDR7 – may regulate activity by influencing CBP-IDR behaviour. For example, the adenovirus protein Early region 1A (E1A) can bind to multiple sites in the N– and C-terminal tails of CBP, but is only able to inhibit the HAT activity of CBP when it interacts with a region overlapping CBP IDR6 . Mutations in E1A which specifically disrupt its binding to CBP IDR6 , but not other sites in CBP 29 , resulted in the loss of this inhibition. Similarly, stimulation of CBP HAT activity was seen with mutants of Activator of Thyroid and Retinoic acid Receptors (ACTR) that interact with the C-terminus of CBP via the CBP NCBD , but not by cAMP Response Element-Binding protein (CREB) that binds to the N-terminal CBP KIX domain 29 . Our data has broader implications for the deregulation of CBP function in disease. Importantly, many variants in CBP associated with diseases such as the developmental disorders Rubinstein Taybi Syndrome (RTS) 67 , 68 and Menke-Hennekam Syndrome (MHS) 69 , and cancers such as B-cell lymphoma 70 , map to IDRs characterised here. Disease-associated variants in the HAT domain of CBP are understandably the best characterised, as they are more prevalent and lead to easily definable changes in HAT activity 68 , 70 – 72 . However, increasing evidence highlights how variants in IDRs can also lead to disease, including by changing patterns of condensate formation 73 . This study defines clear roles for CBP-IDRs in regulating diverse cellular functions, which if disrupted by mutations could contribute to disease etiology. Indeed, many diseases arising from variants in CBP are heterozygous 70 , and therefore the ability of CBP-IDRs to confer dominant positive/negative effects on endogenous CBP condensates by disrupting homotypic interactions may be relevant to these mixed populations. We also highlight significant sequence divergence between functionally relevant IDRs in CBP and their counterparts in p300. We speculate that these differences in sequence could help to explain the contrasting behaviour of CBP wt -GFP ( Figure 4E-G ) and p300 wt -GFP condensates following treatment with A-485 11 . Although not tested here, it’s possible that these less well-conserved, but functionally important domains, could form the basis for functional specialisation of CBP and p300. Limitations There are a number of limitations to our study. Firstly, as we did not deplete endogenous CBP, we cannot rule out the possibility of complexities arising from mixed populations of mutant and wild-type CBP. Our results show how CBP-IDR mutations can affect the behaviour of endogenous CBP condensates ( Figure 2L ), but we did not look at how CBP-IDRs affected condensates formed by other factors or address the contribution of heterotypic interactions to CBP condensates; given the complex nature of condensates, which are composed of a plethora of factors including both CBP and p300 10 , 11 , we might expect that larger heterotypic interaction networks are similarly disrupted. This has further implications for changes in histone acetylation, as the impact of CBP-IDR mutations on H3K27ac is likely complicated by the recruitment of endogenous copies of CBP wt and potentially p300 to the same loci. Secondly, our initial studies used transient co-expression of CBP-GFP to assess condensate behaviour. This system is imperfect, as the formation of condensates is highly sensitive to protein concentration, and differences in transfection efficiency could therefore lead to inconsistent behaviour at a cell-to-cell level. Nevertheless, we believe these approaches accentuate behaviours that can also occur at near-endogenous expression levels, as demonstrated using inducible CBP expression ( Figure 4L ). We cannot rule out the possibility that changes to CBP condensates result from the gain or loss of TF binding, or changes to PTMs on CBP-IDRs. CBP IDR6 and CBP IDR7 bridge CBP NCBD , a TF binding domain that associates with different TFs 15 – 19 . It is possible that disrupted CBP NCBD folding, changes TF binding profiles and that this could explain changes in condensate behaviour, although we note that deletion the equivalent region in p300 only mildly impacted p300 chromatin association 65 . Finally, CBP AL has a variety of roles that could each individually impact CBP condensates, making experiments focussed on CBP AL challenging to interpret. Firstly, CBP AL is a key binding site for RNAs in the nucleus 22 ; given the importance of RNA in condensate formation 59 , it is likely that disrupting interactions between CBP AL and RNA could alter condensate properties. Indeed, our data suggest that RNA helps to maintain CBP condensates ( Figure 2J-K ). Secondly, acetylation of lysines in CBP AL directly regulates CBP’s catalytic activity 21 , potentially altering global lysine acetylation with implications for condensates 56 , 74 . CBP is fundamentally important for controlling gene expression, integrating diverse environmental signals to generate precise histone acetylation profiles and scaffold assembly of transcription complexes 10 , 12 . Our work highlights how CBP-IDRs facilitate this process, regulating CBP condensate properties and changing how CBP responds to other environmental factors such as lysine acetylation and changing chromatin localisation, histone acetylation and gene expression patterns. We therefore underline the importance of understanding the unique behaviours of CBP-IDRs and IDRs in other multivalent transcription coactivators when considering their role in gene expression. Resource availability Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Daniel Bose ( d.bose{at}sheffield.ac.uk ). All plasmids generated for this study are available from Addgene. All unique/stable reagents generated in this study are available from the lead contact without restriction. The high-throughput sequencing data data from this publication have been deposited to the GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and assigned the identifiers GSE268266 (ChIP-seq), GSE299613 (CUT&RUN) and GSE299614 (RNA-seq). Datasets GSE268266 GSE299613 GSE299614 have been grouped under SuperSeries GSE299618 . Author contributions The study was conceived and led by D.A.B, A.E.T, T.D.C and K.L.G. D.A.B, A.E.T and K.L.G designed experiments with input from T.D.C and N.A.C. K.L.G carried out all imaging experiments; N.A.C generated tagged cell lines and prepared samples for high-throughput sequencing data; L.J.H, M.D and D.A.B analyzed NGS data; K.L.G, N.A.C, G.G, L.J.H, B.V.E, T.E, S.B carried out all other experiments. D.A.B., K.L.G and A.E.T wrote the manuscript. All authors reviewed and commented on the manuscript. Disclosure and competing interests statement Timothy Craggs is the founder and CEO of Exciting Instruments, a company that develops and sells instrumentation for single-molecule fluorescence experiments, including smFRET. Supplemental information Supplemental information includes: 7 supplemental figures, 4 tables, 1 document containing pairwise sequence alignments, 8 movies. Methods Materials and Methods Cell culture Culture and maintenance Human Embryonic Kidney cells stably expressing the SV40 large T antigen (HEK293T, ATCC) and GP2-293 (Clontech) cells were cultured in complete DMEM (10% FBS, 1% Penicillin-Streptomycin (Gibco)) and grown in 5% CO 2 at 37°C. HEK293T cells containing stable doxycycline inducible CBP-GFP, were cultured in complete DMEM (10% Tetracycline free FBS, 1% Penicillin-Streptomycin) including 2 mg/ml G418 (Generon) and 50ug/ml hygromycin (ThermoFisher). All cell lines were screened every three months for mycoplasma infection. Transient transfections Transient transfections were done using either Lipofectamine 3000 (ThermoFisher Scientific) or LipoD293 (TEBU-Bio). Manufacturers’ recommended protocol was followed for 6-well dishes with the following details: 1.5 μg of DNA was transfected per well and 7.5 μl of Lipofectamine 3000 reagent was used per well. For LipoD293 (TEBU-Bio), the manufacturers protocol for 6-well 35-mm dishes was followed using: 1 μg of DNA and 3 μl of LipoD293 per well. Retroviral transduction Lentiviral transduction of CBP-GFP was done using the pRetroX TM Tet-On R 3G inducible expression system (Clontech). CBP wt -GFP, CBP ΔIDR6 -GFP, and CBP ΔIDR7 -GFP were cloned into the pRetroX-pTRE3G vector for lentiviral transduction. To generate lentiviral particles, 2 µg of CBP-pRetroX-pTRE3G constructs or pRetroX-Tet3G were co-transfected with 2 µg of the envelope pVSV-G plasmid into GP2-293 cells using lipofectamine 3000 (ThermoFisher). After 48 hours, with 1 media change after 24 hours, the viral supernatant was collected and concentrated using Lenti-X concentrator (Takara) following manufacturers instructions. To generate polyclonal pRetroX-Tet3G HEK293T cells, 8 ug/ml polybrene (Merck Millipore) was added to the concentrated virus and used to infect HEK293T cells. Infected cells were selected using G418 (Generon) at a concentration of 8 mg/ml for 1 week. To generate CBP-pRetroX-pTRE3G cells, polyclonal pRetroX-Tet3G HEK293T cells were transduced with viral particles and 8 ug/ml polybrene, then selected using 8 mg/ml of G418 and 125 µg/ml hygromycin (ThermoFisher) for 1 week. Clonal cell lines were generated by inducing expression of CBP-GFP with 2000 ng/ml of doxycycline for 48 hours before fluorescence-activated cell sorting (FACS) based on the GFP signal, using a FACSMelody Cell Sorter (BD Biosciences) at the University of Sheffield Flow Cytometry Core Facility. Clonal lines were cultured in the background of 2 mg/ml G418 and 50 µg/ml hygromycin (ThermoFisher). Doxycycline induction of CBP expression For doxycycline validation experiments, HEK293T cells were plated in 10 cm dishes (Sarstedt) for western blot or 35-mm glass bottom dishes (Ibidi) for imaging. 