Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 Mar 19.
Published in final edited form as: Mol Cell. 2015 Feb 26;57(6):1047–1058. doi: 10.1016/j.molcel.2015.01.025

The Structure of A Biologically Active Estrogen Receptor-Coactivator Complex on DNA

Ping Yi 1,2,†, Zhao Wang 3,†, Qin Feng 1, Grigore D Pintilie 3, Charles E Foulds 1, Rainer B Lanz 1, Steven J Ludtke 3, Michael F Schmid 3, Wah Chiu 1,3,*, Bert W O’Malley 1,*
PMCID: PMC4369429  NIHMSID: NIHMS659755  PMID: 25728767

SUMMARY

Estrogen receptor (ER) is a transcription factor critical for development, reproduction, metabolism and cancer. ER function hinges on its ability to recruit primary and secondary coactivators, yet structural information on the full-length receptor-coactivator complex to complement pre-existing and sometimes controversial biochemical information is lacking. Here we use cryo-EM to determine the quaternary structure of an active complex of DNA-bound ERα, steroid receptor coactivator 3 (SRC-3) and a secondary coactivator (p300). Our structural model suggests the following assembly mechanism for the complex: each of the two ligand-bound ERα monomers independently recruits one SRC-3 protein via the transactivation domain of ERα; the two SRC-3s in turn bind to different regions of one p300 protein through multiple contacts. We also present structural evidence for the location of activation function 1 (AF-1) in a full-length nuclear receptor, which supports a role for AF-1 in SRC-3 recruitment.

INTRODUCTION

Transcription involves numerous interactions of coregulators in response to specific stimuli. Knowledge of the structure of transcription factor complexes is essential for a complete understanding of the transcriptional control of gene expression. ER belongs to the nuclear receptor superfamily of ligand-activated transcription factors. It contains a ligand-independent transactivation functional domain (AF-1) at the N-terminus, a central DNA binding domain (DBD), and a ligand-binding domain (LBD) at the C-terminus, which also has a ligand-dependent transactivation function (known as AF-2). Like many other transcription factors, ER function requires proper assembly of coactivator complexes and the recruitment of coactivators determines transcription outcome (Feng and O’Malley, 2014). The steroid receptor coactivator p160 family proteins (SRC-1/2/3) serve as primary coactivators that directly interact with estrogen-bound ER through conserved LXXLL motifs in their receptor interaction domains (Heery et al., 1997). They, in turn, recruit multiple secondary coactivators, such as the histone acetyltransferases (HATs) p300/CBP, to form a minimal receptor-coactivator complex that can promote chromatin remodeling and facilitate transcriptional activation. SRCs and p300 are among the first coactivators assembled with ER on ER targeted gene promoters (Metivier et al., 2003; Shang et al., 2000). Multiple biochemical studies have mapped the interaction regions between ER and SRCs, ER and p300, and SRCs and p300 (Heery et al., 1997; Kamei et al., 1996; Torchia et al., 1997). X-ray crystallography studies also have illustrated how the ligand-bound ERα LBD interacts with short LXXLL motif-containing peptides of SRCs (Brzozowski et al., 1997; Shiau et al., 1998). However, the structure of the full-length nuclear receptor in a complex with full-length coactivators has remained elusive. Moreover, controversies arise from these biochemical and peptide crystallography studies regarding whether one or two molecules of SRC interact with the NR dimer (Bovet et al., 2008; Gee et al., 1999; Margeat et al., 2001; Osz et al., 2012; Shiau et al., 1998; Zhang et al., 2004); whether one or two molecules of p300 participate in the complex and whether an interaction between the NR and p300 is important for complex assembly; whether coactivators also contact DNA; and whether there are induced structural changes in members of the complex following assembly (Demarest et al., 2002; Hanstein et al., 1996; Kamei et al., 1996; Kraus et al., 1999; Lee et al., 2001; Li et al., 2000; Millard et al., 2013; Waters et al., 2006). Furthermore, it remains unclear as to how SRCs bring in other secondary coactivators to NR targeted promoters and whether the constitutively active NR AF-1 domain plays any role in the NR-coactivator complex assembly.

Both SRC and p300/CBP can interact with different transcription factors and coactivators. These proteins appear to contain intrinsically disordered regions, but can convert to consistent structures when interacting with other proteins (Demarest et al., 2002; Millard et al., 2013; Waters et al., 2006). Indeed, we recently demonstrated that ER can form a very stable complex with coregulators on DNA (Foulds et al., 2013). It remains to be answered how the ER/SRC/p300 minimal complex retains the flexibility to interact with different coactivators while maintaining stability in the complex. Here we present the quaternary structure of a nuclear receptor and coactivator complex (~720 kDa), consisting of estrogen receptor alpha (ERα), SRC-3 and p300, bound to the 700bp estrogen response element (ERE), at a resolution of ~25 Å using electron cryo-microscopy (cryo-EM).

RESULTS

ERα, SRC-3 and p300 form an active protein complex on ERE DNA

SRC-3 plays an essential role in mediating ERα transcriptional activity (Shao et al., 2004) and is a rate-limiting factor for estrogen-dependent breast cancer cell growth (List et al., 2001). ChIP-seq (Chromatin Immunoprecipitation-sequencing) analysis has been used to assess the genome-wide binding of ERα and coactivators (Zwart et al., 2011). We carried out a similar analysis in MCF-7 breast cancer cells in order to demonstrate the presence of a biologically relevant ER-coactivator complex. We analyzed multiple publicly available ChIP-seq datasets, including two ERα cistromes (Carroll et al., 2005; Schmidt et al., 2010), our own SRC-3 dataset (Lanz et al., 2010) and recent ENCODE datasets for p300. Many of the DNA sequences that are pulled down by antibodies to both ERα and SRC-3 are also pulled down by antibodies to p300 (Figure 1A and Figure S1). As expected, these DNA sequences were enriched in motifs recognized by ERα. Further gene function enrichment analysis on presumptive target genes showed that these genes are responsive to estrogen and steroid hormone stimuli within the top-scoring annotation cluster. These bioinformatics results suggest that a significant amount of ERα/SRC-3/p300 complex exists in cells, is bound to ERE-DNA, and actively participates in ERα-targeted gene transcription.

Figure 1.

Figure 1

Open in a new tab

ERα, SRC-3 and p300 form an active transcription complex. (A) ChIP-seq analysis on the genome wide binding sites for ERα (Odom lab dataset (Schmidt et al., 2010)), SRC-3 and p300 in MCF-7 cells. (B) SRC-3 and p300 coactivate ERα-mediated in vitro transcription synergistically in the presence of estradiol. Data are represented as mean (+/−) SEM. Details of the in vitro transcription reaction are described in the Experimental Procedures. See also Figure S1.

Based on this information, we constructed the ERα/SRC-3/p300 complex from its purified components (Coomassie blue staining of the purified proteins are shown in Figure 2A), each of which was pre-tested for activity using an established in vitro transcription assay containing a nuclear extract that includes RNA polymerase and a very low amount of coactivators necessary for basal transcription (Foulds et al., 2013; Kraus and Kadonaga, 1998). As shown in Figure 1B, ERα alone has low transcriptional activity, while the addition of SRC-3 or p300 enhanced the ERα-driven transcription. Adding both SRC-3 and p300 synergistically enhances ER transactivation, suggesting that the complex of ERα/SRC-3/p300 is indeed transcriptionally active.

Figure 2.

Figure 2

Open in a new tab

The cryo-EM structure of ERE DNA and estrogen-bound ERα/SRC-3/p300 complex (A) Coomassie staining of the purified ERα, SRC-3 and p300 proteins. (B) Cryo-EM images of ERE-DNA/ERα/SRC-3/p300 complexes boxed out by white boxes and DNA indicated by white arrows. (C) Cryo-EM density map of the complex derived from EMAN2. Density map shows at a threshold of 0.5. (D) The 3D statistical variance map of the ERα-coactivator complex structure. Shown in red is the variance higher than 0.45 standard variation overlapped with the density of the complex. Higher variance was observed in SRC-3a, p300 densities and the interacting area between them. See also Figure S2.

