Molecular dynamics and nuclear receptor function

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Vol.16 No.1 Jan/Feb 2005

Molecular dynamics and nuclear receptor function Cruz A.D. Hinojos1, Z. Dave Sharp2 and Michael A. Mancini1 1

Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza, Houston TX 77030, USA University of Texas Health Science Center at San Antonio, Institute of Biotechnology, Department of Molecular Medicine, 15355 Lambda Drive, San Antonio TX 78245, USA 2

The development of live cell and biochemical analysis methods has led to an increase in our understanding of the dynamic regulation of transcription. Live single cell studies using photobleaching techniques indicate that many proteins have a high nuclear mobility. Pioneering work using promoter array systems based on the lac operon or the mouse mammary tumor virus promoter enabled the study of chromatin structure, promoter occupancy and protein–chromatin interaction dynamics in relation to transcription. Chromatin immunoprecipitation (ChIP)-based assays allow an exhaustive analysis of the temporal recruitment of proteins to an endogenous promoter and provide evidence of cyclic protein– protein and protein–promoter interactions. Although reflecting different timescales, both ChIP and live cell studies indicate a highly dynamic control of transcription that until now has gone undetected and unappreciated. Diverse processes such as reproduction, development, metabolism and tumorigenesis are genetically regulated to a large degree by a superfamily of transcription factors termed nuclear receptors (NRs). These receptors mediate their actions either without ligands or by binding hormones or other metabolic signaling molecules. In both states, they interact with cognate sequences (e.g. hormone response elements) in gene promoters or enhancers to regulate transcription. To accomplish such diverse physiological responses, NRs repress or activate the transcription of target genes through varied interactions with a large group of transcription coregulators. Nuclear receptor coregulators, as with other transcription factors, mediate chromatin modifications leading to repressed or activated states of target genes specific for different physiological goals. Classically, the coregulation of NR-mediated transcription is thought to occur through the formation of stable multiprotein complexes. These complexes, identified by biochemical approaches using cell lysates or purified components, participate in either a combinatorial or a sequential fashion to promote or to inhibit transcription (reviewed in Ref. [1]). By contrast, recent studies making use of technological advances in microscopy and genetically engineered cell lines in live cell studies indicate that Corresponding author: Mancini, M.A. ([email protected]). Available online 7 December 2004

NRs and coregulators have a high rate of movement and rapidly exchange with target promoters. The principal technique used to measure protein mobility is fluorescence recovery after photobleaching (FRAP), although variant approaches including inverse FRAP and fluorescence loss in photobleaching (FLIP) have been also used [2–4]. From these studies has emerged an appreciation that highly dynamic interactions are involved in the regulation of NR-mediated transcription. The current challenge is to reconcile the classic model of stable protein complexes as transcription regulators with these emerging concepts of molecular dynamics. In this review, we discuss recent advances in assessing the dynamics of transcription and compare and contrast the results from live cell studies with those from biochemical studies. The NR transcriptional model Biochemical approaches have provided the bulk of evidence contributing to our understanding of transcription factor mechanisms of the transcription process. Functional approaches have largely focused on either the in vitro binding and reconstitution of transcription complexes or the transient transfection of cultured cells coupled with determination of reporter activity. On the basis of these studies, a generally accepted combinatorial model of NR transcriptional regulation has emerged [1,5]. The model posits that NRs recruit variable combinations of coregulators to a promoter depending on ligand availability. In the antagonized state, the promoterlocalized NR recruits a corepressor complex comprising histone deacetylases and NR corepressors. These complexes are thought to generate a transcriptionally prohibitive environment through differential histone modifications (e.g. acetylation or methylation) [6]. Alternatively, binding of an agonist to the NR induces the release of the corepressor complex from the promoter and the sequential recruitment of several coactivator complexes with the end result being transcriptional initiation. The model proposes that, after agonist binding to the NR, the corepressor complex is replaced by a chromatin remodeling complex that includes the ATP-coupled SWI/SNF complex. This facilitates the recruitment of a third complex containing histone acetylases [the steroid receptor coactivator (SRC)/p160 family or CREB-binding protein (CBP)/p300], histone methylases