24 hours post-plating the media was changed to media containing the predetermined concentration of doxycycline calculated to ensure induction of CBP-GFP but not increase overall CBP expression levels (Figure S4K-L)), 2 mg/ml G418 and 50 µg/ml hygromycin. Molecular Biology and cloning All PCR reactions were completed using a 50 µl reaction containing: 0.5 µl PFuUltra II fusion HS DNA Polymerase (Agilent), 1 % PFu Ultra reaction buffer, 5 % dimethyl sulfoxide (DMSO, Sigma), 200 mM dNTP mix, 0.2 µM forward and reverse primer, and template DNA. DNA was initially denatured at 95°C with an extension temperature of 68°C for DNA less than 10 Kb, and 72°C for DNA greater than 10 Kb, with 35 extension cycles unless otherwise stated. To confirm correct assembly and presence of mutations, all plasmids were checked by Sanger sequencing and most were checked by Whole plasmid sequencing (Eurofins). All Constructs have been made available through Addgene ( https://www.addgene.org/ ). Full length human CBP (CBP wt ) To generate human CBP wt (transcript variant 1, NCBI Reference: NM_004380.3) tagged with a C-terminal GFP for overexpression experiments (CBP wt -GFP), Homo sapiens CBP transcript variant 2 (NCBI Reference NM_001079846.1, Sino Biological HG17295-UT) was cloned in-frame into pAcGFP-N1 (Clontech) using NEBuilder HiFi DNA Assembly reaction protocol (NEB). CBP was amplified using primers: Fwd: Human CBP_fwd, Rev: Human CBP_rev and pAcGFP-N1 was amplified using primers: Fwd: pAcGFP-N1_fwd, Rev: pAcGFP-N1_rev ; (For primer sequences see Supplementary table 1). Assembled constructs were checked by Sanger sequencing (Eurofins). To convert transcript variant 2 to transcript variant 1, the missing sequence comprising exon 5 was ordered as a custom-synthesised DNA from IDT and inserted into CBP-pAcGFP-N1 using the NEB HiFi assembly. CBP exon 5 was amplified using primers: CBP missing Exon_fwd, CBP missing Exon_rev . CBP-pAcGFP-N1 was amplified using primers: Fwd: GFP-CBP_fwd, Rev: GFP-CBP_rev . Fully assembled CBP wt -GFP was sequenced by Sanger sequencing using sequential primers at 900bp intervals and confirmed using Whole Plasmid Sequencing (Eurofins) to check for correct assembly. CBP-IDRs for optoDroplet The optoDroplet construct pHR-mCh-Cry2WT was a gift from Clifford Brangwynne (Addgene plasmid #101221) 39 . To target the optoDroplet construct to the nucleus we used custom synthesised DNA (gBlock, IDT) encoding the SV40 nuclear localisation signal (NLS) to generate pHR-mCh-Cry2WT-NLS 36 . The SV40 NLS was amplified by PCR using primers: Fwd: SV40_NLS_NotIRD_fwd, Rev: SV40_NLS_SbfIRD_rev , to introduce restriction sites for NotI and SbfI. Following restriction digestion with NotI-HF and SbfI (NEB), pHR-mCh-Cry2WT and the synthesised NLS were ligated using T4 DNA ligase (NEB) and the construct was checked by Sanger sequencing. CBP-IDRs were cloned into pHR-mCh-Cry2WT-NLS construct using the NEB HiFi DNA assembly protocol. pHR-mCh-Cry2WT-NLS was amplified using primers: Fwd: pHR-mCh-Cry2WT-NLS_fwd, Rev: pHR-mCh-Cry2WT-NLS_rev . CBP-IDRs were amplified from CBP wt -GFP using IDR-specific primers (Supplementary table 1). All constructs were checked using Sanger sequencing. CBP ΔIDR -GFP deletion mutants To generate CBP ΔIDR mutants, primers were designed to amplify CBP wt -GFP in reverse directions to delete residues comprising the identified CBP-IDRs (Supplementary table 1). Amplified PCR products were digested using DpnI (NEB), the ends of the PCR fragments were then phosphorylated using T4 polynucleotide kinase (PNK, NEB) before undergoing ligation using T4 DNA ligase (NEB). Constructs were sequenced by Sanger sequencing to check the IDRs had been correctly removed from the construct. Autoregulatory Loop (CBP AL ) mutants Two mutants of the Autoinhibitory Loop (CBP AL , CBP 1558-1607 ) were designed. Firstly, CBP KTG contained the AL with all lysines mutated to glycine (K1564G, K1565G, K1583G, K1586G, K1587G, K1588G, K1591G, K1592G, K1595G, K1597G, K1605G, K1606G, and K1607G). Secondly, in CBP ΔAL the AL was replaced with a glycine/serine linker (sequence GSAGSAAGSGQF) to maintain correct folding 23 . CBP 4322-5818 – which are flanked by unique restriction sites for NruI and PmlI – were synthesised as gBlocks (IDT) containing the mutant AL sequences (Supplementary table 1). The synthesised gBlocks and CBP-pAcGFP-N1 constructs (CBP-GFP for single mutants; CBP ΔIDR6 -GFP, CBP ΔIDR7 -GFP, and CBP ΔCFID -GFP for double mutants) were digested using NruI-HF and PmlI (NEB). The digested constructs were dephosphorylated using Quick Calf Intestinal Phosphatase (CIP, NEB), before the inserts and vectors were assembled using T4 DNA ligase (NEB). The assembled constructs were checked by Sanger sequencing. Doxycycline inducible CBP-GFP CBP-GFP, CBP ΔIDR6 -GFP, and CBP ΔIDR7 -GFP, were sub-cloned into a modified pRetroX-pTRE3G plasmid (Clontech) containing a hygromycin resistance cassette using BamHI-HF and NotI-HF (NEB) restriction enzymes. The fragments were annealed using T4 DNA ligase (NEB) before sequencing to check for correct insertion and subsequently by whole plasmid sequencing. CBP ΔIDR6H2 -GFP and Cloning CBP ΔIDR7H1 -GFP To delete predicted a-helices in CBP IDR6 and CBP IDR7 , DNA sequences were synthesised containing CBP 5332 – 7674 which resides within the N-terminal GFP tag, and spans two unique endogenous restriction sites for MluI-HF and BssHII (GeneArt, ThermoFisher). Synthesized sequences contained deletions of CBP 1951-1978 (CBP ΔIDR6H2 -GFP) and CBP 2187-2216 (CBP ΔIDR7H1 -GFP). CBP wt -GFP and synthesised sequences were digested with MluI-HF and BssHII (NEB) and purified by agarose gel extraction. The digested CBP wt -GFP vector was dephosphorylated using Quick Calf Intestinal Phosphatase (CIP, NEB) before assembly using T4 DNA ligase (NEB). Correct insertion was checked by Sanger sequencing. CBP IDR6-Shuffle -GFP and Cloning CBP ΔIDR7-Shuffle -GFP DNA sequences were synthesised of CBP IDR6 and CBP IDR7 where the overall sequence composition was maintained but the sequence was randomly shuffled to disrupt the sequence patterning. Design of the shuffled sequences was performed using GOOSE 52 to randomize the input sequence amino acid sequence. DNA coding for the shuffled sequences was designed and codon optimised for expression in H. sapiens (GeneArt, ThermoFisher). The synthesised DNA contained two unique restriction sites for MluI-HF and BssHII, cloning was performed as described for CBP ΔIDR6H2 -GFP and Cloning CBP ΔIDR7H1 -GFP. Cloning of gRNA plasmids Designed gRNAs (Supplementary table 1) were cloned into pSpCas9(BB)-2A-GFP (PX458). PX458 was a gift from Feng Zhang (Addgene plasmid # 48138) 75 . 100 μM forward and reverse oligo pairs were combined with T4 polynucleotide kinase (PNK) (NEB) and 10X T4 ligation buffer (NEB) containing essential ATP. For annealing, reactions were heated to 37°C for 30 minutes, followed by 95°C for a further 5 minutes and then cooled to 25°C at a ramp rate of –5°C per minute. Annealed gRNAs were then diluted 1:100 in sterile H 2 O in preparation for the ligation reaction. pX458 plasmid was digested with BbsI-HF (NEB) DNA and annealed gRNA oligos were ligated using T4 DNA ligase (NEB). Constructs were validated using Sanger sequencing. Construction of stably integrated CBP-Halotag cell lines gRNA design Single guide RNAs (sgRNAs) targeting the C-terminus of CBP were designed using the UCSC CRISPR targets tool ( https://genome.ucsc.edu/ ). After selection in UCSC, crRNAs were further evaluated using the Evaluation tool on the E-CRISP site ( http://www.e-crisp.org/E-CRISP/reannotate_crispr.html ). Plasmids encoding CBP-targeting sgRNAs were transfected into HEK293T cells using the Neon electroporation system and 100 µl kit (ThermoFisher), at 1100V, 20 ms pulse width and 2 pulses. After 48 hours, genomic DNA was extracted using QuickExtract solution (Lucigen) according to the manufacturer’s instructions and PCR of CBP C-terminal region was carried out using primers CBP_C-T_fwd1/2, CBP_C-T_rvs (Supplementary Table 1). gRNA validation PCR products amplifying the C-terminal region of CBP in both edited and unedited cells were cleaned up using the Monarch PCR cleanup kit (NEB). DNA concentrations were measured using the Qubit dsDNA BR kit (ThermoFisher) according to the manufacturer’s instructions. 