We used this purified ERα/SRC-3/p300 complex, bound to an ERE-DNA fragment, for cryo-EM structure determination. We have carried out glycerol gradient ultracentrifugation on the DNA-bound complex (data not shown). We found that some lower glycerol gradient fractions contain only ERα but the SRC-3 and p300 proteins fall into the same continuous fractions in higher glycerol gradients together with ERα, suggesting that there are DNA-bound ERαs without forming complex with the coactivators – and that all of the SRC-3 and p300 are in the ERα complex. Figure 2B shows representative raw cryo-EM images of the complex. The individual complex has an asymmetric shape. In some views, density extending from the complex may represent DNA (Figure 2B white arrows). Using EMAN2 (Tang et al., 2007), we obtained a density map of the ERE-DNA/ERα/SRC-3/p300 complex with dimensions of 220×260×320 Å (Figure 2C). The resolution of the map was estimated to be 25 Å (Figure S2A) based on the gold standard definition with two independent maps (Henderson et al., 2012). To assure the reliability of this map, we employed a wide range of validation strategies. These validations included (see Experimental Procedures): agreement between projections and the map (Figure S2B and S2C), tilt-pair validation (Figure S2D), assessing particle orientation distribution (Figure S2E), and reprocessing of the image data using RELION, an alternative image processing software (Figure S2F). The overall structural features are fairly similar from the reconstructions using the two commonly used image reconstruction protocols (EMAN2 and RELION) regardless of their initial templates for the particle orientation refinement. This supports the reliability of the map and also suggests the potential variations among the particles. Such structural variation is further substantiated by the 3-D variance map (Chen et al., 2013; Penczek et al., 2006) based on the EMAN reconstruction (Figure 2C and S2G).

Localization of the protein components in the complex

p300 is an important HAT and an integrator essential for the function of numerous transcription factors (Chan and La Thangue, 2001; Goodman and Smolik, 2000). It is the largest component (300 kDa) of the ERE-DNA/ERα/SRC-3/p300 complex, and therefore is a logical choice for the first protein component to identify in the complex. Most attempts to dock a smaller component into a larger complex, particularly in a low resolution map, using cross-correlation simply fail; the smaller component, by the nature of the calculation, falls into the highest density (usually the center) of the complex. A more sensible approach is to label both the complex and p300 with the same monoclonal antibody, and use the mutual orientations of the labels to guide and validate the localization of p300 in the complex. Experimentally, we determined three additional cryo-EM structures (Figure 3 and Figure S3A): a p300-specific monoclonal antibody (Ab1) bound to the complex (Figure 3A), the same antibody bound to biochemically isolated p300 (Figure 3B) and also another monoclonal antibody (Ab2) bound to biochemically isolated p300 (Figure 3C). As a control, we also determined the structure of p300 alone (Figure S3A). The resolution of these maps and assessment of their reliability (Figs. S3 B–I) were confirmed as was done for the complex. Only the part of the antibody closest to the p300 is resolved, probably due to the flexibility of the non-antigen binding region of the antibody as commonly encountered in cryo-EM antibody labeling experiments (Serysheva et al., 2008). The p300 densities in the p300-Ab1 and p300-Ab2 maps are nearly identical and thus represent a strong validation of these two completely independent reconstructions (Supplementary Video 1). Our antibody maps also define the locations of the epitopes of the antibodies. Docking of p300-Ab1 into the complex-Ab1 density map (Supplementary Video 2) allows us to match the footprints of Ab1 in the two maps. The p300-Ab1 appears to fit within the density of the complex-Ab1.

Figure 3.

Figure 3

Open in a new tab

Antibody labeling of the p300. (A–B) Binding of a p300-specific monoclonal antibody (Ab1) to the ERE-DNA/ERα/SRC-3/p300 complex (A), or to the biochemically isolated p300 (B). (C) Binding of another p300-specific monoclonal antibody (Ab2) to the biochemically isolated p300. The p300 density is annotated in dark or light blue while the antibodies are annotated in yellow or brown. Densities were Weiner filtered according to the Fourier Shell Correlation (FSC) plot (Figure S3I). See also Figure S3 and Supplementary Video 1, 2 and 3.

Especially because p300 is an intrinsically disordered protein (Demarest et al., 2002), its structures alone may not necessarily be the same as that in the complex. Interestingly, our structure of p300 in the complex, as well as in the presence of either antibody, shows some structural variation from p300 alone, though the overall shapes are preserved (Supplementary Video 3, Figure S3A). In order to seek additional evidence to substantiate the molecular boundary of the p300, we used segmentation software Segger (Pintilie and Chiu, 2012) guided by these multiple p300 maps (See Experimental Procedures). In addition to locating the p300 density as assigned above, the segmentation results showed three other distinct segments (Figure 4A). By visual inspection, two of the segments (red and orange) have structural similarities, while the other segment (green) has internal 2-fold symmetry. The structural similarity of red and orange densities is confirmed by quantitative docking to each other (Figure S4A; Supplementary Video 4). The 2-fold symmetry of the green density is confirmed by a symmetry-detection procedure (see Experimental Procedures). Considering the fact that ERα forms a dimer, and each of the ERα monomers interacts with one SRC peptide (Shiau et al., 1998), we assigned the middle smaller segment as the ERα dimer (green) and the two side densities as SRC-3a (orange) and SRC-3b (red). Consistent with this assignment, the volume ratio between each of the two side densities and the middle density (1.3 and 1.4:1) is similar to the molecular weight ratio of 1.2:1 between SRC-3 monomer (160 kDa) and the ERα dimer (132 kDa).

Figure 4.

Figure 4

Open in a new tab

Identification of SRC-3 and ERα in the complex. (A) The segmentation of the complex (red, orange and green) after computationally removing the p300 density. These components were assigned to SRC-3a, SRC-3b and ERα as described in the text. 2-fold symmetry axes of the ERα (green arrow) and a fitted LBD crystal structure (purple arrow) are also shown. White solid axis shows another 2-fold axis found by symmetry search. (B) Localization of ERα AF-1 domain in the complex using AF-1-specific monoclonal antibody (yellow). Densities were Weiner filtered according to the FSC plot (Figure S3I). See also Figure S4 and Supplementary Video 4 and 5.

We should point out that our map has a much lower resolution than the crystal structure of LBD domain of ER and thus any computational search for the crystal structure in the cryo-EM map cannot be done with confidence. Thus, in order to locate the LBD domain, we took the approach of aligning the known pseudo 2-fold axis (purple arrow in Figure 4A) in the crystal structure (Brzozowski et al., 1997; Shiau et al., 1998) to the 2-fold symmetry axis of ERα in our map (green arrow in Figure 4A). Using a similar rationale, we also place a previous cryo-EM map of another nuclear receptor heterodimer (RXR/VDR) (Orlov et al., 2012) that lacks an AF-1 domain to the ERα in our map (Figure S4B). The segmented density of ERα in our map is larger than either of those previously determined domain structures because our map has the intact AF-1 domain. The segmentation procedure identified this density as being composed of three sub-segments, with the central segment being of roughly the same size as these docked maps and crystal structures of the LBD domain. We therefore attribute the two additional segmented densities on either side to the AF-1 domains of ERα (Figure 4A and Figure S4B).