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[coactivator-associated arginine methyltransferase-1 (CARM-1) and protein arginine methyltransferase-1 (PRMT-1)], members of the basal transcription machinery [TATA-binding proteins (TBPs) and TBP-associated factors)], and RNA polymerase II (Pol II). Transcription initiation is then influenced by the action of a complex comprising vitamin D receptor interacting protein (DRIP) and thyroid receptor associated protein (TRAP). Specificity is generated by, first, the functional redundancy of many of the coregulators, which results in an exponential number of protein combinations within a complex; second, the promoter-specific recruitment of coregulators; and third, the modulation of coregulators by signal transduction pathways. An overall view arising from these studies is that transcription is regulated through the recruitment of stable protein complexes, which each has a distinct function. This model of NR-mediated transcription has been tested in cell populations by ChIP-based assays with great success. ChIP studies Cyclic association of the estrogen receptor with endogenous promoters Recent advances in biochemical approaches (i.e. ChIP) have revealed that the regulation of NR and coregulator function is dynamic. ChIP assays involve the following steps: (i) crosslinking the tissue or cells with formaldehyde; (ii) fragmenting the chromatin; (iii) immunoprecipitating the chromatin fragments with antibodies to NRs or coregulators; (iv) reversing the crosslinking; and (v) detecting the promoter DNA. Recent advances include the availability of more highly specific antibodies and the use of polymerase chain reaction (PCR) to detect DNA, facilitating a more comprehensive analysis of promoter occupancy and greatly increasing the detection sensitivity, respectively (reviewed in [7]). The utility of ChIP to assess indirectly the occupancy of endogenous promoters by NRs and coregulators has provided a technical means by which to test the transcription model at an endogenous promoter. Such ChIP studies have yielded unexpected insights into NR regulation. In a seminal paper by Shang et al. [8], ChIP coupled with PCR has been used to assess indirectly the occupancy of endogenous estrogen-responsive promoters (cathepsin D, pS2 and c-Myc) by the estrogen receptor-a (ER) bound either to an agonist, estradiol or estrogen (E2), or to a partial agonist, 4-hydroxytamoxifen (4HT), as well as by coregulators in an MCF-7 breast cancer cell line [8]. In this bulk population-based approach, the cells were chemically treated with a reversible crosslinking agent (formaldehyde; see below), the chromatin was sheared, and the fragments were immunoprecipitated with antisera to proteins that might be crosslinked to the promoter. Quantitative PCR was then used to detect the promoter DNA in the immunoprecipitated pellet. As predicted, E2 induced occupancy of the E2-responsive promoters by both the ER and members of the p160 family of coactivators, including SRC-1, SRC-3 and glucocorticoid receptor interacting protein 1 (GRIP1). By contrast, 4HT was shown to induce occupancy of the promoters by the ER and the corepressors nuclear receptor corepressor (N-CoR) and www.sciencedirect.com

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silencing mediator of retinoic acid and thyroid hormone receptor (SMRT). Shang et al. [8] extended ChIP analysis in an approach termed ‘kinetic ChIP’ by introducing a temporal component to investigate the averaged, ordered assembly of the ER transcription complex on the cathepsin D promoter. Remarkably, after promoter clearance and synchronization by the RNA Pol II inhibitor a-amanitin [8] and in the absence of E2, the ER was observed to cycle on and off the ER-responsive promoters with a cycling periodicity of about 20 min, although RNA Pol II was not observed to associate with the promoter [9]. In the continuous presence of E2, by contrast, the ER, RNA Pol II and coactivators were observed to cycle on and off the ERresponsive promoters with a periodicity of about 40 min. Cycling off the promoter was found to depend on phosphorylation of the carboxy-terminal domain of RNA Pol II. It was also observed that occupancy of endogenous promoters by the ER and p160 coactivators has similar periodicities, is concurrent with histone acetylation, and is followed by occupancy of the promoters by RNA Pol II, CBP and p300/CBP-associated factor (pCAF) [8]. In addition, it was shown that peroxisome proliferatoractivated receptor binding protein (PBP), the protein that anchors the DRIP–TRAP complex to the ER and other NRs, is recruited to the cathepsin D promoter with a periodicity similar to that of the ER and the p160 coactivator SRC-3. These results support a combinatorial model of complex recruitment in which complexes containing PBP and SRC-3 act simultaneously on the promoter. Kinetic ChIP has been also used to investigate the recruitment of the ER transcription complex to the pS2 promoter. Burakov et al. [10] used kinetic ChIP to show, in contrast to the results on the cathepsin D promoter, that the DRIP–Mediator complex and p160 proteins associate alternatively with the pS2 promoter [10]. This reciprocal association with the pS2 promoter of the DRIP–Mediator and p160 complex proteins favors a sequential model of complex use. The varied observations of these two research groups might be explained by promoter specificity, which could result in the differential recruitment of NR coregulators. Cycling of the ER on and off a promoter also seems to depend on a functional proteasome; for example, the periodicity is markedly reduced (w2 h) in response to proteasome inhibition. Furthermore, E3 ubiquitin ligases (MDM2 and E6AP) and a component of the proteasome regulatory subunit (Rpt6) cycle on the promoter concurrently with the ER in the presence and absence of E2 [9]. In summary, ChIP can be used to assess promoter occupancy indirectly, and the observation of cycling of the ER and coregulators on endogenous promoters can provide a technical means by which to determine the order of recruitment of NRs and coregulators to an endogenous promoter and to determine whether this recruitment is combinatorial or sequential. The ‘transcriptional clock’ A recent paper by Metivier et al. [11] has further advanced the combinatorial model. Using ChIP, these authors