10X NEB buffer 2 (NEB) was added to 200 ng DNA and PCR products were denatured to single strands by heating at 95°C for 5 minutes. DNA strands were then hybridised by decreasing temperature from 95°C to 85°C at a ramp rate of –2°C/second, then from 85°C to 25°C at a ramp rate of –0.1°C per second. T7 Endonuclease 1 (T7E1) enzyme (NEB) was added and incubated at 37°C for 15 minutes, followed by quenching with 0.25 M EDTA. The total reaction volume was run on a 1% agarose gel. To analyse Sanger sequencing data of CRISPR edited DNA sequences, .ab1 files of CBP C-terminal PCR products were uploaded to the Inference of CRISPR Edits (ICE, Synthego) tool ( https://ice.synthego.com/#/ , Conant et al. 2022). Generation of clonal CBP-Halo HEK293T cell lines Validated plasmids encoding CBP gRNA and custom synthesised CBP HDR template plasmid (Supplementary Table 1, ThermoFisher) were co-transfected into HEK293T cells using the Neon electroporation system and 100 µl kit (ThermoFisher) at 1100V, 20 ms pulse width and 2 pulses. After 48 hours, single cell sorting was performed using a FACSMelody cell sorter (BD Biosciences) into 96 well plates. Clones were allowed to grow until confluent and then screened PCR genotyping for successful integration of the Halotag using primers CBP_C-T_fwd1/2, CBP_C-T_rvs (Supplementary Table 1). We performed sufficient screening to identify heterozygous clones. However, we cannot eliminate the possibility that the C-terminal HaloTag caused detrimental effects for CBP function that resulted in no homozygotes being obtained. qPCR Total RNA was extracted from WT and CBP-HaloTag HEK293T cells, using TRIzol (ThermoFisher) and treated with Turbo DNase (Invitrogen) to remove genomic DNA, then purified using phenol/chloroform and ethanol precipitation. Reverse Transcription was performed using the High Capacity cDNA kit (ThermoFisher) and qPCR was carried out using Power SYBR reaction mastermix (ThermoFisher) and a Quantstudio 12K Flex (ThermoFisher). A mean Ct was calculated using each triplicate reaction and normalised to 18S rRNA expression. Imaging Live cell imaging of CBP-HaloTag HEK293T cells containing endogenous CBP-HaloTag were seeded at 400,000 cells/well on 35 mm glass bottom dishes that had been coated in 20 µg/ml of poly-L lysine (PLL, Merck) diluted in sterile dH 2 O for 1 hour at 37°C, before washing twice in sterile dH 2 O. After 48 hours, cells were labelled with HaloTag ligand TMR (Promega) at a concentration of 50 nM for 15 minutes at 37°C in the dark. Cells were left for a further 2 hours before staining with Hoechst 33342 (Fisher) in DPBS as described in a previous section, before washing in DPBS and storing in imaging media (FluoroBright DMEM (Fisher) supplemented with a final concentration of 20 nM Gibco HEPES (ThermoFisher Scientific)) immediately prior to imaging. Cells were imaged using the Nikon W1 spinning disc confocal microscope equipped with a temperature stage set to 37°C. Images were taken using the 100X oil immersion lens (NA 1.45), using the 405 nm laser to image Hoechst using 45 % laser power with a 100 ms exposure, TMR was visualised using the 514 nm laser using 60 % laser power with an exposure of 300 ms. Images were taken every 500 ms in the absence of binning. Captured images and videos were processed ImageJ/Fiji 76 . FRAP of CBP-HaloTag CBP-HaloTag cells were plated on PLL coated 35-mm dishes, and labelled with Janelia Fluor Ⓡ 549 (JF549, Promega) at a concentration of 50 nM for 15 minutes. Cells were subsequently washed twice in DPBS and placed in imaging media for a 15 minute recovery. Cells were imaged using a custom built iLas TIRF/FRAP single-molecule scanning microscope by Cairn. Puncta were imaged using 561 nm laser with 200 ms exposure at 10 % laser power, on the 100 % oil objective. ROIs were drawn with a diameter of 10 to mark where the lasers should target, this could be multiple puncta per field of view. FRAP settings are as follows: 10 repetitions using the 561 nm laser line of weight 2 on 3 % laser power. A time course was taken with the following pattern: 15 time points with a 500 ms delay prior to FRAP which was performed as described above, followed by 60 time points with a 500 ms delay and 30 time points with a 2 second delay. Images were quantified and processed in ImageJ/Fiji 76 . Imaging of transfected CBP-HaloTag with CBP-GFP, CBP ΔIDR6 -GFP, CBP ΔIDR7 -GFP Endogenous CBP-HaloTag cells were seeded at 250,000 cells/well on PLL coated glass bottom 35-mm dishes and transfected after 24 hours with CBP-GFP, CBP ΔIDR6 -GFP, CBP ΔIDR7 -GFP using LipoD293, as has been previously described. Cells were labelled with Janelia Fluor Ⓡ 646 (JF646, Promega) at a final concentration of 2 nM for 15 minutes before washing in DPBS and imaging in imaging media. 35 mm dishes were labelled sequentially, immediately before imaging. Imaging using custom built iLas TIRF/FRAP single-molecule scanning microscope by Cairn 4-colour control images were also taken where the HaloTag had not been labelled, to check for bleed-through of overexpressed constructs. In this case, the media was changed to imaging media and imaged using laser lines 405 nm, 488 nm, 532 nm and 637 nm, with an exposure time of 200 ms using 10 % laser power. A 4-colour control was also taken with CBP-HaloTag labelled with JF646 and no overexpression, for this all laser lines used the same conditions as before except the 637 nm laser had a power of 80 % to visualise the endogenous protein. For colocalization experiments, 2 colour multidimensional images were captured using the 488 nm laser with 10 % laser power and a 200 ms exposure to visualise GFP tagged constructs, and 637 nm laser with 80 % laser power and 200 ms exposure to view endogenously tagged HaloTag. Images were processed in ImageJ/Fiji 76 . Imaging using Zeiss Lattice Lightsheet 7 3D images of CBP-HaloTag and overexpressed CBP-GFP, CBP ΔIDR6 -GFP, CBP ΔIDR7 -GFP were taken using the Zeiss Lattice Lightsheet 7, using the Sinc3 30 x 1000 lightsheet with a calibrated magnification of 50. The system was calibrated following manufacturers guidelines. 488 nm laser line was used to image overexpressed GFP tagged constructs at 40% laser power using 50 ms exposure, the endogenous CBP-HaloTag was imaged using the 638 nm laser line using 80 % laser power with a 100 ms exposure. Zen Blue software was used to deskew the dataset and for representative images channel alignment was performed using default settings, where the CBP-HaloTag (638 nm images) were used for reference. Images were then pre-processed in ImageJ/Fiji 76 , before quantification using Arivis Vision4D version 3.4. Imaging of doxycycline inducible clones For imaging cells were seeded at a concentration of 250,00 cells/well on PLL coated 35-mm dishes and doxycycline induced for 48-hours. Imaging was performed in imaging media using the Nikon W1 spinning disc confocal microscope, using the 100X oil objective. Laser lines 405 nm and 488 nm were used to image the Hoechst 33342 (Fisher) and therefore the nuclei, and GFP expression respectively. The 405 nm laser was set with a 100 ms exposure with 60 % laser power, and the 488 nm laser was set with 300 ms exposure time and 60 % laser power. For quantification Z-stacks were taken to capture the whole volume of the nuclei in 0.5 μm increments, these were further processed in ImageJ/Fiji 76 . For the plus doxycycline conditions, imaging media was supplemented with the appropriate concentration of doxycycline. optoDroplet 35-mm glass bottomed dishes (Ibidi) were coated in PLL for 1 hour at 37°C before being washed twice with dH 2 O and seeded with HEK293T cells at a concentration of 200,000 cells/well. 24 hours post-plating the cells were transfected using LipoD293 TM (SignaGen Laboratories), following manufacturer’s guidelines for 35 mm dishes. After 24 hours the media was changed into complete DMEM (10% FBS, 1% Pen/Strep). After a further 24 hours, prior to imaging the media was changed into FluoroBright DMEM (Fisher) with a final concentration of 20 mM HEPES (ThermoFisher). For IDR1, IDR3, IDR4, AL, IDR6, IDR7 and the CFID the live cell imaging was performed on Nikon A1 confocal using the 60X oil immersion objective (NA 1.4), equipped with a humidified temperature stage set to 37°C. For the IDR2 and IDR5 live cell imaging was performed on the Nikon W1 spinning disc confocal microscope, using a temperature stage set to 37°C and the 100X oil objective lens. In both cases, two laser wavelengths were used to induce global activation of the optoDroplet system; 488 nm to induce the dimerisation of the Cry2 and 560 nm to image mCherry. An image was captured for the mCherry every 8 seconds, with subsequent activation of the mCherry for the same time. Time courses were taken for each construct, for a period of up to 3 minutes. 3 time courses were taken per construct per biological replicate, with a total of 3 biological replicates being taken. Fluorescence recovery after photobleaching (FRAP) in transfected cells For FRAP experiments, 250,000 cells/well of HEK293T cells were plated in 35 mm dishes and transfected using LipoD293 as was described for the optoDroplet live cell imaging. 24-hours post transfection the media was removed and the cells were washed in DPBS before leaving the cells in imaging media. Imaging was performed using a custom built iLas TIRF/FRAP single-molecule scanning microscope by Cairn, using an 100X oil immersion objective. Puncta was visualised using the 488 nm laser set to 5 % laser power with a 100 ms exposure. A circular ROI with dimensions of 4.4 x 4.4 μm was drawn over the puncta to be photobleached; there may be multiple regions within each field of view. Photobleaching was performed using the 488 nm laser, with 10 % laser power, using 5 repetitions with a thickness of 5. 