To confirm the identity of the density assigned to the ERα AF-1 domain, we determined another cryo-EM structure of an AF-1 domain specific monoclonal antibody bound to the complex (Figure 4B). In the difference map between the complex with and without this antibody, we observed an extra density close to the interaction region of SRC-3 with ERα and adjacent to the LBD (AF-2) domain as discussed above. Interestingly, only one antibody was found in the complex, at the interface between SRC-3b and ERα, even though there are two AF-1 domains per complex in our proposed model. The absence of the other antibody can be attributed to steric interference by the SRC-3a density at the equivalent binding site on the other ERα subunit, because the interaction interfaces between ERα and each of the SRC-3s are different (Supplementary Video 5).

Multiple interactions between SRC-3 and p300

To biochemically confirm our observed multiple contacts between the SRC-3s and p300, we performed a co-IP experiment using exogenously expressed flag-tagged p300 fragments to precipitate endogenous SRC-3 (Figure 5B). We found that 4 regions of p300 are able to interact with SRC-3, including the primary SRC interaction domain (SRCID) at the C-terminus. This latter interaction is consistent with previous observations that the SRCID of p300 interacts with the CBP-interaction domain (CID) of SRC-3 (Kamei et al., 1996; Torchia et al., 1997). In our assay, the SRCID of p300 had the strongest binding to SRC-3, taking into account its significantly lower expression level compared to other p300 fragments. Since Ab2 recognizes residues 1921–2023 of p300 (Figure 5B, brown bar), which is located next to the SRCID (2033–2147), the Ab2 labeled p300 structure (Figure 3C) indicates that the SRCID region of p300 (the white arrow in Figure 5A) mainly interacts with SRC-3a, while some other regions of p300 interact with SRC-3b. Using a GST pull-down assay, we also observed several weak interactions between GST-SRC-3 fragments and full-length p300 protein with the CID of SRC-3 clearly displaying the best binding (Figure S5A), confirming multiple interactions between SRC-3 and p300.

Figure 5.

Figure 5

Open in a new tab

The structure of the ERE-DNA/ERα/SRC-3/p300 complex and functional analysis of the complex. (A) An annotated cryo-EM density map and a cartoon illustration of the ERα-coactivator complex. The white arrow indicates the C-terminal SRCID of p300 that mainly interacts with SRC-3a. (B) Multiple domains of p300 can interact with SRC-3. Schematic representation of the seven-domain structure of p300 is shown in the upper panel. The yellow and brown bars represent the Ab1 recognition region (774–1045) and Ab2 recognition region (1921–2023) respectively. Bottom panel, the interaction between SRC-3 and different flag tagged p300 fragments as assayed by co-immunoprecipitation (co-IP) using flag antibody. (C) The CID deletion mutant of SRC-3 loses the ability to recruit p300 to DNA-bound ERα in vitro. Purified ERα, SRC-3, and p300 were incubated in the presence of 1 μM estradiol with immobilized biotinylated EREs. The DNA-bound ERα, SRC-3, and p300 and those remaining unbound (supernatant) were visualized by Western blot analysis. (D) The CID deletion mutant loses the ability to coactivate ERα-mediated transcription in vitro. Purified SRC-3 WT or ΔCID mutant were added to ERα and HeLa nuclear extract in an in vitro transcription assay (as detailed in the Experimental Procedures). Data are represented as mean (+/−) SEM. (E) ERα and SRC-3 significantly increased p300 HAT activity toward histone H3 substrate. The left panel shows the 3H autoradiography of acetylated H3 and H4 proteins in the absence or presence of p300, SRC-3 and ERα. The right panel is the quantitation graph of the H3 and H4 acetylation levels. Data are represented as mean (+/−) SEM. See also Figure S5.

To further substantiate the above biological implication of our model, we generated a CID deletion mutant of SRC-3, which is predicted to lose the ability to recruit p300 to the DNA-bound complex. Shown in Figure 5C, p300 was associated with ERE-bound ERα in the presence of WT SRC-3, but not with the ΔCID mutant, nor in the absence of SRC-3 (see Figure S5B for the Coomassie staining of purified proteins). Deletion of the CID domain also completely abolished the coactivator activity of SRC-3 in our ERα-dependent in vitro transcription system (Figure 5D). Furthermore, it repressed basal transcriptional activity (Figure 5D lane 4 vs. lane 2), suggesting that it may serve as a dominant negative mutant because it replaces the functional endogenous SRC-3 with a binding-competent, but non-p300-recruiting form. In summary, our biochemical results strongly support our model of the core ERα-coactivator complex.

Ab1 recognizes residues 774–1045 in the middle of p300 next to the bromodomain (1038–1161; see Figure 5B yellow bar and Figure 3A and 3B), and is located on the opposite side of p300 from the C-terminal SRCID. The bromodomain is a conserved sequence found in many chromatin-associated proteins including HATs and it is important for p300 binding to chromatin, for acetyltransferase activity, and for its coactivator function (Kraus et al., 1999; Manning et al., 2001; Suganuma et al., 2002). With this orientation, the p300 protein is anchored to the ERE sequence region through SRC-3, and hence to ERα, while its bromodomain, and possibly the adjacent HAT domain, can still access nearby histones without incurring steric hindrance from either of the SRC-3s or from ERα.

Binding of SRC-3 and ERα alters p300 conformation and its HAT activity

Interestingly, when we analyzed the structure of p300 alone (Figure S3A), we found that it is very similar, but not identical to the corresponding p300 density in either the DNA-bound ERα-coactivator complex or p300-Ab1/p300-Ab2 (Figure S3A and Supplementary Videos 2, 3). Structural flexibility of p300 is a well-documented property based on previous biophysical evidence (Demarest et al., 2002; Waters et al., 2006). Since p300 has the HAT activity and this activity is important for ER-mediated transcriptional activation, we then asked whether the conformational state of p300 affects its HAT activity. As shown in Figure 5E, p300 alone but not SRC-3 alone can acetylate both histone H3 and H4. When SRC-3 was pre-incubated with p300, H3, but not H4, acetylation level was significantly increased. This H3 acetylation level was further enhanced when ERα was included in this reaction. In contrast to the WT SRC-3, the addition of SRC-3ΔCID mutant and ERα did not have any effect on the p300 HAT activity (Figure S5C), which is consistent with our structural data that SRC-3 induces a conformational change in p300. Histone acetylation is usually a landmark for active transcription. These results suggest that ERα and SRC-3 not only recruit p300 to the ER binding sites at the chromosome to acetylate histones, but also induce a conformational change of p300 to boost its acetylation activity toward histone H3, promoting a stronger activation of ER-targeted gene transcription. These biochemical results support our observation that p300 can adopt a different structure (and thus have a different function) in the complex than it has in isolation (Figure S3A).

DISCUSSION

The interpretation of our cryo-EM map (Figure 2) led to a model of spatial organization of all the components in this DNA-bound ERα-coactivator complex (Figure 5A). This structural model suggests the following mechanism for the assembly of the individual components into the complex: The ERα binds the ERE DNA as a dimer, and then recruits two SRC-3 proteins; these two SRC-3 proteins, in turn, secure one molecule of p300 to the complex through multiple contacts. p300 does not directly bind either DNA or ER.

The cryo-EM structure of the ER/SRC-3/p300 complex we present here not only reveals the structural organization of a transcriptionally active ER-coactivator complex but also provides information about the overall structure of individual proteins. Using an ERα AF-1 specific antibody, we are able to locate the AF-1 domain (A/B domain) within the full length ER protein (Figure 4A and B). Although several NR structures have been reported (Chandra et al., 2008; Chandra et al., 2013; Orlov et al., 2012), neither the location nor the structure of their AF-1 domains could be determined due to their high mobility or the absence of AF-1 domain in the crystal. We observe that the A/B domain is located in proximity to the LBD (AF-2) and it also participates in the SRC-3 recruitment together with AF-2. This structural organization allows potential intercommunication between the two domains, providing a structural support for previous observations of a direct interaction between the N- and C-terminal domains resulting in cooperativity in ER transactivation (Dutertre and Smith, 2003; Metivier et al., 2001; Onate et al., 1998). It also may allow cooperative interaction between other coactivators which bind AF-1 and AF-2.