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evaluated basal and agonist-stimulated occupancy of the pS2 promoter by numerous transcription factors, coregulators, histone modifiers, RNA Pol II and its interaction partners, and other proteins involved in transcription initiation. In addition, a second coimmunoprecipitation step was done (re-ChIP) to determine the protein composition of complexes recruited in response to E2. Six different complexes were shown to be present exclusively on the promoter, in favor of a sequential model of complex recruitment. These complexes included (i) a p68-dependent complex; (ii) a complex containing alternative histone acetyltransferases, histone methyltransferases and p160; (iii) a PRMT-1/SWI/SNF-dependent complex; (iv) a complex dependent on the histone acetyltransferase GCN5; (v) a mediator/TFIIH-dependent complex; and (vi) a complex containing activated Pol II, elongator and SWI/SNF. Many of the proteins within such complexes are functionally redundant, and steric limitations might abrogate two of the proteins being in the same complex simultaneously. In the context of these striking data, it is important to recall that ChIP is based on cell population averages, and conclusive determination of protein complex constituents on a single promoter is not yet possible. Kinetic ChIP was then used to improve these comprehensive analyses of temporal interactions by the ER, coregulators, RNA Pol II and associated proteins at the endogenous promoter pS2. From the results, Metivier et al. [11] proposed the presence of a ‘transcriptional clock’. This notion involves the ordered and sequential association and disassociation of proteins on a promoter to effect transcription initiation. Three cycles of the clock were proposed: first, an initial transcriptionally unproductive cycle; second, a transcriptionally productive cycle; and third, a reinitiation cycle. Thus, in the context of population averaging, ChIP-based assays have been used to define a sequential and combinatorial model of the recruitment and release of proteins necessary to form a transcription complex. We should mention here that, during the development of ChIP, single cell approaches aimed at understanding transcriptional complexes in living cells also proposed the varied mobility of many nuclear proteins, including transcription factors, and suggested that molecular dynamics are more robust than the data derived from ChIP assays imply. Live cell experiments: dynamic motion and interactions by nuclear proteins Highly mobile nuclear proteins: the rule or the exception? Numerous live cell studies have been carried out to examine the dynamics of transcription factors, including NRs and their coregulators. For example, FRAP has been used to examine the dynamics of the motion of basic transcription factors TBP and TFIIB at different stages of the cell cycle. During mitosis, a fusion protein of green fluorescent protein (GFP) and TBP localized to condensed chromosomes and did not show appreciable fluorescence recovery 20 min after bleaching [12]. During interphase, however, GFP–TBP fluorescence recovery was nearly www.sciencedirect.com