10 images were taken prior to FRAP, followed by 700 frames being collected after, with a frame interval of 0.387 seconds. 1,6 – Hexanediol treatment Cells were plated and transfected as previously described for FRAP in transfected cells. Images were captured using the Nikon W1 spinning disc confocal microscope using the 100X oil immersion objective. Images were taken using the 488 nm laser with a 200 ms exposure time on 20 % laser power. A 10% solution of 1,6 – Hexanediol (Merck) was diluted from a 50% stock in warm imaging media. Time courses were taken of the constructs over a 3 minute period, imaging every 500 ms. Without pausing imaging, after 30 seconds 1 ml of 10% 1,6 – Hexanediol was added dropwise to the 35 mm dish that contained 1 ml of imaging media for a final concentration of 5% 1,6 – Hexanediol. Imaging continued until the end of the time course. Image quantification and processing was performed in ImageJ/Fiji 76 . RNAse treatment Cells were plated and transfected in 35mm glass bottom plates as described above. On the day of imaging, the media was removed and replaced with FluoroBrite media and images were collected of the untreated cells. The cells were then RNAse treated 77 as follows: firstly the cells were washed with PBS and reaction buffer (20mM Tris pH 7.5, 5 mM MgCl 2 , 0.5mM EGTA, 1x protease inhibitor cocktail) before being permeated with 0.1% Triton X-100 for 5 mins. A second round of washes was then applied before 20 minute incubation with 0.2 mg/ml final RNase A (NEB), diluted in the nuclease buffer (5 mM MgCl 2 in PBS) to a final concentration of 100 µg/ml. After treatment the RNase solution was removed and replaced with imaging media. Images were subsequently collected of the treated cells. Imaging was performed using the Nikon W1 spinning disc confocal microscope, using the 100X oil objective. The 488 nm laser line was used to image GFP expression. For quantification Z-stacks were taken to capture the whole volume of the nuclei in 0.5 μm increments, these were further processed in ImageJ/Fiji 76 . Immunofluorescence and fixed cell imaging Immunofluorescence and fixed cell imaging Circular coverslips (Ibidi) were acid washed in 0.25% acetic acid before washing and storing in 100% ethanol. Coverslips were coated in poly-L lysine (PLL, Merck) for 1 hour at 37°C before washing twice in sterile dH 2 O. HEK293T cells were grown in 6-well plates at a concentration of 200,000 cells/well containing two coverslips per well for 48 hours before fixing. If the cells were transfected, transfection was performed 24 hours after plating using Lipofectamine 3000 transfection reagent (ThermoFisher) or LipoD293 (TEBU-Bio) following manufacturers instructions. Cells were washed in DPBS twice before fixing in 2% paraformaldehyde (PFA) for 30 minutes at room temperature in the dark, before being washed 3 times in DPBS. For immunofluorescence, coverslips were blocked using a blocking buffer (5% Bovine serum albumin (BSA) with 0.2% Triton in PBS) for 1 hour at 37°C. Primary antibodies (for full list of antibodies see Supplementary Table 2) were prepared in a blocking buffer and incubated at 37°C for 1 hour. After washing 3 times in PBS, secondary antibodies were diluted in the blocking buffer and incubated for 37°C for 1 hour. After fixing, coverslips were mounted onto slides (VWR, 631-1554) using VECTORshield that contained 4,6-diamidino-2-phenylindole (DAPI) (Vector laboratories, H-2000-10). Fixed slides were stored at 4°C. Imaging work was performed at the Wolfson Light Microscopy Facility using the Nikon A1 confocal microscope. All fixed cell imaging was performed using the 60X oil immersion objective (NA 1.4). The microscope has 4 laser wavelengths, typically only 3 of the 4 were used (these include, 405 nm for DAPI, 488 nm for GFP, 562 nm for mCherry and 642 nm for Alexa Fluor 647). Z-stacks were taken every 0.5 μm to cover the depth of the nuclei; a minimum of 3 fields of view were imaged per construct over 2 coverslips, per biological replicate. For CBP deletion mutants CBP ΔIDR2 and CBP ΔIDR5 images were captured on the Nikon W1 spinning disc confocal microscope, using the 100X oil objective and the 488 nm laser line. Z-stacks were taken as described above. A-485 treatment Cells were cultured in 6-well plates, containing PLL-treated circular coverslips as described above. HEK293T cells were transfected with LipoD293 (TEBU-Bio) after 24 hours following manufacturers instructions. For 36 hour A-485 treatment, media was removed after 8-hours of transfection and replaced with media supplemented with A-485 to a final concentration of 5 uM, or with media containing DMSO as a negative control. The cells were treated for 36 hours before fixing with 2 % paraformaldehyde and mounted on slides using VECTORshield containing DAPI as described above. For the A-485 concentration experiments, cells were transfected after 24 hours of culture, and treated 24 hours after transfection. Media was replaced either 2 hours before fixing or 1 hour before fixing with media containing A-485 at concentrations of 1 uM, 5 uM or 10 uM. A DMSO control was performed at each time point. After treatment cells were fixed as described above. Imaging was performed using the Nikon W1 spinning disc confocal microscope, using the 100X oil objective. Laser lines 405 nm and 488 nm were used to image the DAPI and therefore the nuclei, and GFP expression respectively. For quantification Z-stacks were taken to capture the whole volume of the nuclei in 0.5 μm increments, these were further processed in ImageJ/Fiji 76 . TSA treatment Cells were cultured in 6-well plates, containing PLL-treated circular coverslips as described above. HEK293T cells were transfected with LipoD293 (TEBU-Bio) after 24 hours following manufacturers instructions. After ∼36 hours cells were treated with Trichostatin A (TSA, Stratech) at a final concentration of 500 nM for 90 minutes. After 90 minutes the cells were fixed and imaged as described above for A-485 treatment. Image analysis Integrated Intensity Density Before calculating the Integrated density, individual nuclei were isolated from a maximum projection and saved as .tif files where the file names were blinded using ImageJ/Fiji plugin: Blind Analysis Tool, File Name Encryptor 76 . These blinded files were categorized by two individuals independently, scoring the images as either diffuse, containing puncta, overexpressed or untransfected. Any nucleus that had a single puncta, was described as containing puncta; those that were transfected but displayed a diffuse signal were categorized as diffuse. Overexpressed nuclei were any nuclei where the signal intensity was too great to identify individual puncta, and untransfected cells were nuclei where little to no signal intensity was observed (Figure S2B). Both overexpressed and untransfected nuclei were removed from the dataset and an average percentage of nuclei which displayed either puncta or a diffuse phenotype was determined for each of the constructs. To assess the punctate nature of the nuclei in an unbiased manner we also calculated the standard deviation of pixel intensity across the nucleus. Nuclei containing puncta would display a higher standard deviation between pixels compared to nuclei with a diffuse signal. A region of interest (ROI) was drawn around the nucleus by applying a manual threshold to isolate only the nuclei in ImageJ/Fiji 76 . This region was applied to the raw image and the standard deviation was calculated within this region. All downstream analysis was done using R in Rstudio; significance p values for comparison of punctate signals were calculated using a Kruskal-Wallis test. Graphs and statistical testing was performed using R in RStudio 78 . Integrated density, the intensity multiplied by the area, for each condensate produced by a defined construct was calculated in ImageJ/Fiji 76 using a custom macro. A maximum projection was generated from each Z-stack, and the condensates were identified by applying a manual intensity threshold to each image to generate a mask. The intensity threshold was internally consistent within each experimental repeat, where the threshold was chosen to best isolate condensates across the range of different phenotypes observed within the constructs tested. Within the mask, each independent ROI was labelled, and the area, Integrated Density, and circularity was measured for each ROI. Once these images had been analysed, the percentage of nuclei which contained a ROI which has an intensity higher than that of the set intensity threshold value was further calculated. This value was described as the transfection efficiency, and was generated to identify which nuclei had passed the threshold value. Filters were then applied sequentially to the data: 1) To exclude overexpressed nuclei, a maximum grey value of 10 was set; 2) To remove regions of high intensity that were too small to represent puncta, an area threshold (<3 pixels/0.36um) was applied; 3) To remove regions of overlapping puncta, a circularity threshold (<0.25) was set. All downstream analysis was done using R in Rstudio; significance p values for comparison of CBP-GFP behaviours (number of condensate per nuclei and integrated