The published crystal structures of the NR LBD in complex with a SRC NR box peptide provided a clear illustration about how NR LBD recruits SRC coactivators (Shiau et al., 1998). It was suggested that each of the ER monomers bind one SRC NR box peptide (Bovet et al., 2008; Shiau et al., 1998). In contrast, biochemical studies using NR and SRC NR box peptides or small fragments suggest that the stoichiometry of the NR and SRC interaction is 2:1 (Gee et al., 1999; Margeat et al., 2001; Osz et al., 2012). These biochemical observations led to hypotheses that either one SRC protein binds to one NR dimer, possibly using two consecutive NR boxes from one SRC binding to each of the NR LBD (Nolte et al., 1998) or that one LBD can remain unoccupied (Osz et al., 2012). Using full length SRC-3 protein and in the presence of p300 protein, our structure now settles this long-standing controversy concerning the stoichiometry of ERα and SRC. Two molecules of SRC-3 should be more efficient than one in recruiting p300 to allow SRC-3 to fulfill its adaptor role in assembly of a functional complex.

Interestingly, the conformation of this complex is not static. We found that the highest variability in the variance map (Figure 2D) within the complex involves SRC-3a and p300; additionally, our structure indicates relatively rigid binding between ERα and SRC-3b but a rather flexible interaction with SRC-3a. Therefore, it is conceivable that in the absence of p300 ERα may also bind the two SRCs non-equivalently with different binding strengths. If so, this may explain certain of the prior biochemical observations mentioned above. Since this ER and coactivator core complex can interact with many different coactivators that have no structural homology (Foulds et al., 2013), conformational flexibility would allow the core complex to adopt different conformations depending on the signaling, cellular and gene-specific context. Similar examples of conformational constraint or conformational change induced by coactivator binding have been previously observed in other transcription factors, such as VP16, p53 and c-Myc, as well as for the AF-1 domain of ER (Warnmark et al., 2003).

Since it appears that ERα and p300 both allow different orientations of SRC-3 to bind to them, they also may accommodate other SRC family members, and this raises the possibility that the two SRC proteins in a complex do not have to be the same molecular species. Indeed, it has been postulated that SRC-1:SRC-3 and SRC-2:SRC-3 heterodimers may form on ERα- or AR- targeted gene promoters (Zhang et al., 2004). The possibility of different SRCs and of other different coactivators being recruited by the same ERα dimer could allow diverse signals to impinge on ERα regulated-transcription simultaneously through regulation of diverse coactivators. It would be expected that different SRCs would have different preferences for recruiting additional coactivators. Combinations of SRCs would increase the complexity of ERα-mediated transactivation at the level of formation of the basal complex and would fine-tune transcription in response to different extra- or intra- cellular signals.

We observed that p300 is recruited to the DNA-bound ERα complex mainly through its interaction with SRC-3. This finding is consistent with a previous report, which suggests that SRCs mediate the interaction between p300 and ERα (Hanstein et al., 1996). Without SRC-3, we did not observe stable binding of p300 to ERα by cryo-EM. Although the N-terminus of p300/CBP was reported to interact directly with NRs, it has a minimal role in NR-mediated transcription (Kraus et al., 1999; Li et al., 2000). In contrast, the C-terminal SRC-interaction domain is clearly required for activating NRs (Kraus et al., 1999; Li et al., 2000). Our protein complex assembly experiment and in vitro transcription results using the CID deletion mutant of SRC-3 (Figure 5C and D) underline the importance of the SRC-3-p300 interaction for ERα-mediated transcription. The ChIP-seq analysis (Figure 1A and Figure S1) demonstrated that the vast majority of ERα and p300 co-binding sites in the genome are co-occupied by SRC-3 in estradiol-stimulated MCF-7 cells, providing in vivo evidence for the essential role of SRCs in recruiting p300 to ERα-targeted promoters.

Inspired by our model, various biochemical experiments were designed (Figure 5 and S5), which unanimously supported our quaternary structure assignments, the assembly pathway for the complex, and the biological implication in transcriptional control of gene expression. The AF-1 domain of ER is located proximate to the LBD/AF-2 domain to actively participate in the SRC-3 recruitment. A 3D-variance analysis and reconstructions using two different algorithms demonstrate that the whole complex remains consistent in shape and size but displays local flexibility (Figure 2D and Figure S2G), which is consistent with its ability to recruit additional coregulators. The p300 in different environments (alone or in complex with antibodies or co-activators) reflects its intrinsically disordered nature and conformational variability. This ER-coactivator complex structure provides an initial step toward our visual understanding of the assembly of a full transcriptionally active NR-coactivator complex. Our structures indeed can explain the conflicting observations of biochemistry and crystallography that studied only domains or peptides of some of the molecules involved.

EXPERIMENTAL PROCEDURES

ChIP seq analysis

Metagenomics data analysis was performed in a FileMaker 12 relational database management system. ER/SRC-3/p300-shared chromatin binding sites were determined on publicly available ChIP-Seq datasets (ER(Carroll et al., 2005; Schmidt et al., 2010), SRC-3 (Lanz et al., 2010), p300: ENCODE/HAIB P300/EP300 (sc-585)_SL13492 and _SL16335, NCBI GRCh37 (hg19), GSM1010800). Cistromes of older assemblies were brought to hg19 using the browser-based UCSC hgLiftOver tool (http://genome.ucsc.edu/cgi-bin/hgLiftOver). Shared binding sequences were assembled from ChIP-Seq peaks if they included any overlap. SeqPos motif tool v1.0.0 and CEAS – Enrichment on chromosome and annotation v1.0.0 run at Galaxy/Cistrome (http://cistrome.org/ap/root) were used to find enriched DNA sequence motifs and preferences for specific genomic regions, respectively, for the ERα/SRC-3/p300 reconstituted binding sites. Genes were called on the GRCh37.p5 assembly using the Extended Promoter Region (TSS − 7.5Kb, + 2.5 Kb) and ± 10Kb gene margin as previously described (Lanz et al., 2010) and DAVID Bioinformatics Resources 6.7 (PMIDs: 19131956, 19033363) (http://david.abcc.ncifcrf.gov/) was used for gene function analyses.

In vitro transcription assay

The nucleosomes were assembled using purified HeLa core histones and the pERE-E4 plasmid (a gift of W. Lee Kraus (Kraus and Kadonaga, 1998)), which contains 4 ERE sequences on the promoter region driving the transcription of E4 mRNA as described previously (Feng et al., 2006). The in vitro transcription reactions on chromatin templates were initiated by incubating 10 μl of assembled nucleosomes (with 100 ng of DNA) with 6 ng ERα, 100 nM estradiol (E2), 9 μM acetyl-CoA, 4 – 108 ng of SRC-3, and/or 300 ng of p300, with the addition of 50 μg of HeLa nuclear extract. The reactions were incubated at room temperature for 25 minutes followed by addition of 0.625 mM rNTPs to initiate transcription and incubation was continued at 30°C for 50 min. The transcribed E4 mRNAs were isolated, DNase-treated, and quantified by RT-qPCR. Statistical significance was determined by a two-tailed t-test from independent duplicates. Each experiment was performed at least two times. GraphPad InStat software was used for the statistical analysis, and the mean (+/−) SEM was shown.