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100% after 20 min, whereas GFP–TFIIB recovered fully in only a few seconds. This is compelling evidence that there is a pool of differentially mobile transcription factors in the nucleus. In an earlier study, Phair and Misteli [4] used FRAP to analyze the dynamics of three functionally different nuclear proteins: HMG-17, which is involved in transcription; SF2/ASF, which has a role in splicing precursor mRNA; and fibrillarin, which participates in rRNA processing. Each protein showed rapid movement that was consistent with a diffusion-based process but was about 100 times slower than the diffusion of free solutes or GFP alone in the nucleus. It is likely that the low mobility of the nuclear proteins is due to their interactions with other nuclear components. Furthermore, in the most comprehensive FRAP study of chromatin-binding proteins carried out so far, it was shown that most (18 of 20) proteins showed high binding rates on chromatin with a residence time on the order of seconds [13]. On the basis of this rapid movement, Phair et al. [13] put forth a stochastic model for the formation of protein complexes that maximizes responsiveness to small changes in the availability of potential binding partners. On the basis of this model, it was suggested that the rapid movement of many nuclear proteins might minimize the need for preformed and/or long-lived stable protein complexes. In this way, the cell can harness the free energy of diffusion to accomplish a multitude of tasks. These studies further underscore the possibility that dynamic regulation of transcription might occur at several levels. Ligand-dependent ER mobility The ER has been also extensively studied in live cells. The agonist E2, the partial antagonist 4HT, and the pure antagonist ICI 182 780 (ICI) cause the ER and SRC-1 (only E2) to go from a diffuse nucleoplasmic spread to a punctate distribution with several small foci [14,15]. Surprisingly, the spatial distribution of the endogenous ER and the sites of transcription marked by active RNA Pol IIo show only minor overlap. Subsequent live cell photobleaching analyses have been carried out to understand better the spatio-temporal movement of the ER [16]. FRAP analyses showed a rapid rate of recovery (half-time of recovery !0.1 s) of a fusion of cyan fluorescent protein (CFP) and the ER in the absence of E2, and a reduced, but still dynamic, rate of recovery (half-time of recovery w5–6 s) in the presence of E2 and 4HT. Intriguingly, both inhibition by ICI and inhibition of the proteasome, which have been linked to transcriptional repression of the ER [17], resulted in little recovery regardless of the presence or absence of agonist [16]. Furthermore, incubation in ATP-depleted media resulted in the reversible immobilization of CFP–ER in the absence of E2. In agreement with the function of SRC-1 as a steroid receptor coactivator, dual FRAP analyses showed that the mobility of a fusion of yellow fluorescent protein (YFP) and SRC-1 mirrored the dynamics of CFP–ER in the absence and presence of E2. Each protein showed high mobility in the absence of E2 and a significant decrease in mobility in

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the presence of E2, with the recovery of YFP–SRC-1 lagging behind that of CFP–ER. By contrast, marked changes in ER mobility caused by ICI or proteasome inhibitors did not affect SRC-1 dynamics. These mobilities were observed despite evidence indicating that each protein was biochemically bound to the nuclear matrix – a poorly understood non-chromatin, RNA-rich structure that has been linked to transcription [18]. Thus, it has become apparent that live cell studies can reveal nuclear protein dynamics that are not appreciated when other approaches are used. Live cell experiments with integrated gene arrays The lac operator system Nearly a decade ago, Belmont and colleagues [19] generated a Chinese hamster ovary cell line containing stably integrated repeats of the lac operator (lacO). Using these cells, the lac repressor (LacR), antisera specific for LacR and also a GFP–LacR fusion protein, these authors were the first to show imaging of stably integrated DNA in fixed or live cells. The original purpose of the lacO array system was to facilitate direct studies of nuclear and chromosomal ultrastructure; however, the utility of the lacO array system for studying the transcriptional responses of chromatin structure during ‘activation’ was subsequently made apparent through the use of a triple fusion of the potent viral transcription activator protein VP16, LacR and GFP [20]. Targeting this triple fusion protein to the lacO array resulted in visualization of chromatin decondensation within 15 min, accompanied by the recruitment of histone acetyltransferases and by histone hyperacetylation. However, chromosome decondensation was found to be independent of transcription – a phenomenon that was perhaps influenced by the repetitive nature of the bacterial lacO DNA. To evaluate more directly the role of chromosome modification in relation to gene activation (at least in a cis configuration), lacO sequences have been introduced 5 0 to a long stretch of tet operators, thereby creating an inducible promoter that can be ‘marked’ with fluorescently labeled LacR. This promoter regulates a viral TATA box and the expression of a novel reporter gene encoding CFP and a peroxisome targeting signal-1, Ser-Lys-Leu (CFP–SKL) [21]. The result of this genetic engineering has enabled, for the first time, imaging of an active gene locus in a live cell. Specifically, chromatin reorganization (identified by YFP–LacR binding at the 5 0 lacO sequences) was first observed about 30 min after transcription induction; CFP–SKL mRNA was first detected 2 h after induction by RNA fluorescence in situ hybridization; and CFP–SKL protein was first observed 3 h after induction. In an elegant next-generation lacO array model, imaging of transcribed mRNA in live cells has been recently achieved by introducing MS2 bacteriophage mRNA stem loop (MS2) repeats to the CFP–SKL transcript, which can then bind to a YFP fusion of the MS2 RNA-binding protein [22]. Consistent with the time frame for chromatin remodeling, the YFP–MS2 signal was found to accumulate in a particulate pattern in the nucleus within minutes. In addition, the YFP–MS2 signal www.sciencedirect.com