density) were calculated using a Kruskal-Wallis test. Graphs and statistical testing was performed using R in RStudio 78 . optoDroplet A custom ImageJ macro was written to identify puncta formed in the mCherry channel. Images were run through an ImageJ plugin called Stack Registration (StackReg, 79 ), and a threshold was applied to generate a binary mask that underwent binary processing of closing followed by opening. For IDR1, IDR3, IDR4, AL, IDR6, IDR7 and the CFID the threshold was set using RenyiEntropy, and for IDR2 and IDR5 the Default setting was used. The parameters were then set in analyse particles, applying a size range of 50 – infinity, to generate ROIs which equated to the outline of the signal region, which was the nuclei. These ROIs were then applied to the original, raw image that underwent a multi-measure to calculate the standard deviation of the pixels within the nuclei over the time course. Regions found in the first frame were used to monitor the change in the standard deviation over the time course, where the average Fold Change was then calculated. A rate of change was then calculated over the time course based on the time at which the curve for the positive control plateau. For IDR1, IDR3, IDR4, AL, IDR6, IDR7 and the CFID this was done over the first 32 seconds, whereas for IDR2 and IDR5 was calculated over the first 72 seconds. For IDR1, IDR3, IDR4, AL, IDR6, IDR7 and the CFID the statistics for the rate of change were performed in GraphPad prism, where an unpaired t-test was used to determine statistical significance (Prism 80 ). For the IDR2 and IDR5 statistics were performed using R in RStudio, using the Kruskal-Wallis test. Graphs for visualisation were made using R in RStudio 78 . FRAP in CBP-HaloTag Images for each FRAP time course were loaded into ImageJ/Fiji 76 and processed using StackReg ( 79 ) to remove drift in the sample. Over each time course, the intensity was calculated for a region of interest around the bleached area, before being corrected for photobleaching over the time course using a reference region within the same nuclei. Relative intensity was calculated by subtracting the intensity at T = 0, where this was defined as the first frame after photobleaching, and then normalised to the pre-bleach intensity for each construct. Rate constants and T = ½ were calculated in GraphPad Prism 9 80 , using a non-linear regression with settings one phase association with a variance weighting of 1/Y 2 . FRAP in transfected cells Time courses from FRAP of overexpressed protein were quantified using ImageJ/Fiji 76 .The intensity was calculated over the time course, using a ROI of 0.22 μm, which is smaller than the condensate to only monitor the intensity within the condensate. The condensate was manually tracked throughout the time course, moving the ROI when the condensate moved. The relative fluorescence recovery was calculated by subtracting the intensity at T = 0, the first frame post bleaching and then normalised to the pre-bleach intensity for each construct. Rate constants and T = ½ were calculated as described for FRAP of CBP-HaloTag. Quantification of CBP-HaloTag puncta data from the Zeiss Lattice Lightsheet 7 in the absence and presence of overexpressed CBP-GFP, CBP ΔIDR6 -GFP, CBP ΔIDR7 -GFP Images were preprocessed in ImageJ/Fiji 76 , where background was subtracted using a rolling ball of 50, and the images were sharpened. The preprocessed images were then converted to .sis files using Arivis SIS converter software before being quantified using Arivis Vision4D version 3.4. The data was first imported into the pipeline as a current time point. A denoise preset was run on either the Janelia Fluor channel for CBP-HaloTag only, or on the GFP channel in dual colour images to isolate either all nuclei present or all transfected nuclei respectively. A discrete gaussian of 5 µm was applied to this channel, to blur the edges of the nuclei, after the denoise the results were saved as a temporary document. Next an intensity threshold segmentor was applied to the denoised channel to isolate the nuclei of interest. For CBP-HaloTag only a threshold of 350 was applied, with a core filter of 400 and size range of 500 – 10,000 µm 2 was applied to isolate only nuclei. For overexpressed GFP constructs a threshold of 600 was applied, with a core filter of 1000 and size range of 500 – 10,000 µm 2 was applied. The blob finder was then applied to the Janelia Fluor channel for endogenous CBP-HaloTag in all cases. For CBP-HaloTag only a diameter of 5 µm was applied with a probability threshold of 22 % and a split sensitivity of 50 %. In the dual colour images a diameter of 5 µm was applied with a probability threshold of 6 % and a split sensitivity of 65 % was applied. A segment feature filter was then applied to remove any objects that are too small to be classified as puncta. A compartment section was then applied to assign the condensates identified in the blob finder to the nuclei identified within the intensity threshold segmentor. The compartmentalisation was selected as a full overlap so that only puncta contained within the nucleus was counted. The data was then exported as a Master-Details report, containing features of the nuclei and details of the condensates – these features included volume, area and intensity of puncta. Graphs for visualisation were made using R in RStudio 78 . Western blotting For western blotting HEK293T cells were plated in 10 cm dishes (Sarstedt), and induced or treated as described in the imaging section. Cells were harvested and after washing twice in PBS the pellet was lysed in RIPA buffer (50 mM Tris-HCl pH 8 stored at 4°C, 100 mM NaCl, 2 mM MgCl 2 , 1 % Triton X-100, 0.1 % Sodium deoxycholate, 0.1 % Sodium Dodecyl Sulfate (SDS)) supplemented with 1 mM Dithiothreitol (DTT), 1X Halt protease inhibitor cocktail, 10 mM sodium butyrate and 500 U/μl benzonase. 25 – 50 µg of overall protein containing sample buffer and reducing buffer was loaded onto either a 3 – 8% Tris-Acetate gel (Thermo Fisher Scientific) using Tris Acetate running buffer (Life Technologies) for large proteins such as CBP, or 4 – 12% Bis-Tris gel with MOPS running buffer for visualising small things such as H3K27ac. Gel was transferred onto a membrane using trans-blot turbo mini 0.2 µm nitrocellulose transfer packs (Biorad) before blocking and probing for CBP, GFP, acetylated CBP 1535, H3K27ac and GAPDH (for full list of antibodies see Supplementary Table 2). Western blots were imaged using G:box (Syngene) gel imager. Images were processed using ImageJ/Fiji 76 and assembled using Adobe Illustrator. Histone acetyltransferase assay Expression of CBP wt -GFP, CBP ΔIDR6 -GFP, CBP ΔIDR7 -GFP was induced in the respective cell lines by 48 hours treatment with previously determined doxycycline concentrations to ensure equal expression levels ( Figure 4M & S4K-L). Cells were harvested immediately after doxycycline treatment for cell lysis. Cells were washed with PBS and resuspended in NET buffer (50 mM Tris-HCl, 150 mM NaCl, 2 mM MgCl2, 2 mM CaCl2, 2 mM ZnCl2) supplemented with 0.1% NP40, 10mM sodium butyrate and Halt™ Protease and Phosphatase Inhibitor Cocktail. Lysed cells were incubated with benzonase (1kU) at 37°C for 30 mins, followed by centrifugation at 4°C to obtain the cell lysate. To immunoprecipitate CBP-GFP, 500 µg – 1 mg cell lysate was incubated with either 25 µl ChromoTek GFP-Trap® Magnetic Particles M-270 or 50 µl Protein G Dynabeads™. After recovery, beads were resuspended in 500 µl of wash buffer (NET buffer supplemented with 10mM sodium butyrate and 0.05% NP-40). 300 µl of the bead suspension was retained for a Western blot to confirm successful immunoprecipitation of the GFP-tagged protein. The remaining 200 µl was used for the in vitro HAT assay. Beads were resuspended in HAT buffer (250 mM Tris-HCl, 25% glycerol, 0.5 mM EDTA, 250 mM KCl) supplemented with 0.1M DTT, 10mM PMSF, 1M sodium butyrate, 1mM acetyl CoA and 0.55µg/ml recombinant polynucleosomes (H3.1; Active Motif) and the reaction mixture was incubated for 30 mins at 30°C. After incubation, loading dye and reducing agent were added before boiling the beads. 