Protein complex assembly on ERE containing DNA

Recombinant SRC-3 protein with a His tag at the N-terminus and a Flag tag at the C-terminus was produced in baculovirus and purified using nickel and anti-Flag affinity columns. 1 μg of biotinylated ERE DNA (921bp, PCR product made from pERE-E4 plasmid) was bound by 20 μl Dynabeads M280 streptavidin (Invitrogen). 0.6 μg of recombinant ERα (Invitrogen), SRC-3 and p300 (Protein one) proteins were then incubated with the DNA in the presence of 1 μM estradiol. The DNA-bound protein complex was then released from the Dynabeads by EcoRI restriction enzyme digestion.

Co-immunoprecipitation

Different Flag-tagged p300 fragments were transiently transfected into 293T cells. The cells were treated with 10μM MG132 for one day before harvesting in order to increase the levels of some p300 fragments which were not stable. Cells were lysed in lysis buffer (20mM Tris-HCl, pH 8.0, 125mM NaCl, 0.5% NP-40, 20mM NaF, 0.2mM Na3VO4, 2mM EDTA, 1mM DTT, and protease inhibitors) and 500 μg of cell lysates were subjected to precipitation with anti-Flag-M2 sepharose beads (Sigma). The associated endogenous SRC-3 protein was detected using anti-SRC-3 antibody (custom raised).

GST pull-down

Different GST-fused SRC-3 fragments were expressed in E. coli and bound by 5 μl of glutathione beads for 2 hrs at 4°C. After extensive washing, the beads were then incubated with 500 μg of MCF-7 cell nuclear extracts for 4 hrs. GST-SRC-3 associated p300 protein was determined by the Western blot analysis using p300-specific antibody (Santa Cruz N-15).

Antibody labeling

0.3 μg of p300 protein was incubated with an equal amount of p300 mouse monoclonal antibody (Novus Biological RW105, which recognizes residues 1921–2023 or Santa Cruz F-4 which recognizes residues 774–1045), 1mM DTT and 1X PBS buffer on ice for 1 hr before subjected to cryo-EM sample preparation. The antibody-labeling for the complex was carried out by incubating 0.1 μg of p300 antibody (Santa Cruz F-4) and ERα antibody (Santa Cruz D-12) with purified complex released from Dynabeads on ice for 1hr.

Histone acetylation assay

For in vitro histone acetylation assay, 0.3 μg recombinant p300 protein in the absence or presence of 0.2 μg SRC-3 WT or CID deletion mutant protein, 0.28 μg ERα protein were pre-incubated on ice for 30 min. The reaction mixture was then incubated with recombinant histone H3 and H4 (1 μg each per reaction) in a 20 μl reaction mixture containing 20 mM Tris-HCl (pH 8.0), 4 mM EDTA, 1 mM phenylmethylsulfonyl fluoride, 0.5 mM dithiothreitol, and 1μl 3H-Acetyl Coenzyme A (3.69 Ci/mmol; Perkin Elmer) for 1 h at 30°C. Reactions were stopped by the addition of 6× sodium dodecyl sulfate (SDS) loading buffer, and proteins were separated in a 4 to 15% SDS-polyacrylamide gel electrophoresis (PAGE) gel. Following fixation with buffer containing 50% methanol and 20% acetic acid, gels were treated with autoradiography Amplify reagent (Amersham Biosciences) for 20 min, dried, and exposed to X-ray films.

Cryo-EM specimen preparation and data collection

The sample was kept on ice before vitrification (Dubochet et al., 1988) on the grid. A 2.0 μl aliquot of the above-prepared samples was applied onto a continuous carbon film supported by a 200-mesh R1.2/1.3 Quantifoil grid. The grid was previously washed and glow discharged. After applying the sample, the grid was blotted and rapidly frozen in liquid ethane using a Vitrobot IV (FEI), with constant temperature and humidity during the process of blotting, and the grid was stored in liquid nitrogen before imaging. All grids were screened on JEM2010F electron cryo-microscope operated at 200 kV, spot size=2, condenser aperture = 70 μm and objective aperture = 60 μm. Images were recorded with a Gatan 4k×4k CCD camera (model no. 895, Gatan) at 50,000× microscope magnification, (2.16 Å/pixel sampling) and a dose of 25 electrons /Å2. A total of 806 CCD frames with a defocus range of 2–5 μm were collected for ERα-coactivator complex.

Following the same procedure, grids of the isolated p300 sample with antibody 1 and 2, complex with p300 antibody 1 and complex with ERα antibody were prepared. 130 CCD frames (p300 combined with antibody 1) and 174 CCD frames (p300 combined with antibody 2) were recorded on a JEM 2010F electron cryo-microscope operated at 200kV, using the same setting as above except the microscope magnification set at 30,000× (3.62 Å/pixel sampling). 131 CCD frames of complex with p300 antibody 1 and 199 CCD frames of complex with ERα antibody were recorded on JEM 2010F at 50,000× (2.16 Å/pixel sampling).

Cryo-EM data processing

All particle images were manually boxed with the EMAN2 program e2boxer.py. Defocus of the particles in each frame average was automatically determined by EMAN2 program e2ctf.py. Particles were then phase flipped and form stack files for further processing. 2D reference free class averages were computed by e2refine2d.py. Initial models for every reconstruction were generated from scratch by e2initialmodel.py program using selected 2D averages of good quality without applying any symmetry. 2D averages used in the first model generation and their corresponding projections for all the maps are shown in Figure S3H for the complex. Refinements were carried out with a final search angle of 2 degrees using e2refine.py program. Using the same protocol described above, we obtained maps for ERE-DNA/ERα/SRC-3/p300 complex + p300 antibody 1, the complex + ERα AF-1 antibody, free p300 with and without antibody 1/antibody 2 (Figure S3A). The numbers of particle images for these reconstructions are: 18,120 (complex), 3,088 (complex+p300 antibody1), 4,877 (complex+AF-1 antibody), 1,654 (p300+antibody 1), 3,048 (p300+antibody 2) and 3579 (p300). None of these maps was used as a reference to compute any other map to avoid any model bias.

Cryo-EM map validation

We validated the cryo-EM maps using several independent methods. First, as a necessary, but not sufficient condition for map accuracy, the orientation distribution of the particles is adequately represented in the data (Figure S2E, S3F). Second, another necessary but not sufficient condition, the final class averages match well with map projections (Figure S2B–C, S3C and H), demonstrating self-consistency of the final solution. Third, using a method which directly validates the accuracy of the structure, we performed a standard tilt-validation test, in which the same particles are imaged in two different orientations, and we insure that the map-predicted angles match the experimental angles (Henderson et al., 2011; Rosenthal and Henderson, 2003). 8 pairs of CCD images frames of the ERα complex were recorded on a JEM2010F electron microscope at magnifications of 50,000× (with a relative tilt of 30 degrees, along a known axis). 15 pairs of p300 images were recorded on a 30,000× magnification with a relative 20 degrees tilt. Some bad images were removed due to charging or drift. Each pair of particle images thus has a known experimental relative tilt. We then determined the orientation of each particle image in the pair using the final-reconstructed map of complex as references by e2tiltvalidate.py program provided by EMAN2 (Tang et al., 2007). The relative tilt between these computed orientations should match the experimental tilt. Each point represents one particle per tilt pair with radius representing computed relative tilt, and azimuth representing tilt angle (Figure S2D, S3G). Ideally all points would lie in exactly the same location; however, there is always some uncertainty in orientation determination, exacerbated in this case by radiation damage in the second image. As previously observed (Murray et al., 2013), if the map is incorrect, the relative angles would not correlate at all, and will produce a nearly random distribution over the sphere. Clear clusters as observed in our case the complex is successful validation.

Additional validation for ER complex map using EMAN2 and RELION reconstructions

We carried out an additional validation for the ER complex by refining the same particle data using two completely different software packages. Utilizing the final EMAN2 map (Figure S2F the first one from left) low-pass filtered to 60 Å (Figure S2F the second one), we performed a 3D auto refinement in RELION and obtained a map resolution of ~24 Å (Figure S2F, the third one). The 24 Å map strongly resembled the reconstruction produced by EMAN2 with only some localized differences. As a cross-validation, this map was then used as an initial model for another round of EMAN2 reconstruction. The resulting map (Figure S2F, the last one from left) appears almost identical to the original EMAN2 refinement, except for the flexible region near the core of the structure.