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appeared in the cytoplasm in conjunction with CFP–SKL protein. Thus, the lacO array-based systems can be useful tools for studying chromatin remodeling and NR regulation by providing the ability to visualize chromatin reorganization in relation to transcriptional activation, the ability to target and to image transcriptional activators on the lacO array in living cells, and the ability to relate histone modifications such as acetylation to transcriptional activation. The lacO system has been also successfully used to study nuclear hormone receptor biology directly in living cells. For example, Stenoien et al. [23] have detected interactions between the ER and both SRC-1 and CBP [23]. They tethered CFP–ER to the lacO array via a functional fusion with the lac repressor (termed ‘CFPlacER’). Coexpression of CFPlacER with YFP–SRC-1 or YFP–CBP showed that in the absence of E 2 YFP–SRC-1 accumulated extensively with CFPlacER, whereas the addition of E2 resulted in further and rapid (within 5 min) recruitment of nucleoplasmic SRC-1; notably, relatively slower recruitment was observed for YFP–CBP (w30 min). FRAP analyses showed that the half-time of recovery for SRC-1 was rapid (almost instant) in the absence of E2. The addition of E2 still resulted in a rapid recovery of SRC-1 (seconds), which became progressively longer in the continued presence of E2. These data might possibly indicate a greater ER–SRC-1 association over time but, in both cases, the receptor–coregulator complex was remarkably dynamic, particularly in comparison to the slowly recovering lacR–lacO interactions. In addition, FRAP analysis showed that YFP–CBP has a shorter half-time of recovery than YFP–SRC-1 in response to E2; furthermore, the recovery of YFP–CBP does not change in response to incubation time, suggesting that there is a distinct, transient association between ER and CBP. These data indicate that the ER–SRC-1 and ER–CBP associations are highly dynamic, with subunits exchanging within seconds. The live cell data contrast with in vitro studies indicating that ER, SRC-1 and CBP are part of a biochemically stable complex. Thus, the rapid exchange of coregulator complex subunits in live cells provides a different context to the biochemical view in which stable regulatory complexes control transcription. At the very least, a new consideration of how we think about and use the term ‘stable’ might be appropriate because of these microscopy-based approaches. Further use of the lacO system has provided evidence for a novel function of a subset of transcriptional and histone-modifying proteins, including transactivation/ transformation-domain associated protein (TRRAP), Brm and Brm-related gene-1 (BRG1) [24]. These proteins seem to act as harbingers, showing early targeting to the lacO array before the recruitment of multiple proteins (GCN5, pCAF, CBP, TIP60 and barrier-to-autointegration factor) and parallel histone acetylation and chromatin remodeling. The sequential recruitment to the lacO array of various proteins that were previously thought to be part of nucleoplasmic complexes suggests that proteins might be targeted to a promoter as single proteins or, at most, as

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small complexes. This work also addresses the possibility that steric hindrance could be involved in the recruitment of large histone-modifying complexes to condensed chromatin. In brief, initially recruited histone-modifying proteins might be necessary to commence some level of chromatin modification and to enable more proteins to access the chromatin simultaneously to facilitate transcription or repression. Further work is necessary to determine the order of recruitment and the transcriptional dependency of each regulator in improved model systems that are less dependent on viral or bacterial components.