50 µg of overall protein was loaded onto either a 3-8% Tris-Acetate gel with Tris Acetate running buffer (to visualise CBP) or a 4-12% Bis-Tris gel with MOPS running buffer (to visualise H3K27ac). Chromatin Immunoprecipitation (ChIP) For ChIP experiments, Dox inducible cells were plated in 10 cm dishes, 2 plates per construct. Cells were induced with concentrations of Dox that were identified using western blot as inducing CBP-GFP without altering overall CBP expression levels ( Figure 4M & S4K-L). After 48h, cells were crosslinked at room temperature for 10 minutes using formaldehyde (1.1 % final). Crosslinking was quenched using 2.5 M Glycine (Melford, 125 mM final) incubating for 5 minutes at room temperature. Cells were harvested by cell scraping in PBS, and pelleted by centrifugation at 200 rcf for 5 minutes. Cell lysis was performed in ChIP lysis buffer 1 (50 mM HEPES-KOH (Sigma), pH 7.5 140 mM NaCl, 1 mM EDTA, 10 % Glycerol, 0.5 % NP40, 0.25 % Triton X – 100, Complete protease inhibitor cocktail (Roche)) by rotating at 4°C for 5 minutes. Nuclei were pelleted by centrifugation at 1500 rcf for 5 minutes, re-suspended in ChIP Buffer 2 (10 mM Tris-HCl pH 8.0, 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA (Sigma), Complete protease inhibitor cocktail) and incubated at room temperature on a rotator for 10 minutes. Nuclei were pelleted by centrifugation at 1500 rcf for 5 minutes and re-suspended in ChIP lysis buffer 3 (10 mM Tris-HCl pH 8.0, 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 0.1 % Na-deoxycholate, 0.5 % N-lauroylsarcosine (Sigma), Complete protease inhibitor cocktail) for shearing. Chromatin was sheared to 150 – 300 bp fragments, using the Bioruptor Pico (Diagenode), samples were sonicated for 12 cycles of 30 seconds on, 30 seconds off pulse sonication. Lysates were cleared by centrifugation at 20,000xg for 20 min. Concentrations of lysates was determined by BCA assay (ThermoFisher), IP’s were done with 900 μg of sheared protein in a total of 300 μl with ChIP IP buffer (10 mM Tris-HCl pH 8.0, 600 mM NaCl, 1 mM EDTA, 3 % Triton X-100, Complete protease inhibitor cocktail), input reactions were made for each sample with 90 μg of protein in 50 μl of ChIP IP buffer. Immunoprecipitations were performed by incubating with 4 μg of antibody overnight with rotation at 4°C. Immunocomplexes were recovered by adding blocked Protein G Dynabeads and incubated for 90 minutes at 4°C with rotation. Beads were washed 5 times in ChIP wash buffer (50 mM HEPES-KOH pH 7.5, 500 mM LiCl, 1 mM EDTA, 1 % NP40, 0.7 % Na-deoxycholate, 0.1 % N-lauroylsarcosine) and 1x in ChIP final wash buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA, 50 mM NaCl). Sample was eluted by incubation at 65°C for 30 min in ChIP elution buffer (50 mM Tris-HCl pH 8.0, 200 mM NaCl, 10 mM EDTA, 1 % SDS) with rotation in a thermomixer at 900 rpm. Cross-linking was reversed by incubation at 65°C overnight. Immunoprecipitated DNA was treated with RNase A (0.2 mg/ml final), supplemented with 4 mM CaCl 2 for 2 hours at 37°C, then Proteinase K (0.2 mg/ml final) for 2 hours at 55°C. DNA was then purified by phenol:chloroform extraction and ethanol precipitation and resuspended in 1x TE buffer. ChIP-seq library preparation For ChIP-seq, samples were prepared using NEBNext Ultra TM II DNA Library Prep Kit for Illumina (NEB, E7645) following manufacturers instructions. Briefly, fragmented DNA underwent 5’ phosphorylation and dA-Tailing to prepare the fragment ends for adapter ligation. Sample concentration was checked using Qubit dsDNA High Sensitivity (HS) kit (Thermo Fisher), to determine adapter dilutions. For input samples the adapters were not diluted, however a 1:25 dilution of adapters in 10 mM Tris-HCl pH 7.5, was performed for immunoprecipitation samples. A cleanup of the adapter ligation was performed using AMPure XP beads (Beckman Coulter) for size selection following the 200 bp protocol. PCR amplification was performed with 3 cycles of amplification for input samples, and 13 cycles of amplification for immunoprecipitation samples. A cleanup of the PCR reaction was performed using AMPure XP beads (Beckman Coulter), following protocol guidelines. Fragment sizes were checked before sequencing using the TapeStation (Agilent), using High Sensitivity DNA ScreenTape (Agilent). ChIP-seq data analysis ChIP-seq samples were sequenced using paired-end 150 sequencing on an Illumina NovaSeq 6000 platform (Novogene). Raw data quality was assessed using FastQC v0.11.9 81 and adapters were trimmed using Cutadapt v3.4 82 implemented in Trim Galore ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ ). Trimmed reads were aligned to human genome assembly GRCh38 using Burrows-Wheeler Alignment (BWA) v0.7.17-r1188 83 . For downstream analysis, replicates were merged and duplicate reads removed using Picard v2.27.4 ( https://broadinstitute.github.io/picard/ ), before read quality filtering using SAMTools v1.15.1 84 . BigWig files were generated by normalizing per million reads mapped (RPM) and converting to bedgraph format with Bedtools v2.30.0 85 , then to BigWig format using UCSC utilities (bedGraphToBigWig v377) 86 . ChIP-seq peaks were called on filtered data using MACS2 v2.2.7.1 60 using the BAMPE option and a broad peak cutoff of 0.001. All gene co-ordinates were obtained from Refseq. All initial processing, alignment and peak calling was completed as part of the Nextflow ChIP-seq pipeline v2.00 87 on the University of Sheffield High Performance Computing (HPC) cluster. Intersection of ChIP-seq peaks, calculation of relative distance plots 61 and Jaccard statistics 61 were done using Bedtools v2.31.0. For intersection with genome regions, intersection was made in the order Promoter (1kb window upstream of TSS) > Exons > Introns > Intergenic. Control peaks corresponding to each sample were calculated using bedtools shuffle, over a window restricted to 40kb upstream of transcription start sites on the same chromosome. Subsequent analysis was done using a local installation of DeepTools v3.5.5 88 . Read density coverage was calculated using multiBigwigSummary in 1kb bins over the entire genome; Correlation coefficients between samples were calculated using plotCorrelation; Heatmaps and metaplots displaying signals over a 5kb window aligned to peak centres were generated using computeMatrix and plotHeatmap; Read density enrichment over defined peak regions were calculated using plotEnrichment. All downstream analysis was done using R in Rstudio; significance p values for tag enrichment were calculated using a two-sided Mann-Whitney U-test in R 78 . All sequencing data analysed in this study have been deposited at NCBI’s GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and assigned the identifier GSE268266. Cleavage Under Targets and Release Using Nuclease (CUT&RUN) For CUT&RUN experiments, doxycycline inducible CBP-GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP cells were plated into 10 cm dishes and induced using the same concentrations of doxycycline as in ChIP experiments for 48 hours. 100,000 cells per reaction or input sample were harvested and DNA fragments were prepared using the CST CUT&RUN Assay kit according to the manufacturer’s instructions. In brief, 100,000 cells per reaction were harvested, washed and bound to concanavalin A coated magnetic beads. Antibodies for each reaction were added (0.5 µg IgG: Rabbit (DA1E) IgG (CST, part of CUT&RUN assay kit); 1 µg H3K27ac: Histone H3K27ac (Active Motif)) and incubated overnight at 4°C. pAG-MNase was added to each tube and incubated for 1 hour, then activated through the addiction of 3 mM CaCl 2 for 30 minutes at 4°C. Stop buffer was added, supplemented with 50 pg Spike-in DNA per sample (CST, part of CUT&RUN assay kit) and DNA fragments were eluted from the beads. DNA was then purified by phenol:chloroform extraction and ethanol precipitation and resuspended in 50 µl 1x TE buffer. CUT&RUN library preparation CUT&RUN DNA fragments were used to prepare libraries using the NEBNext Ultra II Library prep kit as described for ChIP-seq with the following changes. Adaptors were diluted for 1:10 for non-input samples and were cleaned up without size selection. Between 10-14 cycles of PCR were used for adaptor ligation dependent upon starting DNA concentration. CUT&RUN data analysis CUT&RUN sequencing data were processed and analyzed following a spike-in normalization strategy to enable quantitative comparisons across samples. Samples were sequenced using paired-end 150 sequencing on an Illumina NovaSeq 6000 platform (Novogene). Raw data quality was assessed using FastQC v0.11.9 81 and adapters were trimmed using Cutadapt v3.4 82 implemented in Trim Galore ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ ). Trimmed reads were aligned to two distinct reference genomes: Homo sapiens GRCh38 (Target genome) or S.cervisiae SacCer3 R64 (spike-in control genome) using bowtie2 v2.5.4 89 in very sensitive local alignment mode (--local –-very-sensitive-local –-no-unal –-no-mixed –-no-discordant –q –I 10 –X 700 –-dovetail –x), before read quality filtering using SAMTools v1.15.1 84 . We used featureCounts v2.0.6 90 to generate a count matrix for each sample containing the total number of reads uniquely mapping to the spike-in genome. This was used to calculate a scaling factor for each sample using DEseq2 v1.40.2 91 . To enable direct quantitative comparison of signal intensity across samples, normalized BigWig files were generated in MACS3 v3.0.0b1. Firstly we created bedgraph files using the callpeak function on MACS3, and then scaled by the previously calculated spike-in scaling factor. Normalized bedgraph files were then used to calculate the fold enrichment relative to the IgG background control. H3K27ac enriched peaks were called using MACS3. Peak intensity values from spike-in normalized BigWig files were then used for inter-sample comparisons and differential analyses using a local installation of DeepTools v3.5.3 88 as described previously for ChIPseq data. All sequencing data analysed in this study have been deposited at NCBI’s GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and assigned the identifier GSE299613 (CUT&RUN) . RNA-seq RNA extraction For RNA-seq doxycycline inducible CBP-GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP cells were plated into 10 cm dishes and induced using the same concentrations of doxycycline as