Conformational and compositional variability are handled differently by different cryo-EM software packages. For refinement EMAN2 uses projection matching combined with class-averaging (Tang et al., 2007), whereas RELION uses regularized maximum likelihood (Scheres, 2012) in Fourier space. We have demonstrated that with highly homogeneous particles (unpublished), the two packages produce virtually identical results to near-atomic resolution. However, when variability is present, the two software packages respond to inconsistent regions differently. It can thus be quite valuable to perform comparative refinements with the same data in both packages to gain some insight into which regions of the structure are the most contentious. This also provides a resolution limit beyond which the maps should not, and were not, interpreted. Variance maps, discussed below, also can play a valuable, but different, role.

Resolution evaluation and feature reliability

An estimate of the level of structural detail at which the data can confidently be interpreted as a convergent structure comes from the “gold standard” test (Henderson et al., 2012), wherein the raw data is randomly divided into two populations, which are then refined completely independently from one another, using two different starting models generated in EMAN2. The RELION refinement followed a similar gold-standard procedure. The resolution is estimated by the similarity of the two maps, in our case, 25 Å (Figure S2A) based on the FSC at 0.143 criterion (Rosenthal and Henderson, 2003; Scheres and Chen, 2012). The final map (Figure 2B) is obtained by merging the two maps followed by a Gaussian low pass filter based on the reported resolution to eliminate any unwarranted high-resolution details. Thus the visual features of this map should be quite trustworthy. We evaluated all density maps according to this “gold standard” test (FSC curves for all refinements are shown in Figure S2A and Figure S4I).

3-D variance map calculation

A 3-D standard deviation was estimated from 100 3-D reconstructions produced using random resampling of particles with replacement (Penczek et al., 2006) applied to individual classification information generated by the final refinement of 25 Å density map shown in Figure 2C. Individual particle images were low pass filtered at 25 Å before generating variance map.

Map post-processing (segmentation) and visualization

Maps were low pass filtered to the same resolution and aligned by Foldhunter before any further analysis. Antibody densities were determined according to difference maps generated by the proc3d program by EMAN1.8 (with a parameter of diffmap).

The entire complex is known to consist of 3 protein components: p300, ERα, and SRC-3. A semi-automated segmentation method was used, which applies repeated smoothing operations to the map while grouping watershed regions representing peaks in the density map (Demarest et al., 2002). The segmentation method is automated in the sense that the user does not define the shape and size of each region, however the user does have to decide how many smoothing steps to apply. This method has been shown to produce reliable segmentations of individual proteins in a variety of complexes especially at moderate resolutions (Demarest et al., 2002). While the boundaries between the segments naturally follow low-density areas, the final boundaries after smoothing and grouping are approximate and can mis-appropriate long narrow segments, for example. Hence the segments can be further refined manually by subtracting smaller segments from some regions and reassigning them to other segments. However, this was not done arbitrarily and was guided by multiple cryo-EM maps.

In the case of segmenting p300 in the complex, we took advantage of the availability of several different maps that contained p300 moiety to guide the decision on the final segmentation choice. After applying the smoothing procedure for 6 steps to the original ER complex map, 5 regions are obtained. Two of them appear to be similar to the p300-alone and p300-Ab maps. Docking the p300-Ab1 into these segments is such that the Ab1 in the p300 and the ER complex are superimposed. The similarity of the segments and the superimposition of the Ab1 convinced us that the segmentation and assignment of p300 in the complex map is correct. We adjusted the segmentation only slightly where p300 contacts other components as follows: a few small segments were removed from a non-p300 segment and added to the p300 segment so that the p300 segment more closely resembles p300-alone or with Ab1/Ab2. The remaining (non-p300) segments were attributed to be SRC-3a, SRC-3b, and ER, as further detailed in the main text.

Comparing structures of SRC-3a and SRC-3b

The two segmented densities attributed to SRC-3a and SRC-3b were first extracted from the map of the complex in order to compare them. The SRC-3b density was docked into the SRC-3a density via an exhaustive search that places it in various positions and orientations; each position/orientation constitutes a “docking”. For each docking, a cross-correlation is calculated between the two densities, which indicates how well they match in that particular position and orientation. The scores were sorted from highest to lowest (Figure S4A). The docking with the highest score of 0.86 places the two densities in a similar orientation; they are shown side by side in this orientation in Figure S4A and Supplementary Video 4. The z-score for this docking (how many standard deviations it is above the average of the next 10 lower scores) is 2.2, indicating moderate statistical significance of the docking, keeping in mind that at low resolutions, docking z-scores tend to be quite low. While the SRC-3a and SRC-3b densities are expected to vary because they bind p300 differently, this comparison shows the densities are still quantitatively and visually similar.

Docking the ERα crystal structure to the segmented density

In the crystal structure of the ERα dimer, the two LBD domains are related by a two-fold axis (Shiau et al., 1998). We searched for the 2-fold axis in the ERα segment in our map using an automated symmetry-finding procedure using e2symsearch3d (Tang et al., 2007). Two possible symmetric axes were found. When the two-axis of the crystal structure is aligned with one of the two possible dyad axes of the ER segment, their SRC contact points, seen in the crystal structure, also align properly with the two segments labeled SRC-3a and SRC-3b (Figure 4A). Conversely, aligning it with the other axis of the ER segment of the map does not allow these contacts to coincide. In the former two-fold axis alignment, the ERα LBD crystal structure also matches well with the density map.

Supplementary Material

1
Download video file (1.9MB, mp4)
2
Download video file (3.4MB, mp4)
3
Download video file (3MB, mp4)
4
Download video file (5.7MB, mp4)
5

Acknowledgments

This work is supported by Komen Foundation (5PG12221410) & Clayton Foundation Research grants (B.W.O.), DOD R038318-I (B.W.O.), NIH grants (HD8818 and NIDDK59820 to B.W.O.; P41GM103832 and R01GM079429 to W.C.; R01GM080139 to S.J.L.; K01DK084209 and P30DK079638PJ4 to Q.F.) and NCI Cancer Center Support Grant P30CA125123 (BCM Monoclonal Antibody/Recombinant Protein Expression Shared Resource).

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Accession number: All the cryo-EM maps have been deposited to EMDB (accession numbers (EMD-6241)

Author Contributions: P.Y., Z.W., M.F.S, W.C. and B.W.O conceived and designed the experiments. P.Y., Q.F. and C.E.F. performed the biochemical experiments. R.B.L analyzed ChIP-seq data. Z.W., G.D.P. and S.J.L. did cryo-EM imaging and computational analysis. P.Y., Z.W., G.D.P., M.F.S., W.C. and B.W.O. interpreted the data and wrote the manuscript. All the authors discussed the results and commented on the manuscript.