The mouse mammary tumor virus system Another model system for the live study of transcription and chromatin regulation is a cell line containing a large tandem array of mouse mammary tumor virus and Harvey viral ras (MMTV/v-Ha-ras) reporter sequences (hereafter termed ‘MMTV’) [25]. A derivative of this cell line expresses a GFP fusion protein of the glucocorticoid receptor (GR) under the control of a tetracycline-repressible promoter. On removal of tetracycline and addition of the agonist dexamethasone, the cytoplasmic GFP–GR protein translocates to the nucleus, where it forms several foci including the MMTV DNA array itself and induces viral gene transcription [3,26]. The MMTV array system thus has distinct advantages for studying NR regulation, the direct binding of an NR (i.e. GR), GR binding in response to agonist treatment, and the direct link between GR binding and transcription mediated by a viral promoter. To test directly how static or dynamic the NR–DNA interaction might be, FRAP and FLIP have been carried out in the presence of dexamethasone and have shown that there is a high rate of exchange between the arraybound and free nucleoplasmic pool of GFP–GR. Remarkably, recovery is evident as early as 1.6 s [3]. The rate of exchange of GFP–GR on the MMTV array is inversely correlated with the level of transcription in response to dexamethasone. Furthermore, the exchange rate has been shown to be influenced by chaperone and proteasome function [27]. Another MMTV array study has shown that there is a correlation between the amount of MMTV decondensation in response to dexamethasone and the level of transcription [28]. Several proteins, including the transcription factors AP-2 and NF1, the steroid coactivators SRC-1 and CBP, and BRG1 were found to accumulate with GFP–GR on the MMTV array in the presence of dexamethasone, thereby enabling the dynamics of these proteins to be studied in a living cell. Analogous to the rapid dynamics of SRC-1 recruitment to the ER immobilized to lacO arrays, GRIP1 (a member of the p160 class of NR coactivators) has been shown to have a similarly rapid recovery rate [29]. On the basis of the rapid recovery of GR after photobleaching, a dynamic view of transcriptional initiation has been proposed in which GR continuously cycles on and off the MMTV promoter [29]; this contrasts with the static view in which the GR occupies the promoter for extended periods of time [3]. www.sciencedirect.com

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Future directions The next generation of promoter arrays The use of promoter arrays has greatly facilitated the study of NR dynamics. Although important insights have been gained, there are some concerns with the lacO and MMTV array systems, including their dependence on bacterial or viral elements (both systems) and the indirect marking of a locus in cis with highly repetitive bacterial DNA (the lacO system). Furthermore, counter to current thinking, studies using the lacO array and lacER have shown chromatin decondensation in the absence of E2 and partial condensation in the presence of E2 [30]. Thus, further development of array systems would benefit by focusing on mammalian promoters in as natural a context as possible. Towards this end, we have developed an array system based on the mammalian prolactin promoter/enhancer, which contains Pit-1 (a POU-class transcription factor) [31] and ER-binding sites and is constructed to control the expression of a peroxisome-targeted red fluorescent protein (RFP–SKL) [32]. The addition of the RFP–SKL provides a readout of transcription homologous to that provided by the lacO array system ([21]; and Z.D. Sharp et al., unpublished), but results in a more versatile (and brighter) reporter. Preliminary results with the prolactin array stably integrated into the HeLa genome suggest that this system has considerable physiological relevance. In contrast to the lacER and lacO array experiments, prolactin-arraycontaining cells expressing the ER show chromatin decondensation in the presence of E2; furthermore, sharp condensation in the presence of 4HT or ICI 172 780 is consistent with antagonist activity. Thus, the mammalian prolactin promoter array system will be useful for studying transcriptional synergy [33] (e.g. cooperation between ER and Pit-1) and should therefore provide an understanding of ER and Pit-1 regulation of transcription in a physiologically relevant manner. Refinement of ChIP assays The use of ChIP-based assays to assess promoter occupancy and complex formations has been revolutionary, but it remains limited by the biochemical nature of the technique. Live cell analyses have shown rapid movement (within seconds) of NRs and coregulators. Because formaldehyde is a slow crosslinker (as compared with glutaraldehyde, the ultrastructural fixative of choice) and because sample preparation is difficult in general, the time required for ChIP fixation (a minimum of 2.5 min) [10,34] means that ChIP is unable to detect events in the same time frame as live imaging. Furthermore, ChIP can assess the promoter occupancy of an averaged cell population only indirectly, and thus it cannot confirm whether proteins are truly in a complex on a promoter but can only show that they are somehow associated with the promoter sometime between the near instant death of a cell from formaldehyde and the eventual loose crosslinking that occurs during the course of fixation. In an exciting new technological development, Nagaich et al. [33] have recently reported an in vitro chromatin