described previously. RNA was extracted using TRIzol and chloroform, DNase treated to remove genomic DNA, then further purified with a subsequent phenol chloroform extraction and ethanol precipitation. RNA concentrations were measured using the broad range RNA Qubit kit (ThermoFisher). RNA-seq library preparation RNA-seq libraries were prepared using the Quant-seq 3’ mRNA-Seq Library Prep kit according to the manufacturer’s instructions. In brief, 500 ng RNA was used per sample for cDNA synthesis, subsequent RNA removal and purification. qPCR was used to identify the optimal number of cycles for PCR amplification: between 16-23 depending upon sample (qPCR Add-on Kit, Lexogen) and the cDNA was then amplified accordingly, followed by purification of the libraries using magnetic beads. RNA-seq data analysis RNA-seq samples were sequenced using paired-end 150 sequencing on an Illumina NovaSeq 6000 platform (Novogene). Following sequencing, Read 2 was discarded and downstream data analysis was performed using only Read 1, according to manufacturer’s recommendations for libraries prepared using the Quant-seq 3’ mRNA-Seq Library Prep kit. Raw data quality was assessed using FastQC v0.11.9(Babraham bioinformatics – FastQC A qu…) and adapters were trimmed using Cutadapt v3.4 (Martin 2011) implemented in Trim Galore ( https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ ). Reads were aligned using STAR (v2.7.6) 92 allowing soft-clipping of read ends during alignment to generate a geneCounts matrix. This was then used as input for all downstream analysis in DESeq2 v1.40.2 in Bioconductor 91 . All sequencing data analysed in this study have been deposited at NCBI’s GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and assigned the identifier GSE299614 (RNA-seq) . Computational analysis Identification of CBP-IDRs To predict disordered regions in CBP, we used DISOPRED3 93 and PONDR 37 disorder prediction software. Tested CBP-IDRs were determined using PONDR VSL2 predictor 37 , where stretches of amino acids that have a prediction of disorder above 50% were classed as intrinsically disordered regions 36 . A mutant was also generated spanning the region where CBP binds to FUS 38 we termed the CBP-FUS Interaction Domain (CFID). Analysis of CBP sequence properties NARDINI+ Sequence-level features of the target protein were analyzed using NARDINI+ (version 1.1) 43 , 44 implemented through a Colab Notebook. Analysis of Full length CBP wt was done using the ‘NARDINI+_from_accession’ iPython notebook with Uniprot accession Q92793 . IDRs identified by NARDINI were subsequently mapped to our CBP-IDRs identified using PONDR 37 . In particular, ‘IDR #1’ from NARDINI+ was not identified by PONDR, as it was less than 50 amino acids in length; IDR #7 from NARDINI+ corresponded to CBP AL . For individual IDR sequences and CBP shuffle mutant sequences, we implemented the ‘NARDINI+_from_fasta’ iPython notebook. The resulting quantitative z-score vectors were used to characterize the protein’s molecular grammar and predict its functional roles. localCIDER Analysis of sequence properties was carried out using a local installation of localCIDER 50 . Linear composition plots for full length CBP wt and CBP CFID were calculated using a blob length window of 200bp and 50bp respectively. PLAAC analysis PLAAC analysis was carried out using the web-based PLAAC server 55 . Generating shuffle variants Shuffle sequence variants were generated in GOOSE 52 using the ‘Constant residues variant’ option to randomly shuffle residues without changing the overall amino acid composition of the IDRs. AlphaFold structure prediction (version 2.3.2) All structure predictions were performed using AlphaFold version 2.3.2 35 implemented through a Colab notebook. We used the monomer model with relaxation and specified five recycles. AlphaFold produces a per-residue confidence metric called predicted local distance difference test (pLDDT) on a scale from 0 to 100. pLDDT estimates how well the prediction would agree with an experimental structure; a pLDDT >70 is considered to correspond to a generally correct backbone prediction 94 . To assess the confidence of predictions carried out on CBP C-termnal domains (Figure S3E), we provided a duplicate view of our model coloured by pLDDT score. All visualisation was done using UCSF ChimeraX 95 . Resource availability Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Daniel Bose ( d.bose{at}sheffield.ac.uk ). All plasmids generated for this study are available from Addgene. All unique/stable reagents generated in this study are available from the lead contact without restriction. The high-throughput sequencing data data from this publication have been deposited to the GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and assigned the identifiers GSE268266 (ChIP-seq), GSE299613 (CUT&RUN) and GSE299614 (RNA-seq). Datasets GSE268266 GSE299613 GSE299614 have been grouped under SuperSeries GSE299618 . Figure legends Download figure Open in new tab Figure S1 A-B) Analysis of PCR products from edited locus: (A) PCR using primers spanning the 3’ end of CBP wt ; (B) Inference of CRISPR Edits (ICE) 96 analysis of Sanger sequencing data from polyclonal CBP-Halo HEK293T (Top) and HEK293T control cells (bottom). C) RT-qPCR using primers for CBP or HaloTag in control HEK293T cells (orange) and CBP-Halo HEK293T cells (magenta). Bars represent mean ± s.e.m, n=3. D) AlphaFold v2.3.2 35 prediction for CBP wt . Domains are coloured the same as Figure 1H . E) Analysis of sequence composition and patterning in CBP-IDRs using NARDINI+ 43 , 44 which compares enrichment or depletion of compositional features relative to all human IDR-containing proteins. Features represented by negative z-scores are generally depleted in the IDR, while features with positive z-scores are generally enriched; features where –1 ≤ z ≤ +1 are not considered to be enriched or depleted compared to representation in all human IDRs 43 , 44 . Features referred to in the main text are highlighted in bold. F) CBP-IDR constructs used for OptoDroplet assay. G) Live-cell confocal microscopy images showing behaviour of all tested CBP-IDRs in OptoDroplet assay. Cells were imaged for 200s following exposure to blue light. Datasets for CBP IDR2 and CBP IDR5 were collected independently. Orange boxes indicate regions enlarged in bottom panel. Scale bars: 10 μm. Blue dashed box highlights data in Figure 1I . H-I) Optodroplet analysis of CBP IDR2 & CBP IDR5 . H) Fold change in the calculated SD of the grey values. Grey shading highlights the 32 second window used to calculate the initial rate of change. +ve, Opto-FUS IDR positive control; –ve, Opto-NLS negative control. Bars represent mean ± s.e.m, n=3; I) Initial rate of change over the first 32 seconds following blue light exposure. Bars represent mean ± s.e.m; significant p values are reported (ns, not significant), n=3. Download figure Open in new tab Figure S2 A) Western blot for CBP and GFP shows relative expression levels of transiently transfected CBP-GFP constructs. B) Reference images used to guide blind scoring for Figure 2C . C) Filtering strategy used for selecting transfected nuclei for analysis. Transfected nuclei were selected based on an intensity threshold 76 . GFP puncta were then filtered by: i) Area – to remove overexpression artefacts (e.g oversaturated fluorescent nuclei); ii) noise less than 3 pixels in diameter; iii) Circularity – to isolate single from overlapping puncta. Images show examples of nuclei removed by the filter, scale bars: 10 μm. D) Summary of filtering results. Highlighted populations are: Nuclei passing filter (Purple); Large area to remove oversaturated cells/nuclei with no clear puncta (dark blue); low circularity (<0.25) to remove overlapping puncta (light blue); Puncta < 3 pixels to remove speckle noise (salmon). E) Percentage of transfected nuclei for each condition remaining following application of the filter. F) Mean ± s.e.m and SD in the number of condensates per nuclei and mean IID ± s.e.m. G-I) Behaviour of CBP ΔIDR2 -GFP and CBP ΔIDR5 -GFP. G) Standard deviation in grey values for nuclei transfected with CBP-GFP. p values were calculated using a Kruskal-Wallis test; H) Number of condensates per nuclei following filtering. Dashed line represents a threshold value of 6 puncta per nuclei. Data points highlight individual nuclei from 3 biological replicates; I) Integrated intensity density (IID) of condensates. p values were calculated using a Kruskal-Wallis test. J) Calculated values for recovery rate over the time course following bleaching and the time to reach 50% pre-bleach intensity (T 1/2 ). K) Percentage of punctate nuclei following RNAse treatment. L) Number of CBP condensates per nucleus following RNAse treatment. M) CBP-IDR mutations have a dominant negative/positve effect on the behaviour of endogenous CBP condensates. CBP-Halo HEK293T cells were transfected with CBP wt -GFP, CBP ΔIDR6 -GFP or CBP ΔIDR7 -GFP for 24h. Endogenous CBP-Halo was labelled with Janelia FluorⓇ 646 Halo ligand (CBP-Halo JF646 ). N) Multiple channel control for live cell imaging in Figure S2J. CBP-Halo was labelled with Janelia Fluor Ⓡ 646 Halo ligand (CBP-Halo JF646 ). Download figure Open in new tab Figure S3 A-B) Randomly shuffled sequences