References

  1. Bovet C, Ruff M, Eiler S, Granger F, Wenzel R, Nazabal A, Moras D, Zenobi R. Monitoring ligand modulation of protein-protein interactions by mass spectrometry: estrogen receptor alpha-SRC1. Anal Chem. 2008;80:7833–7839. doi: 10.1021/ac8007169. [DOI] [PubMed] [Google Scholar]
  2. Brzozowski AM, Pike AC, Dauter Z, Hubbard RE, Bonn T, Engstrom O, Ohman L, Greene GL, Gustafsson JA, Carlquist M. Molecular basis of agonism and antagonism in the oestrogen receptor. Nature. 1997;389:753–758. doi: 10.1038/39645. [DOI] [PubMed] [Google Scholar]
  3. Carroll JS, Liu XS, Brodsky AS, Li W, Meyer CA, Szary AJ, Eeckhoute J, Shao W, Hestermann EV, Geistlinger TR, et al. Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein FoxA1. Cell. 2005;122:33–43. doi: 10.1016/j.cell.2005.05.008. [DOI] [PubMed] [Google Scholar]
  4. Chan HM, La Thangue NB. p300/CBP proteins: HATs for transcriptional bridges and scaffolds. J Cell Sci. 2001;114:2363–2373. doi: 10.1242/jcs.114.13.2363. [DOI] [PubMed] [Google Scholar]
  5. Chandra V, Huang P, Hamuro Y, Raghuram S, Wang Y, Burris TP, Rastinejad F. Structure of the intact PPAR-gamma-RXR- nuclear receptor complex on DNA. Nature. 2008;456:350–356. doi: 10.1038/nature07413. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chandra V, Huang P, Potluri N, Wu D, Kim Y, Rastinejad F. Multidomain integration in the structure of the HNF-4alpha nuclear receptor complex. Nature. 2013;495:394–398. doi: 10.1038/nature11966. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chen DH, Madan D, Weaver J, Lin Z, Schroder GF, Chiu W, Rye HS. Visualizing GroEL/ES in the act of encapsulating a folding protein. Cell. 2013;153:1354–1365. doi: 10.1016/j.cell.2013.04.052. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Demarest SJ, Martinez-Yamout M, Chung J, Chen H, Xu W, Dyson HJ, Evans RM, Wright PE. Mutual synergistic folding in recruitment of CBP/p300 by p160 nuclear receptor coactivators. Nature. 2002;415:549–553. doi: 10.1038/415549a. [DOI] [PubMed] [Google Scholar]
  9. Dubochet J, Adrian M, Chang JJ, Homo JC, Lepault J, McDowall AW, Schultz P. Cryo-electron microscopy of vitrified specimens. Q Rev Biophys. 1988;21:129–228. doi: 10.1017/s0033583500004297. [DOI] [PubMed] [Google Scholar]
  10. Dutertre M, Smith CL. Ligand-independent interactions of p160/steroid receptor coactivators and CREB-binding protein (CBP) with estrogen receptor-alpha: regulation by phosphorylation sites in the A/B region depends on other receptor domains. Mol Endocrinol. 2003;17:1296–1314. doi: 10.1210/me.2001-0316. [DOI] [PubMed] [Google Scholar]
  11. Feng Q, O’Malley BW. Nuclear receptor modulation – Role of coregulators in selective estrogen receptor modulator (SERM) actions. Steroids. 2014 doi: 10.1016/j.steroids.2014.06.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Feng Q, Yi P, Wong J, O’Malley BW. Signaling within a coactivator complex: methylation of SRC-3/AIB1 is a molecular switch for complex disassembly. Mol Cell Biol. 2006;26:7846–7857. doi: 10.1128/MCB.00568-06. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Foulds CE, Feng Q, Ding C, Bailey S, Hunsaker TL, Malovannaya A, Hamilton RA, Gates LA, Zhang Z, Li C, et al. Proteomic Analysis of Coregulators Bound to ERalpha on DNA and Nucleosomes Reveals Coregulator Dynamics. Mol Cell. 2013;51:185–199. doi: 10.1016/j.molcel.2013.06.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gee AC, Carlson KE, Martini PG, Katzenellenbogen BS, Katzenellenbogen JA. Coactivator peptides have a differential stabilizing effect on the binding of estrogens and antiestrogens with the estrogen receptor. Mol Endocrinol. 1999;13:1912–1923. doi: 10.1210/mend.13.11.0373. [DOI] [PubMed] [Google Scholar]
  15. Goodman RH, Smolik S. CBP/p300 in cell growth, transformation, and development. Genes Dev. 2000;14:1553–1577. [PubMed] [Google Scholar]
  16. Hanstein B, Eckner R, DiRenzo J, Halachmi S, Liu H, Searcy B, Kurokawa R, Brown M. p300 is a component of an estrogen receptor coactivator complex. Proc Natl Acad Sci U S A. 1996;93:11540–11545. doi: 10.1073/pnas.93.21.11540. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Heery DM, Kalkhoven E, Hoare S, Parker MG. A signature motif in transcriptional co-activators mediates binding to nuclear receptors. Nature. 1997;387:733–736. doi: 10.1038/42750. [DOI] [PubMed] [Google Scholar]
  18. Henderson R, Chen S, Chen JZ, Grigorieff N, Passmore LA, Ciccarelli L, Rubinstein JL, Crowther RA, Stewart PL, Rosenthal PB. Tilt-pair analysis of images from a range of different specimens in single-particle electron cryomicroscopy. J Mol Biol. 2011;413:1028–1046. doi: 10.1016/j.jmb.2011.09.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Henderson R, Sali A, Baker ML, Carragher B, Devkota B, Downing KH, Egelman EH, Feng Z, Frank J, Grigorieff N, et al. Outcome of the first electron microscopy validation task force meeting. Structure. 2012;20:205–214. doi: 10.1016/j.str.2011.12.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kamei Y, Xu L, Heinzel T, Torchia J, Kurokawa R, Gloss B, Lin SC, Heyman RA, Rose DW, Glass CK, et al. A CBP integrator complex mediates transcriptional activation and AP-1 inhibition by nuclear receptors. Cell. 1996;85:403–414. doi: 10.1016/s0092-8674(00)81118-6. [DOI] [PubMed] [Google Scholar]
  21. Kraus WL, Kadonaga JT. p300 and estrogen receptor cooperatively activate transcription via differential enhancement of initiation and reinitiation. Genes Dev. 1998;12:331–342. doi: 10.1101/gad.12.3.331. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kraus WL, Manning ET, Kadonaga JT. Biochemical analysis of distinct activation functions in p300 that enhance transcription initiation with chromatin templates. Mol Cell Biol. 1999;19:8123–8135. doi: 10.1128/mcb.19.12.8123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lanz RB, Bulynko Y, Malovannaya A, Labhart P, Wang L, Li W, Qin J, Harper M, O’Malley BW. Global characterization of transcriptional impact of the SRC-3 coregulator. Mol Endocrinol. 2010;24:859–872. doi: 10.1210/me.2009-0499. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Lee JW, Lee YC, Na SY, Jung DJ, Lee SK. Transcriptional coregulators of the nuclear receptor superfamily: coactivators and corepressors. Cell Mol Life Sci. 2001;58:289–297. doi: 10.1007/PL00000856. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Li J, O’Malley BW, Wong J. p300 requires its histone acetyltransferase activity and SRC-1 interaction domain to facilitate thyroid hormone receptor activation in chromatin. Mol Cell Biol. 2000;20:2031–2042. doi: 10.1128/mcb.20.6.2031-2042.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. List HJ, Lauritsen KJ, Reiter R, Powers C, Wellstein A, Riegel AT. Ribozyme targeting demonstrates that the nuclear receptor coactivator AIB1 is a rate-limiting factor for estrogen-dependent growth of human MCF-7 breast cancer cells. J Biol Chem. 2001;276:23763–23768. doi: 10.1074/jbc.M102397200. [DOI] [PubMed] [Google Scholar]