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remodeling assay using MMTV chromatin, GR, BRG1 and histones 2A and 2b (H2A and H2B) in which crosslinking is achieved by an ultrafast ultraviolet (UV) laser. This system has demonstrated a cyclical association of proteins with chromatin, which is reminiscent of previous ChIP results detailing cycling of the ER and coregulators but occurs at much faster rates (5-min cycles) [34]. The displacement of GR from chromatin was found to be dependent on chromatin remodeling and the presence of SWI/SNF and ATP. Notably, these results also indicated that H2A and H2B associate at different times with the chromatin, in contrast to evidence indicating that the two proteins function as a dimer pair. Because ultrafast UV laser crosslinking occurs during a single 5-ns laser pulse, it has a time resolution that is much faster than that of conventional (formaldehyde crosslinking) ChIP and the results of cycling are much closer to those obtained in live cells studies. So far UV crosslinking has not been used to study NRs in vivo, but it should provide a tremendous advantage when it is. Quantifying protein–protein interactions in live cells Mammalian two-hybrid assays are capable of assaying protein–protein interactions, but numerous issues such as false positives limit the applicability of this approach and it remains dependent on biochemical techniques for confirmation. An alternative direct microscopic method, live cell fluorescence resonance energy transfer (FRET), has been also used to analyze protein interactions [35–37]. If spectrally appropriate fluorescent protein pairs (e.g. CFP and YFP) are used, then the binding of two fusion proteins can be detected and measured. Technical difficulties have impeded the widespread use of this method; however, the development of selective bleaching techniques and the introduction of spectral imaging detectors that can resolve overlapping spectra [38–41] have made it possible to overcome these problems and to generate reliable live FRET data. Because FRET is based on distances measured in angstroms, it effectively allows imaging that is below the resolution of the light microscope, giving rise to the appropriately coined term ‘nanoscopy’ [42]. Concluding remarks Significant advances in molecular biological, biochemical and imaging techniques have rapidly pushed the NR biology field forward. Recent studies involving ChIP and live cell imaging have produced a dynamic mindset regarding transcription regulation, but on very different time intervals. Although ChIP and several biochemical studies are based on weak and reversible formaldehyde crosslinking in cell populations [8–11,34], they do provide support for a model of relatively stable promoter-based complexes averaged over periods of tens of minutes. The transient complexes can be assigned specific functions and are thought to accumulate and to disassociate sequentially from a promoter. By contrast, the varied mobility rates of nuclear proteins observed using live cell approaches argue against the universal presence of stable, preformed or promoter-bound protein complexes. Instead, these data suggest that a more stochastically driven www.sciencedirect.com

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assembly and disassembly process takes place on the basis of protein–protein interactions [3,4,12,13,23,24,27,29]. Which model most closely represents reality? The ChIP and biochemical results that show complex formation suffers from a relatively long and weak fixative procedure in which proteins that might be undergoing rapid, stochastic interactions with each other are crosslinked into a ‘snapshot’ of complexes that are subsequently interpreted as stable multiprotein complexes. The use of ultrafast UV laser crosslinking [34], if adapted to an in vivo system, would improve the time resolution such that the results would be on a timescale more comparable to that provided by live cell FRAP. The observed cycling of some proteins by both ChIP and FRAP analyses possibly suggests that the rates detected by FRAP might change over time, perhaps with important regulatory consequences. The ability to assess repetitive, short-term FRAP experiments in the same cell over a few hours would help to resolve this issue, but it would require the use of faster, less-phototoxic approaches (e.g. multiphoton FRAP imaging) that are not yet in general use. With continued advances in both live cell and biochemical approaches and with improved cellular models, the transcription field is poised to uncover additional mechanisms steeped in molecular dynamics.

Acknowledgements This work was supported by NIH/NIDDK grant DK55622.

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