for: A) CBP IDR6-shuffle and; B) CBP IDR7-shuffle calculated using GOOSE 52 . C) Percentage of transfected nuclei for each condition remaining after filtering. D) Percentage of punctate nuclei CBP wt , CBP IDR6-shuffle and CBP IDR7-shuffle . E) AlphaFold v2.3.2 35 prediction of CBP’s C-terminal domains. Left panel: The positions of the predicted interacting ɑ-helices CBP IDR6H2 (cyan), CBP IDR7H1 (dark blue), CBP IDR7H2 (light blue), and the CBP NCBD are highlighted; Right Panel) pLDDT confidence scores. F) Domain structure of the CBP CFID highlighting the positions of CBP IDR6 (cyan) and CBP IDR7 (light blue). CBP NCBD and predicted helices are highlighted. Dashed lines show the interactions between ɑ-helices predicted by AlphaFold v2.3.2 35 . G) Fixed cell confocal microscopy comparing the behaviour of CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP with CBP ΔIDR6H2 -GFP and CBP ΔIDR7H1 -GFP. Scale bars: 10 μm. H-I) Comparison of condensates formed by CBP ΔIDR6H2 -GFP and CBP ΔIDR7H1 -GFP with CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP. H) Number of puncta per nuclei; I) Integrated intensity density. p values were calculated using a Kruskal-Wallis test. J) Amino acid sequence conservation between CBP and p300 from local pairwise sequence alignment using EMBOSS Matcher 97 . N-term, regions N-terminal to the HAT domain residues CBP 1-1195; p300 1-1159. (Full alignments are available in Supplementary material). K) Comparison of sequence composition and patterning of CBP IDR6 and CBP IDR7 with p300 IDR6 and p300 IDR7 using NARDINI+ 43 , 44 . Features represented by negative z-scores are depleted in the IDR (relative to all human IDR proteins), while features with positive z-scores are enriched; features where –1 ≤ z ≤ +1 are not considered to be enriched or depleted compared to representation in all human IDRs 43 , 44 . Features referred to in the main text are highlighted in bold. L) PLAAC analysis 53 , 55 of CBP (purple) and p300 (Magenta) C-terminal regions. The relative positions of CBP IDR6 and CBP IDR7 are highlighted. Positions in p300 are based on local pairwise sequence alignment using EMBOSS Matcher 97 (Full alignments are available in Supplementary material). Download figure Open in new tab Figure S4 A) Western blot of CBP, GFP, K1535ac in the AL of CBP/p300 and H3K27ac and following treatment with 500nM A-485 for 36 hours 57 and 500nM Trichostatin A (TSA) 58 for 90 minutes. CBP was resolved using 3-8% Tris-Acetate PAGE (loading control: GAPDH A ) and H3K27ac was resolved using 12% Bis-Tris PAGE (loading control: GAPDH B ). B) Fixed cell confocal microscopy of CBP wt -GFP, CBP ΔIDR6 -GFP and CBP ΔIDR7 -GFP after 48h treatment with YYnM Trichostatin A (TSA), DMSO or no treatment. Scale bars: 5 μm. C-E) Effect of A-485 concentration on CBP condensate behaviour: C) Fixed cell confocal microscopy of CBP wt -GFP and CBP ΔIDR6 -GFP after 120 minutes treatment with stated concentration of A-485 (0 μm = DMSO). Scale bars: 5 μm; D) Number of condensates per nuclei; E) Integrated intensity density of condensates. Scale: Pseudo-log base 10. F) CBP AL constructs showing sequences of CBP wt , CBP ΔAL -GFP and CBP KTG -GFP. In CBP ΔAL -GFP the deleted region was replaced by a 12-residue flexible linker (blue); Lysine residues subject to acetylation are highlighted (red, bold); positions of K>G mutations are highlighted (orange, bold). G) Fixed cell confocal microscopy of CBP AL double mutant constructs. Scale bars: 10 μm H-I) Number of condensates per nucleus for CBP ΔAL -GFP and CBP KTG -GFP on a background of: H) CBP ΔIDR7 -GFP and I) CBP ΔCFID -GFP. J) K) Inducible CBP-GFP expression: CBP wt -GFP HEK293T cells were treated with 0-50ng/ml Doxycycline for 48h. Confocal microscopy images. Scale bars: 10μm; L) Inducible CBP-GFP expression: western blot for CBP and GFP. The concentration of Doxycycline that induced even CBP-GFP expression is highlighted (red) M-O) Behaviour of CBP-GFP condensates following Dox induction. L) Percentage of nuclei displaying diffuse or punctate signal; N) Number of condensates per nuclei; O) Integrated intensity density of condensates formed by CBP ΔIDR -GFP constructs. All p-values for IID were calculated using Kruskal-Wallis tests . P-Q) Quantification of western blots in Figure 4N : O) Foldchange in intensity of H3K27ac following normalisation to H4; P) Foldchange in intensity of CBP (K1535ac) following normalisation to CBP. (n=1). R) Quantification of western blots from immunoprecipitation HAT assay in Figure 4O . Intensity of H3K27ac following normalisation to H4 and CBP loading controls. Download figure Open in new tab Figure S5: CBP-IDRs regulate nuclear chromatin association and H3K27ac. A-B) Correlation between ChIP-seq datasets: A) Pearson’s correlation coefficient. Numbers denote 95% Confidence Interval (Upper and lower bounds); Degrees of freedom = 1,416,090; p < 2.2e - 16 for all values; B) R 2 . C-D) Read density enrichment at endogenous 14,913 endogenous CBP wt peaks identified in CBP ChIP-seq from CBP wt-Tet3G cells. C) Heatmaps showing a ±2.5-kb window from the centre of each called CBP peak. D) Boxplots show CBP ChIP-seq reads in HEK293T Tet3G cells (purple); GFP ChIP-seq reads in CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) and CBP IDR7 -GFP (dark blue). p values from Mann-Whitney U-test. E) Relative distance plots for CBP-GFP ChIP-seq peaks (GFP ChIP). When intervals are closer than expected by chance, distributions shift towards lower relative distance values. Shuffled control regions (green) were restricted to TSS –40 kb. F) Venn diagrams showing overlap between CBP binding sites in maternal HEK293T Tet3G lines (purple) and CBP-GFP cell lines; CBP wt -GFP (orange), CBP ΔIDR6 -GFP (light blue) and CBP IDR7 -GFP (dark blue). p values from permutation test with random regions restricted to TSS –40 kb; Jaccard statistic (J) measures overlap between two sets of intervals; perfect correlation = 1. G-H) Read density enrichment at 7,661 CBP wt -GFP peaks. E) H3K27ac; F) CBP-GFP. CBP ΔIDR6 -GFP (light blue) and CBP IDR7 -GFP sites were randomly downsampled to 7,661 peaks; p values from Mann-Whitney U test. H-I) Heatmaps of 4,657 common CBP peaks. Heatmaps show ±2.5 Kb window from the centre of peaks. H) CBP-GFP ChIP-seq; I) H3K27ac CUT&RUN. J-K) Read density enrichment at CBP binding sites unique to each CBP-IDR mutation. J) CBP-GFP; K) H3K27ac; p values from Mann-Whitney U test. Download figure Open in new tab Figure S6 A) Pearson correlation coefficient between RNA-seq datasets from inducible CBP-GFP HEK293T cell lines following induction of CBP-GFP expression using doxycycline ( Figure 4M & S4K). Data shows two biological replicates (Rep1/Rep2) for each CBP-IDR deletion. B) Principle Components Analysis (PCA) of all RNAseq datasets. C-D) Gene expression differences between: C) CBP wt -GFP and CBP ΔIDR6 -GFP; and D) CBP wt -GFP and CBP ΔIDR7 -GFP. Genes showing significant changes in expression (p<0.05) are highlighted (red points). Download figure Open in new tab Figure S7 B) Summary of the contribution of CBP-IDRs to CBP condensate behaviours relative to CBP wt -GFP. IDRs are clustered according to whether they are: N-terminal to the HAT domain; in the Autoregulatory Loop (AL); or C-terminal to the HAT domain. All behaviours refer to behaviour of CBP following deletion of each IDR, except the OptoDroplet data which is the behaviour of the IDR in isolation. Endogenous = behaviour of endogenous CBP condensates following transfection with CBP-GFP construct. Acknowledgements D.B. and AT are Sir Henry Dale Fellows, funded by the Wellcome Trust and the Royal Society (grant numbers 213501/Z/18/Z and 220192/Z/20/Z respectively); K.G., D.B., A.T. and T.D.C. are supported by a BBSRC Pioneer Award (grant number: BB/Y513453/1); K.G. was supported by a studentship from the White Rose BBSRC Doctoral Training Partnership (grant number: BB/M011151/1 ) ; L.J.H. was supported by a studentship from the Medical Research Council Discovery Medicine North (DiMeN) Doctoral Training Partnership (grant number: MR/N013840); N.A.C and G.G were supported by UoS PhD studentships and N.A.C by a UoS publication scholarship; T.D.C was funded by (BB/T008032/1); D.B also received funding from The Royal Society (grant number: RSG\R1\180410). M.D. is part of the Sheffield Bioinformatics Core team. At the University of Sheffield, we thank Susan Clark for support at the Flow Cytometry Core Facility; IT services for access to High Performance Computing and the Wolfson Light Microscopy Facility. The Nikon W1 spinning disk confocal was funded by a BBSRC ALERT2021 award (grant number: BB/V019368/1). This research was funded in whole, or in part, by the Wellcome Trust [213501/Z/18/Z and 220192/Z/20/Z]. For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Funder Information Declared Wellcome Trust , 213501/Z/18/Z , 220192/Z/20/Z Biotechnology and Biological Sciences Research Council , BB/Y513453/1 , BB/M011151/1 , BB/T008032/1 Medical Research Council , MR/N013840 Footnotes We are uploading a comprehensive revision of the previous manuscript, produced in response to peer review, and also reflecting improvements in available analysis software since our previous submission. 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