  27. Manning ET, Ikehara T, Ito T, Kadonaga JT, Kraus WL. p300 forms a stable, template-committed complex with chromatin: role for the bromodomain. Mol Cell Biol. 2001;21:3876–3887. doi: 10.1128/MCB.21.12.3876-3887.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Margeat E, Poujol N, Boulahtouf A, Chen Y, Muller JD, Gratton E, Cavailles V, Royer CA. The human estrogen receptor alpha dimer binds a single SRC-1 coactivator molecule with an affinity dictated by agonist structure. J Mol Biol. 2001;306:433–442. doi: 10.1006/jmbi.2000.4418. [DOI] [PubMed] [Google Scholar]
  29. Metivier R, Penot G, Flouriot G, Pakdel F. Synergism between ERalpha transactivation function 1 (AF-1) and AF-2 mediated by steroid receptor coactivator protein-1: requirement for the AF-1 alpha-helical core and for a direct interaction between the N- and C-terminal domains. Mol Endocrinol. 2001;15:1953–1970. doi: 10.1210/mend.15.11.0727. [DOI] [PubMed] [Google Scholar]
  30. Metivier R, Penot G, Hubner MR, Reid G, Brand H, Kos M, Gannon F. Estrogen receptor-alpha directs ordered, cyclical, and combinatorial recruitment of cofactors on a natural target promoter. Cell. 2003;115:751–763. doi: 10.1016/s0092-8674(03)00934-6. [DOI] [PubMed] [Google Scholar]
  31. Millard CJ, Watson PJ, Fairall L, Schwabe JW. An evolving understanding of nuclear receptor coregulator proteins. J Mol Endocrinol. 2013;51:T23–36. doi: 10.1530/JME-13-0227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Murray SC, Flanagan J, Popova OB, Chiu W, Ludtke SJ, Serysheva II. Validation of Cryo-EM Structure of IP3R1 Channel. Structure. 2013;21:900–909. doi: 10.1016/j.str.2013.04.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Nolte RT, Wisely GB, Westin S, Cobb JE, Lambert MH, Kurokawa R, Rosenfeld MG, Willson TM, Glass CK, Milburn MV. Ligand binding and co-activator assembly of the peroxisome proliferator-activated receptor-gamma. Nature. 1998;395:137–143. doi: 10.1038/25931. [DOI] [PubMed] [Google Scholar]
  34. Onate SA, Boonyaratanakornkit V, Spencer TE, Tsai SY, Tsai MJ, Edwards DP, O’Malley BW. The steroid receptor coactivator-1 contains multiple receptor interacting and activation domains that cooperatively enhance the activation function 1 (AF1) and AF2 domains of steroid receptors. J Biol Chem. 1998;273:12101–12108. doi: 10.1074/jbc.273.20.12101. [DOI] [PubMed] [Google Scholar]
  35. Orlov I, Rochel N, Moras D, Klaholz BP. Structure of the full human RXR/VDR nuclear receptor heterodimer complex with its DR3 target DNA. Embo J. 2012;31:291–300. doi: 10.1038/emboj.2011.445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Osz J, Brelivet Y, Peluso-Iltis C, Cura V, Eiler S, Ruff M, Bourguet W, Rochel N, Moras D. Structural basis for a molecular allosteric control mechanism of cofactor binding to nuclear receptors. Proc Natl Acad Sci U S A. 2012;109:E588–594. doi: 10.1073/pnas.1118192109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Penczek PA, Frank J, Spahn CM. A method of focused classification, based on the bootstrap 3D variance analysis, and its application to EF-G-dependent translocation. J Struct Biol. 2006;154:184–194. doi: 10.1016/j.jsb.2005.12.013. [DOI] [PubMed] [Google Scholar]
  38. Pintilie G, Chiu W. Comparison of Segger and other methods for segmentation and rigid-body docking of molecular components in cryo-EM density maps. Biopolymers. 2012;97:742–760. doi: 10.1002/bip.22074. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Rosenthal PB, Henderson R. Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy. J Mol Biol. 2003;333:721–745. doi: 10.1016/j.jmb.2003.07.013. [DOI] [PubMed] [Google Scholar]
  40. Scheres SH. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J Struct Biol. 2012;180:519–530. doi: 10.1016/j.jsb.2012.09.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Scheres SH, Chen S. Prevention of overfitting in cryo-EM structure determination. Nat Methods. 2012;9:853–854. doi: 10.1038/nmeth.2115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Schmidt D, Schwalie PC, Ross-Innes CS, Hurtado A, Brown GD, Carroll JS, Flicek P, Odom DT. A CTCF-independent role for cohesin in tissue-specific transcription. Genome Res. 2010;20:578–588. doi: 10.1101/gr.100479.109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Serysheva II, Ludtke SJ, Baker ML, Cong Y, Topf M, Eramian D, Sali A, Hamilton SL, Chiu W. Subnanometer-resolution electron cryomicroscopy-based domain models for the cytoplasmic region of skeletal muscle RyR channel. Proc Natl Acad Sci U S A. 2008;105:9610–9615. doi: 10.1073/pnas.0803189105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Shang Y, Hu X, DiRenzo J, Lazar MA, Brown M. Cofactor dynamics and sufficiency in estrogen receptor-regulated transcription. Cell. 2000;103:843–852. doi: 10.1016/s0092-8674(00)00188-4. [DOI] [PubMed] [Google Scholar]
  45. Shao W, Keeton EK, McDonnell DP, Brown M. Coactivator AIB1 links estrogen receptor transcriptional activity and stability. Proc Natl Acad Sci U S A. 2004;101:11599–11604. doi: 10.1073/pnas.0402997101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Shiau AK, Barstad D, Loria PM, Cheng L, Kushner PJ, Agard DA, Greene GL. The structural basis of estrogen receptor/coactivator recognition and the antagonism of this interaction by tamoxifen. Cell. 1998;95:927–937. doi: 10.1016/s0092-8674(00)81717-1. [DOI] [PubMed] [Google Scholar]
  47. Suganuma T, Kawabata M, Ohshima T, Ikeda MA. Growth suppression of human carcinoma cells by reintroduction of the p300 coactivator. Proc Natl Acad Sci U S A. 2002;99:13073–13078. doi: 10.1073/pnas.192586699. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Tang G, Peng L, Baldwin PR, Mann DS, Jiang W, Rees I, Ludtke SJ. EMAN2: an extensible image processing suite for electron microscopy. J Struct Biol. 2007;157:38–46. doi: 10.1016/j.jsb.2006.05.009. [DOI] [PubMed] [Google Scholar]
  49. Torchia J, Rose DW, Inostroza J, Kamei Y, Westin S, Glass CK, Rosenfeld MG. The transcriptional co-activator p/CIP binds CBP and mediates nuclear-receptor function. Nature. 1997;387:677–684. doi: 10.1038/42652. [DOI] [PubMed] [Google Scholar]
  50. Warnmark A, Treuter E, Wright AP, Gustafsson JA. Activation functions 1 and 2 of nuclear receptors: molecular strategies for transcriptional activation. Mol Endocrinol. 2003;17:1901–1909. doi: 10.1210/me.2002-0384. [DOI] [PubMed] [Google Scholar]
  51. Waters L, Yue B, Veverka V, Renshaw P, Bramham J, Matsuda S, Frenkiel T, Kelly G, Muskett F, Carr M, et al. Structural diversity in p160/CREB-binding protein coactivator complexes. J Biol Chem. 2006;281:14787–14795. doi: 10.1074/jbc.M600237200. [DOI] [PubMed] [Google Scholar]
  52. Zhang H, Yi X, Sun X, Yin N, Shi B, Wu H, Wang D, Wu G, Shang Y. Differential gene regulation by the SRC family of coactivators. Genes Dev. 2004;18:1753–1765. doi: 10.1101/gad.1194704. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Zwart W, Theodorou V, Kok M, Canisius S, Linn S, Carroll JS. Oestrogen receptor-co-factor-chromatin specificity in the transcriptional regulation of breast cancer. Embo J. 2011;30:4764–4776. doi: 10.1038/emboj.2011.368. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
Download video file (1.9MB, mp4)
2
Download video file (3.4MB, mp4)
3
Download video file (3MB, mp4)
4
Download video file (5.7MB, mp4)
5
NIHMS659755-supplement-5.pdf (4.4MB, pdf)

RESOURCES